Miracle-dz/UniFAR-FTUs huggingface dataset:
Oral hydroxycitrate supplementation enhances glycogen synthesis in exercised human skeletal muscle

Glycogen stored in skeletal muscle is the main fuel for endurance exercise. The present study examined the effects of oral hydroxycitrate (HCA) supplementation on post-meal glycogen synthesis in exercised human skeletal muscle. Eight healthy male volunteers (aged 22·0 (se 0·3) years) completed a 60-min cycling exercise at 70–75 % \dot {>V}O_{2\hairsp max} and received HCA or placebo in a crossover design repeated after a 7 d washout period. They consumed 500 mg HCA or placebo with a high-carbohydrate meal (2 g carbohydrate/kg body weight, 80 % carbohydrate, 8 % fat, 12 % protein) for a 3-h post-exercise recovery. Muscle biopsy samples were obtained from vastus lateralis immediately and 3 h after the exercise. We found that HCA supplementation significantly lowered post-meal insulin response with similar glucose level compared to placebo. The rate of glycogen synthesis with the HCA meal was approximately onefold higher than that with the placebo meal. In contrast, GLUT4 protein level after HCA supplementation was significantly decreased below the placebo level, whereas expression of fatty acid translocase (FAT)/CD36 mRNA was significantly increased above the placebo level. Furthermore, HCA supplementation significantly increased energy reliance on fat oxidation, estimated by the gaseous exchange method. However, no differences were found in circulating NEFA and glycerol levels with the HCA meal compared with the placebo meal. The present study reports the first evidence that HCA supplementation enhanced glycogen synthesis rate in exercised human skeletal muscle and improved post-meal insulin sensitivity.
Lossless embedded compression using multi-mode DPCM & averaging prediction for HEVC-like video codec

Video encoders and decoders for HEVC-like compression standards require huge external memory bandwidth, which composes a significant portion of the codec power consumption. To reduce the memory bandwidth, this paper presents a new lossless embedded compression algorithm and a high-throughput hardware architecture. Firstly, hybrid spatial-domain prediction is proposed to combine the merits of DPCM scanning and averaging. The prediction is then enhanced with multiple modes to accommodate various image characteristics. Finally, efficient residual regrouping is used to improve the compression performance based on semi-fixed length (SFL) coding. Experimental results show the proposed scheme can reduce data traffic by an average of 57.6%. The average compression ratio is 2.49, improved by at least 13.2% relative to the state-of-the-art algorithms. Although the complexity is increased, by applying several optimizations the hardware cost of designed architecture increases slightly. This work can be implemented with 54.2k gates cost for compressor and 46k gates for decompressor, which can support 4k×2k@120fps decoder.
Hypoxic Air Inhalation and Ischemia Interventions Both Elicit Preconditioning Which Attenuate Subsequent Cellular Stress In vivo Following Blood Flow Occlusion and Reperfusion

Ischemic preconditioning (IPC) is valid technique which elicits reductions in femoral blood flow occlusion mediated reperfusion stress (oxidative stress, Hsp gene transcripts) within the systemic blood circulation and/or skeletal muscle. It is unknown whether systemic hypoxia, evoked by hypoxic preconditioning (HPC) has efficacy in priming the heat shock protein (Hsp) system thus reducing reperfusion stress following blood flow occlusion, in the same manner as IPC. The comparison between IPC and HPC being relevant as a preconditioning strategy prior to orthopedic surgery. In an independent group design, 18 healthy men were exposed to 40 min of (1) passive whole-body HPC (FiO2 = 0.143; no ischemia. N = 6), (2) IPC (FiO2 = 0.209; four bouts of 5 min ischemia and 5 min reperfusion. n = 6), or (3) rest (FiO2 = 0.209; no ischemia. n = 6). The interventions were administered 1 h prior to 30 min of tourniquet derived femoral blood flow occlusion and were followed by 2 h subsequent reperfusion. Systemic blood samples were taken pre- and post-intervention. Systemic blood and gastrocnemius skeletal muscle samples were obtained pre-, 15 min post- (15PoT) and 120 min (120PoT) post-tourniquet deflation. To determine the cellular stress response gastrocnemius and leukocyte Hsp72 mRNA and Hsp32 mRNA gene transcripts were determined by RT-qPCR. The plasma oxidative stress response (protein carbonyl, reduced glutathione/oxidized glutathione ratio) was measured utilizing commercially available kits. In comparison to control, at 15PoT a significant difference in gastrocnemius Hsp72 mRNA was seen in HPC (−1.93-fold; p = 0.007) and IPC (−1.97-fold; p = 0.006). No significant differences were observed in gastrocnemius Hsp32 and Hsp72 mRNA, leukocyte Hsp72 and Hsp32 mRNA, or oxidative stress markers (p > 0.05) between HPC and IPC. HPC provided near identical amelioration of blood flow occlusion mediated gastrocnemius stress response (Hsp72 mRNA), compared to an established IPC protocol. This was seen independent of changes in systemic oxidative stress, which likely explains the absence of change in Hsp32 mRNA transcripts within leukocytes and the gastrocnemius. Both the established IPC and novel HPC interventions facilitate a priming of the skeletal muscle, but not leukocyte, Hsp system prior to femoral blood flow occlusion. This response demonstrates a localized tissue specific adaptation which may ameliorate reperfusion stress.
Assessment of nicotine dependence and its demographic correlates among African American smokers

Title of thesis: ASSESSMENT OF NICOTINE DEPENDENCE AND ITS DEMOGRAPHIC CORRELATES AMONG AFRICAN AMERICAN SMOKERS Eva Sharma Acharya, Master of Public Health, 2008 Directed By: Associate Professor Donna E. Howard Department of Public and Community Health Despite scientific evidence that smoking is highly addictive, little information is available on the prevalence of nicotine dependence among African American smokers. The primary objective of this study was to examine the associations between demographic variables, socioeconomic status, self reported smoking history and the level of nicotine dependence among African American smokers. This study was a cross-sectional secondary analysis of data collected during a randomized clinical trial from African American participants (n=206). The results showed that age of smokers, number of years of regular smoking, low education level and negative perception of ability to quit smoking were associated with high nicotine dependence. The multivariate analysis showed that those with negative perception of their ability to quit smoking had greater odds of having high nicotine dependence. The findings suggested that tailored interventions should include components that increase self efficacy among African American smokers depending on the level of nicotine dependence. ASSESSMENT OF NICOTINE DEPENDENCE AND ITS DEMOGRAPHIC CORRELATES AMONG AFRICAN AMERICAN SMOKERS
Gender Differences in Overt Behavior and Mediators of Depression Severity

For several decades, evolutionary and social learning theories have been explanatory frameworks to explicate gender differences in overt behaviors and the prevalence, etiology, and maintenance of mental health problems. To further explore relations among gender, overt behaviors, and depression severity, this study used a daily diary methodology to examine gender differences within thirteen behavioral domains and whether differential frequency of overt behaviors and environmental reward mediated the relationship between gender and depression severity. Overall, females engaged in a significantly greater breadth of behavioral domains and reported a higher level of environmental reward. Females reported spending more time in the domains of health/hygiene, spiritual activities, and eating with others. In contrast, males spent a greater duration of time in the domains of physical activity, sexual activity, and hobbies and recreational experiences. In relation to males, females found social activities, passive/sedentary behaviors, eating with others, and engagement in “other” activities to be more rewarding. Gender had a significant direct effect on depression severity, with females reporting increased depression. This effect was attenuated by the mediator (total environmental reward) such that to the extent that females exhibited increased environmental reward, the gender effect on depression was reduced. These data support behavioral models of depression and have clinical relevance as highlighted in the context of behavioral activation interventions for depression.
The association of self-efficacy and parent social support on physical activity in male and female adolescents.

OBJECTIVE Previous research has shown that cognitive factors may account for the relationship between interpersonal factors and health behaviors. Given these findings, the current study sought to further explore the direct and indirect relationship between parental social support and adolescent physical activity (PA). METHOD Data were collected from 1,421 sixth graders (73% Black, 54% females, 71% on free or reduced lunch) in South Carolina. Measures for emotional social support, instrumental social support, and adolescent self-efficacy (SE) were assessed and PA was assessed via accelerometry. RESULTS Parent instrumental social support was directly related to girls' PA and parent emotional social support was inversely related to girls' PA. Parent instrumental social support was indirectly related to boys' PA through boys' SE. The covaried association of SE with PA was significant for boys and marginal for girls. CONCLUSIONS SE for overcoming barriers may be an important construct for understanding the relationship between parent instrumental social support and boys' PA in underserved populations. The mechanisms for engaging in PA may be different for adolescent girls and boys.
Releasing efficient beta cores to market early

Verification of modern processors is an expensive, time consuming, and challenging task. Although it is estimated that over half of total design time is spent on verification, we often find processors with bugs released into the market. This paper proposes an architecture that tolerates, not just the typically infrequent bugs found in current processors, but a significantly larger set of bugs. The objective is to allow for a much quicker time to market. We propose an architecture built around Beta Cores, which are cores partially verified. Our proposal intelligently activates and deactivates a simple single issue in-order Checker Core to verify a buggy superscalar out-of-order Beta Core. Our Beta Core Solution (BCS), which includes the Beta Core, the Checker Core, and the logic to detect potentially buggy situations consumes just 5% more power than the stand-alone Beta Core. We also show that performance is only slightly diminished with an average slowdown of 1.6%. By leveraging program signatures, our BCS only needs a simple in-order Checker Core, at half the frequency, to verify a complex 4 issue out-of-order Beta Core. The BCS architecture allows for a decrease in verification effort and thus a quicker time to market.
Pulsed field ionization of Rydberg atoms

Fully quantum and classical trajectory Monte Carlo calculations are performed for a Rydberg alkali-metal atom that is kicked by a pulsed electric field. The two calculations are compared to recent experimental results through the ionization probability versus peak field strength. The energy distributions of the final electrons are compared between the two calculations. There is a qualitative difference between the classical and quantum momentum distributions which is measurable in principle. An experiment to detect the time-dependent precession of the orbital angular momentum in Cs is also proposed. @S1050-2947~97! 51211-X#
Ordered and quantum treemaps: Making effective use of 2D space to display hierarchies

Treemaps, a space-filling method for visualizing large hierarchical data sets, are receiving increasing attention. Several algorithms have been previously proposed to create more useful displays by controlling the aspect ratios of the rectangles that make up a treemap. While these algorithms do improve visibility of small items in a single layout, they introduce instability over time in the display of dynamically changing data, fail to preserve order of the underlying data, and create layouts that are difficult to visually search. In addition, continuous treemap algorithms are not suitable for displaying fixed-sized objects within them, such as images.This paper introduces a new "strip" treemap algorithm which addresses these shortcomings, and analyzes other "pivot" algorithms we recently developed showing the trade-offs between them. These ordered treemap algorithms ensure that items near each other in the given order will be near each other in the treemap layout. Using experimental evidence from Monte Carlo trials and from actual stock market data, we show that, compared to other layout algorithms, ordered treemaps are more stable, while maintaining relatively favorable aspect ratios of the constituent rectangles. A user study with 20 participants clarifies the human performance benefits of the new algorithms. Finally, we present quantum treemap algorithms, which modify the layout of the continuous treemap algorithms to generate rectangles that are integral multiples of an input object size. The quantum treemap algorithm has been applied to PhotoMesa, an application that supports browsing of large numbers of images.
. Introduction 2. Advanced Modulation Techniques 2.1 Ultrawideband 2.1.1 Ieee 802.15.3a 2.1.2 Wimedia Alliance 2.1.3 Uwb Forum 2.2 Orthogonal Frequency-division Multiplexing (ofdm) 3. Multi-antenna Techniques 3.1 Multiple Input Single Output (miso) 3.2 Multiple Input Multiple Output (mimo) 3.3 Space

A number of recent advances in the physical layer are enabling wireless communications devices to reach ever-greater speeds. These developments in modulation techniques, coding, and radio architecture enable better spectrum allocation, more power-efficient, errorresistant transmissions, and more flexible architectures for receiving signals. Many of the advances are being included in upcoming standards, like 802.16 and 802.11n, and will likely improve the already-fast adoption of wireless networking equipment. See Also: A Review of Key Wireless Physical Layer Concepts | Wireless Networking: Issues and Trends
Edge Weight Method for Community Detection on Mixed Scale-Free Networks

In this paper, we proposed an edge weight method for performing a community detection on mixed scale-free networks.We use the phrase “mixed scale-free networks” for networks where some communities have node degree that follows a power law similar to scale-free networks, while some have node degree that follows normal distribution. In this type of network, community detection algorithms that are designed for scale-free networks will have reduced accuracy because some communities do not have scale-free properties. On the other hand, algorithms that are not designed for scale-free networks will also have reduced accuracy because some communities have scale-free properties. To solve this problem, our algorithm consists of two community detection steps; one is aimed at extracting communities whose node degree follows power law distribution (scale-free), while the other one is aimed at extracting communities whose node degree follows normal distribution (non scale-free). To evaluate our method, we use NMI — Normalized Mutual Information — to measure our results on both synthetic and real-world datasets comparing with both scale-free and non scale-free community detection methods. The results show that our method outperforms all other based line methods on mixed scale-free networks.
Restoration of motion blurred image in scenes with moving objects

This paper analyze the motion blur that occurs during the process of image sampling by the camera on Turntable. In order to effectively restore scene blurred image with moving objects which is generated in the process, a restoration algorithm is proposed. Firstly, the moving objects are extracted from the scene blurred images. Then the scene blurred images and moving objects blurred images are restored respectively by using classical restoration methods and blind restoration methods. Finally, brightness compensation is used by the restored moving objects image which would be fused into scene image. Experimental results illustrate that the proposed algorithm is effective to the scene blurred image with moving objects and the restoration result is nice.
SparkNet: Training Deep Networks in Spark

Training deep networks is a time-consuming process, with networks for object recognition often requiring multiple days to train. For this reason, leveraging the resources of a cluster to speed up training is an important area of work. However, widely-popular batch-processing computational frameworks like MapReduce and Spark were not designed to support the asynchronous and communication-intensive workloads of existing distributed deep learning systems. We introduce SparkNet, a framework for training deep networks in Spark. Our implementation includes a convenient interface for reading data from Spark RDDs, a Scala interface to the Caffe deep learning framework, and a lightweight multi-dimensional tensor library. Using a simple parallelization scheme for stochastic gradient descent, SparkNet scales well with the cluster size and tolerates very high-latency communication. Furthermore, it is easy to deploy and use with no parameter tuning, and it is compatible with existing Caffe models. We quantify the dependence of the speedup obtained by SparkNet on the number of machines, the communication frequency, and the cluster's communication overhead, and we benchmark our system's performance on the ImageNet dataset.
User Preference Analysis and Visualization through the Browser History of Smart Devices

This paper studied the analysis of user preference and visualization through the browser history of smart devices. For the analysis of user preference, the browser history data which the user produced through smart devices in everyday life were automatically collected and transmitted to the server. Then using a web crawler the appropriate web pages were collected then classified by topics through a mechanical learning algorithm, and analyzed to determine which topic and category in the contents the user preferred. As a result of the experiment, the application of the Naïve Bayes algorithm yielded the best classifying capacity. And this experiment delivered the data through visualization to provide the user or the service provider reference. Through this test the experiment could classify the user character according to the consumption of contents by the smart device user, and understand the preference of the contents by the type of the user. Also, it could be utilized as an essential technique to provide personalized recommendation.
Identification of an optimized 2′-O-methylated trinucleotide RNA motif inhibiting Toll-like receptors 7 and 8

Bacterial RNA serves an important function as activator of the innate immune system. In humans bacterial RNA is sensed by the endosomal receptors TLR7 and TLR8. Differences in the posttranscriptional modification profile of prokaryotic when compared with eukaryotic RNA allow innate immune cells to discriminate between “host” and “foreign” RNA. Ribose 2′-O-methylation is of particular importance and has been reported to antagonize TLR7/8 activation. Yet, the exact sequence context in which 2′-O-methylation has to occur to mediate its inhibitory activity remains largely undefined. On the basis of a naturally occurring 2′-O-methylated RNA sequence, we performed a systematic permutation of the methylated nucleotide as well as adjacent bases and hereby identify two minimal trinucleotide motifs within a 9-mer oligoribonucleotide that are necessary and sufficient to antagonize TLR7 and TLR8 activation, respectively. Given the growing interest in the development of inhibitors of nucleic acid-sensing TLRs for therapeutic purposes, these results will facilitate the rational design of such antagonists in the future.
Efektifitas Intervensi Terapi Musik Klasik Terhadap Stress Dalam Menyusun Skripsi Pada Mhasiswa PSIK Undip Semarang

Stress is a condition of physical and psychological stress due to the demands of the self and the environment. The many demands of the task and the thesis is a stressor that can cause stress for students. One method to overcome the stress that is with music therapy. This study aims to determine differences in stress levels before and after music therapy at the final stage of a student who was writing his thesis at the University of Diponegoro PSIK Semarang. The sampling technique in this study was purposive sampling with the number of respondents 31 people. This type of study is pre-experiment which belong to the pre test and post test one group design.Analysis of statistical data used is the Wilcoxon Match Pairs Test. The data was collected at the time before and after therapy is given to classical music by using the DASS 42 Instrument developed by Lovibond and Lovibond (1995) is used as a stress gauge items. Based on this research, there are differences in stress levels of respondents before and after the therapy is given to classical music. From the results of Wilcoxon test for levels of stress before and after therapy to classical music both obtained significance value of 0.000 which is smaller than α = 0.05. The difference can be seen is the decline in the number of respondents prior to the classical music therapy on stress levels of students is 8 people students
Coordinate Regulation of Mature Dopaminergic Axon Morphology by Macroautophagy and the PTEN Signaling Pathway

Macroautophagy is a conserved mechanism for the bulk degradation of proteins and organelles. Pathological studies have implicated defective macroautophagy in neurodegeneration, but physiological functions of macroautophagy in adult neurons remain unclear. Here we show that Atg7, an essential macroautophagy component, regulates dopaminergic axon terminal morphology. Mature Atg7-deficient midbrain dopamine (DA) neurons harbored selectively enlarged axonal terminals. This contrasted with the phenotype of DA neurons deficient in Pten – a key negative regulator of the mTOR kinase signaling pathway and neuron size – that displayed enlarged soma but unaltered axon terminals. Surprisingly, concomitant deficiency of both Atg7 and Pten led to a dramatic enhancement of axon terminal enlargement relative to Atg7 deletion alone. Similar genetic interactions between Atg7 and Pten were observed in the context of DA turnover and DA-dependent locomotor behaviors. These data suggest a model for morphological regulation of mature dopaminergic axon terminals whereby the impact of mTOR pathway is suppressed by macroautophagy.