Miracle-dz/UniFAR-FTUs huggingface dataset:
Volumizing effect of a new hyaluronic acid sub‐dermal facial filler: A retrospective analysis based on 102 cases

Introduction: Many signs of aging are due to the loss of subcutaneous fat. Dermal fillers are non‐surgical cosmetic treatments used to restore facial volume. Voluma® is a new hyaluronic acid sub‐dermal facial filler. The objective of this study was to assess its effectiveness in maintaining increased volume for up to 18 months post‐treatment and its safety. Methods: Retrospective record analysis was made for 102 patients (93 females, nine males; mean age: 51.27 years) who received Voluma injected into the midface. All patients were assessed at baseline and at 1 month and 6–18 months post‐injection. Results: Investigator Global Aesthetic Improvement assessment after 1 month and 6–18 months showed that most patients were ‘much’ or ‘very much’ improved. Investigator volume loss assessment confirmed that most patients were either stage 1 or 2 (normal or slight ptosis) 1 month post‐treatment, which was maintained at 6–18 months. Patient efficacy assessment was ‘very good’ or ‘good’ in most cases. Conclusions: Voluma provides aesthetic improvements according to investigator and patient assessment for up to 18 months post‐treatment. Combination treatment comprising facial fillers and botulinum neurotoxin can enhance treatment benefits. Further methodologically rigorous studies are required to establish the performance of Voluma alone and in combination.
Camera compensation using feature projection matrix for person re-identification

Matching individuals across a group of spatially non-overlapping surveillance cameras, also known as person re-identification, has recently attracted a lot of research interests. Current methods mainly focus on feature extraction or metric learning, which directly compare person images captured by different cameras, but seldom consider device differences caused by various surveillance conditions, e.g. view switching, scale zooming and illumination variation. Although brightness transfer function was proposed to address the problem of illumination variation, it could not handle view and scale changes among various cameras. In this paper, we propose an effective data-driven method to conquer device differences in the practical surveillance camera network. More precisely, with the help of a set of labelled pair-wise person images captured by two disjoint cameras, a feature projection matrix can be learned to project the person images of one camera to the feature space of the other camera, and thus images from these two different cameras can be accurately compared in a common feature space. Extensive comparative experiments conducted on three standard datasets have shown the promising prospect of our proposed methods.
A hierarchical statistical modeling approach for the unsupervised 3D reconstruction of the scoliotic spine

In this paper, we propose a new and accurate 3D reconstruction technique for the scoliotic spine from a pair planar and conventional radiographic images (postero-anterior and lateral). The proposed model uses a priori hierarchical global knowledge, both on the geometric structure of the whole spine and of each vertebra. More precisely, it relies on the specification of two 3D templates. The first, a rough geometric template on which rigid admissible deformations are defined, is used to ensure a crude registration of the whole spine. 3D reconstruction is then refined for each vertebra, by a template on which nonlinear admissible global deformations are modeled, with statistical modal analysis of the pathological deformations observed on a representative scoliotic vertebra population. This unsupervised coarse-to-fine 3D reconstruction procedure is stated as a double energy function minimization problems efficiently solved with a stochastic optimization algorithm. The proposed method, tested on several pairs of biplanar radiographic images with scoliotic deformities, is comparable in terms of accuracy with the classical CT-scan technique while being unsupervised and requiring a lower amount of radiation for the patient.
Multilevel Segmentation of Histopathological Images Using Cooccurrence of Tissue Objects

This paper presents a new approach for unsupervised segmentation of histopathological tissue images. This approach has two main contributions. First, it introduces a new set of high-level texture features to represent the prior knowledge of spatial organization of the tissue components. These texture features are defined on the tissue components, which are approximately represented by tissue objects, and quantify the frequency of two component types being cooccurred in a particular spatial relationship. As they are defined on components, rather than on image pixels, these object cooccurrence features are expected to be less vulnerable to noise and variations that are typically observed at the pixel level of tissue images. Second, it proposes to obtain multiple segmentations by multilevel partitioning of a graph constructed on the tissue objects and combine them by an ensemble function. This multilevel graph partitioning algorithm introduces randomization in graph construction and refinements in its multilevel scheme to increase diversity of individual segmentations, and thus, improve the final result. The experiments on 200 colon tissue images reveal that the proposed approach-the object cooccurrence features together with the multilevel segmentation algorithm-is effective to obtain high-quality results. The experiments also show that it improves the segmentation results compared to the previous approaches.
Design and analysis of the WCCI 2010 active learning challenge

We organized a data mining challenge on “active learning” for IJCNN/WCCI 2010, addressing machine learning problems where labeling data is expensive, but large amounts of unlabeled data are available at low cost. Examples include handwriting and speech recognition, document classification, vision tasks, drug design using recombinant molecules and protein engineering. Such problems might be tackled from different angles: learning from unlabeled data or active learning. In the former case, the algorithms must satisfy themselves with the limited amount of labeled data and capitalize on the unlabeled data with semi-supervised learning methods. Several challenges have addressed this problem in the past. In the latter case, the algorithms may place a limited number of queries to get new sample labels. The goal in that case is to optimize the queries and the problem is referred to as active learning. While the problem of active learning is of great importance, organizing a challenge in that area is non trivial. This is the problem we have addressed, and we describe our approach in this paper. The “active learning” challenge is part of the WCCI 2010 competition program (http://www.wcci2010. org/competition-program). The website of the challenge remains open for submission of new methods beyond the termination of the challenge as a resource for students and researchers (http://clopinet.com/al).
Innovative Test Techniques for Advanced Technology Nodes

The introduction of nanometer technologies, has allowed the semiconductor industry to keep pace with increased performance-capacity demands from consumers. This has brightened the prospects for future industry growth; however, new technologies come with new challenges. Semiconductor test costs have been growing steadily. Testing techniques for integrated circuits are today facing many exciting and complex challenges. In the era of large systems embedded in a single system-on-chip (SOC) and fabricated in continuously shrinking technologies, it is important to ensure correct behavior of the whole system. This work addresses the calls for the design and implementation of novel test strategies which provide high quality test. This paper within the context of semiconductor test, briefly describes the significant contributions made in the diverse areas of Reliability, SelfHeating, Ultra-Low Voltage Processors, Adaptive Voltage Scaling, Analysis of Timing Margins & IP Qualification.
Content Based Image Retrieval with Graphical Processing Unit

— CBIR is the method of searching the digital images from an image database. “Content-based” means that the search analyzes the contents of the image rather than the metadata such as colours, shapes, textures, or any other information that can be derived from the image itself. The GPU is a powerful graphics engine and a highly parallel programmable processor having better efficiency and high speed that overshadows CPU. It is used in high performance computing system. The implementation of GPU can be done with CUDA C. Due to its highly parallel structure it is used in a number of real time applications like image processing, computational fluid mechanics, medical imaging etc. Graphical Processors Units (GPU) is more common in most image processing applications due to multithread execution of algorithms, programmability and low cost. In this paper, we are explaining the parallel implementation of CBIR with GPU. We have shown various stages of CBIR with GPU results into better performance as well as speed ups. We have given a review of various techniques that can be practised for high performance CBIR stages with Graphics Processing Units.
A conditional transgenic reporter of presynaptic terminals reveals novel features of the mouse corticospinal tract

In many neurodegenerative disorders, including amyotrophic lateral sclerosis (ALS), synaptic alterations precede the demise of the neuronal cell, making synapses a useful vantage point from which to monitor the onset and progression of clinical signs and pathological changes. While murine models of ALS display many features in common with the clinical picture observed in patients, corticospinal tract (CST) involvement is usually less severe in mice than the picture observed in humans. In this paper we describe the characterization of a new conditional transgenic line obtained by targeted integration of a GFP-VAMP2 fusion gene into the Rosa26 locus, and devised to permit the detection of genetically defined presynaptic terminals in wild type mice and murine models of neural disorders. This reporter molecule is selectively enriched in presynaptic boutons, significantly reducing the background signal produced by fibers of passage. The specific features of this reporter line allow us to strongly support the view that murine CST terminals give rise to very few direct contacts with spinal motor neurons. Moreover, the evidence described here reveals the existence of previously uncharacterized, putative direct connections between CST presynaptic boutons and Renshaw neurons in the spinal cord. These results constitute a proof of concept for the potential application of this indicator line to morphological analyses of wild type and diseased synapses.
Ieee Transactions on Image Processing { Submitted in April 2000 Multiple Motion Segmentation with Level Sets

This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version will be superseded. Abstract|Segmentation of motion in an image sequence is one of the most challenging problems in image processing, while at the same time one that nds numerous applications. To date, a wealth of approaches to motion segmen-tation have been proposed. Many of them suuer from the local nature of models used. Global models, such as those based on Markov random elds, perform, in general, better. In this paper, we propose a new approach to motion segmentation that is based on a global model. The novelty of the approach is twofold. First, inspired by recent work of other researchers we formulate the problem as that of region competition, but we solve it using the level set methodology. The key features of a level set representation, as compared to active contours, often used in this context, are its ability to handle variations in the topology of the segmentation and its numerical stability. The second novelty of the paper is the formulation in which, unlike in many other motion seg-mentation algorithms, we do not use intensity boundaries as an accessory; the segmentation is purely based on motion. This permits accurate estimation of motion boundaries of an object even when its intensity boundaries are hardly visible. Since occasionally intensity boundaries may prove beneecial, we extend the formulation to account for the coincidence of motion and intensity boundaries. We also show how to control the segmentation topology and we generalize the approach to multiple motions. We discuss possible dis-cretizations of the evolution (PDE) equations and we give details of an initialization scheme so that the results could be duplicated. We show numerous experimental results for various formulations on natural images with either synthetic or natural motion.
Differential regulation of adrenergic receptor development by sympathetic innervation

Rat sweat glands provide an interesting model system for a developmental study of adrenergic receptor expression because their sympathetic innervation undergoes a switch from a nonadrenergic to cholinergic and peptidergic phenotype. alpha 1B, alpha 2B, and beta 2 receptors are expressed in rat footpads; alpha 1 and beta 2 receptors are localized specifically to sweat glands, and alpha 2 receptors also are expressed in other tissues. alpha 1 and, to a lesser extent, beta 2 receptors decrease during development, whereas alpha 2 levels remain relatively constant. Decreased receptor expression is accompanied by the loss of alpha 1-stimulated inositol phosphate accumulation, but no change in beta-stimulated cAMP production. The number of alpha 1 and beta 2 receptors decreases after P21, when the sympathetic innervation no longer produces catecholamines. Neonatal sympathectomy causes a partial failure of alpha 1 downregulation, but has no effect on beta 2 or alpha 2 receptor levels. Therefore, at least two distinct mechanisms regulate development of adrenergic receptors in sweat glands. Innervation-independent processes control developmental expression of alpha 1, beta 2, and alpha 2 receptors, and an additional, innervation- dependent mechanism influences expression of alpha 1 receptors. Denervation at postnatal day 20, when the sympathetic innervation is cholinergic and peptidergic, results in retention of alpha 1 receptors, but cholinergic blockade begun at P20 does not. These results indicate that regulation of receptor expression in sweat glands is complex, and suggest that the innervation-dependent factors that decrease alpha 1 levels during development act through a nonadrenergic, noncholinergic mechanism.
Move from Perturbed scheme to exponential weighting average

In an online decision problem, one makes decisions often with a pool of decision sequence called experts but without knowledge of the future. After each step, one pays a cost based on the decision and observed rate. One reasonal goal would be to perform as well as the best expert in the pool. The modern and well-known way to attain this goal is the algorithm of exponential weighting. However, recently, another algorithm called follow the perturbed leader is developed and achieved about the same performance. In our work, we first show the properties shared in common by the two algorithms which explain the similarities on the performance. Next we will show that for a specific perturbation, the two algorithms are identical. Finally, we show with some examples that follow-the-leader style algorithms extend naturally to a large class of structured online problems for which the exponential algorithms are inefficient.
Omnipotence Without Omniscience: Efficient Sensor Management for Planning

Classical planners have traditionally made the closed world assumption — facts absent from the planner's world model are false. Incomplete-information planners make the open world assumption — the truth value of a fact absent from the planner's model is unknown, and must be sensed. The open world assumption leads to two difficulties: (1) How can the planner determine the scope of a universally quantified goal? (2) When is a sensory action redundant, yielding information already known to the planner? This paper describes the fully-implemented XII planner, which solves both problems by representing and reasoning about local closed world information (LCW). We report on experiments utilizing our UNIX softbot (software robot) which demonstrate that LCW can substantially improve the softbot's performance by eliminating redundant information gathering.
New insights into the role of dietary spermine on inflammation, immune function and related-signalling molecules in the thymus and spleen of piglets

ABSTRACT This study aimed to determine the effects of dietary spermine supplementation on the inflammatory response and immune function of the thymus and spleen in piglets. Eighty suckling piglets were randomly assigned to receive adequate nutrients supplemented with spermine (0.4 mmol/kg body weight) or restricted nutrient intake supplemented with normal saline for 7 h or 3, 6 and 9 days in pairs. Regardless of treatment time, spermine supplementation decreased (p < 0.05, compared with the controls) the following: (1) tumour necrosis factor α (TNF-α), interleukin (IL)-1β, 2 and 6, and interferon (IFN)-γ levels in serum; (2) gene expression of cluster of differentiation 8 and integrin beta-2 in the thymus and spleen and the lymphocyte function-associated antigen 1 in the thymus; (3) mRNA levels of TNF-α, IL 1β, 2, 6, and 12, IFN-γ and inducible nitric oxide synthase in the thymus and spleen, as well as IL-8 in the spleen; and (4) eukaryotic IF4E-binding protein 1, Janus kinase 2, signal transducer and activator of transcription 3, and nuclear factor-kappa B P65 gene transcriptions in the thymus and spleen. By contrast, spermine supplementation increased (p < 0.05) the following: (1) immunoglobulin M, IL-10, and transforming growth factor β1 gene expression, as well as (2) relative mRNA levels of mammalian target of rapamycin (mTOR) and ribosomal protein S6 kinase 1 in the thymus and spleen. These effects were also observed upon prolonged spermine administration (p < 0.05). In summary, dietary spermine supplementation can alleviate inflammatory response, enhance the immune function and regulate the gene expression of signalling molecules related to inflammation.
Physical self-concept and participation in physical activity in college students.

INTRODUCTION The purpose of this study was to test for reciprocal relations between physical self-concept (PSC) and participation in physical activity (PA). We hypothesized specific bidirectional relations between PSC dimensions (i.e., perceived endurance, sport competence, and strength and body attractiveness) and participation in corresponding types of PA (i.e., aerobic exercise, team or individual sports, and strength training). METHODS Data were gathered from a questionnaire administered to 386 college students on two occasions (3-month interval) to assess PSC and participation in PA. RESULTS Structural equation modeling revealed significant paths between each PSC dimension and a corresponding type of PA. Students reported more frequent participation in a specific PA when their PSC concerning the activity was high. However, participation in a given PA did not predict subsequent PSC in the corresponding PA, suggesting unidirectional effects of previous PSC on subsequent participation in PA. CONCLUSIONS These results suggest that strategies that contribute to reinforce PSC are primordial and should be targeted as key components for designing effective PA behavior change interventions among college students.
Sleep Moderates the Association Between Response Inhibition and Self-Regulation in Early Childhood

Early childhood is a time of rapid developmental changes in sleep, cognitive control processes, and the regulation of emotion and behavior. This experimental study examined sleep-dependent effects on response inhibition and self-regulation, as well as whether acute sleep restriction moderated the association between these processes. Preschool children (N = 19; 45.6 ± 2.2 months; 11 female) followed a strict sleep schedule for at least 3 days before each of 2 morning behavior assessments: baseline (habitual nap/night sleep) and sleep restriction (missed nap/delayed bedtime). Response inhibition was evaluated via a go/no-go task. Twelve self-regulation strategies were coded from videotapes of children while attempting an unsolvable puzzle. We then created composite variables representing adaptive and maladaptive self-regulation strategies. Although we found no sleep-dependent effects on response inhibition or self-regulation measures, linear mixed-effects regression showed that acute sleep restriction moderated the relationship between these processes. At baseline, children with better response inhibition were more likely to use adaptive self-regulation strategies (e.g., self-talk, alternate strategies), and those with poorer response inhibition showed increased use of maladaptive self-regulation strategies (e.g., perseveration, fidgeting); however, response inhibition was not related to self-regulation strategies following sleep restriction. Our results showing a sleep-dependent effect on the associations between response inhibition and self-regulation strategies indicate that adequate sleep facilitates synergy between processes supporting optimal social-emotional functioning in early childhood. Although replication studies are needed, findings suggest that sleep may alter connections between maturing emotional and cognitive systems, which have important implications for understanding risk for or resilience to developmental psychopathology.
MAGNETIC PRANDTL NUMBER DEPENDENCE OF THE KINETIC-TO-MAGNETIC DISSIPATION RATIO

Using direct numerical simulations of three-dimensional hydromagnetic turbulence, either with helical or non-helical forcing, we show that the kinetic-to-magnetic energy dissipation ratio always increases with the magnetic Prandtl number, i.e., the ratio of kinematic viscosity to magnetic diffusivity. This dependence can always be approximated by a power law, but the exponent is not the same in all cases. For non-helical turbulence, the exponent is around 1/3, while for helical turbulence it is between 0.6 and 2/3. In the statistically steady state, the rate of energy conversion from kinetic into magnetic by the dynamo must be equal to the Joule dissipation rate. We emphasize that for both small-scale and large-scale dynamos, the efficiency of the energy conversion depends sensitively on the magnetic Prandtl number, and thus on the microphysical dissipation process. To understand this behavior, we also study shell models of turbulence and one-dimensional passive and active scalar models. We conclude that the magnetic Prandtl number dependence is qualitatively best reproduced in the one-dimensional model as a result of dissipation via localized Alfvén kinks.