Miracle-dz/UniFAR-FTUs huggingface dataset:
Self-setting of physical activity goals and effects on perceived difficulty, importance and competence

Goal setting can be a powerful method for persuading individuals to adopt an active lifestyle. In order for this to be the case, it is important to set concrete and challenging goals, and to strongly commit to them. In this study, we explored how people set goals for physical activity and how these goals were reflected in self-regulatory mechanisms to drive goal attainment. Our approach is novel in two ways: first, we used an unobtrusive wearable sensor to accurately measure physical activity throughout the day rather than rely on self-report, and second, we provided individuals with feedback about the contribution of their common daily activities (e.g., household activities) to their physical activity level. Our results showed that on the basis of this feedback, participants were able to indicate to what degree they intended to change their behavior. Nevertheless, they failed to set concrete goals that matched their intentions precisely. In particular, we observed that overall the set goals were in accordance with intentions (i.e., goals were set in the desired direction), but we saw a strong tendency to focus on enhancing vigorous activity at the cost of moderate intensity activity. This suggests that many individuals have intentions to change and goal setting support is needed to compose goals that accurately reflect these intentions. Technology-mediated interventions might be ideal to support individuals along that path.
Laetoli footprints reveal bipedal gait biomechanics different from those of modern humans and chimpanzees

Bipedalism is a key adaptation that shaped human evolution, yet the timing and nature of its evolution remain unclear. Here we use new experimentally based approaches to investigate the locomotor mechanics preserved by the famous Pliocene hominin footprints from Laetoli, Tanzania. We conducted footprint formation experiments with habitually barefoot humans and with chimpanzees to quantitatively compare their footprints to those preserved at Laetoli. Our results show that the Laetoli footprints are morphologically distinct from those of both chimpanzees and habitually barefoot modern humans. By analysing biomechanical data that were collected during the human experiments we, for the first time, directly link differences between the Laetoli and modern human footprints to specific biomechanical variables. We find that the Laetoli hominin probably used a more flexed limb posture at foot strike than modern humans when walking bipedally. The Laetoli footprints provide a clear snapshot of an early hominin bipedal gait that probably involved a limb posture that was slightly but significantly different from our own, and these data support the hypothesis that important evolutionary changes to hominin bipedalism occurred within the past 3.66 Myr.
A regularized trust region method for joint reconstruction of spin magnitude, T2∗ decay, and off-resonance field map

Joint reconstruction of three parameter images - spin magnitude, T2* decay and off-resonance field map - is an important technique in some applications of magnetic resonance imaging (MRI). Despite its importance, the reconstruction problem is very challenging due to its nonlinearity and ill-conditioning. The standard conjugate gradient (CG) method with regularization is usually very slow for this problem. In this work, we propose a novel regularized trust region (TR) method that reconstructs the three images by solving a constrained linear sub-problem in each iteration. In particular, this method employs a change-of-variable technique, making the sub-problem linear yet keeping the convergence fast. To solve the sub-problem, we use a penalty method with preconditioned conjugate gradient (PCG) algorithm. Based on a synthesized data set, we demonstrate that our algorithm stably converges even with a poor initial guess, and the convergence rate is much higher than that of the CG algorithm.
OptorSim : A Grid Simulator for Replica Optimisation

The remit of the European DataGrid (EDG) [2] project was to develop an infrastructure that could support the intensive computational and data handling needs of widely distributed scientific communities. An important part of managing the data present in such a Grid is file replication placing copies of files at different sites in order to reduce data access times, hence shortening job running times and improving the use of Grid resources. In the search for an optimal solution to this problem, the Grid simulator OptorSim [3] was developed as part of the EDG project. Here, an overview of OptorSim is presented with details of its implementation, features and capabilites.
Development of a Robotic Motor Skills Assessment System for Children With Autism

Autism is a developmental disorder characterized by atypical social interactions and repetitive behaviors/restricted interests[1]. It is found that children with autism also experience delayed or impaired motor skills development [2]. It would be advantageous to develop methods that precisely evaluate these motor skills impairments. The use of robots for evaluating upper limb motor competency have been looked at in the stroke literature [3]. We would like to leverage robotic tools for motor skills assessment but with focus for children with autism spectrum disorder. Robotic methodologies provide a unique way of testing upper limb motor skills. For instance, if a person holds on to the end of a robot arm and moves the robot arm in space, the robot can apply forces and prevent or assist the person with these motions. In this fashion, the robot can apply perturbations in a repeatable and precise manner with high fidelity. Since individuals with autism have anxieties interacting with other individuals[4], using an impersonal robot would alleviate the anxiety of social interactions. These individuals learn motor skills best with consistent repetition and strong reinforcement, qualities that robots provide. Therefore, a robot based evaluation strategy and therapy paradigm for children with Autism would be beneficial for the community. 2 Methods
Usage of the webcam as 3D input device

The paper is focused on using the webcam as a 3D input device. Generally it means the user may use any object and shadow of this object to obtain the coordinates x , y and z (position in the space). This idea allows to use a navigation in three dimensions without an expensive or atypical hardware. The system needs one ordinary webcam, an ordinary computer and a source of suitable light. The goal of this paper is to describe an implementation of a software usable for handling an input from webcam with conditions described previously.
Automatic prefetching in a WAN

File systems have become slow relative to processor, memory and network speeds. The high latencies of distributed file systems (particularly wide area file systems) have only exacerbated the problem. The authors believe that file system prefetching provides an effective method for alleviating the latency bottleneck. File system prefetching requires knowledge of future file accesses. The authors are currently investigating efficient methods for accurately predicting future file activity automatically without application intervention. They have designed and implemented a system which uses past file activity to predict future file system needs. The initial results indicate that reasonable accuracy can be obtained even when relatively simple algorithms are employed.
Clerodendrum inerme Leaf Extract Alleviates Animal Behaviors, Hyperlocomotion, and Prepulse Inhibition Disruptions, Mimicking Tourette Syndrome and Schizophrenia

Previously, we found a patient with intractable motor tic disorder, a spectrum of Tourette syndrome (TS), responsive to the ground leaf juice of Clerodendrum inerme (CI). Here, we examined the effect of the ethanol extract of CI leaves (CI extract) on animal behaviors mimicking TS, hyperlocomotion, and sensorimotor gating deficit. The latter is also observed in schizophrenic patients and can be reflected by a disruption of prepulse inhibition of acoustic startle response (PPI) in animal models induced by methamphetamine and NMDA channel blockers (ketamine or MK-801), based on hyperdopaminergic and hypoglutamatergic hypotheses, respectively. CI extract (10–300 mg/kg, i.p.) dose-dependently inhibited hyperlocomotion induced by methamphetamine (2 mg/kg, i.p.) and PPI disruptions induced by methamphetamine, ketamine (30 mg/kg, i.p.), and MK-801 (0.3 mg/kg, i.p.) but did not affect spontaneous locomotor activity, rotarod performance, and grip force. These results suggest that CI extract can relieve hyperlocomotion and improve sensorimotor gating deficit, supporting the therapeutic potential of CI for TS and schizophrenia.
Women and men — Different but equal: On the impact of identifier style on source code reading

Program comprehension is preliminary to any program evolution task. Researchers agree that identifiers play an important role in code reading and program understanding activities. Yet, to the best of our knowledge, only one work investigated the impact of gender on the memorability of identifiers and thus, ultimately, on program comprehension. This paper reports the results of an experiment involving 15 male subjects and nine female subjects to study the impact of gender on the subjects' visual effort, required time, as well as accuracy to recall Camel Case versus Underscore identifiers in source code reading. We observe no statistically-significant difference in term of accuracy, required time, and effort. However, our data supports the conjecture that male and female subjects follow different comprehension strategies: female subjects seem to carefully weight all options and spend more time to rule out wrong answers while male subjects seem to quickly set their minds on some answers, possibly the wrong ones. Indeed, we found that the effort spent on wrong answers is significantly higher for female subjects and that there is an interaction between the effort that female subjects invested on wrong answers and their higher percentages of correct answers when compared to male subjects.
Intracellular calcium concentration and hormone secretion are controlled differently by TRH in rat neonatal lactotrophs and somatotrophs.

We studied the effects of TRH on the cytosolic free calcium concentration ([Ca2+]i) of female rat pituitary prolactin-secreting (lactotroph) and GH-secreting (somatotroph) cells in the early postnatal period, i.e. at postnatal days 5 and 10. [Ca2+]i of single identified lactotrophs and somatotrophs was recorded by dual-emission microspectrofluorimetry using the intracellular fluorescent calcium probe indo 1. An application of TRH (100 nM, 10 s) induced a marked [Ca2+]i increase in 65% of neonatal lactotrophs and 34% of neonatal somatotrophs while the remaining cells were unaffected. Most of the responsive cells, both lactotrophs and somatotrophs, exhibited a similar biphasic Ca2+ response, made up of an initial rapid large increase in [Ca2+]i followed by sustained [Ca2+]i fluctuations. In both cell types, removal of Ca2+ from the extracellular medium or addition of the Ca2+ channel blocker, cadmium chloride (500 microM), inhibited the second phase whereas the first phase persisted. Furthermore, in both cell types, protein kinase C (PKC) depletion by incubation in phorbol myristate acetate (1 microM) for 24 h abolished the second phase but did not inhibit the first phase. Conversely, when cells were pretreated with the Ca(2+)-ATPase inhibitor, thapsigargin (100 nM), all TRH-induced [Ca2+]i changes in both cell types disappeared. TRH therefore induces a biphasic increase in [Ca2+]i involving intra- and extracellular Ca2+ in neonatal lactotrophs and somatotrophs as it does in adult lactotrophs. The first phase is presumably due to mobilization of Ca2+ from intracellular stores whereas the second phase presumably results from a PKC-sensitive influx of Ca2+. TRH action on membrane potential was then investigated using the patch-clamp technique in the whole-cell mode. TRH-induced changes in membrane potential consisted of an initial hyperpolarization followed by depolarization and action potential firing. We also investigated TRH action on prolactin and GH secretion by neonatal pituitary cells using RIA. Surprisingly, static assays of prolactin and GH revealed only stimulation of prolactin release by TRH but no effect on GH secretion, although, as expected, GH-releasing factor was a potent agonist of GH secretion. Our results suggest that TRH regulates neonatal lactotrophs and somatotrophs differently, in that the [Ca2+]i changes do not correlate with stimulation of exocytosis in the latter cell type.
A Novel Active Contour Model for MRI Brain Segmentation used in Radiotherapy Treatment Planning

Introduction Brain image segmentation is one of the most important clinical tools used in radiology and radiotherapy. But accurate segmentation is a very difficult task because these images mostly contain noise, inhomogeneities, and sometimes aberrations. The purpose of this study was to introduce a novel, locally statistical active contour model (ACM) for magnetic resonance image segmentation in the presence of intense inhomogeneity with the ability to determine the position of contour and energy diagram. Methods A Gaussian distribution model with different means and variances was used for inhomogeneity, and a moving window was used to map the original image into another domain in which the intensity distributions of inhomogeneous objects were still Gaussian but were better separated. The means of the Gaussian distributions in the transformed domain can be adaptively estimated by multiplying a bias field by the original signal within the window. Then, a statistical energy function is defined for each local region. Also, to evaluate the performance of our method, experiments were conducted on MR images of the brain for segment tumors or normal tissue as visualization and energy functions. Results In the proposed method, we were able to determine the size and position of the initial contour and to count iterations to have a better segmentation. The energy function for 20 to 430 iterations was calculated. The energy function was reduced by about 5 and 7% after 70 and 430 iterations, respectively. These results showed that, with increasing iterations, the energy function decreased, but it decreased faster during the early iterations, after which it decreased slowly. Also, this method enables us to stop the segmentation based on the threshold that we define for the energy equation. Conclusion An active contour model based on the energy function is a useful tool for medical image segmentation. The proposed method combined the information about neighboring pixels that belonged to the same class, thereby making it strong to separate the desired objects from the background.
Design and Demonstration of a Miniature Lidar System for Rover Applications

Public awareness of harmful human environmental effects such as global warming has increased greatly in recent years and researchers have increased their efforts in gaining more knowledge about the Earth s atmosphere. Natural and man-made processes pose threats to the environment and human life, so knowledge of all atmospheric processes is necessary. Ozone and aerosols are important factors in many atmospheric processes and active remote sensing techniques provide a way to analyze their quantity and distribution. A compact ground-based lidar system for a robotic platform meant for atmospheric aerosol measurements was designed, tested, and evaluated. The system will eventually be deployed for ozone and aerosol measurements in Mars and lunar missions to improve our knowledge and understanding of atmospheres on Mars and the Moon. All of the major subsystems were described in detail and atmospheric testing was performed to test the operability of the receiver system to acquire the lidar return signal from clouds and aerosols. The measured backscattered results are discussed and compared with theoretical results.
Customizable resource usage analysis for java bytecode

Automatic cost analysis of programs has been traditionally studied in terms of a number of concrete, predefined resources such as execution steps, time, or memory. However, the increasing relevance of analysis applications such as static debugging and/or certification of user-level properties (including for mobile code) makes it interesting to develop analyses for resource notions that are actually applicationdependent. This may include, for example, bytes sent or received by an application, number of files left open, number of SMSs sent or received, number of accesses to a database, money spent, energy consumption, etc. We present a fully automated analysis for inferring upper bounds on the usage that a Java bytecode program makes of a set of application programmer-definable resources. In our context, a resource is defined by programmer-provided annotations which state the basic consumption that certain program elements make of that resource. From these definitions our analysis derives functions which return an upper bound on the usage that the whole program (and individual blocks) make of that resource for any given set of input data sizes. The analysis proposed is independent of the particular resource. We also present some experimental results from a prototype implementation of the approach covering an ample set of interesting resources.
Macro Prediction Model of Road Traffic Accident Based on Neural Network and Genetic Algorithm

The whole society has paid more and more attention to the road traffic safety in China. In order to scientifically and accurately predict the future road traffic safety situation, evaluation indexes and main influence factors of road traffic safety were analyzed. Then traffic accident death toll was selected as the evolution index and three factors were taken as parameters, including motor vehicle amount, highway mileage and per capital gdp. The two prediction models of BP neural network and hybrid algorithm based on neural network and genetic algorithm were built respectively. The neural models used the traffic accident data from 1978 to 1998 as training samples. And the data from 1999 to 2004 were used to check the models. Forecasting result shows that neural network model based on genetic algorithms has higher prediction accuracy and more network generalization than those of BP neural network; the forecasting values of accident death toll in 2010 and 2020 are 139 thousand people and 167 thousand people respectively.
Prediction of Diabetes Using Bayesian Network

This paper helps in predicting diabetes by applying data mining technique. The discovery of knowledge from medical datasets is important in order to make effective medical diagnosis. The aim of data mining is to extract knowledge from information stored in dataset and generate clear and understandable description of patterns. Diabetes mellitus is a chronic disease and a major public health challenge worldwide. Using data mining methods to aid people to predict diabetes has gain major popularity. In this paper , Bayesian Network classifier was proposed to predict the persons whether diabetic or not. The dataset used is collected from a hospital, which collects the information of persons with and without diabetes. We used Weka tool for the experiment and analysis. Classification algorithm is applied on the dataset of persons collected from hospital. Results have been obtained
Autonomy, religion and clinical decisions: findings from a national physician survey

Background: Patient autonomy has been promoted as the most important principle to guide difficult clinical decisions. To examine whether practising physicians indeed value patient autonomy above other considerations, physicians were asked to weight patient autonomy against three other criteria that often influence doctors’ decisions. Associations between physicians’ religious characteristics and their weighting of the criteria were also examined. Methods: Mailed survey in 2007 of a stratified random sample of 1000 US primary care physicians, selected from the American Medical Association masterfile. Physicians were asked how much weight should be given to the following: (1) the patient’s expressed wishes and values, (2) the physician’s own judgment about what is in the patient’s best interest, (3) standards and recommendations from professional medical bodies and (4) moral guidelines from religious traditions. Results: Response rate 51% (446/879). Half of physicians (55%) gave the patient’s expressed wishes and values “the highest possible weight”. In comparative analysis, 40% gave patient wishes more weight than the other three factors, and 13% ranked patient wishes behind some other factor. Religious doctors tended to give less weight to the patient’s expressed wishes. For example, 47% of doctors with high intrinsic religious motivation gave patient wishes the “highest possible weight”, versus 67% of those with low (OR 0.5; 95% CI 0.3 to 0.8). Conclusions: Doctors believe patient wishes and values are important, but other considerations are often equally or more important. This suggests that patient autonomy does not guide physicians’ decisions as much as is often recommended in the ethics literature.
A Standardized Bleeding Risk Score Aligns Anticoagulation Choices with Current Evidence

Objectives: Atrial fibrillation (AF), the most common arrhythmia in elderly patients, accounts for 15% of strokes. Oral anticoagulation (OAC) can reduce the risk of stroke by 60% but is underprescribed. The HAS-BLED score (Hypertension, Abnormal renal or liver function, Stroke, Bleeding, Labile INR, Elderly, Drugs) can predict OAC bleeding complications. The authors hypothesized that use of HAS-BLED can help align decision making with current evidence. Methods: The authors developed a survey with four clinical vignettes designed to highlight the complexity in deciding whether to anticoagulate elderly patients with AF. Physicians were randomly assigned to receive the survey either including the HAS-BLED score and the estimated annual risk of bleeding (intervention) or without (control). Following each vignette, participants were asked: (1) whether they would recommend OAC and (2) to estimate the risk of bleeding and stroke. The “appropriate” anticoagulation decision was defined as the choice that minimized the risk of stroke and major bleeding. Results: A total of 203 physicians were recruited for the survey, with 55 responses obtained (27%). Physicians who were given the HAS-BLED score were 18% more likely to choose appropriate anticoagulation (74% vs. 56%, P < .05). The HAS-BLED score assisted physicians in both choosing to anticoagulate when appropriate and not to anticoagulate when the risk of bleeding outweighed the benefit. Overall, physicians were poor at estimating the risk of stroke (42% correct) and major bleeding (31% correct). Conclusions: Presentation of the HAS-BLED score led to an 18% improvement in appropriate OAC choices. Future study should evaluate incorporation of HAS-BLED use in real-time clinical situations.