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Detecting epistatic drivers of human phenotypes is a considerable challenge. Traditional approaches use regression to sequentially test multiplicative interaction terms involving pairs of genetic variants. For higher-order interactions and genome-wide large-scale data, this strategy is computationally intractable. Moreover, multiplicative terms used in regression modeling may not capture the form of biological interactions. Building on the Predictability, Computability, Stability (PCS) framework, we introduce the epiTree pipeline to extract higher-order interactions from genomic data using tree-based models. The epiTree pipeline first selects a set of variants derived from tissue-specific estimates of gene expression. Next, it uses iterative random forests (iRF) to search training data for candidate Boolean interactions (pairwise and higher-order). We derive significance tests for interactions, based on a stabilized likelihood ratio test, by simulating Boolean tree-structured null (no epistasis) and alternative (epistasis) distributions on hold-out test data. Finally, our pipeline computes PCS epistasis p-values that probabilisticly quantify improvement in prediction accuracy via bootstrap sampling on the test set. We validate the epiTree pipeline in two case studies using data from the UK Biobank: predicting red hair and multiple sclerosis (MS). In the case of predicting red hair, epiTree recovers known epistatic interactions surrounding MC1R and novel interactions, representing non-linearities not captured by logistic regression models. In the case of predicting MS, a more complex phenotype than red hair, epiTree rankings prioritize novel interactions surrounding HLA-DRB1, a variant previously associated with MS in several populations. Taken together, these results highlight the potential for epiTree rankings to help reduce the design space for follow up experiments. [ABSTRACT FROM AUTHOR]

Objective: This study explores the contribution of nutrition knowledge to the health status of pre-school children's mothers in Niger State, North-Central, Nigeria. Design: The study is a descriptive cross-sectional design using a quantitative data collection method. Setting/participants: A multi-stage sampling technique was used to recruit 450 mothers of pre-school children across Niger state, Nigeria. Chi-square and linear regression were used to test the level of statistical significance (at p < 0.05). Socioeconomic and demographic information, anthropometric indices and nutrition knowledge were obtained using semi-structured questionnaires. Feeding patterns were also assessed using a qualitative 7-day dietary recall. Result: The results showed that the majority (63.8%) of the mothers were within 26–35 years, and more than half (51.6%) of the mothers lacked knowledge of a "balanced diet". Fruits, vegetables, and dairy products were the least consumed food group among the mothers (7.1% and 9.1%, respectively). Place of residence, occupation, and method of waste disposal were significantly associated with maternal minimum dietary diversity adequacy (p<0.05). Over half (57.6%) of the mothers were within the normal BMI range, and the mean waist/hip ratio was 0.82± 0.08. Social media/online was the most (36.4%) explored source of nutrition information among the mothers. This study shows no significant association between nutrition knowledge and adequacy of minimum dietary diversity among the mothers of preschool children (p = 0.09, χ2 = 13.682). Conclusion: Dietary diversity among mothers was associated with the socioeconomic status and BMI of the mothers, which were strong determinants of meal quality and health outcomes in Nigeria and other developing countries experiencing food insecurity. [ABSTRACT FROM AUTHOR]

Hikers and hillwalkers typically use the gradient in the direction of travel (walking slope) as the main variable in established methods for predicting walking time (via the walking speed) along a route. Research into fell-running has suggested further variables which may improve speed algorithms in this context; the gradient of the terrain (hill slope) and the level of terrain obstruction. Recent improvements in data availability, as well as widespread use of GPS tracking now make it possible to explore these variables in a walking speed model at a sufficient scale to test statistical significance. We tested various established models used to predict walking speed against public GPS data from almost 88,000 km of UK walking / hiking tracks. Tracks were filtered to remove breaks and non-walking sections. A new generalised linear model (GLM) was then used to predict walking speeds. Key differences between the GLM and established rules were that the GLM considered the gradient of the terrain (hill slope) irrespective of walking slope, as well as the terrain type and level of terrain obstruction in off-road travel. All of these factors were shown to be highly significant, and this is supported by a lower root-mean-square-error compared to existing functions. We also observed an increase in RMSE between the GLM and established methods as hill slope increases, further supporting the importance of this variable. [ABSTRACT FROM AUTHOR]

In order to develop a statistical model for complex interactions among factors affecting early childhood caries development (ECC), 234 children from the "XXXX oral growth longitudinal study" were analysed at ages 3, 4 and 5. A questionnaire for children's parents (clinical history, nutritional and oral hygiene habits) and clinical oral examinations were recorded each year. The probabilistic dependence structure on the most significant factors was modelled with an Undirected Graphical Model (UGM or Markov random fields) which provides a probabilistic reasoning approach for the establishment of multi-way associations. The best fitting UGM was estimated through the maximum likelihood principle and two-way factor associations were verified through Fisher's exact statistical hypothesis tests for count data. The effect of sugar intake on caries incidence is mediated by oral hygiene; for caries incidence, oral hygiene quality is more relevant than toothbrushing time; the effect of pacifier on caries incidence is statistically significant only when considered in combination with breastfeeding time. Among behavioural ECC risk factors, the quality of oral hygiene, and not the toothbrushing frequency, is a primary factor that modulates the sugar intake in his primary role of the ECC developer. School-based oral health programs for ECC prevention should be improved with supervised toothbrushing program. UGM analysis could improve the school-based oral health programs with more effective and efficient prevention strategies based on the hierarchical interactions among the ECC risk factors. Oral hygiene plays a pivotal role in early childhood caries and can modulate positively or negatively their development. Supervised toothbrushing is a crucial intervention to be included in the daily educational and clinical practice and in the school-based oral health promotion programs. Trial registration: Clinical trial registration number: NCT02798809. [ABSTRACT FROM AUTHOR]

When the in/consistency in Pairwise Comparisons (PCs) is taken into consideration as the subarea of the Multi Attribute Decision Making (MADM) scientific field, it has many repercussions in various types of research areas including different modelling scenarios e.g. reduction of inconsistency during PCs, deriving appropriate consistency thresholds for inconsistent Pairwise Comparison Matrices (PCMs), completing of incomplete PCMs, aggregating of individual PCMs in relation to Group Decision Making (GDM) aspects, and PCMs in/consistency relation to credibility of Priority Vectors (PV) derived from PCMs with the application of various Priorities Deriving Methods (PDMs). The examination objective in the latter area of research is the uncertainty related to the inexactitude of prioritization based on derived PVs. However, only few research studies examine this problem from the perspective of PCM applicability for credible designation of decision maker's (DM) priorities in the way that leads to minimization of the prioritization uncertainty related to possible, and sometimes very probable, ranking fluctuations. This problem constitutes the primary area of interest for this research paper as no research study was thus far identified that examines this problem from the perspective of consistent PCMs. Hence, a research gap was identified. Thus, the objective of this research paper is to fill in this scientific gap. The research findings have serious repercussions in relation to prioritization quality with the application of PCs methodology, mostly in relation to the interpretation and reliability evaluation of prioritization results. Firstly, the research study outcome changes the perspective of the rank reversal phenomenon, which shed new light on many research studies that have been presented in the subject's literature for many decades. Secondly, the research study results throw new light on the discussion concerning the fuzziness of AHP's results. Last but not least, the effect of the research opens the unique opportunity to evaluate the prioritization outcome obtained within the process of consistent PCs from the well-known perspective of statistical hypothesis testing i.e. the probability designation of the chance that accepted ranking results which were considered as correct due to low probability of change may be incorrect, hence they should be rejected, and the probability designation of the chance that rejected ranking results which were considered as incorrect due to high probability of change may be correct and should be accepted. The paramount finding of the research is the fact that consistent PCMs provide PVs, which elements cannot be considered as established, but only approximated within certain confidence intervals estimated with a certain level of probability. As problems related to heuristics can be analyzed only via a computer simulation process, because they cannot be mathematically determined, the problem examined in this research paper is examined via Monte Carlo simulations, appropriately coded and executed with the application of Wolfram's Mathematica Software. It is believed that this research findings should be very important and useful for all decision makers and researchers during their problems' examinations that relate to prioritization processes with the application of PCs methodology. [ABSTRACT FROM AUTHOR]

Background: Composite multidimensional indices are broadly used to measure child poverty and social exclusion. Many of such indices are based on EU-SILC data or similar large scale complex sampling surveys, with the household as unit of analysis. Indicators related to households with or without children may quantify the intended attribute differently depending on the household structure and characteristics of individuals, potentially compromising the assessment. Methods: We conducted statistical modelling and hypotheses tests using a two-parameter logistic item response model (IRM) and the likelihood-ratio test for DIF verification. Methods were applied to 2020 EU-SILC Portuguese data comprising 11,367 households representing a population of 4,099,052. Statistical analysis have allowed for the survey sampling design. Conclusion: Our findings demonstrate differential item functioning in the assessment material deprivation in households with or without children. [ABSTRACT FROM AUTHOR]

Mapper, a topological algorithm, is frequently used as an exploratory tool to build a graphical representation of data. This representation can help to gain a better understanding of the intrinsic shape of high-dimensional genomic data and to retain information that may be lost using standard dimension-reduction algorithms. We propose a novel workflow to process and analyze RNA-seq data from tumor and healthy subjects integrating Mapper, differential gene expression, and spectral shape analysis. Precisely, we show that a Gaussian mixture approximation method can be used to produce graphical structures that successfully separate tumor and healthy subjects, and produce two subgroups of tumor subjects. A further analysis using DESeq2, a popular tool for the detection of differentially expressed genes, shows that these two subgroups of tumor cells bear two distinct gene regulations, suggesting two discrete paths for forming lung cancer, which could not be highlighted by other popular clustering methods, including t-distributed stochastic neighbor embedding (t-SNE). Although Mapper shows promise in analyzing high-dimensional data, tools to statistically analyze Mapper graphical structures are limited in the existing literature. In this paper, we develop a scoring method using heat kernel signatures that provides an empirical setting for statistical inferences such as hypothesis testing, sensitivity analysis, and correlation analysis. [ABSTRACT FROM AUTHOR]

To determine the relevance of morphometric properties attributed to the meat yield and fatness index of the saltwater hard clam Meretrix meretrix. A new strain of M. meretrix with red shell color was produced after five generations of selection within a family of full-sibs. 7 morphometric traits, including shell length (SL), shell height (SH), shell width (SW), ligament length (LL), projection length (PL), projection width (PW), and live body weight (LW), and 2 meat characteristics, including meat yield (MY) and fatness index (FI) were measured from 50 individuals of three-year-old M. meretrix. The correlation coefficients, path coefficients, determination coefficients among attributes were analyzed. The results indicated that correlation achieved very significant levels (P<0.01). In addition, the multiple regression equations were formulated by considering the meat yield and fatness index as the dependent variables, respectively, and 7 other morphometric traits as independent variables. The correlation indices (R2) of morphometric traits against the meat yield and fatness index of clams were 0.901 and 0,929, respectively, indicating that the live body weight and shell length were the common main factors influencing the meat characteristics. By testing the significance of partial regression coefficient and gradually removing the non-significant morphometric traits, a multiple regression equation was established to estimate the relationship between shell length (SL, mm), live body weight (LW, g), ligament length (LL, mm) and meat yield (MY, %), fat index (FI, %): MY (%) = 0.432SL+0.251LW and FI (%) = 0.156SL+0.067LL+0.42LW-3.533. The study draws a conclusion that live body weight and shell length have a predominant direct effect on the meat yield and fatness index, which provides theoretical information for the breeding of M. meretrix. [ABSTRACT FROM AUTHOR]

Introduction: Few studies including contradictory results have addressed the acute effects of the 11+ on motor performance, indicating a potentially reduced applicability of the program for warming up before competitions. This study aims to compare the acute effects of a soccer-specific warm-up (Football+) and the 11+ on motor performance. Materials and methods: Thirty-eight volunteer collegiate players (22 males; age = 21.1±1.9 years, height = 1.81± 0.06 m, weight = 73.4± 9.5 kg; 16 females; age = 21.3±1.5 years; height = 1.71± 0.07 m, weight = 67.8± 8.5 kg) underwent the 11+ and the Football+ in a randomized crossover design with a one-week washout. The Football+ starts with a self-estimated 40–50 percent running, followed by dynamic stretching of the hip muscles, shoulder contact, controlled lunge, Copenhagen exercise, and modified Nordic hamstring exercise. The second part involves roughly intensive small-sided games, followed by plyometric and anaerobic exercises in the third part. The warm ups' effects on performance were determined by a linear sprinting test (20 m), countermovement jump performance (CMJ), Illinois agility (IA), and dribbling speed (DS) tests. Within-subject differences were reported as the means and SD. Pairwise t tests at the significance level of p<0.05 were used to calculate the significant differences. Results: Overall, except for the CMJ (mean = -0.43±3.20 cm, p = 0.21, d = -0.13), significant differences for the 20 m sprint (mean = 0.04±0.10 s, p = 0.005, d = 0.42), IA (mean = 0.65±0.45 s, p = 0.01, d = 1.43), and DS (mean = 0.60±1.58 s, p = 0.012, d = 0.38) were observed. In females, significant differences observed only for IA (mean difference = 0.52±0.42 s, p<0.001, d = 1.24) and DS (mean difference = 1.29±1,77 s, p = 0.005, d = 0.73), with the Football+ showing superiority. In males, significant differences were found only for 20 m sprinting (mean difference = 0.06±0.09, p = 0.005, d = 0.60) and IA (mean difference = 0.74±0.46, p<0.001, d = 1.62), with the Football+ having superiority. Discussion: Although practicable for injury prevention, the 11+ may not optimize acute performance and prepare players for high-intensity physical tasks as well as a well-structured, roughly intensive warm-up. Further gender-specific studies should evaluate the long-term effects of the Football+ on performance and injury prevention. [ABSTRACT FROM AUTHOR]

Diagnostic screening models for the interpretation of null hypothesis significance test (NHST) results have been influential in highlighting the effect of selective publication on the reproducibility of the published literature, leading to John Ioannidis' much-cited claim that most published research findings are false. These models, however, are typically based on the assumption that hypotheses are dichotomously true or false, without considering that effect sizes for different hypotheses are not the same. To address this limitation, we develop a simulation model that overcomes this by modeling effect sizes explicitly using different continuous distributions, while retaining other aspects of previous models such as publication bias and the pursuit of statistical significance. Our results show that the combination of selective publication, bias, low statistical power and unlikely hypotheses consistently leads to high proportions of false positives, irrespective of the effect size distribution assumed. Using continuous effect sizes also allows us to evaluate the degree of effect size overestimation and prevalence of estimates with the wrong sign in the literature, showing that the same factors that drive false-positive results also lead to errors in estimating effect size direction and magnitude. Nevertheless, the relative influence of these factors on different metrics varies depending on the distribution assumed for effect sizes. The model is made available as an R ShinyApp interface, allowing one to explore features of the literature in various scenarios. [ABSTRACT FROM AUTHOR]

In the case of comparing means of various groups, data exploration and comparison for affecting factors or relative indices would be involved. This process is not only complex requiring extensive statistical knowledge and methods, but also challenging for the complex installation of existing tools for users who lack of statistical knowledge and coding experience. Like, the normal distribution and equal variance are crucial premises of parametric statistical analysis. But some studies reported that associated data from various industries violated the normal distribution and equal variance, parametric analysis still involved leading to invalid results. This is owing to that the normal distribution tests and homogeneity of variance test for different variables are time-cost and error-prone, posing an urgent need for an automatic and user-friendly analysis application, not only integrating normal distribution tests and homogeneity of variance test, but also associated the following statistical analysis. To address this, we developed a Shiny/R application, moreThanANOVA, which is an interactive, user-friendly, open-source and cloud-based visualization application to achieve automatic distribution tests, and correlative significance tests, then customize post-hoc analysis based on the considerations to the trade-off of Type I and Type II errors (deployed at https://hanchen.shinyapps.io/moreThanANOVA/). moreThanANOVA enables novice users to perform their complex statistical analyses quickly and credibly with interactive visualization and download publication-ready graphs for further analysis. [ABSTRACT FROM AUTHOR]

The event related P300 potentials, positive waveforms in electroencephalography (EEG) signals, are often utilized in brain computer interfaces (BCI). Many studies have been carried out to improve the performance of P300 speller systems either by developing signal processing algorithms and classifiers with different architectures or by designing new paradigms. In this study, a new paradigm is proposed for this purpose. The proposed paradigm combines two remarkable properties of being a 3D animation and utilizing column-only flashings as opposed to classical paradigms which are based on row-column flashings in 2D manner. The new paradigm is utilized in a traditional two-layer artificial neural networks model with a single output neuron, and numerous experiments are conducted to evaluate and compare the performance of the proposed paradigm with that of the classical approach. The experimental results, including statistical significance tests, are presented for single and multiple EEG electrode usage combinations in 1, 3 and 15 flashing repetitions to detect P300 waves as well as to recognize target characters. Using the proposed paradigm, the best average classification accuracy rates on the test data are improved from 89.97% to 93.90% (an improvement of 4.36%) for 1 flashing, from 97.11% to 98.10% (an improvement of 1.01%) for 3 flashings and from 99.70% to 99.81% (an improvement of 0.11%) for 15 flashings when all electrodes, included in the study, are utilized. On the other hand, the accuracy rates are improved by 9.69% for 1 flashing, 4.72% for 3 flashings and 1.73% for 15 flashings when the proposed paradigm is utilized with a single EEG electrode (P8). It is observed that the proposed speller paradigm is especially useful in BCI systems designed for few EEG electrodes usage, and hence, it is more suitable for practical implementations. Moreover, all participants, given a subjective test, declared that the proposed paradigm is more user-friendly than classical ones. [ABSTRACT FROM AUTHOR]

Cervical cancer remains one of the top causes of cancer-related morbidity and mortality all over the world. Currently, however, there are no published studies to assess the knowledge of HPV and cervical cancer in Kazakhstan. This study aimed to assess the awareness of HPV, the knowledge of HPV as a cause of cervical cancer, and the awareness of HPV vaccination among Kazakhstani women visiting gynecological clinics across the country. In addition, the study aimed to identify the factors associated with the awareness of HPV and the HPV vaccine and knowledge of HPV as a major cause of cervical cancer. This was a cross-sectional survey-based study with 2,272 women aged between 18–70 years attending gynecological clinics, who were administered paper-based questionnaires. Data analysis included descriptive statistics consisting of mean values, standard deviations, and frequencies, where applicable. Differences in categorical variables between groups were analyzed using the Chi-square test with a significance value of <0.005. Crude odds ratio (OR) and adjusted odds ratio (AOR) with 95% corresponding confidence intervals were calculated in regression analysis using univariate and multivariable logistic regression models. The mean age of participants was 36.33±10.09 years. More than half (53%) of the participants had been screened for cervical cancer. Among those who were aware of HPV, 46% knew that HPV causes cervical cancer and 52% were aware of the HPV vaccine. The key factors related to outcome variables were age, ethnicity, education, family, number of deliveries, and menarche. From a subgroup analysis, results from the HPV test and Pap smear test were factors related to dependent variables such as awareness of HPV and awareness of HPV vaccination. [ABSTRACT FROM AUTHOR]

Background: Null Hypothesis Significance Testing (NHST) is the most familiar statistical procedure for making inferences about population effects. Important problems associated with this method have been addressed and various alternatives that overcome these problems have been developed. Despite its many well-documented drawbacks, NHST remains the prevailing method for drawing conclusions from data. Reasons for this have been insufficiently investigated. Therefore, the aim of our study was to explore the perceived barriers and facilitators related to the use of NHST and alternative statistical procedures among relevant stakeholders in the scientific system. Methods: Individual semi-structured interviews and focus groups were conducted with junior and senior researchers, lecturers in statistics, editors of scientific journals and program leaders of funding agencies. During the focus groups, important themes that emerged from the interviews were discussed. Data analysis was performed using the constant comparison method, allowing emerging (sub)themes to be fully explored. A theory substantiating the prevailing use of NHST was developed based on the main themes and subthemes we identified. Results: Twenty-nine interviews and six focus groups were conducted. Several interrelated facilitators and barriers associated with the use of NHST and alternative statistical procedures were identified. These factors were subsumed under three main themes: the scientific climate, scientific duty, and reactivity. As a result of the factors, most participants feel dependent in their actions upon others, have become reactive, and await action and initiatives from others. This may explain why NHST is still the standard and ubiquitously used by almost everyone involved. Conclusion: Our findings demonstrate how perceived barriers to shift away from NHST set a high threshold for actual behavioral change and create a circle of interdependency between stakeholders. By taking small steps it should be possible to decrease the scientific community's strong dependence on NHST and p-values. [ABSTRACT FROM AUTHOR]

In a balanced design, researchers allocate the same number of units across all treatment groups. It has been believed as a rule of thumb among some researchers in agriculture. Sometimes, an unbalanced design outperforms a balanced design. Given a specific parameter of interest, researchers can design an experiment by unevenly distributing experimental units to increase statistical information about the parameter of interest. An additional way of improving an experiment is an adaptive design (e.g., spending the total sample size in multiple steps). It is helpful to have some knowledge about the parameter of interest to design an experiment. In the initial phase of an experiment, a researcher may spend a portion of the total sample size to learn about the parameter of interest. In the later phase, the remaining portion of the sample size can be distributed in order to gain more information about the parameter of interest. Though such ideas have existed in statistical literature, they have not been applied broadly in agricultural studies. In this article, we used simulations to demonstrate the superiority of the experimental designs over the balanced designs under three practical situations: comparing two groups, studying a dose-response relationship with right-censored data, and studying a synergetic effect of two treatments. The simulations showed that an objective-specific design provides smaller error in parameter estimation and higher statistical power in hypothesis testing when compared to a balanced design. We also conducted an adaptive experimental design applied to a dose-response study with right-censored data to quantify the effect of ethanol on weed control. Retrospective simulations supported the benefit of this adaptive design as well. All researchers face different practical situations, and appropriate experimental designs will help utilize available resources efficiently. [ABSTRACT FROM AUTHOR]

The significant resource investment in research on ecosystems for development of the Global South does not necessarily result in high levels of research knowledge utilisation (RKU). Understanding the factors associated with various levels of RKU can inform funding agencies and researchers developing new projects. We applied a combination of a questionnaire survey and follow up interviews with members of research teams of multiple, broadly comparable projects to make an assessment of achieved RKU levels using a combination of quantitative statistical hypothesis testing and narrative description of survey responses. Research knowledge dissemination by members of the project team who work for non-academic institutions or champions, e.g. particularly motivated people that promote and facilitate implementation or adoption of the project results, and via television was associated with higher research knowledge utilization. By contrast, dissemination by members of the project team working for academic institutions and via peer-reviewed journals was associated with lower RKU. The achieved level of RKU was consistently lower than the targeted level of RKU across spatial scales. The discrepancy between the perceived level of RKU and the evidence provided by survey respondents indicates the need for better monitoring the utilisation of research knowledge in development pathways. Our results further suggest that three years project duration is too short to achieve high levels of RKU in socio-ecological systems. We recommend involvement of non-academic members of the project team in project design, leadership and dissemination for increasing RKU. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has become a long-term crisis that calls for long-term solutions. We combined an augmented SEIR simulation model with real-time human mobility data to decompose the effects of lockdown, travel bans and effective testing measures in the curtailment of COVID-19 spread in China over different time horizons. Our analysis reveals that the significant growth in the detection rate of infectious cases, thanks to the expansion in testing efficiency, were as effective as city lockdowns in explaining the reduction in new infections up to mid-March. However, as we extended the analysis to July, increasing the detection rate to at least 50% is the only reliable way to bring the spread under control. [ABSTRACT FROM AUTHOR]

Many affective computing studies have developed automatic emotion recognition models, mostly using emotional images, audio and videos. In recent years, virtual reality (VR) has been also used as a method to elicit emotions in laboratory environments. However, there is still a need to analyse the validity of VR in order to extrapolate the results it produces and to assess the similarities and differences in physiological responses provoked by real and virtual environments. We investigated the cardiovascular oscillations of 60 participants during a free exploration of a real museum and its virtualisation viewed through a head-mounted display. The differences between the heart rate variability features in the high and low arousal stimuli conditions were analysed through statistical hypothesis testing; and automatic arousal recognition models were developed across the real and the virtual conditions using a support vector machine algorithm with recursive feature selection. The subjects' self-assessments suggested that both museums elicited low and high arousal levels. In addition, the real museum showed differences in terms of cardiovascular responses, differences in vagal activity, while arousal recognition reached 72.92% accuracy. However, we did not find the same arousal-based autonomic nervous system change pattern during the virtual museum exploration. The results showed that, while the direct virtualisation of a real environment might be self-reported as evoking psychological arousal, it does not necessarily evoke the same cardiovascular changes as a real arousing elicitation. These contribute to the understanding of the use of VR in emotion recognition research; future research is needed to study arousal and emotion elicitation in immersive VR. [ABSTRACT FROM AUTHOR]

Understanding the dynamics by which urban areas attract visitors is important in today's cities that are continuously increasing in population towards higher densities. Identifying services that relate to highly attractive districts is useful to make policies regarding the placement of such places. Thus, we present a framework for classifying districts in cities by their attractiveness to daily commuters and relating Points of Interests (POIs) types to districts' attraction patterns. We used Origin-Destination matrices (ODs) mined from cell phone data that capture the flow of trips between each pair of places in Riyadh, Saudi Arabia. We define the attraction profile for a place based on three main statistical features: The number of visitors a place received, the distribution of distance traveled by visitors on the road network, and the spatial spread of locations from where trips started. We used a hierarchical clustering algorithm to classify all places in the city by their features of attraction. We discovered three main types of Urban Attractors in Riyadh during the morning period: Global, which are significant places in the city, Downtown, which contains the central business district, and Residential attractors. In addition, we uncovered what makes districts possess certain attraction patterns. We used a statistical significance testing approach to quantify the relationship between Points of Interests (POIs) types (services) and the patterns of Urban Attractors detected. [ABSTRACT FROM AUTHOR]

One-to-multiple path analysis model describes the regulation mechanism of multiple independent variables to one dependent variable by dividing the correlation coefficient and the determination coefficient. How to analyse more complex regulation mechanisms of multiple independent variables to multiple dependent variables? Similarly, according to multiple-to-multiple linear regression analysis, multiple-to-multiple path analysis model was proposed in this paper and it demonstrated more complex regulation mechanisms among multiple independent variables and multiple dependent variables by dividing the generalized determination coefficient. Differently, three other types of paths were generated in multiple-to-multiple path analysis model in that the correlation among multiple dependent variables was considered. Then, the decision coefficient of each independent variable was constructed for dependent variables system, and its hypothesis testing statistics were given. Finally, the research example of the wheat breeding rules in arid area demonstrated that the multiple-to-multiple path analysis considering more correlation information can get better results. [ABSTRACT FROM AUTHOR]

Feature selection on high dimensional data along with the interaction effects is a critical challenge for classical statistical learning techniques. Existing feature selection algorithms such as random LASSO leverages LASSO capability to handle high dimensional data. However, the technique has two main limitations, namely the inability to consider interaction terms and the lack of a statistical test for determining the significance of selected features. This study proposes a High Dimensional Selection with Interactions (HDSI) algorithm, a new feature selection method, which can handle high-dimensional data, incorporate interaction terms, provide the statistical inferences of selected features and leverage the capability of existing classical statistical techniques. The method allows the application of any statistical technique like LASSO and subset selection on multiple bootstrapped samples; each contains randomly selected features. Each bootstrap data incorporates interaction terms for the randomly sampled features. The selected features from each model are pooled and their statistical significance is determined. The selected statistically significant features are used as the final output of the approach, whose final coefficients are estimated using appropriate statistical techniques. The performance of HDSI is evaluated using both simulated data and real studies. In general, HDSI outperforms the commonly used algorithms such as LASSO, subset selection, adaptive LASSO, random LASSO and group LASSO. [ABSTRACT FROM AUTHOR]

Introduction: Hypertension is a major public health problem globally and it is a leading cause of death and disability in developing countries. This review aims to estimate the pooled prevalence of hypertension and its determinants in Ethiopia. Methods: A systematic literature search was conducted at the electronic databases (PubMed, Hinari, and Google Scholar) to locate potential studies. Heterogeneity between studies checked using Cochrane Q test statistics and I2 test statistics and small study effect were checked using Egger's statistical test at 5% significance level. Sensitivity analysis was checked. A random-effects model was employed to estimate the pooled prevalence of hypertension and its determinants in Ethiopia. Results: In this review, 38 studies that are conducted in Ethiopia and fulfilled the inclusion criteria with a total number of 51,427 study participants were reviewed. The overall pooled prevalence of hypertension in the country was 21.81% (95% CI: 19.20–24.42, I2 = 98.35%). The result of the review also showed that the point of prevalence was higher among males (23.21%) than females (19.62%). When we see the pervasiveness of hypertension from provincial perspective; the highest prevalence of hypertension was observed in Addis Ababa (25.35%) and the lowest was in Tigray region (15.36%). In meta-regression analysis as the mean age increases by one year, the likelihood of developing hypertension increases by a factor of 0.58 times (β = 0.58, 95% CI: 0.31–0.86, R2 = 36.67). Male sex (OR = 1.29, 95% CI: 1.03–1.61, I2 = 81.35%), age > 35 years (OR = 3.59, 95% CI: 2.57–5.02, I2 = 93.48%), overweight and/or obese (OR = 3.34, 95% CI: 2.12–5.26, I2 = 95.41%), khat chewing (OR = 1.42, 95% CI: I2 = 62%), alcohol consumption (OR = 1.50, 95% CI: 1.21–1.85, I2 = 64%), family history of hypertension (OR = 2.56, 95% CI: 1.64–3.99, I2 = 83.28%), and family history of diabetes mellitus (OR = 3.69, 95% CI: 1.85–7.59, I2 = 89.9%) are significantly associated with hypertension. Conclusion: Hypertension is becoming a major public health problem in Ethiopia. Nearly two out of ten individuals who are older than 18 years living with hypertension. Sex, age, overweight and/or obese, khat chewing, alcohol consumption, and family history of hypertension and diabetes mellitus are statistically significant determinant factors for hypertension in Ethiopia. Primary attention should be given for behavioral risk factors to tackle the alarming increase of hypertension in Ethiopia. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate the effects of two prebiotics in different concentrations on nutrient digestibility, fermentative products and immunological variables in adult dogs. Twenty-four adult dogs were randomly divided into six blocks according to their metabolic body weights (BW0.75); within these groups, dogs were randomized to four treatments: control without prebiotics (CO); inclusion of 0.5% prebiotic blend Yes-Golf (B1); inclusion of 1.0% galactooligosaccharide (GOS); and inclusion of 1.0% prebiotic blend Yes-Golf (B2). The experiment lasted 30 days, with 20 days adaptation and 10 days stool and blood collection. Results were analyzed for normality and means were separated by ANOVA and adjusted by the Tukey test at the significance level of 5.0%. Prebiotic supplementation had no effect on apparent digestibility coefficients (ADC), total stool production and fecal scores (p > 0.05). Prebiotics evaluated also did not alter fecal pH, nor the concentrations of ammonia, lactic acid, short chain fatty acids (SCFA) and most fecal branched chain fatty acids (BCFA) (p > 0.05). The addition of GOS decreased the concentration of iso-valeric acid (p = 0.0423). Regarding immunological variables, concentrations of fecal IgA were not influenced by the treatments. Treatments GOS and B2 increased the total number of polymorphonuclear cells, as well as the oxidative burst in relation to treatments B1 and CO (p < 0.0001). Treatment B2 improved the rate of S. aureus phagocytosis in relation to CO (p = 0.0111), and both the GOS and B2 treatments had a better index for E. coli phagocytosis than the CO treatment (p = 0.0067). In conclusion, there was indication that both prebiotics GOS and B2 at 1.0% inclusion improved the immunity of healthy dogs. [ABSTRACT FROM AUTHOR]

Introduction: There is ongoing research into the development of novel molecular markers that may complement fluid cytology malignant pleural effusion (MPE) diagnosis. In this exploratory pilot study, we hypothesized that there are distinct differences in the pleural fluid microbiome profile of malignant and non-malignant pleural diseases. Method: From a prospectively enrolled pleural fluid biorepository, samples of MPE were included. Non-MPE effusion were included as comparators. 16S rRNA gene V4 region amplicon sequencing was performed. Exact Sequence Variants (ESVs) were used for diversity analyses. The Shannon and Richness indices of alpha diversity and UniFrac beta diversity measures were tested for significance using permutational multivariate analysis of variance. Analyses of Composition of Microbiome was used to identify differentially abundant bacterial ESVs between the groups controlled for multiple hypothesis testing. Results: 38 patients with MPE and 9 with non-MPE were included. A subgroup of patients with metastatic adenocarcinoma histology were identified among MPE group (adenocarcinoma of lung origin (LA-MPE) = 11, breast origin (BA-MPE) = 11). MPE presented with significantly greater alpha diversity compared to non-MPE group. Within the MPE group, BA-MPE was more diverse compared to LA-MPE group. In multivariable analysis, ESVs belonging to family S24-7 and genera Allobaculum, Stenotrophomonas, and Epulopiscium were significantly enriched in the malignant group compared to the non-malignant group. Conclusion: Our results are the first to demonstrate a microbiome signature according to MPE and non-MPE. The role of microbiome in pleural effusion pathogenesis needs further exploration. [ABSTRACT FROM AUTHOR]

Logic relationship analysis is a data mining method that comprehensively detects item triplets that satisfy logic relationships from a binary matrix dataset, such as an ortholog table in comparative genomics. Thanks to recent technological advancements, many binary matrix datasets are now being produced in genomics, transcriptomics, epigenomics, metagenomics, and many other fields for comparative purposes. However, regardless of presumed interpretability and importance of logic relationships, existing data mining methods are not based on the framework of statistical hypothesis testing. That means, the type-1 and type-2 error rates are neither controlled nor estimated. Here, we developed Logicome Profiler, which exhaustively detects statistically significant triplet logic relationships from a binary matrix dataset (Logicome means ome of logics). To test all item triplets in a dataset while avoiding false positives, Logicome Profiler adjusts a significance level by the Bonferroni or Benjamini-Yekutieli method for the multiple testing correction. Its application to an ocean metagenomic dataset showed that Logicome Profiler can effectively detect statistically significant triplet logic relationships among environmental microbes and genes, which include those among urea transporter, urease, and photosynthesis-related genes. Beyond omics data analysis, Logicome Profiler is applicable to various binary matrix datasets in general for finding significant triplet logic relationships. The source code is available at https://github.com/fukunagatsu/LogicomeProfiler. [ABSTRACT FROM AUTHOR]

Questions about the evolution of material culture are widespread in the humanities and social sciences. Statistical modeling of long-term changes in material culture is less common due to a lack of appropriate frameworks. Our goal is to close this gap and provide robust statistical methods for examining changes in the diversity of material culture. We provide an open-source and quantitative workflow for estimating rates of origination, extinction, and preservation, as well as identifying key shift points in the diversification histories of material culture. We demonstrate our approach using two distinct kinds of data: age ranges for the production of American car models, and radiocarbon dates associated with archaeological cultures of the European Neolithic. Our approach improves on existing frameworks by disentangling the relative contributions of origination and extinction to diversification. Our method also permits rigorous statistical testing of competing hypotheses to explain changes in diversity. Finally, we stress the value of a flexible approach that can be applied to data in various forms; this flexibility allows scholars to explore commonalities between forms of material culture and ask questions about the general properties of cultural change. [ABSTRACT FROM AUTHOR]

Childhood obesity is an undeniable reality that has rapidly increased in many countries. Obesity at an early age not only increases the risks of chronic diseases but also produces a problem for the whole healthcare system. One way to alleviate this problem is to provide each patient with an appropriate menu that is defined by a mathematical model. Existing mathematical models only partially address the objective and constraints of childhood obesity; therefore, the solutions provided are insufficient for health specialists to prepare nutritional menus for individual patients. This manuscript proposes a multiobjective mathematical programming model to aid in healthy nutritional menu planning that may prevent childhood obesity. This model provides a plan for combinations and amounts of food across different schedules and daily meals. This approach minimizes the major risk factors of childhood obesity (i.e., glycemic load and cholesterol intake). In addition, this approach considers the minimization of nutritional mismatch and total cost. The model is solved using a deterministic method and two metaheuristic methods. Test instances associated with children aged 4–18 years were created with the support of health professionals to complete this numerical study. The quality of the solutions generated using the three methods was similar, but the metaheuristic methods provided solutions in a shorter computational time. These results are submitted to statistical hypothesis tests to be validated. The numerical results indicate proper guidelines for personalized plans for individual children. [ABSTRACT FROM AUTHOR]

Niche theory suggests that the coexistence of ecologically similar species in the same site requires some form of resource partitioning that reduces or avoids interspecific competition. Here, from July 2013 to December 2015, we investigated spatial niche differentiation at three different scales of two sympatric congeneric spiders, Peucetia rubrolineata and P. flava, along an altitudinal gradient in shaded and open areas in an Atlantic forest in Serra do Japi, SP, Brazil. These spiders are peculiar in that they present an exclusive association with the plant Trichogoniopsis adenantha (Asteraceae). In theory, the coexistence of two Peucetia species could be explained by: (1) microhabitat segregation with individuals from different species occupying different parts of the same plants; (2) mesohabitat segregation with different species using plant in different environments; (3) macrohabitat segregation, where different species would not co-occur along the altitudinal gradient. With respect to micro-habitat use, in both species, different instars used different plant parts, while the same instars of both species used the same type of substrate. However, the two Peucetia species segregated by meso-habitat type, with P. rubrolineata preferring T. adenantha plants in shaded areas and P. flava preferring those in open areas. Our results support the hypothesis of niche partitioning begetting diversity, and highlight the importance of analyzing habitat use at multiple scales to understand mechanisms related to coexistence. [ABSTRACT FROM AUTHOR]

Weeds are the major limitation to efficient crop production, and effective weed management is necessary to prevent yield losses due to crop-weed competition. Assessments of the relative efficacy of weed control treatments by traditional counting methods is labor intensive and expensive. More efficient methods are needed for weed control assessments. There is extensive literature on advanced techniques of image analysis for weed recognition, identification, classification, and leaf area, but there is limited information on statistical methods for hypothesis testing when data are obtained by image analysis (RGB decimal code). A traditional multiple comparison test, such as the Dunnett-Tukey-Kramer (DTK) test, is not an optimal statistical strategy for the image analysis because it does not fully utilize information contained in RGB decimal code. In this article, a bootstrap method and a Poisson model are considered to incorporate RGB decimal codes and pixels for comparing multiple treatments on weed control. These statistical methods can also estimate interpretable parameters such as the relative proportion of weed coverage and weed densities. The simulation studies showed that the bootstrap method and the Poisson model are more powerful than the DTK test for a fixed significance level. Using these statistical methods, three soil disinfestation treatments, steam, allyl-isothiocyanate (AITC), and control, were compared. Steam was found to be significantly more effective than AITC, a difference which could not be detected by the DTK test. Our study demonstrates that an appropriate statistical method can leverage statistical power even with a simple RGB index. [ABSTRACT FROM AUTHOR]

Quantifying patterns of deforestation and linking these patterns to potentially influencing variables is a key component of modelling and projecting land use change. Statistical methods based on null hypothesis testing are only partially successful for interpreting deforestation in the context of the processes that have led to their formation. Simplifications of cause-consequence relationships that are difficult to support empirically may influence environment and development policies because they suggest simple solutions to complex problems. Deforestation is a complex process driven by multiple proximate and underlying factors and a range of scales. In this study we use a multivariate statistical analysis to provide contextual explanation for deforestation in the Usumacinta River Basin based on partial pattern matching. Our approach avoided testing trivial null hypotheses of lack of association and investigated the strength and form of the response to drivers. As not all factors involved in deforestation are easily mapped as GIS layers, analytical challenges arise due to lack of a one to one correspondence between mappable attributes and drivers. We avoided testing simple statistical hypotheses such as the detectability of a significant linear relationship between deforestation and proximity to roads or water. We developed a series of informative generalised additive models based on combinations of layers that corresponded to hypotheses regarding processes. The importance of the variables representing accessibility was emphasised by the analysis. We provide evidence that land tenure is a critical factor in shaping the decision to deforest and that direct beam insolation has an effect associated with fire frequency and intensity. The effect of winter insolation was found to have many applied implications for land management. The methodology was useful for interpreting the relative importance of sets of variables representing drivers of deforestation. It was an informative approach, thus allowing the construction of a comprehensive understanding of its causes. [ABSTRACT FROM AUTHOR]

Classical null hypothesis significance tests are not appropriate in corpus linguistics, because the randomness assumption underlying these testing procedures is not fulfilled. Nevertheless, there are numerous scenarios where it would be beneficial to have some kind of test in order to judge the relevance of a result (e.g. a difference between two corpora) by answering the question whether the attribute of interest is pronounced enough to warrant the conclusion that it is substantial and not due to chance. In this paper, I outline such a test. [ABSTRACT FROM AUTHOR]

Recent research has shown Major League Baseball (MLB) players that bat left-handed and throw right-handed, otherwise known as sinister right-handers, are more likely to have a career batting average (BA) of .299 or higher compared to players with other combinations of batting and throwing handedness. Moreover, possibly owing to early exposure to hockey, Canadian-born MLB players have an increased propensity to be sinister right-handers, however, it has yet to be determined whether this provides a relative offensive performance advantage compared to players born in other countries. Using the largest archival dataset of MLB statistics available, the present study examined the independent influence of batting (i.e., left, right, switch) and throwing (i.e., left, right) handedness combinations and country/region of origin (i.e., Canada, USA, Latin America, Asia, Other) on several indices of offensive performance including BA, slugging percentage (SLG), on-base plus slugging (OPS), on-base plus slugging plus (OPS+), home runs (HR), runs batted in (RBI), strikeouts (SO) and wins above replacement (WAR). Mediation models were also computed to examine whether birthplace influences offensive performance through handedness. Examination of all recorded MLB batters revealed that batting left, regardless of throwing handedness, confers an offensive performance advantage. Since the inception of the MLB, the relative proportion of Canadian-born sinister right-handers is at least two times greater than players from other regions, although being Canadian-born does not provide a direct offensive advantage. Rather, results showed evidence of a significant indirect effect in that being Canadian-born increases the odds of being a sinister right-hander and in turn leads to greater performance across each offensive performance statistic. Collectively, findings provide further support for the hockey influence on batting hypothesis and suggest this effect extends to offensive performance. [ABSTRACT FROM AUTHOR]

Purpose: Most ophthalmologists appear to have no distinct preference between unilateral recess-resect (R&R) and bilateral lateral rectus (BLR) recessions to treat basic-type exotropia. This study aimed to determine whether differences in distance-near discrepancy and resultant exotropia types of recurrent exotropia following surgery for primary basic-type exotropia exist between the two surgical options. Methods: Ninety-three patients with recurrent exotropia following BLR recessions for basic-type exotropia (BLR group) and 95 following R&R for basic-type exotropia (R&R group) were included in this retrospective study. The exotropia types in recurrent exotropia were classified into three types according to distance-near discrepancy: basic, divergence-excess, and convergence-insufficiency. The BLR and R&R groups were compared. Results: After surgery for basic-type exotropia, the type composition changed differently in each group (p < 0.001). The basic-type of primary exotropia was more often maintained in recurrent exotropia in the R&R group than in the BLR group. The incidence of postoperative convergence-insufficiency type exotropia in the BLR group was 28.0% and 8.4% in the R&R group (p = 0.001). Postoperative near stereopsis and fusion control grade of distance deviation did not differ between the two groups (p > 0.05). Conclusions: Convergence-insufficiency type recurrent exotropia occurred more frequently after BLR recessions than after R&R for basic-type exotropia. The high rate of secondary convergence-insufficiency type exotropia after BLR recessions should be considered when clinicians select a surgical option to treat exotropia. [ABSTRACT FROM AUTHOR]

This study compares husbands' and wives' views on the person in a couple who should be responsible for preparing for hurricane hazards; it also examines whether the varying levels of agreement reached by husbands and wives regarding this responsibility are associated with actual preparedness behaviors. An online survey targeting married, heterosexual couples living in Sarasota County, Florida, USA was sent out between March and May, 2015. Both the husbands and the wives were asked to fill out the survey. A total of 170 surveys were used for analysis. Results suggested that husbands and wives felt that they had shared responsibility for most of the 19 preparedness behaviors considered. However, a few stereotypically masculine preparedness behaviors were found to typically fall to husbands. Husbands' and wives' views of perceived responsibility were not statistically different, but husbands tended to favor individual responsibility, while wives tended to favor joint responsibility. Higher levels of agreement were significantly associated with greater engagement in planning-related preparedness behaviors. Policy implications are discussed. [ABSTRACT FROM AUTHOR]

Background and purpose: Moyamoya disease (MMD) is a progressive cerebrovascular disease with unknown etiology. Growing evidence suggest its involvement of autoimmune and genetic mechanisms in the pathogenesis of MMD. This study aims to clarify the association between HLA allele and MMD. Methods: Case-control study: the DNA of 136 MMD patients in Japan was extracted and the genotype of human leukocyte antigen (HLA) from this DNA was determined by super-high-resolution single-molecule sequence-based typing using next-generation sequencing. Next, the frequency of each HLA allele (HLA-A, HLA-B, HLA-C, HLA-DRB1, HLA-DQB1, and HLA-DPB1) was compared with those in the Japanese control database. In addition, haplotype estimation was performed using the expectation maximization algorithm. Results: The frequencies of the HLA-DRB1*04:10 allele (4.77% vs. 1.47% in the control group; P = 1.7 × 10−3; odds ratio [OR] = 3.35) and of the HLA-DRB1*04:10–HLA-DQB1*04:02 haplotype (haplotype frequency 4.41% vs. 1.35% in the control group; P = 2.0 × 10−3; OR = 3.37) significantly increased. The frequency of thyroid diseases, such as Graves’ disease and Hashimoto thyroiditis, increased in HLA-DRB1*04:10-positive MMD patients compared with that in HLA-DRB1*04:10-negative MMD patients. Conclusions: HLA-DRB1*04:10 is a risk allele and HLA-DRB1*04:10–HLA-DQB1*04:02 a risk haplotype for MMD. In addition, HLA-DRB1*04:10 is associated with thyroid disease in MMD patients. [ABSTRACT FROM AUTHOR]

Background: Nabiximols (THC/CBD Oromucosal Spray, Sativex) is used as an add-on therapy to treat moderate to severe spasticity of Multiple Sclerosis (MS). Objectives: To examine the impact of physiotherapy (PT) programs on effectiveness and persistence of nabiximols treatment in people with MS-related spasticity. Methods: This is an observational multicenter study with a follow-up period of 12 weeks, conducted in routine care settings in Italy. Patients with moderate to severe MS-related spasticity who started nabiximols were included. Spasticity was evaluated by the patient-rated 0–10 numerical rating scale (NRS). Clinical data were collected at baseline (T0), 4 weeks (T1) and 12 weeks (T2) months after enrollment. Results: A total of 297 MS patients were selected, 290 completed the 3 months follow-up period. Mean NRS scores were 7.6 ± 1.1 at T0, 5.8 ± 1.4 at T1 and 5.5 ± 1.5 at T2. At T1, 77% of patients reached ≥20% improvement (initial response, IR); 22% reached ≥30% improvement (clinically relevant response, CRR). At T1, patients undergoing PT had a higher probability to reach CRR (Odds Ratio = 2.6 95% CI 1.3–5.6, p = 0.01). Nabiximols was discontinued in 30/290 (10.3%) patients at T1 (early discontinuers) and in 71/290 (24.5%) patients at T2 (late discontinuers). The probability of being late discontinuers was reduced in patients undergoing PT (Hazard Ratio = 0.41; 95% CI 0.23–0.69, p = 0.001). Conclusions: Our real-life study confirms nabiximols’ effectiveness in MS-related spasticity and suggests that the association of a PT program may improve overall response and persistence to nabiximols treatment. [ABSTRACT FROM AUTHOR]

Objective: In this study, it is aimed to determine obsessive compulsive-related disorders (OCRDs) comorbidity among the patients with obsessive compulsive disorder (OCD) and compare patients with OCD with or without comorbid OCRDs in terms of the severity of their OCD symptoms, symptom dimensions, and comorbidity with other axis I disorders. Methods: The study included 90 patients diagnosed as having OCD according to the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR). The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) diagnostic criteria for OCRDs were used to determine the presence of OCRDs. In order to determine the symptom dimensions and severity of these individuals’ OCD symptoms, we administered the Dimensional Obsessive Compulsive Scale (DOCS) and The Yale-Brown Obsessive Compulsive Scale (Y-BOCS). Results: In our study, 20% of the patients with OCD simultaneously met the criteria for at least one OCRD, we also found that a significantly greater proportion of this group were men. None of the mentioned disorders was associated with any symptom dimensions we evaluated using DOCS. In addition, no differences were found in the severity of OCD symptoms and comorbid axis I disorders between the group with comorbid OCRDs and the group without comorbid OCRDs. Discussion: There was no significant relationship between the symptom dimensions of OCD and OCRDs. It is found that OCRD comorbidity does not increase the severity of OCD symptoms and the prevalence of an axis I diagnosis. [ABSTRACT FROM AUTHOR]

Background: The prediction of readmission or death after a hospital discharge for heart failure (HF) remains a major challenge. Modern healthcare systems, electronic health records, and machine learning (ML) techniques allow us to mine data to select the most significant variables (allowing for reduction in the number of variables) without compromising the performance of models used for prediction of readmission and death. Moreover, ML methods based on transformation of variables may potentially further improve the performance. Objective: To use ML techniques to determine the most relevant and also transform variables for the prediction of 30-day readmission or death in HF patients. Methods: We identified all Western Australian patients aged 65 years and above admitted for HF between 2003–2008 in linked administrative data. We evaluated variables associated with HF readmission or death using standard statistical and ML based selection techniques. We also tested the new variables produced by transformation of the original variables. We developed multi-layer perceptron prediction models and compared their predictive performance using metrics such as Area Under the receiver operating characteristic Curve (AUC), sensitivity and specificity. Results: Following hospital discharge, the proportion of 30-day readmissions or death was 23.7% in our cohort of 10,757 HF patients. The prediction model developed by us using a smaller set of variables (n = 8) had comparable performance (AUC 0.62) to the traditional model (n = 47, AUC 0.62). Transformation of the original 47 variables further improved (p<0.001) the performance of the predictive model (AUC 0.66). Conclusions: A small set of variables selected using ML matched the performance of the model that used the full set of 47 variables for predicting 30-day readmission or death in HF patients. Model performance can be further significantly improved by transforming the original variables using ML methods. [ABSTRACT FROM AUTHOR]

Introduction: During the third trimester of development, the human fetus accumulates fat, an important energy reservoir during the early postnatal period. The fetal liver, perfused by the nutrient-rich and well-oxygenated blood coming directly from the placenta, is assumed to play a central role in these processes. Earlier studies have linked fetal liver blood flow with maternal nutritional status and response to the maternal oral glucose tolerance test. Our aim was to explore the effect of a regular maternal meal on fetal liver blood flow at two timepoints during the third trimester, representing the start and towards the end of the fetal fat accretion period. We also sought to explore the influence of prepregancy body mass index on how the maternal meal affects fetal liver blood flow. Methods: Using ultrasound Doppler, we examined 108 healthy women with singleton pregnancies in gestational weeks 30 and 36. At each visit, the first examination was performed with the participant in a fasting state at 08.30 a.m., followed by a standard breakfast meal of approximately 400 kcal. The examination was repeated after 105 minutes. Umbilical vein and ductus venosus blood flow was estimated from diameter and blood flow velocity measurements. Fetal liver flow was calculated as umbilical vein flow minus ductus venosus flow, and change in liver blood flow as flow after minus before the meal. The total group was divided into a normal-weight group (prepregancy body mass index 18.5–25.0 kg/m2; n = 83) and an overweight group (prepregancy body mass index >25.0 kg/m2; n = 21). Four women with prepregancy body mass index <18.5 kg/m2 were excluded from these analyses. Non-parametric statistical hypothesis tests were used for group comparisons. Results: For the total group, we observed a significant increase in median (10th - 90th percentile) liver flow 28.9 (‒67.9–111.6) ml/min (p = 0.002) following the meal in week 36, but not in week 30, ‒2.63 (‒53.2–65.0) ml/min (p = 0.91). This result in turn yielded a statistically significant increase in delta liver flow from weeks 30 to 36 of 26.0 (‒107.1–146.6) ml/min (p = 0.008). The increase in postprandial liver flow was observed only in the normal-weight group in week 36. Accordingly, the delta liver flow values between the two weight groups were significantly different in week 36 (p = 0.006) but not in week 30 (p = 0.155). Among the normal-weight women, the increase in delta liver blood flow from weeks 30 to 36 was 39.3 (‒83.0–156.1) ml/min (p<0.001); in contrast, we observed no statistically significant change in the overweight group (‒44.5 (‒229.0–123.2) ml/min; p = 0.073). As a substitute for liver size, we divided the delta liver flow values by abdominal circumference and found no changes in the statistical significance results within or between the two weight groups. Conclusion: In our healthy study population, we observed a statistically significant difference in liver blood flow after maternal intake of a regular meal. This effect depended on gestational age and maternal prepregancy body mass index, but apparently was independent of liver size, based on abdominal circumference as a proxy measure. [ABSTRACT FROM AUTHOR]

Feature screening has become a real prerequisite for the analysis of high-dimensional genomic data, as it is effective in reducing dimensionality and removing redundant features. However, existing methods for feature screening have been mostly relying on the assumptions of linear effects and independence (or weak dependence) between features, which might be inappropriate in real practice. In this paper, we consider the problem of selecting continuous features for a categorical outcome from high-dimensional data. We propose a powerful statistical procedure that consists of two steps, a nonparametric significance test based on edge count and a multiple testing procedure with dependence adjustment for false discovery rate control. The new method presents two novelties. First, the edge-count test directly targets distributional difference between groups, therefore it is sensitive to nonlinear effects. Second, we relax the independence assumption and adapt Efron’s procedure to adjust for the dependence between features. The performance of the proposed procedure, in terms of statistical power and false discovery rate, is illustrated by simulated data. We apply the new method to three genomic datasets to identify genes associated with colon, cervical and prostate cancers. [ABSTRACT FROM AUTHOR]

Invasive fungal infections (IFIs) are a leading cause of morbidity and attributable mortality in oncohematologic patients. Timely diagnosis is essential but challenging. Herein we retrospectively describe 221 cases of antifungal treatments (AFT) administered in a monocentric real-life cohort of hematological malignancies. Between January 2010 and July 2017, 196 oncohematologic patients were treated with AFT at our Hematology Department. Diagnosis of IFIs was carried out according to EORTC/MSG-2008 guidelines.The most represented disease was acute myeloid leukemia (104 patients). Median age was 61 years; at fever onset 177 (80%) patients had a neutrophil count<0.5x109/L. Twenty-nine (13%) patients were receiving antifungal prophylaxis (26 posaconazole, 2 fluconazole, 1 itraconazole). The incidence of AFT was 13%. Serum galactomannan antigen (GM) was positive in 20% of the tested cases, while 85% of the patients had a CT scan suggestive for IFI. Twenty-one percent of these cases had a GM positive. Sixty-five out of 196 patients (33%) showed positive culture results, in particular Candida spp. were identified in 45 isolates, while Aspergillus spp. in 16 cases. Fourteen patients presented multiple positivity. Twenty-two (10%) cases were classified as proven IFIs, 61 (28%) as probable and 81 (37%) as possible, but 57 (26%) cases could not be classified. Fifty-nine percent of the patients received single agent AFT, 37% sequential AFT, 8% a combination regimen. Liposomal-amphotericin-B was the most used AFT. IFIs attributable mortality was 20%. This epidemiologic survey underlined a persistent significant use of AFT and a high mortality rate of IFIs. We suggest that further powerful diagnostic approaches should be investigated to improve the diagnostic accuracy and potential therapeutic implication. [ABSTRACT FROM AUTHOR]

Introduction: Pancreatic ductal adenocarcinoma is associated to dismal prognosis despite the use of palliative chemotherapy, partly due to the lack of knowledge of biological processes underlying disease progression. Exosomes have been identified as biomarkers sources in different cancer types. Aim of the study was to analyse the contents of circulating exosomes in patients with pancreatic cancer who received palliative chemotherapy. Patients and methods: Patients were submitted to blood sample collection before chemotherapy (T0) and after 3 months (T3). We quantified by an ELISA-based technique specific proteins of cancer-derived exosomes (CD44,CD44v6,EpCAM,CD9,CD81,Tspan8,Integrin α6,Integrin β4,CD24,CXCR4). We correlated the baseline levels of these factors and changes between T3 and T0 and survival outcomes. Survival analyses were performed by Kaplan-Meier method. Correlation was assessed by log-rank test and level of statistical significance was set at 0.05. Multivariate analysis was performed by logistic regression analysis. Results: Nineteen patients were enrolled. EpCAM T0 levels and increased EpCAM levels from T0 to T3 were those mostly associated with differences in survival. Patients having higher EpCAM had median progression free survival (PFS) of 3.18vs7.31 months (HR:2.82,95%CI:1.03–7.73,p = 0.01). Overall survival (OS) was shorter for patients having higher EpCAM (5.83vs16.45 months,HR:6.16,95%CI:1.93–19.58,p = 0.0001) and also response rates (RR) were worse (20%vs87%,p = 0.015). EpCAM increase during treatment was associated with better median PFS (2.88vs7.31 months,HR:0.24,95%CI:0.04–1.22,p = 0.003). OS was also better (8.75vs11.04 months, HR:0.77,95%CI:0.21–2.73,p = 0.66) and RR were 60%vs20% (p = 0.28). Among clinical factors that might determine changes on PFS and OS, only ECOG PS was associated to significantly worse PFS and OS (p = 0.0137and<0.001 respectively).Multivariate analysis confirmed EpCAM T0 levels and EpCAM T0/T3 changes as independent prognostic factors for PFS. Conclusions: Pancreatic cancer patients exosomes express EpCAM, whose levels change during treatment. This represents a useful prognostic factor and also suggests that future treatment modalities who target EpCAM should be tested in pancreatic cancer patients selected by exosome EpCAM expression. [ABSTRACT FROM AUTHOR]

England’s national Improving Access to Psychological Therapies (IAPT) programme advocates stepped care as its organizational delivery of psychological therapies to common mental health problems. There is limited evidence regarding the efficacy of stepped care as a service delivery model, heterogeneity of definition and differences in model implementation in both research and routine practice, hence outcome comparison in terms of effectiveness of model is difficult. Despite sound evidence of the efficacy of low intensity interventions there appears to be a perpetuation of the notion that severity and complexity should only be treated by a high intensity intervention through the continuation of a stratified care model. Yet no psychotherapy treatment is found to be more superior to another, and not enough is known about what works for whom to aid the matching of treatment decision. In the absence of understanding precise treatment factors optimal for recovery, it may be useful to better understand the impact of a service delivery model, and whether different models achieve different outcomes. This study aims to contribute to the discussion regarding the stepped care definition and delivery, and explores the impact on clinical outcomes where different types of stepped care have been implemented within the same service. An observational cohort study analysed retrospective data (n = 16,723) over a 4 year period, in a single IAPT service, where delivery changed from one type of stepped care model to another. We compared the outcomes of treatment completers with a stratified care model and a progression care model. We also explored the assumption that patients who score severe on psychological measures, and therefore are potentially complex, would achieve better outcomes in a stratified model. Outcomes in each model type were compared, alongside baseline factor variables. A significant association was observed between a recovery outcome and model type, with patients 1.5 times more likely to recover in the progression delivery model. The potential implications are that with a progression stepped care model of service delivery, more patients can be treated with a lower intensity intervention, even with initial severe presentations, ensuring that only those that need high intensity CBT or equivalent are stepped up. This could provide services with an effective clinical model that is efficient and potentially more cost effective. [ABSTRACT FROM AUTHOR]

Objectives: This study aimed to determine the relationship between stunting in children 6 to 36 months old and maternal employment status in Peru. Methods: A secondary data analysis was conducted using information from the Demographic and Health Survey (DHS) in Peru. We used a representative sample of 4637 mother-child binomials to determine the association between stunting in children 6 to 36 months of age and the employment status of their mothers. Results: The prevalence of stunting among children was 15.9% (95% CI: 13.9–16.7). The prevalence of working mothers was 63.7%. No association was found between maternal employment status and the presence of stunting in children [prevalence ratio (PR) = 1.04; 95% confidence interval (95% CI): 0.9 to 1.2; p = 0.627). However, on multivariate analysis we found that the prevalence of stunting was significantly higher among children of mothers performing unpaid work (12.4%) (PR = 1.38; 95% CI: 1.2–1.6; p < 0.001) compared with those of paid working mothers. Conclusion: No significant association was found between maternal employment status and the presence of stunting in children 6 to 36 months of age. However, children of mothers doing unpaid work are at higher risk of stunting. These findings support the implementation of educational programs and labour policies to reduce the prevalence of stunting among children. [ABSTRACT FROM AUTHOR]

In the last 15 years, Theory of Mind research has been revolutionized by the development of new implicit tasks. Such tasks aim at tapping children’s and adults’ uninstructed, largely automatic mental state ascription, indicated in spontaneous looking behavior when observing agents who act on the basis of false beliefs. Studies with anticipatory looking, in particular, have suggested that basic ToM capacities operate from very early in life and remain in unconscious operation throughout the lifespan. Recently, however, systematic replication attempts of anticipatory looking measures have yielded a complex and puzzling mixture of successful, partial and non-replications. The present study aimed at shedding light on the question whether there is a system to this pattern. More specifically, in a set of three preregistered experiments, it was tested whether those conditions that could previously be replicated and those that could not differ in crucial conceptual respects such that the former do not strictly require ToM whereas the latter do. This was tested by the implementation of novel control conditions. The results were complex. There was generally no unambiguous evidence for reliable spontaneous ToM and no effect of the number of passed familiarization trials. Neither was there any unambiguous evidence that the previous mixed patterns of (non-)replications could be explained (away) by the sub-mentalizing account tested in the new control conditions. The empirical situation remains puzzling, and the question whether there is some such thing as implicit and spontaneous ToM remains to be clarified. [ABSTRACT FROM AUTHOR]

We compare the surgical outcomes of intermittent exotropia of the basic, pseudo-divergence excess (pseudo-DE) and true divergence excess (true DE) types. A study was performed with 342 patients who had undergone surgery for intermittent exotropia of the basic, pseudo-DE or true DE type with a postoperative follow-up period of 6 months or more. The main outcome measures were postoperative angles of deviation at distance and near, and surgical success rates. Surgical success was defined as alignment between exodeviation of 10 PD and esodeviation of 5 PD at distance and near. Additionally, survival curves of recurrence were analyzed by the Kaplan-Meier method. The postoperative angles of deviation at both distance and near in pseudo-DE type were significantly smaller than those in basic type at the final examination (p = 0.003, <0.001). The final surgical success rate in pseudo-DE (70.2%) was better than in basic (46.3%) or true DE (28.6%) (p = 0.003, 0.01). Reoperation for recurrent exotropia was performed in 27% of the basic, 17% of the pseudo-DE, and 35.7% of the true DE cases. According to a survival analysis for recurrence, patients with pseudo-DE showed lower incidence of recurrence than did patients with basic and true DE (p = 0.003, 0.02). In conclusion, the patients with intermittent exotropia of the pseudo-DE type showed better surgical outcomes than those with the basic or true DE type. Pseudo-DE also showed a lower recurrence rate than did the other 2 groups. [ABSTRACT FROM AUTHOR]

Open Educational Resources (OER) have been lauded for their ability to reduce student costs and improve equity in higher education. Research examining whether OER provides learning benefits have produced mixed results, with most studies showing null effects. We argue that the common methods used to examine OER efficacy are unlikely to detect positive effects based on predictions of the access hypothesis. The access hypothesis states that OER benefits learning by providing access to critical course materials, and therefore predicts that OER should only benefit students who would not otherwise have access to the materials. Through the use of simulation analysis, we demonstrate that even if there is a learning benefit of OER, standard research methods are unlikely to detect it. [ABSTRACT FROM AUTHOR]

We categorize Stockholm’s urban green spaces according to the use values and social meanings they support, based on a sociotope mapping, and estimate their impact on property prices with a hedonic pricing model. The approach allows us to identify the most and least desired green space characteristics (attributes) and to assess the willingness to pay for the multifunctionality of green spaces. To do this, we test the following hypotheses, each with a separate hedonic pricing model: We find partial support for the first hypothesis: the green space attributes of “aesthetics”, “social activity” and “nature” seem to be desired by real estate buyers, whereas “physical activity” and “play” seem not to be desired. We also find support for the second hypothesis: the higher the number of characteristics an urban green space has, the stronger its impact on property prices. This study furthers the discussion on the economic value of urban green spaces by assigning monetary value to their perceived character and use values. In doing so, it highlights the need to understand green spaces both as ecological features and social constructs. [ABSTRACT FROM AUTHOR]

Background: Propensity score (PS) methods are commonly used to control for confounding in comparative effectiveness studies. Electronic health records (EHRs) contain much unstructured data that could be used as proxies for potential confounding factors. The goal of this study was to assess whether the unstructured information can also be used to construct PS models that would allow to properly deal with confounding. We used an example of coxibs (Cox-2 inhibitors) vs. traditional NSAIDs and the risk of upper gastro-intestinal bleeding as example, since this association is often confounded due to channeling of coxibs to patients at higher risk of upper gastro-intestinal bleeding. Methods: In a cohort study of new users of nonsteroidal anti-inflammatory drugs (NSAIDs) from the Dutch Integrated Primary Care Information (IPCI) database, we identified all patients who experienced an upper gastrointestinal bleeding (UGIB). We used a large-scale regularized regression to fit two PS models using all structured and unstructured information in the EHR. We calculated hazard ratios (HRs) to estimate the risk of UGIB among selective cyclo-oxygenase-2 (COX-2) inhibitor users compared to nonselective NSAID (nsNSAID) users. Results: The crude hazard ratio of UGIB for COX-2 inhibitors compared to nsNSAIDs was 0.50 (95% confidence interval 0.18–1.36). Matching only on age resulted in an HR of 0.36 (0.11–1.16), and of 0.35 (0.11–1.11) when further adjusted for sex. Matching on PS only, the first model yielded an HR of 0.42 (0.13–1.38), which reduced to 0.35 (0.96–1.25) when adjusted for age and sex. The second model resulted in an HR of 0.42 (0.13–1.39), which dropped to 0.31 (0.09–1.08) after adjustment for age and sex. Conclusions: PS models can be created using unstructured information in EHRs. An incremental benefit was observed by matching on PS over traditional matching and adjustment for covariates. [ABSTRACT FROM AUTHOR]

Background: The beliefs we hold about stress play an important role in coping with stressors. Various theoretical frameworks of stress point to the efficacy of reframing stress-related information through brief reappraisal interventions in order to promote adaptive coping. Purpose: The goal of the current meta-analysis and systematic review is to substantiate the efficacy of reappraisal interventions on stress responsivity compared to control conditions. Differences in experimental methodologies (e.g., type of stressor used, timing of reappraisal intervention, and content of intervention instructions) will be examined to further delineate their effects on intervention outcomes. Methods: The literature searches were conducted on May 16, 2018 using PsycINFO, ProQuest Dissertations and Theses, and PILOTS databases with no date restriction. The search terms included stress, reframing, reappraisal, mindset and reconceptualising. A total of 14 articles with 36 independent samples were included in the meta-analysis, while 22 articles with 46 independent samples were included in the systematic review. Random-effects model was used to test the null hypothesis using two-tailed significance testing. Fisher’s Z value was reported for each corresponding test. Heterogeneity tests are reported via Cochran’s Q-statistics. Results: Findings from both the meta-analysis and systematic review revealed that overall, reappraisal interventions are effective in attenuating subjective responsivity to stress. Standard differences in means across groups are 0.429 (SE = 0.185, 95% CI = 0.067 to 0.791; z = 2.320, p = .020). However, reappraisal intervention groups did not outperform control groups on measures of physiological stress, with standard differences of -0.084 (SE = 0.135, 95% CI = -0.349 to 0.180; z = -0.627, p = .531). Moderator analysis revealed heterogeneous effects suggesting large variability in findings. Conclusions: On one hand, findings may suggest a promising avenue for the effective management of self-reported stress and optimization of stress responses. However, more research is needed to better elucidate the effects, if any, of reappraisal interventions on stress physiology. Implications for the use of reappraisal interventions on stress optimization are discussed in the context of theoretical frameworks and considerations for future studies. [ABSTRACT FROM AUTHOR]