Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of a school-based activity program on the motor skills, perceived physical competence, enjoyment and physical activity of adolescent girls: the Sport4Fun pilot randomised controlled trial

Objectives: The aim of this study was to assess the feasibility, acceptability and potential efficacy of a school-based intervention targeting improvement of motor skills to promote physical activity among low-fit adolescent females. Design: A six-month, 2-arm parallel-group, pilot randomised controlled trial was conducted in a co-educational high school in Sydney, Australia. Methods: Twenty secondary-school girls in Grades 7, 8, and 9, with a cardiorespiratory fitness in the lowest 30 percentile, were randomized to intervention or control group. The intervention comprised sex-specific motor skill activities delivered during school sport and sportsand fitness-based activities delivered after school. In addition, theory-based behaviour modification lessons were conducted during homeroom (roll call lessons). The control group received regular school sport and personal development lessons. Primary outcomes were accelerometer-measured physical activity and fundamental movement skill proficiency. Results: Compared with girls in the control group, girls in the intervention group showed a significantly greater increase in total weekday physical activity, a significantly smaller increase in weekday sedentary time and a non-significant greater improvement in fundamental movement skill proficiency. Conclusions: A multi-component school-based intervention can be feasible and potentially efficacious in promoting physical activity and movement skills among low-fit adolescent girls.
Gesture-recognition with Non-referenced Tracking

This paper presents 3motion, a novel 3D gesture interaction system consisting of a low-cost, lightweight hardware component and a general-purpose software development kit. The system provides gesture-based 3D interaction for situations where traditional tracking systems are too expensive or impractical due to the calibration and reference source requirements. The hardware component is built around a 3-axis linear accelerometer chip and transmits a continuous data stream to a host device via a wireless Bluetooth link. The software component receives this data and matches it against a library of 3D gestures to trigger actions. The system has been validated extensively with various example applications, including a “Battle of the Wizards” game, a character manipulation demonstrator, and a golf game implemented on a mobile phone.
Postprandial Chylomicron Clearance Rate in Late Teenagers with Diabetes Mellitus Type 1

A delayed chylomicron (CM) clearance rate, a known risk factor for atherosclerosis, has been described in adults with diabetes type 1 (DM1). We determined the CM clearance rate in late teenagers with DM1, and the relationship between CM clearance rate and elevated plasma lipid concentrations in DM1 teenagers in poor metabolic control (as characterized by HbA1c percentage). Plasma lipids and CM clearance were determined in nine patients with DM1 (mean age ± SD: 17.5 ± 0.6 y) and four healthy controls (mean age ± SD: 20.1 ± 0.8 y), by measuring breath 13CO2, plasma triglyceride, retinyl palmitate, and 13C-labeled oleic acid concentrations, after oral administration of a fat-rich meal together with vitamin A and 13C-oleic acid. In patients with DM1, fasting triglyceride and cholesterol concentrations were positively correlated with HbA1c percentage (p < 0.05). Neither in DM1 patients, nor in controls, was an elevated triglyceride concentration (above 1.7 mmol/L) found. Yet, in 22% of DM1 patients, cholesterol concentration was above 5.2 mmol/L, but not in any of the controls. CM clearance rate in DM1 patients was similar to that in controls and did not significantly correlate with HbA1c percentage. Fasting lipid concentrations in DM1 patients were not significantly correlated with CM clearance rate. Present data indicate that elevated lipid concentrations in late teenagers with DM1 are not attributable to a delay in CM clearance rate. A delayed CM clearance rate at late teenager age is not a risk factor contributing to the increased risk for atherosclerosis in DM1.
Cascade object detection with deformable part models

We describe a general method for building cascade classifiers from part-based deformable models such as pictorial structures. We focus primarily on the case of star-structured models and show how a simple algorithm based on partial hypothesis pruning can speed up object detection by more than one order of magnitude without sacrificing detection accuracy. In our algorithm, partial hypotheses are pruned with a sequence of thresholds. In analogy to probably approximately correct (PAC) learning, we introduce the notion of probably approximately admissible (PAA) thresholds. Such thresholds provide theoretical guarantees on the performance of the cascade method and can be computed from a small sample of positive examples. Finally, we outline a cascade detection algorithm for a general class of models defined by a grammar formalism. This class includes not only tree-structured pictorial structures but also richer models that can represent each part recursively as a mixture of other parts.
A region-based SLAM algorithm capturing metric, topological, and semantic properties

This paper proposes a SLAM algorithm based on FastSLAM 2.0 that maps features representing regions with a semantic type, topological properties, and an approximative geometric extent. The resulting maps enable spatial reasoning on a semantic level and provide abstract information allowing efficient semantic planning and a convenient interface for human-machine interaction. We present novel region features and an algorithm for estimating the feature parameters from uncertain measurements. In particular, we provide a means of estimating parameters even if the region feature is considerably larger than the robot's sensor range. Finally, we adapt the FastSLAM 2.0 algorithm to map the proposed features and show simulation-based results illustrating the capabilities of the proposed algorithm.
Once upon Multivariate Analyses: When They Tell Several Stories about Biological Evolution

Geometric morphometrics aims to characterize of the geometry of complex traits. It is therefore by essence multivariate. The most popular methods to investigate patterns of differentiation in this context are (1) the Principal Component Analysis (PCA), which is an eigenvalue decomposition of the total variance-covariance matrix among all specimens; (2) the Canonical Variate Analysis (CVA, a.k.a. linear discriminant analysis (LDA) for more than two groups), which aims at separating the groups by maximizing the between-group to within-group variance ratio; (3) the between-group PCA (bgPCA) which investigates patterns of between-group variation, without standardizing by the within-group variance. Standardizing within-group variance, as performed in the CVA, distorts the relationships among groups, an effect that is particularly strong if the variance is similarly oriented in a comparable way in all groups. Such shared direction of main morphological variance may occur and have a biological meaning, for instance corresponding to the most frequent standing genetic variation in a population. Here we undertake a case study of the evolution of house mouse molar shape across various islands, based on the real dataset and simulations. We investigated how patterns of main variance influence the depiction of among-group differentiation according to the interpretation of the PCA, bgPCA and CVA. Without arguing about a method performing ‘better’ than another, it rather emerges that working on the total or between-group variance (PCA and bgPCA) will tend to put the focus on the role of direction of main variance as line of least resistance to evolution. Standardizing by the within-group variance (CVA), by dampening the expression of this line of least resistance, has the potential to reveal other relevant patterns of differentiation that may otherwise be blurred.
Prediction Accuracy Measurements for Ensemble Classifier

Multiple classifier combination (or ensemble method) has been shown to be very helpful in improving the performance of classification over single classifier approach. The diversity among base classifiers (or ensemble members) is important when constructing a classifier ensemble. Although there have been several measures of diversity, but there is no reliable measure that can predict the ensemble accuracy. The base classifiers accuracy will increase when the diversity decreases and this is known as the accuracy-diversity dilemma. This paper presents a new method to measure diversity in classifier ensembles. Furthermore another parameter which based on this diversity measure is defined. It is hope that the new parameter will be able to predict the ensemble accuracy. Based on experimental results on classification of 84 samples of fruit images using nearest mean classifier ensembles, it has been shown that there is a positive linear relationship between the new parameter and the ensemble accuracy. This parameter is expected to assist in constructing diverse and accurate ensemble.
Line sharing cache: Exploring cache capacity with frequent line value locality

This paper proposes a new last level cache architecture called line sharing cache (LSC), which can reduce the number of cache misses without increasing the size of the cache memory. It stores lines which contain the identical value in a single line entry, which enables to store greater amount of lines. Evaluation results show performance improvements of up to 35% across a set of SPEC CPU2000 benchmarks.
Distant Supervision via Prototype-Based Global Representation Learning

Distant supervision (DS) is a promising technique for relation extraction. Currently, most DS approaches build relation extraction models in local instance feature space, often suffer from the multi-instance problem and the missing label problem. In this paper, we propose a new DS method — prototype-based global representation learning, which can effectively resolve the multi-instance problem and the missing label problem by learning informative entity pair representations, and building discriminative extraction models at the entity pair level, rather than at the instance level. Specifically, we propose a prototype-based embedding algorithm, which can embed entity pairs into a prototype-based global feature space; we then propose a neural network model, which can classify entity pairs into target relation types by summarizing relevant information from multiple instances. Experimental results show that our method can achieve significant performance improvement over traditional DS methods.
FlashStorageSim: Performance Modeling for SSD Architectures

We present FlashStorageSim, an SSD architecture performance model for data center servers, validated with an enterprise SSD. In addition to the SSD controller, SSD organization, and flash devices, FlashStorageSim models the host interface (e.g., SATA, PCIe, DDR). This allows users to explore non-traditional SSD use cases. We also implement mechanisms to improve simulation speed, which is shown to reduce simulation time by more than 7X. We show how FlashStorageSim can help researchers understand SSD design decisions.
Angiogenesis in Spontaneous Tumors and Implications for Comparative Tumor Biology

Blood supply is essential for development and growth of tumors and angiogenesis is the fundamental process of new blood vessel formation from preexisting ones. Angiogenesis is a prognostic indicator for a variety of tumors, and it coincides with increased shedding of neoplastic cells into the circulation and metastasis. Several molecules such as cell surface receptors, growth factors, and enzymes are involved in this process. While antiangiogenic therapy for cancer has been proposed over 20 years ago, it has garnered much controversy in recent years within the scientific community. The complex relationships between the angiogenic signaling cascade and antiangiogenic substances have indicated the angiogenic pathway as a valid target for anticancer drug development and VEGF has become the primary antiangiogenic drug target. This review discusses the basic and clinical perspectives of angiogenesis highlighting the importance of comparative biology in understanding tumor angiogenesis and the integration of these model systems for future drug development.
A systematic review of the use of opioids in the management of dyspnoea

Background: Opioids are commonly used to treat dyspnoea in palliative medicine but there has been no formal evaluation of the evidence for their effectiveness in the treatment of dyspnoea. A systematic review was therefore carried out to examine this. Methods: The criteria for inclusion required that studies were double blind, randomised, placebo controlled trials of opioids for the treatment of dyspnoea secondary to any cause. The methods used to identify suitable studies included electronic searching of the literature, hand searching of the literature, and personal contact with relevant individuals and organisations. Random effects meta-analyses were performed on all included studies and on various subgroups (studies involving nebulised opioids or patients with chronic obstructive pulmonary disease (COPD)). Subgroups were compared using meta-regression. Some studies included in the systematic review could not be included in the meta-analysis because insufficient data were presented. Results: Eighteen studies fulfilled the criteria for the review. The meta-analysis showed a statistically significant positive effect of opioids on the sensation of breathlessness (p=0.0008). Meta-regression indicated a greater effect for studies using oral or parenteral opioids than for studies using nebulised opioids (p=0.02). The subgroup analysis failed to show a positive effect of nebulised opioids on the sensation of breathlessness. The results of the subgroup analysis of the COPD studies were essentially similar to the results of the main analysis. Conclusion: This review supports the continued use of oral and parenteral opioids to treat dyspnoea in patients with advanced disease. There are insufficient data from the meta-analysis to conclude whether nebulised opioids are effective, but the results from included studies that did not contribute to the meta-analysis suggest that they are no better than nebulised normal saline.
PEPITO: improved discontinuous B-cell epitope prediction using multiple distance thresholds and half sphere exposure

MOTIVATION Accurate prediction of B-cell epitopes is an important goal of computational immunology. Up to 90% of B-cell epitopes are discontinuous in nature, yet most predictors focus on linear epitopes. Even when the tertiary structure of the antigen is available, the accurate prediction of B-cell epitopes remains challenging. RESULTS Our predictor, PEPITO, uses a combination of amino-acid propensity scores and half sphere exposure values at multiple distances to achieve state-of-the-art performance. PEPITO achieves an area under the curve (AUC) of 75.4 on the Discotope dataset. Additionally, we benchmark PEPITO as well as the Discotope predictor on the more recent Epitome dataset, achieving AUCs of 68.3 and 66.0, respectively. AVAILABILITY PEPITO is available as part of the SCRATCH suite of protein structure predictors via www.igb. uci.edu. CONTACT pfbaldi@ics.uci.edu SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Feldenkrais Method Balance Classes Improve Balance in Older Adults: A Controlled Trial

The objective of this study was to investigate the effects of Feldenkrais Method balance classes on balance and mobility in older adults. This was a prospective non-randomized controlled study with pre/post measures. The setting for this study was the general community. A convenience sample of 26 community-dwelling older adults (median age 75 years) attending Feldenkrais Method balance classes formed the Intervention group. Thirty-seven volunteers were recruited for the Control group (median age 76.5 years). A series of Feldenkrais Method balance classes (the 33312Getting Grounded Gracefully33313 series), two classes per week for 10 weeks, were conducted. Main outcome measures were Activities-Specific Balance Confidence (ABC) questionnaire, Four Square Step Test (FSST), self-selected gait speed (using GAITRite instrumented gait mat). At re-testing, the Intervention group showed significant improvement on all of the measures (ABC, P = .016, FSST, P = .001, gait speed, P < .001). The Control group improved significantly on one measure (FSST, P < .001). Compared to the Control group, the Intervention group made a significant improvement in their ABC score (P = .005), gait speed (P = .017) and FSST time (P = .022). These findings suggest that Feldenkrais Method balance classes may improve mobility and balance in older adults.
Conformational analysis of nucleic acids revisited: Curves+

We describe Curves+, a new nucleic acid conformational analysis program which is applicable to a wide range of nucleic acid structures, including those with up to four strands and with either canonical or modified bases and backbones. The program is algorithmically simpler and computationally much faster than the earlier Curves approach, although it still provides both helical and backbone parameters, including a curvilinear axis and parameters relating the position of the bases to this axis. It additionally provides a full analysis of groove widths and depths. Curves+ can also be used to analyse molecular dynamics trajectories. With the help of the accompanying program Canal, it is possible to produce a variety of graphical output including parameter variations along a given structure and time series or histograms of parameter variations during dynamics.
Percolation on uniform infinite planar maps

We construct the uniform infinite planar map (UIPM), obtained as the $n \to \infty$ local limit of planar maps with $n$ edges, chosen uniformly at random. We then describe how the UIPM can be sampled using a "peeling" process, in a similar way as for uniform triangulations. This process allows us to prove that for bond and site percolation on the UIPM, the percolation thresholds are $p^{\textrm{bond}}_c=1/2$ and $p^{\textrm{site}}_c=2/3$ respectively. This method also works for other classes of random infinite planar maps, and we show in particular that for bond percolation on the uniform infinite planar quadrangulation, the percolation threshold is $p^{\textrm{bond}}_c=1/3$.
The Effect of Thickness on the Sealing Ability of CEM Cement as a Root-end Filling Material

Background and aims. Different materials have been used for root-end filling during surgical endodontic treatment. The aim of this in vitro study was to evaluate the dye penetration in different thicknesses of calcium enriched mixture (CEM) cement as root-end filling material. Materials and methods. Following root canal filling in 70 extracted human single-rooted premolar teeth, the apical 3 mm of their root-ends was resected; the root-end cavities with depths of 1, 2 and 3 mm were prepared by ultrasonic retrotips and filled with CEM cement. After setting of cement, the roots were immersed in 2% Rhodamine B and the dye leakage was measured under stereomicroscope (×16) using Image J software. The data were analyzed by one-way ANOVA and Bonferroni post hoc tests at 5% significance level. Results. The means and standard deviations of dye penetration in the 1, 2, and 3 mm groups were 3395.5±1893.4, 3410.4±1440.5, and 2581.6±1852.9 μm, respectively. The one-way ANOVA analysis indicated significant differences (P < 0.001); however, the Bonferroni post hoc test revealed that only the positive control group differed significantly from the experimental groups (P < 0.001). Conclusion. The findings demonstrated CEM cement to have an adequate root-end sealing ability in 3-mm thickness.
Fuzzy Goals for Requirements-Driven Adaptation

Self-adaptation is imposing as a key characteristic of many modern software systems to tackle their complexity and cope with the many environments in which they can operate. Self-adaptation is a requirement per-se, but it also impacts the other (conventional) requirements of the system; all these new and old requirements must be elicited and represented in a coherent and homogenous way. This paper presents FLAGS, an innovative goal model that generalizes the KAOS model, adds adaptive goals to embed adaptation countermeasures, and fosters self-adaptation by considering requirements as live, runtime entities. FLAGS also distinguishes between crisp goals, whose satisfaction is boolean, and fuzzy goals, whose satisfaction is represented through fuzzy constraints. Adaptation countermeasures are triggered by violated goals and the goal model is modified accordingly to maintain a coherent view of the system and enforce adaptation directives on the running system. The main elements of the approach are demonstrated through an example application.
ProFi: design and evaluation of a product finder in a supermarket scenario

This paper presents the design and evaluation of ProFi, a PROduct FInding assistant in a supermarket scenario. We explore the idea of micro-navigation in supermarkets and aim at enhancing visual search processes in front of a shelf. In order to assess the concept, a prototype is built combining visual recognition techniques with an Augmented Reality interface. Two AR patterns (circle and spotlight) are designed to highlight target products. The prototype is formally evaluated in a controlled environment. Quantitative and qualitative data is collected to evaluate the usability and user preference. The results show that ProFi significantly improves the users' product finding performance, especially when using the circle pattern, and that ProFi is well accepted by users.