Miracle-dz/UniFAR-FTUs huggingface dataset:
On-line space sculpturing for 3D shape manipulation

We present a new data structure, called the Multi-Sculpture, to represent 3D shapes at multiple levels of detail. The input shape at high resolution is described as a mesh of triangles. A coarse approximation of this shape is provided by the convex hull of the mesh, while intermediate approximations are obtained by sculpturing the space that separates the convex hull from the mesh. A higher level of detail corresponds to a higher degree of concavity in the shape approximation. The data structure supports online extraction of a shape representation at a user-defined level of detail, possibly varing over different parts of the shape. This mechanism allows speeding up recognition, classification, collision detection, and planning of manipulation tasks.
Automatic segmentation of age-related white matter changes on flair images: Method and multicentre validation

White matter hyperintensities (WMH) are commonly seen on T2-weighted images in elderly people. They are considered as a potential marker of vascular pathology and have been associated with motor and cognitive deficits. In this paper, non linear diffusion was applied to FLAIR images and combined with precise anatomical knowledge extracted from T1-weighted images to automatically segment WMH. Evaluation was performed on 24 patients with mild cognitive impairment (MCI) from 5 different centres. Results showed excellent volume agreement with manual delineation (Pearson coefficient: r=0.98, p&#60;0.001) and substantial spatial correspondence (Similarity index: 66%±17%). Our method appeared robust to acquisition differences across the centres.
Competitive routing in multiuser communication networks

The authors consider a communication network shared by several selfish users. Each user seeks to optimize its own performance by controlling the routing of its given flow demand, giving rise to a noncooperative game. They investigate the Nash equilibrium of such systems. For a two-node multiple links system, uniqueness of the Nash equilibrium is proven under reasonable convexity conditions. It is shown that this Nash equilibrium point possesses interesting monotonicity properties. For general networks, these convexity conditions are not sufficient for guaranteeing uniqueness, and a counterexample is presented. Nonetheless, uniqueness of the Nash equilibrium for general topologies is established under various assumptions. >
Does foreign aid crowd out government investments? Evidence from rural health centres in Rwanda

Background Rural healthcare facilities in low-income countries play a major role in providing primary care to rural populations. We examined the link of foreign aid with government investments and medical service provision in rural health centres in Rwanda. Methods Using the District Health System Strengthening Tool, a web-based database built by the Ministry of Health in Rwanda, we constructed two composite indices representing provision of (1) child and maternal care and (2) HIV, tuberculosis (TB) and malaria services in 330 rural health centres between 2009 and 2011. Financing variables in a healthcare centre included received funds from various sources, including foreign donors and government. We used multilevel random-effects model in regression analyses and examined the robustness of results to a range of alternative specification, including scale of dependent variables, estimation methods and timing of aid effects. Findings Both government and foreign donors increased their direct investments in the 330 rural healthcare centres during the period. Foreign aid was positively associated with government investments (0.13, 95% CI 0.06 to 0.19) in rural health centres. Aid in the previous year was positively associated with service provision for child and maternal health (0.008, 95% CI 0.002 to 0.014) and service provision for HIV, TB and malaria (0.014, 95% CI 0.004 to 0.022) in the current year. The results are robust when using fixed-effects models. Conclusions These findings suggest that foreign aid did not crowd out government investments in the rural healthcare centres. Foreign aid programmes, conducted in addition to government investments, could benefit rural residents in low-income countries through increased service provision in rural healthcare facilities.
A Monoclonal Antibody TrkB Receptor Agonist as a Potential Therapeutic for Huntington’s Disease

Huntington’s disease (HD) is a devastating, genetic neurodegenerative disease caused by a tri-nucleotide expansion in exon 1 of the huntingtin gene. HD is clinically characterized by chorea, emotional and psychiatric disturbances and cognitive deficits with later symptoms including rigidity and dementia. Pathologically, the cortico-striatal pathway is severely dysfunctional as reflected by striatal and cortical atrophy in late-stage disease. Brain-derived neurotrophic factor (BDNF) is a neuroprotective, secreted protein that binds with high affinity to the extracellular domain of the tropomyosin-receptor kinase B (TrkB) receptor promoting neuronal cell survival by activating the receptor and down-stream signaling proteins. Reduced cortical BDNF production and transport to the striatum have been implicated in HD pathogenesis; the ability to enhance TrkB signaling using a BDNF mimetic might be beneficial in disease progression, so we explored this as a therapeutic strategy for HD. Using recombinant and native assay formats, we report here the evaluation of TrkB antibodies and a panel of reported small molecule TrkB agonists, and identify the best candidate, from those tested, for in vivo proof of concept studies in transgenic HD models.
Controlled Physical Activity Trials in Cancer Survivors: A Systematic Review and Meta-analysis

Background: Approximately 9.8 million cancer survivors are alive in the United States today. Enthusiasm for prescribing physical activity for cancer survivors depends on evidence regarding whether physical activity during or after completion of treatment results in improved outcomes such as cardiorespiratory fitness, fatigue, symptoms, quality of life, mental health, or change in body size. Methods: A systematic qualitative and quantitative review of the English language scientific literature identified controlled trials of physical activity interventions in cancer survivors during and after treatment. Data from 32 studies were abstracted, weighted mean effect sizes (WMES) were calculated from the 22 high-quality studies, and a systematic level of evidence criteria was applied to evaluate 25 outcomes. Results: There was qualitative and quantitative evidence of a small to moderate effect of physical activity interventions on cardiorespiratory fitness (WMES = 0.51 and 0.65 during and after treatment respectively, P < 0.01), physiologic outcomes and symptoms during treatment (WMES = 0.28, P < 0.01 and 0.39, P < 0.01, respectively), and vigor posttreatment (WMES = 0.83, P = 0.04). Physical activity was well tolerated in cancer survivors during and after treatment, but the available literature does not allow conclusions to be drawn regarding adverse events from participation. Conclusions: Physical activity improves cardiorespiratory fitness during and after cancer treatment, symptoms and physiologic effects during treatment, and vigor posttreatment. Additional physical activity intervention studies are needed to more firmly establish the range and magnitude of positive effects of physical activity among cancer survivors.
PixelMaps: a new visual data mining approach for analyzing large spatial data sets

PixelMaps are a new pixel-oriented visual data mining technique for large spatial datasets. They combine kernel-density-based clustering with pixel-oriented displays to emphasize clusters while avoiding overlap in locally dense point sets on maps. Because a full evaluation of density functions is prohibitively expensive, we also propose an efficient approximation, Fast-PixelMap, based on a synthesis of the quadtree and gridfile data structures.
Visualization to facilitate association rules modelling : A review

Association rules modelling is one of most widely used data mining modelling tools; it finds interesting associations or correlation relationships among a set of data attributes. One of the major problems with association rules modelling, however, is the overwhelming number of rules that can be generated, many of which may not be interesting. This paper surveys the current state of art in application of visualization techniques to facilitate association rules modelling process in terms of visualization of derived rules, visualization of rule evaluation, and visual interactive rule derivation. A number of issues that have been overlooked and areas that need to be improved are identified through reviewing a collection of related research and examining four current data mining softwares with respect to their design of a few important visualization features to support association rules modelling.
Subtelomere specific microarray based comparative genomic hybridisation: a rapid detection system for cryptic rearrangements in idiopathic mental retardation

Mental retardation (MR) occurs in 2–3% of the general population, and more than half of MR patients are categorised as idiopathic—that is, the cause is unknown.1,2 Patients with idiopathic MR are presumed to be affected with certain genetic disorders or undetectable chromosomal abnormalities. MR may also be caused by environmental factors independently or by their interaction with genetic factors. Subtelomeric rearrangements comprise about half of segmental aneusomies,3 and are one of the major causes of MR.4,5 A recent review showed that subtelomeric rearrangements were detected in 131 (5.1%) of 2585 children with MR.1,4–6 Conventional cytogenetic analysis can detect many, but not all, rearrangements, depending on its powers of resolution.4 Other methods, such as fluorescent in situ hybridisation (FISH) using a complete set of subtelomeric probes, multicolour FISH (M-FISH), comparative genomic hybridisation (CGH), spectrum karyotyping, multiple amplifiable probe hybridisation, primed in situ labelling, and genotyping have been designed to detect subtelomeric rearrangements, but none of them is ideal in terms of sensitivity and/or efficiency.4,6 Microarray based CGH is a promising, high throughput method of detecting subtelomeric rearrangements.4 Veltman et al recently reported a microarray CGH system using crude bacterial/plasmid derived artificial chromosome (BAC/PAC) DNA for the analysis of subtelomeric aberrations, and suggested that degenerate oligonucleotide primed (DOP)-PCR products could also be used instead of crude clone DNA, although the performance of DOP-PCR products might be less sensitive.7 We have developed a microarray CGH system to identify rearrangements involving a subtelomeric region, using DOP-PCR that amplifies subtelomeric BAC/PAC DNA. Here we describe details of the method and the results of microarray CGH analyses of five cases of Wolf-Hirschhorn syndrome (WHS) associated with terminal 4p deletions as positive controls, and of 69 patients with idiopathic MR with or without multiple …
Evolutionary-Progressive Method for Multiple Sequence Alignment

In this paper a new evolutionary-progressive method for multiple sequence alignment (MSA) is proposed. The method efficiently combines flexibility of evolutionary approach with speed and accuracy of progressive technique. Both stages of introduced hybrid method are described in detail. The results of comparison with several well-known methods show that proposed evolutionary-progressive method is an interesting alternative for purely genetic and purely progressive approaches
Structural damage prediction of an AAR affected dam

Alkali-aggregate reaction (AAR) is a deleterious reaction that affects a large number of concrete structures, among which concrete dams, worldwide. It has been observed on dams built on each of the five continents. In France, they are about thirty affected dams, and in Cameroon AAR have been noticed on the Song Loulou hydropower dam. AAR produces concrete expansion and generally leads to a loss of both strength and stiffness due to the cracking. That creates undesirable deformations, disturbances in the equilibrium of internal forces, and affects the operability and safety of dams. In this work, we develop the real case of predicting the Song Loulou spillway's gate damage by both modeling a spillway's pier and implementing a methodology in Cast3M. The loss of functionality considered here is jamming of the spillway's gate due to the deformations induced by AAR, which is one of the most dangerous disorder impacting negatively the dam on all the other assets. First of all, we present a brief review of chemo-physical processes that control the structural behaviour of concrete dams suffering from AAR. In a second step, we make a summary of the simplified methodology for recalculating an AAR affected structure proposed by the IFSTTAR in the technical guide for internal swelling reaction affecting structures management support. It is mainly based on damage law proposed by Larive, works by Ulm and his collaborators, and model suggested by Li and Coussy. Thirdly, we indicate the collected and processed data (geometry, material properties, loads, temperature and relative humidity) for our case study. Computations performed with Cast3M predict the date of occurrence of the spillway's gate's blocking due to AAR. Although this work might be used as a maintenance management tool of the Song Loulou AAR affected hydropower dam, it would be more efficient to consider the effect of uncertainties affecting the input data and the model parameters. Probabilistic approaches, reliability analysis in particular, will be used to address this problem in a further work.
Chemotherapy-induced peripheral neuropathy: assessment of oncology nurses' knowledge and practice.

PURPOSE/OBJECTIVES To explore oncology nurses' practice behaviors and knowledge of chemotherapy-induced peripheral neuropathy (CIPN) in the assessment of patients with cancer. DESIGN Cross-sectional, exploratory. SETTING Two hospital-based outpatient chemotherapy clinics in Baltimore, MD. SAMPLE Self-selected convenience sample of 39 oncology nurses. METHODS Completion of the principal investigator-developed questionnaire consisting of 16 knowledge and 16 practice-behavior items, 8 instruction and perception items, and a 9-item demographic survey. MAIN RESEARCH VARIABLES CIPN assessment practice behaviors and knowledge; tool reliability. FINDINGS The mean CIPN knowledge score of 12.6 (SD=1.7) demonstrated knowledge deficits (maximum score of 16). All respondents indicated CIPN assessment is essential in their oncology role, but 75% rated their CIPN assessment skills as fair to poor. Assessment practices did not routinely include neurologic physical assessment. In addition, 82% believed CIPN is a significant problem for patients. Cronbach alpha for the tool was 0.84. CONCLUSIONS Results indicated participants had knowledge deficits pertaining to CIPN and lacked training, proficiency, and confidence in neurologic physical assessment. Education and training programs are needed to improve knowledge and neurologic assessment skills. IMPLICATIONS FOR NURSING To date, CIPN nursing assessment guidelines do not exist. Practice guidelines for CIPN nursing assessment and management should be efficient and appropriate to the role of the chemotherapy infusion oncology nurse working in a busy setting where chair turnover time, accuracy, safety, and quality service are competing priorities.
Happy and agreeable?: multi-label classification of impressions in social video

The mobile and ubiquitous nature of conversational social video has placed video blogs among the most popular forms of online video. For this reason, there has been an increasing interest in conducting studies of human behavior from video blogs in affective and social computing. In this context, we consider the problem of mood and personality trait impression inference using verbal and nonverbal audio-visual features. Under a multi-label classification framework, we show that for both mood and personality trait binary label sets, not only the simultaneous inference of multiple labels is feasible, but also that classification accuracy increases moderately for several labels, compared to a single-label approach. The multi-label method we consider naturally exploits label correlations, which motivate our approach, and our results are consistent with models proposed in psychology to define human emotional states and personality. Our approach points to the automatic specification of co-occurring emotional states and personality, by inferring several labels at once, compared to single-label approaches. We also propose a new set of facial features, based on emotion valence from facial expressions, and analyze their suitability in the multi-label framework.
A model for cerebral cortical neuron group electric activity and its implications for cerebral function

The electroencephalogram, or EEG, is a recording of the field potential generated by the electric activity of neuronal populations of the brain. Its utility has long been recognized as a monitor which reflects the vigilance states of the brain, such as arousal, drowsiness, and sleep stages. Moreover, it is used to detect pathological conditions such as seizures, to calibrate drug action during anesthesia, and to understand cognitive task signatures in healthy and abnormal subjects. Being an aggregate measure of neural activity, understanding the neural origins of EEG oscillations has been limited. With the advent of recording techniques, however, and as an influx of experimental evidence on cellular and network properties of the neocortex has become available, a closer look into the neuronal mechanisms for EEG generation is warranted. Accordingly, we introduce an effective neuronal skeleton circuit at a neuronal group level which could reproduce basic EEG-observable slow (< 15 Hz) oscillatory phenomenon. The circuit incorporates basic laminar organization principles of the cortex. Interaction between neuronal groups is defined on three scales, namely the columnar (0.3mm), columnar assembly (1-2mm) and areal (> 3mm). The effective circuit makes use of the dynamic properties of the layer 5 network to explain intra-cortically generated augmenting responses, restful alpha, slow wave (< 1Hz) oscillations, and disinhibition-induced seizures. Based on recent cellular evidence, we propose a hierarchical binding mechanism in tufted layer 5 cells which acts as a controlled gate between local cortical activity and inputs arriving from distant cortical areas. This gate is manifested by the switch in output firing patterns in tufted layer 5 cells between burst firing and regular spiking, with specific implications on local functional connectivity. This hypothesized mechanism provides an explanation of different alpha band (10Hz) oscillations observed recently under cognitive states. In particular, evoked alpha rhythms, which occur transiently after an input stimulus, could account for initial reogranization of local neural activity based on (mis)match between driving inputs and modulatory feedback of higher order cortical structures, or internal expectations. Emitted alpha rhythms, on the other hand, is an example of extreme attention where dominance of higher order control inputs could drive reorganization of local cortical activity. Finally, the model makes predictions on the role of burst firing patterns in tufted layer 5 cells in redefining local cortical dynamics, based on internal representations, as a prelude to high frequency oscillations observed in various sensory systems during cognition. Thesis Supervisor: Munther A. Dahleh Title: Professor Thesis Supervisor: Steve G. Massaquoi Title: Assistant Professor Thesis Reader: Emery N. Brown Title: Associate Professor, Harvard Medical School-HST
I/o-eecient Scientiic Computation Using Tpie

In recent years, I/O-eecient algorithms for a wide variety of problems have appeared in the literature. Thus far, however, systems speciically designed to assist programmers in implementing such algorithms have remained scarce. TPIE is a system designed to ll this void. It supports I/O-eecient paradigms for problems from a variety of domains, including computational geometry, graph algorithms, and scientiic computation. The TPIE interface frees programmers from having to deal not only of explicit read and write calls, but also the complex memory management that must be performed for I/O-eecient computation. In this paper, we discuss applications of TPIE to problems in scientiic computation. We discuss algorithmic issues underlying the design and implementation of the relevant components of TPIE and present performance results of programs written to solve a series of benchmark problems using our current TPIE prototype. Some of the benchmarks we present are based on the NAS parallel benchmarks 5], while others are of our own creation. We demonstrate that the CPU overhead required to manage I/O is small and that even with just a single disk the I/O overhead of I/O-eecient computation ranges from negligible to the same order of magnitude as CPU time. We conjecture that if we use a number of disks in parallel this overhead can be all but eliminated.
Measurement of scattering in X, C and L bands on wet and inundated soil surface for the monitoring of paddy fields using SAR data

Laboratory experiments were conducted to measure microwave scattering on specimens to simulate paddy fields for the purpose of developing microwave scattering model of paddy fields. In the experiment, the specimens were produced into fiber reinforced plastic (FRP) tube with 70 x 60 x 60 cm 3 volume. The specimens contained soils, water layer and paddy. X-band antennas measured the backscatter from the specimens, and the fully polarimetric data were decomposed into four components by applying the methodology proposed by Yamaguchi et al. [1]. The results show that the scattering of paddy to X-band microwave is composed of volume scattering mainly. However, it was also shown that the effects reflected from the edge of the FRP tube cannot be neglected. Therefore, further experiment will be necessary to examine the scattering of paddy, in which the tube should be replaced with another case material such as polystyrene case.
Overview of Genetically Engineered Mouse Models of Papillary and Anaplastic Thyroid Cancers: Enabling Translational Biology for Patient Care Improvement

The prognosis from thyroid cancer subtypes in humans covers a spectrum from “cured at almost 90%” to “100% lethal. ” Invasive and poorly differentiated forms of thyroid cancer are among the most aggressive human cancers, and there are few effective therapeutic options. Genetically engineered mice, based on mutations observed in patients, can accurately recapitulate the human disease and its progression, providing invaluable tools for the preclinical evaluation of novel therapeutic approaches. This overview details models developed to date as well as their uses for identifying novel anticancer agents. © 2015 by John Wiley & Sons, Inc.