Miracle-dz/UniFAR-FTUs huggingface dataset:
French-speaking students' academic experiences at a private provider of higher education offering foundation programmes

The academic experiences of French-speaking immigrant students involve a negotiation of the French language with the language of learning and teaching (LoLT). Utilising Legitimate Peripheral Participation (LPP), case study, observation, document analysis and a narrative inquiry, this research set out to explore the academic experiences of French-speaking students at a private provider of higher education offering foundation programmes as a route to mainstream degree programmes. It was found that sociocultural factors played vital roles in the survival of French-speaking students at the academic institution. South African students spoke Sotho and Zulu both within and outside of the lecture rooms, a scenario which undermined the capacity of French-speaking students to adapt academically and socio-culturally to the academic institution. Unfriendliness on the part of South African students and introversion (an inherent character trait) along with the incongruous posture of the French-speaking students in terms of their incessant use of the French language challenged their academic survival.
Modification of Luyckx et al.’s Integrated Process Oriented Model of Identity Formation

Abstract Our study attempts to assess the validity of a modification of the Luyckx, Schwartz, Berzonsky, Soenens, Vansteenkiste, Smits and Goossens’ dual-cycle model of identity formation (2008). The model has been extended to include a six dimensions because it takes two types of ruminative exploration into account. Thus, the model consists of reflective exploration in breadth, ruminative exploration in breadth and commitment making, which form a commitment formation cycle, and reflective exploration in depth, ruminative exploration in depth and identification with commitment, which in turn form a commitment evaluation cycle. Six hundred and forty-two Caucasian Poles (including 51 early adolescents, 270 late adolescents, 272 emerging adults and 49 young adults; 66% women) participated in our study. Confirmatory factor analysis and correlation analysis between identity dimensions indicate that the proposed model has a satisfactory internal validity. Analysis of variance in groups with different educational-professional contexts and ages, as well as correlation analysis of the identity dimensions with adjustment indicators, and ruminative and reflective self-consciousness show a satisfactory external validity. In summary, the proposed modification may present an alternative to the original model, but its limitations will also be discussed.
Multithreaded home-based lazy release consistency over VIA

Summary form only given. A distributed shared memory (DSM) system is a software or hardware mechanism that provides a distributed application with a shared virtual address space. The efficiency of a DSM system relies mainly on a memory coherency protocol and an efficient communication layer. We propose a design for implementing the communication layer on top of the virtual interface architecture (VIA), an industry standard for user-level networking protocols on high-speed clusters. User-level communication protocols operate in a user mode, thus removing the operating system kernel's overhead from the critical communication pass and significantly diminishing communication overhead as a result. We analyze VIA's facilities and limitations in order to ascertain which implementation trade-offs can be best applied to our development of an efficient communication substrate optimized for DSM requirements. We then implement a multithreaded version of the home-based lazy release consistency (HLRC) protocol on top of this efficient substrate. We evaluate and analyze the performance of this protocol over a wide set of benchmark applications.
First Report of Cowpea Mild Mottle Carlavirus on Yardlong Bean (Vigna unguiculata subsp. sesquipedalis) in Venezuela

Yardlong bean (Vigna unguiculata subsp. sesquipedalis) plants with virus-like systemic mottling and leaf distortion were observed in both experimental and commercial fields in Aragua State, Venezuela. Symptomatic leaves were shown to contain carlavirus-like particles. RT-PCR analysis with carlavirus-specific primers was positive in all tested samples. Nucleotide sequences of the obtained amplicons showed 84%–74% similarity to corresponding sequences of Cowpea mild mottle virus (CPMMV) isolates deposited in the GenBank database. This is the first report of CPMMV in Venezuela and is thought to be the first report of CPMMV infecting yardlong bean.
Unsupervised Alignment of Actions in Video with Text Descriptions

Advances in video technology and data storage have made large scale video data collections of complex activities readily accessible. An increasingly popular approach for automatically inferring the details of a video is to associate the spatio-temporal segments in a video with its natural language descriptions. Most algorithms for connecting natural language with video rely on pre-aligned supervised training data. Recently, several models have been shown to be effective for unsupervised alignment of objects in video with language. However, it remains difficult to generate good spatio-temporal video segments for actions that align well with language. This paper presents a framework that extracts higher level representations of low-level action features through hyperfeature coding from video and aligns them with language. We propose a two-step process that creates a high-level action feature codebook with temporally consistent motions, and then applies an unsupervised alignment algorithm over the action codewords and verbs in the language to identify individual activities. We show an improvement over previous alignment models of objects and nouns on videos of biological experiments, and also evaluate our system on a larger scale collection of videos involving kitchen activities.
Modelling Land Use, Land-Use Change, and Forestry in Climate Change: A Review of Major Approaches

The rapid development of climate policies and the need to understand the dynamics of climate change have highlighted and shaped the role of land use, land-use change and forestry dynamics (LULUCF), making it an issue of global importance. As a consequence, LULUCF has become a central topic in economic theory and in environmental sciences. The attention is focused on creating and expanding comprehensive global land-use datasets and on improving the modelling strategies allowing for an extensive representation of the land-use system. However, this is a relatively new research field and the development of this challenging process is likely to require greater effort in the years to come. By adopting a straightforward model classification, this paper provides a broad, but detailed, overview of the most representative methods and models developed to date. This summary will guide a critical discussion on relevant methodological aspects related to the global modelling of land use and its changes. An additional focus is placed on the representation of forest-carbon sequestration within climate mitigation, which represents one of the most demanding issues from a modelling perspective.
Automatic Web Service Composition with a Heuristic-Based Search Algorithm

Service Oriented Architectures and web service technology are becoming popular in recent years. As more web services can be used over the Internet, the need to find efficient algorithms for web services composition that can deal with large amounts of services becomes important. These algorithms must deal with different issues like performance, semantics or user restrictions. In this paper we present an A* algorithm which solves the problem of semantic input-output message structure matching for web service composition. Given are quest, a service dependency graph with a subset of the original services from an external repository is dynamically generated. Then, the A*search algorithm is used to find a minimal composition that satisfies the user request. Moreover, in order to improve the performance, a set of dynamic optimization techniques has been implemented over the search process. A full experimental validation with eight different public repositories has been done showing a good performance as in all tests as the algorithm finds a valid solution with minimal number of services and execution path.
Clinical Psychology Five Classes of Research Questions in Clinical Psychology Defining and Measuring Constructs

Quantitative sophistication is increasingly central to research in clinical psychology. Both our theories and the statistical techniques available to test our hypotheses have grown in complexity over the last few decades, such that the novice clinical researcher now faces a bewildering array of analytic options. The purpose of this article is to provide a conceptual overview of the use of statistics in clinical science. The first portion of this article describes five major research questions that clinical psychology researchers commonly address and provides a brief overview of the statistical methods that frequently are employed to address each class of questions. These questions are neither exhaustive nor mutually exclusive , but rather are intended to serve as a heuristic for organizing and thinking about classes of research questions in clinical psychology and the techniques most closely associated with them. The second portion of the article articulates guiding principles that underlie the responsible use of statistics in clinical psychology. Careful attention to the definition and measurement of constructs is the bread and butter of clinical research. Constructs refer to abstract psychological entities and phenomena such as depression, marital violence, genetic influences, attention to negative information, acculturation, and cognitive-behavioral therapy (CBT). We specify these unobserved variables (see Latent Variable), as well as their interrelationships , in a theoretical model (e.g., CBT might be assumed to decrease depression in one's partner, which then decreases the likelihood of marital violence in the relationship). Our measurement model (see Measurement: Overview) specifies the way in which we operationally define the constructs of interest (e.g., our 'measurement variable', or 'indica-tor variable', for the construct of depression might be patient scores on the Beck Depression Inventory (BDI) [4]). Finally, our analytical model refers to the way in which we statistically evaluate the hypothesized relationships between our measured variables (e.g., we might use structural-equation modeling (SEM), analysis of variance (ANOVA), or logistic regression). Later in this article, we discuss the importance of the consistency between these three models for making valid inferences about a theoretical model, as well as the importance of 'starting at the top' (i.e., the importance of theory for the rapid advancement of clinical research). Readers are urged to consult McFall and Townsend [36] for a more comprehensive overview of the specification and evaluation of the multiple layers of scientific models in clinical research. Deciding how best to measure our constructs – that is, specifying the measurement …
Rackham: An Interactive Robot-Guide

Rackham is an interactive robot-guide that has been used in several places and exhibitions. This paper presents its design and reports on results that have been obtained after its deployment in a permanent exhibition. The project is conducted so as to incrementally enhance the robot functional and decisional capabilities based on the observation of the interaction between the public and the robot. Besides robustness and efficiency in the robot navigation abilities in a dynamic environment, our focus was to develop and test a methodology to integrate human-robot interaction abilities in a systematic way. We first present the robot and some of its key design issues. Then, we discuss a number of lessons that we have drawn from its use in interaction with the public and how that will serve to refine our design choices and to enhance robot efficiency and acceptability
RNA-eXpress annotates novel transcript features in RNA-seq data

Summary: Next-generation sequencing is rapidly becoming the approach of choice for transcriptional analysis experiments. Substantial advances have been achieved in computational approaches to support these technologies. These approaches typically rely on existing transcript annotations, introducing a bias towards known genes, require specific experimental design and computational resources, or focus only on identification of splice variants (ignoring other biologically relevant transcribed features contained within the data that may be important for downstream analysis). Biologically relevant transcribed features also include large and small non-coding RNA, new transcription start sites, alternative promoters, RNA editing and processing of coding transcripts. Also, many existing solutions lack accessible interfaces required for wide scale adoption. We present a user-friendly, rapid and computation-efficient feature annotation framework (RNA-eXpress) that enables identification of transcripts and other genomic and transcriptional features independently of current annotations. RNA-eXpress accepts mapped reads in the standard binary alignment (BAM) format and produces a study-specific feature annotation in GTF format, comparison statistics, sequence extraction and feature counts. The framework is designed to be easily accessible while allowing advanced users to integrate new feature-identification algorithms through simple class extension, thus facilitating expansion to novel feature types or identification of study-specific feature types. Availability and implementation: RNA-eXpress software, source code, user manuals, supporting tutorials, developer guides and example data are available at http://www.rnaexpress. org. Contact: paul.hertzog@monash.edu Supplementary information: Supplementary data are available at Bioinformatics online.
Wi-Fi broadband maritime communications using 5.8 GHz band

Current maritime communications rely on expensive or proprietary technology, such as satellite, WiMAX, and narrowband HF radios. Broadband communications are limited to the near shore 3G/4G coverage provided by mobile operators. The usage of unlicensed and IEEE 802.11 networks may provide ship owners a low-cost broadband access to the Internet offshore, enabling real-time navigation applications and voice/video communications, while increasing safety onboard. Also, they can support underwater communications by acting as a bridge between shore and devices operating underwater. In this paper we present a performance evaluation of IEEE 802.11n networks in the 5.8 GHz band in a maritime environment. A point-to-point link was established between a fishing ship and shore. From our tests, communication links up to 7 km at 1 Mbit/s are possible, showing the advantage of using long range IEEE 802.11 links for broadband maritime communications.
Impulse response shortening for x DSL discrete multitone modems with linear phase filters

The problem of shortening the effective channel impulse response in xDSL is addressed. A new approach is described based on linear phase FIR equaliser filters. The mathematical framework for the LPIRS method is developed and simulation results are presented for several VDSL loops. For a similar performance, the novel method offers a design with considerably lower computational complexity and a simpler solution, on either DSP or dedicated hardware implementations.
Fiberio: a touchscreen that senses fingerprints

We present Fiberio, a rear-projected multitouch table that identifies users biometrically based on their fingerprints during each touch interaction. Fiberio accomplishes this using a new type of screen material: a large fiber optic plate. The plate diffuses light on transmission, thereby allowing it to act as projection surface. At the same time, the plate reflects light specularly, which produces the contrast required for fingerprint sensing. In addition to offering all the functionality known from traditional diffused illumination systems, Fiberio is the first interactive tabletop system that authenticates users during touch interaction-unobtrusively and securely using the biometric features of fingerprints, which eliminates the need for users to carry any identification tokens.
An iterative algorithm for multiple-source detection using an array

In multiple source detection of using an array, the threshold of the generalized likelihood ratio test (GLRT) is only related with the noise power. And the false alarm probability will increase when one signal is present in the sidelobe of beamformer's pattern because of energy leakage. A constant false alarm ratio (CFAR) based multiple-source detection algorithm was proposed in this paper. The detection probability and false alarm probability were analyzed theoretically and by simulations, and the threshold setting method was given out. The simulation showed the algorithm proposed can detect out the multiple signals effectively and the false alarm probability keeps constant.
An Approach to Detect and Prevent SQL Injection Attacks in Database Using Web Service

SQL injection is an attack methodology that targets the data residing in a database through the firewall that shields it. The attack takes advantage of poor input validation in code and website administration. SQL Injection Attacks occur when an attacker is able to insert a series of SQL statements in to a ‘query’ by manipulating user input data in to a web-based application, attacker can take advantages of web application programming security flaws and pass unexpected malicious SQL statements through a web application for execution by the backend database. This paper proposes a novel specification-based methodology for the prevention of SQL injection Attacks. The two most important advantages of the new approach against existing analogous mechanisms are that, first, it prevents all forms of SQL injection attacks; second, Current technique does not allow the user to access database directly in database server. The innovative technique “Web Service Oriented XPATH Authentication Technique” is to detect and prevent SQLInjection Attacks in database the deployment of this technique is by generating functions of two filtration models that are Active Guard and Service Detector of application scripts additionally allowing seamless integration with currently-deployed systems.
Efficient Learning and Planning Within the Dyna Framework

Sutton's Dyna framework provides a novel and computationally appealing way to integrate learning, planning, and reacting in autonomous agents. Examined here is a class of strategies designed to enhance the learning and planning power of Dyna systems by increasing their computational efficiency. The benefit of using these strategies is demonstrated on some simple abstract learning tasks.
An Indonesian question analyzer to enhance the performance of Indonesian-English CLQA

The most common approach in Cross Language Question Answering (CLQA) is to employ question translation. The easiest way to conduct question translation is by translating the source question into target language using existing machine translation or bilingual dictionary. However, the error resulted by the question translation may influence the accuracy of CLQA. This research proposes an adaptation in Indonesian question analyzer in order to extend the English monolingual QA (Question Answering) framework into Indonesian-English CLQA. The monolingual QA used in this research is Open Ephyra, an open domain QA framework that is modular, extensible and language independent. This research is conducted by custumizing the Open Ephyra into CLQA and implementing it for the Indonesian-English CLQA. A better performance is shown by employing a question analyzer on the source language side than using the question translation on the target language side. It should be noticed that the question analyzer is also suitable for monolingual QA in Indonesian QA.
Predicting emergency coronary artery bypass graft following PCI: application of a computational model to refer patients to hospitals with and without onsite surgical backup

Background Clinical tools to stratify patients for emergency coronary artery bypass graft (ECABG) after percutaneous coronary intervention (PCI) create the opportunity to selectively assign patients undergoing procedures to hospitals with and without onsite surgical facilities for dealing with potential complications while balancing load across providers. The goal of our study was to investigate the feasibility of a computational model directly optimised for cohort-level performance to predict ECABG in PCI patients for this application. Methods Blue Cross Blue Shield of Michigan Cardiovascular Consortium registry data with 69 pre-procedural and angiographic risk variables from 68 022 PCI procedures in 2004–2007 were used to develop a support vector machine (SVM) model for ECABG. The SVM model was optimised for the area under the receiver operating characteristic curve (AUROC) at the level of the training cohort and validated on 42 310 PCI procedures performed in 2008–2009. Results There were 87 cases of ECABG (0.21%) in the validation cohort. The SVM model achieved an AUROC of 0.81 (95% CI 0.76 to 0.86). Patients in the predicted top decile were at a significantly increased risk relative to the remaining patients (OR 9.74, 95% CI 6.39 to 14.85, p<0.001) for ECABG. The SVM model optimised for the AUROC on the training cohort significantly improved discrimination, net reclassification and calibration over logistic regression and traditional SVM classification optimised for univariate performance. Conclusions Computational risk stratification directly optimising cohort-level performance holds the potential of high levels of discrimination for ECABG following PCI. This approach has value in selectively referring PCI patients to hospitals with and without onsite surgery.
Maximal Repetitions in Written Texts: Finite Energy Hypothesis vs. Strong Hilberg Conjecture

The article discusses two mutually-incompatible hypotheses about the stochastic mechanism of the generation of texts in natural language, which could be related to entropy. The first hypothesis, the finite energy hypothesis, assumes that texts are generated by a process with exponentially-decaying probabilities. This hypothesis implies a logarithmic upper bound for maximal repetition, as a function of the text length. The second hypothesis, the strong Hilberg conjecture, assumes that the topological entropy grows as a power law. This hypothesis leads to a hyperlogarithmic lower bound for maximal repetition. By a study of 35 written texts in German, English and French, it is found that the hyperlogarithmic growth of maximal repetition holds for natural language. In this way, the finite energy hypothesis is rejected, and the strong Hilberg conjecture is partly corroborated.