Miracle-dz/UniFAR-FTUs huggingface dataset:
Concurrent Validity of the Wechsler Abbreviated Scale of Intelligence (WASI) with a Sample of Canadian Children

The Wechsler Abbreviated Scale of Intelligence (WASI; Wechsler, 1999) subtest and IQ scores were correlated with the Canadian Achievement Tests/2 and the Canadian Test of Cognitive Skills using 64 grade four Canadian children. The pattern of correlations offer preliminary support for the use of the WASI in assessing the ability levels of Canadian school children.
Analysis of WWW traffic in Cambodia and Ghana

In this paper we present an analysis of HTTP traffic captured from Internet cafés and kiosks from two different developing countries -- Cambodia and Ghana. This paper has two main contributions. The first contribution is a analysis of the characteristics of the web trace, including the distribution and classification of the web objects requested by the users. We outline notable features of the data set which effect the performance of the web for users in developing regions. Using the trace data, we also perform several simulation analyses of cache performance, including both traditional caching and more novel off-line caching proposals. The second contribution is a set of suggestions on mechanisms to improve the user experience of the web in these regions. These mechanisms include both applications of well-known research techniques as well as offering some less well-studied suggestions based on intermittent connectivity.
Building an Infrastructure for Urgent Computing

Large-scale scientific computing is playing an ever-increasing role in critical decision-making and dynamic, event-driven systems. While some computation can simply wait in a job queue until resources become available, key decisions concerning life-threatening situations must be made quickly. A computation to predict the flow of airborne contaminants from a ruptured railcar must guide evacuation rapidly, before the results are meaningless. Although not as urgent, on-demand computing is often required to leverage a scientific opportunity. For example, a burst of data from seismometers could trigger urgent computation that then redirects instruments to focus data collection on specific regions, before the opportunity is lost. This paper describes the challenges of building an infrastructure to support urgent computing. We focus on three areas: the needs and requirements of an urgent computing system, a prototype urgent computing system called SPRUCE currently deployed on the TeraGrid, and future technologies and directions for urgent computing. Since the days of the first supercomputers, computation has been playing an everincreasing role in science.
Integrating tags in a semantic content-based recommender

Basic content personalization consists in matching up the attributes of a user profile, in which preferences and interests are stored, with the attributes of a content object. The Web 2.0 (r)evolution and the advent of user generated content have changed the game for personalization, since the role of people has evolved from passive consumers of information to that of active contributors. One of the forms of user generated content that has drawn more attention from the research community is folksonomy, a taxonomy generated by users who collaboratively annotate and categorize resources of interests with freely chosen keywords called tags. In this paper, we investigate whether folksonomies might be a valuable source of information about user interests. The main contribution is a strategy that enables a content-based recommender to infer user interests by applying machine learning techniques both on the "official" item descriptions provided by a publisher, and on tags which users adopt to freely annotate relevant items. Static content and tags are preventively analyzed by advanced linguistic techniques in order to capture the semantics of the user interests often hidden behind keywords. The proposed approach has been evaluated in the context of cultural heritage personalization. Preliminary experiments involving 30 real users show an improvement in the predictive accuracy of the tag-augmented recommender compared to the pure content-based one.
Family and Neighborhood Violence: Predictors of Depressive Symptomatology among Incarcerated Youth

This study surveyed 178 children incarcerated in training schools in North Carolina to estimate the proportion of children who had been witnesses to or victims of neighborhood and family violence, the children's levels of depressive symptoms, and relationships between violence exposure and depressive symptoms. Neighborhood violence was assessed using questions adapted from Richters and Martinez, family violence was assessed using questions from the Conflict Tactics Scales, and depressive symptoms were assessed using the Children's Depression Inventory. Results showed that the majority of children reported having been exposed to neighborhood and family violence. Children evidenced high levels of depressive symptoms with more than 70% showing clinically relevant levels of symptomatology. Multiple linear regression procedures found that both neighborhood and family violence were predictive of the levels of depressive symptoms. These findings underline the need to provide highquality therapeutic services to children during incarceration in training schools and after their discharge.
Effect of the Lipoxygenase Inhibitor Baicalein on Muscles in Ovariectomized Rats

Sarcopenia, a loss of muscle mass accompanying osteoporosis, leads to falls and fall-related injuries. Baicalein, as a phytochemical agent, has an antioxidative and anti-inflammatory effect in muscle. In this study, sixty-one female Sprague Dawley rats were divided into five groups: four groups were ovariectomized (OVX) and one control group was nonovariectomized (NON-OVX). Eight weeks after ovariectomy, three disparate concentrations (1 mg/kg body weight (BW), 10 mg/kg BW, and 100 mg/kg BW) of baicalein were applied subcutaneously daily in three OVX groups. Mm. soleus, gastrocnemius, and longissimus were extracted; their diameter, area, relation to body, and muscle weights as well as number of capillaries per fibre were recorded. In Mm. soleus and gastrocnemius, the baicalein effect (increasing number of capillaries per fibre) was proportional to the dose applied. The fibre diameters and area under baicalein treatment were significantly greater compared to OVX and NON-OVX groups. In M. longissimus, we observed a shift to type IIa fibres. Serum creatine kinase levels were significantly lower in highest baicalein concentration group. We conclude that baicalein can stimulate angiogenesis, though not fibre type-specific, in skeletal muscle and reduce the estrogen-related loss of fibre diameter and area in the skeletal muscle in rats. Therefore, a protective effect of baicalein on muscle cells can be assumed.
Performance analysis of free-space optical communication systems over atmospheric turbulence channels

Turbulence fading is one of the main impairments affecting the operation of free-space optical (FSO) communication systems. The authors study the performance of FSO communication systems, also known as wireless optical communication systems, over log-normal and gamma-gamma atmospheric turbulence-induced fading channels. These fading models describe the atmospheric turbulence because of its very good agreement with experimental measurement data. Closed-form expressions for the average (ergodic) capacity and the outage probability are derived for both statistical models. Another contribution of this work is a study of how the performance metrics are affected by the atmospheric conditions and other parameters such as the length of the link and the receiver's aperture diameter. The derived analytical expressions are verified by various numerical examples and can be used as an alternative to time-consuming Monte-Carlo simulations.
Effects of hypobaric pressure on human skin: Implications for cryogen spray cooling (Part II)

Clinical results have demonstrated that dark purple port wine stain (PWS) birthmarks respond favorably to laser induced photothermolysis after the first three to five treatments. Nevertheless, complete blanching is rarely achieved and the lesions stabilize at a red‐pink color. In a feasibility study (Part I), we showed that local hypobaric pressure on PWS human skin prior to laser irradiation induced significant lesion blanching. The objective of the present study (Part II) is to investigate the effects of hypobaric pressures on the efficiency of cryogen spray cooling (CSC), a technique that assists laser therapy of PWS and other dermatoses.
Teacher Support, School Goal Structures, and Teenage Mothers' School Engagement

This study investigates how perceptions of teacher support and achievement goal structures in the school environment correlate with school engagement, and whether depressive symptoms mediate or moderate this association, among 64 low-income teenage mothers. Controlling for prior grades, perceptions of teacher support correlate with higher levels of positive affect and lower levels of negative affect about school. Perceptions of an emphasis on mastery goals in the school environment correlate with higher levels of positive affect and lower levels of school alienation. In contrast, perceptions of an emphasis on performance goals in the school environment correlate with higher levels of negative affect and school alienation. Perceptions of performance goals are especially detrimental to teenage mothers with higher levels of depressive symptoms.
Ensuring Appropriate Education: Emerging Remedies, Litigation, Compensation, and other Legal Considerations

The Individuals with Disabilities Education Act (IDEA) provides procedural and substantive educational rights to ensure a free appropriate public education (FAPE) to qualified people with disabilities. As a result of this Act, parents have been successful in receiving various remedies for violations that inhibit a student's right to FAPE. This article examines traditional remedies, such as reimbursement for residential placements, related services, and legal fees, with an added emphasis on the increasingly used remedy of compensatory education and the potential for the award of monetary damages. Compensatory education has been established as a bona fide remedy, and the award of monetary damages is appropriate given legislative mandates and judiciary holdings.
TLR7/TLR9- and B Cell Receptor-Signaling Crosstalk: Promotion of Potentially Dangerous B Cells

B cells are capable of receptor-mediated responses to foreign antigens. Recognition of microbial-derived nucleic acid (NA) by toll-like receptors (TLRs) 7 and 9 in B cells has been substantiated. Endogenous NA released from damaged or dying cells can also be immunogenic in certain contexts and can incite aberrant activation of B cells. When TLR-driven B cell receptor (BCR)-activated B cells are not properly constrained, pathologic autoantibodies are produced. It is also clear that endosomal TLR7/TLR9 can operate in conjunction with BCR. In addition to BCR signaling, a balance between TLR7 and TLR9 is pivotal in the development of B cell autoreactivity. While TLR9 is important in normal memory B cell responses through BCR, TLR9 activation has been implicated in autoantibody production. Paradoxically, TLR9 also plays known protective roles against autoimmunity by directly and indirectly inhibiting TLR7-mediated autoantibody production. Herein, we summarize literature supporting mechanisms underpinning the promotion of pathological BCR-activated B cells by TLR7 and TLR9. We focus on the literature regarding known points of TLR7/TLR9 and BCR crosstalk. Data also suggest that the degree of TLR responsiveness relies on alterations of certain intrinsic B-cell signaling molecules and is also context specific. Because allogeneic hematopoietic stem cell transplantation is a high NA and B cell-activating factor environment, we conclude that B cell studies of synergistic TLR–BCR signaling in human diseases like chronic graft-versus-host disease are warranted. Further understanding of the distinct molecular pathways mediating TLR–BCR synergy will lead to the development of therapeutic strategies in autoimmune disease states.
Astronomical Image Denoising Using Dictionary Learning

Astronomical images suffer a constant presence of multiple defects that are consequences of the atmospheric conditions and of the intrinsic properties of the acquisition equipment. One of the most frequent defects in astronomical imaging is the presence of additive noise which makes a denoising step mandatory before processing data. During the last decade, a particular modeling scheme, based on sparse representations, has drawn the attention of an ever growing community of researchers. Sparse representations offer a promising framework to many image and signal processing tasks, especially denoising and restoration applications. At first, the harmonics, wavelets and similar bases, and overcomplete representations have been considered as candidate domains to seek the sparsest representation. A new generation of algorithms, based on data-driven dictionaries, evolved rapidly and compete now with the off-the-shelf fixed dictionaries. Although designing a dictionary relies on guessing the representative elementary forms and functions, the framework of dictionary learning offers the possibility of constructing the dictionary using the data themselves, which provides us with a more flexible setup to sparse modeling and allows us to build more sophisticated dictionaries. In this paper, we introduce the centered dictionary learning (CDL) method and we study its performance for astronomical image denoising. We show how CDL outperforms wavelet or classic dictionary learning denoising techniques on astronomical images, and we give a comparison of the effects of these different algorithms on the photometry of the denoised images.
The diagnostic concept of schizophrenia: its history, evolution, and future prospects

More than a century since the delineation of dementia praecox by Kraepelin, the etiology, neuropathology and pathophysiology of schizophrenia remain elusive. Despite the availability of criteria allowing reliable diagnostic identification, schizophrenia essentially remains a broad clinical syndrome defined by reported subjective experiences (symptoms), loss of function (behavioral impairments), and variable patterns of course. Research has identified a number of putative biological markers associated with the disorder, including neurocognitive dysfunction, brain dysmorphology, and neurochemical abnormalities. Yet none of these variables has to date been definitively proven to possess the sensitivity and specificity expected of a diagnostic test. Genetic linkage and association studies have targeted multiple candidate loci and genes, but failed to demonstrate that any specif ic gene variant, or a combination of genes, is either necessary or sufficient to cause schizophrenia. Thus, the existence of a specific brain disease underlying schizophrenia remains a hypothesis. Against a background of an ever-increasing volume of research data, the inconclusiveness of the search for causes of the disorder fuels doubts about the validity of the schizophrenia construct as presently defined. Given the protean nature of the symptoms of schizophrenia and the poor coherence of the clinical and biological findings, such doubts are not without reason. However, simply dismantling the concept is unlikely to result in an alternative model that would account for the host of clinical phenomena and research data consistent with a disease hypothesis of schizophrenia. For the time being, the clinical concept of schizophrenia is supported by empirical evidence that its multiple facets form a broad syndrome with non-negligible internal cohesion and a characteristic evolution over time. The dissection of the syndrome with the aid of endophenotypes is beginning to be perceived as a promising approach in schizophrenia genetics.
Efficient Determination of Optimal Smoothing Parameters in Spline Approximations

In this paper, we present a systematic method for determining an optimal smoothing parameter, an important issue in the design of smoothing splines. The optimal parameter is obtained as the minimizer of the so-called cross-validation function, and the global minimum is found very efficiently using extrema detection method of spline functions. Compared to the conventional search algorithm, the computational amount is reduced dramatically. The effectiveness is verified by a numerical example
Spectrum Sharing in Cognitive Radio Based on Spatial Coding

In cognitive radio, secondary users wittily occupy the spectrum hole and enhance the efficiency at the right location and time. Secondary users reward a chance to access primary user band with the aid of smart cognitive radio technology. In this study we explore the idea of secondary access spectrum through using the cognitive radio network in which the secondary user shares the spectrum with the primary user and defends the primary user from the detrimental interference. Spatial coding akin to adaptive beam-forming and null steering are utilized for appropriate spectrum sharing in cognitive radio. By using these algorithms in cognitive systems, secondary transmitter steers the beam in the direction of secondary receiver and generate the nulls in primary direction so that the minimum interference spawn toward the primary receiver. Simulation outcome established the strength and efficiency of the spectrum sharing.
Learning in a small world

Understanding how we are able to perform a diverse set of complex tasks is a central question for the Artificial Intelligence community. A popular approach is to use temporal abstraction as a framework to capture the notion of subtasks. However, this transfers the problem to finding the right subtasks, which is still an open problem. Existing approaches for subtask generation require too much knowledge of the environment, and the abstractions they create can overwhelm the agent. We propose a simple algorithm inspired by small world networks to learn subtasks while solving a task that requires virtually no information of the environment. Additionally, we show that the subtasks we learn can be easily composed by the agent to solve any other task; more formally, we prove that any task can be solved using only a logarithmic combination of these subtasks and primitive actions. Experimental results show that the subtasks we generate outperform other popular subtask generation schemes on standard domains.
Low and stable HIV infection rates in Senegal: natural course of the epidemic or evidence for success of prevention?

OBJECTIVES To document the level of HIV infection in Senegal and also to review evidence of the impact of efforts in prevention, developed by the National AIDS Control Programme and the Civil Society, on the level of the HIV epidemic. METHODS Research, compilation and critical review of all relevant data on HIV and sexually transmission diseases (STDs) epidemiology, sexual behaviour, and the efforts in prevention developed in Senegal. RESULTS From 1989 to 1996, the levels of HIV infection estimated in four sentinel urban regions remained stable at around 1.2% in the population of pregnant women, and at 3% in male STD patients. It had increased to 19% in female sex workers. A strong political and community commitment led to an early response to the HIV/AIDS epidemic that has been extended since 1986. Blood transfusion safety was established at the start of the HIV epidemic. The level of knowledge of preventive practices relating to HIV/AIDS among the general population exceeded 90% in the early 1990s. From 1991 to 1996, a 30% to 66% decrease of the STD prevalence rates was observed in pregnant women and sex workers in Dakar. In 1997, 33% of men aged 15-49 years in Dakar reported having had sex with non-regular partners. Among them 67% reported condom use. CONCLUSIONS It is not possible to know what the course of the HIV epidemic in Senegal would have taken in the absence of efforts at prevention. Certainly, several factors that pre-dated the occurrence of AIDS in Senegal laid the groundwork for a positive response. However, data from a number of sources do reveal the successfulness of efforts in prevention. From available data, Senegal can rightfully claim to have contained the spread of HIV by intervening early and comprehensively to increase knowledge and awareness of HIV/AIDS and to promote safe sexual behaviour.
Multi-evidence, multi-criteria, lazy associative document classification

We present a novel approach for classifying documents that combines different pieces of evidence (e.g., textual features of documents, links, and citations) transparently, through a data mining technique which generates rules associating these pieces of evidence to predefined classes. These rules can contain any number and mixture of the available evidence and are associated with several quality criteria which can be used in conjunction to choose the "best" rule to be applied at classification time. Our method is able to perform evidence enhancement by link forwarding/backwarding (i.e., navigating among documents related through citation), so that new pieces of link-based evidence are derived when necessary. Furthermore, instead of inducing a single model (or rule set) that is good on average for all predictions, the proposed approach employs a lazy method which delays the inductive process until a document is given for classification, therefore taking advantage of better qualitative evidence coming from the document. We conducted a systematic evaluation of the proposed approach using documents from the ACM Digital Library and from a Brazilian Web directory. Our approach was able to outperform in both collections all classifiers based on the best available evidence in isolation as well as state-of-the-art multi-evidence classifiers. We also evaluated our approach using the standard WebKB collection, where our approach showed gains of 1% in accuracy, being 25 times faster. Further, our approach is extremely efficient in terms of computational performance, showing gains of more than one order of magnitude when compared against other multi-evidence classifiers.
Probabilistic acoustic volume analysis for speech affected by depression

Alterations in speech motor control in depressed individuals have been found to manifest as a reduction in spectral variability. In this paper we present a novel method for measuring acoustic volume a model-based measure that is reflective of this decrease in spectral variability and assess the ability of features resulting from this measure for indexing a speaker’s level of depression. A Monte Carlo approximation that enables the computation of this measure is also outlined in this paper. Results found using the AVEC 2013 Challenge Dataset indicate there is a statistically significant reduction in acoustic variation with increasing levels of speaker depression, and using features designed to capture this change it is possible to outperform a range of conventional spectral measures when predicting a speaker’s level of depression.