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Sample records for models identified factors

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

    NARCIS (Netherlands)

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

    1994-01-01

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

  2. Use of model plant hosts to identify Pseudomonas aeruginosa virulence factors

    Science.gov (United States)

    Rahme, Laurence G.; Tan, Man-Wah; Le, Long; Wong, Sandy M.; Tompkins, Ronald G.; Calderwood, Stephen B.; Ausubel, Frederick M.

    1997-01-01

    We used plants as an in vivo pathogenesis model for the identification of virulence factors of the human opportunistic pathogen Pseudomonas aeruginosa. Nine of nine TnphoA mutant derivatives of P. aeruginosa strain UCBPP-PA14 that were identified in a plant leaf assay for less pathogenic mutants also exhibited significantly reduced pathogenicity in a burned mouse pathogenicity model, suggesting that P. aeruginosa utilizes common strategies to infect both hosts. Seven of these nine mutants contain TnphoA insertions in previously unknown genes. These results demonstrate that an alternative nonvertebrate host of a human bacterial pathogen can be used in an in vivo high throughput screen to identify novel bacterial virulence factors involved in mammalian pathogenesis. PMID:9371831

  3. 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.

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

    International Nuclear Information System (INIS)

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

    2014-01-01

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

  5. 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.

  6. Conceptual model to identify factors with influence in Brazilian beef consumption

    Directory of Open Access Journals (Sweden)

    Fernanda Scharnberg Brandão

    2015-06-01

    Full Text Available The complexity of the consumers' behavior has taken the food industry to a new level of dynamism. Therefore, understanding the factors that influence this behavior is decisive for the differentiation of products to niche markets and even to adjust the supply according to consumers' expectancy. This article proposes a conceptual model to identify the factors influencing beef consumption in Brazil. The methodological approach was characterized by a systematic review through a synthesis of research related directly to this topic. Therefore, 76 papers published during the 2000-2014 period, including official documents (statistics, full research papers, abstracts, proceedings, and reports, were selected. Four main factors were related to influences in consumer behavior and/or directly in beef consumption: sociocultural, economic, health/food, and environmental. Among these dimensions, there was an emphasis on recent publications related to health/food and the environment. The compilation and analysis of these papers enabled the conception of the proposed model and suggests the consideration of four main dimensions in beef consumption.

  7. 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.

  8. Testing job typologies and identifying at-risk subpopulations using factor mixture models.

    Science.gov (United States)

    Keller, Anita C; Igic, Ivana; Meier, Laurenz L; Semmer, Norbert K; Schaubroeck, John M; Brunner, Beatrice; Elfering, Achim

    2017-10-01

    Research in occupational health psychology has tended to focus on the effects of single job characteristics or various job characteristics combined into 1 factor. However, such a variable-centered approach does not account for the clustering of job attributes among groups of employees. We addressed this issue by using a person-centered approach to (a) investigate the occurrence of different empirical constellations of perceived job stressors and resources and (b) validate the meaningfulness of profiles by analyzing their association with employee well-being and performance. We applied factor mixture modeling to identify profiles in 4 large samples consisting of employees in Switzerland (Studies 1 and 2) and the United States (Studies 3 and 4). We identified 2 profiles that spanned the 4 samples, with 1 reflecting a combination of relatively low stressors and high resources (P1) and the other relatively high stressors and low resources (P3). The profiles differed mainly in terms of their organizational and social aspects. Employees in P1 reported significantly higher mean levels of job satisfaction, performance, and general health, and lower means in exhaustion compared with P3. Additional analyses showed differential relationships between job attributes and outcomes depending on profile membership. These findings may benefit organizational interventions as they show that perceived work stressors and resources more strongly influence satisfaction and well-being in particular profiles. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  9. 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.

  10. Staphylococcus aureus virulence factors identified by using a high-throughput Caenorhabditis elegans-killing model.

    Science.gov (United States)

    Begun, Jakob; Sifri, Costi D; Goldman, Samuel; Calderwood, Stephen B; Ausubel, Frederick M

    2005-02-01

    Staphylococcus aureus is an important human pathogen that is also able to kill the model nematode Caenorhabditis elegans. We constructed a 2,950-member Tn917 transposon insertion library in S. aureus strain NCTC 8325. Twenty-one of these insertions exhibited attenuated C. elegans killing, and of these, 12 contained insertions in different genes or chromosomal locations. Ten of these 12 insertions showed attenuated killing phenotypes when transduced into two different S. aureus strains, and 5 of the 10 mutants correspond to genes that have not been previously identified in signature-tagged mutagenesis studies. These latter five mutants were tested in a murine renal abscess model, and one mutant harboring an insertion in nagD exhibited attenuated virulence. Interestingly, Tn917 was shown to have a very strong bias for insertions near the terminus of DNA replication.

  11. [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.

  12. 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.

  13. Testing job typologies and identifying at-risk subpopulations using factor mixture models

    NARCIS (Netherlands)

    Keller, A. C.; Igic, Ivana; Meier, Laurenz L.; Semmer, N. K.; Schaubroeck, J.; Brunner, Beatrice; Elfering, Achim

    2017-01-01

    Research in occupational health psychology has tended to focus on the effects of single job characteristics or various job characteristics combined into 1 factor. However, such a variable-centered approach does not account for the clustering of job attributes among groups of employees. We addressed

  14. 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...... for inhibition of cell growth may provide leads for the development of efficient cancer treatment strategies....

  15. [Conceptual model for identifying factors relevant to the safety of children in school buses].

    Science.gov (United States)

    Bernal, Martha Lucía; Daza, Carolina; Rincón, Ovidio

    2010-06-01

    Prepare a conceptual model that facilitates understanding of the relationships between the variables that lead children to adopt postures in school transportation vehicles that increase injuries in traffic accidents. For identification of the variables, direct information on school transportation was collected through focus groups, with bus aides and bus drivers, on-board filming during the transport of children, and recording of the dimensions of components in different types of school buses. The information collected was analyzed using the Atlas.ti v6 software and the construction of a model through deduction. Important relationships were found between adoption of potentially hazardous postures by children during transport to and from school and the seat and seat belt dimensions, the characteristics of the transportation service, and the role of bus aides. In order to adopt coherent interventions in school transportation safety, it is necessary to consider not only the technical aspects of the vehicle or posture that are controlled in crash tests but the specific variables of the activities that lead children to adopt postures that put them at greater risk of injury.

  16. Sparse Linear Identifiable Multivariate Modeling

    DEFF Research Database (Denmark)

    Henao, Ricardo; Winther, Ole

    2011-01-01

    In this paper we consider sparse and identifiable linear latent variable (factor) and linear Bayesian network models for parsimonious analysis of multivariate data. We propose a computationally efficient method for joint parameter and model inference, and model comparison. It consists of a fully...... Bayesian hierarchy for sparse models using slab and spike priors (two-component δ-function and continuous mixtures), non-Gaussian latent factors and a stochastic search over the ordering of the variables. The framework, which we call SLIM (Sparse Linear Identifiable Multivariate modeling), is validated...... computational complexity. We attribute this mainly to the stochastic search strategy used, and to parsimony (sparsity and identifiability), which is an explicit part of the model. We propose two extensions to the basic i.i.d. linear framework: non-linear dependence on observed variables, called SNIM (Sparse Non-linear...

  17. Identifying personality subtypes based on the five-factor model dimensions in male prisoners: implications for psychopathy and criminal offending.

    Science.gov (United States)

    Claes, Laurence; Tavernier, Geert; Roose, Annelore; Bijttebier, Patricia; Smith, Sarah Francis; Lilienfeld, Scott O

    2014-01-01

    The current study was designed to identify personality subtypes on the basis of the five-factor model dimensions in male prisoners. Participants included 110 Flemish male prisoners assessed by means of the Neuroticism, Extraversion, Openness Five Factor Inventory and different symptom, personality, and coping measures. We found two clusters: an emotionally stable/resilient cluster and an aggressive/undercontrolled cluster. Prisoners within the aggressive/undercontrolled cluster scored significantly higher on almost all Minnesota Multiphasic Personality Inventory-2 basic scales, (in)direct aggression measures, and depressive coping scales compared with resilients. They also scored higher on drug abuse and committed more sexual offenses than resilient prisoners. These two personality subtypes bear theoretically and practically important implications for psychopathy subtypes and different pathways to criminal offenses.

  18. Modeling Nitrous Oxide emissions and identifying emission controlling factors for a spruce forest ecosystem on drained organic soil

    Science.gov (United States)

    He, Hongxing; Kasimir, Åsa; Jansson, Per-Erik; Svensson, Magnus; Meyer, Astrid; Klemedtsson, Leif

    2015-04-01

    High Nitrous Oxide (N2O) emission has been identified in hemiboreal forests on drained organic soils. However, the controlling factors regulating the emissions have been unclear. To examine the importance of different factors on the N2O emission in a spruce forest on drained organic soil, a process-based model, CoupModel, was calibrated by the generalized likelihood uncertainty estimation (GLUE) method. The calibrated model reproduced most of the high resolution data (total net radiation, soil temperature, groundwater level, net ecosystem exchange, etc.) very well, as well as accumulated measured N2O emissions, but showed difficulties to capture all the measured emission peaks. Parameter uncertainties could be reduced by combining selected criteria with the measurement data. The model showed the N2O emissions during the summer to be controlled mainly by the competition between plants and microbes while during the winter season snow melt periods are important. The simulated N budget shows >100 kg N ha-1 yr-1 to be in circulation between soil and plants and back again. Each year the peat mineralization adds about 60 kg N ha-1 and atmospheric deposition 12 kg N ha-1. Most of the mineralized litter and peat N is directly taken up by the plants but only a part accumulates in the plant biomass. As long as no timber is harvested the main N loss from the system is through nitrate leaching (30 kg N ha-1 yr-1) and gas emissions (20 kg N ha-1 yr-1), 55% as NO, 27% as N2O and 18% as N2. Regarding N2O gas emissions, our modeling indicates denitrification to be the most responsible process, of the size 6 kg N ha-1 yr-1, which could be compared to 0.04 kg N ha-1 yr-1 from nitrification. Our modelling also reveal 88% of the N2O mainly to be produced by denitrification in the capillary fringe (c.a. 40-60 cm below soil surface) of the anaerobic zone using nitrate produced in the upper more aerobic layers. We conclude N2O production/emission to be controlled mainly by the complex

  19. Using Dynamic Walking Models to Identify Factors that Contribute to Increased Risk of Falling in Older Adults

    Science.gov (United States)

    Roos, Paulien E.; Dingwell, Jonathan B.

    2013-01-01

    Falls are common in older adults. The most common cause of falls is tripping while walking. Simulation studies demonstrated that older adults may be restricted by lower limb strength and movement speed to regain balance after a trip. This review examines how modeling approaches can be used to determine how different measures predict actual fall risk and what some of the causal mechanisms of fall risk are. Although increased gait variability predicts increased fall risk experimentally, it is not clear which variability measures could best be used, or what magnitude of change corresponded with increased fall risk. With a simulation study we showed that the increase in fall risk with a certain increase in gait variability was greatly influenced by the initial level of variability. Gait variability can therefore not easily be used to predict fall risk. We therefore explored other measures that may be related to fall risk and investigated the relationship between stability measures such as Floquet multipliers and local divergence exponents and actual fall risk in a dynamic walking model. We demonstrated that short-term local divergence exponents were a good early predictor for fall risk. Neuronal noise increases with age. It has however not been fully understood if increased neuronal noise would cause an increased fall risk. With our dynamic walking model we showed that increased neuronal noise caused increased fall risk. Although people who are at increased risk of falling reduce their walking speed it had been questioned whether this slower speed would actually cause a reduced fall risk. With our model we demonstrated that a reduced walking speed caused a reduction in fall risk. This may be due to the decreased kinematic variability as a result of the reduced signal-dependent noise of the smaller muscle forces that are required for slower. These insights may be used in the development of fall prevention programs in order to better identify those at increased risk of

  20. Using dynamic walking models to identify factors that contribute to increased risk of falling in older adults.

    Science.gov (United States)

    Roos, Paulien E; Dingwell, Jonathan B

    2013-10-01

    Falls are common in older adults. The most common cause of falls is tripping while walking. Simulation studies demonstrated that older adults may be restricted by lower limb strength and movement speed to regain balance after a trip. This review examines how modeling approaches can be used to determine how different measures predict actual fall risk and what some of the causal mechanisms of fall risk are. Although increased gait variability predicts increased fall risk experimentally, it is not clear which variability measures could best be used, or what magnitude of change corresponded with increased fall risk. With a simulation study we showed that the increase in fall risk with a certain increase in gait variability was greatly influenced by the initial level of variability. Gait variability can therefore not easily be used to predict fall risk. We therefore explored other measures that may be related to fall risk and investigated the relationship between stability measures such as Floquet multipliers and local divergence exponents and actual fall risk in a dynamic walking model. We demonstrated that short-term local divergence exponents were a good early predictor for fall risk. Neuronal noise increases with age. It has however not been fully understood if increased neuronal noise would cause an increased fall risk. With our dynamic walking model we showed that increased neuronal noise caused increased fall risk. Although people who are at increased risk of falling reduce their walking speed it had been questioned whether this slower speed would actually cause a reduced fall risk. With our model we demonstrated that a reduced walking speed caused a reduction in fall risk. This may be due to the decreased kinematic variability as a result of the reduced signal-dependent noise of the smaller muscle forces that are required for slower. These insights may be used in the development of fall prevention programs in order to better identify those at increased risk of

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

    Science.gov (United States)

    Kim, Go-Un; Seo, Kyong-Hwan

    2018-01-01

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

  2. Identifying Some Risk Factors for the Time to Death of the Elderly Using the Semi-Parametric Blended Model of Survival Analysis With Competing Risks

    Directory of Open Access Journals (Sweden)

    Samane Hajiabbasi

    2018-01-01

    Conclusion In single-variable fitting, age, history of myocardial infarction, history of stroke, and kidney problems were identified to have significant effects on the time to death of the elderly. Based on one-variable semi-parametric competing risk mixture fitted models, more significant risk factors for the time to death of elderly was identified when compared with a fitted multivariate mode to the data. This implies that the role of some independent variables can be explained by other independent variables.

  3. 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)

    2014-01-01

    Background 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. Methods 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 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. Conclusions The autologistic regression model was used to identify spatial risk factors and model spatial risk patterns of HFMD. HFMD

  4. 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

  5. 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.

  6. Causal Modeling of Cancer-Stromal Communication Identifies PAPPA as a Novel Stroma-Secreted Factor Activating NFκB Signaling in Hepatocellular Carcinoma

    Science.gov (United States)

    Engelmann, Julia C.; Amann, Thomas; Ott-Rötzer, Birgitta; Nützel, Margit; Reinders, Yvonne; Reinders, Jörg; Thasler, Wolfgang E.; Kristl, Theresa; Teufel, Andreas; Huber, Christian G.; Oefner, Peter J.

    2015-01-01

    Inter-cellular communication with stromal cells is vital for cancer cells. Molecules involved in the communication are potential drug targets. To identify them systematically, we applied a systems level analysis that combined reverse network engineering with causal effect estimation. Using only observational transcriptome profiles we searched for paracrine factors sending messages from activated hepatic stellate cells (HSC) to hepatocellular carcinoma (HCC) cells. We condensed these messages to predict ten proteins that, acting in concert, cause the majority of the gene expression changes observed in HCC cells. Among the 10 paracrine factors were both known and unknown cancer promoting stromal factors, the former including Placental Growth Factor (PGF) and Periostin (POSTN), while Pregnancy-Associated Plasma Protein A (PAPPA) was among the latter. Further support for the predicted effect of PAPPA on HCC cells came from both in vitro studies that showed PAPPA to contribute to the activation of NFκB signaling, and clinical data, which linked higher expression levels of PAPPA to advanced stage HCC. In summary, this study demonstrates the potential of causal modeling in combination with a condensation step borrowed from gene set analysis [Model-based Gene Set Analysis (MGSA)] in the identification of stromal signaling molecules influencing the cancer phenotype. PMID:26020769

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

    Science.gov (United States)

    Liu, Tianyang; Hao, Xiaoning; Zhang, Zhenzhong

    2016-11-15

    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. 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. 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. In Beijing, China, aging care arrangement preference is the

  8. 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

  9. 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

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

    OpenAIRE

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

    2014-01-01

    Background 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. Methods HFMD re...

  11. A Study of the Effects of a Culturally-Based Dance Education Model on Identified Stress Factors in American Indian College Women.

    Science.gov (United States)

    Skye, Ferial Deer; And Others

    1989-01-01

    Finds that, among 39 American Indian college women, those who participated in a 4-week dance education program incorporating cultural support symbols showed significantly lower posttest trait anxiety than controls but did not differ from controls in posttest state anxiety. Reports stress factors identified from subjects' questionnaire responses.…

  12. Application of a Mechanistic Model to Evaluate Putative Mechanisms of Tolvaptan Drug-Induced Liver Injury and Identify Patient Susceptibility Factors.

    Science.gov (United States)

    Woodhead, Jeffrey L; Brock, William J; Roth, Sharin E; Shoaf, Susan E; Brouwer, Kim L R; Church, Rachel; Grammatopoulos, Tom N; Stiles, Linsey; Siler, Scott Q; Howell, Brett A; Mosedale, Merrie; Watkins, Paul B; Shoda, Lisl K M

    2017-01-01

    Tolvaptan is a selective vasopressin V2 receptor antagonist, approved in several countries for the treatment of hyponatremia and autosomal dominant polycystic kidney disease (ADPKD). No liver injury has been observed with tolvaptan treatment in healthy subjects and in non-ADPKD indications, but ADPKD clinical trials showed evidence of drug-induced liver injury (DILI). Although all DILI events resolved, additional monitoring in tolvaptan-treated ADPKD patients is required. In vitro assays identified alterations in bile acid disposition and inhibition of mitochondrial respiration as potential mechanisms underlying tolvaptan hepatotoxicity. This report details the application of DILIsym software to determine whether these mechanisms could account for the liver safety profile of tolvaptan observed in ADPKD clinical trials. DILIsym simulations included physiologically based pharmacokinetic estimates of hepatic exposure for tolvaptan and2 metabolites, and their effects on hepatocyte bile acid transporters and mitochondrial respiration. The frequency of predicted alanine aminotransferase (ALT) elevations, following simulated 90/30  mg split daily dosing, was 7.9% compared with clinical observations of 4.4% in ADPKD trials. Toxicity was multifactorial as inhibition of bile acid transporters and mitochondrial respiration contributed to the simulated DILI. Furthermore, simulation analysis identified both pre-treatment risk factors and on-treatment biomarkers predictive of simulated DILI. The simulations demonstrated that in vivo hepatic exposure to tolvaptan and the DM-4103 metabolite, combined with these 2 mechanisms of toxicity, were sufficient to account for the initiation of tolvaptan-mediated DILI. Identification of putative risk-factors and potential novel biomarkers provided insight for the development of mechanism-based tolvaptan risk-mitigation strategies. © The Author 2016. Published by Oxford University Press on behalf of the Society of Toxicology.

  13. Recently Identified Factors that Regulate Hemostasis and Thrombosis

    Science.gov (United States)

    Geddings, Julia E; Mackman, Nigel

    2014-01-01

    The blood coagulation cascade is essential for hemostasis but excessive activation can cause thrombosis. Importantly, recent studies have identified factors that contribute to thrombosis but not hemostasis. These include factor XII (FXII), tissue factor-positive microparticles (MPs) and neutrophil extracellular traps (NETs). Recent studies have shown that FXII plays a role in thrombosis but not hemostasis. FXII is activated in vivo by a variety of negatively-charged polyphosphates, which include extracellular RNA, DNA and inorganic polyphosphate (PolyP) that are released during cell damage and infection. These findings have triggered the development of nucleic acid-binding polymers as a new class of anticoagulant drug. Other studies have analyzed the role of MPs in experimental thrombosis. MPs are small membrane vesicles released from activated or apoptotic cells. We and others have found that tissue factor-positive MPs enhance thrombosis in mouse models and are elevated in the plasma of pancreatic cancer patients. Finally, NETs have been shown to contribute to experimental venous thrombosis in mouse models and are present in human thrombi. NETs are composed of chromatin fibers that are released from neutrophils undergoing cell death. NETs can capture platelets and increase fibrin deposition. The recent advances in our understanding of the factors contributing to thrombosis in animal models provide new opportunities for the development of safer anticoagulant drugs. PMID:24573314

  14. Exploiting intrinsic fluctuations to identify model parameters.

    Science.gov (United States)

    Zimmer, Christoph; Sahle, Sven; Pahle, Jürgen

    2015-04-01

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

  15. 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

  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

  17. Identifying nonproportional covariates in the Cox model

    Czech Academy of Sciences Publication Activity Database

    Kraus, David

    2008-01-01

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

  18. Identifying factors affecting destination choice of medical tourists: a ...

    African Journals Online (AJOL)

    medical tourism”, has emerged as a new source of competitive advantage all over the world. The present study seeks to identify the factors that affect destination choice of medical tourists. Methods: We systematically searched relevant databases ...

  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. Asthma trajectories in early childhood: identifying modifiable factors.

    Science.gov (United States)

    Panico, Lidia; Stuart, Beth; Bartley, Mel; Kelly, Yvonne

    2014-01-01

    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. 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. 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. 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. We identified correlated intervenable pathways in infancy

  1. 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.

  2. 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...

  3. Effectiveness of a structured checklist of risk factors in identifying ...

    African Journals Online (AJOL)

    Background: Gestational diabetes mellitus (GDM) is associated with increased risk of mortality and morbidity for pregnant women and newborns. Identifying pregnant women with risk factors for GDM based on the clinical suspicion is a popular approach. However, the effectiveness of the use of a structured checklist of risk ...

  4. Identifying factors affecting about outsourcing in paraclinical services

    African Journals Online (AJOL)

    Objective: Outsourcing refers to the transfer of services or functions to an outsider supplier, which controls them through a contract or cooperative. The main problem of senior managers in health organizations is determining the services which should be outsourced. The present study seeks to identify the factors that affect ...

  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. Lung cancer and risk factors: how to identify phenotypic markers?

    International Nuclear Information System (INIS)

    Clement-Duchene, Christelle

    2009-01-01

    Lung cancer is the leading cause of death in the world. Most lung cancer are diagnosed at an advanced stage (IIIB and IV), with a poor prognosis. The main risk factors are well known like active smoking, and occupational exposure (asbestos), but 10 a 20% occur in never smokers. In this population, various studies have been conducted in order to identify possible risk factors, and although many have been identified, none seem to explain more than a small percentage of the cases. According to the histological types, adenocarcinoma is now the more frequent type, and its association with the main risk factors (tobacco exposure, asbestos exposure) is still studied. The tumoral location is associated with the exposure to the risk factors. Finally, the survival seems to be different between gender, and between smokers, and never smokers. All these characteristics are perhaps associated with different pathways of carcinogenesis. In this context, we have analyzed a cohort of 1493 patients with lung cancer in order to identify phenotypic markers, and to understand the mechanisms of the lung carcinogenesis. (author) [fr

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

    Science.gov (United States)

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

    2007-05-01

    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 analysis of the data was performed to establish a framework of factors that influence workplace learning, within which framework comparisons between groups could be made. A framework consisting of 56 factors was identified. These were grouped into 10 categories, which in turn were grouped into four domains: the working environment, educational factors in the workplace, NHPT characteristics and supervisor characteristics. Of the factors that influence workplace learning, social integration was cited most often. Supervisors more often reported educational factors and NHPTs more frequently reported impediments. The educational relationship may be improved when supervisors explicitly discuss the learning process and learning conditions within the workplace, thereby focusing on the NHPT needs. Special attention should be paid to the aspects of social integration. A good start could be to answer the question regarding how to establish a basic feeling of 'knowing where you are' and 'how to go about things' to make residents feel comfortable enough to focus on the learning process.

  8. Newly identified risk factors for MRSA carriage in The Netherlands.

    Directory of Open Access Journals (Sweden)

    W S N Lekkerkerk

    Full Text Available To elucidate new risk factors for MRSA carriers without known risk factors (MRSA of unknown origin; MUO. These MUO carriers are neither pre-emptively screened nor isolated as normally dictated by the Dutch Search & Destroy policy, thus resulting in policy failure.We performed a prospective case control study to determine risk factors for MUO acquisition/carriage (Dutch Trial Register: NTR2041. Cases were MUO carriers reported by participating medical microbiological laboratories to the RIVM from September 1st 2011 until September 1st 2013. Controls were randomly selected from the community during this period.Significant risk factors for MUO in logistic multivariate analysis were antibiotic use in the last twelve months, aOR 8.1 (5.6-11.7, screened as contact in a contact tracing but not detected as a MRSA carrier at that time, aOR 4.3 (2.1-8.8, having at least one foreign parent, aOR 2.4 (1.4-3.9 and receiving ambulatory care, aOR 2.3 (1.4-3.7. Our found risk factors explained 83% of the MUO carriage.Identifying new risk factors for MRSA carriers remains crucial for countries that apply a targeted screening approach as a Search and Destroy policy or as vertical infection prevention measure.

  9. Identifiable risk factors in hepatitis b and c

    International Nuclear Information System (INIS)

    Rehman, F.U.; Pervez, A.; Rafiq, A.

    2011-01-01

    Background: Both hepatitis B and C are common infections affecting masses and are leading causes of Chronic Liver Disease in Pakistan as well as worldwide. In majority of cases both viral diseases spread by factors that are preventable. The present study is conducted to determine the identifiable risk factors in patients admitted with Chronic Hepatitis B and C. Methods: An observational study was carried out for a period of 6 months. All age groups and both sexes were included. The patients were interviewed and the identifiable risk factors were looked for. The standard methods for detection of Hepatitis B and C were used. Results: One-hundred and ten patients were studied from January to July 2009. Sixty-five patients had Hepatitis C, 35 had Hepatitis B, and 10 had both Hepatitis B and C. Ninety-three patients had a history of injections and transfusions etc., and 38 had surgical scars. Tattoos were present in 42 patients and nose and/or ear piercing marks were present in 28 patients. The number of risk factors increased in co-infection. Conclusion: There is a role of unhygienic health delivery practices, lack of awareness and resources for standard screening protocol for spread of Hepatitis B and C. (author)

  10. 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.

  11. IDENTIFIABILITY VERSUS HETEROGENEITY IN GROUNDWATER MODELING SYSTEMS

    Directory of Open Access Journals (Sweden)

    A M BENALI

    2003-06-01

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

  12. Uncomplicated Acute Diverticulitis: Identifying Risk Factors for Severe Outcomes.

    Science.gov (United States)

    Jaung, Rebekah; Kularatna, Malsha; Robertson, Jason P; Vather, Ryash; Rowbotham, David; MacCormick, Andrew D; Bissett, Ian P

    2017-09-01

    The management of uncomplicated (Modified Hinchey Classification Ia) acute diverticulitis (AD) has become increasingly conservative, with a focus on symptomatic relief and supportive management. Clear criteria for patient selection are required to implement this safely. This retrospective study aimed to identify risk factors for severe clinical course in patients with uncomplicated AD. Patients admitted to General Surgery at two New Zealand tertiary centres over a period of 18 months were included. Univariate and multivariate analyses were carried out in order to identify factors associated with a more severe clinical course. This was defined by three endpoints: need for procedural intervention, admission >7 days and 30-day readmission; these were analysed separately and as a combined outcome. Uncomplicated AD was identified in 319 patients. Fifteen patients (5%) required procedural intervention; this was associated with SIRS (OR 3.92). Twenty-two (6.9%) patients were admitted for >7 days; this was associated with patient-reported pain score >8/10 (OR 5.67). Thirty-one patients (9.8%) required readmission within 30 days; this was associated with pain score >8/10 (OR 6.08) and first episode of AD (OR 2.47). Overall, 49 patients had a severe clinical course, and associated factors were regular steroid/immunomodulator use (OR 4.34), pain score >8/10 (OR 5.9) and higher temperature (OR 1.51) and CRP ≥200 (OR 4.1). SIRS, high pain score and CRP, first episode and regular steroid/immunomodulator use were identified as predictors of worse outcome in uncomplicated AD. These findings have the potential to inform prospective treatment decisions in this patient group.

  13. 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

  14. 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.

  15. Identifying Factors Associated With Mobility Decline Among Hospitalized Older Adults.

    Science.gov (United States)

    Chase, Jo-Ana D; Lozano, Alicia; Hanlon, Alexandra; Bowles, Kathryn H

    2018-02-01

    Hospitalization can negatively affect mobility among older adults. Early detection of older patients most at risk for mobility decline can lead to early intervention and prevention of mobility loss. This study's purpose was to identify factors from the International Classification of Functioning, Disability, and Health associated with mobility decline among hospitalized elders. We conducted a secondary analysis of data from 959 hospitalized adults age 65 and older. We estimated the effects of health conditions and environmental and personal factors on mobility decline using logistic regression. Almost half of the sample declined in mobility function during hospitalization. Younger age, longer length of hospital stay, having a hearing impairment, and non-emergency admit type were associated with mobility decline, after adjusting for covariates. Findings may be used to develop an evidence-based, risk-determination tool for hospitalized elders. Future research should focus on individual, environmental, and policy-based interventions promoting physical activity in the hospital.

  16. Identifying factors that promote functional aging in Caenorhabditis elegans.

    Science.gov (United States)

    Wolkow, Catherine A

    2006-10-01

    A major feature of aging is a reduction in muscle strength from sarcopenia, the loss of muscle mass. Sarcopenia impairs physical ability, reduces quality of life and increases the risk of fall and injury. Since aging is a process of stochastic decline, there may be many factors that impinge on the progression of sarcopenia. Possible factors that may promote muscle decline are contraction-related injury and oxidative stress. However, relatively little is understood about the cellular pathways affecting muscle aging, in part because lifespan studies are difficult to conduct in species with large muscles, such as rodents and primates. For this reason, shorter-lived invertebrate models of aging may be more useful for unraveling causes of sarcopenia and functional declines during aging. Recent studies have examined both physiological and genetic factors that affect aging-related declines in Caenorhabditis elegans nematodes. In C. elegans, aging leads to significant functional declines that correlate with muscle deterioration, similar to those documented for longer-lived vertebrates. This article will examine the current research into aging-related functional declines in this species, focusing on recent studies of locomotory and feeding decline during aging in the nematode, C. elegans.

  17. Modelo conceptual para identificar factores relevantes en la seguridad de los niños en los autobuses escolares Conceptual model for identifying factors relevant to the safety of children in school buses

    Directory of Open Access Journals (Sweden)

    Martha Lucía Bernal

    2010-06-01

    Full Text Available OBJETIVO: Elaborar un modelo conceptual que permita comprender las relaciones entre las variables que llevan a los niños a adoptar posturas en los vehículos de transporte escolar que incrementan los efectos lesivos en caso de accidentes de tránsito. MÉTODOS: Para la identificación de las variables se recolectó información directa de la actividad del transporte escolar por medio de grupos de enfoque, con asistentes de ruta y conductores de estos vehículos, la filmación interior de autobuses durante el transporte de los niños, y el registro de dimensiones de componentes en diferentes tipos de autobuses escolares. El análisis de la información recolectada se hizo mediante el software Atlas ti v6 y, la construcción del modelo, por medio de un proceso deductivo. RESULTADOS: Se encontraron relaciones importantes entre la adopción de posturas potencialmente riesgosas por parte de los niños durante el transporte escolar y las características dimensionales de los asientos y cinturones de seguridad, las características del servicio de transporte y el rol del asistente de ruta. CONCLUSIONES: Para llevar a cabo intervenciones coherentes y específicas en el ámbito de la seguridad en el transporte escolar, se deben considerar no solo aspectos técnicos concernientes al vehículo o condiciones posturales controladas en pruebas de choque en laboratorio, sino también las variables específicas de la actividad que llevan a los niños a adoptar posturas que incrementan el riesgo de lesiones.OBJECTIVE: Prepare a conceptual model that facilitates understanding of the relationships between the variables that lead children to adopt postures in school transportation vehicles that increase injuries in traffic accidents. METHODS: For identification of the variables, direct information on school transportation was collected through focus groups, with bus aides and bus drivers, on-board filming during the transport of children, and recording of the

  18. 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.

  19. 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.

  20. 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.

  1. A Major Decision: Identifying Factors that Influence Agriculture Students’ Choice of Academic Major

    Directory of Open Access Journals (Sweden)

    Kristin Stair

    2016-06-01

    Full Text Available Colleges of Agriculture (CoAs are estimated to supply only slightly more than half of the number of graduates needed to fill job openings through 2015. The purpose of this research study was to describe the factors influencing agriculture students’ choice of major. The population for this descriptive research study consisted of full-time CoA freshmen enrolled in AGRI 1001: Introduction to Agriculture at Louisiana State University. A total of 259 students were asked to participate in the electronic survey. All students completed the survey for a 100% response rate. Consistent with the model proposed by Hodges and Karpova (2010, the factors identified in this study included personal characteristics, interpersonal factors, and environmental factors. Moreover, contextual factors unique to agriculture were identified.

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

    Science.gov (United States)

    Meshkat, Nicolette; Sullivant, Seth; Eisenberg, Marisa

    2015-08-01

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

  3. 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

  4. Factorization of the Ising model form factors

    International Nuclear Information System (INIS)

    Assis, M; McCoy, B M; Maillard, J-M

    2011-01-01

    We present a general method for analytically factorizing the n-fold form factor integrals f (n) N,N (t) for the correlation functions of the Ising model on the diagonal in terms of the hypergeometric functions 2 F 1 ([1/2, N + 1/2]; [N + 1]; t) which appear in the form factor f (1) N,N (t). New quadratic recursion and quartic identities are obtained for the form factors for n = 2, 3. For n = 2, 3, 4 explicit results are given for the form factors. These factorizations are proved for all N for n = 2, 3. These results yield the emergence of palindromic polynomials canonically associated with elliptic curves. As a consequence, understanding the form factors amounts to describing and understanding an infinite set of palindromic polynomials, canonically associated with elliptic curves. From an analytical viewpoint the relation of these palindromic polynomials with hypergeometric functions associated with elliptic curves is made very explicitly, and from a differential algebra viewpoint this corresponds to the emergence of direct sums of differential operators homomorphic to symmetric powers of a second order operator associated with elliptic curve.

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

    Science.gov (United States)

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

    2016-10-01

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

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

    DEFF Research Database (Denmark)

    Labouriau, Rodrigo

    2014-01-01

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

  7. 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...

  8. Identifying factors causing cost overrun of the construction projects ...

    Indian Academy of Sciences (India)

    , 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 ...

  9. Robust Nonnegative Matrix Factorization via Joint Graph Laplacian and Discriminative Information for Identifying Differentially Expressed Genes

    Directory of Open Access Journals (Sweden)

    Ling-Yun Dai

    2017-01-01

    Full Text Available Differential expression plays an important role in cancer diagnosis and classification. In recent years, many methods have been used to identify differentially expressed genes. However, the recognition rate and reliability of gene selection still need to be improved. In this paper, a novel constrained method named robust nonnegative matrix factorization via joint graph Laplacian and discriminative information (GLD-RNMF is proposed for identifying differentially expressed genes, in which manifold learning and the discriminative label information are incorporated into the traditional nonnegative matrix factorization model to train the objective matrix. Specifically, L2,1-norm minimization is enforced on both the error function and the regularization term which is robust to outliers and noise in gene data. Furthermore, the multiplicative update rules and the details of convergence proof are shown for the new model. The experimental results on two publicly available cancer datasets demonstrate that GLD-RNMF is an effective method for identifying differentially expressed genes.

  10. 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.

  11. 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.

  12. 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.

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

    NARCIS (Netherlands)

    den Hertog, J.H.

    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

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

    NARCIS (Netherlands)

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

    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

  15. 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

  16. Identifying factors of comfort in using hand tools

    NARCIS (Netherlands)

    Kuijt-Evers, L.F.M.; Groenesteijn, L.; Looze, M.P.de; Vink, P.

    2004-01-01

    To design comfortable hand tools, knowledge about comfort/discomfort in using hand tools is required. We investigated which factors determine comfort/discomfort in using hand tools according to users. Therefore, descriptors of comfort/discomfort in using hand tools were collected from literature and

  17. 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...

  18. Identifying factors causing cost overrun of the construction projects ...

    Indian Academy of Sciences (India)

    Swapnil P Wanjari

    were received and it was analyzed using various statistical tools such as analysis of variance (ANOVA) and factor analysis ... ponents, 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 ...

  19. Other Shades of Diversity: Identifying Factors that Facilitate Critical Thought

    Science.gov (United States)

    2015-06-01

    strength and also eliminates the threat of damage to each member’s self - esteem from hearing his or her own judgments on vital issues criticized by...These include a need to fit in socially, a lack of self - esteem , and a lack of self -confidence. One factor contributing to these traits, especially...to determine whether it is possible to have diversity of thought among a group of people of the same race and/or gender , specifically Caucasian

  20. Identifying risk factors that contribute to acute mountain sickness

    African Journals Online (AJOL)

    Female. 45 (51). 21 (57). 24 (46). Smoker. 0.63. Yes. 14 (16). 5 (14). 9 (17). No. 75 (84). 32 (86). 43 (83). Height above sea level of permanent residence. 0.23 .... al.[13] showed no correlation between AMS scores and hypoxic ventilatory response or. VO2 max. One of the risk factors proposed by Hackett et al.[4] is that of ...

  1. 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

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

    DEFF Research Database (Denmark)

    Jaeger, Manfred

    2013-01-01

    Classical learning theory is based on a tight linkage between hypothesis space (a class of function on a domain X), data space (function-value examples (x, f(x))), and the space of queries for the learned model (predicting function values for new examples x). However, in many learning scenarios......: the identification of temporal logic properties of probabilistic automata learned from sequence data, the identification of causal dependencies in probabilistic graphical models, and the transfer of probabilistic relational models to new domains....

  3. 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.

  4. [Identifying clinical risk factors in recurrent idiopathic deep venous thrombosis].

    Science.gov (United States)

    Del Río Solá, M Lourdes; González Fajardo, José Antonio; Vaquero Puerta, Carlos

    2016-03-18

    Oral anticoagulant therapy for more than 6 months in patients with an episode of idiopathic thromboembolic disease is controversial. The objective was to determine predictive clinical signs that identify patients at increased risk of thromboembolic recurrence after stopping anticoagulant therapy for 6 months after an episode of idiopathic deep vein thrombosis (DVT). A prospective study which included 306 consecutive patients with a first episode of idiopathic DVT from June 2012 to June 2014. Predictor variables of recurrent thromboembolic disease and episodes of recurrence during follow-up of the patients (28.42 months) were collected. We performed a multivariate analysis to analyze possible predictors (P<.20) and an analysis of Kaplan-Meier to establish mean recurrence-free survival. We identified 91 episodes of residual vein thrombosis on follow-up of the patients (37.5% men and 20.3% women) (OR 1.84; 95% CI 1.25-2.71). In the Cox regression analysis stratified by gender, variables showed significant presence of hyperechoic thrombus (P=.001) in males, and persistence of residual thrombus in women (P=.046). The mean recurrence-free survival was shorter in both groups. The presence of echogenic thrombus in men and the existence of residual DVT in women were 2 clinical signs associated with increased risk of thromboembolic recurrence after stopping anticoagulant therapy for 6 months after an episode of idiopathic DVT in our study. Copyright © 2015 Elsevier España, S.L.U. All rights reserved.

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

    Science.gov (United States)

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

    2017-01-17

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

  6. A Multinomial Probit Model with Latent Factors

    DEFF Research Database (Denmark)

    Piatek, Rémi; Gensowski, Miriam

    2017-01-01

    be meaningfully linked to an economic model. We provide sufficient conditions that make this structure identified and interpretable. For inference, we design a Markov chain Monte Carlo sampler based on marginal data augmentation. A simulation exercise shows the good numerical performance of our sampler......We develop a parametrization of the multinomial probit model that yields greater insight into the underlying decision-making process, by decomposing the error terms of the utilities into latent factors and noise. The latent factors are identified without a measurement system, and they can...

  7. 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.

  8. Structural identifiability analysis of a cardiovascular system model.

    Science.gov (United States)

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

    2016-05-01

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

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

    African Journals Online (AJOL)

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

  10. The use of systems models to identify food waste drivers

    NARCIS (Netherlands)

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

    2018-01-01

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

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

    African Journals Online (AJOL)

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

  12. 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'…

  13. Wrong-way driving crashes: A multiple correspondence approach to identify contributing factors.

    Science.gov (United States)

    Jalayer, Mohammad; Pour-Rouholamin, Mahdi; Zhou, Huaguo

    2018-01-02

    Wrong-way driving (WWD) crashes result in 1.34 fatalities per fatal crash, whereas for other non-WWD fatal crashes this number drops to 1.10. As such, further in-depth investigation of WWD crashes is necessary. The objective of this study is 2-fold: to identify the characteristics that best describe WWD crashes and to verify the factors associated with WWD occurrence. We collected and analyzed 15 years of crash data from the states of Illinois and Alabama. The final data set includes 398 WWD crashes. The rarity of WWD events and the consequently small sample size of the crash database significantly influence the application of conventional log-linear models in analyzing the data, because they use maximum-likelihood estimation. To overcome this issue, in this study, we employ multiple correspondence analysis (MCA) to define the structure of the crash data set and identify the significant contributing factors to WWD crashes on freeways. The results of the present study specify various factors that characterize and influence the probability of WWD crashes and can thus lead to the development of several safety countermeasures and recommendations. According to the obtained results, factors such as driver age, driver condition, roadway surface conditions, and lighting conditions were among the most significant contributors to WWD crashes. Despite many other methods that identify only the contributing factors, this method can identify possible associations between various contributing factors. This is an inherent advantage of the MCA method, which can provide a major opportunity for state departments of transportation (DOTs) to select safety countermeasures that are associated with multiple safety benefits.

  14. 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.

  15. Application of positive matrix factorization to identify potential sources of PAHs in soil of Dalian, China

    International Nuclear Information System (INIS)

    Wang Degao; Tian Fulin; Yang Meng; Liu Chenlin; Li Yifan

    2009-01-01

    Soil derived sources of polycyclic aromatic hydrocarbons (PAHs) in the region of Dalian, China were investigated using positive matrix factorization (PMF). Three factors were separated based on PMF for the statistical investigation of the datasets both in summer and winter. These factors were dominated by the pattern of single sources or groups of similar sources, showing seasonal and regional variations. The main sources of PAHs in Dalian soil in summer were the emissions from coal combustion average (46%), diesel engine (30%), and gasoline engine (24%). In winter, the main sources were the emissions from coal-fired boiler (72%), traffic average (20%), and gasoline engine (8%). These factors with strong seasonality indicated that coal combustion in winter and traffic exhaust in summer dominated the sources of PAHs in soil. These results suggested that PMF model was a proper approach to identify the sources of PAHs in soil. - PMF model is a proper approach to identify potential sources of PAHs in soil based on the PAH profiles measured in the field and those published in the literature.

  16. Identifying factors inhibiting or enhancing family presence during resuscitation in the emergency department.

    Science.gov (United States)

    Davidson, Judy E; Buenavista, Ruth; Hobbs, Keynan; Kracht, Kathleen

    2011-01-01

    The purpose of this qualitative study was to explore inhibitors and enhancing factors surrounding the practice of allowing family presence in the emergency room. Staff and physician interviews were transcribed and decoded for themes. A visual model was built to depict the results. Inhibitors and enhancing factors included the following drivers: staff emotions, personalizing the patient, seeing/hearing everything, closure, emotional support of the family, and "if it were me." The following staff needs were also identified as important issues that needed to be addressed before practice could change further: staff education, optimize environment for privacy, and implementation of a family liaison. The use of qualitative research methods was effective in identifying organizational barriers to transition of evidence into practice.

  17. Quasi-Poisson versus negative binomial regression models in identifying factors affecting initial CD4 cell count change due to antiretroviral therapy administered to HIV-positive adults in North-West Ethiopia (Amhara region).

    Science.gov (United States)

    Seyoum, Awoke; Ndlovu, Principal; Zewotir, Temesgen

    2016-01-01

    CD4 cells are a type of white blood cells that plays a significant role in protecting humans from infectious diseases. Lack of information on associated factors on CD4 cell count reduction is an obstacle for improvement of cells in HIV positive adults. Therefore, the main objective of this study was to investigate baseline factors that could affect initial CD4 cell count change after highly active antiretroviral therapy had been given to adult patients in North West Ethiopia. A retrospective cross-sectional study was conducted among 792 HIV positive adult patients who already started antiretroviral therapy for 1 month of therapy. A Chi square test of association was used to assess of predictor covariates on the variable of interest. Data was secondary source and modeled using generalized linear models, especially Quasi-Poisson regression. The patients' CD4 cell count changed within a month ranged from 0 to 109 cells/mm 3 with a mean of 15.9 cells/mm 3 and standard deviation 18.44 cells/mm 3 . The first month CD4 cell count change was significantly affected by poor adherence to highly active antiretroviral therapy (aRR = 0.506, P value = 2e -16 ), fair adherence (aRR = 0.592, P value = 0.0120), initial CD4 cell count (aRR = 1.0212, P value = 1.54e -15 ), low household income (aRR = 0.63, P value = 0.671e -14 ), middle income (aRR = 0.74, P value = 0.629e -12 ), patients without cell phone (aRR = 0.67, P value = 0.615e -16 ), WHO stage 2 (aRR = 0.91, P value = 0.0078), WHO stage 3 (aRR = 0.91, P value = 0.0058), WHO stage 4 (0876, P value = 0.0214), age (aRR = 0.987, P value = 0.000) and weight (aRR = 1.0216, P value = 3.98e -14 ). Adherence to antiretroviral therapy, initial CD4 cell count, household income, WHO stages, age, weight and owner of cell phone played a major role for the variation of CD4 cell count in our data. Hence, we recommend a close follow-up of patients to adhere the prescribed medication for

  18. Characterizations of identified sets delivered by structural econometric models

    OpenAIRE

    Chesher, Andrew; Rosen, Adam M.

    2016-01-01

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

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

    Directory of Open Access Journals (Sweden)

    B. Guse

    2017-11-01

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

  20. Identifying Factors That Predict Worse Constipation Symptoms in Palliative Care Patients: A Secondary Analysis.

    Science.gov (United States)

    Clark, Katherine; Lam, Lawrence T; Talley, Nicholas J; Phillips, Jane L; Currow, David C

    2017-05-01

    The aim of this work was to investigate whether variables identified as likely to impact the experience of constipation in other clinical settings similarly affected the experiences of constipated palliative care patients. The majority of palliative care patients with cancer are likely to be bothered by constipation symptoms at some point in their disease trajectory. Despite this, it remains unclear as to which factors predict more severe problems. This study was conducted in a sample of 94 constipated palliative care patients who were asked to voluntarily complete a series of questions regarding their demographic and other characteristics, including whether they had chronic constipation symptoms, that is, constipation symptoms for 12 months. Other variables included age, body mass index, sex, performance status, and regular opioids and their doses. At the same time, they were asked to complete the Patient Assessment of Constipation Symptoms (PAC-SYM) and Patient Assessment of Constipation Quality of Life (PAC-QOL) questionnaires. Descriptive statistics summarized baseline data. Unadjusted associations between the selected variables on PAC-SYM were examined by using bi-variate analyses. Significant variables identified on bi-variate analyses were included in a multivariate analysis. The final results identified that only the chronicity of constipation symptoms predicted more severe symptoms. This relationship persisted when this single variable was retained in the final model, illustrating that PAC-SYM scores are 0.41 higher in patients with chronic constipation compared with those without it (p = 0.02). In contrast, regular opioid use was not identified as a significant factor (p = 0.56). This study suggests that the factor most likely to predict worse constipation symptoms was the duration that people had experienced problems. Further, those who perceived their constipation symptoms to be more severe had a poorer quality of life. More work is required to

  1. An in vitro cord formation assay identifies unique vascular phenotypes associated with angiogenic growth factors.

    Directory of Open Access Journals (Sweden)

    Beverly L Falcon

    Full Text Available Vascular endothelial growth factor (VEGF plays a dominant role in angiogenesis. While inhibitors of the VEGF pathway are approved for the treatment of a number of tumor types, the effectiveness is limited and evasive resistance is common. One mechanism of evasive resistance to inhibition of the VEGF pathway is upregulation of other pro-angiogenic factors such as fibroblast growth factor (FGF and epidermal growth factor (EGF. Numerous in vitro assays examine angiogenesis, but many of these assays are performed in media or matrix with multiple growth factors or are driven by VEGF. In order to study angiogenesis driven by other growth factors, we developed a basal medium to use on a co-culture cord formation system of adipose derived stem cells (ADSCs and endothelial colony forming cells (ECFCs. We found that cord formation driven by different angiogenic factors led to unique phenotypes that could be differentiated and combination studies indicate dominant phenotypes elicited by some growth factors. VEGF-driven cords were highly covered by smooth muscle actin, and bFGF-driven cords had thicker nodes, while EGF-driven cords were highly branched. Multiparametric analysis indicated that when combined EGF has a dominant phenotype. In addition, because this assay system is run in minimal medium, potential proangiogenic molecules can be screened. Using this assay we identified an inhibitor that promoted cord formation, which was translated into in vivo tumor models. Together this study illustrates the unique roles of multiple anti-angiogenic agents, which may lead to improvements in therapeutic angiogenesis efforts and better rational for anti-angiogenic therapy.

  2. How to identify the speed limiting factor of a TCP flow

    NARCIS (Netherlands)

    Timmer, Mark

    2005-01-01

    This thesis develops a method for identifying the speed limiting factor of a TCP flow. Five factors are considered: the receive window, the send buffer, the network and two kinds of application layer factors. Criteria for recognizing each factor based on TCP header information are put forward. These

  3. 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.

  4. Estimate variable importance for recurrent event outcomes with an application to identify hypoglycemia risk factors.

    Science.gov (United States)

    Duan, Ran; Fu, Haoda

    2015-08-30

    Recurrent event data are an important data type for medical research. In particular, many safety endpoints are recurrent outcomes, such as hypoglycemic events. For such a situation, it is important to identify the factors causing these events and rank these factors by their importance. Traditional model selection methods are not able to provide variable importance in this context. Methods that are able to evaluate the variable importance, such as gradient boosting and random forest algorithms, cannot directly be applied to recurrent events data. In this paper, we propose a two-step method that enables us to evaluate the variable importance for recurrent events data. We evaluated the performance of our proposed method by simulations and applied it to a data set from a diabetes study. Copyright © 2015 John Wiley & Sons, Ltd.

  5. Identifying fMRI Model Violations with Lagrange Multiplier Tests

    Science.gov (United States)

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

    2013-01-01

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

  6. Drosophila Cancer Models Identify Functional Differences between Ret Fusions

    Directory of Open Access Journals (Sweden)

    Sarah Levinson

    2016-09-01

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

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

    International Nuclear Information System (INIS)

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

    1989-01-01

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

  8. Identifying environmental risk factors for asthma emergency care" a multilevel approach for ecological study.

    Science.gov (United States)

    Allacci, MaryAnn Sorensen

    2005-01-01

    This ongoing empirical study suggests a model for evaluating a combination of environmental risk factors to explain neighborhood differences in adult use of Harlem Hospital's Asthma Emergency Department services. A multilevel or "nested" model incorporates methods for hypothesis testing using geographic information systems (GIS) and existing data from Harlem Hospital Center, city agencies, and other sources to measure variables on both building and street segment levels. Selection of the best geographic scale by which to measure housing conditions, neighborhood physical quality, income indicators, and access to healthcare is an important strategy toward identifying neighborhood socioenvironmental patterns contributing to geographic clustering of asthma emergencies. Specific community interventions may then be defined to improve the health outcomes of residents with asthma.

  9. Multivariate linear regression analysis to identify general factors for quantitative predictions of implant stability quotient values.

    Directory of Open Access Journals (Sweden)

    Hairong Huang

    Full Text Available This study identified potential general influencing factors for a mathematical prediction of implant stability quotient (ISQ values in clinical practice.We collected the ISQ values of 557 implants from 2 different brands (SICace and Osstem placed by 2 surgeons in 336 patients. Surgeon 1 placed 329 SICace implants, and surgeon 2 placed 113 SICace implants and 115 Osstem implants. ISQ measurements were taken at T1 (immediately after implant placement and T2 (before dental restoration. A multivariate linear regression model was used to analyze the influence of the following 11 candidate factors for stability prediction: sex, age, maxillary/mandibular location, bone type, immediate/delayed implantation, bone grafting, insertion torque, I-stage or II-stage healing pattern, implant diameter, implant length and T1-T2 time interval.The need for bone grafting as a predictor significantly influenced ISQ values in all three groups at T1 (weight coefficients ranging from -4 to -5. In contrast, implant diameter consistently influenced the ISQ values in all three groups at T2 (weight coefficients ranging from 3.4 to 4.2. Other factors, such as sex, age, I/II-stage implantation and bone type, did not significantly influence ISQ values at T2, and implant length did not significantly influence ISQ values at T1 or T2.These findings provide a rational basis for mathematical models to quantitatively predict the ISQ values of implants in clinical practice.

  10. 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.

  11. Factors identified by experts to support decision making for post acute referral.

    Science.gov (United States)

    Bowles, Kathryn H; Holmes, John H; Ratcliffe, Sarah J; Liberatore, Matthew; Nydick, Robert; Naylor, Mary D

    2009-01-01

    Each year, more than 13 million post acute referral decisions are made for Medicare recipients, yet there are no national, empirically derived decision support tools to assist in making these important decisions. The aim of this study was to elicit expert knowledge about factors important to referral decision making and identify the characteristics of hospitalized patients who need a post acute referral. This was a retrospective and prospective mixed-methods study of the referral decisions made by discharge planning experts for 355 hospitalized older adults. Variables included sociodemographics, living arrangement, insurance, diagnosis, comorbid conditions, adverse events, medications, home care use, hospitalization in last 30 days or 6 months, patients' perception of need for and use of assistive devices or post acute services, length of stay, cognition, self-rated health, depression, functional status, and post acute referral decision. The final model identified six factors associated with the need for a post acute referral. A cutpoint was derived with a sensitivity and specificity of 87.6% and 63.2%, respectively. Experts were more likely to refer patients who had no or intermittent help available (odds ratio [OR] = 3.0), major walking restrictions (OR = 6.5), less than excellent self-rated health (3.1 and 4.0 times more likely with good and fair-poor health, respectively), remained in the hospital longer (OR = 1.2), and had higher depression scores (OR = 1.1) or number of comorbidities (OR = 1.2). This study begins to identify information useful to clinicians caring for hospitalized older adults who may benefit from post acute services. By assuring the systematic, valid, and reliable collection of these items, the multidisciplinary team is alerted to patients who may benefit from post acute services. Further work is needed to increase the specificity and generalizability of the model and to test its effects on patient and clinician outcomes.

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

    Directory of Open Access Journals (Sweden)

    Nishanee Rampersad

    2017-02-01

    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 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.

  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. Liver transplantation in highest acuity recipients: identifying factors to avoid futility.

    Science.gov (United States)

    Petrowsky, Henrik; Rana, Abbas; Kaldas, Fady M; Sharma, Anuj; Hong, Johnny C; Agopian, Vatche G; Durazo, Francisco; Honda, Henry; Gornbein, Jeffrey; Wu, Victor; Farmer, Douglas G; Hiatt, Jonathan R; Busuttil, Ronald W

    2014-06-01

    To identify medical predictors of futility in recipients with laboratory Model of End-Stage Liver Disease (MELD) scores of 40 or more at the time of orthotopic liver transplantation (OLT). Although the survival benefit for transplant patients with the highest MELD scores is indisputable, the medical and economic effort to bring these highest acuity recipients through OLT presents a major challenge for every transplant center. This study was undertaken to analyze outcomes in patients with MELD scores of 40 or more undergoing OLT during the period February 2002 to December 2010. The analysis was focused on futile outcome (3-month or in-hospital mortality) and long-term posttransplant outcome. Independent predictors of futility and failure-free survival were identified and a futility risk model was created. During the study period, 1522 adult cadaveric OLTs were performed, and 169 patients (13%) had a MELD score of 40 or more. The overall 1, 3, 5, and 8-year patient survivals were 72%, 64%, 60%, and 56%. Futile outcome occurred in 37 patients (22%). MELD score, pretransplant septic shock, cardiac risk, and comorbidities were independent predictors of futile outcome. Using all 4 factors, the futility risk model had a good discriminatory ability (c-statistic 0.75). Recipient age per year, life-threatening postoperative complications, hepatitis C, and metabolic syndrome were independent predictors for long-term survival in nonfutile patients (Harrels c-statistic 0.72). Short- and long-term outcomes of recipients with MELD scores of 40 or more are primarily determined by disease-specific factors. Cardiac risk, pretransplant septic shock, and comorbidities are the most important predictors and can be used for risk stratification in these highest acuity recipients.

  16. 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.

  17. Identifying fast-onset antidepressants using rodent models.

    Science.gov (United States)

    Ramaker, M J; Dulawa, S C

    2017-05-01

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

  18. 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.

    2015-01-01

    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. PMID:25971969

  19. 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. © 2015 by The American Society for Biochemistry and Molecular

  20. A Parametric Factor Model of the Term Structure of Mortality

    DEFF Research Database (Denmark)

    Haldrup, Niels; Rosenskjold, Carsten Paysen T.

    The prototypical Lee-Carter mortality model is characterized by a single common time factor that loads differently across age groups. In this paper we propose a factor model for the term structure of mortality where multiple factors are designed to influence the age groups differently via...... parametric loading functions. We identify four different factors: a factor common for all age groups, factors for infant and adult mortality, and a factor for the "accident hump" that primarily affects mortality of relatively young adults and late teenagers. Since the factors are identified via restrictions...... on the loading functions, the factors are not designed to be orthogonal but can be dependent and can possibly cointegrate when the factors have unit roots. We suggest two estimation procedures similar to the estimation of the dynamic Nelson-Siegel term structure model. First, a two-step nonlinear least squares...

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

    Science.gov (United States)

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

    2018-01-01

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

  2. A screening system to identify transcription factors that induce binding site-directed DNA demethylation.

    Science.gov (United States)

    Suzuki, Takahiro; Maeda, Shiori; Furuhata, Erina; Shimizu, Yuri; Nishimura, Hajime; Kishima, Mami; Suzuki, Harukazu

    2017-12-08

    DNA methylation is a fundamental epigenetic modification that is involved in many biological systems such as differentiation and disease. We and others recently showed that some transcription factors (TFs) are involved in the site-specific determination of DNA demethylation in a binding site-directed manner, although the reports of such TFs are limited. Here, we develop a screening system to identify TFs that induce binding site-directed DNA methylation changes. The system involves the ectopic expression of target TFs in model cells followed by DNA methylome analysis and overrepresentation analysis of the corresponding TF binding motif at differentially methylated regions. It successfully identified binding site-directed demethylation of SPI1, which is known to promote DNA demethylation in a binding site-directed manner. We extended our screening system to 15 master TFs involved in cellular differentiation and identified eight novel binding site-directed DNA demethylation-inducing TFs (RUNX3, GATA2, CEBPB, MAFB, NR4A2, MYOD1, CEBPA, and TBX5). Gene ontology and tissue enrichment analysis revealed that these TFs demethylate genomic regions associated with corresponding biological roles. We also describe the characteristics of binding site-directed DNA demethylation induced by these TFs, including the targeting of highly methylated CpGs, local DNA demethylation, and the overlap of demethylated regions between TFs of the same family. Our results show the usefulness of the developed screening system for the identification of TFs that induce DNA demethylation in a site-directed manner.

  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. 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.

  5. Modelling oxygen transfer using dynamic alpha factors.

    Science.gov (United States)

    Jiang, Lu-Man; Garrido-Baserba, Manel; Nolasco, Daniel; Al-Omari, Ahmed; DeClippeleir, Haydee; Murthy, Sudhir; Rosso, Diego

    2017-11-01

    Due to the importance of wastewater aeration in meeting treatment requirements and due to its elevated energy intensity, it is important to describe the real nature of an aeration system to improve design and specification, performance prediction, energy consumption, and process sustainability. Because organic loadings drive aeration efficiency to its lowest value when the oxygen demand (energy) is the highest, the implications of considering their dynamic nature on energy costs are of utmost importance. A dynamic model aimed at identifying conservation opportunities is presented. The model developed describes the correlation between the COD concentration and the α factor in activated sludge. Using the proposed model, the aeration efficiency is calculated as a function of the organic loading (i.e. COD). This results in predictions of oxygen transfer values that are more realistic than the traditional method of assuming constant α values. The model was applied to two water resource recovery facilities, and was calibrated and validated with time-sensitive databases. Our improved aeration model structure increases the quality of prediction of field data through the recognition of the dynamic nature of the alpha factor (α) as a function of the applied oxygen demand. For the cases presented herein, the model prediction of airflow improved by 20-35% when dynamic α is used. The proposed model offers a quantitative tool for the prediction of energy demand and for minimizing aeration design uncertainty. Copyright © 2017 Elsevier Ltd. All rights reserved.

  6. Using SMAP to identify structural errors in hydrologic models

    Science.gov (United States)

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

    2017-12-01

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

  7. Using a Systematic Approach to Identifying Organizational Factors in Root Cause Analysis

    International Nuclear Information System (INIS)

    Gallogly, Kay Wilde

    2011-01-01

    This presentation set the scene for the second discussion session. In her presentation, the author observed that: - Investigators do not see the connection between the analysis tools available and the identification of HOF. Most investigators use the tools in a cursory manner and so do not derive the full benefits of the tools. Some tools are used for presentation purposes as opposed to being used for analytical purposes e.g. event and causal factors charts. In some cases, the report will indicate that specific analytical tools were used in the investigation but the analysis is not in the body of the report. - Some investigators are documenting HOF causes but do not recognize them as such. This indicates a lack of understanding of HOF. - Others investigators focus on technical issues because of their own comfort level. - The culture of the Organisation will affect the depth of the investigation and therefore the use of the analytical tools to pursue HOF issues. - The author contends that if analysis tools are applied systematically to gather factually based data, then HOF issues can be identified. The use of factual information (without judgement and subjectivity) is important to maintain the credibility of the investigation especially when HOF issues are identified. - Systematic use of tools assists in better communication of the issues to foster greater understanding and acceptance by senior management. - Barrier Analysis, Change Analysis, and TWIN (Task Demands, Work Environment, Individual Capabilities, and Human Nature) all offer the opportunity to identify HOF issues if the analyst pursues this line of investigation. It was illustrated that many elements of the TWIN Error Precursors are themselves Organisational in nature. - The TWIN model applied to the Anatomy of an Event will help to distinguish those which are Organisational issues (Latent Organisational Weaknesses, Error Precursors and Flawed Defences) and those which are human factors (Active Errors

  8. Identifying risk factors associated with smear positivity of pulmonary tuberculosis in Kazakhstan.

    Directory of Open Access Journals (Sweden)

    Sabrina Hermosilla

    Full Text Available Sputum smear-positive tuberculosis (TB patients have a high risk of transmission and are of great epidemiological and infection control significance. Little is known about the smear-positive populations in high TB burden regions, such as Kazakhstan. The objective of this study is to characterize the smear-positive population in Kazakhstan and identify associated modifiable risk factors.Data on incident TB cases' (identified between April 2012 and March 2014 socio-demographic, risk behavior, and comorbidity characteristics were collected in four regions of Kazakhstan through structured survey and medical record review. We used multivariable logistic regression to determine factors associated with smear positivity.Of the total sample, 193 (34.3% of the 562 study participants tested smear-positive. In the final adjusted multivariable logistic regression model, sex (adjusted odds ratio (aOR = 2.0, 95% CI:1.3-3.1, p < 0.01, incarceration (aOR = 3.6, 95% CI:1.2-11.1, p = 0.03, alcohol dependence (aOR = 2.6, 95% CI:1.2-5.7, p = 0.02, diabetes (aOR = 5.0, 95% CI:2.4-10.7, p < 0.01, and physician access (aOR = 2.7, 95% CI:1.3-5.5p < 0.01 were associated with smear-positivity.Incarceration, alcohol dependence, diabetes, and physician access are associated with smear positivity among incident TB cases in Kazakhstan. To stem the TB epidemic, screening, treatment and prevention policies should address these factors.

  9. Simple Model for Identifying Critical Regions in Atrial Fibrillation

    Science.gov (United States)

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

    2015-01-01

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

  10. 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

  11. 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.

  12. 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...... 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...

  13. Identifying Risk Factors for Drug Use in an Iranian Treatment Sample: A Prediction Approach Using Decision Trees.

    Science.gov (United States)

    Amirabadizadeh, Alireza; Nezami, Hossein; Vaughn, Michael G; Nakhaee, Samaneh; Mehrpour, Omid

    2018-05-12

    Substance abuse exacts considerable social and health care burdens throughout the world. The aim of this study was to create a prediction model to better identify risk factors for drug use. A prospective cross-sectional study was conducted in South Khorasan Province, Iran. Of the total of 678 eligible subjects, 70% (n: 474) were randomly selected to provide a training set for constructing decision tree and multiple logistic regression (MLR) models. The remaining 30% (n: 204) were employed in a holdout sample to test the performance of the decision tree and MLR models. Predictive performance of different models was analyzed by the receiver operating characteristic (ROC) curve using the testing set. Independent variables were selected from demographic characteristics and history of drug use. For the decision tree model, the sensitivity and specificity for identifying people at risk for drug abuse were 66% and 75%, respectively, while the MLR model was somewhat less effective at 60% and 73%. Key independent variables in the analyses included first substance experience, age at first drug use, age, place of residence, history of cigarette use, and occupational and marital status. While study findings are exploratory and lack generalizability they do suggest that the decision tree model holds promise as an effective classification approach for identifying risk factors for drug use. Convergent with prior research in Western contexts is that age of drug use initiation was a critical factor predicting a substance use disorder.

  14. Risk factors for atherosclerosis - can they be used to identify the ...

    African Journals Online (AJOL)

    Risk factors are often used in preventive care programmes to identify the patient at particular risk for developing atherosclerosis. Risk factors for atherosclerosis have also been shown to be linked to the presence of the disease at a given time, a fact that may be helpful when screening for additional atherosclerotic disease in ...

  15. 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....

  16. 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

  17. 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.

  18. 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.

  19. Anthropometric Computed Tomography Reconstruction Identifies Risk Factors for Cortical Perforation in Revision Total Hip Arthroplasty.

    Science.gov (United States)

    Guild, George N; Runner, Robert P; Rickels, Tracy D; Oldja, Ryan; Faizan, Ahmad

    2016-11-01

    The incidence of revision hip arthroplasty is increasing with nearly 100,000 annual procedures expected in the near future. Many surgeons use straight modular tapered stems in revisions; however, complications of periprosthetic fracture and cortical perforation occur, resulting in poor outcomes. Our objective was to identify patient demographics and femoral characteristics that predispose patients to cortical perforation when using the straight modular stems. We used a computed tomography database and modeling software to identify patient demographics and morphologic femoral characteristics that predispose patients to cortical perforation during revision hip arthroplasty. Overall, 561 femurs from patients of various backgrounds were used, and statistical analysis was performed via the 2-sample t test. Decreased patient height (mean 163.0 vs 168.8 cm), radius of curvature (818 vs 939 mm), anterior-posterior (8.5 vs 13.8 mm) and medial-lateral (7.9 vs 11.3 mm) width of the isthmus, and distance of the isthmus from the greater trochanter (179 vs 186 mm) were all statistically significant risk factors for cortical perforation (P revision hip arthroplasty using straight modular tapered stems and highlights the importance of preoperative planning especially in patients with shorter stature, proximal location of the femoral isthmus, narrow femoral canal, and smaller radius of curvature. Also, when using a mid-length modular tapered stem without an extended trochanteric osteotomy, consideration should be given to using a kinked stem to avoid anterior cortical perforation. Copyright © 2016 Elsevier Inc. All rights reserved.

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

    Science.gov (United States)

    Walz, Johanna M; Boehringer, Daniel; Deissler, Heidrun L; Faerber, Lothar; Goepfert, Jens C; Heiduschka, Peter; Kleeberger, Susannah M; Klettner, Alexa; Krohne, Tim U; Schneiderhan-Marra, Nicole; Ziemssen, Focke; Stahl, Andreas

    2016-01-01

    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.

  1. Identifying Predictive Factors for Incident Reports in Patients Receiving Radiation Therapy

    Energy Technology Data Exchange (ETDEWEB)

    Elnahal, Shereef M., E-mail: selnaha1@jhmi.edu [Department of Radiation Oncology and Molecular Radiation Sciences, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, Maryland (United States); Blackford, Amanda [Department of Oncology Biostatistics, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, Maryland (United States); Smith, Koren; Souranis, Annette N.; Briner, Valerie; McNutt, Todd R.; DeWeese, Theodore L.; Wright, Jean L.; Terezakis, Stephanie A. [Department of Radiation Oncology and Molecular Radiation Sciences, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, Maryland (United States)

    2016-04-01

    Purpose: To describe radiation therapy cases during which voluntary incident reporting occurred; and identify patient- or treatment-specific factors that place patients at higher risk for incidents. Methods and Materials: We used our institution's incident learning system to build a database of patients with incident reports filed between January 2011 and December 2013. Patient- and treatment-specific data were reviewed for all patients with reported incidents, which were classified by step in the process and root cause. A control group of patients without events was generated for comparison. Summary statistics, likelihood ratios, and mixed-effect logistic regression models were used for group comparisons. Results: The incident and control groups comprised 794 and 499 patients, respectively. Common root causes included documentation errors (26.5%), communication (22.5%), technical treatment planning (37.5%), and technical treatment delivery (13.5%). Incidents were more frequently reported in minors (age <18 years) than in adult patients (37.7% vs 0.4%, P<.001). Patients with head and neck (16% vs 8%, P<.001) and breast (20% vs 15%, P=.03) primaries more frequently had incidents, whereas brain (18% vs 24%, P=.008) primaries were less frequent. Larger tumors (17% vs 10% had T4 lesions, P=.02), and cases on protocol (9% vs 5%, P=.005) or with intensity modulated radiation therapy/image guided intensity modulated radiation therapy (52% vs 43%, P=.001) were more likely to have incidents. Conclusions: We found several treatment- and patient-specific variables associated with incidents. These factors should be considered by treatment teams at the time of peer review to identify patients at higher risk. Larger datasets are required to recommend changes in care process standards, to minimize safety risks.

  2. A computational method using the random walk with restart algorithm for identifying novel epigenetic factors.

    Science.gov (United States)

    Li, JiaRui; Chen, Lei; Wang, ShaoPeng; Zhang, YuHang; Kong, XiangYin; Huang, Tao; Cai, Yu-Dong

    2018-02-01

    Epigenetic regulation has long been recognized as a significant factor in various biological processes, such as development, transcriptional regulation, spermatogenesis, and chromosome stabilization. Epigenetic alterations lead to many human diseases, including cancer, depression, autism, and immune system defects. Although efforts have been made to identify epigenetic regulators, it remains a challenge to systematically uncover all the components of the epigenetic regulation in the genome level using experimental approaches. The advances of constructing protein-protein interaction (PPI) networks provide an excellent opportunity to identify novel epigenetic factors computationally in the genome level. In this study, we identified potential epigenetic factors by using a computational method that applied the random walk with restart (RWR) algorithm on a protein-protein interaction (PPI) network using reported epigenetic factors as seed nodes. False positives were identified by their specific roles in the PPI network or by a low-confidence interaction and a weak functional relationship with epigenetic regulators. After filtering out the false positives, 26 candidate epigenetic factors were finally accessed. According to previous studies, 22 of these are thought to be involved in epigenetic regulation, suggesting the robustness of our method. Our study provides a novel computational approach which successfully identified 26 potential epigenetic factors, paving the way on deepening our understandings on the epigenetic mechanism.

  3. 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

  4. 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

  5. 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.

  6. Identifying work setting profile factors from the Career Pathway Evaluation Program.

    Science.gov (United States)

    Schommer, Jon C; Sogol, Elliott M; Brown, Lawrence M

    2013-11-12

    To describe the work factors associated with 28 different career areas as reported by pharmacists who responded to the American Pharmacists Association (APhA) Career Pathway Evaluation Program for Pharmacy Professionals, 2012 Pharmacist Profile Survey. Data from the 1,119 completed survey instruments from the 2012 Pharmacist Profile Survey were analyzed. Exploratory factor analysis was used to identify the underlying factors that best represented respondents' work setting profiles. Eleven underlying factors were identified for the respondents' work setting profiles: patient care, application of clinical knowledge, innovation, stress, research, managerial responsibility, work schedule flexibility, job position flexibility, self-actualization, geographic location, and continuity of coworker relationships. Findings revealed variation for these underlying factors among career categories. Variation among pharmacist career types exists. The profiles constructed in this study describe the characteristics of various career paths and can be helpful for decisions regarding educational, experiential, residency, and certification training in pharmacist careers.

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

    Science.gov (United States)

    Ko, Minsam; Yeo, Jaeryong; Lee, Juyeong; Lee, Uichin; Jang, Young Jae

    2016-01-01

    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.

  8. 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.

  9. Identifying Work Setting Profile Factors From the Career Pathway Evaluation Program

    Science.gov (United States)

    Sogol, Elliott M.; Brown, Lawrence M.

    2013-01-01

    Objectives. To describe the work factors associated with 28 different career areas as reported by pharmacists who responded to the American Pharmacists Association (APhA) Career Pathway Evaluation Program for Pharmacy Professionals, 2012 Pharmacist Profile Survey Methods. Data from the 1,119 completed survey instruments from the 2012 Pharmacist Profile Survey were analyzed. Exploratory factor analysis was used to identify the underlying factors that best represented respondents’ work setting profiles. Results. Eleven underlying factors were identified for the respondents’ work setting profiles: patient care, application of clinical knowledge, innovation, stress, research, managerial responsibility, work schedule flexibility, job position flexibility, self-actualization, geographic location, and continuity of coworker relationships. Findings revealed variation for these underlying factors among career categories. Conclusion. Variation among pharmacist career types exists. The profiles constructed in this study describe the characteristics of various career paths and can be helpful for decisions regarding educational, experiential, residency, and certification training in pharmacist careers. PMID:24249856

  10. Robust and Sparse Factor Modelling

    DEFF Research Database (Denmark)

    Croux, Christophe; Exterkate, Peter

    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...

  11. 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

  12. 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.

  13. Modeling birth weight neonates and associated factors

    Directory of Open Access Journals (Sweden)

    Mansour Rezaei

    2017-01-01

    Full Text Available Background: Neonate with abnormal weight is at risk of increased mortality and morbidity. Many factors affect pregnancy outcome. Because of the importance and vital role in birth weight, in this study, some of the factors associated with birth weight in a sample of Iranians neonates were investigated. Materials and Methods: In this cross-sectional study, 245 newborns in a sample of Iranians neonates in the year 2013 were selected, and characteristics of neonate and their mothers were derived. Birth weights were registered by the neonatal scale. To identify the direct and indirect factors affecting birth weight, we used path analysis (PA and IBM AMOS and SPSS software. Results: The mean ± standard deviation of weight in girls (3200 ± 421 g less than boys (3310 ± 444 g significantly (P = 0.04. Gestational age (P < 0.001, birth rank (P = 0.012, distance from a previous pregnancy (P = 0.028, and mother weight (P = 0.04 had a statistical significant relationship with birth weight. In the final PA model, gestational age has a highest total effect, type of delivery with gestational age-mediated had the highest indirect effect and type of delivery, and gestational age had the greatest total impact on the birth weight. Conclusion: Gestational age, sex, distance from a previous pregnancy, maternal weight, type of delivery, number of abortion, and birth rank were related with birth weight. Due to the termination of pregnancy and avoid unnecessary deliveries through cesarean section and other related factors should be further consideration by childbirth experts. In addition, factors affecting these variables are carefully identified and prevented as much as possible.

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

    African Journals Online (AJOL)

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

  15. Identifying environmental risk factors and mapping the risk of human West Nile virus in South Dakota.

    Science.gov (United States)

    Hess, A.; Davis, J. K.; Wimberly, M. C.

    2017-12-01

    Human West Nile virus (WNV) first arrived in the USA in 1999 and has since then spread across the country. Today, the highest incidence rates are found in the state of South Dakota. The disease occurrence depends on the complex interaction between the mosquito vector, the bird host and the dead-end human host. Understanding the spatial domain of this interaction and being able to identify disease transmission hotspots is crucial for effective disease prevention and mosquito control. In this study we use geospatial environmental information to understand what drives the spatial distribution of cases of human West Nile virus in South Dakota and to map relative infection risk across the state. To map the risk of human West Nile virus in South Dakota, we used geocoded human case data from the years 2004-2016. Satellite data from the Landsat ETM+ and MODIS for the years 2003 to 2016 were used to characterize environmental patterns. From these datasets we calculated indices, such as the normalized differenced vegetation index (NDVI) and the normalized differenced water index (NDWI). In addition, datasets such as the National Land Data Assimilation System (NLDAS), National Land Cover Dataset (NLCD), National Wetland inventory (NWI), National Elevation Dataset (NED) and Soil Survey Geographic Database (SSURGO) were utilized. Environmental variables were summarized for a buffer zone around the case and control points. We used a boosted regression tree model to identify the most important variables describing the risk of WNV infection. We generated a risk map by applying this model across the entire state. We found that the highest relative risk is present in the James River valley in northeastern South Dakota. Factors that were identified as influencing the transmission risk include inter-annual variability of vegetation cover, water availability and temperature. Land covers such as grasslands, low developed areas and wetlands were also found to be good predictors for human

  16. Identifying patients with therapy-resistant depression by using factor analysis

    DEFF Research Database (Denmark)

    Andreasson, K; Liest, V; Lunde, M

    2010-01-01

    INTRODUCTION: Attempts to identify the factor structure in patients with treatment-resistant depression have been very limited. METHODS: Principal component analysis was performed using the baseline datasets from 3 add-on studies [2 with repetitive transcranial magnetic stimulation and one...... with transcranial pulsed electromagnetic fields (T-PEMF)], in which the relative effect as percentage of improvement during the treatment period was analysed. RESULTS: We identified 2 major factors, the first of which was a general factor. The second was a dual factor consisting of a depression subscale comprising...... the negatively loaded items (covering the pure depression items) and a treatment resistant subscale comprising the positively loaded items (covering lassitude, concentration difficulties and sleep problems). These 2 dual subscales were used as outcome measures. Improvement on the treatment resistant subscale...

  17. 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

  18. Identifying risk factors for first-episode neck pain: A systematic review.

    Science.gov (United States)

    Kim, Rebecca; Wiest, Colin; Clark, Kelly; Cook, Chad; Horn, Maggie

    2018-02-01

    Neck pain affects 15.1% of the United States' general population every 3 months, and ranks fourth in global disability. Because of the tendency for neck pain to become a chronic issue, it is important to identify risk factors that could encourage prevention and early diagnosis. The purpose of this systematic review was to identify risk factors for a first episode of neck pain. Three databases were searched with key words such as "neck pain" and "first incidence." Risk factors from the resulting articles were reported as either a physical or psychosocial risk factor and ranked by the strength of their odds/risk/hazard ratio: empowering leadership, high perceived social climate, leisure physical activity, and cervical extensor endurance. Most risk factors found for neck pain were related to psychosocial characteristics, rather than physical characteristics. A number of these risk factors were mediating factors, suggesting that a prevention-based program may be useful in modifying the existence of the risk factors before the occurrence of neck pain. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

    OpenAIRE

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

    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...

  20. Identifying risk factors and protective factors for venous leg ulcer recurrence using a theoretical approach: A longitudinal study.

    Science.gov (United States)

    Finlayson, Kathleen; Wu, Min-Lin; Edwards, Helen E

    2015-06-01

    The high recurrence rate of chronic venous leg ulcers has a significant impact on an individual's quality of life and healthcare costs. This study aimed to identify risk and protective factors for recurrence of venous leg ulcers using a theoretical approach by applying a framework of self and family management of chronic conditions to underpin the study. Secondary analysis of combined data collected from three previous prospective longitudinal studies. The contributing studies' participants were recruited from two metropolitan hospital outpatient wound clinics and three community-based wound clinics. Data were available on a sample of 250 adults, with a leg ulcer of primarily venous aetiology, who were followed after ulcer healing for a median follow-up time of 17 months after healing (range: 3-36 months). Data from the three studies were combined. The original participant data were collected through medical records and self-reported questionnaires upon healing and every 3 months thereafter. A Cox proportion-hazards regression analysis was undertaken to determine the influential factors on leg ulcer recurrence based on the proposed conceptual framework. The median time to recurrence was 42 weeks (95% CI 31.9-52.0), with an incidence of 22% (54 of 250 participants) recurrence within three months of healing, 39% (91 of 235 participants) for those who were followed for six months, 57% (111 of 193) by 12 months, 73% (53 of 72) by two years and 78% (41 of 52) of those who were followed up for three years. A Cox proportional-hazards regression model revealed that the risk factors for recurrence included a history of deep vein thrombosis (HR 1.7, 95% CI 1.07-2.67, p=0.024), history of multiple previous leg ulcers (HR 4.4, 95% CI 1.84-10.5, p=0.001), and longer duration (in weeks) of previous ulcer (HR 1.01, 95% CI 1.003-1.01, pulcer recurrence based on the chronic disease self and family management framework. These results in turn provide essential steps towards

  1. Identifying the controlling factors of sedimentation in a recently restored tidal freshwater wetland

    Science.gov (United States)

    van der Perk, Marcel; Verschelling, Eelco; van der Deijl, Eveline; Sloff, Kees; Middelkoop, Hans

    2017-04-01

    Sediment deposition is one of the key mechanisms to counteract the impact of sea level rise in tidal freshwater wetlands (TFWs). In a study to identify the factors controlling sedimentation in a recently restored tidal freshwater wetland in the Biesbosch National Park in the Rhine-Meuse delta - The Netherlands, we adopted both a modelling and a field measurement approach. This approximately 700 ha large tidal freshwater wetland is characterised by two openings with the main inlet connected to the Nieuwe Merwede river, a distributary of the River Rhine, two artificial channels connecting the in- and outlet of the area, and tidal flats. We quantified the sediment budgets of the TFW using 10-minute interval measurement of water level, discharge and suspended sediment concentration at the in- and outlet of the area for several events including a river discharge event and several windstorm events, and for different tidal ranges. In addition, we conducted 14 numerical experiments using a combined hydrodynamic and sediment transport model to simulate sedimentation rates and patterns for different river discharges, windstorm magnitudes, and tidal conditions. Both the results from the field measurements and the modelling results show that the overall sediment budget is positive in the area and increases with river discharge due to the associated higher water inflow and suspended sediment concentrations at the main inlet of the study area. The short-term sediment budget is generally positive during flood and negative during ebb, but the net sediment budget during a tidal cycle is not influenced by the tidal range. The sedimentation rates decrease with increasing windstorm magnitude, as wind waves cause sediment resuspension on the tidal flats and transport of the resuspended sediment towards the channels. Sediment trapping efficiencies are in the order of 45% of the incoming sediment load, but decrease with increasing river discharge and wind magnitude. The effect of wind on

  2. WordSpy: identifying transcription factor binding motifs by building a dictionary and learning a grammar.

    Science.gov (United States)

    Wang, Guandong; Yu, Taotao; Zhang, Weixiong

    2005-07-01

    Transcription factor (TF) binding sites or motifs (TFBMs) are functional cis-regulatory DNA sequences that play an essential role in gene transcriptional regulation. Although many experimental and computational methods have been developed, finding TFBMs remains a challenging problem. We propose and develop a novel dictionary based motif finding algorithm, which we call WordSpy. One significant feature of WordSpy is the combination of a word counting method and a statistical model which consists of a dictionary of motifs and a grammar specifying their usage. The algorithm is suitable for genome-wide motif finding; it is capable of discovering hundreds of motifs from a large set of promoters in a single run. We further enhance WordSpy by applying gene expression information to separate true TFBMs from spurious ones, and by incorporating negative sequences to identify discriminative motifs. In addition, we also use randomly selected promoters from the genome to evaluate the significance of the discovered motifs. The output from WordSpy consists of an ordered list of putative motifs and a set of regulatory sequences with motif binding sites highlighted. The web server of WordSpy is available at http://cic.cs.wustl.edu/wordspy.

  3. Identifying Associations Between Brain Imaging Phenotypes and Genetic Factors via A Novel Structured SCCA Approach.

    Science.gov (United States)

    Du, Lei; Zhang, Tuo; Liu, Kefei; Yan, Jingwen; Yao, Xiaohui; Risacher, Shannon L; Saykin, Andrew J; Han, Junwei; Guo, Lei; Shen, Li

    2017-06-01

    Brain imaging genetics attracts more and more attention since it can reveal associations between genetic factors and the structures or functions of human brain. Sparse canonical correlation analysis (SCCA) is a powerful bi-multivariate association identification technique in imaging genetics. There have been many SCCA methods which could capture different types of structured imaging genetic relationships. These methods either use the group lasso to recover the group structure, or employ the graph/network guided fused lasso to find out the network structure. However, the group lasso methods have limitation in generalization because of the incomplete or unavailable prior knowledge in real world. The graph/network guided methods are sensitive to the sign of the sample correlation which may be incorrectly estimated. We introduce a new SCCA model using a novel graph guided pairwise group lasso penalty, and propose an efficient optimization algorithm. The proposed method has a strong upper bound for the grouping effect for both positively and negatively correlated variables. We show that our method performs better than or equally to two state-of-the-art SCCA methods on both synthetic and real neuroimaging genetics data. In particular, our method identifies stronger canonical correlations and captures better canonical loading profiles, showing its promise for revealing biologically meaningful imaging genetic associations.

  4. 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.

  5. Analysis Approach to Identify Factors Influencing Digital Learning Technology Adoption and Utilization in Developing Countries

    Directory of Open Access Journals (Sweden)

    Abubaker Kashada

    2018-02-01

    Full Text Available The Internet has given learners the ability to learn anytime and anywhere at their own pace facilitated by interactive and adaptive software. Digital learning technology is more than just providing students with a laptop. Digital learning requires a combination of technology, digital content, and instruction. This study aims to identify and observe the impact and mediation of top management support in relation to the successful adoption of digital learning technologies in developing countries. A questionnaire was designed and distributed to rate the successful adoption and utilization of digital learning technologies in developing countries and data was analyzed using structural equation modeling. This study provides empirical evidence and explains many complex factors, such as user awareness, perceived usefulness, perceived ease of use, and information communication technology infrastructure, in the context of top management support to facilitate the effective utilization of a digital learning technology. Mediating the top management support between adoption of a digital learning technology and user awareness, perceived usefulness, and perceived ease of use provides clear and crucial evidence to support the effective adoption of a digital learning technology.

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

    International Nuclear Information System (INIS)

    Thomassen, Mads; Tan, Qihua; Kruse, Torben A

    2008-01-01

    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 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. We have analyzed 8 publicly available gene expression data sets. A global approach, 'gene set enrichment analysis' as well as an approach focusing on a subset of significantly differently regulated genes, GenMAPP, has been applied to rank pathway gene sets according to differential regulation in metastasizing tumors compared to non-metastasizing tumors. Meta-analysis has been used to determine overrepresentation of pathways and transcription factors targets, concordant deregulated in metastasizing breast tumors, in several data sets. The major findings are up-regulation of cell cycle pathways and a metabolic shift towards glucose metabolism reflected in several pathways in metastasizing tumors. Growth factor pathways seem to play dual roles; EGF and PDGF pathways are decreased, while VEGF and sex-hormone pathways are increased in tumors that metastasize. Furthermore, migration, proteasome, immune 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. By pathway meta-analysis many biological mechanisms beyond major characteristics such as proliferation are identified. Transcription factor analysis identifies a number of key factors that support central pathways. Several previously proposed treatment targets are identified and several new pathways that may

  7. 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.

  8. 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,…

  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. TB/HIV risk factors identified from a General Household Survey of ...

    African Journals Online (AJOL)

    TB/HIV risk factors identified from a General Household Survey of South Africa in 2006. ... This study examined TB and HIV affecting people living in South Africa. ... Therefore, follow-up care and special preventative measures are urgently needed in provinces with higher reported rates of TB and/or HIV such as KN.

  11. Using exploratory factor analysis of FFQ data to identify dietary patterns among Yup'ik people.

    Science.gov (United States)

    Ryman, Tove K; Austin, Melissa A; Hopkins, Scarlett; Philip, Jacques; O'Brien, Diane; Thummel, Kenneth; Boyer, Bert B

    2014-03-01

    An FFQ developed by the Center for Alaska Native Health Research for studies in Yup'ik people includes market foods and subsistence foods such as moose, seal, waterfowl and salmon that may be related to disease risk. Because the FFQ contains >100 food items, we sought to characterize dietary patterns more simply for use in ongoing pharmacogenomics studies. Exploratory factor analysis was used to derive a small number of 'factors' that explain a substantial amount of the variation in the Yup'ik diet. We estimated factor scores and measured associations with demographic characteristics and biomarkers. South-west Alaska, USA. Yup'ik people (n 358) aged ≥18 years. We identified three factors that each accounted for ≥10 % of the common variance: the first characterized by 'processed foods' (e.g. salty snacks, sweetened cereals); the second by 'fruits and vegetables' (e.g. fresh citrus, potato salad); and the third by 'subsistence foods' (seal or walrus soup, non-oily fish). Participants from coastal communities had higher values for the 'subsistence' factor, whereas participants from inland communities had higher values for the 'fruits and vegetables' factor. A biomarker of marine intake, δ 15N, was correlated with the 'subsistence' factor, whereas a biomarker of corn- and sugarcane-based market food intake, δ 13C, was correlated with 'processed foods'. The exploratory factor analysis identified three factors that appeared to reflect dietary patterns among Yup'ik based on associations with participant characteristics and biomarkers. These factors will be useful for chronic disease studies in this population.

  12. Risk Factors in Domestic Homicides: Identifying Common Clusters in the Canadian Context.

    Science.gov (United States)

    Dawson, Myrna; Piscitelli, Anthony

    2017-09-01

    Little research has attempted to examine risk factor combinations when examining intimate partner violence. A variety of risk factors have been identified in domestic homicides, and it is recognized that risk of lethality may increase with the presence of more rather than less risk factors. This relationship is not necessarily linear, however. The objective of this study was to identify whether particular risk factor combinations are common in cases of domestic homicide. The study comprised 183 deaths that occurred between 2002 and 2012 and were reviewed by the Domestic Violence Death Review Committee, Office of the Chief Coroner of Ontario, Canada, with particular focus on the presence/absence of 40 empirically based risk factors. The analyses identified three distinct risk factor clusters that differed primarily by victim-perpetrator relationship and the likelihood of perpetrator suicide or attempts to commit suicide. Cases involving perpetrators currently in legal marriages or cohabitating with their victims were most common among the Non-Depressed/Non-Violent Cluster followed by the Depressed/Violent Cluster. In contrast, the majority of those in the Non-Depressed/Violent Cluster were estranged from their victims and the least likely to attempt/commit suicide. The study demonstrates that particular risk factor combinations are common in cases of domestic homicide. Future research should expand the number of risk factors examined, increase the sample size to further test cluster validity, and compare lethal and non-lethal intimate partner violence and homicide to allow for an examination of the clusters more unique to lethality. Prevention initiatives should emphasize the heterogeneity of domestic homicides and target specific interventions.

  13. 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 2 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 nursing interventions designed to reduce bothersome behaviors as identified by family caregivers. PMID:23686515

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

    Science.gov (United States)

    Chakraborty, Joheen; Banerji, Sugata

    2018-03-01

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

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

    Science.gov (United States)

    Kolossa, Antonio; Kopp, Bruno

    2016-01-01

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

  16. Construction and Research of System Identifiable Mathematical Models

    OpenAIRE

    Robertas Janickas

    2011-01-01

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

  17. Construction and Research of System Identifiable Mathematical Models

    Directory of Open Access Journals (Sweden)

    Robertas Janickas

    2011-08-01

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

  18. Identifying at-risk profiles and protective factors for problem gambling: A longitudinal study across adolescence and early adulthood.

    Science.gov (United States)

    Allami, Youssef; Vitaro, Frank; Brendgen, Mara; Carbonneau, René; Tremblay, Richard E

    2018-03-19

    Past studies have identified various risk and protective factors for problem gambling (PG). However, no study has examined the interplay between these factors using a combination of person-centered and variable-centered approaches embedded within a longitudinal design. The present study aimed to (a) identify distinct profiles in early adolescence based on a set of risk factors commonly associated with PG (impulsivity, depression, anxiety, drug-alcohol use, aggressiveness, and antisociality), (b) explore the difference in reported gambling problems between these profiles during midadolescence and early adulthood, and (c) identify family- and peer-related variables that could operate as protective or compensatory factors in this context. Two samples were used: (a) a population sample (N = 1,033) living in low socioeconomic-status neighborhoods and (b) a population sample (N = 3,017) representative of students attending Quebec schools. Latent profile analyses were conducted to identify at-risk profiles based on individual risk factors measured at age 12 years. Negative binomial regression models were estimated to compare profiles in terms of their reported gambling problems at ages 16 and 23. Finally, family- and peer-related variables measured at age 14 were included to test their protective or compensatory role with respect to the link between at-risk profiles and gambling problems. Four profiles were identified: well-adjusted, internalizing, externalizing, and comorbid. Compared to the well-adjusted profile, the externalizing and comorbid profiles reported more gambling problems at ages 16 and 23, but the internalizing profile did not differ significantly. Various protective and compensatory factors emerged for each profile at both time points. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  19. 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

  20. 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.

  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. Identifying sex-specific risk factors for stress fractures in adolescent runners.

    Science.gov (United States)

    Tenforde, Adam S; Sayres, Lauren C; McCurdy, Mary Liz; Sainani, Kristin L; Fredericson, Michael

    2013-10-01

    Adolescent females and males participating in running represent a population at high risk of stress fracture. Few investigators have evaluated risk factors for prospective stress fracture in this population. To better characterize risk factors for and incidence of stress fractures in this population, we collected baseline risk factor data on 748 competitive high school runners (442 girls and 306 boys) using an online survey. We then followed them prospectively for the development of stress fractures for a mean ± SD of 2.3 ± 1.2 total seasons of cross-country and track and field; follow-up data were available for 428 girls and 273 boys. We identified prospective stress fractures in 5.4% of girls (n = 23) and 4.0% of boys (n = 11). Tibial stress fractures were most common in girls, and the metatarsus was most frequently fractured in boys. Multivariate regression identified four independent risk factors for stress fractures in girls: prior fracture, body mass index dance. For boys, prior fracture and increased number of seasons were associated with an increased rate of stress fractures, whereas prior participation in basketball was associated with a decreased risk of stress fractures. Prior fracture represents the most robust predictor of stress fractures in both sexes. Low body mass index, late menarche, and prior participation in gymnastics and dance are identifiable risk factors for stress fractures in girls. Participation in basketball appears protective in boys and may represent a modifiable risk factor for stress fractures. These findings may help guide future translational research and clinical care in the management and prevention of stress fractures in young runners.

  3. Identifying Objective and Subjective Words via Topic Modeling.

    Science.gov (United States)

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

    2018-03-01

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

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

    Science.gov (United States)

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

    2017-01-01

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

  5. Identifying Model-Based Reconfiguration Goals through Functional Deficiencies

    Science.gov (United States)

    Benazera, Emmanuel; Trave-Massuyes, Louise

    2004-01-01

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

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

    Directory of Open Access Journals (Sweden)

    CA Bisschoff

    2014-08-01

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

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

    Science.gov (United States)

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

    2009-05-01

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

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

    Science.gov (United States)

    Czarnatowicz, Alexis; Ybarra, Jason E.

    2018-01-01

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

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

    Indian Academy of Sciences (India)

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

  10. Resident Workflow and Psychiatric Emergency Consultation: Identifying Factors for Quality Improvement in a Training Environment.

    Science.gov (United States)

    Blair, Thomas; Wiener, Zev; Seroussi, Ariel; Tang, Lingqi; O'Hora, Jennifer; Cheung, Erick

    2017-06-01

    Quality improvement to optimize workflow has the potential to mitigate resident burnout and enhance patient care. This study applied mixed methods to identify factors that enhance or impede workflow for residents performing emergency psychiatric consultations. The study population consisted of all psychiatry program residents (55 eligible, 42 participating) at the Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles. The authors developed a survey through iterative piloting, surveyed all residents, and then conducted a focus group. The survey included elements hypothesized to enhance or impede workflow, and measures pertaining to self-rated efficiency and stress. Distributional and bivariate analyses were performed. Survey findings were clarified in focus group discussion. This study identified several factors subjectively associated with enhanced or impeded workflow, including difficulty with documentation, the value of personal organization systems, and struggles to communicate with patients' families. Implications for resident education are discussed.

  11. 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…

  12. 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.

  13. Identifying practice-related factors for high-volume prescribers of antibiotics in Danish general practice

    DEFF Research Database (Denmark)

    Aabenhus, Rune; Siersma, Volkert; Sandholdt, Håkon

    2017-01-01

    Objectives: In Denmark, general practice is responsible for 75% of antibiotic prescribing in the primary care sector. We aimed to identify practice-related factors associated with high prescribers, including prescribers of critically important antibiotics as defined by WHO, after accounting for c...... underuse or overuse of diagnostic tests in general practice as well as organizational factors were associated with high-prescribing practices. Furthermore, the choice of antibiotic type seemed less rational among high prescribers.......Objectives: In Denmark, general practice is responsible for 75% of antibiotic prescribing in the primary care sector. We aimed to identify practice-related factors associated with high prescribers, including prescribers of critically important antibiotics as defined by WHO, after accounting...... for case mix by practice. Methods: We performed a nationwide register-based survey of antibiotic prescribing in Danish general practice from 2012 to 2013. The unit of analysis was the individual practice. We used multivariable regression analyses and an assessment of relative importance to identify...

  14. Transcription factor expression uniquely identifies most postembryonic neuronal lineages in the Drosophila thoracic central nervous system.

    Science.gov (United States)

    Lacin, Haluk; Zhu, Yi; Wilson, Beth A; Skeath, James B

    2014-03-01

    Most neurons of the adult Drosophila ventral nerve cord arise from a burst of neurogenesis during the third larval instar stage. Most of this growth occurs in thoracic neuromeres, which contain 25 individually identifiable postembryonic neuronal lineages. Initially, each lineage consists of two hemilineages--'A' (Notch(On)) and 'B' (Notch(Off))--that exhibit distinct axonal trajectories or fates. No reliable method presently exists to identify these lineages or hemilineages unambiguously other than labor-intensive lineage-tracing methods. By combining mosaic analysis with a repressible cell marker (MARCM) analysis with gene expression studies, we constructed a gene expression map that enables the rapid, unambiguous identification of 23 of the 25 postembryonic lineages based on the expression of 15 transcription factors. Pilot genetic studies reveal that these transcription factors regulate the specification and differentiation of postembryonic neurons: for example, Nkx6 is necessary and sufficient to direct axonal pathway selection in lineage 3. The gene expression map thus provides a descriptive foundation for the genetic and molecular dissection of adult-specific neurogenesis and identifies many transcription factors that are likely to regulate the development and differentiation of discrete subsets of postembryonic neurons.

  15. 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.

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

    Directory of Open Access Journals (Sweden)

    James R Hatten

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

  17. Identifying Critical Factors in the Eco-Efficiency of Remanufacturing Based on the Fuzzy DEMATEL Method

    Directory of Open Access Journals (Sweden)

    Qianwang Deng

    2015-11-01

    Full Text Available Remanufacturing can bring considerable economic and environmental benefits such as cost saving, conservation of energy and resources, and reduction of emissions. With the increasing awareness of sustainable manufacturing, remanufacturing gradually becomes the research priority. Most studies concentrate on the analysis of influencing factors, or the evaluation of the economic and environmental performance in remanufacturing, while little effort has been devoted to investigating the critical factors influencing the eco-efficiency of remanufacturing. Considering the current development of the remanufacturing industry in China, this paper proposes a set of factors influencing the eco-efficiency of remanufacturing and then utilizes a fuzzy Decision Making Trial and Evaluation Laboratory (DEMATEL method to establish relation matrixes reflecting the interdependent relationships among these factors. Finally, the contributions of each factor to eco-efficiency and mutual influence values among them are obtained, and critical factors in eco-efficiency of remanufacturing are identified. The results of the present work can provide theoretical supports for the government to make appropriate policies to improve the eco-efficiency of remanufacturing.

  18. Analyzing and identifying risk factors for acute pancreatitis with different etiologies in pregnancy.

    Science.gov (United States)

    Jin, Jin; Yu, Yan-hong; Zhong, Mei; Zhang, Guo-wei

    2015-02-01

    To identify the risk factors of acute pancreatitis (AP) associated with different etiologies, in pregnancy (APP). Forty-seven eligible patients were divided into two groups: biliary acute pancreatitis in pregnancy (BAPP, n = 31) and hypertriglyceridemic-induced pancreatitis in pregnancy (HAPP, n = 16). Multivariate analysis was utilized in identifying independent risk factors of BAPP and HAPP. The independent risk factors of BAPP included gallbladder stones (OR, 3.924; p = 0.007) and high-fat diet in pregnancy (OR, 4.878; p = 0.001). Hypertriglyceridemia (OR, 3.667; p = 0.035) was the only independent risk factor for HAPP. Based on the severity of AP, no significant differences in adverse outcomes were found between BAPP and HAPP. High-fat diet should be prohibited for gravida with biliary diseases. Compared to biliary tract stones, the study observed that gallstones were more likely to cause AP for pregnant women. Hypertriglyceridemic pregnant women were found to be more susceptible to AP.

  19. Factor Analysis of Therapist-Identified Treatment Targets in Community-Based Children's Mental Health.

    Science.gov (United States)

    Love, Allison R; Okado, Izumi; Orimoto, Trina E; Mueller, Charles W

    2018-01-01

    The present study used exploratory and confirmatory factor analyses to identify underlying latent factors affecting variation in community therapists' endorsement of treatment targets. As part of a statewide practice management program, therapist completed monthly reports of treatment targets (up to 10 per month) for a sample of youth (n = 790) receiving intensive in-home therapy. Nearly 75 % of youth were diagnosed with multiple co-occurring disorders. Five factors emerged: Disinhibition, Societal Rules Evasion, Social Engagement Deficits, Emotional Distress, and Management of Biodevelopmental Outcomes. Using logistic regression, primary diagnosis predicted therapist selection of Disinhibition and Emotional Distress targets. Client age predicted endorsement of Societal Rules Evasion targets. Practice-to-research implications are discussed.

  20. Design Factors Affecting the Reaction Time for Identifying Toilet Signs: A Preliminary Study.

    Science.gov (United States)

    Chen, Yi-Lang; Sie, Cai-Cin

    2016-04-01

    This study focused on the manner in which design factors affect the reaction time for identifying toilet signs. Taiwanese university students and staff members (50 men, 50 women; M age = 23.5 year, SD = 5.7) participated in the study. The 36 toilet signs were modified on three factors (six presenting styles, two figure-ground exchanges, and three colors), and the reaction time data of all participants were collected when the signs were presented in a simulation onscreen. Participants were quickest when reading Chinese text, followed by graphics and English texts. The findings also showed that men and women had different reaction times across various design combinations. These findings can serve as a reference for practically designing toilet signs, since design factors can lead to difficulties with comprehension based on reaction time measurements. © The Author(s) 2016.

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

    Science.gov (United States)

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

    2015-10-01

    In an effort to better understand meaning from natural language texts, we explore methods aimed at organizing lexical objects into contexts. A number of these methods for organization fall into a family defined by word ordering. Unlike demographic or spatial partitions of data, these collocation models are of special importance for their universal applicability. While we are interested here in text and have framed our treatment appropriately, our work is potentially applicable to other areas of research (e.g., speech, genomics, and mobility patterns) where one has ordered categorical data (e.g., sounds, genes, and locations). Our approach focuses on the phrase (whether word or larger) as the primary meaning-bearing lexical unit and object of study. To do so, we employ our previously developed framework for generating word-conserving phrase-frequency data. Upon training our model with the Wiktionary, an extensive, online, collaborative, and open-source dictionary that contains over 100000 phrasal definitions, we develop highly effective filters for the identification of meaningful, missing phrase entries. With our predictions we then engage the editorial community of the Wiktionary and propose short lists of potential missing entries for definition, developing a breakthrough, lexical extraction technique and expanding our knowledge of the defined English lexicon of phrases.

  2. Identifying factors of bicycle comfort: An online survey with enthusiast cyclists.

    Science.gov (United States)

    Ayachi, F S; Dorey, J; Guastavino, C

    2015-01-01

    Racing bicycles have evolved significantly over the past decades as technology and cyclists' comfort have become a critical design issue. Although ample research has been conducted on comfort for other means of transportation, cyclists' perception of dynamic comfort has received scant attention in the scientific literature. The present study investigates how enthusiast cyclists conceptualize comfort using an online survey with 244 respondents. The purpose is to determine which factors contribute to comfort when riding a bicycle, to identify situations in which comfort is relevant and to determine the extent to which vibrations play a role in comfort evaluations. We found that comfort is influenced by factors related to bicycle components (specifically the frame, saddle and handlebar), as well as environmental factors (type or road, weather conditions) and factors related to the cyclist (position, adjustments, body parts). Respondents indicated that comfort is a concern when riding a bicycle in most situations and they believed that comfort is compatible with performance. The PCA analysis shows that for the perception "human factor-body parts" are put in evidence, and the "cyclist's comfort" evaluation is mainly based on certain qualities related to the bicycle components, then the road and external conditions (e.g. weather, temperature). Copyright © 2014 Elsevier Ltd and The Ergonomics Society. All rights reserved.

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

    Science.gov (United States)

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

    2017-05-01

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

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

    Science.gov (United States)

    Weng, Stephen Franklin; Redsell, Sarah A; Swift, Judy A; Yang, Min; Glazebrook, Cristine P

    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 independent associations with childhood overweight were identified for maternal pre-pregnancy overweight, high infant birth weight and rapid weight gain during the first year of life. Meta-analysis comparing breastfed with non-breastfed infants found a 15% decrease (95% CI 0.74 to 0.99; I2=73.3%; n=10) in the odds of childhood overweight. For children of mothers smoking during pregnancy there was a 47% increase (95% CI 1.26 to 1.73; I2=47.5%; n=7) in the odds of childhood overweight. There was some evidence associating early introduction of solid foods and childhood overweight. There was conflicting evidence for duration of breastfeeding, socioeconomic status at birth, parity and maternal marital status at birth. No association with childhood overweight was found for maternal age or education at birth, maternal depression or infant ethnicity. There was inconclusive evidence for delivery type, gestational weight gain, maternal postpartum weight loss and ‘fussy’ infant temperament due to the limited number of studies. Conclusions Several risk factors for both overweight and obesity in childhood are identifiable during infancy. Future research needs to focus on whether it is clinically feasible for healthcare professionals to identify infants at greatest risk. PMID:23109090

  5. Dietary patterns as identified by factor analysis and colorectal cancer among middle-aged Americans.

    Science.gov (United States)

    Flood, Andrew; Rastogi, Tanuja; Wirfält, Elisabet; Mitrou, Panagiota N; Reedy, Jill; Subar, Amy F; Kipnis, Victor; Mouw, Traci; Hollenbeck, Albert R; Leitzmann, Michael; Schatzkin, Arthur

    2008-07-01

    Although diet has long been suspected as an etiological factor for colorectal cancer, studies of single foods and nutrients have provided inconsistent results. We used factor analysis methods to study associations between dietary patterns and colorectal cancer in middle-aged Americans. Diet was assessed among 293,615 men and 198,767 women in the National Institutes of Health-AARP Diet and Health Study. Principal components factor analysis identified 3 primary dietary patterns: a fruit and vegetables, a diet foods, and a red meat and potatoes pattern. State cancer registries identified 2151 incident cases of colorectal cancer in men and 959 in women between 1995 and 2000. Men with high scores on the fruit and vegetable pattern were at decreased risk [relative risk (RR) for quintile (Q) 5 versus Q1: 0.81; 95% CI: 0.70, 0.93; P for trend = 0.004]. Both men and women had a similar risk reduction with high scores on the diet food factor: men (RR: 0.82; 95% CI: 0.72, 0.94; P for trend = 0.001) and women (RR: 0.87; 95% CI: 0.71, 1.07; P for trend = 0.06). High scores on the red meat factor were associated with increased risk: men (RR: 1.17; 95% CI: 1.02, 1.35; P for trend = 0.14) and women (RR: 1.48; 95% CI: 1.20, 1.83; P for trend = 0.0002). These results suggest that dietary patterns characterized by a low frequency of meat and potato consumption and frequent consumption of fruit and vegetables and fat-reduced foods are consistent with a decreased risk of colorectal cancer.

  6. The Five-Factor Model: General Overview

    Directory of Open Access Journals (Sweden)

    A A Vorobyeva

    2011-12-01

    Full Text Available The article describes the five-factor model (FFM, giving an overview of its history, basic dimensions, cross-cultural research conducted on the model and highlights some practical studies based on the FFM, including the studies on job performance, leader performance and daily social interactions. An overview of the recent five-factor theory is also provided. According to the theory, the five factors are encoded in human genes, therefore it is almost impossible to change the basic factors themselves, but a person's behavior might be changed due to characteristic adaptations which do not alter personality dimensions, only a person's behavior.

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

    Science.gov (United States)

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

    2014-01-01

    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.

  8. 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.

  9. Using a Delphi Method to Identify Human Factors Contributing to Nursing Errors.

    Science.gov (United States)

    Roth, Cheryl; Brewer, Melanie; Wieck, K Lynn

    2017-07-01

    The purpose of this study was to identify human factors associated with nursing errors. Using a Delphi technique, this study used feedback from a panel of nurse experts (n = 25) on an initial qualitative survey questionnaire followed by summarizing the results with feedback and confirmation. Synthesized factors regarding causes of errors were incorporated into a quantitative Likert-type scale, and the original expert panel participants were queried a second time to validate responses. The list identified 24 items as most common causes of nursing errors, including swamping and errors made by others that nurses are expected to recognize and fix. The responses provided a consensus top 10 errors list based on means with heavy workload and fatigue at the top of the list. The use of the Delphi survey established consensus and developed a platform upon which future study of nursing errors can evolve as a link to future solutions. This list of human factors in nursing errors should serve to stimulate dialogue among nurses about how to prevent errors and improve outcomes. Human and system failures have been the subject of an abundance of research, yet nursing errors continue to occur. © 2016 Wiley Periodicals, Inc.

  10. [Lake eutrophication modeling in considering climatic factors change: a review].

    Science.gov (United States)

    Su, Jie-Qiong; Wang, Xuan; Yang, Zhi-Feng

    2012-11-01

    Climatic factors are considered as the key factors affecting the trophic status and its process in most lakes. Under the background of global climate change, to incorporate the variations of climatic factors into lake eutrophication models could provide solid technical support for the analysis of the trophic evolution trend of lake and the decision-making of lake environment management. This paper analyzed the effects of climatic factors such as air temperature, precipitation, sunlight, and atmosphere on lake eutrophication, and summarized the research results about the lake eutrophication modeling in considering in considering climatic factors change, including the modeling based on statistical analysis, ecological dynamic analysis, system analysis, and intelligent algorithm. The prospective approaches to improve the accuracy of lake eutrophication modeling with the consideration of climatic factors change were put forward, including 1) to strengthen the analysis of the mechanisms related to the effects of climatic factors change on lake trophic status, 2) to identify the appropriate simulation models to generate several scenarios under proper temporal and spatial scales and resolutions, and 3) to integrate the climatic factors change simulation, hydrodynamic model, ecological simulation, and intelligent algorithm into a general modeling system to achieve an accurate prediction of lake eutrophication under climatic change.

  11. 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

    2014-12-29

    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.

  12. 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....

  13. Identifying the factors affecting bike-sharing usage and degree of satisfaction in Ningbo, China.

    Science.gov (United States)

    Guo, Yanyong; Zhou, Jibiao; Wu, Yao; Li, Zhibin

    2017-01-01

    The boom in bike-sharing is receiving growing attention as societies become more aware of the importance of active non-motorized traffic modes. However, the low usage of this transport mode in China raises concerns. The primary objective of this study is to explore factors affecting bike-sharing usage and satisfaction degree of bike-sharing among the bike-sharing user population in China. Data were collected by a questionnaire survey in Ningbo. A bivariate ordered probit (BOP) model was developed to examine simultaneously those factors associated with both bike-sharing usage and satisfaction degree of bike-sharing among users. Marginal effects for contributory factors were calculated to quantify their impacts on the outcomes. The results showed that the BOP model can account for commonly shared unobserved characteristics within usage and satisfaction of bike-sharing. The BOP model results showed that the usage of bike-sharing was affected by gender, household bicycle/e-bike ownership, trip model, travel time, bike-sharing stations location, and users' perception of bike-sharing. The satisfaction degree of bike-sharing was affected by household income, bike-sharing stations location, and users' perception of bike-sharing. It is also found that bike-sharing usage and satisfaction degree are strongly correlated and positive in direction. The results can enhance our comprehension of the factors that affect usage and satisfaction degree of bike-sharing. Based on the results, some suggestions regarding planning, engineering, and public advocacy were discussed to increase the usage of bike-sharing in Ningbo, China.

  14. Identifying the factors affecting bike-sharing usage and degree of satisfaction in Ningbo, China.

    Directory of Open Access Journals (Sweden)

    Yanyong Guo

    Full Text Available The boom in bike-sharing is receiving growing attention as societies become more aware of the importance of active non-motorized traffic modes. However, the low usage of this transport mode in China raises concerns. The primary objective of this study is to explore factors affecting bike-sharing usage and satisfaction degree of bike-sharing among the bike-sharing user population in China. Data were collected by a questionnaire survey in Ningbo. A bivariate ordered probit (BOP model was developed to examine simultaneously those factors associated with both bike-sharing usage and satisfaction degree of bike-sharing among users. Marginal effects for contributory factors were calculated to quantify their impacts on the outcomes. The results showed that the BOP model can account for commonly shared unobserved characteristics within usage and satisfaction of bike-sharing. The BOP model results showed that the usage of bike-sharing was affected by gender, household bicycle/e-bike ownership, trip model, travel time, bike-sharing stations location, and users' perception of bike-sharing. The satisfaction degree of bike-sharing was affected by household income, bike-sharing stations location, and users' perception of bike-sharing. It is also found that bike-sharing usage and satisfaction degree are strongly correlated and positive in direction. The results can enhance our comprehension of the factors that affect usage and satisfaction degree of bike-sharing. Based on the results, some suggestions regarding planning, engineering, and public advocacy were discussed to increase the usage of bike-sharing in Ningbo, China.

  15. Pilot Critical Incident Reports as a Means to Identify Human Factors of Remotely Piloted Aircraft

    Science.gov (United States)

    Hobbs, Alan; Cardoza, Colleen; Null, Cynthia

    2016-01-01

    It has been estimated that aviation accidents are typically preceded by numerous minor incidents arising from the same causal factors that ultimately produced the accident. Accident databases provide in-depth information on a relatively small number of occurrences, however incident databases have the potential to provide insights into the human factors of Remotely Piloted Aircraft System (RPAS) operations based on a larger volume of less-detailed reports. Currently, there is a lack of incident data dealing with the human factors of unmanned aircraft systems. An exploratory study is being conducted to examine the feasibility of collecting voluntary critical incident reports from RPAS pilots. Twenty-three experienced RPAS pilots volunteered to participate in focus groups in which they described critical incidents from their own experience. Participants were asked to recall (1) incidents that revealed a system flaw, or (2) highlighted a case where the human operator contributed to system resilience or mission success. Participants were asked to only report incidents that could be included in a public document. During each focus group session, a note taker produced a de-identified written record of the incident narratives. At the end of the session, participants reviewed each written incident report, and made edits and corrections as necessary. The incidents were later analyzed to identify contributing factors, with a focus on design issues that either hindered or assisted the pilot during the events. A total of 90 incidents were reported. Human factor issues included the impact of reduced sensory cues, traffic separation in the absence of an out-the-window view, control latencies, vigilance during monotonous and ultra-long endurance flights, control station design considerations, transfer of control between control stations, the management of lost link procedures, and decision-making during emergencies. Pilots participated willingly and enthusiastically in the study

  16. Identifying sources of atmospheric fine particles in Havana City using Positive Matrix Factorization technique

    International Nuclear Information System (INIS)

    Pinnera, I.; Perez, G.; Ramos, M.; Guibert, R.; Aldape, F.; Flores M, J.; Martinez, M.; Molina, E.; Fernandez, A.

    2011-01-01

    In previous study a set of samples of fine and coarse airborne particulate matter collected in a urban area of Havana City were analyzed by Particle-Induced X-ray Emission (PIXE) technique. The concentrations of 14 elements (S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Br and Pb) were consistently determined in both particle sizes. The analytical database provided by PIXE was statistically analyzed in order to determine the local pollution sources. The Positive Matrix Factorization (PMF) technique was applied to fine particle data in order to identify possible pollution sources. These sources were further verified by enrichment factor (EF) calculation. A general discussion about these results is presented in this work. (Author)

  17. 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......). 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...... if the patient has a prior fracture or declined body height. Since fallers generally have higher fracture risk, the ED might serve as an additional entrance to osteodensitometry compared to referral from primary care....

  18. Genome-Wide Association Study of Golden Retrievers Identifies Germ-Line Risk Factors Predisposing to Mast Cell Tumours.

    Directory of Open Access Journals (Sweden)

    Maja L Arendt

    2015-11-01

    Full Text Available Canine mast cell tumours (CMCT are one of the most common skin tumours in dogs with a major impact on canine health. Certain breeds have a higher risk of developing mast cell tumours, suggesting that underlying predisposing germ-line genetic factors play a role in the development of this disease. The genetic risk factors are largely unknown, although somatic mutations in the oncogene C-KIT have been detected in a proportion of CMCT, making CMCT a comparative model for mastocytosis in humans where C-KIT mutations are frequent. We have performed a genome wide association study in golden retrievers from two continents and identified separate regions in the genome associated with risk of CMCT in the two populations. Sequence capture of associated regions and subsequent fine mapping in a larger cohort of dogs identified a SNP associated with development of CMCT in the GNAI2 gene (p = 2.2x10-16, introducing an alternative splice form of this gene resulting in a truncated protein. In addition, disease associated haplotypes harbouring the hyaluronidase genes HYAL1, HYAL2 and HYAL3 on cfa20 and HYAL4, SPAM1 and HYALP1 on cfa14 were identified as separate risk factors in European and US golden retrievers, respectively, suggesting that turnover of hyaluronan plays an important role in the development of CMCT.

  19. 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.

  20. The use of human factors methods to identify and mitigate safety issues in radiation therapy

    International Nuclear Information System (INIS)

    Chan, Alvita J.; Islam, Mohammad K.; Rosewall, Tara; Jaffray, David A.; Easty, Anthony C.; Cafazzo, Joseph A.

    2010-01-01

    Background and purpose: New radiation therapy technologies can enhance the quality of treatment and reduce error. However, the treatment process has become more complex, and radiation dose is not always delivered as intended. Using human factors methods, a radiotherapy treatment delivery process was evaluated, and a redesign was undertaken to determine the effect on system safety. Material and methods: An ethnographic field study and workflow analysis was conducted to identify human factors issues of the treatment delivery process. To address specific issues, components of the user interface were redesigned through a user-centered approach. Sixteen radiation therapy students were then used to experimentally evaluate the redesigned system through a usability test to determine the effectiveness in mitigating use errors. Results: According to findings from the usability test, the redesigned system successfully reduced the error rates of two common errors (p < .04 and p < .01). It also improved the mean task completion time by 5.5% (p < .02) and achieved a higher level of user satisfaction. Conclusions: These findings demonstrated the importance and benefits of applying human factors methods in the design of radiation therapy systems. Many other opportunities still exist to improve patient safety in this area using human factors methods.

  1. 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.

  2. 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.

  3. Identifying the principal driving factors of water ecosystem dependence and the corresponding indicator species in a pilot City, China

    Science.gov (United States)

    Zhao, C. S.; Shao, N. F.; Yang, S. T.; Xiang, H.; Lou, H. Z.; Sun, Y.; Yang, Z. Y.; Zhang, Y.; Yu, X. Y.; Zhang, C. B.; Yu, Q.

    2018-01-01

    The world's aquatic ecosystems yield numerous vital services, which are essential to human existence but have deteriorated seriously in recent years. By studying the mechanisms of interaction between ecosystems and habitat processes, the constraining factors can be identified, and this knowledge can be used to improve the success rate of ecological restoration initiatives. At present, there is insufficient data on the link between hydrological, water quality factors and the changes in the structure of aquatic communities to allow any meaningful study of driving factors of aquatic ecosystems. In this study, the typical monitoring stations were selected by fuzzy clustering analysis based on the spatial and temporal distribution characteristics of water ecology in Jinan City, the first pilot city for the construction of civilized aquatic ecosystems in China. The dominant species identification model was used to identify the dominant species of the aquatic community. The driving effect of hydrological and water quality factors on dominant species was analyzed by Canonical Correspondence Analysis. Then, the principal factors of aquatic ecosystem dependence were selected. The results showed that there were 10 typical monitoring stations out of 59 monitoring sites, which were representative of aquatic ecosystems, 9 dominant fish species, and 20 dominant invertebrate species. The selection of factors for aquatic ecosystem dependence in Jinan were highly influenced by its regional conditions. Chemical environmental parameters influence the temporal and spatial variation of invertebrate much more than that of fish in Jinan City. However, the methodologies coupling typical monitoring stations selection, dominant species determination and driving factors identification were certified to be a cost-effective way, which can provide in-deep theoretical and technical directions for the restoration of aquatic ecosystems elsewhere.

  4. 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.

  5. Depression in Intimate Partner Violence Victims in Slovenia: A Crippling Pattern of Factors Identified in Family Practice Attendees.

    Science.gov (United States)

    Guček, Nena Kopčavar; Selič, Polona

    2018-01-26

    This multi-centre cross-sectional study explored associations between prevalence of depression and exposure to intimate partner violence (IPV) at any time in patients' adult life in 471 participants of a previous IPV study. In 2016, 174 interviews were performed, using the Short Form Domestic Violence Exposure Questionnaire, the Zung Scale and questions about behavioural patterns of exposure to IPV. Family doctors reviewed patients' medical charts for period from 2012 to 2016, using the Domestic Violence Exposure Medical Chart Check List, for conditions which persisted for at least three years. Depression was found to be associated with any exposure to IPV in adult life and was more likely to affect women. In multivariable logistic regression modelling, factors associated with self-rated depression were identified (p < 0.05). Exposure to emotional and physical violence was identified as a risk factor in the first model, explaining 23% of the variance. The second model explained 66% of the variance; past divorce, dysfunctional family relationships and a history of incapacity to work increased the likelihood of depression in patients. Family doctors should consider IPV exposure when detecting depression, since lifetime IPV exposure was found to be 40.4% and 36.9% of depressed revealed it.

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

    DEFF Research Database (Denmark)

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

    2010-01-01

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

  7. Using conditional inference forests to identify the factors affecting crash severity on arterial corridors.

    Science.gov (United States)

    Das, Abhishek; Abdel-Aty, Mohamed; Pande, Anurag

    2009-01-01

    The study aims at identifying traffic/highway design/driver-vehicle information significantly related with fatal/severe crashes on urban arterials for different crash types. Since the data used in this study are observational (i.e., collected outside the purview of a designed experiment), an information discovery approach is adopted for this study. Random Forests, which are ensembles of individual trees grown by CART (Classification and Regression Tree) algorithm, are applied in numerous applications for this purpose. Specifically, conditional inference forests have been implemented. In each tree of the conditional inference forest, splits are based on how good the association is. Chi-square test statistics are used to measure the association. Apart from identifying the variables that improve classification accuracy, the methodology also clearly identifies the variables that are neutral to accuracy, and also those that decrease it. The methodology is quite insightful in identifying the variables of interest in the database (e.g., alcohol/ drug use and higher posted speed limits contribute to severe crashes). Failure to use safety equipment by all passengers and presence of driver/passenger in the vulnerable age group (more than 55 years or less than 3 years) increased the severity of injuries given a crash had occurred. A new variable, 'element' has been used in this study, which assigns crashes to segments, intersections, or access points based on the information from site location, traffic control, and presence of signals. The authors were able to identify roadway locations where severe crashes tend to occur. For example, segments and access points were found to be riskier for single vehicle crashes. Higher skid resistance and k-factor also contributed toward increased severity of injuries in crashes.

  8. Design considerations for identifying breast cancer risk factors in a population-based study in Africa.

    Science.gov (United States)

    Brinton, Louise A; Awuah, Baffour; Nat Clegg-Lamptey, Joe; Wiafe-Addai, Beatrice; Ansong, Daniel; Nyarko, Kofi M; Wiafe, Seth; Yarney, Joel; Biritwum, Richard; Brotzman, Michelle; Adjei, Andrew A; Adjei, Ernest; Aitpillah, Francis; Edusei, Lawrence; Dedey, Florence; Nyante, Sarah J; Oppong, Joseph; Osei-Bonsu, Ernest; Titiloye, Nicholas; Vanderpuye, Verna; Brew Abaidoo, Emma; Arhin, Bernard; Boakye, Isaac; Frempong, Margaret; Ohene Oti, Naomi; Okyne, Victoria; Figueroa, Jonine D

    2017-06-15

    Although breast cancer is becoming more prevalent in Africa, few epidemiologic studies have been undertaken and appropriate methodologic approaches remain uncertain. We therefore conducted a population-based case-control study in Accra and Kumasi, Ghana, enrolling 2,202 women with lesions suspicious for breast cancer and 2,161 population controls. Biopsy tissue for cases prior to neoadjuvant therapy (if given), blood, saliva and fecal samples were sought for study subjects. Response rates, risk factor prevalences and odds ratios for established breast cancer risk factors were calculated. A total of 54.5% of the recruited cases were diagnosed with malignancies, 36.0% with benign conditions and 9.5% with indeterminate diagnoses. Response rates to interviews were 99.2% in cases and 91.9% in controls, with the vast majority of interviewed subjects providing saliva (97.9% in cases vs. 98.8% in controls) and blood (91.8% vs. 82.5%) samples; lower proportions (58.1% vs. 46.1%) provided fecal samples. While risk factor prevalences were unique as compared to women in other countries (e.g., less education, higher parity), cancer risk factors resembled patterns identified elsewhere (elevated risks associated with higher levels of education, familial histories of breast cancer, low parity and larger body sizes). Subjects with benign conditions were younger and exhibited higher socioeconomic profiles (e.g., higher education and lower parity) than those with malignancies, suggesting selective referral influences. While further defining breast cancer risk factors in Africa, this study showed that successful population-based interdisciplinary studies of cancer in Africa are possible but require close attention to diagnostic referral biases and standardized and documented approaches for high-quality data collection, including biospecimens. © 2017 UICC.

  9. Identifying factors associated with the discharge of male State patients from Weskoppies Hospital

    Directory of Open Access Journals (Sweden)

    Riaan G. Prinsloo

    2017-12-01

    Full Text Available Background: Designated psychiatric facilities are responsible for the care, treatment and reintegration of State patients. The necessary long-term care places a considerable strain on health-care resources. Resource use should be optimised while managing the risks that patients pose to themselves and the community. Identifying unique factors associated with earlier discharge may decrease the length of stay. Factors associated with protracted inpatient care without discharge could identify patients who require early and urgent intervention. Aim: We identify socio-economic, demographic, psychiatric and charge-related factors associated with the discharge of male State patients. Methods: We reviewed the files of discharged and admitted forensic State patients at Weskoppies Psychiatric Hospital. Data were captured in an electronic recording sheet. The association between factors and the outcome measure (discharged vs. admitted was determined using chi-squared tests and Fischer’s exact tests. Results: Discharged State patients were associated with being a primary caregiver (p = 0.031 having good insight into illness (p = 0.025 or offence (p = 0.005 and having had multiple successful leaves of absences. A lack of substance abuse during admission (p = 0.027, an absence of a diagnosis of substance use disorder (p = 0.013 and the absence of verbal and physical aggression (p = 0.002 and p = 0.016 were associated with being discharged. Prolonged total length of stay (9–12 years, p = 0.031 and prolonged length of stay in open wards (6–9 years, p = 0.000 were associated with being discharged. A history of previous offences (p = 0.022, a diagnosis of substance use disorder (p = 0.023, recent substance abuse (p = 0.018 and a history of physical aggression since admission (p = 0.017 were associated with continued admission. Conclusion: Discharge of State patients is associated with an absence of substance abuse, lack of aggression

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

    Science.gov (United States)

    Aleem, Aamer

    2010-09-01

    Renal involvement in patients with sickle cell disease (SCD) is associated with significant 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 proteinuria 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 considered 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-ß⁰ thalassemia. None of the parameters evaluated correlated with proteinuria although there was a borderline association with older age and higher systolic blood pressure (P = 0.073 and 0.061 respectively). 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.

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

    Science.gov (United States)

    Healy, J D

    2003-10-01

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

  12. 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.

  13. 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.

  14. Factors associated with phyllodes tumor of the breast after core needle biopsy identifies fibroepithelial neoplasm.

    Science.gov (United States)

    Gould, Daniel J; Salmans, Jessica A; Lassinger, Brian K; Contreras, Alejandro; Gutierrez, Carolina; Bonefas, Elizabeth; Liscum, Kathleen R; Silberfein, Eric J

    2012-11-01

    Phyllodes tumors represent less than 1% of all breast neoplasms and can mimic fibroadenoma on core needle biopsy (CNB). The treatment of fibroepithelial (FE) neoplasms identified on CNB is controversial. We sought to identify factors that were associated with phyllodes tumors after CNB suggested FE neoplasm. A retrospective database was queried for all patients diagnosed with FE neoplasm on CNB at Ben Taub General Hospital over a 10-y period. One hundred twenty-three patients were identified and demographic, clinical, and outcome data were analyzed. Of the 123 patients, 46 (37%) were found to have fibroadenomatous features and 59 (48%) were found to have FE features. All went on to have surgical excision. Forty (38%) contained phyllodes tumors, and 65 (62%) found no phyllodes tumor on final pathology. There were significant differences in the median size of the masses (4 cm versus 2.4 cm P phyllodes tumors and the group that did not on preoperative imaging. Further evaluation did not show any significant differences on preoperative imaging between benign and borderline/malignant phyllodes tumors. Hispanic ethnicity correlated with a higher chance of phyllodes tumor after CNB (P phyllodes tumor, surgical excision remains the standard of care; however, patients with suspicious FE neoplasms represent a treatment dilemma as many will prove to be benign. Preoperative size and the density of the mass on imaging and ethnicity were associated with phyllodes tumors on final pathology. Copyright © 2012 Elsevier Inc. All rights reserved.

  15. Long-term married couples' health promotion behaviors: identifying factors that impact decision-making.

    Science.gov (United States)

    Padula, Cynthia A; Sullivan, Mary

    2006-10-01

    Knowledge about health promotion behaviors and their determinants in older individuals is scant. Even less is known about persons in long-term marriages, although a growing interdependence in health decision-making has been suggested. The purpose of this study was to identify determinants of health promotion activities in older adults who were in long-term marriages. Pender's Health Promotion Model and a proposed re-conceptualization of Pender's interpersonal influences were used to guide selection of study variables. Perceived barriers and perceived self-efficacy, two behavior-specific cognitions, and relationship quality and social support, proposed interpersonal influences, were hypothesized to predict participation in health promotion behaviors. A convenience sample of 80 individuals in long-term marriages was recruited. Regression analysis identified four predictor variables as explaining 31% of the participation in health promotion behaviors: relationship quality, perceived barriers, perceived self-efficacy, and social support. Implications for nursing practice and for further research are discussed.

  16. 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.

  17. Prioritizing Agricultural Services and Identifying Effective Factors on Serving in Guilan Agricultural Jihad Centers

    Directory of Open Access Journals (Sweden)

    Mohammad Karim Motamd

    2015-01-01

    Full Text Available In order to identify different agricultural services, by correlation-descriptive method, the present study attempts to prioritize demands of villagers for agricultural services, determine the role of effective factors on serving villagers through discriminant analysis and compute correlation between demands of agricultural services with education services through Spearman's Coefficient in Guilan Agricultural Jihad centers. The results showed that the five demands of services which had the priority were related to applicants of agricultural machines, draft discussion for fertilizer, facilities for livestock and poultry units, quota of fuel for agricultural machines and agricultural units and demands related to rice agronomy. In addition,educational services had a positive correlation with educational needs of villagers and staff factor enjoyed more important role in compare with human resource factor, equipment and rural coordination to offer services. Regarding that priorities in service demands from the centers requires providing credits, cooperation to establish local funds to provide agricultural machines which is the first demands of villagers and agreeing with collective ownership of these agricultural instruments are proper options so that the fund could be effective to provide other inputs and credits.

  18. 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.

  19. 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

    2017-01-04

    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. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  20. 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...

  1. A hierarchical model for ordinal matrix factorization

    DEFF Research Database (Denmark)

    Paquet, Ulrich; Thomson, Blaise; Winther, Ole

    2012-01-01

    This paper proposes a hierarchical probabilistic model for ordinal matrix factorization. Unlike previous approaches, we model the ordinal nature of the data and take a principled approach to incorporating priors for the hidden variables. Two algorithms are presented for inference, one based...

  2. 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.

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

    Science.gov (United States)

    Mueller, Christine; Savik, Kay

    2010-10-01

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

  4. Model for Evaluating Social Factors in National and International ...

    African Journals Online (AJOL)

    This model analyses social using laws of thermodynamics to make the study of social systems more accurate given that laws of physical sciences are more precise than those of social sciences. It identifies social factors that determine the social stability of a country and how this affects economic performance. It quantifies ...

  5. Identifying the factors affecting bike-sharing usage and degree of satisfaction in Ningbo, China

    OpenAIRE

    Guo, Yanyong; Zhou, Jibiao; Wu, Yao; Li, Zhibin

    2017-01-01

    The boom in bike-sharing is receiving growing attention as societies become more aware of the importance of active non-motorized traffic modes. However, the low usage of this transport mode in China raises concerns. The primary objective of this study is to explore factors affecting bike-sharing usage and satisfaction degree of bike-sharing among the bike-sharing user population in China. Data were collected by a questionnaire survey in Ningbo. A bivariate ordered probit (BOP) model was devel...

  6. Ensemble Topic Modeling via Matrix Factorization

    OpenAIRE

    Belford, Mark; MacNamee, Brian; Greene, Derek

    2016-01-01

    Topic models can provide us with an insight into the underlying latent structure of a large corpus of documents, facilitating knowledge discovery and information summarization. A range of methods have been proposed in the literature, including probabilistic topic models and techniques based on matrix factorization. However, these methods tend to have stochastic elements in their initialization, which can lead to their output being unstable. That is, if a topic modeling algorithm is applied to...

  7. 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.

  8. Imaging-Based Screen Identifies Laminin 411 as a Physiologically Relevant Niche Factor with Importance for i-Hep Applications.

    Science.gov (United States)

    Ong, John; Serra, Maria Paola; Segal, Joe; Cujba, Ana-Maria; Ng, Soon Seng; Butler, Richard; Millar, Val; Hatch, Stephanie; Zimri, Salman; Koike, Hiroyuki; Chan, Karen; Bonham, Andrew; Walk, Michelle; Voss, Ty; Heaton, Nigel; Mitry, Ragai; Dhawan, Anil; Ebner, Daniel; Danovi, Davide; Nakauchi, Hiromitsu; Rashid, S Tamir

    2018-03-13

    Use of hepatocytes derived from induced pluripotent stem cells (i-Heps) is limited by their functional differences in comparison with primary cells. Extracellular niche factors likely play a critical role in bridging this gap. Using image-based characterization (high content analysis; HCA) of freshly isolated hepatocytes from 17 human donors, we devised and validated an algorithm (Hepatocyte Likeness Index; HLI) for comparing the hepatic properties of cells against a physiological gold standard. The HLI was then applied in a targeted screen of extracellular niche factors to identify substrates driving i-Heps closer to the standard. Laminin 411, the top hit, was validated in two additional induced pluripotent stem cell (iPSC) lines, primary tissue, and an in vitro model of α1-antitrypsin deficiency. Cumulatively, these data provide a reference method to control and screen for i-Hep differentiation, identify Laminin 411 as a key niche protein, and underscore the importance of combining substrates, soluble factors, and HCA when developing iPSC applications. Crown Copyright © 2018. Published by Elsevier Inc. All rights reserved.

  9. Usability of geographic information -- factors identified from qualitative analysis of task-focused user interviews.

    Science.gov (United States)

    Harding, Jenny

    2013-11-01

    Understanding user needs for geographic information and the factors which influence the usability of such information in diverse user contexts is an essential part of user centred development of information products. There is relatively little existing research focused on the design and usability of information products in general. This paper presents a research approach based on semi structured interviews with people working with geographic information on a day to day basis, to establish a reference base of qualitative data on user needs for geographic information with respect to context of use. From this reference data nine key categories of geographic information usability are identified and discussed in the context of limited existing research concerned with geographic information usability. Copyright © 2012 Elsevier Ltd and The Ergonomics Society. All rights reserved.

  10. 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

    , 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....... The 'traditional' pattern was positively associated with male gender and age, whereas the 'health-conscious' pattern was positively associated with being female, increasing age and educational level. The 'fast food' pattern was inversely associated with age and smoking.Conclusions:Three distinct dietary patterns......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...

  11. 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.

  12. May genetic factors in fibromyalgia help to identify patients with differentially altered frequencies of immune cells?

    Science.gov (United States)

    Carvalho, L S C; Correa, H; Silva, G C; Campos, F S; Baião, F R; Ribeiro, L S; Faria, A M; d'Avila Reis, D

    2008-12-01

    There is common agreement that fibromyalgia (FM) is an extremely heterogeneous entity. Patients differ in their clinical symptoms, endocrine and immune parameters. In this study we evaluated endocrine and immunological features of distinct subsets of FM patients. In contrast to previous attempts to identify subsets of FM patients, based solely on their psychological and cognitive features, herein we propose to separate FM patients by genetic features. Allelic expression of the polymorphic promoter region of the serotonin transporter (5-HTTLPR) was analysed as a relevant genetic factor for FM. Seventy-five patients meeting the American College of Rheumatology criteria and 27 healthy age-matched controls participated in this study. All controls and FM patients were submitted to genotyping of 5-HTTLPR. Twenty-seven FM patients, who were able to discontinue hypnotic, sedative or psychotropic prescription medications for at least 2 weeks, were then subdivided into L (homozygote LL) or S groups (genotypes LS and SS). They were evaluated for salivary cortisol levels, absolute number of leucocyte subpopulations, including natural killer (NK) cells and activated T and B lymphocytes. Both groups presented decreased cortisol levels, more intense in the L group, increased all B lymphocytes subsets and reduced CD4+CD25high T lymphocytes. The L group had increased CD4+CD25low activated T lymphocytes, while the S group displayed elevated CD4+ human leucocyte antigen D-related (HLA-DR)+ activated T lymphocytes and decreased NK cells. We demonstrate that genetic factors may help to identify FM individuals with differentially altered frequencies of immune cells.

  13. Readily Identifiable Risk Factors of Nursing Home Residents' Oral Hygiene: Dementia, Hospice, and Length of Stay.

    Science.gov (United States)

    Zimmerman, Sheryl; Austin, Sophie; Cohen, Lauren; Reed, David; Poole, Patricia; Ward, Kimberly; Sloane, Philip D

    2017-11-01

    The poor oral hygiene of nursing home (NH) residents is a matter of increasing concern, especially because of its relationship with pneumonia and other health events. Because details and related risk factors in this area are scant and providers need to be able to easily identify those residents at most risk, this study comprehensively examined the plaque, gingival, and denture status of NH residents, as well as readily available correlates of those indicators of oral hygiene, including items from the Minimum Data Set (MDS). Oral hygiene assessment and chart abstract conducted on a cross-section of NH residents. NHs in North Carolina (N = 14). NH residents (N = 506). Descriptive data from the MDS and assessments using three standardized measures: the Plaque Index for Long-Term Care (PI-LTC), the Gingival Index for Long-Term Care (GI-LTC), and the Denture Plaque Index (DPI). Oral hygiene scores averaged 1.7 (of 3) for the PI-LTC, 1.5 (of 4) for the GI-LTC, and 2.2 (of 4) for the DPI. Factors most strongly associated with poor oral hygiene scores included having dementia, being on hospice care, and longer stay. MDS ratings of gingivitis differed significantly from oral hygiene assessments. The findings identify resident subgroups at especially high risk of poor oral health who can be targeted in quality improvement efforts related to oral hygiene; they also indicate need to improve the accuracy of how MDS items are completed. © 2017, Copyright the Authors Journal compilation © 2017, The American Geriatrics Society.

  14. [Identifying transcription factors involved in Arabidopsis adventious shoot regeneration by RNA-Seq technology].

    Science.gov (United States)

    Wang, Xingchun; Chen, Zhao; Fan, Juan; He, Miaomiao; Han, Yuanhuai; Yang, Zhirong

    2015-04-01

    Transcriptional regulation is one of the major regulations in plant adventious shoot regeneration, but the exact mechanism remains unclear. In our study, the RNA-seq technology based on the IlluminaHiSeq 2000 sequencing platform was used to identify differentially expressed transcription factor (TF) encoding genes during callus formation stage and adventious shoot regeneration stage between wild type and adventious shoot formation defective mutant be1-3 and during the transition from dedifferentiation to redifferentiation stage in wildtype WS. Results show that 155 TFs were differentially expressed between be1-3 mutant and wild type during callus formation, of which 97 genes were up-regulated, and 58 genes were down-regulated; and that 68 genes were differentially expressed during redifferentiation stage, with 40 genes up-regulated and 28 genes down-regulated; whereas at the transition stage from dedifferentiation to redifferention in WS wild type explants, a total of 231 differentially expressed TF genes were identified, including 160 up-regualted genes and 71 down-regulated genes. Among these TF genes, the adventious shoot related transcription factor 1 (ART1) gene encoding a MYB-related (v-myb avian myeloblastosis viral oncogene homolog) TF, was up-regulated 3 217 folds, and was the highest up-regulated gene during be1-3 callus formation. Over expression of the ART1 gene caused defects in callus formation and shoot regeneration and inhibited seedling growth, indicating that the ART1 gene is a negative regulator of callus formation and shoot regeneration. This work not only enriches our knowledge about the transcriptional regulation mechanism of adventious shoot regeneration, but also provides valuable information on candidate TF genes associated with adventious shoot regeneration for future research.

  15. APPLICATION OF MULTIPLE LOGISTIC REGRESSION, BAYESIAN LOGISTIC AND CLASSIFICATION TREE TO IDENTIFY THE SIGNIFICANT FACTORS INFLUENCING CRASH SEVERITY

    Directory of Open Access Journals (Sweden)

    MILAD TAZIK

    2017-11-01

    Full Text Available Identifying cases in which road crashes result in fatality or injury of drivers may help improve their safety. In this study, datasets of crashes happened in TehranQom freeway, Iran, were examined by three models (multiple logistic regression, Bayesian logistic and classification tree to analyse the contribution of several variables to fatal accidents. For multiple logistic regression and Bayesian logistic models, the odds ratio was calculated for each variable. The model which best suited the identification of accident severity was determined based on AIC and DIC criteria. Based on the results of these two models, rollover crashes (OR = 14.58, %95 CI: 6.8-28.6, not using of seat belt (OR = 5.79, %95 CI: 3.1-9.9, exceeding speed limits (OR = 4.02, %95 CI: 1.8-7.9 and being female (OR = 2.91, %95 CI: 1.1-6.1 were the most important factors in fatalities of drivers. In addition, the results of the classification tree model have verified the findings of the other models.

  16. 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.

  17. Mathematical modeling identifies optimum lapatinib dosing schedules for the treatment of glioblastoma patients.

    Directory of Open Access Journals (Sweden)

    Shayna Stein

    2018-01-01

    Full Text Available Human primary glioblastomas (GBM often harbor mutations within the epidermal growth factor receptor (EGFR. Treatment of EGFR-mutant GBM cell lines with the EGFR/HER2 tyrosine kinase inhibitor lapatinib can effectively induce cell death in these models. However, EGFR inhibitors have shown little efficacy in the clinic, partly because of inappropriate dosing. Here, we developed a computational approach to model the in vitro cellular dynamics of the EGFR-mutant cell line SF268 in response to different lapatinib concentrations and dosing schedules. We then used this approach to identify an effective treatment strategy within the clinical toxicity limits of lapatinib, and developed a partial differential equation modeling approach to study the in vivo GBM treatment response by taking into account the heterogeneous and diffusive nature of the disease. Despite the inability of lapatinib to induce tumor regressions with a continuous daily schedule, our modeling approach consistently predicts that continuous dosing remains the best clinically feasible strategy for slowing down tumor growth and lowering overall tumor burden, compared to pulsatile schedules currently known to be tolerated, even when considering drug resistance, reduced lapatinib tumor concentrations due to the blood brain barrier, and the phenotypic switch from proliferative to migratory cell phenotypes that occurs in hypoxic microenvironments. Our mathematical modeling and statistical analysis platform provides a rational method for comparing treatment schedules in search for optimal dosing strategies for glioblastoma and other cancer types.

  18. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  20. A New Bayesian Method to Identify the Environmental Factors That Influence Recent Migration

    Science.gov (United States)

    Faubet, Pierre; Gaggiotti, Oscar E.

    2008-01-01

    We present a new multilocus genotype method that makes inferences about recent immigration rates and identifies the environmental factors that are more likely to explain observed gene flow patterns. It also estimates population-specific inbreeding coefficients, allele frequencies, and local population FST's and performs individual assignments. We generate synthetic data sets to determine the region of the parameter space where our method is and is not able to provide accurate estimates. Our simulation study indicates that reliable results can be obtained when the global level of genetic differentiation (FST) is >1%, the number of loci is only 10, and sample sizes are of the order of 50 individuals per population. We illustrate our method by applying it to Pakistani human data, considering altitude and geographic distance as explanatory factors. Our results suggest that altitude explains better the genetic data than geographic distance. Additionally, they show that southern low-altitude populations have higher migration rates than northern high-altitude ones. PMID:18245344

  1. Identifying potential molecular factors involved in Bacillus amyloliquefaciens 5113 mediated abiotic stress tolerance in wheat.

    Science.gov (United States)

    Abd El-Daim, I A; Bejai, S; Fridborg, I; Meijer, J

    2018-03-01

    Abiotic stressors are main limiting factors for agricultural production around the world. Plant growth-promoting bacteria have been successfully used to improve abiotic stress tolerance in several crops including wheat. However, the molecular changes involved in the improvement of stress management are poorly understood. The present investigation addressed some molecular factors involved in bacterially induced plant abiotic stress responses by identifying differentially expressed genes in wheat (Triticum aestivum) seedlings treated with the beneficial bacterium Bacillus amyloliquefaciens subsp. plantarum UCMB5113 prior to challenge with abiotic stress conditions such as heat, cold or drought. cDNA-AFLP analysis revealed differential expression of more than 200 transcript-derived fragments (TDFs) in wheat leaves. Expression of selected TDFs was confirmed using RT-PCR. DNA sequencing of 31 differentially expressed TDFs revealed significant homology with both known and unknown genes in database searches. Virus-induced gene silencing of two abscisic acid-related TDFs showed different effects upon heat and drought stress. We conclude that treatment with B. amyloliquefaciens 5113 caused molecular modifications in wheat in order to induce tolerance against heat, cold and drought stress. Bacillus treatment provides systemic effects that involve metabolic and regulatory functions supporting both growth and stress management. © 2017 German Society for Plant Sciences and The Royal Botanical Society of the Netherlands.

  2. Identifying Risk Factors for Incidence of Mental Disorders after Traumatic Brain Injury

    Directory of Open Access Journals (Sweden)

    Sajjad Rezaei

    2014-09-01

    Full Text Available Background: Organic brain pathology usually may be followed by mental disorders. This research was aimed at constructing a predictive model and investigating the risk factors in the incidence of mental disorders after traumatic brain injury (TBI. Materials and Methods: Two hundred and thirty eight patients (195 males and 43 females were entered the study in a descriptive-longitudinal design by non-probable and consecutive sampling method. They were undergone neurosurgical examinations and psychological evaluations. After a 4-month follow-up, 65.1% of the patients (N=155 referred to a psychiatrist in order to determine the nature of mental disorder following TBI, using a structured clinical interview based on DSM-IV diagnostic criteria. Results: 75.48% (117 cases of patients had a form of mental disorder‎ secondary to TBI. The Results of binary logistic regression analyses for calculating odds ratio (OR model with 95% confidence interval (CI indicating the severity of TBI ‎(OR‏=‏3.497,‎ 95% CI =1.259-9.712‎, presence of subcranial injury (OR‏=‏‎2.834,‎ 95% CI =1.022-7.857‎ and falling level of general compatibility, as measured by modified version of GHQ-28 (OR‏=‏1.072, 95% ‎CI =1.035-1.111 indicated an increasing risk in the incidence of mental disorder. Conclusion: Findings revealed that in the development of post-TBI mental disorders, first there was a close relationship with organic brain pathology (TBI severity and subcranial injury, although the role of effective psychological factors such as level of general compatibility after trauma should not be neglected. Also in order to predict the people at risk of mental disorders after TBI, the proposed predictive model in this study can be used.

  3. Identifying factors that predict longitudinal outcomes of untreated common mental disorders.

    Science.gov (United States)

    Henriksen, Christine Anne; Stein, Murray B; Afifi, Tracie O; Enns, Murray W; Lix, Lisa M; Sareen, Jitender

    2015-02-01

    Historically, meeting criteria for a mental disorder has been used as a proxy for the need for mental health services, yet research suggests that a significant proportion of disorders remit without treatment. In this study, risk factors for poor longitudinal outcomes of individuals with untreated common mental disorders were determined, with the goal of identifying individuals with unmet need and informing the development of targeted interventions. Data came from the National Epidemiologic Survey of Alcohol and Related Conditions (NESARC), a longitudinal, nationally representative survey of the adult U.S. population (age ≥18; N=34,653). Respondents were assessed for past-year depressive, anxiety, and substance use disorders and mental health service use via face-to-face interviews conducted at two time points, three years apart. Among respondents without a history of mental health treatment, logistic regression analyses examined factors associated with persistence of the disorder, comorbidity, or suicide attempt (that is, presence of any axis I disorder in the past year at wave 2 or any suicide attempt during the follow-up) versus spontaneous recovery of baseline disorders. Certain sociodemographic factors, comorbid mental disorders at baseline (such as three or more axis I disorders, adjusted odds ratio [AOR]=1.64, 95% confidence interval [CI]=1.27-2.12), and childhood maltreatment (AOR=1.47, CI=1.23-1.75) were predictors of disorder persistence, comorbidity, or suicide attempt in depressive, anxiety, and substance use disorders during the follow-up. In addition to considering the presence of a mental disorder, policy makers should consider other variables, such as childhood maltreatment and comorbidity, in estimating treatment need.

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

    Directory of Open Access Journals (Sweden)

    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.

  5. 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

  6. Linking Strengths: Identifying and Exploring Protective Factor Clusters in Academically Resilient Low-Socioeconomic Urban Students of Color

    Science.gov (United States)

    Morales, Erik E.

    2010-01-01

    Based on data from qualitative interviews with 50 high-achieving low-socioeconomic students of color, two "clusters" of important and symbiotic protective factors are identified and explored. Each cluster consists of a series of interrelated protective factors identified by the participants as crucial to their statistically exceptional academic…

  7. 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.

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

    Science.gov (United States)

    Eisenberg, Marisa C; Jain, Harsh V

    2017-10-27

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

  9. Assessing risk factors for dental caries: a statistical modeling approach.

    Science.gov (United States)

    Trottini, Mario; Bossù, Maurizio; Corridore, Denise; Ierardo, Gaetano; Luzzi, Valeria; Saccucci, Matteo; Polimeni, Antonella

    2015-01-01

    The problem of identifying potential determinants and predictors of dental caries is of key importance in caries research and it has received considerable attention in the scientific literature. From the methodological side, a broad range of statistical models is currently available to analyze dental caries indices (DMFT, dmfs, etc.). These models have been applied in several studies to investigate the impact of different risk factors on the cumulative severity of dental caries experience. However, in most of the cases (i) these studies focus on a very specific subset of risk factors; and (ii) in the statistical modeling only few candidate models are considered and model selection is at best only marginally addressed. As a result, our understanding of the robustness of the statistical inferences with respect to the choice of the model is very limited; the richness of the set of statistical models available for analysis in only marginally exploited; and inferences could be biased due the omission of potentially important confounding variables in the model's specification. In this paper we argue that these limitations can be overcome considering a general class of candidate models and carefully exploring the model space using standard model selection criteria and measures of global fit and predictive performance of the candidate models. Strengths and limitations of the proposed approach are illustrated with a real data set. In our illustration the model space contains more than 2.6 million models, which require inferences to be adjusted for 'optimism'.

  10. Vulnerability and Psychosocial Risk Factors Regarding People who Identify as Transgender. A Systematic Review of the Research Evidence.

    Science.gov (United States)

    McCann, Edward; Brown, Michael

    2018-01-01

    The aim of this systematic review was to identify the issues related to the vulnerability and psychosocial risk factors of people who identify as transgender. A search of relevant electronic databases from 2007 to 2017 was conducted. Included studies involved transgender people, vulnerability, and risk factors. Following the application of rigorous inclusion and exclusion criteria, a total of 21 papers were considered suitable for the review. The identified themes included sexual risks, substance use, psychological vulnerability risk factors, and protective factors and behaviors. Nurses are in a strong position to address pertinent concerns and to provide the necessary psychosocial supports to this population.

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

    OpenAIRE

    Stennett, Sabrina

    2016-01-01

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

  12. 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.

  13. 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

  14. A graph regularized non-negative matrix factorization method for identifying microRNA-disease associations.

    Science.gov (United States)

    Xiao, Qiu; Luo, Jiawei; Liang, Cheng; Cai, Jie; Ding, Pingjian

    2017-09-01

    MicroRNAs (miRNAs) play crucial roles in post-transcriptional regulations and various cellular processes. The identification of disease-related miRNAs provides great insights into the underlying pathogenesis of diseases at a system level. However, most existing computational approaches are biased towards known miRNA-disease associations, which is inappropriate for those new diseases or miRNAs without any known association information. In this study, we propose a new method with graph regularized non-negative matrix factorization in heterogeneous omics data, called GRNMF, to discover potential associations between miRNAs and diseases, especially for new diseases and miRNAs or those diseases and miRNAs with sparse known associations. First, we integrate the disease semantic information and miRNA functional information to estimate disease similarity and miRNA similarity, respectively. Considering that there is no available interaction observed for new diseases or miRNAs, a preprocessing step is developed to construct the interaction score profiles that will assist in prediction. Next, a graph regularized non-negative matrix factorization framework is utilized to simultaneously identify potential associations for all diseases. The results indicated that our proposed method can effectively prioritize disease-associated miRNAs with higher accuracy compared with other recent approaches. Moreover, case studies also demonstrated the effectiveness of GRNMF to infer unknown miRNA-disease associations for those novel diseases and miRNAs. The code of GRNMF is freely available at https://github.com/XIAO-HN/GRNMF/. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

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

    Directory of Open Access Journals (Sweden)

    Fatemeh Vida Zohoori

    Full Text Available 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.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.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.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.

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

    International Nuclear Information System (INIS)

    Sousa, A.L.; Ribeiro, A.C.O.; Duarte, J.P.; Frutuoso e Melo, P.F.

    2013-01-01

    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)

  17. 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)

  18. 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…

  19. 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.

  20. 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.

  1. Identifying the Risk Factors for Typhoid Fever among the Residents of Rural Islamabad

    International Nuclear Information System (INIS)

    Javed, N.; Bashir, F.; Abbasi, S.; Tahir, M.

    2017-01-01

    Background: During August 2015, unusually high typhoid fever cases were reported from rural Islamabad at Federal General Hospital (FGH), Islamabad. Objectives: To determine the risk factors for typhoid fever outbreak and recommend preventive measures. Study design, settings and duration: Outbreak investigation study conducted in Union Councils 19 and 22 of rural Islamabad in the catchment area for Federal General Hospital, from 7th July-30th August 2015. Subjects and Methods: A questionnaire was used to identify risk factors of typhoid fever. A case was defined as any resident of the rural Islamabad within the mauza Chatta Bakhtawar and Terlai Kalan presenting with high grade fever (>101 F) with one of the following signs/symptoms; headache, abdominal pain and vomiting with positive typhidot test from 7th July-30th August 2015. Two age and sex matched controls for each case was selected from the neighborhood. Epi Info 7 was used for analysis. Results: Total of 50 cases and 100 controls were enrolled. Among cases 30 (61 percent) were females and 20 (39 percent) males with M;F ratio of 1:1.5. Mean age was 23.0 years (9.9 +- SD). The most affected age group was 15-25 years (AR 0.19 percent, n=21). Only one case died (CFR 2percent). Use of untreated public water after rains (OR 3.7 CI 1.6-9.7 p< 0.0002), reconstruction areas and bursting/leaking of water pipes (OR 4.017 CI 1.6-9.7 p < 0.001) and presence of confirmed typhoid cases at home/close contacts (OR 5.7 CI 2.019-16.18 p < 0.0003) were the significant risk factors found associated with the disease. Whereas using well/private bore (OR 0.29 CI 0.329-0.653 p < 0.001) and hand washing practices (OR 0.7 CI 0.297-1.9 < 0.5) had a protective effect. Multivariate analysis showed that use of untreated public water (OR: 3.34, CI: 1.52-7.29, p < 0.002), bursting/leaking pipes (OR 2.86, CI 0.96-8.48, p < 0.05) were significantly associated with typhoid disease. Conclusion

  2. To identify the factors affecting the risk of recurrent febrile seizures in saudi children

    International Nuclear Information System (INIS)

    Jamal, M.M.; Ahmed, W.

    2015-01-01

    Objective: To identify the risk factors of recurrent febrile seizures (FS) in Saudi children in a Northern Province of Hail in Saudi Arabia. Study Design: Descriptive prospective study. Place and Duration of Study: Pediatric department, King Khalid Hospital Hail, Kingdom of Saudi Arabia from 01 October 2010 to 30 September 2011. Patients and Methods: A total of 132 children (age ranges from 03 months to 60 months) were included in the study, while they were admitted with the diagnosis of FS during the study period, in the Pediatric department of the King Khalid University Hospital, Hail. A predesigned study proforma was utilized for data collection. All the children included in the study were followed for a period of 01 year after discharge from the pediatric ward for any recurrence of FS. Results: During the study period 132 children were admitted for FS, the mean age of children in our sample was 16 months. There was a preponderance of male children. Among the causes of fever, mostly 63(47.73%) had symptoms of viral prodrome. Recurrent febrile seizure was found in 46 (34.85%) children. There was a statistically significant association between low temperature at onset of seizure and recurrent FS in 65.22% cases p-value= 0.001). Similarly, the association of duration of fever (= 6 hour) prior to onset of FS and recurrence was found to be significant in 56.52% (p-value= 0.001). Moreover it was found that lower age <12 months at onset of first FS and complex FS had a statistically significant association with its recurrence in 65.22% and 69.57% cases respectively p-value= 0.01 and 0.001). Non significant factors were sex and family history. Conclusion: FS is a common paediatric problem predominantly seen in males. Almost one third of these children are at risk for recurrence in later dates. The risk factors for these recurrences are modest rise in body temperature at the onset of seizure, younger age at presentation, onset of seizure within 6 hours of fever and

  3. 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

  4. Challenges of implementing collaborative models of decision making with trans-identified patients.

    Science.gov (United States)

    Dewey, Jodie M

    2015-10-01

    Factors health providers face during the doctor-patient encounter both impede and assist the development of collaborative models of treatment. I investigated decision making among medical and therapeutic professionals who work with trans-identified patients to understand factors that might impede or facilitate the adoption of the collaborative decision-making model in their clinical work. Following a grounded theory approach, I collected and analysed data from semi-structured interviews with 10 U.S. physicians and 10 U.S. mental health professionals. Doctors and therapists often desire collaboration with their patients but experience dilemmas in treating the trans-identified patients. Dilemmas include lack of formal education, little to no institutional support and inconsistent understanding and application of the main documents used by professionals treating trans-patients. Providers face considerable risk in providing unconventional treatments due to the lack of institutional and academic support relating to the treatment for trans-people, and the varied interpretation and application of the diagnostic and treatment documents used in treating trans-people. To address this risk, the relationship with the patient becomes crucial. However, trust, a component required for collaboration, is thwarted when the patients feel obliged to present in ways aligned with these documents in order to receive desired treatments. When trust cannot be established, medical and mental health providers can and do delay or deny treatments, resulting in the imbalance of power between patient and provider. The documents created to assist in treatment actually thwart professional desire to work collaboratively with patients. © 2013 John Wiley & Sons Ltd.

  5. 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.

  6. An All-Recombinant Protein-Based Culture System Specifically Identifies Hematopoietic Stem Cell Maintenance Factors.

    Science.gov (United States)

    Ieyasu, Aki; Ishida, Reiko; Kimura, Takaharu; Morita, Maiko; Wilkinson, Adam C; Sudo, Kazuhiro; Nishimura, Toshinobu; Ohehara, Jun; Tajima, Yoko; Lai, Chen-Yi; Otsu, Makoto; Nakamura, Yukio; Ema, Hideo; Nakauchi, Hiromitsu; Yamazaki, Satoshi

    2017-03-14

    Hematopoietic stem cells (HSCs) are considered one of the most promising therapeutic targets for the treatment of various blood disorders. However, due to difficulties in establishing stable maintenance and expansion of HSCs in vitro, their insufficient supply is a major constraint to transplantation studies. To solve these problems we have developed a fully defined, all-recombinant protein-based culture system. Through this system, we have identified hemopexin (HPX) and interleukin-1α as responsible for HSC maintenance in vitro. Subsequent molecular analysis revealed that HPX reduces intracellular reactive oxygen species levels within cultured HSCs. Furthermore, bone marrow immunostaining and 3D immunohistochemistry revealed that HPX is expressed in non-myelinating Schwann cells, known HSC niche constituents. These results highlight the utility of this fully defined all-recombinant protein-based culture system for reproducible in vitro HSC culture and its potential to contribute to the identification of factors responsible for in vitro maintenance, expansion, and differentiation of stem cell populations. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  7. An All-Recombinant Protein-Based Culture System Specifically Identifies Hematopoietic Stem Cell Maintenance Factors

    Directory of Open Access Journals (Sweden)

    Aki Ieyasu

    2017-03-01

    Full Text Available Hematopoietic stem cells (HSCs are considered one of the most promising therapeutic targets for the treatment of various blood disorders. However, due to difficulties in establishing stable maintenance and expansion of HSCs in vitro, their insufficient supply is a major constraint to transplantation studies. To solve these problems we have developed a fully defined, all-recombinant protein-based culture system. Through this system, we have identified hemopexin (HPX and interleukin-1α as responsible for HSC maintenance in vitro. Subsequent molecular analysis revealed that HPX reduces intracellular reactive oxygen species levels within cultured HSCs. Furthermore, bone marrow immunostaining and 3D immunohistochemistry revealed that HPX is expressed in non-myelinating Schwann cells, known HSC niche constituents. These results highlight the utility of this fully defined all-recombinant protein-based culture system for reproducible in vitro HSC culture and its potential to contribute to the identification of factors responsible for in vitro maintenance, expansion, and differentiation of stem cell populations.

  8. 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.  

  9. 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.

  10. Evolutionary and molecular analysis of Dof transcription factors identified a conserved motif for intercellular protein trafficking.

    Science.gov (United States)

    Chen, Huan; Ahmad, Munawar; Rim, Yeonggil; Lucas, William J; Kim, Jae-Yean

    2013-06-01

    · Cell-to-cell trafficking of transcription factors (TFs) has been shown to play an important role in the regulation of plant developmental events, but the evolutionary relationship between cell-autonomous and noncell-autonomous (NCA) TFs remains elusive. · AtDof4.1, named INTERCELLULAR TRAFFICKING DOF 1 (ITD1), was chosen as a representative NCA member to explore this evolutionary relationship. Using domain structure-function analyses and swapping studies, we examined the cell-to-cell trafficking of plant-specific Dof TF family members across Arabidopsis and other species. · We identified a conserved intercellular trafficking motif (ITM) that is necessary and sufficient for selective cell-to-cell trafficking and can impart gain-of-function cell-to-cell movement capacity to an otherwise cell-autonomous TF. The functionality of related motifs from Dof members across the plant kingdom extended, surprisingly, to a unicellular alga that lacked plasmodesmata. By contrast, the algal homeodomain related to the NCA KNOX homeodomain was either inefficient or unable to impart such cell-to-cell movement function. · The Dof ITM appears to predate the evolution of selective plasmodesmal trafficking in the plant kingdom, which may well have acted as a molecular template for the evolution of Dof proteins as NCA TFs. However, the ability to efficiently traffic for KNOX homeodomain (HD) proteins may have been acquired during the evolution of early nonvascular plants. © 2013 The Authors. New Phytologist © 2013 New Phytologist Trust.

  11. 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.

  12. Identifying the Factors Influence Turkish Deposit Banks to Join Corporate Social Responsibility Activities by Using Panel Probit Method

    Directory of Open Access Journals (Sweden)

    Serhat Yuksel

    2017-02-01

    Full Text Available This study aims to determine the influencing factors of the banks to join corporate social responsibility activities. Within this scope, annual data of 23 deposit banks in Turkey for the periods between 2005 and 2015 was taken into the consideration. In addition to this situation, panel probit model was used in the analysis so as to achieve this objective. According to the results of the analysis, it was determined that there is a negative relationship between CSR activities and nonperforming loans ratio. This situation shows that banks do not prefer to make social responsibility activities in case of higher financial losses. In addition to this situation, it was also identified that there is a positive relationship between return on asset and corporate social responsibility activities of the banks. In other words, it can be understood that Turkish deposit banks, which have higher profitability, joint more CSR activities in comparison with others.

  13. Capital Cost Optimization for Prefabrication: A Factor Analysis Evaluation Model

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    Hong Xue

    2018-01-01

    Full Text Available High capital cost is a significant hindrance to the promotion of prefabrication. In order to optimize cost management and reduce capital cost, this study aims to explore the latent factors and factor analysis evaluation model. Semi-structured interviews were conducted to explore potential variables and then questionnaire survey was employed to collect professionals’ views on their effects. After data collection, exploratory factor analysis was adopted to explore the latent factors. Seven latent factors were identified, including “Management Index”, “Construction Dissipation Index”, “Productivity Index”, “Design Efficiency Index”, “Transport Dissipation Index”, “Material increment Index” and “Depreciation amortization Index”. With these latent factors, a factor analysis evaluation model (FAEM, divided into factor analysis model (FAM and comprehensive evaluation model (CEM, was established. The FAM was used to explore the effect of observed variables on the high capital cost of prefabrication, while the CEM was used to evaluate comprehensive cost management level on prefabrication projects. Case studies were conducted to verify the models. The results revealed that collaborative management had a positive effect on capital cost of prefabrication. Material increment costs and labor costs had significant impacts on production cost. This study demonstrated the potential of on-site management and standardization design to reduce capital cost. Hence, collaborative management is necessary for cost management of prefabrication. Innovation and detailed design were needed to improve cost performance. The new form of precast component factories can be explored to reduce transportation cost. Meanwhile, targeted strategies can be adopted for different prefabrication projects. The findings optimized the capital cost and improved the cost performance through providing an evaluation and optimization model, which helps managers to

  14. Sexual Risk Behavior Among Youth With Bipolar Disorder: Identifying Demographic and Clinical Risk Factors.

    Science.gov (United States)

    Krantz, Megan; Goldstein, Tina; Rooks, Brian; Merranko, John; Liao, Fangzi; Gill, Mary Kay; Diler, Rasim; Hafeman, Danella; Ryan, Neal; Goldstein, Benjamin; Yen, Shirley; Hower, Heather; Hunt, Jeffrey; Keller, Martin; Strober, Michael; Axelson, David; Birmaher, Boris

    2018-02-01

    This study aims to document rates of sexual activity among youth with bipolar spectrum disorder (BD) and to examine demographic and clinical factors associated with first sexual activity and sexual risk behavior during follow-up. The sample was drawn from the Course and Outcome of Bipolar Youth (COBY) study of 413 youth 7 to 17 years at baseline who met criteria for bipolar spectrum disorder according to the Schedule for Affective Disorders and Schizophrenia for School-Aged Children. Psychiatric symptoms during follow-up were assessed using the Adolescent Longitudinal Interview Follow-Up Evaluation (ALIFE). Sexual behavior and level of sexual risk (e.g., unprotected sex, multiple partners, and/or partners with known sexually transmitted infections) were assessed by trained evaluators using the ALIFE Psychosocial Functioning Scale. Analyses were conducted in relation to first sexual behavior during follow-up and then to subsequent sexual behaviors (mean 9.7 years, standard deviation 3.2). Sexually active COBY youth (n = 292 of 413; 71%) were more likely females, using substances, and not living with both parents. Consistent with findings among healthy youth, earlier first sexual activity in the sample was significantly associated with low socioeconomic status, female sex, comorbid disruptive behavior disorder, and substance use. As with healthy youth, sexual risk behavior during follow-up was significantly associated with non-Caucasian race, low socioeconomic status, substance use, and history of sexual abuse. Of those COBY youth who were sexually active, 11% reported sexual assault or abuse, 36% reported becoming pregnant (or the significant other becoming pregnant), and 15% reported having at least 1 abortion (or the significant other having an abortion) during follow-up. Hypomanic symptoms during follow-up were temporally associated with the greatest risk for sexual risk behavior. Demographic and clinical factors could help identify youth with bipolar spectrum

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

    Directory of Open Access Journals (Sweden)

    Dan Li

    2018-01-01

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

  16. Diversity Outbred Mice Identify Population-Based Exposure Thresholds and Genetic Factors that Influence Benzene-Induced Genotoxicity

    Science.gov (United States)

    Gatti, Daniel M.; Morgan, Daniel L.; Kissling, Grace E.; Shockley, Keith R.; Knudsen, Gabriel A.; Shepard, Kim G.; Price, Herman C.; King, Deborah; Witt, Kristine L.; Pedersen, Lars C.; Munger, Steven C.; Svenson, Karen L.; Churchill, Gary A.

    2014-01-01

    Background Inhalation of benzene at levels below the current exposure limit values leads to hematotoxicity in occupationally exposed workers. Objective We sought to evaluate Diversity Outbred (DO) mice as a tool for exposure threshold assessment and to identify genetic factors that influence benzene-induced genotoxicity. Methods We exposed male DO mice to benzene (0, 1, 10, or 100 ppm; 75 mice/exposure group) via inhalation for 28 days (6 hr/day for 5 days/week). The study was repeated using two independent cohorts of 300 animals each. We measured micronuclei frequency in reticulocytes from peripheral blood and bone marrow and applied benchmark concentration modeling to estimate exposure thresholds. We genotyped the mice and performed linkage analysis. Results We observed a dose-dependent increase in benzene-induced chromosomal damage and estimated a benchmark concentration limit of 0.205 ppm benzene using DO mice. This estimate is an order of magnitude below the value estimated using B6C3F1 mice. We identified a locus on Chr 10 (31.87 Mb) that contained a pair of overexpressed sulfotransferases that were inversely correlated with genotoxicity. Conclusions The genetically diverse DO mice provided a reproducible response to benzene exposure. The DO mice display interindividual variation in toxicity response and, as such, may more accurately reflect the range of response that is observed in human populations. Studies using DO mice can localize genetic associations with high precision. The identification of sulfotransferases as candidate genes suggests that DO mice may provide additional insight into benzene-induced genotoxicity. Citation French JE, Gatti DM, Morgan DL, Kissling GE, Shockley KR, Knudsen GA, Shepard KG, Price HC, King D, Witt KL, Pedersen LC, Munger SC, Svenson KL, Churchill GA. 2015. Diversity Outbred mice identify population-based exposure thresholds and genetic factors that influence benzene-induced genotoxicity. Environ Health Perspect 123:237

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

    Science.gov (United States)

    Kéry, Marc

    2018-02-01

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

  18. Identifying factors of activities of daily living important for cost and caregiver outcomes in Alzheimer's disease.

    Science.gov (United States)

    Reed, Catherine; Belger, Mark; Vellas, Bruno; Andrews, Jeffrey Scott; Argimon, Josep M; Bruno, Giuseppe; Dodel, Richard; Jones, Roy W; Wimo, Anders; Haro, Josep Maria

    2016-02-01

    We aimed to obtain a better understanding of how different aspects of patient functioning affect key cost and caregiver outcomes in Alzheimer's disease (AD). Baseline data from a prospective observational study of community-living AD patients (GERAS) were used. Functioning was assessed using the Alzheimer's Disease Cooperative Study-Activities of Daily Living Scale. Generalized linear models were conducted to analyze the relationship between scores for total activities of daily living (ADL), basic ADL (BADL), instrumental ADL (IADL), ADL subdomains (confirmed through factor analysis) and individual ADL questions, and total societal costs, patient healthcare and social care costs, total and supervision caregiver time, and caregiver burden. Four distinct ADL subdomains were confirmed: basic activities, domestic/household activities, communication, and outside activities. Higher total societal costs were associated with impairments in all aspects of ADL, including all subdomains; patient costs were associated with total ADL and BADL, and basic activities subdomain scores. Both total and supervision caregiver hours were associated with total ADL and IADL scores, and domestic/household and outside activities subdomain scores (greater hours associated with greater functional impairments). There was no association between caregiver burden and BADL or basic activities subdomain scores. The relationship between total ADL, IADL, and the outside activities subdomain and outcomes differed between patients with mild and moderate-to-severe AD. Identification of ADL subdomains may lead to a better understanding of the association between patient function and costs and caregiver outcomes at different stages of AD, in particular the outside activities subdomain within mild AD.

  19. Identifying social factors that undermine support for nature-based coastal management.

    Science.gov (United States)

    Josephs, Lauren I; Humphries, Austin T

    2018-04-15

    Human use and degradation of coastal ecosystems is at an all-time high. Thus, a current challenge for environmental management and research is moving beyond ecological definitions of success and integrating socioeconomic factors. Projects and studies with this aim, however, have focused primarily on monetary valuations of ecosystem functions, overlooking the behaviors and psycho-social motivations of environmental management. Using a nature-based salt marsh restoration project on Martha's Vineyard, Massachusetts, we assess the role of human attitudes and preferences in evaluating social success for ecosystem management. We use structural equation modeling to compare the strengths of social variables in predicting restoration project support, and find public understanding to be a more important predictor than personal values. Our results show that even among stakeholders with strong pro-environmental values, a weak understanding of the management initiative can undermine support. We also find that project support does not necessarily translate to the prioritization of similar management strategies. Instead, when individuals consider overall management priorities, differences arise between particular resource user-groups. This suggests that strong public support for individual initiatives can misconstrue complexities in stakeholder preferences that emerge in more comprehensive management considerations. Future investigations of the psycho-social components of management solutions should address the potentially tiered nature of human preferences, as well as whether public perceptions of management effectiveness act as an additional context-dependency of social viability. Copyright © 2018 Elsevier Ltd. All rights reserved.

  20. 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.

  1. 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.

  2. 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

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

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    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/.

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

    Science.gov (United States)

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

    2003-07-01

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

  5. Mouse models for core binding factor leukemia.

    Science.gov (United States)

    Chin, D W L; Watanabe-Okochi, N; Wang, C Q; Tergaonkar, V; Osato, M

    2015-10-01

    RUNX1 and CBFB are among the most frequently mutated genes in human leukemias. Genetic alterations such as chromosomal translocations, copy number variations and point mutations have been widely reported to result in the malfunction of RUNX transcription factors. Leukemias arising from such alterations in RUNX family genes are collectively termed core binding factor (CBF) leukemias. Although adult CBF leukemias generally are considered a favorable risk group as compared with other forms of acute myeloid leukemia, the 5-year survival rate remains low. An improved understanding of the molecular mechanism for CBF leukemia is imperative to uncover novel treatment options. Over the years, retroviral transduction-transplantation assays and transgenic, knockin and knockout mouse models alone or in combination with mutagenesis have been used to study the roles of RUNX alterations in leukemogenesis. Although successful in inducing leukemia, the existing assays and models possess many inherent limitations. A CBF leukemia model which induces leukemia with complete penetrance and short latency would be ideal as a platform for drug discovery. Here, we summarize the currently available mouse models which have been utilized to study CBF leukemias, discuss the advantages and limitations of individual experimental systems, and propose suggestions for improvements of mouse models.

  6. 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

  7. 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.

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

    CERN Document Server

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

    1996-01-01

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

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

    DEFF Research Database (Denmark)

    Lo, Simon M.S.; Wilke, Ralf

    2017-01-01

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

  10. Regulatory activity based risk model identifies survival of stage II and III colorectal carcinoma.

    Science.gov (United States)

    Liu, Gang; Dong, Chuanpeng; Wang, Xing; Hou, Guojun; Zheng, Yu; Xu, Huilin; Zhan, Xiaohui; Liu, Lei

    2017-11-17

    Clinical and pathological indicators are inadequate for prognosis of stage II and III colorectal carcinoma (CRC). In this study, we utilized the activity of regulatory factors, univariate Cox regression and random forest for variable selection and developed a multivariate Cox model to predict the overall survival of Stage II/III colorectal carcinoma in GSE39582 datasets (469 samples). Patients in low-risk group showed a significant longer overall survival and recurrence-free survival time than those in high-risk group. This finding was further validated in five other independent datasets (GSE14333, GSE17536, GSE17537, GSE33113, and GSE37892). Besides, associations between clinicopathological information and risk score were analyzed. A nomogram including risk score was plotted to facilitate the utilization of risk score. The risk score model is also demonstrated to be effective on predicting both overall and recurrence-free survival of chemotherapy received patients. After performing Gene Set Enrichment Analysis (GSEA) between high and low risk groups, we found that several cell-cell interaction KEGG pathways were identified. Funnel plot results showed that there was no publication bias in these datasets. In summary, by utilizing the regulatory activity in stage II and III colorectal carcinoma, the risk score successfully predicts the survival of 1021 stage II/III CRC patients in six independent datasets.

  11. 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.

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

    Science.gov (United States)

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

    2018-04-01

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

  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. Shape Modelling Using Maximum Autocorrelation Factors

    DEFF Research Database (Denmark)

    Larsen, Rasmus

    2001-01-01

    of Active Shape Models by Timothy Cootes and Christopher Taylor by building new information into the model. This new information consists of two types of prior knowledge. First, in many situation we will be given an ordering of the shapes of the training set. This situation occurs when the shapes....... Both these types of knowledge may be used to defined Shape Maximum Autocorrelation Factors. The resulting point distribution models are compared to ordinary principal components analysis using leave-one-out validation.......This paper addresses the problems of generating a low dimensional representation of the shape variation present in a training set after alignment using Procrustes analysis and projection into shape tangent space. We will extend the use of principal components analysis in the original formulation...

  15. 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

    preliminary projects on how to identify and analyze CF. CONCLUSION: New methods are urgently needed to assist researchers to identify and characterize CF that significantly influence the interpretation of results in clinical trials. The CFMG defined first steps to develop further guidance....

  16. Identifying crash contributory factors at urban roundabouts and using association rules to explore their relationships to different crash types.

    Science.gov (United States)

    Montella, Alfonso

    2011-07-01

    The use of roundabouts improves intersection safety by eliminating or altering conflict types, reducing crash severity, and causing drivers to reduce speeds. However, roundabout performances can degrade if precautions are not taken during either the design or the operation phase. Therefore, additional information on the safety of the roundabouts is extremely helpful for planners and designers in identifying existing deficiencies and in refining the design criteria currently being used. The aim of the paper was to investigate the crash contributory factors in 15 urban roundabouts located in Italy and to study the interdependences between these factors. The crash data refer to the period 2003-2008. The identification of the crash contributory factors was based on site inspections and rigorous analyses performed by a team of specialists with a relevant road safety engineering background. Each roundabout was inspected once every year from 2004 to 2009, both in daytime and in nighttime. Overall, 62 different contributory factors and 2156 total contributory factors were identified. In 51 crashes, a single contributory factor was found, whereas in the other 223 crashes, a combination of contributory factors was identified. Given the large amount of data, the interdependences between the contributory factors and between the contributory factors and the different crash types were explored by an association discovery. Association discovery is the identification of sets of items (i.e., crash contributory factors and crash types in our study) that occur together in a given event (i.e., a crash in our study). The rules were filtered by support, confidence, and lift. As a result, 112 association rules were discovered. Overall, numerous contributory factors related to the road and environment deficiencies but not related to the road user or to the vehicle were identified. The most important factors related to geometric design were the radius of deflection and the deviation angle

  17. Cultural Factors in Decision-Making about Child Physical Abuse: Identifying Reporter Characteristics Influencing Reporting Tendencies

    Science.gov (United States)

    Ibanez, Elizabeth S.; Borrego, Joaquin, Jr.; Pemberton, Joy R.; Terao, Sherri

    2006-01-01

    Objective: This study examined cultural factors that may influence child physical abuse reporting. Relevant cultural factors such as the respondents' ethnic identity and corporal punishment acceptability were investigated as proximal variables of ethnicity that affect child physical abuse reporting tendencies. Method: Participants consisted of 378…

  18. Linking demand and supply factors in identifying cultural ecosystem services of urban green infrastructures

    DEFF Research Database (Denmark)

    Hegetschweiler, K. Tessa; de Vries, Sjerp; Arnberger, Arne

    2017-01-01

    characteristics of the ecosystem. We conducted a review of publications dealing with demand or social factors such as user needs, preferences and values as well as spatially explicit supply or physical factors such as amount of green space, (bio)diversity, recreational infrastructure, etc. and linking demand...... applicability for urban management and planning...

  19. Identifying and Ranking the Factors Affecting Virtuousness in Yazd University-Affiliated Hospitals

    Directory of Open Access Journals (Sweden)

    H Shekari

    2015-07-01

    Conclusion: The results of ranking the factors of organizational virtuous showed that for moving toward virtuousness, the factors of ethical Culture, vision and Care for Community should be improvedby promoting ethics (Providing ethical standards for employee’s and manager’s behavior, Corporate Philanthropy, considering virtues in mission and vision etc. in mentioned hospitals.

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

    Czech Academy of Sciences Publication Activity Database

    Urbanová, Martina; Kobera, Libor; Brus, Jiří

    2013-01-01

    Roč. 51, č. 11 (2013), s. 734-742 ISSN 0749-1581 R&D Projects: GA ČR(CZ) GA13-24155S Institutional support: RVO:61389013 Keywords : solid-state NMR * 27Al MAS NMR * factor analysis Subject RIV: JN - Civil Engineering Impact factor: 1.559, year: 2013

  1. 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.

  2. 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.

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

    Science.gov (United States)

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

    2017-03-01

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

  4. 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

  5. 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.

  6. Factors influencing speech and language outcomes of children with early identified severe/profound hearing loss: Clinician-identified facilitators and barriers.

    Science.gov (United States)

    Fulcher, Anne Nivelles; Purcell, Alison; Baker, Elise; Munro, Natalie

    2015-06-01

    Early identification of severe/profound childhood hearing loss (HL) gives these children access to hearing devices and early intervention to facilitate improved speech and language outcomes. Predicting which infants will go on to achieve such outcomes remains difficult. This study describes clinician identified malleable and non-malleable factors that may influence speech and language outcomes for children with severe/profound HL. Semi-structured interviews were conducted with six experienced auditory verbal clinicians. A collective case study design was implemented. The interviews were transcribed and coded into themes using constant comparative analysis. Clinicians identified that, for children with severe/profound HL, early identification, early amplification and commencing auditory-verbal intervention under 6 months of age may facilitate child progress. Possible barriers were living in rural/remote areas, the clinicians' lack of experience and confidence in providing intervention for infants under age 6-months and belonging to a family with a culturally and linguistically diverse (CALD) background. The results indicate that multiple factors need to be considered by clinicians working with children with HL and their families to determine how each child functions within their own environment and personal contexts, consistent with the International Classification of Functioning, Disability and Health (ICF) framework. Such an approach is likely to empower clinicians to carefully balance potential barriers to, and facilitators of, optimal speech and language outcomes for all children with HL.

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

    DEFF Research Database (Denmark)

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

    2016-01-01

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

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

    Science.gov (United States)

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

  9. Evaluation of bentonite alteration due to interactions with iron. Sensitivity analyses to identify the important factors for the bentonite alteration

    International Nuclear Information System (INIS)

    Sasamoto, Hiroshi; Wilson, James; Sato, Tsutomu

    2013-01-01

    Performance assessment of geological disposal systems for high-level radioactive waste requires a consideration of long-term systems behaviour. It is possible that the alteration of swelling clay present in bentonite buffers might have an impact on buffer functions. In the present study, iron (as a candidate overpack material)-bentonite (I-B) interactions were evaluated as the main buffer alteration scenario. Existing knowledge on alteration of bentonite during I-B interactions was first reviewed, then the evaluation methodology was developed considering modeling techniques previously used overseas. A conceptual model for smectite alteration during I-B interactions was produced. The following reactions and processes were selected: 1) release of Fe 2+ due to overpack corrosion; 2) diffusion of Fe 2+ in compacted bentonite; 3) sorption of Fe 2+ on smectite edge and ion exchange in interlayers; 4) dissolution of primary phases and formation of alteration products. Sensitivity analyses were performed to identify the most important factors for the alteration of bentonite by I-B interactions. (author)

  10. Long-Term Military Contingency Operations: Identifying the Factors Affecting Budgeting in Annual or Supplemental Appropriations

    National Research Council Canada - National Science Library

    Evans, Amanda B

    2006-01-01

    .... The results show that planning, timing, accountability, visibility, politics and policy, stakeholder influence, military objectives, and fear of change are the most important factors. These findings can help stakeholders shape funding strategy.

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

    NARCIS (Netherlands)

    Essers, G.; Dulmen, S. van; Weel, C. van; Vleuten, C. van der; Kramer, A.

    2011-01-01

    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 performance

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

    Science.gov (United States)

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

    2013-01-01

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

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

    Science.gov (United States)

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

    2013-01-01

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

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

    Science.gov (United States)

    Boens, Noël; Van der Auweraer, Mark

    2014-02-01

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

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

    DEFF Research Database (Denmark)

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

    2015-01-01

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

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

    OpenAIRE

    Borut Jereb; Teodora Ivanuša; Bojan Rosi

    2013-01-01

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

  17. 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

    ) simulations and hydrogen/deuterium exchange (HX) mass spectrometry on free and TF-bound FVIIa. The differences in conformational dynamics from MD simulations are shown to be confined to regions of FVIIa observed to undergo structural stabilization as judged by HX experiments, especially implicating activation......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...... stability of activation loop 3. Altogether, our findings strongly support an allosteric activation mechanism initiated by the stabilization of the Leu305{163}/Phe374{225} pair, which, in turn, stabilizes activation loop 3 and the S(1) and S(3) substrate pockets, the activation pocket, and N...

  18. 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.

  19. An effective method to identify various factors for denoising wrist pulse signal using wavelet denoising algorithm.

    Science.gov (United States)

    Garg, Nidhi; Ryait, Hardeep S; Kumar, Amod; Bisht, Amandeep

    2018-01-01

    WPS is a non-invasive method to investigate human health. During signal acquisition, noises are also recorded along with WPS. Clean WPS with high peak signal to noise ratio is a prerequisite before use in disease diagnosis. Wavelet Transform is a commonly used method in the filtration process. Apart from its extensive use, the appropriate factors for wavelet denoising algorithm is not yet clear in WPS application. The presented work gives an effective approach to select various factors for wavelet denoise algorithm. With the appropriate selection of wavelet and factors, it is possible to reduce noise in WPS. In this work, all the factors of wavelet denoising are varied successively. Various evaluation parameters such as MSE, PSNR, PRD and Fit Coefficient are used to find out the performance of the wavelet denoised algorithm at every one step. The results obtained from computerized WPS illustrates that the presented approach can successfully select the mother wavelet and other factors for wavelet denoise algorithm. The selection of db9 as mother wavelet with sure threshold function and single rescaling function using UWT has been a better option for our database. The empirical results proves that the methodology discussed here could be effective in denoising WPS of any morphological pattern.

  20. Identifying the Factors That Influence Change in SEBD Using Logistic Regression Analysis

    Science.gov (United States)

    Camilleri, Liberato; Cefai, Carmel

    2013-01-01

    Multiple linear regression and ANOVA models are widely used in applications since they provide effective statistical tools for assessing the relationship between a continuous dependent variable and several predictors. However these models rely heavily on linearity and normality assumptions and they do not accommodate categorical dependent…

  1. 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.

  2. 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

    the LFT matrices represent the mapping of the uncertainties in and out of the full and reduced FE system matrices. Scaling the LFT matrices easily leads to the amplitudes of the uncertainty parameters., Youla Parametrization method is applied to transform the identification problem into an open...... for model-based control design and fast identification., The paper elucidates how nodal parametric uncertainties, which are easily represented in the full FE coordinate system, can be represented in the new coordinate system of the reduced model. The uncertainty is described as a single column vector...... of the system matrix A of the full FE model while it is represented as several elements spread over multiple rows and columns of the system matrix of the reduced model. The parametric uncertainty, for both the full and reduced FE model, is represented using Linear Fractional Transformation (LFT). In this way...

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

    Directory of Open Access Journals (Sweden)

    Molraudee Saratun

    2013-11-01

    Full Text Available Normal 0 false false false IN X-NONE X-NONE MicrosoftInternetExplorer4 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 organisational 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 satisfaction at the Thai state enterprise. Keywords: Performance management, contextual factors, performance management satisfaction, public organisations, Thailand. /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;}

  4. 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.

  5. 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…

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

    Science.gov (United States)

    Williams, Grant; Clement, John

    2015-01-01

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

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

    Science.gov (United States)

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

    2010-04-01

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

  8. 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.

  9. A Drosophila Model Identifies a Critical Role for Zinc in Mineralization for Kidney Stone Disease

    Science.gov (United States)

    Lang, Sven; Bose, Neelanjan; Kahn, Arnold; Flechner, Lawrence; Blaschko, Sarah D.; Zee, Tiffany; Muteliefu, Gulinuer; Bond, Nichole; Kolipinski, Marysia; Fakra, Sirine C.; Mandel, Neil; Miller, Joe; Ramanathan, Arvind; Killilea, David W.; Brückner, Katja; Kapahi, Pankaj; Stoller, Marshall L.

    2015-01-01

    Ectopic calcification is a driving force for a variety of diseases, including kidney stones and atherosclerosis, but initiating factors remain largely unknown. Given its importance in seemingly divergent disease processes, identifying fundamental principal actors for ectopic calcification may have broad translational significance. Here we establish a Drosophila melanogaster model for ectopic calcification by inhibiting xanthine dehydrogenase whose deficiency leads to kidney stones in humans and dogs. Micro X-ray absorption near edge spectroscopy (μXANES) synchrotron analyses revealed high enrichment of zinc in the Drosophila equivalent of kidney stones, which was also observed in human kidney stones and Randall’s plaques (early calcifications seen in human kidneys thought to be the precursor for renal stones). To further test the role of zinc in driving mineralization, we inhibited zinc transporter genes in the ZnT family and observed suppression of Drosophila stone formation. Taken together, genetic, dietary, and pharmacologic interventions to lower zinc confirm a critical role for zinc in driving the process of heterogeneous nucleation that eventually leads to stone formation. Our findings open a novel perspective on the etiology of urinary stones and related diseases, which may lead to the identification of new preventive and therapeutic approaches. PMID:25970330

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

    Science.gov (United States)

    2010-01-01

    Background 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. Methods 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 Results 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. Summary 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

  11. 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.

  12. 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

  13. Identifying Socio-Cultural Factors That Impact the Use of Open Educational Resources in Local Public Administrations

    OpenAIRE

    Julia Stoffregen; Jan M. Pawlowski; Eric Ras; Snezana Scepanovic; Dragica Zugic

    2016-01-01

    The goal of this paper is to define relevant barriers to the exchange of Open Educational Resources in local public administrations. Building upon a cultural model, eleven experts were interviewed and asked to evaluate several factors, such as openness in discourse, learning at the workplace, and superior support, among others. The result is a set of socio-cultural factors that shape the use of Open Educational Resources in public administrations. Significant factors are, in...

  14. 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…

  15. 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…

  16. 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…

  17. 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.

  18. Identifying Factors That Are Most Influential in Veteran Teachers Seriously Considering Leaving the Profession

    Science.gov (United States)

    Culkin, Michaela A.

    2016-01-01

    This study investigated the factors most influential when veteran teachers seriously consider leaving the teaching profession. Teachers in the education profession who are in the later stages of their careers hold the experience that benefits all who teach in schools. There is ample literature discussing why new teachers leave the profession, but…

  19. Adjustment and Other Factors Related to High School Aged Students Identified as Hearing Impaired

    Science.gov (United States)

    Milano, Charlene; Upshire, Tara; Scarazzo, Sara; Schade, Benjamin P.; Larwin, Karen H.

    2016-01-01

    Healthy social, emotional and cognitive development of deaf children depends upon complex interactions between the many individual and environmental factors associated with deafness. Deaf children and adolescents have been reported to possess greater rates of mental health problems than hearing children and adolescents. Dysfunction in one or more…

  20. A birth cohort study in South-West Ethiopia to identify factors ...

    African Journals Online (AJOL)

    Information was collected on socio-economic, behavioral, biological, and environmental factors for infants, mothers, and family immediately after birth and in consecutive visits. Overall, infant mortality was 106.2/1000, with estimates of 97.0/1000 and 113.5/1000 for urban and rural areas, respectively. Based on the results of ...

  1. Effects of exposure to factor concentrates containing donations from identified AIDS patients

    International Nuclear Information System (INIS)

    Jason, J.; Holman, R.C.; Dixon, G.; Lawrence, D.N.; Bozeman, L.H.; Chorba, T.L.; Tregillus, L.; Evatt, B.L.

    1986-01-01

    The authors recipients of eight lots of factors VII and IX voluntarily withdrawn from distribution because one donor was known to have subsequently developed the acquired immunodeficiency syndrome with a nonexposed cohort matched by age, sex, and factor use. The factor VIII recipient cohorts did not differ in prevalence of antibody to human immunodeficiency virus (HIV), T-cell subset numbers, T-helper to T-suppressor ratios, or immunogloubulin levels. Exposed individuals had higher levels of immune complexes by C1q binding and staphylococcal binding assays and lower responses to phytohemagglutinin and concanavalin A. However, only the staphylococcal binding assay values were outside the normal range for our laboratory. Factor IX recipient cohorts did not differ in HIV antibody prevalence or any immune tests. Although exposed and nonexposed individuals did not differ from each other in a clinically meaningful fashion at initial testing, both the exposed and nonexposed cohorts had high rats of HIV seroprevalence. Market withdrawals were clearly insufficient means of limiting the spread of HIV in hemophilic patients; however, the currently available methods of donor screening and viral inactivation of blood products will prevent continued exposed within this population

  2. 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…

  3. 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.

  4. An assessment of ventilator-associated pneumonias and risk factors identified in the Intensive Care Unit.

    Science.gov (United States)

    Karatas, Mevlut; Saylan, Sedat; Kostakoglu, Ugur; Yilmaz, Gurdal

    2016-01-01

    Ventilator-associated pneumonia (VAP) is a significant cause of hospital-related infections, one that must be prevented due to its high morbidity and mortality. The purpose of this study was to evaluate the incidence and risk factors in patients developing VAP in our intensive care units (ICUs). This retrospective cohort study involved in mechanically ventilated patients hospitalized for more than 48 hours. VAP diagnosed patients were divided into two groups, those developing pneumonia (VAP(+)) and those not (VAP(-)).\\. We researched 1560 patients in adult ICUs, 1152 (73.8%) of whom were mechanically ventilated. The MV use rate was 52%. VAP developed in 15.4% of patients. The VAP rate was calculated as 15.7/1000 ventilator days. Mean length of stay in the ICU for VAP(+) and VAP(-) patients were (26.7±16.3 and 18.1±12.7 days (p<0.001)) and mean length of MV use was (23.5±10.3 and 12.6±7.4 days (p<0.001)). High APACHE II and Charlson co-morbidity index scores, extended length of hospitalization and MV time, previous history of hospitalization and antibiotherapy, reintubation, enteral nutrition, chronic obstructive pulmonary disease, cerebrovascular disease, diabetes mellitus and organ failure were determined as significant risk factors for VAP. The mortality rate in the VAP(+) was 65.2%, with 23.6% being attributed to VAP. VAPs are prominent nosocomial infections that can cause considerable morbidity and mortality in ICUs. Patient care procedures for the early diagnosis of patients with a high risk of VAP and for the reduction of risk factors must be implemented by providing training concerning risk factors related to VAP for ICU personnel, and preventable risk factors must be reduced to a minimum.

  5. Identifying the factors that affect the job satisfaction of early career Notre Dame graduate physiotherapists.

    Science.gov (United States)

    Bacopanos, Eleni; Edgar, Susan

    2016-11-01

    Objective Previous studies have highlighted the short career intentions and high attrition rates of physiotherapists from the profession. The aim of the present study was to examine the job satisfaction and attrition rates of early career physiotherapists graduating from one Western Australian university. Methods A self-administered online survey was conducted of 157 Notre Dame physiotherapy graduates (2006-2012), incorporating a job satisfaction rating scale. Results Results showed that lowered job satisfaction was related to working in the cardiorespiratory area of physiotherapy and working in multiple jobs since graduation. The majority of graduates did not predict a long-term career in physiotherapy, highlighting a lack of career progression and limited scope of practice as influential factors. Conclusions Job satisfaction in early career physiotherapists varies across different clinical areas of practice related to several factors, including challenge and flexibility. New roles in the profession, including extended scope roles, may impact on the future job satisfaction of physiotherapists. Further studies are needed to explore the effect of these roles on workforce trends, including attrition rates. What is known about the topic? Physiotherapists predict careers of 10 years or less on entry into the profession. No previous studies have explored the individual factors influencing job satisfaction in early career physiotherapists across different clinical settings. What does this paper add? This study highlights specific factors influencing the job satisfaction of early career physiotherapists, including clinical area of practice. Physiotherapists working in the cardiorespiratory area were less satisfied, as were physiotherapists undertaking multiple positions since graduation. What are the implications for practitioners? This study informs employers and workforce planners on the factors affecting job satisfaction in early career physiotherapists. In addition

  6. INNOVATIVE PRACTICES IN TOURISM. APOSSIBLE MODEL BY FOSTERING SHADOW FACTORS

    Directory of Open Access Journals (Sweden)

    Ada Mirela TOMESCU

    2015-08-01

    Full Text Available The paper is the result of an empirical research, a study that includes a theoretical framework. The data used to test our hypotheses come from 60 small tourism firms from Bihor County, Romania. The research conducted has revealed that actions focusing on innovation must be based on a solid analysis, supported by the knowledge and the understanding of the contextual factors (environment, culture as a mental programming, values also based on the organizational factors (the management commitment, systemic perspective, learning and practice of experimentation, rapid transfer of knowledge within the organization. For the purpose of this work, the contextual factors that are exogenous represent the shadow factors. The studies performed in three European projects implemented in tourism SMEs of Bihor County have allowed us to advance the idea that contextual and organizational factors, that are identified as the source of innovation are based on rationality, which is enlarged by affectivity and imagination. The identified correlations may be considered, in our opinion an element of novelty and originality. Finally, the purpose of this paper is to provide a possible model, based on the idea of building an innovative firm, the one that has learned how to determine their own employees to be innovative. O03, L2, L26

  7. Does violence affect the use of contraception? Identifying the hidden factors from rural India.

    Science.gov (United States)

    Singh, Nishikant; Shukla, Sudheer Kumar

    2017-01-01

    The objective of this study is to investigates the relationship between domestic violence and use of contraception among married women in rural India. Third round of National Family Health Survey (NFHS-III). Cross tabulation as bivariate analysis and Binary Logistic Regression as multivariate analysis has been employed to fulfill the objective. 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. 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.

  8. 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.

  9. 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......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...... tumors compared to non-metastasizing tumors. Meta-analysis has been used to determine overrepresentation of pathways and transcription factors targets, concordant deregulated in metastasizing breast tumors, in several data sets. RESULTS: The major findings are upregulation of cell cycle pathways...

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

    CSIR Research Space (South Africa)

    Genovesio, A

    2011-05-01

    Full Text Available and the parasite likely plays key roles in the outcome of the disease, suggesting genetic individuality of parasite clones [13,14]. At least 6 different subgroups of T. cruzi have recently been recognized based on genetic, molecular or immunological markers [12... using individual siRNAs in two different cell lines. Overall, our screening strategy allowed us to identify and validate 14 genes whose silencing impaired T. cruzi infection, providing clues about the molecular mechanisms that guide the infection...

  11. 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 ...

  12. 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...

  13. Job satisfaction of nurses and identifying factors of job satisfaction in Slovenian Hospitals

    OpenAIRE

    Lorber, Mateja; Skela Savič, Brigita

    2012-01-01

    Aim To determine the level of job satisfaction of nursing professionals in Slovenian hospitals and factors influencing job satisfaction in nursing. Methods The study included 4 hospitals selected from the hospital list comprising 26 hospitals in Slovenia. The employees of these hospitals represent 29.8% and 509 employees included in the study represent 6% of all employees in nursing in Slovenian hospitals. One structured survey questionnaire was administered to the lea...

  14. Job satisfaction of nurses and identifying factors of job satisfaction in Slovenian Hospitals.

    Science.gov (United States)

    Lorber, Mateja; Skela Savič, Brigita

    2012-06-01

    To determine the level of job satisfaction of nursing professionals in Slovenian hospitals and factors influencing job satisfaction in nursing. The study included 4 hospitals selected from the hospital list comprising 26 hospitals in Slovenia. The employees of these hospitals represent 29.8% and 509 employees included in the study represent 6% of all employees in nursing in Slovenian hospitals. One structured survey questionnaire was administered to the leaders and the other to employees, both consisting 154 items evaluated on a 5 point Likert-type scale. We examined the correlation between independent variables (age, number of years of employment, behavior of leaders, personal characteristics of leaders, and managerial competencies of leaders) and the dependent variable (job satisfaction - satisfaction with the work, coworkers, management, pay, etc) by applying correlation analysis and multivariate regression analysis. In addition, factor analysis was used to establish characteristic components of the variables measured. We found a medium level of job satisfaction in both leaders (3.49±0.5) and employees (3.19±0.6), however, there was a significant difference between their estimates (t=3.237; P=lt;0.001). Job satisfaction was explained by age (Plt;0.05; β=0.091), years of employment (Plt;0.05; β=0.193), personal characteristics of leaders (Plt;0.001; β=0.158), and managerial competencies of leaders (Plt;0.000; β=0.634) in 46% of cases. The factor analysis yielded four factors explaining 64% of the total job satisfaction variance. Satisfied employees play a crucial role in an organization's success, so health care organizations must be aware of the importance of employees' job satisfaction. It is recommended to monitor employees' job satisfaction levels on an annual basis.

  15. Does violence affect the use of contraception? Identifying the hidden factors from rural India

    OpenAIRE

    Nishikant Singh; Sudheer Kumar Shukla

    2017-01-01

    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. Alterna...

  16. Making Bunyaviruses Talk: Interrogation Tactics to Identify Host Factors Required for Infection

    Directory of Open Access Journals (Sweden)

    Amber M. Riblett

    2016-05-01

    Full Text Available The identification of host cellular genes that act as either proviral or antiviral factors has been aided by the development of an increasingly large number of high-throughput screening approaches. Here, we review recent advances in which these new technologies have been used to interrogate host genes for the ability to impact bunyavirus infection, both in terms of technical advances as well as a summary of biological insights gained from these studies.

  17. A metabolomics approach to identify factors influencing glucosinolate thermal degradation rates in Brassica vegetables.

    Science.gov (United States)

    Hennig, K; de Vos, R C H; Maliepaard, C; Dekker, M; Verkerk, R; Bonnema, G

    2014-07-15

    Thermal processing of Brassica vegetables can lead to substantial loss of potential health-promoting glucosinolates (GLs). The extent of thermal degradation of a specific GL varies in different vegetables, possibly due to differences in the composition of other metabolites within the plant matrices. An untargeted metabolomics approach followed by random forest regression was applied to identify metabolites associated to thermal GL degradation in a segregating Brassica oleracea population. Out of 413 metabolites, 15 were associated with the degradation of glucobrassicin, six with that of glucoraphanin and two with both GLs. Among these 23 metabolites three were identified as flavonols (one kaempferol- and two quercetin-derivatives) and two as other GLs (4-methoxyglucobrassicin, gluconasturtiin). Twenty quantitative trait loci (QTLs) for these metabolites, which were associated with glucoraphanin and glucobrassicin degradation, were identified on linkage groups C01, C07 and C09. Two flavonols mapped on linkage groups C07 and C09 and co-localise with the QTL for GL degradation determined previously. Copyright © 2014 Elsevier Ltd. All rights reserved.

  18. Random mutagenesis identifies factors involved in formate-dependent growth of the methanogenic archaeon Methanococcus maripaludis.

    Science.gov (United States)

    Sattler, Christian; Wolf, Sandro; Fersch, Julia; Goetz, Stefan; Rother, Michael

    2013-09-01

    Methane is a key intermediate in the carbon cycle and biologically produced by methanogenic archaea. Most methanogens are able to conserve energy by reducing CO2 to methane using molecular hydrogen as electron donor (hydrogenotrophic methanogenesis), but several hydrogenotrophic methanogens can also use formate as electron donor for methanogenesis. Formate dehydrogenase (Fdh) oxidizes formate to CO2 and is involved in funneling reducing equivalents into the methanogenic pathway, but details on other factors relevant for formate-dependent physiology of methanogens are not available. To learn more about the factors involved in formate-dependent growth of Methanococcus maripaludis strain JJ, we used a recently developed system for random in vitro mutagenesis, which is based on a modified insect transposable element to create 2,865 chromosomal transposon mutants and screened them for impaired growth on formate. Of 12 M. maripaludis transposon-induced mutants exhibiting this phenotype, the transposon insertion sites in the chromosome were mapped. Among the genes, apparently affecting formate-dependent growth were those encoding archaeal transcription factor S, a regulator of ion transport, and carbon monoxide dehydrogenase/acetyl-CoA synthase. Interestingly, in seven of the mutants, transposons were localized in a 10.2 kb region where Fdh1, one of two Fdh isoforms in the organism, is encoded. Two transcription start sites within the 10.2 kb region could be mapped, and quantification of transcripts revealed that transposon insertion in this region diminished fdhA1 expression due to polar effects.

  19. Identifying associated factors with social capital using path analysis: A population-based survey in Tehran, Iran (Urban HEART-2).

    Science.gov (United States)

    Asadi-Lari, Mohsen; Hassanzadeh, Jafar; Torabinia, Mansour; Vaez-Mahdavi, Mohammad Reza; Montazeri, Ali; Ghaem, Haleh; Menati, Rostam; Niazi, Mohsen; Kassani, Aziz

    2016-01-01

    Background: Social capital has been defined as norms, networks, and social links that facilitate collective actions. Social capital is related to a number of main social and public health variables. Therefore, the present study aimed to determine the factors associated with social capital among the residents of Tehran, Iran. Methods: In this large cross-sectional population-based study, 31531 residents aged 20 years and above were selected through multi-stage sampling method from 22 districts of Tehran in 2011. The social capital questionnaire, 28-item General Health Questionnaire (GHQ-28), and Short-Form Health Survey (SF-12) were used. Hypothetical causal models were designed to identify the pathways through which different variables influenced the components of social capital. Then, path analysis was conducted for identifying the determinants of social capital. Results: The most influential variables in 'individual trust' were job status (β=0.37, p=0.02), marital status (β=0.32, p=0.01), Physical Component Summary (PCS) (β=0.37, p=0.02), and age (β=0.34, p=0.03). On the other hand, education level (β=0.34, p=0.01), age (β=0.33, p=0.02), marital status (β=0.33, p=0.01), and job status (β=0.32, p=0.01) were effective in 'cohesion and social support'. Additionally, age (β=0.18, p=0.02), PCS (β=0.36, p=0.01), house ownership (β=0.23, p=0.03), and mental health (β=0.26, p=0.01) were influential in 'social trust/collective relations'. Conclusion: Social capital can be improved in communities by planning to improve education and occupation status, paying more attention to strengthening family bonds, and provision of local facilities and neighborhood bonds to reduce migration within the city.

  20. 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...

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

    Science.gov (United States)

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

    2014-02-01

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

  2. The Identifying, Evaluating and Prioritizing the Factors Affecting Customers’ Satisfaction with E-service Centers of Iran's Police

    Directory of Open Access Journals (Sweden)

    Seyed Ali Ziaee Azimi

    2016-11-01

    Full Text Available The present research is classified as an applied one employing a descriptive survey design to describe the status quo of the factors affecting customers’ satisfaction with the E-service centers of Iran’s police, known as 10 + police centers. The research population involves all the costumers of the 10+ police centers, among which 420 individuals were chosen through simple random sampling technique. Furthermore, 45 10 + police service centers were selected with probability proportional to size. After Determining the validity and reliability of the researcher-made questionnaire, it has been used to collect the required data. Then, a conceptual model was developed using the theoretical framework and background literature. After that, SPSS software was used to examine and make an analysis of the research hypothesises. The findings indicate that all the identified indices to the customers’ satisfaction with the 10 + police e- service centers (including trust and confidence, staff performance, system facility, environmental facility, basic amenity, providing sufficient notification, time and cost, easy access to the office have an effect on the customers’ satisfaction. In the end, some practical suggestions were made for an improvement in the satisfaction level of the customers to the 10 + police e- service centers.

  3. Waste disposal and households' heterogeneity. Identifying factors shaping attitudes towards source-separated recycling in Bogotá, Colombia.

    Science.gov (United States)

    J Padilla, Alcides; Trujillo, Juan C

    2018-04-01

    Solid waste management in many cities of developing countries is not environmentally sustainable. People traditionally dispose of their solid waste in unsuitable urban areas like sidewalks and satellite dumpsites. This situation nowadays has become a serious public health problem in big Latin American conurbations. Among these densely-populated urban spaces, the Colombia's capital and main city stands out as a special case. In this study, we aim to identify the factors that shape the attitudes towards source-separated recycling among households in Bogotá. Using data from the Colombian Department of Statistics and Bogotá's multi-purpose survey, we estimated a multivariate Probit model. In general, our results show that the higher the household's socioeconomic class, the greater its effort for separating solid wastes. Likewise, our findings also allowed us to characterize household profiles regarding solid waste separation and considering each socioeconomic class. Among these profiles, we found that at lower socioeconomic classes, the attitudes towards solid waste separation are influenced by the use of Internet, the membership to an environmentalist organization, the level of education of the head of household and the homeownership. Hence, increasing the education levels within the poorest segment of the population, promoting affordable housing policies and facilitating Internet access for the vulnerable population could reinforce households' attitudes towards a greater source-separated recycling effort. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

    Science.gov (United States)

    James E. Smith; Linda S. Heath

    2001-01-01

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

  5. 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.

  6. Human factors engineering program review model

    International Nuclear Information System (INIS)

    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

  7. 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.

  8. 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

  9. Progress in Australian dendroclimatology: Identifying growth limiting factors in four climate zones.

    Science.gov (United States)

    Haines, Heather A; Olley, Jon M; Kemp, Justine; English, Nathan B

    2016-12-01

    Dendroclimatology can be used to better understand past climate in regions such as Australia where instrumental and historical climate records are sparse and rarely extend beyond 100years. Here we review 36 Australian dendroclimatic studies which cover the four major climate zones of Australia; temperate, arid, subtropical and tropical. We show that all of these zones contain tree and shrub species which have the potential to provide high quality records of past climate. Despite this potential only four dendroclimatic reconstructions have been published for Australia, one from each of the climate zones: A 3592year temperature record for the SE-temperate zone, a 350year rainfall record for the Western arid zone, a 140year rainfall record for the northern tropics and a 146year rainfall record for SE-subtropics. We report on the spatial distribution of tree-ring studies, the environmental variables identified as limiting tree growth in each study, and identify the key challenges in using tree-ring records for climate reconstruction in Australia. We show that many Australian species have yet to be tested for dendroclimatological potential, and that the application of newer techniques including isotopic analysis, carbon dating, wood density measurements, and anatomical analysis, combined with traditional ring-width measurements should enable more species in each of the climate zones to be used, and long-term climate records to be developed across the entire continent. Copyright © 2016 Elsevier B.V. All rights reserved.

  10. [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.

  11. 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.

  12. IDENTIFYING FACTORS THAT CONTRIBUTE TO THE SATISFACTION OF STUDENTS IN E-LEARNING

    Directory of Open Access Journals (Sweden)

    Levent CALLI,

    2013-01-01

    Full Text Available There has been an increasing interest in the application of e-learning through the enhancement of internet and computer technologies. Satisfaction has appeared as a key factor in order to develop efficient course content in line with students’ demands and expectations. Thus, a lot of research has been conducted on the concept of satisfaction in electronic environments. Satisfaction has been seen to be the most significant variable on loyalty and usage intention in marketing and information science terms, which can also be highly related to academic success. In this regard, this study set out to investigate the effects of several variables on the learning processes of 930 e-learning students in the Sakarya University distance learning program. The findings of the research indicated that factors perceived playfulness, perceived ease of use and multimedia content effectiveness had a significant effect on perceived usefulness. Furthermore, it was concluded that satisfaction was affected by perceived usefulness, perceived playfulness and multimedia content effectivenes

  13. Identifying psychological and socio-economic factors affecting motorcycle helmet use.

    Science.gov (United States)

    Haqverdi, Mahdi Quchaniyan; Seyedabrishami, Seyedehsan; Groeger, John A

    2015-12-01

    Sixty percent of motorcyclist fatalities in traffic accidents of Iran are due to head injuries, but helmet use is low, despite it being a legal requirement. This study used face-to-face interviews to investigate the factors associated with helmet use among motorcycle riders in Mashhad city, the second largest city in Iran. Principal component analysis (PCA) and confirmatory factor analysis (CFA) were used for data reduction and identification of consistent features of the data. Ordered and multinomial logit analyses were used to quantify the influences on helmet use and non-use. The data show that 47% of the sample used a helmet, but a substantial proportion of these did not wear their helmet properly. In addition, 5% of motorcyclists believed that helmets reduced their safety. Norms, attitudes toward helmet use, risky traffic behavior and awareness of traffic rules were found to be the key determinants of helmet use, but perceptions of enforcement lacked influence. Duration of daily motorcycle trips, riding experience and type of job also affected helmet use. Results indicate that motorcyclist training, safety courses for offending motorcyclists and social programs to improve social norms and attitudes regarding helmet use are warranted, as are more effective law enforcement techniques, in order to increase proper use of helmets in Iranian motorcyclists. In addition, special safety courses should be considered for motorcyclists who have committed traffic violations. Copyright © 2015 Elsevier Ltd. All rights reserved.

  14. Identifying and mitigating Sudden Unexpected Death in Epilepsy (SUDEP) risk factors.

    Science.gov (United States)

    Watkins, Lance; Shankar, Rohit; Sander, Josemir W

    2018-04-01

    Sudden Unexpected Death in Epilepsy (SUDEP) is a significant cause of death for people with chronic epilepsy. Good practice guidance in the UK and the USA expect SUDEP to be discussed with the individual. The event rarity, methodological variance and lack of robust research into the pathological mechanisms, associated risk factors, and management strategies have created a challenge on how and what to discuss. There are some significant associations which allows for risk assessment and mitigation. Areas covered: The current understanding of static and modifiable risk factors for SUDEP and how to manage these more effectively are reviewed. Longitudinal risk may be assessed using standardised risk assessment tools which help in communicating risk. Technological advancement allows measurement of physiological parameters associated with seizures and risk of SUDEP using small wearable devices. Further evidence is needed to demonstrate such technologies are efficacious and safe. Expert commentary: Risk reduction should be an important part of epilepsy management and we suggest a Gold Standard of Care which healthcare professionals and services should aim for when approaching SUDEP risk management. A Minimum Standard of Care is also proposed that is practical to implement, that all people with epilepsy should expect to receive.

  15. A retrospective chart review to identify perinatal factors associated with food allergies

    Science.gov (United States)

    2012-01-01

    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. PMID:23078601

  16. 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.

  17. 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.

  18. 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.

  19. 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?

  20. A retrospective chart review to identify perinatal factors associated with food allergies.

    Science.gov (United States)

    Dowhower Karpa, Kelly; Paul, Ian M; Leckie, J Alexander; Shung, Sharon; Carkaci-Salli, Nurgul; Vrana, Kent E; Mauger, David; Fausnight, Tracy; Poger, Jennifer

    2012-10-19

    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. 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. 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). 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.

  1. Talent identification model for sprinter using discriminant factor

    Science.gov (United States)

    Kusnanik, N. W.; Hariyanto, A.; Herdyanto, Y.; Satia, A.

    2018-01-01

    The main purpose of this study was to identify young talented sprinter using discriminant factor. The research was conducted in 3 steps including item pool, screening of item pool, and trial of instruments at the small and big size of samples. 315 male elementary school students participated in this study with mean age of 11-13 years old. Data were collected by measuring anthropometry (standing height, sitting height, body mass, and leg length); testing physical fitness (40m sprint for speed, shuttle run for agility, standing broad jump for power, multistage fitness test for endurance). Data were analyzed using discriminant factor. The result of this study found that there were 5 items that selected as an instrument to identify young talented sprinter: sitting height, body mass, leg length, sprint 40m, and multistage fitness test. Model of Discriminant for talent identification in sprinter was D = -24,497 + (0,155 sitting height) + (0,080 body mass) + (0,148 leg length) + (-1,225 Sprint 40m) + (0,563 MFT). The conclusion of this study: instrument tests that have been selected and discriminant model that have been found can be applied to identify young talented as a sprinter.

  2. Application of a human factors classification framework for patient safety to identify precursor and contributing factors to adverse clinical incidents in hospital.

    Science.gov (United States)

    Mitchell, Rebecca J; Williamson, Ann; Molesworth, Brett

    2016-01-01

    This study aimed to identify temporal precursor and associated contributing factors for adverse clinical incidents in a hospital setting using the Human Factors Classification Framework (HFCF) for patient safety. A random sample of 498 clinical incidents were reviewed. The framework identified key precursor events (PE), contributing factors (CF) and the prime causes of incidents. Descriptive statistics and correspondence analysis were used to examine incident characteristics. Staff action was the most common type of PE identified. Correspondence analysis for all PEs that involved staff action by error type showed that rule-based errors were strongly related to performing medical or monitoring tasks or the administration of medication. Skill-based errors were strongly related to misdiagnoses. Factors relating to the organisation (66.9%) or the patient (53.2%) were the most commonly identified CFs. The HFCF for patient safety was able to identify patterns of causation for the clinical incidents, highlighting the need for targeted preventive approaches, based on an understanding of how and why incidents occur. Copyright © 2015 Elsevier Ltd and The Ergonomics Society. All rights reserved.

  3. Identifying and Quantifying Cultural Factors That Matter to the IT Workforce: An Approach Based on Automated Content Analysis

    DEFF Research Database (Denmark)

    Schmiedel, Theresa; Müller, Oliver; Debortoli, Stefan

    2016-01-01

    builds on 112,610 online reviews of Fortune 500 IT companies collected from Glassdoor, an online platform on which current and former employees can anonymously review companies and their management. We perform an automated content analysis to identify cultural factors that employees emphasize...

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

    Science.gov (United States)

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

    2015-09-29

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

  5. 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.

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

    Science.gov (United States)

    Clark, Renee M; Besterfield-Sacre, Mary E

    2009-03-01

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

  8. 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.

  9. 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

  10. 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.

  11. 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.

  12. 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.

  13. Job satisfaction of nurses and identifying factors of job satisfaction in Slovenian Hospitals

    Science.gov (United States)

    Lorber, Mateja; Skela Savič, Brigita

    2012-01-01

    Aim To determine the level of job satisfaction of nursing professionals in Slovenian hospitals and factors influencing job satisfaction in nursing. Methods The study included 4 hospitals selected from the hospital list comprising 26 hospitals in Slovenia. The employees of these hospitals represent 29.8% and 509 employees included in the study represent 6% of all employees in nursing in Slovenian hospitals. One structured survey questionnaire was administered to the leaders and the other to employees, both consisting 154 items evaluated on a 5 point Likert-type scale. We examined the correlation between independent variables (age, number of years of employment, behavior of leaders, personal characteristics of leaders, and managerial competencies of leaders) and the dependent variable (job satisfaction – satisfaction with the work, coworkers, management, pay, etc) by applying correlation analysis and multivariate regression analysis. In addition, factor analysis was used to establish characteristic components of the variables measured. Results We found a medium level of job satisfaction in both leaders (3.49 ± 0.5) and employees (3.19 ± 0.6), however, there was a significant difference between their estimates (t = 3.237; P = Job satisfaction was explained by age (P job satisfaction variance. Conclusion Satisfied employees play a crucial role in an organization’s success, so health care organizations must be aware of the importance of employees’ job satisfaction. It is recommended to monitor employees’ job satisfaction levels on an annual basis. PMID:22661140

  14. 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,…

  15. Satellite retrieval of actual evapotranspiration in the Tibetan Plateau: Components partitioning, multidecadal trends and dominated factors identifying

    Science.gov (United States)

    Wang, Weiguang; Li, Jinxing; Yu, Zhongbo; Ding, Yimin; Xing, Wanqiu; Lu, Wenjun

    2018-04-01

    As the only connecting term between water balance and energy budget in the earth-atmospheric system, evapotranspiration (ET) is considered the most excellent indicator for the activity for the water and energy cycle. Under the background of global change, regional ET estimates, components partitioning as well as their spatial and temporal patterns recognition are of great importance in understanding the hydrological processes and improving water management practices. This is particularly true for the Tibetan Plateau (TP), one of most sensitive and vulnerable region in response to the environment change in the earth. In this study, with flux site observation data and monthly ET data from the monthly water balance method incorporating the terrestrial water storage changes from the Gravity Recovery and Climate Experiment satellite (GRACE) production as the multiple validations, the long-term daily ET in the TP was retrieved by a modified Penman-Monteith-Leuning (PML) model with considering evapotranspiration over snow covered area during 1982-2012. The spatial and temporal changes of partitioned three components of ET, i.e., soil evaporation (Es), transpiration through the stomata of plant (Ec) and canopy interception (Ei), were investigated in the TP. Meanwhile, how the ET components contribute to ET changes and respond to the change in environmental factors in the TP was revealed and discussed. The results indicate that Es dominates ET in most areas of the TP with the mean annual ratio of 65.7%, except southeastern regions where the vegetation coverage is high. Although regional average ET and three main components all present obvious increase trends during the past decades, high spatial heterogeneity for their trends are identified in the TP. Moreover, a mixed changing pattern can be apparently found for Es in southeastern area, Ec and Ei in northwestern and southeastern area. Spatially, the ET variation are mainly attributed to change in Es, followed by Ec and Ei

  16. Modelling impulsive factors for electronics and restaurant coupons’ e-store display

    Science.gov (United States)

    Ariningsih, P. K.; Nainggolan, M.; Sandy, I. A.

    2018-04-01

    In many times, the increment of e-store visitors does not followed by sales increment. Most purchases through e-commerce are impulsive buying, however only small amount of study is available to understand impulsive factors of e-store display. This paper suggests a preliminary concept on understanding the impulsive factors in Electronics and Restaurant Coupons e-store display, which are two among few popular group products sold through e-commerce. By conducting literature study and survey, 31 attributes were identified as impulsive factors in electronics e-store display and 20 attributes were identified as impulsive factors for restaurant coupon e-store. The attributes were then grouped into comprehensive impulsive factors by factor analysis. Each group of impulsive attributes were generated into 3 factors. Accessibility Factors and Trust Factors appeared for each group products. The other factors are Internal Factors for electronics e-store and Marketing factors for restaurant coupons e-store. Structural Equation Model of the impulsive factors was developed for each type of e-store, which stated the covariance between Trust Factors and Accessibility Factors. Based on preliminary model, Internal Factor and Trust Factor are influencing impulsive buying in electronics store. Special factor for electronics e-store is Internal Factor, while for restaurant coupons e-store is Marketing Factor.

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

    Science.gov (United States)

    Thatte, Bhalchandra D

    2013-01-01

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

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

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    H. C. Winsemius

    2006-01-01

    Full Text Available Variations of water stocks in the upper Zambezi river basin have been determined by 2 different hydrological modelling approaches. The purpose was to provide preliminary terrestrial storage estimates in the upper Zambezi, which will be compared with estimates derived from the Gravity Recovery And Climate Experiment (GRACE in a future study. The first modelling approach is GIS-based, distributed and conceptual (STREAM. The second approach uses Lumped Elementary Watersheds identified and modelled conceptually (LEW. The STREAM model structure has been assessed using GLUE (Generalized Likelihood Uncertainty Estimation a posteriori to determine parameter identifiability. The LEW approach could, in addition, be tested for model structure, because computational efforts of LEW are low. Both models are threshold models, where the non-linear behaviour of the Zambezi river basin is explained by a combination of thresholds and linear reservoirs. The models were forced by time series of gauged and interpolated rainfall. Where available, runoff station data was used to calibrate the models. Ungauged watersheds were generally given the same parameter sets as their neighbouring calibrated watersheds. It appeared that the LEW model structure could be improved by applying GLUE iteratively. Eventually, it led to better identifiability of parameters and consequently a better model structure than the STREAM model. Hence, the final model structure obtained better represents the true hydrology. After calibration, both models show a comparable efficiency in representing discharge. However the LEW model shows a far greater storage amplitude than the STREAM model. This emphasizes the storage uncertainty related to hydrological modelling in data-scarce environments such as the Zambezi river basin. It underlines the need and potential for independent observations of terrestrial storage to enhance our understanding and modelling capacity of the hydrological processes. GRACE

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

    DEFF Research Database (Denmark)

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

    2013-01-01

    Purpose: Life cycle impact assessment (LCIA) is a field of active development. The last decade has seen prolific publication of new impact assessment methods covering many different impact categories and providing characterization factors that often deviate from each other for the same substance...... 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...... of characterization models or factors were done in the project. From a total of 156 models, 91 were short listed as possible candidates for a recommendation within their impact category. Criteria were developed for analyzing the models within each impact category. The criteria addressed both scientific qualities...

  20. Identifying individual risk factors and documenting the pattern of heat-related illness through analyses of hospitalization and patterns of household cooling.

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    Michael T Schmeltz

    Full Text Available As climate change increases the frequency and intensity of extreme heat events researchers and public health officials must work towards understanding the causes and outcomes of heat-related morbidity and mortality. While there have been many studies on both heat-related illness (HRI, there are fewer on heat-related morbidity than on heat-related mortality.To identify individual and environmental risk factors for hospitalizations and document patterns of household cooling.We performed a pooled cross-sectional analysis of secondary U.S. data, the Nationwide Inpatient Sample. Risk ratios were calculated from multivariable models to identify risk factors for hospitalizations. Hierarchical modeling was also employed to identify relationships between individual and hospital level predictors of hospitalizations. Patterns of air conditioning use were analyzed among the vulnerable populations identified.Hospitalizations due to HRI increased over the study period compared to all other hospitalizations. Populations at elevated risk for HRI hospitalization were blacks, males and all age groups above the age of 40. Those living in zip-codes in the lowest income quartile and the uninsured were also at an increased risk. Hospitalizations for HRI in rural and small urban clusters were elevated, compared to urban areas.Risk factors for HRI include age greater than 40, male gender and hospitalization in rural areas or small urban clusters. Our analysis also revealed an increasing pattern of HRI hospitalizations over time and decreased association between common comorbidities and heat illnesses which may be indicative of underreporting.

  1. Using exploratory factor analysis of food frequency questionnaires to identify dietary patterns among Yup’ik People

    Science.gov (United States)

    Ryman, Tove K.; Austin, Melissa A.; Hopkins, Scarlett; Philip, Jacques; O’Brien, Diane; Thummel, Kenneth; Boyer, Bert B.

    2012-01-01

    Objective A food frequency questionnaire (FFQ) developed by the Center for Alaska Native Health Research for studies in Yup’ik people includes market foods and subsistence foods such as moose, seal, waterfowl and salmon that may be related to disease risk. Because the FFQ contains >100 food items, we sought to characterize dietary patterns more simply for use in ongoing pharmacogenomics studies. Design Exploratory factor analysis was used to derive a small number of “factors” that explain a substantial amount of the variation in the Yup’ik diet. We estimated factor scores and measured associations with demographic characteristics and biomarkers. Setting Southwest Alaska, US Subjects 358 Yup’ik people, ≥ 18 years Results We identified 3 factors that each accounted for ≥10% of the common variance: the first characterized by “processed foods” (e.g., salty snacks, sweetened cereals); the second by “fruits and vegetables” (e.g., fresh citrus, potato salad); and the third by “subsistence foods” (seal or walrus soup, non-oily fish). Participants from coastal communities had higher values for the “subsistence” factor, whereas participants from inland communities had higher values for the “fruits and vegetables” factor. A biomarker of marine intake, δ 15N, was correlated with the “subsistence” factor, whereas a biomarker of corn and sugar-cane based market food intake, δ 13C, was correlated with “processed foods”. Conclusions This exploratory factor analysis identified 3 factors that appear to reflect dietary patterns among Yup’ik based on associations with participant characteristics and biomarkers. These factors will be useful for chronic disease studies in this population. PMID:23290469

  2. Identifying The Effective Factors for Cost Overrun and Time Delay in Water Construction Projects

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    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.

  3. Genome-Wide Analysis to Identify HLA Factors Potentially Associated With Severe Dengue

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    Sudheer Gupta

    2018-04-01

    Full Text Available The pathogenesis of dengue hemorrhagic fever (DHF, following dengue virus (DENV infection, is a complex and poorly understood phenomenon. In view of the clinical need of identifying patients with higher likelihood of developing this severe outcome, we undertook a comparative genome-wide association analysis of epitope variants from sequences available in the ViPR database that have been reported to be differentially related to dengue fever and DHF. Having enumerated the incriminated epitope variants, we determined the corresponding HLA alleles in the context of which DENV infection could potentially precipitate DHF. Our analysis considered the development of DHF in three different perspectives: (a as a consequence of primary DENV infection, (b following secondary DENV infection with a heterologous serotype, (c as a result of DENV infection following infection with related flaviviruses like Zika virus, Japanese Encephalitis virus, West Nile virus, etc. Subject to experimental validation, these viral and host markers would be valuable in triaging DENV-infected patients for closer supervision owing to the relatively higher risk of poor prognostic outcome and also for the judicious allocation of scarce institutional resources during large outbreaks.

  4. Identifying risk factors for child neglect in rural areas of western China.

    Science.gov (United States)

    Li, Q; Zhong, Y; Chen, K; Zhong, Z; Pan, J

    2015-11-01

    Children who are neglected can experience serious and lifelong consequences. Earlier identification of children at risk for child neglect might reduce the individual, medical and societal costs. A cross-sectional survey using multi-stage stratified cluster random sampling was conducted in Shaanxi and Chongqing from September 2012 to April 2013. The child neglect was measured by scale on child neglect in Rural China. The neglect rates between groups were compared with a chi-squared test. Factors possibly associated with neglect were analysed with binary logistic regression. All analyses were conducted in 2014. A total of 4131 eligible participants (2094 boys and 2037 girls) from 21 schools were recruited. The overall prevalence of child neglect was 55.50%. Significant differences were found between children of Han nationality (53.07%) and children of minorities (68.76%) (P neglect. The neglect rate of school-aged children in rural areas of western China is much higher than that in urban areas and eastern China. Children belonging to minorities, step families and multi-child families, whose mother seldom goes home, are at a higher risk of being neglected. The left-behind children deserve more attention from government and researchers. © 2015 John Wiley & Sons Ltd.

  5. Identifying Factors Reinforcing Robotization: Interactive Forces of Employment, Working Hour and Wage

    Directory of Open Access Journals (Sweden)

    Joonmo Cho

    2018-02-01

    Full Text Available Unlike previous studies on robotization approaching the future based on the cutting-edge technologies and adopting a framework where robotization is considered as an exogenous variable, this study considers that robotization occurs endogenously and uses it as a dependent variable for an objective examination of the effect of robotization on the labor market. To this end, a robotization indicator is created based on the actual number of industrial robots currently deployed in workplaces, and a multiple regression analysis is performed using the robotization indicator and labor variables such as employment, working hours, and wage. The results using the multiple regression considering the triangular relationship of employment–working-hours–wages show that job destruction due to robotization is not too remarkable yet that use. Our results show the complementary relation between employment and robotization, but the substituting relation between working hour and robotization. The results also demonstrate the effects of union, the size of the company and the proportion of production workers and simple labor workers etc. These findings indicate that the degree of robotization may vary with many factors of the labor market. Limitations of this study and implications for future research are also discussed.

  6. Identifying factors associated with hospital readmissions among stroke patients in Taipei.

    Science.gov (United States)

    Chuang, Kun-Yang; Wu, Shwu-Chong; Ma, Ai-Hsuan Sandra; Chen, Yu-Hui; Wu, Chen-Long

    2005-06-01

    Hospital readmissions contribute significantly to the cost of medical care, and may reflect unresolved problems at discharge or a lack of resources in post-hospital care. The purpose of this paper is to assess the effects of patient characteristics at discharge, the need for nursing care, discharge planning program, post-hospital care arrangements, and caregiver characteristics on readmissions of stroke patients. Patients discharged from neurological wards in seven hospitals in the Taipei area were recruited into the study. Surveys were conducted before their discharge, and at one month after discharge. Of the 489 patients included in the study, 24.3% were readmitted. After controlling for other variables, factors associated with readmissions were number of limitations in activities of daily living (ADL), first incidence of stroke, the need for wound nursing care, the adoption of a care plan, and the discharge locations. Contrary to expectation, age, length of stay, counseling before discharge, and caregiver burden were not associated with readmissions. The findings of this study indicate that ADL limitation is an effective predictor of readmissions. Increasing home nursing resources to meet the demand for wound nursing care may also be effective in reducing readmissions. Discharging patients into institutions for a short period of time may also prove to be more economically viable due to the reduction in readmissions.

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

    Science.gov (United States)

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

    2018-01-01

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

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

    Science.gov (United States)

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

    2011-04-01

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

  9. Coupling field and laboratory measurements to estimate the emission factors of identified and unidentified trace gases for prescribed fires

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    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

  10. Identifying and Studying the Factors Effective on Greenhouses Profitability in the Varamin Plain

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    Narges Rajabi Tehrani

    2017-01-01

    Full Text Available The purpose of this research was economic evaluation of green houses and the factors that affect their profitability in the Varamin plain. The type of this research is descriptive-correlation research that was conducted by using a survey method. The statistical population of the research consisted of the beneficiary farmers of established and cultivated green houses in the Varamin plain. The sample size was 108 farmers. The sampling method was simple random sampling method. The main tool of this research study is a questionnaire that whose validity was verified by using a panel of experts and professors in the field of agriculture. The reliability of the questionnaire was assessed through a pre-test for which the Cronbach alpha was between 0.78 and 0.85 which is considered to be acceptable. The results of this research study show that the mean of the profitability index of cost benefit  was 2.286 and thus there is a significant positive correlation between agricultural experience, the level of famer education, agricultural income, the total area of the green house, technical knowledge, using of information resources with the cost benefit  profitability index. The results of regression analysis also indicated that the five variables of agricultural experience, agricultural income, the total area of the green house, technical knowledge, using of information resources well explain for 51.5 % of the changes in the cost benefit profitability index of the green houses located in the Varamin plain. Finally, it is recommended to improve the cost benefit profitability index by actions such as increasing the level of technical knowledge and farmers' access to and use of information resources.

  11. Identifying biological concepts from a protein-related corpus with a probabilistic topic model

    Directory of Open Access Journals (Sweden)

    Lu Xinghua

    2006-02-01

    Full Text Available Abstract Background Biomedical literature, e.g., MEDLINE, contains a wealth of knowledge regarding functions of proteins. Major recurring biological concepts within such text corpora represent the domains of this body of knowledge. The goal of this research is to identify the major biological topics/concepts from a corpus of protein-related MEDLINE© titles and abstracts by applying a probabilistic topic model. Results The latent Dirichlet allocation (LDA model was applied to the corpus. Based on the Bayesian model selection, 300 major topics were extracted from the corpus. The majority of identified topics/concepts was found to be semantically coherent and most represented biological objects or concepts. The identified topics/concepts were further mapped to the controlled vocabulary of the Gene Ontology (GO terms based on mutual information. Conclusion The major and recurring biological concepts within a collection of MEDLINE documents can be extracted by the LDA model. The identified topics/concepts provide parsimonious and semantically-enriched representation of the texts in a semantic space with reduced dimensionality and can be used to index text.

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

    Science.gov (United States)

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

    2017-11-01

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

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

    Science.gov (United States)

    Wu, Hao

    2016-12-01

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

  14. 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.

  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

    2017-12-01

    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. 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

  17. Undisclosed Human Immunodeficiency Virus Risk Factors Identified through a Computer-based Questionnaire Program among Blood Donors in Brazil

    Science.gov (United States)

    Blatyta, Paula Fraiman; Custer, Brian; Gonçalez, Thelma Terezinha; Birch, Rebecca; Lopes, Maria Esther; Ferreira, Maria Ines Lopes; Proietti, Anna Barbara Carneiro; Sabino, Ester Cerdeira; Page, Kimberly; de Almeida Neto, Cesar

    2013-01-01

    Background HIV risk factor screening among blood donors remains a cornerstone for the safety of blood supply and is dependent on prospective donor self-disclosure and an attentive predonation interview. Residual risk of HIV transmission through blood transfusion is higher in Brazil than in many other countries. Audio computer-assisted structured-interview (ACASI) has been shown to increase self-reporting of risk behaviors. Study design and methods This cross-sectional study was conducted between January 2009 and March 2011 at four Brazilian blood centers to identify the population of HIV-negative eligible blood donors that answered face-to-face interviews without disclosing risks, but subsequently disclosed deferrable risk factors by ACASI. Compared to the donor interview, the ACASI contained expanded content on demographics, sexual behavior and other HIV risk factors questions. Results 901 HIV-negative blood donors were interviewed. On the ACASI, 13% of donors (N=120) declared a risk factor that would have resulted in deferral that was not disclosed during the face-to-face assessment. The main risk factors identified were recent unprotected sex with an unknown or irregular partner (49 donors), sex with a person with exposure to blood/ fluids (26 donors), multiple sexual partners (19 donors), and male-male sexual behavior (10 donors). Independent factors associated with the disclosure of any risk factor for HIV were age (≥40 years vs. 18–25 years, AOR=0.45; 95% CI 0.23–0.88) and blood center (Hemope vs. Hemominas, AOR=2.51; 95% CI 1.42–4.44). Conclusion ACASI elicited increased disclosure of HIV risk factors among blood donors. ACASI may be a valuable modality of interview to be introduced in Brazilian blood banks. PMID:23521083

  18. 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

  19. Competing Factor Models of Child and Adolescent Psychopathology.

    Science.gov (United States)

    Doyle, Mark M; Murphy, Jamie; Shevlin, Mark

    2016-11-01

    Co-occurring psychological disorders are highly prevalent among children and adolescents. To date, the most widely utilised factor model used to explain this co-occurrence is the two factor model of internalising and externalising (Achenbach 1966). Several competing models of general psychopathology have since been reported as alternatives, including a recent three factor model of Distress, Fear and Externalising Dimensions (Krueger 1999). Evidence for the three factor model suggests there are advantages to utilising a more complex model. Using the British Child and Adolescent Mental Health Survey 2004 data (B-CAMHS; N = 7997), confirmatory factor analysis was used to test competing factor structure models of child and adolescent psychopathology. The B-CAMHS was an epidemiological survey of children between the ages of 5 and 16 in Great Britain. Child psychological disorders were assessed using the Strength and Difficulties Questionnaire (Goodman 1997), and the Development and Wellbeing Assessment (Goodman et al. 2000). A range of covariates and risk variables including trauma, parent mental health and family functioning where subsequently utilised within a MIMIC model framework to predict each dimension of the 2 and three factor structure models. Two models demonstrated acceptable fit. The first complimented Achenbach's Internalising and Externalising structure. The three factor model was found to have highly comparable fit indices to the two factor model. The second order models did not accurately represent the data nor did an alternative three factor model of Internalising, Externalising and ADHD. The two factor and three factor MIMIC models observed unique profiles of risk for each dimension. The findings suggest that child and adolescent psychopathology may also be accurately conceptualised in terms of distress, fear and externalising dimensions. The MIMIC models demonstrated that the Distress and Fear dimensions have their own unique etiological profile of

  20. 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.

  1. 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.

  2. Identifying the effects of parameter uncertainty on the reliability of modeling the stability of overhanging, multi-layered, river banks

    Science.gov (United States)

    Samadi, A.; Amiri-Tokaldany, E.; Davoudi, M. H.; Darby, S. E.

    2011-11-01

    Composite river banks consist of a basal layer of non-cohesive material overlain by a cohesive layer of fine-grained material. In such banks, fluvial erosion of the lower, non-cohesive, layer typically occurs at a much higher rate than erosion of the upper part of the bank. Consequently, such banks normally develop a cantilevered bank profile, with bank retreat of the upper part of the bank taking place predominantly by the failure of these cantilevers. To predict the undesirable impacts of this type of bank retreat, a number of bank stability models have been presented in the literature. These models typically express bank stability by defining a factor of safety as the ratio of resisting and driving forces acting on the incipient failure block. These forces are affected by a range of controlling factors that include such aspects as the overhanging block geometry, and the geotechnical properties of the bank materials. In this paper, we introduce a new bank stability relation (for shear-type cantilever failures) that considers the hydrological status of cantilevered riverbanks, while beam-type failures are analyzed using a previously proposed relation. We employ these stability models to evaluate the effects of parameter uncertainty on the reliability of riverbank stability modeling of overhanging banks. This is achieved by employing a simple model of overhanging failure with respect to shear and beam failure mechanisms in a series of sensitivity tests and Monte Carlo analyses to identify, for each model parameter, the range of values that induce significant changes in the simulated factor of safety. The results show that care is required in parameterising (i) the geometrical shape of the overhanging-block and (ii) the bank material cohesion and unit weight, as predictions of bank stability are sensitive to variations of these factors.

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

    DEFF Research Database (Denmark)

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

    2017-01-01

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

  4. Genome-Wide Expression Profiling of Five Mouse Models Identifies Similarities and Differences with Human Psoriasis

    Science.gov (United States)

    Swindell, William R.; Johnston, Andrew; Carbajal, Steve; Han, Gangwen; Wohn, Christian; Lu, Jun; Xing, Xianying; Nair, Rajan P.; Voorhees, John J.; Elder, James T.; Wang, Xiao-Jing; Sano, Shigetoshi; Prens, Errol P.; DiGiovanni, John; Pittelkow, Mark R.; Ward, Nicole L.; Gudjonsson, Johann E.

    2011-01-01

    Development of a suitable mouse model would facilitate the investigation of pathomechanisms underlying human psoriasis and would also assist in development of therapeutic treatments. However, while many psoriasis mouse models have been proposed, no single model recapitulates all features of the human disease, and standardized validation criteria for psoriasis mouse models have not been widely applied. In this study, whole-genome transcriptional profiling is used to compare gene expression patterns manifested by human psoriatic skin lesions with those that occur in five psoriasis mouse models (K5-Tie2, imiquimod, K14-AREG, K5-Stat3C and K5-TGFbeta1). While the cutaneous gene expression profiles associated with each mouse phenotype exhibited statistically significant similarity to the expression profile of psoriasis in humans, each model displayed distinctive sets of similarities and differences in comparison to human psoriasis. For all five models, correspondence to the human disease was strong with respect to genes involved in epidermal development and keratinization. Immune and inflammation-associated gene expression, in contrast, was more variable between models as compared to the human disease. These findings support the value of all five models as research tools, each with identifiable areas of convergence to and divergence from the human disease. Additionally, the approach used in this paper provides an objective and quantitative method for evaluation of proposed mouse models of psoriasis, which can be strategically applied in future studies to score strengths of mouse phenotypes relative to specific aspects of human psoriasis. PMID:21483750

  5. Applying psychological theory to evidence-based clinical practice: identifying factors predictive of taking intra-oral radiographs.

    Science.gov (United States)

    Bonetti, Debbie; Pitts, Nigel B; Eccles, Martin; Grimshaw, Jeremy; Johnston, Marie; Steen, Nick; Glidewell, Liz; Thomas, Ruth; Maclennan, Graeme; Clarkson, Jan E; Walker, Anne

    2006-10-01

    This study applies psychological theory to the implementation of evidence-based clinical practice. The first objective was to see if variables from psychological frameworks (developed to understand, predict and influence behaviour) could predict an evidence-based clinical behaviour. The second objective was to develop a scientific rationale to design or choose an implementation intervention. Variables from the Theory of Planned Behaviour, Social Cognitive Theory, Self-Regulation Model, Operant Conditioning, Implementation Intentions and the Precaution Adoption Process were measured, with data collection by postal survey. The primary outcome was the number of intra-oral radiographs taken per course of treatment collected from a central fee claims database. Participants were 214 Scottish General Dental Practitioners. At the theory level, the Theory of Planned Behaviour explained 13% variance in the number of radiographs taken, Social Cognitive Theory explained 7%, Operant Conditioning explained 8%, Implementation Intentions explained 11%. Self-Regulation and Stage Theory did not predict significant variance in radiographs taken. Perceived behavioural control, action planning and risk perception explained 16% of the variance in number of radiographs taken. Knowledge did not predict the number of radiographs taken. The results suggest an intervention targeting predictive psychological variables could increase the implementation of this evidence-based practice, while influencing knowledge is unlikely to do so. Measures which predicted number of radiographs taken also predicted intention to take radiographs, and intention accounted for significant variance in behaviour (adjusted R(2)=5%: F(1,166)=10.28, ptheory-based approach enabled the creation of a methodology that can be replicated for identifying factors predictive of clinical behaviour and for the design and choice of interventions to modify practice as new evidence emerges.

  6. 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.

  7. 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

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

    Science.gov (United States)

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

    2014-01-01

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

  9. Change management in Iranian hospitals: social factors model

    Directory of Open Access Journals (Sweden)

    B. Delgoshaei

    2012-02-01

    Full Text Available Background: Continuous change in the complex health care environments is a major challenge for administrative managers. This study aimed to design a change model to facilitate change implementation in the Iranian hospitals. Methods: This is a descriptive and comparative study. The data were collected through library search and in-depth interview with 15 hospital managers. Nine well-established change theories developed by Lewin, Action Research, Kotter, Ackerman- Anderson and Anderson, Prosci , Kilman, Beer, Continuum, and Gelicher were compared. Common denominators of the theories were identified and tabulated. Experienced hospital managers’ suggestions about social factors were acquired. The initial model was designed and validated using the Delphi Technique. Results: The majority of the selected change models emphasize the significance of social factors in change implementation such as effective communication, organizational climate and culture, and leadership. The results from the interviews indicate that low readiness to change, lack of confidence (or trust for change, and autocratic leadership style ,and poor communication could hinder the change process. Conclusion: Based on the model developed in the study, effective communication, readiness of employees, and a contingency leadership/management combined could lead to successful implementation of change in the hospital.

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

    Directory of Open Access Journals (Sweden)

    Grosul Victoria A.

    2017-06-01

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

  11. 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 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.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.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.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.

  12. Relating genes to function: identifying enriched transcription factors using the ENCODE ChIP-Seq significance tool.

    Science.gov (United States)

    Auerbach, Raymond K; Chen, Bin; Butte, Atul J

    2013-08-01

    Biological analysis has shifted from identifying genes and transcripts to mapping these genes and transcripts to biological functions. The ENCODE Project has generated hundreds of ChIP-Seq experiments spanning multiple transcription factors and cell lines for public use, but tools for a biomedical scientist to analyze these data are either non-existent or tailored to narrow biological questions. We present the ENCODE ChIP-Seq Significance Tool, a flexible web application leveraging public ENCODE data to identify enriched transcription factors in a gene or transcript list for comparative analyses. The ENCODE ChIP-Seq Significance Tool is written in JavaScript on the client side and has been tested on Google Chrome, Apple Safari and Mozilla Firefox browsers. Server-side scripts are written in PHP and leverage R and a MySQL database. The tool is available at http://encodeqt.stanford.edu. abutte@stanford.edu Supplementary material is available at Bioinformatics online.

  13. A clinical decision rule identifies risk factors associated with antimicrobial-resistant urinary pathogens in the emergency department: a retrospective validation study.

    Science.gov (United States)

    Faine, Brett A; Harland, Kari K; Porter, Blake; Liang, Stephen Y; Mohr, Nicholas

    2015-06-01

    Identifying patients at high risk for multidrug-resistant urinary tract infections (UTIs) is important for guiding empirical antimicrobial therapy. Clinical risk factors associated with antimicrobial-resistant urinary pathogens and the derivation of a simple clinical decision rule could help define health care-associated UTI. To derive a simple clinical decision rule to identify clinical risk factors associated with antimicrobial-resistant urinary pathogens. This was a retrospective case-control study of all emergency department (ED) patients from July 1, 2011, to July 1, 2012, who presented to the ED with UTI and a positive urine culture. Candidate risk factors were collected retrospectively from medical record review. We compared differences in patient characteristics stratified by the presence of an antimicrobial-resistant urinary pathogen. A total of 360 patients with UTI had a positive, noncontaminated urine culture during the study period. About 6.7% of patients (n = 24) had a multidrug-resistant (MDR) urinary infection. Logistic regression modeling identified 3 clinical factors associated with the identification of a MDR pathogen: male sex, chronic hemodialysis, and nursing home residence. A scoring system was created to identify patients with MDR pathogens. Test characteristics were calculated using bootstrapping for internal validation, with a sensitivity of 74.7% (95% CI = 55.1%-91.3%) and specificity of 85.1% (95% CI = 77.8%-86.2%), positive likelihood ratio of 4.3, and a negative likelihood ratio of 0.3. Clinical factors can be used to identify UTI patients at high risk of MDR urinary pathogens. © The Author(s) 2015.

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

    Science.gov (United States)

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

    2015-07-01

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

  15. Early-life risk factors identified for owner-reported feline overweight and obesity at around two years of age.

    Science.gov (United States)

    Rowe, E C; Browne, W J; Casey, R A; Gruffydd-Jones, T J; Murray, J K

    2017-08-01

    Obesity is considered the second most common health problem in pet cats in developed countries. This study used prospective data from a longitudinal study of pet cats ('C.L.A.W.S.', www.bristol.ac.uk/vetscience/claws) to identify early-life risk factors for feline overweight/obesity occurring at around two years of age. Data were collected via five owner-completed questionnaires (for cats aged two-six months, six months, 12 months, 18 months and two years respectively) completed between May 2011 and April 2015. Owner-reported body condition scores (BCS) of cats at age two years, assessed using images from the 9-point BCS system (Laflamme, 1997), were categorised into a dichotomous variable: overweight/obese (BCS 6-9) and not overweight (BCS 1-5) and used as the dependent variable. Of the 375 cats with owner-reported BCS, 25.3% were overweight or obese at two years of age. Multivariable logistic regression models were built using stepwise forward-selection. To account for potential hierarchical clustering due to multi-cat households two-level random intercept models were considered but clustering had no impact on the analysis. Models were compared using Wald tests. Six factors were significantly associated with overweight/obesity at two years of age: being overweight or obese at one year of age (OR=10.6, 95%CI 4.4-25.3); owner belief that BCS 7 was the ideal weight (OR=33.2, 95%CI 8.5-129.4), or that BCS represented overweight cats but they would not be concerned if their cat were classified in this category (OR=2.7, 95%CI 1.2-6.2), at questionnaire five completion; vets advising owners that the cat should lose weight, or making no comment on their weight, between one and two years of age (OR=12.1, 95%CI 3.2-44.9 and OR=3.9, 95%CI 1.5-10.3 respectively); owners giving their cat treats when they "felt happy" with them at 18 months of age (OR=2.7, 95%CI 1.0 - 7.3); feeding ≥250g wet food daily between two and six months of age (OR=2.7, 95%CI 1.2-5.9), and feeding

  16. Genome-wide association study identifies vitamin B5 biosynthesis as a host specificity factor in Campylobacter

    OpenAIRE

    Sheppard, Samuel K.; Didelot, Xavier; Meric, Guillaume; Torralbo, Alicia; Jolley, Keith A.; Kelly, David J.; Bentley, Stephen D.; Maiden, Martin C. J.; Parkhill, Julian; Falush, Daniel

    2013-01-01

    Genome-wide association studies have the potential to identify causal genetic factors underlying important phenotypes but have rarely been performed in bacteria. We present an association mapping method that takes into account the clonal population structure of bacteria and is applicable to both core and accessory genome variation. Campylobacter is a common cause of human gastroenteritis as a consequence of its proliferation in multiple farm animal species and its transmission via contaminate...

  17. 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

  18. 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.

  19. Applying psychological theories to evidence-based clinical practice: identifying factors predictive of managing upper respiratory tract infections without antibiotics.

    Science.gov (United States)

    Eccles, Martin P; Grimshaw, Jeremy M; Johnston, Marie; Steen, Nick; Pitts, Nigel B; Thomas, Ruth; Glidewell, Elizabeth; Maclennan, Graeme; Bonetti, Debbie; Walker, Anne

    2007-08-03

    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. 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.

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

    Science.gov (United States)

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

    2011-09-01

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

  1. Identifying factors which enhance capacity to engage in clinical education among podiatry practitioners: an action research project.

    Science.gov (United States)

    Abey, Sally; Lea, Susan; Callaghan, Lynne; Shaw, Steve; Cotton, Debbie

    2015-01-01

    Health profession students develop practical skills whilst integrating theory with practice in a real world environment as an important component of their training. Research in the area of practice placements has identified challenges and barriers to the delivery of effective placement learning. However, there has been little research in podiatry and the question of which factors impact upon clinical educators' capacity to engage with the role remains an under-researched area. This paper presents the second phase of an action research project designed to determine the factors that impact upon clinical educators' capacity to engage with the mentorship role. An online survey was developed and podiatry clinical educators recruited through National Health Service (NHS) Trusts. The survey included socio-demographic items, and questions relating to the factors identified as possible variables influencing clinical educator capacity; the latter was assessed using the 'Clinical Educator Capacity to Engage' scale (CECE). Descriptive statistics were used to explore demographic data whilst the relationship between the CECE and socio-demographic factors were examined using inferential statistics in relation to academic profile, career profile and organisation of the placement. The survey response rate was 42 % (n = 66). Multiple linear regression identified four independent variables which explain a significant proportion of the variability of the dependent variable, 'capacity to engage with clinical education', with an adjusted R2 of 0.428. The four variables were: protected mentorship time, clinical educator relationship with university, sign-off responsibility, and volunteer status. The identification of factors that impact upon clinical educators' capacity to engage in mentoring of students has relevance for strategic planning and policy-making with the emphasis upon capacity-building at an individual level, so that the key attitudes and characteristics that are linked

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

    Science.gov (United States)

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

    2016-09-13

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

  3. Ecological Niche Modeling Identifies Fine-Scale Areas at High Risk of Dengue Fever in the Pearl River Delta, China.

    Science.gov (United States)

    Li, Qiaoxuan; Ren, Hongyan; Zheng, Lan; Cao, Wei; Zhang, An; Zhuang, Dafang; Lu, Liang; Jiang, Huixian

    2017-06-09

    Dengue fever (DF) is one of the most common and rapidly spreading mosquito-borne viral diseases in tropical and subtropical regions. In recent years, this imported disease has posed a serious threat to public health in China, especially in the Pearl River Delta (PRD). Although the severity of DF outbreaks in the PRD is generally associated with known risk factors, fine scale assessments of areas at high risk for DF outbreaks are limited. We built five ecological niche models to identify such areas including a variety of climatic, environmental, and socioeconomic variables, as well as, in some models, extracted principal components. All the models we tested accurately identified the risk of DF, the area under the receiver operating characteristic curve (AUC) were greater than 0.8, but the model using all original variables was the most accurate (AUC = 0.906). Socioeconomic variables had a greater impact on this model (total contribution 55.27%) than climatic and environmental variables (total contribution 44.93%). We found the highest risk of DF outbreaks on the border of Guangzhou and Foshan (in the central PRD), and in northern Zhongshan (in the southern PRD). Our fine-scale results may help health agencies to focus epidemic monitoring tightly on the areas at highest risk of DF outbreaks.

  4. Ecological Niche Modeling Identifies Fine-Scale Areas at High Risk of Dengue Fever in the Pearl River Delta, China

    Directory of Open Access Journals (Sweden)

    Qiaoxuan Li

    2017-06-01

    Full Text Available Dengue fever (DF is one of the most common and rapidly spreading mosquito-borne viral diseases in tropical and subtropical regions. In recent years, this imported disease has posed a serious threat to public health in China, especially in the Pearl River Delta (PRD. Although the severity of DF outbreaks in the PRD is generally associated with known risk factors, fine scale assessments of areas at high risk for DF outbreaks are limited. We built five ecological niche models to identify such areas including a variety of climatic, environmental, and socioeconomic variables, as well as, in some models, extracted principal components. All the models we tested accurately identified the risk of DF, the area under the receiver operating characteristic curve (AUC were greater than 0.8, but the model using all original variables was the most accurate (AUC = 0.906. Socioeconomic variables had a greater impact on this model (total contribution 55.27% than climatic and environmental variables (total contribution 44.93%. We found the highest risk of DF outbreaks on the border of Guangzhou and Foshan (in the central PRD, and in northern Zhongshan (in the southern PRD. Our fine-scale results may help health agencies to focus epidemic monitoring tightly on the areas at highest risk of DF outbreaks.

  5. Identifying sub-categories of social fears using an alternative factor analytic structure of the Social Phobia and Anxiety Inventory.

    Science.gov (United States)

    Panayiotou, Georgia; Michaelides, Michalis P; Theodorou, Marios; Neophytou, Klavdia

    2017-05-01

    This study evaluates an alternative factor structure of the Social Phobia and Anxiety Inventory (Turner et al., 1989), a widely used measure of social anxiety. Existing models ignore variance due to the different social contexts where social fears are expressed. Taking a different approach to scoring than previous studies, this investigation proposes a new model, which, in addition to 4-5 symptom dimensions, is able to capture the situations (strangers, authority figures, members of the opposite sex and people in general) that are of concern to the examinee. To test this model, all 96 items of the Social Phobia scale, rather than the average of the sub-items of its 23 questions were subjected to confirmatory factor analysis. The model shows good fit and is superior to models ignoring the "situation" factors, which show good predictive validity in respect to real life demographics. Utilization of all single questions of the SPAI can capture a wider range of social fears related to social anxiety than using the average of the items, which has implications for the understanding and clinical assessment of social anxiety. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

  6. Identifying unique and shared risk factors for physical intimate partner violence and clinically-significant physical intimate partner violence.

    Science.gov (United States)

    Slep, Amy M Smith; Foran, Heather M; Heyman, Richard E; Snarr, Jeffery D; Usaf Family Advocacy Research Program

    2015-05-01

    Intimate partner violence (IPV) is a significant public health concern. To date, risk factor research has not differentiated physical violence that leads to injury and/or fear (i.e., clinically significant IPV; CS-IPV) from general physical IPV. Isolating risk relations is necessary to best inform prevention and treatment efforts. The current study used an ecological framework and evaluated relations of likely risk factors within individual, family, workplace, and community levels with both CS-IPV and general IPV to determine whether they were related to one type of IPV, both, or neither for both men and women. Probable risk and promotive factors from multiple ecological levels of influence were selected from the literature and assessed, along with CS-IPV and general IPV, via an anonymous, web-based survey. The sample comprised US Air Force (AF) active duty members and civilian spouses (total N = 36,861 men; 24,331 women) from 82 sites worldwide. Relationship satisfaction, age, and alcohol problems were identified as unique risk factors (in the context of the 23 other risk factors examined) across IPV and CS-IPV for men and women. Other unique risk factors were identified that differed in prediction of IPV and CS-IPV. The results suggest a variety of both established and novel potential foci for indirectly targeting partner aggression and clinically-significant IPV by improving people's risk profiles at the individual, family, workplace, and community levels. Aggr. Behav. 41:227-241, 2015. © 2014 Wiley Periodicals, Inc. © 2014 Wiley Periodicals, Inc.

  7. Identifying non-pharmacological risk factors for falling in older adults with type 2 diabetes mellitus: a systematic review.

    Science.gov (United States)

    Gravesande, Janelle; Richardson, Julie

    2017-07-01

    To identify the non-pharmacological risk factors for falling in older adults with type 2 diabetes mellitus (DM2). A systematic review of randomized controlled trials, prospective cohort studies, cross-sectional studies and before/after studies was conducted. Eligible studies identified non-pharmacological risk factors for falling in older adults with DM2. Medline, Embase, Pubmed and CINAHL were searched for relevant studies published through December 2015. Reference lists were also searched for relevant studies. Search terms were DM2, risk factors, falls and falling, older adults, aging, non-insulin dependent diabetes mellitus, accidental falls and trip. Publication language was restricted to English. Thirteen studies met the inclusion criteria: four cross-sectional, six prospective cohorts, two randomized controlled trials and one before/after study. These studies included a total of 13,104 participants, ≥50 years. The most common risk factors for falling were impaired balance, reduced walking velocity, peripheral neuropathy and comorbid conditions. However, lower extremity pain, being overweight and comorbid conditions had the greatest impact on fall risk. Interventions to reduce falling in older adults with type 2 diabetes mellitus should focus on reducing lower extremity pain, reducing body weight and managing comorbid conditions. Implications for Rehabilitation    Diabetes mellitus:   • Older adults with type 2 diabetes mellitus (DM2) have a higher risk for falling than older adults without.   • Older adults with DM2 are more likely to suffer serious injuries when they fall.   • Comprehensive risk factor identification is necessary for rehabilitation professionals to accurately determine whether their clients are at risk for falling.   • Rehabilitation professionals also need to tailor interventions based on the client's risk factors in order to effectively reduce falls and fall-related injuries.

  8. Genome-wide significant localization for working and spatial memory: Identifying genes for psychosis using models of cognition.

    Science.gov (United States)

    Knowles, Emma E M; Carless, Melanie A; de Almeida, Marcio A A; Curran, Joanne E; McKay, D Reese; Sprooten, Emma; Dyer, Thomas D; Göring, Harald H; Olvera, Rene; Fox, Peter; Almasy, Laura; Duggirala, Ravi; Kent, Jack W; Blangero, John; Glahn, David C

    2014-01-01

    It is well established that risk for developing psychosis is largely mediated by the influence of genes, but identifying precisely which genes underlie that risk has been problematic. Focusing on endophenotypes, rather than illness risk, is one solution to this problem. Impaired cognition is a well-established endophenotype of psychosis. Here we aimed to characterize the genetic architecture of cognition using phenotypically detailed models as opposed to relying on general IQ or individual neuropsychological measures. In so doing we hoped to identify genes that mediate cognitive ability, which might also contribute to psychosis risk. Hierarchical factor models of genetically clustered cognitive traits were subjected to linkage analysis followed by QTL region-specific association analyses in a sample of 1,269 Mexican American individuals from extended pedigrees. We identified four genome wide significant QTLs, two for working and two for spatial memory, and a number of plausible and interesting candidate genes. The creation of detailed models of cognition seemingly enhanced the power to detect genetic effects on cognition and provided a number of possible candidate genes for psychosis. © 2013 Wiley Periodicals, Inc.

  9. Identify High-Quality Protein Structural