Miracle-dz/UniFAR-FTUs huggingface dataset:
Testing a theoretical model of the stress process in Alzheimer's caregivers with race as a moderator.

PURPOSE The primary aim of this study was to test the stress process model (SPM; Pearlin, Mullan, Semple, & Skaff, 1990) in a racially diverse sample of Alzheimer's caregivers (CGs) using structural equation modeling (SEM) and regression techniques. A secondary aim was to examine race or ethnicity as a moderator of the relation between latent constructs (e.g., subjective stressors and role strain) in the SPM. SAMPLE Participants included White or Caucasian (n = 212), Black or African American (n = 201), and Hispanic or Latino (n = 196) Alzheimer's CGs from the Resources for Enhancing Alzheimer's Caregiver Health (REACH) II clinical trial. RESULTS SEM revealed that the Pearlin model obtains a satisfactory fit across race or ethnicity in the REACH II data, despite significant racial differences in each of the latent constructs. Race or ethnicity moderated the impact of resources on intrapsychic strain, such that CGs reported similar intrapsychic strain across race at lower levels of resources, but White or Caucasian CGs reported more intrapsychic strain than Black or African American or Hispanic or Latino CGs when resources are higher. IMPLICATIONS Strengths and weaknesses for each race or ethnicity vary considerably, suggesting that interventions must target different aspects of the stress process to provide optimal benefit for individuals of different cultural or ethnic backgrounds.
Solving and analyzing Sudokus with cultural algorithms

This paper studies how cultural algorithm suits to solving and analyzing Sudoku puzzles. Sudoku is a number puzzle that has recently become a worldwide phenomenon. It can be regarded as a combinatorial problem, but when solved with evolutionary algorithms it can also be handled as a constraint satisfaction or multi-objective optimization problem. The objectives of this study were 1) to test if a cultural algorithm with a belief space solves Sudoku puzzles more efficiently than a normal permutation genetic algorithm, 2) to see if the belief space gathers information that helps analyze the results and improve the method accordingly, 3) to improve our previous Sudoku solver presented in CEC2007. Experiments showed that proposed the cultural algorithm performed slightly better than the previous genetic algorithm based Sudoku solver.
Inference of complex population histories using whole-genome sequences from multiple populations

Significance An increasing number of population genomic studies now try to infer complex models of population history using a number of whole-genome sequences sampled from multiple populations. A key technical challenge to this effort is to compute model likelihoods, which involves integrating out latent variables (genealogical histories) that live in extremely high dimensions. This is a notoriously difficult computational problem, especially when the sample size is greater than a handful and the underlying population genetic model is complex. Here, we present an efficient, flexible statistical method that can scale to larger sample sizes and more populations than previously possible. Aside from demographic inference, our method can be used in other statistical inference problems in evolutionary biology and human genetics. There has been much interest in analyzing genome-scale DNA sequence data to infer population histories, but inference methods developed hitherto are limited in model complexity and computational scalability. Here we present an efficient, flexible statistical method, diCal2, that can use whole-genome sequence data from multiple populations to infer complex demographic models involving population size changes, population splits, admixture, and migration. Applying our method to data from Australian, East Asian, European, and Papuan populations, we find that the population ancestral to Australians and Papuans started separating from East Asians and Europeans about 100,000 y ago, and that the separation of East Asians and Europeans started about 50,000 y ago, with pervasive gene flow between all pairs of populations.
Convergent Validity of a Student Model: Recent-Performance Factors Analysis

Models of student performance can incorporate a skill decomposition that lists the skills that each activity requires. A good model must be sensitive to improvements in skill decomposition. We validate the Recent-Performance Factors Analysis model of student performance by checking its sensitivity to the skill decomposition. We use a dataset from a tutoring system where the skill model has been improved by the Learning Factors Analysis algorithm for skill model refinement and by expert validation. We find that R-PFA reflects improvements in the skill model, providing evidence of convergent validity of R-PFA. We argue that R-PFA may be sensible as a predictive model in Learning Factors Analysis because of its convergent validity and because the R predictor of R-PFA represents mastery-aligned learning curves.
Tracing the Episteme of Growth Rationality: Nexus of Mainstream Economics and Development Teleology

The present work attempts an appraisal of what was construed as a paradigmatic shift in policy discourse from growth postulations to alternative approaches in addressing the cause of underdevelopment. Studying the issues behind the development debates, this paper posits to explore the pro-development propositions of the two matrices -- growth and development. It is argued that the implication of the debate lies not merely in defining the contours of pro-poor development -- enumerative or subjective -- but in invigorating the concept of development from teleological perspective. In sum, the present discussion emphasizes the significance of the theoretical contestations in re-creating a reflexive development paradigm.
Reconstruction for Limited-Projection Fluorescence Molecular Tomography Based on a Double-Mesh Strategy

Limited-projection fluorescence molecular tomography (FMT) has short data acquisition time that allows fast resolving of the three-dimensional visualization of fluorophore within small animal in vivo. However, limited-projection FMT reconstruction suffers from severe ill-posedness because only limited projections are used for reconstruction. To alleviate the ill-posedness, a feasible region extraction strategy based on a double mesh is presented for limited-projection FMT. First, an initial result is rapidly recovered using a coarse discretization mesh. Then, the reconstructed fluorophore area in the initial result is selected as a feasible region to guide the reconstruction using a fine discretization mesh. Simulation experiments on a digital mouse and small animal experiment in vivo are performed to validate the proposed strategy. It demonstrates that the presented strategy provides a good distribution of fluorophore with limited projections of fluorescence measurements. Hence, it is suitable for reconstruction of limited-projection FMT.
Economic theory and Psychological Data: Bridging the Divide

Classical decision theory is a picture of harmony. Models are designed to predict economically consequential choices, and empirical tests concern their ability to explain these choices. The models themselves are typically solved using optimization techniques with solid axiomatic foundations. These foundations allow for a complete understanding of the qualitative and quantitative relationship of the models to relevant choice data. The consensus within economics concerning this decision theoretic methodology has had powerful positive externalities, ensuring strong communication across professional subdisciplines. Economics stands out in this respect from other social sciences, in which the approach to model-building is more fragmented, and in which communication problems are correspondingly more profound. Despite its harmony, many researchers view classical decision theory as limited in its ability to incorporate psychological factors. As detailed in section 15.2, this has led to ever growing interest in non standard economic models that sit outside the choice theoretic tradition. At the same time, diverse new forms of “psychological” data are being developed, concerning features of informational search, eye movements, neurological responses, and answers to non-standard survey questions. The possibilities for new insights to be gleaned by appropriately combining non-standard theories with novel psychological data excite many prominent researchers (e.g. Benhabib and Bisin [this volume], Camerer [this volume], Crawford [this volume], and Schotter [this volume]). While the recent expansion in the scope of economic theory and measurement opens up intriguing new vistas, it also raises profound challenges. In particular, it has disturbed the harmonic situation that previously prevailed. In striking contrast with the classical theory, there are expanding gaps between the new economic models and the psychological data that are used to inspire and to test them. Should these gaps continue to expand, it will pose a significant threat to
DPS: A dynamic procrastination scheduler for multi-core/multi-processor hard real time systems

Energy consumption plays an important role in designing embedded devices. In recent years, leakage energy gained significant importance in overall energy consumption. This paper addresses leakage energy at operating system level by optimizing scheduler level energy consumption. This is achieved by (i) modifying the first fit allocation algorithm (MFF) to increase shutdown duration of some processors by allocating low frequency tasks to that processors and (ii) maximizing the shutdown duration using dynamic procrastination algorithm (DPS). The procrastination is achieved by postponing the execution of upcoming jobs whenever possible by meeting all timing constraints. This helps in improving shutdown duration along with reducing decision points and static energy consumption. Shutdown decision is based on pre-computed shutdown threshold which is architecture and task set dependent. The experimental evaluation of the proposed algorithm with synthetically generated benchmark program suites shows 88.66%, 14.75% and 1% of saving in total energy consumption over no procrastination (NOPRO) with MFF task allocation, static procrastination (STATICPRO) with MFF task allocation and DPS with FF task allocation respectively.
GXL: toward a standard exchange format

This paper describes ongoing work toward the development of a standard software exchange format (SEF), for exchanging information among tools that analyze computer programs. A particular exchange format called GXL (Graph Exchange Language) is proposed. GXL can be viewed as a merger of well known formats (e.g. GraX, PROGRES, RPA, RSF and TA) for exchanging typed, attributed, directed graphs. By using XML as the notation, GXL offers a scalable and adaptable means to facilitate interoperability of reengineering tools.
Deuterium and oxygen-18 in present-day precipitation: data and modelling

Abstract The cycles of the water isotopic species (HDO and H2 18O) have been incorporated in three atmospheric General Circulation Models (GCMs) with the main objective of predicting the distribution of water stable isotopes in precipitation, The performances of those models are examined for present-day climate through a comparison with existing data available from the IAEA/WMO network established in 1961 and from other sources.
Leakage reduction, variation compensation using partition-based tunable body-biasing techniques

As fabrication technology progresses, several new challenges follow. Among them, the most noticeable two are process variations and leakage current of the circuit. To tackle these two problems, an effective way is to use body biasing technique. In substance, using RBB technique can minimize leakage current but increase the delay of a gate. FBB technique decreases the delay but increases leakage current. In previous works, a single body biasing is applied to whole circuit. In a slow circuit, since the FBB is applied to whole circuit, the leakage current increases dramatically. In a fast circuit, RBB is applied to decrease the leakage current. However, without violating the timing specification, the value of body biasing is restricted by the critical paths, and the saving of leakage current is limited. In this paper, we propose a design flow to partition the circuit into subcircuits so that each subcircuit can be applied its individual RBB or FBB to reduce the leakage current and cope with process variations. In the experimental result, our method is able to save leakage current from 41% to 46% as compared with design without body biasing technique. Under process variations, our method can save 40% to 49% leakage on fast circuits and 15% to 32% on slow circuits.
Clinical Decision Support: Effectiveness in Improving Quality Processes and Clinical Outcomes and Factors That May Influence Success

The use of electronic health records has skyrocketed following the 2009 HITECH Act, which provides financial incentives to health care providers for the “meaningful use” of electronic medical record systems. An important component of the “Meaningful Use” legislation is the integration of Clinical Decision Support Systems (CDSS) into the computerized record, providing up-to-date medical knowledge and evidence-based guidance to the physician at the point of care. As reimbursement is increasingly tied to process and clinical outcomes, CDSS will be integral to future medical practice. Studies of CDSS indicate improvement in preventive services, appropriate care, and clinical and cost outcomes with strong evidence for CDSS effectiveness in process measures. Increasing provider adherence to CDSS recommendations is essential in improving CDSS effectiveness, and factors that influence adherence are currently under study.
An Online Prediction Framework for Non-Stationary Time Series

We extend an online time series prediction algorithm for ARMA processes to describe a framework for time series prediction that can efficiently handle non-stationarities that exist in many real time series. We show that appropriate transformations to such time series can lead to theoretical and empirical gains. To account for the phenomenon of cointegration in the multivariate case, we present a novel algorithm EC-VARMA-OGD that estimates both the auto-regressive and the cointegrating parameters. Relaxing the assumptions for the analysis, we prove a sub-linear regret bound for all the methods described. We note that the theoretical guarantees do not provide a complete picture, thus we provide a data-dependent analysis of the follow-the-leader algorithm for least squares loss that explains the success of using non-stationary transformations. We support all of our results with experiments on simulated and real data.
Longitudinally guided level sets for consistent tissue segmentation of neonates

Quantification of brain development as well as disease‐induced pathologies in neonates often requires precise delineation of white matter, grey matter and cerebrospinal fluid. Unlike adults, tissue segmentation in neonates is significantly more challenging due to the inherently lower tissue contrast. Most existing methods take a voxel‐based approach and are limited to working with images from a single time‐point, even though longitudinal scans are available. We take a different approach by taking advantage of the fact that the pattern of the major sulci and gyri are already present in the neonates and generally preserved but fine‐tuned during brain development. That is, the segmentation of late‐time‐point image can be used to guide the segmentation of neonatal image. Accordingly, we propose a novel longitudinally guided level‐sets method for consistent neonatal image segmentation by combining local intensity information, atlas spatial prior, cortical thickness constraint, and longitudinal information into a variational framework. The minimization of the proposed energy functional is strictly derived from a variational principle. Validation performed on both simulated and in vivo neonatal brain images shows promising results. Hum Brain Mapp, 2013. © 2011 Wiley Periodicals, Inc.
Summary of Results and Discussions From the Gene-Based Tests Group at Genetic Analysis Workshop 18

I present a summary of the results and discussions held within the working group on gene‐based tests at Genetic Analysis Workshop 18 (GAW18). The main focus of interest in our working group was modeling the action of combinations or “groups” of genetic variants, with a group of variants most often defined as a set of single‐nucleotide polymorphisms lying within a known gene. Some contributions investigated the performance of previously proposed methods (particularly rare variant collapsing or burden‐type methods) for addressing this question, applied to the GAW18 data, and other contributions developed novel approaches and addressed novel questions. Most approaches were successful in detecting significant effects at MAP4 in the simulated data. No other genetic effects were consistently detected across different analyses. Low power was noted, particularly for those methods that restricted analysis to purely the subset of unrelated individuals.
Correlates of Social, Demographic and Behavioral Factors affecting Adolescent Sexuality in a Traditional Society in India: Perspectives and Challenges

Background: Adolescent risk behavior is a major concern. Objectives: The study assessed the effect of school background, personal, social and other deviant behavior on school going adolescent sexual behavior. Material and Methods: The sample covered 3069 randomly selected adolescents (students) from 9 th to 12 th standard in various governments, private and missionary run schools from two districts namely; Aizawl being state capital and Champhai being distant under developed district. Summary: School background, leisure and entertainment practices, influence of taking alcohol, tobacco, drug, peer influence were found to be the major risk factor for indulgence in unsafe sex practices among adolescents. About 10% accepted involvement in premarital sex and majority of them (70%) of them had premarital sex between age group 15-19 years. The schools lacked in organizing awareness program and counseling activities on consequences of adolescent sex. The ARSH Program needs to synergize with school health program for desired results. Conclusions: Adolescent sexual risk behavior is a part of overall deviant behavior and can be managed in holistic manner.
Vehicle attitude control with saturating actuators: Workload balancing and reference adaptation

This paper addresses the problem of vehicle attitude control in the presence of saturating actuators. A novel approach of actuation balancing is proven to be the best way to keep the vehicle off saturation or, at least, to postpone the saturation occurrences as late as possible. In hard conditions, this may be not sufficient to guarantee tracking; hence the joint design of a load-balancing control law and an adapted reference generator is addressed, in order to cope with the lack in the control action and prevent unstable behaviors. On top of the formal results, the method is validated by means of simulations.
Assessing 21st Century Skills: Competency Modeling to the Rescue

Neubert, Mainert, Kretzschmar, and Greiff (2015) rightly argue that today's business world requires employees to frequently engage in nonroutine, creative, and interactive tasks. The authors go further to describe two potentially important skills—complex problem solving and collaborative problem solving—which they believe can address gaps in our current understanding of employee skill assessment. I contend however that the authors might be reinventing the wheel with this framework, given that the already popular practice of competency modeling satisfies the very deficiencies that the authors argue exist. To expand on this argument, I will first provide a brief history and discussion of what competency modeling is, followed by an explanation of several key benefits of this approach in terms of addressing the authors’ concerns. Then, on the basis of my applied experience as an external consultant, I will discuss how I might use competency modeling to address one of the authors’ own example scenarios, which should help identify ways in which competency modeling subsumes Neubert and colleagues’ approach.
A Framework for Measuring Software Obfuscation Resilience against Automated Attacks

Software obfuscation of programs, with the goal of protecting against attackers having physical access to the machine executing them, is a common practice motivated by the necessity of keeping intellectual property (such as business critical algorithms) and critical data (such as cryptographic keys) secret. However, as of today, it is unclear how secure popular obfuscation operators are relative to each other or to other protection techniques. In this paper we propose a formal framework to characterize attacker models and guarantees, inspired by similar notions from cryptography. We then map prior work in the area of deobfuscation to our formal model to the possible extent. We also perform a case-study about using symbolic execution for deobfuscation, concretely mapped onto our formal model.
Tumor boundary extraction in multislice MR brain images using region and contour deformation

In this paper, we present a new approach for the extraction of brain tumor boundary in a series of 2D MR image slices. The shape and position of tumor in one slice could be assumed to be similar to that in its neighboring slices. Using this correlation between consecutive images, the initial plan applied for each slice is extracted from the resulting boundary of the previous slice. The tumor boundary is located using region and contour deformation, which tolerates a rough initial plan. Therefore, only one coarse manual initial plan is required for the whole series of MR image slices. Performance of our approach is evaluated on MR image set. Comparisons with manual tracing show the accuracy and effectiveness of our approach.
Norm of the screen for child social anxiety related emotional disorders in Chinese urban children.

【Objective】 To develop the norm of Social Anxiety Scale for Children(SASC) in Chinese urban and to test the reliability and validity of this scale. 【Methods】 Students of a total of 2 019 subjects(1 012 males and 1 007 females) from 14 cities of China with the mean age(11.29±2.34) completed the Scale. 【Results】 The reliability was good.Significant correlations were found between the total scores,the anxiety index of SASC and Child Behavior Checklist(CBCL) and SCARED.The scores of children with the social anxiety disorders were higher than that of normal subjects. 【Conclusion】 SASC is found to have good psychometrics properties,with adequate reliability and validity.In particular,the SASC is applicable to assess social anxiety syndrome of Chinese children.