Miracle-dz/UniFAR-FTUs huggingface dataset:
A Mixed-Methods Approach to Understanding the Impact of a First-Year Peer Mentor Program.

This study is a mixed-methods research project designed to measure the effectiveness of a peer mentor program in meeting institutional goals such as increased academic performance and retention. The results suggest that peers are useful in helping students manage the demands of the first year by normalizing the experience and linking the students to campus supports. The results also demonstrate a relationship between first-year students who interact with a peer mentor and increased academic performance; however, the link to retention is not as clear. More research, over a longer time frame, is needed to understand the factors that affect retention. The intention of this research is to contribute to the growing body of literature that helps practitioners champion retention initiatives that respond to the holistic needs of first-year students. Peer programs are initiated fora variety of reasons, including fostering success among first-year students, connecting students to a major, helping athletes balance the demands of a high-performance sport with the rigors of academia, and bringing together like-minded students for social causes. Whatever the reason, peer mentor programs seek to have more advanced students engage, teach, recruit, and retain first-year students. While postsecondary environments engage peers as mentors with a general understanding that this is a good way to assist students, there is little evidence to suggest an impact on institutional goals (Budge, 2006; Crisp & Cruz, 2009; Gershenfeld, 2014). This project was designed to investigate the effect of a peer mentor program on institutional goals, such as improved academic performance and lower attrition rates between first and second year, and is an important piece of research linking student affairs activity with critical institutional priorities.
Unstructured Mesh Motion Using Sliding Cells and Mapping Domains

This paper addresses the problem of generating unstructured meshes with fixed connectivity for large rigid body motion. The proposed approach consists in generating a mesh in computational space for a generic configuration of the moving body. The management of body and mesh motion is then carried out in computational space using a sliding mesh paradigm. Afterwards, the mesh in physical space is obtained through the Winslow equation to map the computational mesh to the physical space. Two new discritization techniques are implemented, validated and compared for performing the Winslow operator on unstructured grids. The first approach used a 9-point Cartesian stencil inside each patch of the computational mesh and discritizes the mapping operators on that using conventional finite difference schemes. The second approach used finite volume discritization technique by linearizing the system of mapping equations. This methodology is applied to complex geometric configurations representative of engineering applications.
Unsupervised segmentation for automatic detection of brain tumors in MRI

In this paper, we present a new automatic segmentation method for magnetic resonance images. The aim of this segmentation is to divide the brain into homogeneous regions and to detect the presence of tumors. Our method is divided into two parts. First, we make a pre-segmentation to extract the brain from the head. Then, a second segmentation is done inside the brain. Several techniques are combined like anisotropic filtering or stochastic model-based segmentation during the two processes. The paper describes the main features of the method, and gives some segmentation results.
Semantic Categorization of Web Services

Web services are new solution for dynamic business interactions over the Internet. Describing Web service with semantics provides the ability for automatic Web service discovery, invocation, composition and interoperation, and Web service execution monitoring. A critical step in the process of reusing existing Web services is the automatic discovery of potentially relevant components which can be achieved if some semantic description is provided in description of Web service. Approach proposed in this paper is to provide semantic annotation of Web service's functionality in WSDL's documentation tag which will be extracted and used for categorization of a Web service into one of the pre defined categories by calculating the Normalized Similarity Score (NSS), a Measure of Semantic Relatedness (MSR) of each word with every pre-defined category. Sum of NSS of all the terms in a particular Web service is calculated with all the categories and Web service is assigned a category with highest value. In contrast with previous approaches, this mechanism provides an efficient method for semantic indexing and approximate retrieval of services, leading to automatic semantic categorization of Web Services. Empirical evaluation of the work performed on a small test set is presented.
Calibrating Multimodel Forecast Ensembles with Exchangeable and Missing Members Using Bayesian Model Averaging

Bayesian model averaging (BMA) is a statistical postprocessing technique that generates calibrated and sharp predictive probability density functions (PDFs) from forecast ensembles. It represents the predictive PDF as a weighted average of PDFs centered on the bias-corrected ensemble members, where the weights reflect the relative skill of the individual members over a training period. This work adapts the BMA approach to situations that arise frequently in practice; namely, when one or more of the member forecasts are exchangeable, and when there are missing ensemble members. Exchangeable members differ in random perturbations only, such as the members of bred ensembles, singular vector ensembles, or ensemble Kalman filter systems. Accounting for exchangeability simplifies the BMA approach, in that the BMA weights and the parameters of the component PDFs can be assumed to be equal within each exchangeable group. With these adaptations, BMA can be applied to postprocess multimodel ensembles of any composition. In experiments with surface temperature and quantitative precipitation forecasts from the University of Washington mesoscale ensemble and ensemble Kalman filter systems over the Pacific Northwest, the proposed extensions yield good results. The BMA method is robust to exchangeability assumptions, and the BMA postprocessed combined ensemble shows better verification results than any of the individual, raw, or BMA postprocessed ensemble systems. These results suggest that statistically postprocessed multimodel ensembles can outperform individual ensemble systems, even in cases in which one of the constituent systems is superior to the others.
Biochemical validation of a self-administered semi-quantitative food-frequency questionnaire

The present study is a biochemical validation of a food-frequency questionnaire (FFQ) with optical reading, i.e. containing food portion photographs to help to assess quantities. Forty-four healthy subjects, non-smokers and not taking vitamin supplements, were recruited for the study. After completion of the questionnaire, subjects were asked to keep a 7 d weighed dietary record (7DR). Three 24 h urine samples were collected on 3 different days over the week of food recording for the analysis of urea-N, P and K. On the 4th day of food recording, blood was collected for determination of u-tocopherol, &carotene and ascorbic acid. N, P and K determined in wines and from 7DR were significantly correlated (Spearman rank correlation test), r values being 0.77,0*57 and 0-42 respectively. The correlations with the FFQ were significant only for N (rO45) and P (~0.39). Blood ascorbic acid and p-carotene concentrations correlated with dietary intake when determined from 7DR (both Y 0.44), but not when determined from FFQ. No correlation was found for &ocopherol. The data obtained seem to prove the validity of the FFQ in defining eating patterns in terms of some nutrients, but not vitamins, at least as far as nonsupplemented subjects are concerned. The way in which foods were grouped in the questionnaire could account for these results.
IIIT Hyderabad at CLEF 2007 - Adhoc Indian Language CLIR Task

This paper presents the experiments of Language Technologies Research Centre (LTRC) 1 as part of their participation in CLEF 2 2007 Indian language to English ad-hoc cross language document retrieval task. In this paper we discuss our Hindi and Telugu to English CLIR system and the experiments using CLEF 2007 dataset. We used a variant of TFIDF algorithm in combination with a bilingual lexicon for query translation. We also explored the role of a document summary in fielded queries and two dierent boolean formulations of query translations. We find that a hybrid boolean formulation using a combination of boolean AND and boolean OR operators improves ranking of documents. We also find that simple disjunctive combination of translated query
I/O-complexity of graph algorithms

We show lower bounds of Q( $ Sort(V)) for the I/Ocomplexity of graph theoretic problems like connected components, biconnected components, and minimum spanning trees, where E and V are the number of edges and vertices in the input graph, respectively. We also present a deterministic O($ Sort(V) ’ max(l,loglog 9)) algorithm for the problem of graph connectivity, where B and D denote respectively the block size and number of disks. Our algorithm includes a breadth first search; this maybe of independent
Coulomb distortion in the inelastic regime

The Coulomb distortion effects have been for a long time neglected in deep inelastic scattering for the good reason that the incident energies were very high. But for energies in the range of earlier data from SLAC or at JLab, the Coulomb distortion could have the potential consequence of affecting the A-dependence of the EMC effect and of the longitudinal to transverse virtual photon absorption cross section ratio R(x,Q2).
The stimulatory effect of LXRα is blocked by SHP despite the presence of a LXRα binding site in the rabbit CYP7A1 promoter Published, JLR Papers in Press, February 17, 2006.

The transcription of the cholesterol 7α-hydroxylase gene (CYP7A1) is greatly decreased in cholesterol-fed rabbits. To determine whether the molecular structure of the promoter is responsible for this downregulation, we cloned the rabbit CYP7A1 promoter, identified the binding sites for α-fetoprotein transcription factor (FTF) and liver X receptor (LXRα), and studied the effects of FTF, LXRα, and SHP on its transcription. Adding LXRα/retinoid X receptor together with their ligands (L/R) to the promoter/reporter construct transfected into HepG2 cells greatly increased its activity. FTF did not increase promoter activity, nor did it enhance the stimulatory effect of L/R. Mutating the FTF binding site abolished the promoter baseline activity. Increasing amounts of SHP abolished the effect of L/R, and FTF enhanced the ability of SHP to decrease promoter activity below baseline levels. Thus, downregulation of CYP7A1 in cholesterol-fed rabbits is attributable secondarily to the activation of farnesoid X receptor, which increases SHP expression to override the positive effects of LXRα. Although FTF is a competent factor for maintaining baseline activity, it does not further enhance and may suppress CYP7A1 transcription.
Adaptive MMSE multiuser detection for MIMO OFDM over Turbo-Equalization for Single-Carrier Transmission wireless channel

This paper presents an adaptive multiuser receivers scheme for MIMO OFDM over Turbo-Equalization for Single-Carrier Transmission. It involves the joint adaptive minimum mean square error multiuser detection and decoding algorithm with prior information of the channel and interference cancelation in the spatial domain. A partially filtered gradient LMS (Adaptive) algorithm is also applied to improve the convergence speed and tracking ability of the adaptive detectors with slight increase in complexity. The proposed technique is analyzed in a slow and fast Rayleigh fading channels in MIMO OFDM systems. The adaptive multiuser detection for MIMO OFDM (AMUD MIMO OFDM) perform as well as the iterative equalization for single-carrier.
Evaluation of Lexical Acquisition Algorithms

Since there is a continuously growing amount of lexical acquisition algorithms for all kinds of lexical knowledge, be it morphologic, syntactic, semantic, domain specific or other information, it is necessary to be able to compare their quality. Furthermore at the same time it is necessary to provide an evaluation method that is easy to grasp and as uniform as possible so that it can be applied to all kinds of algorithms and provide comparable and most importantly reproducible results. We propose an extension of the gold standard evaluation method by generalizing most lexical knowledge to binary relations and then give an evaluation framework based on precision and recall. To show the effectiveness of this approach we compare the well-known mutual information measure with the dice coefficient. Information Maßes und des Dice Koeffizienten dar.
Adding paraphrases of the same quality to the C-STAR BTEC

We present a method to expand a linguistic resource with paraphrases, which combines two techniques whose drawbacks neutralise reciprocally. The first step over-generates sentences by using analogy, while the second step overeliminates erroneous sentences which do not meet a criterion on N -gram occurrences. In a practical experiment, we added 17,862 paraphrases to a linguistic resource of 97,769 English sentences. The new paraphrases are 99% correct English sentences (p-value = 2.22%), a quality approximately equal to that of the original linguistic resource (p-value = 1.92%).
Active stereo based compact mapping

In this paper we propose a method for extracting the planes from a 3D dense map. Three-dimensional data is acquired using active stereo in order to fill texture gaps which are typical in indoor environments. Then, a randomized SLAM algorithm recently proposed by the authors is applied to compute the 3D map by teleoperating a mobile robot. A 3D mesh generation algorithm specially designed to triangulate not solids but open objects, is the basis for computing the main planes in the map after clustering the normals of the vertices in the mesh. Finally, we present our experimental results in indoor environments.
Extracting timing and status descriptors for colonoscopy testing from electronic medical records

Colorectal cancer (CRC) screening rates are low despite confirmed benefits. The authors investigated the use of natural language processing (NLP) to identify previous colonoscopy screening in electronic records from a random sample of 200 patients at least 50 years old. The authors developed algorithms to recognize temporal expressions and 'status indicators', such as 'patient refused', or 'test scheduled'. The new methods were added to the existing KnowledgeMap concept identifier system, and the resulting system was used to parse electronic medical records (EMR) to detect completed colonoscopies. Using as the 'gold standard' expert physicians' manual review of EMR notes, the system identified timing references with a recall of 0.91 and precision of 0.95, colonoscopy status indicators with a recall of 0.82 and precision of 0.95, and references to actually completed colonoscopies with recall of 0.93 and precision of 0.95. The system was superior to using colonoscopy billing codes alone. Health services researchers and clinicians may find NLP a useful adjunct to traditional methods to detect CRC screening status. Further investigations must validate extension of NLP approaches for other types of CRC screening applications.
Global Price Updates Help

Periodic global updates of dual variables have been shown to yield a substantial speed advantage in implementations of push-relabel algorithms for the maximum flow and minimum cost flow problems. In this paper, we show that in the context of the bipartite matching and assignment problems, global updates yield a theoretical improvement as well. For bipartite matching, a push-relabel algorithm that uses global updates runs in $O\big(\sqrt n m\frac{\log(n^2/m)}{\log n}\big)$ time (matching the best bound known) and performs worse by a factor of $\sqrt n$ without the updates. A similar result holds for the assignment problem, for which an algorithm that assumes integer costs in the range $[\,-C,\ldots, C\,]$ and that runs in time $O(\sqrt n m\log(nC))$ (matching the best cost-scaling bound known) is presented.
Adaptive Profiling for Root-Cause Analysis of Performance Anomalies in Web-Based Applications

The most important factor in the assessment of the availability of a system is the mean-time to repair (MTTR). The lower the MTTR the higher the availability. A significant portion of the MTTR is spent in the detection and localization of the cause of the failure. One possible method that may provide good results in the root-cause analysis of application failures is run-time profiling. The major drawback of run-time profiling is the performance impact. In this paper we describe two algorithms for selective and adaptive profiling of web-based applications. The algorithms make use of a dynamic profiling interval and are mainly triggered when some of the transactions start presenting some symptoms of performance anomaly. The algorithms were tested under different types of degradation scenarios and compared to static sampling strategies. We observed through experimentation that the pinpoint of performance anomalies, supported by the data collected using the adaptive profiling algorithms, stills timely as with full-profiling while the response time overhead is reduced in almost 60%. When compared to a non-profiled version the response time overhead is less than 1.5%. These results show the viability of using run-time profiling to support quickly detection and pinpointing of performance anomalies and enable timely recovery.
Authors, Genre, and Linguistic Convention

Authorship, Language, and Individual Choice The basic premise underlying authorship attribution studies is that while the form of expression in language is in some respects strictly bound by linguistic rule systems and in others somewhat constrained by topic and genre, it is in some other respects freely available for configuration or preferential choice by author or speaker. This individual variation can be observed, detected, and predicted to some extent, using traditional stylostatistic measures. For instance, word length varies from author to author [Mendenhall, 1887, e.g.]; sentence length likewise; and some forms of lexical expression are characteristic of speakers, either on an individual level or on a community level [Book of Judges].
Touchless Fingerprint Biometrics: A Survey on 2D and 3D Technologies

Traditional fingerprint recognition systems require that the users touch a sensor to perform biometric acquisitions. In order to increase the usability, acceptability, and accuracy of fingerprint recognition technologies, touchless systems have recently been studied. With respect to touch-based biometric techniques, these systems present important differences in most of the steps of the recognition process.Studies in the literature can be classified into technologies based on two-dimensional and three-dimensional methods. These studies also present important differences in terms of accuracy and required level of user cooperation. This paper presents a brief survey on touchless recognition technologies, proposing a classification of two-dimensional and three-dimensional biometric recognition techniques.
An Ecological Model of Memory and Inferences

In this paper, we develop a memory model that predicts retrieval characteristics of real-world facts. First, we show how ACT-R’s memory model can be used to predict people’s knowledge about real-world objects. The model assumes the probability of retrieving a chunk of information about an object and the time to retrieve this information depend on the pattern of prior environmental exposure to the object. Second, we use frequencies of information appearing on the Internet as a proxy for what information people would encounter in their natural environment, outside the laboratory. In two Experiments, we use this model to account for subjects’ associative knowledge about real-world objects as well as the associated retrieval latencies. Third, in a computer simulation, we explore how such model predictions can be used to understand the workings and performance of decision strategies that operate on the contents of declarative memory.
Efectos de un entrenamiento pliométrico en extremidades superiores e inferiores en el rendimiento físico en jóvenes tenistas. [Effects of upper and lower body plyometric training on physical performance in young tennis players].

espanolEl objetivo del presente estudio fue evaluar el efecto de un entrenamiento pliometrico (ejercicios en extremidades superiores e inferiores) en acciones fisicas explosivas especificas en jovenes tenistas. Veintiun jovenes tenistas (11 chicos, 10 chicas; media de edad 14.33 ± 1.77 anos) participaron en el presente estudio y fueron divididos de forma no aleatoria en grupo control, el cual continuo con su entrenamiento habitual de preparacion fisica y en experimental, al que se le sustituyo su entrenamiento de preparacion fisica habitual por un programa de entrenamiento pliometrico dos veces por semana durante un periodo de 8 semanas. Las variables de rendimiento fueron analizadas a traves de diferentes valoraciones: un sprint de 20 metros (tiempos parciales 5m, 10m y 15m), un sprint de 5 + 5 metros con un cambio de direccion de 180o, un test de salto con contramovimiento bilateral (CMJ) y unilateral, un test de lanzamiento de balon medicinal a la maxima distancia (BM), un test de velocidad de servicio y un test de salto horizontal bilateral (SH) y unilateral (SHU). El efecto producido por el entrenamiento fue calculado en base al tamano del efecto. Todas las variables de rendimiento fueron mejoradas en ambos grupos en comparacion con los valores del pre-test. Ademas, el grupo experimental obtuvo mejoras sustanciales con respecto al grupo control en el SH, SHU, CMJ Y BM. Por lo tanto, el programa de entrenamiento pliometrico podria considerarse como un estimulo efectivo en la mejora de las acciones explosivas en jovenes tenistas. EnglishThe aim of the current study was to assess the effect of plyometric training (upper and lower body exercises) in explosive actions in young tennis players. Twenty-one young tennis players (11 males, 10 females, age 14.33 ± 1.77 years old) participated in the present study and were divided, in a non-randomized manner, into a control group which continued with a regular physical training and in a experimental group, which performed a biweekly plyometric training instead of the habitual fitness training during an 8-week period. Performance variables were assessed through several assessments; a 20-m sprint test (split 5m, 10m and 15m), a 5 + 5 m sprint with a 180o change of direction test, a bilateral (CMJ) and unilateral countermouvement jump test, a maximum distance medicine ball throw test (BM), a speed serve test and a bilateral (SH) and unilateral (SHU) standing broad jump test. Performance’s effect was calculated based on the effect size. All performance variables were improved in both group compared to the pre-test. Furthermore, substantial greater enhancements were obtained in SH, SHU, CMJ and BM in the experimental group in comparison to the control group. Therefore, the plyometric training program might be considered as an effective stimulus to improve explosive actions in young tennis players.