Prediction of the oscillator strengths for the electric dipole transitions in Th II

Energy Technology Data Exchange (ETDEWEB)

Dembczynski, Jerzy [Institute of Control and Information Engineering, Faculty of Electrical Engineering, Poznan University of Technology, Piotrowo 3A, 60-965 Poznan (Poland); Ruczkowski, Jaroslaw; Elantkowska, Magdalena [Laboratory of Quantum Engineering and Metrology, Faculty of Technical Physics, Poznan University of Technology, Nieszawska 13B, 60-965 Poznan (Poland)

2014-07-01

In order to parametrize the oscillator strength, the matrix of angular coefficients of the possible transitions in multiconfiguration system were calculated. In the odd and even configuration systems, the fine structure eigenvectors for both parities were obtained, using our semiempirical method, which taken into account also the second order effects, resulting from the excitations from electronic closed shells to open shells and from open shells to empty shell. The correctness of the fine structure wave functions was verified by the comparison of calculated and experimental hyperfine structure constants for Th II available in the literature. The least square fit to experimental values for some transitions allow to obtain the values of radial parameters and predict the oscillator strengths values for all possible transitions from the levels under consideration. These calculations are necessary for the design of the nuclear frequency standard based on the thorium ion.

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.

Predicting landscape vegetation dynamics using state-and-transition simulation models

Science.gov (United States)

Colin J. Daniel; Leonardo. Frid

2012-01-01

This paper outlines how state-and-transition simulation models (STSMs) can be used to project changes in vegetation over time across a landscape. STSMs are stochastic, empirical simulation models that use an adapted Markov chain approach to predict how vegetation will transition between states over time, typically in response to interactions between succession,...

Transition Prediction in Hypersonic Boundary Layers Using Receptivity and Freestream Spectra

Science.gov (United States)

Balakumar, P.; Chou, Amanda

2016-01-01

Boundary-layer transition in hypersonic flows over a straight cone can be predicted using measured freestream spectra, receptivity, and threshold values for the wall pressure fluctuations at the transition onset points. Simulations are performed for hypersonic boundary-layer flows over a 7-degree half-angle straight cone with varying bluntness at a freestream Mach number of 10. The steady and the unsteady flow fields are obtained by solving the two-dimensional Navier-Stokes equations in axisymmetric coordinates using a 5th-order accurate weighted essentially non-oscillatory (WENO) scheme for space discretization and using a third-order total-variation-diminishing (TVD) Runge-Kutta scheme for time integration. The calculated N-factors at the transition onset location increase gradually with increasing unit Reynolds numbers for flow over a sharp cone and remain almost the same for flow over a blunt cone. The receptivity coefficient increases slightly with increasing unit Reynolds numbers. They are on the order of 4 for a sharp cone and are on the order of 1 for a blunt cone. The location of transition onset predicted from the simulation including the freestream spectrum, receptivity, and the linear and the weakly nonlinear evolutions yields a solution close to the measured onset location for the sharp cone. The simulations over-predict transition onset by about twenty percent for the blunt cone.

Prediction of wall shear stresses in transitional boundary layers using near-wall mean velocity profiles

International Nuclear Information System (INIS)

Jeon, Woo Pyung; Shin, Sung Ho; Kang, Shin Hyoung

2000-01-01

The local wall shear stress in transitional boundary layer was estimated from the near-wall mean velocity data using the principle of Computational Preston tube Method(CPM). The previous DNS and experimental databases of transitional boundary layers were used to demonstrate the accuracy of the method and to provide the applicable range of wall unit y + . The skin friction coefficients predicted by the CPM agreed well with those from previous studies. To reexamine the applicability of the CPM, near-wall hot-wire measurements were conducted in developing transitional boundary layers on a flat plate with different freestream turbulence intensities. The intermittency profiles across the transitional boundary layers were reasonably obtained from the conditional sampling technique. An empirical correlation between the representative intermittency near the wall and the free parameter K 1 of the extended wall function of CPM has been newly proposed using the present and other experimental data. The CPM has been verified as a useful tool to measure the wall shear stress in transitional boundary layer with reasonable accuracy

Prediction of boundary-layer transition caused by crossflow disturbances

OpenAIRE

Nomura, Toshiyuki; 野村　聡幸

1999-01-01

A prediction system for boundary layer transition is developed which consists of the Navier-Stokes code computing a compressible boundary layer, the linear PSE (Parabolized Stability Equations) code computing the spatial growth of a disturbance, and the N-factor code integrating the growth rate. The system is applied to the case that the transition of the compressible boundary layer on a swept cylinder is caused by cross flow disturbances which have the same spanwise wavelength as observed in...

Functional dyspepsia, upper gastrointestinal symptoms, and transit in children

NARCIS (Netherlands)

Chitkara, Denesh K.; Delgado-Aros, Silvia; Bredenoord, Albert J.; Cremonini, Filippo; El-Youssef, Mounif; Freese, Deborah; Camilleri, Michael

2003-01-01

To assess the prevalence of abnormal gastric emptying and small bowel transit in children with functional dyspepsia at a tertiary care center, and the relationship between abnormal gastric and small bowel transit and symptoms in pediatric patients with functional gastrointestinal disorders. Patients

Mitochondrial morphology transitions and functions: implications for retrograde signaling?

Science.gov (United States)

Picard, Martin; Shirihai, Orian S.; Gentil, Benoit J.

2013-01-01

In response to cellular and environmental stresses, mitochondria undergo morphology transitions regulated by dynamic processes of membrane fusion and fission. These events of mitochondrial dynamics are central regulators of cellular activity, but the mechanisms linking mitochondrial shape to cell function remain unclear. One possibility evaluated in this review is that mitochondrial morphological transitions (from elongated to fragmented, and vice-versa) directly modify canonical aspects of the organelle's function, including susceptibility to mitochondrial permeability transition, respiratory properties of the electron transport chain, and reactive oxygen species production. Because outputs derived from mitochondrial metabolism are linked to defined cellular signaling pathways, fusion/fission morphology transitions could regulate mitochondrial function and retrograde signaling. This is hypothesized to provide a dynamic interface between the cell, its genome, and the fluctuating metabolic environment. PMID:23364527

A two-parameter model to predict fracture in the transition

International Nuclear Information System (INIS)

DeAquino, C.T.; Landes, J.D.; McCabe, D.E.

1995-01-01

A model is proposed that uses a numerical characterization of the crack tip stress field modified by the J - Q constraint theory and a weak link assumption to predict fracture behavior in the transition for reactor vessel steels. This model predicts the toughness scatter band for a component model from a toughness scatter band measured on a test specimen geometry. The model has been applied previously to two-dimensional through cracks. Many applications to actual components structures involve three-dimensional surface flaws. These cases require a more difficult level of analysis and need additional information. In this paper, both the current model for two-dimensional cracks and an approach needed to extend the model for the prediction of transition fracture behavior in three-dimensional surface flaws are discussed. Examples are presented to show how the model can be applied and in some cases to compare with other test results. (author). 13 refs., 7 figs

Nucleic acid-functionalized transition metal nanosheets for biosensing applications.

Science.gov (United States)

Mo, Liuting; Li, Juan; Liu, Qiaoling; Qiu, Liping; Tan, Weihong

2017-03-15

In clinical diagnostics, as well as food and environmental safety practices, biosensors are powerful tools for monitoring biological or biochemical processes. Two-dimensional (2D) transition metal nanomaterials, including transition metal chalcogenides (TMCs) and transition metal oxides (TMOs), are receiving growing interest for their use in biosensing applications based on such unique properties as high surface area and fluorescence quenching abilities. Meanwhile, nucleic acid probes based on Watson-Crick base-pairing rules are also being widely applied in biosensing based on their excellent recognition capability. In particular, the emergence of functional nucleic acids in the 1980s, especially aptamers, has substantially extended the recognition capability of nucleic acids to various targets, ranging from small organic molecules and metal ions to proteins and cells. Based on π-π stacking interaction between transition metal nanosheets and nucleic acids, biosensing systems can be easily assembled. Therefore, the combination of 2D transition metal nanomaterials and nucleic acids brings intriguing opportunities in bioanalysis and biomedicine. In this review, we summarize recent advances of nucleic acid-functionalized transition metal nanosheets in biosensing applications. The structure and properties of 2D transition metal nanomaterials are first discussed, emphasizing the interaction between transition metal nanosheets and nucleic acids. Then, the applications of nucleic acid-functionalized transition metal nanosheet-based biosensors are discussed in the context of different signal transducing mechanisms, including optical and electrochemical approaches. Finally, we provide our perspectives on the current challenges and opportunities in this promising field. Copyright © 2016 Elsevier B.V. All rights reserved.

Novel Approach for the Recognition and Prediction of Multi-Function Radar Behaviours Based on Predictive State Representations.

Science.gov (United States)

Ou, Jian; Chen, Yongguang; Zhao, Feng; Liu, Jin; Xiao, Shunping

2017-03-19

The extensive applications of multi-function radars (MFRs) have presented a great challenge to the technologies of radar countermeasures (RCMs) and electronic intelligence (ELINT). The recently proposed cognitive electronic warfare (CEW) provides a good solution, whose crux is to perceive present and future MFR behaviours, including the operating modes, waveform parameters, scheduling schemes, etc. Due to the variety and complexity of MFR waveforms, the existing approaches have the drawbacks of inefficiency and weak practicability in prediction. A novel method for MFR behaviour recognition and prediction is proposed based on predictive state representation (PSR). With the proposed approach, operating modes of MFR are recognized by accumulating the predictive states, instead of using fixed transition probabilities that are unavailable in the battlefield. It helps to reduce the dependence of MFR on prior information. And MFR signals can be quickly predicted by iteratively using the predicted observation, avoiding the very large computation brought by the uncertainty of future observations. Simulations with a hypothetical MFR signal sequence in a typical scenario are presented, showing that the proposed methods perform well and efficiently, which attests to their validity.

Prediction of rainfall anomalies during the dry to wet transition season over the Southern Amazonia using machine learning tools

Science.gov (United States)

Shan, X.; Zhang, K.; Zhuang, Y.; Fu, R.; Hong, Y.

2017-12-01

Seasonal prediction of rainfall during the dry-to-wet transition season in austral spring (September-November) over southern Amazonia is central for improving planting crops and fire mitigation in that region. Previous studies have identified the key large-scale atmospheric dynamic and thermodynamics pre-conditions during the dry season (June-August) that influence the rainfall anomalies during the dry to wet transition season over Southern Amazonia. Based on these key pre-conditions during dry season, we have evaluated several statistical models and developed a Neural Network based statistical prediction system to predict rainfall during the dry to wet transition for Southern Amazonia (5-15°S, 50-70°W). Multivariate Empirical Orthogonal Function (EOF) Analysis is applied to the following four fields during JJA from the ECMWF Reanalysis (ERA-Interim) spanning from year 1979 to 2015: geopotential height at 200 hPa, surface relative humidity, convective inhibition energy (CIN) index and convective available potential energy (CAPE), to filter out noise and highlight the most coherent spatial and temporal variations. The first 10 EOF modes are retained for inputs to the statistical models, accounting for at least 70% of the total variance in the predictor fields. We have tested several linear and non-linear statistical methods. While the regularized Ridge Regression and Lasso Regression can generally capture the spatial pattern and magnitude of rainfall anomalies, we found that that Neural Network performs best with an accuracy greater than 80%, as expected from the non-linear dependence of the rainfall on the large-scale atmospheric thermodynamic conditions and circulation. Further tests of various prediction skill metrics and hindcasts also suggest this Neural Network prediction approach can significantly improve seasonal prediction skill than the dynamic predictions and regression based statistical predictions. Thus, this statistical prediction system could have

Improving Prediction of Large-scale Regime Transitions

Science.gov (United States)

Gyakum, J. R.; Roebber, P.; Bosart, L. F.; Honor, A.; Bunker, E.; Low, Y.; Hart, J.; Bliankinshtein, N.; Kolly, A.; Atallah, E.; Huang, Y.

2017-12-01

Cool season atmospheric predictability over the CONUS on subseasonal times scales (1-4 weeks) is critically dependent upon the structure, configuration, and evolution of the North Pacific jet stream (NPJ). The NPJ can be perturbed on its tropical side on synoptic time scales by recurving and transitioning tropical cyclones (TCs) and on subseasonal time scales by longitudinally varying convection associated with the Madden-Julian Oscillation (MJO). Likewise, the NPJ can be perturbed on its poleward side on synoptic time scales by midlatitude and polar disturbances that originate over the Asian continent. These midlatitude and polar disturbances can often trigger downstream Rossby wave propagation across the North Pacific, North America, and the North Atlantic. The project team is investigating the following multiscale processes and features: the spatiotemporal distribution of cyclone clustering over the Northern Hemisphere; cyclone clustering as influenced by atmospheric blocking and the phases and amplitudes of the major teleconnection indices, ENSO and the MJO; composite and case study analyses of representative cyclone clustering events to establish the governing dynamics; regime change predictability horizons associated with cyclone clustering events; Arctic air mass generation and modification; life cycles of the MJO; and poleward heat and moisture transports of subtropical air masses. A critical component of the study is weather regime classification. These classifications are defined through: the spatiotemporal clustering of surface cyclogenesis; a general circulation metric combining data at 500-hPa and the dynamic tropopause; Self Organizing Maps (SOM), constructed from dynamic tropopause and 850 hPa equivalent potential temperature data. The resultant lattice of nodes is used to categorize synoptic classes and their predictability, as well as to determine the robustness of the CFSv2 model climate relative to observations. Transition pathways between these

Predicting the glass transition temperature and viscosity of secondary organic material using molecular composition

Science.gov (United States)

Wong DeRieux, Wing-Sy; Li, Ying; Lin, Peng; Laskin, Julia; Laskin, Alexander; Bertram, Allan K.; Nizkorodov, Sergey A.; Shiraiwa, Manabu

2018-05-01

Secondary organic aerosol (SOA) accounts for a large fraction of submicron particles in the atmosphere. SOA can occur in amorphous solid or semi-solid phase states depending on chemical composition, relative humidity (RH), and temperature. The phase transition between amorphous solid and semi-solid states occurs at the glass transition temperature (Tg). We have recently developed a method to estimate Tg of pure compounds containing carbon, hydrogen, and oxygen atoms (CHO compounds) with molar mass less than 450 g mol-1 based on their molar mass and atomic O : C ratio. In this study, we refine and extend this method for CH and CHO compounds with molar mass up to ˜ 1100 g mol-1 using the number of carbon, hydrogen, and oxygen atoms. We predict viscosity from the Tg-scaled Arrhenius plot of fragility (viscosity vs. Tg/T) as a function of the fragility parameter D. We compiled D values of organic compounds from the literature and found that D approaches a lower limit of ˜ 10 (±1.7) as the molar mass increases. We estimated the viscosity of α-pinene and isoprene SOA as a function of RH by accounting for the hygroscopic growth of SOA and applying the Gordon-Taylor mixing rule, reproducing previously published experimental measurements very well. Sensitivity studies were conducted to evaluate impacts of Tg, D, the hygroscopicity parameter (κ), and the Gordon-Taylor constant on viscosity predictions. The viscosity of toluene SOA was predicted using the elemental composition obtained by high-resolution mass spectrometry (HRMS), resulting in a good agreement with the measured viscosity. We also estimated the viscosity of biomass burning particles using the chemical composition measured by HRMS with two different ionization techniques: electrospray ionization (ESI) and atmospheric pressure photoionization (APPI). Due to differences in detected organic compounds and signal intensity, predicted viscosities at low RH based on ESI and APPI measurements differ by 2-5 orders

Novel Approach for the Recognition and Prediction of Multi-Function Radar Behaviours Based on Predictive State Representations

Directory of Open Access Journals (Sweden)

Jian Ou

2017-03-01

Full Text Available The extensive applications of multi-function radars (MFRs have presented a great challenge to the technologies of radar countermeasures (RCMs and electronic intelligence (ELINT. The recently proposed cognitive electronic warfare (CEW provides a good solution, whose crux is to perceive present and future MFR behaviours, including the operating modes, waveform parameters, scheduling schemes, etc. Due to the variety and complexity of MFR waveforms, the existing approaches have the drawbacks of inefficiency and weak practicability in prediction. A novel method for MFR behaviour recognition and prediction is proposed based on predictive state representation (PSR. With the proposed approach, operating modes of MFR are recognized by accumulating the predictive states, instead of using fixed transition probabilities that are unavailable in the battlefield. It helps to reduce the dependence of MFR on prior information. And MFR signals can be quickly predicted by iteratively using the predicted observation, avoiding the very large computation brought by the uncertainty of future observations. Simulations with a hypothetical MFR signal sequence in a typical scenario are presented, showing that the proposed methods perform well and efficiently, which attests to their validity.

Simplified Approach to Predicting Rough Surface Transition

Science.gov (United States)

Boyle, Robert J.; Stripf, Matthias

2009-01-01

Turbine vane heat transfer predictions are given for smooth and rough vanes where the experimental data show transition moving forward on the vane as the surface roughness physical height increases. Consiste nt with smooth vane heat transfer, the transition moves forward for a fixed roughness height as the Reynolds number increases. Comparison s are presented with published experimental data. Some of the data ar e for a regular roughness geometry with a range of roughness heights, Reynolds numbers, and inlet turbulence intensities. The approach ta ken in this analysis is to treat the roughness in a statistical sense , consistent with what would be obtained from blades measured after e xposure to actual engine environments. An approach is given to determ ine the equivalent sand grain roughness from the statistics of the re gular geometry. This approach is guided by the experimental data. A roughness transition criterion is developed, and comparisons are made with experimental data over the entire range of experimental test co nditions. Additional comparisons are made with experimental heat tran sfer data, where the roughness geometries are both regular as well a s statistical. Using the developed analysis, heat transfer calculatio ns are presented for the second stage vane of a high pressure turbine at hypothetical engine conditions.

Microbial Functional Gene Diversity Predicts Groundwater Contamination and Ecosystem Functioning.

Science.gov (United States)

He, Zhili; Zhang, Ping; Wu, Linwei; Rocha, Andrea M; Tu, Qichao; Shi, Zhou; Wu, Bo; Qin, Yujia; Wang, Jianjun; Yan, Qingyun; Curtis, Daniel; Ning, Daliang; Van Nostrand, Joy D; Wu, Liyou; Yang, Yunfeng; Elias, Dwayne A; Watson, David B; Adams, Michael W W; Fields, Matthew W; Alm, Eric J; Hazen, Terry C; Adams, Paul D; Arkin, Adam P; Zhou, Jizhong

2018-02-20

Contamination from anthropogenic activities has significantly impacted Earth's biosphere. However, knowledge about how environmental contamination affects the biodiversity of groundwater microbiomes and ecosystem functioning remains very limited. Here, we used a comprehensive functional gene array to analyze groundwater microbiomes from 69 wells at the Oak Ridge Field Research Center (Oak Ridge, TN), representing a wide pH range and uranium, nitrate, and other contaminants. We hypothesized that the functional diversity of groundwater microbiomes would decrease as environmental contamination (e.g., uranium or nitrate) increased or at low or high pH, while some specific populations capable of utilizing or resistant to those contaminants would increase, and thus, such key microbial functional genes and/or populations could be used to predict groundwater contamination and ecosystem functioning. Our results indicated that functional richness/diversity decreased as uranium (but not nitrate) increased in groundwater. In addition, about 5.9% of specific key functional populations targeted by a comprehensive functional gene array (GeoChip 5) increased significantly ( P contamination and ecosystem functioning. This study indicates great potential for using microbial functional genes to predict environmental contamination and ecosystem functioning. IMPORTANCE Disentangling the relationships between biodiversity and ecosystem functioning is an important but poorly understood topic in ecology. Predicting ecosystem functioning on the basis of biodiversity is even more difficult, particularly with microbial biomarkers. As an exploratory effort, this study used key microbial functional genes as biomarkers to provide predictive understanding of environmental contamination and ecosystem functioning. The results indicated that the overall functional gene richness/diversity decreased as uranium increased in groundwater, while specific key microbial guilds increased significantly as

Impulsive Stimulated Light Scattering Studies of the Liquid-Glass Transition: on the Experimental Verification of Mode-Coupling Theory Predictions.

Science.gov (United States)

Halalay, Ion C.

A study of the structural glass transition trough impulsive stimulated light scattering experiments has been carried out in concentrated aqueous lithium chloride solutions, at temperatures ranging from ambient to cryogenic. A specially designed sample cell made it possible to cover the whole temperature interval from simple liquid, to viscoelastic supercooled liquid, to glass. It is shown that a phenomenological description of the results of these experiments in terms of a spectrum of relaxation times through the use of a Kohlrausch-Williams-Watts relaxation function is inadequate. Based on predictions of mode-coupling theory of the liquid-glass transition, an alternative approach to data interpretation is proposed. It is shown that for an aqueous lithium chloride solution, the prediction of simple scaling and identical scaling for mechanical and electrical susceptibilities seems to be valid. However, another prediction of theory is called into question: instead of a power-law behavior on temperature difference, it is found experimentally that the behavior of the susceptibility spectrum minimum is exponential. Similar disagreements are found for other two materials, triphenyl phosphite and polypropylene oxide. The causes for these discrepancies are discussed and it is concluded that additional experimentation is necessary to verify theoretical claims. Experiments are proposed which can test these predictions and serve as guide for the construction of theoretical models for the glass transition in real systems. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617 -253-5668; Fax 617-253-1690.).

Functionalization of 2D transition metal dichalcogenides for biomedical applications

International Nuclear Information System (INIS)

Li, Zibiao; Wong, Swee Liang

2017-01-01

Recent research has revealed a gamut of interesting properties present in layered two-dimensional (2D) transition metal dichalcogenides (TMDCs) such as photoluminescence, comparatively high electron mobility, flexibility, mechanical strength and relatively low toxicity. The large surface to area ratio inherent in these materials also allows easy functionalization and maximal interaction with the external environment. Due to its unique physical and chemical properties, much work has been done in tailoring TMDCs through chemical functionalization for use in a diverse range of biomedical applications as biosensors, drug delivery carriers or even as therapeutic agents. In this review, current progress on the different types of TMDC functionalization for various biological applications will be presented and its future outlook will be discussed. - Highlights: • The different functionalization strategies and approaches of transition metal dichalcogenides are reviewed. • Properties of transition metal dichalcogenides useful for biomedical usage and their methods of synthesis are introduced. • Functionalization approaches are presented according to material type and their different application purpose is discussed.

Integration of relational and hierarchical network information for protein function prediction

Directory of Open Access Journals (Sweden)

Jiang Xiaoyu

2008-08-01

Full Text Available Abstract Background In the current climate of high-throughput computational biology, the inference of a protein's function from related measurements, such as protein-protein interaction relations, has become a canonical task. Most existing technologies pursue this task as a classification problem, on a term-by-term basis, for each term in a database, such as the Gene Ontology (GO database, a popular rigorous vocabulary for biological functions. However, ontology structures are essentially hierarchies, with certain top to bottom annotation rules which protein function predictions should in principle follow. Currently, the most common approach to imposing these hierarchical constraints on network-based classifiers is through the use of transitive closure to predictions. Results We propose a probabilistic framework to integrate information in relational data, in the form of a protein-protein interaction network, and a hierarchically structured database of terms, in the form of the GO database, for the purpose of protein function prediction. At the heart of our framework is a factorization of local neighborhood information in the protein-protein interaction network across successive ancestral terms in the GO hierarchy. We introduce a classifier within this framework, with computationally efficient implementation, that produces GO-term predictions that naturally obey a hierarchical 'true-path' consistency from root to leaves, without the need for further post-processing. Conclusion A cross-validation study, using data from the yeast Saccharomyces cerevisiae, shows our method offers substantial improvements over both standard 'guilt-by-association' (i.e., Nearest-Neighbor and more refined Markov random field methods, whether in their original form or when post-processed to artificially impose 'true-path' consistency. Further analysis of the results indicates that these improvements are associated with increased predictive capabilities (i.e., increased

Ecological Factors Predict Transition Readiness/Self-Management in Youth With Chronic Conditions.

Science.gov (United States)

Javalkar, Karina; Johnson, Meredith; Kshirsagar, Abhijit V; Ocegueda, Sofia; Detwiler, Randal K; Ferris, Maria

2016-01-01

Health care transition readiness or self-management among adolescents and young adults (AYA) with chronic conditions may be influenced by factors related to their surrounding environment. Study participants were AYA diagnosed with a chronic condition and evaluated at pediatric- and adult-focused subspecialty clinics at the University of North Carolina Hospital Systems. All participants were administered a provider-administered self-management/transition-readiness tool, the UNC TRxANSITION Scale. Geographic area and associated characteristics (ecological factors) were identified for each participant's ZIP code using the published U.S. Census data. The Level 1 model of the hierarchical linear regression used individual-level predictors of transition readiness/self-management. The Level 2 model incorporated the ecological factors. We enrolled 511 AYA with different chronic conditions aged 12-31 years with the following characteristics: mean age of 20± 4 years, 45% white, 42% black, and 54% female. Participants represented 214 ZIP codes in or around North Carolina, USA. The Level 1 model showed that age, gender, and race were significant predictors of transition readiness/self-management. On adding the ecological factors in the Level 2 model, race was no longer significant. Participants from a geographic area with a greater percentage of females (β = .114, p = .005) and a higher median income (β = .126, p = .002) had greater overall transition readiness. Ecological factors also predicted subdomains of transition readiness/self-management. In this cohort of adolescents and young adults with different chronic conditions, ecological disparities such as sex composition, median income, and language predict self-management/transition readiness. It is important to take ecological risk factors into consideration when preparing patients for health self-management or transition. Copyright © 2016 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All

Incorporating functional inter-relationships into protein function prediction algorithms

Directory of Open Access Journals (Sweden)

Kumar Vipin

2009-05-01

Full Text Available Abstract Background Functional classification schemes (e.g. the Gene Ontology that serve as the basis for annotation efforts in several organisms are often the source of gold standard information for computational efforts at supervised protein function prediction. While successful function prediction algorithms have been developed, few previous efforts have utilized more than the protein-to-functional class label information provided by such knowledge bases. For instance, the Gene Ontology not only captures protein annotations to a set of functional classes, but it also arranges these classes in a DAG-based hierarchy that captures rich inter-relationships between different classes. These inter-relationships present both opportunities, such as the potential for additional training examples for small classes from larger related classes, and challenges, such as a harder to learn distinction between similar GO terms, for standard classification-based approaches. Results We propose a method to enhance the performance of classification-based protein function prediction algorithms by addressing the issue of using these interrelationships between functional classes constituting functional classification schemes. Using a standard measure for evaluating the semantic similarity between nodes in an ontology, we quantify and incorporate these inter-relationships into the k-nearest neighbor classifier. We present experiments on several large genomic data sets, each of which is used for the modeling and prediction of over hundred classes from the GO Biological Process ontology. The results show that this incorporation produces more accurate predictions for a large number of the functional classes considered, and also that the classes benefitted most by this approach are those containing the fewest members. In addition, we show how our proposed framework can be used for integrating information from the entire GO hierarchy for improving the accuracy of

Transition point prediction in a multicomponent lattice Boltzmann model: Forcing scheme dependencies

Science.gov (United States)

Küllmer, Knut; Krämer, Andreas; Joppich, Wolfgang; Reith, Dirk; Foysi, Holger

2018-02-01

Pseudopotential-based lattice Boltzmann models are widely used for numerical simulations of multiphase flows. In the special case of multicomponent systems, the overall dynamics are characterized by the conservation equations for mass and momentum as well as an additional advection diffusion equation for each component. In the present study, we investigate how the latter is affected by the forcing scheme, i.e., by the way the underlying interparticle forces are incorporated into the lattice Boltzmann equation. By comparing two model formulations for pure multicomponent systems, namely the standard model [X. Shan and G. D. Doolen, J. Stat. Phys. 81, 379 (1995), 10.1007/BF02179985] and the explicit forcing model [M. L. Porter et al., Phys. Rev. E 86, 036701 (2012), 10.1103/PhysRevE.86.036701], we reveal that the diffusion characteristics drastically change. We derive a generalized, potential function-dependent expression for the transition point from the miscible to the immiscible regime and demonstrate that it is shifted between the models. The theoretical predictions for both the transition point and the mutual diffusion coefficient are validated in simulations of static droplets and decaying sinusoidal concentration waves, respectively. To show the universality of our analysis, two common and one new potential function are investigated. As the shift in the diffusion characteristics directly affects the interfacial properties, we additionally show that phenomena related to the interfacial tension such as the modeling of contact angles are influenced as well.

Transition point prediction in a multicomponent lattice Boltzmann model: Forcing scheme dependencies.

Science.gov (United States)

Küllmer, Knut; Krämer, Andreas; Joppich, Wolfgang; Reith, Dirk; Foysi, Holger

2018-02-01

Pseudopotential-based lattice Boltzmann models are widely used for numerical simulations of multiphase flows. In the special case of multicomponent systems, the overall dynamics are characterized by the conservation equations for mass and momentum as well as an additional advection diffusion equation for each component. In the present study, we investigate how the latter is affected by the forcing scheme, i.e., by the way the underlying interparticle forces are incorporated into the lattice Boltzmann equation. By comparing two model formulations for pure multicomponent systems, namely the standard model [X. Shan and G. D. Doolen, J. Stat. Phys. 81, 379 (1995)JSTPBS0022-471510.1007/BF02179985] and the explicit forcing model [M. L. Porter et al., Phys. Rev. E 86, 036701 (2012)PLEEE81539-375510.1103/PhysRevE.86.036701], we reveal that the diffusion characteristics drastically change. We derive a generalized, potential function-dependent expression for the transition point from the miscible to the immiscible regime and demonstrate that it is shifted between the models. The theoretical predictions for both the transition point and the mutual diffusion coefficient are validated in simulations of static droplets and decaying sinusoidal concentration waves, respectively. To show the universality of our analysis, two common and one new potential function are investigated. As the shift in the diffusion characteristics directly affects the interfacial properties, we additionally show that phenomena related to the interfacial tension such as the modeling of contact angles are influenced as well.

Location Prediction Based on Transition Probability Matrices Constructing from Sequential Rules for Spatial-Temporal K-Anonymity Dataset

Science.gov (United States)

Liu, Zhao; Zhu, Yunhong; Wu, Chenxue

2016-01-01

Spatial-temporal k-anonymity has become a mainstream approach among techniques for protection of users’ privacy in location-based services (LBS) applications, and has been applied to several variants such as LBS snapshot queries and continuous queries. Analyzing large-scale spatial-temporal anonymity sets may benefit several LBS applications. In this paper, we propose two location prediction methods based on transition probability matrices constructing from sequential rules for spatial-temporal k-anonymity dataset. First, we define single-step sequential rules mined from sequential spatial-temporal k-anonymity datasets generated from continuous LBS queries for multiple users. We then construct transition probability matrices from mined single-step sequential rules, and normalize the transition probabilities in the transition matrices. Next, we regard a mobility model for an LBS requester as a stationary stochastic process and compute the n-step transition probability matrices by raising the normalized transition probability matrices to the power n. Furthermore, we propose two location prediction methods: rough prediction and accurate prediction. The former achieves the probabilities of arriving at target locations along simple paths those include only current locations, target locations and transition steps. By iteratively combining the probabilities for simple paths with n steps and the probabilities for detailed paths with n-1 steps, the latter method calculates transition probabilities for detailed paths with n steps from current locations to target locations. Finally, we conduct extensive experiments, and correctness and flexibility of our proposed algorithm have been verified. PMID:27508502

Predicting the glass transition temperature and viscosity of secondary organic material using molecular composition

Directory of Open Access Journals (Sweden)

W.-S. W. DeRieux

2018-05-01

Full Text Available Secondary organic aerosol (SOA accounts for a large fraction of submicron particles in the atmosphere. SOA can occur in amorphous solid or semi-solid phase states depending on chemical composition, relative humidity (RH, and temperature. The phase transition between amorphous solid and semi-solid states occurs at the glass transition temperature (Tg. We have recently developed a method to estimate Tg of pure compounds containing carbon, hydrogen, and oxygen atoms (CHO compounds with molar mass less than 450 g mol−1 based on their molar mass and atomic O : C ratio. In this study, we refine and extend this method for CH and CHO compounds with molar mass up to ∼ 1100 g mol−1 using the number of carbon, hydrogen, and oxygen atoms. We predict viscosity from the Tg-scaled Arrhenius plot of fragility (viscosity vs. Tg∕T as a function of the fragility parameter D. We compiled D values of organic compounds from the literature and found that D approaches a lower limit of ∼ 10 (±1.7 as the molar mass increases. We estimated the viscosity of α-pinene and isoprene SOA as a function of RH by accounting for the hygroscopic growth of SOA and applying the Gordon–Taylor mixing rule, reproducing previously published experimental measurements very well. Sensitivity studies were conducted to evaluate impacts of Tg, D, the hygroscopicity parameter (κ, and the Gordon–Taylor constant on viscosity predictions. The viscosity of toluene SOA was predicted using the elemental composition obtained by high-resolution mass spectrometry (HRMS, resulting in a good agreement with the measured viscosity. We also estimated the viscosity of biomass burning particles using the chemical composition measured by HRMS with two different ionization techniques: electrospray ionization (ESI and atmospheric pressure photoionization (APPI. Due to differences in detected organic compounds and signal intensity, predicted viscosities at low RH based on ESI and

Trip time prediction in mass transit companies. A machine learning approach

OpenAIRE

João M. Moreira; Alípio Jorge; Jorge Freire de Sousa; Carlos Soares

2005-01-01

In this paper we discuss how trip time prediction can be useful foroperational optimization in mass transit companies and which machine learningtechniques can be used to improve results. Firstly, we analyze which departmentsneed trip time prediction and when. Secondly, we review related work and thirdlywe present the analysis of trip time over a particular path. We proceed by presentingexperimental results conducted on real data with the forecasting techniques wefound most adequate, and concl...

Prediction and Analysis of the Nonsteady Transition and Separation Processes on an Oscillating Wind Turbine Airfoil using the \\gamma-Re_\\theta Transition Model.

Energy Technology Data Exchange (ETDEWEB)

Nandi, Taraj; Brasseur, James; Vijayakumar, Ganesh

2016-01-04

This study is aimed at gaining insight into the nonsteady transitional boundary layer dynamics of wind turbine blades and the predictive capabilities of URANS based transition and turbulence models for similar physics through the analysis of a controlled flow with similar nonsteady parameters.

A Predictive Coexpression Network Identifies Novel Genes Controlling the Seed-to-Seedling Phase Transition in Arabidopsis thaliana.

Science.gov (United States)

Silva, Anderson Tadeu; Ribone, Pamela A; Chan, Raquel L; Ligterink, Wilco; Hilhorst, Henk W M

2016-04-01

The transition from a quiescent dry seed to an actively growing photoautotrophic seedling is a complex and crucial trait for plant propagation. This study provides a detailed description of global gene expression in seven successive developmental stages of seedling establishment in Arabidopsis (Arabidopsis thaliana). Using the transcriptome signature from these developmental stages, we obtained a coexpression gene network that highlights interactions between known regulators of the seed-to-seedling transition and predicts the functions of uncharacterized genes in seedling establishment. The coexpressed gene data sets together with the transcriptional module indicate biological functions related to seedling establishment. Characterization of the homeodomain leucine zipper I transcription factor AtHB13, which is expressed during the seed-to-seedling transition, demonstrated that this gene regulates some of the network nodes and affects late seedling establishment. Knockout mutants for athb13 showed increased primary root length as compared with wild-type (Columbia-0) seedlings, suggesting that this transcription factor is a negative regulator of early root growth, possibly repressing cell division and/or cell elongation or the length of time that cells elongate. The signal transduction pathways present during the early phases of the seed-to-seedling transition anticipate the control of important events for a vigorous seedling, such as root growth. This study demonstrates that a gene coexpression network together with transcriptional modules can provide insights that are not derived from comparative transcript profiling alone. © 2016 American Society of Plant Biologists. All Rights Reserved.

Prediction of B1 to B10 phase transition in LuN under pressure: An ab-initio investigation

Energy Technology Data Exchange (ETDEWEB)

Sahoo, B. D., E-mail: bdsahoo@barc.gov.in; Mukherjee, D.; Joshi, K. D.; Kaushik, T. C.; Gupta, Satish C. [Applied Physics Division, Bhabha Atomic Research Centre, Mumbai, India 400085 (India)

2016-05-23

Ab-initio total energy calculations have been performed in lutetium nitride (LuN) as a function of hydrostatic compression to understand the high pressure behavior of this compound. Our calculations predict a phase transition from ambient rocksalt type structure (B1 phase) to a tetragonal structure (B10 phase) at ~ 240 GPa. The phase transition has been identified as first order in nature with volume discontinuity of ~ 6%. The predicted high pressure phase has been found to be stable up to at least 400 GPa, the maximum pressure up to which calculations have been performed.Further, to substantiate the results of static lattice calculations analysis of lattice dynamic stability of B1 and B10 phase has been carried out at different pressures. Apart from this, we have analyzed the lattice dynamic stability CsCl type (B2) phase around the 240 GPa, the pressure reported for B1 to B2 transition in previous all-electron calculations by Gupta et al. 2013. We find that the B2 structure is lattice dynamically unstable at this pressure and remains unstable up to ~ 400 GPa, ruling out the possibility of B1 to B2 phase transition at least up to ~ 400 GPa. Further, the theoretically determined equation of state has been utilized to derive various physical quantities such as zero pressure equilibrium volume, bulk modulus, and pressure derivative of bulk modulus of B1 phase at ambient conditions.

Relationship between functional elongated colonic transit time and constipation

International Nuclear Information System (INIS)

Xie Yuchang; Qian Xuequn; Zhang Genfu

2002-01-01

Objective: To retrospectively analyze the role of colonic transit test in diagnosis and aetiology of constipation. Methods: 87 cases of constipation diagnosed under Agachan scoring system and having completed transit test at least once were enrolled. All cases were divided into two groups: group A have normal colonic transit time, group B have extended colonic transit time. A comparison of the ratio of rectosigmoid transit by total colon (RRT) between group A and B. Result: 32 cases were enrolled in group A and 55 in group B. Low value of RRT was presented in 10 cases out of 32 in group A (31.3%), while in group B the abnormality was observed in 9 cases out of 55 (16.4%). A statistical difference between the two group was revealed by x 2 test (P < 0.01). Conclusion: Colonic transit test helps the confirming the aetiology of constipation, and the evaluation of rectosigmoid transit function is especially valuable

Text mining improves prediction of protein functional sites.

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Karin M Verspoor

Full Text Available We present an approach that integrates protein structure analysis and text mining for protein functional site prediction, called LEAP-FS (Literature Enhanced Automated Prediction of Functional Sites. The structure analysis was carried out using Dynamics Perturbation Analysis (DPA, which predicts functional sites at control points where interactions greatly perturb protein vibrations. The text mining extracts mentions of residues in the literature, and predicts that residues mentioned are functionally important. We assessed the significance of each of these methods by analyzing their performance in finding known functional sites (specifically, small-molecule binding sites and catalytic sites in about 100,000 publicly available protein structures. The DPA predictions recapitulated many of the functional site annotations and preferentially recovered binding sites annotated as biologically relevant vs. those annotated as potentially spurious. The text-based predictions were also substantially supported by the functional site annotations: compared to other residues, residues mentioned in text were roughly six times more likely to be found in a functional site. The overlap of predictions with annotations improved when the text-based and structure-based methods agreed. Our analysis also yielded new high-quality predictions of many functional site residues that were not catalogued in the curated data sources we inspected. We conclude that both DPA and text mining independently provide valuable high-throughput protein functional site predictions, and that integrating the two methods using LEAP-FS further improves the quality of these predictions.

Text Mining Improves Prediction of Protein Functional Sites

Science.gov (United States)

Cohn, Judith D.; Ravikumar, Komandur E.

2012-01-01

We present an approach that integrates protein structure analysis and text mining for protein functional site prediction, called LEAP-FS (Literature Enhanced Automated Prediction of Functional Sites). The structure analysis was carried out using Dynamics Perturbation Analysis (DPA), which predicts functional sites at control points where interactions greatly perturb protein vibrations. The text mining extracts mentions of residues in the literature, and predicts that residues mentioned are functionally important. We assessed the significance of each of these methods by analyzing their performance in finding known functional sites (specifically, small-molecule binding sites and catalytic sites) in about 100,000 publicly available protein structures. The DPA predictions recapitulated many of the functional site annotations and preferentially recovered binding sites annotated as biologically relevant vs. those annotated as potentially spurious. The text-based predictions were also substantially supported by the functional site annotations: compared to other residues, residues mentioned in text were roughly six times more likely to be found in a functional site. The overlap of predictions with annotations improved when the text-based and structure-based methods agreed. Our analysis also yielded new high-quality predictions of many functional site residues that were not catalogued in the curated data sources we inspected. We conclude that both DPA and text mining independently provide valuable high-throughput protein functional site predictions, and that integrating the two methods using LEAP-FS further improves the quality of these predictions. PMID:22393388

Transitioning a Chesapeake Bay Ecological Prediction System to Operations

Science.gov (United States)

Brown, C.; Green, D. S.; Eco Forecasters

2011-12-01

Ecological prediction of the impacts of physical, chemical, biological, and human-induced change on ecosystems and their components, encompass a wide range of space and time scales, and subject matter. They vary from predicting the occurrence and/or transport of certain species, such harmful algal blooms, or biogeochemical constituents, such as dissolved oxygen concentrations, to large-scale ecosystem responses and higher trophic levels. The timescales of ecological prediction, including guidance and forecasts, range from nowcasts and short-term forecasts (days), to intraseasonal and interannual outlooks (weeks to months), to decadal and century projections in climate change scenarios. The spatial scales range from small coastal inlets to basin and global scale biogeochemical and ecological forecasts. The types of models that have been used include conceptual, empirical, mechanistic, and hybrid approaches. This presentation will identify the challenges and progress toward transitioning experimental model-based ecological prediction into operational guidance and forecasting. Recent efforts are targeting integration of regional ocean, hydrodynamic and hydrological models and leveraging weather and water service infrastructure to enable the prototyping of an operational ecological forecast capability for the Chesapeake Bay and its tidal tributaries. A path finder demonstration predicts the probability of encountering sea nettles (Chrysaora quinquecirrha), a stinging jellyfish. These jellyfish can negatively impact safety and economic activities in the bay and an impact-based forecast that predicts where and when this biotic nuisance occurs may help management effects. The issuance of bay-wide nowcasts and three-day forecasts of sea nettle probability are generated daily by forcing an empirical habitat model (that predicts the probability of sea nettles) with real-time and 3-day forecasts of sea-surface temperature (SST) and salinity (SSS). In the first demonstration

Predicting transition in two- and three-dimensional separated flows

International Nuclear Information System (INIS)

Cutrone, L.; De Palma, P.; Pascazio, G.; Napolitano, M.

2008-01-01

This paper is concerned with the numerical prediction of two- and three-dimensional transitional separated flows of turbomachinery interest. The recently proposed single-point transition model based on the use of a laminar kinetic energy transport equation is considered, insofar as it does not require to evaluate any integral parameter, such as boundary-layer thickness, and is thus directly applicable to three-dimensional flows. A well established model, combining a transition-onset correlation with an intermittency transport equation, is also used for comparison. Both models are implemented within a Reynolds-averaged Navier-Stokes solver employing a low-Reynolds-number k-ω turbulence model. The performance of the transition models have been evaluated and tested versus well-documented incompressible flows past a flat plate with semi-circular leading edge, namely: tests T3L2, T3L3, T3L5, and T3LA1 of ERCOFTAC, with different Reynolds numbers and free-stream conditions, the last one being characterized by a non-zero pressure gradient. In all computations, the first model has proven as adequate as or superior to the second one and has been then applied with success to two more complex test cases, for which detailed experimental data are available in the literature, namely: the two- and three-dimensional flows through the T106 linear turbine cascade

Systematic prediction of high-pressure melting curves of transition metals

International Nuclear Information System (INIS)

Hieu, Ho Khac

2014-01-01

The pressure effects on melting temperatures of transition metals have been studied based on the combination of the modified Lindemann criterion with statistical moment method in quantum statistical mechanics. Numerical calculations have been performed for five transition metals including Cu, Pd, Pt, Ni, and Mn up to pressure 100 GPa. Our results are in good and reasonable agreements with available experimental data. This approach gives us a relatively simple method for qualitatively calculating high-pressure melting temperature. Moreover, it can be used to verify future experimental and theoretical works. This research proposes the potential of the combination of statistical moment method and the modified Lindemann criterion on predicting high-pressure melting of materials.

Short-Term Prediction Research and Transition (SPoRT) Center: Transitioning Satellite Data to Operations

Science.gov (United States)

Zavodsky, Bradley

2012-01-01

The Short-term Prediction Research and Transition (SPoRT) Center located at NASA Marshall Space Flight Center has been conducting testbed activities aimed at transitioning satellite products to National Weather Service operational end users for the last 10 years. SPoRT is a NASA/NOAA funded project that has set the bar for transition of products to operational end users through a paradigm of understanding forecast challenges and forecaster needs, displaying products in end users decision support systems, actively assessing the operational impact of these products, and improving products based on forecaster feedback. Aiming for quality partnerships rather than a large quantity of data users, SPoRT has become a community leader in training operational forecasters on the use of up-and-coming satellite data through the use of legacy instruments and proxy data. Traditionally, SPoRT has supplied satellite imagery and products from NASA instruments such as the Moderate-resolution Imaging Spectroradiometer (MODIS) and the Atmospheric Infrared Sounder (AIRS). However, recently, SPoRT has been funded by the GOES-R and Joint Polar Satellite System (JPSS) Proving Grounds to accelerate the transition of selected imagery and products to help improve forecaster awareness of upcoming operational data from the Visible Infrared Imager Radiometer Suite (VIIRS), Cross-track Infrared Sounder (CrIS), Advanced Baseline Imager (ABI), and Geostationary Lightning Mapper (GLM). This presentation provides background on the SPoRT Center, the SPoRT paradigm, and some example products that SPoRT is excited to work with forecasters to evaluate.

Boundary-layer transition prediction using a simplified correlation-based model

Directory of Open Access Journals (Sweden)

Xia Chenchao

2016-02-01

Full Text Available This paper describes a simplified transition model based on the recently developed correlation-based γ-Reθt transition model. The transport equation of transition momentum thickness Reynolds number is eliminated for simplicity, and new transition length function and critical Reynolds number correlation are proposed. The new model is implemented into an in-house computational fluid dynamics (CFD code and validated for low and high-speed flow cases, including the zero pressure flat plate, airfoils, hypersonic flat plate and double wedge. Comparisons between the simulation results and experimental data show that the boundary-layer transition phenomena can be reasonably illustrated by the new model, which gives rise to significant improvements over the fully laminar and fully turbulent results. Moreover, the new model has comparable features of accuracy and applicability when compared with the original γ-Reθt model. In the meantime, the newly proposed model takes only one transport equation of intermittency factor and requires fewer correlations, which simplifies the original model greatly. Further studies, especially on separation-induced transition flows, are required for the improvement of the new model.

Microbial Functional Gene Diversity Predicts Groundwater Contamination and Ecosystem Functioning

Directory of Open Access Journals (Sweden)

Zhili He

2018-02-01

Full Text Available Contamination from anthropogenic activities has significantly impacted Earth’s biosphere. However, knowledge about how environmental contamination affects the biodiversity of groundwater microbiomes and ecosystem functioning remains very limited. Here, we used a comprehensive functional gene array to analyze groundwater microbiomes from 69 wells at the Oak Ridge Field Research Center (Oak Ridge, TN, representing a wide pH range and uranium, nitrate, and other contaminants. We hypothesized that the functional diversity of groundwater microbiomes would decrease as environmental contamination (e.g., uranium or nitrate increased or at low or high pH, while some specific populations capable of utilizing or resistant to those contaminants would increase, and thus, such key microbial functional genes and/or populations could be used to predict groundwater contamination and ecosystem functioning. Our results indicated that functional richness/diversity decreased as uranium (but not nitrate increased in groundwater. In addition, about 5.9% of specific key functional populations targeted by a comprehensive functional gene array (GeoChip 5 increased significantly (P < 0.05 as uranium or nitrate increased, and their changes could be used to successfully predict uranium and nitrate contamination and ecosystem functioning. This study indicates great potential for using microbial functional genes to predict environmental contamination and ecosystem functioning.

Experimental and computational prediction of glass transition temperature of drugs.

Science.gov (United States)

Alzghoul, Ahmad; Alhalaweh, Amjad; Mahlin, Denny; Bergström, Christel A S

2014-12-22

Glass transition temperature (Tg) is an important inherent property of an amorphous solid material which is usually determined experimentally. In this study, the relation between Tg and melting temperature (Tm) was evaluated using a data set of 71 structurally diverse druglike compounds. Further, in silico models for prediction of Tg were developed based on calculated molecular descriptors and linear (multilinear regression, partial least-squares, principal component regression) and nonlinear (neural network, support vector regression) modeling techniques. The models based on Tm predicted Tg with an RMSE of 19.5 K for the test set. Among the five computational models developed herein the support vector regression gave the best result with RMSE of 18.7 K for the test set using only four chemical descriptors. Hence, two different models that predict Tg of drug-like molecules with high accuracy were developed. If Tm is available, a simple linear regression can be used to predict Tg. However, the results also suggest that support vector regression and calculated molecular descriptors can predict Tg with equal accuracy, already before compound synthesis.

Value of radionuclide oesophageal transit in studies of functional dysphagia

International Nuclear Information System (INIS)

Llamas-Elvira, J.M.; Martinez-Parades, M.; Velasco-Lajo, T.

1986-01-01

Radionuclide oesophageal transit time was evaluated in 70 individuals, divided into three groups: normal individuals, patients with non-organic dysphagia and patients with primary oesophageal motility disorders treated with per-endoscopic forced pneumatic dilatation. In all of them the oesophageal transit time of a bolus of water with 18.5 MBq (500 μCi) of 99 Tcsup(m) sulphur colloid was assessed, as was the percentage of residual activity of the bolus in the oesophagus. There was a significant difference in these parameters between the control group and the group with non-organic dysphagia, the diagnostic capacity of this test being 93% sensitivity, 100% specificity, 100% positive predictive value and 90% negative predictive value, which suggests its inclusion in diagnostic protocols of dysphagias. In patients with primary oesophageal motility disorders, a significant decrease in values of residual activity has been observed after treatment with per-endoscopic forced pneumatic dilation. (author)

Density-functional theory for f-electron systems. The α-γ phase transition in cerium

International Nuclear Information System (INIS)

Casadei, Marco

2013-01-01

Rare earths are technologically important and scientifically highly interesting elements. The description of the volume collapse exhibited by some rare earth metals poses a great challenge to density-functional theory (DFT) since local/semi-local functionals (LDA/GGA) only partially capture the associated phase transitions. In this work this problem is approached by treating all electrons at the same quantum mechanical level, using both hybrid functionals (e.g. PBE0 and HSE06) and exact-exchange plus correlation in the random-phase approximation (EX+cRPA). The performance of recently developed beyond RPA schemes is also assessed. The isostructural α-γ phase transition in cerium is the most studied. The exact exchange contribution in PBE0 and HSE06 is crucial to produce two distinct solutions that can be associated with the α and γ phases. The two solutions emerge in bulk as well as in cluster calculations. Most notable is their presence in the cerium dimer. However, quantitative agreement with the extrapolated phase diagram requires EX+cRPA. So far the EX+cRPA correction can only be applied to cerium clusters and not to the bulk. A cluster of 19 atoms cut from the fcc crystal structure (the same that characterizes the α and γ phases) was therefore determined as representative. (EX+cRPA) rate at PBE0 for Ce 19 provides good agreement with the extrapolated transition pressure to zero temperature. We predict that a pressure induced phase transition should exist at or close to zero. A finite temperature phase diagram can be drawn in reasonable agreement with experiment by adding entropic effects. The cerium neighbors are also studied: lanthanum, which has no f electrons, praseodymium, with three f electrons and a volume collapse, and neodymium, with four f electrons and no volume collapse. Multiple solutions are also present for these f electron elements, confirming the importance of exact-exchange for f electron systems.

Proteome Profiling Outperforms Transcriptome Profiling for Coexpression Based Gene Function Prediction

Energy Technology Data Exchange (ETDEWEB)

Wang, Jing; Ma, Zihao; Carr, Steven A.; Mertins, Philipp; Zhang, Hui; Zhang, Zhen; Chan, Daniel W.; Ellis, Matthew J. C.; Townsend, R. Reid; Smith, Richard D.; McDermott, Jason E.; Chen, Xian; Paulovich, Amanda G.; Boja, Emily S.; Mesri, Mehdi; Kinsinger, Christopher R.; Rodriguez, Henry; Rodland, Karin D.; Liebler, Daniel C.; Zhang, Bing

2016-11-11

Coexpression of mRNAs under multiple conditions is commonly used to infer cofunctionality of their gene products despite well-known limitations of this “guilt-by-association” (GBA) approach. Recent advancements in mass spectrometry-based proteomic technologies have enabled global expression profiling at the protein level; however, whether proteome profiling data can outperform transcriptome profiling data for coexpression based gene function prediction has not been systematically investigated. Here, we address this question by constructing and analyzing mRNA and protein coexpression networks for three cancer types with matched mRNA and protein profiling data from The Cancer Genome Atlas (TCGA) and the Clinical Proteomic Tumor Analysis Consortium (CPTAC). Our analyses revealed a marked difference in wiring between the mRNA and protein coexpression networks. Whereas protein coexpression was driven primarily by functional similarity between coexpressed genes, mRNA coexpression was driven by both cofunction and chromosomal colocalization of the genes. Functionally coherent mRNA modules were more likely to have their edges preserved in corresponding protein networks than functionally incoherent mRNA modules. Proteomic data strengthened the link between gene expression and function for at least 75% of Gene Ontology (GO) biological processes and 90% of KEGG pathways. A web application Gene2Net (http://cptac.gene2net.org) developed based on the three protein coexpression networks revealed novel gene-function relationships, such as linking ERBB2 (HER2) to lipid biosynthetic process in breast cancer, identifying PLG as a new gene involved in complement activation, and identifying AEBP1 as a new epithelial-mesenchymal transition (EMT) marker. Our results demonstrate that proteome profiling outperforms transcriptome profiling for coexpression based gene function prediction. Proteomics should be integrated if not preferred in gene function and human disease studies

Functional changes through the usage of 3D-printed transitional prostheses in children.

Science.gov (United States)

Zuniga, Jorge M; Peck, Jean L; Srivastava, Rakesh; Pierce, James E; Dudley, Drew R; Than, Nicholas A; Stergiou, Nicholas

2017-11-08

There is limited knowledge on the use of 3 D-printed transitional prostheses, as they relate to changes in function and strength. Therefore, the purpose of this study was to identify functional and strength changes after usage of 3 D-printed transitional prostheses for multiple weeks for children with upper-limb differences. Gross manual dexterity was assessed using the Box and Block Test and wrist strength was measured using a dynamometer. This testing was conducted before and after a period of 24 ± 2.61 weeks of using a 3 D-printed transitional prosthesis. The 11 children (five girls and six boys; 3-15 years of age) who participated in the study, were fitted with a 3 D-printed transitional partial hand (n = 9) or an arm (n = 2) prosthesis. Separate two-way repeated measures ANOVAs were performed to analyze function and strength data. There was a significant hand by time interaction for function, but not for strength. Conclusion and relevance to the study of disability and rehabilitation: The increase in manual gross dexterity suggests that the Cyborg Beast 2 3 D-printed prosthesis can be used as a transitional device to improve function in children with traumatic or congenital upper-limb differences. Implications for Rehabilitation Children's prosthetic needs are complex due to their small size, rapid growth, and psychosocial development. Advancements in computer-aided design and additive manufacturing offer the possibility of designing and printing transitional prostheses at a very low cost, but there is limited knowledge on the function of this type of devices. The use of 3D printed transitional prostheses may improve manual gross dexterity in children after several weeks of using it.

Network-based model for predicting the effect of fuel price on transit ridership and greenhouse gas emissions

Directory of Open Access Journals (Sweden)

Michael W. Levin

2017-12-01

Full Text Available As fuel prices increase, drivers may make travel choices to minimize not only travel time, but also fuel consumption. Consideration of fuel consumption would affect route choice and influence trip frequency and mode choice. For instance, travelers may elect to live closer to their workplace, or use public transit to avoid fuel consumption and the associated costs. To incorporate network characteristics into predictions of the effects of fuel prices, we develop a multi-class combined elastic demand, mode choice, and user equilibrium model using a generalized cost function of travel time and fuel consumption with a combined solution algorithm. The algorithm is implemented in a custom software package, and a case study application on the Austin, Texas network is presented. We evaluate the fuel-price sensitivity of key variables such as drive-alone and transit class proportions, person-miles traveled, link-level traffic flow and per capita fuel consumption and emissions. These effects are examined across a heterogeneous demand set, with multiple user-classes categorized based on their value of travel time. The highest relative transit elasticities against fuel price are observed among low value of time classes, as expected. Although total personal vehicle travel decreases, congestion increases on some roads due to the generalized cost function. Reductions in system-wide fuel consumption and greenhouse gas emissions are observed as well. The study uncovers the combined interactions among fuel prices, multi-modal choice behavior, travel performance, and resultant environmental impacts, all of which dictate the urban travel market. It also equips agencies with motivation to tailor emissions reduction and transit-ridership stimulus policies around the most responsive user classes.

Phase transitions in blends functionalized thermoplastics

International Nuclear Information System (INIS)

Grigoryeva, O.; Sergeeva, L.; Starostenko, O.; Pissis, P.

2001-01-01

Phase transitions, morphology and structure-property relationships in polymer blends based on functionalized thermoplastics, i.e. widely used polyurethanes and styrene-acrylic acid copolymers, were investigated by means of inter-expletive non-destructive methods. Wide and small angle X-ray scattering (WAXS and SAXS), dynamic mechanical thermal analysis, thermally stimulated depolarization currents techniques, dielectric relaxation spectroscopy and several physico-mechanical characterization techniques were used. The results obtained by the various techniques were critically compared to each other. (author)

Hard-Wired Dopant Networks and the Prediction of High Transition Temperatures in Ceramic Superconductors

International Nuclear Information System (INIS)

Phillips, J.C.

2010-01-01

The review multiple successes of the discrete hard-wired dopant network model ZZIP, and comment on the equally numerous failures of continuum models, in describing and predicting the properties of ceramic superconductors. The prediction of transition temperatures can be regarded in several ways, either as an exacting test of theory, or as a tool for identifying theoretical rules for defining new homology models. Popular first principle methods for predicting transition temperatures in conventional crystalline superconductors have failed for cuprate HTSC, as have parameterized models based on CuO2 planes (with or without apical oxygen). Following a path suggested by Bayesian probability, it was found that the glassy, self-organized dopant network percolative model is so successful that it defines a new homology class appropriate to ceramic superconductors. The reasons for this success in an exponentially complex (non-polynomial complete, NPC) problem are discussed, and a critical comparison is made with previous polynomial (PC) theories. The predictions are successful for the superfamily of all ceramics, including new non-cuprates based on FeAs in place of CuO2.

Density crosslink study of gamma irradiated LDPE predicted by gel-fraction, swelling and glass transition temperature characterization

International Nuclear Information System (INIS)

Cardoso, Elisabeth C.L.; Scagliusi, Sandra R.; Moraes, Guilherme F.; Ono, Lilian S.; Parra, D.F.; Lugao, Ademar B.

2011-01-01

Experimental results showed that the crosslink density of polymeric stocks may be predicted from values of gel content based on the reactive portion of the stocks, that is, exclusive of plasticizers and fillers. Where entanglements may be neglected, the crosslink density is directly proportional to functions of the gel and sol contents. In order to predict the behavior of carbon-chain polymers exposed to ionizing radiation, an empirical rule can be used. According to this rule, polymers containing a hydrogen atom at each carbon atom predominantly undergo crosslinking. During irradiation, chain scission occurs simultaneously and competitively with crosslinking, the end result being determined by the ratio of the yields of the two reactions. The ratio of crosslinking to scission depends basically on factors including total irradiation dose, dose rate and the presence of oxygen. The glass transition temperature (Tg), temperature below which the polymer segments do not have sufficient energy to move past one another, marks the onset of segmental mobility for a polymer. Properties such as melt index, melt strength, crystallinity, glass transition, gel fraction, swelling ratio and elasticity modulus were assessed in LDPE (2.6 g.10 min -1 melt index) gamma irradiated within a 10, 15, 20 and 30 kGy and results obtained were further discussed prior conclusion. (author)

Functional aspects of distal oesophageal spasm: the role of onset velocity and contraction amplitude on bolus transit

Science.gov (United States)

Pohl, Daniel; Ciolino, Jody; Roberts, Jason; Savarino, Edoardo; Freeman, Janice; Nietert, Paul J; Tutuian, Radu; Castell, Donald

2012-01-01

Background Distal oesophageal spasm (DES) is a rare and under-investigated motility abnormality. Recent studies indicate effective bolus transit in varying percentages of DES patients. Aim Explore functional aspects including contraction onset velocity and contraction amplitude cut-off values for simultaneous contractions to predict complete bolus transit Methods We re-examined data from 107 impedance-manometry recordings with a diagnosis of DES. Receiver operating characteristic (ROC) analysis was conducted, regarding effects of onset velocity on bolus transit taking into account distal oesophageal amplitude (DEA) and correcting for intra-individual repeated measures. Results Mean area under the ROC curve for saline and viscous swallows were 0.84±0.05 and 0.84±0.04, respectively. Velocity criteria of >30cm/s when DEA>100mmHg and 8cm/s when DEADEA>100mmHg and >7cm/s when DEAsensitivity of 75% and specificity of 80% to identify complete bolus transit. Using these criteria, final diagnosis changed in 44.9% of patients. Abnormal bolus transit was observed in 50.9% of newly diagnosed DES patients versus 7.5% of patients classified as normal. DES patients with DEA>100mmHg suffered twice as often from chest pain than those with DEA<100mmHg. Conclusion The proposed velocity cut-offs for diagnosing distal oesophageal spasm improve the ability to identify patients with spasm and abnormal bolus transit. PMID:22475443

Structural predictions for Correlated Electron Materials Using the Functional Dynamical Mean Field Theory Approach

Science.gov (United States)

Haule, Kristjan

2018-04-01

The Dynamical Mean Field Theory (DMFT) in combination with the band structure methods has been able to address reach physics of correlated materials, such as the fluctuating local moments, spin and orbital fluctuations, atomic multiplet physics and band formation on equal footing. Recently it is getting increasingly recognized that more predictive ab-initio theory of correlated systems needs to also address the feedback effect of the correlated electronic structure on the ionic positions, as the metal-insulator transition is almost always accompanied with considerable structural distortions. We will review recently developed extension of merger between the Density Functional Theory (DFT) and DMFT method, dubbed DFT+ embedded DMFT (DFT+eDMFT), whichsuccessfully addresses this challenge. It is based on the stationary Luttinger-Ward functional to minimize the numerical error, it subtracts the exact double-counting of DFT and DMFT, and implements self-consistent forces on all atoms in the unit cell. In a few examples, we will also show how the method elucidated the important feedback effect of correlations on crystal structure in rare earth nickelates to explain the mechanism of the metal-insulator transition. The method showed that such feedback effect is also essential to understand the dynamic stability of the high-temperature body-centered cubic phase of elemental iron, and in particular it predicted strong enhancement of the electron-phonon coupling over DFT values in FeSe, which was very recently verified by pioneering time-domain experiment.

Wetting transitions: A functional renormalization-group approach

International Nuclear Information System (INIS)

Fisher, D.S.; Huse, D.A.

1985-01-01

A linear functional renormalization group is introduced as a framework in which to treat various wetting transitions of films on substrates. A unified treatment of the wetting transition in three dimensions with short-range interactions is given. The results of Brezin, Halperin, and Leibler in their three different regimes are reproduced along with new results on the multicritical behavior connecting the various regimes. In addition, the critical behavior as the coexistence curve is approached at complete wetting is analyzed. Wetting in the presence of long-range substrate-film interactions that fall off as power laws is also studied. The possible effects of the nonlinear terms in the renormalization group are examined briefly and it appears that they do not alter the critical behavior found using the truncated linear renormalization group

21 CFR 868.1890 - Predictive pulmonary-function value calculator.

Science.gov (United States)

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Predictive pulmonary-function value calculator... SERVICES (CONTINUED) MEDICAL DEVICES ANESTHESIOLOGY DEVICES Diagnostic Devices § 868.1890 Predictive pulmonary-function value calculator. (a) Identification. A predictive pulmonary-function value calculator is...

Prospective prediction of children's smoking transitions: role of parents' and older siblings' smoking.

Science.gov (United States)

Bricker, Jonathan B; Peterson, Arthur V; Leroux, Brian G; Andersen, M Robyn; Rajan, K Bharat; Sarason, Irwin G

2006-01-01

To use a novel social epidemic probability model to investigate longitudinally the extent to which parents' and older siblings' smoking predict children's smoking transitions. Parents' and older siblings' smoking status was assessed when children were in 3rd grade (baseline). Three smoking transitions were assessed over the period of child/adolescent smoking acquisition (up to 12th grade): (1) transition from never smoking to trying smoking, (2) transition from trying to monthly smoking and (3) transition from monthly to daily smoking. Forty Washington State school districts participating in the long term Hutchinson Smoking Prevention Project (HSPP). Participants were the 5520 families for whom data on both parents' and older siblings' baseline smoking status, as well as on children's smoking transitions, were available. The probability that a smoking parent influenced their child to make the first transition to trying smoking was 32% (95% CI: 27%, 36%); to make the second transition from trying to monthly smoking, 15% (95% CI: 10%, 19%); and to make the third transition from monthly to daily smoking, 28% (95% CI: 21%, 34%). The probability that an older sibling influenced a child to make the first transition to trying smoking was 29% (95% CI: 17%, 39%); to make the second transition from trying to monthly smoking, 0% (95% CI: 0%, 8%); and to make the third transition from monthly to daily smoking, 20% (95% CI: 4%, 33%). In contrast to previous research, the results provide new evidence suggesting that family smoking influences both initiation and escalation of children's smoking. Results also quantify, in terms of probabilities, the importance of parents' and older siblings' smoking on children's three major smoking transitions. Parents' smoking, as well as older siblings' smoking, are important behaviors to target in preventing adolescents from making smoking transitions.

Conserved Functional Motifs and Homology Modeling to Predict Hidden Moonlighting Functional Sites

KAUST Repository

Wong, Aloysius Tze

2015-06-09

Moonlighting functional centers within proteins can provide them with hitherto unrecognized functions. Here, we review how hidden moonlighting functional centers, which we define as binding sites that have catalytic activity or regulate protein function in a novel manner, can be identified using targeted bioinformatic searches. Functional motifs used in such searches include amino acid residues that are conserved across species and many of which have been assigned functional roles based on experimental evidence. Molecules that were identified in this manner seeking cyclic mononucleotide cyclases in plants are used as examples. The strength of this computational approach is enhanced when good homology models can be developed to test the functionality of the predicted centers in silico, which, in turn, increases confidence in the ability of the identified candidates to perform the predicted functions. Computational characterization of moonlighting functional centers is not diagnostic for catalysis but serves as a rapid screening method, and highlights testable targets from a potentially large pool of candidates for subsequent in vitro and in vivo experiments required to confirm the functionality of the predicted moonlighting centers.

Conserved Functional Motifs and Homology Modeling to Predict Hidden Moonlighting Functional Sites

KAUST Repository

Wong, Aloysius Tze; Gehring, Christoph A; Irving, Helen R.

2015-01-01

Moonlighting functional centers within proteins can provide them with hitherto unrecognized functions. Here, we review how hidden moonlighting functional centers, which we define as binding sites that have catalytic activity or regulate protein function in a novel manner, can be identified using targeted bioinformatic searches. Functional motifs used in such searches include amino acid residues that are conserved across species and many of which have been assigned functional roles based on experimental evidence. Molecules that were identified in this manner seeking cyclic mononucleotide cyclases in plants are used as examples. The strength of this computational approach is enhanced when good homology models can be developed to test the functionality of the predicted centers in silico, which, in turn, increases confidence in the ability of the identified candidates to perform the predicted functions. Computational characterization of moonlighting functional centers is not diagnostic for catalysis but serves as a rapid screening method, and highlights testable targets from a potentially large pool of candidates for subsequent in vitro and in vivo experiments required to confirm the functionality of the predicted moonlighting centers.

Correlation functions in first-order phase transitions

Science.gov (United States)

Garrido, V.; Crespo, D.

1997-09-01

Most of the physical properties of systems underlying first-order phase transitions can be obtained from the spatial correlation functions. In this paper, we obtain expressions that allow us to calculate all the correlation functions from the droplet size distribution. Nucleation and growth kinetics is considered, and exact solutions are obtained for the case of isotropic growth by using self-similarity properties. The calculation is performed by using the particle size distribution obtained by a recently developed model (populational Kolmogorov-Johnson-Mehl-Avrami model). Since this model is less restrictive than that used in previously existing theories, the result is that the correlation functions can be obtained for any dependence of the kinetic parameters. The validity of the method is tested by comparison with the exact correlation functions, which had been obtained in the available cases by the time-cone method. Finally, the correlation functions corresponding to the microstructure developed in partitioning transformations are obtained.

Prediction Error During Functional and Non-Functional Action Sequences

DEFF Research Database (Denmark)

Nielbo, Kristoffer Laigaard; Sørensen, Jesper

2013-01-01

recurrent networks were made and the results are presented in this article. The simulations show that non-functional action sequences do indeed increase prediction error, but that context representations, such as abstract goal information, can modulate the error signal considerably. It is also shown...... that the networks are sensitive to boundaries between sequences in both functional and non-functional actions....

The function and failure of sensory predictions.

Science.gov (United States)

Bansal, Sonia; Ford, Judith M; Spering, Miriam

2018-04-23

Humans and other primates are equipped with neural mechanisms that allow them to automatically make predictions about future events, facilitating processing of expected sensations and actions. Prediction-driven control and monitoring of perceptual and motor acts are vital to normal cognitive functioning. This review provides an overview of corollary discharge mechanisms involved in predictions across sensory modalities and discusses consequences of predictive coding for cognition and behavior. Converging evidence now links impairments in corollary discharge mechanisms to neuropsychiatric symptoms such as hallucinations and delusions. We review studies supporting a prediction-failure hypothesis of perceptual and cognitive disturbances. We also outline neural correlates underlying prediction function and failure, highlighting similarities across the visual, auditory, and somatosensory systems. In linking basic psychophysical and psychophysiological evidence of visual, auditory, and somatosensory prediction failures to neuropsychiatric symptoms, our review furthers our understanding of disease mechanisms. © 2018 New York Academy of Sciences.

Microbial Functional Gene Diversity Predicts Groundwater Contamination and Ecosystem Functioning

Science.gov (United States)

Zhang, Ping; Wu, Linwei; Rocha, Andrea M.; Shi, Zhou; Wu, Bo; Qin, Yujia; Wang, Jianjun; Yan, Qingyun; Curtis, Daniel; Ning, Daliang; Van Nostrand, Joy D.; Wu, Liyou; Watson, David B.; Adams, Michael W. W.; Alm, Eric J.; Adams, Paul D.; Arkin, Adam P.

2018-01-01

ABSTRACT Contamination from anthropogenic activities has significantly impacted Earth’s biosphere. However, knowledge about how environmental contamination affects the biodiversity of groundwater microbiomes and ecosystem functioning remains very limited. Here, we used a comprehensive functional gene array to analyze groundwater microbiomes from 69 wells at the Oak Ridge Field Research Center (Oak Ridge, TN), representing a wide pH range and uranium, nitrate, and other contaminants. We hypothesized that the functional diversity of groundwater microbiomes would decrease as environmental contamination (e.g., uranium or nitrate) increased or at low or high pH, while some specific populations capable of utilizing or resistant to those contaminants would increase, and thus, such key microbial functional genes and/or populations could be used to predict groundwater contamination and ecosystem functioning. Our results indicated that functional richness/diversity decreased as uranium (but not nitrate) increased in groundwater. In addition, about 5.9% of specific key functional populations targeted by a comprehensive functional gene array (GeoChip 5) increased significantly (P contamination and ecosystem functioning. This study indicates great potential for using microbial functional genes to predict environmental contamination and ecosystem functioning. PMID:29463661

A longitudinal examination of factors predicting anxiety during the transition to middle school

Science.gov (United States)

Grills-Taquechel, Amie E.; Norton, Peter; Ollendick, Thomas H.

2010-01-01

The transition from elementary to middle or junior high school is commonly regarded as a period of stress and turmoil for young adolescents, and has been associated with changes in anxiety and other psychological problems. However, less is known about risk and resilience factors that may predict these changes. This study examined changes in anxiety, as well as predictors of these changes among 77, predominantly Caucasian (88%), male and female (52%) adolescents from Grades 6 to 8. Repeated measures analysis of variance was conducted to examine the predicted grade and gender differences. Multiple regression analyses were conducted to examine the prediction of eighth grade anxiety symptoms by sixth grade self-worth, perceived social acceptance, and social support, as well as the potential moderating role of gender in these relations. Results suggested a significant decrease in anxiety, particularly social anxiety, over this period for boys but not girls. Examination of predictors of changes in anxiety suggested that, in general, global self-worth, social acceptance, and gender were each associated with overall and social anxiety. Findings are integrated with extant literature on developmental changes associated with anxiety and school transitions and clinical implications of these findings are discussed. PMID:20711893

Experimental mapping of the absolute magnitude of the transition dipole moment function μe(R) of the Na2 AΣ1u+-XΣ1g+ transition

Science.gov (United States)

Ahmed, E. H.; Qi, P.; Beser, B.; Bai, J.; Field, R. W.; Huennekens, J. P.; Lyyra, A. M.

2008-05-01

The absolute magnitude of the transition dipole moment function μe(R) of the AΣ1u+-XΣ1g+ band system of Na2 was mapped experimentally over a relatively large range of internuclear distance R . The transition dipole moment matrix element of a set of rovibrational transitions between the AΣ1u+ and XΣ1g+ states was measured using the Autler-Townes effect. By employing the R -centroid approximation, or a fit to a polynomial function involving higher order R centroids, μe as a function of the internuclear distance was obtained. These Autler-Townes effect based measurements yield the absolute magnitude of μe , which can be used to test ab initio theoretical transition dipole moment functions or to “normalize” experimental transition moment functions obtained from intensity measurements, which in general give only the relative behavior of μe(R) .

Variational predictions of transition energies and electron affinities: He and Li ground states and Li, Be, and Mg core-excited states

International Nuclear Information System (INIS)

Fischer, C.F.

1990-01-01

Variational procedures for predicting energy differences of many-electron systems are investigated. Several different calculations for few-electron systems are considered that illustrate the problems encountered when a many-electron system is modeled as a core plus outer electrons. It is shown that sequences of increasingly more accurate calculations for outer correlation may converge yielding wrong transition energies. At the same time, accurate core-polarization calculations overestimate the binding energy, requiring a core-valence correction. For the high-spin, core-excited states of Li, it was found that outer correlation only predicted electron affinities as accurately as full-correlation studies. This observation suggested a prediction of the core-excited 4 P endash 4 S transition in Be - , based on observed 3 P 0 endash 3 P transition energies of the neutral species, predicted electron affinities including only outer correlation, and a core-valence correction, that is shown to be in good agreement with experiment. A similar calculation for Mg - predicts a wavelength of 2895.1 A for this transition

Roles for text mining in protein function prediction.

Science.gov (United States)

Verspoor, Karin M

2014-01-01

The Human Genome Project has provided science with a hugely valuable resource: the blueprints for life; the specification of all of the genes that make up a human. While the genes have all been identified and deciphered, it is proteins that are the workhorses of the human body: they are essential to virtually all cell functions and are the primary mechanism through which biological function is carried out. Hence in order to fully understand what happens at a molecular level in biological organisms, and eventually to enable development of treatments for diseases where some aspect of a biological system goes awry, we must understand the functions of proteins. However, experimental characterization of protein function cannot scale to the vast amount of DNA sequence data now available. Computational protein function prediction has therefore emerged as a problem at the forefront of modern biology (Radivojac et al., Nat Methods 10(13):221-227, 2013).Within the varied approaches to computational protein function prediction that have been explored, there are several that make use of biomedical literature mining. These methods take advantage of information in the published literature to associate specific proteins with specific protein functions. In this chapter, we introduce two main strategies for doing this: association of function terms, represented as Gene Ontology terms (Ashburner et al., Nat Genet 25(1):25-29, 2000), to proteins based on information in published articles, and a paradigm called LEAP-FS (Literature-Enhanced Automated Prediction of Functional Sites) in which literature mining is used to validate the predictions of an orthogonal computational protein function prediction method.

Rumination prospectively predicts executive functioning impairments in adolescents.

Science.gov (United States)

Connolly, Samantha L; Wagner, Clara A; Shapero, Benjamin G; Pendergast, Laura L; Abramson, Lyn Y; Alloy, Lauren B

2014-03-01

The current study tested the resource allocation hypothesis, examining whether baseline rumination or depressive symptom levels prospectively predicted deficits in executive functioning in an adolescent sample. The alternative to this hypothesis was also evaluated by testing whether lower initial levels of executive functioning predicted increases in rumination or depressive symptoms at follow-up. A community sample of 200 adolescents (ages 12-13) completed measures of depressive symptoms, rumination, and executive functioning at baseline and at a follow-up session approximately 15 months later. Adolescents with higher levels of baseline rumination displayed decreases in selective attention and attentional switching at follow-up. Rumination did not predict changes in working memory or sustained and divided attention. Depressive symptoms were not found to predict significant changes in executive functioning scores at follow-up. Baseline executive functioning was not associated with change in rumination or depression over time. Findings partially support the resource allocation hypothesis that engaging in ruminative thoughts consumes cognitive resources that would otherwise be allocated towards difficult tests of executive functioning. Support was not found for the alternative hypothesis that lower levels of initial executive functioning would predict increased rumination or depressive symptoms at follow-up. Our study is the first to find support for the resource allocation hypothesis using a longitudinal design and an adolescent sample. Findings highlight the potentially detrimental effects of rumination on executive functioning during early adolescence. Copyright © 2013 Elsevier Ltd. All rights reserved.

Normal mode-guided transition pathway generation in proteins.

Directory of Open Access Journals (Sweden)

Byung Ho Lee

Full Text Available The biological function of proteins is closely related to its structural motion. For instance, structurally misfolded proteins do not function properly. Although we are able to experimentally obtain structural information on proteins, it is still challenging to capture their dynamics, such as transition processes. Therefore, we need a simulation method to predict the transition pathways of a protein in order to understand and study large functional deformations. Here, we present a new simulation method called normal mode-guided elastic network interpolation (NGENI that performs normal modes analysis iteratively to predict transition pathways of proteins. To be more specific, NGENI obtains displacement vectors that determine intermediate structures by interpolating the distance between two end-point conformations, similar to a morphing method called elastic network interpolation. However, the displacement vector is regarded as a linear combination of the normal mode vectors of each intermediate structure, in order to enhance the physical sense of the proposed pathways. As a result, we can generate more reasonable transition pathways geometrically and thermodynamically. By using not only all normal modes, but also in part using only the lowest normal modes, NGENI can still generate reasonable pathways for large deformations in proteins. This study shows that global protein transitions are dominated by collective motion, which means that a few lowest normal modes play an important role in this process. NGENI has considerable merit in terms of computational cost because it is possible to generate transition pathways by partial degrees of freedom, while conventional methods are not capable of this.

Efficacy of surface error corrections to density functional theory calculations of vacancy formation energy in transition metals.

Science.gov (United States)

Nandi, Prithwish Kumar; Valsakumar, M C; Chandra, Sharat; Sahu, H K; Sundar, C S

2010-09-01

We calculate properties like equilibrium lattice parameter, bulk modulus and monovacancy formation energy for nickel (Ni), iron (Fe) and chromium (Cr) using Kohn-Sham density functional theory (DFT). We compare the relative performance of local density approximation (LDA) and generalized gradient approximation (GGA) for predicting such physical properties for these metals. We also make a relative study between two different flavors of GGA exchange correlation functional, namely PW91 and PBE. These calculations show that there is a discrepancy between DFT calculations and experimental data. In order to understand this discrepancy in the calculation of vacancy formation energy, we introduce a correction for the surface intrinsic error corresponding to an exchange correlation functional using the scheme implemented by Mattsson et al (2006 Phys. Rev. B 73 195123) and compare the effectiveness of the correction scheme for Al and the 3d transition metals.

Acute Pancreatitis as a Model to Predict Transition of Systemic Inflammation to Organ Failure in Trauma and Critical Illness

Science.gov (United States)

2017-10-01

models ); • clinical interventions; • new business creation; and • other. Nothing to report. Nothing to report. Nothing to report. 17...AWARD NUMBER: W81XWH-14-1-0376 TITLE: Acute Pancreatitis as a Model to Predict Transition of Systemic Inflammation to Organ Failgure in Trauma...COVERED 22 Sep 2016 - 21 Sep 2017 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Acute Pancreatitis as a Model to Predict Transition of Systemic

Joint resummation for pion wave function and pion transition form factor

Energy Technology Data Exchange (ETDEWEB)

Li, Hsiang-nan [Institute of Physics, Academia Sinica,Academia Rd., Taipei, Taiwan 115 (China); Department of Physics, National Cheng-Kung University,University Rd., Tainan, Taiwan 701 (China); Department of Physics, National Tsing-Hua University,Kuang-Fu Rd., Hsinchu, Taiwan 300 (China); Shen, Yue-Long [College of Information Science and Engineering, Ocean University of China,Songling Rd, Qingdao, Shandong 266100 (China); Wang, Yu-Ming [Institut für Theoretische Teilchenphysik und Kosmologie RWTH Aachen,Physikzentrum Otto-Blumenthal-Straße, D-52056 Aachen (Germany); Physik Department T31, Technische Universität München,James-Franck-Straße, D-85748 Garching (Germany)

2014-01-03

We construct an evolution equation for the pion wave function in the k{sub T} factorization formalism, whose solution sums the mixed logarithm ln xln k{sub T} to all orders, with x (k{sub T}) being a parton momentum fraction (transverse momentum). This joint resummation induces strong suppression of the pion wave function in the small x and large b regions, b being the impact parameter conjugate to k{sub T}, and improves the applicability of perturbative QCD to hard exclusive processes. The above effect is similar to those from the conventional threshold resummation for the double logarithm ln{sup 2} x and the conventional k{sub T} resummation for ln{sup 2} k{sub T}. Combining the evolution equation for the hard kernel, we are able to organize all large logarithms in the γ{sup ∗}π{sup 0}→γ scattering, and to establish a scheme-independent k{sub T} factorization formula. It will be shown that the significance of next-to-leading-order contributions and saturation behaviors of this process at high energy differ from those under the conventional resummations. It implies that QCD logarithmic corrections to a process must be handled appropriately, before its data are used to extract a hadron wave function. Our predictions for the involved pion transition form factor, derived under the joint resummation and the input of a non-asymptotic pion wave function with the second Gegenbauer moment a{sub 2}=0.05, match reasonably well the CLEO, BaBar, and Belle data.

Analytic properties of the Ruelle ζ-function for mean field models of phase transition

International Nuclear Information System (INIS)

Hallerberg, Sarah; Just, Wolfram; Radons, Guenter

2005-01-01

We evaluate by analytical means the Ruelle ζ-function for a spin model with global coupling. The implications of the ferromagnetic phase transitions for the analytical properties of the ζ-function are discussed in detail. In the paramagnetic phase the ζ-function develops a single branch point. In the low-temperature regime two branch points appear which correspond to the ferromagnetic state and the metastable state. The results are typical for any Ginsburg-Landau-type phase transition

Characterization of the glass transition of water predicted by molecular dynamics simulations using nonpolarizable intermolecular potentials.

Science.gov (United States)

Kreck, Cara A; Mancera, Ricardo L

2014-02-20

Molecular dynamics simulations allow detailed study of the experimentally inaccessible liquid state of supercooled water below its homogeneous nucleation temperature and the characterization of the glass transition. Simple, nonpolarizable intermolecular potentials are commonly used in classical molecular dynamics simulations of water and aqueous systems due to their lower computational cost and their ability to reproduce a wide range of properties. Because the quality of these predictions varies between the potentials, the predicted glass transition of water is likely to be influenced by the choice of potential. We have thus conducted an extensive comparative investigation of various three-, four-, five-, and six-point water potentials in both the NPT and NVT ensembles. The T(g) predicted from NPT simulations is strongly correlated with the temperature of minimum density, whereas the maximum in the heat capacity plot corresponds to the minimum in the thermal expansion coefficient. In the NVT ensemble, these points are instead related to the maximum in the internal pressure and the minimum of its derivative, respectively. A detailed analysis of the hydrogen-bonding properties at the glass transition reveals that the extent of hydrogen-bonds lost upon the melting of the glassy state is related to the height of the heat capacity peak and varies between water potentials.

SitesIdentify: a protein functional site prediction tool

Directory of Open Access Journals (Sweden)

Doig Andrew J

2009-11-01

Full Text Available Abstract Background The rate of protein structures being deposited in the Protein Data Bank surpasses the capacity to experimentally characterise them and therefore computational methods to analyse these structures have become increasingly important. Identifying the region of the protein most likely to be involved in function is useful in order to gain information about its potential role. There are many available approaches to predict functional site, but many are not made available via a publicly-accessible application. Results Here we present a functional site prediction tool (SitesIdentify, based on combining sequence conservation information with geometry-based cleft identification, that is freely available via a web-server. We have shown that SitesIdentify compares favourably to other functional site prediction tools in a comparison of seven methods on a non-redundant set of 237 enzymes with annotated active sites. Conclusion SitesIdentify is able to produce comparable accuracy in predicting functional sites to its closest available counterpart, but in addition achieves improved accuracy for proteins with few characterised homologues. SitesIdentify is available via a webserver at http://www.manchester.ac.uk/bioinformatics/sitesidentify/

Prediction of non-brittle fracture in the welded joint of C-Mn steel in the brittle-ductile transition domain; Prediction de la non-rupture fragile dans un joint soude en acier C-Mn dans le domaine de la transition fragile/ductile

Energy Technology Data Exchange (ETDEWEB)

Nguyen, Thai Ha

2009-11-15

This work concerns the nuclear safety, specifically the secondary circuit integrity of pressurized water reactors (PWR). The problem is that of the fracture of a thin tubular structure in ferritic steel with many welded joints. The ferritic steel and weld present a brittle/ductile tenacity transition. Moreover, the welds present geometry propitious to the appearance of fatigue cracks, due to vibrations and expansions. These cracks may cause the complete fracture of the structure. The objectives of this work are to establish a criterion of non-fracture by cleavage of thin welded structures in ferritic steel, applicable to actual structures. Therefore, the present study focuses on the fracture behaviour of welded thin structures in brittle/ductile transition. It aims at developing the threshold stress model initially proposed by Chapuliot, to predict the non-brittle-fracture of this welded structure. The model is identified for the welded joint in C-Mn steel for nuclear construction, specifically in the upper part of the transition. A threshold stress, below which the cleavage cannot take place, is identified using tensile tests at low temperature on axis-symmetrical notched specimens taken in welded joint. This threshold stress is used to define the threshold volume where the maximum principal stress exceeds the threshold stress during the test. The analysis by SEM of specimen fracture surfaces shows that the gross solidification molten zone in the weld is the most likely to cleave. The relation between the brittle fracture probability and the threshold volume in the gross solidification molten zone is established via a sensitivity function, using multi-materials simulations. The model thus identified is tested for the prediction of non-brittle-fracture of SENT specimens taken in the welded joint and tested in tension. The results obtained are encouraging with regards to the transferability of the model to the actual structure. (author)

Functions, Operations, and Decalage in the Development of Transitivity.

Science.gov (United States)

Chapman, Michael; Lindenberger, Ulman

1988-01-01

Tested the hypothesis that some attempts to reduce the performance demands of concrete Piagetian operational tasks may have allowed children to solve those tasks with preoperational functions. Administered two previously used versions of the transitivity task for length and weight to 120 children six- to nine-years-old. The second version was…

PREDICTION OF THERMODYNAMIC PROPERTIES OF COMPLEX FLUIDS

International Nuclear Information System (INIS)

Marc Donohue

2006-01-01

The goal of this research has been to generalize Density Functional Theory (DFT) for complex molecules, i.e. molecules whose size, shape, and interaction energies cause them to show significant deviations from mean-field behavior. We considered free energy functionals and minimized them for systems with different geometries and dimensionalities including confined fluids (such as molecular layers on surfaces and molecules in nano-scale pores), systems with directional interactions and order-disorder transitions, amphiphilic dimers, block copolymers, and self-assembled nano-structures. The results of this procedure include equations of equilibrium for these systems and the development of computational tools for predicting phase transitions and self-assembly in complex fluids. DFT was developed for confined fluids. A new phenomenon, surface compression of confined fluids, was predicted theoretically and confirmed by existing experimental data and by simulations. The strong attraction to a surface causes adsorbate molecules to attain much higher densities than that of a normal liquid. Under these conditions, adsorbate molecules are so compressed that they repel each other. This phenomenon is discussed in terms of experimental data, results of Monte Carlo simulations, and theoretical models. Lattice version of DFT was developed for modeling phase transitions in adsorbed phase including wetting, capillary condensation, and ordering. Phase behavior of amphiphilic dimers on surfaces and in solutions was modeled using lattice DFT and Monte Carlo simulations. This study resulted in predictive models for adsorption isotherms and for local density distributions in solutions. We have observed a wide variety of phase behavior for amphiphilic dimers, including formation of lamellae and micelles. Block copolymers were modeled in terms of configurational probabilities and in the approximation of random mixing entropy. Probabilities of different orientations for the segments were

Transitioning to adolescence: how changes in child personality and overreactive parenting predict adolescent adjustment problems.

Science.gov (United States)

van den Akker, Alithe L; Deković, Maja; Prinzie, Peter

2010-01-01

The present study examined how changes in child Big Five personality characteristics and overreactive parenting during the transition from childhood to adolescence predict adolescent adjustment problems. The sample included 290 children, aged 8-9 years. At three moments, with 2-year intervals, mothers, fathers, and a teacher reported on the child's personality, and mothers and fathers reported on their parenting behavior. At the third measurement moment, mothers, fathers, and children reported on the child's adjustment problems. Rank-order stability of the personality dimensions and overreactive parenting were high. Univariate latent growth models revealed mean-level decreases for extraversion, conscientiousness, and imagination. Mean levels of benevolence, emotional stability, and overreactive parenting were stable. Multivariate latent growth models revealed that decreases in extraversion and emotional stability predicted internalizing problems, whereas decreases in benevolence, conscientiousness, and emotional stability predicted externalizing problems. Increases in overreactive parenting predicted externalizing, but not internalizing problems. The associations were similar for boys and girls. The results indicate that changes in child personality and overreactive parenting during the transition to adolescence are associated with adolescent adjustment problems. Overall, child personality was more important than overreactive parenting, and children were more likely to "act out" than to "withdraw" in reaction to overreactive parenting.

Synthetic receiver function profiles through the upper mantle and the transition zone for upwelling scenarios

Science.gov (United States)

Nagel, Thorsten; Düsterhöft, Erik; Schiffer, Christian

2017-04-01

We investigate the signature relevant mantle lithologies leave in the receiver function record for different adiabatic thermal gradients down to 800 kilometers depth. The parameter space is chosen to target the visibility of upwelling mantle (a plume). Seismic velocities for depleted mantle, primitive mantle, and three pyroxenites are extracted from thermodynamically calculated phases diagrams, which also provide the adiabatic decompression paths. Results suggest that compositional variations, i.e. the presence or absence of considerable amounts of pyroxenites in primitive mantle should produce a clear footprint while horizontal differences in thermal gradients for similar compositions might be more subtle. Peridotites best record the classic discontinuities at around 410 and 650 kilometers depth, which are associated with the olivin-wadsleyite and ringwoodite-perovskite transitions, respectively. Pyroxenites, instead, show the garnet-perovskite transition below 700 kilometers depth and SiO2-supersaturated compositions like MORB display the coesite-stishovite transition between 300 and 340 kilometers depth. The latter shows the strongest temperature-depth dependency of all significant transitions potentially allowing to infer information about the thermal state if the mantle contains a sufficient fraction of MORB-like compositions. For primitive and depleted mantle compositions, the olivin-wadsleyite transition shows a certain temperature-depth dependency reflected in slightly larger delay times for higher thermal gradients. The lower-upper-mantle discontinuity, however, is predicted to display larger delay times for higher thermal gradients although the associated assemblage transition occurs at shallower depths thus requiring a very careful depth migration if a thermal anomaly should be recognized. This counterintuitive behavior results from the downward replacement of the assemblage wadsleyite+garnet with the assemblage garnet+periclase at high temperatures

Analysis of the development and prediction of the rate of unemployment in selected countries with market and transitive economy

Directory of Open Access Journals (Sweden)

Erich Maca

2004-01-01

Full Text Available The paper is aimed at the presentation of findings achieved in the study of the dynamics and trends of the rate of unemployment in selected countries with market and transitive economy in the reference period 1995–2001. In addition to the description of developmental trends of analysed time series by means of trend functions of linear, quadratic, exponential, logarithmic, power and inverse types their informative ability was verified as a starting base for the realization of point prediction of investigated events for 2005. With given 95% probability, minimum and maximum values are determined of the evaluated macroeconomic indicator for a defined time horizon.

A genome-wide gene function prediction resource for Drosophila melanogaster.

Directory of Open Access Journals (Sweden)

Han Yan

2010-08-01

Full Text Available Predicting gene functions by integrating large-scale biological data remains a challenge for systems biology. Here we present a resource for Drosophila melanogaster gene function predictions. We trained function-specific classifiers to optimize the influence of different biological datasets for each functional category. Our model predicted GO terms and KEGG pathway memberships for Drosophila melanogaster genes with high accuracy, as affirmed by cross-validation, supporting literature evidence, and large-scale RNAi screens. The resulting resource of prioritized associations between Drosophila genes and their potential functions offers a guide for experimental investigations.

Higher-order predictions for splitting functions and coefficient functions from physical evolution kernels

International Nuclear Information System (INIS)

Vogt, A; Soar, G.; Vermaseren, J.A.M.

2010-01-01

We have studied the physical evolution kernels for nine non-singlet observables in deep-inelastic scattering (DIS), semi-inclusive e + e - annihilation and the Drell-Yan (DY) process, and for the flavour-singlet case of the photon- and heavy-top Higgs-exchange structure functions (F 2 , F φ ) in DIS. All known contributions to these kernels show an only single-logarithmic large-x enhancement at all powers of (1-x). Conjecturing that this behaviour persists to (all) higher orders, we have predicted the highest three (DY: two) double logarithms of the higher-order non-singlet coefficient functions and of the four-loop singlet splitting functions. The coefficient-function predictions can be written as exponentiations of 1/N-suppressed contributions in Mellin-N space which, however, are less predictive than the well-known exponentiation of the ln k N terms. (orig.)

Phase Transition between Black and Blue Phosphorenes: A Quantum Monte Carlo Study

Science.gov (United States)

Li, Lesheng; Yao, Yi; Reeves, Kyle; Kanai, Yosuke

Phase transition of the more common black phosphorene to blue phosphorene is of great interest because they are predicted to exhibit unique electronic and optical properties. However, these two phases are predicted to be separated by a rather large energy barrier. In this work, we study the transition pathway between black and blue phosphorenes by using the variable cell nudge elastic band method combined with density functional theory calculation. We show how diffusion quantum Monte Carlo method can be used for determining the energetics of the phase transition and demonstrate the use of two approaches for removing finite-size errors. Finally, we predict how applied stress can be used to control the energetic balance between these two different phases of phosphorene.

Prediction of pressure induced structural phase transitions and internal mode frequency changes in solid N2+

International Nuclear Information System (INIS)

Etters, R.D.; Kobashi, K.; Chandrasekharan, V.

1983-01-01

A rhombohedral distortion of the Pm3n structure is introduced which shows that a low temperature phase transition occurs from P4 2 /mnm into the R3c calcite structure at P approx. = 19.2 kbar with a volume change of 0.125 cm 3 /mole. This transition agrees with recent Raman scattering measurements. Another transition from R3c into R3m is predicted at P approx. = 67.5 kbar, with a volume change of 0.1 cm 3 /mole. The pressure dependence of the intramolecular mode frequencies for the R3c structure is in reasonably good agreement with the two main branches observed experimentally

COPRED: prediction of fold, GO molecular function and functional residues at the domain level.

Science.gov (United States)

López, Daniel; Pazos, Florencio

2013-07-15

Only recently the first resources devoted to the functional annotation of proteins at the domain level started to appear. The next step is to develop specific methodologies for predicting function at the domain level based on these resources, and to implement them in web servers to be used by the community. In this work, we present COPRED, a web server for the concomitant prediction of fold, molecular function and functional sites at the domain level, based on a methodology for domain molecular function prediction and a resource of domain functional annotations previously developed and benchmarked. COPRED can be freely accessed at http://csbg.cnb.csic.es/copred. The interface works in all standard web browsers. WebGL (natively supported by most browsers) is required for the in-line preview and manipulation of protein 3D structures. The website includes a detailed help section and usage examples. pazos@cnb.csic.es.

Predicting critical transitions in dynamical systems from time series using nonstationary probability density modeling.

Science.gov (United States)

Kwasniok, Frank

2013-11-01

A time series analysis method for predicting the probability density of a dynamical system is proposed. A nonstationary parametric model of the probability density is estimated from data within a maximum likelihood framework and then extrapolated to forecast the future probability density and explore the system for critical transitions or tipping points. A full systematic account of parameter uncertainty is taken. The technique is generic, independent of the underlying dynamics of the system. The method is verified on simulated data and then applied to prediction of Arctic sea-ice extent.

Critical temperature for shape transition in hot nuclei within covariant density functional theory

Science.gov (United States)

Zhang, W.; Niu, Y. F.

2018-05-01

Prompted by the simple proportional relation between critical temperature for pairing transition and pairing gap at zero temperature, we investigate the relation between critical temperature for shape transition and ground-state deformation by taking even-even Cm-304286 isotopes as examples. The finite-temperature axially deformed covariant density functional theory with BCS pairing correlation is used. Since the Cm isotopes are the newly proposed nuclei with octupole correlations, we studied in detail the free energy surface, the Nilsson single-particle (s.p.) levels, and the components of s.p. levels near the Fermi level in 292Cm. Through this study, the formation of octupole equilibrium is understood by the contribution coming from the octupole driving pairs with Ω [N ,nz,ml] and Ω [N +1 ,nz±3 ,ml] for single-particle levels near the Fermi surfaces as it provides a good manifestation of the octupole correlation. Furthermore, the systematics of deformations, pairing gaps, and the specific heat as functions of temperature for even-even Cm-304286 isotopes are discussed. Similar to the relation between the critical pairing transition temperature and the pairing gap at zero temperature Tc=0.6 Δ (0 ) , a proportional relation between the critical shape transition temperature and the deformation at zero temperature Tc=6.6 β (0 ) is found for both octupole shape transition and quadrupole shape transition for the isotopes considered.

Hybrid system prediction for the stock market: The case of transitional markets

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Ralević Nebojša

2017-01-01

Full Text Available The subject of this paper is the creation and testing of an enhanced fuzzy neural network backpropagation model for the prediction of stock market indexes, including the comparison with the traditional neural network backpropagation model. The objective of the research is to gather information concerning the possibilities of using the enhanced fuzzy neural network backpropagation model for the prediction of stock market indexes focusing on transitional markets. The methodology used involves the integration of fuzzified weights into the neural network. The research results will be beneficial both for the broader investment community and the academia, in terms of the application of the enhanced model in the investment decision-making, as well as in improving the knowledge in this subject matter.

Low-lying electronic states of the OH radical: potential energy curves, dipole moment functions, and transition probabilities

Energy Technology Data Exchange (ETDEWEB)

Qin, X.; Zhang, S. D. [Qufu Normal University, Qufu (China)

2014-12-15

The six doublet and the two quartet electronic states ({sup 2}Σ{sup +}(2), {sup 2}Σ{sup -}, {sup 2}Π(2), {sup 2}Δ, {sup 4}Σ{sup -}, and {sup 4}Π) of the OH radical have been studied using the multi-reference configuration interaction (MRCI) method where the Davidson correction, core-valence interaction and relativistic effect are considered with large basis sets of aug-cc-pv5z, aug-cc-pcv5z, and cc-pv5z-DK, respectively. Potential energy curves (PECs) and dipole moment functions are also calculated for these states for internuclear distances ranging from 0.05 nm to 0.80 nm. All possible vibrational levels and rotational constants for the bound state X{sup 2}Π and A{sup 2}Σ{sup +} of OH are predicted by numerical solving the radial Schroedinger equation through the Level program, and spectroscopic parameters, which are in good agreements with experimental results, are obtained. Transition dipole moments between the ground state X{sup 2}Π and other excited states are also computed using MRCI, and the transition probability, lifetime, and Franck-Condon factors for the A{sup 2}Σ{sup +} - X{sup 2}Π transition are discussed and compared with existing experimental values.

QCD dipole predictions for DIS and diffractive structure functions

International Nuclear Information System (INIS)

Royon, C.

1997-01-01

The proton structure function F 2 , the gluon density F G , and the longitudinal structure function F L are derived in the QCD dipole picture of BFKL dynamics. We use a three parameter fit to describe the 1994 H1 proton structure function F 2 data in the low x, moderate Q 2 range. Without any additional parameter, the gluon density and the longitudinal structure functions are predicted. The diffractive dissociation processes are also discussed within the same framework, and a new prediction for the proton diffractive structure function is obtained

Gene function prediction based on Gene Ontology Hierarchy Preserving Hashing.

Science.gov (United States)

Zhao, Yingwen; Fu, Guangyuan; Wang, Jun; Guo, Maozu; Yu, Guoxian

2018-02-23

Gene Ontology (GO) uses structured vocabularies (or terms) to describe the molecular functions, biological roles, and cellular locations of gene products in a hierarchical ontology. GO annotations associate genes with GO terms and indicate the given gene products carrying out the biological functions described by the relevant terms. However, predicting correct GO annotations for genes from a massive set of GO terms as defined by GO is a difficult challenge. To combat with this challenge, we introduce a Gene Ontology Hierarchy Preserving Hashing (HPHash) based semantic method for gene function prediction. HPHash firstly measures the taxonomic similarity between GO terms. It then uses a hierarchy preserving hashing technique to keep the hierarchical order between GO terms, and to optimize a series of hashing functions to encode massive GO terms via compact binary codes. After that, HPHash utilizes these hashing functions to project the gene-term association matrix into a low-dimensional one and performs semantic similarity based gene function prediction in the low-dimensional space. Experimental results on three model species (Homo sapiens, Mus musculus and Rattus norvegicus) for interspecies gene function prediction show that HPHash performs better than other related approaches and it is robust to the number of hash functions. In addition, we also take HPHash as a plugin for BLAST based gene function prediction. From the experimental results, HPHash again significantly improves the prediction performance. The codes of HPHash are available at: http://mlda.swu.edu.cn/codes.php?name=HPHash. Copyright © 2018 Elsevier Inc. All rights reserved.

Lung perfusion SPECT in predicting postoperative pulmonary function in lung cancer

International Nuclear Information System (INIS)

Hirose, Yoshiaki; Imaeda, Takeyoshi; Doi, Hidetaka; Kokubo, Mitsuharu; Sakai, Satoshi; Hirose, Hajime

1993-01-01

The aim of this prospective study is to evaluate the availability of preoperative perfusion SPECT in predicting postoperative pulmonary function following resection. Twenty-three patients with lung cancer who were candidates for lobectomy were investigated preoperatively with spirometry, x-ray computed tomography and 99m Tc-macroaggregated albumin SPECT. Their postoperative pulmonary functions were predicted with these examinations. The forced vital capacity and the forced expiratory volume in one second were selected as parameters for overall pulmonary function. The postoperative pulmonary function was predicted by the following formula: Predicted postoperative value=observed preoperative value x precent perfusion of the lung not to be resected. The patients were reinvestigated with spirometry at 3 months and 6 months after lobectomy, and the values obtained were statistically compared with the predicted values. Close relationships were found between predicted and observed forced vital capacity (r=0.87, p<0.001), and predicted and observed forced expiratory volume in one second (r=0.90, p<0.001). The accurate prediction of pulmonary function after lobectomy could be achieved by means of lung perfusion SPECT. (author)

QCD dipole prediction for dis and diffractive structure functions

International Nuclear Information System (INIS)

Royon, CH.

1996-01-01

The F 2 , F G , R = F L /F T proton structure functions are derived in the QCD dipole picture of BFKL dynamics. We get a three parameter fit describing the 1994 H1 proton structure function F 2 data in the low x, moderate Q 2 range. Without any additional parameter, the gluon density and the longitudinal structure functions are predicted. The diffractive dissociation processes are also discussed, and a new prediction for the proton diffractive structure function is obtained. (author)

Scoring function to predict solubility mutagenesis

Directory of Open Access Journals (Sweden)

Deutsch Christopher

2010-10-01

Full Text Available Abstract Background Mutagenesis is commonly used to engineer proteins with desirable properties not present in the wild type (WT protein, such as increased or decreased stability, reactivity, or solubility. Experimentalists often have to choose a small subset of mutations from a large number of candidates to obtain the desired change, and computational techniques are invaluable to make the choices. While several such methods have been proposed to predict stability and reactivity mutagenesis, solubility has not received much attention. Results We use concepts from computational geometry to define a three body scoring function that predicts the change in protein solubility due to mutations. The scoring function captures both sequence and structure information. By exploring the literature, we have assembled a substantial database of 137 single- and multiple-point solubility mutations. Our database is the largest such collection with structural information known so far. We optimize the scoring function using linear programming (LP methods to derive its weights based on training. Starting with default values of 1, we find weights in the range [0,2] so that predictions of increase or decrease in solubility are optimized. We compare the LP method to the standard machine learning techniques of support vector machines (SVM and the Lasso. Using statistics for leave-one-out (LOO, 10-fold, and 3-fold cross validations (CV for training and prediction, we demonstrate that the LP method performs the best overall. For the LOOCV, the LP method has an overall accuracy of 81%. Availability Executables of programs, tables of weights, and datasets of mutants are available from the following web page: http://www.wsu.edu/~kbala/OptSolMut.html.

Transitions between compound states of spherical nuclei

International Nuclear Information System (INIS)

Kadmenskii, S.G.; Markushev, V.P.; Furman, V.I.

1980-01-01

Wigner's statistical matrices are used to study the average reduced g widths and their dispersion for g transitions from a compound state c to another state f, with a lower excitation energy but of arbitrary complexity, for spherical nuclei. It is found that the Porter--Thomas distribution holds for the g widths for all cases of practical interest. In g transitions between compound states c and c' with E/sub g/< or =2 MeV, the most important transitions are M1 transitions involving the major many-quasiparticle components of state c and E1 transitions involving the minor components of state c. It is shown that the strength functions predicted by the various theories for M1 and E1 transitions between compound states with E/sub g/< or =2 MeV are similar. Preference is assigned to the M1-transition version because of experimental results on (n,ga) reactions with thermal and resonance neutrons

Growth hormone deficiency in the transition period: body composition and gonad function.

Science.gov (United States)

Balercia, G; Giovannini, L; Paggi, F; Spaziani, M; Tahani, N; Boscaro, M; Lenzi, A; Radicioni, A

2011-10-01

Recombinant GH therapy is normally administered to GH-deficient children in order to achieve a satisfactory height - the main target during childhood and adolescence. However, the role of GH does not end once final height has been reached, but continues during the so-called transition period. In this phase of life, the body undergoes several changes, both physical and psychological, that culminate in adulthood. During this period, GH has a part in numerous metabolic functions. These include the lipid profile, where it increases HDL and reduces LDL, with the global effect of cardiovascular protection. It also has important effects on body composition (improved muscle strength and lean body mass and reduced body fat), the achievement of proper peak bone density, and gonad maturation. Retesting during the transition period, involving measurement of IGF-I plus a provocative test (insulin tolerance test or GHRH + arginine test), is thus necessary to establish any persistent GH deficiency requiring additional replacement therapy. The close cooperation of the medical professionals involved in the patient's transition from a pediatric to an adult endocrinologist is essential. The aim of this review is to point out the main aspects of GH treatment on body composition, metabolic and gonad functions in the transition period.

Three-dimensional computed tomographic volumetry precisely predicts the postoperative pulmonary function.

Science.gov (United States)

Kobayashi, Keisuke; Saeki, Yusuke; Kitazawa, Shinsuke; Kobayashi, Naohiro; Kikuchi, Shinji; Goto, Yukinobu; Sakai, Mitsuaki; Sato, Yukio

2017-11-01

It is important to accurately predict the patient's postoperative pulmonary function. The aim of this study was to compare the accuracy of predictions of the postoperative residual pulmonary function obtained with three-dimensional computed tomographic (3D-CT) volumetry with that of predictions obtained with the conventional segment-counting method. Fifty-three patients scheduled to undergo lung cancer resection, pulmonary function tests, and computed tomography were enrolled in this study. The postoperative residual pulmonary function was predicted based on the segment-counting and 3D-CT volumetry methods. The predicted postoperative values were compared with the results of postoperative pulmonary function tests. Regarding the linear correlation coefficients between the predicted postoperative values and the measured values, those obtained using the 3D-CT volumetry method tended to be higher than those acquired using the segment-counting method. In addition, the variations between the predicted and measured values were smaller with the 3D-CT volumetry method than with the segment-counting method. These results were more obvious in COPD patients than in non-COPD patients. Our findings suggested that the 3D-CT volumetry was able to predict the residual pulmonary function more accurately than the segment-counting method, especially in patients with COPD. This method might lead to the selection of appropriate candidates for surgery among patients with a marginal pulmonary function.

Functional Impairment and Changes in Depression Subtypes for Women in STAR*D: A Latent Transition Analysis

Science.gov (United States)

Rothschild, Anthony J.; Lapane, Kate L.

2016-01-01

Abstract Objective: To characterize the association between functional impairment and major depression subtypes at baseline and to characterize changes in subtypes by functional impairment level in women receiving citalopram in level 1 of the Sequenced Treatment Alternatives to Relieve Depression trial. Method: Women who completed baseline and week 12 study visits were included. Items from the self-reported Quick Inventory of Depressive Symptomatology were used to define the latent depression subtypes. The Work and Social Adjustment Scale was used to classify baseline functional impairment. A latent transition analysis model provided estimates of the prevalence of subtype membership and transition probabilities by functional impairment level. Results: Of the 755 women included, 69% had major functional impairment at baseline. Regardless of functional impairment level, the subtypes were differentiated by depression severity, appetite changes, psychomotor disturbances, and insomnia. Sixty-seven percent of women with normal/significant functional impairment and 60% of women with major impairment were likely to transition to a symptom resolution subtype at week 12. Women with baseline major impairment who were in the severe with psychomotor agitation subtype at the beginning of the study were least likely to transition to the symptom resolution subtype (4% chance). Conclusions: Functional impairment level was related to both the baseline depression subtype and the likelihood of moving to a different subtype. These results underscore the need to incorporate not only depression symptoms but also functioning in the assessment and treatment of depression. PMID:26488110

Prediction of non-brittle fracture in the welded joint of C-Mn steel in the brittle-ductile transition domain

International Nuclear Information System (INIS)

Nguyen, Thai Ha

2009-11-01

This work concerns the nuclear safety, specifically the secondary circuit integrity of pressurized water reactors (PWR). The problem is that of the fracture of a thin tubular structure in ferritic steel with many welded joints. The ferritic steel and weld present a brittle/ductile tenacity transition. Moreover, the welds present geometry propitious to the appearance of fatigue cracks, due to vibrations and expansions. These cracks may cause the complete fracture of the structure. The objectives of this work are to establish a criterion of non-fracture by cleavage of thin welded structures in ferritic steel, applicable to actual structures. Therefore, the present study focuses on the fracture behaviour of welded thin structures in brittle/ductile transition. It aims at developing the threshold stress model initially proposed by Chapuliot, to predict the non-brittle-fracture of this welded structure. The model is identified for the welded joint in C-Mn steel for nuclear construction, specifically in the upper part of the transition. A threshold stress, below which the cleavage cannot take place, is identified using tensile tests at low temperature on axis-symmetrical notched specimens taken in welded joint. This threshold stress is used to define the threshold volume where the maximum principal stress exceeds the threshold stress during the test. The analysis by SEM of specimen fracture surfaces shows that the gross solidification molten zone in the weld is the most likely to cleave. The relation between the brittle fracture probability and the threshold volume in the gross solidification molten zone is established via a sensitivity function, using multi-materials simulations. The model thus identified is tested for the prediction of non-brittle-fracture of SENT specimens taken in the welded joint and tested in tension. The results obtained are encouraging with regards to the transferability of the model to the actual structure. (author)

Effect of aspect ratio on the laminar-to-turbulent transition in rectangular channel

International Nuclear Information System (INIS)

Wang Chang; Gao Puzhen; Tan Sichao; Xu Chao

2012-01-01

Highlights: ► Effect of aspect ratio on the transition Reynolds number in rectangular channel is studied. ► Prediction correlation for transition Reynolds number is proposed. ► The initiation location of flow transition is studied. - Abstract: The critical Reynolds number of the laminar-to-turbulent transition in the rectangular channel is investigated based on the energy gradient method. The results show that the critical Reynolds number decreases with the increasing aspect ratio. However, the relative location of laminar breakdown does not migrate significantly with the variation of the aspect ratio. In addition, a theoretical correlation as a function of the aspect ratio is proposed to calculate the transition Reynolds number, and the predicted values are in good agreement with the experimental data obtained in the published literatures.

Predictability of Genetic Interactions from Functional Gene Modules

Directory of Open Access Journals (Sweden)

Jonathan H. Young

2017-02-01

Full Text Available Characterizing genetic interactions is crucial to understanding cellular and organismal response to gene-level perturbations. Such knowledge can inform the selection of candidate disease therapy targets, yet experimentally determining whether genes interact is technically nontrivial and time-consuming. High-fidelity prediction of different classes of genetic interactions in multiple organisms would substantially alleviate this experimental burden. Under the hypothesis that functionally related genes tend to share common genetic interaction partners, we evaluate a computational approach to predict genetic interactions in Homo sapiens, Drosophila melanogaster, and Saccharomyces cerevisiae. By leveraging knowledge of functional relationships between genes, we cross-validate predictions on known genetic interactions and observe high predictive power of multiple classes of genetic interactions in all three organisms. Additionally, our method suggests high-confidence candidate interaction pairs that can be directly experimentally tested. A web application is provided for users to query genes for predicted novel genetic interaction partners. Finally, by subsampling the known yeast genetic interaction network, we found that novel genetic interactions are predictable even when knowledge of currently known interactions is minimal.

Time-Dependent Density Functional Theory Analysis of Triphenylamine-Functionalized Graphene Doped with Transition Metals for Photocatalytic Hydrogen Production.

Science.gov (United States)

Mota, Elder A V; Neto, Abel F G; Marques, Francisco C; Mota, Gunar V S; Martins, Marcelo G; Costa, Fabio L P; Borges, Rosivaldo S; Neto, Antonio M J C

2018-07-01

The electronic structures and optical properties of triphenylamine-functionalized graphene (G-TPA) doped with transition metals, using water as a solvent, were theoretically investigated to verify the efficiency of photocatalytic hydrogen production with the use of transition metals. This study was performed by Density Functional Theory and Time-dependent Density Functional Theory through Gaussian 09W software, adopting the B3LYP functional for all structures. The 6-31g(d) basis set was used for H, C and N atoms, and the LANL2DZ basis set for transition metals using the Effective Core Potentials method. Two approaches were adopted: (1) using single metallic dopants (Ni, Pd, Fe, Os and Pt) and (2) using combinations of Ni with the other dopants (NiPd, NiPt, NiFe and NiOs). The DOS spectra reveal an increase of accessible states in the valence shell, in addition to a gap decrease for all dopants. This doping also increases the absorption in the visible region of solar radiation where sunlight is most intense (400 nm to 700 nm), with additional absorption peaks. The results lead us to propose the G-TPA structures doped with Ni, Pd, Pt, NiPt or NiPd to be novel catalysts for the conversion of solar energy for photocatalytic hydrogen production, since they improve the absorption of solar energy in the range of interest for solar radiation; and act as reaction centers, reducing the required overpotential for hydrogen production from water.

Predicting Hydrologic Function With Aquatic Gene Fragments

Science.gov (United States)

Good, S. P.; URycki, D. R.; Crump, B. C.

2018-03-01

Recent advances in microbiology techniques, such as genetic sequencing, allow for rapid and cost-effective collection of large quantities of genetic information carried within water samples. Here we posit that the unique composition of aquatic DNA material within a water sample contains relevant information about hydrologic function at multiple temporal scales. In this study, machine learning was used to develop discharge prediction models trained on the relative abundance of bacterial taxa classified into operational taxonomic units (OTUs) based on 16S rRNA gene sequences from six large arctic rivers. We term this approach "genohydrology," and show that OTU relative abundances can be used to predict river discharge at monthly and longer timescales. Based on a single DNA sample from each river, the average Nash-Sutcliffe efficiency (NSE) for predicted mean monthly discharge values throughout the year was 0.84, while the NSE for predicted discharge values across different return intervals was 0.67. These are considerable improvements over predictions based only on the area-scaled mean specific discharge of five similar rivers, which had average NSE values of 0.64 and -0.32 for seasonal and recurrence interval discharge values, respectively. The genohydrology approach demonstrates that genetic diversity within the aquatic microbiome is a large and underutilized data resource with benefits for prediction of hydrologic function.

Role of Symmetry Breaking on the Optical Transitions in Lead-Salt Quantum Dots

KAUST Repository

Nootz, Gero

2010-09-08

The influence of quantum confinement on the one- and two-photon absorption spectra (1PA and 2PA) of PbS and PbSe semiconductor quantum dots (QDs) is investigated. The results show 2PA peaks at energies where only 1PA transitions are predicted and 1PA peaks where only 2PA transitions are predicted by the often used isotropic k•p four-band envelope function formalism. The first experimentally identified two-photon absorption peak coincides with the energy of the first one photon allowed transition. This first two-photon peak cannot be explained by band anisotropy, verifying that the inversion symmetry of the wave functions is broken and relaxation of the parity selection rules has to be taken into account to explain optical transitions in lead-salt QDs. Thus, while the band anisotropy of the bulk semiconductor plays a role in the absorption spectra, especially for the more anisotropic PbSe QDs, a complete model of the absorption spectra, for both 1PA and 2PA, must also include symmetry breaking of the quantum confined wave functions. These studies clarify the controversy of the origin of spectral features in lead-salt QDs. © 2010 American Chemical Society.

Role of Symmetry Breaking on the Optical Transitions in Lead-Salt Quantum Dots

KAUST Repository

Nootz, Gero; Padilha, Lazaro A.; Olszak, Peter D.; Webster, Scott; Hagan, David J.; Van Stryland, Eric W.; Levina, Larissa; Sukhovatkin, Vlad; Brzozowski, Lukasz; Sargent, Edward H.

2010-01-01

The influence of quantum confinement on the one- and two-photon absorption spectra (1PA and 2PA) of PbS and PbSe semiconductor quantum dots (QDs) is investigated. The results show 2PA peaks at energies where only 1PA transitions are predicted and 1PA peaks where only 2PA transitions are predicted by the often used isotropic k•p four-band envelope function formalism. The first experimentally identified two-photon absorption peak coincides with the energy of the first one photon allowed transition. This first two-photon peak cannot be explained by band anisotropy, verifying that the inversion symmetry of the wave functions is broken and relaxation of the parity selection rules has to be taken into account to explain optical transitions in lead-salt QDs. Thus, while the band anisotropy of the bulk semiconductor plays a role in the absorption spectra, especially for the more anisotropic PbSe QDs, a complete model of the absorption spectra, for both 1PA and 2PA, must also include symmetry breaking of the quantum confined wave functions. These studies clarify the controversy of the origin of spectral features in lead-salt QDs. © 2010 American Chemical Society.

Predicting functional upstream open reading frames in Saccharomyces cerevisiae

Directory of Open Access Journals (Sweden)

Kristiansson Erik

2009-12-01

Full Text Available Abstract Background Some upstream open reading frames (uORFs regulate gene expression (i.e., they are functional and can play key roles in keeping organisms healthy. However, how uORFs are involved in gene regulation is not yet fully understood. In order to get a complete view of how uORFs are involved in gene regulation, it is expected that a large number of experimentally verified functional uORFs are needed. Unfortunately, wet-experiments to verify that uORFs are functional are expensive. Results In this paper, a new computational approach to predicting functional uORFs in the yeast Saccharomyces cerevisiae is presented. Our approach is based on inductive logic programming and makes use of a novel combination of knowledge about biological conservation, Gene Ontology annotations and genes' responses to different conditions. Our method results in a set of simple and informative hypotheses with an estimated sensitivity of 76%. The hypotheses predict 301 further genes to have 398 novel functional uORFs. Three (RPC11, TPK1, and FOL1 of these 301 genes have been hypothesised, following wet-experiments, by a related study to have functional uORFs. A comparison with another related study suggests that eleven of the predicted functional uORFs from genes LDB17, HEM3, CIN8, BCK2, PMC1, FAS1, APP1, ACC1, CKA2, SUR1, and ATH1 are strong candidates for wet-lab experimental studies. Conclusions Learning based prediction of functional uORFs can be done with a high sensitivity. The predictions made in this study can serve as a list of candidates for subsequent wet-lab verification and might help to elucidate the regulatory roles of uORFs.

Improving protein function prediction methods with integrated literature data

Directory of Open Access Journals (Sweden)

Gabow Aaron P

2008-04-01

Full Text Available Abstract Background Determining the function of uncharacterized proteins is a major challenge in the post-genomic era due to the problem's complexity and scale. Identifying a protein's function contributes to an understanding of its role in the involved pathways, its suitability as a drug target, and its potential for protein modifications. Several graph-theoretic approaches predict unidentified functions of proteins by using the functional annotations of better-characterized proteins in protein-protein interaction networks. We systematically consider the use of literature co-occurrence data, introduce a new method for quantifying the reliability of co-occurrence and test how performance differs across species. We also quantify changes in performance as the prediction algorithms annotate with increased specificity. Results We find that including information on the co-occurrence of proteins within an abstract greatly boosts performance in the Functional Flow graph-theoretic function prediction algorithm in yeast, fly and worm. This increase in performance is not simply due to the presence of additional edges since supplementing protein-protein interactions with co-occurrence data outperforms supplementing with a comparably-sized genetic interaction dataset. Through the combination of protein-protein interactions and co-occurrence data, the neighborhood around unknown proteins is quickly connected to well-characterized nodes which global prediction algorithms can exploit. Our method for quantifying co-occurrence reliability shows superior performance to the other methods, particularly at threshold values around 10% which yield the best trade off between coverage and accuracy. In contrast, the traditional way of asserting co-occurrence when at least one abstract mentions both proteins proves to be the worst method for generating co-occurrence data, introducing too many false positives. Annotating the functions with greater specificity is harder

Prediction of Chemical Function: Model Development and ...

Science.gov (United States)

The United States Environmental Protection Agency’s Exposure Forecaster (ExpoCast) project is developing both statistical and mechanism-based computational models for predicting exposures to thousands of chemicals, including those in consumer products. The high-throughput (HT) screening-level exposures developed under ExpoCast can be combined with HT screening (HTS) bioactivity data for the risk-based prioritization of chemicals for further evaluation. The functional role (e.g. solvent, plasticizer, fragrance) that a chemical performs can drive both the types of products in which it is found and the concentration in which it is present and therefore impacting exposure potential. However, critical chemical use information (including functional role) is lacking for the majority of commercial chemicals for which exposure estimates are needed. A suite of machine-learning based models for classifying chemicals in terms of their likely functional roles in products based on structure were developed. This effort required collection, curation, and harmonization of publically-available data sources of chemical functional use information from government and industry bodies. Physicochemical and structure descriptor data were generated for chemicals with function data. Machine-learning classifier models for function were then built in a cross-validated manner from the descriptor/function data using the method of random forests. The models were applied to: 1) predict chemi

Predicting gene function using hierarchical multi-label decision tree ensembles

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Kocev Dragi

2010-01-01

Full Text Available Abstract Background S. cerevisiae, A. thaliana and M. musculus are well-studied organisms in biology and the sequencing of their genomes was completed many years ago. It is still a challenge, however, to develop methods that assign biological functions to the ORFs in these genomes automatically. Different machine learning methods have been proposed to this end, but it remains unclear which method is to be preferred in terms of predictive performance, efficiency and usability. Results We study the use of decision tree based models for predicting the multiple functions of ORFs. First, we describe an algorithm for learning hierarchical multi-label decision trees. These can simultaneously predict all the functions of an ORF, while respecting a given hierarchy of gene functions (such as FunCat or GO. We present new results obtained with this algorithm, showing that the trees found by it exhibit clearly better predictive performance than the trees found by previously described methods. Nevertheless, the predictive performance of individual trees is lower than that of some recently proposed statistical learning methods. We show that ensembles of such trees are more accurate than single trees and are competitive with state-of-the-art statistical learning and functional linkage methods. Moreover, the ensemble method is computationally efficient and easy to use. Conclusions Our results suggest that decision tree based methods are a state-of-the-art, efficient and easy-to-use approach to ORF function prediction.

Introducing ab initio based neural networks for transition-rate prediction in kinetic Monte Carlo simulations

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Messina, Luca; Castin, Nicolas; Domain, Christophe; Olsson, Pär

2017-02-01

The quality of kinetic Monte Carlo (KMC) simulations of microstructure evolution in alloys relies on the parametrization of point-defect migration rates, which are complex functions of the local chemical composition and can be calculated accurately with ab initio methods. However, constructing reliable models that ensure the best possible transfer of physical information from ab initio to KMC is a challenging task. This work presents an innovative approach, where the transition rates are predicted by artificial neural networks trained on a database of 2000 migration barriers, obtained with density functional theory (DFT) in place of interatomic potentials. The method is tested on copper precipitation in thermally aged iron alloys, by means of a hybrid atomistic-object KMC model. For the object part of the model, the stability and mobility properties of copper-vacancy clusters are analyzed by means of independent atomistic KMC simulations, driven by the same neural networks. The cluster diffusion coefficients and mean free paths are found to increase with size, confirming the dominant role of coarsening of medium- and large-sized clusters in the precipitation kinetics. The evolution under thermal aging is in better agreement with experiments with respect to a previous interatomic-potential model, especially concerning the experiment time scales. However, the model underestimates the solubility of copper in iron due to the excessively high solution energy predicted by the chosen DFT method. Nevertheless, this work proves the capability of neural networks to transfer complex ab initio physical properties to higher-scale models, and facilitates the extension to systems with increasing chemical complexity, setting the ground for reliable microstructure evolution simulations in a wide range of alloys and applications.

A New Approach for Accurate Prediction of Liquid Loading of Directional Gas Wells in Transition Flow or Turbulent Flow

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Ruiqing Ming

2017-01-01

Full Text Available Current common models for calculating continuous liquid-carrying critical gas velocity are established based on vertical wells and laminar flow without considering the influence of deviation angle and Reynolds number on liquid-carrying. With the increase of the directional well in transition flow or turbulent flow, the current common models cannot accurately predict the critical gas velocity of these wells. So we built a new model to predict continuous liquid-carrying critical gas velocity for directional well in transition flow or turbulent flow. It is shown from sensitivity analysis that the correction coefficient is mainly influenced by Reynolds number and deviation angle. With the increase of Reynolds number, the critical liquid-carrying gas velocity increases first and then decreases. And with the increase of deviation angle, the critical liquid-carrying gas velocity gradually decreases. It is indicated from the case calculation analysis that the calculation error of this new model is less than 10%, where accuracy is much higher than those of current common models. It is demonstrated that the continuous liquid-carrying critical gas velocity of directional well in transition flow or turbulent flow can be predicted accurately by using this new model.

Quantum phase transitions between a class of symmetry protected topological states

Energy Technology Data Exchange (ETDEWEB)

Tsui, Lokman; Jiang, Hong-Chen; Lu, Yuan-Ming; Lee, Dung-Hai

2015-07-01

The subject of this paper is the phase transition between symmetry protected topological states (SPTs). We consider spatial dimension d and symmetry group G so that the cohomology group, Hd+1(G,U(1)), contains at least one Z2n or Z factor. We show that the phase transition between the trivial SPT and the root states that generate the Z2n or Z groups can be induced on the boundary of a (d+1)-dimensional View the MathML source-symmetric SPT by a View the MathML source symmetry breaking field. Moreover we show these boundary phase transitions can be “transplanted” to d dimensions and realized in lattice models as a function of a tuning parameter. The price one pays is for the critical value of the tuning parameter there is an extra non-local (duality-like) symmetry. In the case where the phase transition is continuous, our theory predicts the presence of unusual (sometimes fractionalized) excitations corresponding to delocalized boundary excitations of the non-trivial SPT on one side of the transition. This theory also predicts other phase transition scenarios including first order transition and transition via an intermediate symmetry breaking phase.

Troubles in the systematic prediction of transition metal thermochemistry with contemporary out-of-the-box methods

KAUST Repository

Minenkov, Yury

2016-03-22

The recently developed DLPNO-CCSD(T) method and 7 popular DFT functionals (B3LYP, M06, M06L, PBE, PBE0, TPSS and TPSSh) with and without an empirical dispersion term have been tested to reproduce 111 gas phase reaction enthalpies involving 11 different transition metals. Our calculations, corrected for both relativistic effects and basis set incompleteness, indicate that most of the methods applied with default settings perform with acceptable accuracy on average. Nevertheless, our calculations also evidenced unexpected and non systematic large deviations for specific cases. For group 12 metals (Zn, Cd, Hg) most of the methods provided mean unsigned errors (MUE) less than 5.0 kcal/mol, with DLPNO-CCSD(T) and PBE methods performing excellently (MUE lower 2.0 kcal/mol). Problems started with group 4 metals (Ti and Zr). Best performer for Zr complexes with a MUE of 1.8 kcal/mol, PBE0-D3, provides a MUE larger than 8 kcal/mol for Ti. DLPNO-CCSD(T) provides a reasonable MUE of 3.3 kcal/mol for Ti reactions, but gives MUE a larger than 14.4 kcal/mol for Zr complexes, with all the larger deviations for reactions involving ZrF4. Large and non-systematic errors have been obtained for group 6 metals (Mo and W), for 8 reactions containing Fe, Cu, Nb and Re complexes. Finally, for the whole set of 111 reactions, the DLPNO-CCSD(T), B3LYP-D3 and PBE0-D3 methods turned out to be the best performers, both providing MUE below 5.0 kcal/mol. Since DFT results cannot be systematically improved and large non-systematic deviations of 20-30 kcal/mol were obtained even for best performers, our results indicates that current DFT methods are still unable to provide robust predictions in transition metal thermochemistry, at least for the functionals explored in this work. The same conclusion holds for both DLPNO-CCSD(T) and canonical CCSD(T) methods when used entirely as out-of-the-box. However if careful investigation core correlation is performed, relativistic effects are properly included

Correlation-based Transition Modeling for External Aerodynamic Flows

Science.gov (United States)

Medida, Shivaji

is not captured with conventional turbulence models. The validated transition model is successfully applied to rotating blade configurations in axial flow conditions to study the effects of transitional boundary layers on rotor thrust and torque. In helicopter rotors, inclusion of transition effects increased thrust prediction by 2% and decreased torque by as much as 8% at lower collective angles, due to reduced airfoil profile drag. In wind turbine rotors, transition model predicted a 7%--70% increase in generated shaft torque at lower wind speeds, due to lower viscous drag. This has important implications for CFD analysis of small wind turbines operating at low values of rated power. Transition onset locations along upper and lower surfaces of rotor blades are analyzed in detail. A new crossflow transition onset criterion is developed to account for crossflow instability effects in three-dimensional boundary layers. Preliminary results for swept wing and rotating blade flows demonstrate the need to account for crossflow transition in three-dimensional simulations of wings, rotating blades, and airframes. Inclusion of crossflow effects resulted in accelerated transition in the presence of favorable pressure gradients and yawed flow. Finally, a new correction to the wall damping function in the Spalart-Allmaras turbulence model is proposed to improve sensitivity of the model to strong adverse pressure gradients (APG). The correction reduces turbulence production in the boundary layer when the ratio of magnitudes of local turbulent stress to the wall shear stress exceeds a threshold value, therefore enabling earlier separation of boundary layer. Improved prediction of static and dynamic stall on two-dimensional airfoils is demonstrated with the APG correction.

Executive function processes predict mobility outcomes in older adults.

Science.gov (United States)

Gothe, Neha P; Fanning, Jason; Awick, Elizabeth; Chung, David; Wójcicki, Thomas R; Olson, Erin A; Mullen, Sean P; Voss, Michelle; Erickson, Kirk I; Kramer, Arthur F; McAuley, Edward

2014-02-01

To examine the relationship between performance on executive function measures and subsequent mobility outcomes in community-dwelling older adults. Randomized controlled clinical trial. Champaign-Urbana, Illinois. Community-dwelling older adults (N = 179; mean age 66.4). A 12-month exercise trial with two arms: an aerobic exercise group and a stretching and strengthening group. Established cognitive tests of executive function (flanker task, task switching, and a dual-task paradigm) and the Wisconsin card sort test. Mobility was assessed using the timed 8-foot up and go test and times to climb up and down a flight of stairs. Participants completed the cognitive tests at baseline and the mobility measures at baseline and after 12 months of the intervention. Multiple regression analyses were conducted to determine whether baseline executive function predicted postintervention functional performance after controlling for age, sex, education, cardiorespiratory fitness, and baseline mobility levels. Selective baseline executive function measurements, particularly performance on the flanker task (β = 0.15-0.17) and the Wisconsin card sort test (β = 0.11-0.16) consistently predicted mobility outcomes at 12 months. The estimates were in the expected direction, such that better baseline performance on the executive function measures predicted better performance on the timed mobility tests independent of intervention. Executive functions of inhibitory control, mental set shifting, and attentional flexibility were predictive of functional mobility. Given the literature associating mobility limitations with disability, morbidity, and mortality, these results are important for understanding the antecedents to poor mobility function that well-designed interventions to improve cognitive performance can attenuate. © 2014, Copyright the Authors Journal compilation © 2014, The American Geriatrics Society.

Active Life Expectancy and Functional Health Transition among Filipino Older People

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Grace T. Cruz

2007-12-01

Full Text Available The study provides a baseline information on the functional health transition patterns of older people and computes for the Active Life Expectancy (ALE using a multistate life table method. Findings on ALE demonstrate that females and urban residents live longer and have a greater proportion of their remaining life in active state compared to their counterparts. Health transition analysis indicates a significant proportion experiencing recovery. Age, sex, place of residence and health status/behavior indicators (self-assessed health, drinking and exercise display a significant influence on future health and mortality trajectories although surprisingly, education did not show any significant effect.

Functional Assessment in Transition and Rehabilitation for Adolescents and Adults with Learning Disorders.

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Bullis, Michael, Ed.; Davis, Cheryl D., Ed.

This manual is based on a 3-year, federally funded program, Project FASTER (Functional Assessment Services for Transition, Education, and Rehabilitation), that developed functional assessment procedures and provided assessment services to adolescents and adults with learning or behavioral disorders who were involved in school-based transition…

A molecular dynamics approach for predicting the glass transition temperature and plasticization effect in amorphous pharmaceuticals.

Science.gov (United States)

Gupta, Jasmine; Nunes, Cletus; Jonnalagadda, Sriramakamal

2013-11-04

The objectives of this study were as follows: (i) To develop an in silico technique, based on molecular dynamics (MD) simulations, to predict glass transition temperatures (Tg) of amorphous pharmaceuticals. (ii) To computationally study the effect of plasticizer on Tg. (iii) To investigate the intermolecular interactions using radial distribution function (RDF). Amorphous sucrose and water were selected as the model compound and plasticizer, respectively. MD simulations were performed using COMPASS force field and isothermal-isobaric ensembles. The specific volumes of amorphous cells were computed in the temperature range of 440-265 K. The characteristic "kink" observed in volume-temperature curves, in conjunction with regression analysis, defined the Tg. The MD computed Tg values were 367 K, 352 K and 343 K for amorphous sucrose containing 0%, 3% and 5% w/w water, respectively. The MD technique thus effectively simulated the plasticization effect of water; and the corresponding Tg values were in reasonable agreement with theoretical models and literature reports. The RDF measurements revealed strong hydrogen bond interactions between sucrose hydroxyl oxygens and water oxygen. Steric effects led to weak interactions between sucrose acetal oxygens and water oxygen. MD is thus a powerful predictive tool for probing temperature and water effects on the stability of amorphous systems during drug development.

Identification of predictive biomarkers of disease state in transition dairy cows.

Science.gov (United States)

Hailemariam, D; Mandal, R; Saleem, F; Dunn, S M; Wishart, D S; Ametaj, B N

2014-05-01

In dairy cows, periparturient disease states, such as metritis, mastitis, and laminitis, are leading to increasingly significant economic losses for the dairy industry. Treatments for these pathologies are often expensive, ineffective, or not cost-efficient, leading to production losses, high veterinary bills, or early culling of the cows. Early diagnosis or detection of these conditions before they manifest themselves could lower their incidence, level of morbidity, and the associated economic losses. In an effort to identify predictive biomarkers for postpartum or periparturient disease states in dairy cows, we undertook a cross-sectional and longitudinal metabolomics study to look at plasma metabolite levels of dairy cows during the transition period, before and after becoming ill with postpartum diseases. Specifically we employed a targeted quantitative metabolomics approach that uses direct flow injection mass spectrometry to track the metabolite changes in 120 different plasma metabolites. Blood plasma samples were collected from 12 dairy cows at 4 time points during the transition period (-4 and -1 wk before and 1 and 4 wk after parturition). Out of the 12 cows studied, 6 developed multiple periparturient disorders in the postcalving period, whereas the other 6 remained healthy during the entire experimental period. Multivariate data analysis (principal component analysis and partial least squares discriminant analysis) revealed a clear separation between healthy controls and diseased cows at all 4 time points. This analysis allowed us to identify several metabolites most responsible for separating the 2 groups, especially before parturition and the start of any postpartum disease. Three metabolites, carnitine, propionyl carnitine, and lysophosphatidylcholine acyl C14:0, were significantly elevated in diseased cows as compared with healthy controls as early as 4 wk before parturition, whereas 2 metabolites, phosphatidylcholine acyl-alkyl C42:4 and

Linear Prediction Using Refined Autocorrelation Function

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M. Shahidur Rahman

2007-07-01

Full Text Available This paper proposes a new technique for improving the performance of linear prediction analysis by utilizing a refined version of the autocorrelation function. Problems in analyzing voiced speech using linear prediction occur often due to the harmonic structure of the excitation source, which causes the autocorrelation function to be an aliased version of that of the vocal tract impulse response. To estimate the vocal tract characteristics accurately, however, the effect of aliasing must be eliminated. In this paper, we employ homomorphic deconvolution technique in the autocorrelation domain to eliminate the aliasing effect occurred due to periodicity. The resulted autocorrelation function of the vocal tract impulse response is found to produce significant improvement in estimating formant frequencies. The accuracy of formant estimation is verified on synthetic vowels for a wide range of pitch frequencies typical for male and female speakers. The validity of the proposed method is also illustrated by inspecting the spectral envelopes of natural speech spoken by high-pitched female speaker. The synthesis filter obtained by the current method is guaranteed to be stable, which makes the method superior to many of its alternatives.

Predictive model for functional consequences of oral cavity tumour resections

NARCIS (Netherlands)

van Alphen, M.J.A.; Hageman, T.A.G.; Hageman, Tijmen Antoon Geert; Smeele, L.E.; Balm, Alfonsus Jacobus Maria; Balm, A.J.M.; van der Heijden, Ferdinand; Lemke, H.U.

2013-01-01

The prediction of functional consequences after treatment of large oral cavity tumours is mainly based on the size and location of the tumour. However, patient specific factors play an important role in the functional outcome, making the current predictions unreliable and subjective. An objective

Covariant trace formalism for heavy meson s-wave to p-wave transitions

International Nuclear Information System (INIS)

Balk, S.; Koerner, J.G.; Thompson, G.; Hussain, F.

1992-06-01

Heavy meson, s- to p-wave, weak transitions are studied in the context of the Heavy Quark Effective Theory using covariant meson wave functions. We use the trace formalism to evaluate the weak transitions. As expected from heavy quark symmetry, the eight transitions between s- and p-wave states are described in terms of only two universal form factors which are given in terms of explicit wave function overlap integrals. We present our results in terms of both invariant and helicity amplitudes. Using our helicity amplitude expressions we discuss rate formulae, helicity structure functions and joint angular decay distributions in the decays B-bar→D**(→(D,D*)+π)+W - (→l - ν l ). The heavy quark symmetry predictions for the one-pion transitions D**→(D,D*)+π are similarly worked out by using trace techniques. (author). 35 refs, 3 figs, 2 tabs

Stability theory and transition prediction applied to a general aviation fuselage

Science.gov (United States)

Spall, R. E.; Wie, Y.-S.

1993-01-01

The linear stability of a fully three-dimensional boundary layer formed over a general aviation fuselage was investigated. The location of the onset of transition was estimated using the N-factor method. The results were compared with existing experimental data and indicate N-factors of approximately 8.5 on the side of the fuselage and 3.0 near the top. Considerable crossflow existed along the side of the body, which significantly affected the unstable modes present in the boundary layer. Fair agreement was found between the predicted frequency range of linear instability modes and available experimental data concerning the spectral content of the boundary layer.

Predicting estuarine benthic production using functional diversity

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Marina Dolbeth

2014-05-01

Full Text Available We considered an estuarine system having naturally low levels of diversity, but attaining considerable high production levels, and being subjected to different sorts of anthropogenic impacts and climate events to investigate the relationship between diversity and secondary production. Functional diversity measures were used to predict benthic production, which is considered as a proxy of the ecosystem provisioning services. To this end, we used a 14-year dataset on benthic invertebrate community production from a seagrass and a sandflat habitat and we adopted a sequential modeling approach, where abiotic, trait community weighted means (CWM and functional diversity indices were tested by generalized linear models (GLM, and their significant variables were then combined to produce a final model. Almost 90% of variance of the benthic production could be predicted by combining the number of locomotion types, the absolute maximum atmospheric temperature (proxy of the heat waves occurrence, the type of habitat and the mean body mass, by order of importance. This result is in agreement with the mass ratio hypothesis, where ecosystem functions/services can be chiefly predicted by the dominant trait in the community, here measured as CWM. The increase of benthic production with the number of locomotion types may be seen as greater possibility of using the resources available in the system. Such greater efficiency would increase production. The other variables were also discussed in line of the previous hypothesis and taking into account the general positive relationship obtained between production and functional diversity indices. Overall, it was concluded that traits representative of wider possibilities of using available resources and higher functional diversity are related with higher benthic production.

Functional enrichment analyses and construction of functional similarity networks with high confidence function prediction by PFP

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Kihara Daisuke

2010-05-01

Full Text Available Abstract Background A new paradigm of biological investigation takes advantage of technologies that produce large high throughput datasets, including genome sequences, interactions of proteins, and gene expression. The ability of biologists to analyze and interpret such data relies on functional annotation of the included proteins, but even in highly characterized organisms many proteins can lack the functional evidence necessary to infer their biological relevance. Results Here we have applied high confidence function predictions from our automated prediction system, PFP, to three genome sequences, Escherichia coli, Saccharomyces cerevisiae, and Plasmodium falciparum (malaria. The number of annotated genes is increased by PFP to over 90% for all of the genomes. Using the large coverage of the function annotation, we introduced the functional similarity networks which represent the functional space of the proteomes. Four different functional similarity networks are constructed for each proteome, one each by considering similarity in a single Gene Ontology (GO category, i.e. Biological Process, Cellular Component, and Molecular Function, and another one by considering overall similarity with the funSim score. The functional similarity networks are shown to have higher modularity than the protein-protein interaction network. Moreover, the funSim score network is distinct from the single GO-score networks by showing a higher clustering degree exponent value and thus has a higher tendency to be hierarchical. In addition, examining function assignments to the protein-protein interaction network and local regions of genomes has identified numerous cases where subnetworks or local regions have functionally coherent proteins. These results will help interpreting interactions of proteins and gene orders in a genome. Several examples of both analyses are highlighted. Conclusion The analyses demonstrate that applying high confidence predictions from PFP

An auxiliary optimization method for complex public transit route network based on link prediction

Science.gov (United States)

Zhang, Lin; Lu, Jian; Yue, Xianfei; Zhou, Jialin; Li, Yunxuan; Wan, Qian

2018-02-01

Inspired by the missing (new) link prediction and the spurious existing link identification in link prediction theory, this paper establishes an auxiliary optimization method for public transit route network (PTRN) based on link prediction. First, link prediction applied to PTRN is described, and based on reviewing the previous studies, the summary indices set and its algorithms set are collected for the link prediction experiment. Second, through analyzing the topological properties of Jinan’s PTRN established by the Space R method, we found that this is a typical small-world network with a relatively large average clustering coefficient. This phenomenon indicates that the structural similarity-based link prediction will show a good performance in this network. Then, based on the link prediction experiment of the summary indices set, three indices with maximum accuracy are selected for auxiliary optimization of Jinan’s PTRN. Furthermore, these link prediction results show that the overall layout of Jinan’s PTRN is stable and orderly, except for a partial area that requires optimization and reconstruction. The above pattern conforms to the general pattern of the optimal development stage of PTRN in China. Finally, based on the missing (new) link prediction and the spurious existing link identification, we propose optimization schemes that can be used not only to optimize current PTRN but also to evaluate PTRN planning.

Rotator side chains trigger cooperative transition for shape and function memory effect in organic semiconductors.

Science.gov (United States)

Chung, Hyunjoong; Dudenko, Dmytro; Zhang, Fengjiao; D'Avino, Gabriele; Ruzié, Christian; Richard, Audrey; Schweicher, Guillaume; Cornil, Jérôme; Beljonne, David; Geerts, Yves; Diao, Ying

2018-01-18

Martensitic transition is a solid-state phase transition involving cooperative movement of atoms, mostly studied in metallurgy. The main characteristics are low transition barrier, ultrafast kinetics, and structural reversibility. They are rarely observed in molecular crystals, and hence the origin and mechanism are largely unexplored. Here we report the discovery of martensitic transition in single crystals of two different organic semiconductors. In situ microscopy, single-crystal X-ray diffraction, Raman and nuclear magnetic resonance spectroscopy, and molecular simulations combined indicate that the rotating bulky side chains trigger cooperative transition. Cooperativity enables shape memory effect in single crystals and function memory effect in thin film transistors. We establish a molecular design rule to trigger martensitic transition in organic semiconductors, showing promise for designing next-generation smart multifunctional materials.

Scoring protein relationships in functional interaction networks predicted from sequence data.

Directory of Open Access Journals (Sweden)

Gaston K Mazandu

Full Text Available UNLABELLED: The abundance of diverse biological data from various sources constitutes a rich source of knowledge, which has the power to advance our understanding of organisms. This requires computational methods in order to integrate and exploit these data effectively and elucidate local and genome wide functional connections between protein pairs, thus enabling functional inferences for uncharacterized proteins. These biological data are primarily in the form of sequences, which determine functions, although functional properties of a protein can often be predicted from just the domains it contains. Thus, protein sequences and domains can be used to predict protein pair-wise functional relationships, and thus contribute to the function prediction process of uncharacterized proteins in order to ensure that knowledge is gained from sequencing efforts. In this work, we introduce information-theoretic based approaches to score protein-protein functional interaction pairs predicted from protein sequence similarity and conserved protein signature matches. The proposed schemes are effective for data-driven scoring of connections between protein pairs. We applied these schemes to the Mycobacterium tuberculosis proteome to produce a homology-based functional network of the organism with a high confidence and coverage. We use the network for predicting functions of uncharacterised proteins. AVAILABILITY: Protein pair-wise functional relationship scores for Mycobacterium tuberculosis strain CDC1551 sequence data and python scripts to compute these scores are available at http://web.cbio.uct.ac.za/~gmazandu/scoringschemes.

Vulnerability analysis and passenger source prediction in urban rail transit networks.

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Junjie Wang

Full Text Available Based on large-scale human mobility data collected in San Francisco and Boston, the morning peak urban rail transit (URT ODs (origin-destination matrix were estimated and the most vulnerable URT segments, those capable of causing the largest service interruptions, were identified. In both URT networks, a few highly vulnerable segments were observed. For this small group of vital segments, the impact of failure must be carefully evaluated. A bipartite URT usage network was developed and used to determine the inherent connections between urban rail transits and their passengers' travel demands. Although passengers' origins and destinations were easy to locate for a large number of URT segments, a few show very complicated spatial distributions. Based on the bipartite URT usage network, a new layer of the understanding of a URT segment's vulnerability can be achieved by taking the difficulty of addressing the failure of a given segment into account. Two proof-of-concept cases are described here: Possible transfer of passenger flow to the road network is here predicted in the cases of failures of two representative URT segments in San Francisco.

Using Combined Computational Techniques to Predict the Glass Transition Temperatures of Aromatic Polybenzoxazines

Science.gov (United States)

Mhlanga, Phumzile; Wan Hassan, Wan Aminah; Hamerton, Ian; Howlin, Brendan J.

2013-01-01

The Molecular Operating Environment software (MOE) is used to construct a series of benzoxazine monomers for which a variety of parameters relating to the structures (e.g. water accessible surface area, negative van der Waals surface area, hydrophobic volume and the sum of atomic polarizabilities, etc.) are obtained and quantitative structure property relationships (QSPR) models are formulated. Three QSPR models (formulated using up to 5 descriptors) are first used to make predictions for the initiator data set (n = 9) and compared to published thermal data; in all of the QSPR models there is a high level of agreement between the actual data and the predicted data (within 0.63–1.86 K of the entire dataset). The water accessible surface area is found to be the most important descriptor in the prediction of Tg. Molecular modelling simulations of the benzoxazine polymer (minus initiator) carried out at the same time using the Materials Studio software suite provide an independent prediction of Tg. Predicted Tg values from molecular modelling fall in the middle of the range of the experimentally determined Tg values, indicating that the structure of the network is influenced by the nature of the initiator used. Hence both techniques can provide predictions of glass transition temperatures and provide complementary data for polymer design. PMID:23326419

Using combined computational techniques to predict the glass transition temperatures of aromatic polybenzoxazines.

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Phumzile Mhlanga

Full Text Available The Molecular Operating Environment software (MOE is used to construct a series of benzoxazine monomers for which a variety of parameters relating to the structures (e.g. water accessible surface area, negative van der Waals surface area, hydrophobic volume and the sum of atomic polarizabilities, etc. are obtained and quantitative structure property relationships (QSPR models are formulated. Three QSPR models (formulated using up to 5 descriptors are first used to make predictions for the initiator data set (n = 9 and compared to published thermal data; in all of the QSPR models there is a high level of agreement between the actual data and the predicted data (within 0.63-1.86 K of the entire dataset. The water accessible surface area is found to be the most important descriptor in the prediction of T(g. Molecular modelling simulations of the benzoxazine polymer (minus initiator carried out at the same time using the Materials Studio software suite provide an independent prediction of T(g. Predicted T(g values from molecular modelling fall in the middle of the range of the experimentally determined T(g values, indicating that the structure of the network is influenced by the nature of the initiator used. Hence both techniques can provide predictions of glass transition temperatures and provide complementary data for polymer design.

Combining specificity determining and conserved residues improves functional site prediction

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Gelfand Mikhail S

2009-06-01

Full Text Available Abstract Background Predicting the location of functionally important sites from protein sequence and/or structure is a long-standing problem in computational biology. Most current approaches make use of sequence conservation, assuming that amino acid residues conserved within a protein family are most likely to be functionally important. Most often these approaches do not consider many residues that act to define specific sub-functions within a family, or they make no distinction between residues important for function and those more relevant for maintaining structure (e.g. in the hydrophobic core. Many protein families bind and/or act on a variety of ligands, meaning that conserved residues often only bind a common ligand sub-structure or perform general catalytic activities. Results Here we present a novel method for functional site prediction based on identification of conserved positions, as well as those responsible for determining ligand specificity. We define Specificity-Determining Positions (SDPs, as those occupied by conserved residues within sub-groups of proteins in a family having a common specificity, but differ between groups, and are thus likely to account for specific recognition events. We benchmark the approach on enzyme families of known 3D structure with bound substrates, and find that in nearly all families residues predicted by SDPsite are in contact with the bound substrate, and that the addition of SDPs significantly improves functional site prediction accuracy. We apply SDPsite to various families of proteins containing known three-dimensional structures, but lacking clear functional annotations, and discusse several illustrative examples. Conclusion The results suggest a better means to predict functional details for the thousands of protein structures determined prior to a clear understanding of molecular function.

Predicting animal home-range structure and transitions using a multistate Ornstein-Uhlenbeck biased random walk

Science.gov (United States)

Breed, Greg A.; Golson, Emily A.; Tinker, M. Tim

2017-01-01

The home‐range concept is central in animal ecology and behavior, and numerous mechanistic models have been developed to understand home range formation and maintenance. These mechanistic models usually assume a single, contiguous home range. Here we describe and implement a simple home‐range model that can accommodate multiple home‐range centers, form complex shapes, allow discontinuities in use patterns, and infer how external and internal variables affect movement and use patterns. The model assumes individuals associate with two or more home‐range centers and move among them with some estimable probability. Movement in and around home‐range centers is governed by a two‐dimensional Ornstein‐Uhlenbeck process, while transitions between centers are modeled as a stochastic state‐switching process. We augmented this base model by introducing environmental and demographic covariates that modify transition probabilities between home‐range centers and can be estimated to provide insight into the movement process. We demonstrate the model using telemetry data from sea otters (Enhydra lutris) in California. The model was fit using a Bayesian Markov Chain Monte Carlo method, which estimated transition probabilities, as well as unique Ornstein‐Uhlenbeck diffusion and centralizing tendency parameters. Estimated parameters could then be used to simulate movement and space use that was virtually indistinguishable from real data. We used Deviance Information Criterion (DIC) scores to assess model fit and determined that both wind and reproductive status were predictive of transitions between home‐range centers. Females were less likely to move between home‐range centers on windy days, less likely to move between centers when tending pups, and much more likely to move between centers just after weaning a pup. These tendencies are predicted by theoretical movement rules but were not previously known and show that our model can extract meaningful

Predicting animal home-range structure and transitions using a multistate Ornstein-Uhlenbeck biased random walk.

Science.gov (United States)

Breed, Greg A; Golson, Emily A; Tinker, M Tim

2017-01-01

The home-range concept is central in animal ecology and behavior, and numerous mechanistic models have been developed to understand home range formation and maintenance. These mechanistic models usually assume a single, contiguous home range. Here we describe and implement a simple home-range model that can accommodate multiple home-range centers, form complex shapes, allow discontinuities in use patterns, and infer how external and internal variables affect movement and use patterns. The model assumes individuals associate with two or more home-range centers and move among them with some estimable probability. Movement in and around home-range centers is governed by a two-dimensional Ornstein-Uhlenbeck process, while transitions between centers are modeled as a stochastic state-switching process. We augmented this base model by introducing environmental and demographic covariates that modify transition probabilities between home-range centers and can be estimated to provide insight into the movement process. We demonstrate the model using telemetry data from sea otters (Enhydra lutris) in California. The model was fit using a Bayesian Markov Chain Monte Carlo method, which estimated transition probabilities, as well as unique Ornstein-Uhlenbeck diffusion and centralizing tendency parameters. Estimated parameters could then be used to simulate movement and space use that was virtually indistinguishable from real data. We used Deviance Information Criterion (DIC) scores to assess model fit and determined that both wind and reproductive status were predictive of transitions between home-range centers. Females were less likely to move between home-range centers on windy days, less likely to move between centers when tending pups, and much more likely to move between centers just after weaning a pup. These tendencies are predicted by theoretical movement rules but were not previously known and show that our model can extract meaningful behavioral insight from complex

Chemical Function Predictions for Tox21 Chemicals

Data.gov (United States)

U.S. Environmental Protection Agency — Random forest chemical function predictions for Tox21 chemicals in personal care products uses and "other" uses. This dataset is associated with the following...

Pulmonary blood volume and transit time in cirrhosis: relation to lung function

DEFF Research Database (Denmark)

Møller, Søren; Burchardt, H; Øgard, CG

2006-01-01

BACKGROUND/AIMS: In cirrhosis a systemic vasodilatation leads to an abnormal distribution of the blood volume with a contracted central blood volume. In addition, the patients have a ventilation/perfusion imbalance with a low diffusing capacity. As the size of the pulmonary blood volume (PBV) has...... not been determined separately we assessed PBV and pulmonary transit time (PTT) in relation to lung function in patients with cirrhosis and in controls. METHODS: Pulmonary and cardiac haemodynamics and transit times were determined by radionuclide techniques in 22 patients with alcoholic cirrhosis......, in the controls, Pvolume...

QCD predictions for weak neutral current structure functions

International Nuclear Information System (INIS)

Wu Jimin

1987-01-01

Employing the analytic expression (to the next leading order) for non-singlet component of structure function which the author got from QCD theory and putting recent experiment result of neutral current structure function at Q 2 = 11 (GeV/C) 2 as input, the QCD prediction for neutral current structure function of their scaling violation behaviours was given

Response predictions using the observed autocorrelation function

DEFF Research Database (Denmark)

Nielsen, Ulrik Dam; H. Brodtkorb, Astrid; Jensen, Jørgen Juncher

2018-01-01

This article studies a procedure that facilitates short-time, deterministic predictions of the wave-induced motion of a marine vessel, where it is understood that the future motion of the vessel is calculated ahead of time. Such predictions are valuable to assist in the execution of many marine......-induced response in study. Thus, predicted (future) values ahead of time for a given time history recording are computed through a mathematical combination of the sample autocorrelation function and previous measurements recorded just prior to the moment of action. Importantly, the procedure does not need input...... show that predictions can be successfully made in a time horizon corresponding to about 8-9 wave periods ahead of current time (the moment of action)....

Resistive transition for two-dimensional superconductors: Comparison between experiments and Coulomb-gas-model predictions

International Nuclear Information System (INIS)

Minnhagen, P.

1983-01-01

The Coulomb-gas model of vortex fluctuations leads to scaling relations for the resistive transition which can be directly tested by experiments. By analyzing published resistance data, it is shown that there is experimental evidence for the Coulomb-gas scaling relation in the absence of a perpendicular magnetic field. It is also shown that there exists some suggestive support for the Coulomb-gas predictions in the presence of a magnetic field

A study of the colonic transit function by dual radionuclide colon scintigraphy

International Nuclear Information System (INIS)

Yang Weidong; Sun Buzhou; Song Changyi; Lu Jinyan; Wang Shejiao; Zheng Xianghong; Huang Lin; Lei Yamei

1999-01-01

Objective: To establish a new, simple and noninvasive method which can quantitatively analyze the colonic transit function by dual radionuclide colon scintigraphy. Methods: 24 patients with constipation and 32 normal controls were studied. Na 131 I was sealed into capsule made by polyvinylchloride which can not be digested and absorbed in gastrointestinal tract. Patients and normal volunteers swallow 131 I capsules and drink 99 Tc m labelled sulfur colloid solution at the same time. The static image was acquired at the regular time, then calculate the Geometric Center values (GC). Results: 1) The capsules can be clearly located through the colonic contour shown by 99 Tc m labeled sulfur colloid when it reached the large bowel. 2) The transiting time from mouth to cecum, through colon and through whole gastrointestinal in normal people were (6.61 +- 1.94), (36.61 +- 10.51) and (42.72 +- 10.02) h, respectively, in constipation group were (8.03 +- 3.63), (65.50 +- 28.40) and (74.05 +- 28.17) h, respectively. There was no significant difference (P > 0.05) in two groups compared with each other. But the transiting time through colon and whole gastrointestinal in constipation was slower than that in normal people, with significant difference (P < 0.01). 3) Through examination the colonic transit abnormality can be divided into three patterns: whole colon transit delay, right-colon transit delay and left-colon transit delay. Conclusions: This method is a simple, physiologic and quantitative in evaluating the colonic transit, it can also stage the colonic dyskinesia of the patients

Fabrication and electrocatalytic application of functionalized nanoporous carbon material with different transition metal oxides

International Nuclear Information System (INIS)

Samiee, L.; Shoghi, F.; Vinu, A.

2013-01-01

Highlights: ► Fabrication of highly ordered functionalized nanoporous carbon material with different types of transition metal oxides. ► Novel electrocatalytic activity of functionalized nanoporous carbon material. ► Simultaneous effect of surface area and surface reactivity parameters on electrocatalytic activity. - Abstract: In the work presented here, an attempt is made to study the effect of functionalization with different transition metal oxides on the mesostructural properties as well as electrochemical behavior of Pt/nanoporous carbon supports. In this respect, the functionalized samples have been synthesized by using CMK-3 and metallocene as transition metal sources. The platinum catalysts (5 wt% Pt) obtained through a conventional wet impregnation method. All the materials have been characterized by XRD (low and high), N 2 adsorption–desorption isotherms, high-resolution transmission electron microscopy, high-resolution field emission scanning electron, EDX mapping images and cyclic voltammetry (CV) and rotating disk electrode (RDE) techniques. The results showed that the mesostructural order has been destroyed by functionalization of CMK-3 with CoO, whereas it is not that much affected in NiO and CuO functionalized samples. EDX image mapping exhibited the good and uniform dispersion of functionalizing elements (Ni, Cu, Fe and Co), Pt in the carbon supports. Moreover, XRD studies revealed the formation of smaller platinum crystallite sizes in NiO and CuO functionalized samples in relative to other functionalized supports. Electrochemical measurements were performed using CV and RDE method. Kinetic analysis revealed an activity increases in the following order: CMK-3-NiO-Pt > CMK-3-CuO-Pt > CMK-3-CoO-Pt > CMK-3-Fe 2 O 3 -Pt which is showing of simultaneous effect of surface area and surface reactivity parameters.

Fabrication and electrocatalytic application of functionalized nanoporous carbon material with different transition metal oxides

Energy Technology Data Exchange (ETDEWEB)

Samiee, L., E-mail: Leila.Samiee83@gmail.com [Development and Optimization of Energy Technologies Research Division, Research Institute of Petroleum Industry (RIPI), West Boulevard, Near Azadi Sports Complex, Tehran (Iran, Islamic Republic of); Shoghi, F. [Development and Optimization of Energy Technologies Research Division, Research Institute of Petroleum Industry (RIPI), West Boulevard, Near Azadi Sports Complex, Tehran (Iran, Islamic Republic of); Vinu, A., E-mail: a.vinu@uq.edu.au [Australian Institute for Bioengineering and Nanotechnology(AIBN), University of Queensland, Corner College and Cooper Roads (Bld75), Brisbane, Qld 4072 (Australia)

2013-01-15

Highlights: Black-Right-Pointing-Pointer Fabrication of highly ordered functionalized nanoporous carbon material with different types of transition metal oxides. Black-Right-Pointing-Pointer Novel electrocatalytic activity of functionalized nanoporous carbon material. Black-Right-Pointing-Pointer Simultaneous effect of surface area and surface reactivity parameters on electrocatalytic activity. - Abstract: In the work presented here, an attempt is made to study the effect of functionalization with different transition metal oxides on the mesostructural properties as well as electrochemical behavior of Pt/nanoporous carbon supports. In this respect, the functionalized samples have been synthesized by using CMK-3 and metallocene as transition metal sources. The platinum catalysts (5 wt% Pt) obtained through a conventional wet impregnation method. All the materials have been characterized by XRD (low and high), N{sub 2} adsorption-desorption isotherms, high-resolution transmission electron microscopy, high-resolution field emission scanning electron, EDX mapping images and cyclic voltammetry (CV) and rotating disk electrode (RDE) techniques. The results showed that the mesostructural order has been destroyed by functionalization of CMK-3 with CoO, whereas it is not that much affected in NiO and CuO functionalized samples. EDX image mapping exhibited the good and uniform dispersion of functionalizing elements (Ni, Cu, Fe and Co), Pt in the carbon supports. Moreover, XRD studies revealed the formation of smaller platinum crystallite sizes in NiO and CuO functionalized samples in relative to other functionalized supports. Electrochemical measurements were performed using CV and RDE method. Kinetic analysis revealed an activity increases in the following order: CMK-3-NiO-Pt > CMK-3-CuO-Pt > CMK-3-CoO-Pt > CMK-3-Fe{sub 2}O{sub 3}-Pt which is showing of simultaneous effect of surface area and surface reactivity parameters.

Crystallographic phase transitions in actinide metals as a function of pressure

International Nuclear Information System (INIS)

Eriksson, O.; Soederlind, P.; Melsen, J.; Ahuja, R.; Johansson, B.

1993-01-01

We present first-principles calculations of the equilibrium volumes and crystal structures of the light actinides (Th--Pu). The calculated equilibrium volumes for fcc Th, bct Pu, α-U, and β-Np are found to agree reasonably well with the experimental data, and when comparing the total energies of the bcc, fcc, bct, α-U, and β-Np structures we obtain the correct crystal structures for all studied systems. Equilibrium volumes for Th--Pu, using a hypothetical fcc structure, have been calculated; although spin-orbit coupling is included in these calculations, the calculated equilibrium volume of Pu is smaller than for Np, in disagreement with experiment. Moreover, the calculated tetragonal elastic constant, C', is shown to be negative for bcc U, bcc Np, bcc Pu, and fcc Pu. Thus, our zero temperature calculations suggest that the bcc structure is unstable for these elements and that fcc Pu is also unstable. This is in conflict with experiment and we are led to the conclusion that temperature effects must be of crucial importance for stabilizing cubic structures in U, Np, and Pu. Further, as a function of decreasing volume we predict a crystal structure sequence fcc → bct → fcc in Th, a sequence α-U → bct → bcc in U, and a sequence β-Np → bct → bcc in Np. Also, a sequence of transitions in Sc as a function of decreasing volume have been calculated, namely hcp → fcc → ω → β-Np → bcc

Parametric Bayesian priors and better choice of negative examples improve protein function prediction.

Science.gov (United States)

Youngs, Noah; Penfold-Brown, Duncan; Drew, Kevin; Shasha, Dennis; Bonneau, Richard

2013-05-01

Computational biologists have demonstrated the utility of using machine learning methods to predict protein function from an integration of multiple genome-wide data types. Yet, even the best performing function prediction algorithms rely on heuristics for important components of the algorithm, such as choosing negative examples (proteins without a given function) or determining key parameters. The improper choice of negative examples, in particular, can hamper the accuracy of protein function prediction. We present a novel approach for choosing negative examples, using a parameterizable Bayesian prior computed from all observed annotation data, which also generates priors used during function prediction. We incorporate this new method into the GeneMANIA function prediction algorithm and demonstrate improved accuracy of our algorithm over current top-performing function prediction methods on the yeast and mouse proteomes across all metrics tested. Code and Data are available at: http://bonneaulab.bio.nyu.edu/funcprop.html

Characterization of Phase Transition in Heisenberg Fluids from Density Functional Theory

International Nuclear Information System (INIS)

Li Liangsheng; Li Li; Chen Xiaosong

2009-01-01

The phase transition of Heisenberg fluid has been investigated with the density functional theory in mean-field approximation (MF). The matrix of the second derivatives of the grand canonical potential Ω with respect to the particle density fluctuations and the magnetization fluctuations has been investigated and diagonalized. The smallest eigenvalue being 0 signalizes the phase instability and the related eigenvector characterizes this phase transition. We find a Curie line where the order parameter is pure magnetization and a spinodal where the order parameter is a mixture of particle density and magnetization. Along the spinodal, the character of phase instability changes continuously from predominant condensation to predominant ferromagnetic phase transition with the decrease of total density. The spinodal meets the Curie line at the critical endpoint with the reduced density ρ* = ρσ 3 = 0.224 and the reduced temperature T* = kT/ element of = 1.87 (σ is the diameter of Heisenberg hard sphere and element of is the coupling constant).

Predicted stability, structures, and magnetism of 3d transition metal nitrides: the M4N phases

NARCIS (Netherlands)

Fang, C.M.; Koster, R.S.; Li, W.F.; van Huis, M.A.

2014-01-01

The 3d transition metal nitrides M4N (Sc4N, Ti4N, V4N, Cr4N, Mn4N, Fe4N, Co4N, Ni4N, and Cu4N) have unique phase relationships, crystal structures, and electronic and magnetic properties. Here we present a systematic density functional theory (DFT) study on these transition metal nitrides, assessing

Temperature-dependent study of isotropic-nematic transition for a Gay-Berne fluid using density-functional theory

International Nuclear Information System (INIS)

Singh, Ram Chandra

2007-01-01

We have used the density-functional theory to study the effect of varying temperature on the isotropic-nematic transition of a fluid of molecules interacting via the Gay-Berne intermolecular potential. The nematic phase is found to be stable with respect to isotropic phase in the temperature range 0.80≤T*≤1.25. Pair correlation functions needed as input information in density-functional theory is calculated using the Percus-Yevick integral equation theory. We find that the density-functional theory is good for studying the isotropic-nematic transition in molecular fluids if the values of the pair-correlation functions in the isotropic phase are known accurately. We have also compared our results with computer simulation results wherever they are available

Pair distribution function and its relation to the glass transition in an amorphous alloy

International Nuclear Information System (INIS)

Basak, S.; Clarke, R.; Nagel, S.R.

1979-01-01

Data for the pair distribution function g (r) are presented as a function of temperature for amorphous Nb/sub 0.4/Ni/sub 0.6/. We show, based on a simple model, that g (r) varies linearly with T over a wide temperature range in the glass as was found empirically by Wendt and Abraham. We also find that in our glass the behavior of g (r) near the glass transition is, within experimental error, similar to what they found in their Monte Carlo calculation. We interpret the deviation from linearity at the glass transition as due to the onset of diffusive motion of the atoms

Determination of global and regional heart functions with minimum transit times

International Nuclear Information System (INIS)

Feinendegen, L.E.; Becker, V.; Vyska, K.; Freundlieb, C.; Bosiljanoff, P.

1980-01-01

The minimum transit time obviously represents the most constant flow parameter. By means of a constant, that was chosen to be 1.2 for cardiac flow, it is equal to the quotient of volume to flow and is also inversely related proportional to the fraction of ejection that is concerned. The first indicator passage through the heart is measured for the minimum cardiac transit time, whereby interesting regions were chosen for the two auricula, the two ventricula, the pulmonary artery and the aorta. The time activity characteristica obtained from the particular regions need a special smoothing by means of the gliding mean, so that the arrival times can easily be recognized. This way in one examination process the differences of arrival times respectively the minimal transit times can be obtained for each particular cardiac segment, the pulmonary circuit and the whole cardio-pulmonary circuit. The advantages of minimum cardiac transit time measurements are the simplicity and the speed of the noninvasive functional diagnostic with lower radiation load and accuracy and reproductability with low error limits, especially for the whole cardio-pulmonary MTT. The simultaneous acquisition of multiple cardiac segments is to emphasize a special way. For its particular values similar error widths were found as for the left ventricular function measurement with the triggered scintigraphy of the interior of the heart. A further advantage of the measurement is an almost problem-less application in body load. Therefore the MTT-measurement is especially useful for preventive diagnostics of coronary diseases. A combination of MTT-measurements of all segments of the small circuit with the triggered scintigraphy of the interior of the heart for analysis of regional left-ventricular ejection fractions and left-ventricular wall movements would essentially enrich the noninvasive cardiac diagnostics. (orig./APR) [de

Strength functions of primary transitions following thermal neutron capture in strontium

International Nuclear Information System (INIS)

Winter, C.; Lieb, K.P.

1989-01-01

The primary E1, M1 and E2 γ-radiation in 87,88,89 Sr observed after thermal neutron capture was compared with the predictions of single particle and giant resonance models. The nuclei feature a wide range of neutron binding energies between 6.3 and 11.1 MeV, which makes a 5.5 MeV spectrum of primary transition energies available for investigation. The (n, γ) reaction was used to estimate the parameters of the spin-flip M1 giant resonance in strontium. The total energy weighted M1 strength of this resonance exceeds the results of shell model and random phase approximation calculations for 90 Zr by a factor of 3-4. The E1 strengths were found to agree with the established giant dipole resonance model. The few data on primary E2 transitions do not allow to differentiate between the giant quadrupole resonance and the single particle models. (orig.)

PRISM offers a comprehensive genomic approach to transcription factor function prediction

KAUST Repository

Wenger, A. M.; Clarke, S. L.; Guturu, H.; Chen, J.; Schaar, B. T.; McLean, C. Y.; Bejerano, G.

2013-01-01

The human genome encodes 1500-2000 different transcription factors (TFs). ChIP-seq is revealing the global binding profiles of a fraction of TFs in a fraction of their biological contexts. These data show that the majority of TFs bind directly next to a large number of context-relevant target genes, that most binding is distal, and that binding is context specific. Because of the effort and cost involved, ChIP-seq is seldom used in search of novel TF function. Such exploration is instead done using expression perturbation and genetic screens. Here we propose a comprehensive computational framework for transcription factor function prediction. We curate 332 high-quality nonredundant TF binding motifs that represent all major DNA binding domains, and improve cross-species conserved binding site prediction to obtain 3.3 million conserved, mostly distal, binding site predictions. We combine these with 2.4 million facts about all human and mouse gene functions, in a novel statistical framework, in search of enrichments of particular motifs next to groups of target genes of particular functions. Rigorous parameter tuning and a harsh null are used to minimize false positives. Our novel PRISM (predicting regulatory information from single motifs) approach obtains 2543 TF function predictions in a large variety of contexts, at a false discovery rate of 16%. The predictions are highly enriched for validated TF roles, and 45 of 67 (67%) tested binding site regions in five different contexts act as enhancers in functionally matched cells.

PRISM offers a comprehensive genomic approach to transcription factor function prediction

KAUST Repository

Wenger, A. M.

2013-02-04

The human genome encodes 1500-2000 different transcription factors (TFs). ChIP-seq is revealing the global binding profiles of a fraction of TFs in a fraction of their biological contexts. These data show that the majority of TFs bind directly next to a large number of context-relevant target genes, that most binding is distal, and that binding is context specific. Because of the effort and cost involved, ChIP-seq is seldom used in search of novel TF function. Such exploration is instead done using expression perturbation and genetic screens. Here we propose a comprehensive computational framework for transcription factor function prediction. We curate 332 high-quality nonredundant TF binding motifs that represent all major DNA binding domains, and improve cross-species conserved binding site prediction to obtain 3.3 million conserved, mostly distal, binding site predictions. We combine these with 2.4 million facts about all human and mouse gene functions, in a novel statistical framework, in search of enrichments of particular motifs next to groups of target genes of particular functions. Rigorous parameter tuning and a harsh null are used to minimize false positives. Our novel PRISM (predicting regulatory information from single motifs) approach obtains 2543 TF function predictions in a large variety of contexts, at a false discovery rate of 16%. The predictions are highly enriched for validated TF roles, and 45 of 67 (67%) tested binding site regions in five different contexts act as enhancers in functionally matched cells.

Functional Independence in Late-Life: Maintaining Physical Functioning in Older Adulthood Predicts Daily Life Function after Age 80.

Science.gov (United States)

Vaughan, Leslie; Leng, Xiaoyan; La Monte, Michael J; Tindle, Hilary A; Cochrane, Barbara B; Shumaker, Sally A

2016-03-01

We examined physical functioning (PF) trajectories (maintaining, slowly declining, and rapidly declining) spanning 15 years in older women aged 65-80 and protective factors that predicted better current levels and less decline in functional independence outcomes after age 80. Women's Health Initiative extension participants who met criteria (enrolled in either the clinical trial or observational study cohort, >80 years at the data release cutoff, PF survey data from initial enrollment to age 80, and functional independence survey data after age 80) were included in these analyses (mean [SD] age = 84.0 [1.4] years; N = 10,478). PF was measured with the SF-36 (mean = 4.9 occasions). Functional independence was measured by self-reported level of dependence in basic and instrumental activities of daily living (ADLs and IADLs) (mean = 3.4 and 3.3 occasions). Maintaining consistent PF in older adulthood extends functional independence in ADL and IADL in late-life. Protective factors shared by ADL and IADL include maintaining PF over time, self-reported excellent or very good health, no history of hip fracture after age 55, and no history of cardiovascular disease. Better IADL function is uniquely predicted by a body mass index less than 25 and no depression. Less ADL and IADL decline is predicted by better self-reported health, and less IADL decline is uniquely predicted by having no history of hip fracture after age 55. Maintaining or improving PF and preventing injury and disease in older adulthood (ages 65-80) has far-reaching implications for improving late-life (after age 80) functional independence. © The Author 2016. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Negative to positive magnetoresistance transition in functionalization of carbon nanotube and polyaniline composite

Science.gov (United States)

Prasad Maity, Krishna; Tanty, Narendra; Patra, Ananya; Prasad, V.

2018-03-01

Electrical resistivity and magnetoresistance(MR) in polyaniline(PANI) with carbon nanotube(CNT) and functionalized carbon nanotube(fCNT) composites have been studied for different weight percentages down to the temperature 4.2 K and up to magnetic field 5 T. Resistivity increases significantly in composite at low temperature due to functionalization of CNT compared to only CNT. Interestingly a transition from negative to positive magnetoresistance has been observed when the filler is changed from pure CNT to functionalized CNT after a certain percentage (10wt%) as the effect of more disorder in fCNT/PANI composite. This result depicts that the MR has strong dependency on disorder in the composite system. The transition of MR has been explained on the basis of polaron-bipolaron model. The long range Coulomb interaction between two polarons screened by disorder in the composite of fCNT/PANI, increases the effective on-site Coulomb repulsion energy to form bipolaron which leads to change the sign of MR from negative to positive.

Ages and transit times as important diagnostics of model performance for predicting carbon dynamics in terrestrial vegetation models

Science.gov (United States)

Ceballos-Núñez, Verónika; Richardson, Andrew D.; Sierra, Carlos A.

2018-03-01

The global carbon cycle is strongly controlled by the source/sink strength of vegetation as well as the capacity of terrestrial ecosystems to retain this carbon. These dynamics, as well as processes such as the mixing of old and newly fixed carbon, have been studied using ecosystem models, but different assumptions regarding the carbon allocation strategies and other model structures may result in highly divergent model predictions. We assessed the influence of three different carbon allocation schemes on the C cycling in vegetation. First, we described each model with a set of ordinary differential equations. Second, we used published measurements of ecosystem C compartments from the Harvard Forest Environmental Measurement Site to find suitable parameters for the different model structures. And third, we calculated C stocks, release fluxes, radiocarbon values (based on the bomb spike), ages, and transit times. We obtained model simulations in accordance with the available data, but the time series of C in foliage and wood need to be complemented with other ecosystem compartments in order to reduce the high parameter collinearity that we observed, and reduce model equifinality. Although the simulated C stocks in ecosystem compartments were similar, the different model structures resulted in very different predictions of age and transit time distributions. In particular, the inclusion of two storage compartments resulted in the prediction of a system mean age that was 12-20 years older than in the models with one or no storage compartments. The age of carbon in the wood compartment of this model was also distributed towards older ages, whereas fast cycling compartments had an age distribution that did not exceed 5 years. As expected, models with C distributed towards older ages also had longer transit times. These results suggest that ages and transit times, which can be indirectly measured using isotope tracers, serve as important diagnostics of model structure

Can the care transitions measure predict rehospitalization risk or home health nursing use of home healthcare patients?

Science.gov (United States)

Ryvicker, Miriam; McDonald, Margaret V; Trachtenberg, Melissa; Peng, Timothy R; Sridharan, Sridevi; Feldman, Penny H

2013-01-01

The Care Transitions Measure (CTM) was designed to assess the quality of patient transitions from the hospital. Many hospitals are using the measure to inform their efforts to improve transitional care. We sought to determine if the measure would have utility for home healthcare providers by predicting newly admitted patients at heightened risk for emergency department use, rehospitalization, or increased home health nursing visits. The CTM was administered to 495 home healthcare patients shortly after hospital discharge and home healthcare admission. Follow-up interviews were completed 30 and 60 days post hospital discharge. Interview data were supplemented with agency assessment and service use data. We did not find evidence that the CTM could predict home healthcare patients having an elevated risk for emergent care, rehospitalization, or higher home health nursing use. Because Medicare/Medicaid-certified home healthcare providers already use a comprehensive, mandated start of care assessment, the CTM may not provide them additional crucial information. Process and outcome measurement is increasingly becoming part of usual care. Selection of measures appropriate for each service setting requires thorough site-specific evaluation. In light of our findings, we cannot recommend the CTM as an additional measure in the home healthcare setting. © 2013 National Association for Healthcare Quality.

Feature Selection and the Class Imbalance Problem in Predicting Protein Function from Sequence

NARCIS (Netherlands)

Al-Shahib, A.; Breitling, R.; Gilbert, D.

2005-01-01

Abstract: When the standard approach to predict protein function by sequence homology fails, other alternative methods can be used that require only the amino acid sequence for predicting function. One such approach uses machine learning to predict protein function directly from amino acid sequence

H/L transition time estimation in JET using conformal predictors

Energy Technology Data Exchange (ETDEWEB)

Gonzalez, S., E-mail: sergio.gonzalez@ciemat.es [Asociacion EURATOM/CIEMAT para Fusion, Madrid 28040 (Spain); Vega, J. [Asociacion EURATOM/CIEMAT para Fusion, Madrid 28040 (Spain); Murari, A. [Consorzio RFX, Associazione EURATOM/ENEA per la Fusione, Padova 4-25127 (Italy); Pereira, A. [Asociacion EURATOM/CIEMAT para Fusion, Madrid 28040 (Spain); Dormido-Canto, S.; Ramirez, J.M. [Departamento de Informatica y Automatica, UNED, Madrid 28040 (Spain)

2012-12-15

Highlights: Black-Right-Pointing-Pointer H/L transitions have been predicted using H/L and L/H models. Black-Right-Pointing-Pointer Models have been built using conformal predictors to hedge the prediction with confidence and credibility measures. Black-Right-Pointing-Pointer Models have been trained using linear and radial basis function kernels. Black-Right-Pointing-Pointer Conformal measures have proven their usefulness to validate data-driven models. - Abstract: Recent advances in data mining allow the automatic recognition of physical phenomena in the databases of fusion devices without human intervention. This is important to create large databases of physical events (thereby increasing the statistical relevance) in an unattended manner. Important examples are the L/H and H/L transitions. In this contribution, a novel technique is introduced to automatically locate H/L transitions in JET by using conformal predictors. The focus is on H/L transitions because typically there is not a clear signature in the time series of the most widely available signals to recognize the change of confinement. Conformal predictors hedge their prediction by means of two parameters: confidence and credibility. The technique has been based on binary supervised classifiers to separate the samples of the respective confinement modes. Results with several underlying classifiers are presented.

Winding Up of the Wave-Function Phase by an Insulator-to-Superfluid Transition in a Ring of Coupled Bose-Einstein Condensates

International Nuclear Information System (INIS)

Dziarmaga, Jacek; Meisner, Jakub; Zurek, Wojciech H.

2008-01-01

We study phase transition from the Mott insulator to superfluid in a periodic optical lattice. Kibble-Zurek mechanism predicts buildup of winding number through random walk of BEC phases, with the step size scaling as a third root of transition rate. We confirm this and demonstrate that this scaling accounts for the net winding number after the transition

Fusion excitation functions involving transitional nuclei

Energy Technology Data Exchange (ETDEWEB)

Rehm, K.E.; Jiang, C.L.; Esbensen, H. [and others

1995-08-01

Measurements of fusion excitation functions involving transitional nuclei {sup 78}Kr and {sup 100}Mo showed a different behavior at low energies, if compared to measurements with {sup 86}Kr and {sup 92}Mo. This points to a possible influence of nuclear structure on the fusion process. One way to characterize the structure of vibrational nuclei is via their restoring force parameters C{sub 2} which can be calculated from the energy of the lowest 2{sup +} state and the corresponding B(E2) value. A survey of the even-even nuclei between A = 28-150 shows strong variations in C{sub 2} values spanning two orders of magnitude. The lowest values for C{sub 2} are observed for {sup 78}Kr, {sup 104}Ru and {sup 124}Xe followed by {sup 74,76}Ge, {sup 74,76}Se, {sup 100}Mo and {sup 110}Pd. In order to learn more about the influence of {open_quotes}softness{close_quotes} on the sub-barrier fusion enhancement, we measured cross sections for evaporation residue production for the systems {sup 78}Kr + {sup 104}Ru and {sup 78}Kr + {sup 76}Ge with the gas-filled magnet technique. For both systems, fusion excitation functions involving the closed neutron shell nucleus {sup 86}Kr were measured previously. The data are presently being analyzed.

Integrative approaches to the prediction of protein functions based on the feature selection

Directory of Open Access Journals (Sweden)

Lee Hyunju

2009-12-01

Full Text Available Abstract Background Protein function prediction has been one of the most important issues in functional genomics. With the current availability of various genomic data sets, many researchers have attempted to develop integration models that combine all available genomic data for protein function prediction. These efforts have resulted in the improvement of prediction quality and the extension of prediction coverage. However, it has also been observed that integrating more data sources does not always increase the prediction quality. Therefore, selecting data sources that highly contribute to the protein function prediction has become an important issue. Results We present systematic feature selection methods that assess the contribution of genome-wide data sets to predict protein functions and then investigate the relationship between genomic data sources and protein functions. In this study, we use ten different genomic data sources in Mus musculus, including: protein-domains, protein-protein interactions, gene expressions, phenotype ontology, phylogenetic profiles and disease data sources to predict protein functions that are labelled with Gene Ontology (GO terms. We then apply two approaches to feature selection: exhaustive search feature selection using a kernel based logistic regression (KLR, and a kernel based L1-norm regularized logistic regression (KL1LR. In the first approach, we exhaustively measure the contribution of each data set for each function based on its prediction quality. In the second approach, we use the estimated coefficients of features as measures of contribution of data sources. Our results show that the proposed methods improve the prediction quality compared to the full integration of all data sources and other filter-based feature selection methods. We also show that contributing data sources can differ depending on the protein function. Furthermore, we observe that highly contributing data sets can be similar among

Protein Function Prediction Based on Sequence and Structure Information

KAUST Repository

Smaili, Fatima Z.

2016-05-25

The number of available protein sequences in public databases is increasing exponentially. However, a significant fraction of these sequences lack functional annotation which is essential to our understanding of how biological systems and processes operate. In this master thesis project, we worked on inferring protein functions based on the primary protein sequence. In the approach we follow, 3D models are first constructed using I-TASSER. Functions are then deduced by structurally matching these predicted models, using global and local similarities, through three independent enzyme commission (EC) and gene ontology (GO) function libraries. The method was tested on 250 “hard” proteins, which lack homologous templates in both structure and function libraries. The results show that this method outperforms the conventional prediction methods based on sequence similarity or threading. Additionally, our method could be improved even further by incorporating protein-protein interaction information. Overall, the method we use provides an efficient approach for automated functional annotation of non-homologous proteins, starting from their sequence.

Topological transitions at finite temperatures: A real-time numerical approach

International Nuclear Information System (INIS)

Grigoriev, D.Yu.; Rubakov, V.A.; Shaposhnikov, M.E.

1989-01-01

We study topological transitions at finite temperatures within the (1+1)-dimensional abelian Higgs model by a numerical simulation in real time. Basic ideas of the real-time approach are presented and some peculiarities of the Metropolis technique are discussed. It is argued that the processes leading to topological transitions are of classical origin; the transitions can be observed by solving the classical field equations in real time. We show that the topological transitions actually pass via the sphaleron configuration. The transition rate as a function of temperature is found to be in good agreement with the analytical predictions. No extra suppression of the rate is observed. The conditions of applicability of our approach are discussed. The temperature interval where the low-temperature broken phase persists is estimated. (orig.)

Predictive assessment of models for dynamic functional connectivity

DEFF Research Database (Denmark)

Nielsen, Søren Føns Vind; Schmidt, Mikkel Nørgaard; Madsen, Kristoffer Hougaard

2018-01-01

represent functional brain networks as a meta-stable process with a discrete number of states; however, there is a lack of consensus on how to perform model selection and learn the number of states, as well as a lack of understanding of how different modeling assumptions influence the estimated state......In neuroimaging, it has become evident that models of dynamic functional connectivity (dFC), which characterize how intrinsic brain organization changes over time, can provide a more detailed representation of brain function than traditional static analyses. Many dFC models in the literature...... dynamics. To address these issues, we consider a predictive likelihood approach to model assessment, where models are evaluated based on their predictive performance on held-out test data. Examining several prominent models of dFC (in their probabilistic formulations) we demonstrate our framework...

Robust Predictive Functional Control for Flight Vehicles Based on Nonlinear Disturbance Observer

Directory of Open Access Journals (Sweden)

Yinhui Zhang

2015-01-01

Full Text Available A novel robust predictive functional control based on nonlinear disturbance observer is investigated in order to address the control system design for flight vehicles with significant uncertainties, external disturbances, and measurement noise. Firstly, the nonlinear longitudinal dynamics of the flight vehicle are transformed into linear-like state-space equations with state-dependent coefficient matrices. And then the lumped disturbances are considered in the linear structure predictive model of the predictive functional control to increase the precision of the predictive output and resolve the intractable mismatched disturbance problem. As the lumped disturbances cannot be derived or measured directly, the nonlinear disturbance observer is applied to estimate the lumped disturbances, which are then introduced to the predictive functional control to replace the unknown actual lumped disturbances. Consequently, the robust predictive functional control for the flight vehicle is proposed. Compared with the existing designs, the effectiveness and robustness of the proposed flight control are illustrated and validated in various simulation conditions.

Automatic single- and multi-label enzymatic function prediction by machine learning

Directory of Open Access Journals (Sweden)

Shervine Amidi

2017-03-01

Full Text Available The number of protein structures in the PDB database has been increasing more than 15-fold since 1999. The creation of computational models predicting enzymatic function is of major importance since such models provide the means to better understand the behavior of newly discovered enzymes when catalyzing chemical reactions. Until now, single-label classification has been widely performed for predicting enzymatic function limiting the application to enzymes performing unique reactions and introducing errors when multi-functional enzymes are examined. Indeed, some enzymes may be performing different reactions and can hence be directly associated with multiple enzymatic functions. In the present work, we propose a multi-label enzymatic function classification scheme that combines structural and amino acid sequence information. We investigate two fusion approaches (in the feature level and decision level and assess the methodology for general enzymatic function prediction indicated by the first digit of the enzyme commission (EC code (six main classes on 40,034 enzymes from the PDB database. The proposed single-label and multi-label models predict correctly the actual functional activities in 97.8% and 95.5% (based on Hamming-loss of the cases, respectively. Also the multi-label model predicts all possible enzymatic reactions in 85.4% of the multi-labeled enzymes when the number of reactions is unknown. Code and datasets are available at https://figshare.com/s/a63e0bafa9b71fc7cbd7.

Statistical Prediction of Laminar-turbulent Transition

National Research Council Canada - National Science Library

Rubinstein, Robert

2000-01-01

... on representative stability theories including the resonant triad model and the parabolized stability equations. The first type of model can describe the effect of initial phase differences among disturbance modes on transition location...

Transition-state theory predicts clogging at the microscale

Science.gov (United States)

Laar, T. Van De; Klooster, S. Ten; Schroën, K.; Sprakel, J.

2016-06-01

Clogging is one of the main failure mechanisms encountered in industrial processes such as membrane filtration. Our understanding of the factors that govern the build-up of fouling layers and the emergence of clogs is largely incomplete, so that prevention of clogging remains an immense and costly challenge. In this paper we use a microfluidic model combined with quantitative real-time imaging to explore the influence of pore geometry and particle interactions on suspension clogging in constrictions, two crucial factors which remain relatively unexplored. We find a distinct dependence of the clogging rate on the entrance angle to a membrane pore which we explain quantitatively by deriving a model, based on transition-state theory, which describes the effect of viscous forces on the rate with which particles accumulate at the channel walls. With the same model we can also predict the effect of the particle interaction potential on the clogging rate. In both cases we find excellent agreement between our experimental data and theory. A better understanding of these clogging mechanisms and the influence of design parameters could form a stepping stone to delay or prevent clogging by rational membrane design.

Assessment of personality functioning in the transition from adolescent to adult life: preliminary findings.

Science.gov (United States)

Naughton, M; Oppenheim, A; Hill, J

1996-01-01

The Adolescent to Adult Personality Functioning Assessment (ADAPFA) a modification of the Adult Personality Functioning Assessment (APFA) is described. It may be used to assess specific and general social dysfunction in the transition from childhood to adult life. Two raters independently rated 38 audiotaped interviews to test the interrater reliability of the instrument. The relationship between dysfunction in specific domains and overall psychosocial dysfunction was examined. Interrater reliabilities for the total ADAPFA score and for the majority of the domains were high. Agreement on type of dysfunction and on categorical ratings indicating the presence of personality disorder were good. The ADAPFA is a useful measure of interpersonal and social role performance in the transition between adolescent and adult life.

Transition prediction on the NORDTANK 500/41 turbine rotor

Energy Technology Data Exchange (ETDEWEB)

Soerensen, N.N.

2002-09-01

A new simplified transition model for wind turbine blades is described along with the implementation in the EllipSys3D code. The method is based on a sectional treatment of the turbine blade under the assumption of chordwise flow, and lookup tables of transition point location computed by external 2D programs. The coupling of the 2D transition point location and the 3D sectional flow is performed through the stagnation point location. The method is applied to a single rotor case, the NORDTANK 500/41 rotor with LM19.1 blades. The transitional computations show improved agreement with measurements for wind speeds between 11 and 15 m/s. For higher wind speeds, the validity of the transition location computed by the 2D XFOIL code is questionable, and the results cannot be trusted. Analysis of the results comparing fully turbulent and transitional spanwise distributions of tangential forces, reveal that the decrease in power production when applying the transition model is mainly a consequence of the decrease in driving force on the inboard part of the blade between 5 and 12 meter radius. The results are very encouraging, and further studies of other rotors are needed for further validation. (au)

Transition from boiling to two-phase forced convection

International Nuclear Information System (INIS)

Maroti, L.

1985-01-01

The paper presents a method for the prediction of the boundary points of the transition region between fully developed boiling and two-phase forced convection. It is shown that the concept for the determination of the onset of fully developed boiling can also be applied for the calculation of the point where the heat transfer is effected again by the forced convection. Similarly, the criterion for the onset of nucleate boiling can be used for the definition of the point where boiling is completely suppressed and pure two-phase forced convection starts. To calculate the heat transfer coefficient for the transition region, an equation is proposed that applies the boundary points and a relaxation function ensuring the smooth transition of the heat transfer coefficient at the boundaries

Transitional region of phase transitions in nuclear models

Energy Technology Data Exchange (ETDEWEB)

Kotze, A A

1988-01-01

The phase transition in an exactly solvable nuclear model, the Lipkin model, is scrutinised, first using Hartree-Fock methods or the plain mean flield approximation, and then using projected wave functions. It turns out that the plain mean field is not reliable in the transitional region. Although the projection methods give better resutls in the transitional region, it leads to spurious singularities. While the energy of the projection before variation is slightly better than its projection after variation counterpart, the perfomance of the wave function is considerably worse in the transitional region. The model's wave function undergoes dramatic changes in the transitional region. The mechanism that brings about these changes is studied within a model Hamiltonian that can reproduce the Lipkin model mathematically. It turns out that the numerous exceptional points found in the transitional region, bring about the change of the ground state wave function. Exceptional points are associated with level crossings in the complex plane. These level crossings can be seen as level repulsions in the spectrum. Level repulsion and a sensitive dependence of the system on some external parameter are characteristics of chaotic behaviour. These two features are found in the transitional region of the Lipkin model. In order to study chaos, one has to resort to a statistical analysis. A measure of the chaotic behaviour of systems, the ..delta../sub 3/ statistic, is introduced. The results show that the Lipkin model is harmonic, even in the transitional region. For the Lipkin model the exceptional points are regularly distributed in the complex plane. In a total chaotic system the points would be randomly distributed.

Concomitant prediction of function and fold at the domain level with GO-based profiles.

Science.gov (United States)

Lopez, Daniel; Pazos, Florencio

2013-01-01

Predicting the function of newly sequenced proteins is crucial due to the pace at which these raw sequences are being obtained. Almost all resources for predicting protein function assign functional terms to whole chains, and do not distinguish which particular domain is responsible for the allocated function. This is not a limitation of the methodologies themselves but it is due to the fact that in the databases of functional annotations these methods use for transferring functional terms to new proteins, these annotations are done on a whole-chain basis. Nevertheless, domains are the basic evolutionary and often functional units of proteins. In many cases, the domains of a protein chain have distinct molecular functions, independent from each other. For that reason resources with functional annotations at the domain level, as well as methodologies for predicting function for individual domains adapted to these resources are required.We present a methodology for predicting the molecular function of individual domains, based on a previously developed database of functional annotations at the domain level. The approach, which we show outperforms a standard method based on sequence searches in assigning function, concomitantly predicts the structural fold of the domains and can give hints on the functionally important residues associated to the predicted function.

Kosterlitz-Thouless transition in high-Tc superconductor films

International Nuclear Information System (INIS)

Davis, L.C.; Beasley, M.R.; Scalapino, D.J.

1990-01-01

Dynamical theory for the polarization of bound vortex-antivortex pairs near the Kosterlitz-Thouless transition (T KT =88.4 K) has been applied to thin films of YBa 2 Cu 3 O 7 . Calculations show that the correct order of magnitude is predicted for the loss function ωG/c 2 at T KT , but the temperature dependence below the transition is wrong. The theoretical value drops much more rapidly with decreasing temperature than observed experimentally. Similar disagreement is found for the penetration depth λ(T). Estimates of the loss function at microwave frequencies show rather large effects near the critical temperature, but these become negligible by 80 K. The performance of microwave devices operating at liquid-N 2 temperature should not be degraded by vortex-antivortex pairs

Disorganized Symptoms and Executive Functioning Predict Impaired Social Functioning in Subjects at Risk for Psychosis

OpenAIRE

Eslami, Ali; Jahshan, Carol; Cadenhead, Kristin S.

2011-01-01

Predictors of social functioning deficits were assessed in 22 individuals “at risk” for psychosis. Disorganized symptoms and executive functioning predicted social functioning at follow-up. Early intervention efforts that focus on social and cognitive skills are indicated in this vulnerable population.

Patient-specific prediction of functional recovery after stroke.

Science.gov (United States)

Douiri, Abdel; Grace, Justin; Sarker, Shah-Jalal; Tilling, Kate; McKevitt, Christopher; Wolfe, Charles DA; Rudd, Anthony G

2017-07-01

Background and aims Clinical predictive models for stroke recovery could offer the opportunity of targeted early intervention and more specific information for patients and carers. In this study, we developed and validated a patient-specific prognostic model for monitoring recovery after stroke and assessed its clinical utility. Methods Four hundred and ninety-five patients from the population-based South London Stroke Register were included in a substudy between 2002 and 2004. Activities of daily living were assessed using Barthel Index) at one, two, three, four, six, eight, 12, 26, and 52 weeks after stroke. Penalized linear mixed models were developed to predict patients' functional recovery trajectories. An external validation cohort included 1049 newly registered stroke patients between 2005 and 2011. Prediction errors on discrimination and calibration were assessed. The potential clinical utility was evaluated using prognostic accuracy measurements and decision curve analysis. Results Predictive recovery curves showed good accuracy, with root mean squared deviation of 3 Barthel Index points and a R 2 of 83% up to one year after stroke in the external cohort. The negative predictive values of the risk of poor recovery (Barthel Index <8) at three and 12 months were also excellent, 96% (95% CI [93.6-97.4]) and 93% [90.8-95.3], respectively, with a potential clinical utility measured by likelihood ratios (LR+:17 [10.8-26.8] at three months and LR+:11 [6.5-17.2] at 12 months). Decision curve analysis showed an increased clinical benefit, particularly at threshold probabilities of above 5% for predictive risk of poor outcomes. Conclusions A recovery curves tool seems to accurately predict progression of functional recovery in poststroke patients.

Size and pressure effects on glass transition temperature of poly (methyl methacrylate) thin films

International Nuclear Information System (INIS)

Lang, X.Y.; Zhang, G.H.; Lian, J.S.; Jiang, Q.

2006-01-01

A simple and unified model, without any adjustable parameter, is developed for size and pressure effects on glass transition temperatures of nanopolymers. The model is based on a model for size dependent glass transition temperature of nanopolymer glasses under ambient pressure, and a pressure-dependent function of the root of mean-square displacement of atom vibration. It is found that the size- and pressure-dependent glass transition temperatures of free-standing films or supported films having weak interaction with substrates decreases with decreasing of pressure and size. However, the glass transition temperature of supported films having strong interaction with substrates increases with the increase of pressure and the decrease of size. The predicted results correspond with available experimental evidences for atactic-Poly (methyl methacrylate) thin films under hydrostatic pressure or under the pressure induced by supercritical fluid CO 2 . In addition, the predicted glass transition temperature of isotactic-Poly (methyl methacrylate) thin films under ambient pressure is consistent with available experimental evidences

Mixed-order phase transition in a colloidal crystal

Science.gov (United States)

Alert, Ricard; Tierno, Pietro; Casademunt, Jaume

2017-12-01

Mixed-order phase transitions display a discontinuity in the order parameter like first-order transitions yet feature critical behavior like second-order transitions. Such transitions have been predicted for a broad range of equilibrium and nonequilibrium systems, but their experimental observation has remained elusive. Here, we analytically predict and experimentally realize a mixed-order equilibrium phase transition. Specifically, a discontinuous solid-solid transition in a 2D crystal of paramagnetic colloidal particles is induced by a magnetic field H. At the transition field Hs, the energy landscape of the system becomes completely flat, which causes diverging fluctuations and correlation length ξ∝|H2-Hs2|-1/2. Mean-field critical exponents are predicted, since the upper critical dimension of the transition is du=2. Our colloidal system provides an experimental test bed to probe the unconventional properties of mixed-order phase transitions.

Mixed-order phase transition in a colloidal crystal.

Science.gov (United States)

Alert, Ricard; Tierno, Pietro; Casademunt, Jaume

2017-12-05

Mixed-order phase transitions display a discontinuity in the order parameter like first-order transitions yet feature critical behavior like second-order transitions. Such transitions have been predicted for a broad range of equilibrium and nonequilibrium systems, but their experimental observation has remained elusive. Here, we analytically predict and experimentally realize a mixed-order equilibrium phase transition. Specifically, a discontinuous solid-solid transition in a 2D crystal of paramagnetic colloidal particles is induced by a magnetic field [Formula: see text] At the transition field [Formula: see text], the energy landscape of the system becomes completely flat, which causes diverging fluctuations and correlation length [Formula: see text] Mean-field critical exponents are predicted, since the upper critical dimension of the transition is [Formula: see text] Our colloidal system provides an experimental test bed to probe the unconventional properties of mixed-order phase transitions.

Assessing Uncertainties in Boundary Layer Transition Predictions for HIFiRE-1 at Non-zero Angles of Attack

Science.gov (United States)

Marek, Lindsay C.

2011-01-01

Boundary layer stability was analyzed for the HIFiRE-1 flight vehicle geometry for ground tests conducted at the CUBRC LENS I hypersonic shock test facility and the Langley Research Center (LaRC) 20- inch Mach 6 Tunnel. Boundary layer stability results were compared to transition onset location obtained from discrete heat transfer measurements from thin film gauges during the CUBRC test and spatially continuous heat transfer measurements from thermal phosphor paint data during the LaRC test. The focus of this analysis was on conditions at non-zero angles of attack as stability analysis has already been performed at zero degrees angle of attack. Also, the transition onset data obtained during flight testing was at nonzero angles of attack, so this analysis could be expanded in the future to include the results of the flight test data. Stability analysis was performed using the 2D parabolized stability software suite STABL (Stability and Transition Analysis for Hypersonic Boundary Layers) developed at the University of Minnesota and the mean flow solutions were computed using the DPLR finite volume Navier-Stokes computational fluid dynamics (CFD) solver. A center line slice of the 3D mean flow solution was used for the stability analysis to incorporate the angle of attack effects while still taking advantage of the 2D STABL software suite. The N-factors at transition onset and the value of Re(sub theta)/M(sub e), commonly used to predict boundary layer transition onset, were compared for all conditions analyzed. Ground test data was analyzed at Mach 7.2 and Mach 6.0 and angles of attack of 1deg, 3deg and 5deg. At these conditions, the flow was found to be second mode dominant for the HIFiRE-1 slender cone geometry. On the leeward side of the vehicle, a strong trend of transition onset location with angle of attack was observed as the boundary layer on the leeward side of the vehicle developed inflection points at streamwise positions on the vehicle that correlated to

Tuning Glass Transition in Polymer Nanocomposites with Functionalized Cellulose Nanocrystals through Nanoconfinement.

Science.gov (United States)

Qin, Xin; Xia, Wenjie; Sinko, Robert; Keten, Sinan

2015-10-14

Cellulose nanocrystals (CNCs) exhibit impressive interfacial and mechanical properties that make them promising candidates to be used as fillers within nanocomposites. While glass-transition temperature (Tg) is a common metric for describing thermomechanical properties, its prediction is extremely difficult as it depends on filler surface chemistry, volume fraction, and size. Here, taking CNC-reinforced poly(methyl-methacrylate) (PMMA) nanocomposites as a relevant model system, we present a multiscale analysis that combines atomistic molecular dynamics (MD) surface energy calculations with coarse-grained (CG) simulations of relaxation dynamics near filler-polymer interfaces to predict composite properties. We discover that increasing the volume fraction of CNCs results in nanoconfinement effects that lead to an appreciation of the composite Tg provided that strong interfacial interactions are achieved, as in the case of TEMPO-mediated surface modifications that promote hydrogen bonding. The upper and lower bounds of shifts in Tg are predicted by fully accounting for nanoconfinement and interfacial properties, providing new insight into tuning these aspects in nanocomposite design. Our multiscale, materials-by-design framework is validated by recent experiments and breaks new ground in predicting, without any empirical parameters, key structure-property relationships for nanocomposites.

A study of isotropic-nematic transition of quadrupolar Gay-Berne fluid using density-functional theory approach

Science.gov (United States)

Singh, Ram Chandra; Ram, Jokhan

2011-11-01

The effects of quadrupole moments on the isotropic-nematic (IN) phase transitions are studied using the density-functional theory (DFT) for a Gay-Berne (GB) fluid for a range of length-to-breadth parameters ? in the reduced temperature range ? . The pair-correlation functions of the isotropic phase, which enter into the DFT as input parameters are found by solving the Percus-Yevick integral equation theory. The method used involves an expansion of angle-dependent functions appearing in the integral equations in terms of spherical harmonics and the harmonic coefficients are obtained by an iterative algorithm. All the terms of harmonic coefficients which involve l indices up to less than or equal to 6 are considered. The numerical accuracy of the results depends on the number of spherical harmonic coefficients considered for each orientation-dependent function. As the length-to-breadth ratio of quadrupolar GB molecules is increased, the IN transition is seen to move to lower density (and pressure) at a given temperature. It has been observed that the DFT is good to study the IN transitions in such fluids. The theoretical results have also been compared with the computer simulation results wherever they are available.

Predicting Protein Function via Semantic Integration of Multiple Networks.

Science.gov (United States)

Yu, Guoxian; Fu, Guangyuan; Wang, Jun; Zhu, Hailong

2016-01-01

Determining the biological functions of proteins is one of the key challenges in the post-genomic era. The rapidly accumulated large volumes of proteomic and genomic data drives to develop computational models for automatically predicting protein function in large scale. Recent approaches focus on integrating multiple heterogeneous data sources and they often get better results than methods that use single data source alone. In this paper, we investigate how to integrate multiple biological data sources with the biological knowledge, i.e., Gene Ontology (GO), for protein function prediction. We propose a method, called SimNet, to Semantically integrate multiple functional association Networks derived from heterogenous data sources. SimNet firstly utilizes GO annotations of proteins to capture the semantic similarity between proteins and introduces a semantic kernel based on the similarity. Next, SimNet constructs a composite network, obtained as a weighted summation of individual networks, and aligns the network with the kernel to get the weights assigned to individual networks. Then, it applies a network-based classifier on the composite network to predict protein function. Experiment results on heterogenous proteomic data sources of Yeast, Human, Mouse, and Fly show that, SimNet not only achieves better (or comparable) results than other related competitive approaches, but also takes much less time. The Matlab codes of SimNet are available at https://sites.google.com/site/guoxian85/simnet.

Identification of key residues for protein conformational transition using elastic network model.

Science.gov (United States)

Su, Ji Guo; Xu, Xian Jin; Li, Chun Hua; Chen, Wei Zu; Wang, Cun Xin

2011-11-07

Proteins usually undergo conformational transitions between structurally disparate states to fulfill their functions. The large-scale allosteric conformational transitions are believed to involve some key residues that mediate the conformational movements between different regions of the protein. In the present work, a thermodynamic method based on the elastic network model is proposed to predict the key residues involved in protein conformational transitions. In our method, the key functional sites are identified as the residues whose perturbations largely influence the free energy difference between the protein states before and after transition. Two proteins, nucleotide binding domain of the heat shock protein 70 and human/rat DNA polymerase β, are used as case studies to identify the critical residues responsible for their open-closed conformational transitions. The results show that the functionally important residues mainly locate at the following regions for these two proteins: (1) the bridging point at the interface between the subdomains that control the opening and closure of the binding cleft; (2) the hinge region between different subdomains, which mediates the cooperative motions between the corresponding subdomains; and (3) the substrate binding sites. The similarity in the positions of the key residues for these two proteins may indicate a common mechanism in their conformational transitions.

An Influence Function Method for Predicting Store Aerodynamic Characteristics during Weapon Separation,

Science.gov (United States)

1981-05-14

8217 AO-Ail 777 GRUMMAN AEROSPACE CORP BETHPAGE NY F/G 20/4 AN INFLUENCE FUNCTION METHOD FOR PREDICTING STORE AERODYNAMIC C--ETCCU) MAY 8 1 R MEYER, A...CENKO, S YARDS UNCLASSIFIED N ’.**~~N**n I EHEEKI j~j .25 Q~4 111110 111_L 5. AN INFLUENCE FUNCTION METHOD FOR PREDICTING STORE AERODYNAMIC...extended to their logical conclusion one is led quite naturally to consideration of an " Influence Function Method" for I predicting store aerodynamic

Prediction of postoperative pulmonary function using 99mTc-MAA perfusion lung SPECT

International Nuclear Information System (INIS)

Hosokawa, Nobuyuki; Tanabe, Masatada; Satoh, Katashi; Takashima, Hitoshi; Ohkawa, Motoomi; Maeda, Masazumi; Tamai, Toyosato; Kojima, Kanji.

1995-01-01

In order to predict postoperative pulmonary function, 99m Tc-MAA perfusion lung SPECT and spirometry were performed preoperatively in 52 patients with resectable primary lung cancer; 44 underwent lobectomy, eight pneumonectomy. Local pulmonary function (called local effective volume) was evaluated according to the degree of radionuclide distribution of each voxel in the SPECT images. The total effective volume was defined as the sum of the local effective volume, and the residual effective volume was the total effective volume excluding loss after operation. Predicted pulmonary function (VC and FEV 1.0) was calculated by the following formula: Predicted value=preoperative value x percent of the residual effective volume. Postoperative pulmonary function was predicted in the same patients by means of 99m Tc-MAA perfusion lung planar scintigraphy and X-ray CT. The patients were reinvestigated with spirometry at one and four months after surgery, and the values were compared with the predicted values. The correlations between the predicted values using SPECT and measured postoperative pulmonary function were highly significant (VC: r=0.867, FEV1.0: r=0.864 one month after operation; VC: r=0.860, FEV1.0: r=0.907 4 months after operation). The predicted values calculated using SPECT were accurate compared with the predicted values calculated using planar scintigraphy or X-ray CT. The patients with predicted FEV1.0 of less than 0.8 liter required home oxygen therapy. This method is valuable for the prediction of postoperative pulmonary function before the surgical procedure. (author)

Regional differences in prediction models of lung function in Germany

Directory of Open Access Journals (Sweden)

Schäper Christoph

2010-04-01

Full Text Available Abstract Background Little is known about the influencing potential of specific characteristics on lung function in different populations. The aim of this analysis was to determine whether lung function determinants differ between subpopulations within Germany and whether prediction equations developed for one subpopulation are also adequate for another subpopulation. Methods Within three studies (KORA C, SHIP-I, ECRHS-I in different areas of Germany 4059 adults performed lung function tests. The available data consisted of forced expiratory volume in one second, forced vital capacity and peak expiratory flow rate. For each study multivariate regression models were developed to predict lung function and Bland-Altman plots were established to evaluate the agreement between predicted and measured values. Results The final regression equations for FEV1 and FVC showed adjusted r-square values between 0.65 and 0.75, and for PEF they were between 0.46 and 0.61. In all studies gender, age, height and pack-years were significant determinants, each with a similar effect size. Regarding other predictors there were some, although not statistically significant, differences between the studies. Bland-Altman plots indicated that the regression models for each individual study adequately predict medium (i.e. normal but not extremely high or low lung function values in the whole study population. Conclusions Simple models with gender, age and height explain a substantial part of lung function variance whereas further determinants add less than 5% to the total explained r-squared, at least for FEV1 and FVC. Thus, for different adult subpopulations of Germany one simple model for each lung function measures is still sufficient.

Resting-State Functional Connectivity Predicts Cognitive Impairment Related to Alzheimer's Disease

Directory of Open Access Journals (Sweden)

Qi Lin

2018-04-01

Full Text Available Resting-state functional connectivity (rs-FC is a promising neuromarker for cognitive decline in aging population, based on its ability to reveal functional differences associated with cognitive impairment across individuals, and because rs-fMRI may be less taxing for participants than task-based fMRI or neuropsychological tests. Here, we employ an approach that uses rs-FC to predict the Alzheimer's Disease Assessment Scale (11 items; ADAS11 scores, which measure overall cognitive functioning, in novel individuals. We applied this technique, connectome-based predictive modeling, to a heterogeneous sample of 59 subjects from the Alzheimer's Disease Neuroimaging Initiative, including normal aging, mild cognitive impairment, and AD subjects. First, we built linear regression models to predict ADAS11 scores from rs-FC measured with Pearson's r correlation. The positive network model tested with leave-one-out cross validation (LOOCV significantly predicted individual differences in cognitive function from rs-FC. In a second analysis, we considered other functional connectivity features, accordance and discordance, which disentangle the correlation and anticorrelation components of activity timecourses between brain areas. Using partial least square regression and LOOCV, we again built models to successfully predict ADAS11 scores in novel individuals. Our study provides promising evidence that rs-FC can reveal cognitive impairment in an aging population, although more development is needed for clinical application.

Prediction of flow rates through an orifice at pressures corresponding to the transition between molecular and isentropic flow

International Nuclear Information System (INIS)

DeMuth, S.F.; Watson, J.S.

1985-01-01

A model of compressible flow through an orifice, in the region of transition from free molecular to isentropic expansion flow, has been developed and tested for accuracy. The transitional or slip regime is defined as the conditions where molecular interactions are too many for free molecular flow modeling, yet not great enough for isentropic expansion flow modeling. Due to a lack of literature establishing a well-accepted model for predicting transitional flow, it was felt such work would be beneficial. The model is nonlinear and cannot be satisfactorily linearized for a linear regression analysis. Consequently, a computer routine was developed which minimized the sum of the squares of the residual flow for the nonlinear model. The results indicate an average accuracy within 15% of the measured flow throughout the range of test conditions. Furthermore, the results of the regression analysis indicate that the transitional regime lies between Knudsen numbers of approximately 2 and 45. 4 refs., 3 figs., 1 tab

Orthology prediction at scalable resolution by phylogenetic tree analysis

NARCIS (Netherlands)

Heijden, R.T.J.M. van der; Snel, B.; Noort, V. van; Huynen, M.A.

2007-01-01

BACKGROUND: Orthology is one of the cornerstones of gene function prediction. Dividing the phylogenetic relations between genes into either orthologs or paralogs is however an oversimplification. Already in two-species gene-phylogenies, the complicated, non-transitive nature of phylogenetic

Trends in the Hydrodeoxygenation Activity and Selectivity of Transition Metal Surfaces

DEFF Research Database (Denmark)

Lausche, Adam C.; Falsig, Hanne; Jensen, Anker Degn

2014-01-01

This paper reports the use of a combination of density functional theory and microkinetic modelling to establish trends in the hydrodeoxygenation rates and selectivites of transition metal surfaces. Biomass and biomass-derived chemicals often contain large fractions of oxygenates. Removal...... of the oxygen through hydrotreating represents one strategy for producing commodity chemicals from these renewable materials. Using the model developed in this paper, we predict ethylene glycol hydrodeoxygenation selectivities for transition metals that are consistent with those reported in the literature...

Predicting cognitive function of the Malaysian elderly: a structural equation modelling approach.

Science.gov (United States)

Foong, Hui Foh; Hamid, Tengku Aizan; Ibrahim, Rahimah; Haron, Sharifah Azizah; Shahar, Suzana

2018-01-01

The aim of this study was to identify the predictors of elderly's cognitive function based on biopsychosocial and cognitive reserve perspectives. The study included 2322 community-dwelling elderly in Malaysia, randomly selected through a multi-stage proportional cluster random sampling from Peninsular Malaysia. The elderly were surveyed on socio-demographic information, biomarkers, psychosocial status, disability, and cognitive function. A biopsychosocial model of cognitive function was developed to test variables' predictive power on cognitive function. Statistical analyses were performed using SPSS (version 15.0) in conjunction with Analysis of Moment Structures Graphics (AMOS 7.0). The estimated theoretical model fitted the data well. Psychosocial stress and metabolic syndrome (MetS) negatively predicted cognitive function and psychosocial stress appeared as a main predictor. Socio-demographic characteristics, except gender, also had significant effects on cognitive function. However, disability failed to predict cognitive function. Several factors together may predict cognitive function in the Malaysian elderly population, and the variance accounted for it is large enough to be considered substantial. Key factor associated with the elderly's cognitive function seems to be psychosocial well-being. Thus, psychosocial well-being should be included in the elderly assessment, apart from medical conditions, both in clinical and community setting.

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

Predicting restoration of kidney function during CRRT-free intervals

Directory of Open Access Journals (Sweden)

Heise Daniel

2012-01-01

Full Text Available Abstract Background Renal failure is common in critically ill patients and frequently requires continuous renal replacement therapy (CRRT. CRRT is discontinued at regular intervals for routine changes of the disposable equipment or for replacing clogged filter membrane assemblies. The present study was conducted to determine if the necessity to continue CRRT could be predicted during the CRRT-free period. Materials and methods In the period from 2003 to 2006, 605 patients were treated with CRRT in our ICU. A total of 222 patients with 448 CRRT-free intervals had complete data sets and were used for analysis. Of the total CRRT-free periods, 225 served as an evaluation group. Twenty-nine parameters with an assumed influence on kidney function were analyzed with regard to their potential to predict the restoration of kidney function during the CRRT-free interval. Using univariate analysis and logistic regression, a prospective index was developed and validated in the remaining 223 CRRT-free periods to establish its prognostic strength. Results Only three parameters showed an independent influence on the restoration of kidney function during CRRT-free intervals: the number of previous CRRT cycles (medians in the two outcome groups: 1 vs. 2, the "Sequential Organ Failure Assessment"-score (means in the two outcome groups: 8.3 vs. 9.2 and urinary output after the cessation of CRRT (medians in two outcome groups: 66 ml/h vs. 10 ml/h. The prognostic index, which was calculated from these three variables, showed a satisfactory potential to predict the kidney function during the CRRT-free intervals; Receiver operating characteristic (ROC analysis revealed an area under the curve of 0.798. Conclusion Restoration of kidney function during CRRT-free periods can be predicted with an index calculated from three variables. Prospective trials in other hospitals must clarify whether our results are generally transferable to other patient populations.

Glass transition in soft-sphere dispersions

International Nuclear Information System (INIS)

RamIrez-Gonzalez, P E; Medina-Noyola, M

2009-01-01

The concept of dynamic equivalence among mono-disperse soft-sphere fluids is employed in the framework of the self-consistent generalized Langevin equation (SCGLE) theory of colloid dynamics to calculate the ideal glass transition phase diagram of model soft-sphere colloidal dispersions in the softness-concentration state space. The slow dynamics predicted by this theory near the glass transition is compared with available experimental data for the decay of the intermediate scattering function of colloidal dispersions of soft-microgel particles. Increasing deviations from this simple scheme occur for increasingly softer potentials, and this is studied here using the Rogers-Young static structure factor of the soft-sphere systems as the input of the SCGLE theory, without assuming a priori the validity of the equivalence principle above.

Sub-Seasonal Prediction of the Maritime Continent Rainfall of Wet-Dry Transitional Seasons in the NCEP Climate Forecast Version 2

Directory of Open Access Journals (Sweden)

Tuantuan Zhang

2016-02-01

Full Text Available This study investigates the characteristics and prediction of the Maritime Continent (MC rainfall for the transitional periods between wet and dry seasons. Several observational data sets and the output from the 45-day hindcast by the U.S. National Centers for Environmental Prediction (NCEP Climate Forecast System version 2 (CFSv2 are used. Results show that the MC experiences a sudden transition from wet season to dry season (WTD around the 27th pentad, and a gradual transition from dry season to wet season (DTW around the 59th pentad. Correspondingly, the westerlies over the equatorial Indian Ocean, the easterlies over the equatorial Pacific Ocean, and the Australia High become weaker, contributing to weakening of the convergence over the MC. The subtropical western Pacific high intensifies and extends northeastward during the WTD. The Mascarene High becomes weaker, an anomalous anticyclonic circulation forms over the northeast of the Philippines, and an anomalous low-level convergence occurs over the western MC during the DTW. The NCEP CFSv2 captures the major features of rainfall and related atmospheric circulation when forecast lead time is less than three weeks for WTD and two weeks for DTW. The model predicts a weaker amplitude of the changes in rainfall and related atmospheric circulation for both WTD and DTW as lead time increases.

The transitional region of phase transitions in nuclear models

International Nuclear Information System (INIS)

Kotze, A.A.

1988-01-01

The phase transition in an exactly solvable nuclear model, the Lipkin model, is scrutinised, first using Hartree-Fock methods or the plain mean flield approximation, and then using projected wave functions. It turns out that the plain mean field is not reliable in the transitional region. Although the projection methods give better resutls in the transitional region, it leads to spurious singularities. While the energy of the projection before variation is slightly better than its projection after variation counterpart, the perfomance of the wave function is considerably worse in the transitional region. The model's wave function undergoes dramatic changes in the transitional region. The mechanism that brings about these changes is studied within a model Hamiltonian that can reproduce the Lipkin model mathematically. It turns out that the numerous exceptional points found in the transitional region, bring about the change of the ground state wave function. Exceptional points are associated with level crossings in the complex plane. These level crossings can be seen as level repulsions in the spectrum. Level repulsion and a sensitive dependence of the system on some external parameter are characteristics of chaotic behaviour. These two features are found in the transitional region of the Lipkin model. In order to study chaos, one has to resort to a statistical analysis. A measure of the chaotic behaviour of systems, the Δ 3 statistic, is introduced. The results show that the Lipkin model is harmonic, even in the transitional region. For the Lipkin model the exceptional points are regularly distributed in the complex plane. In a total chaotic system the points would be randomly distributed

Predicting functional decline and survival in amyotrophic lateral sclerosis.

Science.gov (United States)

Ong, Mei-Lyn; Tan, Pei Fang; Holbrook, Joanna D

2017-01-01

Better predictors of amyotrophic lateral sclerosis disease course could enable smaller and more targeted clinical trials. Partially to address this aim, the Prize for Life foundation collected de-identified records from amyotrophic lateral sclerosis sufferers who participated in clinical trials of investigational drugs and made them available to researchers in the PRO-ACT database. In this study, time series data from PRO-ACT subjects were fitted to exponential models. Binary classes for decline in the total score of amyotrophic lateral sclerosis functional rating scale revised (ALSFRS-R) (fast/slow progression) and survival (high/low death risk) were derived. Data was segregated into training and test sets via cross validation. Learning algorithms were applied to the demographic, clinical and laboratory parameters in the training set to predict ALSFRS-R decline and the derived fast/slow progression and high/low death risk categories. The performance of predictive models was assessed by cross-validation in the test set using Receiver Operator Curves and root mean squared errors. A model created using a boosting algorithm containing the decline in four parameters (weight, alkaline phosphatase, albumin and creatine kinase) post baseline, was able to predict functional decline class (fast or slow) with fair accuracy (AUC = 0.82). However similar approaches to build a predictive model for decline class by baseline subject characteristics were not successful. In contrast, baseline values of total bilirubin, gamma glutamyltransferase, urine specific gravity and ALSFRS-R item score-climbing stairs were sufficient to predict survival class. Using combinations of small numbers of variables it was possible to predict classes of functional decline and survival across the 1-2 year timeframe available in PRO-ACT. These findings may have utility for design of future ALS clinical trials.

Protein function prediction using neighbor relativity in protein-protein interaction network.

Science.gov (United States)

Moosavi, Sobhan; Rahgozar, Masoud; Rahimi, Amir

2013-04-01

There is a large gap between the number of discovered proteins and the number of functionally annotated ones. Due to the high cost of determining protein function by wet-lab research, function prediction has become a major task for computational biology and bioinformatics. Some researches utilize the proteins interaction information to predict function for un-annotated proteins. In this paper, we propose a novel approach called "Neighbor Relativity Coefficient" (NRC) based on interaction network topology which estimates the functional similarity between two proteins. NRC is calculated for each pair of proteins based on their graph-based features including distance, common neighbors and the number of paths between them. In order to ascribe function to an un-annotated protein, NRC estimates a weight for each neighbor to transfer its annotation to the unknown protein. Finally, the unknown protein will be annotated by the top score transferred functions. We also investigate the effect of using different coefficients for various types of functions. The proposed method has been evaluated on Saccharomyces cerevisiae and Homo sapiens interaction networks. The performance analysis demonstrates that NRC yields better results in comparison with previous protein function prediction approaches that utilize interaction network. Copyright © 2012 Elsevier Ltd. All rights reserved.

Evidence for plasma phase transition in high pressure hydrogen from ab-initio simulations

Energy Technology Data Exchange (ETDEWEB)

Morales, M; Pierleoni, C; Schwegler, E; Ceperley, D

2010-02-08

We have performed a detailed study of molecular dissociation in liquid hydrogen using both Born-Oppenheimer molecular dynamics with Density Functional Theory and Coupled Electron-Ion Monte Carlo simulations. We observe a range of densities where (dP/d{rho}){sub T} = 0 that coincides with sharp discontinuities in the electronic conductivity, which is clear evidence of the plasma phase transition for temperatures 600K {le} T {le} 1500K. Both levels of theory exhibit the transition, although Quantum Monte Carlo predicts higher transition pressures. Based on the temperature dependence of the discontinuity in the electronic conductivity, we estimate the critical point of the transition at temperatures slightly below 2000 K. We examine the influence of proton zero point motion by using Path Integral Molecular Dynamics with Density Functional Theory; the main effect is to shift the transition to lower pressures. Furthermore, we calculate the melting curve of molecular hydrogen up to pressures of 200 GPa, finding a reentrant melting line in good agreement with previous calculations. The melting line crosses the metalization line at 700 K and 220 GPa using density functional energetics and at 550 K and 290 GPa using Quantum Monte Carlo energetics.

Weaknesses in executive functioning predict the initiating of adolescents' alcohol use.

Science.gov (United States)

Peeters, Margot; Janssen, Tim; Monshouwer, Karin; Boendermaker, Wouter; Pronk, Thomas; Wiers, Reinout; Vollebergh, Wilma

2015-12-01

Recently, it has been suggested that impairments in executive functioning might be risk factors for the onset of alcohol use rather than a result of heavy alcohol use. In the present study, we examined whether two aspects of executive functioning, working memory and response inhibition, predicted the first alcoholic drink and first binge drinking episode in young adolescents using discrete survival analyses. Adolescents were selected from several Dutch secondary schools including both mainstream and special education (externalizing behavioral problems). Participants were 534 adolescents between 12 and 14 years at baseline. Executive functioning and alcohol use were assessed four times over a period of two years. Working memory uniquely predicted the onset of first drink (p=.01) and first binge drinking episode (p=.04) while response inhibition only uniquely predicted the initiating of the first drink (p=.01). These results suggest that the association of executive functioning and alcohol consumption found in former studies cannot simply be interpreted as an effect of alcohol consumption, as weaknesses in executive functioning, found in alcohol naïve adolescents, predict the initiating of (binge) drinking. Though, prolonged and heavy alcohol use might further weaken already existing deficiencies. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Application of an excited state LDA exchange energy functional for the calculation of transition energy of atoms within time-independent density functional theory

Energy Technology Data Exchange (ETDEWEB)

Shamim, Md; Harbola, Manoj K, E-mail: sami@iitk.ac.i, E-mail: mkh@iitk.ac.i [Department of Physics, Indian Institute of Technology, Kanpur 208 016 (India)

2010-11-14

Transition energies of a new class of excited states (two-gap systems) of various atoms are calculated in time-independent density functional formalism by using a recently proposed local density approximation exchange energy functional for excited states. It is shown that the excitation energies calculated with this functional compare well with those calculated with exact exchange theories.

Application of an excited state LDA exchange energy functional for the calculation of transition energy of atoms within time-independent density functional theory

International Nuclear Information System (INIS)

Shamim, Md; Harbola, Manoj K

2010-01-01

Transition energies of a new class of excited states (two-gap systems) of various atoms are calculated in time-independent density functional formalism by using a recently proposed local density approximation exchange energy functional for excited states. It is shown that the excitation energies calculated with this functional compare well with those calculated with exact exchange theories.

Applications of NASA and NOAA Satellite Observations by NASA's Short-term Prediction Research and Transition (SPoRT) Center in Response to Natural Disasters

Science.gov (United States)

Molthan, Andrew L.; Burks, Jason E.; McGrath, Kevin M.; Jedlovec, Gary J.

2012-01-01

NASA s Short-term Prediction Research and Transition (SPoRT) Center supports the transition of unique NASA and NOAA research activities to the operational weather forecasting community. SPoRT emphasizes real-time analysis and prediction out to 48 hours. SPoRT partners with NOAA s National Weather Service (NWS) Weather Forecast Offices (WFOs) and National Centers to improve current products, demonstrate future satellite capabilities and explore new data assimilation techniques. Recently, the SPoRT Center has been involved in several activities related to disaster response, in collaboration with NOAA s National Weather Service, NASA s Applied Sciences Disasters Program, and other partners.

An exactly solvable model for first- and second-order transitions

International Nuclear Information System (INIS)

Klushin, L I; Skvortsov, A M; Gorbunov, A A

1998-01-01

The possibility of an exact analytical description of first-order and second-order transitions is demonstrated using a specific microscopic model. Predictions using the exactly calculated partition function are compared with those based on the Landau and Yang-Lee approaches. The model employed is an adsorbed polymer chain with an arbitrary number of links and an external force applied to its end, for which the variation of the partition function with the adsorption interaction parameter and the magnitude of the applied force is calculated. In the thermodynamic limit, the system has one isotropic and two anisotropic, ordered phases, each of which is characterized by two order parameters and between which first-order and second-order transitions occur and a bicritical point exists. The Landau free energy is found exactly as a function of each order parameter separately and, near the bicritical point, as a function of both of them simultaneously. An exact analytical formula is found for the distribution of the complex zeros of the partition function in first-order and second-order phase transitions. Hypotheses concerning the way in which the free energy and the positions of the complex zeros scale with the number of particles N in the system are verified. (reviews of topical problems)

Dynamic prediction of cumulative incidence functions by direct binomial regression.

Science.gov (United States)

Grand, Mia K; de Witte, Theo J M; Putter, Hein

2018-03-25

In recent years there have been a series of advances in the field of dynamic prediction. Among those is the development of methods for dynamic prediction of the cumulative incidence function in a competing risk setting. These models enable the predictions to be updated as time progresses and more information becomes available, for example when a patient comes back for a follow-up visit after completing a year of treatment, the risk of death, and adverse events may have changed since treatment initiation. One approach to model the cumulative incidence function in competing risks is by direct binomial regression, where right censoring of the event times is handled by inverse probability of censoring weights. We extend the approach by combining it with landmarking to enable dynamic prediction of the cumulative incidence function. The proposed models are very flexible, as they allow the covariates to have complex time-varying effects, and we illustrate how to investigate possible time-varying structures using Wald tests. The models are fitted using generalized estimating equations. The method is applied to bone marrow transplant data and the performance is investigated in a simulation study. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Financial Distress Prediction Using Discrete-time Hazard Model and Rating Transition Matrix Approach

Science.gov (United States)

Tsai, Bi-Huei; Chang, Chih-Huei

2009-08-01

Previous studies used constant cut-off indicator to distinguish distressed firms from non-distressed ones in the one-stage prediction models. However, distressed cut-off indicator must shift according to economic prosperity, rather than remains fixed all the time. This study focuses on Taiwanese listed firms and develops financial distress prediction models based upon the two-stage method. First, this study employs the firm-specific financial ratio and market factors to measure the probability of financial distress based on the discrete-time hazard models. Second, this paper further focuses on macroeconomic factors and applies rating transition matrix approach to determine the distressed cut-off indicator. The prediction models are developed by using the training sample from 1987 to 2004, and their levels of accuracy are compared with the test sample from 2005 to 2007. As for the one-stage prediction model, the model in incorporation with macroeconomic factors does not perform better than that without macroeconomic factors. This suggests that the accuracy is not improved for one-stage models which pool the firm-specific and macroeconomic factors together. In regards to the two stage models, the negative credit cycle index implies the worse economic status during the test period, so the distressed cut-off point is adjusted to increase based on such negative credit cycle index. After the two-stage models employ such adjusted cut-off point to discriminate the distressed firms from non-distressed ones, their error of misclassification becomes lower than that of one-stage ones. The two-stage models presented in this paper have incremental usefulness in predicting financial distress.

Predicting taxonomic and functional structure of microbial communities in acid mine drainage.

Science.gov (United States)

Kuang, Jialiang; Huang, Linan; He, Zhili; Chen, Linxing; Hua, Zhengshuang; Jia, Pu; Li, Shengjin; Liu, Jun; Li, Jintian; Zhou, Jizhong; Shu, Wensheng

2016-06-01

Predicting the dynamics of community composition and functional attributes responding to environmental changes is an essential goal in community ecology but remains a major challenge, particularly in microbial ecology. Here, by targeting a model system with low species richness, we explore the spatial distribution of taxonomic and functional structure of 40 acid mine drainage (AMD) microbial communities across Southeast China profiled by 16S ribosomal RNA pyrosequencing and a comprehensive microarray (GeoChip). Similar environmentally dependent patterns of dominant microbial lineages and key functional genes were observed regardless of the large-scale geographical isolation. Functional and phylogenetic β-diversities were significantly correlated, whereas functional metabolic potentials were strongly influenced by environmental conditions and community taxonomic structure. Using advanced modeling approaches based on artificial neural networks, we successfully predicted the taxonomic and functional dynamics with significantly higher prediction accuracies of metabolic potentials (average Bray-Curtis similarity 87.8) as compared with relative microbial abundances (similarity 66.8), implying that natural AMD microbial assemblages may be better predicted at the functional genes level rather than at taxonomic level. Furthermore, relative metabolic potentials of genes involved in many key ecological functions (for example, nitrogen and phosphate utilization, metals resistance and stress response) were extrapolated to increase under more acidic and metal-rich conditions, indicating a critical strategy of stress adaptation in these extraordinary communities. Collectively, our findings indicate that natural selection rather than geographic distance has a more crucial role in shaping the taxonomic and functional patterns of AMD microbial community that readily predicted by modeling methods and suggest that the model-based approach is essential to better understand natural

A new phase of ThC at high pressure predicted from a first-principles study

Science.gov (United States)

Guo, Yongliang; Qiu, Wujie; Ke, Xuezhi; Huai, Ping; Cheng, Cheng; Han, Han; Ren, Cuilan; Zhu, Zhiyuan

2015-08-01

The phase transition of thorium monocarbide (ThC) at high pressure has been studied by means of density functional theory. Through structure search, a new phase with space group P 4 / nmm has been predicted. The calculated phonons demonstrate that this new phase and the previous B2 phase are dynamically stable as the external pressure is greater than 60 GPa and 120 GPa, respectively. The transformation from B1 to P 4 / nmm is predicted to be a first-order transition, while that from P 4 / nmm to B2 is found to be a second-order transition.

Rational Design and Tuning of Functional RNA Switch to Control an Allosteric Intermolecular Interaction.

Science.gov (United States)

Endoh, Tamaki; Sugimoto, Naoki

2015-08-04

Conformational transitions of biomolecules in response to specific stimuli control many biological processes. In natural functional RNA switches, often called riboswitches, a particular RNA structure that has a suppressive or facilitative effect on gene expression transitions to an alternative structure with the opposite effect upon binding of a specific metabolite to the aptamer region. Stability of RNA secondary structure (-ΔG°) can be predicted based on thermodynamic parameters and is easily tuned by changes in nucleobases. We envisioned that tuning of a functional RNA switch that causes an allosteric interaction between an RNA and a peptide would be possible based on a predicted switching energy (ΔΔG°) that corresponds to the energy difference between the RNA secondary structure before (-ΔG°before) and after (-ΔG°after) the RNA conformational transition. We first selected functional RNA switches responsive to neomycin with predicted ΔΔG° values ranging from 5.6 to 12.2 kcal mol(-1). We then demonstrated a simple strategy to rationally convert the functional RNA switch to switches responsive to natural metabolites thiamine pyrophosphate, S-adenosyl methionine, and adenine based on the predicted ΔΔG° values. The ΔΔG° values of the designed RNA switches proportionally correlated with interaction energy (ΔG°interaction) between the RNA and peptide, and we were able to tune the sensitivity of the RNA switches for the trigger molecule. The strategy demonstrated here will be generally applicable for construction of functional RNA switches and biosensors in which mechanisms are based on conformational transition of nucleic acids.

A Predictive Metabolic Signature for the Transition From Gestational Diabetes Mellitus to Type 2 Diabetes.

Science.gov (United States)

Allalou, Amina; Nalla, Amarnadh; Prentice, Kacey J; Liu, Ying; Zhang, Ming; Dai, Feihan F; Ning, Xian; Osborne, Lucy R; Cox, Brian J; Gunderson, Erica P; Wheeler, Michael B

2016-09-01

Gestational diabetes mellitus (GDM) affects 3-14% of pregnancies, with 20-50% of these women progressing to type 2 diabetes (T2D) within 5 years. This study sought to develop a metabolomics signature to predict the transition from GDM to T2D. A prospective cohort of 1,035 women with GDM pregnancy were enrolled at 6-9 weeks postpartum (baseline) and were screened for T2D annually for 2 years. Of 1,010 women without T2D at baseline, 113 progressed to T2D within 2 years. T2D developed in another 17 women between 2 and 4 years. A nested case-control design used 122 incident case patients matched to non-case patients by age, prepregnancy BMI, and race/ethnicity. We conducted metabolomics with baseline fasting plasma and identified 21 metabolites that significantly differed by incident T2D status. Machine learning optimization resulted in a decision tree modeling that predicted T2D incidence with a discriminative power of 83.0% in the training set and 76.9% in an independent testing set, which is far superior to measuring fasting plasma glucose levels alone. The American Diabetes Association recommends T2D screening in the early postpartum period via oral glucose tolerance testing after GDM, which is a time-consuming and inconvenient procedure. Our metabolomics signature predicted T2D incidence from a single fasting blood sample. This study represents the first metabolomics study of the transition from GDM to T2D validated in an independent testing set, facilitating early interventions. © 2016 by the American Diabetes Association.

Predictive value and construct validity of the work functioning screener-healthcare (WFS-H)

Science.gov (United States)

Boezeman, Edwin J.; Nieuwenhuijsen, Karen; Sluiter, Judith K.

2016-01-01

Objectives: To test the predictive value and convergent construct validity of a 6-item work functioning screener (WFS-H). Methods: Healthcare workers (249 nurses) completed a questionnaire containing the work functioning screener (WFS-H) and a work functioning instrument (NWFQ) measuring the following: cognitive aspects of task execution and general incidents, avoidance behavior, conflicts and irritation with colleagues, impaired contact with patients and their family, and level of energy and motivation. Productivity and mental health were also measured. Negative and positive predictive values, AUC values, and sensitivity and specificity were calculated to examine the predictive value of the screener. Correlation analysis was used to examine the construct validity. Results: The screener had good predictive value, since the results showed that a negative screener score is a strong indicator of work functioning not hindered by mental health problems (negative predictive values: 94%-98%; positive predictive values: 21%-36%; AUC:.64-.82; sensitivity: 42%-76%; and specificity 85%-87%). The screener has good construct validity due to moderate, but significant (pvalue and good construct validity. Its score offers occupational health professionals a helpful preliminary insight into the work functioning of healthcare workers. PMID:27010085

Predictive value and construct validity of the work functioning screener-healthcare (WFS-H).

Science.gov (United States)

Boezeman, Edwin J; Nieuwenhuijsen, Karen; Sluiter, Judith K

2016-05-25

To test the predictive value and convergent construct validity of a 6-item work functioning screener (WFS-H). Healthcare workers (249 nurses) completed a questionnaire containing the work functioning screener (WFS-H) and a work functioning instrument (NWFQ) measuring the following: cognitive aspects of task execution and general incidents, avoidance behavior, conflicts and irritation with colleagues, impaired contact with patients and their family, and level of energy and motivation. Productivity and mental health were also measured. Negative and positive predictive values, AUC values, and sensitivity and specificity were calculated to examine the predictive value of the screener. Correlation analysis was used to examine the construct validity. The screener had good predictive value, since the results showed that a negative screener score is a strong indicator of work functioning not hindered by mental health problems (negative predictive values: 94%-98%; positive predictive values: 21%-36%; AUC:.64-.82; sensitivity: 42%-76%; and specificity 85%-87%). The screener has good construct validity due to moderate, but significant (ppredictive value and good construct validity. Its score offers occupational health professionals a helpful preliminary insight into the work functioning of healthcare workers.

Preparing Transition-Age Students with High-Functioning Autism Spectrum Disorders for Meaningful Work

Science.gov (United States)

Lee, Gloria K.; Carter, Erik W.

2012-01-01

This article provides an overview of promising essential elements for fostering vocational success among students with high-functioning autism spectrum disorders (HFASDs) by drawing literature from the fields of school-to-work transition for post-secondary students and vocational rehabilitation for individuals with disabilities. We highlight seven…

Predicting glass-to-glass and liquid-to-liquid phase transitions in supercooled water using classical nucleation theory

Science.gov (United States)

Tournier, Robert F.

2018-01-01

Glass-to-glass and liquid-to-liquid phase transitions are observed in bulk and confined water, with or without applied pressure. They result from the competition of two liquid phases separated by an enthalpy difference depending on temperature. The classical nucleation equation of these phases is completed by this quantity existing at all temperatures, a pressure contribution, and an enthalpy excess. This equation leads to two homogeneous nucleation temperatures in each liquid phase; the first one (Tn- below Tm) being the formation temperature of an "ordered" liquid phase and the second one corresponding to the overheating temperature (Tn+ above Tm). Thermodynamic properties, double glass transition temperatures, sharp enthalpy and volume changes are predicted in agreement with experimental results. The first-order transition line at TLL = 0.833 × Tm between fragile and strong liquids joins two critical points. Glass phase above Tg becomes "ordered" liquid phase disappearing at TLL at low pressure and at Tn+ = 1.302 × Tm at high pressure.

Density Functional Theory of Open-Shell Systems. The 3d-Series Transition-Metal Atoms and Their Cations.

Science.gov (United States)

Luo, Sijie; Averkiev, Boris; Yang, Ke R; Xu, Xuefei; Truhlar, Donald G

2014-01-14

The 3d-series transition metals (also called the fourth-period transition metals), Sc to Zn, are very important in industry and biology, but they provide unique challenges to computing the electronic structure of their compounds. In order to successfully describe the compounds by theory, one must be able to describe their components, in particular the constituent atoms and cations. In order to understand the ingredients required for successful computations with density functional theory, it is useful to examine the performance of various exchange-correlation functionals; we do this here for 4s(N)3d(N') transition-metal atoms and their cations. We analyze the results using three ways to compute the energy of the open-shell states: the direct variational method, the weighted-averaged broken symmetry (WABS) method, and a new broken-symmetry method called the reinterpreted broken symmetry (RBS) method. We find the RBS method to be comparable in accuracy with the WABS method. By examining the overall accuracy in treating 18 multiplicity-changing excitations and 10 ionization potentials with the RBS method, 10 functionals are found to have a mean-unsigned error of systems, the M06-L functional is the most accurate. And by combining the results with our previous studies of p-block and 4d-series elements as well as databases for alkyl bond dissociation, main-group atomization energies, and π-π noncovalent interactions, we find five functionals, namely, PW6B95, MPW1B95, M08-SO, SOGGA11-X, and MPWB1K, to be highly recommended. We also studied the performance of PW86 and C09 exchange functionals, which have drawn wide interest in recent studies due to their claimed ability to reproduce Hartree-Fock exchange at long distance. By combining them with four correlation functionals, we find the performance of the resulting functionals disappointing both for 3d transition-metal chemistry and in broader tests, and thus we do not recommend PW86 and C09 as components of generalized

Colon Transit Time Test in Korean Children with Chronic Functional Constipation

Science.gov (United States)

Yoo, Ha Yeong; Kim, Mock Ryeon; Park, Hye Won; Son, Jae Sung

2016-01-01

Purpose Each ethnic group has a unique life style, including diets. Life style affects bowel movement. The aim of this study is to describe the results of colon transit time (CTT) tests in Korean children who had chronic functional constipation based on highly refined data. Methods One hundred ninety (86 males) out of 415 children who performed a CTT test under the diagnosis of chronic constipation according to Rome III criteria at Konkuk University Medical Center from January 2006 through March 2015 were enrolled in this study. Two hundreds twenty-five children were excluded on the basis of CTT test result, defecation diary, and clinical setting. Shapiro-Wilk and Mann-Whitney U, and chi-square tests were used for statistical analysis. Results The median value and interquartile range (IQR) of CTT was 54 (37.5) hours in Encopresis group, and those in non-encopresis group was 40.2 (27.9) hours (pencopresis group and encopresis was statistically significant (p=0.002). The non-encopresis group (n=154, 81.1%) was divided into normal transit subgroup (n=84, 54.5%; median value and IQR of CTT=26.4 [9.6] hours), outlet obstruction subgroup (n=18, 11.7%; 62.4 [15.6] hours), and slow transit subgroup (n=52, 33.8%; 54.6 [21.0] hours]. The encopresis group (n=36, 18.9%) was divided into normal transit subgroup (n=8, 22.2%; median value and IQR of CTT=32.4 [9.9] hours), outlet obstruction subgroup (n=8, 22.2%; 67.8 [34.8] hours), and slow transit subgroup (n=20, 55.6%; 59.4 [62.7]hours). Conclusion This study provided the basic pattern and value of the CTT test in Korean children with chronic constipation. PMID:27064388

Pulmonary blood volume and transit time in cirrhosis: relation to lung function

DEFF Research Database (Denmark)

Møller, Søren; Burchardt, H; Øgard, CG

2006-01-01

BACKGROUND/AIMS: In cirrhosis a systemic vasodilatation leads to an abnormal distribution of the blood volume with a contracted central blood volume. In addition, the patients have a ventilation/perfusion imbalance with a low diffusing capacity. As the size of the pulmonary blood volume (PBV) has...... in cirrhosis. The relation between PBV and PTT and the low diffusing capacity suggests the pulmonary vascular compartment as an important element in the pathophysiology of the lung dysfunction in cirrhosis....... not been determined separately we assessed PBV and pulmonary transit time (PTT) in relation to lung function in patients with cirrhosis and in controls. METHODS: Pulmonary and cardiac haemodynamics and transit times were determined by radionuclide techniques in 22 patients with alcoholic cirrhosis...

NARX prediction of some rare chaotic flows: Recurrent fuzzy functions approach

International Nuclear Information System (INIS)

Goudarzi, Sobhan; Jafari, Sajad; Moradi, Mohammad Hassan; Sprott, J.C.

2016-01-01

The nonlinear and dynamic accommodating capability of time domain models makes them a useful representation of chaotic time series for analysis, modeling and prediction. This paper is devoted to the modeling and prediction of chaotic time series with hidden attractors using a nonlinear autoregressive model with exogenous inputs (NARX) based on a novel recurrent fuzzy functions (RFFs) approach. Case studies of recently introduced chaotic systems with hidden attractors plus classical chaotic systems demonstrate that the proposed modeling methodology exhibits better prediction performance from different viewpoints (short term and long term) compared to some other existing methods. - Highlights: • A new method is proposed for prediction of chaotic time series. • This method is based on novel recurrent fuzzy functions (RFFs) approach. • Some rare chaotic flows are used as test systems. • The new method shows proper performance in short-term prediction. • It also shows proper performance in prediction of attractor's topology.

NARX prediction of some rare chaotic flows: Recurrent fuzzy functions approach

Energy Technology Data Exchange (ETDEWEB)

Goudarzi, Sobhan [Biomedical Engineering Department, Amirkabir University of Technology, Tehran 15875-4413 (Iran, Islamic Republic of); Jafari, Sajad, E-mail: sajadjafari@aut.ac.ir [Biomedical Engineering Department, Amirkabir University of Technology, Tehran 15875-4413 (Iran, Islamic Republic of); Moradi, Mohammad Hassan [Biomedical Engineering Department, Amirkabir University of Technology, Tehran 15875-4413 (Iran, Islamic Republic of); Sprott, J.C. [Department of Physics, University of Wisconsin–Madison, Madison, WI 53706 (United States)

2016-02-15

The nonlinear and dynamic accommodating capability of time domain models makes them a useful representation of chaotic time series for analysis, modeling and prediction. This paper is devoted to the modeling and prediction of chaotic time series with hidden attractors using a nonlinear autoregressive model with exogenous inputs (NARX) based on a novel recurrent fuzzy functions (RFFs) approach. Case studies of recently introduced chaotic systems with hidden attractors plus classical chaotic systems demonstrate that the proposed modeling methodology exhibits better prediction performance from different viewpoints (short term and long term) compared to some other existing methods. - Highlights: • A new method is proposed for prediction of chaotic time series. • This method is based on novel recurrent fuzzy functions (RFFs) approach. • Some rare chaotic flows are used as test systems. • The new method shows proper performance in short-term prediction. • It also shows proper performance in prediction of attractor's topology.

Longitudinal changes in sexual functioning as women transition through menopause: results from the Study of Women's Health Across the Nation.

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Avis, Nancy E; Brockwell, Sarah; Randolph, John F; Shen, Shunhua; Cain, Virginia S; Ory, Marcia; Greendale, Gail A

2009-01-01

Sexual functioning is an important component of women's lives. The extent to which the menopausal transition is associated with decreased sexual functioning remains inconclusive. This study seeks to determine if advancing through the menopausal transition is associated with changes in sexual functioning. This was a prospective, longitudinal cohort study of women aged 42 to 52 years at baseline recruited at seven US sites (N = 3,302) in the Study of Women's Health Across the Nation (SWAN). Cohort-eligible women had an intact uterus, had at least one ovary, were not currently using exogenous hormones, were either premenopausal or early perimenopausal, and self-identified as one of the study's designated racial/ethnic groups. Data from the baseline interview and six annual follow-up visits are reported. Outcomes are self-reported ratings of importance of sex; frequency of sexual desire, arousal, masturbation, sexual intercourse, and pain during intercourse; and degree of emotional satisfaction and physical pleasure. With adjustment for baseline age, chronological aging, and relevant social, health, and psychological parameters, the odds of reporting vaginal or pelvic pain increased and desire decreased by late perimenopause. Masturbation increased at early perimenopause but declined during postmenopause. The menopausal transition was unrelated to other outcomes. Health, psychological functioning, and importance of sex were related to all sexual function outcomes. Age, race/ethnicity, marital status, change in relationship, and vaginal dryness were also associated with sexual functioning. Pain during sexual intercourse increases and sexual desire decreases over the menopausal transition. Masturbation increases during the early transition, but then declines in postmenopause. With adjustment for other factors, the menopausal transition was not independently associated with reports of the importance of sex, sexual arousal, frequency of sexual intercourse, emotional

Evaluation of Fluorescent Analogs of Deoxycytidine for Monitoring DNA Transitions from Duplex to Functional Structures

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Yogini P. Bhavsar

2011-01-01

Full Text Available Topological variants of single-strand DNA (ssDNA structures, referred to as “functional DNA,” have been detected in regulatory regions of many genes and are thought to affect gene expression. Two fluorescent analogs of deoxycytidine, Pyrrolo-dC (PdC and 1,3-diaza-2-oxophenoxazine (tC∘, can be incorporated into DNA. Here, we describe spectroscopic studies of both analogs to determine fluorescent properties that report on structural transitions from double-strand DNA (dsDNA to ssDNA, a common pathway in the transition to functional DNA structures. We obtained fluorescence-detected circular dichroism (FDCD spectra, steady-state fluorescence spectra, and fluorescence lifetimes of the fluorophores in DNA. Our results show that PdC is advantageous in fluorescence lifetime studies because of a distinct ~2 ns change between paired and unpaired bases. However, tC∘ is a better probe for FDCD experiments that report on the helical structure of DNA surrounding the fluorophore. Both fluorophores provide complementary data to measure DNA structural transitions.

Reconstructive structural phase transitions in dense Mg

International Nuclear Information System (INIS)

Yao Yansun; Klug, Dennis D

2012-01-01

The question raised recently about whether the high-pressure phase transitions of Mg follow a hexagonal close-packed (hcp) → body centered cubic (bcc) or hcp → double hexagonal close-packed (dhcp) → bcc sequence at room temperature is examined by the use of first principles density functional methods. Enthalpy calculations show that the bcc structure replaces the hcp structure to become the most stable structure near 48 GPa, whereas the dhcp structure is never the most stable structure in the pressure range of interest. The characterized phase-transition mechanisms indicate that the hcp → dhcp transition is also associated with a higher enthalpy barrier. At room temperature, the structural sequence hcp → bcc is therefore more energetically favorable for Mg. The same conclusion is also reached from the simulations of the phase transitions using metadynamics methods. At room temperature, the metadynamics simulations predict the onset of a hcp → bcc transition at 40 GPa and the transition becomes more prominent upon further compression. At high temperatures, the metadynamics simulations reveal a structural fluctuation among the hcp, dhcp, and bcc structures at 15 GPa. With increasing pressure, the structural evolution at high temperatures becomes more unambiguous and eventually settles to a bcc structure once sufficient pressure is applied. (paper)

Improved survival prediction from lung function data in a large population sample

DEFF Research Database (Denmark)

Miller, M.R.; Pedersen, O.F.; Lange, P.

2008-01-01

Studies relating tung function to survival commonly express lung function impairment as a percent of predicted but this retains age, height and sex bias. We have studied alternative methods of expressing forced expiratory volume in 1 s (FEV1) for predicting all cause and airway related lung disease.......1 respectively. Cut levels of lung function were used to categorise impairment and the HR for multivariate prediction of all cause and airway related lung disease mortality were 10 and 2044 respectively for the worst category of FEV1/ht(2) compared to 5 and 194 respectively for the worst category of FEV1PP....... In univariate predictions of all cause mortality the HR for FEV1/ht(2) categories was 2-4 times higher than those for FEV1PP and 3-10 times higher for airway related tung disease mortality. We conclude that FEV1/ht(2) is superior to FEV1PP for predicting survival. in a general population and this method...

A predictive model for steam generator degradation through PW SCC in roll transitions

International Nuclear Information System (INIS)

Hernalsteen, P.

1989-01-01

The tubebundle of pressurized water reactors steam generators (SG) has been affected by numerous corrosion damages, in various nuclear plants, all over the world. One of the main problems is primary water stress corrosion cracking (PWSCC) in the roll transitions of mill annealed Inconel 600 tubes mechanically expanded in the SG tubesheet. Multiple axial cracks are initiated from the primary side and grow rapidly through water; they further grow in length and propagate outside of the roll transition. In most plants, both in Europe and in the USA, short penning has been performed on the inside diameter of the expanded section of susceptible tubing. While the compressive surface layer induced by peening is considered to be efficient in preventing crack initiation, field experience showed that it did not prevent preexisting cracks from further propagation. For the usual case of SG peened after crack initiation, there is thus a remaining concern about the long term evolution of the population of cracked tubes. This paper presents a model to predict the SG degradation process in order to support both the maintenance policy and the longer term repair/replacement strategy

Do functional tests predict low back pain?

Science.gov (United States)

Takala, E P; Viikari-Juntura, E

2000-08-15

A cohort of 307 nonsymptomatic workers and another cohort of 123 workers with previous episodes of low back pain were followed up for 2 years. The outcomes were measured by symptoms, medical consultations, and sick leaves due to low back disorders. To study the predictive value of a set of tests measuring the physical performance of the back in a working population. The hypothesis was that subjects with poor functional capacity are liable to back disorders. Reduced functional performance has been associated with back pain. There are few data to show whether reduced functional capacity is a cause or a consequence of pain. Mobility of the trunk in forward and side bending, maximal isokinetic trunk extension, flexion and lifting strength, and static endurance of back extension were measured. Standing balance and foot reaction time were recorded with a force plate. Clinical tests for the provocation of back or leg pain were performed. Gender, workload, age, and anthropometrics were managed as potential confounders in the analysis. Marked overlapping was seen in the measures of the subjects with different outcomes. Among the nonsymptomatic subjects, low performance in tests of mobility and standing balance was associated with future back disorders. Among workers with previous episodes of back pain, low isokinetic extension strength, poor standing balance, and positive clinical signs predicted future pain. Some associations were found between the functional tests and future low back pain. The wide variation in the results questions the value of the tests in health examinations (e.g., in screening or surveillance of low back disorders).

Stages of Change or Changes of Stage? Predicting Transitions in Transtheoretical Model Stages in Relation to Healthy Food Choice

Science.gov (United States)

Armitage, Christopher J.; Sheeran, Paschal; Conner, Mark; Arden, Madelynne A.

2004-01-01

Relatively little research has examined factors that account for transitions between transtheoretical model (TTM) stages of change. The present study (N=787) used sociodemographic, TTM, and theory of planned behavior (TPB) variables, as well as theory-driven interventions to predict changes in stage. Longitudinal analyses revealed that…

The modulation of neural gain facilitates a transition between functional segregation and integration in the brain.

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Shine, James M; Aburn, Matthew J; Breakspear, Michael; Poldrack, Russell A

2018-01-29

Cognitive function relies on a dynamic, context-sensitive balance between functional integration and segregation in the brain. Previous work has proposed that this balance is mediated by global fluctuations in neural gain by projections from ascending neuromodulatory nuclei. To test this hypothesis in silico, we studied the effects of neural gain on network dynamics in a model of large-scale neuronal dynamics. We found that increases in neural gain directed the network through an abrupt dynamical transition, leading to an integrated network topology that was maximal in frontoparietal 'rich club' regions. This gain-mediated transition was also associated with increased topological complexity, as well as increased variability in time-resolved topological structure, further highlighting the potential computational benefits of the gain-mediated network transition. These results support the hypothesis that neural gain modulation has the computational capacity to mediate the balance between integration and segregation in the brain. © 2018, Shine et al.

IMP 2.0: a multi-species functional genomics portal for integration, visualization and prediction of protein functions and networks.

Science.gov (United States)

Wong, Aaron K; Krishnan, Arjun; Yao, Victoria; Tadych, Alicja; Troyanskaya, Olga G

2015-07-01

IMP (Integrative Multi-species Prediction), originally released in 2012, is an interactive web server that enables molecular biologists to interpret experimental results and to generate hypotheses in the context of a large cross-organism compendium of functional predictions and networks. The system provides biologists with a framework to analyze their candidate gene sets in the context of functional networks, expanding or refining their sets using functional relationships predicted from integrated high-throughput data. IMP 2.0 integrates updated prior knowledge and data collections from the last three years in the seven supported organisms (Homo sapiens, Mus musculus, Rattus norvegicus, Drosophila melanogaster, Danio rerio, Caenorhabditis elegans, and Saccharomyces cerevisiae) and extends function prediction coverage to include human disease. IMP identifies homologs with conserved functional roles for disease knowledge transfer, allowing biologists to analyze disease contexts and predictions across all organisms. Additionally, IMP 2.0 implements a new flexible platform for experts to generate custom hypotheses about biological processes or diseases, making sophisticated data-driven methods easily accessible to researchers. IMP does not require any registration or installation and is freely available for use at http://imp.princeton.edu. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Multiconfiguration pair-density functional theory: barrier heights and main group and transition metal energetics.

Science.gov (United States)

Carlson, Rebecca K; Li Manni, Giovanni; Sonnenberger, Andrew L; Truhlar, Donald G; Gagliardi, Laura

2015-01-13

Kohn-Sham density functional theory, resting on the representation of the electronic density and kinetic energy by a single Slater determinant, has revolutionized chemistry, but for open-shell systems, the Kohn-Sham Slater determinant has the wrong symmetry properties as compared to an accurate wave function. We have recently proposed a theory, called multiconfiguration pair-density functional theory (MC-PDFT), in which the electronic kinetic energy and classical Coulomb energy are calculated from a multiconfiguration wave function with the correct symmetry properties, and the rest of the energy is calculated from a density functional, called the on-top density functional, that depends on the density and the on-top pair density calculated from this wave function. We also proposed a simple way to approximate the on-top density functional by translation of Kohn-Sham exchange-correlation functionals. The method is much less expensive than other post-SCF methods for calculating the dynamical correlation energy starting with a multiconfiguration self-consistent-field wave function as the reference wave function, and initial tests of the theory were quite encouraging. Here, we provide a broader test of the theory by applying it to bond energies of main-group molecules and transition metal complexes, barrier heights and reaction energies for diverse chemical reactions, proton affinities, and the water dimerization energy. Averaged over 56 data points, the mean unsigned error is 3.2 kcal/mol for MC-PDFT, as compared to 6.9 kcal/mol for Kohn-Sham theory with a comparable density functional. MC-PDFT is more accurate on average than complete active space second-order perturbation theory (CASPT2) for main-group small-molecule bond energies, alkyl bond dissociation energies, transition-metal-ligand bond energies, proton affinities, and the water dimerization energy.

Comparison of statistical and clinical predictions of functional outcome after ischemic stroke.

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Douglas D Thompson

Full Text Available To determine whether the predictions of functional outcome after ischemic stroke made at the bedside using a doctor's clinical experience were more or less accurate than the predictions made by clinical prediction models (CPMs.A prospective cohort study of nine hundred and thirty one ischemic stroke patients recruited consecutively at the outpatient, inpatient and emergency departments of the Western General Hospital, Edinburgh between 2002 and 2005. Doctors made informal predictions of six month functional outcome on the Oxford Handicap Scale (OHS. Patients were followed up at six months with a validated postal questionnaire. For each patient we calculated the absolute predicted risk of death or dependence (OHS≥3 using five previously described CPMs. The specificity of a doctor's informal predictions of OHS≥3 at six months was good 0.96 (95% CI: 0.94 to 0.97 and similar to CPMs (range 0.94 to 0.96; however the sensitivity of both informal clinical predictions 0.44 (95% CI: 0.39 to 0.49 and clinical prediction models (range 0.38 to 0.45 was poor. The prediction of the level of disability after stroke was similar for informal clinical predictions (ordinal c-statistic 0.74 with 95% CI 0.72 to 0.76 and CPMs (range 0.69 to 0.75. No patient or clinician characteristic affected the accuracy of informal predictions, though predictions were more accurate in outpatients.CPMs are at least as good as informal clinical predictions in discriminating between good and bad functional outcome after ischemic stroke. The place of these models in clinical practice has yet to be determined.

Clinical and functional criteria for predicting asthma in infants

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Yu. L. Mizemitskiy

2015-01-01

Full Text Available Objective: to determine clinical and functional criteria for predicting asthma in children who have sustained acute obstructive bronchitis in infancy. Subjects and methods. A total of 125 infants aged 2 to 36 months who had experienced 1 -2 episodes of acute obstructive bronchitis and treated at hospital were examined when bronchial obstruction syndrome was being relieved. In addition to physical examination, functional studies (computerized bronchophonography and heart rate variability assessment were used. Immunological examination included determination of the serum levels of immunoglobulin E and interleuMn-17A. The infants who had sustained acute obstructive bronchitis were followed up for 12-36 months. Results. The infants who had sustained acute obstructive bronchitis in the presence of mild perinatal CNS damage caused by hypoxia were typified by high respiratory morbidity; early-onset bronchial obstruction; long-term bronchial obstruction relief; high incidence of grade 2 respiratory failure in acute obstructive bronchitis. These patients developed asthma more often than twice and repeated episodes of bronchial obstruction. ROC analysis was used to elaborate clinical and functional criteria for predicting the development of asthma in infants. Conclusion. The proposed additional clinical and functional criteria characterizing external respiratory dysfunction and autonomic homeostatic changes contribute to the early diagnosis of asthma and substantially increase the validity of prediction of its development in children younger than 3 years, which is of great importance for goal-oriented preventive measures.

Establishing the kinetics of ballistic-to-diffusive transition using directional statistics

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Liu, Pai; Heinson, William R.; Sumlin, Benjamin J.; Shen, Kuan-Yu; Chakrabarty, Rajan K.

2018-04-01

We establish the kinetics of ballistic-to-diffusive (BD) transition observed in two-dimensional random walk using directional statistics. Directional correlation is parameterized using the walker's turning angle distribution, which follows the commonly adopted wrapped Cauchy distribution (WCD) function. During the BD transition, the concentration factor (ρ) governing the WCD shape is observed to decrease from its initial value. We next analytically derive the relationship between effective ρ and time, which essentially quantifies the BD transition rate. The prediction of our kinetic expression agrees well with the empirical datasets obtained from correlated random walk simulation. We further connect our formulation with the conventionally used scaling relationship between the walker's mean-square displacement and time.

Assessing the health, functional characteristics, and health needs of youth attending a noncategorical transition support program.

Science.gov (United States)

Woodward, Jason F; Swigonski, Nancy L; Ciccarelli, Mary R

2012-09-01

To assess the health, functional characteristics, and health care service needs of youth and young adults with special health care needs attending a comprehensive, noncategorical transition program. A self-administered survey was developed from national health surveys and clinical experience to assess concepts identified as important for successful transition to adulthood. Surveys were mailed to 198 parents of youth and young adults with special health care needs attending the transition clinic. Parents were asked about the youth's health, functional status, and health care services needed. The clinical database provided demographic and patient health characteristics. Results were compared against the 2005-2006 National Survey of Children with Special Health Care Needs. Forty-four percent of surveys were returned. Average age of youth was 17.5 (11-22) years old and diagnoses included cerebral palsy (36%), spina bifida (10%), developmental delay or Down syndrome (17%), and autism (6%). Most youth needed assistance with personal care (69%) and routine needs (91%) and used assistive devices (59%). Compared with the 2005-2006 National Survey of Children with Special Health Care Needs, parents reported higher needs for all services except mental health care and tobacco or substance use counseling. Forty three percent reported at least one unmet health need. Few parents reported the need for counseling on substance use (1%), sexual health screening (16%), nutrition (34%), and exercise (41%). Youth attending our transition program had more functional limitations, poorer reported health status, different diagnosis distribution, and higher levels of needed health services. Few parents identified needs for other recommended adolescent preventive services. Transition programs should assess patient health characteristics and service needs to design effective patient-centered services. Copyright © 2012 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All

Prediction of postoperative respiratory function of lung cancer patients using 99mTc-MAA SPECT

International Nuclear Information System (INIS)

Kokubo, Mitsuharu; Sakai, Satoshi; Miyata, Tomoyuki

1991-01-01

In this study, we evaluated the correlation between the predicted postoperative respiratory function using 99m Tc-MAA SPECT with chest CT and the postoperative respiratory function. 99m Tc-MAA SPECT were performed in 10 patients with lung cancer who underwent lobectomy. We measured the fractional loss in the pulmonary flow of the lobe to be resected using 99m Tc-MAA SPECT with chest CT. The value of predicted postoperative respiratory function was measured as follows: the value of predicted postoperative respiratory function=the value of preoperative respiratory function x (1-the fractional loss in the pulmonary flow of the lobe to be resected). Postoperative forced vital capacity (FVC), forced expiratory volume in the first second (FEV 1.0 ) and % vital capacity (%VC) were predicted in this study, and were compared to the respiratory function at three months and six months after operation. The predicted postoperative respiratory function was highly correlated with the actually observed postoperative respiratory function. (author)

Prediction of the transition energies of atomic No and Lr by the intermediate Hamiltonian coupled cluster method

International Nuclear Information System (INIS)

Borschevsky, A.; Eliav, E.; Kaldor, U.; Vilkas, M.J.; Ishikawa, Y.

2007-01-01

Complete text of publication follows: Measurements of the spectroscopic properties of the superheavy elements present a serious challenge to the experimentalist. Their short lifetimes and the low quantities of their production necessitate reliable prediction of transition energies to avoid the need for broad wavelength scans and to assist in identifying the lines. Thus, reliable high-accuracy calculations are necessary prior and parallel to experimental research. Nobelium and Lawrencium are at present the two most likely candidates for spectroscopic measurements, with the first experiments planned at GSI, Darmstadt. The intermediate Hamiltonian (IH) coupled cluster method is applied to the ionization potentials, electron affinities, and excitation energies of atomic nobelium and lawrencium. Large basis sets are used (37s31p26d21f16g11h6i). All levels of a particular atom are obtained simultaneously by diagonalizing the IH matrix. The matrix elements correspond to all excitations from correlated occupied orbitals to virtual orbitals in a large P space, and are 'dressed' by folding in excitations to higher virtual orbitals (Q space) at the coupled cluster singles-and-doubles level. Lamb-shift corrections are included. The same approach was applied to the lighter homologues of Lr and No, lutetium and ytterbium, for which many transition energies are experimentally known, in order to assess the accuracy of the calculation. The average absolute error of 20 excitation energies of Lu is 423 cm -1 , and the error limits for Lr are therefore put at 700 cm -1 . Predicted Lr excitations with large transition moments in the prime range for the planned experiment, 20,000-30,000 cm -1 , are 7p → 8s at 20,100 cm -1 and 7p →p 7d at 28,100 cm -1 . In case of Yb, the calculated ionization potential was within 20 cm -1 of the experiment, and the average error of the 20 lowest calculated excitations was about 300 cm -1 . Hence, the error limits of nobelium are set to 800 cm -1

Theoretical prediction of morphotropic compositions in Na1/2Bi1/2TiO3-based solid solutions from transition pressures

Science.gov (United States)

Gröting, Melanie; Albe, Karsten

2014-02-01

In this article we present a method based on ab initio calculations to predict compositions at morphotropic phase boundaries in lead-free perovskite solid solutions. This method utilizes the concept of flat free energy surfaces and involves the monitoring of pressure-induced phase transitions as a function of composition. As model systems, solid solutions of Na1/2Bi1/2TiO3 with the alkali substituted Li1/2Bi1/2TiO3 and K1/2Bi1/2TiO3 and the alkaline earth substituted CaTiO3 and BaTiO3 are chosen. The morphotropic compositions are identified by determining the composition at which the phase transition pressure equals zero. In addition, we discuss the different effects of hydrostatic pressure (compression and tension) and chemical substitution on the antiphase tilts about the [111] axis (a-a-a-) present in pure Na1/2Bi1/2TiO3 and how they develop in the two solid solutions Na1/2Bi1/2TiO3-CaTiO3 and Na1/2Bi1/2TiO3-BaTiO3. Finally, we discuss the advantages and shortcomings of this simple computational approach.

Prediction of postoperative lung function after pulmonary resection

International Nuclear Information System (INIS)

Yoshikawa, Koichi

1988-01-01

Lung scintigraphy and ordinary lung function test as well as split lung function test by using bronchospirometry was performed in 78 patients with primary lung cancer and clinical significance of ventilation and perfusion scintigraphy was evaluated. Results obtained from this study are as follows. 1) The ratio of right VC to total VC obtained by preoperative bronchospirometry was well correlated to the ratio of right lung count to the total lung count obtained by ventiration and/or perfusion scintigraphy (r = 0.84, r = 0.69). 2) Evaluation of the data obtained from the patients undergoing pneumonectomy indicated that the right and left VC obtained preoperatively by bronchospirometry have their clinical significance only in the form of left to right ratio not in the form their absolure value. 3) As to the reliability of predicting the residual vital capacity after pneumonectomy on the basis of left-to-right of lung scintigraphy, ventilation scintigraphy is more reliable than perfusion scintigraphy. 4) Irrespective of using ventilation scintigraphy or perfusion scintigraphy, Ali's formular showed high reliability in predicting the residual vital capacity as well as FEV 1.0 after lobectomy. 5) Reduction of the perfusion rate in the operated side of the lung is more marked than of the ventilation rate, resulting in a significant elevation of ventilation/perfusion ratio of the operated side of the lung. From the results descrived above, it can be said that lung ventilation and perfusion scintigraphy are very useful method to predict the residual lung function as well as the change of ventilation/perfusion ratio after pulmonary resection. (author)

Numerical detection of the Gardner transition in a mean-field glass former.

Science.gov (United States)

Charbonneau, Patrick; Jin, Yuliang; Parisi, Giorgio; Rainone, Corrado; Seoane, Beatriz; Zamponi, Francesco

2015-07-01

Recent theoretical advances predict the existence, deep into the glass phase, of a novel phase transition, the so-called Gardner transition. This transition is associated with the emergence of a complex free energy landscape composed of many marginally stable sub-basins within a glass metabasin. In this study, we explore several methods to detect numerically the Gardner transition in a simple structural glass former, the infinite-range Mari-Kurchan model. The transition point is robustly located from three independent approaches: (i) the divergence of the characteristic relaxation time, (ii) the divergence of the caging susceptibility, and (iii) the abnormal tail in the probability distribution function of cage order parameters. We show that the numerical results are fully consistent with the theoretical expectation. The methods we propose may also be generalized to more realistic numerical models as well as to experimental systems.

Lipid mobilization, immune function and the paradigm of vitamin E in transition cows.

Directory of Open Access Journals (Sweden)

Ioannis Politis

2016-06-01

Full Text Available The number of metabolic disorders that dairy cows have to cope during the transition to lactation can be divided in three main categories. The first category includes disorders related to abnormal energy metabolism (ketosis, fatty liver, acidosis. The second and the third categories include disorders related to mineral metabolism (milk fever and disorders related directly or indirectly to impaired immune function (mastitis, metritis, retained placenta, respectively. Among the many physiological changes during the transition period, perhaps the most crucial, is an increase in the concentration of plasma non-esterified fatty acids (NEFA. A portion of this increase in NEFA is obligatory and it is under hormonal control while another portion is the result of a situation known as negative energy balance (difference between energy consumed and energy spent. In this presentation I will present data from a collaborative study between the University of Milan and the Agricultural University of Athens which proves that negative correlations exist between blood concentrations of NEFA and β-hydroxybutyrate with α-tocopherol. The adipose tissue contains two main categories of cells: adipocytes and immunocompetent cells mainly monocytes/macrophages. Our research has tested the hypothesis that a cross-talk exists between adipocytes and monocytes/macrophages and this cross-talk is mediated by fatty acids released by adipocytes especially during the transition period. Results indicate that all fatty acids tested (myristic, palmitic, palmitoleic, stearic and oleic upregulate the expression of numerous pro-inflammatory genes by both monocytes but neutrophils, as well. The longer the carbon chain, the most potent is the effect.  Another hypothesis that we have tested is that vitamin E can interfere and block the cross talk between adipocytes and immunocompetent cells. Against this notion, α-tocopherol does not interfere with the effect of fatty acids on

Water hammer prediction and control: the Green's function method

Science.gov (United States)

Xuan, Li-Jun; Mao, Feng; Wu, Jie-Zhi

2012-04-01

By Green's function method we show that the water hammer (WH) can be analytically predicted for both laminar and turbulent flows (for the latter, with an eddy viscosity depending solely on the space coordinates), and thus its hazardous effect can be rationally controlled and minimized. To this end, we generalize a laminar water hammer equation of Wang et al. (J. Hydrodynamics, B2, 51, 1995) to include arbitrary initial condition and variable viscosity, and obtain its solution by Green's function method. The predicted characteristic WH behaviors by the solutions are in excellent agreement with both direct numerical simulation of the original governing equations and, by adjusting the eddy viscosity coefficient, experimentally measured turbulent flow data. Optimal WH control principle is thereby constructed and demonstrated.

A phenomenological prediction of dryout based on the churn-to-annular flow transition criterion in uniformly heated vertical tubes

International Nuclear Information System (INIS)

Hong, Sung-Deok; Chun, Se-Young; Yang, Sun-Kyu; Chung, Moon-Ki; Lashgari, Farbod

2000-01-01

A phenomenological model is proposed to predict dryout in uniformly heated vertical tubes. The major point of the study was refining the initial conditions at the onset of annular flow location that starts the liquid film dryout process. The void fraction at the onset of the annular flow location has been derived from the vapor superficial velocity obtained by the churn-to-annular flow criterion with the help of the void-quality relationship. The thermodynamic equilibrium quality calculated through the iteration of flow quality using the profile-fit model to find the accurate starting point of the annular-flow in a tube. The present method was validated by worldwide data covering wide parametric ranges, a diameter of 5.1-37.5, exit quality over 10%, a flow rate of 183-5261 kg/m 2 -s and a system pressure of 0.5-17.7 MPa. The churn-to-annular flow transition criterion of Taitel et al.'s shows better prediction results than the other transition criteria. The present model improved the CHF prediction capability as a mean of 0.97 and root mean square error of 11% for the 3883 experimental data and extended the applicable range to the relatively low quality region. (author)

Systematic expansion in the order parameter for replica theory of the dynamical glass transition.

Science.gov (United States)

Jacquin, Hugo; Zamponi, Francesco

2013-03-28

It has been shown recently that predictions from mode-coupling theory for the glass transition of hard-spheres become increasingly bad when dimensionality increases, whereas replica theory predicts a correct scaling. Nevertheless if one focuses on the regime around the dynamical transition in three dimensions, mode-coupling results are far more convincing than replica theory predictions. It seems thus necessary to reconcile the two theoretic approaches in order to obtain a theory that interpolates between low-dimensional, mode-coupling results, and "mean-field" results from replica theory. Even though quantitative results for the dynamical transition issued from replica theory are not accurate in low dimensions, two different approximation schemes--small cage expansion and replicated hyper-netted-chain (RHNC)--provide the correct qualitative picture for the transition, namely, a discontinuous jump of a static order parameter from zero to a finite value. The purpose of this work is to develop a systematic expansion around the RHNC result in powers of the static order parameter, and to calculate the first correction in this expansion. Interestingly, this correction involves the static three-body correlations of the liquid. More importantly, we separately demonstrate that higher order terms in the expansion are quantitatively relevant at the transition, and that the usual mode-coupling kernel, involving two-body direct correlation functions of the liquid, cannot be recovered from static computations.

RANDOM FUNCTIONS AND INTERVAL METHOD FOR PREDICTING THE RESIDUAL RESOURCE OF BUILDING STRUCTURES

Directory of Open Access Journals (Sweden)

Shmelev Gennadiy Dmitrievich

2017-11-01

Full Text Available Subject: possibility of using random functions and interval prediction method for estimating the residual life of building structures in the currently used buildings. Research objectives: coordination of ranges of values to develop predictions and random functions that characterize the processes being predicted. Materials and methods: when performing this research, the method of random functions and the method of interval prediction were used. Results: in the course of this work, the basic properties of random functions, including the properties of families of random functions, are studied. The coordination of time-varying impacts and loads on building structures is considered from the viewpoint of their influence on structures and representation of the structures’ behavior in the form of random functions. Several models of random functions are proposed for predicting individual parameters of structures. For each of the proposed models, its scope of application is defined. The article notes that the considered approach of forecasting has been used many times at various sites. In addition, the available results allowed the authors to develop a methodology for assessing the technical condition and residual life of building structures for the currently used facilities. Conclusions: we studied the possibility of using random functions and processes for the purposes of forecasting the residual service lives of structures in buildings and engineering constructions. We considered the possibility of using an interval forecasting approach to estimate changes in defining parameters of building structures and their technical condition. A comprehensive technique for forecasting the residual life of building structures using the interval approach is proposed.

Role of Transition Zone Index in the Prediction of Clinical Benign Prostatic Hyperplasia

Directory of Open Access Journals (Sweden)

Muhammet Güzelsoy

2016-12-01

Full Text Available Objective The objective of this study was to determine the role of the transition zone (TZ index (TZI in the prediction of clinical benign prostatic hyperplasia (BPH in patients who underwent transurethral prostatectomy (TUR-P and to analyze the correlation between the amount of resected tissue and TZ volume (TZV. Materials and Methods Twenty-six male clinical BPH patients with obstructive complaints and 17 male benign prostate enlargement (BPE patients without any complaints were included in the study. Both the groups were over the age of 50. Clinical BPH patients underwent complete TUR-P. Statistical analysis was done with SPSS. Sensitivity, specificity, positive and negative predictive values of TZI-as a method of assessing clinical BPH-were measured. Results There was a statistically significant difference in prostate volume, uroflowmetry patterns, prostate-specific antigen (PSA, International prostate symptom score (IPSS, TZV and TZI between the two groups. There was a correlation between TZV and the amount of resected tissue (r=0.97; p0.40 has a high level of sensitivity and specificity in the prediction of clinical BPH among patients who undergo TUR-P due to obstructive symptoms and reported as BPH. There is a strong correlation between the amount of resected tissue and TZV. TZI is a valuable tool in diagnosis, and TZV gives valuable information about the patient to the surgeon.

Plant functional traits predict green roof ecosystem services.

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Lundholm, Jeremy; Tran, Stephanie; Gebert, Luke

2015-02-17

Plants make important contributions to the services provided by engineered ecosystems such as green roofs. Ecologists use plant species traits as generic predictors of geographical distribution, interactions with other species, and ecosystem functioning, but this approach has been little used to optimize engineered ecosystems. Four plant species traits (height, individual leaf area, specific leaf area, and leaf dry matter content) were evaluated as predictors of ecosystem properties and services in a modular green roof system planted with 21 species. Six indicators of ecosystem services, incorporating thermal, hydrological, water quality, and carbon sequestration functions, were predicted by the four plant traits directly or indirectly via their effects on aggregate ecosystem properties, including canopy density and albedo. Species average height and specific leaf area were the most useful traits, predicting several services via effects on canopy density or growth rate. This study demonstrates that easily measured plant traits can be used to select species to optimize green roof performance across multiple key services.

Prediction of postoperative respiratory function of lung cancer patients using quantitative lung scans

International Nuclear Information System (INIS)

Konishi, Hiroshi

1982-01-01

Quantitative sup(99m)Tc-MISA inhalation scan and sup(99m)Tc-MAA perfusion scan were performed in 35 patients with lung cancer who underwent lobectomies. Quantitative 133 Xe ventilation-perfusion scans were also performed in 34 patients with lung cancer who underwent lobectomies. To predict functional loss after lobectomy, the proportion of the No. of segments in the lobe to be resected to the No. of entire segments of that lung was provided for the study. Postoperative FVC, FEVsub(1.0) and MVV were predicted in the study, and which were compared to the respiratory function at one month after operation and more than four months after operation. The predicted postoperative respiratory function was highly correlated with the actually observed postoperative respiratory function (0.7413 lt r lt 0.9278, p lt 0.001). In this study, the postoperative respiratory function was proven to be quite accurately predicted preoperatively with combination of quantitative lung scans and spirometric respiratory function. Therefore this method is useful not only for judgement of operative indication but also for choice of operative method and for counterplan of postoperative respiratory insufficiency. (J.P.N.)

DIANA-microT web server: elucidating microRNA functions through target prediction.

Science.gov (United States)

Maragkakis, M; Reczko, M; Simossis, V A; Alexiou, P; Papadopoulos, G L; Dalamagas, T; Giannopoulos, G; Goumas, G; Koukis, E; Kourtis, K; Vergoulis, T; Koziris, N; Sellis, T; Tsanakas, P; Hatzigeorgiou, A G

2009-07-01

Computational microRNA (miRNA) target prediction is one of the key means for deciphering the role of miRNAs in development and disease. Here, we present the DIANA-microT web server as the user interface to the DIANA-microT 3.0 miRNA target prediction algorithm. The web server provides extensive information for predicted miRNA:target gene interactions with a user-friendly interface, providing extensive connectivity to online biological resources. Target gene and miRNA functions may be elucidated through automated bibliographic searches and functional information is accessible through Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The web server offers links to nomenclature, sequence and protein databases, and users are facilitated by being able to search for targeted genes using different nomenclatures or functional features, such as the genes possible involvement in biological pathways. The target prediction algorithm supports parameters calculated individually for each miRNA:target gene interaction and provides a signal-to-noise ratio and a precision score that helps in the evaluation of the significance of the predicted results. Using a set of miRNA targets recently identified through the pSILAC method, the performance of several computational target prediction programs was assessed. DIANA-microT 3.0 achieved there with 66% the highest ratio of correctly predicted targets over all predicted targets. The DIANA-microT web server is freely available at www.microrna.gr/microT.

HIGH-RESOLUTION ROTATIONAL SPECTRUM, DUNHAM COEFFICIENTS, AND POTENTIAL ENERGY FUNCTION OF NaCl

International Nuclear Information System (INIS)

Cabezas, C.; Peña, I.; Alonso, J. L.; Cernicharo, J.; Quintana-Lacaci, G.; Agundez, M.; Prieto, L. Velilla; Castro-Carrizo, A.; Zuñiga, J.; Bastida, A.; Requena, A.

2016-01-01

We report laboratory spectroscopy for the first time of the J = 1–0 and J = 2–1 lines of Na 35 Cl and Na 37 Cl in several vibrational states. The hyperfine structure has been resolved in both transitions for all vibrational levels, which permit us to predict with high accuracy the hyperfine splitting of the rotational transitions of the two isotopologues at higher frequencies. The new data have been merged with all previous works at microwave, millimeter, and infrared wavelengths and fitted to a series of mass-independent Dunham parameters and to a potential energy function. The obtained parameters have been used to compute a new dipole moment function, from which the dipole moment for infrared transitions up to Δ v = 8 has been derived. Frequency and intensity predictions are provided for all rovibrational transitions up to J = 150 and v = 8, from which the ALMA data of evolved stars can be modeled and interpreted.

HIGH-RESOLUTION ROTATIONAL SPECTRUM, DUNHAM COEFFICIENTS, AND POTENTIAL ENERGY FUNCTION OF NaCl

Energy Technology Data Exchange (ETDEWEB)

Cabezas, C.; Peña, I.; Alonso, J. L. [Grupo de Espectroscopía Molecular, Edificio Quifima, Laboratorios de Espectroscopía y Bioespectroscopía, Unidad asociada CSIC, Parque científico Uva, Universidad de Valladolid, Paseo de Belén 5, E-47011, Valladolid (Spain); Cernicharo, J.; Quintana-Lacaci, G.; Agundez, M.; Prieto, L. Velilla [Group of Molecular Astrophysics, ICMM, CSIC. C/Sor Juana Inés de la Cruz 3, E-28049 Cantoblanco, Madrid (Spain); Castro-Carrizo, A. [Institut de Radioastronomie Millimétrique, 300 rue de la la Piscine, F-38406, Saint Martin d’Hères (France); Zuñiga, J.; Bastida, A.; Requena, A. [Universidad de Murcia. Faculdad de Química, Dpto. de Química-Física, Campus Espinardo E-30100, Murcia (Spain)

2016-07-10

We report laboratory spectroscopy for the first time of the J = 1–0 and J = 2–1 lines of Na{sup 35}Cl and Na{sup 37}Cl in several vibrational states. The hyperfine structure has been resolved in both transitions for all vibrational levels, which permit us to predict with high accuracy the hyperfine splitting of the rotational transitions of the two isotopologues at higher frequencies. The new data have been merged with all previous works at microwave, millimeter, and infrared wavelengths and fitted to a series of mass-independent Dunham parameters and to a potential energy function. The obtained parameters have been used to compute a new dipole moment function, from which the dipole moment for infrared transitions up to Δ v = 8 has been derived. Frequency and intensity predictions are provided for all rovibrational transitions up to J = 150 and v = 8, from which the ALMA data of evolved stars can be modeled and interpreted.

Correlation of bowel symptoms with colonic transit, length, and faecal load in functional faecal retention

DEFF Research Database (Denmark)

Raahave, Dennis; Christensen, Elsebeth; Loud, Franck B.

2009-01-01

INTRODUCTION: Abdominal pain, bloating, and defecation disturbances are common complaints in gastrointestinal functional disorders. This study explores whether bowel symptoms are correlated to colon transit time (CTT), faecal loading (coprostasis), and colon length; and whether prokinetic interve...

AptRank: an adaptive PageRank model for protein function prediction on   bi-relational graphs.

Science.gov (United States)

Jiang, Biaobin; Kloster, Kyle; Gleich, David F; Gribskov, Michael

2017-06-15

Diffusion-based network models are widely used for protein function prediction using protein network data and have been shown to outperform neighborhood-based and module-based methods. Recent studies have shown that integrating the hierarchical structure of the Gene Ontology (GO) data dramatically improves prediction accuracy. However, previous methods usually either used the GO hierarchy to refine the prediction results of multiple classifiers, or flattened the hierarchy into a function-function similarity kernel. No study has taken the GO hierarchy into account together with the protein network as a two-layer network model. We first construct a Bi-relational graph (Birg) model comprised of both protein-protein association and function-function hierarchical networks. We then propose two diffusion-based methods, BirgRank and AptRank, both of which use PageRank to diffuse information on this two-layer graph model. BirgRank is a direct application of traditional PageRank with fixed decay parameters. In contrast, AptRank utilizes an adaptive diffusion mechanism to improve the performance of BirgRank. We evaluate the ability of both methods to predict protein function on yeast, fly and human protein datasets, and compare with four previous methods: GeneMANIA, TMC, ProteinRank and clusDCA. We design four different validation strategies: missing function prediction, de novo function prediction, guided function prediction and newly discovered function prediction to comprehensively evaluate predictability of all six methods. We find that both BirgRank and AptRank outperform the previous methods, especially in missing function prediction when using only 10% of the data for training. The MATLAB code is available at https://github.rcac.purdue.edu/mgribsko/aptrank . gribskov@purdue.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

A multiple-field coupled resistive transition model for superconducting Nb3Sn

Science.gov (United States)

Yang, Lin; Ding, He; Zhang, Xin; Qiao, Li

2016-12-01

A study on the superconducting transition width as functions of the applied magnetic field and strain is performed in superconducting Nb3Sn. A quantitative, yet universal phenomenological resistivity model is proposed. The numerical simulation by the proposed model shows predicted resistive transition characteristics under variable magnetic fields and strain, which in good agreement with the experimental observations. Furthermore, a temperature-modulated magnetoresistance transition behavior in filamentary Nb3Sn conductors can also be well described by the given model. The multiple-field coupled resistive transition model is helpful for making objective determinations of the high-dimensional critical surface of Nb3Sn in the multi-parameter space, offering some preliminary information about the basic vortex-pinning mechanisms, and guiding the design of the quench protection system of Nb3Sn superconducting magnets.

On the use of spring baseflow recession for a more accurate parameterization of aquifer transit time distribution functions

Directory of Open Access Journals (Sweden)

J. Farlin

2013-05-01

Full Text Available Baseflow recession analysis and groundwater dating have up to now developed as two distinct branches of hydrogeology and have been used to solve entirely different problems. We show that by combining two classical models, namely the Boussinesq equation describing spring baseflow recession, and the exponential piston-flow model used in groundwater dating studies, the parameters describing the transit time distribution of an aquifer can be in some cases estimated to a far more accurate degree than with the latter alone. Under the assumption that the aquifer basis is sub-horizontal, the mean transit time of water in the saturated zone can be estimated from spring baseflow recession. This provides an independent estimate of groundwater transit time that can refine those obtained from tritium measurements. The approach is illustrated in a case study predicting atrazine concentration trend in a series of springs draining the fractured-rock aquifer known as the Luxembourg Sandstone. A transport model calibrated on tritium measurements alone predicted different times to trend reversal following the nationwide ban on atrazine in 2005 with different rates of decrease. For some of the springs, the actual time of trend reversal and the rate of change agreed extremely well with the model calibrated using both tritium measurements and the recession of spring discharge during the dry season. The agreement between predicted and observed values was however poorer for the springs displaying the most gentle recessions, possibly indicating a stronger influence of continuous groundwater recharge during the summer months.

Manipulating Light with Transition Metal Clusters, Organic Dyes, and Metal Organic Frameworks

Energy Technology Data Exchange (ETDEWEB)

Ogut, Serdar [Univ. of Illinois, Chicago, IL (United States)

2017-09-11

The primary goals of our research program is to develop and apply state-of-the-art first-principles methods to predict electronic and optical properties of three systems of significant scientific and technological interest: transition metal clusters, organic dyes, and metal-organic frameworks. These systems offer great opportunities to manipulate light for a wide ranging list of energy-related scientific problems and applications. During this grant period, we focused our investigations on the development, implementation, and benchmarking of many-body Green’s function methods (GW approximation and the Bethe-Salpeter equation) to examine excited-state properties of transition metal/transition-metal-oxide clusters and organic molecules that comprise the building blocks of dyes and metal-organic frameworks.

Computational prediction of drug-drug interactions based on drugs functional similarities.

Science.gov (United States)

Ferdousi, Reza; Safdari, Reza; Omidi, Yadollah

2017-06-01

Therapeutic activities of drugs are often influenced by co-administration of drugs that may cause inevitable drug-drug interactions (DDIs) and inadvertent side effects. Prediction and identification of DDIs are extremely vital for the patient safety and success of treatment modalities. A number of computational methods have been employed for the prediction of DDIs based on drugs structures and/or functions. Here, we report on a computational method for DDIs prediction based on functional similarity of drugs. The model was set based on key biological elements including carriers, transporters, enzymes and targets (CTET). The model was applied for 2189 approved drugs. For each drug, all the associated CTETs were collected, and the corresponding binary vectors were constructed to determine the DDIs. Various similarity measures were conducted to detect DDIs. Of the examined similarity methods, the inner product-based similarity measures (IPSMs) were found to provide improved prediction values. Altogether, 2,394,766 potential drug pairs interactions were studied. The model was able to predict over 250,000 unknown potential DDIs. Upon our findings, we propose the current method as a robust, yet simple and fast, universal in silico approach for identification of DDIs. We envision that this proposed method can be used as a practical technique for the detection of possible DDIs based on the functional similarities of drugs. Copyright © 2017. Published by Elsevier Inc.

Fungal NRPS-dependent siderophores: From function to prediction

DEFF Research Database (Denmark)

Sørensen, Jens Laurids; Knudsen, Michael; Hansen, Frederik Teilfeldt

2014-01-01

discuss the function of siderophores in relation to fungal iron uptake mechanisms and their importance for coexistence with host organisms. The chemical nature of the major groups of siderophores and their regulation is described along with the function and architecture of the large multi-domain enzymes...... responsible for siderophore synthesis, namely the non-ribosomal peptide synthetases (NRPSs). Finally, we present the most recent advances in our understanding of the structural biology of fungal NRPSs and discuss opportunities for the development of a fungal NRPS prediction server...

Characterization and Prediction of Chemical Functions and ...

Science.gov (United States)

Assessing exposures from the thousands of chemicals in commerce requires quantitative information on the chemical constituents of consumer products. Unfortunately, gaps in available composition data prevent assessment of exposure to chemicals in many products. Here we propose filling these gaps via consideration of chemical functional role. We obtained function information for thousands of chemicals from public sources and used a clustering algorithm to assign chemicals into 35 harmonized function categories (e.g., plasticizers, antimicrobials, solvents). We combined these functions with weight fraction data for 4115 personal care products (PCPs) to characterize the composition of 66 different product categories (e.g., shampoos). We analyzed the combined weight fraction/function dataset using machine learning techniques to develop quantitative structure property relationship (QSPR) classifier models for 22 functions and for weight fraction, based on chemical-specific descriptors (including chemical properties). We applied these classifier models to a library of 10196 data-poor chemicals. Our predictions of chemical function and composition will inform exposure-based screening of chemicals in PCPs for combination with hazard data in risk-based evaluation frameworks. As new information becomes available, this approach can be applied to other classes of products and the chemicals they contain in order to provide essential consumer product data for use in exposure-b

An Ordered Regression Model to Predict Transit Passengers’ Behavioural Intentions

Energy Technology Data Exchange (ETDEWEB)

Oña, J. de; Oña, R. de; Eboli, L.; Forciniti, C.; Mazzulla, G.

2016-07-01

Passengers’ behavioural intentions after experiencing transit services can be viewed as signals that show if a customer continues to utilise a company’s service. Users’ behavioural intentions can depend on a series of aspects that are difficult to measure directly. More recently, transit passengers’ behavioural intentions have been just considered together with the concepts of service quality and customer satisfaction. Due to the characteristics of the ways for evaluating passengers’ behavioural intentions, service quality and customer satisfaction, we retain that this kind of issue could be analysed also by applying ordered regression models. This work aims to propose just an ordered probit model for analysing service quality factors that can influence passengers’ behavioural intentions towards the use of transit services. The case study is the LRT of Seville (Spain), where a survey was conducted in order to collect the opinions of the passengers about the existing transit service, and to have a measure of the aspects that can influence the intentions of the users to continue using the transit service in the future. (Author)

How do generalized jamming transitions affect collective migration in confluent tissues?

Science.gov (United States)

Manning, M. Lisa

Recent experiments have demonstrated that tissues involved in embryonic development, lung function, wound healing, and cancer progression are close to fluid-to-solid, or ``jamming'' transitions. Theoretical models for confluent 2D tissues have also been shown to exhibit continuous rigidity transitions. However, in vivobiological systems can differ in significant ways from the simple 2D models. For example, many tissues are three-dimensional, mechanically heterogeneous, and/or composed of mechanosensitive cells interspersed with extracellular matrix. We have extended existing models for confluent tissues to capture these features, and we find interesting predictions for collective cell motion that are ultimately related to an underlying generalized jamming transition. For example, in 2D, we find that heterogeneous mixtures of cells spontaneously self-organize into rigid regions of stiffer cells interspersed with string-like groups of soft cells, reminiscent of cellular streaming seen in cancer. We also find that alignment interactions (of the sort often explored in self-propelled particle models) alter the transition and generate interesting flocked liquid and flocked solid collective migration patterns. Our model predicts that 3D tissues also exhibit a jamming transition governed by cell shape, as well as history-dependent aging, and we are currently exploring whether ECM-like interactions in 3D models might help explain compressional stiffening seen in experiments on human tissue.

Predicting bioactive glass properties from the molecular chemical composition: glass transition temperature.

Science.gov (United States)

O'Donnell, Matthew D

2011-05-01

The glass transition temperature (T(g)) of inorganic glasses is an important parameter than can be used to correlate with other glass properties, such as dissolution rate, which governs in vitro and in vivo bioactivity. Seven bioactive glass compositional series reported in the literature (77 in total) were analysed here with T(g) values obtained by a number of different methods: differential thermal analysis, differential scanning calorimetry and dilatometry. An iterative least-squares fitting method was used to correlate T(g) from thermal analysis of these compositions with the levels of individual oxide and fluoride components in the glasses. When all seven series were fitted a reasonable correlation was found between calculated and experimental values (R(2)=0.89). When the two compositional series that were designed in weight percentages (the remaining five were designed in molar percentage) were removed from the model an improved fit was achieved (R(2)=0.97). This study shows that T(g) for a wide range in compositions (e.g. SiO(2) content of 37.3-68.4 mol.%) can be predicted to reasonable accuracy enabling processing parameters to be predicted such as annealing, fibre-drawing and sintering temperatures. Copyright © 2011 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

The perimenopausal aging transition in the female rat brain: decline in bioenergetic systems and synaptic plasticity.

Science.gov (United States)

Yin, Fei; Yao, Jia; Sancheti, Harsh; Feng, Tao; Melcangi, Roberto C; Morgan, Todd E; Finch, Caleb E; Pike, Christian J; Mack, Wendy J; Cadenas, Enrique; Brinton, Roberta D

2015-07-01

The perimenopause is an aging transition unique to the female that leads to reproductive senescence which can be characterized by multiple neurological symptoms. To better understand potential underlying mechanisms of neurological symptoms of perimenopause, the present study determined genomic, biochemical, brain metabolic, and electrophysiological transformations that occur during this transition using a rat model recapitulating fundamental characteristics of the human perimenopause. Gene expression analyses indicated two distinct aging programs: chronological and endocrine. A critical period emerged during the endocrine transition from regular to irregular cycling characterized by decline in bioenergetic gene expression, confirmed by deficits in fluorodeoxyglucose-positron emission tomography (FDG-PET) brain metabolism, mitochondrial function, and long-term potentiation. Bioinformatic analysis predicted insulin/insulin-like growth factor 1 and adenosine monophosphate-activated protein kinase/peroxisome proliferator-activated receptor gamma coactivator 1 alpha (AMPK/PGC1α) signaling pathways as upstream regulators. Onset of acyclicity was accompanied by a rise in genes required for fatty acid metabolism, inflammation, and mitochondrial function. Subsequent chronological aging resulted in decline of genes required for mitochondrial function and β-amyloid degradation. Emergence of glucose hypometabolism and impaired synaptic function in brain provide plausible mechanisms of neurological symptoms of perimenopause and may be predictive of later-life vulnerability to hypometabolic conditions such as Alzheimer's. Copyright © 2015 Elsevier Inc. All rights reserved.

Organization of intrinsic functional brain connectivity predicts decisions to reciprocate social behavior.

Science.gov (United States)

Cáceda, Ricardo; James, G Andrew; Gutman, David A; Kilts, Clinton D

2015-10-01

Reciprocation of trust exchanges is central to the development of interpersonal relationships and societal well-being. Understanding how humans make pro-social and self-centered decisions in dyadic interactions and how to predict these choices has been an area of great interest in social neuroscience. A functional magnetic resonance imaging (fMRI) based technology with potential clinical application is the study of resting state brain connectivity. We tested if resting state connectivity may predict choice behavior in a social context. Twenty-nine healthy adults underwent resting state fMRI before performing the Trust Game, a two person monetary exchange game. We assessed the ability of patterns of resting-state functional brain organization, demographic characteristics and a measure of moral development, the Defining Issues Test (DIT-2), to predict individuals' decisions to reciprocate money during the Trust Game. Subjects reciprocated in 74.9% of the trials. Independent component analysis identified canonical resting-state networks. Increased functional connectivity between the salience (bilateral insula/anterior cingulate) and central executive (dorsolateral prefrontal cortex/ posterior parietal cortex) networks significantly predicted the choice to reciprocate pro-social behavior (R(2) = 0.20, p = 0.015). Stepwise linear regression analysis showed that functional connectivity between these two networks (p = 0.002), age (p = 0.007) and DIT-2 personal interest schema score (p = 0.032) significantly predicted reciprocity behavior (R(2) = 0.498, p = 0.001). Intrinsic functional connectivity between neural networks in conjunction with other individual characteristics may be a valuable tool for predicting performance during social interactions. Future replication and temporal extension of these findings may bolster the understanding of decision making in clinical, financial and marketing settings. Copyright © 2015 Elsevier B.V. All rights reserved.

Idiopathic Pulmonary Fibrosis: Gender-Age-Physiology Index Stage for Predicting Future Lung Function Decline.

Science.gov (United States)

Salisbury, Margaret L; Xia, Meng; Zhou, Yueren; Murray, Susan; Tayob, Nabihah; Brown, Kevin K; Wells, Athol U; Schmidt, Shelley L; Martinez, Fernando J; Flaherty, Kevin R

2016-02-01

Idiopathic pulmonary fibrosis is a progressive lung disease with variable course. The Gender-Age-Physiology (GAP) Index and staging system uses clinical variables to stage mortality risk. It is unknown whether clinical staging predicts future decline in pulmonary function. We assessed whether the GAP stage predicts future pulmonary function decline and whether interval pulmonary function change predicts mortality after accounting for stage. Patients with idiopathic pulmonary fibrosis (N = 657) were identified retrospectively at three tertiary referral centers, and baseline GAP stages were assessed. Mixed models were used to describe average trajectories of FVC and diffusing capacity of the lung for carbon monoxide (Dlco). Multivariable Cox proportional hazards models were used to assess whether declines in pulmonary function ≥ 10% in 6 months predict mortality after accounting for GAP stage. Over a 2-year period, GAP stage was not associated with differences in yearly lung function decline. After accounting for stage, a 10% decrease in FVC or Dlco over 6 months independently predicted death or transplantation (FVC hazard ratio, 1.37; Dlco hazard ratio, 1.30; both, P ≤ .03). Patients with GAP stage 2 with declining pulmonary function experienced a survival profile similar to patients with GAP stage 3, with 1-year event-free survival of 59.3% (95% CI, 49.4-67.8) vs 56.9% (95% CI, 42.2-69.1). Baseline GAP stage predicted death or lung transplantation but not the rate of future pulmonary function decline. After accounting for GAP stage, a decline of ≥ 10% over 6 months independently predicted death or lung transplantation. Copyright © 2016 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.

Improving Care Transitions Management: Examining the Role of Accountable Care Organization Participation and Expanded Electronic Health Record Functionality.

Science.gov (United States)

Huber, Thomas P; Shortell, Stephen M; Rodriguez, Hector P

2017-08-01

Examine the extent to which physician organization participation in an accountable care organization (ACO) and electronic health record (EHR) functionality are associated with greater adoption of care transition management (CTM) processes. A total of 1,398 physician organizations from the third National Study of Physician Organization survey (NSPO3), a nationally representative sample of medical practices in the United States (January 2012-May 2013). We used data from the third National Study of Physician Organization survey (NSPO3) to assess medical practice characteristics, including CTM processes, ACO participation, EHR functionality, practice type, organization size, ownership, public reporting, and pay-for-performance participation. Multivariate linear regression models estimated the extent to which ACO participation and EHR functionality were associated with greater CTM capabilities, controlling for practice size, ownership, public reporting, and pay-for-performance participation. Approximately half (52.4 percent) of medical practices had a formal program for managing care transitions in place. In adjusted analyses, ACO participation (p risk-bearing arrangements across the country may improve the management of care transitions by physician organizations. © Health Research and Educational Trust.

Challenges in microbial ecology: Building predictive understanding of community function and dynamics

DEFF Research Database (Denmark)

Widder, Stefanie; Allen, Rosalind J.; Pfeiffer, Thomas

2016-01-01

The importance of microbial communities (MCs) cannot be overstated. MCs underpin the biogeochemical cycles of the earth's soil, oceans and the atmosphere, and perform ecosystem functions that impact plants, animals and humans. Yet our ability to predict and manage the function of these highly...... complex, dynamically changing communities is limited. Building predictive models that link MC composition to function is a key emerging challenge in microbial ecology. Here, we argue that addressing this challenge requires close coordination of experimental data collection and method development...... is needed to achieve significant progress in our understanding of MC dynamics and function, and we make specific practical suggestions as to how this could be achieved....

PFP: Automated prediction of gene ontology functional annotations with confidence scores using protein sequence data.

Science.gov (United States)

Hawkins, Troy; Chitale, Meghana; Luban, Stanislav; Kihara, Daisuke

2009-02-15

Protein function prediction is a central problem in bioinformatics, increasing in importance recently due to the rapid accumulation of biological data awaiting interpretation. Sequence data represents the bulk of this new stock and is the obvious target for consideration as input, as newly sequenced organisms often lack any other type of biological characterization. We have previously introduced PFP (Protein Function Prediction) as our sequence-based predictor of Gene Ontology (GO) functional terms. PFP interprets the results of a PSI-BLAST search by extracting and scoring individual functional attributes, searching a wide range of E-value sequence matches, and utilizing conventional data mining techniques to fill in missing information. We have shown it to be effective in predicting both specific and low-resolution functional attributes when sufficient data is unavailable. Here we describe (1) significant improvements to the PFP infrastructure, including the addition of prediction significance and confidence scores, (2) a thorough benchmark of performance and comparisons to other related prediction methods, and (3) applications of PFP predictions to genome-scale data. We applied PFP predictions to uncharacterized protein sequences from 15 organisms. Among these sequences, 60-90% could be annotated with a GO molecular function term at high confidence (>or=80%). We also applied our predictions to the protein-protein interaction network of the Malaria plasmodium (Plasmodium falciparum). High confidence GO biological process predictions (>or=90%) from PFP increased the number of fully enriched interactions in this dataset from 23% of interactions to 94%. Our benchmark comparison shows significant performance improvement of PFP relative to GOtcha, InterProScan, and PSI-BLAST predictions. This is consistent with the performance of PFP as the overall best predictor in both the AFP-SIG '05 and CASP7 function (FN) assessments. PFP is available as a web service at http

Transition Heat Transfer Modeling Based on the Characteristics of Turbulent Spots

Science.gov (United States)

Simon, Fred; Boyle, Robert

1998-01-01

While turbulence models are being developed which show promise for simulating the transition region on a turbine blade or vane, it is believed that the best approach with the greatest potential for practical use is the use of models which incorporate the physics of turbulent spots present in the transition region. This type of modeling results in the prediction of transition region intermittency which when incorporated in turbulence models give a good to excellent prediction of the transition region heat transfer. Some models are presented which show how turbulent spot characteristics and behavior can be employed to predict the effect of pressure gradient and Mach number on the transition region. The models predict the spot formation rate which is needed, in addition to the transition onset location, in the Narasimha concentrated breakdown intermittency equation. A simplified approach is taken for modeling turbulent spot growth and interaction in the transition region which utilizes the turbulent spot variables governing transition length and spot generation rate. The models are expressed in terms of spot spreading angle, dimensionless spot velocity, dimensionless spot area, disturbance frequency and Mach number. The models are used in conjunction with a computer code to predict the effects of pressure gradient and Mach number on the transition region and compared with VKI experimental turbine data.

Oxygen effect on the work function of electropositive metal films adsorbed on 4d and 5d-transition metals

International Nuclear Information System (INIS)

Kultashev, O.K.; Makarov, A.P.; Rozhkov, S.E.

1976-01-01

The thermionic emission method was used to study the effect of oxygen upon the work function of films of electropositive metals, Sc, Y, La and Ba on some monocrystal and polycrystalline specimens of 4d- and 5d-transition metals of groups 4-8 of the Periodic system. It was revealed that when the supports were polycrystalline and monocrystalline specimens of transition metals of Group 5 (niobium and tantalum), the work function phi of films of electropositive adsorbates dropped substantially as compared, e.g., to the phi values on the same faces of tungsten. When the concentration of the electropositive adsorbate exceeds the optimum value (in the absence of oxygen), oxygen exerts an appreciably activating action upon the work function phi of films of electropositive adsorbates on transition metals of the Groups 7 and 8. The activating action of oxygen is assumed to be due to a possibility of formation of surface interstitial structures

Phase transitions

CERN Document Server

Sole, Ricard V; Solé, Ricard V; Solé, Ricard V; Sol, Ricard V; Solé, Ricard V

2011-01-01

Phase transitions--changes between different states of organization in a complex system--have long helped to explain physics concepts, such as why water freezes into a solid or boils to become a gas. How might phase transitions shed light on important problems in biological and ecological complex systems? Exploring the origins and implications of sudden changes in nature and society, Phase Transitions examines different dynamical behaviors in a broad range of complex systems. Using a compelling set of examples, from gene networks and ant colonies to human language and the degradation of diverse ecosystems, the book illustrates the power of simple models to reveal how phase transitions occur. Introductory chapters provide the critical concepts and the simplest mathematical techniques required to study phase transitions. In a series of example-driven chapters, Ricard Solé shows how such concepts and techniques can be applied to the analysis and prediction of complex system behavior, including the origins of ...

Clinical and functional criteria for predicting asthma in infants

OpenAIRE

Yu. L. Mizemitskiy; V. A. Pavlenko; I. M. Melnikova

2015-01-01

Objective: to determine clinical and functional criteria for predicting asthma in children who have sustained acute obstructive bronchitis in infancy. Subjects and methods. A total of 125 infants aged 2 to 36 months who had experienced 1 -2 episodes of acute obstructive bronchitis and treated at hospital were examined when bronchial obstruction syndrome was being relieved. In addition to physical examination, functional studies (computerized bronchophonography and heart rate variability asses...

Customizing Countermeasure Prescriptions using Predictive Measures of Sensorimotor Adaptability

Science.gov (United States)

Bloomberg, J. J.; Peters, B. T.; Mulavara, A. P.; Miller, C. A.; Batson, C. D.; Wood, S. J.; Guined, J. R.; Cohen, H. S.; Buccello-Stout, R.; DeDios, Y. E.;

Function and Phenotype prediction through Data and Knowledge Fusion

KAUST Repository

Vespoor, Karen

2016-01-01

I will introduce the use of text mining techniques to support analysis of biological data sets, and will specifically discuss applications in protein function and phenotype prediction, as well as analysis of genetic variants that are supported

Prediction and Factor Extraction of Drug Function by Analyzing Medical Records in Developing Countries.

Science.gov (United States)

Hu, Min; Nohara, Yasunobu; Nakamura, Masafumi; Nakashima, Naoki

2017-01-01

The World Health Organization has declared Bangladesh one of 58 countries facing acute Human Resources for Health (HRH) crisis. Artificial intelligence in healthcare has been shown to be successful for diagnostics. Using machine learning to predict pharmaceutical prescriptions may solve HRH crises. In this study, we investigate a predictive model by analyzing prescription data of 4,543 subjects in Bangladesh. We predict the function of prescribed drugs, comparing three machine-learning approaches. The approaches compare whether a subject shall be prescribed medicine from the 21 most frequently prescribed drug functions. Receiver Operating Characteristics (ROC) were selected as a way to evaluate and assess prediction models. The results show the drug function with the best prediction performance was oral hypoglycemic drugs, which has an average AUC of 0.962. To understand how the variables affect prediction, we conducted factor analysis based on tree-based algorithms and natural language processing techniques.

Quantifying confidence in density functional theory predictions of magnetic ground states

Science.gov (United States)

Houchins, Gregory; Viswanathan, Venkatasubramanian

2017-10-01

Density functional theory (DFT) simulations, at the generalized gradient approximation (GGA) level, are being routinely used for material discovery based on high-throughput descriptor-based searches. The success of descriptor-based material design relies on eliminating bad candidates and keeping good candidates for further investigation. While DFT has been widely successfully for the former, oftentimes good candidates are lost due to the uncertainty associated with the DFT-predicted material properties. Uncertainty associated with DFT predictions has gained prominence and has led to the development of exchange correlation functionals that have built-in error estimation capability. In this work, we demonstrate the use of built-in error estimation capabilities within the BEEF-vdW exchange correlation functional for quantifying the uncertainty associated with the magnetic ground state of solids. We demonstrate this approach by calculating the uncertainty estimate for the energy difference between the different magnetic states of solids and compare them against a range of GGA exchange correlation functionals as is done in many first-principles calculations of materials. We show that this estimate reasonably bounds the range of values obtained with the different GGA functionals. The estimate is determined as a postprocessing step and thus provides a computationally robust and systematic approach to estimating uncertainty associated with predictions of magnetic ground states. We define a confidence value (c-value) that incorporates all calculated magnetic states in order to quantify the concurrence of the prediction at the GGA level and argue that predictions of magnetic ground states from GGA level DFT is incomplete without an accompanying c-value. We demonstrate the utility of this method using a case study of Li-ion and Na-ion cathode materials and the c-value metric correctly identifies that GGA-level DFT will have low predictability for NaFePO4F . Further, there

Executive functioning predicts reading, mathematics, and theory of mind during the elementary years.

Science.gov (United States)

Cantin, Rachelle H; Gnaedinger, Emily K; Gallaway, Kristin C; Hesson-McInnis, Matthew S; Hund, Alycia M

2016-06-01

The goal of this study was to specify how executive functioning components predict reading, mathematics, and theory of mind performance during the elementary years. A sample of 93 7- to 10-year-old children completed measures of working memory, inhibition, flexibility, reading, mathematics, and theory of mind. Path analysis revealed that all three executive functioning components (working memory, inhibition, and flexibility) mediated age differences in reading comprehension, whereas age predicted mathematics and theory of mind directly. In addition, reading mediated the influence of executive functioning components on mathematics and theory of mind, except that flexibility also predicted mathematics directly. These findings provide important details about the development of executive functioning, reading, mathematics, and theory of mind during the elementary years. Copyright © 2016 Elsevier Inc. All rights reserved.

Longitudinal Changes in Sexual Functioning as Women Transition Through Menopause: Results from the Study of Women’s Health Across the Nation (SWAN)

Science.gov (United States)

Avis, Nancy E.; Brockwell, Sarah; Randolph, John F.; Shen, Shunhua; Cain, Virginia S.; Ory, Marcia; Greendale, Gail A.

2009-01-01

Objective Sexual functioning is an important component of women’s lives. The extent to which the menopause transition is associated with decreased sexual functioning remains inconclusive. This study seeks to determine if advancing through the menopause transition is associated with changes in sexual functioning. Design A prospective, longitudinal cohort study of women aged 42–52 at baseline recruited at 7 US sites (N=3302) in the Study of Women’s Health Across the Nation (SWAN). Cohort eligible women had an intact uterus, at least one ovary, were not currently using exogenous hormones, were either pre- or early perimenopausal, and self-identified as one of the study’s designated racial/ethnic groups. Data from the baseline interview and six annual follow-up visits are reported. Outcomes are self-reported ratings of importance of sex; frequency of sexual desire, arousal, masturbation, sexual intercourse, and pain during intercourse; degree of emotional satisfaction and physical pleasure. Results Adjusting for baseline age, chronological aging, and relevant social, health, and psychological parameters, the odds of reporting vaginal or pelvic pain increased and desire decreased by late perimenopause. Masturbation increased at early perimenopause, but declined during postmenopause. Menopausal transition was unrelated to other outcomes. Health, psychological functioning, and importance of sex were related to all sexual function outcomes. Age, race/ethnicity, marital status, change in relationship, and vaginal dryness were also associated with sexual functioning. Conclusions Pain during sexual intercourse increases and sexual desire decreases over the menopausal transition. Masturbation increases during the early transition, but then declines in postmenopause. Adjusting for other factors, the menopausal transition was not independently associated with reports of the importance of sex, sexual arousal, frequency of sexual intercourse, emotional satisfaction with

Spectral simplicity of apparent complexity. I. The nondiagonalizable metadynamics of prediction

Science.gov (United States)

Riechers, Paul M.; Crutchfield, James P.

2018-03-01

Virtually all questions that one can ask about the behavioral and structural complexity of a stochastic process reduce to a linear algebraic framing of a time evolution governed by an appropriate hidden-Markov process generator. Each type of question—correlation, predictability, predictive cost, observer synchronization, and the like—induces a distinct generator class. Answers are then functions of the class-appropriate transition dynamic. Unfortunately, these dynamics are generically nonnormal, nondiagonalizable, singular, and so on. Tractably analyzing these dynamics relies on adapting the recently introduced meromorphic functional calculus, which specifies the spectral decomposition of functions of nondiagonalizable linear operators, even when the function poles and zeros coincide with the operator's spectrum. Along the way, we establish special properties of the spectral projection operators that demonstrate how they capture the organization of subprocesses within a complex system. Circumventing the spurious infinities of alternative calculi, this leads in the sequel, Part II [P. M. Riechers and J. P. Crutchfield, Chaos 28, 033116 (2018)], to the first closed-form expressions for complexity measures, couched either in terms of the Drazin inverse (negative-one power of a singular operator) or the eigenvalues and projection operators of the appropriate transition dynamic.

The mythology of renal function measurement

International Nuclear Information System (INIS)

Britton, K.E.

2003-01-01

The kidney is a conservative organ. In principle it retains what the body needs, and what is not needed is excreted. It has a number of basic properties. It has the ability to take solutes up from the blood whether by filtration or secretion, which is best called its Uptake function. In the special circumstance where the kidneys are the only exit for the solute from the body, then the rate of loss from the blood is equal to the rate of uptake by the kidney. It has the ability to move solutes among its nephrons, which is its Transit function. The solutes may be absorbed in whole or part and be retained or returned to the blood, its Reabsorption function. In the special case where the solute is non- reabsorbable, then, if there is an increase in salt and water reabsorption as in functionally significant renovascular disease or obstructive nephropathy, the transit function is altered and the transit time through the parenchyme is prolonged. In renovascular disorder the transit time is prolonged through both cortical and juxta-medullary nephrons and collecting ducts. In obstructive nephropathy the transit time is prolonged through the cortical nephrons, but usually is shortened through the juxta-medullary nephrons and collecting ducts due to loss of medullary concentrating ability. After transit through the kidney, the solutes move through the pelvis and ureter, its Excretory function. No more can come out of the kidney then went in previously. If less comes out than what went in, then an increased resistance to outflow is predicted. The balance between excretory function and uptake function is measurable by the Output (Outflow) Efficiency. The kidney also has receptors for hormones, which may modify its reabsorptive functions, for example increased Vasopressin binding decreases the permeability of the collecting duct to water. The kidney also has the ability through enzymes to modify solutes, such as the activation of Vitamin D

Predictions of glass transition temperature for hydrogen bonding biomaterials.

Science.gov (United States)

van der Sman, R G M

2013-12-19

We show that the glass transition of a multitude of mixtures containing hydrogen bonding materials correlates strongly with the effective number of hydroxyl groups per molecule, which are available for intermolecular hydrogen bonding. This correlation is in compliance with the topological constraint theory, wherein the intermolecular hydrogen bonds constrain the mobility of the hydrogen bonded network. The finding that the glass transition relates to hydrogen bonding rather than free volume agrees with our recent finding that there is little difference in free volume among carbohydrates and polysaccharides. For binary and ternary mixtures of sugars, polyols, or biopolymers with water, our correlation states that the glass transition temperature is linear with the inverse of the number of effective hydroxyl groups per molecule. Only for dry biopolymer/sugar or sugar/polyol mixtures do we find deviations due to nonideal mixing, imposed by microheterogeneity.

A new method for predicting functional recovery of stroke patients with hemiplegia: logarithmic modelling.

Science.gov (United States)

Koyama, Tetsuo; Matsumoto, Kenji; Okuno, Taiji; Domen, Kazuhisa

2005-10-01

To examine the validity and applicability of logarithmic modelling for predicting functional recovery of stroke patients with hemiplegia. Longitudinal postal survey. Stroke patients with hemiplegia staying in a long-term rehabilitation facility, who had been referred from acute medical service 30-60 days after onset. Functional Independence Measure (FIM) scores were periodically assessed during hospitalization. For each individual, a logarithmic formula that was scaled by an interval increase in FIM scores during the initial 2-6 weeks was used for predicting functional recovery. For the study, we recruited 18 patients who showed a wide variety of disability levels on admission (FIM scores 25-107). For each patient, the predicted FIM scores derived from the logarithmic formula matched the actual change in FIM scores. The changes predicted the recovery of motor rather than cognitive functions. Regression analysis showed a close fit between logarithmic modelling and actual FIM scores (across-subject R2 = 0.945). Provided with two initial time-point samplings, logarithmic modelling allows accurate prediction of functional recovery for individuals. Because the modelling is mathematically simple, it can be widely applied in daily clinical practice.

Transition probabilities of health states for workers in Malaysia using a Markov chain model

Science.gov (United States)

Samsuddin, Shamshimah; Ismail, Noriszura

2017-04-01

The aim of our study is to estimate the transition probabilities of health states for workers in Malaysia who contribute to the Employment Injury Scheme under the Social Security Organization Malaysia using the Markov chain model. Our study uses four states of health (active, temporary disability, permanent disability and death) based on the data collected from the longitudinal studies of workers in Malaysia for 5 years. The transition probabilities vary by health state, age and gender. The results show that men employees are more likely to have higher transition probabilities to any health state compared to women employees. The transition probabilities can be used to predict the future health of workers in terms of a function of current age, gender and health state.

Predicting College Students' Positive Psychology Associated Traits with Executive Functioning Dimensions

Science.gov (United States)

Marshall, Seth

2016-01-01

More research is needed that investigates how positive psychology-associated traits are predicted by neurocognitive processes. Correspondingly, the purpose of this study was to ascertain how, and to what extent, four traits, namely, grit, optimism, positive affect, and life satisfaction were predicted by the executive functioning (EF) dimensions…

Phase transitions in single macromolecules: Loop-stretch transition versus loop adsorption transition in end-grafted polymer chains

Science.gov (United States)

Zhang, Shuangshuang; Qi, Shuanhu; Klushin, Leonid I.; Skvortsov, Alexander M.; Yan, Dadong; Schmid, Friederike

2018-01-01

We use Brownian dynamics simulations and analytical theory to compare two prominent types of single molecule transitions. One is the adsorption transition of a loop (a chain with two ends bound to an attractive substrate) driven by an attraction parameter ɛ and the other is the loop-stretch transition in a chain with one end attached to a repulsive substrate, driven by an external end-force F applied to the free end. Specifically, we compare the behavior of the respective order parameters of the transitions, i.e., the mean number of surface contacts in the case of the adsorption transition and the mean position of the chain end in the case of the loop-stretch transition. Close to the transition points, both the static behavior and the dynamic behavior of chains with different length N are very well described by a scaling ansatz with the scaling parameters (ɛ - ɛ*)Nϕ (adsorption transition) and (F - F*)Nν (loop-stretch transition), respectively, where ϕ is the crossover exponent of the adsorption transition and ν is the Flory exponent. We show that both the loop-stretch and the loop adsorption transitions provide an exceptional opportunity to construct explicit analytical expressions for the crossover functions which perfectly describe all simulation results on static properties in the finite-size scaling regime. Explicit crossover functions are based on the ansatz for the analytical form of the order parameter distributions at the respective transition points. In contrast to the close similarity in equilibrium static behavior, the dynamic relaxation at the two transitions shows qualitative differences, especially in the strongly ordered regimes. This is attributed to the fact that the surface contact dynamics in a strongly adsorbed chain is governed by local processes, whereas the end height relaxation of a strongly stretched chain involves the full spectrum of Rouse modes.

Validation of Skeletal Muscle cis-Regulatory Module Predictions Reveals Nucleotide Composition Bias in Functional Enhancers

Science.gov (United States)

Kwon, Andrew T.; Chou, Alice Yi; Arenillas, David J.; Wasserman, Wyeth W.

2011-01-01

We performed a genome-wide scan for muscle-specific cis-regulatory modules (CRMs) using three computational prediction programs. Based on the predictions, 339 candidate CRMs were tested in cell culture with NIH3T3 fibroblasts and C2C12 myoblasts for capacity to direct selective reporter gene expression to differentiated C2C12 myotubes. A subset of 19 CRMs validated as functional in the assay. The rate of predictive success reveals striking limitations of computational regulatory sequence analysis methods for CRM discovery. Motif-based methods performed no better than predictions based only on sequence conservation. Analysis of the properties of the functional sequences relative to inactive sequences identifies nucleotide sequence composition can be an important characteristic to incorporate in future methods for improved predictive specificity. Muscle-related TFBSs predicted within the functional sequences display greater sequence conservation than non-TFBS flanking regions. Comparison with recent MyoD and histone modification ChIP-Seq data supports the validity of the functional regions. PMID:22144875

Validation of skeletal muscle cis-regulatory module predictions reveals nucleotide composition bias in functional enhancers.

Directory of Open Access Journals (Sweden)

Andrew T Kwon

2011-12-01

Full Text Available We performed a genome-wide scan for muscle-specific cis-regulatory modules (CRMs using three computational prediction programs. Based on the predictions, 339 candidate CRMs were tested in cell culture with NIH3T3 fibroblasts and C2C12 myoblasts for capacity to direct selective reporter gene expression to differentiated C2C12 myotubes. A subset of 19 CRMs validated as functional in the assay. The rate of predictive success reveals striking limitations of computational regulatory sequence analysis methods for CRM discovery. Motif-based methods performed no better than predictions based only on sequence conservation. Analysis of the properties of the functional sequences relative to inactive sequences identifies nucleotide sequence composition can be an important characteristic to incorporate in future methods for improved predictive specificity. Muscle-related TFBSs predicted within the functional sequences display greater sequence conservation than non-TFBS flanking regions. Comparison with recent MyoD and histone modification ChIP-Seq data supports the validity of the functional regions.

Models for predicting objective function weights in prostate cancer IMRT

International Nuclear Information System (INIS)

Boutilier, Justin J.; Lee, Taewoo; Craig, Tim; Sharpe, Michael B.; Chan, Timothy C. Y.

2015-01-01

Purpose: To develop and evaluate the clinical applicability of advanced machine learning models that simultaneously predict multiple optimization objective function weights from patient geometry for intensity-modulated radiation therapy of prostate cancer. Methods: A previously developed inverse optimization method was applied retrospectively to determine optimal objective function weights for 315 treated patients. The authors used an overlap volume ratio (OV) of bladder and rectum for different PTV expansions and overlap volume histogram slopes (OVSR and OVSB for the rectum and bladder, respectively) as explanatory variables that quantify patient geometry. Using the optimal weights as ground truth, the authors trained and applied three prediction models: logistic regression (LR), multinomial logistic regression (MLR), and weighted K-nearest neighbor (KNN). The population average of the optimal objective function weights was also calculated. Results: The OV at 0.4 cm and OVSR at 0.1 cm features were found to be the most predictive of the weights. The authors observed comparable performance (i.e., no statistically significant difference) between LR, MLR, and KNN methodologies, with LR appearing to perform the best. All three machine learning models outperformed the population average by a statistically significant amount over a range of clinical metrics including bladder/rectum V53Gy, bladder/rectum V70Gy, and dose to the bladder, rectum, CTV, and PTV. When comparing the weights directly, the LR model predicted bladder and rectum weights that had, on average, a 73% and 74% relative improvement over the population average weights, respectively. The treatment plans resulting from the LR weights had, on average, a rectum V70Gy that was 35% closer to the clinical plan and a bladder V70Gy that was 29% closer, compared to the population average weights. Similar results were observed for all other clinical metrics. Conclusions: The authors demonstrated that the KNN and MLR

Models for predicting objective function weights in prostate cancer IMRT

Energy Technology Data Exchange (ETDEWEB)

Boutilier, Justin J., E-mail: j.boutilier@mail.utoronto.ca; Lee, Taewoo [Department of Mechanical and Industrial Engineering, University of Toronto, 5 King’s College Road, Toronto, Ontario M5S 3G8 (Canada); Craig, Tim [Radiation Medicine Program, UHN Princess Margaret Cancer Centre, 610 University of Avenue, Toronto, Ontario M5T 2M9, Canada and Department of Radiation Oncology, University of Toronto, 148 - 150 College Street, Toronto, Ontario M5S 3S2 (Canada); Sharpe, Michael B. [Radiation Medicine Program, UHN Princess Margaret Cancer Centre, 610 University of Avenue, Toronto, Ontario M5T 2M9 (Canada); Department of Radiation Oncology, University of Toronto, 148 - 150 College Street, Toronto, Ontario M5S 3S2 (Canada); Techna Institute for the Advancement of Technology for Health, 124 - 100 College Street, Toronto, Ontario M5G 1P5 (Canada); Chan, Timothy C. Y. [Department of Mechanical and Industrial Engineering, University of Toronto, 5 King’s College Road, Toronto, Ontario M5S 3G8, Canada and Techna Institute for the Advancement of Technology for Health, 124 - 100 College Street, Toronto, Ontario M5G 1P5 (Canada)

2015-04-15

Purpose: To develop and evaluate the clinical applicability of advanced machine learning models that simultaneously predict multiple optimization objective function weights from patient geometry for intensity-modulated radiation therapy of prostate cancer. Methods: A previously developed inverse optimization method was applied retrospectively to determine optimal objective function weights for 315 treated patients. The authors used an overlap volume ratio (OV) of bladder and rectum for different PTV expansions and overlap volume histogram slopes (OVSR and OVSB for the rectum and bladder, respectively) as explanatory variables that quantify patient geometry. Using the optimal weights as ground truth, the authors trained and applied three prediction models: logistic regression (LR), multinomial logistic regression (MLR), and weighted K-nearest neighbor (KNN). The population average of the optimal objective function weights was also calculated. Results: The OV at 0.4 cm and OVSR at 0.1 cm features were found to be the most predictive of the weights. The authors observed comparable performance (i.e., no statistically significant difference) between LR, MLR, and KNN methodologies, with LR appearing to perform the best. All three machine learning models outperformed the population average by a statistically significant amount over a range of clinical metrics including bladder/rectum V53Gy, bladder/rectum V70Gy, and dose to the bladder, rectum, CTV, and PTV. When comparing the weights directly, the LR model predicted bladder and rectum weights that had, on average, a 73% and 74% relative improvement over the population average weights, respectively. The treatment plans resulting from the LR weights had, on average, a rectum V70Gy that was 35% closer to the clinical plan and a bladder V70Gy that was 29% closer, compared to the population average weights. Similar results were observed for all other clinical metrics. Conclusions: The authors demonstrated that the KNN and MLR

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.

A multiple-field coupled resistive transition model for superconducting Nb3Sn

Directory of Open Access Journals (Sweden)

Lin Yang

2016-12-01

Full Text Available A study on the superconducting transition width as functions of the applied magnetic field and strain is performed in superconducting Nb3Sn. A quantitative, yet universal phenomenological resistivity model is proposed. The numerical simulation by the proposed model shows predicted resistive transition characteristics under variable magnetic fields and strain, which in good agreement with the experimental observations. Furthermore, a temperature-modulated magnetoresistance transition behavior in filamentary Nb3Sn conductors can also be well described by the given model. The multiple-field coupled resistive transition model is helpful for making objective determinations of the high-dimensional critical surface of Nb3Sn in the multi-parameter space, offering some preliminary information about the basic vortex-pinning mechanisms, and guiding the design of the quench protection system of Nb3Sn superconducting magnets.

Rainfall and Extratropical Transition of Tropical Cyclones: Simulation, Prediction, and Projection

Science.gov (United States)

Liu, Maofeng

Rainfall and associated flood hazards are one of the major threats of tropical cyclones (TCs) to coastal and inland regions. The interaction of TCs with extratropical systems can lead to enhanced precipitation over enlarged areas through extratropical transition (ET). To achieve a comprehensive understanding of rainfall and ET associated with TCs, this thesis conducts weather-scale analyses by focusing on individual storms and climate-scale analyses by focusing on seasonal predictability and changing properties of climatology under global warming. The temporal and spatial rainfall evolution of individual storms, including Hurricane Irene (2011), Hurricane Hanna (2008), and Hurricane Sandy (2012), is explored using the Weather Research and Forecast (WRF) model and a variety of hydrometeorological datasets. ET and Orographic mechanism are two key players in the rainfall distribution of Irene over regions experiencing most severe flooding. The change of TC rainfall under global warming is explored with the Forecast-oriented Low Ocean Resolution (FLOR) climate model under representative concentration pathway (RCP) 4.5 scenario. Despite decreased TC frequency, FLOR projects increased landfalling TC rainfall over most regions of eastern United States, highlighting the risk of increased flood hazards. Increased storm rain rate is an important player of increased landfalling TC rainfall. A higher atmospheric resolution version of FLOR (HiFLOR) model projects increased TC rainfall at global scales. The increase of TC intensity and environmental water vapor content scaled by the Clausius-Clapeyron relation are two key factors that explain the projected increase of TC rainfall. Analyses on the simulation, prediction, and projection of the ET activity with FLOR are conducted in the North Atlantic. FLOR model exhibits good skills in simulating many aspects of present-day ET climatology. The 21st-century-projection under RCP4.5 scenario demonstrates the dominant role of ET

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)

Steric effects of CO2 binding to transition metal-benzene complexes: a first-principles study

OpenAIRE

Bae, Hyeonhu; Huang, Bing; Lee, Hoonkyung

2016-01-01

Using density functional theory (DFT) calculations, we investigated the adsorption of CO2 molecules on 3d transition metal (TM)-benzene complexes. Our calculations show that the maximum number of CO2 molecules adsorbable on Sc or Ti atoms is three, but the 18-electron rule predicts it should be four. The 18-electron rule is generally successful in predicting the maximum H2 adsorption number for TM atoms including Sc or Ti atoms. We found that the 18-electron rule fails to correctly predict CO...

Gain-Scheduled Model Predictive Control of Wind Turbines using Laguerre Functions

DEFF Research Database (Denmark)

Adegas, Fabiano Daher; Wisniewski, Rafal; Larsen, Lars Finn Sloth

2014-01-01

This paper presents a systematic approach to design gain-scheduled predictive controllers for wind turbines. The predictive control law is based on Laguerre functions to parameterize control signals and a parameter-dependent cost function that is analytically determined from turbine data....... These properties facilitate the design of speed controllers by placement of the closed-loop poles (when constraints are not active) and systematic adaptation towards changes in the operating point. Vibration control of undamped modes is achieved by imposing a certain degree of stability to the closed-loop system....... The approach can be utilized to the design of new controllers and to represent existing gain-scheduled controllers as predictive controllers. The numerical example and simulations illustrate the design of a speed controller augmented with active damping of the tower fore-aft displacement....

Revisiting the flocking transition using active spins.

Science.gov (United States)

Solon, A P; Tailleur, J

2013-08-16

We consider an active Ising model in which spins both diffuse and align on lattice in one and two dimensions. The diffusion is biased so that plus or minus spins hop preferably to the left or to the right, which generates a flocking transition at low temperature and high density. We construct a coarse-grained description of the model that predicts this transition to be a first-order liquid-gas transition in the temperature-density ensemble, with a critical density sent to infinity. In this first-order phase transition, the magnetization is proportional to the liquid fraction and thus varies continuously throughout the phase diagram. Using microscopic simulations, we show that this theoretical prediction holds in 2D whereas the fluctuations alter the transition in 1D, preventing, for instance, any spontaneous symmetry breaking.

Gene-specific function prediction for non-synonymous mutations in monogenic diabetes genes.

Directory of Open Access Journals (Sweden)

Quan Li

Full Text Available The rapid progress of genomic technologies has been providing new opportunities to address the need of maturity-onset diabetes of the young (MODY molecular diagnosis. However, whether a new mutation causes MODY can be questionable. A number of in silico methods have been developed to predict functional effects of rare human mutations. The purpose of this study is to compare the performance of different bioinformatics methods in the functional prediction of nonsynonymous mutations in each MODY gene, and provides reference matrices to assist the molecular diagnosis of MODY. Our study showed that the prediction scores by different methods of the diabetes mutations were highly correlated, but were more complimentary than replacement to each other. The available in silico methods for the prediction of diabetes mutations had varied performances across different genes. Applying gene-specific thresholds defined by this study may be able to increase the performance of in silico prediction of disease-causing mutations.

Numerical study of the glass-glass transition in short-ranged attractive colloids

International Nuclear Information System (INIS)

Zaccarelli, Emanuela; Sciortino, Francesco; Tartaglia, Piero

2004-01-01

We report extensive numerical simulations in the glass region for a simple model of short-ranged attractive colloids, the square well model. We investigate the behaviour of the density autocorrelation function and of the static structure factor in the region of temperatures and packing fractions where a glass-glass transition is expected according to theoretical predictions. We strengthen our observations by studying both waiting time and history dependence of the numerical results. We provide evidence supporting the possibility that activated bond-breaking processes destabilize the attractive glass, preventing the full observation of a sharp glass-glass kinetic transition

An integrative approach to ortholog prediction for disease-focused and other functional studies.

Science.gov (United States)

Hu, Yanhui; Flockhart, Ian; Vinayagam, Arunachalam; Bergwitz, Clemens; Berger, Bonnie; Perrimon, Norbert; Mohr, Stephanie E

2011-08-31

Mapping of orthologous genes among species serves an important role in functional genomics by allowing researchers to develop hypotheses about gene function in one species based on what is known about the functions of orthologs in other species. Several tools for predicting orthologous gene relationships are available. However, these tools can give different results and identification of predicted orthologs is not always straightforward. We report a simple but effective tool, the Drosophila RNAi Screening Center Integrative Ortholog Prediction Tool (DIOPT; http://www.flyrnai.org/diopt), for rapid identification of orthologs. DIOPT integrates existing approaches, facilitating rapid identification of orthologs among human, mouse, zebrafish, C. elegans, Drosophila, and S. cerevisiae. As compared to individual tools, DIOPT shows increased sensitivity with only a modest decrease in specificity. Moreover, the flexibility built into the DIOPT graphical user interface allows researchers with different goals to appropriately 'cast a wide net' or limit results to highest confidence predictions. DIOPT also displays protein and domain alignments, including percent amino acid identity, for predicted ortholog pairs. This helps users identify the most appropriate matches among multiple possible orthologs. To facilitate using model organisms for functional analysis of human disease-associated genes, we used DIOPT to predict high-confidence orthologs of disease genes in Online Mendelian Inheritance in Man (OMIM) and genes in genome-wide association study (GWAS) data sets. The results are accessible through the DIOPT diseases and traits query tool (DIOPT-DIST; http://www.flyrnai.org/diopt-dist). DIOPT and DIOPT-DIST are useful resources for researchers working with model organisms, especially those who are interested in exploiting model organisms such as Drosophila to study the functions of human disease genes.

Density-functional theory for fluid-solid and solid-solid phase transitions.

Science.gov (United States)

Bharadwaj, Atul S; Singh, Yashwant

2017-03-01

We develop a theory to describe solid-solid phase transitions. The density functional formalism of classical statistical mechanics is used to find an exact expression for the difference in the grand thermodynamic potentials of the two coexisting phases. The expression involves both the symmetry conserving and the symmetry broken parts of the direct pair correlation function. The theory is used to calculate phase diagram of systems of soft spheres interacting via inverse power potentials u(r)=ε(σ/r)^{n}, where parameter n measures softness of the potential. We find that for 1/nfcc) structure while for 1/n≥0.154 the body-centred-cubic (bcc) structure is preferred. The bcc structure transforms into the fcc structure upon increasing the density. The calculated phase diagram is in good agreement with the one found from molecular simulations.

Catalase degradation in sunflower cotyledons during peroxisome transition from glyoxysomal to leaf peroxisomal function

International Nuclear Information System (INIS)

Eising, R.; Gerhardt, B.

1987-01-01

First order rate constant for the degradation (degradation constants) of catalase in the cotyledons of sunflower (Helianthus annuus L.) were determined by measuring the loss of catalase containing 14 C-labeled heme. During greening of the cotyledons, a period when peroxisomes change from glyoxysomal to leaf peroxisomal function, the degradation of glyoxysomal catalase is significantly slower than during all other stages of cotyledon development in light or darkness. The degradation constant during the transition stage of peroxisome function amounts to 0.205 day -1 in contrast to the constants ranging from 0.304 day -1 to 0.515 day -1 during the other developmental stages. Density labeling experiments comprising labeling of catalase with 2 H 2 O and its isopycnic centrifugation on CsCl gradients demonstrated that the determinations of the degradation constants were not substantially affected by reutilization of 14 C-labeled compounds for catalase synthesis. The degradation constants for both glyoxysomal catalase and catalase synthesized during the transition of peroxisome function do not differ. This was shown by labeling the catalases with different isotopes and measuring the isotope ratio during the development of the cotyledons. The results are inconsistent with the concept that an accelerated and selective degradation of glyoxysomes underlies the change in peroxisome function. The data suggest that catalase degradation is at least partially due to an individual turnover of catalase and does not only result from a turnover of the whole peroxisomes

Correlation between Colon Transit Time Test Value and Initial Maintenance Dose of Laxative in Children with Chronic Functional Constipation

Science.gov (United States)

Kim, Mock Ryeon; Park, Hye Won; Son, Jae Sung; Lee, Ran

2016-01-01

Purpose To evaluate the correlation between colon transit time (CTT) test value and initial maintenance dose of polyethylene glycol (PEG) 4000 or lactulose. Methods Of 415 children with chronic functional constipation, 190 were enrolled based on exclusion criteria using the CTT test, defecation diary, and clinical chart. The CTT test was performed with prior disimpaction. The laxative dose for maintenance was determined on the basis of the defecation diary and clinical chart. The Shapiro-Wilk test and Pearson's and Spearman's correlations were used for statistical analysis. Results The overall group median value and interquartile range of the CTT test was 43.8 (31.8) hours. The average PEG 4000 dose for maintenance in the overall group was 0.68±0.18 g/kg/d; according to age, the dose was 0.73±0.16 g/kg/d (encopresis, abnormal CTT test subtype) for either laxative. Even in the largest group (overall, n=109, younger than 8 years and on PEG 4000), the correlation was weak (Pearson's correlation coefficient [R]=0.268, p=0.005). Within the abnormal transit group, subgroup (n=73, younger than 8 years and on PEG 4000) correlation was weak (R=0.267, p=0.022). Conclusion CTT test value cannot predict the initial maintenance dose of PEG 4000 or lactulose with linear correlation. PMID:27738600

Application of Functional Link Artificial Neural Network for Prediction of Machinery Noise in Opencast Mines

Directory of Open Access Journals (Sweden)

Santosh Kumar Nanda

2011-01-01

Full Text Available Functional link-based neural network models were applied to predict opencast mining machineries noise. The paper analyzes the prediction capabilities of functional link neural network based noise prediction models vis-à-vis existing statistical models. In order to find the actual noise status in opencast mines, some of the popular noise prediction models, for example, ISO-9613-2, CONCAWE, VDI, and ENM, have been applied in mining and allied industries to predict the machineries noise by considering various attenuation factors. Functional link artificial neural network (FLANN, polynomial perceptron network (PPN, and Legendre neural network (LeNN were used to predict the machinery noise in opencast mines. The case study is based on data collected from an opencast coal mine of Orissa, India. From the present investigations, it could be concluded that the FLANN model give better noise prediction than the PPN and LeNN model.

School belongingness and mental health functioning across the primary-secondary transition in a mainstream sample: multi-group cross-lagged analyses.

Science.gov (United States)

Vaz, Sharmila; Falkmer, Marita; Parsons, Richard; Passmore, Anne Elizabeth; Parkin, Timothy; Falkmer, Torbjörn

2014-01-01

The relationship between school belongingness and mental health functioning before and after the primary-secondary school transition has not been previously investigated in students with and without disabilities. This study used a prospective longitudinal design to test the bi-directional relationships between these constructs, by surveying 266 students with and without disabilities and their parents, 6-months before and after the transition to secondary school. Cross-lagged multi-group analyses found student perception of belongingness in the final year of primary school to contribute to change in their mental health functioning a year later. The beneficial longitudinal effects of school belongingness on subsequent mental health functioning were evident in all student subgroups; even after accounting for prior mental health scores and the cross-time stability in mental health functioning and school belongingness scores. Findings of the current study substantiate the role of school contextual influences on early adolescent mental health functioning. They highlight the importance for primary and secondary schools to assess students' school belongingness and mental health functioning and transfer these records as part of the transition process, so that appropriate scaffolds are in place to support those in need. Longer term longitudinal studies are needed to increase the understanding of the temporal sequencing between school belongingness and mental health functioning of all mainstream students.

School Belongingness and Mental Health Functioning across the Primary-Secondary Transition in a Mainstream Sample: Multi-Group Cross-Lagged Analyses

Science.gov (United States)

Vaz, Sharmila; Falkmer, Marita; Parsons, Richard; Passmore, Anne Elizabeth; Parkin, Timothy; Falkmer, Torbjörn

2014-01-01

The relationship between school belongingness and mental health functioning before and after the primary-secondary school transition has not been previously investigated in students with and without disabilities. This study used a prospective longitudinal design to test the bi-directional relationships between these constructs, by surveying 266 students with and without disabilities and their parents, 6-months before and after the transition to secondary school. Cross-lagged multi-group analyses found student perception of belongingness in the final year of primary school to contribute to change in their mental health functioning a year later. The beneficial longitudinal effects of school belongingness on subsequent mental health functioning were evident in all student subgroups; even after accounting for prior mental health scores and the cross-time stability in mental health functioning and school belongingness scores. Findings of the current study substantiate the role of school contextual influences on early adolescent mental health functioning. They highlight the importance for primary and secondary schools to assess students’ school belongingness and mental health functioning and transfer these records as part of the transition process, so that appropriate scaffolds are in place to support those in need. Longer term longitudinal studies are needed to increase the understanding of the temporal sequencing between school belongingness and mental health functioning of all mainstream students. PMID:24967580

School belongingness and mental health functioning across the primary-secondary transition in a mainstream sample: multi-group cross-lagged analyses.

Directory of Open Access Journals (Sweden)

Sharmila Vaz

Full Text Available The relationship between school belongingness and mental health functioning before and after the primary-secondary school transition has not been previously investigated in students with and without disabilities. This study used a prospective longitudinal design to test the bi-directional relationships between these constructs, by surveying 266 students with and without disabilities and their parents, 6-months before and after the transition to secondary school. Cross-lagged multi-group analyses found student perception of belongingness in the final year of primary school to contribute to change in their mental health functioning a year later. The beneficial longitudinal effects of school belongingness on subsequent mental health functioning were evident in all student subgroups; even after accounting for prior mental health scores and the cross-time stability in mental health functioning and school belongingness scores. Findings of the current study substantiate the role of school contextual influences on early adolescent mental health functioning. They highlight the importance for primary and secondary schools to assess students' school belongingness and mental health functioning and transfer these records as part of the transition process, so that appropriate scaffolds are in place to support those in need. Longer term longitudinal studies are needed to increase the understanding of the temporal sequencing between school belongingness and mental health functioning of all mainstream students.

Changes in cognitive functions of students in the transitional period from elementary school to junior high school.

Science.gov (United States)

Mizuno, Kei; Tanaka, Masaaki; Fukuda, Sanae; Sasabe, Tetsuya; Imai-Matsumura, Kyoko; Watanabe, Yasuyoshi

2011-05-01

When students proceed to junior high school from elementary school, rapid changes in the environment occur, which may cause various behavioral and emotional problems. However, the changes in cognitive functions during this transitional period have rarely been studied. In 158 elementary school students from 4th- to 6th-grades and 159 junior high school students from 7th- to 9th-grades, we assessed various cognitive functions, including motor processing, spatial construction ability, semantic fluency, immediate memory, delayed memory, spatial and non-spatial working memory, and selective, alternative, and divided attention. Our findings showed that performance on spatial and non-spatial working memory, alternative attention, divided attention, and semantic fluency tasks improved from elementary to junior high school. In particular, performance on alternative and divided attention tasks improved during the transitional period from elementary to junior high school. Our finding suggests that development of alternative and divided attention is of crucial importance in the transitional period from elementary to junior high school. Copyright © 2010 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.

Computation of piecewise affine terminal cost functions for model predictive control

NARCIS (Netherlands)

Brunner, F.D.; Lazar, M.; Allgöwer, F.; Fränzle, Martin; Lygeros, John

2014-01-01

This paper proposes a method for the construction of piecewise affine terminal cost functions for model predictive control (MPC). The terminal cost function is constructed on a predefined partition by solving a linear program for a given piecewise affine system, a stabilizing piecewise affine

DeepGO: predicting protein functions from sequence and interactions using a deep ontology-aware classifier

KAUST Repository

Kulmanov, Maxat

2017-09-27

Motivation A large number of protein sequences are becoming available through the application of novel high-throughput sequencing technologies. Experimental functional characterization of these proteins is time-consuming and expensive, and is often only done rigorously for few selected model organisms. Computational function prediction approaches have been suggested to fill this gap. The functions of proteins are classified using the Gene Ontology (GO), which contains over 40 000 classes. Additionally, proteins have multiple functions, making function prediction a large-scale, multi-class, multi-label problem. Results We have developed a novel method to predict protein function from sequence. We use deep learning to learn features from protein sequences as well as a cross-species protein–protein interaction network. Our approach specifically outputs information in the structure of the GO and utilizes the dependencies between GO classes as background information to construct a deep learning model. We evaluate our method using the standards established by the Computational Assessment of Function Annotation (CAFA) and demonstrate a significant improvement over baseline methods such as BLAST, in particular for predicting cellular locations.

A large-scale evaluation of computational protein function prediction

NARCIS (Netherlands)

Radivojac, P.; Clark, W.T.; Oron, T.R.; Schnoes, A.M.; Wittkop, T.; Kourmpetis, Y.A.I.; Dijk, van A.D.J.; Friedberg, I.

2013-01-01

Automated annotation of protein function is challenging. As the number of sequenced genomes rapidly grows, the overwhelming majority of protein products can only be annotated computationally. If computational predictions are to be relied upon, it is crucial that the accuracy of these methods be

Density functional theory studies of transition metal nanoparticles in catalysis

DEFF Research Database (Denmark)

Greeley, Jeffrey Philip; Rankin, Rees; Zeng, Zhenhua

2013-01-01

Periodic Density Functional Theory calculations are capable of providing powerful insights into the structural, energetics, and electronic phenomena that underlie heterogeneous catalysis on transition metal nanoparticles. Such calculations are now routinely applied to single crystal metal surfaces...... and to subnanometer metal clusters. Descriptions of catalysis on truly nanosized structures, however, are generally not as well developed. In this talk, I will illustrate different approaches to analyzing nanocatalytic phenomena with DFT calculations. I will describe case studies from heterogeneous catalysis...... and electrocatalysis, in which single crystal models are combined with Wulff construction-based ideas to produce descriptions of average nanocatalyst behavior. Then, I will proceed to describe explicitly DFT-based descriptions of catalysis on truly nanosized particles (

Study of the phase transition dynamics of the L to H transition

International Nuclear Information System (INIS)

Moyer, R.A.; Rhodes, T.L.; Rettig, C.L.

1997-12-01

A highly radiating zone (MARFE) just above the divertor X-point has been used to access the marginal transition regime P sep ∼ P thres to study the existence of a critical point for the L to H transition. Phase transition models predict that at the critical point, the transition duration increases and the plasma parameters vary continuously between L-mode and H-mode. In these experiments, the L to H transition duration increased 50--100 times over fast transitions. However, the evolution of E r shear, edge density gradient, H-mode pedestal, and fluctuations is essentially unchanged from that in fast transitions. The only difference is in the speed with which and the degree to which the fluctuation amplitudes are transiently reduced. This difference is understandable in terms of the time scales for fluctuation amplitude reduction (≤ 100 micros) and edge pressure gradient increase (several ms), provided the edge fluctuations are pressure-gradient driven

Analytical expressions for transition edge sensor excess noise models

International Nuclear Information System (INIS)

Brandt, Daniel; Fraser, George W.

2010-01-01

Transition edge sensors (TESs) are high-sensitivity thermometers used in cryogenic microcalorimeters which exploit the steep gradient in resistivity with temperature during the superconducting phase transition. Practical TES devices tend to exhibit a white noise of uncertain origin, arising inside the device. We discuss two candidate models for this excess noise, phase slip shot noise (PSSN) and percolation noise. We extend the existing PSSN model to include a magnetic field dependence and derive a basic analytical model for percolation noise. We compare the predicted functional forms of the noise current vs. resistivity curves of both models with experimental data and provide a set of equations for both models to facilitate future experimental efforts to clearly identify the source of excess noise.

Modeling of the heat transfer in bypass transitional boundary-layer flows

Science.gov (United States)

Simon, Frederick F.; Stephens, Craig A.

1991-01-01

A low Reynolds number k-epsilon turbulence model and conditioned momentum, energy and turbulence equations were used to predict bypass transition heat transfer on a flat plate in a high-disturbance environment with zero pressure gradient. The use of conditioned equations was demonstrated to be an improvement over the use of the global-time-averaged equations for the calculation of velocity profiles and turbulence intensity profiles in the transition region of a boundary layer. The approach of conditioned equations is extended to include heat transfer and a modeling of transition events is used to predict transition onset and the extent of transition on a flat plate. The events, which describe the boundary layer at the leading edge, result in boundary-layer regions consisting of: (1) the laminar, (2) pseudolaminar, (3) transitional, and (4) turbulent boundary layers. The modeled transition events were incorporated into the TEXSTAN 2-D boundary-layer code which is used to numerically predict the heat transfer. The numerical predictions in general compared well with the experimental data and revealed areas where additional experimental information is needed.

Self-reported Physical Activity Predicts Pain Inhibitory and Facilitatory Function

Science.gov (United States)

Naugle, Kelly M.; Riley, Joseph L.

2013-01-01

Considerable evidence suggests regular physical activity can reduce chronic pain symptoms. Dysfunction of endogenous facilitatory and inhibitory systems has been implicated in multiple chronic pain conditions. However, few studies have investigated the relationship between levels of physical activity and descending pain modulatory function. Purpose This study’s purpose was to determine whether self-reported levels of physical activity in healthy adults predicted 1) pain sensitivity to heat and cold stimuli, 2) pain facilitatory function as tested by temporal summation of pain (TS), and 3) pain inhibitory function as tested by conditioned pain modulation (CPM) and offset analgesia. Methods Forty-eight healthy adults (age range 18–76) completed the International Physical Activity Questionnaire (IPAQ) and the following pain tests: heat pain thresholds (HPT), heat pain suprathresholds, cold pressor pain (CPP), temporal summation of heat pain, conditioned pain modulation, and offset analgesia. The IPAQ measured levels of walking, moderate, vigorous and total physical activity over the past seven days. Hierarchical linear regressions were conducted to determine the relationship between each pain test and self-reported levels of physical activity, while controlling for age, sex and psychological variables. Results Self-reported total and vigorous physical activity predicted TS and CPM (p’s pain and greater CPM. The IPAQ measures did not predict any of the other pain measures. Conclusion Thus, these results suggest that healthy older and younger adults who self-report greater levels of vigorous and total physical activity exhibit enhanced descending pain modulatory function. Improved descending pain modulation may be a mechanism through which exercise reduces or prevents chronic pain symptoms. PMID:23899890

Predicting Nanocrystal Shape through Consideration of Surface-Ligand Interactions

KAUST Repository

Bealing, Clive R.

2012-03-27

Density functional calculations for the binding energy of oleic acid-based ligands on Pb-rich {100} and {111} facets of PbSe nanocrystals determine the surface energies as a function of ligand coverage. Oleic acid is expected to bind to the nanocrystal surface in the form of lead oleate. The Wulff construction predicts the thermodynamic equilibrium shape of the PbSe nanocrystals. The equilibrium shape is a function of the ligand surface coverage, which can be controlled by changing the concentration of oleic acid during synthesis. The different binding energy of the ligand on the {100} and {111} facets results in different equilibrium ligand coverages on the facets, and a transition in the equilibrium shape from octahedral to cubic is predicted when increasing the ligand concentration during synthesis. © 2012 American Chemical Society.

Cardiac structure and function predicts functional decline in the oldest old.

Science.gov (United States)

Leibowitz, David; Jacobs, Jeremy M; Lande-Stessman, Irit; Gilon, Dan; Stessman, Jochanan

2018-02-01

Background This study examined the association between cardiac structure and function and the deterioration in activities of daily living (ADLs) in an age-homogenous, community-dwelling population of patients born in 1920-1921 over a five-year follow-up period. Design Longitudinal cohort study. Methods Patients were recruited from the Jerusalem Longitudinal Cohort Study, which has followed an age-homogenous cohort of Jerusalem residents born in 1920-1921. Patients underwent home echocardiography and were followed up for five years. Dependence was defined as needing assistance with one or more basic ADL. Standard echocardiographic assessment of cardiac structure and function, including systolic and diastolic function, was performed. Reassessment of ADLs was performed at the five-year follow-up. Results A total of 459 patients were included in the study. Of these, 362 (79%) showed a deterioration in at least one ADL at follow-up. Patients with functional deterioration had a significantly higher left ventricular mass index and left atrial volume with a lower ejection fraction. There was no significant difference between the diastolic parameters the groups in examined. When the data were examined categorically, a significantly larger percentage of patients with functional decline had an abnormal left ventricular ejection fraction and left ventricular hypertrophy. The association between left ventricular mass index and functional decline remained significant in all multivariate models. Conclusions In this cohort of the oldest old, an elevated left ventricular mass index, higher left atrial volumes and systolic, but not diastolic dysfunction, were predictive of functional disability.

An integrative approach to ortholog prediction for disease-focused and other functional studies

Directory of Open Access Journals (Sweden)

Perrimon Norbert

2011-08-01

Full Text Available Abstract Background Mapping of orthologous genes among species serves an important role in functional genomics by allowing researchers to develop hypotheses about gene function in one species based on what is known about the functions of orthologs in other species. Several tools for predicting orthologous gene relationships are available. However, these tools can give different results and identification of predicted orthologs is not always straightforward. Results We report a simple but effective tool, the Drosophila RNAi Screening Center Integrative Ortholog Prediction Tool (DIOPT; http://www.flyrnai.org/diopt, for rapid identification of orthologs. DIOPT integrates existing approaches, facilitating rapid identification of orthologs among human, mouse, zebrafish, C. elegans, Drosophila, and S. cerevisiae. As compared to individual tools, DIOPT shows increased sensitivity with only a modest decrease in specificity. Moreover, the flexibility built into the DIOPT graphical user interface allows researchers with different goals to appropriately 'cast a wide net' or limit results to highest confidence predictions. DIOPT also displays protein and domain alignments, including percent amino acid identity, for predicted ortholog pairs. This helps users identify the most appropriate matches among multiple possible orthologs. To facilitate using model organisms for functional analysis of human disease-associated genes, we used DIOPT to predict high-confidence orthologs of disease genes in Online Mendelian Inheritance in Man (OMIM and genes in genome-wide association study (GWAS data sets. The results are accessible through the DIOPT diseases and traits query tool (DIOPT-DIST; http://www.flyrnai.org/diopt-dist. Conclusions DIOPT and DIOPT-DIST are useful resources for researchers working with model organisms, especially those who are interested in exploiting model organisms such as Drosophila to study the functions of human disease genes.

Evaluating a variety of text-mined features for automatic protein function prediction with GOstruct.

Science.gov (United States)

Funk, Christopher S; Kahanda, Indika; Ben-Hur, Asa; Verspoor, Karin M

2015-01-01

Most computational methods that predict protein function do not take advantage of the large amount of information contained in the biomedical literature. In this work we evaluate both ontology term co-mention and bag-of-words features mined from the biomedical literature and analyze their impact in the context of a structured output support vector machine model, GOstruct. We find that even simple literature based features are useful for predicting human protein function (F-max: Molecular Function =0.408, Biological Process =0.461, Cellular Component =0.608). One advantage of using literature features is their ability to offer easy verification of automated predictions. We find through manual inspection of misclassifications that some false positive predictions could be biologically valid predictions based upon support extracted from the literature. Additionally, we present a "medium-throughput" pipeline that was used to annotate a large subset of co-mentions; we suggest that this strategy could help to speed up the rate at which proteins are curated.

Study of the hard-disk system at high densities: the fluid-hexatic phase transition.

Science.gov (United States)

Mier-Y-Terán, Luis; Machorro-Martínez, Brian Ignacio; Chapela, Gustavo A; Del Río, Fernando

2018-06-21

Integral equations of uniform fluids have been considered unable to predict any characteristic feature of the fluid-solid phase transition, including the shoulder that arises in the second peak of the fluid-phase radial distribution function, RDF, of hard-core systems obtained by computer simulations, at fluid densities very close to the structural two-step phase transition. This reasoning is based on the results of traditional integral approximations, like Percus-Yevick, PY, which does not show such a shoulder in hard-core systems, neither in two nor three dimensions. In this work, we present results of three Ansätze, based on the PY theory, that were proposed to remedy the lack of PY analytical solutions in two dimensions. This comparative study shows that one of those Ansätze does develop a shoulder in the second peak of the RDF at densities very close to the phase transition, qualitatively describing this feature. Since the shoulder grows into a peak at still higher densities, this integral equation approach predicts the appearance of an orientational order characteristic of the hexatic phase in a continuous fluid-hexatic phase transition.

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.

The protection motivation theory within the stages of the transtheoretical model - stage-specific interplay of variables and prediction of exercise stage transitions.

Science.gov (United States)

Lippke, Sonia; Plotnikoff, Ronald C

2009-05-01

Two different theories of health behaviour have been chosen with the aim of theory integration: a continuous theory (protection motivation theory, PMT) and a stage model (transtheoretical model, TTM). This is the first study to test whether the stages of the TTM moderate the interrelation of PMT-variables and the mediation of motivation, as well as PMT-variables' interactions in predicting stage transitions. Hypotheses were tested regarding (1) mean patterns, stage pair-comparisons and nonlinear trends using ANOVAs; (2) prediction-patterns for the different stage groups employing multi-group structural equation modelling (MSEM) and nested model analyses; and (3) stage transitions using binary logistic regression analyses. Adults (N=1,602) were assessed over a 6 month period on their physical activity stages, PMT-variables and subsequent behaviour. (1) Particular mean differences and nonlinear trends in all test variables were found. (2) The PMT adequately fitted the five stage groups. The MSEM revealed that covariances within threat appraisal and coping appraisal were invariant and all other constrains were stage-specific, i.e. stage was a moderator. Except for self-efficacy, motivation fully mediated the relationship between the social-cognitive variables and behaviour. (3) Predicting stage transitions with the PMT-variables underscored the importance of self-efficacy. Only when threat appraisal and coping appraisal were high, stage movement was more likely in the preparation stage. Results emphasize stage-specific differences of the PMT mechanisms, and hence, support the stage construct. The findings may guide further theory building and research integrating different theoretical approaches.

Modelling and prediction for chaotic fir laser attractor using rational function neural network.

Science.gov (United States)

Cho, S

2001-02-01

Many real-world systems such as irregular ECG signal, volatility of currency exchange rate and heated fluid reaction exhibit highly complex nonlinear characteristic known as chaos. These chaotic systems cannot be retreated satisfactorily using linear system theory due to its high dimensionality and irregularity. This research focuses on prediction and modelling of chaotic FIR (Far InfraRed) laser system for which the underlying equations are not given. This paper proposed a method for prediction and modelling a chaotic FIR laser time series using rational function neural network. Three network architectures, TDNN (Time Delayed Neural Network), RBF (radial basis function) network and the RF (rational function) network, are also presented. Comparisons between these networks performance show the improvements introduced by the RF network in terms of a decrement in network complexity and better ability of predictability.

Modified Displacement Transfer Functions for Deformed Shape Predictions of Slender Curved Structures with Varying Curvatives

Science.gov (United States)

Ko, William L.; Fleischer, Van Tran

2014-01-01

To eliminate the need to use finite-element modeling for structure shape predictions, a new method was invented. This method is to use the Displacement Transfer Functions to transform the measured surface strains into deflections for mapping out overall structural deformed shapes. The Displacement Transfer Functions are expressed in terms of rectilinearly distributed surface strains, and contain no material properties. This report is to apply the patented method to the shape predictions of non-symmetrically loaded slender curved structures with different curvatures up to a full circle. Because the measured surface strains are not available, finite-element analysis had to be used to analytically generate the surface strains. Previously formulated straight-beam Displacement Transfer Functions were modified by introducing the curvature-effect correction terms. Through single-point or dual-point collocations with finite-elementgenerated deflection curves, functional forms of the curvature-effect correction terms were empirically established. The resulting modified Displacement Transfer Functions can then provide quite accurate shape predictions. Also, the uniform straight-beam Displacement Transfer Function was applied to the shape predictions of a section-cut of a generic capsule (GC) outer curved sandwich wall. The resulting GC shape predictions are quite accurate in partial regions where the radius of curvature does not change sharply.

Experimental-confirmation and functional-annotation of predicted proteins in the chicken genome

Directory of Open Access Journals (Sweden)

McCarthy Fiona M

2007-11-01

Full Text Available Abstract Background The chicken genome was sequenced because of its phylogenetic position as a non-mammalian vertebrate, its use as a biomedical model especially to study embryology and development, its role as a source of human disease organisms and its importance as the major source of animal derived food protein. However, genomic sequence data is, in itself, of limited value; generally it is not equivalent to understanding biological function. The benefit of having a genome sequence is that it provides a basis for functional genomics. However, the sequence data currently available is poorly structurally and functionally annotated and many genes do not have standard nomenclature assigned. Results We analysed eight chicken tissues and improved the chicken genome structural annotation by providing experimental support for the in vivo expression of 7,809 computationally predicted proteins, including 30 chicken proteins that were only electronically predicted or hypothetical translations in human. To improve functional annotation (based on Gene Ontology, we mapped these identified proteins to their human and mouse orthologs and used this orthology to transfer Gene Ontology (GO functional annotations to the chicken proteins. The 8,213 orthology-based GO annotations that we produced represent an 8% increase in currently available chicken GO annotations. Orthologous chicken products were also assigned standardized nomenclature based on current chicken nomenclature guidelines. Conclusion We demonstrate the utility of high-throughput expression proteomics for rapid experimental structural annotation of a newly sequenced eukaryote genome. These experimentally-supported predicted proteins were further annotated by assigning the proteins with standardized nomenclature and functional annotation. This method is widely applicable to a diverse range of species. Moreover, information from one genome can be used to improve the annotation of other genomes and

Theory of quantum metal to superconductor transitions in highly conducting systems

Energy Technology Data Exchange (ETDEWEB)

Spivak, B.

2010-04-06

We derive the theory of the quantum (zero temperature) superconductor to metal transition in disordered materials when the resistance of the normal metal near criticality is small compared to the quantum of resistivity. This can occur most readily in situations in which 'Anderson's theorem' does not apply. We explicitly study the transition in superconductor-metal composites, in an swave superconducting film in the presence of a magnetic field, and in a low temperature disordered d-wave superconductor. Near the point of the transition, the distribution of the superconducting order parameter is highly inhomogeneous. To describe this situation we employ a procedure which is similar to that introduced by Mott for description of the temperature dependence of the variable range hopping conduction. As the system approaches the point of the transition from the metal to the superconductor, the conductivity of the system diverges, and the Wiedemann-Franz law is violated. In the case of d-wave (or other exotic) superconductors we predict the existence of (at least) two sequential transitions as a function of increasing disorder: a d-wave to s-wave, and then an s-wave to metal transition.

Predictive modelling of grain size distributions from marine electromagnetic profiling data using end-member analysis and a radial basis function network

Science.gov (United States)

Baasch, B.; M"uller, H.; von Dobeneck, T.

2018-04-01

In this work we present a new methodology to predict grain-size distributions from geophysical data. Specifically, electric conductivity and magnetic susceptibility of seafloor sediments recovered from electromagnetic profiling data are used to predict grain-size distributions along shelf-wide survey lines. Field data from the NW Iberian shelf are investigated and reveal a strong relation between the electromagnetic properties and grain-size distribution. The here presented workflow combines unsupervised and supervised machine learning techniques. Nonnegative matrix factorisation is used to determine grain-size end-members from sediment surface samples. Four end-members were found which well represent the variety of sediments in the study area. A radial-basis function network modified for prediction of compositional data is then used to estimate the abundances of these end-members from the electromagnetic properties. The end-members together with their predicted abundances are finally back transformed to grain-size distributions. A minimum spatial variation constraint is implemented in the training of the network to avoid overfitting and to respect the spatial distribution of sediment patterns. The predicted models are tested via leave-one-out cross-validation revealing high prediction accuracy with coefficients of determination (R2) between 0.76 and 0.89. The predicted grain-size distributions represent the well-known sediment facies and patterns on the NW Iberian shelf and provide new insights into their distribution, transition and dynamics. This study suggests that electromagnetic benthic profiling in combination with machine learning techniques is a powerful tool to estimate grain-size distribution of marine sediments.

An Overview of Practical Applications of Protein Disorder Prediction and Drive for Faster, More Accurate Predictions.

Science.gov (United States)

Deng, Xin; Gumm, Jordan; Karki, Suman; Eickholt, Jesse; Cheng, Jianlin

2015-07-07

Protein disordered regions are segments of a protein chain that do not adopt a stable structure. Thus far, a variety of protein disorder prediction methods have been developed and have been widely used, not only in traditional bioinformatics domains, including protein structure prediction, protein structure determination and function annotation, but also in many other biomedical fields. The relationship between intrinsically-disordered proteins and some human diseases has played a significant role in disorder prediction in disease identification and epidemiological investigations. Disordered proteins can also serve as potential targets for drug discovery with an emphasis on the disordered-to-ordered transition in the disordered binding regions, and this has led to substantial research in drug discovery or design based on protein disordered region prediction. Furthermore, protein disorder prediction has also been applied to healthcare by predicting the disease risk of mutations in patients and studying the mechanistic basis of diseases. As the applications of disorder prediction increase, so too does the need to make quick and accurate predictions. To fill this need, we also present a new approach to predict protein residue disorder using wide sequence windows that is applicable on the genomic scale.

An Overview of Practical Applications of Protein Disorder Prediction and Drive for Faster, More Accurate Predictions

Directory of Open Access Journals (Sweden)

Xin Deng

2015-07-01

Full Text Available Protein disordered regions are segments of a protein chain that do not adopt a stable structure. Thus far, a variety of protein disorder prediction methods have been developed and have been widely used, not only in traditional bioinformatics domains, including protein structure prediction, protein structure determination and function annotation, but also in many other biomedical fields. The relationship between intrinsically-disordered proteins and some human diseases has played a significant role in disorder prediction in disease identification and epidemiological investigations. Disordered proteins can also serve as potential targets for drug discovery with an emphasis on the disordered-to-ordered transition in the disordered binding regions, and this has led to substantial research in drug discovery or design based on protein disordered region prediction. Furthermore, protein disorder prediction has also been applied to healthcare by predicting the disease risk of mutations in patients and studying the mechanistic basis of diseases. As the applications of disorder prediction increase, so too does the need to make quick and accurate predictions. To fill this need, we also present a new approach to predict protein residue disorder using wide sequence windows that is applicable on the genomic scale.

Cognitive function predicts 24-month weight loss success after bariatric surgery.

Science.gov (United States)

Spitznagel, Mary Beth; Alosco, Michael; Strain, Gladys; Devlin, Michael; Cohen, Ronald; Paul, Robert; Crosby, Ross D; Mitchell, James E; Gunstad, John

2013-01-01

Clinically significant cognitive impairment, particularly in attention/executive and memory function, is found in many patients undergoing bariatric surgery. These difficulties have previously been linked to decreased weight loss 12 months after surgery, but more protracted examination of this relationship has not yet been conducted. The present study prospectively examined the independent contribution of cognitive function to weight loss 24 months after bariatric surgery. Given the rapid rate of cognitive improvement observed after surgery, postoperative cognitive function (i.e., cognition 12 weeks after surgery, controlling for baseline cognition) was expected to predict lower body mass index (BMI) and higher percent total weight loss (%WL) at 24-month follow-up. Data were collected by 3 sites of the Longitudinal Assessment of Bariatric Surgery (LABS) parent project. Fifty-seven individuals enrolled in the LABS project who were undergoing bariatric surgery completed cognitive evaluation at baseline, 12 weeks, and 24 months. BMI and %WL were calculated for 24-month postoperative follow-up. Better cognitive function 12 weeks after surgery predicted higher %WL and lower BMI at 24 months, and specific domains of attention/executive and memory function were robustly related to decreased BMI and greater %WL at 24 months. Results show that cognitive performance shortly after bariatric surgery predicts greater long-term %WL and lower BMI 24 months after bariatric surgery. Further work is needed to clarify the degree to which this relationship is mediated by adherence to postoperative guidelines. Copyright © 2013 American Society for Bariatric Surgery. Published by Elsevier Inc. All rights reserved.

Flocking Transition in Confluent Tissues

Science.gov (United States)

Paoluzzi, Matteo; Giavazzi, Fabio; Macchi, Marta; Scita, Giorgio; Cerbino, Roberto; Manning, Lisa; Marchetti, Cristina

The emerging of collective migration in biological tissues plays a pivotal role in embryonic morphogenesis, wound healing and cancer invasion. While many aspects of single cell movements are well established, the mechanisms leading to coherent displacements of cohesive cell groups are still poorly understood. Some of us recently proposed a Self-Propelled Voronoi (SPV) model of dense tissues that combines self-propelled particle models and vertex models of confluent cell layers and exhibits a liquid-solid transition as a function of cell shape and cell motility. We now examine the role of cell polarization on collective cell dynamics by introducing an orientation mechanism that aligns cell polarization with local cell motility. The model predicts a density-independent flocking transition tuned by the strength of the aligning interaction, with both solid and liquid flocking states existing in different regions of parameter space. MP and MCM were supported by the Simons Foundation Targeted Grant in the Mathematical Modeling of Living Systems Number: 342354 and by the Syracuse Soft Matter Program.

Early post-stroke cognition in stroke rehabilitation patients predicts functional outcome at 13 months.

Science.gov (United States)

Wagle, Jørgen; Farner, Lasse; Flekkøy, Kjell; Bruun Wyller, Torgeir; Sandvik, Leiv; Fure, Brynjar; Stensrød, Brynhild; Engedal, Knut

2011-01-01

To identify prognostic factors associated with functional outcome at 13 months in a sample of stroke rehabilitation patients. Specifically, we hypothesized that cognitive functioning early after stroke would predict long-term functional outcome independently of other factors. 163 stroke rehabilitation patients underwent a structured neuropsychological examination 2-3 weeks after hospital admittance, and their functional status was subsequently evaluated 13 months later with the modified Rankin Scale (mRS) as outcome measure. Three predictive models were built using linear regression analyses: a biological model (sociodemographics, apolipoprotein E genotype, prestroke vascular factors, lesion characteristics and neurological stroke-related impairment); a functional model (pre- and early post-stroke cognitive functioning, personal and instrumental activities of daily living, ADL, and depressive symptoms), and a combined model (including significant variables, with p value Stroke Scale; β = 0.402, p stroke cognitive functioning (Repeatable Battery of Neuropsychological Status, RBANS; β = -0.248, p = 0.001) and prestroke personal ADL (Barthel Index; β = -0.217, p = 0.002). Further linear regression analyses of which RBANS indexes and subtests best predicted long-term functional outcome showed that Coding (β = -0.484, p stroke cognitive functioning as measured by the RBANS is a significant and independent predictor of long-term functional post-stroke outcome. Copyright © 2011 S. Karger AG, Basel.

Predicting a new phase (T'') of two-dimensional transition metal di-chalcogenides and strain-controlled topological phase transition

Science.gov (United States)

Ma, Fengxian; Gao, Guoping; Jiao, Yalong; Gu, Yuantong; Bilic, Ante; Zhang, Haijun; Chen, Zhongfang; Du, Aijun

2016-02-01

Single layered transition metal dichalcogenides have attracted tremendous research interest due to their structural phase diversities. By using a global optimization approach, we have discovered a new phase of transition metal dichalcogenides (labelled as T''), which is confirmed to be energetically, dynamically and kinetically stable by our first-principles calculations. The new T'' MoS2 phase exhibits an intrinsic quantum spin Hall (QSH) effect with a nontrivial gap as large as 0.42 eV, suggesting that a two-dimensional (2D) topological insulator can be achieved at room temperature. Most interestingly, there is a topological phase transition simply driven by a small tensile strain of up to 2%. Furthermore, all the known MX2 (M = Mo or W; X = S, Se or Te) monolayers in the new T'' phase unambiguously display similar band topologies and strain controlled topological phase transitions. Our findings greatly enrich the 2D families of transition metal dichalcogenides and offer a feasible way to control the electronic states of 2D topological insulators for the fabrication of high-speed spintronics devices.Single layered transition metal dichalcogenides have attracted tremendous research interest due to their structural phase diversities. By using a global optimization approach, we have discovered a new phase of transition metal dichalcogenides (labelled as T''), which is confirmed to be energetically, dynamically and kinetically stable by our first-principles calculations. The new T'' MoS2 phase exhibits an intrinsic quantum spin Hall (QSH) effect with a nontrivial gap as large as 0.42 eV, suggesting that a two-dimensional (2D) topological insulator can be achieved at room temperature. Most interestingly, there is a topological phase transition simply driven by a small tensile strain of up to 2%. Furthermore, all the known MX2 (M = Mo or W; X = S, Se or Te) monolayers in the new T'' phase unambiguously display similar band topologies and strain controlled topological

Lower solar chromosphere-corona transition region. II - Wave pressure effects for a specific form of the heating function

Science.gov (United States)

Woods, D. Tod; Holzer, Thomas E.; Macgregor, Keith B.

1990-01-01

Lower transition region models with a balance between mechanical heating and radiative losses are expanded to include wave pressure effects. The models are used to study the simple damping length form of the heating function. The results are compared to the results obtained by Woods et al. (1990) for solutions in the lower transition region. The results suggest that a mixture of fast-mode and slow-mode waves may provide the appropriate heating mechanism in the lower transition region, with the decline in effective vertical wave speed caused by the refraction and eventual total reflection of the fast-mode wave resulting from the decreasing atmospheric density.

Topological phase transitions of (BixSb1-x)2Se3 alloys by density functional theory.

Science.gov (United States)

Abdalla, L B; Padilha José, E; Schmidt, T M; Miwa, R H; Fazzio, A

2015-07-01

We have performed an ab initio total energy investigation of the topological phase transition, and the electronic properties of topologically protected surface states of (BixSb1-x)2Se3 alloys. In order to provide an accurate alloy concentration for the phase transition, we have considered the special quasirandom structures to describe the alloy system. The trivial → topological transition concentration was obtained by (i) the calculation of the band gap closing as a function of Bi concentration (x), and (ii) the calculation of the Z2 topological invariant number. We show that there is a topological phase transition, for x around 0.4, verified for both procedures (i) and (ii). We also show that in the concentration range 0.4 x < 0.7, the alloy does not present any other band at the Fermi level besides the Dirac cone, where the Dirac point is far from the bulk states. This indicates that a possible suppression of the scattering process due to bulk states will occur.

Variational transition-state theory

International Nuclear Information System (INIS)

Truhlar, D.G.; Garrett, B.C.

1980-01-01

A general introduction to and some results from studies of a procedure called variational transition-state theory are presented. A fundamental assumption of this theory is that the net rate of forward reaction at equilibrium equals the equilibrium flux in the product direction through the transition state where the transition state is a surface in phase space dividing reactants from products. Classical generalized-transition-state-theory calculations for nine collinear systems are compared to classical trajectory calculations. This new technique should provide useful insight into the successes and failures of the conventional theory and useful quantitative estimates of possible errors on the predictions of conventional transition-state theory. This should also contribute to a more accurate theory now available for the practical calculations of chemical reaction rates and thermochemical and structural interpretations of rate processes

Order-disorder phase transitions in the two-dimensional semiconducting transition metal dichalcogenide alloys Mo1−xWxX2 (X = S, Se, and Te)

KAUST Repository

Gan, Liyong

2014-10-21

A combination of density functional theory, an empirical model, and Monte Carlo simulations is used to shed light on the evolution of the atomic distribution in the two-dimensional semiconducting transition metal dichalcogenide alloys Mo1−xWxX2 (X = S, Se, and Te) as a function of the W concentration and temperature. Both random and ordered phases are discovered and the origin of the phase transitions is clarified. While the empirical model predicts at x = 1/3 and 2/3 ordered alloys, Monte Carlo simulations suggest that they only exist at low temperature due to a small energetic preference of Mo-X-W over Mo-X-Mo and W-X-W interactions, explaining the experimental observation of random alloy Mo1−xWxS2. Negative formation energies point to a high miscibility. Tunability of the band edges and band gaps by alteration of the W concentration gives rise to a broad range of applications.

Order-disorder phase transitions in the two-dimensional semiconducting transition metal dichalcogenide alloys Mo1−xWxX2 (X = S, Se, and Te)

KAUST Repository

Gan, Liyong; Zhang, Qingyun; Zhao, Yu-Jun; Cheng, Yingchun; Schwingenschlö gl, Udo

2014-01-01

A combination of density functional theory, an empirical model, and Monte Carlo simulations is used to shed light on the evolution of the atomic distribution in the two-dimensional semiconducting transition metal dichalcogenide alloys Mo1−xWxX2 (X = S, Se, and Te) as a function of the W concentration and temperature. Both random and ordered phases are discovered and the origin of the phase transitions is clarified. While the empirical model predicts at x = 1/3 and 2/3 ordered alloys, Monte Carlo simulations suggest that they only exist at low temperature due to a small energetic preference of Mo-X-W over Mo-X-Mo and W-X-W interactions, explaining the experimental observation of random alloy Mo1−xWxS2. Negative formation energies point to a high miscibility. Tunability of the band edges and band gaps by alteration of the W concentration gives rise to a broad range of applications.

A Method of Calculating Functional Independence Measure at Discharge from Functional Independence Measure Effectiveness Predicted by Multiple Regression Analysis Has a High Degree of Predictive Accuracy.

Science.gov (United States)

Tokunaga, Makoto; Watanabe, Susumu; Sonoda, Shigeru

2017-09-01

Multiple linear regression analysis is often used to predict the outcome of stroke rehabilitation. However, the predictive accuracy may not be satisfactory. The objective of this study was to elucidate the predictive accuracy of a method of calculating motor Functional Independence Measure (mFIM) at discharge from mFIM effectiveness predicted by multiple regression analysis. The subjects were 505 patients with stroke who were hospitalized in a convalescent rehabilitation hospital. The formula "mFIM at discharge = mFIM effectiveness × (91 points - mFIM at admission) + mFIM at admission" was used. By including the predicted mFIM effectiveness obtained through multiple regression analysis in this formula, we obtained the predicted mFIM at discharge (A). We also used multiple regression analysis to directly predict mFIM at discharge (B). The correlation between the predicted and the measured values of mFIM at discharge was compared between A and B. The correlation coefficients were .916 for A and .878 for B. Calculating mFIM at discharge from mFIM effectiveness predicted by multiple regression analysis had a higher degree of predictive accuracy of mFIM at discharge than that directly predicted. Copyright © 2017 National Stroke Association. Published by Elsevier Inc. All rights reserved.

A New Approach for Determining Onset of Transition

Science.gov (United States)

Hassan, H. A.; Warren, E. S.

1997-01-01

The final report consists of three papers which outline and demonstrate the new method for determining transition onset. The procedure developed under this grant requires specification of the instability mechanism, i.e., Tollmien-Schlichting or crossflow, that leads to transition. The attached papers are entitled: 'An Alternative to the e(sup n) Method for Determining Onset of Transition', 'Transition Model for Swept Wing Flows', and 'A Transition Closure Model for Predicting Transition Onset'.

PHOTOMETRIC AND SPECTRAL SIGNATURES OF THREE-DIMENSIONAL MODELS OF TRANSITING GIANT EXOPLANETS

International Nuclear Information System (INIS)

Burrows, A.; Spiegel, D. S.; Rauscher, E.; Menou, K.

2010-01-01

Using a three-dimensional general circulation model, we create dynamical model atmospheres of a representative transiting giant exoplanet, HD 209458b. We post-process these atmospheres with an opacity code to obtain transit radius spectra during the primary transit. Using a spectral atmosphere code, we integrate over the face of the planet seen by an observer at various orbital phases and calculate light curves as a function of wavelength and for different photometric bands. The products of this study are generic predictions for the phase variations of a zero-eccentricity giant planet's transit spectrum and of its light curves. We find that for these models the temporal variations in all quantities and the ingress/egress contrasts in the transit radii are small (<1.0%). Moreover, we determine that the day/night contrasts and phase shifts of the brightness peaks relative to the ephemeris are functions of photometric band. The J, H, and K bands are shifted most, while the IRAC bands are shifted least. Therefore, we verify that the magnitude of the downwind shift in the planetary 'hot spot' due to equatorial winds is strongly wavelength dependent. The phase and wavelength dependence of light curves, as well as the associated day/night contrasts, can be used to constrain the circulation regime of irradiated giant planets and to probe different pressure levels of a hot Jupiter atmosphere. We posit that though our calculations focus on models of HD 209458b, similar calculations for other transiting hot Jupiters in low-eccentricity orbits should yield transit spectra and light curves of a similar character.

Prediction of Detailed Enzyme Functions and Identification of Specificity Determining Residues by Random Forests

Science.gov (United States)

Nagao, Chioko; Nagano, Nozomi; Mizuguchi, Kenji

2014-01-01

Determining enzyme functions is essential for a thorough understanding of cellular processes. Although many prediction methods have been developed, it remains a significant challenge to predict enzyme functions at the fourth-digit level of the Enzyme Commission numbers. Functional specificity of enzymes often changes drastically by mutations of a small number of residues and therefore, information about these critical residues can potentially help discriminate detailed functions. However, because these residues must be identified by mutagenesis experiments, the available information is limited, and the lack of experimentally verified specificity determining residues (SDRs) has hindered the development of detailed function prediction methods and computational identification of SDRs. Here we present a novel method for predicting enzyme functions by random forests, EFPrf, along with a set of putative SDRs, the random forests derived SDRs (rf-SDRs). EFPrf consists of a set of binary predictors for enzymes in each CATH superfamily and the rf-SDRs are the residue positions corresponding to the most highly contributing attributes obtained from each predictor. EFPrf showed a precision of 0.98 and a recall of 0.89 in a cross-validated benchmark assessment. The rf-SDRs included many residues, whose importance for specificity had been validated experimentally. The analysis of the rf-SDRs revealed both a general tendency that functionally diverged superfamilies tend to include more active site residues in their rf-SDRs than in less diverged superfamilies, and superfamily-specific conservation patterns of each functional residue. EFPrf and the rf-SDRs will be an effective tool for annotating enzyme functions and for understanding how enzyme functions have diverged within each superfamily. PMID:24416252

Transition in the equilibrium distribution function of relativistic particles.

Science.gov (United States)

Mendoza, M; Araújo, N A M; Succi, S; Herrmann, H J

2012-01-01

We analyze a transition from single peaked to bimodal velocity distribution in a relativistic fluid under increasing temperature, in contrast with a non-relativistic gas, where only a monotonic broadening of the bell-shaped distribution is observed. Such transition results from the interplay between the raise in thermal energy and the constraint of maximum velocity imposed by the speed of light. We study the Bose-Einstein, the Fermi-Dirac, and the Maxwell-Jüttner distributions, and show that they all exhibit the same qualitative behavior. We characterize the nature of the transition in the framework of critical phenomena and show that it is either continuous or discontinuous, depending on the group velocity. We analyze the transition in one, two, and three dimensions, with special emphasis on twodimensions, for which a possible experiment in graphene, based on the measurement of the Johnson-Nyquist noise, is proposed.

Microgravity Two-Phase Flow Transition

Science.gov (United States)

Parang, M.; Chao, D.

1999-01-01

Two-phase flows under microgravity condition find a large number of important applications in fluid handling and storage, and spacecraft thermal management. Specifically, under microgravity condition heat transfer between heat exchanger surfaces and fluids depend critically on the distribution and interaction between different fluid phases which are often qualitatively different from the gravity-based systems. Heat transfer and flow analysis in two-phase flows under these conditions require a clear understanding of the flow pattern transition and development of appropriate dimensionless scales for its modeling and prediction. The physics of this flow is however very complex and remains poorly understood. This has led to various inadequacies in flow and heat transfer modeling and has made prediction of flow transition difficult in engineering design of efficient thermal and flow systems. In the present study the available published data for flow transition under microgravity condition are considered for mapping. The transition from slug to annular flow and from bubbly to slug flow are mapped using dimensionless variable combination developed in a previous study by the authors. The result indicate that the new maps describe the flow transitions reasonably well over the range of the data available. The transition maps are examined and the results are discussed in relation to the presumed balance of forces and flow dynamics. It is suggested that further evaluation of the proposed flow and transition mapping will require a wider range of microgravity data expected to be made available in future studies.

Lesions Responsible for Delayed Oral Transit Time in Post-stroke Dysphagia.

Science.gov (United States)

Moon, Hyun Im; Yoon, Seo Yeon; Yi, Tae Im; Jeong, Yoon Jeong; Cho, Tae Hwan

2017-10-11

Some stroke patients show oral phase dysphagia, characterized by a markedly prolonged oral transit time that hinders oral feeding. The aim of this study was to clarify the clinical characteristics and lesions responsible for delayed swallowing. We reviewed 90 patients with stroke. The oral processing time plus the postfaucial aggregation time required to swallow semisolid food was assessed. The patients were divided into two groups according to oral transit time, and we analyzed the differences in characteristics such as demographic factors, lesion factors, and cognitive function. Logistic regression analyses were performed to examine the predictors of delayed oral transit time. Lesion location and volume were measured on brain magnetic resonance images. We generated statistic maps of lesions related to delayed oral phase in swallowing using voxel-based lesion symptom mapping (VLSM). The group of patients who showed delayed oral transit time had significantly low cognitive function. Also, in a regression model, delayed oral phase was predicted with low K-MMSE (Korean version of the Mini Mental Status Exam). Using VLSM, we found the lesion location to be associated with delayed oral phase after adjusting for K-MMSE score. Although these results did not reach statistical significance, they showed the lesion pattern with predominant distribution in the left frontal lobe. Delayed oral phase in post-stroke patients was not negligible clinically. Patients' cognitive impairments affect the oral transit time. When adjusting it, we found a trend that the lesion responsible for delayed oral phase was located in the left frontal lobe, though the association did not reach significance. The delay might be related to praxis function.

Determination of intensity functions for predicting subsidence from coal mining, potash mining, and groundwater withdrawal using the influence function technique

Energy Technology Data Exchange (ETDEWEB)

Triplett, T; Yurchak, D [Twin Cities Research Center, Bureau of Mines, US Dept. of the Interior, Minneapolis, MN (United States)

1997-12-31

This paper presents research, conducted by the Bureau of Mines, on modifying the influence function method to predict subsidence. According to theory, this technique must incorporate an intensity function to represent the relative significance of the causes of subsidence. This paper shows that the inclusion of a reasonable intensity function increases the accuracy of the technique, then presents the required functions for case studies of longwall coal mining subsidence in Illinois, USA, potash mining subsidence in new Mexico, USA, and subsidence produced by ground water withdrawal in California, USA. Finally, the paper discusses a method to predict the resultant strain from a simply measured site constant and ground curvatures calculated by the technique. (orig.)

Determination of intensity functions for predicting subsidence from coal mining, potash mining, and groundwater withdrawal using the influence function technique

Energy Technology Data Exchange (ETDEWEB)

Triplett, T.; Yurchak, D. [Twin Cities Research Center, Bureau of Mines, US Dept. of the Interior, Minneapolis, MN (United States)

1996-12-31

This paper presents research, conducted by the Bureau of Mines, on modifying the influence function method to predict subsidence. According to theory, this technique must incorporate an intensity function to represent the relative significance of the causes of subsidence. This paper shows that the inclusion of a reasonable intensity function increases the accuracy of the technique, then presents the required functions for case studies of longwall coal mining subsidence in Illinois, USA, potash mining subsidence in new Mexico, USA, and subsidence produced by ground water withdrawal in California, USA. Finally, the paper discusses a method to predict the resultant strain from a simply measured site constant and ground curvatures calculated by the technique. (orig.)

Divergence of relative difference in Gaussian distribution function and stochastic resonance in a bistable system with frictionless state transition

Science.gov (United States)

Kasai, Seiya; Ichiki, Akihisa; Tadokoro, Yukihiro

2018-03-01

A bistable system efficiently detects a weak signal by adding noise, which is referred to as stochastic resonance. A previous theory deals with friction in state transition; however, this hypothesis is inadequate when friction force is negligible such as in nano- and molecular-scale systems. We show that, when the transition occurs without friction, the sensitivity of the bistable system to a Gaussian-noise-imposed weak signal becomes significantly high. The sensitivity is determined by the relative difference in noise distribution function. We find that the relative difference in Gaussian distribution function diverges in its tail edge, resulting in a high sensitivity in the present system.

3D CFD computations of transitional flows using DES and a correlation based transition model; Wind turbines

Energy Technology Data Exchange (ETDEWEB)

Soerensen, Niels N.

2009-07-15

The report describes the application of the correlation based transition model of Menter et. al. [1, 2] to the cylinder drag crisis and the stalled flow over an DU-96-W-351 airfoil using the DES methodology. When predicting the flow over airfoils and rotors, the laminar-turbulent transition process can be important for the aerodynamic performance. Today, the most widespread approach is to use fully turbulent computations, where the transitional process is ignored and the entire boundary layer on the wings or airfoils is handled by the turbulence model. The correlation based transition model has lately shown promising results, and the present paper describes the application of the model to predict the drag and shedding frequency for flow around a cylinder from sub to super-critical Reynolds numbers. Additionally, the model is applied to the flow around the DU-96 airfoil, at high angles of attack. (au)

The mechanism of heat transfer in transition boiling

International Nuclear Information System (INIS)

Chin Pan; Hwang, J.Y.; Lin, T.L.

1989-01-01

Liquid-solid contact in transition boiling is modelled by involving transient conduction, boiling incipience, macrolayer evaporation and vapour film boiling. The prediction of liquid contact duration and time fraction agrees reasonably well with experimental data, and the model is able to predict both of the boiling curve transitions - the critical and minimum heat fluxes. The study concludes that the liquid turbulence due to buoyancy forces and bubble agitation is an important parameter for transition boiling. It is found that surface coating (oxidation or deposition) tends to improve the transition boiling heat transfer and elevate the wall superheats at both the critical heat flux and the minimum film boiling points, which agrees with the experimental observations. (author)

Ammonia and hydrazine. Transition-metal-catalyzed hydroamination and metal-free catalyzed functionalization

Energy Technology Data Exchange (ETDEWEB)

Bertrand, Guy [Univ. of California, San Diego, CA (United States)

2012-06-29

The efficient and selective preparation of organic molecules is critical for mankind. For the future, it is of paramount importance to find catalysts able to transform abundant and cheap feedstocks into useful compounds. Acyclic and heterocyclic nitrogen-containing derivatives are common components of naturally occurring compounds, agrochemicals, cosmetics, and pharmaceuticals; they are also useful intermediates in a number of industrial processes. One of the most widely used synthetic strategies, allowing the formation of an N-C bond, is the addition of an N-H bond across a carbon-carbon multiple bond, the so-called hydroamination reaction. This chemical transformation fulfills the principle of “green chemistry” since it ideally occurs with 100% atom economy. Various catalysts have been found to promote this reaction, although many limitations remain; one of the most prominent is the lack of methods that permit the use of NH₃ and NH₂NH₂ as the amine partners. In fact, ammonia and hydrazine have rarely succumbed to homogeneous catalytic transformations. Considering the low cost and abundance of ammonia (136 million metric tons produced in 2011) and hydrazine, catalysts able to improve the reactivity and selectivity of the NH₃- and NH₂NH₂-hydroamination reaction, and more broadly speaking the functionalization of these chemicals, are highly desirable. In the last funded period, we discovered the first homogeneous catalysts able to promote the hydroamination of alkynes and allenes with ammonia and the parent hydrazine. The key feature of our catalytic systems is that the formation of catalytically inactive Werner complexes is reversible, in marked contrast to most of the known ammonia and hydrazine transition metal complexes. This is due to the peculiar electronic properties of our neutral ancillary ligands, especially their strong donating capabilities. However, our catalysts currently require

Electronic structure, magnetism, and exchange integrals in transition-metal oxides: Role of the spin polarization of the functional in DFT+U calculations

Science.gov (United States)

Keshavarz, Samara; Schött, Johan; Millis, Andrew J.; Kvashnin, Yaroslav O.

2018-05-01

Density functional theory augmented with Hubbard-U corrections (DFT+U ) is currently one of the most widely used methods for first-principles electronic structure modeling of insulating transition-metal oxides (TMOs). Since U is relatively large compared to bandwidths, the magnetic excitations in TMOs are expected to be well described by a Heisenberg model. However, in practice the calculated exchange parameters Ji j depend on the magnetic configuration from which they are extracted and on the functional used to compute them. In this work we investigate how the spin polarization dependence of the underlying exchange-correlation functional influences the calculated magnetic exchange constants of TMOs. We perform a systematic study of the predictions of calculations based on the local density approximation plus U (LDA+U ) and the local spin density approximation plus U (LSDA+U ) for the electronic structures, total energies, and magnetic exchange interactions Ji j extracted from ferromagnetic (FM) and antiferromagnetic (AFM) configurations of several transition-metal oxide materials. We report that for realistic choices of Hubbard U and Hund's J parameters, LSDA+U and LDA+U calculations result in different values of the magnetic exchange constants and band gap. The dependence of the band gap on the magnetic configuration is stronger in LDA+U than in LSDA+U and we argue that this is the main reason why the configuration dependence of Ji j is found to be systematically more pronounced in LDA+U than in LSDA+U calculations. We report a very good correspondence between the computed total energies and the parametrized Heisenberg model for LDA+U calculations, but not for LSDA+U , suggesting that LDA+U is a more appropriate method for estimating exchange interactions.

Masturbation frequency and sexual function domains are associated with serum reproductive hormone levels across the menopausal transition.

Science.gov (United States)

Randolph, John F; Zheng, Huiyong; Avis, Nancy E; Greendale, Gail A; Harlow, Siobán D

2015-01-01

To determine whether reproductive hormones are related to sexual function during the menopausal transition. The Study of Women's Health Across the Nation (SWAN) is a multiethnic cohort study of the menopausal transition located at seven US sites. At baseline, the 3302 community-based participants, aged 42-52, had an intact uterus and at least one ovary and were not using exogenous hormones. Participants self-identified as White, Black, Hispanic, Chinese, or Japanese. At baseline and at each of the 10 follow-up visits, sexual function was assessed by self-administered questionnaires, and blood was drawn to assay serum levels of T, estradiol, FSH, SHBG, and dehydroepiandrosterone sulfate. Self-reported frequency of masturbation, sexual desire, sexual arousal, orgasm, and pain during intercourse. Masturbation, sexual desire, and arousal were positively associated with T. Masturbation, arousal, and orgasm were negatively associated with FSH. Associations were modest. Estradiol was not related to any measured sexual function domain. Pain with intercourse was not associated with any hormone. Reproductive hormones were associated with sexual function in midlife women. T was positively associated, supporting the role of androgens in female sexual function. FSH was negatively associated, supporting the role of menopausal status in female sexual function. The modest associations in this large study suggest that the relationships are subtle and may be of limited clinical significance.

Tropical and Subtropical Cloud Transitions in Weather and Climate Prediction Models: The GCSS/WGNE Pacific Cross-Section Intercomparison (GPCI)

Science.gov (United States)

Teixeira, J.; Cardoso, S.; Bonazzola, M.; Cole, J.; DeGenio, A.; DeMott, C.; Franklin, C.; Hannay, C.; Jakob, C.; Jiao, Y.;

Factors predicting work outcome in Japanese patients with schizophrenia: role of multiple functioning levels.

Science.gov (United States)

Sumiyoshi, Chika; Harvey, Philip D; Takaki, Manabu; Okahisa, Yuko; Sato, Taku; Sora, Ichiro; Nuechterlein, Keith H; Subotnik, Kenneth L; Sumiyoshi, Tomiki

2015-09-01

Functional outcomes in individuals with schizophrenia suggest recovery of cognitive, everyday, and social functioning. Specifically improvement of work status is considered to be most important for their independent living and self-efficacy. The main purposes of the present study were 1) to identify which outcome factors predict occupational functioning, quantified as work hours, and 2) to provide cut-offs on the scales for those factors to attain better work status. Forty-five Japanese patients with schizophrenia and 111 healthy controls entered the study. Cognition, capacity for everyday activities, and social functioning were assessed by the Japanese versions of the MATRICS Cognitive Consensus Battery (MCCB), the UCSD Performance-based Skills Assessment-Brief (UPSA-B), and the Social Functioning Scale Individuals' version modified for the MATRICS-PASS (Modified SFS for PASS), respectively. Potential factors for work outcome were estimated by multiple linear regression analyses (predicting work hours directly) and a multiple logistic regression analyses (predicting dichotomized work status based on work hours). ROC curve analyses were performed to determine cut-off points for differentiating between the better- and poor work status. The results showed that a cognitive component, comprising visual/verbal learning and emotional management, and a social functioning component, comprising independent living and vocational functioning, were potential factors for predicting work hours/status. Cut-off points obtained in ROC analyses indicated that 60-70% achievements on the measures of those factors were expected to maintain the better work status. Our findings suggest that improvement on specific aspects of cognitive and social functioning are important for work outcome in patients with schizophrenia.

Neuroscience of inhibition for addiction medicine: from prediction of initiation to prediction of relapse.

Science.gov (United States)

Moeller, Scott J; Bederson, Lucia; Alia-Klein, Nelly; Goldstein, Rita Z

2016-01-01

A core deficit in drug addiction is the inability to inhibit maladaptive drug-seeking behavior. Consistent with this deficit, drug-addicted individuals show reliable cross-sectional differences from healthy nonaddicted controls during tasks of response inhibition accompanied by brain activation abnormalities as revealed by functional neuroimaging. However, it is less clear whether inhibition-related deficits predate the transition to problematic use, and, in turn, whether these deficits predict the transition out of problematic substance use. Here, we review longitudinal studies of response inhibition in children/adolescents with little substance experience and longitudinal studies of already addicted individuals attempting to sustain abstinence. Results show that response inhibition and its underlying neural correlates predict both substance use outcomes (onset and abstinence). Neurally, key roles were observed for multiple regions of the frontal cortex (e.g., inferior frontal gyrus, dorsal anterior cingulate cortex, and dorsolateral prefrontal cortex). In general, less activation of these regions during response inhibition predicted not only the onset of substance use, but interestingly also better abstinence-related outcomes among individuals already addicted. The role of subcortical areas, although potentially important, is less clear because of inconsistent results and because these regions are less classically reported in studies of healthy response inhibition. Overall, this review indicates that response inhibition is not simply a manifestation of current drug addiction, but rather a core neurocognitive dimension that predicts key substance use outcomes. Early intervention in inhibitory deficits could have high clinical and public health relevance. © 2016 Elsevier B.V. All rights reserved.

Assessment of a transitional boundary layer theory at low hypersonic Mach numbers

Science.gov (United States)

Shamroth, S. J.; Mcdonald, H.

1972-01-01

An investigation was carried out to assess the accuracy of a transitional boundary layer theory in the low hypersonic Mach number regime. The theory is based upon the simultaneous numerical solution of the boundary layer partial differential equations for the mean motion and an integral form of the turbulence kinetic energy equation which controls the magnitude and development of the Reynolds stress. Comparisions with experimental data show the theory is capable of accurately predicting heat transfer and velocity profiles through the transitional regime and correctly predicts the effects of Mach number and wall cooling on transition Reynolds number. The procedure shows promise of predicting the initiation of transition for given free stream disturbance levels. The effects on transition predictions of the pressure dilitation term and of direct absorption of acoustic energy by the boundary layer were evaluated.

Predictive codes of familiarity and context during the perceptual learning of facial identities

Science.gov (United States)

Apps, Matthew A. J.; Tsakiris, Manos

2013-11-01

Face recognition is a key component of successful social behaviour. However, the computational processes that underpin perceptual learning and recognition as faces transition from unfamiliar to familiar are poorly understood. In predictive coding, learning occurs through prediction errors that update stimulus familiarity, but recognition is a function of both stimulus and contextual familiarity. Here we show that behavioural responses on a two-option face recognition task can be predicted by the level of contextual and facial familiarity in a computational model derived from predictive-coding principles. Using fMRI, we show that activity in the superior temporal sulcus varies with the contextual familiarity in the model, whereas activity in the fusiform face area covaries with the prediction error parameter that updated facial familiarity. Our results characterize the key computations underpinning the perceptual learning of faces, highlighting that the functional properties of face-processing areas conform to the principles of predictive coding.

Identification of optimal soil hydraulic functions and parameters for predicting soil moisture

Science.gov (United States)

We examined the accuracy of several commonly used soil hydraulic functions and associated parameters for predicting observed soil moisture data. We used six combined methods formed by three commonly used soil hydraulic functions – i.e., Brooks and Corey (1964) (BC), Campbell (19...

Prediction of human protein function according to Gene Ontology categories

DEFF Research Database (Denmark)

Jensen, Lars Juhl; Gupta, Ramneek; Stærfeldt, Hans Henrik

2003-01-01

developed a method for prediction of protein function for a subset of classes from the Gene Ontology classification scheme. This subset includes several pharmaceutically interesting categories-transcription factors, receptors, ion channels, stress and immune response proteins, hormones and growth factors...

Prediction of functional sites in proteins using conserved functional group analysis.

Science.gov (United States)

Innis, C Axel; Anand, A Prem; Sowdhamini, R

2004-04-02

A detailed knowledge of a protein's functional site is an absolute prerequisite for understanding its mode of action at the molecular level. However, the rapid pace at which sequence and structural information is being accumulated for proteins greatly exceeds our ability to determine their biochemical roles experimentally. As a result, computational methods are required which allow for the efficient processing of the evolutionary information contained in this wealth of data, in particular that related to the nature and location of functionally important sites and residues. The method presented here, referred to as conserved functional group (CFG) analysis, relies on a simplified representation of the chemical groups found in amino acid side-chains to identify functional sites from a single protein structure and a number of its sequence homologues. We show that CFG analysis can fully or partially predict the location of functional sites in approximately 96% of the 470 cases tested and that, unlike other methods available, it is able to tolerate wide variations in sequence identity. In addition, we discuss its potential in a structural genomics context, where automation, scalability and efficiency are critical, and an increasing number of protein structures are determined with no prior knowledge of function. This is exemplified by our analysis of the hypothetical protein Ydde_Ecoli, whose structure was recently solved by members of the North East Structural Genomics consortium. Although the proposed active site for this protein needs to be validated experimentally, this example illustrates the scope of CFG analysis as a general tool for the identification of residues likely to play an important role in a protein's biochemical function. Thus, our method offers a convenient solution to rapidly and automatically process the vast amounts of data that are beginning to emerge from structural genomics projects.

Cognitive functioning differentially predicts different dimensions of older drivers' on-road safety.

Science.gov (United States)

Aksan, Nazan; Anderson, Steve W; Dawson, Jeffrey; Uc, Ergun; Rizzo, Matthew

2015-02-01

The extent to which deficits in specific cognitive domains contribute to older drivers' safety risk in complex real-world driving tasks is not well understood. We selected 148 drivers older than 70 years of age both with and without neurodegenerative diseases (Alzheimer disease-AD and Parkinson disease-PD) from an existing driving database of older adults. Participant assessments included on-road driving safety and cognitive functioning in visuospatial construction, speed of processing, memory, and executive functioning. The standardized on-road drive test was designed to examine multiple facets of older driver safety including navigation performance (e.g., following a route, identifying landmarks), safety errors while concurrently performing secondary navigation tasks ("on-task" safety errors), and safety errors in the absence of any secondary navigation tasks ("baseline" safety errors). The inter-correlations of these outcome measures were fair to moderate supporting their distinctiveness. Participants with diseases performed worse than the healthy aging group on all driving measures and differences between those with AD and PD were minimal. In multivariate analyses, different domains of cognitive functioning predicted distinct facets of driver safety on road. Memory and set-shifting predicted performance in navigation-related secondary tasks, speed of processing predicted on-task safety errors, and visuospatial construction predicted baseline safety errors. These findings support broad assessments of cognitive functioning to inform decisions regarding older driver safety on the road and suggest navigation performance may be useful in evaluating older driver fitness and restrictions in licensing. Copyright © 2014 Elsevier Ltd. All rights reserved.

Towards Transition Theory

NARCIS (Netherlands)

J. de Haan (Hans)

2010-01-01

textabstractThis thesis is a treatise on a theory for societal transitions: pillar theory. Societal transitions are complex processes taking place in complex systems, large-scale, long-term processes in which societal systems radically change the way they are composed and function. Since we all are

Fast dynamics perturbation analysis for prediction of protein functional sites

Directory of Open Access Journals (Sweden)

Cohn Judith D

2008-01-01

Full Text Available Abstract Background We present a fast version of the dynamics perturbation analysis (DPA algorithm to predict functional sites in protein structures. The original DPA algorithm finds regions in proteins where interactions cause a large change in the protein conformational distribution, as measured using the relative entropy Dx. Such regions are associated with functional sites. Results The Fast DPA algorithm, which accelerates DPA calculations, is motivated by an empirical observation that Dx in a normal-modes model is highly correlated with an entropic term that only depends on the eigenvalues of the normal modes. The eigenvalues are accurately estimated using first-order perturbation theory, resulting in a N-fold reduction in the overall computational requirements of the algorithm, where N is the number of residues in the protein. The performance of the original and Fast DPA algorithms was compared using protein structures from a standard small-molecule docking test set. For nominal implementations of each algorithm, top-ranked Fast DPA predictions overlapped the true binding site 94% of the time, compared to 87% of the time for original DPA. In addition, per-protein recall statistics (fraction of binding-site residues that are among predicted residues were slightly better for Fast DPA. On the other hand, per-protein precision statistics (fraction of predicted residues that are among binding-site residues were slightly better using original DPA. Overall, the performance of Fast DPA in predicting ligand-binding-site residues was comparable to that of the original DPA algorithm. Conclusion Compared to the original DPA algorithm, the decreased run time with comparable performance makes Fast DPA well-suited for implementation on a web server and for high-throughput analysis.

Less-structured time in children's daily lives predicts self-directed executive functioning.

Science.gov (United States)

Barker, Jane E; Semenov, Andrei D; Michaelson, Laura; Provan, Lindsay S; Snyder, Hannah R; Munakata, Yuko

2014-01-01

Executive functions (EFs) in childhood predict important life outcomes. Thus, there is great interest in attempts to improve EFs early in life. Many interventions are led by trained adults, including structured training activities in the lab, and less-structured activities implemented in schools. Such programs have yielded gains in children's externally-driven executive functioning, where they are instructed on what goal-directed actions to carry out and when. However, it is less clear how children's experiences relate to their development of self-directed executive functioning, where they must determine on their own what goal-directed actions to carry out and when. We hypothesized that time spent in less-structured activities would give children opportunities to practice self-directed executive functioning, and lead to benefits. To investigate this possibility, we collected information from parents about their 6-7 year-old children's daily, annual, and typical schedules. We categorized children's activities as "structured" or "less-structured" based on categorization schemes from prior studies on child leisure time use. We assessed children's self-directed executive functioning using a well-established verbal fluency task, in which children generate members of a category and can decide on their own when to switch from one subcategory to another. The more time that children spent in less-structured activities, the better their self-directed executive functioning. The opposite was true of structured activities, which predicted poorer self-directed executive functioning. These relationships were robust (holding across increasingly strict classifications of structured and less-structured time) and specific (time use did not predict externally-driven executive functioning). We discuss implications, caveats, and ways in which potential interpretations can be distinguished in future work, to advance an understanding of this fundamental aspect of growing up.

Predicting the enthalpies of melting and vaporization for pure components

Science.gov (United States)

Esina, Z. N.; Korchuganova, M. R.

2014-12-01

A mathematical model of the melting and vaporization enthalpies of organic components based on the theory of thermodynamic similarity is proposed. In this empirical model, the phase transition enthalpy for the homological series of n-alkanes, carboxylic acids, n-alcohols, glycols, and glycol ethers is presented as a function of the molecular mass, the number of carbon atoms in a molecule, and the normal transition temperature. The model also uses a critical or triple point temperature. It is shown that the results from predicting the melting and vaporization enthalpies enable the calculation of binary phase diagrams.

Identification of antibody glycosylation structures that predict monoclonal antibody Fc-effector function.

Science.gov (United States)

Chung, Amy W; Crispin, Max; Pritchard, Laura; Robinson, Hannah; Gorny, Miroslaw K; Yu, Xiaojie; Bailey-Kellogg, Chris; Ackerman, Margaret E; Scanlan, Chris; Zolla-Pazner, Susan; Alter, Galit

2014-11-13

To determine monoclonal antibody (mAb) features that predict fragment crystalizable (Fc)-mediated effector functions against HIV. Monoclonal antibodies, derived from Chinese hamster ovary cells or Epstein-Barr virus-immortalized mouse heteromyelomas, with specificity to key regions of the HIV envelope including gp120-V2, gp120-V3 loop, gp120-CD4(+) binding site, and gp41-specific antibodies, were functionally profiled to determine the relative contribution of the variable and constant domain features of the antibodies in driving robust Fc-effector functions. Each mAb was assayed for antibody-binding affinity to gp140(SR162), antibody-dependent cellular cytotoxicity (ADCC), antibody-dependent cellular phagocytosis (ADCP) and for the ability to bind to FcγRIIa, FcγRIIb and FcγRIIIa receptors. Antibody glycan profiles were determined by HPLC. Neither the specificity nor the affinity of the mAbs determined the potency of Fc-effector function. FcγRIIIa binding strongly predicted ADCC and decreased galactose content inversely correlated with ADCP, whereas N-glycolylneuraminic acid-containing structures exhibited enhanced ADCP. Additionally, the bi-antenary glycan arm onto which galactose was added predicted enhanced binding to FcγRIIIa and ADCC activity, independent of the specificity of the mAb. Our studies point to the specific Fc-glycan structures that can selectively promote Fc-effector functions independently of the antibody specificity. Furthermore, we demonstrated antibody glycan structures associated with enhanced ADCP activity, an emerging Fc-effector function that may aid in the control and clearance of HIV infection.

DA-9701 improves colonic transit time and symptoms in patients with functional constipation: A prospective study.

Science.gov (United States)

Kim, Su Young; Woo, Hyun Sun; Kim, Kyoung Oh; Choi, Sung Han; Kwon, Kwang An; Chung, Jun-Won; Kim, Yoon Jae; Kim, Jung Ho; Kim, Su Ji; Park, Dong Kyun

2017-12-01

DA-9701, a newly developed prokinetic agent formulated with Pharbitis Semen and Corydalis Tuber, has been shown to effectively treat functional dyspepsia. Recently, it has also been suspected to improve gastrointestinal motor function. The aims of this study were to assess the effect of DA-9701 on colonic transit time (CTT) and symptoms of functional constipation. Thirty-three patients with functional constipation based on the Rome III criteria were prospectively enrolled. The patients received 30-mg DA-9701 three times a day for 24 days. CTT was estimated initially and at the end of treatment. Symptoms such as spontaneous bowel movements, straining, stool form, feeling of incomplete emptying and anorectal blockage, abdominal discomfort and pain, overall defecation satisfaction, and incidence of adverse events were also analyzed. Twenty-seven patients completed the study. DA-9701 was associated with a significantly reduced CTT from 34.9 ± 17.6 to 23.7 ± 19.1 h (P = 0.001). Segmental CTT also significantly decreased after treatment (right CTT: from 16.8 [0.0-28.8] to 6.0 [0.0-25.2] hours, P DA-9701 accelerates colonic transit and safely improves symptoms in patients with functional constipation. Therefore, we suggest that this novel agent could help to treat patients with this condition. © 2017 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.

Filling- and interaction-driven Mott transition. Quantum cluster calculations within self-energy-functional theory

International Nuclear Information System (INIS)

Balzer, Matthias

2008-01-01

The central goal of this thesis is the examination of strongly correlated electron systems on the basis of the two-dimensional Hubbard model. We analyze how the properties of the Mott insulator change upon doping and with interaction strength. The numerical evaluation is done using quantum cluster approximations, which allow for a thermodynamically consistent description of the ground state properties. The framework of self-energy-functional theory offers great flexibility for the construction of cluster approximations. A detailed analysis sheds light on the quality and the convergence properties of different cluster approximations within the self-energy-functional theory. We use the one-dimensional Hubbard model for these examinations and compare our results with the exact solution. In two dimensions the ground state of the particle-hole symmetric model at half-filling is an antiferromagnetic insulator, independent of the interaction strength. The inclusion of short-range spatial correlations by our cluster approach leads to a considerable improvement of the antiferromagnetic order parameter as compared to dynamical mean-field theory. In the paramagnetic phase we furthermore observe a metal-insulator transition as a function of the interaction strength, which qualitatively differs from the pure mean-field scenario. Starting from the antiferromagnetic Mott insulator a filling-controlled metal-insulator transition in a paramagnetic metallic phase can be observed. Depending on the cluster approximation used an antiferromagnetic metallic phase may occur at first. In addition to long-range antiferromagnetic order, we also considered superconductivity in our calculations. The superconducting order parameter as a function of doping is in good agreement with other numerical methods, as well as with experimental results. (orig.)

Strange metals and quantum phase transitions from gauge/gravity duality

Science.gov (United States)

Liu, Hong

2011-03-01

Metallic materials whose thermodynamic and transport properties differ significantly from those predicted by Fermi liquid theory, so-called non-Fermi liquids, include the strange metal phase of cuprate superconductors, and heavy fermion systems near a quantum phase transition. We use gauge/gravity duality to identify a class of non-Fermi liquids. Their low-energy behavior is governed by a nontrivial infrared fixed point which exhibits non-analytic scaling behavior only in the temporal direction. Some representatives of this class have single-particle spectral functions and transport behavior similar to those of the strange metals, with conductivity inversely proportional to the temperature. Such holographic systems may also exhibit novel ``magnetic instabilities'', where the quantum critical behavior near the transition involves a nontrivial interplay between local and bulk physics, with the local physics again described by a similar infrared fixed point. The resulting quantum phase transitions do not obey the standard Landau-Ginsburg-Wilson paradigm and resemble those of the heavy fermion quantum critical points.

Functional imaging of semantic memory predicts postoperative episodic memory functions in chronic temporal lobe epilepsy.

Science.gov (United States)

Köylü, Bülent; Walser, Gerald; Ischebeck, Anja; Ortler, Martin; Benke, Thomas

2008-08-05

Medial temporal (MTL) structures have crucial functions in episodic (EM), but also in semantic memory (SM) processing. Preoperative functional magnetic resonance imaging (fMRI) activity within the MTL is increasingly used to predict post-surgical memory capacities. Based on the hypothesis that EM and SM memory functions are both hosted by the MTL the present study wanted to explore the relationship between SM related activations in the MTL as assessed before and the capacity of EM functions after surgery. Patients with chronic unilateral left (n=14) and right (n=12) temporal lobe epilepsy (TLE) performed a standard word list learning test pre- and postoperatively, and a fMRI procedure before the operation using a semantic decision task. SM processing caused significant bilateral MTL activations in both patient groups. While right TLE patients showed asymmetry of fMRI activation with more activation in the left MTL, left TLE patients had almost equal activation in both MTL regions. Contrasting left TLE versus right TLE patients revealed greater activity within the right MTL, whereas no significant difference was observed for the reverse contrast. Greater effect size in the MTL region ipsilateral to the seizure focus was significantly and positively correlated with preoperative EM abilities. Greater effect size in the contralateral MTL was correlated with better postoperative verbal EM, especially in left TLE patients. These results suggest that functional imaging of SM tasks may be useful to predict postoperative verbal memory in TLE. They also advocate a common neuroanatomical basis for SM and EM processes in the MTL.

[Hepatic transit times and liver elasticity compared with meld in predicting a 1 year adverse clinical outcome of a clinically diagnosed cirrhosis].

Science.gov (United States)

Koller, Tomáš; Piešťanská, Zuzana; Hlavatý, Tibor; Holomáň, Jozef; Glasa, Jozef; Payer, Juraj

Hepatic transit times measured by the contrast enhanced ultrasonography and liver elasticity were found to predict a clinically significant portal hypertension. However, these modalities we not yet sufficiently evaluated in predicting adverse clinical outcome in patients with clinically diagnosed cirrhosis (D´Amico stages > 1), having a clinically significant portal hypertension. The aim of our study was to assess the predictive power of the liver transit times and the liver elasticity on an adverse clinical outcome of clinically diagnosed cirrhosis compared with the MELD score. The study group included 48 consecutive outpatients with cirrhosis in the 2., 3. and 4. DAmico stages. Patients with stage 4 could have jaundice, patients with other complications of portal hypertension were excluded. Transit times were measured from the time of intravenous administration of contrast agent (Sonovue) to a signal appearance in a hepatic vein (hepatic vein arrival time, HVAT) or time difference between the contrast signal in the hepatic artery and hepatic vein (hepatic transit time, HTT) in seconds. Elasticity was measured using the transient elastography (Fibroscan). The transit times and elasticity were measured at baseline and patients were followed for up for 1 year. Adverse outcome of cirrhosis was defined as the appearance of clinically apparent ascites and/or hospitalization for liver disease and/or death within 1 year. The mean age was 61 years, with female/male ratio 23/25. At baseline, the median Child-Pugh score was 5 (IQR 5.0-6.0), MELD 9.5 (IQR 7.6 to 12.1), median HVAT was 22 s (IQR 19-25) and HTT 6 (IQR 5-9). HTT and HVAT negatively correlated with Child-Pugh (-0.351 and -0.441, p = 0.002) and MELD (-0.479 and -0.388, p = 0.006) scores. The adverse outcome at 1-year was observed in 11 cases (22.9 %), including 6 deaths and 5 hospitalizations. Median HVAT in those with/without the adverse outcome was 20 seconds (IQR 19.3-23.5) compared with 22 s (IQR 19-26, p