Miracle-dz/UniFAR-FTUs huggingface dataset:
Versão reduzida da escala portuguesa de afeto positivo e negativo - PANAS-VRP: Análise fatorial confirmatória e invariância temporal

Embora a Positive and Negative Affect Schedule (PANAS: Watson, Clark, & Tellegen, 1988) seja uma escala parcimoniosa, varios autores referem a necessidade de desenvolver versoes reduzidas da escala. Este estudo desenvolveu uma versao portuguesa reduzida da PANAS portuguesa (adaptada por Galinha & Ribeiro, 2005), analisou a sua estrutura fatorial e testou a invariância temporal, num intervalo de dois meses. Uma amostra de 245 participantes adultos, no ensino superior e em formacao profissional, foi recolhida e replicada com dois meses de intervalo. A nova versao reduzida da PANAS portuguesa (PANAS-VRP) foi posteriormente analisada numa segunda amostra de 535 estudantes universitarios. Os resultados mostram que embora a estrutura da PANAS-VRP se tenha revelado variavel entre as duas amostras do estudo (o que pode ser explicado pelos pressupostos teoricos da escala), apresentou boas caracteristicas psicometricas em ambas as amostras. A PANAS-VRP revelou ainda invariância temporal num intervalo de dois meses e uma correlacao elevada com a versao integral da escala, nas duas amostras, indicando que ambas as versoes estao a medir os mesmos constructos.
Connecting Participatory Methods in a Study of Older Lesbian and Gay Citizens in Rural Areas

The aim in this paper is to present a discussion of the participatory research methods employed to explore intersectionality between sexuality, rurality and age through consideration of a research project investigating how older lesbian and gay citizens in rural southwest England and Wales interact with their local community. The aim of the project is to explore how older lesbian and gay citizens adjust to and connect with their rural environment, exploring the notion of a “rural idyll” for groups who may be seen as different. Discussion of the different methods used to explore themes surrounding connectivity, place, space and identity will be offered. These include a core biographic narrative interpretive method (BNIM), a visual ethnographic method, and an overarching participatory methodology. This methodological approach is reviewed using the six principles for working with disempowered groups identified by Whitmore and McGee (2001).
ICT and the future of healthcare: Aspects of pervasive health monitoring

ABSTRACT Along with the digital revolution, information and communication technology applications are currently transforming the delivery of health and social care services. This paper investigates prevailing opinions toward future technology-based healthcare solutions among Austrian healthcare professionals. During a biphasic online Delphi survey, panelists rated expected outcomes of two future scenarios describing pervasive health monitoring applications. Experts perceived that the scenarios were highly innovative, but only moderately desirable, and that their implementation could especially improve patients’ knowledge, quality of healthcare, and living standard. Contrarily, monetary aspects, technical prerequisites, and data security were identified as key obstacles. We further compared the impact of professional affiliation. Clearly, opinions toward pervasive healthcare differed between the interest groups, medical professionals, patient advocates, and administrative personnel. These data suggest closer collaborations between stakeholder groups to harmonize differences in expectations regarding pervasive health monitoring.
Echocardiography-Guided Left Ventricular Lead Placement for Cardiac Resynchronization Therapy: Results of the Speckle Tracking Assisted Resynchronization Therapy for Electrode Region Trial

Background—Cardiac resynchronization therapy improves mortality and morbidity in patients with heart failure (HF) with wide QRS complex and diminished left ventricular (LV) function, but response is variable. Methods and Results—The Speckle Tracking Assisted Resynchronization Therapy for Electrode Region (STARTER) was a prospective, double-blind, randomized controlled trial testing the hypothesis that an incremental benefit to cardiac resynchronization therapy would be gained by echo-guided (EG) transvenous LV lead placement versus a routine fluoroscopic approach. EG LV lead placement was attempted at the site of latest time to peak radial strain by speckle tracking echocardiography. The prespecified primary end point was first HF hospitalization or death. Of 187 New York Heart Association class II to IV patients with HF (62% ischemic; ejection fraction 26±6%; QRS 159±27 ms), 110 were randomized to EG and 77 to routine strategies. Primary events included 30 deaths and 37 HF hospitalizations over 1.8 years. Using intention-to-treat, patients randomized to an EG strategy had a significantly more favorable event-free survival (hazard ratio, 0.48; 95% confidence interval, 0.28–0.82; P=0.006). Exact or adjacent concordance of LV lead with latest site could be achieved in 85% of the EG group and occurred fortuitously in 66% of controls (P=0.010) and was associated with an improvement in event-free survival (hazard ratio, 0.40; 95% confidence interval, 0.22–0.71; P=0.002). Conclusions—A strategy of EG LV lead placement for cardiac resynchronization therapy improved patient outcomes by reducing the combined risk of death or HF hospitalizations and has implications for delivery of cardiac resynchronization therapy. Clinical Trial Registration—URL: http://www.clinicaltrials. gov. Unique identifier: NCT00156390.
Large-scale and drift-free surface reconstruction using online subvolume registration

Depth cameras have helped commoditize 3D digitization of the real-world. It is now feasible to use a single Kinect-like camera to scan in an entire building or other large-scale scenes. At large scales, however, there is an inherent challenge of dealing with distortions and drift due to accumulated pose estimation errors. Existing techniques suffer from one or more of the following: a) requiring an expensive offline global optimization step taking hours to compute; b) needing a full second pass over the input depth frames to correct for accumulated errors; c) relying on RGB data alongside depth data to optimize poses; or d) requiring the user to create explicit loop closures to allow gross alignment errors to be resolved. In this paper, we present a method that addresses all of these issues. Our method supports online model correction, without needing to reprocess or store any input depth data. Even while performing global correction of a large 3D model, our method takes only minutes rather than hours to compute. Our model does not require any explicit loop closures to be detected and, finally, relies on depth data alone, allowing operation in low-lighting conditions. We show qualitative results on many large scale scenes, highlighting the lack of error and drift in our reconstructions. We compare to state of the art techniques and demonstrate large-scale dense surface reconstruction “in the dark”, a capability not offered by RGB-D techniques.
Soft-Input Soft-Output List Sphere Detection with a Probabilistic Radius Tightening

In this paper, we present a low-complexity list sphere detection algorithm for achieving near-optimal a posteriori probability (APP) detection in an iterative detection and decoding (IDD). Motivated by the fact that the list sphere decoding searching a fixed number of candidates is computationally inefficient in many scenarios, we design a criterion to search lattice points with non-vanishing likelihood and then derive a hypersphere radius satisfying this condition. Further, in order to exploit the original sphere constraint as it is instead of using necessary conditioned version, we combine a probabilistic tree pruning strategy and the proposed list sphere search. Two features, tightened hypersphere radius and probabilistic tree pruning, collaborate and improve the search efficiency in a complementary fashion. Through simulations on 4x4 MIMO system, we show that the proposed method provides substantial reduction in complexity while achieving negligible performance loss over the conventional list sphere detection.
Home-based treadmill training for individuals with Parkinson’s disease: a randomized controlled pilot trial

Objective: To investigate the feasibility and effectiveness of six weeks of home-based treadmill training in people with mild Parkinson’s disease. Design: Pilot randomized controlled trial of a six-week intervention followed by a further six weeks follow-up. Setting: Home-based treadmill training with outcome measures taken at a hospital clinic. Participants: Twenty cognitively intact participants with mild Parkinson’s disease and gait disturbance. Two participants from the treadmill training group and one from the control group dropped out. Interventions: The treadmill training group undertook a semi-supervised home-based programme of treadmill walking for 20–40 minutes, four times a week for six weeks. The control group received usual care. Main outcome measures: The feasibility of the intervention was assessed by recording exercise adherence and acceptability, exercise intensity, fatigue, muscle soreness and adverse events. The primary outcome measure of efficacy was walking capacity (6-minute walk test distance). Results: Home-based treadmill training was feasible, acceptable and safe with participants completing 78% (SD 36) of the prescribed training sessions. The treadmill training group did not improve their walking capacity compared to the control group. The treadmill training group showed a greater improvement than the control group in fatigue at post test (P = 0.04) and in quality of life at six weeks follow-up testing (P = 0.02). Conclusions: Semi-supervised home-based treadmill training is a feasible and safe form of exercise for cognitively intact people with mild Parkinson’s disease. Further investigation regarding the effectiveness of home-based treadmill training is warranted.
Barcelona Media SMT system description for the IWSLT 2009

This paper describes the Barcelona Media SMT system in the IWSLT 2009 evaluation campaign. The Barcelona Media system is an statistical phrase-based system enriched with source context information. Adding source context in an SMT system is interesting to enhance the translation in order to solve lexical and structural choice errors. The novel technique uses a similarity metric among each test sentence and each training sentence. First experimental results of this technique are reported in the Arabic and Chinese Basic Traveling Expression Corpus (BTEC) task. Although working in a single domain, there are ambiguities in SMT translation units and slight improvements in BLEU are shown in both tasks (Zh2En and Ar2En).
Parallel Computing for Accelerated Texture Classification with Local Binary Pattern Descriptors using OpenCL

In this paper, a novel parallelized implementation of rotation invariant texture classification using Heterogeneous Computing Platforms like CPU and Graphics Processing Unit (GPU) is proposed. A complete modeling of the LBP operator as well as its improvised versions of Complete Local Binary Patterns (CLBP) and Multi-scale Local Binary Patterns (MLBP) has been developed on a CPU and GPU based Heterogeneous computing platforms using OpenCL. The tests using these feature descriptors of Local Binary Pattern (LBP) algorithms and their parallelized implementation using OpenCL were also performed. Significant Improvement in computation speed is achieved over traditional CPU-based algorithms. To test the accuracy of the GPU implemented algorithms a set of textures were classified using selected LBP, CLBP and MLBP descriptors. Classification was performed by applying these descriptors to several unique texture classes at various spatial resolutions and rotations. The primary focus of this paper is to provide an overview of these algorithms, demonstrate observed performance gains and to verify the validity of using these descriptors for texture analysis on a CPU and GPU based Heterogeneous Platform.
Proximity-Based Clustering: A Search for Structural Consistency in Data With Semantic Blocks of Features

A class of clustering problems that is studied here is concerned with the development of a structure of a global nature given a collection of structures (clusters) constructed locally for data that are represented by several collections (blocks) of features. These blocks of features come with a well-defined semantics. For instance, in spatiotemporal data, a certain block of features concerns a spatial component of the data (say, x-y or x-y-z coordinates), while another one deals with the features that describe time series associated with the corresponding locations. The results of clustering that are being produced locally are reconciled by minimizing a distance between the proximity matrices that are formed at the higher conceptual level and induced by the individual partition matrices. The optimization problem is formulated and presented along with its iterative scheme.
Application of augmented reality to industrial tele-training

Augmented Reality (AR) is a departure from standard virtual reality in a sense that it allows users to see computer generated virtual objects superimposed over the real world through the use of see-through head-mounted display. Users of such system can interact in the real/virtual world using additional information, such as 3D virtual models and instructions on how to perform these tasks in the form of video clips, annotations, speech instructions, and images. In this paper, we describe a prototype of a collaborative industrial Tele-training system. The distributed aspect of this system will enable users on remote sites to collaborate on training tasks by sharing the view of the local user equipped with a wearable computer. The users can interactively manipulate virtual objects that substitute real objects allowing the trainee to try out and discuss the various tasks that needs to be performed. Experimental results are presented.
The Different Meanings of Food in Chinese Patients Suffering from Anorexia Nervosa

Abstract The metaphoric meanings of food have cast new lights on Social Work intervention with Chinese patients suffering from anorexia nervosa (AN) and their families. Hitherto, there is inadequate documentation on the different meanings of food in families with a daughter suffering from AN in a Chinese context. To fill this knowledge gap, this article reports the 3-year clinical observations of a sample of 34 adolescents and young women suffering from AN, as well as their families under family treatment. These observations show that food can be conceptualized in the following ways: (1) eating as an expression of filial piety; (2) food preparation as part of the woman's nurturing role; (3) self-starvation as refusal to grow up; (4) self-starvation as struggle for autonomy; (5) assignment of food as part of the family hierarchy; and (6) assignment of food as part of parental control. Its implications for clinical social work practice and the roles of social workers in helping are discussed.
Reduction of immunogenicity by covalent modification of murine and rabbit immunoglobulins with oxidized dextrans of low molecular weight.

This communication describes the covalent modification of monoclonal and polyclonal antibodies with oxidized dextrans of low molecular weight to generate conjugates having low immunogenicity in vivo. Conjugation conditions were optimized to generate monomeric, dextran-modified antibodies, free of both high-molecular-weight polymeric aggregates and unmodified antibodies. Conjugates could be prepared with varying levels of dextran substitution. These conjugates retained optimal immunoreactivity as well as in vivo pharmacokinetics and tumor-localization properties. In addition, multiple i.v. administrations of dextran-modified antibodies in animals did not elicit a measurable immune response to either the antibody or the dextran portion of these conjugates.
Chlamydomonas Kinesin-II–dependent Intraflagellar Transport (IFT): IFT Particles Contain Proteins Required for Ciliary Assembly in Caenorhabditis elegans Sensory Neurons

We previously described a kinesin-dependent movement of particles in the flagella of Chlamydomonas reinhardtii called intraflagellar transport (IFT) (Kozminski, K.G., K.A. Johnson, P. Forscher, and J.L. Rosenbaum. 1993. Proc. Natl. Acad. Sci. USA. 90:5519–5523). When IFT is inhibited by inactivation of a kinesin, FLA10, in the temperature-sensitive mutant, fla10, existing flagella resorb and new flagella cannot be assembled. We report here that: (a) the IFT-associated FLA10 protein is a subunit of a heterotrimeric kinesin; (b) IFT particles are composed of 15 polypeptides comprising two large complexes; (c) the FLA10 kinesin-II and IFT particle polypeptides, in addition to being found in flagella, are highly concentrated around the flagellar basal bodies; and, (d) mutations affecting homologs of two of the IFT particle polypeptides in Caenorhabditis elegans result in defects in the sensory cilia located on the dendritic processes of sensory neurons. In the accompanying report by Pazour, G.J., C.G. Wilkerson, and G.B. Witman (1998. J. Cell Biol. 141:979–992), a Chlamydomonas mutant (fla14) is described in which only the retrograde transport of IFT particles is disrupted, resulting in assembly-defective flagella filled with an excess of IFT particles. This microtubule- dependent transport process, IFT, defined by mutants in both the anterograde (fla10) and retrograde (fla14) transport of isolable particles, is probably essential for the maintenance and assembly of all eukaryotic motile flagella and nonmotile sensory cilia.
Fast algorithms for maximizing submodular functions

There has been much progress recently on improved approximations for problems involving submodular objective functions, and many interesting techniques have been developed. However, the resulting algorithms are often slow and impractical. In this paper we develop algorithms that match the best known approximation guarantees, but with significantly improved running times, for maximizing a monotone submodular function f: 2[n] → R+ subject to various constraints. As in previous work, we measure the number of oracle calls to the objective function which is the dominating term in the running time. Our first result is a simple algorithm that gives a (1--1/e -- e)-approximation for a cardinality constraint using O(n/e log n/e) queries, and a 1/(p + 2e + 1 + e)-approximation for the intersection of a p-system and e knapsack (linear) constraints using O (n/e2 log2 n/e) queries. This is the first approximation for a p-system combined with linear constraints. (We also show that the factor of p cannot be improved for maximizing over a p-system.) The main idea behind these algorithms serves as a building block in our more sophisticated algorithms. Our main result is a new variant of the continuous greedy algorithm, which interpolates between the classical greedy algorithm and a truly continuous algorithm. We show how this algorithm can be implemented for matroid and knapsack constraints using O(n2) oracle calls to the objective function. (Previous variants and alternative techniques were known to use at least O(n4) oracle calls. ) This leads to an O(n2/e4 log2 n/e)-time (1--1/e -- e)-approximation for a matroid constraint. For a knapsack constraint, we develop a more involved (1--1/e -- e)-approximation algorithm that runs in time O(n2(1/e log n)poly(1/e)).
Eliminating motion artifacts from fabric-mounted wearable sensors

Sensors embedded into clothing for measuring human movement are becoming more widespread in research, with applications in clinical diagnostics or rehabilitation studies. A major issue with their use is the undesired effect of fabric motion artifacts corrupting movement signals. This paper presents a method for learning body movements, viewing the undesired motion as stochastic perturbations to the sensed motion, and utilising errors-in-variables models to eliminate these errors in the learning process. Experiments, both in simulation and with a physical fabric-mounted sensor, indicate improved prediction accuracy as compared to standard learning methods.
A survey on resource allocation strategies in cloud computing

Cloud computing provides user-requested services that are reliable, dynamic, flexible and efficient. In order to offer such guaranteed services to cloud users, effective resource allocation strategies must be implemented. The methodology used should also confirm to the Service Level Agreement (SLA) drawn between the customer and the service provider. This work presents a study of such resource allocation strategies in cloud computing. The strategies include resource requirements prediction algorithms and resource allocation algorithms. This works studies the various resource allocation techniques utilized in cloud computing and makes a comparative study of the merits and demerits of each technique. This study aims to identify an efficient resource allocation strategy that utilizes resources effectively in the resource constrained environment of cloud computing.
Bionemo: molecular information on biodegradation metabolism

Bionemo (http://bionemo.bioinfo.cnio.es) stores manually curated information about proteins and genes directly implicated in the Biodegradation metabolism. When possible, the database includes information on sequence, domains and structures for proteins; and sequence, regulatory elements and transcription units for genes. Thus, Bionemo is a unique resource that complements other biodegradation databases such as the University of Minessota Biocatalysis/Biodegradation Database, or Metarouter, which focus more on the biochemical aspects of biodegradation than in the nature of the biomolecules carrying out the reactions. Bionemo has been built by manually associating sequences database entries to biodegradation reactions, using the information extracted from published articles. Information on transcription units and their regulation was also extracted from the literature for biodegradation genes, and linked to the underlying biochemical network. In its current version, Bionemo contains sequence information for 324 reactions and transcription regulation information for more than 100 promoters and 100 transcription factors. The information in the Bionemo database is available via a web server and the full database is also downloadable as a PostgresSQL dump. To facilitate the programmatic use of the information contained in the database, an object-oriented Perl API is also provided.
Convex programming based robust localization in NLOS prone cluttered environments

In a large variety of industrial scale processes, fixed or mobile sensors are typically deployed in large-scale vessels to monitor parameters such as temperature, pressure and chemical concentration. When these vessels are cluttered with obstacles, e.g. large cooling ponds cluttered with nuclear waste containers, it becomes increasingly difficult for the sensors to estimate their position. The acoustic ranging signals used for estimating distances between each sensor node and reference nodes fixed to the vessel infrastructure can suffer from Non-Line-Of-Sight (NLOS) signal propagation and thus introduce large positive errors in some of the estimated distances. In this paper we present a robust localization algorithm for localizing sensors in cluttered NLOS environments. We show that if the number of erroneous range measurements is less than half, it is possible to accurately estimate these NLOS errors at each sensor node by solving a convex optimization problem. Each sensor node can then use its estimate of NLOS errors to accurately localize itself. Our approach is completely independent of the physical hardware used to perform range measurements and thus can be used to localize sensor nodes in any NLOS prone environment. We demonstrate this with the help of experimental results with three different hardware platforms each employing a different ranging mechanism.