Miracle-dz/UniFAR-FTUs huggingface dataset:
Learned Resourcefulness and Coping with Stress in Mothers of Children with Disabilities.

Problem Statement: Research has indicated that some mothers can cope with stressful life conditions and continue their lives normally, whereas others are unable to overcome such challenging conditions. Recent research has shown that mothers of children with disabilities are likely to know more about why some mothers have relatively well-adjusted lives despite stressful conditions, as well as why they cope better with these conditions than others. However, to date, studies in Turkey have only concentrated on the degree to which mothers of children with disabilities feel stress and which coping ways they use to curb the negative effects of stress. Purpose of the Study: This study aimed to examine the relationships between learned resourcefulness and ways of coping with stress. Methods: The study sample consisted of 222 mothers of children attending special education institutions during the 2011–2012 academic year in Sakarya, Turkey. The Self-Control Schedule and Ways of Coping Inventory were used to assess learned resourcefulness and coping strategies, the relationships among which investigated using Pearson
The Evolution of the Niobium Production in Brazil

Niobium (Nb) was initially applied in the industry in 1933 to stabilize stainless steels against intergranular corrosion. Around 1970, niobium started to be used in many technological applications, especially in heat treatments at high temperatures, in the form of superalloys and, over the past four decades, Nb has been employed on an industrial scale. During recent years, applications of niobium have increased steadily in various segments such as: micro-alloyed steels, super alloys, thin films, medical implants, titanium and aluminum alloys, superconductors and copper alloys, electrolytic and ceramic capacitors. The worldwide demand for Nb grew at an annual rate of 10% between the years 2000-2010, were the sectors of energy, automotive and construction of the largest consumers FeNb. In 2000 the brazilian production was 35,458 t of Nb and, in 2007, reached 82,000 t of concentrate Nb. Brazil has the world's largest reserves of Nb (98.53%), which totaled 842.4 million t. So, in this paper is made a study on the evolution of the production of niobium in Brazil and its main industrial and technological applications.
Nutritional value of whole coconut, coconut powder, and coconut fiber treated with sodium hydroxide for sheep

The growing consumption of green coconut - fresh and industrialized - in Brazil generates a large volume of wastes and coproducts that justifies the search for alternatives for their use in animal feeding. The most limiting factor to the inclusion of these coproducts in ruminant diets is their high fiber content, which may restrict intake and performance. The present study determined the composition and in vitro dry matter degradability of whole coconut, coconut powder, and coconut fiber treated with sodium hydroxide (0%, 3%, and 6%) and the effect of including whole coconut hydrolyzed with 6% sodium hydroxide at different concentrations (25%, 30%, 35%, and 40%) in the diet on apparent digestibility of nutrients, performance, and feeding behavior of sheep. Alkalinization decreased the hemicellulose, NDF, and ADF contents of the evaluated coproducts. Whole coconut and coconut powder provided greater in vitro degradation of DM compared with coconut fiber, with highest values obtained with the inclusion of 6% sodium hydroxide. Inclusion of whole coconut in the diets did not affect the intakes of DM, CP, NDF, and ADF, but influenced weight gain, feed conversion, and apparent digestibility of DM and NDF. Regarding the feeding behavior of the animals, the inclusion of whole coconut in the diet only affected their rumination time. Whole coconut hydrolyzed with 6% NAOH can be included in diets for feedlot sheep at up to 35% without reducing intake or weight gain.
Bleeding Classification of Enhanced Wireless Capsule Endoscopy Images using Deep Convolutional Neural Network

This paper investigates the performance of a Deep Convolutional Neural Network (DCNN) algorithm to identify bleeding areas of wireless capsule endoscopy (WCE) images without known prior knowledge of bleeding and normal features of the images. In this study, a pre-processing technique has been proposed to improve the classification accuracy of WCE images into bleeding areas and normal areas by enhancing the WCE images. The proposed technique is applied to WCE images from six cases and divided into one training case and five test cases. To evaluate the effectiveness of the processes, the results were then compared between DCNN, SVM and Fuzzy, and also between DCNN with completely enhanced images and DCNN with normalized images. DCNN has shown to give a better result compared to SVM and Fuzzy logic; and the latter experiment has shown that the WCE images that have undergone the proposed enhancement technique gives better classification result compared to those images that did not go through the technique. The specificity, sensitivity and average are 0.8703, 0.8271 and 0.8907 respectively. In conclusion, DCNN has been proven to be able to successfully detecting bleeding areas from images without having any specific knowledge on imaging diagnosis or pathology.
University of Groningen Structure of the alexithymic brain

Alexithymia refers to deficiencies in identifying and expressing emotions. This might be related to changes in structural brain volumes, but its neuroanatomical basis remains uncertain as studies have shown heterogeneous findings. Therefore, we conducted a parametric coordinate-based meta-analysis. We identified seventeen structural neuroimaging studies (including a total of 2586 individuals with different levels of alexithymia) investigating the association between gray matter volume and alexithymia. Volumes of the left insula, left amygdala, orbital frontal cortex and striatum were consistently smaller in people with high levels of alexithymia. These areas are important for emotion perception and emotional experience. Smaller volumes in these areas might lead to deficiencies in appropriately identifying and expressing emotions. These findings provide the first quantitative integration of results pertaining to the structural neuroanatomical basis of alexithymia.
Robust ANCOVA, Curvature, and the Curse of Dimensionality

There is a substantial collection of robust analysis of covariance (ANCOVA) methods that effectively deals with non-normality, unequal population slope parameters, outliers, and heteroscedasticity. Some are based on the usual linear model and others are based on smoothers (nonparametric regression estimators). However, extant results are limited to one or two covariates. A minor goal here is to extend a recently-proposed method, based on the usual linear model, to situations where there are up to six covariates. The usual linear model might provide a poor approximation of the true regression surface. The main goal is to suggest a method, based on a robust smoother, for dealing with curvature when there are three or four covariates. The results include perspectives on the curse of dimensionality. Perspectives on the use of a linear model versus a smoother are given.
Infrared Studies of Aragonite, Calcite, and Vaterite Type Structures in the Borates, Carbonates, and Nitrates

Infrared absorption spectra have been obtained on the alkali nitrates, the divalent metal carbonates, and the rare earth borates which assume the aragonite, calcite, or vaterite crystal structures. It was observed that similar structures give rise to analogous spectra except for the carbonate and borates having the vaterite structure. The marked differences observed in these latter spectra are discussed. Frequency shifts produced by cation substitution are ascribed to repulsion between closed electron shells of oxygen atoms. It is concluded that this repulsive force determines the structure type in the rare earth borates.
Effect of Website Characteristics on Consumer Behavior : A Multilevel Analysis

This paper uses a hierarchical linear modeling approach to examine factors that affect Website effectiveness from a customer viewpoint. Use of hierarchical linear modeling allows analysis of multilevel and cross-level interactions that have not been explicitly considered in previous research. Our preliminary analysis of online Web survey data suggests that the relative importance of different Website features may vary depending on the domain in which Websites are nested.
A Hybrid Dead Reckon System Based on 3-Dimensional Dynamic Time Warping

In recent years, using smartphones for indoor positioning has become increasingly popular with consumers. This paper presents an integrated localization technique for inertial and magnetic field sensors to challenge indoor positioning without Wi-Fi signals. For dead-reckoning (DR), attitude angle estimation, step length calculation, and step counting estimation are introduced. Dynamic time warping (DTW) usually calculates the distance between the measured magnetic field and magnetic fingerprint in the database. For DR/Magnetic matching (MM), we creatively propose 3-dimensional dynamic time warping (3DDTW) to calculate the distance. Unlike traditional DTW, 3DDTW extends the original one-dimensional signal to a two-dimensional signal. Finally, the weighted least squares further improves indoor positioning accuracy. In the three different experimental scenarios—teaching building, study room, office building—DR/MM hybrid positioning accuracy is about 3.34 m.
Effects of Managing Element Interactivity on Student Achievement and their Academic Self-Concept in Science

Element interactivity, an essential feature underpinning cognitive load theory, has been identified as a major construct for explaining complexity in learning materials, but is not commonly used by teachers. The main aim of this study was to present some preliminary intervention effects following an in-service workshop that enabled teachers to apply an instructional strategy to manage element interactivity. Results showed that Year 7 students (N=156) benefitted from instruction that reduced element interactivity, not only in terms of their achievement, but also in their self-concept. Teachers who understand and are able to use element interactivity to manage instruction will be more effective in designing instruction that benefits their students, thus progressing teacher education to a new level.
Asset freezing, corporate political resources and the Tullock paradox

In 1967, Gordon Tullock asked why firms do not spend more on campaign contributions, despite the large rents that could be generated from political activities. We suggest in this paper that part of the puzzle could come from the fact that one important type of political activity has been neglected by the literature which focuses on campaign contributions or political connections. We call this neglected activity “asset freezing”: situations in which firms delay lay-offs or invest in specific technologies to support local politicians’ re-election objectives. In doing so, firms bear a potentially significant cost as they do not use a portion of their economic assets in the most efficient or productive way. The purpose of this paper is to provide a first theoretical exploration of this phenomenon. Building on the literature on corporate political resources, we argue that a firm's economic assets can be evaluated based on their degree of “political freezability,” which depends on the flexibility of their use and on their value for policy-makers. We then develop a simple model in which financial contributions and freezing assets are alternative options for a firm willing to lawfully influence public policy-making, and derive some of our initial hypotheses more formally.
A First Investigation of Congestion Control for LTE-V2X Mode 4

3GPP LTE-V2X is a recent new cellular technology allowing direct communications between vehicles and any other stations. Its Sidelink mode 4 allows the scheduler to be fully distributed and not requiring any support from cellular infrastructures, thus making this mode well fitted for V2X safety-related communications. Based on a Listen-before-Talk (LBT) strategy, the scheduler, however, remains subject to performance degradation under increased channel load, and thus requires wireless congestion control mechanisms. In this work, we focus on the interactions between the strategies used by the LTE-V2X Sidelink mode 4 for autonomous resource allocations - LBT and Semi-persistent scheduling (SPS) - and decentralized congestion control (DCC) mechanisms. Simulations under various scenarios showed counter-productive interactions leading to performance degradations, and strategies to mitigate them are suggested.
POLITECNICO DI TORINO Repository ISTITUZIONALE A Framework for Decision Fusion in Image Forensics Based on Dempster

In this work we present a decision fusion strategy for image forensics. We define a framework that exploits information provided by available forensic tools to yield a global judgment about the authenticity of an image. Sources of information are modeled and fused using Dempster-Shafer Theory of Evidence, since this theory allows to handle uncertain answers from tools and lack of knowledge about prior probabilities better than the classical Bayesian approach. The proposed framework permits to exploit any available information about tools reliability and about the compatibility between the traces the forensic tools look for. The framework is easily extendable: new tools can be added incrementally with a little effort. Comparison with logical disjunctionand SVMbased fusion approaches shows an improvement in classification accuracy, particularly when strong generalization capabilities are needed.
Short‐term response of Dicamptodon tenebrosus larvae to timber management in southwestern Oregon

In the Pacific Northwest, previous studies have found a negative effect of timber management on the abundance of stream amphibians, but results have been variable and region specific. These studies have generally used survey methods that did not account for differences in capture probability and focused on stands that were harvested under older management practices. We examined the influences of contemporary forest practices on larval Dicamptodon tenebrosus as part of the Hinkle Creek paired watershed study. We used a mark–recapture analysis to estimate D. tenebrosus density at 100 1-m sites spread throughout the basin and used extended linear models that accounted for correlation resulting from the repeated surveys at sites across years. Density was associated with substrate, but we found no evidence of an effect of harvest. While holding other factors constant, the model-averaged estimates indicated; 1) each 10% increase in small cobble or larger substrate increased median density of D. tenebrosus 1.05 times, 2) each 100-ha increase in the upstream area drained decreased median density of D. tenebrosus 0.96 times, and 3) increasing the fish density in the 40 m around a site by 0.01 increased median salamander density 1.01 times. Although this study took place in a single basin, it suggests that timber management in similar third-order basins of the southwestern Oregon Cascade foothills is unlikely to have short-term effects of D. tenebrosus larvae. © 2011 The Wildlife Society.
An Incremental Local Outlier Detection Method in the Data Stream

Outlier detection has attracted a wide range of attention for its broad applications, such as fault diagnosis and intrusion detection, among which the outlier analysis in data streams with high uncertainty and infinity is more challenging. Recent major work of outlier detection has focused on principle research of the local outlier factor, and there are few studies on incremental updating strategies, which are vital to outlier detection in data streams. In this paper, a novel incremental local outlier detection approach is introduced to dynamically evaluate the local outlier in the data stream. An extended local neighborhood consisting of k nearest neighbors, reverse nearest neighbors and shared nearest neighbors is estimated for each data. The theoretical evidence of algorithm complexity for the insertion of new data and deletion of old data in the composite neighborhood shows that the amount of affected data in the incremental calculation is finite. Finally, experiments performed on both synthetic and real datasets verify its scalability and outlier detection accuracy. All results show that the proposed approach has comparable performance with state-of-the-art k nearest neighbor-based methods.
An Approach for Energy Efficient Deadline-Constrained Flow Scheduling and Routing

With the development and extensive use of the network, its huge energy consumption has attracted more and more attentions. We mainly focus on the network-level energy-saving through the means of flow scheduling and routing, where flow means a certain amount of data that has to be transmitted from a specified source to a specified destination with hard deadline-constraint. We discuss the deadline-constrained flow scheduling and routing problem. Then we propose our EEDFSR method to reduce the active power consumption based on the SDN architecture. The proposed method can be used in both DCN and general topologies. The simulation result has shown that our EEDFSR has ascendancies in reducing the active power consumption of networks which have adequate connections.
Developing Tools for Arabic Corpus for Researchers

This paper presents an ongoing research that aims to construct a sizable and reliable text corpus along with a set of tools to experiment with natural language applications for Arabic. The corpus is used by graduate students at the University of Jordan (UJ) to conduct experiments on many useful applications. Earlier, we were not able to verify these experiments because of the lack of reliable data. We are working on annotating and tagging the corpus texts and making it available for researchers in XML format.
First of all , I wish to thank my supervisors

The Gibbard-Satterthwaite Theorem states that any non-dictatorial and surjective social choice function is susceptible to manipulation if there are at least three alternatives. This classical result assumes that manipulators are naive: they think that every other voter will cast a sincere ballot. Furthermore, it is assumed that voters have full information regarding the preferences of other voters. These assumptions make it unrealistically easy to manipulate an election. We argue that voters are likely to realise that other voters may act strategically too, and choose the best strategy accordingly. This thesis investigates the strategic incentives of higher-order reasoning voters, that is, voters who reflect on the uncertainty about the uncertainty of other voters, and so on. We develop a dynamic epistemic model for strategic voting and use this model to analyse strategic behaviour of higher-order reasoning voters. In the traditional ‘one-shot’ voting setting, voters use their cognitive capacities to predict the votes of fellow voters, in order to determine their own optimal (sincere or insincere) ballot. We show that in general, sophisticated agents who apply higher-order reasoning will not refrain from manipulation. We also consider higher-order reasoning in iterative voting procedures. We investigate whether voters that are able to predict (possibly harmful) future manipulations by fellow voters will avoid a strategic vote. For positional scoring rules and Condorcet extensions, we prove that this is not the case. Finally, we investigate how strategic incentives are affected if we allow voters to communicate with each other. It is shown that in many cases, voters cannot improve the outcome of the election by sharing personal information with their peers.
The janus triad: exploiting parallelism through dynamic binary modification

We present a unified approach for exploiting thread-level, data-level, and memory-level parallelism through a same-ISA dynamic binary modifier guided by static binary analysis. A static binary analyser first examines an executable and determines the operations required to extract parallelism at runtime, encoding them as a series of rewrite rules that a dynamic binary modifier uses to perform binary transformation. We demonstrate this framework by exploiting three different kinds of parallelism to perform automatic vectorisation, software prefetching, and automatic parallelisation together on legacy application binaries. Software prefetch insertion alone achieves an average speedup of 1.2x, comparing favourably with an automatic compiler pass. Automatic vectorisation brings speedups of 2.7x on the TSVC benchmarks, significantly beating a compiler approach for some workloads. Finally, combining prefetching, vectorisation, and parallelisation realises a speedup of 3.8x on a representative application loop.
6353 Gender , Access to Finance , Occupational Choice , and Business Performance

We present a theoretical and empirical analysis of the links between the gender of an entrepreneur, access to finance, occupational choice, and business performance. Our theoretical model predicts that, when lenders discriminate against women entrepreneurs, the average entrepreneurial skill of women who become entrepreneurs or enter paid employment as managers is higher than that of their men counterparts. This suggests that the firms owned or managed by women should perform better than the firms owned or managed by men, ceteris paribus. We find empirical support for the assumptions and the predictions of our model using firm-level data for 28 emerging economies in Europe and Asia; the effect is especially strong in the small and medium enterprises, possibly, because in large firms borrowing is a less essential source of finance. An important policy implication of our findings is that discrimination in the capital market spills over to the labour market, leading to the distortion of occupational choice and inefficiency in allocation of physical and human resources. JEL-Codes: J240, J710.
All's Well That Ends Well? On the Importance of How Returns Are Achieved

We demonstrate that investor satisfaction and investment behavior are influenced substantially by the price path by which the final investor return is achieved. In a series of experiments, we analyze various different price paths. Investors are most satisfied if their assets first fall in value and then recover, and they are least satisfied with the opposite pattern, independent of whether the final return is positive or negative. Price paths systematically influence risk preferences, return beliefs, and ultimately trading decisions. Our results enable a much more holistic perspective on a wide range of topics in finance, such as the disposition effect, risk-taking behavior after previous gains and losses, and behavioral asset pricing.
Swedish tribalism and Tanzanian entrepreneurship: preconditions for trust formation

This paper sets out to explore the preconditions for trust formation using a comparative approach. It takes an empirical point of departure, in two longitudinal and ethnographically inspired studies in the differing contexts of Sweden and Tanzania. The comparison reveals many similarities between the contexts with regard to the influence of informal institutions, as well as the significance of categories in trust formation. Perhaps surprisingly, trust and co-operation are not as low as could be expected in Tanzania, given the inadequate formal institutional environment, but instead, the greater need for co-operation evoked entrepreneurial initiatives that enabled the creation of trust. While the Swedish small-business owners could afford their ‘tribalism’, Tanzanians created trust in an entrepreneurial way. The importance of interventions to understand the local institutional framework is highlighted and it is argued that arranging business training, or similar events, is a fruitful way to facilitate the trust creation process in development contexts.