Miracle-dz/UniFAR-FTUs huggingface dataset:
Triptolide Inhibits IL-12/IL-23 Expression in APCs via CCAAT/Enhancer-Binding Protein α

Triptolide is a biologically active component purified from Chinese herbal plant Tripterygium wilfordii Hook F. It is widely used in East Asia for treatment of systemic lupus erythematosus, rheumatoid arthritis, nephritis, Bechect’s disease, psoriasis, atopic dermatitis, and asthma. However, its immunological mechanisms are poorly understood. IL-12 and IL-23 are closely related heterodimeric cytokines that share the common subunit p40. They are produced by APCs and are key factors in the generation and effector functions of Th1 and Th17 cells, respectively. They have been strongly implicated in the pathogenesis of several autoimmune disorders. In this study, we investigated the molecular mechanism whereby triptolide inhibits the expression of the p40 gene in APCs. We demonstrate that triptolide does so at the transcriptional level in part through targeting CCAAT/enhancer-binding protein-α (C/EBPα), which directly interacts with the p40 promoter and inhibits its transcription in inflammatory macrophages. Triptolide can activate the transcription of C/EBPα, and phosphorylation of Ser21 and Thr222/226 critical for C/EBPα inhibition of p40. Further, activation of C/EBPα by triptolide is dependent on upstream kinases ERK1/2 and Akt-GSK3β. This study provides mechanistic insights into the immunomodulatory capacity of triptolide and has strong implications for its therapeutic applications in autoimmune diseases.
The Influence of Study Away Experiences on Global Perspective-Taking

This article examines the relationship between 2 study away experiences—study abroad and service-learning—and the development of a global perspective. Three different studies are presented using cross-sectional and longitudinal designs and multi-institutional samples. The results specifically link involvement in study abroad and service-learning to the varying dimensions of the Global Perspective Inventory, demonstrating the influence such involvement has on student learning and development across cognitive, intrapersonal, and interpersonal domains. The article concludes with a discussion of the results and implications for administrators and practitioners interested in assessing global learning on their campuses.
Effects of Exercise Training under Hyperbaric Oxygen on Oxidative Stress Markers and Endurance Performance in Young Soccer Players: A Pilot Study

The aim of the present study was to determine the effects of three weeks of hyperbaric oxygen (HBO2) training on oxidative stress markers and endurance performance in young soccer players. Participants (18.6 ± 1.6 years) were randomized into hyperbaric-hyperoxic (HH) training (n = 6) and normobaric normoxic (NN) training (n = 6) groups. Immediately before and after the 5th, 10th, and 15th training sessions, plasma oxidative stress markers (lipid hydroperoxides and uric acid), plasma antioxidant capacity (6-hydroxy-2,5,7,8-tetramethylchroman-2-carboxylic acid [TROLOX]), arterial blood gases, acid-base balance, bases excess (BE), and blood lactate analyses were performed. Before and after intervention, maximal oxygen uptake (VO2max) and peak power output (PPO) were determined. Neither HH nor NN experienced significant changes on oxidative stress markers or antioxidant capacity during intervention. VO2max and PPO were improved (moderate effect size) after HH training. The results suggest that HBO2 endurance training does not increase oxidative stress markers and improves endurance performance in young soccer players. Our findings warrant future investigation to corroborate that HBO2 endurance training could be a potential training approach for highly competitive young soccer players.
Implementation and assessment of diffusion‐weighted partial Fourier readout‐segmented echo‐planar imaging

Single‐shot echo‐planar imaging has been used widely in diffusion magnetic resonance imaging due to the difficulties in correcting motion‐induced phase corruption in multishot data. Readout‐segmented EPI has addressed the multishot problem by introducing a two‐dimensional nonlinear navigator correction with online reacquisition of uncorrectable data to enable acquisition of high‐resolution diffusion data with reduced susceptibility artifact and T*2 blurring. The primary shortcoming of readout‐segmented EPI in its current form is its long acquisition time (longer than similar resolution single‐shot echo‐planar imaging protocols by approximately the number of readout segments), which limits the number of diffusion directions. By omitting readout segments at one side of k‐space and using partial Fourier reconstruction, readout‐segmented EPI imaging times could be reduced. In this study, the effects of homodyne and projection onto convex sets reconstructions on estimates of the fractional anisotropy, mean diffusivity, and diffusion orientation in fiber tracts and raw T2‐ and trace‐weighted signal are compared, along with signal‐to‐noise ratio results. It is found that projections onto convex sets reconstruction with 3/5 segments in a 2 mm isotropic diffusion tensor image acquisition and 9/13 segments in a 0.9 × 0.9 × 4.0 mm3 diffusion‐weighted image acquisition provide good fidelity relative to the full k‐space parameters. This allows application of readout‐segmented EPI to tractography studies, and clinical stroke and oncology protocols. Magn Reson Med, 2012. © 2011 Wiley‐Liss, Inc.
SmartClean: An Incremental Data Cleaning Tool

This paper presents the SmartClean tool. The purpose of this tool is to detect and correct the Data Quality Problems (DQPs). Compared with existing tools, SmartClean has the following main advantage: the user does not need to specify the execution sequence of the data cleaning operations. For that, an execution sequence was developed. The problems are manipulated (i.e., detected and corrected) following that sequence. The sequence also supports the incremental execution of the operations. In this paper, the underlying architecture of the tool is presented and its components are described in detail. The tool’s validity and, consequently, of the architecture is demonstrated through the presentation of a case study. Although SmartClean has cleaning capabilities in all other levels, in this paper are only described those related with the attribute value level.
Scintillation Properties of CsI:Na,  $^{133}$Ba Crystal

In Hyperball-J experiments, the lutetium oxyorthosilicate (Lu<sub>2</sub>SiO<sub>5</sub>:Ce, LSO) scintillators are constantly used to monitor and calibrate the Ge detectors. The LSO crystal has <sup>176</sup>Lu as a natural radioactive source. A new CsI:Na crystal that contains a <sup>133</sup>Ba radioactive source was developed in this study. This developed crystal can be used for detector calibration instead of LSO scintillators. The crystal was grown using a 2-zone vertical Bridgman method with a pulling speed of 0.5 mm/h. The CsI:Na, <sup>133</sup>Ba crystal was cut to Φφ 10 mm x 5 mm. Under X-ray excitation, the emission band of the crystal was observed between 330 nm and 650 nm. The scintillation properties of the CsI:Na, <sup>133</sup>Ba crystal such as light yield, energy resolution and decay time, were also measured using a <sup>137</sup>Cs γ-ray source. A High Purity Germanium (HPGe) detector was used to estimate the radioactivity in the crystal. The γ-ray peaks were identiήed from <sup>133</sup>Ba decay in the CsI:Na, <sup>133</sup>Ba crystal with a HPGe detector.
Jitter and Amplitude Noise Accumulations in Cascaded All-Optical Regenerators

This paper proposes and demonstrates a simulation model to systematically investigate jitter accumulations in cascaded all-optical 2R regenerators. The simulation results indicate that when the pattern dependence from the memory effect is minimized, the jitter accumulation depends critically on the degree of the regenerative nonlinearity. Studies of tradeoffs between the jitter from bandwidth limitation and the signal-to-noise-ratio degradation help identify the optimized regenerator bandwidth for various degrees of regenerative nonlinearity. The simulation then considers the pattern dependence from the memory effect and finds that it can severely degrade the cascadability of an optical 2R regenerator and can make it worse than that of a linear optical amplifier (optical 1R). The simulation results show good matches to the experimental results of an optical 2R regenerator based on a semiconductor optical amplifier based Mach-Zehnder interferometer. To overcome the jitter accumulation associated with the optical 2R regeneration, we experimentally demonstrate an optical 3R regenerator for optical nonreturn-to-zero signals with all-optical clock recovery. The experiments achieve more than 1000-hop cascadability for pseudorandom binary sequence 231-1 inputs with a 100-km recirculation loop using lab fiber. Field trial experiments then demonstrate a more than 1000-hop cascadability for a 3R spacing of 66 km and a 100-hop cascadability for a 3R spacing of 264 km.
Acceleration of Communication-Aware Task Mapping Techniques through GPU Computing

The era of distributed computing, where applications are executed on platforms like clusters, grids and/or clouds of computers, have shown the need for taking into account the communications that take place on distributed computer architectures when executing applications. In that environment, different communication-aware mapping techniques were proposed for improving the system performance, both for off-chip and for on-chip networks. Some of these proposals are based on heuristic search for finding pseudo-optimal assignments of a given population of tasks and processing elements. The technology improvement has allowed a significant increase in the problem size, multiplying the number of processor cores in each chip. Therefore, the proposals based on heuristic search must be accelerated in order to search in larger exploration domains within the same execution times. In this paper, we propose a comparative study of the parallel version of the local search method for communication-aware task mapping techniques. Unlike other comparative studies of heuristic methods implemented on GPUs, we compare the performance provided by the parallel version for GPUs with the performance provided by a MPI parallel version in terms of execution times and fitness values provided. The MPI version was executed on a cluster optimized for MPI applications. Also, we have considered a GPU with Fermi architecture and we have mapped the local search algorithm onto the GPU in order to improve the performance. The results show that the parallel implementation on a single GPU provides similar fitness function values than the MPI implementation on the cluster. However, the execution times required by the GPU implementation are significantly lower than the ones required by the MPI implementation, and these differences increase as so does size of the parallel system.
Algorithms for solid noise synthesis

A solid noise is a function that defines a random value at each point in space. Solid noises have immediate and powerful applications in surface texturing, stochastic modeling, and the animation of natural phenomena.Existing solid noise synthesis algorithms are surveyed and two new algorithms are presented. The first uses Wiener interpolation to interpolate random values on a discrete lattice. The second is an efficient sparse convolution algorithm. Both algorithms are developed for model-directed synthesis, in which sampling and construction of the noise occur only at points where the noise value is required, rather than over a regularly sampled region of space. The paper attempts to present the rationale for the selection of these particular algorithms.The new algorithms have advantages of efficiency, improved control over the noise power spectrum, and the absence of artifacts. The convolution algorithm additionally allows quality to be traded for efficiency without introducing obvious deterministic effects. The algorithms are particularly suitable for applications where high-quality solid noises are required. Several sample applications in stochastic modeling and solid texturing are shown.
CATP-6, a C. elegans Ortholog of ATP13A2 PARK9, Positively Regulates GEM-1, an SLC16A Transporter

In previous work, we found that gain-of-function mutations that hyperactivate GEM-1 (an SLC16A transporter protein) can bypass the requirement for GON-2 (a TRPM channel protein) during the initiation of gonadogenesis in C. elegans. Consequently, we proposed that GEM-1 might function as part of a Mg2+ uptake pathway that functions in parallel to GON-2. In this study, we report that CATP-6, a C. elegans ortholog of the P5B ATPase, ATP13A2 (PARK9), is necessary for gem-1 gain-of-function mutations to suppress the effects of gon-2 inactivation. One possible explanation for this observation is that GEM-1 serves to activate CATP-6, which then functions as a Mg2+ transporter. However, we found that overexpression of GEM-1 can alleviate the requirement for CATP-6 activity, suggesting that CATP-6 probably acts as a non-essential upstream positive regulator of GEM-1. Our results are consistent with the notion that P5B ATPases govern intracellular levels of Mg2+ and/or Mn2+ by regulating the trafficking of transporters and other proteins associated with the plasma membrane.
Effects of Modafinil on Wakefulness and Executive Function in Patients With Narcolepsy Experiencing Late-Day Sleepiness

Objectives:A modafinil daily dosing strategy promotes wakefulness in narcolepsy patients experiencing excessive daytime sleepiness; however, some patients may continue to experience late-day sleepiness. Excessive sleepiness in narcolepsy is associated with cognitive impairment. Modafinil has improved executive function in other models of excessive sleepiness. This study evaluated the effects of once-daily vs. split doses of modafinil on wakefulness and of combined doses on executive function in narcolepsy patients experiencing late-day sleepiness despite satisfactory modafinil treatment earlier in the day. Methods:After a 2-week washout, 24 patients received 3 weeks of double-blind treatment with modafinil 400-mg once daily (7 AM) plus placebo (noon) or modafinil 600-mg split dose (400 mg, 7 AM; 200 mg, noon). Assessments included a Maintenance of Wakefulness Test (MWT) for individual regimens and the Wisconsin Card Sort Test (WCST) for treatments combined. Results:Modafinil 600-mg split dose was significantly more effective than modafinil 400-mg once daily in improving late-day MWT scores (5 PM–7 PM; P < 0.05). Significant mean (± SEM) reductions from baseline of 8.2 ± 2.7 in the total number of errors and 5.9 ± 1.9 in total percent of errors (P < 0.05, both) were demonstrated for modafinil on the WCST. Modafinil was well tolerated; adverse events included headache (n = 1), emotional lability (n = 1), bronchitis (n = 1), and accidental injury (n = 2), with no reports of insomnia. Conclusions:For patients with residual late-day sleepiness associated with narcolepsy, an additional 200-mg dose of modafinil taken at midday was effective in sustaining wakefulness throughout the entire waking day. Treatment with modafinil also significantly improved executive function.
Prediction or Not? An Energy-Efficient Framework for Clustering-Based Data Collection in Wireless Sensor Networks

For many applications in wireless sensor networks (WSNs), users may want to continuously extract data from the networks for analysis later. However, accurate data extraction is difficult-it is often too costly to obtain all sensor readings, as well as not necessary in the sense that the readings themselves only represent samples of the true state of the world. Clustering and prediction techniques, which exploit spatial and temporal correlation among the sensor data provide opportunities for reducing the energy consumption of continuous sensor data collection. Integrating clustering and prediction techniques makes it essential to design a new data collection scheme, so as to achieve network energy efficiency and stability. We propose an energy-efficient framework for clustering-based data collection in wireless sensor networks by integrating adaptively enabling/disabling prediction scheme. Our framework is clustering based. A cluster head represents all sensor nodes in the cluster and collects data values from them. To realize prediction techniques efficiently in WSNs, we present adaptive scheme to control prediction used in our framework, analyze the performance tradeoff between reducing communication cost and limiting prediction cost, and design algorithms to exploit the benefit of adaptive scheme to enable/disable prediction operations. Our framework is general enough to incorporate many advanced features and we show how sleep/awake scheduling can be applied, which takes our framework approach to designing a practical algorithm for data aggregation: it avoids the need for rampant node-to-node propagation of aggregates, but rather it uses faster and more efficient cluster-to-cluster propagation. To the best of our knowledge, this is the first work adaptively enabling/disabling prediction scheme for clustering-based continuous data collection in sensor networks. Our proposed models, analysis, and framework are validated via simulation and comparison with competing techniques.
Multitask multivariate common sparse representations for robust multimodal biometrics recognition

In this paper, we propose multitask multivairate common sparse representations for robust multimodal biometrics recognition. The proposed approach can be viewed as an extension of previous work on joint sparse representations for robust multimodal biometrics recognition. The proposed algorithm utilizes the discriminative information among different modalities simultaneously by enforcing the common sparse representation across all the modalities and achieves more robust multimodal recognition especially when all modalities are noisy and “weak”. Alternating direction method of multipliers is proposed to solve the resulting optimization problem. Experiments on two biometric datasets show that our method performs better than the state-of-the-art fusion methods.
Impact of Plug-In Hybrid Electric Vehicles on distribution systems

Today the electricity systems and the transportation systems face a number of challenges related to reliability, security and environmental sustainability. Electric transportation has many attractive features in today's energy environment including decreasing greenhouse gas emissions from the transportation sector, reducing dependence on imported petroleum, and potentially providing consumers a lower cost alternative to gasoline. Plug-in Hybrid Electric Vehicles (PHEVs) represents the most promising approach to electrification of a significant portion of the transportation sector. The batteries of the plug-in hybrid electric vehicles are to be charged at home from a standard outlet, on a park lot or park deck, play as extra electrical loads, while the batteries on PHEVs can provide power to the grid when parked, known as vehicle-to-grid (V2G) concept. Considering the high penetration level of PHEVs and the charge profiles of PHEVs battery pack, the PHEVs play as the extra electrical loads have an impact on the distribution systems is analyzed in term of fault analysis in this paper.
State of Art in Ontology Development Tools

Ontology plays an important role in semantic web, information extraction, artificial intelligence, natural language processing, knowledge management etc. Ontology building is a challenging task in today’s world of semantic web. Manually construction of ontology is very time consuming and complex process. Wide variety of methods and tools are available for building ontology. These tools help users to construct the ontology and it is necessary to choose the appropriate tool for this purpose. This paper explores and analyzes various tools available for construction of ontology and also provides contrast among these tools.
The Effects of Removable Denture on Swallowing

Objective To investigate the relationship between removable dentures and swallowing and describe risks. Methods Twenty-four patients with removable dentures who were referred for videofluoroscopic swallowing study (VFSS) were enrolled. We evaluated the change of swallowing function using VFSS before and after the removal of the removable denture. The masticatory performance by Kazunori's method, sensation of oral cavity by Christian's method, underlying disease, and National Institutes of Health Stroke Scale for level of consciousness were collected. Functional dysphagia scales, including the oral transit time (OTT), pharyngeal transit time (PTT), percentage of oral residue, percentage of pharyngeal residue, oropharyngeal swallow efficiency (OPSE), and presence of aspiration were measured. Results Four patients dropped out and 20 patients were analyzed (stroke, 13 patients; pneumonia, 3 patients; and others, 4 patients). The mean age was 73.3±11.4 years. There were significant differences before and after the removal of the denture for the OTT. OTT was significantly less after the removal of the denture (8.87 vs. 4.38 seconds, p=0.01). OPSE increased remarkably after the removal of the denture, but without significance (18.24%/sec vs. 25.26%/sec, p=0.05). The OTT and OPSE, while donning a removable denture, were correlated with the masticatory performance (OTT, p=0.04; OPSE, p=0.003) and sensation of oral cavity (OTT, p=0.006; OPSE, p=0.007). Conclusion A removable denture may have negative effects on swallowing, especially OTT and OPSE. These affects may be caused by impaired sensation of the oral cavity or masticatory performance induced by the removable denture.
Implementation of a graph-based data model for complex objects

We have developed a graph-based data model called the Hypernode Model whose single data structure is the hypernode, a directed graph whose nodes may themselves reference further directed graphs. A prototype database system supporting this model is being developed at London University as part of a project whose aims are threefold: (i) to ascertain the expressiveness and flexibility of the hypernode model, (ii) to experiment with various querying paradigms for this model, and (iii) to investigate the suitability of the directed graph as a data structure supported throughout all levels of the implementation. The purpose of this paper is to report upon our findings to date.
EE shape low loss three-phase AC filter inductor design for three-phase PWM inverter

This paper proposes a three-phase AC filter inductor, which uses two soft magnetic materials, for use in three-phase pulse-width modulated (PWM) inverters. This inductor features loss reduction, achieves the same volume as conventional inductors, and has good inductance balance in each phase. First, a three-phase inductor that provides the same value of inductance in each phase is designed. Then, the inductor losses in a three-phase AC filter inductor used in a 1 kVA three-phase PWM inverter are evaluated through simulations and experiments. The conversion efficiency simulations illustrate that the proposed inductor improves the conversion efficiency. The conversion efficiencies of actual three-phase 1 kVA PWM inverters are measured, for the conventional and proposed AC filter inductors. In the experiments, the conversion efficiency in the case using the proposed inductor is found to be improved by approximately 1% at low power loads, when compared to the conventional inductors.