Miracle-dz/UniFAR-FTUs huggingface dataset:
Role of VHL, HIF1A and SDH on the expression of miR-210: Implications for tumoral pseudo-hypoxic fate

The hypoxia-inducible factor 1α (HIF-1α) and its microRNA target, miR-210, are candidate tumor-drivers of metabolic reprogramming in cancer. Neuroendocrine neoplasms such as paragangliomas (PGLs) are particularly appealing for understanding the cancer metabolic adjustments because of their associations with deregulations of metabolic enzymes, such as succinate dehydrogenase (SDH), and the von Hippel Lindau (VHL) gene involved in HIF-1α stabilization. However, the role of miR-210 in the pathogenesis of SDH-related tumors remains an unmet challenge. Herein is described an in vivo genetic analysis of the role of VHL, HIF1A and SDH on miR-210 by using knockout murine models, siRNA gene silencing, and analyses of human tumors. HIF-1α knockout abolished hypoxia-induced miR-210 expression in vivo but did not alter its constitutive expression in paraganglia. Normoxic miR-210 levels substantially increased by complete, but not partial, VHL silencing in paraganglia of knockout VHL-mice and by over-expression of p76del-mutated pVHL. Similarly, VHL-mutated PGLs, not those with decreased VHL-gene/mRNA dosage, over-expressed miR-210 and accumulate HIF-1α in most tumor cells. Ablation of SDH activity in SDHD-null cell lines or reduction of the SDHD or SDHB protein levels elicited by siRNA-induced gene silencing did not induce miR-210 whereas the presence of SDH mutations in PGLs and tumor-derived cell lines was associated with mild increase of miR-210 and the presence of a heterogeneous, HIF-1α-positive and HIF-1α-negative, tumor cell population. Thus, activation of HIF-1α is likely an early event in VHL-defective PGLs directly linked to VHL mutations, but it is a late event favored but not directly triggered by SDHx mutations. This combined analysis provides insights into the mechanisms of HIF-1α/miR-210 regulation in normal and tumor tissues potentially useful for understanding the pathogenesis of cancer and other diseases sharing similar underpinnings.
The Throughput and Access Delay of Slotted-Aloha With Exponential Backoff

The behavior of exponential backoff (EB) has challenged researchers ever since its introduction, but only approximate and partial results have been produced up to this date. This paper presents accurate results about the effect of protocol parameters on throughput and delay, assuming queues in saturation. Among the manifold results, we first introduce a simple model that provides close-form results for the approximated model known as “decoupling assumption. ” Since the latter fails to provide well approximated results in many cases, we also introduce a Markovian model able to trade the precision of the results with complexity even with an infinite number of users, enabling us to get definite throughput results, such as 0.3706 with binary EB, and 0.4303 with an optimized base. Analytical considerations allow to derive the tail of the access-delay distribution, found to be slowly decreasing and with no variance as the number of users goes to infinity. Taking into account the overall performance, preliminary results seem to indicate that the exponential base <inline-formula> <tex-math notation="LaTeX">$b=1.35$ </tex-math></inline-formula> is more appealing than the standard value <inline-formula> <tex-math notation="LaTeX">$b=2$ </tex-math></inline-formula>.
Parallel Multi-Label Propagation Based on Influence Model and Its Application to Overlapping Community Discovery

Finding communities in networks is one of the challenging issues in complex network research. We have to deal with very large networks that contain billions of vertices, which makes community discovery a computationally intensive work. Moreover, communities usually overlap each other, which greatly increases the difficulty of identifying the boundaries of communities. In this paper, we propose a parallel multi-label propagation algorithm (PMLPA) that enhances traditional multi-label propagation algorithm (MLPA) in two ways. First, the critical steps of MLPA are parallelized based on the MapReduce model to get higher scalability. Second, new label updating strategy is used to automatically determine the most valuable labels of each vertex. Furthermore, we study the improvement of PMLPA through considering the influence of vertices and labels on label updating. In this way, the importance of each label can be described with higher precision. Experiments on artificial and real networks prove that the proposed algorithms can achieve both high discovering accuracy and high scalability.
Impact of Blood Flow Restriction Exercise on Muscle Fatigue Development and Recovery

PurposeThe present study was designed to provide mechanistic insight into the time course and etiology of muscle fatigue development and recovery during and after low-intensity exercise when it is combined with blood flow restriction (BFR). MethodsSeventeen resistance-trained males completed four sets of low-intensity isotonic resistance exercise under two experimental conditions: knee extension exercise (i) with BFR and (ii) without BFR (CON). Neuromuscular tests were performed before, during (immediately after each set of knee extension exercise), and 1, 2, 4, and 8 min after each experimental condition. Maximal voluntary torque, quadriceps twitch torque in response to paired electrical stimuli at 10 Hz (PS10) and 100 Hz (PS100), PS10·PS100−1 ratio as an index of low-frequency fatigue, and voluntary activation were measured under isometric conditions. Perceptual and EMG data were recorded during each exercise condition. ResultsAfter the first set of exercise, BFR induced significantly greater reductions in maximal voluntary torque, PS100, and PS10·PS100−1 ratio compared with CON. These parameters progressively declined throughout the BFR protocol but recovered substantially within 2 min postexercise when blood flow was restored. Neither a progressive decline in the course of the exercise protocol nor a substantial recovery of these parameters occurred during and after CON. Only at exercise termination, voluntary activation differed significantly between BFR and CON with greater reductions during BFR. ConclusionAt the early stage of exercise, BFR exacerbated the development of muscle fatigue mainly due to a pronounced impairment in contractile function. Despite the high level of muscle fatigue during BFR exercise, the effect of BFR on muscle fatigue was diminished after 2 min of reperfusion, suggesting that BFR has a strong but short-lasting effect on neuromuscular function.
European Conference on Information Systems ( ECIS ) Summer 10-6-2011 FROM AGILE TO LEAN : THE PERSPECTIVES OF THE TWO AGILE ONLINE COMMUNITIES OF INTEREST

In the last several years there has been a noticeable focus shift of agile methods from eXtreme Programming (XP) and Scrum to Lean approaches, which is indicated as “from agile to lean”. However our understanding of the driving factors behind this focus shift is very limited. The study proposed in this paper attempts to investigate the shift through a content analysis of two major agile mailing lists. The expected result is a set of driving factors behind the shift from agile to lean, which can contribute to a better understanding of if and why Lean software development is “the next wave of
Implementation of Human-Machine Synchronization Control for Active Rehabilitation Using an Inertia Sensor

According to neuro-rehabilitation practice, active training is effective for mild stroke patients, which means these patients are able to recovery effective when they perform the training to overcome certain resistance by themselves. Therefore, for rehabilitation devices without backdrivability, implementation of human-machine synchronization is important and a precondition to perform active training. In this paper, a method to implement this precondition is proposed and applied in a user’s performance of elbow flexions and extensions when he wore an upper limb exoskeleton rehabilitation device (ULERD), which is portable, wearable and non-backdrivable. In this method, an inertia sensor is adapted to detect the motion of the user’s forearm. In order to get a smooth value of the velocity of the user’s forearm, an adaptive weighted average filtering is applied. On the other hand, to obtain accurate tracking performance, a double close-loop control is proposed to realize real-time and stable tracking. Experiments have been conducted to prove that these methods are effective and feasible for active rehabilitation.
Connectivity-Driven Parcellation Methods for the Human Cerebral Cortex

In this thesis, we present robust and fully-automated methods for the subdivision of the entire human cerebral cortex based on connectivity information. Our contributions are four-fold: First, we propose a clustering approach to delineate a cortical parcellation that provides a reliable abstraction of the brain's functional organisation. Second, we cast the parcellation problem as a feature reduction problem and make use of manifold learning and image segmentation techniques to identify cortical regions with distinct structural connectivity patterns. Third, we present a multi-layer graphical model that combines within- and between-subject connectivity, which is then decomposed into a cortical parcellation that can represent the whole population, while accounting for the variability across subjects. Finally, we conduct a large-scale, systematic comparison of existing parcellation methods, with a focus on providing some insight into the reliability of brain parcellations in terms of reflecting the underlying connectivity, as well as, revealing their impact on network analysis. We evaluate the proposed parcellation methods on publicly available data from the Human Connectome Project and a plethora of quantitative and qualitative evaluation techniques investigated in the literature. Experiments across multiple resolutions demonstrate the accuracy of the presented methods at both subject and group levels with regards to reproducibility and fidelity to the data. The neuro-biological interpretation of the proposed parcellations is also investigated by comparing parcel boundaries with well-structured properties of the cerebral cortex. Results show the advantage of connectivity-driven parcellations over traditional approaches in terms of better fitting the underlying connectivity.
Effects of water absorption and osmotic degradation on long-term behavior of glass fiber reinforced polyester

Glass fiber reinforced polyester composites, with gelcoat, are widely used as structural materials for hulls, pools, pipes, and tanks in aggressive environments, despite the lack of knowledge concerning their resistance to water in the long term. In addition, these materials may be damaged through an osmotic process, especially when immersed in water, as are boat hulls, and this phenomenon can lead to a delamination of the gelcoat and of the laminate plies. The aim of this experimental study is to evaluate the mechanical characteristics with time of orthotropic laminates subjected to accelerated tests of humid aging. The evolution of the properties with water absorption is followed by a nondestructive test procedure based on vibrational mode analysis. The results are additionally confirmed by quasi-static bending and shear tests. It is shown that the main effects of water on the composite mechanical properties are the plasticization of the matrix an the osmotic delamination of the plies ; on the other hand, gelcoat blistering had no influence on the durability. This paper highlights the need for and the complementarity of both nondestructive and destructive mechanical tests for studying the long-term behavior of composites in marine environments.
Optimal receiver design for SCMA system

Sparse code multiple access (SCMA) is a promising non-orthogonal multiple access scheme for 5G systems. In this paper, based on the sphere decoding (SD), we design an optimal receiver for SCMA, which provides much lower complexity than the maximum likelihood (ML) detection without sacrifice of the optimal performance. Regarding the coded SCMA system, we propose a list sphere decoding (LSD) method to output each user's bit soft decisions to the corresponding channel decoders. In addition, the existing lattice points in the list are employed to set the original radius so as to further reduce the complexity of LSD. The performance and complexity analyses indicate that the proposed optimal receiver provides notable gain compared to the most popular SCMA receiver equipped with the message passing algorithm.
Strategies for Re-Training a Pruned Neural Network in an Edge Computing Paradigm

Construction of robust and accurate deep neural networks (DNNs) is a computationally demanding and time-consuming process. Such networks also end up being memory intensive. Today, there is ever-increasing need to provide proactive and personalized support for users of smart devices. We could provide better personalization if we have the ability to update/train the DNN on edge devices. Also, by moving some computation to the edge of the cloud infrastructure, we could reduce the load on computing clusters, thus providing them more resources to handle core and complex tasks. To this end, weight pruning for DNNs has been proposed to reduce their storage footprint by an order of magnitude. However, it is yet unclear as to how to update/re-train DNNs once they are deployed on mobile devices. In this paper, we introduce the concept of re-training of pruned networks that should aid personalization of smart devices as well as increase their fault tolerance. We assume that the data used to re-train the pruned network comes from a distribution similar to what used in the original, unpruned network. We propose various strategies for pruning and re-training the networks and show that we may obtain a significant improvement on the new data while minimizing the reduction in performance on the original data.
The principles of beautiful Web design

The Principles of Beautiful Web Design is the ideal book for people who can build websites, but are seeking the skills and knowledge to visually enhance their sites.This book will teach you how to:Understand what makes "good design," from discovery through to implementationUse color effectively, develop color schemes, and create a paletteCreate pleasing layouts using grids, the rule of thirds, and symmetryEmploy textures: lines, points, shapes, volumes, and depthApply typography to make ordinary designs look greatChoose, edit, and position effective imageryAnd lots more.This easy-to-follow guide is illustrated with beautiful, full-color examples, and will lead you through the process of creating great designs from start to finish. The third edition of this book has been greatly revised and now features:Updated and expanded coverage of mobile and responsive web design (RWD)A new sample projectNew sections on user interface and icon designCommon user-interface patterns and resources
xMWAS: a data-driven integration and differential network analysis tool

Summary Integrative omics is a central component of most systems biology studies. Computational methods are required for extracting meaningful relationships across different omics layers. Various tools have been developed to facilitate integration of paired heterogenous omics data; however most existing tools allow integration of only two omics datasets. Furthermore, existing data integration tools do not incorporate additional steps of identifying sub-networks or communities of highly connected entities and evaluating the topology of the integrative network under different conditions. Here we present xMWAS, a software for data integration, network visualization, clustering, and differential network analysis of data from biochemical and phenotypic assays, and two or more omics platforms. Availability and implementation https://kuppal.shinyapps. io/xmwas (Online) and https://github.com/kuppal2/xMWAS/ (R). Contact kuppal2@emory.edu. Supplementary information Supplementary data are available at Bioinformatics online.
Three-dimensional cohesive modeling of impact damage of composites

The objective of this work is to establish the applicability of cohesive theories of fracture in situations involving material interface, material heterogeneity (e.g., layered composites), material anisotropy(e.g., fiber-reinforced composites), shear cracks, intersonic dynamic crack growth and dynamic crack branching. The widely used cohesive model is extended to orthotropic range. The so-developed computational tool, completed by a self-adaptive fracture procedure and a frictional contact algorithm, is capable of following the evolution of three-dimensional damage processes, modeling the progressive decohesion of interfaces and anisotropic materials. The material parameters required by cohesive laws are directly obtained from static experiments. The ability of the methodology to simulate diverse problems such as delamination between fibers of graphite/epoxy composites, as well as sandwich structures and branching within brittle bulk materials has been demonstrated.
Deterministic Distributed Edge-Coloring via Hypergraph Maximal Matching

We present a deterministic distributed algorithm that computes a (2&#x03B4;-1)-edge-coloring, or even list-edge-coloring, in any n-node graph with maximum degree &#x03B4;, in O(log^8 &#x03B4; &#x22C5; log n) rounds. This answers one of the long-standing open questions of distributed graph algorithms} from the late 1980s, which asked for a polylogarithmic-time algorithm. See, e.g., Open Problem 4 in the Distributed Graph Coloring book of Barenboim and Elkin. The previous best round complexities were 2^{O(&#x221A;{log n})} by Panconesi and Srinivasan [STOC92] and &#x00D5;(&#x221A;{&#x03B4;}) + O(log^* n) by Fraigniaud, Heinrich, and Kosowski [FOCS16]. A corollary of our deterministic list-edge-coloring also improves the randomized complexity of (2&#x03B4;-1)-edge-coloring to poly(loglog n) rounds.The key technical ingredient is a deterministic distributed algorithm for hypergraph maximal matching, which we believe will be of interest beyond this result. In any hypergraph of rank r &#x2014; where each hyperedge has at most r vertices &#x2014; with n nodes and maximum degree &#x03B4;, this algorithm computes a maximal matching in O(r^5 log^{6+log r } &#x03B4; &#x22C5; log n) rounds.This hypergraph matching algorithm and its extensions also lead to a number of other results. In particular, we obtain a polylogarithmic-time deterministic distributed maximal independent set (MIS) algorithm for graphs with bounded neighborhood independence, hence answering Open Problem 5 of Barenboim and Elkins book, a \big((log &#x03B4;/&#x03B5;)^{O(log 1/&#x03B5;)}\big)-round deterministic algorithm for (1+&#x03B5;)-approximation of maximum matching, and a quasi-polylogarithmic-time deterministic distributed algorithm for orienting &#x03BB;-arboricity graphs with out-degree at most \lceil (1+&#x03B5;)&#x03BB; \rceil, for any constant &#x03B5; 0, hence partially answering Open Problem 10 of Barenboim and Elkins book.
Use of metabolomics and lipidomics to evaluate the hypocholestreolemic effect of Proanthocyanidins from grape seed in a pig model.

SCOPE This work aims to evaluate changes in the fecal metabolomic profile due to grape seed extract (GSE) intake by untargeted and targeted analysis using high resolution mass spectrometry in conjunction with multivariate statistics. METHODS AND RESULTS An intervention study with six crossbred female pigs was performed. The pigs followed a standard diet for 3 days, then they were fed with a supplemented diet containing 1% (w/w) of MegaNatural® Gold grape seed extract for 6 days. Fresh pig fecal samples were collected daily. A combination of untargeted high resolution mass spectrometry, multivariate analysis (PLS-DA), data-dependent MS/MS scan, and accurate mass database matching was used to measure the effect of the treatment on fecal composition. The resultant PLS-DA models showed a good discrimination among classes with great robustness and predictability. A total of 14 metabolites related to the GSE consumption were identified including biliary acid, dicarboxylic fatty acid, cholesterol metabolites, purine metabolites, and eicosanoid metabolites among others. Moreover, targeted metabolomics using GC-MS showed that cholesterol and its metabolites fecal excretion was increased due to the proanthocyanidins from grape seed extract. CONCLUSION The results show that oligomeric procyanidins from GSE modifies bile acid and steroid excretion, which could exert a hypocholesterolemic effect.
AReNA: Adaptive Distributed Catalog Infrastructure Based On Relevance Networks

Wide area applications (WAAs) utilize a WAN infrastructure (e.g., the Internet) to connect a federation of hundreds of servers with tens of thousands of clients. Earlier generations of WAA relied on Web accessible sources and the http protocol for data delivery. Recent developments such as the PlanetLab [8] testbed is now demonstrating an emerging class of data- and compute- intensive wide area applications.
Toughening of Polystyrene with Ethylene-Propylene-Diene Terpolymer (EPDM) Compatibilized by Styrene-Butadiene-Styrene Block Copolymer (SBS)

Polystyrene (PS) was toughened with ethylene-propylene-diene terpolymer (EPDM) in the presence of styrene-butadiene-styrene block copolymer (SBS). Incorporation of SBS into the PS/EPDM blends clearly improved the impact properties. For PS/EPDM/SBS (mass ratio: 69/21/10 blends, the notched Charpy impact strength reached a maximimum value of 26.3 kJm 2 . Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) showed that SBS was distributed on the interface between PS and EPDM. Butanone extraction and FTIR analysis found that there was a grafting reaction between PS and EPDM phase during melt compounding. Shearing and processing rheological behaviors of blends were evaluated with a Haake capillary rheometer and a torque rheometer, respectively.
Simulations of fiber braided bending actuator: Investigation on position of fiber layer placement and air chamber diameter

Over recent years, studies on soft mechanism are rapidly being paid to attention especially in pneumatic actuator field. The actuator should provide sufficient force and flexibility in movement. The flexibility feature is vital in bending motion which needed in soft robotic actuation. There is no conventional fiber sleeve on single chamber actuator that can offer bending motion. In this paper, a new bending type actuator is introduced which the bending motion can be realized when braided fibers reinforcements on the cylindrical actuator rubber inner layer are formed from two different fiber angles. Two design parameters; position of fiber layer placement and air chamber diameter were varied and simulated to obtain the best specification of the proposed actuator design. The effects given by each design parameter were discussed and the dominant design parameter is also acknowledged from the FEM analysis. Significant bending motion was realized from the best model simulated. Actuator model with largest air chamber diameter and has the outermost position of fiber layer from the center point shows the highest bending capability.