WorldWideScience

Sample records for model identifies key

  1. Identifying tier one key suppliers.

    Science.gov (United States)

    Wicks, Steve

    2013-01-01

    In today's global marketplace, businesses are becoming increasingly reliant on suppliers for the provision of key processes, activities, products and services in support of their strategic business goals. The result is that now, more than ever, the failure of a key supplier has potential to damage reputation, productivity, compliance and financial performance seriously. Yet despite this, there is no recognised standard or guidance for identifying a tier one key supplier base and, up to now, there has been little or no research on how to do so effectively. This paper outlines the key findings of a BCI-sponsored research project to investigate good practice in identifying tier one key suppliers, and suggests a scalable framework process model and risk matrix tool to help businesses effectively identify their tier one key supplier base.

  2. A mouse model of alcoholic liver fibrosis-associated acute kidney injury identifies key molecular pathways

    International Nuclear Information System (INIS)

    Furuya, Shinji; Chappell, Grace A.; Iwata, Yasuhiro; Uehara, Takeki; Kato, Yuki; Kono, Hiroshi; Bataller, Ramon; Rusyn, Ivan

    2016-01-01

    Clinical data strongly indicate that acute kidney injury (AKI) is a critical complication in alcoholic hepatitis, an acute-on-chronic form of liver failure in patients with advanced alcoholic fibrosis. Development of targeted therapies for AKI in this setting is hampered by the lack of an animal model. To enable research into molecular drivers and novel therapies for fibrosis- and alcohol-associated AKI, we aimed to combine carbon tetrachloride (CCl 4 )-induced fibrosis with chronic intra-gastric alcohol feeding. Male C57BL/6J mice were administered a low dose of CCl 4 (0.2 ml/kg 2 × week/6 weeks) followed by alcohol intragastrically (up to 25 g/kg/day for 3 weeks) and with continued CCl 4 . We observed that combined treatment with CCl 4 and alcohol resulted in severe liver injury, more pronounced than using each treatment alone. Importantly, severe kidney injury was evident only in the combined treatment group. This mouse model reproduced distinct pathological features consistent with AKI in human alcoholic hepatitis. Transcriptomic analysis of kidneys revealed profound effects in the combined treatment group, with enrichment for damage-associated pathways, such as apoptosis, inflammation, immune-response and hypoxia. Interestingly, Havcr1 and Lcn2, biomarkers of AKI, were markedly up-regulated. Overall, this study established a novel mouse model of fibrosis- and alcohol-associated AKI and identified key mechanistic pathways. - Highlights: • Acute kidney injury (AKI) is a critical complication in alcoholic hepatitis • We developed a novel mouse model of fibrosis- and alcohol-associated AKI • This model reproduces key molecular and pathological features of human AKI • This animal model can help identify new targeted therapies for alcoholic hepatitis

  3. A mouse model of alcoholic liver fibrosis-associated acute kidney injury identifies key molecular pathways

    Energy Technology Data Exchange (ETDEWEB)

    Furuya, Shinji; Chappell, Grace A.; Iwata, Yasuhiro [Department of Veterinary Integrative Biosciences, Texas A& M University, College Station, TX (United States); Uehara, Takeki; Kato, Yuki [Laboratory of Veterinary Pathology, Osaka Prefecture University, Osaka (Japan); Kono, Hiroshi [First Department of Surgery, University of Yamanashi, Yamanashi (Japan); Bataller, Ramon [Division of Gastroenterology & Hepatology, Department of Medicine, University of North Carolina, Chapel Hill, NC (United States); Rusyn, Ivan, E-mail: irusyn@tamu.edu [Department of Veterinary Integrative Biosciences, Texas A& M University, College Station, TX (United States)

    2016-11-01

    Clinical data strongly indicate that acute kidney injury (AKI) is a critical complication in alcoholic hepatitis, an acute-on-chronic form of liver failure in patients with advanced alcoholic fibrosis. Development of targeted therapies for AKI in this setting is hampered by the lack of an animal model. To enable research into molecular drivers and novel therapies for fibrosis- and alcohol-associated AKI, we aimed to combine carbon tetrachloride (CCl{sub 4})-induced fibrosis with chronic intra-gastric alcohol feeding. Male C57BL/6J mice were administered a low dose of CCl{sub 4} (0.2 ml/kg 2 × week/6 weeks) followed by alcohol intragastrically (up to 25 g/kg/day for 3 weeks) and with continued CCl{sub 4}. We observed that combined treatment with CCl{sub 4} and alcohol resulted in severe liver injury, more pronounced than using each treatment alone. Importantly, severe kidney injury was evident only in the combined treatment group. This mouse model reproduced distinct pathological features consistent with AKI in human alcoholic hepatitis. Transcriptomic analysis of kidneys revealed profound effects in the combined treatment group, with enrichment for damage-associated pathways, such as apoptosis, inflammation, immune-response and hypoxia. Interestingly, Havcr1 and Lcn2, biomarkers of AKI, were markedly up-regulated. Overall, this study established a novel mouse model of fibrosis- and alcohol-associated AKI and identified key mechanistic pathways. - Highlights: • Acute kidney injury (AKI) is a critical complication in alcoholic hepatitis • We developed a novel mouse model of fibrosis- and alcohol-associated AKI • This model reproduces key molecular and pathological features of human AKI • This animal model can help identify new targeted therapies for alcoholic hepatitis.

  4. Modelling Creativity: Identifying Key Components through a Corpus-Based Approach.

    Science.gov (United States)

    Jordanous, Anna; Keller, Bill

    2016-01-01

    Creativity is a complex, multi-faceted concept encompassing a variety of related aspects, abilities, properties and behaviours. If we wish to study creativity scientifically, then a tractable and well-articulated model of creativity is required. Such a model would be of great value to researchers investigating the nature of creativity and in particular, those concerned with the evaluation of creative practice. This paper describes a unique approach to developing a suitable model of how creative behaviour emerges that is based on the words people use to describe the concept. Using techniques from the field of statistical natural language processing, we identify a collection of fourteen key components of creativity through an analysis of a corpus of academic papers on the topic. Words are identified which appear significantly often in connection with discussions of the concept. Using a measure of lexical similarity to help cluster these words, a number of distinct themes emerge, which collectively contribute to a comprehensive and multi-perspective model of creativity. The components provide an ontology of creativity: a set of building blocks which can be used to model creative practice in a variety of domains. The components have been employed in two case studies to evaluate the creativity of computational systems and have proven useful in articulating achievements of this work and directions for further research.

  5. Computational modeling identifies key gene regulatory interactions underlying phenobarbital-mediated tumor promotion

    Science.gov (United States)

    Luisier, Raphaëlle; Unterberger, Elif B.; Goodman, Jay I.; Schwarz, Michael; Moggs, Jonathan; Terranova, Rémi; van Nimwegen, Erik

    2014-01-01

    Gene regulatory interactions underlying the early stages of non-genotoxic carcinogenesis are poorly understood. Here, we have identified key candidate regulators of phenobarbital (PB)-mediated mouse liver tumorigenesis, a well-characterized model of non-genotoxic carcinogenesis, by applying a new computational modeling approach to a comprehensive collection of in vivo gene expression studies. We have combined our previously developed motif activity response analysis (MARA), which models gene expression patterns in terms of computationally predicted transcription factor binding sites with singular value decomposition (SVD) of the inferred motif activities, to disentangle the roles that different transcriptional regulators play in specific biological pathways of tumor promotion. Furthermore, transgenic mouse models enabled us to identify which of these regulatory activities was downstream of constitutive androstane receptor and β-catenin signaling, both crucial components of PB-mediated liver tumorigenesis. We propose novel roles for E2F and ZFP161 in PB-mediated hepatocyte proliferation and suggest that PB-mediated suppression of ESR1 activity contributes to the development of a tumor-prone environment. Our study shows that combining MARA with SVD allows for automated identification of independent transcription regulatory programs within a complex in vivo tissue environment and provides novel mechanistic insights into PB-mediated hepatocarcinogenesis. PMID:24464994

  6. Predictive model identifies key network regulators of cardiomyocyte mechano-signaling.

    Directory of Open Access Journals (Sweden)

    Philip M Tan

    2017-11-01

    Full Text Available Mechanical strain is a potent stimulus for growth and remodeling in cells. Although many pathways have been implicated in stretch-induced remodeling, the control structures by which signals from distinct mechano-sensors are integrated to modulate hypertrophy and gene expression in cardiomyocytes remain unclear. Here, we constructed and validated a predictive computational model of the cardiac mechano-signaling network in order to elucidate the mechanisms underlying signal integration. The model identifies calcium, actin, Ras, Raf1, PI3K, and JAK as key regulators of cardiac mechano-signaling and characterizes crosstalk logic imparting differential control of transcription by AT1R, integrins, and calcium channels. We find that while these regulators maintain mostly independent control over distinct groups of transcription factors, synergy between multiple pathways is necessary to activate all the transcription factors necessary for gene transcription and hypertrophy. We also identify a PKG-dependent mechanism by which valsartan/sacubitril, a combination drug recently approved for treating heart failure, inhibits stretch-induced hypertrophy, and predict further efficacious pairs of drug targets in the network through a network-wide combinatorial search.

  7. Evaluating predictive models for solar energy growth in the US states and identifying the key drivers

    Science.gov (United States)

    Chakraborty, Joheen; Banerji, Sugata

    2018-03-01

    Driven by a desire to control climate change and reduce the dependence on fossil fuels, governments around the world are increasing the adoption of renewable energy sources. However, among the US states, we observe a wide disparity in renewable penetration. In this study, we have identified and cleaned over a dozen datasets representing solar energy penetration in each US state, and the potentially relevant socioeconomic and other factors that may be driving the growth in solar. We have applied a number of predictive modeling approaches - including machine learning and regression - on these datasets over a 17-year period and evaluated the relative performance of the models. Our goals were: (1) identify the most important factors that are driving the growth in solar, (2) choose the most effective predictive modeling technique for solar growth, and (3) develop a model for predicting next year’s solar growth using this year’s data. We obtained very promising results with random forests (about 90% efficacy) and varying degrees of success with support vector machines and regression techniques (linear, polynomial, ridge). We also identified states with solar growth slower than expected and representing a potential for stronger growth in future.

  8. Physiologically-based toxicokinetic models help identifying the key factors affecting contaminant uptake during flood events

    Energy Technology Data Exchange (ETDEWEB)

    Brinkmann, Markus; Eichbaum, Kathrin [Department of Ecosystem Analysis, Institute for Environmental Research,ABBt – Aachen Biology and Biotechnology, RWTH Aachen University, Worringerweg 1, 52074 Aachen (Germany); Kammann, Ulrike [Thünen-Institute of Fisheries Ecology, Palmaille 9, 22767 Hamburg (Germany); Hudjetz, Sebastian [Department of Ecosystem Analysis, Institute for Environmental Research,ABBt – Aachen Biology and Biotechnology, RWTH Aachen University, Worringerweg 1, 52074 Aachen (Germany); Institute of Hydraulic Engineering and Water Resources Management, RWTH Aachen University, Mies-van-der-Rohe-Straße 1, 52056 Aachen (Germany); Cofalla, Catrina [Institute of Hydraulic Engineering and Water Resources Management, RWTH Aachen University, Mies-van-der-Rohe-Straße 1, 52056 Aachen (Germany); Buchinger, Sebastian; Reifferscheid, Georg [Federal Institute of Hydrology (BFG), Department G3: Biochemistry, Ecotoxicology, Am Mainzer Tor 1, 56068 Koblenz (Germany); Schüttrumpf, Holger [Institute of Hydraulic Engineering and Water Resources Management, RWTH Aachen University, Mies-van-der-Rohe-Straße 1, 52056 Aachen (Germany); Preuss, Thomas [Department of Environmental Biology and Chemodynamics, Institute for Environmental Research,ABBt- Aachen Biology and Biotechnology, RWTH Aachen University, Worringerweg 1, 52074 Aachen (Germany); and others

    2014-07-01

    Highlights: • A PBTK model for trout was coupled with a sediment equilibrium partitioning model. • The influence of physical exercise on pollutant uptake was studies using the model. • Physical exercise during flood events can increase the level of biliary metabolites. • Cardiac output and effective respiratory volume were identified as relevant factors. • These confounding factors need to be considered also for bioconcentration studies. - Abstract: As a consequence of global climate change, we will be likely facing an increasing frequency and intensity of flood events. Thus, the ecotoxicological relevance of sediment re-suspension is of growing concern. It is vital to understand contaminant uptake from suspended sediments and relate it to effects in aquatic biota. Here we report on a computational study that utilizes a physiologically based toxicokinetic model to predict uptake, metabolism and excretion of sediment-borne pyrene in rainbow trout (Oncorhynchus mykiss). To this end, data from two experimental studies were compared with the model predictions: (a) batch re-suspension experiments with constant concentration of suspended particulate matter at two different temperatures (12 and 24 °C), and (b) simulated flood events in an annular flume. The model predicted both the final concentrations and the kinetics of 1-hydroxypyrene secretion into the gall bladder of exposed rainbow trout well. We were able to show that exhaustive exercise during exposure in simulated flood events can lead to increased levels of biliary metabolites and identified cardiac output and effective respiratory volume as the two most important factors for contaminant uptake. The results of our study clearly demonstrate the relevance and the necessity to investigate uptake of contaminants from suspended sediments under realistic exposure scenarios.

  9. Physiologically-based toxicokinetic models help identifying the key factors affecting contaminant uptake during flood events

    International Nuclear Information System (INIS)

    Brinkmann, Markus; Eichbaum, Kathrin; Kammann, Ulrike; Hudjetz, Sebastian; Cofalla, Catrina; Buchinger, Sebastian; Reifferscheid, Georg; Schüttrumpf, Holger; Preuss, Thomas

    2014-01-01

    Highlights: • A PBTK model for trout was coupled with a sediment equilibrium partitioning model. • The influence of physical exercise on pollutant uptake was studies using the model. • Physical exercise during flood events can increase the level of biliary metabolites. • Cardiac output and effective respiratory volume were identified as relevant factors. • These confounding factors need to be considered also for bioconcentration studies. - Abstract: As a consequence of global climate change, we will be likely facing an increasing frequency and intensity of flood events. Thus, the ecotoxicological relevance of sediment re-suspension is of growing concern. It is vital to understand contaminant uptake from suspended sediments and relate it to effects in aquatic biota. Here we report on a computational study that utilizes a physiologically based toxicokinetic model to predict uptake, metabolism and excretion of sediment-borne pyrene in rainbow trout (Oncorhynchus mykiss). To this end, data from two experimental studies were compared with the model predictions: (a) batch re-suspension experiments with constant concentration of suspended particulate matter at two different temperatures (12 and 24 °C), and (b) simulated flood events in an annular flume. The model predicted both the final concentrations and the kinetics of 1-hydroxypyrene secretion into the gall bladder of exposed rainbow trout well. We were able to show that exhaustive exercise during exposure in simulated flood events can lead to increased levels of biliary metabolites and identified cardiac output and effective respiratory volume as the two most important factors for contaminant uptake. The results of our study clearly demonstrate the relevance and the necessity to investigate uptake of contaminants from suspended sediments under realistic exposure scenarios

  10. Probing molecular mechanisms of the Hsp90 chaperone: biophysical modeling identifies key regulators of functional dynamics.

    Directory of Open Access Journals (Sweden)

    Anshuman Dixit

    Full Text Available Deciphering functional mechanisms of the Hsp90 chaperone machinery is an important objective in cancer biology aiming to facilitate discovery of targeted anti-cancer therapies. Despite significant advances in understanding structure and function of molecular chaperones, organizing molecular principles that control the relationship between conformational diversity and functional mechanisms of the Hsp90 activity lack a sufficient quantitative characterization. We combined molecular dynamics simulations, principal component analysis, the energy landscape model and structure-functional analysis of Hsp90 regulatory interactions to systematically investigate functional dynamics of the molecular chaperone. This approach has identified a network of conserved regions common to the Hsp90 chaperones that could play a universal role in coordinating functional dynamics, principal collective motions and allosteric signaling of Hsp90. We have found that these functional motifs may be utilized by the molecular chaperone machinery to act collectively as central regulators of Hsp90 dynamics and activity, including the inter-domain communications, control of ATP hydrolysis, and protein client binding. These findings have provided support to a long-standing assertion that allosteric regulation and catalysis may have emerged via common evolutionary routes. The interaction networks regulating functional motions of Hsp90 may be determined by the inherent structural architecture of the molecular chaperone. At the same time, the thermodynamics-based "conformational selection" of functional states is likely to be activated based on the nature of the binding partner. This mechanistic model of Hsp90 dynamics and function is consistent with the notion that allosteric networks orchestrating cooperative protein motions can be formed by evolutionary conserved and sparsely connected residue clusters. Hence, allosteric signaling through a small network of distantly connected

  11. Using Range-Wide Abundance Modeling to Identify Key Conservation Areas for the Micro-Endemic Bolson Tortoise (Gopherus flavomarginatus.

    Directory of Open Access Journals (Sweden)

    Cinthya A Ureña-Aranda

    Full Text Available A widespread biogeographic pattern in nature is that population abundance is not uniform across the geographic range of species: most occurrence sites have relatively low numbers, whereas a few places contain orders of magnitude more individuals. The Bolson tortoise Gopherus flavomarginatus is endemic to a small region of the Chihuahuan Desert in Mexico, where habitat deterioration threatens this species with extinction. In this study we combined field burrows counts and the approach for modeling species abundance based on calculating the distance to the niche centroid to obtain range-wide abundance estimates. For the Bolson tortoise, we found a robust, negative relationship between observed burrows abundance and distance to the niche centroid, with a predictive capacity of 71%. Based on these results we identified four priority areas for the conservation of this microendemic and threatened tortoise. We conclude that this approach may be a useful approximation for identifying key areas for sampling and conservation efforts in elusive and rare species.

  12. Identifying a key physical factor sensitive to the performance of Madden-Julian oscillation simulation in climate models

    Science.gov (United States)

    Kim, Go-Un; Seo, Kyong-Hwan

    2018-01-01

    A key physical factor in regulating the performance of Madden-Julian oscillation (MJO) simulation is examined by using 26 climate model simulations from the World Meteorological Organization's Working Group for Numerical Experimentation/Global Energy and Water Cycle Experiment Atmospheric System Study (WGNE and MJO-Task Force/GASS) global model comparison project. For this, intraseasonal moisture budget equation is analyzed and a simple, efficient physical quantity is developed. The result shows that MJO skill is most sensitive to vertically integrated intraseasonal zonal wind convergence (ZC). In particular, a specific threshold value of the strength of the ZC can be used as distinguishing between good and poor models. An additional finding is that good models exhibit the correct simultaneous convection and large-scale circulation phase relationship. In poor models, however, the peak circulation response appears 3 days after peak rainfall, suggesting unfavorable coupling between convection and circulation. For an improving simulation of the MJO in climate models, we propose that this delay of circulation in response to convection needs to be corrected in the cumulus parameterization scheme.

  13. A systems toxicology approach identifies Lyn as a key signaling phosphoprotein modulated by mercury in a B lymphocyte cell model

    Energy Technology Data Exchange (ETDEWEB)

    Caruso, Joseph A.; Stemmer, Paul M. [Institute of Environmental Health Sciences, Wayne State University, Detroit, MI (United States); Dombkowski, Alan [Department of Pediatrics, Wayne State University, Detroit, MI (United States); Caruthers, Nicholas J. [Institute of Environmental Health Sciences, Wayne State University, Detroit, MI (United States); Gill, Randall [Department of Immunology and Microbiology, Wayne State University, Detroit, MI (United States); Rosenspire, Allen J., E-mail: arosenspire@wayne.edu [Department of Immunology and Microbiology, Wayne State University, Detroit, MI (United States)

    2014-04-01

    Network and protein–protein interaction analyses of proteins undergoing Hg{sup 2+}-induced phosphorylation and dephosphorylation in Hg{sup 2+}-intoxicated mouse WEHI-231 B cells identified Lyn as the most interconnected node. Lyn is a Src family protein tyrosine kinase known to be intimately involved in the B cell receptor (BCR) signaling pathway. Under normal signaling conditions the tyrosine kinase activity of Lyn is controlled by phosphorylation, primarily of two well known canonical regulatory tyrosine sites, Y-397 and Y-508. However, Lyn has several tyrosine residues that have not yet been determined to play a major role under normal signaling conditions, but are potentially important sites for phosphorylation following mercury exposure. In order to determine how Hg{sup 2+} exposure modulates the phosphorylation of additional residues in Lyn, a targeted MS assay was developed. Initial mass spectrometric surveys of purified Lyn identified 7 phosphorylated tyrosine residues. A quantitative assay was developed from these results using the multiple reaction monitoring (MRM) strategy. WEHI-231 cells were treated with Hg{sup 2+}, pervanadate (a phosphatase inhibitor), or anti-Ig antibody (to stimulate the BCR). Results from these studies showed that the phosphoproteomic profile of Lyn after exposure of the WEHI-231 cells to a low concentration of Hg{sup 2+} closely resembled that of anti-Ig antibody stimulation, whereas exposure to higher concentrations of Hg{sup 2+} led to increases in the phosphorylation of Y-193/Y-194, Y-501 and Y-508 residues. These data indicate that mercury can disrupt a key regulatory signal transduction pathway in B cells and point to phospho-Lyn as a potential biomarker for mercury exposure. - Highlights: • Inorganic mercury (Hg{sup 2+}) induces changes in the WEHI-231 B cell phosphoproteome. • The B cell receptor (BCR) signaling pathway was the pathway most affected by Hg{sup 2+}. • The Src family phosphoprotein kinase Lyn was the

  14. A Video Analysis of Intra- and Interprofessional Leadership Behaviors Within "The Burns Suite": Identifying Key Leadership Models.

    Science.gov (United States)

    Sadideen, Hazim; Weldon, Sharon-Marie; Saadeddin, Munir; Loon, Mark; Kneebone, Roger

    2016-01-01

    Leadership is particularly important in complex highly interprofessional health care contexts involving a number of staff, some from the same specialty (intraprofessional), and others from different specialties (interprofessional). The authors recently published the concept of "The Burns Suite" (TBS) as a novel simulation tool to deliver interprofessional and teamwork training. It is unclear which leadership behaviors are the most important in an interprofessional burns resuscitation scenario, and whether they can be modeled on to current leadership theory. The purpose of this study was to perform a comprehensive video analysis of leadership behaviors within TBS. A total of 3 burns resuscitation simulations within TBS were recorded. The video analysis was grounded-theory inspired. Using predefined criteria, actions/interactions deemed as leadership behaviors were identified. Using an inductive iterative process, 8 main leadership behaviors were identified. Cohen's κ coefficient was used to measure inter-rater agreement and calculated as κ = 0.7 (substantial agreement). Each video was watched 4 times, focusing on 1 of the 4 team members per viewing (senior surgeon, senior nurse, trainee surgeon, and trainee nurse). The frequency and types of leadership behavior of each of the 4 team members were recorded. Statistical significance to assess any differences was assessed using analysis of variance, whereby a p Leadership behaviors were triangulated with verbal cues and actions from the videos. All 3 scenarios were successfully completed. The mean scenario length was 22 minutes. A total of 362 leadership behaviors were recorded from the 12 participants. The most evident leadership behaviors of all team members were adhering to guidelines (which effectively equates to following Advanced Trauma and Life Support/Emergency Management of Severe Burns resuscitation guidelines and hence "maintaining standards"), followed by making decisions. Although in terms of total

  15. BENCHMARKING - PRACTICAL TOOLS IDENTIFY KEY SUCCESS FACTORS

    Directory of Open Access Journals (Sweden)

    Olga Ju. Malinina

    2016-01-01

    Full Text Available The article gives a practical example of the application of benchmarking techniques. The object of study selected fashion store Company «HLB & M Hennes & Mauritz», located in the shopping center «Gallery», Krasnodar. Hennes & Mauritz. The purpose of this article is to identify the best ways to develop a fashionable brand clothing store Hennes & Mauritz on the basis of benchmarking techniques. On the basis of conducted market research is a comparative analysis of the data from different perspectives. The result of the author’s study is a generalization of the ndings, the development of the key success factors that will allow to plan a successful trading activities in the future, based on the best experience of competitors.

  16. Identifying Key Attributes for Protein Beverages.

    Science.gov (United States)

    Oltman, A E; Lopetcharat, K; Bastian, E; Drake, M A

    2015-06-01

    This study identified key attributes of protein beverages and evaluated effects of priming on liking of protein beverages. An adaptive choice-based conjoint study was conducted along with Kano analysis to gain insight on protein beverage consumers (n = 432). Attributes evaluated included label claim, protein type, amount of protein, carbohydrates, sweeteners, and metabolic benefits. Utility scores for levels and importance scores for attributes were determined. Subsequently, two pairs of clear acidic whey protein beverages were manufactured that differed by age of protein source or the amount of whey protein per serving. Beverages were evaluated by 151 consumers on two occasions with or without priming statements. One priming statement declared "great flavor," the other priming statement declared 20 g protein per serving. A two way analysis of variance was applied to discern the role of each priming statement. The most important attribute for protein beverages was sweetener type, followed by amount of protein, followed by type of protein followed by label claim. Beverages with whey protein, naturally sweetened, reduced sugar and ≥15 g protein per serving were most desired. Three consumer clusters were identified, differentiated by their preferences for protein type, sweetener and amount of protein. Priming statements positively impacted concept liking (P 0.05). Consistent with trained panel profiles of increased cardboard flavor with higher protein content, consumers liked beverages with 10 g protein more than beverages with 20 g protein (6.8 compared with 5.7, P appeal. © 2015 Institute of Food Technologists®

  17. Identifying Key Actors in Heterogeneous Networks

    Science.gov (United States)

    2017-11-29

    Department of Defense (DOD) present social situations that are outside the scope and violate the assumptions of existing formal social science models. SNA by...assumptions of these existing social science models. SNA by its very construction focuses on dyadic relations and standard SNA metrics are focused only on...problematic for our purposes of determining relative valuations among vertices, but it is in contrast to the behavior of valuations like the Shapley value

  18. Identifying key controls on the behavior of an acidic-U(VI) plume in the Savannah River Site using reactive transport modeling.

    Science.gov (United States)

    Bea, Sergio A; Wainwright, Haruko; Spycher, Nicolas; Faybishenko, Boris; Hubbard, Susan S; Denham, Miles E

    2013-08-01

    Acidic low-level waste radioactive waste solutions were discharged to three unlined seepage basins at the F-Area of the Department of Energy (DOE) Savannah River Site (SRS), South Carolina, USA, from 1955 through 1989. Despite many years of active remediation, the groundwater remains acidic and contaminated with significant levels of U(VI) and other radionuclides. Monitored Natural Attenuation (MNA) is a desired closure strategy for the site, based on the premise that regional flow of clean background groundwater will eventually neutralize the groundwater acidity, immobilizing U(VI) through adsorption. An in situ treatment system is currently in place to accelerate this in the downgradient portion of the plume and similar measures could be taken upgradient if necessary. Understanding the long-term pH and U(VI) adsorption behavior at the site is critical to assess feasibility of MNA along with the in-situ remediation treatments. This paper presents a reactive transport (RT) model and uncertainty quantification (UQ) analyses to explore key controls on the U(VI)-plume evolution and long-term mobility at this site. Two-dimensional numerical RT simulations are run including the saturated and unsaturated (vadose) zones, U(VI) and H(+) adsorption (surface complexation) onto sediments, dissolution and precipitation of Al and Fe minerals, and key hydrodynamic processes are considered. UQ techniques are applied using a new open-source tool that is part of the developing ASCEM reactive transport modeling and analysis framework to: (1) identify the complex physical and geochemical processes that control the U(VI) plume migration in the pH range where the plume is highly mobile, (2) evaluate those physical and geochemical parameters that are most controlling, and (3) predict the future plume evolution constrained by historical, chemical and hydrological data. The RT simulation results show a good agreement with the observed historical pH and concentrations of U(VI), nitrates

  19. Research Note Identifying key grazing indicators to monitor trends in ...

    African Journals Online (AJOL)

    Research Note Identifying key grazing indicators to monitor trends in the veld condition of Lambert's Bay Strandveld, South Africa. ... from which a minimum number of species necessary to monitor trends in the condition of the veld were determined, making it user-friendly for land-users, extension officers and others. The key ...

  20. Identifiability in stochastic models

    CERN Document Server

    1992-01-01

    The problem of identifiability is basic to all statistical methods and data analysis, occurring in such diverse areas as Reliability Theory, Survival Analysis, and Econometrics, where stochastic modeling is widely used. Mathematics dealing with identifiability per se is closely related to the so-called branch of ""characterization problems"" in Probability Theory. This book brings together relevant material on identifiability as it occurs in these diverse fields.

  1. Model plant Key Measurement Points

    International Nuclear Information System (INIS)

    Schneider, R.A.

    1984-01-01

    For IAEA safeguards a Key Measurement Point is defined as the location where nuclear material appears in such a form that it may be measured to determine material flow or inventory. This presentation describes in an introductory manner the key measurement points and associated measurements for the model plant used in this training course

  2. Soil fauna: key to new carbon models

    OpenAIRE

    Filser, Juliane; Faber, Jack H.; Tiunov, Alexei V.; Brussaard, Lijbert; Frouz, Jan; Deyn, Gerlinde; Uvarov, Alexei V.; Berg, Matty P.; Lavelle, Patrick; Loreau, Michel; Wall, Diana H.; Querner, Pascal; Eijsackers, Herman; Jiménez, Juan José

    2016-01-01

    Soil organic matter (SOM) is key to maintaining soil fertility, mitigating climate change, combatting land degradation, and conserving above- and below-ground biodiversity and associated soil processes and ecosystem services. In order to derive management options for maintaining these essential services provided by soils, policy makers depend on robust, predictive models identifying key drivers of SOM dynamics. Existing SOM models and suggested guidelines for future SOM modelling are defined ...

  3. Social Network Analysis Identifies Key Participants in Conservation Development.

    Science.gov (United States)

    Farr, Cooper M; Reed, Sarah E; Pejchar, Liba

    2018-05-01

    Understanding patterns of participation in private lands conservation, which is often implemented voluntarily by individual citizens and private organizations, could improve its effectiveness at combating biodiversity loss. We used social network analysis (SNA) to examine participation in conservation development (CD), a private land conservation strategy that clusters houses in a small portion of a property while preserving the remaining land as protected open space. Using data from public records for six counties in Colorado, USA, we compared CD participation patterns among counties and identified actors that most often work with others to implement CDs. We found that social network characteristics differed among counties. The network density, or proportion of connections in the network, varied from fewer than 2 to nearly 15%, and was higher in counties with smaller populations and fewer CDs. Centralization, or the degree to which connections are held disproportionately by a few key actors, was not correlated strongly with any county characteristics. Network characteristics were not correlated with the prevalence of wildlife-friendly design features in CDs. The most highly connected actors were biological and geological consultants, surveyors, and engineers. Our work demonstrates a new application of SNA to land-use planning, in which CD network patterns are examined and key actors are identified. For better conservation outcomes of CD, we recommend using network patterns to guide strategies for outreach and information dissemination, and engaging with highly connected actor types to encourage widespread adoption of best practices for CD design and stewardship.

  4. Identifying key hospital service quality factors in online health communities.

    Science.gov (United States)

    Jung, Yuchul; Hur, Cinyoung; Jung, Dain; Kim, Minki

    2015-04-07

    The volume of health-related user-created content, especially hospital-related questions and answers in online health communities, has rapidly increased. Patients and caregivers participate in online community activities to share their experiences, exchange information, and ask about recommended or discredited hospitals. However, there is little research on how to identify hospital service quality automatically from the online communities. In the past, in-depth analysis of hospitals has used random sampling surveys. However, such surveys are becoming impractical owing to the rapidly increasing volume of online data and the diverse analysis requirements of related stakeholders. As a solution for utilizing large-scale health-related information, we propose a novel approach to identify hospital service quality factors and overtime trends automatically from online health communities, especially hospital-related questions and answers. We defined social media-based key quality factors for hospitals. In addition, we developed text mining techniques to detect such factors that frequently occur in online health communities. After detecting these factors that represent qualitative aspects of hospitals, we applied a sentiment analysis to recognize the types of recommendations in messages posted within online health communities. Korea's two biggest online portals were used to test the effectiveness of detection of social media-based key quality factors for hospitals. To evaluate the proposed text mining techniques, we performed manual evaluations on the extraction and classification results, such as hospital name, service quality factors, and recommendation types using a random sample of messages (ie, 5.44% (9450/173,748) of the total messages). Service quality factor detection and hospital name extraction achieved average F1 scores of 91% and 78%, respectively. In terms of recommendation classification, performance (ie, precision) is 78% on average. Extraction and

  5. Key clinical features to identify girls with CDKL5 mutations.

    Science.gov (United States)

    Bahi-Buisson, Nadia; Nectoux, Juliette; Rosas-Vargas, Haydeé; Milh, Mathieu; Boddaert, Nathalie; Girard, Benoit; Cances, Claude; Ville, Dorothée; Afenjar, Alexandra; Rio, Marlène; Héron, Delphine; N'guyen Morel, Marie Ange; Arzimanoglou, Alexis; Philippe, Christophe; Jonveaux, Philippe; Chelly, Jamel; Bienvenu, Thierry

    2008-10-01

    Mutations in the human X-linked cyclin-dependent kinase-like 5 (CDKL5) gene have been shown to cause infantile spasms as well as Rett syndrome (RTT)-like phenotype. To date, less than 25 different mutations have been reported. So far, there are still little data on the key clinical diagnosis criteria and on the natural history of CDKL5-associated encephalopathy. We screened the entire coding region of CDKL5 for mutations in 183 females with encephalopathy with early seizures by denaturing high liquid performance chromatography and direct sequencing, and we identified in 20 unrelated girls, 18 different mutations including 7 novel mutations. These mutations were identified in eight patients with encephalopathy with RTT-like features, five with infantile spasms and seven with encephalopathy with refractory epilepsy. Early epilepsy with normal interictal EEG and severe hypotonia are the key clinical features in identifying patients likely to have CDKL5 mutations. Our study also indicates that these patients clearly exhibit some RTT features such as deceleration of head growth, stereotypies and hand apraxia and that these RTT features become more evident in older and ambulatory patients. However, some RTT signs are clearly absent such as the so called RTT disease profile (period of nearly normal development followed by regression with loss of acquired fine finger skill in early childhood and characteristic intensive eye communication) and the characteristic evolution of the RTT electroencephalogram. Interestingly, in addition to the overall stereotypical symptomatology (age of onset and evolution of the disease) resulting from CDKL5 mutations, atypical forms of CDKL5-related conditions have also been observed. Our data suggest that phenotypic heterogeneity does not correlate with the nature or the position of the mutations or with the pattern of X-chromosome inactivation, but most probably with the functional transcriptional and/or translational consequences of CDKL5

  6. Identifying key genes associated with acute myocardial infarction.

    Science.gov (United States)

    Cheng, Ming; An, Shoukuan; Li, Junquan

    2017-10-01

    This study aimed to identify key genes associated with acute myocardial infarction (AMI) by reanalyzing microarray data. Three gene expression profile datasets GSE66360, GSE34198, and GSE48060 were downloaded from GEO database. After data preprocessing, genes without heterogeneity across different platforms were subjected to differential expression analysis between the AMI group and the control group using metaDE package. P FI) network. Then, DEGs in each module were subjected to pathway enrichment analysis using DAVID. MiRNAs and transcription factors predicted to regulate target DEGs were identified. Quantitative real-time polymerase chain reaction (RT-PCR) was applied to verify the expression of genes. A total of 913 upregulated genes and 1060 downregulated genes were identified in the AMI group. A FI network consists of 21 modules and DEGs in 12 modules were significantly enriched in pathways. The transcription factor-miRNA-gene network contains 2 transcription factors FOXO3 and MYBL2, and 2 miRNAs hsa-miR-21-5p and hsa-miR-30c-5p. RT-PCR validations showed that expression levels of FOXO3 and MYBL2 were significantly increased in AMI, and expression levels of hsa-miR-21-5p and hsa-miR-30c-5p were obviously decreased in AMI. A total of 41 DEGs, such as SOCS3, VAPA, and COL5A2, are speculated to have roles in the pathogenesis of AMI; 2 transcription factors FOXO3 and MYBL2, and 2 miRNAs hsa-miR-21-5p and hsa-miR-30c-5p may be involved in the regulation of the expression of these DEGs.

  7. Identifying the key concerns of Irish persons with intellectual disability.

    Science.gov (United States)

    García Iriarte, Edurne; O'Brien, Patricia; McConkey, Roy; Wolfe, Marie; O'Doherty, Siobhain

    2014-11-01

    Internationally, people with intellectual disability are socially marginalized, and their rights under the United Nations Convention for the Rights of Persons with Disabilities (CRPD) are often ignored. This paper aims to define the key concerns of adults with an intellectual disability in relation to their participation in society using an inclusive research strategy for both data gathering and data analysis. A national study involving 23 focus groups and 168 persons was conducted on the island of Ireland with people with intellectual disability as co-facilitators. A thematic content analysis was undertaken of the verbatim transcripts initially by university co-researchers, and 19 themes were identified. Co-researchers with intellectual disability joined in identifying the eight core themes. These were as follows: living options, employment, relationships, citizenship, leisure time, money management, self-advocacy, and communication. The concerns are discussed within the framework of the CRPD, and implications for transforming service policy are drawn. Why we did the research In many countries, people with intellectual disability have difficulties doing things other people without disabilities do, for example to study, to get a job or to live independently. They also find that their rights are not respected under the Convention on the Rights of Persons with Disabilities (the Convention). We did this study to Learn what are the main issues for adults with intellectual disability in Ireland. Do research with people with intellectual disability. How we did the research People with intellectual disability and their supporters worked with university researchers to plan and do the research. We met with people in groups and 168 people told us about things important to them. What we found out We found that there were very important things that people talked about in the groups. We chose the most important: living options, employment, relationships, rights, leisure, money

  8. Risk and Performance Technologies: Identifying the Keys to Successful Implementation

    International Nuclear Information System (INIS)

    McClain, Lynn; Smith, Art; O'Regan, Patrick

    2002-01-01

    The nuclear power industry has been utilizing risk and performance based technologies for over thirty years. Applications of these technologies have included risk assessment (e.g. Individual Plant Examinations), burden reduction (e.g. Risk-Informed Inservice Inspection, RI-ISI) and risk management (Maintenance Rule, 10CFR50.65). Over the last five to ten years the number of risk-informed (RI) burden reduction initiatives has increased. Unfortunately, the efficiencies of some of these applications have been questionable. This paper investigates those attributes necessary to support successful, cost-effective RI-applications. The premise to this paper is that by understanding the key attributes that support one successful application, insights can be gleaned that will streamline/coordinate future RI-applications. This paper is an extension to a paper presented at the Pressure Vessel and Piping (PVP-2001) Conference. In that paper, a number issues and opportunities were identified that needed to be assessed in order to support future (and efficient) RI-applications. It was noted in the paper that a proper understanding and resolution of these issues will facilitate implementation of risk and performance technology in the operation, maintenance and design disciplines. In addition, it will provide the foundation necessary to support regulatory review and approval. (authors)

  9. A Sensitivity Analysis Approach to Identify Key Environmental Performance Factors

    Directory of Open Access Journals (Sweden)

    Xi Yu

    2014-01-01

    Full Text Available Life cycle assessment (LCA is widely used in design phase to reduce the product’s environmental impacts through the whole product life cycle (PLC during the last two decades. The traditional LCA is restricted to assessing the environmental impacts of a product and the results cannot reflect the effects of changes within the life cycle. In order to improve the quality of ecodesign, it is a growing need to develop an approach which can reflect the changes between the design parameters and product’s environmental impacts. A sensitivity analysis approach based on LCA and ecodesign is proposed in this paper. The key environmental performance factors which have significant influence on the products’ environmental impacts can be identified by analyzing the relationship between environmental impacts and the design parameters. Users without much environmental knowledge can use this approach to determine which design parameter should be first considered when (redesigning a product. A printed circuit board (PCB case study is conducted; eight design parameters are chosen to be analyzed by our approach. The result shows that the carbon dioxide emission during the PCB manufacture is highly sensitive to the area of PCB panel.

  10. Soil fauna: key to new carbon models

    Science.gov (United States)

    Filser, Juliane; Faber, Jack H.; Tiunov, Alexei V.; Brussaard, Lijbert; Frouz, Jan; De Deyn, Gerlinde; Uvarov, Alexei V.; Berg, Matty P.; Lavelle, Patrick; Loreau, Michel; Wall, Diana H.; Querner, Pascal; Eijsackers, Herman; José Jiménez, Juan

    2016-11-01

    Soil organic matter (SOM) is key to maintaining soil fertility, mitigating climate change, combatting land degradation, and conserving above- and below-ground biodiversity and associated soil processes and ecosystem services. In order to derive management options for maintaining these essential services provided by soils, policy makers depend on robust, predictive models identifying key drivers of SOM dynamics. Existing SOM models and suggested guidelines for future SOM modelling are defined mostly in terms of plant residue quality and input and microbial decomposition, overlooking the significant regulation provided by soil fauna. The fauna controls almost any aspect of organic matter turnover, foremost by regulating the activity and functional composition of soil microorganisms and their physical-chemical connectivity with soil organic matter. We demonstrate a very strong impact of soil animals on carbon turnover, increasing or decreasing it by several dozen percent, sometimes even turning C sinks into C sources or vice versa. This is demonstrated not only for earthworms and other larger invertebrates but also for smaller fauna such as Collembola. We suggest that inclusion of soil animal activities (plant residue consumption and bioturbation altering the formation, depth, hydraulic properties and physical heterogeneity of soils) can fundamentally affect the predictive outcome of SOM models. Understanding direct and indirect impacts of soil fauna on nutrient availability, carbon sequestration, greenhouse gas emissions and plant growth is key to the understanding of SOM dynamics in the context of global carbon cycling models. We argue that explicit consideration of soil fauna is essential to make realistic modelling predictions on SOM dynamics and to detect expected non-linear responses of SOM dynamics to global change. We present a decision framework, to be further developed through the activities of KEYSOM, a European COST Action, for when mechanistic SOM models

  11. Key Clinical Features to Identify Girls with "CDKL5" Mutations

    Science.gov (United States)

    Bahi-Buisson, Nadia; Nectoux, Juliette; Rosas-Vargas, Haydee; Milh, Mathieu; Boddaert, Nathalie; Girard, Benoit; Cances, Claude; Ville, Dorothee; Afenjar, Alexandra; Rio, Marlene; Heron, Delphine; Morel, Marie Ange N'Guyen; Arzimanoglou, Alexis; Philippe, Christophe; Jonveaux, Philippe; Chelly, Jamel; Bienvenu, Thierry

    2008-01-01

    Mutations in the human X-linked cyclin-dependent kinase-like 5 ("CDKL5") gene have been shown to cause infantile spasms as well as Rett syndrome (RTT)-like phenotype. To date, less than 25 different mutations have been reported. So far, there are still little data on the key clinical diagnosis criteria and on the natural history of…

  12. Human-automation collaboration in manufacturing: identifying key implementation factors

    OpenAIRE

    Charalambous, George; Fletcher, Sarah; Webb, Philip

    2013-01-01

    Human-automation collaboration refers to the concept of human operators and intelligent automation working together interactively within the same workspace without conventional physical separation. This concept has commanded significant attention in manufacturing because of the potential applications, such as the installation of large sub-assemblies. However, the key human factors relevant to human-automation collaboration have not yet been fully investigated. To maximise effective implement...

  13. Identifying the Key Weaknesses in Network Security at Colleges.

    Science.gov (United States)

    Olsen, Florence

    2000-01-01

    A new study identifies and ranks the 10 security gaps responsible for most outsider attacks on college computer networks. The list is intended to help campus system administrators establish priorities as they work to increase security. One network security expert urges that institutions utilize multiple security layers. (DB)

  14. Identifying key nodes in multilayer networks based on tensor decomposition.

    Science.gov (United States)

    Wang, Dingjie; Wang, Haitao; Zou, Xiufen

    2017-06-01

    The identification of essential agents in multilayer networks characterized by different types of interactions is a crucial and challenging topic, one that is essential for understanding the topological structure and dynamic processes of multilayer networks. In this paper, we use the fourth-order tensor to represent multilayer networks and propose a novel method to identify essential nodes based on CANDECOMP/PARAFAC (CP) tensor decomposition, referred to as the EDCPTD centrality. This method is based on the perspective of multilayer networked structures, which integrate the information of edges among nodes and links between different layers to quantify the importance of nodes in multilayer networks. Three real-world multilayer biological networks are used to evaluate the performance of the EDCPTD centrality. The bar chart and ROC curves of these multilayer networks indicate that the proposed approach is a good alternative index to identify real important nodes. Meanwhile, by comparing the behavior of both the proposed method and the aggregated single-layer methods, we demonstrate that neglecting the multiple relationships between nodes may lead to incorrect identification of the most versatile nodes. Furthermore, the Gene Ontology functional annotation demonstrates that the identified top nodes based on the proposed approach play a significant role in many vital biological processes. Finally, we have implemented many centrality methods of multilayer networks (including our method and the published methods) and created a visual software based on the MATLAB GUI, called ENMNFinder, which can be used by other researchers.

  15. Identifying key processes in the hydrochemistry of a basin through ...

    Indian Academy of Sciences (India)

    through the combined use of factor and regression models. Sandow Mark ... Department of Earth Science, University of Ghana, Legon, Accra, Ghana. ∗ ... influence groundwater hydrochemistry and deter- mine its .... 1600 mm) due to the differences in climatic zones. .... dropped so that it does not cloud the results of the.

  16. Identifying key conservation threats to Alpine birds through expert knowledge

    Science.gov (United States)

    Pedrini, Paolo; Brambilla, Mattia; Rolando, Antonio; Girardello, Marco

    2016-01-01

    Alpine biodiversity is subject to a range of increasing threats, but the scarcity of data for many taxa means that it is difficult to assess the level and likely future impact of a given threat. Expert opinion can be a useful tool to address knowledge gaps in the absence of adequate data. Experts with experience in Alpine ecology were approached to rank threat levels for 69 Alpine bird species over the next 50 years for the whole European Alps in relation to ten categories: land abandonment, climate change, renewable energy, fire, forestry practices, grazing practices, hunting, leisure, mining and urbanization. There was a high degree of concordance in ranking of perceived threats among experts for most threat categories. The major overall perceived threats to Alpine birds identified through expert knowledge were land abandonment, urbanization, leisure and forestry, although other perceived threats were ranked highly for particular species groups (renewable energy and hunting for raptors, hunting for gamebirds). For groups of species defined according to their breeding habitat, open habitat species and treeline species were perceived as the most threatened. A spatial risk assessment tool based on summed scores for the whole community showed threat levels were highest for bird communities of the northern and western Alps. Development of the approaches given in this paper, including addressing biases in the selection of experts and adopting a more detailed ranking procedure, could prove useful in the future in identifying future threats, and in carrying out risk assessments based on levels of threat to the whole bird community. PMID:26966659

  17. Identifying key conservation threats to Alpine birds through expert knowledge

    Directory of Open Access Journals (Sweden)

    Dan E. Chamberlain

    2016-02-01

    Full Text Available Alpine biodiversity is subject to a range of increasing threats, but the scarcity of data for many taxa means that it is difficult to assess the level and likely future impact of a given threat. Expert opinion can be a useful tool to address knowledge gaps in the absence of adequate data. Experts with experience in Alpine ecology were approached to rank threat levels for 69 Alpine bird species over the next 50 years for the whole European Alps in relation to ten categories: land abandonment, climate change, renewable energy, fire, forestry practices, grazing practices, hunting, leisure, mining and urbanization. There was a high degree of concordance in ranking of perceived threats among experts for most threat categories. The major overall perceived threats to Alpine birds identified through expert knowledge were land abandonment, urbanization, leisure and forestry, although other perceived threats were ranked highly for particular species groups (renewable energy and hunting for raptors, hunting for gamebirds. For groups of species defined according to their breeding habitat, open habitat species and treeline species were perceived as the most threatened. A spatial risk assessment tool based on summed scores for the whole community showed threat levels were highest for bird communities of the northern and western Alps. Development of the approaches given in this paper, including addressing biases in the selection of experts and adopting a more detailed ranking procedure, could prove useful in the future in identifying future threats, and in carrying out risk assessments based on levels of threat to the whole bird community.

  18. Sparse Linear Identifiable Multivariate Modeling

    DEFF Research Database (Denmark)

    Henao, Ricardo; Winther, Ole

    2011-01-01

    and bench-marked on artificial and real biological data sets. SLIM is closest in spirit to LiNGAM (Shimizu et al., 2006), but differs substantially in inference, Bayesian network structure learning and model comparison. Experimentally, SLIM performs equally well or better than LiNGAM with comparable......In this paper we consider sparse and identifiable linear latent variable (factor) and linear Bayesian network models for parsimonious analysis of multivariate data. We propose a computationally efficient method for joint parameter and model inference, and model comparison. It consists of a fully...

  19. Time to refine key climate policy models

    Science.gov (United States)

    Barron, Alexander R.

    2018-05-01

    Ambition regarding climate change at the national level is critical but is often calibrated with the projected costs — as estimated by a small suite of energy-economic models. Weaknesses in several key areas in these models will continue to distort policy design unless collectively addressed by a diversity of researchers.

  20. Tamper-proof secret image-sharing scheme for identifying cheated secret keys and shared images

    Science.gov (United States)

    Chen, Chien-Chang; Liu, Chong-An

    2013-01-01

    A (t,n) secret image-sharing scheme shares a secret image to n participants, and the t users recover the image. During the recovery procedure of a conventional secret image-sharing scheme, cheaters may use counterfeit secret keys or modified shared images to cheat other users' secret keys and shared images. A cheated secret key or shared image leads to an incorrect secret image. Unfortunately, the cheater cannot be identified. We present an exponent and modulus-based scheme to provide a tamper-proof secret image-sharing scheme for identifying cheaters on secret keys or shared images. The proposed scheme allows users to securely select their secret key. This assignment can be performed over networks. Modulus results of each shared image is calculated to recognize cheaters of a shared image. Experimental results indicate that the proposed scheme is excellent at identifying cheated secret keys and shared images.

  1. Exploring the effects of spatial autocorrelation when identifying key drivers of wildlife crop-raiding.

    Science.gov (United States)

    Songhurst, Anna; Coulson, Tim

    2014-03-01

    Few universal trends in spatial patterns of wildlife crop-raiding have been found. Variations in wildlife ecology and movements, and human spatial use have been identified as causes of this apparent unpredictability. However, varying spatial patterns of spatial autocorrelation (SA) in human-wildlife conflict (HWC) data could also contribute. We explicitly explore the effects of SA on wildlife crop-raiding data in order to facilitate the design of future HWC studies. We conducted a comparative survey of raided and nonraided fields to determine key drivers of crop-raiding. Data were subsampled at different spatial scales to select independent raiding data points. The model derived from all data was fitted to subsample data sets. Model parameters from these models were compared to determine the effect of SA. Most methods used to account for SA in data attempt to correct for the change in P-values; yet, by subsampling data at broader spatial scales, we identified changes in regression estimates. We consequently advocate reporting both model parameters across a range of spatial scales to help biological interpretation. Patterns of SA vary spatially in our crop-raiding data. Spatial distribution of fields should therefore be considered when choosing the spatial scale for analyses of HWC studies. Robust key drivers of elephant crop-raiding included raiding history of a field and distance of field to a main elephant pathway. Understanding spatial patterns and determining reliable socio-ecological drivers of wildlife crop-raiding is paramount for designing mitigation and land-use planning strategies to reduce HWC. Spatial patterns of HWC are complex, determined by multiple factors acting at more than one scale; therefore, studies need to be designed with an understanding of the effects of SA. Our methods are accessible to a variety of practitioners to assess the effects of SA, thereby improving the reliability of conservation management actions.

  2. Identifying Key Drivers of Return Reversal with Dynamical Bayesian Factor Graph.

    Directory of Open Access Journals (Sweden)

    Shuai Zhao

    Full Text Available In the stock market, return reversal occurs when investors sell overbought stocks and buy oversold stocks, reversing the stocks' price trends. In this paper, we develop a new method to identify key drivers of return reversal by incorporating a comprehensive set of factors derived from different economic theories into one unified dynamical Bayesian factor graph. We then use the model to depict factor relationships and their dynamics, from which we make some interesting discoveries about the mechanism behind return reversals. Through extensive experiments on the US stock market, we conclude that among the various factors, the liquidity factors consistently emerge as key drivers of return reversal, which is in support of the theory of liquidity effect. Specifically, we find that stocks with high turnover rates or high Amihud illiquidity measures have a greater probability of experiencing return reversals. Apart from the consistent drivers, we find other drivers of return reversal that generally change from year to year, and they serve as important characteristics for evaluating the trends of stock returns. Besides, we also identify some seldom discussed yet enlightening inter-factor relationships, one of which shows that stocks in Finance and Insurance industry are more likely to have high Amihud illiquidity measures in comparison with those in other industries. These conclusions are robust for return reversals under different thresholds.

  3. Identifying Key Stakeholder Groups for Implementing a Place Branding Policy in Saint Petersburg

    Directory of Open Access Journals (Sweden)

    Kulibanova V. V.

    2017-10-01

    Full Text Available Regional brands have become a valuable intangible asset and a crucial competitive resource for forging partnerships. An effective place branding policy is impossible without a precise understanding of the interests of stakeholder groups. It is essential to realize that each region is unique in its own way. Territories differ in the structure of stakeholders, their influence on regional development, and the range of leverages over regional decision-makers. This study aims to give a more precise definition of key groups of stakeholders in Saint Petersburg place branding, and to identify them. The authors employ the method of theoretical and empirical typology of a territory’s stakeholders within a theoretical framework proposed by E. Freeman, P. Kotler, S. Zenker, and E. Brown. The article defines the concept of key regional stakeholders and identifies them. The proposed target audience (stakeholder group model for a place branding policy is tested on the case of Saint Petersburg. The authors show that each target audience of place marketing requires an individual policy. This is explained by the fact that each group enjoys its unique features that should be taken into account when creating and transmitting messages.

  4. Identifying the key personnel in a nurse-initiated hospital waste reduction program.

    Science.gov (United States)

    McDermott-Levy, Ruth; Fazzini, Carol

    2010-01-01

    Hospitals in the United States generate more than 6600 tons of trash a day and approximately 85% of the waste is nonhazardous solid waste such as food, cardboard, and plastic. Treatment and management of hospital waste can lead to environmental problems for the communities that receive the waste. One health system's shared governance model provided the foundation to develop a nurse-led hospital waste reduction program that focused on point-of-care waste management. Waste reduction program development required working with a variety of departments within and external to the health system. The interdisciplinary approach informed the development of the waste reduction program. This article identifies the key departments that were necessary to include when developing a hospital waste reduction program.

  5. Identifying Determinants of Organizational Development as the Key Developers of Employee Soft Skill

    Directory of Open Access Journals (Sweden)

    Shahjahan Laghari

    2016-10-01

    Full Text Available The purpose of this article is to identify the determinants of organizational development as the key developers of employee soft skills. Various studies have been taken where determinants of organizational development defining soft skills in employees are discussed. However, the current study is different in Pakistani industry context as the link was missing about the determinants of organizational development which in synchronized way help in developing soft skills in employees of firm. This research uses explanatory approach; incorporating secondary data extracted under the light of existing school of thoughts paired with quantification through data collected from respondents in Pakistani corporate sector. Hypotheses are tested using structural equation model (SEM technique. Results This research showed an affirmative link between determinants of organizational development and development of soft skills in employees. Finally, the study proposes enriching insights on few missing links that can be researched and triggered achieving maximized outcomes.

  6. Using sensitivity analysis to identify key factors for the propagation of a plant epidemic.

    Science.gov (United States)

    Rimbaud, Loup; Bruchou, Claude; Dallot, Sylvie; Pleydell, David R J; Jacquot, Emmanuel; Soubeyrand, Samuel; Thébaud, Gaël

    2018-01-01

    Identifying the key factors underlying the spread of a disease is an essential but challenging prerequisite to design management strategies. To tackle this issue, we propose an approach based on sensitivity analyses of a spatiotemporal stochastic model simulating the spread of a plant epidemic. This work is motivated by the spread of sharka, caused by plum pox virus , in a real landscape. We first carried out a broad-range sensitivity analysis, ignoring any prior information on six epidemiological parameters, to assess their intrinsic influence on model behaviour. A second analysis benefited from the available knowledge on sharka epidemiology and was thus restricted to more realistic values. The broad-range analysis revealed that the mean duration of the latent period is the most influential parameter of the model, whereas the sharka-specific analysis uncovered the strong impact of the connectivity of the first infected orchard. In addition to demonstrating the interest of sensitivity analyses for a stochastic model, this study highlights the impact of variation ranges of target parameters on the outcome of a sensitivity analysis. With regard to sharka management, our results suggest that sharka surveillance may benefit from paying closer attention to highly connected patches whose infection could trigger serious epidemics.

  7. Identifying key drivers of greenhouse gas emissions from biomass feedstocks for energy production

    International Nuclear Information System (INIS)

    Johnson, David R.; Curtright, Aimee E.; Willis, Henry H.

    2013-01-01

    Highlights: • Production emissions dominate transportation and processing emissions. • Choice of feedstock, geographic location and prior land use drive emissions profile. • Within scenarios, emissions variability is driven by uncertainty in yields. • Favorable scenarios maximize carbon storage from direct land-use change. • Similarly, biomass production should attempt to minimize indirect land-use change. -- Abstract: Many policies in the United States, at both the federal and state levels, encourage the adoption of renewable energy from biomass. Though largely motivated by a desire to reduce greenhouse gas emissions, these policies do not explicitly identify scenarios in which the use of biomass will produce the greatest benefits. We have modeled “farm-to-hopper” emissions associated with seven biomass feedstocks, under a wide variety of scenarios and production choices, to characterize the uncertainty in emissions. We demonstrate that only a handful of factors have a significant impact on life cycle emissions: choice of feedstock, geographic location, prior land use, and time dynamics. Within a given production scenario, the remaining variability in emissions is driven by uncertainty in feedstock yields and the release rate of N 2 O into the atmosphere from nitrogen fertilizers. With few exceptions, transport and processing choices have relatively little impact on total emissions. These results illustrate the key decisions that will determine the success of biomass programs in reducing the emissions profile of energy production, and our publicly available model provides a useful tool for identifying the most beneficial production scenarios. While model data and results are restricted to biomass production in the contiguous United States, we provide qualitative guidance for identifying favorable production scenarios that should be applicable in other regions

  8. Identifying key radiogenomic associations between DCE-MRI and micro-RNA expressions for breast cancer

    Science.gov (United States)

    Samala, Ravi K.; Chan, Heang-Ping; Hadjiiski, Lubomir; Helvie, Mark A.; Kim, Renaid

    2017-03-01

    Understanding the key radiogenomic associations for breast cancer between DCE-MRI and micro-RNA expressions is the foundation for the discovery of radiomic features as biomarkers for assessing tumor progression and prognosis. We conducted a study to analyze the radiogenomic associations for breast cancer using the TCGA-TCIA data set. The core idea that tumor etiology is a function of the behavior of miRNAs is used to build the regression models. The associations based on regression are analyzed for three study outcomes: diagnosis, prognosis, and treatment. The diagnosis group consists of miRNAs associated with clinicopathologic features of breast cancer and significant aberration of expression in breast cancer patients. The prognosis group consists of miRNAs which are closely associated with tumor suppression and regulation of cell proliferation and differentiation. The treatment group consists of miRNAs that contribute significantly to the regulation of metastasis thereby having the potential to be part of therapeutic mechanisms. As a first step, important miRNA expressions were identified and their ability to classify the clinical phenotypes based on the study outcomes was evaluated using the area under the ROC curve (AUC) as a figure-of-merit. The key mapping between the selected miRNAs and radiomic features were determined using least absolute shrinkage and selection operator (LASSO) regression analysis within a two-loop leave-one-out cross-validation strategy. These key associations indicated a number of radiomic features from DCE-MRI to be potential biomarkers for the three study outcomes.

  9. Identifying Key Performance Indicators for Holistic Hospital Management with a Modified DEMATEL Approach.

    Science.gov (United States)

    Si, Sheng-Li; You, Xiao-Yue; Liu, Hu-Chen; Huang, Jia

    2017-08-19

    Performance analysis is an important way for hospitals to achieve higher efficiency and effectiveness in providing services to their customers. The performance of the healthcare system can be measured by many indicators, but it is difficult to improve them simultaneously due to the limited resources. A feasible way is to identify the central and influential indicators to improve healthcare performance in a stepwise manner. In this paper, we propose a hybrid multiple criteria decision making (MCDM) approach to identify key performance indicators (KPIs) for holistic hospital management. First, through integrating evidential reasoning approach and interval 2-tuple linguistic variables, various assessments of performance indicators provided by healthcare experts are modeled. Then, the decision making trial and evaluation laboratory (DEMATEL) technique is adopted to build an interactive network and visualize the causal relationships between the performance indicators. Finally, an empirical case study is provided to demonstrate the proposed approach for improving the efficiency of healthcare management. The results show that "accidents/adverse events", "nosocomial infection", ''incidents/errors", "number of operations/procedures" are significant influential indicators. Also, the indicators of "length of stay", "bed occupancy" and "financial measures" play important roles in performance evaluation of the healthcare organization. The proposed decision making approach could be considered as a reference for healthcare administrators to enhance the performance of their healthcare institutions.

  10. A User Centered Innovation Approach Identifying Key User Values for the E-Newspaper

    OpenAIRE

    Carina Ihlström Eriksson; Jesper Svensson

    2009-01-01

    We have studied the pre-adoption phase of the e-newspaper, i.e. a newspaper published with e-paper technology. The research question of this article is: In what way can a user centered innovation process contribute to identifying key values in mobile innovations? The aim of this article is threefold: firstly, to identify key values for the e-newspaper, secondly, to examine the intention to adopt a new possible innovation and thirdly, to explore user centered design processes ability to captur...

  11. Ebola Virus Infection Modelling and Identifiability Problems

    Directory of Open Access Journals (Sweden)

    Van-Kinh eNguyen

    2015-04-01

    Full Text Available The recent outbreaks of Ebola virus (EBOV infections have underlined the impact of the virus as a major threat for human health. Due to the high biosafety classification of EBOV (level 4, basic research is very limited. Therefore, the development of new avenues of thinking to advance quantitative comprehension of the virus and its interaction with the host cells is urgently neededto tackle this lethal disease. Mathematical modelling of the EBOV dynamics can be instrumental to interpret Ebola infection kinetics on quantitative grounds. To the best of our knowledge, a mathematical modelling approach to unravel the interaction between EBOV and the host cells isstill missing. In this paper, a mathematical model based on differential equations is used to represent the basic interactions between EBOV and wild-type Vero cells in vitro. Parameter sets that represent infectivity of pathogens are estimated for EBOV infection and compared with influenza virus infection kinetics. The average infecting time of wild-type Vero cells in EBOV is slower than in influenza infection. Simulation results suggest that the slow infecting time of EBOV could be compensated by its efficient replication. This study reveals several identifiability problems and what kind of experiments are necessary to advance the quantification of EBOV infection. A first mathematical approach of EBOV dynamics and the estimation of standard parametersin viral infections kinetics is the key contribution of this work, paving the way for future modelling work on EBOV infection.

  12. Experimental infections with Mycoplasma agalactiae identify key factors involved in host-colonization.

    Directory of Open Access Journals (Sweden)

    Eric Baranowski

    Full Text Available Mechanisms underlying pathogenic processes in mycoplasma infections are poorly understood, mainly because of limited sequence similarities with classical, bacterial virulence factors. Recently, large-scale transposon mutagenesis in the ruminant pathogen Mycoplasma agalactiae identified the NIF locus, including nifS and nifU, as essential for mycoplasma growth in cell culture, while dispensable in axenic media. To evaluate the importance of this locus in vivo, the infectivity of two knock-out mutants was tested upon experimental infection in the natural host. In this model, the parental PG2 strain was able to establish a systemic infection in lactating ewes, colonizing various body sites such as lymph nodes and the mammary gland, even when inoculated at low doses. In these PG2-infected ewes, we observed over the course of infection (i the development of a specific antibody response and (ii dynamic changes in expression of M. agalactiae surface variable proteins (Vpma, with multiple Vpma profiles co-existing in the same animal. In contrast and despite a sensitive model, none of the knock-out mutants were able to survive and colonize the host. The extreme avirulent phenotype of the two mutants was further supported by the absence of an IgG response in inoculated animals. The exact role of the NIF locus remains to be elucidated but these data demonstrate that it plays a key role in the infectious process of M. agalactiae and most likely of other pathogenic mycoplasma species as many carry closely related homologs.

  13. Identifying the impacts of climate change on key pests and diseases of plant and animal industries

    International Nuclear Information System (INIS)

    Luck, Jo; Aurambout, Jean-Philippe; Finlay, Kyla; Azuloas, Joe; Constable, Fiona; Rijswijk, Bonny Rowles-Van

    2007-01-01

    Full text: Full text: Climate change is increasingly recognised as a major threat to natural and agricultural systems. Understanding these threats will enable government and primary industries to better prepare and adapt to climate change. While observations of climate change are well documented, the potential effects on pests, pathogens and their hosts are not clearly understood. To address this, a review of the potential impacts on plant biosecurity was undertaken to determine the effects of climate change on the behaviour and distribution of emergent plant pests and pathogens. The review identified increasing C02 and temperature, decreasing frost events, heavy and unseasonal rains, increased humidity, drought, cyclones and hurricanes, and warmer winter temperatures as influencing the behaviour of plant pests and pathogens. To study the effects of these changes in detail, three key plant biosecurity threats were analysed in case studies; wheat stripe rust, silver leaf whitefly and citrus canker. The predicted distribution of citrus canker was examined with increasing temperature scenarios using the bioclimatic model CLIMEX. The model predicted a southerly shift in the geographic range of the causal organism which would threaten the major southern citrus growing regions in future climates. A similar study on Bluetongue disease of sheep, spread by the Culicoides midge, also predicted a southerly shift in the vector's geographic range. Significant limitations were identified with bioclimatic modelling when examining the effects of climate change on pests and diseases. The model was unable to assess the plant and animal response to increasing temperature in conjunction with the pest. Also the influence of temperature on the life cycle of the organism, pathogenicity of strains, competition with other species, host coverage and the general effect on the biology of the organism could not be assessed. To begin to address this, a dynamic model was constructed using daily

  14. Key Questions in Building Defect Prediction Models in Practice

    Science.gov (United States)

    Ramler, Rudolf; Wolfmaier, Klaus; Stauder, Erwin; Kossak, Felix; Natschläger, Thomas

    The information about which modules of a future version of a software system are defect-prone is a valuable planning aid for quality managers and testers. Defect prediction promises to indicate these defect-prone modules. However, constructing effective defect prediction models in an industrial setting involves a number of key questions. In this paper we discuss ten key questions identified in context of establishing defect prediction in a large software development project. Seven consecutive versions of the software system have been used to construct and validate defect prediction models for system test planning. Furthermore, the paper presents initial empirical results from the studied project and, by this means, contributes answers to the identified questions.

  15. Key Issues in Empirically Identifying Chronically Low-Performing and Turnaround Schools

    Science.gov (United States)

    Hansen, Michael

    2012-01-01

    One of the US Department of Education's key priorities is turning around the nation's persistently low-achieving schools, yet exactly how to identify low-performing schools is a task left to state policy makers, and a myriad of definitions have been utilized. In addition, exactly how to recognize when a school begins to turn around is not well…

  16. Integrated systems approach identifies risk regulatory pathways and key regulators in coronary artery disease.

    Science.gov (United States)

    Zhang, Yan; Liu, Dianming; Wang, Lihong; Wang, Shuyuan; Yu, Xuexin; Dai, Enyu; Liu, Xinyi; Luo, Shanshun; Jiang, Wei

    2015-12-01

    Coronary artery disease (CAD) is the most common type of heart disease. However, the molecular mechanisms of CAD remain elusive. Regulatory pathways are known to play crucial roles in many pathogenic processes. Thus, inferring risk regulatory pathways is an important step toward elucidating the mechanisms underlying CAD. With advances in high-throughput data, we developed an integrated systems approach to identify CAD risk regulatory pathways and key regulators. Firstly, a CAD-related core subnetwork was identified from a curated transcription factor (TF) and microRNA (miRNA) regulatory network based on a random walk algorithm. Secondly, candidate risk regulatory pathways were extracted from the subnetwork by applying a breadth-first search (BFS) algorithm. Then, risk regulatory pathways were prioritized based on multiple CAD-associated data sources. Finally, we also proposed a new measure to prioritize upstream regulators. We inferred that phosphatase and tensin homolog (PTEN) may be a key regulator in the dysregulation of risk regulatory pathways. This study takes a closer step than the identification of disease subnetworks or modules. From the risk regulatory pathways, we could understand the flow of regulatory information in the initiation and progression of the disease. Our approach helps to uncover its potential etiology. We developed an integrated systems approach to identify risk regulatory pathways. We proposed a new measure to prioritize the key regulators in CAD. PTEN may be a key regulator in dysregulation of the risk regulatory pathways.

  17. Identifiability of PBPK Models with Applications to ...

    Science.gov (United States)

    Any statistical model should be identifiable in order for estimates and tests using it to be meaningful. We consider statistical analysis of physiologically-based pharmacokinetic (PBPK) models in which parameters cannot be estimated precisely from available data, and discuss different types of identifiability that occur in PBPK models and give reasons why they occur. We particularly focus on how the mathematical structure of a PBPK model and lack of appropriate data can lead to statistical models in which it is impossible to estimate at least some parameters precisely. Methods are reviewed which can determine whether a purely linear PBPK model is globally identifiable. We propose a theorem which determines when identifiability at a set of finite and specific values of the mathematical PBPK model (global discrete identifiability) implies identifiability of the statistical model. However, we are unable to establish conditions that imply global discrete identifiability, and conclude that the only safe approach to analysis of PBPK models involves Bayesian analysis with truncated priors. Finally, computational issues regarding posterior simulations of PBPK models are discussed. The methodology is very general and can be applied to numerous PBPK models which can be expressed as linear time-invariant systems. A real data set of a PBPK model for exposure to dimethyl arsinic acid (DMA(V)) is presented to illustrate the proposed methodology. We consider statistical analy

  18. Soil fauna: key to new carbon models

    NARCIS (Netherlands)

    Filser, Juliane; Faber, J.H.; Tiunov, Alexei V.; Brussaard, L.; Frouz, J.; Deyn, de G.B.; Uvarov, Alexei V.; Berg, Matty P.; Lavelle, Patrick; Loreau, M.; Wall, D.H.; Querner, Pascal; Eijsackers, Herman; Jimenez, Juan Jose

    2016-01-01

    Soil organic matter (SOM) is key to maintaining soil fertility, mitigating climate change, combatting land degradation, and conserving above- and below-ground biodiversity and associated soil processes and ecosystem services. In order to derive management options for maintaining these essential

  19. Iterative key-residues interrogation of a phytase with thermostability increasing substitutions identified in directed evolution.

    Science.gov (United States)

    Shivange, Amol V; Roccatano, Danilo; Schwaneberg, Ulrich

    2016-01-01

    Bacterial phytases have attracted industrial interest as animal feed supplement due to their high activity and sufficient thermostability (required for feed pelleting). We devised an approach named KeySIDE,  an iterative Key-residues interrogation of the wild type with Substitutions Identified in Directed Evolution for improving Yersinia mollaretii phytase (Ymphytase) thermostability by combining key beneficial substitutions and elucidating their individual roles. Directed evolution yielded in a discovery of nine positions in Ymphytase and combined iteratively to identify key positions. The "best" combination (M6: T77K, Q154H, G187S, and K289Q) resulted in significantly improved thermal resistance; the residual activity improved from 35 % (wild type) to 89 % (M6) at 58 °C and 20-min incubation. Melting temperature increased by 3 °C in M6 without a loss of specific activity. Molecular dynamics simulation studies revealed reduced flexibility in the loops located next to helices (B, F, and K) which possess substitutions (Helix-B: T77K, Helix-F: G187S, and Helix-K: K289E/Q). Reduced flexibility in the loops might be caused by strengthened hydrogen bonding network (e.g., G187S and K289E/K289Q) and a salt bridge (T77K). Our results demonstrate a promising approach to design phytases in food research, and we hope that the KeySIDE might become an attractive approach for understanding of structure-function relationships of enzymes.

  20. Structural Identifiability of Dynamic Systems Biology Models.

    Science.gov (United States)

    Villaverde, Alejandro F; Barreiro, Antonio; Papachristodoulou, Antonis

    2016-10-01

    A powerful way of gaining insight into biological systems is by creating a nonlinear differential equation model, which usually contains many unknown parameters. Such a model is called structurally identifiable if it is possible to determine the values of its parameters from measurements of the model outputs. Structural identifiability is a prerequisite for parameter estimation, and should be assessed before exploiting a model. However, this analysis is seldom performed due to the high computational cost involved in the necessary symbolic calculations, which quickly becomes prohibitive as the problem size increases. In this paper we show how to analyse the structural identifiability of a very general class of nonlinear models by extending methods originally developed for studying observability. We present results about models whose identifiability had not been previously determined, report unidentifiabilities that had not been found before, and show how to modify those unidentifiable models to make them identifiable. This method helps prevent problems caused by lack of identifiability analysis, which can compromise the success of tasks such as experiment design, parameter estimation, and model-based optimization. The procedure is called STRIKE-GOLDD (STRuctural Identifiability taKen as Extended-Generalized Observability with Lie Derivatives and Decomposition), and it is implemented in a MATLAB toolbox which is available as open source software. The broad applicability of this approach facilitates the analysis of the increasingly complex models used in systems biology and other areas.

  1. Identifying key performance indicators for nursing and midwifery care using a consensus approach.

    Science.gov (United States)

    McCance, Tanya; Telford, Lorna; Wilson, Julie; Macleod, Olive; Dowd, Audrey

    2012-04-01

    The aim of this study was to gain consensus on key performance indicators that are appropriate and relevant for nursing and midwifery practice in the current policy context. There is continuing demand to demonstrate effectiveness and efficiency in health and social care and to communicate this at boardroom level. Whilst there is substantial literature on the use of clinical indicators and nursing metrics, there is less evidence relating to indicators that reflect the patient experience. A consensus approach was used to identify relevant key performance indicators. A nominal group technique was used comprising two stages: a workshop involving all grades of nursing and midwifery staff in two HSC trusts in Northern Ireland (n = 50); followed by a regional Consensus Conference (n = 80). During the workshop, potential key performance indicators were identified. This was used as the basis for the Consensus Conference, which involved two rounds of consensus. Analysis was based on aggregated scores that were then ranked. Stage one identified 38 potential indicators and stage two prioritised the eight top-ranked indicators as a core set for nursing and midwifery. The relevance and appropriateness of these indicators were confirmed with nurses and midwives working in a range of settings and from the perspective of service users. The eight indicators identified do not conform to the majority of other nursing metrics generally reported in the literature. Furthermore, they are strategically aligned to work on the patient experience and are reflective of the fundamentals of nursing and midwifery practice, with the focus on person-centred care. Nurses and midwives have a significant contribution to make in determining the extent to which these indicators are achieved in practice. Furthermore, measurement of such indicators provides an opportunity to evidence of the unique impact of nursing/midwifery care on the patient experience. © 2011 Blackwell Publishing Ltd.

  2. Postsecondary Students With Psychiatric Disabilities Identify Core Services and Key Ingredients to Supporting Education Goals.

    Science.gov (United States)

    Biebel, Kathleen; Mizrahi, Raphael; Ringeisen, Heather

    2017-10-26

    Accessing and successfully completing postsecondary educational opportunities may be challenging for those living with psychiatric disabilities. This exploratory study highlights the experiences of individuals with psychiatric disabilities participating in postsecondary educational support initiatives. Investigators conducted case studies with 3 education support initiatives across the United States. Focus groups revealed what concrete supported education services were helpful and key ingredients in delivering education supports. Access to specialists, mindfulness techniques, help with time management and procrastination, and facilitating classroom accommodations were identified as critical. Developing authentic relationships with supported education staff, flexibility in service delivery and access to student peers living with psychiatric disabilities were noted as key ingredients in service delivery. Incorporating the voice of students with psychiatric disabilities into supported education services can increase access, involvement, and retention, therein providing more supports to students with psychiatric disabilities achieving their postsecondary education goals. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  3. Methods of Developing User-Friendly Keys to Identify Green Sea Turtles (Chelonia mydas L. from Photographs

    Directory of Open Access Journals (Sweden)

    Jane R. Lloyd

    2012-01-01

    Full Text Available Identifying individual animals is important in understanding their ecology and behaviour, as well as providing estimates of population sizes for conservation efforts. We produce identification keys from photographs of green sea turtles to identify them while foraging in Akumal Bay, Mexico. We create three keys, which (a minimise the length of the key, (b present the most obvious differential characteristics first, and (c remove the strict dichotomy from key b. Keys were capable of identifying >99% of turtles in >2500 photographs during the six-month study period. The keys differed significantly in success rate for students to identify individual turtles, with key (c being the best with >70% success and correctly being followed further than other keys before making a mistake. User-friendly keys are, therefore, a suitable method for the photographic identification of turtles and could be used for other large marine vertebrates in conservation or behavioural studies.

  4. Identifying optimal models to represent biochemical systems.

    Directory of Open Access Journals (Sweden)

    Mochamad Apri

    Full Text Available Biochemical systems involving a high number of components with intricate interactions often lead to complex models containing a large number of parameters. Although a large model could describe in detail the mechanisms that underlie the system, its very large size may hinder us in understanding the key elements of the system. Also in terms of parameter identification, large models are often problematic. Therefore, a reduced model may be preferred to represent the system. Yet, in order to efficaciously replace the large model, the reduced model should have the same ability as the large model to produce reliable predictions for a broad set of testable experimental conditions. We present a novel method to extract an "optimal" reduced model from a large model to represent biochemical systems by combining a reduction method and a model discrimination method. The former assures that the reduced model contains only those components that are important to produce the dynamics observed in given experiments, whereas the latter ensures that the reduced model gives a good prediction for any feasible experimental conditions that are relevant to answer questions at hand. These two techniques are applied iteratively. The method reveals the biological core of a model mathematically, indicating the processes that are likely to be responsible for certain behavior. We demonstrate the algorithm on two realistic model examples. We show that in both cases the core is substantially smaller than the full model.

  5. GuiaTreeKey, a multi-access electronic key to identify tree genera in French Guiana

    OpenAIRE

    Brousseau, Louise; Baraloto, Christopher

    2016-01-01

    The tropical rainforest of Amazonia is one of the most species-rich ecosystems on earth, with an estimated 16000 tree species. Due to this high diversity, botanical identification of trees in the Amazon is difficult, even to genus, often requiring the assistance of parataxonomists or taxonomic specialists. Advances in informatics tools offer a promising opportunity to develop user-friendly electronic keys to improve Amazonian tree identification. Here, we introduce an original mult...

  6. GuiaTreeKey, a multi-access electronic key to identify tree genera in French Guiana.

    Science.gov (United States)

    Engel, Julien; Brousseau, Louise; Baraloto, Christopher

    2016-01-01

    The tropical rainforest of Amazonia is one of the most species-rich ecosystems on earth, with an estimated 16000 tree species. Due to this high diversity, botanical identification of trees in the Amazon is difficult, even to genus, often requiring the assistance of parataxonomists or taxonomic specialists. Advances in informatics tools offer a promising opportunity to develop user-friendly electronic keys to improve Amazonian tree identification. Here, we introduce an original multi-access electronic key for the identification of 389 tree genera occurring in French Guiana terra-firme forests, based on a set of 79 morphological characters related to vegetative, floral and fruit characters. Its purpose is to help Amazonian tree identification and to support the dissemination of botanical knowledge to non-specialists, including forest workers, students and researchers from other scientific disciplines. The electronic key is accessible with the free access software Xper ², and the database is publicly available on figshare: https://figshare.com/s/75d890b7d707e0ffc9bf (doi: 10.6084/m9.figshare.2682550).

  7. Coherence method of identifying signal noise model

    International Nuclear Information System (INIS)

    Vavrin, J.

    1981-01-01

    The noise analysis method is discussed in identifying perturbance models and their parameters by a stochastic analysis of the noise model of variables measured on a reactor. The analysis of correlations is made in the frequency region using coherence analysis methods. In identifying an actual specific perturbance, its model should be determined and recognized in a compound model of the perturbance system using the results of observation. The determination of the optimum estimate of the perturbance system model is based on estimates of related spectral densities which are determined from the spectral density matrix of the measured variables. Partial and multiple coherence, partial transfers, the power spectral densities of the input and output variables of the noise model are determined from the related spectral densities. The possibilities of applying the coherence identification methods were tested on a simple case of a simulated stochastic system. Good agreement was found of the initial analytic frequency filters and the transfers identified. (B.S.)

  8. Identifying and characterizing key nodes among communities based on electrical-circuit networks.

    Science.gov (United States)

    Zhu, Fenghui; Wang, Wenxu; Di, Zengru; Fan, Ying

    2014-01-01

    Complex networks with community structures are ubiquitous in the real world. Despite many approaches developed for detecting communities, we continue to lack tools for identifying overlapping and bridging nodes that play crucial roles in the interactions and communications among communities in complex networks. Here we develop an algorithm based on the local flow conservation to effectively and efficiently identify and distinguish the two types of nodes. Our method is applicable in both undirected and directed networks without a priori knowledge of the community structure. Our method bypasses the extremely challenging problem of partitioning communities in the presence of overlapping nodes that may belong to multiple communities. Due to the fact that overlapping and bridging nodes are of paramount importance in maintaining the function of many social and biological networks, our tools open new avenues towards understanding and controlling real complex networks with communities accompanied with the key nodes.

  9. Identifying and weighting of key performance indicators of knowledge management2.0 in organizations

    Directory of Open Access Journals (Sweden)

    Saeed Khalilazar

    2016-03-01

    Full Text Available Main purpose of this research is identifying and weighting of key performance indicators of knowledge management2.0 in organizations. According to widespread permeation of technology, especially social media in different organizational dimensions and functional view to this phenomenon in knowledge management, performance measurement of this kind of media in order to meet organizational goals seems necessary. KM2.0 key performance indicators in this article has been identified and weighted through Delphi methodology, via questionnaire in three rounds. KM2.0 KPIs which are identified and weighted in this article are applicable in organizations that are eager to implement KM2.0 initiative and they can measure the performance of KM2.0 activities therefore this research is applicable in goal oriented approach. According to the results, KM2.0 participation process consists of 3 stages and 8 steps as mentioned below: First stage which is presence, consists of 3 steps which are registration, visit and download. Second stage which is feedback consists of 3 steps which are conversation, applause and amplification. Finally, third stage which is creation consists of 2 steps which are codification and personalization. Ultimate contribution of this research is identifying and weighting KPIs of KM2.0 in conceptual framework of KM2.0. Based on developing a conceptual framework and participation process in KM2.0 and listing related KPIs as an applicable solution in order to measure and improve the performance of organizational social media, this research has unique innovation among related and other articles.

  10. Key West, Florida Tsunami Forecast Grids for MOST Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Key West, Florida Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model. MOST...

  11. Exploiting intrinsic fluctuations to identify model parameters.

    Science.gov (United States)

    Zimmer, Christoph; Sahle, Sven; Pahle, Jürgen

    2015-04-01

    Parameterisation of kinetic models plays a central role in computational systems biology. Besides the lack of experimental data of high enough quality, some of the biggest challenges here are identification issues. Model parameters can be structurally non-identifiable because of functional relationships. Noise in measured data is usually considered to be a nuisance for parameter estimation. However, it turns out that intrinsic fluctuations in particle numbers can make parameters identifiable that were previously non-identifiable. The authors present a method to identify model parameters that are structurally non-identifiable in a deterministic framework. The method takes time course recordings of biochemical systems in steady state or transient state as input. Often a functional relationship between parameters presents itself by a one-dimensional manifold in parameter space containing parameter sets of optimal goodness. Although the system's behaviour cannot be distinguished on this manifold in a deterministic framework it might be distinguishable in a stochastic modelling framework. Their method exploits this by using an objective function that includes a measure for fluctuations in particle numbers. They show on three example models, immigration-death, gene expression and Epo-EpoReceptor interaction, that this resolves the non-identifiability even in the case of measurement noise with known amplitude. The method is applied to partially observed recordings of biochemical systems with measurement noise. It is simple to implement and it is usually very fast to compute. This optimisation can be realised in a classical or Bayesian fashion.

  12. Identifying Regional Key Eco-Space to Maintain Ecological Security Using GIS

    Directory of Open Access Journals (Sweden)

    Hualin Xie

    2014-02-01

    Full Text Available Ecological security and environmental sustainability are the foundations of sustainable development. With the acceleration of urbanization, increasing human activities have promoted greater impacts on the eco-spaces that maintain ecological security. Regional key eco-space has become the primary need to maintain environmental sustainability and can offer society with continued ecosystem services. In this paper, considering the security of water resources, biodiversity conservation, disaster avoidance and protection and natural recreation, an integrated index of eco-space importance was established and a method for identifying key eco-space was created using GIS, with Lanzhou City, China as a case study. The results show that the area of core eco-space in the Lanzhou City is approximately 50,908.7 hm2, accounting for 40% of the region’s total area. These areas mainly consist of geological hazard protection zones and the core zones of regional river systems, wetlands, nature reserves, forest parks and scenic spots. The results of this study provide some guidance for the management of ecological security, ecological restoration and environmental sustainability.

  13. [Key effect genes responding to nerve injury identified by gene ontology and computer pattern recognition].

    Science.gov (United States)

    Pan, Qian; Peng, Jin; Zhou, Xue; Yang, Hao; Zhang, Wei

    2012-07-01

    In order to screen out important genes from large gene data of gene microarray after nerve injury, we combine gene ontology (GO) method and computer pattern recognition technology to find key genes responding to nerve injury, and then verify one of these screened-out genes. Data mining and gene ontology analysis of gene chip data GSE26350 was carried out through MATLAB software. Cd44 was selected from screened-out key gene molecular spectrum by comparing genes' different GO terms and positions on score map of principal component. Function interferences were employed to influence the normal binding of Cd44 and one of its ligands, chondroitin sulfate C (CSC), to observe neurite extension. Gene ontology analysis showed that the first genes on score map (marked by red *) mainly distributed in molecular transducer activity, receptor activity, protein binding et al molecular function GO terms. Cd44 is one of six effector protein genes, and attracted us with its function diversity. After adding different reagents into the medium to interfere the normal binding of CSC and Cd44, varying-degree remissions of CSC's inhibition on neurite extension were observed. CSC can inhibit neurite extension through binding Cd44 on the neuron membrane. This verifies that important genes in given physiological processes can be identified by gene ontology analysis of gene chip data.

  14. Identifying key areas for active interprofessional learning partnerships: A facilitated dialogue.

    Science.gov (United States)

    Steven, Kathryn; Angus, Allyson; Breckenridge, Jenna; Davey, Peter; Tully, Vicki; Muir, Fiona

    2016-11-01

    Student and service user involvement is recognised as an important factor in creating interprofessional education (IPE) opportunities. We used a team-based learning approach to bring together undergraduate health professional students, early career professionals (ECPs), public partners, volunteers, and carers to explore learning partnerships. Influenced by evaluative inquiry, this qualitative study used a free text response to allow participants to give their own opinion. A total of 153 participants (50 public partners and 103 students and professionals representing 11 healthcare professions) took part. Participants were divided into mixed groups of six (n = 25) and asked to identify areas where students, professionals, and public could work together to improve health professional education. Each group documented their discussions by summarising agreed areas and next steps. Responses were collected and transcribed for inductive content analysis. Seven key themes (areas for joint working) were identified: communication, public as partners, standards of conduct, IPE, quality improvement, education, and learning environments. The team-based learning format enabled undergraduate and postgraduate health professionals to achieve consensus with public partners on areas for IPE and collaboration. Some of our results may be context-specific but the approach is generalisable to other areas.

  15. Key identifiers and spelling conventions in MXit-lingo as found in conversations with Dr Math

    Directory of Open Access Journals (Sweden)

    Laurie Butgereit

    2012-07-01

    Full Text Available Different human languages look different from other human languages. To use a term from the computer industry, each human language has its own “look and feel”. European English speakers can easily recognise a phrase such as “Comment allez-vous?” as being written in French while the phrase “¿Habla usted español?” is written in Spanish. Each language has its own letter frequencies, word frequencies and other identifiers. This paper describes key identifiers in MXit lingo as found in Dr Math conversations. MXit is a mobile instant messaging system which originated in South Africa and is expanding to other countries. Dr Math is a mobile tutoring system which uses MXit as a communication protocol. Primary and secondary school pupils can receive help with the mathematics homework using the Dr Math tutoring system. The pupils use MXit on their cell phones and the tutors use traditional Internet workstations. After exploring how MXit lingo is written, this paper will briefly explore why MXit lingo is written the way it is. By identifying and describing the orthographic conventions visible in the spelling of MXit lingo, although with some theoretical support, insight into the purposeful and functional nature of written, mobile communication will be revealed. In highlighting spelling that is influenced by Black South African English, an attempt will be made to contribute to the empirical development of a field of study that explores the construction of words used in South African mobile communication. Keywords: MXit, Math, letters, writing, orthography Disciplines: Linguistics, mathematics, information technology

  16. Framework for Identifying Key Environmental Concerns in Marine Renewable Energy Projects- Appendices

    Energy Technology Data Exchange (ETDEWEB)

    Kramer, Sharon; Previsic, Mirko; Nelson, Peter; Woo, Sheri

    2010-06-17

    Marine wave and tidal energy technology could interact with marine resources in ways that are not well understood. As wave and tidal energy conversion projects are planned, tested, and deployed, a wide range of stakeholders will be engaged; these include developers, state and federal regulatory agencies, environmental groups, tribal governments, recreational and commercial fishermen, and local communities. Identifying stakeholders’ environmental concerns in the early stages of the industry’s development will help developers address and minimize potential environmental effects. Identifying important concerns will also assist with streamlining siting and associated permitting processes, which are considered key hurdles by the industry in the U.S. today. In September 2008, RE Vision consulting, LLC was selected by the Department of Energy (DoE) to conduct a scenario-based evaluation of emerging hydrokinetic technologies. The purpose of this evaluation is to identify and characterize environmental impacts that are likely to occur, demonstrate a process for analyzing these impacts, identify the “key” environmental concerns for each scenario, identify areas of uncertainty, and describe studies that could address that uncertainty. This process is intended to provide an objective and transparent tool to assist in decision-making for siting and selection of technology for wave and tidal energy development. RE Vision worked with H. T. Harvey & Associates, to develop a framework for identifying key environmental concerns with marine renewable technology. This report describes the results of this study. This framework was applied to varying wave and tidal power conversion technologies, scales, and locations. The following wave and tidal energy scenarios were considered: 4 wave energy generation technologies 3 tidal energy generation technologies 3 sites: Humboldt coast, California (wave); Makapu’u Point, Oahu, Hawaii (wave); and the Tacoma Narrows, Washington (tidal

  17. Identify and rank key factors influencing the adoption of cloud computing for a healthy Electronics

    Directory of Open Access Journals (Sweden)

    Javad Shukuhy

    2015-02-01

    Full Text Available Cloud computing as a new technology with Internet infrastructure and new approaches can be significant benefits in providing medical services electronically. Aplying this technology in E-Health requires consideration of various factors. The main objective of this study is to identify and rank the factors influencing the adoption of e-health cloud. Based on the Technology-Organization-Environment (TOE framework and Human-Organization-Technology fit (HOT-fit model, 16 sub-factors were identified in four major factors. With survey of 60 experts, academics and experts in health information technology and with the help of fuzzy analytic hierarchy process had ranked these sub-factors and factors. In the literature, considering newness this study, no internal or external study, have not alluded these number of criteria. The results show that when deciding to adopt cloud computing in E-Health, respectively, must be considered technological, human, organizational and environmental factors.

  18. Orthognathic model surgery with LEGO key-spacer.

    Science.gov (United States)

    Tsang, Alfred Chee-Ching; Lee, Alfred Siu Hong; Li, Wai Keung

    2013-12-01

    A new technique of model surgery using LEGO plates as key-spacers is described. This technique requires less time to set up compared with the conventional plaster model method. It also retains the preoperative setup with the same set of models. Movement of the segments can be measured and examined in detail with LEGO key-spacers. Copyright © 2013 American Association of Oral and Maxillofacial Surgeons. Published by Elsevier Inc. All rights reserved.

  19. Predicting suicidal ideation in primary care: An approach to identify easily assessable key variables.

    Science.gov (United States)

    Jordan, Pascal; Shedden-Mora, Meike C; Löwe, Bernd

    To obtain predictors of suicidal ideation, which can also be used for an indirect assessment of suicidal ideation (SI). To create a classifier for SI based on variables of the Patient Health Questionnaire (PHQ) and sociodemographic variables, and to obtain an upper bound on the best possible performance of a predictor based on those variables. From a consecutive sample of 9025 primary care patients, 6805 eligible patients (60% female; mean age = 51.5 years) participated. Advanced methods of machine learning were used to derive the prediction equation. Various classifiers were applied and the area under the curve (AUC) was computed as a performance measure. Classifiers based on methods of machine learning outperformed ordinary regression methods and achieved AUCs around 0.87. The key variables in the prediction equation comprised four items - namely feelings of depression/hopelessness, low self-esteem, worrying, and severe sleep disturbances. The generalized anxiety disorder scale (GAD-7) and the somatic symptom subscale (PHQ-15) did not enhance prediction substantially. In predicting suicidal ideation researchers should refrain from using ordinary regression tools. The relevant information is primarily captured by the depression subscale and should be incorporated in a nonlinear model. For clinical practice, a classification tree using only four items of the whole PHQ may be advocated. Copyright © 2018 Elsevier Inc. All rights reserved.

  20. Identifying Key Features of Effective Active Learning: The Effects of Writing and Peer Discussion

    Science.gov (United States)

    Pangle, Wiline M.; Wyatt, Kevin H.; Powell, Karli N.; Sherwood, Rachel E.

    2014-01-01

    We investigated some of the key features of effective active learning by comparing the outcomes of three different methods of implementing active-learning exercises in a majors introductory biology course. Students completed activities in one of three treatments: discussion, writing, and discussion + writing. Treatments were rotated weekly between three sections taught by three different instructors in a full factorial design. The data set was analyzed by generalized linear mixed-effect models with three independent variables: student aptitude, treatment, and instructor, and three dependent (assessment) variables: change in score on pre- and postactivity clicker questions, and coding scores on in-class writing and exam essays. All independent variables had significant effects on student performance for at least one of the dependent variables. Students with higher aptitude scored higher on all assessments. Student scores were higher on exam essay questions when the activity was implemented with a writing component compared with peer discussion only. There was a significant effect of instructor, with instructors showing different degrees of effectiveness with active-learning techniques. We suggest that individual writing should be implemented as part of active learning whenever possible and that instructors may need training and practice to become effective with active learning. PMID:25185230

  1. Practical Implementation of Various Public Key Infrastructure Models

    Directory of Open Access Journals (Sweden)

    Dmitriy Anatolievich Melnikov

    2016-03-01

    Full Text Available The paper proposes a short comparative analysis of the contemporary models of public key infrastructure (PKI and the issues of the PKI models real implementation. The Russian model of PKI is presented. Differences between the North American and West Europe models of PKI and Russian model of PKI are described. The problems of creation and main directions of further development and improvement of the Russian PKI and its integration into the global trust environment are defined.

  2. Key performance indicators in hospital based on balanced scorecard model

    Directory of Open Access Journals (Sweden)

    Hamed Rahimi

    2017-01-01

    Full Text Available Introduction: Performance measurement is receiving increasing verification all over the world. Nowadays in a lot of organizations, irrespective of their type or size, performance evaluation is the main concern and a key issue for top administrators. The purpose of this study is to organize suitable key performance indicators (KPIs for hospitals’ performance evaluation based on the balanced scorecard (BSC. Method: This is a mixed method study. In order to identify the hospital’s performance indicators (HPI, first related literature was reviewed and then the experts’ panel and Delphi method were used. In this study, two rounds were needed for the desired level of consensus. The experts rated the importance of the indicators, on a five-point Likert scale. In the consensus calculation, the consensus percentage was calculated by classifying the values 1-3 as not important (0 and 4-5 to (1 as important. Simple additive weighting technique was used to rank the indicators and select hospital’s KPIs. The data were analyzed by Excel 2010 software. Results: About 218 indicators were obtained from a review of selected literature. Through internal expert panel, 77 indicators were selected. Finally, 22 were selected for KPIs of hospitals. Ten indicators were selected in internal process perspective and 5, 4, and 3 indicators in finance, learning and growth, and customer, respectively. Conclusion: This model can be a useful tool for evaluating and comparing the performance of hospitals. However, this model is flexible and can be adjusted according to differences in the target hospitals. This study can be beneficial for hospital administrators and it can help them to change their perspective about performance evaluation.

  3. Identifying key features of effective active learning: the effects of writing and peer discussion.

    Science.gov (United States)

    Linton, Debra L; Pangle, Wiline M; Wyatt, Kevin H; Powell, Karli N; Sherwood, Rachel E

    2014-01-01

    We investigated some of the key features of effective active learning by comparing the outcomes of three different methods of implementing active-learning exercises in a majors introductory biology course. Students completed activities in one of three treatments: discussion, writing, and discussion + writing. Treatments were rotated weekly between three sections taught by three different instructors in a full factorial design. The data set was analyzed by generalized linear mixed-effect models with three independent variables: student aptitude, treatment, and instructor, and three dependent (assessment) variables: change in score on pre- and postactivity clicker questions, and coding scores on in-class writing and exam essays. All independent variables had significant effects on student performance for at least one of the dependent variables. Students with higher aptitude scored higher on all assessments. Student scores were higher on exam essay questions when the activity was implemented with a writing component compared with peer discussion only. There was a significant effect of instructor, with instructors showing different degrees of effectiveness with active-learning techniques. We suggest that individual writing should be implemented as part of active learning whenever possible and that instructors may need training and practice to become effective with active learning. © 2014 D. L. Linton et al. CBE—Life Sciences Education © 2014 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

  4. Rubella vaccination in India: identifying broad consequences of vaccine introduction and key knowledge gaps.

    Science.gov (United States)

    Winter, A K; Pramanik, S; Lessler, J; Ferrari, M; Grenfell, B T; Metcalf, C J E

    2018-01-01

    Rubella virus infection typically presents as a mild illness in children; however, infection during pregnancy may cause the birth of an infant with congenital rubella syndrome (CRS). As of February 2017, India began introducing rubella-containing vaccine (RCV) into the public-sector childhood vaccination programme. Low-level RCV coverage among children over several years can result in an increase in CRS incidence by increasing the average age of infection without sufficiently reducing rubella incidence. We evaluated the impact of RCV introduction on CRS incidence across India's heterogeneous demographic and epidemiological contexts. We used a deterministic age-structured model that reflects Indian states' rural and urban area-specific demography and vaccination coverage levels to simulate rubella dynamics and estimate CRS incidence with and without RCV introduction to the public sector. Our analysis suggests that current low-level private-sector vaccination has already slightly increased the burden of CRS in India. We additionally found that the effect of public-sector RCV introduction depends on the basic reproductive number, R 0, of rubella. If R 0 is five, a value empirically estimated from an array of settings, CRS incidence post-RCV introduction will likely decrease. However, if R 0 is seven or nine, some states may experience short-term or annual increases in CRS, even if a long-term total reduction in cases (30 years) is expected. Investment in population-based serological surveys and India's fever/rash surveillance system will be key to monitoring the success of the vaccination programme.

  5. Modeling key processes causing climate change and variability

    Energy Technology Data Exchange (ETDEWEB)

    Henriksson, S.

    2013-09-01

    Greenhouse gas warming, internal climate variability and aerosol climate effects are studied and the importance to understand these key processes and being able to separate their influence on the climate is discussed. Aerosol-climate model ECHAM5-HAM and the COSMOS millennium model consisting of atmospheric, ocean and carbon cycle and land-use models are applied and results compared to measurements. Topics at focus are climate sensitivity, quasiperiodic variability with a period of 50-80 years and variability at other timescales, climate effects due to aerosols over India and climate effects of northern hemisphere mid- and high-latitude volcanic eruptions. The main findings of this work are (1) pointing out the remaining challenges in reducing climate sensitivity uncertainty from observational evidence, (2) estimates for the amplitude of a 50-80 year quasiperiodic oscillation in global mean temperature ranging from 0.03 K to 0.17 K and for its phase progression as well as the synchronising effect of external forcing, (3) identifying a power law shape S(f) {proportional_to} f-{alpha} for the spectrum of global mean temperature with {alpha} {approx} 0.8 between multidecadal and El Nino timescales with a smaller exponent in modelled climate without external forcing, (4) separating aerosol properties and climate effects in India by season and location (5) the more efficient dispersion of secondary sulfate aerosols than primary carbonaceous aerosols in the simulations, (6) an increase in monsoon rainfall in northern India due to aerosol light absorption and a probably larger decrease due to aerosol dimming effects and (7) an estimate of mean maximum cooling of 0.19 K due to larger northern hemisphere mid- and high-latitude volcanic eruptions. The results could be applied or useful in better isolating the human-caused climate change signal, in studying the processes further and in more detail, in decadal climate prediction, in model evaluation and in emission policy

  6. Model of key success factors for Business Intelligence implementation

    Directory of Open Access Journals (Sweden)

    Peter Mesaros

    2016-07-01

    Full Text Available New progressive technologies recorded growth in every area. Information-communication technologies facilitate the exchange of information and it facilitates management of everyday activities in enterprises. Specific modules (such as Business Intelligence facilitate decision-making. Several studies have demonstrated the positive impact of Business Intelligence to decision-making. The first step is to put in place the enterprise. The implementation process is influenced by many factors. This article discusses the issue of key success factors affecting to successful implementation of Business Intelligence. The article describes the key success factors for successful implementation and use of Business Intelligence based on multiple studies. The main objective of this study is to verify the effects and dependence of selected factors and proposes a model of key success factors for successful implementation of Business Intelligence. Key success factors and the proposed model are studied in Slovak enterprises.

  7. Summary on several key techniques in 3D geological modeling.

    Science.gov (United States)

    Mei, Gang

    2014-01-01

    Several key techniques in 3D geological modeling including planar mesh generation, spatial interpolation, and surface intersection are summarized in this paper. Note that these techniques are generic and widely used in various applications but play a key role in 3D geological modeling. There are two essential procedures in 3D geological modeling: the first is the simulation of geological interfaces using geometric surfaces and the second is the building of geological objects by means of various geometric computations such as the intersection of surfaces. Discrete geometric surfaces that represent geological interfaces can be generated by creating planar meshes first and then spatially interpolating; those surfaces intersect and then form volumes that represent three-dimensional geological objects such as rock bodies. In this paper, the most commonly used algorithms of the key techniques in 3D geological modeling are summarized.

  8. Spatial age-length key modelling using continuation ratio logits

    DEFF Research Database (Denmark)

    Berg, Casper W.; Kristensen, Kasper

    2012-01-01

    -called age-length key (ALK) is then used to obtain the age distribution. Regional differences in ALKs are not uncommon, but stratification is often problematic due to a small number of samples. Here, we combine generalized additive modelling with continuation ratio logits to model the probability of age...

  9. Identifying Key Features of Student Performance in Educational Video Games and Simulations through Cluster Analysis

    Science.gov (United States)

    Kerr, Deirdre; Chung, Gregory K. W. K.

    2012-01-01

    The assessment cycle of "evidence-centered design" (ECD) provides a framework for treating an educational video game or simulation as an assessment. One of the main steps in the assessment cycle of ECD is the identification of the key features of student performance. While this process is relatively simple for multiple choice tests, when…

  10. Identifying Key Stakeholders in Blended Tertiary Environments: Experts' Perspectives

    Science.gov (United States)

    Tuapawa, Kimberley

    2017-01-01

    Although key stakeholders in blended tertiary environments (BTEs) fulfil an extraordinary role in higher education, significant gaps in knowledge about their identities may be impeding the provision of stakeholder support, limiting their ability to promote effective learning and teaching. As online growth intensifies, it is critical that tertiary…

  11. DISTANCE AS KEY FACTOR IN MODELLING STUDENTS’ RECRUITMENT BY UNIVERSITIES

    Directory of Open Access Journals (Sweden)

    SIMONA MĂLĂESCU

    2015-10-01

    Full Text Available Distance as Key Factor in Modelling Students’ Recruitment by Universities. In a previous paper analysing the challenge of keeping up with the current methodologies in the analysis and modelling of students’ recruitment by universities in the case of some ECE countries which still don’t register or develop key data to take advantage from the state of the art knowledge on the domain, we have promised to approach the factor distance in a future work due to the extent of the topic. This paper fulfill that promise bringing a review of the literature especially dealing with modelling the geographical area of recruiting students of an university, where combining distance with the proximate key factors previously reviewed, complete the meta-analysis of existing literature we have started a year ago. Beyond the theoretical benefit from a practical perspective, the metaanalysis aimed at synthesizing elements of good practice that can be applied to the local university system.

  12. Numerical rigid plastic modelling of shear capacity of keyed joints

    DEFF Research Database (Denmark)

    Herfelt, Morten Andersen; Poulsen, Peter Noe; Hoang, Linh Cao

    2015-01-01

    Keyed shear joints are currently designed using simple and conservative design formulas, yet these formulas do not take the local mechanisms in the concrete core of the joint into account. To investigate this phenomenon a rigid, perfectly plastic finite element model of keyed joints is used....... The model is formulated for second-order conic optimisation as a lower bound problem, which yields a statically admissible stress field that satisfies the yield condition in every point. The dual solution to the problem can be interpreted as the collapse mode and will be used to analyse the properties...

  13. Identifying key research objectives to make European forests greener for bats

    Directory of Open Access Journals (Sweden)

    Danilo Russo

    2016-07-01

    Full Text Available Bats are a biodiverse mammal order providing key ecosystem services such as pest suppression, pollination and seed dispersal. Bats are also very sensitive to human actions, and significant declines in many bat populations have been recorded consequently. Many bat species find crucial roosting and foraging opportunities in European forests. Such forests have historically been exploited by humans and are still influenced by harvesting. One of the consequences of this pressure is the loss of key habitat resources, often making forests inhospitable to bats. Despite the legal protection granted to bats across Europe, the impacts of forestry on bats are still often neglected. Because forest exploitation influences forest structure at several spatial scales, economically viable forestry could become more sustainable and even favour bats. We highlight that a positive future for bat conservation that simultaneously benefits forestry is foreseeable, although more applied research is needed to develop sound management. Key future research topics include the detection of factors influencing the carrying capacity of forests, and determining the impacts of forest management and the economic importance of bats in forests. Predictive tools to inform forest managers are much needed, together with greater synergies between forest managers and bat conservationists.

  14. An Integrated Strategy to Identify Key Genes in Almond Adventitious Shoot Regeneration

    Science.gov (United States)

    Plant genetic transformation usually depends on efficient adventitious regeneration systems. In almond (Prunus dulcis Mill.), regeneration of transgenic adventitious shoots was achieved but with low efficiency. Histological studies identified two main stages of organogenesis in almond explants that ...

  15. Identifying Key Flavors in Strawberries Driving Liking via Internal and External Preference Mapping.

    Science.gov (United States)

    Oliver, Penelope; Cicerale, Sara; Pang, Edwin; Keast, Russell

    2018-04-01

    Australian consumers desire the development of a more flavorsome Australian strawberry cultivar. To aid in the development of well-liked strawberries, the attributes driving liking need to be identified. The objective of this research is to apply Preference Mapping (PM) techniques to the descriptive profile of commercial and newly bred strawberry cultivars, together with consumer preference data to determine the flavors contributing to liking. A trained sensory panel (n = 12) used Quantitative Descriptive Analysis (QDA®) methodology to evaluate two appearance, seven aroma, five texture, 10 flavor and 10 aftertaste attributes of three commercial strawberry cultivars and six elite breeding lines grown in Victoria, Australia. Strawberry consumers (n = 150) assessed their liking of the same strawberry cultivars. QDA® significantly discriminated strawberries on 28 of the 34 sensory attributes. There were significant differences in hedonic ratings of strawberries (F(8,714) = 11.5, P = 0.0001), with Hierarchical Cluster Analysis (HCA) identifying three consumer clusters each displaying differing patterns of preference. Internal and external PM techniques were applied to the data to identify the attributes driving consumer acceptability. Sweet, berry, caramel, fruity and floral attributes were identified as most contributing to liking. Sour, citrus, green, astringent, firm and gritty attributes were conversely associated with a reduction in consumer liking. Elite Lines 2 and 6 have been identified as having the broadest appeal, satisfying between 60% and 70% of consumers in the population assessed, thus the introduction of these cultivars should satisfy the largest group of consumers in the Australian market. The results of this research could be applied to breeding programs, to ensure newly bred cultivars express characteristics that were identified as well-liked amongst consumers. In addition, this research provides evidence for marketing strawberries by

  16. Key processes and input parameters for environmental tritium models

    International Nuclear Information System (INIS)

    Bunnenberg, C.; Taschner, M.; Ogram, G.L.

    1994-01-01

    The primary objective of the work reported here is to define key processes and input parameters for mathematical models of environmental tritium behaviour adequate for use in safety analysis and licensing of fusion devices like NET and associated tritium handling facilities. (author). 45 refs., 3 figs

  17. Key processes and input parameters for environmental tritium models

    Energy Technology Data Exchange (ETDEWEB)

    Bunnenberg, C; Taschner, M [Niedersaechsisches Inst. fuer Radiooekologie, Hannover (Germany); Ogram, G L [Ontario Hydro, Toronto, ON (Canada)

    1994-12-31

    The primary objective of the work reported here is to define key processes and input parameters for mathematical models of environmental tritium behaviour adequate for use in safety analysis and licensing of fusion devices like NET and associated tritium handling facilities. (author). 45 refs., 3 figs.

  18. A multivariate and stochastic approach to identify key variables to rank dairy farms on profitability.

    Science.gov (United States)

    Atzori, A S; Tedeschi, L O; Cannas, A

    2013-05-01

    The economic efficiency of dairy farms is the main goal of farmers. The objective of this work was to use routinely available information at the dairy farm level to develop an index of profitability to rank dairy farms and to assist the decision-making process of farmers to increase the economic efficiency of the entire system. A stochastic modeling approach was used to study the relationships between inputs and profitability (i.e., income over feed cost; IOFC) of dairy cattle farms. The IOFC was calculated as: milk revenue + value of male calves + culling revenue - herd feed costs. Two databases were created. The first one was a development database, which was created from technical and economic variables collected in 135 dairy farms. The second one was a synthetic database (sDB) created from 5,000 synthetic dairy farms using the Monte Carlo technique and based on the characteristics of the development database data. The sDB was used to develop a ranking index as follows: (1) principal component analysis (PCA), excluding IOFC, was used to identify principal components (sPC); and (2) coefficient estimates of a multiple regression of the IOFC on the sPC were obtained. Then, the eigenvectors of the sPC were used to compute the principal component values for the original 135 dairy farms that were used with the multiple regression coefficient estimates to predict IOFC (dRI; ranking index from development database). The dRI was used to rank the original 135 dairy farms. The PCA explained 77.6% of the sDB variability and 4 sPC were selected. The sPC were associated with herd profile, milk quality and payment, poor management, and reproduction based on the significant variables of the sPC. The mean IOFC in the sDB was 0.1377 ± 0.0162 euros per liter of milk (€/L). The dRI explained 81% of the variability of the IOFC calculated for the 135 original farms. When the number of farms below and above 1 standard deviation (SD) of the dRI were calculated, we found that 21

  19. Labont? Identifies Key Issues for Health Promoters in the New World Order

    OpenAIRE

    Raphael, Dennis

    2016-01-01

    For over 35 years Ronald Labonté has been critically analyzing the state of health promotion in Canada and the world. In 1981, he identified the shortcomings of the groundbreaking Lalonde Report by warning of the seductive appeal of so-called lifestyle approaches to health. Since then, he has left a trail of critical work identifying the barriers to — and opportunities for —health promotion work. More recently, he has shown how the rise of economic globalization and acceptance of neo-liberal ...

  20. The Five Key Questions of Human Performance Modeling.

    Science.gov (United States)

    Wu, Changxu

    2018-01-01

    Via building computational (typically mathematical and computer simulation) models, human performance modeling (HPM) quantifies, predicts, and maximizes human performance, human-machine system productivity and safety. This paper describes and summarizes the five key questions of human performance modeling: 1) Why we build models of human performance; 2) What the expectations of a good human performance model are; 3) What the procedures and requirements in building and verifying a human performance model are; 4) How we integrate a human performance model with system design; and 5) What the possible future directions of human performance modeling research are. Recent and classic HPM findings are addressed in the five questions to provide new thinking in HPM's motivations, expectations, procedures, system integration and future directions.

  1. Research on Digital Product Modeling Key Technologies of Digital Manufacturing

    Institute of Scientific and Technical Information of China (English)

    DING Guoping; ZHOU Zude; HU Yefa; ZHAO Liang

    2006-01-01

    With the globalization and diversification of the market and the rapid development of Information Technology (IT) and Artificial Intelligence (AI), the digital revolution of manufacturing is coming. One of the key technologies in digital manufacturing is product digital modeling. This paper firstly analyzes the information and features of the product digital model during each stage in the product whole lifecycle, then researches on the three critical technologies of digital modeling in digital manufacturing-product modeling, standard for the exchange of product model data and digital product data management. And the potential signification of the product digital model during the process of digital manufacturing is concluded-product digital model integrates primary features of each stage during the product whole lifecycle based on graphic features, applies STEP as data exchange mechanism, and establishes PDM system to manage the large amount, complicated and dynamic product data to implement the product digital model data exchange, sharing and integration.

  2. Identifying key performance indicators in food technology contract R&D

    NARCIS (Netherlands)

    Flipse, S.M.; Sanden, van der M.C.A.; Velden, van der T.; Fortuin, F.T.J.M.; Omta, S.W.F.; Osseweijer, P.

    2013-01-01

    Innovating companies increasingly rely on outsourcing to Contract Research Organisations (CROs) for their Research and Development (R&D), which are largely understudied. This paper presents the outcome of a case study in the field of food technology contract research, identifying context

  3. The Promise of Virtual Teams: Identifying Key Factors in Effectiveness and Failure

    Science.gov (United States)

    Horwitz, Frank M.; Bravington, Desmond; Silvis, Ulrik

    2006-01-01

    Purpose: The aim of the investigation is to identify enabling and disenabling factors in the development and operation of virtual teams; to evaluate the importance of factors such as team development, cross-cultural variables, leadership, communication and social cohesion as contributors to virtual team effectiveness. Design/methodology/approach:…

  4. Mergeomics: a web server for identifying pathological pathways, networks, and key regulators via multidimensional data integration.

    Science.gov (United States)

    Arneson, Douglas; Bhattacharya, Anindya; Shu, Le; Mäkinen, Ville-Petteri; Yang, Xia

    2016-09-09

    Human diseases are commonly the result of multidimensional changes at molecular, cellular, and systemic levels. Recent advances in genomic technologies have enabled an outpour of omics datasets that capture these changes. However, separate analyses of these various data only provide fragmented understanding and do not capture the holistic view of disease mechanisms. To meet the urgent needs for tools that effectively integrate multiple types of omics data to derive biological insights, we have developed Mergeomics, a computational pipeline that integrates multidimensional disease association data with functional genomics and molecular networks to retrieve biological pathways, gene networks, and central regulators critical for disease development. To make the Mergeomics pipeline available to a wider research community, we have implemented an online, user-friendly web server ( http://mergeomics. idre.ucla.edu/ ). The web server features a modular implementation of the Mergeomics pipeline with detailed tutorials. Additionally, it provides curated genomic resources including tissue-specific expression quantitative trait loci, ENCODE functional annotations, biological pathways, and molecular networks, and offers interactive visualization of analytical results. Multiple computational tools including Marker Dependency Filtering (MDF), Marker Set Enrichment Analysis (MSEA), Meta-MSEA, and Weighted Key Driver Analysis (wKDA) can be used separately or in flexible combinations. User-defined summary-level genomic association datasets (e.g., genetic, transcriptomic, epigenomic) related to a particular disease or phenotype can be uploaded and computed real-time to yield biologically interpretable results, which can be viewed online and downloaded for later use. Our Mergeomics web server offers researchers flexible and user-friendly tools to facilitate integration of multidimensional data into holistic views of disease mechanisms in the form of tissue-specific key regulators

  5. Evaluation of unique identifiers used as keys to match identical publications in Pure and SciVal

    DEFF Research Database (Denmark)

    Madsen, Heidi Holst; Madsen, Dicte; Gauffriau, Marianne

    2016-01-01

    , and erroneous optical or special character recognition. The case study explores the use of UIDs in the integration between the databases Pure and SciVal. Specifically journal publications in English are matched between the two databases. We find all error types except erroneous optical or special character......Unique identifiers (UID) are seen as an effective key to match identical publications across databases or identify duplicates in a database. The objective of the present study is to investigate how well UIDs work as match keys in the integration between Pure and SciVal, based on a case...... also briefly discuss how publication sets formed by using UIDs as the match keys may affect the bibliometric indicators number of publications, number of citations, and the average number of citations per publication. The objective is addressed in a literature review and a case study. The literature...

  6. Co-extinction in a host-parasite network: identifying key hosts for network stability.

    Science.gov (United States)

    Dallas, Tad; Cornelius, Emily

    2015-08-17

    Parasites comprise a substantial portion of total biodiversity. Ultimately, this means that host extinction could result in many secondary extinctions of obligate parasites and potentially alter host-parasite network structure. Here, we examined a highly resolved fish-parasite network to determine key hosts responsible for maintaining parasite diversity and network structure (quantified here as nestedness and modularity). We evaluated four possible host extinction orders and compared the resulting co-extinction dynamics to random extinction simulations; including host removal based on estimated extinction risk, parasite species richness and host level contributions to nestedness and modularity. We found that all extinction orders, except the one based on realistic extinction risk, resulted in faster declines in parasite diversity and network structure relative to random biodiversity loss. Further, we determined species-level contributions to network structure were best predicted by parasite species richness and host family. Taken together, we demonstrate that a small proportion of hosts contribute substantially to network structure and that removal of these hosts results in rapid declines in parasite diversity and network structure. As network stability can potentially be inferred through measures of network structure, our findings may provide insight into species traits that confer stability.

  7. Genomic Landscape Survey Identifies SRSF1 as a Key Oncodriver in Small Cell Lung Cancer.

    Directory of Open Access Journals (Sweden)

    Liyan Jiang

    2016-04-01

    Full Text Available Small cell lung cancer (SCLC is an aggressive disease with poor survival. A few sequencing studies performed on limited number of samples have revealed potential disease-driving genes in SCLC, however, much still remains unknown, particularly in the Asian patient population. Here we conducted whole exome sequencing (WES and transcriptomic sequencing of primary tumors from 99 Chinese SCLC patients. Dysregulation of tumor suppressor genes TP53 and RB1 was observed in 82% and 62% of SCLC patients, respectively, and more than half of the SCLC patients (62% harbored TP53 and RB1 mutation and/or copy number loss. Additionally, Serine/Arginine Splicing Factor 1 (SRSF1 DNA copy number gain and mRNA over-expression was strongly associated with poor survival using both discovery and validation patient cohorts. Functional studies in vitro and in vivo demonstrate that SRSF1 is important for tumorigenicity of SCLC and may play a key role in DNA repair and chemo-sensitivity. These results strongly support SRSF1 as a prognostic biomarker in SCLC and provide a rationale for personalized therapy in SCLC.

  8. A matter of definition--key elements identified in a discourse analysis of definitions of palliative care.

    Science.gov (United States)

    Pastrana, T; Jünger, S; Ostgathe, C; Elsner, F; Radbruch, L

    2008-04-01

    For more than 30 years, the term "palliative care" has been used. From the outset, the term has undergone a series of transformations in its definitions and consequently in its tasks and goals. There remains a lack of consensus on a definition. The aim of this article is to analyse the definitions of palliative care in the specialist literature and to identify the key elements of palliative care using discourse analysis: a qualitative methodology. The literature search focused on definitions of the term 'palliative medicine' and 'palliative care' in the World Wide Web and medical reference books in English and German. A total of 37 English and 26 German definitions were identified and analysed. Our study confirmed the lack of a consistent meaning concerning the investigated terms, reflecting on-going discussion about the nature of the field among palliative care practitioners. Several common key elements were identified. Four main categories emerged from the discourse analysis of the definition of palliative care: target groups, structure, tasks and expertise. In addition, the theoretical principles and goals of palliative care were discussed and found to be key elements, with relief and prevention of suffering and improvement of quality of life as main goals. The identified key elements can contribute to the definition of the concept 'palliative care'. Our study confirms the importance of semantic and ethical influences on palliative care that should be considered in future research on semantics in different languages.

  9. IDENTIFIABILITY VERSUS HETEROGENEITY IN GROUNDWATER MODELING SYSTEMS

    Directory of Open Access Journals (Sweden)

    A M BENALI

    2003-06-01

    Full Text Available Review of history matching of reservoirs parameters in groundwater flow raises the problem of identifiability of aquifer systems. Lack of identifiability means that there exists parameters to which the heads are insensitive. From the guidelines of the study of the homogeneous case, we inspect the identifiability of the distributed transmissivity field of heterogeneous groundwater aquifers. These are derived from multiple realizations of a random function Y = log T  whose probability distribution function is normal. We follow the identifiability of the autocorrelated block transmissivities through the measure of the sensitivity of the local derivatives DTh = (∂hi  ∕ ∂Tj computed for each sample of a population N (0; σY, αY. Results obtained from an analysis of Monte Carlo type suggest that the more a system is heterogeneous, the less it is identifiable.

  10. Identifying key genes in rheumatoid arthritis by weighted gene co-expression network analysis.

    Science.gov (United States)

    Ma, Chunhui; Lv, Qi; Teng, Songsong; Yu, Yinxian; Niu, Kerun; Yi, Chengqin

    2017-08-01

    This study aimed to identify rheumatoid arthritis (RA) related genes based on microarray data using the WGCNA (weighted gene co-expression network analysis) method. Two gene expression profile datasets GSE55235 (10 RA samples and 10 healthy controls) and GSE77298 (16 RA samples and seven healthy controls) were downloaded from Gene Expression Omnibus database. Characteristic genes were identified using metaDE package. WGCNA was used to find disease-related networks based on gene expression correlation coefficients, and module significance was defined as the average gene significance of all genes used to assess the correlation between the module and RA status. Genes in the disease-related gene co-expression network were subject to functional annotation and pathway enrichment analysis using Database for Annotation Visualization and Integrated Discovery. Characteristic genes were also mapped to the Connectivity Map to screen small molecules. A total of 599 characteristic genes were identified. For each dataset, characteristic genes in the green, red and turquoise modules were most closely associated with RA, with gene numbers of 54, 43 and 79, respectively. These genes were enriched in totally enriched in 17 Gene Ontology terms, mainly related to immune response (CD97, FYB, CXCL1, IKBKE, CCR1, etc.), inflammatory response (CD97, CXCL1, C3AR1, CCR1, LYZ, etc.) and homeostasis (C3AR1, CCR1, PLN, CCL19, PPT1, etc.). Two small-molecule drugs sanguinarine and papaverine were predicted to have a therapeutic effect against RA. Genes related to immune response, inflammatory response and homeostasis presumably have critical roles in RA pathogenesis. Sanguinarine and papaverine have a potential therapeutic effect against RA. © 2017 Asia Pacific League of Associations for Rheumatology and John Wiley & Sons Australia, Ltd.

  11. Identifying key topics for a description of sexual behavior among Danish adolescents: A qualitative study

    DEFF Research Database (Denmark)

    Jørgensen, Marianne Johansson; Maindal, Helle Terkildsen; Olesen, Frede

    . Results: Four major categories of risk behavior were identified: Alcohol consumption is associated with “no condom use”, Nights on the town and meetings in foreign counties or at festivals are associated with one night stands and often lead to unsafe sex, Low self-esteem increases the risk of pushing one...... one Danish Folk High School, but with different social and educational backgrounds. The interview guide was developed from literature reviews and hypotheses based on years of experience with sexually transmitted infections. Data were transcribed verbatim and analyzed using qualitative description...

  12. Characteristics of evolving models of care for arthritis: A key informant study

    Directory of Open Access Journals (Sweden)

    Veinot Paula

    2008-07-01

    Full Text Available Abstract Background The burden of arthritis is increasing in the face of diminishing health human resources to deliver care. In response, innovative models of care delivery are developing to facilitate access to quality care. Most models have developed in response to local needs with limited evaluation. The primary objective of this study is to a examine the range of models of care that deliver specialist services using a medical/surgical specialist and at least one other health care provider and b document the strengths and challenges of the identified models. A secondary objective is to identify key elements of best practice models of care for arthritis. Methods Semi-structured interviews were conducted with a sample of key informants with expertise in arthritis from jurisdictions with primarily publicly-funded health care systems. Qualitative data were analyzed using a constant comparative approach to identify common types of models of care, strengths and challenges of models, and key components of arthritis care. Results Seventy-four key informants were interviewed from six countries. Five main types of models of care emerged. 1 Specialized arthritis programs deliver comprehensive, multidisciplinary team care for arthritis. Two models were identified using health care providers (e.g. nurses or physiotherapists in expanded clinical roles: 2 triage of patients with musculoskeletal conditions to the appropriate services including specialists; and 3 ongoing management in collaboration with a specialist. Two models promoting rural access were 4 rural consultation support and 5 telemedicine. Key informants described important components of models of care including knowledgeable health professionals and patients. Conclusion A range of models of care for arthritis have been developed. This classification can be used as a framework for discussing care delivery. Areas for development include integration of care across the continuum, including primary

  13. Predicting establishment of non-native fishes in Greece: identifying key features

    Directory of Open Access Journals (Sweden)

    Christos Gkenas

    2015-11-01

    Full Text Available Non-native fishes are known to cause economic damage to human society and are considered a major threat to biodiversity loss in freshwater ecosystems. The growing concern about these impacts has driven to an investigation of the biological traits that facilitate the establishment of non-native fish. However, invalid assessment in choosing the appropriate statistical model can lead researchers to ambiguous conclusions. Here, we present a comprehensive comparison of traditional and alternative statistical methods for predicting fish invasions using logistic regression, classification trees, multicorrespondence analysis and random forest analysis to determine characteristics of successful and failed non-native fishes in Hellenic Peninsula through establishment. We defined fifteen categorical predictor variables with biological relevance and measures of human interest. Our study showed that accuracy differed according to the model and the number of factors considered. Among all the models tested, random forest and logistic regression performed best, although all approaches predicted non-native fish establishment with moderate to excellent results. Detailed evaluation among the models corresponded with differences in variables importance, with three biological variables (parental care, distance from nearest native source and maximum size and two variables of human interest (prior invasion success and propagule pressure being important in predicting establishment. The analyzed statistical methods presented have a high predictive power and can be used as a risk assessment tool to prevent future freshwater fish invasions in this region with an imperiled fish fauna.

  14. Identifying Key Proteins in Hg Methylation Pathways of Desulfovibrio by Global Proteomics, Final Technical Report

    Energy Technology Data Exchange (ETDEWEB)

    Summers, Anne O. [Univ. of Georgia, Athens, GA (United States). Dept. of Microbiology; Miller, Susan M. [Univ. of California, San Francisco, CA (United States). Dept. of Pharmaceutical Chemistry; Wall, Judy [Univ. of Missouri, Columbia, MO (United States). Dept. of Biochemistry; Lipton, Mary [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2016-06-18

    Elemental mercury, Hg(0) is a contaminant at many DOE sites, especially at Oak Ridge National Laboratory (ORNL) where the spread of spilled Hg and its effects on microbial populations have been monitored for decades. To explore the microbial interactions with Hg, we have devised a global proteomic approach capable of directly detecting Hg-adducts of proteins. This technique developed in the facultative anaerobe, Escherichia coli, allows us to identify the proteins most vulnerable to acute exposure to organomercurials phenyl- and ethyl-mercury (as surrogates for the highly neurotoxic methyl-Hg) (Polacco, et al, 2011). We have found >300 such proteins in all metabolic functional groups and cellular compartments; most are highly conserved and can serve as markers for acute Hg exposure (Zink, et al. 2016, in preparation). We have also discovered that acute Hg exposure severely disrupts thiol, iron and redox homeostases, and electrolyte balance (LaVoie, et al., 2015) Thus, we proposed to bring these techniques to bear on the central problem of identifying the cellular proteins involved in bacterial uptake and methylation of mercury and its release from the cell.

  15. Identifying key components for an effective case report poster: an observational study.

    Science.gov (United States)

    Willett, Lisa L; Paranjape, Anuradha; Estrada, Carlos

    2009-03-01

    Residents demonstrate scholarly activity by presenting posters at academic meetings. Although recommendations from national organizations are available, evidence identifying which components are most important is not. To develop and test an evaluation tool to measure the quality of case report posters and identify the specific components most in need of improvement. Faculty evaluators reviewed case report posters and provided on-site feedback to presenters at poster sessions of four annual academic general internal medicine meetings. A newly developed ten-item evaluation form measured poster quality for specific components of content, discussion, and format (5-point Likert scale, 1 = lowest, 5 = highest). Evaluation tool performance, including Cronbach alpha and inter-rater reliability, overall poster scores, differences across meetings and evaluators and specific components of the posters most in need of improvement. Forty-five evaluators from 20 medical institutions reviewed 347 posters. Cronbach's alpha of the evaluation form was 0.84 and inter-rater reliability, Spearman's rho 0.49 (p words. Our evaluation tool provides empirical data to guide trainees as they prepare posters for presentation which may improve poster quality and enhance their scholarly productivity.

  16. Identifying Key Issues and Potential Solutions for Integrated Arrival, Departure, Surface Operations by Surveying Stakeholder Preferences

    Science.gov (United States)

    Aponso, Bimal; Coppenbarger, Richard A.; Jung, Yoon; Quon, Leighton; Lohr, Gary; O’Connor, Neil; Engelland, Shawn

    2015-01-01

    predictability and suggested several key attributes that were necessary to make the concept successful. The goals and objectives of the planned ATD-2 sub-project will incorporate the results of this stakeholder feedback.

  17. Projecting biodiversity and wood production in future forest landscapes: 15 key modeling considerations.

    Science.gov (United States)

    Felton, Adam; Ranius, Thomas; Roberge, Jean-Michel; Öhman, Karin; Lämås, Tomas; Hynynen, Jari; Juutinen, Artti; Mönkkönen, Mikko; Nilsson, Urban; Lundmark, Tomas; Nordin, Annika

    2017-07-15

    A variety of modeling approaches can be used to project the future development of forest systems, and help to assess the implications of different management alternatives for biodiversity and ecosystem services. This diversity of approaches does however present both an opportunity and an obstacle for those trying to decide which modeling technique to apply, and interpreting the management implications of model output. Furthermore, the breadth of issues relevant to addressing key questions related to forest ecology, conservation biology, silviculture, economics, requires insights stemming from a number of distinct scientific disciplines. As forest planners, conservation ecologists, ecological economists and silviculturalists, experienced with modeling trade-offs and synergies between biodiversity and wood biomass production, we identified fifteen key considerations relevant to assessing the pros and cons of alternative modeling approaches. Specifically we identified key considerations linked to study question formulation, modeling forest dynamics, forest processes, study landscapes, spatial and temporal aspects, and the key response metrics - biodiversity and wood biomass production, as well as dealing with trade-offs and uncertainties. We also provide illustrative examples from the modeling literature stemming from the key considerations assessed. We use our findings to reiterate the need for explicitly addressing and conveying the limitations and uncertainties of any modeling approach taken, and the need for interdisciplinary research efforts when addressing the conservation of biodiversity and sustainable use of environmental resources. Copyright © 2017 Elsevier Ltd. All rights reserved.

  18. A structured elicitation method to identify key direct risk factors for the management of natural resources

    Directory of Open Access Journals (Sweden)

    Michael Smith

    2015-11-01

    Full Text Available The high level of uncertainty inherent in natural resource management requires planners to apply comprehensive risk analyses, often in situations where there are few resources. In this paper, we demonstrate a broadly applicable, novel and structured elicitation approach to identify important direct risk factors. This new approach combines expert calibration and fuzzy based mathematics to capture and aggregate subjective expert estimates of the likelihood that a set of direct risk factors will cause management failure. A specific case study is used to demonstrate the approach; however, the described methods are widely applicable in risk analysis. For the case study, the management target was to retain all species that characterise a set of natural biological elements. The analysis was bounded by the spatial distribution of the biological elements under consideration and a 20-year time frame. Fourteen biological elements were expected to be at risk. Eleven important direct risk factors were identified that related to surrounding land use practices, climate change, problem species (e.g., feral predators, fire and hydrological change. In terms of their overall influence, the two most important risk factors were salinisation and a lack of water which together pose a considerable threat to the survival of nine biological elements. The described approach successfully overcame two concerns arising from previous risk analysis work: (1 the lack of an intuitive, yet comprehensive scoring method enabling the detection and clarification of expert agreement and associated levels of uncertainty; and (2 the ease with which results can be interpreted and communicated while preserving a rich level of detail essential for informed decision making.

  19. Local and regional energy companies offering energy services: Key activities and implications for the business model

    International Nuclear Information System (INIS)

    Kindström, Daniel; Ottosson, Mikael

    2016-01-01

    Highlights: • Many companies providing energy services are experiencing difficulties. • This research identifies key activities for the provision of energy services. • Findings are aggregated to the business-model level providing managerial insights. • This research identifies two different business model innovation paths. • Energy companies may need to renew parts of, or the entire, business model. - Abstract: Energy services play a key role in increasing energy efficiency in the industry. The key actors in these services are the local and regional energy companies that are increasingly implementing energy services as part of their market offering and developing service portfolios. Although expectations for energy services have been high, progress has so far been limited, and many companies offering energy services, including energy companies, are experiencing difficulties in implementing energy services and providing them to the market. Overall, this research examines what is needed for local and regional energy companies to successfully implement energy services (and consequently provide them to the market). In doing this, a two-stage process is used: first, we identify key activities for the successful implementation of energy services, and second, we aggregate the findings to the business model level. This research demonstrates that to succeed in implementing energy services, an energy company may need to renew parts or all of its existing product-based business model, formulate a new business model, or develop coexisting multiple business models. By discussing two distinct business model innovation processes, this research demonstrates that there can be different paths to success.

  20. The changing model of big pharma: impact of key trends.

    Science.gov (United States)

    Gautam, Ajay; Pan, Xiaogang

    2016-03-01

    Recent years have seen exciting breakthroughs in biomedical sciences that are producing truly novel therapeutics for unmet patient needs. However, the pharmaceutical industry is also facing significant barriers in the form of pricing and reimbursement, continued patent expirations and challenging market dynamics. In this article, we have analyzed data from the 1995-2015 period, on key aspects such as revenue distribution, research units, portfolio mix and emerging markets to identify four key trends that help to understand the change in strategic focus, realignment of R&D footprint, the shift from primary care toward specialty drugs and biologics and the growth of emerging markets as major revenue drivers for big pharma. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

  1. Preparedness for physiotherapy in private practice: Novices identify key factors in an interpretive description study.

    Science.gov (United States)

    Atkinson, Robyn; McElroy, Theresa

    2016-04-01

    Physiotherapists in Australia deliver services to a diverse range of clients, across many settings, however little research exists examining graduate preparedness for practice, even in the populous field of private practice. To explore novice physiotherapist perspectives on preparedness for work in private practice. The qualitative approach of interpretive description was used to guide in-depth interviews with 8 novice physiotherapists from 3 universities working in 5 private practices in Melbourne. All interviews were digitally recorded, transcribed verbatim and analyzed thematically. Four main themes influencing graduate preparedness for work in private practice were identified: 1) non-curricular experiences (e.g. sports training) 2) elective curricular: practicum experiences; 3) curricular: attainment of skills specific to private practice; and 4) the private practice setting: supportive colleagues. This combination of non-curricular, curricular, and practice setting factors offered the necessary scaffolding for the graduates to report feeling prepared for work in private practice. Non-curricular activities, radiological instruction, clinical placements, building supportive colleague relations and professional development in private practice are recommended as potential means of building preparedness in novice therapists. Findings have implications for physiotherapy students, educators and private practice clinics looking to recruit new graduates. Copyright © 2015 Elsevier Ltd. All rights reserved.

  2. Pharmacy patronage: identifying key factors in the decision making process using the determinant attribute approach.

    Science.gov (United States)

    Franic, Duska M; Haddock, Sarah M; Tucker, Leslie Tootle; Wooten, Nathan

    2008-01-01

    To use the determinant attribute approach, a research method commonly used in marketing to identify the wants of various consumer groups, to evaluate consumer pharmacy choice when having a prescription order filled in different pharmacy settings. Cross sectional. Community independent, grocery store, community chain, and discount store pharmacies in Georgia between April 2005 and April 2006. Convenience sample of adult pharmacy consumers (n = 175). Survey measuring consumer preferences on 26 attributes encompassing general pharmacy site features (16 items), pharmacist characteristics (5 items), and pharmacy staff characteristics (5 items). 26 potential determinant attributes for pharmacy selection. 175 consumers were surveyed at community independent (n = 81), grocery store (n = 44), community chain (n = 27), or discount store (n = 23) pharmacy settings. The attributes of pharmacists and staff at all four pharmacy settings were shown to affect pharmacy patronage motives, although consumers frequenting non-community independent pharmacies were also motivated by secondary convenience factors, e.g., hours of operation, and prescription coverage. Most consumers do not perceive pharmacies as merely prescription-distribution centers that vary only by convenience. Prescriptions are not just another economic good. Pharmacy personnel influence pharmacy selection; therefore, optimal staff selection and training is likely the greatest asset and most important investment for ensuring pharmacy success.

  3. Using the Delphi Technique to Identify Key Elements for Effective and Sustainable Visitor Use Planning Frameworks

    Directory of Open Access Journals (Sweden)

    Jessica P. Fefer

    2016-04-01

    Full Text Available Protected areas around the world receive nearly 800 billion visits/year, with international tourism continuing to increase. While protected areas provide necessary benefits to communities and visitors, the increased visitation may negatively impact the resource and the recreational experience, hence the need to manage visitor use in protected areas around the world. This research focused on obtaining information from experts to document their experiences utilizing one visitor use planning framework: Visitor Experience and Resource Protection (VERP. Using the Delphi Technique, 31 experts from seven regions around the world were asked to identify elements necessary for effective visitor management, as well as elements that facilitated or limited success when using VERP. Elements were categorized and rated in terms of importance. Scoring of the final categories was analyzed using Wilcoxon and Median non-parametric statistical tests. Results suggest that planning challenges stem from limitations in organizational capacity to support a long-term, adaptive management process, inferring that VERP may be sufficiently developed, but implementation capacity may not. The results can be used to refine existing frameworks, and to aid in the development of new recreation frameworks.

  4. Gene expression profiling in Entamoeba histolytica identifies key components in iron uptake and metabolism.

    Directory of Open Access Journals (Sweden)

    Nora Adriana Hernández-Cuevas

    Full Text Available Entamoeba histolytica is an ameboid parasite that causes colonic dysentery and liver abscesses in humans. The parasite encounters dramatic changes in iron concentration during its invasion of the host, with relatively low levels in the intestinal lumen and then relatively high levels in the blood and liver. The liver notably contains sources of iron; therefore, the parasite's ability to use these sources might be relevant to its survival in the liver and thus the pathogenesis of liver abscesses. The objective of the present study was to identify factors involved in iron uptake, use and storage in E. histolytica. We compared the respective transcriptomes of E. histolytica trophozoites grown in normal medium (containing around 169 µM iron, low-iron medium (around 123 µM iron, iron-deficient medium (around 91 µM iron, and iron-deficient medium replenished with hemoglobin. The differentially expressed genes included those coding for the ATP-binding cassette transporters and major facilitator transporters (which share homology with bacterial siderophores and heme transporters and genes involved in heme biosynthesis and degradation. Iron deficiency was associated with increased transcription of genes encoding a subset of cell signaling molecules, some of which have previously been linked to adaptation to the intestinal environment and virulence. The present study is the first to have assessed the transcriptome of E. histolytica grown under various iron concentrations. Our results provide insights into the pathways involved in iron uptake and metabolism in this parasite.

  5. Gene expression profiling in Entamoeba histolytica identifies key components in iron uptake and metabolism.

    Science.gov (United States)

    Hernández-Cuevas, Nora Adriana; Weber, Christian; Hon, Chung-Chau; Guillen, Nancy

    2014-01-01

    Entamoeba histolytica is an ameboid parasite that causes colonic dysentery and liver abscesses in humans. The parasite encounters dramatic changes in iron concentration during its invasion of the host, with relatively low levels in the intestinal lumen and then relatively high levels in the blood and liver. The liver notably contains sources of iron; therefore, the parasite's ability to use these sources might be relevant to its survival in the liver and thus the pathogenesis of liver abscesses. The objective of the present study was to identify factors involved in iron uptake, use and storage in E. histolytica. We compared the respective transcriptomes of E. histolytica trophozoites grown in normal medium (containing around 169 µM iron), low-iron medium (around 123 µM iron), iron-deficient medium (around 91 µM iron), and iron-deficient medium replenished with hemoglobin. The differentially expressed genes included those coding for the ATP-binding cassette transporters and major facilitator transporters (which share homology with bacterial siderophores and heme transporters) and genes involved in heme biosynthesis and degradation. Iron deficiency was associated with increased transcription of genes encoding a subset of cell signaling molecules, some of which have previously been linked to adaptation to the intestinal environment and virulence. The present study is the first to have assessed the transcriptome of E. histolytica grown under various iron concentrations. Our results provide insights into the pathways involved in iron uptake and metabolism in this parasite.

  6. Identifying Key Drivers of the Impact of an HIV Cure Intervention in Sub-Saharan Africa

    DEFF Research Database (Denmark)

    Phillips, Andrew N; Cambiano, Valentina; Revill, Paul

    2016-01-01

    BACKGROUND: It is unknown what properties would be required to make an intervention in low income countries that can eradicate or control human immunodeficiency virus (HIV) without antiretroviral therapy (ART) cost-effective. METHODS: We used a model of HIV and ART to investigate the effect...... of introducing an ART-free viral suppression intervention in 2022 using Zimbabwe as an example country. We assumed that the intervention (cost: $500) would be accessible for 90% of the population, be given to those receiving effective ART, have sufficient efficacy to allow ART interruption in 95%, with a rate...... of viral rebound of 5% per year in the first 3 months, and a 50% decline in rate with each successive year. RESULTS: An ART-free viral suppression intervention with these properties would result in >0.53 million disability-adjusted-life-years averted over 2022-2042, with a reduction in HIV program costs...

  7. Identifying key soil cyanobacteria easy to isolate and culture for arid soil restoration

    Science.gov (United States)

    Roncero-Ramos, Beatriz; Ángeles Muñoz-Martín, M.; Chamizo, Sonia; Román, Raúl; Rodriguez-Caballero, Emilio; Mateo, Pilar; Cantón, Yolanda

    2017-04-01

    Drylands represent an important fraction of the Earth land's surface. Low cover of vascular plants characterizes these regions, and the large open areas among plants are often colonized by cyanobacteria, mosses, lichens, algae, bryophytes, bacteria and fungi, known as biocrusts. Because these communities are on or within the soil surface, they contribute to improve physicochemical properties of the uppermost soil layers and have important effects on soil fertility and stability, so they could play an important role on soil restoration. Cyanobacteria appear to be a cross component of biocrusts and they have been demonstrated to enhance water availability, soil fertility (fixing atmospheric C and N), and soil aggregation (thanks to their filamentous morphology and the exopolysaccharides they excrete), and significantly reduce water and wind erosion. Besides, they are able to tolerate high temperatures and UV radiation. All these features convert cyanobacteria in pioneer organisms capable of colonizing degraded soils and may be crucial in facilitating the succession of more developed organisms such as vascular plants. Therefore, the use of native cyanobacteria, already adapted to site environmental conditions, could guarantee a successful restoration approach of degraded soils. However, previous to their application for soil restoration, the most representative species inhabiting these soils should be identified. The objective of this study was to identify (morphologically and genetically) and isolate representative native cyanobacteria species from arid soils in SE Spain, characterized for being easily isolated and cultured with the aim of using them to inoculate degraded arid soil. We selected two study areas in Almería, SE Spain, where biocrust cover most of the open spaces between plants: El Cautivo experimental site located in the Tabernas desert and a limestone quarry located at the southeastern edge of the Gádor massif. The first site is characterized by

  8. Fragmentation patterns of evergreen oak woodlands in Southwestern Iberia: identifying key spatial indicators.

    Science.gov (United States)

    Costa, Augusta; Madeira, Manuel; Lima Santos, José; Plieninger, Tobias; Seixas, Júlia

    2014-01-15

    Mediterranean evergreen oak woodlands (composed of Quercus suber L. and Quercus rotundifolia Lam.) are becoming increasingly fragmented in the human-modified landscapes of Southwestern Portugal and Spain. Previous studies have largely neglected to assess the spatial changes of oak woodlands in relation to their surrounding landscape matrix, and to characterize and quantify woodland boundaries and edges. The present study aims to fill this gap by analyzing fragmentation patterns of oak woodlands over a 50-year period (1958-2007) in three landscapes. Using archived aerial imagery from 1958, 1995 and 2007, for two consecutive periods (1958-1995 and 1995-2007), we calculated a set of landscape metrics to compare woodland fragmentation over time. Our results indicated a continuous woodland fragmentation characterized by their edge dynamics. From 1958 to 2007, the replacement of open farmland by shrubland and by new afforestation areas in the oak woodland landscape surrounding matrix, led to the highest values for edge contrast length trends of 5.0 and 12.3, respectively. Linear discriminant analysis was performed to delineate fragmented woodland structures and identify metric variables that characterize woodland spatial configuration. The edge contrast length with open farmland showed a strong correlation with F1 (correlations ranging between 0.55 and 0.98) and may be used as a proxy for oak woodland mixedness in landscape matrix. The edge dynamics of oak woodlands may result in different patterns of oak recruitment and therefore, its study may be helpful in highlighting future baselines for the sustainable management of oak woodlands. Copyright © 2013 Elsevier Ltd. All rights reserved.

  9. Identifying plant traits: a key aspect for suitable species selection in ecological restoration of semiarid slopes

    Science.gov (United States)

    Bochet, Esther; García-Fayos, Patricio

    2017-04-01

    In the context of ecological restoration, one of the greatest challenges for practitioners and scientists is to select suitable species for revegetation purposes. In semiarid environments where restoration projects often fail, little attention has been paid so far to the contribution of plant traits to species success. The objective of this study was to (1) identify plant traits associated with species success on four roadside situations along an erosion-productivity gradient, and (2) to provide an ecological framework for selecting suitable species on the basis of their morphological and functional traits, applied to semiarid environments. We analyzed the association of 10 different plant traits with species success of 296 species surveyed on the four roadside situations in a semiarid region (Valencia, Spain). Plant traits included general plant traits (longevity, woodiness) and more specific root-, seed- and leaf-related traits (root type, sprouting ability, seed mucilage, seed mass, seed susceptibility to removal, specific leaf area and leaf dry matter content). All of them were selected according to the prevailing limiting ecogeomorphological processes acting along the erosion-productivity gradient. We observed strong shifts along the erosion-productivity gradient in the traits associated to species success. At the harshest end of the gradient, the most intensely eroded and driest one, species success was mainly associated to seed resistance to removal by runoff and to resistance to drought. At the opposite end of the gradient, the most productive one, species success was associated to a competitive-ruderal plant strategy (herbaceous successful species with high specific leaf area and low leaf dry matter content). Our study provides an ecologically-based approach for selecting suitable native species on the basis or their morphological and functional traits and supports a differential trait-based selection of species as regards roadslope type and aspect. In

  10. Using Persuasion Models to Identify Givers.

    Science.gov (United States)

    Ferguson, Mary Ann; And Others

    1986-01-01

    Assesses the feasibility of and suggests using W. J. McGuire's information processing theory and cognitive response analysis theory in research studies to identify "givers"--those who are likely to contribute money and resources to charities or volunteer to aid philanthropic organizations. (SRT)

  11. Simulation-based Assessment to Reliably Identify Key Resident Performance Attributes.

    Science.gov (United States)

    Blum, Richard H; Muret-Wagstaff, Sharon L; Boulet, John R; Cooper, Jeffrey B; Petrusa, Emil R; Baker, Keith H; Davidyuk, Galina; Dearden, Jennifer L; Feinstein, David M; Jones, Stephanie B; Kimball, William R; Mitchell, John D; Nadelberg, Robert L; Wiser, Sarah H; Albrecht, Meredith A; Anastasi, Amanda K; Bose, Ruma R; Chang, Laura Y; Culley, Deborah J; Fisher, Lauren J; Grover, Meera; Klainer, Suzanne B; Kveraga, Rikante; Martel, Jeffrey P; McKenna, Shannon S; Minehart, Rebecca D; Mitchell, John D; Mountjoy, Jeremi R; Pawlowski, John B; Pilon, Robert N; Shook, Douglas C; Silver, David A; Warfield, Carol A; Zaleski, Katherine L

    2018-04-01

    Obtaining reliable and valid information on resident performance is critical to patient safety and training program improvement. The goals were to characterize important anesthesia resident performance gaps that are not typically evaluated, and to further validate scores from a multiscenario simulation-based assessment. Seven high-fidelity scenarios reflecting core anesthesiology skills were administered to 51 first-year residents (CA-1s) and 16 third-year residents (CA-3s) from three residency programs. Twenty trained attending anesthesiologists rated resident performances using a seven-point behaviorally anchored rating scale for five domains: (1) formulate a clear plan, (2) modify the plan under changing conditions, (3) communicate effectively, (4) identify performance improvement opportunities, and (5) recognize limits. A second rater assessed 10% of encounters. Scores and variances for each domain, each scenario, and the total were compared. Low domain ratings (1, 2) were examined in detail. Interrater agreement was 0.76; reliability of the seven-scenario assessment was r = 0.70. CA-3s had a significantly higher average total score (4.9 ± 1.1 vs. 4.6 ± 1.1, P = 0.01, effect size = 0.33). CA-3s significantly outscored CA-1s for five of seven scenarios and domains 1, 2, and 3. CA-1s had a significantly higher proportion of worrisome ratings than CA-3s (chi-square = 24.1, P < 0.01, effect size = 1.50). Ninety-eight percent of residents rated the simulations more educational than an average day in the operating room. Sensitivity of the assessment to CA-1 versus CA-3 performance differences for most scenarios and domains supports validity. No differences, by experience level, were detected for two domains associated with reflective practice. Smaller score variances for CA-3s likely reflect a training effect; however, worrisome performance scores for both CA-1s and CA-3s suggest room for improvement.

  12. Identifying misbehaving models using baseline climate variance

    Science.gov (United States)

    Schultz, Colin

    2011-06-01

    The majority of projections made using general circulation models (GCMs) are conducted to help tease out the effects on a region, or on the climate system as a whole, of changing climate dynamics. Sun et al., however, used model runs from 20 different coupled atmosphere-ocean GCMs to try to understand a different aspect of climate projections: how bias correction, model selection, and other statistical techniques might affect the estimated outcomes. As a case study, the authors focused on predicting the potential change in precipitation for the Murray-Darling Basin (MDB), a 1-million- square- kilometer area in southeastern Australia that suffered a recent decade of drought that left many wondering about the potential impacts of climate change on this important agricultural region. The authors first compared the precipitation predictions made by the models with 107 years of observations, and they then made bias corrections to adjust the model projections to have the same statistical properties as the observations. They found that while the spread of the projected values was reduced, the average precipitation projection for the end of the 21st century barely changed. Further, the authors determined that interannual variations in precipitation for the MDB could be explained by random chance, where the precipitation in a given year was independent of that in previous years.

  13. A Simple Key for Identifying the Sibling Species of the Malaria Vector Anopheles gambiae (Giles Complex by Polytene Chromosome Cytogenetics

    Directory of Open Access Journals (Sweden)

    Music Temitope OBEMBE

    2018-03-01

    Full Text Available It has been established that Anopheles gambiae complex sibling species are the major Plasmodium malaria vectors in Africa; however, not all the sibling species transmit the infection. Easier molecular methods, PCR-based assays, have been developed to distinguish the several members of the A. gambiae complex. However, malaria vector research in less developed countries, particularly sub-Saharan Africa, is being hampered by the lack of PCR facilities in laboratories and the cost of carrying out the assay within lack of funding. Hence, the present study was designed to develop a simple identification key, based on an affordable method of polytene chromosome cytotaxonomy, for identifying the major P. falciparum vectors. The Identification Key was successfully used to identify two members of the A. gambiae complex, A. gambiae sensu stricto and A. arabiensis, which are the most potent malaria vectors in Africa; even so, it could not be used to establish the infective and the refractory strains.

  14. A genetic screen identifies BRCA2 and PALB2 as key regulators of G2 checkpoint maintenance

    DEFF Research Database (Denmark)

    Menzel, Tobias; Nähse-Kumpf, Viola; Kousholt, Arne Nedergaard

    2011-01-01

    To identify key connections between DNA-damage repair and checkpoint pathways, we performed RNA interference screens for regulators of the ionizing radiation-induced G2 checkpoint, and we identified the breast cancer gene BRCA2. The checkpoint was also abrogated following depletion of PALB2......, an interaction partner of BRCA2. BRCA2 and PALB2 depletion led to premature checkpoint abrogation and earlier activation of the AURORA A-PLK1 checkpoint-recovery pathway. These results indicate that the breast cancer tumour suppressors and homologous recombination repair proteins BRCA2 and PALB2 are main...

  15. Protocol for a thematic synthesis to identify key themes and messages from a palliative care research network.

    LENUS (Irish Health Repository)

    Nicholson, Emma

    2016-10-21

    Research networks that facilitate collaborative research are increasing both regionally and globally and such collaborations contribute greatly to knowledge transfer particularly in health research. The Palliative Care Research Network is an Irish-based network that seeks to create opportunities and engender a collaborative environment to encourage innovative research that is relevant for policy and practice. The current review outlines a methodology to identify cross-cutting messages to identify how dissemination outputs can be optimized to ensure that key messages from this research reaches all knowledge users.

  16. Identifying nonproportional covariates in the Cox model

    Czech Academy of Sciences Publication Activity Database

    Kraus, David

    2008-01-01

    Roč. 37, č. 4 (2008), s. 617-625 ISSN 0361-0926 R&D Projects: GA AV ČR(CZ) IAA101120604; GA MŠk(CZ) 1M06047; GA ČR(CZ) GD201/05/H007 Institutional research plan: CEZ:AV0Z10750506 Keywords : Cox model * goodness of fit * proportional hazards assumption * time-varying coefficients Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.324, year: 2008

  17. Modified Principal Component Analysis for Identifying Key Environmental Indicators and Application to a Large-Scale Tidal Flat Reclamation

    Directory of Open Access Journals (Sweden)

    Kejian Chu

    2018-01-01

    Full Text Available Identification of the key environmental indicators (KEIs from a large number of environmental variables is important for environmental management in tidal flat reclamation areas. In this study, a modified principal component analysis approach (MPCA has been developed for determining the KEIs. The MPCA accounts for the two important attributes of the environmental variables: pollution status and temporal variation, in addition to the commonly considered numerical divergence attribute. It also incorporates the distance correlation (dCor to replace the Pearson’s correlation to measure the nonlinear interrelationship between the variables. The proposed method was applied to the Tiaozini sand shoal, a large-scale tidal flat reclamation region in China. Five KEIs were identified as dissolved inorganic nitrogen, Cd, petroleum in the water column, Hg, and total organic carbon in the sediment. The identified KEIs were shown to respond well to the biodiversity of phytoplankton. This demonstrated that the identified KEIs adequately represent the environmental condition in the coastal marine system. Therefore, the MPCA is a practicable method for extracting effective indicators that have key roles in the coastal and marine environment.

  18. Selecting a climate model subset to optimise key ensemble properties

    Directory of Open Access Journals (Sweden)

    N. Herger

    2018-02-01

    Full Text Available End users studying impacts and risks caused by human-induced climate change are often presented with large multi-model ensembles of climate projections whose composition and size are arbitrarily determined. An efficient and versatile method that finds a subset which maintains certain key properties from the full ensemble is needed, but very little work has been done in this area. Therefore, users typically make their own somewhat subjective subset choices and commonly use the equally weighted model mean as a best estimate. However, different climate model simulations cannot necessarily be regarded as independent estimates due to the presence of duplicated code and shared development history. Here, we present an efficient and flexible tool that makes better use of the ensemble as a whole by finding a subset with improved mean performance compared to the multi-model mean while at the same time maintaining the spread and addressing the problem of model interdependence. Out-of-sample skill and reliability are demonstrated using model-as-truth experiments. This approach is illustrated with one set of optimisation criteria but we also highlight the flexibility of cost functions, depending on the focus of different users. The technique is useful for a range of applications that, for example, minimise present-day bias to obtain an accurate ensemble mean, reduce dependence in ensemble spread, maximise future spread, ensure good performance of individual models in an ensemble, reduce the ensemble size while maintaining important ensemble characteristics, or optimise several of these at the same time. As in any calibration exercise, the final ensemble is sensitive to the metric, observational product, and pre-processing steps used.

  19. Selecting a climate model subset to optimise key ensemble properties

    Science.gov (United States)

    Herger, Nadja; Abramowitz, Gab; Knutti, Reto; Angélil, Oliver; Lehmann, Karsten; Sanderson, Benjamin M.

    2018-02-01

    End users studying impacts and risks caused by human-induced climate change are often presented with large multi-model ensembles of climate projections whose composition and size are arbitrarily determined. An efficient and versatile method that finds a subset which maintains certain key properties from the full ensemble is needed, but very little work has been done in this area. Therefore, users typically make their own somewhat subjective subset choices and commonly use the equally weighted model mean as a best estimate. However, different climate model simulations cannot necessarily be regarded as independent estimates due to the presence of duplicated code and shared development history. Here, we present an efficient and flexible tool that makes better use of the ensemble as a whole by finding a subset with improved mean performance compared to the multi-model mean while at the same time maintaining the spread and addressing the problem of model interdependence. Out-of-sample skill and reliability are demonstrated using model-as-truth experiments. This approach is illustrated with one set of optimisation criteria but we also highlight the flexibility of cost functions, depending on the focus of different users. The technique is useful for a range of applications that, for example, minimise present-day bias to obtain an accurate ensemble mean, reduce dependence in ensemble spread, maximise future spread, ensure good performance of individual models in an ensemble, reduce the ensemble size while maintaining important ensemble characteristics, or optimise several of these at the same time. As in any calibration exercise, the final ensemble is sensitive to the metric, observational product, and pre-processing steps used.

  20. The Use of Key Informant Method for Identifying Children with Blindness and Severe Visual Impairment in Developing Countries.

    Science.gov (United States)

    du Toit, Rènée; Courtright, Paul; Lewallen, Susan

    2017-06-01

    An estimated 19 million children are visually impaired; of these, 1.4 million are irreversibly blind. A key challenge is to identify them early in life to benefit maximally from visual rehabilitation, and/or treatment. This aggregative review and structured literature analysis summarizes evidence of what it is about the key informant (KI) approach that works to identify children with blindness or severe visual impairment (B/SVI) in the community (for whom, to what extent, in what circumstances, in what respect, how and why). Peer-reviewed (PubMed, hand search) and grey literature (Google, World Health Organization website, academic theses, direct requests) were included, and methods and criteria used for identification, productivity (number of children referred per KI), accuracy of referrals (positive predictive value, PPV), age of children with B/SVI, KI definition, sex, information about cost and comparisons aggregated. We included 31 documents describing 22 unique KI programs. Mostly KIs identified children with B/SVI in 1-3 weeks, i.e. "campaign mode." In 60%, KIs were community volunteers, others formal health sector workers (FHSW). Around 0.02-1.56 children per KI (median = 0.25) were successfully recruited. PPV ranged from 12 to 66%. In two studies comparing FHSWs and community KIs, the latter were 8 and 10 times more productive. KIs working in campaign mode may provide an effective approach to identifying children with B/SVI in communities. Including identification of ocular problems and/or other impairments has been recommended. Research on factors that influence effectiveness and on whether KIs continue to contribute could inform programs.

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

    Directory of Open Access Journals (Sweden)

    David M. Makori

    2017-02-01

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

  2. Key aspects of stratospheric tracer modeling using assimilated winds

    Directory of Open Access Journals (Sweden)

    B. Bregman

    2006-01-01

    Full Text Available This study describes key aspects of global chemistry-transport models and their impact on stratospheric tracer transport. We concentrate on global models that use assimilated winds from numerical weather predictions, but the results also apply to tracer transport in general circulation models. We examined grid resolution, numerical diffusion, air parcel dispersion, the wind or mass flux update frequency, and time interpolation. The evaluation is performed with assimilated meteorology from the "operational analyses or operational data" (OD from the European Centre for Medium-Range Weather Forecasts (ECMWF. We also show the effect of the mass flux update frequency using the ECMWF 40-year re-analyses (ERA40. We applied the three-dimensional chemistry-transport Tracer Model version 5 (TM5 and a trajectory model and performed several diagnoses focusing on different transport regimes. Covering different time and spatial scales, we examined (1 polar vortex dynamics during the Arctic winter, (2 the large-scale stratospheric meridional circulation, and (3 air parcel dispersion in the tropical lower stratosphere. Tracer distributions inside the Arctic polar vortex show considerably worse agreement with observations when the model grid resolution in the polar region is reduced to avoid numerical instability. The results are sensitive to the diffusivity of the advection. Nevertheless, the use of a computational cheaper but diffusive advection scheme is feasible for tracer transport when the horizontal grid resolution is equal or smaller than 1 degree. The use of time interpolated winds improves the tracer distributions, particularly in the middle and upper stratosphere. Considerable improvement is found both in the large-scale tracer distribution and in the polar regions when the update frequency of the assimilated winds is increased from 6 to 3 h. It considerably reduces the vertical dispersion of air parcels in the tropical lower stratosphere. Strong

  3. A Key Factor of the DCF Model Coherency

    Directory of Open Access Journals (Sweden)

    Piotr Adamczyk

    2017-04-01

    Full Text Available Aim/purpose - The aim of this paper is to provide economically justified evidence that the business value calculated by income valuation methods is the same, regardless of the type of cash flow used in the valuation algorithm. Design/methodology/approach - The evidence was arrived at using free cash flow to equity (FCFE, debt (FCFD and firm (FCFF. The article draws attention to the FCFF method's particular popularity in income valuation, based on analysts' practice. It shows an overview of various approaches to determine the capital structure in the formula for WACC, both in practice and theory. Finally, it examines an empirical example with the authors' own derivations and postulates. Findings - The conclusion drawn from the conducted analysis is that the key to the reconciliation process, and thus DCF model coherency, is to apply the appropriate method of capital structure estimation during the calculation of the weighted average cost of capital (WACC. This capital structure will henceforth be referred to as 'income weights'. Research implications/limitations - It should be noted that the obtained compliance of valuation results does not imply that the income valuation becomes an objective way of determining business value. It still remains subjective. Originality/value/contribution - According to the presented approach, the DCF model's subjectivism is limited to the forecasts. The rest is the algorithm which, based on the principles of mathematics, should be used in the same way in every situation.

  4. Identifiability Results for Several Classes of Linear Compartment Models.

    Science.gov (United States)

    Meshkat, Nicolette; Sullivant, Seth; Eisenberg, Marisa

    2015-08-01

    Identifiability concerns finding which unknown parameters of a model can be estimated, uniquely or otherwise, from given input-output data. If some subset of the parameters of a model cannot be determined given input-output data, then we say the model is unidentifiable. In this work, we study linear compartment models, which are a class of biological models commonly used in pharmacokinetics, physiology, and ecology. In past work, we used commutative algebra and graph theory to identify a class of linear compartment models that we call identifiable cycle models, which are unidentifiable but have the simplest possible identifiable functions (so-called monomial cycles). Here we show how to modify identifiable cycle models by adding inputs, adding outputs, or removing leaks, in such a way that we obtain an identifiable model. We also prove a constructive result on how to combine identifiable models, each corresponding to strongly connected graphs, into a larger identifiable model. We apply these theoretical results to several real-world biological models from physiology, cell biology, and ecology.

  5. Identifying key factors and strategies for reducing industrial CO2 emissions from a non-Kyoto protocol member's (Taiwan) perspective

    International Nuclear Information System (INIS)

    Lin, Sue J.; Lu, I.J.; Lewis, Charles

    2006-01-01

    In this study we use Divisia index approach to identify key factors affecting CO 2 emission changes of industrial sectors in Taiwan. The changes of CO 2 emission are decomposed into emission coefficient, energy intensity, industrial structure and economic growth. Furthermore, comparisons with USA, Japan, Germany, the Netherlands and South Korea are made to have a better understanding of emission tendency in these countries and to help formulate our CO 2 reduction strategies for responding to the international calls for CO 2 cuts. The results show that economic growth and high energy intensity were two key factors for the rapid increase of industrial CO 2 emission in Taiwan, while adjustment of industrial structure was the main component for the decrease. Although economic development is important, Taiwan must keep pace with the international trends for CO 2 reduction. Among the most important strategies are continuous efforts to improve energy intensity, fuel mix toward lower carbon, setting targets for industrial CO 2 cuts, and advancing green technology through technology transfer. Also, the clean development mechanism (CDM) is expected to play an important role in the future

  6. A Note on the Identifiability of Generalized Linear Mixed Models

    DEFF Research Database (Denmark)

    Labouriau, Rodrigo

    2014-01-01

    I present here a simple proof that, under general regularity conditions, the standard parametrization of generalized linear mixed model is identifiable. The proof is based on the assumptions of generalized linear mixed models on the first and second order moments and some general mild regularity...... conditions, and, therefore, is extensible to quasi-likelihood based generalized linear models. In particular, binomial and Poisson mixed models with dispersion parameter are identifiable when equipped with the standard parametrization...

  7. In-Silico Integration Approach to Identify a Key miRNA Regulating a Gene Network in Aggressive Prostate Cancer

    Science.gov (United States)

    Colaprico, Antonio; Bontempi, Gianluca; Castiglioni, Isabella

    2018-01-01

    Like other cancer diseases, prostate cancer (PC) is caused by the accumulation of genetic alterations in the cells that drives malignant growth. These alterations are revealed by gene profiling and copy number alteration (CNA) analysis. Moreover, recent evidence suggests that also microRNAs have an important role in PC development. Despite efforts to profile PC, the alterations (gene, CNA, and miRNA) and biological processes that correlate with disease development and progression remain partially elusive. Many gene signatures proposed as diagnostic or prognostic tools in cancer poorly overlap. The identification of co-expressed genes, that are functionally related, can identify a core network of genes associated with PC with a better reproducibility. By combining different approaches, including the integration of mRNA expression profiles, CNAs, and miRNA expression levels, we identified a gene signature of four genes overlapping with other published gene signatures and able to distinguish, in silico, high Gleason-scored PC from normal human tissue, which was further enriched to 19 genes by gene co-expression analysis. From the analysis of miRNAs possibly regulating this network, we found that hsa-miR-153 was highly connected to the genes in the network. Our results identify a four-gene signature with diagnostic and prognostic value in PC and suggest an interesting gene network that could play a key regulatory role in PC development and progression. Furthermore, hsa-miR-153, controlling this network, could be a potential biomarker for theranostics in high Gleason-scored PC. PMID:29562723

  8. Toward Designing a Quantum Key Distribution Network Simulation Model

    OpenAIRE

    Miralem Mehic; Peppino Fazio; Miroslav Voznak; Erik Chromy

    2016-01-01

    As research in quantum key distribution network technologies grows larger and more complex, the need for highly accurate and scalable simulation technologies becomes important to assess the practical feasibility and foresee difficulties in the practical implementation of theoretical achievements. In this paper, we described the design of simplified simulation environment of the quantum key distribution network with multiple links and nodes. In such simulation environment, we analyzed several ...

  9. Hillslope characterization: Identifying key controls on local-scale plant communities' distribution using remote sensing and subsurface data fusion.

    Science.gov (United States)

    Falco, N.; Wainwright, H. M.; Dafflon, B.; Leger, E.; Peterson, J.; Steltzer, H.; Wilmer, C.; Williams, K. H.; Hubbard, S. S.

    2017-12-01

    Mountainous watershed systems are characterized by extreme heterogeneity in hydrological and pedological properties that influence biotic activities, plant communities and their dynamics. To gain predictive understanding of how ecosystem and watershed system evolve under climate change, it is critical to capture such heterogeneity and to quantify the effect of key environmental variables such as topography, and soil properties. In this study, we exploit advanced geophysical and remote sensing techniques - coupled with machine learning - to better characterize and quantify the interactions between plant communities' distribution and subsurface properties. First, we have developed a remote sensing data fusion framework based on the random forest (RF) classification algorithm to estimate the spatial distribution of plant communities. The framework allows the integration of both plant spectral and structural information, which are derived from multispectral satellite images and airborne LiDAR data. We then use the RF method to evaluate the estimated plant community map, exploiting the subsurface properties (such as bedrock depth, soil moisture and other properties) and geomorphological parameters (such as slope, curvature) as predictors. Datasets include high-resolution geophysical data (electrical resistivity tomography) and LiDAR digital elevation maps. We demonstrate our approach on a mountain hillslope and meadow within the East River watershed in Colorado, which is considered to be a representative headwater catchment in the Upper Colorado Basin. The obtained results show the existence of co-evolution between above and below-ground processes; in particular, dominant shrub communities in wet and flat areas. We show that successful integration of remote sensing data with geophysical measurements allows identifying and quantifying the key environmental controls on plant communities' distribution, and provides insights into their potential changes in the future

  10. Key Issues for Seamless Integrated Chemistry–Meteorology Modeling

    Science.gov (United States)

    Online coupled meteorology–atmospheric chemistry models have greatly evolved in recent years. Although mainly developed by the air quality modeling community, these integrated models are also of interest for numerical weather prediction and climate modeling, as they can con...

  11. Toward Designing a Quantum Key Distribution Network Simulation Model

    Directory of Open Access Journals (Sweden)

    Miralem Mehic

    2016-01-01

    Full Text Available As research in quantum key distribution network technologies grows larger and more complex, the need for highly accurate and scalable simulation technologies becomes important to assess the practical feasibility and foresee difficulties in the practical implementation of theoretical achievements. In this paper, we described the design of simplified simulation environment of the quantum key distribution network with multiple links and nodes. In such simulation environment, we analyzed several routing protocols in terms of the number of sent routing packets, goodput and Packet Delivery Ratio of data traffic flow using NS-3 simulator.

  12. 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.

  13. Structural identifiability analysis of a cardiovascular system model.

    Science.gov (United States)

    Pironet, Antoine; Dauby, Pierre C; Chase, J Geoffrey; Docherty, Paul D; Revie, James A; Desaive, Thomas

    2016-05-01

    The six-chamber cardiovascular system model of Burkhoff and Tyberg has been used in several theoretical and experimental studies. However, this cardiovascular system model (and others derived from it) are not identifiable from any output set. In this work, two such cases of structural non-identifiability are first presented. These cases occur when the model output set only contains a single type of information (pressure or volume). A specific output set is thus chosen, mixing pressure and volume information and containing only a limited number of clinically available measurements. Then, by manipulating the model equations involving these outputs, it is demonstrated that the six-chamber cardiovascular system model is structurally globally identifiable. A further simplification is made, assuming known cardiac valve resistances. Because of the poor practical identifiability of these four parameters, this assumption is usual. Under this hypothesis, the six-chamber cardiovascular system model is structurally identifiable from an even smaller dataset. As a consequence, parameter values computed from limited but well-chosen datasets are theoretically unique. This means that the parameter identification procedure can safely be performed on the model from such a well-chosen dataset. Thus, the model may be considered suitable for use in diagnosis. Copyright © 2016 IPEM. Published by Elsevier Ltd. All rights reserved.

  14. An Application Of Receptor Modeling To Identify Airborne Particulate ...

    African Journals Online (AJOL)

    An Application Of Receptor Modeling To Identify Airborne Particulate Sources In Lagos, Nigeria. FS Olise, OK Owoade, HB Olaniyi. Abstract. There have been no clear demarcations between industrial and residential areas of Lagos with focus on industry as the major source. There is need to identify potential source types in ...

  15. A System-Level Throughput Model for Quantum Key Distribution

    Science.gov (United States)

    2015-09-17

    discrete logarithms in a finite field [35]. Arguably the most popular asymmetric encryption scheme is the RSA algorithm, published a year later in...Theory, vol. 22, no. 6, pp. 644-654, 1976. [36] G. Singh and S. Supriya, ’A Study of Encryption Algorithms ( RSA , DES, 3DES and AES) for Information...xv Dictionary QKD = Quantum Key Distribution OTP = One-Time Pad cryptographic algorithm DES = Data Encryption Standard 3DES

  16. Identifying extensions required by RUP (Rational Unified Process) to comply with CMM (Capability Maturity Model) levels 2 and 3

    OpenAIRE

    Manzoni, Lisandra Vielmo; Price, Roberto Tom

    2003-01-01

    This paper describes an assessment of the Rational Unified Process (RUP) based on the Capability Maturity Model (CMM). For each key practice (KP) identified in each key process area (KPA) of CMM levels 2 and 3, the Rational Unified Process was assessed to determine whether it satisfied the KP or not. For each KPA, the percentage of the key practices supported was calculated, and the results were tabulated. The report includes considerations about the coverage of each key process area, describ...

  17. Identifiability of Model Properties in Over-Parameterized Model Classes

    DEFF Research Database (Denmark)

    Jaeger, Manfred

    2013-01-01

    Classical learning theory is based on a tight linkage between hypothesis space (a class of function on a domain X), data space (function-value examples (x, f(x))), and the space of queries for the learned model (predicting function values for new examples x). However, in many learning scenarios t...

  18. Key Challenges and Potential Urban Modelling Opportunities in ...

    African Journals Online (AJOL)

    Chris Wray

    There is a risk within .... Giere (2004) models are generally considered as simple representations of reality ..... morphology, connectivity, bid rent and virtual model room – were developed to ... term integrated planning of education and health.

  19. Identifying the important factors in simulation models with many factors

    NARCIS (Netherlands)

    Bettonvil, B.; Kleijnen, J.P.C.

    1994-01-01

    Simulation models may have many parameters and input variables (together called factors), while only a few factors are really important (parsimony principle). For such models this paper presents an effective and efficient screening technique to identify and estimate those important factors. The

  20. Structural identifiability of cyclic graphical models of biological networks with latent variables.

    Science.gov (United States)

    Wang, Yulin; Lu, Na; Miao, Hongyu

    2016-06-13

    Graphical models have long been used to describe biological networks for a variety of important tasks such as the determination of key biological parameters, and the structure of graphical model ultimately determines whether such unknown parameters can be unambiguously obtained from experimental observations (i.e., the identifiability problem). Limited by resources or technical capacities, complex biological networks are usually partially observed in experiment, which thus introduces latent variables into the corresponding graphical models. A number of previous studies have tackled the parameter identifiability problem for graphical models such as linear structural equation models (SEMs) with or without latent variables. However, the limited resolution and efficiency of existing approaches necessarily calls for further development of novel structural identifiability analysis algorithms. An efficient structural identifiability analysis algorithm is developed in this study for a broad range of network structures. The proposed method adopts the Wright's path coefficient method to generate identifiability equations in forms of symbolic polynomials, and then converts these symbolic equations to binary matrices (called identifiability matrix). Several matrix operations are introduced for identifiability matrix reduction with system equivalency maintained. Based on the reduced identifiability matrices, the structural identifiability of each parameter is determined. A number of benchmark models are used to verify the validity of the proposed approach. Finally, the network module for influenza A virus replication is employed as a real example to illustrate the application of the proposed approach in practice. The proposed approach can deal with cyclic networks with latent variables. The key advantage is that it intentionally avoids symbolic computation and is thus highly efficient. Also, this method is capable of determining the identifiability of each single parameter and

  1. Exploring key factors in online shopping with a hybrid model.

    Science.gov (United States)

    Chen, Hsiao-Ming; Wu, Chia-Huei; Tsai, Sang-Bing; Yu, Jian; Wang, Jiangtao; Zheng, Yuxiang

    2016-01-01

    Nowadays, the web increasingly influences retail sales. An in-depth analysis of consumer decision-making in the context of e-business has become an important issue for internet vendors. However, factors affecting e-business are complicated and intertwined. To stimulate online sales, understanding key influential factors and causal relationships among the factors is important. To gain more insights into this issue, this paper introduces a hybrid method, which combines the Decision Making Trial and Evaluation Laboratory (DEMATEL) with the analytic network process, called DANP method, to find out the driving factors that influence the online business mostly. By DEMATEL approach the causal graph showed that "online service" dimension has the highest degree of direct impact on other dimensions; thus, the internet vendor is suggested to made strong efforts on service quality throughout the online shopping process. In addition, the study adopted DANP to measure the importance of key factors, among which "transaction security" proves to be the most important criterion. Hence, transaction security should be treated with top priority to boost the online businesses. From our study with DANP approach, the comprehensive information can be visually detected so that the decision makers can spotlight on the root causes to develop effectual actions.

  2. Key Elements of the Tutorial Support Management Model

    Science.gov (United States)

    Lynch, Grace; Paasuke, Philip

    2011-01-01

    In response to an exponential growth in enrolments the "Tutorial Support Management" (TSM) model has been adopted by Open Universities Australia (OUA) after a two-year project on the provision of online tutor support in first year, online undergraduate units. The essential focus of the TSM model was the development of a systemic approach…

  3. EMF 7 model comparisons: key relationships and parameters

    Energy Technology Data Exchange (ETDEWEB)

    Hickman, B.G.

    1983-12-01

    A simplified textbook model of aggregate demand and supply interprets the similarities and differences in the price and income responses of the various EMF 7 models to oil and policy shocks. The simplified model is a marriage of Hicks' classic IS-LM formulation of the Keynesian theory of effective demand with a rudimentary model of aggregate supply, combining a structural Phillips curve for wage determination and a markup theory of price determination. The reduced-form income equation from the fix-price IS-LM model is used to define an aggregate demand (AD) locus in P-Y space, showing alternative pairs of the implicit GNP deflator and real GNP which would simultaneously satisfy the saving-investment identity and the condition for money market equilibrium. An aggregate supply (AS) schedule is derived by a similar reduction of relations between output and labor demand, unemployment and wage inflation, and the wage-price-productivity nexus governing markup pricing. Given a particular econometric model it is possible to derive IS and LM curves algebraically. The resulting locuses would show alternative combinations of interest rate and real income which equilibrate real income identity on the IS side and the demand and supply of money on the LM side. By further substitution the reduced form fix-price income relation could be obtained for direct quantification of the AD locus. The AS schedule is obtainable by algebraic reduction of the structural supply side equations.

  4. COMPREHENSIVE CHECK MEASUREMENT OF KEY PARAMETERS ON MODEL BELT CONVEYOR

    Directory of Open Access Journals (Sweden)

    Vlastimil MONI

    2013-07-01

    Full Text Available Complex measurements of characteristic parameters realised on a long distance model belt conveyor are described. The main objective was to complete and combine the regular measurements of electric power on drives of belt conveyors operated in Czech opencast mines with measurements of other physical quantities and to gain by this way an image of their mutual relations and relations of quantities derived from them. The paper includes a short description and results of the measurements on an experimental model conveyor with a closed material transport way.

  5. Selection of key terrain attributes for SOC model

    DEFF Research Database (Denmark)

    Greve, Mogens Humlekrog; Adhikari, Kabindra; Chellasamy, Menaka

    As an important component of the global carbon pool, soil organic carbon (SOC) plays an important role in the global carbon cycle. SOC pool is the basic information to carry out global warming research, and needs to sustainable use of land resources. Digital terrain attributes are often use...... was selected, total 2,514,820 data mining models were constructed by 71 differences grid from 12m to 2304m and 22 attributes, 21 attributes derived by DTM and the original elevation. Relative importance and usage of each attributes in every model were calculated. Comprehensive impact rates of each attribute...

  6. Identifying key factors for mobilising under-utilised low carbon land resources : A case study on Kalimantan

    NARCIS (Netherlands)

    Goh, Chun Sheng; Junginger, Martin; Potter, Lesley; Faaij, André; Wicke, Birka

    2018-01-01

    Mobilising under-utilised low carbon (ULC) land for future agricultural expansion helps minimising further carbon stock loss. This study examined the regency cases in Kalimantan, a carbon loss hotspot, to understand the key factors for mobilising ULC land via narrative interviews with a range of

  7. Use of a scenario-neutral approach to identify the key hydro-meteorological attributes that impact runoff from a natural catchment

    Science.gov (United States)

    Guo, Danlu; Westra, Seth; Maier, Holger R.

    2017-11-01

    Scenario-neutral approaches are being used increasingly for assessing the potential impact of climate change on water resource systems, as these approaches allow the performance of these systems to be evaluated independently of climate change projections. However, practical implementations of these approaches are still scarce, with a key limitation being the difficulty of generating a range of plausible future time series of hydro-meteorological data. In this study we apply a recently developed inverse stochastic generation approach to support the scenario-neutral analysis, and thus identify the key hydro-meteorological variables to which the system is most sensitive. The stochastic generator simulates synthetic hydro-meteorological time series that represent plausible future changes in (1) the average, extremes and seasonal patterns of rainfall; and (2) the average values of temperature (Ta), relative humidity (RH) and wind speed (uz) as variables that drive PET. These hydro-meteorological time series are then fed through a conceptual rainfall-runoff model to simulate the potential changes in runoff as a function of changes in the hydro-meteorological variables, and runoff sensitivity is assessed with both correlation and Sobol' sensitivity analyses. The method was applied to a case study catchment in South Australia, and the results showed that the most important hydro-meteorological attributes for runoff were winter rainfall followed by the annual average rainfall, while the PET-related meteorological variables had comparatively little impact. The high importance of winter rainfall can be related to the winter-dominated nature of both the rainfall and runoff regimes in this catchment. The approach illustrated in this study can greatly enhance our understanding of the key hydro-meteorological attributes and processes that are likely to drive catchment runoff under a changing climate, thus enabling the design of tailored climate impact assessments to specific

  8. Identifying the connective strength between model parameters and performance criteria

    Directory of Open Access Journals (Sweden)

    B. Guse

    2017-11-01

    Full Text Available In hydrological models, parameters are used to represent the time-invariant characteristics of catchments and to capture different aspects of hydrological response. Hence, model parameters need to be identified based on their role in controlling the hydrological behaviour. For the identification of meaningful parameter values, multiple and complementary performance criteria are used that compare modelled and measured discharge time series. The reliability of the identification of hydrologically meaningful model parameter values depends on how distinctly a model parameter can be assigned to one of the performance criteria. To investigate this, we introduce the new concept of connective strength between model parameters and performance criteria. The connective strength assesses the intensity in the interrelationship between model parameters and performance criteria in a bijective way. In our analysis of connective strength, model simulations are carried out based on a latin hypercube sampling. Ten performance criteria including Nash–Sutcliffe efficiency (NSE, Kling–Gupta efficiency (KGE and its three components (alpha, beta and r as well as RSR (the ratio of the root mean square error to the standard deviation for different segments of the flow duration curve (FDC are calculated. With a joint analysis of two regression tree (RT approaches, we derive how a model parameter is connected to different performance criteria. At first, RTs are constructed using each performance criterion as the target variable to detect the most relevant model parameters for each performance criterion. Secondly, RTs are constructed using each parameter as the target variable to detect which performance criteria are impacted by changes in the values of one distinct model parameter. Based on this, appropriate performance criteria are identified for each model parameter. In this study, a high bijective connective strength between model parameters and performance criteria

  9. Gene Network Construction from Microarray Data Identifies a Key Network Module and Several Candidate Hub Genes in Age-Associated Spatial Learning Impairment.

    Science.gov (United States)

    Uddin, Raihan; Singh, Shiva M

    2017-01-01

    As humans age many suffer from a decrease in normal brain functions including spatial learning impairments. This study aimed to better understand the molecular mechanisms in age-associated spatial learning impairment (ASLI). We used a mathematical modeling approach implemented in Weighted Gene Co-expression Network Analysis (WGCNA) to create and compare gene network models of young (learning unimpaired) and aged (predominantly learning impaired) brains from a set of exploratory datasets in rats in the context of ASLI. The major goal was to overcome some of the limitations previously observed in the traditional meta- and pathway analysis using these data, and identify novel ASLI related genes and their networks based on co-expression relationship of genes. This analysis identified a set of network modules in the young, each of which is highly enriched with genes functioning in broad but distinct GO functional categories or biological pathways. Interestingly, the analysis pointed to a single module that was highly enriched with genes functioning in "learning and memory" related functions and pathways. Subsequent differential network analysis of this "learning and memory" module in the aged (predominantly learning impaired) rats compared to the young learning unimpaired rats allowed us to identify a set of novel ASLI candidate hub genes. Some of these genes show significant repeatability in networks generated from independent young and aged validation datasets. These hub genes are highly co-expressed with other genes in the network, which not only show differential expression but also differential co-expression and differential connectivity across age and learning impairment. The known function of these hub genes indicate that they play key roles in critical pathways, including kinase and phosphatase signaling, in functions related to various ion channels, and in maintaining neuronal integrity relating to synaptic plasticity and memory formation. Taken together, they

  10. Accessing key steps of human tumor progression in vivo by using an avian embryo model

    Science.gov (United States)

    Hagedorn, Martin; Javerzat, Sophie; Gilges, Delphine; Meyre, Aurélie; de Lafarge, Benjamin; Eichmann, Anne; Bikfalvi, Andreas

    2005-02-01

    Experimental in vivo tumor models are essential for comprehending the dynamic process of human cancer progression, identifying therapeutic targets, and evaluating antitumor drugs. However, current rodent models are limited by high costs, long experimental duration, variability, restricted accessibility to the tumor, and major ethical concerns. To avoid these shortcomings, we investigated whether tumor growth on the chick chorio-allantoic membrane after human glioblastoma cell grafting would replicate characteristics of the human disease. Avascular tumors consistently formed within 2 days, then progressed through vascular endothelial growth factor receptor 2-dependent angiogenesis, associated with hemorrhage, necrosis, and peritumoral edema. Blocking of vascular endothelial growth factor receptor 2 and platelet-derived growth factor receptor signaling pathways by using small-molecule receptor tyrosine kinase inhibitors abrogated tumor development. Gene regulation during the angiogenic switch was analyzed by oligonucleotide microarrays. Defined sample selection for gene profiling permitted identification of regulated genes whose functions are associated mainly with tumor vascularization and growth. Furthermore, expression of known tumor progression genes identified in the screen (IL-6 and cysteine-rich angiogenic inducer 61) as well as potential regulators (lumican and F-box-only 6) follow similar patterns in patient glioma. The model reliably simulates key features of human glioma growth in a few days and thus could considerably increase the speed and efficacy of research on human tumor progression and preclinical drug screening. angiogenesis | animal model alternatives | glioblastoma

  11. Identifiability and error minimization of receptor model parameters with PET

    International Nuclear Information System (INIS)

    Delforge, J.; Syrota, A.; Mazoyer, B.M.

    1989-01-01

    The identifiability problem and the general framework for experimental design optimization are presented. The methodology is applied to the problem of the receptor-ligand model parameter estimation with dynamic positron emission tomography data. The first attempts to identify the model parameters from data obtained with a single tracer injection led to disappointing numerical results. The possibility of improving parameter estimation using a new experimental design combining an injection of the labelled ligand and an injection of the cold ligand (displacement experiment) has been investigated. However, this second protocol led to two very different numerical solutions and it was necessary to demonstrate which solution was biologically valid. This has been possible by using a third protocol including both a displacement and a co-injection experiment. (authors). 16 refs.; 14 figs

  12. USING THE PARETO DIAGRAM AND FMEA (FAILURE MODE AND EFFECTS ANALYSIS TO IDENTIFY KEY DEFECTS IN A PRODUCT

    Directory of Open Access Journals (Sweden)

    Michał ZASADZIEŃ

    2014-10-01

    Full Text Available The article presents the results of studies conducted in a company manufacturing aluminium forgings for the automotive industry. The aim of the research was to identify the defects which form during the production process as well as the locations and causes of their occurrence. Selected quality management tools were used in the process. Based on the FMEA and the costs generated by the identified defects, a hierarchy of them was created for the company along with a proposal of improvements in case of the most significant ones in order to reduce their number and increase the detection efficiency.

  13. Genome-wide association studies of autoimmune vitiligo identify 23 new risk loci and highlight key pathways and regulatory variants

    NARCIS (Netherlands)

    Jin, Ying; Andersen, Genevieve; Yorgov, Daniel; Ferrara, Tracey M.; Ben, Songtao; Brownson, Kelly M.; Holland, Paulene J.; Birlea, Stanca A.; Siebert, Janet; Hartmann, Anke; Lienert, Anne; van Geel, Nanja; Lambert, Jo; Luiten, Rosalie M.; Wolkerstorfer, Albert; Wietze van der Veen, J. P.; Bennett, Dorothy C.; Taïeb, Alain; Ezzedine, Khaled; Kemp, E. Helen; Gawkrodger, David J.; Weetman, Anthony P.; Kõks, Sulev; Prans, Ele; Kingo, Külli; Karelson, Maire; Wallace, Margaret R.; McCormack, Wayne T.; Overbeck, Andreas; Moretti, Silvia; Colucci, Roberta; Picardo, Mauro; Silverberg, Nanette B.; Olsson, Mats; Valle, Yan; Korobko, Igor; Böhm, Markus; Lim, Henry W.; Hamzavi, Iltefat; Zhou, Li; Mi, Qing-Sheng; Fain, Pamela R.; Santorico, Stephanie A.; Spritz, Richard A.

    2016-01-01

    Vitiligo is an autoimmune disease in which depigmented skin results from the destruction of melanocytes, with epidemiological association with other autoimmune diseases. In previous linkage and genome-wide association studies (GWAS1 and GWAS2), we identified 27 vitiligo susceptibility loci in

  14. A Large-Scale RNAi Screen Identifies SGK1 as a Key Survival Kinase for GBM Stem Cells.

    Science.gov (United States)

    Kulkarni, Shreya; Goel-Bhattacharya, Surbhi; Sengupta, Sejuti; Cochran, Brent H

    2018-01-01

    Glioblastoma multiforme (GBM) is the most common type of primary malignant brain cancer and has a very poor prognosis. A subpopulation of cells known as GBM stem-like cells (GBM-SC) have the capacity to initiate and sustain tumor growth and possess molecular characteristics similar to the parental tumor. GBM-SCs are known to be enriched in hypoxic niches and may contribute to therapeutic resistance. Therefore, to identify genetic determinants important for the proliferation and survival of GBM stem cells, an unbiased pooled shRNA screen of 10,000 genes was conducted under normoxic as well as hypoxic conditions. A number of essential genes were identified that are required for GBM-SC growth, under either or both oxygen conditions, in two different GBM-SC lines. Interestingly, only about a third of the essential genes were common to both cell lines. The oxygen environment significantly impacts the cellular genetic dependencies as 30% of the genes required under hypoxia were not required under normoxic conditions. In addition to identifying essential genes already implicated in GBM such as CDK4, KIF11 , and RAN , the screen also identified new genes that have not been previously implicated in GBM stem cell biology. The importance of the serum and glucocorticoid-regulated kinase 1 (SGK1) for cellular survival was validated in multiple patient-derived GBM stem cell lines using shRNA, CRISPR, and pharmacologic inhibitors. However, SGK1 depletion and inhibition has little effect on traditional serum grown glioma lines and on differentiated GBM-SCs indicating its specific importance in GBM stem cell survival. Implications: This study identifies genes required for the growth and survival of GBM stem cells under both normoxic and hypoxic conditions and finds SGK1 as a novel potential drug target for GBM. Mol Cancer Res; 16(1); 103-14. ©2017 AACR . ©2017 American Association for Cancer Research.

  15. Does Your Terrestrial Model Capture Key Arctic-Boreal Relationships?: Functional Benchmarks in the ABoVE Model Benchmarking System

    Science.gov (United States)

    Stofferahn, E.; Fisher, J. B.; Hayes, D. J.; Schwalm, C. R.; Huntzinger, D. N.; Hantson, W.

    2017-12-01

    The Arctic-Boreal Region (ABR) is a major source of uncertainties for terrestrial biosphere model (TBM) simulations. These uncertainties are precipitated by a lack of observational data from the region, affecting the parameterizations of cold environment processes in the models. Addressing these uncertainties requires a coordinated effort of data collection and integration of the following key indicators of the ABR ecosystem: disturbance, vegetation / ecosystem structure and function, carbon pools and biogeochemistry, permafrost, and hydrology. We are continuing to develop the model-data integration framework for NASA's Arctic Boreal Vulnerability Experiment (ABoVE), wherein data collection is driven by matching observations and model outputs to the ABoVE indicators via the ABoVE Grid and Projection. The data are used as reference datasets for a benchmarking system which evaluates TBM performance with respect to ABR processes. The benchmarking system utilizes two types of performance metrics to identify model strengths and weaknesses: standard metrics, based on the International Land Model Benchmarking (ILaMB) system, which relate a single observed variable to a single model output variable, and functional benchmarks, wherein the relationship of one variable to one or more variables (e.g. the dependence of vegetation structure on snow cover, the dependence of active layer thickness (ALT) on air temperature and snow cover) is ascertained in both observations and model outputs. This in turn provides guidance to model development teams for reducing uncertainties in TBM simulations of the ABR.

  16. From spatially variable streamflow to distributed hydrological models: Analysis of key modeling decisions

    Science.gov (United States)

    Fenicia, Fabrizio; Kavetski, Dmitri; Savenije, Hubert H. G.; Pfister, Laurent

    2016-02-01

    This paper explores the development and application of distributed hydrological models, focusing on the key decisions of how to discretize the landscape, which model structures to use in each landscape element, and how to link model parameters across multiple landscape elements. The case study considers the Attert catchment in Luxembourg—a 300 km2 mesoscale catchment with 10 nested subcatchments that exhibit clearly different streamflow dynamics. The research questions are investigated using conceptual models applied at hydrologic response unit (HRU) scales (1-4 HRUs) on 6 hourly time steps. Multiple model structures are hypothesized and implemented using the SUPERFLEX framework. Following calibration, space/time model transferability is tested using a split-sample approach, with evaluation criteria including streamflow prediction error metrics and hydrological signatures. Our results suggest that: (1) models using geology-based HRUs are more robust and capture the spatial variability of streamflow time series and signatures better than models using topography-based HRUs; this finding supports the hypothesis that, in the Attert, geology exerts a stronger control than topography on streamflow generation, (2) streamflow dynamics of different HRUs can be represented using distinct and remarkably simple model structures, which can be interpreted in terms of the perceived dominant hydrologic processes in each geology type, and (3) the same maximum root zone storage can be used across the three dominant geological units with no loss in model transferability; this finding suggests that the partitioning of water between streamflow and evaporation in the study area is largely independent of geology and can be used to improve model parsimony. The modeling methodology introduced in this study is general and can be used to advance our broader understanding and prediction of hydrological behavior, including the landscape characteristics that control hydrologic response, the

  17. RNA sequencing of Populus x canadensis roots identifies key molecular mechanisms underlying physiological adaption to excess zinc.

    Directory of Open Access Journals (Sweden)

    Andrea Ariani

    Full Text Available Populus x canadensis clone I-214 exhibits a general indicator phenotype in response to excess Zn, and a higher metal uptake in roots than in shoots with a reduced translocation to aerial parts under hydroponic conditions. This physiological adaptation seems mainly regulated by roots, although the molecular mechanisms that underlie these processes are still poorly understood. Here, differential expression analysis using RNA-sequencing technology was used to identify the molecular mechanisms involved in the response to excess Zn in root. In order to maximize specificity of detection of differentially expressed (DE genes, we consider the intersection of genes identified by three distinct statistical approaches (61 up- and 19 down-regulated and validate them by RT-qPCR, yielding an agreement of 93% between the two experimental techniques. Gene Ontology (GO terms related to oxidation-reduction processes, transport and cellular iron ion homeostasis were enriched among DE genes, highlighting the importance of metal homeostasis in adaptation to excess Zn by P. x canadensis clone I-214. We identified the up-regulation of two Populus metal transporters (ZIP2 and NRAMP1 probably involved in metal uptake, and the down-regulation of a NAS4 gene involved in metal translocation. We identified also four Fe-homeostasis transcription factors (two bHLH38 genes, FIT and BTS that were differentially expressed, probably for reducing Zn-induced Fe-deficiency. In particular, we suggest that the down-regulation of FIT transcription factor could be a mechanism to cope with Zn-induced Fe-deficiency in Populus. These results provide insight into the molecular mechanisms involved in adaption to excess Zn in Populus spp., but could also constitute a starting point for the identification and characterization of molecular markers or biotechnological targets for possible improvement of phytoremediation performances of poplar trees.

  18. Global metabolic analyses identify key differences in metabolite levels between polymyxin-susceptible and polymyxin-resistant Acinetobacter baumannii.

    Science.gov (United States)

    Maifiah, Mohd Hafidz Mahamad; Cheah, Soon-Ee; Johnson, Matthew D; Han, Mei-Ling; Boyce, John D; Thamlikitkul, Visanu; Forrest, Alan; Kaye, Keith S; Hertzog, Paul; Purcell, Anthony W; Song, Jiangning; Velkov, Tony; Creek, Darren J; Li, Jian

    2016-02-29

    Multidrug-resistant Acinetobacter baumannii presents a global medical crisis and polymyxins are used as the last-line therapy. This study aimed to identify metabolic differences between polymyxin-susceptible and polymyxin-resistant A. baumannii using untargeted metabolomics. The metabolome of each A. baumannii strain was measured using liquid chromatography-mass spectrometry. Multivariate and univariate statistics and pathway analyses were employed to elucidate metabolic differences between the polymyxin-susceptible and -resistant A. baumannii strains. Significant differences were identified between the metabolic profiles of the polymyxin-susceptible and -resistant A. baumannii strains. The lipopolysaccharide (LPS) deficient, polymyxin-resistant 19606R showed perturbation in specific amino acid and carbohydrate metabolites, particularly pentose phosphate pathway (PPP) and tricarboxylic acid (TCA) cycle intermediates. Levels of nucleotides were lower in the LPS-deficient 19606R. Furthermore, 19606R exhibited a shift in its glycerophospholipid profile towards increased abundance of short-chain lipids compared to the parent polymyxin-susceptible ATCC 19606. In contrast, in a pair of clinical isolates 03-149.1 (polymyxin-susceptible) and 03-149.2 (polymyxin-resistant, due to modification of lipid A), minor metabolic differences were identified. Notably, peptidoglycan biosynthesis metabolites were significantly depleted in both of the aforementioned polymyxin-resistant strains. This is the first comparative untargeted metabolomics study to show substantial differences in the metabolic profiles of the polymyxin-susceptible and -resistant A. baumannii.

  19. Genome-wide association studies of autoimmune vitiligo identify 23 new risk loci and highlight key pathways and regulatory variants.

    Science.gov (United States)

    Jin, Ying; Andersen, Genevieve; Yorgov, Daniel; Ferrara, Tracey M; Ben, Songtao; Brownson, Kelly M; Holland, Paulene J; Birlea, Stanca A; Siebert, Janet; Hartmann, Anke; Lienert, Anne; van Geel, Nanja; Lambert, Jo; Luiten, Rosalie M; Wolkerstorfer, Albert; Wietze van der Veen, J P; Bennett, Dorothy C; Taïeb, Alain; Ezzedine, Khaled; Kemp, E Helen; Gawkrodger, David J; Weetman, Anthony P; Kõks, Sulev; Prans, Ele; Kingo, Külli; Karelson, Maire; Wallace, Margaret R; McCormack, Wayne T; Overbeck, Andreas; Moretti, Silvia; Colucci, Roberta; Picardo, Mauro; Silverberg, Nanette B; Olsson, Mats; Valle, Yan; Korobko, Igor; Böhm, Markus; Lim, Henry W; Hamzavi, Iltefat; Zhou, Li; Mi, Qing-Sheng; Fain, Pamela R; Santorico, Stephanie A; Spritz, Richard A

    2016-11-01

    Vitiligo is an autoimmune disease in which depigmented skin results from the destruction of melanocytes, with epidemiological association with other autoimmune diseases. In previous linkage and genome-wide association studies (GWAS1 and GWAS2), we identified 27 vitiligo susceptibility loci in patients of European ancestry. We carried out a third GWAS (GWAS3) in European-ancestry subjects, with augmented GWAS1 and GWAS2 controls, genome-wide imputation, and meta-analysis of all three GWAS, followed by an independent replication. The combined analyses, with 4,680 cases and 39,586 controls, identified 23 new significantly associated loci and 7 suggestive loci. Most encode immune and apoptotic regulators, with some also associated with other autoimmune diseases, as well as several melanocyte regulators. Bioinformatic analyses indicate a predominance of causal regulatory variation, some of which corresponds to expression quantitative trait loci (eQTLs) at these loci. Together, the identified genes provide a framework for the genetic architecture and pathobiology of vitiligo, highlight relationships with other autoimmune diseases and melanoma, and offer potential targets for treatment.

  20. Genome-wide association studies of autoimmune vitiligo identify 23 new risk loci and highlight key pathways and regulatory variants

    Science.gov (United States)

    Jin, Ying; Andersen, Genevieve; Yorgov, Daniel; Ferrara, Tracey M; Ben, Songtao; Brownson, Kelly M; Holland, Paulene J; Birlea, Stanca A; Siebert, Janet; Hartmann, Anke; Lienert, Anne; van Geel, Nanja; Lambert, Jo; Luiten, Rosalie M; Wolkerstorfer, Albert; van der Veen, JP Wietze; Bennett, Dorothy C; Taïeb, Alain; Ezzedine, Khaled; Kemp, E Helen; Gawkrodger, David J; Weetman, Anthony P; Kõks, Sulev; Prans, Ele; Kingo, Külli; Karelson, Maire; Wallace, Margaret R; McCormack, Wayne T; Overbeck, Andreas; Moretti, Silvia; Colucci, Roberta; Picardo, Mauro; Silverberg, Nanette B; Olsson, Mats; Valle, Yan; Korobko, Igor; Böhm, Markus; Lim, Henry W.; Hamzavi, Iltefat; Zhou, Li; Mi, Qing-Sheng; Fain, Pamela R.; Santorico, Stephanie A; Spritz, Richard A

    2016-01-01

    Vitiligo is an autoimmune disease in which depigmented skin results from destruction of melanocytes1, with epidemiologic association with other autoimmune diseases2. In previous linkage and genome-wide association studies (GWAS1, GWAS2), we identified 27 vitiligo susceptibility loci in patients of European (EUR) ancestry. We carried out a third GWAS (GWAS3) in EUR subjects, with augmented GWAS1 and GWAS2 controls, genome-wide imputation, and meta-analysis of all three GWAS, followed by an independent replication. The combined analyses, with 4,680 cases and 39,586 controls, identified 23 new loci and 7 suggestive loci, most encoding immune and apoptotic regulators, some also associated with other autoimmune diseases, as well as several melanocyte regulators. Bioinformatic analyses indicate a predominance of causal regulatory variation, some corresponding to eQTL at these loci. Together, the identified genes provide a framework for vitiligo genetic architecture and pathobiology, highlight relationships to other autoimmune diseases and melanoma, and offer potential targets for treatment. PMID:27723757

  1. Modelling the regional application of stakeholder identified land management strategies.

    Science.gov (United States)

    Irvine, B. J.; Fleskens, L.; Kirkby, M. J.

    2012-04-01

    The DESIRE project has trialled a series of sustainable land management (SLM) technologies. These technologies have been identified as being beneficial in mitigating land degradation by local stakeholders from a range of semi-arid study sites. The field results and the qualitative WOCAT technology assessment ftom across the study sites have been used to develop the adapted PESERA SLM model. This paper considers the development of the adapted PESERA SLM model and the potential for applying locally successful SLM technologies across a wider range of climatic and environmental conditions with respect to degradation risk, biomass production and the investment cost interface (PESERA/DESMICE). The integrate PESERA/DESMICE model contributes to the policy debate by providing a biophysical and socio-economic assessment of technology and policy scenarios.

  2. Bi-directional gene set enrichment and canonical correlation analysis identify key diet-sensitive pathways and biomarkers of metabolic syndrome

    Directory of Open Access Journals (Sweden)

    Gaora Peadar Ó

    2010-10-01

    Full Text Available Abstract Background Currently, a number of bioinformatics methods are available to generate appropriate lists of genes from a microarray experiment. While these lists represent an accurate primary analysis of the data, fewer options exist to contextualise those lists. The development and validation of such methods is crucial to the wider application of microarray technology in the clinical setting. Two key challenges in clinical bioinformatics involve appropriate statistical modelling of dynamic transcriptomic changes, and extraction of clinically relevant meaning from very large datasets. Results Here, we apply an approach to gene set enrichment analysis that allows for detection of bi-directional enrichment within a gene set. Furthermore, we apply canonical correlation analysis and Fisher's exact test, using plasma marker data with known clinical relevance to aid identification of the most important gene and pathway changes in our transcriptomic dataset. After a 28-day dietary intervention with high-CLA beef, a range of plasma markers indicated a marked improvement in the metabolic health of genetically obese mice. Tissue transcriptomic profiles indicated that the effects were most dramatic in liver (1270 genes significantly changed; p Conclusion Bi-directional gene set enrichment analysis more accurately reflects dynamic regulatory behaviour in biochemical pathways, and as such highlighted biologically relevant changes that were not detected using a traditional approach. In such cases where transcriptomic response to treatment is exceptionally large, canonical correlation analysis in conjunction with Fisher's exact test highlights the subset of pathways showing strongest correlation with the clinical markers of interest. In this case, we have identified selenoamino acid metabolism and steroid biosynthesis as key pathways mediating the observed relationship between metabolic health and high-CLA beef. These results indicate that this type of

  3. Structural characterization of POM6 Fab and mouse prion protein complex identifies key regions for prions conformational conversion.

    Science.gov (United States)

    Baral, Pravas Kumar; Swayampakula, Mridula; Aguzzi, Adriano; James, Michael N G

    2018-05-01

    Conversion of the cellular prion protein PrP C into its pathogenic isoform PrP S c is the hallmark of prion diseases, fatal neurodegenerative diseases affecting many mammalian species including humans. Anti-prion monoclonal antibodies can arrest the progression of prion diseases by stabilizing the cellular form of the prion protein. Here, we present the crystal structure of the POM6 Fab fragment, in complex with the mouse prion protein (moPrP). The prion epitope of POM6 is in close proximity to the epitope recognized by the purportedly toxic antibody fragment, POM1 Fab also complexed with moPrP. The POM6 Fab recognizes a larger binding interface indicating a likely stronger binding compared to POM1. POM6 and POM1 exhibit distinct biological responses. Structural comparisons of the bound mouse prion proteins from the POM6 Fab:moPrP and POM1 Fab:moPrP complexes reveal several key regions of the prion protein that might be involved in initiating mis-folding events. The structural data of moPrP:POM6 Fab complex are available in the PDB under the accession number www.rcsb.org/pdb/search/structidSearch.do?structureId=6AQ7. © 2018 Federation of European Biochemical Societies.

  4. Community landscapes: an integrative approach to determine overlapping network module hierarchy, identify key nodes and predict network dynamics.

    Directory of Open Access Journals (Sweden)

    István A Kovács

    Full Text Available BACKGROUND: Network communities help the functional organization and evolution of complex networks. However, the development of a method, which is both fast and accurate, provides modular overlaps and partitions of a heterogeneous network, has proven to be rather difficult. METHODOLOGY/PRINCIPAL FINDINGS: Here we introduce the novel concept of ModuLand, an integrative method family determining overlapping network modules as hills of an influence function-based, centrality-type community landscape, and including several widely used modularization methods as special cases. As various adaptations of the method family, we developed several algorithms, which provide an efficient analysis of weighted and directed networks, and (1 determine persvasively overlapping modules with high resolution; (2 uncover a detailed hierarchical network structure allowing an efficient, zoom-in analysis of large networks; (3 allow the determination of key network nodes and (4 help to predict network dynamics. CONCLUSIONS/SIGNIFICANCE: The concept opens a wide range of possibilities to develop new approaches and applications including network routing, classification, comparison and prediction.

  5. The Relationship between Race and Students' Identified Career Role Models and Perceived Role Model Influence

    Science.gov (United States)

    Karunanayake, Danesh; Nauta, Margaret M.

    2004-01-01

    The authors examined whether college students' race was related to the modal race of their identified career role models, the number of identified career role models, and their perceived influence from such models. Consistent with A. Bandura's (1977, 1986) social learning theory, students tended to have role models whose race was the same as…

  6. RNA-Seq analysis identifies key genes associated with haustorial development in the root hemiparasite Santalum album

    Directory of Open Access Journals (Sweden)

    Xinhua eZhang

    2015-09-01

    Full Text Available Santalum album (sandalwood is one of the economically important plant species in the Santalaceae for its production of highly valued perfume oils. Sandalwood is also a hemiparasitic tree that obtains some of its water and simple nutrients by tapping into other plants through haustoria which are highly specialized organs in parasitic angiosperms. However, an understanding of the molecular mechanisms involved in haustorium development is limited. In this study, RNA sequencing (RNA-seq analyses were performed to identify changes in gene expression and metabolic pathways associated with the development of the S. album haustorium. A total of 56,011 non-redundant contigs with a mean contig size of 618 bp were obtained by de novo assembly of the transcriptome of haustoria and non-haustorial seedling roots. A substantial number of the identified differentially expressed genes were involved in cell wall metabolism and protein metabolism, as well as mitochondrial electron transport functions. Phytohormone-mediated regulation might play an important role during haustorial development. Especially, auxin signaling is likely to be essential for haustorial initiation, and genes related to cytokinin and gibberellin biosynthesis and metabolism are involved in haustorial development. Our results suggest that genes encoding nodulin-like proteins may be important for haustorial morphogenesis in S. album. The obtained sequence data will become a rich resource for future research in this interesting species. This information improves our understanding of haustorium development in root hemiparasitic species and will allow further exploration of the detailed molecular mechanisms underlying plant parasitism.

  7. Genomics and relative expression analysis identifies key genes associated with high female to male flower ratio in Jatropha curcas L.

    Science.gov (United States)

    Gangwar, Manali; Sood, Hemant; Chauhan, Rajinder Singh

    2016-04-01

    Jatropha curcas, has been projected as a major source of biodiesel due to high seed oil content (42 %). A major roadblock for commercialization of Jatropha-based biodiesel is low seed yield per inflorescence, which is affected by low female to male flower ratio (1:25-30). Molecular dissection of female flower development by analyzing genes involved in phase transitions and floral organ development is, therefore, crucial for increasing seed yield. Expression analysis of 42 genes implicated in floral organ development and sex determination was done at six floral developmental stages of a J. curcas genotype (IC561235) with inherently higher female to male flower ratio (1:8-10). Relative expression analysis of these genes was done on low ratio genotype. Genes TFL1, SUP, AP1, CRY2, CUC2, CKX1, TAA1 and PIN1 were associated with reproductive phase transition. Further, genes CUC2, TAA1, CKX1 and PIN1 were associated with female flowering while SUP and CRY2 in female flower transition. Relative expression of these genes with respect to low female flower ratio genotype showed up to ~7 folds increase in transcript abundance of SUP, TAA1, CRY2 and CKX1 genes in intermediate buds but not a significant increase (~1.25 folds) in female flowers, thereby suggesting that these genes possibly play a significant role in increased transition towards female flowering by promoting abortion of male flower primordia. The outcome of study has implications in feedstock improvement of J. curcas through functional validation and eventual utilization of key genes associated with female flowering.

  8. Solution scanning as a key policy tool: identifying management interventions to help maintain and enhance regulating ecosystem services

    Directory of Open Access Journals (Sweden)

    William J. Sutherland

    2014-06-01

    Full Text Available The major task of policy makers and practitioners when confronted with a resource management problem is to decide on the potential solution(s to adopt from a range of available options. However, this process is unlikely to be successful and cost effective without access to an independently verified and comprehensive available list of options. There is currently burgeoning interest in ecosystem services and quantitative assessments of their importance and value. Recognition of the value of ecosystem services to human well-being represents an increasingly important argument for protecting and restoring the natural environment, alongside the moral and ethical justifications for conservation. As well as understanding the benefits of ecosystem services, it is also important to synthesize the practical interventions that are capable of maintaining and/or enhancing these services. Apart from pest regulation, pollination, and global climate regulation, this type of exercise has attracted relatively little attention. Through a systematic consultation exercise, we identify a candidate list of 296 possible interventions across the main regulating services of air quality regulation, climate regulation, water flow regulation, erosion regulation, water purification and waste treatment, disease regulation, pest regulation, pollination and natural hazard regulation. The range of interventions differs greatly between habitats and services depending upon the ease of manipulation and the level of research intensity. Some interventions have the potential to deliver benefits across a range of regulating services, especially those that reduce soil loss and maintain forest cover. Synthesis and applications: Solution scanning is important for questioning existing knowledge and identifying the range of options available to researchers and practitioners, as well as serving as the necessary basis for assessing cost effectiveness and guiding implementation strategies. We

  9. Interpretive Structural Model of Key Performance Indicators for Sustainable Maintenance Evaluatian in Rubber Industry

    Science.gov (United States)

    Amrina, E.; Yulianto, A.

    2018-03-01

    Sustainable maintenance is a new challenge for manufacturing companies to realize sustainable development. In this paper, an interpretive structural model is developed to evaluate sustainable maintenance in the rubber industry. The initial key performance indicators (KPIs) is identified and derived from literature and then validated by academic and industry experts. As a result, three factors of economic, social, and environmental dividing into a total of thirteen indicators are proposed as the KPIs for sustainable maintenance evaluation in rubber industry. Interpretive structural modeling (ISM) methodology is applied to develop a network structure model of the KPIs consisting of three levels. The results show the economic factor is regarded as the basic factor, the social factor as the intermediate factor, while the environmental factor indicated to be the leading factor. Two indicators of social factor i.e. labor relationship, and training and education have both high driver and dependence power, thus categorized as the unstable indicators which need further attention. All the indicators of environmental factor and one indicator of social factor are indicated as the most influencing indicator. The interpretive structural model hoped can aid the rubber companies in evaluating sustainable maintenance performance.

  10. Identifying Student and Teacher Difficulties in Interpreting Atomic Spectra Using a Quantum Model of Emission and Absorption of Radiation

    Science.gov (United States)

    Savall-Alemany, Francisco; Domènech-Blanco, Josep Lluís; Guisasola, Jenaro; Martínez-Torregrosa, Joaquín

    2016-01-01

    Our study sets out to identify the difficulties that high school students, teachers, and university students encounter when trying to explain atomic spectra. To do so, we identify the key concepts that any quantum model for the emission and absorption of electromagnetic radiation must include to account for the gas spectra and we then design two…

  11. Metabolic profiles of triple-negative and luminal A breast cancer subtypes in African-American identify key metabolic differences.

    Science.gov (United States)

    Tayyari, Fariba; Gowda, G A Nagana; Olopade, Olufunmilayo F; Berg, Richard; Yang, Howard H; Lee, Maxwell P; Ngwa, Wilfred F; Mittal, Suresh K; Raftery, Daniel; Mohammed, Sulma I

    2018-02-20

    Breast cancer, a heterogeneous disease with variable pathophysiology and biology, is classified into four major subtypes. While hormonal- and antibody-targeted therapies are effective in the patients with luminal and HER-2 subtypes, the patients with triple-negative breast cancer (TNBC) subtype do not benefit from these therapies. The incidence rates of TNBC subtype are higher in African-American women, and the evidence indicates that these women have worse prognosis compared to women of European descent. The reasons for this disparity remain unclear but are often attributed to TNBC biology. In this study, we performed metabolic analysis of breast tissues to identify how TNBC differs from luminal A breast cancer (LABC) subtypes within the African-American and Caucasian breast cancer patients, respectively. We used High-Resolution Magic Angle Spinning (HR-MAS) 1H Nuclear magnetic resonance (NMR) to perform the metabolomic analysis of breast cancer and adjacent normal tissues (total n=82 samples). TNBC and LABC subtypes in African American women exhibited different metabolic profiles. Metabolic profiles of these subtypes were also distinct from those revealed in Caucasian women. TNBC in African-American women expressed higher levels of glutathione, choline, and glutamine as well as profound metabolic alterations characterized by decreased mitochondrial respiration and increased glycolysis concomitant with decreased levels of ATP. TNBC in Caucasian women was associated with increased pyrimidine synthesis. These metabolic alterations could potentially be exploited as novel treatment targets for TNBC.

  12. Comparative and functional genomics of Legionella identified eukaryotic like proteins as key players in host-pathogen interactions

    Directory of Open Access Journals (Sweden)

    Laura eGomez-Valero

    2011-10-01

    Full Text Available Although best known for its ability to cause severe pneumonia in people whose immune defenses are weakened, Legionella pneumophila and Legionella longbeachae are two species of a large genus of bacteria that are ubiquitous in nature, where they parasitize protozoa. Adaptation to the host environment and exploitation of host cell functions are critical for the success of these intracellular pathogens. The establishment and publication of the complete genome sequences of L. pneumophila and L. longbeachae isolates paved the way for major breakthroughs in understanding the biology of these organisms. In this review we present the knowledge gained from the analyses and comparison of the complete genome sequences of different L. pneumophila and L. longbeachae strains. Emphasis is given on putative virulence and Legionella life cycle related functions, such as the identification of an extended array of eukaryotic-like proteins, many of which have been shown to modulate host cell functions to the pathogen's advantage. Surprisingly, many of the eukaryotic domain proteins identified in L. pneumophila as well as many substrates of the Dot/Icm type IV secretion system essential for intracellular replication are different between these two species, although they cause the same disease. Finally, evolutionary aspects regarding the eukaryotic like proteins in Legionella are discussed.

  13. Identifying and Prioritizing the Key Factors Influencing Customer Decision Making in Buying Organizational Software (A survey about HAMKARAN Co.

    Directory of Open Access Journals (Sweden)

    shahryar Azizi

    2013-07-01

    Full Text Available Expansion of adopting information systems, specially packed software, facilitate managing the organizational process, hence, identification the factors influence customer buying decision is vital for software providers. This mixed method study tried to identify the factors affecting decision making of buying new organizational software, classify and rank them beside. In-depth interviews with 10 customers of Hamkaran system that had the potential of buying new software have been done and content analysis of these interviews revealed some factors in five categories that became the base of questionnaire design. This study is applied in view of aim, and is descriptive-survey in view of entity. Sample of 177 customers of System Group Co. have been chosen for the study. Kruskal-Wallis test and T test of normality showed all factors to be effective. Then the factors have been prioritized using Frideman test which are as follows: buyer`s internal organizational factors, product feature, factors related to sellers organization, factors related to process and selling promotion, market and environmental factors.

  14. How to identify the key factors that affect driver perception of accident risk. A comparison between Italian and Spanish driver behavior.

    Science.gov (United States)

    de Oña, Juan; de Oña, Rocio; Eboli, Laura; Forciniti, Carmen; Mazzulla, Gabriella

    2014-12-01

    Road crashes can be caused by different factors, including infrastructure, vehicles, and human variables. Many research studies have focused solely on identifying the key factors that cause road crashes. From these studies, it emerged that human factors have the most relevant impact on accident severity. More specifically, accident severity depends on several factors related directly to the driver, i.e., driving experience, driver's socio-economic characteristics, and driving behavior and attitudes. In this paper, we investigate driver behaviors and attitudes while driving and specifically focus on different methods for identifying the factors that most affect the driver's perception of accident risk. To this end, we designed and conducted a survey in two different European contexts: the city of Cosenza, which is located in the south of Italy, and the city of Granada, which is located in the south of Spain. Samples of drivers were contacted for their opinions on certain aspects of driving rules and attitudes while driving, and different types of questions were addressed to the drivers to assess their judgments of these aspects. Consequently, different methods of data analysis were applied to determine the aspects that heavily influence driver perception of accident risk. An experiment based on the stated preferences (SP) was carried out with the drivers, and the SP data were analyzed using an ordered probit (OP) model. Interesting findings emerged from different analyses of the data and from the comparisons among the data collected in the two different territorial contexts. We found that both Italian and Spanish drivers consider driving in an altered psychophysical state and violating the overtaking rules to be the most risky behaviors. Copyright © 2014 Elsevier Ltd. All rights reserved.

  15. Drosophila Cancer Models Identify Functional Differences between Ret Fusions.

    Science.gov (United States)

    Levinson, Sarah; Cagan, Ross L

    2016-09-13

    We generated and compared Drosophila models of RET fusions CCDC6-RET and NCOA4-RET. Both RET fusions directed cells to migrate, delaminate, and undergo EMT, and both resulted in lethality when broadly expressed. In all phenotypes examined, NCOA4-RET was more severe than CCDC6-RET, mirroring their effects on patients. A functional screen against the Drosophila kinome and a library of cancer drugs found that CCDC6-RET and NCOA4-RET acted through different signaling networks and displayed distinct drug sensitivities. Combining data from the kinome and drug screens identified the WEE1 inhibitor AZD1775 plus the multi-kinase inhibitor sorafenib as a synergistic drug combination that is specific for NCOA4-RET. Our work emphasizes the importance of identifying and tailoring a patient's treatment to their specific RET fusion isoform and identifies a multi-targeted therapy that may prove effective against tumors containing the NCOA4-RET fusion. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

  16. Identifying key demographic parameters of a small island–associated population of Indo-Pacific bottlenose dolphins (Reunion, Indian Ocean)

    Science.gov (United States)

    Estrade, Vanessa; Fayan, Jacques

    2017-01-01

    Photo-identification surveys of Indo-Pacific bottlenose dolphins were conducted from 2009 to 2014 off Reunion Island (55°E33’/21°S07’), in the Indian Ocean. Robust Design models were applied to produce the most reliable estimate of population abundance and survival rate, while accounting for temporary emigration from the survey area (west coast). The sampling scheme consisted of a five-month (June–October) sampling period in each year of the study. The overall population size at Reunion was estimated to be 72 individuals (SE = 6.17, 95%CI = 61–85), based on a random temporary emigration (γ”) of 0.096 and a proportion of 0.70 (SE = 0.03) distinct individuals. The annual survival rate was 0.93 (±0.018 SE, 95%CI = 0.886–0.958) and was constant over time and between sexes. Models considering gender groups indicated different movement patterns between males and females. Males showed null or quasi-null temporary emigration (γ” = γ’ < 0.01), while females showed a random temporary emigration (γ”) of 0.10, suggesting that a small proportion of females was outside the survey area during each primary sampling period. Sex-specific temporary migration patterns were consistent with movement and residency patterns observed in other areas. The Robust Design approach provided an appropriate sampling scheme for deriving island-associated population parameters, while allowing to restrict survey effort both spatially (i.e. west coast only) and temporally (five months per year). Although abundance and survival were stable over the six years, the small population size of fewer than 100 individuals suggested that this population is highly vulnerable. Priority should be given to reducing any potential impact of human activity on the population and its habitat. PMID:28640918

  17. Identifying key demographic parameters of a small island-associated population of Indo-Pacific bottlenose dolphins (Reunion, Indian Ocean).

    Science.gov (United States)

    Dulau, Violaine; Estrade, Vanessa; Fayan, Jacques

    2017-01-01

    Photo-identification surveys of Indo-Pacific bottlenose dolphins were conducted from 2009 to 2014 off Reunion Island (55°E33'/21°S07'), in the Indian Ocean. Robust Design models were applied to produce the most reliable estimate of population abundance and survival rate, while accounting for temporary emigration from the survey area (west coast). The sampling scheme consisted of a five-month (June-October) sampling period in each year of the study. The overall population size at Reunion was estimated to be 72 individuals (SE = 6.17, 95%CI = 61-85), based on a random temporary emigration (γ") of 0.096 and a proportion of 0.70 (SE = 0.03) distinct individuals. The annual survival rate was 0.93 (±0.018 SE, 95%CI = 0.886-0.958) and was constant over time and between sexes. Models considering gender groups indicated different movement patterns between males and females. Males showed null or quasi-null temporary emigration (γ" = γ' < 0.01), while females showed a random temporary emigration (γ") of 0.10, suggesting that a small proportion of females was outside the survey area during each primary sampling period. Sex-specific temporary migration patterns were consistent with movement and residency patterns observed in other areas. The Robust Design approach provided an appropriate sampling scheme for deriving island-associated population parameters, while allowing to restrict survey effort both spatially (i.e. west coast only) and temporally (five months per year). Although abundance and survival were stable over the six years, the small population size of fewer than 100 individuals suggested that this population is highly vulnerable. Priority should be given to reducing any potential impact of human activity on the population and its habitat.

  18. Identifying key demographic parameters of a small island-associated population of Indo-Pacific bottlenose dolphins (Reunion, Indian Ocean.

    Directory of Open Access Journals (Sweden)

    Violaine Dulau

    Full Text Available Photo-identification surveys of Indo-Pacific bottlenose dolphins were conducted from 2009 to 2014 off Reunion Island (55°E33'/21°S07', in the Indian Ocean. Robust Design models were applied to produce the most reliable estimate of population abundance and survival rate, while accounting for temporary emigration from the survey area (west coast. The sampling scheme consisted of a five-month (June-October sampling period in each year of the study. The overall population size at Reunion was estimated to be 72 individuals (SE = 6.17, 95%CI = 61-85, based on a random temporary emigration (γ" of 0.096 and a proportion of 0.70 (SE = 0.03 distinct individuals. The annual survival rate was 0.93 (±0.018 SE, 95%CI = 0.886-0.958 and was constant over time and between sexes. Models considering gender groups indicated different movement patterns between males and females. Males showed null or quasi-null temporary emigration (γ" = γ' < 0.01, while females showed a random temporary emigration (γ" of 0.10, suggesting that a small proportion of females was outside the survey area during each primary sampling period. Sex-specific temporary migration patterns were consistent with movement and residency patterns observed in other areas. The Robust Design approach provided an appropriate sampling scheme for deriving island-associated population parameters, while allowing to restrict survey effort both spatially (i.e. west coast only and temporally (five months per year. Although abundance and survival were stable over the six years, the small population size of fewer than 100 individuals suggested that this population is highly vulnerable. Priority should be given to reducing any potential impact of human activity on the population and its habitat.

  19. A molecular key for building hyphae aggregates: the role of the newly identified Streptomyces protein HyaS.

    Science.gov (United States)

    Koebsch, Ilona; Overbeck, Jens; Piepmeyer, Sophie; Meschke, Holger; Schrempf, Hildgund

    2009-05-01

    Streptomycetes produce many metabolites with medical and biotechnological applications. During fermentations, their hyphae build aggregates, a process in which the newly identified protein HyaS plays an important role. The corresponding hyaS gene is present within all investigated Streptomyces species. Reporter fusions indicate that transcription of hyaS occurs within substrate hyphae of the Streptomyces lividans wild type (WT). The HyaS protein is dominantly associated with the substrate hyphae. The WT strain forms cylindrically shaped clumps of densely packed substrate hyphae, often fusing to higher aggregates (pellets), which remain stably associated during shaking. Investigations by electron microscopy suggest that HyaS induces tight fusion-like contacts among substrate hyphae. In contrast, the pellets of the designed hyaS disruption mutant ΔH are irregular in shape, contain frequently outgrowing bunches of hyphae, and fuse less frequently. ΔH complemented with a plasmid carrying hyaS resembles the WT phenotype. Biochemical studies indicate that the C-terminal region of HyaS has amine oxidase activity. Investigations of ΔH transformants, each carrying a specifically mutated gene, lead to the conclusion that the in situ oxidase activity correlates with the pellet-inducing role of HyaS, and depends on the presence of certain histidine residues. Furthermore, the level of undecylprodigiosin, a red pigment with antibiotic activity, is influenced by the engineered hyaS subtype within a strain. These data present the first molecular basis for future manipulation of pellets, and concomitant production of secondary metabolites during biotechnological processes. © 2009 The Authors. Journal compilation © 2009 Society for Applied Microbiology and Blackwell Publishing Ltd.

  20. Transcriptome Analysis Identifies Key Metabolic Changes in the Hooded Seal (Cystophora cristata Brain in Response to Hypoxia and Reoxygenation.

    Directory of Open Access Journals (Sweden)

    Mariana Leivas Müller Hoff

    Full Text Available The brain of diving mammals tolerates low oxygen conditions better than the brain of most terrestrial mammals. Previously, it has been demonstrated that the neurons in brain slices of the hooded seal (Cystophora cristata withstand hypoxia longer than those of mouse, and also tolerate reduced glucose supply and high lactate concentrations. This tolerance appears to be accompanied by a shift in the oxidative energy metabolism to the astrocytes in the seal while in terrestrial mammals the aerobic energy production mainly takes place in neurons. Here, we used RNA-Seq to compare the effect of hypoxia and reoxygenation in vitro on brain slices from the visual cortex of hooded seals. We saw no general reduction of gene expression, suggesting that the response to hypoxia and reoxygenation is an actively regulated process. The treatments caused the preferential upregulation of genes related to inflammation, as found before e.g. in stroke studies using mammalian models. Gene ontology and KEGG pathway analyses showed a downregulation of genes involved in ion transport and other neuronal processes, indicative for a neuronal shutdown in response to a shortage of O2 supply. These differences may be interpreted in terms of an energy saving strategy in the seal's brain. We specifically analyzed the regulation of genes involved in energy metabolism. Hypoxia and reoxygenation caused a similar response, with upregulation of genes involved in glucose metabolism and downregulation of the components of the pyruvate dehydrogenase complex. We also observed upregulation of the monocarboxylate transporter Mct4, suggesting increased lactate efflux. Together, these data indicate that the seal brain responds to the hypoxic challenge by a relative increase in the anaerobic energy metabolism.

  1. Simple Model for Identifying Critical Regions in Atrial Fibrillation

    Science.gov (United States)

    Christensen, Kim; Manani, Kishan A.; Peters, Nicholas S.

    2015-01-01

    Atrial fibrillation (AF) is the most common abnormal heart rhythm and the single biggest cause of stroke. Ablation, destroying regions of the atria, is applied largely empirically and can be curative but with a disappointing clinical success rate. We design a simple model of activation wave front propagation on an anisotropic structure mimicking the branching network of heart muscle cells. This integration of phenomenological dynamics and pertinent structure shows how AF emerges spontaneously when the transverse cell-to-cell coupling decreases, as occurs with age, beyond a threshold value. We identify critical regions responsible for the initiation and maintenance of AF, the ablation of which terminates AF. The simplicity of the model allows us to calculate analytically the risk of arrhythmia and express the threshold value of transversal cell-to-cell coupling as a function of the model parameters. This threshold value decreases with increasing refractory period by reducing the number of critical regions which can initiate and sustain microreentrant circuits. These biologically testable predictions might inform ablation therapies and arrhythmic risk assessment.

  2. At-line monitoring of key parameters of nisin fermentation by near infrared spectroscopy, chemometric modeling and model improvement.

    Science.gov (United States)

    Guo, Wei-Liang; Du, Yi-Ping; Zhou, Yong-Can; Yang, Shuang; Lu, Jia-Hui; Zhao, Hong-Yu; Wang, Yao; Teng, Li-Rong

    2012-03-01

    An analytical procedure has been developed for at-line (fast off-line) monitoring of 4 key parameters including nisin titer (NT), the concentration of reducing sugars, cell concentration and pH during a nisin fermentation process. This procedure is based on near infrared (NIR) spectroscopy and Partial Least Squares (PLS). Samples without any preprocessing were collected at intervals of 1 h during fifteen batch of fermentations. These fermentation processes were implemented in 3 different 5 l fermentors at various conditions. NIR spectra of the samples were collected in 10 min. And then, PLS was used for modeling the relationship between NIR spectra and the key parameters which were determined by reference methods. Monte Carlo Partial Least Squares (MCPLS) was applied to identify the outliers and select the most efficacious methods for preprocessing spectra, wavelengths and the suitable number of latent variables (n (LV)). Then, the optimum models for determining NT, concentration of reducing sugars, cell concentration and pH were established. The correlation coefficients of calibration set (R (c)) were 0.8255, 0.9000, 0.9883 and 0.9581, respectively. These results demonstrated that this method can be successfully applied to at-line monitor of NT, concentration of reducing sugars, cell concentration and pH during nisin fermentation processes.

  3. Rheumatoid arthritis: identifying and characterising polymorphisms using rat models

    Science.gov (United States)

    2016-01-01

    ABSTRACT Rheumatoid arthritis is a chronic inflammatory joint disorder characterised by erosive inflammation of the articular cartilage and by destruction of the synovial joints. It is regulated by both genetic and environmental factors, and, currently, there is no preventative treatment or cure for this disease. Genome-wide association studies have identified ∼100 new loci associated with rheumatoid arthritis, in addition to the already known locus within the major histocompatibility complex II region. However, together, these loci account for only a modest fraction of the genetic variance associated with this disease and very little is known about the pathogenic roles of most of the risk loci identified. Here, we discuss how rat models of rheumatoid arthritis are being used to detect quantitative trait loci that regulate different arthritic traits by genetic linkage analysis and to positionally clone the underlying causative genes using congenic strains. By isolating specific loci on a fixed genetic background, congenic strains overcome the challenges of genetic heterogeneity and environmental interactions associated with human studies. Most importantly, congenic strains allow functional experimental studies be performed to investigate the pathological consequences of natural genetic polymorphisms, as illustrated by the discovery of several major disease genes that contribute to arthritis in rats. We discuss how these advances have provided new biological insights into arthritis in humans. PMID:27736747

  4. A new approach to hazardous materials transportation risk analysis: decision modeling to identify critical variables.

    Science.gov (United States)

    Clark, Renee M; Besterfield-Sacre, Mary E

    2009-03-01

    We take a novel approach to analyzing hazardous materials transportation risk in this research. Previous studies analyzed this risk from an operations research (OR) or quantitative risk assessment (QRA) perspective by minimizing or calculating risk along a transport route. Further, even though the majority of incidents occur when containers are unloaded, the research has not focused on transportation-related activities, including container loading and unloading. In this work, we developed a decision model of a hazardous materials release during unloading using actual data and an exploratory data modeling approach. Previous studies have had a theoretical perspective in terms of identifying and advancing the key variables related to this risk, and there has not been a focus on probability and statistics-based approaches for doing this. Our decision model empirically identifies the critical variables using an exploratory methodology for a large, highly categorical database involving latent class analysis (LCA), loglinear modeling, and Bayesian networking. Our model identified the most influential variables and countermeasures for two consequences of a hazmat incident, dollar loss and release quantity, and is one of the first models to do this. The most influential variables were found to be related to the failure of the container. In addition to analyzing hazmat risk, our methodology can be used to develop data-driven models for strategic decision making in other domains involving risk.

  5. Application of the Value Optimization Model of Key Factors Based on DSEM

    Directory of Open Access Journals (Sweden)

    Chao Su

    2016-01-01

    Full Text Available The key factors of the damping solvent extraction method (DSEM for the analysis of the unbounded medium are the size of bounded domain, the artificial damping ratio, and the finite element mesh density. To control the simulation accuracy and computational efficiency of the soil-structure interaction, this study establishes a value optimization model of key factors that is composed of the design variables, the objective function, and the constraint function system. Then the optimum solutions of key factors are obtained by the optimization model. According to some comparisons of the results provided by the different initial conditions, the value optimization model of key factors is feasible to govern the simulation accuracy and computational efficiency and to analyze the practical unbounded medium-structure interaction.

  6. Integrated RNA-Seq and sRNA-Seq Analysis Identifies Chilling and Freezing Responsive Key Molecular Players and Pathways in Tea Plant (Camellia sinensis)

    Science.gov (United States)

    Zheng, Chao; Zhao, Lei; Wang, Yu; Shen, Jiazhi; Zhang, Yinfei; Jia, Sisi; Li, Yusheng; Ding, Zhaotang

    2015-01-01

    Tea [Camellia sinensis (L) O. Kuntze, Theaceae] is one of the most popular non-alcoholic beverages worldwide. Cold stress is one of the most severe abiotic stresses that limit tea plants’ growth, survival and geographical distribution. However, the genetic regulatory network and signaling pathways involved in cold stress responses in tea plants remain unearthed. Using RNA-Seq, DGE and sRNA-Seq technologies, we performed an integrative analysis of miRNA and mRNA expression profiling and their regulatory network of tea plants under chilling (4℃) and freezing (-5℃) stress. Differentially expressed (DE) miRNA and mRNA profiles were obtained based on fold change analysis, miRNAs and target mRNAs were found to show both coherent and incoherent relationships in the regulatory network. Furthermore, we compared several key pathways (e.g., ‘Photosynthesis’), GO terms (e.g., ‘response to karrikin’) and transcriptional factors (TFs, e.g., DREB1b/CBF1) which were identified as involved in the early chilling and/or freezing response of tea plants. Intriguingly, we found that karrikins, a new group of plant growth regulators, and β-primeverosidase (BPR), a key enzyme functionally relevant with the formation of tea aroma might play an important role in both early chilling and freezing response of tea plants. Quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR) analysis further confirmed the results from RNA-Seq and sRNA-Seq analysis. This is the first study to simultaneously profile the expression patterns of both miRNAs and mRNAs on a genome-wide scale to elucidate the molecular mechanisms of early responses of tea plants to cold stress. In addition to gaining a deeper insight into the cold resistant characteristics of tea plants, we provide a good case study to analyse mRNA/miRNA expression and profiling of non-model plant species using next-generation sequencing technology. PMID:25901577

  7. Identifying Key Features, Cutting Edge Cloud Resources, and Artificial Intelligence Tools to Achieve User-Friendly Water Science in the Cloud

    Science.gov (United States)

    Pierce, S. A.

    2017-12-01

    Decision making for groundwater systems is becoming increasingly important, as shifting water demands increasingly impact aquifers. As buffer systems, aquifers provide room for resilient responses and augment the actual timeframe for hydrological response. Yet the pace impacts, climate shifts, and degradation of water resources is accelerating. To meet these new drivers, groundwater science is transitioning toward the emerging field of Integrated Water Resources Management, or IWRM. IWRM incorporates a broad array of dimensions, methods, and tools to address problems that tend to be complex. Computational tools and accessible cyberinfrastructure (CI) are needed to cross the chasm between science and society. Fortunately cloud computing environments, such as the new Jetstream system, are evolving rapidly. While still targeting scientific user groups systems such as, Jetstream, offer configurable cyberinfrastructure to enable interactive computing and data analysis resources on demand. The web-based interfaces allow researchers to rapidly customize virtual machines, modify computing architecture and increase the usability and access for broader audiences to advanced compute environments. The result enables dexterous configurations and opening up opportunities for IWRM modelers to expand the reach of analyses, number of case studies, and quality of engagement with stakeholders and decision makers. The acute need to identify improved IWRM solutions paired with advanced computational resources refocuses the attention of IWRM researchers on applications, workflows, and intelligent systems that are capable of accelerating progress. IWRM must address key drivers of community concern, implement transdisciplinary methodologies, adapt and apply decision support tools in order to effectively support decisions about groundwater resource management. This presentation will provide an overview of advanced computing services in the cloud using integrated groundwater management case

  8. Systemic Thinking and Requisite Holism in Mastering Logistics Risks: the Model for Identifying Risks in Organisations and Supply Chain

    OpenAIRE

    Borut Jereb; Teodora Ivanuša; Bojan Rosi

    2013-01-01

    Risks in logistic processes represent one of the major issues in supply chain management nowadays. Every organization strives for success, and uninterrupted operations are the key factors in achieving this goal, which cannot be achieved without efficient risk management. In the scope of supply chain risk research, we identified some key issues in the field, the major issue being the lack of standardization and models, which can make risk management in an organization easier and more efficient...

  9. Modeling secondary accidents identified by traffic shock waves.

    Science.gov (United States)

    Junhua, Wang; Boya, Liu; Lanfang, Zhang; Ragland, David R

    2016-02-01

    The high potential for occurrence and the negative consequences of secondary accidents make them an issue of great concern affecting freeway safety. Using accident records from a three-year period together with California interstate freeway loop data, a dynamic method for more accurate classification based on the traffic shock wave detecting method was used to identify secondary accidents. Spatio-temporal gaps between the primary and secondary accident were proven be fit via a mixture of Weibull and normal distribution. A logistic regression model was developed to investigate major factors contributing to secondary accident occurrence. Traffic shock wave speed and volume at the occurrence of a primary accident were explicitly considered in the model, as a secondary accident is defined as an accident that occurs within the spatio-temporal impact scope of the primary accident. Results show that the shock waves originating in the wake of a primary accident have a more significant impact on the likelihood of a secondary accident occurrence than the effects of traffic volume. Primary accidents with long durations can significantly increase the possibility of secondary accidents. Unsafe speed and weather are other factors contributing to secondary crash occurrence. It is strongly suggested that when police or rescue personnel arrive at the scene of an accident, they should not suddenly block, decrease, or unblock the traffic flow, but instead endeavor to control traffic in a smooth and controlled manner. Also it is important to reduce accident processing time to reduce the risk of secondary accident. Copyright © 2015 Elsevier Ltd. All rights reserved.

  10. Procedure for identifying models for the heat dynamics of buildings

    DEFF Research Database (Denmark)

    Bacher, Peder; Madsen, Henrik

    This report describes a new method for obtaining detailed information about the heat dynamics of a building using frequent reading of the heat consumption. Such a procedure is considered to be of uttermost importance as a key procedure for using readings from smart meters, which is expected...

  11. Identifiability of Baranyi model and comparison with empirical ...

    African Journals Online (AJOL)

    In addition, performance of the Baranyi model was compared with those of the empirical modified Gompertz and logistic models and Huang models. Higher values of R2, modeling efficiency and lower absolute values of mean bias error, root mean square error, mean percentage error and chi-square were obtained with ...

  12. An improved model for identifying influential bloggers on the web ...

    African Journals Online (AJOL)

    The benefits of achieving competitive advantages in a blog community by identify influential blogger have created several research gaps and the popularity of these services has make the problem of identifying the most influential bloggers noteworthy, since its solution can lead to major benefits for the users of this services ...

  13. Password-only authenticated three-party key exchange with provable security in the standard model.

    Science.gov (United States)

    Nam, Junghyun; Choo, Kim-Kwang Raymond; Kim, Junghwan; Kang, Hyun-Kyu; Kim, Jinsoo; Paik, Juryon; Won, Dongho

    2014-01-01

    Protocols for password-only authenticated key exchange (PAKE) in the three-party setting allow two clients registered with the same authentication server to derive a common secret key from their individual password shared with the server. Existing three-party PAKE protocols were proven secure under the assumption of the existence of random oracles or in a model that does not consider insider attacks. Therefore, these protocols may turn out to be insecure when the random oracle is instantiated with a particular hash function or an insider attack is mounted against the partner client. The contribution of this paper is to present the first three-party PAKE protocol whose security is proven without any idealized assumptions in a model that captures insider attacks. The proof model we use is a variant of the indistinguishability-based model of Bellare, Pointcheval, and Rogaway (2000), which is one of the most widely accepted models for security analysis of password-based key exchange protocols. We demonstrated that our protocol achieves not only the typical indistinguishability-based security of session keys but also the password security against undetectable online dictionary attacks.

  14. Password-Only Authenticated Three-Party Key Exchange with Provable Security in the Standard Model

    Directory of Open Access Journals (Sweden)

    Junghyun Nam

    2014-01-01

    Full Text Available Protocols for password-only authenticated key exchange (PAKE in the three-party setting allow two clients registered with the same authentication server to derive a common secret key from their individual password shared with the server. Existing three-party PAKE protocols were proven secure under the assumption of the existence of random oracles or in a model that does not consider insider attacks. Therefore, these protocols may turn out to be insecure when the random oracle is instantiated with a particular hash function or an insider attack is mounted against the partner client. The contribution of this paper is to present the first three-party PAKE protocol whose security is proven without any idealized assumptions in a model that captures insider attacks. The proof model we use is a variant of the indistinguishability-based model of Bellare, Pointcheval, and Rogaway (2000, which is one of the most widely accepted models for security analysis of password-based key exchange protocols. We demonstrated that our protocol achieves not only the typical indistinguishability-based security of session keys but also the password security against undetectable online dictionary attacks.

  15. The building blocks of a 'Liveable Neighbourhood': Identifying the key performance indicators for walking of an operational planning policy in Perth, Western Australia.

    Science.gov (United States)

    Hooper, Paula; Knuiman, Matthew; Foster, Sarah; Giles-Corti, Billie

    2015-11-01

    Planning policy makers are requesting clearer guidance on the key design features required to build neighbourhoods that promote active living. Using a backwards stepwise elimination procedure (logistic regression with generalised estimating equations adjusting for demographic characteristics, self-selection factors, stage of construction and scale of development) this study identified specific design features (n=16) from an operational planning policy ("Liveable Neighbourhoods") that showed the strongest associations with walking behaviours (measured using the Neighbourhood Physical Activity Questionnaire). The interacting effects of design features on walking behaviours were also investigated. The urban design features identified were grouped into the "building blocks of a Liveable Neighbourhood", reflecting the scale, importance and sequencing of the design and implementation phases required to create walkable, pedestrian friendly developments. Copyright © 2015 Elsevier Ltd. All rights reserved.

  16. Identifying western yellow-billed cuckoo breeding habitat with a dual modelling approach

    Science.gov (United States)

    Johnson, Matthew J.; Hatten, James R.; Holmes, Jennifer A.; Shafroth, Patrick B.

    2017-01-01

    The western population of the yellow-billed cuckoo (Coccyzus americanus) was recently listed as threatened under the federal Endangered Species Act. Yellow-billed cuckoo conservation efforts require the identification of features and area requirements associated with high quality, riparian forest habitat at spatial scales that range from nest microhabitat to landscape, as well as lower-suitability areas that can be enhanced or restored. Spatially explicit models inform conservation efforts by increasing ecological understanding of a target species, especially at landscape scales. Previous yellow-billed cuckoo modelling efforts derived plant-community maps from aerial photography, an expensive and oftentimes inconsistent approach. Satellite models can remotely map vegetation features (e.g., vegetation density, heterogeneity in vegetation density or structure) across large areas with near perfect repeatability, but they usually cannot identify plant communities. We used aerial photos and satellite imagery, and a hierarchical spatial scale approach, to identify yellow-billed cuckoo breeding habitat along the Lower Colorado River and its tributaries. Aerial-photo and satellite models identified several key features associated with yellow-billed cuckoo breeding locations: (1) a 4.5 ha core area of dense cottonwood-willow vegetation, (2) a large native, heterogeneously dense forest (72 ha) around the core area, and (3) moderately rough topography. The odds of yellow-billed cuckoo occurrence decreased rapidly as the amount of tamarisk cover increased or when cottonwood-willow vegetation was limited. We achieved model accuracies of 75–80% in the project area the following year after updating the imagery and location data. The two model types had very similar probability maps, largely predicting the same areas as high quality habitat. While each model provided unique information, a dual-modelling approach provided a more complete picture of yellow-billed cuckoo habitat

  17. Genome-wide expression profiling analysis to identify key genes in the anti-HIV mechanism of CD4+ and CD8+ T cells.

    Science.gov (United States)

    Gao, Lijie; Wang, Yunqi; Li, Yi; Dong, Ya; Yang, Aimin; Zhang, Jie; Li, Fengying; Zhang, Rongqiang

    2018-07-01

    Comprehensive bioinformatics analyses were performed to explore the key biomarkers in response to HIV infection of CD4 + and CD8 + T cells. The numbers of CD4 + and CD8 + T cells of HIV infected individuals were analyzed and the GEO database (GSE6740) was screened for differentially expressed genes (DEGs) in HIV infected CD4 + and CD8 + T cells. Gene Ontology enrichment, KEGG pathway analyses, and protein-protein interaction (PPI) network were performed to identify the key pathway and core proteins in anti-HIV virus process of CD4 + and CD8 + T cells. Finally, we analyzed the expressions of key proteins in HIV-infected T cells (GSE6740 dataset) and peripheral blood mononuclear cells(PBMCs) (GSE511 dataset). 1) CD4 + T cells counts and ratio of CD4 + /CD8 + T cells decreased while CD8 + T cells counts increased in HIV positive individuals; 2) 517 DEGs were found in HIV infected CD4 + and CD8 + T cells at acute and chronic stage with the criterial of P-value T cells. The main biological processes of the DEGs were response to virus and defense response to virus. At chronic stage, ISG15 protein, in conjunction with IFN-1 pathway might play key roles in anti-HIV responses of CD4 + T cells; and 4) The expression of ISG15 increased in both T cells and PBMCs after HIV infection. Gene expression profile of CD4 + and CD8 + T cells changed significantly in HIV infection, in which ISG15 gene may play a central role in activating the natural antiviral process of immune cells. © 2018 Wiley Periodicals, Inc.

  18. What are the key drivers of MAC curves? A partial-equilibrium modelling approach for the UK

    International Nuclear Information System (INIS)

    Kesicki, Fabian

    2013-01-01

    Marginal abatement cost (MAC) curves are widely used for the assessment of costs related to CO 2 emissions reduction in environmental economics, as well as domestic and international climate policy. Several meta-analyses and model comparisons have previously been performed that aim to identify the causes for the wide range of MAC curves. Most of these concentrate on general equilibrium models with a focus on aspects such as specific model type and technology learning, while other important aspects remain almost unconsidered, including the availability of abatement technologies and level of discount rates. This paper addresses the influence of several key parameters on MAC curves for the United Kingdom and the year 2030. A technology-rich energy system model, UK MARKAL, is used to derive the MAC curves. The results of this study show that MAC curves are robust even to extreme fossil fuel price changes, while uncertainty around the choice of the discount rate, the availability of key abatement technologies and the demand level were singled out as the most important influencing factors. By using a different model type and studying a wider range of influencing factors, this paper contributes to the debate on the sensitivity of MAC curves. - Highlights: ► A partial-equilibrium model is employed to test key sensitivities of MAC curves. ► MAC curves are found to be robust to wide-ranging changes in fossil fuel prices. ► Most influencing factors are the discount rate, availability of key technologies. ► Further important uncertainty in MAC curves is related to demand changes

  19. The relationship between the key elements of Donabedian's conceptual model within the field of assistive technology

    DEFF Research Database (Denmark)

    Sund, Terje; Iwarsson, Susanne; Brandt, Åse

    2015-01-01

    Previous research has suggested that there is a relationship between the three key components of Donabedian's conceptual model for quality assessments: structure of care, process, and outcome of care. That is, structure predicted both process and outcome of care, and better processes predict better...

  20. Valuing snorkeling visits to the Florida Keys with stated and revealed preference models

    Science.gov (United States)

    Timothy Park; J. Michael Bowker; Vernon R. Leeworthy

    2002-01-01

    Coastal coral reefs, especially in the Florida Keys, are declining at a disturbing rate. Marine ecologists and reef scientists have emphasized the importance of establishing nonmarket values of coral reefs to assess the cost effectiveness of coral reef management and remediation programs. The purpose of this paper is to develop a travel cost--contingent valuation model...

  1. Nine key principles to guide youth mental health: development of service models in New South Wales.

    Science.gov (United States)

    Howe, Deborah; Batchelor, Samantha; Coates, Dominiek; Cashman, Emma

    2014-05-01

    Historically, the Australian health system has failed to meet the needs of young people with mental health problems and mental illness. In 2006, New South Wales (NSW) Health allocated considerable funds to the reform agenda of mental health services in NSW to address this inadequacy. Children and Young People's Mental Health (CYPMH), a service that provides mental health care for young people aged 12-24 years, with moderate to severe mental health problems, was chosen to establish a prototype Youth Mental Health (YMH) Service Model for NSW. This paper describes nine key principles developed by CYPMH to guide the development of YMH Service Models in NSW. A literature review, numerous stakeholder consultations and consideration of clinical best practice were utilized to inform the development of the key principles. Subsequent to their development, the nine key principles were formally endorsed by the Mental Health Program Council to ensure consistency and monitor the progress of YMH services across NSW. As a result, between 2008 and 2012 YMH Services across NSW regularly reported on their activities against each of the nine key principles demonstrating how each principle was addressed within their service. The nine key principles provide mental health services a framework for how to reorient services to accommodate YMH and provide a high-quality model of care. [Corrections added on 29 November 2013, after first online publication: The last two sentences of the Results section have been replaced with "As a result, between 2008 and 2012 YMH Services across NSW regularly reported on their activities against each of the nine key principles demonstrating how each principle was addressed within their service."]. © 2013 Wiley Publishing Asia Pty Ltd.

  2. Modelling intelligence-led policing to identify its potential

    NARCIS (Netherlands)

    Hengst-Bruggeling, M. den; Graaf, H.A.L.M. de; Scheepstal, P.G.M. van

    2014-01-01

    lntelligence-led policing is a concept of policing that has been applied throughout the world. Despite some encouraging reports, the effect of intelligence-led policing is largely unknown. This paper presents a method with which it is possible to identify intelligence-led policing's potential to

  3. Modelling discontinuous well log signal to identify lithological ...

    Indian Academy of Sciences (India)

    1Indian School of Mines (ISM), Dhanbad 826 004, India. ... new wavelet transform-based algorithm to model the abrupt discontinuous changes from well log data by taking care of ...... the 11th ACM International Conference on Multimedia,.

  4. Dome effect of black carbon and its key influencing factors: a one-dimensional modelling study

    Science.gov (United States)

    Wang, Zilin; Huang, Xin; Ding, Aijun

    2018-02-01

    Black carbon (BC) has been identified to play a critical role in aerosol-planetary boundary layer (PBL) interaction and further deterioration of near-surface air pollution in megacities, which has been referred to as the dome effect. However, the impacts of key factors that influence this effect, such as the vertical distribution and aging processes of BC, as well as the underlying land surface, have not been quantitatively explored yet. Here, based on available in situ measurements of meteorology and atmospheric aerosols together with the meteorology-chemistry online coupled model WRF-Chem, we conduct a set of parallel simulations to quantify the roles of these factors in influencing the BC dome effect and surface haze pollution. Furthermore, we discuss the main implications of the results to air pollution mitigation in China. We found that the impact of BC on the PBL is very sensitive to the altitude of aerosol layer. The upper-level BC, especially that near the capping inversion, is more essential in suppressing the PBL height and weakening the turbulent mixing. The dome effect of BC tends to be significantly intensified as BC mixed with scattering aerosols during winter haze events, resulting in a decrease in PBL height by more than 15 %. In addition, the dome effect is more substantial (up to 15 %) in rural areas than that in the urban areas with the same BC loading, indicating an unexpected regional impact of such an effect to air quality in countryside. This study indicates that China's regional air pollution would greatly benefit from BC emission reductions, especially those from elevated sources from chimneys and also domestic combustion in rural areas, through weakening the aerosol-boundary layer interactions that are triggered by BC.

  5. A Method to Identify Flight Obstacles on Digital Surface Model

    Institute of Scientific and Technical Information of China (English)

    ZHAO Min; LIN Xinggang; SUN Shouyu; WANG Youzhi

    2005-01-01

    In modern low-altitude terrain-following guidance, a constructing method of the digital surface model (DSM) is presented in the paper to reduce the threat to flying vehicles of tall surface features for safe flight. The relationship between an isolated obstacle size and the intervals of vertical- and cross-section in the DSM model is established. The definition and classification of isolated obstacles are proposed, and a method for determining such isolated obstacles in the DSM model is given. The simulation of a typical urban district shows that when the vertical- and cross-section DSM intervals are between 3 m and 25 m, the threat to terrain-following flight at low-altitude is reduced greatly, and the amount of data required by the DSM model for monitoring in real time a flying vehicle is also smaller. Experiments show that the optimal results are for an interval of 12.5 m in the vertical- and cross-sections in the DSM model, with a 1:10 000 DSM scale grade.

  6. Using the Theory of Planned Behavior to identify key beliefs underlying chlamydia testing intentions in a sample of young people living in deprived areas.

    Science.gov (United States)

    Booth, Amy R; Norman, Paul; Harris, Peter R; Goyder, Elizabeth

    2015-09-01

    The Theory of Planned Behavior was used to identify the key behavioural, normative and control beliefs underlying intentions to test regularly for chlamydia among young people living in socially and economically deprived areas - a high-risk group for infection. Participants (N = 278, 53% male; mean age 17 years) were recruited from a vocational college situated in an area in the most deprived national quintile (England). Participants completed measures of behavioural, normative and control beliefs, plus intention to test regularly for chlamydia. The behavioural, normative and control beliefs most strongly correlated with intentions to test regularly for chlamydia were beliefs about stopping the spread of infection, partners' behaviour and the availability of testing. These beliefs represent potential targets for interventions to increase chlamydia testing among young people living in deprived areas. © The Author(s) 2013.

  7. A preliminary model to identify low-risk MBA applicants

    Directory of Open Access Journals (Sweden)

    CA Bisschoff

    2014-08-01

    The reliability of the discriminant function rates favourably with 71% (MBA in 3 years, 62% (MBA in 4 years and 83% (dropping out of the programme being categorised correctly by the respective discriminant functions. Being a preliminary model, its predictive capabilities need to be verified in practice before it can  be implemented as tool to render assistance in MBA admissions.  The value of this research lies  in the fact that it constitutes a model that could be employed and improved as a predictive tool in an environment where very limited predictive tools exist.  Therefore, although it is by no means a tried and tested model, it sets the scene by supplying a scientific base from which incremental improvements could result.

  8. Identifying Clusters with Mixture Models that Include Radial Velocity Observations

    Science.gov (United States)

    Czarnatowicz, Alexis; Ybarra, Jason E.

    2018-01-01

    The study of stellar clusters plays an integral role in the study of star formation. We present a cluster mixture model that considers radial velocity data in addition to spatial data. Maximum likelihood estimation through the Expectation-Maximization (EM) algorithm is used for parameter estimation. Our mixture model analysis can be used to distinguish adjacent or overlapping clusters, and estimate properties for each cluster.Work supported by awards from the Virginia Foundation for Independent Colleges (VFIC) Undergraduate Science Research Fellowship and The Research Experience @Bridgewater (TREB).

  9. Energy Demand Modeling Methodology of Key State Transitions of Turning Processes

    Directory of Open Access Journals (Sweden)

    Shun Jia

    2017-04-01

    Full Text Available Energy demand modeling of machining processes is the foundation of energy optimization. Energy demand of machining state transition is integral to the energy requirements of the machining process. However, research focus on energy modeling of state transition is scarce. To fill this gap, an energy demand modeling methodology of key state transitions of the turning process is proposed. The establishment of an energy demand model of state transition could improve the accuracy of the energy model of the machining process, which also provides an accurate model and reliable data for energy optimization of the machining process. Finally, case studies were conducted on a CK6153i CNC lathe, the results demonstrating that predictive accuracy with the proposed method is generally above 90% for the state transition cases.

  10. Oncology Modeling for Fun and Profit! Key Steps for Busy Analysts in Health Technology Assessment.

    Science.gov (United States)

    Beca, Jaclyn; Husereau, Don; Chan, Kelvin K W; Hawkins, Neil; Hoch, Jeffrey S

    2018-01-01

    In evaluating new oncology medicines, two common modeling approaches are state transition (e.g., Markov and semi-Markov) and partitioned survival. Partitioned survival models have become more prominent in oncology health technology assessment processes in recent years. Our experience in conducting and evaluating models for economic evaluation has highlighted many important and practical pitfalls. As there is little guidance available on best practices for those who wish to conduct them, we provide guidance in the form of 'Key steps for busy analysts,' who may have very little time and require highly favorable results. Our guidance highlights the continued need for rigorous conduct and transparent reporting of economic evaluations regardless of the modeling approach taken, and the importance of modeling that better reflects reality, which includes better approaches to considering plausibility, estimating relative treatment effects, dealing with post-progression effects, and appropriate characterization of the uncertainty from modeling itself.

  11. A bibliometric model for identifying emerging research topics

    DEFF Research Database (Denmark)

    Wang, Qi

    2018-01-01

    –1843, 2015), the most serious problems are the lack of an acknowledged definition of emergence and incomplete elaboration of the linkages between the definitions that are used and the indicators that are created. With these issues in mind, this study first adjusts the definition of an emerging technology...... that Rotolo et al. (2015) have proposed to accommodate the analysis. Next, a set of criteria for the identification of emerging topics is proposed according to the adjusted definition and attributes of emergence. Using two sets of parameter values, several emerging research topics are identified. Finally...

  12. Modeling of CPDOs - Identifying Optimal and Implied Leverage

    DEFF Research Database (Denmark)

    Dorn, Jochen

    famous notably by Standard & Poor's rating model error which illustrated that closed-form analytical pricing is necessary in order to evaluate and understand complex derivatives. This article aims to shed a light on CPDOs specific structural enhancements and mechanisms. The author quantifies inherent...... risks and provides a dynamic closed-form pricing formula....

  13. Modeling of CPDOs - Identifying optimal and implied leverage

    DEFF Research Database (Denmark)

    Dorn, Jochen

    2010-01-01

    by Standard & Poor's rating model error which illustrated that closed-form analytical pricing is necessary in order to evaluate and understand complex derivatives. This article aims to shed a light on CPDOs' specific structural enhancements and mechanisms. We quantify inherent risks and provide a dynamic...

  14. A computer model for identifying security system upgrades

    International Nuclear Information System (INIS)

    Lamont, A.

    1988-01-01

    This paper describes a prototype safeguards analysis tool that automatically identifies system weaknesses against an insider adversary and suggest possible upgrades to improve the probability that the adversary will be detected. The tool is based on this premise: as the adversary acts, he or she creates a set of facts that can be detected by safeguards components. Whenever an adversary's planned set of actions create a set of facts which the security personnel would consider irregular or unusual, we can improve the security system by implementing safeguards that detect those facts. Therefore, an intelligent computer program can suggest upgrades to the facility if we construct a knowledge base that contains information about: (1) the facts created by each possible adversary action, (2) the facts that each possible safeguard can detect, and (3) groups of facts which will be considered irregular whenever they occur together. The authors describe the structure of the knowledge base and show how the above information can be represented in it. They also describe the procedures that a computer program can use to identify missing or weak safeguards and to suggest upgrades

  15. A decision support model for identification and prioritization of key performance indicators in the logistics industry

    OpenAIRE

    Kucukaltan, Berk; Irani, Zahir; Aktas, Emel

    2016-01-01

    Performance measurement of logistics companies is based upon various performance indicators. Yet, in the logistics industry, there are several vaguenesses, such as deciding on key indicators and determining interrelationships between performance indicators. In order to resolve these vaguenesses, this paper first presents the stakeholder-informed Balanced Scorecard (BSC) model, by incorporating financial (e.g. cost) and non-financial (e.g. social media) performance indicators, with a comprehen...

  16. Key factors regulating the mass delivery of macromolecules to model cell membranes

    DEFF Research Database (Denmark)

    Campbell, Richard A.; Watkins, Erik B.; Jagalski, Vivien

    2014-01-01

    We show that both gravity and electrostatics are key factors regulating interactions between model cell membranes and self-assembled liquid crystalline aggregates of dendrimers and phospholipids. The system is a proxy for the trafficking of reservoirs of therapeutic drugs to cell membranes for slow...... of the aggregates to activate endocytosis pathways on specific cell types is discussed in the context of targeted drug delivery applications....

  17. Integrated network analysis identifies fight-club nodes as a class of hubs encompassing key putative switch genes that induce major transcriptome reprogramming during grapevine development.

    Science.gov (United States)

    Palumbo, Maria Concetta; Zenoni, Sara; Fasoli, Marianna; Massonnet, Mélanie; Farina, Lorenzo; Castiglione, Filippo; Pezzotti, Mario; Paci, Paola

    2014-12-01

    We developed an approach that integrates different network-based methods to analyze the correlation network arising from large-scale gene expression data. By studying grapevine (Vitis vinifera) and tomato (Solanum lycopersicum) gene expression atlases and a grapevine berry transcriptomic data set during the transition from immature to mature growth, we identified a category named "fight-club hubs" characterized by a marked negative correlation with the expression profiles of neighboring genes in the network. A special subset named "switch genes" was identified, with the additional property of many significant negative correlations outside their own group in the network. Switch genes are involved in multiple processes and include transcription factors that may be considered master regulators of the previously reported transcriptome remodeling that marks the developmental shift from immature to mature growth. All switch genes, expressed at low levels in vegetative/green tissues, showed a significant increase in mature/woody organs, suggesting a potential regulatory role during the developmental transition. Finally, our analysis of tomato gene expression data sets showed that wild-type switch genes are downregulated in ripening-deficient mutants. The identification of known master regulators of tomato fruit maturation suggests our method is suitable for the detection of key regulators of organ development in different fleshy fruit crops. © 2014 American Society of Plant Biologists. All rights reserved.

  18. Identifying traffic accident black spots with Poisson-Tweedie models

    DEFF Research Database (Denmark)

    Debrabant, Birgit; Halekoh, Ulrich; Bonat, Wagner Hugo

    2018-01-01

    This paper aims at the identification of black spots for traffic accidents, i.e. locations with accident counts beyond what is usual for similar locations, using spatially and temporally aggregated hospital records from Funen, Denmark. Specifically, we apply an autoregressive Poisson-Tweedie model...... considered calendar years and calculated by simulations a probability of p=0.03 for these to be chance findings. Altogether, our results recommend these sites for further investigation and suggest that our simple approach could play a role in future area based traffic accident prevention planning....

  19. Identifying the Source of Misfit in Item Response Theory Models.

    Science.gov (United States)

    Liu, Yang; Maydeu-Olivares, Alberto

    2014-01-01

    When an item response theory model fails to fit adequately, the items for which the model provides a good fit and those for which it does not must be determined. To this end, we compare the performance of several fit statistics for item pairs with known asymptotic distributions under maximum likelihood estimation of the item parameters: (a) a mean and variance adjustment to bivariate Pearson's X(2), (b) a bivariate subtable analog to Reiser's (1996) overall goodness-of-fit test, (c) a z statistic for the bivariate residual cross product, and (d) Maydeu-Olivares and Joe's (2006) M2 statistic applied to bivariate subtables. The unadjusted Pearson's X(2) with heuristically determined degrees of freedom is also included in the comparison. For binary and ordinal data, our simulation results suggest that the z statistic has the best Type I error and power behavior among all the statistics under investigation when the observed information matrix is used in its computation. However, if one has to use the cross-product information, the mean and variance adjusted X(2) is recommended. We illustrate the use of pairwise fit statistics in 2 real-data examples and discuss possible extensions of the current research in various directions.

  20. Identifying missing dictionary entries with frequency-conserving context models

    Science.gov (United States)

    Williams, Jake Ryland; Clark, Eric M.; Bagrow, James P.; Danforth, Christopher M.; Dodds, Peter Sheridan

    2015-10-01

    In an effort to better understand meaning from natural language texts, we explore methods aimed at organizing lexical objects into contexts. A number of these methods for organization fall into a family defined by word ordering. Unlike demographic or spatial partitions of data, these collocation models are of special importance for their universal applicability. While we are interested here in text and have framed our treatment appropriately, our work is potentially applicable to other areas of research (e.g., speech, genomics, and mobility patterns) where one has ordered categorical data (e.g., sounds, genes, and locations). Our approach focuses on the phrase (whether word or larger) as the primary meaning-bearing lexical unit and object of study. To do so, we employ our previously developed framework for generating word-conserving phrase-frequency data. Upon training our model with the Wiktionary, an extensive, online, collaborative, and open-source dictionary that contains over 100 000 phrasal definitions, we develop highly effective filters for the identification of meaningful, missing phrase entries. With our predictions we then engage the editorial community of the Wiktionary and propose short lists of potential missing entries for definition, developing a breakthrough, lexical extraction technique and expanding our knowledge of the defined English lexicon of phrases.

  1. Parent-identified barriers to pediatric health care: a process-oriented model.

    Science.gov (United States)

    Sobo, Elisa J; Seid, Michael; Reyes Gelhard, Leticia

    2006-02-01

    To further understand barriers to care as experienced by health care consumers, and to demonstrate the importance of conjoining qualitative and quantitative health services research. Transcripts from focus groups conducted in San Diego with English- and Spanish-speaking parents of children with special health care needs. Participants were asked about the barriers to care they had experienced or perceived, and their strategies for overcoming these barriers. Using elementary anthropological discourse analysis techniques, a process-based conceptual model of the parent experience was devised. The analysis revealed a parent-motivated model of barriers to care that enriched our understanding of quantitative findings regarding the population from which the focus group sample was drawn. Parent-identified barriers were grouped into the following six temporally and spatially sequenced categories: necessary skills and prerequisites for gaining access to the system; realizing access once it is gained; front office experiences; interactions with physicians; system arbitrariness and fragmentation; outcomes that affect future interaction with the system. Key to the successful navigation of the system was parents' functional biomedical acculturation; this construct likens the biomedical health services system to a cultural system within which all parents/patients must learn to function competently. Qualitative analysis of focus group data enabled a deeper understanding of barriers to care--one that went beyond the traditional association of marker variables with poor outcomes ("what") to reveal an understanding of the processes by which parents experience the health care system ("how,"why") and by which disparities may arise. Development of such process-oriented models furthers the provision of patient-centered care and the creation of interventions, programs, and curricula to enhance such care. Qualitative discourse analysis, for example using this project's widely applicable

  2. Ocean Heat and Carbon Uptake in Transient Climate Change: Identifying Model Uncertainty

    Science.gov (United States)

    Romanou, Anastasia; Marshall, John

    2015-01-01

    Global warming on decadal and centennial timescales is mediated and ameliorated by the oceansequestering heat and carbon into its interior. Transient climate change is a function of the efficiency by whichanthropogenic heat and carbon are transported away from the surface into the ocean interior (Hansen et al. 1985).Gregory and Mitchell (1997) and Raper et al. (2002) were the first to identify the importance of the ocean heat uptakeefficiency in transient climate change. Observational estimates (Schwartz 2012) and inferences from coupledatmosphere-ocean general circulation models (AOGCMs; Gregory and Forster 2008; Marotzke et al. 2015), suggest thatocean heat uptake efficiency on decadal timescales lies in the range 0.5-1.5 W/sq m/K and is thus comparable to theclimate feedback parameter (Murphy et al. 2009). Moreover, the ocean not only plays a key role in setting the timing ofwarming but also its regional patterns (Marshall et al. 2014), which is crucial to our understanding of regional climate,carbon and heat uptake, and sea-level change. This short communication is based on a presentation given by A.Romanou at a recent workshop, Oceans Carbon and Heat Uptake: Uncertainties and Metrics, co-hosted by US CLIVARand OCB. As briefly reviewed below, we have incomplete but growing knowledge of how ocean models used in climatechange projections sequester heat and carbon into the interior. To understand and thence reduce errors and biases inthe ocean component of coupled models, as well as elucidate the key mechanisms at work, in the final section we outlinea proposed model intercomparison project named FAFMIP. In FAFMIP, coupled integrations would be carried out withprescribed overrides of wind stress and freshwater and heat fluxes acting at the sea surface.

  3. Understanding the Day Cent model: Calibration, sensitivity, and identifiability through inverse modeling

    Science.gov (United States)

    Necpálová, Magdalena; Anex, Robert P.; Fienen, Michael N.; Del Grosso, Stephen J.; Castellano, Michael J.; Sawyer, John E.; Iqbal, Javed; Pantoja, Jose L.; Barker, Daniel W.

    2015-01-01

    The ability of biogeochemical ecosystem models to represent agro-ecosystems depends on their correct integration with field observations. We report simultaneous calibration of 67 DayCent model parameters using multiple observation types through inverse modeling using the PEST parameter estimation software. Parameter estimation reduced the total sum of weighted squared residuals by 56% and improved model fit to crop productivity, soil carbon, volumetric soil water content, soil temperature, N2O, and soil3NO− compared to the default simulation. Inverse modeling substantially reduced predictive model error relative to the default model for all model predictions, except for soil 3NO− and 4NH+. Post-processing analyses provided insights into parameter–observation relationships based on parameter correlations, sensitivity and identifiability. Inverse modeling tools are shown to be a powerful way to systematize and accelerate the process of biogeochemical model interrogation, improving our understanding of model function and the underlying ecosystem biogeochemical processes that they represent.

  4. Identifying the effects of parameter uncertainty on the reliability of riverbank stability modelling

    Science.gov (United States)

    Samadi, A.; Amiri-Tokaldany, E.; Darby, S. E.

    2009-05-01

    Bank retreat is a key process in fluvial dynamics affecting a wide range of physical, ecological and socioeconomic issues in the fluvial environment. To predict the undesirable effects of bank retreat and to inform effective measures to prevent it, a wide range of bank stability models have been presented in the literature. These models typically express bank stability by defining a factor of safety as the ratio of driving and resisting forces acting on the incipient failure block. These forces are affected by a range of controlling factors that include such aspects as the bank profile (bank height and angle), the geotechnical properties of the bank materials, as well as the hydrological status of the riverbanks. In this paper we evaluate the extent to which uncertainties in the parameterization of these controlling factors feed through to influence the reliability of the resulting bank stability estimate. This is achieved by employing a simple model of riverbank stability with respect to planar failure (which is the most common type of bank stability model) in a series of sensitivity tests and Monte Carlo analyses to identify, for each model parameter, the range of values that induce significant changes in the simulated factor of safety. These identified parameter value ranges are compared to empirically derived parameter uncertainties to determine whether they are likely to confound the reliability of the resulting bank stability calculations. Our results show that parameter uncertainties are typically high enough that the likelihood of generating unreliable predictions is typically very high (> ˜ 80% for predictions requiring a precision of < ± 15%). Because parameter uncertainties are derived primarily from the natural variability of the parameters, rather than measurement errors, much more careful attention should be paid to field sampling strategies, such that the parameter uncertainties and consequent prediction unreliabilities can be quantified more

  5. Coupling process-based models and plant architectural models: A key issue for simulating crop production

    NARCIS (Netherlands)

    Reffye, de P.; Heuvelink, E.; Guo, Y.; Hu, B.G.; Zhang, B.G.

    2009-01-01

    Process-Based Models (PBMs) can successfully predict the impact of environmental factors (temperature, light, CO2, water and nutrients) on crop growth and yield. These models are used widely for yield prediction and optimization of water and nutrient supplies. Nevertheless, PBMs do not consider

  6. Diagnosing climate change impacts and identifying adaptation strategies by involving key stakeholder organisations and farmers in Sikkim, India: Challenges and opportunities.

    Science.gov (United States)

    Azhoni, Adani; Goyal, Manish Kumar

    2018-06-01

    Narrowing the gap between research, policy making and implementing adaptation remains a challenge in many parts of the world where climate change is likely to severely impact water security. This research aims to narrow this gap by matching the adaptation strategies being framed by policy makers to that of the perspectives of development agencies, researchers and farmers in the Himalayan state of Sikkim in India. Our case study examined the perspectives of various stakeholders for climate change impacts, current adaptation strategies, knowledge gaps and adaptation barriers, particularly in the context of implementing the Sikkim State Action Plan on Climate Change through semi-structured interviews carried out with decision makers in the Sikkim State Government, researchers, consultants, local academia, development agencies and farmers. Using Stakeholders Network Analysis tools, this research unravels the complexities of perceiving climate change impacts, identifying strategies, and implementing adaptation. While farmers are less aware about the global phenomenon of climate change impacts for water security, their knowledge of the local conditions and their close interaction with the State Government Agriculture Department provides them opportunities. Although important steps are being initiated through the Sikkim State Action Plan on Climate Change it is yet to deliver effective means of adaptation implementation and hence, strengthening the networks of close coordination between the various implementing agencies will pay dividends. Knowledge gaps and the need for capacity building identified in this research, based on the understandings of key stakeholders are highly relevant to both the research community and for informing policy. Copyright © 2018 Elsevier B.V. All rights reserved.

  7. Assessing Reliability of Cellulose Hydrolysis Models to Support Biofuel Process Design – Identifiability and Uncertainty Analysis

    DEFF Research Database (Denmark)

    Sin, Gürkan; Meyer, Anne S.; Gernaey, Krist

    2010-01-01

    The reliability of cellulose hydrolysis models is studied using the NREL model. An identifiability analysis revealed that only 6 out of 26 parameters are identifiable from the available data (typical hydrolysis experiments). Attempting to identify a higher number of parameters (as done in the ori......The reliability of cellulose hydrolysis models is studied using the NREL model. An identifiability analysis revealed that only 6 out of 26 parameters are identifiable from the available data (typical hydrolysis experiments). Attempting to identify a higher number of parameters (as done...

  8. Choosing preclinical study models of diabetic retinopathy: key problems for consideration

    Science.gov (United States)

    Mi, Xue-Song; Yuan, Ti-Fei; Ding, Yong; Zhong, Jing-Xiang; So, Kwok-Fai

    2014-01-01

    Diabetic retinopathy (DR) is the most common complication of diabetes mellitus in the eye. Although the clinical treatment for DR has already developed to a relative high level, there are still many urgent problems that need to be investigated in clinical and basic science. Currently, many in vivo animal models and in vitro culture systems have been applied to solve these problems. Many approaches have also been used to establish different DR models. However, till now, there has not been a single study model that can clearly and exactly mimic the developmental process of the human DR. Choosing the suitable model is important, not only for achieving our research goals smoothly, but also, to better match with different experimental proposals in the study. In this review, key problems for consideration in choosing study models of DR are discussed. These problems relate to clinical relevance, different approaches for establishing models, and choice of different species of animals as well as of the specific in vitro culture systems. Attending to these considerations will deepen the understanding on current study models and optimize the experimental design for the final goal of preventing DR. PMID:25429204

  9. Identifying the Areas Benefitting from the Prevention of Wind Erosion by the Key Ecological Function Area for the Protection of Desertification in Hunshandake, China

    Directory of Open Access Journals (Sweden)

    Yu Xiao

    2017-10-01

    Full Text Available Research on the spatial flow of ecosystem services can help to identify the spatial relationships between service-providing areas (SPAs and service-benefitting areas (SBAs. In this study, we used the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT model to stimulate the flow paths of the wind erosion prevented by ecosystems in Hunshandake, China. By interpolating these paths, the SBAs were identified, and their benefits in terms of land cover, population, and Gross Domestic Product (GDP were determined. The results indicated that the flow paths mostly extended to the eastern part of the study area, and the estimated cover of the SBAs was 39.21% of the total area of China. The grid cells through which many (≥10% of the trajectories passed were mainly located in the western part of north-eastern China and the eastern part of northern China. The benefitting population accounted for 74.51% of the total population of China, and the GDP was 67.11% of the total in 2010. Based on this research, we described a quantitative relationship between the SPAs and the SBAs and identified the actual beneficiaries. This work may provide scientific knowledge that can be used by decision makers to develop management strategies, such as ecological compensation to mitigate damage from sandstorms in the study area.

  10. Key Issues in Modeling of Complex 3D Structures from Video Sequences

    Directory of Open Access Journals (Sweden)

    Shengyong Chen

    2012-01-01

    Full Text Available Construction of three-dimensional structures from video sequences has wide applications for intelligent video analysis. This paper summarizes the key issues of the theory and surveys the recent advances in the state of the art. Reconstruction of a scene object from video sequences often takes the basic principle of structure from motion with an uncalibrated camera. This paper lists the typical strategies and summarizes the typical solutions or algorithms for modeling of complex three-dimensional structures. Open difficult problems are also suggested for further study.

  11. Backup key generation model for one-time password security protocol

    Science.gov (United States)

    Jeyanthi, N.; Kundu, Sourav

    2017-11-01

    The use of one-time password (OTP) has ushered new life into the existing authentication protocols used by the software industry. It introduced a second layer of security to the traditional username-password authentication, thus coining the term, two-factor authentication. One of the drawbacks of this protocol is the unreliability of the hardware token at the time of authentication. This paper proposes a simple backup key model that can be associated with the real world applications’user database, which would allow a user to circumvent the second authentication stage, in the event of unavailability of the hardware token.

  12. Key Process Uncertainties in Soil Carbon Dynamics: Comparing Multiple Model Structures and Observational Meta-analysis

    Science.gov (United States)

    Sulman, B. N.; Moore, J.; Averill, C.; Abramoff, R. Z.; Bradford, M.; Classen, A. T.; Hartman, M. D.; Kivlin, S. N.; Luo, Y.; Mayes, M. A.; Morrison, E. W.; Riley, W. J.; Salazar, A.; Schimel, J.; Sridhar, B.; Tang, J.; Wang, G.; Wieder, W. R.

    2016-12-01

    Soil carbon (C) dynamics are crucial to understanding and predicting C cycle responses to global change and soil C modeling is a key tool for understanding these dynamics. While first order model structures have historically dominated this area, a recent proliferation of alternative model structures representing different assumptions about microbial activity and mineral protection is providing new opportunities to explore process uncertainties related to soil C dynamics. We conducted idealized simulations of soil C responses to warming and litter addition using models from five research groups that incorporated different sets of assumptions about processes governing soil C decomposition and stabilization. We conducted a meta-analysis of published warming and C addition experiments for comparison with simulations. Assumptions related to mineral protection and microbial dynamics drove strong differences among models. In response to C additions, some models predicted long-term C accumulation while others predicted transient increases that were counteracted by accelerating decomposition. In experimental manipulations, doubling litter addition did not change soil C stocks in studies spanning as long as two decades. This result agreed with simulations from models with strong microbial growth responses and limited mineral sorption capacity. In observations, warming initially drove soil C loss via increased CO2 production, but in some studies soil C rebounded and increased over decadal time scales. In contrast, all models predicted sustained C losses under warming. The disagreement with experimental results could be explained by physiological or community-level acclimation, or by warming-related changes in plant growth. In addition to the role of microbial activity, assumptions related to mineral sorption and protected C played a key role in driving long-term model responses. In general, simulations were similar in their initial responses to perturbations but diverged over

  13. How cannabis causes paranoia: using the intravenous administration of ∆9-tetrahydrocannabinol (THC) to identify key cognitive mechanisms leading to paranoia.

    Science.gov (United States)

    Freeman, Daniel; Dunn, Graham; Murray, Robin M; Evans, Nicole; Lister, Rachel; Antley, Angus; Slater, Mel; Godlewska, Beata; Cornish, Robert; Williams, Jonathan; Di Simplicio, Martina; Igoumenou, Artemis; Brenneisen, Rudolf; Tunbridge, Elizabeth M; Harrison, Paul J; Harmer, Catherine J; Cowen, Philip; Morrison, Paul D

    2015-03-01

    Paranoia is receiving increasing attention in its own right, since it is a central experience of psychotic disorders and a marker of the health of a society. Paranoia is associated with use of the most commonly taken illicit drug, cannabis. The objective was to determine whether the principal psychoactive ingredient of cannabis-∆(9)-tetrahydrocannabinol (THC)-causes paranoia and to use the drug as a probe to identify key cognitive mechanisms underlying paranoia. A randomized, placebo-controlled, between-groups test of the effects of intravenous THC was conducted. A total of 121 individuals with paranoid ideation were randomized to receive placebo, THC, or THC preceded by a cognitive awareness condition. Paranoia was assessed extensively via a real social situation, an immersive virtual reality experiment, and standard self-report and interviewer measures. Putative causal factors were assessed. Principal components analysis was used to create a composite paranoia score and composite causal variables to be tested in a mediation analysis. THC significantly increased paranoia, negative affect (anxiety, worry, depression, negative thoughts about the self), and a range of anomalous experiences, and reduced working memory capacity. The increase in negative affect and in anomalous experiences fully accounted for the increase in paranoia. Working memory changes did not lead to paranoia. Making participants aware of the effects of THC had little impact. In this largest study of intravenous THC, it was definitively demonstrated that the drug triggers paranoid thoughts in vulnerable individuals. The most likely mechanism of action causing paranoia was the generation of negative affect and anomalous experiences. © The Author 2014. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center.

  14. Sulfur Denitrosylation by an Engineered Trx-like DsbG Enzyme Identifies Nucleophilic Cysteine Hydrogen Bonds as Key Functional Determinant.

    Science.gov (United States)

    Lafaye, Céline; Van Molle, Inge; Tamu Dufe, Veronica; Wahni, Khadija; Boudier, Ariane; Leroy, Pierre; Collet, Jean-François; Messens, Joris

    2016-07-15

    Exposure of bacteria to NO results in the nitrosylation of cysteine thiols in proteins and low molecular weight thiols such as GSH. The cells possess enzymatic systems that catalyze the denitrosylation of these modified sulfurs. An important player in these systems is thioredoxin (Trx), a ubiquitous, cytoplasmic oxidoreductase that can denitrosylate proteins in vivo and S-nitrosoglutathione (GSNO) in vitro However, a periplasmic or extracellular denitrosylase has not been identified, raising the question of how extracytoplasmic proteins are repaired after nitrosative damage. In this study, we tested whether DsbG and DsbC, two Trx family proteins that function in reducing pathways in the Escherichia coli periplasm, also possess denitrosylating activity. Both DsbG and DsbC are poorly reactive toward GSNO. Moreover, DsbG is unable to denitrosylate its specific substrate protein, YbiS. Remarkably, by borrowing the CGPC active site of E. coli Trx-1 in combination with a T200M point mutation, we transformed DsbG into an enzyme highly reactive toward GSNO and YbiS. The pKa of the nucleophilic cysteine, as well as the redox and thermodynamic properties of the engineered DsbG are dramatically changed and become similar to those of E. coli Trx-1. X-ray structural insights suggest that this results from a loss of two direct hydrogen bonds to the nucleophilic cysteine sulfur in the DsbG mutant. Our results highlight the plasticity of the Trx structural fold and reveal that the subtle change of the number of hydrogen bonds in the active site of Trx-like proteins is the key factor that thermodynamically controls reactivity toward nitrosylated compounds. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

  15. Identifying the key factors in increasing recycling and reducing residual household waste: a case study of the Flemish region of Belgium.

    Science.gov (United States)

    Gellynck, X; Jacobsen, R; Verhelst, P

    2011-10-01

    The competent waste authority in the Flemish region of Belgium created the 'Implementation plan household waste 2003-2007' and the 'Implementation plan sustainable management 2010-2015' to comply with EU regulation. It incorporates European and regional requirements and describes strategies, goals, actions and instruments for the collection and treatment of household waste. The central mandatory goal is to reduce and maintain the amount of residual household waste to 150 kg per capita per year between 2010-2015. In literature, a reasonable body of information has been published on the effectiveness and efficiency of a variety of policy instruments, but the information is complex, often contradictory and difficult to interpret. The objective of this paper is to identify, through the development of a binary logistic regression model, those variables of the waste collection scheme that help municipalities to reach the mandatory 150 kg goal. The model covers a number of variables for household characteristics, provision of recycling services, frequency of waste collection and charging for waste services. This paper, however, is not about waste prevention and reuse. The dataset originates from 2003. Four out of 12 variables in the model contributed significantly: income per capita, cost of residual waste collection, collection frequency and separate curbside collection of organic waste. Copyright © 2011 Elsevier Ltd. All rights reserved.

  16. Quantifying Key Climate Parameter Uncertainties Using an Earth System Model with a Dynamic 3D Ocean

    Science.gov (United States)

    Olson, R.; Sriver, R. L.; Goes, M. P.; Urban, N.; Matthews, D.; Haran, M.; Keller, K.

    2011-12-01

    Climate projections hinge critically on uncertain climate model parameters such as climate sensitivity, vertical ocean diffusivity and anthropogenic sulfate aerosol forcings. Climate sensitivity is defined as the equilibrium global mean temperature response to a doubling of atmospheric CO2 concentrations. Vertical ocean diffusivity parameterizes sub-grid scale ocean vertical mixing processes. These parameters are typically estimated using Intermediate Complexity Earth System Models (EMICs) that lack a full 3D representation of the oceans, thereby neglecting the effects of mixing on ocean dynamics and meridional overturning. We improve on these studies by employing an EMIC with a dynamic 3D ocean model to estimate these parameters. We carry out historical climate simulations with the University of Victoria Earth System Climate Model (UVic ESCM) varying parameters that affect climate sensitivity, vertical ocean mixing, and effects of anthropogenic sulfate aerosols. We use a Bayesian approach whereby the likelihood of each parameter combination depends on how well the model simulates surface air temperature and upper ocean heat content. We use a Gaussian process emulator to interpolate the model output to an arbitrary parameter setting. We use Markov Chain Monte Carlo method to estimate the posterior probability distribution function (pdf) of these parameters. We explore the sensitivity of the results to prior assumptions about the parameters. In addition, we estimate the relative skill of different observations to constrain the parameters. We quantify the uncertainty in parameter estimates stemming from climate variability, model and observational errors. We explore the sensitivity of key decision-relevant climate projections to these parameters. We find that climate sensitivity and vertical ocean diffusivity estimates are consistent with previously published results. The climate sensitivity pdf is strongly affected by the prior assumptions, and by the scaling

  17. Key transmission parameters of an institutional outbreak during the 1918 influenza pandemic estimated by mathematical modelling

    Directory of Open Access Journals (Sweden)

    Nelson Peter

    2006-11-01

    Full Text Available Abstract Aim To estimate the key transmission parameters associated with an outbreak of pandemic influenza in an institutional setting (New Zealand 1918. Methods Historical morbidity and mortality data were obtained from the report of the medical officer for a large military camp. A susceptible-exposed-infectious-recovered epidemiological model was solved numerically to find a range of best-fit estimates for key epidemic parameters and an incidence curve. Mortality data were subsequently modelled by performing a convolution of incidence distribution with a best-fit incidence-mortality lag distribution. Results Basic reproduction number (R0 values for three possible scenarios ranged between 1.3, and 3.1, and corresponding average latent period and infectious period estimates ranged between 0.7 and 1.3 days, and 0.2 and 0.3 days respectively. The mean and median best-estimate incidence-mortality lag periods were 6.9 and 6.6 days respectively. This delay is consistent with secondary bacterial pneumonia being a relatively important cause of death in this predominantly young male population. Conclusion These R0 estimates are broadly consistent with others made for the 1918 influenza pandemic and are not particularly large relative to some other infectious diseases. This finding suggests that if a novel influenza strain of similar virulence emerged then it could potentially be controlled through the prompt use of major public health measures.

  18. Development of generic key performance indicators for PMBOK® using a 3D project integration model

    Directory of Open Access Journals (Sweden)

    Craig Langston

    2013-12-01

    Full Text Available Since Martin Barnes’ so-called ‘iron triangle’ circa 1969, much debate has occurred over how best to describe the fundamental constraints that underpin project success. This paper develops a 3D project integration model for PMBOK® comprising core constraints of scope, cost, time and risk as a basis to propose six generic key performance indicators (KPIs that articulate successful project delivery. These KPIs are defined as value, efficiency, speed, innovation, complexity and impact and can each be measured objectively as ratios of the core constraints. An overall KPI (denoted as s3/ctr is also derived. The aim in this paper is to set out the case for such a model and to demonstrate how it can be employed to assess the performance of project teams in delivering successful outcomes at various stages in the project life cycle. As part of the model’s development, a new PMBOK® knowledge area concerning environmental management is advanced.

  19. Topical video object discovery from key frames by modeling word co-occurrence prior.

    Science.gov (United States)

    Zhao, Gangqiang; Yuan, Junsong; Hua, Gang; Yang, Jiong

    2015-12-01

    A topical video object refers to an object, that is, frequently highlighted in a video. It could be, e.g., the product logo and the leading actor/actress in a TV commercial. We propose a topic model that incorporates a word co-occurrence prior for efficient discovery of topical video objects from a set of key frames. Previous work using topic models, such as latent Dirichelet allocation (LDA), for video object discovery often takes a bag-of-visual-words representation, which ignored important co-occurrence information among the local features. We show that such data driven co-occurrence information from bottom-up can conveniently be incorporated in LDA with a Gaussian Markov prior, which combines top-down probabilistic topic modeling with bottom-up priors in a unified model. Our experiments on challenging videos demonstrate that the proposed approach can discover different types of topical objects despite variations in scale, view-point, color and lighting changes, or even partial occlusions. The efficacy of the co-occurrence prior is clearly demonstrated when compared with topic models without such priors.

  20. Choosing preclinical study models of diabetic retinopathy: key problems for consideration

    Directory of Open Access Journals (Sweden)

    Mi XS

    2014-11-01

    Full Text Available Xue-Song Mi,1,2 Ti-Fei Yuan,3,4 Yong Ding,1 Jing-Xiang Zhong,1 Kwok-Fai So4,5 1Department of Ophthalmology, First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, People’s Republic of China; 2Department of Anatomy, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, People’s Republic of China; 3School of Psychology, Nanjing Normal University, Nanjing, People’s Republic of China; 4Department of Ophthalmology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong; 5Guangdong-Hongkong-Macau Institute of Central Nervous System, Jinan University, Guangzhou, People’s Republic of China Abstract: Diabetic retinopathy (DR is the most common complication of diabetes mellitus in the eye. Although the clinical treatment for DR has already developed to a relative high level, there are still many urgent problems that need to be investigated in clinical and basic science. Currently, many in vivo animal models and in vitro culture systems have been applied to solve these problems. Many approaches have also been used to establish different DR models. However, till now, there has not been a single study model that can clearly and exactly mimic the developmental process of the human DR. Choosing the suitable model is important, not only for achieving our research goals smoothly, but also, to better match with different experimental proposals in the study. In this review, key problems for consideration in choosing study models of DR are discussed. These problems relate to clinical relevance, different approaches for establishing models, and choice of different species of animals as well as of the specific in vitro culture systems. Attending to these considerations will deepen the understanding on current study models and optimize the experimental design for the final goal of preventing DR. Keywords: animal model, in vitro culture, ex vivo culture, neurovascular dysfunction

  1. The giant Jiaodong gold province: The key to a unified model for orogenic gold deposits?

    Directory of Open Access Journals (Sweden)

    David I. Groves

    2016-05-01

    Full Text Available Although the term orogenic gold deposit has been widely accepted for all gold-only lode-gold deposits, with the exception of Carlin-type deposits and rare intrusion-related gold systems, there has been continuing debate on their genesis. Early syngenetic models and hydrothermal models dominated by meteoric fluids are now clearly unacceptable. Magmatic-hydrothermal models fail to explain the genesis of orogenic gold deposits because of the lack of consistent spatially – associated granitic intrusions and inconsistent temporal relationships. The most plausible, and widely accepted, models involve metamorphic fluids, but the source of these fluids is hotly debated. Sources within deeper segments of the supracrustal successions hosting the deposits, the underlying continental crust, and subducted oceanic lithosphere and its overlying sediment wedge all have their proponents. The orogenic gold deposits of the giant Jiaodong gold province of China, in the delaminated North China Craton, contain ca. 120 Ma gold deposits in Precambrian crust that was metamorphosed over 2000 million years prior to gold mineralization. The only realistic source of fluid and gold is a subducted oceanic slab with its overlying sulfide-rich sedimentary package, or the associated mantle wedge. This could be viewed as an exception to a general metamorphic model where orogenic gold has been derived during greenschist- to amphibolite-facies metamorphism of supracrustal rocks: basaltic rocks in the Precambrian and sedimentary rocks in the Phanerozoic. Alternatively, if a holistic view is taken, Jiaodong can be considered the key orogenic gold province for a unified model in which gold is derived from late-orogenic metamorphic devolatilization of stalled subduction slabs and oceanic sediments throughout Earth history. The latter model satisfies all geological, geochronological, isotopic and geochemical constraints but the precise mechanisms of auriferous fluid release, like many

  2. Automatic generation of predictive dynamic models reveals nuclear phosphorylation as the key Msn2 control mechanism.

    Science.gov (United States)

    Sunnåker, Mikael; Zamora-Sillero, Elias; Dechant, Reinhard; Ludwig, Christina; Busetto, Alberto Giovanni; Wagner, Andreas; Stelling, Joerg

    2013-05-28

    Predictive dynamical models are critical for the analysis of complex biological systems. However, methods to systematically develop and discriminate among systems biology models are still lacking. We describe a computational method that incorporates all hypothetical mechanisms about the architecture of a biological system into a single model and automatically generates a set of simpler models compatible with observational data. As a proof of principle, we analyzed the dynamic control of the transcription factor Msn2 in Saccharomyces cerevisiae, specifically the short-term mechanisms mediating the cells' recovery after release from starvation stress. Our method determined that 12 of 192 possible models were compatible with available Msn2 localization data. Iterations between model predictions and rationally designed phosphoproteomics and imaging experiments identified a single-circuit topology with a relative probability of 99% among the 192 models. Model analysis revealed that the coupling of dynamic phenomena in Msn2 phosphorylation and transport could lead to efficient stress response signaling by establishing a rate-of-change sensor. Similar principles could apply to mammalian stress response pathways. Systematic construction of dynamic models may yield detailed insight into nonobvious molecular mechanisms.

  3. Key issues

    International Nuclear Information System (INIS)

    Cook, N.G.W.

    1980-01-01

    Successful modeling of the thermo-mechanical and hydrochemical behavior of radioactive waste repositories in hard rock is possible in principle. Because such predictions lie outside the realm of experience, their adequacy depends entirely upon a thorough understanding of three fundamental questions: an understanding of the chemical and physical processess that determine the behavior of rock and all its complexities; accurate and realistic numerical models of the geologic media within which a repository may be built; and sufficient in-situ data covering the entire geologic region affected by, or effecting the behavior of a repository. At present sufficient is known to be able to identify most of those areas which require further attention. These areas extend all the way from a complete understanding of the chemical and physical processes determining the behavior of rock through to the exploration mapping and testing that must be done during the development of any potential repository. Many of the techniques, laboratory equipment, field instrumentation, and numerical methods needed to accomplish this do not exist at present. Therefore it is necessary to accept that a major investment in scientific research is required to generate this information over the next few years. The spectrum of scientific and engineering activities is wide extending from laboratory measurements through the development of numerical models to the measurement of data in-situ, but there is every prospect that sufficient can be done to resolve these key issues. However, to do so requires overt recognition of the many gaps which exist in our knowledge and abilities today, and of the need to bridge these gaps and of the significant costs involved in doing so

  4. A lock-and-key model for protein–protein interactions

    OpenAIRE

    Morrison, Julie L.; Breitling, Rainer; Higham, Desmond J.; Gilbert, David R.

    2006-01-01

    Motivation: Protein–protein interaction networks are one of the major post-genomic data sources available to molecular biologists. They provide a comprehensive view of the global interaction structure of an organism’s proteome, as well as detailed information on specific interactions. Here we suggest a physical model of protein interactions that can be used to extract additional information at an intermediate level: It enables us to identify proteins which share biological interaction motifs,...

  5. A pilot study using scripted ventilation conditions to identify key factors affecting indoor pollutant concentration and air exchange rate in a residence.

    Science.gov (United States)

    Johnson, Ted; Myers, Jeffrey; Kelly, Thomas; Wisbith, Anthony; Ollison, Will

    2004-01-01

    A pilot study was conducted using an occupied, single-family test house in Columbus, OH, to determine whether a script-based protocol could be used to obtain data useful in identifying the key factors affecting air-exchange rate (AER) and the relationship between indoor and outdoor concentrations of selected traffic-related air pollutants. The test script called for hourly changes to elements of the test house considered likely to influence air flow and AER, including the position (open or closed) of each window and door and the operation (on/off) of the furnace, air conditioner, and ceiling fans. The script was implemented over a 3-day period (January 30-February 1, 2002) during which technicians collected hourly-average data for AER, indoor, and outdoor air concentrations for six pollutants (benzene, formaldehyde (HCHO), polycyclic aromatic hydrocarbons (PAH), carbon monoxide (CO), nitric oxide (NO), and nitrogen oxides (NO(x))), and selected meteorological variables. Consistent with expectations, AER tended to increase with the number of open exterior windows and doors. The 39 AER values measured during the study when all exterior doors and windows were closed varied from 0.36 to 2.29 h(-1) with a geometric mean (GM) of 0.77 h(-1) and a geometric standard deviation (GSD) of 1.435. The 27 AER values measured when at least one exterior door or window was opened varied from 0.50 to 15.8 h(-1) with a GM of 1.98 h(-1) and a GSD of 1.902. AER was also affected by temperature and wind speed, most noticeably when exterior windows and doors were closed. Results of a series of stepwise linear regression analyses suggest that (1) outdoor pollutant concentration and (2) indoor pollutant concentration during the preceding hour were the "variables of choice" for predicting indoor pollutant concentration in the test house under the conditions of this study. Depending on the pollutant and ventilation conditions, one or more of the following variables produced a small, but

  6. Global identifiability of linear compartmental models--a computer algebra algorithm.

    Science.gov (United States)

    Audoly, S; D'Angiò, L; Saccomani, M P; Cobelli, C

    1998-01-01

    A priori global identifiability deals with the uniqueness of the solution for the unknown parameters of a model and is, thus, a prerequisite for parameter estimation of biological dynamic models. Global identifiability is however difficult to test, since it requires solving a system of algebraic nonlinear equations which increases both in nonlinearity degree and number of terms and unknowns with increasing model order. In this paper, a computer algebra tool, GLOBI (GLOBal Identifiability) is presented, which combines the topological transfer function method with the Buchberger algorithm, to test global identifiability of linear compartmental models. GLOBI allows for the automatic testing of a priori global identifiability of general structure compartmental models from general multi input-multi output experiments. Examples of usage of GLOBI to analyze a priori global identifiability of some complex biological compartmental models are provided.

  7. Key Elements of the User-Friendly, GFDL SKYHI General Circulation Model

    Directory of Open Access Journals (Sweden)

    Richard S. Hemler

    2000-01-01

    Full Text Available Over the past seven years, the portability of the GFDL SKYHI general circulation model has greatly increased. Modifications to the source code have allowed SKYHI to be run on the GFDL Cray Research PVP machines, the TMC CM-5 machine at Los Alamos National Laboratory, and more recently on the GFDL 40-processor Cray Research T3E system. At the same time, changes have been made to the model to make it more usable and flexible. Because of the reduction of the human resources available to manage and analyze scientific experiments, it is no longer acceptable to consider only the optimization of computer resources when producing a research code; one must also consider the availability and cost of the people necessary to maintain, modify and use the model as an investigative tool, and include these factors in defining the form of the model code. The new SKYHI model attempts to strike a balance between the optimization of the use of machine resources (CPU time, memory, disc and the optimal use of human resources (ability to understand code, ability to modify code, ability to perturb code to do experiments, ability to run code on different platforms. Two of the key features that make the new SKYHI code more usable and flexible are the archiving package and the user variable block. The archiving package is used to manage the writing of all archive files, which contain data for later analysis. The model-supplied user variable block allows the easy inclusion of any new variables needed for particular experiments.

  8. Plant modeling as a key tool for nuclear I and C design and V and V

    International Nuclear Information System (INIS)

    Krasnov, V.; Sokolov, O.; Symkin, B.

    2006-01-01

    This paper summarizes an intensive experience of LvivORGRES in the design and implementation of the digital control systems at VVER-1000 and VVER-440 nuclear power plants in Ukraine and Bulgaria. This experience is applicable to the digital I and C upgrade projects for other types of reactor equipment as well as to the design and testing of new I and C systems for new constructions. LvivORGRES was recently involved in several modernization projects as a functional designer and, also, provided technical support and supervision during the factory and site acceptance testing. It is widely accepted and proved by the industry's practice that a level and quality of system validation at all design and implementation phases are key to the successful future operation of I and C systems. The plant control systems have some additional validation requirements in comparing with the information and monitoring systems. According to the Ukrainian nuclear regulation standards, the scope of the control system projects should include the close loop stability analysis at all unit modes of operation. Besides the control system algorithms verification and validation, it was necessary to determine the tuning parameters for the system and use them initially during the system commissioning. LvivORGRES has developed the Adaptive Plant Modeling process that was used as a key tool in all design stages of control system upgrade projects: Software engineering tests, Integrated system validation tests, Factory acceptance tests. The Plant Model was developed on a modular basis which allowed the testing of all primary and secondary side regulators for all unit modes of operation including transients and unit start-up and shutdown. The Plant Model has been adapted to each project's requirements. The use of the plant simulation provided technical bases for important project decisions and documents including among others: system test strategy, initial tuning parameters, training plan, etc. The Plant

  9. Antimicrobial Nanoplexes meet Model Bacterial Membranes: the key role of Cardiolipin

    Science.gov (United States)

    Marín-Menéndez, Alejandro; Montis, Costanza; Díaz-Calvo, Teresa; Carta, Davide; Hatzixanthis, Kostas; Morris, Christopher J.; McArthur, Michael; Berti, Debora

    2017-01-01

    Antimicrobial resistance to traditional antibiotics is a crucial challenge of medical research. Oligonucleotide therapeutics, such as antisense or Transcription Factor Decoys (TFDs), have the potential to circumvent current resistance mechanisms by acting on novel targets. However, their full translation into clinical application requires efficient delivery strategies and fundamental comprehension of their interaction with target bacterial cells. To address these points, we employed a novel cationic bolaamphiphile that binds TFDs with high affinity to form self-assembled complexes (nanoplexes). Confocal microscopy revealed that nanoplexes efficiently transfect bacterial cells, consistently with biological efficacy on animal models. To understand the factors affecting the delivery process, liposomes with varying compositions, taken as model synthetic bilayers, were challenged with nanoplexes and investigated with Scattering and Fluorescence techniques. Thanks to the combination of results on bacteria and synthetic membrane models we demonstrate for the first time that the prokaryotic-enriched anionic lipid Cardiolipin (CL) plays a key-role in the TFDs delivery to bacteria. Moreover, we can hypothesize an overall TFD delivery mechanism, where bacterial membrane reorganization with permeability increase and release of the TFD from the nanoplexes are the main factors. These results will be of great benefit to boost the development of oligonucleotides-based antimicrobials of superior efficacy.

  10. Keys to the House: Unlocking Residential Savings With Program Models for Home Energy Upgrades

    Energy Technology Data Exchange (ETDEWEB)

    Grevatt, Jim [Energy Futures Group (United States); Hoffman, Ian [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Hoffmeyer, Dale [US Department of Energy, Washington, DC (United States)

    2017-07-05

    After more than 40 years of effort, energy efficiency program administrators and associated contractors still find it challenging to penetrate the home retrofit market, especially at levels commensurate with state and federal goals for energy savings and emissions reductions. Residential retrofit programs further have not coalesced around a reliably successful model. They still vary in design, implementation and performance, and they remain among the more difficult and costly options for acquiring savings in the residential sector. If programs are to contribute fully to meeting resource and policy objectives, administrators need to understand what program elements are key to acquiring residential savings as cost effectively as possible. To that end, the U.S. Department of Energy (DOE) sponsored a comprehensive review and analysis of home energy upgrade programs with proven track records, focusing on those with robustly verified savings and constituting good examples for replication. The study team reviewed evaluations for the period 2010 to 2014 for 134 programs that are funded by customers of investor-owned utilities. All are programs that promote multi-measure retrofits or major system upgrades. We paid particular attention to useful design and implementation features, costs, and savings for nearly 30 programs with rigorous evaluations of performance. This meta-analysis describes program models and implementation strategies for (1) direct install retrofits; (2) heating, ventilating and air-conditioning (HVAC) replacement and early retirement; and (3) comprehensive, whole-home retrofits. We analyze costs and impacts of these program models, in terms of both energy savings and emissions avoided. These program models can be useful guides as states consider expanding their strategies for acquiring energy savings as a resource and for emissions reductions. We also discuss the challenges of using evaluations to create program models that can be confidently applied in

  11. Operational Details of the Five Domains Model and Its Key Applications to the Assessment and Management of Animal Welfare

    Science.gov (United States)

    Mellor, David J.

    2017-01-01

    Simple Summary The Five Domains Model is a focusing device to facilitate systematic, structured, comprehensive and coherent assessment of animal welfare; it is not a definition of animal welfare, nor is it intended to be an accurate representation of body structure and function. The purpose of each of the five domains is to draw attention to areas that are relevant to both animal welfare assessment and management. This paper begins by briefly describing the major features of the Model and the operational interactions between the five domains, and then it details seven interacting applications of the Model. These underlie its utility and increasing application to welfare assessment and management in diverse animal use sectors. Abstract In accord with contemporary animal welfare science understanding, the Five Domains Model has a significant focus on subjective experiences, known as affects, which collectively contribute to an animal’s overall welfare state. Operationally, the focus of the Model is on the presence or absence of various internal physical/functional states and external circumstances that give rise to welfare-relevant negative and/or positive mental experiences, i.e., affects. The internal states and external circumstances of animals are evaluated systematically by referring to each of the first four domains of the Model, designated “Nutrition”, “Environment”, “Health” and “Behaviour”. Then affects, considered carefully and cautiously to be generated by factors in these domains, are accumulated into the fifth domain, designated “Mental State”. The scientific foundations of this operational procedure, published in detail elsewhere, are described briefly here, and then seven key ways the Model may be applied to the assessment and management of animal welfare are considered. These applications have the following beneficial objectives—they (1) specify key general foci for animal welfare management; (2) highlight the foundations of

  12. Network analysis of patient flow in two UK acute care hospitals identifies key sub-networks for A&E performance.

    Science.gov (United States)

    Bean, Daniel M; Stringer, Clive; Beeknoo, Neeraj; Teo, James; Dobson, Richard J B

    2017-01-01

    The topology of the patient flow network in a hospital is complex, comprising hundreds of overlapping patient journeys, and is a determinant of operational efficiency. To understand the network architecture of patient flow, we performed a data-driven network analysis of patient flow through two acute hospital sites of King's College Hospital NHS Foundation Trust. Administration databases were queried for all intra-hospital patient transfers in an 18-month period and modelled as a dynamic weighted directed graph. A 'core' subnetwork containing only 13-17% of all edges channelled 83-90% of the patient flow, while an 'ephemeral' network constituted the remainder. Unsupervised cluster analysis and differential network analysis identified sub-networks where traffic is most associated with A&E performance. Increased flow to clinical decision units was associated with the best A&E performance in both sites. The component analysis also detected a weekend effect on patient transfers which was not associated with performance. We have performed the first data-driven hypothesis-free analysis of patient flow which can enhance understanding of whole healthcare systems. Such analysis can drive transformation in healthcare as it has in industries such as manufacturing.

  13. Key Characteristics of Combined Accident including TLOFW accident for PSA Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Bo Gyung; Kang, Hyun Gook [KAIST, Daejeon (Korea, Republic of); Yoon, Ho Joon [Khalifa University of Science, Technology and Research, Abu Dhabi (United Arab Emirates)

    2015-05-15

    The conventional PSA techniques cannot adequately evaluate all events. The conventional PSA models usually focus on single internal events such as DBAs, the external hazards such as fire, seismic. However, the Fukushima accident of Japan in 2011 reveals that very rare event is necessary to be considered in the PSA model to prevent the radioactive release to environment caused by poor treatment based on lack of the information, and to improve the emergency operation procedure. Especially, the results from PSA can be used to decision making for regulators. Moreover, designers can consider the weakness of plant safety based on the quantified results and understand accident sequence based on human actions and system availability. This study is for PSA modeling of combined accidents including total loss of feedwater (TLOFW) accident. The TLOFW accident is a representative accident involving the failure of cooling through secondary side. If the amount of heat transfer is not enough due to the failure of secondary side, the heat will be accumulated to the primary side by continuous core decay heat. Transients with loss of feedwater include total loss of feedwater accident, loss of condenser vacuum accident, and closure of all MSIVs. When residual heat removal by the secondary side is terminated, the safety injection into the RCS with direct primary depressurization would provide alternative heat removal. This operation is called feed and bleed (F and B) operation. Combined accidents including TLOFW accident are very rare event and partially considered in conventional PSA model. Since the necessity of F and B operation is related to plant conditions, the PSA modeling for combined accidents including TLOFW accident is necessary to identify the design and operational vulnerabilities.The PSA is significant to assess the risk of NPPs, and to identify the design and operational vulnerabilities. Even though the combined accident is very rare event, the consequence of combined

  14. Predictive Modelling to Identify Near-Shore, Fine-Scale Seabird Distributions during the Breeding Season.

    Science.gov (United States)

    Warwick-Evans, Victoria C; Atkinson, Philip W; Robinson, Leonie A; Green, Jonathan A

    2016-01-01

    During the breeding season seabirds are constrained to coastal areas and are restricted in their movements, spending much of their time in near-shore waters either loafing or foraging. However, in using these areas they may be threatened by anthropogenic activities such as fishing, watersports and coastal developments including marine renewable energy installations. Although many studies describe large scale interactions between seabirds and the environment, the drivers behind near-shore, fine-scale distributions are not well understood. For example, Alderney is an important breeding ground for many species of seabird and has a diversity of human uses of the marine environment, thus providing an ideal location to investigate the near-shore fine-scale interactions between seabirds and the environment. We used vantage point observations of seabird distribution, collected during the 2013 breeding season in order to identify and quantify some of the environmental variables affecting the near-shore, fine-scale distribution of seabirds in Alderney's coastal waters. We validate the models with observation data collected in 2014 and show that water depth, distance to the intertidal zone, and distance to the nearest seabird nest are key predictors in the distribution of Alderney's seabirds. AUC values for each species suggest that these models perform well, although the model for shags performed better than those for auks and gulls. While further unexplained underlying localised variation in the environmental conditions will undoubtedly effect the fine-scale distribution of seabirds in near-shore waters we demonstrate the potential of this approach in marine planning and decision making.

  15. Predictive Modelling to Identify Near-Shore, Fine-Scale Seabird Distributions during the Breeding Season.

    Directory of Open Access Journals (Sweden)

    Victoria C Warwick-Evans

    Full Text Available During the breeding season seabirds are constrained to coastal areas and are restricted in their movements, spending much of their time in near-shore waters either loafing or foraging. However, in using these areas they may be threatened by anthropogenic activities such as fishing, watersports and coastal developments including marine renewable energy installations. Although many studies describe large scale interactions between seabirds and the environment, the drivers behind near-shore, fine-scale distributions are not well understood. For example, Alderney is an important breeding ground for many species of seabird and has a diversity of human uses of the marine environment, thus providing an ideal location to investigate the near-shore fine-scale interactions between seabirds and the environment. We used vantage point observations of seabird distribution, collected during the 2013 breeding season in order to identify and quantify some of the environmental variables affecting the near-shore, fine-scale distribution of seabirds in Alderney's coastal waters. We validate the models with observation data collected in 2014 and show that water depth, distance to the intertidal zone, and distance to the nearest seabird nest are key predictors in the distribution of Alderney's seabirds. AUC values for each species suggest that these models perform well, although the model for shags performed better than those for auks and gulls. While further unexplained underlying localised variation in the environmental conditions will undoubtedly effect the fine-scale distribution of seabirds in near-shore waters we demonstrate the potential of this approach in marine planning and decision making.

  16. Test and lower bound modeling of keyed shear connections in RC shear walls

    DEFF Research Database (Denmark)

    Sørensen, Jesper Harrild; Herfelt, Morten Andersen; Hoang, Linh Cao

    2018-01-01

    This paper presents an investigation into the ultimate behavior of a recently developed design for keyed shear connections. The influence of the key depth on the failure mode and ductility of the connection has been studied by push-off tests. The tests showed that connections with larger key...

  17. Representing Microbial Dormancy in Soil Decomposition Models Improves Model Performance and Reveals Key Ecosystem Controls on Microbial Activity

    Science.gov (United States)

    He, Y.; Yang, J.; Zhuang, Q.; Wang, G.; Liu, Y.

    2014-12-01

    Climate feedbacks from soils can result from environmental change and subsequent responses of plant and microbial communities and nutrient cycling. Explicit consideration of microbial life history traits and strategy may be necessary to predict climate feedbacks due to microbial physiology and community changes and their associated effect on carbon cycling. In this study, we developed an explicit microbial-enzyme decomposition model and examined model performance with and without representation of dormancy at six temperate forest sites with observed soil efflux ranged from 4 to 10 years across different forest types. We then extrapolated the model to all temperate forests in the Northern Hemisphere (25-50°N) to investigate spatial controls on microbial and soil C dynamics. Both models captured the observed soil heterotrophic respiration (RH), yet no-dormancy model consistently exhibited large seasonal amplitude and overestimation in microbial biomass. Spatially, the total RH from temperate forests based on dormancy model amounts to 6.88PgC/yr, and 7.99PgC/yr based on no-dormancy model. However, no-dormancy model notably overestimated the ratio of microbial biomass to SOC. Spatial correlation analysis revealed key controls of soil C:N ratio on the active proportion of microbial biomass, whereas local dormancy is primarily controlled by soil moisture and temperature, indicating scale-dependent environmental and biotic controls on microbial and SOC dynamics. These developments should provide essential support to modeling future soil carbon dynamics and enhance the avenue for collaboration between empirical soil experiment and modeling in the sense that more microbial physiological measurements are needed to better constrain and evaluate the models.

  18. Key data elements for use in cost-utility modeling of biological treatments for rheumatoid arthritis.

    Science.gov (United States)

    Ganz, Michael L; Hansen, Brian Bekker; Valencia, Xavier; Strandberg-Larsen, Martin

    2015-05-01

    Economic evaluation is becoming more common and important as new biologic therapies for rheumatoid arthritis (RA) are developed. While much has been published about how to design cost-utility models for RA to conduct these evaluations, less has been written about the sources of data populating those models. The goal is to review the literature and to provide recommendations for future data collection efforts. This study reviewed RA cost-utility models published between January 2006 and February 2014 focusing on five key sources of data (health-related quality-of-life and utility, clinical outcomes, disease progression, course of treatment, and healthcare resource use and costs). It provided recommendations for collecting the appropriate data during clinical and other studies to support modeling of biologic treatments for RA. Twenty-four publications met the selection criteria. Almost all used two steps to convert clinical outcomes data to utilities rather than more direct methods; most did not use clinical outcomes measures that captured absolute levels of disease activity and physical functioning; one-third of them, in contrast with clinical reality, assumed zero disease progression for biologic-treated patients; little more than half evaluated courses of treatment reflecting guideline-based or actual clinical care; and healthcare resource use and cost data were often incomplete. Based on these findings, it is recommended that future studies collect clinical outcomes and health-related quality-of-life data using appropriate instruments that can convert directly to utilities; collect data on actual disease progression; be designed to capture real-world courses of treatment; and collect detailed data on a wide range of healthcare resources and costs.

  19. Uncertainty and Variability in Physiologically-Based Pharmacokinetic (PBPK) Models: Key Issues and Case Studies (Final Report)

    Science.gov (United States)

    EPA announced the availability of the final report, Uncertainty and Variability in Physiologically-Based Pharmacokinetic (PBPK) Models: Key Issues and Case Studies. This report summarizes some of the recent progress in characterizing uncertainty and variability in physi...

  20. The Importance of Representing Certain Key Vegetation Canopy Processes Explicitly in a Land Surface Model

    Science.gov (United States)

    Napoly, A.; Boone, A. A.; Martin, E.; Samuelsson, P.

    2015-12-01

    Land surface models are moving to more detailed vegetation canopy descriptions in order to better represent certain key processes, such as Carbon dynamics and snowpack evolution. Since such models are usually applied within coupled numerical weather prediction or spatially distributed hydrological models, these improvements must strike a balance between computational cost and complexity. The consequences of simplified or composite canopy approaches can be manifested in terms of increased errors with respect to soil temperatures, estimates of the diurnal cycle of the turbulent fluxes or snow canopy interception and melt. Vegetated areas and particularly forests are modeled in a quite simplified manner in the ISBA land surface model. However, continuous developments of surface processes now require a more accurate description of the canopy. A new version of the the model now includes a multi energy balance (MEB) option to explicitly represent the canopy and the forest floor. It will be shown that certain newly included processes such as the shading effect of the vegetation, the explicit heat capacity of the canopy, and the insulating effect of the forest floor turn out to be essential. A detailed study has been done for four French forested sites. It was found that the MEB option significantly improves the ground heat flux (RMSE decrease from 50W/m2 to 10W/m2 on average) and soil temperatures when compared against measurements. Also the sensible heat flux calculation was improved primarily owing to a better phasing with the solar insulation owing to a lower vegetation heat capacity. However, the total latent heat flux is less modified compared to the classical ISBA simulation since it is more related to water uptake and the formulation of the stomatal resistance (which are unchanged). Next, a benchmark over 40 Fluxnet sites (116 cumulated years) was performed and compared with results from the default composite soil-vegetation version of ISBA. The results show

  1. Developmental programming: the concept, large animal models, and the key role of uteroplacental vascular development.

    Science.gov (United States)

    Reynolds, L P; Borowicz, P P; Caton, J S; Vonnahme, K A; Luther, J S; Hammer, C J; Maddock Carlin, K R; Grazul-Bilska, A T; Redmer, D A

    2010-04-01

    Developmental programming refers to the programming of various bodily systems and processes by a stressor of the maternal system during pregnancy or during the neonatal period. Such stressors include nutritional stress, multiple pregnancy (i.e., increased numbers of fetuses in the gravid uterus), environmental stress (e.g., high environmental temperature, high altitude, prenatal steroid exposure), gynecological immaturity, and maternal or fetal genotype. Programming refers to impaired function of numerous bodily systems or processes, leading to poor growth, altered body composition, metabolic dysfunction, and poor productivity (e.g., poor growth, reproductive dysfunction) of the offspring throughout their lifespan and even across generations. A key component of developmental programming seems to be placental dysfunction, leading to altered fetal growth and development. We discuss various large animal models of developmental programming and how they have and will continue to contribute to our understanding of the mechanisms underlying altered placental function and developmental programming, and, further, how large animal models also will be critical to the identification and application of therapeutic strategies that will alleviate the negative consequences of developmental programming to improve offspring performance in livestock production and human medicine.

  2. Three novel approaches to structural identifiability analysis in mixed-effects models.

    Science.gov (United States)

    Janzén, David L I; Jirstrand, Mats; Chappell, Michael J; Evans, Neil D

    2016-05-06

    Structural identifiability is a concept that considers whether the structure of a model together with a set of input-output relations uniquely determines the model parameters. In the mathematical modelling of biological systems, structural identifiability is an important concept since biological interpretations are typically made from the parameter estimates. For a system defined by ordinary differential equations, several methods have been developed to analyse whether the model is structurally identifiable or otherwise. Another well-used modelling framework, which is particularly useful when the experimental data are sparsely sampled and the population variance is of interest, is mixed-effects modelling. However, established identifiability analysis techniques for ordinary differential equations are not directly applicable to such models. In this paper, we present and apply three different methods that can be used to study structural identifiability in mixed-effects models. The first method, called the repeated measurement approach, is based on applying a set of previously established statistical theorems. The second method, called the augmented system approach, is based on augmenting the mixed-effects model to an extended state-space form. The third method, called the Laplace transform mixed-effects extension, is based on considering the moment invariants of the systems transfer function as functions of random variables. To illustrate, compare and contrast the application of the three methods, they are applied to a set of mixed-effects models. Three structural identifiability analysis methods applicable to mixed-effects models have been presented in this paper. As method development of structural identifiability techniques for mixed-effects models has been given very little attention, despite mixed-effects models being widely used, the methods presented in this paper provides a way of handling structural identifiability in mixed-effects models previously not

  3. Key parameters of the sediment surface morphodynamics in an estuary - An assessment of model solutions

    Science.gov (United States)

    Sampath, D. M. R.; Boski, T.

    2018-05-01

    Large-scale geomorphological evolution of an estuarine system was simulated by means of a hybrid estuarine sedimentation model (HESM) applied to the Guadiana Estuary, in Southwest Iberia. The model simulates the decadal-scale morphodynamics of the system under environmental forcing, using a set of analytical solutions to simplified equations of tidal wave propagation in shallow waters, constrained by empirical knowledge of estuarine sedimentary dynamics and topography. The key controlling parameters of the model are bed friction (f), current velocity power of the erosion rate function (N), and sea-level rise rate. An assessment of sensitivity of the simulated sediment surface elevation (SSE) change to these controlling parameters was performed. The model predicted the spatial differentiation of accretion and erosion, the latter especially marked in the mudflats within mean sea level and low tide level and accretion was mainly in a subtidal channel. The average SSE change mutually depended on both the friction coefficient and power of the current velocity. Analysis of the average annual SSE change suggests that the state of intertidal and subtidal compartments of the estuarine system vary differently according to the dominant processes (erosion and accretion). As the Guadiana estuarine system shows dominant erosional behaviour in the context of sea-level rise and sediment supply reduction after the closure of the Alqueva Dam, the most plausible sets of parameter values for the Guadiana Estuary are N = 1.8 and f = 0.8f0, or N = 2 and f = f0, where f0 is the empirically estimated value. For these sets of parameter values, the relative errors in SSE change did not exceed ±20% in 73% of simulation cells in the studied area. Such a limit of accuracy can be acceptable for an idealized modelling of coastal evolution in response to uncertain sea-level rise scenarios in the context of reduced sediment supply due to flow regulation. Therefore, the idealized but cost

  4. Modeling urbanized watershed flood response changes with distributed hydrological model: key hydrological processes, parameterization and case studies

    Science.gov (United States)

    Chen, Y.

    2017-12-01

    Urbanization is the world development trend for the past century, and the developing countries have been experiencing much rapider urbanization in the past decades. Urbanization brings many benefits to human beings, but also causes negative impacts, such as increasing flood risk. Impact of urbanization on flood response has long been observed, but quantitatively studying this effect still faces great challenges. For example, setting up an appropriate hydrological model representing the changed flood responses and determining accurate model parameters are very difficult in the urbanized or urbanizing watershed. In the Pearl River Delta area, rapidest urbanization has been observed in China for the past decades, and dozens of highly urbanized watersheds have been appeared. In this study, a physically based distributed watershed hydrological model, the Liuxihe model is employed and revised to simulate the hydrological processes of the highly urbanized watershed flood in the Pearl River Delta area. A virtual soil type is then defined in the terrain properties dataset, and its runoff production and routing algorithms are added to the Liuxihe model. Based on a parameter sensitive analysis, the key hydrological processes of a highly urbanized watershed is proposed, that provides insight into the hydrological processes and for parameter optimization. Based on the above analysis, the model is set up in the Songmushan watershed where there is hydrological data observation. A model parameter optimization and updating strategy is proposed based on the remotely sensed LUC types, which optimizes model parameters with PSO algorithm and updates them based on the changed LUC types. The model parameters in Songmushan watershed are regionalized at the Pearl River Delta area watersheds based on the LUC types of the other watersheds. A dozen watersheds in the highly urbanized area of Dongguan City in the Pearl River Delta area were studied for the flood response changes due to

  5. MOLECULAR MODELLING OF HUMAN ALDEHYDE OXIDASE AND IDENTIFICATION OF THE KEY INTERACTIONS IN THE ENZYME-SUBSTRATE COMPLEX

    Directory of Open Access Journals (Sweden)

    Siavoush Dastmalchi

    2005-05-01

    Full Text Available Aldehyde oxidase (EC 1.2.3.1, a cytosolic enzyme containing FAD, molybdenum and iron-sulphur cluster, is a member of non-cytochrome P-450 enzymes called molybdenum hydroxylases which is involved in the metabolism of a wide range of endogenous compounds and many drug substances. Drug metabolism is one of the important characteristics which influences many aspects of a therapeutic agent such as routes of administration, drug interaction and toxicity and therefore, characterisation of the key interactions between enzymes and substrates is very important from drug development point of view. The aim of this study was to generate a three-dimensional model of human aldehyde oxidase (AO in order to assist us to identify the mode of interaction between enzyme and a set of phethalazine/quinazoline derivatives. Both sequence-based (BLAST and inverse protein fold recognition methods (THREADER were used to identify the crystal structure of bovine xanthine dehydrogenase (pdb code of 1FO4 as the suitable template for comparative modelling of human AO. Model structure was generated by aligning and then threading the sequence of human AO onto the template structure, incorporating the associated cofactors, and molecular dynamics simulations and energy minimization using GROMACS program. Different criteria which were measured by the PROCHECK, QPACK, VERIFY-3D were indicative of a proper fold for the predicted structural model of human AO. For example, 97.9 percentages of phi and psi angles were in the favoured and most favoured regions in the ramachandran plot, and all residues in the model are assigned environmentally positive compatibility scores. Further evaluation on the model quality was performed by investigation of AO-mediated oxidation of a set of phthalazine/quinazoline derivatives to develop QSAR model capable of describing the extent of the oxidation. Substrates were aligned by docking onto the active site of the enzyme using GOLD technology and then

  6. An effective automatic procedure for testing parameter identifiability of HIV/AIDS models.

    Science.gov (United States)

    Saccomani, Maria Pia

    2011-08-01

    Realistic HIV models tend to be rather complex and many recent models proposed in the literature could not yet be analyzed by traditional identifiability testing techniques. In this paper, we check a priori global identifiability of some of these nonlinear HIV models taken from the recent literature, by using a differential algebra algorithm based on previous work of the author. The algorithm is implemented in a software tool, called DAISY (Differential Algebra for Identifiability of SYstems), which has been recently released (DAISY is freely available on the web site http://www.dei.unipd.it/~pia/ ). The software can be used to automatically check global identifiability of (linear and) nonlinear models described by polynomial or rational differential equations, thus providing a general and reliable tool to test global identifiability of several HIV models proposed in the literature. It can be used by researchers with a minimum of mathematical background.

  7. A simple method for identifying parameter correlations in partially observed linear dynamic models.

    Science.gov (United States)

    Li, Pu; Vu, Quoc Dong

    2015-12-14

    Parameter estimation represents one of the most significant challenges in systems biology. This is because biological models commonly contain a large number of parameters among which there may be functional interrelationships, thus leading to the problem of non-identifiability. Although identifiability analysis has been extensively studied by analytical as well as numerical approaches, systematic methods for remedying practically non-identifiable models have rarely been investigated. We propose a simple method for identifying pairwise correlations and higher order interrelationships of parameters in partially observed linear dynamic models. This is made by derivation of the output sensitivity matrix and analysis of the linear dependencies of its columns. Consequently, analytical relations between the identifiability of the model parameters and the initial conditions as well as the input functions can be achieved. In the case of structural non-identifiability, identifiable combinations can be obtained by solving the resulting homogenous linear equations. In the case of practical non-identifiability, experiment conditions (i.e. initial condition and constant control signals) can be provided which are necessary for remedying the non-identifiability and unique parameter estimation. It is noted that the approach does not consider noisy data. In this way, the practical non-identifiability issue, which is popular for linear biological models, can be remedied. Several linear compartment models including an insulin receptor dynamics model are taken to illustrate the application of the proposed approach. Both structural and practical identifiability of partially observed linear dynamic models can be clarified by the proposed method. The result of this method provides important information for experimental design to remedy the practical non-identifiability if applicable. The derivation of the method is straightforward and thus the algorithm can be easily implemented into a

  8. Systemic Thinking and Requisite Holism in Mastering Logistics Risks: the Model for Identifying Risks in Organisations and Supply Chain

    Directory of Open Access Journals (Sweden)

    Bojan Rosi

    2013-02-01

    Full Text Available Risks in logistic processes represent one of the major issues in supply chain management nowadays. Every organization strives for success, and uninterrupted operations are the key factors in achieving this goal, which cannot be achieved without efficient risk management. In the scope of supply chain risk research, we identified some key issues in the field, the major issue being the lack of standardization and models, which can make risk management in an organization easier and more efficient. Consequently, we developed a model, which captures and identifies risks in an organization and its supply chain. It is in accordance with the general risk management standard – ISO 31000, and incorporates some relevant recent findings from general and supply chain risk management, especially from the viewpoint of public segmentation. This experimental catalogue (which is also published online can serve as a checklist and a starting point of supply chain risk management in organizations. Its main idea is cooperation between experts from the area in order to compile an ever-growing list of possible risks and to provide an insight in the model and its value in practice, for which reason input and opinions of anyone who uses our model are greatly appreciated and included in the catalogue.

  9. Identifiability in N-mixture models: a large-scale screening test with bird data.

    Science.gov (United States)

    Kéry, Marc

    2018-02-01

    Binomial N-mixture models have proven very useful in ecology, conservation, and monitoring: they allow estimation and modeling of abundance separately from detection probability using simple counts. Recently, doubts about parameter identifiability have been voiced. I conducted a large-scale screening test with 137 bird data sets from 2,037 sites. I found virtually no identifiability problems for Poisson and zero-inflated Poisson (ZIP) binomial N-mixture models, but negative-binomial (NB) models had problems in 25% of all data sets. The corresponding multinomial N-mixture models had no problems. Parameter estimates under Poisson and ZIP binomial and multinomial N-mixture models were extremely similar. Identifiability problems became a little more frequent with smaller sample sizes (267 and 50 sites), but were unaffected by whether the models did or did not include covariates. Hence, binomial N-mixture model parameters with Poisson and ZIP mixtures typically appeared identifiable. In contrast, NB mixtures were often unidentifiable, which is worrying since these were often selected by Akaike's information criterion. Identifiability of binomial N-mixture models should always be checked. If problems are found, simpler models, integrated models that combine different observation models or the use of external information via informative priors or penalized likelihoods, may help. © 2017 by the Ecological Society of America.

  10. A mouse model of harlequin ichthyosis delineates a key role for Abca12 in lipid homeostasis.

    Directory of Open Access Journals (Sweden)

    Ian Smyth

    2008-09-01

    Full Text Available Harlequin Ichthyosis (HI is a severe and often lethal hyperkeratotic skin disease caused by mutations in the ABCA12 transport protein. In keratinocytes, ABCA12 is thought to regulate the transfer of lipids into small intracellular trafficking vesicles known as lamellar bodies. However, the nature and scope of this regulation remains unclear. As part of an original recessive mouse ENU mutagenesis screen, we have identified and characterised an animal model of HI and showed that it displays many of the hallmarks of the disease including hyperkeratosis, loss of barrier function, and defects in lipid homeostasis. We have used this model to follow disease progression in utero and present evidence that loss of Abca12 function leads to premature differentiation of basal keratinocytes. A comprehensive analysis of lipid levels in mutant epidermis demonstrated profound defects in lipid homeostasis, illustrating for the first time the extent to which Abca12 plays a pivotal role in maintaining lipid balance in the skin. To further investigate the scope of Abca12's activity, we have utilised cells from the mutant mouse to ascribe direct transport functions to the protein and, in doing so, we demonstrate activities independent of its role in lamellar body function. These cells have severely impaired lipid efflux leading to intracellular accumulation of neutral lipids. Furthermore, we identify Abca12 as a mediator of Abca1-regulated cellular cholesterol efflux, a finding that may have significant implications for other diseases of lipid metabolism and homeostasis, including atherosclerosis.

  11. Estimation of Key Parameters of the Coupled Energy and Water Model by Assimilating Land Surface Data

    Science.gov (United States)

    Abdolghafoorian, A.; Farhadi, L.

    2017-12-01

    Accurate estimation of land surface heat and moisture fluxes, as well as root zone soil moisture, is crucial in various hydrological, meteorological, and agricultural applications. Field measurements of these fluxes are costly and cannot be readily scaled to large areas relevant to weather and climate studies. Therefore, there is a need for techniques to make quantitative estimates of heat and moisture fluxes using land surface state observations that are widely available from remote sensing across a range of scale. In this work, we applies the variational data assimilation approach to estimate land surface fluxes and soil moisture profile from the implicit information contained Land Surface Temperature (LST) and Soil Moisture (SM) (hereafter the VDA model). The VDA model is focused on the estimation of three key parameters: 1- neutral bulk heat transfer coefficient (CHN), 2- evaporative fraction from soil and canopy (EF), and 3- saturated hydraulic conductivity (Ksat). CHN and EF regulate the partitioning of available energy between sensible and latent heat fluxes. Ksat is one of the main parameters used in determining infiltration, runoff, groundwater recharge, and in simulating hydrological processes. In this study, a system of coupled parsimonious energy and water model will constrain the estimation of three unknown parameters in the VDA model. The profile of SM (LST) at multiple depths is estimated using moisture diffusion (heat diffusion) equation. In this study, the uncertainties of retrieved unknown parameters and fluxes are estimated from the inverse of Hesian matrix of cost function which is computed using the Lagrangian methodology. Analysis of uncertainty provides valuable information about the accuracy of estimated parameters and their correlation and guide the formulation of a well-posed estimation problem. The results of proposed algorithm are validated with a series of experiments using a synthetic data set generated by the simultaneous heat and

  12. A Public-key based Information Management Model for Mobile Agents

    OpenAIRE

    Rodriguez, Diego; Sobrado, Igor

    2000-01-01

    Mobile code based computing requires development of protection schemes that allow digital signature and encryption of data collected by the agents in untrusted hosts. These algorithms could not rely on carrying encryption keys if these keys could be stolen or used to counterfeit data by hostile hosts and agents. As a consequence, both information and keys must be protected in a way that only authorized hosts, that is the host that provides information and the server that has sent the mobile a...

  13. Phenotypic Screening Identifies Modulators of Amyloid Precursor Protein Processing in Human Stem Cell Models of Alzheimer’s Disease

    Directory of Open Access Journals (Sweden)

    Philip W. Brownjohn

    2017-04-01

    Full Text Available Summary: Human stem cell models have the potential to provide platforms for phenotypic screens to identify candidate treatments and cellular pathways involved in the pathogenesis of neurodegenerative disorders. Amyloid precursor protein (APP processing and the accumulation of APP-derived amyloid β (Aβ peptides are key processes in Alzheimer's disease (AD. We designed a phenotypic small-molecule screen to identify modulators of APP processing in trisomy 21/Down syndrome neurons, a complex genetic model of AD. We identified the avermectins, commonly used as anthelmintics, as compounds that increase the relative production of short Aβ peptides at the expense of longer, potentially more toxic peptides. Further studies demonstrated that this effect is not due to an interaction with the core γ-secretase responsible for Aβ production. This study demonstrates the feasibility of phenotypic drug screening in human stem cell models of Alzheimer-type dementia, and points to possibilities for indirectly modulating APP processing, independently of γ-secretase modulation. : In this article, Livesey and colleagues perform a phenotypic drug screen in a human stem cell model of Alzheimer's disease. The anthelminthic avermectins are identified as a family of compounds that increase the production of short Aβ peptides over longer more toxic Aβ forms. The effect is analogous to existing γ-secretase modulators, but is independent of the core γ-secretase complex. Keywords: neural stem cells, Alzheimer's disease, phenotypic screening, iPSCs, human neurons, dementia, Down syndrome, amyloid beta, ivermectin, selamectin

  14. Bayesian inference for partially identified models exploring the limits of limited data

    CERN Document Server

    Gustafson, Paul

    2015-01-01

    Introduction Identification What Is against Us? What Is for Us? Some Simple Examples of Partially Identified ModelsThe Road Ahead The Structure of Inference in Partially Identified Models Bayesian Inference The Structure of Posterior Distributions in PIMs Computational Strategies Strength of Bayesian Updating, Revisited Posterior MomentsCredible Intervals Evaluating the Worth of Inference Partial Identification versus Model Misspecification The Siren Call of Identification Comp

  15. Modelling management process of key drivers for economic sustainability in the modern conditions of economic development

    Directory of Open Access Journals (Sweden)

    Pishchulina E.S.

    2017-01-01

    Full Text Available The text is about issues concerning the management of driver for manufacturing enterprise economic sustainability and manufacturing enterprise sustainability assessment as the key aspect of the management of enterprise economic sustainability. The given issues become topical as new requirements for the methods of manufacturing enterprise management in the modern conditions of market economy occur. An economic sustainability model that is considered in the article is an integration of enterprise economic growth, economic balance of external and internal environment and economic sustainability. The method of assessment of economic sustainability of a manufacturing enterprise proposed in the study allows to reveal some weaknesses in the enterprise performance, and untapped reserves, which can be further used to improve the economic sustainability and efficiency of the enterprise. The management of manufacturing enterprise economic sustainability is one of the most important factors of business functioning and development in modern market economy. The relevance of this trend is increasing in accordance with the objective requirements of the growing volumes of production and sale, the increasing complexity of economic relations, changing external environment of an enterprise.

  16. iPSC-Based Models to Unravel Key Pathogenetic Processes Underlying Motor Neuron Disease Development

    Directory of Open Access Journals (Sweden)

    Irene Faravelli

    2014-10-01

    Full Text Available Motor neuron diseases (MNDs are neuromuscular disorders affecting rather exclusively upper motor neurons (UMNs and/or lower motor neurons (LMNs. The clinical phenotype is characterized by muscular weakness and atrophy leading to paralysis and almost invariably death due to respiratory failure. Adult MNDs include sporadic and familial amyotrophic lateral sclerosis (sALS-fALS, while the most common infantile MND is represented by spinal muscular atrophy (SMA. No effective treatment is ccurrently available for MNDs, as for the vast majority of neurodegenerative disorders, and cures are limited to supportive care and symptom relief. The lack of a deep understanding of MND pathogenesis accounts for the difficulties in finding a cure, together with the scarcity of reliable in vitro models. Recent progresses in stem cell field, in particular in the generation of induced Pluripotent Stem Cells (iPSCs has made possible for the first time obtaining substantial amounts of human cells to recapitulate in vitro some of the key pathogenetic processes underlying MNDs. In the present review, recently published studies involving the use of iPSCs to unravel aspects of ALS and SMA pathogenesis are discussed with an overview of their implications in the process of finding a cure for these still orphan disorders.

  17. Tuning and Test of Fragmentation Models Based on Identified Particles and Precision Event Shape Data

    CERN Document Server

    Abreu, P; Adye, T; Ajinenko, I; Alekseev, G D; Alemany, R; Allport, P P; Almehed, S; Amaldi, Ugo; Amato, S; Andreazza, A; Andrieux, M L; Antilogus, P; Apel, W D; Åsman, B; Augustin, J E; Augustinus, A; Baillon, Paul; Bambade, P; Barão, F; Barate, R; Barbi, M S; Bardin, Dimitri Yuri; Baroncelli, A; Bärring, O; Barrio, J A; Bartl, Walter; Bates, M J; Battaglia, Marco; Baubillier, M; Baudot, J; Becks, K H; Begalli, M; Beillière, P; Belokopytov, Yu A; Belous, K S; Benvenuti, Alberto C; Berggren, M; Bertini, D; Bertrand, D; Besançon, M; Bianchi, F; Bigi, M; Bilenky, S M; Billoir, P; Bloch, D; Blume, M; Bolognese, T; Bonesini, M; Bonivento, W; Booth, P S L; Bosio, C; Botner, O; Boudinov, E; Bouquet, B; Bourdarios, C; Bowcock, T J V; Bozzo, M; Branchini, P; Brand, K D; Brenke, T; Brenner, R A; Bricman, C; Brown, R C A; Brückman, P; Brunet, J M; Bugge, L; Buran, T; Burgsmüller, T; Buschmann, P; Buys, A; Cabrera, S; Caccia, M; Calvi, M; Camacho-Rozas, A J; Camporesi, T; Canale, V; Canepa, M; Cankocak, K; Cao, F; Carena, F; Carroll, L; Caso, Carlo; Castillo-Gimenez, M V; Cattai, A; Cavallo, F R; Chabaud, V; Charpentier, P; Chaussard, L; Checchia, P; Chelkov, G A; Chen, M; Chierici, R; Chliapnikov, P V; Chochula, P; Chorowicz, V; Chudoba, J; Cindro, V; Collins, P; Contreras, J L; Contri, R; Cortina, E; Cosme, G; Cossutti, F; Cowell, J H; Crawley, H B; Crennell, D J; Crosetti, G; Cuevas-Maestro, J; Czellar, S; Dahl-Jensen, Erik; Dahm, J; D'Almagne, B; Dam, M; Damgaard, G; Dauncey, P D; Davenport, Martyn; Da Silva, W; Defoix, C; Deghorain, A; Della Ricca, G; Delpierre, P A; Demaria, N; De Angelis, A; de Boer, Wim; De Brabandere, S; De Clercq, C; La Vaissière, C de; De Lotto, B; De Min, A; De Paula, L S; De Saint-Jean, C; Dijkstra, H; Di Ciaccio, Lucia; Di Diodato, A; Djama, F; Dolbeau, J; Dönszelmann, M; Doroba, K; Dracos, M; Drees, J; Drees, K A; Dris, M; Durand, J D; Edsall, D M; Ehret, R; Eigen, G; Ekelöf, T J C; Ekspong, Gösta; Elsing, M; Engel, J P; Erzen, B; Espirito-Santo, M C; Falk, E; Fassouliotis, D; Feindt, Michael; Ferrer, A; Fichet, S; Filippas-Tassos, A; Firestone, A; Fischer, P A; Föth, H; Fokitis, E; Fontanelli, F; Formenti, F; Franek, B J; Frenkiel, P; Fries, D E C; Frodesen, A G; Frühwirth, R; Fulda-Quenzer, F; Fuster, J A; Galloni, A; Gamba, D; Gandelman, M; García, C; García, J; Gaspar, C; Gasparini, U; Gavillet, P; Gazis, E N; Gelé, D; Gerber, J P; Gokieli, R; Golob, B; Gopal, Gian P; Gorn, L; Górski, M; Guz, Yu; Gracco, Valerio; Graziani, E; Green, C; Grefrath, A; Gris, P; Grosdidier, G; Grzelak, K; Gumenyuk, S A; Gunnarsson, P; Günther, M; Guy, J; Hahn, F; Hahn, S; Hajduk, Z; Hallgren, A; Hamacher, K; Harris, F J; Hedberg, V; Henriques, R P; Hernández, J J; Herquet, P; Herr, H; Hessing, T L; Higón, E; Hilke, Hans Jürgen; Hill, T S; Holmgren, S O; Holt, P J; Holthuizen, D J; Hoorelbeke, S; Houlden, M A; Hrubec, Josef; Huet, K; Hultqvist, K; Jackson, J N; Jacobsson, R; Jalocha, P; Janik, R; Jarlskog, C; Jarlskog, G; Jarry, P; Jean-Marie, B; Johansson, E K; Jönsson, L B; Jönsson, P E; Joram, Christian; Juillot, P; Kaiser, M; Kapusta, F; Karafasoulis, K; Karlsson, M; Karvelas, E; Katsanevas, S; Katsoufis, E C; Keränen, R; Khokhlov, Yu A; Khomenko, B A; Khovanskii, N N; King, B J; Kjaer, N J; Klapp, O; Klein, H; Klovning, A; Kluit, P M; Köne, B; Kokkinias, P; Koratzinos, M; Korcyl, K; Kostyukhin, V; Kourkoumelis, C; Kuznetsov, O; Kreuter, C; Kronkvist, I J; Krumshtein, Z; Krupinski, W; Kubinec, P; Kucewicz, W; Kurvinen, K L; Lacasta, C; Laktineh, I; Lamsa, J; Lanceri, L; Lane, D W; Langefeld, P; Lapin, V; Laugier, J P; Lauhakangas, R; Leder, Gerhard; Ledroit, F; Lefébure, V; Legan, C K; Leitner, R; Lemonne, J; Lenzen, Georg; Lepeltier, V; Lesiak, T; Libby, J; Liko, D; Lindner, R; Lipniacka, A; Lippi, I; Lörstad, B; Loken, J G; López, J M; Loukas, D; Lutz, P; Lyons, L; Naughton, J M; Maehlum, G; Mahon, J R; Maio, A; Malmgren, T G M; Malychev, V; Mandl, F; Marco, J; Marco, R P; Maréchal, B; Margoni, M; Marin, J C; Mariotti, C; Markou, A; Martínez-Rivero, C; Martínez-Vidal, F; Martí i García, S; Masik, J; Matorras, F; Matteuzzi, C; Matthiae, Giorgio; Mazzucato, M; McCubbin, M L; McKay, R; McNulty, R; Medbo, J; Merk, M; Meroni, C; Meyer, S; Meyer, W T; Myagkov, A; Michelotto, M; Migliore, E; Mirabito, L; Mitaroff, Winfried A; Mjörnmark, U; Moa, T; Møller, R; Mönig, K; Monge, M R; Morettini, P; Müller, H; Mulders, M; Mundim, L M; Murray, W J; Muryn, B; Myatt, Gerald; Naraghi, F; Navarria, Francesco Luigi; Navas, S; Nawrocki, K; Negri, P; Neumann, W; Neumeister, N; Nicolaidou, R; Nielsen, B S; Nieuwenhuizen, M; Nikolaenko, V; Niss, P; Nomerotski, A; Normand, Ainsley; Oberschulte-Beckmann, W; Obraztsov, V F; Olshevskii, A G; Onofre, A; Orava, Risto; Österberg, K; Ouraou, A; Paganini, P; Paganoni, M; Pagès, P; Pain, R; Palka, H; Papadopoulou, T D; Papageorgiou, K; Pape, L; Parkes, C; Parodi, F; Passeri, A; Pegoraro, M; Peralta, L; Pernegger, H; Pernicka, Manfred; Perrotta, A; Petridou, C; Petrolini, A; Petrovykh, M; Phillips, H T; Piana, G; Pierre, F; Plaszczynski, S; Podobrin, O; Pol, M E; Polok, G; Poropat, P; Pozdnyakov, V; Privitera, P; Pukhaeva, N; Pullia, Antonio; Radojicic, D; Ragazzi, S; Rahmani, H; Rames, J; Ratoff, P N; Read, A L; Reale, M; Rebecchi, P; Redaelli, N G; Regler, Meinhard; Reid, D; Renton, P B; Resvanis, L K; Richard, F; Richardson, J; Rídky, J; Rinaudo, G; Ripp, I; Romero, A; Roncagliolo, I; Ronchese, P; Roos, L; Rosenberg, E I; Rosso, E; Roudeau, Patrick; Rovelli, T; Rückstuhl, W; Ruhlmann-Kleider, V; Ruiz, A; Rybicki, K; Saarikko, H; Sacquin, Yu; Sadovskii, A; Sahr, O; Sajot, G; Salt, J; Sánchez, J; Sannino, M; Schimmelpfennig, M; Schneider, H; Schwickerath, U; Schyns, M A E; Sciolla, G; Scuri, F; Seager, P; Sedykh, Yu; Segar, A M; Seitz, A; Sekulin, R L; Serbelloni, L; Shellard, R C; Siegrist, P; Silvestre, R; Simonetti, S; Simonetto, F; Sissakian, A N; Sitár, B; Skaali, T B; Smadja, G; Smirnov, N; Smirnova, O G; Smith, G R; Sokolov, A; Sosnowski, R; Souza-Santos, D; Spassoff, Tz; Spiriti, E; Sponholz, P; Squarcia, S; Stanescu, C; Stapnes, Steinar; Stavitski, I; Stevenson, K; Stichelbaut, F; Stocchi, A; Strauss, J; Strub, R; Stugu, B; Szczekowski, M; Szeptycka, M; Tabarelli de Fatis, T; Tavernet, J P; Chikilev, O G; Thomas, J; Tilquin, A; Timmermans, J; Tkatchev, L G; Todorov, T; Todorova, S; Toet, D Z; Tomaradze, A G; Tomé, B; Tonazzo, A; Tortora, L; Tranströmer, G; Treille, D; Trischuk, W; Tristram, G; Trombini, A; Troncon, C; Tsirou, A L; Turluer, M L; Tyapkin, I A; Tyndel, M; Tzamarias, S; Überschär, B; Ullaland, O; Uvarov, V; Valenti, G; Vallazza, E; van Apeldoorn, G W; van Dam, P; Van Eldik, J; Vassilopoulos, N; Vegni, G; Ventura, L; Venus, W A; Verbeure, F; Verlato, M; Vertogradov, L S; Vilanova, D; Vincent, P; Vitale, L; Vlasov, E; Vodopyanov, A S; Vrba, V; Wahlen, H; Walck, C; Waldner, F; Weierstall, M; Weilhammer, Peter; Weiser, C; Wetherell, Alan M; Wicke, D; Wickens, J H; Wielers, M; Wilkinson, G R; Williams, W S C; Winter, M; Witek, M; Woschnagg, K; Yip, K; Yushchenko, O P; Zach, F; Zaitsev, A; Zalewska-Bak, A; Zalewski, Piotr; Zavrtanik, D; Zevgolatakos, E; Zimin, N I; Zito, M; Zontar, D; Zucchelli, G C; Zumerle, G

    1996-01-01

    Event shape and charged particle inclusive distributions are measured using 750000 decays of the $Z$ to hadrons from the DELPHI detector at LEP. These precise data allow a decisive confrontation with models of the hadronization process. Improved tunings of the JETSET ARIADNE and HERWIG parton shower models and the JETSET matrix element model are obtained by fitting the models to these DELPHI data as well as to identified particle distributions from all LEP experiments. The description of the data distributions by the models is critically reviewed with special importance attributed to identified particles.

  18. Maximum Key Size and Classification Performance of Fuzzy Commitment for Gaussian Modeled Biometric Sources

    NARCIS (Netherlands)

    Kelkboom, E.J.C.; Breebaart, J.; Buhan, I.R.; Veldhuis, Raymond N.J.

    Template protection techniques are used within biometric systems in order to protect the stored biometric template against privacy and security threats. A great portion of template protection techniques are based on extracting a key from, or binding a key to the binary vector derived from the

  19. Analytical template protection performance and maximum key size given a Gaussian-modeled biometric source

    NARCIS (Netherlands)

    Kelkboom, E.J.C.; Breebaart, Jeroen; Buhan, I.R.; Veldhuis, Raymond N.J.; Vijaya Kumar, B.V.K.; Prabhakar, Salil; Ross, Arun A.

    2010-01-01

    Template protection techniques are used within biometric systems in order to protect the stored biometric template against privacy and security threats. A great portion of template protection techniques are based on extracting a key from or binding a key to a biometric sample. The achieved

  20. A Hybrid Network Model to Extract Key Criteria and Its Application for Brand Equity Evaluation

    Directory of Open Access Journals (Sweden)

    Chin-Yi Chen

    2012-01-01

    Full Text Available Making a decision implies that there are alternative choices to be considered, and a major challenge of decision-making is to identify the adequate criteria for program planning or problem evaluation. The decision-makers’ criteria consists of the characteristics or requirements each alternative must possess and the alternatives are rated on how well they possess each criterion. We often use criteria developed and used by different researchers and institutions, and these criteria have similar means and can be substituted for one another. Choosing from existing criteria offers a practical method to engineers hoping to derive a set of criteria for evaluating objects or programs. We have developed a hybrid model for extracting evaluation criteria which considers substitutions between the criteria. The model is developed based on Social Network Analysis and Maximum Mean De-Entropy algorithms. In this paper, the introduced methodology will also be applied to analyze the criteria for assessing brand equity as an application example. The proposed model demonstrates that it is useful in planning feasibility criteria and has applications in other evaluation-planning purposes.

  1. Statistical identifiability and convergence evaluation for nonlinear pharmacokinetic models with particle swarm optimization.

    Science.gov (United States)

    Kim, Seongho; Li, Lang

    2014-02-01

    The statistical identifiability of nonlinear pharmacokinetic (PK) models with the Michaelis-Menten (MM) kinetic equation is considered using a global optimization approach, which is particle swarm optimization (PSO). If a model is statistically non-identifiable, the conventional derivative-based estimation approach is often terminated earlier without converging, due to the singularity. To circumvent this difficulty, we develop a derivative-free global optimization algorithm by combining PSO with a derivative-free local optimization algorithm to improve the rate of convergence of PSO. We further propose an efficient approach to not only checking the convergence of estimation but also detecting the identifiability of nonlinear PK models. PK simulation studies demonstrate that the convergence and identifiability of the PK model can be detected efficiently through the proposed approach. The proposed approach is then applied to clinical PK data along with a two-compartmental model. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  2. Identifying Ghanaian Pre-Service Teachers' Readiness for Computer Use: A Technology Acceptance Model Approach

    Science.gov (United States)

    Gyamfi, Stephen Adu

    2016-01-01

    This study extends the technology acceptance model to identify factors that influence technology acceptance among pre-service teachers in Ghana. Data from 380 usable questionnaires were tested against the research model. Utilising the extended technology acceptance model (TAM) as a research framework, the study found that: pre-service teachers'…

  3. Protein-protein interaction networks identify targets which rescue the MPP+ cellular model of Parkinson’s disease

    Science.gov (United States)

    Keane, Harriet; Ryan, Brent J.; Jackson, Brendan; Whitmore, Alan; Wade-Martins, Richard

    2015-11-01

    Neurodegenerative diseases are complex multifactorial disorders characterised by the interplay of many dysregulated physiological processes. As an exemplar, Parkinson’s disease (PD) involves multiple perturbed cellular functions, including mitochondrial dysfunction and autophagic dysregulation in preferentially-sensitive dopamine neurons, a selective pathophysiology recapitulated in vitro using the neurotoxin MPP+. Here we explore a network science approach for the selection of therapeutic protein targets in the cellular MPP+ model. We hypothesised that analysis of protein-protein interaction networks modelling MPP+ toxicity could identify proteins critical for mediating MPP+ toxicity. Analysis of protein-protein interaction networks constructed to model the interplay of mitochondrial dysfunction and autophagic dysregulation (key aspects of MPP+ toxicity) enabled us to identify four proteins predicted to be key for MPP+ toxicity (P62, GABARAP, GBRL1 and GBRL2). Combined, but not individual, knockdown of these proteins increased cellular susceptibility to MPP+ toxicity. Conversely, combined, but not individual, over-expression of the network targets provided rescue of MPP+ toxicity associated with the formation of autophagosome-like structures. We also found that modulation of two distinct proteins in the protein-protein interaction network was necessary and sufficient to mitigate neurotoxicity. Together, these findings validate our network science approach to multi-target identification in complex neurological diseases.

  4. A new discrete dynamic model of ABA-induced stomatal closure predicts key feedback loops.

    Directory of Open Access Journals (Sweden)

    Réka Albert

    2017-09-01

    Full Text Available Stomata, microscopic pores in leaf surfaces through which water loss and carbon dioxide uptake occur, are closed in response to drought by the phytohormone abscisic acid (ABA. This process is vital for drought tolerance and has been the topic of extensive experimental investigation in the last decades. Although a core signaling chain has been elucidated consisting of ABA binding to receptors, which alleviates negative regulation by protein phosphatases 2C (PP2Cs of the protein kinase OPEN STOMATA 1 (OST1 and ultimately results in activation of anion channels, osmotic water loss, and stomatal closure, over 70 additional components have been identified, yet their relationships with each other and the core components are poorly elucidated. We integrated and processed hundreds of disparate observations regarding ABA signal transduction responses underlying stomatal closure into a network of 84 nodes and 156 edges and, as a result, established those relationships, including identification of a 36-node, strongly connected (feedback-rich component as well as its in- and out-components. The network's domination by a feedback-rich component may reflect a general feature of rapid signaling events. We developed a discrete dynamic model of this network and elucidated the effects of ABA plus knockout or constitutive activity of 79 nodes on both the outcome of the system (closure and the status of all internal nodes. The model, with more than 1024 system states, is far from fully determined by the available data, yet model results agree with existing experiments in 82 cases and disagree in only 17 cases, a validation rate of 75%. Our results reveal nodes that could be engineered to impact stomatal closure in a controlled fashion and also provide over 140 novel predictions for which experimental data are currently lacking. Noting the paucity of wet-bench data regarding combinatorial effects of ABA and internal node activation, we experimentally confirmed

  5. A new discrete dynamic model of ABA-induced stomatal closure predicts key feedback loops.

    Science.gov (United States)

    Albert, Réka; Acharya, Biswa R; Jeon, Byeong Wook; Zañudo, Jorge G T; Zhu, Mengmeng; Osman, Karim; Assmann, Sarah M

    2017-09-01

    Stomata, microscopic pores in leaf surfaces through which water loss and carbon dioxide uptake occur, are closed in response to drought by the phytohormone abscisic acid (ABA). This process is vital for drought tolerance and has been the topic of extensive experimental investigation in the last decades. Although a core signaling chain has been elucidated consisting of ABA binding to receptors, which alleviates negative regulation by protein phosphatases 2C (PP2Cs) of the protein kinase OPEN STOMATA 1 (OST1) and ultimately results in activation of anion channels, osmotic water loss, and stomatal closure, over 70 additional components have been identified, yet their relationships with each other and the core components are poorly elucidated. We integrated and processed hundreds of disparate observations regarding ABA signal transduction responses underlying stomatal closure into a network of 84 nodes and 156 edges and, as a result, established those relationships, including identification of a 36-node, strongly connected (feedback-rich) component as well as its in- and out-components. The network's domination by a feedback-rich component may reflect a general feature of rapid signaling events. We developed a discrete dynamic model of this network and elucidated the effects of ABA plus knockout or constitutive activity of 79 nodes on both the outcome of the system (closure) and the status of all internal nodes. The model, with more than 1024 system states, is far from fully determined by the available data, yet model results agree with existing experiments in 82 cases and disagree in only 17 cases, a validation rate of 75%. Our results reveal nodes that could be engineered to impact stomatal closure in a controlled fashion and also provide over 140 novel predictions for which experimental data are currently lacking. Noting the paucity of wet-bench data regarding combinatorial effects of ABA and internal node activation, we experimentally confirmed several predictions

  6. Advanced computational biology methods identify molecular switches for malignancy in an EGF mouse model of liver cancer.

    Directory of Open Access Journals (Sweden)

    Philip Stegmaier

    Full Text Available The molecular causes by which the epidermal growth factor receptor tyrosine kinase induces malignant transformation are largely unknown. To better understand EGFs' transforming capacity whole genome scans were applied to a transgenic mouse model of liver cancer and subjected to advanced methods of computational analysis to construct de novo gene regulatory networks based on a combination of sequence analysis and entrained graph-topological algorithms. Here we identified transcription factors, processes, key nodes and molecules to connect as yet unknown interacting partners at the level of protein-DNA interaction. Many of those could be confirmed by electromobility band shift assay at recognition sites of gene specific promoters and by western blotting of nuclear proteins. A novel cellular regulatory circuitry could therefore be proposed that connects cell cycle regulated genes with components of the EGF signaling pathway. Promoter analysis of differentially expressed genes suggested the majority of regulated transcription factors to display specificity to either the pre-tumor or the tumor state. Subsequent search for signal transduction key nodes upstream of the identified transcription factors and their targets suggested the insulin-like growth factor pathway to render the tumor cells independent of EGF receptor activity. Notably, expression of IGF2 in addition to many components of this pathway was highly upregulated in tumors. Together, we propose a switch in autocrine signaling to foster tumor growth that was initially triggered by EGF and demonstrate the knowledge gain form promoter analysis combined with upstream key node identification.

  7. From conceptual model to remediation: bioavailability, a key to clean up heavy metal contaminated soils.

    Science.gov (United States)

    Petruzzelli, Gianniantonio; Pedron, Francesca; Pezzarossa, Beatrice

    2013-04-01

    that aim to increase the bioavailability of pollutants are used in technologies which remove or destroy the solubilized contaminants. These procedures can increase mass transfer from the absorbed phase by means of sieving in order to decrease the diffusion processes (soil washing), by increasing the temperature (low temperature thermal desorption), or through the addition of chemical additives, such as chelating agents (Phytoextraction Elektrokinetic remediation). Concluding remarks Bioavailability should be a key component of the exposure evaluation in order to develop the conceptual model and to select the technology, in particular when: • only some chemical forms of contaminants are a source of risk for the site; • default assumptions regarding bioavailability are not suitable because of the site's specific characteristics; • the final destination of the site will not be modified at least in the near future.

  8. Key Factors Influencing the Energy Absorption of Dual-Phase Steels: Multiscale Material Model Approach and Microstructural Optimization

    Science.gov (United States)

    Belgasam, Tarek M.; Zbib, Hussein M.

    2018-06-01

    The increase in use of dual-phase (DP) steel grades by vehicle manufacturers to enhance crash resistance and reduce body car weight requires the development of a clear understanding of the effect of various microstructural parameters on the energy absorption in these materials. Accordingly, DP steelmakers are interested in predicting the effect of various microscopic factors as well as optimizing microstructural properties for application in crash-relevant components of vehicle bodies. This study presents a microstructure-based approach using a multiscale material and structure model. In this approach, Digimat and LS-DYNA software were coupled and employed to provide a full micro-macro multiscale material model, which is then used to simulate tensile tests. Microstructures with varied ferrite grain sizes, martensite volume fractions, and carbon content in DP steels were studied. The impact of these microstructural features at different strain rates on energy absorption characteristics of DP steels is investigated numerically using an elasto-viscoplastic constitutive model. The model is implemented in a multiscale finite-element framework. A comprehensive statistical parametric study using response surface methodology is performed to determine the optimum microstructural features for a required tensile toughness at different strain rates. The simulation results are validated using experimental data found in the literature. The developed methodology proved to be effective for investigating the influence and interaction of key microscopic properties on the energy absorption characteristics of DP steels. Furthermore, it is shown that this method can be used to identify optimum microstructural conditions at different strain-rate conditions.

  9. Review: To be or not to be an identifiable model. Is this a relevant question in animal science modelling?

    Science.gov (United States)

    Muñoz-Tamayo, R; Puillet, L; Daniel, J B; Sauvant, D; Martin, O; Taghipoor, M; Blavy, P

    2018-04-01

    What is a good (useful) mathematical model in animal science? For models constructed for prediction purposes, the question of model adequacy (usefulness) has been traditionally tackled by statistical analysis applied to observed experimental data relative to model-predicted variables. However, little attention has been paid to analytic tools that exploit the mathematical properties of the model equations. For example, in the context of model calibration, before attempting a numerical estimation of the model parameters, we might want to know if we have any chance of success in estimating a unique best value of the model parameters from available measurements. This question of uniqueness is referred to as structural identifiability; a mathematical property that is defined on the sole basis of the model structure within a hypothetical ideal experiment determined by a setting of model inputs (stimuli) and observable variables (measurements). Structural identifiability analysis applied to dynamic models described by ordinary differential equations (ODEs) is a common practice in control engineering and system identification. This analysis demands mathematical technicalities that are beyond the academic background of animal science, which might explain the lack of pervasiveness of identifiability analysis in animal science modelling. To fill this gap, in this paper we address the analysis of structural identifiability from a practitioner perspective by capitalizing on the use of dedicated software tools. Our objectives are (i) to provide a comprehensive explanation of the structural identifiability notion for the community of animal science modelling, (ii) to assess the relevance of identifiability analysis in animal science modelling and (iii) to motivate the community to use identifiability analysis in the modelling practice (when the identifiability question is relevant). We focus our study on ODE models. By using illustrative examples that include published

  10. Extending existing structural identifiability analysis methods to mixed-effects models.

    Science.gov (United States)

    Janzén, David L I; Jirstrand, Mats; Chappell, Michael J; Evans, Neil D

    2018-01-01

    The concept of structural identifiability for state-space models is expanded to cover mixed-effects state-space models. Two methods applicable for the analytical study of the structural identifiability of mixed-effects models are presented. The two methods are based on previously established techniques for non-mixed-effects models; namely the Taylor series expansion and the input-output form approach. By generating an exhaustive summary, and by assuming an infinite number of subjects, functions of random variables can be derived which in turn determine the distribution of the system's observation function(s). By considering the uniqueness of the analytical statistical moments of the derived functions of the random variables, the structural identifiability of the corresponding mixed-effects model can be determined. The two methods are applied to a set of examples of mixed-effects models to illustrate how they work in practice. Copyright © 2017 Elsevier Inc. All rights reserved.

  11. Use of gas chromatography-olfactometry to identify key odorant compounds in dark chocolate. Comparison of samples before and after conching.

    Science.gov (United States)

    Counet, Christine; Callemien, Delphine; Ouwerx, Caroline; Collin, Sonia

    2002-04-10

    After vacuum distillation and liquid-liquid extraction, the volatile fractions of dark chocolates were analyzed by gas chromatography-olfactometry and gas chromatography-mass spectrometry. Aroma extract dilution analysis revealed the presence of 33 potent odorants in the neutral/basic fraction. Three of these had a strong chocolate flavor: 2-methylpropanal, 2-methylbutanal, and 3-methylbutanal. Many others were characterized by cocoa/praline-flavored/nutty/coffee notes: 2,3-dimethylpyrazine, trimethylpyrazine, tetramethylpyrazine, 3(or 2),5-dimethyl-2(or 3)-ethylpyrazine, 3,5(or 6)-diethyl-2-methylpyrazine, and furfurylpyrrole. Comparisons carried out before and after conching indicate that although no new key odorant is synthesized during the heating process, levels of 2-phenyl-5-methyl-2-hexenal, Furaneol, and branched pyrazines are significantly increased while most Strecker aldehydes are lost by evaporation.

  12. Identifying and Supporting English Learner Students with Learning Disabilities: Key Issues in the Literature and State Practice. REL 2015-086

    Science.gov (United States)

    Burr, Elizabeth; Haas, Eric; Ferriere, Karen

    2015-01-01

    While the literature on learning disabilities and on second-language acquisition is relatively extensive within the field of education, less is known about the specific characteristics and representation of English learner students with learning disabilities. Because there are no definitive resources and processes for identifying and determining…

  13. Cadmium-induced immune abnormality is a key pathogenic event in human and rat models of preeclampsia.

    Science.gov (United States)

    Zhang, Qiong; Huang, Yinping; Zhang, Keke; Huang, Yanjun; Yan, Yan; Wang, Fan; Wu, Jie; Wang, Xiao; Xu, Zhangye; Chen, Yongtao; Cheng, Xue; Li, Yong; Jiao, Jinyu; Ye, Duyun

    2016-11-01

    With increased industrial development, cadmium is an increasingly important environmental pollutant. Studies have identified various adverse effects of cadmium on human beings. However, the relationships between cadmium pollution and the pathogenesis of preeclampsia remain elusive. The objective of this study is to explore the effects of cadmium on immune system among preeclamptic patients and rats. The results showed that the cadmium levels in the peripheral blood of preeclamptic patients were significantly higher than those observed in normal pregnancy. Based on it, a novel rat model of preeclampsia was established by the intraperitoneal administration of cadmium chloride (CdCl2) (0.125 mg of Cd/kg body weight) on gestational days 9-14. Key features of preeclampsia, including hypertension, proteinuria, placental abnormalities and small foetal size, appeared in pregnant rats after the administration of low-dose of CdCl2. Cadmium increased immunoglobulin production, mainly angiotensin II type 1-receptor-agonistic autoantibodies (AT1-AA), by increasing the expression of activation-induced cytosine deaminase (AID) in B cells. AID is critical for the maturation of antibody and autoantibody responses. In addition, angiotensin II type 1-receptor-agonistic autoantibody, which emerged recently as a potential pathogenic contributor to PE, was responsible for the deposition of complement component 5 (C5) in kidneys of pregnant rats via angiotensin II type 1 receptor (AT1R) activation. C5a is a fragment of C5 that is released during C5 activation. Selectively interfering with C5a signalling by a complement C5a receptor-specific antagonist significantly attenuated hypertension and proteinuria in Cd-injected pregnant rats. Our results suggest that cadmium induces immune abnormalities that may be a key pathogenic contributor to preeclampsia and provide new insights into treatment strategies of preeclampsia. Copyright © 2016 Elsevier Ltd. All rights reserved.

  14. Solid images for geostructural mapping and key block modeling of rock discontinuities

    Science.gov (United States)

    Assali, Pierre; Grussenmeyer, Pierre; Villemin, Thierry; Pollet, Nicolas; Viguier, Flavien

    2016-04-01

    Rock mass characterization is obviously a key element in rock fall hazard analysis. Managing risk and determining the most adapted reinforcement method require a proper understanding of the considered rock mass. Description of discontinuity sets is therefore a crucial first step in the reinforcement work design process. The on-field survey is then followed by a structural modeling in order to extrapolate the data collected at the rock surface to the inner part of the massif. Traditional compass survey and manual observations can be undoubtedly surpassed by dense 3D data such as LiDAR or photogrammetric point clouds. However, although the acquisition phase is quite fast and highly automated, managing, handling and exploiting such great amount of collected data is an arduous task and especially for non specialist users. In this study, we propose a combined approached using both 3D point clouds (from LiDAR or image matching) and 2D digital images, gathered into the concept of ''solid image''. This product is the connection between the advantages of classical true colors 2D digital images, accessibility and interpretability, and the particular strengths of dense 3D point clouds, i.e. geometrical completeness and accuracy. The solid image can be considered as the information support for carrying-out a digital survey at the surface of the outcrop without being affected by traditional deficiencies (lack of data and sampling difficulties due to inaccessible areas, safety risk in steep sectors, etc.). Computational tools presented in this paper have been implemented into one standalone software through a graphical user interface helping operators with the completion of a digital geostructural survey and analysis. 3D coordinates extraction, 3D distances and area measurement, planar best-fit for discontinuity orientation, directional roughness profiles, block size estimation, and other tools have been experimented on a calcareous quarry in the French Alps.

  15. Identifying developmental vascular disruptor compounds using a predictive signature and alternative toxicity models

    Science.gov (United States)

    Identifying Developmental Vascular Disruptor Compounds Using a Predictive Signature and Alternative Toxicity Models Presenting Author: Tamara Tal Affiliation: U.S. EPA/ORD/ISTD, RTP, NC, USA Chemically induced vascular toxicity during embryonic development can result in a wide...

  16. Identifying the Goal, User model and Conditions of Recommender Systems for Formal and Informal Learning

    NARCIS (Netherlands)

    Drachsler, Hendrik; Hummel, Hans; Koper, Rob

    2008-01-01

    Drachsler, H., Hummel, H. G. K., & Koper, R. (2009). Identifying the Goal, User model and Conditions of Recommender Systems for Formal and Informal Learning. Journal of Digital Information, 10(2), 4-24.

  17. Parameter sensitivity and identifiability for a biogeochemical model of hypoxia in the northern Gulf of Mexico

    Science.gov (United States)

    Local sensitivity analyses and identifiable parameter subsets were used to describe numerical constraints of a hypoxia model for bottom waters of the northern Gulf of Mexico. The sensitivity of state variables differed considerably with parameter changes, although most variables ...

  18. Laboratory infrastructure driven key performance indicator development using the smart grid architecture model

    DEFF Research Database (Denmark)

    Syed, Mazheruddin H.; Guillo-Sansano, Efren; Blair, Steven M.

    2017-01-01

    This study presents a methodology for collaboratively designing laboratory experiments and developing key performance indicators for the testing and validation of novel power system control architectures in multiple laboratory environments. The contribution makes use of the smart grid architecture...

  19. Using maximum entropy modeling to identify and prioritize red spruce forest habitat in West Virginia

    Science.gov (United States)

    Nathan R. Beane; James S. Rentch; Thomas M. Schuler

    2013-01-01

    Red spruce forests in West Virginia are found in island-like distributions at high elevations and provide essential habitat for the endangered Cheat Mountain salamander and the recently delisted Virginia northern flying squirrel. Therefore, it is important to identify restoration priorities of red spruce forests. Maximum entropy modeling was used to identify areas of...

  20. Developing a Model for Identifying Students at Risk of Failure in a First Year Accounting Unit

    Science.gov (United States)

    Smith, Malcolm; Therry, Len; Whale, Jacqui

    2012-01-01

    This paper reports on the process involved in attempting to build a predictive model capable of identifying students at risk of failure in a first year accounting unit in an Australian university. Identifying attributes that contribute to students being at risk can lead to the development of appropriate intervention strategies and support…

  1. Identification of miRNA Signatures Associated with Epithelial Ovarian Cancer Chemoresistance with Further Biological and Functional Validation of Identified Key miRNAs

    Science.gov (United States)

    2012-08-01

    separated on 12% SDS PAGE gels and transferred to nitrocellulose membranes. After blocking with 5% non- fat milk (Labscientific, Inc) in TBS-Tween buffer... Raw mass spectrometric data were processed and analyzed for variations in the spectral counts of peptides between sample sets and bioinformatics was...accomplished using Ingenuity Pathways Analysis (IPA). Results: The total numbers of proteins and peptides identified are listed in the table

  2. Identifying the key processes for technology transfer through spin-offs in academic institutions : a case study in Flanders and The Netherlands

    OpenAIRE

    Meysman, Jasmine; Cleyn, De, Sven H.; Braet, Johan

    2017-01-01

    Abstract: The position and role of technology transfer offices within universities and academic institutions have changed under influence of todays society, with diminishing government subsidies and technology transfer related policies having their impact on the technology transfer processes. In order to find out what the effect of this impact is, we performed a multiple-case study on six technology transfer offices in Flanders and The Netherlands. As a result of the study, we identified two ...

  3. Kinome-wide shRNA Screen Identifies the Receptor Tyrosine Kinase AXL as a Key Regulator for Mesenchymal Glioblastoma Stem-like Cells

    Directory of Open Access Journals (Sweden)

    Peng Cheng

    2015-05-01

    Full Text Available Glioblastoma is a highly lethal cancer for which novel therapeutics are urgently needed. Two distinct subtypes of glioblastoma stem-like cells (GSCs were recently identified: mesenchymal (MES and proneural (PN. To identify mechanisms to target the more aggressive MES GSCs, we combined transcriptomic expression analysis and kinome-wide short hairpin RNA screening of MES and PN GSCs. In comparison to PN GSCs, we found significant upregulation and phosphorylation of the receptor tyrosine kinase AXL in MES GSCs. Knockdown of AXL significantly decreased MES GSC self-renewal capacity in vitro and inhibited the growth of glioblastoma patient-derived xenografts. Moreover, inhibition of AXL with shRNA or pharmacologic inhibitors also increased cell death significantly more in MES GSCs. Clinically, AXL expression was elevated in the MES GBM subtype and significantly correlated with poor prognosis in multiple cancers. In conclusion, we identified AXL as a potential molecular target for novel approaches to treat glioblastoma and other solid cancers.

  4. Dynamical compensation and structural identifiability of biological models: Analysis, implications, and reconciliation.

    Science.gov (United States)

    Villaverde, Alejandro F; Banga, Julio R

    2017-11-01

    The concept of dynamical compensation has been recently introduced to describe the ability of a biological system to keep its output dynamics unchanged in the face of varying parameters. However, the original definition of dynamical compensation amounts to lack of structural identifiability. This is relevant if model parameters need to be estimated, as is often the case in biological modelling. Care should we taken when using an unidentifiable model to extract biological insight: the estimated values of structurally unidentifiable parameters are meaningless, and model predictions about unmeasured state variables can be wrong. Taking this into account, we explore alternative definitions of dynamical compensation that do not necessarily imply structural unidentifiability. Accordingly, we show different ways in which a model can be made identifiable while exhibiting dynamical compensation. Our analyses enable the use of the new concept of dynamical compensation in the context of parameter identification, and reconcile it with the desirable property of structural identifiability.

  5. A Numerical Procedure for Model Identifiability Analysis Applied to Enzyme Kinetics

    DEFF Research Database (Denmark)

    Daele, Timothy, Van; Van Hoey, Stijn; Gernaey, Krist

    2015-01-01

    The proper calibration of models describing enzyme kinetics can be quite challenging. In the literature, different procedures are available to calibrate these enzymatic models in an efficient way. However, in most cases the model structure is already decided on prior to the actual calibration...... and Pronzato (1997) and which can be easily set up for any type of model. In this paper the proposed approach is applied to the forward reaction rate of the enzyme kinetics proposed by Shin and Kim(1998). Structural identifiability analysis showed that no local structural model problems were occurring......) identifiability problems. By using the presented approach it is possible to detect potential identifiability problems and avoid pointless calibration (and experimental!) effort....

  6. A Systematic Approach to Determining the Identifiability of Multistage Carcinogenesis Models.

    Science.gov (United States)

    Brouwer, Andrew F; Meza, Rafael; Eisenberg, Marisa C

    2017-07-01

    Multistage clonal expansion (MSCE) models of carcinogenesis are continuous-time Markov process models often used to relate cancer incidence to biological mechanism. Identifiability analysis determines what model parameter combinations can, theoretically, be estimated from given data. We use a systematic approach, based on differential algebra methods traditionally used for deterministic ordinary differential equation (ODE) models, to determine identifiable combinations for a generalized subclass of MSCE models with any number of preinitation stages and one clonal expansion. Additionally, we determine the identifiable combinations of the generalized MSCE model with up to four clonal expansion stages, and conjecture the results for any number of clonal expansion stages. The results improve upon previous work in a number of ways and provide a framework to find the identifiable combinations for further variations on the MSCE models. Finally, our approach, which takes advantage of the Kolmogorov backward equations for the probability generating functions of the Markov process, demonstrates that identifiability methods used in engineering and mathematics for systems of ODEs can be applied to continuous-time Markov processes. © 2016 Society for Risk Analysis.

  7. Robust global identifiability theory using potentials--Application to compartmental models.

    Science.gov (United States)

    Wongvanich, N; Hann, C E; Sirisena, H R

    2015-04-01

    This paper presents a global practical identifiability theory for analyzing and identifying linear and nonlinear compartmental models. The compartmental system is prolonged onto the potential jet space to formulate a set of input-output equations that are integrals in terms of the measured data, which allows for robust identification of parameters without requiring any simulation of the model differential equations. Two classes of linear and non-linear compartmental models are considered. The theory is first applied to analyze the linear nitrous oxide (N2O) uptake model. The fitting accuracy of the identified models from differential jet space and potential jet space identifiability theories is compared with a realistic noise level of 3% which is derived from sensor noise data in the literature. The potential jet space approach gave a match that was well within the coefficient of variation. The differential jet space formulation was unstable and not suitable for parameter identification. The proposed theory is then applied to a nonlinear immunological model for mastitis in cows. In addition, the model formulation is extended to include an iterative method which allows initial conditions to be accurately identified. With up to 10% noise, the potential jet space theory predicts the normalized population concentration infected with pathogens, to within 9% of the true curve. Copyright © 2015 Elsevier Inc. All rights reserved.

  8. Examples of testing global identifiability of biological and biomedical models with the DAISY software.

    Science.gov (United States)

    Saccomani, Maria Pia; Audoly, Stefania; Bellu, Giuseppina; D'Angiò, Leontina

    2010-04-01

    DAISY (Differential Algebra for Identifiability of SYstems) is a recently developed computer algebra software tool which can be used to automatically check global identifiability of (linear and) nonlinear dynamic models described by differential equations involving polynomial or rational functions. Global identifiability is a fundamental prerequisite for model identification which is important not only for biological or medical systems but also for many physical and engineering systems derived from first principles. Lack of identifiability implies that the parameter estimation techniques may not fail but any obtained numerical estimates will be meaningless. The software does not require understanding of the underlying mathematical principles and can be used by researchers in applied fields with a minimum of mathematical background. We illustrate the DAISY software by checking the a priori global identifiability of two benchmark nonlinear models taken from the literature. The analysis of these two examples includes comparison with other methods and demonstrates how identifiability analysis is simplified by this tool. Thus we illustrate the identifiability analysis of other two examples, by including discussion of some specific aspects related to the role of observability and knowledge of initial conditions in testing identifiability and to the computational complexity of the software. The main focus of this paper is not on the description of the mathematical background of the algorithm, which has been presented elsewhere, but on illustrating its use and on some of its more interesting features. DAISY is available on the web site http://www.dei.unipd.it/ approximately pia/. 2010 Elsevier Ltd. All rights reserved.

  9. Labonté Identifies Key Issues for Health Promoters in the New World Order Comment on "Health Promotion in an Age of Normative Equity and Rampant Inequality".

    Science.gov (United States)

    Raphael, Dennis Raphael

    2016-11-02

    For over 35 years Ronald Labonté has been critically analyzing the state of health promotion in Canada and the world. In 1981, he identified the shortcomings of the groundbreaking Lalonde Report by warning of the seductive appeal of so-called lifestyle approaches to health. Since then, he has left a trail of critical work identifying the barriers to - and opportunities for -health promotion work. More recently, he has shown how the rise of economic globalization and acceptance of neo-liberal ideology has come to threaten the health of those in both developed and developing nations. In his recent commentary, Labonté shows how the United Nations' 2015 Sustainable Development Goals (SDGs) can offer a new direction for health promoters in these difficult times. © 2017 The Author(s); Published by Kerman University of Medical Sciences. This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

  10. The Baby TALK Model: An Innovative Approach to Identifying High-Risk Children and Families

    Science.gov (United States)

    Villalpando, Aimee Hilado; Leow, Christine; Hornstein, John

    2012-01-01

    This research report examines the Baby TALK model, an innovative early childhood intervention approach used to identify, recruit, and serve young children who are at-risk for developmental delays, mental health needs, and/or school failure, and their families. The report begins with a description of the model. This description is followed by an…

  11. Modeling Success: Using Preenrollment Data to Identify Academically At-Risk Students

    Science.gov (United States)

    Gansemer-Topf, Ann M.; Compton, Jonathan; Wohlgemuth, Darin; Forbes, Greg; Ralston, Ekaterina

    2015-01-01

    Improving student success and degree completion is one of the core principles of strategic enrollment management. To address this principle, institutional data were used to develop a statistical model to identify academically at-risk students. The model employs multiple linear regression techniques to predict students at risk of earning below a…

  12. Identifying Multiple Levels of Discussion-Based Teaching Strategies for Constructing Scientific Models

    Science.gov (United States)

    Williams, Grant; Clement, John

    2015-01-01

    This study sought to identify specific types of discussion-based strategies that two successful high school physics teachers using a model-based approach utilized in attempting to foster students' construction of explanatory models for scientific concepts. We found evidence that, in addition to previously documented dialogical strategies that…

  13. Key intermediates in nitrogen transformation during microwave pyrolysis of sewage sludge: a protein model compound study.

    Science.gov (United States)

    Zhang, Jun; Tian, Yu; Cui, Yanni; Zuo, Wei; Tan, Tao

    2013-03-01

    The nitrogen transformations with attention to NH3 and HCN were investigated at temperatures of 300-800°C during microwave pyrolysis of a protein model compound. The evolution of nitrogenated compounds in the char, tar and gas products were conducted. The amine-N, heterocyclic-N and nitrile-N compounds were identified as three important intermediates during the pyrolysis. NH3 and HCN were formed with comparable activation energies competed to consume the same reactive substances at temperatures of 300-800°C. The deamination and dehydrogenation of amine-N compounds from protein cracking contributed to the formation of NH3 (about 8.9% of Soy-N) and HCN (6.6%) from 300 to 500°C. The cracking of nitrile-N and heterocyclic-N compounds from the dehydrogenation and polymerization of amine-N generated HCN (13.4%) and NH3 (31.3%) between 500 and 800°C. It might be able to reduce the HCN and NH3 emissions through controlling the intermediates production at temperatures of 500-800°C. Copyright © 2013 Elsevier Ltd. All rights reserved.

  14. Critical and shielding parametric studies with the Monte Carlo code TRIPOLI to identify the key points to take into account during the transportation of blanket assemblies with high ratio of americium

    International Nuclear Information System (INIS)

    Gosmain, Cecile-Aline

    2011-01-01

    In the framework of French research program on Generation IV sodium cooled fast reactor, one possible option consists in burning minor actinides in this kind of Advanced Sodium Technological Reactor. Two types of transmutation mode are studied in the world : the homogeneous mode of transmutation where actinides are scattered with very low enrichment ratio in fissile assemblies and the heterogeneous mode where fissile core is surrounded by blanket assemblies filled with minor actinides with ratio of incorporated actinides up to 20%. Depending on which element is considered to be burnt and on its content, these minor actinides contents imply constraints on assemblies' transportation between Nuclear Power Plants and fuel cycle facilities. In this study, we present some academic studies in order to identify some key constraints linked to the residual power and neutron/gamma load of such kind of blanket assemblies. To simplify the approach, we considered a modeling of a 'model cask' dedicated to the transportation of a unique irradiated blanket assembly loaded with 20% of Americium and basically inspired from an existent cask designed initially for the damaged fissile Superphenix assembly transport. Thermal calculations performed with EDF-SYRTHES code have shown that due to thermal limitations on cladding temperature, the decay time to be considered before transportation is 20 years. This study is based on explicit 3D representations of the cask and the contained blanket assembly with the Monte Carlo code TRIPOLI/JEFF3.1.1 library and concludes that after such a decay time, the transportation of a unique Americium radial blanket is feasible only if the design of our model cask is modified in order to comply with the dose limitation criterion. (author)

  15. Simultaneous Parameters Identifiability and Estimation of an E. coli Metabolic Network Model

    Directory of Open Access Journals (Sweden)

    Kese Pontes Freitas Alberton

    2015-01-01

    Full Text Available This work proposes a procedure for simultaneous parameters identifiability and estimation in metabolic networks in order to overcome difficulties associated with lack of experimental data and large number of parameters, a common scenario in the modeling of such systems. As case study, the complex real problem of parameters identifiability of the Escherichia coli K-12 W3110 dynamic model was investigated, composed by 18 differential ordinary equations and 35 kinetic rates, containing 125 parameters. With the procedure, model fit was improved for most of the measured metabolites, achieving 58 parameters estimated, including 5 unknown initial conditions. The results indicate that simultaneous parameters identifiability and estimation approach in metabolic networks is appealing, since model fit to the most of measured metabolites was possible even when important measures of intracellular metabolites and good initial estimates of parameters are not available.

  16. Integrated analysis of oral tongue squamous cell carcinoma identifies key variants and pathways linked to risk habits, HPV, clinical parameters and tumor recurrence [version 1; referees: 2 approved

    Directory of Open Access Journals (Sweden)

    Neeraja Krishnan

    2015-11-01

    Full Text Available Oral tongue squamous cell carcinomas (OTSCC are a homogeneous group of tumors characterized by aggressive behavior, early spread to lymph nodes and a higher rate of regional failure. Additionally, the incidence of OTSCC among younger population (<50yrs is on the rise; many of whom lack the typical associated risk factors of alcohol and/or tobacco exposure. We present data on single nucleotide variations (SNVs, indels, regions with loss of heterozygosity (LOH, and copy number variations (CNVs from fifty-paired oral tongue primary tumors and link the significant somatic variants with clinical parameters, epidemiological factors including human papilloma virus (HPV infection and tumor recurrence. Apart from the frequent somatic variants harbored in TP53, CASP8, RASA1, NOTCH and CDKN2A genes, significant amplifications and/or deletions were detected in chromosomes 6-9, and 11 in the tumors. Variants in CASP8 and CDKN2A were mutually exclusive. CDKN2A, PIK3CA, RASA1 and DMD variants were exclusively linked to smoking, chewing, HPV infection and tumor stage. We also performed a whole-genome gene expression study that identified matrix metalloproteases to be highly expressed in tumors and linked pathways involving arachidonic acid and NF-k-B to habits and distant metastasis, respectively. Functional knockdown studies in cell lines demonstrated the role of CASP8 in a HPV-negative OTSCC cell line. Finally, we identified a 38-gene minimal signature that predicts tumor recurrence using an ensemble machine-learning method. Taken together, this study links molecular signatures to various clinical and epidemiological factors in a homogeneous tumor population with a relatively high HPV prevalence.

  17. Identifiability of tree-child phylogenetic networks under a probabilistic recombination-mutation model of evolution.

    Science.gov (United States)

    Francis, Andrew; Moulton, Vincent

    2018-06-07

    Phylogenetic networks are an extension of phylogenetic trees which are used to represent evolutionary histories in which reticulation events (such as recombination and hybridization) have occurred. A central question for such networks is that of identifiability, which essentially asks under what circumstances can we reliably identify the phylogenetic network that gave rise to the observed data? Recently, identifiability results have appeared for networks relative to a model of sequence evolution that generalizes the standard Markov models used for phylogenetic trees. However, these results are quite limited in terms of the complexity of the networks that are considered. In this paper, by introducing an alternative probabilistic model for evolution along a network that is based on some ground-breaking work by Thatte for pedigrees, we are able to obtain an identifiability result for a much larger class of phylogenetic networks (essentially the class of so-called tree-child networks). To prove our main theorem, we derive some new results for identifying tree-child networks combinatorially, and then adapt some techniques developed by Thatte for pedigrees to show that our combinatorial results imply identifiability in the probabilistic setting. We hope that the introduction of our new model for networks could lead to new approaches to reliably construct phylogenetic networks. Copyright © 2018 Elsevier Ltd. All rights reserved.

  18. An Approach for Automatically Deriving Key Performance Indicators from Ontological Enterprise Models

    NARCIS (Netherlands)

    Aksu, U.A.; Schunselaar, D.M.M.; Reijers, H.A.

    2017-01-01

    Organizations use Key Performance Indicators (KPIs) to monitor whether they attain their goals. Software vendors that supply generic software provide predefined KPIs in their software products for these organizations. However, each organization wants KPIs to be tailored to its specific goals.Th

  19. Identifying Keys to Success in Innovative Teaching: Student Engagement and Instructional Practices as Predictors of Student Learning in a Course Using a Team-Based Learning Approach

    Directory of Open Access Journals (Sweden)

    Rosa M. Alvarez-Bell

    2017-09-01

    Full Text Available When implementing innovative teaching techniques, instructors often seek to gauge the success of their methods. Proposing one approach to assessing classroom innovation, this study examines the ability of students’ ratings of engagement and instructional practices to predict their learning in a cooperative (team-based framework. After identifying the factor structures underlying measures of student engagement and instructional practices, these factors were used as predictors of self-reported student learning in a general chemistry course delivered using a team-based learning approach. Exploratory factor analyses showed a four-factor structure of engagement: teamwork involvement, investment in the learning process, feelings about team-based learning, level of academic challenge; and a three-factor structure of instructional practices: instructional guidance, fostering self-directed learning skills, and cognitive level. Multiple linear regression revealed that feelings about team-based learning and perceptions of instructional guidance had significant effects on learning, beyond other predictors, while controlling gender, GPA, class level, number of credit hours, whether students began college at their current institution, expected highest level of education, racial or ethnic identification, and parental level of education. These results yield insight into student perceptions about team-based learning, and how to measure learning in a team-based learning framework, with implications for how to evaluate innovative instructional methods.

  20. Paving the Way to Successful Implementation: Identifying Key Barriers to Use of Technology-Based Therapeutic Tools for Behavioral Health Care.

    Science.gov (United States)

    Ramsey, Alex; Lord, Sarah; Torrey, John; Marsch, Lisa; Lardiere, Michael

    2016-01-01

    This study aimed to identify barriers to use of technology for behavioral health care from the perspective of care decision makers at community behavioral health organizations. As part of a larger survey of technology readiness, 260 care decision makers completed an open-ended question about perceived barriers to use of technology. Using the Consolidated Framework for Implementation Research (CFIR), qualitative analyses yielded barrier themes related to characteristics of technology (e.g., cost and privacy), potential end users (e.g., technology literacy and attitudes about technology), organization structure and climate (e.g., budget and infrastructure), and factors external to organizations (e.g., broadband accessibility and reimbursement policies). Number of reported barriers was higher among respondents representing agencies with lower annual budgets and smaller client bases relative to higher budget, larger clientele organizations. Individual barriers were differentially associated with budget, size of client base, and geographic location. Results are discussed in light of implementation science frameworks and proactive strategies to address perceived obstacles to adoption and use of technology-based behavioral health tools.

  1. Cation-Poor Complex Metallic Alloys in Ba(Eu)-Au-Al(Ga) Systems: Identifying the Keys that Control Structural Arrangements and Atom Distributions at the Atomic Level.

    Science.gov (United States)

    Smetana, Volodymyr; Steinberg, Simon; Mudryk, Yaroslav; Pecharsky, Vitalij; Miller, Gordon J; Mudring, Anja-Verena

    2015-11-02

    Four complex intermetallic compounds BaAu(6±x)Ga(6±y) (x = 1, y = 0.9) (I), BaAu(6±x)Al(6±y) (x = 0.9, y = 0.6) (II), EuAu6.2Ga5.8 (III), and EuAu6.1Al5.9 (IV) have been synthesized, and their structures and homogeneity ranges have been determined by single crystal and powder X-ray diffraction. Whereas I and II originate from the NaZn13-type structure (cF104-112, Fm3̅c), III (tP52, P4/nbm) is derived from the tetragonal Ce2Ni17Si9-type, and IV (oP104, Pbcm) crystallizes in a new orthorhombic structure type. Both I and II feature formally anionic networks with completely mixed site occupation by Au and triel (Tr = Al, Ga) atoms, while a successive decrease of local symmetry from the parental structures of I and II to III and, ultimately, to IV correlates with increasing separation of Au and Tr on individual crystallographic sites. Density functional theory-based calculations were employed to determine the crystallographic site preferences of Au and the respective triel element to elucidate reasons for the atom distribution ("coloring scheme"). Chemical bonding analyses for two different "EuAu6Tr6" models reveal maximization of the number of heteroatomic Au-Tr bonds as the driving force for atom organization. The Fermi levels fall in broad pseudogaps for both models allowing some electronic flexibility. Spin-polarized band structure calculations on the "EuAu6Tr6" models hint to singlet ground states for europium and long-range magnetic coupling for both EuAu6.2Ga5.8 (III) and EuAu6.1Al5.9 (IV). This is substantiated by experimental evidence because both compounds show nearly identical magnetic behavior with ferromagnetic transitions at TC = 6 K and net magnetic moments of 7.35 μB/f.u. at 2 K. The effective moments of 8.3 μB/f.u., determined from Curie-Weiss fits, point to divalent oxidation states for europium in both III and IV.

  2. Vertebrae classification models - Validating classification models that use morphometrics to identify ancient salmonid (Oncorhynchus spp.) vertebrae to species

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Using morphometric characteristics of modern salmonid (Oncorhynchus spp.) vertebrae, we have developed classification models to identify salmonid vertebrae to the...

  3. A Bayesian approach to identifying and compensating for model misspecification in population models.

    Science.gov (United States)

    Thorson, James T; Ono, Kotaro; Munch, Stephan B

    2014-02-01

    State-space estimation methods are increasingly used in ecology to estimate productivity and abundance of natural populations while accounting for variability in both population dynamics and measurement processes. However, functional forms for population dynamics and density dependence often will not match the true biological process, and this may degrade the performance of state-space methods. We therefore developed a Bayesian semiparametric state-space model, which uses a Gaussian process (GP) to approximate the population growth function. This offers two benefits for population modeling. First, it allows data to update a specified "prior" on the population growth function, while reverting to this prior when data are uninformative. Second, it allows variability in population dynamics to be decomposed into random errors around the population growth function ("process error") and errors due to the mismatch between the specified prior and estimated growth function ("model error"). We used simulation modeling to illustrate the utility of GP methods in state-space population dynamics models. Results confirmed that the GP model performs similarly to a conventional state-space model when either (1) the prior matches the true process or (2) data are relatively uninformative. However, GP methods improve estimates of the population growth function when the function is misspecified. Results also demonstrated that the estimated magnitude of "model error" can be used to distinguish cases of model misspecification. We conclude with a discussion of the prospects for GP methods in other state-space models, including age and length-structured, meta-analytic, and individual-movement models.

  4. Objective Model Selection for Identifying the Human Feedforward Response in Manual Control.

    Science.gov (United States)

    Drop, Frank M; Pool, Daan M; van Paassen, Marinus Rene M; Mulder, Max; Bulthoff, Heinrich H

    2018-01-01

    Realistic manual control tasks typically involve predictable target signals and random disturbances. The human controller (HC) is hypothesized to use a feedforward control strategy for target-following, in addition to feedback control for disturbance-rejection. Little is known about human feedforward control, partly because common system identification methods have difficulty in identifying whether, and (if so) how, the HC applies a feedforward strategy. In this paper, an identification procedure is presented that aims at an objective model selection for identifying the human feedforward response, using linear time-invariant autoregressive with exogenous input models. A new model selection criterion is proposed to decide on the model order (number of parameters) and the presence of feedforward in addition to feedback. For a range of typical control tasks, it is shown by means of Monte Carlo computer simulations that the classical Bayesian information criterion (BIC) leads to selecting models that contain a feedforward path from data generated by a pure feedback model: "false-positive" feedforward detection. To eliminate these false-positives, the modified BIC includes an additional penalty on model complexity. The appropriate weighting is found through computer simulations with a hypothesized HC model prior to performing a tracking experiment. Experimental human-in-the-loop data will be considered in future work. With appropriate weighting, the method correctly identifies the HC dynamics in a wide range of control tasks, without false-positive results.

  5. Identifying influences on model uncertainty: an application using a forest carbon budget model

    Science.gov (United States)

    James E. Smith; Linda S. Heath

    2001-01-01

    Uncertainty is an important consideration for both developers and users of environmental simulation models. Establishing quantitative estimates of uncertainty for deterministic models can be difficult when the underlying bases for such information are scarce. We demonstrate an application of probabilistic uncertainty analysis that provides for refinements in...

  6. Structural identifiability of systems biology models: a critical comparison of methods.

    Directory of Open Access Journals (Sweden)

    Oana-Teodora Chis

    Full Text Available Analysing the properties of a biological system through in silico experimentation requires a satisfactory mathematical representation of the system including accurate values of the model parameters. Fortunately, modern experimental techniques allow obtaining time-series data of appropriate quality which may then be used to estimate unknown parameters. However, in many cases, a subset of those parameters may not be uniquely estimated, independently of the experimental data available or the numerical techniques used for estimation. This lack of identifiability is related to the structure of the model, i.e. the system dynamics plus the observation function. Despite the interest in knowing a priori whether there is any chance of uniquely estimating all model unknown parameters, the structural identifiability analysis for general non-linear dynamic models is still an open question. There is no method amenable to every model, thus at some point we have to face the selection of one of the possibilities. This work presents a critical comparison of the currently available techniques. To this end, we perform the structural identifiability analysis of a collection of biological models. The results reveal that the generating series approach, in combination with identifiability tableaus, offers the most advantageous compromise among range of applicability, computational complexity and information provided.

  7. Air quality models and unusually large ozone increases: Identifying model failures, understanding environmental causes, and improving modeled chemistry

    Science.gov (United States)

    Couzo, Evan A.

    Several factors combine to make ozone (O3) pollution in Houston, Texas, unique when compared to other metropolitan areas. These include complex meteorology, intense clustering of industrial activity, and significant precursor emissions from the heavily urbanized eight-county area. Decades of air pollution research have borne out two different causes, or conceptual models, of O 3 formation. One conceptual model describes a gradual region-wide increase in O3 concentrations "typical" of many large U.S. cities. The other conceptual model links episodic emissions of volatile organic compounds to spatially limited plumes of high O3, which lead to large hourly increases that have exceeded 100 parts per billion (ppb) per hour. These large hourly increases are known to lead to violations of the federal O 3 standard and impact Houston's status as a non-attainment area. There is a need to further understand and characterize the causes of peak O 3 levels in Houston and simulate them correctly so that environmental regulators can find the most cost-effective pollution controls. This work provides a detailed understanding of unusually large O 3 increases in the natural and modeled environments. First, we probe regulatory model simulations and assess their ability to reproduce the observed phenomenon. As configured for the purpose of demonstrating future attainment of the O3 standard, the model fails to predict the spatially limited O3 plumes observed in Houston. Second, we combine ambient meteorological and pollutant measurement data to identify the most likely geographic origins and preconditions of the concentrated O3 plumes. We find evidence that the O3 plumes are the result of photochemical activity accelerated by industrial emissions. And, third, we implement changes to the modeled chemistry to add missing formation mechanisms of nitrous acid, which is an important radical precursor. Radicals control the chemical reactivity of atmospheric systems, and perturbations to

  8. Towards a Unified Business Model Vocabulary: A Proposition of Key Constructs

    OpenAIRE

    Mettler, Tobias

    2014-01-01

    The design of business models is of decisive importance and as such it has been a major research theme in service and particularly electronic markets. Today, different definitions of the term and ideas of core constructs of business models exist. In this paper we present a unified vocabulary for business models that builds upon the elementary perception of three existing, yet very dissimilar ontologies for modeling the essence of a business. The resulting unified business model vocabulary not...

  9. Passage Key Inlet, Florida; CMS Modeling and Borrow Site Impact Analysis

    Science.gov (United States)

    2016-06-01

    Impact Analysis by Kelly R. Legault and Sirisha Rayaprolu PURPOSE: This Coastal and Hydraulics Engineering Technical Note (CHETN) describes the...driven sediment transport at Passage Key Inlet. This analysis resulted in issuing a new Florida Department of Environmental Protection (FDEP) permit to...Funding for this study was provided by the USACE Regional Sediment Management (RSM) Program, a Navigation Research, Development, and Technology Portfolio

  10. Calibrating and Validating a Simulation Model to Identify Drivers of Urban Land Cover Change in the Baltimore, MD Metropolitan Region

    Directory of Open Access Journals (Sweden)

    Claire Jantz

    2014-09-01

    Full Text Available We build upon much of the accumulated knowledge of the widely used SLEUTH urban land change model and offer advances. First, we use SLEUTH’s exclusion/attraction layer to identify and test different urban land cover change drivers; second, we leverage SLEUTH’s self-modification capability to incorporate a demographic model; and third, we develop a validation procedure to quantify the influence of land cover change drivers and assess uncertainty. We found that, contrary to our a priori expectations, new development is not attracted to areas serviced by existing or planned water and sewer infrastructure. However, information about where population and employment growth is likely to occur did improve model performance. These findings point to the dominant role of centrifugal forces in post-industrial cities like Baltimore, MD. We successfully developed a demographic model that allowed us to constrain the SLEUTH model forecasts and address uncertainty related to the dynamic relationship between changes in population and employment and urban land use. Finally, we emphasize the importance of model validation. In this work the validation procedure played a key role in rigorously assessing the impacts of different exclusion/attraction layers and in assessing uncertainty related to population and employment forecasts.

  11. A Conceptual Model to Identify Intent to Use Chemical-Biological Weapons

    Directory of Open Access Journals (Sweden)

    Mary Zalesny

    2017-10-01

    Full Text Available This paper describes a conceptual model to identify and interrelate indicators of intent of non-state actors to use chemical or biological weapons. The model expands on earlier efforts to understand intent to use weapons of mass destruction by building upon well-researched theories of intent and behavior and focusing on a sub-set of weapons of mass destruction (WMD to account for the distinct challenges of employing different types of WMD in violent acts. The conceptual model is presented as a first, critical step in developing a computational model for assessing the potential for groups to use chemical or biological weapons.

  12. Identified state-space prediction model for aero-optical wavefronts

    Science.gov (United States)

    Faghihi, Azin; Tesch, Jonathan; Gibson, Steve

    2013-07-01

    A state-space disturbance model and associated prediction filter for aero-optical wavefronts are described. The model is computed by system identification from a sequence of wavefronts measured in an airborne laboratory. Estimates of the statistics and flow velocity of the wavefront data are shown and can be computed from the matrices in the state-space model without returning to the original data. Numerical results compare velocity values and power spectra computed from the identified state-space model with those computed from the aero-optical data.

  13. Identifying best-fitting inputs in health-economic model calibration: a Pareto frontier approach.

    Science.gov (United States)

    Enns, Eva A; Cipriano, Lauren E; Simons, Cyrena T; Kong, Chung Yin

    2015-02-01

    To identify best-fitting input sets using model calibration, individual calibration target fits are often combined into a single goodness-of-fit (GOF) measure using a set of weights. Decisions in the calibration process, such as which weights to use, influence which sets of model inputs are identified as best-fitting, potentially leading to different health economic conclusions. We present an alternative approach to identifying best-fitting input sets based on the concept of Pareto-optimality. A set of model inputs is on the Pareto frontier if no other input set simultaneously fits all calibration targets as well or better. We demonstrate the Pareto frontier approach in the calibration of 2 models: a simple, illustrative Markov model and a previously published cost-effectiveness model of transcatheter aortic valve replacement (TAVR). For each model, we compare the input sets on the Pareto frontier to an equal number of best-fitting input sets according to 2 possible weighted-sum GOF scoring systems, and we compare the health economic conclusions arising from these different definitions of best-fitting. For the simple model, outcomes evaluated over the best-fitting input sets according to the 2 weighted-sum GOF schemes were virtually nonoverlapping on the cost-effectiveness plane and resulted in very different incremental cost-effectiveness ratios ($79,300 [95% CI 72,500-87,600] v. $139,700 [95% CI 79,900-182,800] per quality-adjusted life-year [QALY] gained). Input sets on the Pareto frontier spanned both regions ($79,000 [95% CI 64,900-156,200] per QALY gained). The TAVR model yielded similar results. Choices in generating a summary GOF score may result in different health economic conclusions. The Pareto frontier approach eliminates the need to make these choices by using an intuitive and transparent notion of optimality as the basis for identifying best-fitting input sets. © The Author(s) 2014.

  14. Improving the precision of lake ecosystem metabolism estimates by identifying predictors of model uncertainty

    Science.gov (United States)

    Rose, Kevin C.; Winslow, Luke A.; Read, Jordan S.; Read, Emily K.; Solomon, Christopher T.; Adrian, Rita; Hanson, Paul C.

    2014-01-01

    Diel changes in dissolved oxygen are often used to estimate gross primary production (GPP) and ecosystem respiration (ER) in aquatic ecosystems. Despite the widespread use of this approach to understand ecosystem metabolism, we are only beginning to understand the degree and underlying causes of uncertainty for metabolism model parameter estimates. Here, we present a novel approach to improve the precision and accuracy of ecosystem metabolism estimates by identifying physical metrics that indicate when metabolism estimates are highly uncertain. Using datasets from seventeen instrumented GLEON (Global Lake Ecological Observatory Network) lakes, we discovered that many physical characteristics correlated with uncertainty, including PAR (photosynthetically active radiation, 400-700 nm), daily variance in Schmidt stability, and wind speed. Low PAR was a consistent predictor of high variance in GPP model parameters, but also corresponded with low ER model parameter variance. We identified a threshold (30% of clear sky PAR) below which GPP parameter variance increased rapidly and was significantly greater in nearly all lakes compared with variance on days with PAR levels above this threshold. The relationship between daily variance in Schmidt stability and GPP model parameter variance depended on trophic status, whereas daily variance in Schmidt stability was consistently positively related to ER model parameter variance. Wind speeds in the range of ~0.8-3 m s–1 were consistent predictors of high variance for both GPP and ER model parameters, with greater uncertainty in eutrophic lakes. Our findings can be used to reduce ecosystem metabolism model parameter uncertainty and identify potential sources of that uncertainty.

  15. Clustering of transcriptional profiles identifies changes to insulin signaling as an early event in a mouse model of Alzheimer's disease.

    Science.gov (United States)

    Jackson, Harriet M; Soto, Ileana; Graham, Leah C; Carter, Gregory W; Howell, Gareth R

    2013-11-25

    Alzheimer's disease affects more than 35 million people worldwide but there is no known cure. Age is the strongest risk factor for Alzheimer's disease but it is not clear how age-related changes impact the disease. Here, we used a mouse model of Alzheimer's disease to identify age-specific changes that occur prior to and at the onset of traditional Alzheimer-related phenotypes including amyloid plaque formation. To identify these early events we used transcriptional profiling of mouse brains combined with computational approaches including singular value decomposition and hierarchical clustering. Our study identifies three key events in early stages of Alzheimer's disease. First, the most important drivers of Alzheimer's disease onset in these mice are age-specific changes. These include perturbations of the ribosome and oxidative phosphorylation pathways. Second, the earliest detectable disease-specific changes occur to genes commonly associated with the hypothalamic-adrenal-pituitary (HPA) axis. These include the down-regulation of genes relating to metabolism, depression and appetite. Finally, insulin signaling, in particular the down-regulation of the insulin receptor substrate 4 (Irs4) gene, may be an important event in the transition from age-related changes to Alzheimer's disease specific-changes. A combination of transcriptional profiling combined with computational analyses has uncovered novel features relevant to Alzheimer's disease in a widely used mouse model and offers avenues for further exploration into early stages of AD.

  16. Identifying musical pieces from fMRI data using encoding and decoding models.

    Science.gov (United States)

    Hoefle, Sebastian; Engel, Annerose; Basilio, Rodrigo; Alluri, Vinoo; Toiviainen, Petri; Cagy, Maurício; Moll, Jorge

    2018-02-02

    Encoding models can reveal and decode neural representations in the visual and semantic domains. However, a thorough understanding of how distributed information in auditory cortices and temporal evolution of music contribute to model performance is still lacking in the musical domain. We measured fMRI responses during naturalistic music listening and constructed a two-stage approach that first mapped musical features in auditory cortices and then decoded novel musical pieces. We then probed the influence of stimuli duration (number of time points) and spatial extent (number of voxels) on decoding accuracy. Our approach revealed a linear increase in accuracy with duration and a point of optimal model performance for the spatial extent. We further showed that Shannon entropy is a driving factor, boosting accuracy up to 95% for music with highest information content. These findings provide key insights for future decoding and reconstruction algorithms and open new venues for possible clinical applications.

  17. Data Mining and Pattern Recognition Models for Identifying Inherited Diseases: Challenges and Implications

    OpenAIRE

    Iddamalgoda, Lahiru; Das, Partha S.; Aponso, Achala; Sundararajan, Vijayaraghava S.; Suravajhala, Prashanth; Valadi, Jayaraman K.

    2016-01-01

    Data mining and pattern recognition methods reveal interesting findings in genetic studies, especially on how the genetic makeup is associated with inherited diseases. Although researchers have proposed various data mining models for biomedical approaches, there remains a challenge in accurately prioritizing the single nucleotide polymorphisms (SNP) associated with the disease. In this commentary, we review the state-of-art data mining and pattern recognition models for identifying inherited ...

  18. An overview of mice models: a key for understanding subtypes of mania

    Directory of Open Access Journals (Sweden)

    Jorge Mauricio Cuartas Arias

    2016-09-01

    Full Text Available Animal models have been broadly used in the study of pathophysiology and molecular and neurochemical pathways in neuropsychiatric diseases. Different approaches have used both consanguineous and non-consanguineous mice models to model behavioral patterns associated with the maniac spectrum. However, the disadvantages of validating clinical and experimental protocols have hindered the replication of these studies. In this article, the advantages and disadvantages of using consanguineous lines and non-consanguineous stocks in mice animal models for the study of mania and its subtypes are discussed. Additionally, new experimental alternatives to advance the pathogenesis and pharmacogenetics of mania using animal models are proposed and analyzed.

  19. A study of key features of the RAE atmospheric turbulence model

    Science.gov (United States)

    Jewell, W. F.; Heffley, R. K.

    1978-01-01

    A complex atmospheric turbulence model for use in aircraft simulation is analyzed in terms of its temporal, spectral, and statistical characteristics. First, a direct comparison was made between cases of the RAE model and the more conventional Dryden turbulence model. Next the control parameters of the RAE model were systematically varied and the effects noted. The RAE model was found to possess a high degree of flexibility in its characteristics, but the individual control parameters are cross-coupled in terms of their effect on various measures of intensity, bandwidth, and probability distribution.

  20. Comparison of two model approaches in the Zambezi river basin with regard to model reliability and identifiability

    Directory of Open Access Journals (Sweden)

    H. C. Winsemius

    2006-01-01

    Full Text Available Variations of water stocks in the upper Zambezi river basin have been determined by 2 different hydrological modelling approaches. The purpose was to provide preliminary terrestrial storage estimates in the upper Zambezi, which will be compared with estimates derived from the Gravity Recovery And Climate Experiment (GRACE in a future study. The first modelling approach is GIS-based, distributed and conceptual (STREAM. The second approach uses Lumped Elementary Watersheds identified and modelled conceptually (LEW. The STREAM model structure has been assessed using GLUE (Generalized Likelihood Uncertainty Estimation a posteriori to determine parameter identifiability. The LEW approach could, in addition, be tested for model structure, because computational efforts of LEW are low. Both models are threshold models, where the non-linear behaviour of the Zambezi river basin is explained by a combination of thresholds and linear reservoirs. The models were forced by time series of gauged and interpolated rainfall. Where available, runoff station data was used to calibrate the models. Ungauged watersheds were generally given the same parameter sets as their neighbouring calibrated watersheds. It appeared that the LEW model structure could be improved by applying GLUE iteratively. Eventually, it led to better identifiability of parameters and consequently a better model structure than the STREAM model. Hence, the final model structure obtained better represents the true hydrology. After calibration, both models show a comparable efficiency in representing discharge. However the LEW model shows a far greater storage amplitude than the STREAM model. This emphasizes the storage uncertainty related to hydrological modelling in data-scarce environments such as the Zambezi river basin. It underlines the need and potential for independent observations of terrestrial storage to enhance our understanding and modelling capacity of the hydrological processes. GRACE

  1. A Modeling methodology for NoSQL Key-Value databases

    Directory of Open Access Journals (Sweden)

    Gerardo ROSSEL

    2017-08-01

    Full Text Available In recent years, there has been an increasing interest in the field of non-relational databases. However, far too little attention has been paid to design methodology. Key-value data stores are an important component of a class of non-relational technologies that are grouped under the name of NoSQL databases. The aim of this paper is to propose a design methodology for this type of database that allows overcoming the limitations of the traditional techniques. The proposed methodology leads to a clean design that also allows for better data management and consistency.

  2. Optimal input shaping for Fisher identifiability of control-oriented lithium-ion battery models

    Science.gov (United States)

    Rothenberger, Michael J.

    This dissertation examines the fundamental challenge of optimally shaping input trajectories to maximize parameter identifiability of control-oriented lithium-ion battery models. Identifiability is a property from information theory that determines the solvability of parameter estimation for mathematical models using input-output measurements. This dissertation creates a framework that exploits the Fisher information metric to quantify the level of battery parameter identifiability, optimizes this metric through input shaping, and facilitates faster and more accurate estimation. The popularity of lithium-ion batteries is growing significantly in the energy storage domain, especially for stationary and transportation applications. While these cells have excellent power and energy densities, they are plagued with safety and lifespan concerns. These concerns are often resolved in the industry through conservative current and voltage operating limits, which reduce the overall performance and still lack robustness in detecting catastrophic failure modes. New advances in automotive battery management systems mitigate these challenges through the incorporation of model-based control to increase performance, safety, and lifespan. To achieve these goals, model-based control requires accurate parameterization of the battery model. While many groups in the literature study a variety of methods to perform battery parameter estimation, a fundamental issue of poor parameter identifiability remains apparent for lithium-ion battery models. This fundamental challenge of battery identifiability is studied extensively in the literature, and some groups are even approaching the problem of improving the ability to estimate the model parameters. The first approach is to add additional sensors to the battery to gain more information that is used for estimation. The other main approach is to shape the input trajectories to increase the amount of information that can be gained from input

  3. Identifying the default mode network structure using dynamic causal modeling on resting-state functional magnetic resonance imaging.

    Science.gov (United States)

    Di, Xin; Biswal, Bharat B

    2014-02-01

    The default mode network is part of the brain structure that shows higher neural activity and energy consumption when one is at rest. The key regions in the default mode network are highly interconnected as conveyed by both the white matter fiber tracing and the synchrony of resting-state functional magnetic resonance imaging signals. However, the causal information flow within the default mode network is still poorly understood. The current study used the dynamic causal modeling on a resting-state fMRI data set to identify the network structure underlying the default mode network. The endogenous brain fluctuations were explicitly modeled by Fourier series at the low frequency band of 0.01-0.08Hz, and those Fourier series were set as driving inputs of the DCM models. Model comparison procedures favored a model wherein the MPFC sends information to the PCC and the bilateral inferior parietal lobule sends information to both the PCC and MPFC. Further analyses provide evidence that the endogenous connectivity might be higher in the right hemisphere than in the left hemisphere. These data provided insight into the functions of each node in the DMN, and also validate the usage of DCM on resting-state fMRI data. © 2013.

  4. Inference in partially identified models with many moment inequalities using Lasso

    DEFF Research Database (Denmark)

    Bugni, Federico A.; Caner, Mehmet; Kock, Anders Bredahl

    This paper considers the problem of inference in a partially identified moment (in)equality model with possibly many moment inequalities. Our contribution is to propose a novel two-step new inference method based on the combination of two ideas. On the one hand, our test statistic and critical...

  5. Using neutral models to identify constraints on low-severity fire regimes.

    Science.gov (United States)

    Donald McKenzie; Amy E. Hessl; Lara-Karena B. Kellogg

    2006-01-01

    Climate, topography, fuel loadings, and human activities all affect spatial and temporal patterns of fire occurrence. Because fire is modeled as a stochastic process, for which each fire history is only one realization, a simulation approach is necessary to understand baseline variability, thereby identifying constraints, or forcing functions, that affect fire regimes...

  6. Using Predictive Modelling to Identify Students at Risk of Poor University Outcomes

    Science.gov (United States)

    Jia, Pengfei; Maloney, Tim

    2015-01-01

    Predictive modelling is used to identify students at risk of failing their first-year courses and not returning to university in the second year. Our aim is twofold. Firstly, we want to understand the factors that lead to poor first-year experiences at university. Secondly, we want to develop simple, low-cost tools that would allow universities to…

  7. Identifying biological concepts from a protein-related corpus with a probabilistic topic model

    Directory of Open Access Journals (Sweden)

    Lu Xinghua

    2006-02-01

    Full Text Available Abstract Background Biomedical literature, e.g., MEDLINE, contains a wealth of knowledge regarding functions of proteins. Major recurring biological concepts within such text corpora represent the domains of this body of knowledge. The goal of this research is to identify the major biological topics/concepts from a corpus of protein-related MEDLINE© titles and abstracts by applying a probabilistic topic model. Results The latent Dirichlet allocation (LDA model was applied to the corpus. Based on the Bayesian model selection, 300 major topics were extracted from the corpus. The majority of identified topics/concepts was found to be semantically coherent and most represented biological objects or concepts. The identified topics/concepts were further mapped to the controlled vocabulary of the Gene Ontology (GO terms based on mutual information. Conclusion The major and recurring biological concepts within a collection of MEDLINE documents can be extracted by the LDA model. The identified topics/concepts provide parsimonious and semantically-enriched representation of the texts in a semantic space with reduced dimensionality and can be used to index text.

  8. Structural identifiability analyses of candidate models for in vitro Pitavastatin hepatic uptake.

    Science.gov (United States)

    Grandjean, Thomas R B; Chappell, Michael J; Yates, James W T; Evans, Neil D

    2014-05-01

    In this paper a review of the application of four different techniques (a version of the similarity transformation approach for autonomous uncontrolled systems, a non-differential input/output observable normal form approach, the characteristic set differential algebra and a recent algebraic input/output relationship approach) to determine the structural identifiability of certain in vitro nonlinear pharmacokinetic models is provided. The Organic Anion Transporting Polypeptide (OATP) substrate, Pitavastatin, is used as a probe on freshly isolated animal and human hepatocytes. Candidate pharmacokinetic non-linear compartmental models have been derived to characterise the uptake process of Pitavastatin. As a prerequisite to parameter estimation, structural identifiability analyses are performed to establish that all unknown parameters can be identified from the experimental observations available. Copyright © 2013. Published by Elsevier Ireland Ltd.

  9. Antibiotic Resistances in Livestock: A Comparative Approach to Identify an Appropriate Regression Model for Count Data

    Directory of Open Access Journals (Sweden)

    Anke Hüls

    2017-05-01

    Full Text Available Antimicrobial resistance in livestock is a matter of general concern. To develop hygiene measures and methods for resistance prevention and control, epidemiological studies on a population level are needed to detect factors associated with antimicrobial resistance in livestock holdings. In general, regression models are used to describe these relationships between environmental factors and resistance outcome. Besides the study design, the correlation structures of the different outcomes of antibiotic resistance and structural zero measurements on the resistance outcome as well as on the exposure side are challenges for the epidemiological model building process. The use of appropriate regression models that acknowledge these complexities is essential to assure valid epidemiological interpretations. The aims of this paper are (i to explain the model building process comparing several competing models for count data (negative binomial model, quasi-Poisson model, zero-inflated model, and hurdle model and (ii to compare these models using data from a cross-sectional study on antibiotic resistance in animal husbandry. These goals are essential to evaluate which model is most suitable to identify potential prevention measures. The dataset used as an example in our analyses was generated initially to study the prevalence and associated factors for the appearance of cefotaxime-resistant Escherichia coli in 48 German fattening pig farms. For each farm, the outcome was the count of samples with resistant bacteria. There was almost no overdispersion and only moderate evidence of excess zeros in the data. Our analyses show that it is essential to evaluate regression models in studies analyzing the relationship between environmental factors and antibiotic resistances in livestock. After model comparison based on evaluation of model predictions, Akaike information criterion, and Pearson residuals, here the hurdle model was judged to be the most appropriate

  10. Development of the information model for consumer assessment of key quality indicators by goods labelling

    Science.gov (United States)

    Koshkina, S.; Ostrinskaya, L.

    2018-04-01

    An information model for “key” quality indicators of goods has been developed. This model is based on the assessment of f standardization existing state and the product labeling quality. According to the authors’ opinion, the proposed “key” indicators are the most significant for purchasing decision making. Customers will be able to use this model through their mobile technical devices. The developed model allows to decompose existing processes in data flows and to reveal the levels of possible architectural solutions. In-depth analysis of the presented information model decomposition levels will allow determining the stages of its improvement and to reveal additional indicators of the goods quality that are of interest to customers in the further research. Examining the architectural solutions for the customer’s information environment functioning when integrating existing databases will allow us to determine the boundaries of the model flexibility and customizability.

  11. Upscaling key ecosystem functions across the conterminous United States by a water‐centric ecosystem model

    Science.gov (United States)

    Ge Sun; Peter Caldwell; Asko Noormets; Steven G. McNulty; Erika Cohen; al. et.

    2011-01-01

    We developed a water‐centric monthly scale simulation model (WaSSI‐C) by integrating empirical water and carbon flux measurements from the FLUXNET network and an existing water supply and demand accounting model (WaSSI). The WaSSI‐C model was evaluated with basin‐scale evapotranspiration (ET), gross ecosystem productivity (GEP), and net ecosystem exchange (NEE)...

  12. IDENTIFYING OPERATIONAL REQUIREMENTS TO SELECT SUITABLE DECISION MODELS FOR A PUBLIC SECTOR EPROCUREMENT DECISION SUPPORT SYSTEM

    Directory of Open Access Journals (Sweden)

    Mohamed Adil

    2014-10-01

    Full Text Available Public sector procurement should be a transparent and fair process. Strict legal requirements are enforced on public sector procurement to make it a standardised process. To make fair decisions on selecting suppliers, a practical method which adheres to legal requirements is important. The research that is the base for this paper aimed at identifying a suitable Multi-Criteria Decision Analysis (MCDA method for the specific legal and functional needs of the Maldivian Public Sector. To identify such operational requirements, a set of focus group interviews were conducted in the Maldives with public officials responsible for procurement decision making. Based on the operational requirements identified through focus groups, criteria-based evaluation is done on published MCDA methods to identify the suitable methods for e-procurement decision making. This paper describes the identification of the operational requirements and the results of the evaluation to select suitable decision models for the Maldivian context.

  13. Modeling the Formation of Giant Planet Cores I: Evaluating Key Processes

    OpenAIRE

    Levison, H. F.; Thommes, E.; Duncan, M. J.

    2009-01-01

    One of the most challenging problems we face in our understanding of planet formation is how Jupiter and Saturn could have formed before the the solar nebula dispersed. The most popular model of giant planet formation is the so-called 'core accretion' model. In this model a large planetary embryo formed first, mainly by two-body accretion. This is then followed by a period of inflow of nebular gas directly onto the growing planet. The core accretion model has an Achilles heel, namely the very...

  14. Evaluation of unique identifiers used as keys to match identical publications in Pure and SciVal – a case study from health science [version 2; referees: 1 approved, 2 approved with reservations

    Directory of Open Access Journals (Sweden)

    Heidi Holst Madsen

    2016-09-01

    Full Text Available Unique identifiers (UID are seen as an effective key to match identical publications across databases or identify duplicates in a database. The objective of the present study is to investigate how well UIDs work as match keys in the integration between Pure and SciVal, based on a case with publications from the health sciences. We evaluate the matching process based on information about coverage, precision, and characteristics of publications matched versus not matched with UIDs as the match keys. We analyze this information to detect errors, if any, in the matching process. As an example we also briefly discuss how publication sets formed by using UIDs as the match keys may affect the bibliometric indicators number of publications, number of citations, and the average number of citations per publication.  The objective is addressed in a literature review and a case study. The literature review shows that only a few studies evaluate how well UIDs work as a match key. From the literature we identify four error types: Duplicate digital object identifiers (DOI, incorrect DOIs in reference lists and databases, DOIs not registered by the database where a bibliometric analysis is performed, and erroneous optical or special character recognition. The case study explores the use of UIDs in the integration between the databases Pure and SciVal. Specifically journal publications in English are matched between the two databases. We find all error types except erroneous optical or special character recognition in our publication sets. In particular the duplicate DOIs constitute a problem for the calculation of bibliometric indicators as both keeping the duplicates to improve the reliability of citation counts and deleting them to improve the reliability of publication counts will distort the calculation of average number of citations per publication. The use of UIDs as a match key in citation linking is implemented in many settings, and the availability of

  15. Identifying 'unhealthy' food advertising on television: a case study applying the UK Nutrient Profile model.

    Science.gov (United States)

    Jenkin, Gabrielle; Wilson, Nick; Hermanson, Nicole

    2009-05-01

    To evaluate the feasibility of the UK Nutrient Profile (NP) model for identifying 'unhealthy' food advertisements using a case study of New Zealand television advertisements. Four weeks of weekday television from 15.30 hours to 18.30 hours was videotaped from a state-owned (free-to-air) television channel popular with children. Food advertisements were identified and their nutritional information collected in accordance with the requirements of the NP model. Nutrient information was obtained from a variety of sources including food labels, company websites and a national nutritional database. From the 60 h sample of weekday afternoon television, there were 1893 advertisements, of which 483 were for food products or retailers. After applying the NP model, 66 % of these were classified as advertising high-fat, high-salt and high-sugar (HFSS) foods; 28 % were classified as advertising non-HFSS foods; and the remaining 2 % were unclassifiable. More than half (53 %) of the HFSS food advertisements were for 'mixed meal' items promoted by major fast-food franchises. The advertising of non-HFSS food was sparse, covering a narrow range of food groups, with no advertisements for fresh fruit or vegetables. Despite the NP model having some design limitations in classifying real-world televised food advertisements, it was easily applied to this sample and could clearly identify HFSS products. Policy makers who do not wish to completely restrict food advertising to children outright should consider using this NP model for regulating food advertising.

  16. Controls on the spatial variability of key soil properties: comparing field data with a mechanistic soilscape evolution model

    Science.gov (United States)

    Vanwalleghem, T.; Román, A.; Giraldez, J. V.

    2016-12-01

    There is a need for better understanding the processes influencing soil formation and the resulting distribution of soil properties. Soil properties can exhibit strong spatial variation, even at the small catchment scale. Especially soil carbon pools in semi-arid, mountainous areas are highly uncertain because bulk density and stoniness are very heterogeneous and rarely measured explicitly. In this study, we explore the spatial variability in key soil properties (soil carbon stocks, stoniness, bulk density and soil depth) as a function of processes shaping the critical zone (weathering, erosion, soil water fluxes and vegetation patterns). We also compare the potential of a geostatistical versus a mechanistic soil formation model (MILESD) for predicting these key soil properties. Soil core samples were collected from 67 locations at 6 depths. Total soil organic carbon stocks were 4.38 kg m-2. Solar radiation proved to be the key variable controlling soil carbon distribution. Stone content was mostly controlled by slope, indicating the importance of erosion. Spatial distribution of bulk density was found to be highly random. Finally, total carbon stocks were predicted using a random forest model whose main covariates were solar radiation and NDVI. The model predicts carbon stocks that are double as high on north versus south-facing slopes. However, validation showed that these covariates only explained 25% of the variation in the dataset. Apparently, present-day landscape and vegetation properties are not sufficient to fully explain variability in the soil carbon stocks in this complex terrain under natural vegetation. This is attributed to a high spatial variability in bulk density and stoniness, key variables controlling carbon stocks. Similar results were obtained with the mechanistic soil formation model MILESD, suggesting that more complex models might be needed to further explore this high spatial variability.

  17. Indistinguishability and identifiability of kinetic models for the MurC reaction in peptidoglycan biosynthesis.

    Science.gov (United States)

    Hattersley, J G; Pérez-Velázquez, J; Chappell, M J; Bearup, D; Roper, D; Dowson, C; Bugg, T; Evans, N D

    2011-11-01

    An important question in Systems Biology is the design of experiments that enable discrimination between two (or more) competing chemical pathway models or biological mechanisms. In this paper analysis is performed between two different models describing the kinetic mechanism of a three-substrate three-product reaction, namely the MurC reaction in the cytoplasmic phase of peptidoglycan biosynthesis. One model involves ordered substrate binding and ordered release of the three products; the competing model also assumes ordered substrate binding, but with fast release of the three products. The two versions are shown to be distinguishable; however, if standard quasi-steady-state assumptions are made distinguishability cannot be determined. Once model structure uniqueness is ensured the experimenter must determine if it is possible to successfully recover rate constant values given the experiment observations, a process known as structural identifiability. Structural identifiability analysis is carried out for both models to determine which of the unknown reaction parameters can be determined uniquely, or otherwise, from the ideal system outputs. This structural analysis forms an integrated step towards the modelling of the full pathway of the cytoplasmic phase of peptidoglycan biosynthesis. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

  18. Using cloud models of heartbeats as the entity identifier to secure mobile devices.

    Science.gov (United States)

    Fu, Donglai; Liu, Yanhua

    2017-01-01

    Mobile devices are extensively used to store more private and often sensitive information. Therefore, it is important to protect them against unauthorised access. Authentication ensures that authorised users can use mobile devices. However, traditional authentication methods, such as numerical or graphic passwords, are vulnerable to passive attacks. For example, an adversary can steal the password by snooping from a shorter distance. To avoid these problems, this study presents a biometric approach that uses cloud models of heartbeats as the entity identifier to secure mobile devices. Here, it is identified that these concepts including cloud model or cloud have nothing to do with cloud computing. The cloud model appearing in the study is the cognitive model. In the proposed method, heartbeats are collected by two ECG electrodes that are connected to one mobile device. The backward normal cloud generator is used to generate ECG standard cloud models characterising the heartbeat template. When a user tries to have access to their mobile device, cloud models regenerated by fresh heartbeats will be compared with ECG standard cloud models to determine if the current user can use this mobile device. This authentication method was evaluated from three aspects including accuracy, authentication time and energy consumption. The proposed method gives 86.04% of true acceptance rate with 2.73% of false acceptance rate. One authentication can be done in 6s, and this processing consumes about 2000 mW of power.

  19. Identifying best existing practice for characterization modeling in life cycle impact assessment

    DEFF Research Database (Denmark)

    Hauschild, Michael Zwicky; Goedkoop, Mark; Guinée, Jeroen

    2013-01-01

    Purpose: Life cycle impact assessment (LCIA) is a field of active development. The last decade has seen prolific publication of new impact assessment methods covering many different impact categories and providing characterization factors that often deviate from each other for the same substance...... and impact. The LCA standard ISO 14044 is rather general and unspecific in its requirements and offers little help to the LCA practitioner who needs to make a choice. With the aim to identify the best among existing characterization models and provide recommendations to the LCA practitioner, a study...... was performed for the Joint Research Centre of the European Commission (JRC). Methods Existing LCIA methods were collected and their individual characterization models identified at both midpoint and endpoint levels and supplemented with other environmental models of potential use for LCIA. No new developments...

  20. Identifying and quantifying energy savings on fired plant using low cost modelling techniques

    International Nuclear Information System (INIS)

    Tucker, Robert; Ward, John

    2012-01-01

    Research highlights: → Furnace models based on the zone method for radiation calculation are described. → Validated steady-state and transient models have been developed. → We show how these simple models can identify the best options for saving energy. → High emissivity coatings predicted to give performance enhancement on a fired heater. → Optimal heat recovery strategies on a steel reheating furnace are predicted. -- Abstract: Combustion in fired heaters, boilers and furnaces often accounts for the major energy consumption on industrial processes. Small improvements in efficiency can result in large reductions in energy consumption, CO 2 emissions, and operating costs. This paper will describe some useful low cost modelling techniques based on the zone method to help identify energy saving opportunities on high temperature fuel-fired process plant. The zone method has for many decades, been successfully applied to small batch furnaces through to large steel-reheating furnaces, glass tanks, boilers and fired heaters on petrochemical plant. Zone models can simulate both steady-state furnace operation and more complex transient operation typical of a production environment. These models can be used to predict thermal efficiency and performance, and more importantly, to assist in identifying and predicting energy saving opportunities from such measures as: ·Improving air/fuel ratio and temperature controls. ·Improved insulation. ·Use of oxygen or oxygen enrichment. ·Air preheating via flue gas heat recovery. ·Modification to furnace geometry and hearth loading. There is also increasing interest in the application of refractory coatings for increasing surface radiation in fired plant. All of the techniques can yield savings ranging from a few percent upwards and can deliver rapid financial payback, but their evaluation often requires robust and reliable models in order to increase confidence in making financial investment decisions. This paper gives

  1. Using exploratory regression to identify optimal driving factors for cellular automaton modeling of land use change.

    Science.gov (United States)

    Feng, Yongjiu; Tong, Xiaohua

    2017-09-22

    Defining transition rules is an important issue in cellular automaton (CA)-based land use modeling because these models incorporate highly correlated driving factors. Multicollinearity among correlated driving factors may produce negative effects that must be eliminated from the modeling. Using exploratory regression under pre-defined criteria, we identified all possible combinations of factors from the candidate factors affecting land use change. Three combinations that incorporate five driving factors meeting pre-defined criteria were assessed. With the selected combinations of factors, three logistic regression-based CA models were built to simulate dynamic land use change in Shanghai, China, from 2000 to 2015. For comparative purposes, a CA model with all candidate factors was also applied to simulate the land use change. Simulations using three CA models with multicollinearity eliminated performed better (with accuracy improvements about 3.6%) than the model incorporating all candidate factors. Our results showed that not all candidate factors are necessary for accurate CA modeling and the simulations were not sensitive to changes in statistically non-significant driving factors. We conclude that exploratory regression is an effective method to search for the optimal combinations of driving factors, leading to better land use change models that are devoid of multicollinearity. We suggest identification of dominant factors and elimination of multicollinearity before building land change models, making it possible to simulate more realistic outcomes.

  2. Genome-Wide Expression Profiling of Five Mouse Models Identifies Similarities and Differences with Human Psoriasis

    Science.gov (United States)

    Swindell, William R.; Johnston, Andrew; Carbajal, Steve; Han, Gangwen; Wohn, Christian; Lu, Jun; Xing, Xianying; Nair, Rajan P.; Voorhees, John J.; Elder, James T.; Wang, Xiao-Jing; Sano, Shigetoshi; Prens, Errol P.; DiGiovanni, John; Pittelkow, Mark R.; Ward, Nicole L.; Gudjonsson, Johann E.

    2011-01-01

    Development of a suitable mouse model would facilitate the investigation of pathomechanisms underlying human psoriasis and would also assist in development of therapeutic treatments. However, while many psoriasis mouse models have been proposed, no single model recapitulates all features of the human disease, and standardized validation criteria for psoriasis mouse models have not been widely applied. In this study, whole-genome transcriptional profiling is used to compare gene expression patterns manifested by human psoriatic skin lesions with those that occur in five psoriasis mouse models (K5-Tie2, imiquimod, K14-AREG, K5-Stat3C and K5-TGFbeta1). While the cutaneous gene expression profiles associated with each mouse phenotype exhibited statistically significant similarity to the expression profile of psoriasis in humans, each model displayed distinctive sets of similarities and differences in comparison to human psoriasis. For all five models, correspondence to the human disease was strong with respect to genes involved in epidermal development and keratinization. Immune and inflammation-associated gene expression, in contrast, was more variable between models as compared to the human disease. These findings support the value of all five models as research tools, each with identifiable areas of convergence to and divergence from the human disease. Additionally, the approach used in this paper provides an objective and quantitative method for evaluation of proposed mouse models of psoriasis, which can be strategically applied in future studies to score strengths of mouse phenotypes relative to specific aspects of human psoriasis. PMID:21483750

  3. A New Algorithm for Identifying Cis-Regulatory Modules Based on Hidden Markov Model

    Directory of Open Access Journals (Sweden)

    Haitao Guo

    2017-01-01

    Full Text Available The discovery of cis-regulatory modules (CRMs is the key to understanding mechanisms of transcription regulation. Since CRMs have specific regulatory structures that are the basis for the regulation of gene expression, how to model the regulatory structure of CRMs has a considerable impact on the performance of CRM identification. The paper proposes a CRM discovery algorithm called ComSPS. ComSPS builds a regulatory structure model of CRMs based on HMM by exploring the rules of CRM transcriptional grammar that governs the internal motif site arrangement of CRMs. We test ComSPS on three benchmark datasets and compare it with five existing methods. Experimental results show that ComSPS performs better than them.

  4. A New Algorithm for Identifying Cis-Regulatory Modules Based on Hidden Markov Model

    Science.gov (United States)

    2017-01-01

    The discovery of cis-regulatory modules (CRMs) is the key to understanding mechanisms of transcription regulation. Since CRMs have specific regulatory structures that are the basis for the regulation of gene expression, how to model the regulatory structure of CRMs has a considerable impact on the performance of CRM identification. The paper proposes a CRM discovery algorithm called ComSPS. ComSPS builds a regulatory structure model of CRMs based on HMM by exploring the rules of CRM transcriptional grammar that governs the internal motif site arrangement of CRMs. We test ComSPS on three benchmark datasets and compare it with five existing methods. Experimental results show that ComSPS performs better than them. PMID:28497059

  5. Data warehouse model for monitoring key performance indicators (KPIs) using goal oriented approach

    Science.gov (United States)

    Abdullah, Mohammed Thajeel; Ta'a, Azman; Bakar, Muhamad Shahbani Abu

    2016-08-01

    The growth and development of universities, just as other organizations, depend on their abilities to strategically plan and implement development blueprints which are in line with their vision and mission statements. The actualizations of these statements, which are often designed into goals and sub-goals and linked to their respective actors are better measured by defining key performance indicators (KPIs) of the university. The proposes ReGADaK, which is an extended the GRAnD approach highlights the facts, dimensions, attributes, measures and KPIs of the organization. The measures from the goal analysis of this unit serve as the basis of developing the related university's KPIs. The proposed data warehouse schema is evaluated through expert review, prototyping and usability evaluation. The findings from the evaluation processes suggest that the proposed data warehouse schema is suitable for monitoring the University's KPIs.

  6. Tumor xenograft modeling identifies an association between TCF4 loss and breast cancer chemoresistance

    Directory of Open Access Journals (Sweden)

    Gorka Ruiz de Garibay

    2018-05-01

    Full Text Available Understanding the mechanisms of cancer therapeutic resistance is fundamental to improving cancer care. There is clear benefit from chemotherapy in different breast cancer settings; however, knowledge of the mutations and genes that mediate resistance is incomplete. In this study, by modeling chemoresistance in patient-derived xenografts (PDXs, we show that adaptation to therapy is genetically complex and identify that loss of transcription factor 4 (TCF4; also known as ITF2 is associated with this process. A triple-negative BRCA1-mutated PDX was used to study the genetics of chemoresistance. The PDX was treated in parallel with four chemotherapies for five iterative cycles. Exome sequencing identified few genes with de novo or enriched mutations in common among the different therapies, whereas many common depleted mutations/genes were observed. Analysis of somatic mutations from The Cancer Genome Atlas (TCGA supported the prognostic relevance of the identified genes. A mutation in TCF4 was found de novo in all treatments, and analysis of drug sensitivity profiles across cancer cell lines supported the link to chemoresistance. Loss of TCF4 conferred chemoresistance in breast cancer cell models, possibly by altering cell cycle regulation. Targeted sequencing in chemoresistant tumors identified an intronic variant of TCF4 that may represent an expression quantitative trait locus associated with relapse outcome in TCGA. Immunohistochemical studies suggest a common loss of nuclear TCF4 expression post-chemotherapy. Together, these results from tumor xenograft modeling depict a link between altered TCF4 expression and breast cancer chemoresistance.

  7. Key West, Florida 1/3 Arc-second NAVD 88 Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  8. models of hourly dry bulb temperature and relative humidity of key

    African Journals Online (AJOL)

    user

    3: Worst cases of MFE for Dry bulb temperature and Relative humidity. Fig. 4: Best cases of ... the Second Joint International Conference of. University of Ilorin, Ilorin, Nigeria and University ... Erbs, D. G., “Models and Applications for Weather.

  9. Key West, Florida 1/3 Arc-second MHW Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  10. Identifying and Classifying Mobile Business Models Based on Meta-Synthesis Approach

    Directory of Open Access Journals (Sweden)

    Porrandokht Niroomand

    2012-03-01

    Full Text Available The appearance of mobile has provided unique opportunities and fields through the development and creation of businesses and has been able to create the new job opportunities. The current research tries to familiarize entrepreneures who are running the businesses especially in the area of mobile services with business models. These business models can familiarize them for implementing the new ideas and designs since they can enter to business market. Searching in many papers shows that there are no propitiated papers and researches that can identify, categorize and analyze the mobile business models. Consequently, this paper involves innovation. The first part of this paper presents the review about the concepts and theories about the different mobile generations, the mobile commerce and business models. Afterwards, 92 models are compared, interpreted, translated and combined using 33 papers, books based on two different criteria that are expert criterion and kind of product criterion. In the classification of models according to models that are presented by experts, the models are classified based on criteria such as business fields, business partners, the rate of dynamism, the kind of activity, the focus areas, the mobile generations, transparency, the type of operator activities, marketing and advertisements. The models that are classified based on the kind of product have been analyzed and classified at four different areas of mobile commerce including the content production, technology (software and hardware, network and synthetic.

  11. Methodology for identifying parameters for the TRNSYS model Type 210 - wood pellet stoves and boilers

    Energy Technology Data Exchange (ETDEWEB)

    Persson, Tomas; Fiedler, Frank; Nordlander, Svante

    2006-05-15

    This report describes a method how to perform measurements on boilers and stoves and how to identify parameters from the measurements for the boiler/stove-model TRNSYS Type 210. The model can be used for detailed annual system simulations using TRNSYS. Experience from measurements on three different pellet stoves and four boilers were used to develop this methodology. Recommendations for the set up of measurements are given and the required combustion theory for the data evaluation and data preparation are given. The data evaluation showed that the uncertainties are quite large for the measured flue gas flow rate and for boilers and stoves with high fraction of energy going to the water jacket also the calculated heat rate to the room may have large uncertainties. A methodology for the parameter identification process and identified parameters for two different stoves and three boilers are given. Finally the identified models are compared with measured data showing that the model generally agreed well with measured data during both stationary and dynamic conditions.

  12. Modelling the exposure of wildlife to radiation: key findings and activities of IAEA working groups

    Energy Technology Data Exchange (ETDEWEB)

    Beresford, Nicholas A. [NERC Centre for Ecology and Hydrology, Lancaster Environment Center, Library Av., Bailrigg, Lancaster, LA1 4AP (United Kingdom); School of Environment and Life Sciences, University of Salford, Manchester, M4 4WT (United Kingdom); Vives i Batlle, Jordi; Vandenhove, Hildegarde [Belgian Nuclear Research Centre, Belgian Nuclear Research Centre, Boeretang 200, 2400 Mol (Belgium); Beaugelin-Seiller, Karine [Institut de Radioprotection et de Surete Nucleaire (IRSN), PRP-ENV, SERIS, LM2E, Cadarache (France); Johansen, Mathew P. [ANSTO Australian Nuclear Science and Technology Organisation, New Illawarra Rd, Menai, NSW (Australia); Goulet, Richard [Canadian Nuclear Safety Commission, Environmental Risk Assessment Division, 280 Slater, Ottawa, K1A0H3 (Canada); Wood, Michael D. [School of Environment and Life Sciences, University of Salford, Manchester, M4 4WT (United Kingdom); Ruedig, Elizabeth [Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins (United States); Stark, Karolina; Bradshaw, Clare [Department of Ecology, Environment and Plant Sciences, Stockholm University, SE-10691 (Sweden); Andersson, Pal [Swedish Radiation Safety Authority, SE-171 16, Stockholm (Sweden); Copplestone, David [Biological and Environmental Sciences, University of Stirling, Stirling, FK9 4LA (United Kingdom); Yankovich, Tamara L.; Fesenko, Sergey [International Atomic Energy Agency, Vienna International Centre, 1400, Vienna (Austria)

    2014-07-01

    In total, participants from 14 countries, representing 19 organisations, actively participated in the model application/inter-comparison activities of the IAEA's EMRAS II programme Biota Modelling Group. A range of models/approaches were used by participants (e.g. the ERICA Tool, RESRAD-BIOTA, the ICRP Framework). The agreed objectives of the group were: 'To improve Member State's capabilities for protection of the environment by comparing and validating models being used, or developed, for biota dose assessment (that may be used) as part of the regulatory process of licensing and compliance monitoring of authorised releases of radionuclides.' The activities of the group, the findings of which will be described, included: - An assessment of the predicted unweighted absorbed dose rates for 74 radionuclides estimated by 10 approaches for five of the ICRPs Reference Animal and Plant geometries assuming 1 Bq per unit organism or media. - Modelling the effect of heterogeneous distributions of radionuclides in sediment profiles on the estimated exposure of organisms. - Model prediction - field data comparisons for freshwater ecosystems in a uranium mining area and a number of wetland environments. - An evaluation of the application of available models to a scenario considering radioactive waste buried in shallow trenches. - Estimating the contribution of {sup 235}U to dose rates in freshwater environments. - Evaluation of the factors contributing to variation in modelling results. The work of the group continues within the framework of the IAEA's MODARIA programme, which was initiated in 2012. The work plan of the MODARIA working group has largely been defined by the findings of the previous EMRAS programme. On-going activities of the working group, which will be described, include the development of a database of dynamic parameters for wildlife dose assessment and exercises involving modelling the exposure of organisms in the marine coastal

  13. Identifying data gaps and prioritizing restoration strategies for Fremont cottonwood using linked geomorphic and population models

    Science.gov (United States)

    Harper, E. B.; Stella, J. C.; Fremier, A. K.

    2009-12-01

    Fremont cottonwood (Populus fremontii) is an important component of semi-arid riparian ecosystems throughout western North America, but its populations are in decline due to flow regulation. Achieving a balance between human resource needs and riparian ecosystem function requires a mechanistic understanding of the multiple geomorphic and biological factors affecting tree recruitment and survival, including the timing and magnitude of river flows, and the concomitant influence on suitable habitat creation and mortality from scour and sedimentation burial. Despite a great deal of empirical research on some components of the system, such as factors affecting cottonwood recruitment, other key components are less studied. Yet understanding the relative influence of the full suite of physical and life-history drivers is critical to modeling whole-population dynamics under changing environmental conditions. We addressed these issues for the Fremont cottonwood population along the Sacramento River, CA using a sensitivity analysis approach to quantify uncertainty in parameters on the outcomes of a patch-based, dynamic population model. Using a broad range of plausible values for 15 model parameters that represent key physical, biological and climatic components of the ecosystem, we ran 1,000 population simulations that consisted of a subset of 14.3 million possible combinations of parameter estimates to predict the frequency of patch colonization and total forest habitat predicted to occur under current hydrologic conditions after 175 years. Results indicate that Fremont cottonwood populations are highly sensitive to the interactions among flow regime, sedimentation rate and the depth of the capillary fringe (Fig. 1). Estimates of long-term floodplain sedimentation rate would substantially improve model accuracy. Spatial variation in sediment texture was also important to the extent that it determines the depth of the capillary fringe, which regulates the availability of

  14. Animal Models of Diabetic Macrovascular Complications: Key Players in the Development of New Therapeutic Approaches

    Directory of Open Access Journals (Sweden)

    Suvi E. Heinonen

    2015-01-01

    Full Text Available Diabetes mellitus is a lifelong, incapacitating metabolic disease associated with chronic macrovascular complications (coronary heart disease, stroke, and peripheral vascular disease and microvascular disorders leading to damage of the kidneys (nephropathy and eyes (retinopathy. Based on the current trends, the rising prevalence of diabetes worldwide will lead to increased cardiovascular morbidity and mortality. Therefore, novel means to prevent and treat these complications are needed. Under the auspices of the IMI (Innovative Medicines Initiative, the SUMMIT (SUrrogate markers for Micro- and Macrovascular hard end points for Innovative diabetes Tools consortium is working on the development of novel animal models that better replicate vascular complications of diabetes and on the characterization of the available models. In the past years, with the high level of genomic information available and more advanced molecular tools, a very large number of models has been created. Selecting the right model for a specific study is not a trivial task and will have an impact on the study results and their interpretation. This review gathers information on the available experimental animal models of diabetic macrovascular complications and evaluates their pros and cons for research purposes as well as for drug development.

  15. TRI Microspheres prevent key signs of dry eye disease in a murine, inflammatory model.

    Science.gov (United States)

    Ratay, Michelle L; Balmert, Stephen C; Acharya, Abhinav P; Greene, Ashlee C; Meyyappan, Thiagarajan; Little, Steven R

    2017-12-13

    Dry eye disease (DED) is a highly prevalent, ocular disorder characterized by an abnormal tear film and ocular surface. Recent experimental data has suggested that the underlying pathology of DED involves inflammation of the lacrimal functional unit (LFU), comprising the cornea, conjunctiva, lacrimal gland and interconnecting innervation. This inflammation of the LFU ultimately results in tissue deterioration and the symptoms of DED. Moreover, an increase of pathogenic lymphocyte infiltration and the secretion of pro-inflammatory cytokines are involved in the propagation of DED-associated inflammation. Studies have demonstrated that the adoptive transfer of regulatory T cells (Tregs) can mediate the inflammation caused by pathogenic lymphocytes. Thus, as an approach to treating the inflammation associated with DED, we hypothesized that it was possible to enrich the body's own endogenous Tregs by locally delivering a specific combination of Treg inducing factors through degradable polymer microspheres (TRI microspheres; TGF-β1, Rapamycin (Rapa), and IL-2). This local controlled release system is capable of shifting the balance of Treg/T effectors and, in turn, preventing key signs of dry eye disease such as aqueous tear secretion, conjunctival goblet cells, epithelial corneal integrity, and reduce the pro-inflammatory cytokine milieu in the tissue.

  16. Emporium Model: The Key to Content Retention in Secondary Math Courses

    Directory of Open Access Journals (Sweden)

    Sandra Wilder

    2016-07-01

    Full Text Available The math emporium model was first developed by Virginia Tech in 1999. In the emporium model students use computer-based learning resources, engage in active learning, and work toward mastery of concepts. This approach to teaching and learning mathematics was piloted in a rural STEM high school. The purpose of this experimental study was to compare the impact of the emporium model and the traditional approach to instruction on student achievement and retention of algebra. The results indicated that both approaches to instruction were equally effective in improving student mathematics knowledge. However, the findings revealed that the students in the emporium section had significantly higher retention of the content knowledge.

  17. Novel personalized pathway-based metabolomics models reveal key metabolic pathways for breast cancer diagnosis

    DEFF Research Database (Denmark)

    Huang, Sijia; Chong, Nicole; Lewis, Nathan

    2016-01-01

    diagnosis. We applied this method to predict breast cancer occurrence, in combination with correlation feature selection (CFS) and classification methods. Results: The resulting all-stage and early-stage diagnosis models are highly accurate in two sets of testing blood samples, with average AUCs (Area Under.......993. Moreover, important metabolic pathways, such as taurine and hypotaurine metabolism and the alanine, aspartate, and glutamate pathway, are revealed as critical biological pathways for early diagnosis of breast cancer. Conclusions: We have successfully developed a new type of pathway-based model to study...... metabolomics data for disease diagnosis. Applying this method to blood-based breast cancer metabolomics data, we have discovered crucial metabolic pathway signatures for breast cancer diagnosis, especially early diagnosis. Further, this modeling approach may be generalized to other omics data types for disease...

  18. Explaining electric conductivity using the particle-in-a-box model: quantum superposition is the key

    Science.gov (United States)

    Sivanesan, Umaseh; Tsang, Kin; Izmaylov, Artur F.

    2017-12-01

    Most of the textbooks explaining electric conductivity in the context of quantum mechanics provide either incomplete or semi-classical explanations that are not connected with the elementary concepts of quantum mechanics. We illustrate the conduction phenomena using the simplest model system in quantum dynamics, a particle in a box (PIB). To induce the particle dynamics, a linear potential tilting the bottom of the box is introduced, which is equivalent to imposing a constant electric field for a charged particle. Although the PIB model represents a closed system that cannot have a flow of electrons through the system, we consider the oscillatory dynamics of the particle probability density as the analogue of the electric current. Relating the amplitude and other parameters of the particle oscillatory dynamics with the gap between the ground and excited states of the PIB model allows us to demonstrate one of the most basic dependencies of electric conductivity on the valence-conduction band gap of the material.

  19. Identifying and Modeling Dynamic Preference Evolution in Multipurpose Water Resources Systems

    Science.gov (United States)

    Mason, E.; Giuliani, M.; Castelletti, A.; Amigoni, F.

    2018-04-01

    Multipurpose water systems are usually operated on a tradeoff of conflicting operating objectives. Under steady state climatic and socioeconomic conditions, such tradeoff is supposed to represent a fair and/or efficient preference. Extreme variability in external forcing might affect water operators' risk aversion and force a change in her/his preference. Properly accounting for these shifts is key to any rigorous retrospective assessment of the operator's behaviors, and to build descriptive models for projecting the future system evolution. In this study, we explore how the selection of different preferences is linked to variations in the external forcing. We argue that preference selection evolves according to recent, extreme variations in system performance: underperforming in one of the objectives pushes the preference toward the harmed objective. To test this assumption, we developed a rational procedure to simulate the operator's preference selection. We map this selection onto a multilateral negotiation, where multiple virtual agents independently optimize different objectives. The agents periodically negotiate a compromise policy for the operation of the system. Agents' attitudes in each negotiation step are determined by the recent system performance measured by the specific objective they maximize. We then propose a numerical model of preference dynamics that implements a concept from cognitive psychology, the availability bias. We test our modeling framework on a synthetic lake operated for flood control and water supply. Results show that our model successfully captures the operator's preference selection and dynamic evolution driven by extreme wet and dry situations.

  20. A business planning model to identify new safety net clinic locations.

    Science.gov (United States)

    Langabeer, James; Helton, Jeffrey; DelliFraine, Jami; Dotson, Ebbin; Watts, Carolyn; Love, Karen

    2014-01-01

    Community health clinics serving the poor and underserved are geographically expanding due to changes in U.S. health care policy. This paper describes the experience of a collaborative alliance of health care providers in a large metropolitan area who develop a conceptual and mathematical decision model to guide decisions on expanding its network of community health clinics. Community stakeholders participated in a collaborative process that defined constructs they deemed important in guiding decisions on the location of community health clinics. This collaboration also defined key variables within each construct. Scores for variables within each construct were then totaled and weighted into a community-specific optimal space planning equation. This analysis relied entirely on secondary data available from published sources. The model built from this collaboration revolved around the constructs of demand, sustainability, and competition. It used publicly available data defining variables within each construct to arrive at an optimal location that maximized demand and sustainability and minimized competition. This is a model that safety net clinic planners and community stakeholders can use to analyze demographic and utilization data to optimize capacity expansion to serve uninsured and Medicaid populations. Communities can use this innovative model to develop a locally relevant clinic location-planning framework.

  1. A Study of Scientometric Methods to Identify Emerging Technologies via Modeling of Milestones

    Energy Technology Data Exchange (ETDEWEB)

    Abercrombie, Robert K [ORNL; Udoeyop, Akaninyene W [ORNL; Schlicher, Bob G [ORNL

    2012-01-01

    This work examines a scientometric model that tracks the emergence of an identified technology from initial discovery (via original scientific and conference literature), through critical discoveries (via original scientific, conference literature and patents), transitioning through Technology Readiness Levels (TRLs) and ultimately on to commercial application. During the period of innovation and technology transfer, the impact of scholarly works, patents and on-line web news sources are identified. As trends develop, currency of citations, collaboration indicators, and on-line news patterns are identified. The combinations of four distinct and separate searchable on-line networked sources (i.e., scholarly publications and citation, patents, news archives, and online mapping networks) are assembled to become one collective network (a dataset for analysis of relations). This established network becomes the basis from which to quickly analyze the temporal flow of activity (searchable events) for the example subject domain we investigated.

  2. Use of model plant hosts to identify Pseudomonas aeruginosa virulence factors

    Science.gov (United States)

    Rahme, Laurence G.; Tan, Man-Wah; Le, Long; Wong, Sandy M.; Tompkins, Ronald G.; Calderwood, Stephen B.; Ausubel, Frederick M.

    1997-01-01

    We used plants as an in vivo pathogenesis model for the identification of virulence factors of the human opportunistic pathogen Pseudomonas aeruginosa. Nine of nine TnphoA mutant derivatives of P. aeruginosa strain UCBPP-PA14 that were identified in a plant leaf assay for less pathogenic mutants also exhibited significantly reduced pathogenicity in a burned mouse pathogenicity model, suggesting that P. aeruginosa utilizes common strategies to infect both hosts. Seven of these nine mutants contain TnphoA insertions in previously unknown genes. These results demonstrate that an alternative nonvertebrate host of a human bacterial pathogen can be used in an in vivo high throughput screen to identify novel bacterial virulence factors involved in mammalian pathogenesis. PMID:9371831

  3. Identify High-Quality Protein Structural Models by Enhanced K-Means.

    Science.gov (United States)

    Wu, Hongjie; Li, Haiou; Jiang, Min; Chen, Cheng; Lv, Qiang; Wu, Chuang

    2017-01-01

    Background. One critical issue in protein three-dimensional structure prediction using either ab initio or comparative modeling involves identification of high-quality protein structural models from generated decoys. Currently, clustering algorithms are widely used to identify near-native models; however, their performance is dependent upon different conformational decoys, and, for some algorithms, the accuracy declines when the decoy population increases. Results. Here, we proposed two enhanced K -means clustering algorithms capable of robustly identifying high-quality protein structural models. The first one employs the clustering algorithm SPICKER to determine the initial centroids for basic K -means clustering ( SK -means), whereas the other employs squared distance to optimize the initial centroids ( K -means++). Our results showed that SK -means and K -means++ were more robust as compared with SPICKER alone, detecting 33 (59%) and 42 (75%) of 56 targets, respectively, with template modeling scores better than or equal to those of SPICKER. Conclusions. We observed that the classic K -means algorithm showed a similar performance to that of SPICKER, which is a widely used algorithm for protein-structure identification. Both SK -means and K -means++ demonstrated substantial improvements relative to results from SPICKER and classical K -means.

  4. Key features of the IPSL ocean atmosphere model and its sensitivity to atmospheric resolution

    Energy Technology Data Exchange (ETDEWEB)

    Marti, Olivier; Braconnot, P.; Bellier, J.; Brockmann, P.; Caubel, A.; Noblet, N. de; Friedlingstein, P.; Idelkadi, A.; Kageyama, M. [Unite Mixte CEA-CNRS-UVSQ, IPSL/LSCE, Gif-sur-Yvette Cedex (France); Dufresne, J.L.; Bony, S.; Codron, F.; Fairhead, L.; Grandpeix, J.Y.; Hourdin, F.; Musat, I. [Unite Mixte CNRS-Ecole Polytechnique-ENS-UPCM, IPSL/LMD, Paris Cedex 05 (France); Benshila, R.; Guilyardi, E.; Levy, C.; Madec, G.; Mignot, J.; Talandier, C. [unite mixte CNRS-IRD-UPMC, IPLS/LOCEAN, Paris Cedex 05 (France); Cadule, P.; Denvil, S.; Foujols, M.A. [Institut Pierre Simon Laplace des Sciences de l' Environnement (IPSL), Paris Cedex 05 (France); Fichefet, T.; Goosse, H. [Universite Catholique de Louvain, Institut d' Astronomie et de Geophysique Georges Lemaitre, Louvain-la-Neuve (Belgium); Krinner, G. [Unite mixte CNRS-UJF Grenoble, LGGE, BP96, Saint-Martin-d' Heres (France); Swingedouw, D. [CNRS/CERFACS, Toulouse (France)

    2010-01-15

    This paper presents the major characteristics of the Institut Pierre Simon Laplace (IPSL) coupled ocean-atmosphere general circulation model. The model components and the coupling methodology are described, as well as the main characteristics of the climatology and interannual variability. The model results of the standard version used for IPCC climate projections, and for intercomparison projects like the Paleoclimate Modeling Intercomparison Project (PMIP 2) are compared to those with a higher resolution in the atmosphere. A focus on the North Atlantic and on the tropics is used to address the impact of the atmosphere resolution on processes and feedbacks. In the North Atlantic, the resolution change leads to an improved representation of the storm-tracks and the North Atlantic oscillation. The better representation of the wind structure increases the northward salt transports, the deep-water formation and the Atlantic meridional overturning circulation. In the tropics, the ocean-atmosphere dynamical coupling, or Bjerknes feedback, improves with the resolution. The amplitude of ENSO (El Nino-Southern oscillation) consequently increases, as the damping processes are left unchanged. (orig.)

  5. Integrating semantics and procedural generation: key enabling factors for declarative modeling of virtual worlds

    NARCIS (Netherlands)

    Bidarra, R.; Kraker, K.J. de; Smelik, R.M.; Tutenel, T.

    2010-01-01

    Manual content creation for virtual worlds can no longer satisfy the increasing demand arising from areas as entertainment and serious games, simulations, movies, etc. Furthermore, currently deployed modeling tools basically do not scale up: while they become more and more specialized and complex,

  6. A computational technique to identify the optimal stiffness matrix for a discrete nuclear fuel assembly model

    International Nuclear Information System (INIS)

    Park, Nam-Gyu; Kim, Kyoung-Joo; Kim, Kyoung-Hong; Suh, Jung-Min

    2013-01-01

    Highlights: ► An identification method of the optimal stiffness matrix for a fuel assembly structure is discussed. ► The least squares optimization method is introduced, and a closed form solution of the problem is derived. ► The method can be expanded to the system with the limited number of modes. ► Identification error due to the perturbed mode shape matrix is analyzed. ► Verification examples show that the proposed procedure leads to a reliable solution. -- Abstract: A reactor core structural model which is used to evaluate the structural integrity of the core contains nuclear fuel assembly models. Since the reactor core consists of many nuclear fuel assemblies, the use of a refined fuel assembly model leads to a considerable amount of computing time for performing nonlinear analyses such as the prediction of seismic induced vibration behaviors. The computational time could be reduced by replacing the detailed fuel assembly model with a simplified model that has fewer degrees of freedom, but the dynamic characteristics of the detailed model must be maintained in the simplified model. Such a model based on an optimal design method is proposed in this paper. That is, when a mass matrix and a mode shape matrix are given, the optimal stiffness matrix of a discrete fuel assembly model can be estimated by applying the least squares minimization method. The verification of the method is completed by comparing test results and simulation results. This paper shows that the simplified model's dynamic behaviors are quite similar to experimental results and that the suggested method is suitable for identifying reliable mathematical model for fuel assemblies

  7. Endogenous superoxide is a key effector of the oxygen sensitivity of a model obligate anaerobe.

    Science.gov (United States)

    Lu, Zheng; Sethu, Ramakrishnan; Imlay, James A

    2018-04-03

    It has been unclear whether superoxide and/or hydrogen peroxide play important roles in the phenomenon of obligate anaerobiosis. This question was explored using Bacteroides thetaiotaomicron , a major fermentative bacterium in the human gastrointestinal tract. Aeration inactivated two enzyme families-[4Fe-4S] dehydratases and nonredox mononuclear iron enzymes-whose homologs, in contrast, remain active in aerobic Escherichia coli Inactivation-rate measurements of one such enzyme, B. thetaiotaomicron fumarase, showed that it is no more intrinsically sensitive to oxidants than is an E. coli fumarase. Indeed, when the E. coli enzymes were expressed in B. thetaiotaomicron , they no longer could tolerate aeration; conversely, the B. thetaiotaomicron enzymes maintained full activity when expressed in aerobic E. coli Thus, the aerobic inactivation of the B. thetaiotaomicron enzymes is a feature of their intracellular environment rather than of the enzymes themselves. B. thetaiotaomicron possesses superoxide dismutase and peroxidases, and it can repair damaged enzymes. However, measurements confirmed that the rate of reactive oxygen species production inside aerated B. thetaiotaomicron is far higher than in E. coli Analysis of the damaged enzymes recovered from aerated B. thetaiotaomicron suggested that they had been inactivated by superoxide rather than by hydrogen peroxide. Accordingly, overproduction of superoxide dismutase substantially protected the enzymes from aeration. We conclude that when this anaerobe encounters oxygen, its internal superoxide levels rise high enough to inactivate key catabolic and biosynthetic enzymes. Superoxide thus comprises a major element of the oxygen sensitivity of this anaerobe. The extent to which molecular oxygen exerts additional direct effects remains to be determined.

  8. A data-driven modeling approach to identify disease-specific multi-organ networks driving physiological dysregulation.

    Directory of Open Access Journals (Sweden)

    Warren D Anderson

    2017-07-01

    Full Text Available Multiple physiological systems interact throughout the development of a complex disease. Knowledge of the dynamics and connectivity of interactions across physiological systems could facilitate the prevention or mitigation of organ damage underlying complex diseases, many of which are currently refractory to available therapeutics (e.g., hypertension. We studied the regulatory interactions operating within and across organs throughout disease development by integrating in vivo analysis of gene expression dynamics with a reverse engineering approach to infer data-driven dynamic network models of multi-organ gene regulatory influences. We obtained experimental data on the expression of 22 genes across five organs, over a time span that encompassed the development of autonomic nervous system dysfunction and hypertension. We pursued a unique approach for identification of continuous-time models that jointly described the dynamics and structure of multi-organ networks by estimating a sparse subset of ∼12,000 possible gene regulatory interactions. Our analyses revealed that an autonomic dysfunction-specific multi-organ sequence of gene expression activation patterns was associated with a distinct gene regulatory network. We analyzed the model structures for adaptation motifs, and identified disease-specific network motifs involving genes that exhibited aberrant temporal dynamics. Bioinformatic analyses identified disease-specific single nucleotide variants within or near transcription factor binding sites upstream of key genes implicated in maintaining physiological homeostasis. Our approach illustrates a novel framework for investigating the pathogenesis through model-based analysis of multi-organ system dynamics and network properties. Our results yielded novel candidate molecular targets driving the development of cardiovascular disease, metabolic syndrome, and immune dysfunction.

  9. Cultural Branding as a Key in Positioning Schools: A Conceptual Model

    Directory of Open Access Journals (Sweden)

    Hidayatun

    2017-08-01

    Full Text Available The increase of people’s prosperity and education creates a change in their view about education and the need towards it. Consequently, their choice of educational institutions becomes more selective. On the other hand, the competition in this field becomes more viable due to the growth of the educational institutions. The management strategy should be evaluated. This paper discusses the interfaces between culture and school, especially those that refer to the branding. The study was carried out on a premise that creating a bond between the school and community is possible by adopting the culture in a formal education environment. This effort is expected to help schools to get a certain position in the community. Therefore, this study attempts to promote a conceptual model of cultural branding in schools and to reveal the reasons why the model becomes an effective marketing strategy in this era.

  10. Scenario-Led Habitat Modelling of Land Use Change Impacts on Key Species.

    Directory of Open Access Journals (Sweden)

    Matthew Geary

    Full Text Available Accurate predictions of the impacts of future land use change on species of conservation concern can help to inform policy-makers and improve conservation measures. If predictions are spatially explicit, predicted consequences of likely land use changes could be accessible to land managers at a scale relevant to their working landscape. We introduce a method, based on open source software, which integrates habitat suitability modelling with scenario-building, and illustrate its use by investigating the effects of alternative land use change scenarios on landscape suitability for black grouse Tetrao tetrix. Expert opinion was used to construct five near-future (twenty years scenarios for the 800 km2 study site in upland Scotland. For each scenario, the cover of different land use types was altered by 5-30% from 20 random starting locations and changes in habitat suitability assessed by projecting a MaxEnt suitability model onto each simulated landscape. A scenario converting grazed land to moorland and open forestry was the most beneficial for black grouse, and 'increased grazing' (the opposite conversion the most detrimental. Positioning of new landscape blocks was shown to be important in some situations. Increasing the area of open-canopy forestry caused a proportional decrease in suitability, but suitability gains for the 'reduced grazing' scenario were nonlinear. 'Scenario-led' landscape simulation models can be applied in assessments of the impacts of land use change both on individual species and also on diversity and community measures, or ecosystem services. A next step would be to include landscape configuration more explicitly in the simulation models, both to make them more realistic, and to examine the effects of habitat placement more thoroughly. In this example, the recommended policy would be incentives on grazing reduction to benefit black grouse.

  11. MODELING THE FORMATION OF GIANT PLANET CORES. I. EVALUATING KEY PROCESSES

    International Nuclear Information System (INIS)

    Levison, Harold F.; Thommes, Edward; Duncan, Martin J.

    2010-01-01

    One of the most challenging problems we face in our understanding of planet formation is how Jupiter and Saturn could have formed before the solar nebula dispersed. The most popular model of giant planet formation is the so-called core accretion model. In this model a large planetary embryo formed first, mainly by two-body accretion. This is then followed by a period of inflow of nebular gas directly onto the growing planet. The core accretion model has an Achilles heel, namely the very first step. We have undertaken the most comprehensive study of this process to date. In this study, we numerically integrate the orbits of a number of planetary embryos embedded in a swarm of planetesimals. In these experiments, we have included a large number of physical processes that might enhance accretion. In particular, we have included (1) aerodynamic gas drag, (2) collisional damping between planetesimals, (3) enhanced embryo cross sections due to their atmospheres, (4) planetesimal fragmentation, and (5) planetesimal-driven migration. We find that the gravitational interaction between the embryos and the planetesimals leads to the wholesale redistribution of material-regions are cleared of material and gaps open near the embryos. Indeed, in 90% of our simulations without fragmentation, the region near those embryos is cleared of planetesimals before much growth can occur. Thus, the widely used assumption that the surface density distribution of planetesimals is smooth can lead to misleading results. In the remaining 10% of our simulations, the embryos undergo a burst of outward migration that significantly increases growth. On timescales of ∼10 5 years, the outer embryo can migrate ∼6 AU and grow to roughly 30 M + . This represents a largely unexplored mode of core formation. We also find that the inclusion of planetesimal fragmentation tends to inhibit growth except for a narrow range of fragment migration rates.

  12. Comprehensive analyses of ventricular myocyte models identify targets exhibiting favorable rate dependence.

    Directory of Open Access Journals (Sweden)

    Megan A Cummins

    2014-03-01

    Full Text Available Reverse rate dependence is a problematic property of antiarrhythmic drugs that prolong the cardiac action potential (AP. The prolongation caused by reverse rate dependent agents is greater at slow heart rates, resulting in both reduced arrhythmia suppression at fast rates and increased arrhythmia risk at slow rates. The opposite property, forward rate dependence, would theoretically overcome these parallel problems, yet forward rate dependent (FRD antiarrhythmics remain elusive. Moreover, there is evidence that reverse rate dependence is an intrinsic property of perturbations to the AP. We have addressed the possibility of forward rate dependence by performing a comprehensive analysis of 13 ventricular myocyte models. By simulating populations of myocytes with varying properties and analyzing population results statistically, we simultaneously predicted the rate-dependent effects of changes in multiple model parameters. An average of 40 parameters were tested in each model, and effects on AP duration were assessed at slow (0.2 Hz and fast (2 Hz rates. The analysis identified a variety of FRD ionic current perturbations and generated specific predictions regarding their mechanisms. For instance, an increase in L-type calcium current is FRD when this is accompanied by indirect, rate-dependent changes in slow delayed rectifier potassium current. A comparison of predictions across models identified inward rectifier potassium current and the sodium-potassium pump as the two targets most likely to produce FRD AP prolongation. Finally, a statistical analysis of results from the 13 models demonstrated that models displaying minimal rate-dependent changes in AP shape have little capacity for FRD perturbations, whereas models with large shape changes have considerable FRD potential. This can explain differences between species and between ventricular cell types. Overall, this study provides new insights, both specific and general, into the determinants of

  13. Simultaneous detection of landmarks and key-frame in cardiac perfusion MRI using a joint spatial-temporal context model

    Science.gov (United States)

    Lu, Xiaoguang; Xue, Hui; Jolly, Marie-Pierre; Guetter, Christoph; Kellman, Peter; Hsu, Li-Yueh; Arai, Andrew; Zuehlsdorff, Sven; Littmann, Arne; Georgescu, Bogdan; Guehring, Jens

    2011-03-01

    Cardiac perfusion magnetic resonance imaging (MRI) has proven clinical significance in diagnosis of heart diseases. However, analysis of perfusion data is time-consuming, where automatic detection of anatomic landmarks and key-frames from perfusion MR sequences is helpful for anchoring structures and functional analysis of the heart, leading toward fully automated perfusion analysis. Learning-based object detection methods have demonstrated their capabilities to handle large variations of the object by exploring a local region, i.e., context. Conventional 2D approaches take into account spatial context only. Temporal signals in perfusion data present a strong cue for anchoring. We propose a joint context model to encode both spatial and temporal evidence. In addition, our spatial context is constructed not only based on the landmark of interest, but also the landmarks that are correlated in the neighboring anatomies. A discriminative model is learned through a probabilistic boosting tree. A marginal space learning strategy is applied to efficiently learn and search in a high dimensional parameter space. A fully automatic system is developed to simultaneously detect anatomic landmarks and key frames in both RV and LV from perfusion sequences. The proposed approach was evaluated on a database of 373 cardiac perfusion MRI sequences from 77 patients. Experimental results of a 4-fold cross validation show superior landmark detection accuracies of the proposed joint spatial-temporal approach to the 2D approach that is based on spatial context only. The key-frame identification results are promising.

  14. Quantum key management

    Energy Technology Data Exchange (ETDEWEB)

    Hughes, Richard John; Thrasher, James Thomas; Nordholt, Jane Elizabeth

    2016-11-29

    Innovations for quantum key management harness quantum communications to form a cryptography system within a public key infrastructure framework. In example implementations, the quantum key management innovations combine quantum key distribution and a quantum identification protocol with a Merkle signature scheme (using Winternitz one-time digital signatures or other one-time digital signatures, and Merkle hash trees) to constitute a cryptography system. More generally, the quantum key management innovations combine quantum key distribution and a quantum identification protocol with a hash-based signature scheme. This provides a secure way to identify, authenticate, verify, and exchange secret cryptographic keys. Features of the quantum key management innovations further include secure enrollment of users with a registration authority, as well as credential checking and revocation with a certificate authority, where the registration authority and/or certificate authority can be part of the same system as a trusted authority for quantum key distribution.

  15. Key factors contributing to accident severity rate in construction industry in Iran: a regression modelling approach.

    Science.gov (United States)

    Soltanzadeh, Ahmad; Mohammadfam, Iraj; Moghimbeigi, Abbas; Ghiasvand, Reza

    2016-03-01

    Construction industry involves the highest risk of occupational accidents and bodily injuries, which range from mild to very severe. The aim of this cross-sectional study was to identify the factors associated with accident severity rate (ASR) in the largest Iranian construction companies based on data about 500 occupational accidents recorded from 2009 to 2013. We also gathered data on safety and health risk management and training systems. Data were analysed using Pearson's chi-squared coefficient and multiple regression analysis. Median ASR (and the interquartile range) was 107.50 (57.24- 381.25). Fourteen of the 24 studied factors stood out as most affecting construction accident severity (p<0.05). These findings can be applied in the design and implementation of a comprehensive safety and health risk management system to reduce ASR.

  16. The Progressive BSSG Rat Model of Parkinson's: Recapitulating Multiple Key Features of the Human Disease.

    Directory of Open Access Journals (Sweden)

    Jackalina M Van Kampen

    Full Text Available The development of effective neuroprotective therapies for Parkinson's disease (PD has been severely hindered by the notable lack of an appropriate animal model for preclinical screening. Indeed, most models currently available are either acute in nature or fail to recapitulate all characteristic features of the disease. Here, we present a novel progressive model of PD, with behavioural and cellular features that closely approximate those observed in patients. Chronic exposure to dietary phytosterol glucosides has been found to be neurotoxic. When fed to rats, β-sitosterol β-d-glucoside (BSSG triggers the progressive development of parkinsonism, with clinical signs and histopathology beginning to appear following cessation of exposure to the neurotoxic insult and continuing to develop over several months. Here, we characterize the progressive nature of this model, its non-motor features, the anatomical spread of synucleinopathy, and response to levodopa administration. In Sprague Dawley rats, chronic BSSG feeding for 4 months triggered the progressive development of a parkinsonian phenotype and pathological events that evolved slowly over time, with neuronal loss beginning only after toxin exposure was terminated. At approximately 3 months following initiation of BSSG exposure, animals displayed the early emergence of an olfactory deficit, in the absence of significant dopaminergic nigral cell loss or locomotor deficits. Locomotor deficits developed gradually over time, initially appearing as locomotor asymmetry and developing into akinesia/bradykinesia, which was reversed by levodopa treatment. Late-stage cognitive impairment was observed in the form of spatial working memory deficits, as assessed by the radial arm maze. In addition to the progressive loss of TH+ cells in the substantia nigra, the appearance of proteinase K-resistant intracellular α-synuclein aggregates was also observed to develop progressively, appearing first in the

  17. Identifying influential data points in hydrological model calibration and their impact on streamflow predictions

    Science.gov (United States)

    Wright, David; Thyer, Mark; Westra, Seth

    2015-04-01

    Highly influential data points are those that have a disproportionately large impact on model performance, parameters and predictions. However, in current hydrological modelling practice the relative influence of individual data points on hydrological model calibration is not commonly evaluated. This presentation illustrates and evaluates several influence diagnostics tools that hydrological modellers can use to assess the relative influence of data. The feasibility and importance of including influence detection diagnostics as a standard tool in hydrological model calibration is discussed. Two classes of influence diagnostics are evaluated: (1) computationally demanding numerical "case deletion" diagnostics; and (2) computationally efficient analytical diagnostics, based on Cook's distance. These diagnostics are compared against hydrologically orientated diagnostics that describe changes in the model parameters (measured through the Mahalanobis distance), performance (objective function displacement) and predictions (mean and maximum streamflow). These influence diagnostics are applied to two case studies: a stage/discharge rating curve model, and a conceptual rainfall-runoff model (GR4J). Removing a single data point from the calibration resulted in differences to mean flow predictions of up to 6% for the rating curve model, and differences to mean and maximum flow predictions of up to 10% and 17%, respectively, for the hydrological model. When using the Nash-Sutcliffe efficiency in calibration, the computationally cheaper Cook's distance metrics produce similar results to the case-deletion metrics at a fraction of the computational cost. However, Cooks distance is adapted from linear regression with inherit assumptions on the data and is therefore less flexible than case deletion. Influential point detection diagnostics show great potential to improve current hydrological modelling practices by identifying highly influential data points. The findings of this

  18. Identifying mechanisms that structure ecological communities by snapping model parameters to empirically observed tradeoffs.

    Science.gov (United States)

    Thomas Clark, Adam; Lehman, Clarence; Tilman, David

    2018-04-01

    Theory predicts that interspecific tradeoffs are primary determinants of coexistence and community composition. Using information from empirically observed tradeoffs to augment the parametrisation of mechanism-based models should therefore improve model predictions, provided that tradeoffs and mechanisms are chosen correctly. We developed and tested such a model for 35 grassland plant species using monoculture measurements of three species characteristics related to nitrogen uptake and retention, which previous experiments indicate as important at our site. Matching classical theoretical expectations, these characteristics defined a distinct tradeoff surface, and models parameterised with these characteristics closely matched observations from experimental multi-species mixtures. Importantly, predictions improved significantly when we incorporated information from tradeoffs by 'snapping' characteristics to the nearest location on the tradeoff surface, suggesting that the tradeoffs and mechanisms we identify are important determinants of local community structure. This 'snapping' method could therefore constitute a broadly applicable test for identifying influential tradeoffs and mechanisms. © 2018 The Authors. Ecology Letters published by CNRS and John Wiley & Sons Ltd.

  19. A Multi-Compartment Hybrid Computational Model Predicts Key Roles for Dendritic Cells in Tuberculosis Infection

    Directory of Open Access Journals (Sweden)

    Simeone Marino

    2016-10-01

    Full Text Available Tuberculosis (TB is a world-wide health problem with approximately 2 billion people infected with Mycobacterium tuberculosis (Mtb, the causative bacterium of TB. The pathologic hallmark of Mtb infection in humans and Non-Human Primates (NHPs is the formation of spherical structures, primarily in lungs, called granulomas. Infection occurs after inhalation of bacteria into lungs, where resident antigen-presenting cells (APCs, take up bacteria and initiate the immune response to Mtb infection. APCs traffic from the site of infection (lung to lung-draining lymph nodes (LNs where they prime T cells to recognize Mtb. These T cells, circulating back through blood, migrate back to lungs to perform their immune effector functions. We have previously developed a hybrid agent-based model (ABM, labeled GranSim describing in silico immune cell, bacterial (Mtb and molecular behaviors during tuberculosis infection and recently linked that model to operate across three physiological compartments: lung (infection site where granulomas form, lung draining lymph node (LN, site of generation of adaptive immunity and blood (a measurable compartment. Granuloma formation and function is captured by a spatio-temporal model (i.e., ABM, while LN and blood compartments represent temporal dynamics of the whole body in response to infection and are captured with ordinary differential equations (ODEs. In order to have a more mechanistic representation of APC trafficking from the lung to the lymph node, and to better capture antigen presentation in a draining LN, this current study incorporates the role of dendritic cells (DCs in a computational fashion into GranSim. Results: The model was calibrated using experimental data from the lungs and blood of NHPs. The addition of DCs allowed us to investigate in greater detail mechanisms of recruitment, trafficking and antigen presentation and their role in tuberculosis infection. Conclusion: The main conclusion of this study is

  20. Identifying Mechanical Properties of Viscoelastic Materials in Time Domain Using the Fractional Zener Model

    Directory of Open Access Journals (Sweden)

    Ana Paula Delowski Ciniello

    Full Text Available Abstract The present paper aims at presenting a methodology for characterizing viscoelastic materials in time domain, taking into account the fractional Zener constitutive model and the influence of temperature through Williams, Landel, and Ferry’s model. To that effect, a set of points obtained experimentally through uniaxial tensile tests with different constant strain rates is considered. The approach is based on the minimization of the quadratic relative distance between the experimental stress-strain curves and the corresponding ones given by the theoretical model. In order to avoid the local minima in the process of optimization, a hybrid technique based on genetic algorithms and non-linear programming techniques is used. The methodology is applied in the characterization of two different commercial viscoelastic materials. The results indicate that the proposed methodology is effective in identifying thermorheologically simple viscoelastic materials.

  1. Prospective validation of a predictive model that identifies homeless people at risk of re-presentation to the emergency department.

    Science.gov (United States)

    Moore, Gaye; Hepworth, Graham; Weiland, Tracey; Manias, Elizabeth; Gerdtz, Marie Frances; Kelaher, Margaret; Dunt, David

    2012-02-01

    To prospectively evaluate the accuracy of a predictive model to identify homeless people at risk of representation to an emergency department. A prospective cohort analysis utilised one month of data from a Principal Referral Hospital in Melbourne, Australia. All visits involving people classified as homeless were included, excluding those who died. Homelessness was defined as living on the streets, in crisis accommodation, in boarding houses or residing in unstable housing. Rates of re-presentation, defined as the total number of visits to the same emergency department within 28 days of discharge from hospital, were measured. Performance of the risk screening tool was assessed by calculating sensitivity, specificity, positive and negative predictive values and likelihood ratios. Over the study period (April 1, 2009 to April 30, 2009), 3298 presentations from 2888 individuals were recorded. The homeless population accounted for 10% (n=327) of all visits and 7% (n=211) of all patients. A total of 90 (43%) homeless people re-presented to the emergency department. The predictive model included nine variables and achieved 98% (CI, 0.92-0.99) sensitivity and 66% (CI, 0.57-0.74) specificity. The positive predictive value was 68% and the negative predictive value was 98%. The positive likelihood ratio 2.9 (CI, 2.2-3.7) and the negative likelihood ratio was 0.03 (CI, 0.01-0.13). The high emergency department re-presentation rate for people who were homeless identifies unresolved psychosocial health needs. The emergency department remains a vital access point for homeless people, particularly after hours. The risk screening tool is key to identify medical and social aspects of a homeless patient's presentation to assist early identification and referral. Copyright © 2012 College of Emergency Nursing Australasia Ltd. Published by Elsevier Ltd. All rights reserved.

  2. Applying complexity theory: A primer for identifying and modeling firm anomalies

    Directory of Open Access Journals (Sweden)

    Arch G. Woodside

    2018-01-01

    Full Text Available This essay elaborates on the usefulness of embracing complexity theory, modeling outcomes rather than directionality, and modeling complex rather than simple outcomes in strategic management. Complexity theory includes the tenet that most antecedent conditions are neither sufficient nor necessary for the occurrence of a specific outcome. Identifying a firm by individual antecedents (i.e., non-innovative versus highly innovative, small versus large size in sales or number of employees, or serving local versus international markets provides shallow information in modeling specific outcomes (e.g., high sales growth or high profitability—even if directional analyses (e.g., regression analysis, including structural equation modeling indicates that the independent (main effects of the individual antecedents relate to outcomes directionally—because firm (case anomalies almost always occur to main effects. Examples: a number of highly innovative firms have low sales while others have high sales and a number of non-innovative firms have low sales while others have high sales. Breaking-away from the current dominant logic of directionality testing—null hypotheses statistic testing (NHST—to embrace somewhat precise outcome testing (SPOT is necessary for extracting highly useful information about the causes of anomalies—associations opposite to expected and “statistically significant” main effects. The study of anomalies extends to identifying the occurrences of four-corner strategy outcomes: firms doing well in favorable circumstances, firms doing badly in favorable circumstances, firms doing well in unfavorable circumstances, and firms doing badly in unfavorable circumstances. Models of four-corner strategy outcomes advances strategic management beyond the current dominant logic of directional modeling of single outcomes.

  3. The Early Eocene equable climate problem: can perturbations of climate model parameters identify possible solutions?

    Science.gov (United States)

    Sagoo, Navjit; Valdes, Paul; Flecker, Rachel; Gregoire, Lauren J

    2013-10-28

    Geological data for the Early Eocene (56-47.8 Ma) indicate extensive global warming, with very warm temperatures at both poles. However, despite numerous attempts to simulate this warmth, there are remarkable data-model differences in the prediction of these polar surface temperatures, resulting in the so-called 'equable climate problem'. In this paper, for the first time an ensemble with a perturbed climate-sensitive model parameters approach has been applied to modelling the Early Eocene climate. We performed more than 100 simulations with perturbed physics parameters, and identified two simulations that have an optimal fit with the proxy data. We have simulated the warmth of the Early Eocene at 560 ppmv CO2, which is a much lower CO2 level than many other models. We investigate the changes in atmospheric circulation, cloud properties and ocean circulation that are common to these simulations and how they differ from the remaining simulations in order to understand what mechanisms contribute to the polar warming. The parameter set from one of the optimal Early Eocene simulations also produces a favourable fit for the last glacial maximum boundary climate and outperforms the control parameter set for the present day. Although this does not 'prove' that this model is correct, it is very encouraging that there is a parameter set that creates a climate model able to simulate well very different palaeoclimates and the present-day climate. Interestingly, to achieve the great warmth of the Early Eocene this version of the model does not have a strong future climate change Charney climate sensitivity. It produces a Charney climate sensitivity of 2.7(°)C, whereas the mean value of the 18 models in the IPCC Fourth Assessment Report (AR4) is 3.26(°)C±0.69(°)C. Thus, this value is within the range and below the mean of the models included in the AR4.

  4. Markov and semi-Markov switching linear mixed models used to identify forest tree growth components.

    Science.gov (United States)

    Chaubert-Pereira, Florence; Guédon, Yann; Lavergne, Christian; Trottier, Catherine

    2010-09-01

    Tree growth is assumed to be mainly the result of three components: (i) an endogenous component assumed to be structured as a succession of roughly stationary phases separated by marked change points that are asynchronous among individuals, (ii) a time-varying environmental component assumed to take the form of synchronous fluctuations among individuals, and (iii) an individual component corresponding mainly to the local environment of each tree. To identify and characterize these three components, we propose to use semi-Markov switching linear mixed models, i.e., models that combine linear mixed models in a semi-Markovian manner. The underlying semi-Markov chain represents the succession of growth phases and their lengths (endogenous component) whereas the linear mixed models attached to each state of the underlying semi-Markov chain represent-in the corresponding growth phase-both the influence of time-varying climatic covariates (environmental component) as fixed effects, and interindividual heterogeneity (individual component) as random effects. In this article, we address the estimation of Markov and semi-Markov switching linear mixed models in a general framework. We propose a Monte Carlo expectation-maximization like algorithm whose iterations decompose into three steps: (i) sampling of state sequences given random effects, (ii) prediction of random effects given state sequences, and (iii) maximization. The proposed statistical modeling approach is illustrated by the analysis of successive annual shoots along Corsican pine trunks influenced by climatic covariates. © 2009, The International Biometric Society.

  5. Scoping review identifies significant number of knowledge translation theories, models and frameworks with limited use.

    Science.gov (United States)

    Strifler, Lisa; Cardoso, Roberta; McGowan, Jessie; Cogo, Elise; Nincic, Vera; Khan, Paul A; Scott, Alistair; Ghassemi, Marco; MacDonald, Heather; Lai, Yonda; Treister, Victoria; Tricco, Andrea C; Straus, Sharon E

    2018-04-13

    To conduct a scoping review of knowledge translation (KT) theories, models and frameworks that have been used to guide dissemination or implementation of evidence-based interventions targeted to prevention and/or management of cancer or other chronic diseases. We used a comprehensive multistage search process from 2000-2016, which included traditional bibliographic database searching, searching using names of theories, models and frameworks, and cited reference searching. Two reviewers independently screened the literature and abstracted data. We found 596 studies reporting on the use of 159 KT theories, models or frameworks. A majority (87%) of the identified theories, models or frameworks were used in five or fewer studies, with 60% used once. The theories, models and frameworks were most commonly used to inform planning/design, implementation and evaluation activities, and least commonly used to inform dissemination and sustainability/scalability activities. Twenty-six were used across the full implementation spectrum (from planning/design to sustainability/scalability) either within or across studies. All were used for at least individual-level behavior change, while 48% were used for organization-level, 33% for community-level and 17% for system-level change. We found a significant number of KT theories, models and frameworks with a limited evidence base describing their use. Copyright © 2018. Published by Elsevier Inc.

  6. Biodiversity and Climate Modeling Workshop Series: Identifying gaps and needs for improving large-scale biodiversity models

    Science.gov (United States)

    Weiskopf, S. R.; Myers, B.; Beard, T. D.; Jackson, S. T.; Tittensor, D.; Harfoot, M.; Senay, G. B.

    2017-12-01

    At the global scale, well-accepted global circulation models and agreed-upon scenarios for future climate from the Intergovernmental Panel on Climate Change (IPCC) are available. In contrast, biodiversity modeling at the global scale lacks analogous tools. While there is great interest in development of similar bodies and efforts for international monitoring and modelling of biodiversity at the global scale, equivalent modelling tools are in their infancy. This lack of global biodiversity models compared to the extensive array of general circulation models provides a unique opportunity to bring together climate, ecosystem, and biodiversity modeling experts to promote development of integrated approaches in modeling global biodiversity. Improved models are needed to understand how we are progressing towards the Aichi Biodiversity Targets, many of which are not on track to meet the 2020 goal, threatening global biodiversity conservation, monitoring, and sustainable use. We brought together biodiversity, climate, and remote sensing experts to try to 1) identify lessons learned from the climate community that can be used to improve global biodiversity models; 2) explore how NASA and other remote sensing products could be better integrated into global biodiversity models and 3) advance global biodiversity modeling, prediction, and forecasting to inform the Aichi Biodiversity Targets, the 2030 Sustainable Development Goals, and the Intergovernmental Platform on Biodiversity and Ecosystem Services Global Assessment of Biodiversity and Ecosystem Services. The 1st In-Person meeting focused on determining a roadmap for effective assessment of biodiversity model projections and forecasts by 2030 while integrating and assimilating remote sensing data and applying lessons learned, when appropriate, from climate modeling. Here, we present the outcomes and lessons learned from our first E-discussion and in-person meeting and discuss the next steps for future meetings.

  7. Modeling strategy to identify patients with primary immunodeficiency utilizing risk management and outcome measurement.

    Science.gov (United States)

    Modell, Vicki; Quinn, Jessica; Ginsberg, Grant; Gladue, Ron; Orange, Jordan; Modell, Fred

    2017-06-01

    This study seeks to generate analytic insights into risk management and probability of an identifiable primary immunodeficiency defect. The Jeffrey Modell Centers Network database, Jeffrey Modell Foundation's 10 Warning Signs, the 4 Stages of Testing Algorithm, physician-reported clinical outcomes, programs of physician education and public awareness, the SPIRIT® Analyzer, and newborn screening, taken together, generates P values of less than 0.05%. This indicates that the data results do not occur by chance, and that there is a better than 95% probability that the data are valid. The objectives are to improve patients' quality of life, while generating significant reduction of costs. The advances of the world's experts aligned with these JMF programs can generate analytic insights as to risk management and probability of an identifiable primary immunodeficiency defect. This strategy reduces the uncertainties related to primary immunodeficiency risks, as we can screen, test, identify, and treat undiagnosed patients. We can also address regional differences and prevalence, age, gender, treatment modalities, and sites of care, as well as economic benefits. These tools support high net benefits, substantial financial savings, and significant reduction of costs. All stakeholders, including patients, clinicians, pharmaceutical companies, third party payers, and government healthcare agencies, must address the earliest possible precise diagnosis, appropriate intervention and treatment, as well as stringent control of healthcare costs through risk assessment and outcome measurement. An affected patient is entitled to nothing less, and stakeholders are responsible to utilize tools currently available. Implementation offers a significant challenge to the entire primary immunodeficiency community.

  8. The Electric Vehicles Ecosystem Model: Construct, Analysis and Identification of Key Challenges

    Directory of Open Access Journals (Sweden)

    Zulkarnain

    2014-09-01

    Full Text Available This paper builds a conceptual model of electric vehicles’ (EV ecosystem and value chain build-up. Based on the literature, the research distinguishes the most critical challenges that are on the way of mobility systems’ electrification. Consumers still have some questions that call for answers before they are ready to adopt evs.With regard to technical aspects, some challenges are coming from vehicles, charging infrastructure, battery technology, and standardization. The use of battery in EVs will bring in additional environmental challenges, coming from the battery life cycle for used battery, the manufacturing, and from some materials used and treated in the manufacturing process. The policy aspects include mostly taxation strategies. For most part, established market conditions are still lacking and there are a number of unresolved challenges on both supply and demand side of the EV market.

  9. Identifying the preferred subset of enzymatic profiles in nonlinear kinetic metabolic models via multiobjective global optimization and Pareto filters.

    Directory of Open Access Journals (Sweden)

    Carlos Pozo

    Full Text Available Optimization models in metabolic engineering and systems biology focus typically on optimizing a unique criterion, usually the synthesis rate of a metabolite of interest or the rate of growth. Connectivity and non-linear regulatory effects, however, make it necessary to consider multiple objectives in order to identify useful strategies that balance out different metabolic issues. This is a fundamental aspect, as optimization of maximum yield in a given condition may involve unrealistic values in other key processes. Due to the difficulties associated with detailed non-linear models, analysis using stoichiometric descriptions and linear optimization methods have become rather popular in systems biology. However, despite being useful, these approaches fail in capturing the intrinsic nonlinear nature of the underlying metabolic systems and the regulatory signals involved. Targeting more complex biological systems requires the application of global optimization methods to non-linear representations. In this work we address the multi-objective global optimization of metabolic networks that are described by a special class of models based on the power-law formalism: the generalized mass action (GMA representation. Our goal is to develop global optimization methods capable of efficiently dealing with several biological criteria simultaneously. In order to overcome the numerical difficulties of dealing with multiple criteria in the optimization, we propose a heuristic approach based on the epsilon constraint method that reduces the computational burden of generating a set of Pareto optimal alternatives, each achieving a unique combination of objectives values. To facilitate the post-optimal analysis of these solutions and narrow down their number prior to being tested in the laboratory, we explore the use of Pareto filters that identify the preferred subset of enzymatic profiles. We demonstrate the usefulness of our approach by means of a case study

  10. Identifying the preferred subset of enzymatic profiles in nonlinear kinetic metabolic models via multiobjective global optimization and Pareto filters.

    Science.gov (United States)

    Pozo, Carlos; Guillén-Gosálbez, Gonzalo; Sorribas, Albert; Jiménez, Laureano

    2012-01-01

    Optimization models in metabolic engineering and systems biology focus typically on optimizing a unique criterion, usually the synthesis rate of a metabolite of interest or the rate of growth. Connectivity and non-linear regulatory effects, however, make it necessary to consider multiple objectives in order to identify useful strategies that balance out different metabolic issues. This is a fundamental aspect, as optimization of maximum yield in a given condition may involve unrealistic values in other key processes. Due to the difficulties associated with detailed non-linear models, analysis using stoichiometric descriptions and linear optimization methods have become rather popular in systems biology. However, despite being useful, these approaches fail in capturing the intrinsic nonlinear nature of the underlying metabolic systems and the regulatory signals involved. Targeting more complex biological systems requires the application of global optimization methods to non-linear representations. In this work we address the multi-objective global optimization of metabolic networks that are described by a special class of models based on the power-law formalism: the generalized mass action (GMA) representation. Our goal is to develop global optimization methods capable of efficiently dealing with several biological criteria simultaneously. In order to overcome the numerical difficulties of dealing with multiple criteria in the optimization, we propose a heuristic approach based on the epsilon constraint method that reduces the computational burden of generating a set of Pareto optimal alternatives, each achieving a unique combination of objectives values. To facilitate the post-optimal analysis of these solutions and narrow down their number prior to being tested in the laboratory, we explore the use of Pareto filters that identify the preferred subset of enzymatic profiles. We demonstrate the usefulness of our approach by means of a case study that optimizes the

  11. Diagnosing observed characteristics of the wet season across Africa to identify deficiencies in climate model simulations

    Science.gov (United States)

    Dunning, C.; Black, E.; Allan, R. P.

    2017-12-01

    The seasonality of rainfall over Africa plays a key role in determining socio-economic impacts for agricultural stakeholders, influences energy supply from hydropower, affects the length of the malaria transmission season and impacts surface water supplies. Hence, failure or delays of these rains can lead to significant socio-economic impacts. Diagnosing and interpreting interannual variability and long-term trends in seasonality, and analysing the physical driving mechanisms, requires a robust definition of African precipitation seasonality, applicable to both observational datasets and model simulations. Here we present a methodology for objectively determining the onset and cessation of multiple wet seasons across the whole of Africa. Compatibility with known physical drivers of African rainfall, consistency with indigenous methods, and generally strong agreement between satellite-based rainfall data sets confirm that the method is capturing the correct seasonal progression of African rainfall. Application of this method to observational datasets reveals that over East Africa cessation of the short rains is 5 days earlier in La Nina years, and the failure of the rains and subsequent humanitarian disaster is associated with shorter as well as weaker rainy seasons over this region. The method is used to examine the representation of the seasonality of African precipitation in CMIP5 model simulations. Overall, atmosphere-only and fully coupled CMIP5 historical simulations represent essential aspects of the seasonal cycle; patterns of seasonal progression of the rainy season are captured, for the most part mean model onset/ cessation dates agree with mean observational dates to within 18 days. However, unlike the atmosphere-only simulations, the coupled simulations do not capture the biannual regime over the southern West African coastline, linked to errors in Gulf of Guinea Sea Surface Temperature. Application to both observational and climate model datasets, and

  12. A molecular systems approach to modelling human skin pigmentation: identifying underlying pathways and critical components.

    Science.gov (United States)

    Raghunath, Arathi; Sambarey, Awanti; Sharma, Neha; Mahadevan, Usha; Chandra, Nagasuma

    2015-04-29

    Ultraviolet radiations (UV) serve as an environmental stress for human skin, and result in melanogenesis, with the pigment melanin having protective effects against UV induced damage. This involves a dynamic and complex regulation of various biological processes that results in the expression of melanin in the outer most layers of the epidermis, where it can exert its protective effect. A comprehensive understanding of the underlying cross talk among different signalling molecules and cell types is only possible through a systems perspective. Increasing incidences of both melanoma and non-melanoma skin cancers necessitate the need to better comprehend UV mediated effects on skin pigmentation at a systems level, so as to ultimately evolve knowledge-based strategies for efficient protection and prevention of skin diseases. A network model for UV-mediated skin pigmentation in the epidermis was constructed and subjected to shortest path analysis. Virtual knock-outs were carried out to identify essential signalling components. We describe a network model for UV-mediated skin pigmentation in the epidermis. The model consists of 265 components (nodes) and 429 directed interactions among them, capturing the manner in which one component influences the other and channels information. Through shortest path analysis, we identify novel signalling pathways relevant to pigmentation. Virtual knock-outs or perturbations of specific nodes in the network have led to the identification of alternate modes of signalling as well as enabled determining essential nodes in the process. The model presented provides a comprehensive picture of UV mediated signalling manifesting in human skin pigmentation. A systems perspective helps provide a holistic purview of interconnections and complexity in the processes leading to pigmentation. The model described here is extensive yet amenable to expansion as new data is gathered. Through this study, we provide a list of important proteins essential

  13. Multiscale models and stochastic simulation methods for computing rare but key binding events in cell biology

    Energy Technology Data Exchange (ETDEWEB)

    Guerrier, C. [Applied Mathematics and Computational Biology, IBENS, Ecole Normale Supérieure, 46 rue d' Ulm, 75005 Paris (France); Holcman, D., E-mail: david.holcman@ens.fr [Applied Mathematics and Computational Biology, IBENS, Ecole Normale Supérieure, 46 rue d' Ulm, 75005 Paris (France); Mathematical Institute, Oxford OX2 6GG, Newton Institute (United Kingdom)

    2017-07-01

    The main difficulty in simulating diffusion processes at a molecular level in cell microdomains is due to the multiple scales involving nano- to micrometers. Few to many particles have to be simulated and simultaneously tracked while there are exploring a large portion of the space for binding small targets, such as buffers or active sites. Bridging the small and large spatial scales is achieved by rare events representing Brownian particles finding small targets and characterized by long-time distribution. These rare events are the bottleneck of numerical simulations. A naive stochastic simulation requires running many Brownian particles together, which is computationally greedy and inefficient. Solving the associated partial differential equations is also difficult due to the time dependent boundary conditions, narrow passages and mixed boundary conditions at small windows. We present here two reduced modeling approaches for a fast computation of diffusing fluxes in microdomains. The first approach is based on a Markov mass-action law equations coupled to a Markov chain. The second is a Gillespie's method based on the narrow escape theory for coarse-graining the geometry of the domain into Poissonian rates. The main application concerns diffusion in cellular biology, where we compute as an example the distribution of arrival times of calcium ions to small hidden targets to trigger vesicular release.

  14. HIGHLY QUALIFIED WORKING FORCE – KEY ELEMENT OF INNOVATIVE DEVELOPMENT MODEL

    Directory of Open Access Journals (Sweden)

    M. Avksientiev

    2014-12-01

    Full Text Available Highly qualified working force is a central element of intensive development model in modern society. The article surveys the experience of countries that managed to transform their economy to the innovative one. Ukrainian economy cannot stand aside processes that dominate the world economy trends, thus we are to use this experience to succeed in future. Today any government of the world is facing challenges that occur due to transformation of the economy into informational one. This type of economy causes its transformation form extensive to intensive one. The main reasons under that is limitation of nature resources, material factors of production. Thus this approach depends much on the quality of working force. Unfortunately in Ukraine there is a misbalance in specialist preparation. This puts additional pressure on the educational sphere also. In order to avoid this pressure we are to conduct reforms in education sphere. Nowadays, in the world views and concepts of governmental role in the social development are changing. This why, even at times of economic recession educational costs are not reduced under the new economical doctrine in the EU. Highly qualified specialists, while creating new products and services play role of engineers in XXI century. They are to lead their industries to world leading positions. From economic point of view, highly qualified specialists benefit society with higher income rates, taxation and thus, increasing the living standards in society. Thus, the majority if modern scientists prove the importance of highly trained working force for more effective economic development.

  15. Multiscale models and stochastic simulation methods for computing rare but key binding events in cell biology

    International Nuclear Information System (INIS)

    Guerrier, C.; Holcman, D.

    2017-01-01

    The main difficulty in simulating diffusion processes at a molecular level in cell microdomains is due to the multiple scales involving nano- to micrometers. Few to many particles have to be simulated and simultaneously tracked while there are exploring a large portion of the space for binding small targets, such as buffers or active sites. Bridging the small and large spatial scales is achieved by rare events representing Brownian particles finding small targets and characterized by long-time distribution. These rare events are the bottleneck of numerical simulations. A naive stochastic simulation requires running many Brownian particles together, which is computationally greedy and inefficient. Solving the associated partial differential equations is also difficult due to the time dependent boundary conditions, narrow passages and mixed boundary conditions at small windows. We present here two reduced modeling approaches for a fast computation of diffusing fluxes in microdomains. The first approach is based on a Markov mass-action law equations coupled to a Markov chain. The second is a Gillespie's method based on the narrow escape theory for coarse-graining the geometry of the domain into Poissonian rates. The main application concerns diffusion in cellular biology, where we compute as an example the distribution of arrival times of calcium ions to small hidden targets to trigger vesicular release.

  16. Gaussian Graphical Models Identify Networks of Dietary Intake in a German Adult Population.

    Science.gov (United States)

    Iqbal, Khalid; Buijsse, Brian; Wirth, Janine; Schulze, Matthias B; Floegel, Anna; Boeing, Heiner

    2016-03-01

    Data-reduction methods such as principal component analysis are often used to derive dietary patterns. However, such methods do not assess how foods are consumed in relation to each other. Gaussian graphical models (GGMs) are a set of novel methods that can address this issue. We sought to apply GGMs to derive sex-specific dietary intake networks representing consumption patterns in a German adult population. Dietary intake data from 10,780 men and 16,340 women of the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam cohort were cross-sectionally analyzed to construct dietary intake networks. Food intake for each participant was estimated using a 148-item food-frequency questionnaire that captured the intake of 49 food groups. GGMs were applied to log-transformed intakes (grams per day) of 49 food groups to construct sex-specific food networks. Semiparametric Gaussian copula graphical models (SGCGMs) were used to confirm GGM results. In men, GGMs identified 1 major dietary network that consisted of intakes of red meat, processed meat, cooked vegetables, sauces, potatoes, cabbage, poultry, legumes, mushrooms, soup, and whole-grain and refined breads. For women, a similar network was identified with the addition of fried potatoes. Other identified networks consisted of dairy products and sweet food groups. SGCGMs yielded results comparable to those of GGMs. GGMs are a powerful exploratory method that can be used to construct dietary networks representing dietary intake patterns that reveal how foods are consumed in relation to each other. GGMs indicated an apparent major role of red meat intake in a consumption pattern in the studied population. In the future, identified networks might be transformed into pattern scores for investigating their associations with health outcomes. © 2016 American Society for Nutrition.

  17. Building Analysis for Urban Energy Planning Using Key Indicators on Virtual 3d City Models - the Energy Atlas of Berlin

    Science.gov (United States)

    Krüger, A.; Kolbe, T. H.

    2012-07-01

    In the context of increasing greenhouse gas emission and global demographic change with the simultaneous trend to urbanization, it is a big challenge for cities around the world to perform modifications in energy supply chain and building characteristics resulting in reduced energy consumption and carbon dioxide mitigation. Sound knowledge of energy resource demand and supply including its spatial distribution within urban areas is of great importance for planning strategies addressing greater energy efficiency. The understanding of the city as a complex energy system affects several areas of the urban living, e.g. energy supply, urban texture, human lifestyle, and climate protection. With the growing availability of 3D city models around the world based on the standard language and format CityGML, energy system modelling, analysis and simulation can be incorporated into these models. Both domains will profit from that interaction by bringing together official and accurate building models including building geometries, semantics and locations forming a realistic image of the urban structure with systemic energy simulation models. A holistic view on the impacts of energy planning scenarios can be modelled and analyzed including side effects on urban texture and human lifestyle. This paper focuses on the identification, classification, and integration of energy-related key indicators of buildings and neighbourhoods within 3D building models. Consequent application of 3D city models conforming to CityGML serves the purpose of deriving indicators for this topic. These will be set into the context of urban energy planning within the Energy Atlas Berlin. The generation of indicator objects covering the indicator values and related processing information will be presented on the sample scenario estimation of heating energy consumption in buildings and neighbourhoods. In their entirety the key indicators will form an adequate image of the local energy situation for

  18. Mathematical modeling identifies optimum lapatinib dosing schedules for the treatment of glioblastoma patients.

    Directory of Open Access Journals (Sweden)

    Shayna Stein

    2018-01-01

    Full Text Available Human primary glioblastomas (GBM often harbor mutations within the epidermal growth factor receptor (EGFR. Treatment of EGFR-mutant GBM cell lines with the EGFR/HER2 tyrosine kinase inhibitor lapatinib can effectively induce cell death in these models. However, EGFR inhibitors have shown little efficacy in the clinic, partly because of inappropriate dosing. Here, we developed a computational approach to model the in vitro cellular dynamics of the EGFR-mutant cell line SF268 in response to different lapatinib concentrations and dosing schedules. We then used this approach to identify an effective treatment strategy within the clinical toxicity limits of lapatinib, and developed a partial differential equation modeling approach to study the in vivo GBM treatment response by taking into account the heterogeneous and diffusive nature of the disease. Despite the inability of lapatinib to induce tumor regressions with a continuous daily schedule, our modeling approach consistently predicts that continuous dosing remains the best clinically feasible strategy for slowing down tumor growth and lowering overall tumor burden, compared to pulsatile schedules currently known to be tolerated, even when considering drug resistance, reduced lapatinib tumor concentrations due to the blood brain barrier, and the phenotypic switch from proliferative to migratory cell phenotypes that occurs in hypoxic microenvironments. Our mathematical modeling and statistical analysis platform provides a rational method for comparing treatment schedules in search for optimal dosing strategies for glioblastoma and other cancer types.

  19. Identifying Variability in Mental Models Within and Between Disciplines Caring for the Cardiac Surgical Patient.

    Science.gov (United States)

    Brown, Evans K H; Harder, Kathleen A; Apostolidou, Ioanna; Wahr, Joyce A; Shook, Douglas C; Farivar, R Saeid; Perry, Tjorvi E; Konia, Mojca R

    2017-07-01

    The cardiac operating room is a complex environment requiring efficient and effective communication between multiple disciplines. The objectives of this study were to identify and rank critical time points during the perioperative care of cardiac surgical patients, and to assess variability in responses, as a correlate of a shared mental model, regarding the importance of these time points between and within disciplines. Using Delphi technique methodology, panelists from 3 institutions were tasked with developing a list of critical time points, which were subsequently assigned to pause point (PP) categories. Panelists then rated these PPs on a 100-point visual analog scale. Descriptive statistics were expressed as percentages, medians, and interquartile ranges (IQRs). We defined low response variability between panelists as an IQR ≤ 20, moderate response variability as an IQR > 20 and ≤ 40, and high response variability as an IQR > 40. Panelists identified a total of 12 PPs. The PPs identified by the highest number of panelists were (1) before surgical incision, (2) before aortic cannulation, (3) before cardiopulmonary bypass (CPB) initiation, (4) before CPB separation, and (5) at time of transfer of care from operating room (OR) to intensive care unit (ICU) staff. There was low variability among panelists' ratings of the PP "before surgical incision," moderate response variability for the PPs "before separation from CPB," "before transfer from OR table to bed," and "at time of transfer of care from OR to ICU staff," and high response variability for the remaining 8 PPs. In addition, the perceived importance of each of these PPs varies between disciplines and between institutions. Cardiac surgical providers recognize distinct critical time points during cardiac surgery. However, there is a high degree of variability within and between disciplines as to the importance of these times, suggesting an absence of a shared mental model among disciplines caring for

  20. Where is the competitive advantage going?: a management model that incorporates people as a key element of the business strategy

    Directory of Open Access Journals (Sweden)

    Emilio García Vega

    2015-09-01

    Full Text Available Competitive advantage is a concept that has evolved in an accelerated way during the last few years. Some scholars and executives claim that people are a fundamental element of its construction. In this line, business management has shown an inclination towards the human resources management – also called “talents” – as the key element of its organizational success. In this journey, the ideas, paradigms and conceptions have been modified in an interesting way. This paper tries to propose these new conceptions facing the organization management challenge, and proposes a management model based on the importance of the people in the competitive advantage administration.

  1. A stochastic model for identifying differential gene pair co-expression patterns in prostate cancer progression

    Directory of Open Access Journals (Sweden)

    Mao Yu

    2009-07-01

    Full Text Available Abstract Background The identification of gene differential co-expression patterns between cancer stages is a newly developing method to reveal the underlying molecular mechanisms of carcinogenesis. Most researches of this subject lack an algorithm useful for performing a statistical significance assessment involving cancer progression. Lacking this specific algorithm is apparently absent in identifying precise gene pairs correlating to cancer progression. Results In this investigation we studied gene pair co-expression change by using a stochastic process model for approximating the underlying dynamic procedure of the co-expression change during cancer progression. Also, we presented a novel analytical method named 'Stochastic process model for Identifying differentially co-expressed Gene pair' (SIG method. This method has been applied to two well known prostate cancer data sets: hormone sensitive versus hormone resistant, and healthy versus cancerous. From these data sets, 428,582 gene pairs and 303,992 gene pairs were identified respectively. Afterwards, we used two different current statistical methods to the same data sets, which were developed to identify gene pair differential co-expression and did not consider cancer progression in algorithm. We then compared these results from three different perspectives: progression analysis, gene pair identification effectiveness analysis, and pathway enrichment analysis. Statistical methods were used to quantify the quality and performance of these different perspectives. They included: Re-identification Scale (RS and Progression Score (PS in progression analysis, True Positive Rate (TPR in gene pair analysis, and Pathway Enrichment Score (PES in pathway analysis. Our results show small values of RS and large values of PS, TPR, and PES; thus, suggesting that gene pairs identified by the SIG method are highly correlated with cancer progression, and highly enriched in disease-specific pathways. From

  2. Identifying the Minimum Model Features to Replicate Historic Morphodynamics of a Juvenile Delta

    Science.gov (United States)

    Czapiga, M. J.; Parker, G.

    2017-12-01

    We introduce a quasi-2D morphodynamic delta model that improves on past models that require many simplifying assumptions, e.g. a single channel representative of a channel network, fixed channel width, and spatially uniform deposition. Our model is useful for studying long-term progradation rates of any generic micro-tidal delta system with specification of: characteristic grain size, input water and sediment discharges and basin morphology. In particular, we relax the assumption of a single, implicit channel sweeping across the delta topset in favor of an implicit channel network. This network, coupled with recent research on channel-forming Shields number, quantitative assessments of the lateral depositional length of sand (corresponding loosely to levees) and length between bifurcations create a spatial web of deposition within the receiving basin. The depositional web includes spatial boundaries for areas infilling with sands carried as bed material load, as well as those filling via passive deposition of washload mud. Our main goal is to identify the minimum features necessary to accurately model the morphodynamics of channel number, width, depth, and overall delta progradation rate in a juvenile delta. We use the Wax Lake Delta in Louisiana as a test site due to its rapid growth in the last 40 years. Field data including topset/island bathymetry, channel bathymetry, topset/island width, channel width, number of channels, and radial topset length are compiled from US Army Corps of Engineers data for 1989, 1998, and 2006. Additional data is extracted from a DEM from 2015. These data are used as benchmarks for the hindcast model runs. The morphology of Wax Lake Delta is also strongly affected by a pre-delta substrate that acts as a lower "bedrock" boundary. Therefore, we also include closures for a bedrock-alluvial transition and an excess shear rate-law incision model to estimate bedrock incision. The model's framework is generic, but inclusion of individual

  3. Can Predictive Modeling Identify Head and Neck Oncology Patients at Risk for Readmission?

    Science.gov (United States)

    Manning, Amy M; Casper, Keith A; Peter, Kay St; Wilson, Keith M; Mark, Jonathan R; Collar, Ryan M

    2018-05-01

    Objective Unplanned readmission within 30 days is a contributor to health care costs in the United States. The use of predictive modeling during hospitalization to identify patients at risk for readmission offers a novel approach to quality improvement and cost reduction. Study Design Two-phase study including retrospective analysis of prospectively collected data followed by prospective longitudinal study. Setting Tertiary academic medical center. Subjects and Methods Prospectively collected data for patients undergoing surgical treatment for head and neck cancer from January 2013 to January 2015 were used to build predictive models for readmission within 30 days of discharge using logistic regression, classification and regression tree (CART) analysis, and random forests. One model (logistic regression) was then placed prospectively into the discharge workflow from March 2016 to May 2016 to determine the model's ability to predict which patients would be readmitted within 30 days. Results In total, 174 admissions had descriptive data. Thirty-two were excluded due to incomplete data. Logistic regression, CART, and random forest predictive models were constructed using the remaining 142 admissions. When applied to 106 consecutive prospective head and neck oncology patients at the time of discharge, the logistic regression model predicted readmissions with a specificity of 94%, a sensitivity of 47%, a negative predictive value of 90%, and a positive predictive value of 62% (odds ratio, 14.9; 95% confidence interval, 4.02-55.45). Conclusion Prospectively collected head and neck cancer databases can be used to develop predictive models that can accurately predict which patients will be readmitted. This offers valuable support for quality improvement initiatives and readmission-related cost reduction in head and neck cancer care.

  4. Probing the dynamics of identified neurons with a data-driven modeling approach.

    Directory of Open Access Journals (Sweden)

    Thomas Nowotny

    2008-07-01

    Full Text Available In controlling animal behavior the nervous system has to perform within the operational limits set by the requirements of each specific behavior. The implications for the corresponding range of suitable network, single neuron, and ion channel properties have remained elusive. In this article we approach the question of how well-constrained properties of neuronal systems may be on the neuronal level. We used large data sets of the activity of isolated invertebrate identified cells and built an accurate conductance-based model for this cell type using customized automated parameter estimation techniques. By direct inspection of the data we found that the variability of the neurons is larger when they are isolated from the circuit than when in the intact system. Furthermore, the responses of the neurons to perturbations appear to be more consistent than their autonomous behavior under stationary conditions. In the developed model, the constraints on different parameters that enforce appropriate model dynamics vary widely from some very tightly controlled parameters to others that are almost arbitrary. The model also allows predictions for the effect of blocking selected ionic currents and to prove that the origin of irregular dynamics in the neuron model is proper chaoticity and that this chaoticity is typical in an appropriate sense. Our results indicate that data driven models are useful tools for the in-depth analysis of neuronal dynamics. The better consistency of responses to perturbations, in the real neurons as well as in the model, suggests a paradigm shift away from measuring autonomous dynamics alone towards protocols of controlled perturbations. Our predictions for the impact of channel blockers on the neuronal dynamics and the proof of chaoticity underscore the wide scope of our approach.

  5. Using Watershed Models and Human Behavioral Analyses to identify Management Options to Reduce Lake Erie's Harmful Algal Blooms

    Science.gov (United States)

    Martin, J.; Wilson, R. S.; Aloysius, N.; Kalcic, M. M.; Roe, B.; Howard, G.; Irwin, E.; Zhang, W.; Liu, H.

    2017-12-01

    In early 2016, the United States and Canada formally agreed to reduce phosphorus inputs to Lake Erie by 40% to reduce the severity of annual Harmful Algal Blooms (HABs). These blooms have become more severe, with record events occurring in 2011 and 2015, and have compromised public safety, shut down drinking water supplies, and negatively impacted the economy of the western Lake Erie basin. Now, a key question is what management options should be pursued to reach the 40% reduction. This presentation will highlight interdisciplinary research to compare the amount and types of practices needed for this reduction to the current and projected levels of adoption. Multiple models of the Maumee watershed identified management plans and adoption rates needed to reach the reduction targets. For example, one successful scenario estimated necessary adoption rates of 50% for subsurface application of fertilizer on row crops, 58% for cover crops, and 78% for buffer strips. Current adoption is below these levels, but future projections based on farmer surveys shows these levels are possible. This information was then used to guide another round of watershed modeling analysis to evaluate scenarios that represented more realistic scenarios based on potential levels of management adoption. In general, these results show that accelerated adoption of management plans is needed compared to past adoption rates, and that some of these greater adoption levels are possible based on likely adoption rates. Increasing the perceived efficacy of the practices is one method that will support greater voluntary rates of adoption.

  6. Data Mining and Pattern Recognition Models for Identifying Inherited Diseases: Challenges and Implications.

    Science.gov (United States)

    Iddamalgoda, Lahiru; Das, Partha S; Aponso, Achala; Sundararajan, Vijayaraghava S; Suravajhala, Prashanth; Valadi, Jayaraman K

    2016-01-01

    Data mining and pattern recognition methods reveal interesting findings in genetic studies, especially on how the genetic makeup is associated with inherited diseases. Although researchers have proposed various data mining models for biomedical approaches, there remains a challenge in accurately prioritizing the single nucleotide polymorphisms (SNP) associated with the disease. In this commentary, we review the state-of-art data mining and pattern recognition models for identifying inherited diseases and deliberate the need of binary classification- and scoring-based prioritization methods in determining causal variants. While we discuss the pros and cons associated with these methods known, we argue that the gene prioritization methods and the protein interaction (PPI) methods in conjunction with the K nearest neighbors' could be used in accurately categorizing the genetic factors in disease causation.

  7. Data mining and Pattern Recognizing Models for Identifying Inherited Diseases: Challenges and Implications

    Directory of Open Access Journals (Sweden)

    Lahiru Iddamalgoda

    2016-08-01

    Full Text Available Data mining and pattern recognition methods reveal interesting findings in genetic studies, especially on how genetic makeup is associated with inherited diseases. Although researchers have proposed various data mining models for biomedical approaches, there remains a challenge in accurately determining the responsible genetic factors for prioritizing the single nucleotide polymorphisms (SNP associated with the disease. In this commentary, we review the state-of-art data mining and pattern recognition models for identifying inherited diseases and deliberate the need of binary classification and scoring based prioritization methods for determining causal variants. While we discuss the pros and cons associated with these methods known, we argue that the gene prioritization methods and the protein interaction (PPI methods in conjunction with the K nearest neighbors’ could be used in accurately categorizing the genetic factors in disease causation

  8. Staphylococcus aureus virulence factors identified by using a high-throughput Caenorhabditis elegans-killing model.

    Science.gov (United States)

    Begun, Jakob; Sifri, Costi D; Goldman, Samuel; Calderwood, Stephen B; Ausubel, Frederick M

    2005-02-01

    Staphylococcus aureus is an important human pathogen that is also able to kill the model nematode Caenorhabditis elegans. We constructed a 2,950-member Tn917 transposon insertion library in S. aureus strain NCTC 8325. Twenty-one of these insertions exhibited attenuated C. elegans killing, and of these, 12 contained insertions in different genes or chromosomal locations. Ten of these 12 insertions showed attenuated killing phenotypes when transduced into two different S. aureus strains, and 5 of the 10 mutants correspond to genes that have not been previously identified in signature-tagged mutagenesis studies. These latter five mutants were tested in a murine renal abscess model, and one mutant harboring an insertion in nagD exhibited attenuated virulence. Interestingly, Tn917 was shown to have a very strong bias for insertions near the terminus of DNA replication.

  9. A Simple Model to Identify Risk of Sarcopenia and Physical Disability in HIV-Infected Patients.

    Science.gov (United States)

    Farinatti, Paulo; Paes, Lorena; Harris, Elizabeth A; Lopes, Gabriella O; Borges, Juliana P

    2017-09-01

    Farinatti, P, Paes, L, Harris, EA, Lopes, GO, and Borges, JP. A simple model to identify risk of sarcopenia and physical disability in HIV-infected patients. J Strength Cond Res 31(9): 2542-2551, 2017-Early detection of sarcopenia might help preventing muscle loss and disability in HIV-infected patients. This study proposed a model for estimating appendicular skeletal muscle mass (ASM) to calculate indices to identify "sarcopenia" (SA) and "risk for disability due to sarcopenia" (RSA) in patients with HIV. An equation to estimate ASM was developed in 56 patients (47.2 ± 6.9 years), with a cross-validation sample of 24 patients (48.1 ± 6.6 years). The model validity was determined by calculating, in both samples: (a) Concordance between actual vs. estimated ASM; (b) Correlations between actual/estimated ASM vs. peak torque (PT) and total work (TW) during isokinetic knee extension/flexion; (c) Agreement of patients classified with SA and RSA. The predictive equation was ASM (kg) = 7.77 (sex; F = 0/M = 1) + 0.26 (arm circumference; cm) + 0.38 (thigh circumference; cm) + 0.03 (Body Mass Index; kg·m) - 8.94 (R = 0.74; Radj = 0.72; SEE = 3.13 kg). Agreement between actual vs. estimated ASM was confirmed in validation (t = 0.081/p = 0.94; R = 0.86/p < 0.0001) and cross-validation (t = 0.12/p = 0.92; R = 0.87/p < 0.0001) samples. Regression characteristics in cross-validation sample (Radj = 0.80; SEE = 3.65) and PRESS (RPRESS = 0.69; SEEPRESS = 3.35) were compatible with the original model. Percent agreements for the classification of SA and RSA from indices calculated using actual and estimated ASM were of 87.5% and 77.2% (gamma correlations 0.72-1.0; p < 0.04) in validation, and 95.8% and 75.0% (gamma correlations 0.98-0.97; p < 0.001) in cross-validation sample, respectively. Correlations between actual/estimated ASM vs. PT (range 0.50-0.73, p ≤ 0.05) and TW (range 0.59-0.74, p ≤ 0.05) were similar in both samples. In conclusion, our model correctly estimated ASM

  10. Sensitivity of Ocean Reflectance Inversion Models for Identifying and Discriminating Between Phytoplankton Functional Groups

    Science.gov (United States)

    Werdell, P. Jeremy; Ooesler, Collin S.

    2012-01-01

    The daily, synoptic images provided by satellite ocean color instruments provide viable data streams for observing changes in the biogeochemistrY of marine ecosystems. Ocean reflectance inversion models (ORMs) provide a common mechanism for inverting the "color" of the water observed a satellite into marine inherent optical properties (lOPs) through a combination of empiricism and radiative transfer theory. lOPs, namely the spectral absorption and scattering characteristics of ocean water and its dissolved and particulate constituents, describe the contents of the upper ocean, information critical for furthering scientific understanding of biogeochemical oceanic processes. Many recent studies inferred marine particle sizes and discriminated between phytoplankton functional groups using remotely-sensed lOPs. While all demonstrated the viability of their approaches, few described the vertical distributions of the water column constituents under consideration and, thus, failed to report the biophysical conditions under which their model performed (e.g., the depth and thickness of the phytoplankton bloom(s)). We developed an ORM to remotely identifY Noctiluca miliaris and other phytoplankton functional types using satellite ocean color data records collected in the northern Arabian Sea. Here, we present results from analyses designed to evaluate the applicability and sensitivity of the ORM to varied biophysical conditions. Specifically, we: (1) synthesized a series of vertical profiles of spectral inherent optical properties that represent a wide variety of bio-optical conditions for the northern Arabian Sea under aN Miliaris bloom; (2) generated spectral remote-sensing reflectances from these profiles using Hydrolight; and, (3) applied the ORM to the synthesized reflectances to estimate the relative concentrations of diatoms and N Miliaris for each example. By comparing the estimates from the inversion model to those from synthesized vertical profiles, we were able to

  11. DESCARTES' RULE OF SIGNS AND THE IDENTIFIABILITY OF POPULATION DEMOGRAPHIC MODELS FROM GENOMIC VARIATION DATA.

    Science.gov (United States)

    Bhaskar, Anand; Song, Yun S

    2014-01-01

    The sample frequency spectrum (SFS) is a widely-used summary statistic of genomic variation in a sample of homologous DNA sequences. It provides a highly efficient dimensional reduction of large-scale population genomic data and its mathematical dependence on the underlying population demography is well understood, thus enabling the development of efficient inference algorithms. However, it has been recently shown that very different population demographies can actually generate the same SFS for arbitrarily large sample sizes. Although in principle this nonidentifiability issue poses a thorny challenge to statistical inference, the population size functions involved in the counterexamples are arguably not so biologically realistic. Here, we revisit this problem and examine the identifiability of demographic models under the restriction that the population sizes are piecewise-defined where each piece belongs to some family of biologically-motivated functions. Under this assumption, we prove that the expected SFS of a sample uniquely determines the underlying demographic model, provided that the sample is sufficiently large. We obtain a general bound on the sample size sufficient for identifiability; the bound depends on the number of pieces in the demographic model and also on the type of population size function in each piece. In the cases of piecewise-constant, piecewise-exponential and piecewise-generalized-exponential models, which are often assumed in population genomic inferences, we provide explicit formulas for the bounds as simple functions of the number of pieces. Lastly, we obtain analogous results for the "folded" SFS, which is often used when there is ambiguity as to which allelic type is ancestral. Our results are proved using a generalization of Descartes' rule of signs for polynomials to the Laplace transform of piecewise continuous functions.

  12. DESCARTES’ RULE OF SIGNS AND THE IDENTIFIABILITY OF POPULATION DEMOGRAPHIC MODELS FROM GENOMIC VARIATION DATA1

    Science.gov (United States)

    Bhaskar, Anand; Song, Yun S.

    2016-01-01

    The sample frequency spectrum (SFS) is a widely-used summary statistic of genomic variation in a sample of homologous DNA sequences. It provides a highly efficient dimensional reduction of large-scale population genomic data and its mathematical dependence on the underlying population demography is well understood, thus enabling the development of efficient inference algorithms. However, it has been recently shown that very different population demographies can actually generate the same SFS for arbitrarily large sample sizes. Although in principle this nonidentifiability issue poses a thorny challenge to statistical inference, the population size functions involved in the counterexamples are arguably not so biologically realistic. Here, we revisit this problem and examine the identifiability of demographic models under the restriction that the population sizes are piecewise-defined where each piece belongs to some family of biologically-motivated functions. Under this assumption, we prove that the expected SFS of a sample uniquely determines the underlying demographic model, provided that the sample is sufficiently large. We obtain a general bound on the sample size sufficient for identifiability; the bound depends on the number of pieces in the demographic model and also on the type of population size function in each piece. In the cases of piecewise-constant, piecewise-exponential and piecewise-generalized-exponential models, which are often assumed in population genomic inferences, we provide explicit formulas for the bounds as simple functions of the number of pieces. Lastly, we obtain analogous results for the “folded” SFS, which is often used when there is ambiguity as to which allelic type is ancestral. Our results are proved using a generalization of Descartes’ rule of signs for polynomials to the Laplace transform of piecewise continuous functions. PMID:28018011

  13. Parallel approach to identifying the well-test interpretation model using a neurocomputer

    Science.gov (United States)

    May, Edward A., Jr.; Dagli, Cihan H.

    1996-03-01

    The well test is one of the primary diagnostic and predictive tools used in the analysis of oil and gas wells. In these tests, a pressure recording device is placed in the well and the pressure response is recorded over time under controlled flow conditions. The interpreted results are indicators of the well's ability to flow and the damage done to the formation surrounding the wellbore during drilling and completion. The results are used for many purposes, including reservoir modeling (simulation) and economic forecasting. The first step in the analysis is the identification of the Well-Test Interpretation (WTI) model, which determines the appropriate solution method. Mis-identification of the WTI model occurs due to noise and non-ideal reservoir conditions. Previous studies have shown that a feed-forward neural network using the backpropagation algorithm can be used to identify the WTI model. One of the drawbacks to this approach is, however, training time, which can run into days of CPU time on personal computers. In this paper a similar neural network is applied using both a personal computer and a neurocomputer. Input data processing, network design, and performance are discussed and compared. The results show that the neurocomputer greatly eases the burden of training and allows the network to outperform a similar network running on a personal computer.

  14. Targetable vulnerabilities in T- and NK-cell lymphomas identified through preclinical models.

    Science.gov (United States)

    Ng, Samuel Y; Yoshida, Noriaki; Christie, Amanda L; Ghandi, Mahmoud; Dharia, Neekesh V; Dempster, Joshua; Murakami, Mark; Shigemori, Kay; Morrow, Sara N; Van Scoyk, Alexandria; Cordero, Nicolas A; Stevenson, Kristen E; Puligandla, Maneka; Haas, Brian; Lo, Christopher; Meyers, Robin; Gao, Galen; Cherniack, Andrew; Louissaint, Abner; Nardi, Valentina; Thorner, Aaron R; Long, Henry; Qiu, Xintao; Morgan, Elizabeth A; Dorfman, David M; Fiore, Danilo; Jang, Julie; Epstein, Alan L; Dogan, Ahmet; Zhang, Yanming; Horwitz, Steven M; Jacobsen, Eric D; Santiago, Solimar; Ren, Jian-Guo; Guerlavais, Vincent; Annis, D Allen; Aivado, Manuel; Saleh, Mansoor N; Mehta, Amitkumar; Tsherniak, Aviad; Root, David; Vazquez, Francisca; Hahn, William C; Inghirami, Giorgio; Aster, Jon C; Weinstock, David M; Koch, Raphael

    2018-05-22

    T- and NK-cell lymphomas (TCL) are a heterogenous group of lymphoid malignancies with poor prognosis. In contrast to B-cell and myeloid malignancies, there are few preclinical models of TCLs, which has hampered the development of effective therapeutics. Here we establish and characterize preclinical models of TCL. We identify multiple vulnerabilities that are targetable with currently available agents (e.g., inhibitors of JAK2 or IKZF1) and demonstrate proof-of-principle for biomarker-driven therapies using patient-derived xenografts (PDXs). We show that MDM2 and MDMX are targetable vulnerabilities within TP53-wild-type TCLs. ALRN-6924, a stapled peptide that blocks interactions between p53 and both MDM2 and MDMX has potent in vitro activity and superior in vivo activity across 8 different PDX models compared to the standard-of-care agent romidepsin. ALRN-6924 induced a complete remission in a patient with TP53-wild-type angioimmunoblastic T-cell lymphoma, demonstrating the potential for rapid translation of discoveries from subtype-specific preclinical models.

  15. Hidden Markov model approach for identifying the modular framework of the protein backbone.

    Science.gov (United States)

    Camproux, A C; Tuffery, P; Chevrolat, J P; Boisvieux, J F; Hazout, S

    1999-12-01

    The hidden Markov model (HMM) was used to identify recurrent short 3D structural building blocks (SBBs) describing protein backbones, independently of any a priori knowledge. Polypeptide chains are decomposed into a series of short segments defined by their inter-alpha-carbon distances. Basically, the model takes into account the sequentiality of the observed segments and assumes that each one corresponds to one of several possible SBBs. Fitting the model to a database of non-redundant proteins allowed us to decode proteins in terms of 12 distinct SBBs with different roles in protein structure. Some SBBs correspond to classical regular secondary structures. Others correspond to a significant subdivision of their bounding regions previously considered to be a single pattern. The major contribution of the HMM is that this model implicitly takes into account the sequential connections between SBBs and thus describes the most probable pathways by which the blocks are connected to form the framework of the protein structures. Validation of the SBBs code was performed by extracting SBB series repeated in recoding proteins and examining their structural similarities. Preliminary results on the sequence specificity of SBBs suggest promising perspectives for the prediction of SBBs or series of SBBs from the protein sequences.

  16. A model-based approach to identify binding sites in CLIP-Seq data.

    Directory of Open Access Journals (Sweden)

    Tao Wang

    Full Text Available Cross-linking immunoprecipitation coupled with high-throughput sequencing (CLIP-Seq has made it possible to identify the targeting sites of RNA-binding proteins in various cell culture systems and tissue types on a genome-wide scale. Here we present a novel model-based approach (MiClip to identify high-confidence protein-RNA binding sites from CLIP-seq datasets. This approach assigns a probability score for each potential binding site to help prioritize subsequent validation experiments. The MiClip algorithm has been tested in both HITS-CLIP and PAR-CLIP datasets. In the HITS-CLIP dataset, the signal/noise ratios of miRNA seed motif enrichment produced by the MiClip approach are between 17% and 301% higher than those by the ad hoc method for the top 10 most enriched miRNAs. In the PAR-CLIP dataset, the MiClip approach can identify ∼50% more validated binding targets than the original ad hoc method and two recently published methods. To facilitate the application of the algorithm, we have released an R package, MiClip (http://cran.r-project.org/web/packages/MiClip/index.html, and a public web-based graphical user interface software (http://galaxy.qbrc.org/tool_runner?tool_id=mi_clip for customized analysis.

  17. C. elegans model identifies genetic modifiers of alpha-synuclein inclusion formation during aging.

    Directory of Open Access Journals (Sweden)

    Tjakko J van Ham

    2008-03-01

    Full Text Available Inclusions in the brain containing alpha-synuclein are the pathological hallmark of Parkinson's disease, but how these inclusions are formed and how this links to disease is poorly understood. We have developed a C. elegans model that makes it possible to monitor, in living animals, the formation of alpha-synuclein inclusions. In worms of old age, inclusions contain aggregated alpha- synuclein, resembling a critical pathological feature. We used genome-wide RNA interference to identify processes involved in inclusion formation, and identified 80 genes that, when knocked down, resulted in a premature increase in the number of inclusions. Quality control and vesicle-trafficking genes expressed in the ER/Golgi complex and vesicular compartments were overrepresented, indicating a specific role for these processes in alpha-synuclein inclusion formation. Suppressors include aging-associated genes, such as sir-2.1/SIRT1 and lagr-1/LASS2. Altogether, our data suggest a link between alpha-synuclein inclusion formation and cellular aging, likely through an endomembrane-related mechanism. The processes and genes identified here present a framework for further study of the disease mechanism and provide candidate susceptibility genes and drug targets for Parkinson's disease and other alpha-synuclein related disorders.

  18. Use of artificial intelligence to identify cardiovascular compromise in a model of hemorrhagic shock.

    Science.gov (United States)

    Glass, Todd F; Knapp, Jason; Amburn, Philip; Clay, Bruce A; Kabrisky, Matt; Rogers, Steven K; Garcia, Victor F

    2004-02-01

    To determine whether a prototype artificial intelligence system can identify volume of hemorrhage in a porcine model of controlled hemorrhagic shock. Prospective in vivo animal model of hemorrhagic shock. Research foundation animal surgical suite; computer laboratories of collaborating industry partner. Nineteen, juvenile, 25- to 35-kg, male and female swine. Anesthetized animals were instrumented for arterial and systemic venous pressure monitoring and blood sampling, and a splenectomy was performed. Following a 1-hr stabilization period, animals were hemorrhaged in aliquots to 10, 20, 30, 35, 40, 45, and 50% of total blood volume with a 10-min recovery between each aliquot. Data were downloaded directly from a commercial monitoring system into a proprietary PC-based software package for analysis. Arterial and venous blood gas values, glucose, and cardiac output were collected at specified intervals. Electrocardiogram, electroencephalogram, mixed venous oxygen saturation, temperature (core and blood), mean arterial pressure, pulmonary artery pressure, central venous pressure, pulse oximetry, and end-tidal CO(2) were continuously monitored and downloaded. Seventeen of 19 animals (89%) died as a direct result of hemorrhage. Stored data streams were analyzed by the prototype artificial intelligence system. For this project, the artificial intelligence system identified and compared three electrocardiographic features (R-R interval, QRS amplitude, and R-S interval) from each of nine unknown samples of the QRS complex. We found that the artificial intelligence system, trained on only three electrocardiographic features, identified hemorrhage volume with an average accuracy of 91% (95% confidence interval, 84-96%). These experiments demonstrate that an artificial intelligence system, based solely on the analysis of QRS amplitude, R-R interval, and R-S interval of an electrocardiogram, is able to accurately identify hemorrhage volume in a porcine model of lethal

  19. Identifying the decision to be supported: a review of papers from environmental modelling and software

    Science.gov (United States)

    Sojda, Richard S.; Chen, Serena H.; El Sawah, Sondoss; Guillaume, Joseph H.A.; Jakeman, A.J.; Lautenbach, Sven; McIntosh, Brian S.; Rizzoli, A.E.; Seppelt, Ralf; Struss, Peter; Voinov, Alexey; Volk, Martin

    2012-01-01

    Two of the basic tenets of decision support system efforts are to help identify and structure the decisions to be supported, and to then provide analysis in how those decisions might be best made. One example from wetland management would be that wildlife biologists must decide when to draw down water levels to optimise aquatic invertebrates as food for breeding ducks. Once such a decision is identified, a system or tool to help them make that decision in the face of current and projected climate conditions could be developed. We examined a random sample of 100 papers published from 2001-2011 in Environmental Modelling and Software that used the phrase “decision support system” or “decision support tool”, and which are characteristic of different sectors. In our review, 41% of the systems and tools related to the water resources sector, 34% were related to agriculture, and 22% to the conservation of fish, wildlife, and protected area management. Only 60% of the papers were deemed to be reporting on DSS. This was based on the papers reviewed not having directly identified a specific decision to be supported. We also report on the techniques that were used to identify the decisions, such as formal survey, focus group, expert opinion, or sole judgment of the author(s). The primary underlying modelling system, e.g., expert system, agent based model, Bayesian belief network, geographical information system (GIS), and the like was categorised next. Finally, since decision support typically should target some aspect of unstructured decisions, we subjectively determined to what degree this was the case. In only 23% of the papers reviewed, did the system appear to tackle unstructured decisions. This knowledge should be useful in helping workers in the field develop more effective systems and tools, especially by being exposed to the approaches in different, but related, disciplines. We propose that a standard blueprint for reporting on DSS be developed for

  20. A Fuzzy Computing Model for Identifying Polarity of Chinese Sentiment Words.

    Science.gov (United States)

    Wang, Bingkun; Huang, Yongfeng; Wu, Xian; Li, Xing

    2015-01-01

    With the spurt of online user-generated contents on web, sentiment analysis has become a very active research issue in data mining and natural language processing. As the most important indicator of sentiment, sentiment words which convey positive and negative polarity are quite instrumental for sentiment analysis. However, most of the existing methods for identifying polarity of sentiment words only consider the positive and negative polarity by the Cantor set, and no attention is paid to the fuzziness of the polarity intensity of sentiment words. In order to improve the performance, we propose a fuzzy computing model to identify the polarity of Chinese sentiment words in this paper. There are three major contributions in this paper. Firstly, we propose a method to compute polarity intensity of sentiment morphemes and sentiment words. Secondly, we construct a fuzzy sentiment classifier and propose two different methods to compute the parameter of the fuzzy classifier. Thirdly, we conduct extensive experiments on four sentiment words datasets and three review datasets, and the experimental results indicate that our model performs better than the state-of-the-art methods.

  1. A Fuzzy Computing Model for Identifying Polarity of Chinese Sentiment Words

    Directory of Open Access Journals (Sweden)

    Bingkun Wang

    2015-01-01

    Full Text Available With the spurt of online user-generated contents on web, sentiment analysis has become a very active research issue in data mining and natural language processing. As the most important indicator of sentiment, sentiment words which convey positive and negative polarity are quite instrumental for sentiment analysis. However, most of the existing methods for identifying polarity of sentiment words only consider the positive and negative polarity by the Cantor set, and no attention is paid to the fuzziness of the polarity intensity of sentiment words. In order to improve the performance, we propose a fuzzy computing model to identify the polarity of Chinese sentiment words in this paper. There are three major contributions in this paper. Firstly, we propose a method to compute polarity intensity of sentiment morphemes and sentiment words. Secondly, we construct a fuzzy sentiment classifier and propose two different methods to compute the parameter of the fuzzy classifier. Thirdly, we conduct extensive experiments on four sentiment words datasets and three review datasets, and the experimental results indicate that our model performs better than the state-of-the-art methods.

  2. Identifying potential misfit items in cognitive process of learning engineering mathematics based on Rasch model

    International Nuclear Information System (INIS)

    Ataei, Sh; Mahmud, Z; Khalid, M N

    2014-01-01

    The students learning outcomes clarify what students should know and be able to demonstrate after completing their course. So, one of the issues on the process of teaching and learning is how to assess students' learning. This paper describes an application of the dichotomous Rasch measurement model in measuring the cognitive process of engineering students' learning of mathematics. This study provides insights into the perspective of 54 engineering students' cognitive ability in learning Calculus III based on Bloom's Taxonomy on 31 items. The results denote that some of the examination questions are either too difficult or too easy for the majority of the students. This analysis yields FIT statistics which are able to identify if there is data departure from the Rasch theoretical model. The study has identified some potential misfit items based on the measurement of ZSTD where the removal misfit item was accomplished based on the MNSQ outfit of above 1.3 or less than 0.7 logit. Therefore, it is recommended that these items be reviewed or revised to better match the range of students' ability in the respective course.

  3. A Fuzzy Computing Model for Identifying Polarity of Chinese Sentiment Words

    Science.gov (United States)

    Huang, Yongfeng; Wu, Xian; Li, Xing

    2015-01-01

    With the spurt of online user-generated contents on web, sentiment analysis has become a very active research issue in data mining and natural language processing. As the most important indicator of sentiment, sentiment words which convey positive and negative polarity are quite instrumental for sentiment analysis. However, most of the existing methods for identifying polarity of sentiment words only consider the positive and negative polarity by the Cantor set, and no attention is paid to the fuzziness of the polarity intensity of sentiment words. In order to improve the performance, we propose a fuzzy computing model to identify the polarity of Chinese sentiment words in this paper. There are three major contributions in this paper. Firstly, we propose a method to compute polarity intensity of sentiment morphemes and sentiment words. Secondly, we construct a fuzzy sentiment classifier and propose two different methods to compute the parameter of the fuzzy classifier. Thirdly, we conduct extensive experiments on four sentiment words datasets and three review datasets, and the experimental results indicate that our model performs better than the state-of-the-art methods. PMID:26106409

  4. Theoretical and Numerical Modeling of Transport of Land Use-Specific Fecal Source Identifiers

    Science.gov (United States)

    Bombardelli, F. A.; Sirikanchana, K. J.; Bae, S.; Wuertz, S.

    2008-12-01

    Microbial contamination in coastal and estuarine waters is of particular concern to public health officials. In this work, we advocate that well-formulated and developed mathematical and numerical transport models can be combined with modern molecular techniques in order to predict continuous concentrations of microbial indicators under diverse scenarios of interest, and that they can help in source identification of fecal pollution. As a proof of concept, we present initially the theory, numerical implementation and validation of one- and two-dimensional numerical models aimed at computing the distribution of fecal source identifiers in water bodies (based on Bacteroidales marker DNA sequences) coming from different land uses such as wildlife, livestock, humans, dogs or cats. These models have been developed to allow for source identification of fecal contamination in large bodies of water. We test the model predictions using diverse velocity fields and boundary conditions. Then, we present some preliminary results of an application of a three-dimensional water quality model to address the source of fecal contamination in the San Pablo Bay (SPB), United States, which constitutes an important sub-embayment of the San Francisco Bay. The transport equations for Bacteroidales include the processes of advection, diffusion, and decay of Bacteroidales. We discuss the validation of the developed models through comparisons of numerical results with field campaigns developed in the SPB. We determine the extent and importance of the contamination in the bay for two decay rates obtained from field observations, corresponding to total host-specific Bacteroidales DNA and host-specific viable Bacteroidales cells, respectively. Finally, we infer transport conditions in the SPB based on the numerical results, characterizing the fate of outflows coming from the Napa, Petaluma and Sonoma rivers.

  5. Modelling efforts needed to advance herpes simplex virus (HSV) vaccine development: Key findings from the World Health Organization Consultation on HSV Vaccine Impact Modelling.

    Science.gov (United States)

    Gottlieb, Sami L; Giersing, Birgitte; Boily, Marie-Claude; Chesson, Harrell; Looker, Katharine J; Schiffer, Joshua; Spicknall, Ian; Hutubessy, Raymond; Broutet, Nathalie

    2017-06-21

    Development of a vaccine against herpes simplex virus (HSV) is an important goal for global sexual and reproductive health. In order to more precisely define the health and economic burden of HSV infection and the theoretical impact and cost-effectiveness of an HSV vaccine, in 2015 the World Health Organization convened an expert consultation meeting on HSV vaccine impact modelling. The experts reviewed existing model-based estimates and dynamic models of HSV infection to outline critical future modelling needs to inform development of a comprehensive business case and preferred product characteristics for an HSV vaccine. This article summarizes key findings and discussions from the meeting on modelling needs related to HSV burden, costs, and vaccine impact, essential data needs to carry out those models, and important model components and parameters. Copyright © 2017. Published by Elsevier Ltd.

  6. Stable isotopes of fossil teeth corroborate key general circulation model predictions for the Last Glacial Maximum in North America

    Science.gov (United States)

    Kohn, Matthew J.; McKay, Moriah

    2010-11-01

    Oxygen isotope data provide a key test of general circulation models (GCMs) for the Last Glacial Maximum (LGM) in North America, which have otherwise proved difficult to validate. High δ18O pedogenic carbonates in central Wyoming have been interpreted to indicate increased summer precipitation sourced from the Gulf of Mexico. Here we show that tooth enamel δ18O of large mammals, which is strongly correlated with local water and precipitation δ18O, is lower during the LGM in Wyoming, not higher. Similar data from Texas, California, Florida and Arizona indicate higher δ18O values than in the Holocene, which is also predicted by GCMs. Tooth enamel data closely validate some recent models of atmospheric circulation and precipitation δ18O, including an increase in the proportion of winter precipitation for central North America, and summer precipitation in the southern US, but suggest aridity can bias pedogenic carbonate δ18O values significantly.

  7. Kernel density surface modelling as a means to identify significant concentrations of vulnerable marine ecosystem indicators.

    Directory of Open Access Journals (Sweden)

    Ellen Kenchington

    Full Text Available The United Nations General Assembly Resolution 61/105, concerning sustainable fisheries in the marine ecosystem, calls for the protection of vulnerable marine ecosystems (VME from destructive fishing practices. Subsequently, the Food and Agriculture Organization (FAO produced guidelines for identification of VME indicator species/taxa to assist in the implementation of the resolution, but recommended the development of case-specific operational definitions for their application. We applied kernel density estimation (KDE to research vessel trawl survey data from inside the fishing footprint of the Northwest Atlantic Fisheries Organization (NAFO Regulatory Area in the high seas of the northwest Atlantic to create biomass density surfaces for four VME indicator taxa: large-sized sponges, sea pens, small and large gorgonian corals. These VME indicator taxa were identified previously by NAFO using the fragility, life history characteristics and structural complexity criteria presented by FAO, along with an evaluation of their recovery trajectories. KDE, a non-parametric neighbour-based smoothing function, has been used previously in ecology to identify hotspots, that is, areas of relatively high biomass/abundance. We present a novel approach of examining relative changes in area under polygons created from encircling successive biomass categories on the KDE surface to identify "significant concentrations" of biomass, which we equate to VMEs. This allows identification of the VMEs from the broader distribution of the species in the study area. We provide independent assessments of the VMEs so identified using underwater images, benthic sampling with other gear types (dredges, cores, and/or published species distribution models of probability of occurrence, as available. For each VME indicator taxon we provide a brief review of their ecological function which will be important in future assessments of significant adverse impact on these habitats here

  8. Trace Metal Bioremediation: Assessment of Model Components from Laboratory and Field Studies to Identify Critical Variables

    International Nuclear Information System (INIS)

    Peter Jaffe; Herschel Rabitz

    2003-01-01

    bioremediation of trace metals was highly sensitive to the formulation of the denitrification process. Simulations were performed to illustrate the effect of biostimulation on the transport and precipitation of uranium in the subsurface, at conditions equivalent to UMTRA sites. These simulations predicted that uranium would precipitate in bands that are located relatively close to the acetate injection well. The simulations also showed the importance of properly determining U(IV) oxidative dissolution rates, in order to assess the stability of precipitates once oxygenated water reenters the aquifer after bioremediation is discontinued. The objective of this project was to provide guidance to NABIR's Systems Integration Element, on the development of models to simulate the bioremediation of trace metals and radionuclides. Such models necessarily need to integrate hydrological, geochemical, and microbiological processes. In order to gain a better understanding of the key processes that such a model should contain, it was deemed desirable to convene a workshop with experts from these different fields. The goal was to obtain a preliminary consensus on the required level of detail for the formulations of these different chemical, physical, and microbiological processes. The workshop was held on December 18, 1998

  9. Key Challenges and Opportunities Associated with the Use of In Vitro Models to Detect Human DILI: Integrated Risk Assessment and Mitigation Plans

    Directory of Open Access Journals (Sweden)

    Franck A. Atienzar

    2016-01-01

    Full Text Available Drug-induced liver injury (DILI is a major cause of late-stage clinical drug attrition, market withdrawal, black-box warnings, and acute liver failure. Consequently, it has been an area of focus for toxicologists and clinicians for several decades. In spite of considerable efforts, limited improvements in DILI prediction have been made and efforts to improve existing preclinical models or develop new test systems remain a high priority. While prediction of intrinsic DILI has improved, identifying compounds with a risk for idiosyncratic DILI (iDILI remains extremely challenging because of the lack of a clear mechanistic understanding and the multifactorial pathogenesis of idiosyncratic drug reactions. Well-defined clinical diagnostic criteria and risk factors are also missing. This paper summarizes key data interpretation challenges, practical considerations, model limitations, and the need for an integrated risk assessment. As demonstrated through selected initiatives to address other types of toxicities, opportunities exist however for improvement, especially through better concerted efforts at harmonization of current, emerging and novel in vitro systems or through the establishment of strategies for implementation of preclinical DILI models across the pharmaceutical industry. Perspectives on the incorporation of newer technologies and the value of precompetitive consortia to identify useful practices are also discussed.

  10. Development of a model system to identify differences in spring and winter oat.

    Science.gov (United States)

    Chawade, Aakash; Lindén, Pernilla; Bräutigam, Marcus; Jonsson, Rickard; Jonsson, Anders; Moritz, Thomas; Olsson, Olof

    2012-01-01

    Our long-term goal is to develop a Swedish winter oat (Avena sativa). To identify molecular differences that correlate with winter hardiness, a winter oat model comprising of both non-hardy spring lines and winter hardy lines is needed. To achieve this, we selected 294 oat breeding lines, originating from various Russian, German, and American winter oat breeding programs and tested them in the field in south- and western Sweden. By assaying for winter survival and agricultural properties during four consecutive seasons, we identified 14 breeding lines of different origins that not only survived the winter but also were agronomically better than the rest. Laboratory tests including electrolytic leakage, controlled crown freezing assay, expression analysis of the AsVrn1 gene and monitoring of flowering time suggested that the American lines had the highest freezing tolerance, although the German lines performed better in the field. Finally, six lines constituting the two most freezing tolerant lines, two intermediate lines and two spring cultivars were chosen to build a winter oat model system. Metabolic profiling of non-acclimated and cold acclimated leaf tissue samples isolated from the six selected lines revealed differential expression patterns of 245 metabolites including several sugars, amino acids, organic acids and 181 hitherto unknown metabolites. The expression patterns of 107 metabolites showed significant interactions with either a cultivar or a time-point. Further identification, characterisation and validation of these metabolites will lead to an increased understanding of the cold acclimation process in oats. Furthermore, by using the winter oat model system, differential sequencing of crown mRNA populations would lead to identification of various biomarkers to facilitate winter oat breeding.

  11. Experimentally Identify the Effective Plume Chimney over a Natural Draft Chimney Model

    Science.gov (United States)

    Rahman, M