nils-herrmann/clean_scirepeval huggingface dataset:
Concrete-Pictorial-Abstract : Surveying its origins and charting its future

The Concrete-Pictorial-Abstract (CPA) approach, based on Bruner’s conception of the enactive, iconic and symbolic modes of representation, is a well-known instructional heuristic advocated by the Singapore Ministry of Education since early 1980’s. Despite its ubiquity as a teaching strategy throughout the entire mathematics education community in Singapore, it is somewhat surprising to see a lack of an account of its theoretical roots. This paper is an attempt to contribute to this discussion on the CPA strategy and its potential role in continuing advancement of quality mathematics education.
An Optical-Camera Complement to a PIR Sensor Array for Intrusion Detection and Classfication in an Outdoor Environment

An important issue faced while employing Pyroelectric InfraRed (PIR) sensors in an outdoor Wireless Sensor Network (WSN) deployment for intrusion detection, is that the output of the PIR sensor can, as shown in a recent paper, degenerate into a weak and unpredictable signal when the background temperature is close to that of the intruder. The current paper explores the use of an optical camera as a complementary sensing modality in an outdoor WSN deployment to reliably handle such situations. A combination of backgroundsubtraction and the Lucas-Kanade optical-flow algorithms is used to classify between human and animal in an outdoor environment based on video data.,,The algorithms were developed keeping in mind the need for the camera to act when called upon, as a substitute for the PIR sensor by turning in comparable classification accuracies. All algorithms are implemented on a mote in the case of the PIR sensor array and on an Odroid single-board computer in the case of the optical camera. Three sets of experimental results are presented. The first set shows the optical-camera platform to turn in under supervised learning, high accuracy classification (in excess of 95%) comparable to that of the PIR sensor array. The second set of results correspond to an outdoor WSN deployment over a period of 7 days where similar accuracies are achieved. The final set also corresponds to a single-day outdoor WSN deployment and shows that the optical camera can act as a stand-in for the PIR sensor array when the ambient temperature conditions cause the PIR sensor to perform poorly.
The Impact of Sleep on Learning and Behavior in Adolescents

Many adolescents are experiencing a reduction in sleep as a consequence of a variety of behavioral factors (e.g., academic workload, social and employment opportunities), even though scientific evidence suggests that the biological need for sleep increases during maturation. Consequently, the ability to effectively interact with peers while learning and processing novel information may be diminished in many sleepdeprived adolescents. Furthermore, sleep deprivation may account for reductions in cognitive efficiency in many children and adolescents with special education needs. In response to recognition of this potential problem by parents, educators, and scientists, some school districts have implemented delayed bus schedules and school start times to allow for increased sleep duration for high school students, in an effort to increase academic performance and decrease behavioral problems. The long-term effects of this change are yet to be determined; however, preliminary studies suggest that the short-term impact on learning and behavior has been beneficial. Thus, many parents, teachers, and scientists are supporting further consideration of this information to formulate policies that may maximize learning and developmental opportunities for children. Although changing school start times may be an effective method to combat sleep deprivation in most adolescents, some adolescents experience sleep deprivation and consequent diminished daytime performance because of common underlying sleep disorders (e.g., asthma or sleep apnea). In such cases, surgical, pharmaceutical, or respiratory therapy, or a combination of the three, interventions are required to restore normal sleep and daytime performance.
SSD as SQLite Engine

As a proof-of-concept for the vision “SSD as SQL Engine” (SaS in short), we demonstrate that SQLite , a popular mobile database engine, in its entirety can run inside a real SSD development platform. By turning storage device into database engine, SaS allows applications to directly interact with full SQL database server running inside storage device. In SaS, the SQL language itself, not the traditional dummy block interface, will be provided as new interface between applications and storage device. In addition, since SaS plays the role of the uni ed platform of database computing node and storage node, the host and the storage need not be segregated any more as separate physical computing components.
Psychometric properties of the Life Regard Index-Revised: a validation study of a measure of personal meaning.

A validation study of the English version of the 28-item Life Regard Index-Revised was undertaken with a sample of 91 participants from the general population. All previous studies of the Index have examined the Dutch version. The test-retest reliabilities at 8 wk. for the total Index (r =.87), Framework (r =.82), and Fulfillment (r =.81) subscales were very high. Cronbach alphas were .92, .83, and .87, respectively. A significant restriction of range was observed at the high-meaning end of the scale. Factor analysis only weakly supported the theorized two-factor structure. A very high disattenuated correlation between the Framework and Fulfillment subscales was observed (r=.94). The Index appeared to have adequate evidence supporting its concurrent and discriminant validity when compared with measures of hopelessness, spiritual well-being, and other measures of personal meaning. A significant positive association was found between the index and the Marlowe-Crowne Social Desirability Scale (r=.38). The Index was also significantly associated with sex (women scoring higher) and marital status (divorced people scoring lower). Revisions of the English version may address the restriction of range problem by employing a 5-point rating scale, instead of the current 3-point scale, or by adding more discriminating items. Further factor-analytic studies with larger samples are needed before conclusions can be drawn regarding this scale's factor structure.
A new two-phase sampling based algorithm for discovering association rules

This paper introduces FAST, a novel two-phase sampling-based algorithm for discovering association rules in large databases. In Phase I a large initial sample of transactions is collected and used to quickly and accurately estimate the support of each individual item in the database. In Phase II these estimated supports are used to either trim "outlier" transactions or select "representative" transactions from the initial sample, thereby forming a small final sample that more accurately reflects the statistical characteristics (i.e., itemset supports) of the entire database. The expensive operation of discovering association rules is then performed on the final sample. In an empirical study, FAST was able to achieve 90--95% accuracy using a final sample having a size of only 15--33% of that of a comparable random sample. This efficiency gain resulted in a speedup by roughly a factor of 10 over previous algorithms that require expensive processing of the entire database --- even efficient algorithms that exploit sampling. Our new sampling technique can be used in conjunction with almost any standard association-rule algorithm, and can potentially render scalable other algorithms that mine "count" data.
A graph-theory algorithm for rapid protein side-chain prediction.

Fast and accurate side-chain conformation prediction is important for homology modeling, ab initio protein structure prediction, and protein design applications. Many methods have been presented, although only a few computer programs are publicly available. The SCWRL program is one such method and is widely used because of its speed, accuracy, and ease of use. A new algorithm for SCWRL is presented that uses results from graph theory to solve the combinatorial problem encountered in the side-chain prediction problem. In this method, side chains are represented as vertices in an undirected graph. Any two residues that have rotamers with nonzero interaction energies are considered to have an edge in the graph. The resulting graph can be partitioned into connected subgraphs with no edges between them. These subgraphs can in turn be broken into biconnected components, which are graphs that cannot be disconnected by removal of a single vertex. The combinatorial problem is reduced to finding the minimum energy of these small biconnected components and combining the results to identify the global minimum energy conformation. This algorithm is able to complete predictions on a set of 180 proteins with 34342 side chains in <7 min of computer time. The total chi(1) and chi(1 + 2) dihedral angle accuracies are 82.6% and 73.7% using a simple energy function based on the backbone-dependent rotamer library and a linear repulsive steric energy. The new algorithm will allow for use of SCWRL in more demanding applications such as sequence design and ab initio structure prediction, as well addition of a more complex energy function and conformational flexibility, leading to increased accuracy.
Hot Row Identification of DRAM Memory in a Multicore System

Access locality in single-core system is not easily observed in multicore system due to interleaved requests from different cores. Requests that come to DRAM-based main memory is mapped to a specific bank in DRAM and accessed through row buffer in the bank. DRAM row-buffer conflicts occur when a sequence of requests on different rows goes to the same memory bank, causing much higher memory access latency than requests to the same row or to different banks.
 In this paper, we first show that strong locality exists in memory requests of multicore systems. For many workloads, the accesses to some rows are more frequent than others, which we call them hot rows. Based on the observation, we propose a simple hot row buffer (HRB) scheme that is able to detect and capture these hot rows in DRAM. Results have shown that the proposed scheme is able to provide average 56% hit ratio over all row accesses in a bank for 10 selected workloads from SPEC CPU2006. A simple stream prefetcher prefetching in the hot row is implemented and results show an average of 9.1% IPC improvement over no prefetcher design.
Hierarchical Variational Models

Black box variational inference allows researchers to easily prototype and evaluate an array of models. Recent advances allow such algorithms to scale to high dimensions. However, a central question remains: How to specify an expressive variational distribution that maintains efficient computation? To address this, we develop hierarchical variational models (HVMs). HVMs augment a variational approximation with a prior on its parameters, which allows it to capture complex structure for both discrete and continuous latent variables. The algorithm we develop is black box, can be used for any HVM, and has the same computational efficiency as the original approximation. We study HVMs on a variety of deep discrete latent variable models. HVMs generalize other expressive variational distributions and maintains higher fidelity to the posterior.
On the Individuality of Fingerprints: Models and Methods

Fingerprint individuality is the study of the extent of uniqueness of fingerprints and is the central premise of expert testimony in court. A forensic expert testifies whether a pair of fingerprints is either a match or non-match by comparing salient features of the fingerprint pair. However, the experts are rarely questioned on the uncertainty associated with the match: How likely is the observed match between the fingerprint pair due to just random chance? The main concern with the admissibility of fingerprint evidence is that the matching error rates (i.e., the fundamental error rates of matching by the human expert) are unknown. The problem of unknown error rates is also prevalent in other modes of identification such as handwriting, lie detection, etc. Realizing this, the U.S. Supreme Court, in the 1993 case of Daubert vs. Merrell Dow Pharmaceuticals, ruled that forensic evidence presented in a court is subject to five principles of scientific validation, namely whether (i) the particular technique or methodology has been subject to statistical hypothesis testing, (ii) its error rates has been established, (iii) standards controlling the technique’s operation exist and have been maintained, (iv) it has been peer reviewed, and (v) it has a general widespread acceptance. Following Daubert, forensic evidence based on fingerprints was first challenged in the 1999 case of USA vs. Byron Mitchell based on the “known error rate” condition 2 mentioned above, and subsequently, in 20 other cases involving fingerprint evidence. The establishment of matching error rates is directly related to the extent of fingerprint individualization. This article gives an overview of the problem of fingerprint individuality, the challenges faced and the models and methods that have been developed to study this problem.  Fingerprint individuality, fingerprint matching automatic, fingerprint matching manual, forensic evidence of fingerprint, individuality.  This is the match between two fingerprint images of the same person. 2. Impostor match: This is the match between a pair of fingerprints from two different persons. 3. Fingerprint individuality: It is the study of the extent of which different fingerprints tend to match with each other. It is the most important measure to be judged when fingerprint evidence is presented in court as it reflects the uncertainty with the experts’ decision. 4.  It refers to the differences in the observed features from one sample to another in a population. The differences can be random, that is, just by chance, or systematic due to some underlying factor that governs the variability.
Locality Statistics for Anomaly Detection in Time Series of Graphs

The ability to detect change-points in a dynamic network or a time series of graphs is an increasingly important task in many applications of the emerging discipline of graph signal processing. This paper formulates change-point detection as a hypothesis testing problem in terms of a generative latent position model, focusing on the special case of the Stochastic Block Model time series. We analyze two classes of scan statistics, based on distinct underlying locality statistics presented in the literature. Our main contribution is the derivation of the limiting properties and power characteristics of the competing scan statistics. Performance is compared theoretically, on synthetic data, and empirically, on the Enron email corpus.
Adverse childhood experiences, chronic diseases, and risky health behaviors in Saudi Arabian adults: a pilot study.

Adverse childhood experiences (ACEs) have been linked with risky health behaviors and the development of chronic diseases in adulthood. This study examined associations between ACEs, chronic diseases, and risky behaviors in adults living in Riyadh, Saudi Arabia in 2012 using the ACE International Questionnaire (ACE-IQ). A cross-sectional design was used, and adults who were at least 18 years of age were eligible to participate. ACEs event scores were measured for neglect, household dysfunction, abuse (physical, sexual, and emotional), and peer and community violence. The ACE-IQ was supplemented with questions on risky health behaviors, chronic diseases, and mood. A total of 931 subjects completed the questionnaire (a completion rate of 88%); 57% of the sample was female, 90% was younger than 45 years, 86% had at least a college education, 80% were Saudi nationals, and 58% were married. One-third of the participants (32%) had been exposed to 4 or more ACEs, and 10%, 17%, and 23% had been exposed to 3, 2, or 1 ACEs respectively. Only 18% did not have an ACE. The prevalence of risky health behaviors ranged between 4% and 22%. The prevalence of self-reported chronic diseases ranged between 6% and 17%. Being exposed to 4 or more ACEs increased the risk of having chronic diseases by 2-11 fold, and increased risky health behaviors by 8-21 fold. The findings of this study will contribute to the planning and development of programs to prevent child maltreatment and to alleviate the burden of chronic diseases in adults.
Botnet Research Survey

Botnets are emerging threat with hundreds of millions of computers infected. A study shows that about 40% of all computers connected to the internet in the world are infected bots and controlled by attackers. This article is a survey of recent advances in botnet research. The survey classifies the botnet research into three areas: understanding botnets, detecting and tracking botnets, and defending against botnets. While botnets are widespread, the research and solutions for botnets are still in their infancy. The paper also summarizes the existing research and proposes future directions for botnet research.
Beautiful People Are Better , At Least Online : Associations Between Photo Attractiveness and Text Attractiveness in Women ' s Online Dating Profiles

Do physically attractive individuals truly possess a multitude of better characteristics? The current study aimed to answer the age old question, “Do looks matter?” within the context of online dating and framed itself using cursory research performed by Brand and colleagues (2012). Good Genes Theory, Halo Effect, Physical Attractiveness Stereotype, and Social Information Procession theory were also used to explore what function appearance truly plays in online dating and how it influences a user’s written text. 83 men were surveyed and asked to rate 84 women’s online dating profiles (photos and texts) independently of one another to determine if those who were perceived as physically attractive also wrote more attractive texts as well. Results indicated that physical attractiveness was correlated with text attractiveness but not with text confidence. Findings also indicated the more attractive a woman’s photo, the less discrepancy there was between her photo attractiveness and text attractiveness scores. Finally, photo attractiveness did not differ significantly for men’s ratings of women in this study and women’s ratings of men in the Brand et al. (2012) study.
Title of paper : KASPAR – A Minimally Expressive Humanoid Robot for Human-Robot Interaction Research

This article provides a comprehensive introduction to the design of the minimally expressive robot KASPAR which is particularly suitable for human-robot interaction studies. A low-cost design with off-the-shelf components has been used in a novel design inspired from a multi-disciplinary viewpoint, including comics design and Japanese Noh theatre. The design rationale of the robot and its technical features are described in detail. Three research studies will be presented that have been using KASPAR extensively. Firstly, we present its application in robot-assisted play and therapy for children with autism. Secondly, we illustrate its use in human-robot interaction studies investigating the role of interaction kinesics and gestures. Lastly, we describe a study in the field of developmental robotics into computational architectures based on interaction histories for robot ontogeny. The three areas differ in the way how the robot is being operated and its role in social interaction scenarios. Each will be introduced briefly and examples of the results are presented. Reflections on the specific design features of KASPAR that were important in these studies and lessons learnt from these studies concerning the design of humanoid robots for social interaction will be discussed. An assessment of the robot in terms of utility of the design for human-robot interaction experiments concludes the paper.
Effects of Zika Virus Strain and Aedes Mosquito Species on Vector Competence

In the Western Hemisphere, Zika virus is thought to be transmitted primarily by Aedes aegypti mosquitoes. To determine the extent to which Ae. albopictus mosquitoes from the United States are capable of transmitting Zika virus and the influence of virus dose, virus strain, and mosquito species on vector competence, we evaluated multiple doses of representative Zika virus strains in Ae. aegypti and Ae. albopictus mosquitoes. Virus preparation (fresh vs. frozen) significantly affected virus infectivity in mosquitoes. We calculated 50% infectious doses to be 6.1-7.5 log 10 PFU/mL; minimum infective dose was 4.2 log 10 PFU/mL. Ae. albopictus mosquitoes were more susceptible to infection than Ae. aegypti mosquitoes, but transmission efficiency was higher for Ae. aegypti mosquitoes, indicating a transmission barrier in Ae. albopictus mosquitoes. Results suggest that, although Zika virus transmission is relatively inefficient overall and dependent on virus strain and mosquito species, Ae. albopictus mosquitoes could become major vectors in the Americas.
Problem Based Learning, curriculum development and change process at Faculty of Medicine, Makerere University, Uganda.

The faculty of Medicine, (FOM) Makerere University Kampala was started in 1924 and has been running a traditional curriculum for 79 years. A few years back it embarked on changing its curriculum from traditional to Problem Based Learning (PBL) and Community Based Education and Service (COBES) as well as early clinical exposure. This curriculum has been implemented since the academic year 2003/2004. The study was done to describe the steps taken to change and implement the curriculum at the Faculty of Medicine, Makerere University Kampala.



To describe the steps taken to change and implement the new curriculum at the Faculty of Medicine.



The stages taken during the process were described and analysed.



The following stages were recognized characterization of Uganda's health status, analysis of government policy, analysis of old curriculum, needs assessment, adoption of new model (SPICES), workshop/retreats for faculty sensitization, incremental development of programs by faculty, implementation of new curriculum.



The FOM has successfully embarked on curriculum change. This has not been without challenges. However, challenges have been taken on and handled as they arose and this has led to the implementation of new curriculum. Problem based learning can be adopted even in a low resourced country like Uganda.
The Accrual Anomaly: Risk or Mispricing?

We document considerable return comovement associated with accruals after controlling for other common factors. An accrual-based factor-mimicking portfolio has a Sharpe ratio of 0.15, higher than that of the market factor or the HML factor of Fama and French (1993). In time series regressions, a model that includes the Fama-French factors and the additional accrual factor captures the accrual anomaly in average returns. However, further time series and cross-sectional tests indicate that it is the accrual characteristic rather than the accrual factor loading that predicts returns. These findings favor a behavioral explanation for the accrual anomaly.
Predicting the Outcome of NBA Playoffs Based on the Maximum Entropy Principle

Predicting the outcome of National Basketball Association (NBA) matches poses a challenging problem of interest to the research community as well as the general public. In this article, we formalize the problem of predicting NBA game results as a classification problem and apply the principle of Maximum Entropy to construct an NBA Maximum Entropy (NBAME) model that fits to discrete statistics for NBA games, and then predict the outcomes of NBA playoffs using the model. Our results reveal that the model is able to predict the winning team with 74.4% accuracy, outperforming other classical machine learning algorithms that could only afford a maximum prediction accuracy of 70.6% in the experiments that we performed.