Miracle-dz/UniFAR-FTUs huggingface dataset:
Hardware Implementation and Performance Analysis of Resource Efficient Probabilistic Hard Decision LDPC Decoders

The Gallager B (GaB), among the hard-decision class of low-density-parity-check (LDPC) algorithms, is an ideal candidate for designing high-throughput decoder hardware. However, GaB suffers from poor error-correction performance. We introduce a probabilistic GaB (PGaB) algorithm that disturbs the decisions made during the decoding iterations randomly with a probability value determined based on experimental studies. We propose a heuristic that switches the decoding from GaB to PGaB after certain number of iterations and show that our heuristic reduces the average iteration count by up to 62% compared with GaB. We evaluate the hardware performance and resource requirement trends of PGaB over three quasicyclic codes using the Xilinx Virtex-6 field programmable gate array. We extend this analysis to performance comparison over our implementations of gradient descent bit flipping (GDBF) and probabilistic GDBF (PGDBF) algorithms for each code studied in this paper. We achieve up to four orders of magnitude better error correction performance than the GaB with less than 1% loss in throughput performance. Our heuristic consistently results with an improvement in maximum operational clock rate across all codes compared with the GDBF and PGDBF.
Adaptive Federated Learning in Resource Constrained Edge Computing Systems

Emerging technologies and applications including Internet of Things, social networking, and crowd-sourcing generate large amounts of data at the network edge. Machine learning models are often built from the collected data, to enable the detection, classification, and prediction of future events. Due to bandwidth, storage, and privacy concerns, it is often impractical to send all the data to a centralized location. In this paper, we consider the problem of learning model parameters from data distributed across multiple edge nodes, without sending raw data to a centralized place. Our focus is on a generic class of machine learning models that are trained using gradient-descent-based approaches. We analyze the convergence bound of distributed gradient descent from a theoretical point of view, based on which we propose a control algorithm that determines the best tradeoff between local update and global parameter aggregation to minimize the loss function under a given resource budget. The performance of the proposed algorithm is evaluated via extensive experiments with real datasets, both on a networked prototype system and in a larger-scale simulated environment. The experimentation results show that our proposed approach performs near to the optimum with various machine learning models and different data distributions.
Propolis: Chemical Composition and Its Applications in Endodontics

Introduction: The aim of this study was to review the chemical composition of propolis and its application in endodontics. Methods and Materials: For this purpose, keywords were searched on ScienceDirect, PubMed and World of Chemicals databases in order to find published papers from 1988 to February 2018. Results: There are many different compounds in propolis of different geographic regions; flavonoids are one of the most important agents which have anti-inflammatory, anti-viral, anti-allergic, anti-cancer, anti-bacterial and antioxidant effects. According to the mentioned properties, propolis can be used as a canal irrigation solution as well as intracanal medicament in endodontic treatments. Studies have shown that propolis as a storage medium is capable of maintaining the vitality of the periodontal ligaments cells and also has the ability to inhibit osteoclastic activity due to one of the active compounds present in it. In vital pulp therapy, propolis can induce the production of tubular dentin and also decrease the inflammation of the pulp. Conclusion: Considering the propolis components like resin, pollen, vitamins, flavonoids and phenols; it can be used for various purposes in endodontics and would have a promising role in future medicine as well as dentistry.
Affective Experience on Social Networking Sites Predicts Psychological Well-Being Off-Line

Previous studies have pondered the relevance of social networking sites (SNSs) to psychological well-being, but few have taken online affective experience into consideration. To extend previous research on the relationship between SNSs and psychological well-being, we opted to target emotions experienced while visiting SNSs as a means to predict off-line well-being. In our two studies, we surveyed affective experience on SNSs, overall life satisfaction, and general emotional well-being of young adults who access SNSs regularly. The results consistently demonstrated a positive association between SNS affective experience and off-line well-being. This finding held with SNS activities (Studies 1 and 2) and relevant personality traits (i.e., the Big Five factors, self-esteem; Study 2) considered in simultaneity. Our research highlights the important role of affective experience on SNSs in predicting off-line well-being as well as helps clarify the relationship between SNSs and well-being.
Exploration and Design of a Synchronous Message Passing Framework for a CPU-NPU Heterogeneous Architecture

In this paper we present the development of a framework for communication between an NPU (network processing unit) and CPU through synchronous message passing that is compliant with the synchronous communication events of the CSP formalisms. This framework is designed to be used for passing generic information between application components operating on both architectures and is intended to operate in conjunction with existing datapaths present on the NPU which in turn are responsible for network traffic transmission. An investigation of different message passing topologies is covered before the proposed message passing fabric is presented. As a proof of concept, an initial implementation of the fabric is developed and tested to determine its viability and correctness. Through testing it is shown that the implemented framework operates as intended. However, it is noted the throughput of the exploratory implementation is not considered suitable for high-performance applications and further evaluation is required.
Assessing the Use of Area- and Time-Averaging Based on Known De-correlation Scales to Provide Satellite Derived Sea Surface Temperatures in Coastal Areas

Satellite derived sea surface temperatures (SSTs) are often used as a proxy for in situ water temperatures, as they are readily available over large spatial and temporal scales. However, contamination of satellite images can prohibit their use in coastal areas. We compared in situ temperatures to SST foundation (~10 m depth) at 31 sites inshore of the East Australian Current (EAC), the dynamic western boundary current of the south Pacific gyre, using an area averaging approach to overcome coastal contamination. Varying across- and along-shelf distances were used to area average SST measurements and de-correlation time scales were used to gap fill data. As the EAC is typically anisotropic (dominant along-shore flow) the choice of across-shelf distances influenced the correlation with in situ temperatures more than along-shelf distances. However, the “optimal” distances for both measurements were within known de-correlation length scales. Incorporating both SST area and time averaging (based on de-correlation time scales) produced data for an average of 96% of days that in situ loggers were deployed, compared to 27% (52%) without (with) area averaging. Temperature differences between the in situ data and SSTs varied depending on time of year, with higher differences in the austral summer when daily in situ temperatures can range by up to 4.20°C. The differences between the in situ and SST measurements were, however, significant with or without area averaging (t-test: p-values < 0.05). Nevertheless, when using the area averaging approaches SSTs were only an average of ~1.05°C different from in situ temperatures and less than in situ temperature fluctuations. Linear mixed models revealed that latitude, distance to the coast and nearest estuary did not influence the difference between the in situ and satellite data as much as the water depth. This study shows that using de-correlation length and time scales to inform how to process satellite data can overcome contamination and missing data thereby greatly increasing the coverage and utility of SST data, particularly in coastal areas.
Face color facilitates the disambiguation of confusing emotion expressions: Toward a social functional account of face color in emotion communication.

Facial expressions of emotion include both muscular and color modulations that contribute to the accurate perception of emotion. However, some emotion categories share common facial-muscular features during the dynamic expressive sequence, which can lead to confusion and misidentification. The current research posits that a potential social function of facial-color expression lies in its ability to disambiguate confusing facial-muscular emotion expressions. In Experiment 1, participants were asked to rate and categorize confusing emotion expressions (i.e., mixed anger-disgust) that varied in facial color (i.e., CIELAB a*, red-green axis). The results showed that changes in facial color facilitated the disambiguation of the confusing emotion expressions for both ratings and categorizations. In Experiment 2, participants were asked to change the color on faces with either disgust, confusing, or anger expressions, to match the emotion being expressed. The results showed that participants differentially used color information to make the faces maximally expressive. Additionally, participants in Experiment 2 consistently applied facial color changes regardless of disambiguating information provided by either explicit instructions or validated expressions. The findings from the current research support a social functional account of facial color in the communication of emotion; facial color makes a unique contribution to emotion expression, independent of facial musculature. (PsycINFO Database Record
A Large Randomized Trial: Effects of Mindfulness-Based Stress Reduction (MBSR) for Breast Cancer (BC) Survivors on Salivary Cortisol and IL-6

Breast cancer survivors (BCS) often experience psychological and physiological symptoms after cancer treatment. Mindfulness-based stress reduction (MBSR), a complementary and alternative therapy, has reduced subjective measures of stress, anxiety, and fatigue among BCS. Little is known, however, about how MBSR affects objective markers of stress, specifically the stress hormone cortisol and the pro-inflammatory cytokine interleukin-6 (IL-6). In the present study, BCS (N = 322) were randomly assigned to a 6-week MBSR program for BC or usual-care control. Measurements of cortisol, IL-6, symptoms, and quality of life were obtained at orientation and 6 weeks. Cortisol and IL-6 were also measured prior to and after the MBSR(BC) class Weeks 1 and 6. The mean age of participants was 56.6 years and 69.4% were White non-Hispanic. Most had Stage I (33.8%) or II (35.7%) BC, and 35.7% had received chemotherapy and radiation. Cortisol levels were reduced immediately following MBSR(BC) class compared to before the class Weeks 1 and 6 (Wilcoxon-signed rank test; p < .01, d = .52–.56). IL-6 was significantly reduced from pre- to postclass at Week 6 (Wilcoxon-signed rank test; p < .01, d = .21). No differences were observed between the MBSR(BC) and control groups from baseline to Week 6 using linear mixed models. Significant relationships with small effect sizes were observed between IL-6 and both symptoms and quality of life in both groups. Results support the use of MBSR(BC) to reduce salivary cortisol and IL-6 levels in the short term in BCS.
Performance and Scalability of Lightweight Multi-kernel Based Operating Systems

Multi-kernels leverage today's multi-core chips to run multiple operating system (OS) kernels, typically a Light Weight Kernel (LWK) and a Linux kernel, simultaneously. The LWK provides high performance and scalability, while the Linux kernel provides compatibility. Multi-kernels show the promise of being able to meet tomorrow's extreme-scale computing needs while providing strong isolation, yielding high performance and scalability needed by classical HPC applications. McKernel and mOS started as independent research initiatives to explore the above potential. Previous work described their design and architecture advantages. This paper deploys the two LWKs and presents results from running them on a 2,048-node system with Intel Xeon Phi processors (KNL) connected by Intel Omni-Path Fabric. We compare the performance of McKernel, mOS, and Linux. Although the two multi-kernel efforts approached the problem from different angles, the results show a median performance improvement of 9% with some applications as high as 280% validating the efficacy of the multi-kernel approach. We provide insight into the performance improvements and discuss the strengths of the two different multi-kernel approaches.
A versatile and flexible framework for e-assessment in Higher-Education

This article describes an infrastructure that is being deployed across a university to enable teachers to conduct online exams for their courses. Two examination experiences are described, one corresponding to an open book examination on the University's computers and the other corresponding to an examination involving the use of software on students' computers. The performance of the students from the first experiment is analyzed to evaluate the impact of the online format compared to the paper format. The opinions of the students of the second experiment are collected to analyze their feelings regarding the BYOD format. The results provide significant and interesting indications for the development of eassessment.
Enhancing value and lowering costs of care: a qualitative exploration of a randomized linkage to care intervention in South Africa

ABSTRACT While interventions to improve HIV linkage and retention in care exist, none have demonstrated results sufficient to reach UNAIDS 90-90-90 goals. We explored values and costs of seeking clinical care through testing three strategies to improve linkage to care: Point of care CD4 testing alone (POC-CD4), POC-CD4 combined with transportation support and combined with care facilitation. We conducted in-depth interviews with participants and transcribed audio-recordings of care facilitation sessions. Participants described values and costs enhanced or addressed by the three interventions. Psychosocial support provided through the care facilitation intervention appeared salient. Participants named other values and costs of seeking care unrelated to the intervention, such as encouragement from healthcare workers and aversion to lifelong treatment. Combined with the quantitative results of this trial, these findings may point to why the care facilitation arm was successful but not the POC-CD4 only or transportation arms. It also provides guidance for future interventions.
The MicroRNA‐326: Autoimmune diseases, diagnostic biomarker, and therapeutic target

MicroRNAs (miRNAs) are uniquely regulated in healthy, inflamed, activated, cancerous, or other cells and tissues of a pathological state. Many studies confirm that immune dysregulation and autoimmune diseases with inflammation are correlated with various miRNA expression changes in targeted tissues and cells in innate or adaptive immunity. In this review, we will explain the history and classification of epigenetic changes. Next, we will describe the role of miRNAs changes, especially mir‐326 in autoimmunity, autoinflammatory, and other pathological conditions. A systematic search of MEDLINE, Embase, and Cochrane Library was presented for all related studies from 1899 to 2017 with restrictions in the English language. In recent years, researchers have concentrated on mostly those roles of miRNA that are correlated with the inflammatory and anti‐inflammatory process. Latest studies have proposed a fundamental pathogenic role in cancers and autoinflammatory diseases. Studies have described the role of microRNAs in autoimmunity and autoinflammatory diseases, cancers, and so on. The miRNA‐326 expression plays a significant role in autoimmune and other types of diseases.
Video Co-Saliency Guided Co-Segmentation

We introduce the term video co-saliency to denote the task of extracting the common noticeable, or salient, regions from multiple relevant videos. The proposed video co-saliency approach accounts for both inter-video foreground correspondences and intra-video saliency stimuli to emphasize the salient foreground regions of video frames and, at the same time, disregard irrelevant visual information of the background. Compared with image co-saliency, it is more reliable due to the utilization of temporal information of video sequence. Benefiting from the discriminability of video co-saliency, we present a unified framework for segmenting out the common salient regions of relevant videos, guided by video co-saliency prior. Unlike naive video co-segmentation approaches employing simple color differences and local motion features, the presented video co-saliency provides a more powerful indicator for the common salient regions, thus conducting video co-segmentation efficiently. Extensive experiments show that the proposed method successfully infers video co-saliency and extracts the common salient regions, outperforming the state-of-the-art methods.
Optimal Oxygen Excess Ratio Control for PEM Fuel Cells

In this paper, a feedback linearization controller is proposed for the van compressor in the air supply system of a proton exchange membrane fuel cell. The control goal is to avoid oxygen starvation and reduce power consumption by tracking an optimal reference oxygen excess ratio. Specifically, an improved control-oriented third-order model of the air supply system is proposed with the model identification of the air compressor. The optimal reference oxygen excess ratio is obtained from experiments to maintain a maximum net power. Based on the air supply system model, a nonlinear controller is designed to track the optimal oxygen excess ratio using feedback linearization. Lyapunov-based technique is utilized to analyze the stability of the closed-loop system. Effectiveness of the proposed approach is illustrated by experimental results.
Effect of Chlorogenic Acid Supplementation in MPTP-Intoxicated Mouse

Oxidative stress and neuroinflammation play a key role in dopaminergic (DA) neuronal degeneration, which results in the hindrance of normal ongoing biological processes in the case of Parkinson’s disease. As shown in several studies, on 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) administration, different behavioral parameters have suggested motor impairment and damage of antioxidant defence. Thus, some specific biological molecules found in medicinal plants can be used to inhibit the DA neuronal degeneration through their antioxidant and anti-inflammatory activities. With this objective, we studied chlorogenic acid (CGA), a naturally occurring polyphenolic compound, for its antioxidant and anti-inflammatory properties in MPTP-intoxicated mice. We observed significant reoccurrence of motor coordination and antioxidant defence on CGA supplementation, which has been in contrast with MPTP-injected mice. Moreover, in the case of CGA-treated mice, the enhanced expression of tyrosine hydroxylase (TH) within the nigrostriatal region has supported its beneficial effect. The activation of glial cells and oxidative stress levels were also estimated using inducible nitric oxide synthase (iNOS) and glial fibrillary acidic protein (GFAP) immunoreactivity within substantia nigra (SN) and striatum of MPTP-injected mice. Administration of CGA has prevented the neuroinflammation in SN by regulating the nuclear factor-κB expression in the MPTP-induced group. The significant release of certain pro-inflammatory mediators such as tumor necrosis factor-α and interleukin (IL)-1β has also been inhibited by CGA with the enhanced expression of anti-inflammatory cytokine IL-10. Moreover, reduced GFAP staining within the nigrostriatal region has supported the fact that CGA has significantly helped in the attenuation of astrocyte activation. Hence, our study has shown that CGA supplementation shows its therapeutic ability by reducing the oxidative stress and neuroinflammation in MPTP-intoxicated mice.
Predicting serum vitamin D concentrations based on self-reported lifestyle factors and personal attributes

Abstract Evidence supports the role of vitamin D in various conditions of development and ageing. Serum 25-hydroxyvitamin D (25(OH)D) is the best indicator for current vitamin D status. However, the cost of its measurement can be prohibitive in epidemiological research. We developed and validated multivariable regression models that quantified the relationships between vitamin D determinants, measured through an in-person interview, and serum 25(OH)D concentrations. A total of 200 controls participating in a population-based case–control study in Montreal, Canada, provided a blood specimen and completed an in-person interview on socio-demographic, reproductive, medical and lifestyle characteristics and personal attributes. Serum 25(OH)D concentrations were quantified by liquid chromatography–tandem MS. Multivariable least squares regression was used to build models that predict 25(OH)D concentrations from interview responses. We assessed high-order effects, performed sensitivity analysis using the lasso method and conducted cross-validation of the prediction models. Prediction models were built for users and non-users of vitamin D supplements separately. Among users, alcohol intake, outdoor time, sun protection, dose of supplement use, menopausal status and recent vacation were predictive of 25(OH)D concentrations. Among non-users, BMI, sun sensitivity, season and recent vacation were predictive of 25(OH)D concentrations. In cross-validation, 46–47 % of the variation in 25(OH)D concentrations were explained by these predictors. In the absence of 25(OH)D measures, our study supports that predicted 25(OH)D scores may be used to assign exposure in epidemiological studies that examine vitamin D exposure.