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Sample records for predictable biological distributions

  1. Does scale matter? A systematic review of incorporating biological realism when predicting changes in species distributions.

    Science.gov (United States)

    Record, Sydne; Strecker, Angela; Tuanmu, Mao-Ning; Beaudrot, Lydia; Zarnetske, Phoebe; Belmaker, Jonathan; Gerstner, Beth

    2018-01-01

    There is ample evidence that biotic factors, such as biotic interactions and dispersal capacity, can affect species distributions and influence species' responses to climate change. However, little is known about how these factors affect predictions from species distribution models (SDMs) with respect to spatial grain and extent of the models. Understanding how spatial scale influences the effects of biological processes in SDMs is important because SDMs are one of the primary tools used by conservation biologists to assess biodiversity impacts of climate change. We systematically reviewed SDM studies published from 2003-2015 using ISI Web of Science searches to: (1) determine the current state and key knowledge gaps of SDMs that incorporate biotic interactions and dispersal; and (2) understand how choice of spatial scale may alter the influence of biological processes on SDM predictions. We used linear mixed effects models to examine how predictions from SDMs changed in response to the effects of spatial scale, dispersal, and biotic interactions. There were important biases in studies including an emphasis on terrestrial ecosystems in northern latitudes and little representation of aquatic ecosystems. Our results suggest that neither spatial extent nor grain influence projected climate-induced changes in species ranges when SDMs include dispersal or biotic interactions. We identified several knowledge gaps and suggest that SDM studies forecasting the effects of climate change should: 1) address broader ranges of taxa and locations; and 1) report the grain size, extent, and results with and without biological complexity. The spatial scale of analysis in SDMs did not affect estimates of projected range shifts with dispersal and biotic interactions. However, the lack of reporting on results with and without biological complexity precluded many studies from our analysis.

  2. Biological and ecological characteristics of soft ticks (Ixodida: Argasidae and their impact for predicting tick and associated disease distribution

    Directory of Open Access Journals (Sweden)

    Vial L.

    2009-09-01

    Full Text Available As evidence of global changes is accumulating, scientists are challenged to detect distribution changes of vectors, reservoirs and pathogens caused by anthropogenic and/or environmental changes. Statistical and mathematical distribution models are emerging for ixodid hard ticks whereas no prediction has ever been developed for argasid ones. These last organisms remain unknown and under-reported; they differ from hard ticks by many structural, biological and ecological properties, which complicate direct adaptation of hard tick models. However, investigations on bibliographic resources concerning these ticks suggest that distribution modelling based on natural niche concept and using environmental factors especially climate is also possible, bearing in mind the scale of prediction and their specificities including their nidicolous lifestyle, an indiscriminate host feeding and a short bloodmeal duration, as well as a flexible development cycle through diapause periods.

  3. Prediction uncertainty assessment of a systems biology model requires a sample of the full probability distribution of its parameters

    Directory of Open Access Journals (Sweden)

    Simon van Mourik

    2014-06-01

    Full Text Available Multi-parameter models in systems biology are typically ‘sloppy’: some parameters or combinations of parameters may be hard to estimate from data, whereas others are not. One might expect that parameter uncertainty automatically leads to uncertain predictions, but this is not the case. We illustrate this by showing that the prediction uncertainty of each of six sloppy models varies enormously among different predictions. Statistical approximations of parameter uncertainty may lead to dramatic errors in prediction uncertainty estimation. We argue that prediction uncertainty assessment must therefore be performed on a per-prediction basis using a full computational uncertainty analysis. In practice this is feasible by providing a model with a sample or ensemble representing the distribution of its parameters. Within a Bayesian framework, such a sample may be generated by a Markov Chain Monte Carlo (MCMC algorithm that infers the parameter distribution based on experimental data. Matlab code for generating the sample (with the Differential Evolution Markov Chain sampler and the subsequent uncertainty analysis using such a sample, is supplied as Supplemental Information.

  4. Predicting potential global distributions of two Miscanthus grasses: implications for horticulture, biofuel production, and biological invasions.

    Science.gov (United States)

    Hager, Heather A; Sinasac, Sarah E; Gedalof, Ze'ev; Newman, Jonathan A

    2014-01-01

    In many regions, large proportions of the naturalized and invasive non-native floras were originally introduced deliberately by humans. Pest risk assessments are now used in many jurisdictions to regulate the importation of species and usually include an estimation of the potential distribution in the import area. Two species of Asian grass (Miscanthus sacchariflorus and M. sinensis) that were originally introduced to North America as ornamental plants have since escaped cultivation. These species and their hybrid offspring are now receiving attention for large-scale production as biofuel crops in North America and elsewhere. We evaluated their potential global climate suitability for cultivation and potential invasion using the niche model CLIMEX and evaluated the models' sensitivity to the parameter values. We then compared the sensitivity of projections of future climatically suitable area under two climate models and two emissions scenarios. The models indicate that the species have been introduced to most of the potential global climatically suitable areas in the northern but not the southern hemisphere. The more narrowly distributed species (M. sacchariflorus) is more sensitive to changes in model parameters, which could have implications for modelling species of conservation concern. Climate projections indicate likely contractions in potential range in the south, but expansions in the north, particularly in introduced areas where biomass production trials are under way. Climate sensitivity analysis shows that projections differ more between the selected climate change models than between the selected emissions scenarios. Local-scale assessments are required to overlay suitable habitat with climate projections to estimate areas of cultivation potential and invasion risk.

  5. Predictable return distributions

    DEFF Research Database (Denmark)

    Pedersen, Thomas Quistgaard

    trace out the entire distribution. A univariate quantile regression model is used to examine stock and bond return distributions individually, while a multivariate model is used to capture their joint distribution. An empirical analysis on US data shows that certain parts of the return distributions......-of-sample analyses show that the relative accuracy of the state variables in predicting future returns varies across the distribution. A portfolio study shows that an investor with power utility can obtain economic gains by applying the empirical return distribution in portfolio decisions instead of imposing...

  6. Quantum Mechanics predicts evolutionary biology.

    Science.gov (United States)

    Torday, J S

    2018-07-01

    Nowhere are the shortcomings of conventional descriptive biology more evident than in the literature on Quantum Biology. In the on-going effort to apply Quantum Mechanics to evolutionary biology, merging Quantum Mechanics with the fundamentals of evolution as the First Principles of Physiology-namely negentropy, chemiosmosis and homeostasis-offers an authentic opportunity to understand how and why physics constitutes the basic principles of biology. Negentropy and chemiosmosis confer determinism on the unicell, whereas homeostasis constitutes Free Will because it offers a probabilistic range of physiologic set points. Similarly, on this basis several principles of Quantum Mechanics also apply directly to biology. The Pauli Exclusion Principle is both deterministic and probabilistic, whereas non-localization and the Heisenberg Uncertainty Principle are both probabilistic, providing the long-sought after ontologic and causal continuum from physics to biology and evolution as the holistic integration recognized as consciousness for the first time. Copyright © 2018 Elsevier Ltd. All rights reserved.

  7. Incorporating uncertainty in predictive species distribution modelling.

    Science.gov (United States)

    Beale, Colin M; Lennon, Jack J

    2012-01-19

    Motivated by the need to solve ecological problems (climate change, habitat fragmentation and biological invasions), there has been increasing interest in species distribution models (SDMs). Predictions from these models inform conservation policy, invasive species management and disease-control measures. However, predictions are subject to uncertainty, the degree and source of which is often unrecognized. Here, we review the SDM literature in the context of uncertainty, focusing on three main classes of SDM: niche-based models, demographic models and process-based models. We identify sources of uncertainty for each class and discuss how uncertainty can be minimized or included in the modelling process to give realistic measures of confidence around predictions. Because this has typically not been performed, we conclude that uncertainty in SDMs has often been underestimated and a false precision assigned to predictions of geographical distribution. We identify areas where development of new statistical tools will improve predictions from distribution models, notably the development of hierarchical models that link different types of distribution model and their attendant uncertainties across spatial scales. Finally, we discuss the need to develop more defensible methods for assessing predictive performance, quantifying model goodness-of-fit and for assessing the significance of model covariates.

  8. Prediction of Some Biological Film Characteristic

    International Nuclear Information System (INIS)

    Ibrahim, G.; Khalaf, K.

    2004-01-01

    A multi components biofilm model has been developed and discussed which accounts for all well established biological processes with biofilm(s): s ubstrate utilization [aerobically, axenically and anaerobically]. D enitrification process. n itrification process. t he effect of diffusion and mass transfer limitations. The model has predicted some important characteristics of bio films such as:- s pace distribution of substrate(s) within bio films. W eight or thickness of biofilm layer (aerobic layer, anoxic layer and anaerobic layer). The results indicates that the relative thickness of biofilm layers (aerobically, anoxically and anaerobic) is highly affected by the availability of the main electron acceptor (O 2 and NO 3 and the organic load)

  9. Applications of contact predictions to structural biology

    Directory of Open Access Journals (Sweden)

    Felix Simkovic

    2017-05-01

    methods. Finally, predicted contacts can distinguish between biologically relevant interfaces and mere lattice contacts in a final crystal structure, and have potential in the identification of functionally important regions and in foreseeing the consequences of mutations.

  10. Biological distribution of 51Cr-heparin

    International Nuclear Information System (INIS)

    Almeida, M.A.T.M. de.

    1979-01-01

    The kinetics of heparin in normal Wistar rats using the radioactive tracer 51 Cr, has been studied. The labeled and purified 51 Cr-heparin was injected into rats intravenously and by intraperitoneal injection. In measuring the radioactivity of organs it was possible to conclude that the tissues rich in mast cells, liver and spleen, were found to take up the greater amounts of heparin. The curve that represents the logarithm of the concentration of heparin versus time is biexponential. The half-lives of the two exponential were determined. The volume of distribution, the rate constant and the renal clearance were determined by the values of the plasma levels and urinary excretions. The biological half-time, the turnover rate and the turnover time were determined by measuring the residual radioactivity of the total body and urinary excretions. With the data obtained from the mentioned experiments a compartmental model was performed in which the plasma is the central compartment for the distribution of the drug, exchanging with another extraplasmatic compartment and finally the drug being stored in reticulo endothelial system cells. (Author) [pt

  11. Predicting biological system objectives de novo from internal state measurements

    Directory of Open Access Journals (Sweden)

    Maranas Costas D

    2008-01-01

    Full Text Available Abstract Background Optimization theory has been applied to complex biological systems to interrogate network properties and develop and refine metabolic engineering strategies. For example, methods are emerging to engineer cells to optimally produce byproducts of commercial value, such as bioethanol, as well as molecular compounds for disease therapy. Flux balance analysis (FBA is an optimization framework that aids in this interrogation by generating predictions of optimal flux distributions in cellular networks. Critical features of FBA are the definition of a biologically relevant objective function (e.g., maximizing the rate of synthesis of biomass, a unit of measurement of cellular growth and the subsequent application of linear programming (LP to identify fluxes through a reaction network. Despite the success of FBA, a central remaining challenge is the definition of a network objective with biological meaning. Results We present a novel method called Biological Objective Solution Search (BOSS for the inference of an objective function of a biological system from its underlying network stoichiometry as well as experimentally-measured state variables. Specifically, BOSS identifies a system objective by defining a putative stoichiometric "objective reaction," adding this reaction to the existing set of stoichiometric constraints arising from known interactions within a network, and maximizing the putative objective reaction via LP, all the while minimizing the difference between the resultant in silico flux distribution and available experimental (e.g., isotopomer flux data. This new approach allows for discovery of objectives with previously unknown stoichiometry, thus extending the biological relevance from earlier methods. We verify our approach on the well-characterized central metabolic network of Saccharomyces cerevisiae. Conclusion We illustrate how BOSS offers insight into the functional organization of biochemical networks

  12. Confronting species distribution model predictions with species functional traits.

    Science.gov (United States)

    Wittmann, Marion E; Barnes, Matthew A; Jerde, Christopher L; Jones, Lisa A; Lodge, David M

    2016-02-01

    Species distribution models are valuable tools in studies of biogeography, ecology, and climate change and have been used to inform conservation and ecosystem management. However, species distribution models typically incorporate only climatic variables and species presence data. Model development or validation rarely considers functional components of species traits or other types of biological data. We implemented a species distribution model (Maxent) to predict global climate habitat suitability for Grass Carp (Ctenopharyngodon idella). We then tested the relationship between the degree of climate habitat suitability predicted by Maxent and the individual growth rates of both wild (N = 17) and stocked (N = 51) Grass Carp populations using correlation analysis. The Grass Carp Maxent model accurately reflected the global occurrence data (AUC = 0.904). Observations of Grass Carp growth rate covered six continents and ranged from 0.19 to 20.1 g day(-1). Species distribution model predictions were correlated (r = 0.5, 95% CI (0.03, 0.79)) with observed growth rates for wild Grass Carp populations but were not correlated (r = -0.26, 95% CI (-0.5, 0.012)) with stocked populations. Further, a review of the literature indicates that the few studies for other species that have previously assessed the relationship between the degree of predicted climate habitat suitability and species functional traits have also discovered significant relationships. Thus, species distribution models may provide inferences beyond just where a species may occur, providing a useful tool to understand the linkage between species distributions and underlying biological mechanisms.

  13. Distributed model predictive control made easy

    CERN Document Server

    Negenborn, Rudy

    2014-01-01

    The rapid evolution of computer science, communication, and information technology has enabled the application of control techniques to systems beyond the possibilities of control theory just a decade ago. Critical infrastructures such as electricity, water, traffic and intermodal transport networks are now in the scope of control engineers. The sheer size of such large-scale systems requires the adoption of advanced distributed control approaches. Distributed model predictive control (MPC) is one of the promising control methodologies for control of such systems.   This book provides a state-of-the-art overview of distributed MPC approaches, while at the same time making clear directions of research that deserve more attention. The core and rationale of 35 approaches are carefully explained. Moreover, detailed step-by-step algorithmic descriptions of each approach are provided. These features make the book a comprehensive guide both for those seeking an introduction to distributed MPC as well as for those ...

  14. Predictive access control for distributed computation

    DEFF Research Database (Denmark)

    Yang, Fan; Hankin, Chris; Nielson, Flemming

    2013-01-01

    We show how to use aspect-oriented programming to separate security and trust issues from the logical design of mobile, distributed systems. The main challenge is how to enforce various types of security policies, in particular predictive access control policies — policies based on the future beh...... behavior of a program. A novel feature of our approach is that we can define policies concerning secondary use of data....

  15. Do predictions from Species Sensitivity Distributions match with field data?

    International Nuclear Information System (INIS)

    Smetanová, S.; Bláha, L.; Liess, M.; Schäfer, R.B.; Beketov, M.A.

    2014-01-01

    Species Sensitivity Distribution (SSD) is a statistical model that can be used to predict effects of contaminants on biological communities, but only few comparisons of this model with field studies have been conducted so far. In the present study we used measured pesticides concentrations from streams in Germany, France, and Finland, and we used SSD to calculate msPAF (multiple substance potentially affected fraction) values based on maximum toxic stress at localities. We compared these SSD-based predictions with the actual effects on stream invertebrates quantified by the SPEAR pesticides bioindicator. The results show that the msPAFs correlated well with the bioindicator, however, the generally accepted SSD threshold msPAF of 0.05 (5% of species are predicted to be affected) severely underestimated the observed effects (msPAF values causing significant effects are 2–1000-times lower). These results demonstrate that validation with field data is required to define the appropriate thresholds for SSD predictions. - Highlights: • We validated the statistical model Species Sensitivity Distribution with field data. • Good correlation was found between the model predictions and observed effects. • But, the generally accepted threshold msPAF 0.05 severely underestimated the effects. - Comparison of the SSD-based prediction with the field data evaluated with the SPEAR pesticides index shows that SSD threshold msPAF of 0.05 severely underestimates the effects observed in the field

  16. Single-mode biological distributed feedback laser

    DEFF Research Database (Denmark)

    Vannahme, Christoph; Maier-Flaig, Florian; Lemmer, Uli

    2013-01-01

    Single-mode second order distributed feedback (DFB) lasers of riboflavin (vitamin B2) doped gelatine films on nanostructured low refractive index material are demonstrated. Manufacturing is based on a simple UV nanoimprint and spin-coating. Emission wavelengths of 543 nm and 562 nm for two...

  17. Toward scalable parts families for predictable design of biological circuits.

    Science.gov (United States)

    Lucks, Julius B; Qi, Lei; Whitaker, Weston R; Arkin, Adam P

    2008-12-01

    Our current ability to engineer biological circuits is hindered by design cycles that are costly in terms of time and money, with constructs failing to operate as desired, or evolving away from the desired function once deployed. Synthetic biologists seek to understand biological design principles and use them to create technologies that increase the efficiency of the genetic engineering design cycle. Central to the approach is the creation of biological parts--encapsulated functions that can be composited together to create new pathways with predictable behaviors. We define five desirable characteristics of biological parts--independence, reliability, tunability, orthogonality and composability, and review studies of small natural and synthetic biological circuits that provide insights into each of these characteristics. We propose that the creation of appropriate sets of families of parts with these properties is a prerequisite for efficient, predictable engineering of new function in cells and will enable a large increase in the sophistication of genetic engineering applications.

  18. 78 FR 57293 - Distribution of Reference Biological Standards and Biological Preparations

    Science.gov (United States)

    2013-09-18

    ... DEPARTMENT OF HEALTH AND HUMAN SERVICES 42 CFR Part 7 [Docket No. CDC-2013-0013] RIN 0920-AA52 Distribution of Reference Biological Standards and Biological Preparations AGENCY: Centers for Disease Control and Prevention (HHS/CDC), Department of Health and Human Services (HHS). ACTION: Confirmation of...

  19. Hierarchical Model Predictive Control for Resource Distribution

    DEFF Research Database (Denmark)

    Bendtsen, Jan Dimon; Trangbæk, K; Stoustrup, Jakob

    2010-01-01

    units. The approach is inspired by smart-grid electric power production and consumption systems, where the flexibility of a large number of power producing and/or power consuming units can be exploited in a smart-grid solution. The objective is to accommodate the load variation on the grid, arising......This paper deals with hierarchichal model predictive control (MPC) of distributed systems. A three level hierachical approach is proposed, consisting of a high level MPC controller, a second level of so-called aggregators, controlled by an online MPC-like algorithm, and a lower level of autonomous...... on one hand from varying consumption, on the other hand by natural variations in power production e.g. from wind turbines. The approach presented is based on quadratic optimization and possess the properties of low algorithmic complexity and of scalability. In particular, the proposed design methodology...

  20. The biology and distribution of the monkfish Lophius vomerinus off ...

    African Journals Online (AJOL)

    The monkfish Lophius vomerinus is economically the most important bycatch species in the South African demersal hake fishery. To assist in the development of a bycatch management plan for the species, age and growth characteristics, reproductive and feeding biology, and distribution patterns were investigated.

  1. A distributed approach for parameters estimation in System Biology models

    International Nuclear Information System (INIS)

    Mosca, E.; Merelli, I.; Alfieri, R.; Milanesi, L.

    2009-01-01

    Due to the lack of experimental measurements, biological variability and experimental errors, the value of many parameters of the systems biology mathematical models is yet unknown or uncertain. A possible computational solution is the parameter estimation, that is the identification of the parameter values that determine the best model fitting respect to experimental data. We have developed an environment to distribute each run of the parameter estimation algorithm on a different computational resource. The key feature of the implementation is a relational database that allows the user to swap the candidate solutions among the working nodes during the computations. The comparison of the distributed implementation with the parallel one showed that the presented approach enables a faster and better parameter estimation of systems biology models.

  2. Biological instability in a chlorinated drinking water distribution network.

    Science.gov (United States)

    Nescerecka, Alina; Rubulis, Janis; Vital, Marius; Juhna, Talis; Hammes, Frederik

    2014-01-01

    The purpose of a drinking water distribution system is to deliver drinking water to the consumer, preferably with the same quality as when it left the treatment plant. In this context, the maintenance of good microbiological quality is often referred to as biological stability, and the addition of sufficient chlorine residuals is regarded as one way to achieve this. The full-scale drinking water distribution system of Riga (Latvia) was investigated with respect to biological stability in chlorinated drinking water. Flow cytometric (FCM) intact cell concentrations, intracellular adenosine tri-phosphate (ATP), heterotrophic plate counts and residual chlorine measurements were performed to evaluate the drinking water quality and stability at 49 sampling points throughout the distribution network. Cell viability methods were compared and the importance of extracellular ATP measurements was examined as well. FCM intact cell concentrations varied from 5×10(3) cells mL(-1) to 4.66×10(5) cells mL(-1) in the network. While this parameter did not exceed 2.1×10(4) cells mL(-1) in the effluent from any water treatment plant, 50% of all the network samples contained more than 1.06×10(5) cells mL(-1). This indisputably demonstrates biological instability in this particular drinking water distribution system, which was ascribed to a loss of disinfectant residuals and concomitant bacterial growth. The study highlights the potential of using cultivation-independent methods for the assessment of chlorinated water samples. In addition, it underlines the complexity of full-scale drinking water distribution systems, and the resulting challenges to establish the causes of biological instability.

  3. Distribution and Biological Effects of Nanoparticles in the Reproductive System.

    Science.gov (United States)

    Liu, Ying; Li, Hongxia; Xiao, Kai

    2016-01-01

    Nanoparticles have shown great potential in biomedical applications such as imaging probes and drug delivery. However, the increasing use of nanoparticles has raised concerns about their adverse effects on human health and environment. Reproductive tissues and gametes represent highly delicate biological systems with the essential function of transmitting genetic information to the offspring, which is highly sensitive to environmental toxicants. This review aims to summarzie the penetration of physiological barriers (blood-testis barrier and placental barrier), distribution and biological effects of nanoparticles in the reproductive system, which is essential to control the beneficial effects of nanoparticles applications and to avoid their adverse effects on the reproductive system. We referred to a large number of relevant peer-reviewed research articles about the reproductive toxicity of nanoparticles. The comprehensive information was summarized into two parts: physiological barrier penetration and biological effects of nanoparticles in male or female reproductive system; distribution and metabolism of nanoparticles in the reproductive system. The representative examples were also presented in four tables. The in vitro and in vivo studies imply that some nanoparticles are able to cross the blood-testis barrier or placental barrier, and their penetration depends on the physicochemical characteristics of nanoparticles (e.g., composition, shape, particle size and surface coating). The toxicity assays indicate that nanoparticles might induce adverse physiological effects and impede fertility or embryogenesis. The barrier penetration, adverse physiological effects, distribution and metabolism are closely related to physicochemical characteristics of nanoparticles. Further systematic and mechanistic studies using well-characterized nanoparticles, relevant administration routes, and doses relevant to the expected exposure level are required to improve our

  4. Predicting Statistical Distributions of Footbridge Vibrations

    DEFF Research Database (Denmark)

    Pedersen, Lars; Frier, Christian

    2009-01-01

    The paper considers vibration response of footbridges to pedestrian loading. Employing Newmark and Monte Carlo simulation methods, a statistical distribution of bridge vibration levels is calculated modelling walking parameters such as step frequency and stride length as random variables...

  5. A systems biology approach to transcription factor binding site prediction.

    Directory of Open Access Journals (Sweden)

    Xiang Zhou

    2010-03-01

    Full Text Available The elucidation of mammalian transcriptional regulatory networks holds great promise for both basic and translational research and remains one the greatest challenges to systems biology. Recent reverse engineering methods deduce regulatory interactions from large-scale mRNA expression profiles and cross-species conserved regulatory regions in DNA. Technical challenges faced by these methods include distinguishing between direct and indirect interactions, associating transcription regulators with predicted transcription factor binding sites (TFBSs, identifying non-linearly conserved binding sites across species, and providing realistic accuracy estimates.We address these challenges by closely integrating proven methods for regulatory network reverse engineering from mRNA expression data, linearly and non-linearly conserved regulatory region discovery, and TFBS evaluation and discovery. Using an extensive test set of high-likelihood interactions, which we collected in order to provide realistic prediction-accuracy estimates, we show that a careful integration of these methods leads to significant improvements in prediction accuracy. To verify our methods, we biochemically validated TFBS predictions made for both transcription factors (TFs and co-factors; we validated binding site predictions made using a known E2F1 DNA-binding motif on E2F1 predicted promoter targets, known E2F1 and JUND motifs on JUND predicted promoter targets, and a de novo discovered motif for BCL6 on BCL6 predicted promoter targets. Finally, to demonstrate accuracy of prediction using an external dataset, we showed that sites matching predicted motifs for ZNF263 are significantly enriched in recent ZNF263 ChIP-seq data.Using an integrative framework, we were able to address technical challenges faced by state of the art network reverse engineering methods, leading to significant improvement in direct-interaction detection and TFBS-discovery accuracy. We estimated the accuracy

  6. Prediction of oil droplet size distribution in agitated aquatic environments

    International Nuclear Information System (INIS)

    Khelifa, A.; Lee, K.; Hill, P.S.

    2004-01-01

    Oil spilled at sea undergoes many transformations based on physical, biological and chemical processes. Vertical dispersion is the hydrodynamic mechanism controlled by turbulent mixing due to breaking waves, vertical velocity, density gradients and other environmental factors. Spilled oil is dispersed in the water column as small oil droplets. In order to estimate the mass of an oil slick in the water column, it is necessary to know how the droplets formed. Also, the vertical dispersion and fate of oil spilled in aquatic environments can be modelled if the droplet-size distribution of the oil droplets is known. An oil spill remediation strategy can then be implemented. This paper presented a newly developed Monte Carlo model to predict droplet-size distribution due to Brownian motion, turbulence and a differential settling at equilibrium. A kinematic model was integrated into the proposed model to simulate droplet breakage. The key physical input of the model is the maximum droplet size permissible in the simulation. Laboratory studies were found to be in good agreement with field studies. 26 refs., 1 tab., 5 figs

  7. The biology of eukaryotic promoter prediction - a review

    DEFF Research Database (Denmark)

    Pedersen, Anders Gorm; Baldi, Pierre; Chauvin, Yves

    1999-01-01

    between functional promoters has been estimated to be in the range of 30-40 kilobases. Although it is conceivable that some of these predicted promoters correspond to cryptic initiation sites that are used in vivo, it is likely that most are false positives. This suggests that it is important to carefully......Computational prediction of eukaryotic promoters from the nucleotide sequence is one of the most attractive problems in sequence analysis today, but it is also a very difficult one. Thus, current methods predict in the order of one promoter per kilobase in human DNA, while the average distance...... reconsider the biological data that forms the basis of current algorithms, and we here present a review of data that may be useful in this regard. The review covers the following topics: (1) basal transcription and core promoters, (2) activated transcription and transcription factor binding sites, (3) Cp...

  8. Distributed Model Predictive Control via Dual Decomposition

    DEFF Research Database (Denmark)

    Biegel, Benjamin; Stoustrup, Jakob; Andersen, Palle

    2014-01-01

    This chapter presents dual decomposition as a means to coordinate a number of subsystems coupled by state and input constraints. Each subsystem is equipped with a local model predictive controller while a centralized entity manages the subsystems via prices associated with the coupling constraints...

  9. Predicting spiral wave patterns from cell properties in a model of biological self-organization.

    Science.gov (United States)

    Geberth, Daniel; Hütt, Marc-Thorsten

    2008-09-01

    In many biological systems, biological variability (i.e., systematic differences between the system components) can be expected to outrank statistical fluctuations in the shaping of self-organized patterns. In principle, the distribution of single-element properties should thus allow predicting features of such patterns. For a mathematical model of a paradigmatic and well-studied pattern formation process, spiral waves of cAMP signaling in colonies of the slime mold Dictyostelium discoideum, we explore this possibility and observe a pronounced anticorrelation between spiral waves and cell properties (namely, the firing rate) and particularly a clustering of spiral wave tips in regions devoid of spontaneously firing (pacemaker) cells. Furthermore, we observe local inhomogeneities in the distribution of spiral chiralities, again induced by the pacemaker distribution. We show that these findings can be explained by a simple geometrical model of spiral wave generation.

  10. Children's biological responsivity to acute stress predicts concurrent cognitive performance.

    Science.gov (United States)

    Roos, Leslie E; Beauchamp, Kathryn G; Giuliano, Ryan; Zalewski, Maureen; Kim, Hyoun K; Fisher, Philip A

    2018-04-10

    Although prior research has characterized stress system reactivity (i.e. hypothalamic-pituitary-adrenal axis, HPAA; autonomic nervous system, ANS) in children, it has yet to examine the extent to which biological reactivity predicts concurrent goal-directed behavior. Here, we employed a stressor paradigm that allowed concurrent assessment of both stress system reactivity and performance on a speeded-response task to investigate the links between biological reactivity and cognitive function under stress. We further investigated gender as a moderator given previous research suggesting that the ANS may be particularly predictive of behavior in males due to gender differences in socialization. In a sociodemographically diverse sample of young children (N = 58, M age = 5.38 yrs; 44% male), individual differences in sociodemographic covariates (age, household income), HPAA (i.e. cortisol), and ANS (i.e. respiratory sinus arrhythmia, RSA, indexing the parasympathetic branch; pre-ejection period, PEP, indexing the sympathetic branch) function were assessed as predictors of cognitive performance under stress. We hypothesized that higher income, older age, and greater cortisol reactivity would be associated with better performance overall, and flexible ANS responsivity (i.e. RSA withdrawal, PEP shortening) would be predictive of performance for males. Overall, females performed better than males. Two-group SEM analyses suggest that, for males, greater RSA withdrawal to the stressor was associated with better performance, while for females, older age, higher income, and greater cortisol reactivity were associated with better performance. Results highlight the relevance of stress system reactivity to cognitive performance under stress. Future research is needed to further elucidate for whom and in what situations biological reactivity predicts goal-directed behavior.

  11. Biologically effective dose distribution based on the linear quadratic model and its clinical relevance

    International Nuclear Information System (INIS)

    Lee, Steve P.; Leu, Min Y.; Smathers, James B.; McBride, William H.; Parker, Robert G.; Withers, H. Rodney

    1995-01-01

    Purpose: Radiotherapy plans based on physical dose distributions do not necessarily entirely reflect the biological effects under various fractionation schemes. Over the past decade, the linear-quadratic (LQ) model has emerged as a convenient tool to quantify biological effects for radiotherapy. In this work, we set out to construct a mechanism to display biologically oriented dose distribution based on the LQ model. Methods and Materials: A computer program that converts a physical dose distribution calculated by a commercially available treatment planning system to a biologically effective dose (BED) distribution has been developed and verified against theoretical calculations. This software accepts a user's input of biological parameters for each structure of interest (linear and quadratic dose-response and repopulation kinetic parameters), as well as treatment scheme factors (number of fractions, fractional dose, and treatment time). It then presents a two-dimensional BED display in conjunction with anatomical structures. Furthermore, to facilitate clinicians' intuitive comparison with conventional fractionation regimen, a conversion of BED to normalized isoeffective dose (NID) is also allowed. Results: Two sample cases serve to illustrate the application of our tool in clinical practice. (a) For an orthogonal wedged pair of x-ray beams treating a maxillary sinus tumor, the biological effect at the ipsilateral mandible can be quantified, thus illustrates the so-called 'double-trouble' effects very well. (b) For a typical four-field, evenly weighted prostate treatment using 10 MV x-rays, physical dosimetry predicts a comparable dose at the femoral necks between an alternate two-fields/day and four-fields/day schups. However, our BED display reveals an approximate 21% higher BED for the two-fields/day scheme. This excessive dose to the femoral necks can be eliminated if the treatment is delivered with a 3:2 (anterio-posterior/posterio-anterior (AP

  12. Predictive modelling of complex agronomic and biological systems.

    Science.gov (United States)

    Keurentjes, Joost J B; Molenaar, Jaap; Zwaan, Bas J

    2013-09-01

    Biological systems are tremendously complex in their functioning and regulation. Studying the multifaceted behaviour and describing the performance of such complexity has challenged the scientific community for years. The reduction of real-world intricacy into simple descriptive models has therefore convinced many researchers of the usefulness of introducing mathematics into biological sciences. Predictive modelling takes such an approach another step further in that it takes advantage of existing knowledge to project the performance of a system in alternating scenarios. The ever growing amounts of available data generated by assessing biological systems at increasingly higher detail provide unique opportunities for future modelling and experiment design. Here we aim to provide an overview of the progress made in modelling over time and the currently prevalent approaches for iterative modelling cycles in modern biology. We will further argue for the importance of versatility in modelling approaches, including parameter estimation, model reduction and network reconstruction. Finally, we will discuss the difficulties in overcoming the mathematical interpretation of in vivo complexity and address some of the future challenges lying ahead. © 2013 John Wiley & Sons Ltd.

  13. The role of biological fertility in predicting family size

    DEFF Research Database (Denmark)

    Joffe, M; Key, J; Best, N

    2009-01-01

    for the first child. CONCLUSIONS: Within the limits of the available data quality, family size appears to be predicted by biological fertility, even after adjustment for maternal age, if the woman was at least 20 years old when the couple's first attempt at conception started. The contribution of behavioural......BACKGROUND: It is plausible that a couple's ability to achieve the desired number of children is limited by biological fertility, especially if childbearing is postponed. Family size has declined and semen quality may have deteriorated in much of Europe, although studies have found an increase....... Potential confounders were maternal age when unprotected sex began prior to the first birth, and maternal smoking. Desired family size was available in only one of the datasets. RESULTS: Couples with a TTP of at least 12 months tended to have smaller families, with odds ratios for the risk of not having...

  14. Genomic Signal Processing: Predicting Basic Molecular Biological Principles

    Science.gov (United States)

    Alter, Orly

    2005-03-01

    Advances in high-throughput technologies enable acquisition of different types of molecular biological data, monitoring the flow of biological information as DNA is transcribed to RNA, and RNA is translated to proteins, on a genomic scale. Future discovery in biology and medicine will come from the mathematical modeling of these data, which hold the key to fundamental understanding of life on the molecular level, as well as answers to questions regarding diagnosis, treatment and drug development. Recently we described data-driven models for genome-scale molecular biological data, which use singular value decomposition (SVD) and the comparative generalized SVD (GSVD). Now we describe an integrative data-driven model, which uses pseudoinverse projection (1). We also demonstrate the predictive power of these matrix algebra models (2). The integrative pseudoinverse projection model formulates any number of genome-scale molecular biological data sets in terms of one chosen set of data samples, or of profiles extracted mathematically from data samples, designated the ``basis'' set. The mathematical variables of this integrative model, the pseudoinverse correlation patterns that are uncovered in the data, represent independent processes and corresponding cellular states (such as observed genome-wide effects of known regulators or transcription factors, the biological components of the cellular machinery that generate the genomic signals, and measured samples in which these regulators or transcription factors are over- or underactive). Reconstruction of the data in the basis simulates experimental observation of only the cellular states manifest in the data that correspond to those of the basis. Classification of the data samples according to their reconstruction in the basis, rather than their overall measured profiles, maps the cellular states of the data onto those of the basis, and gives a global picture of the correlations and possibly also causal coordination of

  15. Application of 'SPICE' to predict temperature distribution in heat pipes

    Energy Technology Data Exchange (ETDEWEB)

    Li, H M; Liu, Y; Damodaran, M [Nanyang Technological Univ., Singapore (SG). School of Mechanical and Production Engineering

    1991-11-01

    This article presents a new alternative approach to predict temperature distribution in heat pipes. In this method, temperature distribution in a heat pipe, modelled as an analogous electrical circuit, is predicted by applying SPICE, a general-purpose circuit simulation program. SPICE is used to simulate electrical circuit designs before the prototype is assembled. Useful predictions are obtained for heat pipes with and without adiabatic sections and for heat pipes with various evaporator and condenser lengths. Comparison of the predicted results with experiments demonstrates fairly good agreement. It is also shown how interdisciplinary developments could be used appropriately. (author).

  16. Prediction of spatial distribution for some land use allometric ...

    African Journals Online (AJOL)

    Prediction of spatial distribution for some land use allometric characteristics in land use planning models with geostatistic and Geographical Information System (GIS) (Case study: Boein and Miandasht, Isfahan Province, Iran)

  17. Hafnium oxide nanoparticles: toward an in vitro predictive biological effect?

    International Nuclear Information System (INIS)

    Marill, Julie; Anesary, Naeemunnisa Mohamed; Zhang, Ping; Vivet, Sonia; Borghi, Elsa; Levy, Laurent; Pottier, Agnes

    2014-01-01

    Hafnium oxide, NBTXR3 nanoparticles were designed for high dose energy deposition within cancer cells when exposed to ionizing radiation. The purpose of this study was to assess the possibility of predicting in vitro the biological effect of NBTXR3 nanoparticles when exposed to ionizing radiation. Cellular uptake of NBTXR3 nanoparticles was assessed in a panel of human cancer cell lines (radioresistant and radiosensitive) by transmission electron microscopy. The radioenhancement of NBTXR3 nanoparticles was measured by the clonogenic survival assay. NBTXR3 nanoparticles were taken up by cells in a concentration dependent manner, forming clusters in the cytoplasm. Differential nanoparticle uptake was observed between epithelial and mesenchymal or glioblastoma cell lines. The dose enhancement factor increased with increase NBTXR3 nanoparticle concentration and radiation dose. Beyond a minimum number of clusters per cell, the radioenhancement of NBTXR3 nanoparticles could be estimated from the radiation dose delivered and the radiosensitivity of the cancer cell lines. Our preliminary results suggest a predictable in vitro biological effect of NBTXR3 nanoparticles exposed to ionizing radiation

  18. Challenges and progress in predicting biological responses to incorporated radioactivity

    International Nuclear Information System (INIS)

    Howell, R. W.; Neti, P. V. S. V.; Pinto, M.; Gerashchenko, B. I.; Narra, V. R.; Azzam, E. I.

    2006-01-01

    Prediction of risks and therapeutic outcome in nuclear medicine largely rely on calculation of the absorbed dose. Absorbed dose specification is complex due to the wide variety of radiations emitted, non-uniform activity distribution, biokinetics, etc. Conventional organ absorbed dose estimates assumed that radioactivity is distributed uniformly throughout the organ. However, there have been dramatic improvements in dosimetry models that reflect the substructure of organs as well as tissue elements within them. These models rely on improved nuclear medicine imaging capabilities that facilitate determination of activity within voxels that represent tissue elements of ∼0.2-1 cm 3 . However, even these improved approaches assume that all cells within the tissue element receive the same dose. The tissue element may be comprised of a variety of cells having different radiosensitivities and different incorporated radioactivity. Furthermore, the extent to which non-uniform distributions of radioactivity within a small tissue element impact the absorbed dose distribution is strongly dependent on the number, type, and energy of the radiations emitted by the radionuclide. It is also necessary to know whether the dose to a given cell arises from radioactive decays within itself (self-dose) or decays in surrounding cells (cross-dose). Cellular response to self-dose can be considerably different than its response to cross-dose from the same radiopharmaceutical. Bystander effects can also play a role in the response. Evidence shows that even under conditions of 'uniform' distribution of radioactivity, a combination of organ dosimetry, voxel dosimetry and dosimetry at the cellular and multicellular levels can be required to predict response. (authors)

  19. Predictive Analytics for Coordinated Optimization in Distribution Systems

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Rui [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2018-04-13

    This talk will present NREL's work on developing predictive analytics that enables the optimal coordination of all the available resources in distribution systems to achieve the control objectives of system operators. Two projects will be presented. One focuses on developing short-term state forecasting-based optimal voltage regulation in distribution systems; and the other one focuses on actively engaging electricity consumers to benefit distribution system operations.

  20. Maxent modelling for predicting the potential distribution of Thai Palms

    DEFF Research Database (Denmark)

    Tovaranonte, Jantrararuk; Barfod, Anders S.; Overgaard, Anne Blach

    2011-01-01

    on presence data. The aim was to identify potential hot spot areas, assess the determinants of palm distribution ranges, and provide a firmer knowledge base for future conservation actions. We focused on a relatively small number of climatic, environmental and spatial variables in order to avoid...... overprediction of species distribution ranges. The models with the best predictive power were found by calculating the area under the curve (AUC) of receiver-operating characteristic (ROC). Here, we provide examples of contrasting predicted species distribution ranges as well as a map of modeled palm diversity...

  1. Ortholog prediction of the Aspergillus genus applicable for synthetic biology

    DEFF Research Database (Denmark)

    Rasmussen, Jane Lind Nybo; Vesth, Tammi Camilla; Theobald, Sebastian

    of genotype-to-phenotype. To achieve this, we have developed orthologous protein prediction software that utilizes genus-wide genetic diversity. The approach is optimized for large data sets, based on BLASTp considering protein identity and alignment coverage, and clustering using single linkage of bi......The Aspergillus genus contains leading industrial microorganisms, excelling in producing bioactive compounds and enzymes. Using synthetic biology and bioinformatics, we aim to re-engineer these organisms for applications within human health, pharmaceuticals, environmental engineering, and food......-directional hits. The result is orthologous protein families describing the genomic and functional features of individual species, clades and the core/pan genome of Aspergillus; and applicable to genotype-to-phenotype analyses in other microbial genera....

  2. The role of biological fertility in predicting family size.

    Science.gov (United States)

    Joffe, M; Key, J; Best, N; Jensen, T K; Keiding, N

    2009-08-01

    It is plausible that a couple's ability to achieve the desired number of children is limited by biological fertility, especially if childbearing is postponed. Family size has declined and semen quality may have deteriorated in much of Europe, although studies have found an increase rather than a decrease in couple fertility. Using four high-quality European datasets, we took the reported time to pregnancy (TTP) as the predictor variable; births reported as following contraceptive failure were an additional category. The outcome variable was final or near-final family size. Potential confounders were maternal age when unprotected sex began prior to the first birth, and maternal smoking. Desired family size was available in only one of the datasets. Couples with a TTP of at least 12 months tended to have smaller families, with odds ratios for the risk of not having a second child approximately 1.8, and for the risk of not having a third child approximately 1.6. Below 12 months no association was observed. Findings were generally consistent across datasets. There was also a more than 2-fold risk of not achieving the desired family size if TTP was 12 months or more for the first child. Within the limits of the available data quality, family size appears to be predicted by biological fertility, even after adjustment for maternal age, if the woman was at least 20 years old when the couple's first attempt at conception started. The contribution of behavioural factors to this result also needs to be investigated.

  3. Stand diameter distribution modelling and prediction based on Richards function.

    Directory of Open Access Journals (Sweden)

    Ai-guo Duan

    Full Text Available The objective of this study was to introduce application of the Richards equation on modelling and prediction of stand diameter distribution. The long-term repeated measurement data sets, consisted of 309 diameter frequency distributions from Chinese fir (Cunninghamia lanceolata plantations in the southern China, were used. Also, 150 stands were used as fitting data, the other 159 stands were used for testing. Nonlinear regression method (NRM or maximum likelihood estimates method (MLEM were applied to estimate the parameters of models, and the parameter prediction method (PPM and parameter recovery method (PRM were used to predict the diameter distributions of unknown stands. Four main conclusions were obtained: (1 R distribution presented a more accurate simulation than three-parametric Weibull function; (2 the parameters p, q and r of R distribution proved to be its scale, location and shape parameters, and have a deep relationship with stand characteristics, which means the parameters of R distribution have good theoretical interpretation; (3 the ordinate of inflection point of R distribution has significant relativity with its skewness and kurtosis, and the fitted main distribution range for the cumulative diameter distribution of Chinese fir plantations was 0.4∼0.6; (4 the goodness-of-fit test showed diameter distributions of unknown stands can be well estimated by applying R distribution based on PRM or the combination of PPM and PRM under the condition that only quadratic mean DBH or plus stand age are known, and the non-rejection rates were near 80%, which are higher than the 72.33% non-rejection rate of three-parametric Weibull function based on the combination of PPM and PRM.

  4. Estimating confidence intervals in predicted responses for oscillatory biological models.

    Science.gov (United States)

    St John, Peter C; Doyle, Francis J

    2013-07-29

    The dynamics of gene regulation play a crucial role in a cellular control: allowing the cell to express the right proteins to meet changing needs. Some needs, such as correctly anticipating the day-night cycle, require complicated oscillatory features. In the analysis of gene regulatory networks, mathematical models are frequently used to understand how a network's structure enables it to respond appropriately to external inputs. These models typically consist of a set of ordinary differential equations, describing a network of biochemical reactions, and unknown kinetic parameters, chosen such that the model best captures experimental data. However, since a model's parameter values are uncertain, and since dynamic responses to inputs are highly parameter-dependent, it is difficult to assess the confidence associated with these in silico predictions. In particular, models with complex dynamics - such as oscillations - must be fit with computationally expensive global optimization routines, and cannot take advantage of existing measures of identifiability. Despite their difficulty to model mathematically, limit cycle oscillations play a key role in many biological processes, including cell cycling, metabolism, neuron firing, and circadian rhythms. In this study, we employ an efficient parameter estimation technique to enable a bootstrap uncertainty analysis for limit cycle models. Since the primary role of systems biology models is the insight they provide on responses to rate perturbations, we extend our uncertainty analysis to include first order sensitivity coefficients. Using a literature model of circadian rhythms, we show how predictive precision is degraded with decreasing sample points and increasing relative error. Additionally, we show how this method can be used for model discrimination by comparing the output identifiability of two candidate model structures to published literature data. Our method permits modellers of oscillatory systems to confidently

  5. Towards biologically conformal radiation therapy (BCRT): Selective IMRT dose escalation under the guidance of spatial biology distribution

    International Nuclear Information System (INIS)

    Yang Yong; Xing Lei

    2005-01-01

    It is well known that the spatial biology distribution (e.g., clonogen density, radiosensitivity, tumor proliferation rate, functional importance) in most tumors and sensitive structures is heterogeneous. Recent progress in biological imaging is making the mapping of this distribution increasingly possible. The purpose of this work is to establish a theoretical framework to quantitatively incorporate the spatial biology data into intensity modulated radiation therapy (IMRT) inverse planning. In order to implement this, we first derive a general formula for determining the desired dose to each tumor voxel for a known biology distribution of the tumor based on a linear-quadratic model. The desired target dose distribution is then used as the prescription for inverse planning. An objective function with the voxel-dependent prescription is constructed with incorporation of the nonuniform dose prescription. The functional unit density distribution in a sensitive structure is also considered phenomenologically when constructing the objective function. Two cases with different hypothetical biology distributions are used to illustrate the new inverse planning formalism. For comparison, treatments with a few uniform dose prescriptions and a simultaneous integrated boost are also planned. The biological indices, tumor control probability (TCP) and normal tissue complication probability (NTCP), are calculated for both types of plans and the superiority of the proposed technique over the conventional dose escalation scheme is demonstrated. Our calculations revealed that it is technically feasible to produce deliberately nonuniform dose distributions with consideration of biological information. Compared with the conventional dose escalation schemes, the new technique is capable of generating biologically conformal IMRT plans that significantly improve the TCP while reducing or keeping the NTCPs at their current levels. Biologically conformal radiation therapy (BCRT

  6. Effects of species biological traits and environmental heterogeneity on simulated tree species distribution shifts under climate change.

    Science.gov (United States)

    Wang, Wen J; He, Hong S; Thompson, Frank R; Spetich, Martin A; Fraser, Jacob S

    2018-09-01

    Demographic processes (fecundity, dispersal, colonization, growth, and mortality) and their interactions with environmental changes are not well represented in current climate-distribution models (e.g., niche and biophysical process models) and constitute a large uncertainty in projections of future tree species distribution shifts. We investigate how species biological traits and environmental heterogeneity affect species distribution shifts. We used a species-specific, spatially explicit forest dynamic model LANDIS PRO, which incorporates site-scale tree species demography and competition, landscape-scale dispersal and disturbances, and regional-scale abiotic controls, to simulate the distribution shifts of four representative tree species with distinct biological traits in the central hardwood forest region of United States. Our results suggested that biological traits (e.g., dispersal capacity, maturation age) were important for determining tree species distribution shifts. Environmental heterogeneity, on average, reduced shift rates by 8% compared to perfect environmental conditions. The average distribution shift rates ranged from 24 to 200myear -1 under climate change scenarios, implying that many tree species may not able to keep up with climate change because of limited dispersal capacity, long generation time, and environmental heterogeneity. We suggest that climate-distribution models should include species demographic processes (e.g., fecundity, dispersal, colonization), biological traits (e.g., dispersal capacity, maturation age), and environmental heterogeneity (e.g., habitat fragmentation) to improve future predictions of species distribution shifts in response to changing climates. Copyright © 2018 Elsevier B.V. All rights reserved.

  7. Prediction of phenotypes of missense mutations in human proteins from biological assemblies.

    Science.gov (United States)

    Wei, Qiong; Xu, Qifang; Dunbrack, Roland L

    2013-02-01

    Single nucleotide polymorphisms (SNPs) are the most frequent variation in the human genome. Nonsynonymous SNPs that lead to missense mutations can be neutral or deleterious, and several computational methods have been presented that predict the phenotype of human missense mutations. These methods use sequence-based and structure-based features in various combinations, relying on different statistical distributions of these features for deleterious and neutral mutations. One structure-based feature that has not been studied significantly is the accessible surface area within biologically relevant oligomeric assemblies. These assemblies are different from the crystallographic asymmetric unit for more than half of X-ray crystal structures. We find that mutations in the core of proteins or in the interfaces in biological assemblies are significantly more likely to be disease-associated than those on the surface of the biological assemblies. For structures with more than one protein in the biological assembly (whether the same sequence or different), we find the accessible surface area from biological assemblies provides a statistically significant improvement in prediction over the accessible surface area of monomers from protein crystal structures (P = 6e-5). When adding this information to sequence-based features such as the difference between wildtype and mutant position-specific profile scores, the improvement from biological assemblies is statistically significant but much smaller (P = 0.018). Combining this information with sequence-based features in a support vector machine leads to 82% accuracy on a balanced dataset of 50% disease-associated mutations from SwissVar and 50% neutral mutations from human/primate sequence differences in orthologous proteins. Copyright © 2012 Wiley Periodicals, Inc.

  8. Distributed estimation based on observations prediction in wireless sensor networks

    KAUST Repository

    Bouchoucha, Taha

    2015-03-19

    We consider wireless sensor networks (WSNs) used for distributed estimation of unknown parameters. Due to the limited bandwidth, sensor nodes quantize their noisy observations before transmission to a fusion center (FC) for the estimation process. In this letter, the correlation between observations is exploited to reduce the mean-square error (MSE) of the distributed estimation. Specifically, sensor nodes generate local predictions of their observations and then transmit the quantized prediction errors (innovations) to the FC rather than the quantized observations. The analytic and numerical results show that transmitting the innovations rather than the observations mitigates the effect of quantization noise and hence reduces the MSE. © 2015 IEEE.

  9. ASSERT and COBRA predictions of flow distribution in vertical bundles

    International Nuclear Information System (INIS)

    Tahir, A.; Carver, M.B.

    1983-01-01

    COBRA and ASSERT are subchannel codes which compute flow and enthalpy distributions in rod bundles. COBRA is a well known code, ASSERT is under development at CRNL. This paper gives a comparison of the two codes with boiling experiments in vertical seven rod bundles. ASSERT predictions of the void distribution are shown to be in good agreement with reported experimental results, while COBRA predictions are unsatisfactory. The mixing models in both COBRA and ASSERT are briefly discussed. The reasons for the failure of COBRA-IV and the success of ASSERT in simulating the experiments are highlighted

  10. Predicting Brain Metastasis in Breast Cancer Patients: Stage Versus Biology.

    Science.gov (United States)

    Azim, Hamdy A; Abdel-Malek, Raafat; Kassem, Loay

    2018-04-01

    Brain metastasis (BM) is a life-threatening event in breast cancer patients. Identifying patients at a high risk for BM can help to adopt screening programs and test preventive interventions. We tried to identify the incidence of BM in different stages and subtypes of breast cancer. We reviewed the clinical records of 2193 consecutive breast cancer patients who presented between January 1999 and December 2010. We explored the incidence of BM in relation to standard clinicopathological factors, and determined the cumulative risk of BM according to the disease stage and phenotype. Of the 2193 included women, 160 (7.3%) developed BM at a median follow-up of 5.8 years. Age younger than 60 years (P = .015), larger tumors (P = .004), lymph node (LN) positivity (P < .001), high tumor grade (P = .012), and HER2 positivity (P < .001) were associated with higher incidence of BM in the whole population. In patients who presented with locoregional disease, 3 factors independently predicted BM: large tumors (hazard ratio [HR], 3.60; 95% confidence interval [CI], 1.54-8.38; P = .003), axillary LN metastasis (HR, 4.03; 95% CI, 1.91-8.52; P < .001), and HER2 positivity (HR, 1.89; 95% CI, 1.0-3.41; P = .049). A Brain Relapse Index was formulated using those 3 factors, with 5-year cumulative incidence of BM of 19.2% in those having the 2 or 3 risk factors versus 2.5% in those with no or 1 risk factor (P < .001). In metastatic patients, 3 factors were associated with higher risk of BM: HER2 positivity (P = .007), shorter relapse-free interval (P < .001), and lung metastasis (P < .001). Disease stage and biological subtypes predict the risk for BM and subsequent treatment outcome. Copyright © 2017 Elsevier Inc. All rights reserved.

  11. Prediction of wind energy distribution in complex terrain using CFD

    DEFF Research Database (Denmark)

    Xu, Chang; Li, Chenqi; Yang, Jianchuan

    2013-01-01

    Based on linear models, WAsP software predicts wind energy distribution, with a good accuracy for flat terrain, but with a large error under complicated topography. In this paper, numerical simulations are carried out using the FLUENT software on a mesh generated by the GAMBIT and ARGIS software ...

  12. Nonparametric Bayesian predictive distributions for future order statistics

    Science.gov (United States)

    Richard A. Johnson; James W. Evans; David W. Green

    1999-01-01

    We derive the predictive distribution for a specified order statistic, determined from a future random sample, under a Dirichlet process prior. Two variants of the approach are treated and some limiting cases studied. A practical application to monitoring the strength of lumber is discussed including choices of prior expectation and comparisons made to a Bayesian...

  13. Performance prediction model for distributed applications on multicore clusters

    CSIR Research Space (South Africa)

    Khanyile, NP

    2012-07-01

    Full Text Available discusses some of the short comings of this law in the current age. We propose a theoretical model for predicting the behavior of a distributed algorithm given the network restrictions of the cluster used. The paper focuses on the impact of latency...

  14. Working memory capacity of biological movements predicts empathy traits.

    Science.gov (United States)

    Gao, Zaifeng; Ye, Tian; Shen, Mowei; Perry, Anat

    2016-04-01

    Working memory (WM) and empathy are core issues in cognitive and social science, respectively. However, no study so far has explored the relationship between these two constructs. Considering that empathy takes place based on the others' observed experiences, which requires extracting the observed dynamic scene into WM and forming a coherent representation, we hypothesized that a sub-type of WM capacity, i.e., WM for biological movements (BM), should predict one's empathy level. Therefore, WM capacity was measured for three distinct types of stimuli in a change detection task: BM of human beings (BM; Experiment 1), movements of rectangles (Experiment 2), and static colors (Experiment 3). The first two stimuli were dynamic and shared one WM buffer which differed from the WM buffer for colors; yet only the BM conveyed social information. We found that BM-WM capacity was positively correlated with both cognitive and emotional empathy, with no such correlations for WM capacity of movements of rectangles or of colors. Thus, the current study is the first to provide evidence linking a specific buffer of WM and empathy, and highlights the necessity for considering different WM capacities in future social and clinical research.

  15. IQ Predicts Biological Motion Perception in Autism Spectrum Disorders

    Science.gov (United States)

    Rutherford, M. D.; Troje, Nikolaus F.

    2012-01-01

    Biological motion is easily perceived by neurotypical observers when encoded in point-light displays. Some but not all relevant research shows significant deficits in biological motion perception among those with ASD, especially with respect to emotional displays. We tested adults with and without ASD on the perception of masked biological motion…

  16. Use of artificial neural networks to predict biological outcomes for patients receiving radical radiotherapy of the prostate

    International Nuclear Information System (INIS)

    Gulliford, Sarah L.; Webb, Steve; Rowbottom, Carl G.; Corne, David W.; Dearnaley, David P.

    2004-01-01

    Background and purpose: This paper discusses the application of artificial neural networks (ANN) in predicting biological outcomes following prostate radiotherapy. A number of model-based methods have been developed to correlate the dose distributions calculated for a patient receiving radiotherapy and the radiobiological effect this will produce. Most widely used are the normal tissue complication probability and tumour control probability models. An alternative method for predicting specific examples of tumour control and normal tissue complications is to use an ANN. One of the advantages of this method is that there is no need for a priori information regarding the relationship between the data being correlated. Patients and methods: A set of retrospective clinical data from patients who received radical prostate radiotherapy was used to train ANNs to predict specific biological outcomes by learning the relationship between the treatment plan prescription, dose distribution and the corresponding biological effect. The dose and volume were included as a differential dose-volume histogram in order to provide a holistic description of the available data. Results: It was shown that the ANNs were able to predict biochemical control and specific bladder and rectum complications with sensitivity and specificity of above 55% when the outcomes were dichotomised. It was also possible to analyse information from the ANNs to investigate the effect of individual treatment parameters on the outcome. Conclusion: ANNs have been shown to learn something of the complex relationship between treatment parameters and outcome which, if developed further, may prove to be a useful tool in predicting biological outcomes

  17. DBH Prediction Using Allometry Described by Bivariate Copula Distribution

    Science.gov (United States)

    Xu, Q.; Hou, Z.; Li, B.; Greenberg, J. A.

    2017-12-01

    Forest biomass mapping based on single tree detection from the airborne laser scanning (ALS) usually depends on an allometric equation that relates diameter at breast height (DBH) with per-tree aboveground biomass. The incapability of the ALS technology in directly measuring DBH leads to the need to predict DBH with other ALS-measured tree-level structural parameters. A copula-based method is proposed in the study to predict DBH with the ALS-measured tree height and crown diameter using a dataset measured in the Lassen National Forest in California. Instead of exploring an explicit mathematical equation that explains the underlying relationship between DBH and other structural parameters, the copula-based prediction method utilizes the dependency between cumulative distributions of these variables, and solves the DBH based on an assumption that for a single tree, the cumulative probability of each structural parameter is identical. Results show that compared with the bench-marking least-square linear regression and the k-MSN imputation, the copula-based method obtains better accuracy in the DBH for the Lassen National Forest. To assess the generalization of the proposed method, prediction uncertainty is quantified using bootstrapping techniques that examine the variability of the RMSE of the predicted DBH. We find that the copula distribution is reliable in describing the allometric relationship between tree-level structural parameters, and it contributes to the reduction of prediction uncertainty.

  18. Popularity prediction tool for ATLAS distributed data management

    International Nuclear Information System (INIS)

    Beermann, T; Maettig, P; Stewart, G; Lassnig, M; Garonne, V; Barisits, M; Vigne, R; Serfon, C; Goossens, L; Nairz, A; Molfetas, A

    2014-01-01

    This paper describes a popularity prediction tool for data-intensive data management systems, such as ATLAS distributed data management (DDM). It is fed by the DDM popularity system, which produces historical reports about ATLAS data usage, providing information about files, datasets, users and sites where data was accessed. The tool described in this contribution uses this historical information to make a prediction about the future popularity of data. It finds trends in the usage of data using a set of neural networks and a set of input parameters and predicts the number of accesses in the near term future. This information can then be used in a second step to improve the distribution of replicas at sites, taking into account the cost of creating new replicas (bandwidth and load on the storage system) compared to gain of having new ones (faster access of data for analysis). To evaluate the benefit of the redistribution a grid simulator is introduced that is able replay real workload on different data distributions. This article describes the popularity prediction method and the simulator that is used to evaluate the redistribution.

  19. Popularity Prediction Tool for ATLAS Distributed Data Management

    Science.gov (United States)

    Beermann, T.; Maettig, P.; Stewart, G.; Lassnig, M.; Garonne, V.; Barisits, M.; Vigne, R.; Serfon, C.; Goossens, L.; Nairz, A.; Molfetas, A.; Atlas Collaboration

    2014-06-01

    This paper describes a popularity prediction tool for data-intensive data management systems, such as ATLAS distributed data management (DDM). It is fed by the DDM popularity system, which produces historical reports about ATLAS data usage, providing information about files, datasets, users and sites where data was accessed. The tool described in this contribution uses this historical information to make a prediction about the future popularity of data. It finds trends in the usage of data using a set of neural networks and a set of input parameters and predicts the number of accesses in the near term future. This information can then be used in a second step to improve the distribution of replicas at sites, taking into account the cost of creating new replicas (bandwidth and load on the storage system) compared to gain of having new ones (faster access of data for analysis). To evaluate the benefit of the redistribution a grid simulator is introduced that is able replay real workload on different data distributions. This article describes the popularity prediction method and the simulator that is used to evaluate the redistribution.

  20. Predicting Polylepis distribution: vulnerable and increasingly important Andean woodlands

    Directory of Open Access Journals (Sweden)

    Brian R. Zutta

    2012-11-01

    Full Text Available Polylepis woodlands are a vital resource for preserving biodiversity and hydrological functions, which will be altered by climate change and challenge the sustainability of local human communities. However, these highaltitude Andean ecosystems are becoming increasingly vulnerable due to anthropogenic pressure including fragmentation, deforestation and the increase in livestock. Predicting the distribution of native woodlands has become increasingly important to counteract the negative effects of climate change through reforestation and conservation. The objective of this study was to develop and analyze the distribution models of two species that form extensive woodlands along the Andes, namely Polylepis sericea and P. weberbaueri. This study utilized the program Maxent, climate and remotely sensed environmental layers at 1 km resolution. The predicted distribution model for P. sericea indicated that the species could be located in a variety of habitats along the Andean Cordillera, while P. weberbaueri was restricted to the high elevations of southern Peru and Bolivia. For both species, elevation and temperature metrics were the most significant factors for predicted distribution. Further model refinement of Polylepis and other Andean species using increasingly available satellite data demonstrate the potential to help define areas of diversity and improve conservation strategies for the Andes.

  1. Predicting Biological Information Flow in a Model Oxygen Minimum Zone

    Science.gov (United States)

    Louca, S.; Hawley, A. K.; Katsev, S.; Beltran, M. T.; Bhatia, M. P.; Michiels, C.; Capelle, D.; Lavik, G.; Doebeli, M.; Crowe, S.; Hallam, S. J.

    2016-02-01

    Microbial activity drives marine biochemical fluxes and nutrient cycling at global scales. Geochemical measurements as well as molecular techniques such as metagenomics, metatranscriptomics and metaproteomics provide great insight into microbial activity. However, an integration of molecular and geochemical data into mechanistic biogeochemical models is still lacking. Recent work suggests that microbial metabolic pathways are, at the ecosystem level, strongly shaped by stoichiometric and energetic constraints. Hence, models rooted in fluxes of matter and energy may yield a holistic understanding of biogeochemistry. Furthermore, such pathway-centric models would allow a direct consolidation with meta'omic data. Here we present a pathway-centric biogeochemical model for the seasonal oxygen minimum zone in Saanich Inlet, a fjord off the coast of Vancouver Island. The model considers key dissimilatory nitrogen and sulfur fluxes, as well as the population dynamics of the genes that mediate them. By assuming a direct translation of biocatalyzed energy fluxes to biosynthesis rates, we make predictions about the distribution and activity of the corresponding genes. A comparison of the model to molecular measurements indicates that the model explains observed DNA, RNA, protein and cell depth profiles. This suggests that microbial activity in marine ecosystems such as oxygen minimum zones is well described by DNA abundance, which, in conjunction with geochemical constraints, determines pathway expression and process rates. Our work further demonstrates how meta'omic data can be mechanistically linked to environmental redox conditions and biogeochemical processes.

  2. Predicted and measured velocity distribution in a model heat exchanger

    International Nuclear Information System (INIS)

    Rhodes, D.B.; Carlucci, L.N.

    1984-01-01

    This paper presents a comparison between numerical predictions, using the porous media concept, and measurements of the two-dimensional isothermal shell-side velocity distributions in a model heat exchanger. Computations and measurements were done with and without tubes present in the model. The effect of tube-to-baffle leakage was also investigated. The comparison was made to validate certain porous media concepts used in a computer code being developed to predict the detailed shell-side flow in a wide range of shell-and-tube heat exchanger geometries

  3. Isobio software: biological dose distribution and biological dose volume histogram from physical dose conversion using linear-quadratic-linear model.

    Science.gov (United States)

    Jaikuna, Tanwiwat; Khadsiri, Phatchareewan; Chawapun, Nisa; Saekho, Suwit; Tharavichitkul, Ekkasit

    2017-02-01

    To develop an in-house software program that is able to calculate and generate the biological dose distribution and biological dose volume histogram by physical dose conversion using the linear-quadratic-linear (LQL) model. The Isobio software was developed using MATLAB version 2014b to calculate and generate the biological dose distribution and biological dose volume histograms. The physical dose from each voxel in treatment planning was extracted through Computational Environment for Radiotherapy Research (CERR), and the accuracy was verified by the differentiation between the dose volume histogram from CERR and the treatment planning system. An equivalent dose in 2 Gy fraction (EQD 2 ) was calculated using biological effective dose (BED) based on the LQL model. The software calculation and the manual calculation were compared for EQD 2 verification with pair t -test statistical analysis using IBM SPSS Statistics version 22 (64-bit). Two and three-dimensional biological dose distribution and biological dose volume histogram were displayed correctly by the Isobio software. Different physical doses were found between CERR and treatment planning system (TPS) in Oncentra, with 3.33% in high-risk clinical target volume (HR-CTV) determined by D 90% , 0.56% in the bladder, 1.74% in the rectum when determined by D 2cc , and less than 1% in Pinnacle. The difference in the EQD 2 between the software calculation and the manual calculation was not significantly different with 0.00% at p -values 0.820, 0.095, and 0.593 for external beam radiation therapy (EBRT) and 0.240, 0.320, and 0.849 for brachytherapy (BT) in HR-CTV, bladder, and rectum, respectively. The Isobio software is a feasible tool to generate the biological dose distribution and biological dose volume histogram for treatment plan evaluation in both EBRT and BT.

  4. Predicting Translation Initiation Rates for Designing Synthetic Biology

    International Nuclear Information System (INIS)

    Reeve, Benjamin; Hargest, Thomas; Gilbert, Charlie; Ellis, Tom

    2014-01-01

    In synthetic biology, precise control over protein expression is required in order to construct functional biological systems. A core principle of the synthetic biology approach is a model-guided design and based on the biological understanding of the process, models of prokaryotic protein production have been described. Translation initiation rate is a rate-limiting step in protein production from mRNA and is dependent on the sequence of the 5′-untranslated region and the start of the coding sequence. Translation rate calculators are programs that estimate protein translation rates based on the sequence of these regions of an mRNA, and as protein expression is proportional to the rate of translation initiation, such calculators have been shown to give good approximations of protein expression levels. In this review, three currently available translation rate calculators developed for synthetic biology are considered, with limitations and possible future progress discussed.

  5. Estimating Predictive Variance for Statistical Gas Distribution Modelling

    International Nuclear Information System (INIS)

    Lilienthal, Achim J.; Asadi, Sahar; Reggente, Matteo

    2009-01-01

    Recent publications in statistical gas distribution modelling have proposed algorithms that model mean and variance of a distribution. This paper argues that estimating the predictive concentration variance entails not only a gradual improvement but is rather a significant step to advance the field. This is, first, since the models much better fit the particular structure of gas distributions, which exhibit strong fluctuations with considerable spatial variations as a result of the intermittent character of gas dispersal. Second, because estimating the predictive variance allows to evaluate the model quality in terms of the data likelihood. This offers a solution to the problem of ground truth evaluation, which has always been a critical issue for gas distribution modelling. It also enables solid comparisons of different modelling approaches, and provides the means to learn meta parameters of the model, to determine when the model should be updated or re-initialised, or to suggest new measurement locations based on the current model. We also point out directions of related ongoing or potential future research work.

  6. Mistaking geography for biology: inferring processes from species distributions.

    Science.gov (United States)

    Warren, Dan L; Cardillo, Marcel; Rosauer, Dan F; Bolnick, Daniel I

    2014-10-01

    Over the past few decades, there has been a rapid proliferation of statistical methods that infer evolutionary and ecological processes from data on species distributions. These methods have led to considerable new insights, but they often fail to account for the effects of historical biogeography on present-day species distributions. Because the geography of speciation can lead to patterns of spatial and temporal autocorrelation in the distributions of species within a clade, this can result in misleading inferences about the importance of deterministic processes in generating spatial patterns of biodiversity. In this opinion article, we discuss ways in which patterns of species distributions driven by historical biogeography are often interpreted as evidence of particular evolutionary or ecological processes. We focus on three areas that are especially prone to such misinterpretations: community phylogenetics, environmental niche modelling, and analyses of beta diversity (compositional turnover of biodiversity). Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.

  7. Building predictive models of soil particle-size distribution

    Directory of Open Access Journals (Sweden)

    Alessandro Samuel-Rosa

    2013-04-01

    Full Text Available Is it possible to build predictive models (PMs of soil particle-size distribution (psd in a region with complex geology and a young and unstable land-surface? The main objective of this study was to answer this question. A set of 339 soil samples from a small slope catchment in Southern Brazil was used to build PMs of psd in the surface soil layer. Multiple linear regression models were constructed using terrain attributes (elevation, slope, catchment area, convergence index, and topographic wetness index. The PMs explained more than half of the data variance. This performance is similar to (or even better than that of the conventional soil mapping approach. For some size fractions, the PM performance can reach 70 %. Largest uncertainties were observed in geologically more complex areas. Therefore, significant improvements in the predictions can only be achieved if accurate geological data is made available. Meanwhile, PMs built on terrain attributes are efficient in predicting the particle-size distribution (psd of soils in regions of complex geology.

  8. Popularity Prediction Tool for ATLAS Distributed Data Management

    CERN Document Server

    Beermann, T; The ATLAS collaboration; Stewart, G; Lassnig, M; Garonne, V; Barisits, M; Vigne, R; Serfon, C; Goossens, L; Nairz, A; Molfetas, A

    2013-01-01

    This paper describes a popularity prediction tool for data-intensive data management systems, such as ATLAS distributed data management (DDM). It is fed by the DDM popularity system, which produces historical reports about ATLAS data usage, providing information about files, datasets, users and sites where data was accessed. The tool described in this contribution uses this historical information to make a prediction about the future popularity of data. It finds trends in the usage of data using a set of neural networks and a set of input parameters and predicts the number of accesses in the near term future. This information can then be used in a second step to improve the distribution of replicas at sites, taking into account the cost of creating new replicas (bandwidth and load on the storage system) compared to gain of having new ones (faster access of data for analysis). To evaluate the benefit of the redistribution a grid simulator is introduced that is able replay real workload on different data distri...

  9. Popularity Prediction Tool for ATLAS Distributed Data Management

    CERN Document Server

    Beermann, T; The ATLAS collaboration; Stewart, G; Lassnig, M; Garonne, V; Barisits, M; Vigne, R; Serfon, C; Goossens, L; Nairz, A; Molfetas, A

    2014-01-01

    This paper describes a popularity prediction tool for data-intensive data management systems, such as ATLAS distributed data management (DDM). It is fed by the DDM popularity system, which produces historical reports about ATLAS data usage, providing information about files, datasets, users and sites where data was accessed. The tool described in this contribution uses this historical information to make a prediction about the future popularity of data. It finds trends in the usage of data using a set of neural networks and a set of input parameters and predicts the number of accesses in the near term future. This information can then be used in a second step to improve the distribution of replicas at sites, taking into account the cost of creating new replicas (bandwidth and load on the storage system) compared to gain of having new ones (faster access of data for analysis). To evaluate the benefit of the redistribution a grid simulator is introduced that is able replay real workload on different data distri...

  10. Predicting Dynamical Crime Distribution From Environmental and Social Influences

    Directory of Open Access Journals (Sweden)

    Simon Garnier

    2018-05-01

    Full Text Available Understanding how social and environmental factors contribute to the spatio-temporal distribution of criminal activities is a fundamental question in modern criminology. Thanks to the development of statistical techniques such as Risk Terrain Modeling (RTM, it is possible to evaluate precisely the criminogenic contribution of environmental features to a given location. However, the role of social information in shaping the distribution of criminal acts is largely understudied by the criminological research literature. In this paper we investigate the existence of spatio-temporal correlations between successive robbery events, after controlling for environmental influences as estimated by RTM. We begin by showing that a robbery event increases the likelihood of future robberies at and in the neighborhood of its location. This event-dependent influence decreases exponentially with time and as an inverse function of the distance to the original event. We then combine event-dependence and environmental influences in a simulation model to predict robbery patterns at the scale of a large city (Newark, NJ. We show that this model significantly improves upon the predictions of RTM alone and of a model taking into account event-dependence only when tested against real data that were not used to calibrate either model. We conclude that combining risk from exposure (past event and vulnerability (environment, following from the Theory of Risky Places, when modeling crime distribution can improve crime suppression and prevention efforts by providing more accurate forecasting of the most likely locations of criminal events.

  11. Modeling the distribution of Culex tritaeniorhynchus to predict Japanese encephalitis distribution in the Republic of Korea

    Directory of Open Access Journals (Sweden)

    Penny Masuoka

    2010-11-01

    Full Text Available Over 35,000 cases of Japanese encephalitis (JE are reported worldwide each year. Culex tritaeniorhynchus is the primary vector of the JE virus, while wading birds are natural reservoirs and swine amplifying hosts. As part of a JE risk analysis, the ecological niche modeling programme, Maxent, was used to develop a predictive model for the distribution of Cx. tritaeniorhynchus in the Republic of Korea, using mosquito collection data, temperature, precipitation, elevation, land cover and the normalized difference vegetation index (NDVI. The resulting probability maps from the model were consistent with the known environmental limitations of the mosquito with low probabilities predicted for forest covered mountains. July minimum temperature and land cover were the most important variables in the model. Elevation, summer NDVI (July-September, precipitation in July, summer minimum temperature (May-August and maximum temperature for fall and winter months also contributed to the model. Comparison of the Cx. tritaeniorhynchus model to the distribution of JE cases in the Republic of Korea from 2001 to 2009 showed that cases among a highly vaccinated Korean population were located in high-probability areas for Cx. tritaeniorhynchus. No recent JE cases were reported from the eastern coastline, where higher probabilities of mosquitoes were predicted, but where only small numbers of pigs are raised. The geographical distribution of reported JE cases corresponded closely with the predicted high-probability areas for Cx. tritaeniorhynchus, making the map a useful tool for health risk analysis that could be used for planning preventive public health measures.

  12. Distribution of tessera terrain on Venus: Prediction for Magellan

    International Nuclear Information System (INIS)

    Bindschadler, D.L.; Head, J.W.; Kreslavsky, M.A.; Shkuratov, Yu.G.; Ivanov, M.A.; Basilevsky, A.T.

    1990-01-01

    Tessera terrain is the dominant tectonic unit in the northern hemisphere of Venus and is characterized by complex sets of intersecting structural trends and distinctive radar properties due to a high degree of meter and sub-meter scale (5 cm to 10 m) roughness. Based on these distinctive radar properties, a prediction of the global distribution of tessera can be made using Pioneer Venus (PV) reflectivity and roughness data. Where available, Venera 15/16 and Arecibo images and PV diffuse scattering data were used to evaluate the prediction. From this assessment, the authors conclude that most of the regions with prediction values greater than 0.6 (out of 1) are likely to be tessera, and are almost certain to be tectonically deformed. Lada Terra and Phoebe Regio are very likely to contain tessera terrain, while much of Aphrodite Terra is most likely to be either tessera or a landform which has not yet been recognized on Venus. This prediction map will assist in targeting Magellan investigations of Venus tectonics

  13. Model Predictive Control for Distributed Microgrid Battery Energy Storage Systems

    DEFF Research Database (Denmark)

    Morstyn, Thomas; Hredzak, Branislav; Aguilera, Ricardo P.

    2018-01-01

    , and converter current constraints to be addressed. In addition, nonlinear variations in the charge and discharge efficiencies of lithium ion batteries are analyzed and included in the control strategy. Real-time digital simulations were carried out for an islanded microgrid based on the IEEE 13 bus prototypical......This brief proposes a new convex model predictive control (MPC) strategy for dynamic optimal power flow between battery energy storage (ES) systems distributed in an ac microgrid. The proposed control strategy uses a new problem formulation, based on a linear $d$ – $q$ reference frame voltage...... feeder, with distributed battery ES systems and intermittent photovoltaic generation. It is shown that the proposed control strategy approaches the performance of a strategy based on nonconvex optimization, while reducing the required computation time by a factor of 1000, making it suitable for a real...

  14. Biosecurity and Open-Source Biology: The Promise and Peril of Distributed Synthetic Biological Technologies.

    Science.gov (United States)

    Evans, Nicholas G; Selgelid, Michael J

    2015-08-01

    In this article, we raise ethical concerns about the potential misuse of open-source biology (OSB): biological research and development that progresses through an organisational model of radical openness, deskilling, and innovation. We compare this organisational structure to that of the open-source software model, and detail salient ethical implications of this model. We demonstrate that OSB, in virtue of its commitment to openness, may be resistant to governance attempts.

  15. Distributed predictive control of spiral wave in cardiac excitable media

    International Nuclear Information System (INIS)

    Zheng-Ning, Gan; Xin-Ming, Cheng

    2010-01-01

    In this paper, we propose the distributed predictive control strategies of spiral wave in cardiac excitable media. The modified FitzHugh–Nagumo model was used to express the cardiac excitable media approximately. Based on the control-Lyapunov theory, we obtained the distributed control equation, which consists of a positive control-Lyapunov function and a positive cost function. Using the equation, we investigate two kinds of robust control strategies: the time-dependent distributed control strategy and the space-time dependent distributed control strategy. The feasibility of the strategies was demonstrated via an illustrative example, in which the spiral wave was prevented to occur, and the possibility for inducing ventricular fibrillation was eliminated. The strategies are helpful in designing various cardiac devices. Since the second strategy is more efficient and robust than the first one, and the response time in the second strategy is far less than that in the first one, the former is suitable for the quick-response control systems. In addition, our spatiotemporal control strategies, especially the second strategy, can be applied to other cardiac models, even to other reaction-diffusion systems. (general)

  16. Biology and conservation of Xantus's Murrelet: Discovery, taxonomy and distribution

    Science.gov (United States)

    Carter, Harry R.; Sealy, Spencer G.; Burkett, Esther E.; Piatt, John F.

    2005-01-01

    The biology of Xantus's Murrelets Synthliboramphus hypoleucus is similar in many respects to better-studied Ancient Murrelets S. antiquus, especially regarding morphology and the species' precocial mode of post-hatching development. It nests mainly in rock crevices but also under shrubs on islands in southern California, United States, and northwestern Baja California, Mexico (27oN to 34oN). The species was discovered in 1859 by Janos Xantus. Two subspecies (S. h. hypoleucus and S. h. scrippsi) are recognized that show limited evidence of interbreeding. At sea, closely related Craveri's Murrelets S. craveri co-occur with Xantus's Murrelets off California and western Baja California during half the year, but the former species has a discrete breeding range in the Gulf of California, Mexico. Breeding was documented at 13 island groups between 1863 and 1976. Post-breeding dispersal as far north as central British Columbia, Canada (c. 52oN) was observed in the 1940s to 1960s. A few Xantus's Murrelets disperse south of breeding colonies to Magdalena Bay, Baja California (c. 24oN). The southernmost record is the type specimen collected by Xantus near Cabo San Lucas, Baja California (c. 23oN). Chief threats to this species include introduced mammalian predators on breeding islands, heightened predation by natural predators in human-modified island habitats, and oil pollution. In January 2005, a Pacific Seabird Group special symposium, "Biology and conservation of the Xantus's Murrelet," highlighted conservation concerns and promoted publication of recent studies of this little-known alcid, with nine symposium papers published in this issue of Marine Ornithology. Much of what we know about Xantus's Murrelets has been learned in recent years, and many aspects of biology remain to be described.

  17. Biological traits explain the distribution and colonisation ability of the invasive shore crab Hemigrapsus takanoi

    Science.gov (United States)

    Gothland, M.; Dauvin, J. C.; Denis, L.; Dufossé, F.; Jobert, S.; Ovaert, J.; Pezy, J. P.; Tous Rius, A.; Spilmont, N.

    2014-04-01

    Comprehending marine invasions requires a better knowledge of the biological traits of invasive species, and the future spread of invasive species may be predicted through comprehensive overviews of their distribution. This study thus presents the current distribution of a non-indigenous species, the Asian shore crab Hemigrapsus takanoi, as well as the species population characteristics (size distribution and cohorts), based on a five-year survey (2008-2012) along the French coast of the English Channel. Two large populations were found near harbours: one on the Opal Coast (where density reached 61 ± 22 ind.m-2, mean ± s.d., in Dunkirk harbour) and one on the Calvados coast (density up to 26 ± 6 ind.m-2, mean ± s.d, in Honfleur harbour). H. takanoi exhibited a short life cycle, a rapid growth, an early sexual maturity and a high adult mortality. These features, combined with previously described high fecundity and high dispersal ability, endow this species with an 'r-selected strategy'. This strategy, which usually characterises species with a high colonisation ability, would explain the success of H. takanoi for colonising the French coast of the Channel. However, the species was found only in harbours and their vicinity; H. takanoi thus exhibited a discontinuous distribution along the 700 km of coastline. These results are discussed regarding sediment preference and potential introduction vectors. Hemigrapsus takanoi is now considered as established on the French coast and further studies are needed to evaluate the consequences of its introduction on the structure and functioning of the impacted shores.

  18. Using Genome-scale Models to Predict Biological Capabilities

    DEFF Research Database (Denmark)

    O’Brien, Edward J.; Monk, Jonathan M.; Palsson, Bernhard O.

    2015-01-01

    Constraint-based reconstruction and analysis (COBRA) methods at the genome scale have been under development since the first whole-genome sequences appeared in the mid-1990s. A few years ago, this approach began to demonstrate the ability to predict a range of cellular functions, including cellul...

  19. Predictive Models of Nanotoxicity: Relationship of Physicochemical Properties to Particle Movement Through Biological Barriers

    Science.gov (United States)

    Understanding the linkage between the physicochemical (PC) properties of nanoparticles (NP) and their activation of biological systems is poorly understood, yet fundamental to predicting nanotoxicity, idenitifying mode of actions and developing appropriate and effective regul...

  20. Biological lifestyle factors in adult distance education: predicting cognitive and learning performance

    NARCIS (Netherlands)

    Gijselaers, Jérôme

    2015-01-01

    Gijselaers, H. J. M. (2015, 20 October). Biological lifestyle factors in adult distance education: predicting cognitive and learning performance. Presentation given for the inter-faculty Data Science group at the Open University of the Netherlands, Heerlen, The Netherlands.

  1. Exploitation of complex network topology for link prediction in biological interactomes

    KAUST Repository

    Alanis Lobato, Gregorio

    2014-01-01

    In this work, we propose three novel and powerful approaches for the prediction of interactions in biological networks and conclude that it is possible to mine the topology of these complex system representations and produce reliable

  2. The distribution of cultural and biological diversity in Africa

    DEFF Research Database (Denmark)

    Moore, Joslin L; Manne, Lisa; Brooks, Thomas

    2002-01-01

    Anthropologists, biologists and linguists have all noted an apparent coincidence in species diversity and human cultural or linguistic diversity. We present, to our knowledge, one of the first quantitative descriptions of this coincidence and show that, for 2 degrees x 2 degrees grid cells across...... sub-Saharan Africa, cultural diversity and vertebrate species diversity exhibit marked similarities in their overall distribution. In addition, we show that 71% of the observed variation in species richness and 36% in language richness can be explained on the basis of environmental factors, suggesting...

  3. Predicted allowable doses to normal organs for biologically targeted radiotherapy

    International Nuclear Information System (INIS)

    O'Donoghue, J.A.; Wheldon, T.E.; Western Regional Hospital Board, Glasgow

    1988-01-01

    The authors have used Dale's extension to the ''linear quadratic'' (LQ) model (Dale, 1985) to evaluate ''equivalent doses'' in cases involving exponentially decaying dose rates. This analysis indicates that the dose-rate effect will be a significant determinant of allowable doses to organs such as liver, kidney and lung. These organ tolerance doses constitute independent constraints on the therapeutic intensity of biologically targeted radiotherapy in exactly the same way as for conventional external beam radiotherapy. In the context of marrow rescue they will in all likelihood constitute the dose-limiting side-effects and thus be especially important. (author)

  4. Distribution and biology of Indo-Pacific insular hypogeal shrimps

    Science.gov (United States)

    Maciolek, J.A.

    1983-01-01

    Ten species of caridean shrimps, representing nine genera in five families, have been found in exposures of the marine water table at 28 islands from Hawaii to the western Indian Ocean. Synthesis of literature information and personal observations indicate that, as a group, these shrimps are characterized by red body pigment, reduced but pigmented eyes, euryhalinity, a proclivity for interstitial seawater in limestone or lava rock, generalized food requirements, and probable pre-Pleistocene origins. The shrimps have not been found in waters cooler than about 20°C.Species are often solitary, but as many as five are known to coexist. Six of the species have widely scattered populations, some as far apart as Hawaii and the Red Sea. Passive oceanic dispersal is endorsed as a general explanation for such apparently disjunct distributions. On the basis of an assumed primary habitat requirement of interstitial marine water, which could include that in shallow submerged rock as well as that in emergent (insular) rock, I hypothesize a much more cosmopolitan distribution of these shrimps in the Indo-Pacific Tropical Zone.

  5. Precision predictions for Higgs differential distributions at the LHC

    Energy Technology Data Exchange (ETDEWEB)

    Ebert, Markus

    2017-08-15

    After the discovery of a Standard-Model-like Higgs boson at the LHC a central aspect of the LHC physics program is to study the Higgs boson's couplings to Standard Model particles in detail in order to elucidate the nature of the Higgs mechanism and to search for hints of physics beyond the Standard Model. This requires precise theory predictions for both inclusive and differential Higgs cross sections. In this thesis we focus on the application of resummation techniques in the framework of Soft-Collinear Effective Theory (SCET) to obtain accurate predictions with reliable theory uncertainties for various observables. We first consider transverse momentum distributions, where the resummation of large logarithms in momentum (or distribution) space has been a long-standing open question. We show that its two-dimensional nature leads to additional difficulties not observed in one-dimensional observables such as thrust, and solving the associated renormalization group equations (RGEs) in momentum space thus requires a very careful scale setting. This is achieved using distributional scale setting, a new technique to solve differential equations such as RGEs directly in distribution space, as it allows one to treat logarithmic plus distributions like ordinary logarithms. We show that the momentum space solution fundamentally differs from the standard resummation in Fourier space by different boundary terms to all orders in perturbation theory and hence provides an interesting and complementary approach to obtain new insight into the all-order perturbative and nonperturbative structure of transverse momentum distributions. Our work lays the ground for a detailed numerical study of the momentum space resummation. We then show that in the case of a discovery of a new heavy color-singlet resonance such as a heavy Higgs boson, one can reliably and model-independently infer its production mechanism by dividing the data into two mutually exclusive jet bins. The method is

  6. Biological stability in drinking water distribution systems : A novel approach for systematic microbial water quality monitoring

    NARCIS (Netherlands)

    Prest, E.I.E.D.

    2015-01-01

    Challenges to achieve biological stability in drinking water distribution systems Drinking water is distributed from the treatment facility to consumers through extended man-made piping systems. The World Health Organization drinking water guidelines (2006) stated that “Water entering the

  7. Particle size distribution of iron nanomaterials in biological medium by SR-SAXS method

    International Nuclear Information System (INIS)

    Jing Long; Feng Weiyue; Wang Bing; Wang Meng; Ouyang Hong; Zhao Yuliang; Chai Zhifang; Wang Yun; Wang Huajiang; Zhu Motao; Wu Zhonghua

    2009-01-01

    A better understanding of biological effects of nanomaterials in organisms requests knowledge of the physicochemical properties of nanomaterials in biological systems. Affected by high concentration salts and proteins in biological medium, nanoparticles are much easy to agglomerate,hence the difficulties in characterizing size distribution of the nanomaterials in biological medium.In this work, synchrotron radiation small angle X-ray scattering(SR-SAXS) was used to determine size distributions of Fe, Fe 2 O 3 and Fe 3 O 4 nanoparticles of various concentrations in PBS and DMEM culture medium. The results show that size distributions of the nanomaterials could perfectly analyzed by SR-SAXS. The SR-SAXS data were not affected by the particle content and types of the dispersion medium.It is concluded that SR-SAXS can be used for size measurement of nanomaterials in unstable dispersion systems. (authors)

  8. Biological Activity Predictions and Hydrogen Bonding Analysis in Quinolines

    Science.gov (United States)

    Gupta, Palvi; Kamni

    The paper has been designed to make a comprehensive review of a particular series of organic molecular assembly in the form of compendium. An overview of general description of fifteen quinoline derivatives has been given. The biological activity spectra of quinoline derivatives have been correlated on structure activity relationships base which provides the different Pa (possibility of activity) and Pi (possibility of inactivity) values. Expositions of the role of intermolecular interactions in the identified derivatives have been discussed with the standard distance and angle cut-off criteria criteria as proposed by Desiraju and Steiner (1999) in an International monogram on crystallography. Distance-angle scatter plots for intermolecular interactions are presented for a better understanding of the packing interactions which exist in quinoline derivatives.

  9. Technical note: Combining quantile forecasts and predictive distributions of streamflows

    Science.gov (United States)

    Bogner, Konrad; Liechti, Katharina; Zappa, Massimiliano

    2017-11-01

    The enhanced availability of many different hydro-meteorological modelling and forecasting systems raises the issue of how to optimally combine this great deal of information. Especially the usage of deterministic and probabilistic forecasts with sometimes widely divergent predicted future streamflow values makes it even more complicated for decision makers to sift out the relevant information. In this study multiple streamflow forecast information will be aggregated based on several different predictive distributions, and quantile forecasts. For this combination the Bayesian model averaging (BMA) approach, the non-homogeneous Gaussian regression (NGR), also known as the ensemble model output statistic (EMOS) techniques, and a novel method called Beta-transformed linear pooling (BLP) will be applied. By the help of the quantile score (QS) and the continuous ranked probability score (CRPS), the combination results for the Sihl River in Switzerland with about 5 years of forecast data will be compared and the differences between the raw and optimally combined forecasts will be highlighted. The results demonstrate the importance of applying proper forecast combination methods for decision makers in the field of flood and water resource management.

  10. Protein thermodynamics can be predicted directly from biological growth rates.

    Directory of Open Access Journals (Sweden)

    Ross Corkrey

    Full Text Available Life on Earth is capable of growing from temperatures well below freezing to above the boiling point of water, with some organisms preferring cooler and others hotter conditions. The growth rate of each organism ultimately depends on its intracellular chemical reactions. Here we show that a thermodynamic model based on a single, rate-limiting, enzyme-catalysed reaction accurately describes population growth rates in 230 diverse strains of unicellular and multicellular organisms. Collectively these represent all three domains of life, ranging from psychrophilic to hyperthermophilic, and including the highest temperature so far observed for growth (122 °C. The results provide credible estimates of thermodynamic properties of proteins and obtain, purely from organism intrinsic growth rate data, relationships between parameters previously identified experimentally, thus bridging a gap between biochemistry and whole organism biology. We find that growth rates of both unicellular and multicellular life forms can be described by the same temperature dependence model. The model results provide strong support for a single highly-conserved reaction present in the last universal common ancestor (LUCA. This is remarkable in that it means that the growth rate dependence on temperature of unicellular and multicellular life forms that evolved over geological time spans can be explained by the same model.

  11. Predicting weed problems in maize cropping by species distribution modelling

    Directory of Open Access Journals (Sweden)

    Bürger, Jana

    2014-02-01

    Full Text Available Increasing maize cultivation and changed cropping practices promote the selection of typical maize weeds that may also profit strongly from climate change. Predicting potential weed problems is of high interest for plant production. Within the project KLIFF, experiments were combined with species distribution modelling for this task in the region of Lower Saxony, Germany. For our study, we modelled ecological and damage niches of nine weed species that are significant and wide spread in maize cropping in a number of European countries. Species distribution models describe the ecological niche of a species, these are the environmental conditions under which a species can maintain a vital population. It is also possible to estimate a damage niche, i.e. the conditions under which a species causes damage in agricultural crops. For this, we combined occurrence data of European national data bases with high resolution climate, soil and land use data. Models were also projected to simulated climate conditions for the time horizon 2070 - 2100 in order to estimate climate change effects. Modelling results indicate favourable conditions for typical maize weed occurrence virtually all over the study region, but only a few species are important in maize cropping. This is in good accordance with the findings of an earlier maize weed monitoring. Reaction to changing climate conditions is species-specific, for some species neutral (E. crus-galli, other species may gain (Polygonum persicaria or loose (Viola arvensis large areas of suitable habitats. All species with damage potential under present conditions will remain important in maize cropping, some more species will gain regional importance (Calystegia sepium, Setara viridis.

  12. Predicting the Distribution of Yellowfin Tuna in Philippine Waters

    Science.gov (United States)

    Perez, G. J. P.; Leonardo, E. M.

    2015-12-01

    The Philippines is considered as a major tuna producer in the Western and Central Pacific Ocean, both for domestic consumption and on industrial scale. However, with the ever-increasing demand of growing population, it has always been a challenge to achieve sustainable fishing. The creation of satellite-derived potential fishing zone maps is a technology that has been adopted by advanced countries for almost three decades already and has led to reduction in search times by up to 40%. In this study, a Generalized Additive Model (GAM) is developed to predict the distribution of the Yellowfin tuna species in seas surrounding the Philippines based on the Catch-Per-Unit-Effort (CPUE) index. Level 3 gridded chlorophyll-a and sea surface temperature from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Aqua satellite of the National Aeronautics and Space Administration (NASA) are the main input parameters of the model. Chlorophyll-a is linked with the presence of phytoplankton, which indicates primary productivity and suggests potential regions of fish aggregation. Fish also prefers to stay in regions where the temperature is stable, thus the sea surface temperature fronts serve as a guide to locate concentrations of fish school. Historical monthly tuna catch data from Western and Central Pacific Commissions (WCPFC) is used to train the model. The resulting predictions are converted to potential fishing zone maps and are evaluated within and beyond the historical time range of the training data used. Diagnostic tests involving adjusted R2 value, GAM residual plots and root mean square error value are used to assess the accuracy of the model. The generated maps were able to confirm locations of known tuna fishing grounds in Mindanao and other parts of the country, as well us detect their seasonality and interannual variability. To improve the performance of the model, ancillary data such as surface winds reanalysis from National Centers for

  13. Uncertainties of predictions from parton distributions 1, experimental errors

    CERN Document Server

    Martin, A D; Stirling, William James; Thorne, R S; CERN. Geneva

    2003-01-01

    We determine the uncertainties on observables arising from the errors on the experimental data that are fitted in the global MRST2001 parton analysis. By diagonalizing the error matrix we produce sets of partons suitable for use within the framework of linear propagation of errors, which is the most convenient method for calculating the uncertainties. Despite the potential limitations of this approach we find that it can be made to work well in practice. This is confirmed by our alternative approach of using the more rigorous Lagrange multiplier method to determine the errors on physical quantities directly. As particular examples we determine the uncertainties on the predictions of the charged-current deep-inelastic structure functions, on the cross-sections for W production and for Higgs boson production via gluon--gluon fusion at the Tevatron and the LHC, on the ratio of W-minus to W-plus production at the LHC and on the moments of the non-singlet quark distributions. We discuss the corresponding uncertain...

  14. Theoretical predictions of lactate and hydrogen ion distributions in tumours.

    Directory of Open Access Journals (Sweden)

    Maymona Al-Husari

    Full Text Available High levels of lactate and H(+-ions play an important role in the invasive and metastatic cascade of some tumours. We develop a mathematical model of cellular pH regulation focusing on the activity of the Na(+/H(+ exchanger (NHE and the lactate/H(+ symporter (MCT to investigate the spatial correlations of extracellular lactate and H(+-ions. We highlight a crucial role for blood vessel perfusion rates in determining the spatial correlation between these two cations. We also predict critical roles for blood lactate, the activity of the MCTs and NHEs on the direction of the cellular pH gradient in the tumour. We also incorporate experimentally determined heterogeneous distributions of the NHE and MCT transporters. We show that this can give rise to a higher intracellular pH and a lower intracellular lactate but does not affect the direction of the reversed cellular pH gradient or redistribution of protons away from the glycolytic source. On the other hand, including intercellular gap junction communication in our model can give rise to a reversed cellular pH gradient and can influence the levels of pH.

  15. Prediction of HAMR Debris Population Distribution Released from GEO Space

    Science.gov (United States)

    Rosengren, A.; Scheeres, D.

    2012-09-01

    in inclination. When the nodal rate of the system is commensurate with the nodal rate of the Moon, the perturbations build up more effectively over long periods to produce significant effects on the orbit. Such resonances, which occurs for a class of HAMR objects that are not cleared out of orbit, gives rise to strongly changing dynamics over longer time periods. In this paper, we present the averaged model, and discuss its fundamental predictions and comparisons with explicit long-term numerical integrations of HAMR objects in GEO space. Using this tool, we study a range of HAMR objects, released in geostationary orbit, with various area-to-mass ratios, and predict the spatiotemporal distribution of the population. We identified a unique systematic structure associated with their distribution in inclination and ascending node phase space. Given that HAMR objects are the most difficult to target from an observational point of view, this work will have many implications for the space surveillance community, and will allow observers to implement better search strategies for this class of debris.

  16. Synthesis and biology of cyclic imine toxins, an emerging class of potent, globally distributed marine toxins.

    Science.gov (United States)

    Stivala, Craig E; Benoit, Evelyne; Aráoz, Rómulo; Servent, Denis; Novikov, Alexei; Molgó, Jordi; Zakarian, Armen

    2015-03-01

    From a small group of exotic compounds isolated only two decades ago, Cyclic Imine (CI) toxins have become a major class of marine toxins with global distribution. Their distinct chemical structure, biological mechanism of action, and intricate chemistry ensures that CI toxins will continue to be the subject of fascinating fundamental studies in the broad fields of chemistry, chemical biology, and toxicology. The worldwide occurrence of potent CI toxins in marine environments, their accumulation in shellfish, and chemical stability are important considerations in assessing risk factors for human health. This review article aims to provide an account of chemistry, biology, and toxicology of CI toxins from their discovery to the present day.

  17. Fair value versus historical cost-based valuation for biological assets: predictability of financial information

    Directory of Open Access Journals (Sweden)

    Josep M. Argilés

    2011-08-01

    This paper performs an empirical study with a sample of Spanish farms valuing biological assets at HC and a sample applying FV, finding no significant differences between both valuation methods to assess future cash flows. However, most tests reveal more predictive power of future earnings under fair valuation of biological assets, which is not explained by differences in volatility of earnings and profitability. The study also evidences the existence of flawed HC accounting practices for biological assets in agriculture, which suggests scarce information content of this valuation method in the predominant small business units existing in the agricultural sector in advanced Western countries.

  18. Multiple-Swarm Ensembles: Improving the Predictive Power and Robustness of Predictive Models and Its Use in Computational Biology.

    Science.gov (United States)

    Alves, Pedro; Liu, Shuang; Wang, Daifeng; Gerstein, Mark

    2018-01-01

    Machine learning is an integral part of computational biology, and has already shown its use in various applications, such as prognostic tests. In the last few years in the non-biological machine learning community, ensembling techniques have shown their power in data mining competitions such as the Netflix challenge; however, such methods have not found wide use in computational biology. In this work, we endeavor to show how ensembling techniques can be applied to practical problems, including problems in the field of bioinformatics, and how they often outperform other machine learning techniques in both predictive power and robustness. Furthermore, we develop a methodology of ensembling, Multi-Swarm Ensemble (MSWE) by using multiple particle swarm optimizations and demonstrate its ability to further enhance the performance of ensembles.

  19. GGPPS1 predicts the biological character of hepatocellular carcinoma in patients with cirrhosis

    International Nuclear Information System (INIS)

    Yu, De-cai; Liu, Jia; Chen, Jun; Shao, Jiao-jiao; Shen, Xiao; Xia, Hong-guang; Li, Chao-jun; Xue, Bin; Ding, Yi-tao

    2014-01-01

    Hepatocellular carcinoma (HCC) has been associated with diabetes and obesity, but a possible connection with the metabolic syndrome (MetS) and its potential interaction with hepatitis and cirrhosis are open to discussion. Our previous investigations have shown that GGPPS1 plays a critical role during hyperinsulinism. In this report, the expression and distribution of GGPPS1 in liver cancer, and its clinical significance were investigated. 70 patients with hepatocellular carcinoma (HCC) were included in this study. Three different types of tissues from each HCC patient were assembled immediately after surgical resection: tumor-free tissue >5 cm far from tumor edge (TF), adjacent nonmalignant tissue within 2 cm (AT), and tissue from the tumor (TT). Normal liver tissues from 10 liver transplant donors served as healthy control (HC) while 10 patients with liver cirrhosis as cirrhosis control (CC). The expression and distribution of GGPPS1 were detected by immunohistochemistry, western blots, or real-time PCR. The relationship between the expression of GGPPS1 and clinic pathologic index were analyzed. We found that GGPPS1 was intensified mainly in the cytoplasm of liver tumor cells. Both the expression of GGPPS1 mRNA and protein were upregulated in TT comparing to AT or TF. Meanwhile, HCC patients with cirrhosis had relative higher expression of GGPPS1. In addition, many pathologic characters show close correlation with GGPPS1, such as tumor stage, vessel invasion, and early recurrence. GGPPS1 may play a critical role during the development of HCC from cirrhosis and is of clinical significance for predicting biological character of HCC

  20. Single-mode biological distributed feedback lasers based on vitamin B2 doped gelatin

    DEFF Research Database (Denmark)

    Vannahme, Christoph; Maier-Flaig, F.; Lemmer, U.

    Biological second-order distributed feedback (DFB) lasers are presented. Riboflavin (vitamin B2) doped gelatin as active material is spin-coated onto nanoimprinted polymer with low refractive index. DFB grating periods of 368 nm and 384 nm yield laser emission at 543 nm and 562 nm, respectively....

  1. Evaluation of the biological and scanning distribution of hydroxyapatite-153Sm radiotherapeutic agent

    International Nuclear Information System (INIS)

    Herrera, J.; Paredes, N.; Portilla, A.; Miranda, J.; Carrillo, D.

    1999-01-01

    Fixation of 153 Sm labeled hydroxyapatite (HA) in the synovial capsule and extra articular localization were evaluated by means of biological distribution tests and gamma scanning studies. These were carried out using HA- 153 Sm with particle size ranging between 5 and μm, and radiochemical purity above 99%. Animal models used were wistar rats and new zealand rabbits. Rabbits were injected with 7,4 MBq of HA- 153 Sm while rats received between 1,85 and 92,6 MBq of HA- 153 Sm. In both cases injection was given in the intra articular area. After injection, scanning images were obtained in rabbits on the 1 st , 3 rd and 7 st day and in rats on the 2 nd and 7 th day. Biological distribution studies are conducted in the 2 hours to 9 days range in rats and one the 7 th day in rabbits. No extra articular localization of HA- 153 Sm was found in scanning conducted on rabbits by the 1 st , 3 rd and 7 st day after injection, neither on rats by the 2 nd and 7 th day. Biological distributions for rabbits and rats show localization above 99% in the intra articular area, during the evaluated periods of time. The evaluations of the biological distribution and the scintigraphic images show that fixation of HA- 153 Sm in the synovial capsule up to the 9 th day is very high

  2. Responsiveness of performance and morphological traits to experimental submergence predicts field distribution pattern of wetland plants

    NARCIS (Netherlands)

    Luo, Fang-Li; Huang, Lin; Lei, Ting; Xue, Wei; Li, Hong-Li; Yu, Fei-Hai; Cornelissen, J.H.C.

    2016-01-01

    Question: Plant trait mean values and trait responsiveness to different environmental regimes are both important determinants of plant field distribution, but the degree to which plant trait means vs trait responsiveness predict plant distribution has rarely been compared quantitatively. Because

  3. Systems Biology-Derived Biomarkers to Predict Progression of Renal Function Decline in Type 2 Diabetes

    NARCIS (Netherlands)

    Mayer, Gert; Heerspink, Hiddo J. L.; Aschauer, Constantin; Heinzel, Andreas; Heinze, Georg; Kainz, Alexander; Sunzenauer, Judith; Perco, Paul; de Zeeuw, Dick; Rossing, Peter; Pena, Michelle; Oberbauer, Rainer

    OBJECTIVE: Chronic kidney disease (CKD) in diabetes has a complex molecular and likely multifaceted pathophysiology. We aimed to validate a panel of biomarkers identified using a systems biology approach to predict the individual decline of estimated glomerular filtration rate (eGFR) in a large

  4. Predicting and setting conservation priorities for Bolivian mammals based on biological correlates of the risk of decline.

    Science.gov (United States)

    Peñaranda, Diego A; Simonetti, Javier A

    2015-06-01

    The recognition that growing proportions of species worldwide are endangered has led to the development of comparative analyses to elucidate why some species are more prone to extinction than others. Understanding factors and patterns of species vulnerability might provide an opportunity to develop proactive conservation strategies. Such comparative analyses are of special concern at national scales because this is the scale at which most conservation initiatives take place. We applied powerful ensemble learning models to test for biological correlates of the risk of decline among the Bolivian mammals to understand species vulnerability at a national scale and to predict the population trend for poorly known species. Risk of decline was nonrandomly distributed: higher proportions of large-sized taxa were under decline, whereas small-sized taxa were less vulnerable. Body mass, mode of life (i.e., aquatic, terrestrial, volant), geographic range size, litter size, home range, niche specialization, and reproductive potential were strongly associated with species vulnerability. Moreover, we found interacting and nonlinear effects of key traits on the risk of decline of mammals at a national scale. Our model predicted 35 data-deficient species in decline on the basis of their biological vulnerability, which should receive more attention in order to prevent their decline. Our results highlight the relevance of comparative analysis at relatively narrow geographical scales, reveal previously unknown factors related to species vulnerability, and offer species-by-species outcomes that can be used to identify targets for conservation, especially for insufficiently known species. © 2015 Society for Conservation Biology.

  5. Modeling, robust and distributed model predictive control for freeway networks

    NARCIS (Netherlands)

    Liu, S.

    2016-01-01

    In Model Predictive Control (MPC) for traffic networks, traffic models are crucial since they are used as prediction models for determining the optimal control actions. In order to reduce the computational complexity of MPC for traffic networks, macroscopic traffic models are often used instead of

  6. MSD-MAP: A Network-Based Systems Biology Platform for Predicting Disease-Metabolite Links.

    Science.gov (United States)

    Wathieu, Henri; Issa, Naiem T; Mohandoss, Manisha; Byers, Stephen W; Dakshanamurthy, Sivanesan

    2017-01-01

    Cancer-associated metabolites result from cell-wide mechanisms of dysregulation. The field of metabolomics has sought to identify these aberrant metabolites as disease biomarkers, clues to understanding disease mechanisms, or even as therapeutic agents. This study was undertaken to reliably predict metabolites associated with colorectal, esophageal, and prostate cancers. Metabolite and disease biological action networks were compared in a computational platform called MSD-MAP (Multi Scale Disease-Metabolite Association Platform). Using differential gene expression analysis with patient-based RNAseq data from The Cancer Genome Atlas, genes up- or down-regulated in cancer compared to normal tissue were identified. Relational databases were used to map biological entities including pathways, functions, and interacting proteins, to those differential disease genes. Similar relational maps were built for metabolites, stemming from known and in silico predicted metabolite-protein associations. The hypergeometric test was used to find statistically significant relationships between disease and metabolite biological signatures at each tier, and metabolites were assessed for multi-scale association with each cancer. Metabolite networks were also directly associated with various other diseases using a disease functional perturbation database. Our platform recapitulated metabolite-disease links that have been empirically verified in the scientific literature, with network-based mapping of jointly-associated biological activity also matching known disease mechanisms. This was true for colorectal, esophageal, and prostate cancers, using metabolite action networks stemming from both predicted and known functional protein associations. By employing systems biology concepts, MSD-MAP reliably predicted known cancermetabolite links, and may serve as a predictive tool to streamline conventional metabolomic profiling methodologies. Copyright© Bentham Science Publishers; For any

  7. Fractal scaling of particle size distribution and relationships with topsoil properties affected by biological soil crusts.

    Directory of Open Access Journals (Sweden)

    Guang-Lei Gao

    Full Text Available BACKGROUND: Biological soil crusts are common components of desert ecosystem; they cover ground surface and interact with topsoil that contribute to desertification control and degraded land restoration in arid and semiarid regions. METHODOLOGY/PRINCIPAL FINDINGS: To distinguish the changes in topsoil affected by biological soil crusts, we compared topsoil properties across three types of successional biological soil crusts (algae, lichens, and mosses crust, as well as the referenced sandland in the Mu Us Desert, Northern China. Relationships between fractal dimensions of soil particle size distribution and selected soil properties were discussed as well. The results indicated that biological soil crusts had significant positive effects on soil physical structure (P<0.05; and soil organic carbon and nutrients showed an upward trend across the successional stages of biological soil crusts. Fractal dimensions ranged from 2.1477 to 2.3032, and significantly linear correlated with selected soil properties (R(2 = 0.494∼0.955, P<0.01. CONCLUSIONS/SIGNIFICANCE: Biological soil crusts cause an important increase in soil fertility, and are beneficial to sand fixation, although the process is rather slow. Fractal dimension proves to be a sensitive and useful index for quantifying changes in soil properties that additionally implies desertification. This study will be essential to provide a firm basis for future policy-making on optimal solutions regarding desertification control and assessment, as well as degraded ecosystem restoration in arid and semiarid regions.

  8. Repurposing High-Throughput Image Assays Enables Biological Activity Prediction for Drug Discovery.

    Science.gov (United States)

    Simm, Jaak; Klambauer, Günter; Arany, Adam; Steijaert, Marvin; Wegner, Jörg Kurt; Gustin, Emmanuel; Chupakhin, Vladimir; Chong, Yolanda T; Vialard, Jorge; Buijnsters, Peter; Velter, Ingrid; Vapirev, Alexander; Singh, Shantanu; Carpenter, Anne E; Wuyts, Roel; Hochreiter, Sepp; Moreau, Yves; Ceulemans, Hugo

    2018-05-17

    In both academia and the pharmaceutical industry, large-scale assays for drug discovery are expensive and often impractical, particularly for the increasingly important physiologically relevant model systems that require primary cells, organoids, whole organisms, or expensive or rare reagents. We hypothesized that data from a single high-throughput imaging assay can be repurposed to predict the biological activity of compounds in other assays, even those targeting alternate pathways or biological processes. Indeed, quantitative information extracted from a three-channel microscopy-based screen for glucocorticoid receptor translocation was able to predict assay-specific biological activity in two ongoing drug discovery projects. In these projects, repurposing increased hit rates by 50- to 250-fold over that of the initial project assays while increasing the chemical structure diversity of the hits. Our results suggest that data from high-content screens are a rich source of information that can be used to predict and replace customized biological assays. Copyright © 2018 Elsevier Ltd. All rights reserved.

  9. Distributed estimation based on observations prediction in wireless sensor networks

    KAUST Repository

    Bouchoucha, Taha; Ahmed, Mohammed F A; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim

    2015-01-01

    We consider wireless sensor networks (WSNs) used for distributed estimation of unknown parameters. Due to the limited bandwidth, sensor nodes quantize their noisy observations before transmission to a fusion center (FC) for the estimation process

  10. Prediction of residence time distributions in food processing machinery

    DEFF Research Database (Denmark)

    Karlson, Torben; Friis, Alan; Szabo, Peter

    1996-01-01

    The velocity field in a co-rotating disc scraped surface heat exchanger (CDHE) is calculated using a finite element method. The residence time distribution for the CDHE is then obtained by tracing particles introduced in the inlet.......The velocity field in a co-rotating disc scraped surface heat exchanger (CDHE) is calculated using a finite element method. The residence time distribution for the CDHE is then obtained by tracing particles introduced in the inlet....

  11. A consensus approach for estimating the predictive accuracy of dynamic models in biology.

    Science.gov (United States)

    Villaverde, Alejandro F; Bongard, Sophia; Mauch, Klaus; Müller, Dirk; Balsa-Canto, Eva; Schmid, Joachim; Banga, Julio R

    2015-04-01

    Mathematical models that predict the complex dynamic behaviour of cellular networks are fundamental in systems biology, and provide an important basis for biomedical and biotechnological applications. However, obtaining reliable predictions from large-scale dynamic models is commonly a challenging task due to lack of identifiability. The present work addresses this challenge by presenting a methodology for obtaining high-confidence predictions from dynamic models using time-series data. First, to preserve the complex behaviour of the network while reducing the number of estimated parameters, model parameters are combined in sets of meta-parameters, which are obtained from correlations between biochemical reaction rates and between concentrations of the chemical species. Next, an ensemble of models with different parameterizations is constructed and calibrated. Finally, the ensemble is used for assessing the reliability of model predictions by defining a measure of convergence of model outputs (consensus) that is used as an indicator of confidence. We report results of computational tests carried out on a metabolic model of Chinese Hamster Ovary (CHO) cells, which are used for recombinant protein production. Using noisy simulated data, we find that the aggregated ensemble predictions are on average more accurate than the predictions of individual ensemble models. Furthermore, ensemble predictions with high consensus are statistically more accurate than ensemble predictions with large variance. The procedure provides quantitative estimates of the confidence in model predictions and enables the analysis of sufficiently complex networks as required for practical applications. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  12. A new simplified allometric approach for predicting the biological half-life of radionuclides in reptiles

    International Nuclear Information System (INIS)

    Beresford, N.A.; Wood, M.D.

    2014-01-01

    A major source of uncertainty in the estimation of radiation dose to wildlife is the prediction of internal radionuclide activity concentrations. Allometric (mass-dependent) relationships describing biological half-life (T 1/2b ) of radionuclides in organisms can be used to predict organism activity concentrations. The establishment of allometric expressions requires experimental data which are often lacking. An approach to predict the T 1/2b in homeothermic vertebrates has recently been proposed. In this paper we have adapted this to be applicable to reptiles. For Cs, Ra and Sr, over a mass range of 0.02–1.5 kg, resultant predictions were generally within a factor of 6 of reported values demonstrating that the approach can be used when measured T 1/2b data are lacking. However, the effect of mass on reptilian radionuclide T 1/2b is minimal. If sufficient measured data are available for a given radionuclide then it is likely that these would give a reasonable estimate of T 1/2b in any reptile species. - Highlights: • An allometric approach to predict radionuclide T 1/2b values in reptiles is derived. • Predictions are generally within a factor of six of measured values. • Radionuclide biological half-life is in-effect mass independent

  13. Clinical history and biologic age predicted falls better than objective functional tests.

    Science.gov (United States)

    Gerdhem, Paul; Ringsberg, Karin A M; Akesson, Kristina; Obrant, Karl J

    2005-03-01

    Fall risk assessment is important because the consequences, such as a fracture, may be devastating. The objective of this study was to find the test or tests that best predicted falls in a population-based sample of elderly women. The fall-predictive ability of a questionnaire, a subjective estimate of biologic age and objective functional tests (gait, balance [Romberg and sway test], thigh muscle strength, and visual acuity) were compared in 984 randomly selected women, all 75 years of age. A recalled fall was the most important predictor for future falls. Only recalled falls and intake of psycho-active drugs independently predicted future falls. Women with at least five of the most important fall predictors (previous falls, conditions affecting the balance, tendency to fall, intake of psychoactive medication, inability to stand on one leg, high biologic age) had an odds ratio of 11.27 (95% confidence interval 4.61-27.60) for a fall (sensitivity 70%, specificity 79%). The more time-consuming objective functional tests were of limited importance for fall prediction. A simple clinical history, the inability to stand on one leg, and a subjective estimate of biologic age were more important as part of the fall risk assessment.

  14. Estimating biological elementary flux modes that decompose a flux distribution by the minimal branching property

    DEFF Research Database (Denmark)

    Chan, Siu Hung Joshua; Solem, Christian; Jensen, Peter Ruhdal

    2014-01-01

    biologically feasible EFMs by considering their graphical properties. A previous study on the transcriptional regulation of metabolic genes found that distinct branches at a branch point metabolite usually belong to distinct metabolic pathways. This suggests an intuitive property of biologically feasible EFMs......, i.e. minimal branching. RESULTS: We developed the concept of minimal branching EFM and derived the minimal branching decomposition (MBD) to decompose flux distributions. Testing in the core Escherichia coli metabolic network indicated that MBD can distinguish branches at branch points and greatly...... knowledge, which facilitates interpretation. Comparison of the methods applied to a complex flux distribution in Lactococcus lactis similarly showed the advantages of MBD. The minimal branching EFM concept underlying MBD should be useful in other applications....

  15. Plant ecdysteroids: plant sterols with intriguing distributions, biological effects and relations to plant hormones.

    Science.gov (United States)

    Tarkowská, Danuše; Strnad, Miroslav

    2016-09-01

    The present review summarises current knowledge of phytoecdysteroids' biosynthesis, distribution within plants, biological importance and relations to plant hormones. Plant ecdysteroids (phytoecdysteroids) are natural polyhydroxylated compounds that have a four-ringed skeleton, usually composed of either 27 carbon atoms or 28-29 carbon atoms (biosynthetically derived from cholesterol or other plant sterols, respectively). Their physiological roles in plants have not yet been confirmed and their occurrence is not universal. Nevertheless, they are present at high concentrations in various plant species, including commonly consumed vegetables, and have a broad spectrum of pharmacological and medicinal properties in mammals, including hepatoprotective and hypoglycaemic effects, and anabolic effects on skeletal muscle, without androgenic side-effects. Furthermore, phytoecdysteroids can enhance stress resistance by promoting vitality and enhancing physical performance; thus, they are considered adaptogens. This review summarises current knowledge of phytoecdysteroids' biosynthesis, distribution within plants, biological importance and relations to plant hormones.

  16. Dynamic optimization of distributed biological systems using robust and efficient numerical techniques.

    Science.gov (United States)

    Vilas, Carlos; Balsa-Canto, Eva; García, Maria-Sonia G; Banga, Julio R; Alonso, Antonio A

    2012-07-02

    Systems biology allows the analysis of biological systems behavior under different conditions through in silico experimentation. The possibility of perturbing biological systems in different manners calls for the design of perturbations to achieve particular goals. Examples would include, the design of a chemical stimulation to maximize the amplitude of a given cellular signal or to achieve a desired pattern in pattern formation systems, etc. Such design problems can be mathematically formulated as dynamic optimization problems which are particularly challenging when the system is described by partial differential equations.This work addresses the numerical solution of such dynamic optimization problems for spatially distributed biological systems. The usual nonlinear and large scale nature of the mathematical models related to this class of systems and the presence of constraints on the optimization problems, impose a number of difficulties, such as the presence of suboptimal solutions, which call for robust and efficient numerical techniques. Here, the use of a control vector parameterization approach combined with efficient and robust hybrid global optimization methods and a reduced order model methodology is proposed. The capabilities of this strategy are illustrated considering the solution of a two challenging problems: bacterial chemotaxis and the FitzHugh-Nagumo model. In the process of chemotaxis the objective was to efficiently compute the time-varying optimal concentration of chemotractant in one of the spatial boundaries in order to achieve predefined cell distribution profiles. Results are in agreement with those previously published in the literature. The FitzHugh-Nagumo problem is also efficiently solved and it illustrates very well how dynamic optimization may be used to force a system to evolve from an undesired to a desired pattern with a reduced number of actuators. The presented methodology can be used for the efficient dynamic optimization of

  17. Prediction method for thermal ratcheting of a cylinder subjected to axially moving temperature distribution

    International Nuclear Information System (INIS)

    Wada, Hiroshi; Igari, Toshihide; Kitade, Shoji.

    1989-01-01

    A prediction method was proposed for plastic ratcheting of a cylinder, which was subjected to axially moving temperature distribution without primary stress. First, a mechanism of this ratcheting was proposed, which considered the movement of temperature distribution as a driving force of this phenomenon. Predictive equations of the ratcheting strain for two representative temperature distributions were proposed based on this mechanism by assuming the elastic-perfectly-plastic material behavior. Secondly, an elastic-plastic analysis was made on a cylinder subjected to the representative two temperature distributions. Analytical results coincided well with the predicted results, and the applicability of the proposed equations was confirmed. (author)

  18. Hybrid ATDL-gamma distribution model for predicting area source acid gas concentrations

    Energy Technology Data Exchange (ETDEWEB)

    Jakeman, A J; Taylor, J A

    1985-01-01

    An air quality model is developed to predict the distribution of concentrations of acid gas in an urban airshed. The model is hybrid in character, combining reliable features of a deterministic ATDL-based model with statistical distributional approaches. The gamma distribution was identified from a range of distributional models as the best model. The paper shows that the assumptions of a previous hybrid model may be relaxed and presents a methodology for characterizing the uncertainty associated with model predictions. Results are demonstrated for the 98-percentile predictions of 24-h average data over annual periods at six monitoring sites. This percentile relates to the World Health Organization goal for acid gas concentrations.

  19. A joint calibration model for combining predictive distributions

    Directory of Open Access Journals (Sweden)

    Patrizia Agati

    2013-05-01

    Full Text Available In many research fields, as for example in probabilistic weather forecasting, valuable predictive information about a future random phenomenon may come from several, possibly heterogeneous, sources. Forecast combining methods have been developed over the years in order to deal with ensembles of sources: the aim is to combine several predictions in such a way to improve forecast accuracy and reduce risk of bad forecasts.In this context, we propose the use of a Bayesian approach to information combining, which consists in treating the predictive probability density functions (pdfs from the individual ensemble members as data in a Bayesian updating problem. The likelihood function is shown to be proportional to the product of the pdfs, adjusted by a joint “calibration function” describing the predicting skill of the sources (Morris, 1977. In this paper, after rephrasing Morris’ algorithm in a predictive context, we propose to model the calibration function in terms of bias, scale and correlation and to estimate its parameters according to the least squares criterion. The performance of our method is investigated and compared with that of Bayesian Model Averaging (Raftery, 2005 on simulated data.

  20. Predicting the Potential Distribution of Polygala tenuifolia Willd. under Climate Change in China.

    Directory of Open Access Journals (Sweden)

    Hongjun Jiang

    Full Text Available Global warming has created opportunities and challenges for the survival and development of species. Determining how climate change may impact multiple ecosystem levels and lead to various species adaptations is necessary for both biodiversity conservation and sustainable biological resource utilization. In this study, we employed Maxent to predict changes in the habitat range and altitude of Polygala tenuifolia Willd. under current and future climate scenarios in China. Four representative concentration pathways (RCP2.6, RCP4.5, RCP6.0, and RCP8.5 were modeled for two time periods (2050 and 2070. The model inputs included 732 presence points and nine sets of environmental variables under the current conditions and the four RCPs in 2050 and 2070. The area under the receiver-operating characteristic (ROC curve (AUC was used to evaluate model performance. All of the AUCs were greater than 0.80, thereby placing these models in the "very good" category. Using a jackknife analysis, the precipitation in the warmest quarter, annual mean temperature, and altitude were found to be the top three variables that affect the range of P. tenuifolia. Additionally, we found that the predicted highly suitable habitat was in reasonable agreement with its actual distribution. Furthermore, the highly suitable habitat area was slowly reduced over time.

  1. Predictive Distribution of the Dirichlet Mixture Model by the Local Variational Inference Method

    DEFF Research Database (Denmark)

    Ma, Zhanyu; Leijon, Arne; Tan, Zheng-Hua

    2014-01-01

    the predictive likelihood of the new upcoming data, especially when the amount of training data is small. The Bayesian estimation of a Dirichlet mixture model (DMM) is, in general, not analytically tractable. In our previous work, we have proposed a global variational inference-based method for approximately...... calculating the posterior distributions of the parameters in the DMM analytically. In this paper, we extend our previous study for the DMM and propose an algorithm to calculate the predictive distribution of the DMM with the local variational inference (LVI) method. The true predictive distribution of the DMM...... is analytically intractable. By considering the concave property of the multivariate inverse beta function, we introduce an upper-bound to the true predictive distribution. As the global minimum of this upper-bound exists, the problem is reduced to seek an approximation to the true predictive distribution...

  2. Predictive modeling of coral disease distribution within a reef system.

    Directory of Open Access Journals (Sweden)

    Gareth J Williams

    2010-02-01

    Full Text Available Diseases often display complex and distinct associations with their environment due to differences in etiology, modes of transmission between hosts, and the shifting balance between pathogen virulence and host resistance. Statistical modeling has been underutilized in coral disease research to explore the spatial patterns that result from this triad of interactions. We tested the hypotheses that: 1 coral diseases show distinct associations with multiple environmental factors, 2 incorporating interactions (synergistic collinearities among environmental variables is important when predicting coral disease spatial patterns, and 3 modeling overall coral disease prevalence (the prevalence of multiple diseases as a single proportion value will increase predictive error relative to modeling the same diseases independently. Four coral diseases: Porites growth anomalies (PorGA, Porites tissue loss (PorTL, Porites trematodiasis (PorTrem, and Montipora white syndrome (MWS, and their interactions with 17 predictor variables were modeled using boosted regression trees (BRT within a reef system in Hawaii. Each disease showed distinct associations with the predictors. Environmental predictors showing the strongest overall associations with the coral diseases were both biotic and abiotic. PorGA was optimally predicted by a negative association with turbidity, PorTL and MWS by declines in butterflyfish and juvenile parrotfish abundance respectively, and PorTrem by a modal relationship with Porites host cover. Incorporating interactions among predictor variables contributed to the predictive power of our models, particularly for PorTrem. Combining diseases (using overall disease prevalence as the model response, led to an average six-fold increase in cross-validation predictive deviance over modeling the diseases individually. We therefore recommend coral diseases to be modeled separately, unless known to have etiologies that respond in a similar manner to

  3. Distributed Model Predictive Control for Smart Energy Systems

    DEFF Research Database (Denmark)

    Halvgaard, Rasmus Fogtmann; Vandenberghe, Lieven; Poulsen, Niels Kjølstad

    2016-01-01

    Integration of a large number of flexible consumers in a smart grid requires a scalable power balancing strategy. We formulate the control problem as an optimization problem to be solved repeatedly by the aggregator in a model predictive control framework. To solve the large-scale control problem...

  4. Somatic cell count distributions during lactation predict clinical mastitis

    NARCIS (Netherlands)

    Green, M.J.; Green, L.E.; Schukken, Y.H.; Bradley, A.J.; Peeler, E.J.; Barkema, H.W.; Haas, de Y.; Collis, V.J.; Medley, G.F.

    2004-01-01

    This research investigated somatic cell count (SCC) records during lactation, with the purpose of identifying distribution characteristics (mean and measures of variation) that were most closely associated with clinical mastitis. Three separate data sets were used, one containing quarter SCC (n =

  5. Optimal operation of water distribution networks by predictive control ...

    African Journals Online (AJOL)

    This paper presents an approach for the operational optimisation of potable water distribution networks. The maximisation of the use of low-cost power (e.g. overnight pumping) and the maintenance of a target chlorine concentration at final delivery points were defined as important optimisation objectives. The first objective ...

  6. PASS-predicted design, synthesis and biological evaluation of cyclic nitrones as nootropics.

    Science.gov (United States)

    Marwaha, Alka; Goel, R K; Mahajan, Mohinder P

    2007-09-15

    Out of 400 virtually designed imidazoline N-oxides, five cyclic nitrones were selected on the basis of PASS prediction as potent nootropics and were evaluated for their biological activities in albino mice. The selected N-alkyl and aryl-substituted nitrones were found to be excellent nootropics. A series of lead compounds acting as cognition enhancers have been provided, which can be further exploited in search of such New Chemical Entities (NCEs).

  7. Effectiveness of biological surrogates for predicting patterns of marine biodiversity: a global meta-analysis.

    Directory of Open Access Journals (Sweden)

    Camille Mellin

    Full Text Available The use of biological surrogates as proxies for biodiversity patterns is gaining popularity, particularly in marine systems where field surveys can be expensive and species richness high. Yet, uncertainty regarding their applicability remains because of inconsistency of definitions, a lack of standard methods for estimating effectiveness, and variable spatial scales considered. We present a Bayesian meta-analysis of the effectiveness of biological surrogates in marine ecosystems. Surrogate effectiveness was defined both as the proportion of surrogacy tests where predictions based on surrogates were better than random (i.e., low probability of making a Type I error; P and as the predictability of targets using surrogates (R(2. A total of 264 published surrogacy tests combined with prior probabilities elicited from eight international experts demonstrated that the habitat, spatial scale, type of surrogate and statistical method used all influenced surrogate effectiveness, at least according to either P or R(2. The type of surrogate used (higher-taxa, cross-taxa or subset taxa was the best predictor of P, with the higher-taxa surrogates outperforming all others. The marine habitat was the best predictor of R(2, with particularly low predictability in tropical reefs. Surrogate effectiveness was greatest for higher-taxa surrogates at a <10-km spatial scale, in low-complexity marine habitats such as soft bottoms, and using multivariate-based methods. Comparisons with terrestrial studies in terms of the methods used to study surrogates revealed that marine applications still ignore some problems with several widely used statistical approaches to surrogacy. Our study provides a benchmark for the reliable use of biological surrogates in marine ecosystems, and highlights directions for future development of biological surrogates in predicting biodiversity.

  8. Predicting the distribution of spiral waves from cell properties in a developmental-path model of Dictyostelium pattern formation.

    Directory of Open Access Journals (Sweden)

    Daniel Geberth

    2009-07-01

    Full Text Available The slime mold Dictyostelium discoideum is one of the model systems of biological pattern formation. One of the most successful answers to the challenge of establishing a spiral wave pattern in a colony of homogeneously distributed D. discoideum cells has been the suggestion of a developmental path the cells follow (Lauzeral and coworkers. This is a well-defined change in properties each cell undergoes on a longer time scale than the typical dynamics of the cell. Here we show that this concept leads to an inhomogeneous and systematic spatial distribution of spiral waves, which can be predicted from the distribution of cells on the developmental path. We propose specific experiments for checking whether such systematics are also found in data and thus, indirectly, provide evidence of a developmental path.

  9. Predicting the distribution of intensive poultry farming in Thailand

    OpenAIRE

    Van Boeckel, Thomas P; Thanapongtharm, Weerapong; Robinson, Timothy; D’Aietti, Laura; Gilbert, Marius

    2012-01-01

    Intensification of animal production can be an important factor in the emergence of infectious diseases because changes in production structure influence disease transmission patterns. In 2004 and 2005, Thailand was subject to two highly pathogenic avian influenza epidemic waves and large surveys were conducted of the poultry sector, providing detailed spatial data on various poultry types. This study analysed these data with the aim of establishing the distributions of extensive and intensiv...

  10. Fractal-like Distributions over the Rational Numbers in High-throughput Biological and Clinical Data

    Science.gov (United States)

    Trifonov, Vladimir; Pasqualucci, Laura; Dalla-Favera, Riccardo; Rabadan, Raul

    2011-12-01

    Recent developments in extracting and processing biological and clinical data are allowing quantitative approaches to studying living systems. High-throughput sequencing (HTS), expression profiles, proteomics, and electronic health records (EHR) are some examples of such technologies. Extracting meaningful information from those technologies requires careful analysis of the large volumes of data they produce. In this note, we present a set of fractal-like distributions that commonly appear in the analysis of such data. The first set of examples are drawn from a HTS experiment. Here, the distributions appear as part of the evaluation of the error rate of the sequencing and the identification of tumorogenic genomic alterations. The other examples are obtained from risk factor evaluation and analysis of relative disease prevalence and co-mordbidity as these appear in EHR. The distributions are also relevant to identification of subclonal populations in tumors and the study of quasi-species and intrahost diversity of viral populations.

  11. Biomine: predicting links between biological entities using network models of heterogeneous databases

    Directory of Open Access Journals (Sweden)

    Eronen Lauri

    2012-06-01

    Full Text Available Abstract Background Biological databases contain large amounts of data concerning the functions and associations of genes and proteins. Integration of data from several such databases into a single repository can aid the discovery of previously unknown connections spanning multiple types of relationships and databases. Results Biomine is a system that integrates cross-references from several biological databases into a graph model with multiple types of edges, such as protein interactions, gene-disease associations and gene ontology annotations. Edges are weighted based on their type, reliability, and informativeness. We present Biomine and evaluate its performance in link prediction, where the goal is to predict pairs of nodes that will be connected in the future, based on current data. In particular, we formulate protein interaction prediction and disease gene prioritization tasks as instances of link prediction. The predictions are based on a proximity measure computed on the integrated graph. We consider and experiment with several such measures, and perform a parameter optimization procedure where different edge types are weighted to optimize link prediction accuracy. We also propose a novel method for disease-gene prioritization, defined as finding a subset of candidate genes that cluster together in the graph. We experimentally evaluate Biomine by predicting future annotations in the source databases and prioritizing lists of putative disease genes. Conclusions The experimental results show that Biomine has strong potential for predicting links when a set of selected candidate links is available. The predictions obtained using the entire Biomine dataset are shown to clearly outperform ones obtained using any single source of data alone, when different types of links are suitably weighted. In the gene prioritization task, an established reference set of disease-associated genes is useful, but the results show that under favorable

  12. Prediction of sound transmission loss through multilayered panels by using Gaussian distribution of directional incident energy

    Science.gov (United States)

    Kang; Ih; Kim; Kim

    2000-03-01

    In this study, a new prediction method is suggested for sound transmission loss (STL) of multilayered panels of infinite extent. Conventional methods such as random or field incidence approach often given significant discrepancies in predicting STL of multilayered panels when compared with the experiments. In this paper, appropriate directional distributions of incident energy to predict the STL of multilayered panels are proposed. In order to find a weighting function to represent the directional distribution of incident energy on the wall in a reverberation chamber, numerical simulations by using a ray-tracing technique are carried out. Simulation results reveal that the directional distribution can be approximately expressed by the Gaussian distribution function in terms of the angle of incidence. The Gaussian function is applied to predict the STL of various multilayered panel configurations as well as single panels. The compared results between the measurement and the prediction show good agreements, which validate the proposed Gaussian function approach.

  13. Assessment of subchannel code ASSERT-PV for flow-distribution predictions

    International Nuclear Information System (INIS)

    Nava-Dominguez, A.; Rao, Y.F.; Waddington, G.M.

    2014-01-01

    Highlights: • Assessment of the subchannel code ASSERT-PV 3.2 for the prediction of flow distribution. • Open literature and in-house experimental data to quantify ASSERT-PV predictions. • Model changes assessed against vertical and horizontal flow experiments. • Improvement of flow-distribution predictions under CANDU-relevant conditions. - Abstract: This paper reports an assessment of the recently released subchannel code ASSERT-PV 3.2 for the prediction of flow-distribution in fuel bundles, including subchannel void fraction, quality and mass fluxes. Experimental data from open literature and from in-house tests are used to assess the flow-distribution models in ASSERT-PV 3.2. The prediction statistics using the recommended model set of ASSERT-PV 3.2 are compared to those from previous code versions. Separate-effects sensitivity studies are performed to quantify the contribution of each flow-distribution model change or enhancement to the improvement in flow-distribution prediction. The assessment demonstrates significant improvement in the prediction of flow-distribution in horizontal fuel channels containing CANDU bundles

  14. Assessment of subchannel code ASSERT-PV for flow-distribution predictions

    Energy Technology Data Exchange (ETDEWEB)

    Nava-Dominguez, A., E-mail: navadoma@aecl.ca; Rao, Y.F., E-mail: raoy@aecl.ca; Waddington, G.M., E-mail: waddingg@aecl.ca

    2014-08-15

    Highlights: • Assessment of the subchannel code ASSERT-PV 3.2 for the prediction of flow distribution. • Open literature and in-house experimental data to quantify ASSERT-PV predictions. • Model changes assessed against vertical and horizontal flow experiments. • Improvement of flow-distribution predictions under CANDU-relevant conditions. - Abstract: This paper reports an assessment of the recently released subchannel code ASSERT-PV 3.2 for the prediction of flow-distribution in fuel bundles, including subchannel void fraction, quality and mass fluxes. Experimental data from open literature and from in-house tests are used to assess the flow-distribution models in ASSERT-PV 3.2. The prediction statistics using the recommended model set of ASSERT-PV 3.2 are compared to those from previous code versions. Separate-effects sensitivity studies are performed to quantify the contribution of each flow-distribution model change or enhancement to the improvement in flow-distribution prediction. The assessment demonstrates significant improvement in the prediction of flow-distribution in horizontal fuel channels containing CANDU bundles.

  15. Publication Growth in Biological Sub-Fields: Patterns, Predictability and Sustainability

    Directory of Open Access Journals (Sweden)

    Marco Pautasso

    2012-11-01

    Full Text Available Biologists are producing ever-increasing quantities of papers. The question arises of whether current rates of increase in scientific outputs are sustainable in the long term. I studied this issue using publication data from the Web of Science (1991–2010 for 18 biological sub-fields. In the majority of cases, an exponential regression explains more variation than a linear one in the number of papers published each year as a function of publication year. Exponential growth in publication numbers is clearly not sustainable. About 75% of the variation in publication growth among biological sub-fields over the two studied decades can be predicted by publication data from the first six years. Currently trendy fields such as structural biology, neuroscience and biomaterials cannot be expected to carry on growing at the current pace, because in a few decades they would produce more papers than the whole of biology combined. Synthetic and systems biology are problematic from the point of view of knowledge dissemination, because in these fields more than 80% of existing papers have been published over the last five years. The evidence presented here casts a shadow on how sustainable the recent increase in scientific publications can be in the long term.

  16. Thematic and spatial resolutions affect model-based predictions of tree species distribution.

    Science.gov (United States)

    Liang, Yu; He, Hong S; Fraser, Jacob S; Wu, ZhiWei

    2013-01-01

    Subjective decisions of thematic and spatial resolutions in characterizing environmental heterogeneity may affect the characterizations of spatial pattern and the simulation of occurrence and rate of ecological processes, and in turn, model-based tree species distribution. Thus, this study quantified the importance of thematic and spatial resolutions, and their interaction in predictions of tree species distribution (quantified by species abundance). We investigated how model-predicted species abundances changed and whether tree species with different ecological traits (e.g., seed dispersal distance, competitive capacity) had different responses to varying thematic and spatial resolutions. We used the LANDIS forest landscape model to predict tree species distribution at the landscape scale and designed a series of scenarios with different thematic (different numbers of land types) and spatial resolutions combinations, and then statistically examined the differences of species abundance among these scenarios. Results showed that both thematic and spatial resolutions affected model-based predictions of species distribution, but thematic resolution had a greater effect. Species ecological traits affected the predictions. For species with moderate dispersal distance and relatively abundant seed sources, predicted abundance increased as thematic resolution increased. However, for species with long seeding distance or high shade tolerance, thematic resolution had an inverse effect on predicted abundance. When seed sources and dispersal distance were not limiting, the predicted species abundance increased with spatial resolution and vice versa. Results from this study may provide insights into the choice of thematic and spatial resolutions for model-based predictions of tree species distribution.

  17. Research on Fault Prediction of Distribution Network Based on Large Data

    Directory of Open Access Journals (Sweden)

    Jinglong Zhou

    2017-01-01

    Full Text Available With the continuous development of information technology and the improvement of distribution automation level. Especially, the amount of on-line monitoring and statistical data is increasing, and large data is used data distribution system, describes the technology to collect, data analysis and data processing of the data distribution system. The artificial neural network mining algorithm and the large data are researched in the fault diagnosis and prediction of the distribution network.

  18. Predicting protein-protein interactions from multimodal biological data sources via nonnegative matrix tri-factorization.

    Science.gov (United States)

    Wang, Hua; Huang, Heng; Ding, Chris; Nie, Feiping

    2013-04-01

    Protein interactions are central to all the biological processes and structural scaffolds in living organisms, because they orchestrate a number of cellular processes such as metabolic pathways and immunological recognition. Several high-throughput methods, for example, yeast two-hybrid system and mass spectrometry method, can help determine protein interactions, which, however, suffer from high false-positive rates. Moreover, many protein interactions predicted by one method are not supported by another. Therefore, computational methods are necessary and crucial to complete the interactome expeditiously. In this work, we formulate the problem of predicting protein interactions from a new mathematical perspective--sparse matrix completion, and propose a novel nonnegative matrix factorization (NMF)-based matrix completion approach to predict new protein interactions from existing protein interaction networks. Through using manifold regularization, we further develop our method to integrate different biological data sources, such as protein sequences, gene expressions, protein structure information, etc. Extensive experimental results on four species, Saccharomyces cerevisiae, Drosophila melanogaster, Homo sapiens, and Caenorhabditis elegans, have shown that our new methods outperform related state-of-the-art protein interaction prediction methods.

  19. Predicting volume of distribution with decision tree-based regression methods using predicted tissue:plasma partition coefficients.

    Science.gov (United States)

    Freitas, Alex A; Limbu, Kriti; Ghafourian, Taravat

    2015-01-01

    Volume of distribution is an important pharmacokinetic property that indicates the extent of a drug's distribution in the body tissues. This paper addresses the problem of how to estimate the apparent volume of distribution at steady state (Vss) of chemical compounds in the human body using decision tree-based regression methods from the area of data mining (or machine learning). Hence, the pros and cons of several different types of decision tree-based regression methods have been discussed. The regression methods predict Vss using, as predictive features, both the compounds' molecular descriptors and the compounds' tissue:plasma partition coefficients (Kt:p) - often used in physiologically-based pharmacokinetics. Therefore, this work has assessed whether the data mining-based prediction of Vss can be made more accurate by using as input not only the compounds' molecular descriptors but also (a subset of) their predicted Kt:p values. Comparison of the models that used only molecular descriptors, in particular, the Bagging decision tree (mean fold error of 2.33), with those employing predicted Kt:p values in addition to the molecular descriptors, such as the Bagging decision tree using adipose Kt:p (mean fold error of 2.29), indicated that the use of predicted Kt:p values as descriptors may be beneficial for accurate prediction of Vss using decision trees if prior feature selection is applied. Decision tree based models presented in this work have an accuracy that is reasonable and similar to the accuracy of reported Vss inter-species extrapolations in the literature. The estimation of Vss for new compounds in drug discovery will benefit from methods that are able to integrate large and varied sources of data and flexible non-linear data mining methods such as decision trees, which can produce interpretable models. Graphical AbstractDecision trees for the prediction of tissue partition coefficient and volume of distribution of drugs.

  20. Predicting the distribution of contamination from a chlorinated hydrocarbon release

    Energy Technology Data Exchange (ETDEWEB)

    Lupo, M.J. [K.W. Brown Environmental Services, College Station, TX (United States); Moridis, G.J. [Lawrence Berkeley Laboratory, Berkeley, CA (United States)

    1995-03-01

    The T2VOC model with the T2CG1 conjugate gradient package was used to simulate the motion of a dense chlorinated hydrocarbon plume released from an industrial plant. The release involved thousands of kilograms of trichloroethylene (TCE) and other chemicals that were disposed of onsite over a period of nearly twenty years. After the disposal practice ceased, an elongated plume was discovered. Because much of the plume underlies a developed area, it was of interest to study the migration history of the plume to determine the distribution of the contamination.

  1. Gaze distribution analysis and saliency prediction across age groups.

    Science.gov (United States)

    Krishna, Onkar; Helo, Andrea; Rämä, Pia; Aizawa, Kiyoharu

    2018-01-01

    Knowledge of the human visual system helps to develop better computational models of visual attention. State-of-the-art models have been developed to mimic the visual attention system of young adults that, however, largely ignore the variations that occur with age. In this paper, we investigated how visual scene processing changes with age and we propose an age-adapted framework that helps to develop a computational model that can predict saliency across different age groups. Our analysis uncovers how the explorativeness of an observer varies with age, how well saliency maps of an age group agree with fixation points of observers from the same or different age groups, and how age influences the center bias tendency. We analyzed the eye movement behavior of 82 observers belonging to four age groups while they explored visual scenes. Explorative- ness was quantified in terms of the entropy of a saliency map, and area under the curve (AUC) metrics was used to quantify the agreement analysis and the center bias tendency. Analysis results were used to develop age adapted saliency models. Our results suggest that the proposed age-adapted saliency model outperforms existing saliency models in predicting the regions of interest across age groups.

  2. Zebrafish whole-adult-organism chemogenomics for large-scale predictive and discovery chemical biology.

    Directory of Open Access Journals (Sweden)

    Siew Hong Lam

    2008-07-01

    Full Text Available The ability to perform large-scale, expression-based chemogenomics on whole adult organisms, as in invertebrate models (worm and fly, is highly desirable for a vertebrate model but its feasibility and potential has not been demonstrated. We performed expression-based chemogenomics on the whole adult organism of a vertebrate model, the zebrafish, and demonstrated its potential for large-scale predictive and discovery chemical biology. Focusing on two classes of compounds with wide implications to human health, polycyclic (halogenated aromatic hydrocarbons [P(HAHs] and estrogenic compounds (ECs, we generated robust prediction models that can discriminate compounds of the same class from those of different classes in two large independent experiments. The robust expression signatures led to the identification of biomarkers for potent aryl hydrocarbon receptor (AHR and estrogen receptor (ER agonists, respectively, and were validated in multiple targeted tissues. Knowledge-based data mining of human homologs of zebrafish genes revealed highly conserved chemical-induced biological responses/effects, health risks, and novel biological insights associated with AHR and ER that could be inferred to humans. Thus, our study presents an effective, high-throughput strategy of capturing molecular snapshots of chemical-induced biological states of a whole adult vertebrate that provides information on biomarkers of effects, deregulated signaling pathways, and possible affected biological functions, perturbed physiological systems, and increased health risks. These findings place zebrafish in a strategic position to bridge the wide gap between cell-based and rodent models in chemogenomics research and applications, especially in preclinical drug discovery and toxicology.

  3. Coordinated control of active and reactive power of distribution network with distributed PV cluster via model predictive control

    Science.gov (United States)

    Ji, Yu; Sheng, Wanxing; Jin, Wei; Wu, Ming; Liu, Haitao; Chen, Feng

    2018-02-01

    A coordinated optimal control method of active and reactive power of distribution network with distributed PV cluster based on model predictive control is proposed in this paper. The method divides the control process into long-time scale optimal control and short-time scale optimal control with multi-step optimization. The models are transformed into a second-order cone programming problem due to the non-convex and nonlinear of the optimal models which are hard to be solved. An improved IEEE 33-bus distribution network system is used to analyse the feasibility and the effectiveness of the proposed control method

  4. Interpretation of proton relative biological effectiveness using lesion induction, lesion repair, and cellular dose distribution

    International Nuclear Information System (INIS)

    Paganetti, H.

    2005-01-01

    Phenomenological biophysical models have been successfully used to estimate the relative biological effectiveness (RBE) of ions. The predictive power of these models is limited because they require measured dose-response data that are not necessarily available for all clinically relevant end points. Furthermore, input parameters often lack mechanistic interpretation. In order to link RBE to more fundamental biological parameters we combine the concepts of two well-established biophysical models, i.e., the phenomenological 'track structure' model and the more mechanistic 'lethal lesion/potentially lethal lesion' (LPL) model. We parametrize a relation between RBE, dose homogeneity in the cell nucleus and induction rates for different lesion types. The macroscopic dose-response relationship is described in the LPL model and the microscopic, subcellular, relationship is determined by the local dose deposition pattern. The formalism provides a framework for a mechanistic interpretation of RBE values

  5. The nature and use of prediction skills in a biological computer simulation

    Science.gov (United States)

    Lavoie, Derrick R.; Good, Ron

    The primary goal of this study was to examine the science process skill of prediction using qualitative research methodology. The think-aloud interview, modeled after Ericsson and Simon (1984), let to the identification of 63 program exploration and prediction behaviors.The performance of seven formal and seven concrete operational high-school biology students were videotaped during a three-phase learning sequence on water pollution. Subjects explored the effects of five independent variables on two dependent variables over time using a computer-simulation program. Predictions were made concerning the effect of the independent variables upon dependent variables through time. Subjects were identified according to initial knowledge of the subject matter and success at solving three selected prediction problems.Successful predictors generally had high initial knowledge of the subject matter and were formal operational. Unsuccessful predictors generally had low initial knowledge and were concrete operational. High initial knowledge seemed to be more important to predictive success than stage of Piagetian cognitive development.Successful prediction behaviors involved systematic manipulation of the independent variables, note taking, identification and use of appropriate independent-dependent variable relationships, high interest and motivation, and in general, higher-level thinking skills. Behaviors characteristic of unsuccessful predictors were nonsystematic manipulation of independent variables, lack of motivation and persistence, misconceptions, and the identification and use of inappropriate independent-dependent variable relationships.

  6. [Prediction of potential geographic distribution of Lyme disease in Qinghai province with Maximum Entropy model].

    Science.gov (United States)

    Zhang, Lin; Hou, Xuexia; Liu, Huixin; Liu, Wei; Wan, Kanglin; Hao, Qin

    2016-01-01

    To predict the potential geographic distribution of Lyme disease in Qinghai by using Maximum Entropy model (MaxEnt). The sero-diagnosis data of Lyme disease in 6 counties (Huzhu, Zeku, Tongde, Datong, Qilian and Xunhua) and the environmental and anthropogenic data including altitude, human footprint, normalized difference vegetation index (NDVI) and temperature in Qinghai province since 1990 were collected. By using the data of Huzhu Zeku and Tongde, the prediction of potential distribution of Lyme disease in Qinghai was conducted with MaxEnt. The prediction results were compared with the human sero-prevalence of Lyme disease in Datong, Qilian and Xunhua counties in Qinghai. Three hot spots of Lyme disease were predicted in Qinghai, which were all in the east forest areas. Furthermore, the NDVI showed the most important role in the model prediction, followed by human footprint. Datong, Qilian and Xunhua counties were all in eastern Qinghai. Xunhua was in hot spot areaⅡ, Datong was close to the north of hot spot area Ⅲ, while Qilian with lowest sero-prevalence of Lyme disease was not in the hot spot areas. The data were well modeled in MaxEnt (Area Under Curve=0.980). The actual distribution of Lyme disease in Qinghai was in consistent with the results of the model prediction. MaxEnt could be used in predicting the potential distribution patterns of Lyme disease. The distribution of vegetation and the range and intensity of human activity might be related with Lyme disease distribution.

  7. Synthesis, biological distribution and radiation dosimetry of Te-123m analogues of hexadecenoic acid

    International Nuclear Information System (INIS)

    Basmadjian, G.P.; Ice, R.D.; Mills, S.L.

    1982-01-01

    The synthesis and biological distribution of four Te-123m analogues of hexadecenoic acid in rats, rabbits and dogs were described for use as possible myocardial imaging agents. The heart-to-blood ratios ranged from 0.13 for 3-telluranonadecenoic acid in rats at 5 mins to 6.25 for 18-methyl-17-tellura-9-nonadecenoic acid in dogs at 24 hrs. The biological half-life of the Te-123m labelled fatty acids ranged from 26 to 583 hrs in the hearts of the test animals. These Te-123m fatty acids were retained in the heart longer than radioiodinated fatty acids and have acceptable absorbed doses to the various target organs. (U.K.)

  8. Chromophoric Dissolved Organic Matter across a Marine Distributed Biological Observatory in the Pacific Arctic Region

    Science.gov (United States)

    Berman, S. L.; Frey, K. E.; Shake, K. L.; Cooper, L. W.; Grebmeier, J. M.

    2014-12-01

    Dissolved organic matter (DOM) plays an important role in marine ecosystems as both a carbon source for the microbial food web (and thus a source of CO2 to the atmosphere) and as a light inhibitor in marine environments. The presence of chromophoric dissolved organic matter (CDOM; the optically active portion of total DOM) can have significant controlling effects on transmittance of sunlight through the water column and therefore on primary production as well as the heat balance of the upper ocean. However, CDOM is also susceptible to photochemical degradation, which decreases the flux of solar radiation that is absorbed. Knowledge of the current spatial and temporal distribution of CDOM in marine environments is thus critical for understanding how ongoing and future changes in climate may impact these biological, biogeochemical, and physical processes. We describe the quantity and quality of CDOM along five key productive transects across a developing Distributed Biological Observatory (DBO) in the Pacific Arctic region. The samples were collected onboard the CCGS Sir Wilfred Laurier in July 2013 and 2014. Monitoring of the variability of CDOM along transects of high productivity can provide important insights into biological and biogeochemical cycling across the region. Our analyses include overall concentrations of CDOM, as well as proxy information such as molecular weight, lability, and source (i.e., autochthonous vs. allochthonous) of organic matter. We utilize these field observations to compare with satellite-derived CDOM concentrations determined from the Aqua MODIS satellite platform, which ultimately provides a spatially and temporally continuous synoptic view of CDOM concentrations throughout the region. Examining the current relationships among CDOM, sea ice variability, biological productivity, and biogeochemical cycling in the Pacific Arctic region will likely provide key insights for how ecosystems throughout the region will respond in future

  9. An investigation into the population abundance distribution of mRNAs, proteins, and metabolites in biological systems.

    Science.gov (United States)

    Lu, Chuan; King, Ross D

    2009-08-15

    Distribution analysis is one of the most basic forms of statistical analysis. Thanks to improved analytical methods, accurate and extensive quantitative measurements can now be made of the mRNA, protein and metabolite from biological systems. Here, we report a large-scale analysis of the population abundance distributions of the transcriptomes, proteomes and metabolomes from varied biological systems. We compared the observed empirical distributions with a number of distributions: power law, lognormal, loglogistic, loggamma, right Pareto-lognormal (PLN) and double PLN (dPLN). The best-fit for mRNA, protein and metabolite population abundance distributions was found to be the dPLN. This distribution behaves like a lognormal distribution around the centre, and like a power law distribution in the tails. To better understand the cause of this observed distribution, we explored a simple stochastic model based on geometric Brownian motion. The distribution indicates that multiplicative effects are causally dominant in biological systems. We speculate that these effects arise from chemical reactions: the central-limit theorem then explains the central lognormal, and a number of possible mechanisms could explain the long tails: positive feedback, network topology, etc. Many of the components in the central lognormal parts of the empirical distributions are unidentified and/or have unknown function. This indicates that much more biology awaits discovery.

  10. Evaluation of Airborne Remote Sensing Techniques for Predicting the Distribution of Energetic Compounds on Impact Areas

    National Research Council Canada - National Science Library

    Graves, Mark R; Dove, Linda P; Jenkins, Thomas F; Bigl, Susan; Walsh, Marianne E; Hewitt, Alan D; Lambert, Dennis; Perron, Nancy; Ramsey, Charles; Gamey, Jeff; Beard, Les; Doll, William E; Magoun, Dale

    2007-01-01

    .... Remote sensing and geographic information system (GIS) technologies were utilized to assist in the development of enhanced sampling strategies to better predict the landscape-scale distribution of energetic compounds...

  11. Diversity of Pyrrolizidine Alkaloids in the Boraginaceae Structures, Distribution, and Biological Properties

    Directory of Open Access Journals (Sweden)

    Assem El-Shazly

    2014-04-01

    Full Text Available Among the diversity of secondary metabolites which are produced by plants as means of defence against herbivores and microbes, pyrrolizidine alkaloids (PAs are common in Boraginaceae, Asteraceae and some other plant families. Pyrrolizidine alkaloids are infamous as toxic compounds which can alkylate DNA und thus cause mutations and even cancer in herbivores and humans. Almost all genera of the family Boraginaceae synthesize and store this type of alkaloids. This review reports the available information on the present status (literature up to early 2014 of the pyrrolizidine alkaloids in the Boraginaceae and summarizes the topics structure, distribution, chemistry, chemotaxonomic significance, and biological properties.

  12. Exploitation of complex network topology for link prediction in biological interactomes

    KAUST Repository

    Alanis Lobato, Gregorio

    2014-06-01

    The network representation of the interactions between proteins and genes allows for a holistic perspective of the complex machinery underlying the living cell. However, the large number of interacting entities within the cell makes network construction a daunting and arduous task, prone to errors and missing information. Fortunately, the structure of biological networks is not different from that of other complex systems, such as social networks, the world-wide web or power grids, for which growth models have been proposed to better understand their structure and function. This means that we can design tools based on these models in order to exploit the topology of biological interactomes with the aim to construct more complete and reliable maps of the cell. In this work, we propose three novel and powerful approaches for the prediction of interactions in biological networks and conclude that it is possible to mine the topology of these complex system representations and produce reliable and biologically meaningful information that enriches the datasets to which we have access today.

  13. Systems-based biological concordance and predictive reproducibility of gene set discovery methods in cardiovascular disease.

    Science.gov (United States)

    Azuaje, Francisco; Zheng, Huiru; Camargo, Anyela; Wang, Haiying

    2011-08-01

    The discovery of novel disease biomarkers is a crucial challenge for translational bioinformatics. Demonstration of both their classification power and reproducibility across independent datasets are essential requirements to assess their potential clinical relevance. Small datasets and multiplicity of putative biomarker sets may explain lack of predictive reproducibility. Studies based on pathway-driven discovery approaches have suggested that, despite such discrepancies, the resulting putative biomarkers tend to be implicated in common biological processes. Investigations of this problem have been mainly focused on datasets derived from cancer research. We investigated the predictive and functional concordance of five methods for discovering putative biomarkers in four independently-generated datasets from the cardiovascular disease domain. A diversity of biosignatures was identified by the different methods. However, we found strong biological process concordance between them, especially in the case of methods based on gene set analysis. With a few exceptions, we observed lack of classification reproducibility using independent datasets. Partial overlaps between our putative sets of biomarkers and the primary studies exist. Despite the observed limitations, pathway-driven or gene set analysis can predict potentially novel biomarkers and can jointly point to biomedically-relevant underlying molecular mechanisms. Copyright © 2011 Elsevier Inc. All rights reserved.

  14. Novel non-invasive biological predictive index for liver fibrosis in hepatitis C virus genotype 4 patients

    Science.gov (United States)

    Khattab, Mahmoud; Sakr, Mohamed Amin; Fattah, Mohamed Abdel; Mousa, Youssef; Soliman, Elwy; Breedy, Ashraf; Fathi, Mona; Gaber, Salwa; Altaweil, Ahmed; Osman, Ashraf; Hassouna, Ahmed; Motawea, Ibrahim

    2016-01-01

    AIM To investigate the diagnostic ability of a non-invasive biological marker to predict liver fibrosis in hepatitis C genotype 4 patients with high accuracy. METHODS A cohort of 332 patients infected with hepatitis C genotype 4 was included in this cross-sectional study. Fasting plasma glucose, insulin, C-peptide, and angiotensin-converting enzyme serum levels were measured. Insulin resistance was mathematically calculated using the homeostasis model of insulin resistance (HOMA-IR). RESULTS Fibrosis stages were distributed based on Metavir score as follows: F0 = 43, F1 = 136, F2 = 64, F3 = 45 and F4 = 44. Statistical analysis relied upon reclassification of fibrosis stages into mild fibrosis (F0-F) = 179, moderate fibrosis (F2) = 64, and advanced fibrosis (F3-F4) = 89. Univariate analysis indicated that age, log aspartate amino transaminase, log HOMA-IR and log platelet count were independent predictors of liver fibrosis stage (P < 0.0001). A stepwise multivariate discriminant functional analysis was used to drive a discriminative model for liver fibrosis. Our index used cut-off values of ≥ 0.86 and ≤ -0.31 to diagnose advanced and mild fibrosis, respectively, with receiving operating characteristics of 0.91 and 0.88, respectively. The sensitivity, specificity, positive predictive value, negative predictive value and positive likelihood ratio were: 73%, 91%, 75%, 90% and 8.0 respectively for advanced fibrosis, and 67%, 88%, 84%, 70% and 4.9, respectively, for mild fibrosis. CONCLUSION Our predictive model is easily available and reproducible, and predicted liver fibrosis with acceptable accuracy. PMID:27917265

  15. Novel non-invasive biological predictive index for liver fibrosis in hepatitis C virus genotype 4 patients.

    Science.gov (United States)

    Khattab, Mahmoud; Sakr, Mohamed Amin; Fattah, Mohamed Abdel; Mousa, Youssef; Soliman, Elwy; Breedy, Ashraf; Fathi, Mona; Gaber, Salwa; Altaweil, Ahmed; Osman, Ashraf; Hassouna, Ahmed; Motawea, Ibrahim

    2016-11-18

    To investigate the diagnostic ability of a non-invasive biological marker to predict liver fibrosis in hepatitis C genotype 4 patients with high accuracy. A cohort of 332 patients infected with hepatitis C genotype 4 was included in this cross-sectional study. Fasting plasma glucose, insulin, C-peptide, and angiotensin-converting enzyme serum levels were measured. Insulin resistance was mathematically calculated using the homeostasis model of insulin resistance (HOMA-IR). Fibrosis stages were distributed based on Metavir score as follows: F0 = 43, F1 = 136, F2 = 64, F3 = 45 and F4 = 44. Statistical analysis relied upon reclassification of fibrosis stages into mild fibrosis (F0-F) = 179, moderate fibrosis (F2) = 64, and advanced fibrosis (F3-F4) = 89. Univariate analysis indicated that age, log aspartate amino transaminase, log HOMA-IR and log platelet count were independent predictors of liver fibrosis stage ( P < 0.0001). A stepwise multivariate discriminant functional analysis was used to drive a discriminative model for liver fibrosis. Our index used cut-off values of ≥ 0.86 and ≤ -0.31 to diagnose advanced and mild fibrosis, respectively, with receiving operating characteristics of 0.91 and 0.88, respectively. The sensitivity, specificity, positive predictive value, negative predictive value and positive likelihood ratio were: 73%, 91%, 75%, 90% and 8.0 respectively for advanced fibrosis, and 67%, 88%, 84%, 70% and 4.9, respectively, for mild fibrosis. Our predictive model is easily available and reproducible, and predicted liver fibrosis with acceptable accuracy.

  16. Functional knowledge transfer for high-accuracy prediction of under-studied biological processes.

    Directory of Open Access Journals (Sweden)

    Christopher Y Park

    Full Text Available A key challenge in genetics is identifying the functional roles of genes in pathways. Numerous functional genomics techniques (e.g. machine learning that predict protein function have been developed to address this question. These methods generally build from existing annotations of genes to pathways and thus are often unable to identify additional genes participating in processes that are not already well studied. Many of these processes are well studied in some organism, but not necessarily in an investigator's organism of interest. Sequence-based search methods (e.g. BLAST have been used to transfer such annotation information between organisms. We demonstrate that functional genomics can complement traditional sequence similarity to improve the transfer of gene annotations between organisms. Our method transfers annotations only when functionally appropriate as determined by genomic data and can be used with any prediction algorithm to combine transferred gene function knowledge with organism-specific high-throughput data to enable accurate function prediction. We show that diverse state-of-art machine learning algorithms leveraging functional knowledge transfer (FKT dramatically improve their accuracy in predicting gene-pathway membership, particularly for processes with little experimental knowledge in an organism. We also show that our method compares favorably to annotation transfer by sequence similarity. Next, we deploy FKT with state-of-the-art SVM classifier to predict novel genes to 11,000 biological processes across six diverse organisms and expand the coverage of accurate function predictions to processes that are often ignored because of a dearth of annotated genes in an organism. Finally, we perform in vivo experimental investigation in Danio rerio and confirm the regulatory role of our top predicted novel gene, wnt5b, in leftward cell migration during heart development. FKT is immediately applicable to many bioinformatics

  17. An Extrapolation of a Radical Equation More Accurately Predicts Shelf Life of Frozen Biological Matrices.

    Science.gov (United States)

    De Vore, Karl W; Fatahi, Nadia M; Sass, John E

    2016-08-01

    Arrhenius modeling of analyte recovery at increased temperatures to predict long-term colder storage stability of biological raw materials, reagents, calibrators, and controls is standard practice in the diagnostics industry. Predicting subzero temperature stability using the same practice is frequently criticized but nevertheless heavily relied upon. We compared the ability to predict analyte recovery during frozen storage using 3 separate strategies: traditional accelerated studies with Arrhenius modeling, and extrapolation of recovery at 20% of shelf life using either ordinary least squares or a radical equation y = B1x(0.5) + B0. Computer simulations were performed to establish equivalence of statistical power to discern the expected changes during frozen storage or accelerated stress. This was followed by actual predictive and follow-up confirmatory testing of 12 chemistry and immunoassay analytes. Linear extrapolations tended to be the most conservative in the predicted percent recovery, reducing customer and patient risk. However, the majority of analytes followed a rate of change that slowed over time, which was fit best to a radical equation of the form y = B1x(0.5) + B0. Other evidence strongly suggested that the slowing of the rate was not due to higher-order kinetics, but to changes in the matrix during storage. Predicting shelf life of frozen products through extrapolation of early initial real-time storage analyte recovery should be considered the most accurate method. Although in this study the time required for a prediction was longer than a typical accelerated testing protocol, there are less potential sources of error, reduced costs, and a lower expenditure of resources. © 2016 American Association for Clinical Chemistry.

  18. Predictive models of threatened plant species distribution in the Iberian arid south-east

    OpenAIRE

    Benito, Blas M.

    2013-01-01

    Poster on the distribution of three rare, endemic and endangered annual plants of arid zones in the south-eastern Iberian peninsula. Presented in the workshop "Predictive Modelling of Species Distribution: New Tools for the XXI Century (Baeza, Spain, november 2005).

  19. On distributed model predictive control for vehicle platooning with a recursive feasibility guarantee

    NARCIS (Netherlands)

    Shi, Shengling; Lazar, Mircea

    2017-01-01

    This paper proposes a distributed model predictive control algorithm for vehicle platooning and more generally networked systems in a chain structure. The distributed models of the vehicle platoon are coupled through the input of the preceding vehicles. Using the principles of robust model

  20. Prediction of monthly average global solar radiation based on statistical distribution of clearness index

    International Nuclear Information System (INIS)

    Ayodele, T.R.; Ogunjuyigbe, A.S.O.

    2015-01-01

    In this paper, probability distribution of clearness index is proposed for the prediction of global solar radiation. First, the clearness index is obtained from the past data of global solar radiation, then, the parameters of the appropriate distribution that best fit the clearness index are determined. The global solar radiation is thereafter predicted from the clearness index using inverse transformation of the cumulative distribution function. To validate the proposed method, eight years global solar radiation data (2000–2007) of Ibadan, Nigeria are used to determine the parameters of appropriate probability distribution for clearness index. The calculated parameters are then used to predict the future monthly average global solar radiation for the following year (2008). The predicted values are compared with the measured values using four statistical tests: the Root Mean Square Error (RMSE), MAE (Mean Absolute Error), MAPE (Mean Absolute Percentage Error) and the coefficient of determination (R"2). The proposed method is also compared to the existing regression models. The results show that logistic distribution provides the best fit for clearness index of Ibadan and the proposed method is effective in predicting the monthly average global solar radiation with overall RMSE of 0.383 MJ/m"2/day, MAE of 0.295 MJ/m"2/day, MAPE of 2% and R"2 of 0.967. - Highlights: • Distribution of clearnes index is proposed for prediction of global solar radiation. • The clearness index is obtained from the past data of global solar radiation. • The parameters of distribution that best fit the clearness index are determined. • Solar radiation is predicted from the clearness index using inverse transformation. • The method is effective in predicting the monthly average global solar radiation.

  1. Genomic prediction unifies animal and plant breeding programs to form platforms for biological discovery

    DEFF Research Database (Denmark)

    Hickey, John M.; Chiurugwi, Tinashe; Mackay, Ian

    2017-01-01

    The rate of annual yield increases for major staple crops must more than double relative to current levels in order to feed a predicted global population of 9 billion by 2050. Controlled hybridization and selective breeding have been used for centuries to adapt plant and animal species for human...... that unifies breeding approaches, biological discovery, and tools and methods. Here we compare and contrast some animal and plant breeding approaches to make a case for bringing the two together through the application of genomic selection. We propose a strategy for the use of genomic selection as a unifying...... use. However, achieving higher, sustainable rates of improvement in yields in various species will require renewed genetic interventions and dramatic improvement of agricultural practices. Genomic prediction of breeding values has the potential to improve selection, reduce costs and provide a platform...

  2. Genomic prediction unifies animal and plant breeding programs to form platforms for biological discovery.

    Science.gov (United States)

    Hickey, John M; Chiurugwi, Tinashe; Mackay, Ian; Powell, Wayne

    2017-08-30

    The rate of annual yield increases for major staple crops must more than double relative to current levels in order to feed a predicted global population of 9 billion by 2050. Controlled hybridization and selective breeding have been used for centuries to adapt plant and animal species for human use. However, achieving higher, sustainable rates of improvement in yields in various species will require renewed genetic interventions and dramatic improvement of agricultural practices. Genomic prediction of breeding values has the potential to improve selection, reduce costs and provide a platform that unifies breeding approaches, biological discovery, and tools and methods. Here we compare and contrast some animal and plant breeding approaches to make a case for bringing the two together through the application of genomic selection. We propose a strategy for the use of genomic selection as a unifying approach to deliver innovative 'step changes' in the rate of genetic gain at scale.

  3. Towards a Universal Biology: Is the Origin and Evolution of Life Predictable?

    Science.gov (United States)

    Rothschild, Lynn J.

    2017-01-01

    The origin and evolution of life seems an unpredictable oddity, based on the quirks of contingency. Celebrated by the late Stephen Jay Gould in several books, "evolution by contingency" has all the adventure of a thriller, but lacks the predictive power of the physical sciences. Not necessarily so, replied Simon Conway Morris, for convergence reassures us that certain evolutionary responses are replicable. The outcome of this debate is critical to Astrobiology. How can we understand where we came from on Earth without prophesy? Further, we cannot design a rational strategy for the search for life elsewhere - or to understand what the future will hold for life on Earth and beyond - without extrapolating from pre-biotic chemistry and evolution. There are several indirect approaches to understanding, and thus describing, what life must be. These include philosophical approaches to defining life (is there even a satisfactory definition of life?), using what we know of physics, chemistry and life to imagine alternate scenarios, using different approaches that life takes as pseudoreplicates (e.g., ribosomal vs non-ribosomal protein synthesis), and experimental approaches to understand the art of the possible. Given that: (1) Life is a process based on physical components rather than simply an object; (2). Life is likely based on organic carbon and needs a solvent for chemistry, most likely water, and (3) Looking for convergence in terrestrial evolution we can predict certain tendencies, if not quite "laws", that provide predictive power. Biological history must obey the laws of physics and chemistry, the principles of natural selection, the constraints of an evolutionary past, genetics, and developmental biology. This amalgam creates a surprising amount of predictive power in the broad outline. Critical is the apparent prevalence of organic chemistry, and uniformity in the universe of the laws of chemistry and physics. Instructive is the widespread occurrence of

  4. Predicting fundamental and realized distributions based on thermal niche: A case study of a freshwater turtle

    Science.gov (United States)

    Rodrigues, João Fabrício Mota; Coelho, Marco Túlio Pacheco; Ribeiro, Bruno R.

    2018-04-01

    Species distribution models (SDM) have been broadly used in ecology to address theoretical and practical problems. Currently, there are two main approaches to generate SDMs: (i) correlative, which is based on species occurrences and environmental predictor layers and (ii) process-based models, which are constructed based on species' functional traits and physiological tolerances. The distributions estimated by each approach are based on different components of species niche. Predictions of correlative models approach species realized niches, while predictions of process-based are more akin to species fundamental niche. Here, we integrated the predictions of fundamental and realized distributions of the freshwater turtle Trachemys dorbigni. Fundamental distribution was estimated using data of T. dorbigni's egg incubation temperature, and realized distribution was estimated using species occurrence records. Both types of distributions were estimated using the same regression approaches (logistic regression and support vector machines), both considering macroclimatic and microclimatic temperatures. The realized distribution of T. dorbigni was generally nested in its fundamental distribution reinforcing theoretical assumptions that the species' realized niche is a subset of its fundamental niche. Both modelling algorithms produced similar results but microtemperature generated better results than macrotemperature for the incubation model. Finally, our results reinforce the conclusion that species realized distributions are constrained by other factors other than just thermal tolerances.

  5. A hybrid approach to advancing quantitative prediction of tissue distribution of basic drugs in human

    International Nuclear Information System (INIS)

    Poulin, Patrick; Ekins, Sean; Theil, Frank-Peter

    2011-01-01

    A general toxicity of basic drugs is related to phospholipidosis in tissues. Therefore, it is essential to predict the tissue distribution of basic drugs to facilitate an initial estimate of that toxicity. The objective of the present study was to further assess the original prediction method that consisted of using the binding to red blood cells measured in vitro for the unbound drug (RBCu) as a surrogate for tissue distribution, by correlating it to unbound tissue:plasma partition coefficients (Kpu) of several tissues, and finally to predict volume of distribution at steady-state (V ss ) in humans under in vivo conditions. This correlation method demonstrated inaccurate predictions of V ss for particular basic drugs that did not follow the original correlation principle. Therefore, the novelty of this study is to provide clarity on the actual hypotheses to identify i) the impact of pharmacological mode of action on the generic correlation of RBCu-Kpu, ii) additional mechanisms of tissue distribution for the outlier drugs, iii) molecular features and properties that differentiate compounds as outliers in the original correlation analysis in order to facilitate its applicability domain alongside the properties already used so far, and finally iv) to present a novel and refined correlation method that is superior to what has been previously published for the prediction of human V ss of basic drugs. Applying a refined correlation method after identifying outliers would facilitate the prediction of more accurate distribution parameters as key inputs used in physiologically based pharmacokinetic (PBPK) and phospholipidosis models.

  6. [Effects of sampling plot number on tree species distribution prediction under climate change].

    Science.gov (United States)

    Liang, Yu; He, Hong-Shi; Wu, Zhi-Wei; Li, Xiao-Na; Luo, Xu

    2013-05-01

    Based on the neutral landscapes under different degrees of landscape fragmentation, this paper studied the effects of sampling plot number on the prediction of tree species distribution at landscape scale under climate change. The tree species distribution was predicted by the coupled modeling approach which linked an ecosystem process model with a forest landscape model, and three contingent scenarios and one reference scenario of sampling plot numbers were assumed. The differences between the three scenarios and the reference scenario under different degrees of landscape fragmentation were tested. The results indicated that the effects of sampling plot number on the prediction of tree species distribution depended on the tree species life history attributes. For the generalist species, the prediction of their distribution at landscape scale needed more plots. Except for the extreme specialist, landscape fragmentation degree also affected the effects of sampling plot number on the prediction. With the increase of simulation period, the effects of sampling plot number on the prediction of tree species distribution at landscape scale could be changed. For generalist species, more plots are needed for the long-term simulation.

  7. On-line test of power distribution prediction system for boiling water reactors

    International Nuclear Information System (INIS)

    Nishizawa, Y.; Kiguchi, T.; Kobayashi, S.; Takumi, K.; Tanaka, H.; Tsutsumi, R.; Yokomi, M.

    1982-01-01

    A power distribution prediction system for boiling water reactors has been developed and its on-line performance test has proceeded at an operating commercial reactor. This system predicts the power distribution or thermal margin in advance of control rod operations and core flow rate change. This system consists of an on-line computer system, an operator's console with a color cathode-ray tube, and plant data input devices. The main functions of this system are present power distribution monitoring, power distribution prediction, and power-up trajectory prediction. The calculation method is based on a simplified nuclear thermal-hydraulic calculation, which is combined with a method of model identification to the actual reactor core state. It has been ascertained by the on-line test that the predicted power distribution (readings of traversing in-core probe) agrees with the measured data within 6% root-mean-square. The computing time required for one prediction calculation step is less than or equal to 1.5 min by an HIDIC-80 on-line computer

  8. Prediction of vertical distribution and ambient development temperature of Baltic cod, Gadus morhua L., eggs

    DEFF Research Database (Denmark)

    Wieland, Kai; Jarre, Astrid

    1997-01-01

    An artificial neural network (ANN) model was established to predict the vertical distribution of Baltic cod eggs. Data from vertical distribution sampling in the Bornholm Basin over the period 1986-1995 were used to train and test the network, while data sets from sampling in 1996 were used...... for validation. The model explained 82% of the variance between observed and predicted relative frequencies of occurrence of the eggs in relation to salinity, temperature and oxygen concentration; The ANN fitted all observations satisfactorily except for one sampling date, where an exceptional hydrographic...... situation was observed. Mean ambient temperatures, calculated from the predicted vertical distributions of the eggs and used for the computation of egg developmental times, were overestimated by 0.05 degrees C on average. This corresponds to an error in prediction of egg developmental time of less than 1%...

  9. Predicting dihedral angle probability distributions for protein coil residues from primary sequence using neural networks

    DEFF Research Database (Denmark)

    Helles, Glennie; Fonseca, Rasmus

    2009-01-01

    residue in the input-window. The trained neural network shows a significant improvement (4-68%) in predicting the most probable bin (covering a 30°×30° area of the dihedral angle space) for all amino acids in the data set compared to first order statistics. An accuracy comparable to that of secondary...... seem to have a significant influence on the dihedral angles adopted by the individual amino acids in coil segments. In this work we attempt to predict a probability distribution of these dihedral angles based on the flanking residues. While attempts to predict dihedral angles of coil segments have been...... done previously, none have, to our knowledge, presented comparable results for the probability distribution of dihedral angles. Results: In this paper we develop an artificial neural network that uses an input-window of amino acids to predict a dihedral angle probability distribution for the middle...

  10. DNA methylation-based measures of biological age: meta-analysis predicting time to death

    Science.gov (United States)

    Chen, Brian H.; Marioni, Riccardo E.; Colicino, Elena; Peters, Marjolein J.; Ward-Caviness, Cavin K.; Tsai, Pei-Chien; Roetker, Nicholas S.; Just, Allan C.; Demerath, Ellen W.; Guan, Weihua; Bressler, Jan; Fornage, Myriam; Studenski, Stephanie; Vandiver, Amy R.; Moore, Ann Zenobia; Tanaka, Toshiko; Kiel, Douglas P.; Liang, Liming; Vokonas, Pantel; Schwartz, Joel; Lunetta, Kathryn L.; Murabito, Joanne M.; Bandinelli, Stefania; Hernandez, Dena G.; Melzer, David; Nalls, Michael; Pilling, Luke C.; Price, Timothy R.; Singleton, Andrew B.; Gieger, Christian; Holle, Rolf; Kretschmer, Anja; Kronenberg, Florian; Kunze, Sonja; Linseisen, Jakob; Meisinger, Christine; Rathmann, Wolfgang; Waldenberger, Melanie; Visscher, Peter M.; Shah, Sonia; Wray, Naomi R.; McRae, Allan F.; Franco, Oscar H.; Hofman, Albert; Uitterlinden, André G.; Absher, Devin; Assimes, Themistocles; Levine, Morgan E.; Lu, Ake T.; Tsao, Philip S.; Hou, Lifang; Manson, JoAnn E.; Carty, Cara L.; LaCroix, Andrea Z.; Reiner, Alexander P.; Spector, Tim D.; Feinberg, Andrew P.; Levy, Daniel; Baccarelli, Andrea; van Meurs, Joyce; Bell, Jordana T.; Peters, Annette; Deary, Ian J.; Pankow, James S.; Ferrucci, Luigi; Horvath, Steve

    2016-01-01

    Estimates of biological age based on DNA methylation patterns, often referred to as “epigenetic age”, “DNAm age”, have been shown to be robust biomarkers of age in humans. We previously demonstrated that independent of chronological age, epigenetic age assessed in blood predicted all-cause mortality in four human cohorts. Here, we expanded our original observation to 13 different cohorts for a total sample size of 13,089 individuals, including three racial/ethnic groups. In addition, we examined whether incorporating information on blood cell composition into the epigenetic age metrics improves their predictive power for mortality. All considered measures of epigenetic age acceleration were predictive of mortality (p≤8.2×10−9), independent of chronological age, even after adjusting for additional risk factors (p<5.4×10−4), and within the racial/ethnic groups that we examined (non-Hispanic whites, Hispanics, African Americans). Epigenetic age estimates that incorporated information on blood cell composition led to the smallest p-values for time to death (p=7.5×10−43). Overall, this study a) strengthens the evidence that epigenetic age predicts all-cause mortality above and beyond chronological age and traditional risk factors, and b) demonstrates that epigenetic age estimates that incorporate information on blood cell counts lead to highly significant associations with all-cause mortality. PMID:27690265

  11. Semi-supervised drug-protein interaction prediction from heterogeneous biological spaces.

    Science.gov (United States)

    Xia, Zheng; Wu, Ling-Yun; Zhou, Xiaobo; Wong, Stephen T C

    2010-09-13

    Predicting drug-protein interactions from heterogeneous biological data sources is a key step for in silico drug discovery. The difficulty of this prediction task lies in the rarity of known drug-protein interactions and myriad unknown interactions to be predicted. To meet this challenge, a manifold regularization semi-supervised learning method is presented to tackle this issue by using labeled and unlabeled information which often generates better results than using the labeled data alone. Furthermore, our semi-supervised learning method integrates known drug-protein interaction network information as well as chemical structure and genomic sequence data. Using the proposed method, we predicted certain drug-protein interactions on the enzyme, ion channel, GPCRs, and nuclear receptor data sets. Some of them are confirmed by the latest publicly available drug targets databases such as KEGG. We report encouraging results of using our method for drug-protein interaction network reconstruction which may shed light on the molecular interaction inference and new uses of marketed drugs.

  12. Ventilation versus biology: What is the controlling mechanism of nitrous oxide distribution in the North Atlantic?

    Science.gov (United States)

    Paz, Mercedes; García-Ibáñez, Maribel I.; Steinfeldt, Reiner; Ríos, Aida F.; Pérez, Fiz F.

    2017-04-01

    The extent to which water mass mixing and ocean ventilation contribute to nitrous oxide (N2O) distribution at the scale of oceanic basins is poorly constrained. We used novel N2O and chlorofluorocarbon measurements along with multiparameter water mass analysis to evaluate the impact of water mass mixing and Atlantic Meridional Overturning Circulation (AMOC) on N2O distribution along the Observatoire de la variabilité interannuelle et décennale en Atlantique Nord (OVIDE) section, extending from Portugal to Greenland. The biological N2O production has a stronger impact on the observed N2O concentrations in the water masses traveling northward in the upper limb of the AMOC than those in recently ventilated cold water masses in the lower limb, where N2O concentrations reflect the colder temperatures. The high N2O tongue, with concentrations as high as 16 nmol kg-1, propagates above the isopycnal surface delimiting the upper and lower AMOC limbs, which extends from the eastern North Atlantic Basin to the Iceland Basin and coincides with the maximum N2O production rates. Water mixing and basin-scale remineralization account for 72% of variation in the observed distribution of N2O. The mixing-corrected stoichiometric ratio N2O:O2 for the North Atlantic Basin of 0.06 nmol/μmol is in agreement with ratios of N2O:O2 for local N2O anomalies, suggesting than up to 28% of N2O production occurs in the temperate and subpolar Atlantic, an overlooked region for N2O cycling. Overall, our results highlight the importance of taking into account mixing, O2 undersaturation when water masses are formed and the increasing atmospheric N2O concentrations when parameterizing N2O:O2 and biological N2O production in the global oceans.

  13. Systems biological approach of molecular descriptors connectivity: optimal descriptors for oral bioavailability prediction.

    Science.gov (United States)

    Ahmed, Shiek S S J; Ramakrishnan, V

    2012-01-01

    Poor oral bioavailability is an important parameter accounting for the failure of the drug candidates. Approximately, 50% of developing drugs fail because of unfavorable oral bioavailability. In silico prediction of oral bioavailability (%F) based on physiochemical properties are highly needed. Although many computational models have been developed to predict oral bioavailability, their accuracy remains low with a significant number of false positives. In this study, we present an oral bioavailability model based on systems biological approach, using a machine learning algorithm coupled with an optimal discriminative set of physiochemical properties. The models were developed based on computationally derived 247 physicochemical descriptors from 2279 molecules, among which 969, 605 and 705 molecules were corresponds to oral bioavailability, intestinal absorption (HIA) and caco-2 permeability data set, respectively. The partial least squares discriminate analysis showed 49 descriptors of HIA and 50 descriptors of caco-2 are the major contributing descriptors in classifying into groups. Of these descriptors, 47 descriptors were commonly associated to HIA and caco-2, which suggests to play a vital role in classifying oral bioavailability. To determine the best machine learning algorithm, 21 classifiers were compared using a bioavailability data set of 969 molecules with 47 descriptors. Each molecule in the data set was represented by a set of 47 physiochemical properties with the functional relevance labeled as (+bioavailability/-bioavailability) to indicate good-bioavailability/poor-bioavailability molecules. The best-performing algorithm was the logistic algorithm. The correlation based feature selection (CFS) algorithm was implemented, which confirms that these 47 descriptors are the fundamental descriptors for oral bioavailability prediction. The logistic algorithm with 47 selected descriptors correctly predicted the oral bioavailability, with a predictive accuracy

  14. Depressive symptoms predict head and neck cancer survival: Examining plausible behavioral and biological pathways.

    Science.gov (United States)

    Zimmaro, Lauren A; Sephton, Sandra E; Siwik, Chelsea J; Phillips, Kala M; Rebholz, Whitney N; Kraemer, Helena C; Giese-Davis, Janine; Wilson, Liz; Bumpous, Jeffrey M; Cash, Elizabeth D

    2018-03-01

    Head and neck cancers are associated with high rates of depression, which may increase the risk for poorer immediate and long-term outcomes. Here it was hypothesized that greater depressive symptoms would predict earlier mortality, and behavioral (treatment interruption) and biological (treatment response) mediators were examined. Patients (n = 134) reported depressive symptomatology at treatment planning. Clinical data were reviewed at the 2-year follow-up. Greater depressive symptoms were associated with significantly shorter survival (hazard ratio, 0.868; 95% confidence interval [CI], 0.819-0.921; P ratio, 0.865; 95% CI, 0.774-0.966; P = .010), and poorer treatment response (odds ratio, 0.879; 95% CI, 0.803-0.963; P = .005). The poorer treatment response partially explained the depression-survival relation. Other known prognostic indicators did not challenge these results. Depressive symptoms at the time of treatment planning predict overall 2-year mortality. Effects are partly influenced by the treatment response. Depression screening and intervention may be beneficial. Future studies should examine parallel biological pathways linking depression to cancer survival, including endocrine disruption and inflammation. Cancer 2018;124:1053-60. © 2018 American Cancer Society. © 2018 American Cancer Society.

  15. Accumulating Data to Optimally Predict Obesity Treatment (ADOPT): Recommendations from the Biological Domain.

    Science.gov (United States)

    Rosenbaum, Michael; Agurs-Collins, Tanya; Bray, Molly S; Hall, Kevin D; Hopkins, Mark; Laughlin, Maren; MacLean, Paul S; Maruvada, Padma; Savage, Cary R; Small, Dana M; Stoeckel, Luke

    2018-04-01

    The responses to behavioral, pharmacological, or surgical obesity treatments are highly individualized. The Accumulating Data to Optimally Predict obesity Treatment (ADOPT) project provides a framework for how obesity researchers, working collectively, can generate the evidence base needed to guide the development of tailored, and potentially more effective, strategies for obesity treatment. The objective of the ADOPT biological domain subgroup is to create a list of high-priority biological measures for weight-loss studies that will advance the understanding of individual variability in response to adult obesity treatments. This list includes measures of body composition, energy homeostasis (energy intake and output), brain structure and function, and biomarkers, as well as biobanking procedures, which could feasibly be included in most, if not all, studies of obesity treatment. The recommended high-priority measures are selected to balance needs for sensitivity, specificity, and/or comprehensiveness with feasibility to achieve a commonality of usage and increase the breadth and impact of obesity research. The accumulation of data on key biological factors, along with behavioral, psychosocial, and environmental factors, can generate a more precise description of the interplay and synergy among them and their impact on treatment responses, which can ultimately inform the design and delivery of effective, tailored obesity treatments. © 2018 The Obesity Society.

  16. Circulating Biologically Active Adrenomedullin (bio-ADM) Predicts Hemodynamic Support Requirement and Mortality During Sepsis.

    Science.gov (United States)

    Caironi, Pietro; Latini, Roberto; Struck, Joachim; Hartmann, Oliver; Bergmann, Andreas; Maggio, Giuseppe; Cavana, Marco; Tognoni, Gianni; Pesenti, Antonio; Gattinoni, Luciano; Masson, Serge

    2017-08-01

    The biological role of adrenomedullin (ADM), a hormone involved in hemodynamic homeostasis, is controversial in sepsis because administration of either the peptide or an antibody against it may be beneficial. Plasma biologically active ADM (bio-ADM) was assessed on days 1, 2, and 7 after randomization of 956 patients with sepsis or septic shock to albumin or crystalloids for fluid resuscitation in the multicenter Albumin Italian Outcome Sepsis trial. We tested the association of bio-ADM and its time-dependent variation with fluid therapy, vasopressor administration, organ failures, and mortality. Plasma bio-ADM on day 1 (median [Q1-Q3], 110 [59-198] pg/mL) was higher in patients with septic shock, associated with 90-day mortality, multiple organ failures and the average extent of hemodynamic support therapy (fluids and vasopressors), and serum lactate time course over the first week. Moreover, it predicted incident cardiovascular dysfunction in patients without shock at enrollment (OR [95% CI], 1.9 [1.4-2.5]; P sepsis, the circulating, biologically active form of ADM may help individualizing hemodynamic support therapy, while avoiding harmful effects. Its possible pathophysiologic role makes bio-ADM a potential candidate for future targeted therapies. ClinicalTrials.gov; No.: NCT00707122. Copyright © 2017 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.

  17. Two sample Bayesian prediction intervals for order statistics based on the inverse exponential-type distributions using right censored sample

    Directory of Open Access Journals (Sweden)

    M.M. Mohie El-Din

    2011-10-01

    Full Text Available In this paper, two sample Bayesian prediction intervals for order statistics (OS are obtained. This prediction is based on a certain class of the inverse exponential-type distributions using a right censored sample. A general class of prior density functions is used and the predictive cumulative function is obtained in the two samples case. The class of the inverse exponential-type distributions includes several important distributions such the inverse Weibull distribution, the inverse Burr distribution, the loglogistic distribution, the inverse Pareto distribution and the inverse paralogistic distribution. Special cases of the inverse Weibull model such as the inverse exponential model and the inverse Rayleigh model are considered.

  18. Maximizing the biological effect of proton dose delivered with scanned beams via inhomogeneous daily dose distributions

    Energy Technology Data Exchange (ETDEWEB)

    Zeng Chuan; Giantsoudi, Drosoula; Grassberger, Clemens; Goldberg, Saveli; Niemierko, Andrzej; Paganetti, Harald; Efstathiou, Jason A.; Trofimov, Alexei [Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114 (United States)

    2013-05-15

    Purpose: Biological effect of radiation can be enhanced with hypofractionation, localized dose escalation, and, in particle therapy, with optimized distribution of linear energy transfer (LET). The authors describe a method to construct inhomogeneous fractional dose (IFD) distributions, and evaluate the potential gain in the therapeutic effect from their delivery in proton therapy delivered by pencil beam scanning. Methods: For 13 cases of prostate cancer, the authors considered hypofractionated courses of 60 Gy delivered in 20 fractions. (All doses denoted in Gy include the proton's mean relative biological effectiveness (RBE) of 1.1.) Two types of plans were optimized using two opposed lateral beams to deliver a uniform dose of 3 Gy per fraction to the target by scanning: (1) in conventional full-target plans (FTP), each beam irradiated the entire gland, (2) in split-target plans (STP), beams irradiated only the respective proximal hemispheres (prostate split sagittally). Inverse planning yielded intensity maps, in which discrete position control points of the scanned beam (spots) were assigned optimized intensity values. FTP plans preferentially required a higher intensity of spots in the distal part of the target, while STP, by design, employed proximal spots. To evaluate the utility of IFD delivery, IFD plans were generated by rearranging the spot intensities from FTP or STP intensity maps, separately as well as combined using a variety of mixing weights. IFD courses were designed so that, in alternating fractions, one of the hemispheres of the prostate would receive a dose boost and the other receive a lower dose, while the total physical dose from the IFD course was roughly uniform across the prostate. IFD plans were normalized so that the equivalent uniform dose (EUD) of rectum and bladder did not increase, compared to the baseline FTP plan, which irradiated the prostate uniformly in every fraction. An EUD-based model was then applied to estimate tumor

  19. Maximizing the biological effect of proton dose delivered with scanned beams via inhomogeneous daily dose distributions

    International Nuclear Information System (INIS)

    Zeng Chuan; Giantsoudi, Drosoula; Grassberger, Clemens; Goldberg, Saveli; Niemierko, Andrzej; Paganetti, Harald; Efstathiou, Jason A.; Trofimov, Alexei

    2013-01-01

    Purpose: Biological effect of radiation can be enhanced with hypofractionation, localized dose escalation, and, in particle therapy, with optimized distribution of linear energy transfer (LET). The authors describe a method to construct inhomogeneous fractional dose (IFD) distributions, and evaluate the potential gain in the therapeutic effect from their delivery in proton therapy delivered by pencil beam scanning. Methods: For 13 cases of prostate cancer, the authors considered hypofractionated courses of 60 Gy delivered in 20 fractions. (All doses denoted in Gy include the proton's mean relative biological effectiveness (RBE) of 1.1.) Two types of plans were optimized using two opposed lateral beams to deliver a uniform dose of 3 Gy per fraction to the target by scanning: (1) in conventional full-target plans (FTP), each beam irradiated the entire gland, (2) in split-target plans (STP), beams irradiated only the respective proximal hemispheres (prostate split sagittally). Inverse planning yielded intensity maps, in which discrete position control points of the scanned beam (spots) were assigned optimized intensity values. FTP plans preferentially required a higher intensity of spots in the distal part of the target, while STP, by design, employed proximal spots. To evaluate the utility of IFD delivery, IFD plans were generated by rearranging the spot intensities from FTP or STP intensity maps, separately as well as combined using a variety of mixing weights. IFD courses were designed so that, in alternating fractions, one of the hemispheres of the prostate would receive a dose boost and the other receive a lower dose, while the total physical dose from the IFD course was roughly uniform across the prostate. IFD plans were normalized so that the equivalent uniform dose (EUD) of rectum and bladder did not increase, compared to the baseline FTP plan, which irradiated the prostate uniformly in every fraction. An EUD-based model was then applied to estimate tumor

  20. Maximizing the biological effect of proton dose delivered with scanned beams via inhomogeneous daily dose distributions.

    Science.gov (United States)

    Zeng, Chuan; Giantsoudi, Drosoula; Grassberger, Clemens; Goldberg, Saveli; Niemierko, Andrzej; Paganetti, Harald; Efstathiou, Jason A; Trofimov, Alexei

    2013-05-01

    Biological effect of radiation can be enhanced with hypofractionation, localized dose escalation, and, in particle therapy, with optimized distribution of linear energy transfer (LET). The authors describe a method to construct inhomogeneous fractional dose (IFD) distributions, and evaluate the potential gain in the therapeutic effect from their delivery in proton therapy delivered by pencil beam scanning. For 13 cases of prostate cancer, the authors considered hypofractionated courses of 60 Gy delivered in 20 fractions. (All doses denoted in Gy include the proton's mean relative biological effectiveness (RBE) of 1.1.) Two types of plans were optimized using two opposed lateral beams to deliver a uniform dose of 3 Gy per fraction to the target by scanning: (1) in conventional full-target plans (FTP), each beam irradiated the entire gland, (2) in split-target plans (STP), beams irradiated only the respective proximal hemispheres (prostate split sagittally). Inverse planning yielded intensity maps, in which discrete position control points of the scanned beam (spots) were assigned optimized intensity values. FTP plans preferentially required a higher intensity of spots in the distal part of the target, while STP, by design, employed proximal spots. To evaluate the utility of IFD delivery, IFD plans were generated by rearranging the spot intensities from FTP or STP intensity maps, separately as well as combined using a variety of mixing weights. IFD courses were designed so that, in alternating fractions, one of the hemispheres of the prostate would receive a dose boost and the other receive a lower dose, while the total physical dose from the IFD course was roughly uniform across the prostate. IFD plans were normalized so that the equivalent uniform dose (EUD) of rectum and bladder did not increase, compared to the baseline FTP plan, which irradiated the prostate uniformly in every fraction. An EUD-based model was then applied to estimate tumor control probability

  1. Use of biological priors enhances understanding of genetic architecture and genomic prediction of complex traits within and between dairy cattle breeds.

    Science.gov (United States)

    Fang, Lingzhao; Sahana, Goutam; Ma, Peipei; Su, Guosheng; Yu, Ying; Zhang, Shengli; Lund, Mogens Sandø; Sørensen, Peter

    2017-08-10

    A better understanding of the genetic architecture underlying complex traits (e.g., the distribution of causal variants and their effects) may aid in the genomic prediction. Here, we hypothesized that the genomic variants of complex traits might be enriched in a subset of genomic regions defined by genes grouped on the basis of "Gene Ontology" (GO), and that incorporating this independent biological information into genomic prediction models might improve their predictive ability. Four complex traits (i.e., milk, fat and protein yields, and mastitis) together with imputed sequence variants in Holstein (HOL) and Jersey (JER) cattle were analysed. We first carried out a post-GWAS analysis in a HOL training population to assess the degree of enrichment of the association signals in the gene regions defined by each GO term. We then extended the genomic best linear unbiased prediction model (GBLUP) to a genomic feature BLUP (GFBLUP) model, including an additional genomic effect quantifying the joint effect of a group of variants located in a genomic feature. The GBLUP model using a single random effect assumes that all genomic variants contribute to the genomic relationship equally, whereas GFBLUP attributes different weights to the individual genomic relationships in the prediction equation based on the estimated genomic parameters. Our results demonstrate that the immune-relevant GO terms were more associated with mastitis than milk production, and several biologically meaningful GO terms improved the prediction accuracy with GFBLUP for the four traits, as compared with GBLUP. The improvement of the genomic prediction between breeds (the average increase across the four traits was 0.161) was more apparent than that it was within the HOL (the average increase across the four traits was 0.020). Our genomic feature modelling approaches provide a framework to simultaneously explore the genetic architecture and genomic prediction of complex traits by taking advantage of

  2. An appraisal of wind speed distribution prediction by soft computing methodologies: A comparative study

    International Nuclear Information System (INIS)

    Petković, Dalibor; Shamshirband, Shahaboddin; Anuar, Nor Badrul; Saboohi, Hadi; Abdul Wahab, Ainuddin Wahid; Protić, Milan; Zalnezhad, Erfan; Mirhashemi, Seyed Mohammad Amin

    2014-01-01

    Highlights: • Probabilistic distribution functions of wind speed. • Two parameter Weibull probability distribution. • To build an effective prediction model of distribution of wind speed. • Support vector regression application as probability function for wind speed. - Abstract: The probabilistic distribution of wind speed is among the more significant wind characteristics in examining wind energy potential and the performance of wind energy conversion systems. When the wind speed probability distribution is known, the wind energy distribution can be easily obtained. Therefore, the probability distribution of wind speed is a very important piece of information required in assessing wind energy potential. For this reason, a large number of studies have been established concerning the use of a variety of probability density functions to describe wind speed frequency distributions. Although the two-parameter Weibull distribution comprises a widely used and accepted method, solving the function is very challenging. In this study, the polynomial and radial basis functions (RBF) are applied as the kernel function of support vector regression (SVR) to estimate two parameters of the Weibull distribution function according to previously established analytical methods. Rather than minimizing the observed training error, SVR p oly and SVR r bf attempt to minimize the generalization error bound, so as to achieve generalized performance. According to the experimental results, enhanced predictive accuracy and capability of generalization can be achieved using the SVR approach compared to other soft computing methodologies

  3. The electron density and temperature distributions predicted by bow shock models of Herbig-Haro objects

    International Nuclear Information System (INIS)

    Noriega-Crespo, A.; Bohm, K.H.; Raga, A.C.

    1990-01-01

    The observable spatial electron density and temperature distributions for series of simple bow shock models, which are of special interest in the study of Herbig-Haro (H-H) objects are computed. The spatial electron density and temperature distributions are derived from forbidden line ratios. It should be possible to use these results to recognize whether an observed electron density or temperature distribution can be attributed to a bow shock, as is the case in some Herbig-Haro objects. As an example, the empirical and predicted distributions for H-H 1 are compared. The predicted electron temperature distributions give the correct temperature range and they show very good diagnostic possibilities if the forbidden O III (4959 + 5007)/4363 wavelength ratio is used. 44 refs

  4. Measurement and prediction of aromatic solute distribution coefficients for aqueous-organic solvent systems. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Campbell, J.R.; Luthy, R.G.

    1984-06-01

    Experimental and modeling activities were performed to assess techniques for measurement and prediction of distribution coefficients for aromatic solutes between water and immiscible organic solvents. Experiments were performed to measure distribution coefficients in both clean water and wastewater systems, and to assess treatment of a wastewater by solvent extraction. The theoretical portions of this investigation were directed towards development of techniques for prediction of solute-solvent/water distribution coefficients. Experiments were performed to assess treatment of a phenolic-laden coal conversion wastewater by solvent extraction. The results showed that solvent extraction for recovery of phenolic material offered several wastewater processing advantages. Distribution coefficients were measured in clean water and wastewater systems for aromatic solutes of varying functionality with different solvent types. It was found that distribution coefficients for these compounds in clean water systems were not statistically different from distribution coefficients determined in a complex coal conversion process wastewater. These and other aromatic solute distribution coefficient data were employed for evaluation of modeling techniques for prediction of solute-solvent/water distribution coefficients. Eight solvents were selected in order to represent various chemical classes: toluene and benzene (aromatics), hexane and heptane (alkanes), n-octanol (alcohols), n-butyl acetate (esters), diisopropyl ether (ethers), and methylisobutyl ketone (ketones). The aromatic solutes included: nonpolar compounds such as benzene, toluene and naphthalene, phenolic compounds such as phenol, cresol and catechol, nitrogenous aromatics such as aniline, pyridine and aminonaphthalene, and other aromatic solutes such as naphthol, quinolinol and halogenated compounds. 100 references, 20 figures, 34 tables.

  5. Effects of species biological traits and environmental heterogeneity on simulated tree species distribution shifts under climate change

    Science.gov (United States)

    Wen J. Wang; Hong S. He; Frank R. Thompson; Martin A. Spetich; Jacob S. Fraser

    2018-01-01

    Demographic processes (fecundity, dispersal, colonization, growth, and mortality) and their interactions with environmental changes are notwell represented in current climate-distribution models (e.g., niche and biophysical process models) and constitute a large uncertainty in projections of future tree species distribution shifts.We investigate how species biological...

  6. Definition of the dose(tempo)-distribution in the biological irradiation-facility of the RIVM

    International Nuclear Information System (INIS)

    Bader, F.J.M.

    1990-02-01

    The RIVM biological irradiation facility (BBF) for the irradiation of biological samples and small animals is a self shielded device and can be safely operated in an existing laboratory environment. There are two 137 Cs sources (15TBq) in a bilateral geometry to give maximum dose uniformity. The easily accessible irradiation chamber is housed in a rotating lead shielding. The dosimetry of BBF was performed by the Dosimetry Section of the RIVM. Experiments were made to determine the absorbed dose in plastic tubes filled with water and the dose distribution over the tube-holder. Separate experiments were made to determine the absorbed dose during the rotation of the irradiation chamber and to check the irradiation timer. For the experiments LiF:Mg,Ti (TLD-100) extruded ribbons were used. The TLDs were calibrated in a collimated beam of 137 Cs gamma rays. The determination of the absorbed dose in water was based on a users biological irradiation set up. The TLDs were individually sealed in thin plastic foil and put in plastic tubes filled for 1/3 with water. The tubes were vertically placed in the tube-holder and placed in the centre of the irradiation chamber. The results show that the absorbed dose in water (determined on January 1, 1990) is equal to 0.97 Gy/timer-unit, with a total uncertainty of 7 percent (1σ). During the rotation of the irradiation chamber the absorbed dose (determined on January 1, 1990) is equal to 0.38 Gy, with a total uncertainty of 15 percent (1σ). The variation of the dose distribution was determined at 15 different measurement points distributed over the tube-holder. The dosis in the measurement point in the centre of the tube-holder was taken as reference value. The maximum observed deviation over the other 14 measurement points amounts to -16 percent of it. The BBF-timer was checked against a special timer. The results indicate that within a range from 2-11 'timer-units' no differences are present. (author). 6 refs.; 6 figs.; 3 fotos

  7. Predicting the biological condition of streams: Use of geospatial indicators of natural and anthropogenic characteristics of watersheds

    Science.gov (United States)

    Carlisle, D.M.; Falcone, J.; Meador, M.R.

    2009-01-01

    We developed and evaluated empirical models to predict biological condition of wadeable streams in a large portion of the eastern USA, with the ultimate goal of prediction for unsampled basins. Previous work had classified (i.e., altered vs. unaltered) the biological condition of 920 streams based on a biological assessment of macroinvertebrate assemblages. Predictor variables were limited to widely available geospatial data, which included land cover, topography, climate, soils, societal infrastructure, and potential hydrologic modification. We compared the accuracy of predictions of biological condition class based on models with continuous and binary responses. We also evaluated the relative importance of specific groups and individual predictor variables, as well as the relationships between the most important predictors and biological condition. Prediction accuracy and the relative importance of predictor variables were different for two subregions for which models were created. Predictive accuracy in the highlands region improved by including predictors that represented both natural and human activities. Riparian land cover and road-stream intersections were the most important predictors. In contrast, predictive accuracy in the lowlands region was best for models limited to predictors representing natural factors, including basin topography and soil properties. Partial dependence plots revealed complex and nonlinear relationships between specific predictors and the probability of biological alteration. We demonstrate a potential application of the model by predicting biological condition in 552 unsampled basins across an ecoregion in southeastern Wisconsin (USA). Estimates of the likelihood of biological condition of unsampled streams could be a valuable tool for screening large numbers of basins to focus targeted monitoring of potentially unaltered or altered stream segments. ?? Springer Science+Business Media B.V. 2008.

  8. The Distributed Biological Observatory (DBO)-A Change Detection Array in the Pacific Arctic Sector

    Science.gov (United States)

    Grebmeier, J. M.; Moore, S. E.; Cooper, L. W.; Frey, K. E.; Pickart, R. S.

    2011-12-01

    The Pacific sector of the Arctic Ocean is experiencing major reductions in seasonal sea ice extent and increases in sea surface temperatures. One of the key uncertainties in this region is how the marine ecosystem will respond to seasonal shifts in the timing of spring sea ice retreat and/or delays in fall sea ice formation. Variations in upper ocean water hydrography, planktonic production, pelagic-benthic coupling and sediment carbon cycling are all influenced by sea ice and temperature changes. Climate changes are likely to result in shifts in species composition and abundance, northward range expansions, and changes in lower trophic level productivity that can directly cascade and affect the life cycles of higher trophic level organisms. Several regionally critical marine sites in the Pacific Arctic sector that have very high biomass and are focused foraging points for apex predators have been re-occupied during multiple international cruises. The data documenting the importance of these ecosystem "hotspots" provide a growing marine time-series from the northern Bering Sea to Barrow Canyon at the boundary of the Chukchi and Beaufort seas. Results from these studies show spatial changes in carbon production and export to the sediments as indicated by infaunal community composition and biomass, shifts in sediment grain size on a S-to-N latitudinal gradient, and range extensions for lower trophic levels and further northward migration of higher trophic organisms, such as gray whales. There is also direct evidence of negative impacts on ice dependent species, such as walrus and polar bears. To more systematically track the broad biological response to sea ice retreat and associated environmental change, an international consortium of scientists are developing a "Distributed Biological Observatory" (DBO) that includes selected biological measurements at multiple trophic levels. The DBO currently focuses on five regional biological "hotspot" locations along a

  9. A Predictive Distribution Model for Cooperative Braking System of an Electric Vehicle

    Directory of Open Access Journals (Sweden)

    Hongqiang Guo

    2014-01-01

    Full Text Available A predictive distribution model for a series cooperative braking system of an electric vehicle is proposed, which can solve the real-time problem of the optimum braking force distribution. To get the predictive distribution model, firstly three disciplines of the maximum regenerative energy recovery capability, the maximum generating efficiency and the optimum braking stability are considered, then an off-line process optimization stream is designed, particularly the optimal Latin hypercube design (Opt LHD method and radial basis function neural network (RBFNN are utilized. In order to decouple the variables between different disciplines, a concurrent subspace design (CSD algorithm is suggested. The established predictive distribution model is verified in a dynamic simulation. The off-line optimization results show that the proposed process optimization stream can improve the regenerative energy recovery efficiency, and optimize the braking stability simultaneously. Further simulation tests demonstrate that the predictive distribution model can achieve high prediction accuracy and is very beneficial for the cooperative braking system.

  10. Prediction equation for lower limbs lean soft tissue in circumpubertal boys using anthropometry and biological maturation.

    Directory of Open Access Journals (Sweden)

    João Valente-dos-Santos

    Full Text Available Lean soft tissue (LST, a surrogate of skeletal muscle mass, is largely limited to appendicular body regions. Simple and accurate methods to estimate lower limbs LST are often used in attempts to partition out the influence of body size on performance outputs. The aim of the current study was to develop and cross-validate a new model to predict lower limbs LST in boys aged 10-13 years, using dual-energy X-ray absorptiometry (DXA as the reference method. Total body and segmental (lower limbs composition were assessed with a Hologic Explorer-W QDR DXA scanner in a cross-sectional sample of 75 Portuguese boys (144.8±6.4 cm; 40.2±9.0 kg. Skinfolds were measured at the anterior and posterior mid-thigh, and medial calf. Circumferences were measured at the proximal, mid and distal thigh. Leg length was estimated as stature minus sitting height. Current stature expressed as a percentage of attained predicted mature stature (PMS was used as an estimate of biological maturity status. Backward proportional allometric models were used to identify the model with the best statistical fit: ln (lower limbs LST  = 0.838× ln (body mass +0.476× ln (leg length - 0.135× ln (mid-thigh circumference - 0.053× ln (anterior mid-thigh skinfold - 0.098× ln (medial calf skinfold - 2.680+0.010× (percentage of attained PMS (R = 0.95. The obtained equation was cross-validated using the predicted residuals sum of squares statistics (PRESS method (R2PRESS = 0.90. Deming repression analysis between predicted and current lower limbs LST showed a standard error of estimation of 0.52 kg (95% limits of agreement: 0.77 to -1.27 kg. The new model accurately predicts lower limbs LST in circumpubertal boys.

  11. Regional climate model downscaling may improve the prediction of alien plant species distributions

    Science.gov (United States)

    Liu, Shuyan; Liang, Xin-Zhong; Gao, Wei; Stohlgren, Thomas J.

    2014-12-01

    Distributions of invasive species are commonly predicted with species distribution models that build upon the statistical relationships between observed species presence data and climate data. We used field observations, climate station data, and Maximum Entropy species distribution models for 13 invasive plant species in the United States, and then compared the models with inputs from a General Circulation Model (hereafter GCM-based models) and a downscaled Regional Climate Model (hereafter, RCM-based models).We also compared species distributions based on either GCM-based or RCM-based models for the present (1990-1999) to the future (2046-2055). RCM-based species distribution models replicated observed distributions remarkably better than GCM-based models for all invasive species under the current climate. This was shown for the presence locations of the species, and by using four common statistical metrics to compare modeled distributions. For two widespread invasive taxa ( Bromus tectorum or cheatgrass, and Tamarix spp. or tamarisk), GCM-based models failed miserably to reproduce observed species distributions. In contrast, RCM-based species distribution models closely matched observations. Future species distributions may be significantly affected by using GCM-based inputs. Because invasive plants species often show high resilience and low rates of local extinction, RCM-based species distribution models may perform better than GCM-based species distribution models for planning containment programs for invasive species.

  12. Three-dimensional distributions of elements in biological samples by energy-filtered electron tomography

    Energy Technology Data Exchange (ETDEWEB)

    Leapman, R.D.; Kocsis, E.; Zhang, G.; Talbot, T.L.; Laquerriere, P

    2004-07-15

    By combining electron tomography with energy-filtered electron microscopy, we have shown the feasibility of determining the three-dimensional distributions of phosphorus in biological specimens. Thin sections of the nematode, Caenorhabditis elegans were prepared by high-pressure freezing, freeze-substitution and plastic embedding. Images were recorded at energy losses above and below the phosphorus L{sub 2,3} edge using a post-column imaging filter operating at a beam energy of 120 keV. The unstained specimens exhibited minimal contrast in bright-field images. After it was determined that the specimen was sufficiently thin to allow two-window ratio imaging of phosphorus, pairs of pre-edge and post-edge images were acquired in series over a tilt range of {+-}55 deg. at 5 deg. increments for two orthogonal tilt axes. The projected phosphorus distributions were aligned using the pre-edge images that contained inelastic contrast from colloidal gold particles deposited on the specimen surface. A reconstruction and surface rendering of the phosphorus distribution clearly revealed features 15-20 nm in diameter, which were identified as ribosomes distributed along the stacked membranes of endoplasmic reticulum and in the cytoplasm. The sensitivity of the technique was estimated at <35 phosphorus atoms per voxel based on the known total ribosomal phosphorus content of approximately 7000 atoms. Although a high electron dose of approximately 10{sup 7} e/nm{sup 2} was required to record two-axis tilt series, specimens were sufficiently stable to allow image alignment and tomographic reconstruction.

  13. Distribution and ecology of gammarus lacustris G. O. Sars in Norway, with notes on its morphology and biology

    Energy Technology Data Exchange (ETDEWEB)

    Oekland, K A

    1969-01-01

    The distribution of Gammarus lacustris in Norway is found to be affected mainly by hydrographical and geological factors. Of special interest is the species absence in the more acid lakes. In some areas, inefficiencies in dispersal and predation by fish also influence the distribution patterns. A tendency for the larger animals to occur in lakes rich in lime is demonstrated. Morphology, breeding biology, depth distribution, and parasites are also treated.

  14. A postprocessing method in the HMC framework for predicting gene function based on biological instrumental data

    Science.gov (United States)

    Feng, Shou; Fu, Ping; Zheng, Wenbin

    2018-03-01

    Predicting gene function based on biological instrumental data is a complicated and challenging hierarchical multi-label classification (HMC) problem. When using local approach methods to solve this problem, a preliminary results processing method is usually needed. This paper proposed a novel preliminary results processing method called the nodes interaction method. The nodes interaction method revises the preliminary results and guarantees that the predictions are consistent with the hierarchy constraint. This method exploits the label dependency and considers the hierarchical interaction between nodes when making decisions based on the Bayesian network in its first phase. In the second phase, this method further adjusts the results according to the hierarchy constraint. Implementing the nodes interaction method in the HMC framework also enhances the HMC performance for solving the gene function prediction problem based on the Gene Ontology (GO), the hierarchy of which is a directed acyclic graph that is more difficult to tackle. The experimental results validate the promising performance of the proposed method compared to state-of-the-art methods on eight benchmark yeast data sets annotated by the GO.

  15. Historical freshwater fish ecology: a long-term view of distribution changes and biological invasions

    Directory of Open Access Journals (Sweden)

    Miguel Clavero

    2015-12-01

    Full Text Available Past processes and events may have an important influence on contemporaneous ecological patterns, including current human impacts on landscapes and organisms. In spite of that, most of the ecological knowledge has been built upon short-term studies, which very rarely exceed one decade. Ecology and Conservation Biology have an important lack of historical approaches, a deficiency that may become a hindrance for the management of natural systems. In this talk I will present examples of how historical information on the distribution of freshwater fish and other aquatic organisms can be used to address ecological questions. Most analyses are based on two important Spanish historical written sources: the Relaciones de Felipe II (16th century and the Madoz Dictionary (19th century. The examples considered include the European eel (Anguilla anguilla, the brown trout (Salmo trutta, the common carp (Cyprinus carpio and the white clawed crayfish (Austropotamobius italicus, among other species, as well as questions related to biological invasions, habitat loss and the impacts of global warming. The outputs of ecological research based on historical data often become useful tools for present-day biodiversity conservation planning and actions.

  16. Chloridrate of N-isopropyl-p-iodoamphetamine labeled with Iodine-131. Biological distribution in laboratory animals

    International Nuclear Information System (INIS)

    Colturato, Maria Tereza; Muramoto, Emiko; Carvalho, Olga Goncalves de

    2000-01-01

    The development of this work was based on a great interest from the medical class in the utilization of chloridrate of N-isopropyl-p-iodoamphetamine (IMP) labeled with 123 I, for brain perfusion evaluation. Studies were performed to optimize the labeling parameters of IMP with 131 I using nucleophilic substitution: temperature and, time reaction, ascorbic acid mass, pH and relation IMP mass/radioiodo activity, and stability of the final product. Radiochemistry purity method used showed to be efficient, quick and of easily handling for routine production. Biological distribution studies were performed in mice to determine the percent administered dose in the blood, different organs and whole body after intravenous administration of the radiopharmaceutical. The product crossed the intact blood brain barrier, allowing a follow up of further studies after the intravenous administration of the radiopharmaceutical. The principal elimination route 131 I-IMP was the urinary. Based on the results from radiochemical purity, stability and biological behavior in laboratory animals, we concluded that the studied radiopharmaceutical presents all ideal characteristics for clinical use in brain studies in nuclear medicine. (author)

  17. Application of a computer model to predict optimum slaughter end points for different biological types of feeder cattle.

    Science.gov (United States)

    Williams, C B; Bennett, G L

    1995-10-01

    A bioeconomic model was developed to predict slaughter end points of different genotypes of feeder cattle, where profit/rotation and profit/day were maximized. Growth, feed intake, and carcass weight and composition were simulated for 17 biological types of steers. Distribution of carcass weight and proportion in four USDA quality and five USDA yield grades were obtained from predicted carcass weights and composition. Average carcass value for each genotype was calculated from these distributions under four carcass pricing systems that varied from value determined on quality grade alone to value determined on yield grade alone. Under profitable market conditions, rotation length was shorter and carcass weights lighter when the producer's goal was maximum profit/day, compared with maximum profit/rotation. A carcass value system based on yield grade alone resulted in greater profit/rotation and in lighter and leaner carcasses than a system based on quality grade alone. High correlations ( > .97) were obtained between breed profits obtained with different sets of input/output prices and carcass price discount weight ranges. This suggests that breed rankings on the basis of breed profits may not be sensitive to changes in input/output market prices. Steers that were on a grower-stocker system had leaner carcasses, heavier optimum carcass weight, greater profits, and less variation in optimum carcass weights between genotypes than steers that were started on a high-energy finishing diet at weaning. Overall results suggest that breed choices may change with different carcass grading and value systems and postweaning production systems. This model has potential to provide decision support in marketing fed cattle.

  18. The size distribution of marine atmospheric aerosol with regard to primary biological aerosol particles over the South Atlantic Ocean

    Science.gov (United States)

    Matthias-Maser, Sabine; Brinkmann, Jutta; Schneider, Wilhelm

    The marine atmosphere is characterized by particles which originate from the ocean and by those which reached the air by advection from the continent. The bubble-burst mechanism produces both sea salt as well as biological particles. The following article describes the determination of the size distribution of marine aerosol particles with special emphasis on the biological particles. Th data were obtained on three cruises with the German Research Vessel "METEOR" crossing the South Atlantic Ocean. The measurements showed that biological particles amount to 17% in number and 10% in volume concentration. Another type of particle became obvious in the marine atmosphere, the biologically contaminated particle, i.e. particles which consist partly (approximately up to one-third) of biological matter. Their concentration in the evaluated size class ( r>2 μm) is higher than the concentration of the pure biological particles. The concentrations vary over about one to two orders of magnitude during all cruises.

  19. Interpreting predictive maps of disease: highlighting the pitfalls of distribution models in epidemiology

    Directory of Open Access Journals (Sweden)

    Nicola A. Wardrop

    2014-11-01

    Full Text Available The application of spatial modelling to epidemiology has increased significantly over the past decade, delivering enhanced understanding of the environmental and climatic factors affecting disease distributions and providing spatially continuous representations of disease risk (predictive maps. These outputs provide significant information for disease control programmes, allowing spatial targeting and tailored interventions. However, several factors (e.g. sampling protocols or temporal disease spread can influence predictive mapping outputs. This paper proposes a conceptual framework which defines several scenarios and their potential impact on resulting predictive outputs, using simulated data to provide an exemplar. It is vital that researchers recognise these scenarios and their influence on predictive models and their outputs, as a failure to do so may lead to inaccurate interpretation of predictive maps. As long as these considerations are kept in mind, predictive mapping will continue to contribute significantly to epidemiological research and disease control planning.

  20. Predicting plant distribution in an heterogeneous Alpine landscape: does soil matter?

    Science.gov (United States)

    Buri, Aline; Cianfrani, Carmen; Pradervand, Jean-Nicolas; Guisan, Antoine

    2016-04-01

    Topographic and climatic factors are usually used to predict plant distribution because they are known to explain their presence or absence. Soil properties have been widely shown to influence plant growth and distributions. However, they are rarely taken into account as predictors of plant species distribution models (SDM) in an edaphically heterogeneous landscape. Or, when it happens, interpolation techniques are used to project soil factors in space. In heterogeneous landscape, such as in the Alps region, where soil properties change abruptly as a function of environmental conditions over short distances, interpolation techniques require a huge quantities of samples to be efficient. This is costly and time consuming, and bring more errors than predictive approach for an equivalent number of samples. In this study we aimed to assess whether soil proprieties may be generalized over entire mountainous geographic extents and can improve predictions of plant distributions over traditional topo-climatic predictors. First, we used a predictive approach to map two soil proprieties based on field measurements in the western Swiss Alps region; the soil pH and the ratio of stable isotopes 13C/12C (called δ13CSOM). We used ensemble forecasting techniques combining together several predictive algorithms to build models of the geographic variation in the values of both soil proprieties and projected them in the entire study area. As predictive factors, we employed very high resolution topo-climatic data. In a second step, output maps from the previous task were used as an input for vegetation regional models. We integrated the predicted soil proprieties to a set of basic topo-climatic predictors known to be important to model plants species. Then we modelled the distribution of 156 plant species inhabiting the study area. Finally, we compared the quality of the models having or not soil proprieties as predictors to evaluate their effect on the predictive power of our models

  1. Usefulness and limitations of dK random graph models to predict interactions and functional homogeneity in biological networks under a pseudo-likelihood parameter estimation approach

    Directory of Open Access Journals (Sweden)

    Luan Yihui

    2009-09-01

    Full Text Available Abstract Background Many aspects of biological functions can be modeled by biological networks, such as protein interaction networks, metabolic networks, and gene coexpression networks. Studying the statistical properties of these networks in turn allows us to infer biological function. Complex statistical network models can potentially more accurately describe the networks, but it is not clear whether such complex models are better suited to find biologically meaningful subnetworks. Results Recent studies have shown that the degree distribution of the nodes is not an adequate statistic in many molecular networks. We sought to extend this statistic with 2nd and 3rd order degree correlations and developed a pseudo-likelihood approach to estimate the parameters. The approach was used to analyze the MIPS and BIOGRID yeast protein interaction networks, and two yeast coexpression networks. We showed that 2nd order degree correlation information gave better predictions of gene interactions in both protein interaction and gene coexpression networks. However, in the biologically important task of predicting functionally homogeneous modules, degree correlation information performs marginally better in the case of the MIPS and BIOGRID protein interaction networks, but worse in the case of gene coexpression networks. Conclusion Our use of dK models showed that incorporation of degree correlations could increase predictive power in some contexts, albeit sometimes marginally, but, in all contexts, the use of third-order degree correlations decreased accuracy. However, it is possible that other parameter estimation methods, such as maximum likelihood, will show the usefulness of incorporating 2nd and 3rd degree correlations in predicting functionally homogeneous modules.

  2. Usefulness and limitations of dK random graph models to predict interactions and functional homogeneity in biological networks under a pseudo-likelihood parameter estimation approach.

    Science.gov (United States)

    Wang, Wenhui; Nunez-Iglesias, Juan; Luan, Yihui; Sun, Fengzhu

    2009-09-03

    Many aspects of biological functions can be modeled by biological networks, such as protein interaction networks, metabolic networks, and gene coexpression networks. Studying the statistical properties of these networks in turn allows us to infer biological function. Complex statistical network models can potentially more accurately describe the networks, but it is not clear whether such complex models are better suited to find biologically meaningful subnetworks. Recent studies have shown that the degree distribution of the nodes is not an adequate statistic in many molecular networks. We sought to extend this statistic with 2nd and 3rd order degree correlations and developed a pseudo-likelihood approach to estimate the parameters. The approach was used to analyze the MIPS and BIOGRID yeast protein interaction networks, and two yeast coexpression networks. We showed that 2nd order degree correlation information gave better predictions of gene interactions in both protein interaction and gene coexpression networks. However, in the biologically important task of predicting functionally homogeneous modules, degree correlation information performs marginally better in the case of the MIPS and BIOGRID protein interaction networks, but worse in the case of gene coexpression networks. Our use of dK models showed that incorporation of degree correlations could increase predictive power in some contexts, albeit sometimes marginally, but, in all contexts, the use of third-order degree correlations decreased accuracy. However, it is possible that other parameter estimation methods, such as maximum likelihood, will show the usefulness of incorporating 2nd and 3rd degree correlations in predicting functionally homogeneous modules.

  3. An evaluation of the predictive performance of distributional models for flora and fauna in north-east New South Wales.

    Science.gov (United States)

    Pearce, J; Ferrier, S; Scotts, D

    2001-06-01

    To use models of species distributions effectively in conservation planning, it is important to determine the predictive accuracy of such models. Extensive modelling of the distribution of vascular plant and vertebrate fauna species within north-east New South Wales has been undertaken by linking field survey data to environmental and geographical predictors using logistic regression. These models have been used in the development of a comprehensive and adequate reserve system within the region. We evaluate the predictive accuracy of models for 153 small reptile, arboreal marsupial, diurnal bird and vascular plant species for which independent evaluation data were available. The predictive performance of each model was evaluated using the relative operating characteristic curve to measure discrimination capacity. Good discrimination ability implies that a model's predictions provide an acceptable index of species occurrence. The discrimination capacity of 89% of the models was significantly better than random, with 70% of the models providing high levels of discrimination. Predictions generated by this type of modelling therefore provide a reasonably sound basis for regional conservation planning. The discrimination ability of models was highest for the less mobile biological groups, particularly the vascular plants and small reptiles. In the case of diurnal birds, poor performing models tended to be for species which occur mainly within specific habitats not well sampled by either the model development or evaluation data, highly mobile species, species that are locally nomadic or those that display very broad habitat requirements. Particular care needs to be exercised when employing models for these types of species in conservation planning.

  4. Robust distributed model predictive control of linear systems with structured time-varying uncertainties

    Science.gov (United States)

    Zhang, Langwen; Xie, Wei; Wang, Jingcheng

    2017-11-01

    In this work, synthesis of robust distributed model predictive control (MPC) is presented for a class of linear systems subject to structured time-varying uncertainties. By decomposing a global system into smaller dimensional subsystems, a set of distributed MPC controllers, instead of a centralised controller, are designed. To ensure the robust stability of the closed-loop system with respect to model uncertainties, distributed state feedback laws are obtained by solving a min-max optimisation problem. The design of robust distributed MPC is then transformed into solving a minimisation optimisation problem with linear matrix inequality constraints. An iterative online algorithm with adjustable maximum iteration is proposed to coordinate the distributed controllers to achieve a global performance. The simulation results show the effectiveness of the proposed robust distributed MPC algorithm.

  5. Multivariate models for prediction of rheological characteristics of filamentous fermentation broth from the size distribution

    DEFF Research Database (Denmark)

    Petersen, Nanna; Stocks, S.; Gernaey, Krist

    2008-01-01

    fermentations conducted in 550 L pilot scale tanks were characterized with respect to particle size distribution, biomass concentration, and rheological properties. The rheological properties were described using the Herschel-Bulkley model. Estimation of all three parameters in the Herschel-Bulkley model (yield...... in filamentous fermentations. It was therefore chosen to fix this parameter to the average value thereby decreasing the standard deviation of the estimates of the remaining theological parameters significantly. Using a PLSR model, a reasonable prediction of apparent viscosity (mu(app)), yield stress (tau......(y)), and consistency index (K), could be made from the size distributions, biomass concentration, and process information. This provides a predictive method with a high predictive power for the rheology of fermentation broth, and with the advantages over previous models that tau(y) and K can be predicted as well as mu...

  6. Nonparametric Tree-Based Predictive Modeling of Storm Outages on an Electric Distribution Network.

    Science.gov (United States)

    He, Jichao; Wanik, David W; Hartman, Brian M; Anagnostou, Emmanouil N; Astitha, Marina; Frediani, Maria E B

    2017-03-01

    This article compares two nonparametric tree-based models, quantile regression forests (QRF) and Bayesian additive regression trees (BART), for predicting storm outages on an electric distribution network in Connecticut, USA. We evaluated point estimates and prediction intervals of outage predictions for both models using high-resolution weather, infrastructure, and land use data for 89 storm events (including hurricanes, blizzards, and thunderstorms). We found that spatially BART predicted more accurate point estimates than QRF. However, QRF produced better prediction intervals for high spatial resolutions (2-km grid cells and towns), while BART predictions aggregated to coarser resolutions (divisions and service territory) more effectively. We also found that the predictive accuracy was dependent on the season (e.g., tree-leaf condition, storm characteristics), and that the predictions were most accurate for winter storms. Given the merits of each individual model, we suggest that BART and QRF be implemented together to show the complete picture of a storm's potential impact on the electric distribution network, which would allow for a utility to make better decisions about allocating prestorm resources. © 2016 Society for Risk Analysis.

  7. Continuous Distributed Representation of Biological Sequences for Deep Proteomics and Genomics.

    Directory of Open Access Journals (Sweden)

    Ehsaneddin Asgari

    Full Text Available We introduce a new representation and feature extraction method for biological sequences. Named bio-vectors (BioVec to refer to biological sequences in general with protein-vectors (ProtVec for proteins (amino-acid sequences and gene-vectors (GeneVec for gene sequences, this representation can be widely used in applications of deep learning in proteomics and genomics. In the present paper, we focus on protein-vectors that can be utilized in a wide array of bioinformatics investigations such as family classification, protein visualization, structure prediction, disordered protein identification, and protein-protein interaction prediction. In this method, we adopt artificial neural network approaches and represent a protein sequence with a single dense n-dimensional vector. To evaluate this method, we apply it in classification of 324,018 protein sequences obtained from Swiss-Prot belonging to 7,027 protein families, where an average family classification accuracy of 93%±0.06% is obtained, outperforming existing family classification methods. In addition, we use ProtVec representation to predict disordered proteins from structured proteins. Two databases of disordered sequences are used: the DisProt database as well as a database featuring the disordered regions of nucleoporins rich with phenylalanine-glycine repeats (FG-Nups. Using support vector machine classifiers, FG-Nup sequences are distinguished from structured protein sequences found in Protein Data Bank (PDB with a 99.8% accuracy, and unstructured DisProt sequences are differentiated from structured DisProt sequences with 100.0% accuracy. These results indicate that by only providing sequence data for various proteins into this model, accurate information about protein structure can be determined. Importantly, this model needs to be trained only once and can then be applied to extract a comprehensive set of information regarding proteins of interest. Moreover, this representation can be

  8. Trait-based representation of biological nitrification: Model development, testing, and predicted community composition

    Directory of Open Access Journals (Sweden)

    Nick eBouskill

    2012-10-01

    Full Text Available Trait-based microbial models show clear promise as tools to represent the diversity and activity of microorganisms across ecosystem gradients. These models parameterize specific traits that determine the relative fitness of an ‘organism’ in a given environment, and represent the complexity of biological systems across temporal and spatial scales. In this study we introduce a microbial community trait-based modeling framework (MicroTrait focused on nitrification (MicroTrait-N that represents the ammonia-oxidizing bacteria (AOB and ammonia-oxidizing archaea (AOA and nitrite oxidizing bacteria (NOB using traits related to enzyme kinetics and physiological properties. We used this model to predict nitrifier diversity, ammonia (NH3 oxidation rates and nitrous oxide (N2O production across pH, temperature and substrate gradients. Predicted nitrifier diversity was predominantly determined by temperature and substrate availability, the latter was strongly influenced by pH. The model predicted that transient N2O production rates are maximized by a decoupling of the AOB and NOB communities, resulting in an accumulation and detoxification of nitrite to N2O by AOB. However, cumulative N2O production (over six month simulations is maximized in a system where the relationship between AOB and NOB is maintained. When the reactions uncouple, the AOB become unstable and biomass declines rapidly, resulting in decreased NH3 oxidation and N2O production. We evaluated this model against site level chemical datasets from the interior of Alaska and accurately simulated NH3 oxidation rates and the relative ratio of AOA:AOB biomass. The predicted community structure and activity indicate (a parameterization of a small number of traits may be sufficient to broadly characterize nitrifying community structure and (b changing decadal trends in climate and edaphic conditions could impact nitrification rates in ways that are not captured by extant biogeochemical models.

  9. Prediction of vertical distribution and ambient development temperature of Baltic cod, Gadus morhua L., eggs

    DEFF Research Database (Denmark)

    Wieland, Kai; Jarre, Astrid

    1997-01-01

    An artificial neural network (ANN) model was established to predict the vertical distribution of Baltic cod eggs. Data from vertical distribution sampling in the Bornholm Basin over the period 1986-1995 were used to train and test the network, while data sets from sampling in 1996 were used...... for validation. The model explained 82% of the variance between observed and predicted relative frequencies of occurrence of the eggs in relation to salinity, temperature and oxygen concentration; The ANN fitted all observations satisfactorily except for one sampling date, where an exceptional hydrographic...

  10. The effects of model and data complexity on predictions from species distributions models

    DEFF Research Database (Denmark)

    García-Callejas, David; Bastos, Miguel

    2016-01-01

    How complex does a model need to be to provide useful predictions is a matter of continuous debate across environmental sciences. In the species distributions modelling literature, studies have demonstrated that more complex models tend to provide better fits. However, studies have also shown...... that predictive performance does not always increase with complexity. Testing of species distributions models is challenging because independent data for testing are often lacking, but a more general problem is that model complexity has never been formally described in such studies. Here, we systematically...

  11. Enhanced effects of biotic interactions on predicting multispecies spatial distribution of submerged macrophytes after eutrophication.

    Science.gov (United States)

    Song, Kun; Cui, Yichong; Zhang, Xijin; Pan, Yingji; Xu, Junli; Xu, Kaiqin; Da, Liangjun

    2017-10-01

    Water eutrophication creates unfavorable environmental conditions for submerged macrophytes. In these situations, biotic interactions may be particularly important for explaining and predicting the submerged macrophytes occurrence. Here, we evaluate the roles of biotic interactions in predicting spatial occurrence of submerged macrophytes in 1959 and 2009 for Dianshan Lake in eastern China, which became eutrophic since the 1980s. For the four common species occurred in 1959 and 2009, null species distribution models based on abiotic variables and full models based on both abiotic and biotic variables were developed using generalized linear model (GLM) and boosted regression trees (BRT) to determine whether the biotic variables improved the model performance. Hierarchical Bayesian-based joint species distribution models capable of detecting paired biotic interactions were established for each species in both periods to evaluate the changes in the biotic interactions. In most of the GLM and BRT models, the full models showed better performance than the null models in predicting the species presence/absence, and the relative importance of the biotic variables in the full models increased from less than 50% in 1959 to more than 50% in 2009 for each species. Moreover, co-occurrence correlation of each paired species interaction was higher in 2009 than that in 1959. The findings suggest biotic interactions that tend to be positive play more important roles in the spatial distribution of multispecies assemblages of macrophytes and should be included in prediction models to improve prediction accuracy when forecasting macrophytes' distribution under eutrophication stress.

  12. Moving Towards Dynamic Ocean Management: How Well Do Modeled Ocean Products Predict Species Distributions?

    Directory of Open Access Journals (Sweden)

    Elizabeth A. Becker

    2016-02-01

    Full Text Available Species distribution models are now widely used in conservation and management to predict suitable habitat for protected marine species. The primary sources of dynamic habitat data have been in situ and remotely sensed oceanic variables (both are considered “measured data”, but now ocean models can provide historical estimates and forecast predictions of relevant habitat variables such as temperature, salinity, and mixed layer depth. To assess the performance of modeled ocean data in species distribution models, we present a case study for cetaceans that compares models based on output from a data assimilative implementation of the Regional Ocean Modeling System (ROMS to those based on measured data. Specifically, we used seven years of cetacean line-transect survey data collected between 1991 and 2009 to develop predictive habitat-based models of cetacean density for 11 species in the California Current Ecosystem. Two different generalized additive models were compared: one built with a full suite of ROMS output and another built with a full suite of measured data. Model performance was assessed using the percentage of explained deviance, root mean squared error (RMSE, observed to predicted density ratios, and visual inspection of predicted and observed distributions. Predicted distribution patterns were similar for models using ROMS output and measured data, and showed good concordance between observed sightings and model predictions. Quantitative measures of predictive ability were also similar between model types, and RMSE values were almost identical. The overall demonstrated success of the ROMS-based models opens new opportunities for dynamic species management and biodiversity monitoring because ROMS output is available in near real time and can be forecast.

  13. Back to the Roots: Prediction of Biologically Active Natural Products from Ayurveda Traditional Medicine

    DEFF Research Database (Denmark)

    Polur, Honey; Joshi, Tejal; Workman, Christopher

    2011-01-01

    Ayurveda, the traditional Indian medicine is one of the most ancient, yet living medicinal traditions. In the present work, we developed an in silico library of natural products from Ayurveda medicine, coupled with structural information, plant origin and traditional therapeutic use. Following this....... We hereby present a number of examples where the traditional medicinal use of the plant matches with the medicinal use of the drug that is structurally similar to a plant component. With this approach, we have brought to light a number of obscure compounds of natural origin (e.g. kanugin......, we compared their structures with those of drugs from DrugBank and we constructed a structural similarity network. Information on the traditional therapeutic use of the plants was integrated in the network in order to provide further evidence for the predicted biologically active natural compounds...

  14. Model predictions and analysis of enhanced biological effectiveness at low dose rates

    International Nuclear Information System (INIS)

    Watt, D.E.; Sykes, C.E.; Younis, A.-R.S.

    1988-01-01

    A severe challenge to all models purporting to describe the biological effects of ionizing radiation has arisen with the discovery of two phenomena: the anomalous trend with dose rate of the frequency of neoplastic transformation of mammalian cells and the apparent excessive damaging power of electron-capture radionuclides when incorporated into cell nuclei. A new model is proposed which predicts and enables interpretation of these phenomena. Radiation effectiveness is found to be expressible absolutely in terms of the geometrical cross-sectional area of the radiosensitive sites. The duration of the irradiation, the mean free path for ionization, the influence of particles in the slowing-down spectrum perrtaining in the medium and two collective time factors determining the mean repair rate and the mean lifetime of unidentified reactive chemical species [pt

  15. Incorporation of lysosomal sequestration in the mechanistic model for prediction of tissue distribution of basic drugs.

    Science.gov (United States)

    Assmus, Frauke; Houston, J Brian; Galetin, Aleksandra

    2017-11-15

    The prediction of tissue-to-plasma water partition coefficients (Kpu) from in vitro and in silico data using the tissue-composition based model (Rodgers & Rowland, J Pharm Sci. 2005, 94(6):1237-48.) is well established. However, distribution of basic drugs, in particular into lysosome-rich lung tissue, tends to be under-predicted by this approach. The aim of this study was to develop an extended mechanistic model for the prediction of Kpu which accounts for lysosomal sequestration and the contribution of different cell types in the tissue of interest. The extended model is based on compound-specific physicochemical properties and tissue composition data to describe drug ionization, distribution into tissue water and drug binding to neutral lipids, neutral phospholipids and acidic phospholipids in tissues, including lysosomes. Physiological data on the types of cells contributing to lung, kidney and liver, their lysosomal content and lysosomal pH were collated from the literature. The predictive power of the extended mechanistic model was evaluated using a dataset of 28 basic drugs (pK a ≥7.8, 17 β-blockers, 11 structurally diverse drugs) for which experimentally determined Kpu data in rat tissue have been reported. Accounting for the lysosomal sequestration in the extended mechanistic model improved the accuracy of Kpu predictions in lung compared to the original Rodgers model (56% drugs within 2-fold or 88% within 3-fold of observed values). Reduction in the extent of Kpu under-prediction was also evident in liver and kidney. However, consideration of lysosomal sequestration increased the occurrence of over-predictions, yielding overall comparable model performances for kidney and liver, with 68% and 54% of Kpu values within 2-fold error, respectively. High lysosomal concentration ratios relative to cytosol (>1000-fold) were predicted for the drugs investigated; the extent differed depending on the lysosomal pH and concentration of acidic phospholipids among

  16. Mathematical model of heat transfer to predict distribution of hardness through the Jominy bar

    International Nuclear Information System (INIS)

    Lopez, E.; Hernandez, J. B.; Solorio, G.; Vergara, H. J.; Vazquez, O.; Garnica, F.

    2013-01-01

    The heat transfer coefficient was estimated at the bottom surface at Jominy bar end quench specimen by solution of the heat inverse conduction problem. A mathematical model based on the finite-difference method was developed to predict thermal paths and volume fraction of transformed phases. The mathematical model was codified in the commercial package Microsoft Visual Basic v. 6. The calculated thermal path and final phase distribution were used to evaluate the hardness distribution along the AISI 4140 Jominy bar. (Author)

  17. Biology-inspired Microphysiological System Approaches to Solve the Prediction Dilemma of Substance Testing

    Science.gov (United States)

    Marx, Uwe; Andersson, Tommy B.; Bahinski, Anthony; Beilmann, Mario; Beken, Sonja; Cassee, Flemming R.; Cirit, Murat; Daneshian, Mardas; Fitzpatrick, Susan; Frey, Olivier; Gaertner, Claudia; Giese, Christoph; Griffith, Linda; Hartung, Thomas; Heringa, Minne B.; Hoeng, Julia; de Jong, Wim H.; Kojima, Hajime; Kuehnl, Jochen; Luch, Andreas; Maschmeyer, Ilka; Sakharov, Dmitry; Sips, Adrienne J. A. M.; Steger-Hartmann, Thomas; Tagle, Danilo A.; Tonevitsky, Alexander; Tralau, Tewes; Tsyb, Sergej; van de Stolpe, Anja; Vandebriel, Rob; Vulto, Paul; Wang, Jufeng; Wiest, Joachim; Rodenburg, Marleen; Roth, Adrian

    2017-01-01

    Summary The recent advent of microphysiological systems – microfluidic biomimetic devices that aspire to emulate the biology of human tissues, organs and circulation in vitro – is envisaged to enable a global paradigm shift in drug development. An extraordinary US governmental initiative and various dedicated research programs in Europe and Asia have led recently to the first cutting-edge achievements of human single-organ and multi-organ engineering based on microphysiological systems. The expectation is that test systems established on this basis would model various disease stages, and predict toxicity, immunogenicity, ADME profiles and treatment efficacy prior to clinical testing. Consequently, this technology could significantly affect the way drug substances are developed in the future. Furthermore, microphysiological system-based assays may revolutionize our current global programs of prioritization of hazard characterization for any new substances to be used, for example, in agriculture, food, ecosystems or cosmetics, thus, replacing laboratory animal models used currently. Thirty-five experts from academia, industry and regulatory bodies present here the results of an intensive workshop (held in June 2015, Berlin, Germany). They review the status quo of microphysiological systems available today against industry needs, and assess the broad variety of approaches with fit-for-purpose potential in the drug development cycle. Feasible technical solutions to reach the next levels of human biology in vitro are proposed. Furthermore, key organ-on-a-chip case studies, as well as various national and international programs are highlighted. Finally, a roadmap into the future is outlined, to allow for more predictive and regulatory-accepted substance testing on a global scale. PMID:27180100

  18. Logic-based models in systems biology: a predictive and parameter-free network analysis method.

    Science.gov (United States)

    Wynn, Michelle L; Consul, Nikita; Merajver, Sofia D; Schnell, Santiago

    2012-11-01

    Highly complex molecular networks, which play fundamental roles in almost all cellular processes, are known to be dysregulated in a number of diseases, most notably in cancer. As a consequence, there is a critical need to develop practical methodologies for constructing and analysing molecular networks at a systems level. Mathematical models built with continuous differential equations are an ideal methodology because they can provide a detailed picture of a network's dynamics. To be predictive, however, differential equation models require that numerous parameters be known a priori and this information is almost never available. An alternative dynamical approach is the use of discrete logic-based models that can provide a good approximation of the qualitative behaviour of a biochemical system without the burden of a large parameter space. Despite their advantages, there remains significant resistance to the use of logic-based models in biology. Here, we address some common concerns and provide a brief tutorial on the use of logic-based models, which we motivate with biological examples.

  19. Logic-based models in systems biology: a predictive and parameter-free network analysis method†

    Science.gov (United States)

    Wynn, Michelle L.; Consul, Nikita; Merajver, Sofia D.

    2012-01-01

    Highly complex molecular networks, which play fundamental roles in almost all cellular processes, are known to be dysregulated in a number of diseases, most notably in cancer. As a consequence, there is a critical need to develop practical methodologies for constructing and analysing molecular networks at a systems level. Mathematical models built with continuous differential equations are an ideal methodology because they can provide a detailed picture of a network’s dynamics. To be predictive, however, differential equation models require that numerous parameters be known a priori and this information is almost never available. An alternative dynamical approach is the use of discrete logic-based models that can provide a good approximation of the qualitative behaviour of a biochemical system without the burden of a large parameter space. Despite their advantages, there remains significant resistance to the use of logic-based models in biology. Here, we address some common concerns and provide a brief tutorial on the use of logic-based models, which we motivate with biological examples. PMID:23072820

  20. Biological effects of petroleum hydrocarbons: Predictions of long-term effects and recovery

    International Nuclear Information System (INIS)

    Capuzzo, J.M.

    1990-01-01

    Biological effects of petroleum hydrocarbons on marine organisms and ecosystems are dependent on the persistence and bioavailability of specific hydrocarbons, the ability of organisms to accumulate and metabolize various hydrocarbons, the fate of metabolized products, and the interference of specific hydrocarbons with normal metabolic processes that may alter an organism's chances for survival and reproduction in the environment. In considering the long-term effects of petroleum hydrocarbons on marine ecosystems it is important to ascertain what biological effects may result in subtle ecological changes, changes in community structure and function, and possible impairment of fisheries resources. It is also important to understand which hydrocarbons persist in benthic environments and the sublethal effects that lead to reduced growth, delayed development and reduced reproductive effort, population decline and the loss of that population's function in marine communities. Only through a multi-disciplinary approach to the study of the fate, transport and effects of petroleum hydrocarbons on marine ecosystems will there be a significant improvement in the ability to predict the long-term effects of oil spills and to elucidate the mechanisms of recovery

  1. Prediction of druggable proteins using machine learning and systems biology: a mini-review

    Directory of Open Access Journals (Sweden)

    Gaurav eKandoi

    2015-12-01

    Full Text Available The emergence of -omics technologies has allowed the collection of vast amounts of data on biological systems. Although the pace of such collection has been exponential, the impact of these data remains small on many critical biomedical applications such as drug development. Limited resources, high costs and low hit-to-lead ratio have led researchers to search for more cost effective methodologies. A possible alternative is to incorporate computational methods of potential drug target prediction early during drug discovery workflow. Computational methods based on systems approaches have the advantage of taking into account the global properties of a molecule not limited to its sequence, structure or function. Machine learning techniques are powerful tools that can extract relevant information from massive and noisy data sets. In recent years the scientific community has explored the combined power of these fields to propose increasingly accurate and low cost methods to propose interesting drug targets. In this mini-review, we describe promising approaches based on the simultaneous use of systems biology and machine learning to access gene and protein druggability. Moreover, we discuss the state-of-the-art of this emerging and interdisciplinary field, discussing data sources, algorithms and the performance of the different methodologies. Finally, we indicate interesting avenues of research and some remaining open challenges.

  2. Gauss-Kronrod-Trapezoidal Integration Scheme for Modeling Biological Tissues with Continuous Fiber Distributions

    Science.gov (United States)

    Hou, Chieh; Ateshian, Gerard A.

    2015-01-01

    Fibrous biological tissues may be modeled using a continuous fiber distribution (CFD) to capture tension-compression nonlinearity, anisotropic fiber distributions, and load-induced anisotropy. The CFD framework requires spherical integration of weighted individual fiber responses, with fibers contributing to the stress response only when they are in tension. The common method for performing this integration employs the discretization of the unit sphere into a polyhedron with nearly uniform triangular faces (finite element integration or FEI scheme). Although FEI has proven to be more accurate and efficient than integration using spherical coordinates, it presents three major drawbacks: First, the number of elements on the unit sphere needed to achieve satisfactory accuracy becomes a significant computational cost in a finite element analysis. Second, fibers may not be in tension in some regions on the unit sphere, where the integration becomes a waste. Third, if tensed fiber bundles span a small region compared to the area of the elements on the sphere, a significant discretization error arises. This study presents an integration scheme specialized to the CFD framework, which significantly mitigates the first drawback of the FEI scheme, while eliminating the second and third completely. Here, integration is performed only over the regions of the unit sphere where fibers are in tension. Gauss-Kronrod quadrature is used across latitudes and the trapezoidal scheme across longitudes. Over a wide range of strain states, fiber material properties, and fiber angular distributions, results demonstrate that this new scheme always outperforms FEI, sometimes by orders of magnitude in the number of computational steps and relative accuracy of the stress calculation. PMID:26291492

  3. A Gauss-Kronrod-Trapezoidal integration scheme for modeling biological tissues with continuous fiber distributions.

    Science.gov (United States)

    Hou, Chieh; Ateshian, Gerard A

    2016-01-01

    Fibrous biological tissues may be modeled using a continuous fiber distribution (CFD) to capture tension-compression nonlinearity, anisotropic fiber distributions, and load-induced anisotropy. The CFD framework requires spherical integration of weighted individual fiber responses, with fibers contributing to the stress response only when they are in tension. The common method for performing this integration employs the discretization of the unit sphere into a polyhedron with nearly uniform triangular faces (finite element integration or FEI scheme). Although FEI has proven to be more accurate and efficient than integration using spherical coordinates, it presents three major drawbacks: First, the number of elements on the unit sphere needed to achieve satisfactory accuracy becomes a significant computational cost in a finite element (FE) analysis. Second, fibers may not be in tension in some regions on the unit sphere, where the integration becomes a waste. Third, if tensed fiber bundles span a small region compared to the area of the elements on the sphere, a significant discretization error arises. This study presents an integration scheme specialized to the CFD framework, which significantly mitigates the first drawback of the FEI scheme, while eliminating the second and third completely. Here, integration is performed only over the regions of the unit sphere where fibers are in tension. Gauss-Kronrod quadrature is used across latitudes and the trapezoidal scheme across longitudes. Over a wide range of strain states, fiber material properties, and fiber angular distributions, results demonstrate that this new scheme always outperforms FEI, sometimes by orders of magnitude in the number of computational steps and relative accuracy of the stress calculation.

  4. Validation of model predictions of pore-scale fluid distributions during two-phase flow

    Science.gov (United States)

    Bultreys, Tom; Lin, Qingyang; Gao, Ying; Raeini, Ali Q.; AlRatrout, Ahmed; Bijeljic, Branko; Blunt, Martin J.

    2018-05-01

    Pore-scale two-phase flow modeling is an important technology to study a rock's relative permeability behavior. To investigate if these models are predictive, the calculated pore-scale fluid distributions which determine the relative permeability need to be validated. In this work, we introduce a methodology to quantitatively compare models to experimental fluid distributions in flow experiments visualized with microcomputed tomography. First, we analyzed five repeated drainage-imbibition experiments on a single sample. In these experiments, the exact fluid distributions were not fully repeatable on a pore-by-pore basis, while the global properties of the fluid distribution were. Then two fractional flow experiments were used to validate a quasistatic pore network model. The model correctly predicted the fluid present in more than 75% of pores and throats in drainage and imbibition. To quantify what this means for the relevant global properties of the fluid distribution, we compare the main flow paths and the connectivity across the different pore sizes in the modeled and experimental fluid distributions. These essential topology characteristics matched well for drainage simulations, but not for imbibition. This suggests that the pore-filling rules in the network model we used need to be improved to make reliable predictions of imbibition. The presented analysis illustrates the potential of our methodology to systematically and robustly test two-phase flow models to aid in model development and calibration.

  5. The integral biologically effective dose to predict brain stem toxicity of hypofractionated stereotactic radiotherapy

    International Nuclear Information System (INIS)

    Clark, Brenda G.; Souhami, Luis; Pla, Conrado; Al-Amro, Abdullah S.; Bahary, Jean-Paul; Villemure, Jean-Guy; Caron, Jean-Louis; Olivier, Andre; Podgorsak, Ervin B.

    1998-01-01

    Purpose: The aim of this work was to develop a parameter for use during fractionated stereotactic radiotherapy treatment planning to aid in the determination of the appropriate treatment volume and fractionation regimen that will minimize risk of late damage to normal tissue. Materials and Methods: We have used the linear quadratic model to assess the biologically effective dose at the periphery of stereotactic radiotherapy treatment volumes that impinge on the brain stem. This paper reports a retrospective study of 77 patients with malignant and benign intracranial lesions, treated between 1987 and 1995, with the dynamic rotation technique in 6 fractions over a period of 2 weeks, to a total dose of 42 Gy prescribed at the 90% isodose surface. From differential dose-volume histograms, we evaluated biologically effective dose-volume histograms and obtained an integral biologically-effective dose (IBED) in each case. Results: Of the 77 patients in the study, 36 had target volumes positioned so that the brain stem received more than 1% of the prescribed dose, and 4 of these, all treated for meningioma, developed serious late damage involving the brain stem. Other than type of lesion, the only significant variable was the volume of brain stem exposed. An analysis of the IBEDs received by these 36 patients shows evidence of a threshold value for late damage to the brain stem consistent with similar thresholds that have been determined for external beam radiotherapy. Conclusions: We have introduced a new parameter, the IBED, that may be used to represent the fractional effective dose to structures such as the brain stem that are partially irradiated with stereotactic dose distributions. The IBED is easily calculated prior to treatment and may be used to determine appropriate treatment volumes and fractionation regimens minimizing possible toxicity to normal tissue

  6. The Distributed Biological Observatory (DBO): A Change Detection Array in the Pacific Arctic Region

    Science.gov (United States)

    Grebmeier, J. M.; Moore, S. E.; Cooper, L. W.; Frey, K. E.; Pickart, R. S.

    2012-12-01

    The Pacific region of the Arctic Ocean is experiencing major reductions in seasonal sea ice extent and increases in sea surface temperatures. One of the key uncertainties in this region is how the marine ecosystem will respond to seasonal shifts in the timing of spring sea ice retreat and/or delays in fall sea ice formation. Climate changes are likely to result in shifts in species composition and abundance, northward range expansions, and changes in lower trophic level productivity that can directly cascade and affect the life cycles of higher trophic level organisms. The developing Distributed Biological Observatory (DBO) is composed of focused biological and oceanographic sampling at biological "hot spot" sites for lower and higher trophic organisms on a latitudinal S-to-N array. The DBO is being developed by an international consortium of scientists in the Pacific Arctic as a change detection array to systematically track the broad biological response to sea ice retreat and associated environmental change. Coordinated ship-based observations over various seasons, together with satellite and mooring data collections at the designated sites, can provide an early detection system for biological and ecosystem response to climate warming. The data documenting the importance of these ecosystem "hotspots" provide a growing marine time-series from the northern Bering Sea to Barrow Canyon at the boundary of the Chukchi and Beaufort seas. Results from these studies show spatial changes in carbon production and export to the sediments as indicated by infaunal community composition and biomass, shifts in sediment grain size on a S-to-N latitudinal gradient, and range extensions for lower trophic levels and further northward migration of higher trophic organisms, such as gray whales. There is also direct evidence of negative impacts on ice dependent species, such as walrus and polar bears. As a ramp up to a fully operational observatory, hydrographic transects and select

  7. Prediction future asset price which is non-concordant with the historical distribution

    Science.gov (United States)

    Seong, Ng Yew; Hin, Pooi Ah

    2015-12-01

    This paper attempts to predict the major characteristics of the future asset price which is non-concordant with the distribution estimated from the price today and the prices on a large number of previous days. The three major characteristics of the i-th non-concordant asset price are the length of the interval between the occurrence time of the previous non-concordant asset price and that of the present non-concordant asset price, the indicator which denotes that the non-concordant price is extremely small or large by its values -1 and 1 respectively, and the degree of non-concordance given by the negative logarithm of the probability of the left tail or right tail of which one of the end points is given by the observed future price. The vector of three major characteristics of the next non-concordant price is modelled to be dependent on the vectors corresponding to the present and l - 1 previous non-concordant prices via a 3-dimensional conditional distribution which is derived from a 3(l + 1)-dimensional power-normal mixture distribution. The marginal distribution for each of the three major characteristics can then be derived from the conditional distribution. The mean of the j-th marginal distribution is an estimate of the value of the j-th characteristics of the next non-concordant price. Meanwhile, the 100(α/2) % and 100(1 - α/2) % points of the j-th marginal distribution can be used to form a prediction interval for the j-th characteristic of the next non-concordant price. The performance measures of the above estimates and prediction intervals indicate that the fitted conditional distribution is satisfactory. Thus the incorporation of the distribution of the characteristics of the next non-concordant price in the model for asset price has a good potential of yielding a more realistic model.

  8. Novel Radiobiological Gamma Index for Evaluation of 3-Dimensional Predicted Dose Distribution

    Energy Technology Data Exchange (ETDEWEB)

    Sumida, Iori, E-mail: sumida@radonc.med.osaka-u.ac.jp [Department of Radiation Oncology, Osaka University Graduate School of Medicine, Osaka (Japan); Yamaguchi, Hajime; Kizaki, Hisao; Aboshi, Keiko; Tsujii, Mari; Yoshikawa, Nobuhiko; Yamada, Yuji [Department of Radiation Oncology, NTT West Osaka Hospital, Osaka (Japan); Suzuki, Osamu; Seo, Yuji [Department of Radiation Oncology, Osaka University Graduate School of Medicine, Osaka (Japan); Isohashi, Fumiaki [Department of Radiation Oncology, NTT West Osaka Hospital, Osaka (Japan); Yoshioka, Yasuo [Department of Radiation Oncology, Osaka University Graduate School of Medicine, Osaka (Japan); Ogawa, Kazuhiko [Department of Radiation Oncology, NTT West Osaka Hospital, Osaka (Japan)

    2015-07-15

    Purpose: To propose a gamma index-based dose evaluation index that integrates the radiobiological parameters of tumor control (TCP) and normal tissue complication probabilities (NTCP). Methods and Materials: Fifteen prostate and head and neck (H&N) cancer patients received intensity modulated radiation therapy. Before treatment, patient-specific quality assurance was conducted via beam-by-beam analysis, and beam-specific dose error distributions were generated. The predicted 3-dimensional (3D) dose distribution was calculated by back-projection of relative dose error distribution per beam. A 3D gamma analysis of different organs (prostate: clinical [CTV] and planned target volumes [PTV], rectum, bladder, femoral heads; H&N: gross tumor volume [GTV], CTV, spinal cord, brain stem, both parotids) was performed using predicted and planned dose distributions under 2%/2 mm tolerance and physical gamma passing rate was calculated. TCP and NTCP values were calculated for voxels with physical gamma indices (PGI) >1. We propose a new radiobiological gamma index (RGI) to quantify the radiobiological effects of TCP and NTCP and calculate radiobiological gamma passing rates. Results: The mean RGI gamma passing rates for prostate cases were significantly different compared with those of PGI (P<.03–.001). The mean RGI gamma passing rates for H&N cases (except for GTV) were significantly different compared with those of PGI (P<.001). Differences in gamma passing rates between PGI and RGI were due to dose differences between the planned and predicted dose distributions. Radiobiological gamma distribution was visualized to identify areas where the dose was radiobiologically important. Conclusions: RGI was proposed to integrate radiobiological effects into PGI. This index would assist physicians and medical physicists not only in physical evaluations of treatment delivery accuracy, but also in clinical evaluations of predicted dose distribution.

  9. An algal model for predicting attainment of tiered biological criteria of Maine's streams and rivers

    Science.gov (United States)

    Danielson, Thomas J.; Loftin, Cyndy; Tsomides, Leonidas; DiFranco, Jeanne L.; Connors, Beth; Courtemanch, David L.; Drummond, Francis; Davies, Susan

    2012-01-01

    State water-quality professionals developing new biological assessment methods often have difficulty relating assessment results to narrative criteria in water-quality standards. An alternative to selecting index thresholds arbitrarily is to include the Biological Condition Gradient (BCG) in the development of the assessment method. The BCG describes tiers of biological community condition to help identify and communicate the position of a water body along a gradient of water quality ranging from natural to degraded. Although originally developed for fish and macroinvertebrate communities of streams and rivers, the BCG is easily adapted to other habitats and taxonomic groups. We developed a discriminant analysis model with stream algal data to predict attainment of tiered aquatic-life uses in Maine's water-quality standards. We modified the BCG framework for Maine stream algae, related the BCG tiers to Maine's tiered aquatic-life uses, and identified appropriate algal metrics for describing BCG tiers. Using a modified Delphi method, 5 aquatic biologists independently evaluated algal community metrics for 230 samples from streams and rivers across the state and assigned a BCG tier (1–6) and Maine water quality class (AA/A, B, C, nonattainment of any class) to each sample. We used minimally disturbed reference sites to approximate natural conditions (Tier 1). Biologist class assignments were unanimous for 53% of samples, and 42% of samples differed by 1 class. The biologists debated and developed consensus class assignments. A linear discriminant model built to replicate a priori class assignments correctly classified 95% of 150 samples in the model training set and 91% of 80 samples in the model validation set. Locally derived metrics based on BCG taxon tolerance groupings (e.g., sensitive, intermediate, tolerant) were more effective than were metrics developed in other regions. Adding the algal discriminant model to Maine's existing macroinvertebrate discriminant

  10. Fair Value Versus Historical Cost-Based Valuation for Biological Assets: Predictability of Financial Information

    Directory of Open Access Journals (Sweden)

    Josep M. Argilés

    2011-12-01

    Full Text Available There is an intense debate on the convenience of moving from historical cost (HC toward the fair value (FV principle. The debate and academic research is usually concerned with financial instruments, but the IAS 41 requirement of fair valuation for biological assets brings it into the agricultural domain.This paper performs an empirical study with a sample of Spanish farms valuing biological assets at HC and a sample applying FV, finding no significant differences between both valuation methods to assess future cash flows. However, most tests reveal more predictive power of future earnings under fair valuation of biological assets, which is not explained by differences in volatility of earnings and profitability. The study also evidences the existence of flawed HC accounting practices for biological assets in agriculture, which suggests scarce information content of this valuation method in the predominant small business units existing in the agricultural sector in advanced Western countries.La evolución de la contabilidad desde el coste histórico (CH hacia el valor razonable (VR ha suscitado debates y controversias, tanto en el ámbito profesional, como en el académico. Si bien el debate y los estudios se han referido principalmente a los instrumentos financieros, el requerimiento de la NIC41 de valorar los activos biológicos al VR ha ampliado el debate a la contabilidad agrícola.Este trabajo realiza un estudio empírico mediante una muestra de explotaciones agrícolas españolas que valoran sus activos biológicos al CH y otra que valoran al VR, para comparar el poder predictivo de ambos criterios de valoración. No se encuentran diferencias significativas entre ambos criterios para la predicción de los futuros flujos de tesorería. No obstante, la mayor parte de los tests realizados revelan un mayor poder predictivo de los futuros resultados contables bajo el valor razonable, que no se explica en función de diferencias en la

  11. What are the most crucial soil factors for predicting the distribution of alpine plant species?

    Science.gov (United States)

    Buri, A.; Pinto-Figueroa, E.; Yashiro, E.; Guisan, A.

    2017-12-01

    Nowadays the use of species distribution models (SDM) is common to predict in space and time the distribution of organisms living in the critical zone. The realized environmental niche concept behind the development of SDM imply that many environmental factors must be accounted for simultaneously to predict species distributions. Climatic and topographic factors are often primary included, whereas soil factors are frequently neglected, mainly due to the paucity of soil information available spatially and temporally. Furthermore, among existing studies, most included soil pH only, or few other soil parameters. In this study we aimed at identifying what are the most crucial soil factors for explaining alpine plant distributions and, among those identified, which ones further improve the predictive power of plant SDMs. To test the relative importance of the soil factors, we performed plant SDMs using as predictors 52 measured soil properties of various types such as organic/inorganic compounds, chemical/physical properties, water related variables, mineral composition or grain size distribution. We added them separately to a standard set of topo-climatic predictors (temperature, slope, solar radiation and topographic position). We used ensemble forecasting techniques combining together several predictive algorithms to model the distribution of 116 plant species over 250 sites in the Swiss Alps. We recorded the variable importance for each model and compared the quality of the models including different soil proprieties (one at a time) as predictors to models having only topo-climatic variables as predictors. Results show that 46% of the soil proprieties tested become the second most important variable, after air temperature, to explain spatial distribution of alpine plants species. Moreover, we also assessed that addition of certain soil factors, such as bulk soil water density, could improve over 80% the quality of some plant species models. We confirm that soil p

  12. Efficacy of a composite biological age score to predict ten-year survival among Kansas and Nebraska Mennonites.

    Science.gov (United States)

    Uttley, M; Crawford, M H

    1994-02-01

    In 1980 and 1981 Mennonite descendants of a group of Russian immigrants participated in a multidisciplinary study of biological aging. The Mennonites live in Goessel, Kansas, and Henderson, Nebraska. In 1991 the survival status of the participants was documented by each church secretary. Data are available for 1009 individuals, 177 of whom are now deceased. They ranged from 20 to 95 years in age when the data were collected. Biological ages were computed using a stepwise multiple regression procedure based on 38 variables previously identified as being related to survival, with chronological age as the dependent variable. Standardized residuals place participants in either a predicted-younger or a predicted-older group. The independence of the variables biological age and survival status is tested with the chi-square statistic. The significance of biological age differences between surviving and deceased Mennonites is determined by t test values. The two statistics provide consistent results. Predicted age group classification and survival status are related. The group of deceased participants is generally predicted to be older than the group of surviving participants, although neither statistic is significant for all subgroups of Mennonites. In most cases, however, individuals in the predicted-older groups are at a relatively higher risk of dying compared with those in the predicted-younger groups, although the increased risk is not always significant.

  13. Predicting cycle time distributions for integrated processing workstations : an aggregate modeling approach

    NARCIS (Netherlands)

    Veeger, C.P.L.; Etman, L.F.P.; Lefeber, A.A.J.; Adan, I.J.B.F.; Herk, van J.; Rooda, J.E.

    2011-01-01

    To predict cycle time distributions of integrated processing workstations, detailed simulation models are almost exclusively used; these models require considerable development and maintenance effort. As an alternative, we propose an aggregate model that is a lumped-parameter representation of the

  14. Climate change and plant distribution: local models predict high-elevation persistence

    DEFF Research Database (Denmark)

    Randin, Christophe F.; Engler, Robin; Normand, Signe

    2009-01-01

    Mountain ecosystems will likely be affected by global warming during the 21st century, with substantial biodiversity loss predicted by species distribution models (SDMs). Depending on the geographic extent, elevation range, and spatial resolution of data used in making these models, different rates...

  15. Real-time distributed economic model predictive control for complete vehicle energy management

    NARCIS (Netherlands)

    Romijn, Constantijn; Donkers, Tijs; Kessels, John; Weiland, Siep

    2017-01-01

    In this paper, a real-time distributed economic model predictive control approach for complete vehicle energy management (CVEM) is presented using a receding control horizon in combination with a dual decomposition. The dual decomposition allows the CVEM optimization problem to be solved by solving

  16. A Random Forest Approach to Predict the Spatial Distribution of Sediment Pollution in an Estuarine System

    Science.gov (United States)

    Modeling the magnitude and distribution of sediment-bound pollutants in estuaries is often limited by incomplete knowledge of the site and inadequate sample density. To address these modeling limitations, a decision-support tool framework was conceived that predicts sediment cont...

  17. The predictive skill of species distribution models for plankton in a changing climate

    DEFF Research Database (Denmark)

    Brun, Philipp Georg; Kiørboe, Thomas; Licandro, Priscilla

    2016-01-01

    Statistical species distribution models (SDMs) are increasingly used to project spatial relocations of marine taxa under future climate change scenarios. However, tests of their predictive skill in the real-world are rare. Here, we use data from the Continuous Plankton Recorder program, one...... null models, is essential to assess the robustness of projections of marine planktonic species under climate change...

  18. Predictive analytics for truck arrival time estimation : a field study at a European distribution center

    NARCIS (Netherlands)

    van der Spoel, Sjoerd; Amrit, Chintan Amrit; van Hillegersberg, Jos

    2017-01-01

    Distribution centres (DCs) are the hubs connecting transport streams in the supply chain. The synchronisation of coming and going cargo at a DC requires reliable arrival times. To achieve this, a reliable method to predict arrival times is needed. A literature review was performed to find the

  19. Comments on the Redshift Distribution of 44,200 SDSS Quasars: Evidence for Predicted Preferred Redshifts?

    OpenAIRE

    Bell, M. B.

    2004-01-01

    A Sloan Digital Sky Survey (SDSS) source sample containing 44,200 quasar redshifts is examined. Although arguments have been put forth to explain some of the structure observed in the redshift distribution, it is argued here that this structure may just as easily be explained by the presence of previously predicted preferred redshifts.

  20. Predicting the spatial distribution of leaf litterfall in a mixed deciduous forest

    NARCIS (Netherlands)

    Staelens, Jeroen; Nachtergale, Lieven; Luyssaert, Sebastiaan

    2004-01-01

    An accurate prediction of the spatial distribution of litterfall can improve insight in the interaction between the canopy layer and forest floor characteristics, which is a key feature in forest nutrient cycling. Attempts to model the spatial variability of litterfall have been made across forest

  1. Prediction of thermal coagulation from the instantaneous strain distribution induced by high-intensity focused ultrasound

    Science.gov (United States)

    Iwasaki, Ryosuke; Takagi, Ryo; Tomiyasu, Kentaro; Yoshizawa, Shin; Umemura, Shin-ichiro

    2017-07-01

    The targeting of the ultrasound beam and the prediction of thermal lesion formation in advance are the requirements for monitoring high-intensity focused ultrasound (HIFU) treatment with safety and reproducibility. To visualize the HIFU focal zone, we utilized an acoustic radiation force impulse (ARFI) imaging-based method. After inducing displacements inside tissues with pulsed HIFU called the push pulse exposure, the distribution of axial displacements started expanding and moving. To acquire RF data immediately after and during the HIFU push pulse exposure to improve prediction accuracy, we attempted methods using extrapolation estimation and applying HIFU noise elimination. The distributions going back in the time domain from the end of push pulse exposure are in good agreement with tissue coagulation at the center. The results suggest that the proposed focal zone visualization employing pulsed HIFU entailing the high-speed ARFI imaging method is useful for the prediction of thermal coagulation in advance.

  2. Multi-scale approach for predicting fish species distributions across coral reef seascapes.

    Directory of Open Access Journals (Sweden)

    Simon J Pittman

    Full Text Available Two of the major limitations to effective management of coral reef ecosystems are a lack of information on the spatial distribution of marine species and a paucity of data on the interacting environmental variables that drive distributional patterns. Advances in marine remote sensing, together with the novel integration of landscape ecology and advanced niche modelling techniques provide an unprecedented opportunity to reliably model and map marine species distributions across many kilometres of coral reef ecosystems. We developed a multi-scale approach using three-dimensional seafloor morphology and across-shelf location to predict spatial distributions for five common Caribbean fish species. Seascape topography was quantified from high resolution bathymetry at five spatial scales (5-300 m radii surrounding fish survey sites. Model performance and map accuracy was assessed for two high performing machine-learning algorithms: Boosted Regression Trees (BRT and Maximum Entropy Species Distribution Modelling (MaxEnt. The three most important predictors were geographical location across the shelf, followed by a measure of topographic complexity. Predictor contribution differed among species, yet rarely changed across spatial scales. BRT provided 'outstanding' model predictions (AUC = >0.9 for three of five fish species. MaxEnt provided 'outstanding' model predictions for two of five species, with the remaining three models considered 'excellent' (AUC = 0.8-0.9. In contrast, MaxEnt spatial predictions were markedly more accurate (92% map accuracy than BRT (68% map accuracy. We demonstrate that reliable spatial predictions for a range of key fish species can be achieved by modelling the interaction between the geographical location across the shelf and the topographic heterogeneity of seafloor structure. This multi-scale, analytic approach is an important new cost-effective tool to accurately delineate essential fish habitat and support

  3. Preliminary assessment of the interaction of introduced biological agents with biofilms in water distribution systems.

    Energy Technology Data Exchange (ETDEWEB)

    Sinclair, Michael B.; Caldwell, Sara; Jones, Howland D. T.; Altman, Susan Jeanne; Souza, Caroline Ann; McGrath, Lucas K.

    2005-12-01

    Basic research is needed to better understand the potential risk of dangerous biological agents that are unintentionally or intentionally introduced into a water distribution system. We report on our capabilities to conduct such studies and our preliminary investigations. In 2004, the Biofilms Laboratory was initiated for the purpose of conducting applied research related to biofilms with a focus on application, application testing and system-scale research. Capabilities within the laboratory are the ability to grow biofilms formed from known bacteria or biofilms from drinking water. Biofilms can be grown quickly in drip-flow reactors or under conditions more analogous to drinking-water distribution systems in annular reactors. Biofilms can be assessed through standard microbiological techniques (i .e, aerobic plate counts) or with various visualization techniques including epifluorescent and confocal laser scanning microscopy and confocal fluorescence hyperspectral imaging with multivariate analysis. We have demonstrated the ability to grow reproducible Pseudomonas fluorescens biofilms in the annular reactor with plate counts on the order of 10{sup 5} and 10{sup 6} CFU/cm{sup 2}. Stationary phase growth is typically reached 5 to 10 days after inoculation. We have also conducted a series of pathogen-introduction experiments, where we have observed that both polystyrene microspheres and Bacillus cereus (as a surrogate for B. anthracis) stay incorporated in the biofilms for the duration of our experiments, which lasted as long as 36 days. These results indicated that biofilms may act as a safe harbor for bio-pathogens in drinking water systems, making it difficult to decontaminate the systems.

  4. Predicting Posttraumatic Stress Symptom Prevalence and Local Distribution after an Earthquake with Scarce Data.

    Science.gov (United States)

    Dussaillant, Francisca; Apablaza, Mauricio

    2017-08-01

    After a major earthquake, the assignment of scarce mental health emergency personnel to different geographic areas is crucial to the effective management of the crisis. The scarce information that is available in the aftermath of a disaster may be valuable in helping predict where are the populations that are in most need. The objectives of this study were to derive algorithms to predict posttraumatic stress (PTS) symptom prevalence and local distribution after an earthquake and to test whether there are algorithms that require few input data and are still reasonably predictive. A rich database of PTS symptoms, informed after Chile's 2010 earthquake and tsunami, was used. Several model specifications for the mean and centiles of the distribution of PTS symptoms, together with posttraumatic stress disorder (PTSD) prevalence, were estimated via linear and quantile regressions. The models varied in the set of covariates included. Adjusted R2 for the most liberal specifications (in terms of numbers of covariates included) ranged from 0.62 to 0.74, depending on the outcome. When only including peak ground acceleration (PGA), poverty rate, and household damage in linear and quadratic form, predictive capacity was still good (adjusted R2 from 0.59 to 0.67 were obtained). Information about local poverty, household damage, and PGA can be used as an aid to predict PTS symptom prevalence and local distribution after an earthquake. This can be of help to improve the assignment of mental health personnel to the affected localities. Dussaillant F , Apablaza M . Predicting posttraumatic stress symptom prevalence and local distribution after an earthquake with scarce data. Prehosp Disaster Med. 2017;32(4):357-367.

  5. Analysis and evaluation of forecasting methods and tools to predict future demand for secondary chemical-biological configuration items

    OpenAIRE

    Ritchey, Chris D.

    2013-01-01

    Approved for public release; distribution is unlimited As the Engineering Support Activity (ESA) for numerous consumable Chemical Biological items managed by the Defense Logistics Agency (DLA), Edgewood Chemical Biological Center (ECBC) must be able to complete reviews of all procurement packages within 15 calendar days. With such little lead time, it would be very beneficial if ECBC had the ability to forecast when DLA procurement actions will occur. This thesis presents an evaluation of ...

  6. Predicting the probability of slip in gait: methodology and distribution study.

    Science.gov (United States)

    Gragg, Jared; Yang, James

    2016-01-01

    The likelihood of a slip is related to the available and required friction for a certain activity, here gait. Classical slip and fall analysis presumed that a walking surface was safe if the difference between the mean available and required friction coefficients exceeded a certain threshold. Previous research was dedicated to reformulating the classical slip and fall theory to include the stochastic variation of the available and required friction when predicting the probability of slip in gait. However, when predicting the probability of a slip, previous researchers have either ignored the variation in the required friction or assumed the available and required friction to be normally distributed. Also, there are no published results that actually give the probability of slip for various combinations of required and available frictions. This study proposes a modification to the equation for predicting the probability of slip, reducing the previous equation from a double-integral to a more convenient single-integral form. Also, a simple numerical integration technique is provided to predict the probability of slip in gait: the trapezoidal method. The effect of the random variable distributions on the probability of slip is also studied. It is shown that both the required and available friction distributions cannot automatically be assumed as being normally distributed. The proposed methods allow for any combination of distributions for the available and required friction, and numerical results are compared to analytical solutions for an error analysis. The trapezoidal method is shown to be highly accurate and efficient. The probability of slip is also shown to be sensitive to the input distributions of the required and available friction. Lastly, a critical value for the probability of slip is proposed based on the number of steps taken by an average person in a single day.

  7. A Popularity Based Prediction and Data Redistribution Tool for ATLAS Distributed Data Management

    CERN Document Server

    Beermann, T; The ATLAS collaboration; Maettig, P

    2014-01-01

    This paper presents a system to predict future data popularity for data-intensive systems, such as ATLAS distributed data management (DDM). Using these predictions it is possible to make a better distribution of data, helping to reduce the waiting time for jobs using with this data. This system is based on a tracer infrastructure that is able to monitor and store historical data accesses and which is used to create popularity reports. These reports provide detailed summaries about data accesses in the past, including information about the accessed files, the involved users and the sites. From this past data it is possible to then make near-term forecasts for data popularity in the future. The prediction system introduced in this paper makes use of both simple prediction methods as well as predictions made by neural networks. The best prediction method is dependent on the type of data and the data is carefully filtered for use in either system. The second part of the paper introduces a system that effectively ...

  8. Effects of the infectious period distribution on predicted transitions in childhood disease dynamics.

    Science.gov (United States)

    Krylova, Olga; Earn, David J D

    2013-07-06

    The population dynamics of infectious diseases occasionally undergo rapid qualitative changes, such as transitions from annual to biennial cycles or to irregular dynamics. Previous work, based on the standard seasonally forced 'susceptible-exposed-infectious-removed' (SEIR) model has found that transitions in the dynamics of many childhood diseases result from bifurcations induced by slow changes in birth and vaccination rates. However, the standard SEIR formulation assumes that the stage durations (latent and infectious periods) are exponentially distributed, whereas real distributions are narrower and centred around the mean. Much recent work has indicated that realistically distributed stage durations strongly affect the dynamical structure of seasonally forced epidemic models. We investigate whether inferences drawn from previous analyses of transitions in patterns of measles dynamics are robust to the shapes of the stage duration distributions. As an illustrative example, we analyse measles dynamics in New York City from 1928 to 1972. We find that with a fixed mean infectious period in the susceptible-infectious-removed (SIR) model, the dynamical structure and predicted transitions vary substantially as a function of the shape of the infectious period distribution. By contrast, with fixed mean latent and infectious periods in the SEIR model, the shapes of the stage duration distributions have a less dramatic effect on model dynamical structure and predicted transitions. All these results can be understood more easily by considering the distribution of the disease generation time as opposed to the distributions of individual disease stages. Numerical bifurcation analysis reveals that for a given mean generation time the dynamics of the SIR and SEIR models for measles are nearly equivalent and are insensitive to the shapes of the disease stage distributions.

  9. Morphology, Diet Composition, Distribution and Nesting Biology of Four Lark Species in Mongolia

    Directory of Open Access Journals (Sweden)

    Galbadrakh Mainjargal

    2013-12-01

    Full Text Available We aimed to enhance existing knowledge of four lark species (Mongolian lark , Horned lark, Eurasian skylark, and Lesser short-toed lark, with respect to nesting biology, distribution, and diet, using long-term dataset collected during 2000–2012. Nest and egg measurements substantially varied among species. For pooled data across species, the clutch size averaged 3.72 ± 1.13 eggs and did not differ among larks. Body mass of nestlings increased signi fi cantly with age at weighing. Daily increase in body mass of lark nestlings ranged between 3.09 and 3.89 gram per day. Unsurprisingly, the majority of lark locations occurred in steppe ecosystems, followed by human created systems; whereas only 1.8% of the pooled locations across species were observed in forest ecosystem. Diet composition did not vary among species in the proportions of major food categories consumed. The most commonly occurring food items were invertebrates and frequently consumed were being beetles (e.g. Coleoptera: Carabidae, Scarabaeidae, and Curculionidae and grasshoppers (e.g. Orthoptera: Acrididae, and their occurrences accounted for 63.7% of insect related food items. Among the fi ve morphological traits we measured, there were signi fi cant differences in wing span, body mass, bill, and tarsus; however tail lengths did not differ across four species.

  10. Biological distribution of iodo-allyl Gabapentin and iodo-Gabapentin

    International Nuclear Information System (INIS)

    Akat, H.; Yildirim, Y.; Balcan, M.; Yurt Lambrecht, F.; Yilmaz, O.; Duman, Y.

    2008-01-01

    Gabapentin (GBP) is an anticonvulsant and is widely used in the treatment of epilepsy. In this study, GBP and an allyl derivative of GBP were radioiodinated with 131 I using the iodogen method; then their radiopharmaceutical potential in rats and rabbits was investigated. The radiochemical purity of 131 I-GBP and its derivatives was determined by RTLC. The labeling yield was 95±2%. Biological evaluation was performed in normal rats and rabbits. Labeled compounds were intravenously injected into two rabbits via the ear vein after anesthetizing. The dynamic and static scintigrams were obtained using a gamma camera at different time. Then the labeled compounds were administered intravenously into the rats. The distribution was studied by counting the radioactivity in the removed organs. The results of biodistribution in the rats showed the clearance of 131 IALGBP was faster than 131 I-GBP. On the other hand, the uptake of 131 I-ALGBP in the brain was higher than 131 I-GBP at 60 minutes. (author)

  11. The preparation of 125I-β-CIT and its biological distribution in animal

    International Nuclear Information System (INIS)

    Sun Wenshan; Liu Zhenguo; Shen Minghua; Qian Juan; Li Peiyong; Zhu Chengmo; Chen Shengdi

    2000-01-01

    Objective: To prepare and label the 125 I-β-CIT and study its biological distribution in animal. Methods: 125 I-β-CIT was prepared by the peracetic acid method and the chloramine-T method, and dopamine transporter (DAT) binding properties of 125 I-β-CIT were examined by in vivo biodistribution and inhibition studies in mice and whole body autoradiography in rats. Results: The radiolabelling yields of the peracetic acid and the chloramine-T methods were (53.4 +- 7.9)% and (88.4 +- 3.49)%, respectively. Following intravenous injection in mice, 125 I-β-CIT showed high accumulation in striatum, time to peak level uptake was 2 h after injection. GBR12909 significantly inhibited 125 I-β-CIT binding in striatum, while clomipramine significantly inhibited 125 I-β-CIT binding in hippocampus and cerebral cortex. The rat whole body autoradiography showed that the clearance of the tracer occurred through the hepatobiliary route. Conclusions: The results indicate β-CIT is an agent suitable for DAT imaging and can be used for the study of Parkinson's disease

  12. Melatonin Distribution Reveals Clues to Its Biological Significance in Basal Metazoans

    Science.gov (United States)

    Roopin, Modi; Levy, Oren

    2012-01-01

    Although nearly ubiquitous in nature, the precise biological significance of endogenous melatonin is poorly understood in phylogenetically basal taxa. In the present work, we describe insights into the functional role of melatonin at the most “basal” level of metazoan evolution. Hitherto unknown morphological determinants of melatonin distribution were evaluated in Nematostella vectensis by detecting melatonin immunoreactivity and examining the spatial gene expression patterns of putative melatonin biosynthetic and receptor elements that are located at opposing ends of the melatonin signaling pathway. Immuno-melatonin profiling indicated an elaborate interaction with reproductive tissues, reinforcing previous conjectures of a melatonin-responsive component in anthozoan reproduction. In situ hybridization (ISH) to putative melatonin receptor elements highlighted the possibility that the bioregulatory effects of melatonin in anthozoan reproduction may be mediated by interactions with membrane receptors, as in higher vertebrates. Another intriguing finding of the present study pertains to the prevalence of melatonin in centralized nervous structures. This pattern may be of great significance given that it 1) identifies an ancestral association between melatonin and key neuronal components and 2) potentially implies that certain effects of melatonin in basal species may be spread widely by regionalized nerve centers. PMID:23300630

  13. Measurements and predictions of the air distribution systems in high compute density (Internet) data centers

    Energy Technology Data Exchange (ETDEWEB)

    Cho, Jinkyun [HIMEC (Hanil Mechanical Electrical Consultants) Ltd., Seoul 150-103 (Korea); Department of Architectural Engineering, Yonsei University, Seoul 120-749 (Korea); Lim, Taesub; Kim, Byungseon Sean [Department of Architectural Engineering, Yonsei University, Seoul 120-749 (Korea)

    2009-10-15

    When equipment power density increases, a critical goal of a data center cooling system is to separate the equipment exhaust air from the equipment intake air in order to prevent the IT server from overheating. Cooling systems for data centers are primarily differentiated according to the way they distribute air. The six combinations of flooded and locally ducted air distribution make up the vast majority of all installations, except fully ducted air distribution methods. Once the air distribution system (ADS) is selected, there are other elements that must be integrated into the system design. In this research, the design parameters and IT environmental aspects of the cooling system were studied with a high heat density data center. CFD simulation analysis was carried out in order to compare the heat removal efficiencies of various air distribution systems. The IT environment of an actual operating data center is measured to validate a model for predicting the effect of different air distribution systems. A method for planning and design of the appropriate air distribution system is described. IT professionals versed in precision air distribution mechanisms, components, and configurations can work more effectively with mechanical engineers to ensure the specification and design of optimized cooling solutions. (author)

  14. Knowledge-based prediction of three-dimensional dose distributions for external beam radiotherapy

    Energy Technology Data Exchange (ETDEWEB)

    Shiraishi, Satomi; Moore, Kevin L., E-mail: kevinmoore@ucsd.edu [Department of Radiation Medicine and Applied Sciences, University of California, San Diego, La Jolla, California 92093 (United States)

    2016-01-15

    Purpose: To demonstrate knowledge-based 3D dose prediction for external beam radiotherapy. Methods: Using previously treated plans as training data, an artificial neural network (ANN) was trained to predict a dose matrix based on patient-specific geometric and planning parameters, such as the closest distance (r) to planning target volume (PTV) and organ-at-risks (OARs). Twenty-three prostate and 43 stereotactic radiosurgery/radiotherapy (SRS/SRT) cases with at least one nearby OAR were studied. All were planned with volumetric-modulated arc therapy to prescription doses of 81 Gy for prostate and 12–30 Gy for SRS. Using these clinically approved plans, ANNs were trained to predict dose matrix and the predictive accuracy was evaluated using the dose difference between the clinical plan and prediction, δD = D{sub clin} − D{sub pred}. The mean (〈δD{sub r}〉), standard deviation (σ{sub δD{sub r}}), and their interquartile range (IQR) for the training plans were evaluated at a 2–3 mm interval from the PTV boundary (r{sub PTV}) to assess prediction bias and precision. Initially, unfiltered models which were trained using all plans in the cohorts were created for each treatment site. The models predict approximately the average quality of OAR sparing. Emphasizing a subset of plans that exhibited superior to the average OAR sparing during training, refined models were created to predict high-quality rectum sparing for prostate and brainstem sparing for SRS. Using the refined model, potentially suboptimal plans were identified where the model predicted further sparing of the OARs was achievable. Replans were performed to test if the OAR sparing could be improved as predicted by the model. Results: The refined models demonstrated highly accurate dose distribution prediction. For prostate cases, the average prediction bias for all voxels irrespective of organ delineation ranged from −1% to 0% with maximum IQR of 3% over r{sub PTV} ∈ [ − 6, 30] mm. The

  15. Knowledge-based prediction of three-dimensional dose distributions for external beam radiotherapy

    International Nuclear Information System (INIS)

    Shiraishi, Satomi; Moore, Kevin L.

    2016-01-01

    Purpose: To demonstrate knowledge-based 3D dose prediction for external beam radiotherapy. Methods: Using previously treated plans as training data, an artificial neural network (ANN) was trained to predict a dose matrix based on patient-specific geometric and planning parameters, such as the closest distance (r) to planning target volume (PTV) and organ-at-risks (OARs). Twenty-three prostate and 43 stereotactic radiosurgery/radiotherapy (SRS/SRT) cases with at least one nearby OAR were studied. All were planned with volumetric-modulated arc therapy to prescription doses of 81 Gy for prostate and 12–30 Gy for SRS. Using these clinically approved plans, ANNs were trained to predict dose matrix and the predictive accuracy was evaluated using the dose difference between the clinical plan and prediction, δD = D clin − D pred . The mean (〈δD r 〉), standard deviation (σ δD r ), and their interquartile range (IQR) for the training plans were evaluated at a 2–3 mm interval from the PTV boundary (r PTV ) to assess prediction bias and precision. Initially, unfiltered models which were trained using all plans in the cohorts were created for each treatment site. The models predict approximately the average quality of OAR sparing. Emphasizing a subset of plans that exhibited superior to the average OAR sparing during training, refined models were created to predict high-quality rectum sparing for prostate and brainstem sparing for SRS. Using the refined model, potentially suboptimal plans were identified where the model predicted further sparing of the OARs was achievable. Replans were performed to test if the OAR sparing could be improved as predicted by the model. Results: The refined models demonstrated highly accurate dose distribution prediction. For prostate cases, the average prediction bias for all voxels irrespective of organ delineation ranged from −1% to 0% with maximum IQR of 3% over r PTV ∈ [ − 6, 30] mm. The average prediction error was less

  16. Predicting distribution of Aedes aegypti and Culex pipiens complex, potential vectors of Rift Valley fever virus in relation to disease epidemics in East Africa

    Directory of Open Access Journals (Sweden)

    Clement Nyamunura Mweya

    2013-10-01

    Full Text Available Background: The East African region has experienced several Rift Valley fever (RVF outbreaks since the 1930s. The objective of this study was to identify distributions of potential disease vectors in relation to disease epidemics. Understanding disease vector potential distributions is a major concern for disease transmission dynamics. Methods: Diverse ecological niche modelling techniques have been developed for this purpose: we present a maximum entropy (Maxent approach for estimating distributions of potential RVF vectors in un-sampled areas in East Africa. We modelled the distribution of two species of mosquitoes (Aedes aegypti and Culex pipiens complex responsible for potential maintenance and amplification of the virus, respectively. Predicted distributions of environmentally suitable areas in East Africa were based on the presence-only occurrence data derived from our entomological study in Ngorongoro District in northern Tanzania. Results: Our model predicted potential suitable areas with high success rates of 90.9% for A. aegypti and 91.6% for C. pipiens complex. Model performance was statistically significantly better than random for both species. Most suitable sites for the two vectors were predicted in central and northwestern Tanzania with previous disease epidemics. Other important risk areas include western Lake Victoria, northern parts of Lake Malawi, and the Rift Valley region of Kenya. Conclusion: Findings from this study show distributions of vectors had biological and epidemiological significance in relation to disease outbreak hotspots, and hence provide guidance for the selection of sampling areas for RVF vectors during inter-epidemic periods.

  17. Predicting distribution of Aedes aegypti and Culex pipiens complex, potential vectors of Rift Valley fever virus in relation to disease epidemics in East Africa.

    Science.gov (United States)

    Mweya, Clement Nyamunura; Kimera, Sharadhuli Iddi; Kija, John Bukombe; Mboera, Leonard E G

    2013-01-01

    The East African region has experienced several Rift Valley fever (RVF) outbreaks since the 1930s. The objective of this study was to identify distributions of potential disease vectors in relation to disease epidemics. Understanding disease vector potential distributions is a major concern for disease transmission dynamics. DIVERSE ECOLOGICAL NICHE MODELLING TECHNIQUES HAVE BEEN DEVELOPED FOR THIS PURPOSE: we present a maximum entropy (Maxent) approach for estimating distributions of potential RVF vectors in un-sampled areas in East Africa. We modelled the distribution of two species of mosquitoes (Aedes aegypti and Culex pipiens complex) responsible for potential maintenance and amplification of the virus, respectively. Predicted distributions of environmentally suitable areas in East Africa were based on the presence-only occurrence data derived from our entomological study in Ngorongoro District in northern Tanzania. Our model predicted potential suitable areas with high success rates of 90.9% for A. aegypti and 91.6% for C. pipiens complex. Model performance was statistically significantly better than random for both species. Most suitable sites for the two vectors were predicted in central and northwestern Tanzania with previous disease epidemics. Other important risk areas include western Lake Victoria, northern parts of Lake Malawi, and the Rift Valley region of Kenya. Findings from this study show distributions of vectors had biological and epidemiological significance in relation to disease outbreak hotspots, and hence provide guidance for the selection of sampling areas for RVF vectors during inter-epidemic periods.

  18. Spatial distribution of common Minke whale (Balaenoptera acutorostrata) as an indication of a biological hotspot in the East Sea

    Science.gov (United States)

    Lee, Dasom; An, Yong Rock; Park, Kyum Joon; Kim, Hyun Woo; Lee, Dabin; Joo, Hui Tae; Oh, Young Geun; Kim, Su Min; Kang, Chang Keun; Lee, Sang Heon

    2017-09-01

    The minke whale (Balaenoptera acutorostrata) is the most common baleen whale among several marine mammal species observed in Korea. Since a high concentrated condition of prey to whales can be obtained by physical structures, the foraging whale distribution can be an indicator of biological hotspot. Our main objective is verifying the coastal upwelling-southwestern East Sea as a productive biological hotspot based on the geographical distribution of minke whales. Among the cetacean research surveys of the National Institute of Fisheries Science since 1999, 9 years data for the minke whales available in the East Sea were used for this study. The regional primary productivity derived from Moderate-Resolution Imaging Spectroradiometer (MODIS) was used for a proxy of biological productivity. Minke whales observed during the sighting surveys were mostly concentrated in May and found mostly (approximately 70%) in the southwestern coastal areas (whales was found in recent years, which indicate that the major habitats of mink whales have been shifted into the north of the common coastal upwelling regions. This is consistent with the recently reported unprecedented coastal upwelling in the mid-eastern coast of Korea. Based on high phytoplankton productivity and high distribution of minke whales, the southwestern coastal regions can be considered as one of biological hotspots in the East Sea. These regions are important for ecosystem dynamics and the population biology of top marine predators, especially migratory whales and needed to be carefully managed from a resource management perspective.

  19. Study (Prediction of Main Pipes Break Rates in Water Distribution Systems Using Intelligent and Regression Methods

    Directory of Open Access Journals (Sweden)

    Massoud Tabesh

    2011-07-01

    Full Text Available Optimum operation of water distribution networks is one of the priorities of sustainable development of water resources, considering the issues of increasing efficiency and decreasing the water losses. One of the key subjects in optimum operational management of water distribution systems is preparing rehabilitation and replacement schemes, prediction of pipes break rate and evaluation of their reliability. Several approaches have been presented in recent years regarding prediction of pipe failure rates which each one requires especial data sets. Deterministic models based on age and deterministic multi variables and stochastic group modeling are examples of the solutions which relate pipe break rates to parameters like age, material and diameters. In this paper besides the mentioned parameters, more factors such as pipe depth and hydraulic pressures are considered as well. Then using multi variable regression method, intelligent approaches (Artificial neural network and neuro fuzzy models and Evolutionary polynomial Regression method (EPR pipe burst rate are predicted. To evaluate the results of different approaches, a case study is carried out in a part ofMashhadwater distribution network. The results show the capability and advantages of ANN and EPR methods to predict pipe break rates, in comparison with neuro fuzzy and multi-variable regression methods.

  20. Life prediction for white OLED based on LSM under lognormal distribution

    Science.gov (United States)

    Zhang, Jianping; Liu, Fang; Liu, Yu; Wu, Helen; Zhu, Wenqing; Wu, Wenli; Wu, Liang

    2012-09-01

    In order to acquire the reliability information of White Organic Light Emitting Display (OLED), three groups of OLED constant stress accelerated life tests (CSALTs) were carried out to obtain failure data of samples. Lognormal distribution function was applied to describe OLED life distribution, and the accelerated life equation was determined by Least square method (LSM). The Kolmogorov-Smirnov test was performed to verify whether the white OLED life meets lognormal distribution or not. Author-developed software was employed to predict the average life and the median life. The numerical results indicate that the white OLED life submits to lognormal distribution, and that the accelerated life equation meets inverse power law completely. The estimated life information of the white OLED provides manufacturers and customers with important guidelines.

  1. Predicting moisture content and density distribution of Scots pine by microwave scanning of sawn timber

    International Nuclear Information System (INIS)

    Johansson, J.; Hagman, O.; Fjellner, B.A.

    2003-01-01

    This study was carried out to investigate the possibility of calibrating a prediction model for the moisture content and density distribution of Scots pine (Pinus sylvestris) using microwave sensors. The material was initially of green moisture content and was thereafter dried in several steps to zero moisture content. At each step, all the pieces were weighed, scanned with a microwave sensor (Satimo 9,4GHz), and computed tomography (CT)-scanned with a medical CT scanner (Siemens Somatom AR.T.). The output variables from the microwave sensor were used as predictors, and CT images that correlated with known moisture content were used as response variables. Multivariate models to predict average moisture content and density were calibrated using the partial least squares (PLS) regression. The models for average moisture content and density were applied at the pixel level, and the distribution was visualized. The results show that it is possible to predict both moisture content distribution and density distribution with high accuracy using microwave sensors. (author)

  2. Characterizing and predicting the distribution of Baltic Sea flounder (Platichthys flesus) during the spawning season

    Science.gov (United States)

    Orio, Alessandro; Bergström, Ulf; Casini, Michele; Erlandsson, Mårten; Eschbaum, Redik; Hüssy, Karin; Lehmann, Andreas; Ložys, Linas; Ustups, Didzis; Florin, Ann-Britt

    2017-08-01

    Identification of essential fish habitats (EFH), such as spawning habitats, is important for nature conservation, sustainable fisheries management and marine spatial planning. Two sympatric flounder (Platichthys flesus) ecotypes are present in the Baltic Sea, pelagic and demersal spawning flounder, both displaying ecological and physiological adaptations to the low-salinity environment of this young inland sea. In this study we have addressed three main research questions: 1) What environmental conditions characterize the spatial distribution and abundance of adult flounder during the spawning season? 2) What are the main factors defining the habitats of the two flounder ecotypes during the spawning season? 3) Where are the potential spawning areas of flounder? We modelled catch per unit of effort (CPUE) of flounder from gillnet surveys conducted over the southern and central Baltic Sea in the spring of 2014 and 2015 using generalized additive models. A general model included all the stations fished during the survey while two other models, one for the demersal and one for the pelagic spawning flounder, included only the stations where each flounder ecotype should dominate. The general model captured distinct ecotype-specific signals as it identified dual salinity and water depth responses. The model for the demersal spawning flounder revealed a negative relation with the abundance of round goby (Neogobius melanostomus) and a positive relation with Secchi depth and cod abundance. Vegetation and substrate did not play an important role in the choice of habitat for the demersal ecotype. The model for the pelagic spawning flounder showed a negative relation with temperature and bottom current and a positive relation with salinity. Spatial predictions of potential spawning areas of flounder showed a decrease in habitat availability for the pelagic spawning flounder over the last 20 years in the central part of the Baltic Sea, which may explain part of the observed

  3. Do abundance distributions and species aggregation correctly predict macroecological biodiversity patterns in tropical forests?

    Science.gov (United States)

    Wiegand, Thorsten; Lehmann, Sebastian; Huth, Andreas; Fortin, Marie‐Josée

    2016-01-01

    Abstract Aim It has been recently suggested that different ‘unified theories of biodiversity and biogeography’ can be characterized by three common ‘minimal sufficient rules’: (1) species abundance distributions follow a hollow curve, (2) species show intraspecific aggregation, and (3) species are independently placed with respect to other species. Here, we translate these qualitative rules into a quantitative framework and assess if these minimal rules are indeed sufficient to predict multiple macroecological biodiversity patterns simultaneously. Location Tropical forest plots in Barro Colorado Island (BCI), Panama, and in Sinharaja, Sri Lanka. Methods We assess the predictive power of the three rules using dynamic and spatial simulation models in combination with census data from the two forest plots. We use two different versions of the model: (1) a neutral model and (2) an extended model that allowed for species differences in dispersal distances. In a first step we derive model parameterizations that correctly represent the three minimal rules (i.e. the model quantitatively matches the observed species abundance distribution and the distribution of intraspecific aggregation). In a second step we applied the parameterized models to predict four additional spatial biodiversity patterns. Results Species‐specific dispersal was needed to quantitatively fulfil the three minimal rules. The model with species‐specific dispersal correctly predicted the species–area relationship, but failed to predict the distance decay, the relationship between species abundances and aggregations, and the distribution of a spatial co‐occurrence index of all abundant species pairs. These results were consistent over the two forest plots. Main conclusions The three ‘minimal sufficient’ rules only provide an incomplete approximation of the stochastic spatial geometry of biodiversity in tropical forests. The assumption of independent interspecific placements is most

  4. Improved Predictions of the Geographic Distribution of Invasive Plants Using Climatic Niche Models

    Science.gov (United States)

    Ramírez-Albores, Jorge E.; Bustamante, Ramiro O.

    2016-01-01

    Climatic niche models for invasive plants are usually constructed with occurrence records taken from literature and collections. Because these data neither discriminate among life-cycle stages of plants (adult or juvenile) nor the origin of individuals (naturally established or man-planted), the resulting models may mispredict the distribution ranges of these species. We propose that more accurate predictions could be obtained by modelling climatic niches with data of naturally established individuals, particularly with occurrence records of juvenile plants because this would restrict the predictions of models to those sites where climatic conditions allow the recruitment of the species. To test this proposal, we focused on the Peruvian peppertree (Schinus molle), a South American species that has largely invaded Mexico. Three climatic niche models were constructed for this species using high-resolution dataset gathered in the field. The first model included all occurrence records, irrespective of the life-cycle stage or origin of peppertrees (generalized niche model). The second model only included occurrence records of naturally established mature individuals (adult niche model), while the third model was constructed with occurrence records of naturally established juvenile plants (regeneration niche model). When models were compared, the generalized climatic niche model predicted the presence of peppertrees in sites located farther beyond the climatic thresholds that naturally established individuals can tolerate, suggesting that human activities influence the distribution of this invasive species. The adult and regeneration climatic niche models concurred in their predictions about the distribution of peppertrees, suggesting that naturally established adult trees only occur in sites where climatic conditions allow the recruitment of juvenile stages. These results support the proposal that climatic niches of invasive plants should be modelled with data of

  5. The Density Functional Theory of Flies: Predicting distributions of interacting active organisms

    Science.gov (United States)

    Kinkhabwala, Yunus; Valderrama, Juan; Cohen, Itai; Arias, Tomas

    On October 2nd, 2016, 52 people were crushed in a stampede when a crowd panicked at a religious gathering in Ethiopia. The ability to predict the state of a crowd and whether it is susceptible to such transitions could help prevent such catastrophes. While current techniques such as agent based models can predict transitions in emergent behaviors of crowds, the assumptions used to describe the agents are often ad hoc and the simulations are computationally expensive making their application to real-time crowd prediction challenging. Here, we pursue an orthogonal approach and ask whether a reduced set of variables, such as the local densities, are sufficient to describe the state of a crowd. Inspired by the theoretical framework of Density Functional Theory, we have developed a system that uses only measurements of local densities to extract two independent crowd behavior functions: (1) preferences for locations and (2) interactions between individuals. With these two functions, we have accurately predicted how a model system of walking Drosophila melanogaster distributes itself in an arbitrary 2D environment. In addition, this density-based approach measures properties of the crowd from only observations of the crowd itself without any knowledge of the detailed interactions and thus it can make predictions about the resulting distributions of these flies in arbitrary environments, in real-time. This research was supported in part by ARO W911NF-16-1-0433.

  6. Predicting the distribution of bed material accumulation using river network sediment budgets

    Science.gov (United States)

    Wilkinson, Scott N.; Prosser, Ian P.; Hughes, Andrew O.

    2006-10-01

    Assessing the spatial distribution of bed material accumulation in river networks is important for determining the impacts of erosion on downstream channel form and habitat and for planning erosion and sediment management. A model that constructs spatially distributed budgets of bed material sediment is developed to predict the locations of accumulation following land use change. For each link in the river network, GIS algorithms are used to predict bed material supply from gullies, river banks, and upstream tributaries and to compare total supply with transport capacity. The model is tested in the 29,000 km2 Murrumbidgee River catchment in southeast Australia. It correctly predicts the presence or absence of accumulation in 71% of river links, which is significantly better performance than previous models, which do not account for spatial variability in sediment supply and transport capacity. Representing transient sediment storage is important for predicting smaller accumulations. Bed material accumulation is predicted in 25% of the river network, indicating its importance as an environmental problem in Australia.

  7. Using geomorphological variables to predict the spatial distribution of plant species in agricultural drainage networks.

    Science.gov (United States)

    Rudi, Gabrielle; Bailly, Jean-Stéphane; Vinatier, Fabrice

    2018-01-01

    To optimize ecosystem services provided by agricultural drainage networks (ditches) in headwater catchments, we need to manage the spatial distribution of plant species living in these networks. Geomorphological variables have been shown to be important predictors of plant distribution in other ecosystems because they control the water regime, the sediment deposition rates and the sun exposure in the ditches. Whether such variables may be used to predict plant distribution in agricultural drainage networks is unknown. We collected presence and absence data for 10 herbaceous plant species in a subset of a network of drainage ditches (35 km long) within a Mediterranean agricultural catchment. We simulated their spatial distribution with GLM and Maxent model using geomorphological variables and distance to natural lands and roads. Models were validated using k-fold cross-validation. We then compared the mean Area Under the Curve (AUC) values obtained for each model and other metrics issued from the confusion matrices between observed and predicted variables. Based on the results of all metrics, the models were efficient at predicting the distribution of seven species out of ten, confirming the relevance of geomorphological variables and distance to natural lands and roads to explain the occurrence of plant species in this Mediterranean catchment. In particular, the importance of the landscape geomorphological variables, ie the importance of the geomorphological features encompassing a broad environment around the ditch, has been highlighted. This suggests that agro-ecological measures for managing ecosystem services provided by ditch plants should focus on the control of the hydrological and sedimentological connectivity at the catchment scale. For example, the density of the ditch network could be modified or the spatial distribution of vegetative filter strips used for sediment trapping could be optimized. In addition, the vegetative filter strips could constitute

  8. Hierarchical spatial models for predicting pygmy rabbit distribution and relative abundance

    Science.gov (United States)

    Wilson, T.L.; Odei, J.B.; Hooten, M.B.; Edwards, T.C.

    2010-01-01

    Conservationists routinely use species distribution models to plan conservation, restoration and development actions, while ecologists use them to infer process from pattern. These models tend to work well for common or easily observable species, but are of limited utility for rare and cryptic species. This may be because honest accounting of known observation bias and spatial autocorrelation are rarely included, thereby limiting statistical inference of resulting distribution maps. We specified and implemented a spatially explicit Bayesian hierarchical model for a cryptic mammal species (pygmy rabbit Brachylagus idahoensis). Our approach used two levels of indirect sign that are naturally hierarchical (burrows and faecal pellets) to build a model that allows for inference on regression coefficients as well as spatially explicit model parameters. We also produced maps of rabbit distribution (occupied burrows) and relative abundance (number of burrows expected to be occupied by pygmy rabbits). The model demonstrated statistically rigorous spatial prediction by including spatial autocorrelation and measurement uncertainty. We demonstrated flexibility of our modelling framework by depicting probabilistic distribution predictions using different assumptions of pygmy rabbit habitat requirements. Spatial representations of the variance of posterior predictive distributions were obtained to evaluate heterogeneity in model fit across the spatial domain. Leave-one-out cross-validation was conducted to evaluate the overall model fit. Synthesis and applications. Our method draws on the strengths of previous work, thereby bridging and extending two active areas of ecological research: species distribution models and multi-state occupancy modelling. Our framework can be extended to encompass both larger extents and other species for which direct estimation of abundance is difficult. ?? 2010 The Authors. Journal compilation ?? 2010 British Ecological Society.

  9. Predicting how altering propagule pressure changes establishment rates of biological invaders across species pools.

    Science.gov (United States)

    Brockerhoff, Eckehard G; Kimberley, Mark; Liebhold, Andrew M; Haack, Robert A; Cavey, Joseph F

    2014-03-01

    Biological invasions resulting from international trade can cause major environmental and economic impacts. Propagule pressure is perhaps the most important factor influencing establishment, although actual arrival rates of species are rarely recorded. Furthermore, the pool of potential invaders includes many species that vary in their arrival rate and establishment potential. Therefore, we stress that it is essential to consider the size and composition of species pools arriving from source regions when estimating probabilities of establishment and effects of pathway infestation rates. To address this, we developed a novel framework and modeling approach to enable prediction of future establishments in relation to changes in arrival rate across entire species pools. We utilized 13 828 border interception records from the United States and New Zealand for 444 true bark beetle (Scolytinae) and longhorned beetle (Cerambycidae) species detected between 1949 and 2008 as proxies for arrival rates to model the relationship between arrival and establishment rates. Nonlinearity in this relationship implies that measures intended to reduce the unintended transport of potential invaders (such as phytosanitary treatments) must be highly effective in order to substantially reduce the rate of future invasions, particularly if trade volumes continue to increase.

  10. The role of population inertia in predicting the outcome of stage-structured biological invasions.

    Science.gov (United States)

    Guiver, Chris; Dreiwi, Hanan; Filannino, Donna-Maria; Hodgson, Dave; Lloyd, Stephanie; Townley, Stuart

    2015-07-01

    Deterministic dynamic models for coupled resident and invader populations are considered with the purpose of finding quantities that are effective at predicting when the invasive population will become established asymptotically. A key feature of the models considered is the stage-structure, meaning that the populations are described by vectors of discrete developmental stage- or age-classes. The vector structure permits exotic transient behaviour-phenomena not encountered in scalar models. Analysis using a linear Lyapunov function demonstrates that for the class of population models considered, a large so-called population inertia is indicative of successful invasion. Population inertia is an indicator of transient growth or decline. Furthermore, for the class of models considered, we find that the so-called invasion exponent, an existing index used in models for invasion, is not always a reliable comparative indicator of successful invasion. We highlight these findings through numerical examples and a biological interpretation of why this might be the case is discussed. Copyright © 2015. Published by Elsevier Inc.

  11. Concentrations, input prediction and probabilistic biological risk assessment of polycyclic aromatic hydrocarbons (PAHs) along Gujarat coastline.

    Science.gov (United States)

    Gosai, Haren B; Sachaniya, Bhumi K; Dudhagara, Dushyant R; Rajpara, Rahul K; Dave, Bharti P

    2018-04-01

    A comprehensive investigation was conducted in order to assess the levels of PAHs, their input prediction and potential risks to bacterial abundance and human health along Gujarat coastline. A total of 40 sediment samples were collected at quarterly intervals within a year from two contaminated sites-Alang-Sosiya Shipbreaking Yard (ASSBRY) and Navlakhi Port (NAV), situated at Gulf of Khambhat and Gulf of Kutch, respectively. The concentration of ΣPAHs ranged from 408.00 to 54240.45 ng g -1  dw, indicating heavy pollution of PAHs at both the contaminated sites. Furthermore, isomeric ratios and principal component analysis have revealed that inputs of PAHs at both contaminated sites were mixed-pyrogenic and petrogenic. Pearson co-relation test and regression analysis have disclosed Nap, Acel and Phe as major predictors for bacterial abundance at both contaminated sites. Significantly, cancer risk assessment of the PAHs has been exercised based on incremental lifetime cancer risks. Overall, index of cancer risk of PAHs for ASSBRY and NAV ranged from 4.11 × 10 -6 -2.11 × 10 -5 and 9.08 × 10 -6 -4.50 × 10 -3 indicating higher cancer risk at NAV compared to ASSBRY. The present findings provide baseline information that may help in developing advanced bioremediation and bioleaching strategies to minimize biological risk.

  12. Spatiotemporal trends in Canadian domestic wild boar production and habitat predict wild pig distribution

    DEFF Research Database (Denmark)

    Michel, Nicole; Laforge, Michel; van Beest, Floris

    2017-01-01

    eradication of wild pigs is rarely feasible after establishment over large areas, effective management will depend on strengthening regulations and enforcement of containment practices for Canadian domestic wild boar farms. Initiation of coordinated provincial and federal efforts to implement population...... wild boar and test the propagule pressure hypothesis to improve predictive ability of an existing habitat-based model of wild pigs. We reviewed spatiotemporal patterns in domestic wild boar production across ten Canadian provinces during 1991–2011 and evaluated the ability of wild boar farm...... distribution to improve predictive models of wild pig occurrence using a resource selection probability function for wild pigs in Saskatchewan. Domestic wild boar production in Canada increased from 1991 to 2001 followed by sharp declines in all provinces. The distribution of domestic wild boar farms in 2006...

  13. Experimental Validation of Energy Resources Integration in Microgrids via Distributed Predictive Control

    DEFF Research Database (Denmark)

    Mantovani, Giancarlo; Costanzo, Giuseppe Tommaso; Marinelli, Mattia

    2014-01-01

    This paper presents an innovative control scheme for the management of energy consumption in commercial build- ings with local energy production, such as photovoltaic panels or wind turbine and an energy storage unit. The presented scheme is based on distributed model predictive controllers, which...... sources, a vanadium redox battery system, resistive load, and a point of common coupling to the national grid. Several experiments are carried to assess the performance of the control scheme in managing local energy pro- duction and consumption....

  14. Multivariate models for prediction of rheological characteristics of filamentous fermentation broth from the size distribution.

    Science.gov (United States)

    Petersen, Nanna; Stocks, Stuart; Gernaey, Krist V

    2008-05-01

    The main purpose of this article is to demonstrate that principal component analysis (PCA) and partial least squares regression (PLSR) can be used to extract information from particle size distribution data and predict rheological properties. Samples from commercially relevant Aspergillus oryzae fermentations conducted in 550 L pilot scale tanks were characterized with respect to particle size distribution, biomass concentration, and rheological properties. The rheological properties were described using the Herschel-Bulkley model. Estimation of all three parameters in the Herschel-Bulkley model (yield stress (tau(y)), consistency index (K), and flow behavior index (n)) resulted in a large standard deviation of the parameter estimates. The flow behavior index was not found to be correlated with any of the other measured variables and previous studies have suggested a constant value of the flow behavior index in filamentous fermentations. It was therefore chosen to fix this parameter to the average value thereby decreasing the standard deviation of the estimates of the remaining rheological parameters significantly. Using a PLSR model, a reasonable prediction of apparent viscosity (micro(app)), yield stress (tau(y)), and consistency index (K), could be made from the size distributions, biomass concentration, and process information. This provides a predictive method with a high predictive power for the rheology of fermentation broth, and with the advantages over previous models that tau(y) and K can be predicted as well as micro(app). Validation on an independent test set yielded a root mean square error of 1.21 Pa for tau(y), 0.209 Pa s(n) for K, and 0.0288 Pa s for micro(app), corresponding to R(2) = 0.95, R(2) = 0.94, and R(2) = 0.95 respectively. Copyright 2007 Wiley Periodicals, Inc.

  15. A maximum entropy model for predicting wild boar distribution in Spain

    Directory of Open Access Journals (Sweden)

    Jaime Bosch

    2014-09-01

    Full Text Available Wild boar (Sus scrofa populations in many areas of the Palearctic including the Iberian Peninsula have grown continuously over the last century. This increase has led to numerous different types of conflicts due to the damage these mammals can cause to agriculture, the problems they create in the conservation of natural areas, and the threat they pose to animal health. In the context of both wildlife management and the design of health programs for disease control, it is essential to know how wild boar are distributed on a large spatial scale. Given that the quantifying of the distribution of wild species using census techniques is virtually impossible in the case of large-scale studies, modeling techniques have thus to be used instead to estimate animals’ distributions, densities, and abundances. In this study, the potential distribution of wild boar in Spain was predicted by integrating data of presence and environmental variables into a MaxEnt approach. We built and tested models using 100 bootstrapped replicates. For each replicate or simulation, presence data was divided into two subsets that were used for model fitting (60% of the data and cross-validation (40% of the data. The final model was found to be accurate with an area under the receiver operating characteristic curve (AUC value of 0.79. Six explanatory variables for predicting wild boar distribution were identified on the basis of the percentage of their contribution to the model. The model exhibited a high degree of predictive accuracy, which has been confirmed by its agreement with satellite images and field surveys.

  16. Potential Distribution Predicted for Rhynchophorus ferrugineus in China under Different Climate Warming Scenarios.

    Directory of Open Access Journals (Sweden)

    Xuezhen Ge

    Full Text Available As the primary pest of palm trees, Rhynchophorus ferrugineus (Olivier (Coleoptera: Curculionidae has caused serious harm to palms since it first invaded China. The present study used CLIMEX 1.1 to predict the potential distribution of R. ferrugineus in China according to both current climate data (1981-2010 and future climate warming estimates based on simulated climate data for the 2020s (2011-2040 provided by the Tyndall Center for Climate Change Research (TYN SC 2.0. Additionally, the Ecoclimatic Index (EI values calculated for different climatic conditions (current and future, as simulated by the B2 scenario were compared. Areas with a suitable climate for R. ferrugineus distribution were located primarily in central China according to the current climate data, with the northern boundary of the distribution reaching to 40.1°N and including Tibet, north Sichuan, central Shaanxi, south Shanxi, and east Hebei. There was little difference in the potential distribution predicted by the four emission scenarios according to future climate warming estimates. The primary prediction under future climate warming models was that, compared with the current climate model, the number of highly favorable habitats would increase significantly and expand into northern China, whereas the number of both favorable and marginally favorable habitats would decrease. Contrast analysis of EI values suggested that climate change and the density of site distribution were the main effectors of the changes in EI values. These results will help to improve control measures, prevent the spread of this pest, and revise the targeted quarantine areas.

  17. Predicting the geographical distribution of two invasive termite species from occurrence data.

    Science.gov (United States)

    Tonini, Francesco; Divino, Fabio; Lasinio, Giovanna Jona; Hochmair, Hartwig H; Scheffrahn, Rudolf H

    2014-10-01

    Predicting the potential habitat of species under both current and future climate change scenarios is crucial for monitoring invasive species and understanding a species' response to different environmental conditions. Frequently, the only data available on a species is the location of its occurrence (presence-only data). Using occurrence records only, two models were used to predict the geographical distribution of two destructive invasive termite species, Coptotermes gestroi (Wasmann) and Coptotermes formosanus Shiraki. The first model uses a Bayesian linear logistic regression approach adjusted for presence-only data while the second one is the widely used maximum entropy approach (Maxent). Results show that the predicted distributions of both C. gestroi and C. formosanus are strongly linked to urban development. The impact of future scenarios such as climate warming and population growth on the biotic distribution of both termite species was also assessed. Future climate warming seems to affect their projected probability of presence to a lesser extent than population growth. The Bayesian logistic approach outperformed Maxent consistently in all models according to evaluation criteria such as model sensitivity and ecological realism. The importance of further studies for an explicit treatment of residual spatial autocorrelation and a more comprehensive comparison between both statistical approaches is suggested.

  18. Predicting the potential distribution of the amphibian pathogen Batrachochytrium dendrobatidis in East and Southeast Asia.

    Science.gov (United States)

    Moriguchi, Sachiko; Tominaga, Atsushi; Irwin, Kelly J; Freake, Michael J; Suzuki, Kazutaka; Goka, Koichi

    2015-04-08

    Batrachochytrium dendrobatidis (Bd) is the pathogen responsible for chytridiomycosis, a disease that is associated with a worldwide amphibian population decline. In this study, we predicted the potential distribution of Bd in East and Southeast Asia based on limited occurrence data. Our goal was to design an effective survey area where efforts to detect the pathogen can be focused. We generated ecological niche models using the maximum-entropy approach, with alleviation of multicollinearity and spatial autocorrelation. We applied eigenvector-based spatial filters as independent variables, in addition to environmental variables, to resolve spatial autocorrelation, and compared the model's accuracy and the degree of spatial autocorrelation with those of a model estimated using only environmental variables. We were able to identify areas of high suitability for Bd with accuracy. Among the environmental variables, factors related to temperature and precipitation were more effective in predicting the potential distribution of Bd than factors related to land use and cover type. Our study successfully predicted the potential distribution of Bd in East and Southeast Asia. This information should now be used to prioritize survey areas and generate a surveillance program to detect the pathogen.

  19. Predicting Causal Relationships from Biological Data: Applying Automated Casual Discovery on Mass Cytometry Data of Human Immune Cells

    KAUST Repository

    Triantafillou, Sofia; Lagani, Vincenzo; Heinze-Deml, Christina; Schmidt, Angelika; Tegner, Jesper; Tsamardinos, Ioannis

    2017-01-01

    Learning the causal relationships that define a molecular system allows us to predict how the system will respond to different interventions. Distinguishing causality from mere association typically requires randomized experiments. Methods for automated causal discovery from limited experiments exist, but have so far rarely been tested in systems biology applications. In this work, we apply state-of-the art causal discovery methods on a large collection of public mass cytometry data sets, measuring intra-cellular signaling proteins of the human immune system and their response to several perturbations. We show how different experimental conditions can be used to facilitate causal discovery, and apply two fundamental methods that produce context-specific causal predictions. Causal predictions were reproducible across independent data sets from two different studies, but often disagree with the KEGG pathway databases. Within this context, we discuss the caveats we need to overcome for automated causal discovery to become a part of the routine data analysis in systems biology.

  20. Predicting Causal Relationships from Biological Data: Applying Automated Casual Discovery on Mass Cytometry Data of Human Immune Cells

    KAUST Repository

    Triantafillou, Sofia

    2017-03-31

    Learning the causal relationships that define a molecular system allows us to predict how the system will respond to different interventions. Distinguishing causality from mere association typically requires randomized experiments. Methods for automated causal discovery from limited experiments exist, but have so far rarely been tested in systems biology applications. In this work, we apply state-of-the art causal discovery methods on a large collection of public mass cytometry data sets, measuring intra-cellular signaling proteins of the human immune system and their response to several perturbations. We show how different experimental conditions can be used to facilitate causal discovery, and apply two fundamental methods that produce context-specific causal predictions. Causal predictions were reproducible across independent data sets from two different studies, but often disagree with the KEGG pathway databases. Within this context, we discuss the caveats we need to overcome for automated causal discovery to become a part of the routine data analysis in systems biology.

  1. Distributed Learning, Recognition, and Prediction by ART and ARTMAP Neural Networks.

    Science.gov (United States)

    Carpenter, Gail A.

    1997-11-01

    A class of adaptive resonance theory (ART) models for learning, recognition, and prediction with arbitrarily distributed code representations is introduced. Distributed ART neural networks combine the stable fast learning capabilities of winner-take-all ART systems with the noise tolerance and code compression capabilities of multilayer perceptrons. With a winner-take-all code, the unsupervised model dART reduces to fuzzy ART and the supervised model dARTMAP reduces to fuzzy ARTMAP. With a distributed code, these networks automatically apportion learned changes according to the degree of activation of each coding node, which permits fast as well as slow learning without catastrophic forgetting. Distributed ART models replace the traditional neural network path weight with a dynamic weight equal to the rectified difference between coding node activation and an adaptive threshold. Thresholds increase monotonically during learning according to a principle of atrophy due to disuse. However, monotonic change at the synaptic level manifests itself as bidirectional change at the dynamic level, where the result of adaptation resembles long-term potentiation (LTP) for single-pulse or low frequency test inputs but can resemble long-term depression (LTD) for higher frequency test inputs. This paradoxical behavior is traced to dual computational properties of phasic and tonic coding signal components. A parallel distributed match-reset-search process also helps stabilize memory. Without the match-reset-search system, dART becomes a type of distributed competitive learning network.

  2. Predictive modeling and mapping of Malayan Sun Bear (Helarctos malayanus) distribution using maximum entropy.

    Science.gov (United States)

    Nazeri, Mona; Jusoff, Kamaruzaman; Madani, Nima; Mahmud, Ahmad Rodzi; Bahman, Abdul Rani; Kumar, Lalit

    2012-01-01

    One of the available tools for mapping the geographical distribution and potential suitable habitats is species distribution models. These techniques are very helpful for finding poorly known distributions of species in poorly sampled areas, such as the tropics. Maximum Entropy (MaxEnt) is a recently developed modeling method that can be successfully calibrated using a relatively small number of records. In this research, the MaxEnt model was applied to describe the distribution and identify the key factors shaping the potential distribution of the vulnerable Malayan Sun Bear (Helarctos malayanus) in one of the main remaining habitats in Peninsular Malaysia. MaxEnt results showed that even though Malaysian sun bear habitat is tied with tropical evergreen forests, it lives in a marginal threshold of bio-climatic variables. On the other hand, current protected area networks within Peninsular Malaysia do not cover most of the sun bears potential suitable habitats. Assuming that the predicted suitability map covers sun bears actual distribution, future climate change, forest degradation and illegal hunting could potentially severely affect the sun bear's population.

  3. Predictive modeling and mapping of Malayan Sun Bear (Helarctos malayanus distribution using maximum entropy.

    Directory of Open Access Journals (Sweden)

    Mona Nazeri

    Full Text Available One of the available tools for mapping the geographical distribution and potential suitable habitats is species distribution models. These techniques are very helpful for finding poorly known distributions of species in poorly sampled areas, such as the tropics. Maximum Entropy (MaxEnt is a recently developed modeling method that can be successfully calibrated using a relatively small number of records. In this research, the MaxEnt model was applied to describe the distribution and identify the key factors shaping the potential distribution of the vulnerable Malayan Sun Bear (Helarctos malayanus in one of the main remaining habitats in Peninsular Malaysia. MaxEnt results showed that even though Malaysian sun bear habitat is tied with tropical evergreen forests, it lives in a marginal threshold of bio-climatic variables. On the other hand, current protected area networks within Peninsular Malaysia do not cover most of the sun bears potential suitable habitats. Assuming that the predicted suitability map covers sun bears actual distribution, future climate change, forest degradation and illegal hunting could potentially severely affect the sun bear's population.

  4. Asymptotically Constant-Risk Predictive Densities When the Distributions of Data and Target Variables Are Different

    Directory of Open Access Journals (Sweden)

    Keisuke Yano

    2014-05-01

    Full Text Available We investigate the asymptotic construction of constant-risk Bayesian predictive densities under the Kullback–Leibler risk when the distributions of data and target variables are different and have a common unknown parameter. It is known that the Kullback–Leibler risk is asymptotically equal to a trace of the product of two matrices: the inverse of the Fisher information matrix for the data and the Fisher information matrix for the target variables. We assume that the trace has a unique maximum point with respect to the parameter. We construct asymptotically constant-risk Bayesian predictive densities using a prior depending on the sample size. Further, we apply the theory to the subminimax estimator problem and the prediction based on the binary regression model.

  5. Quantification of Hg excretion and distribution in biological samples of mercury-dental-amalgam users and its correlation with biological variables.

    Science.gov (United States)

    Gul, Nayab; Khan, Sardar; Khan, Abbas; Nawab, Javed; Shamshad, Isha; Yu, Xinwei

    2016-10-01

    This is the first study conducted to quantify the excretion and distribution of mercury (Hg) with time (days) in the biological samples collected from Hg dental amalgam users (MDA). The individuals, with Hg-based dental filling were selected, and their biological samples (red blood cells (RBCs), plasma, urine, hair, and nails) were collected on first, third, and 12th day of fillings. The concentrations of Hg observed in the biological samples of MDA were also correlated with the biological variables such as age, weight, restoration, fish consumption, number, and surface area of fillings. The concentrations of Hg in the biological samples of MDA were found 6-8 times higher than the non-amalgam users (control). The concentrations of Hg in the RBCs (4.39 μg/L), plasma (3.02 μg/L), and urine (22.5 μg/L) on first day of filling were found comparatively higher than the concentrations observed on third day (2.15, 1.46, and 12.3 μg/L for RBCs, plasma, urine, respectively) and 12th day (3.05, 2.5, 9.12 μg/L for RBCs, plasma, urine, respectively), while Hg concentrations were found lower in the hair and nails on third day of fillings (1.53 μg/g for hair and 2.35 μg/g for nails) as compared to the 12th day (2.95 μg/g for hair and 3.5 μg/g for nails). The correlations were found significant (p ˂ 0.05) between Hg concentrations in the biological samples of MDA and biological variables (the number of restoration, fish consumption, number, and surface area of fillings), while no significant (p ˃ 0.05) correlations were observed for Hg concentrations in the biological samples with age and weight of MDA. These observations unveil the fact that the use of Hg-based dental filling is the undesirable exposure to Hg which should be replaced by composite (a safer filling material).

  6. Linking macroecology and community ecology: refining predictions of species distributions using biotic interaction networks.

    Science.gov (United States)

    Staniczenko, Phillip P A; Sivasubramaniam, Prabu; Suttle, K Blake; Pearson, Richard G

    2017-06-01

    Macroecological models for predicting species distributions usually only include abiotic environmental conditions as explanatory variables, despite knowledge from community ecology that all species are linked to other species through biotic interactions. This disconnect is largely due to the different spatial scales considered by the two sub-disciplines: macroecologists study patterns at large extents and coarse resolutions, while community ecologists focus on small extents and fine resolutions. A general framework for including biotic interactions in macroecological models would help bridge this divide, as it would allow for rigorous testing of the role that biotic interactions play in determining species ranges. Here, we present an approach that combines species distribution models with Bayesian networks, which enables the direct and indirect effects of biotic interactions to be modelled as propagating conditional dependencies among species' presences. We show that including biotic interactions in distribution models for species from a California grassland community results in better range predictions across the western USA. This new approach will be important for improving estimates of species distributions and their dynamics under environmental change. © 2017 The Authors. Ecology Letters published by CNRS and John Wiley & Sons Ltd.

  7. Performance prediction of a synchronization link for distributed aerospace wireless systems.

    Science.gov (United States)

    Wang, Wen-Qin; Shao, Huaizong

    2013-01-01

    For reasons of stealth and other operational advantages, distributed aerospace wireless systems have received much attention in recent years. In a distributed aerospace wireless system, since the transmitter and receiver placed on separated platforms which use independent master oscillators, there is no cancellation of low-frequency phase noise as in the monostatic cases. Thus, high accurate time and frequency synchronization techniques are required for distributed wireless systems. The use of a dedicated synchronization link to quantify and compensate oscillator frequency instability is investigated in this paper. With the mathematical statistical models of phase noise, closed-form analytic expressions for the synchronization link performance are derived. The possible error contributions including oscillator, phase-locked loop, and receiver noise are quantified. The link synchronization performance is predicted by utilizing the knowledge of the statistical models, system error contributions, and sampling considerations. Simulation results show that effective synchronization error compensation can be achieved by using this dedicated synchronization link.

  8. Influence of covariate distribution on the predictive performance of pharmacokinetic models in paediatric research

    Science.gov (United States)

    Piana, Chiara; Danhof, Meindert; Della Pasqua, Oscar

    2014-01-01

    Aims The accuracy of model-based predictions often reported in paediatric research has not been thoroughly characterized. The aim of this exercise is therefore to evaluate the role of covariate distributions when a pharmacokinetic model is used for simulation purposes. Methods Plasma concentrations of a hypothetical drug were simulated in a paediatric population using a pharmacokinetic model in which body weight was correlated with clearance and volume of distribution. Two subgroups of children were then selected from the overall population according to a typical study design, in which pre-specified body weight ranges (10–15 kg and 30–40 kg) were used as inclusion criteria. The simulated data sets were then analyzed using non-linear mixed effects modelling. Model performance was assessed by comparing the accuracy of AUC predictions obtained for each subgroup, based on the model derived from the overall population and by extrapolation of the model parameters across subgroups. Results Our findings show that systemic exposure as well as pharmacokinetic parameters cannot be accurately predicted from the pharmacokinetic model obtained from a population with a different covariate range from the one explored during model building. Predictions were accurate only when a model was used for prediction in a subgroup of the initial population. Conclusions In contrast to current practice, the use of pharmacokinetic modelling in children should be limited to interpolations within the range of values observed during model building. Furthermore, the covariate point estimate must be kept in the model even when predictions refer to a subset different from the original population. PMID:24433411

  9. Impacts of pesticide mixtures in European rivers as predicted by the Species Sensitivity Distribution (SSD) models and SPEAR bioindication

    Science.gov (United States)

    Jesenska, Sona; Liess, Mathias; Schäfer, Ralf; Beketov, Mikhail; Blaha, Ludek

    2013-04-01

    Species sensitivity distribution (SSD) is statistical method broadly used in the ecotoxicological risk assessment of chemicals. Originally it has been used for prospective risk assessment of single substances but nowadays it is becoming more important also in the retrospective risk assessment of mixtures, including the catchment scale. In the present work, SSD predictions (impacts of mixtures consisting of 25 pesticides; data from several catchments in Germany, France and Finland) were compared with SPEAR-pesticides, which a bioindicator index based on biological traits responsive to the effects of pesticides and post-contamination recovery. The results showed statistically significant correlations (Pearson's R, ppesticides (based on field biomonitoring observations). Comparisons of the thresholds established for the SSD and SPEAR approaches (SPEAR-pesticides=45%, i.e. LOEC level, and msPAF = 0.05 for SSD, i.e. HC5) showed that use of chronic toxicity data significantly improved the agreement between the two methods but the SPEAR-pesticides index was still more sensitive. Taken together, the validation study shows good potential of SSD models in predicting the real impacts of micropollutant mixtures on natural communities of aquatic biota.

  10. Developing and Validating a Survival Prediction Model for NSCLC Patients Through Distributed Learning Across 3 Countries.

    Science.gov (United States)

    Jochems, Arthur; Deist, Timo M; El Naqa, Issam; Kessler, Marc; Mayo, Chuck; Reeves, Jackson; Jolly, Shruti; Matuszak, Martha; Ten Haken, Randall; van Soest, Johan; Oberije, Cary; Faivre-Finn, Corinne; Price, Gareth; de Ruysscher, Dirk; Lambin, Philippe; Dekker, Andre

    2017-10-01

    Tools for survival prediction for non-small cell lung cancer (NSCLC) patients treated with chemoradiation or radiation therapy are of limited quality. In this work, we developed a predictive model of survival at 2 years. The model is based on a large volume of historical patient data and serves as a proof of concept to demonstrate the distributed learning approach. Clinical data from 698 lung cancer patients, treated with curative intent with chemoradiation or radiation therapy alone, were collected and stored at 2 different cancer institutes (559 patients at Maastro clinic (Netherlands) and 139 at Michigan university [United States]). The model was further validated on 196 patients originating from The Christie (United Kingdon). A Bayesian network model was adapted for distributed learning (the animation can be viewed at https://www.youtube.com/watch?v=ZDJFOxpwqEA). Two-year posttreatment survival was chosen as the endpoint. The Maastro clinic cohort data are publicly available at https://www.cancerdata.org/publication/developing-and-validating-survival-prediction-model-nsclc-patients-through-distributed, and the developed models can be found at www.predictcancer.org. Variables included in the final model were T and N category, age, performance status, and total tumor dose. The model has an area under the curve (AUC) of 0.66 on the external validation set and an AUC of 0.62 on a 5-fold cross validation. A model based on the T and N category performed with an AUC of 0.47 on the validation set, significantly worse than our model (PLearning the model in a centralized or distributed fashion yields a minor difference on the probabilities of the conditional probability tables (0.6%); the discriminative performance of the models on the validation set is similar (P=.26). Distributed learning from federated databases allows learning of predictive models on data originating from multiple institutions while avoiding many of the data-sharing barriers. We believe that

  11. Recent advances, and unresolved issues, in the application of computational modelling to the prediction of the biological effects of nanomaterials

    International Nuclear Information System (INIS)

    Winkler, David A.

    2016-01-01

    Nanomaterials research is one of the fastest growing contemporary research areas. The unprecedented properties of these materials have meant that they are being incorporated into products very quickly. Regulatory agencies are concerned they cannot assess the potential hazards of these materials adequately, as data on the biological properties of nanomaterials are still relatively limited and expensive to acquire. Computational modelling methods have much to offer in helping understand the mechanisms by which toxicity may occur, and in predicting the likelihood of adverse biological impacts of materials not yet tested experimentally. This paper reviews the progress these methods, particularly those QSAR-based, have made in understanding and predicting potentially adverse biological effects of nanomaterials, and also the limitations and pitfalls of these methods. - Highlights: • Nanomaterials regulators need good information to make good decisions. • Nanomaterials and their interactions with biology are very complex. • Computational methods use existing data to predict properties of new nanomaterials. • Statistical, data driven modelling methods have been successfully applied to this task. • Much more must be learnt before robust toolkits will be widely usable by regulators.

  12. Applied Distributed Model Predictive Control for Energy Efficient Buildings and Ramp Metering

    Science.gov (United States)

    Koehler, Sarah Muraoka

    Industrial large-scale control problems present an interesting algorithmic design challenge. A number of controllers must cooperate in real-time on a network of embedded hardware with limited computing power in order to maximize system efficiency while respecting constraints and despite communication delays. Model predictive control (MPC) can automatically synthesize a centralized controller which optimizes an objective function subject to a system model, constraints, and predictions of disturbance. Unfortunately, the computations required by model predictive controllers for large-scale systems often limit its industrial implementation only to medium-scale slow processes. Distributed model predictive control (DMPC) enters the picture as a way to decentralize a large-scale model predictive control problem. The main idea of DMPC is to split the computations required by the MPC problem amongst distributed processors that can compute in parallel and communicate iteratively to find a solution. Some popularly proposed solutions are distributed optimization algorithms such as dual decomposition and the alternating direction method of multipliers (ADMM). However, these algorithms ignore two practical challenges: substantial communication delays present in control systems and also problem non-convexity. This thesis presents two novel and practically effective DMPC algorithms. The first DMPC algorithm is based on a primal-dual active-set method which achieves fast convergence, making it suitable for large-scale control applications which have a large communication delay across its communication network. In particular, this algorithm is suited for MPC problems with a quadratic cost, linear dynamics, forecasted demand, and box constraints. We measure the performance of this algorithm and show that it significantly outperforms both dual decomposition and ADMM in the presence of communication delay. The second DMPC algorithm is based on an inexact interior point method which is

  13. CADDIS Volume 4. Data Analysis: Predicting Environmental Conditions from Biological Observations (PECBO Appendix)

    Science.gov (United States)

    Overview of PECBO Module, using scripts to infer environmental conditions from biological observations, statistically estimating species-environment relationships, methods for inferring environmental conditions, statistical scripts in module.

  14. Improved ability of biological and previous caries multimarkers to predict caries disease as revealed by multivariate PLS modelling

    Directory of Open Access Journals (Sweden)

    Ericson Thorild

    2009-11-01

    Full Text Available Abstract Background Dental caries is a chronic disease with plaque bacteria, diet and saliva modifying disease activity. Here we have used the PLS method to evaluate a multiplicity of such biological variables (n = 88 for ability to predict caries in a cross-sectional (baseline caries and prospective (2-year caries development setting. Methods Multivariate PLS modelling was used to associate the many biological variables with caries recorded in thirty 14-year-old children by measuring the numbers of incipient and manifest caries lesions at all surfaces. Results A wide but shallow gliding scale of one fifth caries promoting or protecting, and four fifths non-influential, variables occurred. The influential markers behaved in the order of plaque bacteria > diet > saliva, with previously known plaque bacteria/diet markers and a set of new protective diet markers. A differential variable patterning appeared for new versus progressing lesions. The influential biological multimarkers (n = 18 predicted baseline caries better (ROC area 0.96 than five markers (0.92 and a single lactobacilli marker (0.7 with sensitivity/specificity of 1.87, 1.78 and 1.13 at 1/3 of the subjects diagnosed sick, respectively. Moreover, biological multimarkers (n = 18 explained 2-year caries increment slightly better than reported before but predicted it poorly (ROC area 0.76. By contrast, multimarkers based on previous caries predicted alone (ROC area 0.88, or together with biological multimarkers (0.94, increment well with a sensitivity/specificity of 1.74 at 1/3 of the subjects diagnosed sick. Conclusion Multimarkers behave better than single-to-five markers but future multimarker strategies will require systematic searches for improved saliva and plaque bacteria markers.

  15. A biological network-based regularized artificial neural network model for robust phenotype prediction from gene expression data.

    Science.gov (United States)

    Kang, Tianyu; Ding, Wei; Zhang, Luoyan; Ziemek, Daniel; Zarringhalam, Kourosh

    2017-12-19

    Stratification of patient subpopulations that respond favorably to treatment or experience and adverse reaction is an essential step toward development of new personalized therapies and diagnostics. It is currently feasible to generate omic-scale biological measurements for all patients in a study, providing an opportunity for machine learning models to identify molecular markers for disease diagnosis and progression. However, the high variability of genetic background in human populations hampers the reproducibility of omic-scale markers. In this paper, we develop a biological network-based regularized artificial neural network model for prediction of phenotype from transcriptomic measurements in clinical trials. To improve model sparsity and the overall reproducibility of the model, we incorporate regularization for simultaneous shrinkage of gene sets based on active upstream regulatory mechanisms into the model. We benchmark our method against various regression, support vector machines and artificial neural network models and demonstrate the ability of our method in predicting the clinical outcomes using clinical trial data on acute rejection in kidney transplantation and response to Infliximab in ulcerative colitis. We show that integration of prior biological knowledge into the classification as developed in this paper, significantly improves the robustness and generalizability of predictions to independent datasets. We provide a Java code of our algorithm along with a parsed version of the STRING DB database. In summary, we present a method for prediction of clinical phenotypes using baseline genome-wide expression data that makes use of prior biological knowledge on gene-regulatory interactions in order to increase robustness and reproducibility of omic-scale markers. The integrated group-wise regularization methods increases the interpretability of biological signatures and gives stable performance estimates across independent test sets.

  16. Accurate bearing remaining useful life prediction based on Weibull distribution and artificial neural network

    Science.gov (United States)

    Ben Ali, Jaouher; Chebel-Morello, Brigitte; Saidi, Lotfi; Malinowski, Simon; Fnaiech, Farhat

    2015-05-01

    Accurate remaining useful life (RUL) prediction of critical assets is an important challenge in condition based maintenance to improve reliability and decrease machine's breakdown and maintenance's cost. Bearing is one of the most important components in industries which need to be monitored and the user should predict its RUL. The challenge of this study is to propose an original feature able to evaluate the health state of bearings and to estimate their RUL by Prognostics and Health Management (PHM) techniques. In this paper, the proposed method is based on the data-driven prognostic approach. The combination of Simplified Fuzzy Adaptive Resonance Theory Map (SFAM) neural network and Weibull distribution (WD) is explored. WD is used just in the training phase to fit measurement and to avoid areas of fluctuation in the time domain. SFAM training process is based on fitted measurements at present and previous inspection time points as input. However, the SFAM testing process is based on real measurements at present and previous inspections. Thanks to the fuzzy learning process, SFAM has an important ability and a good performance to learn nonlinear time series. As output, seven classes are defined; healthy bearing and six states for bearing degradation. In order to find the optimal RUL prediction, a smoothing phase is proposed in this paper. Experimental results show that the proposed method can reliably predict the RUL of rolling element bearings (REBs) based on vibration signals. The proposed prediction approach can be applied to prognostic other various mechanical assets.

  17. Spatially distributed flame transfer functions for predicting combustion dynamics in lean premixed gas turbine combustors

    Energy Technology Data Exchange (ETDEWEB)

    Kim, K.T.; Lee, J.G.; Quay, B.D.; Santavicca, D.A. [Center for Advanced Power Generation, Department of Mechanical and Nuclear Engineering, Pennsylvania State University, University Park, PA (United States)

    2010-09-15

    The present paper describes a methodology to improve the accuracy of prediction of the eigenfrequencies and growth rates of self-induced instabilities and demonstrates its application to a laboratory-scale, swirl-stabilized, lean-premixed, gas turbine combustor. The influence of the spatial heat release distribution is accounted for using local flame transfer function (FTF) measurements. The two-microphone technique and CH{sup *} chemiluminescence intensity measurements are used to determine the input (inlet velocity perturbation) and the output functions (heat release oscillation), respectively, for the local flame transfer functions. The experimentally determined local flame transfer functions are superposed using the flame transfer function superposition principle, and the result is incorporated into an analytic thermoacoustic model, in order to predict the linear stability characteristics of a given system. Results show that when the flame length is not acoustically compact the model prediction calculated using the local flame transfer functions is better than the prediction made using the global flame transfer function. In the case of a flame in the compact flame regime, accurate predictions of eigenfrequencies and growth rates can be obtained using the global flame transfer function. It was also found that the general response characteristics of the local FTF (gain and phase) are qualitatively the same as those of the global FTF. (author)

  18. Prediction of metabolic flux distribution from gene expression data based on the flux minimization principle.

    Directory of Open Access Journals (Sweden)

    Hyun-Seob Song

    Full Text Available Prediction of possible flux distributions in a metabolic network provides detailed phenotypic information that links metabolism to cellular physiology. To estimate metabolic steady-state fluxes, the most common approach is to solve a set of macroscopic mass balance equations subjected to stoichiometric constraints while attempting to optimize an assumed optimal objective function. This assumption is justifiable in specific cases but may be invalid when tested across different conditions, cell populations, or other organisms. With an aim to providing a more consistent and reliable prediction of flux distributions over a wide range of conditions, in this article we propose a framework that uses the flux minimization principle to predict active metabolic pathways from mRNA expression data. The proposed algorithm minimizes a weighted sum of flux magnitudes, while biomass production can be bounded to fit an ample range from very low to very high values according to the analyzed context. We have formulated the flux weights as a function of the corresponding enzyme reaction's gene expression value, enabling the creation of context-specific fluxes based on a generic metabolic network. In case studies of wild-type Saccharomyces cerevisiae, and wild-type and mutant Escherichia coli strains, our method achieved high prediction accuracy, as gauged by correlation coefficients and sums of squared error, with respect to the experimentally measured values. In contrast to other approaches, our method was able to provide quantitative predictions for both model organisms under a variety of conditions. Our approach requires no prior knowledge or assumption of a context-specific metabolic functionality and does not require trial-and-error parameter adjustments. Thus, our framework is of general applicability for modeling the transcription-dependent metabolism of bacteria and yeasts.

  19. Predicting the distribution pattern of small carnivores in response to environmental factors in the Western Ghats.

    Science.gov (United States)

    Kalle, Riddhika; Ramesh, Tharmalingam; Qureshi, Qamar; Sankar, Kalyanasundaram

    2013-01-01

    Due to their secretive habits, predicting the pattern of spatial distribution of small carnivores has been typically challenging, yet for conservation management it is essential to understand the association between this group of animals and environmental factors. We applied maximum entropy modeling (MaxEnt) to build distribution models and identify environmental predictors including bioclimatic variables, forest and land cover type, topography, vegetation index and anthropogenic variables for six small carnivore species in Mudumalai Tiger Reserve. Species occurrence records were collated from camera-traps and vehicle transects during the years 2010 and 2011. We used the average training gain from forty model runs for each species to select the best set of predictors. The area under the curve (AUC) of the receiver operating characteristic plot (ROC) ranged from 0.81 to 0.93 for the training data and 0.72 to 0.87 for the test data. In habitat models for F. chaus, P. hermaphroditus, and H. smithii "distance to village" and precipitation of the warmest quarter emerged as some of the most important variables. "Distance to village" and aspect were important for V. indica while "distance to village" and precipitation of the coldest quarter were significant for H. vitticollis. "Distance to village", precipitation of the warmest quarter and land cover were influential variables in the distribution of H. edwardsii. The map of predicted probabilities of occurrence showed potentially suitable habitats accounting for 46 km(2) of the reserve for F. chaus, 62 km(2) for V. indica, 30 km(2) for P. hermaphroditus, 63 km(2) for H. vitticollis, 45 km(2) for H. smithii and 28 km(2) for H. edwardsii. Habitat heterogeneity driven by the east-west climatic gradient was correlated with the spatial distribution of small carnivores. This study exemplifies the usefulness of modeling small carnivore distribution to prioritize and direct conservation planning for habitat specialists in

  20. Predictive modeling of deep-sea fish distribution in the Azores

    Science.gov (United States)

    Parra, Hugo E.; Pham, Christopher K.; Menezes, Gui M.; Rosa, Alexandra; Tempera, Fernando; Morato, Telmo

    2017-11-01

    Understanding the link between fish and their habitat is essential for an ecosystem approach to fisheries management. However, determining such relationship is challenging, especially for deep-sea species. In this study, we applied generalized additive models (GAMs) to relate presence-absence and relative abundance data of eight economically-important fish species to environmental variables (depth, slope, aspect, substrate type, bottom temperature, salinity and oxygen saturation). We combined 13 years of catch data collected from systematic longline surveys performed across the region. Overall, presence-absence GAMs performed better than abundance models and predictions made for the observed data successfully predicted the occurrence of the eight deep-sea fish species. Depth was the most influential predictor of all fish species occurrence and abundance distributions, whereas other factors were found to be significant for some species but did not show such a clear influence. Our results predicted that despite the extensive Azores EEZ, the habitats available for the studied deep-sea fish species are highly limited and patchy, restricted to seamounts slopes and summits, offshore banks and island slopes. Despite some identified limitations, our GAMs provide an improved knowledge of the spatial distribution of these commercially important fish species in the region.

  1. Predicting Spatial Distribution of Key Honeybee Pests in Kenya Using Remotely Sensed and Bioclimatic Variables: Key Honeybee Pests Distribution Models

    Directory of Open Access Journals (Sweden)

    David M. Makori

    2017-02-01

    Full Text Available Bee keeping is indispensable to global food production. It is an alternate income source, especially in rural underdeveloped African settlements, and an important forest conservation incentive. However, dwindling honeybee colonies around the world are attributed to pests and diseases whose spatial distribution and influences are not well established. In this study, we used remotely sensed data to improve the reliability of pest ecological niche (EN models to attain reliable pest distribution maps. Occurrence data on four pests (Aethina tumida, Galleria mellonella, Oplostomus haroldi and Varroa destructor were collected from apiaries within four main agro-ecological regions responsible for over 80% of Kenya’s bee keeping. Africlim bioclimatic and derived normalized difference vegetation index (NDVI variables were used to model their ecological niches using Maximum Entropy (MaxEnt. Combined precipitation variables had a high positive logit influence on all remotely sensed and biotic models’ performance. Remotely sensed vegetation variables had a substantial effect on the model, contributing up to 40.8% for G. mellonella and regions with high rainfall seasonality were predicted to be high-risk areas. Projections (to 2055 indicated that, with the current climate change trend, these regions will experience increased honeybee pest risk. We conclude that honeybee pests could be modelled using bioclimatic data and remotely sensed variables in MaxEnt. Although the bioclimatic data were most relevant in all model results, incorporating vegetation seasonality variables to improve mapping the ‘actual’ habitat of key honeybee pests and to identify risk and containment zones needs to be further investigated.

  2. Prediction of the low-velocity distribution from the pore structure in simple porous media

    Science.gov (United States)

    de Anna, Pietro; Quaife, Bryan; Biros, George; Juanes, Ruben

    2017-12-01

    The macroscopic properties of fluid flow and transport through porous media are a direct consequence of the underlying pore structure. However, precise relations that characterize flow and transport from the statistics of pore-scale disorder have remained elusive. Here we investigate the relationship between pore structure and the resulting fluid flow and asymptotic transport behavior in two-dimensional geometries of nonoverlapping circular posts. We derive an analytical relationship between the pore throat size distribution fλ˜λ-β and the distribution of the low fluid velocities fu˜u-β /2 , based on a conceptual model of porelets (the flow established within each pore throat, here a Hagen-Poiseuille flow). Our model allows us to make predictions, within a continuous-time random-walk framework, for the asymptotic statistics of the spreading of fluid particles along their own trajectories. These predictions are confirmed by high-fidelity simulations of Stokes flow and advective transport. The proposed framework can be extended to other configurations which can be represented as a collection of known flow distributions.

  3. Effects of predicted climatic changes on distribution of organic contaminants in brackish water mesocosms.

    Science.gov (United States)

    Ripszam, M; Gallampois, C M J; Berglund, Å; Larsson, H; Andersson, A; Tysklind, M; Haglund, P

    2015-06-01

    Predicted consequences of future climate change in the northern Baltic Sea include increases in sea surface temperatures and terrestrial dissolved organic carbon (DOC) runoff. These changes are expected to alter environmental distribution of anthropogenic organic contaminants (OCs). To assess likely shifts in their distributions, outdoor mesocosms were employed to mimic pelagic ecosystems at two temperatures and two DOC concentrations, current: 15°C and 4 mg DOCL(-1) and, within ranges of predicted increases, 18°C and 6 mg DOCL(-1), respectively. Selected organic contaminants were added to the mesocosms to monitor changes in their distribution induced by the treatments. OC partitioning to particulate matter and sedimentation were enhanced at the higher DOC concentration, at both temperatures, while higher losses and lower partitioning of OCs to DOC were observed at the higher temperature. No combined effects of higher temperature and DOC on partitioning were observed, possibly because of the balancing nature of these processes. Therefore, changes in OCs' fates may largely depend on whether they are most sensitive to temperature or DOC concentration rises. Bromoanilines, phenanthrene, biphenyl and naphthalene were sensitive to the rise in DOC concentration, whereas organophosphates, chlorobenzenes (PCBz) and polychlorinated biphenyls (PCBs) were more sensitive to temperature. Mitotane and diflufenican were sensitive to both temperature and DOC concentration rises individually, but not in combination. Copyright © 2015 Elsevier B.V. All rights reserved.

  4. Human Papilloma Virus: Prevalence, distribution and predictive value to lymphatic metastasis in penile carcinoma

    Directory of Open Access Journals (Sweden)

    Aluizio Goncalves da Fonseca

    2013-07-01

    Full Text Available Objectives To evaluate the prevalence, distribution and association of HPV with histological pattern of worse prognosis of penile cancer, in order to evaluate its predictive value of inguinal metastasis, as well as evaluation of other previous reported prognostic factors. Material and Methods Tumor samples of 82 patients with penile carcinoma were tested in order to establish the prevalence and distribution of genotypic HPV using PCR. HPV status was correlated to histopathological factors and the presence of inguinal mestastasis. The influence of several histological characteristics was also correlated to inguinal disease-free survival. Results Follow-up varied from 1 to 71 months (median 22 months. HPV DNA was identified in 60.9% of sample, with higher prevalence of types 11 and 6 (64% and 32%, respectively. There was no significant correlation of the histological characteristics of worse prognosis of penile cancer with HPV status. Inguinal disease-free survival in 5 years did also not show HPV status influence (p = 0.45. The only independent pathologic factors of inguinal metastasis were: stage T ≥ T1b-T4 (p = 0.02, lymphovascular invasion (p = 0.04 and infiltrative invasion (p = 0.03. conclusions HPV status and distribution had shown no correlation with worse prognosis of histological aspects, or predictive value for lymphatic metastasis in penile carcinoma.

  5. Methods for Prediction of Temperature Distribution in Flashover Caused by Backdraft Fire

    Directory of Open Access Journals (Sweden)

    Guowei Zhang

    2014-01-01

    Full Text Available Accurately predicting temperature distribution in flashover fire is a key issue for evacuation and fire-fighting. Now many good flashover fire experiments have be conducted, but most of these experiments are proceeded in enclosure with fixed openings; researches on fire development and temperature distribution in flashover caused by backdraft fire did not receive enough attention. In order to study flashover phenomenon caused by backdraft fire, a full-scale fire experiment was conducted in one abandoned office building. Process of fire development and temperature distribution in room and corridor were separately recorded during the experiment. The experiment shows that fire development in enclosure is closely affected by the room ventilation. Unlike existing temperature curves which have only one temperature peak, temperature in flashover caused by backdraft may have more than one peak value and that there is a linear relationship between maximum peak temperature and distance away from fire compartment. Based on BFD curve and experimental data, mathematical models are proposed to predict temperature curve in flashover fire caused by backdraft at last. These conclusions and experiment data obtained in this paper could provide valuable reference to fire simulation, hazard assessment, and fire protection design.

  6. A comparison of biological effect and spray liquid distribution and deposition for different spray application techniques in different crops

    OpenAIRE

    Larsolle, Anders; Wretblad, Per; Westberg, Carl

    2002-01-01

    The objective of this study was to compare a selection of spray application techniques with different application volumes, with respect to the spray liquid distribution on flat surfaces, the deposition in fully developed crops and the biological effect. The spray application techniques in this study were conventional spray technique with three different nozzles: Teelet XR, Lechler ID and Lurmark DriftBeta, and also AirTec, Danfoil, Hardi Twin, Kyndestoit and Släpduk. The dynamic spray liquid ...

  7. Detailed analysis of inversions predicted between two human genomes: errors, real polymorphisms, and their origin and population distribution.

    Science.gov (United States)

    Vicente-Salvador, David; Puig, Marta; Gayà-Vidal, Magdalena; Pacheco, Sarai; Giner-Delgado, Carla; Noguera, Isaac; Izquierdo, David; Martínez-Fundichely, Alexander; Ruiz-Herrera, Aurora; Estivill, Xavier; Aguado, Cristina; Lucas-Lledó, José Ignacio; Cáceres, Mario

    2017-02-01

    The growing catalogue of structural variants in humans often overlooks inversions as one of the most difficult types of variation to study, even though they affect phenotypic traits in diverse organisms. Here, we have analysed in detail 90 inversions predicted from the comparison of two independently assembled human genomes: the reference genome (NCBI36/HG18) and HuRef. Surprisingly, we found that two thirds of these predictions (62) represent errors either in assembly comparison or in one of the assemblies, including 27 misassembled regions in HG18. Next, we validated 22 of the remaining 28 potential polymorphic inversions using different PCR techniques and characterized their breakpoints and ancestral state. In addition, we determined experimentally the derived allele frequency in Europeans for 17 inversions (DAF = 0.01-0.80), as well as the distribution in 14 worldwide populations for 12 of them based on the 1000 Genomes Project data. Among the validated inversions, nine have inverted repeats (IRs) at their breakpoints, and two show nucleotide variation patterns consistent with a recurrent origin. Conversely, inversions without IRs have a unique origin and almost all of them show deletions or insertions at the breakpoints in the derived allele mediated by microhomology sequences, which highlights the importance of mechanisms like FoSTeS/MMBIR in the generation of complex rearrangements in the human genome. Finally, we found several inversions located within genes and at least one candidate to be positively selected in Africa. Thus, our study emphasizes the importance of careful analysis and validation of large-scale genomic predictions to extract reliable biological conclusions. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  8. Predicting spatial and temporal distribution of Indo-Pacific lionfish (Pterois volitans) in Biscayne Bay through habitat suitability modeling

    Science.gov (United States)

    Bernal, Nicholas A.; DeAngelis, Donald L.; Schofield, Pamela J.; Sullivan Sealey, Kathleen

    2014-01-01

    Invasive species may exhibit higher levels of growth and reproduction when environmental conditions are most suitable, and thus their effects on native fauna may be intensified. Understanding potential impacts of these species, especially in the nascent stages of a biological invasion, requires critical information concerning spatial and temporal distributions of habitat suitability. Using empirically supported environmental variables (e.g., temperature, salinity, dissolved oxygen, rugosity, and benthic substrate), our models predicted habitat suitability for the invasive lionfish (Pterois volitans) in Biscayne Bay, Florida. The use of Geographic Information Systems (GIS) as a platform for the modeling process allowed us to quantify correlations between temporal (seasonal) fluctuations in the above variables and the spatial distribution of five discrete habitat quality classes, whose ranges are supported by statistical deviations from the apparent best conditions described in prior studies. Analysis of the resulting models revealed little fluctuation in spatial extent of the five habitat classes on a monthly basis. Class 5, which represented the area with environmental variables closest to the best conditions for lionfish, occupied approximately one-third of Biscayne Bay, with subsequent habitats declining in area. A key finding from this study was that habitat suitability increased eastward from the coastline, where higher quality habitats were adjacent to the Atlantic Ocean and displayed marine levels of ambient water quality. Corroboration of the models with sightings from the USGS-NAS database appeared to support our findings by nesting 79 % of values within habitat class 5; however, field testing (i.e., lionfish surveys) is necessary to confirm the relationship between habitat classes and lionfish distribution.

  9. Study of burden distribution characteristics (IV): the development of a distribution predicting model in which coke collapse has been taken into account

    Energy Technology Data Exchange (ETDEWEB)

    Kamisaka, E; Okuno, Y; Irita, T; Matsuzaki, M; Isoyama, T; Kunitomo, K

    1984-01-01

    Using results quoted in a previous report (see Tetsu To Hagane, Vol. 68, page S 701, 1982), coke collapse has been quantified by means of landslide theory, according to which the stability of the burden is given by a safety factor which equals resistance moment/sliding moment. This has enabled coke collapse to be introduced in a model for predicting burden distribution. Application of this model has resulted in more accurate predictions of burden distribution, the computed values being in close agreement with the results of distribution experiments. 1 reference.

  10. DemQSAR: predicting human volume of distribution and clearance of drugs.

    Science.gov (United States)

    Demir-Kavuk, Ozgur; Bentzien, Jörg; Muegge, Ingo; Knapp, Ernst-Walter

    2011-12-01

    In silico methods characterizing molecular compounds with respect to pharmacologically relevant properties can accelerate the identification of new drugs and reduce their development costs. Quantitative structure-activity/-property relationship (QSAR/QSPR) correlate structure and physico-chemical properties of molecular compounds with a specific functional activity/property under study. Typically a large number of molecular features are generated for the compounds. In many cases the number of generated features exceeds the number of molecular compounds with known property values that are available for learning. Machine learning methods tend to overfit the training data in such situations, i.e. the method adjusts to very specific features of the training data, which are not characteristic for the considered property. This problem can be alleviated by diminishing the influence of unimportant, redundant or even misleading features. A better strategy is to eliminate such features completely. Ideally, a molecular property can be described by a small number of features that are chemically interpretable. The purpose of the present contribution is to provide a predictive modeling approach, which combines feature generation, feature selection, model building and control of overtraining into a single application called DemQSAR. DemQSAR is used to predict human volume of distribution (VD(ss)) and human clearance (CL). To control overtraining, quadratic and linear regularization terms were employed. A recursive feature selection approach is used to reduce the number of descriptors. The prediction performance is as good as the best predictions reported in the recent literature. The example presented here demonstrates that DemQSAR can generate a model that uses very few features while maintaining high predictive power. A standalone DemQSAR Java application for model building of any user defined property as well as a web interface for the prediction of human VD(ss) and CL is

  11. Distribution of Short-Term and Lifetime Predicted Risks of Cardiovascular Diseases in Peruvian Adults.

    Science.gov (United States)

    Quispe, Renato; Bazo-Alvarez, Juan Carlos; Burroughs Peña, Melissa S; Poterico, Julio A; Gilman, Robert H; Checkley, William; Bernabé-Ortiz, Antonio; Huffman, Mark D; Miranda, J Jaime

    2015-08-07

    Short-term risk assessment tools for prediction of cardiovascular disease events are widely recommended in clinical practice and are used largely for single time-point estimations; however, persons with low predicted short-term risk may have higher risks across longer time horizons. We estimated short-term and lifetime cardiovascular disease risk in a pooled population from 2 studies of Peruvian populations. Short-term risk was estimated using the atherosclerotic cardiovascular disease Pooled Cohort Risk Equations. Lifetime risk was evaluated using the algorithm derived from the Framingham Heart Study cohort. Using previously published thresholds, participants were classified into 3 categories: low short-term and low lifetime risk, low short-term and high lifetime risk, and high short-term predicted risk. We also compared the distribution of these risk profiles across educational level, wealth index, and place of residence. We included 2844 participants (50% men, mean age 55.9 years [SD 10.2 years]) in the analysis. Approximately 1 of every 3 participants (34% [95% CI 33 to 36]) had a high short-term estimated cardiovascular disease risk. Among those with a low short-term predicted risk, more than half (54% [95% CI 52 to 56]) had a high lifetime predicted risk. Short-term and lifetime predicted risks were higher for participants with lower versus higher wealth indexes and educational levels and for those living in urban versus rural areas (PPeruvian adults were classified as low short-term risk but high lifetime risk. Vulnerable adults, such as those from low socioeconomic status and those living in urban areas, may need greater attention regarding cardiovascular preventive strategies. © 2015 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

  12. Distribution of Short-Term and Lifetime Predicted Risks of Cardiovascular Diseases in Peruvian Adults

    Science.gov (United States)

    Quispe, Renato; Bazo-Alvarez, Juan Carlos; Burroughs Peña, Melissa S; Poterico, Julio A; Gilman, Robert H; Checkley, William; Bernabé-Ortiz, Antonio; Huffman, Mark D; Miranda, J Jaime

    2015-01-01

    Background Short-term risk assessment tools for prediction of cardiovascular disease events are widely recommended in clinical practice and are used largely for single time-point estimations; however, persons with low predicted short-term risk may have higher risks across longer time horizons. Methods and Results We estimated short-term and lifetime cardiovascular disease risk in a pooled population from 2 studies of Peruvian populations. Short-term risk was estimated using the atherosclerotic cardiovascular disease Pooled Cohort Risk Equations. Lifetime risk was evaluated using the algorithm derived from the Framingham Heart Study cohort. Using previously published thresholds, participants were classified into 3 categories: low short-term and low lifetime risk, low short-term and high lifetime risk, and high short-term predicted risk. We also compared the distribution of these risk profiles across educational level, wealth index, and place of residence. We included 2844 participants (50% men, mean age 55.9 years [SD 10.2 years]) in the analysis. Approximately 1 of every 3 participants (34% [95% CI 33 to 36]) had a high short-term estimated cardiovascular disease risk. Among those with a low short-term predicted risk, more than half (54% [95% CI 52 to 56]) had a high lifetime predicted risk. Short-term and lifetime predicted risks were higher for participants with lower versus higher wealth indexes and educational levels and for those living in urban versus rural areas (PPeruvian adults were classified as low short-term risk but high lifetime risk. Vulnerable adults, such as those from low socioeconomic status and those living in urban areas, may need greater attention regarding cardiovascular preventive strategies. PMID:26254303

  13. Emphysema Distribution and Diffusion Capacity Predict Emphysema Progression in Human Immunodeficiency Virus Infection

    Science.gov (United States)

    Leung, Janice M; Malagoli, Andrea; Santoro, Antonella; Besutti, Giulia; Ligabue, Guido; Scaglioni, Riccardo; Dai, Darlene; Hague, Cameron; Leipsic, Jonathon; Sin, Don D.; Man, SF Paul; Guaraldi, Giovanni

    2016-01-01

    Background Chronic obstructive pulmonary disease (COPD) and emphysema are common amongst patients with human immunodeficiency virus (HIV). We sought to determine the clinical factors that are associated with emphysema progression in HIV. Methods 345 HIV-infected patients enrolled in an outpatient HIV metabolic clinic with ≥2 chest computed tomography scans made up the study cohort. Images were qualitatively scored for emphysema based on percentage involvement of the lung. Emphysema progression was defined as any increase in emphysema score over the study period. Univariate analyses of clinical, respiratory, and laboratory data, as well as multivariable logistic regression models, were performed to determine clinical features significantly associated with emphysema progression. Results 17.4% of the cohort were emphysema progressors. Emphysema progression was most strongly associated with having a low baseline diffusion capacity of carbon monoxide (DLCO) and having combination centrilobular and paraseptal emphysema distribution. In adjusted models, the odds ratio (OR) for emphysema progression for every 10% increase in DLCO percent predicted was 0.58 (95% confidence interval [CI] 0.41–0.81). The equivalent OR (95% CI) for centrilobular and paraseptal emphysema distribution was 10.60 (2.93–48.98). Together, these variables had an area under the curve (AUC) statistic of 0.85 for predicting emphysema progression. This was an improvement over the performance of spirometry (forced expiratory volume in 1 second to forced vital capacity ratio), which predicted emphysema progression with an AUC of only 0.65. Conclusion Combined paraseptal and centrilobular emphysema distribution and low DLCO could identify HIV patients who may experience emphysema progression. PMID:27902753

  14. Predicting plant invasions under climate change: are species distribution models validated by field trials?

    Science.gov (United States)

    Sheppard, Christine S; Burns, Bruce R; Stanley, Margaret C

    2014-09-01

    Climate change may facilitate alien species invasion into new areas, particularly for species from warm native ranges introduced into areas currently marginal for temperature. Although conclusions from modelling approaches and experimental studies are generally similar, combining the two approaches has rarely occurred. The aim of this study was to validate species distribution models by conducting field trials in sites of differing suitability as predicted by the models, thus increasing confidence in their ability to assess invasion risk. Three recently naturalized alien plants in New Zealand were used as study species (Archontophoenix cunninghamiana, Psidium guajava and Schefflera actinophylla): they originate from warm native ranges, are woody bird-dispersed species and of concern as potential weeds. Seedlings were grown in six sites across the country, differing both in climate and suitability (as predicted by the species distribution models). Seedling growth and survival were recorded over two summers and one or two winter seasons, and temperature and precipitation were monitored hourly at each site. Additionally, alien seedling performances were compared to those of closely related native species (Rhopalostylis sapida, Lophomyrtus bullata and Schefflera digitata). Furthermore, half of the seedlings were sprayed with pesticide, to investigate whether enemy release may influence performance. The results showed large differences in growth and survival of the alien species among the six sites. In the more suitable sites, performance was frequently higher compared to the native species. Leaf damage from invertebrate herbivory was low for both alien and native seedlings, with little evidence that the alien species should have an advantage over the native species because of enemy release. Correlations between performance in the field and predicted suitability of species distribution models were generally high. The projected increase in minimum temperature and reduced

  15. Visibility from roads predict the distribution of invasive fishes in agricultural ponds.

    Science.gov (United States)

    Kizuka, Toshikazu; Akasaka, Munemitsu; Kadoya, Taku; Takamura, Noriko

    2014-01-01

    Propagule pressure and habitat characteristics are important factors used to predict the distribution of invasive alien species. For species exhibiting strong propagule pressure because of human-mediated introduction of species, indicators of introduction potential must represent the behavioral characteristics of humans. This study examined 64 agricultural ponds to assess the visibility of ponds from surrounding roads and its value as a surrogate of propagule pressure to explain the presence and absence of two invasive fish species. A three-dimensional viewshed analysis using a geographic information system quantified the visual exposure of respective ponds to humans. Binary classification trees were developed as a function of their visibility from roads, as well as five environmental factors: river density, connectivity with upstream dam reservoirs, pond area, chlorophyll a concentration, and pond drainage. Traditional indicators of human-mediated introduction (road density and proportion of urban land-use area) were alternatively included for comparison instead of visual exposure. The presence of Bluegill (Lepomis macrochirus) was predicted by the ponds' higher visibility from roads and pond connection with upstream dam reservoirs. Results suggest that fish stocking into ponds and their dispersal from upstream sources facilitated species establishment. Largemouth bass (Micropterus salmoides) distribution was constrained by chlorophyll a concentration, suggesting their lower adaptability to various environments than that of Bluegill. Based on misclassifications from classification trees for Bluegill, pond visual exposure to roads showed greater predictive capability than traditional indicators of human-mediated introduction. Pond visibility is an effective predictor of invasive species distribution. Its wider use might improve management and mitigate further invasion. The visual exposure of recipient ecosystems to humans is important for many invasive species that

  16. Distributed Sensor Network for meteorological observations and numerical weather Prediction Calculations

    Directory of Open Access Journals (Sweden)

    Á. Vas

    2013-06-01

    Full Text Available The prediction of weather generally means the solution of differential equations on the base of the measured initial conditions where the data of close and distant neighboring points are used for the calculations. It requires the maintenance of expensive weather stations and supercomputers. However, if weather stations are not only capable of measuring but can also communicate with each other, then these smart sensors can also be applied to run forecasting calculations. This applies the highest possible level of parallelization without the collection of measured data into one place. Furthermore, if more nodes are involved, the result becomes more accurate, but the computing power required from one node does not increase. Our Distributed Sensor Network for meteorological sensing and numerical weather Prediction Calculations (DSN-PC can be applied in several different areas where sensing and numerical calculations, even the solution of differential equations, are needed.

  17. Artificial neural network application for predicting soil distribution coefficient of nickel

    International Nuclear Information System (INIS)

    Falamaki, Amin

    2013-01-01

    The distribution (or partition) coefficient (K d ) is an applicable parameter for modeling contaminant and radionuclide transport as well as risk analysis. Selection of this parameter may cause significant error in predicting the impacts of contaminant migration or site-remediation options. In this regards, various models were presented to predict K d values for different contaminants specially heavy metals and radionuclides. In this study, artificial neural network (ANN) is used to present simplified model for predicting K d of nickel. The main objective is to develop a more accurate model with a minimal number of parameters, which can be determined experimentally or select by review of different studies. In addition, the effects of training as well as the type of the network are considered. The K d values of Ni is strongly dependent on pH of the soil and mathematical relationships were presented between pH and K d of nickel recently. In this study, the same database of these presented models was used to verify that neural network may be more useful tools for predicting of K d . Two different types of ANN, multilayer perceptron and redial basis function, were used to investigate the effect of the network geometry on the results. In addition, each network was trained by 80 and 90% of the data and tested for 20 and 10% of the rest data. Then the results of the networks compared with the results of the mathematical models. Although the networks trained by 80 and 90% of the data the results show that all the networks predict with higher accuracy relative to mathematical models which were derived by 100% of data. More training of a network increases the accuracy of the network. Multilayer perceptron network used in this study predicts better than redial basis function network. - Highlights: ► Simplified models for predicting K d of nickel presented using artificial neural networks. ► Multilayer perceptron and redial basis function used to predict K d of nickel in

  18. Predictions of Gene Family Distributions in Microbial Genomes: Evolution by Gene Duplication and Modification

    International Nuclear Information System (INIS)

    Yanai, Itai; Camacho, Carlos J.; DeLisi, Charles

    2000-01-01

    A universal property of microbial genomes is the considerable fraction of genes that are homologous to other genes within the same genome. The process by which these homologues are generated is not well understood, but sequence analysis of 20 microbial genomes unveils a recurrent distribution of gene family sizes. We show that a simple evolutionary model based on random gene duplication and point mutations fully accounts for these distributions and permits predictions for the number of gene families in genomes not yet complete. Our findings are consistent with the notion that a genome evolves from a set of precursor genes to a mature size by gene duplications and increasing modifications. (c) 2000 The American Physical Society

  19. Predictions of Gene Family Distributions in Microbial Genomes: Evolution by Gene Duplication and Modification

    Energy Technology Data Exchange (ETDEWEB)

    Yanai, Itai; Camacho, Carlos J.; DeLisi, Charles

    2000-09-18

    A universal property of microbial genomes is the considerable fraction of genes that are homologous to other genes within the same genome. The process by which these homologues are generated is not well understood, but sequence analysis of 20 microbial genomes unveils a recurrent distribution of gene family sizes. We show that a simple evolutionary model based on random gene duplication and point mutations fully accounts for these distributions and permits predictions for the number of gene families in genomes not yet complete. Our findings are consistent with the notion that a genome evolves from a set of precursor genes to a mature size by gene duplications and increasing modifications. (c) 2000 The American Physical Society.

  20. A distributed predictive control approach for periodic flow-based networks: application to drinking water systems

    Science.gov (United States)

    Grosso, Juan M.; Ocampo-Martinez, Carlos; Puig, Vicenç

    2017-10-01

    This paper proposes a distributed model predictive control approach designed to work in a cooperative manner for controlling flow-based networks showing periodic behaviours. Under this distributed approach, local controllers cooperate in order to enhance the performance of the whole flow network avoiding the use of a coordination layer. Alternatively, controllers use both the monolithic model of the network and the given global cost function to optimise the control inputs of the local controllers but taking into account the effect of their decisions over the remainder subsystems conforming the entire network. In this sense, a global (all-to-all) communication strategy is considered. Although the Pareto optimality cannot be reached due to the existence of non-sparse coupling constraints, the asymptotic convergence to a Nash equilibrium is guaranteed. The resultant strategy is tested and its effectiveness is shown when applied to a large-scale complex flow-based network: the Barcelona drinking water supply system.

  1. Predictive typing of drug-induced neurological sufferings from studies of the distribution of labelled drugs

    International Nuclear Information System (INIS)

    Takasu, T.

    1980-01-01

    A drug given to an animal becomes widely distributed throughout the body, acting on the living mechanisms or structures, and is gradually excreted. Some drugs can remain in some parts of the body for a long period. For example, 14 C-chloramphenical was found to remain preferentially in the salivary gland, liver and bone marrow of mice 24 hours after its oral administration. If such a drug is given repeatedly, it could possibly accumulate gradually in these organs. Thus, when its accumulation in a particular part of the body exceeds a certain level, the living mechanism or structure may possibly be injured. The harmful effects of a drug in repeated administration are called its chronic toxicity. The author discusses whether it is possible to predict the toxicity of a drug by studying its distribution in relation to time, and, if possible, the points in time. This problem is studied especially in relation to the nervous system. (Auth.)

  2. Distributed model predictive control for constrained nonlinear systems with decoupled local dynamics.

    Science.gov (United States)

    Zhao, Meng; Ding, Baocang

    2015-03-01

    This paper considers the distributed model predictive control (MPC) of nonlinear large-scale systems with dynamically decoupled subsystems. According to the coupled state in the overall cost function of centralized MPC, the neighbors are confirmed and fixed for each subsystem, and the overall objective function is disassembled into each local optimization. In order to guarantee the closed-loop stability of distributed MPC algorithm, the overall compatibility constraint for centralized MPC algorithm is decomposed into each local controller. The communication between each subsystem and its neighbors is relatively low, only the current states before optimization and the optimized input variables after optimization are being transferred. For each local controller, the quasi-infinite horizon MPC algorithm is adopted, and the global closed-loop system is proven to be exponentially stable. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

  3. CFD prediction of flow and phase distribution in fuel assemblies with spacers

    Energy Technology Data Exchange (ETDEWEB)

    Anglart, H.; Nylund, O. [ABB Atom AB, Vasteras (Switzerland); Kurul, N. [Rensselaer Polytechnic Institute, Troy, NY (United States)] [and others

    1995-09-01

    This paper is concerned with the modeling and computation of multi-dimensional two-phase flows in BWR fuel assemblies. The modeling principles are presented based on using a two-fluid model in which lateral interfacial effects are accounted for. This model has been used to evaluate the velocity fields of both vapor and liquid phases, as well as phase distribution, between fuel elements in geometries similar to BWR fuel bundles. Furthermore, this model has been used to predict, in a detailed mechanistic manner, the effects of spacers on flow and phase distribution between, and pressure drop along, fuel elements. The related numerical simulations have been performed using a CFD computer code, CFDS-FLOW3D.

  4. Maxent modeling for predicting the potential geographical distribution of two peony species under climate change.

    Science.gov (United States)

    Zhang, Keliang; Yao, Linjun; Meng, Jiasong; Tao, Jun

    2018-09-01

    Paeonia (Paeoniaceae), an economically important plant genus, includes many popular ornamentals and medicinal plant species used in traditional Chinese medicine. Little is known about the properties of the habitat distribution and the important eco-environmental factors shaping the suitability. Based on high-resolution environmental data for current and future climate scenarios, we modeled the present and future suitable habitat for P. delavayi and P. rockii by Maxent, evaluated the importance of environmental factors in shaping their distribution, and identified distribution shifts under climate change scenarios. The results showed that the moderate and high suitable areas for P. delavayi and P. rockii encompassed ca. 4.46×10 5 km 2 and 1.89×10 5 km 2 , respectively. Temperature seasonality and isothermality were identified as the most critical factors shaping P. delavayi distribution, and UVB-4 and annual precipitation were identified as the most critical for shaping P. rockii distribution. Under the scenario with a low concentration of greenhouse gas emissions (RCP2.6), the range of both species increased as global warming intensified; however, under the scenario with higher concentrations of emissions (RCP8.5), the suitable habitat range of P. delavayi decreased while P. rockii increased. Overall, our prediction showed that a shift in distribution of suitable habitat to higher elevations would gradually become more significant. The information gained from this study should provide a useful reference for implementing long-term conservation and management strategies for these species. Copyright © 2018. Published by Elsevier B.V.

  5. The problem of predicting the size distribution of sediment supplied by hillslopes to rivers

    Science.gov (United States)

    Sklar, Leonard S.; Riebe, Clifford S.; Marshall, Jill A.; Genetti, Jennifer; Leclere, Shirin; Lukens, Claire L.; Merces, Viviane

    2017-01-01

    Sediments link hillslopes to river channels. The size of sediments entering channels is a key control on river morphodynamics across a range of scales, from channel response to human land use to landscape response to changes in tectonic and climatic forcing. However, very little is known about what controls the size distribution of particles eroded from bedrock on hillslopes, and how particle sizes evolve before sediments are delivered to channels. Here we take the first steps toward building a geomorphic transport law to predict the size distribution of particles produced on hillslopes and supplied to channels. We begin by identifying independent variables that can be used to quantify the influence of five key boundary conditions: lithology, climate, life, erosion rate, and topography, which together determine the suite of geomorphic processes that produce and transport sediments on hillslopes. We then consider the physical and chemical mechanisms that determine the initial size distribution of rock fragments supplied to the hillslope weathering system, and the duration and intensity of weathering experienced by particles on their journey from bedrock to the channel. We propose a simple modeling framework with two components. First, the initial rock fragment sizes are set by the distribution of spacing between fractures in unweathered rock, which is influenced by stresses encountered by rock during exhumation and by rock resistance to fracture propagation. That initial size distribution is then transformed by a weathering function that captures the influence of climate and mineralogy on chemical weathering potential, and the influence of erosion rate and soil depth on residence time and the extent of particle size reduction. Model applications illustrate how spatial variation in weathering regime can lead to bimodal size distributions and downstream fining of channel sediment by down-valley fining of hillslope sediment supply, two examples of hillslope control on

  6. A Distributed Model Predictive Control approach for the integration of flexible loads, storage and renewables

    DEFF Research Database (Denmark)

    Ferrarini, Luca; Mantovani, Giancarlo; Costanzo, Giuseppe Tommaso

    2014-01-01

    This paper presents an innovative solution based on distributed model predictive controllers to integrate the control and management of energy consumption, energy storage, PV and wind generation at customer side. The overall goal is to enable an advanced prosumer to autoproduce part of the energy...... he needs with renewable sources and, at the same time, to optimally exploit the thermal and electrical storages, to trade off its comfort requirements with different pricing schemes (including real-time pricing), and apply optimal control techniques rather than sub-optimal heuristics....

  7. Distributed Model Predictive Control for Active Power Control of Wind Farm

    DEFF Research Database (Denmark)

    Zhao, Haoran; Wu, Qiuwei; Rasmussen, Claus Nygaard

    2014-01-01

    This paper presents the active power control of a wind farm using the Distributed Model Predictive Controller (D- MPC) via dual decomposition. Different from the conventional centralized wind farm control, multiple objectives such as power reference tracking performance and wind turbine load can...... be considered to achieve a trade-off between them. Additionally, D- MPC is based on communication among the subsystems. Through the interaction among the neighboring subsystems, the global optimization could be achieved, which significantly reduces the computation burden. It is suitable for the modern large......-scale wind farm control....

  8. Robust Distributed Model Predictive Load Frequency Control of Interconnected Power System

    Directory of Open Access Journals (Sweden)

    Xiangjie Liu

    2013-01-01

    Full Text Available Considering the load frequency control (LFC of large-scale power system, a robust distributed model predictive control (RDMPC is presented. The system uncertainty according to power system parameter variation alone with the generation rate constraints (GRC is included in the synthesis procedure. The entire power system is composed of several control areas, and the problem is formulated as convex optimization problem with linear matrix inequalities (LMI that can be solved efficiently. It minimizes an upper bound on a robust performance objective for each subsystem. Simulation results show good dynamic response and robustness in the presence of power system dynamic uncertainties.

  9. Impact of different satellite soil moisture products on the predictions of a continuous distributed hydrological model

    Science.gov (United States)

    Laiolo, P.; Gabellani, S.; Campo, L.; Silvestro, F.; Delogu, F.; Rudari, R.; Pulvirenti, L.; Boni, G.; Fascetti, F.; Pierdicca, N.; Crapolicchio, R.; Hasenauer, S.; Puca, S.

    2016-06-01

    The reliable estimation of hydrological variables in space and time is of fundamental importance in operational hydrology to improve the flood predictions and hydrological cycle description. Nowadays remotely sensed data can offer a chance to improve hydrological models especially in environments with scarce ground based data. The aim of this work is to update the state variables of a physically based, distributed and continuous hydrological model using four different satellite-derived data (three soil moisture products and a land surface temperature measurement) and one soil moisture analysis to evaluate, even with a non optimal technique, the impact on the hydrological cycle. The experiments were carried out for a small catchment, in the northern part of Italy, for the period July 2012-June 2013. The products were pre-processed according to their own characteristics and then they were assimilated into the model using a simple nudging technique. The benefits on the model predictions of discharge were tested against observations. The analysis showed a general improvement of the model discharge predictions, even with a simple assimilation technique, for all the assimilation experiments; the Nash-Sutcliffe model efficiency coefficient was increased from 0.6 (relative to the model without assimilation) to 0.7, moreover, errors on discharge were reduced up to the 10%. An added value to the model was found in the rainfall season (autumn): all the assimilation experiments reduced the errors up to the 20%. This demonstrated that discharge prediction of a distributed hydrological model, which works at fine scale resolution in a small basin, can be improved with the assimilation of coarse-scale satellite-derived data.

  10. GIS Based Distributed Runoff Predictions in Variable Source Area Watersheds Employing the SCS-Curve Number

    Science.gov (United States)

    Steenhuis, T. S.; Mendoza, G.; Lyon, S. W.; Gerard Marchant, P.; Walter, M. T.; Schneiderman, E.

    2003-04-01

    Because the traditional Soil Conservation Service Curve Number (SCS-CN) approach continues to be ubiquitously used in GIS-BASED water quality models, new application methods are needed that are consistent with variable source area (VSA) hydrological processes in the landscape. We developed within an integrated GIS modeling environment a distributed approach for applying the traditional SCS-CN equation to watersheds where VSA hydrology is a dominant process. Spatial representation of hydrologic processes is important for watershed planning because restricting potentially polluting activities from runoff source areas is fundamental to controlling non-point source pollution. The methodology presented here uses the traditional SCS-CN method to predict runoff volume and spatial extent of saturated areas and uses a topographic index to distribute runoff source areas through watersheds. The resulting distributed CN-VSA method was incorporated in an existing GWLF water quality model and applied to sub-watersheds of the Delaware basin in the Catskill Mountains region of New York State. We found that the distributed CN-VSA approach provided a physically-based method that gives realistic results for watersheds with VSA hydrology.

  11. Predicting occupancy for pygmy rabbits in Wyoming: an independent evaluation of two species distribution models

    Science.gov (United States)

    Germaine, Stephen S.; Ignizio, Drew; Keinath, Doug; Copeland, Holly

    2014-01-01

    Species distribution models are an important component of natural-resource conservation planning efforts. Independent, external evaluation of their accuracy is important before they are used in management contexts. We evaluated the classification accuracy of two species distribution models designed to predict the distribution of pygmy rabbit Brachylagus idahoensis habitat in southwestern Wyoming, USA. The Nature Conservancy model was deductive and based on published information and expert opinion, whereas the Wyoming Natural Diversity Database model was statistically derived using historical observation data. We randomly selected 187 evaluation survey points throughout southwestern Wyoming in areas predicted to be habitat and areas predicted to be nonhabitat for each model. The Nature Conservancy model correctly classified 39 of 77 (50.6%) unoccupied evaluation plots and 65 of 88 (73.9%) occupied plots for an overall classification success of 63.3%. The Wyoming Natural Diversity Database model correctly classified 53 of 95 (55.8%) unoccupied plots and 59 of 88 (67.0%) occupied plots for an overall classification success of 61.2%. Based on 95% asymptotic confidence intervals, classification success of the two models did not differ. The models jointly classified 10.8% of the area as habitat and 47.4% of the area as nonhabitat, but were discordant in classifying the remaining 41.9% of the area. To evaluate how anthropogenic development affected model predictive success, we surveyed 120 additional plots among three density levels of gas-field road networks. Classification success declined sharply for both models as road-density level increased beyond 5 km of roads per km-squared area. Both models were more effective at predicting habitat than nonhabitat in relatively undeveloped areas, and neither was effective at accounting for the effects of gas-energy-development road networks. Resource managers who wish to know the amount of pygmy rabbit habitat present in an

  12. Do sophisticated epistemic beliefs predict meaningful learning? Findings from a structural equation model of undergraduate biology learning

    Science.gov (United States)

    Lee, Silvia Wen-Yu; Liang, Jyh-Chong; Tsai, Chin-Chung

    2016-10-01

    This study investigated the relationships among college students' epistemic beliefs in biology (EBB), conceptions of learning biology (COLB), and strategies of learning biology (SLB). EBB includes four dimensions, namely 'multiple-source,' 'uncertainty,' 'development,' and 'justification.' COLB is further divided into 'constructivist' and 'reproductive' conceptions, while SLB represents deep strategies and surface learning strategies. Questionnaire responses were gathered from 303 college students. The results of the confirmatory factor analysis and structural equation modelling showed acceptable model fits. Mediation testing further revealed two paths with complete mediation. In sum, students' epistemic beliefs of 'uncertainty' and 'justification' in biology were statistically significant in explaining the constructivist and reproductive COLB, respectively; and 'uncertainty' was statistically significant in explaining the deep SLB as well. The results of mediation testing further revealed that 'uncertainty' predicted surface strategies through the mediation of 'reproductive' conceptions; and the relationship between 'justification' and deep strategies was mediated by 'constructivist' COLB. This study provides evidence for the essential roles some epistemic beliefs play in predicting students' learning.

  13. How the Assumed Size Distribution of Dust Minerals Affects the Predicted Ice Forming Nuclei

    Science.gov (United States)

    Perlwitz, Jan P.; Fridlind, Ann M.; Garcia-Pando, Carlos Perez; Miller, Ron L.; Knopf, Daniel A.

    2015-01-01

    The formation of ice in clouds depends on the availability of ice forming nuclei (IFN). Dust aerosol particles are considered the most important source of IFN at a global scale. Recent laboratory studies have demonstrated that the mineral feldspar provides the most efficient dust IFN for immersion freezing and together with kaolinite for deposition ice nucleation, and that the phyllosilicates illite and montmorillonite (a member of the smectite group) are of secondary importance.A few studies have applied global models that simulate mineral specific dust to predict the number and geographical distribution of IFN. These studies have been based on the simple assumption that the mineral composition of soil as provided in data sets from the literature translates directly into the mineral composition of the dust aerosols. However, these tables are based on measurements of wet-sieved soil where dust aggregates are destroyed to a large degree. In consequence, the size distribution of dust is shifted to smaller sizes, and phyllosilicates like illite, kaolinite, and smectite are only found in the size range 2 m. In contrast, in measurements of the mineral composition of dust aerosols, the largest mass fraction of these phyllosilicates is found in the size range 2 m as part of dust aggregates. Conversely, the mass fraction of feldspar is smaller in this size range, varying with the geographical location. This may have a significant effect on the predicted IFN number and its geographical distribution.An improved mineral specific dust aerosol module has been recently implemented in the NASA GISS Earth System ModelE2. The dust module takes into consideration the disaggregated state of wet-sieved soil, on which the tables of soil mineral fractions are based. To simulate the atmospheric cycle of the minerals, the mass size distribution of each mineral in aggregates that are emitted from undispersed parent soil is reconstructed. In the current study, we test the null

  14. Molecular biology in a distributed world. A Kantian perspective on scientific practices and the human mind

    Directory of Open Access Journals (Sweden)

    Mariagrazia Portera

    2016-01-01

    Full Text Available In recent years the number of scholarly publications devoted to Kant's theory of biology has rapidly growing, with particular attention being given to Kant's thoughts about the concepts of teleology, function, organism, and their respective roles in scientific practice. Moving from these recent studies, and distancing itself from their mostly evolutionary background, the main aim of the present paper is to suggest an original "cognitive turn" in the interpretation of Kant's theory of biology. More specifically, the Authors will trace a connection between some Kantian theses about the “peculiar” or special nature of the human mind (intellectus ectypus, advanced in the Critique of the Power of Judgement (§ 76, 77, and some specific epistemological issues pertaining to the research practice of contemporary molecular biology.

  15. On the origin of distribution patterns of motifs in biological networks

    Directory of Open Access Journals (Sweden)

    Lesk Arthur M

    2008-08-01

    Full Text Available Abstract Background Inventories of small subgraphs in biological networks have identified commonly-recurring patterns, called motifs. The inference that these motifs have been selected for function rests on the idea that their occurrences are significantly more frequent than random. Results Our analysis of several large biological networks suggests, in contrast, that the frequencies of appearance of common subgraphs are similar in natural and corresponding random networks. Conclusion Indeed, certain topological features of biological networks give rise naturally to the common appearance of the motifs. We therefore question whether frequencies of occurrences are reasonable evidence that the structures of motifs have been selected for their functional contribution to the operation of networks.

  16. Novel Uses of In Vitro Data to Develop Quantitative Biological Activity Relationship Models for in Vivo Carcinogenicity Prediction.

    Science.gov (United States)

    Pradeep, Prachi; Povinelli, Richard J; Merrill, Stephen J; Bozdag, Serdar; Sem, Daniel S

    2015-04-01

    The availability of large in vitro datasets enables better insight into the mode of action of chemicals and better identification of potential mechanism(s) of toxicity. Several studies have shown that not all in vitro assays can contribute as equal predictors of in vivo carcinogenicity for development of hybrid Quantitative Structure Activity Relationship (QSAR) models. We propose two novel approaches for the use of mechanistically relevant in vitro assay data in the identification of relevant biological descriptors and development of Quantitative Biological Activity Relationship (QBAR) models for carcinogenicity prediction. We demonstrate that in vitro assay data can be used to develop QBAR models for in vivo carcinogenicity prediction via two case studies corroborated with firm scientific rationale. The case studies demonstrate the similarities between QBAR and QSAR modeling in: (i) the selection of relevant descriptors to be used in the machine learning algorithm, and (ii) the development of a computational model that maps chemical or biological descriptors to a toxic endpoint. The results of both the case studies show: (i) improved accuracy and sensitivity which is especially desirable under regulatory requirements, and (ii) overall adherence with the OECD/REACH guidelines. Such mechanism based models can be used along with QSAR models for prediction of mechanistically complex toxic endpoints. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  17. New genetic loci link adipose and insulin biology to body fat distribution

    NARCIS (Netherlands)

    D. Shungin (Dmitry); T.W. Winkler (Thomas W.); D.C. Croteau-Chonka (Damien); T. Ferreira (Teresa); A. Locke (Adam); R. Mägi (Reedik); R.J. Strawbridge (Rona); T.H. Pers (Tune); K. Fischer (Krista); A.E. Justice (Anne); T. Workalemahu (Tsegaselassie); J.M.W. Wu (Joseph M. W.); M.L. Buchkovich (Martin); N.L. Heard-Costa (Nancy); T.S. Roman (Tamara S.); A. Drong (Alexander); C. Song (Ci); S. Gustafsson (Stefan); F.R. Day (Felix); T. Esko (Tõnu); M. Fall (Magnus); Z. Kutalik (Zolta'n); J. Luan; J.C. Randall (Joshua); A. Scherag (Andre); S. Vedantam (Sailaja); A.R. Wood (Andrew); J. Chen (Jin); R.S.N. Fehrmann (Rudolf); J. Karjalainen (Juha); B. Kahali (Bratati); C.-T. Liu (Ching-Ti); E.M. Schmidt (Ellen); D. Absher (Devin); N. Amin (Najaf); M. Beekman (Marian); J.L. Bragg-Gresham (Jennifer L.); S. Buyske (Steven); A. Demirkan (Ayşe); G.B. Ehret (Georg); M.F. Feitosa (Mary Furlan); A. Goel (Anuj); A.U. Jackson (Anne); T. Johnson (Toby); M.E. Kleber (Marcus); K. Kristiansson (Kati); M. Mangino (Massimo); I.M. Leach (Irene Mateo); M.C. Medina-Gomez (Carolina); C. Palmer (Cameron); D. Pasko (Dorota); S. Pechlivanis (Sonali); M.J. Peters (Marjolein); I. Prokopenko (Inga); A. Stanca'kova' (Alena); Y.J. Sung (Yun Ju); T. Tanaka (Toshiko); A. Teumer (Alexander); J.V. van Vliet-Ostaptchouk (Jana); L. Yengo (Loic); W. Zhang (Weihua); E. Albrecht (Eva); J. Ärnlöv (Johan); G.M. Arscott (Gillian M.); S. Bandinelli (Stefania); A. Barrett (Angela); C. Bellis (Claire); A.J. Bennett (Amanda); C. Berne (Christian); M. Blüher (Matthias); S. Böhringer (Stefan); F. Bonnet (Fabrice); Y. Böttcher (Yvonne); M. Bruinenberg (M.); D.B. Carba (Delia B.); I.H. Caspersen (Ida H.); R. Clarke (Robert); E.W. Daw (E. Warwick); J. Deelen (Joris); E. Deelman (Ewa); G. Delgado; A.S.F. Doney (Alex); N. Eklund (Niina); M.R. Erdos (Michael); K. Estrada Gil (Karol); E. Eury (Elodie); N. Friedrich (Nele); M. Garcia (Melissa); V. Giedraitis (Vilmantas); B. Gigante (Bruna); A. Go (Attie); A. Golay (Alain); H. Grallert (Harald); T.B. Grammer (Tanja); J. Gräsler (Jürgen); J. Grewal (Jagvir); C.J. Groves (Christopher); T. Haller (Toomas); G. Hallmans (Göran); C.A. Hartman (Catharina); M. Hassinen (Maija); C. Hayward (Caroline); K. Heikkilä (Kauko); K.H. Herzig; Q. Helmer (Quinta); H.L. Hillege (Hans); O.L. Holmen (Oddgeir); S.C. Hunt (Steven); A. Isaacs (Aaron); T. Ittermann (Till); A.L. James (Alan); I. Johansson (Inger); T. Juliusdottir (Thorhildur); I.-P. Kalafati (Ioanna-Panagiota); L. Kinnunen (Leena); W. Koenig (Wolfgang); I.K. Kooner (Ishminder K.); W. Kratzer (Wolfgang); C. Lamina (Claudia); K. Leander (Karin); N.R. Lee (Nanette R.); P. Lichtner (Peter); L. Lind (Lars); J. Lindström (Jaana); S. Lobbens (Stéphane); M. Lorentzon (Mattias); F. MacH (François); P.K. Magnusson (Patrik); A. Mahajan (Anubha); W.L. McArdle (Wendy); C. Menni (Cristina); S. Merger (Sigrun); E. Mihailov (Evelin); L. Milani (Lili); R. Mills (Rebecca); A. Moayyeri (Alireza); K.L. Monda (Keri); S.P. Mooijaart (Simon); T.W. Mühleisen (Thomas); A. Mulas (Antonella); G. Müller (Gabriele); M. Müller-Nurasyid (Martina); R. Nagaraja (Ramaiah); M.A. Nalls (Michael); N. Narisu (Narisu); N. Glorioso (Nicola); I.M. Nolte (Ilja M.); M. Olden (Matthias); N.W. Rayner (Nigel William); F. Renström (Frida); J.S. Ried (Janina); N.R. Robertson (Neil R.); L.M. Rose (Lynda); S. Sanna (Serena); H. Scharnagl (Hubert); S. Scholtens (Salome); B. Sennblad (Bengt); T. Seufferlein (Thomas); C.M. Sitlani (Colleen); G.D. Smith; K. Stirrups (Kathy); H.M. Stringham (Heather); J. Sundstrom (Johan); M. Swertz (Morris); A.J. Swift (Amy); A.C. Syvanen; B. Tayo (Bamidele); B. Thorand (Barbara); G. Thorleifsson (Gudmar); A. Tomaschitz (Andreas); C. Troffa (Chiara); F.V.A. van Oort (Floor); N. Verweij (Niek); J.M. Vonk (Judith); L. Waite (Lindsay); R. Wennauer (Roman); T. Wilsgaard (Tom); M.K. Wojczynski (Mary ); A. Wong (Andrew); Q. Zhang (Qunyuan); J.H. Zhao (Jing Hua); E.P. Brennan (Eoin P.); M. Choi (Murim); P. Eriksson (Per); L. Folkersen (Lasse); A. Franco-Cereceda (Anders); A.G. Gharavi (Ali G.); A.K. Hedman (Asa); M.-F. Hivert (Marie-France); J. Huang (Jinyan); S. Kanoni (Stavroula); F. Karpe (Fredrik); S. Keildson (Sarah); K. Kiryluk (Krzysztof); L. Liang (Liming); R.P. Lifton (Richard); B. Ma (Baoshan); A.J. McKnight (Amy J.); R. McPherson (Ruth); A. Metspalu (Andres); J.L. Min (Josine L.); M.F. Moffatt (Miriam); G.W. Montgomery (Grant); J. Murabito (Joanne); G. Nicholson (Ggeorge); A.S. Dimas (Antigone); C. Olsson (Christian); J.R.B. Perry (John); E. Reinmaa (Eva); R.M. Salem (Rany); N. Sandholm (Niina); E.E. Schadt (Eric); R.A. Scott (Robert); L. Stolk (Lisette); E.E. Vallejo (Edgar E.); H.J. Westra (Harm-Jan); K.T. Zondervan (Krina); P. Amouyel (Philippe); D. Arveiler (Dominique); S.J.L. Bakker (Stephan); J.P. Beilby (John); R.N. Bergman (Richard); J. Blangero (John); M.J. Brown (Morris); M. Burnier (Michel); H. Campbell (Harry); A. Chakravarti (Aravinda); P.S. Chines (Peter); S. Claudi-Boehm (Simone); F.S. Collins (Francis); D.C. Crawford (Dana); J. Danesh (John); U. de Faire (Ulf); E.J.C. de Geus (Eco); M. Dörr (Marcus); R. Erbel (Raimund); K. Hagen (Knut); M. Farrall (Martin); E. Ferrannini (Ele); J. Ferrieres (Jean); N.G. Forouhi (Nita); T. Forrester (Terrence); O.H. Franco (Oscar); R.T. Gansevoort (Ron); C. Gieger (Christian); V. Gudnason (Vilmundur); C.A. Haiman (Christopher); T.B. Harris (Tamara); A.T. Hattersley (Andrew); M. Heliovaara (Markku); A.A. Hicks (Andrew); A. Hingorani (Aroon); W. Hoffmann (Wolfgang); A. Hofman (Albert); G. Homuth (Georg); S.E. Humphries (Steve); E. Hypponen (Elina); T. Illig (Thomas); M.-R. Jarvelin (Marjo-Riitta); B. Johansen (Berit); P. Jousilahti (Pekka); A. Jula (Antti); J. Kaprio (Jaakko); F. Kee (F.); S. Keinanen-Kiukaanniemi (Sirkka); J.S. Kooner (Jaspal S.); C. Kooperberg (Charles); P. Kovacs (Peter); A. Kraja (Aldi); M. Kumari (Meena); K. Kuulasmaa (Kari); J. Kuusisto (Johanna); T.A. Lakka (Timo); C. Langenberg (Claudia); L. Le Marchand (Loic); T. Lehtimäki (Terho); V. Lyssenko (Valeriya); S. Männistö (Satu); A. Marette (Andre'); T.C. Matise (Tara C.); C.A. McKenzie (Colin A.); B. McKnight (Barbara); A.W. Musk (Arthur); S. Möhlenkamp (Stefan); A.D. Morris (Andrew); M. Nelis (Mari); C. Ohlsson (Claes); A.J. Oldehinkel (Albertine); K.K. Ong (Ken K.); C. Palmer (Cameron); B.W.J.H. Penninx (Brenda); A. Peters (Annette); P.P. Pramstaller (Peter Paul); O. Raitakari (Olli); T. Rankinen (Tuomo); D.C. Rao (Dabeeru C.); T.K. Rice (Treva K.); P.M. Ridker (Paul); M.D. Ritchie (Marylyn D.); I. Rudan (Igor); V. Salomaa (Veikko); N.J. Samani (Nilesh); J. Saramies (Jouko); M.A. Sarzynski (Mark A.); P.E.H. Schwarz (Peter E. H.); A.R. Shuldiner (Alan); J.A. Staessen (Jan); V. Steinthorsdottir (Valgerdur); R.P. Stolk (Ronald); K. Strauch (Konstantin); A. Tönjes (Anke); A. Tremblay (Angelo); E. Tremoli (Elena); M.-C. Vohl (Marie-Claude); U. Völker (Uwe); P. Vollenweider (Peter); J.F. Wilson (James F); J.C.M. Witteman (Jacqueline); L.S. Adair (Linda); M. Bochud (Murielle); B.O. Boehm (Bernhard); S.R. Bornstein (Stefan R.); C. Bouchard (Claude); S. Cauchi (Ste'phane); M. Caulfield (Mark); J.C. Chambers (John C.); D.I. Chasman (Daniel); R.S. Cooper (Richard S.); G.V. Dedoussis (George); L. Ferrucci (Luigi); P. Froguel (Philippe); H.J. Grabe (Hans Jörgen); A. Hamsten (Anders); J. Hui (Jennie); K. Hveem (Kristian); K.-H. Jöckel (Karl-Heinz); M. Kivimaki (Mika); D. Kuh (Diana); M. Laakso (Markku); Y. Liu (YongMei); W. März (Winfried); P. Munroe (Patricia); I. Njølstad (Inger); B.A. Oostra (Ben); C.N.A. Palmer (Colin); N.L. Pedersen (Nancy L.); M. Perola (Markus); L. Perusse (Louis); U. Peters (Ulrike); C. Power (Christopher); T. Quertermous (Thomas); R. Rauramaa (Rainer); F. Rivadeneira Ramirez (Fernando); T. Saaristo (Timo); D. Saleheen; J. Sinisalo (Juha); P.E. Slagboom (Eline); H. Snieder (Harold); T.D. Spector (Timothy); U. Thorsteinsdottir (Unnur); M. Stumvoll (Michael); J. Tuomilehto (Jaakko); A.G. Uitterlinden (André); M. Uusitupa (Matti); P. van der Harst (Pim); G. Veronesi (Giovanni); M. Walker (Mark); N.J. Wareham (Nick); H. Watkins (Hugh); H.E. Wichmann (Heinz Erich); G.R. Abecasis (Gonçalo); T.L. Assimes (Themistocles); S.I. Berndt (Sonja); M. Boehnke (Michael); I.B. Borecki (Ingrid); P. Deloukas (Panagiotis); L. Franke (Lude); T.M. Frayling (Timothy); L. Groop (Leif); D. Hunter (David); R.C. Kaplan (Robert); J.R. O´Connell; L. Qi (Lu); D. Schlessinger (David); D.P. Strachan (David); J-A. Zwart (John-Anker); C.M. van Duijn (Cornelia); C.J. Willer (Cristen); P.M. Visscher (Peter); J. Yang (Joanna); J.N. Hirschhorn (Joel N.); M.C. Zillikens (Carola); M.I. McCarthy (Mark); E.K. Speliotes (Elizabeth); K.E. North (Kari); C.S. Fox (Caroline S.); I.E. Barroso (Inês); P.W. Franks (Paul); D. Anderson (Denise); E. Ingelsson (Erik); I.M. Heid (Iris); R.J.F. Loos (Ruth); L.A. Cupples (Adrienne); A.P. Morris (Andrew); C.M. Lindgren (Cecilia); K.L. Mohlke (Karen)

    2015-01-01

    textabstractBody fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct

  18. New genetic loci link adipose and insulin biology to body fat distribution

    NARCIS (Netherlands)

    Shungin, Dmitry; Winkler, Thomas W.; Croteau-Chonka, Damien C.; Ferreira, Teresa; Locke, Adam E.; Mägi, Reedik; Strawbridge, Rona J.; Pers, Tune H.; Fischer, Krista; Justice, Anne E.; Workalemahu, Tsegaselassie; Wu, Joseph M. W.; Buchkovich, Martin L.; Heard-Costa, Nancy L.; Roman, Tamara S.; Drong, Alexander W.; Song, Ci; Gustafsson, Stefan; Day, Felix R.; Esko, Tonu; Fall, Tove; Kutalik, Zoltán; Luan, Jian'an; Randall, Joshua C.; Scherag, André; Vedantam, Sailaja; Wood, Andrew R.; Chen, Jin; Fehrmann, Rudolf; Karjalainen, Juha; Kahali, Bratati; Liu, Ching-Ti; Schmidt, Ellen M.; Absher, Devin; Amin, Najaf; Anderson, Denise; Beekman, Marian; Bragg-Gresham, Jennifer L.; Buyske, Steven; Demirkan, Ayse; Ehret, Georg B.; Feitosa, Mary F.; Goel, Anuj; Jackson, Anne U.; Johnson, Toby; Kleber, Marcus E.; Kristiansson, Kati; Mangino, Massimo; Mateo Leach, Irene; Medina-Gomez, Carolina; Palmer, Cameron D.; Pasko, Dorota; Pechlivanis, Sonali; Peters, Marjolein J.; Prokopenko, Inga; Stančáková, Alena; Ju Sung, Yun; Tanaka, Toshiko; Teumer, Alexander; van Vliet-Ostaptchouk, Jana V.; Yengo, Loïc; Zhang, Weihua; Albrecht, Eva; Ärnlöv, Johan; Arscott, Gillian M.; Bandinelli, Stefania; Barrett, Amy; Bellis, Claire; Bennett, Amanda J.; Berne, Christian; Blüher, Matthias; Böhringer, Stefan; Bonnet, Fabrice; Böttcher, Yvonne; Bruinenberg, Marcel; Carba, Delia B.; Caspersen, Ida H.; Clarke, Robert; Daw, E. Warwick; Deelen, Joris; Deelman, Ewa; Delgado, Graciela; Doney, Alex S. F.; Eklund, Niina; Erdos, Michael R.; Estrada, Karol; Eury, Elodie; Friedrich, Nele; Garcia, Melissa E.; Giedraitis, Vilmantas; Gigante, Bruna; Go, Alan S.; Golay, Alain; Grallert, Harald; Grammer, Tanja B.; Gräßler, Jürgen; Grewal, Jagvir; Groves, Christopher J.; Haller, Toomas; Hallmans, Goran; Hartman, Catharina A.; Hassinen, Maija; Hayward, Caroline; Heikkilä, Kauko; Herzig, Karl-Heinz; Helmer, Quinta; Hillege, Hans L.; Holmen, Oddgeir; Hunt, Steven C.; Isaacs, Aaron; Ittermann, Till; James, Alan L.; Johansson, Ingegerd; Juliusdottir, Thorhildur; Kalafati, Ioanna-Panagiota; Kinnunen, Leena; Koenig, Wolfgang; Kooner, Ishminder K.; Kratzer, Wolfgang; Lamina, Claudia; Leander, Karin; Lee, Nanette R.; Lichtner, Peter; Lind, Lars; Lindström, Jaana; Lobbens, Stéphane; Lorentzon, Mattias; Mach, François; Magnusson, Patrik K. E.; Mahajan, Anubha; McArdle, Wendy L.; Menni, Cristina; Merger, Sigrun; Mihailov, Evelin; Milani, Lili; Mills, Rebecca; Moayyeri, Alireza; Monda, Keri L.; Mooijaart, Simon P.; Mühleisen, Thomas W.; Mulas, Antonella; Müller, Gabriele; Müller-Nurasyid, Martina; Nagaraja, Ramaiah; Nalls, Michael A.; Narisu, Narisu; Glorioso, Nicola; Nolte, Ilja M.; Olden, Matthias; Rayner, Nigel W.; Renstrom, Frida; Ried, Janina S.; Robertson, Neil R.; Rose, Lynda M.; Sanna, Serena; Scharnagl, Hubert; Scholtens, Salome; Sennblad, Bengt; Seufferlein, Thomas; Sitlani, Colleen M.; Vernon Smith, Albert; Stirrups, Kathleen; Stringham, Heather M.; Sundström, Johan; Swertz, Morris A.; Swift, Amy J.; Syvänen, Ann-Christine; Tayo, Bamidele O.; Thorand, Barbara; Thorleifsson, Gudmar; Tomaschitz, Andreas; Troffa, Chiara; van Oort, Floor V. A.; Verweij, Niek; Vonk, Judith M.; Waite, Lindsay L.; Wennauer, Roman; Wilsgaard, Tom; Wojczynski, Mary K.; Wong, Andrew; Zhang, Qunyuan; Hua Zhao, Jing; Brennan, Eoin P.; Choi, Murim; Eriksson, Per; Folkersen, Lasse; Franco-Cereceda, Anders; Gharavi, Ali G.; Hedman, Åsa K.; Hivert, Marie-France; Huang, Jinyan; Kanoni, Stavroula; Karpe, Fredrik; Keildson, Sarah; Kiryluk, Krzysztof; Liang, Liming; Lifton, Richard P.; Ma, Baoshan; McKnight, Amy J.; McPherson, Ruth; Metspalu, Andres; Min, Josine L.; Moffatt, Miriam F.; Montgomery, Grant W.; Murabito, Joanne M.; Nicholson, George; Nyholt, Dale R.; Olsson, Christian; Perry, John R. B.; Reinmaa, Eva; Salem, Rany M.; Sandholm, Niina; Schadt, Eric E.; Scott, Robert A.; Stolk, Lisette; Vallejo, Edgar E.; Westra, Harm-Jan; Zondervan, Krina T.; Amouyel, Philippe; Arveiler, Dominique; Bakker, Stephan J. L.; Beilby, John; Bergman, Richard N.; Blangero, John; Brown, Morris J.; Burnier, Michel; Campbell, Harry; Chakravarti, Aravinda; Chines, Peter S.; Claudi-Boehm, Simone; Collins, Francis S.; Crawford, Dana C.; Danesh, John; de Faire, Ulf; de Geus, Eco J. C.; Dörr, Marcus; Erbel, Raimund; Eriksson, Johan G.; Farrall, Martin; Ferrannini, Ele; Ferrières, Jean; Forouhi, Nita G.; Forrester, Terrence; Franco, Oscar H.; Gansevoort, Ron T.; Gieger, Christian; Gudnason, Vilmundur; Haiman, Christopher A.; Harris, Tamara B.; Hattersley, Andrew T.; Heliövaara, Markku; Hicks, Andrew A.; Hingorani, Aroon D.; Hoffmann, Wolfgang; Hofman, Albert; Homuth, Georg; Humphries, Steve E.; Hyppönen, Elina; Illig, Thomas; Jarvelin, Marjo-Riitta; Johansen, Berit; Jousilahti, Pekka; Jula, Antti M.; Kaprio, Jaakko; Kee, Frank; Keinanen-Kiukaanniemi, Sirkka M.; Kooner, Jaspal S.; Kooperberg, Charles; Kovacs, Peter; Kraja, Aldi T.; Kumari, Meena; Kuulasmaa, Kari; Kuusisto, Johanna; Lakka, Timo A.; Langenberg, Claudia; Le Marchand, Loic; Lehtimäki, Terho; Lyssenko, Valeriya; Männistö, Satu; Marette, André; Matise, Tara C.; McKenzie, Colin A.; McKnight, Barbara; Musk, Arthur W.; Möhlenkamp, Stefan; Morris, Andrew D.; Nelis, Mari; Ohlsson, Claes; Oldehinkel, Albertine J.; Ong, Ken K.; Palmer, Lyle J.; Penninx, Brenda W.; Peters, Annette; Pramstaller, Peter P.; Raitakari, Olli T.; Rankinen, Tuomo; Rao, D. C.; Rice, Treva K.; Ridker, Paul M.; Ritchie, Marylyn D.; Rudan, Igor; Salomaa, Veikko; Samani, Nilesh J.; Saramies, Jouko; Sarzynski, Mark A.; Schwarz, Peter E. H.; Shuldiner, Alan R.; Staessen, Jan A.; Steinthorsdottir, Valgerdur; Stolk, Ronald P.; Strauch, Konstantin; Tönjes, Anke; Tremblay, Angelo; Tremoli, Elena; Vohl, Marie-Claude; Völker, Uwe; Vollenweider, Peter; Wilson, James F.; Witteman, Jacqueline C.; Adair, Linda S.; Bochud, Murielle; Boehm, Bernhard O.; Bornstein, Stefan R.; Bouchard, Claude; Cauchi, Stéphane; Caulfield, Mark J.; Chambers, John C.; Chasman, Daniel I.; Cooper, Richard S.; Dedoussis, George; Ferrucci, Luigi; Froguel, Philippe; Grabe, Hans-Jörgen; Hamsten, Anders; Hui, Jennie; Hveem, Kristian; Jöckel, Karl-Heinz; Kivimaki, Mika; Kuh, Diana; Laakso, Markku; Liu, Yongmei; März, Winfried; Munroe, Patricia B.; Njølstad, Inger; Oostra, Ben A.; Palmer, Colin N. A.; Pedersen, Nancy L.; Perola, Markus; Pérusse, Louis; Peters, Ulrike; Power, Chris; Quertermous, Thomas; Rauramaa, Rainer; Rivadeneira, Fernando; Saaristo, Timo E.; Saleheen, Danish; Sinisalo, Juha; Slagboom, P. Eline; Snieder, Harold; Spector, Tim D.; Thorsteinsdottir, Unnur; Stumvoll, Michael; Tuomilehto, Jaakko; Uitterlinden, André G.; Uusitupa, Matti; van der Harst, Pim; Veronesi, Giovanni; Walker, Mark; Wareham, Nicholas J.; Watkins, Hugh; Wichmann, H.-Erich; Abecasis, Goncalo R.; Assimes, Themistocles L.; Berndt, Sonja I.; Boehnke, Michael; Borecki, Ingrid B.; Deloukas, Panos; Franke, Lude; Frayling, Timothy M.; Groop, Leif C.; Hunter, David J.; Kaplan, Robert C.; O'Connell, Jeffrey R.; Qi, Lu; Schlessinger, David; Strachan, David P.; Stefansson, Kari; van Duijn, Cornelia M.; Willer, Cristen J.; Visscher, Peter M.; Yang, Jian; Hirschhorn, Joel N.; Zillikens, M. Carola; McCarthy, Mark I.; Speliotes, Elizabeth K.; North, Kari E.; Fox, Caroline S.; Barroso, Inês; Franks, Paul W.; Ingelsson, Erik; Heid, Iris M.; Loos, Ruth J. F.; Cupples, L. Adrienne; Morris, Andrew P.; Lindgren, Cecilia M.; Mohlke, Karen L.; Dastani, Zari; Timpson, Nicholas; Yuan, Xin; Henneman, Peter; Kizer, Jorge R.; Lyytikainen, Leo-Pekka; Fuchsberger, Christian; Small, Kerrin; Coassin, Stefan; Lohman, Kurt; Pankow, James S.; Uh, Hae-Won; Wu, Ying; Bidulescu, Aurelian; Rasmussen-Torvik, Laura J.; Greenwood, Celia M. T.; Ladouceur, Martin; Grimsby, Jonna; Manning, Alisa K.; Kooner, Jaspal; Mooser, Vincent E.; Kapur, Karen A.; Chambers, John; Frants, Rune; Willemsvan-vanDijk, Ko; Willems, Sara M.; Winkler, Thomas; Psaty, Bruce M.; Tracy, Russell P.; Brody, Jennifer; Chen, Ida; Viikari, Jorma; Kähönen, Mika; Evans, David M.; St Pourcain, Beate; Sattar, Naveed; Wood, Andy; Carlson, Olga D.; Egan, Josephine M.; van Heemst, Diana; Kedenko, Lyudmyla; Nuotio, Marja-Liisa; Loo, Britt-Marie; Harris, Tamara; Garcia, Melissa; Kanaya, Alka; Haun, Margot; Klopp, Norman; Wichmann, H. Erich; Katsareli, Efi; Couper, David J.; Duncan, Bruce B.; Kloppenburg, Margreet; Borja, Judith B.; Wilson, James G.; Musani, Solomon; Guo, Xiuqing; Semple, Robert; Teslovich, Tanya M.; Allison, Matthew A.; Redline, Susan; Buxbaum, Sarah G.; Meulenbelt, Ingrid; Ballantyne, Christie M.; Dedoussis, George V.; Hu, Frank B.; Paulweber, Bernhard; Spector, Timothy D.; Jula, Antti; Raitakari, Olli; Florez, Jose C.; Smith, George Davey; Siscovick, David S.; Kronenberg, Florian; van Duijn, Cornelia; Waterworth, Dawn M.; Meigs, James B.; Dupuis, Josee; Richards, John Brent; Willenborg, Christina; Thompson, John R.; Erdmann, Jeanette; Goldstein, Benjamin A.; König, Inke R.; Cazier, Jean-Baptiste; Johansson, Åsa; Hall, Alistair S.; Lee, Jong-Young; Esko, Tõnu; Grundberg, Elin; Havulinna, Aki S.; Ho, Weang K.; Hopewell, Jemma C.; Eriksson, Niclas; Lundmark, Per; Lyytikäinen, Leo-Pekka; Rafelt, Suzanne; Tikkanen, Emmi; van Zuydam, Natalie; Voight, Benjamin F.; Ziegler, Andreas; Altshuler, David; Balmforth, Anthony J.; Braund, Peter S.; Burgdorf, Christof; Cox, David; Dimitriou, Maria; Do, Ron; El Mokhtari, NourEddine; Fontanillas, Pierre; Groop, Leif; Hager, Jörg; Hallmans, Göran; Han, Bok-Ghee; Hunt, Sarah E.; Kang, Hyun M.; Kessler, Thorsten; Knowles, Joshua W.; Kolovou, Genovefa; Langford, Cordelia; Lokki, Marja-Liisa; Lundmark, Anders; Meisinger, Christa; Melander, Olle; Maouche, Seraya; Nikus, Kjell; Peden, John F.; Rayner, N. William; Rasheed, Asif; Rosinger, Silke; Rubin, Diana; Rumpf, Moritz P.; Schäfer, Arne; Sivananthan, Mohan; Stewart, Alexandre F. R.; Tan, Sian-Tsung; Thorgeirsson, Gudmundur; van der Schoot, C. Ellen; Wagner, Peter J.; Wells, George A.; Wild, Philipp S.; Yang, Tsun-Po; Basart, Hanneke; Boerwinkle, Eric; Brambilla, Paolo; Cambien, Francois; Cupples, Adrienne L.; Dehghan, Abbas; Diemert, Patrick; Epstein, Stephen E.; Evans, Alun; Ferrario, Marco M.; Gauguier, Dominique; Goodall, Alison H.; Gudnason, Villi; Hazen, Stanley L.; Holm, Hilma; Iribarren, Carlos; Jang, Yangsoo; Kim, Hyo-Soo; Laaksonen, Reijo; Lee, Ji-Young; Ouwehand, Willem H.; Parish, Sarah; Park, Jeong E.; Rader, Daniel J.; Schadt, Eric; Shah, Svati H.; Stark, Klaus; Trégouët, David-Alexandre; Virtamo, Jarmo; Wallentin, Lars; Wareham, Nicholas; Zimmermann, Martina E.; Nieminen, Markku S.; Hengstenberg, Christian; Sandhu, Manjinder S.; Pastinen, Tomi; Hovingh, G. Kees; Zalloua, Pierre A.; Siegbahn, Agneta; Schreiber, Stefan; Ripatti, Samuli; Blankenberg, Stefan S.; O'Donnell, Christopher; Reilly, Muredach P.; Collins, Rory; Kathiresan, Sekar; Roberts, Robert; Schunkert, Heribert; Pattaro, Cristian; Köttgen, Anna; Garnaas, Maija; Böger, Carsten A.; Chen, Ming-Huei; Tin, Adrienne; Taliun, Daniel; Li, Man; Gao, Xiaoyi; Gorski, Mathias; Yang, Qiong; Hundertmark, Claudia; Foster, Meredith C.; O'Seaghdha, Conall M.; Glazer, Nicole; Smith, Albert V.; Struchalin, Maksim; Li, Guo; Johnson, Andrew D.; Gierman, Hinco J.; Feitosa, Mary; Hwang, Shih-Jen; Atkinson, Elizabeth J.; Cornelis, Marilyn C.; Chouraki, Vincent; Holliday, Elizabeth G.; Sorice, Rossella; Kutalik, Zoltan; Deshmukh, Harshal; Ulivi, Sheila; Chu, Audrey Y.; Murgia, Federico; Trompet, Stella; Imboden, Medea; Kollerits, Barbara; Pistis, Giorgio; Launer, Lenore J.; Aspelund, Thor; Eiriksdottir, Gudny; Mitchell, Braxton D.; Schmidt, Helena; Cavalieri, Margherita; Rao, Madhumathi; de Andrade, Mariza; Turner, Stephen T.; Ding, Jingzhong; Andrews, Jeanette S.; Freedman, Barry I.; Döring, Angela; Wichmann, H. -Erich; Kolcic, Ivana; Zemunik, Tatijana; Boban, Mladen; Minelli, Cosetta; Wheeler, Heather E.; Igl, Wilmar; Zaboli, Ghazal; Wild, Sarah H.; Wright, Alan F.; Ellinghaus, David; Nöthlings, Ute; Jacobs, Gunnar; Biffar, Reiner; Endlich, Karlhans; Ernst, Florian; Kroemer, Heyo K.; Nauck, Matthias; Stracke, Sylvia; Völzke, Henry; Uitterlinden, Andre G.; Aulchenko, Yurii S.; Polasek, Ozren; Hastie, Nick; Vitart, Veronique; Helmer, Catherine; Wang, Jie Jin; Ruggiero, Daniela; Bergmann, Sven; Nikopensius, Tiit; Province, Michael; Ketkar, Shamika; Colhoun, Helen; Doney, Alex; Robino, Antonietta; Giulianini, Franco; Krämer, Bernhard K.; Portas, Laura; Ford, Ian; Buckley, Brendan M.; Adam, Martin; Thun, Gian-Andri; Sala, Cinzia; Metzger, Marie; Mitchell, Paul; Ciullo, Marina; Kim, Stuart K.; Palmer, Colin; Gasparini, Paolo; Pirastu, Mario; Jukema, J. Wouter; Probst-Hensch, Nicole M.; Toniolo, Daniela; Coresh, Josef; Schmidt, Reinhold; Borecki, Ingrid; Kardia, Sharon L. R.; Curhan, Gary C.; Gyllensten, Ulf; Franke, Andre; Rettig, Rainer; Witteman, Jacqueline C. M.; Ridker, Paul; Parsa, Afshin; Goessling, Wolfram; Kao, W. H. Linda; de Boer, Ian H.; Glazer, Nicole L.; Peralta, Carmen A.; Zhao, Jing Hua; Akylbekova, Ermeg; Kramer, Holly; Arking, Dan E.; Franceschini, Nora; Egan, Josephine; Hernandez, Dena; Reilly, Muredach; Townsend, Raymond R.; Lumley, Thomas; Kestenbaum, Bryan; Haritunians, Talin; Waeber, Gerard; Mooser, Vincent; Waterworth, Dawn; Lu, Xiaoning; Leak, Tennille S.; Aasarød, Knut; Skorpen, Frank; Baumert, Jens; Devuyst, Olivier; Mychaleckyj, Josyf C.; Hastie, Nicholas D.; Curhan, Gary; Hallan, Stein; Navis, Gerjan; Shlipak, Michael G.; Bull, Shelley B.; Paterson, Andrew D.; Rotter, Jerome I.; Beckmann, Jacques S.; Dreisbach, Albert W.; Kao, W. H. L.; Styrkarsdottir, Unnur; Evangelou, Evangelos; Hsu, Yi-Hsiang; Duncan, Emma L.; Ntzani, Evangelia E.; Oei, Ling; Albagha, Omar M. E.; Kemp, John P.; Koller, Daniel L.; Minster, Ryan L.; Vandenput, Liesbeth; Willner, Dana; Xiao, Su-Mei; Yerges-Armstrong, Laura M.; Zheng, Hou-Feng; Alonso, Nerea; Eriksson, Joel; Kammerer, Candace M.; Kaptoge, Stephen K.; Leo, Paul J.; Wilson, Scott G.; Aalto, Ville; Alen, Markku; Aragaki, Aaron K.; Center, Jacqueline R.; Dailiana, Zoe; Duggan, David J.; Garcia-Giralt, Natàlia; Giroux, Sylvie; Hocking, Lynne J.; Husted, Lise Bjerre; Jameson, Karen A.; Khusainova, Rita; Kim, Ghi Su; Koromila, Theodora; Kruk, Marcin; Laaksonen, Marika; LaCroix, Andrea Z.; Lee, Seung Hun; Leung, Ping C.; Lewis, Joshua R.; Masi, Laura; Mencej-Bedrac, Simona; Nguyen, Tuan V.; Nogues, Xavier; Patel, Millan S.; Prezelj, Janez; Scollen, Serena; Siggeirsdottir, Kristin; Svensson, Olle; Trummer, Olivia; van Schoor, Natasja M.; Woo, Jean; Zhu, Kun; Balcells, Susana; Brandi, Maria Luisa; Cheng, Sulin; Christiansen, Claus; Cooper, Cyrus; Frost, Morten; Goltzman, David; González-Macías, Jesús; Karlsson, Magnus; Khusnutdinova, Elza; Koh, Jung-Min; Kollia, Panagoula; Langdahl, Bente Lomholt; Leslie, William D.; Lips, Paul; Ljunggren, Östen; Lorenc, Roman S.; Marc, Janja; Mellström, Dan; Obermayer-Pietsch, Barbara; Olmos, José M.; Pettersson-Kymmer, Ulrika; Reid, David M.; Riancho, José A.; Rousseau, François; Tang, Nelson L. S.; Urreizti, Roser; van Hul, Wim; Zarrabeitia, María T.; Castano-Betancourt, Martha; Herrera, Lizbeth; Ingvarsson, Thorvaldur; Johannsdottir, Hrefna; Kwan, Tony; Li, Rui; Luben, Robert; Medina-Gómez, Carolina; Palsson, Stefan Th; Reppe, Sjur; Sigurdsson, Gunnar; van Meurs, Joyce B. J.; Verlaan, Dominique; Williams, Frances M. K.; Zhou, Yanhua; Gautvik, Kaare M.; Raychaudhuri, Soumya; Cauley, Jane A.; Clark, Graeme R.; Cummings, Steven R.; Danoy, Patrick; Dennison, Elaine M.; Eastell, Richard; Eisman, John A.; Jackson, Rebecca D.; Jones, Graeme; Khaw, Kay-Tee; McCloskey, Eugene; Nandakumar, Kannabiran; Nicholson, Geoffrey C.; Peacock, Munro; Pols, Huibert A. P.; Prince, Richard L.; Reid, Ian R.; Robbins, John; Sambrook, Philip N.; Sham, Pak Chung; Tylavsky, Frances A.; Wareham, Nick J.; Econs, Michael J.; Kung, Annie Wai Chee; Reeve, Jonathan; Streeten, Elizabeth A.; Karasik, David; Richards, J. Brent; Brown, Matthew A.; Ralston, Stuart H.; Ioannidis, John P. A.; Kiel, Douglas P.; McKnight, Amy Jayne; Forsblom, Carol; Isakova, Tamara; McKay, Gareth J.; Williams, Winfred W.; Sadlier, Denise M.; Mäkinen, Ville-Petteri; Swan, Elizabeth J.; Palmer, Cameron; Boright, Andrew P.; Ahlqvist, Emma; Deshmukh, Harshal A.; Keller, Benjamin J.; Huang, Huateng; Ahola, Aila; Fagerholm, Emma; Gordin, Daniel; Harjutsalo, Valma; He, Bing; Heikkilä, Outi; Hietala, Kustaa; Kytö, Janne; Lahermo, Päivi; Lehto, Markku; Österholm, Anne-May; Parkkonen, Maija; Pitkäniemi, Janne; Rosengård-Bärlund, Milla; Saraheimo, Markku; Sarti, Cinzia; Söderlund, Jenny; Soro-Paavonen, Aino; Syreeni, Anna; Thorn, Lena M.; Tikkanen, Heikki; Tolonen, Nina; Tryggvason, Karl; Wadén, Johan; Gill, Geoffrey V.; Prior, Sarah; Guiducci, Candace; Mirel, Daniel B.; Taylor, Andrew; Hosseini, Mohsen; Parving, Hans-Henrik; Rossing, Peter; Tarnow, Lise; Ladenvall, Claes; Alhenc-Gelas, François; Lefebvre, Pierre; Rigalleau, Vincent; Roussel, Ronan; Tregouet, David-Alexandre; Maestroni, Anna; Maestroni, Silvia; Falhammar, Henrik; Gu, Tianwei; Möllsten, Anna; Cimponeriu, Dan; Mihai, Ioana; Mota, Maria; Mota, Eugen; Serafinceanu, Cristian; Stavarachi, Monica; Hanson, Robert L.; Nelson, Robert G.; Kretzler, Matthias; Colhoun, Helen M.; Panduru, Nicolae Mircea; Gu, Harvest F.; Brismar, Kerstin; Zerbini, Gianpaolo; Hadjadj, Samy; Marre, Michel; Lajer, Maria; Waggott, Daryl; Savage, David A.; Bain, Stephen C.; Martin, Finian; Godson, Catherine; Groop, Per-Henrik; Maxwell, Alexander P.; Sengupta, Sebanti; Peloso, Gina M.; Ganna, Andrea; Mora, Samia; Chang, Hsing-Yi; Demirkan, Ayşe; den Hertog, Heleen M.; Donnelly, Louise A.; Fraser, Ross M.; Freitag, Daniel F.; Gurdasani, Deepti; Kaakinen, Marika; Kettunen, Johannes; Li, Xiaohui; Montasser, May E.; Petersen, Ann-Kristin; Saxena, Richa; Service, Susan K.; Shah, Sonia; Sidore, Carlo; Surakka, Ida; van den Herik, Evita G.; Volcik, Kelly A.; Asiki, Gershim; Been, Latonya F.; Bolton, Jennifer L.; Bonnycastle, Lori L.; Burnett, Mary S.; Cesana, Giancarlo; Elliott, Paul; Eyjolfsson, Gudmundur Ingi; Goodarzi, Mark O.; Gravito, Martha L.; Hartikainen, Anna-Liisa; Hung, Yi-Jen; Jones, Michelle R.; Kaleebu, Pontiano; Kastelein, John J. P.; Kim, Eric; Komulainen, Pirjo; Lin, Shih-Yi; Müller, Gabrielle; Nieminen, Tuomo V. M.; Nsubuga, Rebecca N.; Olafsson, Isleifur; Palotie, Aarno; Papamarkou, Theodore; Pomilla, Cristina; Pouta, Anneli; Ruokonen, Aimo; Samani, Nilesh; Seeley, Janet; Silander, Kaisa; Tiret, Laurence; van Pelt, L. Joost; Wainwright, Nicholas; Wijmenga, Cisca; Willemsen, Gonneke; Young, Elizabeth H.; Bennett, Franklyn; Boomsma, Dorret I.; Bovet, Pascal; Chen, Yii-Der Ida; Feranil, Alan B.; Freimer, Nelson B.; Hingorani, Aroon; Hsiung, Chao Agnes; Järvelin, Marjo-Riitta; Kesäniemi, Antero; Koudstaal, Peter J.; Krauss, Ronald M.; Kyvik, Kirsten O.; Martin, Nicholas G.; Meneton, Pierre; Moilanen, Leena; Price, Jackie F.; Sanghera, Dharambir K.; Sheu, Wayne H.-H.; Whitfield, John B.; Wolffenbuttel, Bruce H. R.; Ordovas, Jose M.; Rich, Stephen S.; Abecasis, Gonçalo R.; Abecasis, Gonçalo; Caulfield, Mark; Chasman, Dan; Ehret, Georg; Johnson, Andrew; Johnson, Louise; Larson, Martin; Levy, Daniel; Munroe, Patricia; Newton-Cheh, Christopher; O'Reilly, Paul; Palmas, Walter; Psaty, Bruce; Rice, Kenneth; Smith, Albert; Snider, Harold; Tobin, Martin; Verwoert, Germaine; Rice, Kenneth M.; Tobin, Martin D.; Verwoert, Germaine C.; Pihur, Vasyl; O'Reilly, Paul F.; Launer, Lenore; Aulchenko, Yurii; Heath, Simon; Sõber, Siim; Arora, Pankaj; Zhang, Feng; Lucas, Gavin; Milaneschi, Yuri; Parker, Alex N.; Fava, Cristiano; Fox, Ervin R.; Go, Min Jin; Kao, Wen Hong Linda; Sjögren, Marketa; Vinay, D. G.; Alexander, Myriam; Tabara, Yasuharu; Shaw-Hawkins, Sue; Whincup, Peter H.; Shi, Gang; Tayo, Bamidele; Seielstad, Mark; Sim, Xueling; Nguyen, Khanh-Dung Hoang; Matullo, Giuseppe; Gaunt, Tom R.; Onland-Moret, N. Charlotte; Cooper, Matthew N.; Platou, Carl G. P.; Org, Elin; Hardy, Rebecca; Dahgam, Santosh; Palmen, Jutta; Kuznetsova, Tatiana; Uiterwaal, Cuno S. P. M.; Adeyemo, Adebowale; Ludwig, Barbara; Tomaszewski, Maciej; Tzoulaki, Ioanna; Palmer, Nicholette D.; Chang, Yen-Pei C.; Steinle, Nanette I.; Grobbee, Diederick E.; Kardia, Sharon L.; Morrison, Alanna C.; Najjar, Samer; Hadley, David; Connell, John M.; Day, Ian N. M.; Lawlor, Debbie A.; Beilby, John P.; Lawrence, Robert W.; Ongen, Halit; Li, Yali; Young, J. H.; Bis, Joshua C.; Bolton, Judith A. Hoffman; Chaturvedi, Nish; Islam, Muhammad; Jafar, Tazeen H.; Kulkarni, Smita R.; Grässler, Jürgen; Howard, Philip; Guarrera, Simonetta; Ricceri, Fulvio; Emilsson, Valur; Plump, Andrew; Weder, Alan B.; Sun, Yan V.; Scott, Laura J.; Peltonen, Leena; Vartiainen, Erkki; Brand, Stefan-Martin; Wang, Thomas J.; Burton, Paul R.; Artigas, Maria Soler; Dong, Yanbin; Wang, Xiaoling; Zhu, Haidong; Lohman, Kurt K.; Rudock, Megan E.; Heckbert, Susan R.; Smith, Nicholas L.; Wiggins, Kerri L.; Doumatey, Ayo; Shriner, Daniel; Veldre, Gudrun; Viigimaa, Margus; Kinra, Sanjay; Prabhakaran, Dorairajan; Tripathy, Vikal; Langefeld, Carl D.; Rosengren, Annika; Thelle, Dag S.; Corsi, Anna Maria; Singleton, Andrew; Hilton, Gina; Salako, Tunde; Iwai, Naoharu; Kita, Yoshikuni; Ogihara, Toshio; Ohkubo, Takayoshi; Okamura, Tomonori; Ueshima, Hirotsugu; Umemura, Satoshi; Eyheramendy, Susana; Meitinger, Thomas; Cho, Yoon Shin; Kim, Hyung-Lae; Scott, James; Sehmi, Joban S.; Hedblad, Bo; Nilsson, Peter; Stanèáková, Alena; Raffel, Leslie J.; Yao, Jie; O'Donnell, Chris; Schwartz, Stephen M.; Ikram, M. Arfan; Longstreth, W. T.; Mosley, Thomas H.; Seshadri, Sudha; Shrine, Nick R. G.; Wain, Louise V.; Morken, Mario A.; Laitinen, Jaana; Zitting, Paavo; Cooper, Jackie A.; van Gilst, Wiek H.; Janipalli, Charles S.; Mani, K. Radha; Yajnik, Chittaranjan S.; Mattace-Raso, Francesco U. S.; Lakatta, Edward G.; Orru, Marco; Scuteri, Angelo; Ala-Korpela, Mika; Kangas, Antti J.; Soininen, Pasi; Tukiainen, Taru; Würtz, Peter; Ong, Rick Twee-Hee; Galan, Pilar; Hercberg, Serge; Lathrop, Mark; Zelenika, Diana; Zhai, Guangju; Meschia, James F.; Sharma, Pankaj; Terzic, Janos; Kumar, M. J. Kranthi; Denniff, Matthew; Zukowska-Szczechowska, Ewa; Wagenknecht, Lynne E.; Fowkes, F. Gerald R.; Charchar, Fadi J.; Rotimi, Charles; Bots, Michiel L.; Brand, Eva; Talmud, Philippa J.; Nyberg, Fredrik; Laan, Maris; van der Schouw, Yvonne T.; Casas, Juan P.; Vineis, Paolo; Ganesh, Santhi K.; Wong, Tien Y.; Tai, E. Shyong; Rao, Dabeeru C.; Morris, Richard W.; Dominiczak, Anna F.; Marmot, Michael G.; Miki, Tetsuro; Chandak, Giriraj R.; Zhu, Xiaofeng; Gyllensten, Ulf B.; Elosua, Roberto; Soranzo, Nicole; Sijbrands, Eric J. G.; Uda, Manuela; Vasan, Ramachandran S.; Larson, Martin G.; Anderson, Carl A.; Gordon, Scott D.; Guo, Qun; Henders, Anjali K.; Lambert, Ann; Lee, Sang Hong; Kraft, Peter; Kennedy, Stephen H.; Macgregor, Stuart; Missmer, Stacey A.; Painter, Jodie N.; Roseman, Fenella; Treloar, Susan A.; Wallace, Leanne; Alizadeh, Behrooz Z.; de Boer, Rudolf A.; Boezen, H. Marike; van der Klauw, Melanie M.; Ormel, Johan; Postma, Dirkje S.; Rosmalen, Judith G. M.; Slaets, Joris P.; Lagou, Vasiliki; Welch, Ryan P.; Wheeler, Eleanor; Rehnberg, Emil; Lecoeur, Cecile; Johnson, Paul C. D.; Hottenga, Jouke-Jan; Salo, Perttu; Timpson, Nicholas J.; Bielak, Lawrence F.; Zhao, Wei; Horikoshi, Momoko; Navarro, Pau; Esko, Tönu; Chen, Han; Robertson, Neil; Rybin, Denis; Kang, Hyun Min; Song, Kijoung; An, Ping; Marullo, Letizia; Jansen, Hanneke; Edkins, Sarah; Varga, Tibor V.; Oksa, Heikki; Antonella, Mulas; Kong, Augustine; Herder, Christian; Antti, Jula; Miljkovic, Iva; Atalay, Mustafa; Kiess, Wieland; Smit, Johannes H.; Campbell, Susan; Fowkes, Gerard R.; Rathmann, Wolfgang; Maerz, Winfried; Province, Michael A.; Watanabe, Richard M.; Toenjes, Anke; Peyser, Patricia A.; Körner, Antje; Dupuis, Josée; Cucca, Francesco; Balkau, Beverley; Bouatia-Naji, Nabila; Ahmadi, Kourosh R.; Ainali, Chrysanthi; Bataille, Veronique; Bell, Jordana T.; Buil, Alfonso; Dermitzakis, Emmanouil T.; Dimas, Antigone S.; Durbin, Richard; Glass, Daniel; Hassanali, Neelam; Ingle, Catherine; Knowles, David; Krestyaninova, Maria; Lowe, Christopher E.; Meduri, Eshwar; di Meglio, Paola; Montgomery, Stephen B.; Nestle, Frank O.; Nica, Alexandra C.; Nisbet, James; O'Rahilly, Stephen; Parts, Leopold; Potter, Simon; Sekowska, Magdalena; Shin, So-Youn; Small, Kerrin S.; Surdulescu, Gabriela; Travers, Mary E.; Tsaprouni, Loukia; Tsoka, Sophia; Wilk, Alicja; Matise, Tara; Buyske, Steve; Higashio, Julia; Williams, Rasheeda; Nato, Andrew; Ambite, Jose Luis; Manolio, Teri; Hindorff, Lucia; Heiss, Gerardo; Taylor, Kira; Avery, Christy; Graff, Misa; Lin, Danyu; Quibrera, Miguel; Cochran, Barbara; Kao, Linda; Umans, Jason; Cole, Shelley; MacCluer, Jean; Person, Sharina; Pankow, James; Gross, Myron; Fornage, Myriam; Durda, Peter; Jenny, Nancy; Patsy, Bruce; Arnold, Alice; Buzkova, Petra; Crawford, Dana; Haines, Jonathan; Murdock, Deborah; Glenn, Kim; Brown-Gentry, Kristin; Thornton-Wells, Tricia; Dumitrescu, Logan; Jeff, Janina; Bush, William S.; Mitchell, Sabrina L.; Goodloe, Robert; Wilson, Sarah; Boston, Jonathan; Malinowski, Jennifer; Restrepo, Nicole; Oetjens, Matthew; Fowke, Jay; Zheng, Wei; Spencer, Kylee; Ritchie, Marylyn; Pendergrass, Sarah; Le Marchand, Loïc; Wilkens, Lynne; Park, Lani; Tiirikainen, Maarit; Kolonel, Laurence; Lim, Unhee; Cheng, Iona; Wang, Hansong; Shohet, Ralph; Haiman, Christopher; Stram, Daniel; Henderson, Brian; Monroe, Kristine; Schumacher, Fredrick; Anderson, Garnet; Carlson, Chris; Prentice, Ross; LaCroix, Andrea; Wu, Chunyuan; Carty, Cara; Gong, Jian; Rosse, Stephanie; Young, Alicia; Haessler, Jeff; Kocarnik, Jonathan; Lin, Yi; Jackson, Rebecca; Duggan, David; Kuller, Lew; He, Chunyan; Sulem, Patrick; Barbalic, Maja; Broer, Linda; Byrne, Enda M.; Gudbjartsson, Daniel F.; McArdle, Patick F.; Porcu, Eleonora; van Wingerden, Sophie; Zhuang, Wei V.; Lauc, Lovorka Barac; Broekmans, Frank J.; Burri, Andrea; Chanock, Stephen J.; Chen, Constance; Corre, Tanguy; Coviello, Andrea D.; D'Adamo, Pio; Davies, Gail; Deary, Ian J.; Dedoussis, George V. Z.; Deloukas, Panagiotis; Ebrahim, Shah; Fauser, Bart C. J. M.; Ferreli, Liana; Folsom, Aaron R.; Hall, Per; Hankinson, Susan E.; Hass, Merli; Heath, Andrew C.; Janssens, A. Cecile J. W.; Keyzer, Jules; Lahti, Jari; Lai, Sandra; Laisk, Triin; Laven, Joop S. E.; Liu, Jianjun; Lopez, Lorna M.; Louwers, Yvonne V.; Marongiu, Mara; Klaric, Irena Martinovic; Masciullo, Corrado; Medland, Sarah E.; Melzer, David; Newman, Anne B.; Paré, Guillaume; Peeters, Petra H. M.; Plump, Andrew S.; Pop, Victor J. M.; Räikkönen, Katri; Salumets, Andres; Smith, Jennifer A.; Stacey, Simon N.; Starr, John M.; Stathopoulou, Maria G.; Tenesa, Albert; Tryggvadottir, Laufey; Tsui, Kim; van Dam, Rob M.; van Gils, Carla H.; van Nierop, Peter; Vink, Jacqueline M.; Voorhuis, Marlies; Waeber, Gérard; Wallaschofski, Henri; Widen, Elisabeth; Wijnands-van Gent, Colette J. M.; Zgaga, Lina; Zygmunt, Marek; Arnold, Alice M.; Buring, Julie E.; Crisponi, Laura; Demerath, Ellen W.; Murray, Anna; Visser, Jenny A.; Lunetta, Kathryn L.; Elks, Cathy E.; Cousminer, Diana L.; Feenstra, Bjarke; Lin, Peng; McArdle, Patrick F.; van Wingerden, Sophie W.; Smith, Erin N.; Ulivi, Shelia; Warrington, Nicole M.; Alavere, Helen; Barroso, Ines; Berenson, Gerald S.; Blackburn, Hannah; Busonero, Fabio; Chen, Wei; Couper, David; Easton, Douglas F.; Eriksson, Johan; Foroud, Tatiana; Geller, Frank; Hernandez, Dena G.; Kilpeläinen, Tuomas O.; Li, Shengxu; Melbye, Mads; Murray, Jeffrey C.; Murray, Sarah S.; Ness, Andrew R.; Northstone, Kate; Pennell, Craig E.; Pharoah, Paul; Rafnar, Thorunn; Rice, John P.; Ring, Susan M.; Schork, Nicholas J.; Segrè, Ayellet V.; Sovio, Ulla; Srinivasan, Sathanur R.; Tammesoo, Mar-Liis; Tyrer, Jonathon; van Meurs, Joyve B. J.; Weedon, Michael N.; Young, Lauren; Zhuang, Wei Vivian; Bierut, Laura J.; Boyd, Heather A.

    2015-01-01

    Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide

  19. New genetic loci link adipose and insulin biology to body fat distribution

    DEFF Research Database (Denmark)

    Shungin, Dmitry; Winkler, Thomas W; Croteau-Chonka, Damien C.

    2015-01-01

    Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome...

  20. Predicting in vivo effect levels for repeat-dose systemic toxicity using chemical, biological, kinetic and study covariates.

    Science.gov (United States)

    Truong, Lisa; Ouedraogo, Gladys; Pham, LyLy; Clouzeau, Jacques; Loisel-Joubert, Sophie; Blanchet, Delphine; Noçairi, Hicham; Setzer, Woodrow; Judson, Richard; Grulke, Chris; Mansouri, Kamel; Martin, Matthew

    2018-02-01

    In an effort to address a major challenge in chemical safety assessment, alternative approaches for characterizing systemic effect levels, a predictive model was developed. Systemic effect levels were curated from ToxRefDB, HESS-DB and COSMOS-DB from numerous study types totaling 4379 in vivo studies for 1247 chemicals. Observed systemic effects in mammalian models are a complex function of chemical dynamics, kinetics, and inter- and intra-individual variability. To address this complex problem, systemic effect levels were modeled at the study-level by leveraging study covariates (e.g., study type, strain, administration route) in addition to multiple descriptor sets, including chemical (ToxPrint, PaDEL, and Physchem), biological (ToxCast), and kinetic descriptors. Using random forest modeling with cross-validation and external validation procedures, study-level covariates alone accounted for approximately 15% of the variance reducing the root mean squared error (RMSE) from 0.96 log 10 to 0.85 log 10  mg/kg/day, providing a baseline performance metric (lower expectation of model performance). A consensus model developed using a combination of study-level covariates, chemical, biological, and kinetic descriptors explained a total of 43% of the variance with an RMSE of 0.69 log 10  mg/kg/day. A benchmark model (upper expectation of model performance) was also developed with an RMSE of 0.5 log 10  mg/kg/day by incorporating study-level covariates and the mean effect level per chemical. To achieve a representative chemical-level prediction, the minimum study-level predicted and observed effect level per chemical were compared reducing the RMSE from 1.0 to 0.73 log 10  mg/kg/day, equivalent to 87% of predictions falling within an order-of-magnitude of the observed value. Although biological descriptors did not improve model performance, the final model was enriched for biological descriptors that indicated xenobiotic metabolism gene expression, oxidative stress, and

  1. Bayesian Belief Networks for predicting drinking water distribution system pipe breaks

    International Nuclear Information System (INIS)

    Francis, Royce A.; Guikema, Seth D.; Henneman, Lucas

    2014-01-01

    In this paper, we use Bayesian Belief Networks (BBNs) to construct a knowledge model for pipe breaks in a water zone. To the authors’ knowledge, this is the first attempt to model drinking water distribution system pipe breaks using BBNs. Development of expert systems such as BBNs for analyzing drinking water distribution system data is not only important for pipe break prediction, but is also a first step in preventing water loss and water quality deterioration through the application of machine learning techniques to facilitate data-based distribution system monitoring and asset management. Due to the difficulties in collecting, preparing, and managing drinking water distribution system data, most pipe break models can be classified as “statistical–physical” or “hypothesis-generating.” We develop the BBN with the hope of contributing to the “hypothesis-generating” class of models, while demonstrating the possibility that BBNs might also be used as “statistical–physical” models. Our model is learned from pipe breaks and covariate data from a mid-Atlantic United States (U.S.) drinking water distribution system network. BBN models are learned using a constraint-based method, a score-based method, and a hybrid method. Model evaluation is based on log-likelihood scoring. Sensitivity analysis using mutual information criterion is also reported. While our results indicate general agreement with prior results reported in pipe break modeling studies, they also suggest that it may be difficult to select among model alternatives. This model uncertainty may mean that more research is needed for understanding whether additional pipe break risk factors beyond age, break history, pipe material, and pipe diameter might be important for asset management planning. - Highlights: • We show Bayesian Networks for predictive and diagnostic management of water distribution systems. • Our model may enable system operators and managers to prioritize system

  2. Simulated biologic intelligence used to predict length of stay and survival of burns.

    Science.gov (United States)

    Frye, K E; Izenberg, S D; Williams, M D; Luterman, A

    1996-01-01

    From July 13, 1988, to May 14, 1995, 1585 patients with burns and no other injuries besides inhalation were treated; 4.5% did not survive. Artificial neural networks were trained on patient presentation data with known outcomes on 90% of the randomized cases. The remaining cases were then used to predict survival and length of stay in cases not trained on. Survival was predicted with more than 98% accuracy and length of stay to within a week with 72% accuracy in these cases. For anatomic area involved by burn, burns involving the feet, scalp, or both had the largest negative effect on the survival prediction. In survivors burns involving the buttocks, transport to this burn center by the military or by helicopter, electrical burns, hot tar burns, and inhalation were associated with increasing the length of stay prediction. Neural networks can be used to accurately predict the clinical outcome of a burn. What factors affect that prediction can be investigated.

  3. Climatic associations of British species distributions show good transferability in time but low predictive accuracy for range change.

    Directory of Open Access Journals (Sweden)

    Giovanni Rapacciuolo

    Full Text Available Conservation planners often wish to predict how species distributions will change in response to environmental changes. Species distribution models (SDMs are the primary tool for making such predictions. Many methods are widely used; however, they all make simplifying assumptions, and predictions can therefore be subject to high uncertainty. With global change well underway, field records of observed range shifts are increasingly being used for testing SDM transferability. We used an unprecedented distribution dataset documenting recent range changes of British vascular plants, birds, and butterflies to test whether correlative SDMs based on climate change provide useful approximations of potential distribution shifts. We modelled past species distributions from climate using nine single techniques and a consensus approach, and projected the geographical extent of these models to a more recent time period based on climate change; we then compared model predictions with recent observed distributions in order to estimate the temporal transferability and prediction accuracy of our models. We also evaluated the relative effect of methodological and taxonomic variation on the performance of SDMs. Models showed good transferability in time when assessed using widespread metrics of accuracy. However, models had low accuracy to predict where occupancy status changed between time periods, especially for declining species. Model performance varied greatly among species within major taxa, but there was also considerable variation among modelling frameworks. Past climatic associations of British species distributions retain a high explanatory power when transferred to recent time--due to their accuracy to predict large areas retained by species--but fail to capture relevant predictors of change. We strongly emphasize the need for caution when using SDMs to predict shifts in species distributions: high explanatory power on temporally-independent records

  4. Smartphones for distributed multimode sensing: biological and environmental sensing and analysis

    Science.gov (United States)

    Feitshans, Tyler; Williams, Robert

    2013-05-01

    Active and Agile Environmental and Biological sensing are becoming obligatory to generate prompt warnings for the troops and law enforcements conducting missions in hostile environments. The traditional static sensing mesh networks which provide a coarse-grained (far-field) measurement of the environmental conditions like air quality, radiation , CO2, etc … would not serve the dynamic and localized changes in the environment, which requires a fine-grained (near-field) sensing solutions. Further, sensing the biological conditions of (healthy and injured) personnel in a contaminated environment and providing a personalized analysis of the life-threatening conditions in real-time would greatly aid the success of the mission. In this vein, under SATE and YATE programs, the research team at AFRL Tec^Edge Discovery labs had demonstrated the feasibility of developing Smartphone applications , that employ a suite of external environmental and biological sensors, which provide fine-grained and customized sensing in real-time fashion. In its current state, these smartphone applications leverage a custom designed modular standalone embedded platform (with external sensors) that can be integrated seamlessly with Smartphones for sensing and further provides connectivity to a back-end data architecture for archiving, analysis and dissemination of real-time alerts. Additionally, the developed smartphone applications have been successfully tested in the field with varied environmental sensors to sense humidity, CO2/CO, wind, etc…, ; and with varied biological sensors to sense body temperature and pulse with apt real-time analysis

  5. Observations on the distribution and biology of Huffmanela huffmani (Nematoda: Trichosomoididae)

    Czech Academy of Sciences Publication Activity Database

    Cox, M. K.; Huffman, D. G.; Moravec, František

    2004-01-01

    Roč. 51, č. 1 (2004), s. 50-54 ISSN 0015-5683 R&D Projects: GA AV ČR IAA6022201 Institutional research plan: CEZ:AV0Z6022909 Keywords : Nematoda * Trichosomoididae * Huffmanela Subject RIV: EA - Cell Biology Impact factor: 0.837, year: 2004

  6. Plant ecdysteroids: plant sterols with intriguing distributions, biological effects and relations to plant hormones

    Czech Academy of Sciences Publication Activity Database

    Tarkowská, Danuše; Strnad, Miroslav

    2016-01-01

    Roč. 244, č. 3 (2016), s. 545-555 ISSN 0032-0935 R&D Projects: GA MŠk(CZ) LO1204 Institutional support: RVO:61389030 Keywords : Phytoecdysteroids * Ecdysteroids * 20-Hydroxyecdysone Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 3.361, year: 2016

  7. A Parallel Distributed Processing Approach to Behavior and Biology in Schizophrenia

    Science.gov (United States)

    1989-10-01

    delusions) and the other that reflects dopamine underactivity (negative symptoms - e.g., avolition, amotivation and withdrawal). Several authors have... amotivation . While both may be related to frontal lobe Behavior and Biology in Schizophrenia Cohen and Servan-Schreiber 32 deficits, the models in their

  8. Eco-biology of Mastacembelus pancalus (Ham.) and their distribution in different water bodies

    OpenAIRE

    Hussain, M. Afzal; Flowra, F. Adib; Hossain, M. Altaf

    2003-01-01

    The eco-biological of the spiny eel, Mastacembelus pailcalus in the river Padma, adjacent flood plains and ponds were influenced by various physico-chemical factors such as water temperature, water transparency, pH, dissolved oxygen, free carbon dioxide and alkalinity. Flood plain areas are the best habitat for the M. pancalus with maximum abundance.

  9. Hydrological-niche models predict water plant functional group distributions in diverse wetland types.

    Science.gov (United States)

    Deane, David C; Nicol, Jason M; Gehrig, Susan L; Harding, Claire; Aldridge, Kane T; Goodman, Abigail M; Brookes, Justin D

    2017-06-01

    Human use of water resources threatens environmental water supplies. If resource managers are to develop policies that avoid unacceptable ecological impacts, some means to predict ecosystem response to changes in water availability is necessary. This is difficult to achieve at spatial scales relevant for water resource management because of the high natural variability in ecosystem hydrology and ecology. Water plant functional groups classify species with similar hydrological niche preferences together, allowing a qualitative means to generalize community responses to changes in hydrology. We tested the potential for functional groups in making quantitative prediction of water plant functional group distributions across diverse wetland types over a large geographical extent. We sampled wetlands covering a broad range of hydrogeomorphic and salinity conditions in South Australia, collecting both hydrological and floristic data from 687 quadrats across 28 wetland hydrological gradients. We built hydrological-niche models for eight water plant functional groups using a range of candidate models combining different surface inundation metrics. We then tested the predictive performance of top-ranked individual and averaged models for each functional group. Cross validation showed that models achieved acceptable predictive performance, with correct classification rates in the range 0.68-0.95. Model predictions can be made at any spatial scale that hydrological data are available and could be implemented in a geographical information system. We show the response of water plant functional groups to inundation is consistent enough across diverse wetland types to quantify the probability of hydrological impacts over regional spatial scales. © 2017 by the Ecological Society of America.

  10. Proteome-wide Structural Analysis of PTM Hotspots Reveals Regulatory Elements Predicted to Impact Biological Function and Disease.

    Science.gov (United States)

    Torres, Matthew P; Dewhurst, Henry; Sundararaman, Niveda

    2016-11-01

    Post-translational modifications (PTMs) regulate protein behavior through modulation of protein-protein interactions, enzymatic activity, and protein stability essential in the translation of genotype to phenotype in eukaryotes. Currently, less than 4% of all eukaryotic PTMs are reported to have biological function - a statistic that continues to decrease with an increasing rate of PTM detection. Previously, we developed SAPH-ire (Structural Analysis of PTM Hotspots) - a method for the prioritization of PTM function potential that has been used effectively to reveal novel PTM regulatory elements in discrete protein families (Dewhurst et al., 2015). Here, we apply SAPH-ire to the set of eukaryotic protein families containing experimental PTM and 3D structure data - capturing 1,325 protein families with 50,839 unique PTM sites organized into 31,747 modified alignment positions (MAPs), of which 2010 (∼6%) possess known biological function. Here, we show that using an artificial neural network model (SAPH-ire NN) trained to identify MAP hotspots with biological function results in prediction outcomes that far surpass the use of single hotspot features, including nearest neighbor PTM clustering methods. We find the greatest enhancement in prediction for positions with PTM counts of five or less, which represent 98% of all MAPs in the eukaryotic proteome and 90% of all MAPs found to have biological function. Analysis of the top 1092 MAP hotspots revealed 267 of truly unknown function (containing 5443 distinct PTMs). Of these, 165 hotspots could be mapped to human KEGG pathways for normal and/or disease physiology. Many high-ranking hotspots were also found to be disease-associated pathogenic sites of amino acid substitution despite the lack of observable PTM in the human protein family member. Taken together, these experiments demonstrate that the functional relevance of a PTM can be predicted very effectively by neural network models, revealing a large but testable

  11. Prediction of calcite Cement Distribution in Shallow Marine Sandstone Reservoirs using Seismic Data

    Energy Technology Data Exchange (ETDEWEB)

    Bakke, N.E.

    1996-12-31

    This doctoral thesis investigates how calcite cemented layers can be detected by reflection seismic data and how seismic data combined with other methods can be used to predict lateral variation in calcite cementation in shallow marine sandstone reservoirs. Focus is on the geophysical aspects. Sequence stratigraphy and stochastic modelling aspects are only covered superficially. Possible sources of calcite in shallow marine sandstone are grouped into internal and external sources depending on their location relative to the presently cemented rock. Well data and seismic data from the Troll Field in the Norwegian North Sea have been analysed. Tuning amplitudes from stacks of thin calcite cemented layers are analysed. Tuning effects are constructive or destructive interference of pulses resulting from two or more closely spaced reflectors. The zero-offset tuning amplitude is shown to depend on calcite content in the stack and vertical stack size. The relationship is found by regression analysis based on extensive seismic modelling. The results are used to predict calcite distribution in a synthetic and a real data example. It is found that describing calcite cemented beds in shallow marine sandstone reservoirs is not a deterministic problem. Hence seismic inversion and sequence stratigraphy interpretation of well data have been combined in a probabilistic approach to produce models of calcite cemented barriers constrained by a maximum amount of information. It is concluded that seismic data can provide valuable information on distribution of calcite cemented beds in reservoirs where the background sandstones are relatively homogeneous. 63 refs., 78 figs., 10 tabs.

  12. Evaluation of distribution coefficients for the prediction of strontium and cesium migration in a uniform sand

    International Nuclear Information System (INIS)

    Reynolds, W.D.; Gillham, R.W.; Cherry, J.A.

    1982-01-01

    The validity of using a distribution coefficient (Ksub(d)) in the mathematical prediction of strontium and cesium transport through uniform saturated sand was investigated by comparing measured breakthrough curves with curves of simulations using the advection-dispersion and the advection equations. Values for Ksub(d) were determined by batch equilibration tests and, indirectly, by fitting the mathematical model to breakthrough data from column experiments. Although the advection-dispersion equation accurately represented the breakthrough curves for two nonreactive solutes (chloride and tritium), neither it nor the advection equation provided close representations of the strontium and cesium curves. The simulated breakthrough curves for strontium and cesium were nearly symmetrical, whereas the data curves were very asymmetrical, with long tails. Column experiments with different pore-water velocities indicated that the shape of the normalized breakthrough curves was not sensitive to velocity. This suggests that the asymmetry of the measured curves was the result of nonlinear partitioning of the cations between the solid and liquid phases, rather than nonequilibrium effects. The results indicate that the distribution coefficient, when used in advection-dispersion models for prediction of the migration of strontium and cesium in field situations, can result in significant error

  13. Remotely Sensed High-Resolution Global Cloud Dynamics for Predicting Ecosystem and Biodiversity Distributions.

    Directory of Open Access Journals (Sweden)

    Adam M Wilson

    2016-03-01

    Full Text Available Cloud cover can influence numerous important ecological processes, including reproduction, growth, survival, and behavior, yet our assessment of its importance at the appropriate spatial scales has remained remarkably limited. If captured over a large extent yet at sufficiently fine spatial grain, cloud cover dynamics may provide key information for delineating a variety of habitat types and predicting species distributions. Here, we develop new near-global, fine-grain (≈1 km monthly cloud frequencies from 15 y of twice-daily Moderate Resolution Imaging Spectroradiometer (MODIS satellite images that expose spatiotemporal cloud cover dynamics of previously undocumented global complexity. We demonstrate that cloud cover varies strongly in its geographic heterogeneity and that the direct, observation-based nature of cloud-derived metrics can improve predictions of habitats, ecosystem, and species distributions with reduced spatial autocorrelation compared to commonly used interpolated climate data. These findings support the fundamental role of remote sensing as an effective lens through which to understand and globally monitor the fine-grain spatial variability of key biodiversity and ecosystem properties.

  14. Multi-Model Prediction for Demand Forecast in Water Distribution Networks

    Directory of Open Access Journals (Sweden)

    Rodrigo Lopez Farias

    2018-03-01

    Full Text Available This paper presents a multi-model predictor called Qualitative Multi-Model Predictor Plus (QMMP+ for demand forecast in water distribution networks. QMMP+ is based on the decomposition of the quantitative and qualitative information of the time-series. The quantitative component (i.e., the daily consumption prediction is forecasted and the pattern mode estimated using a Nearest Neighbor (NN classifier and a Calendar. The patterns are updated via a simple Moving Average scheme. The NN classifier and the Calendar are executed simultaneously every period and the most suited model for prediction is selected using a probabilistic approach. The proposed solution for water demand forecast is compared against Radial Basis Function Artificial Neural Networks (RBF-ANN, the statistical Autoregressive Integrated Moving Average (ARIMA, and Double Seasonal Holt-Winters (DSHW approaches, providing the best results when applied to real demand of the Barcelona Water Distribution Network. QMMP+ has demonstrated that the special modelling treatment of water consumption patterns improves the forecasting accuracy.

  15. A microbiology-based multi-parametric approach towards assessing biological stability in drinking water distribution networks

    KAUST Repository

    Lautenschlä ger, Karin; Hwang, Chiachi; Liu, Wentso; Boon, Nico; Kö ster, Oliver; Vrouwenvelder, Johannes S.; Egli, Thomas; Hammes, Frederik A.

    2013-01-01

    Biological stability of drinking water implies that the concentration of bacterial cells and composition of the microbial community should not change during distribution. In this study, we used a multi-parametric approach that encompasses different aspects of microbial water quality including microbial growth potential, microbial abundance, and microbial community composition, to monitor biological stability in drinking water of the non-chlorinated distribution system of Zürich. Drinking water was collected directly after treatment from the reservoir and in the network at several locations with varied average hydraulic retention times (6-52h) over a period of four months, with a single repetition two years later. Total cell concentrations (TCC) measured with flow cytometry remained remarkably stable at 9.5 (±0.6)×104cells/ml from water in the reservoir throughout most of the distribution network, and during the whole time period. Conventional microbial methods like heterotrophic plate counts, the concentration of adenosine tri-phosphate, total organic carbon and assimilable organic carbon remained also constant. Samples taken two years apart showed more than 80% similarity for the microbial communities analysed with denaturing gradient gel electrophoresis and 454 pyrosequencing. Only the two sampling locations with the longest water retention times were the exceptions and, sofar for unknown reasons, recorded a slight but significantly higher TCC (1.3(±0.1)×105cells/ml) compared to the other locations. This small change in microbial abundance detected by flow cytometry was also clearly observed in a shift in the microbial community profiles to a higher abundance of members from the Comamonadaceae (60% vs. 2% at other locations). Conventional microbial detection methods were not able to detect changes as observed with flow cytometric cell counts and microbial community analysis. Our findings demonstrate that the multi-parametric approach used provides a powerful

  16. A microbiology-based multi-parametric approach towards assessing biological stability in drinking water distribution networks

    KAUST Repository

    Lautenschläger, Karin

    2013-06-01

    Biological stability of drinking water implies that the concentration of bacterial cells and composition of the microbial community should not change during distribution. In this study, we used a multi-parametric approach that encompasses different aspects of microbial water quality including microbial growth potential, microbial abundance, and microbial community composition, to monitor biological stability in drinking water of the non-chlorinated distribution system of Zürich. Drinking water was collected directly after treatment from the reservoir and in the network at several locations with varied average hydraulic retention times (6-52h) over a period of four months, with a single repetition two years later. Total cell concentrations (TCC) measured with flow cytometry remained remarkably stable at 9.5 (±0.6)×104cells/ml from water in the reservoir throughout most of the distribution network, and during the whole time period. Conventional microbial methods like heterotrophic plate counts, the concentration of adenosine tri-phosphate, total organic carbon and assimilable organic carbon remained also constant. Samples taken two years apart showed more than 80% similarity for the microbial communities analysed with denaturing gradient gel electrophoresis and 454 pyrosequencing. Only the two sampling locations with the longest water retention times were the exceptions and, sofar for unknown reasons, recorded a slight but significantly higher TCC (1.3(±0.1)×105cells/ml) compared to the other locations. This small change in microbial abundance detected by flow cytometry was also clearly observed in a shift in the microbial community profiles to a higher abundance of members from the Comamonadaceae (60% vs. 2% at other locations). Conventional microbial detection methods were not able to detect changes as observed with flow cytometric cell counts and microbial community analysis. Our findings demonstrate that the multi-parametric approach used provides a powerful

  17. SESAM – a new framework integrating macroecological and species distribution models for predicting spatio-temporal patterns of species assemblages

    DEFF Research Database (Denmark)

    Guisan, Antoine; Rahbek, Carsten

    2011-01-01

    Two different approaches currently prevail for predicting spatial patterns of species assemblages. The first approach (macroecological modelling, MEM) focuses directly on realized properties of species assemblages, whereas the second approach (stacked species distribution modelling, S-SDM) starts...

  18. A Random Forest approach to predict the spatial distribution of sediment pollution in an estuarine system.

    Directory of Open Access Journals (Sweden)

    Eric S Walsh

    Full Text Available Modeling the magnitude and distribution of sediment-bound pollutants in estuaries is often limited by incomplete knowledge of the site and inadequate sample density. To address these modeling limitations, a decision-support tool framework was conceived that predicts sediment contamination from the sub-estuary to broader estuary extent. For this study, a Random Forest (RF model was implemented to predict the distribution of a model contaminant, triclosan (5-chloro-2-(2,4-dichlorophenoxyphenol (TCS, in Narragansett Bay, Rhode Island, USA. TCS is an unregulated contaminant used in many personal care products. The RF explanatory variables were associated with TCS transport and fate (proxies and direct and indirect environmental entry. The continuous RF TCS concentration predictions were discretized into three levels of contamination (low, medium, and high for three different quantile thresholds. The RF model explained 63% of the variance with a minimum number of variables. Total organic carbon (TOC (transport and fate proxy was a strong predictor of TCS contamination causing a mean squared error increase of 59% when compared to permutations of randomized values of TOC. Additionally, combined sewer overflow discharge (environmental entry and sand (transport and fate proxy were strong predictors. The discretization models identified a TCS area of greatest concern in the northern reach of Narragansett Bay (Providence River sub-estuary, which was validated with independent test samples. This decision-support tool performed well at the sub-estuary extent and provided the means to identify areas of concern and prioritize bay-wide sampling.

  19. Effects of predicted climatic changes on distribution of organic contaminants in brackish water mesocosms

    Energy Technology Data Exchange (ETDEWEB)

    Ripszam, M., E-mail: matyas.ripszam@chem.umu.se [Department of Chemistry, Umea University, 901 87 Umeå (Sweden); Gallampois, C.M.J. [Department of Chemistry, Umea University, 901 87 Umeå (Sweden); Berglund, Å. [Department of Ecology and Environmental Sciences, Umeå University, 901 87 Umeå (Sweden); Larsson, H. [Umeå Marine Sciences Centre, Umeå University, Norrbyn, 905 71 Hörnefors (Sweden); Andersson, A. [Department of Ecology and Environmental Sciences, Umeå University, 901 87 Umeå (Sweden); Tysklind, M.; Haglund, P. [Department of Chemistry, Umea University, 901 87 Umeå (Sweden)

    2015-06-01

    Predicted consequences of future climate change in the northern Baltic Sea include increases in sea surface temperatures and terrestrial dissolved organic carbon (DOC) runoff. These changes are expected to alter environmental distribution of anthropogenic organic contaminants (OCs). To assess likely shifts in their distributions, outdoor mesocosms were employed to mimic pelagic ecosystems at two temperatures and two DOC concentrations, current: 15 °C and 4 mg DOC L{sup −1} and, within ranges of predicted increases, 18 °C and 6 mg DOC L{sup −1}, respectively. Selected organic contaminants were added to the mesocosms to monitor changes in their distribution induced by the treatments. OC partitioning to particulate matter and sedimentation were enhanced at the higher DOC concentration, at both temperatures, while higher losses and lower partitioning of OCs to DOC were observed at the higher temperature. No combined effects of higher temperature and DOC on partitioning were observed, possibly because of the balancing nature of these processes. Therefore, changes in OCs' fates may largely depend on whether they are most sensitive to temperature or DOC concentration rises. Bromoanilines, phenanthrene, biphenyl and naphthalene were sensitive to the rise in DOC concentration, whereas organophosphates, chlorobenzenes (PCBz) and polychlorinated biphenyls (PCBs) were more sensitive to temperature. Mitotane and diflufenican were sensitive to both temperature and DOC concentration rises individually, but not in combination. - Highlights: • More contaminants remained in the ecosystem at higher organic carbon levels. • More contaminants were lost in the higher temperature treatments. • The combined effects are competitive with respect to contaminant cycling. • The individual properties of each contaminant determine their respective fate.

  20. Effects of predicted climatic changes on distribution of organic contaminants in brackish water mesocosms

    International Nuclear Information System (INIS)

    Ripszam, M.; Gallampois, C.M.J.; Berglund, Å.; Larsson, H.; Andersson, A.; Tysklind, M.; Haglund, P.

    2015-01-01

    Predicted consequences of future climate change in the northern Baltic Sea include increases in sea surface temperatures and terrestrial dissolved organic carbon (DOC) runoff. These changes are expected to alter environmental distribution of anthropogenic organic contaminants (OCs). To assess likely shifts in their distributions, outdoor mesocosms were employed to mimic pelagic ecosystems at two temperatures and two DOC concentrations, current: 15 °C and 4 mg DOC L −1 and, within ranges of predicted increases, 18 °C and 6 mg DOC L −1 , respectively. Selected organic contaminants were added to the mesocosms to monitor changes in their distribution induced by the treatments. OC partitioning to particulate matter and sedimentation were enhanced at the higher DOC concentration, at both temperatures, while higher losses and lower partitioning of OCs to DOC were observed at the higher temperature. No combined effects of higher temperature and DOC on partitioning were observed, possibly because of the balancing nature of these processes. Therefore, changes in OCs' fates may largely depend on whether they are most sensitive to temperature or DOC concentration rises. Bromoanilines, phenanthrene, biphenyl and naphthalene were sensitive to the rise in DOC concentration, whereas organophosphates, chlorobenzenes (PCBz) and polychlorinated biphenyls (PCBs) were more sensitive to temperature. Mitotane and diflufenican were sensitive to both temperature and DOC concentration rises individually, but not in combination. - Highlights: • More contaminants remained in the ecosystem at higher organic carbon levels. • More contaminants were lost in the higher temperature treatments. • The combined effects are competitive with respect to contaminant cycling. • The individual properties of each contaminant determine their respective fate

  1. Distributed BOLD-response in association cortex vector state space predicts reaction time during selective attention.

    Science.gov (United States)

    Musso, Francesco; Konrad, Andreas; Vucurevic, Goran; Schäffner, Cornelius; Friedrich, Britta; Frech, Peter; Stoeter, Peter; Winterer, Georg

    2006-02-15

    Human cortical information processing is thought to be dominated by distributed activity in vector state space (Churchland, P.S., Sejnowski, T.J., 1992. The Computational Brain. MIT Press, Cambridge.). In principle, it should be possible to quantify distributed brain activation with independent component analysis (ICA) through vector-based decomposition, i.e., through a separation of a mixture of sources. Using event-related functional magnetic resonance imaging (fMRI) during a selective attention-requiring task (visual oddball), we explored how the number of independent components within activated cortical areas is related to reaction time. Prior to ICA, the activated cortical areas were determined on the basis of a General linear model (GLM) voxel-by-voxel analysis of the target stimuli (checkerboard reversal). Two activated cortical areas (temporoparietal cortex, medial prefrontal cortex) were further investigated as these cortical regions are known to be the sites of simultaneously active electromagnetic generators which give rise to the compound event-related potential P300 during oddball task conditions. We found that the number of independent components more strongly predicted reaction time than the overall level of "activation" (GLM BOLD-response) in the left temporoparietal area whereas in the medial prefrontal cortex both ICA and GLM predicted reaction time equally well. Comparable correlations were not seen when principle components were used instead of independent components. These results indicate that the number of independently activated components, i.e., a high level of cortical activation complexity in cortical vector state space, may index particularly efficient information processing during selective attention-requiring tasks. To our best knowledge, this is the first report describing a potential relationship between neuronal generators of cognitive processes, the associated electrophysiological evidence for the existence of distributed networks

  2. High-Lift Propeller Noise Prediction for a Distributed Electric Propulsion Flight Demonstrator

    Science.gov (United States)

    Nark, Douglas M.; Buning, Pieter G.; Jones, William T.; Derlaga, Joseph M.

    2017-01-01

    Over the past several years, the use of electric propulsion technologies within aircraft design has received increased attention. The characteristics of electric propulsion systems open up new areas of the aircraft design space, such as the use of distributed electric propulsion (DEP). In this approach, electric motors are placed in many different locations to achieve increased efficiency through integration of the propulsion system with the airframe. Under a project called Scalable Convergent Electric Propulsion Technology Operations Research (SCEPTOR), NASA is designing a flight demonstrator aircraft that employs many "high-lift propellers" distributed upstream of the wing leading edge and two cruise propellers (one at each wingtip). As the high-lift propellers are operational at low flight speeds (take-off/approach flight conditions), the impact of the DEP configuration on the aircraft noise signature is also an important design consideration. This paper describes efforts toward the development of a mulit-fidelity aerodynamic and acoustic methodology for DEP high-lift propeller aeroacoustic modeling. Specifically, the PAS, OVERFLOW 2, and FUN3D codes are used to predict the aerodynamic performance of a baseline high-lift propeller blade set. Blade surface pressure results from the aerodynamic predictions are then used with PSU-WOPWOP and the F1A module of the NASA second generation Aircraft NOise Prediction Program to predict the isolated high-lift propeller noise source. Comparisons of predictions indicate that general trends related to angle of attack effects at the blade passage frequency are captured well with the various codes. Results for higher harmonics of the blade passage frequency appear consistent for the CFD based methods. Conversely, evidence of the need for a study of the effects of increased azimuthal grid resolution on the PAS based results is indicated and will be pursued in future work. Overall, the results indicate that the computational

  3. Towards the prediction of essential genes by integration of network topology, cellular localization and biological process information

    Directory of Open Access Journals (Sweden)

    Lemke Ney

    2009-09-01

    Full Text Available Abstract Background The identification of essential genes is important for the understanding of the minimal requirements for cellular life and for practical purposes, such as drug design. However, the experimental techniques for essential genes discovery are labor-intensive and time-consuming. Considering these experimental constraints, a computational approach capable of accurately predicting essential genes would be of great value. We therefore present here a machine learning-based computational approach relying on network topological features, cellular localization and biological process information for prediction of essential genes. Results We constructed a decision tree-based meta-classifier and trained it on datasets with individual and grouped attributes-network topological features, cellular compartments and biological processes-to generate various predictors of essential genes. We showed that the predictors with better performances are those generated by datasets with integrated attributes. Using the predictor with all attributes, i.e., network topological features, cellular compartments and biological processes, we obtained the best predictor of essential genes that was then used to classify yeast genes with unknown essentiality status. Finally, we generated decision trees by training the J48 algorithm on datasets with all network topological features, cellular localization and biological process information to discover cellular rules for essentiality. We found that the number of protein physical interactions, the nuclear localization of proteins and the number of regulating transcription factors are the most important factors determining gene essentiality. Conclusion We were able to demonstrate that network topological features, cellular localization and biological process information are reliable predictors of essential genes. Moreover, by constructing decision trees based on these data, we could discover cellular rules governing

  4. Microstructure distribution and mechanical properties prediction of boron alloy during hot forming using FE simulation

    International Nuclear Information System (INIS)

    Cui Junjia; Lei Chengxi; Xing Zhongwen; Li Chunfeng

    2012-01-01

    Highlights: ► We model microstructural evolution during hot forming using a metallo-thermo-mechanical model. ► The effect of water-cooled on temperature distribution of blank and tools was investigated. ► The effect of process parameters on microstructure and mechanical properties were investigated. ► FE results were compared to experimental results and the errors of mechanical properties were in a reasonable scope. - Abstract: As a theoretical tool predicting microstructural evolution of boron alloy, the finite element (FE) method has received considerable attention in recent years. In this work, we focus on the boron alloy under non-isothermal hot forming conditions and establish a fully coupled metallo-thermo-mechanical model taking account of cooling and oxide. Based on the proposed model, we investigate the phase transformation and predict the hardness during the hot forming process via FE simulation. In addition, according to the hardness, the tensile strength during non-isothermal forming is predicted. Supporting the feasibility of the proposed model is the experiments where BR1500HS alloy is hot-worked at various conditions that derive a promising agreement of microstructures, hardness, and tensile strength to the simulation data.

  5. Predictions of malaria vector distribution in Belize based on multispectral satellite data.

    Science.gov (United States)

    Roberts, D R; Paris, J F; Manguin, S; Harbach, R E; Woodruff, R; Rejmankova, E; Polanco, J; Wullschleger, B; Legters, L J

    1996-03-01

    Use of multispectral satellite data to predict arthropod-borne disease trouble spots is dependent on clear understandings of environmental factors that determine the presence of disease vectors. A blind test of remote sensing-based predictions for the spatial distribution of a malaria vector, Anopheles pseudopunctipennis, was conducted as a follow-up to two years of studies on vector-environmental relationships in Belize. Four of eight sites that were predicted to be high probability locations for presence of An. pseudopunctipennis were positive and all low probability sites (0 of 12) were negative. The absence of An. pseudopunctipennis at four high probability locations probably reflects the low densities that seem to characterize field populations of this species, i.e., the population densities were below the threshold of our sampling effort. Another important malaria vector, An. darlingi, was also present at all high probability sites and absent at all low probability sites. Anopheles darlingi, like An. pseudopunctipennis, is a riverine species. Prior to these collections at ecologically defined locations, this species was last detected in Belize in 1946.

  6. Evolution of biological sequences implies an extreme value distribution of type I for both global and local pairwise alignment scores.

    Science.gov (United States)

    Bastien, Olivier; Maréchal, Eric

    2008-08-07

    Confidence in pairwise alignments of biological sequences, obtained by various methods such as Blast or Smith-Waterman, is critical for automatic analyses of genomic data. Two statistical models have been proposed. In the asymptotic limit of long sequences, the Karlin-Altschul model is based on the computation of a P-value, assuming that the number of high scoring matching regions above a threshold is Poisson distributed. Alternatively, the Lipman-Pearson model is based on the computation of a Z-value from a random score distribution obtained by a Monte-Carlo simulation. Z-values allow the deduction of an upper bound of the P-value (1/Z-value2) following the TULIP theorem. Simulations of Z-value distribution is known to fit with a Gumbel law. This remarkable property was not demonstrated and had no obvious biological support. We built a model of evolution of sequences based on aging, as meant in Reliability Theory, using the fact that the amount of information shared between an initial sequence and the sequences in its lineage (i.e., mutual information in Information Theory) is a decreasing function of time. This quantity is simply measured by a sequence alignment score. In systems aging, the failure rate is related to the systems longevity. The system can be a machine with structured components, or a living entity or population. "Reliability" refers to the ability to operate properly according to a standard. Here, the "reliability" of a sequence refers to the ability to conserve a sufficient functional level at the folded and maturated protein level (positive selection pressure). Homologous sequences were considered as systems 1) having a high redundancy of information reflected by the magnitude of their alignment scores, 2) which components are the amino acids that can independently be damaged by random DNA mutations. From these assumptions, we deduced that information shared at each amino acid position evolved with a constant rate, corresponding to the

  7. Evolution of biological sequences implies an extreme value distribution of type I for both global and local pairwise alignment scores

    Directory of Open Access Journals (Sweden)

    Maréchal Eric

    2008-08-01

    Full Text Available Abstract Background Confidence in pairwise alignments of biological sequences, obtained by various methods such as Blast or Smith-Waterman, is critical for automatic analyses of genomic data. Two statistical models have been proposed. In the asymptotic limit of long sequences, the Karlin-Altschul model is based on the computation of a P-value, assuming that the number of high scoring matching regions above a threshold is Poisson distributed. Alternatively, the Lipman-Pearson model is based on the computation of a Z-value from a random score distribution obtained by a Monte-Carlo simulation. Z-values allow the deduction of an upper bound of the P-value (1/Z-value2 following the TULIP theorem. Simulations of Z-value distribution is known to fit with a Gumbel law. This remarkable property was not demonstrated and had no obvious biological support. Results We built a model of evolution of sequences based on aging, as meant in Reliability Theory, using the fact that the amount of information shared between an initial sequence and the sequences in its lineage (i.e., mutual information in Information Theory is a decreasing function of time. This quantity is simply measured by a sequence alignment score. In systems aging, the failure rate is related to the systems longevity. The system can be a machine with structured components, or a living entity or population. "Reliability" refers to the ability to operate properly according to a standard. Here, the "reliability" of a sequence refers to the ability to conserve a sufficient functional level at the folded and maturated protein level (positive selection pressure. Homologous sequences were considered as systems 1 having a high redundancy of information reflected by the magnitude of their alignment scores, 2 which components are the amino acids that can independently be damaged by random DNA mutations. From these assumptions, we deduced that information shared at each amino acid position evolved with a

  8. Predicting the distribution of the Asian tapir in Peninsular Malaysia using maximum entropy modeling.

    Science.gov (United States)

    Clements, Gopalasamy Reuben; Rayan, D Mark; Aziz, Sheema Abdul; Kawanishi, Kae; Traeholt, Carl; Magintan, David; Yazi, Muhammad Fadlli Abdul; Tingley, Reid

    2012-12-01

    In 2008, the IUCN threat status of the Asian tapir (Tapirus indicus) was reclassified from 'vulnerable' to 'endangered'. The latest distribution map from the IUCN Red List suggests that the tapirs' native range is becoming increasingly fragmented in Peninsular Malaysia, but distribution data collected by local researchers suggest a more extensive geographical range. Here, we compile a database of 1261 tapir occurrence records within Peninsular Malaysia, and demonstrate that this species, indeed, has a much broader geographical range than the IUCN range map suggests. However, extreme spatial and temporal bias in these records limits their utility for conservation planning. Therefore, we used maximum entropy (MaxEnt) modeling to elucidate the potential extent of the Asian tapir's occurrence in Peninsular Malaysia while accounting for bias in existing distribution data. Our MaxEnt model predicted that the Asian tapir has a wider geographic range than our fine-scale data and the IUCN range map both suggest. Approximately 37% of Peninsular Malaysia contains potentially suitable tapir habitats. Our results justify a revision to the Asian tapir's extent of occurrence in the IUCN Red List. Furthermore, our modeling demonstrated that selectively logged forests encompass 45% of potentially suitable tapir habitats, underscoring the importance of these habitats for the conservation of this species in Peninsular Malaysia. © 2012 Wiley Publishing Asia Pty Ltd, ISZS and IOZ/CAS.

  9. Predicting malaria vector distribution under climate change scenarios in China: Challenges for malaria elimination

    Science.gov (United States)

    Ren, Zhoupeng; Wang, Duoquan; Ma, Aimin; Hwang, Jimee; Bennett, Adam; Sturrock, Hugh J. W.; Fan, Junfu; Zhang, Wenjie; Yang, Dian; Feng, Xinyu; Xia, Zhigui; Zhou, Xiao-Nong; Wang, Jinfeng

    2016-02-01

    Projecting the distribution of malaria vectors under climate change is essential for planning integrated vector control activities for sustaining elimination and preventing reintroduction of malaria. In China, however, little knowledge exists on the possible effects of climate change on malaria vectors. Here we assess the potential impact of climate change on four dominant malaria vectors (An. dirus, An. minimus, An. lesteri and An. sinensis) using species distribution models for two future decades: the 2030 s and the 2050 s. Simulation-based estimates suggest that the environmentally suitable area (ESA) for An. dirus and An. minimus would increase by an average of 49% and 16%, respectively, under all three scenarios for the 2030 s, but decrease by 11% and 16%, respectively in the 2050 s. By contrast, an increase of 36% and 11%, respectively, in ESA of An. lesteri and An. sinensis, was estimated under medium stabilizing (RCP4.5) and very heavy (RCP8.5) emission scenarios. in the 2050 s. In total, we predict a substantial net increase in the population exposed to the four dominant malaria vectors in the decades of the 2030 s and 2050 s, considering land use changes and urbanization simultaneously. Strategies to achieve and sustain malaria elimination in China will need to account for these potential changes in vector distributions and receptivity.

  10. Predicting malaria vector distribution under climate change scenarios in China: Challenges for malaria elimination.

    Science.gov (United States)

    Ren, Zhoupeng; Wang, Duoquan; Ma, Aimin; Hwang, Jimee; Bennett, Adam; Sturrock, Hugh J W; Fan, Junfu; Zhang, Wenjie; Yang, Dian; Feng, Xinyu; Xia, Zhigui; Zhou, Xiao-Nong; Wang, Jinfeng

    2016-02-12

    Projecting the distribution of malaria vectors under climate change is essential for planning integrated vector control activities for sustaining elimination and preventing reintroduction of malaria. In China, however, little knowledge exists on the possible effects of climate change on malaria vectors. Here we assess the potential impact of climate change on four dominant malaria vectors (An. dirus, An. minimus, An. lesteri and An. sinensis) using species distribution models for two future decades: the 2030 s and the 2050 s. Simulation-based estimates suggest that the environmentally suitable area (ESA) for An. dirus and An. minimus would increase by an average of 49% and 16%, respectively, under all three scenarios for the 2030 s, but decrease by 11% and 16%, respectively in the 2050 s. By contrast, an increase of 36% and 11%, respectively, in ESA of An. lesteri and An. sinensis, was estimated under medium stabilizing (RCP4.5) and very heavy (RCP8.5) emission scenarios. in the 2050 s. In total, we predict a substantial net increase in the population exposed to the four dominant malaria vectors in the decades of the 2030 s and 2050 s, considering land use changes and urbanization simultaneously. Strategies to achieve and sustain malaria elimination in China will need to account for these potential changes in vector distributions and receptivity.

  11. Predicting Impacts of Future Climate Change on the Distribution of the Widespread Conifer Platycladus orientalis.

    Directory of Open Access Journals (Sweden)

    Xian-Ge Hu

    Full Text Available Chinese thuja (Platycladus orientalis has a wide but fragmented distribution in China. It is an important conifer tree in reforestation and plays important roles in ecological restoration in the arid mountains of northern China. Based on high-resolution environmental data for current and future scenarios, we modeled the present and future suitable habitat for P. orientalis, evaluated the importance of environmental factors in shaping the species' distribution, and identified regions of high risk under climate change scenarios. The niche models showed that P. orientalis has suitable habitat of ca. 4.2×106 km2 across most of eastern China and identified annual temperature, monthly minimum and maximum ultraviolet-B radiation and wet-day frequency as the critical factors shaping habitat availability for P. orientalis. Under the low concentration greenhouse gas emissions scenario, the range of the species may increase as global warming intensifies; however, under the higher concentrations of emissions scenario, we predicted a slight expansion followed by contraction in distribution. Overall, the range shift to higher latitudes and elevations would become gradually more significant. The information gained from this study should be an useful reference for implementing long-term conservation and management strategies for the species.

  12. [Predicting the impact of global warming on the geographical distribution pattern of Quercus variabilis in China].

    Science.gov (United States)

    Li, Yao; Zhang, Xing-wang; Fang, Yan-ming

    2014-12-01

    The geographical distribution of Quercus variabilis in China with its climate characteristics was analyzed based on DIVA-GIS which was also used to estimate the response of future potential distribution to global warming by Bioclim and Domain models. Analysis results showed the geographical distribution of Q. variabilis could be divided into 7 subregions: Henduan Mountains, Yunnan-Guizhou Plateau, North China, East China, Liaodong-Shandong Peninsula, Taiwan Island, and Qinling-Daba Mountains. These subregions are across 7 temperature zones, 2 moisture regions and 17 climatic subregions, including 8 climate types. The modern abundance center of Q. variabilis is Qinling, Daba and Funiu mountains. The condition of mean annual temperature 7.5-19.8 degrees C annual precipitation 471-1511 mm, is suitable for Q. variabilis. Areas under the receiver operating characteristic curve (AUC values), of Domain and Boiclim models were 0.910, 0.779; the former predicted that the potential regions of high suitability for Q. variabilis are Qinling, Daba, Funiu, Tongbai, and Dabie mountains, eastern and western Yunnan-Guizhou Plateau, hills of southern Jiangsu and Anhui, part of the mountains in North China. Global warming might lead to the shrinking in suitable region and retreating from the south for Q. variabilis.

  13. Predicting the distribution of commercially important invertebrate stocks under future climate.

    Directory of Open Access Journals (Sweden)

    Bayden D Russell

    Full Text Available The future management of commercially exploited species is challenging because techniques used to predict the future distribution of stocks under climate change are currently inadequate. We projected the future distribution and abundance of two commercially harvested abalone species (blacklip abalone, Haliotis rubra and greenlip abalone, H. laevigata inhabiting coastal South Australia, using multiple species distribution models (SDM and for decadal time slices through to 2100. Projections are based on two contrasting global greenhouse gas emissions scenarios. The SDMs identified August (winter Sea Surface Temperature (SST as the best descriptor of abundance and forecast that warming of winter temperatures under both scenarios may be beneficial to both species by allowing increased abundance and expansion into previously uninhabited coasts. This range expansion is unlikely to be realised, however, as projected warming of March SST is projected to exceed temperatures which cause up to 10-fold increases in juvenile mortality. By linking fine-resolution forecasts of sea surface temperature under different climate change scenarios to SDMs and physiological experiments, we provide a practical first approximation of the potential impact of climate-induced change on two species of marine invertebrates in the same fishery.

  14. Biological variation of lipid constituents and distribution of tocopherols and astaxanthin in farmed Atlantic salmon (Salmo salar)

    DEFF Research Database (Denmark)

    Refsgaard, Hanne; Brockhoff, Per B; Jensen, Benny

    1998-01-01

    The contents of fat, astaxanthin, and tocogherols and the fatty acid composition of a homogeneous group of 145 farmed Atlantic salmon (Salmo salar) were determined. The analytical variation of the data was stastistically-separated from the biological variation. The fat content in the muscle near...... the head was 15.0% with a biological standard deviation of 3.0%. The astaxanthin concentration was 5.5 mg/kg of muscle with a biological standard deviation of 1.1 mg/kg of muscle, and the canthaxanthin concentration was 200 mu g/kg of muscle with a standard deviation of 47 mu g/kg of muscle....... The concentrations of alpha-, gamma-, and delta-tocopherols were approximately 32, 2.9, and 0.4 mg/kg of muscle, respectively, and the biological standard deviations were 4.5, 0.4, and 0.07 mg/kg (14, 14, and 20%), respectively. in another group of five salmon the distributions throughout the fillet were determined...

  15. [The incidence and distribution of accidents with biological fluids among health personnel and the general population].

    Science.gov (United States)

    Imaz Iglesia, I; Gómez López, L I; Fernández Martínez, J A; Mareca Doñate, R; Sangrador Arenas, L A

    1996-01-01

    To assess the informative usefulness of the Registry, to calculate the incidence rates of accident with biological fluids among health care workers and in the community, to know about the postaccident rate of seroconversion to HIV and to identify risk groups. A descriptive study of the HIV records file of the Registry of Accidental Contacts to Biological Fluids in the Clinic Hospital of Zaragoza was conducted, between January 1987 and September 1993. The registry includes the reports of health care workers and the general population of Health Area III in Aragón (Spain), except for the Calatayud's Hospital. Incidence rates, rate ratios and their 95% confidence intervals were calculated. A total number of 595 accidents were reported, in none of them and HIV infection occurred subsequently. The incidence rate in health care workers was of 1.7 reports per 100 workers per year, while in the community it was of 8.1 per 100,000 people. The housekeeping staff was the group with a higher incidence (rate = 6.7; 95% IC: 3-14.8) and the type of accident more frequently described was needlestick injury. The incidence of reported accidents has increased in the community and in health care workers, which may be due to the increase in the reporting. In health care workers, the incidence in 1993 was within the range reported from other countries. The perception of risk is universal after accidents with unknown biological fluids. The correct disposal of material with biological contamination should be the more important preventive action.

  16. Drivers of extinction risk in African mammals: the interplay of distribution state, human pressure, conservation response and species biology.

    Science.gov (United States)

    Di Marco, Moreno; Buchanan, Graeme M; Szantoi, Zoltan; Holmgren, Milena; Grottolo Marasini, Gabriele; Gross, Dorit; Tranquilli, Sandra; Boitani, Luigi; Rondinini, Carlo

    2014-01-01

    Although conservation intervention has reversed the decline of some species, our success is outweighed by a much larger number of species moving towards extinction. Extinction risk modelling can identify correlates of risk and species not yet recognized to be threatened. Here, we use machine learning models to identify correlates of extinction risk in African terrestrial mammals using a set of variables belonging to four classes: species distribution state, human pressures, conservation response and species biology. We derived information on distribution state and human pressure from satellite-borne imagery. Variables in all four classes were identified as important predictors of extinction risk, and interactions were observed among variables in different classes (e.g. level of protection, human threats, species distribution ranges). Species biology had a key role in mediating the effect of external variables. The model was 90% accurate in classifying extinction risk status of species, but in a few cases the observed and modelled extinction risk mismatched. Species in this condition might suffer from an incorrect classification of extinction risk (hence require reassessment). An increased availability of satellite imagery combined with improved resolution and classification accuracy of the resulting maps will play a progressively greater role in conservation monitoring.

  17. Prediction of the filtrate particle size distribution from the pore size distribution in membrane filtration: Numerical correlations from computer simulations

    Science.gov (United States)

    Marrufo-Hernández, Norma Alejandra; Hernández-Guerrero, Maribel; Nápoles-Duarte, José Manuel; Palomares-Báez, Juan Pedro; Chávez-Rojo, Marco Antonio

    2018-03-01

    We present a computational model that describes the diffusion of a hard spheres colloidal fluid through a membrane. The membrane matrix is modeled as a series of flat parallel planes with circular pores of different sizes and random spatial distribution. This model was employed to determine how the size distribution of the colloidal filtrate depends on the size distributions of both, the particles in the feed and the pores of the membrane, as well as to describe the filtration kinetics. A Brownian dynamics simulation study considering normal distributions was developed in order to determine empirical correlations between the parameters that characterize these distributions. The model can also be extended to other distributions such as log-normal. This study could, therefore, facilitate the selection of membranes for industrial or scientific filtration processes once the size distribution of the feed is known and the expected characteristics in the filtrate have been defined.

  18. Study on the biological half-life and organ-distribution of tritiated lysine-vasopressin in Brattleboro rats

    International Nuclear Information System (INIS)

    Laczi, F.; Laszlo, F.A.; Keri, Gy.; Teplan, I.

    1980-01-01

    The biological half-life and organ-distribution of tritiated lysine-vasopressin were determined in R-Amsterdam rats, and in homozygous and heterozygous Brattleboro rats with hereditary central diabetes insipidus. It was found that the biological half-life of the tritiated lysin-vasopressin in the Brattleboro rats did not differ significantly from that found in the R-Amsterdam rats. The highest radioactivities were observed in the neuro- and adenohypophyses and in the kidneys of both the R-Amsterdam and the Brattleboro rats. The accumulation of tritiated LVP was higher in the small intestine of the Brattleboro rats than in that of the R-Amsterdam animals. The results have led to the conclusion that the accelerated elimination of vasopressin and its pathologic organ-accumulation are probably not involved in the water metabolism disturbance of Brattleboro rats with hereditary hypothalamic diabetes insipidus. (author)

  19. Proteome-wide Structural Analysis of PTM Hotspots Reveals Regulatory Elements Predicted to Impact Biological Function and Disease*

    Science.gov (United States)

    Dewhurst, Henry; Sundararaman, Niveda

    2016-01-01

    Post-translational modifications (PTMs) regulate protein behavior through modulation of protein-protein interactions, enzymatic activity, and protein stability essential in the translation of genotype to phenotype in eukaryotes. Currently, less than 4% of all eukaryotic PTMs are reported to have biological function - a statistic that continues to decrease with an increasing rate of PTM detection. Previously, we developed SAPH-ire (Structural Analysis of PTM Hotspots) - a method for the prioritization of PTM function potential that has been used effectively to reveal novel PTM regulatory elements in discrete protein families (Dewhurst et al., 2015). Here, we apply SAPH-ire to the set of eukaryotic protein families containing experimental PTM and 3D structure data - capturing 1,325 protein families with 50,839 unique PTM sites organized into 31,747 modified alignment positions (MAPs), of which 2010 (∼6%) possess known biological function. Here, we show that using an artificial neural network model (SAPH-ire NN) trained to identify MAP hotspots with biological function results in prediction outcomes that far surpass the use of single hotspot features, including nearest neighbor PTM clustering methods. We find the greatest enhancement in prediction for positions with PTM counts of five or less, which represent 98% of all MAPs in the eukaryotic proteome and 90% of all MAPs found to have biological function. Analysis of the top 1092 MAP hotspots revealed 267 of truly unknown function (containing 5443 distinct PTMs). Of these, 165 hotspots could be mapped to human KEGG pathways for normal and/or disease physiology. Many high-ranking hotspots were also found to be disease-associated pathogenic sites of amino acid substitution despite the lack of observable PTM in the human protein family member. Taken together, these experiments demonstrate that the functional relevance of a PTM can be predicted very effectively by neural network models, revealing a large but testable

  20. PREDICTING LEVELS OF STRESS FROM BIOLOGICAL ASSESSMENT DATA: EMPIRICAL MODELS FROM THE EASTERN CORN BELT PLAINS

    Science.gov (United States)

    Biological assessment is becoming an increasingly popular tool in the evaluation of stream ecosystem integrity. However, little progress has been made to date in developing tools to relate assessment results to specific stressors. This paper continues the investigation of the f...

  1. Biology-inspired microphysiological system approaches to solve the prediction dilemma of substance testing

    NARCIS (Netherlands)

    Marx, Uwe; Andersson, Tommy B; Bahinski, Anthony; Beilmann, Mario; Beken, Sonja; Cassee, Flemming R; Cirit, Murat; Daneshian, Mardas; Fitzpatrick, Susan; Frey, Olivier; Gaertner, Claudia; Giese, Christoph; Griffith, Linda; Hartung, Thomas; Heringa, Minne B; Hoeng, Julia; de Jong, Wim H; Kojima, Hajime; Kuehnl, Jochen; Leist, Marcel; Luch, Andreas; Maschmeyer, Ilka; Sakharov, Dmitry; Sips, Adrienne J A M; Steger-Hartmann, Thomas; Tagle, Danilo A; Tonevitsky, Alexander; Tralau, Tewes; Tsyb, Sergej; van de Stolpe, Anja; Vandebriel, Rob; Vulto, Paul; Wang, Jufeng; Wiest, Joachim; Rodenburg, Marleen; Roth, Adrian

    2016-01-01

    The recent advent of microphysiological systems - microfluidic biomimetic devices that aspire to emulate the biology of human tissues, organs and circulation in vitro - is envisaged to enable a global paradigm shift in drug development. An extraordinary US governmental initiative and various

  2. Elemental distribution and sample integrity comparison of freeze-dried and frozen-hydrated biological tissue samples with nuclear microprobe

    Energy Technology Data Exchange (ETDEWEB)

    Vavpetič, P., E-mail: primoz.vavpetic@ijs.si [Jožef Stefan Institute, Jamova 39, SI-1000 Ljubljana (Slovenia); Vogel-Mikuš, K. [Biotechnical Faculty, Department of Biology, University of Ljubljana, Jamnikarjeva 101, SI-1000 Ljubljana (Slovenia); Jeromel, L. [Jožef Stefan Institute, Jamova 39, SI-1000 Ljubljana (Slovenia); Ogrinc Potočnik, N. [Jožef Stefan Institute, Jamova 39, SI-1000 Ljubljana (Slovenia); FOM-Institute AMOLF, Science Park 104, 1098 XG Amsterdam (Netherlands); Pongrac, P. [Biotechnical Faculty, Department of Biology, University of Ljubljana, Jamnikarjeva 101, SI-1000 Ljubljana (Slovenia); Department of Plant Physiology, University of Bayreuth, Universitätstr. 30, 95447 Bayreuth (Germany); Drobne, D.; Pipan Tkalec, Ž.; Novak, S.; Kos, M.; Koren, Š.; Regvar, M. [Biotechnical Faculty, Department of Biology, University of Ljubljana, Jamnikarjeva 101, SI-1000 Ljubljana (Slovenia); Pelicon, P. [Jožef Stefan Institute, Jamova 39, SI-1000 Ljubljana (Slovenia)

    2015-04-01

    The analysis of biological samples in frozen-hydrated state with micro-PIXE technique at Jožef Stefan Institute (JSI) nuclear microprobe has matured to a point that enables us to measure and examine frozen tissue samples routinely as a standard research method. Cryotome-cut slice of frozen-hydrated biological sample is mounted between two thin foils and positioned on the sample holder. The temperature of the cold stage in the measuring chamber is kept below 130 K throughout the insertion of the samples and the proton beam exposure. Matrix composition of frozen-hydrated tissue is consisted mostly of ice. Sample deterioration during proton beam exposure is monitored during the experiment, as both Elastic Backscattering Spectrometry (EBS) and Scanning Transmission Ion Microscopy (STIM) in on–off axis geometry are recorded together with the events in two PIXE detectors and backscattered ions from the chopper in a single list-mode file. The aim of this experiment was to determine differences and similarities between two kinds of biological sample preparation techniques for micro-PIXE analysis, namely freeze-drying and frozen-hydrated sample preparation in order to evaluate the improvements in the elemental localisation of the latter technique if any. In the presented work, a standard micro-PIXE configuration for tissue mapping at JSI was used with five detection systems operating in parallel, with proton beam cross section of 1.0 × 1.0 μm{sup 2} and a beam current of 100 pA. The comparison of the resulting elemental distributions measured at the biological tissue prepared in the frozen-hydrated and in the freeze-dried state revealed differences in elemental distribution of particular elements at the cellular level due to the morphology alteration in particular tissue compartments induced either by water removal in the lyophilisation process or by unsatisfactory preparation of samples for cutting and mounting during the shock-freezing phase of sample preparation.

  3. 2012 best practices for repositories collection, storage, retrieval, and distribution of biological materials for research international society for biological and environmental repositories.

    Science.gov (United States)

    2012-04-01

    Third Edition [Formula: see text] [Box: see text] Printed with permission from the International Society for Biological and Environmental Repositories (ISBER) © 2011 ISBER All Rights Reserved Editor-in-Chief Lori D. Campbell, PhD Associate Editors Fay Betsou, PhD Debra Leiolani Garcia, MPA Judith G. Giri, PhD Karen E. Pitt, PhD Rebecca S. Pugh, MS Katherine C. Sexton, MBA Amy P.N. Skubitz, PhD Stella B. Somiari, PhD Individual Contributors to the Third Edition Jonas Astrin, Susan Baker, Thomas J. Barr, Erica Benson, Mark Cada, Lori Campbell, Antonio Hugo Jose Froes Marques Campos, David Carpentieri, Omoshile Clement, Domenico Coppola, Yvonne De Souza, Paul Fearn, Kelly Feil, Debra Garcia, Judith Giri, William E. Grizzle, Kathleen Groover, Keith Harding, Edward Kaercher, Joseph Kessler, Sarah Loud, Hannah Maynor, Kevin McCluskey, Kevin Meagher, Cheryl Michels, Lisa Miranda, Judy Muller-Cohn, Rolf Muller, James O'Sullivan, Karen Pitt, Rebecca Pugh, Rivka Ravid, Katherine Sexton, Ricardo Luis A. Silva, Frank Simione, Amy Skubitz, Stella Somiari, Frans van der Horst, Gavin Welch, Andy Zaayenga 2012 Best Practices for Repositories: Collection, Storage, Retrieval and Distribution of Biological Materials for Research INTERNATIONAL SOCIETY FOR BIOLOGICAL AND ENVIRONMENTAL REPOSITORIES (ISBER) INTRODUCTION T he availability of high quality biological and environmental specimens for research purposes requires the development of standardized methods for collection, long-term storage, retrieval and distribution of specimens that will enable their future use. Sharing successful strategies for accomplishing this goal is one of the driving forces for the International Society for Biological and Environmental Repositories (ISBER). For more information about ISBER see www.isber.org . ISBER's Best Practices for Repositories (Best Practices) reflect the collective experience of its members and has received broad input from other repository professionals. Throughout this document

  4. Optimization of labeling conditions of n-isopropyl-p-iodoamphetamine chloridate (IMP) with radioiodine. Biological distribution studies

    International Nuclear Information System (INIS)

    Colturato, Maria Tereza

    2000-01-01

    The development of this work was based on a great interest from the medical community in the utilization of N-isopropyl-p-iodoamphetamine chloridate (IMP) labeled with 123 l, for brain perfusion evaluation. The IMP was initially characterized by: Melting Point (MP), Infrared Spectrophotometry (IR), Nuclear Magnetic Resonance Spectrometry (NMR), Elemental Analysis and High Performance Liquid Chromatography (HPLC). After having chosen the ideal method (nucleophilic substitution) to label IMP with that used Cu(I) as reducing agent and ascorbic acid as catalyzing of Cu(II), studies were performed to optimize the labeling parameters of 123 l-IMP: temperature reaction, time reaction, ascorbic acid mass, pH and molar ratio, and stability of the final product. The quality control method (ascending paper chromatographic) used to determine the radiochemistry purity showed to be efficient, fast and of easily handling for routine production. Biological distribution studies were performed with laboratory animals (mice) to determine the percent administered dose in the blood, different organs and whole body after intravenous administration of the radiopharmaceutical. Toxicological evaluation and in vitro study to determine the plasmatic protein binding were also done. The data of the biological distribution in mice have shown that the product crossed the intact blood brain barrier, for a enough time to obtain brain scintigraphic image, thus, allowing a follow up of further studies after the intravenous administration of the radiopharmaceutical. The 123 l-IMP showed a blood clearance and then the principal elimination route was the urinary. The kinetic study of 123 l-IMP, submitting blood samples data to BIEXP.BAS program, showed a biexponential pattern which allowed demonstrating that the compound presents a first phase of quick distribution and a second one slower corresponding to the equilibrium and elimination. Based on the results from radiochemical purity, stability and

  5. Predicting the distribution of four species of raptors (Aves: Accipitridae) in southern Spain: statistical models work better than existing maps

    OpenAIRE

    Bustamante, Javier; Seoane, Javier

    2004-01-01

    Aim To test the effectiveness of statistical models based on explanatory environmental variables vs. existing distribution information (maps and breeding atlas), for predicting the distribution of four species of raptors (family Accipitridae): common buzzard Buteo buteo (Linnaeus, 1758), short-toed eagle Circaetus gallicus (Gmelin, 1788), booted eagle Hieraaetus pennatus (Gmelin, 1788) and black kite Milvus migrans (Boddaert, 1783). Location Andalusia, southe...

  6. A nodal model to predict vertical temperature distribution in a room with floor heating and displacement ventilation

    DEFF Research Database (Denmark)

    Wu, Xiaozhou; Olesen, Bjarne W.; Fang, Lei

    2013-01-01

    In this paper, the development of a nodal model that predicts vertical temperature distribution in a typical office room with floor heating and displacement ventilation (FHDV) is described. The vertical air flow distribution is first determined according to the principle of displacement ventilati...

  7. Biological half-life and distribution of radiocesium in a contaminated population of green treefrogs Hyla cinerea

    International Nuclear Information System (INIS)

    Dapson, R.W.; Kaplan, L.

    1975-01-01

    Radiocesium content of adult male green treefrogs Hyla cinerea from a contaminated habitat is adequately described by a log normal distribution with mean 2.277 log 10 pCi g -1 dry wt (189.2 pCi g -1 ) and variance of 0.031. There was significant negative correlation of body burden with body length and weight (p 2 = 0.10). Biological half-life of radiocesium in unfed, captive frogs held at 20 deg - 30 deg C averaged 30.1 d. (author)

  8. Predicting Causal Relationships from Biological Data: Applying Automated Causal Discovery on Mass Cytometry Data of Human Immune Cells

    KAUST Repository

    Triantafillou, Sofia; Lagani, Vincenzo; Heinze-Deml, Christina; Schmidt, Angelika; Tegner, Jesper; Tsamardinos, Ioannis

    2017-01-01

    Learning the causal relationships that define a molecular system allows us to predict how the system will respond to different interventions. Distinguishing causality from mere association typically requires randomized experiments. Methods for automated  causal discovery from limited experiments exist, but have so far rarely been tested in systems biology applications. In this work, we apply state-of-the art causal discovery methods on a large collection of public mass cytometry data sets, measuring intra-cellular signaling proteins of the human immune system and their response to several perturbations. We show how different experimental conditions can be used to facilitate causal discovery, and apply two fundamental methods that produce context-specific causal predictions. Causal predictions were reproducible across independent data sets from two different studies, but often disagree with the KEGG pathway databases. Within this context, we discuss the caveats we need to overcome for automated causal discovery to become a part of the routine data analysis in systems biology.

  9. Predicting Causal Relationships from Biological Data: Applying Automated Causal Discovery on Mass Cytometry Data of Human Immune Cells

    KAUST Repository

    Triantafillou, Sofia

    2017-09-29

    Learning the causal relationships that define a molecular system allows us to predict how the system will respond to different interventions. Distinguishing causality from mere association typically requires randomized experiments. Methods for automated  causal discovery from limited experiments exist, but have so far rarely been tested in systems biology applications. In this work, we apply state-of-the art causal discovery methods on a large collection of public mass cytometry data sets, measuring intra-cellular signaling proteins of the human immune system and their response to several perturbations. We show how different experimental conditions can be used to facilitate causal discovery, and apply two fundamental methods that produce context-specific causal predictions. Causal predictions were reproducible across independent data sets from two different studies, but often disagree with the KEGG pathway databases. Within this context, we discuss the caveats we need to overcome for automated causal discovery to become a part of the routine data analysis in systems biology.

  10. Mapping molecular orientational distributions for biological sample in 3D (Conference Presentation)

    Science.gov (United States)

    HE, Wei; Ferrand, Patrick; Richter, Benjamin; Bastmeyer, Martin; Brasselet, Sophie

    2016-04-01

    Measuring molecular orientation properties is very appealing for scientists in molecular and cell biology, as well as biomedical research. Orientational organization at the molecular scale is indeed an important brick to cells and tissues morphology, mechanics, functions and pathologies. Recent work has shown that polarized fluorescence imaging, based on excitation polarization tuning in the sample plane, is able to probe molecular orientational order in biological samples; however this applies only to information in 2D, projected in the sample plane. To surpass this limitation, we extended this approach to excitation polarization tuning in 3D. The principle is based on the decomposition of any arbitrary 3D linear excitation in a polarization along the longitudinal z-axis, and a polarization in the transverse xy-sample plane. We designed an interferometer with one arm generating radial polarization light (thus producing longitudinal polarization under high numerical aperture focusing), the other arm controlling a linear polarization in the transverse plane. The amplitude ratio between the two arms can vary so as to get any linear polarized excitation in 3D at the focus of a high NA objective. This technique has been characterized by polarimetry imaging at the back focal plane of the focusing objective, and modeled theoretically. 3D polarized fluorescence microscopy is demonstrated on actin stress fibers in non-flat cells suspended on synthetic polymer structures forming supporting pillars, for which heterogeneous actin orientational order could be identified. This technique shows a great potential in structural investigations in 3D biological systems, such as cell spheroids and tissues.

  11. Ecology, distribution, and predictive occurrence modeling of Palmers chipmunk (Tamias palmeri): a high-elevation small mammal endemic to the Spring Mountains in southern Nevada, USA

    Science.gov (United States)

    Lowrey, Chris E.; Longshore, Kathleen M.; Riddle, Brett R.; Mantooth, Stacy

    2016-01-01

    Although montane sky islands surrounded by desert scrub and shrub steppe comprise a large part of the biological diversity of the Basin and Range Province of southwestern North America, comprehensive ecological and population demographic studies for high-elevation small mammals within these areas are rare. Here, we examine the ecology and population parameters of the Palmer’s chipmunk (Tamias palmeri) in the Spring Mountains of southern Nevada, and present a predictive GIS-based distribution and probability of occurrence model at both home range and geographic spatial scales. Logistic regression analyses and Akaike Information Criterion model selection found variables of forest type, slope, and distance to water sources as predictive of chipmunk occurrence at the geographic scale. At the home range scale, increasing population density, decreasing overstory canopy cover, and decreasing understory canopy cover contributed to increased survival rates.

  12. Predictions for an invaded world: A strategy to predict the distribution of native and non-indigenous species at multiple scales

    Science.gov (United States)

    Reusser, D.A.; Lee, H.

    2008-01-01

    Habitat models can be used to predict the distributions of marine and estuarine non-indigenous species (NIS) over several spatial scales. At an estuary scale, our goal is to predict the estuaries most likely to be invaded, but at a habitat scale, the goal is to predict the specific locations within an estuary that are most vulnerable to invasion. As an initial step in evaluating several habitat models, model performance for a suite of benthic species with reasonably well-known distributions on the Pacific coast of the US needs to be compared. We discuss the utility of non-parametric multiplicative regression (NPMR) for predicting habitat- and estuary-scale distributions of native and NIS. NPMR incorporates interactions among variables, allows qualitative and categorical variables, and utilizes data on absence as well as presence. Preliminary results indicate that NPMR generally performs well at both spatial scales and that distributions of NIS are predicted as well as those of native species. For most species, latitude was the single best predictor, although similar model performance could be obtained at both spatial scales with combinations of other habitat variables. Errors of commission were more frequent at a habitat scale, with omission and commission errors approximately equal at an estuary scale. ?? 2008 International Council for the Exploration of the Sea. Published by Oxford Journals. All rights reserved.

  13. Selecting Optimal Random Forest Predictive Models: A Case Study on Predicting the Spatial Distribution of Seabed Hardness

    Science.gov (United States)

    Li, Jin; Tran, Maggie; Siwabessy, Justy

    2016-01-01

    Spatially continuous predictions of seabed hardness are important baseline environmental information for sustainable management of Australia’s marine jurisdiction. Seabed hardness is often inferred from multibeam backscatter data with unknown accuracy and can be inferred from underwater video footage at limited locations. In this study, we classified the seabed into four classes based on two new seabed hardness classification schemes (i.e., hard90 and hard70). We developed optimal predictive models to predict seabed hardness using random forest (RF) based on the point data of hardness classes and spatially continuous multibeam data. Five feature selection (FS) methods that are variable importance (VI), averaged variable importance (AVI), knowledge informed AVI (KIAVI), Boruta and regularized RF (RRF) were tested based on predictive accuracy. Effects of highly correlated, important and unimportant predictors on the accuracy of RF predictive models were examined. Finally, spatial predictions generated using the most accurate models were visually examined and analysed. This study confirmed that: 1) hard90 and hard70 are effective seabed hardness classification schemes; 2) seabed hardness of four classes can be predicted with a high degree of accuracy; 3) the typical approach used to pre-select predictive variables by excluding highly correlated variables needs to be re-examined; 4) the identification of the important and unimportant predictors provides useful guidelines for further improving predictive models; 5) FS methods select the most accurate predictive model(s) instead of the most parsimonious ones, and AVI and Boruta are recommended for future studies; and 6) RF is an effective modelling method with high predictive accuracy for multi-level categorical data and can be applied to ‘small p and large n’ problems in environmental sciences. Additionally, automated computational programs for AVI need to be developed to increase its computational efficiency and

  14. Predicted tyre-soil interface area and vertical stress distribution based on loading characteristics

    DEFF Research Database (Denmark)

    Schjønning, Per; Stettler, M.; Keller, Thomas

    2015-01-01

    The upper boundary condition for all models simulating stress patterns throughout the soil profile is the stress distribution at the tyre–soil interface. The so-called FRIDA model (Schjønning et al., 2008. Biosyst. Eng. 99, 119–133) treats the contact area as a superellipse and has been shown...... of the actual to recommended inflation pressure ratio. We found that VT and Kr accounted for nearly all variation in the data with respect to the contact area. The contact area width was accurately described by a combination of tyre width and Kr, while the superellipse squareness parameter, n, diminished...... slightly with increasing Kr. Estimated values of the contact area length related to observed data with a standard deviation of about 0.06 m. A difference between traction and implement tyres called for separate prediction equations, especially for the contact area. The FRIDA parameters α and β, reflecting...

  15. Predicting drivers and distributions of deep-sea ecosystems: A cold-water coral case study

    DEFF Research Database (Denmark)

    Mohn, Christian; Rengstorf, Anna; Brown, Colin

    2015-01-01

    pertusa as a case study (Rengstorf et al., 2014). The study shows that predictive models incorporating hydrodynamic variables perform significantly better than models based on terrain parameters only. They are a potentially powerful tool to improve our understanding of deep-sea ecosystem functioning......, facilitating species distribution modelling with high spatial detail. In this study, we used high resolution data (250 m grid size) from a newly developed hydrodynamic model to explore linkages between key physical drivers and occurrences of the cold-water coral Lophelia pertusa in selected areas of the NE...... and to provide decision support for marine spatial planning and conservation in the deep sea. Mohn et al., 2014.Linking benthic hydrodynamics and cold water coral occurrences: A high-resolution model study at three cold-water coral provinces in the NE Atlantic. Progress in Oceanography 122, 92-104. Rengstorf et...

  16. Economic Model Predictive Control for Large-Scale and Distributed Energy Systems

    DEFF Research Database (Denmark)

    Standardi, Laura

    Sources (RESs) in the smart grids is increasing. These energy sources bring uncertainty to the production due to their fluctuations. Hence,smart grids need suitable control systems that are able to continuously balance power production and consumption.  We apply the Economic Model Predictive Control (EMPC......) strategy to optimise the economic performances of the energy systems and to balance the power production and consumption. In the case of large-scale energy systems, the electrical grid connects a high number of power units. Because of this, the related control problem involves a high number of variables......In this thesis, we consider control strategies for large and distributed energy systems that are important for the implementation of smart grid technologies.  An electrical grid has to ensure reliability and avoid long-term interruptions in the power supply. Moreover, the share of Renewable Energy...

  17. Hierarchical Model Predictive Control for Plug-and-Play Resource Distribution

    DEFF Research Database (Denmark)

    Bendtsen, Jan Dimon; Trangbæk, K; Stoustrup, Jakob

    2012-01-01

    of autonomous units. The approach is inspired by smart-grid electric power production and consumption systems, where the flexibility of a large number of power producing and/or power consuming units can be exploited in a smart-grid solution. The objective is to accommodate the load variation on the grid......This chapter deals with hierarchical model predictive control (MPC) of distributed systems. A three level hierarchical approach is proposed, consisting of a high level MPC controller, a second level of so-called aggregators, controlled by an online MPC-like algorithm, and a lower level......, arising on one hand from varying consumption, on the other hand by natural variations in power production e.g. from wind turbines. The proposed method can also be applied to supply chain management systems, where the challenge is to balance demand and supply, using a number of storages each with a maximal...

  18. Distributed Model Predictive Load Frequency Control of Multi-area Power System with DFIGs

    Institute of Scientific and Technical Information of China (English)

    Yi Zhang; Xiangjie Liu; Bin Qu

    2017-01-01

    Reliable load frequency control(LFC) is crucial to the operation and design of modern electric power systems. Considering the LFC problem of a four-area interconnected power system with wind turbines, this paper presents a distributed model predictive control(DMPC) based on coordination scheme.The proposed algorithm solves a series of local optimization problems to minimize a performance objective for each control area. The generation rate constraints(GRCs), load disturbance changes, and the wind speed constraints are considered. Furthermore, the DMPC algorithm may reduce the impact of the randomness and intermittence of wind turbine effectively. A performance comparison between the proposed controller with and without the participation of the wind turbines is carried out. Analysis and simulation results show possible improvements on closed–loop performance, and computational burden with the physical constraints.

  19. Prediction of corrosion rates of water distribution pipelines according to aggressive corrosive water in Korea.

    Science.gov (United States)

    Chung, W S; Yu, M J; Lee, H D

    2004-01-01

    The drinking water network serving Korea has been used for almost 100 years. Therefore, pipelines have suffered various degrees of deterioration due to aggressive environments. The pipe breaks were caused by in-external corrosion, water hammer, surface loading, etc. In this paper, we focused on describing corrosion status in water distribution pipes in Korea and reviewing some methods to predict corrosion rates. Results indicate that corrosive water of lakes was more aggressive than river water and the winter was more aggressive compared to other seasons. The roughness growth rates of Dongbok lake showed 0.23 mm/year. The high variation of corrosion rates is controlled by the aging pipes and smaller diameter. Also the phenolphthalein test on a cementitious core of cement mortar lined ductile cast iron pipe indicated the pipes over 15 years old had lost 50-100% of their lime active cross sectional area.

  20. Predicting Salmonella populations from biological, chemical, and physical indicators in Florida surface waters.

    Science.gov (United States)

    McEgan, Rachel; Mootian, Gabriel; Goodridge, Lawrence D; Schaffner, Donald W; Danyluk, Michelle D

    2013-07-01

    Coliforms, Escherichia coli, and various physicochemical water characteristics have been suggested as indicators of microbial water quality or index organisms for pathogen populations. The relationship between the presence and/or concentration of Salmonella and biological, physical, or chemical indicators in Central Florida surface water samples over 12 consecutive months was explored. Samples were taken monthly for 12 months from 18 locations throughout Central Florida (n = 202). Air and water temperature, pH, oxidation-reduction potential (ORP), turbidity, and conductivity were measured. Weather data were obtained from nearby weather stations. Aerobic plate counts and most probable numbers (MPN) for Salmonella, E. coli, and coliforms were performed. Weak linear relationships existed between biological indicators (E. coli/coliforms) and Salmonella levels (R(2) Florida surface water through logistic regression.

  1. Predicting Salmonella Populations from Biological, Chemical, and Physical Indicators in Florida Surface Waters

    OpenAIRE

    McEgan, Rachel; Mootian, Gabriel; Goodridge, Lawrence D.; Schaffner, Donald W.; Danyluk, Michelle D.

    2013-01-01

    Coliforms, Escherichia coli, and various physicochemical water characteristics have been suggested as indicators of microbial water quality or index organisms for pathogen populations. The relationship between the presence and/or concentration of Salmonella and biological, physical, or chemical indicators in Central Florida surface water samples over 12 consecutive months was explored. Samples were taken monthly for 12 months from 18 locations throughout Central Florida (n = 202). Air and wat...

  2. A biological approach to the interspecies prediction of radiation-induced mortality risk

    International Nuclear Information System (INIS)

    Carnes, B.A.; Grahn, D.; Olshansky, S.J.

    1997-01-01

    Evolutionary explanations for why sexually reproducing organisms grow old suggest that the forces of natural selection affect the ages when diseases occur that are subject to a genetic influence (referred to here as intrinsic diseases). When extended to the population level for a species, this logic leads to the general prediction that age-specific death rates from intrinsic causes should begin to rise as the force of selection wanes once the characteristic age of sexual maturity is attained. Results consistent with these predictions have been found for laboratory mice, beagles, and humans where, after adjusting for differences in life span, it was demonstrated that these species share a common age pattern of mortality for intrinsic causes of death. In quantitative models used to predict radiation-induced mortality, risks are often expressed as multiples of those observed in a control population. A control population, however, is an aging population. As such, mortality risks related to exposure must be interpreted relative to the age-specific risk of death associated with aging. Given the previous success in making interspecies predictions of age-related mortality, the purpose of this study was to determine whether radiation-induced mortality observed in one species could also be predicted quantitatively from a model used to describe the mortality consequences of exposure to radiation in a different species. Mortality data for B6CF 1 mice and beagles exposed to 60 Co γ-rays for the duration of life were used for analysis

  3. Systems Biology-Derived Biomarkers to Predict Progression of Renal Function Decline in Type 2 Diabetes

    DEFF Research Database (Denmark)

    Mayer, Gert; Heerspink, Hiddo J L; Aschauer, Constantin

    2017-01-01

    hormone 1, hepatocyte growth factor, matrix metalloproteinase (MMP) 2, MMP7, MMP8, MMP13, tyrosine kinase, and tumor necrosis factor receptor-1. These biomarkers were measured in baseline serum samples from 1,765 patients recruited into two large clinical trials. eGFR decline was predicted based...... on molecular markers, clinical risk factors (including baseline eGFR and albuminuria), and both combined, and these predictions were evaluated using mixed linear regression models for longitudinal data. RESULTS: The variability of annual eGFR loss explained by the biomarkers, indicated by the adjusted R2 value......, combined with clinical variables, enhances the prediction of renal function loss over a wide range of baseline eGFR values in patients with type 2 diabetes and CKD....

  4. Prediction of hydrogen distribution in the reactor building in CANDU6 plant

    International Nuclear Information System (INIS)

    Jin, Y.; Song, Y.

    2008-01-01

    The CANDU plants have a lot of zircaloy. The fuel cladding, calandria tubes and pressure tubes are made of zircaloy. The zircaloy can be oxidized and hydrogen is generated during severe accident progression. The detonation or deflagration to detonation transition (DDT) due to hydrogen combustion may occur if the local hydrogen concentration or global hydrogen concentration exceeds certain value. The detonation may result in the rupture of the reactor building. The inside of the reactor building of CANDU plants is complex. So prediction of hydrogen distribution in the reactor building is important. This prediction is made using ISAAC code and GOTHIC code. ISAAC code partitioned the reactor building in to 7 compartments. GOTHIC code modeled the CANDU6 reactor building using 12 nodes. The hydrogen concentrations in the various compartments in the reactor building are compared. GOTHIC code slightly underpredicts hydrogen concentration in the F/M rooms than ISAAC code, but trend is same. The hydrogen concentration in the boiler room and the moderator room shows almost same as for both codes. (author)

  5. Numerical Investigation of Temperature Distribution in an Eroded Bend Pipe and Prediction of Erosion Reduced Thickness

    Science.gov (United States)

    Zhu, Hongjun; Feng, Guang; Wang, Qijun

    2014-01-01

    Accurate prediction of erosion thickness is essential for pipe engineering. The objective of the present paper is to study the temperature distribution in an eroded bend pipe and find a new method to predict the erosion reduced thickness. Computational fluid dynamic (CFD) simulations with FLUENT software are carried out to investigate the temperature field. And effects of oil inlet rate, oil inlet temperature, and erosion reduced thickness are examined. The presence of erosion pit brings about the obvious fluctuation of temperature drop along the extrados of bend. And the minimum temperature drop presents at the most severe erosion point. Small inlet temperature or large inlet velocity can lead to small temperature drop, while shallow erosion pit causes great temperature drop. The dimensionless minimum temperature drop is analyzed and the fitting formula is obtained. Using the formula we can calculate the erosion reduced thickness, which is only needed to monitor the outer surface temperature of bend pipe. This new method can provide useful guidance for pipeline monitoring and replacement. PMID:24719576

  6. [Drug vectorization or how to modulate tissular and cellular distribution of biologically active compounds].

    Science.gov (United States)

    Couvreur, P

    2001-07-01

    Drug vectorization has undergone considerable development over the last few years. This review focuses on the intravenous route of administration. Colloid formulations allow a modulation of drug tissue distribution. Using liposomes and nanoparticles with unmodified surfaces, drugs can be targeted to macrophages of the reticulum endothelium system. When the liposomes or nanoparticles are covered with hydrophilic or flexible polymers, the vascular phase can be favored in order, for example, to facilitate selective extravasation at a tumor site. Therapeutic applications of these systems are presented. The development of "intelligent" vectors capable of modulating intracellular distribution of an active compounds is an equally interesting approach, for example pH-sensitive liposomes or nanoparticles decorated with folic acid capable of targeting intracellular cytoplasm.

  7. ProBiS tools (algorithm, database, and web servers) for predicting and modeling of biologically interesting proteins.

    Science.gov (United States)

    Konc, Janez; Janežič, Dušanka

    2017-09-01

    ProBiS (Protein Binding Sites) Tools consist of algorithm, database, and web servers for prediction of binding sites and protein ligands based on the detection of structurally similar binding sites in the Protein Data Bank. In this article, we review the operations that ProBiS Tools perform, provide comments on the evolution of the tools, and give some implementation details. We review some of its applications to biologically interesting proteins. ProBiS Tools are freely available at http://probis.cmm.ki.si and http://probis.nih.gov. Copyright © 2017 Elsevier Ltd. All rights reserved.

  8. Stress Prediction for Distributed Structural Health Monitoring Using Existing Measurements and Pattern Recognition.

    Science.gov (United States)

    Lu, Wei; Teng, Jun; Zhou, Qiushi; Peng, Qiexin

    2018-02-01

    The stress in structural steel members is the most useful and directly measurable physical quantity to evaluate the structural safety in structural health monitoring, which is also an important index to evaluate the stress distribution and force condition of structures during structural construction and service phases. Thus, it is common to set stress as a measure in steel structural monitoring. Considering the economy and the importance of the structural members, there are only a limited number of sensors that can be placed, which means that it is impossible to obtain the stresses of all members directly using sensors. This study aims to develop a stress response prediction method for locations where there are insufficent sensors, using measurements from a limited number of sensors and pattern recognition. The detailed improved aspects are: (1) a distributed computing process is proposed, where the same pattern is recognized by several subsets of measurements; and (2) the pattern recognition using the subset of measurements is carried out by considering the optimal number of sensors and number of fusion patterns. The validity and feasibility of the proposed method are verified using two examples: the finite-element simulation of a single-layer shell-like steel structure, and the structural health monitoring of the space steel roof of Shenzhen Bay Stadium; for the latter, the anti-noise performance of this method is verified by the stress measurements from a real-world project.

  9. Prediction for the flow distribution and the pressure drop of a plate type fuel assembly

    International Nuclear Information System (INIS)

    Park, Jong Hark; Jo, Dea Sung; Chae, Hee Taek; Lee, Byung Chul

    2011-01-01

    A plate type fuel assembly widely used in many research reactors does not allow the coolant to mix with neighboring fuel channels due to the completely separated flow channels. If there is a serious inequality of coolant distribution among channels, it can reduce thermal-hydraulic safety margin, as well as it can cause a deformation of fuel plates by the pressure difference between neighboring channels, thus the flow uniformity in the fuel assembly should be confirmed. When designing a primary cooling system (PCS), the pressure drop through a reactor core is a dominant value to determine the PCS pump size. The major portion of reactor core pressure drop is caused by the fuel assemblies. However it is not easy to get a reasonable estimation of pressure drop due to the geometric complexity of the fuel assembly and the thin gaps between fuel assemblies. The flow rate through the gap is important part to determine the total flow rate of PCS, so it should be estimated as reasonable as possible. It requires complex and difficult jobs to get useful data. In this study CFD analysis to predict the flow distribution and the pressure drop were conducted on the plate type fuel assembly, which results would be used to be preliminary data to determine the PCS flow rate and to improve the design of a fuel assembly

  10. Abdominal fat distribution on computed tomography predicts ureteric calculus fragmentation by shock wave lithotripsy

    International Nuclear Information System (INIS)

    Juan, Hsu-Cheng; Chou, Yii-Her; Lin, Hung-Yu; Yang, Yi-Hsin; Shih, Paul Ming-Chen; Chuang, Shu-Mien; Shen, Jung-Tsung; Juan, Yung-Shun

    2012-01-01

    To assess the effects of abdominal fat on shock wave lithotripsy (SWL). We used pre-SWL unenhanced computed tomography (CT) to evaluate the impact of abdominal fat distribution and calculus characteristics on the outcome of SWL. One hundred and eighty-five patients with a solitary ureteric calculus treated with SWL were retrospectively reviewed. Each patient underwent unenhanced CT within 1 month before SWL treatment. Treatment outcomes were evaluated 1 month later. Unenhanced CT parameters, including calculus surface area, Hounsfield unit (HU) density, abdominal fat area and skin to calculus distance (SSD) were analysed. One hundred and twenty-eight of the 185 patients were found to be calculus-free following treatment. HU density, total fat area, visceral fat area and SSD were identified as significant variables on multivariate logistic regression analysis. The receiver-operating characteristic analyses showed that total fat area, para/perirenal fat area and visceral fat area were sensitive predictors of SWL outcomes. This study revealed that higher quantities of abdominal fat, especially visceral fat, are associated with a lower calculus-free rate following SWL treatment. Unenhanced CT is a convenient technique for diagnosing the presence of a calculus, assessing the intra-abdominal fat distribution and thereby helping to predict the outcome of SWL. (orig.)

  11. Abdominal fat distribution on computed tomography predicts ureteric calculus fragmentation by shock wave lithotripsy

    Energy Technology Data Exchange (ETDEWEB)

    Juan, Hsu-Cheng; Chou, Yii-Her [Kaohsiung Medical University Hospital, Department of Urology, Kaohsiung (China); Lin, Hung-Yu [Kaohsiung Medical University, Graduate Institute of Medicine, Kaohsiung (China); E-Da Hospital/ I-Shou University, Department of Urology, Kaohsiung (China); Yang, Yi-Hsin [Kaohsiung Medical University, Institute of Oral Health Sciences, Kaohsiung (China); Shih, Paul Ming-Chen [Kaohsiung Municipal Hsiao-Kang Hospital, Department of Radiology, Kaohsiung (China); Kaohsiung Medical University, Department of Radiology, Kaohsiung (China); Chuang, Shu-Mien [Yuh-Ing Junior College of Health Care and Management, Kaohsiung (China); Shen, Jung-Tsung [Kaohsiung Municipal Hsiao-Kang Hospital, Department of Urology, Kaohsiung (China); Juan, Yung-Shun [Kaohsiung Medical University Hospital, Department of Urology, Kaohsiung (China); Kaohsiung Medical University, Graduate Institute of Medicine, Kaohsiung (China); Kaohsiung Medical University, Department of Urology, Faculty of Medicine, Kaohsiung (China)

    2012-08-15

    To assess the effects of abdominal fat on shock wave lithotripsy (SWL). We used pre-SWL unenhanced computed tomography (CT) to evaluate the impact of abdominal fat distribution and calculus characteristics on the outcome of SWL. One hundred and eighty-five patients with a solitary ureteric calculus treated with SWL were retrospectively reviewed. Each patient underwent unenhanced CT within 1 month before SWL treatment. Treatment outcomes were evaluated 1 month later. Unenhanced CT parameters, including calculus surface area, Hounsfield unit (HU) density, abdominal fat area and skin to calculus distance (SSD) were analysed. One hundred and twenty-eight of the 185 patients were found to be calculus-free following treatment. HU density, total fat area, visceral fat area and SSD were identified as significant variables on multivariate logistic regression analysis. The receiver-operating characteristic analyses showed that total fat area, para/perirenal fat area and visceral fat area were sensitive predictors of SWL outcomes. This study revealed that higher quantities of abdominal fat, especially visceral fat, are associated with a lower calculus-free rate following SWL treatment. Unenhanced CT is a convenient technique for diagnosing the presence of a calculus, assessing the intra-abdominal fat distribution and thereby helping to predict the outcome of SWL. (orig.)

  12. The prediction of the-circumferential fuel-temperature distribution under ballonian condition. Vol. 3

    Energy Technology Data Exchange (ETDEWEB)

    Abdallah, A M; El-Sherbiny, E M [Reactor Department, Nuclear Research Center, Atomic Energy Authority, Cairo (Egypt)

    1996-03-01

    Swelling and thermal distortion of nuclear fuel elements due to depressurization of reactor coolant may cause contracts in points or finite regions between adjacent fuel elements in square and triangle lattices. This is very probable in Advanced Pressurized Water Reactors where the clearance between fuel elements is about 1 mm. This results in partial blocking of the coolant flow and formation of hot spots in the contact regions. In these regions, absence of coolant results in nonuniform clad circumferential temperature distribution. This causes excessive thermal stresses which may produce local melting or clad failure. An accurate prediction of the clad circumferential temperature distribution during these severe incidents is very important. This problem was studied numerically during transient and steady state conditions. Recently, a semi analytical solution for the underlying problem was derived assuming the heat transfer coefficient to vary linearly with the circumferential distance measured from the cusp point, and the heat flux at the fuel-clad interface to be a constant quantity. In the present work, an approximate analytic solution is obtained. The accuracy is tested by solving the problem numerically. Also the problem is reanalyzed by considering the heat flux at the fuel-clad interface to be a power function of the angular distance along the clad surface. Moreover, the heat transfer coefficient is assumed to be a function of both the circumferential coordinate and temperature of the clad. Discussion of the analytical solution and the assumptions are rationalized in the text. 4 figs.

  13. Summer temperature metrics for predicting brook trout (Salvelinus fontinalis) distribution in streams

    Science.gov (United States)

    Parrish, Donna; Butryn, Ryan S.; Rizzo, Donna M.

    2012-01-01

    We developed a methodology to predict brook trout (Salvelinus fontinalis) distribution using summer temperature metrics as predictor variables. Our analysis used long-term fish and hourly water temperature data from the Dog River, Vermont (USA). Commonly used metrics (e.g., mean, maximum, maximum 7-day maximum) tend to smooth the data so information on temperature variation is lost. Therefore, we developed a new set of metrics (called event metrics) to capture temperature variation by describing the frequency, area, duration, and magnitude of events that exceeded a user-defined temperature threshold. We used 16, 18, 20, and 22°C. We built linear discriminant models and tested and compared the event metrics against the commonly used metrics. Correct classification of the observations was 66% with event metrics and 87% with commonly used metrics. However, combined event and commonly used metrics correctly classified 92%. Of the four individual temperature thresholds, it was difficult to assess which threshold had the “best” accuracy. The 16°C threshold had slightly fewer misclassifications; however, the 20°C threshold had the fewest extreme misclassifications. Our method leveraged the volumes of existing long-term data and provided a simple, systematic, and adaptable framework for monitoring changes in fish distribution, specifically in the case of irregular, extreme temperature events.

  14. Prediction of fission mass-yield distributions based on cross section calculations

    International Nuclear Information System (INIS)

    Hambsch, F.-J.; G.Vladuca; Tudora, Anabella; Oberstedt, S.; Ruskov, I.

    2005-01-01

    For the first time, fission mass-yield distributions have been predicted based on an extended statistical model for fission cross section calculations. In this model, the concept of the multi-modality of the fission process has been incorporated. The three most dominant fission modes, the two asymmetric standard I (S1) and standard II (S2) modes and the symmetric superlong (SL) mode are taken into account. De-convoluted fission cross sections for S1, S2 and SL modes for 235,238 U(n, f) and 237 Np(n, f), based on experimental branching ratios, were calculated for the first time in the incident neutron energy range from 0.01 to 5.5 MeV providing good agreement with the experimental fission cross section data. The branching ratios obtained from the modal fission cross section calculations have been used to deduce the corresponding fission yield distributions, including mean values also for incident neutron energies hitherto not accessible to experiment

  15. Prediction of in-phantom dose distribution using in-air neutron beam characteristics for BNCS

    Energy Technology Data Exchange (ETDEWEB)

    Verbeke, Jerome M.

    1999-12-14

    A monoenergetic neutron beam simulation study is carried out to determine the optimal neutron energy range for treatment of rheumatoid arthritis using radiation synovectomy. The goal of the treatment is the ablation of diseased synovial membranes in joints, such as knees and fingers. This study focuses on human knee joints. Two figures-of-merit are used to measure the neutron beam quality, the ratio of the synovium absorbed dose to the skin absorbed dose, and the ratio of the synovium absorbed dose to the bone absorbed dose. It was found that (a) thermal neutron beams are optimal for treatment, (b) similar absorbed dose rates and therapeutic ratios are obtained with monodirectional and isotropic neutron beams. Computation of the dose distribution in a human knee requires the simulation of particle transport from the neutron source to the knee phantom through the moderator. A method was developed to predict the dose distribution in a knee phantom from any neutron and photon beam spectra incident on the knee. This method was revealed to be reasonably accurate and enabled one to reduce by a factor of 10 the particle transport simulation time by modeling the moderator only.

  16. Prediction of in-phantom dose distribution using in-air neutron beam characteristics for BNCS

    International Nuclear Information System (INIS)

    Verbeke, Jerome M.

    1999-01-01

    A monoenergetic neutron beam simulation study is carried out to determine the optimal neutron energy range for treatment of rheumatoid arthritis using radiation synovectomy. The goal of the treatment is the ablation of diseased synovial membranes in joints, such as knees and fingers. This study focuses on human knee joints. Two figures-of-merit are used to measure the neutron beam quality, the ratio of the synovium absorbed dose to the skin absorbed dose, and the ratio of the synovium absorbed dose to the bone absorbed dose. It was found that (a) thermal neutron beams are optimal for treatment, (b) similar absorbed dose rates and therapeutic ratios are obtained with monodirectional and isotropic neutron beams. Computation of the dose distribution in a human knee requires the simulation of particle transport from the neutron source to the knee phantom through the moderator. A method was developed to predict the dose distribution in a knee phantom from any neutron and photon beam spectra incident on the knee. This method was revealed to be reasonably accurate and enabled one to reduce by a factor of 10 the particle transport simulation time by modeling the moderator only

  17. Biology and distribution of chafers (Coleoptera, Scarabaeidae) living in hollow trees in Sweden.

    OpenAIRE

    Nilsson, Sven; Baranowski, Rickard; Hedin, Jonas; Jansson, Niklas; Ranius, Thomas

    2002-01-01

    We review the ecology and distributions of the chafers Liocola marmorata (F.), Gnorimus nobilis (L.) and Gnorimus variabilis (L.) in Sweden based on museum and several large private collections. These species live in hollow deciduous trees, in Sweden especially in oaks. The former and recently documented localities are shown on maps. More than 100 years ago, all the species as well as their habitats were more common in Sweden than today. One problem when interpreting old finds is that hollow ...

  18. Radiation distribution through serpentine concrete using local materials and its application as a reactor biological shield

    International Nuclear Information System (INIS)

    Kansouh, W.A.

    2012-01-01

    Highlights: ► New serpentine concrete was made and examined as a reactor biological shield. ► Ilmenite–limonite concrete is a better reactor biological shield. ► New serpentine concrete is a better reactor fast neutrons shield than ordinary and hematite–serpentine concretes. ► Serpentine concrete has lower properties as a reactor total gamma rays shields. - Abstract: In the present work attempt has been made to estimate the shielding parameters of the new serpentine concrete (density = 2.4 g/cm 3 ) using local materials on the shielding parameters for two types of heat resistant concretes, namely hematite–serpentine (density = 2.5 g/cm 3 ) and ilmenite–limonite (density = 2.9 g/cm 3 ). Shielding parameters for ordinary concrete (density = 2.3 g/cm 3 ) were also discussed. These parameters were determined experimentally for serpentine concrete and compared with previously published values for other concretes, which had also been obtained using local materials. The leakage spectra of reactor fast neutrons and total gamma photon beams from cylindrical samples of these concrete shields were also investigated using a collimated beam from ET-RR-1 reactor. A neutron–gamma spectrometer was used in order to obtain pulse height spectra of reactor fast neutrons and the total gamma rays leakage through the investigated concrete samples. These spectra were utilized to obtain the energy spectra required in these investigations. Removal cross section Σ R (E n ) and linear attenuation coefficient μ(E g ) for reactor fast neutrons and total gamma rays and their relative coefficients were evaluated and presented. Measured results were compared with those previously measured for other concretes. The results show that ilmenite–limonite concrete is a better reactor biological shield than the other three concretes. Serpentine concrete under investigation is a better reactor fast neutrons shield than ordinary and hematite–serpentine concretes. Serpentine concrete

  19. Abdominal fat distribution on computed tomography predicts ureteric calculus fragmentation by shock wave lithotripsy.

    Science.gov (United States)

    Juan, Hsu-Cheng; Lin, Hung-Yu; Chou, Yii-Her; Yang, Yi-Hsin; Shih, Paul Ming-Chen; Chuang, Shu-Mien; Shen, Jung-Tsung; Juan, Yung-Shun

    2012-08-01

    To assess the effects of abdominal fat on shock wave lithotripsy (SWL). We used pre-SWL unenhanced computed tomography (CT) to evaluate the impact of abdominal fat distribution and calculus characteristics on the outcome of SWL. One hundred and eighty-five patients with a solitary ureteric calculus treated with SWL were retrospectively reviewed. Each patient underwent unenhanced CT within 1 month before SWL treatment. Treatment outcomes were evaluated 1 month later. Unenhanced CT parameters, including calculus surface area, Hounsfield unit (HU) density, abdominal fat area and skin to calculus distance (SSD) were analysed. One hundred and twenty-eight of the 185 patients were found to be calculus-free following treatment. HU density, total fat area, visceral fat area and SSD were identified as significant variables on multivariate logistic regression analysis. The receiver-operating characteristic analyses showed that total fat area, para/perirenal fat area and visceral fat area were sensitive predictors of SWL outcomes. This study revealed that higher quantities of abdominal fat, especially visceral fat, are associated with a lower calculus-free rate following SWL treatment. Unenhanced CT is a convenient technique for diagnosing the presence of a calculus, assessing the intra-abdominal fat distribution and thereby helping to predict the outcome of SWL. • Unenhanced CT is now widely used to assess ureteric calculi. • The same CT protocol can provide measurements of abdominal fat distribution. • Ureteric calculi are usually treated by shock wave lithotripsy (SWL). • Greater intra-abdominal fat stores are generally associated with poorer SWL results.

  20. Contribution to biology and distribution studies on some ground beetles species (Coleoptera, Carabidae registered in the Red Data Book of Krasnodarsky Krai

    Directory of Open Access Journals (Sweden)

    Alexander S. Bondarenko

    2017-05-01

    Full Text Available Some biological features and distributional data on seven species of the ground beetles, registered in the Red Data Book of Krasnodarsky Krai, are presented, namely Carabus obtusus, Carabus kaljuzhnyji, Carabus miroshnikovi, Carabus caucasicus, Leistus spinibarbis, Poecilus lyroderus, and Harpalus petri. The results of the field researches, carried out by the authors in 2010–2015, expanded considerably the knowledge of their biological features and regional distribution areas; furthermore, life cycles were reconstructed for four of the above listed species.

  1. Distribution of biologic, anthropogenic, and volcanic constituents as a proxy for sediment transport in the San Francisco Bay Coastal System

    Science.gov (United States)

    McGann, Mary; Erikson, Li H.; Wan, Elmira; Powell, Charles; Maddocks, Rosalie F.; Barnard, P.L.; Jaffee, B.E.; Schoellhamer, D.H.

    2013-01-01

    Although conventional sediment parameters (mean grain size, sorting, and skewness) and provenance have typically been used to infer sediment transport pathways, most freshwater, brackish, and marine environments are also characterized by abundant sediment constituents of biological, and possibly anthropogenic and volcanic, origin that can provide additional insight into local sedimentary processes. The biota will be spatially distributed according to its response to environmental parameters such as water temperature, salinity, dissolved oxygen, organic carbon content, grain size, and intensity of currents and tidal flow, whereas the presence of anthropogenic and volcanic constituents will reflect proximity to source areas and whether they are fluvially- or aerially-transported. Because each of these constituents have a unique environmental signature, they are a more precise proxy for that source area than the conventional sedimentary process indicators. This San Francisco Bay Coastal System study demonstrates that by applying a multi-proxy approach, the primary sites of sediment transport can be identified. Many of these sites are far from where the constituents originated, showing that sediment transport is widespread in the region. Although not often used, identifying and interpreting the distribution of naturally-occurring and allochthonous biologic, anthropogenic, and volcanic sediment constituents is a powerful tool to aid in the investigation of sediment transport pathways in other coastal systems.

  2. Predicting habitat suitability for rare plants at local spatial scales using a species distribution model.

    Science.gov (United States)

    Gogol-Prokurat, Melanie

    2011-01-01

    If species distribution models (SDMs) can rank habitat suitability at a local scale, they may be a valuable conservation planning tool for rare, patchily distributed species. This study assessed the ability of Maxent, an SDM reported to be appropriate for modeling rare species, to rank habitat suitability at a local scale for four edaphic endemic rare plants of gabbroic soils in El Dorado County, California, and examined the effects of grain size, spatial extent, and fine-grain environmental predictors on local-scale model accuracy. Models were developed using species occurrence data mapped on public lands and were evaluated using an independent data set of presence and absence locations on surrounding lands, mimicking a typical conservation-planning scenario that prioritizes potential habitat on unsurveyed lands surrounding known occurrences. Maxent produced models that were successful at discriminating between suitable and unsuitable habitat at the local scale for all four species, and predicted habitat suitability values were proportional to likelihood of occurrence or population abundance for three of four species. Unfortunately, models with the best discrimination (i.e., AUC) were not always the most useful for ranking habitat suitability. The use of independent test data showed metrics that were valuable for evaluating which variables and model choices (e.g., grain, extent) to use in guiding habitat prioritization for conservation of these species. A goodness-of-fit test was used to determine whether habitat suitability values ranked habitat suitability on a continuous scale. If they did not, a minimum acceptable error predicted area criterion was used to determine the threshold for classifying habitat as suitable or unsuitable. I found a trade-off between model extent and the use of fine-grain environmental variables: goodness of fit was improved at larger extents, and fine-grain environmental variables improved local-scale accuracy, but fine-grain variables

  3. Implementation of Complex Biological Logic Circuits Using Spatially Distributed Multicellular Consortia

    Science.gov (United States)

    Urrios, Arturo; de Nadal, Eulàlia; Solé, Ricard; Posas, Francesc

    2016-01-01

    Engineered synthetic biological devices have been designed to perform a variety of functions from sensing molecules and bioremediation to energy production and biomedicine. Notwithstanding, a major limitation of in vivo circuit implementation is the constraint associated to the use of standard methodologies for circuit design. Thus, future success of these devices depends on obtaining circuits with scalable complexity and reusable parts. Here we show how to build complex computational devices using multicellular consortia and space as key computational elements. This spatial modular design grants scalability since its general architecture is independent of the circuit’s complexity, minimizes wiring requirements and allows component reusability with minimal genetic engineering. The potential use of this approach is demonstrated by implementation of complex logical functions with up to six inputs, thus demonstrating the scalability and flexibility of this method. The potential implications of our results are outlined. PMID:26829588

  4. Topographic Metric Predictions of Soil redistribution and Organic Carbon Distribution in Croplands

    Science.gov (United States)

    Mccarty, G.; Li, X.

    2017-12-01

    Landscape topography is a key factor controlling soil redistribution and soil organic carbon (SOC) distribution in Iowa croplands (USA). In this study, we adopted a combined approach based on carbon () and cesium (137Cs) isotope tracers, and digital terrain analysis to understand patterns of SOC redistribution and carbon sequestration dynamics as influenced by landscape topography in tilled cropland under long term corn/soybean management. The fallout radionuclide 137Cs was used to estimate soil redistribution rates and a Lidar-derived DEM was used to obtain a set of topographic metrics for digital terrain analysis. Soil redistribution rates and patterns of SOC distribution were examined across 560 sampling locations at two field sites as well as at larger scale within the watershed. We used δ13C content in SOC to partition C3 and C4 plant derived C density at 127 locations in one of the two field sites with corn being the primary source of C4 C. Topography-based models were developed to simulate SOC distribution and soil redistribution using stepwise ordinary least square regression (SOLSR) and stepwise principal component regression (SPCR). All topography-based models developed through SPCR and SOLSR demonstrated good simulation performance, explaining more than 62% variability in SOC density and soil redistribution rates across two field sites with intensive samplings. However, the SOLSR models showed lower reliability than the SPCR models in predicting SOC density at the watershed scale. Spatial patterns of C3-derived SOC density were highly related to those of SOC density. Topographic metrics exerted substantial influence on C3-derived SOC density with the SPCR model accounting for 76.5% of the spatial variance. In contrast C4 derived SOC density had poor spatial structure likely reflecting the substantial contribution of corn vegetation to recently sequestered SOC density. Results of this study highlighted the utility of topographic SPCR models for scaling

  5. Cognitive Difficulty and Format of Exams Predicts Gender and Socioeconomic Gaps in Exam Performance of Students in Introductory Biology Courses.

    Science.gov (United States)

    Wright, Christian D; Eddy, Sarah L; Wenderoth, Mary Pat; Abshire, Elizabeth; Blankenbiller, Margaret; Brownell, Sara E

    2016-01-01

    Recent reform efforts in undergraduate biology have recommended transforming course exams to test at more cognitively challenging levels, which may mean including more cognitively challenging and more constructed-response questions on assessments. However, changing the characteristics of exams could result in bias against historically underserved groups. In this study, we examined whether and to what extent the characteristics of instructor-generated tests impact the exam performance of male and female and middle/high- and low-socioeconomic status (SES) students enrolled in introductory biology courses. We collected exam scores for 4810 students from 87 unique exams taken across 3 yr of the introductory biology series at a large research university. We determined the median Bloom's level and the percentage of constructed-response questions for each exam. Despite controlling for prior academic ability in our models, we found that males and middle/high-SES students were disproportionately favored as the Bloom's level of exams increased. Additionally, middle/high-SES students were favored as the proportion of constructed-response questions on exams increased. Given that we controlled for prior academic ability, our findings do not likely reflect differences in academic ability level. We discuss possible explanations for our findings and how they might impact how we assess our students. © 2016 C. D. Wright, S. L. Eddy, et al. CBE—Life Sciences Education © 2016 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

  6. SBSI: an extensible distributed software infrastructure for parameter estimation in systems biology.

    Science.gov (United States)

    Adams, Richard; Clark, Allan; Yamaguchi, Azusa; Hanlon, Neil; Tsorman, Nikos; Ali, Shakir; Lebedeva, Galina; Goltsov, Alexey; Sorokin, Anatoly; Akman, Ozgur E; Troein, Carl; Millar, Andrew J; Goryanin, Igor; Gilmore, Stephen

    2013-03-01

    Complex computational experiments in Systems Biology, such as fitting model parameters to experimental data, can be challenging to perform. Not only do they frequently require a high level of computational power, but the software needed to run the experiment needs to be usable by scientists with varying levels of computational expertise, and modellers need to be able to obtain up-to-date experimental data resources easily. We have developed a software suite, the Systems Biology Software Infrastructure (SBSI), to facilitate the parameter-fitting process. SBSI is a modular software suite composed of three major components: SBSINumerics, a high-performance library containing parallelized algorithms for performing parameter fitting; SBSIDispatcher, a middleware application to track experiments and submit jobs to back-end servers; and SBSIVisual, an extensible client application used to configure optimization experiments and view results. Furthermore, we have created a plugin infrastructure to enable project-specific modules to be easily installed. Plugin developers can take advantage of the existing user-interface and application framework to customize SBSI for their own uses, facilitated by SBSI's use of standard data formats. All SBSI binaries and source-code are freely available from http://sourceforge.net/projects/sbsi under an Apache 2 open-source license. The server-side SBSINumerics runs on any Unix-based operating system; both SBSIVisual and SBSIDispatcher are written in Java and are platform independent, allowing use on Windows, Linux and Mac OS X. The SBSI project website at http://www.sbsi.ed.ac.uk provides documentation and tutorials.

  7. Predicting the distribution of Endophyllum osteospermi (Uredinales, Pucciniaceae) in Australia based on its climatic requirements and distribution in South Africa

    NARCIS (Netherlands)

    Wood, A.R.; Crous, P.W.; Lennox, C.L.

    2004-01-01

    The perennial bush Chrysanthemoides monilifera ssp. monilifera (Asteraceae) is infected by the autoecious, microcyclic rust fungus Endophyllum osteospermi. Both organisms are native to South Africa, whilst the plant has also become naturalised in Australia where it is the target of a biological

  8. Translating crustacean biological responses from CO2 bubbling experiments into population-level predictions

    Science.gov (United States)

    Many studies of animal responses to ocean acidification focus on uniformly conditioned age cohorts that lack complexities typically found in wild populations. These studies have become the primary data source for predicting higher level ecological effects, but the roles of intras...

  9. Effect of foam on temperature prediction and heat recovery potential from biological wastewater treatment.

    Science.gov (United States)

    Corbala-Robles, L; Volcke, E I P; Samijn, A; Ronsse, F; Pieters, J G

    2016-05-15

    Heat is an important resource in wastewater treatment plants (WWTPs) which can be recovered. A prerequisite to determine the theoretical heat recovery potential is an accurate heat balance model for temperature prediction. The insulating effect of foam present on the basin surface and its influence on temperature prediction were assessed in this study. Experiments were carried out to characterize the foam layer and its insulating properties. A refined dynamic temperature prediction model, taking into account the effect of foam, was set up. Simulation studies for a WWTP treating highly concentrated (manure) wastewater revealed that the foam layer had a significant effect on temperature prediction (3.8 ± 0.7 K over the year) and thus on the theoretical heat recovery potential (30% reduction when foam is not considered). Seasonal effects on the individual heat losses and heat gains were assessed. Additionally, the effects of the critical basin temperature above which heat is recovered, foam thickness, surface evaporation rate reduction and the non-absorbed solar radiation on the theoretical heat recovery potential were evaluated. Copyright © 2016 Elsevier Ltd. All rights reserved.

  10. The Nature and Use of Prediction Skills in a Biological Computer Simulation.

    Science.gov (United States)

    Lavoie, Derrick R.; Good, Ron

    1988-01-01

    Describes mechanisms of thought associated with making predictions. Concludes that successful predictors had high initial knowledge of the subject matter and were formally operational. Unsuccessful predictors had low initial knowledge and were concretely operational. Systematic manipulation, note taking, and higher-level thinking skills were…

  11. Evaluating and Predicting the Effectiveness of Green Infrastructure on a Small Watershed Scale - Emphasis on Water Quality, Flow, Thermal Regime, Substrate Integrity, and Biological Condition

    Science.gov (United States)

    Assessments of the effectiveness of stormwater best management practices (BMPs) have focused on measurement of load or concentration reductions, which can be translated to predict biological impacts based on chemical water quality criteria. However, many of the impacts of develo...

  12. The StreamCat Dataset: Accumulated Attributes for NHDPlusV2 Catchments (Version 2.1) for the Conterminous United States: Predicted Biological Condition

    Data.gov (United States)

    U.S. Environmental Protection Agency — This dataset consists of predicted probabilities of good biological condition based in the US EPA 2008/2009 National Rivers and Streams Assessment (NRSA). NRSA...

  13. A microbiology-based multi-parametric approach towards assessing biological stability in drinking water distribution networks.

    Science.gov (United States)

    Lautenschlager, Karin; Hwang, Chiachi; Liu, Wen-Tso; Boon, Nico; Köster, Oliver; Vrouwenvelder, Hans; Egli, Thomas; Hammes, Frederik

    2013-06-01

    Biological stability of drinking water implies that the concentration of bacterial cells and composition of the microbial community should not change during distribution. In this study, we used a multi-parametric approach that encompasses different aspects of microbial water quality including microbial growth potential, microbial abundance, and microbial community composition, to monitor biological stability in drinking water of the non-chlorinated distribution system of Zürich. Drinking water was collected directly after treatment from the reservoir and in the network at several locations with varied average hydraulic retention times (6-52 h) over a period of four months, with a single repetition two years later. Total cell concentrations (TCC) measured with flow cytometry remained remarkably stable at 9.5 (± 0.6) × 10(4) cells/ml from water in the reservoir throughout most of the distribution network, and during the whole time period. Conventional microbial methods like heterotrophic plate counts, the concentration of adenosine tri-phosphate, total organic carbon and assimilable organic carbon remained also constant. Samples taken two years apart showed more than 80% similarity for the microbial communities analysed with denaturing gradient gel electrophoresis and 454 pyrosequencing. Only the two sampling locations with the longest water retention times were the exceptions and, so far for unknown reasons, recorded a slight but significantly higher TCC (1.3 (± 0.1) × 10(5) cells/ml) compared to the other locations. This small change in microbial abundance detected by flow cytometry was also clearly observed in a shift in the microbial community profiles to a higher abundance of members from the Comamonadaceae (60% vs. 2% at other locations). Conventional microbial detection methods were not able to detect changes as observed with flow cytometric cell counts and microbial community analysis. Our findings demonstrate that the multi-parametric approach used

  14. Comparison of modeling methods to predict the spatial distribution of deep-sea coral and sponge in the Gulf of Alaska

    Science.gov (United States)

    Rooper, Christopher N.; Zimmermann, Mark; Prescott, Megan M.

    2017-08-01

    biological theory. For data with highly zero-inflated distributions and non-normal distributions such as the abundance data from this study, the tree-based methods performed better. Ensemble models that averaged predictions across the four model types, performed better than the GLM or GAM models but slightly poorer than the tree-based methods, suggesting ensemble models might be more robust to overfitting than tree methods, while mitigating some of the disadvantages in predictive performance of regression methods.

  15. Distributional changes and range predictions of downy brome (Bromus tectorum) in Rocky Mountain National Park

    Science.gov (United States)

    Bromberg, J.E.; Kumar, S.; Brown, C.S.; Stohlgren, T.J.

    2011-01-01

    Downy brome (Bromus tectorum L.), an invasive winter annual grass, may be increasing in extent and abundance at high elevations in the western United States. This would pose a great threat to high-elevation plant communities and resources. However, data to track this species in high-elevation environments are limited. To address changes in the distribution and abundance of downy brome and the factors most associated with its occurrence, we used field sampling and statistical methods, and niche modeling. In 2007, we resampled plots from two vegetation surveys in Rocky Mountain National Park for presence and cover of downy brome. One survey was established in 1993 and had been resampled in 1999. The other survey was established in 1996 and had not been resampled until our study. Although not all comparisons between years demonstrated significant changes in downy brome abundance, its mean cover increased nearly fivefold from 1993 (0.7%) to 2007 (3.6%) in one of the two vegetation surveys (P = 0.06). Although the average cover of downy brome within the second survey appeared to be increasing from 1996 to 2007, this slight change from 0.5% to 1.2% was not statistically significant (P = 0.24). Downy brome was present in 50% more plots in 1999 than in 1993 (P = 0.02) in the first survey. In the second survey, downy brome was present in 30% more plots in 2007 than in 1996 (P = 0.08). Maxent, a species-environmental matching model, was generally able to predict occurrences of downy brome, as new locations were in the ranges predicted by earlier generated models. The model found that distance to roads, elevation, and vegetation community influenced the predictions most. The strong response of downy brome to interannual environmental variability makes detecting change challenging, especially with small sample sizes. However, our results suggest that the area in which downy brome occurs is likely increasing in Rocky Mountain National Park through increased frequency and cover

  16. Predicting habitat distribution to conserve seagrass threatened by sea level rise

    Science.gov (United States)

    Saunders, M. I.; Baldock, T.; Brown, C. J.; Callaghan, D. P.; Golshani, A.; Hamylton, S.; Hoegh-guldberg, O.; Leon, J. X.; Lovelock, C. E.; Lyons, M. B.; O'Brien, K.; Mumby, P.; Phinn, S. R.; Roelfsema, C. M.

    2013-12-01

    Sea level rise (SLR) over the 21st century will cause significant redistribution of valuable coastal habitats. Seagrasses form extensive and highly productive meadows in shallow coastal seas support high biodiversity, including economically valuable and threatened species. Predictive habitat models can inform local management actions that will be required to conserve seagrass faced with multiple stressors. We developed novel modelling approaches, based on extensive field data sets, to examine the effects of sea level rise and other stressors on two representative seagrass habitats in Australia. First, we modelled interactive effects of SLR, water clarity and adjacent land use on estuarine seagrass meadows in Moreton Bay, Southeast Queensland. The extent of suitable seagrass habitat was predicted to decline by 17% by 2100 due to SLR alone, but losses were predicted to be significantly reduced through improvements in water quality (Fig 1a) and by allowing space for seagrass migration with inundation. The rate of sedimentation in seagrass strongly affected the area of suitable habitat for seagrass in sea level rise scenarios (Fig 1b). Further research to understand spatial, temporal and environmental variability of sediment accretion in seagrass is required. Second, we modelled changes in wave energy distribution due to predicted SLR in a linked coral reef and seagrass ecosystem at Lizard Island, Great Barrier Reef. Scenarios where the water depth over the coral reef deepened due to SLR and minimal reef accretion, resulted in larger waves propagating shoreward, changing the existing hydrodynamic conditions sufficiently to reduce area of suitable habitat for seagrass. In a scenario where accretion of the coral reef was severely compromised (e.g. warming, acidification, overfishing), the probability of the presence of seagrass declined significantly. Management to maintain coral health will therefore also benefit seagrasses subject to SLR in reef environments. Further

  17. Prediction of hepatocellular carcinoma biological behavior in patient selection for liver transplantation

    Science.gov (United States)

    Cillo, Umberto; Giuliani, Tommaso; Polacco, Marina; Herrero Manley, Luz Maria; Crivellari, Gino; Vitale, Alessandro

    2016-01-01

    Morphological criteria have always been considered the benchmark for selecting hepatocellular carcinoma (HCC) patients for liver transplantation (LT). These criteria, which are often inappropriate to express the tumor’s biological behavior and aggressiveness, offer only a static view of the disease burden and are frequently unable to correctly stratify the tumor recurrence risk after LT. Alpha-fetoprotein (AFP) and its progression as well as AFP-mRNA, AFP-L3%, des-γ-carboxyprothrombin, inflammatory markers and other serological tests appear to be correlated with post-transplant outcomes. Several other markers for patient selection including functional imaging studies such as 18F-FDG-PET imaging, histological evaluation of tumor grade, tissue-specific biomarkers, and molecular signatures have been outlined in the literature. HCC growth rate and response to pre-transplant therapies can further contribute to the transplant evaluation process of HCC patients. While AFP, its progression, and HCC response to pre-transplant therapy have already been used as a part of an integrated prognostic model for selecting patients, the utility of other markers in the transplant setting is still under investigation. This article intends to review the data in the literature concerning predictors that could be included in an integrated LT selection model and to evaluate the importance of biological aggressiveness in the evaluation process of these patients. PMID:26755873

  18. The role of genomics in the identification, prediction, and prevention of biological threats.

    Directory of Open Access Journals (Sweden)

    W Florian Fricke

    2009-10-01

    Full Text Available In all likelihood, it is only a matter of time before our public health system will face a major biological threat, whether intentionally dispersed or originating from a known or newly emerging infectious disease. It is necessary not only to increase our reactive "biodefense," but also to be proactive and increase our preparedness. To achieve this goal, it is essential that the scientific and public health communities fully embrace the genomic revolution, and that novel bioinformatic and computing tools necessary to make great strides in our understanding of these novel and emerging threats be developed. Genomics has graduated from a specialized field of science to a research tool that soon will be routine in research laboratories and clinical settings. Because the technology is becoming more affordable, genomics can and should be used proactively to build our preparedness and responsiveness to biological threats. All pieces, including major continued funding, advances in next-generation sequencing technologies, bioinformatics infrastructures, and open access to data and metadata, are being set in place for genomics to play a central role in our public health system.

  19. Distribution and Diversity of Organic and Biological Signatures in Soils From the Atacama Desert

    Science.gov (United States)

    Sharma, Aditi

    2005-01-01

    The Atacama Desert is amongst the driest places on Earth. It is considered to be a suitable analog for the Martian surface in which to conduct studies of life and life detection. Soil samples were collected in June 2005 from the Atacama Desert and analyzed in the lab for amino acid content. HPLC was the primary tool used to analyze samples. The amino acids of interest are aspartic acid, serine, glutamic acid, glycine, and alanine. D and L isomers of each amino acid (except for glycine) were separated through HPLC. The purpose of this study is to find correlations between location of the sample collection sites and amino acid content as well as D/L isomer ratios in order to formulate theories of how different types of environments may affect the abundance and distribution of life forms. Initial analysis of data shows a general lack of or slight correlation between location and amino acid content. Some data appears to contradict the hypothesis that harsher environments would have lower amino acid content than less harsh environments. Further analysis of data is needed to come up with a more conclusive report of the distribution of amino acids in the Atacama Desert.

  20. Predicting the distribution of Stipa purpurea across the Tibetan Plateau via the MaxEnt model.

    Science.gov (United States)

    Ma, Baibing; Sun, Jian

    2018-02-21

    The ecosystems across Tibetan Plateau are changing rapidly under the influence of climate warming, which has caused substantial changes in spatial and temporal environmental patterns. Stipa purpurea, as a dominant herbsage resource in alpine steppe, has a great influence on animal husbandry in the Tibetan Plateau. Global warming has been forecasted to continue in the future (2050s, 2070s), questioning the future distribution of S. purpurea and its response to climate change. The maximum entropy (MaxEnt) modeling, due to its multiple advantages (e.g. uses presence-only data, performs well with incomplete data, and requires small sample sizes and gaps), has been used to understand species environment relationships and predict species distributions across locations that have not been sampled. Annual mean temperature, annual precipitation, temperature seasonality, altitude, and precipitation during the driest month, significantly affected the distribution of S. purpurea. Only 0.70% of the Tibetan Plateau area included a very highly suitable habitat (habitat suitability [HS] = 0.8-1.0). Highly suitable habitat (HS = 0.6-0.8), moderately suitable habitat (HS = 0.4-0.6), and unsuitable habitat (HS = 0.2-0.4) occupied 6.20, 14.30 and 22.40% of the Tibetan Plateau area, respectively, and the majority (56.40%) of the Tibetan Plateau area constituted a highly unsuitable habitat (HS = 0-0.2). In addition, the response curves of species ecological suitability simulated by generalized additive model nearly corresponded with the response curves generated by the MaxEnt model. At a temporal scale, the habitat suitability of S. purpurea tends to increase from the 1990s to 2050s, but decline from the 2050s to 2070s. At a spatial scale, the future distribution of S. purpurea will not exhibit sweeping changes and will remain in the central and southeastern regions of the Tibetan Plateau. These results benefit the local animal husbandry and provide evidence for establishing

  1. Predicting bottlenose dolphin distribution along Liguria coast (northwestern Mediterranean Sea) through different modeling techniques and indirect predictors.

    Science.gov (United States)

    Marini, C; Fossa, F; Paoli, C; Bellingeri, M; Gnone, G; Vassallo, P

    2015-03-01

    Habitat modeling is an important tool to investigate the quality of the habitat for a species within a certain area, to predict species distribution and to understand the ecological processes behind it. Many species have been investigated by means of habitat modeling techniques mainly to address effective management and protection policies and cetaceans play an important role in this context. The bottlenose dolphin (Tursiops truncatus) has been investigated with habitat modeling techniques since 1997. The objectives of this work were to predict the distribution of bottlenose dolphin in a coastal area through the use of static morphological features and to compare the prediction performances of three different modeling techniques: Generalized Linear Model (GLM), Generalized Additive Model (GAM) and Random Forest (RF). Four static variables were tested: depth, bottom slope, distance from 100 m bathymetric contour and distance from coast. RF revealed itself both the most accurate and the most precise modeling technique with very high distribution probabilities predicted in presence cells (90.4% of mean predicted probabilities) and with 66.7% of presence cells with a predicted probability comprised between 90% and 100%. The bottlenose distribution obtained with RF allowed the identification of specific areas with particularly high presence probability along the coastal zone; the recognition of these core areas may be the starting point to develop effective management practices to improve T. truncatus protection. Copyright © 2014 Elsevier Ltd. All rights reserved.

  2. Predicting Student Success in a Major's Introductory Biology Course via Logistic Regression Analysis of Scientific Reasoning Ability and Mathematics Scores

    Science.gov (United States)

    Thompson, E. David; Bowling, Bethany V.; Markle, Ross E.

    2018-02-01

    Studies over the last 30 years have considered various factors related to student success in introductory biology courses. While much of the available literature suggests that the best predictors of success in a college course are prior college grade point average (GPA) and class attendance, faculty often require a valuable predictor of success in those courses wherein the majority of students are in the first semester and have no previous record of college GPA or attendance. In this study, we evaluated the efficacy of the ACT Mathematics subject exam and Lawson's Classroom Test of Scientific Reasoning in predicting success in a major's introductory biology course. A logistic regression was utilized to determine the effectiveness of a combination of scientific reasoning (SR) scores and ACT math (ACT-M) scores to predict student success. In summary, we found that the model—with both SR and ACT-M as significant predictors—could be an effective predictor of student success and thus could potentially be useful in practical decision making for the course, such as directing students to support services at an early point in the semester.

  3. Genomic prediction unifies animal and plant breeding programs to form platforms for biological discovery

    OpenAIRE

    Hickey, John M; Chiurugwi, Tinashe; Mackay, Ian; Powell, Wayne; Implementing Genomic Selection in CGIAR Breeding Programs Workshop Participants

    2017-01-01

    The rate of annual yield increases for major staple crops must more than double relative to current levels in order to feed a predicted global population of 9 billion by 2050. Controlled hybridization and selective breeding have been used for centuries to adapt plant and animal species for human use. However, achieving higher, sustainable rates of improvement in yields in various species will require renewed genetic interventions and dramatic improvement of agricultural practices. Genomic pre...

  4. Extending and Applying Spartan to Perform Temporal Sensitivity Analyses for Predicting Changes in Influential Biological Pathways in Computational Models.

    Science.gov (United States)

    Alden, Kieran; Timmis, Jon; Andrews, Paul S; Veiga-Fernandes, Henrique; Coles, Mark

    2017-01-01

    Through integrating real time imaging, computational modelling, and statistical analysis approaches, previous work has suggested that the induction of and response to cell adhesion factors is the key initiating pathway in early lymphoid tissue development, in contrast to the previously accepted view that the process is triggered by chemokine mediated cell recruitment. These model derived hypotheses were developed using spartan, an open-source sensitivity analysis toolkit designed to establish and understand the relationship between a computational model and the biological system that model captures. Here, we extend the functionality available in spartan to permit the production of statistical analyses that contrast the behavior exhibited by a computational model at various simulated time-points, enabling a temporal analysis that could suggest whether the influence of biological mechanisms changes over time. We exemplify this extended functionality by using the computational model of lymphoid tissue development as a time-lapse tool. By generating results at twelve- hour intervals, we show how the extensions to spartan have been used to suggest that lymphoid tissue development could be biphasic, and predict the time-point when a switch in the influence of biological mechanisms might occur.

  5. When theory and biology differ: The relationship between reward prediction errors and expectancy.

    Science.gov (United States)

    Williams, Chad C; Hassall, Cameron D; Trska, Robert; Holroyd, Clay B; Krigolson, Olave E

    2017-10-01

    Comparisons between expectations and outcomes are critical for learning. Termed prediction errors, the violations of expectancy that occur when outcomes differ from expectations are used to modify value and shape behaviour. In the present study, we examined how a wide range of expectancy violations impacted neural signals associated with feedback processing. Participants performed a time estimation task in which they had to guess the duration of one second while their electroencephalogram was recorded. In a key manipulation, we varied task difficulty across the experiment to create a range of different feedback expectancies - reward feedback was either very expected, expected, 50/50, unexpected, or very unexpected. As predicted, the amplitude of the reward positivity, a component of the human event-related brain potential associated with feedback processing, scaled inversely with expectancy (e.g., unexpected feedback yielded a larger reward positivity than expected feedback). Interestingly, the scaling of the reward positivity to outcome expectancy was not linear as would be predicted by some theoretical models. Specifically, we found that the amplitude of the reward positivity was about equivalent for very expected and expected feedback, and for very unexpected and unexpected feedback. As such, our results demonstrate a sigmoidal relationship between reward expectancy and the amplitude of the reward positivity, with interesting implications for theories of reinforcement learning. Copyright © 2017 Elsevier B.V. All rights reserved.

  6. Controlled destruction and temperature distributions in biological tissues subjected to monoactive electrocoagulation.

    Science.gov (United States)

    Erez, A; Shitzer, A

    1980-02-01

    An analysis of the temperature fields developed in a biological tissue undergoing a monoactive electrical coagulating process is presented, including thermal recovery following prolonged heating. The analysis is performed for the passage of alternating current and assumes a homogeneous and isotropic tissue model which is uniformly perfused by blood at arterial temperature. Solution for the one-dimensional spherical geometry is obtained by a Laplace transform and numerical integrations. Results obtained indicate the major role which blood perfusion plays in determining the effects of the coagulating process; tissue temperatures and depth of destruction are drastically reduced as blood perfusion increases. Metabolic heat generation rate is found to have negligible effects on tissue temperatures whereas electrode thermal inertia affects temperature levels appreciably. However, electrodes employed in practice would have a low thermal inertia which might be regarded as zero for all practical purposes. It is also found that the depth of tissue destruction is almost directly proportional to the electrical power and duration of application. To avoid excessively high temperatures and charring, it would be advantageous to reduce power and increase the time of application. Results of this study should be regarded as a first approximation to the rather complex phenomena associated with electrocoagulation. They may, nevertheless, serve as preliminary guidelines to practicing surgeons applying this technique.

  7. Biological marker distribution in coexisting kerogen, bitumen and asphaltenes in Monterey Formation diatomite, California

    Science.gov (United States)

    Tannenbaum, E.; Ruth, E.; Huizinga, B. J.; Kaplan, I. R.

    1986-01-01

    Organic-rich (18.2%) Monterey Formation diatomite from California was studied. The organic matter consist of 94% bitumen and 6% kerogen. Biological markers from the bitumen and from pyrolysates of the coexisting asphaltenes and kerogen were analyzed in order to elucidate the relationship between the various fractions of the organic matter. While 17 alpha(H), 18 alpha(H), 21 alpha(H)-28,30-bisnorhopane was present in the bitumen and in the pryolysate of the asphaltenes, it was not detected in the pyrolysates of the kerogen. A C40-isoprenoid with "head to head" linkage, however, was present in pyrolysates of both kerogen and asphaltenes, but not in the bitumen from the diatomite. The maturation level of the bitumen, based on the extent of isomerization of steranes and hopanes, was that of a mature oil, whereas the pyrolysate from the kerogen showed a considerably lower maturation level. These relationships indicate that the bitumen may not be indigenous to the diatomite and that it is a mature oil that migrated into the rock. We consider the possibility, however, that some of the 28,30-bisnorhopane-rich Monterey Formation oils have not been generated through thermal degradation of kerogen, but have been expelled from the source rock at an early stage of diagenesis.

  8. Enantiomeric Distribution of Some Linalool Containing Essential Oils and Their Biological Activities

    Directory of Open Access Journals (Sweden)

    K. Hüsnü Can Başer

    2010-10-01

    Full Text Available The enantiomeric composition of linalool was determined in 42 essential oils using chiral columns. Essential oils were analyzed by multidimentional gas chromatography-mass spectrometry using a non-chiral and chiral FSC columns combination with modified g -cyclodextrine (Lipodex E as the chiral stationary phase without previous isolation of the compound from the mixture. The essential oils of Achillea, Ballota, Calamintha, Micromeria, Hedychium, Tanacetum, Coriandrum, Xanthoxylum, Ocimum, Thymus, Lavandula, Elettaria, Cinnamomum, Salvia, Origanum, Satureja, Nepeta, Stachys were used as source material for enantiomeric separation of linalool. Enantiomeric distribution of linalool showed (--linalool was much more common than the (+-linalool in the essential oils in this study. (-- and (+-linalool enantiomers were evaluated for antimicrobial, antifungal and antimalarial activities. Both enantiomers demonstrated approximately 50% growth inhibition of Botrytis cinerea at 48 hrs.

  9. Modalities of gene action predicted by the classical evolutionary biological theory of aging.

    Science.gov (United States)

    Martin, George M

    2007-04-01

    What might now be referred to as the "classical" evolutionary biological theory of why we age has had a number of serious challenges in recent years. While the theory might therefore have to be modified under certain circumstances, in the author's opinion, it still provides the soundest theoretical basis for thinking about how we age. Nine modalities of gene action that have the potential to modulate processes of aging are reviewed, including the two most widely reviewed and accepted concepts ("antagonistic pleiotropy" and "mutation accumulation"). While several of these nine mechanisms can be regarded as derivatives of the antagonistic pleiotropic concept, they frame more specific questions for future research. Such research should pursue what appears to be the dominant factor in the determination of intraspecific variations in longevity-stochastic mechanisms, most likely based upon epigenetics. This contrasts with the dominant factor in the determination of interspecific variations in longevity-the constitutional genome, most likely based upon variations in regulatory loci.

  10. Kmerind: A Flexible Parallel Library for K-mer Indexing of Biological Sequences on Distributed Memory Systems.

    Science.gov (United States)

    Pan, Tony; Flick, Patrick; Jain, Chirag; Liu, Yongchao; Aluru, Srinivas

    2017-10-09

    Counting and indexing fixed length substrings, or k-mers, in biological sequences is a key step in many bioinformatics tasks including genome alignment and mapping, genome assembly, and error correction. While advances in next generation sequencing technologies have dramatically reduced the cost and improved latency and throughput, few bioinformatics tools can efficiently process the datasets at the current generation rate of 1.8 terabases every 3 days. We present Kmerind, a high performance parallel k-mer indexing library for distributed memory environments. The Kmerind library provides a set of simple and consistent APIs with sequential semantics and parallel implementations that are designed to be flexible and extensible. Kmerind's k-mer counter performs similarly or better than the best existing k-mer counting tools even on shared memory systems. In a distributed memory environment, Kmerind counts k-mers in a 120 GB sequence read dataset in less than 13 seconds on 1024 Xeon CPU cores, and fully indexes their positions in approximately 17 seconds. Querying for 1% of the k-mers in these indices can be completed in 0.23 seconds and 28 seconds, respectively. Kmerind is the first k-mer indexing library for distributed memory environments, and the first extensible library for general k-mer indexing and counting. Kmerind is available at https://github.com/ParBLiSS/kmerind.

  11. Detection methods predict differences in biology and survival in breast cancer patients

    International Nuclear Information System (INIS)

    Redondo, Maximino; Pereda, Teresa; Domingo, Laia; Morales-Suarez Varela, María; Sala, Maria; Rueda, Antonio; Funez, Rafael; Medina-Cano, Francisco; Rodrigo, Isabel; Acebal, Mercedes; Tellez, Teresa; Roldan, M Jose; Hortas, M Luisa; Bellinvia, Ana

    2012-01-01

    The aim of this study was to measure the biological characteristics involved in tumorigenesis and the progression of breast cancer in symptomatic and screen-detected carcinomas to identify possible differences. For this purpose, we evaluated clinical-pathological parameters and proliferative and apoptotic activities in a series of 130 symptomatic and 161 screen-detected tumors. After adjustment for the smaller size of the screen-detected carcinomas compared with symptomatic cancers, those detected in the screening program presented longer disease-free survival (RR = 0.43, CI = 0.19-0.96) and had high estrogen and progesterone receptor concentrations more often than did symptomatic cancers (OR = 3.38, CI = 1.72-6.63 and OR = 3.44, CI = 1.94-6.10, respectively). Furthermore, the expression of bcl-2, a marker of good prognosis in breast cancer, was higher and HER2/neu expression was lower in screen-detected cancers than in symptomatic cancers (OR = 1.77, CI = 1.01-3.23 and OR = 0.64, CI = 0.40-0.98, respectively). However, when comparing prevalent vs incident screen-detected carcinomas, prevalent tumors were larger (OR = 2.84, CI = 1.05-7.69), were less likely to be HER2/neu positive (OR = 0.22, CI = 0.08-0.61) and presented lower Ki67 expression (OR = 0.36, CI = 0.17-0.77). In addition, incident tumors presented a shorter survival time than did prevalent ones (RR = 4.88, CI = 1.12-21.19). Incident carcinomas include a variety of screen-detected carcinomas that exhibit differences in biology and prognosis relative to prevalent carcinomas. The detection method is important and should be taken into account when making therapy decisions

  12. Moving the Hazard Prediction and Assessment Capability to a Distributed, Portable Architecture

    Energy Technology Data Exchange (ETDEWEB)

    Lee, RW

    2002-09-05

    The Hazard Prediction and Assessment Capability (HPAC) has been re-engineered from a Windows application with tight binding between computation and a graphical user interface (GUI) to a new distributed object architecture. The key goals of this new architecture are platform portability, extensibility, deployment flexibility, client-server operations, easy integration with other systems, and support for a new map-based GUI. Selection of Java as the development and runtime environment is the major factor in achieving each of the goals, platform portability in particular. Portability is further enforced by allowing only Java components in the client. Extensibility is achieved via Java's dynamic binding and class loading capabilities and a design by interface approach. HPAC supports deployment on a standalone host, as a heavy client in client-server mode with data stored on the client but calculations performed on the server host, and as a thin client with data and calculations on the server host. The principle architectural element supporting deployment flexibility is the use of Universal Resource Locators (URLs) for all file references. Java WebStart{trademark} is used for thin client deployment. Although there were many choices for the object distribution mechanism, the Common Object Request Broker Architecture (CORBA) was chosen to support HPAC client server operation. HPAC complies with version 2.0 of the CORBA standard and does not assume support for pass-by-value method arguments. Execution in standalone mode is expedited by having most server objects run in the same process as client objects, thereby bypassing CORBA object transport. HPAC provides four levels for access by other tools and systems, starting with a Windows library providing transport and dispersion (T&D) calculations and output generation, detailed and more abstract sets of CORBA services, and reusable Java components.

  13. Predicting breeding shorebird distributions on the Arctic Coastal Plain of Alaska

    Science.gov (United States)

    Saalfeld, Sarah T.; Lanctot, Richard B.; Brown, Stephen C.; Saalfeld, David T.; Johnson, James A.; Andres, Brad A.; Bart, Jonathan R.

    2013-01-01

    The Arctic Coastal Plain (ACP) of Alaska is an important region for millions of migrating and nesting shorebirds. However, this region is threatened by climate change and increased human development (e.g., oil and gas production) that have the potential to greatly impact shorebird populations and breeding habitat in the near future. Because historic data on shorebird distributions in the ACP are very coarse and incomplete, we sought to develop detailed, contemporary distribution maps so that the potential impacts of climate-mediated changes and development could be ascertained. To do this, we developed and mapped habitat suitability indices for eight species of shorebirds (Black-bellied Plover [Pluvialis squatarola], American Golden-Plover [Pluvialis dominica], Semipalmated Sandpiper [Calidris pusilla], Pectoral Sandpiper [Calidris melanotos], Dunlin [Calidris alpina], Long-billed Dowitcher [Limnodromus scolopaceus], Red-necked Phalarope [Phalaropus lobatus], and Red Phalarope [Phalaropus fulicarius]) that commonly breed within the ACP of Alaska. These habitat suitability models were based on 767 plots surveyed during nine years between 1998 and 2008 (surveys were not conducted in 2003 and 2005), using single-visit rapid area searches during territory establishment and incubation (8 June, 1 July). Sp