Miracle-dz/UniFAR-FTUs huggingface dataset:
Measuring the Impact of Exchange Rate Movements on Domestic Prices: A Cointegrated VAR Analysis

This paper measures the pass-through of exchange rate changes into domestic inflation within a cointegrated VAR (CVAR) framework. This issue is of particular interest for the euro area (EA) as Member Sates cede their national currencies and no longer have options of using monetary policy to respond to local conditions. In fact, a common exchange rate shock, in the absence of a national monetary policy, may have differential impact on EA countries, leading notably to possible divergence in inflation levels. Using quarterly data for 12 EA covering 1980:1 to 2010:4, we report a large degree of heterogeneity in the rates of pass-through across our sample, especially, between "peripheral" and "core" EA economies. For instance, prices rise by 84% in Portugal following one percent depreciation of exchange rate, while for the German economy the extent of pass-through is not exceeding 0.20%. This outcome would have important implications for the general risk perceived by foreign firms and investors regarding the inflationary environment within each EA country.
Field Efficacy Comparison of In Ovo and Conventional Marek ’ s Disease Vaccine Administration

By mid-August 1995, 55% of broiler embryos in North America were vaccinated for Marek’s disease using the INOVOJECT system, with 201 INOVOJECT machines placed with 16 of the top 25 poultry producers, providing the industry with the capacity to inject in excess of 400 million eggs per month or about 5 billion eggs per annum. In ovo administration of a bursal disease antibody-infectious bursal disease virus (BDA-IBDV) complexed vaccine to specificpathogen-free (SPF) embryos was safer and more potent than conventional IBDV vaccine alone because it delayed the appearance of bursal lesions, produced no early mortality, produced higher geometric mean antibody titers against IBDV, and generated protective immunity against challenge. In ovo administration of a BDA-IBDV complexed vaccine to broiler embryos generated antibody titers against IBDV sooner than conventional virus vaccinates, and generated protective immunity against challenge. Direct DNA injection of plasmid DNA encoding b-galactosidase into breast muscle in ovo and posthatch was an effective means to achieve both gene transfer and expression, with potential for the development of gene vaccines using plasmids encoding protective antigens from poultry pathogens. In ovo administration of 800 U chicken myelomonocytic growth factor (cMGF), a chicken hematopoietic cytokine for cells of the monocytic-granulocytic lineages, significantly reduced mortality associated with Escherichia coli exposure within the hatcher when compared to PBS controls (6.1 vs 12.4, P ≤ 0.05), but not when compared to a yeast expression control. A procedure was developed enabling injection prior to the onset of incubation without compromising embryo viability. This in ovo injection process has opened up the window of embryo development during incubation for intervention, as illustrated by the 100% male phenotype produced in chicks hatching from eggs injected with aromatase inhibitor prior to incubation. These data illustrate some of the in ovo applications presently in use by the poultry industry, and under development or in research at
Outlier Identification using Symmetric Neighborhood

In recent research outlier mining is used in wide areas such as telecommunication, health care, finance and network intrusion detection. Applying outlier mining in network anomaly detection, rare occurring attacks can be identified. In this paper we propose an outlier mining algorithm based on symmetric neighborhood relationships. We evaluate the method with UCI ML Repository datasets, benchmark dataset KDD Cup 1999 and real time intrusion datasets. The experimental results are compared with existing approaches and performances are excellent.
Statistical Relational Learning for Game Theory

In this paper, we motivate the use of models and algorithms from the area of Statistical Relational Learning (SRL) as a framework for the description and the analysis of games. SRL combines the powerful formalism of first-order logic with the capability of probabilistic graphical models in handling uncertainty in data and representing dependencies between random variables: for this reason, SRL models can be effectively used to represent several categories of games, including games with partial information, graphical games and stochastic games. Inference algorithms can be used to approach the opponent modeling problem, as well as to find Nash equilibria or Pareto optimal solutions. Structure learning algorithms can be applied, in order to automatically extract probabilistic logic clauses describing the strategies of an opponent with a high-level, human-interpretable formalism. Experiments conducted using Markov logic networks, one of the most used SRL frameworks, show the potential of the approach.
Understanding the Role of Internship as an Activity Based Learning: A Case Study

Activity based learning is a successful educational model in various disciplines and recently it has been proved very effective in business institutes also. This paper was intended to explore the effects of internship in the university students of Pakistan as an activity based learning in order to boost their skills and abilities. Qualitative research as research design was adopted for the study following interpretivist paradigm. For the purpose of data collection, 30 students from business institutes were interviewed. Only those candidates were chosen who had recently completed their internship in well-known organizations of Pakistan. Data analyses were done through NVivo software version 11, suggested for qualitative data analyses. Findings proposed that industrial internship is a viable activity for the learning and growth of university students. Practical experience, teamwork, understanding strengths and weaknesses, financial support for further studies and exposure to real world problems were found chief outcomes of internship in terms of professional development. Likewise, goal setting, internal motivation, confidence, punctuality, regularity and understanding responsibility in terms of personality development were found as key outcomes of internship for business students. Keywords: activity based learning, business students, internships, professional development.
Detection of Syntactic Aspect Interaction in UML State Diagrams Using Critical Pair Analysis in Graph Transformation

Aspect Oriented Modeling separates crosscutting concerns by defining Aspects and composition mechanisms at the model level. Composition of multiple Aspects will most likely result in more than one Aspect matching the same join points. Consequently, Aspects do not always interact in a predictable manner when woven together. Intended interaction among aspects is designed by the system designer. Unintended interaction (or interference) must be automatically managed. When the woven aspect demonstrates a behavior that is different than its autonomous behavior, then this is a potential interference. Interference has been recently reported in Aspect Oriented Software Development (AOSD) by the industry. Leaving this problem unsolved may result in erratic software behavior and will hinder the adaptation of AOSD by the industry. This identified problem is similar to a phenomenon that exists in graph transformation systems where multiple Graph Transformation rules share some conflicting elements, it is referred to as Critical Pair Analysis and it provides an algebraic-based mechanism to detect and analyze the interaction of the rules. In this paper we propose a framework to detect unintended Aspect interaction at the model level. The proposed framework transforms Aspects modeled in UML State Diagram to Graph Transformation Rules, and then it applies Critical Pair Analysis to detect unintended interactions among aspects. This will enable developers to specify only the order of precedence for intended interaction among aspects without the need to manually investigate unintended interactions for the combinations of every Aspect to every other Aspect in the system. The proposed interaction detection solution is automated, modular, and independent of the base model; which adds the advantage of not having to re-evaluate the interaction each time the base model changes.
Computational Pragmatics in HCI: Using Dialog Context in a MultiModal Interface*

This report describes a prototype built to explore the use of context representation in a multi-modal interface. The report focuses on the definition of new graphical interaction techniques that make use of context information for context-based interaction. This report describes the motivations for such techniques, it presents some sample techniques and their natural language equivalents. The report finally describes a prototype that has been built to explore some of these issues.
Perceptually motivated spatial and temporal integration of pixel based video quality measures

In the evaluation of video quality often a full reference approach is used, thus calculating some measure of difference between the reference frames and the distorted frames. Often this measure returns one value per pixel, in the simplest case the squared difference. Conventionally, this pixel based measure is averaged over space and time. This paper introduces a psychophysically derived algorithm for this step. It uses the distribution of the cells in the fovea and the assumption that in a subjective test the part with the highest distortion is most important. Additionally, a temporal integration step is proposed which models the recency and forgiveness effect. Different video quality measures are enhanced with these two steps and their performance is evaluated using the results of a subjective test.
Epistasis and the Structure of Fitness Landscapes: Are Experimental Fitness Landscapes Compatible with Fisher’s Geometric Model?

The fitness landscape defines the relationship between genotypes and fitness in a given environment and underlies fundamental quantities such as the distribution of selection coefficient and the magnitude and type of epistasis. A better understanding of variation in landscape structure across species and environments is thus necessary to understand and predict how populations will adapt. An increasing number of experiments investigate the properties of fitness landscapes by identifying mutations, constructing genotypes with combinations of these mutations, and measuring the fitness of these genotypes. Yet these empirical landscapes represent a very small sample of the vast space of all possible genotypes, and this sample is often biased by the protocol used to identify mutations. Here we develop a rigorous statistical framework based on Approximate Bayesian Computation to address these concerns and use this flexible framework to fit a broad class of phenotypic fitness models (including Fisher’s model) to 26 empirical landscapes representing nine diverse biological systems. Despite uncertainty owing to the small size of most published empirical landscapes, the inferred landscapes have similar structure in similar biological systems. Surprisingly, goodness-of-fit tests reveal that this class of phenotypic models, which has been successful so far in interpreting experimental data, is a plausible in only three of nine biological systems. More precisely, although Fisher’s model was able to explain several statistical properties of the landscapes—including the mean and SD of selection and epistasis coefficients—it was often unable to explain the full structure of fitness landscapes.
Per-pixel translational symmetry detection, optimization, and segmentation

We present a novel method for translational symmetry detection, optimization, and symmetry object segmentation in façade images. Unlike most previous methods, our detection algorithm accumulates pixel-level correspondence in translation space. Thus it does not rely on feature point detection and handles patterns with low repetition counts. To improve the robustness with multiple interfering symmetries, we introduce an image-space global optimization, which resolves multiple per-pixel symmetry lattices. We then propose a learning-based method that generates refined segmentation of foreground symmetry objects of arbitrary shapes, with the aid of the per-pixel symmetry information. Our proposed method is accurate, robust and efficient as demonstrated by an extensive evaluation using a large façade image database.
The Craft Attitude: Navigating Mess in Mixed Methods Research

Acknowledging and navigating “mess” are clear priorities in the mixed methods literature. Mess enters the mixed methods process in two interrelated ways. The first is empirically, where quantitative and qualitative findings diverge or contrast rather than cohere; the second is through design, where research contexts demand unplanned adaptation. This article outlines three practices that help mixed methods researchers recognize and navigate both kinds of mess, collectively called the “craft attitude. ” The craft attitude consists of comfort with uncertainty, a nonlinear/recursive approach to research, and understanding research as storytelling. I further argue these components can orient researchers to mess in both structured and flexible ways by fostering three intellectual activities: science, craft/art, and ethical value judgment. This article contributes to the field of mixed methods by offering a practice-oriented concept facilitating the collective acknowledgement and engagement of mess, rather than concealing it in our research.
Service-Oriented E-Learning Architecture Using Web Service-Based Intelligent Agents

There is no doubt that e-learning has found its way in our lives. From the very start to the Ph.D. level one can find e-learning courses every where and all the big names are supporting it. One thing that is needed to be understood is that e-learning is basically the integration of various technologies. Now this technology is maturing and we can find different standards for e-learning . New technologies such as agents and web services are promising better results. In this paper we have proposed an e-learning architecture that is dependent on multi-agent systems and web services. These communication technologies will make the architecture more robust, scalable and efficient.
Effect of Leukocyte-Rich and Platelet-Rich Plasma on Healing of a Horizontal Medial Meniscus Tear in a Rabbit Model

There are limited reports on the effect of platelet-rich plasma (PRP) on meniscus healing. The purpose of this study was to investigate the effect of leukocyte-rich PRP (L-PRP) on potential healing of the horizontal medial meniscus tears in a rabbit model. A horizontal medial meniscus tear was created in both knees of nine skeletally mature adult rabbits. Left or right knees were randomly assigned to a L-PRP group, or a control group. 0.5 mL of L-PRP from 10 mL of each rabbit's whole blood was prepared and injected into the horizontal tears in a L-PRP group. None was applied to the horizontal tears in a control group. The histological assessment of meniscus healing was performed at two, four, and six weeks after surgery. We found that there were no significant differences of quantitative histologic scoring between two groups at 2, 4, and 6 weeks after surgery (p > 0.05). This study failed to show the positive effect of single injection of L-PRP on enhancing healing of the horizontal medial meniscus tears in a rabbit model. Single injection of L-PRP into horizontal meniscus tears may not effectively enhance healing of horizontal medial meniscus tears.
Selection of data process outsourcing provider based on AHP

Based on the excess information, how to use data more deeply is a problem which faced by the enterprise. Enterprise can outsource their data to the data process outsourcing provider. Data process outsourcing is a time, effort and money-consuming activity. So how to select the reliable provider is the important problem. The selection model of data process outsourcing provider is structured based on AHP which based on mathematics and psychology. Three hierarchy is set up include the decision goal, the criteria for evaluating the alternatives and the last one is the alternatives for reaching the goal. From the AHP model, the different weight of the alternatives can be calculated. So the enterprise can make a right decision about how to select appropriate outsourcing providers according to the different weight of the alternatives. This method is applied into the selection of data process outsourcing provider, which provides a new method for selection.
Reassessing the View that American Schools are Broken

The author evaluates the popular belief that the U.S. public school system is flawed and can be corrected only through fundamental changes in the institutions governing education. He finds that the system is not inherently flawed, and may actually be reasonably effective. Based on these findings, he offers incremental proposals to improve U.S. schools.
One of the blokes: Brewsters, branding and gender (in)visibility in New Zealand’s craft beer industry

Beer drinking has long been valorised as a masculine performance and a social ritual. But as more women enter the craft beer industry, new opportunities emerge to reframe the cultural discourses around beer. With an interest in the stories women brewers (‘brewsters’) tell, we conducted interviews (n = 6), and a textual analysis of brand strategies (n = 10) used by women-owned beer brands in New Zealand. With an attention towards how gender identity factors into these narratives, we found that women largely reproduce the narrative trope of ‘authenticity’ utilised by craft brewers broadly. Gender identity is largely rendered invisible at the expense of promoting authenticity as a seemingly gender-neutral value. In New Zealand, however, these strategies must be contextualised in a cultural history in which beer drinking and national identity are fundamentally intertwined, and in ways that have has always been coded masculine. Our findings suggest that while branding can potentially enhance the visibility of women as legitimate producers of beer, New Zealand brewsters maintain craft beer as a Pākehā (White European) middle-class masculine cultural form.
Fonctionnements psychosocial et neuropsychologique associés à un épisode dépressif majeur dans le cadre d'un trouble de l'humeur sévère et complexe

This thesis investigated psychosocial and neurocognitive functioning associated with a major depressive episode in the case of severe and complex mood disorders. In the first study (Chapter II), the primary aim was to characterize the psychosocial and neurocognitive profiles of patients with major depressive disorder (MDD) and bipolar disorder (BD) during a depressive episode. The nature and extent of deficits were clarified, while profiles were compared according to the type of mood disorders. The results suggested a psychosocial and neurocognitive functioning similar among MDD and BD patients. A global psychosocial dysfunction was observed, characterized by occupational, relational and social impairments. Moreover, the neurocognitive profile was heterogeneous with regard to the nature and extent of cognitive deficits, predominated frequently by an attentional dysfunction. In the second study of this thesis (Chapter III), psychosocial and neurocognitive profiles of MDD and BD patients were documented during a major depressive episode through a 12-month follow-up. Better psychosocial and neurocognitive functioning were observed among MDD and BD patients as depressive severity decreased. Despite these mild improvements, results suggested that psychosocial and cognitive deficits persisted for most of patients at the 12-month follow-up. Overall, the present thesis made significant contributions to the understanding of psychosocial and neurocognitive functioning in MDD and BD patients during a major depressive episode. This thesis revealed: (a) A global psychosocial dysfunction, with occupational, relational and social impairments, during unipolar and bipolar depression, (b) an heterogeneity in cognitive profiles among depressed patients, with predominance to the dysfunction of basic cognitive processes, and (c) the important persistence of functional and cognitive deficits beyond one year of treatment. However, this thesis did not reveal difference in psychosocial and neurocognitive functioning among patients groups. Severe and complex MDD and BD seem to refer to a similar clinical reality, characterized by an alteration of daily functioning and attentional deficits.
Semantically aware time evolution tracking of communities in co-authorship networks

This is paper addresses the problem of tracking the time evolution of communities within co-authorship networks. We consider an evolutionary clustering approach which adapts the statistical framework of shrinkage estimation to obtain a smoothed version of the overall affinity matrix as the optimal weighted average between the matrices of past and current affinities. Moreover, the current affinity matrix at each time step is formed as the optimal mixing between the raw structural relationships between authors coupled with the semantic similarity of their published works, captured by performing LDA-based topic modeling on the corresponding corpora of abstracts. The proposed parametric weighting scheme is simultaneously optimized on a real co-authorship dataset emerging from the network of participants in the ICMB conferences, held from 2002 to 2013. Finally, community detection at each time step is conducted by employing spectral clustering on the estimated overall weight matrix. The obtained results justify that our approach provides a clearer revelation of the inherent authors' communities dynamics when compared against incremental cluster formations that rely exclusively on the structural information of the co-authorship network.
Reliability and validity of the Vulnerability Index-Service Prioritization Decision Assistance Tool (VI-SPDAT) in real-world implementation

ABSTRACT This study examined the reliability and validity of the Vulnerability Index-Service Prioritization Decision Assistance Tool (VI-SPDAT), a widely-used assessment of the health and social vulnerabilities and housing needs of individuals experiencing homelessness. Homeless Management Information System data were obtained for 1495 individuals who were administered the VI-SPDAT between 2014 and 2016. Subsamples were selected for reliability and validity assessments. Results suggest there are challenges to the reliability and validity of the VI-SPDAT in practical use. VI-SPDAT total scores did not significantly predict risk of return to homeless services, while type of housing was a significant predictor. Vulnerability assessment instruments have important implications for communities working to end homelessness by facilitating prioritization of scarce housing resources. Findings suggest that further testing and development of the VI-SPDAT is necessary.
Novel and Highly Efficient Reconfigurable Implementation of Data Mining Classification Tree

The available e-data throughout the Web are growing at such a high rate that data mining on the web is considered the biggest challenge of information technology. As a result it is crucial to find new and innovative ways for classifying and mining those huge amounts of data. In this paper we present an implementation of a state-of-the-art data mining algorithm on a modern FPGA. This is one of the first approaches utilizing the resources of an FPGA to accelerate certain very CPU intensive data-mining/data classification schemes and our real-world results from actual runs on hardware demonstrate that it is a highly promising one. In particular, our FPGA-based system achieves, depending on the data classified, a speedup from 4x and up to 50x (on average 25x) when compared with a state-of-the art multi-core CPU, including I/O overhead.