Miracle-dz/UniFAR-FTUs huggingface dataset:
Normative Influence and Rational Conflict Decisions: Group Norms and Cost-Benefit Analyses for Intergroup Behavior

The present paper articulates a model in which ingroup and outgroup norms inform ‘rational’ decision-making (cost-benefit analysis) for conflict behaviors. Norms influence perceptions of the consequences of the behavior, and individuals may thus strategically conform to or violate norms in order to acquire benefits and avoid costs. Two studies demonstrate these processes in the context of conflict in Québec. In the first study, Anglophones’ perceptions of Francophone and Anglophone norms for pro-English behaviors predicted evaluations of the benefits and costs of the behaviors, and these cost-benefit evaluations in turn mediated the norm-intention links for both group norms. In the second study, a manipulated focus on supportive versus hostile ingroup and outgroup norms also predicted cost-benefit evaluations, which mediated the norm-intention relationships. The studies support a model of strategic conflict choices in which group norms inform, rather than suppress, rational expectancy-value processes. Implications for theories of decision-making and normative influence are discussed.
Curriculum Reform and School Performance: An Evaluation of the "New Basics"

The National Commission on Excellence in Education report proposed the imposition of a new high school curriculum, organized around "Five New Basics. " We examine whether the commission's New Basics are likely to enhance levels of cognitive performance, which is the commission's central concern. Using data from the ETS Growth Study, we find that completion of the core curriculum has sizable effects on senior year test performance, even when prior levels of test performance are controlled, and enhances test performance beyond the effects of course work in a particular outcome area alone. However, core completion is effective only if students perform at relatively high levels in their courses. We conclude that the New Basics effectively promote generic verbal and quantitative skills. For this, the commission gets high marks. However, the commission fails to take stock comprehensively of the condition of American education.
High Dimensional Bayesian Optimisation and Bandits via Additive Models

Bayesian Optimisation (BO) is a technique used in optimising a $D$-dimensional function which is typically expensive to evaluate. While there have been many successes for BO in low dimensions, scaling it to high dimensions has been notoriously difficult. Existing literature on the topic are under very restrictive settings. In this paper, we identify two key challenges in this endeavour. We tackle these challenges by assuming an additive structure for the function. This setting is substantially more expressive and contains a richer class of functions than previous work. We prove that, for additive functions the regret has only linear dependence on $D$ even though the function depends on all $D$ dimensions. We also demonstrate several other statistical and computational benefits in our framework. Via synthetic examples, a scientific simulation and a face detection problem we demonstrate that our method outperforms naive BO on additive functions and on several examples where the function is not additive.
Moving-Baseline Localization for Mobile Wireless Sensor Networks by Jun-geun Park

The moving-baseline localization (MBL) problem arises when a group of nodes moves through an environment in which no external coordinate reference is available. When group members cannot see or hear one another directly, each node must employ local sensing and inter-device communication to infer the spatial relationship and motion of all other nodes with respect to itself. We consider a setting in which nodes move with piecewise-linear velocities in the plane, and any node can exchange noisy range estimates with certain sufficiently nearby nodes. We develop a distributed solution to the MBL problem in the plane, in which each node performs robust hyperbola fitting, trilateration with velocity constraints, and subgraph alignment to arrive at a globally consistent view of the network expressed in its own "rest frame. " Changes in any node's motion cause deviations between observed and predicted ranges at nearby nodes, triggering revision of the trajectory estimates computed by all nodes. We implement and analyze our algorithm in a simulation informed by the characteristics of a commercially available ultra-wideband (UWB) radio, and show that recovering node trajectories, rather than just locations, requires substantially less computation at each node. Finally, we quantify the minimum ranging rate and local network density required for the method's successful operation. Thesis Supervisor: Seth Teller Title: Professor of Computer Science and Engineering
Preparing teachers to teach pupils with special educational needs in more inclusive schools: evaluating a PGCE development

As we move towards a more inclusive education system in the UK, there is a real need to equip teachers to work in more diverse classrooms from the start of their teaching careers. In this article, Gill Golder, teaching and research fellow (physical education), Brahm Norwich, Professor of Educational Psychology and Special Educational Needs, and Phil Bayliss, senior lecturer in special educational needs and education studies, all based in the School of Education and Lifelong Learning at the University of Exeter, describe developments in Exeter's secondary phase Post Graduate Certificate in Education (PGCE) programme. The authors set their account in the context of policy requirements in England and international trends towards more inclusive teacher education. They report on an initiative designed to enhance the knowledge, skills and attitudes of trainee teachers and to equip them to differentiate their teaching to meet the individual needs of all pupils, including those with special educational needs. This initiative involved all trainees working intensively with one pupil, supported by the SENCo in their teaching practice school. Building towards a form of dispersed teacher preparation that may have applications in other contexts, the programme offered student teachers a systematic strategy for individualised teaching and the support of web-based resources. Gill Golder, Brahm Norwich and Phil Bayliss include evaluations from student teachers, SENCos and principal subject tutors in their report. They conclude that this is a promising way of working, which highlights the national and international need to develop practical ways of enhancing initial teacher education in relation to special educational needs and inclusion.
Outlier Detection: Applications and techniques in Data Mining

Outlier Detection is one of the major issues in Data Mining; finding outliers from a collection of patterns is a popular problem in the field of data mining. An outlier is that pattern which is dissimilar with respect to all the remaining patterns in the data set. Outlier detection is quiet familiar area of research in mining of data set. It is a quiet important task in various application domains. Earlier outliers considered as noisy data, has now become severe difficulty which has been discovered in various domains of research. The discovery of outlier is useful in detection of unpredicted and unidentified data, in certain areas like fraud detection of credit cards, calling cards, discovering computer intrusion and criminal behaviors etc. A number of surveys, research and review articles cover outlier detection techniques in great details. Here in this review paper, my effort is to take as one several techniques of outlier detection. By this attempt, we wish to gain a improved perceptive of various research on outlier detection and analysis for our well-being as well as for those who are the beginners in this field, so that they can easily pickup the links in details.
Foreebank: Syntactic Analysis of Customer Support Forums

We present a new treebank of English and French technical forum content which has been annotated for grammatical errors and phrase structure. This double annotation allows us to empirically measure the effect of errors on parsing performance. While it is slightly easier to parse the corrected versions of the forum sentences, the errors are not the main factor in making this kind of text hard to parse.
Dilemmas in qualitative health research

Abstract As the use of qualitative methods in health research proliferates, it becomes increasingly necessary to consider how the value of a piece of qualitative research should be assessed. This article discusses the problem posed by the novelty and diversity of qualitative approaches within health psychology and considers the question of what criteria are appropriate for assessing the validity of a qualitative analysis. In keeping with the ethos of much qualitative research, some open-ended, flexible principles are suggested as a guide to the quality of a qualitative study: sensitivity to context; commitment and rigour; transparency and coherence; impact and importance. Examples are given of the very different ways in which various forms of qualitative research can meet these criteria.
Real-time Polyphonic Music Transcription with Non-negative Matrix Factorization and Beta-divergence

In this paper, we investigate the problem of real-time polyphonic music transcription by employing non-negative matrix factorization techniques and the -divergence as a cost function. We consider real-world setups where the music signal arrives incrementally to the system and is transcribed as it unfolds in time. The proposed transcription system is addressed with a modified non-negative matrix factorization scheme, called non-negative decomposition, where the incoming signal is projected onto a fixed basis of templates learned off-line prior to the decomposition. We discuss the use of non-negative matrix factorization with the -divergence to achieve the real-time decomposition. The proposed system is evaluated on the specific task of piano music transcription and the results show that it can outperform several state-of-the-art off-line approaches.
An Assessment of the Multi-level Integrated Database Approach

The Multi-level Integrated Database Approach (MIDA) is an innovative procedure to improve survey research in general and to assess and adjust for nonresponse bias in particular. Its utility for data collection, nonresponse measurement, estimate adjustment, interviewer validation, and analysis are considered. Also discussed is how MIDA extends survey methodology beyond existing practices. A demonstration of a MIDA-enhanced sample frame for U.S. households is carried out. Finally, further steps for the use and testing of MIDA are covered.
Linear Precoding Design for Mutual Information Maximization in Generalized Spatial Modulation With Finite Alphabet Inputs

In this letter, we develop a new precoding scheme that improves the performance of mutual information for generalized spatial modulation (GSM). First, the closed-form expression of the mutual information of the GSM with finite alphabet inputs is derived in order to update the precoder with regard to the mutual information. The joint precoding design problem to maximize the mutual information of the GSM is difficult to solve directly since it is a non-convex coupled problem. In order to solve this problem, we transform the GSM system into a virtual multiple-input multiple-output (MIMO) system, and then an extended ellipsoid algorithm is applied. Each precoder of the GSM can be solved using the common precoder of the virtual MIMO. The numerical results demonstrate that the proposed precoding scheme significantly enhances the performance in terms of the mutual information.
The prevalence and plasmid profile of non-typhoidal salmonellosis in children in Lagos metropolis, South-western Nigeria

Introduction Non-typhoidal Salmonella is the causative agent of gastroenteritis, a food-borne and zoonotic infection which is a major cause of high morbidity and death among children under 5 years of age especially from resource poor settings like the developing countries. Methods This study was carried out for 6 months to determine the prevalence and plasmid profile of non-typhoidal salmonellosis in children in Lagos metropolis. A total of 105 stool samples were collected from diarrheal children aged 3 months to 12 years and processed during this period. The isolates were identified using Selenite F Broth, Salmonella-Shigella Agar, Kligler Iron Agar, and Motility-indole-Urea medium, citrate and sugar utilization tests. Results A total number of 127 isolates were identified, 2 of which are Salmonella enteritidis (1.6%). The non-typhoidal Salmonellae were sensitive to ciprofloxacin, cetotaxime, streptomycin, cotrimxazole and tetracycline. Only one of the 2 isolates (50%) was sensitive to amoxillin and sulphonamide while none of them (0%) was sensitive to cefuroxime. Conclusion The plasmid analysis of the isolates showed that they harboured no detectable plasmids; this suggests that the resistance was chromosomally mediated.
Entrepreneurship education: revisiting our role and its purpose

Purpose – This paper seeks to focus on two questions. First, what value is created by entrepreneurship education? Second, how could any such value be created? The aim therefore is to go beyond any assumed notion that entrepreneurship education is beneficial to students in higher education, to question its underlying value.Design/methodology/approach – A critical realist approach is used to discuss the ontological nature of entrepreneurship education. Specifically, the process through which enterprise knowledge is developed and used by students in higher education. This research is based on a single‐site case study at UTAS with the data collected by the author and complemented by other recent work that sought to empirically consider the notion of student value from entrepreneurship education within the same (UTAS) context.Findings – The paper argues that students in higher education understand quite well the limitations of the knowledge they develop about entrepreneurship. That they (the educators) need to.
Multicenter validation of prostate tumor localization using multiparametric MRI and prior knowledge

Purpose: Tumor localization provides crucial information for radiotherapy dose differentiation treatments, such as focal dose escalation and dose painting by numbers, which aim at achieving tumor control with minimal side effects. Multiparametric (mp‐)MRI is increasingly used for tumor detection and localization in prostate because of its ability to visualize tissue structure and to reveal tumor characteristics. However, it can be challenging to distinguish cancer, particularly in the transition zone. In this study, we enhance the performance of a mp‐MRI‐based tumor localization model by incorporating prior knowledge from two sources: a population‐based tumor probability atlas and patient‐specific biopsy examination results. This information typically would be considered by a physician when carrying out a manual tumor delineation. Materials and methods: Our study involves 40 patients from two centers: 23 patients from the University Hospital Leuven (Leuven), Leuven, Belgium and 17 patients from the Netherlands Cancer Institute (NKI), Amsterdam, the Netherlands. All patients received a mp‐MRI exam consisting of a T2‐weighted, diffusion‐weighted, and dynamic contrast‐enhanced MRI before prostatectomy. Thirty‐one features were extracted for each voxel in the prostate. Among these, 29 were from the multiparametric‐MRI, one was from the population‐based tumor probability atlas and one from the biopsy map. T2‐weighted images of each patient were registered to whole‐mount section pathology slices to obtain the ground truth. The study was validated in two settings: single‐center (training and test sets were from the same cohort); and cross‐center (training and test sets were from different cohorts). In addition, automatic delineations created by our model were compared with manual tumor delineations done by six different teams on a subset of Leuven cohort including 15 patients. Results: In the single‐center setting, mp‐MRI‐based features yielded area under the ROC curves (AUC) of 0.690 on a pooled set of patients from both cohorts. Including prevalence into mp‐MRI‐based features increased the AUC to 0.751 and including all features achieved the best performance with AUC of 0.775. Using all features always showed better results when varying the size of the training set. In addition, its performance is comparable with the average performance of six teams delineating the tumors manually. The error rate using all features was 0.22. The two prior knowledge features ranked among the top four most important features out of the 31 features. In the cross‐center setting, combining all features also yielded the best performance in terms of the mean AUC of 0.777 on the pooled set of patients from both cohorts. In addition, the difference in performance between the single‐center setting and cross‐center setting was not significant. Conclusions: The results showed significant improvements when including prior knowledge features in addition to mp‐MRI‐based features in both single‐ and cross‐center settings.
Expression‐level dependent perturbation of cell proteostasis and nuclear morphology by aggregation‐prone polyglutamine proteins

We describe a gene expression system for use in mammalian cells that yields reproducible, inducible gene expression that can be modulated within the physiological range. A synthetic promoter library was generated from which representatives were selected that gave weak, intermediate‐strength or strong promoter activity. Each promoter resulted in a tight expression range when used to drive single‐copy reporter genes integrated at the same genome location in stable cell lines, in contrast to the broad range of expression typical of transiently transfected cells. To test this new expression system in neurodegenerative disease models, we used each promoter type to generate cell lines carrying single‐copy genes encoding polyglutamine‐containing proteins. Expression over a period of up to three months resulted in a proportion of cells developing juxtanuclear aggresomes whose rate of formation, penetrance, and morphology were expression‐level dependent. At the highest expression levels, fibrillar aggregates deposit close to the nuclear envelope, indicating that cell proteostasis is overwhelmed by misfolded protein species. We also observed expression‐level dependent, abnormal nuclear morphology in cells containing aggresomes, with up to ∼80% of cells affected. This system constitutes a valuable tool in gene regulation at different levels and allows the quantitative assessment of gene expression effects when developing disease models or investigating cell function through the introduction of gene constructs. Biotechnol. Bioeng. 2015;112: 1883–1892. © 2015 Wiley Periodicals, Inc.
Fast Scan-Chain Ordering for 3-D-IC Designs Under Through-Silicon-Via (TSV) Constraints

This brief addresses the problem of scan-chain ordering under a limited number of through-silicon vias (TSVs), and proposes a fast two-stage algorithm to compute a final order of scan flip-flops. To enable 3-D optimization, a greedy algorithm, multiple fragment heuristic, is modified and combined with a dynamic closest-pair data structure, FastPair, to derive a good initial solution in stage one. Stage two initiates two local refinement techniques, 3-D planarization and 3-D relaxation, to reduce the wire (and/or power) cost and to relax the number of TSVs in use to meet TSV constraints, respectively. Experimental results show that the proposed algorithm results in comparable performance (in terms of wire cost only, power cost only, and both wire-and-power cost) to a genetic-algorithm method but runs two-order faster, which makes it practical for TSV-constrained scan-chain ordering for 3-D-IC designs.
Automated Lane Detection in Crowds using Proximity Graphs

Studying the behavior of crowds is vital for understanding and predicting human interactions in public areas. Research has shown that, under certain conditions, large groups of people can form collective behavior patterns: local interactions between individuals results in global movements patterns. To detect these patterns in a crowd, we assume each person is carrying an on-body device that acts a local proximity sensor, e.g., smartphone or bluetooth badge, and represent the texture of the crowd as a proximity graph. Our goal is extract information about crowds from these proximity graphs. In this work, we focus on one particular type of pattern: lane formation. We present a formal definition of a lane, proposed a simple probabilistic model that simulates lanes moving through a stationary crowd, and present an automated lane-detection method. Our preliminary results show that our method is able to detect lanes of different shapes and sizes. We see our work as an initial step towards rich pattern recognition using proximity graphs.
Wireless techniques for capacity enhancement of broadcast and multicast for UMTS networks

Hybrid space-time coding plus adaptive antenna (beamforming) schemes have being researched because of their large increase of capacity. The association with multiple input multiple output (MIMO) channels has also being analysed. The paper shows the enhancement of BER performance and capacity of the future broadband UMTS network air interface, based on the combination of different wireless techniques, namely, beamforming, space-time coding, MIMO systems and adaptive coding/modulation schemes. Link and system level simulations of a real scenario were carried out to evaluate the capacity gain.
A hybrid system approach to kinematic modelling of mutlifingered hand's finger gaits

Large-scale motion of the grasped object is one of the tasks, which is involved in practical dextrous manipulation of multifingered robotic hand. When the large-scale motion can not be accomplished only by rolling and sliding of the finger, finger gaiting, or regrasping, is used. In this paper, we propose a joint space representation of grasps, which represents a stable grasp by a set of joints values with several grasping constraints. Using primitives describing the regrasping process with the joint space representation, we build a kinematic model of finger gaiting as a hybrid automaton. In this model, all grasping constraints are involved. Finally, simulation results verify the validity and efficiency of the model
Personality, Culture, and Organization

In a previous paper, the links between executive personality and the strategic and organizational orientations of troubled firms were examined. In the present paper, original typologies of neurotic styles and corporate pathology are used, but the two are related using the concept of organizational culture which provides a useful vehicle for linking personality with strategy. In the previous paper it was argued that the personality of the top executive could influence strategy only in centralized firms; now, it is believed that through culture this can happen even in decentralized organizations. Several sets of hypotheses are generated to formalize this position.