Miracle-dz/UniFAR-FTUs huggingface dataset:
Use of Cognitive Behavioral Therapy and Token Economy to Alleviate Dysfunctional Behavior in Children with Attention-Deficit Hyperactivity Disorder

Medication has proved highly efficacious as a means of alleviating general symptoms of attention-deficit hyperactivity disorder (ADHD). However, many patients remain functionally impaired by inappropriate behavior. The present study analyzed the use of cognitive behavioral therapy (CBT) with the Token-Economy (TE) technique to alleviate problem behavior for 25 participants with ADHD, all children (19 boys, mean age 10.11) on long-term methylphenidate medication, who were given 20 CBT sessions with 10 weeks of TE introduced as of session 5. Their ten most acute problem behaviors were selected and written records kept. On weekdays, parents recorded each inappropriate behavior and provided a suitable model for their actions. At weekly sessions, problem behaviors were counted and incident-free participants rewarded with a token. To analyze improvement (less frequent problem behavior), a list of 11 behavioral categories was rated: inattention, impulsivity, hyperactivity, disorganization, disobeying rules and routines, poor self-care, verbal/physical aggression, low frustration tolerance, compulsive behavior, antisocial behavior, lacking in initiative and distraction. Two CBT specialists categorized behaviors and an ADHD specialist ruled on discrepancies. Statistical analyses used were Generalized Estimating Equations with Poisson distribution and autoregressive order correlation structure. In the course of the sessions, problematic behaviors decreased significantly in seven categories: impulsiveness, hyperactivity, disorganization, disobeying rules and routine, poor self-care, low frustration tolerance, compulsive behaviors, and antisocial behaviors. Caregiver attitudes to children’s inappropriate behavior were discussed and reshaped. As functional improvement was observed on applying TE for 10 weeks, this type of intervention may be useful as an auxiliary strategy combined with medication.
Utility-aware deferred load balancing in the cloud driven by dynamic pricing of electricity

Distributed computing resources in a cloud computing environment provides an opportunity to reduce energy and its cost by shifting loads in response to dynamically varying availability of energy. This variation in electrical power availability is represented in its dynamically changing price that can be used to drive workload deferral against performance requirements. But such deferral may cause user dissatisfaction. In this paper, we quantify the impact of deferral on user satisfaction and utilize flexibility from the service level agreements (SLAs) for deferral to adapt with dynamic price variation. We differentiate among the jobs based on their requirements for responsiveness and schedule them for energy saving while meeting deadlines and user satisfaction. Representing utility as decaying functions along with workload deferral, we make a balance between loss of user satisfaction and energy efficiency. We model delay as decaying functions and guarantee that no job violates the maximum deadline, and we minimize the overall energy cost. Our simulation on MapReduce traces show that energy consumption can be reduced by ∼15%, with such utility-aware deferred load balancing. We also found that considering utility as a decaying function gives better cost reduction than load balancing with a fixed deadline.
A Proved Approach for Building Correct Instances of UML Associations: Multiplicities Satisfaction

In UML modeling, class diagrams permit to capture the entities involved in a system but also the associations they have with each other. These associations are characterized by a multiplicity on each role to state the min-max number of instances of the opposite class that can be linked to each instance of the class associated with the role. Since these multiplicities may be conflicting, it becomes necessary to check the global consistency of a class diagram. Such verification will ensure that it is possible to find an instantiation of the diagram that satisfies all the multiplicities. In this paper, we describe an automatized approach that permits to validate a class diagram by exhibiting a particular instance. Basically, this approach proceeds in two main steps: first, the multiplicities are represented as a mathematical model, then a constraint solver is used to determine whether it has at least one solution. The correctness of the approach, which is supported by an automatic tool, has been carried out using the B formal method.
Unsupervised Feature Selection for Relation Extraction

This paper presents an unsupervised relation extraction algorithm, which induces relations between entity pairs by grouping them into a “natural” number of clusters based on the similarity of their contexts. Stability-based criterion is used to automatically estimate the number of clusters. For removing noisy feature words in clustering procedure, feature selection is conducted by optimizing a trace based criterion subject to some constraint in an unsupervised manner. After relation clustering procedure, we employ a discriminative category matching (DCM) to find typical and discriminative words to represent different relations. Experimental results show the effectiveness of our algorithm.
An Investigation of Information Technology-Enabled Remote Management and Remote Work Issues

A two phase research study was done to investigate remote work and remote management issues. In Phase 1, focus groups were carried out with remote managers and remote employees to identify key issues. The most common key issues dealt with communications, information technology, leadership and coaching, teamwork, building trust, and performance management. In the second phase, a questionnaire was used to test hypotheses developed from phase 1. The findings supported that higher trust leads to higher job satisfaction and lower job stress, and that more communication between the manager and the remote employee develops higher levels of employee organizational commitment.
Biochemical monitoring after initiation of aldosterone antagonist therapy in users of renin–angiotensin system blockers: a UK primary care cohort study

Objective To determine the frequency of biochemical monitoring after initiation of aldosterone antagonists(AA) in patients also using angiotensin-converting enzyme inhibitors/angiotensin receptor blockers (ACEI/ARB). Setting UK primary care. Participants ACEI/ARB users who initiated AA between 2004 and 2014. Outcomes We calculated the proportions with: (1) biochemical monitoring ≤2 weeks post initiation of AA, (2) adverse biochemical values ≤2 months (potassium ≥6 mmol/L, creatinine ≥220 µmol/L and ≥30% increase in creatinine from baseline) and (3) discontinuers of AA in those with an adverse biochemical value. We used logistic regression to study patient characteristics associated with monitoring and adverse biochemical values. Results In 10 546 initiators of AA, 3291 (31.2%) had a record of biochemical monitoring ≤2 weeks post initiation. A total of 2.0% and 2.7% of those with follow-up monitoring within 2 months of initiation experienced potassium ≥6 mmol/L and creatinine ≥220 µmol/L, respectively, whereas 13.5% had a ≥30% increase in creatinine. Baseline potassium (OR 3.59, 95% CI 2.43 to 5.32 for 5.0–5.5 mmol/L compared with <5.0 mmol/L) and estimated glomerular filtration rate 45-59 ml/min/1.73 m2 (OR 2.06, 95% CI 1.26 to 3.35 compared with ≥60 ml/min/1.73 m2) were independently predictive of potassium ≥6 mmol/L. Women and people with diabetes had higher odds of ≥30% increase in creatinine. Conclusion Less than one-third of patients taking ACEI/ARB had biochemical monitoring within 2 weeks of initiating AAs. Higher levels of monitoring may reduce adverse biochemical events.
Natural Selection and Functional Potentials of Human Noncoding Elements Revealed by Analysis of Next Generation Sequencing Data

Noncoding DNA sequences (NCS) have attracted much attention recently due to their functional potentials. Here we attempted to reveal the functional roles of noncoding sequences from the point of view of natural selection that typically indicates the functional potentials of certain genomic elements. We analyzed nearly 37 million single nucleotide polymorphisms (SNPs) of Phase I data of the 1000 Genomes Project. We estimated a series of key parameters of population genetics and molecular evolution to characterize sequence variations of the noncoding genome within and between populations, and identified the natural selection footprints in NCS in worldwide human populations. Our results showed that purifying selection is prevalent and there is substantial constraint of variations in NCS, while positive selectionis more likely to be specific to some particular genomic regions and regional populations. Intriguingly, we observed larger fraction of non-conserved NCS variants with lower derived allele frequency in the genome, indicating possible functional gain of non-conserved NCS. Notably, NCS elements are enriched for potentially functional markers such as eQTLs, TF motif, and DNase I footprints in the genome. More interestingly, some NCS variants associated with diseases such as Alzheimer's disease, Type 1 diabetes, and immune-related bowel disorder (IBD) showed signatures of positive selection, although the majority of NCS variants, reported as risk alleles by genome-wide association studies, showed signatures of negative selection. Our analyses provided compelling evidence of natural selection forces on noncoding sequences in the human genome and advanced our understanding of their functional potentials that play important roles in disease etiology and human evolution.
Optimal Appearance Model for Visual Tracking

Many studies argue that integrating multiple cues in an adaptive way increases tracking performance. However, what is the definition of adaptiveness and how to realize it remains an open issue. On the premise that the model with optimal discriminative ability is also optimal for tracking the target, this work realizes adaptiveness and robustness through the optimization of multi-cue integration models. Specifically, based on prior knowledge and current observation, a set of discrete samples are generated to approximate the foreground and background distribution. With the goal of optimizing the classification margin, an objective function is defined, and the appearance model is optimized by introducing optimization algorithms. The proposed optimized appearance model framework is embedded into a particle filter for a field test, and it is demonstrated to be robust against various kinds of complex tracking conditions. This model is general and can be easily extended to other parameterized multi-cue models.
Exploring the Attitudinal Structure of Partisanship

This study examined the structure of attitudes toward the political party an individual primarily identifies with and attitudes toward the other party with an emphasis on differentiating between the cognitive and affective components. Participants responded to a telephone survey that included measures of party identification, partisan attitudes, political information involvement activities, and voting behavior. Results indicated attitudes toward the parties were a function of both cognitive and affective components, although strong partisans had an attitudinal structure characterized as having a stronger cognitive component. Strong partisans were more polarized in their attitudes across parties. In addition, individuals with more cognitive-affective ambivalence toward their own parties were less likely to vote, and their votes were less likely to be along party lines. jasp_657 2232.2266
Fear of Crime and the Psychology of Risk

The Encyclopedia of Criminology and Criminal Justice is an international, comprehensive reference tool for the field of Criminology and Criminal Justice that is both cutting edge as well as of very high scientific quality and prestige. This 8-volume work provides a complete and systematic coverage of the field that is unprecedented. The Encyclopedia aims to "define the field" through its choice of organization and entries. It also seeks to identify and bring to the forefront emerging ideas and trends. The Encyclopedia covers Criminology and Criminal Justice in ten broad areas, with leading researchers writing substantive contributions within their area of expertise.
MaltParser and LIBLINEAR Transition-based dependency parsing with linear classification for feature model optimization

In this thesis, MaltParser has been extended with an interface to a software for large-scale linear classification (LIBLINEAR). This combination was then used for learning and parsing with four different treebanks (Slovene, Danish, Arabic, and Turkish). The initial tests compared the accuracy of MaltParser using LIBLINEAR to that when using LibSVM (MaltParser’s default classifier) with its linear algorithm. The results are significantly different in favor of LibSVM for two of the four treebanks (Danish and Arabic). The LIBLINEAR classifier was then used for optimizing a feature model for each of the four treebanks. These results showed a significant improvement compared to the baseline feature model both when using only LIBLINEAR, and when using the optimized feature model with LibSVM. Learning and parsing times are much smaller when using LIBLINEAR, though accuracy is not quite as high as that of LibSVM’s polynomial kernel. In conclusion, using LIBLINEAR for feature model optimization is a good idea, since it takes advantage of the speed of LIBLINEAR while not sacrificing accuracy when using LibSVM’s polynomial kernel for the final feature model. This also indicates that the MaltParser/LIBLINEAR combination should be explored further, and preferably with larger treebanks.
Home Sweet Messy Home: Managing Symbolic Pollution

Hanging up our coat, tidying our desk, classifying our books, what meanings do these mundane practices convey? Extending Mary Douglas’s work, this article investigates tidiness from the angle of symbolic pollution. Based on photo-elicitation, it shows that, similarly to symbolic pollution described at a macro-social level, tidiness depends on two conditions, namely, a set of classifications and the dangerous transgression of these classifications. However, at a micro-social level, individuals negotiate boundaries between classifications in order to cope with symbolic pollution. Consumers define their domestic classifications through a juxtaposition of micro-practices, which does not necessarily create a hierarchically ordered system but which enables these consumers to avoid anomalies and transgressions. Furthermore, respondents are willing to break tidiness rules on specific occasions because the danger-beliefs associated with transgression are context-dependent. This analysis of tidiness gives new insights into materiality, emphasizing the cultural meaning of ordering one’s possessions.
How Do I Trust Thee? Dynamic Trust Profiles and Their Individual and Social Contextual Determinants

Levels of trust in a social relationship can fluctuate over time. However, few studies have directly examined the different trust decisions involved as the relationship progresses and delineated the various trust patterns that arise from these decisions. Our analysis examined the key processes in trust decisions during the phases of trust formation, dissolution, and restoration. These trust decisions across phases give rise to trust profiles. In this chapter, we discuss six unique trust profiles: High Trust, High Distrust, Tit-for-Tat, Seizing and Freezing, Assessment, and Grim Trigger, based on divergent trust patterns across trust phases. We focus on how individual and social contextual factors affect these patterns of trust. Our model highlights the need to consider multiple trust phases both theoretically and empirically to offer a more holistic understanding of how trust unfolds overtime in social relationships.
STRATEGI PENGEMBANGAN USAHA INDUSTRI KECIL PENANGKARAN BURUNG ANIS KEMBANG CURAH NANGKA-AMBULU DI KABUPATEN JEMBER

The general objective of this research is to determine the development strategy of bird breeding small-scale industries in Jember Regency. The specific objectives of this research are : (1) to know the aspects of the strategy management of internal and eksternal environment that can be the strength, weakness, opportunity and threat for the development of bird breeding small-scale industries; and (2) to know the business unit position of the development of bird breeding small-scale industries. According to marks given to the aspects of management strategy of internal and eksternal environment formulated is the SWOT matrix analysis diagram, the bird breeding small-scale industries in Jember Regency lies in the most not beneficial condition. That’s why; the strategy that is used in the bird breeding small-scale industries in Jember Regency is the Turn a Round Strategy. According to the result of teh Market Share Growth matrix analysis diagram of Boston Consulting Group (BCG), the bird breeding small-scale industries in Jember Regency on dogs position. According to the research of teh analysis of the strategy manajement of internal and eksternal environment that can be strength, weakness, opportunity and threat for the development of bird breeding small-scale industriesand the business unit position of the development of bird-breeding small-scale industries, the right development strategy of bird-breeding small-scale industries in Jember Regency is the Turn a Round Strategy through the Improvement Market Growth Rate and Relative Market Share
Limiting information leakage in event-based communication

Event-based communication is a major source of power and flexibility for today's applications. For example, in the context of a web browser, the dynamism of user experience is driven by events: fine-grained interaction of the user with a web application triggers events reactively handled by JavaScript code. This paper explores channels for leaking sensitive information through constructs in a reactive language. We propose a general and realizable security framework for preventing information leaks in a reactive setting with such features as new handler creation and hierarchical event structures. While prior work largely takes an all-or-nothing approach to information flows due to intermediate output, our framework tightly regulates the bandwidth of such flows: at most log(n + 1) bits are allowed to be released, where n is the number of public inputs to the program. We gain flexibility from distinguishing between the security levels of message existence and content. A combination of flow-sensitive analysis and buffering output enables us to enforce security without being overly restrictive.
Reliability of Cardiorespiratory Parameters During Cycling Exercise Performed at the Severe Domain in Active Individuals

Abstract Barbosa, LF, Montagnana, L, Denadai, BS, and Greco, CC. Reliability of cardiorespiratory parameters during cycling exercise performed at the severe domain in active individuals. J Strength Cond Res 28(4): 976–981, 2014—The purpose of this study was to determine the test–retest reliability of cardiorespiratory parameters during cycling exercise performed at severe domain in active individuals. Thirteen active males (24.5 ± 4.5 years) performed the following tests: (a) an incremental test to determine V[Combining Dot Above]O2max and the intensity associated with V[Combining Dot Above]O2max (IV[Combining Dot Above]O2max); and (b) 4 repetitions of square-wave transitions from rest to a power corresponding to 95%IV[Combining Dot Above]O2max to determine the parameters of V[Combining Dot Above]O2 kinetics and time to exhaustion (Tlim). Participants performed only 2 transitions on any given day. The interval between the 2 experimental sessions was 48–72 hours. The intraclass correlation coefficient (ICC) and typical error as the coefficient of variation were used to assess reliability. Although the 2 measures of Tlim were moderately related (ICC = 0.78; p < 0.01), Tlim from the second session (545.2 ± 103.1 seconds) was significantly higher than that of the first (492.5 ± 100.9 seconds; p = 0.02). Moderate to high reliability (ICC = 0.76–0.93) for the amplitudes of the V[Combining Dot Above]O2 kinetics responses was found. Poor reliability, however, was found for time constants and time delays of the V[Combining Dot Above]O2 kinetics responses. Thus, in nonfamiliarized individuals, Tlim shows a relatively low within-subject coefficient of variation. However, the second score in a series of 2 Tlim tests may be significantly greater than the first. We have also demonstrated that the amplitudes of the V[Combining Dot Above]O2 response have significantly moderate to high reliability. The time-based parameters, however, present an important day-to-day intraindividual variation. Therefore, several transitions are recommended to monitoring changes in an individual over any time frame.
The Structure of Liberty: Justice and the Rule of Law

In this book, legal scholar Randy Barnett elaborates and defends the fundamental premise of the Declaration of Independence: that all persons have a natural right to pursue happiness so long as they respect the equal rights of others, and that governments are only justly established to secure these rights. Drawing upon insights from philosophy, economics, political theory, and law, Barnett explains why, when people pursue happiness while living in society with each other, they confront the pervasive social problems of knowledge, interest and power. These problems are best dealt with by ensuring the liberty of the people to pursue their own ends, but this liberty is distinguished from "license" by certain fundamental rights and procedures associated with the classical liberal conception of "justice" and "the rule of law. " He then outlines the constitutional framework that is needed to put these principles into practice. In a new Afterword to this second edition, Barnett elaborates on this thesis by responding to several important criticisms of the original work. He then explains how this "libertarian" approach is more modest than either the "social justice" theories of the left or the "legal moralism" of the right.
A PLSPM-Based Test Statistic for Detecting Gene-Gene Co-Association in Genome-Wide Association Study with Case-Control Design

For genome-wide association data analysis, two genes in any pathway, two SNPs in the two linked gene regions respectively or in the two linked exons respectively within one gene are often correlated with each other. We therefore proposed the concept of gene-gene co-association, which refers to the effects not only due to the traditional interaction under nearly independent condition but the correlation between two genes. Furthermore, we constructed a novel statistic for detecting gene-gene co-association based on Partial Least Squares Path Modeling (PLSPM). Through simulation, the relationship between traditional interaction and co-association was highlighted under three different types of co-association. Both simulation and real data analysis demonstrated that the proposed PLSPM-based statistic has better performance than single SNP-based logistic model, PCA-based logistic model, and other gene-based methods.