Risk Prediction for Epithelial Ovarian Cancer in 11 United States-Based Case-Control Studies: Incorporation of Epidemiologic Risk Factors and 17 Confirmed Genetic Loci.

Previously developed models for predicting absolute risk of invasive epithelial ovarian cancer have included a limited number of risk factors and have had low discriminatory power (area under the receiver operating characteristic curve (AUC) < 0.60). Because of this, we developed and internally validated a relative risk prediction model that incorporates 17 established epidemiologic risk factors and 17 genome-wide significant single nucleotide polymorphisms (SNPs) using data from 11 case-control studies in the United States (5,793 cases; 9,512 controls) from the Ovarian Cancer Association Consortium (data accrued from 1992 to 2010). We developed a hierarchical logistic regression model for predicting case-control status that included imputation of missing data. We randomly divided the data into an 80% training sample and used the remaining 20% for model evaluation. The AUC for the full model was 0.664. A reduced model without SNPs performed similarly (AUC = 0.649). Both models performed better than a baseline model that included age and study site only (AUC = 0.563). The best predictive power was obtained in the full model among women younger than 50 years of age (AUC = 0.714); however, the addition of SNPs increased the AUC the most for women older than 50 years of age (AUC = 0.638 vs. 0.616). Adapting this improved model to estimate absolute risk and evaluating it in prospective data sets is warranted.

Obesity, Cardiovascular Risk Factors, and Weight Loss in a Population of Adult Mexican Americans

The study of obesity has evolved into one of the most important public health issues in the United States (U.S.), particularly in Hispanic populations. Mexican Americans, the largest Hispanic ethnic subgroup in the U.S., have been significantly impacted by obesity and related cardiovascular diseases. Mexican Americans living in the Lower Rio Grande Valley (the Valley) in the Texas-Mexico border are one of the most disadvantaged and hard-to-reach minority groups. Demographic factors, socioeconomic status, acculturation, and physical activity behavior have been found to be important predictors of health, although research findings are mixed when establishing predictors of obesity in this population. Furthermore, while obesity has long been linked to cardiovascular disease (CVD) risk factors such as hypertension, type 2 diabetes, and dyslipidemia; information on the relationships between obesity and these CVD risk factors have been mostly from non-minority population groups. Overall, research has been mixed in establishing the association between obesity and related CVD risk factors in this population calling attention to the need for further research. Nevertheless, identifying predictors of success for weight loss in this population will be important if health disparities are to be addressed. The overall objective of the findings presented in this dissertation was to attain a more informed profile of obesity and CVD risk factors in this population. In particular, we examined predictors of obesity, measures of obesity and association with cardiovascular disease risk factors in a sample of 975 Mexican Americans participating in a health promotion program in the Valley region. Findings suggest acculturation factors to be one of the most important predictors of obesity in this population. Results also point to the need of identifying other possible risk factors for predicting CVD risk. Finally, initial body mass index is an important predictor of weight loss in this population group. Thus, indicating that this population is not only amenable to change, but that improvements in weight loss are feasible. This finding strengthens the relevance of prevention programs such as Beyond Sabor for Mexican populations at risk, in particular, food bank recipients.

The Validity of Broad and Narrow Personality Traits For Predicting Job Performance: The Differential Effects of Time

Research into the dynamicity of job performance criteria has found evidence suggesting the presence of rank-order changes to job performance scores across time as well as intraindividual trajectories in job performance scores across time. These findings have influenced a large body of research into (a) the dynamicity of validities of individual differences predictors of job performance and (b) the relationship between individual differences predictors of job performance and intraindividual trajectories of job performance. In the present dissertation, I addressed these issues within the context of the Five Factor Model of personality. The Five Factor Model is arranged hierarchically, with five broad higher-order factors subsuming a number of more narrowly tailored personality facets. Research has debated the relative merits of broad versus narrow traits for predicting job performance, but the entire body of research has addressed the issue from a static perspective -- by examining the relative magnitude of validities of global factors versus their facets. While research along these lines has been enlightening, theoretical perspectives suggest that the validities of global factors versus their facets may differ in their stability across time. Thus, research is needed to not only compare the relative magnitude of validities of global factors versus their facets at a single point in time, but also to compare the relative stability of validities of global factors versus their facets across time. Also necessary to advance cumulative knowledge concerning intraindividual performance trajectories is research into broad vs. narrow traits for predicting such trajectories. In the present dissertation, I addressed these issues using a four-year longitudinal design. The results indicated that the validities of global conscientiousness were stable across time, while the validities of conscientiousness facets were more likely to fluctuate. However, the validities of emotional stability and extraversion facets were no more likely to fluctuate across time than those of the factors. Finally, while some personality factors and facets predicted performance intercepts (i.e., performance at the first measurement occasion), my results failed to indicate a significant effect of any personality variable on performance growth. Implications for research and practice are discussed.

A novel framework for predicting patients at risk of readmission

Uncertainty in decision-making for patients’ risk of re-admission arises due to non-uniform data and lack of knowledge in health system variables. The knowledge of the impact of risk factors will provide clinicians better decision-making and in reducing the number of patients admitted to the hospital. Traditional approaches are not capable to account for the uncertain nature of risk of hospital re-admissions. More problems arise due to large amount of uncertain information. Patients can be at high, medium or low risk of re-admission, and these strata have ill-defined boundaries. We believe that our model that adapts fuzzy regression method will start a novel approach to handle uncertain data, uncertain relationships between health system variables and the risk of re-admission. Because of nature of ill-defined boundaries of risk bands, this approach does allow the clinicians to target individuals at boundaries. Targeting individuals at boundaries and providing them proper care may provide some ability to move patients from high risk to low risk band. In developing this algorithm, we aimed to help potential users to assess the patients for various risk score thresholds and avoid readmission of high risk patients with proper interventions. A model for predicting patients at high risk of re-admission will enable interventions to be targeted before costs have been incurred and health status have deteriorated. A risk score cut off level would flag patients and result in net savings where intervention costs are much higher per patient. Preventing hospital re-admissions is important for patients, and our algorithm may also impact hospital income.

Japan´s energy future: Between a return to nuclear energy and a turn to renewables

After the triple disaster of 11 March 2011, Japan is at an energy crossroad. In the short and medium run it depends on fossil fuel imports to ensure its energy security, but the long term will be determined by the decisions taken at present. For Japan energy security is a national security challenge, as stated in its National Security Strategy. The article reviews the Japanese nuclear path, studies the factors shaping the Japanese electricity market and analyzes the current energy situation. Moreover, it also assesses the principles that have marked Japan’s energy policy and the two last Strategic Energy Plans -one prior to Fukushima and the other after it- before tackling the debate on the optimal future energy mix that Japan should adopt to meet its energy security trilemma, marked by its environmental commitment.

Modelling the influence of biotic factors on species distribution patterns

Biotic interactions can have large effects on species distributions yet their role in shaping species ranges is seldom explored due to historical difficulties in incorporating biotic factors into models without a priori knowledge on interspecific interactions. Improved SDMs, which account for biotic factors and do not require a priori knowledge on species interactions, are needed to fully understand species distributions. Here, we model the influence of abiotic and biotic factors on species distribution patterns and explore the robustness of distributions under future climate change. We fit hierarchical spatial models using Integrated Nested Laplace Approximation (INLA) for lagomorph species throughout Europe and test the predictive ability of models containing only abiotic factors against models containing abiotic and biotic factors. We account for residual spatial autocorrelation using a conditional autoregressive (CAR) model. Model outputs are used to estimate areas in which abiotic and biotic factors determine species’ ranges. INLA models containing both abiotic and biotic factors had substantially better predictive ability than models containing abiotic factors only, for all but one of the four species. In models containing abiotic and biotic factors, both appeared equally important as determinants of lagomorph ranges, but the influences were spatially heterogeneous. Parts of widespread lagomorph ranges highly influenced by biotic factors will be less robust to future changes in climate, whereas parts of more localised species ranges highly influenced by the environment may be less robust to future climate. SDMs that do not explicitly include biotic factors are potentially misleading and omit a very important source of variation. For the field of species distribution modelling to advance, biotic factors must be taken into account in order to improve the reliability of predicting species distribution patterns both presently and under future climate change.

A mixed logit model for predicting exit choice during building evacuations.

Knowledge on human behaviour in emergency is crucial to increase the safety of buildings and transportation systems. Decision making during evacuations implies different choices, of which one of the most important concerns the escape route. The choice of a route may involve local decisions between alternative exits from an enclosed environment. This work investigates the influence of environmental (presence of smoke, emergency lighting and distance of exit) and social factors (interaction with evacuees close to the exits and with those near the decision-maker) on local exit choice. This goal is pursued using an online stated preference survey carried out making use of non-immersive virtual reality. A sample of 1,503 participants is obtained and a Mixed Logit Model is calibrated using these data. The model shows that presence of smoke, emergency lighting, distance of exit, number of evacuees near the exits and the decision-maker, and flow of evacuees through the exits significantly affect local exit choice. Moreover, the model points out that decision making is affected by a high degree of behavioural uncertainty. Our findings support the improvement of evacuation models and the accuracy of their results, which can assist in designing and managing building and transportation systems. The main contribution of this work is to enrich the understanding of how local exit choices are made and how behavioural uncertainty affects these choices.

Predicting Plant Performance Under Simultaneously Changing Environmental Conditions-The Interplay Between Temperature, Light, and Internode Growth

Plant performance is significantly influenced by prevailing light and temperature conditions during plant growth and development. For plants exposed to natural fluctuations in abiotic environmental conditions it is however laborious and cumbersome to experimentally assign any contribution of individual environmental factors to plant responses. This study aimed at analyzing the interplay between light, temperature and internode growth based on model approaches. We extended the light-sensitive virtual plant model L-Cucumber by implementing a common Arrhenius function for appearance rates, growth rates, and growth durations. For two greenhouse experiments, the temperature-sensitive model approach resulted in a precise prediction of cucumber mean internode lengths and number of internodes, as well as in accurately predicted patterns of individual internode lengths along the main stem. In addition, a system's analysis revealed that environmental data averaged over the experimental period were not necessarily related to internode performance. Finally, the need for a species-specific parameterization of the temperature response function and related aspects in modeling temperature effects on plant development and growth is discussed.

Environmental factors affecting soil metals near outlet roads in Poznan, Poland: impact of grain size, soil depth, and wind dispersal

We determined the Cd, Cr, Cu, Ni, Pb, and Zn concentrations in soil samples collected along the eight main outlet roads of Poznan. Samples were collected at distances of 1, 5, and 10 m from the roadway edges at depth intervals of 0-20 and 40-60 cm. The metal content was determined in seven grain size fractions. The highest metal concentrations were observed in the smallest fraction (<0.063 mm), which were up to four times higher than those in sand fractions. Soil Pb, Cu, and Zn (and to a lesser extent Ni, Cr, and Cd) all increased in relation to the geochemical background. At most sampling sites, metal concentrations decreased with increasing distance from roadway edges and increasing depth. In some locations, the accumulation of metals in soils appears to be strongly influenced by wind direction. Our survey findings should contribute in predicting the behavior of metals along outlet road, which is important by assessing sources for further migration of heavy metals into the groundwater, plants, and humans.

Prevalence and associated factors of TB/HIV co-infection among HIV Infected patients in Amhara region, Ethiopia.

Background: Tuberculosis is one of the world’s most common causes of death in the era of Human immunodeficiency virus. The purpose of this study was to determine the prevalence and associated factors of TB/HIV co-infection. Methods: Hospital based retrospective studies were conducted among adult HIV-positive patients. Logistic regression method and Chi square test were applied. Results: A total of 571 HIV positive study participants were enrolled. Of these, 158 (27.7%) were found to have pulmonary tuberculosis. Lower baseline CD4 count<200cell/μl, patients who drunk alcohol, patients who were ambulatory at the initiation of ART, patients whose marital status was single were significant predictors for increased risk of tuberculosis in PLWHIV (P <0.05). Non smoker patients, patients in WHO clinical stage I, patients in WHO clinical stage II and ownership of the house had significant protective benefit against risk of TB (P <0.05). Conclusion: The prevalence of TB/HIV co-infection in adults on ART in our study was moderately high. Having advanced clinical status and presence of risk factors were found to be the predicting factors for co-infection. The health office should open TB/HIV co-infection units in the hospitals and health workers should be cautious when a patient has an advanced disease.

Ratios and indicators that determine return on equity

This study aims to investigate factors that may affect return on equity (ROE). The ROE is a gauge of profit generating efficiency and a strong measure of how well the management of a firm creates value for its shareholders. Firms with higher ROE typically have competitive advantages over their competitors which translates into superior returns for investors. Therefore, seems imperative to study the drivers of ROE, particularly ratios and indicators that may have considerable impact. The analysis is done on a sample of 90 largest non-financial companies which are components of NASDAQ-100 index and also on industry sector samples. The ordinary least squares method is used to find the most impactful drivers of ROE. The extended DuPont model’s components are considered as the primary factors affecting ROE. In addition, other ratios and indicators such as price to earnings, price to book and current are also incorporated. Consequently, the study uses eight ratios that are believed to have impact on ROE. According to our findings, the most relevant ratios that determine ROE are tax burden, interest burden, operating margin, asset turnover and financial leverage (extended DuPont components) regardless of industry sectors.

Connecting the dots: Examining the role of parental beliefs and preschoolers’ affect and engagement in predicting parent-child number exploration during a meaningful math experience

The current study examined the frequency and quality of how 3- to 4-year-old children and their parents explore the relations between symbolic and non-symbolic quantities in the context of a playful math experience, as well as the role of both parent and child factors in this exploration. Preschool children’s numerical knowledge was assessed while parents completed a survey about the number-related experiences they share with their children at home, and their math-related beliefs. Parent-child dyads were then videotaped playing a modified version of the card game War. Results suggest that parents and children explored quantity explicitly on only half of the cards and card pairs played, and dyads of young children and those with lower number knowledge tended to be most explicit in their quantity exploration. Dyads with older children, on the other hand, often completed their turns without discussing the numbers at all, likely because they were knowledgeable enough about numbers that they could move through the game with ease. However, when dyads did explore the quantities explicitly, they focused on identifying numbers symbolically, used non-symbolic card information interchangeably with symbolic information to make the quantity comparison judgments, and in some instances, emphasized the connection between the symbolic and non-symbolic number representations on the cards. Parents reported that math experiences such as card game play and quantity comparison occurred relatively infrequently at home compared to activities geared towards more foundational practice of number, such as counting out loud and naming numbers. However, parental beliefs were important in predicting both the frequency of at-home math engagement as well as the quality of these experiences. In particular, parents’ specific beliefs about their children’s abilities and interests were associated with the frequency of home math activities, while parents’ math-related ability beliefs and values along with children’s engagement in the card game were associated with the quality of dyads’ number exploration during the card game. Taken together, these findings suggest that card games can be an engaging context for parent-preschooler exploration of numbers in multiple representations, and suggests that parents’ beliefs and children’s level of engagement are important predictors of this exploration.

Lower Aptian Comparative Stratigraphy of the Basco-Cantabrian Region (Spain) and Eastern Cordillera (Colombia): implications for local factors in the depositional record of Oceanic Anoxic Event 1a (OAE-1a)

An important episode of carbon sequestration, Oceanic Anoxic Event 1a (OAE-1a), characterizes the Lower Aptian worldwide, and is mostly known from deeper-water settings. The present work of two Lower Aptian deposits, Madotz (N Spain) and Curití Quarry (Colombia), is a multiproxy study that includes fossil assemblages, microfacies, X-ray diffraction bulk and clay mineralogy, elemental analyses (major, minor, trace elements), Rock-Eval pyrolysis, biomarkers, inorganic and organic carbon content, and stable carbon isotopes. The results provide baseline evidence of the local and global controlling environmental factors influencing OAE-1a in shallow-water settings. The data also improve our general understanding of the conditions under which organic-carbon-rich deposits accumulate. The sequence at Madotz includes four intervals (Unit 1; Subunits 2a, 2b and 2c) that overlap the times prior to, during and after the occurrence of OAE-1a. The Lower Unit 1(3m thick) is essentially siliciclastic, and Subunit 2a (20m) contains Urgonian carbonate facies that document abruptly changing platform conditions prior to OAE-1a. Subunit 2b (24.4 m) is a mixed carbonate-siliciclastic facies with orbitolinid-rich levels that coincides with OAE-1a δ13C stages C4-C6, and is coeval with the upper part of the Deshayesites forbesi ammonite zone. Levels with pyrite and the highest TOC values (0.4-0.97%), interpreted as accumulating under suboxic conditions, and are restricted to δ13C stages C4 and C5. The best development of the suboxic facies is at the level representing the peak of the transgression. Subunit 2c, within δ13C stage C7, shows a return of the Urgonian facies. The 23.35-m section at Curití includes a 6.3-m interval at the base of the Paja Formation dominated by organic-rich marlstones and shales lacking benthic fossils and bioturbation, with TOC values as high as 8.84%. The interval overlies a level containing reworked and phosphatized assemblages of middle Barremian to lowest Aptian ammonites. The range of values and the overall pattern of the δ13Corg (-22.05‰ to -20.47‰) in the 6.3m-interval is comparable with Lower Aptian δ13C stage C7. Thus, conditions of oxygen depletion at this site also occurred after Oceanic Anoxic Event-1a, which developed between carbon isotope stages C3 and C6. Both sites, Madotz and Curití, attest to the importance of terrigenous and nutrient fluxes in increasing OM productivity that led to episodic oxygen deficiency.

Health beliefs affect the correct replacement of daily disposable contact lenses:predicting compliance with the Health Belief Model and the Theory of Planned Behaviour

Purpose: To assess the compliance of Daily Disposable Contact Lenses (DDCLs) wearers with replacing lenses at a manufacturer-recommended replacement frequency. To evaluate the ability of two different Health Behavioural Theories (HBT), The Health Belief Model (HBM) and The Theory of Planned Behaviour (TPB), in predicting compliance. Method: A multi-centre survey was conducted using a questionnaire completed anonymously by contact lens wearers during the purchase of DDCLs. Results: Three hundred and fifty-four questionnaires were returned. The survey comprised 58.5% females and 41.5% males (mean age 34. ±. 12. years). Twenty-three percent of respondents were non-compliant with manufacturer-recommended replacement frequency (re-using DDCLs at least once). The main reason for re-using DDCLs was "to save money" (35%). Predictions of compliance behaviour (past behaviour or future intentions) on the basis of the two HBT was investigated through logistic regression analysis: both TPB factors (subjective norms and perceived behavioural control) were significant (p. <. 0.01); HBM was less predictive with only the severity (past behaviour and future intentions) and perceived benefit (only for past behaviour) as significant factors (p. <. 0.05). Conclusions: Non-compliance with DDCLs replacement is widespread, affecting 1 out of 4 Italian wearers. Results from the TPB model show that the involvement of persons socially close to the wearers (subjective norms) and the improvement of the procedure of behavioural control of daily replacement (behavioural control) are of paramount importance in improving compliance. With reference to the HBM, it is important to warn DDCLs wearers of the severity of a contact-lens-related eye infection, and to underline the possibility of its prevention.

Recent advances in explaining hedge fund returns:implicit factors and exposures

We survey articles covering how hedge fund returns are explained, using largely non-linear multifactor models that examine the non-linear pay-offs and exposures of hedge funds. We provide an integrated view of the implicit factor and statistical factor models that are largely able to explain the hedge fund return-generating process. We present their evolution through time by discussing pioneering studies that made a significant contribution to knowledge, and also recent innovative studies that examine hedge fund exposures using advanced econometric methods. This is the first review that analyzes very recent studies that explain a large part of hedge fund variation. We conclude by presenting some gaps for future research.