Miracle-dz/UniFAR-FTUs huggingface dataset:
Tracing the Emergence of Gendered Language in Childhood

Are gender associations in general language reﬂected in the words spoken to and by children? Previous work has suggested that language reveals gender differences in discourse, speech style, language use and acquisition. Work in artiﬁcial intelligence has shown that word embeddings trained on large corpora reﬂect human gender associations. We connect this work to developmental psychology by exploring whether gender associations in word embeddings are present in the linguistic input and output of children, and if so, how early gendered language emerges. We present a computational method that quantiﬁes the gender associations of words and use a corpus of child-caretaker speech to show that these gender associations correlate signiﬁcantly with those in word embeddings. We discover that gendered word use emerges in English-speaking children around age 2, and the gender associations cannot be explained solely by variables including word length, frequency, concreteness, and valence.
Improving Recommendation Diversity based on Latent Factor Model

data using Non-negative matrix factorization algorithm to regroup users in clusters. Using these clusters, we form the neighborhood set based on the level of diversity of each user to make it as input for the User-based Collaborative filtering algorithm. Additionally, we suggest an integration of a re-ranking algorithm on the recommended list. For the evaluation part, we apply the 5-fold cross validation technique to real datasets. Accordingly, the experimental results have proved the performance and robustness of the new approach on balancing accuracy and diversity in comparison with the benchmark algorithms.
An Improved Matrix Completion Algorithm For Categorical Variables: Application to Active Learning of Drug Responses

High throughput screening is extensively used to discover potential drugs in the early drug development process. However, screening is typically used to ﬁnd compounds that have a desired eﬀect but not to identify potential undesirable side eﬀects because of the large size of the search space. Active machine learning has been proposed as a solution to this problem. In this article, we describe an improved imputation method for modeling the eﬀects of many compounds on many targets using latent correlations between compounds and conditions. Using this to drive active learning in well-characterized settings resulted in a reduction of almost 40% in the number of experiments needed to reach a perfect predictive accuracy compared to random selection of experiments. The results were a signiﬁcant improvement over previous reports and the new algorithm represents the current state-of-the-art for this problem.
Early Fraud Detection with Augmented Graph Learning

Having an effective fraud detection system can help social media to identify suspicious behaviors or accounts. Early detection is crucial to minimize losses if the fraud is ongoing. Existing detection methods perform effectively when good amounts of observed behavior data are available (which sometimes has been too late); however, at an early stage when the observations are limited, the performance would not be satisfactory. In this work, we propose Alfrad, a novel self-training framework that uses behavior data augmentation for early fraud detection. It has a Seq2Seq-based behavior predictor that predicts (i) whether a user will adopt a new item or an item that has been historically adopted and (ii) which item will be adopted. Alfrad utilizes the prediction results of fraud detection methods to make better prediction of future behavior and uses the augmented graph to help fraud detection methods to achieve higher performance while not requiring any additional data. It explores the mutually beneficial relationship between fraud detection and behavior prediction. Experiments show that Alfrad improves the performance of different kinds of fraud detection methods. With Alfrad augmented methods, the performance of fraud detection at an earlier stage is comparable with and/or better than non-augmented methods on a greater amount of observed data.
ANTI BACTERIAL EFFECT OF ZnO-Au NANOCOMPOSITES

The synthesis of ZnO-Au nanocomposites prepared by dissolving 1:1 concentration of Zinc Nitrate and Chloroauric acid in the presence of Sodium Hydroxide. The formation of ZnO-Au nanocomposities can be observed by a change in color from a colorless solution to yellow ish white precipitate. Characterization studies of this stable ZnO-Au nano composities were carried out. AFM, UV absorption, SEM and XRD characterizati on of the synthesized nanocomposites showed an even distribution of gold nanoparticles. The ZnO-Au nanocomposite can be effectively used for controlli ng antimicrobial activity in human physiological systems.
Osteopathy and patients who have experienced sexual violence : management, treatment and self-care

III Acknowledgements . IV Chapter 1: Introduction . 1 The Current Climate . 2 Research Objective . 3 Thesis Structure . 3 Chapter 2: Literature Review . 5 The Search Process . 5 Sexual Violence: Terminology and Definitions . 6 The Parameters of Sexual Violence . 7 The Personal and Social Costs of Sexual Violence . 8 Disclosure of Sexual Violence . 14 Recovery from Sexual Violence. 18 Primary Healthcare, Manual Therapy and the Management of Patients Who have Experienced Sexual Violence . 20 Professional Resilience . 26 Summary . 28 Chapter 3: Research Design . 30 Methodology . 30 Methods . 35 Chapter 4: The Patient and the Experience of Sexual Violence . 43 The Illness Experience . 43 The Mind-Body Connection . 46 Clinical Relevance . 49 Chapter 5: The Role of Osteopathy in Recovery from Sexual Violence . 52 Scope of Practice. 52 The Therapeutic Response . 58 Power in the Therapeutic Relationship . 66 Chapter 6: Professional Resilience in Relation to Sexual Violence . 71
TSAR : A System for Defending Hate Speech Detection Models Against Adversaries

5 I.Introduction 8 II.Related Work 10 III. Literature Survey 12 CURRENT METHODS AND FEATURES 12 Methods 12 Definition 13 Features 13 TF-IDF 14 Bag of Words 14 N-grams 15 GloVe or Word Embeddings 15 Semantic Features 16 IV. Problem Statement Error! Bookmark not defined. V. Proposed Solution 21 A. Models and Datasets 21 B. Proposed Defenses 23 C. Pre-processing Defenses 23 D. Training Defenses 25 VI. Performance and Results 26 A. Typos 27 B. Whitespace Removal 28 C. Benign Word Insertion 30 D. Character Boundary Appending 32 E. Combined attacks 34 Classification of Evasion Schemes 35 VII. Conclusion and Future Work 37
Bounds for Binary Linear Locally Repairable Codes via a Sphere-Packing Approach

For locally repairable codes (LRCs), Cadambe and Mazumdar derived the first field-dependent parameter bound, known as the C-M bound. However, the C-M bound depends on an undetermined parameter <inline-formula> <tex-math notation="LaTeX">$ {k}^{( {q})}_{{\textbf {opt}}}( {n}, {d})$ </tex-math></inline-formula>. In this paper, a sphere-packing approach is developed for upper bounding the parameter <inline-formula> <tex-math notation="LaTeX">$ {k}$ </tex-math></inline-formula> for <inline-formula> <tex-math notation="LaTeX">$[ {n}, {k}, {d}]$ </tex-math></inline-formula> linear LRCs with locality <inline-formula> <tex-math notation="LaTeX">$ {r}$ </tex-math></inline-formula>. When restricted to the binary field, three upper bounds (i.e., <monospace>Bound A</monospace>, <monospace>Bound B</monospace>, and <monospace>Bound C</monospace>) are derived in an explicit form. More specifically, <monospace>Bound A</monospace> holds under the hypothesis that the local repair groups are disjoint and of equal size. Comparing with previous bounds obtained under the same hypothesis, <monospace>Bound A</monospace> either covers them as special cases or has an advantage due to its explicit form. Then, the hypothesis is removed in <monospace>Bound B</monospace> and <monospace>Bound C</monospace>. As the price for explicit form, <monospace>Bound B</monospace> specially holds for <inline-formula> <tex-math notation="LaTeX">$ {d}\geq \text {5}$ </tex-math></inline-formula> and <monospace>Bound C</monospace> for <inline-formula> <tex-math notation="LaTeX">$ {r}=\textbf {2}$ </tex-math></inline-formula>. Through specific comparisons, we show that <monospace>Bound B</monospace> and <monospace>Bound C</monospace> both tend to outperform the C-M bound, as <inline-formula> <tex-math notation="LaTeX">$ {n}$ </tex-math></inline-formula> goes large. Moreover, a family of binary linear LRCs with <inline-formula> <tex-math notation="LaTeX">$ {d}\geq \textbf {6}$ </tex-math></inline-formula> attaining <monospace>Bound B</monospace> are constructed and later extended to a wider range of parameters by a shortening technique. Lastly, most of the bounds and constructions are extended to <inline-formula> <tex-math notation="LaTeX">$ {q}$ </tex-math></inline-formula>-ary LRCs.
Simulation of Voltage Regulation in Distributed Networks with High penetration using Battery Energy Storage Systems

Background: The voltage rise issue in low voltage (LV) distribution networks with high entrance of photovoltaic (PV) assets is one of the most important situations in the advancement of these renewable assets. In this paper, BES frameworks are utilized to explain the voltage fall during the peak PV age just as the voltage drop while meeting the peak load. Method adopted: In this paper, a control method of procedure is suggested for BESs employed in rooftop PV systems to moderate the voltage rise/drop issues in the LV distribution networks with high entrance of PV sources. A planned control methodology is presented in this paper to direct the charge/release of BESs utilizing a mix of the nearby hang based control strategy and an appropriated control conspire which guarantees the voltages of feeder stay inside allowed limits. Results: This paper shows the methodology which has been approved by a LV radial distribution feeder under various working conditions in MATLAB/Simulink. The test results validate that the control plot keeps the voltage in the system inside as far as possible during everyday activities is concerned. Conclusion: In this paper, yet another voltage guideline methodology in the low voltage (LV) distribution networks with high PV penetration has been simulated in MATLAB environment. This technique having a tendency to voltage rise/drop issues utilizing the distributed battery energy stocking (BES) systems. In like mode, a designed control conspire has been created to handle the system voltage and effectively use the capacity range of BESs during every day actions. Key Word: Battery energy Stocking (BES); Distribution networks; Low Voltage(LV); Voltage drop. -------------------------------------------------------------------------------------------------------------------------------------Date of Submission: 14-07-2020 Date of Acceptance: 29-07-2020 -------------------------------------------------------------------------------------------------------------------------------------
The Comparative Analysis of AC-Flux and DC-Flux Resolvers

Resolver, as an electromagnetic sensor, is widely used in many industrial applications. It can detect the position of the rotary part of the electric machines precisely. In commercial resolvers, the excitation winding is connected to the high frequency (HF) AC source. The amplitude-modulated voltages induced in the signal windings need to be demodulated in order to calculate the envelope of the output signals and accordingly detect the position. On the other hand, in PM-resolver, signal windings replaced by Hall-effect sensors to measure the DC magnetic flux which is produced by permanent magnets. In this study, the performance of both AC and DC flux resolvers is investigated under different circumstances. All the simulations are done by the time-stepping finite element method (TSFEM).
Limiting behavior of randomly weighted averages of symmetric heavy-tailed random variables

ABSTRACT In this paper we consider a sequence of independent continuous symmetric random variables X1, X2, …, with heavy-tailed distributions. Then we focus on limiting behavior of randomly weighted averages Sn = R(n)1X1 + ⋅⋅⋅ + R(n)nXn, where the random weights R(n)1, …, Rn(n) which are independent of X1, X2, …, Xn, are the cuts of (0, 1) by the n − 1 order statistics from a uniform distribution. Indeed we prove that cnSn converges in distribution to a symmetric α-stable random variable with cn = n1 − 1/α/Γ1/α(α + 1).
Learning Better Representations for Neural Information Retrieval with Graph Information

Neural ranking models have recently gained much attention in Information Retrieval community and obtain good ranking performance. However, most of these retrieval models focus on capturing the textual matching signals between query and document but do not consider user behavior information that may be helpful for the retrieval task. Specifically, users' click and query reformulation behavior can be represented by a click-through bipartite graph and a session-flow graph, respectively. Such graph representations contain rich user behavior information and may help us better understand users' search intent beyond the textual information. In this study, we aim to incorporate this rich information encoded in these two graphs into existing neural ranking models. We present two graph-based neural ranking models (\emphEmbRanker and AggRanker ) to enrich learned text representations with graph information that captures rich users' interaction behavior information. Experimental results on a large-scale publicly available benchmark dataset show that the two models outperform most existing neural ranking models that only consider textual information, which illustrates the effectiveness of integrating graph information with textual information. Further analyses show how graph information complements text matching signals and examine whether these two models can be adopted in practical applications.
Student-Athletes at an Historically Black University (HBU): Examining the Relationship Between Student-Engagement on Campus and Career Situation Awareness

The purpose of this exploratory study was to examine the relationship between student-athletes’ engagement experiences on campus and their career situation awareness at a historically Black university (HBU) with NCAA Division I affiliation in the Southeastern United States. Data was obtained from a sample (n = 118) of female (n = 45) and male (n = 73) student-athletes using measures from the revised versions of the Student-Athlete Experiences Inventory (SAEI) and the Student-Athlete Career Situation Inventory (SACSI). One-way ANOVA, Pearson product-moment correlation tests, and t-tests were employed to analyze gender and race effects. Following data analysis, three key findings were identified. First, HBCUs are likely to provide socially enriching environments for minority student-athletes of both genders that promote career confidence, particularly for Black female student-athletes. Second, in an HBCU context, White student-athletes may not be as academically involved in university life when compared to their minority counterparts. Third, the use of the library for academic purposes and engagement in socially enriching experiences may have diminishing effects on female student-athletes’ sport identities. Implications and future research recommendations are discussed. To better validate and improve the generalizability, future research should conduct similar studies that employ data from multiple HBCUs.
A Comprehensive Study on implementation of Low Noise Amplifier

A RF receiver design requires a Low noise amplifier that provides sensitivity to the system. The paper gives vast idea on designing low noise amplifier using different techniques. Low noise amplifier is the primary part of the receiver section of the system. The LNA provides an amplification of the collected weak signal to achieve minimum noise contribution. Applying CMOS technology in designing a low noise amplifier is the most preferred topics in the field of research as it is advantageous over low power, low cost and higher integration. Keywords--LNA, CMOS technology, RF receiver, Noise Figure (NF), ULV, ULP, ULW.
Effects of 4-month basketball training on speed, agility and jumping in youth basketball players

The aim of this study is to investigate the effect of 4-month basketball training on speed, agility and jump in youth male basketball players. A total of 14 male basketball players from the youth category participated in the study voluntarily. Before the research, parents' consent documents were obtained from the parents of the players. The study included players who continued basketball training for 4 months. Subjects performed basketball training 3 days a week (90 min every day). 20 m sprint, Illinois agility test, vertical and horizontal jump tests were applied in the research. Pre-, mid-, and post-test designs are used in measurements (First test, 2. month and 4. month), and they were carried out in three different test periods. One-way repeated measures analysis of variance was used to determine differences between measurements. The Holm-Sidak test was used to determine the differences between the groups (p < 0.05). There was a significant difference between the measurements in the body height, body weights and horizontal jump of the subjects. In addition, an improvement in vertical jump, 20 m speed and agility performances were observed at the end of the 4th month. It was found that 4-month basketball training caused a significant increase in physical and motoric features seen in youth male basketball players. It is thought that the significant increase in speed, agility and vertical jump performance will occur after longer training sessions. It should also be remembered that growing up can affect the positive increase in performance.
Using a Telepresence Robot in an Educational Contex

— This paper deals with the use of telepresence robots in an educational context. To this day, these uses are often related to the problematic of "homebound students" 1 . The emphatic context associated with these students masks the pedagogical difﬁculties encountered by telepresence learners. In this article, we ﬁrst detail the use of the robot by homebound students, highlighting motivational factors. Then we focus on persistence using the robot, once this emphatic context declines. Finally, we describe our attempts to reduce transactional distance by adding connected learning environments.
Multiscale analysis of active state failure behind a retaining wall

Discrete element method (DEM) simulates the interaction of particulate material by tracking the displacement and calculation of force for individual grains. Current study, initially simulates the active state failure behind a retaining wall for a cohesionless backfill. The considered particles are differentiated by shape parameter; both spherical and non-spherical particles are included. Additionally, a physical lab-scale model retaining wall that can reproduce active state failure is utilized in this study. Tests are performed on a uniformly graded local sand (Akpinar sand). The model has transparent wall which will allow the observation of the deformation during the test. Eventually, failure surface evolution from DEM simulations is compared qualitatively to those of experimental observations. Obtained results suggest that it is crucial to incorporate non-spherical particles for DEM simulations to enable realistic representation of a granular backfill. RÉSUMÉ: La méthode des éléments discrets (DEM) simule l’interaction des particules en suivant le déplacement et le calcul de la force pour chaque grain. L’étude actuelle simule d’abord la défaillance de l’état actif derrière un mur de soutènement pour un remblai sans cohésion. Les particules considérées sont différenciées par le paramètre de forme; les particules sphériques et non sphériques sont incluses. De plus, un modèle de mur de soutènement physique à l'échelle du laboratoire capable de reproduire une défaillance d'état actif est utilisé dans cette étude. Les tests sont effectués sur un sable local uniformément classé (sable Akpinar). Le modèle a une paroi transparente qui permettra d’observer la déformation au cours de l’essai. Finalement, l'évolution de la surface de défaillance à partir des simulations DEM est comparée qualitativement à celle d'observations expérimentales. Les résultats obtenus suggèrent qu’il est crucial d’incorporer des particules non sphériques dans les simulations DEM afin de permettre une représentation réaliste d’un remblai granulaire.
Efficacy of coblation assisted surgery in obstructive sleep apnea with obstruction at the retropalatal level

BACKGROUND AND OBJECTIVE: Obstructive sleep apnea syndrome is an emerging disorder in India which has contributed to the increased prevalence of various non-communicable diseases. There are many surgical procedures described in the management of OSAS of which Uvulopalatopharyngoplasty is the most commonly performed. The primary objective was to study the efficacy of coblation assisted UPPP in patients with isolated retropalatal obstruction. The effects on Polysomnography indices were also studied. STUDY DESIGN: Prospective study - Before – After analysis. METHODS: Patients diagnosed with moderate and severe obstructive sleep apnea by Polysomnography underwent Drug induced sleep endoscopy and sleep MRI to locate the level of obstruction. Only those with isolated retropalatal obstruction were selected. 25 patients underwent Uvulopalatopharyngoplasty and Polysomnography was repeated after 1 month. The parameters analysed were the Apnea Hypopnea Index, Arousal Index, Oxygen desaturation index and awakenings index. Results were also analyse using Friedman’s staging system. RESULTS: Considering a 50 % reduction in AHI as surgical success, the efficacy of UPPP was 68% in this study. Statistically significant differences in AHI, arousal index, oxygen desaturation index and Awakenings Index were obtained in both successful and unsuccessful groups of patients. CONCLUSIONS: Uvulopalatopharyngoplasty remains a valuable treatment option in OSA. The use of DISE and sleep MRI allows the selection of patients with isolated retropalatal obstruction who are most likely to benefit from UPPP.
Morphological and Molecular Identification of Hard Ticks (Acari: Ixodida) Infesting Herds of Cattle in Zaria, Northwestern Nige

Ticks are important vector arthropods of human and animal pathogens. Information on tick vectors as well as their distribution in Zaria and environs is very scanty. The study was aimed at identifying the various tick species infesting cattle in Zaria using a molecular technique. Ticks were collected from two hundred cattle (n=200) of which 193 (96.5%) were tick infested. The individual ticks were washed, crushed and incubated at 56°C overnight. The extracted DNA of each sample was extracted and amplified targeting the 16S rRNA portion. Ampl icons were sequenced using a capillary sequencer (ABI PRISMR 3130x1 Genetic Analyzer, Applied Biosystems). All sequences were subjected to a Basic Local Alignment Search Tool (BLAST) to determine their identities and assess their homologues and similarities to those in the Gen Bank.