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

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.

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.

Social Network Analysis Identifies Key Participants in Conservation Development.

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

2018-05-01

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

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

International Nuclear Information System (INIS)

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

2013-01-01

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

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

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

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.

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

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Hansen, Michael

2012-01-01

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

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.

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

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Wang, Yulin; Lu, Na; Miao, Hongyu

2016-06-13

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

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

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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.

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

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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.

Orthognathic model surgery with LEGO key-spacer.

Science.gov (United States)

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

2013-12-01

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

Identifying key genes associated with acute myocardial infarction.

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Cheng, Ming; An, Shoukuan; Li, Junquan

2017-10-01

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

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

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

2013-08-01

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

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

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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.

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.

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

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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.

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

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

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

2011-11-07

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

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.

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

Science.gov (United States)

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

2008-04-01

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

Key clinical features to identify girls with CDKL5 mutations.

Science.gov (United States)

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

2008-10-01

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

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

DEFF Research Database (Denmark)

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

2016-01-01

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

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

Science.gov (United States)

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

2016-01-01

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

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.

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.

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

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.

Time to refine key climate policy models

Science.gov (United States)

Barron, Alexander R.

2018-05-01

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

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.

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

Science.gov (United States)

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

2014-01-01

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

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.

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

Science.gov (United States)

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

2016-11-01

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

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...

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.

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.

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

International Nuclear Information System (INIS)

Kesicki, Fabian

2013-01-01

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

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.

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

OpenAIRE

Manzoni, Lisandra Vielmo; Price, Roberto Tom

2003-01-01

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

Identifiability of PBPK Models with Applications to ...

Science.gov (United States)

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

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.

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

Science.gov (United States)

Engel, Julien; Brousseau, Louise; Baraloto, Christopher

2016-01-01

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

Structural Identifiability of Dynamic Systems Biology Models.

Science.gov (United States)

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

2016-10-01

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

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.

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

Directory of Open Access Journals (Sweden)

Chao Su

2016-01-01

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

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.

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

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.

Spatial age-length key modelling using continuation ratio logits

DEFF Research Database (Denmark)

Berg, Casper W.; Kristensen, Kasper

2012-01-01

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

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.

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.

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…

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)

Key performance indicators in hospital based on balanced scorecard model

Directory of Open Access Journals (Sweden)

Hamed Rahimi

2017-01-01

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

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...

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

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.

Numerical rigid plastic modelling of shear capacity of keyed joints

DEFF Research Database (Denmark)

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

2015-01-01

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

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).

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

Science.gov (United States)

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

2015-11-01

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

Modeling key processes causing climate change and variability

Energy Technology Data Exchange (ETDEWEB)

Henriksson, S.

2013-09-01

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

Identifying Key Actors in Heterogeneous Networks

Science.gov (United States)

2017-11-29

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

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

Science.gov (United States)

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

2012-03-01

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

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

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.

Sparse Linear Identifiable Multivariate Modeling

DEFF Research Database (Denmark)

Henao, Ricardo; Winther, Ole

2011-01-01

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

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...

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.

Coherence method of identifying signal noise model

International Nuclear Information System (INIS)

Vavrin, J.

1981-01-01

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

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

Science.gov (United States)

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

2016-01-01

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

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.

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

Science.gov (United States)

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

2006-02-01

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

Human-automation collaboration in manufacturing: identifying key implementation factors

OpenAIRE

Charalambous, George; Fletcher, Sarah; Webb, Philip

2013-01-01

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

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.

Key processes and input parameters for environmental tritium models

International Nuclear Information System (INIS)

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

1994-01-01

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

Key processes and input parameters for environmental tritium models

Energy Technology Data Exchange (ETDEWEB)

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

1994-12-31

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

SUPPLY CHAIN MANAGEMENT – KEY FACTORS

Directory of Open Access Journals (Sweden)

Magdalena Daniela DINU

2014-06-01

Full Text Available This paper exposes Supply Chain Management by its key factors. Briefly, where the Supply Chain Management is treated as strategic part of a company then maintaining both control and influence throughout the entire supply chain are key factors and critical to success. On the other hand, finding the right partner to manage the non-strategic Supply Chains would be another key factor too. To define the most important key factors within Supply Chain Management means a deeply understanding of both Supply Chain’ s components, procedures, workflow, processes and the importance of Supply Chain Management into maximizing company's value. SCORE model able to provide solid information about measuring performance and identifying priorities within Supply Chain Management will help us to understand the key factors by analyzing its elements: Plan, Source, Make, Deliver,Return, Enable. These elements covers all the challenging areas from first to third tier of Supply Chain Management.

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

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.

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.

Key drivers of airline loyalty.

Science.gov (United States)

Dolnicar, Sara; Grabler, Klaus; Grün, Bettina; Kulnig, Anna

2011-10-01

This study investigates drivers of airline loyalty. It contributes to the body of knowledge in the area by investigating loyalty for a number of a priori market segments identified by airline management and by using a method which accounts for the multi-step nature of the airline choice process. The study is based on responses from 687 passengers. Results indicate that, at aggregate level, frequent flyer membership, price, the status of being a national carrier and the reputation of the airline as perceived by friends are the variables which best discriminate between travellers loyal to the airline and those who are not. Differences in drivers of airline loyalty for a number of segments were identified. For example, loyalty programs play a key role for business travellers whereas airline loyalty of leisure travellers is difficult to trace back to single factors. For none of the calculated models satisfaction emerged as a key driver of airline loyalty.

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

Science.gov (United States)

Gautam, Ajay; Pan, Xiaogang

2016-03-01

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

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.

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

OpenAIRE

Brousseau, Louise; Baraloto, Christopher

2016-01-01

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

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

Science.gov (United States)

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

2005-02-01

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

Simple Web-based interactive key development software (WEBiKEY) and an example key for Kuruna (Poaceae: Bambusoideae).

Science.gov (United States)

Attigala, Lakshmi; De Silva, Nuwan I; Clark, Lynn G

2016-04-01

Programs that are user-friendly and freely available for developing Web-based interactive keys are scarce and most of the well-structured applications are relatively expensive. WEBiKEY was developed to enable researchers to easily develop their own Web-based interactive keys with fewer resources. A Web-based multiaccess identification tool (WEBiKEY) was developed that uses freely available Microsoft ASP.NET technologies and an SQL Server database for Windows-based hosting environments. WEBiKEY was tested for its usability with a sample data set, the temperate woody bamboo genus Kuruna (Poaceae). WEBiKEY is freely available to the public and can be used to develop Web-based interactive keys for any group of species. The interactive key we developed for Kuruna using WEBiKEY enables users to visually inspect characteristics of Kuruna and identify an unknown specimen as one of seven possible species in the genus.

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.

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.

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…

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

Science.gov (United States)

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

2017-12-01

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

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

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Music Temitope OBEMBE

2018-03-01

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

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.

Key determinants of managing the marketing asset of global companies

Directory of Open Access Journals (Sweden)

Tatyana Tsygankova

2016-12-01

Full Text Available As a result of organization and summarization of key concepts of evolution of the marketing tools of global companies, the authors determined the role of the marketing assets in the system of modern marketing management (as a dialectically higher stage of development of the analyzed tools, which will allow overcoming the antagonistic contradiction of “P- and C-vectors” of their development. The article identified the optimal set of key elements of the system of marketing assets, which are the brand, customer loyalty, reputation, network cooperation, marketing strategy, internal marketing, marketing information system and marketing innovation. Due to correlation and regression analysis of the impact of each system elements on performance of global companies, the model of the "marketing asset octagon" was built as an integrative management tool. Also, as a result of construction of the said model, the authors identified the most profitable marketing assets, return on investment and development of competencies in the field of efficient management will bring the highest profit to the company. On the basis of summarizing the regional and branch features of managing the disparate elements of the marketing assets of global companies, the key regional and sectoral priorities of formation, development and improvement of existing concepts of the international marketing management were identified, particularly in terms of building an author’s integrative octagon model.

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

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.

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.

Key Clinical Features to Identify Girls with "CDKL5" Mutations

Science.gov (United States)

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

2008-01-01

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

Identification of the Key Fields and Their Key Technical Points of Oncology by Patent Analysis.

Science.gov (United States)

Zhang, Ting; Chen, Juan; Jia, Xiaofeng

2015-01-01

This paper aims to identify the key fields and their key technical points of oncology by patent analysis. Patents of oncology applied from 2006 to 2012 were searched in the Thomson Innovation database. The key fields and their key technical points were determined by analyzing the Derwent Classification (DC) and the International Patent Classification (IPC), respectively. Patent applications in the top ten DC occupied 80% of all the patent applications of oncology, which were the ten fields of oncology to be analyzed. The number of patent applications in these ten fields of oncology was standardized based on patent applications of oncology from 2006 to 2012. For each field, standardization was conducted separately for each of the seven years (2006-2012) and the mean of the seven standardized values was calculated to reflect the relative amount of patent applications in that field; meanwhile, regression analysis using time (year) and the standardized values of patent applications in seven years (2006-2012) was conducted so as to evaluate the trend of patent applications in each field. Two-dimensional quadrant analysis, together with the professional knowledge of oncology, was taken into consideration in determining the key fields of oncology. The fields located in the quadrant with high relative amount or increasing trend of patent applications are identified as key ones. By using the same method, the key technical points in each key field were identified. Altogether 116,820 patents of oncology applied from 2006 to 2012 were retrieved, and four key fields with twenty-nine key technical points were identified, including "natural products and polymers" with nine key technical points, "fermentation industry" with twelve ones, "electrical medical equipment" with four ones, and "diagnosis, surgery" with four ones. The results of this study could provide guidance on the development direction of oncology, and also help researchers broaden innovative ideas and discover new

Setting Organizational Key Performance Indicators in the Precision Machine Industry

Directory of Open Access Journals (Sweden)

Mei-Hsiu Hong

2015-11-01

Full Text Available The aim of this research is to define (or set organizational key performance indicators (KPIs in the precision machine industry using the concept of core competence and the supply chain operations reference (SCOR model. The research is conducted in three steps. In the first step, a benchmarking study is conducted to collect major items of core competence and to group them into main categories in order to form a foundation for the research. In the second step, a case company questionnaire and interviews are conducted to identify the key factors of core competence in the precision machine industry. The analysis is conducted based on four dimensions and hence several analysis rounds are completed. Questionnaire data is analyzed with grey relational analysis (GRA and resulted in 5–6 key factors in each dimension or sub-dimension. Based on the conducted interviews, 13 of these identified key factors are separated into one organization objective, five key factors of core competence and seven key factors of core ability. In the final step, organizational KPIs are defined (or set for the five identified key factors of core competence. The most competitive core abilities for each of the five key factors are established. After that, organizational KPIs are set based on the core abilities within 3 main categories of KPIs (departmental, office grade and hierarchal for each key factor. The developed KPI system based on organizational objectives, core competences, and core abilities allow enterprises to handle dynamic market demand and business environments, as well as changes in overall corporate objectives.

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.

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

Science.gov (United States)

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

2012-07-01

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

Breaking chaotic shift key communication via adaptive key identification

International Nuclear Information System (INIS)

Ren Haipeng; Han Chongzhao; Liu Ding

2008-01-01

This paper proposes an adaptive parameter identification method for breaking chaotic shift key communication from the transmitted signal in public channel. The sensitive dependence property of chaos on parameter mismatch is used for chaos adaptive synchronization and parameter identification. An index function about the synchronization error is defined and conjugate gradient method is used to minimize the index function and to search the transmitter's parameter (key). By using proposed method, secure key is recovered from transmitted signal generated by low dimensional chaos and hyper chaos switching communication. Multi-parameters can also be identified from the transmitted signal with noise

Identifying optimal models to represent biochemical systems.

Directory of Open Access Journals (Sweden)

Mochamad Apri

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

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

Partitioned key-value store with atomic memory operations

Energy Technology Data Exchange (ETDEWEB)

Bent, John M.; Faibish, Sorin; Grider, Gary

2017-02-07

A partitioned key-value store is provided that supports atomic memory operations. A server performs a memory operation in a partitioned key-value store by receiving a request from an application for at least one atomic memory operation, the atomic memory operation comprising a memory address identifier; and, in response to the atomic memory operation, performing one or more of (i) reading a client-side memory location identified by the memory address identifier and storing one or more key-value pairs from the client-side memory location in a local key-value store of the server; and (ii) obtaining one or more key-value pairs from the local key-value store of the server and writing the obtained one or more key-value pairs into the client-side memory location identified by the memory address identifier. The server can perform functions obtained from a client-side memory location and return a result to the client using one or more of the atomic memory operations.

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

Research on Digital Product Modeling Key Technologies of Digital Manufacturing

Institute of Scientific and Technical Information of China (English)

DING Guoping; ZHOU Zude; HU Yefa; ZHAO Liang

2006-01-01

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

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

Science.gov (United States)

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

2016-05-06

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

SARS: Key factors in crisis management.

Science.gov (United States)

Tseng, Hsin-Chao; Chen, Thai-Form; Chou, Shieu-Ming

2005-03-01

This study was conducted at a single hospital selected in Taipei during the SARS (Severe Acute Respiratory Syndrome) outbreak from March to July, 2003 in Taiwan. During this period of time, 104 SARS patients were admitted to the hospital. There were no negative reports related to the selected hospital despite its being located right in the center of an area struck by the epidemic. The purpose of this study was to identify the key factors enabling the hospital to survive SARS unscathed. Data were collected from in-depth interviews with the nursing directors and nursing managers of the SARS units, along with a review of relevant hospital documents. The five key elements identified as survival factors during this SARS crisis are as follows: 1. good control of timing for crisis management, 2. careful decision-making, 3. thorough implementation, 4. effective communication, and 5. trust between management and employees. The results of this study reconfirmed the selected hospital as a model for good crisis management during the SARS epidemic.

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

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

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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

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

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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

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

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Philip Stegmaier

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

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

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

2015-04-01

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

Key Elements of a Successful Drive toward Marketing Strategy Making

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Cann, Cynthia W.; George, Marie A.

2003-01-01

A conceptual model is presented that depicts the relationship between an internal marketing function and an organization's readiness to learn. Learning and marketing orientations are identified as components to marketing strategy making. Key organizational functions, including communication and decision-making, are utilized in a framework for…

Mining key elements for severe convection prediction based on CNN

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Liu, Ming; Pan, Ning; Zhang, Changan; Sha, Hongzhou; Zhang, Bolei; Liu, Liang; Zhang, Meng

2017-04-01

Severe convective weather is a kind of weather disasters accompanied by heavy rainfall, gust wind, hail, etc. Along with recent developments on remote sensing and numerical modeling, there are high-volume and long-term observational and modeling data accumulated to capture massive severe convective events over particular areas and time periods. With those high-volume and high-variety weather data, most of the existing studies and methods carry out the dynamical laws, cause analysis, potential rule study, and prediction enhancement by utilizing the governing equations from fluid dynamics and thermodynamics. In this study, a key-element mining method is proposed for severe convection prediction based on convolution neural network (CNN). It aims to identify the key areas and key elements from huge amounts of historical weather data including conventional measurements, weather radar, satellite, so as numerical modeling and/or reanalysis data. Under this manner, the machine-learning based method could help the human forecasters on their decision-making on operational weather forecasts on severe convective weathers by extracting key information from the real-time and historical weather big data. In this paper, it first utilizes computer vision technology to complete the data preprocessing work of the meteorological variables. Then, it utilizes the information such as radar map and expert knowledge to annotate all images automatically. And finally, by using CNN model, it cloud analyze and evaluate each weather elements (e.g., particular variables, patterns, features, etc.), and identify key areas of those critical weather elements, then help forecasters quickly screen out the key elements from huge amounts of observation data by current weather conditions. Based on the rich weather measurement and model data (up to 10 years) over Fujian province in China, where the severe convective weathers are very active during the summer months, experimental tests are conducted with

Energy Demand Modeling Methodology of Key State Transitions of Turning Processes

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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.

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...

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

Science.gov (United States)

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

2017-07-01

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

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

Science.gov (United States)

Karunanayake, Danesh; Nauta, Margaret M.

2004-01-01

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

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

Science.gov (United States)

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

2018-01-01

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

Setting objectives for managing Key deer

Science.gov (United States)

Diefenbach, Duane R.; Wagner, Tyler; Stauffer, Glenn E.

2014-01-01

The U.S. Fish and Wildlife Service (FWS) is responsible for the protection and management of Key deer (Odocoileus virginianus clavium) because the species is listed as Endangered under the Endangered Species Act (ESA). The purpose of the ESA is to protect and recover imperiled species and the ecosystems upon which they depend. There are a host of actions that could possibly be undertaken to recover the Key deer population, but without a clearly defined problem and stated objectives it can be difficult to compare and evaluate alternative actions. In addition, management goals and the acceptability of alternative management actions are inherently linked to stakeholders, who should be engaged throughout the process of developing a decision framework. The purpose of this project was to engage a representative group of stakeholders to develop a problem statement that captured the management problem the FWS must address with Key deer and identify objectives that, if met, would help solve the problem. In addition, the objectives were organized in a hierarchical manner (i.e., an objectives network) to show how they are linked, and measurable attributes were identified for each objective. We organized a group of people who represented stakeholders interested in and potentially affected by the management of Key deer. These stakeholders included individuals who represented local, state, and federal governments, non-governmental organizations, the general public, and local businesses. This stakeholder group met five full days over the course of an eight-week period to identify objectives that would address the following problem:“As recovery and removal from the Endangered Species list is the purpose of the Endangered Species Act, the U.S. Fish and Wildlife Service needs a management approach that will ensure a sustainable, viable, and healthy Key deer population. Urbanization has affected the behavior and population dynamics of the Key deer and the amount and characteristics

Key principles for adapting South African settlement patterns to climate change

CSIR Research Space (South Africa)

Van Wyk, Llewellyn

2017-06-01

Full Text Available The aim of the paper is to identify key principles for adapting SA settlement patterns to climate change. Section 1 reviews the range of climate-related impacts likely to affect SA settlements using climate change models and scenarios as a context...

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

Science.gov (United States)

Uddin, Raihan; Singh, Shiva M

2017-01-01

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

A data-driven modeling approach to identify disease-specific multi-organ networks driving physiological dysregulation.

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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.

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)

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....

Nonmarket economic user values of the Florida Keys/Key West

Science.gov (United States)

Vernon R. Leeworthy; J. Michael Bowker

1997-01-01

This report provides estimates of the nonmarket economic user values for recreating visitors to the Florida Keys/Key West that participated in natural resource-based activities. Results from estimated travel cost models are presented, including visitor’s responses to prices and estimated per person-trip user values. Annual user values are also calculated and presented...

Key events and their effects on cycling behaviour in Dar-es-Salaam : abstract + powerpoint

OpenAIRE

Nkurunziza, A.; Zuidgeest, M.H.P.; Brussel, M.J.G.; van Maarseveen, M.F.A.M.

2012-01-01

The paper explores key events and investigates their effects on cycling behaviour in the city of Dar-es-Salaam, Tanzania. The objective of the study is to identify specific key events during a person’s life course with a significant effect on change of travel behaviour towards cycling in relation to stage of change. Stage of change is a key construct of the transtheoretical model of behaviour change that defines behavioural readiness (intentions and actions) into six distinct categories (i.e....

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

Science.gov (United States)

Saccomani, Maria Pia

2011-08-01

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

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 ...

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.

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

International Nuclear Information System (INIS)

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

2006-01-01

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

The Effects of Quality Management Practices on Key Results: questionnaires sample for the industry of tourist accommodation in Spain

Directory of Open Access Journals (Sweden)

José Álvarez García

2014-12-01

Full Text Available In this research work, we examine the direct and indirect effects of quality management practices on key results and we identify the relationship between quality practices. To achieve the proposed objective, a structural model was used, taking into account the previous review of the literature, in order to identify the quality practices and causal relationships with the key results. The theoretical model and hypotheses are tested using data collected from a sample of 186 tourist accommodation companies certified with the “Q for Tourist Quality” standard in Spain, from a questionnaire based on quality practices identified in the literature and on the EFQM Model, taking some of the most relevant scales as a reference. The methodology used consists of the application of an Exploratory and Confirmatory Factorial Analysis to validate the scales (reliability, one-dimensionality and validity and define the number of items of each of the measuring instruments of the constructs proposed, to then estimate the causal model proposed, proceeding to test the hypotheses formulated by using the Structural Equation Model (SEM technique. The results achieved support the relationship between quality practices and the direct and positive impact of two of the practices, processes management and quality policy/planning, on the key results. It was also observed that the quality practices that most influence key results are quality policy/planning along with leadership, when considering the total effects (direct and indirect.

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

Science.gov (United States)

Li, Pu; Vu, Quoc Dong

2015-12-14

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

Image encryption using fingerprint as key based on phase retrieval algorithm and public key cryptography

Science.gov (United States)

Zhao, Tieyu; Ran, Qiwen; Yuan, Lin; Chi, Yingying; Ma, Jing

2015-09-01

In this paper, a novel image encryption system with fingerprint used as a secret key is proposed based on the phase retrieval algorithm and RSA public key algorithm. In the system, the encryption keys include the fingerprint and the public key of RSA algorithm, while the decryption keys are the fingerprint and the private key of RSA algorithm. If the users share the fingerprint, then the system will meet the basic agreement of asymmetric cryptography. The system is also applicable for the information authentication. The fingerprint as secret key is used in both the encryption and decryption processes so that the receiver can identify the authenticity of the ciphertext by using the fingerprint in decryption process. Finally, the simulation results show the validity of the encryption scheme and the high robustness against attacks based on the phase retrieval technique.

Key Factors Affecting the Price of Airbnb Listings: A Geographically Weighted Approach

OpenAIRE

Zhihua Zhang; Rachel J. C. Chen; Lee D. Han; Lu Yang

2017-01-01

Airbnb has been increasingly gaining popularity since 2008 due to its low prices and direct interactions with the local community. This paper employed a general linear model (GLM) and a geographically weighted regression (GWR) model to identify the key factors affecting Airbnb listing prices using data sets of 794 samples of Airbnb listings of business units in Metro Nashville, Tennessee. The results showed that the GWR model performs better than the GLM in terms of accuracy and affected vari...

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

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

Structural identifiability of systems biology models: a critical comparison of methods.

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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.

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

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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

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

Directory of Open Access Journals (Sweden)

Javad Shukuhy

2015-02-01

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

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

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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.

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.

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

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

2014-12-01

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

Backup key generation model for one-time password security protocol

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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.

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

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

2015-01-01

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

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

Identified state-space prediction model for aero-optical wavefronts

Science.gov (United States)

Faghihi, Azin; Tesch, Jonathan; Gibson, Steve

2013-07-01

A state-space disturbance model and associated prediction filter for aero-optical wavefronts are described. The model is computed by system identification from a sequence of wavefronts measured in an airborne laboratory. Estimates of the statistics and flow velocity of the wavefront data are shown and can be computed from the matrices in the state-space model without returning to the original data. Numerical results compare velocity values and power spectra computed from the identified state-space model with those computed from the aero-optical data.

Identifying key performance indicators in food technology contract R&D

NARCIS (Netherlands)

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

2013-01-01

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

A model for website analysis and\tconception: the Website Canvas Model applied to\tEldiario.es

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Carles Sanabre Vives

2015-11-01

Full Text Available This article presents the model of ideation and analysis called Website CanvasModel. It allows identifying the key aspects for a website to be successful, and shows how ithas been applied to Eldiario.es. As a result, the key factors prompting the success of thisdigital newspaper have been identified.

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

DEFF Research Database (Denmark)

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

2014-01-01

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

Integrative biology approach identifies cytokine targeting strategies for psoriasis.

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Perera, Gayathri K; Ainali, Chrysanthi; Semenova, Ekaterina; Hundhausen, Christian; Barinaga, Guillermo; Kassen, Deepika; Williams, Andrew E; Mirza, Muddassar M; Balazs, Mercedesz; Wang, Xiaoting; Rodriguez, Robert Sanchez; Alendar, Andrej; Barker, Jonathan; Tsoka, Sophia; Ouyang, Wenjun; Nestle, Frank O

2014-02-12

Cytokines are critical checkpoints of inflammation. The treatment of human autoimmune disease has been revolutionized by targeting inflammatory cytokines as key drivers of disease pathogenesis. Despite this, there exist numerous pitfalls when translating preclinical data into the clinic. We developed an integrative biology approach combining human disease transcriptome data sets with clinically relevant in vivo models in an attempt to bridge this translational gap. We chose interleukin-22 (IL-22) as a model cytokine because of its potentially important proinflammatory role in epithelial tissues. Injection of IL-22 into normal human skin grafts produced marked inflammatory skin changes resembling human psoriasis. Injection of anti-IL-22 monoclonal antibody in a human xenotransplant model of psoriasis, developed specifically to test potential therapeutic candidates, efficiently blocked skin inflammation. Bioinformatic analysis integrating both the IL-22 and anti-IL-22 cytokine transcriptomes and mapping them onto a psoriasis disease gene coexpression network identified key cytokine-dependent hub genes. Using knockout mice and small-molecule blockade, we show that one of these hub genes, the so far unexplored serine/threonine kinase PIM1, is a critical checkpoint for human skin inflammation and potential future therapeutic target in psoriasis. Using in silico integration of human data sets and biological models, we were able to identify a new target in the treatment of psoriasis.

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

Science.gov (United States)

Colaprico, Antonio; Bontempi, Gianluca; Castiglioni, Isabella

2018-01-01

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

Predicting Key Events in the Popularity Evolution of Online Information.

Science.gov (United States)

Hu, Ying; Hu, Changjun; Fu, Shushen; Fang, Mingzhe; Xu, Wenwen

2017-01-01

The popularity of online information generally experiences a rising and falling evolution. This paper considers the "burst", "peak", and "fade" key events together as a representative summary of popularity evolution. We propose a novel prediction task-predicting when popularity undergoes these key events. It is of great importance to know when these three key events occur, because doing so helps recommendation systems, online marketing, and containment of rumors. However, it is very challenging to solve this new prediction task due to two issues. First, popularity evolution has high variation and can follow various patterns, so how can we identify "burst", "peak", and "fade" in different patterns of popularity evolution? Second, these events usually occur in a very short time, so how can we accurately yet promptly predict them? In this paper we address these two issues. To handle the first one, we use a simple moving average to smooth variation, and then a universal method is presented for different patterns to identify the key events in popularity evolution. To deal with the second one, we extract different types of features that may have an impact on the key events, and then a correlation analysis is conducted in the feature selection step to remove irrelevant and redundant features. The remaining features are used to train a machine learning model. The feature selection step improves prediction accuracy, and in order to emphasize prediction promptness, we design a new evaluation metric which considers both accuracy and promptness to evaluate our prediction task. Experimental and comparative results show the superiority of our prediction solution.

Predicting Key Events in the Popularity Evolution of Online Information.

Directory of Open Access Journals (Sweden)

Ying Hu

Full Text Available The popularity of online information generally experiences a rising and falling evolution. This paper considers the "burst", "peak", and "fade" key events together as a representative summary of popularity evolution. We propose a novel prediction task-predicting when popularity undergoes these key events. It is of great importance to know when these three key events occur, because doing so helps recommendation systems, online marketing, and containment of rumors. However, it is very challenging to solve this new prediction task due to two issues. First, popularity evolution has high variation and can follow various patterns, so how can we identify "burst", "peak", and "fade" in different patterns of popularity evolution? Second, these events usually occur in a very short time, so how can we accurately yet promptly predict them? In this paper we address these two issues. To handle the first one, we use a simple moving average to smooth variation, and then a universal method is presented for different patterns to identify the key events in popularity evolution. To deal with the second one, we extract different types of features that may have an impact on the key events, and then a correlation analysis is conducted in the feature selection step to remove irrelevant and redundant features. The remaining features are used to train a machine learning model. The feature selection step improves prediction accuracy, and in order to emphasize prediction promptness, we design a new evaluation metric which considers both accuracy and promptness to evaluate our prediction task. Experimental and comparative results show the superiority of our prediction solution.

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

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

Key Future Engineering Capabilities for Human Capital Retention

Science.gov (United States)

Sivich, Lorrie

Projected record retirements of Baby Boomer generation engineers have been predicted to result in significant losses of mission-critical knowledge in space, national security, and future scientific ventures vital to high-technology corporations. No comprehensive review or analysis of engineering capabilities has been performed to identify threats related to the specific loss of mission-critical knowledge posed by the increasing retirement of tenured engineers. Archival data from a single diversified Fortune 500 aerospace manufacturing engineering company's engineering career database were analyzed to ascertain whether relationships linking future engineering capabilities, engineering disciplines, and years of engineering experience could be identified to define critical knowledge transfer models. Chi square, logistic, and linear regression analyses were used to map patterns of discipline-specific, mission-critical knowledge using archival data of engineers' perceptions of engineering capabilities, key developmental experiences, and knowledge learned from their engineering careers. The results from the study were used to document key engineering future capabilities. The results were then used to develop a proposed human capital retention plan to address specific key knowledge gaps of younger engineers as veteran engineers retire. The potential for social change from this study involves informing leaders of aerospace engineering corporations on how to build better quality mentoring or succession plans to fill the void of lost knowledge from retiring engineers. This plan can secure mission-critical knowledge for younger engineers for current and future product development and increased global competitiveness in the technology market.

Key on demand (KoD) for software-defined optical networks secured by quantum key distribution (QKD).

Science.gov (United States)

Cao, Yuan; Zhao, Yongli; Colman-Meixner, Carlos; Yu, Xiaosong; Zhang, Jie

2017-10-30

Software-defined optical networking (SDON) will become the next generation optical network architecture. However, the optical layer and control layer of SDON are vulnerable to cyberattacks. While, data encryption is an effective method to minimize the negative effects of cyberattacks, secure key interchange is its major challenge which can be addressed by the quantum key distribution (QKD) technique. Hence, in this paper we discuss the integration of QKD with WDM optical networks to secure the SDON architecture by introducing a novel key on demand (KoD) scheme which is enabled by a novel routing, wavelength and key assignment (RWKA) algorithm. The QKD over SDON with KoD model follows two steps to provide security: i) quantum key pools (QKPs) construction for securing the control channels (CChs) and data channels (DChs); ii) the KoD scheme uses RWKA algorithm to allocate and update secret keys for different security requirements. To test our model, we define a security probability index which measures the security gain in CChs and DChs. Simulation results indicate that the security performance of CChs and DChs can be enhanced by provisioning sufficient secret keys in QKPs and performing key-updating considering potential cyberattacks. Also, KoD is beneficial to achieve a positive balance between security requirements and key resource usage.

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...

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

Science.gov (United States)

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

2014-01-01

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

Identification of Key Indicators for Sustainable Construction Materials

Directory of Open Access Journals (Sweden)

Humphrey Danso

2018-01-01

Full Text Available Studies on sustainable construction materials are on the rise with their environmental, social, and economic benefits. This study identifies the key indicators for measuring sustainable construction materials. The design used for the study was that of a survey which relied on a questionnaire with five-point Likert scale to generate data for the analysis. For this purpose, 25 indicators from the three dimensions (environmental, social, and economic identified from the literature were presented to the respondents in a structured questionnaire, and responses were collected and analysed using SPSS. The study identified three key environmental indicators for measuring sustainable construction materials, and these indicators are human toxicity, climate change, and solid waste. Furthermore, adaptability, thermal comfort, local resources, and housing for all were identified as the four key social indicators for sustainable construction materials. In addition, maintenance cost, operational cost, initial cost, long-term savings, and life span were found to be the five key economic indicators for measuring sustainable construction materials. The study therefore suggests that these twelve indicators should be considered in future studies that seek to measure sustainable construction materials.

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.

Key issues

International Nuclear Information System (INIS)

Cook, N.G.W.

1980-01-01

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

Formal Analysis of Key Integrity in PKCS#11

Science.gov (United States)

Falcone, Andrea; Focardi, Riccardo

PKCS#11 is a standard API to cryptographic devices such as smarcards, hardware security modules and usb crypto-tokens. Though widely adopted, this API has been shown to be prone to attacks in which a malicious user gains access to the sensitive keys stored in the devices. In 2008, Delaune, Kremer and Steel proposed a model to formally reason on this kind of attacks. We extend this model to also describe flaws that are based on integrity violations of the stored keys. In particular, we consider scenarios in which a malicious overwriting of keys might fool honest users into using attacker's own keys, while performing sensitive operations. We further enrich the model with a trusted key mechanism ensuring that only controlled, non-tampered keys are used in cryptographic operations, and we show how this modified API prevents the above mentioned key-replacement attacks.

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

Science.gov (United States)

Kim, Seongho; Li, Lang

2014-02-01

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

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.

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.

Identifying the connective strength between model parameters and performance criteria

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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

Evaluation of unique identifiers used as keys to match identical publications in Pure and SciVal – a case study from health science [version 2; referees: 1 approved, 2 approved with reservations

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Heidi Holst Madsen

2016-09-01

Full Text Available Unique identifiers (UID are seen as an effective key to match identical publications across databases or identify duplicates in a database. The objective of the present study is to investigate how well UIDs work as match keys in the integration between Pure and SciVal, based on a case with publications from the health sciences. We evaluate the matching process based on information about coverage, precision, and characteristics of publications matched versus not matched with UIDs as the match keys. We analyze this information to detect errors, if any, in the matching process. As an example we also briefly discuss how publication sets formed by using UIDs as the match keys may affect the bibliometric indicators number of publications, number of citations, and the average number of citations per publication.  The objective is addressed in a literature review and a case study. The literature review shows that only a few studies evaluate how well UIDs work as a match key. From the literature we identify four error types: Duplicate digital object identifiers (DOI, incorrect DOIs in reference lists and databases, DOIs not registered by the database where a bibliometric analysis is performed, and erroneous optical or special character recognition. The case study explores the use of UIDs in the integration between the databases Pure and SciVal. Specifically journal publications in English are matched between the two databases. We find all error types except erroneous optical or special character recognition in our publication sets. In particular the duplicate DOIs constitute a problem for the calculation of bibliometric indicators as both keeping the duplicates to improve the reliability of citation counts and deleting them to improve the reliability of publication counts will distort the calculation of average number of citations per publication. The use of UIDs as a match key in citation linking is implemented in many settings, and the availability of

A Key Factor of the DCF Model Coherency

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Piotr Adamczyk

2017-04-01

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

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

Science.gov (United States)

Villaverde, Alejandro F; Banga, Julio R

2017-11-01

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

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

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Kese Pontes Freitas Alberton

2015-01-01

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

Key aspects of stratospheric tracer modeling using assimilated winds

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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

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

Science.gov (United States)

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

2018-07-01

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

Key Challenges and Opportunities Associated with the Use of In Vitro Models to Detect Human DILI: Integrated Risk Assessment and Mitigation Plans

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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.

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

Science.gov (United States)

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

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

Eight Key Facets of Small Business Management.

Science.gov (United States)

Scott, James Calvert

1980-01-01

Identifies eight key facets of small business management and suggests activities that may be used to assist in their development. The key facets are (1) product or service, (2) competition, (3) marketing strategies, (4) personnel needs, (5) equipment and facility needs, (6) finances, (7) planning, and (8) entrepreneurship. (JOW)

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

Science.gov (United States)

Wu, Hongjie; Li, Haiou; Jiang, Min; Chen, Cheng; Lv, Qiang; Wu, Chuang

2017-01-01

Background. One critical issue in protein three-dimensional structure prediction using either ab initio or comparative modeling involves identification of high-quality protein structural models from generated decoys. Currently, clustering algorithms are widely used to identify near-native models; however, their performance is dependent upon different conformational decoys, and, for some algorithms, the accuracy declines when the decoy population increases. Results. Here, we proposed two enhanced K -means clustering algorithms capable of robustly identifying high-quality protein structural models. The first one employs the clustering algorithm SPICKER to determine the initial centroids for basic K -means clustering ( SK -means), whereas the other employs squared distance to optimize the initial centroids ( K -means++). Our results showed that SK -means and K -means++ were more robust as compared with SPICKER alone, detecting 33 (59%) and 42 (75%) of 56 targets, respectively, with template modeling scores better than or equal to those of SPICKER. Conclusions. We observed that the classic K -means algorithm showed a similar performance to that of SPICKER, which is a widely used algorithm for protein-structure identification. Both SK -means and K -means++ demonstrated substantial improvements relative to results from SPICKER and classical K -means.

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

Security for Key Management Interfaces

OpenAIRE

Kremer , Steve; Steel , Graham; Warinschi , Bogdan

2011-01-01

International audience; We propose a much-needed formal definition of security for cryptographic key management APIs. The advantages of our definition are that it is general, intuitive, and applicable to security proofs in both symbolic and computational models of cryptography. Our definition relies on an idealized API which allows only the most essential functions for generating, exporting and importing keys, and takes into account dynamic corruption of keys. Based on this we can define the ...

Comparison of two model approaches in the Zambezi river basin with regard to model reliability and identifiability

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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

Key Supplier Relationship Management: The Case of Croatian Medium-Sized and Large Manufacturing Companies

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Dario Miočević

2011-06-01

Full Text Available The key supplier relationship management represents a vital organizational process. Companies should pay attention not only to managing customer relationships but also to managing relationships with suppliers in order to perform well. They should identify the extent to which a certain supplier adds value through the procurement process. In this line of reasoning, both theory and practice make a distinction between strategic (key and non-strategic (transactional suppliers. By employing the segmentation of the supply market, companies balance their supplier portfolio and are capable of identifying the key suppliers. They can also develop specific programs and initiatives that are aimed at preserving these relationships. In the empirical part of the paper, a survey was conducted on a sample of 123 medium-sized and large Croatian manufacturing companies. The structural model involving the relationship between the key supplier relationship management and value-oriented purchasing was tested. The results indicate that there is a statistically direct, positive and significant relationship between these two constructs. Likewise, the results stress that a theoretical conceptualization and operationalization of the key supplier relationship management construct is both valid and justified. Finally, the theoretical and practical implications and limitations of this study are offered.

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,...

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.

Key Update Assistant for Resource-Constrained Networks

DEFF Research Database (Denmark)

Yuksel, Ender; Nielson, Hanne Riis; Nielson, Flemming

2012-01-01

developed a push-button solution - powered by stochastic model checking - that network designers can easily benefit from, and it paves the way for consumers to set up key update related security parameters. Key Update Assistant, as we named it, runs necessary model checking operations and determines...

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

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

Science.gov (United States)

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

2018-01-01

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

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...

On the Security of a Simple Three-Party Key Exchange Protocol without Server’s Public Keys

Directory of Open Access Journals (Sweden)

Junghyun Nam

2014-01-01

Full Text Available Authenticated key exchange protocols are of fundamental importance in securing communications and are now extensively deployed for use in various real-world network applications. In this work, we reveal major previously unpublished security vulnerabilities in the password-based authenticated three-party key exchange protocol according to Lee and Hwang (2010: (1 the Lee-Hwang protocol is susceptible to a man-in-the-middle attack and thus fails to achieve implicit key authentication; (2 the protocol cannot protect clients’ passwords against an offline dictionary attack; and (3 the indistinguishability-based security of the protocol can be easily broken even in the presence of a passive adversary. We also propose an improved password-based authenticated three-party key exchange protocol that addresses the security vulnerabilities identified in the Lee-Hwang protocol.

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.

Managing clinical education through understanding key principles.

Science.gov (United States)

Cunningham, Joanne; Wright, Caroline; Baird, Marilyn

2015-01-01

Traditionally, a practicum facilitated the integration of on-campus learning and practical workplace training. Over the past 3 decades, an educative practicum has evolved that promotes clinical reasoning, including analytical and evaluative abilities, through reflective practice. Anecdotal evidence indicates that the delivery of clinical education within medical radiation science entry-level programs continues to vacillate between traditional practicums and the new reflective practicums. To review the literature about clinical education within the medical radiation sciences and identify key principles for practitioners seeking to reflect upon and improve their approach to teaching and supporting students in the clinical environment. A search of 3 major journal databases, Internet searches, and hand searches of reference lists were conducted to identify literature about clinical education in the medical radiation sciences from January 1, 2000, to December 31, 2012. Twenty-two studies were included in this review. The 5 key elements associated with clinical education include the clinical support model and quality, overcoming the theory-practice gap, learning outcomes and reliable and valid assessment, preparing and supporting students, and accommodating differing teaching and learning needs. Many factors influence the quality of clinical education, including the culture of the clinical environment and clinical leadership roles. Several approaches can help students bridge the theory-practice gap, including simulators, role-playing activities, and reflective journals. In addition, clinical educators should use assessment strategies that objectively measure student progress, and they should be positive role models for their students. The successful clinical education of students in the medical radiation sciences depends upon the systems, structures, and people in the clinical environment. Clinical education is accomplished through the collaborative efforts of the

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

OpenAIRE

Raphael, Dennis

2016-01-01

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

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

Science.gov (United States)

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

2018-01-01

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

Controls on the spatial variability of key soil properties: comparing field data with a mechanistic soilscape evolution model

Science.gov (United States)

Vanwalleghem, T.; Román, A.; Giraldez, J. V.

2016-12-01

There is a need for better understanding the processes influencing soil formation and the resulting distribution of soil properties. Soil properties can exhibit strong spatial variation, even at the small catchment scale. Especially soil carbon pools in semi-arid, mountainous areas are highly uncertain because bulk density and stoniness are very heterogeneous and rarely measured explicitly. In this study, we explore the spatial variability in key soil properties (soil carbon stocks, stoniness, bulk density and soil depth) as a function of processes shaping the critical zone (weathering, erosion, soil water fluxes and vegetation patterns). We also compare the potential of a geostatistical versus a mechanistic soil formation model (MILESD) for predicting these key soil properties. Soil core samples were collected from 67 locations at 6 depths. Total soil organic carbon stocks were 4.38 kg m-2. Solar radiation proved to be the key variable controlling soil carbon distribution. Stone content was mostly controlled by slope, indicating the importance of erosion. Spatial distribution of bulk density was found to be highly random. Finally, total carbon stocks were predicted using a random forest model whose main covariates were solar radiation and NDVI. The model predicts carbon stocks that are double as high on north versus south-facing slopes. However, validation showed that these covariates only explained 25% of the variation in the dataset. Apparently, present-day landscape and vegetation properties are not sufficient to fully explain variability in the soil carbon stocks in this complex terrain under natural vegetation. This is attributed to a high spatial variability in bulk density and stoniness, key variables controlling carbon stocks. Similar results were obtained with the mechanistic soil formation model MILESD, suggesting that more complex models might be needed to further explore this high spatial variability.

A Public-key based Information Management Model for Mobile Agents

OpenAIRE

Rodriguez, Diego; Sobrado, Igor

2000-01-01

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

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

Science.gov (United States)

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

2016-01-01

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

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

Directory of Open Access Journals (Sweden)

Victoria C Warwick-Evans

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

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

Directory of Open Access Journals (Sweden)

Shengyong Chen

2012-01-01

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

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 ...

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...

Identifikasi Waste Pada Proses Produksi Key Set Clarinet Dengan Pendekatan Lean Manufacturing

Directory of Open Access Journals (Sweden)

Dana Marsetiya Utama

2016-07-01

Full Text Available This study discusses lean manufacturing concept to identify waste in Key Set Clarinet production process at Yamaha Musical Products Indonesia, Ltd. The lean manufacturing concept is done intially by big picture mapping, waste assessment model (WAM, value stream mapping (VSM and cause and effect diagram respectively. The results show that the dominant waste is defect (26.04%, motion (19.34%, inventory (19.22%, and waiting (13.91%.

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

Identifying key conservation threats to Alpine birds through expert knowledge

Science.gov (United States)

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

2016-01-01

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

Identifying key conservation threats to Alpine birds through expert knowledge

Directory of Open Access Journals (Sweden)

Dan E. Chamberlain

2016-02-01

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

Key Response Planning Factors for the Aftermath of Nuclear Terrorism

Energy Technology Data Exchange (ETDEWEB)

Buddemeier, B R; Dillon, M B

2009-01-21

Despite hundreds of above-ground nuclear tests and data gathered from Hiroshima and Nagasaki, the effects of a ground-level, low-yield nuclear detonation in a modern urban environment are still the subject of considerable scientific debate. Extensive review of nuclear weapon effects studies and discussions with nuclear weapon effects experts from various federal agencies, national laboratories, and technical organizations have identified key issues and bounded some of the unknowns required to support response planning for a low-yield, ground-level nuclear detonation in a modern U.S. city. This study, which is focused primarily upon the hazards posed by radioactive fallout, used detailed fallout predictions from the advanced suite of three-dimensional (3-D) meteorology and plume/fallout models developed at Lawrence Livermore National Laboratory (LLNL), including extensive global Key Response Planning Factors for the Aftermath of Nuclear Terrorism geographical and real-time meteorological databases to support model calculations. This 3-D modeling system provides detailed simulations that account for complex meteorology and terrain effects. The results of initial modeling and analysis were presented to federal, state, and local working groups to obtain critical, broad-based review and feedback on strategy and messaging. This effort involved a diverse set of communities, including New York City, National Capitol Regions, Charlotte, Houston, Portland, and Los Angeles. The largest potential for reducing casualties during the post-detonation response phase comes from reducing exposure to fallout radiation. This can be accomplished through early, adequate sheltering followed by informed, delayed evacuation.B The response challenges to a nuclear detonation must be solved through multiple approaches of public education, planning, and rapid response actions. Because the successful response will require extensive coordination of a large number of organizations, supplemented by

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

A Recommended Set of Key Arctic Indicators

Science.gov (United States)

Stanitski, D.; Druckenmiller, M.; Fetterer, F. M.; Gerst, M.; Intrieri, J. M.; Kenney, M. A.; Meier, W.; Overland, J. E.; Stroeve, J.; Trainor, S.

2017-12-01

The Arctic is an interconnected and environmentally sensitive system of ice, ocean, land, atmosphere, ecosystems, and people. From local to pan-Arctic scales, the area has already undergone major changes in physical and societal systems and will continue at a pace that is greater than twice the global average. Key Arctic indicators can quantify these changes. Indicators serve as the bridge between complex information and policy makers, stakeholders, and the general public, revealing trends and information people need to make important socioeconomic decisions. This presentation evaluates and compiles more than 70 physical, biological, societal and economic indicators into an approachable summary that defines the changing Arctic. We divided indicators into "existing," "in development," "possible," and "aspirational". In preparing a paper on Arctic Indicators for a special issue of the journal Climatic Change, our group established a set of selection criteria to identify indicators to specifically guide decision-makers in their responses to climate change. A goal of the analysis is to select a manageable composite list of recommended indicators based on sustained, reliable data sources with known user communities. The selected list is also based on the development of a conceptual model that identifies components and processes critical to our understanding of the Arctic region. This list of key indicators is designed to inform the plans and priorities of multiple groups such as the U.S. Global Change Research Program (USGCRP), Interagency Arctic Research Policy Committee (IARPC), and the Arctic Council.

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.

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

Science.gov (United States)

Belgasam, Tarek M.; Zbib, Hussein M.

2018-06-01

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

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

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Richard S. Hemler

2000-01-01

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

A Key Event Path Analysis Approach for Integrated Systems

Directory of Open Access Journals (Sweden)

Jingjing Liao

2012-01-01

Full Text Available By studying the key event paths of probabilistic event structure graphs (PESGs, a key event path analysis approach for integrated system models is proposed. According to translation rules concluded from integrated system architecture descriptions, the corresponding PESGs are constructed from the colored Petri Net (CPN models. Then the definitions of cycle event paths, sequence event paths, and key event paths are given. Whereafter based on the statistic results after the simulation of CPN models, key event paths are found out by the sensitive analysis approach. This approach focuses on the logic structures of CPN models, which is reliable and could be the basis of structured analysis for discrete event systems. An example of radar model is given to characterize the application of this approach, and the results are worthy of trust.

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

Science.gov (United States)

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

2015-12-01

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

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

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…

Lean Information Management: Criteria For Selecting Key Performance Indicators At Shop Floor

Science.gov (United States)

Iuga, Maria Virginia; Kifor, Claudiu Vasile; Rosca, Liviu-Ion

2015-07-01

Most successful organizations worldwide use key performance indicators as an important part of their corporate strategy in order to forecast, measure and plan their businesses. Performance metrics vary in their purpose, definition and content. Therefore, the way organizations select what they think are the optimal indicators for their businesses varies from company to company, sometimes even from department to department. This study aims to answer the question of what is the most suitable way to define and select key performance indicators. More than that, it identifies the right criteria to select key performance indicators at shop floor level. This paper contributes to prior research by analysing and comparing previously researched selection criteria and proposes an original six-criteria-model, which caters towards choosing the most adequate KPIs. Furthermore, the authors take the research a step further by further steps to closed research gaps within this field of study.

Key Mechanisms for Employee-Driven Innovation in Governmental Client Organisations

DEFF Research Database (Denmark)

Sørensen, Henrik; Faber, Lene; Wandahl, Søren

2018-01-01

the mechanisms of organisational trust, innovation safety, organisational practices, cultural settings and the recognition and rewards structure to motivate employees. The decision-making procedures should be transparent especially to the idea-owner and the employees involved, and the implementation and putting......In order to ensure that knowledge and ideas are transformed into innovative contributions, a systematic approach is important. The aim of this research was to identify the specific mechanisms that are key to implementing an innovation process model when conducting Employee-driven Innovation...... in a governmental client organisation. The methodological approach was an exploratory case study of a governmental client organisation within the Danish construction industry. The units of analysis were groups of employees and managers within the case organisation. The primary mechanisms identified were...

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

Science.gov (United States)

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

2014-01-01

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

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

Key Mechanisms for Employee-Driven Innovation in Governmental Client Organisations

DEFF Research Database (Denmark)

Sørensen, Henrik; Wandahl, Søren; Faber, Lene

2018-01-01

the mechanisms of organisational trust, innovation safety, organisational practices, cultural settings and the recognition and rewards structure to motivate employees. The decision-making procedures should be transparent especially to the idea-owner and the employees involved, and the implementation and putting......In order to ensure that knowledge and ideas are transformed into innovative contributions, a systematic approach is important. The aim of this research was to identify the specific mechanisms that are key to implementing an innovation process model when conducting Employee-driven Innovation...... into practice should be fast progressed phases in the innovation process....

Drosophila Cancer Models Identify Functional Differences between Ret Fusions.

Science.gov (United States)

Levinson, Sarah; Cagan, Ross L

2016-09-13

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

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

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.

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.

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

DEFF Research Database (Denmark)

Sund, Terje; Iwarsson, Susanne; Brandt, Åse

2015-01-01

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

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.

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

Science.gov (United States)

Francis, Andrew; Moulton, Vincent

2018-06-07

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

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.

On a European collaboration to identify organizational models, potential shortcomings and improvement options in out-of-hours primary health care.

Science.gov (United States)

Leutgeb, Ruediger; Walker, Nicola; Remmen, Roy; Klemenc-Ketis, Zalika; Szecsenyi, Joachim; Laux, Gunter

2014-09-01

Abstract Background: Out-of-hours care (OOHC) provision is an increasingly challenging aspect in the delivery of primary health care services. Although many European countries have implemented organizational models for out-of-hours primary care, which has been traditionally delivered by general practitioners, health care providers throughout Europe are still looking to resolve current challenges in OOHC. It is within this context that the European Research Network for Out-of-Hours Primary Health Care (EurOOHnet) was established in 2010 to investigate the provision of out-of-hours care across European countries, which have diverse political and health care systems. In this paper, we report on the EurOOHnet work related to OOHC organizational models, potential shortcomings and improvement options in out-of-hours primary health care. Needs assessment: The EurOOHnet expert working party proposed that models for OOHC should be reviewed to evaluate the availability and accessibility of OOHC for patients while also seeking ways to make the delivery of care more satisfying for service providers. To move towards resolution of OOHC challenges in primary care, as the first stage, the EurOOHnet expert working party identified the following key needs: clear and uniform definitions of the different OOHC models between different countries; adequate-ideally transnational-definitions of urgency levels and corresponding data; and educational programmes for nurses and doctors (e.g. in the use of a standardized triage system for OOHC). Finally, the need for a modern system of data transfer between different health care providers in regular care and providers in OOHC to prevent information loss was identified.

Optimal input shaping for Fisher identifiability of control-oriented lithium-ion battery models

Science.gov (United States)

Rothenberger, Michael J.

This dissertation examines the fundamental challenge of optimally shaping input trajectories to maximize parameter identifiability of control-oriented lithium-ion battery models. Identifiability is a property from information theory that determines the solvability of parameter estimation for mathematical models using input-output measurements. This dissertation creates a framework that exploits the Fisher information metric to quantify the level of battery parameter identifiability, optimizes this metric through input shaping, and facilitates faster and more accurate estimation. The popularity of lithium-ion batteries is growing significantly in the energy storage domain, especially for stationary and transportation applications. While these cells have excellent power and energy densities, they are plagued with safety and lifespan concerns. These concerns are often resolved in the industry through conservative current and voltage operating limits, which reduce the overall performance and still lack robustness in detecting catastrophic failure modes. New advances in automotive battery management systems mitigate these challenges through the incorporation of model-based control to increase performance, safety, and lifespan. To achieve these goals, model-based control requires accurate parameterization of the battery model. While many groups in the literature study a variety of methods to perform battery parameter estimation, a fundamental issue of poor parameter identifiability remains apparent for lithium-ion battery models. This fundamental challenge of battery identifiability is studied extensively in the literature, and some groups are even approaching the problem of improving the ability to estimate the model parameters. The first approach is to add additional sensors to the battery to gain more information that is used for estimation. The other main approach is to shape the input trajectories to increase the amount of information that can be gained from input

Key Research Issues in Clostridium difficile

Directory of Open Access Journals (Sweden)

George Zhanel

2005-01-01

Full Text Available Clostridium difficile is an emerging pathogen that causes C difficile-associated diarrhea, an important nosocomial infection. Control of this infection remains a challenge, and much needs to be determined about the antimicrobial resistance of the organism, antibiotic stewardship, contamination of the patient environment, and various host factors that determine susceptibility or resistance to infection. A national symposium focusing on C difficile infections, the Clostridium difficile Symposium on Emerging Issues and Research, was hosted on November 23, 2004, by the Department of Medical Microbiology and Infectious Diseases at the University of Manitoba, Winnipeg, Manitoba, in partnership with the Canadian Institutes of Health Research. This symposium, which aimed to summarize key research issues regarding C difficile infections in Canada, had the following objectives: to provide a forum for learning and discussion about C difficile and its impact on the health of Canadians; to identify the key research issues that should be addressed; and to explore potential research funding opportunities and collaboration. The present report summarizes key research issues identified for C difficile infections in Canada by addressing four major themes: diagnosis and surveillance, infection prevention and control, antibiotic stewardship, and clinical management.

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

Science.gov (United States)

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

2016-12-01

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

Structural identifiability analyses of candidate models for in vitro Pitavastatin hepatic uptake.

Science.gov (United States)

Grandjean, Thomas R B; Chappell, Michael J; Yates, James W T; Evans, Neil D

2014-05-01

In this paper a review of the application of four different techniques (a version of the similarity transformation approach for autonomous uncontrolled systems, a non-differential input/output observable normal form approach, the characteristic set differential algebra and a recent algebraic input/output relationship approach) to determine the structural identifiability of certain in vitro nonlinear pharmacokinetic models is provided. The Organic Anion Transporting Polypeptide (OATP) substrate, Pitavastatin, is used as a probe on freshly isolated animal and human hepatocytes. Candidate pharmacokinetic non-linear compartmental models have been derived to characterise the uptake process of Pitavastatin. As a prerequisite to parameter estimation, structural identifiability analyses are performed to establish that all unknown parameters can be identified from the experimental observations available. Copyright © 2013. Published by Elsevier Ireland Ltd.

Key principles for a national clinical decision support knowledge sharing framework: synthesis of insights from leading subject matter experts.

Science.gov (United States)

Kawamoto, Kensaku; Hongsermeier, Tonya; Wright, Adam; Lewis, Janet; Bell, Douglas S; Middleton, Blackford

2013-01-01

To identify key principles for establishing a national clinical decision support (CDS) knowledge sharing framework. As part of an initiative by the US Office of the National Coordinator for Health IT (ONC) to establish a framework for national CDS knowledge sharing, key stakeholders were identified. Stakeholders' viewpoints were obtained through surveys and in-depth interviews, and findings and relevant insights were summarized. Based on these insights, key principles were formulated for establishing a national CDS knowledge sharing framework. Nineteen key stakeholders were recruited, including six executives from electronic health record system vendors, seven executives from knowledge content producers, three executives from healthcare provider organizations, and three additional experts in clinical informatics. Based on these stakeholders' insights, five key principles were identified for effectively sharing CDS knowledge nationally. These principles are (1) prioritize and support the creation and maintenance of a national CDS knowledge sharing framework; (2) facilitate the development of high-value content and tooling, preferably in an open-source manner; (3) accelerate the development or licensing of required, pragmatic standards; (4) acknowledge and address medicolegal liability concerns; and (5) establish a self-sustaining business model. Based on the principles identified, a roadmap for national CDS knowledge sharing was developed through the ONC's Advancing CDS initiative. The study findings may serve as a useful guide for ongoing activities by the ONC and others to establish a national framework for sharing CDS knowledge and improving clinical care.

Key Parameters for Operator Diagnosis of BWR Plant Condition during a Severe Accident

Energy Technology Data Exchange (ETDEWEB)

Clayton, Dwight A [ORNL; Poore III, Willis P [ORNL

2015-01-01

The objective of this research is to examine the key information needed from nuclear power plant instrumentation to guide severe accident management and mitigation for boiling water reactor (BWR) designs (specifically, a BWR/4-Mark I), estimate environmental conditions that the instrumentation will experience during a severe accident, and identify potential gaps in existing instrumentation that may require further research and development. This report notes the key parameters that instrumentation needs to measure to help operators respond to severe accidents. A follow-up report will assess severe accident environmental conditions as estimated by severe accident simulation model analysis for a specific US BWR/4-Mark I plant for those instrumentation systems considered most important for accident management purposes.

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

Indian Academy of Sciences (India)

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

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

Science.gov (United States)

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

2018-01-01

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

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

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…

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 ...

Improving the key biodiversity areas approach for effective conservation planning

CSIR Research Space (South Africa)

Knight, AT

2007-03-01

Full Text Available The key biodiversity areas (KBA) approach aims to identify globally important areas for species conservation. Although a similar methodology has been used successfully to identify important Bird Areas, the authors have identified five limitations...

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.

Quantum hacking: Saturation attack on practical continuous-variable quantum key distribution

Science.gov (United States)

Qin, Hao; Kumar, Rupesh; Alléaume, Romain

2016-07-01

We identify and study a security loophole in continuous-variable quantum key distribution (CVQKD) implementations, related to the imperfect linearity of the homodyne detector. By exploiting this loophole, we propose an active side-channel attack on the Gaussian-modulated coherent-state CVQKD protocol combining an intercept-resend attack with an induced saturation of the homodyne detection on the receiver side (Bob). We show that an attacker can bias the excess noise estimation by displacing the quadratures of the coherent states received by Bob. We propose a saturation model that matches experimental measurements on the homodyne detection and use this model to study the impact of the saturation attack on parameter estimation in CVQKD. We demonstrate that this attack can bias the excess noise estimation beyond the null key threshold for any system parameter, thus leading to a full security break. If we consider an additional criterion imposing that the channel transmission estimation should not be affected by the attack, then the saturation attack can only be launched if the attenuation on the quantum channel is sufficient, corresponding to attenuations larger than approximately 6 dB. We moreover discuss the possible countermeasures against the saturation attack and propose a countermeasure based on Gaussian postselection that can be implemented by classical postprocessing and may allow one to distill the secret key when the raw measurement data are partly saturated.

Water dynamics clue to key residues in protein folding

International Nuclear Information System (INIS)

Gao, Meng; Zhu, Huaiqiu; Yao, Xin-Qiu; She, Zhen-Su

2010-01-01

A computational method independent of experimental protein structure information is proposed to recognize key residues in protein folding, from the study of hydration water dynamics. Based on all-atom molecular dynamics simulation, two key residues are recognized with distinct water dynamical behavior in a folding process of the Trp-cage protein. The identified key residues are shown to play an essential role in both 3D structure and hydrophobic-induced collapse. With observations on hydration water dynamics around key residues, a dynamical pathway of folding can be interpreted.

A bio-inspired methodology of identifying influential nodes in complex networks.

Directory of Open Access Journals (Sweden)

Cai Gao

Full Text Available How to identify influential nodes is a key issue in complex networks. The degree centrality is simple, but is incapable to reflect the global characteristics of networks. Betweenness centrality and closeness centrality do not consider the location of nodes in the networks, and semi-local centrality, leaderRank and pageRank approaches can be only applied in unweighted networks. In this paper, a bio-inspired centrality measure model is proposed, which combines the Physarum centrality with the K-shell index obtained by K-shell decomposition analysis, to identify influential nodes in weighted networks. Then, we use the Susceptible-Infected (SI model to evaluate the performance. Examples and applications are given to demonstrate the adaptivity and efficiency of the proposed method. In addition, the results are compared with existing methods.

Health systems reforms in Singapore: A qualitative study of key stakeholders.

Science.gov (United States)

Ong, Suan Ee; Tyagi, Shilpa; Lim, Jane Mingjie; Chia, Kee Seng; Legido-Quigley, Helena

2018-02-19

In response to a growing chronic disease burden and ageing population, Singapore implemented Regional Health Systems (RHS) in 2008. In January 2017, the MOH announced that the six RHS clusters would be reorganised into three in 2018. This qualitative study sought to identify the health system challenges, opportunities, and ways forward for the implementation of the RHS. We conducted semi-structured interviews with 35 key informants from RHS clusters, government, academia, and private and voluntary sectors. Integration, innovation, and people-centeredness were identified as the key principles of the RHS. The RHS was described as an opportunity to holistically care for a person across the care continuum, address social determinants of health, develop new models of care, and work with social and community partners. Challenges to RHS implementation included difficulties aligning the goals, values, and priorities of multiple actors, the need for better integration across clusters, differing care capabilities and capacities across partners, healthcare financing structures that may not reflect RHS goals, scalability and evaluation of pilot programmes, and disease-centricity, provider-centricity, and medicalisation in health and healthcare. Suggested ways forward included building relationships between actors to facilitate integration; exploring innovative new models of care; clear long-term/scale-up plans for successful pilots; healthcare financing reforms to meet changing patient and population needs; and developing evaluation systems reflective of RHS principles and priorities. Copyright © 2018 Elsevier B.V. All rights reserved.

Key principles to improve programmes and interventions in complementary feeding.

Science.gov (United States)

Lutter, Chessa K; Iannotti, Lora; Creed-Kanashiro, Hilary; Guyon, Agnes; Daelmans, Bernadette; Robert, Rebecca; Haider, Rukhsana

2013-09-01

Although there are some examples of successful complementary feeding programmes to promote healthy growth and prevent stunting at the community level, to date there are few, if any, examples of successful programmes at scale. A lack of systematic process and impact evaluations on pilot projects to generate lessons learned has precluded scaling up of effective programmes. Programmes to effect positive change in nutrition rarely follow systematic planning, implementation, and evaluation (PIE) processes to enhance effectiveness over the long term. As a result a set of programme-oriented key principles to promote healthy growth remains elusive. The purpose of this paper is to fill this gap by proposing a set of principles to improve programmes and interventions to promote healthy growth and development. Identifying such principles for programme success has three requirements: rethinking traditional paradigms used to promote improved infant and young child feeding; ensuring better linkages to delivery platforms; and, improving programming. Following the PIE model for programmes and learning from experiences from four relatively large-scale programmes described in this paper, 10 key principles are identified in the areas of programme planning, programme implementation, programme evaluation, and dissemination, replication, and scaling up. Nonetheless, numerous operational research questions remain, some of which are highlighted in this paper. © 2013 John Wiley & Sons Ltd.

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.

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…

Detector dead-time effects and paralyzability in high-speed quantum key distribution

International Nuclear Information System (INIS)

Rogers, Daniel J; Bienfang, Joshua C; Nakassis, Anastase; Xu Hai; Clark, Charles W

2007-01-01

Recent advances in quantum key distribution (QKD) have given rise to systems that operate at transmission periods significantly shorter than the dead times of their component single-photon detectors. As systems continue to increase in transmission rate, security concerns associated with detector dead times can limit the production rate of sifted bits. We present a model of high-speed QKD in this limit that identifies an optimum transmission rate for a system with given link loss and detector response characteristics

Architectural Building A Public Key Infrastructure Integrated Information Space

Directory of Open Access Journals (Sweden)

Vadim Ivanovich Korolev

2015-10-01

Full Text Available The article keeps under consideration the mattersto apply the cryptographic system having a public key to provide information security and to implya digital signature. It performs the analysis of trust models at the formation of certificates and their use. The article describes the relationships between the trust model and the architecture public key infrastructure. It contains conclusions in respect of the options for building the public key infrastructure for integrated informationspace.

Key properties of expert movement systems in sport : an ecological dynamics perspective.

Science.gov (United States)

Seifert, Ludovic; Button, Chris; Davids, Keith

2013-03-01

This paper identifies key properties of expertise in sport predicated on the performer-environment relationship. Weaknesses of traditional approaches to expert performance, which uniquely focus on the performer and the environment separately, are highlighted by an ecological dynamics perspective. Key properties of expert movement systems include 'multi- and meta-stability', 'adaptive variability', 'redundancy', 'degeneracy' and the 'attunement to affordances'. Empirical research on these expert system properties indicates that skill acquisition does not emerge from the internal representation of declarative and procedural knowledge, or the imitation of expert behaviours to linearly reduce a perceived 'gap' separating movements of beginners and a putative expert model. Rather, expert performance corresponds with the ongoing co-adaptation of an individual's behaviours to dynamically changing, interacting constraints, individually perceived and encountered. The functional role of adaptive movement variability is essential to expert performance in many different sports (involving individuals and teams; ball games and outdoor activities; land and aquatic environments). These key properties signify that, in sport performance, although basic movement patterns need to be acquired by developing athletes, there exists no ideal movement template towards which all learners should aspire, since relatively unique functional movement solutions emerge from the interaction of key constraints.

Identifying suitable sites for Florida panther reintroduction

Science.gov (United States)

Thatcher, Cindy A.; van Manen, Frank T.; Clark, Joseph D.

2006-01-01

A major objective of the 1995 Florida Panther (Puma concolor cory) Recovery Plan is the establishment of 2 additional panther populations within the historic range. Our goal was to identify prospective sites for Florida panther reintroduction within the historic range based on quantitative landscape assessments. First, we delineated 86 panther home ranges using telemetry data collected from 1981 to 2001 in south Florida to develop a Mahalanobis distance (D2) habitat model, using 4 anthropogenic variables and 3 landscape variables mapped at a 500-m resolution. From that analysis, we identified 9 potential reintroduction sites of sufficient size to support a panther population. We then developed a similar D2 model at a higher spatial resolution to quantify the area of favorable panther habitat at each site. To address potential for the population to expand, we calculated the amount of favorable habitat adjacent to each prospective reintroduction site within a range of dispersal distances of female panthers. We then added those totals to the contiguous patches to estimate the total amount of effective panther habitat at each site. Finally, we developed an expert-assisted model to rank and incorporate potentially important habitat variables that were not appropriate for our empirical analysis (e.g., area of public lands, livestock density). Anthropogenic factors heavily influenced both the landscape and the expert-assisted models. Of the 9 areas we identified, the Okefenokee National Wildlife Refuge, Ozark National Forest, and Felsenthal National Wildlife Refuge regions had the highest combination of effective habitat area and expert opinion scores. Sensitivity analyses indicated that variability among key model parameters did not affect the high ranking of those sites. Those sites should be considered as starting points for the field evaluation of potential reintroduction sites.

Identifying best existing practice for characterization modeling in life cycle impact assessment

DEFF Research Database (Denmark)

Hauschild, Michael Zwicky; Goedkoop, Mark; Guinée, Jeroen

2013-01-01

Purpose: Life cycle impact assessment (LCIA) is a field of active development. The last decade has seen prolific publication of new impact assessment methods covering many different impact categories and providing characterization factors that often deviate from each other for the same substance...... and impact. The LCA standard ISO 14044 is rather general and unspecific in its requirements and offers little help to the LCA practitioner who needs to make a choice. With the aim to identify the best among existing characterization models and provide recommendations to the LCA practitioner, a study...... was performed for the Joint Research Centre of the European Commission (JRC). Methods Existing LCIA methods were collected and their individual characterization models identified at both midpoint and endpoint levels and supplemented with other environmental models of potential use for LCIA. No new developments...

Finding the Key Periods for Assimilating HJ-1A/B CCD Data and the WOFOST Model to Evaluate Heavy Metal Stress in Rice.

Science.gov (United States)

Zhao, Shuang; Qian, Xu; Liu, Xiangnan; Xu, Zhao

2018-04-17

Accurately monitoring heavy metal stress in crops is vital for food security and agricultural production. The assimilation of remote sensing images into the World Food Studies (WOFOST) model provides an efficient way to solve this problem. In this study, we aimed at investigating the key periods of the assimilation framework for continuous monitoring of heavy metal stress in rice. The Harris algorithm was used for the leaf area index (LAI) curves to select the key period for an optimized assimilation. To obtain accurate LAI values, the measured dry weight of rice roots (WRT), which have been proven to be the most stress-sensitive indicator of heavy metal stress, were incorporated into the improved WOFOST model. Finally, the key periods, which contain four dominant time points, were used to select remote sensing images for the RS-WOFOST model for continuous monitoring of heavy metal stress. Compared with the key period which contains all the available remote sensing images, the results showed that the optimal key period can significantly improve the time efficiency of the assimilation framework by shortening the model operation time by more than 50%, while maintaining its accuracy. This result is highly significant when monitoring heavy metals in rice on a large-scale. Furthermore, it can also offer a reference for the timing of field measurements in monitoring heavy metal stress in rice.

A Conceptual Model to Identify Intent to Use Chemical-Biological Weapons

Directory of Open Access Journals (Sweden)

Mary Zalesny

2017-10-01

Full Text Available This paper describes a conceptual model to identify and interrelate indicators of intent of non-state actors to use chemical or biological weapons. The model expands on earlier efforts to understand intent to use weapons of mass destruction by building upon well-researched theories of intent and behavior and focusing on a sub-set of weapons of mass destruction (WMD to account for the distinct challenges of employing different types of WMD in violent acts. The conceptual model is presented as a first, critical step in developing a computational model for assessing the potential for groups to use chemical or biological weapons.

Secret-key expansion from covert communication

Science.gov (United States)

Arrazola, Juan Miguel; Amiri, Ryan

2018-02-01

Covert communication allows the transmission of messages in such a way that it is not possible for adversaries to detect that the communication is occurring. This provides protection in situations where knowledge that two parties are talking to each other may be incriminating to them. In this work, we study how covert communication can be used for a different purpose: secret key expansion. First, we show that any message transmitted in a secure covert protocol is also secret and therefore unknown to an adversary. We then propose a covert communication protocol where the amount of key consumed in the protocol is smaller than the transmitted key, thus leading to secure secret key expansion. We derive precise conditions for secret key expansion to occur, showing that it is possible when there are sufficiently low levels of noise for a given security level. We conclude by examining how secret key expansion from covert communication can be performed in a computational security model.

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

Science.gov (United States)

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

2006-01-01

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

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.

A business planning model to identify new safety net clinic locations.

Science.gov (United States)

Langabeer, James; Helton, Jeffrey; DelliFraine, Jami; Dotson, Ebbin; Watts, Carolyn; Love, Karen

2014-01-01

Community health clinics serving the poor and underserved are geographically expanding due to changes in U.S. health care policy. This paper describes the experience of a collaborative alliance of health care providers in a large metropolitan area who develop a conceptual and mathematical decision model to guide decisions on expanding its network of community health clinics. Community stakeholders participated in a collaborative process that defined constructs they deemed important in guiding decisions on the location of community health clinics. This collaboration also defined key variables within each construct. Scores for variables within each construct were then totaled and weighted into a community-specific optimal space planning equation. This analysis relied entirely on secondary data available from published sources. The model built from this collaboration revolved around the constructs of demand, sustainability, and competition. It used publicly available data defining variables within each construct to arrive at an optimal location that maximized demand and sustainability and minimized competition. This is a model that safety net clinic planners and community stakeholders can use to analyze demographic and utilization data to optimize capacity expansion to serve uninsured and Medicaid populations. Communities can use this innovative model to develop a locally relevant clinic location-planning framework.

Modelling the regional application of stakeholder identified land management strategies.

Science.gov (United States)

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

2012-04-01

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

Identifying musical pieces from fMRI data using encoding and decoding models.

Science.gov (United States)

Hoefle, Sebastian; Engel, Annerose; Basilio, Rodrigo; Alluri, Vinoo; Toiviainen, Petri; Cagy, Maurício; Moll, Jorge

2018-02-02

Encoding models can reveal and decode neural representations in the visual and semantic domains. However, a thorough understanding of how distributed information in auditory cortices and temporal evolution of music contribute to model performance is still lacking in the musical domain. We measured fMRI responses during naturalistic music listening and constructed a two-stage approach that first mapped musical features in auditory cortices and then decoded novel musical pieces. We then probed the influence of stimuli duration (number of time points) and spatial extent (number of voxels) on decoding accuracy. Our approach revealed a linear increase in accuracy with duration and a point of optimal model performance for the spatial extent. We further showed that Shannon entropy is a driving factor, boosting accuracy up to 95% for music with highest information content. These findings provide key insights for future decoding and reconstruction algorithms and open new venues for possible clinical applications.

Grouted Connections with Shear Keys

DEFF Research Database (Denmark)

Pedersen, Ronnie; Jørgensen, M. B.; Damkilde, Lars

2012-01-01

This paper presents a finite element model in the software package ABAQUS in which a reliable analysis of grouted pile-to-sleeve connections with shear keys is the particular purpose. The model is calibrated to experimental results and a consistent set of input parameters is estimated so that dif...... that different structural problems can be reproduced successfully....

Safety assessment on the key equipment of coal gasification based on SDG-HAZOP method

Energy Technology Data Exchange (ETDEWEB)

Zhang, B.; Xu, X.; Ma, X.; Wu, C. [Beijing University of Chemical Technology, Beijing (China)

2008-07-15

An example of the coal gasification process was introduced after the explanation of the graphical representation method known as the sign directed graph (SDG). The systematic modeling procedure was also introduced. Firstly, the key variables of the whole system were selected. Then the relationship equations were listed. Finally, the SDG-HAZOP (hazard and operability) model was derived after attaching the abnormal causes and adverse consequences. In order to get a credible SDG model, the model was checked by technicians in the factory. Based on computer-aided analysis, this model can express almost all the dangerous features of the gasification process. It can also reveal the mechanisms of danger propagation, which may effectively help safety engineers to identify potential hazards. 15 refs., 4 figs., 1 tab.

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.

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.

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

Key figures for the regional- and distribution grid

International Nuclear Information System (INIS)

Vikingstad, S.

1996-02-01

In Norway, improving the efficiency of the hydroelectric grid operation is a stated goal of the Energy Act. Several studies have identified potential profits of such improvement. This publication focuses on costs and improvement potentials. Publication of key figures may stimulate grid owners, boards and administrations to improve the operating efficiency of their grids. The publication shows key figures for the regional- and distribution grid and is based on accounting data for 1994. The key figures are divided into: (1) Cost structure: The key figures express the relative contributions of each cost component to the total income of the grid, (2) Costs and physical quantities: The key figures show the cost of delivering the transport services, (3) Physical quantities: The key figures describe the working conditions of the energy utility. It appears that the cost structure of the sector varies considerably. The same is true of the cost related to the delivery of grid services. 30 figs., 6 tabs

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

Science.gov (United States)

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

2014-12-01

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

Identification of Key Residues for Enzymatic Carboxylate Reduction

Directory of Open Access Journals (Sweden)

Holly Stolterfoht

2018-02-01

Full Text Available Carboxylate reductases (CARs, E.C. 1.2.1.30 generate aldehydes from their corresponding carboxylic acid with high selectivity. Little is known about the structure of CARs and their catalytically important amino acid residues. The identification of key residues for carboxylate reduction provides a starting point to gain deeper understanding of enzymatic carboxylate reduction. A multiple sequence alignment of CARs with confirmed activity recently identified in our lab and from the literature revealed a fingerprint of conserved amino acids. We studied the function of conserved residues by multiple sequence alignments and mutational replacements of these residues. In this study, single-site alanine variants of Neurospora crassa CAR were investigated to determine the contribution of conserved residues to the function, expressability or stability of the enzyme. The effect of amino acid replacements was investigated by analyzing enzymatic activity of the variants in vivo and in vitro. Supported by molecular modeling, we interpreted that five of these residues are essential for catalytic activity, or substrate and co-substrate binding. We identified amino acid residues having significant impact on CAR activity. Replacement of His 237, Glu 433, Ser 595, Tyr 844, and Lys 848 by Ala abolish CAR activity, indicating their key role in acid reduction. These results may assist in the functional annotation of CAR coding genes in genomic databases. While some other conserved residues decreased activity or had no significant impact, four residues increased the specific activity of NcCAR variants when replaced by alanine. Finally, we showed that NcCAR wild-type and mutants efficiently reduce aliphatic acids.

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.

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

Key-value store with internal key-value storage interface

Science.gov (United States)

Bent, John M.; Faibish, Sorin; Ting, Dennis P. J.; Tzelnic, Percy; Gupta, Uday; Grider, Gary; Bonnie, David J.

2018-01-16

A key-value store is provided having one or more key-value storage interfaces. A key-value store on at least one compute node comprises a memory for storing a plurality of key-value pairs; and an abstract storage interface comprising a software interface module that communicates with at least one persistent storage device providing a key-value interface for persistent storage of one or more of the plurality of key-value pairs, wherein the software interface module provides the one or more key-value pairs to the at least one persistent storage device in a key-value format. The abstract storage interface optionally processes one or more batch operations on the plurality of key-value pairs. A distributed embodiment for a partitioned key-value store is also provided.

Mapping key antecedents of employee-driven innovations

DEFF Research Database (Denmark)

Smith, Pernille; Ulhøi, John Parm; Kesting, Peter

2012-01-01

Research on employee-driven innovation (EDI) is still in its infancy, and as yet there is no independent body of literature on the topic. The aim of this paper is to review existing insights into the key antecedents of EDI in other research contexts. In particular, we focus on: leader support......, autonomy, collaboration, and organisational norms of exploration. The main contribution of this paper is to discuss how these key antecedents apply to the specific case of EDI and to identify an agenda for new research....

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.

Key Characteristics of Combined Accident including TLOFW accident for PSA Modeling

Energy Technology Data Exchange (ETDEWEB)

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

2015-05-15

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

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

Science.gov (United States)

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

2009-03-01

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

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.

SNP interaction pattern identifier (SIPI)

DEFF Research Database (Denmark)

Lin, Hui Yi; Chen, Dung Tsa; Huang, Po Yu

2017-01-01

Motivation: Testing SNP-SNP interactions is considered as a key for overcoming bottlenecks of genetic association studies. However, related statistical methods for testing SNP-SNP interactions are underdeveloped. Results: We propose the SNP Interaction Pattern Identifier (SIPI), which tests 45...

Chirp investigation in EMLs towards frequency shift keying modulation

DEFF Research Database (Denmark)

Iglesias Olmedo, Miguel; Vegas Olmos, Juan José; Westergren, Urban

2014-01-01

This paper presents a chirp modeling and experimental results that support our vision of enabling frequency shift keying (FSK) exploiting the chirp effect in externally modulated lasers (EMLs).......This paper presents a chirp modeling and experimental results that support our vision of enabling frequency shift keying (FSK) exploiting the chirp effect in externally modulated lasers (EMLs)....

Virtual-optical information security system based on public key infrastructure

Science.gov (United States)

Peng, Xiang; Zhang, Peng; Cai, Lilong; Niu, Hanben

2005-01-01

A virtual-optical based encryption model with the aid of public key infrastructure (PKI) is presented in this paper. The proposed model employs a hybrid architecture in which our previously published encryption method based on virtual-optics scheme (VOS) can be used to encipher and decipher data while an asymmetric algorithm, for example RSA, is applied for enciphering and deciphering the session key(s). The whole information security model is run under the framework of international standard ITU-T X.509 PKI, which is on basis of public-key cryptography and digital signatures. This PKI-based VOS security approach has additional features like confidentiality, authentication, and integrity for the purpose of data encryption under the environment of network. Numerical experiments prove the effectiveness of the method. The security of proposed model is briefly analyzed by examining some possible attacks from the viewpoint of a cryptanalysis.

Nuclear Hybrid Energy System Modeling: RELAP5 Dynamic Coupling Capabilities

Energy Technology Data Exchange (ETDEWEB)

Piyush Sabharwall; Nolan Anderson; Haihua Zhao; Shannon Bragg-Sitton; George Mesina

2012-09-01

The nuclear hybrid energy systems (NHES) research team is currently developing a dynamic simulation of an integrated hybrid energy system. A detailed simulation of proposed NHES architectures will allow initial computational demonstration of a tightly coupled NHES to identify key reactor subsystem requirements, identify candidate reactor technologies for a hybrid system, and identify key challenges to operation of the coupled system. This work will provide a baseline for later coupling of design-specific reactor models through industry collaboration. The modeling capability addressed in this report focuses on the reactor subsystem simulation.

A genetic screen identifies Tor as an interactor of VAPB in a Drosophila model of amyotrophic lateral sclerosis

Directory of Open Access Journals (Sweden)

Senthilkumar Deivasigamani

2014-10-01

Full Text Available Amyotrophic Lateral Sclerosis (ALS is a progressive neurodegenerative disorder characterized by selective death of motor neurons. In 5–10% of the familial cases, the disease is inherited because of mutations. One such mutation, P56S, was identified in human VAPB that behaves in a dominant negative manner, sequestering wild type protein into cytoplasmic inclusions. We have conducted a reverse genetic screen to identify interactors of Drosophila VAPB. We screened 2635 genes and identified 103 interactors, of which 45 were enhancers and 58 were suppressors of VAPB function. Interestingly, the screen identified known ALS loci – TBPH, alsin2 and SOD1. Also identified were genes involved in cellular energetics and homeostasis which were used to build a gene regulatory network of VAPB modifiers. One key modifier identified was Tor, whose knockdown reversed the large bouton phenotype associated with VAP(P58S expression in neurons. A similar reversal was seen by over-expressing Tuberous Sclerosis Complex (Tsc1,2 that negatively regulates TOR signaling as also by reduction of S6K activity. In comparison, the small bouton phenotype associated with VAP(wt expression was reversed with Tsc1 knock down as well as S6K-CA expression. Tor therefore interacts with both VAP(wt and VAP(P58S, but in a contrasting manner. Reversal of VAP(P58S bouton phenotypes in larvae fed with the TOR inhibitor Rapamycin suggests upregulation of TOR signaling in response to VAP(P58S expression. The VAPB network and further mechanistic understanding of interactions with key pathways, such as the TOR cassette, will pave the way for a better understanding of the mechanisms of onset and progression of motor neuron disease.

A genetic screen identifies Tor as an interactor of VAPB in a Drosophila model of amyotrophic lateral sclerosis.

Science.gov (United States)

Deivasigamani, Senthilkumar; Verma, Hemant Kumar; Ueda, Ryu; Ratnaparkhi, Anuradha; Ratnaparkhi, Girish S

2014-10-31

Amyotrophic Lateral Sclerosis (ALS) is a progressive neurodegenerative disorder characterized by selective death of motor neurons. In 5-10% of the familial cases, the disease is inherited because of mutations. One such mutation, P56S, was identified in human VAPB that behaves in a dominant negative manner, sequestering wild type protein into cytoplasmic inclusions. We have conducted a reverse genetic screen to identify interactors of Drosophila VAPB. We screened 2635 genes and identified 103 interactors, of which 45 were enhancers and 58 were suppressors of VAPB function. Interestingly, the screen identified known ALS loci - TBPH, alsin2 and SOD1. Also identified were genes involved in cellular energetics and homeostasis which were used to build a gene regulatory network of VAPB modifiers. One key modifier identified was Tor, whose knockdown reversed the large bouton phenotype associated with VAP(P58S) expression in neurons. A similar reversal was seen by over-expressing Tuberous Sclerosis Complex (Tsc1,2) that negatively regulates TOR signaling as also by reduction of S6K activity. In comparison, the small bouton phenotype associated with VAP(wt) expression was reversed with Tsc1 knock down as well as S6K-CA expression. Tor therefore interacts with both VAP(wt) and VAP(P58S), but in a contrasting manner. Reversal of VAP(P58S) bouton phenotypes in larvae fed with the TOR inhibitor Rapamycin suggests upregulation of TOR signaling in response to VAP(P58S) expression. The VAPB network and further mechanistic understanding of interactions with key pathways, such as the TOR cassette, will pave the way for a better understanding of the mechanisms of onset and progression of motor neuron disease. © 2014. Published by The Company of Biologists Ltd.

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

Inference in partially identified models with many moment inequalities using Lasso

DEFF Research Database (Denmark)

Bugni, Federico A.; Caner, Mehmet; Kock, Anders Bredahl

This paper considers the problem of inference in a partially identified moment (in)equality model with possibly many moment inequalities. Our contribution is to propose a novel two-step new inference method based on the combination of two ideas. On the one hand, our test statistic and critical...

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...

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

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

Physician Appraisals: Key Challenges

Directory of Open Access Journals (Sweden)

Klich Jacek

2017-06-01

Full Text Available The main purpose of the article is to identify key criteria being used for physician appraisals and to find how communication skills of physicians are valued in those appraisals. ScienceDirect and EBSCOhost databases were used for this search. The results show that a physician appraisal is underestimated both theoretically and empirically. The particular gap exists with respect to the communication skills of physicians, which are rarely present in medical training syllabi and physician assessments. The article contributes to the theoretical discourse on physician appraisals and points out at the inconsistency between the high status of physicians as a key hospital resource on the one hand and, on the other hand, at inadequate and poorly researched assessment of their performance with a special emphasis on communication skills. The article may inspire health managers to develop and implement up-to-date assessment forms for physicians and good managerial practices in this respect in hospitals and other health care units.

In Search of Black Swans: Identifying Students at Risk of Failing Licensing Examinations.

Science.gov (United States)

Barber, Cassandra; Hammond, Robert; Gula, Lorne; Tithecott, Gary; Chahine, Saad

2018-03-01

To determine which admissions variables and curricular outcomes are predictive of being at risk of failing the Medical Council of Canada Qualifying Examination Part 1 (MCCQE1), how quickly student risk of failure can be predicted, and to what extent predictive modeling is possible and accurate in estimating future student risk. Data from five graduating cohorts (2011-2015), Schulich School of Medicine & Dentistry, Western University, were collected and analyzed using hierarchical generalized linear models (HGLMs). Area under the receiver operating characteristic curve (AUC) was used to evaluate the accuracy of predictive models and determine whether they could be used to predict future risk, using the 2016 graduating cohort. Four predictive models were developed to predict student risk of failure at admissions, year 1, year 2, and pre-MCCQE1. The HGLM analyses identified gender, MCAT verbal reasoning score, two preclerkship course mean grades, and the year 4 summative objective structured clinical examination score as significant predictors of student risk. The predictive accuracy of the models varied. The pre-MCCQE1 model was the most accurate at predicting a student's risk of failing (AUC 0.66-0.93), while the admissions model was not predictive (AUC 0.25-0.47). Key variables predictive of students at risk were found. The predictive models developed suggest, while it is not possible to identify student risk at admission, we can begin to identify and monitor students within the first year. Using such models, programs may be able to identify and monitor students at risk quantitatively and develop tailored intervention strategies.

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

Science.gov (United States)

Chen, Y.

2017-12-01

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

Key Distribution and Changing Key Cryptosystem Based on Phase Retrieval Algorithm and RSA Public-Key Algorithm

Directory of Open Access Journals (Sweden)

Tieyu Zhao

2015-01-01

Full Text Available The optical image encryption has attracted more and more researchers’ attention, and the various encryption schemes have been proposed. In existing optical cryptosystem, the phase functions or images are usually used as the encryption keys, and it is difficult that the traditional public-key algorithm (such as RSA, ECC, etc. is used to complete large numerical key transfer. In this paper, we propose a key distribution scheme based on the phase retrieval algorithm and the RSA public-key algorithm, which solves the problem for the key distribution in optical image encryption system. Furthermore, we also propose a novel image encryption system based on the key distribution principle. In the system, the different keys can be used in every encryption process, which greatly improves the security of the system.

Key to marine arthropod larvae

Directory of Open Access Journals (Sweden)

John A. Fornshell

2012-03-01

Full Text Available The scope of this key is restricted to the larvae of marine arthropods. The key is based solely on their morphology, patterns of body segmentation, numbers of appendages, and mode of locomotion. An effort has been made to treat all traditionally named larval forms, both planktonic and benthic. It is intended that this key be useful for a researcher working with archived museum specimens and therefore, does not include habitat information as a identifying trait, even though this information is usually available in the archived records. Within the phylum Arthropoda there are two sub-phyla and eleven classes having larval stages in the marineenvironment. Where feasible the original names of the various larval types have been used. Because this nomenclature is less commonly used today compared to the past, the more recent taxonomic affinities are included in parentheses after the original larval name. The key includes the following thirty-four larvae: Branchhiopoda nauplii; Cephalocarida nauplii; Mystacocarida nauplii; trilobite larva; protonymphon; hexapod larvae; Remipedia nauplii; nauplius - Y larvae; Cirripedia nauplii; Ascothoracida nauplii; Ostracoda nauplii; Euphausiacea nauplii; Penaeidea nauplii; Cyclopoida nauplii; Calanoida nauplii; Harpacticoida nauplii;Polyarthra nauplii; cypris larva; eryonecius larva; cypris-Y larva; elapthocaris larvae; mysis larvae; lucifer zoea; acetes zoea; acanthosoma larva; phyllosoma; antizoea larva; anomuran zoea; brachyuran zoea; calyptopis larvae; furcilia larva; crytopia larva; puerulus larva; alima larva.

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...

Using neutral models to identify constraints on low-severity fire regimes.

Science.gov (United States)

Donald McKenzie; Amy E. Hessl; Lara-Karena B. Kellogg

2006-01-01

Climate, topography, fuel loadings, and human activities all affect spatial and temporal patterns of fire occurrence. Because fire is modeled as a stochastic process, for which each fire history is only one realization, a simulation approach is necessary to understand baseline variability, thereby identifying constraints, or forcing functions, that affect fire regimes...

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'…

Key China Energy Statistics 2012

Energy Technology Data Exchange (ETDEWEB)

Levine, Mark [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Fridley, David [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Lu, Hongyou [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Fino-Chen, Cecilia [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

2012-05-01

The China Energy Group at Lawrence Berkeley National Laboratory (LBNL) was established in 1988. Over the years the Group has gained recognition as an authoritative source of China energy statistics through the publication of its China Energy Databook (CED). The Group has published seven editions to date of the CED (http://china.lbl.gov/research/chinaenergy-databook). This handbook summarizes key statistics from the CED and is expressly modeled on the International Energy Agency’s “Key World Energy Statistics” series of publications. The handbook contains timely, clearly-presented data on the supply, transformation, and consumption of all major energy sources.

Key China Energy Statistics 2011

Energy Technology Data Exchange (ETDEWEB)

Levine, Mark [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Fridley, David [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Lu, Hongyou [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Fino-Chen, Cecilia [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

2012-01-15

The China Energy Group at Lawrence Berkeley National Laboratory (LBNL) was established in 1988. Over the years the Group has gained recognition as an authoritative source of China energy statistics through the publication of its China Energy Databook (CED). In 2008 the Group published the Seventh Edition of the CED (http://china.lbl.gov/research/chinaenergy-databook). This handbook summarizes key statistics from the CED and is expressly modeled on the International Energy Agency’s “Key World Energy Statistics” series of publications. The handbook contains timely, clearly-presented data on the supply, transformation, and consumption of all major energy sources.

Identifying and quantifying energy savings on fired plant using low cost modelling techniques

International Nuclear Information System (INIS)

Tucker, Robert; Ward, John

2012-01-01

Research highlights: → Furnace models based on the zone method for radiation calculation are described. → Validated steady-state and transient models have been developed. → We show how these simple models can identify the best options for saving energy. → High emissivity coatings predicted to give performance enhancement on a fired heater. → Optimal heat recovery strategies on a steel reheating furnace are predicted. -- Abstract: Combustion in fired heaters, boilers and furnaces often accounts for the major energy consumption on industrial processes. Small improvements in efficiency can result in large reductions in energy consumption, CO 2 emissions, and operating costs. This paper will describe some useful low cost modelling techniques based on the zone method to help identify energy saving opportunities on high temperature fuel-fired process plant. The zone method has for many decades, been successfully applied to small batch furnaces through to large steel-reheating furnaces, glass tanks, boilers and fired heaters on petrochemical plant. Zone models can simulate both steady-state furnace operation and more complex transient operation typical of a production environment. These models can be used to predict thermal efficiency and performance, and more importantly, to assist in identifying and predicting energy saving opportunities from such measures as: ·Improving air/fuel ratio and temperature controls. ·Improved insulation. ·Use of oxygen or oxygen enrichment. ·Air preheating via flue gas heat recovery. ·Modification to furnace geometry and hearth loading. There is also increasing interest in the application of refractory coatings for increasing surface radiation in fired plant. All of the techniques can yield savings ranging from a few percent upwards and can deliver rapid financial payback, but their evaluation often requires robust and reliable models in order to increase confidence in making financial investment decisions. This paper gives

Identifying and Modeling Dynamic Preference Evolution in Multipurpose Water Resources Systems

Science.gov (United States)

Mason, E.; Giuliani, M.; Castelletti, A.; Amigoni, F.

2018-04-01

Multipurpose water systems are usually operated on a tradeoff of conflicting operating objectives. Under steady state climatic and socioeconomic conditions, such tradeoff is supposed to represent a fair and/or efficient preference. Extreme variability in external forcing might affect water operators' risk aversion and force a change in her/his preference. Properly accounting for these shifts is key to any rigorous retrospective assessment of the operator's behaviors, and to build descriptive models for projecting the future system evolution. In this study, we explore how the selection of different preferences is linked to variations in the external forcing. We argue that preference selection evolves according to recent, extreme variations in system performance: underperforming in one of the objectives pushes the preference toward the harmed objective. To test this assumption, we developed a rational procedure to simulate the operator's preference selection. We map this selection onto a multilateral negotiation, where multiple virtual agents independently optimize different objectives. The agents periodically negotiate a compromise policy for the operation of the system. Agents' attitudes in each negotiation step are determined by the recent system performance measured by the specific objective they maximize. We then propose a numerical model of preference dynamics that implements a concept from cognitive psychology, the availability bias. We test our modeling framework on a synthetic lake operated for flood control and water supply. Results show that our model successfully captures the operator's preference selection and dynamic evolution driven by extreme wet and dry situations.

Identifying Likely Disk-hosting M dwarfs with Disk Detective

Science.gov (United States)

Silverberg, Steven; Wisniewski, John; Kuchner, Marc J.; Disk Detective Collaboration

2018-01-01

M dwarfs are critical targets for exoplanet searches. Debris disks often provide key information as to the formation and evolution of planetary systems around higher-mass stars, alongside the planet themselves. However, less than 300 M dwarf debris disks are known, despite M dwarfs making up 70% of the local neighborhood. The Disk Detective citizen science project has identified over 6000 new potential disk host stars from the AllWISE catalog over the past three years. Here, we present preliminary results of our search for new disk-hosting M dwarfs in the survey. Based on near-infrared color cuts and fitting stellar models to photometry, we have identified over 500 potential new M dwarf disk hosts, nearly doubling the known number of such systems. In this talk, we present our methodology, and outline our ongoing work to confirm systems as M dwarf disks.

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.

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.

Fully device-independent conference key agreement

Science.gov (United States)

Ribeiro, Jérémy; Murta, Gláucia; Wehner, Stephanie

2018-02-01

We present a security analysis of conference key agreement (CKA) in the most adversarial model of device independence (DI). Our protocol can be implemented by any experimental setup that is capable of performing Bell tests [specifically, the Mermin-Ardehali-Belinskii-Klyshko (MABK) inequality], and security can in principle be obtained for any violation of the MABK inequality that detects genuine multipartite entanglement among the N parties involved in the protocol. As our main tool, we derive a direct physical connection between the N -partite MABK inequality and the Clauser-Horne-Shimony-Holt (CHSH) inequality, showing that certain violations of the MABK inequality correspond to a violation of the CHSH inequality between one of the parties and the other N -1 . We compare the asymptotic key rate for device-independent conference key agreement (DICKA) to the case where the parties use N -1 device-independent quantum key distribution protocols in order to generate a common key. We show that for some regime of noise the DICKA protocol leads to better rates.

An SSH key management system: easing the pain of managing key/user/account associations

Science.gov (United States)

Arkhipkin, D.; Betts, W.; Lauret, J.; Shiryaev, A.

2008-07-01

Cyber security requirements for secure access to computing facilities often call for access controls via gatekeepers and the use of two-factor authentication. Using SSH keys to satisfy the two factor authentication requirement has introduced a potentially challenging task of managing the keys and their associations with individual users and user accounts. Approaches for a facility with the simple model of one remote user corresponding to one local user would not work at facilities that require a many-to-many mapping between users and accounts on multiple systems. We will present an SSH key management system we developed, tested and deployed to address the many-to-many dilemma in the environment of the STAR experiment. We will explain its use in an online computing context and explain how it makes possible the management and tracing of group account access spread over many sub-system components (data acquisition, slow controls, trigger, detector instrumentation, etc.) without the use of shared passwords for remote logins.

An SSH key management system: easing the pain of managing key/user/account associations

International Nuclear Information System (INIS)

Arkhipkin, D; Shiryaev, A; Betts, W; Lauret, J

2008-01-01

Cyber security requirements for secure access to computing facilities often call for access controls via gatekeepers and the use of two-factor authentication. Using SSH keys to satisfy the two factor authentication requirement has introduced a potentially challenging task of managing the keys and their associations with individual users and user accounts. Approaches for a facility with the simple model of one remote user corresponding to one local user would not work at facilities that require a many-to-many mapping between users and accounts on multiple systems. We will present an SSH key management system we developed, tested and deployed to address the many-to-many dilemma in the environment of the STAR experiment. We will explain its use in an online computing context and explain how it makes possible the management and tracing of group account access spread over many sub-system components (data acquisition, slow controls, trigger, detector instrumentation, etc.) without the use of shared passwords for remote logins

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.

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...

Key process issues in Cognitive Behavioral Analysis System of Psychotherapy (CBASP): translation of an evidence-based model into clinical practice and training.

Science.gov (United States)

Vivian, Dina; Salwen, Jessica

2013-09-01

Our "desired outcome" in writing this article was to present not only key process issues stemming from the Cognitive Behavioral Analysis System of Psychotherapy (CBASP; McCullough, 2000), but to highlight those therapy maneuvers that we, a "seasoned" clinician/supervisor and a clinical trainee, find most useful in delivering treatment and in conducting supervision. We strongly believe that it is only through the translation of evidence-based therapeutic models, such as CBASP, into effective training that a true integration of science and practice can be obtained. Thus, the congruence of trainer's and trainee's views on what constitute top process issues in therapy is important in evaluating the reliability of a therapy model; with this in mind, we focus on three process issues, as follows: (1) problems are anchored to the "here and now" and to specific situational outcomes; (2) patients are encouraged to identify the role they play in affecting their distressing outcomes and to take responsibility for "fixing" them; and (3) the therapist planfully engages in the process of change via disciplined personal involvement. Research and theory supporting these maneuvers are presented, in conjunction with clinical examples. 2013 APA, all rights reserved

The key kinematic determinants of undulatory underwater swimming at maximal velocity.

Science.gov (United States)

Connaboy, Chris; Naemi, Roozbeh; Brown, Susan; Psycharakis, Stelios; McCabe, Carla; Coleman, Simon; Sanders, Ross

2016-01-01

The optimisation of undulatory underwater swimming is highly important in competitive swimming performance. Nineteen kinematic variables were identified from previous research undertaken to assess undulatory underwater swimming performance. The purpose of the present study was to determine which kinematic variables were key to the production of maximal undulatory underwater swimming velocity. Kinematic data at maximal undulatory underwater swimming velocity were collected from 17 skilled swimmers. A series of separate backward-elimination analysis of covariance models was produced with cycle frequency and cycle length as dependent variables (DVs) and participant as a fixed factor, as including cycle frequency and cycle length would explain 100% of the maximal swimming velocity variance. The covariates identified in the cycle-frequency and cycle-length models were used to form the saturated model for maximal swimming velocity. The final parsimonious model identified three covariates (maximal knee joint angular velocity, maximal ankle angular velocity and knee range of movement) as determinants of the variance in maximal swimming velocity (adjusted-r2 = 0.929). However, when participant was removed as a fixed factor there was a large reduction in explained variance (adjusted r2 = 0.397) and only maximal knee joint angular velocity continued to contribute significantly, highlighting its importance to the production of maximal swimming velocity. The reduction in explained variance suggests an emphasis on inter-individual differences in undulatory underwater swimming technique and/or anthropometry. Future research should examine the efficacy of other anthropometric, kinematic and coordination variables to better understand the production of maximal swimming velocity and consider the importance of individual undulatory underwater swimming techniques when interpreting the data.

Indistinguishability and identifiability of kinetic models for the MurC reaction in peptidoglycan biosynthesis.

Science.gov (United States)

Hattersley, J G; Pérez-Velázquez, J; Chappell, M J; Bearup, D; Roper, D; Dowson, C; Bugg, T; Evans, N D

2011-11-01

An important question in Systems Biology is the design of experiments that enable discrimination between two (or more) competing chemical pathway models or biological mechanisms. In this paper analysis is performed between two different models describing the kinetic mechanism of a three-substrate three-product reaction, namely the MurC reaction in the cytoplasmic phase of peptidoglycan biosynthesis. One model involves ordered substrate binding and ordered release of the three products; the competing model also assumes ordered substrate binding, but with fast release of the three products. The two versions are shown to be distinguishable; however, if standard quasi-steady-state assumptions are made distinguishability cannot be determined. Once model structure uniqueness is ensured the experimenter must determine if it is possible to successfully recover rate constant values given the experiment observations, a process known as structural identifiability. Structural identifiability analysis is carried out for both models to determine which of the unknown reaction parameters can be determined uniquely, or otherwise, from the ideal system outputs. This structural analysis forms an integrated step towards the modelling of the full pathway of the cytoplasmic phase of peptidoglycan biosynthesis. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Methodology for identifying parameters for the TRNSYS model Type 210 - wood pellet stoves and boilers

Energy Technology Data Exchange (ETDEWEB)

Persson, Tomas; Fiedler, Frank; Nordlander, Svante

2006-05-15

This report describes a method how to perform measurements on boilers and stoves and how to identify parameters from the measurements for the boiler/stove-model TRNSYS Type 210. The model can be used for detailed annual system simulations using TRNSYS. Experience from measurements on three different pellet stoves and four boilers were used to develop this methodology. Recommendations for the set up of measurements are given and the required combustion theory for the data evaluation and data preparation are given. The data evaluation showed that the uncertainties are quite large for the measured flue gas flow rate and for boilers and stoves with high fraction of energy going to the water jacket also the calculated heat rate to the room may have large uncertainties. A methodology for the parameter identification process and identified parameters for two different stoves and three boilers are given. Finally the identified models are compared with measured data showing that the model generally agreed well with measured data during both stationary and dynamic conditions.

Scalable Multi-group Key Management for Advanced Metering Infrastructure

OpenAIRE

Benmalek , Mourad; Challal , Yacine; Bouabdallah , Abdelmadjid

2015-01-01

International audience; Advanced Metering Infrastructure (AMI) is composed of systems and networks to incorporate changes for modernizing the electricity grid, reduce peak loads, and meet energy efficiency targets. AMI is a privileged target for security attacks with potentially great damage against infrastructures and privacy. For this reason, Key Management has been identified as one of the most challenging topics in AMI development. In this paper, we propose a new Scalable multi-group key ...

Identifiability of large-scale non-linear dynamic network models applied to the ADM1-case study.

Science.gov (United States)

Nimmegeers, Philippe; Lauwers, Joost; Telen, Dries; Logist, Filip; Impe, Jan Van

2017-06-01

In this work, both the structural and practical identifiability of the Anaerobic Digestion Model no. 1 (ADM1) is investigated, which serves as a relevant case study of large non-linear dynamic network models. The structural identifiability is investigated using the probabilistic algorithm, adapted to deal with the specifics of the case study (i.e., a large-scale non-linear dynamic system of differential and algebraic equations). The practical identifiability is analyzed using a Monte Carlo parameter estimation procedure for a 'non-informative' and 'informative' experiment, which are heuristically designed. The model structure of ADM1 has been modified by replacing parameters by parameter combinations, to provide a generally locally structurally identifiable version of ADM1. This means that in an idealized theoretical situation, the parameters can be estimated accurately. Furthermore, the generally positive structural identifiability results can be explained from the large number of interconnections between the states in the network structure. This interconnectivity, however, is also observed in the parameter estimates, making uncorrelated parameter estimations in practice difficult. Copyright © 2017. Published by Elsevier Inc.

Applying Statistical and Complex Network Methods to Explore the Key Signaling Molecules of Acupuncture Regulating Neuroendocrine-Immune Network

Directory of Open Access Journals (Sweden)

Kuo Zhang

2018-01-01

Full Text Available The mechanisms of acupuncture are still unclear. In order to reveal the regulatory effect of manual acupuncture (MA on the neuroendocrine-immune (NEI network and identify the key signaling molecules during MA modulating NEI network, we used a rat complete Freund’s adjuvant (CFA model to observe the analgesic and anti-inflammatory effect of MA, and, what is more, we used statistical and complex network methods to analyze the data about the expression of 55 common signaling molecules of NEI network in ST36 (Zusanli acupoint, and serum and hind foot pad tissue. The results indicate that MA had significant analgesic, anti-inflammatory effects on CFA rats; the key signaling molecules may play a key role during MA regulating NEI network, but further research is needed.

Manet key management via Mobile Ficlke Key protocol (MFK ...

African Journals Online (AJOL)

Manet key management via Mobile Ficlke Key protocol (MFK) ... Journal of Fundamental and Applied Sciences. Journal Home · ABOUT THIS JOURNAL ... No Abstract. Keywords: MANET; key management scheme; simulation environment ...

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.

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

Prioritize Improvement Opportunities Identified In Self-Assessment Using Multi-Criteria Fuzzy Group Decision

Directory of Open Access Journals (Sweden)

Dr.Ghassem Faraj Pour

2015-05-01

Full Text Available ABSTRACT Efforts to improve the quality are one of the prerequisites for the success of individual companies and for the competitiveness of all whole companies. In the field of improvement and excellence business excellence models answer to the question that what the better organization is what goals and concepts they follow and according to what standards they behave. The EFQM excellence model can be transition from multiplicity to unity of different existing models. The most important approaches of these models are self-assessment and identifying improvement areas in an organization. On the other side organizations which are at lower level of total quality management will encounter so many areas to improve when using this model and implementing of self-improvement. Choosing the most important key problems are always the main challenges and because of resource constraints and strategic goals organizations have to prioritize identified improvement opportunities. This paper introduces a model for prioritizing and choosing the most significant improvement opportunities using the organization Business Excellence team members and because the analysis and decision making atmosphere for excellence team members is not generally complete with accurate information it seems using of fuzzy decision can be very helpful.

Cryptographic Key Management and Critical Risk Assessment

Energy Technology Data Exchange (ETDEWEB)

Abercrombie, Robert K [ORNL

2014-05-01

The Department of Energy Office of Electricity Delivery and Energy Reliability (DOE-OE) CyberSecurity for Energy Delivery Systems (CSEDS) industry led program (DE-FOA-0000359) entitled "Innovation for Increasing CyberSecurity for Energy Delivery Systems (12CSEDS)," awarded a contract to Sypris Electronics LLC to develop a Cryptographic Key Management System for the smart grid (Scalable Key Management Solutions for Critical Infrastructure Protection). Oak Ridge National Laboratory (ORNL) and Sypris Electronics, LLC as a result of that award entered into a CRADA (NFE-11-03562) between ORNL and Sypris Electronics, LLC. ORNL provided its Cyber Security Econometrics System (CSES) as a tool to be modified and used as a metric to address risks and vulnerabilities in the management of cryptographic keys within the Advanced Metering Infrastructure (AMI) domain of the electric sector. ORNL concentrated our analysis on the AMI domain of which the National Electric Sector Cyber security Organization Resource (NESCOR) Working Group 1 (WG1) has documented 29 failure scenarios. The computational infrastructure of this metric involves system stakeholders, security requirements, system components and security threats. To compute this metric, we estimated the stakes that each stakeholder associates with each security requirement, as well as stochastic matrices that represent the probability of a threat to cause a component failure and the probability of a component failure to cause a security requirement violation. We applied this model to estimate the security of the AMI, by leveraging the recently established National Institute of Standards and Technology Interagency Report (NISTIR) 7628 guidelines for smart grid security and the International Electrotechnical Commission (IEC) 63351, Part 9 to identify the life cycle for cryptographic key management, resulting in a vector that assigned to each stakeholder an estimate of their average loss in terms of dollars per day of system

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.

Finding identifiable parameter combinations in nonlinear ODE models and the rational reparameterization of their input-output equations.

Science.gov (United States)

Meshkat, Nicolette; Anderson, Chris; Distefano, Joseph J

2011-09-01

When examining the structural identifiability properties of dynamic system models, some parameters can take on an infinite number of values and yet yield identical input-output data. These parameters and the model are then said to be unidentifiable. Finding identifiable combinations of parameters with which to reparameterize the model provides a means for quantitatively analyzing the model and computing solutions in terms of the combinations. In this paper, we revisit and explore the properties of an algorithm for finding identifiable parameter combinations using Gröbner Bases and prove useful theoretical properties of these parameter combinations. We prove a set of M algebraically independent identifiable parameter combinations can be found using this algorithm and that there exists a unique rational reparameterization of the input-output equations over these parameter combinations. We also demonstrate application of the procedure to a nonlinear biomodel. Copyright © 2011 Elsevier Inc. All rights reserved.

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

Science.gov (United States)

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

2017-08-01

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

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

Science.gov (United States)

Azhoni, Adani; Goyal, Manish Kumar

2018-06-01

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

Simultaneous detection of landmarks and key-frame in cardiac perfusion MRI using a joint spatial-temporal context model

Science.gov (United States)

Lu, Xiaoguang; Xue, Hui; Jolly, Marie-Pierre; Guetter, Christoph; Kellman, Peter; Hsu, Li-Yueh; Arai, Andrew; Zuehlsdorff, Sven; Littmann, Arne; Georgescu, Bogdan; Guehring, Jens

2011-03-01

Cardiac perfusion magnetic resonance imaging (MRI) has proven clinical significance in diagnosis of heart diseases. However, analysis of perfusion data is time-consuming, where automatic detection of anatomic landmarks and key-frames from perfusion MR sequences is helpful for anchoring structures and functional analysis of the heart, leading toward fully automated perfusion analysis. Learning-based object detection methods have demonstrated their capabilities to handle large variations of the object by exploring a local region, i.e., context. Conventional 2D approaches take into account spatial context only. Temporal signals in perfusion data present a strong cue for anchoring. We propose a joint context model to encode both spatial and temporal evidence. In addition, our spatial context is constructed not only based on the landmark of interest, but also the landmarks that are correlated in the neighboring anatomies. A discriminative model is learned through a probabilistic boosting tree. A marginal space learning strategy is applied to efficiently learn and search in a high dimensional parameter space. A fully automatic system is developed to simultaneously detect anatomic landmarks and key frames in both RV and LV from perfusion sequences. The proposed approach was evaluated on a database of 373 cardiac perfusion MRI sequences from 77 patients. Experimental results of a 4-fold cross validation show superior landmark detection accuracies of the proposed joint spatial-temporal approach to the 2D approach that is based on spatial context only. The key-frame identification results are promising.

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.

A Fuzzy Computing Model for Identifying Polarity of Chinese Sentiment Words

Science.gov (United States)

Huang, Yongfeng; Wu, Xian; Li, Xing

2015-01-01

With the spurt of online user-generated contents on web, sentiment analysis has become a very active research issue in data mining and natural language processing. As the most important indicator of sentiment, sentiment words which convey positive and negative polarity are quite instrumental for sentiment analysis. However, most of the existing methods for identifying polarity of sentiment words only consider the positive and negative polarity by the Cantor set, and no attention is paid to the fuzziness of the polarity intensity of sentiment words. In order to improve the performance, we propose a fuzzy computing model to identify the polarity of Chinese sentiment words in this paper. There are three major contributions in this paper. Firstly, we propose a method to compute polarity intensity of sentiment morphemes and sentiment words. Secondly, we construct a fuzzy sentiment classifier and propose two different methods to compute the parameter of the fuzzy classifier. Thirdly, we conduct extensive experiments on four sentiment words datasets and three review datasets, and the experimental results indicate that our model performs better than the state-of-the-art methods. PMID:26106409

Identifying mechanisms that structure ecological communities by snapping model parameters to empirically observed tradeoffs.

Science.gov (United States)

Thomas Clark, Adam; Lehman, Clarence; Tilman, David

2018-04-01

Theory predicts that interspecific tradeoffs are primary determinants of coexistence and community composition. Using information from empirically observed tradeoffs to augment the parametrisation of mechanism-based models should therefore improve model predictions, provided that tradeoffs and mechanisms are chosen correctly. We developed and tested such a model for 35 grassland plant species using monoculture measurements of three species characteristics related to nitrogen uptake and retention, which previous experiments indicate as important at our site. Matching classical theoretical expectations, these characteristics defined a distinct tradeoff surface, and models parameterised with these characteristics closely matched observations from experimental multi-species mixtures. Importantly, predictions improved significantly when we incorporated information from tradeoffs by 'snapping' characteristics to the nearest location on the tradeoff surface, suggesting that the tradeoffs and mechanisms we identify are important determinants of local community structure. This 'snapping' method could therefore constitute a broadly applicable test for identifying influential tradeoffs and mechanisms. © 2018 The Authors. Ecology Letters published by CNRS and John Wiley & Sons Ltd.

Identification of key factors regulating self-renewal and differentiation in EML hematopoietic precursor cells by RNA-sequencing analysis.

Science.gov (United States)

Zong, Shan; Deng, Shuyun; Chen, Kenian; Wu, Jia Qian

2014-11-11

Hematopoietic stem cells (HSCs) are used clinically for transplantation treatment to rebuild a patient's hematopoietic system in many diseases such as leukemia and lymphoma. Elucidating the mechanisms controlling HSCs self-renewal and differentiation is important for application of HSCs for research and clinical uses. However, it is not possible to obtain large quantity of HSCs due to their inability to proliferate in vitro. To overcome this hurdle, we used a mouse bone marrow derived cell line, the EML (Erythroid, Myeloid, and Lymphocytic) cell line, as a model system for this study. RNA-sequencing (RNA-Seq) has been increasingly used to replace microarray for gene expression studies. We report here a detailed method of using RNA-Seq technology to investigate the potential key factors in regulation of EML cell self-renewal and differentiation. The protocol provided in this paper is divided into three parts. The first part explains how to culture EML cells and separate Lin-CD34+ and Lin-CD34- cells. The second part of the protocol offers detailed procedures for total RNA preparation and the subsequent library construction for high-throughput sequencing. The last part describes the method for RNA-Seq data analysis and explains how to use the data to identify differentially expressed transcription factors between Lin-CD34+ and Lin-CD34- cells. The most significantly differentially expressed transcription factors were identified to be the potential key regulators controlling EML cell self-renewal and differentiation. In the discussion section of this paper, we highlight the key steps for successful performance of this experiment. In summary, this paper offers a method of using RNA-Seq technology to identify potential regulators of self-renewal and differentiation in EML cells. The key factors identified are subjected to downstream functional analysis in vitro and in vivo.

Identifying Multiple Populations in M71 using CN

Science.gov (United States)

Gerber, Jeffrey M.; Friel, Eileen D.; Vesperini, Enrico

2018-01-01

It is now well established that globular clusters (GCs) host multiple stellar populations characterized by differences in several light elements. While these populations have been found in nearly all GCs, we still lack an entirely successful model to explain their formation. A key constraint to these models is the detailed pattern of light element abundances seen among the populations; different techniques for identifying these populations probe different elements and do not always yield the same results. We study a large sample of stars in the GC M71 for light elements C and N, using the CN and CH band strength to identify multiple populations. Our measurements come from low-resolution spectroscopy obtained with the WIYN-3.5m telescope for ~150 stars from the tip of the red-giant branch down to the main-sequence turn-off. The large number of stars and broad spatial coverage of our sample (out to ~3.5 half-light radii) allows us to carry out a comprehensive characterization of the multiple populations in M71. We use a combination of the various spectroscopic and photometric indicators to draw a more complete picture of the properties of the populations and to investigate the consistency of classifications using different techniques.

Thoughts on identifiers

CERN Multimedia

CERN. Geneva

2005-01-01

As business processes and information transactions have become an inextricably intertwined with the Web, the importance of assignment, registration, discovery, and maintenance of identifiers has increased. In spite of this, integrated frameworks for managing identifiers have been slow to emerge. Instead, identification systems arise (quite naturally) from immediate business needs without consideration for how they fit into larger information architectures. In addition, many legacy identifier systems further complicate the landscape, making it difficult for content managers to select and deploy identifier systems that meet both the business case and long term information management objectives. This presentation will outline a model for evaluating identifier applications and the functional requirements of the systems necessary to support them. The model is based on a layered analysis of the characteristics of identifier systems, including: * Functional characteristics * Technology * Policy * Business * Social T...

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.

Information Theoretic Secret Key Generation: Structured Codes and Tree Packing

Science.gov (United States)

Nitinawarat, Sirin

2010-01-01

This dissertation deals with a multiterminal source model for secret key generation by multiple network terminals with prior and privileged access to a set of correlated signals complemented by public discussion among themselves. Emphasis is placed on a characterization of secret key capacity, i.e., the largest rate of an achievable secret key,…

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.

Analysing PKCS#11 Key Management APIs with Unbounded Fresh Data

Science.gov (United States)

Fröschle, Sibylle; Steel, Graham

We extend Delaune, Kremer and Steel’s framework for analysis of PKCS#11-based APIs from bounded to unbounded fresh data. We achieve this by: formally defining the notion of an attribute policy; showing that a well-designed API should have a certain class of policy we call complete; showing that APIs with complete policies may be safely abstracted to APIs where the attributes are fixed; and proving that these static APIs can be analysed in a small bounded model such that security properties will hold for the unbounded case. We automate analysis in our framework using the SAT-based security protocol model checker SATMC. We show that a symmetric key management subset of the Eracom PKCS#11 API, used in their ProtectServer product, preserves the secrecy of sensitive keys for unbounded numbers of fresh keys and handles, i.e. pointers to keys. We also show that this API is not robust: if an encryption key is lost to the intruder, SATMC finds an attack whereby all the keys may be compromised.

Dynamic Group Diffie-Hellman Key Exchange under standard assumptions

International Nuclear Information System (INIS)

Bresson, Emmanuel; Chevassut, Olivier; Pointcheval, David

2002-01-01

Authenticated Diffie-Hellman key exchange allows two principals communicating over a public network, and each holding public-private keys, to agree on a shared secret value. In this paper we study the natural extension of this cryptographic problem to a group of principals. We begin from existing formal security models and refine them to incorporate major missing details (e.g., strong-corruption and concurrent sessions). Within this model we define the execution of a protocol for authenticated dynamic group Diffie-Hellman and show that it is provably secure under the decisional Diffie-Hellman assumption. Our security result holds in the standard model and thus provides better security guarantees than previously published results in the random oracle model

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

Science.gov (United States)

Dallas, Tad; Cornelius, Emily

2015-08-17

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

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

DEFF Research Database (Denmark)

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

2009-01-01

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 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...... 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...

Fundamental quantitative security in quantum key generation

International Nuclear Information System (INIS)

Yuen, Horace P.

2010-01-01

We analyze the fundamental security significance of the quantitative criteria on the final generated key K in quantum key generation including the quantum criterion d, the attacker's mutual information on K, and the statistical distance between her distribution on K and the uniform distribution. For operational significance a criterion has to produce a guarantee on the attacker's probability of correctly estimating some portions of K from her measurement, in particular her maximum probability of identifying the whole K. We distinguish between the raw security of K when the attacker just gets at K before it is used in a cryptographic context and its composition security when the attacker may gain further information during its actual use to help get at K. We compare both of these securities of K to those obtainable from conventional key expansion with a symmetric key cipher. It is pointed out that a common belief in the superior security of a quantum generated K is based on an incorrect interpretation of d which cannot be true, and the security significance of d is uncertain. Generally, the quantum key distribution key K has no composition security guarantee and its raw security guarantee from concrete protocols is worse than that of conventional ciphers. Furthermore, for both raw and composition security there is an exponential catch-up problem that would make it difficult to quantitatively improve the security of K in a realistic protocol. Some possible ways to deal with the situation are suggested.

Information security system based on virtual-optics imaging methodology and public key infrastructure

Science.gov (United States)

Peng, Xiang; Zhang, Peng; Cai, Lilong

In this paper, we present a virtual-optical based information security system model with the aid of public-key-infrastructure (PKI) techniques. The proposed model employs a hybrid architecture in which our previously published encryption algorithm based on virtual-optics imaging methodology (VOIM) can be used to encipher and decipher data while an asymmetric algorithm, for example RSA, is applied for enciphering and deciphering the session key(s). For an asymmetric system, given an encryption key, it is computationally infeasible to determine the decryption key and vice versa. The whole information security model is run under the framework of PKI, which is on basis of public-key cryptography and digital signatures. This PKI-based VOIM security approach has additional features like confidentiality, authentication, and integrity for the purpose of data encryption under the environment of network.

Facilitators to Promoting Health in Schools: Is School Health Climate the Key?*

Science.gov (United States)

Lucarelli, Jennifer F.; Alaimo, Katherine; Mang, Ellen; Martin, Caroline; Miles, Richard; Bailey, Deborah; Kelleher, Deanne K.; Drzal, Nicholas B.; Liu, Hui

2017-01-01

BACKGROUND Schools can promote healthy eating in adolescents. This study used a qualitative approach to examine barriers and facilitators to healthy eating in schools. METHODS Case studies were conducted with 8 low-income Michigan middle schools. Interviews were conducted with 1 administrator, the food service director, and 1 member of the coordinated school health team at each school. RESULTS Barriers included budgetary constraints leading to low prioritization of health initiatives; availability of unhealthy competitive foods; and perceptions that students would not eat healthy foods. Schools had made improvements to foods and increased nutrition education. Support from administrators, teamwork among staff, and acknowledging student preferences facilitated positive changes. Schools with a key set of characteristics, (presence of a coordinated school health team, nutrition policies, and a school health champion) made more improvements. CONCLUSIONS The set of key characteristics identified in successful schools may represent a school’s health climate. While models of school climate have been utilized in the educational field in relation to academic outcomes, a health-specific model of school climate would be useful in guiding school health practitioners and researchers and may improve the effectiveness of interventions aimed at improving student dietary intake and other health behaviors. PMID:25099428

Facilitators to promoting health in schools: is school health climate the key?

Science.gov (United States)

Lucarelli, Jennifer F; Alaimo, Katherine; Mang, Ellen; Martin, Caroline; Miles, Richard; Bailey, Deborah; Kelleher, Deanne K; Drzal, Nicholas B; Liu, Hui

2014-02-01

Schools can promote healthy eating in adolescents. This study used a qualitative approach to examine barriers and facilitators to healthy eating in schools. Case studies were conducted with 8 low-income Michigan middle schools. Interviews were conducted with 1 administrator, the food service director, and 1 member of the coordinated school health team at each school. Barriers included budgetary constraints leading to low prioritization of health initiatives; availability of unhealthy competitive foods; and perceptions that students would not eat healthy foods. Schools had made improvements to foods and increased nutrition education. Support from administrators, teamwork among staff, and acknowledging student preferences facilitated positive changes. Schools with a key set of characteristics, (presence of a coordinated school health team, nutrition policies, and a school health champion) made more improvements. The set of key characteristics identified in successful schools may represent a school's health climate. While models of school climate have been utilized in the educational field in relation to academic outcomes, a health-specific model of school climate would be useful in guiding school health practitioners and researchers and may improve the effectiveness of interventions aimed at improving student dietary intake and other health behaviors. © 2014, American School Health Association.

Training tomorrow's global health leaders: applying a transtheoretical model to identify behavior change stages within an intervention for health leadership development.

Science.gov (United States)

Daniels, Joseph; Farquhar, Carey; Nathanson, Neal; Mashalla, Yohana; Petracca, Frances; Desmond, Michelle; Green, Wendy; Davies, Luke; O'Malley, Gabrielle

2014-12-01

Training health professionals in leadership and management skills is a key component of health systems strengthening in low-resource settings. The importance of evaluating the effectiveness of these programs has received increased attention over the past several years, although such evaluations continue to pose significant challenges. This article presents evaluation data from the pilot year of the Afya Bora Fellowship, an African-based training program to increase the leadership capacity of health professionals. Firstly, we describe the goals of the Afya Bora Fellowship. Then, we present an adaptation of the transtheoretical model for behavior change called the Health Leadership Development Model, as an analytical lens to identify and describe evidence of individual leadership behavior change among training participants during and shortly after the pilot year of the program. The Health Leadership Development Model includes the following: pre-contemplation (status quo), contemplation (testing and internalizing leadership), preparation - (moving toward leadership), action (leadership in action), and maintenance (effecting organizational change). We used data from surveys, in-depth interviews, journal entries and course evaluations as data points to populate the Health Leadership Development Model. In the short term, fellows demonstrated increased leadership development during and shortly after the intervention and reflected the contemplation, preparation and action stages of the Health Leadership Development Model. However, expanded interventions and/or additional time may be needed to support behavior change toward the maintenance stages. We conclude that the Health Leadership Development Model is useful for informing health leadership training design and evaluation to contribute to sustainable health organizational change. © The Author(s) 2014.

BUSINESS MODEL IN ELECTRICITY INDUSTRY USING BUSINESS MODEL CANVAS APPROACH; THE CASE OF PT. XYZ

Directory of Open Access Journals (Sweden)

Achmad Arief Wicaksono

2017-01-01

Full Text Available The magnitude of opportunities and project values of electricity system in Indonesia encourages PT. XYZ to develop its business in electrical sector which requires business development strategies. This study aims to identify company's business model using Business Model Canvas approach, formulate business development strategy alternatives, and determine the prioritized business development strategy which is appropriate to the manufacturing business model for PT. XYZ. This study utilized a descriptive approach and the nine elements of the Business Model Canvas. Alternative formulation and priority determination of the strategies were obtained by using Strengths, Weaknesses, Opportunities, Threats (SWOT analysis and pairwise comparison. The results of this study are the improvement of Business Model Canvas on the elements of key resources, key activities, key partners and customer segment. In terms of SWOT analysis on the nine elements of the Business Model Canvas for the first business development, the results show an expansion on the power plant construction project as the main contractor, an increase in sales in its core business in supporting equipment industry of oil and gas,  a development in the second business i.e. an investment in the electricity sector as an independent renewable emery-based power producer. On its first business development, PT. XYZ selected three Business Model Canvas elements which become the priorities of the company i.e. key resources weighing 0.252, key activities weighing 0.240, and key partners weighing 0.231. On its second business development, the company selected three elements to become their the priorities i.e. key partners weighing 0.225, customer segments weighing 0.217, and key resources weighing 0.215.Keywords: business model canvas, SWOT, pairwise comparison, business model

Data Mining and Pattern Recognition Models for Identifying Inherited Diseases: Challenges and Implications

OpenAIRE

Iddamalgoda, Lahiru; Das, Partha S.; Aponso, Achala; Sundararajan, Vijayaraghava S.; Suravajhala, Prashanth; Valadi, Jayaraman K.

2016-01-01

Data mining and pattern recognition methods reveal interesting findings in genetic studies, especially on how the genetic makeup is associated with inherited diseases. Although researchers have proposed various data mining models for biomedical approaches, there remains a challenge in accurately prioritizing the single nucleotide polymorphisms (SNP) associated with the disease. In this commentary, we review the state-of-art data mining and pattern recognition models for identifying inherited ...

Increase in physical activities in kindergarten children with cerebral palsy by employing MaKey-MaKey-based task systems.

Science.gov (United States)

Lin, Chien-Yu; Chang, Yu-Ming

2014-09-01

In this study, we employed Flash- and Scratch-based multimedia by using a MaKey-MaKey-based task system to increase the motivation level of children with cerebral palsy to perform physical activities. MaKey MaKey is a circuit board that converts physical touch to a digital signal, which is interpreted by a computer as a keyboard message. In this study, we used conductive materials to control this interaction. This study followed single-case design using ABAB models in which A indicated the baseline and B indicated the intervention. The experiment period comprised 1 month and a half. The experimental results demonstrated that in the case of two kindergarten children with cerebral palsy, their scores were considerably increased during the intervention phrases. The developmental applications of the results are also discussed. Copyright © 2014 Elsevier Ltd. All rights reserved.

Identifying and Classifying Mobile Business Models Based on Meta-Synthesis Approach

Directory of Open Access Journals (Sweden)

Porrandokht Niroomand

2012-03-01

Full Text Available The appearance of mobile has provided unique opportunities and fields through the development and creation of businesses and has been able to create the new job opportunities. The current research tries to familiarize entrepreneures who are running the businesses especially in the area of mobile services with business models. These business models can familiarize them for implementing the new ideas and designs since they can enter to business market. Searching in many papers shows that there are no propitiated papers and researches that can identify, categorize and analyze the mobile business models. Consequently, this paper involves innovation. The first part of this paper presents the review about the concepts and theories about the different mobile generations, the mobile commerce and business models. Afterwards, 92 models are compared, interpreted, translated and combined using 33 papers, books based on two different criteria that are expert criterion and kind of product criterion. In the classification of models according to models that are presented by experts, the models are classified based on criteria such as business fields, business partners, the rate of dynamism, the kind of activity, the focus areas, the mobile generations, transparency, the type of operator activities, marketing and advertisements. The models that are classified based on the kind of product have been analyzed and classified at four different areas of mobile commerce including the content production, technology (software and hardware, network and synthetic.

An energy security management model using quality function deployment and system dynamics

International Nuclear Information System (INIS)

Shin, Juneseuk; Shin, Wan-Seon; Lee, Changyong

2013-01-01

An energy security management model using quality function deployment (QFD) and system dynamics (SD) is suggested for application in public policymaking in developing economies. Through QFD, experts are guided toward identifying key energy security components, including indicators and policies, and in making these components consistent, focused, and customized for a particular country. Using these components as inputs, we construct an intermediate complex system dynamics model with a minimal number of crucial interactions. Key policies are simulated and evaluated in terms of the improvement of key indicators. Even with little data, our approach provides a coherent, useful, and customized energy security management model to help policymakers more effectively manage national energy security. To demonstrate its advantages, the model is applied to the Korean gas sector as an example. - Highlights: ► We suggest an energy security management model for developing economies. ► We identify a consistent set of key components, indicators and policies by using QFD. ► A coherent and practical system dynamics model based on QFD's output is constructed. ► The model is applied to the Korean gas sector as an example

Key Factors Affecting the Price of Airbnb Listings: A Geographically Weighted Approach

Directory of Open Access Journals (Sweden)

Zhihua Zhang

2017-09-01

Full Text Available Airbnb has been increasingly gaining popularity since 2008 due to its low prices and direct interactions with the local community. This paper employed a general linear model (GLM and a geographically weighted regression (GWR model to identify the key factors affecting Airbnb listing prices using data sets of 794 samples of Airbnb listings of business units in Metro Nashville, Tennessee. The results showed that the GWR model performs better than the GLM in terms of accuracy and affected variable selections. Statistically significant differences varied across regions in Metro Nashville. The coefficients illustrate a decreasing trend while there is an increase in the distance from the listed units to the convention center, which indicates that Airbnb listing prices are more sensitive to the distance from the convention center in the central area than in other areas. These findings can also provide implications for stakeholders such as Airbnb hosts to gain a better understanding of the market situation and formulate a suitable pricing strategy.

Promoter-enhancer interactions identified from Hi-C data using probabilistic models and hierarchical topological domains.

Science.gov (United States)

Ron, Gil; Globerson, Yuval; Moran, Dror; Kaplan, Tommy

2017-12-21

Proximity-ligation methods such as Hi-C allow us to map physical DNA-DNA interactions along the genome, and reveal its organization into topologically associating domains (TADs). As the Hi-C data accumulate, computational methods were developed for identifying domain borders in multiple cell types and organisms. Here, we present PSYCHIC, a computational approach for analyzing Hi-C data and identifying promoter-enhancer interactions. We use a unified probabilistic model to segment the genome into domains, which we then merge hierarchically and fit using a local background model, allowing us to identify over-represented DNA-DNA interactions across the genome. By analyzing the published Hi-C data sets in human and mouse, we identify hundreds of thousands of putative enhancers and their target genes, and compile an extensive genome-wide catalog of gene regulation in human and mouse. As we show, our predictions are highly enriched for ChIP-seq and DNA accessibility data, evolutionary conservation, eQTLs and other DNA-DNA interaction data.

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

Science.gov (United States)

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

Lifelong Learning Key Competence Levels of Graduate Students

Science.gov (United States)

Adabas, Abdurrahman; Kaygin, Hüseyin

2016-01-01

The European Union defines lifelong learning as all activities aimed at improving an individual's knowledge, skills and competences individually, socially or vocationally throughout his/her life. In 2007, eight key competences necessary for lifelong learning were identified by the European Union Education and Culture Commission. These competences…

Identifying Opportunities for Vertical Integration of Biochemistry and Clinical Medicine.

Science.gov (United States)

Wendelberger, Karen J.; Burke, Rebecca; Haas, Arthur L.; Harenwattananon, Marisa; Simpson, Deborah

1998-01-01

Objectives: Retention of basic science knowledge, as judged by National Board of Medical Examiners' (NBME) data, suffers due to lack of apparent relevance and isolation of instruction from clinical application, especially in biochemistry. However, the literature reveals no systematic process for identifying key biochemical concepts and associated clinical conditions. This study systematically identified difficult biochemical concepts and their common clinical conditions as a critical step towards enhancing relevance and retention of biochemistry.Methods: A multi-step/ multiple stakeholder process was used to: (1) identify important biochemistry concepts; (2) determine students' perceptions of concept difficulty; (3) assess biochemistry faculty, student, and clinical teaching scholars' perceived relevance of identified concepts; and (4) identify associated common clinical conditions for relevant and difficult concepts. Surveys and a modified Delphi process were used to gather data, subsequently analyzed using SPSS for Windows.Results: Sixteen key biochemical concepts were identified. Second year medical students rated 14/16 concepts as extremely difficult while fourth year students rated nine concepts as moderately to extremely difficult. On average, each teaching scholar generated common clinical conditions for 6.2 of the 16 concepts, yielding a set of seven critical concepts and associated clinical conditions.Conclusions: Key stakeholders in the instructional process struggle to identify biochemistry concepts that are critical, difficult to learn and associated with common clinical conditions. However, through a systematic process beginning with identification of concepts and associated clinical conditions, relevance of basic science instruction can be enhanced.

Logic programming reveals alteration of key transcription factors in multiple myeloma.

Science.gov (United States)

Miannay, Bertrand; Minvielle, Stéphane; Roux, Olivier; Drouin, Pierre; Avet-Loiseau, Hervé; Guérin-Charbonnel, Catherine; Gouraud, Wilfried; Attal, Michel; Facon, Thierry; Munshi, Nikhil C; Moreau, Philippe; Campion, Loïc; Magrangeas, Florence; Guziolowski, Carito

2017-08-23

Innovative approaches combining regulatory networks (RN) and genomic data are needed to extract biological information for a better understanding of diseases, such as cancer, by improving the identification of entities and thereby leading to potential new therapeutic avenues. In this study, we confronted an automatically generated RN with gene expression profiles (GEP) from a cohort of multiple myeloma (MM) patients and normal individuals using global reasoning on the RN causality to identify key-nodes. We modeled each patient by his or her GEP, the RN and the possible automatically detected repairs needed to establish a coherent flow of the information that explains the logic of the GEP. These repairs could represent cancer mutations leading to GEP variability. With this reasoning, unmeasured protein states can be inferred, and we can simulate the impact of a protein perturbation on the RN behavior to identify therapeutic targets. We showed that JUN/FOS and FOXM1 activities are altered in almost all MM patients and identified two survival markers for MM patients. Our results suggest that JUN/FOS-activation has a strong impact on the RN in view of the whole GEP, whereas FOXM1-activation could be an interesting way to perturb an MM subgroup identified by our method.

E-Commerce Performance. Shopping Cart Key Performance Indicators

Directory of Open Access Journals (Sweden)

Mihaela I. MUNTEAN

2016-01-01

Full Text Available In an e-commerce performance framework is important to identify the key performance indicators that measure success and together provide the greatest context into the business perfor-mance. Shopping carts are an essential part of ecommerce, a minimal set of key performance indicators being the subject of our debate. The theoretical approach is sustained by a case study, an e-shop implemented using PHP and MySQL, for simulating main business processes within the considered performance framework. Our approach opens a perspective for future research using additional indicators in order to properly evaluate the global performance of any e-shop.

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

Science.gov (United States)

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

2012-01-01

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

Antifungal chemical compounds identified using a C. elegans pathogenicity assay.

Directory of Open Access Journals (Sweden)

Julia Breger

2007-02-01

Full Text Available There is an urgent need for the development of new antifungal agents. A facile in vivo model that evaluates libraries of chemical compounds could solve some of the main obstacles in current antifungal discovery. We show that Candida albicans, as well as other Candida species, are ingested by Caenorhabditis elegans and establish a persistent lethal infection in the C. elegans intestinal track. Importantly, key components of Candida pathogenesis in mammals, such as filament formation, are also involved in nematode killing. We devised a Candida-mediated C. elegans assay that allows high-throughput in vivo screening of chemical libraries for antifungal activities, while synchronously screening against toxic compounds. The assay is performed in liquid media using standard 96-well plate technology and allows the study of C. albicans in non-planktonic form. A screen of 1,266 compounds with known pharmaceutical activities identified 15 (approximately 1.2% that prolonged survival of C. albicans-infected nematodes and inhibited in vivo filamentation of C. albicans. Two compounds identified in the screen, caffeic acid phenethyl ester, a major active component of honeybee propolis, and the fluoroquinolone agent enoxacin exhibited antifungal activity in a murine model of candidiasis. The whole-animal C. elegans assay may help to study the molecular basis of C. albicans pathogenesis and identify antifungal compounds that most likely would not be identified by in vitro screens that target fungal growth. Compounds identified in the screen that affect the virulence of Candida in vivo can potentially be used as "probe compounds" and may have antifungal activity against other fungi.

KEY PERFORMANCE INDICATORS DISCLOSURES BY THE INTEGRATED REPORTING

Directory of Open Access Journals (Sweden)

BOBITAN ROXANA-IOANA

2016-02-01

Full Text Available We are in a new era of corporate reporting where the corporate reporting landscape was changed. Institutional and small investors, financial analysts and other key stakeholders are demanding more information about long-term strategies and profitability of companies. Also, the increasing complexity of business models, growing awareness of climate change and resource scarcity and communication are expectations of the role of business in the 21st century and which the key of performance indicators (KPIs is. The companies must change the way these KPIs are being incorporated throughout the annual report and how these are linked to the company’s strategy and business model, their risks and risk mitigation, and their incentive schemes. Regarding this, integrated reporting, continue to gain momentum, the spotlight on the depth, breadth and quality of KPIs being reported will only strengthen. The aim of this discussion paper is to describe which are the most important key performance indicators in sprit of integrating reporting. A good and very known example for the integrated reporting is Philips Electronics, the Dutch healthcare and lighting company, a pioneer that embrace this concept, and the paper make an analysis of the most important key performance indicators.

Key attributes of expert NRL referees.

Science.gov (United States)

Morris, Gavin; O'Connor, Donna

2017-05-01

Experiential knowledge of elite National Rugby League (NRL) referees was investigated to determine the key attributes contributing to expert officiating performance. Fourteen current first-grade NRL referees were asked to identify the key attributes they believed contributed to their expert refereeing performance. The modified Delphi method involved a 3-round process of an initial semi-structured interview followed by 2 questionnaires to reach consensus of opinion. The data revealed 25 attributes that were rated as most important that underpin expert NRL refereeing performance. Results illustrate the significance of the cognitive category, with the top 6 ranked attributes all cognitive skills. Of these, the referees ranked decision-making accuracy as the most important attribute, followed by reading the game, communication, game understanding, game management and knowledge of the rules. Player rapport, positioning and teamwork were the top ranked game skill attributes underpinning performance excellence. Expert referees also highlighted a number of psychological attributes (e.g., concentration, composure and mental toughness) that were significant to performance. There were only 2 physiological attributes (fitness, aerobic endurance) that were identified as significant to elite officiating performance. In summary, expert consensus was attained which successfully provided a hierarchy of the most significant attributes of expert NRL refereeing performance.

An Allometric Modelling Approach to Identify the Optimal Body Shape Associated with, and Differences between Brazilian and Peruvian Youth Motor Performance.

Directory of Open Access Journals (Sweden)

Simonete Silva

Full Text Available Children from developed and developing countries differ in their body size and shape due to marked differences across their life history caused by social, economic and cultural differences which are also linked to their motor performance (MP. We used allometric models to identify size/shape characteristics associated with MP tests between Brazilian and Peruvian schoolchildren. A total of 4,560 subjects, 2,385 girls and 2,175 boys aged 9-15 years were studied. Height and weight were measured; biological maturation was estimated with the maturity offset technique; MP measures included the 12 minute run (12MR, handgrip strength (HG, standing long jump (SLJ and the shuttle run speed (SR tests; physical activity (PA was assessed using the Baecke questionnaire. A multiplicative allometric model was adopted to adjust for body size differences across countries. Reciprocal ponderal index (RPI was found to be the most suitable body shape indicator associated with the 12MR, SLJ, HG and SR performance. A positive maturation offset parameter was also associated with a better performance in SLJ, HG and SR tests. Sex differences were found in all motor tests. Brazilian youth showed better scores in MP than their Peruvian peers, even when controlling for their body size differences The current study identified the key body size associated with four body mass-dependent MP tests. Biological maturation and PA were associated with strength and motor performance. Sex differences were found in all motor tests, as well as across countries favoring Brazilian children even when accounting for their body size/shape differences.

An Allometric Modelling Approach to Identify the Optimal Body Shape Associated with, and Differences between Brazilian and Peruvian Youth Motor Performance.

Science.gov (United States)

Silva, Simonete; Bustamante, Alcibíades; Nevill, Alan; Katzmarzyk, Peter T; Freitas, Duarte; Prista, António; Maia, José

2016-01-01

Children from developed and developing countries differ in their body size and shape due to marked differences across their life history caused by social, economic and cultural differences which are also linked to their motor performance (MP). We used allometric models to identify size/shape characteristics associated with MP tests between Brazilian and Peruvian schoolchildren. A total of 4,560 subjects, 2,385 girls and 2,175 boys aged 9-15 years were studied. Height and weight were measured; biological maturation was estimated with the maturity offset technique; MP measures included the 12 minute run (12MR), handgrip strength (HG), standing long jump (SLJ) and the shuttle run speed (SR) tests; physical activity (PA) was assessed using the Baecke questionnaire. A multiplicative allometric model was adopted to adjust for body size differences across countries. Reciprocal ponderal index (RPI) was found to be the most suitable body shape indicator associated with the 12MR, SLJ, HG and SR performance. A positive maturation offset parameter was also associated with a better performance in SLJ, HG and SR tests. Sex differences were found in all motor tests. Brazilian youth showed better scores in MP than their Peruvian peers, even when controlling for their body size differences The current study identified the key body size associated with four body mass-dependent MP tests. Biological maturation and PA were associated with strength and motor performance. Sex differences were found in all motor tests, as well as across countries favoring Brazilian children even when accounting for their body size/shape differences.

An Allometric Modelling Approach to Identify the Optimal Body Shape Associated with, and Differences between Brazilian and Peruvian Youth Motor Performance

Science.gov (United States)

Silva, Simonete; Bustamante, Alcibíades; Nevill, Alan; Katzmarzyk, Peter T.; Freitas, Duarte; Prista, António; Maia, José

2016-01-01

Children from developed and developing countries differ in their body size and shape due to marked differences across their life history caused by social, economic and cultural differences which are also linked to their motor performance (MP). We used allometric models to identify size/shape characteristics associated with MP tests between Brazilian and Peruvian schoolchildren. A total of 4,560 subjects, 2,385 girls and 2,175 boys aged 9–15 years were studied. Height and weight were measured; biological maturation was estimated with the maturity offset technique; MP measures included the 12 minute run (12MR), handgrip strength (HG), standing long jump (SLJ) and the shuttle run speed (SR) tests; physical activity (PA) was assessed using the Baecke questionnaire. A multiplicative allometric model was adopted to adjust for body size differences across countries. Reciprocal ponderal index (RPI) was found to be the most suitable body shape indicator associated with the 12MR, SLJ, HG and SR performance. A positive maturation offset parameter was also associated with a better performance in SLJ, HG and SR tests. Sex differences were found in all motor tests. Brazilian youth showed better scores in MP than their Peruvian peers, even when controlling for their body size differences The current study identified the key body size associated with four body mass-dependent MP tests. Biological maturation and PA were associated with strength and motor performance. Sex differences were found in all motor tests, as well as across countries favoring Brazilian children even when accounting for their body size/shape differences. PMID:26939118

Certificateless Key-Insulated Generalized Signcryption Scheme without Bilinear Pairings

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Caixue Zhou

2017-01-01

Full Text Available Generalized signcryption (GSC can be applied as an encryption scheme, a signature scheme, or a signcryption scheme with only one algorithm and one key pair. A key-insulated mechanism can resolve the private key exposure problem. To ensure the security of cloud storage, we introduce the key-insulated mechanism into GSC and propose a concrete scheme without bilinear pairings in the certificateless cryptosystem setting. We provide a formal definition and a security model of certificateless key-insulated GSC. Then, we prove that our scheme is confidential under the computational Diffie-Hellman (CDH assumption and unforgeable under the elliptic curve discrete logarithm (EC-DL assumption. Our scheme also supports both random-access key update and secure key update. Finally, we evaluate the efficiency of our scheme and demonstrate that it is highly efficient. Thus, our scheme is more suitable for users who communicate with the cloud using mobile devices.

A System-Level Throughput Model for Quantum Key Distribution

Science.gov (United States)

2015-09-17

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

Using Remote Sensing and High-Resolution Digital Elevation Models to Identify Potential Erosional Hotspots Along River Channels During High Discharge Storm Events

Science.gov (United States)

Orland, E. D.; Amidon, W. H.

2017-12-01

As global warming intensifies, large precipitation events and associated floods are becoming increasingly common. Channel adjustments during floods can occur by both erosion and deposition of sediment, often damaging infrastructure in the process. There is thus a need for predictive models that can help managers identify river reaches that are most prone to adjustment during storms. Because rivers in post-glacial landscapes often flow over a mixture of bedrock and alluvial substrates, the identification of bedrock vs. alluvial channel reaches is an important first step in predicting vulnerability to channel adjustment during flood events, especially because bedrock channels are unlikely to adjust significantly, even during floods. This study develops a semi-automated approach to predicting channel substrate using a high-resolution LiDAR-derived digital elevation model (DEM). The study area is the Middlebury River in Middlebury, VT-a well-studied watershed with a wide variety of channel substrates, including reaches with documented channel adjustments during recent flooding events. Multiple metrics were considered for reference—such as channel width and drainage area—but the study utilized channel slope as a key parameter for identifying morphological variations within the Middlebury River. Using data extracted from the DEM, a power law was fit to selected slope and drainage area values for each branch in order to model idealized slope-drainage area relationships, which were then compared with measured slope-drainage area relationships. Differences in measured slope minus predicted slope (called delta-slope) are shown to help predict river channel substrate. Compared with field observations, higher delta-slope values correlate with more stable, boulder rich channels or bedrock gorges; conversely the lowest delta-slope values correlate with flat, sediment rich alluvial channels. The delta-slope metric thus serves as a reliable first-order predictor of channel

Energy conservation in China: Key provincial sectors at two-digit level

International Nuclear Information System (INIS)

Liao, Hua; Du, Jian; Wei, Yi-Ming

2013-01-01

Highlights: ► We identify the keys for energy conversation across China’s 31 provinces × 65 sectors. ► The results are visualized in map and matrix tables, and easy for use. ► 39 Industrial sectors by province are classified into three categories for conservation. ► There is large energy wasting in the public management sector. ► There are both urban–rural gap and provincial inequality on electricity consumption. - Abstract: In March 2011, China’s central government set a new challenging target of reducing its energy intensity by 16% during 2011–2015, after it had achieved a reduction of 19.1% during 2006–2010. And this new target was assigned to provincial authorities in August 2011. However, China’s provincial energy-economic developments are unbalanced and different provinces have different key sectors for energy conservation. Most previous studies focused on provincial energy efficiency at the aggregate level, or the three-industry level (or one-digit level). However, whether for policy decision or academic research, it is necessary to further subdivide the sectors. In this paper, we use three indicators (Gini Coefficient, energy consumption share and energy intensity) to compare provincial energy conservation potentials at the two-digit sector level. To our knowledge, this paper is the first one to identify the keys for energy conversation across the 31 provinces × 65 sectors. And the results are shown in visualized maps and matrix tables to help identify the key province × sectors for energy conservation easier. This also helps the central and provincial governments to distinguish key sectors when they monitor the energy conservation progress

BIOPROTA Key Issues in Biosphere Aspects of Assessment of the Long-term Impact of Contaminant Releases Associated with Radioactive Waste Management. Theme 2: Task 7: Modelling Processes in the Geosphere Biosphere Interface Zone

International Nuclear Information System (INIS)

Pinedo, P.; Smith, G.; Aguero, A.; Albrecht, A.; Bath, A.; Benhabderrahmane, H.; Van Dorp, F.; Kautsky, U.; Klos, R.; Laciok, A.; Milodowski, T.; Selroos, J.O.; Simon, I.; Texier, D.; Thorne, M.; Willans, M.

2005-01-01

This document reports on BIOPROTA Theme 2, task 7 which investigated modelling processes in the geosphere- biosphere interface zone (GBIZ) during performance assessments. Modelling issues in the treatment of the GBIZ are identified. A large proportion of the identified issues concern modelling radionuclide behaviour in near surface aquifers which are subject to relatively high gradients in chemical and other conditions. Other key issues concern transfer of radionuclides through the unsaturated zone above aquifers, bearing in mind the scope for erosion and variations in the level of the phreatic surface and also the consideration of environmental change. A number of research areas are highlighted that are aimed at addressing each of the identified issues in the treatment of GBIZ. These include (i) Developing of a current statement of continuing problems, and hence clarify and justify the need to do more; (ii) Conducting a review of site investigations as they have been done already, and determine whether they meet performance assessment requirements; (iii) Identifying scenarios and FEPs considered in current treatments; and, (iv) Conducting source-pathway-receptor analysis to demonstrate comprehensiveness of the overall scenario identification process. The objectives of these activities would be to determine the potential to reduce uncertainties and/or conservative assumptions in assessment of radionuclide transfer from the geosphere to biosphere domains, taking account of environmental change; and to develop guidance on site-characterisation needs at different types of site, as regards the near-surface features. (Author) 23 refs

BIOPROTA Key Issues in Biosphere Aspects of Assessment of the Long-term Impact of Contaminant Releases Associated with Radioactive Waste Management Theme 2: Task 7:Modelling Processes in the Geosphere Biosphere Interface Zone

Energy Technology Data Exchange (ETDEWEB)

Pinedo, P.; Smith, G.; Aguero, A.; Albrecht, A.; Bath, A.; Benhabderrahmane, H.; Van Dorp, F.; Kautsky, U.; Klos, R.; Laciok, A.; Milodowski, T.; Selroos, J.O.; Simon, I.; Texier, D.; Thorne, M.; Willans, M.

2005-07-01

This document reports on BIOPROTA Theme 2, task 7 which investigated modelling processes in the geosphere- biosphere interface zone (GBIZ) during performance assessments. Modelling issues in the treatment of the GBIZ are identified. A large proportion of the identified issues concern modelling radionuclide behaviour in near surface aquifers which are subject to relatively high gradients in chemical and other conditions. Other key issues concern transfer of radionuclides through the unsaturated zone above aquifers, bearing in mind the scope for erosion and variations in the level of the phreatic surface and also the consideration of environmental change. A number of research areas are highlighted that are aimed at addressing each of the identified issues in the treatment of GBIZ. These include (i) Developing of a current statement of continuing problems, and hence clarify and justify the need to do more; (ii) Conducting a review of site investigations as they have been done already, and determine whether they meet performance assessment requirements; (iii) Identifying scenarios and FEPs considered in current treatments; and, (iv) Conducting source-pathway-receptor analysis to demonstrate comprehensiveness of the overall scenario identification process. The objectives of these activities would be to determine the potential to reduce uncertainties and/or conservative assumptions in assessment of radionuclide transfer from the geosphere to biosphere domains, taking account of environmental change; and to develop guidance on site-characterisation needs at different types of site, as regards the near-surface features. (Author) 23 refs.

Key Features of the Manufacturing Vision Development Process

DEFF Research Database (Denmark)

Dukovska-Popovska, Iskra; Riis, Jens Ove; Boer, Harry

2005-01-01

of action research. The methodology recommends wide participation of people from different hierarchical and functional positions, who engage in a relatively short, playful and creative process and come up with a vision (concept) for the future manufacturing system in the company. Based on three case studies......This paper discusses the key features of the process of Manufacturing Vision Development, a process that enables companies to develop their future manufacturing concept. The basis for the process is a generic five-phase methodology (Riis and Johansen 2003) developed as a result of ten years...... of companies going through the initial phases of the methodology, this research identified the key features of the Manufacturing Vision Development process. The paper elaborates the key features by defining them, discussing how and when they can appear, and how they influence the process....

Tumor xenograft modeling identifies an association between TCF4 loss and breast cancer chemoresistance

Directory of Open Access Journals (Sweden)

Gorka Ruiz de Garibay

2018-05-01

Full Text Available Understanding the mechanisms of cancer therapeutic resistance is fundamental to improving cancer care. There is clear benefit from chemotherapy in different breast cancer settings; however, knowledge of the mutations and genes that mediate resistance is incomplete. In this study, by modeling chemoresistance in patient-derived xenografts (PDXs, we show that adaptation to therapy is genetically complex and identify that loss of transcription factor 4 (TCF4; also known as ITF2 is associated with this process. A triple-negative BRCA1-mutated PDX was used to study the genetics of chemoresistance. The PDX was treated in parallel with four chemotherapies for five iterative cycles. Exome sequencing identified few genes with de novo or enriched mutations in common among the different therapies, whereas many common depleted mutations/genes were observed. Analysis of somatic mutations from The Cancer Genome Atlas (TCGA supported the prognostic relevance of the identified genes. A mutation in TCF4 was found de novo in all treatments, and analysis of drug sensitivity profiles across cancer cell lines supported the link to chemoresistance. Loss of TCF4 conferred chemoresistance in breast cancer cell models, possibly by altering cell cycle regulation. Targeted sequencing in chemoresistant tumors identified an intronic variant of TCF4 that may represent an expression quantitative trait locus associated with relapse outcome in TCGA. Immunohistochemical studies suggest a common loss of nuclear TCF4 expression post-chemotherapy. Together, these results from tumor xenograft modeling depict a link between altered TCF4 expression and breast cancer chemoresistance.

Using Predictive Modelling to Identify Students at Risk of Poor University Outcomes

Science.gov (United States)

Jia, Pengfei; Maloney, Tim

2015-01-01

Predictive modelling is used to identify students at risk of failing their first-year courses and not returning to university in the second year. Our aim is twofold. Firstly, we want to understand the factors that lead to poor first-year experiences at university. Secondly, we want to develop simple, low-cost tools that would allow universities to…

Designing key-dependent chaotic S-box with larger key space

International Nuclear Information System (INIS)

Yin Ruming; Yuan Jian; Wang Jian; Shan Xiuming; Wang Xiqin

2009-01-01

The construction of cryptographically strong substitution boxes (S-boxes) is an important concern in designing secure cryptosystems. The key-dependent S-boxes designed using chaotic maps have received increasing attention in recent years. However, the key space of such S-boxes does not seem to be sufficiently large due to the limited parameter range of discretized chaotic maps. In this paper, we propose a new key-dependent S-box based on the iteration of continuous chaotic maps. We explore the continuous-valued state space of chaotic systems, and devise the discrete mapping between the input and the output of the S-box. A key-dependent S-box is constructed with the logistic map in this paper. We show that its key space could be much larger than the current key-dependent chaotic S-boxes.

Near Identifiability of Dynamical Systems

Science.gov (United States)

Hadaegh, F. Y.; Bekey, G. A.

1987-01-01

Concepts regarding approximate mathematical models treated rigorously. Paper presents new results in analysis of structural identifiability, equivalence, and near equivalence between mathematical models and physical processes they represent. Helps establish rigorous mathematical basis for concepts related to structural identifiability and equivalence revealing fundamental requirements, tacit assumptions, and sources of error. "Structural identifiability," as used by workers in this field, loosely translates as meaning ability to specify unique mathematical model and set of model parameters that accurately predict behavior of corresponding physical system.

Phylogenetic distribution of extant richness suggests metamorphosis is a key innovation driving diversification in insects.

Directory of Open Access Journals (Sweden)

James L Rainford

Full Text Available Insects and their six-legged relatives (Hexapoda comprise more than half of all described species and dominate terrestrial and freshwater ecosystems. Understanding the macroevolutionary processes generating this richness requires a historical perspective, but the fossil record of hexapods is patchy and incomplete. Dated molecular phylogenies provide an alternative perspective on divergence times and have been combined with birth-death models to infer patterns of diversification across a range of taxonomic groups. Here we generate a dated phylogeny of hexapod families, based on previously published sequence data and literature derived constraints, in order to identify the broad pattern of macroevolutionary changes responsible for the composition of the extant hexapod fauna. The most prominent increase in diversification identified is associated with the origin of complete metamorphosis, confirming this as a key innovation in promoting insect diversity. Subsequent reductions are recovered for several groups previously identified as having a higher fossil diversity during the Mesozoic. In addition, a number of recently derived taxa are found to have radiated following the development of flowering plant (angiosperm floras during the mid-Cretaceous. These results reveal that the composition of the modern hexapod fauna is a product of a key developmental innovation, combined with multiple and varied evolutionary responses to environmental changes from the mid Cretaceous floral transition onward.

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

International Nuclear Information System (INIS)

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

2006-01-01

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

A Key Establishment Protocol for RFID User in IPTV Environment

Science.gov (United States)

Jeong, Yoon-Su; Kim, Yong-Tae; Sohn, Jae-Min; Park, Gil-Cheol; Lee, Sang-Ho

In recent years, the usage of IPTV (Internet Protocol Television) has been increased. The reason is a technological convergence of broadcasting and telecommunication delivering interactive applications and multimedia content through high speed Internet connections. The main critical point of IPTV security requirements is subscriber authentication. That is, IPTV service should have the capability to identify the subscribers to prohibit illegal access. Currently, IPTV service does not provide a sound authentication mechanism to verify the identity of its wireless users (or devices). This paper focuses on a lightweight authentication and key establishment protocol based on the use of hash functions. The proposed approach provides effective authentication for a mobile user with a RFID tag whose authentication information is communicated back and forth with the IPTV authentication server via IPTV set-top box (STB). That is, the proposed protocol generates user's authentication information that is a bundle of two public keys derived from hashing user's private keys and RFID tag's session identifier, and adds 1bit to this bundled information for subscriber's information confidentiality before passing it to the authentication server.

Compulsive buying: a cognitive-behavioural model.

Science.gov (United States)

Kellett, Stephen; Bolton, Jessica V

2009-01-01

Compulsive buying (CB) has only relatively recently become a topic of interest for researchers and clinicians alike. This hiatus means that (unlike other impulse control disorders) there is currently little theoretical guidance for clinicians attempting to intervene with CB clients and no established model for researchers to evaluate, distil and refine. The current paper summarizes and organizes the main extant identified factors in the CB literature into four distinct phases: (1) antecedents; (2) internal/external triggers; (3) the act of buying; and finally, (4) post-purchase. The relationships and interactions between the identified phases are then hypothesized, within the proposed cognitive-behavioural model. The model distinguishes the key cognitive, affective and behavioural factors within each phase and identifies how CB can become self-reinforcing over time. The over-arching treatment implication is that CB can be re-conceptualized as chronic and repetitive failure in self-regulation efforts, and that psychological interventions can accommodate this in attempting to facilitate change. A successful case example is provided of a 'co-dependent compulsive buyer' using the model, with psychometric evaluation of key aspects of CB and mental health at assessment, termination and 6-month follow-up. The research and clinical implications of the proposed model are discussed, alongside identified short-comings and the need for psychological services to respond appropriately to CB clients seeking help.

Ciona intestinalis as a Marine Model System to Study Some Key Developmental Genes Targeted by the Diatom-Derived Aldehyde Decadienal

Directory of Open Access Journals (Sweden)

Anna Lettieri

2015-03-01

Full Text Available The anti-proliferative effects of diatoms, described for the first time in copepods, have also been demonstrated in benthic invertebrates such as polychaetes, sea urchins and tunicates. In these organisms PUAs (polyunsaturated aldehydes induce the disruption of gametogenesis, gamete functionality, fertilization, embryonic mitosis, and larval fitness and competence. These inhibitory effects are due to the PUAs, produced by diatoms in response to physical damage as occurs during copepod grazing. The cell targets of these compounds remain largely unknown. Here we identify some of the genes targeted by the diatom PUA 2-trans-4-trans-decadienal (DD using the tunicate Ciona intestinalis. The tools, techniques and genomic resources available for Ciona, as well as the suitability of Ciona embryos for medium-to high-throughput strategies, are key to their employment as model organisms in different fields, including the investigation of toxic agents that could interfere with developmental processes. We demonstrate that DD can induce developmental aberrations in Ciona larvae in a dose-dependent manner. Moreover, through a preliminary analysis, DD is shown to affect the expression level of genes involved in stress response and developmental processes.

Enhanced Key Management Protocols for Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Baojiang Cui

2015-01-01

Full Text Available With rapid development and extensive use of wireless sensor networks (WSNs, it is urgent to enhance the security for WSNs, in which key management is an effective way to protect WSNs from various attacks. However, different types of messages exchanged in WSNs typically have different security requirements which cannot be satisfied by a single keying mechanism. In this study, a basic key management protocol is described for WSNs based on four kinds of keys, which can be derived from an initial master key, and an enhanced protocol is proposed based on Diffie-Hellman algorithm. The proposed scheme restricts the adverse security impact of a captured node to the rest of WSNs and meets the requirement of energy efficiency by supporting in-network processing. The master key protection, key revocation mechanism, and the authentication mechanism based on one-way hash function are, respectively, discussed. Finally, the performance of the proposed scheme is analyzed from the aspects of computational efficiency, storage requirement and communication cost, and its antiattack capability in protecting WSNs is discussed under various attack models. In this paper, promising research directions are also discussed.

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.

Habitat Restoration as a Key Conservation Lever for Woodland Caribou: A review of restoration programs and key learnings from Alberta

Directory of Open Access Journals (Sweden)

Paula Bentham

2015-12-01

Full Text Available The Recovery Strategy for the Woodland Caribou (Rangifer tarandus caribou, Boreal Population in Canada (EC, 2012, identifies coordinated actions to reclaim woodland caribou habitat as a key step to meeting current and future caribou population objectives. Actions include restoring industrial landscape features such as roads, seismic lines, pipelines, cut-lines, and cleared areas in an effort to reduce landscape fragmentation and the changes in caribou population dynamics associated with changing predator-prey dynamics in highly fragmented landscapes. Reliance on habitat restoration as a recovery action within the federal recovery strategy is high, considering all Alberta populations have less than 65% undisturbed habitat, which is identified in the recovery strategy as a threshold providing a 60% chance that a local population will be self-sustaining. Alberta’s Provincial Woodland Caribou Policy also identifies habitat restoration as a critical component of long-term caribou habitat management. We review and discuss the history of caribou habitat restoration programs in Alberta and present outcomes and highlights of a caribou habitat restoration workshop attended by over 80 representatives from oil and gas, forestry, provincial and federal regulators, academia and consulting who have worked on restoration programs. Restoration initiatives in Alberta began in 2001 and have generally focused on construction methods, revegetation treatments, access control programs, and limiting plant species favourable to alternate prey. Specific treatments include tree planting initiatives, coarse woody debris management along linear features, and efforts for multi-company and multi-stakeholder coordinated habitat restoration on caribou range. Lessons learned from these programs have been incorporated into large scale habitat restoration projects near Grande Prairie, Cold Lake, and Fort McMurray. A key outcome of our review is the opportunity to provide a

Cross-species epigenetics identifies a critical role for VAV1 in SHH subgroup medulloblastoma maintenance.

Science.gov (United States)

Lindsey, J C; Kawauchi, D; Schwalbe, E C; Solecki, D J; Selby, M P; McKinnon, P J; Olson, J M; Hayden, J T; Grundy, R G; Ellison, D W; Williamson, D; Bailey, S; Roussel, M F; Clifford, S C

2015-09-03

The identification of key tumorigenic events in Sonic Hedgehog (SHH) subgroup medulloblastomas (MBSHH) will be essential for the development of individualized therapies and improved outcomes. However, beyond confirmation of characteristic SHH pathway mutations, recent genome-wide sequencing studies have not revealed commonly mutated genes with widespread relevance as potential therapeutic targets. We therefore examined any role for epigenetic DNA methylation events in MBSHH using a cross-species approach to candidate identification, prioritization and validation. MBSHH-associated DNA methylation events were first identified in 216 subgrouped human medulloblastomas (50 MBSHH, 28 Wnt/Wingless, 44 Group 3 and 94 Group 4) and their conservation then assessed in tumors arising from four independent murine models of Shh medulloblastoma, alongside any role in tumorigenesis using functional assessments in mouse and human models. This strategy identified widespread regional CpG hypo-methylation of VAV1, leading to its elevated expression, as a conserved aberrant epigenetic event, which characterizes the majority of MBSHH tumors in both species, and is associated with a poor outcome in MBSHH patients. Moreover, direct modulation of VAV1 in mouse and human models revealed a critical role in tumor maintenance, and its abrogation markedly reduced medulloblastoma growth. Further, Vav1 activity regulated granule neuron precursor germinal zone exit and migration initiation in an ex vivo model of early postnatal cerebellar development. These findings establish VAV1 as a critical epigenetically regulated oncogene with a key role in MBSHH maintenance, and highlight its potential as a validated therapeutic target and prognostic biomarker for the improved therapy of medulloblastoma.

[Key informers. When and How?].

Science.gov (United States)

Martín González, R

2009-03-01

When information obtained through duly designed and developed studies is not available, the solution to certain problems that affect the population or that respond to certain questions may be approached by using the information and experience provided by the so-called key informer. The key informer is defined as a person who is in contact with the community or with the problem to be studied, who is considered to have good knowledge of the situation and therefore who is considered an expert. The search for consensus is the basis to obtain information through the key informers. The techniques used have different characteristics based on whether the experts chosen meet together or not, whether they are guided or not, whether they interact with each other or not. These techniques include the survey, the Delphi technique, the nominal group technique, brainwriting, brainstorming, the Phillips 66 technique, the 6-3-5 technique, the community forum and the community impressions technique. Information provided by key informers through the search for consensus is relevant when this is not available or cannot be obtained by other methods. It has permitted the analysis of the existing neurological care model, elaboration of recommendations on visit times for the out-patient neurological care, and the elaboration of guidelines and recommendations for the management of prevalent neurological problems.

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.

Group key management

Energy Technology Data Exchange (ETDEWEB)

Dunigan, T.; Cao, C.

1997-08-01

This report describes an architecture and implementation for doing group key management over a data communications network. The architecture describes a protocol for establishing a shared encryption key among an authenticated and authorized collection of network entities. Group access requires one or more authorization certificates. The implementation includes a simple public key and certificate infrastructure. Multicast is used for some of the key management messages. An application programming interface multiplexes key management and user application messages. An implementation using the new IP security protocols is postulated. The architecture is compared with other group key management proposals, and the performance and the limitations of the implementation are described.

Novel secret key generation techniques using memristor devices

Science.gov (United States)

Abunahla, Heba; Shehada, Dina; Yeun, Chan Yeob; Mohammad, Baker; Jaoude, Maguy Abi

2016-02-01

This paper proposes novel secret key generation techniques using memristor devices. The approach depends on using the initial profile of a memristor as a master key. In addition, session keys are generated using the master key and other specified parameters. In contrast to existing memristor-based security approaches, the proposed development is cost effective and power efficient since the operation can be achieved with a single device rather than a crossbar structure. An algorithm is suggested and demonstrated using physics based Matlab model. It is shown that the generated keys can have dynamic size which provides perfect security. Moreover, the proposed encryption and decryption technique using the memristor based generated keys outperforms Triple Data Encryption Standard (3DES) and Advanced Encryption Standard (AES) in terms of processing time. This paper is enriched by providing characterization results of a fabricated microscale Al/TiO2/Al memristor prototype in order to prove the concept of the proposed approach and study the impacts of process variations. The work proposed in this paper is a milestone towards System On Chip (SOC) memristor based security.

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...

Emergency management in health: key issues and challenges in the UK.

Science.gov (United States)

Lee, Andrew C K; Phillips, Wendy; Challen, Kirsty; Goodacre, Steve

2012-10-19

Emergency planning in the UK has grown considerably in recent years, galvanised by the threat of terrorism. However, deficiencies in NHS emergency planning were identified and the evidence-base that underpins it is questionable. Inconsistencies in terminologies and concepts also exist. Different models of emergency management exist internationally but the optimal system is unknown. This study examines the evidence-base and evidence requirements for emergency planning in the UK health context. The study involved semi-structured interviews with key stakeholders and opinion leaders. Purposive sampling was used to obtain a breadth of views from various agencies involved in emergency planning and response. Interviews were then analysed using a grounded approach using standard framework analysis techniques. We conducted 17 key informant interviews. Interviewees identified greater gaps in operational than technical aspects of emergency planning. Social and behavioural knowledge gaps were highlighted with regards to how individuals and organisations deal with risk and behave in emergencies. Evidence-based approaches to public engagement and for developing community resilience to disasters are lacking. Other gaps included how knowledge was developed and used. Conflicting views with regards to the optimal configuration and operation of the emergency management system were voiced. Four thematic categories for future research emerged:(i) Knowledge-base for emergency management: Further exploration is needed of how knowledge is acquired, valued, disseminated, adopted and retained.(ii) Social and behavioural issues: Greater understanding of how individuals approach risk and behave in emergencies is required.(iii) Organisational issues in emergencies: Several conflicting organisational issues were identified; value of planning versus plans, flexible versus standardized procedures, top-down versus bottom-up engagement, generic versus specific planning, and reactive versus

Identifying and Ranking the Determinants of Tourism Performance

DEFF Research Database (Denmark)

Assaf, A.George; Josiassen, Alexander

2012-01-01

, their tourism industries, and tourism businesses seek to improve the performance of the tourism industry and its constituents by vigorously promoting themselves to international tourists, cutting costs, and identifying synergies in their tourism endeavors. In seeking to improve the tourism industry......, the determinants that affect tourism performance are of key interest to the stakeholders. A key obstacle toward improving performance is the multitude of determinants that can affect tourism performance. The literature has yet to provide concrete insights into the determinants of tourism performance...... and their relative importance. The present study addresses this important gap. We identify and rank the determinants of tourism performance. We also provide performance measures of international tourism destinations. The results are derived using the Data Envelopment Analysis (DEA) and bootstrap truncated regression...

Identifying Topics in Microblogs Using Wikipedia.

Science.gov (United States)

Yıldırım, Ahmet; Üsküdarlı, Suzan; Özgür, Arzucan

2016-01-01

Twitter is an extremely high volume platform for user generated contributions regarding any topic. The wealth of content created at real-time in massive quantities calls for automated approaches to identify the topics of the contributions. Such topics can be utilized in numerous ways, such as public opinion mining, marketing, entertainment, and disaster management. Towards this end, approaches to relate single or partial posts to knowledge base items have been proposed. However, in microblogging systems like Twitter, topics emerge from the culmination of a large number of contributions. Therefore, identifying topics based on collections of posts, where individual posts contribute to some aspect of the greater topic is necessary. Models, such as Latent Dirichlet Allocation (LDA), propose algorithms for relating collections of posts to sets of keywords that represent underlying topics. In these approaches, figuring out what the specific topic(s) the keyword sets represent remains as a separate task. Another issue in topic detection is the scope, which is often limited to specific domain, such as health. This work proposes an approach for identifying domain-independent specific topics related to sets of posts. In this approach, individual posts are processed and then aggregated to identify key tokens, which are then mapped to specific topics. Wikipedia article titles are selected to represent topics, since they are up to date, user-generated, sophisticated articles that span topics of human interest. This paper describes the proposed approach, a prototype implementation, and a case study based on data gathered during the heavily contributed periods corresponding to the four US election debates in 2012. The manually evaluated results (0.96 precision) and other observations from the study are discussed in detail.

Robust Public Key Cryptography — A New Cryptosystem Surviving Private Key Compromise

Science.gov (United States)

Shaik, Cheman

A weakness of the present-day public key cryptosystems is that these cryptosystems do not survive private-key compromise attacks resulting from an internal breach of trust. In a competitive business environment, private key compromise is a common incident that voids the strength of public key cryptosystems such as RSA and ECC. Bribing corporate employees to disclose their secret keys and inadvertently disclosing secret information are among a plethora of practical attacks that occur at the implementation level. Once a breach of trust takes place and subsequently the private key is revealed, any public key cryptosystem fails to secure electronic data in Internet communications. The revealed key may be used by an attacker to decipher the intercepted data at an intermediary router. This weakness of public key cryptography calls for an additional security measure that enables encryptions to survive private key compromise attacks.

KEY PERFORMANCE INDICATORS FOR HEALTHCARE RESEARCH ORGANIZATIONS BETWEEN 2011 AND 2015

OpenAIRE

ANISKEVICH A.S.; HALFIN R.A.

2017-01-01

In this work we identify 16 key indicators to evaluate the performance of healthcare research organizations. These indicators comprehensively characterize such aspects of performance as research output and relevance, human resource development, integration into the international scientific community, distribution of scientific knowledge, promotion of the prestige of science, and resource provision. Below, we review the existing classification of medical research institutions and their key fea...

Safety culture: analysis of the causal relationships between its key dimensions.

Science.gov (United States)

Fernández-Muñiz, Beatriz; Montes-Peón, José Manuel; Vázquez-Ordás, Camilo José

2007-01-01

Several fields are showing increasing interest in safety culture as a means of reducing accidents in the workplace. The literature shows that safety culture is a multidimensional concept. However, considerable confusion surrounds this concept, about which little consensus has been reached. This study proposes a model for a positive safety culture and tests this on a sample of 455 Spanish companies, using the structural equation modeling statistical technique. Results show the important role of managers in the promotion of employees' safe behavior, both directly, through their attitudes and behaviors, and indirectly, by developing a safety management system. This paper identifies the key dimensions of safety culture. In addition, a measurement scale for the safety management system is validated. This will assist organizations in defining areas where they need to progress if they wish to improve their safety. Also, we stress that managers need to be wholly committed to and personally involved in safety activities, thereby conveying the importance the firm attaches to these issues.

Key Questions in Marine Megafauna Movement Ecology

KAUST Repository

Hays, Graeme C.; Ferreira, Luciana C.; Sequeira, Ana M.M.; Meekan, Mark G.; Duarte, Carlos M.; Bailey, Helen; Bailleul, Fred; Bowen, W. Don; Caley, M. Julian; Costa, Daniel P.; Eguí luz, Victor M.; Fossette, Sabrina; Friedlaender, Ari S.; Gales, Nick; Gleiss, Adrian C.; Gunn, John; Harcourt, Rob; Hazen, Elliott L.; Heithaus, Michael R.; Heupel, Michelle; Holland, Kim; Horning, Markus; Jonsen, Ian; Kooyman, Gerald L.; Lowe, Christopher G.; Madsen, Peter T.; Marsh, Helene; Phillips, Richard A.; Righton, David; Ropert-Coudert, Yan; Sato, Katsufumi; Shaffer, Scott A.; Simpfendorfer, Colin A.; Sims, David W.; Skomal, Gregory; Takahashi, Akinori; Trathan, Philip N.; Wikelski, Martin; Womble, Jamie N.; Thums, Michele

2016-01-01

It is a golden age for animal movement studies and so an opportune time to assess priorities for future work. We assembled 40 experts to identify key questions in this field, focussing on marine megafauna, which include a broad range of birds, mammals, reptiles, and fish. Research on these taxa has both underpinned many of the recent technical developments and led to fundamental discoveries in the field. We show that the questions have broad applicability to other taxa, including terrestrial animals, flying insects, and swimming invertebrates, and, as such, this exercise provides a useful roadmap for targeted deployments and data syntheses that should advance the field of movement ecology. Technical advances make this an exciting time for animal movement studies, with a range of small, reliable data-loggers and transmitters that can record horizontal and vertical movements as well as aspects of physiology and reproductive biology.Forty experts identified key questions in the field of movement ecology.Questions have broad applicability across species, habitats, and spatial scales, and apply to animals in both marine and terrestrial habitats as well as both vertebrates and invertebrates, including birds, mammals, reptiles, fish, insects, and plankton. © 2016 Elsevier Ltd.

Key Questions in Marine Megafauna Movement Ecology

KAUST Repository

Hays, Graeme C.

2016-03-12

It is a golden age for animal movement studies and so an opportune time to assess priorities for future work. We assembled 40 experts to identify key questions in this field, focussing on marine megafauna, which include a broad range of birds, mammals, reptiles, and fish. Research on these taxa has both underpinned many of the recent technical developments and led to fundamental discoveries in the field. We show that the questions have broad applicability to other taxa, including terrestrial animals, flying insects, and swimming invertebrates, and, as such, this exercise provides a useful roadmap for targeted deployments and data syntheses that should advance the field of movement ecology. Technical advances make this an exciting time for animal movement studies, with a range of small, reliable data-loggers and transmitters that can record horizontal and vertical movements as well as aspects of physiology and reproductive biology.Forty experts identified key questions in the field of movement ecology.Questions have broad applicability across species, habitats, and spatial scales, and apply to animals in both marine and terrestrial habitats as well as both vertebrates and invertebrates, including birds, mammals, reptiles, fish, insects, and plankton. © 2016 Elsevier Ltd.

Almost-sure identifiability of multidimensional harmonic retrieval

NARCIS (Netherlands)

Jiang, T; Sidiropoulos, ND; ten Berge, JMF

Two-dimensional (2-D) and, more generally, multidimensional harmonic retrieval is of interest in a variety of applications, including transmitter localization and joint time and frequency offset estimation in wireless communications. The associated identifiability problem is key in understanding the

A key to the Mexican and Central America Genera of Anthonomini (Curculionidae, Curculioninae)

Science.gov (United States)

Hernández, Macotulio Soto; Jones, Robert W.; Castillo, Pedro Reyes

2013-01-01

Abstract Presently the only keys available for identification of genera of Anthonomini are limited to those of the United States of America and Canada. A dichotomous key is presented to identify all genera of Mexican and Central American Anthonomini. Previous keys do not include the genera Achia, Botanebius, Loncophorus, Loncophorellus and Melexerus. A brief synopsis is given for each genus and photographs of representative species are included. PMID:23717181

Modeling sports highlights using a time-series clustering framework and model interpretation

Science.gov (United States)

Radhakrishnan, Regunathan; Otsuka, Isao; Xiong, Ziyou; Divakaran, Ajay

2005-01-01

In our past work on sports highlights extraction, we have shown the utility of detecting audience reaction using an audio classification framework. The audio classes in the framework were chosen based on intuition. In this paper, we present a systematic way of identifying the key audio classes for sports highlights extraction using a time series clustering framework. We treat the low-level audio features as a time series and model the highlight segments as "unusual" events in a background of an "usual" process. The set of audio classes to characterize the sports domain is then identified by analyzing the consistent patterns in each of the clusters output from the time series clustering framework. The distribution of features from the training data so obtained for each of the key audio classes, is parameterized by a Minimum Description Length Gaussian Mixture Model (MDL-GMM). We also interpret the meaning of each of the mixture components of the MDL-GMM for the key audio class (the "highlight" class) that is correlated with highlight moments. Our results show that the "highlight" class is a mixture of audience cheering and commentator's excited speech. Furthermore, we show that the precision-recall performance for highlights extraction based on this "highlight" class is better than that of our previous approach which uses only audience cheering as the key highlight class.