Miracle-dz/UniFAR-FTUs huggingface dataset:
Correlation between roundhouse kick and countermovement jump performance

Background & Study Aim: Taekwondo (TKD) is a combat sport in which leg techniques are predominant. Roundhouse (bandal chagi) is one of the kicking techniques commonly used in competition. Evaluate and monitoring the power and accuracy of each blow is crucial for training process. Sports scientists and coaches have used the countermovement jump to evaluate the strength and power of lower limbs muscles. However, it is not a specific taekwondo test. Therefore, it was interesting to compare kick and jump performance in order to show the importance of monitoring training by specifics tests. The purpose of this study was to correlate the countermovement jump performance with the roundhouse kick performance in TKD athletes. It was hypothesized that there will not be an elevated correlation between them. Material & Methods: Thirty-one taekwondo athletes (18 males and 13 females), following familiarization procedures, performed three countermovement jumps and after about 10 minutes, three roundhouse kicks. Tests were performed in similar contact mats. There was an armoured inertial sensor inside a specific taekwondo racket. Results: There was a strong, positive and significant correlation between tests for group (r = 0.771, p<0.001). The correlation to females was moderate (r = 0.556, p<0.05) and not significant to males (r = 0.421, p = 0.082). The r2 value for group, females and males were 0.594, 0.309, and 0.177, respectively. Conclusions: Once speed kick test is more specific, we suggest that it might be better to monitoring the athletes’ performance by this test. The inertial sensor developed to this study is a simple and good way to monitoring the speed kick performance.
A New Method for Marshaling of Freight Train with Generalization Capability Based on the Processing Time

—This paper proposes a new marshaling method for assembling an outgoing train from freight cars incoming with a random order. In the proposed method, marshaling plans based on the processing time can be obtained by a reinforcement learning system. Also, the incoming freight cars are classified into severaì`sub-tracks'' searching better assignment in order to reduce the total processing time. Then, the number of sub-tracks utilized in the classification is obtained by learning in order to yield generalization capability. In order to evaluate the processing time, the total transfer distance of a locomotive and the total movement counts of freight cars are simultaneously considered. In the proposed method, each set of freight cars that have the same destination make a group, and the desirable group layout constitutes the best outgoing train. Then, the order of movements of freight cars, the position for each removed car, the layout of groups in a train, the arrangement of cars in a group and the number of cars to be moved are simultaneously optimized to achieve minimization of the total processing time for obtaining the desired arrangement of freight cars for an outbound train.
SVM-CASE: An SVM-Based Context Aware Security Framework for Vehicular Ad-Hoc Networks

Vehicular Ad-hoc Networks (VANETs) are known to be very susceptible to various malicious attacks. To detect and mitigate these malicious attacks, many security mechanisms have been studied for VANETs. In this paper, we propose a context aware security framework for VANETs that uses the Support Vector Machine (SVM) algorithm to automatically determine the boundary between malicious nodes and normal ones. Compared to the existing security solutions for VANETs, The proposed framework is more resilient to context changes that are common in VANETs, such as those due to malicious nodes altering their attack patterns over time or rapid changes in environmental factors, such as the motion speed and transmission range. We compare our framework to existing approaches and present evaluation results obtained from simulation studies.
Letter and category fluency in patients with frontal lobe lesions.

This study examines the hypothesis that patients with frontal lobe lesions are impaired on tests of letter but not category fluency. This hypothesis was proposed by Moscovitch (1994), based on a series of cognitive studies with young, normal participants. A group of patients with lateral prefrontal lesions and age-matched controls were tested on 2 tests of verbal fluency, the FAS task and a category fluency task that used semantic categories as cues (e.g., animals). Patients with frontal lobe lesions generated fewer items than controls on both letter and category fluency. This effect did not interact with the type of fluency test, suggesting that the frontal lobes are more generally involved in verbal fluency. Moreover, this pattern of findings, along with previous results of impaired free recall and remote retrieval in this patient group, suggests that patients with frontal lobe lesions do not efficiently organize and develop retrieval strategies.
Convex relaxations and Gramian rank constraints for sensor and actuator selection in networks

We propose a convex relaxation heuristic for sensor and actuator selection problems in dynamical networks using Gramian metrics. We also propose heuristic algorithms to enforce a rank constraint on the Gramian that can be used in conjunction with combinatorial greedy algorithms and the convex relaxation. This allows selection of sensor or actuator sets that optimize an objective function while preserving a certain amount of observability or controllability throughout the state space, combining previous methods that focus exclusively on either rank or Gramian metrics. We illustrate and compare the greedy and convex relaxation heuristics in several numerical examples involving random and regular networks.
Vimentin is involved in regulation of mitochondrial motility and membrane potential by Rac1

ABSTRACT In this study we show that binding of mitochondria to vimentin intermediate filaments (VIF) is regulated by GTPase Rac1. The activation of Rac1 leads to a redoubling of mitochondrial motility in murine fibroblasts. Using double-mutants Rac1(G12V, F37L) and Rac1(G12V, Y40H) that are capable to activate different effectors of Rac1, we show that mitochondrial movements are regulated through PAK1 kinase. The involvement of PAK1 kinase is also confirmed by the fact that expression of its auto inhibitory domain (PID) blocks the effect of activated Rac1 on mitochondrial motility. The observed effect of Rac1 and PAK1 kinase on mitochondria depends on phosphorylation of the Ser-55 of vimentin. Besides the effect on motility Rac1 activation also decreases the mitochondrial membrane potential (MMP) which is detected by ∼20% drop of the fluorescence intensity of mitochondria stained with the potential sensitive dye TMRM. One of important consequences of the discovered regulation of MMP by Rac1 and PAK1 is a spatial differentiation of mitochondria in polarized fibroblasts: at the front of the cell they are less energized (by ∼25%) than at the rear part.
The Antiquity of the Cam Deformity: A Comparison of Proximal Femoral Morphology Between Early and Modern Humans.

BACKGROUND The precise etiology of cam impingement continues to be incompletely understood. The prevailing hypothesis posits that the deformity arises as a developmental injury prior to skeletal maturation. There is a possible evolutionary role, with an aspherical femoral head affording upright humans better stability. We set out to identify the antiquity of the cam deformity to better understand the comparative roles of modern behavior and evolution in its development. METHODS We used 249 physical specimens of femora from the Libben osteological collection, a set of bones from an ancient population who lived between the eighth and the eleventh century. These femora were photographed in four different orientations, and six specific proximal femoral angles were measured. The values were also compared with those from modern human femora using the Student t test, with a two-tailed p value of 0.05 denoting significance. RESULTS In total, 249 femora from 175 individuals were included in the final analysis. The ages of the individuals ranged between seventeen and fifty-five years. Interobserver and intraobserver correlation was good or excellent for all variables measured. Compared with modern populations, ancient human hips were significantly more anteverted (19.96° versus 12.85°; p < 0.001) and varus (true neck-shaft angle, 121.96° versus 129.23°; p < 0.001). The alpha angle was significantly lower in ancient humans (35.33° versus 45.61°; p < 0.001), and none of the ancient femora met the modern criteria for a cam deformity (an alpha angle of >50°). CONCLUSIONS AND CLINICAL RELEVANCE It appears that the cam deformity was nonexistent among ancient humans and is perhaps predominantly a product of modern-day stresses. Further clinical investigation into behavioral modifications in adolescence is warranted to potentially prevent the development of deformity and impingement.
QaMC - QoS Aware Multicast router for NoC fabric

Collective communication support which has been playing a major role in network on chips (NoCs) is used for image processing, multimedia and other signal processing applications. Application Specific NoC utilizes multicasting (MC) and other services like reduction and scattering for parallel data processing. The proposed architecture introduces a new network model, wherein few extra network nodes named QaMC (Quality of Service Aware Multicast) routers have to be added to improve multicasting by providing a direct link to each individual router of the MC groups. It utilizes the concept of application mapping for the formation of MC groups. It also provides a circuit switched model of communication for unicasting through these direct links along with the normal unicasting without the usage of extra buffers. The direct link communication can also be utilized for Guaranteed Services (GSs), which is an added advantage. The proposed architecture along with QaMC routing algorithm enables efficient multicasting as well as guaranteed services in application specific NoCs. An efficient routing algorithm has also been proposed for the convenient flow of multicast packets as well as providing GS. The area overhead for the complete 4×4 mesh network obtained is of about 4.2 % which is comparably negligible and the concept can also be extended to 3D NoCs.
Skipping-Based Collaborative Recommendations inspired from Statistical Language Modeling

Due to the almost unlimited resource space on the Web, efficient search engines and recommender systems have become a key element for users to find resources corresponding to their needs. Recommender systems aims at helping users in this task by providing them some pertinent resources according to their context and their profiles, by applying various techniques such as statistical and knowledge discovery algorithms. One of the most successful approaches is Collaborative Filtering, which consists in considering user ratings to provide recommendations, without considering the content of the resources; however the ratings are the only criterion taken into account to provide the recommendations, although including some other criterion should enhance their accuracy. One such criterion is the context, which can be geographical, meteorological, social, etc. In this chapter we focus on the temporal context, more specifically on the order in which the resources were consulted. The appropriateness of considering the order is domain dependent: for instance, it seems of little help in domains such as online moviestores, in which user transactions are barely sequential; however it is especially appropriate for domains such as Web navigation, which has a sequential structure. We propose to follow this direction for this domain, the challenge being to find a low enough complexity sequential model while providing a better accuracy. We first put forward similarities between Web navigation and natural language, and propose to adapt statistical language models to Web navigation to compute recommendations. Second, we propose a new model inspired from the n-gram skipping model. This model has several advantages: (1) It has both a low time and a low space complexity while providing a full coverage, (2) it is able to handle parallel navigations and noise, (3) it is able to perform recommendations in an anytime framework, (4) weighting schemes are used to alleviate the importance of distant resources. Third, we provide a comparison of this SLM inspired model to the state of the art in terms of features, complexity, accuracy and robustness and present experimental results. Tests are performed on a browsing dataset extracted from Intranet logs provided by a French bank. Results show that the use of exponential decay weighting schemes when taking into account non contiguous resources highly improves the accuracy, and that the anytime configuration is able to provide a satisfying trade-off between an even lower computation time and a good accuracy while conserving a good coverage.
Bcl-XL Mutations Suppress Cellular Sensitivity to Antimycin A*

Cells expressing high levels of the BCL-XL anti-apoptotic protein are preferentially killed by the mitochondrial inhibitor antimycin A (AA). Computational modeling predicts a binding site for AA in the extended hydrophobic groove on BCL-XL, previously identified as an interface for dimerization to BAX and related proapoptotic proteins. Here, we identify BCL-XL hydrophobic groove mutants with normal cellular anti-apoptotic function but suppressed sensitivity to AA. The LD50 of AA for cells expressing BCL-XL mutants directly correlates with the measured in vitro dissociation constants for AA binding. These results indicate that BCL-XL is a principal target mediating AA cytotoxicity.
Evaluation of subcutaneously-implanted glucose sensors for continuous glucose measurements in hyperglycemic pigs.

BACKGROUND Subcutaneously-implanted glucose sensors for continuous glucose monitoring have the potential to replace serial blood glucose measurements. The objective of the present study was to test whether continuous glucose measurements could be obtained with glucose sensors implanted in the subcutis of pigs. Moreover, the in vivo biocompatibility of the sensors was evaluated since an inflammatory reaction may lead to drift in sensor-signaling. MATERIALS AND METHODS Two types of glucose sensor were implanted for 3 days in the subcutis of hyperglycemic pigs. The plasma glucose concentration was correlated to the sensor outputs, and tissue was sampled for histological evaluation. RESULTS There was a good correlation between the interstitial fluid and blood glucose levels. However, there was a statistical significantly difference in linearity from days 0 and 1 to day 2 (p<0.001) and variations in the sensitivity and background current of individual sensors were observed over time. The tissue reaction caused by the sensors was a mild focal subacute fibrinous dermatitis. CONCLUSION Continuous glucose measurement can be achieved by glucose sensors implanted in the subcutis of pigs. The observed drift in sensor signals over time may have been caused by heterophils, macrophages and/or fibrinogen at the tissue-sensor interface.
Virtual Topology for LEO Satellite Networks Based on Earth-Fixed Footprint Mode

In this letter, a formal model is given to clarify the dynamics and fixity of the virtual topology based on Virtual Node method for Low Earth Orbit (LEO) satellite networks. The formal model can generate few snapshots, well-proportioned snapshot length and less path changes than the physical topology with Satellite-fixed footprint mode. Moreover, it can effectively avoid path stretch and contraction deriving from the satellite's movement. Its application in Multi-layered satellite networks can also overcome the main limitation of conventional Satellite Group and Group Manager method.
Genotyping-By-Sequencing (GBS) Detects Genetic Structure and Confirms Behavioral QTL in Tame and Aggressive Foxes (Vulpes vulpes)

The silver fox (Vulpes vulpes) offers a novel model for studying the genetics of social behavior and animal domestication. Selection of foxes, separately, for tame and for aggressive behavior has yielded two strains with markedly different, genetically determined, behavioral phenotypes. Tame strain foxes are eager to establish human contact while foxes from the aggressive strain are aggressive and difficult to handle. These strains have been maintained as separate outbred lines for over 40 generations but their genetic structure has not been previously investigated. We applied a genotyping-by-sequencing (GBS) approach to provide insights into the genetic composition of these fox populations. Sequence analysis of EcoT22I genomic libraries of tame and aggressive foxes identified 48,294 high quality SNPs. Population structure analysis revealed genetic divergence between the two strains and more diversity in the aggressive strain than in the tame one. Significant differences in allele frequency between the strains were identified for 68 SNPs. Three of these SNPs were located on fox chromosome 14 within an interval of a previously identified behavioral QTL, further supporting the importance of this region for behavior. The GBS SNP data confirmed that significant genetic diversity has been preserved in both fox populations despite many years of selective breeding. Analysis of SNP allele frequencies in the two populations identified several regions of genetic divergence between the tame and aggressive foxes, some of which may represent targets of selection for behavior. The GBS protocol used in this study significantly expanded genomic resources for the fox, and can be adapted for SNP discovery and genotyping in other canid species.
Games against nature

In Com,puter Science, important concepts usually come with a plethora of alternative characterizations. The class PSPACE, for example, can be defined either as the class of problelns solvable in polynomially bounded space by a multitape Turing machine or some similar model, or, equivalently, as the class of problems reducible to some polynomial-depth combinatorial two-person game [Stocklneyer and Meyer, Schaefer]. Alternation [Chandra and Stockmeyer] is an interesting variant of the latter point of view. A more recent, also "problem-oriented" characterization of PSPACE is the one in terms of problems involving periodic objects [Orlin]. In this paper, we propose a new characterization of PSPACE, based on some of the most classical and well-looked at problems in Optimization: decision-making under uncertainty. Problems in this class are usually characterized by a discretetime random process, the parameters of which can be influenced by dynamic decisions. Decisions are based on the current state. The goal is to minimize thge expectation of some cost functional of the history of states and decisions. There is a vast . literature on the numerous variants of this problem; the reader is referred for a start to the books by [Denardo, Der.man, IIoward, Bertsekas]. Typically, such a problem is solved by dynamic programming (ill fact, decision-making under uncertainty. was the original and intend.ed application of this technique), with a time and space cost which are usually exponential in the description of the input. In a handful of now classical cases, more clever special techniques have yielded polynomialtime algorithms [Howard, Derman]. Linear programming is sometimes employed. We can formulate a decision problem under uncertain.ty as a new sort of game, in which one
An Improved Algorithm of Slotted-ALOHA Based on Multichannel Statistics

For the low delay requirements of Ad Hoc networks in high traffic-load, it mentioned an improved algorithm named Slotted ALOHA based on Multichannel Statistics (SAMS) . Compared to the widely used protocol of ALOHA, Slotted ALOHA, CSMA and TDMA, the result of SAMS simulation proved it can maintain very low delay of ensuring the high-priority data send successfully in high traffic-load.
Pay-as-you-go maintenance of precomputed nearest neighbors in large graphs

An important building block of many graph applications such as searching in social networks, keyword search in graphs, and retrieval of linked documents is retrieving the transitive neighbors of a node in ascending order of their distances. Since large graphs cannot be kept in memory and graph traversals at query time would be prohibitively expensive, the list of neighbors for each node is usually precomputed and stored in a compact form. While the problem of precomputing all-pairs shortest distances has been well studied for decades, efficiently maintaining this information when the graph changes is not as well understood. This paper presents an algorithm for maintaining nearest neighbor lists in weighted graphs under node insertions and decreasing edge weights. It considers the important case where queries are a lot more frequent than updates, and presents two approaches for transparently performing necessary index updates while executing queries. Extensive experiments with large graphs, including a subset of Twitter's user graph, demonstrate that the overhead for this maintenance is small.
Spatial Metrics and Image Texture for Mapping Urban Land Use

The arrival of new-generation, high-spatial-resolution satellite imagery (e.g., Ikonos) has opened up new opportunities for detailed mapping and analysis of urban land use. Drawing on the traditional approach used in aerial photointerpretation, this study investigates an “object-oriented” method to classify a large urban area into detailed land-use categories. Spatial metrics and texture measures are used to describe the spatial characteristics of land-cover objects within each land-use region as derived from interpreted aerial photographs. In assessing how land-use categories vary in their spatial configuration, spatial metrics were found to provide the most important information for differentiating urban land uses. A detailed land-use map with nine categories was derived for the Santa Barbara South Coast Region area. Results from our work suggest that the region-based method exploiting spatial metrics and texture measurements is a potential new avenue to extract detailed urban land-use information from highresolution satellite imagery.
Learning in Reality: A case study of Stanley, the robot that Won the DARPA Challenge

The Grand Challenge by the Defense Advances Research Projects Agency (DARPA) got a great impact on Machine Learning and Computer Vision research. Stanley was the ﬁrst robot which ﬁrstly was able to drive autonomously a 175 mile course in desert terrain which was a great success in autonomous driving which may be leading to autonomous cares in urban environment in the future. Stanley faced a bunch of problems which needed to be solved to drive autonomously through the course. Some of those Problems are the terrain which has obstacles which need to be avoided and another is the driving speed which has to be maintained to win the challenge. Stanley uses therefore GPS, laser range scanners and a color camera to classify the road into drivable and non-drivable area. This classiﬁcation is used to control speed and steering of the robot.
Establishment of mouse cell lines which constitutively secrete large quantities of interleukin 2, 3, 4 or 5, using modified cDNA expression vectors

Mouse cell lines of different lineages have been established which constitutively secrete large quantities of recombinant mouse interleukins (mIL2, mIL3, mIL4 or mIL5). An existing bovine papilloma virus‐based expression vector, pBV‐lMTHA, was modified to allow transformed X63Ag8‐653 myeloma cells, NIH 3T3 fibroblasts and C127 mammary tumor cells to stably carry multiple copies of the vector, to express the inserted cDNA encoding a single interleukin constitutively, and to secrete the interleukin in high quantities.