Miracle-dz/UniFAR-FTUs huggingface dataset:
Effective Schools: Interpreting the Evidence

This paper develops a theoretical context with which to understand the evidence on effective schools. I begin by specifying a central problem in the operation of inner-city schools--that good teachers are difficult to recruit and almost impossible to retain because the rewards of teaching do not outweigh the frustrations. Exceptions to this are identified in effective schools--schools that are distinctive in important ways. Principals of effective schools have a unitary mission of improved student learning, and their actions convey certainty that these goals can be attained. Such actions include recruiting outstanding teachers who have goals similar to their own and to those of other staff, organizationally buffering teachers to ensure that their efforts are directed toward raising student achievement, monitoring the academic progress teachers make, supplying additional technical assistance to needy teachers, and providing--mostly in concert with teaching colleagues--the opportunities to establish strategies to achieve instructional goals. Because the work of these principals pivots around improving student achievement, teachers have specific, concrete goals toward which to direct their efforts and know precisely when those efforts produce the desired effects. They are further encouraged by a supportive collegial group that lends ideas and assistance where needed. In turn, by achieving goals of student learning, teachers are provided with necessary motivation to continue to produce. The more teachers succeed with students, the greater their certainty that it is possible to succeed and the greater their experimentation procuring success.
Prevention of Oxidative Stress by Taurine in Alloxan-Induced Diabetic Mellitus inWistar Rats

Citation: Jimoh Abdulazeez. , et al. “Prevention of Oxidative Stress by Taurine in Alloxan-Induced Diabetic Mellitus in Wistar Rats”. EC Pharmacology and Toxicology 6.8 (2018): 707-718. Abstract Taurine, is a non-protein amino acid, with a unique chemical structure, it is involved in numerous biological and physiological functions with health benefits. In this study, the preventive effect of taurine on body weight, blood glucose level, oxidative stress and lipid peroxidation in alloxan-induced diabetes mellitus in wistar rats. Diabetes was induced by single intraperitoneal injection of alloxan monohydrate (150 mg/kg). Blood glucose level was measured after 72 hours of induction and diabetes was considered in animals with blood glucose level greater than 200 mg/dL with Accu-Check Active Glucometer. The rats were grouped into (5) groups of five animals each n = (5) Group 1: Normal control group, Group 2: diabetes untreated: Group 3: diabetes treated with 100 mg/kg taurine: Group 4: diabetes treated with 200 mg/kg, and Group 5: diabetes treated with glibenclamide (1 mg/ml). blood glucose and body weight of the rats were determined on weekly bases for three consecutive weeks. At the end of the treatment, all animals were sacrificed and blood samples was collected for determination of oxidative stress biomarkers and lipid peroxidation. The result of the present study shows a significant (P < 0.05) decrease in body weight and blood glucose in groups that received 100 and 200 mg/ kg of taurine compared with diabetic untreated group alone at 21 days of the experiment. Oxidative stress biomarkers superoxide dismutase (SOD), catalase (CAT) and glutathione peroxidase (GPx) recorded a (P < 0.05) decrease in values in groups that received taurine at doses of 100 mg/kg and 200 mg/kg compared with the diabetic untreated group. Lipid peroxidation activities showed a significant (P < 0.05) decrease in serum malondialdehyde (MDA) concentrations in diabetes groups treated with taurine when compared with diabetes untreated only. those treated with glibenclamide also recorded a significant decrease in serum oxidative stress biomarkers and lipid peroxidation when compared with the diabetic untreated group. In conclusion, this study revealed that taurine could be a preventive supplement against oxidative stress in type 1 diabetic and could be a potent supplement to mitigate against it occurrence.
IMPROVING PARENTING OF TODDLERS' EMOTIONS USING AN EMOTION COACHING PARENTING PROGRAM: A PILOT STUDY OF TUNING IN TO TODDLERS

Parental responses to children's emotions influence children's emotion-related abilities. Tuning in to Toddlers (TOTS) is a new emotion-focused parenting program for parents of toddlers aged 18 to 36 months. It is based on the empirically tested Tuning in to Kids program that teaches parents how to emotion coach their children. In the current pilot study, an intervention-only sample of parents of typically developing toddlers attended a 6-session group program. At preprogram and postprogram, parents’ emotion-coaching and emotion-dismissing behaviors were assessed using self-report questionnaires and observation measures. Results showed significant increases in self-reported and observed emotion coaching behaviors and use of emotion talk after intervention. There was also a significant decrease in self-reported and observed emotion dismissing behaviors, and toddler externalizing behavior problems. Overall, findings provide preliminary support for TOTS and suggest its potential as a valuable intervention for supporting parents in their efforts to emotion coach their toddlers.
Prairie Dog (Cynomys ludovicianus) is not a Host for Porcine Reproductive and Respiratory Syndrome Virus

Materials and methods: Sixteen wildcaught prairie dogs were inoculated intraperitoneally with a high-titered mixture of wild-type local PRRSV strains, and seven animals were uninoculated controls. Serum and tissues were collected at 3to 7-day intervals through 28 days for reverse transcriptase-polymerase chain reaction (RT-PCR) analysis of viral RNA and determination of an anti-PRRSV immune response, using a novel ELISA to measure specifi c prairie dog IgG responses to nine viral polypeptides.
Multi-capture Dynamic Calibration of Multi-camera Systems

Multi-camera systems have seen an emergence in various consumer devices enabling many applications e.g. bokeh (Apple IPhone), 3D measurement (Dell Venue 8) etc. An accurately calibrated multi-camera system is essential for proper functioning of these applications. Usually, a onetime factory calibration with technical targets is done to accurately calibrate such systems. Although accurate, factory calibration does not hold over the life time of the device as normal wear and tear, thermal effects, device usage etc. can cause calibration parameters to change. Thus, a dynamic or self-calibration based on multi-view image features is required to refine calibration parameters. One of the important factors governing the accuracy of dynamic calibration is the number and distribution of feature points in the captured scene. A dense feature distribution enables better sampling of the 3D scene, while avoiding degenerate situations (e.g. all features on one plane), thus sufficiently modeling the forward imaging process for calibration. But, single real life images with dense feature distribution are difficult or nearly impossible to capture e.g. texture-less indoor or occluded scenes. In this paper, we propose a new multi-capture paradigm for multi-camera dynamic calibration where multiple multiview images of different 3D scenes (thus varying feature point distribution) are jointly used to calibrate the multi-camera system. We present a new optimality criteria to select the best set of candidate images from a pool of multiview images, along with their order, to use for multi-capture dynamic calibration. We also propose a methodology to jointly model calibration parameters of multiple multi-view images. Finally, we show improved performance of multi-capture dynamic calibration over single-capture dynamic calibration in terms of lower epipolar rectification and 3D measurement error.
An Empirical Investigation of Food Consumer Behaviour in an Emerging Market

This study examines food consumers in the capital of Romania. A study of 485 consumers using the Theory of Reasoned Action underpinned the investigation of determinants of food choice. Drawing on a Structural Equation Models approach, causal paths for six commodities are estimated. Attitudes and habits tend to be significant predictors of intention to consume food. Intention is a significant, yet modest, predictor of actual behaviour. Although attitudes tend to be a key predictor in TRA, the higher paths for attitudes relative to habit contrast the study of Saba and Di Natale (1999). As reported elsewhere (Bagozzi and Warshaw 1990) the predictive power of the models in explaining behavioural intent exceeds the corresponding one for behaviour. The results of this empirical study support the notion that attitudes and habits influence behavioral intentions of food consumers in this emerging market. Competing structural models are discussed and the implications of the study for both food marketers and health campaigners are highlighted.
Electric-field control of the chiral magnetism of multiferroic MnWO 4 as seen via polarized neutron diffraction

T. Finger,1 D. Senff,1 K. Schmalzl,2 W. Schmidt,2 L. P. Regnault,3 P. Becker,4 L. Bohatỳ,4 and M. Braden1,* 1II. Physikalisches Institut, Universität zu Köln, Zülpicher Str. 77, D-50937 Köln, Germany 2Institut für Festkörperforschung, Forschungszentrum Jülich GmbH, JCNS at ILL, 38042 Grenoble Cedex 9, France 3Institut Nanosciences et Cryogénie, CEA-Grenoble, DRFMC-SPSMS-MDN, 38054 Grenoble Cedex 9, France 4Institut für Kristallographie, Universität zu Köln, Zülpicher Str. 49b, D-50674 Köln, Germany Received 5 November 2009; revised manuscript received 9 December 2009; published 18 February 2010
MCE 2018 BIOMETRIC VOX SYSTEM FOR THE MCE 2018 CHALLENGE

This paper describes the systems we developed for the MCE 2018 1st Multi-target speaker detection and identification Challenge Evaluation. The first system uses Linear Discriminant Analysis followed by Probabilistic Linear Discriminant Analysis for scoring, while the second system uses an ensemble of Denoising Autoencoders to compute more representative speaker embeddings. Both systems use Top S-Norm for score normalization. Our best system achieves a Top-1 EER of 6.52%, which represents a 46.8% error reduction with respect to the baseline system provided by organizers.
Divergence Based Non-Negative Matrix Factorization for top-N Recommendations

Personalized top-N recommendation algorithms are among the most effective techniques providing customized suggestions in information retrieval applications. Most of the current methods construct personalized recommendations based on various loss functions such as pairwise ranking loss and point-wise recovery loss. In this paper, we propose a personalized top-N recommendation method based on non-negative matrix factorization with divergence as a point-wise ranking loss function. Our method finds the latent factors from the existing data to improve recommendation predictions. We formulate the learning problem with regularized divergence as a constrained non-convex minimization problem and develop a projected gradient descent optimization algorithm to solve the divergence problem. We evaluate our approach using six personal recommendation task related datasets by employing root mean squared error (RMSE) and hit rate (HR). Our experimental results demonstrate improved RMSE and HR for most of the datasets.
Confirmatory factor analysis of Warr, Cook, and Wall’s (1979) Job Satisfaction Scale Job Satisfaction (JS) is one of the most commonly measured constructs in industrial / organisational (I/O) psychology due to its links to individual and organisational workplace

Warr, Cook, and Wall’s (1979) Job Satisfaction Scale is widely used measure of job satisfaction in industrial/organisational psychology research and practice. However, the factor structure has not been adequately explored, with two-factor and three-factor solutions previously proposed. This study tested the factor structure of the Job Satisfaction Scale using robust analysis methods on data gathered from a convenience sample of 381 (females = 264, males = 116) Australian employees. Confirmatory factor analyses supported a higher order three-factor model of job satisfaction over three factor, two factor and single factor models. Item 13, relating to satisfaction with hours of work, is weakly associated with other items and model fit improves if this item is deleted. The results support the continued use of an overall score of job satisfaction when using this measure in industrial/organisational psychology research and practice. Further testing of the structure is recommended within a range of employment sectors to see if the higher order three factor model holds.
Rhythmic design in the support drums of Agbadza

The Ewe percussion music of Ghana is one of the African musics best understood in structural terms at this time, due to the efforts of a number of researchers. The aim of this paper is to further this accumulation of stylistic information by a detailed analysis of support drum characteristics in the Ewe music Agbadza. Enough data are analysed to make suppositions about general guiding principles which appear to operate in this music. The source of these patterns is primarily my personal study with Ewe master drummer C.K. Ladzekpo, who lives in Berkeley, California. All the patterns were transcribed from performances or demonstrations by African music ensembles led by Mr Ladzekpo.
Implementing Task-based Instruction in ESP Class — An Empirical Study in Marine Engineering English

This study investigated teaching English for Specific Purposes (ESP) within the paradigm of task-based language teaching, concentrating on marine engineering English teaching in a Chinese vocational college. Two natural groups of students taking their ESP courses took part in the study as a control group (N=28) and an experimental group (N=33) from 2014 spring to 2014 fall. Teacher-designed reading, listening and speaking pre-test and post-test (simulating the governmental tests held by China Maritime Safety Administration Bureau), and survey were used as the basis for study. The students in the control group and the experimental group were taught in traditional approach and task-based approach respectively. At the end of one academic year study, the students were given a post-test to determine whether there was effect of the treatment on the experimental group. Data analysis showed that there was no statistically significant difference in reading achievement between students in the control group and students receiving task-based instruction, but there was effect on students’ listening and speaking competency. In the investigation, most students were satisfied with task-based instruction, and they proposed some feedbacks and suggestions for the task-based instruction in ESP courses which are beneficial for future instruction.
How to Test the SME with Space Missions

In this communication, we focus on possibilities to constrain SME coefficients using Cassini and Messenger data. We present simulations of radio science observables within the framework of the SME, identify the linear combinations of SME coefficients the observations depend on and determine the sensitivity of these measurements to the SME coefficients. We show that these datasets are very powerful for constraining SME coefficients.
Refining Terminological Saturation using String Similarity Measures

This paper reports on the refinement of the THD algorithm, developed in the OntoElect framework. This baseline THD algorithm used exact string matches for key term comparison. It has been refined by introducing an appropriate string similarity metric for grouping the terms having similar meaning and looking similar as text strings. To choose the most appropriate metric, several existing metrics have been cross-evaluated on the developed test set of multiword terms in English. The rationale for creating this test set is also presented. Further, the refined algorithm for measuring terminological difference has been cross-evaluated with the baseline THD algorithm. For this cross-evaluation, the bags of terms extracted from the TIME collection of scientific papers were used. The experiment revealed that using the refined algorithm yielded better and quicker terminological saturation, compared to the baseline.
Asymptotic behavior of the Empirical Process for Gaussian data presenting seasonal long-memory

We study the asymptotic behavior of the empirical process when the underlying data are Gaussian and exhibit seasonal long-memory. We prove that the limiting process can be quite different from the limit obtained in the case of regular long-memory. However, in both cases, the limiting process is degenerated. We apply our results to von–Mises functionals and U -Statistics.
Some Results on Tchebychefian Spline Functions

This report derives explicit solutions to problems involving Tchebycheffian spline functions. We use a reproducing kernel Hilbert space which depends on the smoothness criterion, but not on the form of the data, to solve explicitly Hermite-Birkhoff interpolation and smoothing problems. Sard’s best approximation to linear functionals and smoothing with respect to linear inequality constraints are also discussed. Some of the results are used to show that spline interpolation and smoothing is equivalent to prediction and filtering on realizations of certain stochastic processes.
"IMPROVED GEOMETRIC NETWORK MODEL" (IGNM): A NOVEL APPROACH FOR DERIVING CONNECTIVITY GRAPHS FOR INDOOR NAVIGATION

Over the past few years Personal Navigation Systems have become an established tool for route planning, but they are mainly designed for outdoor environments. Indoor navigation is still a challenging research area for several reasons: positioning is not very accurate, users can freely move between the interior boundaries of buildings, path network construction process may not be easy and straightforward due to complexity of indoor space configurations. Therefore the creation of a good network is essential for deriving overall connectivity of a building and for representing position of objects within the environment. This paper reviews current approaches to automatic derivation of route graphs for indoor navigation and discusses some of their limitations. Then, it introduces a novel algorithmic strategy for extracting a 3D connectivity graph for indoor navigation based on 2D floor plans.
A Sampling Method for Quantifying the Information Content of IASI Channels

AbstractThere is a vast amount of information about the atmosphere available from instruments on board satellites. One example is the Infrared Atmospheric Sounding Interferometer (IASI) instrument, which measures radiances emitted from Earth’s atmosphere and surface in 8461 channels. It is difficult to transmit, store, and assimilate such a large amount of data. A practical solution to this has been to select a subset of a few hundred channels based on those that contain the most useful information.Different measures of information content for objective channel selection have been suggested for application to variational data assimilation. These include mutual information and the degrees of freedom for signal. To date, the calculation of these measures of information content has been based on the linear theory that is at the heart of operational variational data assimilation. However, the retrieval of information about the atmosphere from the satellite radiances can be highly nonlinear.Here, a sampling me.
Minimizing the conditional value-at-risk for a coupon-bearing bond using a bond put option

In this paper, we elaborate a formula for determining the optimal strike price for a bond put option, used to hedge a position in a bond. This strike price is optimal in the sense that it minimizes, for a given budget, either Value-at-Risk or Conditional Value-at-Risk. Formulas are derived for both zero coupon and coupon bonds, which can also be understood as a portfolio of bonds. These formulas are valid for any short rate model with a given distribution of future bond prices.
Renal Toxicity of Zinc Oxide Nanoparticles ( ZnONPs ) of Male Westar Rats

Background: Zinc oxide (ZnO) is one of the most commonly utilized materials in diverse industrial fields such as dyes, paints, pigments, metallurgy additives, rubber, alloys, ceramics, chemical fibers, electronics, catalyst, medical diagnosis, sunscreens, cosmetics, personal care products, and food additives. Nano particles have the ability to enter, penetrate physiological barriers, and travel within the circulatory systems to all body organs affecting the health of human and animals. Understanding various adverse effects of ZnO NPs on cellular and organs functions is necessary to provide better approaches for them. Aim of work: In the present study, we evaluated the potential toxicity of ZnONPs in kidney of Westar rats. Methods: The current study was carried out on forty apparently healthy mature male Westar rats weighing between 120-200 gm with average three months age. The rats weredivided randomly into four groups (10 rats/ group). Group I (G1) was kept as a control and fed with a basal diet only. Group II (G2), Group III(G3) and Group IV(G4) were obtained ZnO NPsin a dose 100, 250 and 500 mg/ kg body weight respectively by oral gavage for 21 days. At the end of experiment, cervical dislocation of rats and the kidneys were separated for the histopathological studies. Result: The present investigation revealed that the kidney of the control group (G1) showed normal renal parenchyma without any abnormalities. Meanwhile, G2 and G3 showed mild to moderate necrosis of the renal corpuscle and renal tubules with moderate accumulations of dense acidophilic material in intra tubular parts. With increasing dose of ZnO NPs, the renal toxicity became more obvious where, the kidney of G4 showed severe necrosis in the renal corpuscles with severs dilatation of the renal tubules accompanied with sloughing and degeneration of its lining epithelium, with sever accumulation of dense acidophilic material in intra and inter tubular parts, sever nephritis with sever inflammatory cells infiltration and fibrous tissue proliferation. Conclusion: The present investigation was concluded that the ZnO NPs have potential renal toxicity that may affect the function of the kidney.
Design Patterns for Object-Oriented Scientific Software

Software design patterns are general reusable object-oriented solution. In software engineering, patterns have been proven to offer many benefits. Scientific software also becomes more object-oriented and the importance of design patterns increases. We present a set of design patterns for object-oriented scientific software. Particularly we develop computer-aided engineering software based on the Finite element method. Initially, we decompose the problem into subsystems by applying the commonality and variability analysis. A set of commonalities includes following terms: a representation scheme, a mesh, a solver, etc. A representation scheme is an interface that allows to check whether a point belong to a solid or not. A mesh is the discrete representation of the solid via a set of simple geometric shapes. Four basic design patterns for the scientific software development have been presented in this paper. There are developed UI– Model–Analysis, Representation–Mesh, Element–Mesh, and FEA Problem patterns. These design patterns separate pre-processing, the analysis solver, and post-processing of results.