Miracle-dz/UniFAR-FTUs huggingface dataset:
LETOR: Benchmark Dataset for Research on Learning to Rank for Information Retrieval

This paper is concerned with learning to rank for information retrieval (IR). Ranking is the central problem for information retrieval, and employing machine learning techniques to learn the ranking function is viewed as a promising approach to IR. Unfortunately, there was no benchmark dataset that could be used in comparison of existing learning algorithms and in evaluation of newly proposed algorithms, which stood in the way of the related research. To deal with the problem, we have constructed a benchmark dataset referred to as LETOR and distributed it to the research communities. Specifically we have derived the LETOR data from the existing data sets widely used in IR, namely, OHSUMED and TREC data. The two collections contain queries, the contents of the retrieved documents, and human judgments on the relevance of the documents with respect to the queries. We have extracted features from the datasets, including both conventional features, such as term frequency, inverse document frequency, BM25, and language models for IR, and features proposed recently at SIGIR, such as HostRank, feature propagation, and topical PageRank. We have then packaged LETOR with the extracted features, queries, and relevance judgments. We have also provided the results of several state-ofthe-arts learning to rank algorithms on the data. This paper describes in details about LETOR.
Statistical analysis and prediction of protein–protein interfaces

Predicting protein–protein interfaces from a three‐dimensional structure is a key task of computational structural proteomics. In contrast to geometrically distinct small molecule binding sites, protein–protein interface are notoriously difficult to predict. We generated a large nonredundant data set of 1494 true protein–protein interfaces using biological symmetry annotation where necessary. The data set was carefully analyzed and a Support Vector Machine was trained on a combination of a new robust evolutionary conservation signal with the local surface properties to predict protein–protein interfaces. Fivefold cross validation verifies the high sensitivity and selectivity of the model. As much as 97% of the predicted patches had an overlap with the true interface patch while only 22% of the surface residues were included in an average predicted patch. The model allowed the identification of potential new interfaces and the correction of mislabeled oligomeric states. Proteins 2005. © 2005 Wiley‐Liss, Inc.
IISSSSCC DD IISSCCUUSSSSIIOONN PP AAPPEERR SS EERRIIEESS D OES E DUCATION R AISE P RODUCTIVITY OR J UST R EFLECT I T ? Dr. Arnaud

It is clear that education has an important effect on wages paid in the labour market However it not clear whether this is due to the role that education plays in raising the productivity of workers (the human capital explanation) or whether education simply reflects the ability of the worker (through a signalling role). In this paper we describe and implement, using a variety of UK datasets, a number of tests from the existing literature for discriminating between the two explanations. We find little support for signalling ideas in these tests. However, we have severe reservations about these results because our doubts about the power of these tests and the appropriateness of the data. We propose an alternative test, based on the response of some individuals to a change in education incentives offered to other individuals caused by the changes in the minimum school leaving age in the seventies. Using this idea we find that data in the UK appears to strongly support the human capital explanation. return dummy reduction in the returns to leaving at and for men and return for recent cohorts The return to age gets very large relative scarcity of well educated older individuals people in the most recent cohort. the econometric model). The results suggests some variance in the returns across individuals for unobservable reasons – but this variance, due perhaps to unobserved ability differences, does not appear to be any larger, and is arguably smaller, for more recent cohorts.
Region inference for an object-oriented language

Region-based memory management offers several important potential advantages over garbage collection, including real-time performance, better data locality, and more efficient use of limited memory. Researchers have advocated the use of regions for functional, imperative, and object-oriented languages. Lexically scoped regions are now a core feature of the Real-Time Specification for Java (RTSJ)[5]. Recent research in region-based programming for Java has focused on region checking, which requires manual effort to augment the program with region annotations. In this paper, we propose an automatic region inference system for a core subset of Java. To provide an inference method that is both precise and practical, we support classes and methods that are region-polymorphic, with region-polymorphic recursion for methods. One challenging aspect is to ensure region safety in the presence of features such as class subtyping, method overriding, and downcast operations. Our region inference rules can handle these object-oriented features safely without creating dangling references.
Care of the mentally ill in prisons: challenges and solutions.

So, where did all the [state hospital] patients go? —Emanuel Tanay, MD[1][1] Jails and prisons have become the mental asylums of the 21st Century—CNN[2][2] The United States has the highest rate of adult incarceration among the developed countries, with 2.2 million currently in jails and
Conformational Dynamics of Supramolecular Protein Assemblies in the EMDB

The Electron Microscopy Data Bank (EMDB) is a rapidly growing repository for the dissemination of structural data from single-particle reconstructions of supramolecular protein assemblies including motors, chaperones, cytoskeletal assemblies, and viral capsids. While the static structure of these assemblies provides essential insight into their biological function, their conformational dynamics and mechanics provide additional important information regarding the mechanism of their biological function. Here, we present an unsupervised computational framework to analyze and store for public access the conformational dynamics of supramolecular protein assemblies deposited in the EMDB. Conformational dynamics are analyzed using normal mode analysis in the finite element framework, which is used to compute equilibrium thermal fluctuations, cross-correlations in molecular motions, and strain energy distributions for 452 of the 681 entries stored in the EMDB at present. Results for the viral capsid of hepatitis B, ribosome-bound termination factor RF2, and GroEL are presented in detail and validated with all-atom based models. The conformational dynamics of protein assemblies in the EMDB may be useful in the interpretation of their biological function, as well as in the classification and refinement of EM-based structures.
Genetic control of invasive plants species using selfish genetic elements

Invasive plants cause substantial environmental damage and economic loss. Here, we explore the possibility that a selfish genetic element found in plants called cytoplasmic male sterility (CMS) could be exploited for weed control. CMS is caused by mutations in the mitochondrial genome that sterilize male reproductive organs. We developed an analytical model and a spatial simulation to assess the use of CMS alleles to manage weed populations. Specifically, we examined how fertility, selfing, pollen limitation and dispersal influenced extinction rate and time until extinction in populations where CMS arises. We found that the introduction of a CMS allele can cause rapid population extinction, but only under a restricted set of conditions. Both models suggest that the CMS strategy will be appropriate for species where pollen limitation is negligible, inbreeding depression is high and the fertility advantage of females over hermaphrodites is substantial. In general, spatial structure did not have a strong influence on the simulation outcome, although low pollen dispersal and intermediate levels of seed dispersal tended to reduce population extinction rates. Given these results, the introduction of CMS alleles into a population of invasive plants probably represents an effective control method for only a select number of species.
Study of Polynomial Mapping Functions in Video-Oculography Eye Trackers

Gaze-tracking data have been used successfully in the design of new input devices and as an observational technique in usability studies. Polynomial-based Video-Oculography (VOG) systems are one of the most attractive gaze estimation methods thanks to their simplicity and ease of implementation. Although the functionality of these systems is generally acceptable, there has been no thorough comparative study to date of how the mapping equations affect the final system response. After developing a taxonomic classification of calibration functions, we examined over 400,000 models and evaluated the validity of several conventional assumptions. Our rigorous experimental procedure enabled us to optimize the calibration process for a real VOG gaze-tracking system and halve the calibration time while avoiding a detrimental effect on the accuracy or tolerance to head movement. Finally, a geometry-based method is implemented and tested. The results and performance is compared with those obtained by the general purpose expressions.
An iterative approach in development of the student information system: Lessons learned

Iterative and incremental development (IID) is a staple of multiple software development methods, including Spiral development, Unified process and Agile development. However, a number of papers warn of possible pitfalls in application of this approach in examples of real-life development project. In this paper we will describe an (in our opinion) successful application of IID to a software project which is in everyday use and which has so far proven useful. In addition, we will attempt to draw some conclusions that may be of use for further research on software development methodology.
Matrix Cells from Wharton's Jelly Form Neurons and Glia

We have identified an easily attainable source of primitive, potentially multipotent stem cells from Wharton's jelly, the matrix of umbilical cord. Wharton's jelly cells have been propagated in culture for more than 80 population doublings. Several markers for stem cells, including c‐kit (CD117), and telomerase activity are expressed in these cells. Treatment with basic fibroblast growth factor overnight and low‐serum media plus butylated hydroxyanisole and dimethylsulfoxide induced Wharton's jelly cells to express a neural phenotype. Within several hours of this treatment, Wharton's jelly cells developed rounded cell bodies with multiple neurite‐like extensions, similar to the morphology of neural stem cells. Neuron‐specific enolase (NSE), a neural stem cell marker, was expressed in these cells, as shown by immunocytochemistry. Immunoblot analysis showed similar levels of NSE expression in both untreated and induced Wharton's jelly cells. After 3 days, the induced Wharton's jelly cells resembled bipolar or multipolar neurons, with processes that formed networks reminiscent of primary cultures of neurons. The neuron‐like cells in these cultures stained positively for several neuronal proteins, including neuron‐specific class III β‐tubulin, neurofilament M, an axonal growth‐cone‐associated protein, and tyrosine hydroxylase. Immunoblot analysis showed increasing levels of protein markers for mature neurons over time postinduction. Markers for oligodendrocytes and astrocytes were also detected in Wharton's jelly cells. These exciting findings show that cells from the matrix of umbilical cord have properties of stem cells and may, thus, be a rich source of primitive cells. This study shows their capacity to differentiate into a neural phenotype in vitro.
Logging key assurance indicators in business processes

Management of a modern enterprise is based on the assumption that executive reports of lower-layer management are faithful to what is actually happening in the field. As some well-publicised major recent disasters (such as Barings, AllFirst-Allied Irish Bank, ENRON, Societé Generale) have shown, this assumption is not well-founded. Intermediate managers can misrepresent the actual state of their systems in order to hide negative events or to "doctor" reports which have been already produced. Existing security approaches which guarantee integrity of logs and related reports do not protect the system against these threats, if they are directly applied to a multi-layered corporate structure. In this paper, we extend existing approaches by constructing a logging scheme which ensures that, at each level, logs are both correct and consistent.
Health Seeking Behaviour and Associated Factors among Pulmonary Tuberculosis Suspects in Lay Armachiho District, Northwest Ethiopia: A Community-Based Study

Studies in the northern part of Ethiopia showed high prevalence of undiagnosed cluster of tuberculosis cases within the community which demanded an investigation of the health care seeking behaviour of tuberculosis suspects. A community-based cross-sectional study was conducted in Lay Armachiho district, Northwest Ethiopia. Individuals who had cough for at least two weeks and aged greater than or equal to 15 years were included in the study. Data were collected by interview using pretested and structured questionnaire. Logistic regression was computed and adjusted odds ratio with 95% confidence interval was calculated. Out of the total population surveyed (29, 735), 663 (2.2%) individuals were found to be pulmonary tuberculosis suspects. Majority of the suspects reported that they had visited a modern health care facility. Those aged 15 to 34 and aged 35–54 had secondary educational level and above; those who were civil servants, those who were farmers, those who had previous history of tuberculosis treatment, and those who perceived that they were sick were more likely to visit a modern health care facility. The proportion of respondents who had taken traditional measures was found to be higher than some other districts. Improving the socioeconomic status of the community is recommended.
Decreased regional homogeneity in schizophrenia: a resting state functional magnetic resonance imaging study

We used a newly reported regional homogeneity approach to measure the temporal homogeneity of blood oxygen level-dependent signal for exploring the brain activity of schizophrenia in a resting state. The results showed decreased regional homogeneity in schizophrenia, which distributed over the bilateral frontal, temporal, occipital, cerebellar posterior, right parietal and left limbic lobes, similar to the findings reported in previous resting state functional studies. The brain regions that showed decreased regional homogeneity are believed to be involved in the psychopathology and pathophysiology of schizophrenia. Our results indicate that abnormal brain activity of schizophrenia may exist in a resting state and the regional homogeneity may be potentially helpful in understanding the resting state of schizophrenia.
3D Object recognition using a voting algorithm in a real-world environment

This paper presents a novel 3D object recognition method. The proposed objectives are to overcome shortcoming of the appearance-based method, which lacks a spatial relationship between the parts of an object, and those of other 3D model methods, which require complicated computation. The proposed method is based on a voting process. Appearance estimation is introduced in this work in order to deal with the faulty detection problem. We tested our method for object detection and pose estimation, and the results showed that our method improved the average precision and detection time compared to other methods.
The Role of Neutral Sphingolipids in the Pathogenesis of Parkinson Disease and Dementia with Lewy Bodies

The molecular mechanisms underlying the association between mutations in GBA1 and risk of developing the ‘synucleinopathy’ disorders Parkinson’s disease (PD) and dementia with Lewy bodies (DLB) remain elusive. To better understand the precise molecular cascade that connects GBA1 mutations with α-synuclein dysregulation, a modified lipid extraction and HPTLC protocol was optimized to detect changes in levels of neutral sphingolipids (SLs) from neural cells and tissue expressing wild-type (WT) GBA1, mutant GBA1, or both. We demonstrate that mutant GBA1 does not confer a dominant-negative effect on WT GBA1-mediated activity; however, bona fide loss-of-enzymatic function mutation events led to the accumulation of lipid substrates in neural cells and tissue, and enhance α- synuclein/ubiquitin reactivity in brain tissue of mutant gba1 mice. Our HPLC-MS/MS data are consistent with other studies demonstrating that heterozygous GBA1 mutations do not lead to lipid accumulation, but may alter α-synuclein degradation through a yet-to-be defined novel gain-of-toxic function event.
Chi**2 analysis of the minimal supergravity model including WMAP, g(mu)-2 and b -> s gamma constraints

Recent results from the WMAP measurements of the cosmic background radiation yield very tight constraints on the relic density of supersymmetric cold dark matter. We combine the WMAP constraint with those from the anomalous magnetic moment of the muon and the b -> s gamma branching fraction in a chi^2 determination over the minimal supergravity model (mSUGRA) parameter space. The most favored region of mSUGRA parameter space for almost all tan(beta) values is the hyperbolic branch/focus point (HB/FP) region, with moderate to small values of superpotential Higgs mass |mu| and large GUT scale scalar mass m_0. These favored regions of mSUGRA parameter space can be probed by direct search experiments for supersymmetric dark matter. An exception to the HB/FP region can occur at very large tan(beta) with positive mu values, where wide regions allow resonance annihilation of neutralinos in the early universe.
Quiescent X-ray variability from the neutron star transient Aql X-1

A number of studies have revealed variability from neutron star low-mass X-ray binaries during quiescence. Such variability is not well characterized, or understood, but may be a common property that has been missed due to lack of multiple observations. One such source where variability has been observed is Aql X-1. Here, we analyse 14 Chandra and XMM–Newton observations of Aql X-1 in quiescence, covering a period of approximately 2 yr. There is clear variability between the epochs, with the most striking feature being a flare-like increase in the flux by a factor of 5. Spectral fitting is inconclusive as to whether the power-law and/or thermal component is variable. We suggest that the variability and flare-like behaviour during quiescence is due to accretion at low rates which might reach the neutron star surface.
Automated White Matter Total Lesion Volume Segmentation in Diabetes

BACKGROUND AND PURPOSE: WM lesion segmentation is often performed with the use of subjective rating scales because manual methods are laborious and tedious; however, automated methods are now available. We compared the performance of total lesion volume grading computed by use of an automated WM lesion segmentation algorithm with that of subjective rating scales and expert manual segmentation in a cohort of subjects with type 2 diabetes. MATERIALS AND METHODS: Structural T1 and FLAIR MR imaging data from 50 subjects with diabetes (age, 67.7 ± 7.2 years) and 50 nondiabetic sibling pairs (age, 67.5 ± 9.4 years) were evaluated in an institutional review board–approved study. WM lesion segmentation maps and total lesion volume were generated for each subject by means of the Statistical Parametric Mapping (SPM8) Lesion Segmentation Toolbox. Subjective WM lesion grade was determined by means of a 0–9 rating scale by 2 readers. Ground-truth total lesion volume was determined by means of manual segmentation by experienced readers. Correlation analyses compared manual segmentation total lesion volume with automated and subjective evaluation methods. RESULTS: Correlation between average lesion segmentation and ground-truth total lesion volume was 0.84. Maximum correlation between the Lesion Segmentation Toolbox and ground-truth total lesion volume (ρ = 0.87) occurred at the segmentation threshold of k = 0.25, whereas maximum correlation between subjective lesion segmentation and the Lesion Segmentation Toolbox (ρ = 0.73) occurred at k = 0.15. The difference between the 2 correlation estimates with ground-truth was not statistically significant. The lower segmentation threshold (0.15 versus 0.25) suggests that subjective raters overestimate WM lesion burden. CONCLUSIONS: We validate the Lesion Segmentation Toolbox for determining total lesion volume in diabetes-enriched populations and compare it with a common subjective WM lesion rating scale. The Lesion Segmentation Toolbox is a readily available substitute for subjective WM lesion scoring in studies of diabetes and other populations with changes of leukoaraiosis.
Iterative LBG clustering for SIMO channel identification

This paper deals with the problem of channel identification for Single Input Multiple Output (SIMO) slow fading channels using clustering algorithms. Due to the intrinsic memory of the discrete-time model of the channel, over short observation periods, the received data vectors of the SIMO model are spread in clusters because of the AWGN noise. Each cluster is practically centered around the ideal channel output labels without noise and the noisy received vectors are distributed according to a multivariate Gaussian distribution. Starting from the Markov SIMO channel model, simultaneous maximum-likelihood estimation of the input vector and the channel coefficients reduce to one of obtaining the values of this pair that minimizes the sum of the Euclidean norms between the received and the estimated output vectors. Viterbi algorithm can be used for this purpose provided the trellis diagram of the Markov model can be labeled with the noiseless channel outputs. The problem of identification of the ideal channel outputs, which is the focus of this paper, is then equivalent to designing a Vector Quantizer (VQ) from a training set corresponding to the observed noisy channel outputs. The Linde-Buzo-Gray (LBG)-type clustering algorithms [1] could be used to obtain the noiseless channel output labels from the noisy received vectors. One problem with the use of such algorithms for blind time-varying channel identification is the codebook initialization. This paper looks at two critical issues with regards to the use of VQ for channel identification. The first has to deal with the applicability of this technique in general; we present theoretical results for the conditions under which the technique may be applicable. The second aims at overcoming the codebook initialization problem by proposing a novel approach which attempts to make the first phase of the channel estimation faster than the classical codebook initialization methods. Sample simulation results are provided confirming the effectiveness of the proposed initialization technique.