Miracle-dz/UniFAR-FTUs huggingface dataset:
Inculcating Learners’ Listening Motivation in English Language Teaching: A Case Study of British Education and Training System

Motivation plays a significant and crucial role in ELT and it boosts up the level of aplomb and interaction during learning English language. It creates sense of respect inside learners and makes them on the right direction. This research attempted to identify the impact of motivation on listening skills of students enrolled in English Language Course at British Education and Training System (BETS) Lahore, Pakistan during January to February, 2020. The learners for this class look forward to hone their speaking skills by listening as much as they can. The results show that there is a positive correlation between listening strategy instruction and motivation. Listening motivation was recorded utilizing the English Listening Comprehension Motivation Scale (ELCMS) and strategy use was tracked with the Metacognitive Awareness Listening Questionnaire (MALQ). Pre- and post-test scores of 36 participants (control group, n=20; experiment group, n=16) were analyzed using a mixed-effects regression and paired t-test to determine differences after a four-week treatment period. The results revealed that the participants’ motivation level in both groups decreased over the treatment period, with the experiment group seeing a smaller decrease than the control group.
Impact of the photosensitizers copper and magnesium chlorophyllin on biological and biochemical parameters of Bulinus truncatus snail

Schistosomiasis is one of the major communicable diseases with socioecomomic and health importance in the developing world (Steinmanr et al, 2006). There are multiple parameters affecting schistosomiasis transmission, among which is the snail intermediate host (Abdel-Hamid and Meckawey, 2014). Snails control by molluscicides could be one of the methods of choice for schistosomiasis control (Rizk et al, 2012). Molluscicides of natural origin have several advantages over the synthetic compounds (Perrett and Whitfield, 1996). In 2004, Ibrahim et al demonstrated a great histological damage in the ovotestis of Biomphalaria alexandrina snails post exposure to the plants Panicum repens and Solanum nigrum ARTICLE INFO ABSTRACT Article History: Received: Dec. 30, 2020 Accepted: Jan.27, 2021 Online: Feb. 5, 2021 _______________
The Impact of Anxiety, Psychosomatic Disorders, Stress Trauma, and Socio-economic Family Status on the Mental Health of Indonesian Communities during COVID-19

Objectives: The purpose of this study is to analyze the impact of anxiety, psychosomatic disorders, trauma stress, and socio-economic family status on the mental health of the Indonesian communities during COVID-19. Methods: This study used analytic research with a cross-sectional approach. The research was conducted on Indonesian society due to the covid-19 pandemic. The sample in this study was 1,090 respondents taken based on purposive sampling. This research instrument is the iinstrument (scale) for measuring the socio-economic family status and self-reportingquestionnaire-29 for mental health problems. The questionnaire uses google form which is distributed through social media. Respondents were selected based on the complete answers given to the questionnaire. The parametric statistical tests with the type of interval data (numeric) used the Pearson test and multiple linear regression. Results: The results obtain a p-value 0.001, which means that there is a relationship of anxiety, psychosomatic disorders, stress trauma, and socio-economic family status with the mental health of Indonesian communities during COVID-19. Based on multiple linear regression tests , the factors that have a close relationship with mental health are anxiety, psychosomatic disorders, and stress trauma (p-value 0.001 <0.05). Conclusion: Several factors cause mental health disorders , including anxiety, psychosomatic disorders, trauma stress, and socio-economic family status. As the recommendations for health workers, especially nurses, in providing health services to the community, they must be more comprehensive and familiar with client responses to prevent psychological impacts.
Comparative Analysis between Homoeologous Genome Segments of Brassica napus and Its Progenitor Species Reveals Extensive Sequence-Level Divergence

Foo Cheung,a,1 Martin Trick,b,1 Nizar Drou,b Yong Pyo Lim,c Jee-Young Park,d Soo-Jin Kwon,d Jin-A Kim,d Rod Scott,e J. Chris Pires,f Andrew H. Paterson,g Chris Town,a and Ian Bancroftb,2 a The J. Craig Venter Institute, Rockville, Maryland 20850 b John Innes Centre, Colney, Norwich NR4 7UH, United Kingdom cChungnam National University, Daejeon 305-764, Korea d National Academy of Agricultural Science, Rural Development Administration, Suwon 441-857, South Korea e University of Bath, Bath BA2 7AY, United Kingdom f University of Missouri, Columbia, Missouri 65211-7310 gUniversity of Georgia, Athens, Georgia 30602
Chemical reaction of alkoxysilane molecules in wood modified with silanol groups

Abstract Chemical reaction between silanol-modified wood and methyltrimethoxysilane (MTMS) was carried out using two different approaches with dibutyltin dilaurate (DBTDL) or ethylamine (EtNH2) as catalysts. Modifications were characterised by Fourier-transform infrared (FTIR) spectroscopy, as well as solid-state 13C and 29Si cross-polarisation with magic-angle spinning nuclear magnetic resonance (CP-MAS NMR) spectroscopy and scanning electron microscopy-energy dispersive X-ray (SEM-EDX) analysis. Silanol-modified wood was obtained by carbamoylation reaction with 3-isocyanatopropyltriethoxysilane (IPTES) and subsequent hydrolysis of the triethoxysilane end groups. 29Si CP-MAS NMR spectroscopy indicated that SiOH groups existed mostly in the form of mono- and di-condensed structures in wood, whatever the level of modification (low or high). The attachment of methyltrimethoxysilane (MTMS) molecules to silanol sites was apparently achieved when ethylamine was used as a catalyst. The reacted MTMS remaining in wood was found to exist mostly in the form of polysiloxane polymers (or oligomers), as shown by 29Si CP-MAS NMR results. Reactions performed with unmodified wood were much less effective, thereby demonstrating the importance of the IPTES pre-treatment.
Interleukin-23R (rs11209026) polymorphism confer the susceptibility in Psoriasis patients

Background: The recent advances in the understanding of psoriasis pathogenesis have clarified the pivotal role of interleukin (IL)-23. IL-23 is a heterodimeric cytokine, consisting of two subunits, the unique p19 and p40, which are shared with IL-12.The basic role of IL-23 in psoriasis is the activation and maintenance of the T-helper17 pathway.IL23R is a key player in the proliferation and survival of Th17 cells.The IL23 axis is the protagonist of the immunopathogenesis of psoriasis.therefore present study suggests to evaluated and investigated the single nucleotide polymorphisms of IL-23R (rs11209026) gene in seventy subjects.This study was find out the significant importance of IL-23R rs11209026 in disease susceptibility. Material and Methods: A blood sample was collected from two groups. The first group was patients with Psoriasis; the second group was healthy volunteers. Blood of this sample was collected in ethylinditetracitic acid (EDTA) tube and stored at 4°C for DNA extraction, polymerase-chain reaction -Restraction Fragment Polymorphism in length (PCR-RFLP) method which used to study SNP of IL-23R (rs11209026) gene. Results: The current study showed the range age of patients was (14–60), the results also revealed that 45.7% of the patients were males, and 54.3% of the patients were females.Regarding the IL-23R gene rs11209026 single nucleotide polymorphism in Iraqi psoriasis patients frequency distribution of genotype GG was significantly more frequent in patients group than in control, Patients were distributed as 7 (10.0 %) with allele A and 63 (90.0 %) with allele G; whereas, control group included 21 (30.0 %) individuals with allele A and 49 (70.0 %) subjects with allele G.
Machine learning-guided design of electronic band structures for organic materials

Many functional properties of materials, such as electrical, optical or magnetic, are governed by their electronic band structure (EBS). However, related calculations are computationally demanding, especially for organic crystals, which usually have a large number of atoms in the unit cell. The inverse problem – finding a stable crystal structure given its desired functional properties – is even more challenging. Recently, machine learning based heuristics to narrow down the search space started to gain popularity. In this thesis, I investigate and develop machine learning based tools for high-throughput screening and design of organic functional materials. Organic materials are of high technological relevance due to their elasticity, cheap production costs and the potential to build large area devices. First, the Organic Materials Database (OMDB) is discussed, including a new pattern search functionality that can be used to find non-trivial EBS features. Second, I investigate how machine learning methods can be used for both direct (predict a band structure corresponding to a given crystal structure) and inverse problems. Before considering real materials, an effective (i.e. tight-binding) model is discussed. Here, a direct map from hopping parameters to EBS is learned with kernel ridge regression (KRR). Additionally, by applying gradient descent to this map, it is possible to find an inverse solution. Finally, an example is shown of the transformation of an EBS from a trivial topological class to a class with a crossing. The proposed method can be applied to any machine-learned map, so it provides a general framework for inverse design. Regarding the real materials, a subset of the density functional theory (DFT) calculations contained within the OMDB is prepared. Using this data, a direct map is constructed from a given crystal structure to the band gap at Fermi level. The SOAP (Smooth Overlap of Atom Positions) descriptor is used together with kernel ridge regression. The learned map predicts the band gap with mean absolute error of 0.48 eV. This is a significant improvement of the MAE of 0.99 eV for a naive baseline.
Egyptian Journal of Aquatic Biology & Fisheries

The grass carp belongs to the family Cyprinidae and genus Ctenopharyngodon (Chilton and Muoneke, 1992). The native habitat extended from rivers to lakes in eastern Asia ( Lee et al., 1980). It was cultivated and widespread allover 80 countries worldwide (Fish Base, 2004). The grass carp are a good source of protein and exhibited biological activity of control the growth of aquatic weeds (Opuszynski & Shireman, 1995; Mitchell & Kelly, 2006). Due to the spread of aquatic plants in irrigating canals leading to water depletion, Ctenopharyngodon idella was introduced in Egypt as a biological control agent. Furthermore, the use of herbicides in the control of aquatic plants in the River Nile and irrigation canals in Egypt has been public health concern since 1990. The main issue of Egyptian grass carp production was its inability to spawn in ponds and lakes due to environmental differences from ARTICLE INFO ABSTRACT Article History: Received: Oct. 30, 2020 Accepted: Dec. 26, 2020 Online: Jan. 29, 2021 _______________
Underlying and Consequential Costs of Cyber Security Breaches: Changes in Systematic Risk

Severe security breaches can be costly for publicly listed firms. In order to deploy scarce resources in the most efficient way, decision makers in such firms need to be aware of all cost types associated with security breaches. In addition to obvious direct costs following the discovery of, response to, and mitigation of security breaches, there are also multiple underlying and consequential costs introduced or elevated by security breaches. One cost factor that is prone to be overlooked is systematic risk in the form of cost of equity. We present the results of an analysis of security breach-induced changes in regular, downside, and upside betas that contribute to increases in cost of equity. Analysing a US-centric sample of 202 severe security breaches between 2005 and 2019, we find that severe security breaches are associated with significantly positive increases of systematic risk and systematic downside risk in terms of regular and downside beta, respectively. Given the absence of similar effects for systematic upside risk in terms of upside beta, the analysis also reveals the unsymmetrical nature of the effect of security breaches on systematic risk. The implications of these findings and their relevance for firms’ costs of capital are discussed.
İnönü Üniversitesi Sağlık Hizmetleri Meslek Yüksekokulu Dergisi

In this study, allantoin-loaded chitosan nanoparticles were prepared and the effect of molecular weights (low, medium, and high) of chitosan was investigated on the release of allantoin. The allantoin-loaded chitosan nanoparticles were characterized by various methods. The morphology, size, zeta potential, and loading efficiency were affected by the molecular weight of chitosan. The results displayed that the average hydrodynamic diameter of chitosan nanoparticles was in the range of 427–768 nm and the zeta potential values from 5.97 to 5.12 mV was obtained. The allantoin release from chitosan nanoparticles reached the plateau level in 96 hours. Cumulative allantoin release values of low, medium, and high molecular mass chitosan nanoparticles were determined as 43%, 30%, and 27%, respectively. According to the results, the molecular weight of chitosan influenced on allantoin release.
NOVA at TREC 2020 Conversational Assistance Track

The use of conversational assistants to search for information is becoming more popular among the general public. In particular, in the last few years, the interest in conversational search is increasing, being this a step forward in allowing a more natural interaction with search systems. In this paper, we describe our work and submitted runs to TREC Conversational Assistance Track (CAsT) 2020 [4]. This track is mainly focused on Passage Conversational Information Seeking, being the context of the conversation key to retrieve relevant information. Our approach leverages a three-stage architecture composed of: (a) context tracking via query rewriting, (b) retrieval, and (c) re-ranking using a transformer model. The results obtained with this architecture achieved state-of-the-art results when compared to TREC CAsT 2019 baselines [5].
PERCEPTION OF VOLUNTEERING BY STUDENTS – FUTURE EMPLOYEES IN THE CONTEXT OF BUILDING SOCIAL RESPONSIBILITY IN A WORKPLACE POSTRZEGANIE WOLONTARIATU PRZEZ STUDENTÓW – PRZYSZŁYCH PRACOWNIKÓW W KONTEKŚCIE BUDOWANIA SPOŁECZNEJ ODPOWIEDZIALNOŚCI W MIEJSCU PRACY

The aim of the paper is to show, how students perceive volunteering, what are their motivations and which activities they undertake most often. In addition, the study aims to investigate whether the notion of ‘corporate volunteering’ is known and understood. The target group consists of students of the WSB University, studying Finances and Accounting and Tourism and Leisure. The applied measurement technique was a distributed survey. The results show that students are aware of benefits arising from volunteering, but their own involvement is limited. Less than 4 per cent of respondents took voluntary jobs while studying. Students do not really know the term ‘corporate volunteering’, even if the majority has some experience in working full-time. The results indicate the necessity of action in this respect, including educational one, since students’ attitudes, i.e. future or even current employees, will translate into building of CSR and, in the long term, shaping of the civil society.
Designing of fixed-dose combined tablets containing sustained-release portion of naproxen and immediate-release portion of ranitidine hydrochloride

The present study was performed to find out various ways to formulate a tablet dosage form containing naproxen in the sustained release (SR) portion and ranitidine HCl in the immediate release (IR) portion in order to produce a single tablet containing two different classes of drugs, widely prescribed by doctors. The combined tablets were formulated by two processes: bi-layer tablets and dual component compressed matrix core tablets. The sustained release layer of naproxen was prepared with Methocel K4M and Methocel K15M CR. The powders were evaluated for their flow properties and the finished tablets were evaluated for their physical parameters. The drug release study of ranitidine HCl and naproxen were evaluated using USP-XXII paddle type dissolution apparatus. The release rate of ranitidine HCl was studied for 45 min using water as media and that of naproxen was studied for 2 h in 0.1 M HCl followed by 11 h in pH 7.4 phosphate buffer media using a developed HPLC method at λmax of 240 nm. The release rate of ranitidine HCl from all the formulations was more than 80% at 45 min. In case of Methocel K4M and Methocel K15M based tablets with the increasing of polymer content the release mechanism moved to super case II. The MDT values of all the formulations were also calculated to correlate the values with the rate retardation capacity of drug release of the polymers used. Single tablets with two different drugs in two different layers containing different release pattern were prepared successfully.
An Analytical Solution to the IMU Initialization Problem for Visual-Inertial Systems

The fusion of visual and inertial measurements is becoming more and more popular in the robotics community since both sources of information complement each other well. However, in order to perform this fusion, the biases of the Inertial Measurement Unit (IMU) as well as the direction of gravity must be initialized first. In case of a monocular camera, the metric scale is also needed. The most popular visual-inertial initialization approaches rely on accurate vision-only motion estimates to build a non-linear optimization problem that solves for these parameters in an iterative way. In this letter, we rely on the previous work in [1] and propose an analytical solution to estimate the accelerometer bias, the direction of gravity and the scale factor in a maximum-a-posteriori framework. This formulation results in a very efficient estimation approach and, due to the non-iterative nature of the solution, avoids the intrinsic issues of previous iterative solutions. We present an extensive validation of the proposed IMU initialization approach and a performance comparison against the state-of-the-art approaches described in [2] and [3] with real data from the publicly available EuRoC dataset. Our approach achieves better accuracy without requiring an initial guess for the scale factor and incorporates a prior for the accelerometer bias in order to avoid observability issues. In terms of computational efficiency, it is as fast as the first work and two times faster than the second. We also provide a C++ open source reference implementation.
Distribution-free uncertainty quantification for classification under label shift

Trustworthy deployment of ML models requires a proper measure of uncertainty, especially in safety-critical applications. We focus on uncertainty quantification (UQ) for classification problems via two avenues -- prediction sets using conformal prediction and calibration of probabilistic predictors by post-hoc binning -- since these possess distribution-free guarantees for i.i. d. data. Two common ways of generalizing beyond the i.i. d. setting include handling covariate and label shift. Within the context of distribution-free UQ, the former has already received attention, but not the latter. It is known that label shift hurts prediction, and we first argue that it also hurts UQ, by showing degradation in coverage and calibration. Piggybacking on recent progress in addressing label shift (for better prediction), we examine the right way to achieve UQ by reweighting the aforementioned conformal and calibration procedures whenever some unlabeled data from the target distribution is available. We examine these techniques theoretically in a distribution-free framework and demonstrate their excellent practical performance.
The Merger Dynamics of the Galaxy Cluster A1775: New Insights from Chandra and XMM-Newton for a Cluster Simultaneously Hosting a Wide-angle Tail and a Narrow-angle Tail Radio Source

We present a new study of the merger dynamics of A1775 by analyzing the high-quality Chandra and XMM-Newton archival data. We confirm/identify an arc-shaped edge (i.e., the head) at ∼48 kpc west of the X-ray peak, a split cold gas tail that extends eastward to ∼163 kpc, and a plume of spiral-like X-ray excess (within about 81–324 kpc northeast of the cluster core) that connects to the end of the tail. The head, across which the projected gas temperature rises outward from to keV, is found to be a cold front with a Mach number of . Along the surfaces of the cold front and tail, typical Kelvin–Helmholtz instability features (noses and wings, etc.) are found and are used to constrain the upper limit of the magnetic field (∼11.2 μG) and the viscosity suppression factor (∼0.01). Combining optical and radio evidence, we propose a two-body merger (instead of systematic motion in a large-scale gas environment) scenario and have carried out idealized hydrodynamic simulations to verify it. We find that the observed X-ray emission and temperature distributions can be best reproduced with a merger mass ratio of 5 after the first pericentric passage. The NAT radio galaxy is thus more likely to be a single galaxy falling into the cluster center at a relative velocity of 2800 km s−1, a speed constrained by its radio morphology. The infalling subcluster is expected to have a relatively low gas content, because only a gas-poor subcluster can cause central-only disturbances as observed in such an off-axis merger.
Joint Network Topology Inference via Structured Fusion Regularization

Joint network topology inference represents a canonical problem of jointly learning multiple graph Laplacian matrices from heterogeneous graph signals. In such a problem, a widely employed assumption is that of a simple common component shared among multiple networks. However, in practice, a more intricate topological pattern, comprising simultaneously of sparse, homogeneity and heterogeneity components, would exhibit in multiple networks. In this paper, we propose a general graph estimator based on a novel structured fusion regularization that enables us to jointly learn multiple graph Laplacian matrices with such complex topological patterns, and enjoys both high computational efficiency and rigorous theoretical guarantee. Moreover, in the proposed regularization term, the topological pattern among networks is characterized by a Gram matrix, endowing our graph estimator with the ability of flexible modelling different types of topological patterns by different choices of the Gram matrix. Computationally, the regularization term, coupling the parameters together, makes the formulated optimization problem intractable and thus, we develop a computationally-scalable algorithm based on the alternating direction method of multipliers (ADMM) to solve it efficiently. Theoretically, we provide a theoretical analysis of the proposed graph estimator, which establishes a non-asymptotic bound of the estimation error under the high-dimensional setting and reflects the effect of several key factors on the convergence rate of our algorithm. Finally, the superior performance of the proposed method is illustrated through simulated and real data examples.