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. 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.

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

    Science.gov (United States)

    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. PMID:27706185

  5. 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.

  6. 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.

  7. 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

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

    Science.gov (United States)

    Dixit, Anshuman; Verkhivker, Gennady M

    2012-01-01

    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 residue clusters may be

  9. 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

  10. 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.

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

    Science.gov (United States)

    Ureña-Aranda, Cinthya A; Rojas-Soto, Octavio; Martínez-Meyer, Enrique; Yáñez-Arenas, Carlos; Landgrave Ramírez, Rosario; Espinosa de los Monteros, Alejandro

    2015-01-01

    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 < 0.05 was taken to be significant. 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

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

    Indian Academy of Sciences (India)

    Two key parameters were identified with each of the processes and multiple regression models were developed for each process. These models were tested and found to predict these processes quite accurately, and can be applied anywhere within the terrain. This technique can be reliably applied in areas where logistical ...

  16. 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

  17. 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 ...

  18. 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.

  19. Model plant key measurement points

    International Nuclear Information System (INIS)

    Anon.

    1981-01-01

    The key measurement points for the model low enriched fuel fabrication plant are described as well as the measurement methods. These are the measurement points and methods that are used to complete the plant's formal material balance. The purpose of the session is to enable participants to: (1) understand the basis for each key measurement; and (2) understand the importance of each measurement to the overall plant material balance. The feed to the model low enriched uranium fuel fabrication plant is UF 6 and the product is finished light water reactor fuel assemblies. The waste discards are solid and liquid wastes. The plant inventory consists of unopened UF 6 cylinders, UF 6 heels, fuel assemblies, fuel rods, fuel pellets, UO 2 powder, U 3 O 8 powder, and various scrap materials. At the key measurement points the total plant material balance (flow and inventory) is measured. The two types of key measurement points-flow and inventory are described

  20. Generalized Linear Models to Identify Key Hydromorphological and Chemical Variables Determining the Occurrence of Macroinvertebrates in the Guayas River Basin (Ecuador

    Directory of Open Access Journals (Sweden)

    Minar Naomi Damanik-Ambarita

    2016-07-01

    Full Text Available The biotic integrity of the Guayas River basin in Ecuador is at environmental risk due to extensive anthropogenic activities. We investigated the potential impacts of hydromorphological and chemical variables on biotic integrity using macroinvertebrate-based bioassessments. The bioassessment methods utilized included the Biological Monitoring Working Party adapted for Colombia (BMWP-Col and the average score per taxon (ASPT, via an extensive sampling campaign that was completed throughout the river basin at 120 sampling sites. The BMWP-Col classification ranged from very bad to good, and from probable severe pollution to clean water based on the ASPT scores. Generalized linear models (GLMs and sensitivity analysis were used to relate the bioassessment index to hydromorphological and chemical variables. It was found that elevation, nitrate-N, sediment angularity, logs, presence of macrophytes, flow velocity, turbidity, bank shape, land use and chlorophyll were the key environmental variables affecting the BMWP-Col. From the analyses, it was observed that the rivers at the upstream higher elevations of the river basin were in better condition compared to lowland systems and that a higher flow velocity was linked to a better BMWP-Col score. The nitrate concentrations were very low in the entire river basin and did not relate to a negative impact on the macroinvertebrate communities. Although the results of the models provided insights into the ecosystem, cross fold model development and validation also showed that there was a level of uncertainty in the outcomes. However, the results of the models and sensitivity analysis can support water management actions to determine and focus on alterable variables, such as the land use at different elevations, monitoring of nitrate and chlorophyll concentrations, macrophyte presence, sediment transport and bank stability.

  1. Identifying and tracking key odorants from cattle feedlots

    Science.gov (United States)

    Trabue, Steven; Scoggin, Kenwood; McConnell, Laura; Maghirang, Ronaldo; Razote, Edna; Hatfield, Jerry

    2011-08-01

    Odors from cattle feedlots can negatively affect air quality in local communities. Our objectives were the following: 1) identify key odor-causing compounds using odor activity values (OAVs) and gas chromatography-olfactometry (GC-O) techniques; 2) compare odor threshold values from published databases; and 3) track the movement of odors from a cattle feedlot to receptor community. Odorous compounds emitted from a cattle feedlot were sampled on-site, 250 m downwind and 3.2 km downwind using both sorbent tubes and denuders. Sorbent tubes were analyzed by both GC-MS and GC-MS-O and key odorants determined using both OAV and GC-Surface Nasal Impact Frequency (SNIF) analysis, while denuders were analyzed by ion chromatography. Odorant concentrations had a diurnal pattern with peak concentrations during early morning and late evening periods. Volatile fatty acids (VFAs) were the most abundant of the major odorants. Odorants with concentrations above their odor threshold values at the feedlot included amines, VFAs, phenol compounds, and indole compounds. Key odorants at the feedlot were VFAs and phenol compounds, but their relative importance diminished with downwind distance. Indole compounds, while not the key odorants at the feedlot, increased in relative importance downwind of the feedlot. In general, the odorous compounds identified by GC-SNIF and OAV as having fecal/manure nature were similar. GC-SNIF was the more sensitive analytical technique; it identified several compounds that may have contributed to the unpleasantness of the cattle feedlot odor, but its throughput was extremely low thereby limiting its usefulness. There is a need to improve field sampling devices and odor threshold databases to enhance understanding and confidence in evaluating odors.

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

    Science.gov (United States)

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

    2018-03-03

    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.

  3. 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

  4. 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

  5. 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)

  6. 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.

  7. 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

  8. 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

    2014-01-01

    Background: 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. Aims: This paper aims to define the key concerns of adults with an intellectual disability in relation to their participation in…

  9. 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)

  10. 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.

  11. Sparse Linear Identifiable Multivariate Modeling

    DEFF Research Database (Denmark)

    Henao, Ricardo; Winther, Ole

    2011-01-01

    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...... Bayesian hierarchy for sparse models using slab and spike priors (two-component δ-function and continuous mixtures), non-Gaussian latent factors and a stochastic search over the ordering of the variables. The framework, which we call SLIM (Sparse Linear Identifiable Multivariate modeling), is validated...... computational complexity. We attribute this mainly to the stochastic search strategy used, and to parsimony (sparsity and identifiability), which is an explicit part of the model. We propose two extensions to the basic i.i.d. linear framework: non-linear dependence on observed variables, called SNIM (Sparse Non-linear...

  12. Identifying key genes in glaucoma based on a benchmarked dataset and the gene regulatory network.

    Science.gov (United States)

    Chen, Xi; Wang, Qiao-Ling; Zhang, Meng-Hui

    2017-10-01

    The current study aimed to identify key genes in glaucoma based on a benchmarked dataset and gene regulatory network (GRN). Local and global noise was added to the gene expression dataset to produce a benchmarked dataset. Differentially-expressed genes (DEGs) between patients with glaucoma and normal controls were identified utilizing the Linear Models for Microarray Data (Limma) package based on benchmarked dataset. A total of 5 GRN inference methods, including Zscore, GeneNet, context likelihood of relatedness (CLR) algorithm, Partial Correlation coefficient with Information Theory (PCIT) and GEne Network Inference with Ensemble of Trees (Genie3) were evaluated using receiver operating characteristic (ROC) and precision and recall (PR) curves. The interference method with the best performance was selected to construct the GRN. Subsequently, topological centrality (degree, closeness and betweenness) was conducted to identify key genes in the GRN of glaucoma. Finally, the key genes were validated by performing reverse transcription-quantitative polymerase chain reaction (RT-qPCR). A total of 176 DEGs were detected from the benchmarked dataset. The ROC and PR curves of the 5 methods were analyzed and it was determined that Genie3 had a clear advantage over the other methods; thus, Genie3 was used to construct the GRN. Following topological centrality analysis, 14 key genes for glaucoma were identified, including IL6 , EPHA2 and GSTT1 and 5 of these 14 key genes were validated by RT-qPCR. Therefore, the current study identified 14 key genes in glaucoma, which may be potential biomarkers to use in the diagnosis of glaucoma and aid in identifying the molecular mechanism of this disease.

  13. 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.

  14. On the Use of MCDM Technique for Identifying Key Technology: A Case of Auto Company

    OpenAIRE

    Aliakbar Mazlomi; Rosnah bt. Mohd. Yusuff

    2011-01-01

    In today’s world, technology strategy development for industries is one of the most important tasks in proposing technology roadmap. Moreover, identifying strategic technology is main part of strategydevelopment. This article tries to apply MCDM methods in finding key strategic technologies from identified technologies from in order to provide appropriate technology strategy. TOPSIS method helps in finding key strategic technologies from identified technologies from in order to provide approp...

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. Identifying key interactions stabilizing DOF zinc finger-DNA complexes using in silico approaches.

    Science.gov (United States)

    Hamzeh-Mivehroud, Maryam; Moghaddas-Sani, Hakimeh; Rahbar-Shahrouziasl, Mahdieh; Dastmalchi, Siavoush

    2015-10-07

    DOF (DNA-binding with one finger) proteins, a family of DNA-binding transcription factors, are members of zinc fingers unique to plants. They are associated with different plant specific phenomena including germination, dormancy, light and defense responses. Until now, there is no report of experimentally solved structure for DOF proteins, making empirical investigation of DOF-DNA interaction more challenging. It has been shown that comparative modeling can be used to reliably predict the three-dimensional (3D) model of structurally unknown proteins whenever a suitable template is available. Furthermore, current molecular mechanics force fields allow prediction of interaction energies for macromolecular complexes. Therefore, the approaches considered in this work were to model the 3D structures of DOF zinc fingers (ZFs) from Arabidopsis thaliana complexed with DNA molecule, to calculate their binding energies, to identify key interactions established between ZFs and DNA, and to determine the impact of the different interactions on the binding energies. The results were used to predict the binding affinities for the novel designed ZFs and may be used in engineering DNA binding proteins. Copyright © 2015 Elsevier Ltd. All rights reserved.

  2. 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.

  3. 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.

  4. 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.

  5. 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

  6. Urban Warfare at the Operational Level: Identifying Centers of Gravity and Key Nodes

    National Research Council Canada - National Science Library

    McCleskey, Edward

    1999-01-01

    .... The intent of this paper is to focus the reader on the operational level of urban warfare. A key task for the Joint Force Commander and his staff will be to identify the targets against which he will employ his component forces...

  7. 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.

  8. Identifying same-cell contours in image stacks: a key step in making 3D reconstructions.

    Science.gov (United States)

    Leung, Tony Kin Shun; Veldhuis, Jim H; Krens, S F Gabby; Heisenberg, C P; Brodland, G Wayne

    2011-02-01

    Identification of contours belonging to the same cell is a crucial step in the analysis of confocal stacks and other image sets in which cell outlines are visible, and it is central to the making of 3D cell reconstructions. When the cells are close packed, the contour grouping problem is more complex than that found in medical imaging, for example, because there are multiple regions of interest, the regions are not separable from each other by an identifiable background and regions cannot be distinguished by intensity differences. Here, we present an algorithm that uses three primary metrics-overlap of contour areas in adjacent images, co-linearity of the centroids of these areas across three images in a stack, and cell taper-to assign cells to groups. Decreasing thresholds are used to successively assign contours whose membership is less obvious. In a final step, remaining contours are assigned to existing groups by setting all thresholds to zero and groups having strong hour-glass shapes are partitioned. When applied to synthetic data from isotropic model aggregates, a curved model epithelium in which the long axes of the cells lie at all possible angles to the transection plane, and a confocal image stack, algorithm assignments were between 97 and 100% accurate in sets having at least four contours per cell. The algorithm is not particularly sensitive to the thresholds used, and a single set of parameters was used for all of the tests. The algorithm, which could be extended to time-lapse data, solves a key problem in the translation of image data into cell information.

  9. 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

  10. Identifying Key Factors for Introducing GPS-Based Fleet Management Systems to the Logistics Industry

    Directory of Open Access Journals (Sweden)

    Yi-Chung Hu

    2015-01-01

    Full Text Available The rise of e-commerce and globalization has changed consumption patterns. Different industries have different logistical needs. In meeting needs with different schedules logistics play a key role. Delivering a seamless service becomes a source of competitive advantage for the logistics industry. Global positioning system-based fleet management system technology provides synergy to transport companies and achieves many management goals such as monitoring and tracking commodity distribution, energy saving, safety, and quality. A case company, which is a subsidiary of a very famous food and retail conglomerate and operates the largest shipping line in Taiwan, has suffered from the nonsmooth introduction of GPS-based fleet management systems in recent years. Therefore, this study aims to identify key factors for introducing related systems to the case company. By using DEMATEL and ANP, we can find not only key factors but also causes and effects among key factors. The results showed that support from executives was the most important criterion but it has the worst performance among key factors. It is found that adequate annual budget planning, enhancement of user intention, and collaboration with consultants with high specialty could be helpful to enhance the faith of top executives for successfully introducing the systems to the case company.

  11. Key Lake, a model of Canadian development

    International Nuclear Information System (INIS)

    Runnalls, O.J.C.

    1987-01-01

    Canada ranks among the world's top four countries in terms of measured, indicated, and inferred uranium resources. Since 1984, Canada has been the world's largest uranium producer providing some 30% of the world's total. An important reason for this strong position is related to the discovery of high-grade near-surface uranium deposits in northern Saskatchewan in 1968 and subsequently. The history of the discovery of one such deposit near Key Lake made by the German-controlled Uranerz Exploration and Mining Limited is recounted briefly. The Key Lake mine became operational in 1983 and currently is the largest uranium-producing facility in the world. At present, less than 20% of the country's annual uranium output of approximately 11,000 tonnes U is required to provide fuel for the domestic nuclear power program. The excess, more than 9000 tonnes U annually, is planned to be exported abroad, primarily to customers in Western Europe, Eastern Asia and the United States. Given its strong resource base, large-scale exports from Canada should continue well into the next century. (orig.) [de

  12. 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.

  13. Direct molecular targets of resveratrol: identifying key interactions to unlock complex mechanisms.

    Science.gov (United States)

    Britton, Robert G; Kovoor, Christina; Brown, Karen

    2015-08-01

    To truly understand the mechanisms through which resveratrol exerts its biological effects, the key direct interactions between resveratrol and its target biomolecules must be identified. With an increasing number of biochemical tools to measure and quantify direct physical interactions between biomolecules, there have been around 20 proteins identified as having a specific affinity to resveratrol to date. Resveratrol has been described as a promiscuous molecule, and one would expect it to bind with numerous proteins, which would help explain why resveratrol appears to have so many health benefits and has been shown to act upon various different pathways related to a diverse range of conditions. The aim of this review is to present the direct protein targets of resveratrol that are currently known and highlight the consequences of direct binding and the methods used to identify the nature of these interactions. © 2015 New York Academy of Sciences.

  14. 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.

  15. 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).

  16. 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...

  17. 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.

  18. 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.

  19. 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.

  20. 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

  1. 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

  2. Identifying motifs in folktales using topic models

    NARCIS (Netherlands)

    Karsdorp, F.; Bosch, A.P.J. van den

    2013-01-01

    With the undertake of various folktale digitalization initiatives, the need for computational aids to explore these collections is increasing. In this paper we compare Labeled LDA (L-LDA) to a simple retrieval model on the task of identifying motifs in folktales. We show that both methods are well

  3. Transcription Factor and lncRNA Regulatory Networks Identify Key Elements in Lung Adenocarcinoma

    Directory of Open Access Journals (Sweden)

    Dan Li

    2018-01-01

    Full Text Available Lung cancer is the second most commonly diagnosed carcinoma and is the leading cause of cancer death. Although significant progress has been made towards its understanding and treatment, unraveling the complexities of lung cancer is still hampered by a lack of comprehensive knowledge on the mechanisms underlying the disease. High-throughput and multidimensional genomic data have shed new light on cancer biology. In this study, we developed a network-based approach integrating somatic mutations, the transcriptome, DNA methylation, and protein-DNA interactions to reveal the key regulators in lung adenocarcinoma (LUAD. By combining Bayesian network analysis with tissue-specific transcription factor (TF and targeted gene interactions, we inferred 15 disease-related core regulatory networks in co-expression gene modules associated with LUAD. Through target gene set enrichment analysis, we identified a set of key TFs, including known cancer genes that potentially regulate the disease networks. These TFs were significantly enriched in multiple cancer-related pathways. Specifically, our results suggest that hepatitis viruses may contribute to lung carcinogenesis, highlighting the need for further investigations into the roles that viruses play in treating lung cancer. Additionally, 13 putative regulatory long non-coding RNAs (lncRNAs, including three that are known to be associated with lung cancer, and nine novel lncRNAs were revealed by our study. These lncRNAs and their target genes exhibited high interaction potentials and demonstrated significant expression correlations between normal lung and LUAD tissues. We further extended our study to include 16 solid-tissue tumor types and determined that the majority of these lncRNAs have putative regulatory roles in multiple cancers, with a few showing lung-cancer specific regulations. Our study provides a comprehensive investigation of transcription factor and lncRNA regulation in the context of LUAD

  4. 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...

  5. Excess winter mortality in Europe: a cross country analysis identifying key risk factors.

    Science.gov (United States)

    Healy, J D

    2003-10-01

    Much debate remains regarding why certain countries experience dramatically higher winter mortality. Potential causative factors other than cold exposure have rarely been analysed. Comparatively less research exists on excess winter deaths in southern Europe. Multiple time series data on a variety of risk factors are analysed against seasonal-mortality patterns in 14 European countries to identify key relations Subjects and setting: Excess winter deaths (all causes), 1988-97, EU-14. Coefficients of seasonal variation in mortality are calculated for EU-14 using monthly mortality data. Comparable, longitudinal datasets on risk factors pertaining to climate, macroeconomy, health care, lifestyle, socioeconomics, and housing were also obtained. Poisson regression identifies seasonality relations over time. Portugal suffers from the highest rates of excess winter mortality (28%, CI=25% to 31%) followed jointly by Spain (21%, CI=19% to 23%), and Ireland (21%, CI=18% to 24%). Cross country variations in mean winter environmental temperature (regression coefficient (beta)=0.27), mean winter relative humidity (beta=0.54), parity adjusted per capita national income (beta=1.08), per capita health expenditure (beta=-1.19), rates of income poverty (beta=-0.47), inequality (beta=0.97), deprivation (beta=0.11), and fuel poverty (beta=0.44), and several indicators of residential thermal standards are found to be significantly related to variations in relative excess winter mortality at the 5% level. The strong, positive relation with environmental temperature and strong negative relation with thermal efficiency indicate that housing standards in southern and western Europe play strong parts in such seasonality. High seasonal mortality in southern and western Europe could be reduced through improved protection from the cold indoors, increased public spending on health care, and improved socioeconomic circumstances resulting in more equitable income distribution.

  6. 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.

  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. 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.

  9. 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

    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......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...

  10. 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.

  11. Identifying the key catastrophic variables of urban social-environmental resilience and early warning signal.

    Science.gov (United States)

    Li, Yi; Li, Yangfan; Kappas, Martin; Pavao-Zuckerman, Mitchell

    2018-02-08

    Pursuit of sustainability requires a systematic approach to understand a system's specific dynamics to adapt and enhance from disturbances in social-environmental systems. We developed a systematic resilience assessment of social-environmental systems by connecting catastrophe theory and probability distribution equilibrium. Catastrophe models were used to calculate resilience shifts between slow and fast variables; afterwards, two resilience transition modes ("Less resilient" or "More resilient") were addressed by using probability distribution equilibrium analysis. A tipping point that occurs in "Less resilient" system suggests that the critical resilience transition can be an early warning signal of approaching threshold. Catastrophic shifts were explored between the interacting social-environmental sub-systems of land use and energy (fast variables) and environmental pollution (slow variables), which also identifies the critical factors in maintaining the integrated social-environmental resilience. Furthermore, the early warning signals enable the adaptability of urban systems and their resilience to perturbations, and provide guidelines for urban social-environmental management. Copyright © 2018 Elsevier Ltd. All rights reserved.

  12. Chronologic model and transgressive-regressive signatures in the late neocene siliciclastic foundation (long key formation) of the Florida keys

    Science.gov (United States)

    Guertin, L.A.; McNeill, D.F.

    1999-01-01

    Recent drilling of continuous cores in southernmost Florida has documented a thick unit of upper Neogene siliciclastics subjacent to surficial shallow-water Quaternary carbonates exposed on islands of the Florida Keys. The siliciclastics comprise the Long Key Formation and were identified in two cores collected from the middle and upper Florida Keys. Achronologic model based on new planktic foraminiferal biochronology and strontium-isotope chronology suggests the timing of siliddastic deposition and provides a basis for regional correlation. The chronologic model, supplemented by vertical trends in quartz grain size, pattern of planktic menardiiform coiling direction, and paleoenvironmental interpretations of benthic foraminiferal assemblages, shows that the Long Key Formation contains three intervals (I-III) of varying thickness, grain-size composition, and paleo-water depth. Interval I is uppermost Miocene. The quartz grains in Interval I fine upward from basal very coarse sand to fine and very fine sand. Benthic foraminifera indicate an upward shift from an outershelf to inner-shelf depositional environment. Interval II, deposited during the late early to early late Pliocene, contains reworked upper Miocene siliciclastics and faunas. In the upper Keys, quartz grains in Interval II range from very coarse sand that fines upward to very fine sand and then coarsens to very coarse and medium sand. In situ benthic faunas indicate an upward shift from outer-shelf to inner-shelf deposition. In the middle Keys, Interval II is different, with the quartz grains ranging primarily from medium to very fine sand. In situ benthic taxa indicate deposition on an inner shelf. In both the middle and upper Keys, the upper Pliocene siliciclastics of Interval III contain quartz grains ranging from very coarse to very fine sands that were deposited on an inner shelf. A sequence boundary between Interval I and Interval II is suggested by: an abrupt shift in the strontium

  13. A key for identifying faecal smears to detect domestic infestations of triatomine bugs

    Directory of Open Access Journals (Sweden)

    C.J. Schofield

    1986-03-01

    Full Text Available Early detection of residual populations of domestic triatomine bugs that survive insecticide treatment is a key component of successful evaluation and vigilance for Chagas disease control. We have recently demonstrated that sheets of paper, tacked on to the walls of infested houses, can become streaked with the faeces of triatomine bugs and thus reveal thepresence of an infestation. In thispaper, wepresent a simple key to differentiate the faecal streaks of triatomine bugs from those of other domestic arthropods such as cockroaches, ticks and cimicid bedbugs.

  14. 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…

  15. 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…

  16. Modeling, Simulation and Analysis of Public Key Infrastructure

    Science.gov (United States)

    Liu, Yuan-Kwei; Tuey, Richard; Ma, Paul (Technical Monitor)

    1998-01-01

    Security is an essential part of network communication. The advances in cryptography have provided solutions to many of the network security requirements. Public Key Infrastructure (PKI) is the foundation of the cryptography applications. The main objective of this research is to design a model to simulate a reliable, scalable, manageable, and high-performance public key infrastructure. We build a model to simulate the NASA public key infrastructure by using SimProcess and MatLab Software. The simulation is from top level all the way down to the computation needed for encryption, decryption, digital signature, and secure web server. The application of secure web server could be utilized in wireless communications. The results of the simulation are analyzed and confirmed by using queueing theory.

  17. 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.

  18. 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.

  19. The phenotypic patterns of essential hypertension are the key to identifying "high blood pressure" genes.

    Science.gov (United States)

    Korner, P I

    2010-01-01

    The genes that cause or increase susceptibility to essential hypertension (EH) and related animal models remain unknown. Their identification is unlikely to be realized with current genetic approaches, because of ambiguities in the genotype-phenotype relationships in these polygenic disorders. In turn, the phenotype is not just an aggregate of traits, but needs to be related to specific components of the circulatory control system at different stages of EH. Hence, clues about important genes must come through the phenotype, reversing the order of current approaches. A recent systems analysis has highlighted major differences in circulatory control in the two main syndromes of EH: (1) stress-and-salt-related EH (SSR-EH)--a constrictor hypertension with low blood volume; (2) hypertensive obesity--SSR-EH plus obesity. Each is initiated through sensitization of central synapses linking the cerebral cortex to the hypothalamic defense area. Several mechanisms are probably involved, including cerebellar effects on baroreflexes. The result is a sustained increase in sympathetic neural activity at stimulus levels that have no effect in normal subjects. Subsequent progression of EH is largely through interactions with non-neural mechanisms, including changes in concentration of vascular autacoids (e.g., nitric oxide) and the amplifying effect of structural changes in large resistance vessels. The rising vasoconstriction increases heterogeneity of blood flow, causing rarefaction (decreased microvascular density) and deterioration of vital organs. SSR-EH also increases food intake in response to stress, but only 40% of these individuals develop hypertensive obesity. Their brain ignores the adiposity signals that normally reduce eating. Hyperinsulinemia masks the sympathetic vasoconstriction through its dilator action, raises blood volume, whilst renal nephropathy and other diabetic complications are common. In each syndrome the neural and non-neural determinants of

  20. 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 ...

  1. 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

  2. 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

  3. Genomic Analysis of Kidney Allograft Injury Identifies Hematopoietic Cell Kinase as a Key Driver of Renal Fibrosis.

    Science.gov (United States)

    Wei, Chengguo; Li, Li; Menon, Madhav C; Zhang, Weijia; Fu, Jia; Kidd, Brian; Keung, Karen L; Woytovich, Christopher; Greene, Ilana; Xiao, Wenzhen; Salem, Fadi; Yi, Zhengzi; He, John Cijiang; Dudley, Joel T; Murphy, Barbara

    2017-05-01

    Renal fibrosis is the common pathway of progression for patients with CKD and chronic renal allograft injury (CAI), but the underlying mechanisms remain obscure. We performed a meta-analysis in human kidney biopsy specimens with CAI, incorporating data available publicly and from our Genomics of Chronic Renal Allograft Rejection study. We identified an Src family tyrosine kinase, hematopoietic cell kinase ( Hck ), as upregulated in allografts in CAI. Querying the Kinase Inhibitor Resource database revealed that dasatinib, a Food and Drug Administration-approved drug, potently binds Hck with high selectivity. In vitro , Hck overexpression activated the TGF-β/Smad3 pathway, whereas HCK knockdown inhibited it. Treatment of tubular cells with dasatinib reduced the expression of Col1a1 Dasatinib also reduced proliferation and α-SMA expression in fibroblasts. In a murine model with unilateral ureteric obstruction, pretreatment with dasatinib significantly reduced the upregulation of profibrotic markers, phosphorylation of Smad3, and renal fibrosis observed in kidneys pretreated with vehicle alone. Dasatinib treatment also improved renal function, reduced albuminuria, and inhibited expression of profibrotic markers in animal models with lupus nephritis and folic acid nephropathy. These data suggest that Hck is a key mediator of renal fibrosis and dasatinib could be developed as an antifibrotic drug. Copyright © 2017 by the American Society of Nephrology.

  4. 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

  5. Key metrics for HFIR HEU and LEU models

    Energy Technology Data Exchange (ETDEWEB)

    Ilas, Germina [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Betzler, Benjamin R. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Chandler, David [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Renfro, David G. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Davidson, Eva E. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2016-10-25

    This report compares key metrics for two fuel design models of the High Flux Isotope Reactor (HFIR). The first model represents the highly enriched uranium (HEU) fuel currently in use at HFIR, and the second model considers a low-enriched uranium (LEU) interim design fuel. Except for the fuel region, the two models are consistent, and both include an experiment loading that is representative of HFIR's current operation. The considered key metrics are the neutron flux at the cold source moderator vessel, the mass of 252Cf produced in the flux trap target region as function of cycle time, the fast neutron flux at locations of interest for material irradiation experiments, and the reactor cycle length. These key metrics are a small subset of the overall HFIR performance and safety metrics. They were defined as a means of capturing data essential for HFIR's primary missions, for use in optimization studies assessing the impact of HFIR's conversion from HEU fuel to different types of LEU fuel designs.

  6. Complementary RNA and Protein Profiling Identifies Iron as a Key Regulator of Mitochondrial Biogenesis

    Directory of Open Access Journals (Sweden)

    Jarred W. Rensvold

    2013-01-01

    Full Text Available Mitochondria are centers of metabolism and signaling whose content and function must adapt to changing cellular environments. The biological signals that initiate mitochondrial restructuring and the cellular processes that drive this adaptive response are largely obscure. To better define these systems, we performed matched quantitative genomic and proteomic analyses of mouse muscle cells as they performed mitochondrial biogenesis. We find that proteins involved in cellular iron homeostasis are highly coordinated with this process and that depletion of cellular iron results in a rapid, dose-dependent decrease of select mitochondrial protein levels and oxidative capacity. We further show that this process is universal across a broad range of cell types and fully reversed when iron is reintroduced. Collectively, our work reveals that cellular iron is a key regulator of mitochondrial biogenesis, and provides quantitative data sets that can be leveraged to explore posttranscriptional and posttranslational processes that are essential for mitochondrial adaptation.

  7. Identifying Key Symptoms Differentiating Myalgic Encephalomyelitis and Chronic Fatigue Syndrome from Multiple Sclerosis.

    Science.gov (United States)

    Ohanian, Diana; Brown, Abigail; Sunnquist, Madison; Furst, Jacob; Nicholson, Laura; Klebek, Lauren; Jason, Leonard A

    2016-01-01

    It is unclear what key symptoms differentiate Myalgic Encephalomyelitis (ME) and Chronic Fatigue syndrome (CFS) from Multiple Sclerosis (MS). The current study compared self-report symptom data of patients with ME or CFS with those with MS. The self-report data is from the DePaul Symptom Questionnaire, and participants were recruited to take the questionnaire online. Data were analyzed using a machine learning technique called decision trees. Five symptoms best differentiated the groups. The best discriminating symptoms were from the immune domain (i.e., flu-like symptoms and tender lymph nodes), and the trees correctly categorized MS from ME or CFS 81.2% of the time, with those with ME or CFS having more severe symptoms. Our findings support the use of machine learning to further explore the unique nature of these different chronic diseases.

  8. 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.

  9. 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

  10. 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...

  11. 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.

  12. 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.

  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 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.

  15. 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.

  16. Identifying keys to success in clinical learning: a study of two interprofessional learning environments.

    Science.gov (United States)

    Laksov, Klara Bolander; Boman, Lena Engqvist; Liljedahl, Matilda; Björck, Erik

    2015-03-01

    The aim of this study was to study the intrinsic system behind interprofessional clinical learning environments. Two health care units were selected on the basis of having received a reward for best clinical learning organization. Interviews were carried out with health care staff/clinical supervisors from different professions. The interviews were transcribed and analysed according to qualitative content analysis, and categories and themes were identified. Analysis revealed two different systems of clinical learning environments. In one, the interplay between the structural aspects dominated, and in the other, the interplay between the cultural aspects dominated. An important similarity between the environments was that a defined role for students in the organization and interprofessional teamwork around supervision across professional borders was emphasized.

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

    Science.gov (United States)

    Smith, Michael; Wallace, Ken; Lewis, Loretta; Wagner, Christian

    2015-11-01

    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.

  18. Identifying key non-volatile compounds in ready-to-drink green tea and their impact on taste profile.

    Science.gov (United States)

    Yu, Peigen; Yeo, Angelin Soo-Lee; Low, Mei-Yin; Zhou, Weibiao

    2014-07-15

    Thirty-nine non-volatile compounds in seven ready-to-drink (RTD) green tea samples were analysed and quantified using liquid chromatography. Taste reconstruction experiments using thirteen selected compounds were conducted to identify the key non-volatile tastants. Taste profiles of the reconstructed samples did not differ significantly from the RTD tea samples. To investigate the taste contribution and significance of individual compounds, omission experiments were carried out by removing individual or a group of compounds. Sensory evaluation revealed that the astringent- and bitter-tasting (-)-epigallocatechin gallate, bitter-tasting caffeine, and the umami-tasting l-glutamic acid were the main contributors to the taste of RTD green tea. Subsequently, the taste profile of the reduced recombinant, comprising of a combination of these three compounds and l-theanine, was found to not differ significantly from the sample recombinant and RTD tea sample. Lastly, regression models were developed to objectively predict and assess the intensities of bitterness and astringency in RTD green teas. Copyright © 2014 Elsevier Ltd. All rights reserved.

  19. Key management and encryption under the bounded storage model.

    Energy Technology Data Exchange (ETDEWEB)

    Draelos, Timothy John; Neumann, William Douglas; Lanzone, Andrew J.; Anderson, William Erik

    2005-11-01

    There are several engineering obstacles that need to be solved before key management and encryption under the bounded storage model can be realized. One of the critical obstacles hindering its adoption is the construction of a scheme that achieves reliable communication in the event that timing synchronization errors occur. One of the main accomplishments of this project was the development of a new scheme that solves this problem. We show in general that there exist message encoding techniques under the bounded storage model that provide an arbitrarily small probability of transmission error. We compute the maximum capacity of this channel using the unsynchronized key-expansion as side-channel information at the decoder and provide tight lower bounds for a particular class of key-expansion functions that are pseudo-invariant to timing errors. Using our results in combination with Dziembowski et al. [11] encryption scheme we can construct a scheme that solves the timing synchronization error problem. In addition to this work we conducted a detailed case study of current and future storage technologies. We analyzed the cost, capacity, and storage data rate of various technologies, so that precise security parameters can be developed for bounded storage encryption schemes. This will provide an invaluable tool for developing these schemes in practice.

  20. 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.

  1. 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. PMID:25210888

  2. 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

  3. 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.

  4. 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

  5. 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.

  6. 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...

  7. 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.

  8. Key Considerations in the Modeling of Tropical Maritime Microwave Attenuations

    Directory of Open Access Journals (Sweden)

    Yee Hui Lee

    2015-01-01

    Full Text Available This paper presents some key considerations for modeling of over-sea radio-wave propagations in 5 GHz band. The summarized information is based on a series of measurement campaigns which were recently carried out in the tropical maritime environments near Singapore. Multiray propagations and ducting of radio waves have been highlighted and considered in over-sea path loss modeling and prediction. It is noted that the sea-surface reflection is an important contribution in the received field, while the duct layers could enhance the radio-wave propagations. Our studies also show that the refracted ray inside evaporation duct could be a strong ray for short-range near sea-surface applications and needs to be properly evaluated.

  9. 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

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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

  15. A Key Generation Model for Improving the Security of Cryptographic ...

    African Journals Online (AJOL)

    In public key cryptography, the security of private keys is very importance, for if ever compromised, it can be used to decrypt secret messages. Conventional methods that use textual passwords, graphical passwords and single modal biometric systems that are used to encryption and protect private keys do not provide ...

  16. Culture Models to Define Key Mediators of Cancer Matrix Remodeling

    Directory of Open Access Journals (Sweden)

    Emily Suzanne Fuller

    2014-03-01

    Full Text Available High grade serous epithelial ovarian cancer (HG-SOC is one of the most devastating gynecological cancers affecting women worldwide, with a poor survival rate despite clinical treatment advances. HG-SOC commonly metastasizes within the peritoneal cavity, primarily to the mesothelial cells of the omentum which regulate an extracellular matrix (ECM rich in collagens type I, III and IV along with laminin, vitronectin and fibronectin. Cancer cells depend on their ability to penetrate and invade secondary tissue sites to spread, however a detailed understanding of the molecular mechanisms underlying these processes remain largely unknown. Given the high metastatic potential of HG-SOC and the associated poor clinical outcome, it is extremely important to identify the pathways and the components of which that are responsible for the progression of this disease. In-vitro methods of recapitulating human disease processes are the critical first step in such investigations. In this context, establishment of an in-vitro ‘tumor-like’ microenvironment, such as 3D culture, to study early disease and metastasis of human HG-SOC is an important and highly insightful method. In recent years many such methods have been established to investigate the adhesion and invasion of human ovarian cancer cell lines. The aim of this review is to summarize recent developments in ovarian cancer culture systems and their use to investigate clinically relevant findings concerning the key players in driving human HG-SOC.

  17. 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.

  18. 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.

  19. The use of social networking platforms for sexual health promotion: identifying key strategies for successful user engagement.

    Science.gov (United States)

    Veale, Hilary J; Sacks-Davis, Rachel; Weaver, Emma Rn; Pedrana, Alisa E; Stoové, Mark A; Hellard, Margaret E

    2015-02-06

    Online social networking platforms such as Facebook and Twitter have grown rapidly in popularity, with opportunities for interaction enhancing their health promotion potential. Such platforms are being used for sexual health promotion but with varying success in reaching and engaging users. We aimed to identify Facebook and Twitter profiles that were able to engage large numbers of users, and to identify strategies used to successfully attract and engage users in sexual health promotion on these platforms. We identified active Facebook (n = 60) and Twitter (n = 40) profiles undertaking sexual health promotion through a previous systematic review, and assessed profile activity over a one-month period. Quantitative measures of numbers of friends and followers (reach) and social media interactions were assessed, and composite scores used to give profiles an 'engagement success' ranking. Associations between host activity, reach and interaction metrics were explored. Content of the top ten ranked Facebook and Twitter profiles was analysed using a thematic framework and compared with five poorly performing profiles to identify strategies for successful user engagement. Profiles that were able to successfully engage large numbers of users were more active and had higher levels of interaction per user than lower-ranked profiles. Strategies used by the top ten ranked profiles included: making regular posts/tweets (median 46 posts or 124 tweets/month for top-ranked profiles versus six posts or six tweets for poorly-performing profiles); individualised interaction with users (85% of top-ranked profiles versus 0% for poorly-performing profiles); and encouraging interaction and conversation by posing questions (100% versus 40%). Uploading multimedia material (80% versus 30%) and highlighting celebrity involvement (70% versus 10%) were also key strategies. Successful online engagement on social networking platforms can be measured through quantitative (user numbers and

  20. 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 ...

  1. 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...

  2. Analysis of gene expression in the nervous system identifies key genes and novel candidates for health and disease.

    Science.gov (United States)

    Carpanini, Sarah M; Wishart, Thomas M; Gillingwater, Thomas H; Manson, Jean C; Summers, Kim M

    2017-04-01

    The incidence of neurodegenerative diseases in the developed world has risen over the last century, concomitant with an increase in average human lifespan. A major challenge is therefore to identify genes that control neuronal health and viability with a view to enhancing neuronal health during ageing and reducing the burden of neurodegeneration. Analysis of gene expression data has recently been used to infer gene functions for a range of tissues from co-expression networks. We have now applied this approach to transcriptomic datasets from the mammalian nervous system available in the public domain. We have defined the genes critical for influencing neuronal health and disease in different neurological cell types and brain regions. The functional contribution of genes in each co-expression cluster was validated using human disease and knockout mouse phenotypes, pathways and gene ontology term annotation. Additionally a number of poorly annotated genes were implicated by this approach in nervous system function. Exploiting gene expression data available in the public domain allowed us to validate key nervous system genes and, importantly, to identify additional genes with minimal functional annotation but with the same expression pattern. These genes are thus novel candidates for a role in neurological health and disease and could now be further investigated to confirm their function and regulation during ageing and neurodegeneration.

  3. Key influences identified by first year undergraduate nursing students as impacting on the quality of clinical placement: A qualitative study.

    Science.gov (United States)

    Cooper, John; Courtney-Pratt, Helen; Fitzgerald, Mary

    2015-09-01

    Despite the fact that high quality clinical placement is an integral component of pre-registration nursing education for the development of the future nursing workforce, the literature identifies an ongoing struggle to 'get it right'. To examine qualitative data gathered through the Quality Clinical Placements Evaluation project to identify what pre-registration nursing students deemed helpful and not helpful influences on their first year Professional Experience Placement. A total of 553 first year undergraduate nursing students from 2010 to 2012 were enrolled in the programme and all were invited to complete a validated survey to measure the quality of their first clinical placement. A total of 361 completed surveys were returned. This paper examines the data provided through open-ended questions within the survey related to most helpful and least helpful aspects of their clinical experience. An inductive analysis approach using NVIVO allowed inherent areas to emerge from the raw data forming three key themes that influenced the experience of students. Feeling welcomed, individual versus team attitudes, and student expectations of supervising ward nurses were the themes identified that were perceived by the student as important to the success of learning and the quality of the experience overall. The findings echo previous research into the student experience of clinical placement; however the focus regarding the need for students to have a quality relationship with the supervising nurse is an area that warrants further exploration. Furthermore, we argue that students should be purposely engaged in the tertiary sector and provided guidance and strategies related to forming and maintaining relationships with those that supervise their clinical placement, in order to ensure consistent positive experiences. The outcomes from this study suggest that a missing component is teaching undergraduates how to manage relationships in clinical settings. Copyright © 2015

  4. 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.

  5. 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

  6. Key competences in the new ventures: a model for evaluating

    NARCIS (Netherlands)

    Castillo, S.M.; Hormiga-Pérez, E.; Coromina Soler, L.; Valls Pasola, J.

    2010-01-01

    This research studies from an internal view based on the Competency-Based Perspective (CBP), key organizational competencies developed for small new business. CBP is chosen in an attempt to explain the differences characterizing the closed companies from the consolidated ones. The main contribution

  7. 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......: the identification of temporal logic properties of probabilistic automata learned from sequence data, the identification of causal dependencies in probabilistic graphical models, and the transfer of probabilistic relational models to new domains....

  8. Identification and Development of Key Talents through Competency Modelling in Agriculture Companies

    Directory of Open Access Journals (Sweden)

    Lucie Vnoučková

    2016-01-01

    Full Text Available The necessity of identification of key talents in company is known in all sectors of economy. Therefore the aim of the paper is based on competency analysis to define key factors leading to talent identification and internalization through competency modelling. Paper characterizes areas of necessary competencies on specific job positions in companies. Their targeting on employee and teams in talent management is revealed. The objective is based on analysis of primary survey conducted on 101 agriculture companies. The data were obtained through manager surveys for which a single manager represented the given company. One-dimensional and multi-dimensional statistics were used to evaluate the data. Based on statistical analyses of required competencies five factors characterizing area of key employee and team development were identified. Those factors are inclusive approach, management support, strategic development, leadership development and integrity. The resultant factors create competency models usable in specified job positions. Limits of the paper is narrow focus on primary sector companies. The results may help surveyed companies in primary sector to set required and necessary competencies for specific areas to identify and develop employees, talents and teams.

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

    Science.gov (United States)

    2015-09-17

    credence is given to the monumental task of classical information processing or the time it takes to accomplish relative to quantum transmission. The...object. In quantum entanglement , the physical properties of particle pairs or groups of particles are correlated – the quantum state of each particle...Weihs, ’ Entangled quantum key distribution over two free-space optical links’, Opt. Express, vol. 16, no. 21, p. 16840, 2008. [14] C. Fung, X. Ma and

  10. Practical identifiability analysis of a minimal cardiovascular system model.

    Science.gov (United States)

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

    2017-01-17

    Parameters of mathematical models of the cardiovascular system can be used to monitor cardiovascular state, such as total stressed blood volume status, vessel elastance and resistance. To do so, the model parameters have to be estimated from data collected at the patient's bedside. This work considers a seven-parameter model of the cardiovascular system and investigates whether these parameters can be uniquely determined using indices derived from measurements of arterial and venous pressures, and stroke volume. An error vector defined the residuals between the simulated and reference values of the seven clinically available haemodynamic indices. The sensitivity of this error vector to each model parameter was analysed, as well as the collinearity between parameters. To assess practical identifiability of the model parameters, profile-likelihood curves were constructed for each parameter. Four of the seven model parameters were found to be practically identifiable from the selected data. The remaining three parameters were practically non-identifiable. Among these non-identifiable parameters, one could be decreased as much as possible. The other two non-identifiable parameters were inversely correlated, which prevented their precise estimation. This work presented the practical identifiability analysis of a seven-parameter cardiovascular system model, from limited clinical data. The analysis showed that three of the seven parameters were practically non-identifiable, thus limiting the use of the model as a monitoring tool. Slight changes in the time-varying function modeling cardiac contraction and use of larger values for the reference range of venous pressure made the model fully practically identifiable. Copyright © 2017. Published by Elsevier B.V.

  11. Screening in planarians identifies MORN2 as a key component in LC3-associated phagocytosis and resistance to bacterial infection.

    Science.gov (United States)

    Abnave, Prasad; Mottola, Giovanna; Gimenez, Gregory; Boucherit, Nicolas; Trouplin, Virginie; Torre, Cedric; Conti, Filippo; Ben Amara, Amira; Lepolard, Catherine; Djian, Benjamin; Hamaoui, Daniel; Mettouchi, Amel; Kumar, Atul; Pagnotta, Sophie; Bonatti, Stefano; Lepidi, Hubert; Salvetti, Alessandra; Abi-Rached, Laurent; Lemichez, Emmanuel; Mege, Jean-Louis; Ghigo, Eric

    2014-09-10

    Dugesia japonica planarian flatworms are naturally exposed to various microbes but typically survive this challenge. We show that planarians eliminate bacteria pathogenic to Homo sapiens, Caenorhabditis elegans, and/or Drosophila melanogaster and thus represent a model to identify innate resistance mechanisms. Whole-transcriptome analysis coupled with RNAi screening of worms infected with Staphylococcus aureus or Legionella pneumophila identified 18 resistance genes with nine human orthologs, of which we examined the function of MORN2. Human MORN2 facilitates phagocytosis-mediated restriction of Mycobacterium tuberculosis, L. pneumophila, and S. aureus in macrophages. MORN2 promotes the recruitment of LC3, an autophagy protein also involved in phagocytosis, to M. tuberculosis-containing phagosomes and subsequent maturation to degradative phagolysosomes. MORN2-driven trafficking of M. tuberculosis to single-membrane, LC3-positive compartments requires autophagy-related proteins Atg5 and Beclin-1, but not Ulk-1 and Atg13, highlighting the importance of MORN2 in LC3-associated phagocytosis. These findings underscore the value of studying planarian defenses to identify immune factors. Copyright © 2014 Elsevier Inc. All rights reserved.

  12. Perceptions of graduating students from eight medical schools in Vietnam on acquisition of key skills identified by teachers

    Directory of Open Access Journals (Sweden)

    Son Nguyen

    2008-01-01

    Full Text Available Abstract Background The eight main Vietnamese medical schools recently cooperated to produce a book listing the knowledge, attitudes and skills expected of a graduate, including specification of the required level for each skill. The teaching program should ensure that students can reach that level. The objective of this study was to determine the perception of graduating students on whether they had achieved the level set for a selection of clinical and public health skills as a guide for the schools to adjust either the levels or the teaching. Methods From all eight schools, 1136 of the 1528 final year students completed questionnaires just before completed all the requirements for graduation, a response rate of 87% overall (ranging from 74–99% per school. They rated their own competence on a scale of 0–5 for 129 skills selected from the 557 skills listed in the book, and reported where they thought they had learned them. The scores that the students gave themselves were then compared to the levels proposed by the teachers for each skill. The proportions of the self-assessed achievement to the levels expected by the teachers, means self-assessed scores and the coefficients of variation were calculated to make comparisons among disciplines, among schools and among learning sites. Results Most students felt they had learned most of the skills for key clinical departments to the required level; this varied little among the schools. Self-assessed skill acquisition in public health and minor clinical disciplines was lower and varied more. Sites outside the classroom were especially important for learning skills. The results revealed key similarities and differences between the teachers and the students in their perception about what could be learned and where Conclusion Revising a curriculum for medical schools demands inputs from all stakeholders. Graduating class students can provide valuable feedback on what they have learned in the existing

  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. 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.

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

    African Journals Online (AJOL)

    Urban growth and land use change models, supported by Geographic Information Systems (GIS) software and increased digital data availability, have the ... and opportunities for modelling urban spatial change, with specific reference to the Gauteng City-Region – the heartland of the South African economy and the ...

  17. 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…

  18. PrEP for key populations in combination HIV prevention in Nairobi: a mathematical modelling study.

    Science.gov (United States)

    Cremin, Ide; McKinnon, Lyle; Kimani, Joshua; Cherutich, Peter; Gakii, Gloria; Muriuki, Festus; Kripke, Katharine; Hecht, Robert; Kiragu, Michael; Smith, Jennifer; Hinsley, Wes; Gelmon, Lawrence; Hallett, Timothy B

    2017-05-01

    The HIV epidemic in the population of Nairobi as a whole is in decline, but a concentrated sub-epidemic persists in key populations. We aimed to identify an optimal portfolio of interventions to reduce HIV incidence for a given budget and to identify the circumstances in which pre-exposure prophylaxis (PrEP) could be used in Nairobi, Kenya. A mathematical model was developed to represent HIV transmission in specific key populations (female sex workers, male sex workers, and men who have sex with men [MSM]) and among the wider population of Nairobi. The scale-up of existing interventions (condom promotion, antiretroviral therapy, and male circumcision) for key populations and the wider population as have occurred in Nairobi is represented. The model includes a detailed representation of a PrEP intervention and is calibrated to prevalence and incidence estimates specific to key populations and the wider population. In the context of a declining epidemic overall but with a large sub-epidemic in MSM and male sex workers, an optimal prevention portfolio for Nairobi should focus on condom promotion for male sex workers and MSM in particular, followed by improved antiretroviral therapy retention, earlier antiretroviral therapy, and male circumcision as the budget allows. PrEP for male sex workers could enter an optimal portfolio at similar levels of spending to when earlier antiretroviral therapy is included; however, PrEP for MSM and female sex workers would be included only at much higher budgets. If PrEP for male sex workers cost as much as US$500, average annual spending on the interventions modelled would need to be less than $3·27 million for PrEP for male sex workers to be excluded from an optimal portfolio. Estimated costs per infection averted when providing PrEP to all female sex workers regardless of their risk of infection, and to high-risk female sex workers only, are $65 160 (95% credible interval [CrI] $43 520-$90 250) and $10 920 (95% CrI $4700

  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. The use of systems models to identify food waste drivers

    NARCIS (Netherlands)

    Grainger, Matthew James; Aramyan, Lusine; Logatcheva, Katja; Piras, Simone; Righi, Simone; Setti, Marco; Vittuari, Matteo; Stewart, Gavin Bruce

    2018-01-01

    In developed countries, the largest share of food waste is produced at household level. Most studies on consumers’ food waste use models that identify covariates as significant when in fact they may not be, particularly where these models use many variables. Here, using EU-level Eurobarometer data

  1. Application of Multilevel Logistic Model to Identify Correlates of ...

    African Journals Online (AJOL)

    Implementation of multilevel model is becoming a common analytic technique over a wide range of disciplines including social and economic sciences. In this paper, an attempt has been made to assess the application of multilevel logistic model for the purpose of identifying the effect of household characteristics on poverty ...

  2. The 2013 European Seismic Hazard Model: key components and results

    OpenAIRE

    Jochen Woessner; Danciu Laurentiu; Domenico Giardini; Helen Crowley; Fabrice Cotton; G. Grünthal; Gianluca Valensise; Ronald Arvidsson; Roberto Basili; Mine Betül Demircioglu; Stefan Hiemer; Carlo Meletti; Roger W. Musson; Andrea N. Rovida; Karin Sesetyan

    2015-01-01

    The 2013 European Seismic Hazard Model (ESHM13) results from a community-based probabilistic seismic hazard assessment supported by the EU-FP7 project “Seismic Hazard Harmonization in Europe” (SHARE, 2009–2013). The ESHM13 is a consistent seismic hazard model for Europe and Turkey which overcomes the limitation of national borders and includes a through quantification of the uncertainties. It is the first completed regional effort contributing to the “Global Earthquake Model” initiative. It m...

  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. Key challenges and priorities for modelling European grasslands under climate change.

    Science.gov (United States)

    Kipling, Richard P; Virkajärvi, Perttu; Breitsameter, Laura; Curnel, Yannick; De Swaef, Tom; Gustavsson, Anne-Maj; Hennart, Sylvain; Höglind, Mats; Järvenranta, Kirsi; Minet, Julien; Nendel, Claas; Persson, Tomas; Picon-Cochard, Catherine; Rolinski, Susanne; Sandars, Daniel L; Scollan, Nigel D; Sebek, Leon; Seddaiu, Giovanna; Topp, Cairistiona F E; Twardy, Stanislaw; Van Middelkoop, Jantine; Wu, Lianhai; Bellocchi, Gianni

    2016-10-01

    Grassland-based ruminant production systems are integral to sustainable food production in Europe, converting plant materials indigestible to humans into nutritious food, while providing a range of environmental and cultural benefits. Climate change poses significant challenges for such systems, their productivity and the wider benefits they supply. In this context, grassland models have an important role in predicting and understanding the impacts of climate change on grassland systems, and assessing the efficacy of potential adaptation and mitigation strategies. In order to identify the key challenges for European grassland modelling under climate change, modellers and researchers from across Europe were consulted via workshop and questionnaire. Participants identified fifteen challenges and considered the current state of modelling and priorities for future research in relation to each. A review of literature was undertaken to corroborate and enrich the information provided during the horizon scanning activities. Challenges were in four categories relating to: 1) the direct and indirect effects of climate change on the sward 2) climate change effects on grassland systems outputs 3) mediation of climate change impacts by site, system and management and 4) cross-cutting methodological issues. While research priorities differed between challenges, an underlying theme was the need for accessible, shared inventories of models, approaches and data, as a resource for stakeholders and to stimulate new research. Developing grassland models to effectively support efforts to tackle climate change impacts, while increasing productivity and enhancing ecosystem services, will require engagement with stakeholders and policy-makers, as well as modellers and experimental researchers across many disciplines. The challenges and priorities identified are intended to be a resource 1) for grassland modellers and experimental researchers, to stimulate the development of new research

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

    African Journals Online (AJOL)

    Chris Wray

    thus, used to explain and predict land use and transport relationships in urban systems treated earlier as static, but now considered dynamic (Batty, .... People's Republic of China using logistic regression. 3. South Africa Urban Growth Modelling ..... delivery (GDED, 2008; Kekana, 2010). However, after six years and despite ...

  7. An expression screen for aged-dependent microRNAs identifies miR-30a as a key regulator of aging features in human epidermis.

    Science.gov (United States)

    Muther, Charlotte; Jobeili, Lara; Garion, Maëlle; Heraud, Sandrine; Thepot, Amélie; Damour, Odile; Lamartine, Jérôme

    2017-11-19

    The mechanisms affecting epidermal homeostasis during aging remain poorly understood. To identify age-related microRNAs, a class of non-coding RNAs known to play a key role in the regulation of epidermal homeostasis, an exhaustive miRNA expression screen was performed in human keratinocytes from young or elderly subjects. Many microRNAs modulated by aging were identified, including miR-30a, in which both strands were overexpressed in aged cells and epidermal tissue. Stable MiR-30a over-expression strongly impaired epidermal differentiation, inducing severe barrier function defects in an organotypic culture model. A significant increase was also observed in the level of apoptotic cells in epidermis over-expressing miR-30a. Several gene targets of miR-30a were identified in keratinocytes, including LOX (encoding lysyl oxidase, a regulator of the proliferation/differentiation balance of keratinocytes), IDH1 (encoding isocitrate dehydrogenase, an enzyme of cellular metabolism) and AVEN (encoding a caspase inhibitor). Direct regulation of LOX , IDH1 and AVEN by miR-30a was confirmed in human keratinocytes. They were, moreover, observed to be repressed in aged skin, suggesting a possible link between miR-30a induction and skin-aging phenotype. This study revealed a new miRNA actor and deciphered new molecular mechanisms to explain certain alterations observed in epidermis during aging and especially those concerning keratinocyte differentiation and apoptosis.

  8. Haploid Mammalian Genetic Screen Identifies UBXD8 as a Key Determinant of HMGCR Degradation and Cholesterol Biosynthesis

    NARCIS (Netherlands)

    Loregger, Anke; Raaben, Matthijs; Tan, Josephine; Scheij, Saskia; Moeton, Martina; van den Berg, Marlene; Gelberg-Etel, Hila; Stickel, Elmer; Roitelman, Joseph; Brummelkamp, Thijn; Zelcer, Noam

    2017-01-01

    Objective-The cellular demand for cholesterol requires control of its biosynthesis by the mevalonate pathway. Regulation of HMGCR (3-hydroxy-3-methylglutaryl coenzyme A reductase), a rate-limiting enzyme in this pathway and the target of statins, is a key control point herein. Accordingly, HMGCR is

  9. 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

  10. Characterizations of identified sets delivered by structural econometric models

    OpenAIRE

    Chesher, Andrew; Rosen, Adam M.

    2016-01-01

    This paper develops characterizations of identified sets of structures and structural features for complete and incomplete models involving continuous and/or discrete variables. Multiple values of unobserved variables can be associated with particular combinations of observed variables. This can arise when there are multiple sources of heterogeneity, censored or discrete endogenous variables, or inequality restrictions on functions of observed and unobserved variables. The models generalize t...

  11. Preliminary Review of Models, Assumptions, and Key Data used in Performance Assessments and Composite Analysis at the Idaho National Laboratory

    Energy Technology Data Exchange (ETDEWEB)

    Arthur S. Rood; Swen O. Magnuson

    2009-07-01

    This document is in response to a request by Ming Zhu, DOE-EM to provide a preliminary review of existing models and data used in completed or soon to be completed Performance Assessments and Composite Analyses (PA/CA) documents, to identify codes, methodologies, main assumptions, and key data sets used.

  12. 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

  13. 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

  14. INCREASING DOMESTIC CONSUMPTION OF SOUTH AFRICAN WINES: IDENTIFYING THE KEY MARKET SEGMENTS OF THE “BLACK DIAMONDS”

    OpenAIRE

    Ndanga, Leah Z.B.; Louw, Andre; van Rooyen, Johan

    2009-01-01

    Although South Africans are not predominantly wine drinkers, the industry is looking for ways to develop the local market to balance exports. The black middle class, increasingly referred to as the Black Diamonds are the most powerful marketing trend in the last 10 years as they have emerged as the strongest buying influence in the economy and making inroads in understanding this market presents a good opportunity. The study asserts that the key factors influencing the South African consumers...

  15. 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

  16. Re-orienting a remote acute care model towards a primary health care approach: key enablers.

    Science.gov (United States)

    Carroll, Vicki; Reeve, Carole A; Humphreys, John S; Wakerman, John; Carter, Maureen

    2015-01-01

    The objective of this study was to identify the key enablers of change in re-orienting a remote acute care model to comprehensive primary healthcare delivery. The setting of the study was a 12-bed hospital in Fitzroy Crossing, Western Australia. Individual key informant, in-depth interviews were completed with five of six identified senior leaders involved in the development of the Fitzroy Valley Health Partnership. Interviews were recorded and transcripts were thematically analysed by two investigators for shared views about the enabling factors strengthening primary healthcare delivery in a remote region of Australia. Participants described theestablishment of a culturally relevant primary healthcare service, using a community-driven, 'bottom up' approach characterised by extensive community participation. The formal partnership across the government and community controlled health services was essential, both to enable change to occur and to provide sustainability in the longer term. A hierarchy of major themes emerged. These included community participation, community readiness and desire for self-determination; linkages in the form of a government community controlled health service partnership; leadership; adequate infrastructure; enhanced workforce supply; supportive policy; and primary healthcare funding. The strong united leadership shown by the community and the health service enabled barriers to be overcome and it maximised the opportunities provided by government policy changes. The concurrent alignment around a common vision enabled implementation of change. The key principle learnt from this study is the importance of community and health service relationships and local leadership around a shared vision for the re-orientation of community health services.

  17. Identifying fMRI Model Violations with Lagrange Multiplier Tests

    Science.gov (United States)

    Cassidy, Ben; Long, Christopher J; Rae, Caroline; Solo, Victor

    2013-01-01

    The standard modeling framework in Functional Magnetic Resonance Imaging (fMRI) is predicated on assumptions of linearity, time invariance and stationarity. These assumptions are rarely checked because doing so requires specialised software, although failure to do so can lead to bias and mistaken inference. Identifying model violations is an essential but largely neglected step in standard fMRI data analysis. Using Lagrange Multiplier testing methods we have developed simple and efficient procedures for detecting model violations such as non-linearity, non-stationarity and validity of the common Double Gamma specification for hemodynamic response. These procedures are computationally cheap and can easily be added to a conventional analysis. The test statistic is calculated at each voxel and displayed as a spatial anomaly map which shows regions where a model is violated. The methodology is illustrated with a large number of real data examples. PMID:22542665

  18. Drosophila Cancer Models Identify Functional Differences between Ret Fusions

    Directory of Open Access Journals (Sweden)

    Sarah Levinson

    2016-09-01

    Full Text Available 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.

  19. 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

  20. Identifying potential strategies in the key sectors of China’s food chain to implement sustainable phosphorus management

    NARCIS (Netherlands)

    Li, Guohua; Huang, Gaoqiang; Li, Haigang; Ittersum, van M.K.; Leffelaar, P.A.; Zhang, Fusuo

    2016-01-01

    High extraction of phosphate reserves and low phosphorus utilization efficiency in the food chain in China result in large P losses and serious environmental pollution. The P fertilizer industry, soil P surplus, livestock manure P and wastewater P recycling have been identified as the priority

  1. Parameter estimation for multistage clonal expansion models from cancer incidence data: A practical identifiability analysis.

    Science.gov (United States)

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

    2017-03-01

    Many cancers are understood to be the product of multiple somatic mutations or other rate-limiting events. Multistage clonal expansion (MSCE) models are a class of continuous-time Markov chain models that capture the multi-hit initiation-promotion-malignant-conversion hypothesis of carcinogenesis. These models have been used broadly to investigate the epidemiology of many cancers, assess the impact of carcinogen exposures on cancer risk, and evaluate the potential impact of cancer prevention and control strategies on cancer rates. Structural identifiability (the analysis of the maximum parametric information available for a model given perfectly measured data) of certain MSCE models has been previously investigated. However, structural identifiability is a theoretical property and does not address the limitations of real data. In this study, we use pancreatic cancer as a case study to examine the practical identifiability of the two-, three-, and four-stage clonal expansion models given age-specific cancer incidence data using a numerical profile-likelihood approach. We demonstrate that, in the case of the three- and four-stage models, several parameters that are theoretically structurally identifiable, are, in practice, unidentifiable. This result means that key parameters such as the intermediate cell mutation rates are not individually identifiable from the data and that estimation of those parameters, even if structurally identifiable, will not be stable. We also show that products of these practically unidentifiable parameters are practically identifiable, and, based on this, we propose new reparameterizations of the model hazards that resolve the parameter estimation problems. Our results highlight the importance of identifiability to the interpretation of model parameter estimates.

  2. An Efficient Modeling and Simulation of Quantum Key Distribution Protocols Using OptiSystem™

    OpenAIRE

    Abudhahir Buhari,; Zuriati Ahmad Zukarnain; Shamla K. Subramaniam,; Hishamuddin Zainuddin; Suhairi Saharudin

    2012-01-01

    In this paper, we propose a modeling and simulation framework for quantum key distribution protocols using commercial photonic simulator OptiSystem™. This simulation framework emphasize on experimental components of quantum key distribution. We simulate BB84 operation with several security attacks scenario and noise immune key distribution in this work. We also investigate the efficiency of simulator’s in-built photonic components in terms of experimental configuration. This simulation provid...

  3. 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.

  4. Compartmental analysis of dynamic nuclear medicine data: models and identifiability

    Science.gov (United States)

    Delbary, Fabrice; Garbarino, Sara; Vivaldi, Valentina

    2016-12-01

    Compartmental models based on tracer mass balance are extensively used in clinical and pre-clinical nuclear medicine in order to obtain quantitative information on tracer metabolism in the biological tissue. This paper is the first of a series of two that deal with the problem of tracer coefficient estimation via compartmental modelling in an inverse problem framework. Specifically, here we discuss the identifiability problem for a general n-dimension compartmental system and provide uniqueness results in the case of two-compartment and three-compartment compartmental models. The second paper will utilize this framework in order to show how nonlinear regularization schemes can be applied to obtain numerical estimates of the tracer coefficients in the case of nuclear medicine data corresponding to brain, liver and kidney physiology.

  5. Meta-analysis identifies five novel loci associated with endometriosis highlighting key genes involved in hormone metabolism

    DEFF Research Database (Denmark)

    Sapkota, Yadav; Steinthorsdottir, Valgerdur; Morris, Andrew P

    2017-01-01

    Endometriosis is a heritable hormone-dependent gynecological disorder, associated with severe pelvic pain and reduced fertility; however, its molecular mechanisms remain largely unknown. Here we perform a meta-analysis of 11 genome-wide association case-control data sets, totalling 17,045 endomet......Endometriosis is a heritable hormone-dependent gynecological disorder, associated with severe pelvic pain and reduced fertility; however, its molecular mechanisms remain largely unknown. Here we perform a meta-analysis of 11 genome-wide association case-control data sets, totalling 17......,045 endometriosis cases and 191,596 controls. In addition to replicating previously reported loci, we identify five novel loci significantly associated with endometriosis risk (P... identified five secondary association signals, including two at the ESR1 locus, resulting in 19 independent single nucleotide polymorphisms (SNPs) robustly associated with endometriosis, which together explain up to 5.19% of variance in endometriosis. These results highlight novel variants in or near...

  6. 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.

  7. 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

  8. 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

  9. A new process sensitivity index to identify important system processes under process model and parametric uncertainty

    Energy Technology Data Exchange (ETDEWEB)

    Dai, Heng [Pacific Northwest National Laboratory, Richland Washington USA; Ye, Ming [Department of Scientific Computing, Florida State University, Tallahassee Florida USA; Walker, Anthony P. [Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge Tennessee USA; Chen, Xingyuan [Pacific Northwest National Laboratory, Richland Washington USA

    2017-04-01

    Hydrological models are always composed of multiple components that represent processes key to intended model applications. When a process can be simulated by multiple conceptual-mathematical models (process models), model uncertainty in representing the process arises. While global sensitivity analysis methods have been widely used for identifying important processes in hydrologic modeling, the existing methods consider only parametric uncertainty but ignore the model uncertainty for process representation. To address this problem, this study develops a new method to probe multimodel process sensitivity by integrating the model averaging methods into the framework of variance-based global sensitivity analysis, given that the model averaging methods quantify both parametric and model uncertainty. A new process sensitivity index is derived as a metric of relative process importance, and the index includes variance in model outputs caused by uncertainty in both process models and model parameters. For demonstration, the new index is used to evaluate the processes of recharge and geology in a synthetic study of groundwater reactive transport modeling. The recharge process is simulated by two models that converting precipitation to recharge, and the geology process is also simulated by two models of different parameterizations of hydraulic conductivity; each process model has its own random parameters. The new process sensitivity index is mathematically general, and can be applied to a wide range of problems in hydrology and beyond.

  10. Systems analysis of eleven rodent disease models reveals an inflammatome signature and key drivers.

    Science.gov (United States)

    Wang, I-Ming; Zhang, Bin; Yang, Xia; Zhu, Jun; Stepaniants, Serguei; Zhang, Chunsheng; Meng, Qingying; Peters, Mette; He, Yudong; Ni, Chester; Slipetz, Deborah; Crackower, Michael A; Houshyar, Hani; Tan, Christopher M; Asante-Appiah, Ernest; O'Neill, Gary; Luo, Mingjuan Jane; Thieringer, Rolf; Yuan, Jeffrey; Chiu, Chi-Sung; Lum, Pek Yee; Lamb, John; Boie, Yves; Wilkinson, Hilary A; Schadt, Eric E; Dai, Hongyue; Roberts, Christopher

    2012-07-17

    Common inflammatome gene signatures as well as disease-specific signatures were identified by analyzing 12 expression profiling data sets derived from 9 different tissues isolated from 11 rodent inflammatory disease models. The inflammatome signature significantly overlaps with known drug targets and co-expressed gene modules linked to metabolic disorders and cancer. A large proportion of genes in this signature are tightly connected in tissue-specific Bayesian networks (BNs) built from multiple independent mouse and human cohorts. Both the inflammatome signature and the corresponding consensus BNs are highly enriched for immune response-related genes supported as causal for adiposity, adipokine, diabetes, aortic lesion, bone, muscle, and cholesterol traits, suggesting the causal nature of the inflammatome for a variety of diseases. Integration of this inflammatome signature with the BNs uncovered 151 key drivers that appeared to be more biologically important than the non-drivers in terms of their impact on disease phenotypes. The identification of this inflammatome signature, its network architecture, and key drivers not only highlights the shared etiology but also pinpoints potential targets for intervention of various common diseases.

  11. Evaluation of unique identifiers used as keys to match identical publications in Pure and SciVal - a case study from health science.

    Science.gov (United States)

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

    2016-01-01

    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 UIDs may become

  12. Using an Integrated -Omics Approach to Identify Key Cellular Processes That Are Disturbed in the Kidney After Brain Death

    NARCIS (Netherlands)

    Akhtar, M. Z.; Huang, H.; Kaisar, M.; Lo Faro, M. L.; Rebolledo, R.; Morten, K.; Heather, L. C.; Dona, A.; Leuvenink, H. G.; Fuggle, S. V.; Kessler, B. M.; Pugh, C. W.; Ploeg, R. J.

    In an era where we are becoming more reliant on vulnerable kidneys for transplantation from older donors, there is an urgent need to understand how brain death leads to kidney dysfunction and, hence, how this can be prevented. Using a rodent model of hemorrhagic stroke and next-generation proteomic

  13. 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.

  14. Haploid Mammalian Genetic Screen Identifies UBXD8 as a Key Determinant of HMGCR Degradation and Cholesterol Biosynthesis.

    Science.gov (United States)

    Loregger, Anke; Raaben, Matthijs; Tan, Josephine; Scheij, Saskia; Moeton, Martina; van den Berg, Marlene; Gelberg-Etel, Hila; Stickel, Elmer; Roitelman, Joseph; Brummelkamp, Thijn; Zelcer, Noam

    2017-11-01

    The cellular demand for cholesterol requires control of its biosynthesis by the mevalonate pathway. Regulation of HMGCR (3-hydroxy-3-methylglutaryl coenzyme A reductase), a rate-limiting enzyme in this pathway and the target of statins, is a key control point herein. Accordingly, HMGCR is subject to negative and positive regulation. In particular, the ability of oxysterols and intermediates of the mevalonate pathway to stimulate its proteasomal degradation is an exquisite example of metabolically controlled feedback regulation. To define the genetic determinants that govern this process, we conducted an unbiased haploid mammalian genetic screen. We generated human haploid cells with mNeon fused to endogenous HMGCR using CRISPR/Cas9 and used these cells to interrogate regulation of HMGCR abundance in live cells. This resulted in identification of known and new regulators of HMGCR, and among the latter, UBXD8 (ubiquitin regulatory X domain-containing protein 8), a gene that has not been previously implicated in this process. We demonstrate that UBXD8 is an essential determinant of metabolically stimulated degradation of HMGCR and of cholesterol biosynthesis in multiple cell types. Accordingly, UBXD8 ablation leads to aberrant cholesterol synthesis due to loss of feedback control. Mechanistically, we show that UBXD8 is necessary for sterol-stimulated dislocation of ubiquitylated HMGCR from the endoplasmic reticulum membrane en route to proteasomal degradation, a function dependent on its UBX domain. We establish UBXD8 as a previously unrecognized determinant that couples flux across the mevalonate pathway to control of cholesterol synthesis and demonstrate the feasibility of applying mammalian haploid genetics to study metabolic traits. © 2017 The Authors.

  15. 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.

  16. Identifying and modeling the structural discontinuities of human interactions

    Science.gov (United States)

    Grauwin, Sebastian; Szell, Michael; Sobolevsky, Stanislav; Hövel, Philipp; Simini, Filippo; Vanhoof, Maarten; Smoreda, Zbigniew; Barabási, Albert-László; Ratti, Carlo

    2017-04-01

    The idea of a hierarchical spatial organization of society lies at the core of seminal theories in human geography that have strongly influenced our understanding of social organization. Along the same line, the recent availability of large-scale human mobility and communication data has offered novel quantitative insights hinting at a strong geographical confinement of human interactions within neighboring regions, extending to local levels within countries. However, models of human interaction largely ignore this effect. Here, we analyze several country-wide networks of telephone calls - both, mobile and landline - and in either case uncover a systematic decrease of communication induced by borders which we identify as the missing variable in state-of-the-art models. Using this empirical evidence, we propose an alternative modeling framework that naturally stylizes the damping effect of borders. We show that this new notion substantially improves the predictive power of widely used interaction models. This increases our ability to understand, model and predict social activities and to plan the development of infrastructures across multiple scales.

  17. A simple technique to identify key recruitment issues in randomised controlled trials: Q-QAT - Quanti-Qualitative Appointment Timing.

    Science.gov (United States)

    Paramasivan, Sangeetha; Strong, Sean; Wilson, Caroline; Campbell, Bruce; Blazeby, Jane M; Donovan, Jenny L

    2015-03-11

    Recruitment to pragmatic randomised controlled trials (RCTs) is acknowledged to be difficult, and few interventions have proved to be effective. Previous qualitative research has consistently revealed that recruiters provide imbalanced information about RCT treatments. However, qualitative research can be time-consuming to apply. Within a programme of research to optimise recruitment and informed consent in challenging RCTs, we developed a simple technique, Q-QAT (Quanti-Qualitative Appointment Timing), to systematically investigate and quantify the imbalance to help identify and address recruitment difficulties. The Q-QAT technique comprised: 1) quantification of time spent discussing the RCT and its treatments using transcripts of audio-recorded recruitment appointments, 2) targeted qualitative research to understand the obstacles to recruitment and 3) feedback to recruiters on opportunities for improvement. This was applied to two RCTs with different clinical contexts and recruitment processes. Comparisons were made across clinical centres, recruiters and specialties. In both RCTs, the Q-QAT technique first identified considerable variations in the time spent by recruiters discussing the RCT and its treatments. The patterns emerging from this initial quantification of recruitment appointments then enabled targeted qualitative research to understand the issues and make suggestions to improve recruitment. In RCT1, presentation of the treatments was balanced, but little time was devoted to describing the RCT. Qualitative research revealed patients would have considered participation, but lacked awareness of the RCT. In RCT2, the balance of treatment presentation varied by specialists and centres. Qualitative research revealed difficulties with equipoise and confidence among recruiters presenting the RCT. The quantitative and qualitative findings were well-received by recruiters and opportunities to improve information provision were discussed. A blind coding

  18. Identifying fast-onset antidepressants using rodent models.

    Science.gov (United States)

    Ramaker, M J; Dulawa, S C

    2017-05-01

    Depression is a leading cause of disability worldwide and a major contributor to the burden of suicide. A major limitation of classical antidepressants is that 2-4 weeks of continuous treatment is required to elicit therapeutic effects, prolonging the period of depression, disability and suicide risk. Therefore, the development of fast-onset antidepressants is crucial. Preclinical identification of fast-onset antidepressants requires animal models that can accurately predict the delay to therapeutic onset. Although several well-validated assay models exist that predict antidepressant potential, few thoroughly tested animal models exist that can detect therapeutic onset. In this review, we discuss and assess the validity of seven rodent models currently used to assess antidepressant onset: olfactory bulbectomy, chronic mild stress, chronic forced swim test, novelty-induced hypophagia (NIH), novelty-suppressed feeding (NSF), social defeat stress, and learned helplessness. We review the effects of classical antidepressants in these models, as well as six treatments that possess fast-onset antidepressant effects in the clinic: electroconvulsive shock therapy, sleep deprivation, ketamine, scopolamine, GLYX-13 and pindolol used in conjunction with classical antidepressants. We also discuss the effects of several compounds that have yet to be tested in humans but have fast-onset antidepressant-like effects in one or more of these antidepressant onset sensitive models. These compounds include selective serotonin (5-HT) 2C receptor antagonists, a 5-HT 4 receptor agonist, a 5-HT 7 receptor antagonist, NMDA receptor antagonists, a TREK-1 receptor antagonist, mGluR antagonists and (2R,6R)-HNK. Finally, we provide recommendations for identifying fast-onset antidepressants using rodent behavioral models and molecular approaches.

  19. 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

  20. 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…

  1. Transition and the community college: a Career Keys model for students with disabilities.

    Science.gov (United States)

    Roessler, Richard T.; Brown, Patricia L.

    2000-01-01

    Transition models are needed that address multiple phases in the postsecondary education of students with disabilities. These models must first address the recruitment of high school students with disabilities for community colleges through career exploration experiences that help students clarify their educational and vocational interests and relate those interests to a two-year postsecondary program. Students with disabilities then need a comprehensive service program while attending community college to help them identify accommodation needs in classroom and workplace environments and develop the skills to request such accommodations from their instructors and employers. With this skill base, they are well prepared to initiate the next transition in their lives, that is, the movement from the community college to a four-year educational institution or to employment. Programs are needed to facilitate this transition, such as a placement planning seminar involving rehabilitation professionals and employers and an accommodation follow-up assessment with students in their new educational and employment settings. The "Career Keys" model describes how to deliver the services needed in each of these critical transition phases.

  2. 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.

  3. Dissection of the Ascaris Sperm Motility Machinery Identifies Key Proteins Involved in Major Sperm Protein-based Amoeboid Locomotion

    Science.gov (United States)

    Buttery, Shawnna M.; Ekman, Gail C.; Seavy, Margaret; Stewart, Murray; Roberts, Thomas M.

    2003-01-01

    Although Ascaris sperm motility closely resembles that seen in many other types of crawling cells, the lamellipodial dynamics that drive movement result from modulation of a cytoskeleton based on the major sperm protein (MSP) rather than actin. The dynamics of the Ascaris sperm cytoskeleton can be studied in a cell-free in vitro system based on the movement of plasma membrane vesicles by fibers constructed from bundles of MSP filaments. In addition to ATP, MSP, and a plasma membrane protein, reconstitution of MSP motility in this cell-free extract requires cytosolic proteins that orchestrate the site-specific assembly and bundling of MSP filaments that generates locomotion. Here, we identify a fraction of cytosol that is comprised of a small number of proteins but contains all of the soluble components required to assemble fibers. We have purified two of these proteins, designated MSP fiber proteins (MFPs) 1 and 2 and demonstrated by immunolabeling that both are located in the MSP cytoskeleton in cells and in fibers. These proteins had reciprocal effects on fiber assembly in vitro: MFP1 decreased the rate of fiber growth, whereas MFP2 increased the growth rate. PMID:14565983

  4. Using a structured review of the literature to identify key factors associated with the current nursing shortage.

    Science.gov (United States)

    Duvall, Judy J; Andrews, Diane Randall

    2010-01-01

    The current population of nurses is aging and rapidly approaching retirement, and graduation of new nurses is not expected to meet demand. Multiple reports have offered information regarding the pending shortage and made recommendations regarding interventions. It is important that suggested interventions be based upon current evidence. An integrated review of literature was undertaken, searching CINAHL, PubMed, Academic Search Premier, Medline, and PsychInfo. Studies were limited to those conducted in the United States and published in English between 2000 and 2007. Search terms were nursing shortage, job satisfaction in nursing, stress in nursing, nursing turnover, nursing image, nursing work environment, physical demands of nursing, and nursing faculty shortage. The identified reasons for nurses leaving hospital practice were management issues, job design, job stress, physical demands, and the failure to nurture new nurses. The education issues include a lack of qualified faculty and clinical sites to allow for more students to be accepted into the programs. These are issues that can be addressed; and changes, implemented. Steps must be taken immediately to resolve these issues in an effort to keep an adequate supply of nurses at the bedside. Copyright © 2010 Elsevier Inc. All rights reserved.

  5. Inflammatory and fibrotic proteins proteomically identified as key protein constituents in urine and stone matrix of patients with kidney calculi.

    Science.gov (United States)

    Boonla, Chanchai; Tosukhowong, Piyaratana; Spittau, Björn; Schlosser, Andreas; Pimratana, Chaowat; Krieglstein, Kerstin

    2014-02-15

    To uncover whether urinary proteins are incorporated into stones, the proteomic profiles of kidney stones and urine collected from the same patients have to be explored. We employed 1D-PAGE and nanoHPLC-ESI-MS/MS to analyze the proteomes of kidney stone matrix (n=16), nephrolithiatic urine (n=14) and healthy urine (n=3). We identified 62, 66 and 22 proteins in stone matrix, nephrolithiatic urine and healthy urine, respectively. Inflammation- and fibrosis-associated proteins were frequently detected in the stone matrix and nephrolithiatic urine. Eighteen proteins were exclusively found in the stone matrix and nephrolithiatic urine, considered as candidate biomarkers for kidney stone formation. S100A8 and fibronectin, representatives of inflammation and fibrosis, respectively, were up-regulated in nephrolithiasis renal tissues. S100A8 was strongly expressed in infiltrated leukocytes. Fibronectin was over-expressed in renal tubular cells. S100A8 and fibronectin were immunologically confirmed to exist in nephrolithiatic urine and stone matrix, but in healthy urine they were undetectable. Conclusion, both kidney stones and urine obtained from the same patients greatly contained inflammatory and fibrotic proteins. S100A8 and fibronectin were up-regulated in stone-baring kidneys and nephrolithiatic urine. Therefore, inflammation and fibrosis are suggested to be involved in the formation of kidney calculi. Copyright © 2013 Elsevier B.V. All rights reserved.

  6. 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.

  7. Statistical study to identify the key factors governing ground water recharge in the watersheds of the arid Central Asia.

    Science.gov (United States)

    Zhu, Binq-Qi; Wang, Yue-Ling

    2016-01-01

    Understanding the source and recharge of ground waters is of great significance to our knowledge in hydrological cycles in arid environments over the world. Northern Xinjiang in northwestern China is a significant repository of information relating to the hydrological evolution and climatic changes in central Asia. In this study, two multivariate statistical techniques, hierarchical cluster analysis (HCA) and principal component analysis (PCA), were used to assess the ground water recharge and its governing factors, with the principal idea of exploring the above techniques to utilize all available hydrogeochemical variables in the quality assessment, which are not considered in the conventional techniques like Stiff and Piper diagrams. Q-mode HCA and R-mode PCA were combined to partition the water samples into seven major water clusters (C1-C7) and three principal components (PC1-PC3, PC1 salinity, PC2 hydroclimate, PC3 contaminant). The water samples C1 + C4 were classified as recharge area waters (Ca-HCO3 water), C2 + C3 as transitional zone waters (Ca-Mg-HCO3-SO4 water), and C5 + C6 + C7 as discharge area waters (Na-SO4 water). Based on the Q-mode PCA scores, three groups of geochemical processes influencing recharge regimes were identified: geogenic (i.e., caused by natural geochemical processes), geomorphoclimatic (caused by topography and climate), and anthropogenic (caused by ground water contamination). It is proposed that differences in recharge mechanism and ground water evolution, and possible bedrock composition difference, are responsible for the chemical genesis of these waters. These will continue to influence the geochemistry of the northern Xinjiang drainage system for a long time due to its steady tectonics and arid climate. This study proved that the chemistry differentiation of ground water can effectively support the identification of ground water recharge and evolution patterns.

  8. An analysis of offshore wind farm SCADA measurements to identify key parameters influencing the magnitude of wake effects

    Science.gov (United States)

    Mittelmeier, N.; Blodau, T.; Steinfeld, G.; Rott, A.; Kühn, M.

    2016-09-01

    Atmospheric conditions have a clear influence on wake effects. Stability classification is usually based on wind speed, turbulence intensity, shear and temperature gradients measured partly at met masts, buoys or LiDARs. The objective of this paper is to find a classification for stability based on wind turbine Supervisory Control and Data Acquisition (SCADA) measurements in order to fit engineering wake models better to the current ambient conditions. Two offshore wind farms with met masts have been used to establish a correlation between met mast stability classification and new aggregated statistical signals based on multiple measurement devices. The significance of these new signals on power production is demonstrated for two wind farms with met masts and validated against data from one further wind farm without a met mast. We found a good correlation between the standard deviation of active power divided by the average power of wind turbines in free flow with the ambient turbulence intensity when the wind turbines were operating in partial load.

  9. Using SMAP to identify structural errors in hydrologic models

    Science.gov (United States)

    Crow, W. T.; Reichle, R. H.; Chen, F.; Xia, Y.; Liu, Q.

    2017-12-01

    Despite decades of effort, and the development of progressively more complex models, there continues to be underlying uncertainty regarding the representation of basic water and energy balance processes in land surface models. Soil moisture occupies a central conceptual position between atmosphere forcing of the land surface and resulting surface water fluxes. As such, direct observations of soil moisture are potentially of great value for identifying and correcting fundamental structural problems affecting these models. However, to date, this potential has not yet been realized using satellite-based retrieval products. Using soil moisture data sets produced by the NASA Soil Moisture Active/Passive mission, this presentation will explore the use of the remotely-sensed soil moisture data products as a constraint to reject certain types of surface runoff parameterizations within a land surface model. Results will demonstrate that the precision of the SMAP Level 4 Surface and Root-Zone soil moisture product allows for the robust sampling of correlation statistics describing the true strength of the relationship between pre-storm soil moisture and subsequent storm-scale runoff efficiency (i.e., total storm flow divided by total rainfall both in units of depth). For a set of 16 basins located in the South-Central United States, we will use these sampled correlations to demonstrate that so-called "infiltration-excess" runoff parameterizations under predict the importance of pre-storm soil moisture for determining storm-scale runoff efficiency. To conclude, we will discuss prospects for leveraging this insight to improve short-term hydrologic forecasting and additional avenues for SMAP soil moisture products to provide process-level insight for hydrologic modelers.

  10. 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.

  11. Key landscape and biotic indicators of watersheds sensitivity to forest disturbance identified using remote sensing and historical hydrography data

    Science.gov (United States)

    Buma, Brian; Livneh, Ben

    2017-07-01

    Water is one of the most critical resources derived from natural systems. While it has long been recognized that forest disturbances like fire influence watershed streamflow characteristics, individual studies have reported conflicting results with some showing streamflow increases post-disturbance and others decreases, while other watersheds are insensitive to even large disturbance events. Characterizing the differences between sensitive (e.g. where streamflow does change post-disturbance) and insensitive watersheds is crucial to anticipating response to future disturbance events. Here, we report on an analysis of a national-scale, gaged watershed database together with high-resolution forest mortality imagery. A simple watershed response model was developed based on the runoff ratio for watersheds (n = 73) prior to a major disturbance, detrended for variation in precipitation inputs. Post-disturbance deviations from the expected water yield and streamflow timing from expected (based on observed precipitation) were then analyzed relative to the abiotic and biotic characteristics of the individual watershed and observed extent of forest mortality. The extent of the disturbance was significantly related to change in post-disturbance water yield (p water yield. Highly disturbed, arid watersheds with low soil: water contact time are the most likely to see increases, with the magnitude positively correlated with the extent of disturbance. Watersheds dominated by deciduous forest with low bulk density soils typically show reduced yield post-disturbance. Post-disturbance streamflow timing change was associated with climate, forest type, and soil. Snowy coniferous watersheds were generally insensitive to disturbance, whereas finely textured soils with rapid runoff were sensitive. This is the first national scale investigation of streamflow post-disturbance using fused gage and remotely sensed data at high resolution, and gives important insights that can be used to

  12. 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.

  13. A Model to Identify Sarcopenia in Patients With Cirrhosis.

    Science.gov (United States)

    Tandon, Puneeta; Low, Gavin; Mourtzakis, Marina; Zenith, Laura; Myers, Robert P; Abraldes, Juan G; Shaheen, Abdel Aziz M; Qamar, Hina; Mansoor, Nadia; Carbonneau, Michelle; Ismond, Kathleen; Mann, Sumeer; Alaboudy, Alshimaa; Ma, Mang

    2016-10-01

    The severe depletion of muscle mass at the third lumbar vertebral level (sarcopenia) is a marker of malnutrition and is independently associated with mortality in patients with cirrhosis. Instead of monitoring sarcopenia by cross-sectional imaging, we investigated whether ultrasound-based measurements of peripheral muscle mass, measures of muscle function, along with nutritional factors, are associated with severe loss of muscle mass. We performed a prospective study of 159 outpatients with cirrhosis (56% male; mean age, 58 ± 10 years; mean model for end-stage liver disease score, 10 ± 3; 60% Child-Pugh class A) evaluated at the Cirrhosis Care Clinic at the University of Alberta Hospital from March 2011 through September 2012. Lumbar skeletal muscle indices were determined by computed tomography or magnetic resonance imaging. We collected clinical data and data on patients' body composition, nutrition, and thigh muscle thickness (using ultrasound analysis). We also measured mid-arm muscle circumference, mid-arm circumference, hand grip, body mass index, and serum level of albumin; patients were evaluated using the subjective global assessment scale. Findings from these analyses were compared with those from cross-sectional imaging, for each sex, using logistic regression analysis. Based on cross-sectional imaging analysis, 43% of patients had sarcopenia (57% of men and 25% of women). Results from the subjective global assessment, serum level of albumin, and most nutritional factors were significantly associated with sarcopenia. We used multivariate analysis to develop a model to identify patients with sarcopenia, and developed a nomogram based on body mass index and thigh muscle thickness for patients of each sex. Our model identified men with sarcopenia with an area under the receiver operating characteristic curve value of 0.78 and women with sarcopenia with an area under the receiver operating characteristic curve value of 0.89. In a prospective study of

  14. 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.

  15. 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

  16. 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

  17. A New Key Predistribution Scheme for Multiphase Sensor Networks Using a New Deployment Model

    Directory of Open Access Journals (Sweden)

    Boqing Zhou

    2014-01-01

    Full Text Available During the lifecycle of sensor networks, making use of the existing key predistribution schemes using deployment knowledge for pairwise key establishment and authentication between nodes, a new challenge is elevated. Either the resilience against node capture attacks or the global connectivity will significantly decrease with time. In this paper, a new deployment model is developed for multiphase deployment sensor networks, and then a new key management scheme is further proposed. Compared with the existing schemes using deployment knowledge, our scheme has better performance in global connectivity, resilience against node capture attacks throughout their lifecycle.

  18. 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

  19. 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...

  20. Quantification of key parameters for treating contrails in a large scale climate model

    Energy Technology Data Exchange (ETDEWEB)

    Ponater, M.; Gierens, K. [Deutsche Forschungsanstalt fuer Luft- und Raumfahrt e.V. (DLR), Wessling (Germany). Inst. fuer Physik der Atmosphaere

    1997-12-01

    The general objective of this project, to determine contrail key parameters with respect to their climate effect, has been approached by three tasks: (1) quantification of microphysical key parameters, (2) development of a contrail coverage parametrization for climate models, and (3) determination of the worldwide coverage with persistent contrails due to present day air traffic. The microphysical key parameters are determined using microphysical box model simulations. The contrail parametrization was achieved by deriving (from aircraft measurements) the instantaneous fluctuations of temperature and relative humidity that occur on spatial scales beyond the resolution of climate models. The global and annual mean coverage by persistent contrails was calculated from ECMWF numerical analyses and from actual air traffic density. It was found to be currently about 0.1%, though the atmosphere has the potential to form persistent contrails over a much larger area. (orig.) 144 figs., 42 tabs., 497 refs.

  1. Key-Aspects of Scientific Modeling Exemplified by School Science Models: Some Units for Teaching Contextualized Scientific Methodology

    Science.gov (United States)

    Develaki, Maria

    2016-01-01

    Models and modeling are core elements of scientific methods and consequently also are of key importance for the conception and teaching of scientific methodology. The epistemology of models and its transfer and adaption to nature of science education are not, however, simple themes. We present some conceptual units in which school science models…

  2. 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 sl...... of the aggregates to activate endocytosis pathways on specific cell types is discussed in the context of targeted drug delivery applications.......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...

  3. 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.

  4. 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.

  5. 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...

  6. 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 ...

  7. 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...

  8. 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

  9. 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

    2018-03-06

    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 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.

  10. 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.

  11. 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.

  12. 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.

  13. Avoiding and identifying errors in health technology assessment models: qualitative study and methodological review.

    Science.gov (United States)

    Chilcott, J; Tappenden, P; Rawdin, A; Johnson, M; Kaltenthaler, E; Paisley, S; Papaioannou, D; Shippam, A

    2010-05-01

    , stepping through skeleton models with experts, ensuring transparency in reporting, adopting standard housekeeping techniques, and ensuring that those parties involved in the model development process have sufficient and relevant training. Clarity and mutual understanding were identified as key issues. However, their current implementation is not framed within an overall strategy for structuring complex problems. Some of the questioning may have biased interviewees responses but as all interviewees were represented in the analysis no rebalancing of the report was deemed necessary. A potential weakness of the literature review was its focus on spreadsheet and program development rather than specifically on model development. It should also be noted that the identified literature concerning programming errors was very narrow despite broad searches being undertaken. Published definitions of overall model validity comprising conceptual model validation, verification of the computer model, and operational validity of the use of the model in addressing the real-world problem are consistent with the views expressed by the HTA community and are therefore recommended as the basis for further discussions of model credibility. Such discussions should focus on risks, including errors of implementation, errors in matters of judgement and violations. Discussions of modelling risks should reflect the potentially complex network of cognitive breakdowns that lead to errors in models and existing research on the cognitive basis of human error should be included in an examination of modelling errors. There is a need to develop a better understanding of the skills requirements for the development, operation and use of HTA models. Interaction between modeller and client in developing mutual understanding of a model establishes that model's significance and its warranty. This highlights that model credibility is the central concern of decision-makers using models so it is crucial that the

  14. Construction and Research of System Identifiable Mathematical Models

    OpenAIRE

    Robertas Janickas

    2011-01-01

    Paper discusses about control and data acquisition, processing, visualization, which must be adapted to the investigation and examination of identification process. A description of the device, the functionality and customization possibilities are presented. The relevant experimental model and its characteristics are obtained for measurement, control results using this model.Article in Lithuanian

  15. Construction and Research of System Identifiable Mathematical Models

    Directory of Open Access Journals (Sweden)

    Robertas Janickas

    2011-08-01

    Full Text Available Paper discusses about control and data acquisition, processing, visualization, which must be adapted to the investigation and examination of identification process. A description of the device, the functionality and customization possibilities are presented. The relevant experimental model and its characteristics are obtained for measurement, control results using this model.Article in Lithuanian

  16. 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.

  17. 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

  18. 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...

  19. Identifying Objective and Subjective Words via Topic Modeling.

    Science.gov (United States)

    Wang, Hanqi; Wu, Fei; Lu, Weiming; Yang, Yi; Li, Xi; Li, Xuelong; Zhuang, Yueting

    2018-03-01

    It is observed that distinct words in a given document have either strong or weak ability in delivering facts (i.e., the objective sense) or expressing opinions (i.e., the subjective sense) depending on the topics they associate with. Motivated by the intuitive assumption that different words have varying degree of discriminative power in delivering the objective sense or the subjective sense with respect to their assigned topics, a model named as dentified bjective- ubjective latent Dirichlet allocation (LDA) ( osLDA) is proposed in this paper. In the osLDA model, the simple Pólya urn model adopted in traditional topic models is modified by incorporating it with a probabilistic generative process, in which the novel "Bag-of-Discriminative-Words" (BoDW) representation for the documents is obtained; each document has two different BoDW representations with regard to objective and subjective senses, respectively, which are employed in the joint objective and subjective classification instead of the traditional Bag-of-Topics representation. The experiments reported on documents and images demonstrate that: 1) the BoDW representation is more predictive than the traditional ones; 2) osLDA boosts the performance of topic modeling via the joint discovery of latent topics and the different objective and subjective power hidden in every word; and 3) osLDA has lower computational complexity than supervised LDA, especially under an increasing number of topics.

  20. IDENTIFYING CANCER SPECIFIC METABOLIC SIGNATURES USING CONSTRAINT-BASED MODELS.

    Science.gov (United States)

    Schultz, A; Mehta, S; Hu, C W; Hoff, F W; Horton, T M; Kornblau, S M; Qutub, A A

    2017-01-01

    Cancer metabolism differs remarkably from the metabolism of healthy surrounding tissues, and it is extremely heterogeneous across cancer types. While these metabolic differences provide promising avenues for cancer treatments, much work remains to be done in understanding how metabolism is rewired in malignant tissues. To that end, constraint-based models provide a powerful computational tool for the study of metabolism at the genome scale. To generate meaningful predictions, however, these generalized human models must first be tailored for specific cell or tissue sub-types. Here we first present two improved algorithms for (1) the generation of these context-specific metabolic models based on omics data, and (2) Monte-Carlo sampling of the metabolic model ux space. By applying these methods to generate and analyze context-specific metabolic models of diverse solid cancer cell line data, and primary leukemia pediatric patient biopsies, we demonstrate how the methodology presented in this study can generate insights into the rewiring differences across solid tumors and blood cancers.

  1. Identifying Model-Based Reconfiguration Goals through Functional Deficiencies

    Science.gov (United States)

    Benazera, Emmanuel; Trave-Massuyes, Louise

    2004-01-01

    Model-based diagnosis is now advanced to the point autonomous systems face some uncertain and faulty situations with success. The next step toward more autonomy is to have the system recovering itself after faults occur, a process known as model-based reconfiguration. After faults occur, given a prediction of the nominal behavior of the system and the result of the diagnosis operation, this paper details how to automatically determine the functional deficiencies of the system. These deficiencies are characterized in the case of uncertain state estimates. A methodology is then presented to determine the reconfiguration goals based on the deficiencies. Finally, a recovery process interleaves planning and model predictive control to restore the functionalities in prioritized order.

  2. 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.

  3. 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.

  4. 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).

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

    Indian Academy of Sciences (India)

    In this paper, we have proposed anew wavelet transform-based algorithm to model the abrupt discontinuous changes from well log databy taking care of nonstationary characteristics of the signal. Prior to applying the algorithm on thegeophysical well data, we analyzed the distribution of wavelet coefficients using synthetic ...

  6. An ecohydraulic model to identify and monitor moapa dace habitat

    Science.gov (United States)

    Hatten, James R.; Batt, Thomas R.; Scoppettone, Gayton G.; Dixon, Christopher J.

    2013-01-01

    Moapa dace (Moapa coriacea) is a critically endangered thermophilic minnow native to the Muddy River ecosystem in southeastern Nevada, USA. Restricted to temperatures between 26.0 and 32.0°C, these fish are constrained to the upper two km of the Muddy River and several small tributaries fed by warm springs. Habitat alterations, nonnative species invasion, and water withdrawals during the 20th century resulted in a drastic decline in the dace population and in 1979 the Moapa Valley National Wildlife Refuge (Refuge) was created to protect them. The goal of our study was to determine the potential effects of reduced surface flows that might result from groundwater pumping or water diversions on Moapa dace habitat inside the Refuge. We accomplished our goal in several steps. First, we conducted snorkel surveys to determine the locations of Moapa dace on three warm-spring tributaries of the Muddy River. Second, we conducted hydraulic simulations over a range of flows with a two-dimensional hydrodynamic model. Third, we developed a set of Moapa dace habitat models with logistic regression and a geographic information system. Fourth, we estimated Moapa dace habitat over a range of flows (plus or minus 30% of base flow). Our spatially explicit habitat models achieved classification accuracies between 85% and 91%, depending on the snorkel survey and creek. Water depth was the most significant covariate in our models, followed by substrate, Froude number, velocity, and water temperature. Hydraulic simulations showed 2-11% gains in dace habitat when flows were increased by 30%, and 8-32% losses when flows were reduced by 30%. To ensure the health and survival of Moapa dace and the Muddy River ecosystem, groundwater and surface-water withdrawals and diversions need to be carefully monitored, while fully implementing a proactive conservation strategy.

  7. An ecohydraulic model to identify and monitor Moapa dace habitat.

    Directory of Open Access Journals (Sweden)

    James R Hatten

    Full Text Available Moapa dace (Moapa coriacea is a critically endangered thermophilic minnow native to the Muddy River ecosystem in southeastern Nevada, USA. Restricted to temperatures between 26.0 and 32.0 °C, these fish are constrained to the upper two km of the Muddy River and several small tributaries fed by warm springs. Habitat alterations, nonnative species invasion, and water withdrawals during the 20th century resulted in a drastic decline in the dace population and in 1979 the Moapa Valley National Wildlife Refuge (Refuge was created to protect them. The goal of our study was to determine the potential effects of reduced surface flows that might result from groundwater pumping or water diversions on Moapa dace habitat inside the Refuge. We accomplished our goal in several steps. First, we conducted snorkel surveys to determine the locations of Moapa dace on three warm-spring tributaries of the Muddy River. Second, we conducted hydraulic simulations over a range of flows with a two-dimensional hydrodynamic model. Third, we developed a set of Moapa dace habitat models with logistic regression and a geographic information system. Fourth, we estimated Moapa dace habitat over a range of flows (plus or minus 30% of base flow. Our spatially explicit habitat models achieved classification accuracies between 85% and 91%, depending on the snorkel survey and creek. Water depth was the most significant covariate in our models, followed by substrate, Froude number, velocity, and water temperature. Hydraulic simulations showed 2-11% gains in dace habitat when flows were increased by 30%, and 8-32% losses when flows were reduced by 30%. To ensure the health and survival of Moapa dace and the Muddy River ecosystem, groundwater and surface-water withdrawals and diversions need to be carefully monitored, while fully implementing a proactive conservation strategy.

  8. UNIVERSITY INNOVATION INFRASTRUCTURE MODEL AS A KEY PART OF A TERRITORAL CLUST

    Directory of Open Access Journals (Sweden)

    Nataliya P. Ivashchenko

    2015-01-01

    Full Text Available Over the recent decades there have been increasing efforts by developing countries to reduce the economic gap between developed and developing countries. Asian and Northern European countries demonstrate good progress in these areas.Sweden,Denmark,Chinashow stable high economic indicators that have been achieved by targeted government programs. These programs were aimed at creating a new type of economy based on knowledge and new technologies. Given the success of these countries, a number of developing countries, whose economies are dependent on resources, today, are looking to repeat their way; those countries areRussia,Indonesia,BrazilandChile. The modernization of the economy and the formation of innovative economy are key objectives of the state policies of these countries. The research by leading economists and scientists led to the conclusion that the regional level of national economy plays a key role in formation of knowledgebase economy, which indicates the need to differentiate the innovation policy of the state depending on the economy parameters of each region. This paper presents a model of the first stage of the formation of the entrepreneurialuniversityUniversityinnovation infrastructure model, which is a key part of a territoral cluster. The article consists of five parts. The first part covers the analysis of the two main models of regional development: clustering theory and Triple Helix. This section describes a positive result, which is achieved by using these models simultaneously. The second part of the article shows the importance and the role of the entrepreneurial university in the formation of innovative clusters. It will be explained how and under what conditions this formation is achieved. The third part of this paper will present University innovation infrastructure model. The fourth part will examine the practical first steps to create a cluster "Vorob’evi Gori" on the basis of theMoscowStateUniversity. The fifth

  9. Technology as system innovation: a key informant interview study of the application of the diffusion of innovation model to telecare.

    Science.gov (United States)

    Sugarhood, Paul; Wherton, Joseph; Procter, Rob; Hinder, Sue; Greenhalgh, Trisha

    2014-01-01

    To identify and explore factors that influence adoption, implementation and continued use of telecare technologies. As part of the Assistive Technologies for Healthy Living in Elders: Needs Assessment by Ethnography (ATHENE) project, 16 semi-structured interviews were conducted with key participants from organisations involved in developing and providing telecare technologies and services. Data were analysed thematically, using a conceptual model of diffusion of innovations. Participants identified numerous interacting factors that facilitated or hindered adoption and use. As predicted by the model, these related variously to the technology, individual adopters, the process of social influence, the innovativeness and readiness of organisations, implementation and routinisation processes following initial adoption, and the nature and strength of linkages between these elements. Key issues included (i) the complexity and uniqueness of the "user system", (ii) the ongoing work needed to support telecare use beyond initial adoption, and (iii) the relatively weak links that typically exist between users of telecare technologies and the organisations who design and distribute them. Telecare is not merely a technology but a complex innovation requiring input from, and coordination between, people and organisations. To promote adoption and use, these contextual factors must be specified, understood and addressed.

  10. 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

  11. 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.

  12. 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 100000 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.

  13. [A model for evaluation of key measures for control of chikungunya fever outbreak in China].

    Science.gov (United States)

    Zhao, Jin; Liu, Ruchun; Chen, Shuilian; Chen, Tianmu

    2015-11-01

    To analyze the transmission pattern of Chikungunya (CHIK) fever in community and evaluate the effectiveness of mosquito control, case isolation and other key control measures by using ordinary differential equation (ODE) model. According to natural history of CHIK, an ODE model for the epidemiological analysis of CHIK outbreak was established. The key parameters of the model were obtained by fitting the model with reported outbreak data of the first CHIK outbreak in China. Then the outbreak characteristics without intervention, the effectiveness of mosquito control and case isolation were simulated. Without intervention, an imported case would cause an outbreak in a community with population of 11 000, and cumulative case number would exceed 941 when the total attack rate was 8.55%. The results of our simulation revealed that the effectiveness of case isolation was not perfect enough when it was implemented alone. Although the number of cases could be decreased by case isolation, the duration of outbreak would not be shortened. Differently, the effectiveness of mosquito control was remarkable. In addition, the earlier the measure was implemented, the better the effectiveness would be. The effectiveness of mosquito control plus case isolation was same with mosquito control. To control a CHIK outbreak, mosquito control is the most recommended measures. However, case isolation is also necessary as the supplementation of mosquito control.

  14. A multi-omics approach identifies key hubs associated with cell type-specific responses of airway epithelial cells to staphylococcal alpha-toxin.

    Directory of Open Access Journals (Sweden)

    Erik Richter

    Full Text Available Responsiveness of cells to alpha-toxin (Hla from Staphylococcus aureus appears to occur in a cell-type dependent manner. Here, we compare two human bronchial epithelial cell lines, i.e. Hla-susceptible 16HBE14o- and Hla-resistant S9 cells, by a quantitative multi-omics strategy for a better understanding of Hla-induced cellular programs. Phosphoproteomics revealed a substantial impact on phosphorylation-dependent signaling in both cell models and highlights alterations in signaling pathways associated with cell-cell and cell-matrix contacts as well as the actin cytoskeleton as key features of early rHla-induced effects. Along comparable changes in down-stream activity of major protein kinases significant differences between both models were found upon rHla-treatment including activation of the epidermal growth factor receptor EGFR and mitogen-activated protein kinases MAPK1/3 signaling in S9 and repression in 16HBE14o- cells. System-wide transcript and protein expression profiling indicate induction of an immediate early response in either model. In addition, EGFR and MAPK1/3-mediated changes in gene expression suggest cellular recovery and survival in S9 cells but cell death in 16HBE14o- cells. Strikingly, inhibition of the EGFR sensitized S9 cells to Hla indicating that the cellular capacity of activation of the EGFR is a major protective determinant against Hla-mediated cytotoxic effects.

  15. 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.

  16. Estimation of umbilical cord blood leptin and insulin based on anthropometric data by means of artificial neural network approach: identifying key maternal and neonatal factors.

    Science.gov (United States)

    Guzmán-Bárcenas, José; Hernández, José Alfredo; Arias-Martínez, Joel; Baptista-González, Héctor; Ceballos-Reyes, Guillermo; Irles, Claudine

    2016-07-21

    Leptin and insulin levels are key factors regulating fetal and neonatal energy homeostasis, development and growth. Both biomarkers are used as predictors of weight gain and obesity during infancy. There are currently no prediction algorithms for cord blood (UCB) hormone levels using Artificial Neural Networks (ANN) that have been directly trained with anthropometric maternal and neonatal data, from neonates exposed to distinct metabolic environments during pregnancy (obese with or without gestational diabetes mellitus or lean women). The aims were: 1) to develop ANN models that simulate leptin and insulin concentrations in UCB based on maternal and neonatal data (ANN perinatal model) or from only maternal data during early gestation (ANN prenatal model); 2) To evaluate the biological relevance of each parameter (maternal and neonatal anthropometric variables). We collected maternal and neonatal anthropometric data (n = 49) in normoglycemic healthy lean, obese or obese with gestational diabetes mellitus women, as well as determined UCB leptin and insulin concentrations by ELISA. The ANN perinatal model consisted of an input layer of 12 variables (maternal and neonatal anthropometric and biochemical data from early gestation and at term) while the ANN prenatal model used only 6 variables (maternal anthropometric from early gestation) in the input layer. For both networks, the output layer contained 1 variable to UCB leptin or to UCB insulin concentration. The best architectures for the ANN perinatal models estimating leptin and insulin were 12-5-1 while for the ANN prenatal models, 6-5-1 and 6-4-1 were found for leptin and insulin, respectively. ANN models presented an excellent agreement between experimental and simulated values. Interestingly, the use of only prenatal maternal anthropometric data was sufficient to estimate UCB leptin and insulin values. Maternal BMI, weight and age as well as neonatal birth were the most influential parameters for leptin while

  17. 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

  18. Modeling Key Drivers of Cholera Transmission Dynamics Provides New Perspectives for Parasitology.

    Science.gov (United States)

    Rinaldo, Andrea; Bertuzzo, Enrico; Blokesch, Melanie; Mari, Lorenzo; Gatto, Marino

    2017-08-01

    Hydroclimatological and anthropogenic factors are key drivers of waterborne disease transmission. Information on human settlements and host mobility on waterways along which pathogens and hosts disperse, and relevant hydroclimatological processes, can be acquired remotely and included in spatially explicit mathematical models of disease transmission. In the case of epidemic cholera, such models allowed the description of complex disease patterns and provided insight into the course of ongoing epidemics. The inclusion of spatial information in models of disease transmission can aid in emergency management and the assessment of alternative interventions. Here, we review the study of drivers of transmission via spatially explicit approaches and argue that, because many parasitic waterborne diseases share the same drivers as cholera, similar principles may apply. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. 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

  20. Key Technology Research on Open Architecture for The Sharing of Heterogeneous Geographic Analysis Models

    Science.gov (United States)

    Yue, S. S.; Wen, Y. N.; Lv, G. N.; Hu, D.

    2013-10-01

    In recent years, the increasing development of cloud computing technologies laid critical foundation for efficiently solving complicated geographic issues. However, it is still difficult to realize the cooperative operation of massive heterogeneous geographical models. Traditional cloud architecture is apt to provide centralized solution to end users, while all the required resources are often offered by large enterprises or special agencies. Thus, it's a closed framework from the perspective of resource utilization. Solving comprehensive geographic issues requires integrating multifarious heterogeneous geographical models and data. In this case, an open computing platform is in need, with which the model owners can package and deploy their models into cloud conveniently, while model users can search, access and utilize those models with cloud facility. Based on this concept, the open cloud service strategies for the sharing of heterogeneous geographic analysis models is studied in this article. The key technology: unified cloud interface strategy, sharing platform based on cloud service, and computing platform based on cloud service are discussed in detail, and related experiments are conducted for further verification.

  1. Implementing the Five-A Model of Technical Refinement: Key Roles of the Sport Psychologist.

    Science.gov (United States)

    Carson, Howie J; Collins, Dave

    2016-10-01

    There is increasing evidence for the significant contribution provided by sport psychologists within applied coaching environments. However, this rarely considers their skills/knowledge being applied when refining athletes' already learned and well-established motor skills. Therefore, this article focuses on how a sport psychologist might assist a coach and athlete to implement long-term permanent and pressure proof refinements. It highlights key contributions at each stage of the Five-A model-designed to deliver these important outcomes-providing both psychomotor and psychosocial input to the support delivery. By employing these recommendations, sport psychologists can make multiple positive contributions to completion of this challenging task.

  2. 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.

  3. 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

    2018-01-19

    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. Published by Elsevier B.V.

  4. A mixed-methods study identifying key intervention targets to improve participation in daily living activities in primary Sjögren's syndrome patients.

    Science.gov (United States)

    Hackett, Katie L; Deane, Katherine H O; Newton, Julia L; Deary, Vincent; Bowman, Simon; Rapley, Tim; Ng, Wan-Fai

    2018-02-06

    Functional ability and participation in life situations are compromised in many primary Sjögren's syndrome (PSS) patients. This study aims to identify the key barriers and priorities to participation in daily living activities, in order to develop potential future interventions. Group concept mapping (GCM), a semi-quantitative, mixed-methods, approach was used to identify and structure ideas from UK PSS patients, adults living with a PSS patient (AHMs) and health care professionals (HCPs). Brainstorming generated ideas, which were summarised into a final set of statements. Participants individually arranged these statements into themes and rated each statement for importance. Multidimensional scaling and hierarchical cluster analysis were applied to sorted and rated data to produce visual representations of the ideas (concept maps), enabling identification of agreed priority areas for interventions. 121 patients, 43 AHMs and 67 HCPs took part. 463 ideas were distilled down to 94 statements. These statements were grouped into seven clusters; 'Patient empowerment', 'Symptoms', 'Wellbeing', 'Access and coordination of healthcare', 'Knowledge and support', 'Public awareness and support' and 'Family and friends'. Patient empowerment and Symptoms were rated as priority conceptual themes. Important statements within priority clusters indicate patients should be taken seriously and supported to self-manage symptoms of oral and ocular dryness, fatigue, pain and poor sleep. Our data highlighted that in addition to managing PSS symptoms; interventions aiming to improve patient empowerment, general wellbeing, access to healthcare, patient education and social support are important to facilitate improved participation in daily living activities. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

  5. 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...

  6. 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.

  7. 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.

  8. Security of Device-Independent Quantum Key Distribution in the Bounded-Quantum-Storage Model

    Directory of Open Access Journals (Sweden)

    S. Pironio

    2013-08-01

    Full Text Available Device-independent quantum key distribution (DIQKD is a formalism that supersedes traditional quantum key distribution, as its security does not rely on any detailed modeling of the internal working of the devices. This strong form of security is only possible using devices producing correlations that violate a Bell inequality. Full security proofs of DIQKD have recently been reported, but they tolerate zero or small amounts of noise and are restricted to protocols based on specific Bell inequalities. Here, we provide a security proof of DIQKD that is both more efficient and noise resistant, and also more general, as it applies to protocols based on arbitrary Bell inequalities and can be adapted to cover supraquantum eavesdroppers limited by the no-signaling principle only. It is formulated, however, in the bounded-quantum-storage model, where an upper bound on the adversary’s quantum memory is a priori known. This condition is not a limitation at present, since the best existing quantum memories have very short coherence times.

  9. Use the predictive models to explore the key factors affecting phytoplankton succession in Lake Erhai, China.

    Science.gov (United States)

    Zhu, Rong; Wang, Huan; Chen, Jun; Shen, Hong; Deng, Xuwei

    2018-01-01

    Increasing algae in Lake Erhai has resulted in frequent blooms that have not only led to water ecosystem degeneration but also seriously influenced the quality of the water supply and caused extensive damage to the local people, as the lake is a water resource for Dali City. Exploring the key factors affecting phytoplankton succession and developing predictive models with easily detectable parameters for phytoplankton have been proven to be practical ways to improve water quality. To this end, a systematic survey focused on phytoplankton succession was conducted over 2 years in Lake Erhai. The data from the first study year were used to develop predictive models, and the data from the second year were used for model verification. The seasonal succession of phytoplankton in Lake Erhai was obvious. The dominant groups were Cyanobacteria in the summer, Chlorophyta in the autumn and Bacillariophyta in the winter. The developments and verification of predictive models indicated that compared to phytoplankton biomass, phytoplankton density is more effective for estimating phytoplankton variation in Lake Erhai. CCA (canonical correlation analysis) indicated that TN (total nitrogen), TP (total phosphorus), DO (dissolved oxygen), SD (Secchi depth), Cond (conductivity), T (water temperature), and ORP (oxidation reduction potential) had significant influences (p < 0.05) on the phytoplankton community. The CCA of the dominant species found that Microcystis was significantly influenced by T. The dominant Chlorophyta, Psephonema aenigmaticum and Mougeotia, were significantly influenced by TN. All results indicated that TN and T were the two key factors driving phytoplankton succession in Lake Erhai.

  10. 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.

  11. 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

  12. 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

  13. Breaking a virus: Identifying molecular level failure modes of a viral capsid by multiscale modeling

    Science.gov (United States)

    Krishnamani, V.; Globisch, C.; Peter, C.; Deserno, M.

    2016-10-01

    We use coarse-grained (CG) simulations to study the deformation of empty Cowpea Chlorotic Mottle Virus (CCMV) capsids under uniaxial compression, from the initial elastic response up to capsid breakage. Our CG model is based on the MARTINI force field and has been amended by a stabilizing elastic network, acting only within individual proteins, that was tuned to capture the fluctuation spectrum of capsid protein dimers, obtained from all atom simulations. We have previously shown that this model predicts force-compression curves that match AFM indentation experiments on empty CCMV capsids. Here we investigate details of the actual breaking events when the CCMV capsid finally fails. We present a symmetry classification of all relevant protein contacts and show that they differ significantly in terms of stability. Specifically, we show that interfaces which break readily are precisely those which are believed to form last during assembly, even though some of them might share the same contacts as other non-breaking interfaces. In particular, the interfaces that form pentamers of dimers never break, while the virtually identical interfaces within hexamers of dimers readily do. Since these units differ in the large-scale geometry and, most noticeably, the cone-angle at the center of the 5- or 6-fold vertex, we propose that the hexameric unit fails because it is pre-stressed. This not only suggests that hexamers of dimers form less frequently during the early stages of assembly; it also offers a natural explanation for the well-known β-barrel motif at the hexameric center as a post-aggregation stabilization mechanism. Finally, we identify those amino acid contacts within all key protein interfaces that are most persistent during compressive deformation of the capsid, thereby providing potential targets for mutation studies aiming to elucidate the key contacts upon which overall stability rests.

  14. Microglia-Based Phenotypic Screening Identifies a Novel Inhibitor of Neuroinflammation Effective in Alzheimer's Disease Models.

    Science.gov (United States)

    Zhou, Wei; Zhong, Guifa; Fu, Sihai; Xie, Hui; Chi, Tianyan; Li, Luyi; Rao, Xiurong; Zeng, Shaogao; Xu, Dengfeng; Wang, Hao; Sheng, Guoqing; Ji, Xing; Liu, Xiaorong; Ji, Xuefei; Wu, Donghai; Zou, Libo; Tortorella, Micky; Zhang, Kejian; Hu, Wenhui

    2016-11-16

    Currently, anti-AD drug discovery using target-based approaches is extremely challenging due to unclear etiology of AD and absence of validated therapeutic protein targets. Neuronal death, regardless of causes, plays a key role in AD progression, and it is directly linked to neuroinflammation. Meanwhile, phenotypic screening is making a resurgence in drug discovery process as an alternative to target-focused approaches. Herein, we employed microglia-based phenotypic screenings to search for small molecules that modulate the release of detrimental proinflammatory cytokines. The identified novel pharmacological inhibitor of neuroinflammation (named GIBH-130) was validated to alter phenotypes of neuroinflammation in AD brains. Notably, this molecule exhibited comparable in vivo efficacy of cognitive impairment relief to donepezil and memantine respectively in both β amyloid-induced and APP/PS1 double transgenic Alzheimer's murine models at a substantially lower dose (0.25 mg/kg). Therefore, GIBH-130 constitutes a unique chemical probe for pathogenesis research and drug development of AD, and it also suggests microglia-based phenotypic screenings that target neuroinflammation as an effective and feasible strategy to identify novel anti-AD agents.

  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. 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.

  17. Sensitivity analysis of key components in large-scale hydroeconomic models

    Science.gov (United States)

    Medellin-Azuara, J.; Connell, C. R.; Lund, J. R.; Howitt, R. E.

    2008-12-01

    This paper explores the likely impact of different estimation methods in key components of hydro-economic models such as hydrology and economic costs or benefits, using the CALVIN hydro-economic optimization for water supply in California. In perform our analysis using two climate scenarios: historical and warm-dry. The components compared were perturbed hydrology using six versus eighteen basins, highly-elastic urban water demands, and different valuation of agricultural water scarcity. Results indicate that large scale hydroeconomic hydro-economic models are often rather robust to a variety of estimation methods of ancillary models and components. Increasing the level of detail in the hydrologic representation of this system might not greatly affect overall estimates of climate and its effects and adaptations for California's water supply. More price responsive urban water demands will have a limited role in allocating water optimally among competing uses. Different estimation methods for the economic value of water and scarcity in agriculture may influence economically optimal water allocation; however land conversion patterns may have a stronger influence in this allocation. Overall optimization results of large-scale hydro-economic models remain useful for a wide range of assumptions in eliciting promising water management alternatives.

  18. 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,...

  19. Are there pollination syndromes in the Australian epacrids (Ericaceae: Styphelioideae)? A novel statistical method to identify key floral traits per syndrome.

    Science.gov (United States)

    Johnson, Karen A

    2013-07-01

    Convergent floral traits hypothesized as attracting particular pollinators are known as pollination syndromes. Floral diversity suggests that the Australian epacrid flora may be adapted to pollinator type. Currently there are empirical data on the pollination systems for 87 species (approx. 15 % of Australian epacrids). This provides an opportunity to test for pollination syndromes and their important morphological traits in an iconic element of the Australian flora. Data on epacrid-pollinator relationships were obtained from published literature and field observation. A multivariate approach was used to test whether epacrid floral attributes related to pollinator profiles. Statistical classification was then used to rank floral attributes according to their predictive value. Data sets excluding mixed pollination systems were used to test the predictive power of statistical classification to identify pollination models. Floral attributes are correlated with bird, fly and bee pollination. Using floral attributes identified as correlating with pollinator type, bird pollination is classified with 86 % accuracy, red flowers being the most important predictor. Fly and bee pollination are classified with 78 and 69 % accuracy, but have a lack of individually important floral predictors. Excluding mixed pollination systems improved the accuracy of the prediction of both bee and fly pollination systems. Although most epacrids have generalized pollination systems, a correlation between bird pollination and red, long-tubed epacrids is found. Statistical classification highlights the relative importance of each floral attribute in relation to pollinator type and proves useful in classifying epacrids to bird, fly and bee pollination systems.

  20. 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.

  1. The identifiability of parameters in a water quality model of the Biebrza River, Poland

    NARCIS (Netherlands)

    Perk, van der M.; Bierkens, M.F.P.

    1997-01-01

    The identifiability of model parameters of a steady state water quality model of the Biebrza River and the resulting variation in model results was examined by applying the Monte Carlo method which combines calibration, identifiability analysis, uncertainty analysis, and sensitivity analysis. The

  2. 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

  3. A study of key features of random atmospheric disturbance models for the approach flight phase

    Science.gov (United States)

    Heffley, R. K.

    1977-01-01

    An analysis and brief simulator experiment were performed to identify and classify important features of random turbulence for the landing approach flight phase. The analysis of various wind models was carried out within the context of the longitudinal closed-loop pilot/vehicle system. The analysis demonstrated the relative importance of atmospheric disturbance scale lengths, horizontal versus vertical gust components, decreasing altitude, and spectral forms of disturbances versus the pilot/vehicle system. Among certain competing wind models, the analysis predicted no significant difference in pilot performance. This was confirmed by a moving base simulator experiment which evaluated the two most extreme models. A number of conclusions were reached: attitude constrained equations do provide a simple but effective approach to describing the closed-loop pilot/vehicle. At low altitudes the horizontal gust component dominates pilot/vehicle performance.

  4. 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

  5. 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.

  6. A confidence building exercise in data and identifiability: Modeling cancer chemotherapy as a case study.

    Science.gov (United States)

    Eisenberg, Marisa C; Jain, Harsh V

    2017-10-27

    Mathematical modeling has a long history in the field of cancer therapeutics, and there is increasing recognition that it can help uncover the mechanisms that underlie tumor response to treatment. However, making quantitative predictions with such models often requires parameter estimation from data, raising questions of parameter identifiability and estimability. Even in the case of structural (theoretical) identifiability, imperfect data and the resulting practical unidentifiability of model parameters can make it difficult to infer the desired information, and in some cases, to yield biologically correct inferences and predictions. Here, we examine parameter identifiability and estimability using a case study of two compartmental, ordinary differential equation models of cancer treatment with drugs that are cell cycle-specific (taxol) as well as non-specific (oxaliplatin). We proceed through model building, structural identifiability analysis, parameter estimation, practical identifiability analysis and its biological implications, as well as alternative data collection protocols and experimental designs that render the model identifiable. We use the differential algebra/input-output relationship approach for structural identifiability, and primarily the profile likelihood approach for practical identifiability. Despite the models being structurally identifiable, we show that without consideration of practical identifiability, incorrect cell cycle distributions can be inferred, that would result in suboptimal therapeutic choices. We illustrate the usefulness of estimating practically identifiable combinations (in addition to the more typically considered structurally identifiable combinations) in generating biologically meaningful insights. We also use simulated data to evaluate how the practical identifiability of the model would change under alternative experimental designs. These results highlight the importance of understanding the underlying mechanisms

  7. 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 inde...

  8. P53 and MITF/Bcl-2 identified as key pathways in the acquired resistance of NRAS-mutant melanoma to MEK inhibition.

    Science.gov (United States)

    Najem, Ahmad; Krayem, Mohammad; Salès, François; Hussein, Nader; Badran, Bassam; Robert, Caroline; Awada, Ahmad; Journe, Fabrice; Ghanem, Ghanem E

    2017-09-01

    inhibition to induce massive apoptosis in NRAS-mutant melanoma cells with wild-type or mutant p53. Hence, our data identify MITF/Bcl-2 as a key mechanism underlying resistance of NRAS-mutant melanoma cells to apoptosis by MEK inhibitors and paves the way for a promising drug combination that could prevent or reverse anti-MEK resistance in this group of patients. Copyright © 2017 Elsevier Ltd. All rights reserved.

  9. Minority stress in people who identify as transgender: testing the minority stress model

    OpenAIRE

    Stennett, Sabrina

    2016-01-01

    Objectives: People who identify as transgender are reported to experience high levels of mental health problems in comparison to people who do not identify as transgender. The minority stress model has been used to explain these high prevalence rates. But this model was designed to be used in lesbian, gay and bisexual (LGB) populations (Meyer, 1995, 2003). Researchers have applied some of the hypothesised processes of the model to people who identify as transgender. However, evidence testing ...

  10. 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...

  11. 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

  12. A parsimonious, integrative model of key psychological correlates of UK university students' alcohol consumption.

    Science.gov (United States)

    Atwell, Katie; Abraham, Charles; Duka, Theodora

    2011-01-01

    To examine the predictive utility of psychological correlates of alcohol consumption identified in previous (US-dominated) research for a UK student sample and construct an integrative model predictive of alcohol dependency in a sample of first-year undergraduate students. A self-report questionnaire completed by 230 students measured stable and modifiable correlates of alcohol dependence. Stable correlates included age when first regularly drinking (age of onset), personality traits and religiosity. Modifiable measures included drinking motives, self-efficacy, alcohol-related expectancies, prototype perceptions and normative beliefs. The final multivariate model highlighted the importance of age of onset, sensation-seeking and a series of social cognitive measures including: social drinking motives, confidence in the ability to drink within government guidelines (self-efficacy) and the perceived quantity and frequency of alcohol consumed by university friends. Beta-coefficients indicated that self-efficacy and social drinking motives were particularly important predictors. A significant interaction was observed between age of onset and self-efficacy. Earlier onset was associated with higher levels of alcohol dependence for low and moderate, but not high levels of self-efficacy. The model presented here could be used to identify students at risk of alcohol dependence and inform the design of campus-based interventions.

  13. 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

  14. 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.

  15. Understanding the distribution of marine megafauna in the English channel region: identifying key habitats for conservation within the busiest seaway on earth.

    Science.gov (United States)

    McClellan, Catherine M; Brereton, Tom; Dell'Amico, Florence; Johns, David G; Cucknell, Anna-C; Patrick, Samantha C; Penrose, Rod; Ridoux, Vincent; Solandt, Jean-Luc; Stephan, Eric; Votier, Stephen C; Williams, Ruth; Godley, Brendan J

    2014-01-01

    The temperate waters of the North-Eastern Atlantic have a long history of maritime resource richness and, as a result, the European Union is endeavouring to maintain regional productivity and biodiversity. At the intersection of these aims lies potential conflict, signalling the need for integrated, cross-border management approaches. This paper focuses on the marine megafauna of the region. This guild of consumers was formerly abundant, but is now depleted and protected under various national and international legislative structures. We present a meta-analysis of available megafauna datasets using presence-only distribution models to characterise suitable habitat and identify spatially-important regions within the English Channel and southern bight of the North Sea. The integration of studies from dedicated and opportunistic observer programmes in the United Kingdom and France provide a valuable perspective on the spatial and seasonal distribution of various taxonomic groups, including large pelagic fishes and sharks, marine mammals, seabirds and marine turtles. The Western English Channel emerged as a hotspot of biodiversity for megafauna, while species richness was low in the Eastern English Channel. Spatial conservation planning is complicated by the highly mobile nature of marine megafauna, however they are important components of the marine environment and understanding their distribution is a first crucial step toward their inclusion into marine ecosystem management.

  16. Using analytic hierarchy process to identify the nurses with high stress-coping capability: model and application.

    Science.gov (United States)

    F C Pan, Frank

    2014-03-01

    Nurses have long been relied as the major labor force in hospitals. Featured with complicated and highly labor-intensive job requirement, multiple pressures from different sources was inevitable. Success in identifying stresses and accordingly coping with such stresses is important for job performance of nurses, and service quality of a hospital. Purpose of this research is to identify the determinants of nurses' capabilities. A modified Analytic Hierarchy Process (AHP) was adopted. Overall, 105 nurses from several randomly selected hospitals in southern Taiwan were investigated to generate factors. Ten experienced practitioners were included as the expert in the AHP to produce weights of each criterion. Six nurses from two regional hospitals were then selected to test the model. Four factors are then identified as the second level of hierarchy. The study result shows that the family factor is the most important factor, and followed by the personal attributes. Top three sub-criteria that attribute to the nurse's stress-coping capability are children's education, good career plan, and healthy family. The practical simulation provided evidence for the usefulness of this model. The study suggested including these key determinants into the practice of human-resource management, and restructuring the hospital's organization, creating an employee-support system as well as a family-friendly working climate. The research provided evidence that supports the usefulness of AHP in identifying the key factors that help stabilizing a nursing team.

  17. 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

  18. 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

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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

  6. 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

  7. A simplified method to assess structurally identifiable parameters in Monod-based activated sludge models.

    Science.gov (United States)

    Petersen, Britta; Gernaey, Krist; Devisscher, Martijn; Dochain, Denis; Vanrolleghem, Peter A

    2003-07-01

    The first step in the estimation of parameters of models applied for data interpretation should always be an investigation of the identifiability of the model parameters. In this study the structural identifiability of the model parameters of Monod-based activated sludge models (ASM) was studied. In an illustrative example it was assumed that respirometric (dissolved oxygen or oxygen uptake rates) and titrimetric (cumulative proton production) measurements were available for the characterisation of nitrification. Two model structures, including the presence and absence of significant growth for description of long- and short-term experiments, respectively, were considered. The structural identifiability was studied via the series expansion methods. It was proven that the autotrophic yield becomes uniquely identifiable when combined respirometric and titrimetric data are assumed for the characterisation of nitrification. The most remarkable result of the study was, however, that the identifiability results could be generalised by applying a set of ASM1 matrix based generalisation rules. It appeared that the identifiable parameter combinations could be predicted directly based on the knowledge of the process model under study (in ASM1-like matrix representation), the measured variables and the biodegradable substrate considered. This generalisation reduces the time-consuming task of deriving the structurally identifiable model parameters significantly and helps the user to obtain these directly without the necessity to go too deeply into the mathematical background of structural identifiability.

  8. 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

  9. 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

  10. Identifying targets for topical RNAi therapeutics in psoriasis: assessment of a new in vitro psoriasis model

    NARCIS (Netherlands)

    Bracke, S.; Desmet, E.; Guerrero-Aspizua, S.; Tjabringa, S.; Schalkwijk, J.; Gele, M. Van; Carretero, M.; Lambert, J.

    2013-01-01

    Diseases of the skin are amenable to RNAi-based therapies and targeting key components in the pathophysiology of psoriasis using RNAi may represent a successful new therapeutic strategy. We aimed to develop a straightforward and highly reproducible in vitro psoriasis model useful to study the

  11. 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

  12. 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.

  13. 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.

  14. 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'…

  15. Identifiability of the Sign of Covariate Effects in the Competing Risks Model

    DEFF Research Database (Denmark)

    Lo, Simon M.S.; Wilke, Ralf

    2017-01-01

    We present a new framework for the identification of competing risks models, which also include Roy models. We show that by establishing a Hicksian-type decomposition, the direction of covariate effects on the marginal distributions of the competing risks model can be identified under weak restri...

  16. 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.

  17. iNID: an analytical framework for identifying network models for interplays among developmental signaling in Arabidopsis.

    Science.gov (United States)

    Choi, Daeseok; Choi, Jaemyung; Kang, Byeongsoo; Lee, Seungchul; Cho, Young-hyun; Hwang, Ildoo; Hwang, Daehee

    2014-05-01

    Integration of internal and external cues into developmental programs is indispensable for growth and development of plants, which involve complex interplays among signaling pathways activated by the internal and external factors (IEFs). However, decoding these complex interplays is still challenging. Here, we present a web-based platform that identifies key regulators and Network models delineating Interplays among Developmental signaling (iNID) in Arabidopsis. iNID provides a comprehensive resource of (1) transcriptomes previously collected under the conditions treated with a broad spectrum of IEFs and (2) protein and genetic interactome data in Arabidopsis. In addition, iNID provides an array of tools for identifying key regulators and network models related to interplays among IEFs using transcriptome and interactome data. To demonstrate the utility of iNID, we investigated the interplays of (1) phytohormones and light and (2) phytohormones and biotic stresses. The results revealed 34 potential regulators of the interplays, some of which have not been reported in association with the interplays, and also network models that delineate the involvement of the 34 regulators in the interplays, providing novel insights into the interplays collectively defined by phytohormones, light, and biotic stresses. We then experimentally verified that BME3 and TEM1, among the selected regulators, are involved in the auxin-brassinosteroid (BR)-blue light interplay. Therefore, iNID serves as a useful tool to provide a basis for understanding interplays among IEFs.

  18. 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

  19. 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...

  20. Perception testing: a key component in modeling and simulation at NVESD

    Science.gov (United States)

    Maurer, Tana; Nguyen, Oanh; Thomas, Jim; Boettcher, Evelyn

    2009-05-01

    The U.S. Army's Night Vision and Electronic Sensors Directorate (NVESD) Modeling and Simulation Division is responsible for developing and enhancing electro-optic/infrared sensor performance models that are used in wargames and for sensor trade studies. Predicting how well a sensor performs a military task depends on both the physics of the sensor and how well observers perform specific tasks while using that sensor. An example of such a task could be to search and detect targets of military interest. Another task could be to identify a target as a threat or non-threat. A typical sensor development program involves analyses and trade-offs among a number of variables such as field of view, resolution, range, compression techniques, etc. Observer performance results, obtained in the NVESD perception lab, provide essential information to bridge the gap between the physics of a system and the humans using that system. This information is then used to develop and validate models, to conduct design trade-off studies and to generate insights into the development of new systems for soldiers in surveillance, urban combat, and all types of military activities. Computer scientists and engineers in the perception lab design tests and process both real and simulated imagery in order to isolate the effect or design being studied. Then, in accordance with an approved protocol for human subjects research, experiments are administered to the desired number of observers. Results are tabulated and analyzed. The primary focus of this paper is to describe current capabilities of the NVESD perception lab regarding computer-based observer performance testing of sensor imagery, what types of experiments have been completed and plans for the future.

  1. The bearing capacity experimental determination of the keyed joints models in the transport construction

    Directory of Open Access Journals (Sweden)

    Dovzhenko Oksana

    2017-01-01

    Full Text Available The joints ensure the joint performance of the load carrying structural systems and they are the most responsible and important elements. Keyed joints are widely used in construction. They are characterized by an increased resistance to shear. On these grounds the structural concepts of keyed joints need further improvement. The article presents the research results of experimental test pieces five series in the form of single keys and one-keyed joints. Those samples have been tested in Poltava National Technical Yuriy Kondratyuk University. Follow strength factors have been varied: geometric parameters of joints (depth, height, width and their ratio; angle of support surface (rectangular, trapezoidal and triangular key; level of compression; reinforcement (quality of reinforcement and the nature of its location; jointing width. The samples were made of heavy-weight, expanded clay and fibre concrete. The experiments program includes influence study both of one of these factors and their combinations. The deformations, nature of failure, the ultimate load have been studied. Structural parameters of keyed joints which ensure the efficient behaviour have been installed.

  2. Ogyges Kaup, a flightless genus of Passalidae (Coleoptera) from Mesoamerica: nine new species, a key to identify species, and a novel character to support its monophyly.

    Science.gov (United States)

    Cano, Enio B

    2014-12-02

    Nine new species of Ogyges Kaup (Coleoptera: Passalidae) from the mountainous cloud forests of Mesoamerica are described: O. handali new species and O. menchuae new species from Guatemala; O. cavei new species, O. laurae new species, O. llama new species, O. mutenroshii new species, O. ratcliffei new species, and O. toriyamai new species from Honduras; and O. sandinoi new species from Nicaragua, the first objective record of the genus for this country. A key to the adult Ogyges is included. The work also shows that Ogyges possesses an exclusive autapomorphy: a trituberculate suprainternal tooth of each mandible (one long and wide apical tubercle and two connected, small, almost conical, basal tubercles). This character state is found in all known Ogyges species and is proposed as a synapomorphy that supports the monophyly of the genus.

  3. 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.

  4. A parameter estimation and identifiability analysis methodology applied to a street canyon air pollution model

    DEFF Research Database (Denmark)

    Ottosen, T. B.; Ketzel, Matthias; Skov, H.

    2016-01-01

    Mathematical models are increasingly used in environmental science thus increasing the importance of uncertainty and sensitivity analyses. In the present study, an iterative parameter estimation and identifiability analysis methodology is applied to an atmospheric model – the Operational Street...... of the identifiability analysis, showed that some model parameters were significantly more sensitive than others. The application of the determined optimal parameter values was shown to successfully equilibrate the model biases among the individual streets and species. It was as well shown that the frequentist approach...

  5. 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 ...

  6. 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…

  7. Using Model-Eliciting Activities as a Tool to Identify and Develop Mathematically Creative Students

    Science.gov (United States)

    Coxbill, Emmy; Chamberlin, Scott A.; Weatherford, Jennifer

    2013-01-01

    Traditional classroom methods for identifying mathematically creative students have been inadequate. Identifying students who could potentially be mathematically creative is instrumental in the development of students and in meeting their affective and educational needs. One prospective identification tool is the use of model-eliciting activities…

  8. 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...

  9. Identifiability of parameters and behaviour of MCMC chains: a case study using the reaction norm model.

    Science.gov (United States)

    Shariati, M M; Korsgaard, I R; Sorensen, D

    2009-04-01

    Markov chain Monte Carlo (MCMC) enables fitting complex hierarchical models that may adequately reflect the process of data generation. Some of these models may contain more parameters than can be uniquely inferred from the distribution of the data, causing non-identifiability. The reaction norm model with unknown covariates (RNUC) is a model in which unknown environmental effects can be inferred jointly with the remaining parameters. The problem of identifiability of parameters at the level of the likelihood and the associated behaviour of MCMC chains were discussed using the RNUC as an example. It was shown theoretically that when environmental effects (covariates) are considered as random effects, estimable functions of the fixed effects, (co)variance components and genetic effects are identifiable as well as the environmental effects. When the environmental effects are treated as fixed and there are other fixed factors in the model, the contrasts involving environmental effects, the variance of environmental sensitivities (genetic slopes) and the residual variance are the only identifiable parameters. These different identifiability scenarios were generated by changing the formulation of the model and the structure of the data and the models were then implemented via MCMC. The output of MCMC sampling schemes was interpreted in the light of the theoretical findings. The erratic behaviour of the MCMC chains was shown to be associated with identifiability problems in the likelihood, despite propriety of posterior distributions, achieved by arbitrarily chosen uniform (bounded) priors. In some cases, very long chains were needed before the pattern of behaviour of the chain may signal the existence of problems. The paper serves as a warning concerning the implementation of complex models where identifiability problems can be difficult to detect a priori. We conclude that it would be good practice to experiment with a proposed model and to understand its features

  10. Identifiability of models for time-resolved fluorescence with underlying distributions of rate constants.

    Science.gov (United States)

    Boens, Noël; Van der Auweraer, Mark

    2014-02-01

    The deterministic identifiability analysis of photophysical models for the kinetics of excited-state processes, assuming errorless time-resolved fluorescence data, can verify whether the model parameters can be determined unambiguously. In this work, we have investigated the identifiability of several uncommon models for time-resolved fluorescence with underlying distributions of rate constants which lead to non-exponential decays. The mathematical functions used here for the description of non-exponential fluorescence decays are the stretched exponential or Kohlrausch function, the Becquerel function, the Förster type energy transfer function, decay functions associated with exponential, Gaussian and uniform distributions of rate constants, a decay function with extreme sub-exponential behavior, the Mittag-Leffler function and Heaviside's function. It is shown that all the models are uniquely identifiable, which means that for each specific model there exists a single parameter set that describes its associated fluorescence δ-response function.

  11. 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....

  12. 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.

  13. Label-free quantitative proteomic profiling identifies disruption of ubiquitin homeostasis as a key driver of Schwann cell defects in spinal muscular atrophy.

    Science.gov (United States)

    Aghamaleky Sarvestany, Arwin; Hunter, Gillian; Tavendale, Amy; Lamont, Douglas J; Llavero Hurtado, Maica; Graham, Laura C; Wishart, Thomas M; Gillingwater, Thomas H

    2014-11-07

    Low levels of survival of motor neuron (SMN) protein cause the neuromuscular disease spinal muscular atrophy (SMA), characterized by degeneration of lower motor neurons and atrophy of skeletal muscle. Recent work demonstrated that low levels of SMN also trigger pathological changes in Schwann cells, leading to abnormal axon myelination and disrupted deposition of extracellular matrix proteins in peripheral nerve. However, the molecular pathways linking SMN depletion to intrinsic defects in Schwann cells remained unclear. Label-free proteomics analysis of Schwann cells isolated from SMA mouse peripheral nerve revealed widespread changes to the Schwann cell proteome, including disruption to growth/proliferation, cell death/survival, and molecular transport pathways. Functional clustering analyses revealed significant disruption to a number of proteins contributing to ubiquitination pathways, including reduced levels of ubiquitin-like modifier activating enzyme 1 (Uba1). Pharmacological suppression of Uba1 in Schwann cells was sufficient to reproduce the defective myelination phenotype seen in SMA. These findings demonstrate an important role for SMN protein and ubiquitin-dependent pathways in maintaining Schwann cell homeostasis and provide significant additional experimental evidence supporting a key role for ubiquitin pathways and, Uba1 in particular, in driving SMA pathogenesis across a broad range of cells and tissues.

  14. Key characteristics of successful science learning: the promise of learning by modelling

    NARCIS (Netherlands)

    Mulder, Y.G.; Lazonder, Adrianus W.; de Jong, Anthonius J.M.

    2015-01-01

    The basic premise underlying this research is that scientific phenomena are best learned by creating an external representation that complies with the complex and dynamic nature of such phenomena. Effective representations are assumed to incorporate three key characteristics: they are graphical,

  15. 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…

  16. 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…

  17. 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.

  18. 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)

  19. Combined Chlorophyll Fluorescence and Transcriptomic Analysis Identifies the P3/P4 Transition as a Key Stage in Rice Leaf Photosynthetic Development.

    Science.gov (United States)

    van Campen, Julia C; Yaapar, Muhammad N; Narawatthana, Supatthra; Lehmeier, Christoph; Wanchana, Samart; Thakur, Vivek; Chater, Caspar; Kelly, Steve; Rolfe, Stephen A; Quick, W Paul; Fleming, Andrew J

    2016-03-01

    Leaves are derived from heterotrophic meristem tissue that, at some point, must make the transition to autotrophy via the initiation of photosynthesis. However, the timing and spatial coordination of the molecular and cellular processes underpinning this switch are poorly characterized. Here, we report on the identification of a specific stage in rice (Oryza sativa) leaf development (P3/P4 transition) when photosynthetic competence is first established. Using a combined physiological and molecular approach, we show that elements of stomatal and vascular differentiation are coordinated with the onset of measurable light absorption for photosynthesis. Moreover, by exploring the response of the system to environmental perturbation, we show that the earliest stages of rice leaf development have significant plasticity with respect to elements of cellular differentiation of relevance for mature leaf photosynthetic performance. Finally, by performing an RNA sequencing analysis targeted at the early stages of rice leaf development, we uncover a palette of genes whose expression likely underpins the acquisition of photosynthetic capability. Our results identify the P3/P4 transition as a highly dynamic stage in rice leaf development when several processes for the initiation of photosynthetic competence are coordinated. As well as identifying gene targets for future manipulation of rice leaf structure/function, our data highlight a developmental window during which such manipulations are likely to be most effective. © 2016 American Society of Plant Biologists. All Rights Reserved.

  20. An image-based RNAi screen identifies SH3BP1 as a key effector of Semaphorin 3E–PlexinD1 signaling

    Science.gov (United States)

    Tata, Aleksandra; Stoppel, David C.; Hong, Shangyu; Ben-Zvi, Ayal; Xie, Tiao

    2014-01-01

    Extracellular signals have to be precisely interpreted intracellularly and translated into diverse cellular behaviors often mediated by cytoskeletal changes. Semaphorins are one of the largest families of guidance cues and play a critical role in many systems. However, how different cell types translate extracellular semaphorin binding into intracellular signaling remains unclear. Here we developed and performed a novel image-based genome-wide functional RNAi screen for downstream signaling molecules that convert the interaction between Semaphorin 3E (Sema3E) and PlexinD1 into cellular behaviors. One of the genes identified in this screen is a RhoGAP protein, SH3-domain binding protein 1 (SH3BP1). We demonstrate that SH3BP1 mediates Sema3E-induced cell collapse through interaction with PlexinD1 and regulation of Ras-related C3 botulinum toxin substrate 1 (Rac1) activity. The identification and characterization of SH3BP1 as a novel downstream effector of Sema3E-PlexinD1 provides an explanation for how extracellular signals are translated into cytoskeletal changes and unique cell behavior, but also lays the foundation for characterizing other genes identified from our screen to obtain a more complete picture of plexin signaling. PMID:24841563

  1. An image-based RNAi screen identifies SH3BP1 as a key effector of Semaphorin 3E-PlexinD1 signaling.

    Science.gov (United States)

    Tata, Aleksandra; Stoppel, David C; Hong, Shangyu; Ben-Zvi, Ayal; Xie, Tiao; Gu, Chenghua

    2014-05-26

    Extracellular signals have to be precisely interpreted intracellularly and translated into diverse cellular behaviors often mediated by cytoskeletal changes. Semaphorins are one of the largest families of guidance cues and play a critical role in many systems. However, how different cell types translate extracellular semaphorin binding into intracellular signaling remains unclear. Here we developed and performed a novel image-based genome-wide functional RNAi screen for downstream signaling molecules that convert the interaction between Semaphorin 3E (Sema3E) and PlexinD1 into cellular behaviors. One of the genes identified in this screen is a RhoGAP protein, SH3-domain binding protein 1 (SH3BP1). We demonstrate that SH3BP1 mediates Sema3E-induced cell collapse through interaction with PlexinD1 and regulation of Ras-related C3 botulinum toxin substrate 1 (Rac1) activity. The identification and characterization of SH3BP1 as a novel downstream effector of Sema3E-PlexinD1 provides an explanation for how extracellular signals are translated into cytoskeletal changes and unique cell behavior, but also lays the foundation for characterizing other genes identified from our screen to obtain a more complete picture of plexin signaling. © 2014 Tata et al.

  2. 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.

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

    Science.gov (United States)

    2016-04-01

    parameters in a cohort of ovarian tumor specimens from women diagnosed with stage III, grade 3, papillary serous adenocarcinoma all treated with...sensitize chemoresistant ovarian tumors to platinum treatment and inhibit ovarian cancer dissemination in a pre-clinical ovarian cancer mouse model. Our...chemoresistant cancer cells can sensitize chemoresistant ovarian tumors to cisplatin treatment and inhibit ovarian cancer dissemination in a pre

  4. Use of comparative proteomics to identify key proteins related to hepatic lipid metabolism in broiler chickens: evidence accounting for differential fat deposition between strains.

    Science.gov (United States)

    Huang, Jianzhen; Tang, Xue; Ruan, Jiming; Ma, Haitian; Zou, Sixiang

    2010-01-01

    In order to investigate differences in fat metabolism during embryonic development, a comparative proteomics strategy was employed using Arbor Acres (AA) and San Huang (SH) broiler chickens with different growth and fat deposition characteristics. These birds were floor-reared and fed identical diets, and embryonic livers were collected from AA and SH chicken embryos on days 9, 14 and 19 of incubation and hatching. Proteins were extracted and fractionated by two-dimensional electrophoresis (2-DE), Neuhoff's colloidal Coomassie Blue G-250 staining was carried out, and stained gels were scanned and analyzed using PDQuest7.3 software (Bio-Rad). In-gel trypsin digestion of the differential protein spots and matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF-MS) were subsequently assessed. Peptide mass fingerprinting of the differentially expressed proteins was performed using the server from MASCOT or either Prospector or ProFound, and 37 proteins were successfully identified. In the present study, embryo and liver weights showed a trend toward enhanced growth during embryonic development. Of the 37 identified differential proteins, phosphoenolpyruvate carboxykinase (PEPCK), apolipoprotein A-I (Apo A-I), fatty acid-binding protein (L-FABP) and 3-hydroxy-3-methylglutaryl-Coenzyme A synthase (HMG-CoA synthase) were up-regulated in SH chickens to a greater extent than they were in AA chickens. These observations suggest that the lipid metabolic proteins and enzymes are inherent characteristics that contribute to the apparent differences in fat deposition between the two strains.

  5. 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.

  6. A three-dimensional human model of the fibroblast activation that accompanies bronchopulmonary dysplasia identifies Notch-mediated pathophysiology.

    Science.gov (United States)

    Sucre, Jennifer M S; Wilkinson, Dan; Vijayaraj, Preethi; Paul, Manash; Dunn, Bruce; Alva-Ornelas, Jackelyn A; Gomperts, Brigitte N

    2016-05-15

    Bronchopulmonary dysplasia (BPD) is a leading complication of premature birth and occurs primarily in infants delivered during the saccular stage of lung development. Histopathology shows decreased alveolarization and a pattern of fibroblast proliferation and differentiation to the myofibroblast phenotype. Little is known about the molecular pathways and cellular mechanisms that define BPD pathophysiology and progression. We have developed a novel three-dimensional human model of the fibroblast activation associated with BPD, and using this model we have identified the Notch pathway as a key driver of fibroblast activation and proliferation in response to changes in oxygen. Fetal lung fibroblasts were cultured on sodium alginate beads to generate lung organoids. After exposure to alternating hypoxia and hyperoxia, the organoids developed a phenotypic response characterized by increased α-smooth muscle actin (α-SMA) expression and other genes known to be upregulated in BPD and also demonstrated increased expression of downstream effectors of the Notch pathway. Inhibition of Notch with a γ-secretase inhibitor prevented the development of the pattern of cellular proliferation and α-SMA expression in our model. Analysis of human autopsy tissue from the lungs of infants who expired with BPD demonstrated evidence of Notch activation within fibrotic areas of the alveolar septae, suggesting that Notch may be a key driver of BPD pathophysiology. Copyright © 2016 the American Physiological Society.

  7. Integrated Modeling & Development of Emission Scenarios for Methane and Key Indirect Greenhouse Gases

    Energy Technology Data Exchange (ETDEWEB)

    Jain, Atul K.

    2005-09-30

    This report outlines main accomplishments on the development of Emission inventories and Scenarios for Key Indirect Greenhouse Gases (CO, VOCs, NOx) and methane supported by Office of Science (BER), US Department of Energy. This research produced 3 journal articles, 1 book chapter, and 4 research articles/abstracts in conference proceedings. In addition, this grant supported two PhD students and one undergraduate student at UIUC.

  8. Key Practices of the Capability Maturity Model, Version 1.1

    Science.gov (United States)

    1993-02-01

    siftware work products are identified, controlled, and available. 3. CChaitges to identified software work products are controlled. 4. Affected groups...project manager L2-26 oversight of software process senior management L2-26 improvement L5-32 siftware quality assurance L2-27 sponsorship of

  9. 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...

  10. 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.

  11. 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...

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. Mind the Noise When Identifying Computational Models of Cognition from Brain Activity.

    Science.gov (United States)

    Kolossa, Antonio; Kopp, Bruno

    2016-01-01

    The aim of this study was to analyze how measurement error affects the validity of modeling studies in computational neuroscience. A synthetic validity test was created using simulated P300 event-related potentials as an example. The model space comprised four computational models of single-trial P300 amplitude fluctuations which differed in terms of complexity and dependency. The single-trial fluctuation of simulated P300 amplitudes was computed on the basis of one of the models, at various levels of measurement error and at various numbers of data points. Bayesian model selection was performed based on exceedance probabilities. At very low numbers of data points, the least complex model generally outperformed the data-generating model. Invalid model identification also occurred at low levels of data quality and under low numbers of data points if the winning model's predictors were closely correlated with the predictors from the data-generating model. Given sufficient data quality and numbers of data points, the data-generating model could be correctly identified, even against models which were very similar to the data-generating model. Thus, a number of variables affects the validity of computational modeling studies, and data quality and numbers of data points are among the main factors relevant to the issue. Further, the nature of the model space (i.e., model complexity, model dependency) should not be neglected. This study provided quantitative results which show the importance of ensuring the validity of computational modeling via adequately prepared studies. The accomplishment of synthetic validity tests is recommended for future applications. Beyond that, we propose to render the demonstration of sufficient validity via adequate simulations mandatory to computational modeling studies.

  17. Global metabolic profile identifies choline kinase alpha as a key regulator of glutathione-dependent antioxidant cell defense in ovarian carcinoma.

    Science.gov (United States)

    Granata, Anna; Nicoletti, Roberta; Perego, Paola; Iorio, Egidio; Krishnamachary, Balaji; Benigni, Fabio; Ricci, Alessandro; Podo, Franca; Bhujwalla, Zaver M; Canevari, Silvana; Bagnoli, Marina; Mezzanzanica, Delia

    2015-05-10

    Epithelial Ovarian Cancer (EOC) "cholinic phenotype", characterized by increased intracellular phosphocholine content sustained by over-expression/activity of choline kinase-alpha (ChoKα/CHKA), is a metabolic cellular reprogramming involved in chemoresistance with still unknown mechanisms.By stable CHKA silencing and global metabolic profiling here we demonstrate that CHKA knockdown hampers growth capability of EOC cell lines both in vitro and in xenotransplant in vivo models. It also affected antioxidant cellular defenses, decreasing glutathione and cysteine content while increasing intracellular levels of reactive oxygen species, overall sensitizing EOC cells to current chemotherapeutic regimens. Natural recovering of ChoKα expression after its transient silencing rescued the wild-type phenotype, restoring intracellular glutathione content and drug resistance. Rescue and phenocopy of siCHKA-related effects were also obtained by artificial modulation of glutathione levels. The direct relationship among CHKA expression, glutathione intracellular content and drug sensitivity was overall demonstrated in six different EOC cell lines but notably, siCHKA did not affect growth capability, glutathione metabolism and/or drug sensitivity of non-tumoral immortalized ovarian cells. The "cholinic phenotype", by recapitulating EOC addiction to glutathione content for the maintenance of the antioxidant defense, can be therefore considered a unique feature of cancer cells and a suitable target to improve chemotherapeutics efficacy.

  18. Identifying key climate and environmental factors affecting rates of post-fire big sagebrush (Artemisia tridentata) recovery in the northern Columbia Basin, USA

    Science.gov (United States)

    Shinneman, Douglas; McIlroy, Susan

    2016-01-01

    Sagebrush steppe of North America is considered highly imperilled, in part owing to increased fire frequency. Sagebrush ecosystems support numerous species, and it is important to understand those factors that affect rates of post-fire sagebrush recovery. We explored recovery of Wyoming big sagebrush (Artemisia tridentata ssp.wyomingensis) and basin big sagebrush (A. tridentata ssp. tridentata) communities following fire in the northern Columbia Basin (Washington, USA). We sampled plots across 16 fires that burned in big sagebrush communities from 5 to 28 years ago, and also sampled nearby unburned locations. Mixed-effects models demonstrated that density of large–mature big sagebrush plants and percentage cover of big sagebrush were higher with time since fire and in plots with more precipitation during the winter immediately following fire, but were lower when precipitation the next winter was higher than average, especially on soils with higher available water supply, and with greater post-fire mortality of mature big sagebrush plants. Bunchgrass cover 5 to 28 years after fire was predicted to be lower with higher cover of both shrubs and non-native herbaceous species, and only slightly higher with time. Post-fire recovery of big sagebrush in the northern Columbia Basin is a slow process that may require several decades on average, but faster recovery rates may occur under specific site and climate conditions.

  19. 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.

  20. Clustering reveals limits of parameter identifiability in multi-parameter models of biochemical dynamics.

    Science.gov (United States)

    Nienałtowski, Karol; Włodarczyk, Michał; Lipniacki, Tomasz; Komorowski, Michał

    2015-09-29

    Compared to engineering or physics problems, dynamical models in quantitative biology typically depend on a relatively large number of parameters. Progress in developing mathematics to manipulate such multi-parameter models and so enable their efficient interplay with experiments has been slow. Existing solutions are significantly limited by model size. In order to simplify analysis of multi-parameter models a method for clustering of model parameters is proposed. It is based on a derived statistically meaningful measure of similarity between groups of parameters. The measure quantifies to what extend changes in values of some parameters can be compensated by changes in values of other parameters. The proposed methodology provides a natural mathematical language to precisely communicate and visualise effects resulting from compensatory changes in values of parameters. As a results, a relevant insight into identifiability analysis and experimental planning can be obtained. Analysis of NF-κB and MAPK pathway models shows that highly compensative parameters constitute clusters consistent with the network topology. The method applied to examine an exceptionally rich set of published experiments on the NF-κB dynamics reveals that the experiments jointly ensure identifiability of only 60% of model parameters. The method indicates which further experiments should be performed in order to increase the number of identifiable parameters. We currently lack methods that simplify broadly understood analysis of multi-parameter models. The introduced tools depict mutually compensative effects between parameters to provide insight regarding role of individual parameters, identifiability and experimental design. The method can also find applications in related methodological areas of model simplification and parameters estimation.

  1. 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.

  2. A biophysical model for identifying splicing regulatory elements and their interactions.

    Directory of Open Access Journals (Sweden)

    Ji Wen

    Full Text Available Alternative splicing (AS of precursor mRNA (pre-mRNA is a crucial step in the expression of most eukaryotic genes. Splicing factors (SFs play an important role in AS regulation by binding to the cis-regulatory elements on the pre-mRNA. Although many splicing factors (SFs and their binding sites have been identified, their combinatorial regulatory effects remain to be elucidated. In this paper, we derive a biophysical model for AS regulation that integrates combinatorial signals of cis-acting splicing regulatory elements (SREs and their interactions. We also develop a systematic framework for model inference. Applying the biophysical model to a human RNA-Seq data set, we demonstrate that our model can explain 49.1%-66.5% variance of the data, which is comparable to the best result achieved by biophysical models for transcription. In total, we identified 119 SRE pairs between different regions of cassette exons that may regulate exon or intron definition in splicing, and 77 SRE pairs from the same region that may arise from a long motif or two different SREs bound by different SFs. Particularly, putative binding sites of polypyrimidine tract-binding protein (PTB, heterogeneous nuclear ribonucleoprotein (hnRNP F/H and E/K are identified as interacting SRE pairs, and have been shown to be consistent with the interaction models proposed in previous experimental results. These results show that our biophysical model and inference method provide a means of quantitative modeling of splicing regulation and is a useful tool for identifying SREs and their interactions. The software package for model inference is available under an open source license.

  3. Identifying the molecular basis of host-parasite coevolution: merging models and mechanisms.

    Science.gov (United States)

    Dybdahl, Mark F; Jenkins, Christina E; Nuismer, Scott L

    2014-07-01

    Mathematical models of the coevolutionary process have uncovered consequences of host-parasite interactions that go well beyond the traditional realm of the Red Queen, potentially explaining several important evolutionary transitions. However, these models also demonstrate that the specific consequences of coevolution are sensitive to the structure of the infection matrix, which is embedded in models to describe the likelihood of infection in encounters between specific host and parasite genotypes. Traditional cross-infection approaches to estimating infection matrices might be unreliable because evolutionary dynamics and experimental sampling lead to missing genotypes. Consequently, our goal is to identify the likely structure of infection matrices by synthesizing molecular mechanisms of host immune defense and parasite counterdefense with coevolutionary models. This synthesis reveals that the molecular mechanisms of immune reactions, although complex and diverse, conform to two basic models commonly used within coevolutionary theory: matching infection and targeted recognition. Our synthesis also overturns conventional wisdom, revealing that the general models are not taxonomically restricted but are applicable to plants, invertebrates, and vertebrates. Finally, our synthesis identifies several important areas for future research that should improve the explanatory power of coevolutionary models. The most important among these include empirical studies to identify the molecular hotspots of genotypic specificity and theoretical studies examining the consequences of matrices that more accurately represent multistep infection processes and quantitative defenses.

  4. 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.

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

    Directory of Open Access Journals (Sweden)

    Z. Wang

    2018-02-01

    Full Text Available 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.

  6. 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.

  7. 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)...

  8. An assessment of key model parametric uncertainties in projections of Greenland Ice Sheet behavior

    Directory of Open Access Journals (Sweden)

    P. J. Applegate

    2012-05-01

    Full Text Available Lack of knowledge about the values of ice sheet model input parameters introduces substantial uncertainty into projections of Greenland Ice Sheet contributions to future sea level rise. Computer models of ice sheet behavior provide one of several means of estimating future sea level rise due to mass loss from ice sheets. Such models have many input parameters whose values are not well known. Recent studies have investigated the effects of these parameters on model output, but the range of potential future sea level increases due to model parametric uncertainty has not been characterized. Here, we demonstrate that this range is large, using a 100-member perturbed-physics ensemble with the SICOPOLIS ice sheet model. Each model run is spun up over 125 000 yr using geological forcings and subsequently driven into the future using an asymptotically increasing air temperature anomaly curve. All modeled ice sheets lose mass after 2005 AD. Parameters controlling surface melt dominate the model response to temperature change. After culling the ensemble to include only members that give reasonable ice volumes in 2005 AD, the range of projected sea level rise values in 2100 AD is ~40 % or more of the median. Data on past ice sheet behavior can help reduce this uncertainty, but none of our ensemble members produces a reasonable ice volume change during the mid-Holocene, relative to the present. This problem suggests that the model's exponential relation between temperature and precipitation does not hold during the Holocene, or that the central-Greenland temperature forcing curve used to drive the model is not representative of conditions around the ice margin at this time (among other possibilities. Our simulations also lack certain observed physical processes that may tend to enhance the real ice sheet's response. Regardless, this work has implications for other studies that use ice sheet models to project or hindcast the behavior of the Greenland Ice

  9. An iterative genetic and dynamical modelling approach identifies novel features of the gene regulatory network underlying melanocyte development.

    Science.gov (United States)

    Greenhill, Emma R; Rocco, Andrea; Vibert, Laura; Nikaido, Masataka; Kelsh, Robert N

    2011-09-01

    The mechanisms generating stably differentiated cell-types from multipotent precursors are key to understanding normal development and have implications for treatment of cancer and the therapeutic use of stem cells. Pigment cells are a major derivative of neural crest stem cells and a key model cell-type for our understanding of the genetics of cell differentiation. Several factors driving melanocyte fate specification have been identified, including the transcription factor and master regulator of melanocyte development, Mitf, and Wnt signalling and the multipotency and fate specification factor, Sox10, which drive mitf expression. While these factors together drive multipotent neural crest cells to become specified melanoblasts, the mechanisms stabilising melanocyte differentiation remain unclear. Furthermore, there is controversy over whether Sox10 has an ongoing role in melanocyte differentiation. Here we use zebrafish to explore in vivo the gene regulatory network (GRN) underlying melanocyte specification and differentiation. We use an iterative process of mathematical modelling and experimental observation to explore methodically the core melanocyte GRN we have defined. We show that Sox10 is not required for ongoing differentiation and expression is downregulated in differentiating cells, in response to Mitfa and Hdac1. Unexpectedly, we find that Sox10 represses Mitf-dependent expression of melanocyte differentiation genes. Our systems biology approach allowed us to predict two novel features of the melanocyte GRN, which we then validate experimentally. Specifically, we show that maintenance of mitfa expression is Mitfa-dependent, and identify Sox9b as providing an Mitfa-independent input to melanocyte differentiation. Our data supports our previous suggestion that Sox10 only functions transiently in regulation of mitfa and cannot be responsible for long-term maintenance of mitfa expression; indeed, Sox10 is likely to slow melanocyte differentiation in the

  10. Reconstructing pedigrees: some identifiability questions for a recombination-mutation model.

    Science.gov (United States)

    Thatte, Bhalchandra D

    2013-01-01

    Pedigrees are directed acyclic graphs that represent ancestral relationships between individuals in a population. Based on a schematic recombination process, we describe two simple Markov models for sequences evolving on pedigrees--Model R (recombinations without mutations) and Model RM (recombinations with mutations). For these models, we ask an identifiability question: is it possible to construct a pedigree from the joint probability distribution of extant sequences? We present partial identifiability results for general pedigrees: we show that when the crossover probabilities are sufficiently small, certain spanning subgraph sequences can be counted from the joint distribution of extant sequences. We demonstrate how pedigrees that earlier seemed difficult to distinguish are distinguished by counting their spanning subgraph sequences.

  11. 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

  12. MODELKEY. Models for assessing and forecasting the impact of environmental key pollutants on freshwater and marine ecosystems and biodiversity.

    Science.gov (United States)

    Brack, Werner; Bakker, Joop; de Deckere, Eric; Deerenberg, Charlotte; van Gils, Jos; Hein, Michaela; Jurajda, Pavel; Kooijman, Bas; Lamoree, Marja; Lek, Sovan; López de Alda, Maria Jose; Marcomini, Antonio; Muñoz, Isabel; Rattei, Silke; Segner, Helmut; Thomas, Kevin; von der Ohe, Peter Carsten; Westrich, Bernhard; de Zwart, Dick; Schmitt-Jansen, Mechthild

    2005-09-01

    Triggered by the requirement of Water Framework Directive for a good ecological status for European river systems till 2015 and by still existing lacks in tools for cause identification of insufficient ecological status MODELKEY (http:// www.modelkey.org), an Integrated Project with 26 partners from 14 European countries, was started in 2005. MODELKEY is the acronym for 'Models for assessing and forecasting the impact of environmental key pollutants on freshwater and marine ecosystems and biodiversity'. The project is funded by the European Commission within the Sixth Framework Programme. MODELKEY comprises a multidisciplinary approach aiming at developing interlinked tools for an enhanced understanding of cause-effect-relationships between insufficient ecological status and environmental pollution as causative factor and for the assessment and forecasting of the risks of key pollutants on fresh water and marine ecosystems at a river basin and adjacent marine environment scale. New modelling tools for risk assessment including generic exposure assessment models, mechanistic models of toxic effects in simplified food chains, integrated diagnostic effect models based on community patterns, predictive component effect models applying artificial neural networks and GIS-based analysis of integrated risk indexes will be developed and linked to a user-friendly decision support system for the prioritisation of risks, contamination sources and contaminated sites. Modelling will be closely interlinked with extensive laboratory and field investigations. Early warning strategies on the basis of sub-lethal effects in vitro and in vivo are provided and combined with fractionation and analytical tools for effect-directed analysis of key toxicants. Integrated assessment of exposure and effects on biofilms, invertebrate and fish communities linking chemical analysis in water, sediment and biota with in vitro, in vivo and community level effect analysis is designed to provide data

  13. Maximum Likelihood Item Easiness Models for Test Theory without an Answer Key

    Science.gov (United States)

    France, Stephen L.; Batchelder, William H.

    2015-01-01

    Cultural consensus theory (CCT) is a data aggregation technique with many applications in the social and behavioral sciences. We describe the intuition and theory behind a set of CCT models for continuous type data using maximum likelihood inference methodology. We describe how bias parameters can be incorporated into these models. We introduce…

  14. models of hourly dry bulb temperature and relative humidity of key

    African Journals Online (AJOL)

    user

    use these models as inputs in computer programs for simulation of refrigerator, air conditioning systems and internal combustion engines operating anywhere in Nigeria. Keywords: Dry bulb temperature, Relative humidity, Air conditioning systems, Models, Fourier series. 1. INTRODUCTION. Nigeria is a tropical country in ...

  15. Adaptive Atmospheric Modeling Key Techniques in Grid Generation, Data Structures, and Numerical Operations with Applications

    CERN Document Server

    Behrens, Jörn

    2006-01-01

    Gives an overview and guidance in the development of adaptive techniques for atmospheric modeling. This book covers paradigms of adaptive techniques, such as error estimation and adaptation criteria. Considering applications, it demonstrates several techniques for discretizing relevant conservation laws from atmospheric modeling.

  16. Emporium Model: The Key to Content Retention in Secondary Math Courses

    Science.gov (United States)

    Wilder, Sandra; Berry, Lisa

    2016-01-01

    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…

  17. models of hourly dry bulb temperature and relative humidity of key ...

    African Journals Online (AJOL)

    user

    use these models as inputs in computer programs for simulation of refrigerator, air conditioning systems and internal combustion engines operating anywhere in Nigeria. Keywords: Dry bulb temperature, Relative humidity, Air conditioning systems, Models, Fourier series. 1. INTRODUCTION. Nigeria is a tropical country in ...

  18. Kidney disease models: tools to identify mechanisms and potential therapeutic targets

    Science.gov (United States)

    Bao, Yin-Wu; Yuan, Yuan; Chen, Jiang-Hua; Lin, Wei-Qiang

    2018-01-01

    Acute kidney injury (AKI) and chronic kidney disease (CKD) are worldwide public health problems affecting millions of people and have rapidly increased in prevalence in recent years. Due to the multiple causes of renal failure, many animal models have been developed to advance our understanding of human nephropathy. Among these experimental models, rodents have been extensively used to enable mechanistic understanding of kidney disease induction and progression, as well as to identify potential targets for therapy. In this review, we discuss AKI models induced by surgical operation and drugs or toxins, as well as a variety of CKD models (mainly genetically modified mouse models). Results from recent and ongoing clinical trials and conceptual advances derived from animal models are also explored. PMID:29515089

  19. 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.

  20. Identifying a minimal rheological configuration: a tool for effective and efficient constitutive modeling of soft tissues.

    Science.gov (United States)

    Jordan, Petr; Kerdok, Amy E; Howe, Robert D; Socrate, Simona

    2011-04-01

    We describe a modeling methodology intended as a preliminary step in the identification of appropriate constitutive frameworks for the time-dependent response of biological tissues. The modeling approach comprises a customizable rheological network of viscous and elastic elements governed by user-defined 1D constitutive relationships. The model parameters are identified by iterative nonlinear optimization, minimizing the error between experimental and model-predicted structural (load-displacement) tissue response under a specific mode of deformation. We demonstrate the use of this methodology by determining the minimal rheological arrangement, constitutive relationships, and model parameters for the structural response of various soft tissues, including ex vivo perfused porcine liver in indentation, ex vivo porcine brain cortical tissue in indentation, and ex vivo human cervical tissue in unconfined compression. Our results indicate that the identified rheological configurations provide good agreement with experimental data, including multiple constant strain rate load/unload tests and stress relaxation tests. Our experience suggests that the described modeling framework is an efficient tool for exploring a wide array of constitutive relationships and rheological arrangements, which can subsequently serve as a basis for 3D constitutive model development and finite-element implementations. The proposed approach can also be employed as a self-contained tool to obtain simplified 1D phenomenological models of the structural response of biological tissue to single-axis manipulations for applications in haptic technologies.

  1. 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.

  2. 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

  3. Predictive models for identifying the binding activity of structurally diverse chemicals to human pregnane X receptor.

    Science.gov (United States)

    Yin, Cen; Yang, Xianhai; Wei, Mengbi; Liu, Huihui

    2017-08-01

    Toxic chemicals entered into human body would undergo a series of metabolism, transport and excretion, and the key roles played in there processes were metabolizing enzymes, which was regulated by the pregnane X receptor (PXR). However, some chemicals in environment could activate or antagonize human pregnane X receptor, thereby leading to a disturbance of normal physiological systems. In this study, based on a larger number of 2724 structurally diverse chemicals, we developed qualitative classification models by the k-nearest neighbor method. Moreover, the logarithm of 20 and 50% effective concentrations (log EC 20 and log EC 50 ) was used to establish quantitative structure-activity relationship (QSAR) models. With the classification model, two descriptors were enough to establish acceptable models, with the sensitivity, specificity, and accuracy being larger than 0.7, highlighting a high classification performance of the models. With two QSAR models, the statistics parameters with the correlation coefficient (R 2 ) of 0.702-0.749 and the cross-validation and external validation coefficient (Q 2 ) of 0.643-0.712, this indicated that the models complied with the criteria proposed in previous studies, i.e., R 2  > 0.6, Q 2  > 0.5. The small root mean square error (RMSE) of 0.254-0.414 and the good consistency between observed and predicted values proved satisfactory goodness of fit, robustness, and predictive ability of the developed QSAR models. Additionally, the applicability domains were characterized by the Euclidean distance-based approach and Williams plot, and results indicated that the current models had a wide applicability domain, which especially included a few classes of environmental contaminant, those that were not included in the previous models.

  4. European Bilingual Models beyond "Lingua Franca": Key Findings from CLIL French Programs

    Science.gov (United States)

    Pérez, América; Lorenzo, Francisco; Pavón, Víctor

    2016-01-01

    Content and Language Integrated Learning (CLIL) has expanded all around the continent following European Council guidelines, favored by competence studies that identified educational systems as a strong determinant for second language gains and deficits. Over the years since the turn of the century, CLIL has gained the support of language policy…

  5. 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.

  6. Identifying prescription patterns with a topic model of diseases and medications.

    Science.gov (United States)

    Park, Sungrae; Choi, Doosup; Kim, Minki; Cha, Wonchul; Kim, Chuhyun; Moon, Il-Chul

    2017-11-01

    Wide variance exists among individuals and institutions for treating patients with medicine. This paper analyzes prescription patterns using a topic model with more than four million prescriptions. Specifically, we propose the disease-medicine pattern model (DMPM) to extract patterns from a large collection of insurance data by considering disease codes joined with prescribed medicines. We analyzed insurance prescription data from 2011 with DMPM and found prescription patterns that could not be identified by traditional simple disease classification, such as the International Classification of Diseases (ICD). We analyzed the identified prescription patterns from multiple aspects. First, we found that our model better explain unseen prescriptions than other probabilistic models. Second, we analyzed the similarities of the extracted patterns to identify their characteristics. Third, we compared the identified patterns from DMPM to the known disease categorization, ICD. This comparison showed what additional information can be provided by the data-oriented bottom-up patterns in contrast to the knowledge-based top-down categorization. The comparison results showed that the bottom-up categorization allowed for the identification of (1) diverse treatment options for the same disease symptoms, and (2) diverse disease cases sharing the same prescription options. Additionally, the extracted bottom-up patterns revealed treatment differences based on basic patient information better than the top-down categorization. We conclude that this data-oriented analysis will be an effective alternative method for analyzing the complex interwoven disease-prescription relationship. Copyright © 2017 Elsevier Inc. All rights reserved.

  7. A Note on the Identifiability of Fixed-Effect 3PL Models.

    Science.gov (United States)

    Wu, Hao

    2016-12-01

    In this note, we prove that the 3 parameter logistic model with fixed-effect abilities is identified only up to a linear transformation of the ability scale under mild regularity conditions, contrary to the claims in Theorem 2 of San Martín et al. (Psychometrika, 80(2):450-467, 2015a).

  8. A data-driven framework for identifying nonlinear dynamic models of genetic parts.

    Science.gov (United States)

    Krishnanathan, Kirubhakaran; Anderson, Sean R; Billings, Stephen A; Kadirkamanathan, Visakan

    2012-08-17

    A key challenge in synthetic biology is the development of effective methodologies for characterization of component genetic parts in a form suitable for dynamic analysis and design. In this investigation we propose the use of a nonlinear dynamic modeling framework that is popular in the field of control engineering but is novel to the field of synthetic biology: Nonlinear AutoRegressive Moving Average model with eXogenous inputs (NARMAX). The framework is applied to the identification of a genetic part BBa_T9002 as a case study. A concise model is developed that exhibits accurate representation of the system dynamics and a structure that is compact and consistent across cell populations. A comparison is made with a biochemical model, derived from a simple enzymatic reaction scheme. The NARMAX model is shown to be comparably simple but exhibits much greater prediction accuracy on the experimental data. These results indicate that the data-driven NARMAX framework is an attractive technique for dynamic modeling of genetic parts.

  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. 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...

  11. 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

  12. 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.

  13. 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.

  14. A Hidden Markov Movement Model for rapidly identifying behavioral states from animal tracks

    DEFF Research Database (Denmark)

    Whoriskey, Kim; Auger-Méthé, Marie; Albertsen, Christoffer Moesgaard

    2017-01-01

    1. Electronic telemetry is frequently used to document animal movement through time. Methods that can identify underlying behaviors driving specific movement patterns can help us understand how and why animals use available space, thereby aiding conservation and management efforts. For aquatic...... animal tracking data with significant measurement error, a Bayesian state-space model called the first-Difference Correlated Random Walk with Switching (DCRWS) has often been used for this purpose. However, for aquatic animals, highly accurate tracking data of animal movement are now becoming more common....... 2. We developed a new Hidden Markov Model (HMM) for identifying behavioral states from animal tracks with negligible error, which we called the Hidden Markov Movement Model (HMMM). We implemented as the basis for the HMMM the process equation of the DCRWS, but we used the method of maximum...

  15. 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

  16. 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

  17. 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.

  18. 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.

  19. Evaluating midwifery-led antenatal care: using a programme logic model to identify relevant outcomes.

    Science.gov (United States)

    Butler, Michelle M; Brosnan, Mary C; Drennan, Jonathan; Feeney, Patricia; Gavigan, Orla; Kington, Maureen; O'Brien, Denise; Sheehy, Lucille; Walsh, Maura C

    2014-01-01

    a range of initiatives has been introduced in Ireland and internationally in recent years to establish midwifery-led models of care, generally aimed at increasing the choices available for women for maternity care. A midwifery-led antenatal clinic was first established at the study site (a large urban maternity hospital in Dublin) and extended over recent years. This paper reports on the design of an evaluation of these midwives clinics, in particular the use of a programme logic model to select outcomes to be included in the evaluation. the programme logic model is used to identify the theory of a programme and is an integrative framework for the design and analysis of evaluations using qualitative and quantitative methods. Through an inclusive approach, the aim was to identify the most relevant outcomes to be included in the evaluation, by identifying and linking programme (midwifery-led antenatal clinic) outcomes to the goals, inputs and processes involved in the production of these outcomes. the process involved a literature review, a review of policy documents and previous reviews of the clinics, interviews with midwives, obstetricians and managers to identify possible outcomes, a focus group with midwives, obstetricians, managers and women who had attended the clinics to refine and prioritise outcomes, and a follow-up survey to refine and prioritise the outcomes identified and to identify sources of data on each outcome. seven categories of outcomes were identified: (1) choice, (2) relationship/interaction with caregiver, (3) experience of care, (4) preparation and education for childbirth and parenthood, (5) effectiveness of care, (6) organisational outcomes, and (7) programme viability. A range of sources of information was identified for each outcome, including existing documentation and data, chart audit, survey of women, and interviews and focus groups with midwives, obstetricians, managers and women. the programme logic model provided an inclusive

  20. The Peculiarities of Identifying the Components of a Business Model of Restaurant Industry Enterprise

    Directory of Open Access Journals (Sweden)

    Grosul Victoria A.

    2017-06-01

    Full Text Available The article substantiates the need for elaborating an efficient business model, implementation of which would enable enterprises of restaurant industry to create sustainable competitive advantages and would contribute to successful development in the long term. The basic scientific approaches to defining the business model components have been allocated. The main emphases and standard elements of a business model of enterprise in terms of each of the scientific approaches have been defined. The basic components of a business model of restaurant industry enterprise have been identified, taking into account the pivotal interrelated management processes: production, sales, consumption organization. The characteristics of each component of the business model of enterprise of restaurant industry have been provided in accordance with objectives of its activity in the context of efficient strategical decisions.

  1. 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.

  2. 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...

  3. 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.)

  4. Modeling, Simulation, and Analysis of a Decoy State Enabled Quantum Key Distribution System

    Science.gov (United States)

    2015-03-26

    Protecting Information, New York: Cambridge University Press, 2006. [6] M. A. Nielsen and I. L. Chuang, Quantum Computation and Quantum Information...configurable to interfere with Bob’s ability to detect a weak coherent pulse. DR D 5 The QKD model shall be accurate, flexible, usable , extensible

  5. Modeling information flows in clinical decision support: key insights for enhancing system effectiveness

    NARCIS (Netherlands)

    Medlock, Stephanie; Wyatt, Jeremy C.; Patel, Vimla L.; Shortliffe, Edward H.; Abu-Hanna, Ameen

    2016-01-01

    A fundamental challenge in the field of clinical decision support is to determine what characteristics of systems make them effective in supporting particular types of clinical decisions. However, we lack such a theory of decision support itself and a model to describe clinical decisions and the

  6. 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,

  7. Modeling succession of key resource-harvesting traits of mixotrophic plankton

    DEFF Research Database (Denmark)

    Berge, Terje; Chakraborty, Subhendu; Hansen, Per Juel

    2017-01-01

    building blocks for growth, the model reproduces the observed light-dependent ingestion rates and species-specific growth rates with and without prey from the laboratory. The combination of traits yielding the highest growth rate suggests high investments in photosynthesis, and inorganic nutrient uptake...

  8. Identifying strategy use in category learning tasks: a case for more diagnostic data and models.

    Science.gov (United States)

    Donkin, Chris; Newell, Ben R; Kalish, Mike; Dunn, John C; Nosofsky, Robert M

    2015-07-01

    The strength of conclusions about the adoption of different categorization strategies-and their implications for theories about the cognitive and neural bases of category learning-depend heavily on the techniques for identifying strategy use. We examine performance in an often-used "information-integration" category structure and demonstrate that strategy identification is affected markedly by the range of models under consideration, the type of data collected, and model-selection techniques. We use a set of 27 potential models that represent alternative rule-based and information-integration categorization strategies. Our experimental paradigm includes the presentation of nonreinforced transfer stimuli that improve one's ability to discriminate among the predictions of alternative models. Our model-selection techniques incorporate uncertainty in the identification of individuals as either rule-based or information-integration strategy users. Based on this analysis we identify 48% of participants as unequivocally using an information-integration strategy. However, adopting the standard practice of using a restricted set of models, restricted data, and ignoring the degree of support for a particular strategy, we would typically conclude that 89% of participants used an information-integration strategy. We discuss the implications of potentially erroneous strategy identification for the security of conclusions about the categorization capabilities of various participant and patient groups. (c) 2015 APA, all rights reserved.

  9. 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

  10. Identifying model error in metabolic flux analysis - a generalized least squares approach.

    Science.gov (United States)

    Sokolenko, Stanislav; Quattrociocchi, Marco; Aucoin, Marc G

    2016-09-13

    The estimation of intracellular flux through traditional metabolic flux analysis (MFA) using an overdetermined system of equations is a well established practice in metabolic engineering. Despite the continued evolution of the methodology since its introduction, there has been little focus on validation and identification of poor model fit outside of identifying "gross measurement error". The growing complexity of metabolic models, which are increasingly generated from genome-level data, has necessitated robust validation that can directly assess model fit. In this work, MFA calculation is framed as a generalized least squares (GLS) problem, highlighting the applicability of the common t-test for model validation. To differentiate between measurement and model error, we simulate ideal flux profiles directly from the model, perturb them with estimated measurement error, and compare their validation to real data. Application of this strategy to an established Chinese Hamster Ovary (CHO) cell model shows how fluxes validated by traditional means may be largely non-significant due to a lack of model fit. With further simulation, we explore how t-test significance relates to calculation error and show that fluxes found to be non-significant have 2-4 fold larger error (if measurement uncertainty is in the 5-10 % range). The proposed validation method goes beyond traditional detection of "gross measurement error" to identify lack of fit between model and data. Although the focus of this work is on t-test validation and traditional MFA, the presented framework is readily applicable to other regression analysis methods and MFA formulations.

  11. Key issues for the development and application of the species sensitivity distribution (SSD) model for ecological risk assessment

    DEFF Research Database (Denmark)

    Xu, Fu-Liu; Li, Yi-Long; Wang, Yin

    2015-01-01

    The species sensitivity distribution (SSD) model is one of the most commonly used methods for ecological risk assessment based on the potentially affected fraction (PAF) of and the combined PAF (msPAF) as quantitative indicators. There are usually four steps for the development of SSD models...... fractions (msPAFs) for the joint ecological risk assessment of multiple pollutants. Among the above mentioned four steps, the first two steps are paramount. In the present study, the following six key issues are discussed: (1) how to select the appropriate species, (2) how to preprocess the toxicity data...... for invertebrates. The concentration addition or response addition were discussed to calculate msPAF according to the toxic model of action (TMoA). The uncertainties of the SSD models for five heavy metals and for eight polycyclic aromatic hydrocarbons (PAHs) were performed. The comparison of the coefficients...

  12. Key Players and Key Groups in Teams

    OpenAIRE

    Sudipta Sarangi; Emre Unlu

    2011-01-01

    This paper contributes to the literature on centrality measures in economics by defining a team game and identifying the key players in the game. As an illustration of the theory we create a unique data set from the UEFA Euro 2008 tournament. To capture the interaction between players we create the passing network of each team. This all allows us to identify the key player and key groups of players for both teams in each game. We then use our measure to explain player ratings by experts and t...

  13. 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.

  14. Novel personalized pathway-based metabolomics models reveal key metabolic pathways for breast cancer diagnosis.

    Science.gov (United States)

    Huang, Sijia; Chong, Nicole; Lewis, Nathan E; Jia, Wei; Xie, Guoxiang; Garmire, Lana X

    2016-03-31

    More accurate diagnostic methods are pressingly needed to diagnose breast cancer, the most common malignant cancer in women worldwide. Blood-based metabolomics is a promising diagnostic method for breast cancer. However, many metabolic biomarkers are difficult to replicate among studies. We propose that higher-order functional representation of metabolomics data, such as pathway-based metabolomic features, can be used as robust biomarkers for breast cancer. Towards this, we have developed a new computational method that uses personalized pathway dysregulation scores for disease diagnosis. We applied this method to predict breast cancer occurrence, in combination with correlation feature selection (CFS) and classification methods. The resulting all-stage and early-stage diagnosis models are highly accurate in two sets of testing blood samples, with average AUCs (Area Under the Curve, a receiver operating characteristic curve) of 0.968 and 0.934, sensitivities of 0.946 and 0.954, and specificities of 0.934 and 0.918. These two metabolomics-based pathway models are further validated by RNA-Seq-based TCGA (The Cancer Genome Atlas) breast cancer data, with AUCs of 0.995 and 0.993. 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. 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 diagnosis.

  15. Scenario-Led Habitat Modelling of Land Use Change Impacts on Key Species.

    Science.gov (United States)

    Geary, Matthew; Fielding, Alan H; McGowan, Philip J K; Marsden, Stuart J

    2015-01-01

    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.

  16. Epidemiological Implications of Host Biodiversity and Vector Biology: Key Insights from Simple Models.

    Science.gov (United States)

    Dobson, Andrew D M; Auld, Stuart K J R

    2016-04-01

    Models used to investigate the relationship between biodiversity change and vector-borne disease risk often do not explicitly include the vector; they instead rely on a frequency-dependent transmission function to represent vector dynamics. However, differences between classes of vector (e.g., ticks and insects) can cause discrepancies in epidemiological responses to environmental change. Using a pair of disease models (mosquito- and tick-borne), we simulated substitutive and additive biodiversity change (where noncompetent hosts replaced or were added to competent hosts, respectively), while considering different relationships between vector and host densities. We found important differences between classes of vector, including an increased likelihood of amplified disease risk under additive biodiversity change in mosquito models, driven by higher vector biting rates. We also draw attention to more general phenomena, such as a negative relationship between initial infection prevalence in vectors and likelihood of dilution, and the potential for a rise in density of infected vectors to occur simultaneously with a decline in proportion of infected hosts. This has important implications; the density of infected vectors is the most valid metric for primarily zoonotic infections, while the proportion of infected hosts is more relevant for infections where humans are a primary host.

  17. 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

  18. 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.

  19. Identifying At-Risk Employees: Modeling Psychosocial Precursors of Potential Insider Threats

    Energy Technology Data Exchange (ETDEWEB)

    Greitzer, Frank L.; Kangas, Lars J.; Noonan, Christine F.; Dalton, Angela C.; Hohimer, Ryan E.

    2012-01-04

    In many insider crimes, managers and other coworkers observed that the offenders had exhibited signs of stress, disgruntlement, or other issues, but no alarms were raised. Barriers to using such psychosocial indicators include the inability to recognize the signs and the failure to record the behaviors so that they can be assessed. A psychosocial model was developed to assess an employee's behavior associated with an increased risk of insider abuse. The model is based on case studies and research literature on factors/correlates associated with precursor behavioral manifestations of individuals committing insider crimes. To test the model's agreement with human resources and management professionals, we conducted an experiment with positive results. If implemented in an operational setting, the model would be part of a set of management tools for employee assessment to identify employees who pose a greater insider threat.

  20. Identify High-Quality Protein Structural Models by Enhanced K-Means

    Science.gov (United States)

    Li, Haiou; 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. PMID:28421198

  1. Identifying genetic loci affecting antidepressant drug response in depression using drug–gene interaction models

    Science.gov (United States)

    Noordam, Raymond; Avery, Christy L; Visser, Loes E; Stricker, Bruno H

    2016-01-01

    Antidepressants are often only moderately successful in decreasing the severity of depressive symptoms. In part, antidepressant treatment response in patients with depression is genetically determined. However, although a large number of studies have been conducted aiming to identify genetic variants associated with antidepressant drug response in depression, only a few variants have been repeatedly identified. Within the present review, we will discuss the methodological challenges and limitations of the studies that have been conducted on this topic to date (e.g., ‘treated-only design’, statistical power) and we will discuss how specifically drug–gene interaction models can be used to be better able to identify genetic variants associated with antidepressant drug response in depression. PMID:27248517

  2. 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.

  3. 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

  4. 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

  5. A Multi-Compartment Hybrid Computational Model Predicts Key Roles for Dendritic Cells in Tuberculosis Infection.

    Science.gov (United States)

    Marino, Simeone; Kirschner, Denise E

    2016-01-01

    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 . 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. The main conclusion of this study is that early events after Mtb

  6. 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.

  7. FRIGA, a new approach to identify isotopes and hypernuclei in n -body transport models

    Science.gov (United States)

    Le Fèvre, A.; Leifels, Y.; Aichelin, J.; Hartnack, Ch.; Kireyev, V.; Bratkovskaya, E.

    2017-11-01

    We present a new algorithm to identify fragments in computer simulations of relativistic heavy-ion collisions. It is based on the simulated annealing technique and can be applied to n -body transport models like the Quantum Molecular Dynamics. This new approach is able to predict isotope yields as well as hypernucleus production. In order to illustrate its predicting power, we confront this new method to experimental data, and show the sensitivity on the parameters which govern the cluster formation.

  8. Application of the transtheoretical model to identify predictors of physical activity transition in university students

    OpenAIRE

    Kang, SooJin

    2017-01-01

    Within the physical activity domain the majority of transtheoretical model research has employed a cross sectional research design. While useful for characterizing participants within the various stages of change, it fails to capture the dynamic nature of change. The purpose of the current study was to identify predictors of naturally occurring transitional shift patterns in physical activity behavior observed over six months among 202 university students. The full set of variables from the t...

  9. Identifying Efficiencies in the Supply Chain for Training Ammunition: Methods, Models, and Recommendations

    Science.gov (United States)

    2016-01-01

    Research Report Identifying Efficiencies in the Supply Chain for Training Ammunition Methods , Models, and Recommendations Dwayne M. Butler...RAND’s publications do not necessarily reflect the opinions of its research clients and sponsors. Support RAND Make a tax- deductible charitable...reuse in another form, any of its research documents for commercial use. For information on reprint and linking permissions, please visit www.rand.org

  10. Modeling information flows in clinical decision support: key insights for enhancing system effectiveness.

    Science.gov (United States)

    Medlock, Stephanie; Wyatt, Jeremy C; Patel, Vimla L; Shortliffe, Edward H; Abu-Hanna, Ameen

    2016-09-01

    A fundamental challenge in the field of clinical decision support is to determine what characteristics of systems make them effective in supporting particular types of clinical decisions. However, we lack such a theory of decision support itself and a model to describe clinical decisions and the systems to support them. This article outlines such a framework. We present a two-stream model of information flow within clinical decision-support systems (CDSSs): reasoning about the patient (the clinical stream), and reasoning about the user (the cognitive-behavioral stream). We propose that CDSS "effectiveness" be measured not only in terms of a system's impact on clinical care, but also in terms of how (and by whom) the system is used, its effect on work processes, and whether it facilitates appropriate decisions by clinicians and patients. Future research into which factors improve the effectiveness of decision support should not regard CDSSs as a single entity, but should instead differentiate systems based on their attributes, users, and the decision being supported. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  11. Theoretical Model of God: The Key to Correct Exploration of the Universe

    Science.gov (United States)

    Kalanov, Temur Z.

    2007-04-01

    The problem of the correct approach to exploration of the Universe cannot be solved if there is no solution of the problem of existence of God (Creator, Ruler) in science. In this connection, theoretical proof of existence of God is proposed. The theoretical model of God -- as scientific proof of existence of God -- is the consequence of the system of the formulated axioms. The system of the axioms contains, in particular, the following premises: (1) all objects formed (synthesized) by man are characterized by the essential property: namely, divisibility into aspects; (2) objects which can be mentally divided into aspects are objects formed (synthesized); (3) the system ``Universe'' is mentally divided into aspects. Consequently, the Universe represents the system formed (synthesized); (4) the theorem of existence of God (i.e. Absolute, Creator, Ruler) follows from the principle of logical completeness of system of concepts: if the formed (synthesized) system ``Universe'' exists, then God exists as the Absolute, the Creator, the Ruler of essence (i.e. information) and phenomenon (i.e. material objects). Thus, the principle of existence of God -- the content of the theoretical model of God -- must be a starting-point and basis of correct gnosiology and science of 21 century.

  12. 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.

  13. GIS model for identifying urban areas vulnerable to noise pollution: case study

    Science.gov (United States)

    Bilaşco, Ştefan; Govor, Corina; Roşca, Sanda; Vescan, Iuliu; Filip, Sorin; Fodorean, Ioan

    2017-04-01

    The unprecedented expansion of the national car ownership over the last few years has been determined by economic growth and the need for the population and economic agents to reduce travel time in progressively expanding large urban centres. This has led to an increase in the level of road noise and a stronger impact on the quality of the environment. Noise pollution generated by means of transport represents one of the most important types of pollution with negative effects on a population's health in large urban areas. As a consequence, tolerable limits of sound intensity for the comfort of inhabitants have been determined worldwide and the generation of sound maps has been made compulsory in order to identify the vulnerable zones and to make recommendations how to decrease the negative impact on humans. In this context, the present study aims at presenting a GIS spatial analysis model-based methodology for identifying and mapping zones vulnerable to noise pollution. The developed GIS model is based on the analysis of all the components influencing sound propagation, represented as vector databases (points of sound intensity measurements, buildings, lands use, transport infrastructure), raster databases (DEM), and numerical databases (wind direction and speed, sound intensity). Secondly, the hourly changes (for representative hours) were analysed to identify the hotspots characterised by major traffic flows specific to rush hours. The validated results of the model are represented by GIS databases and useful maps for the local public administration to use as a source of information and in the process of making decisions.

  14. Assessing the performance of community-available global MHD models using key system parameters and empirical relationships

    Science.gov (United States)

    Gordeev, E.; Sergeev, V.; Honkonen, I.; Kuznetsova, M.; Rastätter, L.; Palmroth, M.; Janhunen, P.; Tóth, G.; Lyon, J.; Wiltberger, M.

    2015-12-01

    Global magnetohydrodynamic (MHD) modeling is a powerful tool in space weather research and predictions. There are several advanced and still developing global MHD (GMHD) models that are publicly available via Community Coordinated Modeling Center's (CCMC) Run on Request system, which allows the users to simulate the magnetospheric response to different solar wind conditions including extraordinary events, like geomagnetic storms. Systematic validation of GMHD models against observations still continues to be a challenge, as well as comparative benchmarking of different models against each other. In this paper we describe and test a new approach in which (i) a set of critical large-scale system parameters is explored/tested, which are produced by (ii) specially designed set of computer runs to simulate realistic statistical distributions of critical solar wind parameters and are compared to (iii) observation-based empirical relationships for these parameters. Being tested in approximately similar conditions (similar inputs, comparable grid resolution, etc.), the four models publicly available at the CCMC predict rather well the absolute values and variations of those key parameters (magnetospheric size, magnetic field, and pressure) which are directly related to the large-scale magnetospheric equilibrium in the outer magnetosphere, for which the MHD is supposed to be a valid approach. At the same time, the models have systematic differences in other parameters, being especially different in predicting the global convection rate, total field-aligned current, and magnetic flux loading into the magnetotail after the north-south interplanetary magnetic field turning. According to validation results, none of the models emerges as an absolute leader. The new approach suggested for the evaluation of the models performance against reality may be used by model users while planning their investigations, as well as by model developers and those interesting to quantitatively

  15. 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.

  16. 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

  17. Markov Mixed Effects Modeling Using Electronic Adherence Monitoring Records Identifies Influential Covariates to HIV Preexposure Prophylaxis.

    Science.gov (United States)

    Madrasi, Kumpal; Chaturvedula, Ayyappa; Haberer, Jessica E; Sale, Mark; Fossler, Michael J; Bangsberg, David; Baeten, Jared M; Celum, Connie; Hendrix, Craig W

    2017-05-01

    Adherence is a major factor in the effectiveness of preexposure prophylaxis (PrEP) for HIV prevention. Modeling patterns of adherence helps to identify influential covariates of different types of adherence as well as to enable clinical trial simulation so that appropriate interventions can be developed. We developed a Markov mixed-effects model to understand the covariates influencing adherence patterns to daily oral PrEP. Electronic adherence records (date and time of medication bottle cap opening) from the Partners PrEP ancillary adherence study with a total of 1147 subjects were used. This study included once-daily dosing regimens of placebo, oral tenofovir disoproxil fumarate (TDF), and TDF in combination with emtricitabine (FTC), administered to HIV-uninfected members of serodiscordant couples. One-coin and first- to third-order Markov models were fit to the data using NONMEM ® 7.2. Model selection criteria included objective function value (OFV), Akaike information criterion (AIC), visual predictive checks, and posterior predictive checks. Covariates were included based on forward addition (α = 0.05) and backward elimination (α = 0.001). Markov models better described the data than 1-coin models. A third-order Markov model gave the lowest OFV and AIC, but the simpler first-order model was used for covariate model building because no additional benefit on prediction of target measures was observed for higher-order models. Female sex and older age had a positive impact on adherence, whereas Sundays, sexual abstinence, and sex with a partner other than the study partner had a negative impact on adherence. Our findings suggest adherence interventions should consider the role of these factors. © 2016, The American College of Clinical Pharmacology.

  18. Multiscale models and stochastic simulation methods for computing rare but key binding events in cell biology

    Science.gov (United States)

    Guerrier, C.; Holcman, D.

    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.

  19. 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.

  20. 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.

  1. Integrated hydrologic modeling as a key for sustainable urban water resources planning.

    Science.gov (United States)

    Eshtawi, Tamer; Evers, Mariele; Tischbein, Bernhard; Diekkrüger, Bernd

    2016-09-15

    In this study, a coupling of surface water (SWAT), groundwater (MODFLOW) and solute transport (MT3DMS) models was performed to quantify surface-groundwater and quantity-quality interactions under urban area expansion. The responses of groundwater level, nitrate concentrations (related to human activities) and chloride concentrations (related to seawater intrusion) to urban area expansion and corresponding changes in the urban water budget were examined on a macro-scale level. The potentials of non-conventional water resources scenarios, namely desalination, stormwater harvesting and treated wastewater (TWW) reuse were investigated. In a novel analysis, groundwater improvement and deterioration under each scenario were defined in spatial-temporal approach. The quality deterioration cycle index was estimated as the ratio between the amounts of low and high quality recharge components within the Gaza Strip boundary predicted for year 2030. The improvement index for groundwater level (IIL) and the improvement index for groundwater quality (IIQ) were developed for the scenarios as measures of the effectiveness toward sustainable groundwater planning. Even though the desalination and TWW reuse scenarios reflect a noticeable improvement in the groundwater level, the desalination scenario shows a stronger tendency toward sustainable groundwater quality. The stormwater harvesting scenario shows a slight improvement in both groundwater quality and quantity. This study provides a 'corridor of options', which could facilitate future studies focusing on developing a micro-level assessment of the above scenarios. Copyright © 2016 Elsevier Ltd. All rights reserved.

  2. 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.

  3. Concept design theory and model for multi-use space facilities: Analysis of key system design parameters through variance of mission requirements

    Science.gov (United States)

    Reynerson, Charles Martin

    This research has been performed to create concept design and economic feasibility data for space business parks. A space business park is a commercially run multi-use space station facility designed for use by a wide variety of customers. Both space hardware and crew are considered as revenue producing payloads. Examples of commercial markets may include biological and materials research, processing, and production, space tourism habitats, and satellite maintenance and resupply depots. This research develops a design methodology and an analytical tool to create feasible preliminary design information for space business parks. The design tool is validated against a number of real facility designs. Appropriate model variables are adjusted to ensure that statistical approximations are valid for subsequent analyses. The tool is used to analyze the effect of various payload requirements on the size, weight and power of the facility. The approach for the analytical tool was to input potential payloads as simple requirements, such as volume, weight, power, crew size, and endurance. In creating the theory, basic principles are used and combined with parametric estimation of data when necessary. Key system parameters are identified for overall system design. Typical ranges for these key parameters are identified based on real human spaceflight systems. To connect the economics to design, a life-cycle cost model is created based upon facility mass. This rough cost model estimates potential return on investments, initial investment requirements and number of years to return on the initial investment. Example cases are analyzed for both performance and cost driven requirements for space hotels, microgravity processing facilities, and multi-use facilities. In combining both engineering and economic models, a design-to-cost methodology is created for more accurately estimating the commercial viability for multiple space business park markets.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. Identifying the origin of waterbird carcasses in Lake Michigan using a neural network source tracking model

    Science.gov (United States)

    Kenow, Kevin P.; Ge, Zhongfu; Fara, Luke J.; Houdek, Steven C.; Lubinski, Brian R.

    2016-01-01

    Avian botulism type E is responsible for extensive waterbird mortality on the Great Lakes, yet the actual site of toxin exposure remains unclear. Beached carcasses are often used to describe the spatial aspects of botulism mortality outbreaks, but lack specificity of offshore toxin source locations. We detail methodology for developing a neural network model used for predicting waterbird carcass motions in response to wind, wave, and current forcing, in lieu of a complex analytical relationship. This empirically trained model uses current velocity, wind velocity, significant wave height, and wave peak period in Lake Michigan simulated by the Great Lakes Coastal Forecasting System. A detailed procedure is further developed to use the model for back-tracing waterbird carcasses found on beaches in various parts of Lake Michigan, which was validated using drift data for radiomarked common loon (Gavia immer) carcasses deployed at a variety of locations in northern Lake Michigan during September and October of 2013. The back-tracing model was further used on 22 non-radiomarked common loon carcasses found along the shoreline of northern Lake Michigan in October and November of 2012. The model-estimated origins of those cases pointed to some common source locations offshore that coincide with concentrations of common loons observed during aerial surveys. The neural network source tracking model provides a promising approach for identifying locations of botulinum neurotoxin type E intoxication and, in turn, contributes to developing an understanding of the dynamics of toxin production and possible trophic transfer pathways.

  10. Process-oriented modelling to identify main drivers of erosion-induced carbon fluxes

    Science.gov (United States)

    Wilken, Florian; Sommer, Michael; Van Oost, Kristof; Bens, Oliver; Fiener, Peter

    2017-05-01

    Coupled modelling of soil erosion, carbon redistribution, and turnover has received great attention over the last decades due to large uncertainties regarding erosion-induced carbon fluxes. For a process-oriented representation of event dynamics, coupled soil-carbon erosion models have been developed. However, there are currently few models that represent tillage erosion, preferential water erosion, and transport of different carbon fractions (e.g. mineral bound carbon, carbon encapsulated by soil aggregates). We couple a process-oriented multi-class sediment transport model with a carbon turnover model (MCST-C) to identify relevant redistribution processes for carbon dynamics. The model is applied for two arable catchments (3.7 and 7.8 ha) located in the Tertiary Hills about 40 km north of Munich, Germany. Our findings indicate the following: (i) redistribution by tillage has a large effect on erosion-induced vertical carbon fluxes and has a large carbon sequestration potential; (ii) water erosion has a minor effect on vertical fluxes, but episodic soil organic carbon (SOC) delivery controls the long-term erosion-induced carbon balance; (iii) delivered sediments are highly enriched in SOC compared to the parent soil, and sediment delivery is driven by event size and catchment connectivity; and (iv) soil aggregation enhances SOC deposition due to the transformation of highly mobile carbon-rich fine primary particles into rather immobile soil aggregates.

  11. 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.

  12. Toward the Analysis of JWST Exoplanet Spectra: Identifying Troublesome Model Parameters

    Science.gov (United States)

    Baudino, Jean-Loup; Mollière, Paul; Venot, Olivia; Tremblin, Pascal; Bézard, Bruno; Lagage, Pierre-Olivier

    2017-12-01

    Given the forthcoming launch of the James Webb Space Telescope (JWST), which will allow observing exoplanet atmospheres with unprecedented signal-to-noise ratio, spectral coverage, and spatial resolution, the uncertainties in the atmosphere modeling used to interpret the data need to be assessed. As the first step, we compare three independent 1D radiative-convective models: ATMO, Exo-REM, and petitCODE. We identify differences in physical and chemical processes that are taken into account thanks to a benchmark protocol we have developed. We study the impact of these differences on the analysis of observable spectra. We show the importance of selecting carefully relevant molecular linelists to compute the atmospheric opacity. Indeed, differences between spectra calculated with Hitran and ExoMol exceed the expected uncertainties of future JWST observations. We also show the limits of the precision of the models due to uncertainties on alkali and molecule lineshape, which induce spectral effects that are also larger than the expected JWST uncertainties. We compare two chemical models, Exo-REM and Venot Chemical Code, which do not lead to significant differences in the emission or transmission spectra. We discuss the observational consequences of using equilibrium or out-of-equilibrium chemistry and the major impact of phosphine, detectable with the JWST. Each of the models has benefited from the benchmarking activity and has been updated. The protocol developed in this paper and the online results can constitute a test case for other models.

  13. 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 ASM were of 87.5% and 77.2% (gamma correlations 0.72-1.0; p 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 to determine indices for identifying SA and RSA in HIV-infected patients.

  14. 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.

  15. Identifying critical success factors (CSFs) of implementing building information modeling (BIM) in Malaysian construction industry

    Science.gov (United States)

    Yaakob, Mazri; Ali, Wan Nur Athirah Wan; Radzuan, Kamaruddin

    2016-08-01

    Building Information Modeling (BIM) is defined as existing from the earliest concept to demolition and it involves creating and using an intelligent 3D model to inform and communicate project decisions. This research aims to identify the critical success factors (CSFs) of BIM implementation in Malaysian construction industry. A literature review was done to explore previous BIM studies on definitions and history of BIM, construction issues, application of BIM in construction projects as well as benefits of BIM. A series of interviews with multidisciplinary Malaysian construction experts will be conducted purposely for data collection process guided by the research design and methodology approach of this study. The analysis of qualitative data from the process will be combined with criteria identified in the literature review in order to identify the CSFs. Finally, the CSFs of BIM implementation will be validated by further Malaysian industrialists during a workshop. The validated CSFs can be used as a term of reference for both Malaysian practitioners and academics towards measuring BIM effectiveness level in their organizations.

  16. 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

  17. 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

  18. 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

  19. Models of self-peptide sampling by developing T cells identify candidate mechanisms of thymic selection.

    Directory of Open Access Journals (Sweden)

    Iren Bains

    Full Text Available Conventional and regulatory T cells develop in the thymus where they are exposed to samples of self-peptide MHC (pMHC ligands. This probabilistic process selects for cells within a range of responsiveness that allows the detection of foreign antigen without excessive responses to self. Regulatory T cells are thought to lie at the higher end of the spectrum of acceptable self-reactivity and play a crucial role in the control of autoimmunity and tolerance to innocuous antigens. While many studies have elucidated key elements influencing lineage commitment, we still lack a full understanding of how thymocytes integrate signals obtained by sampling self-peptides to make fate decisions. To address this problem, we apply stochastic models of signal integration by T cells to data from a study quantifying the development of the two lineages using controllable levels of agonist peptide in the thymus. We find two models are able to explain the observations; one in which T cells continually re-assess fate decisions on the basis of multiple summed proximal signals from TCR-pMHC interactions; and another in which TCR sensitivity is modulated over time, such that contact with the same pMHC ligand may lead to divergent outcomes at different stages of development. Neither model requires that T(conv and T(reg are differentially susceptible to deletion or that the two lineages need qualitatively different signals for development, as have been proposed. We find additional support for the variable-sensitivity model, which is able to explain apparently paradoxical observations regarding the effect of partial and strong agonists on T(conv and T(reg development.

  20. A novel mouse model identifies cooperating mutations and therapeutic targets critical for chronic myeloid leukemia progression

    Science.gov (United States)

    Giotopoulos, George; van der Weyden, Louise; Osaki, Hikari; Rust, Alistair G.; Gallipoli, Paolo; Meduri, Eshwar; Horton, Sarah J.; Chan, Wai-In; Foster, Donna; Prinjha, Rab K.; Pimanda, John E.; Tenen, Daniel G.; Vassiliou, George S.; Koschmieder, Steffen; Adams, David J.

    2015-01-01

    The introduction of highly selective ABL-tyrosine kinase inhibitors (TKIs) has revolutionized therapy for chronic myeloid leukemia (CML). However, TKIs are only efficacious in the chronic phase of the disease and effective therapies for TKI-refractory CML, or after progression to blast crisis (BC), are lacking. Whereas the chronic phase of CML is dependent on BCR-ABL, additional mutations are required for progression to BC. However, the identity of these mutations and the pathways they affect are poorly understood, hampering our ability to identify therapeutic targets and improve outcomes. Here, we describe a novel mouse model that allows identification of mechanisms of BC progression in an unbiased and tractable manner, using transposon-based insertional mutagenesis on the background of chronic phase CML. Our BC model is the first to faithfully recapitulate the phenotype, cellular and molecular biology of human CML progression. We report a heterogeneous and unique pattern of insertions identifying known and novel candidate genes and demonstrate that these pathways drive disease progression and provide potential targets for novel therapeutic strategies. Our model greatly informs the biology of CML progression and provides a potent resource for the development of candidate therapies to improve the dismal outcomes in this highly aggressive disease. PMID:26304963

  1. A hidden Markov movement model for rapidly identifying behavioral states from animal tracks.

    Science.gov (United States)

    Whoriskey, Kim; Auger-Méthé, Marie; Albertsen, Christoffer M; Whoriskey, Frederick G; Binder, Thomas R; Krueger, Charles C; Mills Flemming, Joanna

    2017-04-01

    Electronic telemetry is frequently used to document animal movement through time. Methods that can identify underlying behaviors driving specific movement patterns can help us understand how and why animals use available space, thereby aiding conservation and management efforts. For aquatic animal tracking data with significant measurement error, a Bayesian state-space model called the first-Difference Correlated Random Walk with Switching (DCRWS) has often been used for this purpose. However, for aquatic animals, highly accurate tracking data are now becoming more common. We developed a new hidden Markov model (HMM) for identifying behavioral states from animal tracks with negligible error, called the hidden Markov movement model (HMMM). We implemented as the basis for the HMMM the process equation of the DCRWS, but we used the method of maximum likelihood and the R package TMB for rapid model fitting. The HMMM was compared to a modified version of the DCRWS for highly accurate tracks, the DCRWSNOME, and to a common HMM for animal tracks fitted with the R package moveHMM. We show that the HMMM is both accurate and suitable for multiple species by fitting it to real tracks from a grey seal, lake trout, and blue shark, as well as to simulated data. The HMMM is a fast and reliable tool for making meaningful inference from animal movement data that is ideally suited for ecologists who want to use the popular DCRWS implementation and have highly accurate tracking data. It additionally provides a groundwork for development of more complex modeling of animal movement with TMB. To facilitate its uptake, we make it available through the R package swim.

  2. 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

  3. 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.

  4. Information Reference Models for European Pork Supply Networks - Identifying Gaps in Information Infrastructures

    DEFF Research Database (Denmark)

    Lehmann, Richard J.; Hermansen, John Erik; Fritz, Melanie

    2011-01-01

    models for European pork supply networks, which give an aggregated overview about information availability and exchange in the pork sector, identify additional information demands of decision makers at different stages of pork production, and identify gaps in the existing information infrastructure......Several global developments such as diminishing production resources, limits in the availability of water and the growing demand for bio-energy as well as sector-wide crises (e.g. BSE, swine fever, dioxin) have led to a changing attitude of society towards the conse-quences of the food system......‘s activities for social, economic and environmental issues, cap-tured in the term of sustainability. As a consequence, consumers show increasing interest in the characteristics of food, and in turn, on the availability of related information and guaran-tees. The paper introduces different information reference...

  5. 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.

  6. Identifying areas of deforestation risk for REDD+ using a species modeling tool.

    Science.gov (United States)

    Aguilar-Amuchastegui, Naikoa; Riveros, Juan Carlos; Forrest, Jessica L

    2014-01-01

    To implement the REDD+ mechanism (Reducing Emissions for Deforestation and Forest Degradation, countries need to prioritize areas to combat future deforestation CO2 emissions, identify the drivers of deforestation around which to develop mitigation actions, and quantify and value carbon for financial mechanisms. Each comes with its own methodological challenges, and existing approaches and tools to do so can be costly to implement or require considerable technical knowledge and skill. Here, we present an approach utilizing a machine learning technique known as Maximum Entropy Modeling (Maxent) to identify areas at high deforestation risk in the study area in Madre de Dios, Peru under a business-as-usual scenario in which historic deforestation rates continue. We link deforestation risk area to carbon density values to estimate future carbon emissions. We quantified area deforested and carbon emissions between 2000 and 2009 as the basis of the scenario. We observed over 80,000 ha of forest cover lost from 2000-2009 (0.21% annual loss), representing over 39 million Mg CO2. The rate increased rapidly following the enhancement of the Inter Oceanic Highway in 2005. Accessibility and distance to previous deforestation were strong predictors of deforestation risk, while land use designation was less important. The model performed consistently well (AUC > 0.9), significantly better than random when we compared predicted deforestation risk to observed. If past deforestation rates continue, we estimate that 132,865 ha of forest could be lost by the year 2020, representing over 55 million Mg CO2. Maxent provided a reliable method for identifying areas at high risk of deforestation and the major explanatory variables that could draw attention for mitigation action planning under REDD+. The tool is accessible, replicable and easy to use; all necessary for producing good risk estimates and adapt models after potential landscape change. We propose this approach for developing

  7. 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

  8. 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

  9. 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.

  10. Identifying and validating the components of nursing practice models for long-term care facilities.

    Science.gov (United States)

    Mueller, Christine; Savik, Kay

    2010-10-01

    Nursing practice models (NPMs) provide the framework for the design and delivery of nursing care to residents in long-term care (LTC) facilities and characterize the manner in which nursing staff assemble to accomplish clinical goals. The purpose of this study was to identify and validate the distinctive components of NPMs in LTC facilities and develop an instrument to describe and evaluate NPMs in such settings. The study included validation of the NPM components through a literature review and focus groups with nursing staff from LTC facilities; development and modification of the Nursing Practice Model Questionnaire (NPMQ); and examination of the validity and reliability of the NPMQ through pilot testing in 15 LTC facilities with 508 nursing staff. Five factors--decision making, informal continuity of information, formal continuity of information, continuity of care, and accountability--comprise the five subscales of the NPMQ, a 37-item questionnaire with established respectable validity and reliability. Copyright 2010, SLACK Incorporated.

  11. 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.

  12. 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.

  13. 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

  14. 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.

  15. 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

  16. Parameter non-identifiability of the Gyllenberg-Webb ODE model.

    Science.gov (United States)

    Hartung, Niklas

    2014-01-01

    An ODE model introduced by Gyllenberg and Webb (Growth Develop Aging 53:25-33, 1989) describes tumour growth in terms of the dynamics between proliferating and quiescent cell states. The passage from one state to another and vice versa is modelled by two functions r0 and ri depending on the total tumour size. As these functions do not represent any observable quantities, they have to be identified from the observations. In this paper we show that there is an infinite number of pairs (r0, ri) corresponding to the same solution of the ODE system and the functions (r0, ri) will be classified in terms of this equivalence. Surprisingly, the technique used for this classification permits a uniqueness proof of the solution of the ODE model in a non-Lipschitz case. The reasoning can be widened to a more general setting including an extension of the Gyllenberg-Webb model with a nonlinear birth rate. The relevance of this result is discussed in a preclinical application scenario.

  17. 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.

  18. Diazepam-bound GABAA receptor models identify new benzodiazepine binding-site ligands

    Science.gov (United States)

    Richter, Lars; de Graaf, Chris; Sieghart, Werner; Varagic, Zdravko; Mörzinger, Martina; de Esch, Iwan J P; Ecker, Gerhard F; Ernst, Margot

    2012-01-01

    Benzodiazepines exert their anxiolytic, anticonvulsant, muscle-relaxant and sedative-hypnotic properties by allosterically enhancing the action of GABA at GABAA receptors via their benzodiazepine-binding site. Although these drugs have been used clinically since 1960, the molecular basis of this interaction is still not known. By using multiple homology models and an un biased docking protocol, we identified a binding hypothesis for the diazepam-bound structure of the benzodiazepine site, which was confirmed by experimental evidence. Moreover, two independent virtual screening approaches based on this structure identified known benzodiazepine-site ligands from different structural classes and predicted potential new ligands for this site. Receptor-binding assays and electrophysiological studies on recombinant receptors confirmed these predictions and thus identified new chemotypes for the benzodiazepine-binding site. Our results support the validity of the diazepam-bound structure of the benzodiazepine-binding pocket, demonstrate its suitability for drug discovery and pave the way for structure-based drug design. PMID:22446838

  19. Comparison of Statistical Data Models for Identifying Differentially Expressed Genes Using a Generalized Likelihood Ratio Test

    Directory of Open Access Journals (Sweden)

    Kok-Yong Seng

    2008-01-01

    Full Text Available Currently, statistical techniques for analysis of microarray-generated data sets have deficiencies due to limited understanding of errors inherent in the data. A generalized likelihood ratio (GLR test based on an error model has been recently proposed to identify differentially expressed genes from microarray experiments. However, the use of different error structures under the GLR test has not been evaluated, nor has this method been compared to commonly used statistical tests such as the parametric t-test. The concomitant effects of varying data signal-to-noise ratio and replication number on the performance of statistical tests also remain largely unexplored. In this study, we compared the effects of different underlying statistical error structures on the GLR test’s power in identifying differentially expressed genes in microarray data. We evaluated such variants of the GLR test as well as the one sample t-test based on simulated data by means of receiver operating characteristic (ROC curves. Further, we used bootstrapping of ROC curves to assess statistical significance of differences between the areas under the curves. Our results showed that i the GLR tests outperformed the t-test for detecting differential gene expression, ii the identity of the underlying error structure was important in determining the GLR tests’ performance, and iii signal-to-noise ratio was a more important contributor than sample replication in identifying statistically significant differential gene expression.

  20. 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.

  1. Identifying potential misfit items in cognitive process of learning engineering mathematics based on Rasch model

    Science.gov (United States)

    Ataei, Sh; Mahmud, Z.; Khalid, M. N.

    2014-04-01

    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.

  2. 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.

  3. 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.

  4. 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.

  5. Identifying crop vulnerability to groundwater abstraction: modelling and expert knowledge in a GIS.

    Science.gov (United States)

    Procter, Chris; Comber, Lex; Betson, Mark; Buckley, Dennis; Frost, Andy; Lyons, Hester; Riding, Alison; Voyce, Kevin

    2006-11-01

    Water use is expected to increase and climate change scenarios indicate the need for more frequent water abstraction. Abstracting groundwater may have a detrimental effect on soil moisture availability for crop growth and yields. This work presents an elegant and robust method for identifying zones of crop vulnerability to abstraction. Archive groundwater level datasets were used to generate a composite groundwater surface that was subtracted from a digital terrain model. The result was the depth from surface to groundwater and identified areas underlain by shallow groundwater. Knowledge from an expert agronomist was used to define classes of risk in terms of their depth below ground level. Combining information on the permeability of geological drift types further refined the assessment of the risk of crop growth vulnerability. The nature of the mapped output is one that is easy to communicate to the intended farming audience because of the general familiarity of mapped information. Such Geographic Information System (GIS)-based products can play a significant role in the characterisation of catchments under the EU Water Framework Directive especially in the process of public liaison that is fundamental to the setting of priorities for management change. The creation of a baseline allows the impact of future increased water abstraction rates to be modelled and the vulnerability maps are in a format that can be readily understood by the various stakeholders. This methodology can readily be extended to encompass additional data layers and for a range of groundwater vulnerability issues including water resources, ecological impacts, nitrate and phosphorus.

  6. 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

  7. 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

  8. Resolving key drivers of variability through an important circulation choke point in the western Mediterranean Sea; using gliders, models & satellite remote sensing

    Science.gov (United States)

    Heslop, Emma; Aguiar, Eva; Mourre, Baptiste; Juza, Mélanie; Escudier, Romain; Tintoré, Joaquín

    2017-04-01

    The Ibiza Channel plays an important role in the circulation of the Western Mediterranean Sea, it governs the north/south exchange of different water masses that are known to affect regional ecosystems and is influenced by variability in the different drivers that affect sub-basins to the north (N) and south (S). A complex system. In this study we use a multi-platform approach to resolve the key drivers of this variability, and gain insight into the inter-connection between the N and S of the Western Mediterranean Sea through this choke point. The 6-year glider time series from the quasi-continuous glider endurance line monitoring of the Ibiza Channel, undertaken by SOCIB (Balearic Coastal Ocean observing and Forecasting System), is used as the base from which to identify key sub-seasonal to inter-annual patterns and shifts in water mass properties and transport volumes. The glider data indicates the following key components in the variability of the N/S flow of different water mass through the channel; regional winter mode water production, change in intermediate water mass properties, northward flows of a fresher water mass and the basin-scale circulation. To resolve the drivers of these components of variability, the strength of combining datasets from different sources, glider, modeling, altimetry and moorings, is harnessed. To the north atmospheric forcing in the Gulf of Lions is a dominant driver, while to the south the mesoscale circulation patterns of the Atlantic Jet and Alboran gyres dominate the variability but do not appear to influence the fresher inflows. Evidence of a connection between the northern and southern sub-basins is however indicated. The study highlights importance of sub-seasonal variability and the scale of rapid change possible in the Mediterranean, as well as the benefits of leveraging high resolution glider datasets within a multi-platform and modelling study.

  9. 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

  10. Key role of local regulation in chemosensing revealed by a new molecular interaction-based modeling method.

    Directory of Open Access Journals (Sweden)

    Martin Meier-Schellersheim

    2006-07-01

    Full Text Available The signaling network underlying eukaryotic chemosensing is a complex combination of receptor-mediated transmembrane signals, lipid modifications, protein translocations, and differential activation/deactivation of membrane-bound and cytosolic components. As such, it provides particularly interesting challenges for a combined computational and experimental analysis. We developed a novel detailed molecular signaling model that, when used to simulate the response to the attractant cyclic adenosine monophosphate (cAMP, made nontrivial predictions about Dictyostelium chemosensing. These predictions, including the unexpected existence of spatially asymmetrical, multiphasic, cyclic adenosine monophosphate-induced PTEN translocation and phosphatidylinositol-(3,4,5P3 generation, were experimentally verified by quantitative single-cell microscopy leading us to propose significant modifications to the current standard model for chemoattractant-induced biochemical polarization in this organism. Key to this successful modeling effort was the use of "Simmune," a new software package that supports the facile development and testing of detailed computational representations of cellular behavior. An intuitive interface allows user definition of complex signaling networ