Miracle-dz/UniFAR-FTUs huggingface dataset:
Streamline Predicates

Predicates are functions that return Boolean values. They are an essential tool in computer science. A close look at flow feature definitions reveals that they can be seen as point predicates that tell if a specific feature exists at a certain point. Besides the information about features, scientists and engineers like to know the overall behavior of all streamlines in the flow, typically in the connection with the important features in their application domain. We call this a structure definition for the flow. A successful example for a structure definition is flow topology. In this paper, we present streamline predicates as functions that tell the user about the connection between streamlines and features selected by the user. This means answers to questions like: Which streamlines flow through a given vortex, separation bubble, or shock wave? It can be shown that streamline predicates may refine flow topology so that it also reveals questions about vortices in 3D
Engineered antifouling microtopographies – correlating wettability with cell attachment

Abstract Bioadhesion and surface wettability are influenced by microscale topography. In the present study, engineered pillars, ridges and biomimetic topography inspired by the skin of fast moving sharks (Sharklet AF™) were replicated in polydimethylsiloxane elastomer. Sessile drop contact angle changes on the surfaces correlated well (R2 = 0.89) with Wenzel and Cassie and Baxter's relationships for wettability. Two separate biological responses, i.e. settlement of Ulva linza zoospores and alignment of porcine cardiovascular endothelial cells, were inversely proportional to the width (between 5 and 20 μm) of the engineered channels. Zoospore settlement was reduced by ∼85% on the finer (ca 2 μm) and more complex Sharklet AF™ topographies. The response of both cell types suggests their responses are governed by the same underlying thermodynamic principles as wettability.
Anti-α-glucose-based glycan IgM antibodies predict relapse activity in multiple sclerosis after the first neurological event

Background There is no specific serum-based biomarker for the diagnosis or prognosis of relapsing-remitting multiple sclerosis (RRMS). Objective We investigated whether levels of IgM antibodies to Glc(α1,4)Glc(α) (GAGA4) or to a panel of four glucose-based glycans could differentiate MS from other neurological diseases (OND) or predict risk of early relapse following first presentation (FP) of RRMS. Methods Retrospective analysis of 440 sera samples of three cohorts: A) FP-RRMS (n = 44), OND (n = 44); B) FP-RRMS (n = 167), OND (n = 85); and C) FP (n = 100). Anti-GAGA4 IgM levels were measured by enzyme immunoassay in cohort-A and cohort-B. Cohort-C IgM antibodies to glucose-based glycan panel were measured by immunofluorescence. Results FP-RRMS had higher levels of anti-GAGA4 IgM than OND patients (cohort-A, P = 0.01; cohort-B, P = 0.0001). Sensitivity and specificity were 27% and 97% for cohort-A; and 26% and 90% for cohort-B, respectively. In cohort-C, 58 patients experienced early relapse (<24 months), 31 had late relapse (≥24 months), and 11 did not experience second attack during follow-up. Kaplan–Meier curves demonstrated decrease in time to next relapse for patients positive for the antibody panel (P = 0.02, log rank). Conclusions Serum anti-GAGA4 IgM discerns FP-RRMS patients from OND patients. Higher levels of serum anti-α-glucose IgM in FP patients predict imminent early relapse.
Evaluation of Triple-Stream Convolutional Networks for Action Recognition

Recently, Two-Stream Convolutional Network has achieved remarkable performance. Especially, by capturing appearance and motion information, spatial-temporal two- stream networks bring noticeable improvement. On the other hand, dynamic image, which is a powerful representation for videos, has also been confirmed to provide complimentary information to spatial appearance. Inspired by these works, we proposed Triple-Stream Convolutional Networks by fusing a third network stream whose input is dynamic image. In this paper, we implement the proposed Triple-Stream Convolutional Networks and evaluated them in two aspects: (a) how the overall end-to-end classification performance can be benefited by adding the dynamic stream; (b) which way is efficient to use the trained Triple-Stream Convolutional Networks in classification. Our evaluation shows improvements over both single networks (spatial and temporal) and Fused Spatial-temporal Two-Stream Network.
Verapamil Increases the Bactericidal Activity of Bedaquiline against Mycobacterium tuberculosis in a Mouse Model

ABSTRACT Bedaquiline is a newly approved drug for the treatment of multidrug-resistant tuberculosis, but there are concerns about its safety in humans. We found that the coadministration of verapamil with subinhibitory doses of bedaquiline gave the same bactericidal effect in mice as did the full human bioequivalent bedaquiline dosing. Adding verapamil to bedaquiline monotherapy also protected against the development of resistant mutants in vivo. The adjunctive use of verapamil may permit use of lower doses of bedaquiline to be used and thereby reduce its dose-related toxicities in tuberculosis patients.
A Statistical Framework for Post-Silicon Tuning through Body Bias Clustering

Adaptive body biasing (ABB) is a powerful technique that allows post-silicon tuning of individual manufactured dies such that each die optimally meets the delay and power constraints. Assigning individual bias control to each gate leads to severe overhead, rendering the method impractical. However, assigning a single bias control to all gates in the circuit prevents the method from compensating for intra-die variation and greatly reduces its effectiveness. In this paper, we propose a new variability-aware method that clusters gates at design time into a handful of carefully chosen independent body bias groups, which are then individually tuned post-silicon for each die. We show that this allows us to obtain near-optimal performance and power characteristics with minimal overhead. For each gate, we generate the probability distribution of its post-silicon ideal body bias voltage using an efficient sampling method. We then use these distributions and their correlations to drive a statistically-aware clustering technique. We study the physical design constraints and show how the area and wirelength overhead can be significantly limited using the proposed method. Compared to a fixed design time based dual threshold voltage assignment method, we improve leakage power by 38-71% while simultaneously reducing the standard deviation of delay by 2-9times
Adapting to All Domains at Once: Rewarding Domain Invariance in SMT

Existing work on domain adaptation for statistical machine translation has consistently assumed access to a small sample from the test distribution (target domain) at training time. In practice, however, the target domain may not be known at training time or it may change to match user needs. In such situations, it is natural to push the system to make safer choices, giving higher preference to domain-invariant translations, which work well across domains, over risky domain-specific alternatives. We encode this intuition by (1) inducing latent subdomains from the training data only; (2) introducing features which measure how specialized phrases are to individual induced sub-domains; (3) estimating feature weights on out-of-domain data (rather than on the target domain). We conduct experiments on three language pairs and a number of different domains. We observe consistent improvements over a baseline which does not explicitly reward domain invariance.
Probing on Growth and Characterizations of SnFe2O4 Epitaxial Thin Films on MgAl2O4 Substrate

Epitaxial tin ferrite (SnFe2O4) thin films were grown using KrF excimer (248 nm) pulsed laser deposition technique under different growth conditions. Highly epitaxial thin films were obtained at growth temperature of 650 ˚C. The quality and epitaxial nature of the films were examined by X-ray diffraction technique. Furthermore, the phi scans of the film and substrate exhibit four folds symmetry which indicates a cube-on-cube epitaxial growth of the film on MgAl2O4 substrate. Moreover, the magnetic force microscopy measurement shows domains with cluster-like structure which is associated with ferromagnetic phase at room temperature. The coercive field and remnant magnetization of the films decrease with increase in temperature. These high quality ingenious magnetic films could be potentially used in data storage devices.
Proteomics and lipids of lipoproteins isolated at low salt concentrations in D2O/sucrose or in KBr Published, JLR Papers in Press, November 18, 2007.

There is much interest in the significance of apolipoproteins and proteins that are noncovalently associated with lipoproteins. It is possible that the high ionic strength used for isolation of lipoproteins with KBr and NaI could alter the pattern of associated exchangeable proteins. Here we describe lipoprotein classes fractionation from up to 0.5 ml of serum or plasma with buffers of physiological ionic strength and pH prepared with deuterium oxide (D2O) and sucrose. An advantage of the D2O/sucrose procedure was that the lipoproteins could be directly analyzed by the techniques described without need for desalting. We compared the isolated lipoproteins with those obtained using ultracentrifugation in KBr from the same plasma pool. Electrophoretic homogeneity of the lipoproteins was very similar using the two methods, as well as their lipid composition evaluated by HPLC. Two-dimensional electrophoresis and surface-enhanced laser adsorption/ionization time-of-flight mass spectrometry indicated that the patterns of exchangeable proteins of VLDL isolated using with the two procedures were very similar. However, significant differences were found in the profiles of LDL and HDL, indicating that the D2O/sucrose method allowed a more complete characterization of its exchangeable apolipoproteins and proteins.
Frustratingly Hard Domain Adaptation for Dependency Parsing

We describe some challenges of adaptation in the 2007 CoNLL Shared Task on Domain Adaptation. Our error analysis for this task suggests that a primary source of error is differences in annotation guidelines between treebanks. Our suspicions are supported by the observation that no team was able to improve target domain performance substantially over a state of the art baseline.
TECHNICAL NOTE CRIMINALISTICS

Different national and international agencies have selected specific STR sets for forensic database use. To enhance database comparison across national and international borders, a 27-locus multiplex system was developed comprising all 15 STR loci of the European standard set, the current 13 STR loci of the CODIS core, the proposed 22 STR loci of the expanded CODIS core, 4 additional commonly used STR loci, and the amelogenin locus. Development required iterative primer design to resolve primer-related artifacts, amplicon sizing, and locus-to-locus balance issues. The 19.5-min assay incorporated newly developed six-dye chemistry analyzed using a novel microfluidic electrophoresis instrument capable of simultaneous detection and discrimination of 8 or more fluorescent dyes. The 27-locus multiplex offers the potential for a new international STR standard permitting laboratories in any jurisdiction to use a single reaction to determine profiles for loci they typically generate plus an expanded common STR profiling set of global interest.
Worst Case Communication Delay of Real-Time Industrial Switched Ethernet With Multiple Levels

The industrial network, often referred to as fieldbus, becomes an indispensable component for intelligent manufacturing systems. Thus, in order to satisfy the real-time requirements of field devices such as sensors, actuators, and controllers, numerous fieldbus protocols have been developed. But, the application of fieldbus has been limited due to the high cost of hardware and the difficulty in interfacing with multivendor products. As an alternative to fieldbus, the Ethernet (IEEE 802.3) technology is being adapted to the industrial environment. However, the crucial technical obstacle of Ethernet is its nondeterministic behavior that cannot satisfy the real-time requirements. Recently, the switched Ethernet becomes a very promising alternative for real-time industrial application due to the elimination of uncertainties in Ethernet. This paper focuses on the application of the switched Ethernet with multiple levels (that is, cascade structure with multiple switching hubs) for real-time industrial networking. More specifically, this paper presents an analytical performance evaluation of the switched Ethernet with multiple levels from timing diagram analysis, and experimental evaluation from an experimental testbed of networked control system
Diet-Induced Muscle Insulin Resistance in Rats Is Ameliorated by Acute Dietary Lipid Withdrawal or a Single Bout of Exercise: Parallel Relationship Between Insulin Stimulation of Glucose Uptake and Suppression of Long-Chain Fatty Acyl-CoA

Chronic high-fat feeding in rats induces profound whole-body insulin resistance, mainly due to effects in oxidative skeletal muscle. The mechanisms of this reaction remain unclear, but local lipid availability has been implicated. The aim of this study was to examine the influence of three short-term physiological manipulations intended to lower muscle lipid availability on insulin sensitivity in high-fat–fed rats. Adult male Wistar rats fed a high-fat diet for 3 weeks were divided into four groups the day before the study: one group was fed the normal daily high-fat meal (FM); another group was fed an isocaloric low-fat high-glucose meal (GM); a third group was fasted overnight (NM); and a fourth group underwent a single bout of exercise (2-h swim), then were fed the normal high-fat meal (EX). In vivo insulin action was assessed using the hyperinsulinemic glucose clamp (plasma insulin 745 pmol/l, glucose 7.2 mmol/l). Prior exercise, a single low-fat meal, or fasting all significantly increased insulin-stimulated glucose utilization, estimated at either the whole-body level (P < 0.01 vs. FM) or in red quadriceps muscle (EX 18.2, GM 28.1, and NM 19.3 vs. FM 12.6 ± 1.1 μmol · 100 g−1 · min−1; P < 0.05), as well as increased insulin suppressibility of muscle total long-chain fatty acyl-CoA (LCCoA), the metabolically available form of fatty acid (EX 24.0, GM 15.5, and NM 30.6 vs. FM 45.4 nmol/g; P < 0.05). There was a strong inverse correlation between glucose uptake and LC-CoA in red quadriceps during the clamp (r = −0.7, P = 0.001). Muscle triglyceride was significantly reduced by short-term dietary lipid withdrawal (GM −22 and NM −24% vs. FM; P < 0.01), but not prior exercise. We concluded that muscle insulin resistance induced by high-fat feeding is readily ameliorated by three independent, short-term physiological manipulations. The data suggest that insulin resistance is an important factor in the elevated muscle lipid availability induced by chronic high-fat feeding.
Streaming Algorithms for Optimal Generation of Random Bits

Generating random bits from a source of biased coins (the biased is unknown) is a classical question that was originally studied by von Neumann. There are a number of known algorithms that have asymptotically optimal information efficiency, namely, the expected number of generated random bits per input bit is asymptotically close to the entropy of the source. However, only the original von Neumann algorithm has a 'streaming property' - it operates on a single input bit at a time and it generates random bits when possible, alas, it does not have an optimal information efficiency. The main contribution of this paper is an algorithm that generates random bit streams from biased coins, uses bounded space and runs in expected linear time. As the size of the allotted space increases, the algorithm approaches the information-theoretic upper bound on efficiency. In addition, we discuss how to extend this algorithm to generate random bit streams from m-sided dice or correlated sources such as Markov chains.
Effects of a nonionic detergent on calcium uptake by cardiac microsomes.

We investigated the effects of the nonionic detergent octaethylene glycol monododecyl ether (C12E8) on the sarcoplasmic reticulum calcium pump in cardiac microsomes in view of its specific effects on different ATP-accelerated steps in the catalytic cycle of the Ca-ATPase in leaky fast skeletal muscle microsomes. At low concentrations of MgATP2- (< 2.5 microM), a nonsolubilizing concentration of added C12E8 (15 microM) increased apparent Vmax(MgATP) of oxalate-facilitated calcium uptake associated with MgATP2- binding to the high affinity catalytic site. An ATP induced acceleration of calcium uptake, attributable to regulatory nucleotide binding, was seen between 2 and 3 microM MgATP2- in both C12E8-treated and control microsomes. These effects of C12E8 are similar to those seen previously with trypsin treatment of microsomes [Lu, Y. -Z. , Xu, Z. -C. , & Kirchberger, M.A. (1993) Biochemistry 32, 3105-3111]. However, at a saturating Ca2+ between 3 and 10 microM MgATP2-, C12E8 produced a greater reduction in the magnitude of the ATP-induced acceleration of calcium uptake seen with trypsin. At 1 mM MgATP2-, C12E8 and trypsin as well as protein kinase A-catalyzed microsomal phosphorylation all increased the Ca2+ affinity of the pump, but only the latter two treatments significantly increased apparent Vmax(Ca). In fact in trypsin-treated and phosphorylated microsomes, C12E8 reduced Vmax(Ca) to close to the control values; it reduced Vmax(Ca) only slightly in control microsomes. Under our experimental conditions, comparable effects of 15 microM C12E8 on calcium uptake were absent in fast skeletal muscle microsomes, which lack phospholamban. (ABSTRACT TRUNCATED AT 250 WORDS)
Non-Enzymatic Glucose Sensor Composed of Carbon-Coated Nano-Zinc Oxide

Nowadays glucose detection is of great importance in the fields of biological, environmental, and clinical analyzes. In this research, we report a zinc oxide (ZnO) nanorod powder surface-coated with carbon material for non-enzymatic glucose sensor applications through a hydrothermal process and chemical vapor deposition method. A series of tests, including crystallinity analysis, microstructure observation, and electrochemical property investigations were carried out. For the cyclic voltammetric (CV) glucose detection, the low detection limit of 1 mM with a linear range from 0.1 mM to 10 mM was attained. The sensitivity was 2.97 μA/cm2mM, which is the most optimized ever reported. With such good analytical performance from a simple process, it is believed that the nanocomposites composed of ZnO nanorod powder surface-coated with carbon material are promising for the development of cost-effective non-enzymatic electrochemical glucose biosensors with high sensitivity.
Energy-Aware and Rate-Aware Heuristic Beamforming in Downlink MIMO OFDMA Networks With Base-Station Coordination

This paper addresses the problem of coordinated beamforming across a group of base stations (BSs) and frequency slots in the downlink of a multiple-input multiple-output (MIMO) orthogonal frequency-division multiple-access (OFDMA) cellular network. Three figures of merit are considered for system design under a per-BS power constraint: 1) the weighted sum of the rates (WSR) on the frequency slots of the coordinated BSs; 2) the global energy efficiency (GEE), defined as the ratio between the network sum rate and the corresponding consumed power; and 3) the weighted sum of the energy efficiencies (WSEE) on the frequency slots of the coordinated BSs. The Karush-Kuhn-Tucker (KKT) conditions of the considered optimization problems are first derived to gain insight into the structure of the optimal beamformers. Then, we propose a suboptimal design method that can be applied to all considered figures of merit. Numerical results are provided to assess the performance of the proposed beamforming strategies.
Mixing Linear SVMs for Nonlinear Classification

In this paper, we address the problem of combining linear support vector machines (SVMs) for classification of large-scale nonlinear datasets. The motivation is to exploit both the efficiency of linear SVMs (LSVMs) in learning and prediction and the power of nonlinear SVMs in classification. To this end, we develop a LSVM mixture model that exploits a divide-and-conquer strategy by partitioning the feature space into subregions of linearly separable datapoints and learning a LSVM for each of these regions. We do this implicitly by deriving a generative model over the joint data and label distributions. Consequently, we can impose priors on the mixing coefficients and do implicit model selection in a top-down manner during the parameter estimation process. This guarantees the sparsity of the learned model. Experimental results show that the proposed method can achieve the efficiency of LSVMs in the prediction phase while still providing a classification performance comparable to nonlinear SVMs.
Differences in colocalization between Fos and PHI, GRP, VIP and VP in neurons of the rat suprachiasmatic nucleus after a light stimulus during the phase delay versus the phase advance period of the night

Two groups of four rats each received a 15‐minute light stimulus during the first part of the night (ZT14) and the second part (ZT19), respectively. After 45–60 minutes, the animals were killed by perfusion fixation. Adjacent Vibratome sections through the suprachiasmatic nucleus (SCN) were double‐immunostained for the presence of peptide histidine isoleucine (PHI), gastrin releasing peptide (GRP) or vasoactive intestinal peptide (VIP) with Fos by using fluorophore‐conjugated secondary antibodies. A few sections were triple‐immunostained for PHI, GRP or VIP with vasopressin (VP) and Fos. Sections were analyzed with a confocal laser scanning microscope. It turned out that the ZT19 light stimulus induced 4.2 times more nuclear profiles in the SCN immunoreactive for Fos than the light stimulus given at ZT14. The SCN of control animals did not show any Fos immunoreactivity. After the ZT14 light stimulus, approximately 33% of the Fos profiles showed colocalization with a perikaryal profile immunoreactive for PHI, GRP or VIP, whereas at ZT19, this percentage had doubled to approximately 65%. After the light stimulus at ZT14, the relatively low Fos induction was numerically and proportionally most prominent in the PHI‐immunoreactive perikarya. As compared with ZT14, the increase of Fos after the ZT19 light stimulus was most pronounced in the GRP‐immunoreactive perikarya (21×) followed by VIP (15×) and PHI (5×) This outcome suggests that at least three different cell groups characterized by, respectively, PHI alone, GRP, and VIP fully or partly colocalized with PHI, play a prominent role during light‐induced phase shifts: the PHI neurons during light‐induced phase delays, the GRP and VIP/(PHI) neurons during light‐induced phase advances. © 1996 Wiley‐Liss, Inc.
Oral Vaccination with the Porcine Rotavirus VP4 Outer Capsid Protein Expressed by Lactococcus lactis Induces Specific Antibody Production

The objective of this study to design a delivery system resistant to the gastrointestinal environment for oral vaccine against porcine rotavirus. Lactococcus lactis NZ9000 was transformed with segments of vP4 of the porcine rotavirus inserted into the pNZ8112 surface-expression vector, and a recombinant L. lactis expressing VP4 protein was constructed. An approximately 27 kDa VP4 protein was confirmed by SDS-PAGE , Western blot and immunostaining analysis. BALB/c mice were immunized orally with VP4-expression recombinant L. lactis and cellular, mucosal and systemic humoral immune responses were examined. Specific anti-VP4 secretory IgA and IgG were found in feces, ophthalmic and vaginal washes and in serum. The induced antibodies demonstrated neutralizing effects on porcine rotavirus infection on MA104 cells. Our findings suggest that oral immunization with VP4-expressing L. lactis induced both specific local and systemic humoral and cellular immune responses in mice.