Miracle-dz/UniFAR-FTUs huggingface dataset:
Differences in Brain Structure and Function Among Yoga Practitioners and Controls

Background: Yoga is a mind-body based physical activity that has demonstrated a variety of physiological, psychological and cognitive health benefits. Although yoga practice has shown to improve cognitive performance, few studies have examined the underlying neurological correlates. Objective: The current study aimed to determine the differences in gray matter volume of the hippocampus, thalamus and caudate nucleus and brain activation during the Sternberg working memory task. Method: Participants were 13 experienced yoga practitioners (mean age = 35.8), defined as having more than 3 years of regular yoga practice, and 13 age- and sex-matched controls (mean age = 35.7). All participants completed a 6-min walk test to assess fitness, psychosocial and demographic questionnaires; and underwent magnetic resonance imaging to assess gray matter volume and brain activation. Results: There were no group differences on demographic measures of income, education and on estimated VO2max or physical activity levels. Gray matter volume differences were observed in the left hippocampus, showing greater volume in experienced yoga practitioners compared to controls (p = 0.017). The functional MRI results revealed less activation in the dorsolateral prefrontal cortex in yoga practitioners compared to controls during the encoding phase of the Sternberg task (p < 0.05). Reaction time and accuracy on the task did not differ between the groups. Conclusions: Our results suggest an association between regular long-term yoga practice and differential structure and function of specific brain regions involved in executive function, specifically working memory, which has previously shown to improve with yoga practice. Future studies need to examine intervention effects of yoga and explore its potential to maintain and improve cognitive health across the lifespan through longitudinal and intervention studies.
A precise positioning conditional probability estimator for fixed width booth multipliers

This brief proposes a Precise Positioning Conditional Probability (PPCP) estimator for the compensated circuit of the fixed width booth multipliers for various column length for truncation part, w. Unlike the previous works, the proposed work is carried out on the basis of entire zero and non-zero codes based on where it occurs. This PPCP estimator is used in the truncation part to reduce the errors incurred during the fixed width multiplication process. While comparing with the previous works, the proposed work is proved to be a precise one as the probability process is done based on positioning. Also an area efficient architecture of PPCP estimator is proposed. The final results of this brief show that the given multiplier is the most accurate and an area efficient one.
A Bipartite Matching Based User Pairing Scheme for Hybrid VLC-RF NOMA Systems

In this paper, we present a hybrid Visible Light Communication (VLC) and Radio Frequency (RF) based Non-Orthogonal Multiple Access (NOMA) system to extend the coverage of VLC and support multi-user communications at the same time. In the proposed system, all users are divided into multiple user pairs, where the near user who can receive the visible light signal directly would help forward the information to its paired far user through RF transmission. To achieve that, NOMA is adopted during the VLC phase so the near user is able to receive not only its own but also the information for its paired user. Aiming at minimizing the outage probability of system, we formulate the optimal user pairing problem and convert it into the one of finding the maximum weighted matching in a bipartite graph. Kuhn-Munkres (KM) algorithm is utilized to solve the problem. Simulation results demonstrate that the system performance is markedly improved with our proposed scheme.
Energy harvesting in IoT devices: A survey

Normally, IoT devices are powered by the batteries. As the lifetime of battery is limited thus, there is strong need of self-powered devices or alternative sources of energy to continuously power the IoT devices. For the same purpose energy harvesting techniques are used nowadays. Energy harvesting is the process of capturing energy from one or more renewable energy sources and converting them into usable electrical energy. In this paper, we are providing the survey on energy harvesting systems for IoT devices. Firstly, we discussed why energy harvesting is required and different architectures of harvesting systems. Further, we presented the energy harvesting systems considering different energy sources and their comparisons. Overall, the paper summarizes the numerous energy harvesting systems for IoT devices that act as the background for the researchers working in this area.
The Patch-Flow Method for Measuring Inner Source Collaboration

Inner source (IS) is the use of open source software development (SD) practices and the establishment of an open source-like culture within an organization. IS enables and requires developers to collaborate more than traditional SD methods such as plan-driven or agile development. To better understand IS, researchers and practitioners need to measure IS collaboration. However, there is no method yet for doing so. In this paper, we present a method for measuring IS collaboration by measuring the patch-flow within an organization. Patch-flow is the flow of code contributions across organizational boundaries such as project, organizational unit, or profit center boundaries. We evaluate our patch-flow measurement method using case study research with a software developing multi-industry company. By applying the method in the case organization, we evaluate its relevance and viability and discuss its usefulness. We found that about half (47.9%) of all code contributions constitute patch-flow between organizational units, almost all (42.2%) being between organizational units working on different products. Such significant patch-flow indicates high relevance of the patch-flow phenomenon and hence the method presented in this paper. Our patch-flow measurement method is the first of its kind to measure and quantify IS collaboration. It can serve as a base for further quantitative analyses of IS collaboration.
Recognising personality traits using social media

With the fast-emerging technology, the use of social media has also increased to a great extent. People use various social media sites like Facebook, Twitter, Google+, etc. The users are allowed to share various kinds of personal information on their social media accounts. People write what they feel, they also share posts, re-tweets, etc. Therefore, social media can be used to predict personality of a person. Personality is a fundamental aspect of human behavior and can help a lot in various fields of business and marketing. In this paper, we explore the techniques of various machine learning algorithms in order to deduce about personality of a user from his activities on social media. We use three algorithms namely SVM, KNN and MNB and then compare the results of these three algorithms. Finally, in the end we provide a combined result of all the three algorithms.
PAI1 blocks NMDA receptor-mediated effects of tissue-type plasminogen activator on cell signaling and physiology

ABSTRACT The fibrinolysis proteinase tissue-type plasminogen activator (tPA, also known as PLAT) triggers cell signaling and regulates cell physiology. In PC12 cells, Schwann cells and macrophages, the N-methyl-D-aspartate receptor (NMDA-R) mediates tPA signaling. Plasminogen activator inhibitor-1 (PAI1, also known as SERPINE1) is a rapidly acting inhibitor of tPA enzyme activity. Although tPA-initiated cell signaling is not dependent on its enzyme active site, we show that tPA signaling is neutralized by PAI1. In PC12 cells, PAI1 blocked the ERK1/2 activation mediated by tPA as well as neurite outgrowth. In Schwann cells, PAI1 blocked tPA-mediated ERK1/2 activation and cell migration. In macrophages, PAI1 blocked the ability of tPA to inhibit IκBα phosphorylation and cytokine expression. The cell signaling activity of tPA–PAI1 complex was rescued when the complex was formed with PAI1R76E, which binds to LRP1 with decreased affinity, by pre-treating cells with the LRP1 antagonist receptor-associated protein and upon LRP1 gene silencing. The inhibitory role of LRP1 in tPA–PAI1 complex-initiated cell signaling was unanticipated given the reported role of LRP1 as an NMDA-R co-receptor in signaling responses elicited by free tPA or α2-macroglobulin. We conclude that PAI1 functions as an inhibitor not only of the enzyme activity of tPA but also of tPA receptor-mediated activities. Summary: PAI1 inhibits the effects of tissue-type plasminogen activator on cell signaling and physiology mediated by the NMDA receptor. The mechanism of PAI1 activity involves targeting of tPA to the endocytic receptor LRP1.
5 Social Comparison : Motives , Standards , and Mechanisms

Social comparisons comparisons between the self and others are a fundamental psychological mechanism influencing people's judgments, experiences, and behavior. People constantly engage in social comparisons. Whenever they are confronted with information about how others are, what others can and cannot do, or what others have achieved and have failed to achieve, they relate this information to themselves (Dunning & Hayes, 1996). Likewise, whenever they want to know how they themselves are or what they themselves can and cannot do, they do so by comparing their own characteristics, fortunes, and weaknesses to those of others (Festinger, 1954). Social comparisons are even engaged with others who are unlikely to yield relevant information concerning the self (Gilbert, Giesler, & Morris, 1995), or who phenomenologically are not even there, because they were perceived outside of conscious awareness (Mussweiler, Rüter, & Epstude, 2004a; Stapel & Blanton, 2004). Because comparisons with others are such a fundamental, ubiquitous, and robust human proclivity, it may not be surprising that for over fifty years social comparison has been a highly studied topic in social psychological research. This research was guided by three central questions: Why do people engage in social comparisons? To whom do they compare themselves? How do social comparisons influence the self? Before presenting research attempting to answer these three questions, we want to acknowledge briefly the theory of social comparison processesby Festinger (1954) as one major point of departure for the field.
Improved algorithm based on multiscale morphology for intensification of gray scale images

Different image intensified methods are used for improvement of gray scale images. The new and improved algorithm is based on multiscale morphology for intensification of gray scale imges having various structuring elements at each scale as well as at neighbouring scales. The structuring elements used are disc, line, diamond and square for calculating top-hat and bot-hat transformations respectively at different scales. The proposed algorithm is used to extract the white and black region of an image and then calculate their sum of extracted regions. Subsequently, black and white regions are calculated at the neighboring scales also with their calculated sum. The summation of the results reveals the intensified image. From this image, again black and white regions are extracted and the sum is obtained. The results of the white and black regions and at its neighboring scales are combined with the first intensified image to obtain the final image. The results are compared with the other conventional techniques like un-sharp masking, contrast stretching, with the help of Background variance (BV), Detail Variance (DV) and Entropy as performance metrics. Thus the final intensified image shows better results both quantitatively and qualitatively.
A framework for social media network to curtail the banned and abused images

Social Media Networks (SMN) are slanted to a load of oddities nowadays. There is no incorporated control to screen and separate the activities followed in the SMNs. Along these lines we have proposed a framework to analyze and limit to the substance being partaken in the SMNs. As a part of the framework, two algorithms namely CBI and CAI is proposed for banned and abused images respectively. Support Vector Machine (SVM) classifier is adopted to identify and restrict the abused images being shared. The confined but unabused pictures are filtered using K-means clustering algorithm and Harrish-Stephens corner point detection algorithm. The proposed framework is implemented as a model SMN called SatbookLTE, which effectively diminishes the mishandled substance being partaken as pictures. The system analyzes the content being shared through the SMN without influencing the privacy of the client.
Complementing Relaxation Music for Pain During Dialysis

Methods: A randomized partially controlled study was conducted on 26 participants to examine the relationship of relaxation music and acute pain. These patients were randomly assigned to a control group or experimental group to assess pain, blood pressure, pulse and respirations within three minutes of access to the graft. After 30 minutes of listening to relaxation music or having no intervention these vital signs were re-assessed to note the correlation between relaxing music and pain.
Hybrid AC–DC Microgrid: Systematic Evaluation of Control Strategies

Hybrid ac-dc microgrid architecture is attracting special attention since it combines the benefits of both ac and dc systems. Control of hybrid microgrid presents a significant research and engineering challenge and hence needs increased research efforts. This paper attempts to review control strategies that are reported in the literature for the hybrid ac-dc microgrid. At first, typical and emerging hybrid microgrid power topologies are presented briefly. Various types of interlinking converters proposed for connecting ac and dc subgrids are discussed subsequently. Following this, a detailed discussion on control strategies for satisfying various control objectives is taken up. Control strategies have been systematically reviewed focusing on each of the broad aspects of control namely modeling, power management, coordinated control, stability analysis, power quality, and protection strategies. Finally, the research gaps observed during the review process and possible solution approaches are outlined.
Molecular Predictors of 3 D Morphogenesis by Breast Cancer Cell Lines in 3 D Culture

Correlative analysis of molecular markers with phenotypic signatures is the simplest model for hypothesis generation. In this paper, a panel of 24 breast cell lines was grown in 3D culture, their morphology was imaged through phase contrast microscopy, and computational methods were developed to segment and represent each colony at multiple dimensions. Subsequently, subpopulations from these morphological responses were identified through consensus clustering to reveal three clusters of round, grape-like, and stellate phenotypes. In some cases, cell lines with particular pathobiological phenotypes clustered together (e.g., ERBB2 amplified cell lines sharing the same morphometric properties as the grape-like phenotype). Next, associations with molecular features were realized through (i) differential analysis within each morphological cluster, and (ii) regression analysis across the entire panel of cell lines. In both cases, the dominant genes that are predictive of the morphological signatures were identified. Specifically, PPARc has been associated with the invasive stellate morphological phenotype, which corresponds to triple-negative pathobiology. PPARc has been validated through two supporting biological assays. Citation: Han J, Chang H, Giricz O, Lee GY, Baehner FL, et al. (2010) Molecular Predictors of 3D Morphogenesis by Breast Cancer Cell Lines in 3D Culture. PLoS Comput Biol 6(2): e1000684. doi:10.1371/journal.pcbi. 1000684 Editor: Uwe Ohler, Duke University, United States of America Received January 27, 2009; Accepted January 25, 2010; Published February 26, 2010 Copyright: 2010 Han et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: This work was supported by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research (contract DE-AC0205CH11231); the National Institutes of Health under grants U54 CA112970, CA58207, and CA090788; Susan G. Komen for the Cure (KG091136); and the Avon Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist. * E-mail: B_Parvin@lbl.gov ¤ Current address: Genentech, South San Francisco, California, United States of America
A comparison study between data mining tools over regression methods: Recommendation for SMEs

The purpose of this paper is to present comparison dimension methodology and the results of a comparison study of three data mining tools (WEKA, RapidMiner and IBM SPSS). Today, a vast amount of data mining tools supports different algorithms and business objectives with free or paid. This paper attempt to compare three selected data mining tools and the regression algorithms to provide the review information by considering different dimensions like data management tasks, functionality and model type, process-dependent features and system requirements and vendor information for SMEs to choose effective and efficient data mining tools.
Image processing for driver's safety and vehicle control using raspberry Pi and webcam

This paper gives real time approach for detection of driver drowsiness due to fatigue or intoxication. According to survey made by government, 22% accidents are due to drowsiness and 33% accidents are due to alcohol drinking. Actually to develop such a technique in car which can detect the drowsiness of driver is a big task. To complete this task image processing technique can be more useful. The camera is supported by embedded system in which Raspbian OS is used. This embeddd system is serially interfaced with another micro controller with RS232 protocol via serial communication, which will detect the real time siuation of the driver and switch on the alarm when drowsiness is detected the system switches off the car ignition power source by microcontroller based signal. A GSM module is introduced in the system which sends sms to the person whose contact is saved in the system.
On the lift-optimal aspect ratio of a revolving wing at low Reynolds number

Lentink & Dickinson (2009 J. Exp. Biol. 212, 2705–2719. (doi:10.1242/jeb.022269)) showed that rotational acceleration stabilized the leading-edge vortex on revolving, low aspect ratio (AR) wings and hypothesized that a Rossby number of around 3, which is achieved during each half-stroke for a variety of hovering insects, seeds and birds, represents a convergent high-lift solution across a range of scales in nature. Subsequent work has verified that, in particular, the Coriolis acceleration plays a key role in LEV stabilization. Implicit in these results is that there exists an optimal AR for wings revolving about their root, because it is otherwise unclear why, apart from possible morphological reasons, the convergent solution would not occur for an even lower Rossby number. We perform direct numerical simulations of the flow past revolving wings where we vary the AR and Rossby numbers independently by displacing the wing root from the axis of rotation. We show that the optimal lift coefficient represents a compromise between competing trends with competing time scales where the coefficient of lift increases monotonically with AR, holding Rossby number constant, but decreases monotonically with Rossby number, when holding AR constant. For wings revolving about their root, this favours wings of AR between 3 and 4.
Towards recommending diverse seasonal cooking recipes: A preliminary study based on monthly view data

The growth of recipe-sharing websites provides a rich data collection for food-related research. Recent studies have analyzed the monthly views of recipes to study temporal patterns in food consumption. However, seasonal dependency in food choice has not previously been considered in recipe recommendation systems. This paper presents a preliminary study, based on learning from monthly view data, to recommend seasonal recipes. First, using a set of recipe texts and their monthly views, we train a regression model to obtain seasonal scores that capture the relevance of individual time periods for each recipe. Then, given a set of new recipes, we construct a diverse set of seasonal recipes using both the sum of seasonal scores and the number of unique words. Based on experiments conducted on recipes collected from the Cookpad website in Japan, we present a quantitative comparison between possible approaches in calculating seasonal scores. User evaluation also shows a promising result for our diversification scheme.
Fuzzy based MPPT technique for PV system

This paper proposes the Maximum Power Point Tracking based on Fuzzy logic control for PV System. MPPT is required to extract maximum power corresponding to specific operating point. The output power of PV System is depends on weather conditions i.e. solar irradiation and atmospheric temperature. In this work PV System model is implemented in MATLAB at different irradiation and constant atmospheric temperature with different converter topology such as Boost and SEPIC. A Fuzzy Logic control (FLC) based MPPT technique proposed here, shows improvement in the efficiency of a PV based energy system and further comparison is made between Boost and SEPIC Converter under variable atmospheric conditions and temperature to validate the results.
MRI to Assess Neurological Function

This article describes a detailed set of protocols for mouse brain imaging using MRI. We focus primarily on measuring changes in neuroanatomy, and provide both instructions for mouse preparation and details on image acquisition, image processing, and statistics. Practical details as well as theoretical considerations are provided. © 2018 by John Wiley & Sons, Inc.
Gr upSM Differential Diagnosis of Patients with Multiple Sclerosis and Neurobehcet ’ s Disease in Aspects of Evoked Potentials

Although rarely seen, the differential diagnosis of Neurobehcet’s Disease (NB) may sometimes be complicated and Multiple Sclerosis (MS) is the major disease that takes place in the differential diagnosis. In this study, we performed Evoked Potentials (EPs) and Electroneuromyography (ENMG) in patients with MS and NB and in normal volunteers. Our aim was to investigate parameters of electrophysiological tests that might be useful in the differential diagnosis of NB and MS. A total of 95 persons, 55 MS patients, 20 patients with NB and 20 normals were studied electro physiologically. Pattern Visual Evoked Potentials (VEPs), Brainstem Auditory Evoked Potentials (BAEPs), posterior tibial Somatosensory Evoked Potentials (SEPs), nerve conduction studies and needle Electromyography (EMG) studies were performed in all patients and normals. All parameters of EPs were compared between the groups. The Visual Evoked Potential (VEP) study indicated that the amplitude values of P100 potentials in the NB and MS groups were lower than those of the normal group (p<0, 01), however the amplitudes in the NB group were still lower than those of the MS group (p<0, 05). To our knowledge VEPs were not compared between NB and MS patients before and our results confirmed that there could be differences in VEP studies which might be useful in the differential diagnosis of these two patient groups.