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The cyclic stress or liquefaction behavior of granular materials is strongly affected by the relative density and confining pressure of the soil. In this study, the state parameter accounting for both relative density and effective stress was used to evaluate soil liquefaction potential. Based on case histories along with the cone penetration test (CPT) database, models for calculating the state parameter using a group method of data handling (GMDH) neural network were developed and recommended according to their performance. The state parameter was then used to develop a state parameter- based probabilistic liquefaction evaluation method using a logistic regression model. From a conservative point of view, the boundary curve of 20% probability of liquefaction was suggested as a deterministic criterion for state parameter- based liquefaction evaluation. Subsequently, a mapping function relating the calculated factor of safety ([F.sub.S]) to the probability of liquefaction ([P.sub.L]) was proposed based on the compiled CPT database. Based on the developed [P.sub.L]- [F.sub.S] function, a new risk criterion associated with the state parameter-based design chart was proposed. Finally, a flowchart of state-based probabilistic liquefaction evaluation and quality control for ground-improvement projects was presented for the benefit of practitioners. Key words: group method of data handling (GMDH), logistic regression, state parameter, liquefaction, cone penetration test. La contrainte cyclique ou le comportement de liquefaction des materiaux granulaires est fortement affecte par la densite relative et la pression de confinement du sol. Au cours de cette etude, le parametre d'etat tenant compte a la fois de la densite relative et de la contrainte effective a ete utilise pour evaluer le potentiel de liquefaction du sol. Sur la base d'etudes de cas et de la base de donnees de l'essai de penetration au cone (<< CPT >>), des modeles de calcul du parametre d'etat utilisant un reseau neuronal de la methode de groupe de traitement des donnees (<< GMDH >>) ont ete developpes et recommandes en fonction de leurs performances. Le parametre d'etat a ensuite ete utilise pour developper une methode d'evaluation probabiliste de la liquefaction basee sur le parametre d'etat en utilisant un modele de regression logistique. D'un point de vue conservateur, la courbe limite de 20 % de probabilite de liquefaction a ete proposee comme critere deterministe pour l'evaluation de la liquefaction basee sur les parametres d'etat. Par la suite, une fonction de mise en correspondance entre le facteur de securite ([F.sub.S]) calcule et la probabilite de liquefaction ([P.sub.L]) a ete proposee sur la base de donnees CPT compilee. Sur la base de la fonction [P.sub.L]- [F.sub.S] developpee, un nouveau critere de risque associe a la carte de conception basee sur les parametres d'etat a ete propose. Finalement, un organigramme de l'evaluation probabiliste de la liquefaction basee sur l'etat et du controle de la qualite pour les projets d'amelioration du sol a ete presente a l'intention des praticiens. [Traduit par la Redaction] Mots-cles : methode de groupe de traitement des donnees (<< GMDH >>), regression logistique, parametre d'etat, liquefaction, essai de penetration au cone., 1. Introduction Due to the high cost and difficulty associated with collecting high-quality undisturbed soil samples and testing granular soils, various in situ methods are used by geotechnical engineers to [...]

Histoplasmosis is a regionally endemic mycosis caused by inhalation of the spores of the fungus Histoplasma capsulatum from the soil, leading occasionally to symptomatic disease and asymptomatic pulmonary nodules (1). [...]

Objectives To determine whether affluent-born White mother's descending neighborhood income is associated with infant mortality rates (< 365 day, IMR). Methods Stratified and multilevel logistic regression analyses were completed on the Illinois transgenerational dataset of singleton births (1989-1991) to non-Latina White mothers (1956-1976) with an early-life residence in affluent neighborhoods (defined as the fourth quartile of income distribution). The breadth of descending neighborhood income was defined by mother's neighborhood income at the time of delivery. Results Infants of White mothers (n = 4890) who did not suffer descending neighborhood income by the time of delivery had a first-year mortality rate of 5.1/1,000. Infants of White mothers who experienced minor (n = 5112), modest (n = 2158), or extreme (n = 339) descending neighborhood income had IMR of 6.5/1,000, 14.4/1,000, and 11.8/1,000, respectively; RR [95% CI] = 1.3 [0.8, 2.1], 2.8 [1.7, 4.8], and 2.3 [0.8, 6.6], respectively. The incidence of young maternal age, inadequate prenatal care utilization, and cigarette smoking rose as descending neighborhood income increased, p < 0.01. In multilevel logistic regression models, the adjusted (controlling for selected individual-level co-variates) OR [95% CI] of infant mortality for White women with an early-life residence in affluent neighborhoods who subsequently experienced minor or modest to extreme (versus absent) descending neighborhood income equaled 1.0 [0.6, 1.8] and 2.1 [1.1, 3.8] respectively. Conclusions White mother's modest to extreme descending neighborhood income from early-life residence in affluent neighborhoods is associated with a twofold greater risk of infant mortality independent of selected biologic, medical, and behavioral characteristics., Author(s): James W. Jr. Collins [sup.1] [sup.3] , Jennifer Colgan [sup.1] , Kristin M. Rankin [sup.2] , Carla Desisto [sup.2] Author Affiliations: (Aff1) 0000 0004 0388 2248, grid.413808.6, Department of [...]

Abstract. Problem definition: Reference prices arise as price expectations against which consumers evaluate products in their purchase scenarios. We investigate what will happen when prospect theory (e.g., reference prices) meets [...]

Background: Topical tranexamic acid (TA) has been reported to be effective in reducing postoperative bleeding and transfusions after total knee arthroplasty (TKA). The main objective of this study was to [...]

Introduction To determine the association of fruit and vegetable consumption with overall sleep duration among pregnant women. Methods Data from the 2011 and 2012 Behavioral Risk Factors Surveillance System (BRFSS) were used. All women (n = 2951) of childbearing age (18-44 years) who were pregnant and responded to all fruit and vegetable consumption and sleep duration questions were included. Covariates included age, race, education level, exercise, and marital status. Data were analyzed using linear and ordinal logistic regression. Results Total daily fruit and vegetable consumption was not associated with sleep duration among pregnant women, controlling for confounders [[beta] = -0.03, (-0.07, 0.00)]. Orange and green vegetable consumption were both inversely associated with sleep duration [[beta] = -0.19, (-0.38, -0.01) and [beta] = -0.20, (-0.33, -0.08) respectively]. Ordinal logistic regression found that the odds of meeting or exceeding sleep time recommendations increased slightly with each unit increase in total fruit and vegetable consumption [OR = 1.05 (1.003, 1.092)] and for every unit increase in fruit consumption [OR = 1.12 (1.038, 1.208)]. Women who exercised within the past 30 days reported approximately 20 min of additional sleep compared to those who did not [[beta] = 0.32 (0.16, 0.49)]. Age, employment status, and marital status were also independently associated with sleep duration. Discussion Sleep duration in pregnant women was associated with exercise and other demographic factors, but only mildly associated with fruit and vegetable consumption. Future research should investigate the effects of additional factors including sleep quality, gestational age, family status and other medications as potential confounders., Author(s): C. H. Duke [sup.1] , J. A. Williamson [sup.1] , K. R. Snook [sup.1] , K. C. Finch [sup.1] , K. L. Sullivan [sup.1] Author Affiliations: (1) grid.256302.0Department of [...]

Objectives Early pregnancy detection is important for improving pregnancy outcomes as the first trimester is a critical window of fetal development; however, there has been no description of trends in timing of pregnancy awareness among US women. Methods We examined data from the 1995, 2002, 2006-2010 and 2011-2013 National Survey of Family Growth on self-reported timing of pregnancy awareness among women aged 15-44 years who reported at least one pregnancy in the 4 or 5 years prior to interview that did not result in induced abortion or adoption (n = 17, 406). We examined the associations between maternal characteristics and late pregnancy awareness ([greater than or equal to]7 weeks' gestation) using adjusted prevalence ratios from logistic regression models. Gestational age at time of pregnancy awareness (continuous) was regressed over year of pregnancy conception (1990-2012) in a linear model. Results Among all pregnancies reported, gestational age at time of pregnancy awareness was 5.5 weeks (standard error = 0.04) and the prevalence of late pregnancy awareness was 23 % (standard error = 1 %). Late pregnancy awareness decreased with maternal age, was more prevalent among non-Hispanic black and Hispanic women compared to non-Hispanic white women, and for unintended pregnancies versus those that were intended (p < 0.01). Mean time of pregnancy awareness did not change linearly over a 23-year time period after adjustment for maternal age at the time of conception (p < 0.16). Conclusions for Practice On average, timing of pregnancy awareness did not change linearly during 1990-2012 among US women and occurs later among certain groups of women who are at higher risk of adverse birth outcomes., Author(s): Amy M. Branum [sup.1] , Katherine A. Ahrens [sup.2] Author Affiliations: (1) Division of Vital Statistics, National Center for Health Statistics, Centers for Disease Control and Prevention, Reproductive Statistics [...]

Objectives Cigarette smoking during pregnancy is an important modifiable risk factor for poor birth outcomes. We evaluated whether participation in a statewide incentive-based smoking cessation program for pregnant women, the Baby & Me-Tobacco Free (BMTF) program, was associated with improved birth outcomes. Methods Linked program and birth certificate data from 866 pregnant smokers who participated in the BMTF program and 11,568 pregnant smokers who were eligible for but did not enroll in the program were analyzed. The BMTF program consisted of 4 prenatal smoking cessation counselling sessions, 12 postpartum follow-up visits, breath carbon monoxide measurements to monitor smoking status, and rewards of diaper vouchers for quitting smoking. Logistic regression models were used to examine the associations of program participation with infant low birth weight and preterm birth. Results Participants who completed 3-4 prenatal smoking cessation sessions had a significantly lower rate of low birth weight than non-participants (4.9 vs. 11.6 %). After adjustment for multiple potential confounders, the odds ratios for low birth weight were 0.51 (95 % confidence interval, 0.30-0.88) in those participants completing 3-4 sessions and 0.37 (95 % confidence interval, 0.17-0.79) in participants who quit smoking, as compared with non-participants. Although not statistically significant, a protective effect was also suggested for preterm birth. Conclusions We found for the first time that successful participation in the BMTF program, a unique incentive-based smoking cessation program for pregnant women implemented in community settings, was associated with significantly reduced odds of having a low birth weight infant., Author(s): Xianglan Zhang [sup.1] , Rose Devasia [sup.2] , Glenn Czarnecki [sup.3] , Jan Frechette [sup.3] , Sarah Russell [sup.4] , Bruce Behringer [sup.5] Author Affiliations: (1) grid.416951.eTennessee Department of [...]

Objective Malnutrition in children pervades all aspects of their health, growth, cognitive and social development and can lead to irreversible and lifelong effects. We examine the prevalence and determinants of malnutrition in children under 5 in the Ghanaian population. Methods Using data from the latest available Ghana Demographic and Health Survey (GDHS), we estimated and compared prevalence of malnutrition in children among the different subgroups of the population. We used multivariable logistic regression to identify potential factors associated with childhood malnutrition in Ghana. Results Overall, 35.6 % (95 % CI: 33.6, 37.6) of Ghanaian children under 5 years of age suffer from some form of malnutrition. Specifically, 27.5 % (95 % CI: 25.1, 28.7), 13.8 % (95 % CI: 12.5, 15.3), 8.9 % (95 % CI: 7.8, 10.2) were stunted, underweight and wasted, respectively. Results from the logistic regression indicate that gender and age of the child, educational and nutritional status of the mother, and financial status of the household are risk factors associated with childhood malnutrition in Ghana. Conclusions for Practice In view of the observed high rate of malnutrition among Ghanaian children despite the interventions that have been in place since the 1990s, there is a need for increased awareness and improved targeted interventions as well as knowledge translation tools including extensive education on infant and young child feeding practices., Author(s): J. E. Ewusie [sup.1] , J. Beyene [sup.1] [sup.2] , C. Ahiadeke [sup.3] [sup.4] , J. S. Hamid [sup.1] [sup.2] [sup.5] Author Affiliations: (1) grid.25073.33Department of Clinical Epidemiology and [...]

Objectives Antenatal and postnatal depression can lead to poor outcomes for women and their children. The aim of this study was to explore whether risk factors differ for depression symptoms that are present during pregnancy and/or after childbirth. Methods An ethnically and socioeconomically diverse sample of 5301 women completed interviews during the third trimester of pregnancy and 9 months after childbirth. Depression symptoms were measured using the Edinburgh Postnatal Depression Scale (EPDS). Depression symptoms (defined as EPDS >12) among participants and associations with pre-pregnancy and pregnancy maternal characteristics were explored using logistic regression. Results The rate of antenatal depression symptoms (ADS) only was 8.5, 5% of women had depression symptoms at 9 months postpartum (PDS) only and 3% experienced depression symptoms at both time points. Perceived stress and Pacific or Asian ethnicity were risk factors for ADS and PDS. Anxiety during and before pregnancy was a risk factor for ADS only while having a pre-pregnancy diagnosis of depression was a risk factor for PDS only. Having ADS increased the odds ratio of PDS by 1.5 (95% CI 1.01-2.30). Conclusions The results supported evidence from previous longitudinal studies that depression symptoms appear to be higher during pregnancy than in the first year following childbirth. The study found that PDS may often be a continuation or recurrence of ADS., Author(s): Lisa Underwood [sup.1] , Karen E. Waldie [sup.2] , Stephanie D'Souza [sup.1] [sup.2] , Elizabeth R. Peterson [sup.2] , Susan M. B. Morton [sup.1] [sup.3] Author Affiliations: (1) grid.9654.eCentre [...]

The classical Ellsberg experiment presents individuals with a choice problem in which the probability of winning a prize is unknown (uncertain). In this paper, we study how individuals make choices between gambles in which the uncertainty is in different dimensions: the winning probability, the amount of the prize, the payment date, and the combinations thereof. Although the decision-theoretic models accommodate a rich variety of behaviors, we present experimental evidence that points at systematic behavioral patterns: (i) no uncertainty is preferred to uncertainty on any single dimension and to uncertainty on multiple dimensions, and (ii) 'correlated' uncertainty on multiple dimensions is preferred to uncertainty on any single dimension. Data, as supplemental material, are available at http://dx.doi.org/10.1287/mnsc.2015.2240. Keywords: Ellsberg paradox; uncertainty aversion; multidimensional uncertainty History: Received September 23, 2014; accepted April 9, 2015, by Uri Gneezy, behavioral economics. Published online in Articles in Advance December 18, 2015., 1. Introduction When making decisions under uncertainty, we are often confronted with incomplete objective information, or uncertainty, on multiple aspects of the decision problem. The amount of monetary earnings may [...]

For a study area in the Brazilian state of Santa Catarina, the utilities of local and global forest maps in combination with poststratified and model-assisted estimators for increasing the precision of estimates of forest area were compared. Auxiliary information was in the form of local maps, the recent Global Forest Change map, and combinations of these maps. The poststratified estimators produced estimates of greater precision than the model-assisted regression estimators for maps of categorical variables, but the model assisted estimators produced estimates of greater precision for maps of continuous variables. The Global Forest Change map was the least accurate of all the maps, but it produced estimates of forest area that were similar to those for the other maps and that were more precise than if the map had not been used. Thus, the Global Forest Change map maybe an attractive option if local maps are not available or cannot be constructed. The primary contributions of the study are two-fold. First, this is one of the first case studies that rigorously assess the utility of global maps for national estimation. After accumulation of a few more such studies, broader generalizations should be forthcoming. Second, a statistical basis is provided for the previously unexplained greater precision for poststratified estimators than for model-assisted estimators. Key words: logistic regression model, inference, Santa Catarina, Brazil. Sur la base d'une zone d'etude situee dans l'Etat de Santa Catarina au Bresil, nous avons compare l'utilite de cartes du couvert forestier locales et mondiale combinees a des estimateurs stratifies a posteriori ou assistes par un modele pour augmenter la precision de l'estimation des superficies forestieres. L'information auxiliaire etait representee par les cartes locales, la carte recemment produite de 'Global Forest Change' et differentes combinaisons de ces cartes. Pour les cartes avaleurs categoriques, les estimateurs stratifies a posteriori ont produit des estimations plus precises que les estimateurs assistes par un modele de regression, mais, pour les cartes a valeurs continues, les estimateurs assistes par un modele de regression ont produit des estimations de plus grande precision que les estimateurs stratifies. La carte de 'Global Forest Change' etait la moins precise de toutes les cartes mais elle a produit des estimations de la superficie forestiere semblables a celles des autres cartes et plus precises que si seules les donnees de terrain avaient ete utilisees. Par consequent, la carte des changements du couvert forestier mondial peut etre une option interessante si les cartes locales ne sont pas disponibles ou ne peuvent etre produites. Les principales contributions de cette etude resident en deux volets. Premierement, il s'agit d'une des premieres etudes de cas qui evalue rigoureusement l'utilite des cartes mondiales pour des estimations a l'echelle nationale. Apres que d'autres etudes semblables auront ete realisees, il devrait etre possible de generaliser ce fait plus largement. Deuxiemement, nous proposons des fondements statistiques qui permettent dorenavant d'expliquer la plus grande precision des estimateurs stratifies comparativement aux estimateurs assistes par un modele. [Traduit par la Redaction] Mots-cles: modele de regression logistique, inference, Santa Catarina, Bresil., 1. Introduction 1.1. Background In the framework of the United Nations program, Reducing Emissions from Deforestation and Forest Degradation (REDD), incentive payments to developing countries for reducing forest-related greenhouse gas [...]

To describe a range of employment benefits, including maternity and other paid leave, afforded to working women with infants; and to examine the geographic, socio-demographic correlates of such benefits to inform the workplace policy agenda in the US. Using data from the Listening to Mothers II Survey, a national sample of English-speaking women who gave birth in 2005, we conducted multivariable linear and logistic regression analyses to examine the associations between socio-demographic factors and employment leave variables (paid maternity, sick and personal leave). Forty-one percent of women received paid maternity leave for an average of 3.3 weeks with 31 % wage replacement. On average women took 10 weeks of maternity leave and received 10.4 days of paid sick leave and 11.6 days of paid personal time per year. Women who were non-Hispanic Black, privately insured, working full-time, and from higher income families were more likely to receive paid maternity leave, for more time, and at higher levels of wage replacement, when controlling for the other socio-demographic characteristics. Race/ethnicity, family income and employment status were associated with the number of paid personal days. Currently, the majority of female employees with young children in the US do not receive financial compensation for maternity leave and women receive limited paid leave every year to manage health-related family issues. Further, women from disadvantaged backgrounds generally receive less generous benefits. Federal policy that supports paid leave may be one avenue to address such disparities and should be modified to reflect accepted international standards., Author(s): Megan Shepherd-Banigan [sup.1] , Janice F. Bell [sup.1] Author Affiliations: (Aff1) 0000000122986657, grid.34477.33, Department of Health Services, University of Washington, , 98195, Seattle, WA, USA Introduction The rate of [...]

Brazil is shown to have a high level of opportunity inequality by applying an inference-based nonparametric local logistic regression. Children's income distribution functions are estimated based on their fathers' wages. Through intergenerational mobility, children having fathers belonging to lower income strata are encouraged to exert greater effort to realize a certain income level.

The study aims to evaluate and identify the prematriculation and demographic factors associated with suboptimal outcomes for the cohort of US medical school matriculants between 1994 and 1999. The results indicate that factors such as lower scores on the Medical College admission Test, nonwhite race/ethnicity and premedical debt of $50000 were independently associated with dismissal or graduation without attempting passing scores on the US Medical Licensing Examination Step 1 and Step 2CK.

The study attempts to investigate the changes that have taken place in the prevalence of hearing loss in US adolescents. The results indicate that the prevalence of hearing loss among such individuals was higher during 2005 to 2006 as compared with 1988 to 1994.

The study discusses business failure prediction in China using case-based reasoning with hybrid case representation. Results show that hybrid case-based reasoning (HCBR) produces more promising prediction performance than multivariate discriminant analysis (MDA), logistic regression, classical CBR, and support vector machine.

The study aims to evaluate and compare the increased risk of respiratory morbidity in the case of late preterm births as against term births in the U.S. The results indicate that late preterm birth was associated with an increased risk of respiratory morbidity as well as respiratory distress syndrome.

This study assessed the ability of the Symptom Checklist-Revised (SCL-90-R) to discriminate between two groups of fibromyalgia patients (those who were about to begin a treatment including the explicit aim of returning to work and those who were initiating a legal procedure to obtain permanent disability compensation) and two groups of healthy volunteers (medical students and psychology graduates), who were asked to produce a symptomatic resemblance to a chronic pain disorder. Logistic regression analyses were applied to the SCL-90-R subscales and individual probabilistic indices of simulation were calculated. Results showed that the SCL-90-R was able to discriminate between healthy subjects and both groups of patients with a high sensitivity and specificity. The individual indices of simulation, which might be more useful in clinical practice than the comparison of the SCL-90-R profiles, also showed an appropriate level of accuracy. Keywords: fibromyalgia; disease prestige; simulation; stigma; healthcare decisions; symptom checklist DOI: 10.1002/jclp.20698

INTRODUCTION Open Source Software (OSS) is a new mechanism for creating and developing innovative technologies. The source code of open source software is made freely available so that users can […], Open Source Software (OSS) has gained notable importance and popularity among users in recent years. This paper uses data of more than 20,000 OSS projects over a 5-year period to investigate the determinants of Open Source Software survival. The results of logistic regressions show that OSS survival probability is positively correlated with general user interest, intensive user interest, and developer effort, but negatively correlated with the restrictiveness of license. Further investigation of the relationships among the determinants indicates that the interest of intensive users has a persistent positive impact on developer effort, while the interest of general users only has a short-term positive impact. It is also shown that projects on Software Development and System Administration have higher probability of survival than projects on other topics.

A large randomized trial was carried out to determine the association of endovascular repair of abdominal aortic aneurysm with a significantly lower operative mortality than open surgical repair. The endovascular repair was associated with increased rates of graft-related complications and reinterventions which contributed to higher overall cost.

This article introduces a new type of logistic regression model involving functional predictors of binary responses, and provides an extension of this approach to generalized linear models. The predictors are trajectories that have certain sample path properties in common with Brownian motion. Time points arc treated as parameters of interest, and confidence intervals are developed under prospective and retrospective (case-control) sampling designs. In an application to functional magnetic resonance imaging data, signals from individual subjects are used to find the portion of the time course that is most predictive of the response. This allows the identification of sensitive time points specific to a brain region and associated with a certain task, which can be used to distinguish between responses. A second application concerns gene expression data in a case-control study involving breast cancer, where the aim is to identify genetic loci along a chromosome that best discriminate between cases and controls. KEY WORDS: Brownian motion; Empirical process; Functional logistic regression; Functional magnetic resonance imaging; Gene expression; Lasso; M-estimation.

After several decades in service, the deterioration of storm-water pipe assets is inevitable. The deterioration of storm-water pipes is characterized by structural deterioration and hydraulic deterioration. Condition assessment using closed circuit television (CCTV) inspection is often carried out to assess the structural condition of pipes. However, the knowledge on the condition of storm-water pipe assets is still limited for strategic planning of maintenance and rehabilitation, because generally only a small sample is CCTV-inspected and in almost all cases, these pipes are inspected once only due to high costs. The challenge for researchers is to use the sample of CCTV-inspected pipes for developing mathematical models that can predict the structural condition of remaining pipes as well as the future condition of pipes. In this present study, the deterioration pattern of storm-water pipes is constructed on the basis that each pipe has its own deterioration rate due to its pipe factors. Based on this, two mathematical models using multiple logistic regression (MLR) and probabilistic neural networks (PNN) are developed for predicting the structural condition of individual pipes. The MLR model was calibrated using the maximum likelihood method and the PNN model was trained using a genetic algorithm (GA). The predictive performances of both models were compared using CCTV data collected for a local government authority in Melbourne, Australia. The results showed that the PNN model was more suited for modeling the structural deterioration of individual storm-water pipes than the MLR model. Furthermore, the use of GA improved the training results of the PNN model compared to the trial and error method. DOI: 10.1061/(ASCE)0733-9496(2009)135:6(553) CE Database subject headings: Storm-water management; Regression models; Probability; Neural networks; Structural failures; Deterioration.

A study was conducted to evaluate the association between enamel fluorosis and dental caries. Logistic regression analysis was used in the assessment. Findings indicate that permanent maxillary right first molars with fluorosis had lower levels of caries experience than did normal molars.