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Substantial progress has been made in understanding the neurocognitive underpinnings of learning math. Building on this work, it has been hypothesized that declarative and procedural memory, two domain-general learning and memory systems, play important roles in acquiring math skills. In a longitudinal study, we tested whether in fact declarative and procedural memory predict children's math skills during elementary school years. A sample of 109 children was tested across grades 2, 3 and 4. Linear mixed-effects regression and structural equation modeling revealed the following. First, learning in declarative but not procedural memory was associated with math skills within each grade. Second, declarative but not procedural memory in each grade was related to math skills in all later grades (e.g., declarative memory in grade 2 was related to math skills in grade 4). Sensitivity analyses showed that the pattern of results was robust, except for the longitudinal prediction of later math skills when accounting for stable inter-individual differences via the inclusion of random intercepts. Our findings highlight the foundational role of early domain-general learning and memory in children's acquisition of math. [ABSTRACT FROM AUTHOR]

In this paper, we examine q-Bernstein-Bézier surfaces in Minkowski space- R13 with q as the shape parameter. These surfaces, a generalization of Bézier surfaces, have applications in mathematics, computer-aided geometric design, and computer graphics for the surface formation and modeling. We analyze the timelike and spacelike cases of q-Bernstein-Bézier surfaces using known boundary control points. The mean curvature and Gaussian curvature of these q-Bernstein-Bézier surfaces are computed by finding the respective fundamental coefficients. We also investigate the shape operator dependency for timelike and spacelike q-Bernstein-Bézier surfaces in Minkowski space- R13 , and provide biquadratic and bicubic q-Bernstein-Bézier surfaces as illustrative examples for different values of the shape controlling parameter q. [ABSTRACT FROM AUTHOR]

Authoring of help content within educational technologies is labor intensive, requiring many iterations of content creation, refining, and proofreading. In this paper, we conduct an efficacy evaluation of ChatGPT-generated help using a 3 x 4 study design (N = 274) to compare the learning gains of ChatGPT to human tutor-authored help across four mathematics problem subject areas. Participants are randomly assigned to one of three hint conditions (control, human tutor, or ChatGPT) paired with one of four randomly assigned subject areas (Elementary Algebra, Intermediate Algebra, College Algebra, or Statistics). We find that only the ChatGPT condition produces statistically significant learning gains compared to a no-help control, with no statistically significant differences in gains or time-on-task observed between learners receiving ChatGPT vs human tutor help. Notably, ChatGPT-generated help failed quality checks on 32% of problems. This was, however, reducible to nearly 0% for algebra problems and 13% for statistics problems after applying self-consistency, a "hallucination" mitigation technique for Large Language Models. [ABSTRACT FROM AUTHOR]

This study explored the effectiveness of digital story interventions in improving early math skills in kindergarten children with mild intellectual disabilities. Digital stories are multimedia narratives that combine text, images, and audio to enhance learning experience. This experimental study used a pretest-posttest control group design. The intervention group consisted of 15 children who participated in an 8-week digital story intervention targeting early math skills. A matched control group was used to control for sex differences. Data were collected through the TEMA-3 test scores and teacher and child feedback. Post-intervention, the experimental group showed significant improvements in TEMA-3 test scores compared to the control group. Teachers and children reported a positive perception of the intervention's social validity, highlighting enhanced engagement and understanding of math concepts. This study demonstrated that digital story-based education is a promising approach for improving early math skills in children with mild intellectual disabilities. These findings suggest potential implications for integrating digital storytelling into special education curricula and highlight avenues for future research in this field. [ABSTRACT FROM AUTHOR]

Past research has shown that growth mindset and motivational beliefs have an important role in math and science career interest in adolescence. Drawing on situated expectancy-value theory (SEVT), this study extends these findings by investigating the role of parental motivational beliefs (e.g., expectancy beliefs, utility values) and parent growth mindset in math on adolescent career interest in math-intensive fields (e.g., mathematics, computer science, statistics, and engineering; MCSE) through adolescent motivational beliefs in math. Structural equation modeling was used to test the hypothesized model using data from 290 adolescents (201 girls, 69.3%; Mage = 15.20), who participate in informal STEM (science, technology, engineering, mathematics) youth programs, and their parents (162 parents, 87.7% female) in the United Kingdom and the United States. As hypothesized, adolescent expectancy beliefs, utility values, and growth mindset in math had a significant direct effect on MCSE career interest. Further, there was a significant indirect effect of parental expectancy beliefs in math on MCSE career interest through adolescents' expectancy beliefs. Similarly, there was a significant indirect effect from parental utility values in math to MCSE career interest through adolescents' utility values. The findings suggest that parents' math motivational beliefs play a critical role in adolescent math motivational beliefs and their career interest in math-intensive fields. [ABSTRACT FROM AUTHOR]

Students' math motivation can predict engagement, achievement, and career interest in science, technology, engineering, and mathematics (STEM). However, it is not well understood how personality traits and math anxiety may be linked to different types or qualities of math motivation, particularly during high-stress times such as the COVID-19 pandemic. In this study, we examined how fearful or avoidant temperaments contribute to math anxiety and math motivations for college students during the COVID-19 pandemic. Ninety-six undergraduate students from a large public university were assessed on temperamental fear, math anxiety, and math motivation in an online math course. Results showed that higher levels of temperamental fear are directly linked to higher levels of math anxiety. In addition, temperamental fear is indirectly linked to higher levels of autonomous motivation (i.e., intrinsic motivation and identified regulation) and lower levels of controlled motivation (i.e., external regulation) through math anxiety. Results have implications for helping students at high risk for both high math anxiety and for low motivation to engage in math learning. [ABSTRACT FROM AUTHOR]

Algebra and geometry are important components of mathematics that are often considered gatekeepers for future success. However, most studies that have researched the cognitive skills required for success in mathematics have only considered the domain of arithmetic. We extended models of mathematical skills to consider how executive function skills play both a direct role in secondary-school-level mathematical achievement as well as an indirect role via algebra and geometry, alongside arithmetic. We found that verbal and visuospatial working memory were indirectly associated with mathematical achievement via number fact knowledge, calculation skills, algebra and geometry. Inhibition was also indirectly associated with mathematical achievement via number fact knowledge and calculation skills. These findings highlight that there are multiple mechanisms by which executive function skills may be involved in mathematics outcomes. Therefore, using specific measures of mathematical processes as well as context-rich assessments of mathematical achievement is important to understand these mechanisms. [ABSTRACT FROM AUTHOR]

It has long been understood that there exists a strong association between a student's belief in the future utility of mathematics and their self-efficacy in mathematics. This study re-examines this association by studying these variables based on data collected from a sample of 21,444 ninth-grade students who participated in the 2009 High School Longitudinal Study (HSLS09). The nature of the association between future utility beliefs of students in mathematics and self-efficacy of students in mathematics is explored visually using the simple correspondence analysis technique. The main feature that will be utilised from this technique is a two-dimensional graphical display, referred to as a correspondence plot. By studying the HSLS09 data, the first two axes of such a plot summarised nearly 99% of the statistically significant association that exists between a student's beliefs in the future utility of mathematics and their mathematics self-efficacy. It is shown visually that students who strongly believe in the future importance of studying mathematics also perform strongly in the subject, while those who do not believe that there is any future utility from studying mathematics do not perform well at it. This study, therefore, suggests that mathematics ability is associated with a student's perception of its future importance. [ABSTRACT FROM AUTHOR]

A meaningful engagement of learners is critical in the quality teaching and learning of mathematics at school level. Learner engagement has been an ongoing issue in mathematics classrooms in Nepal and elsewhere. In this context, this study aimed to examine the level of engagement (behavioral, social, emotional, and cognitive activities) and their association with learning mathematics through the virtual mode of instruction during the pandemic. The cross-sectional online survey design was employed among 402 secondary-level mathematics teachers in Nepal. Descriptive statistics, correlation, and structural equation modeling were the major statistical techniques used in research. The findings indicate that the level of behavioral, social, emotional, and cognitive engagement of students was found to be high in the online mode of instruction. Additionally, cognitive engagement has significant highest impact on social, behavior, and emotional engagement. [ABSTRACT FROM AUTHOR]

Research into the experiences of students in mathematics with a marginalized sexual identity has remained largely underexplored, relegating these experiences and individuals to remain invisible. In this study, we leverage Queer Theory to address this gap in research by reporting on the experiences of Queer-spectrum undergraduate students (n = 2,454) enrolled in introductory mathematics courses (Precalculus, Calculus 1, and Calculus 2) across the United States. Drawing on student data (n = 24,327) from the Student Post-Secondary Instructional Practices Survey, we examine reported outcomes of math learning experiences and access to learning environments. Overall, within introductory math courses, sexual identity had a significant relationship with accessing learning environments and mathematical learning experiences. Asexual students were among those that reported higher levels of interactions with peers and instructors, a greater sense of community & participation, positive math affect, and were more likely to access learning environments external to the course yet anticipated receiving a lower course grade when compared to straight students. Bisexual students reported lower levels of interactions with instructors, a diminished sense of community & participation, math engagement, positive math affect, and were less likely to access learning environments compared to straight students. These findings suggest that Queer-spectrum students experience mathematical learning in a different manner than their straight peers and in relation to other Queer spectrum identities. Queer-spectrum students with a sexualized identity perceive that mathematics environments are not normative places to be a part of the community, resulting in negative dispositions, reduced interactions, and lower academic success. The impact of sexual identity, although small, contributes to negative indicators of positive mathematical experiences and suggests that the normative discourses in mathematics that are identity neutral, heteronormative, and aligned with binary thinking are differentially impacting Queer-spectrum students. [ABSTRACT FROM AUTHOR]

Mathematics plays a leading part in day-to-day life and has enhanced a necessary component for human accomplishments. Students from many countries do not reach the expected level in mathematics. Therefore, it is essential to pay close consideration to the causes related to ability in mathematics. Mathematics attitude is considered as one of the critical variables in the process of mathematics learning. This study aimed to determine students' attitudes and achievements through problem-based learning in mathematics. The selected study group contained 600 students and 35 teachers from rural public secondary schools in District Rawalpindi, Pakistan. The data collection was done using questionnaires from students and teachers and collected data analyzed by SPSS 23 and Amos 23. This study's result was carried out using Partial Least square structural equation Model (PLS-SEM), descriptive analysis, and hypotheses testing. The outcomes in this study indicated that the mean fluctuated between 1 to 4.5, 3.71 to 4.20, and Std. Deviation fluctuated between 0.6 to 2.0 and 0.75 to 1.55 in the students and teacher models, respectively. The results of the PLS-SEM students' model show a negative attitude towards mathematics. The teachers' PLS-SEM model showed the Effects of using problem-based learning (PBL) on students' achievements. According to the hypotheses testing, the acceptance of hypotheses by stating that the Confidence in Learning Mathematics Scale (C), Value of Mathematics Scale (V), and Student Mathematics Motivation Scale (M) are significant effects for the Students' Attitude Toward Problem-Based Learning (ATPBL). But the Attitude Toward Enjoyment in Mathematics Scale (AE) was rejected, and it did not significantly affect the ATPBL. As well as, the Problem-solving learning and students' achievement (PLA), Advantages of problem-solving learning (APL) and Difficulties in using problem-solving learning (DPL) have a significant positive effect on the ATPBL. Finally, this study suggested that teachers also adopt new teaching methods corresponding to mathematics, and there is a need to explore particular mathematics skills to enhance students' learning abilities. [ABSTRACT FROM AUTHOR]

Professional development has been identified as an effective way to increase college STEM instructors' use of research-based instructional strategies (RBIS) known to benefit student learning and persistence in STEM. Yet only a few studies relate professional development experiences to later teaching behaviors of higher education instructors. This study of 361 undergraduate mathematics instructors, all of whom participated in multi-day, discipline-based workshops on teaching held in 2010–2019, examined the relationship between such participation and later use of RBIS. We found that instructors' RBIS attitudes, knowledge, and skills strengthened after participating in professional development, and their self-reported use of RBIS became more frequent in the first year after the workshop. Applying the Theory of Planned Behavior as a conceptual framework, we used a structural equation model to test whether this theory could explain the roles of workshop participation and other personal, professional and contextual factors in fostering RBIS use. Findings indicated that, along with workshop participation, prior RBIS experience, class size, and course coordination affected RBIS use. That is, both targeted professional development and elements of the local context for implementation were important in supporting instructors' uptake of RBIS—but, remarkably, both immediate and longer-term outcomes of professional development did not depend on other individual or institutional characteristics. In this study, the large sample size, longitudinal measurement approach, and consistency of the form and quality of professional development make it possible to distinguish the importance of multiple possible influences on instructors' uptake of RBIS. We discuss implications for professional development and for institutional structures that support instructors as they apply what they learned, and we offer suggestions for the use of theory in future research on this topic. [ABSTRACT FROM AUTHOR]

Despite the global importance of science, engineering, and math-related fields, women are consistently underrepresented in these areas. One source of this disparity is likely the prevalence of gender stereotypes that constrain girls' and women's math performance and interest. The current research explores the developmental roots of these effects by examining the impact of stereotypes on young girls' intuitive number sense, a universal skill that predicts later math ability. Across four studies, 762 children ages 3–6 were presented with a task measuring their Approximate Number System accuracy. Instructions given before the task varied by condition. In the two control conditions, the task was described to children either as a game or a test of eyesight ability. In the experimental condition, the task was described as a test of math ability and that researchers were interested in whether boys or girls were better at math and counting. Separately, we measured children's explicit beliefs about math and gender. Results conducted on the combined dataset indicated that while only a small number of girls in the sample had stereotypes associating math with boys, these girls performed significantly worse on a test of Approximate Number System accuracy when it was framed as a math test rather than a game or an eyesight test. These results provide novel evidence that for young girls who do endorse stereotypes about math and gender, contextual activation of these stereotypes may impair their intuitive number sense, potentially affecting their acquisition of formal mathematics concepts and developing interest in math-related fields. [ABSTRACT FROM AUTHOR]

Mathematics teachers must be able to engage in self-reflection and think constructively about their professional activities to instruct students effectively. This is also important for students' ability to solve problems in class, as well as the challenges facing them and their societies in the future. This study aimed to examine in-service math teachers' reflective thinking skills in the context of how they are applied to their understanding of their teaching practices. The sample included 322 mathematics teachers, who responded to a questionnaire designed to elucidate how they were thinking reflectively about their teaching practice. The findings revealed that the teachers' practices concerning all the themes of reflective thinking addressed by the questionnaire, especially their ability to self-assess, fluctuated around the intermediate, and advanced levels. The implications of our findings are discussed in terms of extensive and continuous professional development centered on supporting ongoing growth in the reflective thinking skills of in-service math teachers. [ABSTRACT FROM AUTHOR]

The registered report was targeted at identifying latent profiles of competence development in reading and mathematics among N = 15,012 German students in upper secondary education sampled in a multi-stage stratified cluster design across German schools. These students were initially assessed in grade 9 and provided competence assessments on three measurement occasions across six years using tests especially developed for the German National Educational Panel Study (NEPS). Using Latent Growth Mixture Models, Using Latent Growth Mixture Models, we aimed at identifying multiple profiles of competence development. Specifically, we expected to find at least one generalized (i.e., reading and mathematical competence develop similarly) and two specialized profiles (i.e., one of the domains develops faster) of competence development and that these profiles are explained by the specialization of interest and of vocational education of students. Contrary to our expectations, we did not find multiple latent profiles of competence development. The model describing our data best was a single-group latent growth model confirming a competence development profile, which can be described as specializing in mathematical competences, indicating a higher increase in mathematical competences as compared to reading competences in upper secondary school. Since only one latent profile was identified, potential predictors (specialization of vocational education and interest) for different profiles of competence development were not examined. [ABSTRACT FROM AUTHOR]

A growing number of studies suggest that the frequency of numeracy experiences that parents provide at home may relate to children's mathematical development. However, the relation between home numeracy practices and children's numerical skills is complex and might depend upon both the type and difficulty of activities, as well as the type of math skills. Studies have also argued that this relation may be driven by factors that are not systematically controlled for in the literature, including socio-economic status (SES), parental math skills and children's IQ. Finally, as most prior studies have focused on preschoolers, it remains unclear to what extent there remains a relation between the home numeracy environment and math skills when children are in elementary school. In the present study, we tested an extensive range of math skills in 66 8-year-olds, including non-symbolic quantity processing, symbolic number understanding, transcoding, counting, and mental arithmetic. We also asked parents to complete a questionnaire about their SES, academic expectations, academic attitudes, and the numeracy practices that they provide at home. Finally, we measured their arithmetic fluency as a proxy for parental math skills. Over and above differences in socio-economic status, parental arithmetic fluency, child's IQ, and time spent with the child, we found a positive relation between the frequency of formal numeracy practices that were at or above grade level and two separate measures of mental arithmetic. We further found that the frequency of these advanced formal numeracy practices was related to parents' academic expectations. Therefore, our study shows that home numeracy experiences predict arithmetic skills in elementary school children, but only when those activities are formal and sufficiently challenging for children. [ABSTRACT FROM AUTHOR]

fMRI is the preeminent method for collecting signals from the human brain in vivo, for using these signals in the service of functional discovery, and relating these discoveries to anatomical structure. Numerous computational and mathematical techniques have been deployed to extract information from the fMRI signal. Yet, the application of Topological Data Analyses (TDA) remain limited to certain sub-areas such as connectomics (that is, with summarized versions of fMRI data). While connectomics is a natural and important area of application of TDA, applications of TDA in the service of extracting structure from the (non-summarized) fMRI data itself are heretofore nonexistent. "Structure" within fMRI data is determined by dynamic fluctuations in spatially distributed signals over time, and TDA is well positioned to help researchers better characterize mass dynamics of the signal by rigorously capturing shape within it. To accurately motivate this idea, we a) survey an established method in TDA ("persistent homology") to reveal and describe how complex structures can be extracted from data sets generally, and b) describe how persistent homology can be applied specifically to fMRI data. We provide explanations for some of the mathematical underpinnings of TDA (with expository figures), building ideas in the following sequence: a) fMRI researchers can and should use TDA to extract structure from their data; b) this extraction serves an important role in the endeavor of functional discovery, and c) TDA approaches can complement other established approaches toward fMRI analyses (for which we provide examples). We also provide detailed applications of TDA to fMRI data collected using established paradigms, and offer our software pipeline for readers interested in emulating our methods. This working overview is both an inter-disciplinary synthesis of ideas (to draw researchers in TDA and fMRI toward each other) and a detailed description of methods that can motivate collaborative research. [ABSTRACT FROM AUTHOR]

The shutdown of schools in response to the rapid spread of COVID-19 poses risks to the education of young children, including a widening education gap. In the present article, we investigate how school closures in 2020 influenced the performance of German students in a curriculum-based online learning software for mathematics. We analyzed data from more than 2,500 K-12 students who computed over 124,000 mathematical problem sets before and during the shutdown, and found that students' performance increased during the shutdown of schools in 2020 relative to the year before. Our analyses also revealed that low-achieving students showed greater improvements in performance than high-achieving students, suggesting a narrowing gap in performance between low- and high-achieving students. We conclude that online learning environments may be effective in preventing educational losses associated with current and future shutdowns of schools. [ABSTRACT FROM AUTHOR]

The five Platonic solids—tetrahedron, cube, octahedron, dodecahedron, and icosahedron—have found many applications in mathematics, science, and art. Path planning for the Platonic solids had been suggested, but not validated, except for solving the rolling-cube puzzles for a cubic dice. We developed a path-planning algorithm based on the breadth-first-search algorithm that generates a shortest path for each Platonic solid to reach a desired pose, including position and orientation, from an initial one on prescribed grids by edge-rolling. While it is straightforward to generate triangular and square grids, various methods exist for regular-pentagon tiling. We chose the Penrose tiling because it has five-fold symmetry. We discovered that a tetrahedron could achieve only one orientation for a particular position. [ABSTRACT FROM AUTHOR]

Content addition to courses and its subsequent correct sequencing in a study plan or curricula design context determine the success (and, in some cases, the failure) of such study plan in the acquisition of knowledge by students. In this work, we propose a decision model to guide curricular design committees in the tasks of course selection and sequencing in higher education contexts using a novel methodology based on network analysis. In this work, the local and global properties stemming from complex network analysis tools are studied in detail to facilitate the design of the study plan and to ensure its coherence by detecting the communities within a graph, and the local and global centrality of the courses and their dependencies are analyzed, as well as the overlapping subgroups and the functions and different positions among them. The proposed methodology is applied to the study of a real case at the Universidad Rey Juan Carlos. [ABSTRACT FROM AUTHOR]

We analyse academic success using a genealogical approach to the careers of over 95,000 scientists in mathematics and associated fields in physics and chemistry. We look at the effect of Ph.D. supervisors (one's mentors) on the number of Ph.D. students that one supervises later on (one's mentees) as a measure of academic success. Supervisors generally provide important inputs in Ph.D. projects, which can have long-lasting effects on academic careers. Moreover, having multiple supervisors exposes one to a diversity of inputs. We show that Ph.D. students benefit from having multiple supervisors instead of a single one. The cognitive diversity of mentors has a subtler effect in that it increases both the likelihood of success (having many mentees later on) and failure (having no mentees at all later on). We understand the effect of diverse mentorship as a high-risk, high-gain strategy: the recombination of unrelated expertise often fails, but sometimes leads to true novelty. [ABSTRACT FROM AUTHOR]

This study addresses the pressing issue of how to raise the performance of disadvantaged students in mathematics. We combined established findings on effective instruction with emerging research addressing the specific needs of disadvantaged students. A sample of N = 260 disadvantaged 6th-graders received 4 weeks (15 lessons) of fraction instruction either as usual or evidence-based instruction, with and without digital learning support (i.e., interactivity, adaptivity, and immediate explanatory feedback). To examine the sustainability of effects, we assessed students' fraction knowledge immediately after the 4 weeks and once again after a period of additional 8 weeks. Generalized linear mixed models revealed that students only benefitted from evidence-based instruction if digital support was available in addition. Digital support principles implemented in evidence-based instruction helped disadvantaged students to acquire mathematics knowledge—and to maintain this knowledge. [ABSTRACT FROM AUTHOR]

Individuals with Mathematics Learning Disabilities have persistent mathematics underperformance but vary with respect to their cognitive profiles. The present study examined mathematics ability and achievement, and associated mathematics-specific numerical skills and domain-general cognitive abilities, in young children with Turner syndrome compared to their matched peers. We utilized two independent peer groups so that group comparisons would account for verbal skills, a hypothesized strength of girls with Turner syndrome, and nonsymbolic magnitude comparison skills, a hypothesized difference of girls with Turner syndrome. This individual matching approach afforded characterization of mathematics profiles of girls with Turner syndrome and girls without Turner syndrome that share potential key features of the Turner syndrome phenotype. Results indicated differences in mathematics ability and nonsymbolic magnitude comparison tasks between girls with Turner syndrome and peers with similar levels of verbal skill. Mathematics ability and mathematics achievement scores of girls with Turner syndrome did not differ significantly from their peers with similar levels of accuracy on a nonsymbolic magnitude comparison task. Cognitive correlates of mathematics outcomes showed disparate patterns across groups. These quantitative and qualitative differences across profiles enhance our understanding of variation in mathematics ability in early childhood and inform how mathematics skills develop in young children with or without Turner syndrome. [ABSTRACT FROM AUTHOR]

In the research on mathematics education, numerous Likert-type instruments estimating attitudes toward mathematics are sometimes composed of factors with a high correlation, which can make it difficult to assign the statements from the scale to each estimated factor. Further, the measurement of attitudes is usually done by adding the scores but ignoring the existence of possible differences in the importance that each item can have in its factor estimation. A revision of the methodology for the study of attitudes toward mathematics for the correct validation of the instrument is carried out in this research, and an estimation of the factors of attitude is proposed using the calculation of the weighted average of scores based on the importance that each item has in the explanation of its factor, which is given by a structural equation model. This methodology has been applied to Auzmendi's scale of attitudes toward mathematics measurement in a sample of 1293 university students. The factors were estimated using simple and weighted averages; significant differences have been obtained in the measurements, as well on those shown with the organization proposed by Auzmendi. [ABSTRACT FROM AUTHOR]

In a cross-sectional study of youth ages 8–15, we examined implicit and explicit gender stereotypes regarding math and language abilities. We investigated how implicit and explicit stereotypes differ across age and gender groups and whether they are consistent with cultural stereotypes. Participants (N = 270) completed the Affect Misattribution Procedure (AMP) and a survey of explicit beliefs. Across all ages, boys showed neither math nor language implicit gender biases, whereas girls implicitly favored girls in both domains. These findings are counter to cultural stereotypes, which favor boys in math. On the explicit measure, both boys' and girls' primary tendency was to favor girls in math and language ability, with the exception of elementary school boys, who rated genders equally. We conclude that objective gender differences in academic success guide differences in children's explicit reports and implicit biases. [ABSTRACT FROM AUTHOR]

Mathematics is often promoted as endowing those who study it with transferable skills such as an ability to think logically and critically or to have improved investigative skills, resourcefulness and creativity in problem solving. However, there is scant evidence to back up such claims. This project tested participants with increasing levels of mathematics training on 11 well-studied rational and logical reasoning tasks aggregated from various psychological studies. These tasks, that included the Cognitive Reflection Test and the Wason Selection Task, are of particular interest as they have typically and reliably eluded participants in all studies, and results have been uncorrelated with general intelligence, education levels and other demographic information. The results in this study revealed that in general the greater the mathematics training of the participant, the more tasks were completed correctly, and that performance on some tasks was also associated with performance on others not traditionally associated. A ceiling effect also emerged. The work is deconstructed from the viewpoint of adding to the platform from which to approach the greater, and more scientifically elusive, question: are any skills associated with mathematics training innate or do they arise from skills transfer? [ABSTRACT FROM AUTHOR]

We examined reading, spelling, and mathematical skills in an unselected group of 129 Italian fifth graders by testing various cognitive predictors for each behaviour. As dependent variables, we measured performance in behaviours with a clear functional value in everyday life, such as reading a text, spelling under dictation and doing mental and written computations. As predictors, we selected cognitive dimensions having an explicit relation with the target behaviour (called proximal predictors), and prepared various tests in order to select which task had the best predictive power on each behaviour. The aim was to develop a model of proximal predictors of reading (speed and accuracy), spelling (accuracy) and maths (speed and accuracy) characterized by efficacy also in comparison to the prediction based on general cognitive factors (i.e., short-term memory, phonemic verbal fluency, visual perceptual speed, and non-verbal intelligence) and parsimony, pinpointing the role of both common and unique predictors as envisaged in the general perspective of co-morbidity. With one exception (reading accuracy), the proximal predictors models (based on communality analyses) explained a sizeable amount of variance, ranging from 27.5% in the case of calculation (accuracy) to 48.7% of reading (fluency). Models based on general cognitive factors also accounted for some variance (ranging from 6.5% in the case of spelling to 19.5% in the case of reading fluency) but this was appreciably less than that explained by models based on the hypothesized proximal predictors. In general, results confirmed the efficacy of proximal models in predicting reading, spelling and maths although they offered only limited support for common predictors across different learning skills; namely, performance in the Orthographic Decision test entered as a predictor of both reading and spelling indicating that a single orthographic lexicon may account for performance in reading and spelling. Possible lines of research to expand on this approach are illustrated. [ABSTRACT FROM AUTHOR]

Objectives: Soccer leagues reflect the partial standings of the teams involved after each round of competition. However, the ability of partial league standings to predict end-of-season position has largely been ignored. Here we analyze historical partial standings from English soccer to understand the mathematics underpinning league performance and evaluate the predictive 'power' of partial standings. Methods: Match data (1995–2017) from the four senior English leagues was analyzed, together with random match scores generated for hypothetical leagues of equivalent size. For each season the partial standings were computed and Kendall's normalized tau-distance and Spearman r-values determined. Best-fit power-law and logarithmic functions were applied to the respective tau-distance and Spearman curves, with the 'goodness-of-fit' assessed using the R2 value. The predictive ability of the partial standings was evaluated by computing the transition probabilities between the standings at rounds 10, 20 and 30 and the final end-of-season standings for the 22 seasons. The impact of reordering match fixtures was also evaluated. Results: All four English leagues behaved similarly, irrespective of the teams involved, with the tau-distance conforming closely to a power law (R2>0.80) and the Spearman r-value obeying a logarithmic function (R2>0.87). The randomized leagues also conformed to a power-law, but had a different shape. In the English leagues, team position relative to end-of-season standing became 'fixed' much earlier in the season than was the case with the randomized leagues. In the Premier League, 76.9% of the variance in the final standings was explained by round-10, 87.0% by round-20, and 93.9% by round-30. Reordering of match fixtures appeared to alter the shape of the tau-distance curves. Conclusions: All soccer leagues appear to conform to mathematical laws, which constrain the league standings as the season progresses. This means that partial standings can be used to predict end-of-season league position with reasonable accuracy. [ABSTRACT FROM AUTHOR]

Students in many western countries struggle to achieve acceptable standards in numeracy despite its recognition as an important 21st century skill. As commercial math programs remain a staple of classroom instruction, investigations of their effectiveness are essential to inform decision-making regarding how to invest limited resources while maximizing student gains. We conducted a cluster randomized-controlled trial of the effectiveness of JUMP Math, a distinctive math program whose central tenets are empirically supported, for improving elementary math achievement (clinical trial.gov no. NCT02456181). The study involved 554 grade 2 (primary) and 592 grade 5 (junior) students and 193 teachers in 41 schools, in an urban-rural Canadian school board. Schools were randomly assigned to use either JUMP Math or their business-as-usual, problem-based approach to math instruction. We tracked student progress in math achievement on standardized and curriculum-based measures of computation and problem solving, for 2 consecutive school years. Junior students taught with JUMP Math made significantly greater progress in computation than their non-JUMP peers but the groups did not differ significantly in problem solving. Effects took hold relatively quickly, replicating the results from an earlier pilot study. Primary students in the non-JUMP group made significantly greater gains in problem solving and computation in year 1. But those taught with JUMP Math made significantly greater gains in problem solving and the groups did not differ in computation, in year 2. The positive effects of JUMP Math are noteworthy given that the JUMP Math teachers were likely still adjusting to the new program. That these positive findings were obtained in an effectiveness study (i.e. in real-world conditions), suggests that JUMP Math may be a valuable evidence-based addition to the teacher's toolbox. Given the importance of numeracy for 21st century functioning, identifying and implementing effective math instruction programs could have far-reaching, positive implications. [ABSTRACT FROM AUTHOR]

Visual selective attention acts as a filter on perceptual information, facilitating learning and inference about important events in an agent's environment. A role for visual attention in reward-based decisions has previously been demonstrated, but it remains unclear how visual attention is recruited during aversive learning, particularly when learning about multiple stimuli concurrently. This question is of particular importance in psychopathology, where enhanced attention to threat is a putative feature of pathological anxiety. Using an aversive reversal learning task that required subjects to learn, and exploit, predictions about multiple stimuli, we show that the allocation of visual attention is influenced significantly by aversive value but not by uncertainty. Moreover, this relationship is bidirectional in that attention biases value updates for attended stimuli, resulting in heightened value estimates. Our findings have implications for understanding biased attention in psychopathology and support a role for learning in the expression of threat-related attentional biases in anxiety. [ABSTRACT FROM AUTHOR]

Studies conducted in time series could be far more informative than those that only capture a specific moment in time. However, when it comes to transcriptomic data, time points are sparse creating the need for a constant search for methods capable of extracting information out of experiments of this kind. We propose a feature selection algorithm embedded in a hidden Markov model applied to gene expression time course data on either single or even multiple biological conditions. For the latter, in a simple case-control study features or genes are selected under the assumption of no change over time for the control samples, while the case group must have at least one change. The proposed model reduces the feature space according to a two-state hidden Markov model. The two states define change/no-change in gene expression. Features are ranked in consonance with three scores: number of changes across time, magnitude of such changes and quality of replicates as a measure of how much they deviate from the mean. An important highlight is that this strategy overcomes the few samples limitation, common in transcriptome experiments through a process of data transformation and rearrangement. To prove this method, our strategy was applied to three publicly available data sets. Results show that feature domain is reduced by up to 90% leaving only few but relevant features yet with findings consistent to those previously reported. Moreover, our strategy proved to be robust, stable and working on studies where sample size is an issue otherwise. Hence, even with two biological replicates and/or three time points our method proves to work well. [ABSTRACT FROM AUTHOR]

We examined the influence of linear perspective cues and texture gradients in the perceptual rescaling of stimuli over a highly-salient Ponzo illusion of a corridor. We performed two experiments using the Method of Constant Stimuli where participants judged the size of one of two rings. In experiment 1, one ring was presented in the upper visual-field at the end of the corridor and the other in the lower visual-field at the front of the corridor. The perceived size of the top and bottom rings changed as a function of the availability of linear perspective and textures. In experiment 2, only one ring was presented either at the top or the bottom of the image. The perceived size of the top but not the bottom ring changed as a function of the availability of linear perspective and textures. In both experiments, the effects of the cues were additive. Perceptual rescaling was also stronger for the top compared to the bottom ring. Additional eye-tracking revealed that participants tended to gaze more in the upper than the lower visual-field. These findings indicate that top-down mechanisms provide an important contribution to the Ponzo illusion. Nonetheless, additional maximum likelihood estimation analyses revealed that linear perspective fulfilled a greater contribution in experiment 2, which is suggestive of a bottom-up mechanism. We conclude that both top-down and bottom-up mechanisms play important roles. However, the former seems to fulfil a more prominent role when both stimuli are presented in the image. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the dependability and accuracy of midkine (MK) in the diagnosis of hepatocellular carcinoma (HCC). Methods: PubMed, EMBASE, Web of Science, China Biology Medicine disc and grey literature sources were searched from the date of database inception to January 2019. Two authors (B-H.Z. and B.L.) independently extracted the data and evaluated the study quality using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. The sensitivity, specificity, positive likelihood ratio (LR+) and negative likelihood ratio (LR−) were estimated using a bivariate model. Moreover, hierarchical summary receiver operating characteristic curves were generated. The diagnostic odds ratio (DOR) and area under the curve (AUC) were pooled using a univariate model. Results: Nine articles (11 studies) were included (1941 participants). The bivariate analysis revealed that the sensitivity and specificity of MK for HCC diagnosis were 0.85 (95% CI 0.78–0.91) and 0.83 (95% CI 0.76–0.88), respectively. We also found a LR+ of 5.05 (95% CI 3.33–7.40), a LR− of 0.18 (95% CI 0.11–0.28), a DOR of 31.74 (95% CI 13.98–72.09) and an AUC of 0.91 (95% CI 0.84–0.99). Subgroup analyses showed that MK provided the best efficiency for HCC diagnosis when the cutoff value was greater than 0.5 ng/mL. Conclusions: MK has an excellent diagnostic value for hepatocellular carcinoma. [ABSTRACT FROM AUTHOR]

Forecasting extremely rare events is a pressing problem, but efforts to model such outcomes are often limited by the presence of multiple causes within classes of events, insufficient observations of the outcome to assess fit, and biased estimates due to insufficient observations of the outcome. We introduce a novel approach for analyzing rare event data that addresses these challenges by turning attention to the conditions under which rare outcomes do not occur. We detail how configurational methods can be used to identify conditions or sets of conditions that would preclude the occurrence of a rare outcome. Results from Monte Carlo experiments show that our approach can be used to systematically preclude up to 78.6% of observations, and application to ground-truth data coupled with a bootstrap inferential test illustrates how our approach can also yield novel substantive insights that are obscured by standard statistical analyses. [ABSTRACT FROM AUTHOR]

Roe deer (Capreolus capreolus) is the most abundant cervid in Europe and, as such, has a considerable impact over several human activities. Accurate roe deer population size estimates are useful to ensure their proper management. We tested 3 methods for estimating roe deer abundance (drive counts, pellet-group counts, and camera trapping) during two consecutive years (2012 and 2013) in the Apennines (Italy) in order to assess their precision and applicability. During the study period, population density estimates were: drive counts 21.89±12.74 roe deer/km2 and pellet-group counts 18.74±2.31 roe deer/km2 in 2012; drive counts 19.32±11.12 roe deer/km2 and camera trapping 29.05±7.48 roe deer/km2 in 2013. Precision of the density estimates differed widely among the 3 methods, with coefficients of variation ranging from 12% (pellet-group counts) to 58% (drive counts). Drive counts represented the most demanding method on account of the higher number of operators involved. Pellet-group counts yielded the most precise results and required a smaller number of operators, though the sampling effort was considerable. When compared to the other two methods, camera trapping resulted in an intermediate level of precision and required the lowest sampling effort. We also discussed field protocols of each method, considering that volunteers, rather than technicians, will more likely be appointed for these tasks in the near future. For this reason, we strongly suggest that for each method managers of population density monitoring projects take into account ease of use as well as the quality of the results obtained and the resources required. [ABSTRACT FROM AUTHOR]

This systematic review and meta-analysis aimed to examine the effects of physical exercise cum cognitive-behavioural therapy (CBT) on alleviating pain intensity, functional disabilities, and mood/mental symptoms in those suffering with chronic musculoskeletal pain. MEDLINE, EMBASE, PubMEd, PsycINFO and CINAHL were searched to identify relevant randomised controlled trials from inception to 31 December 2018. The inclusion criteria were: (a) adults ≥18 years old with chronic musculoskeletal pain ≥3 months, (b) randomised controlled design, (c) a treatment arm consisting of physical intervention and CBT combined, (d) the comparison arm being waitlist, usual care or other non-pharmacological interventions such as physical exercise or CBT alone, and (e) outcomes including pain intensity, pain-related functional disabilities (primary outcomes), or mood/mental symptoms (secondary outcome). The exclusion criteria were: (a) the presence of comorbid mental illnesses other than depression and anxiety and (b) non-English publication. The search resulted in 1696 records and 18 articles were selected for review. Results varied greatly across studies, with most studies reporting null or small effects but a few studies reporting very large effects up to 2-year follow-up. Pooled effect sizes (Hedges' g) were ~1.00 for pain intensity and functional disability, but no effect was found for mood/mental symptoms. The effects were mainly driven by several studies reporting unusually large differences between the exercise cum CBT intervention and exercise alone. When these outliers were removed, the effect on pain intensity disappeared at post-intervention while a weak effect (g = 0.21) favouring the combined intervention remained at follow-up assessment. More consistent effects were observed for functional disability, though the effects were small (g = 0.26 and 0.37 at post-intervention and follow-up respectively). More importantly, the value of adding CBT to exercise interventions is questionable, as consistent benefits were not seen. The clinical implications and directions for future research are discussed. [ABSTRACT FROM AUTHOR]

Many real systems can be described by a set of interacting entities forming a complex network. To some surprise, these have been shown to share a number of structural properties regardless of their type or origin. It is thus of vital importance to design simple and intuitive models that can explain their intrinsic structure and dynamics. These can, for instance, be used to study networks analytically or to construct networks not observed in real life. Most models proposed in the literature are of two types. A model can be either static, where edges are added between a fixed set of nodes according to some predefined rule, or evolving, where the number of nodes or edges increases over time. However, some real networks do not grow but rather shrink, meaning that the number of nodes or edges decreases over time. We here propose a simple model of shrinking networks called the war pact model. We show that networks generated in such a way exhibit common structural properties of real networks. Furthermore, compared to classical models, these resemble international trade, correlates of war, Bitcoin transactions and other networks more closely. Network shrinking may therefore represent a reasonable explanation of the evolution of some networks and greater emphasis should be put on such models in the future. [ABSTRACT FROM AUTHOR]

Fertility in Ghana has declined steadily since 1980, however, a slight increase was observed between 2008 and 2014. While several factors may account for this pattern, research on the contribution of type of union is limited. This study examined differentials in the fertility of women in different types of union. Secondary data from 6,285 (weighted) ever-married women aged 15–49 years were analysed using compare means, t-test, analysis of variance, Poisson and binary logistic regression analyses. The findings indicate that, independent of other factors, fertility among remarried women is higher compared to first-time married women but this does not hold true when other factors are controlled for. Additionally, there was no significant difference in the fertility of remarried women who were in union and women who were in union in a first-time marriage. However, compared to remarried women who were currently in a union, fertility was significantly lower among remarried women who were not currently in union (β = -0.121, p<0.01) and women who have been married only once but were not currently in union (β = -0.212, p<0.001). Further analysis revealed that remarried women were significantly more likely to desire more children and less likely to use any method of contraception compared to first-time married women. There is the need for further research to better understand the fertility needs of remarried women. [ABSTRACT FROM AUTHOR]

The practice of early marriage, although acknowledged as a human rights violation, continues to occur in many countries. Different studies have identified the associated factors in many developing countries. However, these factors often assume no geographical variation in these factors within countries. Again, cultural practices and beliefs which strongly influence the acceptance and practices of early marriage vary geographically. In addition, geographic clusters of high rates of early marriage and union formation are also unknown. Thus, area specific correlates of early child marriage are required for the development of location specific policies to aid the eradication of early child marriage. Using data from the 2010 Ghana Population and Housing Census, this study examines the extent of geospatial clustering in early marriage amongst girls and their spatially-varying associated factors at the district level. The findings reveal strong clustering of high early marriage amongst districts in the Upper West, Northern and Volta regions. Nationally, 6.96% (CI = 6.83, 7.08) of girls are married or in union before their 18th birthday. The estimates range from 2.7% in the Jaman North district in Brong Ahafo region to 19.0% in the Gushiegu district in Northern region. Economic factors were observed as important spatially-varying associated factors. The findings suggest that targeted interventions are required in the effort to eradicate the practice in Ghana. [ABSTRACT FROM AUTHOR]

To enrich any model and its dynamics introduction of delay is useful, that models a precise description of real-life phenomena. Differential equations in which current time derivatives count on the solution and its derivatives at a prior time are known as delay differential equations (DDEs). In this study, we are introducing new techniques for finding the numerical solution of fractional delay differential equations (FDDEs) based on the application of neural minimization (NM) by utilizing Chebyshev simulated annealing neural network (ChSANN) and Legendre simulated annealing neural network (LSANN). The main purpose of using Chebyshev and Legendre polynomials, along with simulated annealing (SA), is to reduce mean square error (MSE) that leads to more accurate numerical approximations. This study provides the application of ChSANN and LSANN for solving DDEs and FDDEs. Proposed schemes can be effortlessly executed by using Mathematica or MATLAB software to get explicit solutions. Computational outcomes are depicted, for various numerical experiments, numerically and graphically with error analysis to demonstrate the accuracy and efficiency of the methods. [ABSTRACT FROM AUTHOR]

Recent research shows that preschool children born to opioid-dependent mothers are at increased risk for cognitive, psychomotor, attention, and social-emotional adjustment problems. But very little is known about their school-age functioning, particularly their educational achievement. This analysis examined the educational outcomes of a regional cohort of 100 prenatally methadone-exposed children who were prospectively studied from birth to age 9.5 years alongside a comparison group of 110 randomly identified non-exposed children born between 2003 and 2008. At age 9.5, as part of a comprehensive neurodevelopmental evaluation, children's teachers rated their achievement across the school curriculum, and children completed the Woodcock Johnson-III Tests of Achievement (WJ-III). Detailed information about the birth mother's social background, pregnancy substance use, and mental health was also collected during pregnancy/at term. Infant clinical data were collected after birth. Methadone-exposed children performed less well than non-exposed children across seven school curriculum areas rated by teachers (ps ≤.001), performed less well than non-exposed children on all reading and mathematics subtests of the WJ-III, and had higher rates of any educational delay on the WJ-III (57% vs. 15%), OR = 7.47 (3.71–15.02). Results were similar when children with severe intellectual impairment were excluded. After adjusting for confounding factors, methadone-exposed children had increased odds of educational delay, but this was only marginally significant (OR = 3.62, [1.01–13.01], p = .049). Maternal educational attainment level (OR = 0.69, [0.50–0.89], p = .006), and maternal benzodiazepine use during pregnancy (OR = 2.70 [1.03–7.12], p = .044) were also associated with later educational risk. Findings suggest that children born to opioid-dependent women enrolled in methadone maintenance are at high risk of educational delay by age 9.5 years. Children's academic difficulties appeared to reflect the effects of both adverse prenatal exposures and postnatal social risk. [ABSTRACT FROM AUTHOR]

Context: Whether all degrees of periventricular leukomalacia (PVL) and peri-intraventricular haemorrhage (PIVH) have a negative impact on neurodevelopment. Objective: To determine the impact of PVL and PIVH in the incidence of cerebral palsy, sensorineural impairment and development scores in preterm neonates. Registered in PROSPERO (CRD42017073113). Data sources: PubMed, Embase, SciELO, LILACS, and Cochrane databases. Study selection: Prospective cohort studies evaluating neurodevelopment in children born preterm which performed brain imaging in the neonatal period. Data extraction: Two independent researchers extracted data using a predesigned data extraction sheet. Statistical methods: A random-effects model was used, with Mantel-Haenszel approach and a Sidik-Jonkman method for the estimation of variances, combined with Hartung-Knapp-Sidik-Jonkman correction. Heterogeneity was assessed through the I2 statistic and sensitivity analysis were performed when possible. No funnel plots were generated but publication bias was discussed as a possible limitation. Results: Our analysis concluded premature children with any degree of PIVH are at increased risk for cerebral palsy (CP) when compared to children with no PIVH (3.4, 95% CI 1.60–7.22; 9 studies), a finding that persisted on subgroup analysis for studies with mean birth weight of less than 1000 grams. Similarly, PVL was associated with CP, both in its cystic (19.12, 95% CI 4.57–79.90; 2 studies) and non-cystic form (9.27, 95% CI 5.93–14.50; 2 studies). We also found children with cystic PVL may be at risk for visual and hearing impairment compared to normal children, but evidence is weak. Limitations: Major limitations were the lack of data for PVL in general, especially for the outcome of neurodevelopment, the high heterogeneity among methods used to assess neurodevelopment and the small number of studies, which led to meta-analysis with high heterogeneity and wide confidence intervals. Conclusions: There was no evidence supporting the hypothesis that PIVH causes impairment in neuropsychomotor development in our meta-analysis, but review of newer studies show an increased risk for lower intelligence scores in children with severe lesions, both PIVH and PVL. There is evidence to support the hypothesis that children with any degree of PIVH, especially those born below 1000 grams and those with severe haemorrhage, are at increased risk of developing CP, as well as children with PVL, both cystic and non-cystic. [ABSTRACT FROM AUTHOR]

Background: In patients with left heart failure, micro-RNAs (miRNAs) have been shown to be of diagnostic and prognostic value. The present study aims to identify those miRNAs in patients with univentricular heart (UVH) disease that may be associated with overt heart failure. Methods: A large panel of human miRNA arrays were used to determine miRNA expression profiles in the blood of 48 UVH patients and 32 healthy controls. For further selection, the most abundantly expressed miRNA arrays were related to clinical measures of heart failure and selected miRNAs validated by polymerase chain reaction were used for the prediction of overt heart failure and all-cause mortality. Results: According to microarray analysis, 50 miRNAs were found to be significantly abundant in UVH patients of which miR-150-5p was best related to heart failure parameters. According to ROC analysis, NT-proBNP levels (AUC 0.940, 95% CI 0.873–1.000; p = 0.001), miR-150-5p (AUC 0.905, 95% CI 0.779–1.000; p = 0.001) and a higher NYHA class ≥ III (AUC 0.893, 95% CI 0.713–1.000; p = 0.002) were the 3 most significant predictors of overt heart failure. Using a combined biomarker model, AUC increased to 0.980 indicating an additive value of miR-150-5p. Moreover, in the multivariate analysis, a higher NYHA class ≥ III (p = 0.005) and miR-150-5p (p = 0.006) turned out to be independent predictors of overt heart failure. Conclusion: In patients with UVH, miR-150-5p is an independent predictor of overt heart failure and thus may be used in the risk assessment of these patients. [ABSTRACT FROM AUTHOR]

Objectives: To investigate effects of postural changes and bladder distention on intrabladder pressure whilst estimating intra-abdominal pressure in horses. Design: Two-year cohort study. Patients admitted for elective surgical procedures unrelated to gastrointestinal or genitourinary tract. Setting: School of Agricultural and Veterinarian Sciences, Jaboticabal, SP, Brazil. Animals: 20 adult horses, 11 males (stallions and geldings) and 9 females; between 3.5 and 12 years, weighing 350 to 500 kg. Interventions: Intra-abdominal pressure was directly-recorded through abdominocentesis at the ventral midline with a fluid-filled system. Intrabladder pressure was obtained from a bladder catheter with the fluid-filled system zeroed at the level of the tuber ischia with patients in dorsal recumbency or pubic symphysis if in lateral recumbency. Measurements and main results: Body position directly influenced intra-abdominal pressure. In dorsal recumbency, intra-abdominal pressure differed (p < 0.05) from intrabladder pressure at end-inspiration and end-expiration regardless of whether the bladder was empty or distended. There was no correlation nor association between the two pressures in this body position. In lateral recumbency a difference (p <0.05) between intra-abdominal pressure and intrabladder pressure was recorded at end-inspiration with the bladder distended with 25 ml, and at end-expiration for distension volumes of 25 ml and 50 ml. There was a strong correlation between both pressures for left and right lateral recumbency, regardless of the distension volume. Ordinary least product (OLP) regression analysis showed no fixed or proportional bias between both pressures for distension volume of 50 ml, at both end-inspiration and end-expiration. Conclusions: Indirect assessment of equine intra-abdominal pressure cannot be made in dorsal recumbency. For that purpose, patients should be in left lateral recumbency with the bladder distended with 50 ml. Values can be recorded at end-inspiration or end-expiration. Restriction: Occlusion of the catheter tip by the bladder wall when minimally distended. [ABSTRACT FROM AUTHOR]

Background: Dietary management is highly important for the maintenance of renal function in patients with chronic kidney disease (CKD). Cerebral oxygen saturation (rSO2) was reportedly associated with the estimated glomerular filtration rate (eGFR) and cognitive function. However, data concerning the association between cerebral rSO2 and dietary intake of CKD patients is limited. Methods: This was a single-center observational study. We recruited 67 CKD patients not undergoing dialysis. Cerebral rSO2 was monitored using the INVOS 5100c oxygen saturation monitor. Energy intake was evaluated by dietitians based on 3-day meal records. Daily protein and salt intakes were calculated from 24-h urine collection. Results: Multivariable regression analysis showed that cerebral rSO2 was independently associated with energy intake (standardized coefficient: 0.370) and serum albumin concentration (standardized coefficient: 0.236) in Model 1 using parameters with p < 0.10 in simple linear regression analysis (body mass index, Hb level, serum albumin concentration, salt and energy intake) and confounding factors (eGFR, serum sodium concentration, protein intake), and the energy/salt index (standardized coefficient: 0.343) and Hb level (standardized coefficient: 0.284) in Model 2 using energy/protein index as indicated by energy intake/protein intake and energy/salt index by energy intake/salt intake in place of salt, protein and energy intake. Conclusions: Cerebral rSO2 is affected by energy intake, energy/salt index, serum albumin concentration and Hb level. Sufficient energy intake and adequate salt restriction is important to prevent deterioration of cerebral oxygenation, which might contribute to the maintenance of cognitive function in addition to the prevention of renal dysfunction in CKD patients. [ABSTRACT FROM AUTHOR]

Production risk has been ignored in most of the analysis of GM technology, which has mostly focused on its effects on mean yield. We use stochastic dominance to quantify the effect of GM traits on the entire distribution of yields in corn in the USA under a wide range of growing conditions. Although no GM hybrid outperforms conventional hybrids under all growing conditions, we present evidence that most GM hybrids can be considered as improvements of the yield distribution. [ABSTRACT FROM AUTHOR]

The development of automatic methods for segmenting anatomy from medical images is an important goal for many medical and healthcare research areas. Datasets that can be used to train and test computer algorithms, however, are often small due to the difficulties in obtaining experts to segment enough examples. Citizen science provides a potential solution to this problem but the feasibility of using the public to identify and segment anatomy in a medical image has not been investigated. Our study therefore aimed to explore the feasibility, in terms of performance and motivation, of using citizens for such purposes. Public involvement was woven into the study design and evaluation. Twenty-nine citizens were recruited and, after brief training, asked to segment the spine from a dataset of 150 magnetic resonance images. Participants segmented as many images as they could within three one-hour sessions. Their accuracy was evaluated by comparing them, as individuals and as a combined consensus, to the segmentations of three experts. Questionnaires and a focus group were used to determine the citizens' motivation for taking part and their experience of the study. Citizen segmentation accuracy, in terms of agreement with the expert consensus segmentation, varied considerably between individual citizens. The citizen consensus, however, was close to the expert consensus, indicating that when pooled, citizens may be able to replace or supplement experts for generating large image datasets. Personal interest and a desire to help were the two most common reasons for taking part in the study. [ABSTRACT FROM AUTHOR]

The problem of handling non-ignorable non-response has been typically addressed under the design-based approach using the well-known sub-sampling technique introduced by Hansen and Hurwitz [1946, Journal of the American Statistical Association, Vol 41(236), Page 517- 529]. Alternatively, the model-based paradigm emphasizes on utilizing the underlying model relationship between the outcome variable and one or more covariate(s) whose population values are known prior to the survey. This article utilizes the model relationship between the study variable and covariate(s) for handling non-ignorable non-response and obtaining an unbiased estimator for the population total under the sub-sampling technique. The main idea is to combine the estimates obtained from the sample on first call and the sub-sample from second call using separate model relationships. The contribution of this paper helps us in providing unbiased estimates with an improved efficiency under model-based paradigm in presence of non-ignorable non-response. The provided method is more economical than the available estimators under callback methods as we are working sub-sampling and also increase response rate as a stronger mode of interview is employed for data collection. A numerical study using Monte Carlo is presented to illustrate the behavior of the proposed and the efficiency comparison. [ABSTRACT FROM AUTHOR]

Slope one is a popular recommendation algorithm due to its simplicity and high efficiency for sparse data. However, it often suffers from under-fitting since the global information of all relevant users/items are considered. In this paper, we propose a new scheme called enhanced slope one recommendation through local information embedding. First, we employ clustering algorithms to obtain the user clusters as well as item clusters to represent local information. Second, we predict ratings using the local information of users and items in the same cluster. The local information can detect strong localized associations shared within clusters. Third, we design different fusion approaches based on the local information embedding. In this way, both under-fitting and over-fitting problems are alleviated. Experiment results on the real datasets show that our approaches defeats slope one in terms of both mean absolute error and root mean square error. [ABSTRACT FROM AUTHOR]

In recent years, with the development of computer science, deep learning is held as competent enough to solve the problem of inference and learning in high dimensional space. Therefore, it has received unprecedented attention from both the academia and the business community. Compared with CPU/GPU, FPGA has attracted much attention for its high-energy efficiency, short development cycle and reconfigurability in the aspect of deep learning algorithm. However, because of the limited research on OpenCL optimization on FPGA of deep learning algorithms, OpenCL tools and models applied to CPU/GPU cannot be directly used on FPGA. This makes it difficult for software programmers to use FPGA when implementing deep learning algorithms for a rewarding performance. To solve this problem, this paper proposed an OpenCL computational model based on FPGA template architecture to optimize the time-consuming convolution layer in deep learning. The comparison between the program applying the computational model and the corresponding optimization program provided by Xilinx indicates that the former is 8-40 times higher than the latter in terms of performance. [ABSTRACT FROM AUTHOR]