WorldWideScience

Sample records for models identified factors

  1. Prognostic model for brain metastases from lung adenocarcinoma identified with epidermal growth factor receptor mutation status.

    Science.gov (United States)

    Li, Hongwei; Wang, Weili; Jia, Haixia; Lian, Jianhong; Cao, Jianzhong; Zhang, Xiaqin; Song, Xing; Jia, Sufang; Li, Zhengran; Cao, Xing; Zhou, Wei; Han, Songye; Yang, Weihua; Xi, Yanfen; Lian, Shenming

    2017-09-01

    Several indices have been developed to predict survival of brain metastases (BM) based on prognostic factors. However, such models were designed for general brain metastases from different kinds of cancers, and prognostic factors vary between cancers and histological subtypes. Recently, studies have indicated that epidermal growth factor receptor (EGFR) mutation status may be a potential prognostic biological factor in BM from lung adenocarcinoma. Thus, we sought to define the role of EGFR mutation in prognoses and introduce a prognostic model specific for BM from lung adenocarcinoma. Data of 256 patients with BM from lung adenocarcinoma identified with EGFR mutations were collected. Independent prognostic factors were confirmed using a Cox regression model. The new prognostic model was developed based on the results of multivariable analyses. The score of each factor was calculated by six-month survival. Prognostic groups were divided into low, medium, and high risk based on the total scores. The prediction ability of the new model was compared to the three existing models. EGFR mutation and Karnofsky performance status were independent prognostic factors and were thus integrated into the new prognostic model. The new model was superior to the three other scoring systems regarding the prediction of three, six, and 12-month survival by pairwise comparison of the area under the curve. Our proposed prognostic model specific for BM from lung adenocarcinoma incorporating EGFR mutation status was valid in predicting patient survival. Further verification is warranted, with prospective testing using large sample sizes. © 2017 The Authors. Thoracic Cancer published by China Lung Oncology Group and John Wiley & Sons Australia, Ltd.

  2. 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.

  3. Identifying anti-growth factors for human cancer cell lines through genome-scale metabolic modeling

    DEFF Research Database (Denmark)

    Ghaffari, Pouyan; Mardinoglu, Adil; Asplund, Anna

    2015-01-01

    Human cancer cell lines are used as important model systems to study molecular mechanisms associated with tumor growth, hereunder how genomic and biological heterogeneity found in primary tumors affect cellular phenotypes. We reconstructed Genome scale metabolic models (GEMs) for eleven cell lines...... based on RNA-Seq data and validated the functionality of these models with data from metabolite profiling. We used cell line-specific GEMs to analyze the differences in the metabolism of cancer cell lines, and to explore the heterogeneous expression of the metabolic subsystems. Furthermore, we predicted...... antimetabolites using two cell lines with different phenotypic origins, and found that it is effective in inhibiting the growth of these cell lines. Using immunohistochemistry, we also showed high or moderate expression levels of proteins targeted by the validated antimetabolite. Identified anti-growth factors...

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

    Science.gov (United States)

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

    2016-08-01

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

  5. A model for genetic and epigenetic regulatory networks identifies rare pathways for transcription factor induced pluripotency

    Science.gov (United States)

    Artyomov, Maxim; Meissner, Alex; Chakraborty, Arup

    2010-03-01

    Most cells in an organism have the same DNA. Yet, different cell types express different proteins and carry out different functions. This is because of epigenetic differences; i.e., DNA in different cell types is packaged distinctly, making it hard to express certain genes while facilitating the expression of others. During development, upon receipt of appropriate cues, pluripotent embryonic stem cells differentiate into diverse cell types that make up the organism (e.g., a human). There has long been an effort to make this process go backward -- i.e., reprogram a differentiated cell (e.g., a skin cell) to pluripotent status. Recently, this has been achieved by transfecting certain transcription factors into differentiated cells. This method does not use embryonic material and promises the development of patient-specific regenerative medicine, but it is inefficient. The mechanisms that make reprogramming rare, or even possible, are poorly understood. We have developed the first computational model of transcription factor-induced reprogramming. Results obtained from the model are consistent with diverse observations, and identify the rare pathways that allow reprogramming to occur. If validated, our model could be further developed to design optimal strategies for reprogramming and shed light on basic questions in biology.

  6. Spatial Durbin Model (SDM For Identified Influence Dengue Hemorrhagic Fever Factors in Kabupaten Malang

    Directory of Open Access Journals (Sweden)

    Indah Resti Ayuni Suri

    2012-05-01

    Full Text Available Dengue Hemorrhagic Fever or usually populer call DBD (Demam Berdarah Degue is the cronic desease that caused by virus infection who carry by Aedes Aegypti mousquito. The observation act by DBD descriptioning and some factors territorial view that influence them, also DBD’s modeling use Spatial Durbin Model (SDM. SDM is the particullary case from Spatial Autoregresive Model (SAR, it means modeling with spatial lag at dependen variable and independen variable. This observation use ratio DBD invectors amount with population amount of citizenry at Kabupaten Malang in 2009. Some variable was used, those are the precentation of existention free number embrio, ratio of civil amount between family, procentation of healthy clinic between invectors and procentase of the invectors who taking care by medical help with amount of invectors. The fourth variables are independen variable to ratio of DBD invector amount with population of citizenry amount, as dependen variable trough spatial SDM modelling. The result of SDM parameter modelling, the significant influence variable in session % is the procentation of free amount embrio existention from their own district, the procentation of healthy clinic amount with the DBD invector amount from their own district, the ratio of the population of citizenry with the family from their neighborhood district, and the procentation of healthy clinic amount with the DBD invector amount from their neighborhood district.

  7. Modeling the City Distribution System Reliability with Bayesian Networks to Identify Influence Factors

    Directory of Open Access Journals (Sweden)

    Hao Zhang

    2016-01-01

    Full Text Available Under the increasingly uncertain economic environment, the research on the reliability of urban distribution system has great practical significance for the integration of logistics and supply chain resources. This paper summarizes the factors that affect the city logistics distribution system. Starting from the research of factors that influence the reliability of city distribution system, further construction of city distribution system reliability influence model is built based on Bayesian networks. The complex problem is simplified by using the sub-Bayesian network, and an example is analyzed. In the calculation process, we combined the traditional Bayesian algorithm and the Expectation Maximization (EM algorithm, which made the Bayesian model able to lay a more accurate foundation. The results show that the Bayesian network can accurately reflect the dynamic relationship among the factors affecting the reliability of urban distribution system. Moreover, by changing the prior probability of the node of the cause, the correlation degree between the variables that affect the successful distribution can be calculated. The results have significant practical significance on improving the quality of distribution, the level of distribution, and the efficiency of enterprises.

  8. Proteomic profiling identifies breast tumor metastasis-associated factors in an isogenic model

    OpenAIRE

    KREUNIN, PAWEENA; YOO, CHUL; Urquidi, Virginia; Lubman, David M.; Goodison, Steve

    2007-01-01

    A combination of LC and MS was applied to an isogenic breast tumor metastasis model to identify proteins associated with a cellular phenotype. Chromatofocusing followed by nonporous-RP-HPLC/ESI-TOF MS was applied to cell lysates of a pair of monoclonal cell lines from the human breast carcinoma cell line MDA-MB-435 that have different metastatic phenotypes in immune-compromised mice. This method was developed to separate proteins based on pI and hydrophobicity. The high resolution and mass ac...

  9. Multivariate Modeling Identifies Neutrophil- and Th17-Related Factors as Differential Serum Biomarkers of Chronic Murine Colitis

    Science.gov (United States)

    McBee, Megan E.; Zeng, Yu; Parry, Nicola; Nagler, Cathryn R.; Tannenbaum, Steven R.

    2010-01-01

    Background Diagnosis of chronic intestinal inflammation, which characterizes inflammatory bowel disease (IBD), along with prediction of disease state is hindered by the availability of predictive serum biomarker. Serum biomarkers predictive of disease state will improve trials for therapeutic intervention, and disease monitoring, particularly in genetically susceptible individuals. Chronic inflammation during IBD is considered distinct from infectious intestinal inflammation thereby requiring biomarkers to provide differential diagnosis. To address whether differential serum biomarkers could be identified in murine models of colitis, immunological profiles from both chronic spontaneous and acute infectious colitis were compared and predictive serum biomarkers identified via multivariate modeling. Methodology/Principal Findings Discriminatory multivariate modeling of 23 cytokines plus chlorotyrosine and nitrotyrosine (protein adducts from reactive nitrogen species and hypochlorite) in serum and tissue from two murine models of colitis was performed to identify disease-associated biomarkers. Acute C. rodentium-induced colitis in C57BL/6J mice and chronic spontaneous Helicobacter-dependent colitis in TLR4−/− x IL-10−/− mice were utilized for evaluation. Colon profiles of both colitis models were nearly identical with chemokines, neutrophil- and Th17-related factors highly associated with intestinal disease. In acute colitis, discriminatory disease-associated serum factors were not those identified in the colon. In contrast, the discriminatory predictive serum factors for chronic colitis were neutrophil- and Th17-related factors (KC, IL-12/23p40, IL-17, G-CSF, and chlorotyrosine) that were also elevated in colon tissue. Chronic colitis serum biomarkers were specific to chronic colitis as they were not discriminatory for acute colitis. Conclusions/Significance Immunological profiling revealed strikingly similar colon profiles, yet distinctly different serum

  10. [Analysis of dietary pattern and diabetes mellitus influencing factors identified by classification tree model in adults of Fujian].

    Science.gov (United States)

    Yu, F L; Ye, Y; Yan, Y S

    2017-05-10

    Objective: To find out the dietary patterns and explore the relationship between environmental factors (especially dietary patterns) and diabetes mellitus in the adults of Fujian. Methods: Multi-stage sampling method were used to survey residents aged ≥18 years by questionnaire, physical examination and laboratory detection in 10 disease surveillance points in Fujian. Factor analysis was used to identify the dietary patterns, while logistic regression model was applied to analyze relationship between dietary patterns and diabetes mellitus, and classification tree model was adopted to identify the influencing factors for diabetes mellitus. Results: There were four dietary patterns in the population, including meat, plant, high-quality protein, and fried food and beverages patterns. The result of logistic analysis showed that plant pattern, which has higher factor loading of fresh fruit-vegetables and cereal-tubers, was a protective factor for non-diabetes mellitus. The risk of diabetes mellitus in the population at T2 and T3 levels of factor score were 0.727 (95%CI:0.561-0.943) times and 0.736 (95%CI: 0.573-0.944) times higher, respectively, than those whose factor score was in lowest quartile. Thirteen influencing factors and eleven group at high-risk for diabetes mellitus were identified by classification tree model. The influencing factors were dyslipidemia, age, family history of diabetes, hypertension, physical activity, career, sex, sedentary time, abdominal adiposity, BMI, marital status, sleep time and high-quality protein pattern. Conclusion: There is a close association between dietary patterns and diabetes mellitus. It is necessary to promote healthy and reasonable diet, strengthen the monitoring and control of blood lipids, blood pressure and body weight, and have good lifestyle for the prevention and control of diabetes mellitus.

  11. 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.

  12. Sparse Linear Identifiable Multivariate Modeling

    DEFF Research Database (Denmark)

    Henao, Ricardo; Winther, Ole

    2011-01-01

    In this paper we consider sparse and identifiable linear latent variable (factor) and linear Bayesian network models for parsimonious analysis of multivariate data. We propose a computationally efficient method for joint parameter and model inference, and model comparison. It consists of a fully...... Bayesian hierarchy for sparse models using slab and spike priors (two-component δ-function and continuous mixtures), non-Gaussian latent factors and a stochastic search over the ordering of the variables. The framework, which we call SLIM (Sparse Linear Identifiable Multivariate modeling), is validated...... 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...

  13. Prediction of DNA binding motifs from 3D models of transcription factors; identifying TLX3 regulated genes.

    Science.gov (United States)

    Pujato, Mario; Kieken, Fabien; Skiles, Amanda A; Tapinos, Nikos; Fiser, Andras

    2014-12-16

    Proper cell functioning depends on the precise spatio-temporal expression of its genetic material. Gene expression is controlled to a great extent by sequence-specific transcription factors (TFs). Our current knowledge on where and how TFs bind and associate to regulate gene expression is incomplete. A structure-based computational algorithm (TF2DNA) is developed to identify binding specificities of TFs. The method constructs homology models of TFs bound to DNA and assesses the relative binding affinity for all possible DNA sequences using a knowledge-based potential, after optimization in a molecular mechanics force field. TF2DNA predictions were benchmarked against experimentally determined binding motifs. Success rates range from 45% to 81% and primarily depend on the sequence identity of aligned target sequences and template structures, TF2DNA was used to predict 1321 motifs for 1825 putative human TF proteins, facilitating the reconstruction of most of the human gene regulatory network. As an illustration, the predicted DNA binding site for the poorly characterized T-cell leukemia homeobox 3 (TLX3) TF was confirmed with gel shift assay experiments. TLX3 motif searches in human promoter regions identified a group of genes enriched in functions relating to hematopoiesis, tissue morphology, endocrine system and connective tissue development and function. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  14. Identifying key processes in the hydrochemistry of a basin through the combined use of factor and regression models

    Indian Academy of Sciences (India)

    Sandow Mark Yidana; Bruce Banoeng-Yakubo; Patrick Asamoah Sakyi

    2012-04-01

    An innovative technique of measuring the intensities of major sources of variation in the hydrochemistry of (ground) water in a basin has been developed. This technique, which is based on the combination of R-mode factor and multiple regression analyses, can be used to measure the degrees of influence of the major sources of variation in the hydrochemistry without measuring the concentrations of the entire set of physico-chemical parameters which are often used to characterize water systems. R-mode factor analysis was applied to the data of 13 physico-chemical parameters and 50 samples in order to determine the major sources of variation in the hydrochemistry of some aquifers in the western region of Ghana. In this study, three sources of variation in the hydrochemistry were distinguished: the dissolution of chlorides and sulfates of the major cations, carbonate mineral dissolution, and silicate mineral weathering. Two key parameters were identified with each of the processes and multiple regression models were developed for each process. These models were tested and found to predict these processes quite accurately, and can be applied anywhere within the terrain. This technique can be reliably applied in areas where logistical constraints limit water sampling for whole basin hydrochemical characterization. Q-mode hierarchical cluster analysis (HCA) applied to the data revealed three major groundwater associations distinguished on the basis of the major causes of variation in the hydrochemistry. The three groundwater types represent Na–HCO3, Ca–HCO3, and Na–Cl groundwater types. Silicate stability diagrams suggest that all these groundwater types are mainly stable in the kaolinite and montmorillonite fields suggesting moderately restricted flow conditions.

  15. Identifying factors affecting acceptance of new technology in the industry using hybrid model of UTAUT and FUZZY DEMATEL

    Directory of Open Access Journals (Sweden)

    Mojtaba Javidnia

    2012-10-01

    Full Text Available Today and in highly competitive and fast-paced arena of the world, industrial companies focus on achieving technological superiority through the effective use of world modern-day technologies in the production and operation process associated with all their available resources. With using this procedure, these industrial companies try to achieve long-term and sustainable competitive advantages. On the other hand, applying world modern technologies does not solely guarantee success of these companies, rather, preparing preliminary grounds associated with the acceptance of technology will be decisive in this field. This article deals with clarifying factors affecting the adoption of new technologies and showing relationship of these factors together. For this purpose, Unified Theory of Acceptance and Use of Technology (UTAUT Model has been used to study factors affecting the adoption of new technologies. In the same direction, relationship between constituent components of this model has been studied with regard to the acceptance of new technology of Electro-Slag Remelting (ESR in Esfarayen Steel Industry Complex using FUZZY DEMATEL Technique.

  16. Distributed Lag Nonlinear Modelling Approach to Identify Relationship between Climatic Factors and Dengue Incidence in Colombo District, Sri Lanka

    Directory of Open Access Journals (Sweden)

    Thiyanga Talagala

    2015-12-01

    Full Text Available Dengue fever and its more severe deadly complication dengue hemorrhagic fever is an infectious mosquito borne disease. The rise in dengue fever has made a heavy economic burden to the country. Climate variability is considered as the major determinant of dengue transmission. Sri Lanka has a favorable climatic condition for development and transmission of dengue.  Hence the aim of this study is to estimate the effect of diverse climatic variables on the transmission of dengue while taking the lag effect and nonlinear effect into account. Weekly data on dengue cases were obtained from January, 2009 to September, 2014. Temperature, precipitation, visibility, humidity, and wind speed were also recorded as weekly averages. Poisson regression combined with distributed lag nonlinear model was used to quantify the impact of climatic factors. Results of  DLNM  revealed; Mean Temperature 250C – 270C at lag 1 – 8 weeks, Precipitation higher than  70mm at lag 1- 5 weeks and 20- 50mm at  lag 10 – 20 weeks, humidity ranged from 65% to 80% at lag 10 – 18 weeks, visibility greater than 14 km have a positive impact on the occurrence of dengue incidence while, mean temperature higher than 280C at lag 6 – 25 weeks, maximum temperature at lag 4 – 6 weeks, precipitation higher than 65mm at lag 15 – 20 weeks,  humidity less than 70% at lag 4 – 9 weeks, visibility less than 14km, high wind speed have a negative impact on the occurrence of dengue incidence. These findings can aid the targeting of vector control interventions and the planning for dengue vaccine implementation.

  17. Using an autologistic regression model to identify spatial risk factors and spatial risk patterns of hand, foot and mouth disease (HFMD) in Mainland China.

    Science.gov (United States)

    Bo, Yan-Chen; Song, Chao; Wang, Jin-Feng; Li, Xiao-Wen

    2014-04-14

    There have been large-scale outbreaks of hand, foot and mouth disease (HFMD) in Mainland China over the last decade. These events varied greatly across the country. It is necessary to identify the spatial risk factors and spatial distribution patterns of HFMD for public health control and prevention. Climate risk factors associated with HFMD occurrence have been recognized. However, few studies discussed the socio-economic determinants of HFMD risk at a space scale. HFMD records in Mainland China in May 2008 were collected. Both climate and socio-economic factors were selected as potential risk exposures of HFMD. Odds ratio (OR) was used to identify the spatial risk factors. A spatial autologistic regression model was employed to get OR values of each exposures and model the spatial distribution patterns of HFMD risk. Results showed that both climate and socio-economic variables were spatial risk factors for HFMD transmission in Mainland China. The statistically significant risk factors are monthly average precipitation (OR = 1.4354), monthly average temperature (OR = 1.379), monthly average wind speed (OR = 1.186), the number of industrial enterprises above designated size (OR = 17.699), the population density (OR = 1.953), and the proportion of student population (OR = 1.286). The spatial autologistic regression model has a good goodness of fit (ROC = 0.817) and prediction accuracy (Correct ratio = 78.45%) of HFMD occurrence. The autologistic regression model also reduces the contribution of the residual term in the ordinary logistic regression model significantly, from 17.25 to 1.25 for the odds ratio. Based on the prediction results of the spatial model, we obtained a map of the probability of HFMD occurrence that shows the spatial distribution pattern and local epidemic risk over Mainland China. The autologistic regression model was used to identify spatial risk factors and model spatial risk patterns of HFMD. HFMD occurrences were found to be spatially

  18. Identifying Motivational Factors within a Multinational Company

    OpenAIRE

    Daniela Bradutanu

    2011-01-01

    The aim of the study is to identify the main motivational factors within a multinational company. The first objective is to identify work functions, formulated on Abraham Maslow’s pyramid, following the identification of the key characteristics that motivate an employee at the work place and last, but not least, the type of motivation that employees focus, intrinsic or extrinsic. The research method targeted a questionnaire based survey, including various company employees and an interv...

  19. Identifying motivational factors within a multinational company

    Directory of Open Access Journals (Sweden)

    Daniela Bradutanu

    2011-08-01

    Full Text Available The aim of the study is to identify the main motivational factors within a multinational company. The first objective is to identify work functions, formulated on Abraham Maslow’s pyramid, following the identification of the key characteristics that motivate an employee at the work place and last, but not least, the type of motivation that employees focus, intrinsic or extrinsic. The research method targeted a questionnaire based survey, including various company employees and an interview with the manager. The results confirmed that in Romania, employees put great emphasis on extrinsic motivation, a certain income and job security being primary. These results have implications for managers that in order to effectively motivate staff, first, must know their needs and expectations. To identify the main needs and motivational factors we had as a starting point Maslow's pyramid.

  20. Identifying community healthcare supports for the elderly and the factors affecting their aging care model preference: evidence from three districts of Beijing

    Directory of Open Access Journals (Sweden)

    Tianyang Liu

    2016-11-01

    Full Text Available Abstract Background The Chinese tradition of filial piety, which prioritized family-based care for the elderly, is transitioning and elders can no longer necessarily rely on their children. The purpose of this study was to identify community support for the elderly, and analyze the factors that affect which model of old-age care elderly people dwelling in communities prefer. Methods We used the database “Health and Social Support of Elderly Population in Community”. Questionnaires were issued in 2013, covering 3 districts in Beijing. A group of 1036 people over 60 years in age were included in the study. The respondents’ profile variables were organized in Andersen’s Model and community healthcare resource factors were added. A multinomial logistic model was applied to analyze the factors associated with the desired aging care models. Results Cohabiting with children and relying on care from family was still the primary desired aging care model for seniors (78 %, followed by living in institutions (14.8 % and living at home independently while relying on community resources (7.2 %. The regression result indicated that predisposing, enabling and community factors were significantly associated with the aging care model preference. Specifically, compared with those who preferred to cohabit with children, those having higher education, fewer available family and friend helpers, and shorter distance to healthcare center were more likely to prefer to live independently and rely on community support. And compared with choosing to live in institutions, those having fewer available family and friend helpers and those living alone were more likely to prefer to live independently and rely on community. Need factors (health and disability condition were not significantly associated with desired aging care models, indicating that desired aging care models were passive choices resulted from the balancing of family and social caring resources

  1. Factor analysis identifies subgroups of constipation

    Institute of Scientific and Technical Information of China (English)

    Philip G Dinning; Mike Jones; Linda Hunt; Sergio E Fuentealba; Jamshid Kalanter; Denis W King; David Z Lubowski; Nicholas J Talley; Ian J Cook

    2011-01-01

    AIM: To determine whether distinct symptom groupings exist in a constipated population and whether such grouping might correlate with quantifiable pathophysiological measures of colonic dysfunction. METHODS: One hundred and ninety-one patients presenting to a Gastroenterology clinic with constipation and 32 constipated patients responding to a newspaper advertisement completed a 53-item, wide-ranging selfreport questionnaire. One hundred of these patients had colonic transit measured scintigraphically. Factor analysis determined whether constipation-related symptoms grouped into distinct aspects of symptomatology. Cluster analysis was used to determine whether individual patients naturally group into distinct subtypes. RESULTS: Cluster analysis yielded a 4 cluster solution with the presence or absence of pain and laxative unresponsiveness providing the main descriptors. Amongst all clusters there was a considerable proportion of patients with demonstrable delayed colon transit, irritable bowel syndrome positive criteria and regular stool frequency. The majority of patients with these characteristics also reported regular laxative use. CONCLUSION: Factor analysis identified four constipation subgroups, based on severity and laxative unresponsiveness, in a constipated population. However, clear stratification into clinically identifiable groups remains imprecise.

  2. High-Throughput, Signature-Tagged Mutagenic Approach To Identify Novel Virulence Factors of Yersinia pestis CO92 in a Mouse Model of Infection

    Science.gov (United States)

    Ponnusamy, Duraisamy; Fitts, Eric C.; Erova, Tatiana E.; Kozlova, Elena V.; Kirtley, Michelle L.; Tiner, Bethany L.; Andersson, Jourdan A.

    2015-01-01

    The identification of new virulence factors in Yersinia pestis and understanding their molecular mechanisms during an infection process are necessary in designing a better vaccine or to formulate an appropriate therapeutic intervention. By using a high-throughput, signature-tagged mutagenic approach, we created 5,088 mutants of Y. pestis strain CO92 and screened them in a mouse model of pneumonic plague at a dose equivalent to 5 50% lethal doses (LD50) of wild-type (WT) CO92. From this screen, we obtained 118 clones showing impairment in disseminating to the spleen, based on hybridization of input versus output DNA from mutant pools with 53 unique signature tags. In the subsequent screen, 20/118 mutants exhibited attenuation at 8 LD50 when tested in a mouse model of bubonic plague, with infection by 10/20 of the aforementioned mutants resulting in 40% or higher survival rates at an infectious dose of 40 LD50. Upon sequencing, six of the attenuated mutants were found to carry interruptions in genes encoding hypothetical proteins or proteins with putative functions. Mutants with in-frame deletion mutations of two of the genes identified from the screen, namely, rbsA, which codes for a putative sugar transport system ATP-binding protein, and vasK, a component of the type VI secretion system, were also found to exhibit some attenuation at 11 or 12 LD50 in a mouse model of pneumonic plague. Likewise, among the remaining 18 signature-tagged mutants, 9 were also attenuated (40 to 100%) at 12 LD50 in a pneumonic plague mouse model. Previously, we found that deleting genes encoding Braun lipoprotein (Lpp) and acyltransferase (MsbB), the latter of which modifies lipopolysaccharide function, reduced the virulence of Y. pestis CO92 in mouse models of bubonic and pneumonic plague. Deletion of rbsA and vasK genes from either the Δlpp single or the Δlpp ΔmsbB double mutant augmented the attenuation to provide 90 to 100% survivability to mice in a pneumonic plague model at 20

  3. High-throughput, signature-tagged mutagenic approach to identify novel virulence factors of Yersinia pestis CO92 in a mouse model of infection.

    Science.gov (United States)

    Ponnusamy, Duraisamy; Fitts, Eric C; Sha, Jian; Erova, Tatiana E; Kozlova, Elena V; Kirtley, Michelle L; Tiner, Bethany L; Andersson, Jourdan A; Chopra, Ashok K

    2015-05-01

    The identification of new virulence factors in Yersinia pestis and understanding their molecular mechanisms during an infection process are necessary in designing a better vaccine or to formulate an appropriate therapeutic intervention. By using a high-throughput, signature-tagged mutagenic approach, we created 5,088 mutants of Y. pestis strain CO92 and screened them in a mouse model of pneumonic plague at a dose equivalent to 5 50% lethal doses (LD50) of wild-type (WT) CO92. From this screen, we obtained 118 clones showing impairment in disseminating to the spleen, based on hybridization of input versus output DNA from mutant pools with 53 unique signature tags. In the subsequent screen, 20/118 mutants exhibited attenuation at 8 LD50 when tested in a mouse model of bubonic plague, with infection by 10/20 of the aforementioned mutants resulting in 40% or higher survival rates at an infectious dose of 40 LD50. Upon sequencing, six of the attenuated mutants were found to carry interruptions in genes encoding hypothetical proteins or proteins with putative functions. Mutants with in-frame deletion mutations of two of the genes identified from the screen, namely, rbsA, which codes for a putative sugar transport system ATP-binding protein, and vasK, a component of the type VI secretion system, were also found to exhibit some attenuation at 11 or 12 LD50 in a mouse model of pneumonic plague. Likewise, among the remaining 18 signature-tagged mutants, 9 were also attenuated (40 to 100%) at 12 LD50 in a pneumonic plague mouse model. Previously, we found that deleting genes encoding Braun lipoprotein (Lpp) and acyltransferase (MsbB), the latter of which modifies lipopolysaccharide function, reduced the virulence of Y. pestis CO92 in mouse models of bubonic and pneumonic plague. Deletion of rbsA and vasK genes from either the Δlpp single or the Δlpp ΔmsbB double mutant augmented the attenuation to provide 90 to 100% survivability to mice in a pneumonic plague model at 20

  4. Risk factors identified for certain lymphoma subtypes

    Science.gov (United States)

    In a large international collaborative analysis of risk factors for non-Hodgkin lymphoma (NHL), scientists were able to quantify risk associated with medical history, lifestyle factors, family history of blood or lymph-borne cancers, and occupation for 11

  5. Identifying and modeling safety hazards

    Energy Technology Data Exchange (ETDEWEB)

    DANIELS,JESSE; BAHILL,TERRY; WERNER,PAUL W.

    2000-03-29

    The hazard model described in this paper is designed to accept data over the Internet from distributed databases. A hazard object template is used to ensure that all necessary descriptors are collected for each object. Three methods for combining the data are compared and contrasted. Three methods are used for handling the three types of interactions between the hazard objects.

  6. 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...

  7. A Linear Regression Model Identifying the Primary Factors Contributing to Maintenance Man Hours for the C-17 Globemaster III in the Air National Guard

    Science.gov (United States)

    2012-06-15

    correlations of the individual variables with each other in a one to one relationship. Variance Inflation Factor ( VIF ) analysis was also conducted to further...accuracy of the model.   31    VIF determines if the variances of the estimated coefficients in the regression model are inflated due to...larger the variance of bk (Simon, 2004). The VIF itself is comprised of the last portion of the equation: 1 1 According to Dr. Simon, VIF values

  8. Identifying factors affecting optimal management of agricultural water

    Directory of Open Access Journals (Sweden)

    Masoud Samian

    2015-01-01

    In addition to quantitative methodology such as descriptive statistics and factor analysis a qualitative methodology was employed for dynamic simulation among variables through Vensim software. In this study, the factor analysis technique was used through the Kaiser-Meyer-Olkin (KMO and Bartlett tests. From the results, four key elements were identified as factors affecting the optimal management of agricultural water in Hamedan area. These factors were institutional and legal factors, technical and knowledge factors, economic factors and social factors.

  9. Global identifiability of linear structural equation models

    CERN Document Server

    Drton, Mathias; Sullivant, Seth

    2010-01-01

    Structural equation models are multivariate statistical models that are defined by specifying noisy functional relationships among random variables. We consider the classical case of linear relationships and additive Gaussian noise terms. We give a necessary and sufficient condition for global identifiability of the model in terms of a mixed graph encoding the linear structural equations and the correlation structure of the error terms. Global identifiability is understood to mean injectivity of the parametrization of the model and is fundamental in particular for applicability of standard statistical methodology.

  10. Identifying Causal Risk Factors for Violence among Discharged Patients.

    Directory of Open Access Journals (Sweden)

    Jeremy W Coid

    Full Text Available Structured Professional Judgement (SPJ is routinely administered in mental health and criminal justice settings but cannot identify violence risk above moderate accuracy. There is no current evidence that violence can be prevented using SPJ. This may be explained by routine application of predictive instead of causal statistical models when standardising SPJ instruments.We carried out a prospective cohort study of 409 male and female patients discharged from medium secure services in England and Wales to the community. Measures were taken at baseline (pre-discharge, 6 and 12 months post-discharge using the Historical, Clinical and Risk-20 items version 3 (HCR-20v3 and Structural Assessment of Protective Factors (SAPROF. Information on violence was obtained via the McArthur community violence instrument and the Police National Computer.In a lagged model, HCR-20v3 and SAPROF items were poor predictors of violence. Eight items of the HCR-20v3 and 4 SAPROF items did not predict violent behaviour better than chance. In re-analyses considering temporal proximity of risk/ protective factors (exposure on violence (outcome, risk was elevated due to violent ideation (OR 6.98, 95% CI 13.85-12.65, P<0.001, instability (OR 5.41, 95% CI 3.44-8.50, P<0.001, and poor coping/ stress (OR 8.35, 95% CI 4.21-16.57, P<0.001. All 3 risk factors were explanatory variables which drove the association with violent outcome. Self-control (OR 0.13, 95% CI 0.08-0.24, P<0.001 conveyed protective effects and explained the association of other protective factors with violence.Using two standardised SPJ instruments, predictive (lagged methods could not identify risk and protective factors which must be targeted in interventions for discharged patients with severe mental illness. Predictive methods should be abandoned if the aim is to progress from risk assessment to effective risk management and replaced by methods which identify factors causally associated with violence.

  11. Identifying perinatal risk factors for infant maltreatment: an ecological approach

    Directory of Open Access Journals (Sweden)

    Hallisey Elaine J

    2006-12-01

    Full Text Available Abstract Background Child maltreatment and its consequences are a persistent problem throughout the world. Public health workers, human services officials, and others are interested in new and efficient ways to determine which geographic areas to target for intervention programs and resources. To improve assessment efforts, selected perinatal factors were examined, both individually and in various combinations, to determine if they are associated with increased risk of infant maltreatment. State of Georgia birth records and abuse and neglect data were analyzed using an area-based, ecological approach with the census tract as a surrogate for the community. Cartographic visualization suggested some correlation exists between risk factors and child maltreatment, so bivariate and multivariate regression were performed. The presence of spatial autocorrelation precluded the use of traditional ordinary least squares regression, therefore a spatial regression model coupled with maximum likelihood estimation was employed. Results Results indicate that all individual factors or their combinations are significantly associated with increased risk of infant maltreatment. The set of perinatal risk factors that best predicts infant maltreatment rates are: mother smoked during pregnancy, families with three or more siblings, maternal age less than 20 years, births to unmarried mothers, Medicaid beneficiaries, and inadequate prenatal care. Conclusion This model enables public health to take a proactive stance, to reasonably predict areas where poor outcomes are likely to occur, and to therefore more efficiently allocate resources. U.S. states that routinely collect the variables the National Center for Health Statistics (NCHS defines for birth certificates can easily identify areas that are at high risk for infant maltreatment. The authors recommend that agencies charged with reducing child maltreatment target communities that demonstrate the perinatal risks

  12. Identifying influential factors on integrated marketing planning using information technology

    Directory of Open Access Journals (Sweden)

    Karim Hamdi

    2014-07-01

    Full Text Available This paper presents an empirical investigation to identify important factors influencing integrated marketing planning using information technology. The proposed study designs a questionnaire for measuring integrated marketing planning, which consists of three categories of structural factors, behavioral factors and background factors. There are 40 questions associated with the proposed study in Likert scale. Cronbach alphas have been calculated for structural factors, behavioral factors and background factors as 0.89, 0.86 and 0.83, respectively. Using some statistical test, the study has confirmed the effects of three factors on integrated marketing. In addition, the implementation of Freedman test has revealed that structural factors were the most important factor followed by background factors and behavioral factors.

  13. Identifying nonlinear biomechanical models by multicriteria analysis

    Science.gov (United States)

    Srdjevic, Zorica; Cveticanin, Livija

    2012-02-01

    In this study, the methodology developed by Srdjevic and Cveticanin (International Journal of Industrial Ergonomics 34 (2004) 307-318) for the nonbiased (objective) parameter identification of the linear biomechanical model exposed to vertical vibrations is extended to the identification of n-degree of freedom (DOF) nonlinear biomechanical models. The dynamic performance of the n-DOF nonlinear model is described in terms of response functions in the frequency domain, such as the driving-point mechanical impedance and seat-to-head transmissibility function. For randomly generated parameters of the model, nonlinear equations of motion are solved using the Runge-Kutta method. The appropriate data transformation from the time-to-frequency domain is performed by a discrete Fourier transformation. Squared deviations of the response functions from the target values are used as the model performance evaluation criteria, thus shifting the problem into the multicriteria framework. The objective weights of criteria are obtained by applying the Shannon entropy concept. The suggested methodology is programmed in Pascal and tested on a 4-DOF nonlinear lumped parameter biomechanical model. The identification process over the 2000 generated sets of parameters lasts less than 20 s. The model response obtained with the imbedded identified parameters correlates well with the target values, therefore, justifying the use of the underlying concept and the mathematical instruments and numerical tools applied. It should be noted that the identified nonlinear model has an improved accuracy of the biomechanical response compared to the accuracy of a linear model.

  14. Multilevel Mixture Factor Models

    Science.gov (United States)

    Varriale, Roberta; Vermunt, Jeroen K.

    2012-01-01

    Factor analysis is a statistical method for describing the associations among sets of observed variables in terms of a small number of underlying continuous latent variables. Various authors have proposed multilevel extensions of the factor model for the analysis of data sets with a hierarchical structure. These Multilevel Factor Models (MFMs)…

  15. Identifiability of large phylogenetic mixture models.

    Science.gov (United States)

    Rhodes, John A; Sullivant, Seth

    2012-01-01

    Phylogenetic mixture models are statistical models of character evolution allowing for heterogeneity. Each of the classes in some unknown partition of the characters may evolve by different processes, or even along different trees. Such models are of increasing interest for data analysis, as they can capture the variety of evolutionary processes that may be occurring across long sequences of DNA or proteins. The fundamental question of whether parameters of such a model are identifiable is difficult to address, due to the complexity of the parameterization. Identifiability is, however, essential to their use for statistical inference.We analyze mixture models on large trees, with many mixture components, showing that both numerical and tree parameters are indeed identifiable in these models when all trees are the same. This provides a theoretical justification for some current empirical studies, and indicates that extensions to even more mixture components should be theoretically well behaved. We also extend our results to certain mixtures on different trees, using the same algebraic techniques.

  16. Identifying motifs in folktales using topic models

    NARCIS (Netherlands)

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

    2013-01-01

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

  17. Providing a Model to Predict Purchase Behavior of Mobile Phone Buyers in Iran: Identify Cultural, Social, Personal and Psychological Factors of Consumers

    Directory of Open Access Journals (Sweden)

    Kiumars Mohsenimehr

    2016-06-01

    Full Text Available Knowing an insight on factors affecting intentions of customers not enables marketers for better understanding and predicting demand for products or services, but raises motivation and frequency of purchase products or services. More importantly, if the factors are considered for developing new products, those developing products will have a higher probability of success. Therefore, in this research, we will analyze theoretical aspects of consumer’s purchasing behavior and the factors affecting the behavior. The present research is applicable objectively; while it is descriptivesurvey and correlation type in terms of method. Its population consist students of Islamic Azad University's Business Administration. The research data were collected from 386 students according the standardized questionnaires with Likert five-point. Finally, we tested its hypotheses by considering to normality of the data and using parametric methods as well as Pearson Correlation Coefficient and regression. The results indicated a positive impact of all cultural, social, personal and psychological factors on purchasing behavior of mobile phone buyers. Therefore, this article will help marketing managers to better understand of consumers’ decision-making that helping them causes that they use better the factors for providing marketing strategy. Finally, this study will help companies to affect consumers’ decisions by adopting detailed marketing strategies and full knowledge and insight.

  18. Identifiability of Causal Graphs using Functional Models

    CERN Document Server

    Peters, Jonas; Janzing, Dominik; Schoelkopf, Bernhard

    2012-01-01

    This work addresses the following question: Under what assumptions on the data generating process can one infer the causal graph from the joint distribution? The approach taken by conditional independence-based causal discovery methods is based on two assumptions: the Markov condition and faithfulness. It has been shown that under these assumptions the causal graph can be identified up to Markov equivalence (some arrows remain undirected) using methods like the PC algorithm. In this work we propose an alternative by defining Identifiable Functional Model Classes (IFMOCs). As our main theorem we prove that if the data generating process belongs to an IFMOC, one can identify the complete causal graph. To the best of our knowledge this is the first identifiability result of this kind that is not limited to linear functional relationships. We discuss how the IFMOC assumption and the Markov and faithfulness assumptions relate to each other and explain why we believe that the IFMOC assumption can be tested more eas...

  19. Asthma trajectories in early childhood: identifying modifiable factors.

    Directory of Open Access Journals (Sweden)

    Lidia Panico

    Full Text Available BACKGROUND: There are conflicting views as to whether childhood wheezing represents several discreet entities or a single but variable disease. Classification has centered on phenotypes often derived using subjective criteria, small samples, and/or with little data for young children. This is particularly problematic as asthmatic features appear to be entrenched by age 6/7. In this paper we aim to: identify longitudinal trajectories of wheeze and other atopic symptoms in early childhood; characterize the resulting trajectories by the socio-economic background of children; and identify potentially modifiable processes in infancy correlated with these trajectories. DATA AND METHODS: The Millennium Cohort Study is a large, representative birth cohort of British children born in 2000-2002. Our analytical sample includes 11,632 children with data on key variables (wheeze in the last year; ever hay-fever and/or eczema reported by the main carers at age 3, 5 and 7 using a validated tool, the International Study of Asthma and Allergies in Childhood module. We employ longitudinal Latent Class Analysis, a clustering methodology which identifies classes underlying the observed population heterogeneity. RESULTS: Our model distinguished four latent trajectories: a trajectory with both low levels of wheeze and other atopic symptoms (54% of the sample; a trajectory with low levels of wheeze but high prevalence of other atopic symptoms (29%; a trajectory with high prevalence of both wheeze and other atopic symptoms (9%; and a trajectory with high levels of wheeze but low levels of other atopic symptoms (8%. These groups differed in terms of socio-economic markers and potential intervenable factors, including household damp and breastfeeding initiation. CONCLUSION: Using data-driven techniques, we derived four trajectories of asthmatic symptoms in early childhood in a large, population based sample. These groups differ in terms of their socio-economic profiles

  20. Using mixed methods to identify factors influencing patient flow.

    Science.gov (United States)

    Van Vaerenbergh, Cindy

    2009-11-01

    An effective method of identifying operational factors that influence patient flow can potentially lead to improvements and thus have huge benefits on the efficiency of hospital departments. This paper presents a new inductive mixed-method approach to identify operational factors that influence patient flow through an accident and emergency (A&E) department. Preliminary explorative observations were conducted, followed by semi-structured interviews with key stakeholders. A questionnaire survey of all medical, nursing, porter and clerical staff was then conducted. The observations provided factors for further exploration: skill-mix, long working hours, equipment availability, lack of orientation programmes, inefficient IT use and issues regarding communication structures. Interviewees highlighted several factors, including availability of medical supervision and senior nursing staff, nursing documentation issues, lack of morale due to overcrowding, personality differences and factors relating to the department layout. The questionnaire respondents strongly supported the importance of the previously identified factors. This paper demonstrates an effective mixed-method approach that can be replicated by other health-care managers to identify factors influencing patient flow. Further benefits include increased volume and quality of data, increased staff awareness for the influence of internal factors on patient flow and enhancing the evidence base for future decision making when prioritizing A&E projects.

  1. Identifying confounders using additive noise models

    CERN Document Server

    Janzing, Dominik; Mooij, Joris; Schoelkopf, Bernhard

    2012-01-01

    We propose a method for inferring the existence of a latent common cause ('confounder') of two observed random variables. The method assumes that the two effects of the confounder are (possibly nonlinear) functions of the confounder plus independent, additive noise. We discuss under which conditions the model is identifiable (up to an arbitrary reparameterization of the confounder) from the joint distribution of the effects. We state and prove a theoretical result that provides evidence for the conjecture that the model is generically identifiable under suitable technical conditions. In addition, we propose a practical method to estimate the confounder from a finite i.i.d. sample of the effects and illustrate that the method works well on both simulated and real-world data.

  2. How to Identify and Prioritize Psychosocial Factors Impacting Stress Level.

    Directory of Open Access Journals (Sweden)

    Mounia N Hocine

    Full Text Available We develop a methodological approach to identify and prioritize psychosocial factors (stressors requiring priority action to reduce stress levels. Data analysis was carried out on a random sample of 10 000 French employees who completed, during a routine interview with the occupational physician, a 25-item questionnaire about stress levels, as well as a questionnaire about 58 stressors grouped into 5 latent variables: job control, job context, relationships at work, tasks performed and recognition. Our method combines Importance-Performance Analysis, a valuable approach for prioritizing improvements in the quality of services, with Partial Least Squares-Path modeling, a Structural Equation Modeling approach widely applied in psychosocial research. Findings on our data suggest two areas worthy of attention: one with five stressors on which decision makers should concentrate, and another with five stressors that managers should leave alone when acting to reduce stress levels. We show that IPA is robust when answers to questions are dichotomized, as opposed to the initial 6-point Likert scale. We believe that our approach will be a useful tool for experts and decision-makers in the field of stress management and prevention.

  3. Ebola Virus Infection Modelling and Identifiability Problems

    Directory of Open Access Journals (Sweden)

    Van-Kinh eNguyen

    2015-04-01

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

  4. Identifying influential factors of business process performance using dependency analysis

    Science.gov (United States)

    Wetzstein, Branimir; Leitner, Philipp; Rosenberg, Florian; Dustdar, Schahram; Leymann, Frank

    2011-02-01

    We present a comprehensive framework for identifying influential factors of business process performance. In particular, our approach combines monitoring of process events and Quality of Service (QoS) measurements with dependency analysis to effectively identify influential factors. The framework uses data mining techniques to construct tree structures to represent dependencies of a key performance indicator (KPI) on process and QoS metrics. These dependency trees allow business analysts to determine how process KPIs depend on lower-level process metrics and QoS characteristics of the IT infrastructure. The structure of the dependencies enables a drill-down analysis of single factors of influence to gain a deeper knowledge why certain KPI targets are not met.

  5. A comparison of computational methods for identifying virulence factors.

    Directory of Open Access Journals (Sweden)

    Lu-Lu Zheng

    Full Text Available Bacterial pathogens continue to threaten public health worldwide today. Identification of bacterial virulence factors can help to find novel drug/vaccine targets against pathogenicity. It can also help to reveal the mechanisms of the related diseases at the molecular level. With the explosive growth in protein sequences generated in the postgenomic age, it is highly desired to develop computational methods for rapidly and effectively identifying virulence factors according to their sequence information alone. In this study, based on the protein-protein interaction networks from the STRING database, a novel network-based method was proposed for identifying the virulence factors in the proteomes of UPEC 536, UPEC CFT073, P. aeruginosa PAO1, L. pneumophila Philadelphia 1, C. jejuni NCTC 11168 and M. tuberculosis H37Rv. Evaluated on the same benchmark datasets derived from the aforementioned species, the identification accuracies achieved by the network-based method were around 0.9, significantly higher than those by the sequence-based methods such as BLAST, feature selection and VirulentPred. Further analysis showed that the functional associations such as the gene neighborhood and co-occurrence were the primary associations between these virulence factors in the STRING database. The high success rates indicate that the network-based method is quite promising. The novel approach holds high potential for identifying virulence factors in many other various organisms as well because it can be easily extended to identify the virulence factors in many other bacterial species, as long as the relevant significant statistical data are available for them.

  6. Model Correction Factor Method

    DEFF Research Database (Denmark)

    Christensen, Claus; Randrup-Thomsen, Søren; Morsing Johannesen, Johannes

    1997-01-01

    The model correction factor method is proposed as an alternative to traditional polynomial based response surface techniques in structural reliability considering a computationally time consuming limit state procedure as a 'black box'. The class of polynomial functions is replaced by a limit...... statebased on an idealized mechanical model to be adapted to the original limit state by the model correction factor. Reliable approximations are obtained by iterative use of gradient information on the original limit state function analogously to previous response surface approaches. However, the strength...... of the model correction factor method, is that in simpler form not using gradient information on the original limit state function or only using this information once, a drastic reduction of the number of limit state evaluation is obtained together with good approximations on the reliability. Methods...

  7. Clinicopathologic factors identify sporadic mismatch repair-defective colon cancers

    DEFF Research Database (Denmark)

    Halvarsson, Britta; Anderson, Harald; Domanska, Katarina

    2008-01-01

    risks (RRs), eg, mucinous differentiation (RR, 9.0), tumor-infiltrating lymphocytes (RR, 7.5), absence of necrosis (RR, 7.5), and expanding growth pattern (RR, 5.0) into a 7-factor index, the presence of at least 4 features identified the MMR-defective tumors with 92.3% sensitivity and 75.3% specificity...... were linked to MMR status based on immunostaining and BRAF mutation status.MMR defects were identified in 22.7% of the tumors, with 46 classified as sporadic. When the clinical parameters of age, sex, and proximal tumor location were combined with the morphologic features with the highest relative...

  8. Identifying critical factors for implementing good agricultural practice

    Directory of Open Access Journals (Sweden)

    Nelson Gutiérrez Guzmán

    2010-05-01

    Full Text Available This paper deals with identifying the critical factors (CFs involved in implementing a good agricultural practice (GAP programme for coffee and fruit farmers in the Huila department of Colombia. An exploratory factor analysis using principal component analy- sis (PCA factorisation was used. Data matrixes were constructed from the results of applying two defined-structure assessment tools to the populations being studied: Starbucks’ coffee and farmer equity (CAFE practices for small-scale coffee growers and coffee-producers and the EUREPGAP V2.1 Oct.2004 / checklist for fruit and vegetables, as applied to fruit-producers. This inves- tigation led to identifying 6 CFs which must be considered when implementing a GAP programme: infrastructure, established production activities, preparing and maintaining records, environmental awareness, workers’ welfare and safety and quality con- trol.

  9. [Investigation of Predisposition Biomarkers to Identify Risk Factors for Drug-induced Liver Injury in Humans: Analyses of Endogenous Metabolites in an Animal Model Mimicking Human Responders to APAP-induced Hepatotoxicity].

    Science.gov (United States)

    Kobayashi, Akio; Kondo, Kazuma; Sugai, Shoichiro

    2015-01-01

    Drug-induced liver injury is a main reason of regulatory action pertaining to drugs, including restrictions to clinical indications and withdrawal from the marketplace. Acetaminophen (APAP) is a commonly used and effective analgesic/antipyretic agent and relatively safe drug even in long-term treatment. However, it is known that APAP at therapeutic doses may cause hepatotoxicity in some individuals. Hence great efforts have been made to identify risk factors for APAP-induced chronic hepatotoxicity. We investigated the contribution of undernourishment to susceptibility to APAP-induced chronic hepatotoxicity using an animal model. We employed daytime restricted fed (RF) rats as a modified-nutritional state model for human APAP-induced hepatotoxicity. RF and ad libitum fed (ALF) rats were given APAP at 0, 300, and 500 mg/kg for 3 months. Plasma and urinary glutathione-related metabolomes and liver function parameters were measured during the dosing period. Endogenous metabolites forming at different levels between the RF and ALF rats could be potential predisposition biomarkers for APAP-induced hepatotoxicity. In addition, RF rats were considered a useful model to estimate the contribution of nutritional state of patients to APAP-induced chronic hepatotoxicity. In this article we report our current research focusing on nutritional state as risk factor for APAP-induced chronic hepatotoxicity and our findings of hepatotoxicity biomarkers.

  10. Identifying important motivational factors for professionals in Greek hospitals

    Science.gov (United States)

    Kontodimopoulos, Nick; Paleologou, Victoria; Niakas, Dimitris

    2009-01-01

    Background The purpose of this study was to identify important motivational factors according to the views of health-care professionals in Greek hospitals and particularly to determine if these might differ in the public and private sectors. Methods A previously developed -and validated- instrument addressing four work-related motivators (job attributes, remuneration, co-workers and achievements) was used. Three categories of health care professionals, doctors (N = 354), nurses (N = 581) and office workers (N = 418), working in public and private hospitals, participated and motivation was compared across socio-demographic and occupational variables. Results The range of reported motivational factors was mixed and Maslow's conclusions that lower level motivational factors must be met before ascending to the next level were not confirmed. The highest ranked motivator for the entire sample, and by professional subgroup, was achievements (P incentive only for professionals in managerial positions. Health professionals in private hospitals were motivated by all factors significantly more than their public-hospital counterparts. Conclusion The results are in agreement with the literature which focuses attention to management approaches employing both monetary and non-monetary incentives to motivate health care workers. This study showed that intrinsic factors are particularly important and should become a target for effective employee motivation. PMID:19754968

  11. 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

  12. IDENTIFYING MOTIVATION FACTOR INVOLVEMENT OF SARAWAK MALAY WOMEN ENTREPRENEUR

    Directory of Open Access Journals (Sweden)

    Masyantie Mohamad

    2016-03-01

    Full Text Available Sarawak multilayered cake among Sarawak product signature famous among the local as well as international tourist visiting Sarawak. In fact, Sarawak Malay women entrepreneurs have become very necessary players in the entrepreneurial field specifically in this cottage industries from the early introduction of this business, they have facing various problem in this businesses. Thus, this research aims to build an understanding of motivational factor that encourage Sarawak Malay women entrepreneurial experiences especially in multilayered cake businesses. Using qualitative methods, this research aims to identify the entrepreneurial motivations factors; with regards to start-up motivation by Sarawak Malay women. The finding shows that the motivations that influence Malay women within Kuching, Sarawak areas to start and grow their business are involve self-driven and context driven that motivate them involve in multilayered cakes businesses.

  13. Identifying important motivational factors for professionals in Greek hospitals

    Directory of Open Access Journals (Sweden)

    Niakas Dimitris

    2009-09-01

    Full Text Available Abstract Background The purpose of this study was to identify important motivational factors according to the views of health-care professionals in Greek hospitals and particularly to determine if these might differ in the public and private sectors. Methods A previously developed -and validated- instrument addressing four work-related motivators (job attributes, remuneration, co-workers and achievements was used. Three categories of health care professionals, doctors (N = 354, nurses (N = 581 and office workers (N = 418, working in public and private hospitals, participated and motivation was compared across socio-demographic and occupational variables. Results The range of reported motivational factors was mixed and Maslow's conclusions that lower level motivational factors must be met before ascending to the next level were not confirmed. The highest ranked motivator for the entire sample, and by professional subgroup, was achievements (P P Conclusion The results are in agreement with the literature which focuses attention to management approaches employing both monetary and non-monetary incentives to motivate health care workers. This study showed that intrinsic factors are particularly important and should become a target for effective employee motivation.

  14. Identify and Classify Critical Success Factor of Agile Software Development Methodology Using Mind Map

    Directory of Open Access Journals (Sweden)

    Tasneem Abd El Hameed

    2016-05-01

    Full Text Available Selecting the right method, right personnel and right practices, and applying them adequately, determine the success of software development. In this paper, a qualitative study is carried out among the critical factors of success from previous studies. The factors of success match with their relative principles to illustrate the most valuable factor for agile approach success, this paper also prove that the twelve principles poorly identified for few factors resulting from qualitative and quantitative past studies. Dimensions and Factors are presented using Critical success Dimensions and Factors Mind Map Model.

  15. An innovation resistance factor model

    Directory of Open Access Journals (Sweden)

    Siti Salwa Mohd Ishak

    2016-09-01

    Full Text Available The process and implementation strategy of information technology in construction is generally considered through the limiting prism of theoretical contexts generated from innovation diffusion and acceptance. This research argues that more attention should be given to understanding the positive effects of resistance. The study develops a theoretical framing for the Integrated Resistance Factor Model (IRFM. The framing uses a combination of diffusion of innovation theory, technology acceptance model and social network perspective. The model is tested to identify the most significant resistance factors using Partial Least Square (PLS technique. All constructs proposed in the model are found to be significant, valid and consistent with the theoretical framework. IRFM is shown to be an effective and appropriate model of user resistance factors. The most critical factors to influence technology resistance in the online project information management system (OPIMS context are: support from leaders and peers, complexity of the technology, compatibility with key work practices; and pre-trial of the technology before it is actually deployed. The study provides a new model for further research in technology innovation specific to the construction industry.

  16. Treks'n Rapids: Identifying Motivational Factors for Adventure Sports

    Directory of Open Access Journals (Sweden)

    Kshitij Saxena

    2010-01-01

    Full Text Available Problem statement: Treks’n Rapids, a leading adventure sports and human resource enrichment company in India, wanted to identify main motivational factors of attraction towards adventure sports among youths of National Capital Region. Objective was to improve the effectiveness of integrated marketing communications strategy. Adventure sports are categorized into four classes: (1 mountain sports; (2 extreme sports like bungee jumping and free fall; (3 rafting and kayaking; (4 paragliding, sky diving and skiing. A total of fifteen motivational factors have been identified with the help of literature review and an exploratory study. These are: Thrill, Requires zeal/energy, Spells status, Builds confidence, Helps in personality development, Instills self-belief, Creates unique identity, Is a stress buster, Helps in goal-setting, Is challenging, Requires toughness, Builds sense of achievement, Is a unique experience, It is fun/adventure and Improved technology has reduced risk. Approach: A questionnaire was created and sent to over 500 people online. Through word of mouth people were encouraged to visit the website and respond to the questionnaire. Fifty-seven responses were obtained. These were analyzed using SPSS. Results: Only two factors were extracted. First all the 57 responses were analyzed as a whole to find out the main motivational factors. Next each of the four individual categories of adventure sports was separately analyzed and results were found to be highly consistent. Two composite variables that emerged are labeled as: (1 characteristics of the adventure sports encompassing: thrill, challenge, fun, toughness and zeal required; (2 characteristics of the self like: building confidence, personality development, sense of achievement, status, self-belief and help in goal setting. Resultant factors were used to discriminate respondents based on gender and spend. In both the cases more than 73% of original grouped cases were found to be

  17. Identifying Human Factors Issues in Aircraft Maintenance Operations

    Science.gov (United States)

    Veinott, Elizabeth S.; Kanki, Barbara G.; Shafto, Michael G. (Technical Monitor)

    1995-01-01

    Maintenance operations incidents submitted to the Aviation Safety Reporting System (ASRS) between 1986-1992 were systematically analyzed in order to identify issues relevant to human factors and crew coordination. This exploratory analysis involved 95 ASRS reports which represented a wide range of maintenance incidents. The reports were coded and analyzed according to the type of error (e.g, wrong part, procedural error, non-procedural error), contributing factors (e.g., individual, within-team, cross-team, procedure, tools), result of the error (e.g., aircraft damage or not) as well as the operational impact (e.g., aircraft flown to destination, air return, delay at gate). The main findings indicate that procedural errors were most common (48.4%) and that individual and team actions contributed to the errors in more than 50% of the cases. As for operational results, most errors were either corrected after landing at the destination (51.6%) or required the flight crew to stop enroute (29.5%). Interactions among these variables are also discussed. This analysis is a first step toward developing a taxonomy of crew coordination problems in maintenance. By understanding what variables are important and how they are interrelated, we may develop intervention strategies that are better tailored to the human factor issues involved.

  18. On identifiability of certain latent class models.

    NARCIS (Netherlands)

    van Wieringen, W.N.

    2005-01-01

    Blischke [1962. Moment estimators for the parameters of a mixture of two binomial distributions. Ann. Math. Statist. 33, 444-454] studies a mixture of two binomials, a latent class model. In this article we generalize this model to a mixture of two products of binomials. We show when this generalize

  19. Model atmospheres - Tool for identifying interstellar features

    Science.gov (United States)

    Frisch, P. C.; Slojkowski, S. E.; Rodriguez-Bell, T.; York, D.

    1993-01-01

    Model atmosphere parameters are derived for 14 early A stars with rotation velocities, from optical spectra, in excess of 80 km/s. The models are compared with IUE observations of the stars in regions where interstellar lines are expected. In general, with the assumption of solar abundances, excellent fits are obtained in regions longward of 2580 A, and accurate interstellar equivalent widths can be derived using models to establish the continuum. The fits are poorer at shorter wavelengths, particularly at 2026-2062 A, where the stellar model parameters seem inadequate. Features indicating mass flows are evident in stars with known infrared excesses. In gamma TrA, variability in the Mg II lines is seen over the 5-year interval of these data, and also over timescales as short as 26 days. The present technique should be useful in systematic studies of episodic mass flows in A stars and for stellar abundance studies, as well as interstellar features.

  20. Ubiquitination profiling identifies sensitivity factors for IAP antagonist treatment.

    Science.gov (United States)

    Varfolomeev, Eugene; Izrael-Tomasevic, Anita; Yu, Kebing; Bustos, Daisy; Goncharov, Tatiana; Belmont, Lisa D; Masselot, Alexandre; Bakalarski, Corey E; Kirkpatrick, Donald S; Vucic, Domagoj

    2015-02-15

    Evasion of cell death is one crucial capability acquired by tumour cells to ward-off anti-tumour therapies and represents a fundamental challenge to sustaining clinical efficacy for currently available agents. Inhibitor of apoptosis (IAP) proteins use their ubiquitin E3 ligase activity to promote cancer cell survival by mediating proliferative signalling and blocking cell death in response to diverse stimuli. Using immunoaffinity enrichment and MS, ubiquitination sites on thousands of proteins were profiled upon initiation of cell death by IAP antagonists in IAP antagonist-sensitive and -resistant breast cancer cell lines. Our analyses identified hundreds of proteins with elevated levels of ubiquitin-remnant [K-GG (Lys-Gly-Gly)] peptides upon activation of cell death by the IAP antagonist BV6. The majority of these were observed in BV6-sensitive, but not-resistant, cells. Among these were known pro-apoptotic regulators, including CYC (cytochrome c), RIP1 (receptor-interacting protein 1) and a selection of proteins known to reside in the mitochondria or regulate NF-κB (nuclear factor κB) signalling. Analysis of early time-points revealed that IAP antagonist treatment stimulated rapid ubiquitination of NF-κB signalling proteins, including TRAF2 [TNF (tumour necrosis factor) receptor-associated factor 2], HOIL-1 (haem-oxidized iron-regulatory protein 2 ubiquitin ligase-1), NEMO (NF-κB essential modifier), as well as c-IAP1 (cellular IAP1) auto-ubiquitination. Knockdown of several NF-κB pathway members reduced BV6-induced cell death and TNF production in sensitive cell lines. Importantly, RIP1 was found to be constitutively ubiquitinated in sensitive breast-cancer cell lines at higher basal level than in resistant cell lines. Together, these data show the diverse and temporally defined roles of protein ubiquitination following IAP-antagonist treatment and provide critical insights into predictive diagnostics that may enhance clinical efficacy.

  1. Human Factors Model

    Science.gov (United States)

    1993-01-01

    Jack is an advanced human factors software package that provides a three dimensional model for predicting how a human will interact with a given system or environment. It can be used for a broad range of computer-aided design applications. Jack was developed by the computer Graphics Research Laboratory of the University of Pennsylvania with assistance from NASA's Johnson Space Center, Ames Research Center and the Army. It is the University's first commercial product. Jack is still used for academic purposes at the University of Pennsylvania. Commercial rights were given to Transom Technologies, Inc.

  2. Identifying differential transcription factor binding in ChIP-seq

    Directory of Open Access Journals (Sweden)

    Dai-Ying eWu

    2015-04-01

    Full Text Available ChIP seq is a widely used assay to measure genome-wide protein binding. The decrease in costs associated with sequencing has led to a rise in the number of studies that investigate protein binding across treatment conditions or cell lines. In addition to the identification of binding sites, new studies evaluate the variation in protein binding between conditions. A number of approaches to study differential transcription factor binding have recently been developed. Several of these methods build upon established methods from RNA-seq to quantify differences in read counts. We compare how these new approaches perform on different data sets from the ENCODE project to illustrate the impact of data processing pipelines under different study designs. The performance of normalization methods for differential ChIP-seq depends strongly on the variation in total amount of protein bound between conditions, with total read count outperforming effective library size, or variants thereof, when a large variation in binding was studied. Use of input subtraction to correct for non-specific binding showed a relatively modest impact on the number of differential peaks found and the fold change accuracy to biological validation, however a larger impact might be expected for samples with more extreme copy number variations between them. Still, it did identify a small subset of novel differential regions while excluding some differential peaks in regions with high background signal.These results highlight proper scaling for between-sample data normalization as critical for differential transcription factor binding analysis and suggest bioinformaticians need to know about the variation in level of total protein binding between conditions to select the best analysis method. At the same time, validation using fold-change estimates from qRT-PCR suggests there is still room for further method improvement.

  3. Identifying differential transcription factor binding in ChIP-seq.

    Science.gov (United States)

    Wu, Dai-Ying; Bittencourt, Danielle; Stallcup, Michael R; Siegmund, Kimberly D

    2015-01-01

    ChIP seq is a widely used assay to measure genome-wide protein binding. The decrease in costs associated with sequencing has led to a rise in the number of studies that investigate protein binding across treatment conditions or cell lines. In addition to the identification of binding sites, new studies evaluate the variation in protein binding between conditions. A number of approaches to study differential transcription factor binding have recently been developed. Several of these methods build upon established methods from RNA-seq to quantify differences in read counts. We compare how these new approaches perform on different data sets from the ENCODE project to illustrate the impact of data processing pipelines under different study designs. The performance of normalization methods for differential ChIP-seq depends strongly on the variation in total amount of protein bound between conditions, with total read count outperforming effective library size, or variants thereof, when a large variation in binding was studied. Use of input subtraction to correct for non-specific binding showed a relatively modest impact on the number of differential peaks found and the fold change accuracy to biological validation, however a larger impact might be expected for samples with more extreme copy number variations between them. Still, it did identify a small subset of novel differential regions while excluding some differential peaks in regions with high background signal. These results highlight proper scaling for between-sample data normalization as critical for differential transcription factor binding analysis and suggest bioinformaticians need to know about the variation in level of total protein binding between conditions to select the best analysis method. At the same time, validation using fold-change estimates from qRT-PCR suggests there is still room for further method improvement.

  4. Using an interdisciplinary approach to identify factors that affect clinicians' compliance with evidence-based guidelines.

    Science.gov (United States)

    Gurses, Ayse P; Marsteller, Jill A; Ozok, A Ant; Xiao, Yan; Owens, Sharon; Pronovost, Peter J

    2010-08-01

    Our objective was to identify factors that affect clinicians' compliance with the evidence-based guidelines using an interdisciplinary approach and develop a conceptual framework that can provide a comprehensive and practical guide for designing effective interventions. A literature review and a brainstorming session with 11 researchers from a variety of scientific disciplines were used to identify theoretical and conceptual models describing clinicians' guideline compliance. MEDLINE, EMBASE, CINAHL, and the bibliographies of the papers identified were used as data sources for identifying the relevant theoretical and conceptual models. Thirteen different models that originated from various disciplines including medicine, rural sociology, psychology, human factors and systems engineering, organizational management, marketing, and health education were identified. Four main categories of factors that affect compliance emerged from our analysis: clinician characteristics, guideline characteristics, system characteristics, and implementation characteristics. Based on these findings, we developed an interdisciplinary conceptual framework that specifies the expected interrelationships among these four categories of factors and their impact on clinicians' compliance. An interdisciplinary approach is needed to improve clinicians' compliance with evidence-based guidelines. The conceptual framework from this research can provide a comprehensive and systematic guide to identify barriers to guideline compliance and design effective interventions to improve patient safety.

  5. 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.

  6. Using Logistic Regression to Identify Risk Factors Causing Rollover Collisions

    Directory of Open Access Journals (Sweden)

    Essam Dabbour

    2012-12-01

    Full Text Available Rollover collisions are among the most serious collisions that usually result in severe injuries or fatalities. In 2009, there were 8,732 fatal rollover collisions in the United States of America that resulted in the death of 9,833 persons. Those numbers represent approximately 28% and 29% of the total numbers of fatal collisions and fatalities, respectively. The main objective of this paper is to examine the impact of different risk factors that may contribute to this type of serious collisions to help develop countermeasures that limit them. To avoid the bias that may be caused by interactions among different drivers, this analysis focuses on rollover related to single-vehicle collisions so that the behavior of the driver of the collided vehicle can be analyzed more effectively. Logistic regression technique is utilized to analyze single-vehicle rollover collisions that occurred on state and interstate highways in the states of Ohio and Washington in 2009. The results obtained from this analysis have the potential to help decision makers identify different strategies to limit the severity of this type of collisions.

  7. Identifying Common Genetic Risk Factors of Diabetic Neuropathies

    Science.gov (United States)

    Witzel, Ini-Isabée; Jelinek, Herbert F.; Khalaf, Kinda; Lee, Sungmun; Khandoker, Ahsan H.; Alsafar, Habiba

    2015-01-01

    Type 2 diabetes mellitus (T2DM) is a global public health problem of epidemic proportions, with 60–70% of affected individuals suffering from associated neurovascular complications that act on multiple organ systems. The most common and clinically significant neuropathies of T2DM include uremic neuropathy, peripheral neuropathy, and cardiac autonomic neuropathy. These conditions seriously impact an individual’s quality of life and significantly increase the risk of morbidity and mortality. Although advances in gene sequencing technologies have identified several genetic variants that may regulate the development and progression of T2DM, little is known about whether or not the variants are involved in disease progression and how these genetic variants are associated with diabetic neuropathy specifically. Significant missing heritability data and complex disease etiologies remain to be explained. This article is the first to provide a review of the genetic risk variants implicated in the diabetic neuropathies and to highlight potential commonalities. We thereby aim to contribute to the creation of a genetic-metabolic model that will help to elucidate the cause of diabetic neuropathies, evaluate a patient’s risk profile, and ultimately facilitate preventative and targeted treatment for the individual. PMID:26074879

  8. Identifying Sociological Factors for the Success of Space Exploration

    Science.gov (United States)

    Lundquist, C. A.; Tarter, D.; Coleman, A.

    Astrosociology factors relevant to success of future space exploration may best be identified through studies of sociological circumstances of past successful explorations, such as the Apollo-Lunar Missions. These studies benefit from access to primary records of the past programs. The Archives and Special Collections Division of the Salmon Library at the University of Alabama Huntsville (UAH) houses large collections of material from the early periods of the space age. The Huntsville campus of the University of Alabama System had its birth in the mid-1950s at the time when the von Braun rocket team was relocated from Texas to Huntsville. The University, the City of Huntsville and the US Government rocket organizations developed in parallel over subsequent years. As a result, the University has a significant space heritage and focus. This is true not only for the engineering and science disciplines, but also for the social sciences. The life of the University spans the period when Huntsville government and industrial organizations were responsible for producing the rocket vehicles to first take mankind to the Moon. That endeavor was surely as significant sociologically as technologically. In the 1980s, Donald E. Tarter, conducted a series of video interviews with some leading members of the original von Braun team. Although the interviews ranged over many engineering subjects, they also recorded personal features of people involved in the Apollo lunar exploration program and the interactions between these people. Such knowledge was of course an objective. These interviews are now in the collections of the UAH Library Archives, along with extensive documentation from the same period. Under sponsorship of the Archives and the NASA-Marshall Retiree Association, the interview series was restarted in 2006 to obtain comparable oral-history interviews with more than fifty US born members of the rocket team from the 1960s. Again these video interviews are rich with

  9. Identifying the Prognosis Factors in Death after Liver Transplantation via Adaptive LASSO in Iran

    Directory of Open Access Journals (Sweden)

    Hadi Raeisi Shahraki

    2016-01-01

    Full Text Available Despite the widespread use of liver transplantation as a routine therapy in liver diseases, the effective factors on its outcomes are still controversial. This study attempted to identify the most effective factors on death after liver transplantation. For this purpose, modified least absolute shrinkage and selection operator (LASSO, called Adaptive LASSO, was utilized. One of the best advantages of this method is considering high number of factors. Therefore, in a historical cohort study from 2008 to 2013, the clinical findings of 680 patients undergoing liver transplant surgery were considered. Ridge and Adaptive LASSO regression methods were then implemented to identify the most effective factors on death. To compare the performance of these two models, receiver operating characteristic (ROC curve was used. According to the results, 12 factors in Ridge regression and 9 ones in Adaptive LASSO regression were significant. The area under the ROC curve (AUC of Adaptive LASSO was equal to 89% (95% CI: 86%–91%, which was significantly greater than Ridge regression (64%, 95% CI: 61%–68% (p<0.001. As a conclusion, the significant factors and the performance criteria revealed the superiority of Adaptive LASSO method as a penalized model versus traditional regression model in the present study.

  10. Identifying and ranking the factors affecting the adoption of biofuels

    Directory of Open Access Journals (Sweden)

    Saeed Azizi

    2016-09-01

    Full Text Available This paper presents an empirical investigation to determine the important factors influencing on adoption of biofuels from consumer’s perspective. The study designs a questionnaire in Likert scale and distributes it among 211 randomly selected people who use green products in city of Tehran, Iran. Cronbach alpha is calculated as 0.812, which is well above the acceptable level. Using principle component with Varimax rotation, the study has determined five important factors including social commitment, product usefulness, infrastructure, management approach and customer oriented, which influence the most on adaptation of biofuels.

  11. Using Factor Analysis to Identify Topic Preferences Within MBA Courses

    Directory of Open Access Journals (Sweden)

    Earl Chrysler

    2003-02-01

    Full Text Available This study demonstrates the role of a principal components factor analysis in conducting a gap analysis as to the desired characteristics of business alumni. Typically, gap analyses merely compare the emphases that should be given to areas of inquiry with perceptions of actual emphases. As a result, the focus is upon depth of coverage. A neglected area in need of investigation is the breadth of topic dimensions and their differences between the normative (should offer and the descriptive (actually offer. The implications of factor structures, as well as traditional gap analyses, are developed and discussed in the context of outcomes assessment.

  12. On linear models and parameter identifiability in experimental biological systems.

    Science.gov (United States)

    Lamberton, Timothy O; Condon, Nicholas D; Stow, Jennifer L; Hamilton, Nicholas A

    2014-10-07

    A key problem in the biological sciences is to be able to reliably estimate model parameters from experimental data. This is the well-known problem of parameter identifiability. Here, methods are developed for biologists and other modelers to design optimal experiments to ensure parameter identifiability at a structural level. The main results of the paper are to provide a general methodology for extracting parameters of linear models from an experimentally measured scalar function - the transfer function - and a framework for the identifiability analysis of complex model structures using linked models. Linked models are composed by letting the output of one model become the input to another model which is then experimentally measured. The linked model framework is shown to be applicable to designing experiments to identify the measured sub-model and recover the input from the unmeasured sub-model, even in cases that the unmeasured sub-model is not identifiable. Applications for a set of common model features are demonstrated, and the results combined in an example application to a real-world experimental system. These applications emphasize the insight into answering "where to measure" and "which experimental scheme" questions provided by both the parameter extraction methodology and the linked model framework. The aim is to demonstrate the tools' usefulness in guiding experimental design to maximize parameter information obtained, based on the model structure.

  13. X-factor for innovation: identifying future excellent professionals

    NARCIS (Netherlands)

    Banis-den Hertog, Jaantje Hazina

    2016-01-01

    In this study we wanted to identify which type of individual is capable of achieving professional excellence. Our main question therefore read: which individual antecedents predict professional excellence? We chose to focus on personality traits and specifically on proactive personality - the entrep

  14. Identifying factors that influence workplace learning in postgraduate medical education.

    NARCIS (Netherlands)

    Stok-Koch, E.G.H.J.; Bolhuis, S.M.; Koopmans, R.T.C.M.

    2007-01-01

    CONTEXT: In their postgraduate educational programs, residents are immersed in a complex workplace. To improve the quality of the training program, it is necessary to gain insight into the factors that influence the process of learning in the workplace. METHODS: An exploratory study was carried out

  15. Identifying factors that influence workplace learning in postgraduate medical educaton

    NARCIS (Netherlands)

    L. Stok-Koch; R. Koopmans; Dr. S. Bolhuis

    2007-01-01

    In their postgraduate educational programs, residents are immersed in a complex workplace. To improve the quality of the training program, it is necessary to gain insight into the factors that influence the process of learning in the workplace. An exploratory study was carried out among 56 nursing

  16. Clinicopathologic factors identify sporadic mismatch repair-defective colon cancers

    DEFF Research Database (Denmark)

    Halvarsson, Britta; Anderson, Harald; Domanska, Katarina;

    2008-01-01

    Identification of sporadic mismatch repair (MMR)-defective colon cancers is increasingly demanded for decisions on adjuvant therapies. We evaluated clinicopathologic factors for the identification of these prognostically favorable tumors. Histopathologic features in 238 consecutive colon cancers...... and excluded 61.5% of the tumors from MMR testing. This clinicopathologic index thus successfully selects MMR-defective colon cancers. Udgivelsesdato: 2008-Feb...

  17. Identifying factors that influence workplace learning in postgraduate medical education.

    NARCIS (Netherlands)

    Stok-Koch, E.G.H.J.; Bolhuis, S.M.; Koopmans, R.T.C.M.

    2007-01-01

    CONTEXT: In their postgraduate educational programs, residents are immersed in a complex workplace. To improve the quality of the training program, it is necessary to gain insight into the factors that influence the process of learning in the workplace. METHODS: An exploratory study was carried out

  18. Identifying factors that influence workplace learning in postgraduate medical educaton

    NARCIS (Netherlands)

    Stok-Koch, L.; Bolhuis, S.; Koopmans, R.

    2007-01-01

    In their postgraduate educational programs, residents are immersed in a complex workplace. To improve the quality of the training program, it is necessary to gain insight into the factors that influence the process of learning in the workplace. An exploratory study was carried out among 56 nursing h

  19. Identifying the Prognosis Factors in Death after Liver Transplantation via Adaptive LASSO in Iran.

    Science.gov (United States)

    Raeisi Shahraki, Hadi; Pourahmad, Saeedeh; Ayatollahi, Seyyed Mohammad Taghi

    2016-01-01

    Despite the widespread use of liver transplantation as a routine therapy in liver diseases, the effective factors on its outcomes are still controversial. This study attempted to identify the most effective factors on death after liver transplantation. For this purpose, modified least absolute shrinkage and selection operator (LASSO), called Adaptive LASSO, was utilized. One of the best advantages of this method is considering high number of factors. Therefore, in a historical cohort study from 2008 to 2013, the clinical findings of 680 patients undergoing liver transplant surgery were considered. Ridge and Adaptive LASSO regression methods were then implemented to identify the most effective factors on death. To compare the performance of these two models, receiver operating characteristic (ROC) curve was used. According to the results, 12 factors in Ridge regression and 9 ones in Adaptive LASSO regression were significant. The area under the ROC curve (AUC) of Adaptive LASSO was equal to 89% (95% CI: 86%-91%), which was significantly greater than Ridge regression (64%, 95% CI: 61%-68%) (p LASSO method as a penalized model versus traditional regression model in the present study.

  20. Identifying factors that influence workplace learning in postgraduate medical educaton

    OpenAIRE

    Stok-Koch, L.; Bolhuis, S.; Koopmans, R.

    2007-01-01

    In their postgraduate educational programs, residents are immersed in a complex workplace. To improve the quality of the training program, it is necessary to gain insight into the factors that influence the process of learning in the workplace. An exploratory study was carried out among 56 nursing home physicians in training (NHPT) and 62 supervisors. They participated in semi-structured group interviews, in which they discussed four questions regarding workplace learning. Qualitative analysi...

  1. Identifying Protective Factors to Promote Health in American Indian and Alaska Native Adolescents: A Literature Review.

    Science.gov (United States)

    Henson, Michele; Sabo, Samantha; Trujillo, Aurora; Teufel-Shone, Nicolette

    2017-04-01

    Exposure to protective factors, conditions that protect against the occurrence of an undesirable outcome or promote the occurrence of a desirable outcome within an adolescent's environment, can foster healthy adolescent behaviors and reduce adult morbidity and mortality. Yet, little is known about the nature and effect of protective factors on the positive social and health outcomes among American Indian and Alaska Native (AIAN) adolescents. We conducted a review of the literature to identify the protective factors associated with positive health outcomes among AIAN adolescents. We consulted Elsevier Science Direct, ERIC EBSCOhost, PubMed, and the Web of Science databases. A total of 3421 articles were encountered. Excluded publications were those that did not focus on AIAN adolescents (n = 3341), did not identify protective factors (n = 56), were not original research studies (n = 8), or were not written in the English language. We identified nine categories of protective factors positively associated with health and social outcomes, including: current and/or future aspirations, personal wellness, positive self-image, self-efficacy, non-familial connectedness, family connectedness, positive opportunities, positive social norms, and cultural connectedness. Such factors positively influenced adolescent alcohol, tobacco, and substance use; delinquent and violent behavior; emotional health including depression, suicide attempt; resilience; and academic success. Protective factors spanned multiple domains of the socio-ecological model. Strengths-based health promotion efforts that leverage local, innate protective factors and work with AIANs to create environments rich in protective factors are key to improving the health and wellbeing of AIAN adolescents.

  2. Study identifies socio-cultural factors affecting demographic behaviour.

    Science.gov (United States)

    1994-01-01

    The United Nations Educational, Scientific, and Cultural Organization (UNESCO) is undertaking a project that will produce a state-of-the-art paper on sociocultural factors affecting demographic behavior. Particular emphasis will be placed on reproductive behavior in Africa, Asia, Latin America, and the Arab states region. The extent to which this information is incorporated in current population policies and programs will also be examined, and recommendations will be made. The factors to be studied include family and kinship structure; gender status and role; patterns of sexual relations and procreation in general and adolescent sexual behavior and fertility; religion, beliefs, customs, and traditions concerned with sexual relations and procreation; child rearing, socialization, and education; status and role of women; and sociocultural change, change agents, and influentials. The literature search will provide an inventory of methodologies. Guidelines on the use of the methodologies will be drafted for use by project personnel. These will later be tested in pilot studies in rural and urban communities in selected developing countries. The goal is to design programs that will accelerate contraceptive acceptance and sustain contraceptive practice by being sensitive to the sociocultural influences on the reproductive behavior of different subpopulations.

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

    Science.gov (United States)

    2016-01-01

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

  4. Shell model and spectroscopic factors

    Energy Technology Data Exchange (ETDEWEB)

    Poves, P. [Madrid Univ. Autonoma and IFT, UAM/CSIC, E-28049 (Spain)

    2007-07-01

    In these lectures, I introduce the notion of spectroscopic factor in the shell model context. A brief review is given of the present status of the large scale applications of the Interacting Shell Model. The spectroscopic factors and the spectroscopic strength are discussed for nuclei in the vicinity of magic closures and for deformed nuclei. (author)

  5. Identifying the Relevant Factors in Newspaper Advertising Effectiveness

    Directory of Open Access Journals (Sweden)

    Cristóbal Benavides

    2014-01-01

    Full Text Available Este estudio explora varios factores con el fin de establecer cuáles son losmás importantes en motivar a los lectores de periódicos locales a comprar,visitar tiendas y buscar información adicional acerca de los productos oservicios promovidos en los anuncios. El comportamiento durante el pro-ceso de compra es consecuencia de una compleja interacción de dimen-siones culturales, sociales, personales y psicológicas. Este proceso –el cualse produce antes de la acción– tiene implicaciones relevantes y los depar-tamentos de mercadeo deben prestar atención a ello. Una serie de hipóte-sis basadas en la forma como la publicidad atrae a los consumidores y encómo afecta la toma de decisiones al momento de la compra fueron puestasa prueba usando una encuesta que fue administrada a una muestra de 1.333personas encuestadas en Chile. También se realizó un análisis discriminan-te para averiguar por qué algunos lectores de periódicos se ven motivadosa comprar bienes o servicios, visitar una tienda o buscar más información.Los resultados muestran que el atractivo de la oferta anunciada es el factormás importante para explicar el comportamiento posterior del consumidor.

  6. Challenges of Identifying Communities with Shared Semantics in Enterprise Modeling

    NARCIS (Netherlands)

    Hoppenbrouwers, Stijn; Linden, D. van der

    2012-01-01

    In this paper we discuss the use and challenges of identifying communities with shared semantics in Enterprise Modeling. People tend to understand modeling meta-concepts (i.e., a modeling language’s constructs or types) in a certain way and can be grouped by this understanding. Having an insight int

  7. Modeling secondary accidents identified by traffic shock waves.

    Science.gov (United States)

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

    2016-02-01

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

  8. The cyclical component factor model

    DEFF Research Database (Denmark)

    Dahl, Christian Møller; Hansen, Henrik; Smidt, John

    Forecasting using factor models based on large data sets have received ample attention due to the models' ability to increase forecast accuracy with respect to a range of key macroeconomic variables in the US and the UK. However, forecasts based on such factor models do not uniformly outperform...... the simple autoregressive model when using data from other countries. In this paper we propose to estimate the factors based on the pure cyclical components of the series entering the large data set. Monte Carlo evidence and an empirical illustration using Danish data shows that this procedure can indeed...

  9. Comparison of Transcription Factor Binding Site Models

    KAUST Repository

    Bhuyan, Sharifulislam

    2012-05-01

    Modeling of transcription factor binding sites (TFBSs) and TFBS prediction on genomic sequences are important steps to elucidate transcription regulatory mechanism. Dependency of transcription regulation on a great number of factors such as chemical specificity, molecular structure, genomic and epigenetic characteristics, long distance interaction, makes this a challenging problem. Different experimental procedures generate evidence that DNA-binding domains of transcription factors show considerable DNA sequence specificity. Probabilistic modeling of TFBSs has been moderately successful in identifying patterns from a family of sequences. In this study, we compare performances of different probabilistic models and try to estimate their efficacy over experimental TFBSs data. We build a pipeline to calculate sensitivity and specificity from aligned TFBS sequences for several probabilistic models, such as Markov chains, hidden Markov models, Bayesian networks. Our work, containing relevant statistics and evaluation for the models, can help researchers to choose the most appropriate model for the problem at hand.

  10. 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......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...

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

    DEFF Research Database (Denmark)

    Jaeger, Manfred

    2013-01-01

    in the data. In this paper we make some initial steps to extend and adapt basic concepts of computational learnability and statistical identifiability to provide a foundation for investigating learnability in such broader contexts. We exemplify the use of the framework in three different applications...

  12. Identifying Items to Assess Methodological Quality in Physical Therapy Trials: A Factor Analysis

    Science.gov (United States)

    Cummings, Greta G.; Fuentes, Jorge; Saltaji, Humam; Ha, Christine; Chisholm, Annabritt; Pasichnyk, Dion; Rogers, Todd

    2014-01-01

    Background Numerous tools and individual items have been proposed to assess the methodological quality of randomized controlled trials (RCTs). The frequency of use of these items varies according to health area, which suggests a lack of agreement regarding their relevance to trial quality or risk of bias. Objective The objectives of this study were: (1) to identify the underlying component structure of items and (2) to determine relevant items to evaluate the quality and risk of bias of trials in physical therapy by using an exploratory factor analysis (EFA). Design A methodological research design was used, and an EFA was performed. Methods Randomized controlled trials used for this study were randomly selected from searches of the Cochrane Database of Systematic Reviews. Two reviewers used 45 items gathered from 7 different quality tools to assess the methodological quality of the RCTs. An exploratory factor analysis was conducted using the principal axis factoring (PAF) method followed by varimax rotation. Results Principal axis factoring identified 34 items loaded on 9 common factors: (1) selection bias; (2) performance and detection bias; (3) eligibility, intervention details, and description of outcome measures; (4) psychometric properties of the main outcome; (5) contamination and adherence to treatment; (6) attrition bias; (7) data analysis; (8) sample size; and (9) control and placebo adequacy. Limitation Because of the exploratory nature of the results, a confirmatory factor analysis is needed to validate this model. Conclusions To the authors' knowledge, this is the first factor analysis to explore the underlying component items used to evaluate the methodological quality or risk of bias of RCTs in physical therapy. The items and factors represent a starting point for evaluating the methodological quality and risk of bias in physical therapy trials. Empirical evidence of the association among these items with treatment effects and a confirmatory factor

  13. Identifying items to assess methodological quality in physical therapy trials: a factor analysis.

    Science.gov (United States)

    Armijo-Olivo, Susan; Cummings, Greta G; Fuentes, Jorge; Saltaji, Humam; Ha, Christine; Chisholm, Annabritt; Pasichnyk, Dion; Rogers, Todd

    2014-09-01

    Numerous tools and individual items have been proposed to assess the methodological quality of randomized controlled trials (RCTs). The frequency of use of these items varies according to health area, which suggests a lack of agreement regarding their relevance to trial quality or risk of bias. The objectives of this study were: (1) to identify the underlying component structure of items and (2) to determine relevant items to evaluate the quality and risk of bias of trials in physical therapy by using an exploratory factor analysis (EFA). A methodological research design was used, and an EFA was performed. Randomized controlled trials used for this study were randomly selected from searches of the Cochrane Database of Systematic Reviews. Two reviewers used 45 items gathered from 7 different quality tools to assess the methodological quality of the RCTs. An exploratory factor analysis was conducted using the principal axis factoring (PAF) method followed by varimax rotation. Principal axis factoring identified 34 items loaded on 9 common factors: (1) selection bias; (2) performance and detection bias; (3) eligibility, intervention details, and description of outcome measures; (4) psychometric properties of the main outcome; (5) contamination and adherence to treatment; (6) attrition bias; (7) data analysis; (8) sample size; and (9) control and placebo adequacy. Because of the exploratory nature of the results, a confirmatory factor analysis is needed to validate this model. To the authors' knowledge, this is the first factor analysis to explore the underlying component items used to evaluate the methodological quality or risk of bias of RCTs in physical therapy. The items and factors represent a starting point for evaluating the methodological quality and risk of bias in physical therapy trials. Empirical evidence of the association among these items with treatment effects and a confirmatory factor analysis of these results are needed to validate these items.

  14. Identifiability of causal effect for a simple causal model

    Institute of Scientific and Technical Information of China (English)

    郑忠国; 张艳艳; 童行伟

    2002-01-01

    Counterfactual model is put forward to discuss the causal inference in the directed acyclic graph and its corresponding identifiability is thus studied with the ancillary information based on conditional independence. It is shown that the assumption of ignorability can be expanded to the assumption of replaceability,under which the causal efiects are identifiable.

  15. 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'…

  16. Identifying interacting pairs of sites in infinite range Ising models

    CERN Document Server

    Galves, Antonio; Takahashi, Daniel Yasumasa

    2010-01-01

    We consider Ising models (pairwise interaction Gibbs probability measures) in $\\Z^d$ with an infinite range potential. We address the problem of identifying pairs of interacting sites from a finite sample of independent realisations of the Ising model. The sample contains only the values assigned by the Ising model to a finite set of sites in $\\Z^d$. Our main result is an upperbound for the probability with our estimator to misidentify the pairs of interacting sites in this finite set.

  17. Physics-based features for identifying contextual factors affecting landmine detection with ground-penetrating radar

    Science.gov (United States)

    Ratto, Christopher R.; Morton, Kenneth D., Jr.; Collins, Leslie M.; Torrione, Peter A.

    2011-06-01

    It has been established throughout the ground-penetrating radar (GPR) literature that environmental factors can severely impact the performance of GPR sensors in landmine detection applications. Over the years, electromagnetic inversion techniques have been proposed for determining these factors with the goal of mitigating performance losses. However, these techniques are often computationally expensive and require models and responses from canonical targets, and therefore may not be appropriate for real-time route-clearance applications. An alternative technique for mitigating performance changes due to environmental factors is context-dependent classification, in which decision rules are adjusted based on contextual shifts identified from the GPR data. However, analysis of the performance of context-dependent learning has been limited to qualitative comparisons of contextually-similar GPR signatures and quantitative improvement to the ROC curve, while the actual information extracted regarding soils has not been investigated thoroughly. In this work, physics-based features of GPR data used in previous context-dependent approaches were extracted from simulated GPR data generated through Finite-Difference Time-Domain (FDTD) modeling. Statistical techniques where then used to predict several potential contextual factors, including soil dielectric constant, surface roughness, amount of subsurface clutter, and the existence of subsurface layering, based on the features. Results suggest that physics-based features of the GPR background may contain informatin regarding physical properties of the environment, and contextdependent classification based on these features can exploit information regarding these potentially-important environmental factors.

  18. Genome-wide RNAi screen identifies broadly-acting host factors that inhibit arbovirus infection.

    Directory of Open Access Journals (Sweden)

    Ari Yasunaga

    2014-02-01

    Full Text Available Vector-borne viruses are an important class of emerging and re-emerging pathogens; thus, an improved understanding of the cellular factors that modulate infection in their respective vertebrate and insect hosts may aid control efforts. In particular, cell-intrinsic antiviral pathways restrict vector-borne viruses including the type I interferon response in vertebrates and the RNA interference (RNAi pathway in insects. However, it is likely that additional cell-intrinsic mechanisms exist to limit these viruses. Since insects rely on innate immune mechanisms to inhibit virus infections, we used Drosophila as a model insect to identify cellular factors that restrict West Nile virus (WNV, a flavivirus with a broad and expanding geographical host range. Our genome-wide RNAi screen identified 50 genes that inhibited WNV infection. Further screening revealed that 17 of these genes were antiviral against additional flaviviruses, and seven of these were antiviral against other vector-borne viruses, expanding our knowledge of invertebrate cell-intrinsic immunity. Investigation of two newly identified factors that restrict diverse viruses, dXPO1 and dRUVBL1, in the Tip60 complex, demonstrated they contributed to antiviral defense at the organismal level in adult flies, in mosquito cells, and in mammalian cells. These data suggest the existence of broadly acting and functionally conserved antiviral genes and pathways that restrict virus infections in evolutionarily divergent hosts.

  19. On the Identifiability of Transmission Dynamic Models for Infectious Diseases.

    Science.gov (United States)

    Lintusaari, Jarno; Gutmann, Michael U; Kaski, Samuel; Corander, Jukka

    2016-03-01

    Understanding the transmission dynamics of infectious diseases is important for both biological research and public health applications. It has been widely demonstrated that statistical modeling provides a firm basis for inferring relevant epidemiological quantities from incidence and molecular data. However, the complexity of transmission dynamic models presents two challenges: (1) the likelihood function of the models is generally not computable, and computationally intensive simulation-based inference methods need to be employed, and (2) the model may not be fully identifiable from the available data. While the first difficulty can be tackled by computational and algorithmic advances, the second obstacle is more fundamental. Identifiability issues may lead to inferences that are driven more by prior assumptions than by the data themselves. We consider a popular and relatively simple yet analytically intractable model for the spread of tuberculosis based on classical IS6110 fingerprinting data. We report on the identifiability of the model, also presenting some methodological advances regarding the inference. Using likelihood approximations, we show that the reproductive value cannot be identified from the data available and that the posterior distributions obtained in previous work have likely been substantially dominated by the assumed prior distribution. Further, we show that the inferences are influenced by the assumed infectious population size, which generally has been kept fixed in previous work. We demonstrate that the infectious population size can be inferred if the remaining epidemiological parameters are already known with sufficient precision.

  20. Similarity transformation approach to identifiability analysis of nonlinear compartmental models.

    Science.gov (United States)

    Vajda, S; Godfrey, K R; Rabitz, H

    1989-04-01

    Through use of the local state isomorphism theorem instead of the algebraic equivalence theorem of linear systems theory, the similarity transformation approach is extended to nonlinear models, resulting in finitely verifiable sufficient and necessary conditions for global and local identifiability. The approach requires testing of certain controllability and observability conditions, but in many practical examples these conditions prove very easy to verify. In principle the method also involves nonlinear state variable transformations, but in all of the examples presented in the paper the transformations turn out to be linear. The method is applied to an unidentifiable nonlinear model and a locally identifiable nonlinear model, and these are the first nonlinear models other than bilinear models where the reason for lack of global identifiability is nontrivial. The method is also applied to two models with Michaelis-Menten elimination kinetics, both of considerable importance in pharmacokinetics, and for both of which the complicated nature of the algebraic equations arising from the Taylor series approach has hitherto defeated attempts to establish identifiability results for specific input functions.

  1. On the Identifiability of the Post-Nonlinear Causal Model

    CERN Document Server

    Zhang, Kun

    2012-01-01

    By taking into account the nonlinear effect of the cause, the inner noise effect, and the measurement distortion effect in the observed variables, the post-nonlinear (PNL) causal model has demonstrated its excellent performance in distinguishing the cause from effect. However, its identifiability has not been properly addressed, and how to apply it in the case of more than two variables is also a problem. In this paper, we conduct a systematic investigation on its identifiability in the two-variable case. We show that this model is identifiable in most cases; by enumerating all possible situations in which the model is not identifiable, we provide sufficient conditions for its identifiability. Simulations are given to support the theoretical results. Moreover, in the case of more than two variables, we show that the whole causal structure can be found by applying the PNL causal model to each structure in the Markov equivalent class and testing if the disturbance is independent of the direct causes for each va...

  2. Identifiability analysis of the CSTR river water quality model.

    Science.gov (United States)

    Chen, J; Deng, Y

    2006-01-01

    Conceptual river water quality models are widely known to lack identifiability. The causes for that can be due to model structure errors, observational errors and less frequent samplings. Although significant efforts have been directed towards better identification of river water quality models, it is not clear whether a given model is structurally identifiable. Information is also limited regarding the contribution of different unidentifiability sources. Taking the widely applied CSTR river water quality model as an example, this paper presents a theoretical proof that the CSTR model is indeed structurally identifiable. Its uncertainty is thus dominantly from observational errors and less frequent samplings. Given the current monitoring accuracy and sampling frequency, the unidentifiability from sampling frequency is found to be more significant than that from observational errors. It is also noted that there is a crucial sampling frequency between 0.1 and 1 day, over which the simulated river system could be represented by different illusions and the model application could be far less reliable.

  3. Data Mining and Pattern Recognition Models for Identifying Inherited Diseases

    DEFF Research Database (Denmark)

    Iddamalgoda, Lahiru; Das, Partha S; Aponso, Achala;

    2016-01-01

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

  4. A meta-analysis to identify animal and management factors influencing gestating sow efficiency.

    Science.gov (United States)

    Douglas, S L; Szyszka, O; Stoddart, K; Edwards, S A; Kyriazakis, I

    2014-12-01

    A meta-analysis on the effects of management and animal-based factors on the reproductive efficiency of gestating sows can provide information on single-factor and interaction effects that may not have been detected in individual studies. This study analyzed the effects of such factors on the number of piglets born alive per litter (BA), piglet birth weight (BiW) and weaning weight (WW), and number of piglets born alive per kilogram of sow feed intake during gestation (BA/FI). A total of 51 papers and 7 data sources were identified for the meta-analysis, out of which 23 papers and 5 sets of production data were useable (a total of 121 treatments). The information gathered included the dependent variables as well as information regarding animal, management, and feed characteristics. While a number of factors were individually significant, the multivariate models identified significant effects only of 1) floor type (P=0.003), sow BW at the end of gestation (P=0.002), and housing (stalls vs. loose; P=0.004) on BA; as floor type and housing were confounded, they were included in 2 separate models. The BA was higher on solid (12.1) in comparison to partly slatted (11.4) and fully slatted floors (10.2); 2) sow gestation environment (P=0.017) and gestation feed allowance (P=0.046) on BiW, with BiW of pigs higher for sows kept outdoors rather than indoors (1.75 versus 1.49 kg); 3) parity number (P=0.003) and feed intake during gestation (P=0.017) on WW; in addition there was an interaction between parity number×feed ME and parity number×feed CP content of feed during gestation on WW, with the positive effects of feed ME and CP contents seen during early rather than later parities; and 4) floor type (P=0.019) and feed crude fiber (P=0.003) for BA/FI with a greater number for those kept on solid floors (5.11) versus partially and fully slatted floors (4.07 and 4.05). The meta-analysis confirmed the significant effect of several well-known factors on the efficiency of

  5. Identifying overlapping communities as well as hubs and outliers via nonnegative matrix factorization.

    Science.gov (United States)

    Cao, Xiaochun; Wang, Xiao; Jin, Di; Cao, Yixin; He, Dongxiao

    2013-10-21

    Community detection is important for understanding networks. Previous studies observed that communities are not necessarily disjoint and might overlap. It is also agreed that some outlier vertices participate in no community, and some hubs in a community might take more important roles than others. Each of these facts has been independently addressed in previous work. But there is no algorithm, to our knowledge, that can identify these three structures altogether. To overcome this limitation, we propose a novel model where vertices are measured by their centrality in communities, and define the identification of overlapping communities, hubs, and outliers as an optimization problem, calculated by nonnegative matrix factorization. We test this method on various real networks, and compare it with several competing algorithms. The experimental results not only demonstrate its ability of identifying overlapping communities, hubs, and outliers, but also validate its superior performance in terms of clustering quality.

  6. Parameter Identifiability of Ship Manoeuvring Modeling Using System Identification

    Directory of Open Access Journals (Sweden)

    Weilin Luo

    2016-01-01

    Full Text Available To improve the feasibility of system identification in the prediction of ship manoeuvrability, several measures are presented to deal with the parameter identifiability in the parametric modeling of ship manoeuvring motion based on system identification. Drift of nonlinear hydrodynamic coefficients is explained from the point of view of regression analysis. To diminish the multicollinearity in a complicated manoeuvring model, difference method and additional signal method are employed to reconstruct the samples. Moreover, the structure of manoeuvring model is simplified based on correlation analysis. Manoeuvring simulation is performed to demonstrate the validity of the measures proposed.

  7. Sufficient conditions for rate-independent hysteresis in autoregressive identified models

    Science.gov (United States)

    Martins, Samir Angelo Milani; Aguirre, Luis Antonio

    2016-06-01

    This paper shows how hysteresis can be described using polynomial models and what are the sufficient conditions to be met by the model in order to have hysteresis. Such conditions are related to the model equilibria, to the forcing function and to certain term clusters in the polynomial models. The main results of the paper are used in the identification and analysis of nonlinear models estimated from data produced by a magneto-rheological damper (MRD) model with Bouc-Wen rate-independent hysteresis. A striking feature of the identified model is its simplicity and this could turn out to be a key factor in controller design.

  8. Integrated Analysis Identifies Molecular Signatures and Specific Prognostic Factors for Different Gastric Cancer Subtypes

    Directory of Open Access Journals (Sweden)

    Li Min

    2017-02-01

    Full Text Available BACKGROUND: Gastric cancer (GC is the fifth leading cause of cancer-related deaths worldwide. As an effective and easily performed method, microscopy-based Lauren classification has been widely accepted by gastrointestinal surgeons and pathologists for GC subtyping, but molecular characteristics of different Lauren subtypes were poorly revealed. METHODS: GSE62254 was used as a derivation cohort, and GSE15459 was used as a validation cohort. The difference between diffuse and intestinal GC on the gene expression level was measured. Gene ontology (GO enrichment analysis was performed for both subgroups. Hierarchical clustering and heatmap exhibition were also performed. Kaplan-Meier plot and Cox proportional hazards model were used to evaluate survival grouped by the given genes or hierarchical clusters. RESULTS: A total of 4598 genes were found differentially expressed between diffuse and intestinal GC. Immunity- and cell adhesion–related GOs were enriched for diffuse GC, whereas DNA repair– and cell cycle–related GOs were enriched for intestinal GC. We proposed a 40-gene signature (χ2 = 30.71, P < .001 that exhibits better discrimination for prognosis than Lauren classification (χ2 = 12.11, P = .002. FRZB [RR (95% CI = 1.824 (1.115-2.986, P = .017] and EFEMP1 [RR (95% CI = 1.537 (0.969-2.437, P = .067] were identified as independent prognostic factors only in diffuse GC but not in intestinal GC patients. KRT23 [RR (95% CI = 1.616 (0.938-2.785, P = .083] was identified as an independent prognostic factor only in intestinal GC patients but not in diffuse GC patients. Similar results were achieved in the validation cohort. CONCLUSION: We found that GCs with different Lauren classifications had different molecular characteristics and identified FRZB, EFEMP1, and KRT23 as subtype-specific prognostic factors for GC patients.

  9. Caenorhabditis elegans-based screen identifies Salmonella virulence factors required for conserved host-pathogen interactions.

    Science.gov (United States)

    Tenor, Jennifer L; McCormick, Beth A; Ausubel, Frederick M; Aballay, Alejandro

    2004-06-01

    A Caenorhabditis elegans-Salmonella enterica host-pathogen model was used to identify both novel and previously known S. enterica virulence factors (HilA, HilD, InvH, SptP, RhuM, Spi4-F, PipA, VsdA, RepC, Sb25, RfaL, GmhA, LeuO, CstA, and RecC), including several related to the type III secretion system (TTSS) encoded in Salmonella pathogenicity island 1 (SPI-1). Mutants corresponding to presumptive novel virulence-related genes exhibited diminished ability to invade epithelial cells and/or to induce polymorphonuclear leukocyte migration in a tissue culture model of mammalian enteropathogenesis. When expressed in C. elegans intestinal cells, the S. enterica TTSS-exported effector protein SptP inhibited a conserved p38 MAPK signaling pathway and suppressed the diminished pathogenicity phenotype of an S. enterica sptP mutant. These results show that C. elegans is an attractive model to study the interaction between Salmonella effector proteins and components of the innate immune response, in part because there is a remarkable overlap between Salmonella virulence factors required for human and nematode pathogenesis.

  10. Identifiability and identification of a Synthesis Load Model

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    A Synthesis Load Model (SLM) including both the power load and the distribution network has been proposed in the references. The identifiability of SLM is analyzed at first, it is concluded that the model parameters are identifiable if one of the resistance, reactance and the ratio of them is known. The conclusion is validated through a simulation example. A strategy for parameter identification of SLM is proposed with the combination of the component based approach and the measurement based approach. During parameter identification, only the key parameters playing very important roles in the dynamics of the load and the system are estimated, while the other parameters playing limited role are set as the default values. The proposed strategy is verified by the field measurements.

  11. IDENTIFYING THE PARAMETERS OF THE MATHEMATICAL EXPENDITURE SYSTEM MODEL

    Directory of Open Access Journals (Sweden)

    ANA-PETRINA PĂUN

    2013-10-01

    Full Text Available This chapter describes an optimum regulation model for the public expenditures system in Romania. The aim of this work is to design an optimal control system of public expenditures in Romania. It contains an offline identification of the total public expenditures system in Romania for a timespan of 15 years. The total public expenditures system is a MISO type one (Multiple Input – Single Output and is identified by the use of the lowest foursquare applied on an OE (Output Error type model.

  12. Identifying the critical factors that influence intraocular pressure using an automated regression tree

    Directory of Open Access Journals (Sweden)

    Nishanee Rampersad

    2017-01-01

    Full Text Available Background: Assessment of intraocular pressure (IOP is an important test in glaucoma. In addition, anterior segment variables may be useful in screening for glaucoma risk. Studies have investigated the associations between IOP and anterior segment variables using traditional statistical methods. The classification and regression tree (CART method provides another dimension to detect important variables in a relationship automatically.Aim: To identify the critical factors that influence IOP using a regression tree.Methods: A quantitative cross-sectional research design was used. Anterior segment variables were measured in 700 participants using the iVue100 optical coherence tomographer, Oculus Keratograph and Nidek US-500 ultrasonographer. A Goldmann applanation tonometer was used to measure IOP. Data from only the right eyes were analysed because of high levels of interocular symmetry. A regression tree model was generated with the CART method and Pearson’s correlation coefficients were used to assess the relationships between the ocular variables.Results: The mean IOP for the entire sample was 14.63 mmHg ± 2.40 mmHg. The CART method selected three anterior segment variables in the regression tree model. Central corneal thickness was the most important variable with a cut-off value of 527 µm. The other important variables included average paracentral corneal thickness and axial anterior chamber depth. Corneal thickness measurements increased towards the periphery and were significantly correlated with IOP (r ≥ 0.50, p ≤ 0.001.Conclusion: The CART method identified the anterior segment variables that influenced IOP. Understanding the relationship between IOP and anterior segment variables may help to clinically identify patients with ocular risk factors associated with elevated IOPs.

  13. Identifying and assessing the factors affecting skill gap in digital marketing in communication industry companies

    Directory of Open Access Journals (Sweden)

    Fereshteh Ghotbifar

    2017-03-01

    Full Text Available As far as new communication channels are concerned, there have been extensive developments in communications and marketing in digital era. Today, therefore, companies try to take advantage of digital marketing channels to provide suitable services to customers to improve their satisfaction level. However, this study aimed to identify and assess factors affecting skill gap in digital marketing. This was descriptive correlation study. The population consisted of experts in communications industry to identify most important skill gaps in digital marketing and factors affecting them; also, managers and specialists of these companies were investigated to determine the role of identified factors in reducing skills gaps. Using localized questionnaire and interviewing with ten experts who were selected by Delphi snowball method, the skill gaps in marketing and factors affecting them were identified. Also, a researcher made questionnaire with 32 questions was distributed among 226 employees to investigate the identified factors role in reducing skills gap in digital marketing. The results showed that from four identified factors, the components including operational strategic factors and environmental factors had direct and positive impact on creating skill gap in digital marketing of studied companies. The environmental factors such as social and cultural conditions, religion, technology, and economy had more proactive impact on skills gap in digital marketing. Also, the results showed that among skills gaps in digital marketing of studied companies, the skills (Principles of Communication and (Predicting Future had the highest and lowest gaps, respectively.

  14. Identifying factors hampering physical activity in longstanding rheumatoid arthritis: what is the role of glucocorticoid therapy?

    Science.gov (United States)

    van der Goes, M C; Hoes, J N; Cramer, M J; van der Veen, M J; van der Werf, J H; Bijlsma, J W J; Jacobs, J W G

    2014-01-01

    To identify factors hampering the level of physical activity in longstanding rheumatoid arthritis (RA) patients, and to evaluate the effects of glucocorticoid therapy on physical activity. Patient characteristics, disease characteristics and cardiovascular parameters were recorded in 170 patients, who participated in a study about glucose metabolism in longstanding RA treated with or without glucocorticoids. Disease activity scores (DAS28) were calculated and x-rays of hands and feet were taken and scored according to the Sharp van der Heijde score (SHS). Participants completed the health assessment questionnaire and short questionnaire to assess health-enhancing physical activity (SQUASH), which reflect physical disability and physical activity, respectively. Adherence rates to recommendations on physical activity were calculated, and patients were categorised as fully adhering, insufficiently adhering (adherence on less than the recommended number of days per week) or inactive (adherence on none of the days). Forty-four percent of the patients showed adherence to the recommended minimum level of physical activity, and 22% were classified as inactive. Higher DAS28 and SHS, glucocorticoid therapy, and presence of cardiovascular risk factors were associated with lower total SQUASH physical activity scores univariately. In a multivariate model, higher age, higher body mass index (BMI), higher DAS28, and higher SHS negatively influenced the score significantly; cardiovascular risk factors and glucocorticoid therapy were no longer significantly influencing physical activity. Physical activity in longstanding RA is hampered by higher age, higher BMI, higher disease activity, and more radiographic joint damage. Glucocorticoid therapy was not identified as independent risk factor in multivariate analyses.

  15. Identifying gene regulatory network rewiring using latent differential graphical models.

    Science.gov (United States)

    Tian, Dechao; Gu, Quanquan; Ma, Jian

    2016-09-30

    Gene regulatory networks (GRNs) are highly dynamic among different tissue types. Identifying tissue-specific gene regulation is critically important to understand gene function in a particular cellular context. Graphical models have been used to estimate GRN from gene expression data to distinguish direct interactions from indirect associations. However, most existing methods estimate GRN for a specific cell/tissue type or in a tissue-naive way, or do not specifically focus on network rewiring between different tissues. Here, we describe a new method called Latent Differential Graphical Model (LDGM). The motivation of our method is to estimate the differential network between two tissue types directly without inferring the network for individual tissues, which has the advantage of utilizing much smaller sample size to achieve reliable differential network estimation. Our simulation results demonstrated that LDGM consistently outperforms other Gaussian graphical model based methods. We further evaluated LDGM by applying to the brain and blood gene expression data from the GTEx consortium. We also applied LDGM to identify network rewiring between cancer subtypes using the TCGA breast cancer samples. Our results suggest that LDGM is an effective method to infer differential network using high-throughput gene expression data to identify GRN dynamics among different cellular conditions.

  16. Bayesian Estimation of Categorical Dynamic Factor Models

    Science.gov (United States)

    Zhang, Zhiyong; Nesselroade, John R.

    2007-01-01

    Dynamic factor models have been used to analyze continuous time series behavioral data. We extend 2 main dynamic factor model variations--the direct autoregressive factor score (DAFS) model and the white noise factor score (WNFS) model--to categorical DAFS and WNFS models in the framework of the underlying variable method and illustrate them with…

  17. Functional Genomic Screen Identifies Klebsiella pneumoniae Factors Implicated in Blocking Nuclear Factor κB (NF-κB) Signaling.

    Science.gov (United States)

    Tomás, Anna; Lery, Leticia; Regueiro, Verónica; Pérez-Gutiérrez, Camino; Martínez, Verónica; Moranta, David; Llobet, Enrique; González-Nicolau, Mar; Insua, Jose L; Tomas, Juan M; Sansonetti, Philippe J; Tournebize, Régis; Bengoechea, José A

    2015-07-03

    Klebsiella pneumoniae is an etiologic agent of community-acquired and nosocomial pneumonia. It has been shown that K. pneumoniae infections are characterized by reduced early inflammatory response. Recently our group has shown that K. pneumoniae dampens the activation of inflammatory responses by antagonizing the activation of the NF-κB canonical pathway. Our results revealed that K. pneumoniae capsule polysaccharide (CPS) was necessary but not sufficient to attenuate inflammation. To identify additional Klebsiella factors required to dampen inflammation, we standardized and applied a high-throughput gain-of-function screen to examine a Klebsiella transposon mutant library. We identified 114 mutants that triggered the activation of NF-κB. Two gene ontology categories accounted for half of the loci identified in the screening: metabolism and transport genes (32% of the mutants) and envelope-related genes (17%). Characterization of the mutants revealed that the lack of the enterobactin siderophore was linked to a reduced CPS expression, which in turn underlined the NF-κB activation induced by the mutant. The lipopolysaccharide (LPS) O-polysaccharide and the pullulanase (PulA) type 2 secretion system (T2SS) are required for full effectiveness of the immune evasion. Importantly, these factors do not play a redundant role. The fact that LPS O-polysaccharide and T2SS mutant-induced responses were dependent on TLR2-TLR4-MyD88 activation suggested that LPS O-polysaccharide and PulA perturbed Toll-like receptor (TLR)-dependent recognition of K. pneumoniae. Finally, we demonstrate that LPS O-polysaccharide and pulA mutants are attenuated in the pneumonia mouse model. We propose that LPS O-polysaccharide and PulA T2SS could be new targets for the design of new antimicrobials. Increasing TLR-governed defense responses might provide also selective alternatives for the management of K. pneumoniae pneumonia.

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

    Science.gov (United States)

    Delbary, Fabrice; Garbarino, Sara; Vivaldi, Valentina

    2016-12-01

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

  19. Validation of a Predictive Model to Identify Patients at High Risk for Hospital Readmission.

    Science.gov (United States)

    Spiva, LeeAnna; Hand, Marti; VanBrackle, Lewis; McVay, Frank

    2016-01-01

    Hospital readmission is an adverse patient outcome that is serious, common, and costly. For hospitals, identifying patients at risk for hospital readmission is a priority to reduce costs and improve care. The purposes were to validate a predictive algorithm to identify patients at a high risk for preventable hospital readmission within 30 days after discharge and determine if additional risk factors enhance readmission predictability. A retrospective study was conducted on a randomized sample of 598 patients discharged from a Southeast community hospital. Data were collected from the organization's database and manually abstracted from the electronic medical record using a structured tool. Two separate logistic regression models were fit for the probability of readmission within 30 days after discharge. The first model used the LACE index as the predictor variable, and the second model used the LACE index with additional risk factors. The two models were compared to determine if additional risk factors increased the model's predictive ability. The results indicate both models have reasonable prognostic capability. The LACE index with additional risk factors did little to improve prognostication, while adding to the model's complexity. Findings support the use of the LACE index as a practical tool to identify patients at risk for readmission.

  20. Factor Analysis of the DePaul Symptom Questionnaire: Identifying Core Domains

    OpenAIRE

    Jason, Leonard A.; Sunnquist, Madison; Brown, Abigail; Furst, Jacob; Cid, Marjoe; Farietta, Jillianna; Kot, Bobby; Bloomer, Craig; Nicholson, Laura; Williams, Yolonda; Jantke, Rachel; Newton, Julia L.; Strand, Elin Bolle

    2015-01-01

    The present study attempted to identify critical symptom domains of individuals with Myalgic Encephalomyelitis (ME) and chronic fatigue syndrome (CFS). Using patient and control samples collected in the United States, Great Britain, and Norway, exploratory factor analysis (EFA) was used to establish the underlying factor structure of ME and CFS symptoms. The EFA suggested a four-factor solution: post-exertional malaise, cognitive dysfunction, sleep difficulties, and a combined factor consisti...

  1. Genome-wide screen of Pseudomonas aeruginosa In Saccharomyces cerevisiae identifies new virulence factors

    Directory of Open Access Journals (Sweden)

    Rafat eZrieq

    2015-11-01

    Full Text Available Pseudomonas aeruginosa is a human opportunistic pathogen that causes mortality in cystic fibrosis and immunocompromised patients. While many virulence factors of this pathogen have already been identified, several remain to be discovered. In this respect we set an unprecedented genome-wide screen of a P. aeruginosa expression library based on a yeast growth phenotype. 51 candidates were selected in a three-round screening process. The robustness of the screen was validated by the selection of three well known secreted proteins including one demonstrated virulence factor, the protease LepA. Further in silico sorting of the 51 candidates highlighted three potential new Pseudomonas effector candidates (Pec. By testing the cytotoxicity of wild type P. aeruginosa vs pec mutants towards macrophages and the virulence in the Caenorhabditis elegans model, we demonstrated that the three selected Pecs are novel virulence factors of P. aeruginosa. Additional cellular localization experiments in the host revealed specific localization for Pec1 and Pec2 that could inform about their respective functions.

  2. Identifying Major Factors Affecting Groundwater Change in the North China Plain with Grey Relational Analysis

    Directory of Open Access Journals (Sweden)

    Xue Li

    2014-06-01

    Full Text Available The North China Plain (NCP is facing a water crisis under the dual impact of natural and anthropogenic factors. Groundwater levels have declined continuously since 1960, causing a series of environmental problems that have restricted sustainable development in the region. In the present study, we first utilized a previously developed 3D groundwater model to determine changes in groundwater level in the region over the past 50 years (1961–2010. We then applied grey relational analysis (GRA to identify and ordinate major factors that have contributed to these changes. The results show an overall decreasing trend in groundwater levels in this region over the past 50 years and an increase in the water table depth at a rate of approximately 0.36 m/a. Groundwater exploitation showed the most significant correlation with the groundwater table decline, when compared with other factors including precipitation and river leakage. Therefore, human activities should be considered the primary force driving the groundwater level down. The results of this study have implications for developing criteria that consider changes in both climate and socio-economics. Furthermore, since the NCP is one of the most water-scarce and densely populated regions in the world, the analytical approach used in and the insights gained from this study are of international interest.

  3. Choosing Surgery: Identifying Factors Leading to Increased General Surgery Matriculation Rate.

    Science.gov (United States)

    Pointer, David T; Freeman, Matthew D; Korndorffer, James R; Meade, Peter C; Jaffe, Bernard M; Slakey, Douglas P

    2017-03-01

    Tulane graduates have, over the past six years, chosen general surgical residency at a rate above the national average (mean 9.6% vs 6.6%). With much of the recent career choice research focusing on disincentives and declining general surgery applicants, we sought to identify factors that positively influenced our students' decision to pursue general surgery. A 50-question survey was developed and distributed to graduates who matched into a general surgery between the years 2006 and 2014. The survey evaluated demographics, exposure to surgery, and factors affecting interest in a surgical career. We achieved a 54 per cent (61/112) response rate. Only 43 per cent considered a surgical career before medical school matriculation. Fifty-nine per cent had strongly considered a career other than surgery. Sixty-two per cent chose to pursue surgery during or immediately after their surgery clerkship. The most important factors cited for choosing general surgery were perceived career enjoyment of residents and faculty, resident/faculty relationship, and mentorship. Surgery residents and faculty were viewed as role models by 72 and 77 per cent of responders, respectively. This study demonstrated almost half of those choosing a surgical career did so as a direct result of the core rotation experience. We believe that structuring the medical student education experience to optimize the interaction of students, residents, and faculty produces a positive environment encouraging students to choose a general surgery career.

  4. Use of in vivo-induced antigen technology (IVIAT) to identify virulence factors of Porphyromonas gingivalis.

    Science.gov (United States)

    Wallet, Shannon M; Chung, Jin; Handfield, Martin

    2010-01-01

    Porphyromonas gingivalis is a Gram-negative anaerobic bacterium associated with the initiation and progression of adult periodontal disease. The pathogenicity of P. gingivalis is multifaceted and the infection process is influenced by both microbial and host factors. It is generally accepted that genes of a pathogen that are specifically expressed during infection are likely to be important for pathogenicity. Numerous technologies have been developed to identify these genes. A novel strategy known as in vivo-induced antigen technology (IVIAT) avoids the use of animal models and utilizes serum from patients who have experienced disease caused by the pathogen of interest. While a number of putative virulence factors have been described for P. gingivalis, the identity, relevance, and mechanisms of action of virulence factors that actually provide a selective advantage to the organism in the oral cavity of diseased patients is still unclear. Here we describe the IVIAT protocol for identification of in vivo-induced genes of P. gingivalis, which can be adapted with few modifications to any microbial pathogen.

  5. Myocyte Enhancer Factor 2C, an Osteoblast Transcription Factor Identified by Dimethyl Sulfoxide (DMSO)-enhanced Mineralization*

    Science.gov (United States)

    Stephens, Alexandre S.; Stephens, Sebastien R.; Hobbs, Carl; Hutmacher, Deitmar W.; Bacic-Welsh, Desa; Woodruff, Maria Ann; Morrison, Nigel A.

    2011-01-01

    Rapid mineralization of cultured osteoblasts could be a useful characteristic in stem cell-mediated therapies for fracture and other orthopedic problems. Dimethyl sulfoxide (DMSO) is a small amphipathic solvent molecule capable of stimulating cell differentiation. We report that, in primary human osteoblasts, DMSO dose-dependently enhanced the expression of osteoblast differentiation markers alkaline phosphatase activity and extracellular matrix mineralization. Furthermore, similar DMSO-mediated mineralization enhancement was observed in primary osteoblast-like cells differentiated from mouse mesenchymal cells derived from fat, a promising source of starter cells for cell-based therapy. Using a convenient mouse pre-osteoblast model cell line MC3T3-E1, we further investigated this phenomenon showing that numerous osteoblast-expressed genes were elevated in response to DMSO treatment and correlated with enhanced mineralization. Myocyte enhancer factor 2c (Mef2c) was identified as the transcription factor most induced by DMSO, among the numerous DMSO-induced genes, suggesting a role for Mef2c in osteoblast gene regulation. Immunohistochemistry confirmed expression of Mef2c in osteoblast-like cells in mouse mandible, cortical, and trabecular bone. shRNAi-mediated Mef2c gene silencing resulted in defective osteoblast differentiation, decreased alkaline phosphatase activity, and matrix mineralization and knockdown of osteoblast specific gene expression, including osteocalcin and bone sialoprotein. A flow on knockdown of bone-specific transcription factors, Runx2 and osterix by shRNAi knockdown of Mef2c, suggests that Mef2c lies upstream of these two important factors in the cascade of gene expression in osteoblasts. PMID:21652706

  6. Myocyte enhancer factor 2c, an osteoblast transcription factor identified by dimethyl sulfoxide (DMSO)-enhanced mineralization.

    Science.gov (United States)

    Stephens, Alexandre S; Stephens, Sebastien R; Hobbs, Carl; Hutmacher, Deitmar W; Bacic-Welsh, Desa; Woodruff, Maria Ann; Morrison, Nigel A

    2011-08-26

    Rapid mineralization of cultured osteoblasts could be a useful characteristic in stem cell-mediated therapies for fracture and other orthopedic problems. Dimethyl sulfoxide (DMSO) is a small amphipathic solvent molecule capable of stimulating cell differentiation. We report that, in primary human osteoblasts, DMSO dose-dependently enhanced the expression of osteoblast differentiation markers alkaline phosphatase activity and extracellular matrix mineralization. Furthermore, similar DMSO-mediated mineralization enhancement was observed in primary osteoblast-like cells differentiated from mouse mesenchymal cells derived from fat, a promising source of starter cells for cell-based therapy. Using a convenient mouse pre-osteoblast model cell line MC3T3-E1, we further investigated this phenomenon showing that numerous osteoblast-expressed genes were elevated in response to DMSO treatment and correlated with enhanced mineralization. Myocyte enhancer factor 2c (Mef2c) was identified as the transcription factor most induced by DMSO, among the numerous DMSO-induced genes, suggesting a role for Mef2c in osteoblast gene regulation. Immunohistochemistry confirmed expression of Mef2c in osteoblast-like cells in mouse mandible, cortical, and trabecular bone. shRNAi-mediated Mef2c gene silencing resulted in defective osteoblast differentiation, decreased alkaline phosphatase activity, and matrix mineralization and knockdown of osteoblast specific gene expression, including osteocalcin and bone sialoprotein. A flow on knockdown of bone-specific transcription factors, Runx2 and osterix by shRNAi knockdown of Mef2c, suggests that Mef2c lies upstream of these two important factors in the cascade of gene expression in osteoblasts.

  7. Sleeping Beauty mouse models identify candidate genes involved in gliomagenesis.

    Science.gov (United States)

    Vyazunova, Irina; Maklakova, Vilena I; Berman, Samuel; De, Ishani; Steffen, Megan D; Hong, Won; Lincoln, Hayley; Morrissy, A Sorana; Taylor, Michael D; Akagi, Keiko; Brennan, Cameron W; Rodriguez, Fausto J; Collier, Lara S

    2014-01-01

    Genomic studies of human high-grade gliomas have discovered known and candidate tumor drivers. Studies in both cell culture and mouse models have complemented these approaches and have identified additional genes and processes important for gliomagenesis. Previously, we found that mobilization of Sleeping Beauty transposons in mice ubiquitously throughout the body from the Rosa26 locus led to gliomagenesis with low penetrance. Here we report the characterization of mice in which transposons are mobilized in the Glial Fibrillary Acidic Protein (GFAP) compartment. Glioma formation in these mice did not occur on an otherwise wild-type genetic background, but rare gliomas were observed when mobilization occurred in a p19Arf heterozygous background. Through cloning insertions from additional gliomas generated by transposon mobilization in the Rosa26 compartment, several candidate glioma genes were identified. Comparisons to genetic, epigenetic and mRNA expression data from human gliomas implicates several of these genes as tumor suppressor genes and oncogenes in human glioblastoma.

  8. Identifying training deficiencies in military pilots by applying the human factors analysis and classification system.

    Science.gov (United States)

    Li, Wen-Chin; Harris, Don

    2013-01-01

    Without accurate analysis, it is difficult to identify training needs and develop the content of training programs required for preventing aviation accidents. The human factors analysis and classification system (HFACS) is based on Reason's system-wide model of human error. In this study, 523 accidents from the Republic of China Air Force were analyzed in which 1762 human errors were categorized. The results of the analysis showed that errors of judgment and poor decision-making were commonly reported amongst pilots. As a result, it was concluded that there was a need for military pilots to be trained specifically in making decisions in tactical environments. However, application of HFACS also allowed the identification of systemic training deficiencies within the organization further contributing to the accidents observed.

  9. Tombusvirus-yeast interactions identify conserved cell-intrinsic viral restriction factors

    Directory of Open Access Journals (Sweden)

    Zsuzsanna eSasvari

    2014-08-01

    Full Text Available To combat viral infections, plants possess innate and adaptive immune pathways, such as RNA silencing, R gene and recessive gene-mediated resistance mechanisms. However, it is likely that additional cell-intrinsic restriction factors (CIRF are also involved in limiting plant virus replication. This review discusses novel CIRFs with antiviral functions, many of them RNA-binding proteins or affecting the RNA binding activities of viral replication proteins. The CIRFs against tombusviruses have been identified in yeast (Saccharomyces cerevisiae, which is developed as an advanced model organism. Grouping of the identified CIRFs based on their known cellular functions and subcellular localization in yeast reveals that TBSV replication is limited by a wide variety of host gene functions. Yeast proteins with the highest connectivity in the network map include the well-characterized Xrn1p 5’-3’ exoribonuclease, Act1p actin protein and Cse4p centromere protein. The protein network map also reveals an important interplay between the pro-viral Hsp70 cellular chaperone and the antiviral co-chaperones, and possibly key roles for the ribosomal or ribosome-associated factors. We discuss the antiviral functions of selected CIRFs, such as the RNA binding nucleolin, ribonucleases, WW-domain proteins, single- and multi-domain cyclophilins, TPR-domain co-chaperones and cellular ion pumps. These restriction factors frequently target the RNA-binding region in the viral replication proteins, thus interfering with the recruitment of the viral RNA for replication and the assembly of the membrane-bound viral replicase. Although many of the characterized CIRFs act directly against TBSV, we propose that the TPR-domain co-chaperones function as guardians of the cellular Hsp70 chaperone system, which is subverted efficiently by TBSV for viral replicase assembly in the absence of the TPR-domain co-chaperones.

  10. Identifying and modeling the structural discontinuities of human interactions

    Science.gov (United States)

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

    2017-04-01

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

  11. Identifying work ability promoting factors for home care aides and assistant nurses

    Directory of Open Access Journals (Sweden)

    Larsson Agneta

    2012-01-01

    Full Text Available Abstract Background In workplace health promotion, all potential resources needs to be taken into consideration, not only factors relating to the absence of injury and the physical health of the workers, but also psychological aspects. A dynamic balance between the resources of the individual employees and the demands of work is an important prerequisite. In the home care services, there is a noticeable trend towards increased psychosocial strain on employees at work. There are a high frequency of work-related musculoskeletal disorders and injuries, and a low prevalence of sustainable work ability. The aim of this research was to identify factors promoting work ability and self-efficacy in care aides and assistant nurses within home care services. Methods This study is based on cross-sectional data collected in a municipality in northern Sweden. Care aides (n = 58 and assistant nurses (n = 79 replied to a self-administered questionnaire (response rate 46%. Hierarchical multiple regression analyses were performed to assess the influence of several independent variables on self-efficacy (model 1 and work ability (model 2 for care aides and assistant nurses separately. Results Perceptions of personal safety, self-efficacy and musculoskeletal wellbeing contributed to work ability for assistant nurses (R2adj of 0.36, p 2adj of 0.29, p = 0.001. Self-efficacy was associated with the safety climate and the physical demands of the job in both professions (R2adj of 0.24, p = 0.003 for care aides, and also by sex and age for the assistant nurses (R2adj of 0.31, p Conclusions The intermediate factors contributed differently to work ability in the two professions. Self-efficacy, personal safety and musculoskeletal wellbeing were important for the assistant nurses, while the work ability of the care aides was associated with the safety climate, but also with the non-changeable factors age and seniority. All these factors are important to acknowledge in

  12. MONKEY: Identifying conserved transcription-factor binding sitesin multiple alignments using a binding site-specific evolutionarymodel

    Energy Technology Data Exchange (ETDEWEB)

    Moses, Alan M.; Chiang, Derek Y.; Pollard, Daniel A.; Iyer, VenkyN.; Eisen, Michael B.

    2004-10-28

    We introduce a method (MONKEY) to identify conserved transcription-factor binding sites in multispecies alignments. MONKEY employs probabilistic models of factor specificity and binding site evolution, on which basis we compute the likelihood that putative sites are conserved and assign statistical significance to each hit. Using genomes from the genus Saccharomyces, we illustrate how the significance of real sites increases with evolutionary distance and explore the relationship between conservation and function.

  13. Case control study to identify risk factors for acute hepatitis C virus infection in Egypt

    National Research Council Canada - National Science Library

    Kandeel, Amr M; Talaat, Maha; Afifi, Salma A; El-Sayed, Nasr M; Abdel Fadeel, Moustafa A; Hajjeh, Rana A; Mahoney, Frank J

    2012-01-01

    .... We conducted a case-control study, June 2007-September 2008, to investigate risk factors for acute HCV infection in Egypt among 86 patients and 287 age and gender matched controls identified in two...

  14. A Simple Model for Identifying Critical Structures in Atrial Fibrillation

    CERN Document Server

    Christensen, Kim; Peters, Nicholas S

    2014-01-01

    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 wavefront propagation on a structure mimicking the branching network architecture of heart muscle and show how AF emerges spontaneously as age-related parameters change. We identify 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. This analytical result allows us to locate the transition in parameter space and highlights that the transition from regular to fibrillatory behaviour is a finite-size effect present in systems of any size. These clinically testable predictions might inform ablation therapies and arrhythmic risk assessment.

  15. 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…

  16. Use of the shared frailty model to identify the determinants of child ...

    African Journals Online (AJOL)

    user

    improving child survival during 5 years preceding the 2005 RDHS, all the achievements ... identify and rank order the most important factors that contributed to child survival ... observed differential performance in child survival are still not well known .... tool is the hazard function such that the Cox PH model for the individual.

  17. Identifiability of Gaussian Structural Equation Models with Same Error Variances

    CERN Document Server

    Peters, Jonas

    2012-01-01

    We consider structural equation models (SEMs) in which variables can be written as a function of their parents and noise terms (the latter are assumed to be jointly independent). Corresponding to each SEM, there is a directed acyclic graph (DAG) G_0 describing the relationships between the variables. In Gaussian SEMs with linear functions, the graph can be identified from the joint distribution only up to Markov equivalence classes (assuming faithfulness). It has been shown, however, that this constitutes an exceptional case. In the case of linear functions and non-Gaussian noise, the DAG becomes identifiable. Apart from few exceptions the same is true for non-linear functions and arbitrarily distributed additive noise. In this work, we prove identifiability for a third modification: if we require all noise variables to have the same variances, again, the DAG can be recovered from the joint Gaussian distribution. Our result can be applied to the problem of causal inference. If the data follow a Gaussian SEM w...

  18. Identifying Some Factors That Might Predispose Drug Abuse among Learners in a South African Township School

    Science.gov (United States)

    Grobler, R.; Khatite, M.

    2012-01-01

    This study inquires into some of the factors that might predispose the use and abuse of drugs among secondary school learners in a township school. The objective of this research is to identify these factors and to offer a few suggestions on how the abuse may be prevented. A quantitative research strategy is used and a document analysis technique…

  19. Combined and interactive effects of environmental and GWAS-identified risk factors in ovarian cancer

    DEFF Research Database (Denmark)

    Pearce, Celeste Leigh; Rossing, Mary Anne; Lee, Alice W

    2013-01-01

    There are several well-established environmental risk factors for ovarian cancer, and recent genome-wide association studies have also identified six variants that influence disease risk. However, the interplay between such risk factors and susceptibility loci has not been studied....

  20. 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:…

  1. Identifying Spatially Variable Sensitivity of Model Predictions and Calibrations

    Science.gov (United States)

    McKenna, S. A.; Hart, D. B.

    2005-12-01

    Stochastic inverse modeling provides an ensemble of stochastic property fields, each calibrated to measured steady-state and transient head data. These calibrated fields are used as input for predictions of other processes (e.g., contaminant transport, advective travel time). Use of the entire ensemble of fields transfers spatial uncertainty in hydraulic properties to uncertainty in the predicted performance measures. A sampling-based sensitivity coefficient is proposed to determine the sensitivity of the performance measures to the uncertain values of hydraulic properties at every cell in the model domain. The basis of this sensitivity coefficient is the Spearman rank correlation coefficient. Sampling-based sensitivity coefficients are demonstrated using a recent set of transmissivity (T) fields created through a stochastic inverse calibration process for the Culebra dolomite in the vicinity of the WIPP site in southeastern New Mexico. The stochastic inverse models were created using a unique approach to condition a geologically-based conceptual model of T to measured T values via a multiGaussian residual field. This field is calibrated to both steady-state and transient head data collected over an 11 year period. Maps of these sensitivity coefficients provide a means of identifying the locations in the study area to which both the value of the model calibration objective function and the predicted travel times to a regulatory boundary are most sensitive to the T and head values. These locations can be targeted for deployment of additional long-term monitoring resources. Comparison of areas where the calibration objective function and the travel time have high sensitivity shows that these are not necessarily coincident with regions of high uncertainty. The sampling-based sensitivity coefficients are compared to analytically derived sensitivity coefficients at the 99 pilot point locations. Results of the sensitivity mapping exercise are being used in combination

  2. Pre-Analytical Parameters Affecting Vascular Endothelial Growth Factor Measurement in Plasma: Identifying Confounders.

    Directory of Open Access Journals (Sweden)

    Johanna M Walz

    Full Text Available Vascular endothelial growth factor-A (VEGF-A is intensively investigated in various medical fields. However, comparing VEGF-A measurements is difficult because sample acquisition and pre-analytic procedures differ between studies. We therefore investigated which variables act as confounders of VEGF-A measurements.Following a standardized protocol, blood was taken at three clinical sites from six healthy participants (one male and one female participant at each center twice one week apart. The following pre-analytical parameters were varied in order to analyze their impact on VEGF-A measurements: analyzing center, anticoagulant (EDTA vs. PECT / CTAD, cannula (butterfly vs. neonatal, type of centrifuge (swing-out vs. fixed-angle, time before and after centrifugation, filling level (completely filled vs. half-filled tubes and analyzing method (ELISA vs. multiplex bead array. Additionally, intrapersonal variations over time and sex differences were explored. Statistical analysis was performed using a linear regression model.The following parameters were identified as statistically significant independent confounders of VEGF-A measurements: analyzing center, anticoagulant, centrifuge, analyzing method and sex of the proband. The following parameters were no significant confounders in our data set: intrapersonal variation over one week, cannula, time before and after centrifugation and filling level of collection tubes.VEGF-A measurement results can be affected significantly by the identified pre-analytical parameters. We recommend the use of CTAD anticoagulant, a standardized type of centrifuge and one central laboratory using the same analyzing method for all samples.

  3. Identifying the Factors Leading to Success: How an Innovative Science Curriculum Cultivates Student Motivation

    Science.gov (United States)

    Scogin, Stephen C.

    2016-06-01

    PlantingScience is an award-winning program recognized for its innovation and use of computer-supported scientist mentoring. Science learners work on inquiry-based experiments in their classrooms and communicate asynchronously with practicing plant scientist-mentors about the projects. The purpose of this study was to identify specific factors contributing to the program's effectiveness in engaging students. Using multiple data sources, grounded theory (Strauss and Corbin in Basics of qualitative research. Sage, Newbury Park, 1990) was used to develop a conceptual model identifying the central phenomenon, causal conditions, intervening conditions, strategies, contexts, and student outcomes of the project. Student motivation was determined to be the central phenomenon explaining the success of the program, with student empowerment, online mentor interaction, and authenticity of the scientific experiences serving as causal conditions. Teachers contributed to student motivation by giving students more freedom, challenging students to take projects deeper, encouraging, and scaffolding. Scientists contributed to student motivation by providing explanations, asking questions, encouraging, and offering themselves as partners in the inquiry process. Several positive student outcomes of the program were uncovered and included increased positivity, greater willingness to take projects deeper, better understanding of scientific concepts, and greater commitments to collaboration. The findings of this study provide relevant information on how to develop curriculum, use technology, and train practitioners and mentors to utilize strategies and actions that improve learners' motivation to engage in authentic science in the classroom.

  4. Simple Model for Identifying Critical Regions in Atrial Fibrillation

    Science.gov (United States)

    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. PMID:25635565

  5. Patient and carer identified factors which contribute to safety incidents in primary care: a qualitative study.

    Science.gov (United States)

    Hernan, Andrea L; Giles, Sally J; Fuller, Jeffrey; Johnson, Julie K; Walker, Christine; Dunbar, James A

    2015-09-01

    Patients can have an important role in reducing harm in primary-care settings. Learning from patient experience and feedback could improve patient safety. Evidence that captures patients' views of the various contributory factors to creating safe primary care is largely absent. The aim of this study was to address this evidence gap. Four focus groups and eight semistructured interviews were conducted with 34 patients and carers from south-east Australia. Participants were asked to describe their experiences of primary care. Audio recordings were transcribed verbatim and specific factors that contribute to safety incidents were identified in the analysis using the Yorkshire Contributory Factors Framework (YCFF). Other factors emerging from the data were also ascertained and added to the analytical framework. Thirteen factors that contribute to safety incidents in primary care were ascertained. Five unique factors for the primary-care setting were discovered in conjunction with eight factors present in the YCFF from hospital settings. The five unique primary care contributing factors to safety incidents represented a range of levels within the primary-care system from local working conditions to the upstream organisational level and the external policy context. The 13 factors included communication, access, patient factors, external policy context, dignity and respect, primary-secondary interface, continuity of care, task performance, task characteristics, time in the consultation, safety culture, team factors and the physical environment. Patient and carer feedback of this type could help primary-care professionals better understand and identify potential safety concerns and make appropriate service improvements. The comprehensive range of factors identified provides the groundwork for developing tools that systematically capture the multiple contributory factors to patient safety. Published by the BMJ Publishing Group Limited. For permission to use (where not

  6. The Infinite Hierarchical Factor Regression Model

    CERN Document Server

    Rai, Piyush

    2009-01-01

    We propose a nonparametric Bayesian factor regression model that accounts for uncertainty in the number of factors, and the relationship between factors. To accomplish this, we propose a sparse variant of the Indian Buffet Process and couple this with a hierarchical model over factors, based on Kingman's coalescent. We apply this model to two problems (factor analysis and factor regression) in gene-expression data analysis.

  7. Sleeping Beauty mouse models identify candidate genes involved in gliomagenesis.

    Directory of Open Access Journals (Sweden)

    Irina Vyazunova

    Full Text Available Genomic studies of human high-grade gliomas have discovered known and candidate tumor drivers. Studies in both cell culture and mouse models have complemented these approaches and have identified additional genes and processes important for gliomagenesis. Previously, we found that mobilization of Sleeping Beauty transposons in mice ubiquitously throughout the body from the Rosa26 locus led to gliomagenesis with low penetrance. Here we report the characterization of mice in which transposons are mobilized in the Glial Fibrillary Acidic Protein (GFAP compartment. Glioma formation in these mice did not occur on an otherwise wild-type genetic background, but rare gliomas were observed when mobilization occurred in a p19Arf heterozygous background. Through cloning insertions from additional gliomas generated by transposon mobilization in the Rosa26 compartment, several candidate glioma genes were identified. Comparisons to genetic, epigenetic and mRNA expression data from human gliomas implicates several of these genes as tumor suppressor genes and oncogenes in human glioblastoma.

  8. Sleeping Beauty Mouse Models Identify Candidate Genes Involved in Gliomagenesis

    Science.gov (United States)

    Vyazunova, Irina; Maklakova, Vilena I.; Berman, Samuel; De, Ishani; Steffen, Megan D.; Hong, Won; Lincoln, Hayley; Morrissy, A. Sorana; Taylor, Michael D.; Akagi, Keiko; Brennan, Cameron W.; Rodriguez, Fausto J.; Collier, Lara S.

    2014-01-01

    Genomic studies of human high-grade gliomas have discovered known and candidate tumor drivers. Studies in both cell culture and mouse models have complemented these approaches and have identified additional genes and processes important for gliomagenesis. Previously, we found that mobilization of Sleeping Beauty transposons in mice ubiquitously throughout the body from the Rosa26 locus led to gliomagenesis with low penetrance. Here we report the characterization of mice in which transposons are mobilized in the Glial Fibrillary Acidic Protein (GFAP) compartment. Glioma formation in these mice did not occur on an otherwise wild-type genetic background, but rare gliomas were observed when mobilization occurred in a p19Arf heterozygous background. Through cloning insertions from additional gliomas generated by transposon mobilization in the Rosa26 compartment, several candidate glioma genes were identified. Comparisons to genetic, epigenetic and mRNA expression data from human gliomas implicates several of these genes as tumor suppressor genes and oncogenes in human glioblastoma. PMID:25423036

  9. What Makes Sports Fans Interactive? Identifying Factors Affecting Chat Interactions in Online Sports Viewing.

    Directory of Open Access Journals (Sweden)

    Minsam Ko

    Full Text Available Sports fans are able to watch games from many locations using TV services while interacting with other fans online. In this paper, we identify the factors that affect sports viewers' online interactions. Using a large-scale dataset of more than 25 million chat messages from a popular social TV site for baseball, we extract various game-related factors, and investigate the relationships between these factors and fans' interactions using a series of multiple regression analyses. As a result, we identify several factors that are significantly related to viewer interactions. In addition, we determine that the influence of these factors varies according to the user group; i.e., active vs. less active users, and loyal vs. non-loyal users.

  10. Application of the transtheoretical model to identify aspects influencing condom use among Korean college students.

    Science.gov (United States)

    Kwon, Young Mi; Yeun, Eun Ja; Kim, Hee Young; Youn, Mi Sun; Cho, Ju Yeon; Lee, Hee Joo

    2008-12-01

    Increasing condom use requires an understanding of the influencing factors. Previous research has used psychosocial theories such as the social cognitive theory and health belief to explain AIDS risk factors and condom use. However, it is still difficult to effectively predict the multidimensional factors associated with condom use. The present study utilizes the transtheoretical model to investigate condom use among college students by examining stages of change for condom use and measuring decisional balance and self-efficacy for each stage. The aim was to identify the variables affecting condom use so as to provide scientific data that would aid the development of effective strategies for increasing condom use.

  11. 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.

  12. Identifying the influential aquifer heterogeneity factor on nitrate reduction processes by numerical simulation

    Science.gov (United States)

    Jang, E.; He, W.; Savoy, H.; Dietrich, P.; Kolditz, O.; Rubin, Y.; Schüth, C.; Kalbacher, T.

    2017-01-01

    Nitrate reduction reactions in groundwater systems are strongly influenced by various aquifer heterogeneity factors that affect the transport of chemical species, spatial distribution of redox reactive substances and, as a result, the overall nitrate reduction efficiency. In this study, we investigated the influence of physical and chemical aquifer heterogeneity, with a focus on nitrate transport and redox transformation processes. A numerical modeling study for simulating coupled hydrological-geochemical aquifer heterogeneity was conducted in order to improve our understanding of the influence of the aquifer heterogeneity on the nitrate reduction reactions and to identify the most influential aquifer heterogeneity factors throughout the simulation. Results show that the most influential aquifer heterogeneity factors could change over time. With abundant presence of electron donors in the high permeable zones (initial stage), physical aquifer heterogeneity significantly influences the nitrate reduction since it enables the preferential transport of nitrate to these zones and enhances mixing of reactive partners. Chemical aquifer heterogeneity plays a comparatively minor role. Increasing the spatial variability of the hydraulic conductivity also increases the nitrate removal efficiency of the system. However, ignoring chemical aquifer heterogeneity can lead to an underestimation of nitrate removals in long-term behavior. With the increase of the spatial variability of the electron donor, i.e. chemical heterogeneity, the number of the "hot spots" i.e. zones with comparably higher reactivity, should also increase. Hence, nitrate removal efficiencies will also be spatially variable but overall removal efficiency will be sustained if longer time scales are considered and nitrate fronts reach these high reactivity zones.

  13. Antibiotic Resistances in Livestock: A Comparative Approach to Identify an Appropriate Regression Model for Count Data

    Directory of Open Access Journals (Sweden)

    Anke Hüls

    2017-05-01

    Full Text Available Antimicrobial resistance in livestock is a matter of general concern. To develop hygiene measures and methods for resistance prevention and control, epidemiological studies on a population level are needed to detect factors associated with antimicrobial resistance in livestock holdings. In general, regression models are used to describe these relationships between environmental factors and resistance outcome. Besides the study design, the correlation structures of the different outcomes of antibiotic resistance and structural zero measurements on the resistance outcome as well as on the exposure side are challenges for the epidemiological model building process. The use of appropriate regression models that acknowledge these complexities is essential to assure valid epidemiological interpretations. The aims of this paper are (i to explain the model building process comparing several competing models for count data (negative binomial model, quasi-Poisson model, zero-inflated model, and hurdle model and (ii to compare these models using data from a cross-sectional study on antibiotic resistance in animal husbandry. These goals are essential to evaluate which model is most suitable to identify potential prevention measures. The dataset used as an example in our analyses was generated initially to study the prevalence and associated factors for the appearance of cefotaxime-resistant Escherichia coli in 48 German fattening pig farms. For each farm, the outcome was the count of samples with resistant bacteria. There was almost no overdispersion and only moderate evidence of excess zeros in the data. Our analyses show that it is essential to evaluate regression models in studies analyzing the relationship between environmental factors and antibiotic resistances in livestock. After model comparison based on evaluation of model predictions, Akaike information criterion, and Pearson residuals, here the hurdle model was judged to be the most appropriate

  14. Factor Analysis of the DePaul Symptom Questionnaire: Identifying Core Domains.

    Science.gov (United States)

    Jason, Leonard A; Sunnquist, Madison; Brown, Abigail; Furst, Jacob; Cid, Marjoe; Farietta, Jillianna; Kot, Bobby; Bloomer, Craig; Nicholson, Laura; Williams, Yolonda; Jantke, Rachel; Newton, Julia L; Strand, Elin Bolle

    2015-09-01

    The present study attempted to identify critical symptom domains of individuals with Myalgic Encephalomyelitis (ME) and chronic fatigue syndrome (CFS). Using patient and control samples collected in the United States, Great Britain, and Norway, exploratory factor analysis (EFA) was used to establish the underlying factor structure of ME and CFS symptoms. The EFA suggested a four-factor solution: post-exertional malaise, cognitive dysfunction, sleep difficulties, and a combined factor consisting of neuroendocrine, autonomic, and immune dysfunction symptoms. The use of empirical methods could help better understand the fundamental symptom domains of this illness.

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

    Science.gov (United States)

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

    2009-04-01

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

  16. Identifying Factors Influencing the Establishment of a Health System Reform Plan in Iran's Public Hospitals

    Directory of Open Access Journals (Sweden)

    Rasul Fani khiavi

    2016-09-01

    Full Text Available In today's world, health views have found a wider perspective in which non-medical expectations are particularly catered to. The health system reform plan seeks to improve society's health, decrease treatment costs, and increase patient satisfaction. This study investigated factors affecting the successful establishment of a health system reform plan. A mixed qualitative – quantitative approach was applied to conduct to explore influential factors associated with the establishment of a health system reform plan in Iran's public hospitals. The health systems and approaches to improving them in other countries have been studied. A Likert-based five-point questionnaire was the measurement instrument, and its content validity based on content validity ratio (CVR was 0.87. The construct validity, calculated using the factorial analysis and Kaiser Mayer Olkin (KMO techniques, was 0.964, which is a high level and suggests a correlation between the scale items. To complete the questionnaire, 185 experts, specialists, and executives of Iran’s health reform plan were selected using the Purposive Stratified Non Random Sampling and snowball methods. The data was then analyzed using exploratory factorial analysis and SPSS and LISREL software applications. The results of this research imply the existence of a pattern with a significant and direct relationship between the identified independent variables and the dependent variable of the establishment of a health system reform plan. The most important indices of establishing a health system reform plan, in the order of priority, were political support; suitable proportion and coverage of services presented in the society; management of resources; existence of necessary infrastructures; commitment of senior managers; constant planning, monitoring, and evaluation; and presentation of feedback to the plan's executives, intrasector/extrasector cooperation, and the plan’s guiding committee. Considering the

  17. A Two-Factor Model of Temperament

    OpenAIRE

    Evans, David E.; Rothbart, Mary K.

    2009-01-01

    The higher order structure of temperament was examined in two studies using the Adult Temperament Questionnaire. Because previous research showed robust levels of convergence between Rothbart’s constructs of temperament and the Big Five factors, we hypothesized a higher order two-factor model of temperament based on Digman’s higher order two-factor model of personality traits derived from factor analysis of the Big Five factors. Study 1 included 258 undergraduates. Digman’s model did not fit ...

  18. Identifying genetic modulators of the connectivity between transcription factors and their transcriptional targets.

    Science.gov (United States)

    Fazlollahi, Mina; Muroff, Ivor; Lee, Eunjee; Causton, Helen C; Bussemaker, Harmen J

    2016-03-29

    Regulation of gene expression by transcription factors (TFs) is highly dependent on genetic background and interactions with cofactors. Identifying specific context factors is a major challenge that requires new approaches. Here we show that exploiting natural variation is a potent strategy for probing functional interactions within gene regulatory networks. We developed an algorithm to identify genetic polymorphisms that modulate the regulatory connectivity between specific transcription factors and their target genes in vivo. As a proof of principle, we mapped connectivity quantitative trait loci (cQTLs) using parallel genotype and gene expression data for segregants from a cross between two strains of the yeast Saccharomyces cerevisiae We identified a nonsynonymous mutation in the DIG2 gene as a cQTL for the transcription factor Ste12p and confirmed this prediction empirically. We also identified three polymorphisms in TAF13 as putative modulators of regulation by Gcn4p. Our method has potential for revealing how genetic differences among individuals influence gene regulatory networks in any organism for which gene expression and genotype data are available along with information on binding preferences for transcription factors.

  19. An automatic system to identify heart disease risk factors in clinical texts over time.

    Science.gov (United States)

    Chen, Qingcai; Li, Haodi; Tang, Buzhou; Wang, Xiaolong; Liu, Xin; Liu, Zengjian; Liu, Shu; Wang, Weida; Deng, Qiwen; Zhu, Suisong; Chen, Yangxin; Wang, Jingfeng

    2015-12-01

    Despite recent progress in prediction and prevention, heart disease remains a leading cause of death. One preliminary step in heart disease prediction and prevention is risk factor identification. Many studies have been proposed to identify risk factors associated with heart disease; however, none have attempted to identify all risk factors. In 2014, the National Center of Informatics for Integrating Biology and Beside (i2b2) issued a clinical natural language processing (NLP) challenge that involved a track (track 2) for identifying heart disease risk factors in clinical texts over time. This track aimed to identify medically relevant information related to heart disease risk and track the progression over sets of longitudinal patient medical records. Identification of tags and attributes associated with disease presence and progression, risk factors, and medications in patient medical history were required. Our participation led to development of a hybrid pipeline system based on both machine learning-based and rule-based approaches. Evaluation using the challenge corpus revealed that our system achieved an F1-score of 92.68%, making it the top-ranked system (without additional annotations) of the 2014 i2b2 clinical NLP challenge. Copyright © 2015 Elsevier Inc. All rights reserved.

  20. Systematic review and meta-analyses of risk factors for childhood overweight identifiable during infancy

    OpenAIRE

    2012-01-01

    Objective To determine risk factors for childhood overweight that can be identified during the first year of life to facilitate early identification and targeted intervention. Design Systematic review and meta-analysis. Search strategy Electronic database search of MEDLINE, EMBASE, PubMed and CAB Abstracts. Eligibility criteria Prospective observational studies following up children from birth for at least 2 years. Results Thirty prospective studies were identified. Significant and strong ind...

  1. Identifying Risk Factors for PTSD in Women Seeking Medical Help after Rape

    OpenAIRE

    Anna Tiihonen Möller; Torbjörn Bäckström; Hans Peter Söndergaard; Lotti Helström

    2014-01-01

    Objectives: Rape has been found to be the trauma most commonly associated with Posttraumatic Stress Disorder (PTSD) among women. It is therefore important to be able to identify those women at greatest risk of developing PTSD. The aims of the present study were to analyze the PTSD prevalence six months after sexual assaults and identify the major risk factors for developing PTSD. Methods: Participants were 317 female victims of rape who sought help at the Emergency Clinic for Raped Women at S...

  2. Proteinuria in adult Saudi patients with sickle cell disease is not associated with identifiable risk factors

    OpenAIRE

    Aleem Aamer

    2010-01-01

    Renal involvement in patients with sickle cell disease (SCD) is associated with signi-ficant morbidity and mortality. Proteinuria is common in patients with SCD and is a risk factor for future development of renal failure. We sought to identify risk factors, if any, associated with pro-teinuria in adult Saudi patients with SCD. We studied 67 patients with SCD followed-up at the King Khalid University Hospital, Riyadh, Saudi Arabia. All patients underwent 24-hour urine collection to measure cr...

  3. A Fuzzy DEMATEL Method to Identify Critical Success Factors of Knowledge Management Adoption in Supply Chain

    OpenAIRE

    Sachin K. Patil; Kant, R.

    2013-01-01

    In globalisation of business, Knowledge Management (KM) plays an important role in Supply Chain (SC) to create, build and maintain competitive advantage through utilisation of knowledge and through collaborative practices. Literature review have suggested the performance of KM adoption in SC may be affected by various influencing factors but it is always difficult for the practitioners to improve all aspects at the same time. The aim of this study is to identify Critical Success Factors (CSFs...

  4. Identifying erosive periods by using RUSLE factors in mountain fields of the Central Spanish Pyrenees

    Directory of Open Access Journals (Sweden)

    M. López-Vicente

    2008-03-01

    Full Text Available The Mediterranean environment is characterized by strong temporal variations in rainfall volume and intensity, soil moisture and vegetation cover along the year. These factors play a key role on soil erosion. The aim of this work is to identify different erosive periods in function of the temporal changes in rainfall and runoff characteristics (erosivity, maximum intensity and number of erosive events, soil properties (soil erodibility in relation to freeze-thaw processes and soil moisture content and current tillage practices in a set of agricultural fields in a mountainous area of the Central Pyrenees in NE Spain. To this purpose the rainfall and runoff erosivity (R, the soil erodibility (K and the cover-management (C factors of the empirical RUSLE soil loss model were used. The R, K and C factors were calculated at monthly scale. The first erosive period extends from July to October and presents the highest values of erosivity (87.8 MJ mm ha−1 h−1, maximum rainfall intensity (22.3 mm h−1 and monthly soil erosion (0.25 Mg ha−1 month−1 with the minimum values of duration of erosive storms, freeze-thaw cycles, soil moisture content and soil erodibility (0.007 Mg h MJ−1 mm−1. This period includes the harvesting and the plowing tillage practices. The second erosive period has a duration of two months, from May to June, and presents the lowest total and monthly soil losses (0.10 Mg ha−1 month−1 that correspond to the maximum protection of the soil by the crop-cover ($C$ factor = 0.05 due to the maximum stage of the growing season and intermediate values of rainfall and runoff erosivity, maximum rainfall intensity and soil erodibility. The third erosive period extends from November to April and has the minimum values of rainfall erosivity (17.5 MJ mm ha−1 h−1 and

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

    Directory of Open Access Journals (Sweden)

    Ji Wen

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

  6. Large-scale screening of a targeted Enterococcus faecalis mutant library identifies envelope fitness factors.

    Directory of Open Access Journals (Sweden)

    Lionel Rigottier-Gois

    Full Text Available Spread of antibiotic resistance among bacteria responsible for nosocomial and community-acquired infections urges for novel therapeutic or prophylactic targets and for innovative pathogen-specific antibacterial compounds. Major challenges are posed by opportunistic pathogens belonging to the low GC% gram-positive bacteria. Among those, Enterococcus faecalis is a leading cause of hospital-acquired infections associated with life-threatening issues and increased hospital costs. To better understand the molecular properties of enterococci that may be required for virulence, and that may explain the emergence of these bacteria in nosocomial infections, we performed the first large-scale functional analysis of E. faecalis V583, the first vancomycin-resistant isolate from a human bloodstream infection. E. faecalis V583 is within the high-risk clonal complex 2 group, which comprises mostly isolates derived from hospital infections worldwide. We conducted broad-range screenings of candidate genes likely involved in host adaptation (e.g., colonization and/or virulence. For this purpose, a library was constructed of targeted insertion mutations in 177 genes encoding putative surface or stress-response factors. Individual mutants were subsequently tested for their i resistance to oxidative stress, ii antibiotic resistance, iii resistance to opsonophagocytosis, iv adherence to the human colon carcinoma Caco-2 epithelial cells and v virulence in a surrogate insect model. Our results identified a number of factors that are involved in the interaction between enterococci and their host environments. Their predicted functions highlight the importance of cell envelope glycopolymers in E. faecalis host adaptation. This study provides a valuable genetic database for understanding the steps leading E. faecalis to opportunistic virulence.

  7. siRNA Screen Identifies Trafficking Host Factors that Modulate Alphavirus Infection.

    Science.gov (United States)

    Radoshitzky, Sheli R; Pegoraro, Gianluca; Chī, Xi Olì; D Ng, Lián; Chiang, Chih-Yuan; Jozwick, Lucas; Clester, Jeremiah C; Cooper, Christopher L; Courier, Duane; Langan, David P; Underwood, Knashka; Kuehl, Kathleen A; Sun, Mei G; Caì, Yíngyún; Yú, Shu Qìng; Burk, Robin; Zamani, Rouzbeh; Kota, Krishna; Kuhn, Jens H; Bavari, Sina

    2016-03-01

    Little is known about the repertoire of cellular factors involved in the replication of pathogenic alphaviruses. To uncover molecular regulators of alphavirus infection, and to identify candidate drug targets, we performed a high-content imaging-based siRNA screen. We revealed an actin-remodeling pathway involving Rac1, PIP5K1- α, and Arp3, as essential for infection by pathogenic alphaviruses. Infection causes cellular actin rearrangements into large bundles of actin filaments termed actin foci. Actin foci are generated late in infection concomitantly with alphavirus envelope (E2) expression and are dependent on the activities of Rac1 and Arp3. E2 associates with actin in alphavirus-infected cells and co-localizes with Rac1-PIP5K1-α along actin filaments in the context of actin foci. Finally, Rac1, Arp3, and actin polymerization inhibitors interfere with E2 trafficking from the trans-Golgi network to the cell surface, suggesting a plausible model in which transport of E2 to the cell surface is mediated via Rac1- and Arp3-dependent actin remodeling.

  8. siRNA Screen Identifies Trafficking Host Factors that Modulate Alphavirus Infection.

    Directory of Open Access Journals (Sweden)

    Sheli R Radoshitzky

    2016-03-01

    Full Text Available Little is known about the repertoire of cellular factors involved in the replication of pathogenic alphaviruses. To uncover molecular regulators of alphavirus infection, and to identify candidate drug targets, we performed a high-content imaging-based siRNA screen. We revealed an actin-remodeling pathway involving Rac1, PIP5K1- α, and Arp3, as essential for infection by pathogenic alphaviruses. Infection causes cellular actin rearrangements into large bundles of actin filaments termed actin foci. Actin foci are generated late in infection concomitantly with alphavirus envelope (E2 expression and are dependent on the activities of Rac1 and Arp3. E2 associates with actin in alphavirus-infected cells and co-localizes with Rac1-PIP5K1-α along actin filaments in the context of actin foci. Finally, Rac1, Arp3, and actin polymerization inhibitors interfere with E2 trafficking from the trans-Golgi network to the cell surface, suggesting a plausible model in which transport of E2 to the cell surface is mediated via Rac1- and Arp3-dependent actin remodeling.

  9. Development and Validation of a Method to Identify Children With Social Complexity Risk Factors.

    Science.gov (United States)

    Schrager, Sheree M; Arthur, Kimberly C; Nelson, Justine; Edwards, Anne R; Murphy, J Michael; Mangione-Smith, Rita; Chen, Alex Y

    2016-09-01

    We sought to develop and validate a method to identify social complexity risk factors (eg, limited English proficiency) using Minnesota state administrative data. A secondary objective was to examine the relationship between social complexity and caregiver-reported need for care coordination. A total of 460 caregivers of children with noncomplex chronic conditions enrolled in a Minnesota public health care program were surveyed and administrative data on these caregivers and children were obtained. We validated the administrative measures by examining their concordance with caregiver-reported indicators of social complexity risk factors using tetrachoric correlations. Logistic regression analyses subsequently assessed the association between social complexity risk factors identified using Minnesota's state administrative data and caregiver-reported need for care coordination, adjusting for child demographics. Concordance between administrative and caregiver-reported data was moderate to high (correlation range 0.31-0.94, all P values risk factor was significantly associated with need for care coordination before (unadjusted odds ratio = 1.65; 95% confidence interval, 1.07-2.53) but not after adjusting for child demographic factors (adjusted odds ratio = 1.53; 95% confidence interval, 0.98-2.37). Social complexity risk factors may be accurately obtained from state administrative data. The presence of these risk factors may heighten a family's need for care coordination and/or other services for children with chronic illness, even those not considered medically complex. Copyright © 2016 by the American Academy of Pediatrics.

  10. An exploratory study to identify critical factors of innovation culture in organizations

    Directory of Open Access Journals (Sweden)

    Hamed Asgari

    2013-07-01

    Full Text Available During the past two decades, there has been a growing trend on knowledge-based organizations. Innovation, on the other hand, plays essential role on building competitive business units. In this paper, we present an exploratory study to identify critical factors of innovation culture in organizations. We detect important factors influencing innovation culture in construction industry based on the implementation of factor analysis. The proposed study designs a questionnaire and distributes it among 400 experts who are involved in construction industry. Cronbach alpha has been calculated as 0.779, which validates the overall questionnaire. The results of factor analysis have indicated that six factors of building cultural infrastructures, education, organizational vision, established culture, strategic culture and flexible culture are the most important items influencing innovation culture.

  11. Integrative transcriptome analysis identifies deregulated microRNA-transcription factor networks in lung adenocarcinoma

    DEFF Research Database (Denmark)

    Cinegaglia, Naiara C; Andrade, Sonia Cristina S; Tokar, Tomas;

    2016-01-01

    of miR-21 expression were associated with lower patient survival (p = 0.042). We identified a regulatory network including miR-15b and miR-155, and transcription factors with prognostic value in lung cancer. Our findings may contribute to the development of treatment strategies in lung adenocarcinoma....

  12. Robust and Sparse Factor Modelling

    DEFF Research Database (Denmark)

    Croux, Christophe; Exterkate, Peter

    Factor construction methods are widely used to summarize a large panel of variables by means of a relatively small number of representative factors. We propose a novel factor construction procedure that enjoys the properties of robustness to outliers and of sparsity; that is, having relatively few...... nonzero factor loadings. Compared to the traditional factor construction method, we find that this procedure leads to a favorable forecasting performance in the presence of outliers and to better interpretable factors. We investigate the performance of the method in a Monte Carlo experiment...

  13. Osteoporosis among Fallers without Concomitant Fracture Identified in an Emergency Department: Frequencies and Risk Factors

    DEFF Research Database (Denmark)

    Glintborg, Bente; Hesse, Ulrik; Houe, Thomas

    2011-01-01

    aged 50-80 years sustaining a low-energy fall without fracture were identified from an ED (n = 199). Patients answered a questionnaire on risk factors and underwent osteodensitometry. Data was compared to a group of patients routinely referred to osteodensitometry from general practice (n = 201......We aimed to determine whether the Emergency Department (ED) is a suitable entrance point for osteoporosis screening among fallers without concomitant fracture compared to referral from general practice. Furthermore, to identify factors associated with osteoporosis among fallers. Methods. Patients......). Results. Among the 199 included fallers, 41 (21%) had osteoporosis. Among these, 35 (85%) reported either previous fracture or reduced body height (>3¿cm). These two risk factors were more frequent among fallers with osteoporosis compared to fallers with normal bone mineral density or osteopenia (previous...

  14. Identifying erosive periods by using RUSLE factors in mountain fields of the Central Spanish Pyrenees

    Directory of Open Access Journals (Sweden)

    M. López-Vicente

    2007-07-01

    Full Text Available The Mediterranean environment is characterized by strong temporal variations in rainfall volume and intensity, soil moisture and vegetation cover along the year. These factors play a key role on soil erosion. The aim of this work is to identify different erosive periods in function of the temporal changes in rainfall and runoff characteristics (erosivity, maximum intensity and number of erosive events, soil properties (soil erodibility in relation to freeze-thaw processes and soil moisture content and current tillage practices in a set of agricultural fields in a mountainous area of the Central Pyrenees in NE Spain. To this purpose the rainfall and runoff erosivity (R, the soil erodibility (K and the cover-management (C factors of the empirical RUSLE soil loss model were used. The R, K and C factors were calculated at monthly scale. The first erosive period extends from July to October and presents the highest values of erosivity (87.8 MJ mm ha−1 h−1, maximum rainfall intensity (22.3 mm h−1 and monthly soil erosion (0.10 Mg ha−1 month−1 with the minimum values of duration of erosive storms, freeze-thaw cycles, soil moisture content and soil erodibility (0.007 Mg h MJ−1 mm−1. This period includes the harvesting and the plowing tillage practices. The second erosive period has a duration of two months, from May to June, and presents the lowest total and monthly soil losses (0.04 Mg ha−1 month−1 that correspond to the maximum protection of the soil by the crop-cover (C factor = 0.05 due to the maximum stage of the growing season and intermediate values of rainfall and runoff erosivity, maximum rainfall intensity and soil erodibility. The third erosive period extends from November to April and has the minimum values of rainfall erosivity (17.5 MJ mm ha−1 h−1 and maximum rainfall intensity (6.0 mm h−1

  15. Germline DNA copy number aberrations identified as potential prognostic factors for breast cancer recurrence.

    Directory of Open Access Journals (Sweden)

    Yadav Sapkota

    Full Text Available Breast cancer recurrence (BCR is a common treatment outcome despite curative-intent primary treatment of non-metastatic breast cancer. Currently used prognostic and predictive factors utilize tumor-based markers, and are not optimal determinants of risk of BCR. Germline-based copy number aberrations (CNAs have not been evaluated as determinants of predisposition to experience BCR. In this study, we accessed germline DNA from 369 female breast cancer subjects who received curative-intent primary treatment following diagnosis. Of these, 155 experienced BCR and 214 did not, after a median duration of follow up after breast cancer diagnosis of 6.35 years (range = 0.60-21.78 and 8.60 years (range = 3.08-13.57, respectively. Whole genome CNA genotyping was performed on the Affymetrix SNP array 6.0 platform. CNAs were identified using the SNP-Fast Adaptive States Segmentation Technique 2 algorithm implemented in Nexus Copy Number 6.0. Six samples were removed due to poor quality scores, leaving 363 samples for further analysis. We identified 18,561 CNAs with ≥1 kb as a predefined cut-off for observed aberrations. Univariate survival analyses (log-rank tests identified seven CNAs (two copy number gains and five copy neutral-loss of heterozygosities, CN-LOHs showing significant differences (P<2.01×10(-5 in recurrence-free survival (RFS probabilities with and without CNAs.We also observed three additional but distinct CN-LOHs showing significant differences in RFS probabilities (P<2.86×10(-5 when analyses were restricted to stratified cases (luminal A, n = 208 only. After adjusting for tumor stage and grade in multivariate analyses (Cox proportional hazards models, all the CNAs remained strongly associated with the phenotype of BCR. Of these, we confirmed three CNAs at 17q11.2, 11q13.1 and 6q24.1 in representative samples using independent genotyping platforms. Our results suggest further investigations on the potential use of germline DNA

  16. Analytic Couple Modeling Introducing Device Design Factor, Fin Factor, Thermal Diffusivity Factor, and Inductance Factor

    Science.gov (United States)

    Mackey, Jon; Sehirlioglu, Alp; Dynys, Fred

    2014-01-01

    A set of convenient thermoelectric device solutions have been derived in order to capture a number of factors which are previously only resolved with numerical techniques. The concise conversion efficiency equations derived from governing equations provide intuitive and straight-forward design guidelines. These guidelines allow for better device design without requiring detailed numerical modeling. The analytical modeling accounts for factors such as i) variable temperature boundary conditions, ii) lateral heat transfer, iii) temperature variable material properties, and iv) transient operation. New dimensionless parameters, similar to the figure of merit, are introduced including the device design factor, fin factor, thermal diffusivity factor, and inductance factor. These new device factors allow for the straight-forward description of phenomenon generally only captured with numerical work otherwise. As an example a device design factor of 0.38, which accounts for thermal resistance of the hot and cold shoes, can be used to calculate a conversion efficiency of 2.28 while the ideal conversion efficiency based on figure of merit alone would be 6.15. Likewise an ideal couple with efficiency of 6.15 will be reduced to 5.33 when lateral heat is accounted for with a fin factor of 1.0.

  17. Identifying Risk and Protective Factors in Recidivist Juvenile Offenders: A Decision Tree Approach

    Science.gov (United States)

    Ortega-Campos, Elena; García-García, Juan; Gil-Fenoy, Maria José; Zaldívar-Basurto, Flor

    2016-01-01

    Research on juvenile justice aims to identify profiles of risk and protective factors in juvenile offenders. This paper presents a study of profiles of risk factors that influence young offenders toward committing sanctionable antisocial behavior (S-ASB). Decision tree analysis is used as a multivariate approach to the phenomenon of repeated sanctionable antisocial behavior in juvenile offenders in Spain. The study sample was made up of the set of juveniles who were charged in a court case in the Juvenile Court of Almeria (Spain). The period of study of recidivism was two years from the baseline. The object of study is presented, through the implementation of a decision tree. Two profiles of risk and protective factors are found. Risk factors associated with higher rates of recidivism are antisocial peers, age at baseline S-ASB, problems in school and criminality in family members. PMID:27611313

  18. Identifying and ranking the factors affecting entrepreneurial marketing to facilitate exports

    Directory of Open Access Journals (Sweden)

    Mehdi Habibzadeh

    2016-04-01

    Full Text Available Small and medium enterprises (SMEs are believed the most important components of today’s businesses and they can boost the growth of economy. This paper presents an empirical investigation to identify and rank important factors influencing on entrepreneurial marketing to facilitate exports of SMEs. The study designs a questionnaire in Likert scale and distributes it among 387 randomly selected entrepreneurs who act as managers of some SMEs in city of Tehran, Iran. Cronbach alpha is calculated as 0.873, which is well above the acceptable level. Using principle component analysis, the study has determined four factors including competitive intelligence, competitive advantage, external factors and internal factors to facilitate the export of SMEs.

  19. Clusters of Factors Identify A High Prevalence of Pregnancy Involvement Among US Adolescent Males.

    Science.gov (United States)

    Lau, May; Lin, Hua; Flores, Glenn

    2015-08-01

    The study purpose was to use recursive partitioning analysis (RPA) to identify factors that, when clustered, are associated with a high prevalence of pregnancy involvement among US adolescent males. The National Survey of Family Growth is a nationally representative survey of individuals 15-44 years old. RPA was done for the 2002 and 2006-2010 cycles to identify factors which, when combined, identify adolescent males with the highest prevalence of pregnancy involvement. Pregnancy-involvement prevalence among adolescent males was 6 %. Two clusters of adolescent males have the highest pregnancy-involvement prevalence, at 84-87 %. In RPA, the highest pregnancy-involvement prevalence (87 %) was seen in adolescent males who ever HIV tested, had >4 lifetime sexual partners, reported less than an almost certain chance of feeling less physical pleasure with condom use, had an educational attainment of 4 lifetime sexual partners, reported less than an almost certain chance of feeling less physical pleasure with condom use, had an educational attainment ≥11th grade, were >17 years old, and had their first contraceptive education ≥10th grade, had a pregnancy-involvement prevalence of 84 %. Pregnancy-prevention efforts among adolescent males who have been involved in a pregnancy may need to target risk factors identified in clusters with the highest pregnancy prevalence to prevent subsequent pregnancies in these adolescent males and improve their future outcomes.

  20. Identifying errors in dust models from data assimilation.

    Science.gov (United States)

    Pope, R J; Marsham, J H; Knippertz, P; Brooks, M E; Roberts, A J

    2016-09-16

    Airborne mineral dust is an important component of the Earth system and is increasingly predicted prognostically in weather and climate models. The recent development of data assimilation for remotely sensed aerosol optical depths (AODs) into models offers a new opportunity to better understand the characteristics and sources of model error. Here we examine assimilation increments from Moderate Resolution Imaging Spectroradiometer AODs over northern Africa in the Met Office global forecast model. The model underpredicts (overpredicts) dust in light (strong) winds, consistent with (submesoscale) mesoscale processes lifting dust in reality but being missed by the model. Dust is overpredicted in the Sahara and underpredicted in the Sahel. Using observations of lighting and rain, we show that haboobs (cold pool outflows from moist convection) are an important dust source in reality but are badly handled by the model's convection scheme. The approach shows promise to serve as a useful framework for future model development.

  1. Sensitized mutagenesis screen in Factor V Leiden mice identifies thrombosis suppressor loci.

    Science.gov (United States)

    Westrick, Randal J; Tomberg, Kärt; Siebert, Amy E; Zhu, Guojing; Winn, Mary E; Dobies, Sarah L; Manning, Sara L; Brake, Marisa A; Cleuren, Audrey C; Hobbs, Linzi M; Mishack, Lena M; Johnston, Alexander J; Kotnik, Emilee; Siemieniak, David R; Xu, Jishu; Li, Jun Z; Saunders, Thomas L; Ginsburg, David

    2017-09-05

    Factor V Leiden (F5(L) ) is a common genetic risk factor for venous thromboembolism in humans. We conducted a sensitized N-ethyl-N-nitrosourea (ENU) mutagenesis screen for dominant thrombosuppressor genes based on perinatal lethal thrombosis in mice homozygous for F5(L) (F5(L/L) ) and haploinsufficient for tissue factor pathway inhibitor (Tfpi(+/-) ). F8 deficiency enhanced the survival of F5(L/L)Tfpi(+/-) mice, demonstrating that F5(L/L)Tfpi(+/-) lethality is genetically suppressible. ENU-mutagenized F5(L/L) males and F5(L/+)Tfpi(+/-) females were crossed to generate 6,729 progeny, with 98 F5(L/L)Tfpi(+/-) offspring surviving until weaning. Sixteen lines, referred to as "modifier of Factor 5 Leiden (MF5L1-16)," exhibited transmission of a putative thrombosuppressor to subsequent generations. Linkage analysis in MF5L6 identified a chromosome 3 locus containing the tissue factor gene (F3). Although no ENU-induced F3 mutation was identified, haploinsufficiency for F3 (F3(+/-) ) suppressed F5(L/L)Tfpi(+/-) lethality. Whole-exome sequencing in MF5L12 identified an Actr2 gene point mutation (p.R258G) as the sole candidate. Inheritance of this variant is associated with suppression of F5(L/L)Tfpi(+/-) lethality (P = 1.7 × 10(-6)), suggesting that Actr2(p.R258G) is thrombosuppressive. CRISPR/Cas9 experiments to generate an independent Actr2 knockin/knockout demonstrated that Actr2 haploinsufficiency is lethal, supporting a hypomorphic or gain-of-function mechanism of action for Actr2(p.R258G) Our findings identify F8 and the Tfpi/F3 axis as key regulators in determining thrombosis balance in the setting of F5(L) and also suggest a role for Actr2 in this process.

  2. Space Station crew safety - Human factors model

    Science.gov (United States)

    Cohen, M. M.; Junge, M. K.

    1984-01-01

    A model of the various human factors issues and interactions that might affect crew safety is developed. The first step addressed systematically the central question: How is this Space Station different from all other spacecraft? A wide range of possible issue was identified and researched. Five major topics of human factors issues that interacted with crew safety resulted: Protocols, Critical Habitability, Work Related Issues, Crew Incapacitation and Personal Choice. Second, an interaction model was developed that would show some degree of cause and effect between objective environmental or operational conditions and the creation of potential safety hazards. The intermediary steps between these two extremes of causality were the effects on human performance and the results of degraded performance. The model contains three milestones: stressor, human performance (degraded) and safety hazard threshold. Between these milestones are two countermeasure intervention points. The first opportunity for intervention is the countermeasure against stress. If this countermeasure fails, performance degrades. The second opportunity for intervention is the countermeasure against error. If this second countermeasure fails, the threshold of a potential safety hazard may be crossed.

  3. Identify and prioritize effective business process re-engineering factors on organizational agility: case study of Ports & Maritime Organization

    Directory of Open Access Journals (Sweden)

    Mohammad Mahmoodi

    2014-05-01

    Full Text Available The present study intended to identify and prioritize effective business process reengineering factors on organizational agility in the Ports & Maritime organization of Iran. Initially the theoretical principles were discussed. The data gathered in this stage provided us with the possibility to present a conceptual framework for the study. Subsequently, through interviewing with experts, some indices for evaluating the variables in the model were identified. On the following stage, a questionnaire was developed. The questionnaire included 55 items, based on a 5-point Likert scale. After determining the validity and reliability of the questionnaire, 104 experts in Ports & Maritime organization completed the questionnaire. The results of the research revealed that leadership and empowerment variables had the most effect on organizational agility than other variables. After extracting the final model, the variables of the model were prioritized with DEMATEL technique.

  4. Functional genomics identifies a requirement of pre-mRNA splicing factors for sister chromatid cohesion.

    Science.gov (United States)

    Sundaramoorthy, Sriramkumar; Vázquez-Novelle, María Dolores; Lekomtsev, Sergey; Howell, Michael; Petronczki, Mark

    2014-11-18

    Sister chromatid cohesion mediated by the cohesin complex is essential for chromosome segregation during cell division. Using functional genomic screening, we identify a set of 26 pre-mRNA splicing factors that are required for sister chromatid cohesion in human cells. Loss of spliceosome subunits increases the dissociation rate of cohesin from chromatin and abrogates cohesion after DNA replication, ultimately causing mitotic catastrophe. Depletion of splicing factors causes defective processing of the pre-mRNA encoding sororin, a factor required for the stable association of cohesin with chromatin, and an associated reduction of sororin protein level. Expression of an intronless version of sororin and depletion of the cohesin release protein WAPL suppress the cohesion defect in cells lacking splicing factors. We propose that spliceosome components contribute to sister chromatid cohesion and mitotic chromosome segregation through splicing of sororin pre-mRNA. Our results highlight the loss of cohesion as an early cellular consequence of compromised splicing. This may have clinical implications because SF3B1, a splicing factor that we identify to be essential for cohesion, is recurrently mutated in chronic lymphocytic leukaemia.

  5. Detecting Social Desirability Bias Using Factor Mixture Models

    Science.gov (United States)

    Leite, Walter L.; Cooper, Lou Ann

    2010-01-01

    Based on the conceptualization that social desirable bias (SDB) is a discrete event resulting from an interaction between a scale's items, the testing situation, and the respondent's latent trait on a social desirability factor, we present a method that makes use of factor mixture models to identify which examinees are most likely to provide…

  6. Identifying factors associated with changes in CD4+ count in HIV-infected adults in Saskatoon, Saskatchewan

    Science.gov (United States)

    Hunt, Kelsey; Mondal, Prosanta; Konrad, Stephanie; Skinner, Stuart; Gartner, Kali; Lim, Hyun J

    2015-01-01

    OBJECTIVE: To assess the impact of clinical and social factors unique to HIV-infected adults in Saskatoon, Saskatchewan, regarding the rate of CD4+ count change, and to identify factors associated with a risk of CD4+ count decline. METHODS: A retrospective longitudinal cohort study from medical chart reviews at two clinics was conducted in Saskatoon. Univariate and multivariate linear mixed effects models were used to assess the impact of selected factors on CD4+ count change. RESULTS: Four hundred eleven HIV-infected patients were identified from January 1, 2003 to November 30, 2011. Two hundred eighteen (53%) were male, mean (± SD) age was 35.6 ±10.1 years, 257 (70.8%) were First Nations or Métis, 312 (80.2%) were hepatitis C virus (HCV) coinfected and 300 (73.3%) had a history of injection drug use (IDU). In univariate models, age, ethnicity, HCV, IDU, antiretroviral therapy and social assistance were significant. Using ethnicity, HCV and IDU, three multivariate models (models 1, 2, 3) were built due to high correlation. First Nations or Métis ethnicity, HCV coinfection and a history of IDU were associated with significantly lower CD4+ counts in multivariate models. Older age and social assistance were associated with significantly lower CD4+ counts in models 1 and 3. Age was marginally significant in model 2 (P=0.055). Not prescribed antiretroviral therapy was associated with a significantly negative CD4+ count slope in all multivariate models. CONCLUSION: The unique epidemiology of this HIV-infected population may be contributing to CD4+ count change. Increased attention and resources focused on this high-risk population are needed to prevent disease progression and to improve overall health and quality of life. PMID:26361489

  7. Shape Factor Modeling and Simulation

    Science.gov (United States)

    2016-06-01

    10 3. Shape Factor Distributions for Natural Fragments 12 3.1 Platonic Solids and Uniform Viewing from All Viewpoints 12 3.2 Natural Fragments from...12 Fig. 9 The 5 Platonic solids. ............................................................. 12 Fig. 10 Mean shape factor of...of the 5 Platonic solids............................................ 13 Table 3 Sequence of viewing angles in Icosahedron Gage

  8. Factors associated with stroke survivor behaviors as identified by family caregivers.

    Science.gov (United States)

    Gonzalez, Carmanny; Bakas, Tamilyn

    2013-01-01

    Stroke survivor behaviors that caregivers identify as bothersome can lead to family caregiver stress, which can result in premature institutionalization of the survivor. The purpose of this study was to explore demographic and theory-based factors associated with survivor bothersome behaviors as identified by family caregivers. A secondary analysis of a combined sample of 96 family caregivers of stroke survivors was conducted using baseline data from two existing studies. Bothersome behaviors were measured using the Revised Memory and Behavior Problems Checklist (RMBPC). Theory-based factors were measured using well-validated scales. Male stroke survivors exhibited more bothersome behaviors (t = 3.53, p caregiver depressive symptoms, task difficulty, life changes, and threat appraisal (F[5, 88] = 10.82, p caregivers. © 2013 Association of Rehabilitation Nurses.

  9. Skewed factor models using selection mechanisms

    KAUST Repository

    Kim, Hyoung-Moon

    2015-12-21

    Traditional factor models explicitly or implicitly assume that the factors follow a multivariate normal distribution; that is, only moments up to order two are involved. However, it may happen in real data problems that the first two moments cannot explain the factors. Based on this motivation, here we devise three new skewed factor models, the skew-normal, the skew-tt, and the generalized skew-normal factor models depending on a selection mechanism on the factors. The ECME algorithms are adopted to estimate related parameters for statistical inference. Monte Carlo simulations validate our new models and we demonstrate the need for skewed factor models using the classic open/closed book exam scores dataset.

  10. Using an Electronic Medical Records Database to Identify Non-Traditional Cardiovascular Risk Factors in Nonalcoholic Fatty Liver Disease.

    Science.gov (United States)

    Corey, Kathleen E; Kartoun, Uri; Zheng, Hui; Chung, Raymond T; Shaw, Stanley Y

    2016-05-01

    Among adults with nonalcoholic fatty liver disease (NAFLD), 25% of deaths are attributable to cardiovascular disease (CVD). CVD risk reduction in NAFLD requires not only modification of traditional CVD risk factors but identification of risk factors unique to NAFLD. In a NAFLD cohort, we sought to identify non-traditional risk factors associated with CVD. NAFLD was determined by a previously described algorithm and a multivariable logistic regression model determined predictors of CVD. Of the 8,409 individuals with NAFLD, 3,243 had CVD and 5,166 did not. On multivariable analysis, CVD among NAFLD patients was associated with traditional CVD risk factors including family history of CVD (OR 4.25, P=0.0007), hypertension (OR 2.54, P=0.0017), renal failure (OR 1.59, P=0.04), and age (OR 1.05, Prisk factors including albumin, sodium, and Model for End-Stage Liver Disease (MELD) score were associated with CVD. On multivariable analysis, an increased MELD score (OR 1.10, Prisk of CVD. Albumin (OR 0.52, P0.676 than those with a score ≤0.676 (39 vs. 20%, Prisk factors, as well as higher MELD scores and lower albumin and sodium levels. Individuals with evidence of advanced fibrosis were more likely to have CVD. These findings suggest that the drivers of NAFLD may also promote CVD development and progression.

  11. Identifying factors for job motivation of rural health workers in North Viet Nam.

    Science.gov (United States)

    Dieleman, Marjolein; Cuong, Pham Viet; Anh, Le Vu; Martineau, Tim

    2003-11-05

    BACKGROUND: In Viet Nam, most of the public health staff (84%) currently works in rural areas, where 80% of the people live. To provide good quality health care services, it is important to develop strategies influencing staff motivation for better performance. METHOD: An exploratory qualitative research was carried out among health workers in two provinces in North Viet Nam so as to identify entry points for developing strategies that improve staff performance in rural areas. The study aimed to determine the major motivating factors and it is the first in Viet Nam that looks at health workers' job perception and motivation. Apart from health workers, managers at national and at provincial level were interviewed as well as some community representatives. RESULTS: The study showed that motivation is influenced by both financial and non-financial incentives. The main motivating factors for health workers were appreciation by managers, colleagues and the community, a stable job and income and training. The main discouraging factors were related to low salaries and difficult working conditions. CONCLUSION: Activities associated with appreciation such as performance management are currently not optimally implemented, as health workers perceive supervision as control, selection for training as unclear and unequal, and performance appraisal as not useful. The kind of non-financial incentives identified should be taken into consideration when developing HRM strategies. Areas for further studies are identified.

  12. Identifying factors for job motivation of rural health workers in North Viet Nam

    Directory of Open Access Journals (Sweden)

    Anh Le

    2003-11-01

    Full Text Available Abstract Background In Viet Nam, most of the public health staff (84% currently works in rural areas, where 80% of the people live. To provide good quality health care services, it is important to develop strategies influencing staff motivation for better performance. Method An exploratory qualitative research was carried out among health workers in two provinces in North Viet Nam so as to identify entry points for developing strategies that improve staff performance in rural areas. The study aimed to determine the major motivating factors and it is the first in Viet Nam that looks at health workers' job perception and motivation. Apart from health workers, managers at national and at provincial level were interviewed as well as some community representatives. Results The study showed that motivation is influenced by both financial and non-financial incentives. The main motivating factors for health workers were appreciation by managers, colleagues and the community, a stable job and income and training. The main discouraging factors were related to low salaries and difficult working conditions. Conclusion Activities associated with appreciation such as performance management are currently not optimally implemented, as health workers perceive supervision as control, selection for training as unclear and unequal, and performance appraisal as not useful. The kind of non-financial incentives identified should be taken into consideration when developing HRM strategies. Areas for further studies are identified.

  13. Identifying differentially methylated genes using mixed effect and generalized least square models

    Directory of Open Access Journals (Sweden)

    Yan Pearlly S

    2009-12-01

    Full Text Available Abstract Background DNA methylation plays an important role in the process of tumorigenesis. Identifying differentially methylated genes or CpG islands (CGIs associated with genes between two tumor subtypes is thus an important biological question. The methylation status of all CGIs in the whole genome can be assayed with differential methylation hybridization (DMH microarrays. However, patient samples or cell lines are heterogeneous, so their methylation pattern may be very different. In addition, neighboring probes at each CGI are correlated. How these factors affect the analysis of DMH data is unknown. Results We propose a new method for identifying differentially methylated (DM genes by identifying the associated DM CGI(s. At each CGI, we implement four different mixed effect and generalized least square models to identify DM genes between two groups. We compare four models with a simple least square regression model to study the impact of incorporating random effects and correlations. Conclusions We demonstrate that the inclusion (or exclusion of random effects and the choice of correlation structures can significantly affect the results of the data analysis. We also assess the false discovery rate of different models using CGIs associated with housekeeping genes.

  14. Identifying the factor structure of the SOCRATES in a sample of Latino adolescents.

    Science.gov (United States)

    Burrow-Sanchez, Jason J

    2014-03-01

    The Stages of Change Readiness and Treatment Eagerness Scale (SOCRATES) is a frequently used measure to assess client motivation to change an alcohol use problem. The factor structure of this measure has most extensively been studied in samples of adult clients with alcohol use disorders with very little research conducted with adolescents or ethnic minority participants. The purpose of the current study is to determine if the factor structure of the SOCRATES (Version 8A-Alcohol) found in prior research can be generalized to a sample of Latino adolescents with substance use disorders. Latino adolescents (N = 106) were administered the SOCRATES and assessed for alcohol use at a pretreatment baseline assessment as part of a larger study. Competing factor models were tested and results via confirmatory factor analysis indicated that a 14-item two factor model best fit the data for the Latino adolescents in this sample. In addition, scores on the Taking Steps factor predicted alcohol use variables. Implications for these results and suggestions for further research are discussed.

  15. Identifying anaerobic digestion models using simultaneous batch experiments

    Energy Technology Data Exchange (ETDEWEB)

    Flotats, X.; Palatsi, J.; Fernandez, B.; Colomer, M. A.; Illa, J.

    2009-07-01

    As in other wastewater treatment processes, anaerobic digestion models have become a valuable tool to increase the understanding of complex biodegradation processes, to teach and to communicate using a common language, to optimize design plants and operating strategies and for trying operators and process engineers. Models require accurate and significant parameter values for being useful. (Author) 2 refs.

  16. Identifying parameters in active magnetic bearing system using LFT formulation and Youla factorization

    DEFF Research Database (Denmark)

    Lauridsen, Jonas; Sekunda, André Krabdrup; Santos, Ilmar

    2015-01-01

    In this paper, a method for identifying uncertain parameters in a rotordynamic system composed of a flexible rotating shaft, rigid discs and two radial active magnetic bearings is presented. Shaft and disc dynamics are mathematically described using a Finite Element (FE) model while magnetic...... bearing forces are represented by linear springs with negative stiffness. Bearing negative stiffness produces an unstable rotordynamic system, demanding implementation of feedback control to stabilize the rotordynamic system. Thus, to identify the system parameters, closed-loop system identification...... techniques are required., The main focus of the paper relies on how to effectively identify uncertain parameters, such as stiffness and damping force coefficients of bearings and seals in rotordynamic systems. Dynamic condensation method, i.e. pseudo-modal reduction, is used to obtain a reduced order model...

  17. Modelling intelligence-led policing to identify its potential

    NARCIS (Netherlands)

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

    2014-01-01

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

  18. Modelling intelligence-led policing to identify its potential

    NARCIS (Netherlands)

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

    2014-01-01

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

  19. Modeling Ability Differentiation in the Second-Order Factor Model

    Science.gov (United States)

    Molenaar, Dylan; Dolan, Conor V.; van der Maas, Han L. J.

    2011-01-01

    In this article we present factor models to test for ability differentiation. Ability differentiation predicts that the size of IQ subtest correlations decreases as a function of the general intelligence factor. In the Schmid-Leiman decomposition of the second-order factor model, we model differentiation by introducing heteroscedastic residuals,…

  20. Modeling ability differentiation in the second-order factor model

    NARCIS (Netherlands)

    Molenaar, D.; Dolan, C.V.; van der Maas, H.L.J.

    2011-01-01

    In this article we present factor models to test for ability differentiation. Ability differentiation predicts that the size of IQ subtest correlations decreases as a function of the general intelligence factor. In the Schmid-Leiman decomposition of the second-order factor model, we model

  1. The Evolution of a Teacher Community of Practice: Identifying Facilitating and Constraining Factors

    Science.gov (United States)

    Borg, Tracey

    2012-01-01

    This paper presents findings from a larger, qualitative study that explored the potential of a school-based teacher community of practice as a model for a transformative form of teacher professional development. This paper reports on initial findings from a grounded theory exploration of the factors that facilitated and constrained the evolution…

  2. The Evolution of a Teacher Community of Practice: Identifying Facilitating and Constraining Factors

    Science.gov (United States)

    Borg, Tracey

    2012-01-01

    This paper presents findings from a larger, qualitative study that explored the potential of a school-based teacher community of practice as a model for a transformative form of teacher professional development. This paper reports on initial findings from a grounded theory exploration of the factors that facilitated and constrained the evolution…

  3. Novel Application of Statistical Methods to Identify New Urinary Incontinence Risk Factors

    Directory of Open Access Journals (Sweden)

    Theophilus O. Ogunyemi

    2012-01-01

    Full Text Available Longitudinal data for studying urinary incontinence (UI risk factors are rare. Data from one study, the hallmark Medical, Epidemiological, and Social Aspects of Aging (MESA, have been analyzed in the past; however, repeated measures analyses that are crucial for analyzing longitudinal data have not been applied. We tested a novel application of statistical methods to identify UI risk factors in older women. MESA data were collected at baseline and yearly from a sample of 1955 men and women in the community. Only women responding to the 762 baseline and 559 follow-up questions at one year in each respective survey were examined. To test their utility in mining large data sets, and as a preliminary step to creating a predictive index for developing UI, logistic regression, generalized estimating equations (GEEs, and proportional hazard regression (PHREG methods were used on the existing MESA data. The GEE and PHREG combination identified 15 significant risk factors associated with developing UI out of which six of them, namely, urinary frequency, urgency, any urine loss, urine loss after emptying, subject’s anticipation, and doctor’s proactivity, are found most highly significant by both methods. These six factors are potential candidates for constructing a future UI predictive index.

  4. A Bayesian Approach to Identifying New Risk Factors for Dementia: A Nationwide Population-Based Study.

    Science.gov (United States)

    Wen, Yen-Hsia; Wu, Shihn-Sheng; Lin, Chun-Hung Richard; Tsai, Jui-Hsiu; Yang, Pinchen; Chang, Yang-Pei; Tseng, Kuan-Hua

    2016-05-01

    Dementia is one of the most disabling and burdensome health conditions worldwide. In this study, we identified new potential risk factors for dementia from nationwide longitudinal population-based data by using Bayesian statistics.We first tested the consistency of the results obtained using Bayesian statistics with those obtained using classical frequentist probability for 4 recognized risk factors for dementia, namely severe head injury, depression, diabetes mellitus, and vascular diseases. Then, we used Bayesian statistics to verify 2 new potential risk factors for dementia, namely hearing loss and senile cataract, determined from the Taiwan's National Health Insurance Research Database.We included a total of 6546 (6.0%) patients diagnosed with dementia. We observed older age, female sex, and lower income as independent risk factors for dementia. Moreover, we verified the 4 recognized risk factors for dementia in the older Taiwanese population; their odds ratios (ORs) ranged from 3.469 to 1.207. Furthermore, we observed that hearing loss (OR = 1.577) and senile cataract (OR = 1.549) were associated with an increased risk of dementia.We found that the results obtained using Bayesian statistics for assessing risk factors for dementia, such as head injury, depression, DM, and vascular diseases, were consistent with those obtained using classical frequentist probability. Moreover, hearing loss and senile cataract were found to be potential risk factors for dementia in the older Taiwanese population. Bayesian statistics could help clinicians explore other potential risk factors for dementia and for developing appropriate treatment strategies for these patients.

  5. Dynamic Factor Models for the Volatility Surface

    DEFF Research Database (Denmark)

    van der Wel, Michel; Ozturk, Sait R.; Dijk, Dick van

    The implied volatility surface is the collection of volatilities implied by option contracts for different strike prices and time-to-maturity. We study factor models to capture the dynamics of this three-dimensional implied volatility surface. Three model types are considered to examine desirable...... features for representing the surface and its dynamics: a general dynamic factor model, restricted factor models designed to capture the key features of the surface along the moneyness and maturity dimensions, and in-between spline-based methods. Key findings are that: (i) the restricted and spline......-based models are both rejected against the general dynamic factor model, (ii) the factors driving the surface are highly persistent, (iii) for the restricted models option Delta is preferred over the more often used strike relative to spot price as measure for moneyness....

  6. The in vitro real-time oscillation monitoring system identifies potential entrainment factors for circadian clocks

    Directory of Open Access Journals (Sweden)

    Yasuda Akio

    2006-02-01

    Full Text Available Abstract Background Circadian rhythms are endogenous, self-sustained oscillations with approximately 24-hr rhythmicity that are manifested in various physiological and metabolic processes. The circadian organization of these processes in mammals is governed by the master oscillator within the suprachiasmatic nuclei (SCN of the hypothalamus. Recent findings revealed that circadian oscillators exist in most organs, tissues, and even in immortalized cells, and that the oscillators in peripheral tissues are likely to be coordinated by SCN, the master oscillator. Some candidates for endogenous entrainment factors have sporadically been reported, however, their details remain mainly obscure. Results We developed the in vitro real-time oscillation monitoring system (IV-ROMS by measuring the activity of luciferase coupled to the oscillatory gene promoter using photomultiplier tubes and applied this system to screen and identify factors able to influence circadian rhythmicity. Using this IV-ROMS as the primary screening of entrainment factors for circadian clocks, we identified 12 candidates as the potential entrainment factor in a total of 299 peptides and bioactive lipids. Among them, four candidates (endothelin-1, all-trans retinoic acid, 9-cis retinoic acid, and 13-cis retinoic acid have already been reported as the entrainment factors in vivo and in vitro. We demonstrated that one of the novel candidates, 15-deoxy-Δ12,14-prostaglandin J2 (15d-PGJ2, a natural ligand of the peroxisome proliferator-activated receptor-γ (PPAR-γ, triggers the rhythmic expression of endogenous clock genes in NIH3T3 cells. Furthermore, we showed that 15d-PGJ2 transiently induces Cry1, Cry2, and Rorα mRNA expressions and that 15d-PGJ2-induced entrainment signaling pathway is PPAR-γ – and MAPKs (ERK, JNK, p38MAPK-independent. Conclusion Here, we identified 15d-PGJ2 as an entrainment factor in vitro. Using our developed IV-ROMS to screen 299 compounds, we found eight

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2012-01-04

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

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

    Institute of Scientific and Technical Information of China (English)

    ZHAO Min; LIN Xinggang; SUN Shouyu; WANG Youzhi

    2005-01-01

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

  9. Identifying factors causing cost overrun of the construction projects in India

    Indian Academy of Sciences (India)

    SWAPNIL P WANJARI; GAURAV DOBARIYA

    2016-06-01

    Delay and cost overrun are common phenomena in projects worldwide. However, these are especially severe in developing countries. In India as per MOSPI report, 235 projects out of 410 were severely affected cost overrun due to certain factors. A short questionnaire was conducted with 15 prominent factorsresponsible for cost overrun and forwarded to 190 constructional professionals across India. Total 85 responses were received and it was analyzed using various statistical tools such as analysis of variance (ANOVA) and factor analysis tool using SPSS. In this study, top three factors affecting cost overruns were identified such as price escalation of raw material, delay in planned activity and lack of co-ordination between construction parties which could be significantly responsible for cost overnun of construction project in India. Factor analysismethod was also carried out to group the factors into three components of overall questionnaire. These components, such as client control component, project management component, and contractor control component,would be useful to the various parties involved in the construction activities. This paper also provides suggestive frameworks which have been framed after discussing with large number of construction professionals or expert

  10. Cardinality constrained portfolio selection via factor models

    OpenAIRE

    Monge, Juan Francisco

    2017-01-01

    In this paper we propose and discuss different 0-1 linear models in order to solve the cardinality constrained portfolio problem by using factor models. Factor models are used to build portfolios to track indexes, together with other objectives, also need a smaller number of parameters to estimate than the classical Markowitz model. The addition of the cardinality constraints limits the number of securities in the portfolio. Restricting the number of securities in the portfolio allows us to o...

  11. Identifying risk factors for PTSD in women seeking medical help after rape.

    Directory of Open Access Journals (Sweden)

    Anna Tiihonen Möller

    Full Text Available Rape has been found to be the trauma most commonly associated with Posttraumatic Stress Disorder (PTSD among women. It is therefore important to be able to identify those women at greatest risk of developing PTSD. The aims of the present study were to analyze the PTSD prevalence six months after sexual assaults and identify the major risk factors for developing PTSD.Participants were 317 female victims of rape who sought help at the Emergency Clinic for Raped Women at Stockholm South Hospital, Sweden. Baseline assessments of mental health were carried out and followed up after six months.Thirty-nine percent of the women had developed PTSD at the six month assessment, and 47% suffered from moderate or severe depression. The major risk factors for PTSD were having been sexually assaulted by more than one person, suffering from acute stress disorder (ASD shortly after the assault, having been exposed to several acts during the assault, having been injured, having co-morbid depression, and having a history of more than two earlier traumas. Further, ASD on its own was found to be a poor predictor of PTSD because of the substantial ceiling effect after sexual assaults.Development of PTSD is common in the aftermath of sexual assaults. Increased risk of developing PTSD is caused by a combination of victim vulnerability and the extent of the dramatic nature of the current assault. By identifying those women at greatest risk of developing PTSD appropriate therapeutic resources can be directed.

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

    Science.gov (United States)

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

    2013-01-01

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

  13. Localization and transcriptional responses of Chrysoporthe austroafricana in Eucalyptus grandis identify putative pathogenicity factors

    Directory of Open Access Journals (Sweden)

    Ronishree Mangwanda

    2016-12-01

    Full Text Available Chrysoporthe austroafricana is a fungal pathogen that causes the development of stem cankers on susceptible Eucalyptus grandis trees. Clones of E. grandis that are partially resistant and highly susceptible have been identified based on the extent of lesion formation on the stem upon inoculation with C. austroafricana. These interactions have been used as a model pathosystem to enhance our understanding of interactions between pathogenic fungi and woody hosts, which may be different to herbaceous hosts. In previous research, transcriptomics of host responses in these two clones to C. austroafricana suggested roles for salicylic acid and gibberellic acid phytohormone signalling in defense. However, it is unclear how the pathogen infiltrates host tissue and which pathogenicity factors facilitate its spread in the two host genotypes. The aim of this study was to investigate these two aspects of the E. grandis-C. austroafricana interaction and to test the hypothesis that the pathogen possesses mechanisms to modulate the tree phytohormone-mediated defenses. Light microscopy showed that the pathogen occurred in most cell types and structures within infected E. grandis stem tissue. Notably, the fungus appeared to spread through the stem by penetrating cell wall pits. In order to understand the molecular interaction between these organisms and predict putative pathogenicity mechanisms of C. austroafricana, fungal gene expression was studied in vitro and in planta. Fungal genes associated with cell wall degradation, carbohydrate metabolism and phytohormone manipulation were expressed in planta by C. austroafricana. These genes could be involved in fungal spread by facilitating cell wall pit degradation and manipulating phytohormone mediated defense in each host environment, respectively. Specifically, the in planta expression of an ent-kaurene oxidase and salicylate hydroxylase in C. austroafricana suggests putative mechanisms by which the pathogen can

  14. Metabolic disruption identified in the Huntington's disease transgenic sheep model.

    Science.gov (United States)

    Handley, Renee R; Reid, Suzanne J; Patassini, Stefano; Rudiger, Skye R; Obolonkin, Vladimir; McLaughlan, Clive J; Jacobsen, Jessie C; Gusella, James F; MacDonald, Marcy E; Waldvogel, Henry J; Bawden, C Simon; Faull, Richard L M; Snell, Russell G

    2016-02-11

    Huntington's disease (HD) is a dominantly inherited, progressive neurodegenerative disorder caused by a CAG repeat expansion within exon 1 of HTT, encoding huntingtin. There are no therapies that can delay the progression of this devastating disease. One feature of HD that may play a critical role in its pathogenesis is metabolic disruption. Consequently, we undertook a comparative study of metabolites in our transgenic sheep model of HD (OVT73). This model does not display overt symptoms of HD but has circadian rhythm alterations and molecular changes characteristic of the early phase disease. Quantitative metabolite profiles were generated from the motor cortex, hippocampus, cerebellum and liver tissue of 5 year old transgenic sheep and matched controls by gas chromatography-mass spectrometry. Differentially abundant metabolites were evident in the cerebellum and liver. There was striking tissue-specificity, with predominantly amino acids affected in the transgenic cerebellum and fatty acids in the transgenic liver, which together may indicate a hyper-metabolic state. Furthermore, there were more strong pair-wise correlations of metabolite abundance in transgenic than in wild-type cerebellum and liver, suggesting altered metabolic constraints. Together these differences indicate a metabolic disruption in the sheep model of HD and could provide insight into the presymptomatic human disease.

  15. Identifying Environmental Risk Factors of Cholera in a Coastal Area with Geospatial Technologies

    Science.gov (United States)

    Xu, Min; Cao, Chunxiang; Wang, Duochun; Kan, Biao

    2014-01-01

    Satellites contribute significantly to environmental quality and public health. Environmental factors are important indicators for the prediction of disease outbreaks. This study reveals the environmental factors associated with cholera in Zhejiang, a coastal province of China, using both Remote Sensing (RS) and Geographic information System (GIS). The analysis validated the correlation between the indirect satellite measurements of sea surface temperature (SST), sea surface height (SSH) and ocean chlorophyll concentration (OCC) and the local cholera magnitude based on a ten-year monthly data from the year 1999 to 2008. Cholera magnitude has been strongly affected by the concurrent variables of SST and SSH, while OCC has a one-month time lag effect. A cholera prediction model has been established based on the sea environmental factors. The results of hot spot analysis showed the local cholera magnitude in counties significantly associated with the estuaries and rivers. PMID:25551518

  16. Identifying Factors Affecting Professional Motivation of Iranian Seafarers onboard ocean Going Merchant Vessels

    Directory of Open Access Journals (Sweden)

    Asadolah Mehrara

    2016-12-01

    Full Text Available Human force employed in organizations is the main resources available to the managers. Management of human resources is perhaps the most important obligation of the manager activities and behaviors of human being are due to his needs and motivations. Since reinforcing motivations can lead to more improvements and achievements of every organization, the identification of factors affecting on motivation can help managers and supervisors to be aware of the origin of their staff’s motivations and lead their behavior towards the desired organizational aims. For this reason, this research tries to identify the most important factors affecting on professional motivation of the Iranian seafarers working on ocean-going merchant vessels (case study: National Iranian Tanker Company and to prioritize those factors in the next step. This research is of an "applied" and "descriptive-survey" type according to the goal and the methodology respectively. Statistical community of this research includes 540 of N.I.T.C. expert seafarers consisting:1- key officers (high rank officers with at least 10 years of experience, 2- low rank officers with at least 5 years of experience, 3-rating with diploma and at least 10 years of experience. Statistical sample mass based on "Kerjcie-Morgan" table includes 224 seafarers and the sampling method is the "simple random sample" method. The collecting method of data is field and library work. Further to the study of the available texts and researches about motivation and decision-making techniques and also interviewing with experts and lecturers who are masters and chief engineers of ocean-going vessels, a questionnaire has been prepared according to "Delphi method" to the scale of "Likert 5 degrees" and distributed among the statistical community. After analyzing the first questionnaire using the statistical methods and "SPSS" software, 20 affecting variables and also the final factors have been identified. Then the second

  17. A telephone call 1 week after hospitalization can identify risk factors for vascular surgery readmission.

    Science.gov (United States)

    Hornick, John R; Balderman, Joshua A; Eugea, Ronnie; Sanchez, Luis A; Zayed, Mohamed A

    2016-09-01

    Compared with other populations, patients who undergo vascular surgery have higher 30-day hospital readmission rates of up to 25%. Postdischarge telephone call assessments have demonstrated utility in patients with significant medical comorbidities and traditionally high readmission rates. Therefore, we hypothesized that a 1-week postdischarge telephone call evaluation can identify risk factors for readmission among vascular surgery patients. Patients who underwent a vascular surgery procedure during a 1-year period by a single vascular surgeon at one hospital received a postdischarge telephone call questionnaire to review postoperative pain, surgical site, constitutional symptoms, and follow-up arrangement. The primary outcome measure was frequency of postoperative symptoms as collected on the telephone call questionnaire. The secondary outcome measure was 30-day hospital readmission rates. Among 167 patients, 131 (78%) received a telephone call after discharge. Calls identified pain relieved by prescription medication (odds ratio, 6.67; confidence interval, 0.82-53.81; P = .05) and continued dressing application (odds ratio, 9.55; confidence interval, 0.54-166.6; P = .04) as risk factors for 30-day readmission. The 30-day readmission was not statistically different in patients who were successfully and not successfully contacted with a postdischarge telephone call (8% and 17%, respectively; P = .37). Vascular surgery patients are at higher risk of 30-day readmission than are patients in other surgical subspecialties. For the majority of patients, implementing a 1-week postdischarge telephone call for short-term follow-up evaluation is feasible and can help identify potential risk factors for hospital readmission within 30 days. Published by Elsevier Inc.

  18. Identifying cooperative transcription factors by combining ChIP-chip data and knockout data

    Institute of Scientific and Technical Information of China (English)

    Yi Yang; Zili Zhang; Yixue Li; Xin-Guang Zhu; Qi Liu

    2010-01-01

    @@ Dear Editor, Eukaryotic transcriptional regulation networks are extremely complex.Usually,multiple transcription factors(TFs)bind to the promoter region of a gene and cooperate to control gene expression precisely.Identifying cooperative TFs remains a major challenge in modern biological research.Various types of data,including genomic sequences,expression profiles,ChiP-chip data and protein-protein interactions,have been used to identify mechanisms of cooperative transcriptional regulation.However,because of the noise inherent in these data and the fact that each data source only provides partial information about regulation,combining multiple types of data to improve their ability to infer cooperative TFs is advantageous[1-3].

  19. Gene expression meta-analysis identifies metastatic pathways and transcription factors in breast cancer

    DEFF Research Database (Denmark)

    Thomassen, Mads; Tan, Qihua; Kruse, Torben

    2008-01-01

    studies. Besides classification of outcome, these global expression patterns may reflect biological mechanisms involved in metastasis of breast cancer. Our purpose has been to investigate pathways and transcription factors involved in metastasis by use of gene expression data sets. METHODS: We have...... system, angiogenesis, DNA repair and several signal transduction pathways are associated to metastasis. Finally several transcription factors e.g. E2F, NFY, and YY1 are identified as being involved in metastasis. CONCLUSIONS: By pathway meta-analysis many biological mechanisms beyond major......ABSTRACT: BACKGROUND: Metastasis is believed to progress in several steps including different pathways but the determination and understanding of these mechanisms is still fragmentary. Microarray analysis of gene expression patterns in breast tumors has been used to predict outcome in recent...

  20. Identifying dietary patterns and associated health-related lifestyle factors in the adult Danish population

    DEFF Research Database (Denmark)

    Knudsen, Vibeke Kildegaard; Matthiessen, Jeppe; Biltoft-Jensen, Anja Pia

    2014-01-01

    Background/objectives:To identify and describe dietary patterns in Danish adults and to examine which demographic and health-related lifestyle factors are associated with dietary patterns.Subjects/methods:Data derived from the Danish national survey of diet and physical activity collected in 2003......, potatoes and gravy, and cake and biscuits; a 'health-conscious' pattern correlated with coarse bread, fruit, vegetables, low-fat dairy, nuts, water and tea; and a 'fast food' pattern correlated with pizza, hamburger/spring rolls, crisps, rice and pasta, sugar-sweetened soft drinks and sweets...

  1. An OMERACT Initiative Toward Consensus to Identify and Characterize Candidate Contextual Factors

    DEFF Research Database (Denmark)

    Finger, Monika E; Boonen, Annelies; Woodworth, Thasia G

    2017-01-01

    selection of potentially relevant CF. RESULTS: The survey revealed that the WG had mostly used the OMERACT Handbook and/or the International Classification of Functioning, Disability and Health (ICF) definition. However, significant heterogeneity was found in the methods used to identify, refine......, and categorize CF candidates. The SIG participants agreed on using the ICF as a framework along with the OMERACT Handbook definition. A list with 28 variables was collected including person-related factors and physical and social environments. Recommendations from the SIG guided the CFMG to formulate 3...

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

    Directory of Open Access Journals (Sweden)

    Yi-Chung Hu

    2015-01-01

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

  3. ESTIMATING VITICULTURAL FAVORABILITY OF COTNARI VINEYARD AREA AND IDENTIFYING LIMITING FACTORS

    Directory of Open Access Journals (Sweden)

    Cristina Chiriac

    2012-12-01

    Full Text Available For estimating the favorability of agricultural lands for vine in Cotnari vineyard area, we used 16 indicators provided in the Methodology of Soil Survey (Second part and third part - 1986. To determine the average coefficient of evaluation, respectively the class of favorability for the vine in Cotnari Vineyard, we calculated the notes of evaluation for 10 administrative units from Cotnari Vineyard: Flămânzi, Frumuşica, Deleni, Hârlău, Scobinţi, Cepleniţa, Cotnari, Cucuteni, Todireşti, Târgu Frumos. For each administrative unit were selected the territorial units of soil (U.S. within Cotnari Vineyard, from which we extracted only the ecological homogeneous territories (TEO's that are planted with vine. Among the limiting factors identified in Cotnari Vineyard we mention the geomorphologic factor (slope, landslides, the pedological factor (gleying, stagnogleying,salinization/alkalization, texture, reaction, humus content, edaphic volume and the hydrological factor (groundwater depth, excess moisture in surface, flooding by overflow.

  4. Identifying and prioritizing different factors influencing the success of advertisement during the economic depression

    Directory of Open Access Journals (Sweden)

    Aram Rashidi

    2014-04-01

    Full Text Available During the financial crisis of 2007, many businesses and banks faced unexpected circumstances and declared bankruptcy. Market mortgage crisis and the collapse of the economic system in United States created a substantial amount of damage in world economy. Within a few years, the economic downturn was transferred to developing countries such as Iran. The recession has created conditions for Iranian companies that have led them to focus more on the subject of advertising since this is the primary tool of communication and business customers business. Success and failure of many organizations and companies depend on their advertisement planning. In this study, the factors contributing to the success and effectiveness of advertising during the recession time are identified. This survey has been accomplished on investigating an Iranian dairy firm named “Kalle”. Using a questionnaire in Likert scale, the study determines the effects of various factors of advertisement on sales improvement in this firm using Pearson correlation ratio and rank them based on Freedman test. Cronbach alpha has been calculated as 0.93. According to the results, factors that contribute to the success of advertising during a recession include: Responsiveness to customers’ needs, advertising tools, content factors, the amount of money spent and availability.

  5. Identifying and prioritizing the factors effective in customer satisfaction using the TOPSIS method

    Directory of Open Access Journals (Sweden)

    H Forougozar

    2014-01-01

    Full Text Available Introduction: Customer satisfaction has been suggested as one of the interesting and challenging issues of management in the new millennium. In addition, oral and dental health and the quality of the services the health centers delivered to the patients directly affect the customer satisfaction. Therefore, the present study aimed to identify, investigate, and rank the factors affecting the customer satisfaction in the department of dentistry of Shiraz Farhangiyan health center. Method: The present descriptive study was conducted on the specialists and patients of the department of dentistry of Shiraz Farhangiyan health center. The validity of the questionnaire utilized in the study was confirmed by expert professors and its reliability was approved using the Cronbach’s alpha formula. Finally, the study data were analyzed in SPSS statistical software (v. 16, using inferential statistics. Results: All the hypotheses were confirmed by the results of the statistical analyses and quality, services, and expenditures revealed to affect the customer satisfaction in the department of dentistry of Shiraz Farhangiyan health center. Moreover, these factors were ranked using the TOPSIS method and the results showed quality and expenditures as the most and the least effective factors in customer satisfaction, respectively. Conclusion: Since restoring and arranging the organization based on the customer needs is among the main priorities of designing an organization, managers are suggested to take measures for organizational reformation based on the customers’ priorities. Of course, conducting such programs is of utmost importance in health and treatment environments, leading to provision of better services and facilitation of learning, education, and research. Thus, identifying the effective factors in customer satisfaction and ranking them are highly important.

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

    Science.gov (United States)

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

    2015-11-01

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

  7. Identifying effective factors on consumers' choice behavior toward green products: the case of Tehran, the capital of Iran.

    Science.gov (United States)

    Rahnama, Hassan; Rajabpour, Shayan

    2017-01-01

    The environment is increasingly turning to a vital and very important issue for all people. By increasing environmental concerns as well as legislating and regulating rules on the protection of the environment and the emergence of green consumers, implementing green marketing approach for organizations seems to be more crucial and essential. As a result, the need for ecological products and green business activities compels companies to combine environmental issues with marketing strategies. The first step in the success of companies and organizations is to identify consumers and their consumption behaviors correctly and accurately. So, the purpose of this study is to identify effective factors for the choice of consumers of green products. We used consumption values (functional value, social value, emotional value, conditional value, epistemic value, and environmental value) as the effective factor for choosing green products. The original place of this research was in Tehran, capital city of Iran, which is one of the most polluted cities in the world due to environmental issues. The results from the survey questionnaires are analyzed using confirmatory factor analysis and structural equation modelling. The results indicated that functional value-price, functional value-quality, social value, epistemic value, and environmental value had significantly positive effects on the choice of green products; also, conditional value and emotional value had no influence on it. It was concluded that the main influential factors for consumers' choice behavior regarding green products included environmental value and epistemic value. This study emphasized the proper pricing of green products by producers and sellers.

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

    Science.gov (United States)

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

    2016-12-06

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

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

    Science.gov (United States)

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

    2015-10-01

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

  10. 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...... continents and still support aggregation of impact scores over the whole life cycle. For the impact categories human toxicity and ecotoxicity, we are now able to recommend a model, but the number of chemical substances in common use is so high that there is a need to address the substance data shortage...... 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...

  11. Can Positive Matrix Factorization identify sources of organic trace gases at the continental GAW site Hohenpeissenberg?

    Directory of Open Access Journals (Sweden)

    M. Leuchner

    2014-03-01

    Full Text Available From the rural Global Atmosphere Watch (GAW site Hohenpeissenberg in the pre-alpine area of Southern Germany, a dataset of 24 C2–C8 non-methane hydrocarbons over a period of seven years was analyzed. Receptor modeling was performed by Positive Matrix Factorization (PMF and the resulting factors were compared to literature source profiles. Photochemical aging during transport to the relatively remote site violates the PMF prerequisite of mass conservation from source to receptor. However, previous studies showed plausible results with this method at remote sites; the applicability and restrictions of the PMF model to such a remote dataset and the influence of photochemical processing on the interpretability of the results are discussed. A six factor solution showed a high stability and the most plausible results. In addition to biogenic sources and remote sources of very stable compounds – reflecting the continental background – four additional anthropogenic factors were resolved that could be divided into two short- and two long-lived patterns from evaporative sources and incomplete combustion processes, respectively. A method to increase the uncertainty for each individual compound by including photochemical reactivity did not improve the results, but decreased the stability of the model output. The contribution of the different source categories at the site over the entire period was, in decreasing order: remote sources, long-lived evaporative sources, residential heating and long-lived combustion sources, short-lived evaporative sources, short-lived combustion sources, and biogenic sources. Despite a low overall impact, biogenic sources played an important role during summer, in particular in terms of reactivity.

  12. Identifying Stress Transcription Factors Using Gene Expression and TF-Gene Association Data.

    Science.gov (United States)

    Wu, Wei-Sheng; Chen, Bor-Sen

    2009-11-24

    Unicellular organisms such as yeasts have evolved to survive environmental stresses by rapidly reorganizing the genomic expression program to meet the challenges of harsh environments. The complex adaptation mechanisms to stress remain to be elucidated. In this study, we developed Stress Transcription Factor Identification Algorithm (STFIA), which integrates gene expression and TF-gene association data to identify the stress transcription factors (TFs) of six kinds of stresses. We identified some general stress TFs that are in response to various stresses, and some specific stress TFs that are in response to one specific stress. The biological significance of our findings is validated by the literature. We found that a small number of TFs may be sufficient to control a wide variety of expression patterns in yeast under different stresses. Two implications can be inferred from this observation. First, the adaptation mechanisms to different stresses may have a bow-tie structure. Second, there may exist extensive regulatory cross-talk among different stress responses. In conclusion, this study proposes a network of the regulators of stress responses and their mechanism of action.

  13. Using local lexicalized rules to identify heart disease risk factors in clinical notes.

    Science.gov (United States)

    Karystianis, George; Dehghan, Azad; Kovacevic, Aleksandar; Keane, John A; Nenadic, Goran

    2015-12-01

    Heart disease is the leading cause of death globally and a significant part of the human population lives with it. A number of risk factors have been recognized as contributing to the disease, including obesity, coronary artery disease (CAD), hypertension, hyperlipidemia, diabetes, smoking, and family history of premature CAD. This paper describes and evaluates a methodology to extract mentions of such risk factors from diabetic clinical notes, which was a task of the i2b2/UTHealth 2014 Challenge in Natural Language Processing for Clinical Data. The methodology is knowledge-driven and the system implements local lexicalized rules (based on syntactical patterns observed in notes) combined with manually constructed dictionaries that characterize the domain. A part of the task was also to detect the time interval in which the risk factors were present in a patient. The system was applied to an evaluation set of 514 unseen notes and achieved a micro-average F-score of 88% (with 86% precision and 90% recall). While the identification of CAD family history, medication and some of the related disease factors (e.g. hypertension, diabetes, hyperlipidemia) showed quite good results, the identification of CAD-specific indicators proved to be more challenging (F-score of 74%). Overall, the results are encouraging and suggested that automated text mining methods can be used to process clinical notes to identify risk factors and monitor progression of heart disease on a large-scale, providing necessary data for clinical and epidemiological studies. Copyright © 2015 Elsevier Inc. All rights reserved.

  14. Random T-DNA mutagenesis identifies a Cu-Zn-superoxide dismutase gene as a virulence factor of Sclerotinia sclerotiorum

    Science.gov (United States)

    Agrobacterium-mediated transformation (AMT) was used to identify potential virulence factors in Sclerotinia sclerotiorum. Screening AMT transformants identified two mutants showing significantly reduced virulence. The mutants showed similar growth rate, colony morphology, and sclerotial and oxalate ...

  15. Identifying the Source of a Humoral Factor of Remote (PreConditioning Cardioprotection.

    Directory of Open Access Journals (Sweden)

    Svetlana Mastitskaya

    Full Text Available Signalling pathways underlying the phenomenon of remote ischaemic preconditioning (RPc cardioprotection are not completely understood. The existing evidence agrees that intact sensory innervation of the remote tissue/organ is required for the release into the systemic circulation of preconditioning factor(s capable of protecting a transplanted or isolated heart. However, the source and molecular identities of these factors remain unknown. Since the efficacy of RPc cardioprotection is critically dependent upon vagal activity and muscarinic mechanisms, we hypothesized that the humoral RPc factor is produced by the internal organ(s, which receive rich parasympathetic innervation. In a rat model of myocardial ischaemia/reperfusion injury we determined the efficacy of limb RPc in establishing cardioprotection after denervation of various visceral organs by sectioning celiac, hepatic, anterior and posterior gastric branches of the vagus nerve. Electrical stimulation was applied to individually sectioned branches to determine whether enhanced vagal input to a particular target area is sufficient to establish cardioprotection. It was found that RPc cardioprotection is abolished in conditions of either total subdiaphragmatic vagotomy, gastric vagotomy or sectioning of the posterior gastric branch. The efficacy of RPc cardioprotection was preserved when hepatic, celiac or anterior gastric vagal branches were cut. In the absence of remote ischaemia/reperfusion, electrical stimulation of the posterior gastric branch reduced infarct size, mimicking the effect of RPc. These data suggest that the circulating factor (or factors of RPc are produced and released into the systemic circulation by the visceral organ(s innervated by the posterior gastric branch of the vagus nerve.

  16. Bioaccumulation syndrome: identifying factors that make some stream food webs prone to elevated mercury bioaccumulation.

    Science.gov (United States)

    Ward, Darren M; Nislow, Keith H; Folt, Carol L

    2010-05-01

    Mercury is a ubiquitous contaminant in aquatic ecosystems, posing a significant health risk to humans and wildlife that eat fish. Mercury accumulates in aquatic food webs as methylmercury (MeHg), a particularly toxic and persistent organic mercury compound. While mercury in the environment originates largely from anthropogenic activities, MeHg accumulation in freshwater aquatic food webs is not a simple function of local or regional mercury pollution inputs. Studies show that even sites with similar mercury inputs can produce fish with mercury concentrations ranging over an order of magnitude. While much of the foundational work to identify the drivers of variation in mercury accumulation has focused on freshwater lakes, mercury contamination in stream ecosystems is emerging as an important research area. Here, we review recent research on mercury accumulation in stream-dwelling organisms. Taking a hierarchical approach, we identify a suite of characteristics of individual consumers, food webs, streams, watersheds, and regions that are consistently associated with elevated MeHg concentrations in stream fish. We delineate a conceptual, mechanistic basis for explaining the ecological processes that underlie this vulnerability to MeHg. Key factors, including suppressed individual growth of consumers, low rates of primary and secondary production, hydrologic connection to methylation sites (e.g., wetlands), heavily forested catchments, and acidification are frequently associated with increased MeHg concentrations in fish across both streams and lakes. Hence, we propose that these interacting factors define a syndrome of characteristics that drive high MeHg production and bioaccumulation rates across these freshwater aquatic ecosystems. Finally, based on an understanding of the ecological drivers of MeHg accumulation, we identify situations when anthropogenic effects and management practices could significantly exacerbate or ameliorate MeHg accumulation in stream fish.

  17. Proteinuria in adult Saudi patients with sickle cell disease is not associated with identifiable risk factors

    Directory of Open Access Journals (Sweden)

    Aleem Aamer

    2010-01-01

    Full Text Available Renal involvement in patients with sickle cell disease (SCD is associated with signi-ficant morbidity and mortality. Proteinuria is common in patients with SCD and is a risk factor for future development of renal failure. We sought to identify risk factors, if any, associated with pro-teinuria in adult Saudi patients with SCD. We studied 67 patients with SCD followed-up at the King Khalid University Hospital, Riyadh, Saudi Arabia. All patients underwent 24-hour urine collection to measure creatinine clearance and to quantify proteinuria. In addition, blood was examined for evaluation of hematological and biochemical parameters. Clinical information was gathered from review of the patients′ charts. A urine protein level of more than 0.150 grams/24 hours was consi-dered abnormal. Urine protein was correlated with various clinical and laboratory parameters. Thirty-one males and 36 females were evaluated. The mean age of the cohort was 23.8 (± 7.2 years. Twenty-seven patients (40.3% had proteinuria of more than 0.150 grams/24 hours. The study group had a mean hemoglobin level of 8.5 (± 2.8 g/dL and mean fetal hemoglobin (HbF level of 14.4% (± 7.3%. Majority of the patients (61 had hemoglobin SS genotype and six patients had S-β0 thala-ssemia. None of the parameters evaluated correlated with proteinuria although there was a border-line association with older age and higher systolic blood pressure (P = 0.073 and 0.061 respec-tively. Hydroxyurea use for more than a year was not beneficial. In conclusion, our study suggests that proteinuria in adult Saudi patients is not associated with any clear identifiable risk factors.

  18. A systems biological approach to identify key transcription factors and their genomic neighborhoods in human sarcomas

    Institute of Scientific and Technical Information of China (English)

    Antti Ylip(a)(a); Olli Yli-Harja; Wei Zhang; Matti Nykter

    2011-01-01

    Identification of genetic signatures is the main objective for many computational oncology studies. The signature usually consists of numerous genes that are differentially expressed between two clinically distinct groups of samples, such as tumor subtypes. Prospectively, many signatures have been found to generalize poorly to other datasets and, thus, have rarely been accepted into clinical use. Recognizing the limited success of traditionally generated signatures, we developed a systems biology-based framework for robust identification of key transcription factors and their genomic regulatory neighborhoods. Application of the framework to study the differences between gastrointestinal stromal tumor (GIST) and leiomyosarcoma (LMS) resulted in the identification of nine transcription factors (SRF, NKX2-5, CCDC6, LEF1, VDR, ZNF250, TRIM63, MAF, and MYC). Functional annotations of the obtained neighborhoods identified the biological processes which the key transcription factors regulate differently between the tumor types. Analyzing the differences in the expression patterns using our approach resulted in a more robust genetic signature and more biological insight into the diseases compared to a traditional genetic signature.

  19. Application of diffusion maps to identify human factors of self-reported anomalies in aviation.

    Science.gov (United States)

    Andrzejczak, Chris; Karwowski, Waldemar; Mikusinski, Piotr

    2012-01-01

    A study investigating what factors are present leading to pilots submitting voluntary anomaly reports regarding their flight performance was conducted. Diffusion Maps (DM) were selected as the method of choice for performing dimensionality reduction on text records for this study. Diffusion Maps have seen successful use in other domains such as image classification and pattern recognition. High-dimensionality data in the form of narrative text reports from the NASA Aviation Safety Reporting System (ASRS) were clustered and categorized by way of dimensionality reduction. Supervised analyses were performed to create a baseline document clustering system. Dimensionality reduction techniques identified concepts or keywords within records, and allowed the creation of a framework for an unsupervised document classification system. Results from the unsupervised clustering algorithm performed similarly to the supervised methods outlined in the study. The dimensionality reduction was performed on 100 of the most commonly occurring words within 126,000 text records describing commercial aviation incidents. This study demonstrates that unsupervised machine clustering and organization of incident reports is possible based on unbiased inputs. Findings from this study reinforced traditional views on what factors contribute to civil aviation anomalies, however, new associations between previously unrelated factors and conditions were also found.

  20. Use of a twin dataset to identify AMD-related visual patterns controlled by genetic factors

    Science.gov (United States)

    Quellec, Gwénolé; Abràmoff, Michael D.; Russell, Stephen R.

    2010-03-01

    The mapping of genotype to the phenotype of age-related macular degeneration (AMD) is expected to improve the diagnosis and treatment of the disease in a near future. In this study, we focused on the first step to discover this mapping: we identified visual patterns related to AMD which seem to be controlled by genetic factors, without explicitly relating them to the genes. For this purpose, we used a dataset of eye fundus photographs from 74 twin pairs, either monozygotic twins, who have the same genotype, or dizygotic twins, whose genes responsible for AMD are less likely to be identical. If we are able to differentiate monozygotic twins from dizygotic twins, based on a given visual pattern, then this pattern is likely to be controlled by genetic factors. The main visible consequence of AMD is the apparition of drusen between the retinal pigment epithelium and Bruch's membrane. We developed two automated drusen detectors based on the wavelet transform: a shape-based detector for hard drusen, and a texture- and color- based detector for soft drusen. Forty visual features were evaluated at the location of the automatically detected drusen. These features characterize the texture, the shape, the color, the spatial distribution, or the amount of drusen. A distance measure between twin pairs was defined for each visual feature; a smaller distance should be measured between monozygotic twins for visual features controlled by genetic factors. The predictions of several visual features (75.7% accuracy) are comparable or better than the predictions of human experts.

  1. Identifying principal risk factors for the initiation of adolescent smoking behaviors: the significance of psychological reactance.

    Science.gov (United States)

    Miller, Claude H; Burgoon, Michael; Grandpre, Joseph R; Alvaro, Eusebio M

    2006-01-01

    An in-school youth survey for a major state anti-tobacco media campaign was conducted with 1,831 students (Grades 6-12) from 70 randomly selected classrooms throughout the state. Tobacco users accounted for nearly 25% of the sample. Pretest questionnaires assessed demographic variables, tobacco use, and various other risk factors. Several predictors of adolescents' susceptibility to tobacco use, including prior experimentation with tobacco, school performance, parental smoking status, parents' level of education, parental communication, parental relationship satisfaction, best friend's smoking status, prevalence of smokers in social environment, self-perceived potential to smoke related to peer pressure, and psychological reactance, were examined using discriminant analysis and logistic regression to identify the factors most useful in classifying adolescents as either high-risk or low-risk for smoking uptake. Results corroborate findings in the prevention literature indicating that age, prior experimentation, and having friends who smoke are among the principal predictors of smoking risk. New evidence is presented indicating that psychological reactance also should be considered as an important predictor of adolescent smoking initiation. The utility of producing antismoking messages informed by an awareness of the key risk factors-particularly psychological reactance-is discussed both in terms of the targeting and design of anti-tobacco campaigns.

  2. GTRD: a database of transcription factor binding sites identified by ChIP-seq experiments

    Science.gov (United States)

    Yevshin, Ivan; Sharipov, Ruslan; Valeev, Tagir; Kel, Alexander; Kolpakov, Fedor

    2017-01-01

    GTRD—Gene Transcription Regulation Database (http://gtrd.biouml.org)—is a database of transcription factor binding sites (TFBSs) identified by ChIP-seq experiments for human and mouse. Raw ChIP-seq data were obtained from ENCODE and SRA and uniformly processed: (i) reads were aligned using Bowtie2; (ii) ChIP-seq peaks were called using peak callers MACS, SISSRs, GEM and PICS; (iii) peaks for the same factor and peak callers, but different experiment conditions (cell line, treatment, etc.), were merged into clusters; (iv) such clusters for different peak callers were merged into metaclusters that were considered as non-redundant sets of TFBSs. In addition to information on location in genome, the sets contain structured information about cell lines and experimental conditions extracted from descriptions of corresponding ChIP-seq experiments. A web interface to access GTRD was developed using the BioUML platform. It provides: (i) browsing and displaying information; (ii) advanced search possibilities, e.g. search of TFBSs near the specified gene or search of all genes potentially regulated by a specified transcription factor; (iii) integrated genome browser that provides visualization of the GTRD data: read alignments, peaks, clusters, metaclusters and information about gene structures from the Ensembl database and binding sites predicted using position weight matrices from the HOCOMOCO database. PMID:27924024

  3. Identifying risk factors associated with lameness in pasture-based dairy herds.

    Science.gov (United States)

    Ranjbar, S; Rabiee, A R; Gunn, A; House, J K

    2016-09-01

    Lameness is a significant welfare concern for dairy farmers and a major contributing economic loss to the dairy industry. Information is limited on environmental and managerial risk factors associated with lameness in Australian dairy herds. The objective of this study was to explore and quantify the environmental and management risk factors associated with lameness in pasture-based dairy herds. A cross-sectional study was conducted in 63 pasture-based dairy herds between 2011 and 2014, where all lactating cows were locomotion scored (scale 1-4) during a single visit. Environmental and management variables, such as length of main track and animal handling practices, were recorded during the visit. The prevalence of lameness was measured for each farm and associated risk factors were analyzed using a Generalized Linear Model, where farm was the unit of analysis. Estimated average prevalence of lameness was 18.9% (range 5 to 44.5%). The prevalence of lameness was associated with the amount of rainfall during the 30 d before the farm assessment, smoothness of concrete surface and available space per cow in the holding yard, and length of feed-pad available per cow. Inappropriate handling of cows on the track (e.g., causing sideways pushing among cows) was also a contributing risk factor to high prevalence of lameness in these dairy herds. The findings of this study suggest that by managing several environmental and farming practices, producers can reduce the prevalence of lameness, leading to improved productivity of their herds.

  4. Qualitative Comparative Analysis: A Hybrid Method for Identifying Factors Associated with Program Effectiveness.

    Science.gov (United States)

    Cragun, Deborah; Pal, Tuya; Vadaparampil, Susan T; Baldwin, Julie; Hampel, Heather; DeBate, Rita D

    2016-07-01

    Qualitative comparative analysis (QCA) was developed over 25 years ago to bridge the qualitative and quantitative research gap. Upon searching PubMed and the Journal of Mixed Methods Research, this review identified 30 original research studies that utilized QCA. Perceptions that QCA is complex and provides few relative advantages over other methods may be limiting QCA adoption. Thus, to overcome these perceptions, this article demonstrates how to perform QCA using data from fifteen institutions that implemented universal tumor screening (UTS) programs to identify patients at high risk for hereditary colorectal cancer. In this example, QCA revealed a combination of conditions unique to effective UTS programs. Results informed additional research and provided a model for improving patient follow-through after a positive screen.

  5. Quantitative Proteomics Identifies Serum Response Factor Binding Protein 1 as a Host Factor for Hepatitis C Virus Entry

    Directory of Open Access Journals (Sweden)

    Gisa Gerold

    2015-08-01

    Full Text Available Hepatitis C virus (HCV enters human hepatocytes through a multistep mechanism involving, among other host proteins, the virus receptor CD81. How CD81 governs HCV entry is poorly characterized, and CD81 protein interactions after virus binding remain elusive. We have developed a quantitative proteomics protocol to identify HCV-triggered CD81 interactions and found 26 dynamic binding partners. At least six of these proteins promote HCV infection, as indicated by RNAi. We further characterized serum response factor binding protein 1 (SRFBP1, which is recruited to CD81 during HCV uptake and supports HCV infection in hepatoma cells and primary human hepatocytes. SRFBP1 facilitates host cell penetration by all seven HCV genotypes, but not of vesicular stomatitis virus and human coronavirus. Thus, SRFBP1 is an HCV-specific, pan-genotypic host entry factor. These results demonstrate the use of quantitative proteomics to elucidate pathogen entry and underscore the importance of host protein-protein interactions during HCV invasion.

  6. System Identification by Dynamic Factor Models

    NARCIS (Netherlands)

    C. Heij (Christiaan); W. Scherrer; M. Destler

    1996-01-01

    textabstractThis paper concerns the modelling of stochastic processes by means of dynamic factor models. In such models the observed process is decomposed into a structured part called the latent process, and a remainder that is called noise. The observed variables are treated in a symmetric way, so

  7. Alkaline-stress response in Glycine soja leaf identifies specific transcription factors and ABA-mediated signaling factors.

    Science.gov (United States)

    Ge, Ying; Li, Yong; Lv, De-Kang; Bai, Xi; Ji, Wei; Cai, Hua; Wang, Ao-Xue; Zhu, Yan-Ming

    2011-06-01

    Transcriptome of Glycine soja leaf tissue during a detailed time course formed a foundation for examining transcriptional processes during NaHCO(3) stress treatment. Of a total of 2,310 detected differentially expressed genes, 1,664 genes were upregulated and 1,704 genes were downregulated at various time points. The number of stress-regulated genes increased dramatically after a 6-h stress treatment. GO category gene enrichment analysis revealed that most of the differentially expressed genes were involved in cell structure, protein synthesis, energy, and secondary metabolism. Another enrichment test revealed that the response of G. soja to NaHCO(3) highlights specific transcription factors, such as the C2C2-CO-like, MYB-related, WRKY, GARP-G2-like, and ZIM families. Co-expressed genes were clustered into ten classes (P < 0.001). Intriguingly, one cluster of 188 genes displayed a unique expression pattern that increases at an early stage (0.5 and 3 h), followed by a decrease from 6 to 12 h. This group was enriched in regulation of transcription components, including AP2-EREBP, bHLH, MYB/MYB-related, C2C2-CO-like, C2C2-DOF, C2C2, C3H, and GARP-G2-like transcription factors. Analysis of the 1-kb upstream regions of transcripts displaying similar changes in abundance identified 19 conserved motifs, potential binding sites for transcription factors. The appearance of ABA-responsive elements in the upstream of co-expression genes reveals that ABA-mediated signaling participates in the signal transduction in alkaline response.

  8. Risk factors identified for owner-reported feline obesity at around one year of age: Dry diet and indoor lifestyle.

    Science.gov (United States)

    Rowe, Elizabeth; Browne, William; Casey, Rachel; Gruffydd-Jones, Tim; Murray, Jane

    2015-10-01

    Obesity is considered the second most common health problem in pet cats in developed countries. Previous studies investigating risk factors for feline obesity have been cross-sectional, where reverse causality cannot be ruled out. This study is the first to use prospective data from a large scale longitudinal study of pet cats ('Bristol Cats') to identify early-life risk factors for feline overweight/obesity at around one year of age. Data analysed were collected via three owner-completed questionnaires (for cats aged 2-4 months, 6.5-7 months and 12.5-13 months) completed between May 2010 and August 2013. Owner-reported body condition scores (BCS) of cats at age 12.5-13 months, using the 5-point system, were categorised into a dichotomous variable: overweight/obese (BCS 4-5) and not overweight (BCS 1-3) and used as the dependent variable. Cat breed, neuter status, outdoor access, type of diet, frequency of wet and dry food fed and frequency of treats fed were analysed as potential risk factors. Of the 966 cats for which data were available, 7.0% were reported by their owners to be overweight/obese at 12.5-13 months of age. Descriptive data on type of diet fed at different cat ages suggest that a dry diet is the most popular choice for UK domestic cats. Significant potential explanatory variables from univariable logistic regression models were included in multivariable logistic regression models built using stepwise forward-selection. To account for potential hierarchical clustering of data due to multi-cat households these were extended to two-level random intercept models. Models were compared using Wald test p- values. Clustering had no impact on the analysis. The final multivariable logistic regression model identified two risk factors that were independently associated with an increased risk of feline obesity developing at 12.5-13 months of age: restricted or no outdoor access and feeding dry food as the only or major (>50%) type of food in the diet at age 12

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

    Science.gov (United States)

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

    2014-01-01

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

  10. Impact of Hybrid Intelligent Computing in Identifying Constructive Weather Parameters for Modeling Effective Rainfall Prediction

    Directory of Open Access Journals (Sweden)

    M. Sudha

    2015-12-01

    Full Text Available Uncertain atmosphere is a prevalent factor affecting the existing prediction approaches. Rough set and fuzzy set theories as proposed by Pawlak and Zadeh have become an effective tool for handling vagueness and fuzziness in the real world scenarios. This research work describes the impact of Hybrid Intelligent System (HIS for strategic decision support in meteorology. In this research a novel exhaustive search based Rough set reduct Selection using Genetic Algorithm (RSGA is introduced to identify the significant input feature subset. The proposed model could identify the most effective weather parameters efficiently than other existing input techniques. In the model evaluation phase two adaptive techniques were constructed and investigated. The proposed Artificial Neural Network based on Back Propagation learning (ANN-BP and Adaptive Neuro Fuzzy Inference System (ANFIS was compared with existing Fuzzy Unordered Rule Induction Algorithm (FURIA, Structural Learning Algorithm on Vague Environment (SLAVE and Particle Swarm OPtimization (PSO. The proposed rainfall prediction models outperformed when trained with the input generated using RSGA. A meticulous comparison of the performance indicates ANN-BP model as a suitable HIS for effective rainfall prediction. The ANN-BP achieved 97.46% accuracy with a nominal misclassification rate of 0.0254 %.

  11. Identifying the Best-Fitting Factor Structure of the Experience of Close Relations

    DEFF Research Database (Denmark)

    Esbjørn, Barbara Hoff; Breinholst, Sonja; Niclasen, Janni

    2015-01-01

    The aim of this study was to enhance the understanding of cultural and sample differences in the assessment of attachment by examining the factor structure of the Experiences in Close Relationships-Revised (ECR-R). The ECR-R is a self-report measure of adult roman- tic attachment dimensions....... The present study used a Danish sample with the purpose of addressing limitations in previous studies, such as the lack of diversity in cultural back- ground, restricted sample characteristics, and poorly fitting structure models. Participants consisted of 253 parents of children between the ages of 7 and 12...

  12. Integrating fire with hydrological projections: model evaluation to identify uncertainties and tradeoffs in model complexity

    Science.gov (United States)

    Kennedy, M.; McKenzie, D.

    2013-12-01

    It is imperative for resource managers to understand how a changing climate might modify future watershed and hydrological processes, and such an understanding is incomplete if disturbances such as fire are not integrated with hydrological projections. Can a robust fire spread model be developed that approximates patterns of fire spread in response to varying topography wind patterns, and fuel loads and moistures, without requiring intensive calibration to each new study area or time frame? We assessed the performance of a stochastic model of fire spread (WMFire), integrated with the Regional Hydro-Ecological Simulation System (RHESSys), for projecting the effects of climatic change on mountain watersheds. We first use Monte Carlo inference to determine that the fire spread model is able to replicate the spatial pattern of fire spread for a contemporary wildfire in Washington State (the Tripod fire), measured by the lacunarity and fractal dimension of the fire. We then integrate a version of WMFire able to replicate the contemporary wildfire with RHESSys and simulate a New Mexico watershed over the calibration period of RHESSys (1941-1997). In comparing the fire spread model to a single contemporary wildfire we found issues in parameter identifiability for several of the nine parameters, due to model input uncertainty and insensitivity of the mathematical function to certain ranges of the parameter values. Model input uncertainty is caused by the inherent difficulty in reconstructing fuel loads and fuel moistures for a fire event after the fire has occurred, as well as by issues in translating variables relevant to hydrological processes produced by the hydrological model to those known to affect fire spread and fire severity. The first stage in the model evaluation aided the improvement of the model in both of these regards. In transporting the model to a new landscape in order to evaluate fire regimes in addition to patterns of fire spread, we find reasonable

  13. Model correction factor method for system analysis

    DEFF Research Database (Denmark)

    Ditlevsen, Ove Dalager; Johannesen, Johannes M.

    2000-01-01

    The Model Correction Factor Method is an intelligent response surface method based on simplifiedmodeling. MCFM is aimed for reliability analysis in case of a limit state defined by an elaborate model. Herein it isdemonstrated that the method is applicable for elaborate limit state surfaces on which...... severallocally most central points exist without there being a simple geometric definition of the corresponding failuremodes such as is the case for collapse mechanisms in rigid plastic hinge models for frame structures. Taking as simplifiedidealized model a model of similarity with the elaborate model...... surface than existing in the idealized model....

  14. Allele frequencies of variants in ultra conserved elements identify selective pressure on transcription factor binding.

    Directory of Open Access Journals (Sweden)

    Toomas Silla

    Full Text Available Ultra-conserved genes or elements (UCGs/UCEs in the human genome are extreme examples of conservation. We characterized natural variations in 2884 UCEs and UCGs in two distinct populations; Singaporean Chinese (n = 280 and Italian (n = 501 by using a pooled sample, targeted capture, sequencing approach. We identify, with high confidence, in these regions the abundance of rare SNVs (MAF5% are more often found in relatively less-conserved nucleotides within UCEs, compared to rare variants. Moreover, prevalent variants are less likely to overlap transcription factor binding site. Using SNPfold we found no significant influence of RNA secondary structure on UCE conservation. All together, these results suggest UCEs are not under selective pressure as a stretch of DNA but are under differential evolutionary pressure on the single nucleotide level.

  15. An Efficient Method to Identify Conditionally Activated Transcription Factors and their Corresponding Signal Transduction Pathway Segments

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    Haiyan Hu

    2009-11-01

    Full Text Available A signal transduction pathway (STP is a cascade composed of a series of signal transferring steps, which often activate one or more transcription factors (TFs to control the transcription of target genes. Understanding signaling pathways is important to our understanding of the molecular mechanisms of disease. Many condition-annotated pathways have been deposited in public databases. However, condition-annotated pathways are far from complete, considering the large number of possible conditions. Computational methods to assist in the identification of conditionally activated pathways are greatly needed. In this paper, we propose an efficient method to identify conditionally activated pathway segments starting from the identification of conditionally activated TFs, by incorporating protein-DNA binding data, gene expression data and protein interaction data. Applying our methods on several microarray datasets, we have discovered many significantly activated TFs and their corresponding pathway segments, which are supported by evidence in the literature.

  16. Identifying the challenging factors in the transition from colleges of engineering to employment

    Science.gov (United States)

    Baytiyeh, Hoda; Naja, Mohamad

    2012-03-01

    The transition from university to a career in engineering is a challenging process. This study examined the perceptions of engineering graduates regarding the difficulties they encountered in their transition from the university to the workplace. Lebanese practising engineers (n=217), living around the world, were surveyed to identify their current employment situations and their attitudes toward their academic preparation. Factor analysis revealed three main challenges facing engineering graduates: communication; responsibility; self-confidence. Seventeen interviews were conducted to gather information on ways to facilitate this transition. Comments reflected the need for better collaboration between engineering schools and engineering firms. The results will provide insight for engineering colleges, faculty members and administrators into the challenges faced by graduates and their aspirations for a smoother transition into employment.

  17. An investigation to identify potential risk factors associated with common chronic diseases among the older population in India

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    Enemona Emmanuel Adaji

    2017-01-01

    Full Text Available Background: In India, chronic diseases are the leading cause of death and their prevalence has constantly increased over the last decade. Objective: This study aimed to identify risk factors associated with common chronic diseases among people aged 50 years and over in India. Materials and Methods: Data from Wave 1 of the 2007/2008 Indian Study on Global Ageing and Adult Health (SAGE was used to investigate the association between lifestyle choices and chronic diseases using logistic regression. Result: The fully adjusted model showed that significant independent risk factors for angina included area of residence, being diagnosed with diabetes, chronic lung disease (CLD [highest odds ratio (OR 4.77, 95% confidence interval (CI: 2.95-7.70] and arthritis. For arthritis, risk factors included having underlying diabetes, CLD diagnosis, or angina (highest OR 2.32, 95% CI: 1.63-3.31. Risk factors associated with CLD included arthritis, angina (highest OR 4.76, 95% CI: 2.94-7.72, alcohol use, and tobacco use. Risk factors associated with diabetes included level of education, area of residence, socioeconomic status, angina (highest OR 3.59, 95% CI: 2.44-5.29, CLD, arthritis, stroke, and vegetable consumption. Finally, risk factors associated with stroke included diabetes and angina (highest OR 3.34, 95% CI: 1.72-6.50. The presence of any other comorbidity was significantly associated with all five chronic diseases studied. Conclusion: The results show that within the older population, the contribution of lifestyle risk factors to the common chronic diseases investigated in this study was limited. Our findings showed that the major health issue within the study population was multimorbidity.

  18. Identifying contributing factors to fatal and serious injury motorcycle collisions involving children in Malaysia.

    Science.gov (United States)

    Oxley, Jennifer; Ravi, Mano Deepa; Yuen, Jeremy; Hoareau, Effie; Hashim, Hizal Hanis

    2013-01-01

    In Malaysia, motorcycle crashes constitute approximately 60 percent of all road trauma, and a substantial proportion involve children 16 years and younger. There are, however, many gaps in our knowledge on contributing factors to crashes and injury patterns amongst children killed and seriously injured in motorcycle crashes. The aim of this study was to examine fatal and serious injury motorcycle-related collisions to identify contributing factors and injury patterns amongst child motorcyclists. All identified motorcyclist fatal crashes between 2007 and 2011 (inclusive) were extracted from the national Police-reported crash database (M-ROADS) and a range of variables were selected for examination. A total of 17,677 crashes were extracted where a rider or pillion was killed and of these crashes 2,038 involved children, equating to 12 percent. Examination of crashes involving children revealed that some crashes involved more than two children on the motorcycle, therefore, overall children constituted 9.5% of fatal and 18.4% of serious injury collisions. A high proportion of child fatal or serious injury collisions involved the child as the rider (62%), and this was most common for children aged between 10 and 16 years. The majority of collisions occurred on rural roads, in speed limit zones of 50-70km/h, and approximately one-third occurred at an intersection. Collisions involving another motorcycle or a passenger vehicle contributed to 41% and 53% of the total fatalities and severe injuries, respectively. A high proportion (43.9%) of the children (25.5% riders and 18.8% pillion) sustained head injuries with 37.7% being in the 10-16 age group. Furthermore, 52.4% of the children sustaining head injuries did not wear a helmet. The implications of these findings for countermeasures within a Safe System framework, particularly interventions aimed at reducing the rate of unlicensed riding and helmet wearing, and infrastructure countermeasures are discussed.

  19. Factors associated with onset timing, symptoms, and severity of depression identified in the postpartum period.

    Science.gov (United States)

    Fisher, Sheehan D; Wisner, Katherine L; Clark, Crystal T; Sit, Dorothy K; Luther, James F; Wisniewski, Stephen

    2016-10-01

    Unipolar and bipolar depression identified in the postpartum period have a heterogeneous etiology. The objectives of this study are to examine the risk factors that distinguish the timing of onset for unipolar and bipolar depression and the associations between depression onset by diagnosis, and general and atypical depressive symptoms. Symptoms of depression were assessed at 4- to 6-weeks postpartum by the Structured Interview Guide for the Hamilton Depression Rating Scale-Atypical Depression Symptoms in an obstetrical sample of 727 women. Data were analyzed using ANOVA, Chi-square, and linear regression. Mothers with postpartum onset of depression were more likely to be older, Caucasian, educated, married/cohabitating, have one or no previous child, and have private insurance in contrast to mothers with pre-pregnancy and prenatal onset of depression. Mothers with bipolar depression were more likely to have a pre-pregnancy onset. Three general and two atypical depressive symptoms distinguished pre-pregnancy, during pregnancy, and postpartum depression onset, and the presence of agitation distinguished between unipolar and bipolar depression. The sample was urban, which may not be generalizable to other populations. The study was cross-sectional, which excludes potential late onset of depression (after 4-6 weeks) in the first postpartum year. A collective set of factors predicted the onset of depression identified in the postpartum for mothers distinguished by episodes of unipolar versus bipolar depression, which can inform clinical interventions. Future research on the onset of major depressive episodes could inform prophylactic and early psychiatric interventions. Copyright © 2016 Elsevier B.V. All rights reserved.

  20. Boolean modeling identifies Greatwall/MASTL as an important regulator in the AURKA network of neuroblastoma.

    Science.gov (United States)

    Dahlhaus, Meike; Burkovski, Andre; Hertwig, Falk; Mussel, Christoph; Volland, Ruth; Fischer, Matthias; Debatin, Klaus-Michael; Kestler, Hans A; Beltinger, Christian

    2016-02-01

    Aurora Kinase A (AURKA) is often overexpressed in neuroblastoma (NB) with poor outcome. The causes of AURKA overexpression in NB are unknown. Here, we describe a gene regulatory network consisting of core regulators of AURKA protein expression and activation during mitosis to identify potential causes. This network was transformed to a dynamic Boolean model. Simulated activation of the serine/threonine protein kinase Greatwall (GWL, encoded by MASTL) that attenuates the pivotal AURKA inhibitor PP2A, predicted stabilization of AURKA. Consistent with this notion, gene set enrichment analysis showed enrichment of mitotic spindle assembly genes and MYCN target genes in NB with high GWL/MASTL expression. In line with the prediction of GWL/MASTL enhancing AURKA, elevated expression of GWL/MASTL was associated with NB risk factors and poor survival of patients. These results establish Boolean network modeling of oncogenic pathways in NB as a useful means for guided discovery in this enigmatic cancer.

  1. You Want Me to Use THAT Robot? Identifying Underlying Factors Affecting Robot Use

    Science.gov (United States)

    Yagoda, Rosemarie Elaine

    Building on traditional technology acceptance and human-robot interaction (HRI) research, this research sought to investigate operational HRI factors affecting robot use within the context of a high-risk environment. Technology acceptance models have previously focused on perceived usefulness and ease of use, but have tended to ignore barriers or external factors associated with technology adoption. The present studies investigate the role of barriers such as operational risk and lack of HRI trust in determining acceptance of robots. Experiment 1 empirically refined the experimental methodology used in Experiment 2 to investigate factors affecting robot use. Overall, the results highlighted the influence of HRI trust and operational risk on the likelihood of robot use; in addition, they shed light on the importance of the configuration of the robot capabilities needed for task completion. With the proposition that these relationships were moderated by the robot configuration, HRI trust was shown to increase the overall likelihood of robot use and only slight variations were attributed to increased operational risk. HRI trust was shown to have both a positive and negative influence in terms of the operational risks associated with on robot use. In fact, instances when HRI trust is high may lead to using a robot that is not even properly configured for the high-risk task. Therefore, it is beneficial to understand the underlying mechanisms that influence the perception (right or wrong) surrounding unmanned systems. The findings from this research can be used to enhance the utility and acceptance of new or existing unmanned systems.

  2. A Bayesian semiparametric factor analysis model for subtype identification.

    Science.gov (United States)

    Sun, Jiehuan; Warren, Joshua L; Zhao, Hongyu

    2017-04-25

    Disease subtype identification (clustering) is an important problem in biomedical research. Gene expression profiles are commonly utilized to infer disease subtypes, which often lead to biologically meaningful insights into disease. Despite many successes, existing clustering methods may not perform well when genes are highly correlated and many uninformative genes are included for clustering due to the high dimensionality. In this article, we introduce a novel subtype identification method in the Bayesian setting based on gene expression profiles. This method, called BCSub, adopts an innovative semiparametric Bayesian factor analysis model to reduce the dimension of the data to a few factor scores for clustering. Specifically, the factor scores are assumed to follow the Dirichlet process mixture model in order to induce clustering. Through extensive simulation studies, we show that BCSub has improved performance over commonly used clustering methods. When applied to two gene expression datasets, our model is able to identify subtypes that are clinically more relevant than those identified from the existing methods.

  3. Temporal SILAC-based quantitative proteomics identifies host factors involved in chikungunya virus replication.

    Science.gov (United States)

    Treffers, Emmely E; Tas, Ali; Scholte, Florine E M; Van, Myrthe N; Heemskerk, Matthias T; de Ru, Arnoud H; Snijder, Eric J; van Hemert, Martijn J; van Veelen, Peter A

    2015-07-01

    Chikungunya virus (CHIKV) is an arthropod-borne reemerging human pathogen that generally causes a severe persisting arthritis. Since 2005, the virus has infected millions of people during outbreaks in Africa, Indian Ocean Islands, Asia, and South/Central America. Many steps of the replication and expression of CHIKV's 12-kb RNA genome are highly dependent on cellular factors, which thus constitute potential therapeutic targets. SILAC and LC-MS/MS were used to define the temporal dynamics of the cellular response to infection. Using samples harvested at 8, 10, and 12 h postinfection, over 4700 proteins were identified and per time point 2800-3500 proteins could be quantified in both biological replicates. At 8, 10, and 12 h postinfection, 13, 38, and 106 proteins, respectively, were differentially expressed. The majority of these proteins showed decreased abundance. Most subunits of the RNA polymerase II complex were progressively degraded, which likely contributes to the transcriptional host shut-off observed during CHIKV infection. Overexpression of four proteins that were significantly downregulated (Rho family GTPase 3 (Rnd3), DEAD box helicase 56 (DDX56), polo-like kinase 1 (Plk1), and ubiquitin-conjugating enzyme E2C (UbcH10) reduced susceptibility of cells to CHIKV infection, suggesting that infection-induced downregulation of these proteins is beneficial for CHIKV replication. All MS data have been deposited in the ProteomeXchange with identifier PXD001330 (http://proteomecentral.proteomexchange.org/dataset/PXD001330).

  4. Visual Genome-Wide RNAi Screening to Identify Human Host Factors Required for Trypanosoma cruzi Infection

    Science.gov (United States)

    de Macedo Dossin, Fernando; Choi, Seo Yeon; Kim, Nam Youl; Kim, Hi Chul; Jung, Sung Yong; Schenkman, Sergio; Almeida, Igor C.; Emans, Neil; Freitas-Junior, Lucio H.

    2011-01-01

    The protozoan parasite Trypanosoma cruzi is the etiologic agent of Chagas disease, a neglected tropical infection that affects millions of people in the Americas. Current chemotherapy relies on only two drugs that have limited efficacy and considerable side effects. Therefore, the development of new and more effective drugs is of paramount importance. Although some host cellular factors that play a role in T. cruzi infection have been uncovered, the molecular requirements for intracellular parasite growth and persistence are still not well understood. To further study these host-parasite interactions and identify human host factors required for T. cruzi infection, we performed a genome-wide RNAi screen using cellular microarrays of a printed siRNA library that spanned the whole human genome. The screening was reproduced 6 times and a customized algorithm was used to select as hits those genes whose silencing visually impaired parasite infection. The 162 strongest hits were subjected to a secondary screening and subsequently validated in two different cell lines. Among the fourteen hits confirmed, we recognized some cellular membrane proteins that might function as cell receptors for parasite entry and others that may be related to calcium release triggered by parasites during cell invasion. In addition, two of the hits are related to the TGF-beta signaling pathway, whose inhibition is already known to diminish levels of T. cruzi infection. This study represents a significant step toward unveiling the key molecular requirements for host cell invasion and revealing new potential targets for antiparasitic therapy. PMID:21625474

  5. Visual genome-wide RNAi screening to identify human host factors required for Trypanosoma cruzi infection.

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    Auguste Genovesio

    Full Text Available The protozoan parasite Trypanosoma cruzi is the etiologic agent of Chagas disease, a neglected tropical infection that affects millions of people in the Americas. Current chemotherapy relies on only two drugs that have limited efficacy and considerable side effects. Therefore, the development of new and more effective drugs is of paramount importance. Although some host cellular factors that play a role in T. cruzi infection have been uncovered, the molecular requirements for intracellular parasite growth and persistence are still not well understood. To further study these host-parasite interactions and identify human host factors required for T. cruzi infection, we performed a genome-wide RNAi screen using cellular microarrays of a printed siRNA library that spanned the whole human genome. The screening was reproduced 6 times and a customized algorithm was used to select as hits those genes whose silencing visually impaired parasite infection. The 162 strongest hits were subjected to a secondary screening and subsequently validated in two different cell lines. Among the fourteen hits confirmed, we recognized some cellular membrane proteins that might function as cell receptors for parasite entry and others that may be related to calcium release triggered by parasites during cell invasion. In addition, two of the hits are related to the TGF-beta signaling pathway, whose inhibition is already known to diminish levels of T. cruzi infection. This study represents a significant step toward unveiling the key molecular requirements for host cell invasion and revealing new potential targets for antiparasitic therapy.

  6. Pseudomonas aeruginosa killing of Caenorhabditis elegans used to identify P. aeruginosa virulence factors

    Science.gov (United States)

    Tan, Man-Wah; Rahme, Laurence G.; Sternberg, Jeffrey A.; Tompkins, Ronald G.; Ausubel, Frederick M.

    1999-01-01

    We reported recently that the human opportunistic pathogen Pseudomonas aeruginosa strain PA14 kills Caenorhabditis elegans and that many P. aeruginosa virulence factors (genes) required for maximum virulence in mouse pathogenicity are also required for maximum killing of C. elegans. Here we report that among eight P. aeruginosa PA14 TnphoA mutants isolated that exhibited reduced killing of C. elegans, at least five also exhibited reduced virulence in mice. Three of the TnphoA mutants corresponded to the known virulence-related genes lasR, gacA, and lemA. Three of the mutants corresponded to known genes (aefA from Escherichia coli, pstP from Azotobacter vinelandii, and mtrR from Neisseria gonorrhoeae) that had not been shown previously to play a role in pathogenesis, and two of the mutants contained TnphoA inserted into novel sequences. These data indicate that the killing of C. elegans by P. aeruginosa can be exploited to identify novel P. aeruginosa virulence factors important for mammalian pathogenesis. PMID:10051655

  7. Identifying environmental risk factors for human neural tube defects before and after folic acid supplementation

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    Li Xinhu

    2009-10-01

    Full Text Available Abstract Background Birth defects are a major cause of infant mortality and disability in many parts of the world. Neural tube defects (NTDs are one of the most common types of birth defects. In 2001, the Chinese population and family planning commission initiated a national intervention program for the prevention of birth defects. A key step in the program was the introduction of folic acid supplementation. Of interest in the present study was to determine whether folic acid supplementation has the same protective effect on NTDs under various geographical and socioeconomic conditions within the Chinese population and the nature in which the influence of environmental factors varied after folic acid supplementation. Methods In this study, Heshun was selected as the region of interest as a surrogate for helping to answer some of the questions raised in this study on the impact of the intervention program. Spatial filtering in combination with GIS software was used to detect annual potential clusters from 1998 to 2005 in Heshun, and Kruskal-wallis test and multivariate regression were applied to identify the environmental risk factors for NTDs among various regions. Results In 1998, a significant (p Conclusion This suggests that the government needs to adapt the intervention measures according to local conditions. More attention needs to be paid to the poor and to people living in areas near coal mines.

  8. TO STUDY THE INCIDENCE OF ANAEMIA AND IDENTIFY AS RISK FACTOR IN CORONARY ARTERY DISEASE

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    S. Periasamy

    2016-07-01

    Full Text Available AIM AND OBJECTIVE To identify the incidence of anaemia and to identity anaemia itself as a risk factors in coronary artery disease in rural population. METHODS AND MATERIALS A prospective observational study done in patients admitted with evidence of coronary artery disease in Rajah Muthiah Medical College Hospital from January 2016 to April 2016. Patients with age more than 18 years, both gender, evidence of coronary artery disease were included and secondary case for anaemia were excluded. A detailed clinical history and examination, blood count with smear study was done. RESULT In our present study, male predominance (72% with more common in age group between (51-60 years 36%. Mean haemoglobin level in our study showed 11.70 g/dL. The incidence of anaemia was 80% with varying severity 7-9 (2%, 9-11 (32%, 11-13 (46%, >13(20% and smear showed microcytic hypochromic dominated with 52%. CONCLUSION Incidence of anaemia observed in rural population with reference to significances of role as risk factor yet to be studied with detailed study. It is important also to investigate secondary cause of anaemia.

  9. Participation of African social scientists in malaria control: identifying enabling and constraining factors

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    Nyamongo Isaac

    2004-12-01

    Full Text Available Abstract Objective To examine the enabling and constraining factors that influence African social scientists involvement in malaria control. Methods Convenience and snowball sampling was used to identify participants. Data collection was conducted in two phases: a mailed survey was followed by in-depth phone interviews with selected individuals chosen from the survey. Findings Most participants did not necessarily seek malaria as a career path. Having a mentor who provided research and training opportunities, and developing strong technical skills in malaria control and grant or proposal writing facilitated career opportunities in malaria. A paucity of jobs and funding and inadequate technical skills in malaria limited the type and number of opportunities available to social scientists in malaria control. Conclusion Understanding the factors that influence job satisfaction, recruitment and retention in malaria control is necessary for better integration of social scientists into malaria control. However, given the wide array of skills that social scientists have and the variety of deadly diseases competing for attention in Sub Saharan Africa, it might be more cost effective to employ social scientists to work broadly on issues common to communicable diseases in general rather than solely on malaria.

  10. Identifying Factors Associated with Risk Assessment Competencies of Public Health Emergency Responders.

    Science.gov (United States)

    Hao, Jiejing; Ren, Jiaojiao; Wu, Qunhong; Hao, Yanhua; Sun, Hong; Ning, Ning; Ding, Ding

    2017-06-04

    This study aimed to better understand the current situation of risk assessment and identify the factors associated with competence of emergency responders in public health risk assessment. The participants were selected by a multi-stage, stratified cluster sampling method in Heilongjiang Centers for Disease Control and Prevention (CDC). The questionnaires that measured their perceptions on risk assessment competences were administered through the face-to-face survey. A final sample of 1889 staff was obtained. Of this sample, 78.6% of respondents rated their own risk assessment competences as "relatively low", contrasting with 21.4% rated as "relatively high". Most of the respondents (62.7%) did not participate in any risk assessment work. Only 13.7% and 42.7% of respondents reported participating in risk assessment training and were familiar with risk assessment tools. There existed statistical significance between risk assessment-related characteristics of respondents and their self-rated competences scores. Financial support from the government and administrative attention were regarded as the important factors contributing to risk assessment competences of CDC responders. Higher attention should be given to risk assessment training and enhancing the availability of surveillance data. Continuous efforts should be made to remove the financial and technical obstacles to improve the competences of risk assessment for public health emergency responders.

  11. Proteomic analysis of polyribosomes identifies splicing factors as potential regulators of translation during mitosis.

    Science.gov (United States)

    Aviner, Ranen; Hofmann, Sarah; Elman, Tamar; Shenoy, Anjana; Geiger, Tamar; Elkon, Ran; Ehrlich, Marcelo; Elroy-Stein, Orna

    2017-06-02

    Precise regulation of mRNA translation is critical for proper cell division, but little is known about the factors that mediate it. To identify mRNA-binding proteins that regulate translation during mitosis, we analyzed the composition of polysomes from interphase and mitotic cells using unbiased quantitative mass-spectrometry (LC-MS/MS). We found that mitotic polysomes are enriched with a subset of proteins involved in RNA processing, including alternative splicing and RNA export. To demonstrate that these may indeed be regulators of translation, we focused on heterogeneous nuclear ribonucleoprotein C (hnRNP C) as a test case and confirmed that it is recruited to elongating ribosomes during mitosis. Then, using a combination of pulsed SILAC, metabolic labeling and ribosome profiling, we showed that knockdown of hnRNP C affects both global and transcript-specific translation rates and found that hnRNP C is specifically important for translation of mRNAs that encode ribosomal proteins and translation factors. Taken together, our results demonstrate how proteomic analysis of polysomes can provide insight into translation regulation under various cellular conditions of interest and suggest that hnRNP C facilitates production of translation machinery components during mitosis to provide daughter cells with the ability to efficiently synthesize proteins as they enter G1 phase. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  12. Ancestry of pink disease (infantile acrodynia) identified as a risk factor for autism spectrum disorders.

    Science.gov (United States)

    Shandley, Kerrie; Austin, David W

    2011-01-01

    Pink disease (infantile acrodynia) was especially prevalent in the first half of the 20th century. Primarily attributed to exposure to mercury (Hg) commonly found in teething powders, the condition was developed by approximately 1 in 500 exposed children. The differential risk factor was identified as an idiosyncratic sensitivity to Hg. Autism spectrum disorders (ASD) have also been postulated to be produced by Hg. Analogous to the pink disease experience, Hg exposure is widespread yet only a fraction of exposed children develop an ASD, suggesting sensitivity to Hg may also be present in children with an ASD. The objective of this study was to test the hypothesis that individuals with a known hypersensitivity to Hg (pink disease survivors) may be more likely to have descendants with an ASD. Five hundred and twenty-two participants who had previously been diagnosed with pink disease completed a survey on the health outcomes of their descendants. The prevalence rates of ASD and a variety of other clinical conditions diagnosed in childhood (attention deficit hyperactivity disorder, epilepsy, Fragile X syndrome, and Down syndrome) were compared to well-established general population prevalence rates. The results showed the prevalence rate of ASD among the grandchildren of pink disease survivors (1 in 22) to be significantly higher than the comparable general population prevalence rate (1 in 160). The results support the hypothesis that Hg sensitivity may be a heritable/genetic risk factor for ASD.

  13. Integrative transcriptome analysis identifies deregulated microRNA-transcription factor networks in lung adenocarcinoma.

    Science.gov (United States)

    Cinegaglia, Naiara C; Andrade, Sonia Cristina S; Tokar, Tomas; Pinheiro, Maísa; Severino, Fábio E; Oliveira, Rogério A; Hasimoto, Erica N; Cataneo, Daniele C; Cataneo, Antônio J M; Defaveri, Júlio; Souza, Cristiano P; Marques, Márcia M C; Carvalho, Robson F; Coutinho, Luiz L; Gross, Jefferson L; Rogatto, Silvia R; Lam, Wan L; Jurisica, Igor; Reis, Patricia P

    2016-05-17

    Herein, we aimed at identifying global transcriptome microRNA (miRNA) changes and miRNA target genes in lung adenocarcinoma. Samples were selected as training (N = 24) and independent validation (N = 34) sets. Tissues were microdissected to obtain >90% tumor or normal lung cells, subjected to miRNA transcriptome sequencing and TaqMan quantitative PCR validation. We further integrated our data with published miRNA and mRNA expression datasets across 1,491 lung adenocarcinoma and 455 normal lung samples. We identified known and novel, significantly over- and under-expressed (p ≤ 0.01 and FDR≤0.1) miRNAs in lung adenocarcinoma compared to normal lung tissue: let-7a, miR-10a, miR-15b, miR-23b, miR-26a, miR-26b, miR-29a, miR-30e, miR-99a, miR-146b, miR-181b, miR-181c, miR-421, miR-181a, miR-574 and miR-1247. Validated miRNAs included let-7a-2, let-7a-3, miR-15b, miR-21, miR-155 and miR-200b; higher levels of miR-21 expression were associated with lower patient survival (p = 0.042). We identified a regulatory network including miR-15b and miR-155, and transcription factors with prognostic value in lung cancer. Our findings may contribute to the development of treatment strategies in lung adenocarcinoma.

  14. Case control study to identify risk factors for acute hepatitis C virus infection in Egypt

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    Kandeel Amr M

    2012-11-01

    Full Text Available Abstract Background Identification of risk factors of acute hepatitis C virus (HCV infection in Egypt is crucial to develop appropriate prevention strategies. Methods We conducted a case–control study, June 2007-September 2008, to investigate risk factors for acute HCV infection in Egypt among 86 patients and 287 age and gender matched controls identified in two infectious disease hospitals in Cairo and Alexandria. Case-patients were defined as: any patient with symptoms of acute hepatitis; lab tested positive for HCV antibodies and negative for HBsAg, HBc IgM, HAV IgM; and 7-fold increase in the upper limit of transaminase levels. Controls were selected from patients’ visitors with negative viral hepatitis markers. Subjects were interviewed about previous exposures within six months, including community-acquired and health-care associated practices. Results Case-patients were more likely than controls to have received injection with a reused syringe (OR=23.1, CI 4.7-153, to have been in prison (OR=21.5, CI 2.5-479.6, to have received IV fluids in a hospital (OR=13.8, CI 5.3-37.2, to have been an IV drug user (OR=12.1, CI 4.6-33.1, to have had minimal surgical procedures (OR=9.7, CI 4.2-22.4, to have received IV fluid as an outpatient (OR=8, CI 4–16.2, or to have been admitted to hospital (OR=7.9, CI 4.2-15 within the last 6 months. Multivariate analysis indicated that unsafe health facility practices are the main risk factors associated with transmission of HCV infection in Egypt. Conclusion In Egypt, focusing acute HCV prevention measures on health-care settings would have a beneficial impact.

  15. Factor analysis of 27Al MAS NMR spectra for identifying nanocrystalline phases in amorphous geopolymers.

    Science.gov (United States)

    Urbanova, Martina; Kobera, Libor; Brus, Jiri

    2013-11-01

    Nanostructured materials offer enhanced physicochemical properties because of the large interfacial area. Typically, geopolymers with specifically synthesized nanosized zeolites are a promising material for the sorption of pollutants. The structural characterization of these aluminosilicates, however, continues to be a challenge. To circumvent complications resulting from the amorphous character of the aluminosilicate matrix and from the low concentrations of nanosized crystallites, we have proposed a procedure based on factor analysis of (27)Al MAS NMR spectra. The capability of the proposed method was tested on geopolymers that exhibited various tendencies to crystallize (i) completely amorphous systems, (ii) X-ray amorphous systems with nanocrystalline phases, and (iii) highly crystalline systems. Although the recorded (27)Al MAS NMR spectra did not show visible differences between the amorphous systems (i) and the geopolymers with the nanocrystalline phase (ii), the applied factor analysis unambiguously distinguished these materials. The samples were separated into the well-defined clusters, and the systems with the evolving crystalline phase were identified even before any crystalline fraction was detected by X-ray powder diffraction. Reliability of the proposed procedure was verified by comparing it with (29)Si MAS NMR spectra. Factor analysis of (27)Al MAS NMR spectra thus has the ability to reveal spectroscopic features corresponding to the nanocrystalline phases. Because the measurement time of (27)Al MAS NMR spectra is significantly shorter than that of (29)Si MAS NMR data, the proposed procedure is particularly suitable for the analysis of large sets of specifically synthesized geopolymers in which the formation of the limited fractions of nanocrystalline phases is desired. Copyright © 2013 John Wiley & Sons, Ltd.

  16. Bayesian Constrained-Model Selection for Factor Analytic Modeling

    OpenAIRE

    Peeters, Carel F.W.

    2016-01-01

    My dissertation revolves around Bayesian approaches towards constrained statistical inference in the factor analysis (FA) model. Two interconnected types of restricted-model selection are considered. These types have a natural connection to selection problems in the exploratory FA (EFA) and confirmatory FA (CFA) model and are termed Type I and Type II model selection. Type I constrained-model selection is taken to mean the determination of the appropriate dimensionality of a model. This type ...

  17. School absenteeism among children and its correlates: a predictive model for identifying absentees.

    Science.gov (United States)

    Uppal, Preena; Paul, Premila; Sreenivas, V

    2010-11-01

    To determine the magnitude of absenteeism and its correlates and to develop a model to predict absenteeism in school children. A cross-sectional study. three government schools in Delhi. 704 students, aged 10 to15 years. students were registered and interviewed using a pre designed questionnaire. The frequency and causes of school absenteeism were ascertained by school records, leave applications and one months recall. The factors were subjected to univariate analysis and a stepwise multiple logistic regression analysis and a predictive model was developed. The average absenteeism of a student over 6 months was 14.3±10.2 days (95% CI 13.5 -15.0). 48% children absented themselves for more than two days per month on an average. The main factors associated with school absenteeism were younger age, male sex, increasing birth order, lower levels of parental education and income, school truancy, school phobia and family reasons. The discriminating ability of the predictive model developed was 92.4% it is possible to identify potential absentees in school children.

  18. Continuous utility factor in segregation models

    Science.gov (United States)

    Roy, Parna; Sen, Parongama

    2016-02-01

    We consider the constrained Schelling model of social segregation in which the utility factor of agents strictly increases and nonlocal jumps of the agents are allowed. In the present study, the utility factor u is defined in a way such that it can take continuous values and depends on the tolerance threshold as well as the fraction of unlike neighbors. Two models are proposed: in model A the jump probability is determined by the sign of u only, which makes it equivalent to the discrete model. In model B the actual values of u are considered. Model A and model B are shown to differ drastically as far as segregation behavior and phase transitions are concerned. In model A, although segregation can be achieved, the cluster sizes are rather small. Also, a frozen state is obtained in which steady states comprise many unsatisfied agents. In model B, segregated states with much larger cluster sizes are obtained. The correlation function is calculated to show quantitatively that larger clusters occur in model B. Moreover for model B, no frozen states exist even for very low dilution and small tolerance parameter. This is in contrast to the unconstrained discrete model considered earlier where agents can move even when utility remains the same. In addition, we also consider a few other dynamical aspects which have not been studied in segregation models earlier.

  19. Identifying fire plumes in the Arctic with tropospheric FTIR measurements and transport models

    Science.gov (United States)

    Viatte, C.; Strong, K.; Hannigan, J.; Nussbaumer, E.; Emmons, L. K.; Conway, S.; Paton-Walsh, C.; Hartley, J.; Benmergui, J.; Lin, J.

    2015-03-01

    We investigate Arctic tropospheric composition using ground-based Fourier transform infrared (FTIR) solar absorption spectra, recorded at the Polar Environment Atmospheric Research Laboratory (PEARL, Eureka, Nunavut, Canada, 80°05' N, 86°42' W) and at Thule (Greenland, 76°53' N, -68°74' W) from 2008 to 2012. The target species, carbon monoxide (CO), hydrogen cyanide (HCN), ethane (C2H6), acetylene (C2H2), formic acid (HCOOH), and formaldehyde (H2CO) are emitted by biomass burning and can be transported from mid-latitudes to the Arctic. By detecting simultaneous enhancements of three biomass burning tracers (HCN, CO, and C2H6), ten and eight fire events are identified at Eureka and Thule, respectively, within the 5-year FTIR time series. Analyses of Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model back-trajectories coupled with Moderate Resolution Imaging Spectroradiometer (MODIS) fire hotspot data, Stochastic Time-Inverted Lagrangian Transport (STILT) model footprints, and Ozone Monitoring Instrument (OMI) UV aerosol index maps, are used to attribute burning source regions and travel time durations of the plumes. By taking into account the effect of aging of the smoke plumes, measured FTIR enhancement ratios were corrected to obtain emission ratios and equivalent emission factors. The means of emission factors for extratropical forest estimated with the two FTIR data sets are 0.40 ± 0.21 g kg-1 for HCN, 1.24 ± 0.71 g kg-1 for C2H6, 0.34 ± 0.21 g kg-1 for C2H2, and 2.92 ± 1.30 g kg-1 for HCOOH. The emission factor for CH3OH estimated at Eureka is 3.44 ± 1.68 g kg-1. To improve our knowledge concerning the dynamical and chemical processes associated with Arctic pollution from fires, the two sets of FTIR measurements were compared to the Model for OZone And Related chemical Tracers, version 4 (MOZART-4). Seasonal cycles and day-to-day variabilities were compared to assess the ability of the model to reproduce emissions from fires and

  20. Statistical Analyses of Scatterplots to Identify Important Factors in Large-Scale Simulations

    Energy Technology Data Exchange (ETDEWEB)

    Kleijnen, J.P.C.; Helton, J.C.

    1999-04-01

    The robustness of procedures for identifying patterns in scatterplots generated in Monte Carlo sensitivity analyses is investigated. These procedures are based on attempts to detect increasingly complex patterns in the scatterplots under consideration and involve the identification of (1) linear relationships with correlation coefficients, (2) monotonic relationships with rank correlation coefficients, (3) trends in central tendency as defined by means, medians and the Kruskal-Wallis statistic, (4) trends in variability as defined by variances and interquartile ranges, and (5) deviations from randomness as defined by the chi-square statistic. The following two topics related to the robustness of these procedures are considered for a sequence of example analyses with a large model for two-phase fluid flow: the presence of Type I and Type II errors, and the stability of results obtained with independent Latin hypercube samples. Observations from analysis include: (1) Type I errors are unavoidable, (2) Type II errors can occur when inappropriate analysis procedures are used, (3) physical explanations should always be sought for why statistical procedures identify variables as being important, and (4) the identification of important variables tends to be stable for independent Latin hypercube samples.

  1. A cross-sectional study of 329 farms in England to identify risk factors for ovine clinical mastitis.

    Science.gov (United States)

    Cooper, S; Huntley, S J; Crump, R; Lovatt, F; Green, L E

    2016-03-01

    The aims of this study were to estimate the incidence rate of clinical mastitis (IRCM) and identify risk factors for clinical mastitis in suckler ewes to generate hypotheses for future study. A postal questionnaire was sent to 999 randomly selected English sheep farmers in 2010 to gather data on farmer reported IRCM and flock management practices for the calendar year 2009, of which 329 provided usable information. The mean IRCM per flock was 1.2/100 ewes/year (CI:1.10:1.35). The IRCM was 2.0, 0.9 and 1.3/100 ewes/year for flocks that lambed indoors, outdoors and a combination of both, respectively. Farmers ran a variety of managements before, during and after lambing that were not comparable within one model, therefore six mixed effects over-dispersed Poisson regression models were developed. Factors significantly associated with increased IRCM were increasing percentage of the flock with poor udder conformation, increasing mean number of lambs reared/ewe and when some or all ewes lambed in barns compared with outdoors (Model 1). For ewes housed in barns before lambing (Model 2), concrete, earth and other materials were associated with an increase in IRCM compared with hardcore floors (an aggregate of broken bricks and stones). For ewes in barns during lambing (Model 3), an increase in IRCM was associated with concrete compared with hardcore flooring and where bedding was stored covered outdoors or in a building compared with bedding stored outdoors uncovered. For ewes in barns after lambing (Model 4), increased IRCM was associated with earth compared with hardcore floors, and when fresh bedding was added once per week compared with at a frequency of ≤2 days or twice/week. The IRCM was lower for flocks where some or all ewes remained in the same fields before, during and after lambing compared with flocks that did not (Model 5). Where ewes and lambs were turned outdoors after lambing (Model 6), the IRCM increased as the age of the oldest lambs at turnout

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

    NARCIS (Netherlands)

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

    1997-01-01

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

  3. Naturalistic cycling study: identifying risk factors for on-road commuter cyclists.

    Science.gov (United States)

    Johnson, Marilyn; Charlton, Judith; Oxley, Jennifer; Newstead, Stuart

    2010-01-01

    The study aim was to identify risk factors for collisions/near-collisions involving on-road commuter cyclists and drivers. A naturalistic cycling study was conducted in Melbourne, Australia, with cyclists wearing helmet-mounted video cameras. Video recordings captured cyclists' perspective of the road and traffic behaviours including head checks, reactions and manoeuvres. The 100-car naturalistic driving study analysis technique was adapted for data analysis and events were classified by severity: collision, near-collision and incident. Participants were adult cyclists and each filmed 12 hours of commuter cycling trips over a 4-week period. In total, 127 hours and 38 minutes were analysed for 13 participants, 54 events were identified: 2 collisions, 6 near-collisions and 46 incidents. Prior to events, 88.9% of cyclists travelled in a safe/legal manner. Sideswipe was the most frequent event type (40.7%). Most events occurred at an intersection/intersection-related location (70.3%). The vehicle driver was judged at fault in the majority of events (87.0%) and no post-event driver reaction was observed (83.3%). Cross tabulations revealed significant associations between event severity and: cyclist reaction, cyclist post-event manoeuvre, pre-event driver behaviour, other vehicle involved, driver reaction, visual obstruction, cyclist head check (left), event type and vehicle location (proad cyclists and to indicate early before turning/changing lanes when sharing the roadway with cyclists are discussed. Findings will contribute to the development of effective countermeasures to reduce cyclist trauma.

  4. Identifying factors to improve oral cancer screening uptake: a qualitative study.

    Directory of Open Access Journals (Sweden)

    Fatemeh Vida Zohoori

    Full Text Available AIMS: To engage with high risk groups to identify knowledge and awareness of oral cancer signs and symptoms and the factors likely to contribute to improved screening uptake. METHODS: Focus group discussions were undertaken with 18 males; 40+ years of age; smokers and/or drinkers (15+ cigarettes per day and/or 15+ units of alcohol per week, irregular dental attenders living in economically deprived areas of Teesside. RESULTS: There was a striking reported lack of knowledge and awareness of oral cancer and its signs and symptoms among the participants. When oral/mouth cancer leaflets produced by Cancer Research UK were presented to the participants, they claimed that they would seek help on noticing such a condition. There was a preference to seek help from their general practitioner rather than their dentist due to perceptions that a dentist is 'inaccessible' on a physical and psychological level, costly, a 'tooth specialist' not a 'mouth specialist', and also not able to prescribe medication and make referrals to specialists. Interestingly, none of the 18 participants who were offered a free oral cancer examination at a dental practice took up this offer. CONCLUSIONS: The uptake of oral cancer screening may be improved by increasing knowledge of the existence and signs and symptoms of oral cancer. Other factors that may increase uptake are increased awareness of the role of dentists in diagnosing oral cancer, promotion of oral cancer screening by health professionals during routine health checks, and the use of a "health" screening setting as opposed to a "dental" setting for such checks.

  5. Using focus groups to identify factors affecting healthy weight maintenance in college men.

    Science.gov (United States)

    Walsh, Jennifer R; White, Adrienne A; Greaney, Mary L

    2009-06-01

    Healthful eating and physical activity are important for healthy weight maintenance. The hypothesis for this study was that college-aged men would perceive factors affecting eating and physical activity as both contributing to and inhibiting healthy weight maintenance. The overall objective was to explore how men view weight maintenance in the context of these aspects. Subjects (n = 47, mean age = 20.3 +/- 1.7 years) completed an online survey, including the 51-item Three-Factor Eating Questionnaire, and participated in 1 of 6 focus groups. Three face-to-face and 3 online synchronous groups were conducted using a 15-question discussion guide to identify weight maintenance issues around eating, physical activity, and body perceptions. Weight satisfaction decreased with increase in both dietary restraint and disinhibition. Number of attempts to lose weight was positively associated with BMI (r [44] = .465, P = .01) and dietary restraint (r [44] = .515, P = .01). Findings from both focus group formats were similar. Motivators (sports performance/fitness, self-esteem, attractiveness, long-term health) were similar for eating healthfully and being physically active; however, more motivators to be physically active than to eat healthfully emerged. Enablers for eating healthfully included liking the taste, availability of healthful foods, using food rules to guide intake, having a habit of healthful eating, and internal drive/will. Barriers to healthful eating included fat in dairy foods, fruit and vegetable taste, and quick spoilage. Barriers to being physically active included lack of time/time management, obligations, being lazy, and girlfriends. Results may be used to inform future obesity prevention interventions.

  6. On applying safety archetypes to the Fukushima accident to identify nonlinear influencing factors

    Energy Technology Data Exchange (ETDEWEB)

    Sousa, A.L., E-mail: alsousa@cnen.gov.br [Comissao Nacional de Energia Nuclear (CNEN), Rio de Janeiro, RJ (Brazil); Ribeiro, A.C.O., E-mail: antonio.ribeiro@bayer.com [Bayer Crop Science Brasil S.A., Belford Roxo, RJ (Brazil); Duarte, J.P., E-mail: julianapduarte@poli.ufrj.br [Universidade Federal do Rio de Janeiro (UFRJ), RJ (Brazil). Escola Politecnica. Departamento de Engenharia Nuclear; Frutuoso e Melo, P.F., E-mail: frutuoso@nuclear.ufrj.br [Coordenacao dos Programas de Pos-Graduacao em Engenharia (COOPE/UFRJ), RJ (Brazil). Programa de Engenharia Nuclear

    2013-07-01

    Nuclear power plants are typically characterized as high reliable organizations. In other words, they are organizations defined as relatively error free over a long period of time. Another relevant characteristic of the nuclear industry is that safety efforts are credited to design. However, major accidents, like the Fukushima accident, have shown that new tools are needed to identify latent deficiencies and help improve their safety level. Safety archetypes proposed elsewhere (e. g., safety issues stalled in the face of technological advances and eroding safety) consonant with International Atomic Energy Agency (IAEA) efforts are used to examine different aspects of accidents in a systemic perspective of the interaction between individuals, technology and organizational factors. Safety archetypes can help consider nonlinear interactions. Effects are rarely proportional to causes and what happens locally in a system (near the current operating point) often does not apply to distant regions (other system states), so that one has to consider the so-called nonlinear interactions. This is the case, for instance, with human probability failure estimates and safety level identification. In this paper, we discuss the Fukushima accident in order to show how archetypes can highlight nonlinear interactions of factors that influenced it and how to maintain safety levels in order to prevent other accidents. The initial evaluation of the set of archetypes suggested in the literature showed that at least four of them are applicable to the Fukushima accident, as is inferred from official reports on the accident. These are: complacency (that is, the effects of complacency on safety), decreased safety awareness, fixing on symptoms and not the real causes and eroding safety. (author)

  7. New breast cancer prognostic factors identified by computer-aided image analysis of HE stained histopathology images.

    Science.gov (United States)

    Chen, Jia-Mei; Qu, Ai-Ping; Wang, Lin-Wei; Yuan, Jing-Ping; Yang, Fang; Xiang, Qing-Ming; Maskey, Ninu; Yang, Gui-Fang; Liu, Juan; Li, Yan

    2015-05-29

    Computer-aided image analysis (CAI) can help objectively quantify morphologic features of hematoxylin-eosin (HE) histopathology images and provide potentially useful prognostic information on breast cancer. We performed a CAI workflow on 1,150 HE images from 230 patients with invasive ductal carcinoma (IDC) of the breast. We used a pixel-wise support vector machine classifier for tumor nests (TNs)-stroma segmentation, and a marker-controlled watershed algorithm for nuclei segmentation. 730 morphologic parameters were extracted after segmentation, and 12 parameters identified by Kaplan-Meier analysis were significantly associated with 8-year disease free survival (P < 0.05 for all). Moreover, four image features including TNs feature (HR 1.327, 95%CI [1.001-1.759], P = 0.049), TNs cell nuclei feature (HR 0.729, 95%CI [0.537-0.989], P = 0.042), TNs cell density (HR 1.625, 95%CI [1.177-2.244], P = 0.003), and stromal cell structure feature (HR 1.596, 95%CI [1.142-2.229], P = 0.006) were identified by multivariate Cox proportional hazards model to be new independent prognostic factors. The results indicated that CAI can assist the pathologist in extracting prognostic information from HE histopathology images for IDC. The TNs feature, TNs cell nuclei feature, TNs cell density, and stromal cell structure feature could be new prognostic factors.

  8. The Animadora Project: identifying factors related to the promotion of physical activity among Mexican Americans with diabetes.

    Science.gov (United States)

    Ingram, Maia; Ruiz, Maricruz; Mayorga, Maria Theresa; Rosales, Cecilia

    2009-01-01

    There is a dearth of information about factors related to physical activity among Mexican-Americans with diabetes. Self-efficacy and social support are associated with physical activity; however, little is known about their roles within different cultural groups. Focus groups were used to identify factors that motivated walking. Two Mexican-American communities located in Tucson, Arizona. Individuals who attended diabetes education. A community-based provider organized walking groups with people who previously attended diabetes classes. Walkers participated in focus groups exploring themes related to their experiences. Self-efficacy, social support, and collective efficacy. Grounded theory was used to analyze focus group results using two rounds of analysis; the first identified references to self-efficacy and social support, and the second added collective efficacy as a theoretic basis for walking. Among 43 eligible participants, 20 participated in focus groups. Social support was expressed as commitment and companionship. Walkers demonstrated a high level of self-efficacy for walking. Development of group identity/social cohesion was also a motivator to walk. Collective efficacy emerged as an applicable theoretic model encompassing these themes and their interrelationship. Collective efficacy, or the belief that the group can improve their lives through collective effort, is a viable theoretic construct in the development of physical activity interventions targeting Mexican-Americans with diabetes.

  9. Model correction factor method for system analysis

    DEFF Research Database (Denmark)

    Ditlevsen, Ove Dalager; Johannesen, Johannes M.

    2000-01-01

    severallocally most central points exist without there being a simple geometric definition of the corresponding failuremodes such as is the case for collapse mechanisms in rigid plastic hinge models for frame structures. Taking as simplifiedidealized model a model of similarity with the elaborate model...... but with clearly defined failure modes, the MCFM can bestarted from each idealized single mode limit state in turn to identify a locally most central point on the elaborate limitstate surface. Typically this procedure leads to a fewer number of locally most central failure points on the elaboratelimit state...... surface than existing in the idealized model....

  10. 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.

  11. The asset pricing model of musharakah factors

    Science.gov (United States)

    Simon, Shahril; Omar, Mohd; Lazam, Norazliani Md

    2015-02-01

    The existing three-factor model developed by Fama and French for conventional investment was formulated based on risk-free rates element in which contradict with Shariah principles. We note that the underlying principles that govern Shariah investment were mutual risk and profit sharing between parties, the assurance of fairness for all and that transactions were based on an underlying asset. In addition, the three-factor model did not exclude stock that was not permissible by Shariah such as financial services based on riba (interest), gambling operator, manufacture or sale of non-halal products or related products and other activities deemed non-permissible according to Shariah. Our approach to construct the factor model for Shariah investment was based on the basic tenets of musharakah in tabulating the factors. We start by noting that Islamic stocks with similar characteristics should have similar returns and risks. This similarity between Islamic stocks was defined by the similarity of musharakah attributes such as business, management, profitability and capital. These attributes define factor exposures (or betas) to factors. The main takeaways were that musharakah attributes we chose had explain stock returns well in cross section and were significant in different market environments. The management factor seemed to be responsible for the general dynamics of the explanatory power.

  12. Identifying risk factors for Plasmodium infection and anaemia in Kinshasa, Democratic Republic of Congo.

    Science.gov (United States)

    Ferrari, Giovanfrancesco; Ntuku, Henry M T; Ross, Amanda; Schmidlin, Sandro; Kalemwa, Didier M; Tshefu, Antoinette K; Lengeler, Christian

    2016-07-15

    There is little data on the risk factors for malaria infection in large cities in central Africa and in all age groups. There may be different associations with the risk factors for areas with different malaria transmission intensities such as the effect of fever or age. This study aimed at identifying risk factors associated with Plasmodium infection and anaemia among children 6-59 months and individuals aged older than 5 years in Kinshasa, a large city with heterogeneity in malaria prevalence. This study analysed data from 3342 children aged 6-59 months from 25 non-rural health zones (HZs) and for 816 individuals aged older than 5 years from two HZs in Kinshasa (non-rural), collected during a cross sectional malaria survey in 2011. Logistic regression with random effects was used to investigate predictors for malaria and anaemia. Differences in risk factors in areas with a prevalence of less than 10 and 10 % or greater were investigated. There was evidence of a different age-pattern in the two transmission settings. For children under 5 years, the highest prevalence of malaria was observed in the 48-59 months group in both transmission settings, but it increased more gently for the lower transmission HZs (p = 0.009). In a separate analysis in children over 5 years in two selected HZs, the peak prevalence was in 5-9 years old in the higher transmission setting and in 15-19 years old in the lower transmission setting. Reported fever was associated with malaria in both transmission strata, with no evidence of a difference in these associations (p = 0.71); however in children older than 5 years there was a significant interaction with a stronger association in the low transmission HZ. Insecticide-treated net (ITN) use was associated with a lower risk of malaria infection in children 6-59 months in the high transmission HZs. Similar estimates were found in children over 5 years and the lower transmission HZ but the associations there were not

  13. Calibration of Local Area Weather Radar—Identifying significant factors affecting the calibration

    Science.gov (United States)

    Pedersen, Lisbeth; Jensen, Niels Einar; Madsen, Henrik

    2010-07-01

    A Local Area Weather Radar (LAWR) is an X-band weather radar developed to meet the needs of high resolution rainfall data for hydrological applications. The LAWR system and data processing methods are reviewed in the first part of this paper, while the second part of the paper focuses on calibration. The data processing for handling the partial beam filling issue was found to be essential to the calibration. LAWR uses a different calibration process compared to conventional weather radars, which use a power-law relationship between reflectivity and rainfall rate. Instead LAWR uses a linear relationship of reflectivity and rainfall rate as result of the log transformation carried out by the logarithmic receiver as opposed to the linear receiver of conventional weather radars. Based on rain gauge data for a five month period from a dense network of nine gauges within a 500 × 500 m area and data from a nearby LAWR, the existing calibration method was tested and two new methods were developed. The three calibration methods were verified with three external gauges placed in different locations. It can be concluded that the LAWR calibration uncertainties can be reduced by 50% in two out of three cases when the calibration is based on a factorized 3 parameter linear model instead of a single parameter linear model.

  14. Identifying the factors governing attitude towards the e-Agriservice among dairy farmers in Maharashtra, India

    Directory of Open Access Journals (Sweden)

    Sagar Kisan Wadkar

    2016-01-01

    Full Text Available Information and communication technology (ICT projects have a great potential to revolutionise the information delivery system by bridging the gap between farmers and extension personnel. aAQUA (Almost All Questions Answered portal was launched by the Developmental Informatics Laboratory (DIL at Indian Institute of Technology (IIT Mumbai, Maharashtra, India in 2003 as an information providing system to deliver technology options and tailored information for the problems and queries raised by Indian dairy farmers. To measure the effectiveness of this service the attitudinal dimensions of the users of aAQUA e-Agriservice were investigated using a 22 item scale. A simple random sampling technique was used to select 120 dairy farmers from which data were collected and subjected to factor analysis to identify the underlying constructs in this research. From the attitude items, four components were extracted and named as the pessimistic, utility, technical and efficacy perspective, which influenced the development of varied level of attitudinal inclination towards the e-Agriservice. These components explained 64.40 per cent of variation in the attitude of the users towards the aAQUA e-Agriservice. This study provides a framework for technically efficient service provision that might help to reduce the pessimistic attitude of target population to adopt e-Agriservice in their farming system. The results should also be helpful for researchers, academics, ICT based service providers and policy makers to consider these perspectives while planning and implementing ICT projects.

  15. Conceptual and Operational Considerations in Identifying Socioenvironmental Factors Associated with Disability among Community-Dwelling Adults

    Directory of Open Access Journals (Sweden)

    Mathieu Philibert

    2015-04-01

    Full Text Available Disability is conceived as a person–context interaction. Physical and social environments are identified as intervention targets for improving social participation and independence. In comparison to the body of research on place and health, relatively few reports have been published on residential environments and disability in the health sciences literature. We reviewed studies evaluating the socioenvironmental correlates of disability. Searches were conducted in Medline, Embase and CINAHL databases for peer-reviewed articles published between 1997 and 2014. We found many environmental factors to be associated with disability, particularly area-level socioeconomic status and rurality. However, diversity in conceptual and methodological approaches to such research yields a limited basis for comparing studies. Conceptual inconsistencies in operational measures of disability and conceptual disagreement between studies potentially affect understanding of socioenvironmental influences. Similarly, greater precision in socioenvironmental measures and in study designs are likely to improve inference. Consistent and generalisable support for socioenvironmental influences on disability in the general adult population is scarce.

  16. Identifying Risk Factors of Boot Procurement: A Case Study of Stadium Australia

    Directory of Open Access Journals (Sweden)

    Marcus Jefferies

    2012-11-01

    Full Text Available Private sector input into the procurement of public works and services is continuing to increase. This has partly arisen out of a requirement for infrastructure development to be undertaken at a rate that maintains and allows growth. This has become a major challange for the construction industry that cannot be met by government alone. The emergence of Build-Own-Operate-Transfer (BOOT schemes as a response to this challange provides a means for developing the infrastructure of a country without directly impacting on the governments budgetary constraints. The concepts of BOOT are without doubt extremely complex arrangements, which bring to the construction sector risks not experienced previously. Many of the infrastructure partnerships between public and private sector in the pastare yet to provide evidence of successful completion, since few of the concession periods have expired. This paper provides an identified list of risk factors to a case study of Stadium Australia. The most significant risk associated with Stadium Australia include the bidding process, the high level of public scrutiny, post-Olympic Games facility revenue and the complicated nature of the consortium structure.  

  17. Identifying Risk Factors of Boot Procurement: A Case Study of Stadium Australia

    Directory of Open Access Journals (Sweden)

    Marcus Jefferies

    2012-11-01

    Full Text Available Private sector input into the procurement of public works and services is continuing to increase. This has partly arisen out of a requirement for infrastructure development to be undertaken at a rate that maintains and allows growth. This has become a major challange for the construction industry that cannot be met by government alone. The emergence of Build-Own-Operate-Transfer (BOOT schemes as a response to this challange provides a means for developing the infrastructure of a country without directly impacting on the governments budgetary constraints. The concepts of BOOT are without doubt extremely complex arrangements, which bring to the construction sector risks not experienced previously. Many of the infrastructure partnerships between public and private sector in the pastare yet to provide evidence of successful completion, since few of the concession periods have expired. This paper provides an identified list of risk factors to a case study of Stadium Australia. The most significant risk associated with Stadium Australia include the bidding process, the high level of public scrutiny, post-Olympic Games facility revenue and the complicated nature of the consortium structure.

  18. Factors Identified with Higher Levels of Career Satisfaction of Physicians in Andalusia, Spain.

    Science.gov (United States)

    Peña-Sánchez, Juan Nicolás; Lepnurm, Rein; Morales-Asencio, José Miguel; Delgado, Ana; Domagała, Alicja; Górkiewicz, Maciej

    2014-04-26

    The satisfaction of physicians is a worldwide issue linked with the quality of health services; their satisfaction needs to be studied from a multi-dimensional perspective, considering lower- and higher-order needs. The objectives of this study were to: i) measure the career satisfaction of physicians; ii) identify differences in the dimensions of career satisfaction; and iii) test factors that affect higher- and lower-order needs of satisfaction among physicians working in Andalusian hospitals (Spain). Forty-one percent of 299 eligible physicians participated in a study conducted in six selected hospitals. Physicians reported higher professional, inherent, and performance satisfaction than personal satisfaction. Foreign physicians reported higher levels of personal and performance satisfaction than local physicians, and those who received non-monetary incentives had higher professional and performance satisfaction. In conclusion, physicians in the selected Andalusian hospitals reported low levels of personal satisfaction. Non-monetary incentives were more relevant to influence their career satisfaction. Further investigations are recommended to study differences in the career satisfaction between foreign and local physicians.

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

    Science.gov (United States)

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

    2008-01-01

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

  20. Epidermal growth factor gene is a newly identified candidate gene for gout

    Science.gov (United States)

    Han, Lin; Cao, Chunwei; Jia, Zhaotong; Liu, Shiguo; Liu, Zhen; Xin, Ruosai; Wang, Can; Li, Xinde; Ren, Wei; Wang, Xuefeng; Li, Changgui

    2016-01-01

    Chromosome 4q25 has been identified as a genomic region associated with gout. However, the associations of gout with the genes in this region have not yet been confirmed. Here, we performed two-stage analysis to determine whether variations in candidate genes in the 4q25 region are associated with gout in a male Chinese Han population. We first evaluated 96 tag single nucleotide polymorphisms (SNPs) in eight inflammatory/immune pathway- or glucose/lipid metabolism-related genes in the 4q25 region in 480 male gout patients and 480 controls. The SNP rs12504538, located in the elongation of very-long-chain-fatty-acid-like family member 6 gene (Elovl6), was found to be associated with gout susceptibility (Padjusted = 0.00595). In the second stage of analysis, we performed fine mapping analysis of 93 tag SNPs in Elovl6 and in the epidermal growth factor gene (EGF) and its flanking regions in 1017 male patients gout and 1897 healthy male controls. We observed a significant association between the T allele of EGF rs2298999 and gout (odds ratio = 0.77, 95% confidence interval = 0.67–0.88, Padjusted = 6.42 × 10−3). These results provide the first evidence for an association between the EGF rs2298999 C/T polymorphism and gout. Our findings should be validated in additional populations. PMID:27506295

  1. Factor Copula Models for Replicated Spatial Data

    KAUST Repository

    Krupskii, Pavel

    2016-12-19

    We propose a new copula model that can be used with replicated spatial data. Unlike the multivariate normal copula, the proposed copula is based on the assumption that a common factor exists and affects the joint dependence of all measurements of the process. Moreover, the proposed copula can model tail dependence and tail asymmetry. The model is parameterized in terms of a covariance function that may be chosen from the many models proposed in the literature, such as the Matérn model. For some choice of common factors, the joint copula density is given in closed form and therefore likelihood estimation is very fast. In the general case, one-dimensional numerical integration is needed to calculate the likelihood, but estimation is still reasonably fast even with large data sets. We use simulation studies to show the wide range of dependence structures that can be generated by the proposed model with different choices of common factors. We apply the proposed model to spatial temperature data and compare its performance with some popular geostatistics models.

  2. Unitary input DEA model to identify beef cattle production systems typologies

    Directory of Open Access Journals (Sweden)

    Eliane Gonçalves Gomes

    2012-08-01

    Full Text Available The cow-calf beef production sector in Brazil has a wide variety of operating systems. This suggests the identification and the characterization of homogeneous regions of production, with consequent implementation of actions to achieve its sustainability. In this paper we attempted to measure the performance of 21 livestock modal production systems, in their cow-calf phase. We measured the performance of these systems, considering husbandry and production variables. The proposed approach is based on data envelopment analysis (DEA. We used unitary input DEA model, with apparent input orientation, together with the efficiency measurements generated by the inverted DEA frontier. We identified five modal production systems typologies, using the isoefficiency layers approach. The results showed that the knowledge and the processes management are the most important factors for improving the efficiency of beef cattle production systems.

  3. Posterior gut development in Drosophila:a model system for identifying genes controlling epithelial morphogenesis

    Institute of Scientific and Technical Information of China (English)

    LENGYELJUEITHA; SUEJUNLIU

    1998-01-01

    The posterior gut of the Drosophila embryo,consisting of hindgut and Malpighian tubules,provides a simple,well-defined system where it is possible to use a genetic approach to define components essential for epithelial morphogenesis.We review here the advantages of Drosophila as a model genetic organism,the morphogenesis of the epithelial structures of the posterior gut,and what is known about the genetic requirements to form these structures.In overview,primordia are patterned by expression of hierarchies of transcription factors;this leads to localized expression of cell signaling molecules,and finally,to the least understood step:modulation of cell adhesion and cell shape.We describe approaches to identify additional genes that are required for morphogenesis of these simple epithelia,particularly those that might play a structural role by affecting cell adhesion and cell shape.

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

    Science.gov (United States)

    F C Pan, Frank

    2014-03-01

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

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

    Directory of Open Access Journals (Sweden)

    Frank F C Pan

    2014-03-01

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

  6. Identifying Staff Development Needs of Cooperative Extension Faculty Using a Modified Borich Needs Assessment Model.

    Science.gov (United States)

    Waters, Randol G.; Haskell, Larry J.

    1989-01-01

    To identify staff development needs and test the Borich Needs Assessment Model, 68 faculty in Nevada were surveyed (90 percent response). Use of the model made rankings of individual topics substantively different from results obtained by traditional methods. (JOW)

  7. Identifying risk factors of avian infectious diseases at household level in Poyang Lake region, China.

    Science.gov (United States)

    Jiang, Qian; Zhou, Jieting; Jiang, Zhiben; Xu, Bing

    2014-09-01

    Poultry kept in backyard farms are susceptible to acquiring and spreading infectious diseases because of free ranging and poor biosecurity measures. Since some of these diseases are zoonoses, this is also a significant health concern to breeders and their families. Backyard farms are common in rural regions of China. However, there is lack of knowledge of backyard poultry in the country. To obtain first-hand information of backyard poultry and identify risk factors of avian infectious diseases, a cross-sectional study was carried out at household level in rural regions around Poyang Lake. A door-to-door survey was conducted to collect data on husbandry practices, trading practices of backyard farmers, and surrounding environments of backyard farms. Farms were categorized into cases and controls based on their history of poultry death. Data were collected for 137 farms, and the association with occurrence of poultry death event was explored by chi-square tests. Results showed that vaccination implementation was a protective factor (odds ratio OR=0.40, 95% confidence interval CI: 0.20-0.80, p=0.01), while contact with other backyard flocks increased risk (OR=1.72, 95% CI: 0.79-3.74, p=0.16). A concept of "farm connectivity" characterized by the density of particular land-use types in the vicinity of the farm was proposed to characterize the degree of contact between poultry in one household farm and those in other household farms. It was found that housing density in a 20-m buffer zone of the farmhouse was most significantly associated with poultry death occurrence (OR=1.08, 95% CI: 1.02-1.17, p=0.03), and was in agreement with observation of villagers. Binary logistic regression was applied to evaluate the relationship between poultry death event and density of land-use types in all buffer zones. When integrated with vaccination implementation for poultry, prediction accuracy of poultry death event reached 72.0%. Results combining questionnaire survey with

  8. Identifying fire plumes in the Arctic with tropospheric FTIR measurements and transport models

    Directory of Open Access Journals (Sweden)

    C. Viatte

    2014-10-01

    Full Text Available We investigate Arctic tropospheric composition using ground-based Fourier Transform Infrared (FTIR solar absorption spectra, recorded at the Polar Environment Atmospheric Research Laboratory (PEARL, Eureka, Nunavut, Canada, 80°5' N, 86°42' W and at Thule (Greenland, 76°53' N, −68°74' W from 2008 to 2012. The target species: carbon monoxide (CO, hydrogen cyanide (HCN, ethane (C2H6, acetylene (C2H2, formic acid (HCOOH, and formaldehyde (H2CO are emitted by biomass burning and can be transported from mid-latitudes to the Arctic. By detecting simultaneous enhancements of three biomass burning tracers (HCN, CO, and C2H6, ten and eight fire events are identified at Eureka and Thule, respectively, within the five-year FTIR timeseries. Analyses of Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT back-trajectories coupled with Moderate Resolution Imaging Spectroradiometer (MODIS fire hot spot data, Stochastic Time-Inverted Lagrangian Transport model (STILT footprints, and Ozone Monitoring Instrument (OMI UV aerosol index maps are used to attribute burning source regions and travel time durations of the plumes. By taking into account the effect of aging of the smoke plumes, measured FTIR enhancement ratios were corrected to obtain emission ratios and equivalent emission factors. The means of emission factors for extratropical forest estimated with the two FTIR datasets are 0.39 ± 0.15 g kg−1 for HCN, 1.23 ± 0.49 g kg−1 for C2H6, 0.34 ± 0.16 g kg−1 for C2H2, 2.13 ± 0.92 g kg−1 for HCOOH, and 3.14 ± 1.28 g kg−1 for CH3OH. To improve our knowledge concerning the dynamical and chemical processes associated with Arctic pollution from fires, the two sets of FTIR measurements were compared to the Model for Ozone and Related chemical Tracers, version 4 (MOZART-4. Seasonal cycles and day-to-day variabilities were compared to assess the ability of the model to reproduce emissions from fires and their transport. Good

  9. A review of the use of human factors classification frameworks that identify causal factors for adverse events in the hospital setting.

    Science.gov (United States)

    Mitchell, R J; Williamson, A M; Molesworth, B; Chung, A Z Q

    2014-01-01

    Various human factors classification frameworks have been used to identified causal factors for clinical adverse events. A systematic review was conducted to identify human factors classification frameworks that identified the causal factors (including human error) of adverse events in a hospital setting. Six electronic databases were searched, identifying 1997 articles and 38 of these met inclusion criteria. Most studies included causal contributing factors as well as error and error type, but the nature of coding varied considerably between studies. The ability of human factors classification frameworks to provide information on specific causal factors for an adverse event enables the focus of preventive attention on areas where improvements are most needed. This review highlighted some areas needing considerable improvement in order to meet this need, including better definition of terms, more emphasis on assessing reliability of coding and greater sophistication in analysis of results of the classification. Practitioner Summary: Human factors classification frameworks can be used to identify causal factors of clinical adverse events. However, this review suggests that existing frameworks are diverse, limited in their identification of the context of human error and have poor reliability when used by different individuals.

  10. Potential mechanisms for hypoalgesia induced by anti-nerve growth factor immunoglobulin are identified using autoimmune nerve growth factor deprivation

    Science.gov (United States)

    Hoffman, E. Matthew; Zhang, Zijia; Anderson, Michael B.; Schechter, Ruben; Miller, Kenneth E.

    2011-01-01

    Nerve growth factor (NGF) antagonism has long been proposed as a chronic pain treatment. In 2010, the FDA suspended clinical trials using tanezumab, a humanized monoclonal anti-NGF antibody, to treat osteoarthritis due to worsening joint damage in 16 patients. Increased physical activity in the absence of acute pain which normally prevents self harm was purported as a potential cause. Such an adverse effect is consistent with an extension of tanezumab's primary mechanism of action by decreasing pain sensitivity below baseline levels. In animal inflammatory pain models, NGF antagonism decreases intraepidermal nerve fiber (IENF) density and attenuates increases in expression of nociception related proteins, such as calcitonin gene-related peptide (CGRP) and substance P (SP). Little is known of the effects of NGF antagonism in noninflamed animals and the hypoalgesia that ensues. In the current study, we immunized rats with NGF or cytochrome C (cytC) and examined 1) nocifensive behaviors with thermal latencies, mechanical thresholds, the hot plate test, and the tail flick test, 2) IENF density, and 3) expression of CGRP, SP, voltage-gated sodium channel 1.8 (Nav1.8), and glutaminase in subpopulations of dorsal root ganglion (DRG) neurons separated by size and isolectin B4 (IB4) labeling. Rats with high anti-NGF titers had delayed responses on the hot plate test but no other behavioral abnormalities. Delayed hot plate responses correlated with lower IENF density. CGRP and SP expression was decreased principally in medium (400-800 μm2) and small neurons (<400 μm2), respectively, regardless of IB4 labeling. Expression of Nav1.8 was only decreased in small and medium IB4 negative neurons. NGF immunization appears to result in a more profound antagonism of NGF than tanezumab therapy, but we hypothesize that decreases in IENF density and nociception related protein expression are potential mechanisms for tanezumab induced hypoalgesia. PMID:21802499

  11. Identifying the factors influencing minority language use in health care education settings: a European perspective.

    Science.gov (United States)

    Roberts, G W; Paden, L

    2000-07-01

    The recent enhanced status of many minority languages across the European Community has led to increasing demands for their use within the public sector. This is particularly evident in health care, where, in circumstances of stress and vulnerability, denying opportunities for clients to communicate in their preferred language may place them at a personal disadvantage and compromise their health chances. In view of the exclusion of many minority languages from the public domain over the years, their re-introduction demands adaptations to health care education programmes in order to promote language sensitivity in practice. Before embarking on developments which establish such languages within the professional sphere, valuable insight may be gained by examining their current use in practice education. Furthermore, comparing their use across language communities enables the sharing of common experiences and furthers opportunities for developing networks across Europe. This paper describes an ethnographic study of the use, within midwifery education, of the Welsh language in north Wales, the Catalan language in Barcelona and the Irish language in Western Ireland. Semi-structured interviews were conducted with key lecturers, clinical mentors and students across the three communities in order to determine patterns of language use within a range of learning environments. Focus groups were also held in order to confirm the findings. The data reveal many commonalities in terms of language use across the three settings and important factors are identified which support the use of minority languages in practice education. The findings are invaluable for guiding future bilingual initiatives across health care education programmes.

  12. Shelter dogs and their destiny. A retrospective analysis to identify predictive factors - a pilot study

    Directory of Open Access Journals (Sweden)

    Simona Cannas

    2014-10-01

    Full Text Available Consequences of a long stay in dog shelter have particular signifi cance, because, since 1991, the Italian law (14/08/1991, n.281 prohibits euthanasia of dogs unless “they are seriously ill, incurable or proven dangerous”. Caught dogs are recovered for a quarantine period in the sanitary kennel, if they are not returned to the owner, they are moved to shelters until adoption or death. The aim of this work was to identify the relationship between dogs characteristics and their destiny in order to define useful predictors to better manage the stay of dogs in shelter. We analysed the records of all dogs recovered in a sanitary kennel from 2005 to 2010 and subsequently moved to shelters (n=771. Descriptive and inferential statistics were performed in order to investigate possible factors that might affect adoptability of sheltered dogs. The characteristics of dogs that spent more time in PVCS, before being transfer to the CR, were: large size, male gender and age between 11 months and 2 years (p ≤ 0,05. Male dogs spent more days in CR, as opposed to female (p ≤ 0,05. In our sample 76% dogs were adopted, 18% were still in the shelter, 4% died and 2% were euthanized. Female dogs were adopted more than males; young dogs more than elderly (over seven years; sizes medium and small more than large. It would be interesting use the data from this research and complete them with information regarding dogs behaviour, to better manage dogs during the stay in shelter and to improve their relocation.

  13. Clinical incidents involving students on placement: an analysis of incident reports to identify potential risk factors.

    Science.gov (United States)

    Gaida, J E; Maloney, S; Lo, K; Morgan, P

    2015-06-01

    Students are sometimes involved in incidents during clinical training. To the authors' knowledge, no quantitative studies of incidents specifically involving physiotherapy students on clinical placement are available in the literature. A retrospective audit (2008 to 2011) of incident reports involving physiotherapy students was conducted to identify the nature and features of incidents. The study aimed to determine if injuries to a student or patient were more or less likely when the supervisor was in close proximity, and whether students with lower academic performance in their preclinical semester were more likely to be involved in an incident. There were 19 care-delivery-related and three equipment-related incidents. There were no incidents of violent, aggressive or demeaning behaviour towards students. The incident rate was 9.0/100,000 student-hours for third-year students and 6.8/100,000 student-hours for fourth-year students. The majority of incidents (55%) occurred from 11 am to 12-noon and from 3 pm to 3.30 pm. Incidents more often resulted in patient or student injury when the supervisor was not in close proximity (approximately 50% vs approximately 20%), although the difference was not significant (P=0.336). The academic results of students involved in incidents were equivalent to the whole cohort in their preclinical semester {mean 75 [standard deviation (SD) 6] vs 76 (SD 7); P=0.488}. The unexpected temporal clustering of incidents warrants further investigation. Student fatigue may warrant attention as a potential contributor; however, contextual factors, such as staff workload, along with organisational systems, structures and procedures may be more relevant. The potential relationship between supervisor proximity and injury also warrants further exploration. The findings of the present study should be integrated into clinical education curricula and communicated to clinical educators. Copyright © 2014 Chartered Society of Physiotherapy. Published by

  14. Identifying factors associated with concordance with the American College of Rheumatology rheumatoid arthritis treatment recommendations.

    Science.gov (United States)

    Harrold, Leslie R; Reed, George W; Kremer, Joel M; Curtis, Jeffrey R; Solomon, Daniel H; Hochberg, Marc C; Kavanaugh, Arthur; Saunders, Katherine C; Shan, Ying; Spruill, Tanya M; Pappas, Dimitrios A; Greenberg, Jeffrey D

    2016-04-26

    Factors associated with care concordant with the American College of Rheumatology (ACR) recommendations for the use of disease-modifying antirheumatic drugs (DMARDs) in rheumatoid arthritis (RA) are unknown. We identified a national cohort of biologic-naive patients with RA with visits between December 2008 and February 2013. Treatment acceleration (initiation or dose escalation of biologic and nonbiologic DMARDs) in response to moderate to high disease activity (using the Clinical Disease Activity Index) was assessed. The population was divided into two subcohorts: (1) methotrexate (MTX)-only users and (2) multiple nonbiologic DMARD users. In both subcohorts, we compared the characteristics of patients who received care consistent with the ACR recommendations (e.g., prescriptions for treatment acceleration) and their providers with the characteristics of those who did not at the conclusion of one visit and over two visits, using logistic regression and adjusting for clustering of patients by rheumatologist. Our study included 741 MTX monotherapy and 995 multiple nonbiologic DMARD users cared for by 139 providers. Only 36.2 % of MTX monotherapy users and 39.6 % of multiple nonbiologic DMARD users received care consistent with the recommendations after one visit, which increased over two visits to 78.3 % and 76.2 %, respectively (25-30 % achieved low disease activity by the second visit without DMARD acceleration). Increasing time since the ACR publication on RA treatment recommendations was not associated with improved adherence. Allowing two encounters for treatment acceleration was associated with an increase in care concordant with the recommendations; however, time since publication was not.

  15. Three different anti-lipopolysaccharide factors identified from giant freshwater prawn, Macrobrachium rosenbergii.

    Science.gov (United States)

    Ren, Qian; Zhang, Zhao; Li, Xin-Chang; Jie-Du; Hui, Kai-Min; Zhang, Chi-Yu; Wang, Wen

    2012-10-01

    Anti-lipopolysaccharide factor (ALF) is a type of basic protein and an important antimicrobial peptide that can bind and neutralize lipopolysaccharides (LPS). This protein shows a broad spectrum of antimicrobial activity. In this study, three forms of ALF designated as MrALF5, MrALF6, and MrALF7 were identified from giant freshwater prawn, Macrobrachium rosenbergii. MrALF5, MrALF6, and MrALF7 genes encode 133, 121, and 120 amino acids of the corresponding proteins, respectively. All these ALF proteins contain LPS-binding domain with two conserved cysteine residues. The genomic sequences of MrALF5 and MrALF7 were amplified. The genomic structures of MrALF5 and MrALF7 comprise three exons interrupted by two introns. Phylogenetic analysis showed that MrALF5, MrALF6, and MrALF7 were clustered into clade II. Evolutionary analysis showed that ALF genes from M. rosenbergii may suffer a rapid evolution. MrALF5 was expressed mainly in the hepatopancreas, gills, and heart. MrALF6 was mainly distributed in the intestine and hepatopancreas. The highest expression level of MrALF7 was detected in the hepatopancreas. MrALF6, as well as MrALF7, was downregulated by Escherichia coli challenge, and all three ALF genes were upregulated by Vibrio or white spot syndrome virus challenge. MrALF6 was also upregulated by Staphylococcus aureus challenge. In summary, the three isoforms of ALF genes may participate in the innate immune response against bacteria and virus infecting the giant fresh water prawn.

  16. Identifying functional transcription factor binding sites in yeast by considering their positional preference in the promoters.

    Directory of Open Access Journals (Sweden)

    Fu-Jou Lai

    Full Text Available Transcription factor binding site (TFBS identification plays an important role in deciphering gene regulatory codes. With comprehensive knowledge of TFBSs, one can understand molecular mechanisms of gene regulation. In the recent decades, various computational approaches have been proposed to predict TFBSs in the genome. The TFBS dataset of a TF generated by each algorithm is a ranked list of predicted TFBSs of that TF, where top ranked TFBSs are statistically significant ones. However, whether these statistically significant TFBSs are functional (i.e. biologically relevant is still unknown. Here we develop a post-processor, called the functional propensity calculator (FPC, to assign a functional propensity to each TFBS in the existing computationally predicted TFBS datasets. It is known that functional TFBSs reveal strong positional preference towards the transcriptional start site (TSS. This motivates us to take TFBS position relative to the TSS as the key idea in building our FPC. Based on our calculated functional propensities, the TFBSs of a TF in the original TFBS dataset could be reordered, where top ranked TFBSs are now the ones with high functional propensities. To validate the biological significance of our results, we perform three published statistical tests to assess the enrichment of Gene Ontology (GO terms, the enrichment of physical protein-protein interactions, and the tendency of being co-expressed. The top ranked TFBSs in our reordered TFBS dataset outperform the top ranked TFBSs in the original TFBS dataset, justifying the effectiveness of our post-processor in extracting functional TFBSs from the original TFBS dataset. More importantly, assigning functional propensities to putative TFBSs enables biologists to easily identify which TFBSs in the promoter of interest are likely to be biologically relevant and are good candidates to do further detailed experimental investigation. The FPC is implemented as a web tool at http://santiago.ee.ncku.edu.tw/FPC/.

  17. Identifying Watershed, Landscape, and Engineering Design Factors that Influence the Biotic Condition of Restored Streams

    Directory of Open Access Journals (Sweden)

    Barbara Doll

    2016-04-01

    Full Text Available Restored stream reaches at 79 sites across North Carolina were sampled for aquatic macroinvertebrates using a rapid bioassessment protocol. Morphological design parameters and geographic factors, including watershed and landscape parameters (e.g., valley slope, substrate, were also compiled for these streams. Principal component regression analyses revealed correlations between design and landscape variables with macroinvertebrate metrics. The correlations were strengthened by adding watershed variables. Ridge regression was used to find the best-fit model for predicting dominant taxa from the “pollution sensitive” orders of Ephemeroptera (mayflies, Plecoptera (stoneflies, and Trichoptera (caddisflies, or EPT taxa, resulting in coefficient weights that were most interpretable relative to site selection and design parameters. Results indicate that larger (wider streams located in the mountains and foothills where there are steeper valleys, larger substrate, and undeveloped watersheds are expected to have higher numbers of dominant EPT taxa. In addition, EPT taxa numbers are positively correlated with accessible floodplain width and negatively correlated with width-to-depth ratio and sinuosity. This study indicates that both site selection and design should be carefully considered in order to maximize the resulting biotic condition and associated potential ecological uplift of the stream.

  18. Modelling non-normal data : The relationship between the skew-normal factor model and the quadratic factor model

    NARCIS (Netherlands)

    Smits, Iris A.M.; Timmerman, Marieke E.; Stegeman, Alwin

    Maximum likelihood estimation of the linear factor model for continuous items assumes normally distributed item scores. We consider deviations from normality by means of a skew-normally distributed factor model or a quadratic factor model. We show that the item distributions under a skew-normal

  19. Local identifiability and sensitivity analysis of neuromuscular blockade and depth of hypnosis models.

    Science.gov (United States)

    Silva, M M; Lemos, J M; Coito, A; Costa, B A; Wigren, T; Mendonça, T

    2014-01-01

    This paper addresses the local identifiability and sensitivity properties of two classes of Wiener models for the neuromuscular blockade and depth of hypnosis, when drug dose profiles like the ones commonly administered in the clinical practice are used as model inputs. The local parameter identifiability was assessed based on the singular value decomposition of the normalized sensitivity matrix. For the given input signal excitation, the results show an over-parameterization of the standard pharmacokinetic/pharmacodynamic models. The same identifiability assessment was performed on recently proposed minimally parameterized parsimonious models for both the neuromuscular blockade and the depth of hypnosis. The results show that the majority of the model parameters are identifiable from the available input-output data. This indicates that any identification strategy based on the minimally parameterized parsimonious Wiener models for the neuromuscular blockade and for the depth of hypnosis is likely to be more successful than if standard models are used.

  20. A Clinical model to identify patients with high-risk coronary artery disease

    NARCIS (Netherlands)

    Y. Yang (Yelin); L. Chen (Li); Y. Yam (Yeung); S. Achenbach (Stephan); M. Al-Mallah (Mouaz); D.S. Berman (Daniel); M.J. Budoff (Matthew); F. Cademartiri (Filippo); T.Q. Callister (Tracy); H.-J. Chang (Hyuk-Jae); V.Y. Cheng (Victor); K. Chinnaiyan (Kavitha); R.C. Cury (Ricardo); A. Delago (Augustin); A. Dunning (Allison); G.M. Feuchtner (Gudrun); M. Hadamitzky (Martin); J. Hausleiter (Jörg); R.P. Karlsberg (Ronald); P.A. Kaufmann (Philipp); Y.-J. Kim (Yong-Jin); J. Leipsic (Jonathon); T.M. LaBounty (Troy); F.Y. Lin (Fay); E. Maffei (Erica); G.L. Raff (Gilbert); L.J. Shaw (Leslee); T.C. Villines (Todd); J.K. Min (James K.); B.J.W. Chow (Benjamin)

    2015-01-01

    textabstractObjectives This study sought to develop a clinical model that identifies patients with and without high-risk coronary artery disease (CAD). Background Although current clinical models help to estimate a patient's pre-test probability of obstructive CAD, they do not accurately identify th

  1. A Clinical model to identify patients with high-risk coronary artery disease

    NARCIS (Netherlands)

    Y. Yang (Yelin); L. Chen (Li); Y. Yam (Yeung); S. Achenbach (Stephan); M. Al-Mallah (Mouaz); D.S. Berman (Daniel); M.J. Budoff (Matthew); F. Cademartiri (Filippo); T.Q. Callister (Tracy); H.-J. Chang (Hyuk-Jae); V.Y. Cheng (Victor); K. Chinnaiyan (Kavitha); R.C. Cury (Ricardo); A. Delago (Augustin); A. Dunning (Allison); G.M. Feuchtner (Gudrun); M. Hadamitzky (Martin); J. Hausleiter (Jörg); R.P. Karlsberg (Ronald); P.A. Kaufmann (Philipp); Y.-J. Kim (Yong-Jin); J. Leipsic (Jonathon); T.M. LaBounty (Troy); F.Y. Lin (Fay); E. Maffei (Erica); G.L. Raff (Gilbert); L.J. Shaw (Leslee); T.C. Villines (Todd); J.K. Min (James K.); B.J.W. Chow (Benjamin)

    2015-01-01

    textabstractObjectives This study sought to develop a clinical model that identifies patients with and without high-risk coronary artery disease (CAD). Background Although current clinical models help to estimate a patient's pre-test probability of obstructive CAD, they do not accurately identify th

  2. Structural identifiability of a model for the acetic acid fermentation process.

    Science.gov (United States)

    Jiménez-Hornero, Jorge E; Santos-Dueñas, Inés M; Garci A-Garci A, Isidoro

    2008-12-01

    Modelling has proved an essential tool for addressing research into biotechnological processes, particularly with a view to their optimization and control. Parameter estimation via optimization approaches is among the major steps in the development of biotechnology models. In fact, one of the first tasks in the development process is to determine whether the parameters concerned can be unambiguously determined and provide meaningful physical conclusions as a result. The analysis process is known as 'identifiability' and presents two different aspects: structural or theoretical identifiability and practical identifiability. While structural identifiability is concerned with model structure alone, practical identifiability takes into account both the quantity and quality of experimental data. In this work, we discuss the theoretical identifiability of a new model for the acetic acid fermentation process and review existing methods for this purpose.

  3. A combined structural dynamics approach identifies a putative switch in factor VIIa employed by tissue factor to initiate blood coagulation

    DEFF Research Database (Denmark)

    Olsen, Ole H; Rand, Kasper D; Østergaard, Henrik;

    2007-01-01

    Coagulation factor VIIa (FVIIa) requires tissue factor (TF) to attain full catalytic competency and to initiate blood coagulation. In this study, the mechanism by which TF allosterically activates FVIIa is investigated by a structural dynamics approach that combines molecular dynamics (MD...

  4. Aging Successfully: A Four-Factor Model

    Science.gov (United States)

    Lee, Pai-Lin; Lan, William; Yen, Tung-Wen

    2011-01-01

    The study was designed to validate a model for a successful aging process and examine the gender differences in the aging process. Three hundred twelve participants who were 65 or older completed a Taiwan Social Change Survey that measures four factors that define successful aging process: including physical, psychological, social support, and…

  5. Multistructure Statistical Model Applied To Factor Analysis

    Science.gov (United States)

    Bentler, Peter M.

    1976-01-01

    A general statistical model for the multivariate analysis of mean and covariance structures is described. Matrix calculus is used to develop the statistical aspects of one new special case in detail. This special case separates the confounding of principal components and factor analysis. (DEP)

  6. Aging Successfully: A Four-Factor Model

    Science.gov (United States)

    Lee, Pai-Lin; Lan, William; Yen, Tung-Wen

    2011-01-01

    The study was designed to validate a model for a successful aging process and examine the gender differences in the aging process. Three hundred twelve participants who were 65 or older completed a Taiwan Social Change Survey that measures four factors that define successful aging process: including physical, psychological, social support, and…

  7. A hierarchical model for ordinal matrix factorization

    DEFF Research Database (Denmark)

    Paquet, Ulrich; Thomson, Blaise; Winther, Ole

    2012-01-01

    their ratings for other movies. The Netflix data set is used for evaluation, which consists of around 100 million ratings. Using root mean-squared error (RMSE) as an evaluation metric, results show that the suggested model outperforms alternative factorization techniques. Results also show how Gibbs sampling...

  8. Identifying Factors Associated with Changes in CD4+ Count in HIV-Infected Adults in Saskatoon, Saskatchewan

    Directory of Open Access Journals (Sweden)

    Kelsey Hunt

    2015-01-01

    Full Text Available OBJECTIVE: To assess the impact of clinical and social factors unique to HIV-infected adults in Saskatoon, Saskatchewan, regarding the rate of CD4+ count change, and to identify factors associated with a risk of CD4+ count decline.

  9. 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...... are not informative enough (sensitivities of 16 parameters were insignificant). This indicates that the NREL model has severe parameter uncertainty, likely to be the case for other hydrolysis models as well since similar kinetic expressions are used. To overcome this impasse, we have used the Monte Carlo procedure...

  10. Identifying factors that influence customer retention in a South African retail bank

    OpenAIRE

    Gouws, Nadia

    2012-01-01

    Customer retention plays a pivotal role in contributing to the profitability of retail banks. Within this extremely competitive market it necessitates retails banks to follow a structured, data-driven approach to identify “at risk” customers and to launch proactive retention campaigns based on identified drivers of customer attrition. The following main drivers of customer attrition were identified in the retail bank:  Attrition decrease as Vertical Sales Index increase.  Attrition...

  11. Global Quantitative Modeling of Chromatin Factor Interactions

    Science.gov (United States)

    Zhou, Jian; Troyanskaya, Olga G.

    2014-01-01

    Chromatin is the driver of gene regulation, yet understanding the molecular interactions underlying chromatin factor combinatorial patterns (or the “chromatin codes”) remains a fundamental challenge in chromatin biology. Here we developed a global modeling framework that leverages chromatin profiling data to produce a systems-level view of the macromolecular complex of chromatin. Our model ultilizes maximum entropy modeling with regularization-based structure learning to statistically dissect dependencies between chromatin factors and produce an accurate probability distribution of chromatin code. Our unsupervised quantitative model, trained on genome-wide chromatin profiles of 73 histone marks and chromatin proteins from modENCODE, enabled making various data-driven inferences about chromatin profiles and interactions. We provided a highly accurate predictor of chromatin factor pairwise interactions validated by known experimental evidence, and for the first time enabled higher-order interaction prediction. Our predictions can thus help guide future experimental studies. The model can also serve as an inference engine for predicting unknown chromatin profiles — we demonstrated that with this approach we can leverage data from well-characterized cell types to help understand less-studied cell type or conditions. PMID:24675896

  12. A Proteomic Strategy Identifies Lysine Methylation of Splicing Factor snRNP70 by the SETMAR Enzyme*

    Science.gov (United States)

    Carlson, Scott M.; Moore, Kaitlyn E.; Sankaran, Saumya M.; Reynoird, Nicolas; Elias, Joshua E.; Gozani, Or

    2015-01-01

    The lysine methyltransferase (KMT) SETMAR is implicated in the response to and repair of DNA damage, but its molecular function is not clear. SETMAR has been associated with dimethylation of histone H3 lysine 36 (H3K36) at sites of DNA damage. However, SETMAR does not methylate H3K36 in vitro. This and the observation that SETMAR is not active on nucleosomes suggest that H3K36 methylation is not a physiologically relevant activity. To identify potential non-histone substrates, we utilized a strategy on the basis of quantitative proteomic analysis of methylated lysine. Our approach identified lysine 130 of the mRNA splicing factor snRNP70 as a SETMAR substrate in vitro, and we show that the enzyme primarily generates monomethylation at this position. Furthermore, we show that SETMAR methylates snRNP70 Lys-130 in cells. Because snRNP70 is a key early regulator of 5′ splice site selection, our results suggest a model in which methylation of snRNP70 by SETMAR regulates constitutive and/or alternative splicing. In addition, the proteomic strategy described here is broadly applicable and is a promising route for large-scale mapping of KMT substrates. PMID:25795785

  13. Identifying factors affecting the safety of mid-block bicycle lanes considering mixed 2-wheeled traffic flow.

    Science.gov (United States)

    Bai, Lu; Chan, Ching-Yao; Liu, Pan; Xu, Chengcheng

    2017-10-03

    Electric bikes (e-bikes) have been one of the fastest growing trip modes in Southeast Asia over the past 2 decades. The increasing popularity of e-bikes raised some safety concerns regarding urban transport systems. The primary objective of this study was to identify whether and how the generalized linear regression model (GLM) could be used to relate cyclists' safety with various contributing factors when riding in a mid-block bike lane. The types of 2-wheeled vehicles in the study included bicycle-style electric bicycles (BSEBs), scooter-style electric bicycles (SSEBs), and regular bicycles (RBs). Traffic conflict technology was applied as a surrogate measure to evaluate the safety of 2-wheeled vehicles. The safety performance model was developed by adopting a generalized linear regression model for relating the frequency of rear-end conflicts between e-bikes and regular bikes to the operating speeds of BSEBs, SSEBs, and RBs in mid-block bike lanes. The frequency of rear-end conflicts between e-bikes and bikes increased with an increase in the operating speeds of e-bikes and the volume of e-bikes and bikes and decreased with an increase in the width of bike lanes. The large speed difference between e-bikes and bikes increased the frequency of rear-end conflicts between e-bikes and bikes in mid-block bike lanes. A 1% increase in the average operating speed of e-bikes would increase the expected number of rear-end conflicts between e-bikes and bikes by 1.48%. A 1% increase in the speed difference between e-bikes and bikes would increase the expected number of rear-end conflicts between e-bikes/bikes by 0.16%. The conflict frequency in mid-block bike lanes can be modeled using generalized linear regression models. The factors that significantly affected the frequency of rear-end conflicts included the operating speeds of e-bikes, the speed difference between e-bikes and regular bikes, the volume of e-bikes, the volume of bikes, and the width of bike lanes. The

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

    DEFF Research Database (Denmark)

    Lo, Simon M.S.; Wilke, Ralf

    2017-01-01

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

  15. 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

  16. Transcriptome analysis of Neisseria meningitidis in human whole blood and mutagenesis studies identify virulence factors involved in blood survival.

    Directory of Open Access Journals (Sweden)

    Hebert Echenique-Rivera

    2011-05-01

    Full Text Available During infection Neisseria meningitidis (Nm encounters multiple environments within the host, which makes rapid adaptation a crucial factor for meningococcal survival. Despite the importance of invasion into the bloodstream in the meningococcal disease process, little is known about how Nm adapts to permit survival and growth in blood. To address this, we performed a time-course transcriptome analysis using an ex vivo model of human whole blood infection. We observed that Nm alters the expression of ≈30% of ORFs of the genome and major dynamic changes were observed in the expression of transcriptional regulators, transport and binding proteins, energy metabolism, and surface-exposed virulence factors. In particular, we found that the gene encoding the regulator Fur, as well as all genes encoding iron uptake systems, were significantly up-regulated. Analysis of regulated genes encoding for surface-exposed proteins involved in Nm pathogenesis allowed us to better understand mechanisms used to circumvent host defenses. During blood infection, Nm activates genes encoding for the factor H binding proteins, fHbp and NspA, genes encoding for detoxifying enzymes such as SodC, Kat and AniA, as well as several less characterized surface-exposed proteins that might have a role in blood survival. Through mutagenesis studies of a subset of up-regulated genes we were able to identify new proteins important for survival in human blood and also to identify additional roles of previously known virulence factors in aiding survival in blood. Nm mutant strains lacking the genes encoding the hypothetical protein NMB1483 and the surface-exposed proteins NalP, Mip and NspA, the Fur regulator, the transferrin binding protein TbpB, and the L-lactate permease LctP were sensitive to killing by human blood. This increased knowledge of how Nm responds to adaptation in blood could also be helpful to develop diagnostic and therapeutic strategies to control the devastating

  17. A modified reverse one-hybrid screen identifies transcriptional activation in Phyochrome-Interacting Factor 3

    Science.gov (United States)

    Transcriptional activation domains (TAD) are difficult to predict and identify, since they are not conserved and have little consensus. Here, we describe a yeast-based screening method that is able to identify individual amino acid residues involved in transcriptional activation in a high throughput...

  18. Hepatocyte Nuclear Factor 4α (HNF4α) Is a Transcription Factor of Vertebrate Fatty Acyl Desaturase Gene as Identified in Marine Teleost Siganus canaliculatus.

    Science.gov (United States)

    Dong, Yewei; Wang, Shuqi; Chen, Junliang; Zhang, Qinghao; Liu, Yang; You, Cuihong; Monroig, Óscar; Tocher, Douglas R; Li, Yuanyou

    2016-01-01

    Rabbitfish Siganus canaliculatus was the first marine teleost demonstrated to have the capability of biosynthesizing long-chain polyunsaturated fatty acids (LC-PUFA) from C18 precursors, and to possess a Δ4 fatty acyl desaturase (Δ4 Fad) which was the first report in vertebrates, and is a good model for studying the regulatory mechanisms of LC-PUFA biosynthesis in teleosts. In order to understand regulatory mechanisms of transcription of Δ4 Fad, the gene promoter was cloned and characterized in the present study. An upstream sequence of 1859 bp from the initiation codon ATG was cloned as the promoter candidate. On the basis of bioinformatic analysis, several binding sites of transcription factors (TF) including GATA binding protein 2 (GATA-2), CCAAT enhancer binding protein (C/EBP), nuclear factor 1 (NF-1), nuclear factor Y (NF-Y), hepatocyte nuclear factor 4α (HNF4α) and sterol regulatory element (SRE), were identified in the promoter by site-directed mutation and functional assays. HNF4α and NF-1 were confirmed to interact with the core promoter of Δ4 Fad by gel shift assay and mass spectrometry. Moreover, over-expression of HNF4α increased promoter activity in HEK 293T cells and mRNA level of Δ4 Fad in rabbitfish primary hepatocytes, respectively. The results indicated that HNF4α is a TF of rabbitfish Δ4 Fad. To our knowledge, this is the first report on promoter structure of a Δ4 Fad, and also the first demonstration of HNF4α as a TF of vertebrate Fad gene involved in transcription regulation of LC-PUFA biosynthesis.

  19. Identifying Contextual Factors of Employee Satisfaction of Performance Management at a Thai State Enterprise

    Directory of Open Access Journals (Sweden)

    Molraudee Saratun

    2013-10-01

    Full Text Available Although there has been an increase in Performance Management (PM literature over the years arguing that PM perceptions are likely to be a function of PM process components and contextual factors, the actual relationship between the contextual factors and employee satisfaction of PM remains little explored. Extending previous research, this study examines relationships between contextual factors and employees’ PM satisfaction. Derived from the literature, these contextual factors are motivation and empowerment of employees, role conflict, role ambiguity, perceived or- ganisational support, procedural justice and distributive justice. Seven directional hypotheses are tested accordingly through a series of regression analyses. This article finds that these contextual factors, with the exception of role conflict, are directly predictive of enhanced employees’ PM satis- faction at the Thai state enterprise.

  20. Identifying the most critical project complexity factors using Delphi method: the Iranian construction industry

    Directory of Open Access Journals (Sweden)

    Mohammad Mehdi Mozaffari

    2012-09-01

    Full Text Available Complexity is one of the most important issues influencing success of any construction project and there are literally different studies devoted to detect important factors increasing complexity of projects. During the past few years, there have been growing interests in developing mass construction projects in Iran. The proposed study of this paper uses Delphi technique to find out about important factors as barriers of construction projects in Iran. The results show that among 47 project complexity factors, 19 factors are more important than others are. The study groups different factors into seven categories including environmental, organizational, objectives, tasks, stakeholders, technological, information systems and determines the relative importance of each. In each group, many other sub group activities are determined and they are carefully investigated. The study provides some detailed suggestions on each category to reduce the complexity of construction project.

  1. An empirical study on identifying critical success factors on chaos management

    Directory of Open Access Journals (Sweden)

    Naser Azad

    2012-08-01

    Full Text Available Chaos management is one of the most necessary efforts on managing business units. Many organizations fail to cope with undesirable circumstances, which may happen without any prior notice and as a result, they may face with significant financial losses. In this paper, we present an empirical study to determine critical success factors, which could help handle any possible chaos in organizations. The proposed study of this paper is implemented for a set of travel agencies located in Tehran, Iran. Chronbach alpha is calculated as 0.821, which is well above the minimum desirable level. In addition, we have also performed factor analysis, which yields a KMO value of 0.576 with the level of significance of 0.000. The results indicate that there are six important factors including effective management strategy, internal environmental factors, creative and innovative attitudes, external environmental factors and top level management thoughts.

  2. Connections between Graphical Gaussian Models and Factor Analysis

    Science.gov (United States)

    Salgueiro, M. Fatima; Smith, Peter W. F.; McDonald, John W.

    2010-01-01

    Connections between graphical Gaussian models and classical single-factor models are obtained by parameterizing the single-factor model as a graphical Gaussian model. Models are represented by independence graphs, and associations between each manifest variable and the latent factor are measured by factor partial correlations. Power calculations…

  3. Modelling non-normal data: The relationship between the skew-normal factor model and the quadratic factor model.

    Science.gov (United States)

    Smits, Iris A M; Timmerman, Marieke E; Stegeman, Alwin

    2016-05-01

    Maximum likelihood estimation of the linear factor model for continuous items assumes normally distributed item scores. We consider deviations from normality by means of a skew-normally distributed factor model or a quadratic factor model. We show that the item distributions under a skew-normal factor are equivalent to those under a quadratic model up to third-order moments. The reverse only holds if the quadratic loadings are equal to each other and within certain bounds. We illustrate that observed data which follow any skew-normal factor model can be so well approximated with the quadratic factor model that the models are empirically indistinguishable, and that the reverse does not hold in general. The choice between the two models to account for deviations of normality is illustrated by an empirical example from clinical psychology. © 2015 The British Psychological Society.

  4. A preclinical model for identifying rats at risk of alcohol use disorder

    KAUST Repository

    Jadhav, Kshitij S.

    2017-08-21

    Alcohol use is one of the world\\'s leading causes of death and disease, although only a small proportion of individuals develop persistent alcohol use disorder (AUD). The identification of vulnerable individuals prior to their chronic intoxication remains of highest importance. We propose here to adapt current methodologies for identifying rats at risk of losing control over alcohol intake by modeling diagnostic criteria for AUD: Inability to abstain during a signaled period of reward unavailability, increased motivation assessed in a progressive effortful task and persistent alcohol intake despite aversive foot shocks. Factor analysis showed that these three addiction criteria loaded on one underlying construct indicating that they represent a latent construct of addiction trait. Further, not only vulnerable rats displayed higher ethanol consumption, and higher preference for ethanol over sweetened solutions, but they also exhibited pre-existing higher anxiety as compared to resilient rats. In conclusion, the present preclinical model confirms that development of an addiction trait not only requires prolonged exposure to alcohol, but also depends on endophenotype like anxiety that predispose a minority of individuals to lose control over alcohol consumption.

  5. Hybrid models identified a 12-gene signature for lung cancer prognosis and chemoresponse prediction.

    Directory of Open Access Journals (Sweden)

    Ying-Wooi Wan

    Full Text Available Lung cancer remains the leading cause of cancer-related deaths worldwide. The recurrence rate ranges from 35-50% among early stage non-small cell lung cancer patients. To date, there is no fully-validated and clinically applied prognostic gene signature for personalized treatment.From genome-wide mRNA expression profiles generated on 256 lung adenocarcinoma patients, a 12-gene signature was identified using combinatorial gene selection methods, and a risk score algorithm was developed with Naïve Bayes. The 12-gene model generates significant patient stratification in the training cohort HLM & UM (n = 256; log-rank P = 6.96e-7 and two independent validation sets, MSK (n = 104; log-rank P = 9.88e-4 and DFCI (n = 82; log-rank P = 2.57e-4, using Kaplan-Meier analyses. This gene signature also stratifies stage I and IB lung adenocarcinoma patients into two distinct survival groups (log-rank P<0.04. The 12-gene risk score is more significant (hazard ratio = 4.19, 95% CI: [2.08, 8.46] than other commonly used clinical factors except tumor stage (III vs. I in multivariate Cox analyses. The 12-gene model is more accurate than previously published lung cancer gene signatures on the same datasets. Furthermore, this signature accurately predicts chemoresistance/chemosensitivity to Cisplatin, Carboplatin, Paclitaxel, Etoposide, Erlotinib, and Gefitinib in NCI-60 cancer cell lines (P<0.017. The identified 12 genes exhibit curated interactions with major lung cancer signaling hallmarks in functional pathway analysis. The expression patterns of the signature genes have been confirmed in RT-PCR analyses of independent tumor samples.The results demonstrate the clinical utility of the identified gene signature in prognostic categorization. With this 12-gene risk score algorithm, early stage patients at high risk for tumor recurrence could be identified for adjuvant chemotherapy; whereas stage I and II patients at low risk could be spared the toxic side effects of

  6. DIAGNOSIS-GUIDED METHOD FOR IDENTIFYING MULTI-MODALITY NEUROIMAGING BIOMARKERS ASSOCIATED WITH GENETIC RISK FACTORS IN ALZHEIMER'S DISEASE.

    Science.gov (United States)

    Hao, Xiaoke; Yan, Jingwen; Yao, Xiaohui; Risacher, Shannon L; Saykin, Andrew J; Zhang, Daoqiang; Shen, Li

    2016-01-01

    Many recent imaging genetic studies focus on detecting the associations between genetic markers such as single nucleotide polymorphisms (SNPs) and quantitative traits (QTs). Although there exist a large number of generalized multivariate regression analysis methods, few of them have used diagnosis information in subjects to enhance the analysis performance. In addition, few of models have investigated the identification of multi-modality phenotypic patterns associated with interesting genotype groups in traditional methods. To reveal disease-relevant imaging genetic associations, we propose a novel diagnosis-guided multi-modality (DGMM) framework to discover multi-modality imaging QTs that are associated with both Alzheimer's disease (AD) and its top genetic risk factor (i.e., APOE SNP rs429358). The strength of our proposed method is that it explicitly models the priori diagnosis information among subjects in the objective function for selecting the disease-relevant and robust multi-modality QTs associated with the SNP. We evaluate our method on two modalities of imaging phenotypes, i.e., those extracted from structural magnetic resonance imaging (MRI) data and fluorodeoxyglucose positron emission tomography (FDG-PET) data in the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The experimental results demonstrate that our proposed method not only achieves better performances under the metrics of root mean squared error and correlation coefficient but also can identify common informative regions of interests (ROIs) across multiple modalities to guide the disease-induced biological interpretation, compared with other reference methods.

  7. Using Survival Analysis to Identify Risk Factors for Treatment Interruption among New and Retreatment Tuberculosis Patients in Kenya.

    Science.gov (United States)

    Masini, Enos O; Mansour, Omar; Speer, Clare E; Addona, Vittorio; Hanson, Christy L; Sitienei, Joseph K; Kipruto, Hillary K; Githiomi, Martin Muhingo; Mungai, Brenda Nyambura

    2016-01-01

    Despite high tuberculosis (TB) treatment success rate, treatment adherence is one of the major obstacles to tuberculosis control in Kenya. Our objective was to identify patient-related factors that were associated with time to TB treatment interruption and the geographic distribution of the risk of treatment interruption by county. Data of new and retreatment patients registered in TIBU, a Kenyan national case-based electronic data recording system, between 2013 and 2014 was obtained. Kaplan-Meier curves and log rank tests were used to assess the adherence patterns. Mixed-effects Cox proportional hazards modeling was used for multivariate analysis. Records from 90,170 patients were included in the study. The cumulative incidence of treatment interruption was 4.5% for new patients, and 8.5% for retreatment patients. The risk of treatment interruption was highest during the intensive phase of treatment. Having previously been lost to follow-up was the greatest independent risk factor for treatment interruption (HR: 4.79 [3.99, 5.75]), followed by being HIV-positive not on ART (HR: 1.96 [1.70, 2.26]) and TB relapse (HR: 1.70 [1.44, 2.00]). Male and underweight patients had high risks of treatment interruption (HR: 1.46 [1.35, 1.58]; 1.11 [1.03, 1.20], respectively). High rates of treatment interruption were observed in counties in the central part of Kenya while counties in the northeast had the lowest risk of treatment interruption. A better understanding of treatment interruption risk factors is necessary to improve adherence to treatment. Interventions should focus on patients during the intensive phase, patients who have previously been lost to follow-up, and promotion of integrated TB and HIV services among public and private facilities.

  8. Identifying E-Business Model:A Value Chain-Based Analysis

    Institute of Scientific and Technical Information of China (English)

    ZENG Qingfeng; HUANG Lihua

    2004-01-01

    E-business will change the ways that all companies do business, and most traditional businesses will evolve from their current business model to a combination of place and space via e-business model To choose the proper e-business model becomes the important strategic concern for company to succeed The main objective of this paper is to investigate the analysis framework for identifying e-business model Based on the e-business process, from the value chain to the value net perspective. This paper provides a theoretical framework for identifying e-business models, and results in 11 e-business models. The strategic intend of every e-business model is discussed in the end of this paper. An enterprise e-business model design and implementation can be specified by the combination of one or more among 11 e-business models.

  9. Identifying and Ranking the Effective Factors on City Brand Determination (Tehran

    Directory of Open Access Journals (Sweden)

    Sahar Mohammadi Bazargani

    2014-03-01

    Full Text Available This study obtains the probable information by analyzing data pertaining to the sample and finally attributes this information to the main universe. To gather theoretical basic principles related to the subject and to investigate research background, library method has been applied. This paper has used multi-stage cluster sampling method. With regard to the significance level of less than 0.05 for all factors, Chi-square test approved the significant relation of all factors by 95% confidence. Spearman correlation coefficient test revealed that correlation coefficients of this paper factors (environmental, economic, social cultural, historical, infrastructural, political with Tehran branding are 0.429, 0.555, 0.431, 0.462, 0.611, 0.643, respectively. Friedman ranking test ranked factors effective on Tehran branding as environmental, historical, infrastructural, economic, political, social-cultural, respectively.

  10. Identifying context factors explaining physician's low performance in communication assessment: an explorative study in general practice.

    NARCIS (Netherlands)

    Essers, G.T.J.M.; Dulmen, S. van; Weel, C. van; Vleuten, C.P.M. van der; Kramer, A.W.

    2011-01-01

    ABSTRACT: BACKGROUND: Communication is a key competence for health care professionals. Analysis of registrar and GP communication performance in daily practice, however, suggests a suboptimal application of communication skills. The influence of context factors could reveal why communication perform

  11. Are Fit Indices Biased in Favor of Bi-Factor Models in Cognitive Ability Research?: A Comparison of Fit in Correlated Factors, Higher-Order, and Bi-Factor Models via Monte Carlo Simulations

    Directory of Open Access Journals (Sweden)

    Grant B. Morgan

    2015-02-01

    Full Text Available Bi-factor confirmatory factor models have been influential in research on cognitive abilities because they often better fit the data than correlated factors and higher-order models. They also instantiate a perspective that differs from that offered by other models. Motivated by previous work that hypothesized an inherent statistical bias of fit indices favoring the bi-factor model, we compared the fit of correlated factors, higher-order, and bi-factor models via Monte Carlo methods. When data were sampled from a true bi-factor structure, each of the approximate fit indices was more likely than not to identify the bi-factor solution as the best fitting. When samples were selected from a true multiple correlated factors structure, approximate fit indices were more likely overall to identify the correlated factors solution as the best fitting. In contrast, when samples were generated from a true higher-order structure, approximate fit indices tended to identify the bi-factor solution as best fitting. There was extensive overlap of fit values across the models regardless of true structure. Although one model may fit a given dataset best relative to the other models, each of the models tended to fit the data well in absolute terms. Given this variability, models must also be judged on substantive and conceptual grounds.

  12. Scale Factor Self-Dual Cosmological Models

    CERN Document Server

    dS, U Camara; Sotkov, G M

    2015-01-01

    We implement a conformal time scale factor duality for Friedmann-Robertson-Walker cosmological models, which is consistent with the weak energy condition. The requirement for self-duality determines the equations of state for a broad class of barotropic fluids. We study the example of a universe filled with two interacting fluids, presenting an accelerated and a decelerated period, with manifest UV/IR duality. The associated self-dual scalar field interaction turns out to coincide with the "radiation-like" modified Chaplygin gas models. We present an equivalent realization of them as gauged K\\"ahler sigma models (minimally coupled to gravity) with very specific and interrelated K\\"ahler- and super-potentials. Their applications in the description of hilltop inflation and also as quintessence models for the late universe are discussed.

  13. Modeling Relational Data via Latent Factor Blockmodel

    CERN Document Server

    Gao, Sheng; Gallinari, Patrick

    2012-01-01

    In this paper we address the problem of modeling relational data, which appear in many applications such as social network analysis, recommender systems and bioinformatics. Previous studies either consider latent feature based models but disregarding local structure in the network, or focus exclusively on capturing local structure of objects based on latent blockmodels without coupling with latent characteristics of objects. To combine the benefits of the previous work, we propose a novel model that can simultaneously incorporate the effect of latent features and covariates if any, as well as the effect of latent structure that may exist in the data. To achieve this, we model the relation graph as a function of both latent feature factors and latent cluster memberships of objects to collectively discover globally predictive intrinsic properties of objects and capture latent block structure in the network to improve prediction performance. We also develop an optimization transfer algorithm based on the general...

  14. Human Factors Engineering Program Review Model

    Science.gov (United States)

    2004-02-01

    AA NUREG -0711,Rev. 2 Human Factors Engineering Program Review Model 20081009191 I i m To] Bi U.S. Nuclear Regulatory Commission Office of...Material As of November 1999, you may electronically access NUREG -series publications and other NRC records at NRC’s Public Electronic Reading Room at...http://www.nrc.qov/readinq-rm.html. Publicly released records include, to name a few, NUREG -series publications; Federal Register notices; applicant

  15. Identifying the Best-Fitting Factor Structure of the Experience of Close Relations - Revised in a Scandinavian Example.

    Directory of Open Access Journals (Sweden)

    Barbara Hoff Esbjørn

    Full Text Available The aim of this study was to enhance the understanding of cultural and sample differences in the assessment of attachment by examining the factor structure of the Experiences in Close Relationships-Revised (ECR-R. The ECR-R is a self-report measure of adult romantic attachment dimensions. The present study used a Danish sample with the purpose of addressing limitations in previous studies, such as the lack of diversity in cultural background, restricted sample characteristics, and poorly fitting structure models. Participants consisted of 253 parents of children between the ages of 7 and 12 years, 53% being mothers. The parents completed the paper version of the questionnaire. Confirmatory Factor Analyses were carried out to determine whether theoretically and empirically established models including one and two factors would also provide adequate fits in a Danish sample. A previous study using the original ECR suggested that Scandinavian samples may best be described using a five-factor solution. Our results indicated that the one- and two-factor models of the ECR-R did not fit the data well. Exploratory Factor Analysis revealed a five-factor model. Our study provides evidence that further investigation is needed to establish which model may provide the best model fit in the Scandinavian countries.

  16. Local identifiability for two and three-compartment pharmacokinetic models with time-lags.

    Science.gov (United States)

    Merino, J A; De Biasi, J; Plusquellec, Y; Houin, G

    1998-06-01

    In this paper, we show that time-lags between compartments in a 2 and 3 compartment pharmacokinetic model may be taken into account but that separate identification for model parameters and for time-lags would not be suitable. Furthermore, it may happen that a time-lag model is locally identifiable while the corresponding model without delay is not. For two-compartment delayed models, with only one observation, it is not necessary to have two different inputs contrary to the case without time-lag. Both the Laplace transformation and a Jacobian matrix are used in an identifiability study. For all two-compartment models we have investigated which kind of parameters or lags are identifiable from amount (Q) or concentration (C) measures.

  17. Family history of venous thromboembolism and identifying factor V Leiden carriers during pregnancy.

    Science.gov (United States)

    Horton, Amanda L; Momirova, Valerija; Dizon-Townson, Donna; Wenstrom, Katharine; Wendel, George; Samuels, Philip; Sibai, Baha; Spong, Catherine Y; Cotroneo, Margaret; Sorokin, Yoram; Miodovnik, Menachem; O'Sullivan, Mary J; Conway, Deborah; Wapner, Ronald J

    2010-03-01

    To estimate whether there is a correlation between family history of venous thromboembolism and factor V Leiden mutation carriage in gravid women without a personal history of venous thromboembolism. This is a secondary analysis of a prospective observational study of the frequency of pregnancy-related thromboembolic events among carriers of the factor V Leiden mutation. Family history of venous thromboembolism in either first- or second-degree relatives was self-reported. Sensitivity, specificity, and positive and negative predictive values of family history to predict factor V Leiden mutation carrier status were calculated. Women without a personal venous thromboembolism history and with available DNA were included (n=5,168). One hundred forty women (2.7% [95% confidence interval (CI) 2.3-3.2%]) were factor V Leiden mutation-positive. Four hundred twelve women (8.0% [95% CI 7.3-8.7%]) reported a family history of venous thromboembolism. Women with a positive family history were twofold more likely to be factor V Leiden mutation carriers than those with a negative family history (23 of 412 [5.6%] compared with 117 of 4,756 [2.5%], Pfactor V Leiden carriers were 16.4% (95% CI 10.7-23.6%), 92.3% (95% CI 91.5-93.0%), and 5.6% (95% CI 3.6-8.3%), respectively. Although a family history of venous thromboembolism is associated with factor V Leiden mutation in thrombosis-free gravid women, the sensitivity and positive predictive values are too low to recommend screening women for the factor V Leiden mutation based solely on a family history.

  18. A general model-based design of experiments approach to achieve practical identifiability of pharmacokinetic and pharmacodynamic models.

    Science.gov (United States)

    Galvanin, Federico; Ballan, Carlo C; Barolo, Massimiliano; Bezzo, Fabrizio

    2013-08-01

    The use of pharmacokinetic (PK) and pharmacodynamic (PD) models is a common and widespread practice in the preliminary stages of drug development. However, PK-PD models may be affected by structural identifiability issues intrinsically related to their mathematical formulation. A preliminary structural identifiability analysis is usually carried out to check if the set of model parameters can be uniquely determined from experimental observations under the ideal assumptions of noise-free data and no model uncertainty. However, even for structurally identifiable models, real-life experimental conditions and model uncertainty may strongly affect the practical possibility to estimate the model parameters in a statistically sound way. A systematic procedure coupling the numerical assessment of structural identifiability with advanced model-based design of experiments formulations is presented in this paper. The objective is to propose a general approach to design experiments in an optimal way, detecting a proper set of experimental settings that ensure the practical identifiability of PK-PD models. Two simulated case studies based on in vitro bacterial growth and killing models are presented to demonstrate the applicability and generality of the methodology to tackle model identifiability issues effectively, through the design of feasible and highly informative experiments.

  19. Identifying risk factors for clinically significant diabetic macula edema in patients with type 2 diabetes mellitus.

    Science.gov (United States)

    Kamoi, Kyuzi; Takeda, Keiji; Hashimoto, Kaoru; Tanaka, Reiko; Okuyama, Shinya

    2013-05-01

    It is known that clinic blood pressure (BP), gender, cigarette smoking, dyslipidemia, anemia and thiazolidenediones (TZD) treatment are predictors for clinically significant diabetic macula edema (CSDME). We examined a most risky factor for CSDME in Japanese patients with type 2 diabetes mellitus (T2DM) and diabetic retinopathy (DR) confirmed using optical coherence tomography by multiple regression analysis (MRA). As the risk factors, wakening-up BP was added to such factors. Seven diabetic Japanese patients with CSDME (group 1) and 124 subjects without CSDME (group 2) assonated with DR using optical coherence tomography were studied. The durations of T2DM in groups 1 and 2 were 15±10 years and 20±15 years, respectively. There was no statistically difference in means of gender, duration, age, body mass index (BMI), HbA1c, TC, LDL and TC/HDL, serum creatinine, urinary albumin excretion rate, and clinic BP between two groups. Morning systolic home BP (MSHBP), cigarette smoking and foveal thickness were significantly (ppioglitazone as TZD treatment were significantly positive predictors for CSDME, while BMI had a significantly negative predictor. Other variables were not significantly correlated to CSDME. The review summarizes a multiple regression analysis revealed that MSHBP makes an addition to predictive factors for CSDME among risk factors reported previously in patient with T2DM.

  20. Risk factor screening to identify women requiring oral glucose tolerance testing to diagnose gestational diabetes: A systematic review and meta-analysis and analysis of two pregnancy cohorts.

    Science.gov (United States)

    Farrar, Diane; Simmonds, Mark; Bryant, Maria; Lawlor, Debbie A; Dunne, Fidelma; Tuffnell, Derek; Sheldon, Trevor A

    2017-01-01

    Easily identifiable risk factors including: obesity and ethnicity at high risk of diabetes are commonly used to indicate which women should be offered the oral glucose tolerance test (OGTT) to diagnose gestational diabetes (GDM). Evidence regarding these risk factors is limited however. We conducted a systematic review (SR) and meta-analysis and individual participant data (IPD) analysis to evaluate the performance of risk factors in identifying women with GDM. We searched MEDLINE, Medline in Process, Embase, Maternity and Infant Care and the Cochrane Central Register of Controlled Trials (CENTRAL) up to August 2016 and conducted additional reference checking. We included observational, cohort, case-control and cross-sectional studies reporting the performance characteristics of risk factors used to identify women at high risk of GDM. We had access to IPD from the Born in Bradford and Atlantic Diabetes in Pregnancy cohorts, all pregnant women in the two cohorts with data on risk factors and OGTT results were included. Twenty nine published studies with 211,698 women for the SR and a further 14,103 women from two birth cohorts (Born in Bradford and the Atlantic Diabetes in Pregnancy study) for the IPD analysis were included. Six studies assessed the screening performance of guidelines; six examined combinations of risk factors; eight evaluated the number of risk factors and nine examined prediction models or scores. Meta-analysis using data from published studies suggests that irrespective of the method used, risk factors do not identify women with GDM well. Using IPD and combining risk factors to produce the highest sensitivities, results in low specificities (and so higher false positives). Strategies that use the risk factors of age (>25 or >30) and BMI (>25 or 30) perform as well as other strategies with additional risk factors included. Risk factor screening methods are poor predictors of which pregnant women will be diagnosed with GDM. A simple approach of

  1. Clinical prediction model to identify vulnerable patients in ambulatory surgery: towards optimal medical decision-making

    NARCIS (Netherlands)

    H. Mijderwijk (Herjan); R.J. Stolker (Robert); H.J. Duivenvoorden (Hugo); M. Klimek (Markus); E.W. Steyerberg (Ewout)

    2016-01-01

    markdownabstract__Background:__ Ambulatory surgery patients are at risk of adverse psychological outcomes such as anxiety, aggression, fatigue, and depression. We developed and validated a clinical prediction model to identify patients who were vulnerable to these psychological outcome parameters.

  2. Identifying and prioritizing industry-level competitiveness factors: evidence from pharmaceutical market.

    Science.gov (United States)

    Shabaninejad, Hosein; Mehralian, Gholamhossein; Rashidian, Arash; Baratimarnani, Ahmad; Rasekh, Hamid Reza

    2014-04-03

    Pharmaceutical industry is knowledge-intensive and highly globalized, in both developed and developing countries. On the other hand, if companies want to survive, they should be able to compete well in both domestic and international markets. The main purpose of this paper is therefore to develop and prioritize key factors affecting companies' competitiveness in pharmaceutical industry. Based on an extensive literature review, a valid and reliable questionnaire was designed, which was later filled up by participants from the industry. To prioritize the key factors, we used the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The results revealed that human capital and macro-level policies were two key factors placed at the highest rank in respect of their effects on the competitiveness considering the industry-level in pharmaceutical area. This study provides fundamental evidence for policymakers and managers in pharma context to enable them formulating better polices to be proactively competitive and responsive to the markets' needs.

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

    DEFF Research Database (Denmark)

    Ottosen, Thor Bjørn; Ketzel, Matthias; Skov, Henrik

    2016-01-01

    Pollution Model (OSPM®). To assess the predictive validity of the model, the data is split into an estimation and a prediction data set using two data splitting approaches and data preparation techniques (clustering and outlier detection) are analysed. The sensitivity analysis, being part......Mathematical models are increasingly used in environmental science thus increasing the importance of uncertainty and sensitivity analyses. In the present study, an iterative parameter estimation and identifiability analysis methodology is applied to an atmospheric model – the Operational Street...

  4. A New Method for Identifying the Model Error of Adjustment System

    Institute of Scientific and Technical Information of China (English)

    TAO Benzao; ZHANG Chaoyu

    2005-01-01

    Some theory problems affecting parameter estimation are discussed in this paper. Influence and transformation between errors of stochastic and functional models is pointed out as well. For choosing the best adjustment model, a formula, which is different from the literatures existing methods, for estimating and identifying the model error, is proposed. On the basis of the proposed formula, an effective approach of selecting the best model of adjustment system is given.

  5. Identifying the effective factors on customer knowledge management development: Evidence from customs industry

    Directory of Open Access Journals (Sweden)

    Saeedeh Arazpoor

    2016-01-01

    Full Text Available This paper examines the effect of different factors on customer knowledge management development for a custom organization in Bandar Abbas, Iran. The statistical population of this research includes all 440 managers and employees in different levels where 205 people are randomly selected for this survey. Using t-student as well as Friedman tests, the study has confirmed that organizational culture, training, strategy, information and organizational infrastructure, top management commitment, organizational conflict, standardization, employee performance, communication, budget support and necessary skills could influence positively on knowledge management development. In our survey, training is also believed to be the most influential factor.

  6. Applying psychological theories to evidence-based clinical practice: identifying factors predictive of placing preventive fissure sealants

    Directory of Open Access Journals (Sweden)

    Maclennan Graeme

    2010-04-01

    identifying factors that may predict clinical behaviour and so provide possible targets for knowledge translation interventions. Results suggest that more evidence-based behaviour may be achieved by influencing beliefs about the positive outcomes of placing fissure sealants and building a habit of placing them as part of patient management. However a number of conceptual and methodological challenges remain.

  7. Applying psychological theories to evidence-based clinical practice: identifying factors predictive of placing preventive fissure sealants.

    Science.gov (United States)

    Bonetti, Debbie; Johnston, Marie; Clarkson, Jan E; Grimshaw, Jeremy; Pitts, Nigel B; Eccles, Martin; Steen, Nick; Thomas, Ruth; Maclennan, Graeme; Glidewell, Liz; Walker, Anne

    2010-04-08

    Psychological models are used to understand and predict behaviour in a wide range of settings, but have not been consistently applied to health professional behaviours, and the contribution of differing theories is not clear. This study explored the usefulness of a range of models to predict an evidence-based behaviour -- the placing of fissure sealants. Measures were collected by postal questionnaire from a random sample of general dental practitioners (GDPs) in Scotland. Outcomes were behavioural simulation (scenario decision-making), and behavioural intention. Predictor variables were from the Theory of Planned Behaviour (TPB), Social Cognitive Theory (SCT), Common Sense Self-regulation Model (CS-SRM), Operant Learning Theory (OLT), Implementation Intention (II), Stage Model, and knowledge (a non-theoretical construct). Multiple regression analysis was used to examine the predictive value of each theoretical model individually. Significant constructs from all theories were then entered into a 'cross theory' stepwise regression analysis to investigate their combined predictive value. Behavioural simulation - theory level variance explained was: TPB 31%; SCT 29%; II 7%; OLT 30%. Neither CS-SRM nor stage explained significant variance. In the cross theory analysis, habit (OLT), timeline acute (CS-SRM), and outcome expectancy (SCT) entered the equation, together explaining 38% of the variance. Behavioural intention - theory level variance explained was: TPB 30%; SCT 24%; OLT 58%, CS-SRM 27%. GDPs in the action stage had significantly higher intention to place fissure sealants. In the cross theory analysis, habit (OLT) and attitude (TPB) entered the equation, together explaining 68% of the variance in intention. The study provides evidence that psychological models can be useful in understanding and predicting clinical behaviour. Taking a theory-based approach enables the creation of a replicable methodology for identifying factors that may predict clinical behaviour

  8. Identifying psychological factors that determine cattle farmers' intention to use improved natural grassland

    NARCIS (Netherlands)

    Borges, J.A.R.; Oude Lansink, A.G.J.M.

    2016-01-01

    The biome Pampa, in Brazil, is under threat from expansion of agriculture and overgrazing. Although several sustainable livestock farming innovations are currently available to farmers in the region, adoption rate remains low. This paper uses the theory of planned behavior (TPB) to identify the

  9. Identifying the Factors Affecting Science and Mathematics Achievement Using Data Mining Methods

    Science.gov (United States)

    Kiray, S. Ahmet; Gok, Bilge; Bozkir, A. Selman

    2015-01-01

    The purpose of this article is to identify the order of significance of the variables that affect science and mathematics achievement in middle school students. For this aim, the study deals with the relationship between science and math in terms of different angles using the perspectives of multiple causes-single effect and of multiple…

  10. Digital Competence at the Beginning of Upper Secondary School: Identifying Factors Explaining Digital Inclusion

    Science.gov (United States)

    Hatlevik, Ove Edvard; Christophersen, Knut-Andreas

    2013-01-01

    During the last decade, information and communication technology has been given an increasingly large importance in our society. There seems to be a consensus regarding the necessity of supporting and developing school-based digital competence. In order to sustain digital inclusion, schools need to identify digital deficiencies and digital…

  11. Identifying the Factors Affecting Science and Mathematics Achievement Using Data Mining Methods

    Science.gov (United States)

    Kiray, S. Ahmet; Gok, Bilge; Bozkir, A. Selman

    2015-01-01

    The purpose of this article is to identify the order of significance of the variables that affect science and mathematics achievement in middle school students. For this aim, the study deals with the relationship between science and math in terms of different angles using the perspectives of multiple causes-single effect and of multiple…

  12. Identifying the Factors Leading to Success: How an Innovative Science Curriculum Cultivates Student Motivation

    Science.gov (United States)

    Scogin, Stephen C.

    2016-01-01

    "PlantingScience" is an award-winning program recognized for its innovation and use of computer-supported scientist mentoring. Science learners work on inquiry-based experiments in their classrooms and communicate asynchronously with practicing plant scientist-mentors about the projects. The purpose of this study was to identify specific…

  13. IDENTIFYING ELEVEN FACTORS OF SERVICE MARKETING MIX (4PS) EFFECTIVE ON TENDENCY OF PATIENTS TOWARD PRIVATE HOSPITAL

    OpenAIRE

    Hosseini, Seyed Mojtaba; Etesaminia, Samira; Jafari, Mehrnoosh

    2016-01-01

    Introduction: One of the important factors of correct management is to identify the reasons for patient tendency toward private hospitals. This study measures these factors based on service marketing mixes. Patients and methods: This study used a cross sectional descriptive methodology. The study was conducted during 6 months in 2015. The studied population included patients of private hospitals in Tehran. Random sampling was used (n = 200). Data was collected by an author-made questionnaire ...

  14. Identifying Factors That Affect Higher Educational Achievements of Jamaican Seventh-Day Adventists

    Science.gov (United States)

    Campbell, Samuel P.

    2011-01-01

    This mixed-method explanatory research examined factors that influenced Jamaican Seventh-day Adventist (SDA) members to pursue higher education. It sought to investigate whether the source of the motivation is tied to the Church's general philosophy on education or to its overall programs as experienced by the membership at large. The question of…

  15. Management of Highway Projects in Egypt through Identifying Factors Influencing Quality Performance

    Directory of Open Access Journals (Sweden)

    Ahmed Ebrahim Abu El-Maaty

    2016-01-01

    Full Text Available While project management success focuses upon the processes and the successful accomplishments of cost and time objectives, product success deals with the quality of the final product. Recently, quality of the constructed highway has been considered highly important reason for the pavement response and its design life. The main objective of this paper is to improve the management of highway projects in Egypt by determining the most important factors influencing the quality performance of this industry. In total, 39 factors that may influence the quality of highway projects have been defined through a detailed literature review. The factors are tabulated in a questionnaire form, which is sent out to 13 owners of divided highways, 27 owners of regional roads, and 15 consultants. The analysis of the respondents’ perspectives using fuzzy triangle approach shows that the most important factors affecting the quality are availability of experienced staff in the owner’s and contractor’s teams during the project execution; efficiency of the owner’s inspection team; clarity of responsibilities and roles for each owner, consultant, and contractor; pavement which is not designed according to the regional conditions (e.g., soil type, temperature, and traffic volume; and asphalt quality and type used in the construction process.

  16. Identifying Academic & Social Risk Factors of Baccalaureate Nursing Students Using the College Persistence Questionnaire

    Science.gov (United States)

    Betts, Kelly J.; Shirley, Janet A.; Kennedy, Robert

    2017-01-01

    Background: Student success in a baccalaureate nursing program is of utmost importance at a southern College of Nursing (CON).CON faculty wanted to understand better what academic/ social risk factors attributed to attrition in the first year of the nursing program. The purpose of this study was to determine academic and social risk factors…

  17. The CAREFALL Triage instrument identifying risk factors for recurrent falls in elderly patients

    NARCIS (Netherlands)

    Hensbroek, van P. Boele; Dijk, van N.; Breda, van G.F.; Scheffer, A.C.; Cammen, van der T.J.; Lips, P.T.A.M.; Goslings, J.C.; Rooij, S.E.

    2009-01-01

    OBJECTIVE: To validate the CAREFALL Triage Instrument (CTI), a self-administered questionnaire concerning modifiable risk factors for recurrent falls in elderly patients who experienced fall. METHODS: This study in patients 65 years or older who experienced fall was performed at the accident and eme

  18. Increased sexually transmitted infection incidence in a low risk population: identifying the risk factors.

    LENUS (Irish Health Repository)

    Shiely, Frances

    2010-04-01

    Between 1994 and 2006, the incidence of sexually transmitted infections (STIs) in Ireland has increased by over 300%. Recent literature would suggest that this figure is an underestimation of the true scale of infection. Our objective was to determine the risk factors associated with STI diagnosis in a population with a rapidly increasing STI incidence.

  19. Discrete Methods Based on First Order Reversal Curves to Identify Preisach Model of Smart Materials

    Institute of Scientific and Technical Information of China (English)

    LI Fan; ZHAO Jian-hui

    2007-01-01

    Preisach model is widely used in modeling of smart materials. Although first order reversal curves (FORCs) have often found applications in the fields of physics and geology, they are able to serve to identify Preisach model. In order to clarify the relationship between the Preisach model and the first order reversal curves, this paper is directed towards: (1) giving the reason a first order reversal curve is introduced; (2) presenting, for identifying Preisach model, two discrete methods, which are analytically based on first order reversal curves. Herein also is indicated the solution's uniqueness of these two identifying methods. At last, the validity of these two methods is verified by simulating a real smart actuator both methods have been applied to.

  20. Identifiable risk factors for thirty-day complications following arthroscopic rotator cuff repair.

    Science.gov (United States)

    Heyer, Jessica H; Kuang, Xiangyu; Amdur, Richard L; Pandarinath, Rajeev

    2017-10-11

    Shoulder arthroscopy has increased in frequency over the past decade, with rotator cuff repair comprising the majority of cases performed. Prior studies have detailed risk factors for 30-day complications and readmission rates after arthroscopic shoulder surgery using the National Surgical Quality Improvement Program (NSQIP) database, but no study has specifically looked at arthroscopic rotator cuff repair. The purpose of the study is to evaluate the risk factors for 30-day complications following arthroscopic rotator cuff repair using the NSQIP database. The NSQIP database was queried for all patients undergoing arthroscopic rotator cuff repair from 2006-2015. Demographics and thirty-day outcomes for these patients were analyzed using univariate analyses and multivariate regression analysis to determine the risk factors for complications. 21,143 patients underwent arthroscopic rotator cuff repair, with 147 patients (0.70%) having a complication within 30-days. Univariate analysis found age >65 (p = 0.0028), male gender (p = 0.0053), elevated BMI (p = 0.0054), ASA class >2 (p 90 min (p = 0.0316) to be associated with increased risk of complications. Multivariate analysis found female sex to be protective or complication (OR 0.56, p = 0.0017), while American Society of Anesthesiology (ASA) class >2 (OR 1.51, p = 0.0335) and history of COPD (OR 2.41, p = 0.0030) and dyspnea (OR 1.89, p = 0.0359) to be risk factors for complication. The most common complication is venothromboembolic events, accounting for 36.7% of all complications. Male sex, ASA class > 2, and history of COPD and dyspnea were independent risk factors for thirty-day complications following arthroscopic rotator cuff repair. IV.

  1. Identifying predictive factors for long-term complications following button battery impactions: A case series and literature review.

    Science.gov (United States)

    Eliason, Michael J; Melzer, Jonathan M; Winters, Jessica R; Gallagher, Thomas Q

    2016-08-01

    To complement a case series review of button battery impactions managed at our single military tertiary care center with a thorough literature review of laboratory research and clinical cases to develop a protocol to optimize patient care. Specifically, to identify predictive factors of long-term complications which can be used by the pediatric otolaryngologist to guide patient management after button battery impactions. A retrospective review of the Department of Defense's electronic medical record systems was conducted to identify patients with button battery ingestions and then characterize their treatment course. A thorough literature review complemented the lessons learned to identify potentially predictive clinical measures for long-term complications. Eight patients were identified as being treated for button battery impaction in the aerodigestive tract with two sustaining long-term complications. The median age of the patients treated was 33 months old and the median estimated time of impaction in the aerodigestive tract prior to removal was 10.5 h. Time of impaction, anatomic direction of the battery's negative pole, and identifying specific battery parameters were identified as factors that may be employed to predict sequelae. Based on case reviews, advancements in battery manufacturing, and laboratory research, there are distinct clinical factors that should be assessed at the time of initial therapy to guide follow-up management to minimize potential catastrophic sequelae of button battery ingestion. Published by Elsevier Ireland Ltd.

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

    Science.gov (United States)

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

    2015-04-01

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

  3. Integrated network modelling for identifying microbial mechanisms of particulate organic carbon accumulation in coastal marine systems

    Science.gov (United States)

    McDonald, Karlie; Turk, Valentina; Mozetič, Patricija; Tinta, Tinkara; Malfatti, Francesca; Hannah, David; Krause, Stefan

    2016-04-01

    Accumulation of particulate organic carbon (POC) has the potential to change the structure and function of marine ecosystems. High abidance of POC can develop into aggregates, known as marine snow or mucus aggregates that can impair essential marine ecosystem functioning and services. Currently marine POC formation, accumulation and sedimentation processes are being explored as potential pathways to remove CO2 from the atmosphere by CO2 sequestration via fixation into biomass by phytoplankton. However, the current ability of scientists, environmental managers and regulators to analyse and predict high POC concentrations is restricted by the limited understanding of the dynamic nature of the microbial mechanisms regulating POC accumulation events in marine environments. We present a proof of concept study that applies a novel Bayesian Networks (BN) approach to integrate relevant biological and physical-chemical variables across spatial and temporal scales in order to identify the interactions of the main contributing microbial mechanisms regulating POC accumulation in the northern Adriatic Sea. Where previous models have characterised only the POC formed, the BN approach provides a probabilistic framework for predicting the occurrence of POC accumulation by linking biotic factors with prevailing environmental conditions. In this paper the BN was used to test three scenarios (diatom, nanoflagellate, and dinoflagellate blooms). The scenarios predicted diatom blooms to produce high chlorophyll a at the water surface while nanoflagellate blooms were predicted to occur at lower depths (> 6m) in the water column and produce lower chlorophyll a concentrations. A sensitivity analysis identified the variables with the greatest influence on POC accumulation being the enzymes protease and alkaline phosphatase, which highlights the importance of microbial community interactions. The developed proof of concept BN model allows for the first time to quantify the impacts of

  4. Surface proteome analysis identifies platelet derived growth factor receptor-alpha as a critical mediator of transforming growth factor-beta-induced collagen secretion.

    Science.gov (United States)

    Heinzelmann, Katharina; Noskovičová, Nina; Merl-Pham, Juliane; Preissler, Gerhard; Winter, Hauke; Lindner, Michael; Hatz, Rudolf; Hauck, Stefanie M; Behr, Jürgen; Eickelberg, Oliver

    2016-05-01

    Fibroblasts are extracellular matrix-producing cells in the lung. Fibroblast activation by transforming growth factor-beta leads to myofibroblast-differentiation and increased extracellular matrix deposition, a hallmark of pulmonary fibrosis. While fibroblast function with respect to migration, invasion, and extracellular matrix deposition has been well-explored, little is known about the surface proteome of lung fibroblasts in general and its specific response to fibrogenic growth factors, in particular transforming growth factor-beta. We thus performed a cell-surface proteome analysis of primary human lung fibroblasts in presence/absence of transforming growth factor-beta, followed by characterization of our findings using FACS analysis, Western blot, and siRNA-mediated knockdown experiments. We identified 213 surface proteins significantly regulated by transforming growth factor-beta, platelet derived growth factor receptor-alpha being one of the top down-regulated proteins. Transforming growth factor beta-induced downregulation of platelet derived growth factor receptor-alpha induced upregulation of platelet derived growth factor receptor-beta expression and phosphorylation of Akt, a downstream target of platelet derived growth factor signaling. Importantly, collagen type V expression and secretion was strongly increased after forced knockdown of platelet derived growth factor receptor-alpha, an effect that was potentiated by transforming growth factor-beta. We therefore show previously underappreciated cross-talk of transforming growth factor-beta and platelet derived growth factor signaling in human lung fibroblasts, resulting in increased extracellular matrix deposition in a platelet derived growth factor receptor-alpha dependent manner. These findings are of particular importance for the treatment of lung fibrosis patients with high pulmonary transforming growth factor-beta activity.

  5. 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/.

  6. Does violence affect the use of contraception? Identifying the hidden factors from rural India

    Directory of Open Access Journals (Sweden)

    Nishikant Singh

    2017-01-01

    Full Text Available Purpose: The objective of this study is to investigates the relationship between domestic violence and use of contraception among married women in rural India. Data: Third round of National Family Health Survey (NFHS-III. Methodology: Cross tabulation as bivariate analysis and Binary Logistic Regression as multivariate analysis has been employed to fulfill the objective. Findings: The result shows that there are several hidden factors. between physical violence and contraception use. Alternate explanatory variables are significantly affected the use of contraception. With physical violence which reflects that there is a relationship between physical violence and socioeconomic status such as education, awareness, empowerment of women and subsequently the use of contraception. Originality/value: The paper throws light on the hidden factors which are obstacle in use of contraception with physical violence. Results of this study have potentially important implications for programs aimed at preventing violence and promoting family planning programs.

  7. Identifying Risk Factors for Late-Onset (50+) Alcohol Use Disorder and Heavy Drinking

    DEFF Research Database (Denmark)

    Emiliussen, Jakob; Nielsen, Anette Søgaard; Andersen, Kjeld

    2017-01-01

    This systematic review seeks to expand the description and understanding of late-onset AUD and asks “Which risk factors have been reported for late-onset heavy drinking and AUD?” Method: Using PRISMA guidelines, a literature review and search was performed on May 19, 2015 using the following...... with an increased risk for late-onsetAUDor heavy drinking,whereas retirement, death of a spouse or a close relative does not increase the risk. Discussion: Inherent differences in measurements and methodologies precluded a meta-analysis. Therefore, the results presented here are descriptive in nature. Most studies...... possibly has led to misrepresentations and preconceptions on the complex nature of late-onset AUD. There is limited evidence for any specific risk factor for late-onset AUD or heavy drinking. We suggest the adoption of a qualitative approach to uncover what is intrinsic to late-onset AUD followed...

  8. Identifying sources and controlling factors of arsenic release in saline groundwater aquifers

    OpenAIRE

    Liu, C. -W.; Lu, K.-L.; Kao, Y.-H.; Wang, C.-J.; Maji, S.-K.; Lee, J.-F.

    2014-01-01

    An integrated hydrogeochemical study was carried out to realize the occurrence of arsenic (As) in a saline aquifer. Saline groundwater was mostly concentrated in the uppermost aquifer, and non-saline water was in the lower aquifer in the study area. High As concentrations were found in both the uppermost and lower aquifers. No correlation among salinity, well depth and As concentration was observed. Various forms of Fe oxyhydroxides were identified in the magnetic fractions,...

  9. Identifying driving factors for the establishment of cooperative GMO-free zones in Germany

    OpenAIRE

    Consmuller, Nicola; Beckmann, Volker; Petrick, Martin

    2012-01-01

    Since the end of the quasi-moratorium on genetically modified organisms (GMO) in the European Union in 2004, the establishment of GMO-free zones has become an EU wide phenomenon. In contrast to other European countries, Germany follows the concept of cooperative GMO-free zones where neighbouring farmers contractually refrain from GMO cultivation. In this article, we address the question which underlying factors could account for the establishment of cooperative GMO-free zones in Germany. Draw...

  10. Toward biophysical synergy: Investigating advection along the Polar Front to identify factors influencing Alaska sablefish recruitment

    Science.gov (United States)

    Shotwell, S. Kalei; Hanselman, Dana H.; Belkin, Igor M.

    2014-09-01

    In fisheries stock assessment, reliable estimation of year-class strength is often hindered by lack of data on early life history stages and limited knowledge of the underlying environmental processes influencing survival through these stages. One solution to improving these estimates of year-class strength or recruitment is to first develop regional indices representing the spatial and temporal extent of a hypothesized feature influencing a species' recruitment. These covariates should then be integrated within a population model where a variety of model selection techniques may be conducted to test for a reduction in recruitment uncertainty. The best selected model(s) may provide insight for developing hypotheses of mechanisms influencing recruitment. Here we consider the influence of a large-scale oceanographic feature, the North Pacific Polar Front, on recruitment of Alaska sablefish (Anoplopoma fimbria). Our working hypothesis is that advection of oceanic properties along the Polar Front and associated currents plays a key role in shaping the oceanographic climate of Alaskan waters and, hence, the environment that sablefish encounter during their early life history. As a first step in this investigation, we developed time series of sea surface temperature along the Polar Front mean path. We then integrated this data into the recruitment equations of the sablefish assessment base model. Model selection was based on a multistage hypothesis testing procedure combined with cross-validation and a retrospective analysis of prediction error. The impact of the best model was expressed in terms of increased precision of recruitment estimates and proportional changes in female spawning biomass for both current estimates and in future projections. The best model suggested that colder than average wintertime sea surface temperatures in the central North Pacific represent oceanic conditions that create positive recruitment events for sablefish. The incorporation of this

  11. Natural headland sand bypassing; towards identifying and modelling the mechanisms and processes

    NARCIS (Netherlands)

    Bin Ab Razak, M.S.

    2015-01-01

    Natural headland sand bypassing: Towards identifying and modelling the mechanisms and processes contributes to the understanding of the mechanisms and processes of sand bypassing in artificial and non-artificial coastal environments through a numerical modelling study. Sand bypassing processes in ge

  12. 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…

  13. 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…

  14. Factor analysis in the Genetics of Asthma International Network family study identifies five major quantitative asthma phenotypes

    NARCIS (Netherlands)

    Pillai, S. G.; Tang, Y.; van den Oord, E.; Klotsman, M.; Barnes, K.; Carlsen, K.; Gerritsen, J.; Lenney, W.; Silverman, M.; Sly, P.; Sundy, J.; Tsanakas, J.; von Berg, A.; Whyte, M.; Ortega, H. G.; Anderson, W. H.; Helms, P. J.

    2008-01-01

    Background Asthma is a clinically heterogeneous disease caused by a complex interaction between genetic susceptibility and diverse environmental factors. In common with other complex diseases the lack of a standardized scheme to evaluate the phenotypic variability poses challenges in identifying the

  15. Why some make it and others do not: Identifying psychological factors that predict career success in professional adult soccer

    NARCIS (Netherlands)

    Van Yperen, Nico W.

    2009-01-01

    This prospective study was designed to identify psychological factors that predict career success in professional adult soccer. Post hoc, two groups were distinguished: (1) Male soccer players who Successfully progressed into professional adult soccer (n = 18) and (2) Male soccer players who did not

  16. An investigation of gene-environment interactions between 47 newly identified breast cancer susceptibility loci and environmental risk factors

    OpenAIRE

    Rudolph, Anja; Roger L Milne; Truong, Thérèse; Knight, Julia A.; Seibold, Petra; Flesch-Janys, Dieter; Behrens, Sabine; Eilber, Ursula; Bolla, Manjeet K.; Wang, Qin; Dennis, Joe; Dunning, Alison M.; Shah, Mitul; Munday, Hannah R.; Darabi, Hatef

    2014-01-01

    A large genotyping project within the Breast Cancer Association Consortium (BCAC) recently identified 41 associations between single nucleotide polymorphisms (SNPs) and overall breast cancer (BC) risk. We investigated whether the effects of these 41 SNPs, as well as six SNPs associated with estrogen receptor (ER) negative BC risk are modified by 13 environmental risk factors for BC.

  17. An investigation of gene-environment interactions between 47 newly identified breast cancer susceptibility loci and environmental risk factors

    OpenAIRE

    Rudolph, Anja; Milne, Roger L; Truong, Thérèse; Knight, Julia A; Seibold, Petra; Flesch-Janys, Dieter; Behrens, Sabine; Eilber, Ursula; Bolla, Manjeet K.; Wang, Qin; Dennis, Joe; Alison M Dunning; Shah, Mitul; Munday, Hannah R.; Darabi, Hatef

    2014-01-01

    A large genotyping project within the Breast Cancer Association Consortium (BCAC) recently identified 41 associations between single nucleotide polymorphisms (SNPs) and overall breast cancer (BC) risk. We investigated whether the effects of these 41 SNPs, as well as six SNPs associated with estrogen receptor (ER) negative BC risk are modified by 13 environmental risk factors for BC.

  18. Half-trek criterion for generic identifiability of linear structural equation models

    CERN Document Server

    Foygel, Rina; Drton, Mathias

    2011-01-01

    A linear structural equation model relates random variables of interest and corresponding Gaussian noise terms via a linear equation system. Each such model can be represented by a mixed graph in which directed edges encode the linear equations, and bidirected edges indicate possible correlations among noise terms. We study parameter identifiability in these models, that is, we ask for conditions that ensure that the edge coefficients and correlations appearing in a linear structural equation model can be uniquely recovered from the covariance matrix of the associated normal distribution. We treat the case of generic identifiability, where unique recovery is possible for almost every choice of parameters. We give a new graphical criterion that is sufficient for generic identifiability. It improves criteria from prior work and does not require the directed part of the graph to be acyclic. We also develop a related necessary condition and examine the "gap" between sufficient and necessary conditions through sim...

  19. Model Order and Identifiability of Non-Linear Biological Systems in Stable Oscillation.

    Science.gov (United States)

    Wigren, Torbjörn

    2015-01-01

    The paper presents a theoretical result that clarifies when it is at all possible to determine the nonlinear dynamic equations of a biological system in stable oscillation, from measured data. As it turns out the minimal order needed for this is dependent on the minimal dimension in which the stable orbit of the system does not intersect itself. This is illustrated with a simulated fourth order Hodgkin-Huxley spiking neuron model, which is identified using a non-linear second order differential equation model. The simulated result illustrates that the underlying higher order model of the spiking neuron cannot be uniquely determined given only the periodic measured data. The result of the paper is of general validity when the dynamics of biological systems in stable oscillation is identified, and illustrates the need to carefully address non-linear identifiability aspects when validating models based on periodic data.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2017-04-01

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

  1. Helicobacter pylori infection is identified as a cardiovascular risk factor in Central Africans

    Directory of Open Access Journals (Sweden)

    Longo-Mbenza B

    2012-08-01

    Full Text Available Benjamin Longo-Mbenza,1 Jacqueline Nkondi Nsenga,2 Etienne Mokondjimobe,3 Thierry Gombet,3 Itoua Ngaporo Assori,3 Jean Rosaire Ibara,3 Bertrand Ellenga-Mbolla,3 Dieudonné Ngoma Vangu,4 Simon Mbungu Fuele41Faculty of Health Sciences, Walter Sisulu University, Mthatha, South Africa; 2Division of Gastroenterology, University of Kinshasa, Kinshasa, Democratic Republic of the Congo; 3Faculty of Health Sciences, University of Marien Ngouabi, Brazzaville, Democratic Republic of the Congo; 4Biostatistics Unit, Lomo Medical Center, Limete, Kinshasa, Democratic Republic of the CongoBackground: Helicobacter pylori is now incriminated in the pathogenesis of atherosclerosis.Objective: To examine the importance of H. pylori infection as a cardiovascular disease (CVD risk factor.Methods: Two hundred five patients (128 with H. pylori infection [HP-seropositive] and 77 without had a baseline assessment for other potential CVD risk factors and were followed prospectively for 10 years (1999–2008. They were assessed on a monthly basis for the outcomes of carotid plaque, angina pectoris, myocardial infarction, and stroke. In the HP-seropositive group, male sex and quartile 4 for IgG anti-H. pylori antibodies (anti-HP Ab were correlated with traditional CVD risk factors, stroke, myocardial infarction, and angina pectoris.Results: At the baseline assessment, the levels of carotid intima-media thickness, blood fibrinogen, total cholesterol, fasting plasma glucose, and uric acid were higher in H. pylori-infected patients than in the uninfected group. Serum HDL-cholesterol was significantly lower in the HP-seropositive group. Men had higher levels of IgG anti-HP Ab, waist circumference, blood pressure, uric acid, and total cholesterol than women. Within the HP-seropositive group, individuals in quartile 4 for IgG anti-HP Ab had higher rates of elevated fibrinogen, diabetes mellitus, low high-density lipoprotein cholesterol, arterial hypertension, and high total

  2. 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

    exercise, thereby bypassing the challenging task of model structure determination and identification. Parameter identification problems can thus lead to ill-calibrated models with low predictive power and large model uncertainty. Every calibration exercise should therefore be precededby a proper model...... 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......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...

  3. Unscented Kalman filter with parameter identifiability analysis for the estimation of multiple parameters in kinetic models

    OpenAIRE

    Baker Syed; Poskar C; Junker Björn

    2011-01-01

    Abstract In systems biology, experimentally measured parameters are not always available, necessitating the use of computationally based parameter estimation. In order to rely on estimated parameters, it is critical to first determine which parameters can be estimated for a given model and measurement set. This is done with parameter identifiability analysis. A kinetic model of the sucrose accumulation in the sugar cane culm tissue developed by Rohwer et al. was taken as a test case model. Wh...

  4. Identifiability of Normal and Normal Mixture Models With Nonignorable Missing Data

    OpenAIRE

    Miao, Wang; Ding, Peng; Geng, Zhi

    2015-01-01

    Missing data problems arise in many applied research studies. They may jeopardize statistical inference of the model of interest, if the missing mechanism is nonignorable, that is, the missing mechanism depends on the missing values themselves even conditional on the observed data. With a nonignorable missing mechanism, the model of interest is often not identifiable without imposing further assumptions. We find that even if the missing mechanism has a known parametric form, the model is not ...

  5. [Levers in Primary Health Care - Identifying Strategic Success Factors for Improved Primary Care in Upper Austria].

    Science.gov (United States)

    Kriegel, J; Rebhandl, E; Reckwitz, N; Hockl, W

    2016-12-01

    Current and projected general practitioner (GP) and primary care in Austria shows structural and process inadequacies in the quality as well as assurance of healthcare supply. The aim is therefore to develop solution- and patient-oriented measures that take patient-related requirements and medical perspectives into account. Using an effect matrix, subjective expert and user priorities were ascertained, cause and effect relationships were examined, and an expanded circle of success for the optimization of GP and primary care in Upper Austria was developed. Through this, the relevant levers for target-oriented development and optimization of the complex system of GP and primary care in Upper Austria were identified; these are training to become general practitioners, entrepreneurs as well as management and coordination. It is necessary to further adapt the identified levers conceptually and operationally in a targeted approach. This is to be achieved by means of the primary health care (PHC) concept as well as management tools and information and communication technologies (ICT) associated with it. © Georg Thieme Verlag KG Stuttgart · New York.

  6. Biomechanical approaches to identify and quantify injury mechanisms and risk factors in women's artistic gymnastics.

    Science.gov (United States)

    Bradshaw, Elizabeth J; Hume, Patria A

    2012-09-01

    Targeted injury prevention strategies, based on biomechanical analyses, have the potential to help reduce the incidence and severity of gymnastics injuries. This review outlines the potential benefits of biomechanics research to contribute to injury prevention strategies for women's artistic gymnastics by identification of mechanisms of injury and quantification of the effects of injury risk factors. One hundred and twenty-three articles were retained for review after searching electronic databases using key words, including 'gymnastic', 'biomech*', and 'inj*', and delimiting by language and relevance to the paper aim. Impact load can be measured biomechanically by the use of instrumented equipment (e.g. beatboard), instrumentation on the gymnast (accelerometers), or by landings on force plates. We need further information on injury mechanisms and risk factors in gymnastics and practical methods of monitoring training loads. We have not yet shown, beyond a theoretical approach, how biomechanical analysis of gymnastics can help reduce injury risk through injury prevention interventions. Given the high magnitude of impact load, both acute and accumulative, coaches should monitor impact loads per training session, taking into consideration training quality and quantity such as the control of rotation and the height from which the landings are executed.

  7. Sequence Analysis of Hypothetical Proteins from 26695 to Identify Potential Virulence Factors

    Directory of Open Access Journals (Sweden)

    Ahmad Abu Turab Naqvi

    2016-09-01

    Full Text Available Helicobacter pylori is a Gram-negative bacteria that is responsible for gastritis in human. Its spiral flagellated body helps in locomotion and colonization in the host environment. It is capable of living in the highly acidic environment of the stomach with the help of acid adaptive genes. The genome of H. pylori 26695 strain contains 1,555 coding genes that encode 1,445 proteins. Out of these, 340 proteins are characterized as hypothetical proteins (HP. This study involves extensive analysis of the HPs using an established pipeline which comprises various bioinformatics tools and databases to find out probable functions of the HPs and identification of virulence factors. After extensive analysis of all the 340 HPs, we found that 104 HPs are showing characteristic similarities with the proteins with known functions. Thus, on the basis of such similarities, we assigned probable functions to 104 HPs with high confidence and precision. All the predicted HPs contain representative members of diverse functional classes of proteins such as enzymes, transporters, binding proteins, regulatory proteins, proteins involved in cellular processes and other proteins with miscellaneous functions. Therefore, we classified 104 HPs into aforementioned functional groups. During the virulence factors analysis of the HPs, we found 11 HPs are showing significant virulence. The identification of virulence proteins with the help their predicted functions may pave the way for drug target estimation and development of effective drug to counter the activity of that protein.

  8. Identifying Critical Success Factors for TQM and Employee Performance in Malaysian Automotive Industry: A Literature Review

    Science.gov (United States)

    Nadia Dedy, Aimie; Zakuan, Norhayati; Zaidi Bahari, Ahamad; Ariff, Mohd Shoki Md; Chin, Thoo Ai; Zameri Mat Saman, Muhamad

    2016-05-01

    TQM is a management philosophy embracing all activities through which the needs and expectations of the customer and the community and the goals of the companies are satisfied in the most efficient and cost effective way by maximizing the potential of all workers in a continuing drive for total quality improvement. TQM is very important to the company especially in automotive industry in order for them to survive in the competitive global market. The main objective of this study is to review a relationship between TQM and employee performance. Authors review updated literature on TQM study with two main targets: (a) evolution of TQM considering as a set of practice, (b) and its impacts to employee performance. Therefore, two research questions are proposed in order to review TQM constructs and employee performance measure: (a) Is the set of critical success factors associated with TQM valid as a whole? (b) What is the critical success factors should be considered to measure employee performance in automotive industry?

  9. A retrospective chart review to identify perinatal factors associated with food allergies

    Directory of Open Access Journals (Sweden)

    Karpa Kelly

    2012-10-01

    Full Text Available Abstract Background Gut flora are important immunomodulators that may be disrupted in individuals with atopic conditions. Probiotic bacteria have been suggested as therapeutic modalities to mitigate or prevent food allergic manifestations. We wished to investigate whether perinatal factors known to disrupt gut flora increase the risk of IgE-mediated food allergies. Methods Birth records obtained from 192 healthy children and 99 children diagnosed with food allergies were reviewed retrospectively. Data pertaining to delivery method, perinatal antibiotic exposure, neonatal nursery environment, and maternal variables were recorded. Logistic regression analysis was used to assess the association between variables of interest and subsequent food allergy diagnosis. Results Retrospective investigation did not find perinatal antibiotics, NICU admission, or cesarean section to be associated with increased risk of food allergy diagnosis. However, associations between food allergy diagnosis and male gender (66 vs. 33; p=0.02 were apparent in this cohort. Additionally, increasing maternal age at delivery was significantly associated with food allergy diagnosis during childhood (OR, 1.05; 95% CI, 1.017 to 1.105; p=0.005. Conclusions Gut flora are potent immunomodulators, but their overall contribution to immune maturation remains to be elucidated. Additional understanding of the interplay between immunologic, genetic, and environmental factors underlying food allergy development need to be clarified before probiotic therapeutic interventions can routinely be recommended for prevention or mitigation of food allergies. Such interventions may be well-suited in male infants and in infants born to older mothers.

  10. Sequence Analysis of Hypothetical Proteins from Helicobacter pylori 26695 to Identify Potential Virulence Factors

    Science.gov (United States)

    Naqvi, Ahmad Abu Turab; Anjum, Farah; Khan, Faez Iqbal; Islam, Asimul; Ahmad, Faizan

    2016-01-01

    Helicobacter pylori is a Gram-negative bacteria that is responsible for gastritis in human. Its spiral flagellated body helps in locomotion and colonization in the host environment. It is capable of living in the highly acidic environment of the stomach with the help of acid adaptive genes. The genome of H. pylori 26695 strain contains 1,555 coding genes that encode 1,445 proteins. Out of these, 340 proteins are characterized as hypothetical proteins (HP). This study involves extensive analysis of the HPs using an established pipeline which comprises various bioinformatics tools and databases to find out probable functions of the HPs and identification of virulence factors. After extensive analysis of all the 340 HPs, we found that 104 HPs are showing characteristic similarities with the proteins with known functions. Thus, on the basis of such similarities, we assigned probable functions to 104 HPs with high confidence and precision. All the predicted HPs contain representative members of diverse functional classes of proteins such as enzymes, transporters, binding proteins, regulatory proteins, proteins involved in cellular processes and other proteins with miscellaneous functions. Therefore, we classified 104 HPs into aforementioned functional groups. During the virulence factors analysis of the HPs, we found 11 HPs are showing significant virulence. The identification of virulence proteins with the help their predicted functions may pave the way for drug target estimation and development of effective drug to counter the activity of that protein. PMID:27729842

  11. A macroepigenetic approach to identify factors responsible for the autism epidemic in the United States

    Directory of Open Access Journals (Sweden)

    Dufault Renee

    2012-04-01

    Full Text Available Abstract The number of children ages 6 to 21 in the United States receiving special education services under the autism disability category increased 91% between 2005 to 2010 while the number of children receiving special education services overall declined by 5%. The demand for special education services continues to rise in disability categories associated with pervasive developmental disorders. Neurodevelopment can be adversely impacted when gene expression is altered by dietary transcription factors, such as zinc insufficiency or deficiency, or by exposure to toxic substances found in our environment, such as mercury or organophosphate pesticides. Gene expression patterns differ geographically between populations and within populations. Gene variants of paraoxonase-1 are associated with autism in North America, but not in Italy, indicating regional specificity in gene-environment interactions. In the current review, we utilize a novel macroepigenetic approach to compare variations in diet and toxic substance exposure between these two geographical populations to determine the likely factors responsible for the autism epidemic in the United States.

  12. Statistical Mechanical Models of Integer Factorization Problem

    Science.gov (United States)

    Nakajima, Chihiro H.; Ohzeki, Masayuki

    2017-01-01

    We formulate the integer factorization problem via a formulation of the searching problem for the ground state of a statistical mechanical Hamiltonian. The first passage time required to find a correct divisor of a composite number signifies the exponential computational hardness. The analysis of the density of states of two macroscopic quantities, i.e., the energy and the Hamming distance from the correct solutions, leads to the conclusion that the ground state (correct solution) is completely isolated from the other low-energy states, with the distance being proportional to the system size. In addition, the profile of the microcanonical entropy of the model has two peculiar features that are each related to two marked changes in the energy region sampled via Monte Carlo simulation or simulated annealing. Hence, we find a peculiar first-order phase transition in our model.

  13. Coupling field and laboratory measurements to estimate the emission factors of identified and unidentified trace gases for prescribed fires

    Energy Technology Data Exchange (ETDEWEB)

    Yokelson, R. J.; Burling, I. R.; Gilman, J. B.; Warneke, C.; Stockwell, C. E.; de Gouw, J.; Akagi, S. K.; Urbanski, S. P.; Veres, P.; Roberts, J. M.; Kuster, W. C.; Reardon, J.; Griffith, D. W. T.; Johnson, T. J.; Hosseini, S.; Miller, J. W.; Cocker III, D. R.; Jung, H.; Weise, D. R.

    2013-01-01

    Vegetative fuels commonly consumed in prescribed fires were collected from five locations in the southeastern and southwestern U.S. and burned in a series of 77 fires at the U.S. Forest Service Fire Sciences Laboratory in Missoula, Montana. The particulate matter (PM2.5) emissions were measured by gravimetric filter sampling with subsequent analysis for elemental carbon (EC), organic carbon (OC), and 38 elements. The trace gas emissions were measured with a large suite of state-of-the-art instrumentation including an open-path Fourier transform infrared (OP FTIR) spectrometer, proton-transfer-reaction mass spectrometry (PTR-MS), proton-transfer ion-trap mass spectrometry (PIT-MS), negative-ion proton-transfer chemical-ionization mass spectrometry (NI-PT-CIMS), and gas chromatography with MS detection (GC-MS). 204 trace gas species (mostly non-methane organic compounds (NMOC)) were identified and quantified with the above instruments. An additional 152 significant peaks in the unit mass resolution mass spectra were quantified, but either could not be identified or most of the signal at that molecular mass was unaccounted for by identifiable species. As phase II of this study, we conducted airborne and ground-based sampling of the emissions from real prescribed fires mostly in the same land management units where the fuels for the lab fires were collected. A broad variety, but smaller number of species (21 trace gas species and PM2.5) was measured on 14 fires in chaparral and oak savanna in the southwestern US, as well as pine forest understory in the southeastern US and Sierra Nevada mountains of California. These extensive field measurements of emission factors (EF) for temperate biomass burning are useful both for modeling and to examine the representativeness of our lab fire EF. The lab/field EF ratio for the pine understory fuels was not statistically different from one, on average. However, our lab EF for “smoldering compounds” emitted by burning the semi

  14. Latent Fundamentals Arbitrage with a Mixed Effects Factor Model

    Directory of Open Access Journals (Sweden)

    Andrei Salem Gonçalves

    2012-09-01

    Full Text Available We propose a single-factor mixed effects panel data model to create an arbitrage portfolio that identifies differences in firm-level latent fundamentals. Furthermore, we show that even though the characteristics that affect returns are unknown variables, it is possible to identify the strength of the combination of these latent fundamentals for each stock by following a simple approach using historical data. As a result, a trading strategy that bought the stocks with the best fundamentals (strong fundamentals portfolio and sold the stocks with the worst ones (weak fundamentals portfolio realized significant risk-adjusted returns in the U.S. market for the period between July 1986 and June 2008. To ensure robustness, we performed sub period and seasonal analyses and adjusted for trading costs and we found further empirical evidence that using a simple investment rule, that identified these latent fundamentals from the structure of past returns, can lead to profit.

  15. Identifying and Prioritizing the Determinative factors of Customers Repeat Purchasing in Etka Chain Stores by Using Neural Networks Algorithm

    Directory of Open Access Journals (Sweden)

    Behrooz Jahandideh

    2013-01-01

    Full Text Available Nowadays, chain stores are experiencing a severe competitive environment. In such anenvironment, a growing number of customers are equipped by high volumes of informationand are more risk-taking. As they tend to switch their store based on the higher value thatthey might receive elsewhere, as customers switching behavior has become so commonplaceand has become a challenge for retailers. Thus, factors that influence the willingness ofcustomers to repurchase will play a critical role in the performance and success of chainstores. This paper aimed to identify and prioritize the determinative factors that causecustomers repeat patronage in Etka chain stores. Factors were extracted based on a thoroughliterature review and then these factors were modified using pre-test and interview methods.In this study, questionnaires were used for data collection. Respectively, to identify andprioritize determinative factors, correlation analysis and artificial neural networks were used.Results showed that in order of importance, quality, price loyalty program, number of servicecounters, store staff, shelf labels, product selection, parking facilities, home delivery, storebrand, and store atmosphere are factors that determine customers’ repeat patronage of Etkachain stores. Meanwhile, young, educated and wealthy customers showed lower store repeatpatronage. Finally, the paper concludes with suggestions for increasing consumer repeatpatronageof Etka chain-stores and directions for future research

  16. Global analysis of induced transcription factors and cofactors identifies Tfdp2 as an essential coregulator during terminal erythropoiesis.

    Science.gov (United States)

    Chen, Cynthia; Lodish, Harvey F

    2014-06-01

    Key transcriptional regulators of terminal erythropoiesis, such as GATA-binding factor 1 (GATA1) and T-cell acute lymphocytic leukemia protein 1 (TAL1), have been well characterized, but transcription factors and cofactors and their expression modulations have not yet been explored on a global scale. Here, we use global gene expression analysis to identify 28 transcription factors and 19 transcriptional cofactors induced during terminal erythroid differentiation whose promoters are enriched for binding by GATA1 and TAL1. Utilizing protein-protein interaction databases to identify cofactors for each transcription factor, we pinpoint several co-induced pairs, of which E2f2 and its cofactor transcription factor Dp-2 (Tfdp2) were the most highly induced. TFDP2 is a critical cofactor required for proper cell cycle control and gene expression. GATA1 and TAL1 are bound to the regulatory regions of Tfdp2 and upregulate its expression and knockdown of Tfdp2 results in significantly reduced rates of proliferation as well as reduced upregulation of many erythroid-important genes. Loss of Tfdp2 also globally inhibits the normal downregulation of many E2F2 target genes, including those that regulate the cell cycle, causing cells to accumulate in S phase and resulting in increased erythrocyte size. Our findings highlight the importance of TFDP2 in coupling the erythroid cell cycle with terminal differentiation and validate this study as a resource for future work on elucidating the role of diverse transcription factors and coregulators in erythropoiesis.

  17. Identifying and prioritizing factors that influence reapeted patronage of Etka chain-stores customers: a neural network approach

    Directory of Open Access Journals (Sweden)

    Behrouz Jahandideh

    2013-03-01

    Full Text Available Nowadays, chain stores are experiencing a severe competitive environment. In such an environment, a growing number of customers are equipped by high volumes of information and are more risk-taking. As they tend to switch their store based on the higher value that they might receive elsewhere, as customers switching behavior has become so commonplace and has become a challenge for retailers. Thus, factors that influence the willingness of customers to repurchase will play a critical role in the performance and success of chain stores. This paper aimed to identify and prioritize the determinative factors that cause customers repeat patronage in Etka chain stores. Factors were extracted based on a thorough literature review and then these factors were modified using pre-test and interview methods. In this study, questionnaires were used for data collection. Respectively, to identify and prioritize determinative factors, correlation analysis and artificial neural networks were used. Results showed that in order of importance, quality, price loyalty program, number of service counters, store staff, shelf labels, product selection, parking facilities, home delivery, store brand, and store atmosphere are factors that determine customers’ repeat patronage of Etka chain stores. Meanwhile, young, educated and wealthy customers showed lower store repeat patronage. Finally, the paper concludes with suggestions for increasing consumer repeat-patronage of Etka chain-stores and directions for future research.

  18. Identifying niche-mediated regulatory factors of stem cell phenotypic state: a systems biology approach.

    Science.gov (United States)

    Ravichandran, Srikanth; Del Sol, Antonio

    2017-02-01

    Understanding how the cellular niche controls the stem cell phenotype is often hampered due to the complexity of variegated niche composition, its dynamics, and nonlinear stem cell-niche interactions. Here, we propose a systems biology view that considers stem cell-niche interactions as a many-body problem amenable to simplification by the concept of mean field approximation. This enables approximation of the niche effect on stem cells as a constant field that induces sustained activation/inhibition of specific stem cell signaling pathways in all stem cells within heterogeneous populations exhibiting the same phenotype (niche determinants). This view offers a new basis for the development of single cell-based computational approaches for identifying niche determinants, which has potential applications in regenerative medicine and tissue engineering. © 2017 The Authors. FEBS Letters published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.

  19. Previously identified patellar tendinopathy risk factors differ between elite and sub-elite volleyball players.

    Science.gov (United States)

    Janssen, I; Steele, J R; Munro, B J; Brown, N A T

    2015-06-01

    Patellar tendinopathy is the most common knee injury incurred in volleyball, with its prevalence in elite athletes more than three times that of their sub-elite counterparts. The purpose of this study was to determine whether patellar tendinopathy risk factors differed between elite and sub-elite male volleyball players. Nine elite and nine sub-elite male volleyball players performed a lateral stop-jump block movement. Maximum vertical jump, training history, muscle extensibility and strength, three-dimensional landing kinematics (250 Hz), along with lower limb neuromuscular activation patterns (1500 Hz), and patellar tendon loading were collected during each trial. Multivariate analyses of variance (P volleyball players. Interventions designed to reduce landing frequency and improve quadriceps extensibility are recommended to reduce patellar tendinopathy prevalence in volleyball players. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  20. A Systematic Approach to Identify Candidate Transcription Factors that Control Cell Identity

    Directory of Open Access Journals (Sweden)

    Ana C. D’Alessio

    2015-11-01

    Full Text Available Hundreds of transcription factors (TFs are expressed in each cell type, but cell identity can be induced through the activity of just a small number of core TFs. Systematic identification of these core TFs for a wide variety of cell types is currently lacking and would establish a foundation for understanding the transcriptional control of cell identity in development, disease, and cell-based therapy. Here, we describe a computational approach that generates an atlas of candidate core TFs for a broad spectrum of human cells. The potential impact of the atlas was demonstrated via cellular reprogramming efforts where candidate core TFs proved capable of converting human fibroblasts to retinal pigment epithelial-like cells. These results suggest that candidate core TFs from the atlas will prove a useful starting point for studying transcriptional control of cell identity and reprogramming in many human cell types.

  1. Identifying risk factors for healthcare-associated infections from electronic medical record home address data

    Directory of Open Access Journals (Sweden)

    Rosenman Marc B

    2010-09-01

    Full Text Available Abstract Background Residential address is a common element in patient electronic medical records. Guidelines from the U.S. Centers for Disease Control and Prevention specify that residence in a nursing home, skilled nursing facility, or hospice within a year prior to a positive culture date is among the criteria for differentiating healthcare-acquired from community-acquired methicillin-resistant Staphylococcus aureus (MRSA infections. Residential addresses may be useful for identifying patients residing in healthcare-associated settings, but methods for categorizing residence type based on electronic medical records have not been widely documented. The aim of this study was to develop a process to assist in differentiating healthcare-associated from community-associated MRSA infections by analyzing patient addresses to determine if residence reported at the time of positive culture was associated with a healthcare facility or other institutional location. Results We identified 1,232 of the patients (8.24% of the sample with positive cultures as probable cases of healthcare-associated MRSA based on residential addresses contained in electronic medical records. Combining manual review with linking to institutional address databases improved geocoding rates from 11,870 records (79.37% to 12,549 records (83.91%. Standardization of patient home address through geocoding increased the number of matches to institutional facilities from 545 (3.64% to 1,379 (9.22%. Conclusions Linking patient home address data from electronic medical records to institutional residential databases provides useful information for epidemiologic researchers, infection control practitioners, and clinicians. This information, coupled with other clinical and laboratory data, can be used to inform differentiation of healthcare-acquired from community-acquired infections. The process presented should be extensible with little or no added data costs.

  2. Unplanned Hospital Return for Infection following Ureteroscopy-Can We Identify Modifiable Risk Factors?

    Science.gov (United States)

    Moses, Rachel A; Ghali, Fady M; Pais, Vernon M; Hyams, Elias S

    2016-04-01

    Genitourinary infection after ureteroscopy with laser lithotripsy is a clinically significant event that may lead to expensive and morbid return to the hospital. We evaluate factors associated with infection after ureteroscopy with laser lithotripsy leading to unplanned hospital return. We performed a retrospective chart review evaluating all ureteroscopy with laser lithotripsy performed at a single academic institution from April 2011 to August 2014. Data were extracted including patient demographics, comorbidities, surgical encounter characteristics, preoperative urine culture status, antibiotic type/duration and compliance with the AUA Best Practice Statement for antibiotic prophylaxis. Bivariate and multivariate analyses were performed to determine factors associated with unplanned return to the hospital. Among 550 patients undergoing ureteroscopy with laser lithotripsy 45% (248) were female with an average age of 56.8 (± 14.8) years. Overall 3.4% (19 patients) had an unplanned return for genitourinary infection, with most (78.9%, 15 of 19) requiring inpatient readmission. Overall compliance with AUA Best Practice Statement for antibiotic prophylaxis was 48.7% (268 of 550). Rates of infection related returns were higher in patients undergoing preoperative stenting (84.2% vs 58.6%, p=0.025), those with an operative time greater than 120 minutes (89.5% vs 32.6% p risk of infection, underscoring the need for locally appropriate prophylaxis strategies and further study of optimal prophylaxis regimens. Copyright © 2016 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

  3. Multiplex real time PCR panels to identify fourteen colonization factors of enterotoxigenic Escherichia coli (ETEC).

    Science.gov (United States)

    Liu, Jie; Silapong, Sasikorn; Jeanwattanalert, Pimmada; Lertsehtakarn, Paphavee; Bodhidatta, Ladaporn; Swierczewski, Brett; Mason, Carl; McVeigh, Annette L; Savarino, Stephen J; Nshama, Rosemary; Mduma, Esto; Maro, Athanasia; Zhang, Jixian; Gratz, Jean; Houpt, Eric R

    2017-01-01

    Enterotoxigenic Escherichia coli (ETEC) is a leading cause of childhood diarrhea in low income countries and in travelers to those areas. Inactivated enterotoxins and colonization factors (CFs) are leading vaccine candidates, therefore it is important to determine the prevailing CF types in different geographic locations and populations. Here we developed real time PCR (qPCR) assays for 14 colonization factors, including the common vaccine targets. These assays, along with three enterotoxin targets (STh, STp, and LT) were formulated into three 5-plex qPCR panels, and validated on 120 ETEC isolates and 74 E. coli colony pools. The overall sensitivity and specificity was 99% (199/202) and 99% (2497/2514), respectively, compared to the CF results obtained with conventional PCR. Amplicon sequencing of discrepant samples revealed that the qPCR was 100% accurate. qPCR panels were also performed on nucleic acid extracted from stool and compared to the results of the ETEC isolates or E. coli colony pools cultured from them. 95% (105/110) of the CF detections in the cultures were confirmed in the stool. Additionally, direct testing of stool yielded 30 more CF detections. Among 74 randomly selected E. coli colony pools with paired stool, at least one CF was detected in 63% (32/51) of the colony pools while at least one CF was detected in 78% (47/60) of the stool samples (P = NS). We conclude that these ETEC CF assays can be used on both cultures and stool samples to facilitate better understanding of CF distribution for ETEC epidemiology and vaccine development.

  4. spatially identifying vulnerable areas

    African Journals Online (AJOL)

    System (SMDSS) to identify factors that make forest and game reserves vulnerable .... involve the creation of a Digital Elevation Model (DEM), Slope Settlement and ... Feature). Spatial. Analyst Tool. (Slope). Buffer Tool. Buffer Tool. Buffer Tool.

  5. 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...

  6. Identifying and managing risk factors for salt-affected soils: a case study in a semi-arid region in China.

    Science.gov (United States)

    Zhou, De; Xu, Jianchun; Wang, Li; Lin, Zhulu; Liu, Liming

    2015-07-01

    Soil salinization and desalinization are complex processes caused by natural conditions and human-induced risk factors. Conventional salinity risk identification and management methods have limitations in spatial data analysis and often provide an inadequate description of the problem. The objectives of this study were to identify controllable risk factors, to provide response measures, and to design management strategies for salt-affected soils. We proposed to integrate spatial autoregressive (SAR) model, multi-attribute decision making (MADM), and analytic hierarchy process (AHP) for these purposes. Our proposed method was demonstrated through a case study of managing soil salinization in a semi-arid region in China. The results clearly indicated that the SAR model is superior to the OLS model in terms of risk factor identification. These factors include groundwater salinity, paddy area, corn area, aquaculture (i.e., ponds and lakes) area, distance to drainage ditches and irrigation channels, organic fertilizer input, and cropping index, among which the factors related to human land use activities are dominant risk factors that drive the soil salinization processes. We also showed that ecological irrigation and sustainable land use are acceptable strategies for soil salinity management.

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

    Directory of Open Access Journals (Sweden)

    Oana-Teodora Chis

    Full Text Available Analysing the properties of a biological system through in silico experimentation requires a satisfactory mathematical representation of the system including accurate values of the model parameters. Fortunately, modern experimental techniques allow obtaining time-series data of appropriate quality which may then be used to estimate unknown parameters. However, in many cases, a subset of those parameters may not be uniquely estimated, independently of the experimental data available or the numerical techniques used for estimation. This lack of identifiability is related to the structure of the model, i.e. the system dynamics plus the observation function. Despite the interest in knowing a priori whether there is any chance of uniquely estimating all model unknown parameters, the structural identifiability analysis for general non-linear dynamic models is still an open question. There is no method amenable to every model, thus at some point we have to face the selection of one of the possibilities. This work presents a critical comparison of the currently available techniques. To this end, we perform the structural identifiability analysis of a collection of biological models. The results reveal that the generating series approach, in combination with identifiability tableaus, offers the most advantageous compromise among range of applicability, computational complexity and information provided.

  8. Factor Analysis of Drawings: Application to College Student Models of the Greenhouse Effect

    Science.gov (United States)

    Libarkin, Julie C.; Thomas, Stephen R.; Ording, Gabriel

    2015-01-01

    Exploratory factor analysis was used to identify models underlying drawings of the greenhouse effect made by over 200 entering university freshmen. Initial content analysis allowed deconstruction of drawings into salient features, with grouping of these features via factor analysis. A resulting 4-factor solution explains 62% of the data variance,…

  9. IDENTIFYING ELEVEN FACTORS OF SERVICE MARKETING MIX (4PS) EFFECTIVE ON TENDENCY OF PATIENTS TOWARD PRIVATE HOSPITAL.

    Science.gov (United States)

    Hosseini, Seyed Mojtaba; Etesaminia, Samira; Jafari, Mehrnoosh

    2016-10-01

    One of the important factors of correct management is to identify the reasons for patient tendency toward private hospitals. This study measures these factors based on service marketing mixes. This study used a cross sectional descriptive methodology. The study was conducted during 6 months in 2015. The studied population included patients of private hospitals in Tehran. Random sampling was used (n = 200). Data was collected by an author-made questionnaire for service marketing factors. Reliability and validity of the questionnaire were confirmed. Data analysis was done using factor analysis test in SPSS 20. The results showed that constant attendance of physicians and nurses has the highest effect (0.707%) on patient tendency toward private hospitals.

  10. IDENTIFYING ELEVEN FACTORS OF SERVICE MARKETING MIX (4PS) EFFECTIVE ON TENDENCY OF PATIENTS TOWARD PRIVATE HOSPITAL

    Science.gov (United States)

    Hosseini, Seyed Mojtaba; Etesaminia, Samira; Jafari, Mehrnoosh

    2016-01-01

    Introduction: One of the important factors of correct management is to identify the reasons for patient tendency toward private hospitals. This study measures these factors based on service marketing mixes. Patients and methods: This study used a cross sectional descriptive methodology. The study was conducted during 6 months in 2015. The studied population included patients of private hospitals in Tehran. Random sampling was used (n = 200). Data was collected by an author-made questionnaire for service marketing factors. Reliability and validity of the questionnaire were confirmed. Data analysis was done using factor analysis test in SPSS 20. Results: The results showed that constant attendance of physicians and nurses has the highest effect (0.707%) on patient tendency toward private hospitals. PMID:27999486

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

    Directory of Open Access Journals (Sweden)

    Philip Stegmaier

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

  12. Coupling field and laboratory measurements to estimate the emission factors of identified and unidentified trace gases for prescribed fires

    Science.gov (United States)

    Yokelson, R. J.; Burling, I. R.; Gilman, J. B.; Warneke, C.; Stockwell, C. E.; de Gouw, J.; Akagi, S. K.; Urbanski, S. P.; Veres, P.; Roberts, J. M.; Kuster, W. C.; Reardon, J.; Griffith, D. W. T.; Johnson, T. J.; Hosseini, S.; Miller, J. W.; Cocker, D. R., III; Jung, H.; Weise, D. R.

    2013-01-01

    An extensive program of experiments focused on biomass burning emissions began with a laboratory phase in which vegetative fuels commonly consumed in prescribed fires were collected in the southeastern and southwestern US and burned in a series of 71 fires at the US Forest Service Fire Sciences Laboratory in Missoula, Montana. The particulate matter (PM2.5) emissions were measured by gravimetric filter sampling with subsequent analysis for elemental carbon (EC), organic carbon (OC), and 38 elements. The trace gas emissions were measured by an open-path Fourier transform infrared (OP-FTIR) spectrometer, proton-transfer-reaction mass spectrometry (PTR-MS), proton-transfer ion-trap mass spectrometry (PIT-MS), negative-ion proton-transfer chemical-ionization mass spectrometry (NI-PT-CIMS), and gas chromatography with MS detection (GC-MS). 204 trace gas species (mostly non-methane organic compounds (NMOC)) were identified and quantified with the above instruments. Many of the 182 species quantified by the GC-MS have rarely, if ever, been measured in smoke before. An additional 153 significant peaks in the unit mass resolution mass spectra were quantified, but either could not be identified or most of the signal at that molecular mass was unaccounted for by identifiable species. In a second, "field" phase of this program, airborne and ground-based measurements were made of the emissions from prescribed fires that were mostly located in the same land management units where the fuels for the lab fires were collected. A broad variety, but smaller number of species (21 trace gas species and PM2.5) was measured on 14 fires in chaparral and oak savanna in the southwestern US, as well as pine forest understory in the southeastern US and Sierra Nevada mountains of California. The field measurements of emission factors (EF) are useful both for modeling and to examine the representativeness of our lab fire EF. The lab EF/field EF ratio for the pine understory fuels was not

  13. Coupling field and laboratory measurements to estimate the emission factors of identified and unidentified trace gases for prescribed fires

    Directory of Open Access Journals (Sweden)

    R. J. Yokelson

    2013-01-01

    Full Text Available An extensive program of experiments focused on biomass burning emissions began with a laboratory phase in which vegetative fuels commonly consumed in prescribed fires were collected in the southeastern and southwestern US and burned in a series of 71 fires at the US Forest Service Fire Sciences Laboratory in Missoula, Montana. The particulate matter (PM2.5 emissions were measured by gravimetric filter sampling with subsequent analysis for elemental carbon (EC, organic carbon (OC, and 38 elements. The trace gas emissions were measured by an open-path Fourier transform infrared (OP-FTIR spectrometer, proton-transfer-reaction mass spectrometry (PTR-MS, proton-transfer ion-trap mass spectrometry (PIT-MS, negative-ion proton-transfer chemical-ionization mass spectrometry (NI-PT-CIMS, and gas chromatography with MS detection (GC-MS. 204 trace gas species (mostly non-methane organic compounds (NMOC were identified and quantified with the above instruments. Many of the 182 species quantified by the GC-MS have rarely, if ever, been measured in smoke before. An additional 153 significant peaks in the unit mass resolution mass spectra were quantified, but either could not be identified or most of the signal at that molecular mass was unaccounted for by identifiable species.

    In a second, "field" phase of this program, airborne and ground-based measurements were made of the emissions from prescribed fires that were mostly located in the same land management units where the fuels for the lab fires were collected. A broad variety, but smaller number of species (21 trace gas species and PM2.5 was measured on 14 fires in chaparral and oak savanna in the southwestern US, as well as pine forest understory in the southeastern US and Sierra Nevada mountains of California. The field measurements of emission factors (EF are useful both for modeling and to examine the representativeness of our lab fire EF. The lab EF/field EF ratio for

  14. Coupling field and laboratory measurements to estimate the emission factors of identified and unidentified trace gases for prescribed fires

    Directory of Open Access Journals (Sweden)

    R. J. Yokelson

    2012-08-01

    Full Text Available An extensive program of experiments focused on biomass burning emissions began with a laboratory phase in which vegetative fuels commonly consumed in prescribed fires were collected in the southeastern and southwestern US and burned in a series of 71 fires at the US Forest Service Fire Sciences Laboratory in Missoula, Montana. The particulate matter (PM2.5 emissions were measured by gravimetric filter sampling with subsequent analysis for elemental carbon (EC, organic carbon (OC, and 38 elements. The trace gas emissions were measured by an open-path Fourier transform infrared (OP-FTIR spectrometer, proton-transfer-reaction mass spectrometry (PTR-MS, proton-transfer ion-trap mass spectrometry (PIT-MS, negative-ion proton-transfer chemical-ionization mass spectrometry (NI-PT-CIMS, and gas chromatography with MS detection (GC-MS. 204 trace gas species (mostly non-methane organic compounds – NMOC were identified and quantified with the above instruments. Many of the 182 species quantified by the GC-MS have rarely, if ever, been measured in smoke before. An additional 153 significant peaks in the unit mass resolution mass spectra were quantified, but either could not be identified or most of the signal at that molecular mass was unaccounted for by identifiable species.

    In a second, "field" phase of this program, airborne and ground-based measurements were made of the emissions from prescribed fires that were mostly located in the same land management units where the fuels for the lab fires were collected. A broad variety, but smaller number of species (21 trace gas species and PM2.5 was measured on 14 fires in chaparral and oak savanna in the southwestern US, as well as pine forest understory in the southeastern US and Sierra Nevada mountains of California. The field measurements of emission factors (EF are useful both for modeling and to examine the representativeness of our lab fire EF. The lab EF/field EF ratio for

  15. Identifying Environmental and Social Factors Predisposing to Pathological Gambling Combining Standard Logistic Regression and Logic Learning Machine.

    Science.gov (United States)

    Parodi, Stefano; Dosi, Corrado; Zambon, Antonella; Ferrari, Enrico; Muselli, Marco

    2017-03-02

    Identifying potential risk factors for problem gambling (PG) is of primary importance for planning preventive and therapeutic interventions. We illustrate a new approach based on the combination of standard logistic regression and an innovative method of supervised data mining (Logic Learning Machine or LLM). Data were taken from a pilot cross-sectional study to identify subjects with PG behaviour, assessed by two internationally validated scales (SOGS and Lie/Bet). Information was obtained from 251 gamblers recruited in six betting establishments. Data on socio-demographic characteristics, lifestyle and cognitive-related factors, and type, place and frequency of preferred gambling were obtained by a self-administered questionnaire. The following variables associated with PG were identified: instant gratification games, alcohol abuse, cognitive distortion, illegal behaviours and having started gambling with a relative or a friend. Furthermore, the combination of LLM and LR indicated the presence of two different types of PG, namely: (a) daily gamblers, more prone to illegal behaviour, with poor money management skills and who started gambling at an early age, and (b) non-daily gamblers, characterised by superstitious beliefs and a higher preference for immediate reward games. Finally, instant gratification games were strongly associated with the number of games usually played. Studies on gamblers habitually frequently betting shops are rare. The finding of different types of PG by habitual gamblers deserves further analysis in larger studies. Advanced data mining algorithms, like LLM, are powerful tools and potentially useful in identifying risk factors for PG.

  16. Cadmium levels in a North Carolina cohort: Identifying risk factors for elevated levels during pregnancy.

    Science.gov (United States)

    Edwards, Sharon E; Maxson, Pamela; Miranda, Marie Lynn; Fry, Rebecca C

    2015-01-01

    The objectives of this study were to examine cadmium (Cd) levels and relationships to demographics in an observational, prospective pregnancy cohort study in Durham County, North Carolina. Multivariable models were used to compare blood Cd levels across demographic characteristics. The relative risk of having a blood Cd level that exceeds the US national median (0.32 μg/l) was estimated. Overall, >60% of the women had an elevated (>0.32 μg/l) blood Cd level. Controlling for confounding variables, smoking was associated with 21% (95% CI: 15-28%) increased risk for an elevated blood Cd level. High Cd levels were also observed in non-smokers and motivated smoking status-stratified models. Race, age, education, relationship status, insurance status and cotinine level were not associated with risk of elevated Cd levels among smokers; however, older age and higher cotinine levels were associated with elevated Cd levels among non-smokers. Taken together, more than half of pregnant women in this cohort had elevated blood Cd levels. Additionally, among non-smokers, 53% of the women had elevated levels of Cd, highlighting other potential sources of exposure. This study expands on the limited data describing Cd levels in pregnant populations and highlights the importance of understanding Cd exposures among non-smokers. Given the latent health risks of both smoking and Cd exposure, this study further highlights the need to biomonitor for exposure to toxic metals during pregnancy among all women of child-bearing age.

  17. Identifying The Effective Factors for Cost Overrun and Time Delay in Water Construction Projects

    Directory of Open Access Journals (Sweden)

    D. Mirzai Matin

    2016-08-01

    Full Text Available Water construction projects in Iran frequently face problems which cause cost overrun and time delay, the two most common issues in construction projects in general. The objective of this survey is to identify and quantify these problems and thus help in avoiding them. This survey represents a collection of the most significant problems found in the literature, classified into 11 groups according to their source. The questionnaire form used contains 84 questions which were answered by random engineers who work in water construction projects. The Relative Importance Weight (RIW method is used to weight the importance of each one of the 84 problems. The focus of this survey is on overall top ten issues which are: bureaucracy in bidding method, inflation, economical condition of the government, not enough information gathered and surveys done before design, monthly payment difficulties, material cost changes, law changes by the government, financial difficulties, mode of financing and payment for completed work and changes made by the owner. A section for each of these issues provides additional information about them. In the full text of this survey the same weighting method is used to classify the main groups, and the results show that issues related to the groups of government, owner and consultant has the most significant impact. The last part of this survey describes the point of view of the engineers who took part in this survey and the recommendations they made.

  18. Functional gene group analysis identifies synaptic gene groups as risk factor for schizophrenia.

    Science.gov (United States)

    Lips, E S; Cornelisse, L N; Toonen, R F; Min, J L; Hultman, C M; Holmans, P A; O'Donovan, M C; Purcell, S M; Smit, A B; Verhage, M; Sullivan, P F; Visscher, P M; Posthuma, D

    2012-10-01

    Schizophrenia is a highly heritable disorder with a polygenic pattern of inheritance and a population prevalence of ~1%. Previous studies have implicated synaptic dysfunction in schizophrenia. We tested the accumulated association of genetic variants in expert-curated synaptic gene groups with schizophrenia in 4673 cases and 4965 healthy controls, using functional gene group analysis. Identifying groups of genes with similar cellular function rather than genes in isolation may have clinical implications for finding additional drug targets. We found that a group of 1026 synaptic genes was significantly associated with the risk of schizophrenia (P=7.6 × 10(-11)) and more strongly associated than 100 randomly drawn, matched control groups of genetic variants (P<0.01). Subsequent analysis of synaptic subgroups suggested that the strongest association signals are derived from three synaptic gene groups: intracellular signal transduction (P=2.0 × 10(-4)), excitability (P=9.0 × 10(-4)) and cell adhesion and trans-synaptic signaling (P=2.4 × 10(-3)). These results are consistent with a role of synaptic dysfunction in schizophrenia and imply that impaired intracellular signal transduction in synapses, synaptic excitability and cell adhesion and trans-synaptic signaling play a role in the pathology of schizophrenia.

  19. Signature Motifs Identify an Acinetobacter Cif Virulence Factor with Epoxide Hydrolase Activity*

    Science.gov (United States)

    Bahl, Christopher D.; Hvorecny, Kelli L.; Bridges, Andrew A.; Ballok, Alicia E.; Bomberger, Jennifer M.; Cady, Kyle C.; O'Toole, George A.; Madden, Dean R.

    2014-01-01

    Endocytic recycling of the cystic fibrosis transmembrane conductance regulator (CFTR) is blocked by the CFTR inhibitory factor (Cif). Originally discovered in Pseudomonas aeruginosa, Cif is a secreted epoxide hydrolase that is transcriptionally regulated by CifR, an epoxide-sensitive repressor. In this report, we investigate a homologous protein found in strains of the emerging nosocomial pathogens Acinetobacter nosocomialis and Acinetobacter baumannii (“aCif”). Like Cif, aCif is an epoxide hydrolase that carries an N-terminal secretion signal and can be purified from culture supernatants. When applied directly to polarized airway epithelial cells, mature aCif triggers a reduction in CFTR abundance at the apical membrane. Biochemical and crystallographic studies reveal a dimeric assembly with a stereochemically conserved active site, confirming our motif-based identification of candidate Cif-like pathogenic EH sequences. Furthermore, cif expression is transcriptionally repressed by a CifR homolog (“aCifR”) and is induced in the presence of epoxides. Overall, this Acinetobacter protein recapitulates the essential attributes of the Pseudomonas Cif system and thus may facilitate airway colonization in nosocomial lung infections. PMID:24474692

  20. Signature motifs identify an Acinetobacter Cif virulence factor with epoxide hydrolase activity.

    Science.gov (United States)

    Bahl, Christopher D; Hvorecny, Kelli L; Bridges, Andrew A; Ballok, Alicia E; Bomberger, Jennifer M; Cady, Kyle C; O'Toole, George A; Madden, Dean R

    2014-03-14

    Endocytic recycling of the cystic fibrosis transmembrane conductance regulator (CFTR) is blocked by the CFTR inhibitory factor (Cif). Originally discovered in Pseudomonas aeruginosa, Cif is a secreted epoxide hydrolase that is transcriptionally regulated by CifR, an epoxide-sensitive repressor. In this report, we investigate a homologous protein found in strains of the emerging nosocomial pathogens Acinetobacter nosocomialis and Acinetobacter baumannii ("aCif"). Like Cif, aCif is an epoxide hydrolase that carries an N-terminal secretion signal and can be purified from culture supernatants. When applied directly to polarized airway epithelial cells, mature aCif triggers a reduction in CFTR abundance at the apical membrane. Biochemical and crystallographic studies reveal a dimeric assembly with a stereochemically conserved active site, confirming our motif-based identification of candidate Cif-like pathogenic EH sequences. Furthermore, cif expression is transcriptionally repressed by a CifR homolog ("aCifR") and is induced in the presence of epoxides. Overall, this Acinetobacter protein recapitulates the essential attributes of the Pseudomonas Cif system and thus may facilitate airway colonization in nosocomial lung infections.

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

    Science.gov (United States)

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

    2010-05-01

    identifying errors; and barriers and facilitators. There was no common language in the discussion of modelling errors and there was inconsistency in the perceived boundaries of what constitutes an error. Asked about the definition of model error, there was a tendency for interviewees to exclude matters of judgement from being errors and focus on 'slips' and 'lapses', but discussion of slips and lapses comprised less than 20% of the discussion on types of errors. Interviewees devoted 70% of the discussion to softer elements of the process of defining the decision question and conceptual modelling, mostly the realms of judgement, skills, experience and training. The original focus concerned model errors, but it may be more useful to refer to modelling risks. Several interviewees discussed concepts of validation and verification, with notable consistency in interpretation: verification meaning the process of ensuring that the computer model correctly implemented the intended model, whereas validation means the process of ensuring that a model is fit for purpose. Methodological literature on verification and validation of models makes reference to the Hermeneutic philosophical position, highlighting that the concept of model validation should not be externalized from the decision-makers and the decision-making process. Interviewees demonstrated examples of all major error types identified in the literature: errors in the description of the decision problem, in model structure, in use of evidence, in implementation of the model, in operation of the model, and in presentation and understanding of results. The HTA error classifications were compared against existing classifications of model errors in the literature. A range of techniques and processes are currently used to avoid errors in HTA models: engaging with clinical experts, clients and decision-makers to ensure mutual understanding, producing written documentation of the proposed model, explicit conceptual modelling

  2. An absolute risk model to identify individuals at elevated risk for pancreatic cancer in the general population.

    Directory of Open Access Journals (Sweden)

    Alison P Klein

    Full Text Available PURPOSE: We developed an absolute risk model to identify individuals in the general population at elevated risk of pancreatic cancer. PATIENTS AND METHODS: Using data on 3,349 cases and 3,654 controls from the PanScan Consortium, we developed a relative risk model for men and women of European ancestry based on non-genetic and genetic risk factors for pancreatic cancer. We estimated absolute risks based on these relative risks and population incidence rates. RESULTS: Our risk model included current smoking (multivariable adjusted odds ratio (OR and 95% confidence interval: 2.20 [1.84-2.62], heavy alcohol use (>3 drinks/day (OR: 1.45 [1.19-1.76], obesity (body mass index >30 kg/m(2 (OR: 1.26 [1.09-1.45], diabetes >3 years (nested case-control OR: 1.57 [1.13-2.18], case-control OR: 1.80 [1.40-2.32], family history of pancreatic cancer (OR: 1.60 [1.20-2.12], non-O ABO genotype (AO vs. OO genotype (OR: 1.23 [1.10-1.37] to (BB vs. OO genotype (OR 1.58 [0.97-2.59], rs3790844(chr1q32.1 (OR: 1.29 [1.19-1.40], rs401681(5p15.33 (OR: 1.18 [1.10-1.26] and rs9543325(13q22.1 (OR: 1.27 [1.18-1.36]. The areas under the ROC curve for risk models including only non-genetic factors, only genetic factors, and both non-genetic and genetic factors were 58%, 57% and 61%, respectively. We estimate that fewer than 3/1,000 U.S. non-Hispanic whites have more than a 5% predicted lifetime absolute risk. CONCLUSION: Although absolute risk modeling using established risk factors may help to identify a group of individuals at higher than average risk of pancreatic cancer, the immediate clinical utility of our model is limited. However, a risk model can increase awareness of the various risk factors for pancreatic cancer, including modifiable behaviors.

  3. 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.

  4. Identifying barriers to HIV testing: personal and contextual factors associated with late HIV testing.

    Science.gov (United States)

    Schwarcz, Sandra; Richards, T Anne; Frank, Heidi; Wenzel, Conrad; Hsu, Ling Chin; Chin, Chi-Sheng Jennie; Murphy, Jessie; Dilley, James

    2011-07-01

    Late diagnosis of HIV is associated with increased morbidity, mortality, and health care costs. Despite the availability of HIV testing, persons continue to test late in the course of HIV infection. We used the HIV/AIDS case registry of San Francisco Department of Public Health to identify and recruit 41 persons who developed AIDS within 12 months of their HIV diagnosis to participate in a qualitative and quantitative interview regarding late diagnosis of HIV. Thirty-one of the participants were diagnosed with HIV because of symptomatic disease and 50% of the participants were diagnosed with HIV and AIDS concurrently. Half of the subjects had not been tested for HIV prior to diagnosis. Fear was the most frequently cited barrier to testing. Other barriers included being unaware of improved HIV treatment, free/low cost care, and risk for HIV. Recommendations for health care providers to increase early diagnosis of HIV include routine ascertainment of HIV risk behaviors and testing histories, stronger recommendations for patients to be tested, and incorporating testing into routine medical care. Public health messages to increase testing include publicizing that (1) effective, tolerable, and low cost/free care for HIV is readily available, (2) early diagnosis of HIV improves health outcomes, (3) HIV can be transmitted to persons who engage in unprotected oral and insertive anal sex and unprotected receptive anal intercourse without ejaculation and from HIV-infected persons whose infection is well-controlled with antiretroviral therapy, (4) persons who may be infected based upon these behaviors should be tested following exposure, (5) HIV testing information will be kept private, and (6) encouraging friends and family to get HIV tested is beneficial.

  5. Identifying sources and controlling factors of arsenic release in saline groundwater aquifers

    Directory of Open Access Journals (Sweden)

    C.-W. Liu

    2013-08-01

    Full Text Available An integrated hydrogeochemical study is carried out to realize the occurrence of arsenic (As in a saline aquifer. Saline groundwater was mostly concentrated in the uppermost aquifer and non-saline water was in the lower aquifer in the study area. High As concentrations were found in both uppermost and lower aquifers. No correlation among salination, well depth and As concentration was observed. Both reducing and oxidizing forms of Fe oxyhydroxides were identified in the magnetic fractions, which were concentrated by high gradient magnetic separation (HGMS technique, revealing that the redox cycling of Fe occurred in the subsurface. High levels of Fe, HCO3-, DOC and NH4+ concentrations accompanying alkaline pH in the As-rich groundwater were consistent with the mechanism triggered by the microbial-mediated reductive dissolution of Fe oxyhydroxides. A threshold value of 50 μg L−1. As concentration was used as an indicator for identification of active proceeding reductive dissolution of As-bearing Fe oxyhydroxides in the saline aquifer. Desorption behaviors of As were relevant to its valence in the sediments and the co-existence of anions. Experimental and numerical results showed that additions of Cl- and SO42-, which represented the main anions of saline water, had minor effect on leaching sedimentary As. Although bicarbonate addition resulted in less As desorption than that of phosphate on a molar basis, the contribution of bicarbonate to the total release of As was greater than phosphate due to the much higher concentration of bicarbonate in groundwater and the associated microbial mediation. Collectively, the chemical effect of saline water on the As-release to groundwater is mild in the coastal aquifer.

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

    Science.gov (United States)

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

    2014-07-01

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

  7. 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.

  8. Analytic validity of genetic tests to identify factor V Leiden and prothrombin G20210A.

    Science.gov (United States)

    Emadi, Ashkan; Crim, Matthew T; Brotman, Daniel J; Necochea, Alejandro J; Samal, Lipika; Wilson, Lisa M; Bass, Eric B; Segal, Jodi B

    2010-04-01

    The objective of this study is to systematically review methods for detecting Factor V Leiden or prothrombin G20210A. English-language literature from MEDLINE, EMBASE, The Cochrane Library, the Cumulative Index to Nursing and Allied Health Literature, PsycInfo(c), 2000-December 2008. Studies assessed methods for detection of these mutations in at least 10 human blood samples and reported concordance, discordance, or reproducibility. Two investigators abstracted data on the sample selection criteria, test operators, DNA extraction, experimental test, reference standard, commercial instruments, concordance rates, explanation of any discordance, and whether discordance resolved after repetition. We assessed strength of the evidence using the GRADE criteria. We reviewed 7,777 titles and included 66 articles. The majority of the reviewed studies used PCR-RFLP or AS-PCR as the reference standard. The studies demonstrated that commercially available and precommercial tests have high analytic validity with all having greater than 99% concordance with the reference standard. With a few exceptions, discordance resolved with repetition of the test, suggesting operator or administrative errors were responsible for the discordant results. In the quality assurance studies, greater than 98% of laboratories demonstrated high, even perfect, accuracy when asked to diagnose a sample with a known mutation. The majority of errors came from a limited number of laboratories. Although not all methods may be accurate, there is high-grade evidence that genetic tests for the detection of FVL and prothrombin G20210A have excellent analytic validity. There is high-grade evidence that most, but not all, clinical laboratories test for FVL and prothrombin G20210A accurately.

  9. Improvement in prediction of coronary heart disease risk over conventional risk factors using SNPs identified in genome-wide association studies.

    Directory of Open Access Journals (Sweden)

    Jennifer L Bolton

    Full Text Available OBJECTIVE: We examined whether a panel of SNPs, systematically selected from genome-wide association studies (GWAS, could improve risk prediction of coronary heart disease (CHD, over-and-above conventional risk factors. These SNPs have already demonstrated reproducible associations with CHD; here we examined their use in long-term risk prediction. STUDY DESIGN AND SETTING: SNPs identified from meta-analyses of GWAS of CHD were tested in 840 men and women aged 55-75 from the Edinburgh Artery Study, a prospective, population-based study with 15 years of follow-up. Cox proportional hazards models were used to evaluate the addition of SNPs to conventional risk factors in prediction of CHD risk. CHD was classified as myocardial infarction (MI, coronary intervention (angioplasty, or coronary artery bypass surgery, angina and/or unspecified ischaemic heart disease as a cause of death; additional analyses were limited to MI or coronary intervention. Model performance was assessed by changes in discrimination and net reclassification improvement (NRI. RESULTS: There were significant improvements with addition of 27 SNPs to conventional risk factors for prediction of CHD (NRI of 54%, P<0.001; C-index 0.671 to 0.740, P = 0.001, as well as MI or coronary intervention, (NRI of 44%, P<0.001; C-index 0.717 to 0.750, P = 0.256. ROC curves showed that addition of SNPs better improved discrimination when the sensitivity of conventional risk factors was low for prediction of MI or coronary intervention. CONCLUSION: There was significant improvement in risk prediction of CHD over 15 years when SNPs identified from GWAS were added to conventional risk factors. This effect may be particularly useful for identifying individuals with a low prognostic index who are in fact at increased risk of disease than indicated by conventional risk factors alone.

  10. A review on statistical models for identifying climate contributions to crop yields

    Institute of Scientific and Technical Information of China (English)

    SHI Wenjiao; TAO Fulu; ZHANG Zhao

    2013-01-01

    Statistical models using historical data on crop yields and weather to calibrate relatively simple regression equations have been widely and extensively applied in previous studies,and have provided a common alternative to process-based models,which require extensive input data on cultivar,management,and soil conditions.However,very few studies had been conducted to review systematically the previous statistical models for indentifying climate contributions to crop yields.This paper introduces three main statistical methods,i.e.,time-series model,cross-section model and panel model,which have been used to identify such issues in the field of agrometeorology.Generally,research spatial scale could be categorized into two types using statistical models,including site scale and regional scale (e.g.global scale,national scale,provincial scale and county scale).Four issues exist in identifying response sensitivity of crop yields to climate change by statistical models.The issues include the extent of spatial and temporal scale,non-climatic trend removal,colinearity existing in climate variables and non-consideration of adaptations.Respective resolutions for the above four issues have been put forward in the section of perspective on the future of statistical models finally.

  11. Hypersensitivity Reactions to Oxaliplatin: Identifying the Risk Factors and Judging the Efficacy of a Desensitization Protocol.

    Science.gov (United States)

    Okayama, Tetsuya; Ishikawa, Takeshi; Sugatani, Kazuko; Yoshida, Naohisa; Kokura, Satoshi; Matsuda, Kiyomi; Tsukamoto, Shigeru; Ihara, Norihiko; Kuriu, Yoshiaki; Nakanishi, Masayoshi; Nakamura, Terukazu; Kamada, Kazuhiro; Katada, Kazuhiro; Uchiyama, Kazuhiko; Takagi, Tomohisa; Handa, Osamu; Konishi, Hideyuki; Yagi, Nobuaki; Naito, Yuji; Otsuji, Eigo; Hosoi, Hajime; Miki, Tsuneharu; Itoh, Yoshito

    2015-06-01

    We examined the clinical data of patients treated with oxaliplatin to determine the risk factors of oxaliplatin-related hypersensitivity reaction (HSR). In addition, we evaluated the efficacy of rechallenging patients with HSRs with oxaliplatin using prophylactic agents or desensitization procedures. This study consisted of 162 patients with colorectal cancer (88 men and 74 women) who were treated consecutively at the outpatient chemotherapy department at University Hospital, Kyoto Prefectural University of Medicine. Patients underwent chemotherapy, including oxaliplatin, between March 2006 and June 2012. We analyzed the patients' clinical backgrounds (eg, age, sex, performance status, disease stage, and allergic history) to uncover any connections to the development of HSR to oxaliplatin. In addition, we rechallenged 10 patients who had oxaliplatin-related HSR using prophylactic agents or desensitization procedures. Of 162 patients, 28 (17.2%) developed oxaliplatin-related HSRs (16, 2, 9 and 1 patient had grade 1, 2, 3, and 4 HSRs, respectively). The total cumulative dose of oxaliplatin at the onset of the HSR was 301 to 1126 mg/m(2) (median, 582 mg/m(2)), and the first reactions developed in these patients after 5 to 17 infusions of oxaliplatin (median, 8 infusions). Logistic regression analysis indicated that sex (male: odds ratio = 3.624; 95% CI, 1.181-11.122; P = 0.024) and eosinophil count in peripheral blood (odds ratio = 35.118; 95% CI, 1.058-1166.007; P = 0.046) were independent variables for oxaliplatin-related HSRs. Rechallenging patients with prophylactic agents was successful in 2 (28.6%) of 7 patients who successfully completed their treatment. On the other hand, all 3 patients rechallenged with oxaliplatin using a desensitization protocol successfully completed their treatment without new HSRs. In this retrospective study, we observed that being male and having higher counts of peripheral eosinophil could be predictors for HSR to oxaliplatin. In

  12. Identifying rock blocks based on hierarchical rock-mass structure model

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    Rock-masses are divided into many closed blocks by deterministic and stochastic discontinuities and engineering interfaces in complex rock-mass engineering. Determining the sizes, shapes, and adjacent relations of blocks is important for stability analysis of fractured rock masses. Here we propose an algorithm for identifying spatial blocks based on a hierarchical 3D Rock-mass Structure Model (RSM). First, a model is built composed of deterministic discontinuities, engineering interfaces, and the earth’s surface, and the deterministic blocks surrounded by these interfaces are traced. Then, in each deter-ministic block, a network model of stochastic discontinuities is built and the stochastic blocks are traced. Building a unitary wire frame that connects all interfaces seamlessly is the key for our algorithm to identify the above two kinds of blocks. Using this algorithm, geometric models can be built for block theory, discrete element method, and discontinuous deformation analysis.

  13. Proneurogenic Ligands Defined by Modeling Developing Cortex Growth Factor Communication Networks.

    Science.gov (United States)

    Yuzwa, Scott A; Yang, Guang; Borrett, Michael J; Clarke, Geoff; Cancino, Gonzalo I; Zahr, Siraj K; Zandstra, Peter W; Kaplan, David R; Miller, Freda D

    2016-09-01

    The neural stem cell decision to self-renew or differentiate is tightly regulated by its microenvironment. Here, we have asked about this microenvironment, focusing on growth factors in the embryonic cortex at a time when it is largely comprised of neural precursor cells (NPCs) and newborn neurons. We show that cortical NPCs secrete factors that promote their maintenance, while cortical neurons secrete factors that promote differentiation. To define factors important for these activities, we used transcriptome profiling to identify ligands produced by NPCs and neurons, cell-surface mass spectrometry to identify receptors on these cells, and computational modeling to integrate these data. The resultant model predicts a complex growth factor environment with multiple autocrine and paracrine interactions. We tested this communication model, focusing on neurogenesis, and identified IFNγ, Neurturin (Nrtn), and glial-derived neurotrophic factor (GDNF) as ligands with unexpected roles in promoting neurogenic differentiation of NPCs in vivo.

  14. A model to identify high crash road segments with the dynamic segmentation method.

    Science.gov (United States)

    Boroujerdian, Amin Mirza; Saffarzadeh, Mahmoud; Yousefi, Hassan; Ghassemian, Hassan

    2014-12-01

    Currently, high social and economic costs in addition to physical and mental consequences put road safety among most important issues. This paper aims at presenting a novel approach, capable of identifying the location as well as the length of high crash road segments. It focuses on the location of accidents occurred along the road and their effective regions. In other words, due to applicability and budget limitations in improving safety of road segments, it is not possible to recognize all high crash road segments. Therefore, it is of utmost importance to identify high crash road segments and their real length to be able to prioritize the safety improvement in roads. In this paper, after evaluating deficiencies of the current road segmentation models, different kinds of errors caused by these methods are addressed. One of the main deficiencies of these models is that they can not identify the length of high crash road segments. In this paper, identifying the length of high crash road segments (corresponding to the arrangement of accidents along the road) is achieved by converting accident data to the road response signal of through traffic with a dynamic model based on the wavelet theory. The significant advantage of the presented method is multi-scale segmentation. In other words, this model identifies high crash road segments with different lengths and also it can recognize small segments within long segments. Applying the presented model into a real case for identifying 10-20 percent of high crash road segment showed an improvement of 25-38 percent in relative to the existing methods.

  15. Global analysis of WRKY transcription factor superfamily in Setaria identifies potential candidates involved in abiotic stress signalling

    Directory of Open Access Journals (Sweden)

    Mehanathan eMuthamilarasan

    2015-10-01

    Full Text Available Transcription factors (TFs are major players in stress signalling and constitute an integral part of signalling networks. Among the major TFs, WRKY proteins play pivotal roles in regulation of transcriptional reprogramming associated with stress responses. In view of this, genome- and transcriptome-wide identification of WRKY TF family was performed in the C4 model plants, Setaria italica (SiWRKY and S. viridis (SvWRKY, respectively. The study identified 105 SiWRKY and 44 SvWRKY proteins that were computationally analysed for their physicochemical properties. Sequence alignment and phylogenetic analysis classified these proteins into three major groups, namely I, II and III with majority of WRKY proteins belonging to group II (53 SiWRKY and 23 SvWRKY, followed by group III (39 SiWRKY and 11 SvWRKY and group I (10 SiWRKY and 6 SvWRKY. Group II proteins were further classified into 5 subgroups (IIa to IIe based on their phylogeny. Domain analysis showed the presence of WRKY motif and zinc finger-like structures in these proteins along with additional domains in a few proteins. All SiWRKY genes were physically mapped on the S. italica genome and their duplication analysis revealed that 10 and 8 gene pairs underwent tandem and segmental duplications, respectively. Comparative mapping of SiWRKY and SvWRKY genes in related C4 panicoid genomes demonstrated the orthologous relationships between these genomes. In silico expression analysis of SiWRKY and SvWRKY genes showed their differential expression patterns in different tissues and stress conditions. Expression profiling of candidate SiWRKY genes in response to stress (dehydration and salinity and hormone treatments (abscisic acid, salicylic acid and methyl jasmonate suggested the putative involvement of SiWRKY066 and SiWRKY082 in stress and hormone signalling. These genes could be potential candidates for further characterization to delineate their functional roles in abiotic stress signalling.

  16. Identifying and Quantifying Emergent Behavior Through System of Systems Modeling and Simulation

    Science.gov (United States)

    2015-09-01

    EMERGENT BEHAVIOR THROUGH SYSTEM OF SYSTEMS MODELING AND SIMULATION by Mary Ann Cummings September 2015 Dissertation Supervisor: Man-Tak Shing...COVERED Ph.D. Dissertation 4. TITLE AND SUBTITLE IDENTIFYING AND QUANTIFYING EMERGENT BEHAVIOR THROUGH SYSTEM OF SYSTEMS MODELING AND SIMULATION 5...functionality and interfaces in these SoSs. An inherent deficiency of existing M&S approaches, however, lies in the emergent behavior that occurs as a result of

  17. Combat-Related Heterotopic Ossification: Development of Animal Models for Identifying Mechanisms and Testing Therapeutics

    Science.gov (United States)

    2016-03-01

    etiology, treatment, and prevention is the absence of a reliable and reproducible small animal model that can be used to characterize combat‐related HO...contamination and subsequent wound colonization may be a key risk factor. Using a small animal model of blast-related extremity injury involving a...to the systemic and perhaps local antimicrobial therapies geared towards decreasing bioburden in combat wounds. 6 Using our blast-related HO

  18. Transcriptome analyses identify five transcription factors differentially expressed in the hypothalamus of post- versus prepubertal Brahman heifers.

    Science.gov (United States)

    Fortes, M R S; Nguyen, L T; Weller, M M D C A; Cánovas, A; Islas-Trejo, A; Porto-Neto, L R; Reverter, A; Lehnert, S A; Boe-Hansen, G B; Thomas, M G; Medrano, J F; Moore, S S

    2016-09-01

    Puberty onset is a developmental process influenced by genetic determinants, environment, and nutrition. Mutations and regulatory gene networks constitute the molecular basis for the genetic determinants of puberty onset. The emerging knowledge of these genetic determinants presents opportunities for innovation in the breeding of early pubertal cattle. This paper presents new data on hypothalamic gene expression related to puberty in (Brahman) in age- and weight-matched heifers. Six postpubertal heifers were compared with 6 prepubertal heifers using whole-genome RNA sequencing methodology for quantification of global gene expression in the hypothalamus. Five transcription factors (TF) with potential regulatory roles in the hypothalamus were identified in this experiment: , , , , and . These TF genes were significantly differentially expressed in the hypothalamus of postpubertal versus prepubertal heifers and were also identified as significant according to the applied regulatory impact factor metric ( Brahman). Knowledge of key mutations involved in genetic traits is an advantage for genomic prediction because it can increase its accuracy.

  19. Investigation of gene-environment interactions between 47 newly identified breast cancer susceptibility loci and environmental risk factors

    DEFF Research Database (Denmark)

    Rudolph, Anja; Milne, Roger L; Truong, Thérèse

    2015-01-01

    A large genotyping project within the Breast Cancer Association Consortium (BCAC) recently identified 41 associations between single nucleotide polymorphisms (SNPs) and overall breast cancer (BC) risk. We investigated whether the effects of these 41 SNPs, as well as six SNPs associated with estro......A large genotyping project within the Breast Cancer Association Consortium (BCAC) recently identified 41 associations between single nucleotide polymorphisms (SNPs) and overall breast cancer (BC) risk. We investigated whether the effects of these 41 SNPs, as well as six SNPs associated...... with estrogen receptor (ER) negative BC risk are modified by 13 environmental risk factors for BC. Data from 22 studies participating in BCAC were pooled, comprising up to 26,633 cases and 30,119 controls. Interactions between SNPs and environmental factors were evaluated using an empirical Bayes-type shrinkage...

  20. Identifying Basic Factors for Communal Prosperity - Space Technologies are Bridging this Gap

    Science.gov (United States)

    Habib, Shahid

    2006-01-01

    There are many aspects, which are important for maintaining environmentally clean and safe conditions for a healthy and economically self-sufficient community. This problem was somewhat of a lesser concern in earlier days because many communities were small, isolated and solely dependent upon their owners or landlords. Due to an astronomical growth in human population within the last century, extensive use of combustion technologies, and changing environmental conditions has resulted in scarcity of natural resources. In reality, the societal sustainability issues are becoming much more acute and complex. Therefore, the researchers and social scientists are joining forces to address these topics and find solutions to many contentious areas such as public health and diseases, water resources, agriculture production, survivability during and after the natural disasters, energy needs and many others. Forthrightly speaking, there is no canned solution or a methodology to go about solving these issues since the magnitude and complexity of these issues are multi-dimensional and are further inter-locked with other areas. A common sense tells us that we need data, resources and technologies to begin addressing these problems. This is where space observations have provided us with tremendous information and opportunities, which are of great assets to the science, economist, and social scientists. This paper specifically addresses what are critical areas for a successful societal sustainability and growth; and how can we take advantage of multiple sensors and models already in existence. Increasing our knowledge of the home planet, via amplified set of observations, is certainly a right step in a right direction. Furthermore, this is a pre-requisite in understanding multiple hazard phenomena's. This paper further examines various space sensors and observing architectures that can be useful specifically in addressing some of these complex issues. The ultimate goal is to serve

  1. Human factors engineering program review model

    Energy Technology Data Exchange (ETDEWEB)

    1994-07-01

    The staff of the Nuclear Regulatory Commission is performing nuclear power plant design certification reviews based on a design process plan that describes the human factors engineering (HFE) program elements that are necessary and sufficient to develop an acceptable detailed design specification and an acceptable implemented design. There are two principal reasons for this approach. First, the initial design certification applications submitted for staff review did not include detailed design information. Second, since human performance literature and industry experiences have shown that many significant human factors issues arise early in the design process, review of the design process activities and results is important to the evaluation of an overall design. However, current regulations and guidance documents do not address the criteria for design process review. Therefore, the HFE Program Review Model (HFE PRM) was developed as a basis for performing design certification reviews that include design process evaluations as well as review of the final design. A central tenet of the HFE PRM is that the HFE aspects of the plant should be developed, designed, and evaluated on the basis of a structured top-down system analysis using accepted HFE principles. The HFE PRM consists of ten component elements. Each element in divided into four sections: Background, Objective, Applicant Submittals, and Review Criteria. This report describes the development of the HFE PRM and gives a detailed description of each HFE review element.

  2. Identifying an appropriate measurement modeling approach for the Mini-Mental State Examination.

    Science.gov (United States)

    Rubright, Jonathan D; Nandakumar, Ratna; Karlawish, Jason

    2016-02-01

    The Mini-Mental State Examination (MMSE) is a 30-item, dichotomously scored test of general cognition. A number of benefits could be gained by modeling the MMSE in an item response theory (IRT) framework, as opposed to the currently used classical additive approach. However, the test, which is built from groups of items related to separate cognitive subdomains, may violate a key assumption of IRT: local item independence. This study aimed to identify the most appropriate measurement model for the MMSE: a unidimensional IRT model, a testlet response theory model, or a bifactor model. Local dependence analysis using nationally representative data showed a meaningful violation of the local item independence assumption, indicating multidimensionality. In addition, the testlet and bifactor models displayed superior fit indices over a unidimensional IRT model. Statistical comparisons showed that the bifactor model fit MMSE respondent data significantly better than the other models considered. These results suggest that application of a traditional unidimensional IRT model is inappropriate in this context. Instead, a bifactor model is suggested for future modeling of MMSE data as it more accurately represents the multidimensional nature of the scale. (PsycINFO Database Record

  3. A survey of PPR proteins identifies DYW domains like those of land plant RNA editing factors in diverse eukaryotes

    OpenAIRE

    Schallenberg-Rüdinger, Mareike; Lenz, Henning; Polsakiewicz, Monika; Gott, Jonatha M.; Knoop, Volker

    2013-01-01

    The pentatricopeptide repeat modules of PPR proteins are key to their sequence-specific binding to RNAs. Gene families encoding PPR proteins are greatly expanded in land plants where hundreds of them participate in RNA maturation, mainly in mitochondria and chloroplasts. Many plant PPR proteins contain additional carboxyterminal domains and have been identified as essential factors for specific events of C-to-U RNA editing, which is abundant in the two endosymbiotic plant organelles. Among th...

  4. Evaluation of an inpatient fall risk screening tool to identify the most critical fall risk factors in inpatients.

    Science.gov (United States)

    Hou, Wen-Hsuan; Kang, Chun-Mei; Ho, Mu-Hsing; Kuo, Jessie Ming-Chuan; Chen, Hsiao-Lien; Chang, Wen-Yin

    2017-03-01

    To evaluate the accuracy of the inpatient fall risk screening tool and to identify the most critical fall risk factors in inpatients. Variations exist in several screening tools applied in acute care hospitals for examining risk factors for falls and identifying high-risk inpatients. Secondary data analysis. A subset of inpatient data for the period from June 2011-June 2014 was extracted from the nursing information system and adverse event reporting system of an 818-bed teaching medical centre in Taipei. Data were analysed using descriptive statistics, receiver operating characteristic curve analysis and logistic regression analysis. During the study period, 205 fallers and 37,232 nonfallers were identified. The results revealed that the inpatient fall risk screening tool (cut-off point of ≥3) had a low sensitivity level (60%), satisfactory specificity (87%), a positive predictive value of 2·0% and a negative predictive value of 99%. The receiver operating characteristic curve analysis revealed an area under the curve of 0·805 (sensitivity, 71·8%; specificity, 78%). To increase the sensitivity values, the Youden index suggests at least 1·5 points to be the most suitable cut-off point for the inpatient fall risk screening tool. Multivariate logistic regression analysis revealed a considerably increased fall risk in patients with impaired balance and impaired elimination. The fall risk factor was also significantly associated with days of hospital stay and with admission to surgical wards. The findings can raise awareness about the two most critical risk factors for falls among future clinical nurses and other healthcare professionals and thus facilitate the development of fall prevention interventions. This study highlights the needs for redefining the cut-off points of the inpatient fall risk screening tool to effectively identify inpatients at a high risk of falls. Furthermore, inpatients with impaired balance and impaired elimination should be closely

  5. 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

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

    Directory of Open Access Journals (Sweden)

    H. C. Winsemius

    2006-01-01

    Full Text Available Variations of water stocks in the upper Zambezi river basin have been determined by 2 different hydrological modelling approaches. The purpose was to provide preliminary terrestrial storage estimates in the upper Zambezi, which will be compared with estimates derived from the Gravity Recovery And Climate Experiment (GRACE in a future study. The first modelling approach is GIS-based, distributed and conceptual (STREAM. The second approach uses Lumped Elementary Watersheds identified and modelled conceptually (LEW. The STREAM model structure has been assessed using GLUE (Generalized Likelihood Uncertainty Estimation a posteriori to determine parameter identifiability. The LEW approach could, in addition, be tested for model structure, because computational efforts of LEW are low. Both models are threshold models, where the non-linear behaviour of the Zambezi river basin is explained by a combination of thresholds and linear reservoirs. The models were forced by time series of gauged and interpolated rainfall. Where available, runoff station data was used to calibrate the models. Ungauged watersheds were generally given the same parameter sets as their neighbouring calibrated watersheds. It appeared that the LEW model structure could be improved by applying GLUE iteratively. Eventually, it led to better identifiability of parameters and consequently a better model structure than the STREAM model. Hence, the final model structure obtained better represents the true hydrology. After calibration, both models show a comparable efficiency in representing discharge. However the LEW model shows a far greater storage amplitude than the STREAM model. This emphasizes the storage uncertainty related to hydrological modelling in data-scarce environments such as the Zambezi river basin. It underlines the need and potential for independent observations of terrestrial storage to enhance our understanding and modelling capacity of the hydrological processes. GRACE

  7. An Identifiable State Model To Describe Light Intensity Influence on Microalgae Growth.

    Science.gov (United States)

    Bernardi, A; Perin, G; Sforza, E; Galvanin, F; Morosinotto, T; Bezzo, F

    2014-04-23

    Despite the high potential as feedstock for the production of fuels and chemicals, the industrial cultivation of microalgae still exhibits many issues. Yield in microalgae cultivation systems is limited by the solar energy that can be harvested. The availability of reliable models representing key phenomena affecting algae growth may help designing and optimizing effective production systems at an industrial level. In this work the complex influence of different light regimes on seawater alga Nannochloropsis salina growth is represented by first principles models. Experimental data such as in vivo fluorescence measurements are employed to develop the model. The proposed model allows description of all growth curves and fluorescence data in a reliable way. The model structure is assessed and modified in order to guarantee the model identifiability and the estimation of its parametric set in a robust and reliable way.

  8. Using Frequent Item Set Mining and Feature Selection Methods to Identify Interacted Risk Factors - The Atrial Fibrillation Case Study.

    Science.gov (United States)

    Li, Xiang; Liu, Haifeng; Du, Xin; Hu, Gang; Xie, Guotong; Zhang, Ping

    2016-01-01

    Disease risk prediction is highly important for early intervention and treatment, and identification of predictive risk factors is the key point to achieve accurate prediction. In addition to original independent features in a dataset, some interacted features, such as comorbidities and combination therapies, may have non-additive influence on the disease outcome and can also be used in risk prediction to improve the prediction performance. However, it is usually difficult to manually identify the possible interacted risk factors due to the combination explosion of features. In this paper, we propose an automatic approach to identify predictive risk factors with interactions using frequent item set mining and feature selection methods. The proposed approach was applied in the real world case study of predicting ischemic stroke and thromboembolism for atrial fibrillation patients on the Chinese atrial fibrillation registry dataset, and the results show that our approach can not only improve the prediction performance, but also identify the comorbidities and combination therapies that have potential influences on TE occurrence for AF.

  9. 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 va...

  10. Animal model for identifying therapetucually useful compounds for the treatment of sporadic amyotrophic lateral sclerosis

    OpenAIRE

    Gil Ayuso-Gontán, Carmen; Martínez, Ana

    2012-01-01

    [EN] The invention relates to a method for identifying compounds that are potentially useful for the treatment of sporadic amyotrophic lateral sclerosis (ALS), comprising the use of an animal model of rats, developed by means of the administration of β-Ν-methylamino-L-alanine (L-BMAA)

  11. Animal model for identifying therapetucually useful compounds for the treatment of sporadic amyotrophic lateral sclerosis

    OpenAIRE

    Gil, Carmen; Martínez, Ana

    2012-01-01

    [EN] The invention relates to a method for identifying compounds that are potentially useful for the treatment of sporadic amyotrophic lateral sclerosis (ALS), comprising the use of an animal model of rats, developed by means of the administration of β-Ν-methylamino-L-alanine (L-BMAA)

  12. Research on identifying the dynamic error model of strapdown gyro on 3-axis turntable

    Institute of Scientific and Technical Information of China (English)

    WANG Hai; REN Shun-qing; WANG Chang-hong

    2005-01-01

    The dynamic errors of gyros are the important error sources of a strapdown inertial navigation system.In order to identify the dynamic error model coefficients accurately, the static erTor model coefficients which lay a foundation for compensating while identifying the dynamic error model are identified in the gravity acceleration fields by using angular position function of the three-axis turntable. The angular acceleration and angular velocity are excited on the input, output and spin axis of the gyros when the outer axis and the middle axis of a threeaxis turntable are in the uniform angular velocity state simultaneously, while the inner axis of the turntable is in different static angular positions. 8 groups of data are sampled when the inner axis is in 8 different angular positions. These data are the function of the middle axis positions and the inner axis positions. For these data, harmonic analysis method is applied two times versus the middle axis positions and inner axis positions respectively so that the dynamic error model coefficients are finally identified through the least square method. In the meantime the optimal angular velocity of the outer axis and the middle axis are selected by computing the determination value of the information matrix.

  13. 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.

  14. Modelling evapotranspiration during precipitation deficits: identifying critical processes in a land surface model

    Science.gov (United States)

    Ukkola, Anna M.; Pitman, Andy J.; Decker, Mark; De Kauwe, Martin G.; Abramowitz, Gab; Kala, Jatin; Wang, Ying-Ping

    2016-06-01

    Surface fluxes from land surface models (LSMs) have traditionally been evaluated against monthly, seasonal or annual mean states. The limited ability of LSMs to reproduce observed evaporative fluxes under water-stressed conditions has been previously noted, but very few studies have systematically evaluated these models during rainfall deficits. We evaluated latent heat fluxes simulated by the Community Atmosphere Biosphere Land Exchange (CABLE) LSM across 20 flux tower sites at sub-annual to inter-annual timescales, in particular focusing on model performance during seasonal-scale rainfall deficits. The importance of key model processes in capturing the latent heat flux was explored by employing alternative representations of hydrology, leaf area index, soil properties and stomatal conductance. We found that the representation of hydrological processes was critical for capturing observed declines in latent heat during rainfall deficits. By contrast, the effects of soil properties, LAI and stomatal conductance were highly site-specific. Whilst the standard model performs reasonably well at annual scales as measured by common metrics, it grossly underestimates latent heat during rainfall deficits. A new version of CABLE, with a more physically consistent representation of hydrology, captures the variation in the latent heat flux during seasonal-scale rainfall deficits better than earlier versions, but remaining biases point to future research needs. Our results highlight the importance of evaluating LSMs under water-stressed conditions and across multiple plant functional types and climate regimes.

  15. Universal screening for cardiovascular disease risk factors in adolescents to identify high-risk families: a population-based cross-sectional study.

    Science.gov (United States)

    Khoury, Michael; Manlhiot, Cedric; Gibson, Don; Chahal, Nita; Stearne, Karen; Dobbin, Stafford; McCrindle, Brian W

    2016-01-21

    Universal screening of children for dyslipidemia and other cardiovascular risk factors has been recommended. Given the clustering of cardiovascular risk factors within families, one benefit of screening adolescents may be to identify "at-risk" families in which adult members might also be at elevated risk and potentially benefit from medical evaluation. Cross-sectional study of grade 9 students evaluating adiposity, lipids and blood pressure. Data collected by Heart Niagara Inc. through the Healthy Heart Schools' Program. Parents completed questionnaires, evaluating family history of dyslipidemia, hypertension, diabetes and early cardiovascular disease events in parents and siblings (first-degree relatives), and grandparents (second-degree relatives). Associations between positive risk factor findings in adolescents and presence of a positive family history were assessed in logistic regression models. N = 4014 adolescents ages 14-15 years were screened; 3467 (86 %) provided family medical history. Amongst adolescents, 4.7 % had dyslipidemia, 9.5 % had obesity, and 3.5 % had elevated blood pressure. Central adiposity (waist-to-height ratio ≥0.5) in the adolescent was associated with increased odds of diabetes in first- (OR:2.0 (1.6-2.6), p identify increased odds of a positive family history. Presence of obesity and/or dyslipidemia in adolescents identified through a universal school-based screening program is associated with risk factor clustering within families. Universal pediatric cardiometabolic screening may be an effective entry into reverse cascade screening.

  16. A genome-wide screen for spatially restricted expression patterns identifies transcription factors that regulate glial development

    NARCIS (Netherlands)

    Fu, H.; Cai, J.; Clevers, H.; Fast, E.; Gray, S.; Greenberg, R.; Jain, M.K.; Ma, Q.; Qiu, M.; Rowitch, D.H.; Taylor, C.; Stiles, C.D.

    2009-01-01

    Forward genetic screens in genetically accessible invertebrate organisms such as Drosophila melanogaster have shed light on transcription factors that specify formation of neurons in the vertebrate CNS. However, invertebrate models have, to date, been uninformative with respect to genes that specify

  17. IDENTIFYING OPERATIONAL REQUIREMENTS TO SELECT SUITABLE DECISION MODELS FOR A PUBLIC SECTOR EPROCUREMENT DECISION SUPPORT SYSTEM

    Directory of Open Access Journals (Sweden)

    Mohamed Adil

    2014-10-01

    Full Text Available Public sector procurement should be a transparent and fair process. Strict legal requirements are enforced on public sector procurement to make it a standardised process. To make fair decisions on selecting suppliers, a practical method which adheres to legal requirements is important. The research that is the base for this paper aimed at identifying a suitable Multi-Criteria Decision Analysis (MCDA method for the specific legal and functional needs of the Maldivian Public Sector. To identify such operational requirements, a set of focus group interviews were conducted in the Maldives with public officials responsible for procurement decision making. Based on the operational requirements identified through focus groups, criteria-based evaluation is done on published MCDA methods to identify the suitable methods for e-procurement decision making. This paper describes the identification of the operational requirements and the results of the evaluation to select suitable decision models for the Maldivian context.

  18. A Modified Reverse One-Hybrid Screen Identifies Transcriptional Activation Domains in PHYTOCHROME-INTERACTING FACTOR 3.

    Science.gov (United States)

    Dalton, Jutta C; Bätz, Ulrike; Liu, Jason; Curie, Gemma L; Quail, Peter H

    2016-01-01

    Transcriptional activation domains (TADs) are difficult to predict and identify, since they are not conserved and have little consensus. Here, we describe a yeast-based screening method that is able to identify individual amino acid residues involved in transcriptional activation in a high throughput manner. A plant transcriptional activator, PIF3 (phytochrome interacting factor 3), was fused to the yeast GAL4-DNA-binding Domain (BD), driving expression of the URA3 (Orotidine 5'-phosphate decarboxylase) reporter, and used for negative selection on 5-fluroorotic acid (5FOA). Randomly mutagenized variants of PIF3 were then selected for a loss or reduction in transcriptional activation activity by survival on FOA. In the process, we developed a strategy to eliminate false positives from negative selection that can be used for both reverse-1- and 2-hybrid screens. With this method we were able to identify two distinct regions in PIF3 with transcriptional activation activity, both of which are functionally conserved in PIF1, PIF4, and PIF5. Both are collectively necessary for full PIF3 transcriptional activity, but neither is sufficient to induce transcription autonomously. We also found that the TAD appear to overlap physically with other PIF3 functions, such as phyB binding activity and consequent phosphorylation. Our protocol should provide a valuable tool for identifying, analyzing and characterizing novel TADs in eukaryotic transcription factors, and thus potentially contribute to the unraveling of the mechanism underlying transcriptional activation.

  19. A Modified Reverse One-Hybrid Screen Identifies Transcriptional Activation Domains in PHYTOCHROME-INTERACTING FACTOR 3

    Science.gov (United States)

    Dalton, Jutta C.; Bätz, Ulrike; Liu, Jason; Curie, Gemma L.; Quail, Peter H.

    2016-01-01

    Transcriptional activation domains (TADs) are difficult to predict and identify, since they are not conserved and have little consensus. Here, we describe a yeast-based screening method that is able to identify individual amino acid residues involved in transcriptional activation in a high throughput manner. A plant transcriptional activator, PIF3 (phytochrome interacting factor 3), was fused to the yeast GAL4-DNA-binding Domain (BD), driving expression of the URA3 (Orotidine 5′-phosphate decarboxylase) reporter, and used for negative selection on 5-fluroorotic acid (5FOA). Randomly mutagenized variants of PIF3 were then selected for a loss or reduction in transcriptional activation activity by survival on FOA. In the process, we developed a strategy to eliminate false positives from negative selection that can be used for both reverse-1- and 2-hybrid screens. With this method we were able to identify two distinct regions in PIF3 with transcriptional activation activity, both of which are functionally conserved in PIF1, PIF4, and PIF5. Both are collectively necessary for full PIF3 transcriptional activity, but neither is sufficient to induce transcription autonomously. We also found that the TAD appear to overlap physically with other PIF3 functions, such as phyB binding activity and consequent phosphorylation. Our protocol should provide a valuable tool for identifying, analyzing and characterizing novel TADs in eukaryotic transcription factors, and thus potentially contribute to the unraveling of the mechanism underlying transcriptional activation. PMID:27379152

  20. Identifying Critical Factors of Sale Failure on Commercial Property Types, Shop Houses by Using Multi Attribute Variable Technique

    Directory of Open Access Journals (Sweden)

    N.I. Mohamad

    2014-04-01

    Full Text Available The focus of this research is to identify the critical factors of shop houses sale failure in Bandar Baru Nilai and further up to discover the critical factors of sale failure of commercial property types, shop houses in new township as report by valuation and Property services department (JPPH showed 5,931 units of shop houses in Malaysia is currently completed but remained unsold where Johor was recorded as the highest with unsold units followed by Negeri Sembilan. Bandar Baru Nilai (a district of Negeri Sembilan is chosen as research sample for unsold shop houses units due to its strategic location which is near to KLIA, International Sepang Circuit, educational instituitions and surrounded by housing scheme but yet still has numbers of unsold units. Data of the research is obtained from literature review and survey question between developers, local authority, purchasers/tenant and local residents. Relative Importance Index (RII method is applied in identifying the critical factor of shop houses sale failure. Generally, the factors of sale failure are economy, demography, politic, location and access, public and basic facilities, financial loan, physical of product, current stock of shop houses upon completion, future potential of subsale and rental, developer’s background, promotion and marketing, speculation and time.

  1. Investigation of gene-environment interactions between 47 newly identified breast cancer susceptibility loci and environmental risk factors.

    Science.gov (United States)

    Rudolph, Anja; Milne, Roger L; Truong, Thérèse; Knight, Julia A; Seibold, Petra; Flesch-Janys, Dieter; Behrens, Sabine; Eilber, Ursula; Bolla, Manjeet K; Wang, Qin; Dennis, Joe; Dunning, Alison M; Shah, Mitul; Munday, Hannah R; Darabi, Hatef; Eriksson, Mikael; Brand, Judith S; Olson, Janet; Vachon, Celine M; Hallberg, Emily; Castelao, J Esteban; Carracedo, Angel; Torres, Maria; Li, Jingmei; Humphreys, Keith; Cordina-Duverger, Emilie; Menegaux, Florence; Flyger, Henrik; Nordestgaard, Børge G; Nielsen, Sune F; Yesilyurt, Betul T; Floris, Giuseppe; Leunen, Karin; Engelhardt, Ellen G; Broeks, Annegien; Rutgers, Emiel J; Glendon, Gord; Mulligan, Anna Marie; Cross, Simon; Reed, Malcolm; Gonzalez-Neira, Anna; Arias Perez, José Ignacio; Provenzano, Elena; Apicella, Carmel; Southey, Melissa C; Spurdle, Amanda; Häberle, Lothar; Beckmann, Matthias W; Ekici, Arif B; Dieffenbach, Aida Karina; Arndt, Volker; Stegmaier, Christa; McLean, Catriona; Baglietto, Laura; Chanock, Stephen J; Lissowska, Jolanta; Sherman, Mark E; Brüning, Thomas; Hamann, Ute; Ko, Yon-Dschun; Orr, Nick; Schoemaker, Minouk; Ashworth, Alan; Kosma, Veli-Matti; Kataja, Vesa; Hartikainen, Jaana M; Mannermaa, Arto; Swerdlow, Anthony; Giles, Graham G; Brenner, Hermann; Fasching, Peter A; Chenevix-Trench, Georgia; Hopper, John; Benítez, Javier; Cox, Angela; Andrulis, Irene L; Lambrechts, Diether; Gago-Dominguez, Manuela; Couch, Fergus; Czene, Kamila; Bojesen, Stig E; Easton, Doug F; Schmidt, Marjanka K; Guénel, Pascal; Hall, Per; Pharoah, Paul D P; Garcia-Closas, Montserrat; Chang-Claude, Jenny

    2015-03-15

    A large genotyping project within the Breast Cancer Association Consortium (BCAC) recently identified 41 associations between single nucleotide polymorphisms (SNPs) and overall breast cancer (BC) risk. We investigated whether the effects of these 41 SNPs, as well as six SNPs associated with estrogen receptor (ER) negative BC risk are modified by 13 environmental risk factors for BC. Data from 22 studies participating in BCAC were pooled, comprising up to 26,633 cases and 30,119 controls. Interactions between SNPs and environmental factors were evaluated using an empirical Bayes-type shrinkage estimator. Six SNPs showed interactions with associated p-values (pint ) factors and the observed potential interactions require confirmation in independent studies.

  2. Using electroretinograms and multi-model inference to identify spectral classes of photoreceptors and relative opsin expression levels

    Directory of Open Access Journals (Sweden)

    Nicolas Lessios

    2017-07-01

    Full Text Available Understanding how individual photoreceptor cells factor in the spectral sensitivity of a visual system is essential to explain how they contribute to the visual ecology of the animal in question. Existing methods that model the absorption of visual pigments use templates which correspond closely to data from thin cross-sections of photoreceptor cells. However, few modeling approaches use a single framework to incorporate physical parameters of real photoreceptors, which can be fused, and can form vertical tiers. Akaike’s information criterion (AICc was used here to select absorptance models of multiple classes of photoreceptor cells that maximize information, given visual system spectral sensitivity data obtained using extracellular electroretinograms and structural parameters obtained by histological methods. This framework was first used to select among alternative hypotheses of photoreceptor number. It identified spectral classes from a range of dark-adapted visual systems which have between one and four spectral photoreceptor classes. These were the velvet worm, Principapillatus hitoyensis, the branchiopod water flea, Daphnia magna, normal humans, and humans with enhanced S-cone syndrome, a condition in which S-cone frequency is increased due to mutations in a transcription factor that controls photoreceptor expression. Data from the Asian swallowtail, Papilio xuthus, which has at least five main spectral photoreceptor classes in its compound eyes, were included to illustrate potential effects of model over-simplification on multi-model inference. The multi-model framework was then used with parameters of spectral photoreceptor classes and the structural photoreceptor array kept constant. The goal was to map relative opsin expression to visual pigment concentration. It identified relative opsin expression differences for two populations of the bluefin killifish, Lucania goodei. The modeling approach presented here will be useful in

  3. Applying psychological theories to evidence-based clinical practice: Identifying factors predictive of managing upper respiratory tract infections without antibiotics

    Directory of Open Access Journals (Sweden)

    Glidewell Elizabeth

    2007-08-01

    try to avoid the use of antibiotics made significantly fewer scenario-based decisions to prescribe. In the cross theory analysis, perceived behavioural control (TPB, evidence of habitual behaviour (OLT, CS-SRM cause (chance/bad luck, and intention entered the equation, together explaining 36% of the variance. When predicting intention, at the theory level, the proportion of variance explained was: TPB, 30%; SCT, 29%; CS-SRM 27%; OLT, 43%. GPs who reported that they had already decided to change their management to try to avoid the use of antibiotics had a significantly higher intention to manage URTIs without prescribing antibiotics. In the cross theory analysis, OLT evidence of habitual behaviour, TPB attitudes, risk perception, CS-SRM control by doctor, TPB perceived behavioural control and CS-SRM control by treatment entered the equation, together explaining 49% of the variance in intention. Conclusion The study provides evidence that psychological models can be useful in understanding and predicting clinical behaviour. Taking a theory-based approach enables the creation of a replicable methodology for identifying factors that predict clinical behaviour. However, a number of conceptual and methodological challenges remain.

  4. 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.

  5. Evidence for a General Factor Model of ADHD in Adults

    Science.gov (United States)

    Gibbins, Christopher; Toplak, Maggie E.; Flora, David B.; Weiss, Margaret D.; Tannock, Rosemary

    2012-01-01

    Objective: To examine factor structures of "Diagnostic and Statistical Manual of Mental Disorders" (4th ed.) symptoms of ADHD in adults. Method: Two sets of models were tested: (a) models with inattention and hyperactivity/impulsivity as separate but correlated latent constructs and (b) hierarchical general factor models with a general factor for…

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

    DEFF Research Database (Denmark)

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

    2017-01-01

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

  7. 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.

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

    Science.gov (United States)

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

    2017-01-01

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

  9. Genome-wide expression profiling of five mouse models identifies similarities and differences with human psoriasis.

    Directory of Open Access Journals (Sweden)

    William R Swindell

    Full Text Available