Miracle-dz/UniFAR-FTUs huggingface dataset:
MAXSM: A Multi-Heuristic Approach to XML Schema Matching

Transformation of business messages from one trading partner’s definition to another, or from one business message type to another is a common requirement for enterprise data integration applications. Transforming these business messages entails resolving issues of structural and semantic heterogeneity between their schemas. In this paper, we propose an automatic schema matching approach called MAXSM, designed specifically for matching schemas in the context of enterprise data integration. MAXSM is a multi-heuristic schema matcher which employs, amongst other heuristics, a novel heuristic using WordNet for determining natural-language semantic similarity between schemas. MAXSM also introduces “transitive mappings” that can be discovered from known mappings and used to seed production of candidate mappings. We present a cogent tree spanning approach to search two schemas more eectively for node-level match candidates.
Partitionfinder: combined selection of partitioning schemes and substitution models for phylogenetic analyses.

In phylogenetic analyses of molecular sequence data, partitioning involves estimating independent models of molecular evolution for different sets of sites in a sequence alignment. Choosing an appropriate partitioning scheme is an important step in most analyses because it can affect the accuracy of phylogenetic reconstruction. Despite this, partitioning schemes are often chosen without explicit statistical justification. Here, we describe two new objective methods for the combined selection of best-fit partitioning schemes and nucleotide substitution models. These methods allow millions of partitioning schemes to be compared in realistic time frames and so permit the objective selection of partitioning schemes even for large multilocus DNA data sets. We demonstrate that these methods significantly outperform previous approaches, including both the ad hoc selection of partitioning schemes (e.g., partitioning by gene or codon position) and a recently proposed hierarchical clustering method. We have implemented these methods in an open-source program, PartitionFinder. This program allows users to select partitioning schemes and substitution models using a range of information-theoretic metrics (e.g., the Bayesian information criterion, akaike information criterion [AIC], and corrected AIC). We hope that PartitionFinder will encourage the objective selection of partitioning schemes and thus lead to improvements in phylogenetic analyses. PartitionFinder is written in Python and runs under Mac OSX 10.4 and above. The program, source code, and a detailed manual are freely available from www.robertlanfear. com/partitionfinder.
Automatic Generation of Object-Oriented Type Checkers

—Type systems are aimed at preventing programming language constructions from having wrong behavior at runtime. Different formalisms are used to guarantee that a type system is well defined. However, the type systems implemented in commercial language processors (type checkers) do not commonly use tools that translate these formalisms into code. We propose a framework to facilitate the implementation of object-oriented type checkers, following widespread design patterns. A tool generates the specific implementation of a type checker, receiving a specification of the type system as its input. The generated code interacts with an API, accessible from the rest of the language processor implementation.
Parkinson's Disease: Low-Dose Haloperidol Increases Dopamine Receptor Sensitivity and Clinical Response

Background. It is known that ultra-low doses of haloperidol can cause dopamine supersensitivity of dopamine D2 receptors and related behaviour in animals. Objective. The objective was to determine whether a daily ultra-low dose of 40 micrograms of haloperidol could enhance the clinical action of levodopa in Parkinson's disease patients. Method. While continuing their daily treatment with levodopa, 16 patients with Parkinson's disease were followed weekly for six weeks. They received an add-on daily dose of 40 micrograms of haloperidol for the first two weeks only. The SPES/SCOPA scale (short scale for assessment of motor impairments and disabilities in Parkinson's disease) was administered before treatment and weekly throughout the trial. Results. The results showed a mean decrease in SPES/SCOPA scores after one week of the add-on treatment. Conclusion. SCOPA scores decreased after the addition of low-dose haloperidol to the standard daily levodopa dose. This finding is consistent with an increase in sensitivity of dopamine D2 receptors induced by haloperidol. Such treatment for Parkinson's disease may possibly permit the levodopa dose to be reduced and, thus, delay the onset of levodopa side effects.
Investigating the limits of how expectation can shape affective judgement

12 DECLARATION . 13 COPYRIGHT STATEMENT . 13 ACKNOWLEDGEMENTS . 14 1 GENERAL INTRODUCTION . 15 1.1 Preface . 15 1.2 Assimilation-Contrast Theory. 19 1.2.1 Defining assimilation and contrast effects . 19 1.2.2 Investigating the time course of assimilation effects . 20 1.2.3 Establishing the need to determine the boundaries of assimilation effects . 22 1.3 Predictive coding and the prediction error hypothesis . 24 1.3. 1 Predictive coding of liking . 24 1.3. 2 Predictive coding as Bayesian inference . 26 1.3. 3 Prediction errors – A neurological marker of expectation? 27 1.4 Promoting affective expectations . 29 1.4. 1 Affective priming . 29 1.4. 2 Priming affective values and measuring changes in stimulus liking . 30 1.5 The aims of the current investigation . 31 2 GENERAL METHODS . 32 2.1 Participants . 32 2.2 Questionnaire measures . 32 2.2.1 The LOT-R . 33 2.3 Experimental behavioural paradigms . 33 2.4 Implicit attitude measures . 34 2.4. 1 The IAT . 34 2.4. 2 The GNAT. 36 2.5 The Psychometric Function . 38 2.6 Statistical analysis . 40
Diffusion-KLMS Algorithm and its Performance Analysis for Non-Linear Distributed Networks

In a distributed network environment, the diffusion-least mean squares (LMS) algorithm gives faster convergence than the original LMS algorithm. It has also been observed that, the diffusion-LMS generally outperforms other distributed LMS algorithms like spatial LMS and incremental LMS. However, both the original LMS and diffusion-LMS are not applicable in non-linear environments where data may not be linearly separable. A variant of LMS called kernel-LMS (KLMS) has been proposed in the literature for such non-linearities. In this paper, we propose kernelised version of diffusion-LMS for non-linear distributed environments. Simulations show that the proposed approach has superior convergence as compared to algorithms of the same genre. We also introduce a technique to predict the transient and steady-state behaviour of the proposed algorithm. The techniques proposed in this work (or algorithms of same genre) can be easily extended to distributed parameter estimation applications like cooperative spectrum sensing and massive multiple input multiple output (MIMO) receiver design which are potential components for 5G communication systems.
DeDe: design and evaluation of a context-enhanced mobile messaging system

This paper presents the design, implementation and validation of an enhanced mobile phone messaging system (DeDe), allowing the sender to define the context in which the message will be delivered to the recipient. A field trial among a socially tight group of teenagers showed that the DeDe feature was incorporated as part of the participants' existing messaging culture. 11,4% of their total messaging output made use of the DeDe feature. The most frequently used context parameters were location (based on network cell-ID) and time. Novel message practices emerged, as compared to 'normal' messaging, both in terms of timing of message sending, as well as creating content that specifically exploited the DeDe feature. Some use barriers were recognized, the most important being the sender's uncertainty of delivery success. Implications for design are discussed.
Exploring the Washback of the TOEIC in South Korea: A sociocultural perspective on student test activity

ii Acknowledgements . v List of Figures . xiii List of Tables . xiv CHAPTER ONE: INTRODUCTION . 1 1.0 Background and Rationale . 1 1.1 Specific Purpose and Significance . 3 1.2 Structure . 5 PART I: REVIEW OF LITERATURE CHAPTER TWO: SOUTH KOREA AND THE TOEIC . 9 2.0 Overview . 9 2.1 SOUTH KOREA. 9 2.1.1 A Brief Historical Overview . 9 2.1.2 The Korean Education System . 10 2.1. 3 EFL Education and Testing in Korea . 16 2.2 THE TOEIC . 18 2.2.1 Description . 19 2.2.2 An Evaluation of the TOEIC . 21 2.3 Chapter Summary . 32 CHAPTER THREE: WASHBACK . 33 3.0 Overview . 33 3.1 BACKGROUND . 33 3.1.1 Washback in Language Testing . 34 3.2 THE NATURE AND SCOPE OF WASHBACK . 37 3.2.1 Washback vs Impact . 37 3.2.2 Dimensions of Washback . 39 3.2.3 Situating Washback within Validity . 43 3.3 REVIEW OF EMPIRICAL STUDIES . 45 3.3.1 Washback across Different Areas of Learning . 47 3.3.2 Washback and Korean Learners . 56 3.3.3 Washback and the TOEIC . 59 3.3. 4 Summary of Empirical Studies . 61 3.3. 5 A Model of Washback on Learning . 63
Current developments in forensic interpretation of mixed DNA samples (Review)

A number of recent improvements have provided contemporary forensic investigations with a variety of tools to improve the analysis of mixed DNA samples in criminal investigations, producing notable improvements in the analysis of complex trace samples in cases of sexual assult and homicide. Mixed DNA contains DNA from two or more contributors, compounding DNA analysis by combining DNA from one or more major contributors with small amounts of DNA from potentially numerous minor contributors. These samples are characterized by a high probability of drop-out or drop-in combined with elevated stutter, significantly increasing analysis complexity. At some loci, minor contributor alleles may be completely obscured due to amplification bias or over-amplification, creating the illusion of additional contributors. Thus, estimating the number of contributors and separating contributor genotypes at a given locus is significantly more difficult in mixed DNA samples, requiring the application of specialized protocols that have only recently been widely commercialized and standardized. Over the last decade, the accuracy and repeatability of mixed DNA analyses available to conventional forensic laboratories has greatly advanced in terms of laboratory technology, mathematical models and biostatistical software, generating more accurate, rapid and readily available data for legal proceedings and criminal cases.
Prediction of the appearance of monkeys based on weather data and wireless sensing network

Recently agricultural damage caused by monkeys is a critical problem in Japan. We propose a system that predicts what date and time monkeys approach into farmland. In order to make predictions, we had monkeys wear collars with transmitters and collected the trend data of the distances of monkeys by the receivers in this system. The time of appearing monkeys, and the weather data are taken for the estimation. We adopted both of Bayesian estimation as a linear method and Support Vector Machine as a non-linear method. As a result, the Bayesian estimation had little effect, but the Support Vector Machine outperformed the Bayesian estimation, so the effectiveness of the predicting system of monkeys by the weather data was confirmed.
Thread Count Prediction Model: Dynamically Adjusting Threads for Heterogeneous Many-Core Systems

Determining an appropriate thread count for a multithread application running on a heterogeneous many-core system is crucial for improving computing performance and reducing energy consumption. This paper investigates the interrelation between thread count and computing performance of applications, and designs a prediction model of the optimum thread count on the basis of Amdahl's law combined with regression analysis theory to improve computing performance and reduce energy consumption. The prediction model can estimate the optimum tread count relying on the program running behaviors and the architecture characteristics of heterogeneous many-core system. Using the estimated optimum thread count, the number of the active hardware threads and processing cores on the many-core processor is dynamically adjusted in the process of thread mapping to improve the energy efficiency of entire heterogeneous many-core system. The experimental results show that, using this paper proposed thread count prediction model, on an average, the computing performance is improved by 48.6%, energy consumption is reduced by 59%, and additional overhead introduced is 2.03% compared with that of the traditional thread mapping for the PARSEC benchmark programs run on an Intel MIC heterogeneous many-core system.
7 Tesla fMRI Reveals Systematic Functional Organization for Binocular Disparity in Dorsal Visual Cortex

The binocular disparity between the views of the world registered by the left and right eyes provides a powerful signal about the depth structure of the environment. Despite increasing knowledge of the cortical areas that process disparity from animal models, comparatively little is known about the local architecture of stereoscopic processing in the human brain. Here, we take advantage of the high spatial specificity and image contrast offered by 7 tesla fMRI to test for systematic organization of disparity representations in the human brain. Participants viewed random dot stereogram stimuli depicting different depth positions while we recorded fMRI responses from dorsomedial visual cortex. We repeated measurements across three separate imaging sessions. Using a series of computational modeling approaches, we report three main advances in understanding disparity organization in the human brain. First, we show that disparity preferences are clustered and that this organization persists across imaging sessions, particularly in area V3A. Second, we observe differences between the local distribution of voxel responses in early and dorsomedial visual areas, suggesting different cortical organization. Third, using modeling of voxel responses, we show that higher dorsal areas (V3A, V3B/KO) have properties that are characteristic of human depth judgments: a simple model that uses tuning parameters estimated from fMRI data captures known variations in human psychophysical performance. Together, these findings indicate that human dorsal visual cortex contains selective cortical structures for disparity that may support the neural computations that underlie depth perception.
pPen: enabling authenticated pen and touch interaction on tabletop surfaces

This paper introduced pPen, a pressure-sensitive digital pen enabled precise pressure and touch input on vision based interactive tabletops. With the help of pPen inputs and feature matching technology, we implemented a novel method supporting multi-user authenticated interaction in the bimanual pen and touch scenario: login can be performed just by stroking one's signature with pPen on the table; a binding between user and pPen was created at the same time, then each interaction command made by pPen is user differentiating. We also conducted laboratory user studies, which later proved the safety and the high resistance to shoulder surfing problem: in the evaluation procedure, any attacker can never log into other user's working space.
Study and analysis on the control of SCIG and its responses to grid voltage unbalance

This paper describes the control of squirrel cage induction generator (SCIG) and its responses to grid voltage unbalance. The paper presents the vector control of SCIG. On the SCIG side converter, the control strategy enables the independent control of flux and electromagnetic torque. On the grid side converter, the control strategy is implemented to regulate the DC voltage and the reactive power from the grid. In order to study the effect of a grid voltage dip on SCIG, the effect of grid voltage drops are simulated with MATLAB/Simulink.
Linguistic interdependence between Spanish language and English language and reading: A longitudinal exploration from second through fifth grade

ABSTRACT This study explored effects of Spanish oral language skills (vocabulary and syntax) on the development of English oral language skills (vocabulary, morphology, semantics, syntax) and reading comprehension among 156 bilingual Latino children in second through fifth grade whose first language was Spanish and whose second language was English. Using a cohort-sequential design (Cohort 1: second–third grade; Cohort 2: third–fourth grade; Cohort 3: fourth–fifth grade), we estimated Grade 2–5 trajectories of English oral language skills and reading comprehension. We assessed whether early levels of Spanish vocabulary and syntax predicted: (a) students’ fifth-grade English oral language skills and reading comprehension; and (b) students’ Grade 2–5 growth in these skills. Results showed that Spanish syntax predicted all Grade 5 English oral language skills and reading comprehension. Spanish syntax was also positively related to growth in English semantic knowledge. Spanish vocabulary was not associated with any English oral language skills or reading outcomes. Theoretically, results suggest that explorations of “transfer” from Spanish to English are likely moderated by the constructs under study and the means by which they are operationalized. Instructionally, working with bilingual learners around issues related to Spanish and English syntax has implications for bilingually and metalinguistically oriented teaching approaches that may build linguistic knowledge and promote reading comprehension.
Rox, a novel bHLHZip protein expressed in quiescent cells that heterodimerizes with Max, binds a non‐canonical E box and acts as a transcriptional repressor

Proteins of the Myc and Mad family are involved in transcriptional regulation and mediate cell differentiation and proliferation. These molecules share a basic‐helix–loop–helix leucine zipper domain (bHLHZip) and bind DNA at the E box (CANNTG) consensus by forming heterodimers with Max. We report the isolation, characterization and mapping of a human gene and its mouse homolog encoding a new member of this family of proteins, named Rox. Through interaction mating and immunoprecipitation techniques, we demonstrate that Rox heterodimerizes with Max and weakly homodimerizes. Interestingly, bandshift assays demonstrate that the Rox–Max heterodimer shows a novel DNA binding specificity, having a higher affinity for the CACGCG site compared with the canonical E box CACGTG site. Transcriptional studies indicate that Rox represses transcription in both human HEK293 cells and yeast. We demonstrate that repression in yeast is through interaction between the N–terminus of the protein and the Sin3 co‐repressor, as previously shown for the other Mad family members. ROX is highly expressed in quiescent fibroblasts and expression markedly decreases when cells enter the cell cycle. Moreover, ROX expression appears to be induced in U937 myeloid leukemia cells stimulated to differentiate with 12‐O‐tetradecanoylphorbol‐13‐acetate. The identification of a novel Max‐interacting protein adds an important piece to the puzzle of Myc/Max/Mad coordinated action and function in normal and pathological situations. Furthermore, mapping of the human gene to chromosome 17p13.3 in a region that frequently undergoes loss of heterozygosity in a number of malignancies, together with the biochemical and expression features, suggest involvement of ROX in human neoplasia.
Quantitative Genetics Meets Integral Projection Models: Unification of Widely Used Methods from Ecology and Evolution

Micro-evolutionary predictions are complicated by ecological feedbacks like density dependence, while ecological predictions can be complicated by evolutionary change. A widely used approach in micro-evolution, quantitative genetics, struggles to incorporate ecological processes into predictive models, while structured population modelling, a tool widely used in ecology, rarely incorporates evolution explicitly. In this paper we develop a flexible, general framework that links quantitative genetics and structured population models. We use the quantitative genetic approach to write down the phenotype as an additive map. We then construct integral projection models for each component of the phenotype. The dynamics of the distribution of the phenotype are generated by combining distributions of each of its components. Population projection models can be formulated on per generation or on shorter time steps. We introduce the framework before developing example models with parameters chosen to exhibit specific dynamics. These models reveal (i) how evolution of a phenotype can cause populations to move from one dynamical regime to another (e.g. from stationarity to cycles), (ii) how additive genetic variances and covariances (the G matrix) are expected to evolve over multiple generations, (iii) how changing heritability with age can maintain additive genetic variation in the face of selection and (iii) life history, population dynamics, phenotypic characters and parameters in ecological models will change as adaptation occurs. Our approach unifies population ecology and evolutionary biology providing a framework allowing a very wide range of questions to be addressed. The next step is to apply the approach to a variety of laboratory and field systems. Once this is done we will have a much deeper understanding of eco-evolutionary dynamics and feedbacks.
San Francisco State University at LiveQA Track of TREC 2016

There are many situations in our everyday life where we look for answers to some questions “Who wrote this book? ”, “How to grill a fish? ” or “Where is the Opera House located? ”. Twenty years ago to answer these questions people were looking them up in the encyclopedias, recipe books or were asking other people. Moving the information into the electronic form and making it universally accessible helped to automate this process and save an enormous amount of time.
Peer2Schedule - an experimental peer-to-peer application to support present collaboration

This paper describes experiences from implementing an experimental mobile peer-to-peer application called Peer2Schedule aimed at improving and supporting collaboration where people are collocated. Peer2Schedule was built on top of the Peer2Me framework that provides management of mobile ad hoc networks over Bluetooth. The goal of the Peer2Schedule project can be divided into three main areas. 1) To develop a collaborative peer-to-peer application to evaluate the usefulness of such applications; 2) to evaluate the technical limitations of J2ME and Bluetooth in this domain; and 3) to implement and evaluate a mobile application to improve present ad-hoc collaboration. In this paper we also investigates the social and network issues related to such applications. Our findings indicates that Bluetooth and J2ME are useful technology to implement such applications, but the long time to establish connections and security issues in Bluetooth reduce the usability of such applications. In addition, it is essential that collaborative peer-to-peer applications must be developed as open source projects, to allow the users of such applications to evaluate the source code to assess how the application handles privacy. Finally, the paper elaborates on how the problem domain affects how the control-flow is managed in peer-to-peer applications.