Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic Generation of Multicore Chemical Kernels

Abstract-This work presents the Kinetics Preprocessor: Accelerated (KPPA), a general analysis and code generation tool that achieves significantly reduced time-to-solution for chemical kinetics kernels on three multicore platforms: NVIDIA GPUs using CUDA, the Cell Broadband Engine, and Intel Quad-Core Xeon CPUs. A comparative performance analysis of chemical kernels from WRFChem and the Community Multiscale Air Quality Model (CMAQ) is presented for each platform in double and single precision on coarse and fine grids. We introduce the multicore architecture parameterization that KPPA uses to generate a chemical kernel for these platforms and describe a code generation system that produces highly tuned platform-specific code. Compared to state-of-the-art serial implementations, speedups exceeding 25x are regularly observed, with a maximum observed speedup of 41.1x in single precision.
A Space Vector PWM Scheme for Multifrequency Output Voltage Generation With Multiphase Voltage-Source Inverters

Multiphase variable-speed drives, supplied from two-level voltage-source inverters (VSIs), are nowadays considered for various industrial applications. Depending on the drive structure and/or the motor design, the VSI is required to generate either sinusoidal voltages or voltages that contain a certain number of sinusoidal components (ldquomultifrequency output voltagesrdquo). The existing space vector pulsewidth-modulation (SVPWM) schemes are based on selection of (n-1) active space vectors (for odd phase numbers) within a switching period and they yield either sinusoidal voltage or sinusoidal fundamental voltage in combination with a limited amount of other harmonic terms. This paper develops a SVPWM scheme, which enables multifrequency output voltage generation with arbitrary values of various sinusoidal components in the output voltage. The method is based on initial selection of (n-1)2/2 active space vectors within a switching period, instead of the common (n-1) active vectors. By properly arranging the sequence of the vector application, it is possible to provide an automatic postreduction of the number of applied active vectors to (n-1), thus maintaining the same switching frequency as with the existing schemes while simultaneously avoiding the limiting on the generated sinusoidal output voltage components. Theoretical considerations are detailed using a five-phase VSI. The experimental verification is provided using a five-phase two-motor series-connected induction motor drive, supplied from a custom-designed five-phase DSP-controlled VSI.
SCREENING AND IDENTIFICATION CAGE, RAPS4, RAPS4-QF and AUDIT Screening Tests for Men and Women Admitted for Acute Alcohol Intoxication to an Emergency Department: Are Standard Thresholds Appropriate?

Aims: A number of screening instruments are routinely used in Emergency Department (ED) situations to identify alcohol-use disorders (AUD). We wished to study the psychometric features, particularly concerning optimal thresholds scores (TSs), of four assessment scales frequently used to screen for abuse and/or dependence, the cut-down annoyed guilty eye-opener (CAGE), Rapid Alcohol Problem Screen 4 (RAPS4), RAPS4-quantity-frequency and AUD Identification Test (AUDIT) questionnaires, par- ticularly in the sub-group of people admitted for acute alcohol intoxication (AAI). Methods: All included patients (AAI admitted to ED (blood alcohol level ≥0.8 g/l)) were assessed by the four scales, and with a gold standard (alcohol dependenceUabuse section of the Mini International Neuropsychiatric Interview), to determine AUD status. To investigate the TSs of the scales, we used Youden's index, efficiency, receiver operating characteristic (ROC) curve techniques and quality ROC curve technique for optimized TS (indices of quality). Results: A total of 164 persons (122 males, 42 females) were included in the study. Nineteen (11.60%) were identified as alcohol abusers alone and 128 (78.1%) as alcohol dependents (DSM-IV). Results suggest a statistically significant dif- ference between men and women (P < 0.05) in performance of the screening tests RAPS4 (≥1) and CAGE (≥2) for detecting abuse. Also, in this population, we show an increase in TSs of RAPS4 (≥2) and CAGE (≥3) for detecting dependence compared with those typically accepted in non-intoxicated individuals. The AUDIT test demonstrates good performance for detecting alcohol abuse and/ or alcohol-dependent patients (≥7 for women and ≥12 for men) and for distinguishing alcohol dependence (≥11 for women and ≥14 for men) from other conditions. Conclusion: Our study underscores for the first time the need to adapt, taking into account gender, the thresholds of tests typically used for detection of abuse and dependence in this population.
Efficient Cluster-Based Tracking Mechanisms for Camera-Based Wireless Sensor Networks

This paper proposes mechanisms to efficiently address critical tasks in the operation of cluster-based target tracking, namely: (1) measurement integration, (2) inclusion/exclusion in the cluster, and (3) cluster head rotation. They all employ distributed probabilistic tools designed to take into account wireless camera networks (WCNs) capabilities and constraints. They use efficient and distribution-friendly representations and metrics in which each node contributes to the computation in each mechanism without requiring any prior knowledge of the rest of the nodes. These mechanisms are integrated in two different distributed schemes so that they can be implemented in constant time regardless of the cluster size. Their experimental validation showed that the proposed mechanisms and schemes significantly reduce energy consumption (>55 percent) and computational burden with respect to existing methods.
Hand posture recognition using K-NN and Support Vector Machine classifiers evaluated on our proposed HandReader dataset

In this paper, we propose a real-time vision-based hand posture recognition approach, based on appearance-based features of the hand poses. Our approach has three main steps: Preprocessing, Feature Extraction and Posture Recognition. Additionally, a new hand posture dataset called HandReader is created and introduced. HandReader is a dataset of 500 images of 10 different hand postures which are 10 non-motion-based American Sign Language alphabets with dark backgrounds. The dataset is gathered by capturing images of 50 male and female individuals performing these 10 hand postures in front of a common camera. 20% of the HandReader images are used for the training purpose and the remaining 80% are used to test the proposed methodology. All the images are normalized after applying the preprocessing step. The normalized images are then converted to feature vectors in the Feature Extraction step. In order to train the system, k-NN classifier and SVM classifiers with linear and RBF kernel have been employed and results were compared. These approaches were used to classify hand posture images into 10 different posture classes. The SVM classifier with linear kernel performed better with the highest true detection rate (96%) among other proposed techniques.
Genome-scale models of bacterial metabolism: reconstruction and applications

Genome-scale metabolic models bridge the gap between genome-derived biochemical information and metabolic phenotypes in a principled manner, providing a solid interpretative framework for experimental data related to metabolic states, and enabling simple in silico experiments with whole-cell metabolism. Models have been reconstructed for almost 20 bacterial species, so far mainly through expert curation efforts integrating information from the literature with genome annotation. A wide variety of computational methods exploiting metabolic models have been developed and applied to bacteria, yielding valuable insights into bacterial metabolism and evolution, and providing a sound basis for computer-assisted design in metabolic engineering. Recent advances in computational systems biology and high-throughput experimental technologies pave the way for the systematic reconstruction of metabolic models from genomes of new species, and a corresponding expansion of the scope of their applications. In this review, we provide an introduction to the key ideas of metabolic modeling, survey the methods, and resources that enable model reconstruction and refinement, and chart applications to the investigation of global properties of metabolic systems, the interpretation of experimental results, and the re-engineering of their biochemical capabilities.
Bifurcations in turbulent rotating Rayleigh-Bénard convection: A finite-size effect

In turbulent rotating Rayleigh-Bénard convection Ekman vortices extract hot or cold fluid from thermal boundary layers near the bottom or top plate and enhance the Nusselt number. It is known from experiments and direct numerical simulation on cylindrical samples with aspect ratio Γ ≡ D/L (D is the diameter and L the height) that the enhancement occurs only above a bifurcation point at a critical inverse Rossby number 1/Roc, with 1/Roc ∞ 1/Γ. We present a Ginzburg-Landau like model that explains the existence of a bifurcation at finite 1/Roc as a finite-size effect. The model yields the proportionality between 1/Roc and 1/Γ and is consistent with several other measured or computed system properties. Here it is used to estimate the suppression of the heat-transport enhancement by the sidewall.
Spectroscopic evaluations of optical cooling effect in LiNbO3:Yb3+ crystal

Based on the results obtained from detailed investigations of absorption and luminescence spectra of the LiNbO3:Yb3+crystal the availability of this material for solid-state optical refrigerators is evaluated. Anti-Stokes luminescence registered for this crystal in the wavelength region near the 980 nm under the optical excitation at the 1064 nm allows estimation of main characteristics of the laser cooling effect. Conditions for increasing the efficiency of laser cooling effect in the material under study are discussed. The new approach to measure temperature changes of ferroelectric samples under an optical irradiation is proposed.
The geometry of right angled Artin subgroups of mapping class groups

We describe sufficient conditions which guarantee that a finite set of mapping classes generate a right-angled Artin group quasi-isometrically embedded in the mapping class group. Moreover, under these conditions, the orbit map to Teichmuller space is a quasi-isometric embedding for both of the standard metrics. As a consequence, we produce infinitely many genus h surfaces (for any h at least 2) in the moduli space of genus g surfaces (for any g at least 3) for which the universal covers are quasi-isometrically embedded in the Teichmuller space.
Fuzzy based sliding mode control for vector controlled induction motor

A vector controlled induction motor drive with fuzzy based sliding mode controller (SMC) is presented in this paper for improving the dynamic performance of the drive. The fuzzy based SMC employed for speed control compensates for the chattering effect otherwise present with SMC. MATLAB simulation of the scheme for a 5HP, 460 V (50Hz) induction motor is presented to analyse the performance of fuzzy based SMC.
High-Fidelity Per-Flow Delay Measurements With Reference Latency Interpolation

New applications such as soft real-time data center applications, algorithmic trading, and high-performance computing require extremely low latency (in microseconds) from networks. Network operators today lack sufficient fine-grain measurement tools to detect, localize, and repair delay spikes that cause application service level agreement (SLA) violations. A recently proposed solution called LDA provides a scalable way to obtain latency, but only provides aggregate measurements. However, debugging application-specific problems requires per-flow measurements since different flows may exhibit significantly different characteristics even when they are traversing the same link. To enable fine-grained per-flow measurements in routers, we propose a new scalable architecture called reference latency interpolation (RLI) that is based on our observation that packets potentially belonging to different flows that are closely spaced to each other exhibit similar delay properties. In our evaluation using simulations over real traces, we show that while having small overhead, RLI achieves a median relative error of 12% and one to two orders of magnitude higher accuracy than previous per-flow measurement solutions. We also observe RLI achieves as high accuracy as LDA in aggregate latency estimation, and RLI outperforms LDA in standard deviation estimation.
How Reliably Does a Neuron in the Visual Motion Pathway of fhe Fly Encode Behaviourally Relevant Information?

How reliably neurons convey information depends on the extent to which their activity is affected by stochastic processes which are omnipresent in the nervous system. The functional consequences of neuronal noise can only be assessed if the latter is related to the response components that are induced in a normal behavioural situation. In the present study the reliability of neural coding was investigated for an identified neuron in the pathway processing visual motion information of the fly (Lucilia cuprina). The stimuli used to investigate the neuronal performance were not exclusively defined by the experimenter. Instead, they were generated by the fly itself, i.e. by its own actions and reactions in a behavioural closed‐loop experiment, and subsequently replayed to the animal while the activity of an identified motion‐sensitive neuron was recorded. Although the time course of the neuronal responses is time‐locked to the stimulus, individual response traces differ slightly from each other due to stochastic fluctuations in the timing and number of action potentials. Individual responses thus consist of a stimulus‐induced and a stochastic response component. The stimulus‐induced response component can be recovered most reliably from noisy neuronal signals if these are smoothed by intermediate‐sized time windows (40–100 ms). At this time scale the best compromise is achieved between smoothing out the noise and maintaining the temporal resolution of the stimulus‐induced response component. Consequently, in the visual motion pathway of the fly, behaviourally relevant motion stimuli can be resolved best at a time scale where the timing of individual spikes does not matter.
An Integrated System for Precise Genome Modification in Escherichia coli

We describe an optimized system for the easy, effective, and precise modification of the Escherichia coli genome. Genome changes are introduced first through the integration of a 1.3 kbp Landing Pad consisting of a gene conferring resistance to tetracycline (tetA) or the ability to metabolize the sugar galactose (galK). The Landing Pad is then excised as a result of double-strand breaks by the homing endonuclease I-SceI, and replaced with DNA fragments bearing the desired change via λ-Red mediated homologous recombination. Repair of the double strand breaks and counterselection against the Landing Pad (using NiCl2 for tetA or 2-deoxy-galactose for galK) allows the isolation of modified bacteria without the use of additional antibiotic selection. We demonstrate the power of this method to make a variety of genome modifications: the exact integration, without any extraneous sequence, of the lac operon (~6.5 kbp) to any desired location in the genome and without the integration of antibiotic markers; the scarless deletion of ribosomal rrn operons (~6 kbp) through either intrachromosomal or oligonucleotide recombination; and the in situ fusion of native genes to fluorescent reporter genes without additional perturbation.
Teleoperation of AZIMUT-3, an omnidirectional non-holonomic platform with steerable wheels

AZIMUT-3 is an omnidirectional non-holonomic (or pseudo-omnidirectional [1]) robotic platform intended for safe human-robot interaction. In its wheeled configuration, shown in Fig. 1, AZIMUT-3 uses eight actuators for locomotion: four for propulsion and four for steering the wheels, which can rotate 180 degrees around their steering axis. Propulsion is done using standard DC brushless motors (Bayside K064050-3Y) with optical encoders (US Digital E4-300-157-HUB, 0.3 deg of resolution), capable of reaching 1.47 m/s. The platform uses steerable wheels motorized using differential elastic actuators (DEA) [2], [3], which provide compliance, safety and torque control capabilities. AZIMUT-3's hardware architecture consists of distributed modules for sensing and low-level control, communicating with each other through a 1 Mbps CAN bus. A Mini-ITX computer equipped with a 2.0 GHz Core 2 duo processor running Linux with real-time patches (RT-PREEMPT) is used on-board for high-level control modules. Nickel-metal hydride batteries provide power to the platform for up to 3 hours of autonomy. A passive vertical suspension mechanism (Rosta springs) is used to connect the wheels to AZIMUT-3's chassis, allowing them to keep contact with the ground on uneven surfaces. The platform has a 34 kg payload capacity and weights 35 kg.
Characterizing Discriminative Patterns

Discriminative patterns are association patterns that occur with disproportionate frequency in some classes versus others, and have been studied under names such as emerging patterns and contrast sets. Such patterns have demonstrated considerable value for classification and subgroup discovery, but a detailed understanding of the types of interactions among items in a discriminative pattern is lacking. To address this issue, we propose to categorize discriminative patterns according to four types of item interaction: (i) driver-passenger, (ii) coherent, (iii) independent additive and (iv) synergistic beyond independent additive. Either of the last three is of practical importance, with the latter two representing a gain in the discriminative power of a pattern over its subsets. Synergistic patterns are most restrictive, but perhaps the most interesting since they capture a cooperative effect. For domains such as genetic research, differentiating among these types of patterns is critical since each yields very different biological interpretations. For general domains, the characterization provides a novel view of the nature of the discriminative patterns in a dataset, which yields insights beyond those provided by current approaches that focus mostly on pattern-based classification and subgroup discovery. This paper presents a comprehensive discussion that defines these four pattern types and investigates their properties and their relationship to one another. In addition, these ideas are explored for a variety of datasets (ten UCI datasets, one gene expression dataset and two genetic-variation datasets). The results demonstrate the existence, characteristics and statistical significance of the different types of patterns. They also illustrate how pattern characterization can provide novel insights into discriminative pattern mining and the discriminative structure of different datasets.
An interaction approach to enhance situational awareness and the production of anticipatory actions in emergency operation centers

Recent findings from fieldwork conducted at emergency operation centers (EOC) suggest that currently deployed emergency management information systems (EMIS) are not supporting properly the anticipation of individual actions in cooperative work. We present these findings in this paper and introduce joint action theory as an interaction approach to design technologies that explicitly provide for this kind of support. Our main arguments are: (1) contemporary EMIS are affecting negatively cooperative work at EOCs due to their lack of support for the anticipation of individual actions; (2) Available theory that emphasizes the role of anticipation on cooperative work is not impacting on the design of EMIS due to misalignments between the theory and contemporary situations; (3) Joint action theory provides an alternative framework to correct these misalignments; and (4) Joint action theory provides designers of EMIS with guides for an interaction design that supports anticipatory actions in EOCs.
Mesenchymal stem cells can survive on the extracellular matrix-derived decellularized bovine articular cartilage scaffold

Objective (s): The scarcity of articular cartilage defect to repair due to absence of blood vessels and tissue engineering is one of the promising approaches for cartilage regeneration. The objective of this study was to prepare an extracellular matrix derived decellularized bovine articular cartilage scaffold and investigate its interactions with seeded rat bone marrow mesenchymal stem cells (BM-MSCs). Materials and Methods: Bovine articular cartilage that was cut into pieces with 2 mm thickness, were decellularized by combination of physical and chemical methods including snap freeze-thaw and treatment with sodium dodecyl sulfate (SDS). The scaffolds were then seeded with 1, 1’-dioctadecyl-3, 3, 3’, 3’-tetramethylindocarbocyanine perchlorate (DiI) labeled BM-MSCs and cultured for up to two weeks. Results: Histological studies of decellularized bovine articular cartilage showed that using 5 cycles of snap freeze-thaw in liquid nitrogen and treatment with 2.5% SDS for 4 hr led to the best decellularization, while preserving the articular cartilage structure. Adherence and penetration of seeded BM-MSCs on to the scaffold were displayed by histological and florescence examinations and also confirmed by electron microscopy. Conclusion: ECM-derived decellularized articular cartilage scaffold provides a suitable environment to support adhesion and maintenance of cultured BM-MSCs and could be applied to investigate cellular behaviors in this system and may also be useful for studies of cartilage tissue engineering.
Evidence that viral RNAs have evolved for efficient, two-stage packaging

Genome packaging is an essential step in virus replication and a potential drug target. Single-stranded RNA viruses have been thought to encapsidate their genomes by gradual co-assembly with capsid subunits. In contrast, using a single molecule fluorescence assay to monitor RNA conformation and virus assembly in real time, with two viruses from differing structural families, we have discovered that packaging is a two-stage process. Initially, the genomic RNAs undergo rapid and dramatic (approximately 20–30%) collapse of their solution conformations upon addition of cognate coat proteins. The collapse occurs with a substoichiometric ratio of coat protein subunits and is followed by a gradual increase in particle size, consistent with the recruitment of additional subunits to complete a growing capsid. Equivalently sized nonviral RNAs, including high copy potential in vivo competitor mRNAs, do not collapse. They do support particle assembly, however, but yield many aberrant structures in contrast to viral RNAs that make only capsids of the correct size. The collapse is specific to viral RNA fragments, implying that it depends on a series of specific RNA–protein interactions. For bacteriophage MS2, we have shown that collapse is driven by subsequent protein–protein interactions, consistent with the RNA–protein contacts occurring in defined spatial locations. Conformational collapse appears to be a distinct feature of viral RNA that has evolved to facilitate assembly. Aspects of this process mimic those seen in ribosome assembly.
Unified Approach to the Detection and Classification of Speckle Texture in Diagnostic Ultrasound

Second order statistics have been derived for the speckle in diagnostic ultrasound that arises from diffuse (incoherent) scattering in the presence of distributed and organized specular (coherent) scattering. They serve as the basis for a three-dimensional feature space in which tissue textures can be classified. The covariance matrix of the measurements in this space is a generalization of the speckle spot number or sampling concept that arises in the study of signal or lesion detectability.