Miracle-dz/UniFAR-FTUs huggingface dataset:
The effect of visual training for patients with visual field defects due to brain damage: a systematic review

The objective of this review was to evaluate whether systematic visual training leads to (1) a restitution of the visual field (restoration), (2) an increase in the visual search field size or an improvement in scanning strategies (compensation) and (3) a transfer of training-related improvements in activities of daily living such as reading. To retrieve relevant publications, computer-aided searches of databases (Medline, Embase, Cinahl, Cochrane Central Registers of Controlled Trials) and extensive reference tracing and hand searching were performed. Subsequently, all retrieved and blinded studies were scored on methodological quality. 14 studies were included, 2 randomised controlled trials (RCTs) and 12 within-subject repeated-measures designs (RMD). One of the two RCT studies had good quality. The internal validity of the RMD studies varied from poor to good. Five studies reported a significant effect of the vision restoration therapy (VRT), whereas two studies reported no effect using scanning laser ophthalmoscopy or Goldmann perimetry as outcome measure. All authors of the studies on scanning compensatory therapy (SCT) found a significant effect of up to 30° visual search field, a significant increase in reading speed or decrease in reading errors. It is unclear to what extent patients benefit from restoration therapy in relation to a more efficient scanning strategy which enables them to read faster or to avoid obstacles in a better way. No study has given a satisfactory answer. SCT seems to provide a more successful rehabilitation with more simple and user-friendly training techniques. Validated questionnaires provide the most reliable subjective data to assess the transfer of the relevance of training procedures to activities of daily living of the patient. Hence, SCT is recommended until the effect of the VRT is defined.
Cooperative beamforming and relay selection in cognitive radio systems

In this paper, a new scheme is suggested for cooperative beamforming (BF) and relay selection in CR networks, where a pair of secondary users communicates with each other assisted by some multiple antenna relay nodes. The goal of the algorithm is to maximize signal to interference plus noise ratio of secondary user receiver subject to limited interference caused for primary user receiver and power constraints of relay nodes. The relay selection and BF optimization problem is solved separately by employing convex semidefinite programming through rank‐one relaxation. It is shown that our proposed algorithm outperforms conventional relay selection and BF schemes. Copyright © 2014 John Wiley & Sons, Ltd.
Towards a fully integrated, wirelessly powered, and ordinarily equipped on-lens system for successive dry eye syndrome diagnosis

This paper presents a smart contact lens (SCL) sensor system for successive evaluation of tear evaporation. The proposed SCL system integrated with 3D technology is composed of tunable sensitivity sensor-readout circuitry, a tear sensor, and an antenna, and is embedded into a biocompatible hydrogel-based contact lens by a commercial manufacturing process. Moreover, the on-lens system can be addressed using commercial radio-frequency identification (RFID) reader devices for sensor control and data communication. Subjects can wear the SCL for continuous tear-content monitoring. Furthermore, the recordings from the device can provide high distinguishability in different tear phantoms using a variation of capacitance or resistance rather than using the weight loss.
Predicting processor performance with a machine learnt model

Architectural simulators are traditionally used to study the design trade-offs for processor systems. The simulators are implemented in a high-level programming language or a hardware descriptive language, and are used to estimate the system performance prior to the hardware implementation. The simulations, however, may need to run for long periods of time for even a small set of design variations. In this paper, we propose a machine learnt (neural network/NN) model for estimating the execution performance of a superscalar processor. Multiple runs for the model are finished in less than a few milliseconds as compared to days or weeks required for simulation-based methods. The model is able to predict the execution throughput of a processor system with over 85% accuracy when tested with six SPEC2000 CPU integer benchmarks. The proposed model has possible applications in computer architecture research and teaching.
Market Forces and Indigenous Resistance Paradigms

The pervasive force in the relationship between the nation-state and Australian Indigenous peoples during the 1990s and 2000s was, and is, neoliberalism. Free market ideals became the dominant political philosophy and Indigenous people were coerced into a political ‘experimental’ cutting of a neoliberal template into the fabric of Indigenous life. The pairing of market ideology with concerted efforts to de-power Indigenous groups and people align, at least thematically, the Indigenous experience of neoliberalism with that of a social movement. This article details the entwined story of explicit Indigenous resistance and activism and the how and what of the infiltration of market forces into Aboriginal territory. Empirically, it demonstrates the neoliberal infrastructure and ideological rationale for the explicit undermining of Indigenous rights and presence within Australian society and the Indigenous parameters of resistance that emerged to confront and defy the re-confining and redefining pressures of neoliberalism: an Indigenous resistance paradigm. Theoretically, these facets are analysed through the frame of the ‘domain of Aboriginality’ to articulate the broader contours of the reach of neoliberalism into Indigenous lives and the resistance to the developing hegemony.
Populations of aspen (Populus tremuloides Michx.) with different evolutionary histories differ in their climate occupancy

Abstract Quaking aspens (Populus tremuloides Michx.) are found in diverse habitats throughout North America. While the biogeography of aspens' distribution has been documented, the drivers of the phenotypic diversity of aspen are still being explored. In our study, we examined differences in climate between northern and southwestern populations of aspen, finding large‐scale differences between the populations. Our results suggest that northern and southwestern populations live in distinct climates and support the inclusion of genetic and phenotypic data with species distribution modeling for predicting aspens' distribution.
Learner Centred Development of a Mobile and iTV Language Learning Support System

Interactive television (iTV) is a new media technology that has great potential for supporting second language learning, particularly for independent adult learners. It has many characteristics demanded by modern second language (L2) learning theories and is technologically quite sophisticated. However, in order for it to succeed it needs to fit in with these learners’ approaches to media use in language learning. While there is an extensive literature on many other aspects of language learning and teaching, particularly in classroom settings, we know surprisingly little about the independent adult language learner's attitudes and approaches to learning and to technologies for supporting it. In this paper, we describe a project to develop language learning via interactive television (iTV) where a focus group study has been used to elicit the attitudes of potential users in order to direct the design process using a use-case scenario. We present the design implications that emerged from the focus group, broadly suggesting the use of mobile phone in conjunction with iTV to facilitate informal language learning from up-to-date authentic materials broadcast on television
A Real-Time, Multiview Fall Detection System: A LHMM-Based Approach

Automatic detection of a falling person in video sequences has interesting applications in video-surveillance and is an important part of future pervasive home monitoring systems. In this paper, we propose a multiview approach to achieve this goal, where motion is modeled using a layered hidden Markov model (LHMM). The posture classification is performed by a fusion unit, merging the decision provided by the independently processing cameras in a fuzzy logic context. In each view, the fall detection is optimized in a given plane by performing a metric image rectification, making it possible to extract simple and robust features, and being convenient for real-time purpose. A theoretical analysis of the chosen descriptor enables us to define the optimal camera placement for detecting people falling in unspecified situations, and we prove that two cameras are sufficient in practice. Regarding event detection, the LHMM offers a principle way for solving the inference problem. Moreover, the hierarchical architecture decouples the motion analysis into different temporal granularity levels, making the algorithm able to detect very sudden changes, and robust to low-level steps errors.
Predicting Risk of Placement: A Population-based Study of Out-of-Home Placement, Child Maltreatment, and Emergency Housing

Guided by a developmental epidemiology framework, this study examines the extent to which first experiences of child maltreatment and use of emergency housing are predictive of out-of-home placement in early childhood. The study sample is a population of 12,045 second-grade students in a large, urban school district. Information on birth, maternal, and social risk factors was obtained and linked through an integrated data system. Life table analyses were used to develop a descriptive picture of the timing of first out-of-home placement experience. Findings demonstrate that children are most likely to experience a first out-of-home placement during their first year of life. Cox regression analyses are used to examine the extent to which variables for risk factors (specifically child maltreatment and use of emergency housing) predict the first out-of-home placement experience while controlling for demographics, birth risks, and maternal risks. Results demonstrate that children with histories of child maltreatment or emergency housing use are more likely than peers without such histories to be placed in out-of-home care. Further, children with histories of both child maltreatment and emergency housing use are less likely to be placed in out-of-home care than children who have experienced either child maltreatment or emergency housing use (but not both). Findings point to the importance of interagency collaboration and a focus on young children for addressing the needs of vulnerable young children and their families.
Polynomial Depth, Highness and Lowness for E

We study the relations between the notions of highness, lowness and logical depth in the setting of complexity theory. We introduce a new notion of polynomial depth based on time bounded Kolmogorov complexity. We show our polynomial depth notion satisfies all basic logical depth properties, namely neither sets in P nor sets random for EXP are polynomial deep, and only polynomial deep sets can polynomially Turing compute a polynomial deep set. We prove all EXP- complete sets are poly-deep, and under the assumption that NP does not have p-measure zero, then NP contains a polynomial deep set. We show that every high set for E contains a polynomial deep set in its polynomial Turing degree, and that there exists low for E polynomial deep sets.
Functional bowel disorders and functional abdominal pain

The Rome diagnostic criteria for the functional bowel disorders and functional abdominal pain are used widely in research and practice. A committee consensus approach, including criticism from multinational expert reviewers, was used to revise the diagnostic criteria and update diagnosis and treatment recommendations, based on research results. The terminology was clarified and the diagnostic criteria and management recommendations were revised. A functional bowel disorder (FBD) is diagnosed by characteristic symptoms for at least 12 weeks during the preceding 12 months in the absence of a structural or biochemical explanation. The irritable bowel syndrome, functional abdominal bloating, functional constipation, and functional diarrhea are distinguished by symptom-based diagnostic criteria. Unspecified FBD lacks criteria for the other FBDs. Diagnostic testing is individualized, depending on patient age, primary symptom characteristics, and other clinical and laboratory features. Functional abdominal pain (FAP) is defined as either the FAP syndrome, which requires at least six months of pain with poor relation to gut function and loss of daily activities, or unspecified FAP, which lacks criteria for the FAP syndrome. An organic cause for the pain must be excluded, but aspects of the patient’s pain behavior are of primary importance. Treatment of the FBDs relies upon confident diagnosis, explanation, and reassurance. Diet alteration, drug treatment, and psychotherapy may be beneficial, depending on the symptoms and psychological features.
MAP Complexity Results and Approximation Methods

MAP is the problem of nding a most probable instantiation of a set of variables in a Bayesian network, given some evidence. MAP appears to be a signi cantly harder problem than the related problems of computing the probability of evidence (Pr), or MPE (a special case of MAP). Because of the complexity of MAP, and the lack of viable algorithms to approximate it, MAP computations are generally avoided by practitioners. This paper investigates the complexity of MAP. We show that MAP is complete for NPPP. We also provide negative complexity results for elimination based algorithms. It turns out that MAP remains hard even when MPE, and Pr are easy. We show that MAP is NP-complete when the networks are restricted to polytrees, and even then can not be e ectively approximated. Because there is no approximation algorithm with guaranteed results, we investigate best effort approximations. We introduce a generic MAP approximation framework. As one instantiation of it, we implement local search coupled with belief propagation (BP) to approximate MAP. We show how to extract approximate evidence retraction information from belief propagation which allows us to perform e cient local search. This allows MAP approximation even on networks that are too complex to even exactly solve the easier problems of computing Pr or MPE. Experimental results indicate that using BP and local search provides accurate MAP estimates in many cases.
Book review: Organizational Learning at NASA: The Challenger and Columbia Accidents. J. G. Mahler with M. H. Casamayou. Washington, DC: Georgetown University Press, 2009. 238 pp. ISBN 9781589012660

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Characterization of Juquitiba Virus in Oligoryzomys fornesi from Brazilian Cerrado

The Juquitiba virus, an agent of Hantavirus Cardiopulmonary Syndrome, is one of the most widely distributed hantavirus found in South America. It has been detected in Oligoryzomys nigripes, Akodon montensis, Oxymycterus judex, Akodon paranaensis in Brazil and in O. nigripes, Oryzomys sp. and Oligoryzomys fornesi rodents in Argentine, Paraguay and Uruguay. Here, we report the genomic characterization of the complete S segment from the Juquitiba strain, isolated from the lung tissues of O. fornesi, the presumed rodent reservoir of Anajatuba virus in Brazilian Amazon, captured in the Cerrado Biome, Brazil.
An exploratory study of knowledge strategy in a knowledge-intensive firm using a strategy-as-practice approach

We analyse the knowledge strategy (Zack 1999, 2002) in a knowledge-intensive firm, using a Strategy-as-Practice approach (Whittington 1996, 2006), two major research fields in Strategic and Knowledge Management. In order to provide a relevant research field to our investigation, we study the development of the knowledge strategy at one of the leading consultant firms in the fields of strategy as well as knowledge management. First, we explain the Knowledge Strategy framework proposed by Zack (2002). Then, we focus on our research methodology, mainly the approach of Strategy-as-Practice. Thirdly, we present our main analysis results, identifying the key actors of knowledge strategizing and how they are organised to do it. A process view of knowledge strategy is presented identifying key actors, practices and organizational structures. A conclusion of our study is that the conceptualization of knowledge strategy and knowledge gaps does effectively exist in reality. Finally, we discuss the limitations of the present research and propose further research directions and development. This paper explores a new research approach of knowledge management, and could also help knowledge management practitioners.
Nearly-repetitive video synchronisation using nonlinear manifold embedding

This paper introduces a new method for synchronising nearly repetitive video sequences using manifold embedding. The approach recovers the optimal correspondences between two frame sequences in the embedded space. The synchronised map is estimated based on the spatio-temporal extension of Isomap. It is evaluated using the TRECVID rushes video collection. The accuracy for repetitive shot synchronisation is scored using precision and recall of all generated edges on synchronised graph. We show that the approach significantly improves the embedding for repetitive manifolds over the well investigated methods such as multidimensional scaling, locally linear embedding, and the conventional Isomap.
Making Faces

In occupations that are premised on satisfying clients, competent workers need more than technical training. They must be able to both interpret (“read”) people and interact with them deftly. Through accurate character reading, workers altercast others, and thereby demonstrate their command of professional practice. This process is particularly significant for occupations that involve transformation of a client's public persona. To examine the dynamics by which workers read character, we examine the world of portrait painters. We focus on how portrait painters are socialized to the techniques and conventions provided in how-to manuals, intended to train novice portraitists on how to create successful portraits. We describe three processes that contribute to the presentation of a client in a portrait: the recognition of character, the presentation of character, and the negotiation of character.
Machine Recognition of Auslan Signs Using PowerGloves: Towards Large-Lexicon Recognition of Sign Lan

Instrumented gloves use a variety of sensors to provide information about the user's hand. They can be used for recognition of gestures; especially well-deened gesture sets such as sign languages. However, recognising gestures is a diicult task, due to intrapersonal and inter-personal variations in performing them. One approach to solving this problem is to use machine learning. In this case, samples of 95 discrete Australian Sign Language (Auslan) signs were collected using a Power-Glove. Two machine learning techniques were applied { instance-based learning (IBL) and decision-tree learning { to the data after some simple features were extracted. Accuracy of approximately 80 per cent was achieved using IBL, despite the severe limitations of the glove.
FusionAnalyser: a new graphical, event-driven tool for fusion rearrangements discovery

Gene fusions are common driver events in leukaemias and solid tumours; here we present FusionAnalyser, a tool dedicated to the identification of driver fusion rearrangements in human cancer through the analysis of paired-end high-throughput transcriptome sequencing data. We initially tested FusionAnalyser by using a set of in silico randomly generated sequencing data from 20 known human translocations occurring in cancer and subsequently using transcriptome data from three chronic and three acute myeloid leukaemia samples. in all the cases our tool was invariably able to detect the presence of the correct driver fusion event(s) with high specificity. In one of the acute myeloid leukaemia samples, FusionAnalyser identified a novel, cryptic, in-frame ETS2–ERG fusion. A fully event-driven graphical interface and a flexible filtering system allow complex analyses to be run in the absence of any a priori programming or scripting knowledge. Therefore, we propose FusionAnalyser as an efficient and robust graphical tool for the identification of functional rearrangements in the context of high-throughput transcriptome sequencing data.
Incentive Compatible Configuration for Wireless Multicast: A Game Theoretic Approach

Multicast and broadcast service (MBS) is a service offered by the base station (BS) to multiple receivers requesting the same information. Such a BS must be kept updated with the receivers' feedback information (e.g., packet loss rates) to configure the MBS. We propose MBS operation schemes that are dominant-strategy incentive compatible in game theory, i.e., the schemes induce dominant-strategy equilibria, where all selfish receivers reveal their true information. Moreover, the induced equilibria are Pareto efficient and max-min fair. To conclude, the proposed schemes can elicit true feedback information from the receivers, avoiding any manipulation and, thereby, ensuring an efficient and fair system operation.