Miracle-dz/UniFAR-FTUs huggingface dataset:
Classification of Vehicle Collision Patterns in Road Accidents using Data Mining Algorithms

paper emphasizes the importance of Data Mining classification algorithms in predicting the vehicle collision patterns occurred in training accident data set. This paper is aimed at deriving classification rules which can be used for the prediction of manner of collision. The classification algorithms viz. C4.5, C-RT, CS-MC4, Decision List, ID3, Naive Bayes and RndTree have been applied in predicting vehicle collision patterns. The road accident training data set obtained from the Fatality Analysis Reporting System (FARS) which is available in the University of Alabama's Critical Analysis Reporting Environment (CARE) system. The experimental results indicate that RndTree classification algorithm achieved better accuracy than other algorithms in classifying the manner of collision which increases fatality rate in road accidents. Also the feature selection algorithms including CFS, FCBF, Feature Ranking, MIFS and MODTree have been explored to improve the classifier accuracy. The result shows that the Feature Ranking method significantly improved the accuracy of the classifiers.
Regulatory B Cells and Allergy : Uncovering the

Regulatory B (Breg) cells are recognized as immunosuppressive cells. During the last few years, several subsets of Breg cells with different phenotypes and suppressive mechanisms have been described in the literature. We review the role of Breg cells in allergy based on an extensive literature search in PubMed. We describe the types and mechanisms of action of B cells and their role in the pathogenesis of several allergic diseases (allergic asthma, allergic rhinitis, food allergy, contact hypersensitivity, and anaphylaxis).
Mr Davis vs Mr Davin : Effects of name frequency on learning proper names in young and older adults

Two theoretical frameworks relevant to proper name learning in ageing make competing predictions about the effects of name frequency. Under an inhibition model, common (high-frequency; HF) proper names will be harder to learn and remember than rare (low-frequency; LF) names, whereas under a transmission deficit model, HF names will have the advantage. Young adults (ages 18 31) and two groups of healthy older adults (ages 60 74 and 75 89) learned HF (e.g., Davis) and LF (e.g., Davin) surnames in association with new faces. Young adults recalled more names than older or oldest adults, and participants of all ages recalled more HF than LF names. There was no interaction between age and name frequency: The difference favouring HF names was similar in magnitude across age groups. All evidence runs contrary to the inhibitory model’s prediction that interference makes learning HF names difficult.
Fe-S Cluster Assembly Pathways in Bacteria

SUMMARY Iron-sulfur (Fe-S) clusters are required for critical biochemical pathways, including respiration, photosynthesis, and nitrogen fixation. Assembly of these iron cofactors is a carefully controlled process in cells to avoid toxicity from free iron and sulfide. Multiple Fe-S cluster assembly pathways are present in bacteria to carry out basal cluster assembly, stress-responsive cluster assembly, and enzyme-specific cluster assembly. Although biochemical and genetic characterization is providing a partial picture of in vivo Fe-S cluster assembly, a number of mechanistic questions remain unanswered. Furthermore, new factors involved in Fe-S cluster assembly and repair have recently been identified and are expanding the complexity of current models. Here we attempt to summarize recent advances and to highlight new avenues of research in the field of Fe-S cluster assembly.
Unresolved issues in pre-meiotic anther development

Compared to the diversity of other floral organs, the steps in anther ontogeny, final cell types, and overall organ shape are remarkably conserved among Angiosperms. Defects in pre-meiotic anthers that alter cellular composition or function typically result in male-sterility. Given the ease of identifying male-sterile mutants, dozens of genes with key roles in early anther development have been identified and cloned in model species, ordered by time of action and spatiotemporal expression, and used to propose explanatory models for critical steps in cell fate specification. Despite rapid progress, fundamental issues in anther development remain unresolved, and it is unclear if insights from one species can be applied to others. Here we construct a comparison of Arabidopsis, rice, and maize immature anthers to pinpoint distinctions in developmental pace. We analyze the mechanisms by which archesporial (pre-meiotic) cells are specified distinct from the soma, discuss what constitutes meiotic preparation, and review what is known about the secondary parietal layer and its terminal periclinal division that generates the tapetal and middle layers. Finally, roles for small RNAs are examined, focusing on the grass-specific phasiRNAs.
The Socioeconomic Achievement of White Religio-Ethnic Subgroups: Social and Psychological Explanations

In longitudinal data for the decade 1957-67, the socioeconomic achievement of white metropolitan native males from five religio-ethnic backgrounds is examined. Jews, regardless of ethnic ancestry, attain higher levels of education, occupation, and income than all other subgroups, while Roman Catholics of Italian and Mexican heritage achieve the lowest levels. Controlling statistically for social origins reduces the gross differentials by about one-third; no net effect of religio-ethnic affiliation remains during the ten-year period after both social origins and prior achieved statuses are controlled. Thus, there is no evidence of occupational and income discrimination on purely religious or ethnic grounds. Contrary to current emphasis in the social psychology of religio-ethnic achievement, achievement-related work values and motivations of adults are neither key intervening variables nor do they influence the process of stratification to a substantial degree. The most important variable in explaining the differential socioeconomic achievement of the religio-ethnic subgroups is education, after the variation owing to the handicaps and benefits of social origins has been removed statistically.
TRANSFORMATIONAL GRAMMAR AND LANGUAGE TEACHING1

There are two major theories of language learning: one, based on behavioral psychology, emphasizes pattern-practice and memorization; the other, the rationalist approach, attempts to give students the reasons for grammatical phenomena, relating facts about the second language to facts about the student's native language. Of these, the first has been much used recently, both in structuralist texts and those that are supposedly “transformational”. While memorization and pattern-practice drills are sometimes useful, often they are not, because the choice between forms is based on the speaker's awareness of factors outside of the immediate syntactic environment: the definite or indefinite article, some or any, past or perfect tense are a few examples in English. To incorporate such insights in a text the writer must use his knowledge of transformational grainmar indirectly, to enable him to formulate and verify his intuitions; but he will not use any “transformational rules” in the text itself. The text will be rationalistically oriented-it will encourage students to ask themselves why sentences are good and bad-and in this sense will be truly transformational in accordance with the beliefs held by transformational grammarians about the nature and acquisition of language.
Using Chapel to Implement Dense Linear Algebra Libraries

This paper evaluates the parallel global-view language Chapel’s ability to implement dense linear algebra libraries. Both programmability and performance characteristics at the current stage of Chapel’s implementation are considered but since many of Chapel’s compiler optimizations are not implemented our emphasis is on programmability. Our conclusion is that in its current development state Chapel lacks the data locality features required to implement efficient dense linear algebra operations but should be considered again once the complete language and compiler optimizations are implemented.
Lewy Bodies, Vascular Risk Factors, and Subcortical Arteriosclerotic Leukoencephalopathy, but not Alzheimer Pathology, are Associated with Development of Psychosis in Alzheimer's Disease.

BACKGROUND The neuropathological correlates of psychosis in Alzheimer's disease (AD) is unclear, with some studies reporting a correlation between psychosis and increased AD pathology while others have found no association. OBJECTIVE To determine the demographic, clinical, and neuropathological features associated with psychotic symptoms in clinically attributed and neuropathologically proven AD. METHOD We separately reviewed two overlapping groups of clinically diagnosed (cAD) AD patients with neuropathology data and neuropathologically definite (npAD) cases (regardless of clinical diagnosis) from the NACC database, and explored the relationships between psychosis and clinical variables, neuropathologic correlates, and vascular risk factors. Delusions and hallucinations, defined according to the NPI-Q, were analyzed separately. RESULTS 1,073 subjects in the database fulfilled our criteria (890 cAD and 728 npAD patients). 34% of cAD and 37% of npAD had psychotic symptoms during their illness. Hallucinations were associated with greater cognitive and functional impairments on the MMSE and CDR, while delusional patients showed less impairment on CDR, consistent across cAD and npAD groups. Burden of AD pathology appears to relate to presence of psychotic symptoms in the clinical AD group, but this result is not confirmed in the neuropathologically confirmed group suggesting the findings in the clinical group were due to misdiagnosis of AD. Lewy body pathology, subcortical arteriosclerotic leukoencephalopathy, and vascular risk factors, including a history of hypertension and diabetes, were associated with the development of psychosis. METHOD Vascular and Lewy body pathologies and vascular risk factors are important modifiers of the risk of psychosis in AD.
Localization in Large Scale Sensor Networks via Semidefinite Programming and Graph Regularization

The problem of discovering low dimensional representations arises in such diverse fields of engineering as robot navigation, protein clustering, shape recognition, and sensor localization. Recently, researchers in all these areas have converged on common solutions using methods from convex optimization. In particular, many results have been obtained by constructing semidefinite programs (SDPs) with low rank solutions. While the rank of matrix variables in SDPs cannot be directly constrained, it has been observed that low rank solutions emerge naturally by computing high variance or maximal trace solutions that respect local distance constraints. In this paper, we show how to solve very large problems of this type by a matrix factorization that leads to much smaller SDPs than those previously studied. The matrix factorization is derived by expanding the solution of the original problem in terms of the bottom eigenvectors of a graph Laplacian. The smaller SDPs obtained from this matrix factorization yield very good approximations to solutions of the original problem. Moreover, these approximations can be further refined by conjugate gradient descent. We illustrate the approach on localization in large scale sensor networks, where optimizations involving tens of thousands of nodes can be solved in just a few minutes.
Improving Hyperspectral Image Classification by Fusing Spectra and Absorption Features

Many features can be extracted to classify hyperspectral imagery. Classification relying on a single feature set may lose some useful information due to the intrinsic limitation of each feature extraction model. To improve classification accuracy, we propose an information fusion approach, in which both the global and the local aspects of hyperspectral data are taken into account and are combined by a decision-level fusion method. The global features are hyperspectral reflectance curves representing the holistic response to the incident light, and the local features are absorption characteristics reflected by materials’ individual constituents. The decision-level fusion is carried out by analyzing the entropy of the classification output from the global feature set and modifying this output via the results of a multilabel classification using the local feature set. Simulations of classification performance on 16 classes of vegetation from the AVIRIS 92AV3C and Salinas data set show the effectiveness of the method, which increases the classification accuracy compared to a popular support vector machine-based method and a production-rule-based decision fusion method.
Atomoxetine in the treatment of children and adolescents with attention-deficit/hyperactivity disorder: a randomized, placebo-controlled, dose-response study.

OBJECTIVE Atomoxetine is an investigational, nonstimulant pharmacotherapy being studied as potential treatment for attention-deficit/hyperactivity disorder (ADHD). It is thought to act via blockade of the presynaptic norepinephrine transporter in the brain. We assessed the efficacy of 3 doses of atomoxetine compared with placebo in children and adolescents with ADHD. METHODS A total of 297 children and adolescents who were 8 to 18 years of age and had ADHD as defined by the Diagnostic and Statistical Manual of Mental Disorders, 4th edition, were randomized to placebo or atomoxetine dosed on a weight-adjusted basis at 0.5 mg/kg/day, 1.2 mg/kg/day, or 1.8 mg/kg/day for an 8-week period. ADHD symptoms, affective symptoms, and social and family functioning were assessed using parent and investigator rating scales. RESULTS Approximately 71% of children enrolled were male, approximately 67% met criteria for mixed subtype (both inattentive and hyperactive/impulsive symptoms), and the only common psychiatric comorbidity was oppositional defiant disorder (approximately 38% of the sample). At baseline, symptom severity was rated as moderate to severe for most children. At endpoint, atomoxetine 1.2 mg/kg/day and 1.8 mg/kg/day were consistently associated with superior outcomes in ADHD symptoms compared with placebo and were not different from each other. The dose of 0.5 mg/kg/day was associated with intermediate efficacy between placebo and the 2 higher doses, suggesting a graded dose-response. Social and family functioning also were improved in the atomoxetine groups compared with placebo with statistically significant improvements in measures of children's ability to meet psychosocial role expectations and parental impact. Discontinuations as a result of adverse events were <5% for all groups. CONCLUSION Among children and adolescents aged 8 to 18, atomoxetine was superior to placebo in reducing ADHD symptoms and in improving social and family functioning symptoms. Atomoxetine was associated with a graded dose-response, and 1.2 mg/kg/day seems to be as effective as 1.8 mg/kg/day and is likely to be the appropriate initial target dose for most patients. Treatment with atomoxetine was safe and well tolerated.
Evaluation of Colposcopically Directed Cervical Biopsies Yielding a Histologic Diagnosis of CIN 1,2

Objective. To determine the prognostic value of the diagnostic category CIN 1,2. Materials and Methods. Computerized pathology records of patients with CIN 1,2 at colposcopically directed biopsy followed by treatment with excision were examined, and we compared the diagnostic biopsy with the final tissue diagnosis. Two pathologists who were blinded to the final diagnosis reviewed the original biopsies independently. The ability of the referee pathologist to predict CIN 2 or 3 lesions and interobserver consistency are described. Results. Sixty-nine cases of biopsies with CIN 1,2 were reviewed. Nineteen of these patients were lost to follow-up. Of the 46 cases with either an excisional biopsy or hysterectomy, 12 cases (26.1%) demonstrated CIN 2 or greater. Pathologist A and B correctly predicted the high-grade lesions in 66.7% and 58.3% of cases reviewed. Pathologist A and B agreed with each other in 33 of the 46 cases (71.1%). Conclusions. 1) CIN 1,2 on a colposcopic biopsy is associated with a high-grade lesion in 26.1% of the cases. 2) Experienced gynecologic pathologists can identify these high-grade lesions on review in only two thirds of the cases. 3) CIN 1,2 is a useful diagnostic category to prevent undertreatment.
A Measurement-Assisted, Model-Based Admission Control Algorithm for IEEE 802.11e

The enhanced distributed channel access (EDCA) is designed to provide differentiated services without real performance guarantees such as hard bandwidth and delay bounds in the IEEE 802.11e based wireless LANs. In this paper we design a measurement-assisted, model-based call admission control (MM- CAC) scheme to support guaranteed QoS in the EDCA. For this purpose, we first develop a novel analytical model of the legacy IEEE 802.11 DCF under non-saturation conditions; then using this model, we define the concept of equivalent number of competing entities, to convert a heterogeneous (multi-class) EDCA network into an equivalent homogeneous network. Our analytical model is then invoked to decide to admit a new flow or reject it with much little computational complexity as compared to a fully fledged EDCA model. Numerical results validate our model and analysis, and simulations demonstrate the effectiveness of our MM-CAC scheme.
GENDER DIFFERENCES IN ENTREPRENEURIAL INTENTIONS: EVIDENCE FROM BULGARIA

Despite the increasing interest in researching female entrepreneurship, little is known about gender differences in pre-venture process and the variables that mediate the relationship between gender and entrepreneurial intentions. The purpose of this study is to provide a conceptual framework for understanding gender differences in entrepreneurial intentions. Using this framework, we explore gender effects on entrepreneurial intentions and identify factors that may account for the gender gap in entrepreneurial intentions in a sample of Bulgarian university students. Our results show that women have lower entrepreneurial intentions than men. The gender effect on entrepreneurial intentions is fully mediated by perceived behavioral control and partially mediated by perceived subjective norms and attitudes toward entrepreneurship. Policy measures designed to encourage female start-ups should be directed at attitudes, subjective norms, perceived behavioral control and the link between entrepreneurial intentions and behavior among women.
Farm Crisis, Mobility and Structural Change in Swedish Agriculture, 1992–2000

This is a longitudinal study of structural change in Swedish agriculture during 1992 to 1999/ 2000, in which period the country entered the European Union and its agriculture went through a major economic crisis. The study is unique in drawing on a theoretically grounded typology to describe the agrarian structure and its dynamism. The results show that there has been a great deal of mobility of farming households in the agrarian structure during the period. As expected, the rate of closure has been high. It is remarkable, though, that despite the fluidity, the farm structure remains remarkably stable, but increasingly bimodal: it continues to be dominated economically by a relatively small stratum of family farms, while being numerically dominated by part-time farms and by pluriactive farmers.
T3FAH: A TTCN-3 Based Fuzzer with Attack Heuristics

Fuzzing is an effective approach to detect vulnerabilities. Unfortunately, the existing fuzzing approach suffers from some limitations, especially lacking support for automation in extracting the SUT specific knowledge and generating test script. In this paper, by combining fuzzing with TTCN-3 technique, we present T3FAH: a TTCN-3 based Fuzzer with Attack Heuristics. The approach automatically extracts the input syntax of SUT from existing test data definitions in TTCN-3 conformance test suite, generates invalid inputs based on the attack heuristic generation algorithm, and automatically constructs fuzzing test script via reusing the conformance test case. We conducted a case study on three popular SIP terminals with different SIP protocol implementations. In the case study, our approach detected several different vulnerabilities in all three SIP terminals, which may damage user experience in the practical use. It proves that our approach can be effectively used for testing real world applications.
A Tucker Deep Computation Model for Mobile Multimedia Feature Learning

Recently, the deep computation model, as a tensor deep learning model, has achieved super performance for multimedia feature learning. However, the conventional deep computation model involves a large number of parameters. Typically, training a deep computation model with millions of parameters needs high-performance servers with large-scale memory and powerful computing units, limiting the growth of the model size for multimedia feature learning on common devices such as portable CPUs and conventional desktops. To tackle this problem, this article proposes a Tucker deep computation model by using the Tucker decomposition to compress the weight tensors in the full-connected layers for multimedia feature learning. Furthermore, a learning algorithm based on the back-propagation strategy is devised to train the parameters of the Tucker deep computation model. Finally, the performance of the Tucker deep computation model is evaluated by comparing with the conventional deep computation model on two representative multimedia datasets, that is, CUAVE and SNAE2, in terms of accuracy drop, parameter reduction, and speedup in the experiments. Results imply that the Tucker deep computation model can achieve a large-parameter reduction and speedup with a small accuracy drop for multimedia feature learning.
Issues Related to Judging the Alignment of Curriculum Standards and Assessments

Abstract A process for judging the alignment between curriculum standards and assessments developed by the author is presented. This process produces information on the relationship of standards and assessments on four alignment criteria: Categorical Concurrence, Depth of Knowledge Consistency, Range of Knowledge Correspondence, and Balance of Representation. Five issues are identified—but not resolved—that have arisen from conducting alignment studies. All of these issues relate to making a decision about what alignment is good enough. Pragmatic decisions have been made to specify acceptable levels for each of the alignment criteria. The assumptions are described. The issues discussed arise from a change in the underlying assumptions and from considering variations in the purpose for an assessment. The existence of such issues reinforces that alignment judgments have an element of subjectivity.