Miracle-dz/UniFAR-FTUs huggingface dataset:
Drug Testing by the Criminal Justice System: Methods, Research, and Applications

The purposes of drug testing by the criminal justice system are to screen for persons who have recently ingested a drug, to identify chronic drug users, to monitor and deter drug use, and to estimate national and local drug-use trends in criminals. Substantial work has been done on the reliability and methodology of drug-testing technologies. Most criminal justice system tests involve urinalysis. Experimental research is under way on radioimmunoassay of hair samples. Much discussion of criminal justice system drug testing focuses on pretrial drug testing, the national Drug Use Forecasting program, and the testing of juvenile detainees. Adult offenders typically began their drug use in their early teens, and drug testing of juvenile detainees may provide the most effective place for early detection and prevention of drug abuse in a high-risk population. Drug testing of persons detained or monitored by the criminal justice system raises a number of critical legal and ethical issues that differ from those raised by testing other populations.
Marginal Object Weight Ranking for Nearest Neighbor Search in Spatial databases

Uncertainty prevails in spatial databases whose objects are defined as multidimensional probable density function. Identifying an object is tedious task in uncertain spatial databases. Recent work on searching objects and its closeness to other objects was presented as superseding nearest neighbor search technique. In superseding neighbor search, one of all other objects in the spatial database, which was more close to the querying point is called as superseding nearest neighbor object. However there are cases where no object was unavailable to supersede to all other nearest neighbor object, ambiguity arises. To overcomes the situation of ambiguity, in this paper Marginal Object Weight(MOW) is introduced to all nearest neighbor object for any respective query point, from there on most highly ranked object is identified as superseding nearest neighbor object. The performance of MOW ranking on nearest neighbor search is carried out for optimal amount of query point in the spatial databases of real and synthetic dataset. The superseding nearest neighbor object obtained with MOW ranking scheme identify more optimal to the query points compared to that of unranked superseding nearest neighbor object search scheme.
High performance X-band LNAs using a 0.25 μm GaN technology

This work presents two LNAs, referred to in the following as LNA A and LNA B, respectively operating in the 8–10 GHz band and 10–12 GHz band; together they cover the full X-band. The power consumption results very low, being equal to 0.9 W for each amplifier. The total area for each LNA is 3.0×1.5 mm2. A very low noise figure has been achieved, namely of 1.1 dB (LNA A) and 1.3 dB (LNA B). The peak gain is 27 dB (LNA A) and 25 dB (LNA B). The obtained results mark an increase in performance for the 0.25 μm GaN technology in terms of noise figure, gain and matching, improving the current state of the art of GaN-based LNAs.
The Orphan Response Regulator CovR: a Globally Negative Modulator of Virulence in Streptococcus suis Serotype 2

ABSTRACT Streptococcus suis serotype 2 is an emerging zoonotic pathogen responsible for a wide range of life-threatening diseases in pigs and humans. However, the pathogenesis of S. suis serotype 2 infection is not well understood. In this study, we report that an orphan response regulator, CovR, globally regulates gene expression and negatively controls the virulence of S. suis 05ZYH33, a streptococcal toxic shock syndrome (STSS)-causing strain. A covR-defective (ΔcovR) mutant of 05ZYH33 displayed dramatic phenotypic changes, such as formation of longer chains, production of thicker capsules, and increased hemolytic activity. Adherence of the ΔcovR mutant to epithelial cells was greatly increased, and its resistance to phagocytosis and killing by neutrophils and monocytes was also significantly enhanced. More importantly, inactivation of covR increased the lethality of S. suis serotype 2 in experimental infection of piglets, and this phenotype was restored by covR complementation. Colonization experiments also showed that the ΔcovR mutant exhibited an increased ability to colonize susceptible tissues of piglets. The pleiotropic phenotype of the ΔcovR mutant is in full agreement with the large number of genes controlled by CovR as revealed by transcription profile analysis: 2 genes are positively regulated, and 193 are repressed, including many that encode known or putative virulence factors. These findings suggested that CovR is a global repressor in virulence regulation of STSS-causing S. suis serotype 2.
Islam’s View on Physical Activity and Sport

The questions asked in this study were: what kind of views do Egyptian women have on the relationship between Islam and physical activity/sport, and what consequences do different interpretations of Islam have for Egyptian women’s involvement in physical activity and sport? The data were gathered during a four-month field-study in Egypt, and consist of 27 qualitative interviews in addition to many hours of field-observation. The results show that the women in the study agreed that Islam encourages sport participation for women. The women who most strongly emphasized the fact that they had to participate in some sporting activities were supporters of the fundamentalistic interpretation of Islam. Some Muslim women therefore find a non-secular relationship between sport and religion. The study further revealed that the different interpretations of Islam had consequences for the informants’ participation in sport. These were related to the use of the veil, gender segregation, the concept of ‘excitement’ (non-sexual movements) and the power relationship between women and men. Most of these barriers seem to be products of Muslim society’s view of women and their sexuality. The data further support the opinion that power strategies get internalized into people’s bodily practice.
Estimating the pattern frequency spectrum inside the browser

Abstract—We present a browser application for estimating thenumber of frequent patterns, in particular itemsets, as well asthe pattern frequency spectrum. The pattern frequency spectrum isdeﬁned as the function that shows for every value of the frequencythreshold ˙ the number of patterns that are frequent in a givendataset. Our demo implements a recent algorithm proposed bythe authors for ﬁnding the spectrum. The application is 100%JavaScript, and runs in all modern browsers. We observe thatmodern JavaScript engines can deliver performance that makesit viable to run non-trivial data analysis algorithms in browserapplications.Keywords—pattern mining, JavaScript, web browser I. I NTRODUCTION Recent years have shown a trend of implementing moreand more complex pieces of software as browser applications,programs that run inside a browser. Example of these arethe Google Docs 1 suite of ofﬁce applications, WriteLatex 2 ,a collaborative tool for preparing documents using L A TEX, orRStudio Server
A commentary on Professor Chambers' 1999 paper the poverty of accounting discourse

Chambers’ (1999) paper on The Poverty of Accounting Discourse may well have been thelast publication before his death in the same year. Perhaps it reﬂects the dark mood of aperson feeling his end approaching—a man previously most vigorous and deﬁant, evenaggressive in spirit. Yet the paper is by no means out of line with Chambers’ ambitionto convert accounting into a genuine scientiﬁc discipline. Only by being aware of thiscrucial fact can one comprehend the positive aspects as well as fallacies of his paper.But before I touch on the latter, let me discuss those parts with which I wholeheartedlyagree. They concern Chambers’ criticism of the innumerable legal abuses of accounting,particularly those committed by professional accountants themselves, which are summar-ized in the following statements:
A FIVE‐YEAR STUDY OF UPWARD FEEDBACK: WHAT MANAGERS DO WITH THEIR RESULTS MATTERS

We present results for 252 target managers over 5 annual administrations of an upward feedback program (i.e., twice as long as any previous study in this area). We show that managers initially rated poor or moderate showed significant improvements in upward feedback ratings over the 5-year period, and that these improvements were beyond what could be expected due to regression to the mean. We also found that (a) managers who met with direct reports to discuss their upward feedback improved more than other managers, and (b) managers improved more in years when they discussed the previous year's feedback with direct reports than in years when they did not discuss the previous year's feedback with direct reports. This is important because it is the first research evidence demonstrating that what managers do with upward feedback is related to its benefits. We use an accountability framework to discuss our results and suggest directions for future research.
Effort Estimation Framework in Iterative and Incremental Development ; Issues and Proposed Solution

Software effort estimation is now dynamic issue, with the values of factors are updated frequently specially in iterative projects. The cone of uncertainty in project estimates is a reality, however the project does not follow the cone it self. The visibility of cone of uncertainty is more in iterative projects than in sequential, which require use of data from current project. There exist some models which provide the capability to learn and update these factors. However these models have some limitations, which should be addressed to develop an intelligent effort estimation model. This paper highlights some important issues in IID effort estimation and also provides a review of existing models. This paper also proposes a framework/ model to implement idioms in dynamic Bayesian networks for development of estimation model for iterative projects. Keywords-Iterative development; software estimation, uncertainty.
Rearrangement and expression of T cell antigen receptor and gamma genes during thymic development

Rearrangement and expression of the T cell antigen receptor and the gamma genes during T cell ontogeny is a regulated process; the gamma genes are rearranged and expressed first, followed by the beta and then the alpha genes. Expression of both functional alpha and beta gene RNA first occurs at day 17 of gestation, along with the expression of T3 delta chain RNA. T cell antigen receptor gene rearrangements occur primarily or exclusively in the thymus, although some gamma gene rearrangements occur outside the thymus in fetal liver cells that may be committed T cell progenitors. There is no gross difference in the extent of beta and gamma gene rearrangements in the adult thymocyte subpopulations that were analyzed, despite the fact that some of these populations cannot respond to antigen and never emigrate from the thymus. Quantitative analysis of rearrangements in total adult thymocyte DNA shows that beta gene rearrangements generally occur on both chromosomal homologs, and that rearrangements occur preferentially to the J beta 2 gene segment cluster.
INTERVENTIONS: Controversies and Evidence

■ Abstract Efforts to increase the practice of evidence-based psychotherapy in the United States have led to the formation of task forces to define, identify, and disseminate information about empirically supported psychological interventions. The work of several such task forces and other groups reviewing empirically supported treatments (ESTs) in the United States, United Kingdom, and elsewhere is summarized here, along with the lists of treatments that have been identified as ESTs. Also reviewed is the controversy surrounding EST identification and dissemination, including concerns about research methodology, external validity, and utility of EST research, as well as the reliability and transparency of the EST review process.
Categorical Data Clustering based on an Alternative Data Representation Technique

Clustering categorical data is relatively difficult than clustering numeric data. In numeric data the inherent geometric properties can be used in defining distance functions between data points. In case of categorical data, a distance or dissimilarity function can’t be defined directly. An extension of the classical k-means algorithm for categorical data has been done in [1], where a method of representing a cluster using representatives which are very much similar to means used in k-means algorithm has been proposed together with a new distance measure. In this paper we first propose an alternative representation of categorical data as numeric data making it easier to handle. This technique provides a uniform representation for data points and the cluster representatives. The similarity measure proposed in [2] has been used in this new setting. The algorithm used in [1] has been implemented and tested with this new setting and the results obtained have been reported. Experiments were conducted on two real life data sets, namely, soybean diseases, and mushroom data sets. The clusters obtained in soybean dataset are pure clusters with hundred percent accuracy. In the other dataset also it gives relatively higher accuracy with small errors.
Affective Domain and Student Learning in the Geosciences

Abstract Decades of science education research have provided us with a variety of tools to deal with the cognitive processes behind our students' learning. However, we have placed much less attention on student affect, the feelings, attitudes, emotions, and values that can encourage or discourage the adoption of effective learning behaviors. This has occurred even though the affective domain has been demonstrated to have a significant influence on student learning. An increased awareness of the role of the affective domain in the sciences has the potential to improve student learning, boost recruitment of majors, and reduce student attrition. We propose that the geoscience education research community would benefit from giving greater consideration to the role of the affective domain as a key component of the learning process.
Low Vision in the Geriatric Population: Rehabilitation and Management

Older persons represent the fastest growing segment of individuals with visual impairments in industrialized countries. This population is expected to grow dramatically in the coming years. This article discusses the common agerelated changes in vision and the most prevalent visual impairments associated with aging, and the resulting functional implications. It includes information for health care professionals about preparing an older person to benefit from low‐vision rehabilitation services, environmental evaluations and modifications, and orientation to the environment. The importance of functional assessment and instruction in the use of visual skills and vision devices is stressed. The article also emphasizes the need for teamwork to provide a full scope of rehabilitation services to older adults with low vision, and the importance of support by family members and caregivers to maximize coping, adjustment, independence and quality of life.
Visual tracking using D2-clustering and particle filter

Since tracking algorithms should be robust with respect to appearance changes, online algorithms has been investigated recently instead of offline ones which has shown an acceptable performance in controlled environments. The most challenging issue in online algorithms is updating of the model causing tracking failure because of introducing small errors in each update and disturbing the appearance model (drift). In this paper, we propose an online generative tracking algorithm in order to overcome the challenges such as occlusion, object shape changes, and illumination variations. In each frame, color distribution of target candidates is obtained and the candidate having the lowest distance to the object distribution is considered as the object. In addition, in our work, the particle filter structure is used in which the samples are weighted proportional to their distance to the model. The model which is a color distribution is updated using D2-clustring algorithm. The most distinctive features of our algorithm are: 1) Updating the model using D2-clustering, 2) Avoiding drifting by using the color distribution of the target in the first and last frame, and 3) Detecting of occlusion by considering distance between the model and the best candidate. Experimental results show that our tracker outperforms other algorithms in videos containing challenging scenarios.
Latent semantic analysis for an effective region-based video shot retrieval system

We present a complete and efficient framework for video shot indexing and retrieval. Video shots are described by their key-frame, themselves described by their regions. Region-based approaches suffer from the complexity of segmentation and comparison tasks. A compact region-based shot representation is usually obtained thanks to vector-quantization method. We thus introduce LSA to reduce the noise inherent to the segmentation and the quantization processes. Then to better capture the content of video shots, we propose two original methods. The first takes advantage of a multi-scale segmentation of frames while the second uses multiple frames to represent a shot. Both approaches require more computation time during the pre-processing but not for indexing and comparison tasks. Indeed the extra information is included in the original signatures of shots. Finally we introduce a relevance feedback loop to optimize the search and propose a new method to optimize the effect of LSA. In the experimental section, we make an evaluation of latent semantic analysis and proposed approaches on two problems, namely object retrieval and semantic content estimation
Strategy Generation with Cognitive Distance in Two-Player Games

In game theoretical approaches to multi-agent systems, a payoff matrix is often given a priori and used by agents in action selection. By contrast, in this paper we approach the problem of decision making by use of the concept of cognitive distance, which is a notion of the difficulty of an action perceived subjectively by the agent. As opposed to ordinary physical distance, cognitive distance depends on the situation and skills of the agent, ultimately representing the perceived difficulty in performing an action given the current state. The concept of cognitive distance is applied to a two-player game scenario, and it is shown how an agent can learn a model of its skills by estimating and observing the outcomes of its actions. This skill model is then used during play in a minimax search for the best actions
Context-aware sensor-doll as a music expression device

We present a sensor-doll capable of music expression as a sympathetic communication device. The doll is equipped with a computer and various sensors such as a camera, microphone, accelerometer, and touch-sensitive sensors to recognize its own situation and the activities of the user. The doll has its own internal "mind" states reflecting different situated contexts. The user's multi-modal interaction with the passive doll is translated into musical expressions that depend on the state of mind of the doll.
Active visual scene exploration

This thesis addresses information theoretic methods for control of one or several active cameras in the context of visual surveillance. This approach has two advantages. Firstly, any system dealing with real inputs must take into account noise in the measurements and the underlying system model. Secondly, the control of cameras in surveillance often has different, potentially conflicting objectives. Information theoretic metrics not only yield a way to assess the uncertainty in the current state estimate, they also provide means to choose the observation parameters that optimally reduce this uncertainty. The latter property allows comparison of sensing actions with respect to different objectives. This allows specification of a preference for objectives, where the generated control will fulfil these desired objectives accordingly. The thesis provides arguments for the utility of information theoretic approaches to control visual surveillance systems, by addressing the following objectives in particular: Firstly, how to choose a zoom setting of a single camera to optimally track a single target with a Kalman filter. Here emphasis is put on an arbitration between loss of track due to noise in the observation process, and information gain due to higher accuracy after successful observation. The resulting method adds a running average of the Kalman filter’s innovation to the observation noise, which not only ameliorates tracking performance in the case of unexpected target motions, but also provides a higher maximum zoom setting. The second major contribution of this thesis is a term that addresses exploration of the supervised area in an information theoretic manner. The reasoning behind this term is to model the appearance of new targets in the supervised environment, and use this as prior uncertainty about the occupancy of areas currently not under observation. Furthermore, this term uses the performance of an object detection method to gauge the information that observations of a single location can yield. Additionally, this thesis shows experimentally that a preference for control objectives can be set using a single scalar value. This linearly combines the objective functions of the two conflicting objectives of detection and exploration, and results in the desired control behaviour. The third contribution is an objective function that addresses classification methods. The thesis shows in detail how the information can be derived that can be gained from the classification of a single target, under consideration of its gaze direction. Quantitative and qualitative validation show the increase in performance when compared to standard methods.
Complexity not collapse: recasting the geographies of homelessness in a ‘punitive’ age

Over the past decade there has been a proliferation of work on homelessness by geographers. Much of this has been framed by the desire to connect discussions of homelessness to wider debates around gentrification, urban restructuring and the politics of public space. Though such work has been helpful in shifting discussions of homelessness into the mainstream geographical literature, too much of it remains narrowly framed within a US metric of knowledge and too closely focused upon the recent punitive turn in urban social policy. Here we advance instead a framework that recognizes the growing multiplicy of homeless geographies in recent years under policies that are better understood as multifaceted and ambivalent rather than only punitive.
Political Strategy and Cross-Cultural Variation in Games

The author hypothesizes that games of strategy will be more prevalent in societies where political power is based on a “network strategy. ” In such societies, political leaders manipulate social relations and symbols to aggrandize themselves. The author hypothesizes that such activities will promote the importance of obedience, and will foster the emergence and perpetuation of games of strategy. The author tests this hypothesis using data from a random sample of 26 societies, and finds strong support.