Miracle-dz/UniFAR-FTUs huggingface dataset:
An Investigation into the Relationship between Turkish EFL Teachers’ Self-Efficacy and Burnout Level

The present study investigates if any relationship between self-efficacy beliefs and burnout levels as well as the effect of demographic data such as gender, age, teaching experience, average number of students in classrooms on the three dimensions of teacher burnout (emotional exhaustion, depersonalization, and personal accomplishment) and self-efficacy beliefs. 118 Turkish EFL teachers from primary, secondary, high schools and universities in many cities participated in the study. Data came from Maslach Burnout Inventory (MBI), and language teacher self-efficacy beliefs scale (Praver 2014). Findings showed that there was a significant positive relationship between self-efficacy and personal accomplishment and emotional exhaustion. On the other hand, the results showed a negative relationship between emotional exhaustion and personal accomplishment and a negative relationship between personal accomplishment and depersonalization. Generally, teachers felt sufficient, had high self-accomplishment and they had low burnout level. In addition, age and experience were also found to play an important role in personal accomplishment and self-efficacy. These findings have been discussed and implications given for further research.
Microbiological impact of three commercial laying hen housing systems1

Hen housing for commercial egg production continues to be a societal and regulatory concern. Controlled studies have examined various aspects of egg safety, but a comprehensive assessment of commercial hen housing systems in the US has not been conducted. The current study is part of a holistic, multidisciplinary comparison of the diverse aspects of commercial conventional cage, enriched colony cage, and cage-free aviary housing systems and focuses on environmental and egg microbiology. Environmental swabs and eggshell pools were collected from all housing systems during 4 production periods. Total aerobes and coliforms were enumerated, and the prevalence of Salmonella and Campylobacter spp. was determined. Environmental aerobic and coliform counts were highest for aviary drag swabs (7.5 and 4.0 log cfu/mL, respectively) and enriched colony cage scratch pad swabs (6.8 and 3.8 log cfu/mL, respectively). Aviary floor and system wire shell pools had the greatest levels of aerobic contamination for all eggshell pools (4.9 and 4.1 log cfu/mL, respectively). Hens from all housing systems were shedding Salmonella spp. (89–100% of manure belt scraper blade swabs). The dry belt litter removal processes for all housing systems appear to affect Campylobacter spp. detection (0–41% of manure belt scraper blade swabs) considering detection of Campylobacter spp. was much higher for other environmental samples. Aviary forage area drag swabs were 100% contaminated with Campylobacter spp. , whereas enriched colony cage scratch pads had a 93% positive rate. There were no differences in pathogen detection in the shell pools from the 3 housing systems. Results indicate egg safety is enhanced when hens in alternative housing systems use nest boxes. Additionally, current outcomes indicate the use of scratch pads in hen housing systems needs to be more thoroughly investigated for effects on hen health and egg safety.
Local fairing with local inverse

Local fairing techniques are extensively used in the geometry processing of curves and surfaces. They also play an important role in the multiresolution shape editing and synthesis applications. However, due to the inter-dependency of the vertices after applying the current fairing techniques, their inverses are not local. Finding a local fairing operation with local inverse provides a well-defined relationship between the smooth vertices and the initial vertices. This paper introduces a new fairing operation for curves and surfaces that is smoothing and local but with a local inverse. In the curve domain, we find a class of banded smoothing matrices with banded inverses. Then, using the geometric interpretation of the corresponding local operation, this class is extended to surfaces. We discuss the advantages of using this new fairing operation in different applications. Also, the resulting operation is used to find novel subdivision schemes with well-defined reverse subdivisions.
Quasi-nonlinear Evolution of Stochastic Bias

It is generally believed that the spatial distribution of galaxies does not trace that of the total mass. Understanding the bias effect is therefore necessary to determine the cosmological parameters and the primordial density fluctuation spectrum from the galaxy survey. The deterministic description of bias may not be appropriate because of the various stochasticity of galaxy formation process. In nature, the biasing is epoch dependent, and a recent deep survey of the galaxy shows large biasing at high redshift. Hence, we investigate quasi-nonlinear evolution of the stochastic bias by using the tree-level perturbation method. Especially the influence of the initial cross-correlation on the evolution of the skewness and the bi-spectrum is examined in detail. We find that the nonlinear bias can be generated dynamically. The small value of the initial cross-correlation can bend the δg-δm relation effectively and easily lead to the negative curvature (b2<0). We also propose a method to predict the bias, cross-correlation, and skewness at high redshift. As an illustration, the possibility of large biasing at high redshift is discussed. Provided the present bias parameter as b=1.5 and Ω=1.0, we predict the large-scale bias to be b=4.63 at z=3 by fitting the bi-spectrum to the Lick catalog data. Our results will be important for the future deep sky survey.
Using Personal Traits For Brand Preference Prediction

In this paper, we present a comprehensive study of the relationship between an individual’s personal traits and his/her brand preferences. In our analysis, we included a large number of character traits such as personality, personal values and individual needs. These trait features were obtained from both a psychometric survey and automated social media analytics. We also included an extensive set of brand names from diverse product categories. From this analysis, we want to shed some light on (1) whether it is possible to use personal traits to infer an individual’s brand preferences (2) whether the trait features automatically inferred from social media are good proxies for the ground truth character traits in brand preference prediction.
Constraint solvers: An empirical evaluation of design decisions

This paper presents an evaluation of the design decisions made in four state-of-the-art constraint solvers; Choco, ECLiPSe, Gecode, and Minion. To assess the impact of design decisions, instances of the five problem classes n-Queens, Golomb Ruler, Magic Square, Social Golfers, and Balanced Incomplete Block Design are modelled and solved with each solver. The results of the experiments are not meant to give an indication of the performance of a solver, but rather investigate what influence the choice of algorithms and data structures has. The analysis of the impact of the design decisions focuses on the dierent ways of memory management, behaviour with increasing problem size, and specialised algorithms for specific types of variables. It also briefly considers other, less significant decisions.
Detection of Verbatim or Partial Duplication from Multiple Source Documents Using Data Mining Techniques and Case-Based Reasoning Methodologies

This paper aims to specify a Case-Based Reasoning strategy for correctly classifying, storing and preventing duplication efforts of electronic text material. Preservation of complete source documents for checking similarity between them pose a daunting amount of spatial and computational complexity to researchers in this area. The problem is partially solved by applying certain preprocessing steps to reduce the volume of data handling substantially. Reduction of volume in text documents is achieved by applying some stemming algorithm and elimination of stop words from the document utilizing certain text-mining measures such as TF-IDF. A third technique involves extraction of keywords and storing them in a properly indexed base. These then can serve the dual purpose of providing solutions to Lazy Learning classification for automatic subject-wise archiving and formation of relevant word sequences for detection of plagiarism using Association Rule-mining techniques.
A graphical tool for driving the parallel computation of pseudosprectra

This paper presents the programming environment of a new tool for the parallel computation of Pseudospectra. Based on the PPA Talgorithm described in [16, 17], this algorithm offers total reliability and can handle singularities along the level curve without difficulty. It offers a guarantee of termination even in the presence of round-off errors and makes use of the large granularity for parallelism in PAT [17]. This results in large speedups and high efficiency. The software is able to trace multiple level curves simultaneously and task in to account the symmetry of the pseudospectrum in the case of real matrices to reduce the total computational cost. The ability of the software to compute multiple slices of the same level curve simultaneously enhances the speedup and efficiency. The user drives the parallel application through a graphical user interface. The interface includes graphical features (zoom in, zoom out, color control,…) and computational features (raise or lower level curve priority, limit computation to a set of processors,…) crucial for the appreciation of the information provided by the pseudospectrum. Although the application was developed for the computation of the pseudospectrum, it can be used, provided minor modifications, to trace the level curves of any continuous, not necessarily smooth, function f(z): C → R
A 100KHz - 20MHz source follower continuous time filter for SDR applications

The source follower based filters are proposed in the literature for wireless LAN applications and are preferred as they dissipate lower power compared to the filters using other architectures. To comply with multitude standards, filters with bandwidth programmable from 100KHz – 20MHz are required. In this paper, a second order, composite source follower based filter is made to work in weak inversion in order to achieve wide tuning range and to minimize power consumption. The centre frequency of this filter is varied using current steering DAC. The proposed filter is designed and implemented on TSMC-0. 18µm CMOS process with 1.2V supply. The simulation results demonstrate the tunability of the centre frequency from 100KHz to 20MHz which meets the requirements of zero IF receivers for SDR applications. The third order input intercept point (IIP3) is found to be 15 dBVp for an input signal of 200mVp. The power dissipated by the filter is 1µW and 20µW at 100 KHz and 20 MHz respectively. The proposed filter consumes 14 times less power than that proposed in the literature at the cost of 1.5 times increase in the noise. A 55 µ Vrms noise gives a dynamic range of 66dB.
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— In this paper, we model the salient object detection problem under a probabilistic framework encoding the boundary connectivity saliency cue and smoothness constraints in an optimization problem. We show that this problem has a closed form global optimum which estimates the salient object. We further show that along with the probabilistic framework, the proposed method also enjoys a wide range of interpretations, i.e. graph cut, diffusion maps and one-class classification. With an analysis according to these interpretations, we also find that our proposed method provides approximations to the global optimum to another criterion that integrates local/global contrast and large area saliency cues. The proposed approach achieves leading performance compared to the state-of-the-art algorithms over a large set of salient object detection datasets including around 17k images for several evaluation metrics. Furthermore, the computational complexity of the proposed method is favorable/comparable to many state-of-the-art techniques.
The Natural Polyphenol Epigallocatechin Gallate Protects Intervertebral Disc Cells from Oxidative Stress

Oxidative stress-related phenotypic changes and a decline in the number of viable cells are crucial contributors to intervertebral disc degeneration. The polyphenol epigallocatechin 3-gallate (EGCG) can interfere with painful disc degeneration by reducing inflammation, catabolism, and pain. In this study, we hypothesized that EGCG furthermore protects against senescence and/or cell death, induced by oxidative stress. Sublethal and lethal oxidative stress were induced in primary human intervertebral disc cells with H2O2 (total n = 36). Under sublethal conditions, the effects of EGCG on p53-p21 activation, proliferative capacity, and accumulation of senescence-associated β-galactosidase were tested. Further, the effects of EGCG on mitochondria depolarization and cell viability were analyzed in lethal oxidative stress. The inhibitor LY249002 was applied to investigate the PI3K/Akt pathway. EGCG inhibited accumulation of senescence-associated β-galactosidase but did not affect the loss of proliferative capacity, suggesting that EGCG did not fully neutralize exogenous radicals. Furthermore, EGCG increased the survival of IVD cells in lethal oxidative stress via activation of prosurvival PI3K/Akt and protection of mitochondria. We demonstrated that EGCG not only inhibits inflammation but also can enhance the survival of disc cells in oxidative stress, which makes it a suitable candidate for the development of novel therapies targeting disc degeneration.
Effects of Burning and Grazing on a Coastal California Grassland

We tested the effects of fall burning and protection from livestock grazing as management to enhance native grasses on a coastal grassland in central California. Plants from the Mediterranean, introduced beginning in the late 1700s, have invaded and now dominate most of California's grasslands. Coastal grasslands are generally less degraded than those inland and have higher potential for restoration and conservation. Productivity of the experimental plots varied annually and declined over the course of the study because of rainfall patterns. Foliar cover of the native Danthonia californica (California oatgrass) increased more under grazing than grazing exclusion and did not respond to burning. Two other natives, Nassella pulchra (purple needlegrass) and Nassella lepida (foothill needlegrass), responded variably to treatments. The response of N. pulchra differed from that reported on more inland sites in California. Restoring these grasslands is complicated by differing responses of target species to protection from grazing and burning. The current practice of managing to enhance single species of native plants (e.g., N. pulchra) may be detrimental to other equally important native species.
PREDICTING REMEMBERED AND ANTICIPATED UTILITY FOR SEQUENCES OF TEMPORALLY EXTENDED OUTCOMES

A field study was conducted to investigate determinants of overall utility evaluations for sequences of past and future outcomes. Prevalent theories of utility integration have been tested in the context of a non-aversive experience. Heuristic models assume that decision makers retain a few descriptive statistics of experiences for the overall judgment. Performance of these models was compared to the prediction of the simple summation method and an “as if” belief-adjustment process. Results suggest that belief-adjustment may be the possible way of explaining both retrospective and prospective utility judgments in a uniform fashion.
Corruption affecting small businesses in formal and informal districts of Cairo before & after the January 2011 Revolution

I would like to thank my parents & my sisters for their continuous support and endless efforts to help me reach this point. Dr. Jennifer, Dr. Khaled and Dr. Ghada thank you a million times for your guidance, knowledge and feedback throughout this research. Also, special thanks to everyone (Friends, Faculty and Staff) who helped me not only with this research, but also with my journey throughout AUC.
Experimental design for sternocleidomastoid muscle stress measurement

In this paper we assess the sternocleidomastoid muscle stress with two experimental studies to evaluate the developed smart neck support system. The first study involving head rotation angle and sternocleidomastoid muscle (SCM) electromyography (EMG) activity. This (descriptive) study extends efforts from different authors to assess the isometric strength of SCM, in which the experiment is carried out in relation to time. This first study functions as a calibration experiment which provides the input for the second study as a validation experiment. The validation experiment was conducted inside the aircraft cabin simulator. The SCM of participant was evaluated with electromyography. The smart neck support system is to reduce the SCM muscle stress of aircraft passenger adaptively during air travel.
Biomechanical Evaluation of Head Kinematics During Infant Shaking Versus Pediatric Activities of Daily Living

Abusive shaking of infants has been asserted as a primary cause of subdural bleeding, cerebral edema/brain swelling, and retinal hemorrhages. Manual shaking of biofidelic mannequins, however, has failed to generate the rotational accelerations believed necessary to cause these intracranial symptoms in the human infant. This study examines the apparent contradiction between the accepted model and reported biomechanical results. Researchers collected linear and angular motion data from an infant anthropomorphic test device during shaking and during various activities of daily life, as well as from a 7-monthold boy at play in a commercial jumping toy. Results were compared among the experimental conditions and against accepted injury thresholds. Rotational accelerations during shaking of a biofidelic mannequin were consistent with previous published studies and also statistically indistinguishable from the accelerations endured by a normal 7-month-old boy at play. The rotational accelerations during non-contact shaking appear to be tolerated by normal infants, even when repetitive.
EXTENTION COHOMOLOGICAL FIELDS THEORY AND NONCOMMUTATIVE FROBENIUS MANIFOLDS

INTRODUCTION The Cohomological Field Theory was propose by Kontsevich and Manin [5] for description of Gromov-Witten Classes. They prove that Cohomological Field Theory is equivalent to Formal Frobenius manifold. Formal Frobenius manifold is defined by a formal series F , satisfying to associative equations. In points of convergence the series F defines a Frobenius algebras. The set of these points forms a Frobenius manifold [4], i.e. a space of special deformations of Frobenius algebras. Cohomological Field Theory is a system of special homomorphisms to spaces of cohomology of Deline–Mumford compactifications for moduli spaces of complex curves (Riemann spheres) with punctures. In this paper there is an extension (Stable Field Theory) of Cohomological Field Theory. It is a system of homomorphisms to some algebras generated by disks with punctures. I conjecture that they describe relative Gromov–Witten classes. Stable Field Theory is equivalent to some analog of Formal Frobenius manifold. This analog is defined by formal tensor series (Structure Series) satisfying some system of ”differential equations” (including associativity equation). In points of convergence the Structure Series define Extend Frobenius algebras. They are special noncommutative analog of Frobenius algebra. Extended Frobenius algebras describe ’Open-Closed’ Topological Field Theories [6] of genus 0 by analogy that Frobenius algebras describe Atiyah–Witten 2D Topological Field Theories. Thus Structure Series are noncommutable analogs of Formal Frobenius manifolds. In passing it is given some other proof of Kontsevich–Manin theorem about equivalence Cohomological Field Theories and Formal Frobenius manifolds. In sections 1 and 2 it is proposed a general axiomatic of Topological Field Theories over functors. This class involves, 2D Atiyah–Witten [2], [11] ’open-closed’ [6], Klein [3] Topological Field Theories and Cohomological Field Theories [5], [7]. In section 3 it is constructed and investigated a Stabilizing functor on a category of spheres with punctures, disks with punctures and its
Local window K_means clustering and merging for color image segmentation

In this paper, we propose a faster and more efficient color image segmentation technique, which is called local window K_means (LWK_means), consisting of three modules: window presetting, local window clustering, windows merging. LWK_means divides the color image into many windows, and then parallelly processes each window using the proposed local window K_means clustering algorithm, which is adaptive and gives a more reliable initial clustering center instead of random initialization, in compressed HSI color space. And the final windows merging method is proposed in such a way as to automatically pull the independent windows together into an image with good spatial continuity. Experimental results demonstrate that the proposed technique is able to work better than the state-of-the-art color image segmentation algorithms with the least time consumption achieving a higher efficiency.