Miracle-dz/UniFAR-FTUs huggingface dataset:
Second Language Writing Development in English and in Spanish in a Two-way Immersion Programme

Whereas most research on child second language acquisition has focused on the oral production of children, studies are needed to illuminate patterns of literacy development in a second language. This paper aims to shed some light on this process, focusing on the English writing development of a native Spanish speaker, and on the Spanish writing development of a native English speaker, both enrolled in a two-way immersion program in the USA. Data for this particular study come from a longitudinal, national study, involving 484 students in 11 programs across the country. In this paper, we will present a case study of two students in the project, from the beginning of third grade through the end of fifth grade. The students' writing samples will be discussed using an analytic rubric developed for the project. This rubric addresses three major aspects of writing – composition, grammar and mechanics – and provides a clear framework for investigating changes in writing ability over time.
Psychometric properties and standardised data for questionnaires measuring negative affect, dispositional style and daily hassles. A nation‐wide sample

Within the behavioral field, self-report inventories measuring emotional condition from a state/trait perspective are in frequent use. Some of these measures have insufficient standardisation and/or are out of date. In order to upgrade some of the frequently used self-report inventories a nation-wide survey (N=2500) was performed. Measures of negative affect (state-anxiety STAI-S, trait-anger STAS-T), and depression (CES-D), dispositional style (LOT) and daily hassles (DH) were examined. Psychometric data and demographic differences for all the inventories used are presented. The reliability measures for the scales show high consistency, ranging from 0.76 to 0.95 (Cronbach’s alpha). The overall results indicate that females are more hassled, depressed, anxious, hostile, and have a more negative dispositional style than males. These results are most pronounced among younger females.
Guiones de acción de un profesor novel de ciencias a partir de la modelización de la enseñanza

En este trabajo se presentan dos guiones de acción de un profesor novel obtenidos al modelizar su enseñanza. Para esto, se recurre a un instrumento de modelización (IM) que permite caracterizar detalladamente las creencias, objetivos y conocimientos activados prioritariamente en el contexto específico de la clase de ciencias y las acciones implementadas por el profesor, interactuando conjuntamente. El guión de acción es una entidadad teórica que permite capturar e interpretar los aspectos del pensamiento del profesor, a veces los aspectos más tácitos de la enseñanza, como las creencias, conocimientos y objetivos en la acción y, por otro lado, comprender cómo estas cogniciones interactúan entre sí en un contexto particular. El guión de acción se corresponde con una secuencia de acciones implementada por el profesor y reconocida como estandarizada, rutinizada y con dependencia del contenido conceptual de ciencias. Finalmente, se apuntan algunas aplicaciones de los guiones de acción en actividades relacionadas con la reflexión sobre la práctica docente.
Using Online Modules to Bridge Research to Practice in Classrooms

Although research identifies a plethora of evidence-based instructional practices, classroom teachers find research difficult to access and often of little relevance to classroom practice; therefore, they do not implement these practices. Bridging the gap between research and practice requires continued and mediated support as teachers translate and contextualize research through their lenses of prior knowledge, understandings, and impact on student results within their classrooms. This developmental process is both time consuming and unique. To address the need for contextualized support during the implementation process of evidenced-based instructional practices by teachers to determine impact of instruction, online modules have been developed, implemented, and researched using a beta testing process. The authors of this article describe the content of the online modules and mediated support, outline the specific research framework of beta testing procedures and instrumentation, describe the content and structure of the course, analyze the results from the pilot study, and describe the limitations and considerations for continued research.
sinFul and/or Possessed? reliGious belieFs and mental illness stiGma

Stigma—a serious problem for persons with mental illness—is related to reductions in the quality of employment, housing, and social support. Many empirical studies showed common beliefs about persons with mental illness but little was known about how Christian religious beliefs affect perceptions of people with mental illness, or whether beliefs are specific to certain denominations. These two studies (one lab, one Internet-based) assessed religious beliefs about mental illness and their relations to known negative beliefs about mental illness. Our data suggest religious beliefs about mental illness appear as two separate but related dimensions. These dimensions focused on beliefs about sin/morality and spiritually-oriented causes/treatments, and were related to negative secular beliefs about mental illness. They were also related to other individual differences that predict prejudice toward stigmatized groups. Data also suggest these religious beliefs are endorsed differently depending upon religious aff.
Self-organization of Linear Pattern Classiiers. from "one-shot" to Statistical Learning

We studied competitive learning dynamics in diierent time scale regimes of learning. By rst assuming that learning is fast, we develop a self-organizing linear pattern classiier which can categorize patterns based on the presentation of single examples. The system can recognize patterns as "unknown" and autonomously instantiate new categories. Competition is governed by neural eld dynamics, the properties of which enable us to consider the plastic behavior also in the limit of statistical learning. We can show that in this regime the dynamic equations can be approximated by the well known Kohonen algorithm, including a shrinking neighborhood function and decreasing learning rate. Our results show that biological systems might solve diier-ent learning tasks with identical rules by varying relative time scales among neural activity, learning and environmental dynamics.
‘It’s all about developing the whole child’

Between 2011 and 2013, the Department for Education (DfE) in England made £3.3 million available to support the development of opportunities for young disabled people to access high-quality physical education and school sport. The DfE with the Youth Sport Trust (YST) developed a range of initiatives to help meet this aim, including Project Ability, TOPsportsability and the Young Leaders programme. The authors of this article were commissioned by the YST to evaluate the school-based inclusion initiatives. One aspect of the evaluation was an examination of project ‘legacy’ benefits – a term much cited in the run-up to the London 2012 Olympic and Paralympic games. This article asks what additional, unexpected, positive legacy benefits appear to be associated with the capacity built by the DfE Disability project initiatives. A wide range of legacy benefits beyond those the YST set out to achieve were found, including tangible achievements such as accreditation, and intangible benefits such as the holistic development of participants beyond sports.
Normalization by realizability also evaluates

For those of us that generally live in the world of syntax, semantic proof methods such as realizability or logical relations / parametricity sometimes feel like magic. Why do they work? At which point in the proof is "the real work" done? Bernardy and Lasson express realizability and parametricity models as syntactic model -- but the abstraction/adequacy theorems are still explained as meta-level proofs. Hoping to better understand the proof technique, we look at those theorems as programs themselves. How does a normalization proof using realizability actually computes those normal forms? This detective work is an early stage and we propose a first attempt in a simple setting. Instead of arbitrary Pure Type Systems, we use the minimal negative propositional logic (arrows only). Instead of starting from the simply-typed lambda-calculus, we work on sequent-style terms in a simple subset of the Curien-Herbelin L calculus.
Detecting Botnets in Computer Networks Using Multi-agent Technology

The paper presents a hybrid model of the bots detector which is a combination of host intrusion detection system and the operating system event log analyzer. Bot can be defined as a computer that have been attacked by a hacker or infected with malicious software and is used for illegal activities. Collections of infected computers form a botnet. The proposed system is used to detect bots based on the evaluation of events occurring in the operating system and network environment. Detection algorithms based on the signatures derived from the analysis of the various types of malicious software that creates bots. The model has been implemented using multi-agent technology.
Testing Central Processing Unit scheduling algorithms using Metamorphic Testing

Central Processing Unit (CPU) scheduling is used to allocate CPU for multiple processes. CPU is one of the most important resources in the computer system, and its scheduling is vital and influential in operating systems. Thus, it is necessary to ensure the correctness of the CPU scheduling program. However, testing the correctness of a scheduling program is difficult because it is hard to verify the correctness of its output, which is known as the test oracle problem in software testing. Metamorphic Testing (MT) which has been recently proposed to alleviate the test oracle problem, is applied to test the CPU scheduling program. In this paper, we use MT to test the Highest Response Ratio Next (HRRN) scheduling algorithm. Two simulators of HRRN scheduler are used in the evaluation of our method. Surprisingly, some real life faults in one open source simulator are detected by MT. Further experiments are performed based on mutants, and the experimental results show that MT is an effective strategy to test CPU scheduler.
Development of a tool to evaluate lecturers' verbal repertoire in action

A broad communicative repertoire can help university lecturers to motivate and engage diverse student populations. The aim of this study is to develop and explore the usefulness and validity of a tool to identify patterns in lecturers' verbal repertoire. Speech act theory is presented as a framework to study lecturers' verbal communication during teaching. A description of the tool and the analysis of verbal actions are presented. In order to explore the validity, patterns of 12 university lecturers' verbal actions during instruction were examined. Characteristic speech act sequences were identified, similar sequences were clustered and associations with other teaching behaviours were explored to analyse the construct validity. We explain the instrument in detail to assist future use and we discuss to what extent it can provide ways to reflect on lecturers' verbal repertoire in action.
Evaluating tag-based information access in image collections

The availability of social tags has greatly enhanced access to information. Tag clouds have emerged as a new "social" way to find and visualize information, providing both one-click access to information and a snapshot of the "aboutness" of a tagged collection. A range of research projects explored and compared different tag artifacts for information access ranging from regular tag clouds to tag hierarchies. At the same time, there is a lack of user studies that compare the effectiveness of different types of tag-based browsing interfaces from the users point of view. This paper contributes to the research on tag-based information access by presenting a controlled user study that compared three types of tag-based interfaces on two recognized types of search tasks -- lookup and exploratory search. Our results demonstrate that tag-based browsing interfaces significantly outperform traditional search interfaces in both performance and user satisfaction. At the same time, the differences between the two types of tag-based browsing interfaces explored in our study are not as clear.
Michigan vs. Pittsburgh Style GA Optimisation of Fuzzy Rule Bases for Gene Expression Analysis

Microarray studies and gene expression analysis have received a lot of attention and provide many promising avenues towards the understanding of fundamental questions in biology and medicine. In this paper, the authors perform gene expression analysis and apply two hybrid GA-fuzzy approaches to classify gene expression data. Both are based on fuzzy if-then rule bases but they differ in the way these rule bases are optimised. The authors employ both a Michigan style approach, where single rules are handled as individuals in the population of the genetic algorithm, and a Pittsburgh type algorithm, which treats whole rule sets as individuals. Experimental results show that both approaches achieve good classification accuracy but that the Michigan style algorithm clearly outperforms the Pittsburgh classifier.
State-of-the-art sex offender treatment: Outcome and issues

Ill-advised negative media coverage on sex offender treatment program outcomes has increased in recent years. The following article provides current brief insights into why state-of-the-art sex offender treatment programs offer the safest, most cost-effective option in response to sex offender behavior. Issues on the developing discipline of sex offender treatment, current changes in treatment, benefits of treatment versus incarceration, program efficacy and recidivism and politics surrounding these issues are discussed. The article closes with specific advice in providing information to the media.
A Global and Local Superlinear Continuation-Smoothing Method for P0 +R0 and Monotone NCP

We propose a continuation method for a class of nonlinear complementarity problems (NCPs), including the NCP with a P 0 and R 0 function and the monotone NCP with a feasible interior point. The continuation method is based on a class of Chen-Mangasarian smooth functions. Unlike many existing continuation methods, the method follows the non-interior smoothing paths, and as a result, an initial point can be easily constructed. In addition, we introduce a procedure to dynamically update the neighborhoods associated with the smoothing paths, so that the algorithm is both globally convergent and locally superlinearly convergent under suitable assumptions. Finally, a hybrid continuation-smoothing method is proposed and is shown to have the same convergence properties under weaker conditions.
An Automatic Generation of G^1 Curve Fitting of Arabic Characters

An Arabic font is difficult to fit as it is cursive in character, having varying curves and cusps. Here, the Arabic character is represented as an outline font fitted with G1 rational Bezier cubic curves. As a method in reverse engineering, the Arabic character is created by way of digitizing an image that already exists and then fitting G1 curves automatically to the outline of the digitized image. The outline font representation is done in several phases - contour extraction of font image, corner point's detection and lastly contour segment fitting. Image is considered as binary and boundary is obtained accordingly. Eigenvalues of covariance matrix and the concept of region of support are employed to search for the corners of the Arabic characters which are of varying degrees of smoothness. G 1 rational Bezier cubics, iteratively determined, are used in the last step. The weights are adjusted automatically to get curves that are as close as need be to the digitized data points. This technique can be extended to visualizing outlines of other contour-based images automatically
Taxonomic, Phylogenetic, and Trait Beta Diversity in South American Hummingbirds

Comparison of the taxonomic, phylogenetic, and trait dimensions of beta diversity may uncover the mechanisms that generate and maintain biodiversity, such as geographic isolation, environmental filtering, and convergent adaptation. We developed an approach to predict the relationship between environmental and geographic distance and the dimensions of beta diversity. We tested these predictions using hummingbird assemblages in the northern Andes. We expected taxonomic beta diversity to result from recent geographic barriers limiting dispersal, and we found that cost distance, which includes barriers, was a better predictor than Euclidean distance. We expected phylogenetic beta diversity to result from historical connectivity and found that differences in elevation were the best predictors of phylogenetic beta diversity. We expected high trait beta diversity to result from local adaptation to differing environments and found that differences in elevation were correlated with trait beta diversity. When combining beta diversity dimensions, we observe that high beta diversity in all dimensions results from adaption to different environments between isolated assemblages. Comparisons with high taxonomic, low phylogenetic, and low trait beta diversity occurred among lowland assemblages separated by the Andes, suggesting that geographic barriers have recently isolated lineages in similar environments. We provide insight into mechanisms governing hummingbird biodiversity patterns and provide a framework that is broadly applicable to other taxonomic groups.
Parallel sparse LU decomposition using FPGA with an efficient cache architecture

LU decomposition is widely used in the field of numerical analysis and engineering to solve large-scale sparse linear equations. The complex data dependency makes it difficult to parallelize the LU decomposition. In this paper, an architecture with an efficient cache for parallel sparse LU decomposition using FPGA is proposed. The proposed architecture is based on the Gilbert-Peierls (G-P) algorithm. By using the elimination graph, we find the column dependency of the LU decomposition. It is thus possible to exploit the parallelism. Through a dependency table, a simple but efficient cache strategy and its corresponding architecture are proposed. The proposed cache strategy avoids the cache miss and reduces the size of cache used to store all the intermediate data on chip. The experiment demonstrates that, our design can achieve speedup of 2.85x–10.27x, compared with UMFPACK running on general purpose processors. The cache size can be reduced by 50.93% on average with the proposed cache strategy.
Multisensor Data Fusion for Spaceborne and Airborne Reduction of Mine Suspected Areas

The problem of mined area reduction is addressed in this paper. Pieces of information collected using airborne multispectral scanners and airborne full polarimetric SAR, together with context information, all integrated in a geographical information system, are classified and combined in order to find indicators of mine presence and mine absence and provide image analysts with adequate tools to interpret mined scenes during the area reduction process. The paper contains a broad description of the whole problem and of the developed method and focuses on classification and data fusion tools based on the belief function framework and fuzzy sets theory.
Efficient computation of program equivalence for confluent concurrent constraint programming

Concurrent Constraint Programming (ccp) is a well-established declarative framework from concurrency theory. Its foundations and principles e.g., semantics, proof systems, axiomatizations, have been thoroughly studied for over the last two decades. In contrast, the development of algorithms and automatic verification procedures for ccp have hitherto been far too little considered. To the best of our knowledge there is only one existing verification algorithm for the standard notion of ccp program (observational) equivalence. In this paper we first show that this verification algorithm has an exponential-time complexity even for programs from a representative sub-language of ccp; the summation-free fragment (ccp\+). We then significantly improve on the complexity of this algorithm by providing two alternative polynomial-time decision procedures for ccp\+ program equivalence. Each of these two procedures has an advantage over the other. One has a better time complexity. The other can be easily adapted for the full language of ccp to produce significant state space reductions. The relevance of both procedures derives from the importance of ccp\+. This fragment, which has been the subject of many theoretical studies, has strong ties to first-order logic and an elegant denotational semantics, and it can be used to model real-world situations. Its most distinctive feature is that of confluence, a property we exploit to obtain our polynomial procedures.
An Analysis of Protein Abundance Suppression in Data Dependent Liquid Chromatography and Tandem Mass Spectrometry with Tryptic Peptide Mixtures of Five Known Proteins

Reverse-phase liquid chromatography (RPLC) has been widely used in proteomics research for peptide separation. When protein samples are separated by RPLC and identified with electrospray ion trap mass spectrometry (ES-IT-MS), the signals of high-abundance proteins may suppress those of low-abundance proteins, a phenomenon known as abundance suppression. To what degree the abundance suppression correlates to the number of tryptic peptides in the high-abundance proteins has not been carefully investigated. We tried to answer this question by studying the mixtures digested from five known proteins. The number of identified tryptic peptides (longer than five amino acids) of the five proteins ranged from 12 to 47. Four different peptide mixtures with 10- to 100-fold abundance differences of five known proteins were separated by RPLC and identified by ES-IT-MS. Our results showed that abundance suppression was related to the tryptic peptide numbers in the high-abundance protein. Within a 100-fold protein abundance difference range, the tryptic peptide numbers in the low-abundance proteins could be suppressed up to seven times by high-abundance proteins. The procedure we suggest here can help to identify low-abundance proteins co-purified with their high-abundance binding protein. The results can also help to identify specific high-abundance proteins for removal by immunoaffinity.