Miracle-dz/UniFAR-FTUs huggingface dataset:
The Reliability of Lactate Measurements During Exercise

The purpose of this study was to establish the reliability of lactate threshold (LT) measurement across days. Twelve endurance-trained males aged 21-44 years participated in the study. Blood lactate concentration in capillary whole blood was measured at rest and at completion of 5 minute stages on a treadmill at 60%, 65%, 71%, 77%, 83% and 89% of VO2max during 3 separate days of testing. Velocity at LT (LT(VEL)), oxygen consumption at LT (LT(VO2)), and heart rate at LT (LT(HR)) are determined using each of the following criteria: fixed lactate concentrations of 2.0 mmol, 2.5 mmol, and 4.0 mmol, the breakpoint of the lactate-intensity curve, 1 mmol above rest, and 1 mmol above exercise baseline. A one factor repeated measures ANOVA model was used to calculate intraclass reliability coefficients across the 3 testing sessions. Confidence intervals (95%) were calculated around the point estimates of reliability for each LT criterion. Intraclass correlation coefficients ranged from 0.98 to 0.99 LT(VEL) (SEM 0.06 to 0.14 km x hr(-1)), from 0.91 to 0.96 for LT(VO2) (SEM 0.34 to 0.72 ml x kg(-1) x min(-1)), and from 0.75 to 0.96 for LTHR (SEM 0.7 to 1.9 beats x min(-1)). These results support the reliability of LT(VEL), LT(VO2), and LT(HR) measurement.
Tracking Movements and Attention of Crowds in Real Time Analysing Social Streams The case of the Open Ceremony of London 2012

To manage a big event require tracking in real time the movement of crowds. Solution based on mobile network data analysis are effective, but expensive. Obtaining comparable results by analysing public social stream has a clear commercial potential, especially considering that, being able to access also the content of a micro-post, the analysis can also track the attention of crowds.
Low-current probabilistic writes for power-efficient STT-RAM caches

MRAM has emerged as one of the most attractive non-volatile solutions due to fast read access, low leakage power, high bit density, and long endurance. However, the high power consumption of write operations remains a barrier to the commercial adoption of MRAM technology. This paper addresses this problem by introducing low-current probabilistic writes (LCPW), a technique that reduces write access energy by lowering the amplitude of the write current pulse. Although low current pulses no longer guarantee successful bit write operations, we propose and evaluate a simple technique to ensure correctness and achieve significant power reduction over a typical MRAM implementation.
When FPGAs are better at floating-point than microprocessors

It has been shown that FPGAs could outperform high-end microprocessors on floating-point computations thanks to massive parallelism. However, most previous studies re-implement in the FPGA the operators present in a processor. This conservative approach is relatively straightforward, but it doesn't exploit the greater flexibility of the FPGA. We survey the many ways in which the FPGA implementation of a given floating-point computation can be not only faster, but also more accurate than its microprocessor counterpart. Techniques studied here include custom precision, mixing and matching fixed- and floating-point, specific accumulator design, dedicated architectures for coarser operators implemented as software in processors (such as elementary functions or Euclidean norms), operator specialization such as constant multiplication, and others. The FloPoCo project (http://www.ens-lyon.fr/LIP/Arenaire/Ware/FloPoCo/) aims at providing such non-standard operators. As a conclusion, current FPGA fabrics could be enhanced to improve floating-point performance. However, these enhancements should not take the form of hard FPU blocks as others have suggested. Instead, what is needed is smaller building blocks more generally useful to the implementation of floating-point operators, such as cascadable barrel shifters and leading zero counters
Back Propagation Neural Network based Gait Recognition

We describe a new method for recognizing humans by their gait using back propagation neural network(BPNN), BPNN algorithm is used to recognize humans by their gait patterns. Automatic gait recognition using Fourier descriptors and independent component analysis (ICA) for the purpose of human identification at a distance. Firstly, a simple background generation algorithm is introduced to subtract the moving figures accurately and to obtain binary human silhouettes. Secondly, these silhouettes are described with Fourier descriptors and converted into associated onedimension signals. Then ICA is applied to get the independent components of the signals. For reducing the computational cost, a fast and robust fixed-point algorithm for calculating ICs is adopted and a criterion how to select ICs is put forward. Lastly, the nearest neighbour (NN), support vector machine (SVM) and back propagation neural network (BPNN) classifiers are chosen for recognition and this method is tested on the small UMD gait database and the NLPR gait database. Gait recognition aims essentially to address this problem by identifying people based on the way they walk [1]. Gait recognition has 3 steps. The first step is pre-processing, the second step is feature extraction and the third one is classification. This paper focuses on the classification step that is essential to increase the CCR (Correct Classification Rate). Multilayer Perceptron (MLP) is used in this work. In this paper we apply MLP NN for 11 views in our database and compare the CCR values for these views. In experiments, higher gait recognition performances have been achieved.
NetGraph SystemSearching through the Prague Dependency Treebank

The goal of one of the projects being solved at our Center is to build a corpus of Czech with a rich annotation scheme–the Prague Dependency Treebank. Text files containing these data in the form of labeled trees are being created automatically with manual corrections. With the increasing amount of annotated material searching a corpus becomes a complex task. The present paper describes the software system that was developed to contribute to the solution of this problem. Some requirements were established during the analysis of the design: the software has to be able to work in the Internet environment, to display tree structures in a graphical form, and the client part has to be hardware independent.
Specific Inhibition of the Redox Activity of Ape1/Ref-1 by E3330 Blocks Tnf-Α-Induced Activation of Il-8 Production in Liver Cancer Cell Lines

APE1/Ref-1 is a main regulator of cellular response to oxidative stress via DNA-repair function and co-activating activity on the NF-κB transcription factor. APE1 is central in controlling the oxidative stress-based inflammatory processes through modulation of cytokines expression and its overexpression is responsible for the onset of chemoresistance in different tumors including hepatic cancer. We examined the functional role of APE1 overexpression during hepatic cell damage related to fatty acid accumulation and the role of the redox function of APE1 in the inflammatory process. HepG2 cells were stably transfected with functional and non-functional APE1 encoding plasmids and the protective effect of APE1 overexpression toward genotoxic compounds or FAs accumulation, was tested. JHH6 cells were stimulated with TNF-α in the presence or absence of E3330, an APE1 redox inhibitor. IL-8 promoter activity was assessed by a luciferase reporter assay, gene expression by Real-Time PCR and cytokines (IL-6, IL-8, IL-12) levels measured by ELISA. APE1 over-expression did not prevent cytotoxicity induced by lipid accumulation. E3330 treatment prevented the functional activation of NF-κB via the alteration of APE1 subcellular trafficking and reduced IL-6 and IL-8 expression induced by TNF-α and FAs accumulation through blockage of the redox-mediated activation of NF-κB. APE1 overexpression observed in hepatic cancer cells may reflect an adaptive response to cell damage and may be responsible for further cell resistance to chemotherapy and for the onset of inflammatory response. The efficacy of the inhibition of APE1 redox activity in blocking TNF-α and FAs induced inflammatory response opens new perspectives for treatment of inflammatory-based liver diseases.
Global minimum-jerk trajectory planning of robot manipulators

A new approach based on interval analysis is developed to find the global minimum-jerk (MJ) trajectory of a robot manipulator within a joint space scheme using cubic splines. MJ trajectories are desirable for their similarity to human joint movements and for their amenability to path tracking and to limit robot vibrations. This makes them attractive choices for robotic applications, in spite of the fact that the manipulator dynamics are not taken into account. Cubic splines are used in a framework that assures overall continuity of velocities and accelerations in the robot movement. The resulting MJ trajectory planning is shown to be a global constrained minimax optimization problem. This is solved by a newly devised algorithm based on interval analysis and proof of convergence with certainty to an arbitrarily good global solution is provided. The proposed planning method is applied to an example regarding a six-joint manipulator and comparisons with an alternative MJ planner are exposed.
Draft Genome Sequence of Toluene-Resistant Staphylococcus epidermidis SNUT

ABSTRACT Here, we report draft sequence of the Gram-positive toluene-resistant bacterium Staphylococcus epidermidis SNUT. The draft genome sequence is 2,511,658 bases, with 2,346 protein-coding genes, 57 tRNA-coding genes, and 8 rRNA genes.
Detection and treatment of mental health issues by pediatric PCPs in New York State: an evaluation of Project TEACH.

OBJECTIVE The authors evaluated Project TEACH (PT), a statewide training and consultation program for pediatric primary care providers (PCPs) on identification and treatment of mental health conditions. METHODS An intervention group of 176 PCPs who volunteered for PT training was compared with a stratified random sample of 200 PCPs who did not receive PT training. Data on prescription practices, diagnoses, and follow-up care were from New York State Medicaid files (2009-2013) for youths seen by the trained (N=21,784) and untrained (N=46,607) PCPs. RESULTS The percentage of children prescribed psychotropic medication increased after PT training (9% to 12%, p<.001), a larger increase than in the untrained group (4% to 5%, p<.001) (comparison, p<.001). Fewer differences were noted in diagnoses and in medication use and follow-up care among children with depression. CONCLUSIONS This intervention may have an impact on providers' behaviors, but further research is needed to clarify its effectiveness.
Building Dynamic Computing Infrastructures over Distributed Clouds

The emergence of cloud computing infrastructures brings new ways to build and manage computing systems, with the flexibility offered by virtualization technologies. In this context, this PhD thesis focuses on two principal objectives. First, leveraging virtualization and cloud computing infrastructures to build distributed large scale computing platforms from multiple cloud providers, allowing to run software requiring large amounts of computation power. Second, developing mechanisms to make these infrastructures more dynamic. These mechanisms, providing inter-cloud live migration, offer new ways to exploit the inherent dynamic nature of distributed clouds.
A history-based approach for adaptive robot behavior in dynamic environments

The behavior-based approach has proven to be useful in making mobile agents work in dynamic and complex situations. Since the behaviors are responsible for managing the interactions between the agent and its environment, observing their use can be exploited to model these interactions. In our approach, the agent is initially given a set of behaviors to choose from, and the algorithm adapts the selection of behaviors according to the history of behavior use, represented in a tree structure. The approach is validated using a vision-and sonar-based Pioneer I robot in non-stationary conditions, in the context of a multi-robot foraging task. Results show the eeectiveness of the approach in taking advantage of any regularities experienced in the world, leading to fast and adaptable specialization for the learning agent. 1 Introduction Various kinds of autonomous agents, especially in mobile robotics, have been designed using the behavior-based paradigm (Brooks 1986). This approach has been praised for its robustness and simplicity of construction. In a typical behavior-based system, the constituent behaviors are designed parsimoniously, executed in parallel, and prioritized using some xed or exible arbitration mechanism (Matari c 1997a). A xed and parsimonious behavior set, however, does not allow an agent to easily adapt to changes in the environment, thus resulting in diminished exibility (Maes 1989). The ability to adapt to changing dynamics, however, is especially important for agents operating in unpredictable and non-stationary environments. One possible improvement would be to dynamically select behaviors by introducing a cognitive component capable of modeling the environment (Michaud, Lachiver & Le Dinh 1996). When behavior selection is changed according to external and internal states, knowing when to use a behavior becomes as important as the behavior itself.
VLIW across multiple superscalar processors on a single chip

Advances in IC technology increase the integration density for higher clock rates and provide more opportunities for microprocessor design. The authors propose a new paradigm to exploit instruction-level parallelism (ILP) across multiple superscalar processors on a single chip by taking advantages of both VLIW-style static scheduling techniques and dynamic scheduling of superscalar architecture. In the proposed paradigm, ILP is exploited by a compiler from a sequential program and this VLIW-like-parallelized code is further parallelized by 2-way superscalar engines at run-time. Superscalar processors are connected by an aggregate function network, which can enforce the necessary static timing constraints and provide appropriate inter-processor data communication mechanisms that are needed for ILP. The aggregate function operations are statically scheduled and implement not only fine-grain communication and control, but also simple global computations resembling systolic array operations within the network.
NFV virtualisation of the home environment

NFV Technology facilitates implementation of network functions as SW packages, called Virtual Network Functions (VNF) running over common IT platforms and simple network switches. NFV could be used to virtualize dispersed functions and devices currently deployed as CPEs in the customer home. This new architecture has a major impact on public and home networks. Not only are HW components virtualised, but their location and operational responsibility is shifted to the operator scope. Various security and implementation issues are identified as a result of Home Virtualisation and discussed in this paper.
The ANGELINA Videogame Design System—Part II

Procedural content generation is generally viewed as a means to an end—a tool employed by designers to overcome technical problems or achieve a particular design goal. When we move from generating single parts of games to automating the entirety of their design, however, we find ourselves facing a far wider and more interesting set of problems than mere generation. When the designer of a game is a piece of software, we face questions about what it means to be a designer, about computational creativity, and about how to assess the growth of these automated game designers and the value of their output. Answering these questions can lead to new ideas in how to generate content procedurally, and produce systems that can further the cutting edge of game design. This paper describes work done to take an automated game designer and advance it towards being a member of a creative community. We outline extensions made to the system to give it more autonomy and creative independence, in order to strengthen claims that the software is acting creatively. We describe and reflect upon the software’s participation in the games community, including entering two game development contests, and show the opportunities and difficulties of such engagement. We consider methods for evaluating automated game designers as creative entities, and underline the need for automated game design to be a major frontier in future games research.
Leader-following consensus for single-integrator multi-agent systems with multiplicative noises in directed topologies

This paper proposes a leader-following consensus control for continuous-time single-integrator multi-agent systems with multiplicative measurement noises under directed fixed and switching topologies. The consensus controller is developed by combining the graph theory and stochastic tools. The control input for each agent relies on its own state and its neighbours’ states corrupted by noises, the noises are considered proportional to the relative distance between agents, both of the noisy case and the noise-free case are studied, and conditions to achieve mean square convergence under noisy measurement and asymptotic convergence in absence of noises are derived. Finally, in order to prove the validity of the consensus control, some simulations were carried out.
THE NUTRITIONAL REQUIREMENTS OF ACETOBACTER MELANOGENUM AND RELATED SPECIES

During the course of some physiological studies with Acetobacter melanogenum it became necessary to investigate the nutritional requirements of several isolates in considerable detail. Grey and Tatum (1944) already had described a minimal medium for growth of one isolate of this species. However, since only one isolate was studied and the nutritional observations were made more or less incidental to the main investigation of the effect of X-rays on this species, it was thought desirable to confirm and, if possible, to expand their observations. The discrepancies in our knowledge of physiology and nutrition as related to taxonomy and nomenclature are particularly evident among the group of acetic acid bacteria which oxidize ethanol only to the stage of acetic acid and are popularly known as "underoxidizers". Therefore, a culture of A. oxydans was used as a second representative of this group to be compared with the cultures of A. melanogenum in order to determine whether the nutritional requirements differed significantly from those of A. suboxydans. The nutritional requirements of this latter species, a well known member of the group causing partial oxidation of ethanol, have been investigated in detail (see Lampen, Underkofler, and Peterson, 1942; Landy and Dicken, 1942; Underkofler, Bantz, and Peterson, 1943; Landy and Streightoff, 1943; Sarett and Cheldelin, 1945; Cheldelin and Bennett, 1945; and Stokes and Lsen, 1945). The nutritional requirements of A. melanogenum and A. oxydans also were compared with those of a representative culture of A. rancens, one of the species capable of causing complete oxidation ("overoxidation") of ethanol (8ee Visser't Hooft, 1925; Vaughn, 1942). It was
On Proper Unit Selection in Active Learning: Co-Selection Effects for Named Entity Recognition

Active learning is an effective method for creating training sets cheaply, but it is a biased sampling process and fails to explore large regions of the instance space in many applications. This can result in a missed cluster effect, which signficantly lowers recall and slows down learning for infrequent classes. We show that missed clusters can be avoided in sequence classification tasks by using sentences as natural multi-instance units for labeling. Co-selection of other tokens within sentences provides an implicit exploratory component since we found for the task of named entity recognition on two corpora that entity classes co-occur with sufficient frequency within sentences.
Spaceborne Spotlight SAR Interferometry With TerraSAR-X

Recently, synthetic aperture radar (SAR) data with 1-m resolution acquired by satellites in spotlight mode became available to the public. In this paper, we elucidate the differences between interferometric processing of strip map and of spotlight SAR data, and we outline adequate algorithms for key processing steps such as azimuth Doppler filtering. We further present first TerraSAR-X spotlight interferograms, together with an evaluation of the paraeters that are critical for interferometry. Our results indicate a very good geometric accuracy, stability, and phase fidelity of the TerraSAR-X sensor and its products. From the interferograms, we are able to determine the heights of larger buildings and millimeter-scale structural deformation in several examples. The high detail level of imaged buildings and the good temporal phase coherence of urban areas in X-band make spotlight interferometry an exciting processing technique that enables new applications such as surveying individual buildings.
Patterns of expression for the mRNA corresponding to the four isoforms of phospholipase Cβ in mouse brain

Ligand binding to neurotransmitter and hormone receptors which couple to the Gq subclass of GTP‐binding protein leads to the activation of phospholipase Cβ (PLCβ) which hydrolyses phosphatidyl‐inositol 4,5‐bisphosphate, yielding a pair of second messengers, diacylglycerol and inositol 1,4,5‐trisphosphate (IP3). The expression of PLCβ1–4 mRNAs was comparatively examined by in situ hybridization in the mouse brain. In adults, PLCβ1 mRNA was expressed predominantly in the telencephalon, including the cerebral cortex, hippocampus, amygdala, lateral septum and olfactory bulb, with little expression in most thalamic nuclei. PLCβ2 mRNA was distributed in the white matter, suggesting its expression in non‐neuronal cells, most likely oligodendrocytes. PLCβ3 mRNA was specifically expressed in cerebellar Purkinje cells. The highest levels of PLCβ4 mRNA were detected in Purkinje cells. High levels of PLCβ4 mRNA were also found in the thalamus and medial septum, whereas weak signals were detected in most telencephalic regions, thus showing an expression pattern almost reciprocal to that of PLCβ1 mRNA. During development, such characteristic regional expression of PLCβ1 and PLCβ4 were observed starting in late foetal stages, while specific expression of PLCβ2 and PLCβ3 appeared in early postnatal stages. We conclude that despite the existence of four PLCβ isoforms, only one or two of them is expressed in individual neurons and glial cells. The distinct expression of PLCβs provides a molecular basis for analysing the nature of the specific signal transduction pathway leading to the production of diacylglycerol and IP3 in distinct cell types and in different regions of the brain.
Information flow inference for ML

This paper presents a type-based information flow analysis for a call-by-value λ-calculus equipped with references, exceptions and let-polymorphism, which we refer to as ML. The type system is constraint-based and has decidable type inference. Its noninterference proof is reasonably light-weight, thanks to the use of a number of orthogonal techniques. First, a syntactic segregation between values and expressions allows a lighter formulation of the type system. Second, noninterference is reduced to subject reduction for a nonstandard language extension. Lastly, a semi-syntactic approach to type soundness allows dealing with constraint-based polymorphism separately.