Fourth Order Algorithms for Solving the Multivariable Langevin Equation and the Kramers Equation

We develop a fourth order simulation algorithm for solving the stochastic Langevin equation. The method consists of identifying solvable operators in the Fokker-Planck equation, factorizing the evolution operator for small time steps to fourth order and implementing the factorization process numerically. A key contribution of this work is to show how certain double commutators in the factorization process can be simulated in practice. The method is general, applicable to the multivariable case, and systematic, with known procedures for doing fourth order factorizations. The fourth order convergence of the resulting algorithm allowed very large time steps to be used. In simulating the Brownian dynamics of 121 Yukawa particles in two dimensions, the converged result of a first order algorithm can be obtained by using time steps 50 times as large. To further demostrate the versatility of our method, we derive two new classes of fourth order algorithms for solving the simpler Kramers equation without requiring the derivative of the force. The convergence of many fourth order algorithms for solving this equation are compared.Comment: 19 pages, 2 figure

Learning Analytics: Looking to the Future

This second issue of the Journal of Learning Analytics in 2017 is the first edited by the full new journal editorial team. As the baton is passed on, we would like to thank the founding editors for their work initiating the journal and nurturing its development over the past several years. We look forward to continuing that tradition of excellence. This issue includes four research paper contributions, and a special section on the ‘Shape of Educational Data’. This editorial is also an opportunity for us to reflect on the development of the journal so far, and describe some changes we are making to continue the expansion and maturation of a growing community of learning analytics researchers and practitioners.</jats:p

Towards a Convergent Development of Learning Analytics

In the last 7 years, since the first LAK conference, Learning Analytics has grown rapidly as a field from a small group of interested scholars and practitioners to one of the most scientifically successful and institutionally accepted areas of Learning and Educational Technologies. Learning Analytics is often referred as a "Middle-Space" where experts from diverse fields (from the Learning Sciences, Computer Science, Human-Computer Interaction, Psychology and Behavioural Sciences, just to name a few) share their perspectives on how to better understand and optimize learning processes and environments using this new instrument called Data Science

Reliability of reliability coefficients in the estimation of asymmetry

Although promising to provide insight into the interaction between genotype and environment, investigations into fluctuating asymmetry suffer from a lack of standardization in the reporting of measurement error. In the present paper we show, using both anthropometric and odonto-metric data, that the use of the reliability coefficient calculated for a bilateral measurement provides no indication of the reliability of the corresponding asymmetry estimate, because reliability of asymmetry depends on the relationship between measurement error and the difference between sides. Thus, we suggest that future investigations either provide reliability coefficients for asymmetry estimates specifically, or use methods that account for measurement error. © 1995 Wiley-Liss, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/37671/1/1330960109_ftp.pd

Discovery with Models: A Case Study on Carelessness in Computer-based Science Inquiry

In recent years, an increasing number of analyses in Learning Analytics and Educational Data Mining (EDM) have adopted a &quot;Discovery with Models&quot; approach, where an existing model is used as a key component in a new EDM/analytics analysis. This article presents a theoretical discussion on the emergence of discovery with models, its potential to enhance research on learning and learners, and key lessons learned in how discovery with models can be conducted validly and effectively. We illustrate these issues through discussion of a case study where discovery with models was used to investigate a form of disengaged behavior, i.e., carelessness, in the context of middle school computer-based science inquiry. This behavior has been acknowledged as a problem in education as early as the 1920s. With the increasing use of high-stakes testing, the cost of student carelessness can be higher. For instance, within computer-based learning environments careless errors can result in reduced educational effectiveness, with students continuing to receive material they have already mastered. Despite the importance of this problem, it has received minimal research attention, in part due to difficulties in operationalizing carelessness as a construct. Building from theory on carelessness and a Bayesian framework for knowledge modeling, we use machine-learned detectors to predict carelessness within authentic use of a computer-based learning environment. We then use a discovery with models approach to link these validated carelessness measures to survey data, to study the correlations between the prevalence of carelessness and student goal orientation. The second construct, carelessness, refers to incorrect answers given by a student on material that the student should be able to answer correctly Rodriguez-Fornells &amp; Maydeu-Olivares, 2000). The application of discovery with models involves two main phases. First, a model of a construct is developed using machine learning or knowledge engineering techniques, and is then validated, as discussed below. Second, this validated model is applied to data and used as a component in another analysis: For example, for identifying outliers through model predictions; examining which variables best predict the modeled construct; finding relationships between the construct and other variables using correlations, predictions, associations rules, causal relationships or other methods; or studying the contexts where the construct occurs, including its prevalence across domains, systems, or populations. For example, in One essential question to pose prior to a discovery with model analysis is whether the model adopted is valid, both overall, and for the specific situation in which it is being used. Ideally, a model should be validated using an approach such as cross-validation, where the model is repeatedly trained on one portion of the data and tested on a different portion, with model predictions compared to appropriate external measures, for example assessments made by humans with acceptably high inter-rater reliability, such as field observations of student behavior for gaming the system (cf. Even after validating in this fashion, validity should be re-considered if the model is used for a substantially different population or context than was used when developing the model.. An alternative approach is to use a simpler knowledge-engineered definition, rationally deriving a function/rule that is then applied to the data. In this case, the model can be inferred to have face validity. However, knowledge-engineered models often DISCOVERY WITH MODELS: A CASE STUDY ON CARELESSNESS 6 produce different results than machine learning-based models, for example in the case of gaming the system. Research studying whether student or content is a better predictor of gaming the system identified different results, depending on which model was applied (cf. Baker, 2007a

The MentDis_ICF65+ study protocol: prevalence, 1-year incidence and symptom severity of mental disorders in the elderly and their relationship to impairment, functioning (ICF) and service utilisation.

Background: The EU currently lacks reliable data on the prevalence and incidence of mental disorders in older people. Despite the availability of several national and international epidemiological studies, the size and burden of mental disorders in the elderly remain unclear due to various reasons. Therefore, the aims of the MentDis_ICF65+ study are (1) to adapt existing assessment instruments, and (2) to collect data on the prevalence, the incidence, and the natural course and prognosis of mental disorders in the elderly. Method/design: Using a cross-sectional and prospective longitudinal design, this multi-centre study from six European countries and associated states (Germany, Great Britain, Israel, Italy, Spain, and Switzerland) is based on age-stratified, random samples of elderly people living in the community. The study program consists of three phases: (1) a methodological phase devoted primarily to the adaptation of age- and gender-specific assessment tools for older people (e.g., the Composite International Diagnostic Interview, CIDI) as well as psychometric evaluations including translation, back translation; (2) a baseline community study in all participating countries to assess the lifetime, 12 month and 1 month prevalence and comorbidity of mental disorders, including prior course, quality of life, health care utilization and helpseeking, impairments and participation and, (3) a 12 month follow-up of all baseline participants to monitor course and outcome as well as examine predictors. Discussion: The study is an essential step forward towards the further development and improvement of harmonised instruments for the assessment of mental disorders as well as the evaluation of activity impairment and participation in older adults. This study will also facilitate the comparison of cross-cultural results. These results will have bearing on mental health care in the EU and will offer a starting point for necessary structural changes to be initiated for mental health care policy at the level of mental health care politics

Medium/Long wavelength sensitive opsin diversity in Pitheciidae

New World primates feature a complex colour vision system. Most species have polymorphic colour vision where males have a dichromatic colour perception and females can be either ichromatic or trichromatic. The adaptive value of high allelic diversity of opsins, a light sensitive protein, found in primates’ eyes remains unknown. Studies revealing the allelic diversity are important as they shed light on our understanding of the adaptive value of differences in the colouration of species and their ecologies. Here we investigate the allelic types found in Pitheciidae, an understudied New World primate family, revealing the diversity of medium/long wavelength sensitive opsins both in cryptic and conspicuous species of this primate family. We found five alleles in Cacajao, six in Callicebinae (i.e. Plecturocebus, Cheracebus, and Callicebus), four in Chiropotes, and three in Pithecia, some of them reported for the first time. Both cryptic and conspicuous species in this group presented high allelic diversity

Detection and Molecular Characterization of 9000-Year-Old Mycobacterium tuberculosis from a Neolithic Settlement in the Eastern Mediterranean

Background: Mycobacterium tuberculosis is the principal etiologic agent of human tuberculosis. It has no environmental reservoir and is believed to have co-evolved with its host over millennia. This is supported by skeletal evidence of the disease in early humans, and inferred from M. tuberculosis genomic analysis. Direct examination of ancient human remains for M. tuberculosis biomarkers should aid our understanding of the nature of prehistoric tuberculosis and the host/pathogen relationship.Methodology/Principal Findings: We used conventional PCR to examine bone samples with typical tuberculosis lesions from a woman and infant, who were buried together in the now submerged site of Atlit-Yam in the Eastern Mediterranean, dating from 9250-8160 years ago. Rigorous precautions were taken to prevent contamination, and independent centers were used to confirm authenticity of findings. DNA from five M. tuberculosis genetic loci was detected and had characteristics consistent with extant genetic lineages. High performance liquid chromatography was used as an independent method of verification and it directly detected mycolic acid lipid biomarkers, specific for the M. tuberculosis complex.Conclusions/Significance: Human tuberculosis was confirmed by morphological and molecular methods in a population living in one of the first villages with evidence of agriculture and animal domestication. The widespread use of animals was not a source of infection but may have supported a denser human population that facilitated transmission of the tubercle bacillus. The similarity of the M. tuberculosis genetic signature with those of today gives support to the theory of a long-term co-existence of host and pathogen

Plasma Metabolites associated With Cognitive Function across Race/Ethnicities affirming the Importance of Healthy Nutrition

INTRODUCTION: We studied the replication and generalization of previously identified metabolites potentially associated with global cognitive function in multiple race/ethnicities and assessed the contribution of diet to these associations. METHODS: We tested metabolite-cognitive function associations in U.S.A. Hispanic/Latino adults (n = 2222) from the Community Health Study/ Study of Latinos (HCHS/SOL) and in European (n = 1365) and African (n = 478) Americans from the Atherosclerosis Risk In Communities (ARIC) Study. We applied Mendelian Randomization (MR) analyses to assess causal associations between the metabolites and cognitive function and between Mediterranean diet and cognitive function. RESULTS: Six metabolites were consistently associated with lower global cognitive function across all studies. Of these, four were sugar-related (e.g., ribitol). MR analyses provided weak evidence for a potential causal effect of ribitol on cognitive function and bi-directional effects of cognitive performance on diet. DISCUSSION: Several diet-related metabolites were associated with global cognitive function across studies with different race/ethnicities. HIGHLIGHTS: Metabolites associated with cognitive function in Puerto Rican adults were recently identified. We demonstrate the generalizability of these associations across diverse race/ethnicities. Most identified metabolites are related to sugars. Mendelian Randomization (MR) provides weak evidence for a causal effect of ribitol on cognitive function. Beta-cryptoxanthin and other metabolites highlight the importance of a healthy diet

The range of the golden-mantle tamarin, Saguinus tripartitus (Milne Edwards, 1878): distributions and sympatry of four tamarin species in Colombia, Ecuador, and northern Peru

A detailed understanding of the range of the golden-mantle tamarin, Saguinus tripartitus (Milne Edwards, 1878), in Amazonian Peru and Ecuador is of particular relevance, not only because it is poorly known but also because it was on the basis of its supposed sympatry with the saddleback tamarin (S. fuscicollis lagonotus) that Thorington (Am J Primatol 15:367–371, 1988) argued that it is a distinct species rather than a saddleback tamarin subspecies, as was believed by Hershkovitz (Living new world monkeys, vol I. The University of Chicago Press, Chicago, 1977). A number of surveys have been carried out since 1988 in the supposed range of S. tripartitus, in both Ecuador and Peru. Here we summarize and discuss these issues and provide a new suggestion for the geographic range of this species; that is, between the ríos Napo and Curaray in Peru and extending east into Ecuador. We also review current evidence for the distributions of Spix’s black-mantle tamarin (S. nigricollis nigricollis), Graells’ black-mantle tamarin (S. n. graellsi), and the saddleback tamarin (S. fuscicollis lagonotus), which are also poorly known, and examine the evidence regarding sympatry between them. We conclude that despite the existence of a number of specimens with collecting localities that indicate overlap in their geographic ranges, the fact that the four tamarin species are of similar size and undoubtedly very similar in their feeding habits militates strongly against the occurrence of sympatry among them