Miracle-dz/UniFAR-FTUs huggingface dataset:
The Impact of Public Access Venue Information and Communication Technologies in Botswana Public Libraries

Abstract Objective – A study on the impact of Public Access Venue (PAV) Information and Communication Technologies (ICTs) was conducted in Botswana libraries with Internet connections. The main objective was to determine the impact of ICTs in public libraries. Methods –Using the Sustainable Livelihoods Framework as a theoretical lens, the study used semi-structured interviews and focus group discussions to investigate the impact of PAV ICTs in 4 study sites, resulting in data from a total of 39 interviews and 4 focus groups. Methods –Using the Sustainable Livelihoods Framework as a theoretical lens, the study used semi-structured interviews and focus group discussions to investigate the impact of PAV ICTs in 4 study sites, resulting in data from a total of 39 interviews and 4 focus groups. Results – The results of the study show that PAV ICTs had a positive impact on users in the areas of education and economic benefits. Within educational and economic impacts, social benefits were also found, pertaining to the use of social media and the Internet for formal and informal communication. The study also revealed a slight difference between school going users and non-school going elderly users where the use and acquisition of computer skills was concerned. Elderly non-school going users tended to rely on venue staff for skills more than the younger school going users. Conclusion – The study recommends that PAV facilities should be improved in terms of skills offered and resources availed so as to appeal to both the younger school going generation and the older non-school going users. It is also recommended that education on ICT be improved to help curb rising unemployment in Botswana; such skills would enhance the income generation skills of the unemployed users as well as school leavers.
Adjunctive virtual reality for procedural pain management of burn patients during dressing change or physical therapy: A systematic review and meta‐analysis of randomized controlled trials

Dressing change and physical therapy are extremely painful procedures for burn patients. Adjunctive virtual reality therapy reportedly reduces pain when added to analgesics, but a summary analysis of the data has yet to be performed. We conducted this systematic review and meta‐analysis of randomized controlled trials to verify the pain‐reducing efficacy of virtual reality among burn patients undergoing dressing change or physical therapy. We searched MEDLINE (via PubMed), EMBASE (via OVID), and the Cochrane Central Register of Controlled Trials (via OVID) for relevant trials based on predetermined eligibility criteria from database establishment to February 2018. Two reviewers screened citations and extracted data independently. The quality of the included studies was evaluated according to the Cochrane Handbook, whereas statistical heterogeneity was assessed using chi‐square tests and I2 statistics. Review Manager 5.3 was used for statistical analysis. Thirteen randomized controlled trials with 362 patients who underwent 627 burn dressing change or physical therapy sessions were included. The additional use of virtual reality significantly reduced pain intensity, time spent thinking about pain, and unpleasantness, and was more fun compared with that of using analgesics alone. Virtual reality is an effective pain reduction measurement added to analgesics for burn patients undergoing dressing change or physical therapy. However, multicenter, parallel group design randomized controlled trials are still required.
Vehicle Detection Using Convolutional Neural Network for Autonomous Vehicles

This paper implements a region identification to automatically detect vehicles on the road using Convolutional Neural Network (CNN) for autonomous vehicles. The region identification is essential to ensure the autonomous vehicle can safely navigate without having collision with other vehicles. Existing works highlighted the problem of poor detection in autonomous vehicles (AV) during night scene and in bad weathers. This paper develops a technique to improve the detection of vehicles during night scene (poor lighting condition) and bad weathers using CNN approach. The dataset of 301 vehicles from KITTI Vision, Intercity Roads and Adverse Driving Scenarios (iROADS) and Matlab were used. The CNN was trained with 177 input images in the training part while 124 images were used in the testing part. The simulation results show that the detection accuracy has improved under various weathers. The detection accuracies are 94.3% during a sunny weather, 61.4% during night weather, 73.4% and 98.7% during a snowy weather. In conclusion, the CNN technique has shown a promising result in detecting vehicles during the night scene (poor lighting condition) and bad weathers.
An ultra-high affinity ligand of HIV-1 TAR reveals the RNA structure recognized by P-TEFb

Abstract The HIV-1 trans-activator protein Tat binds the trans-activation response element (TAR) to facilitate recruitment of the super elongation complex (SEC) to enhance transcription of the integrated pro-viral genome. The Tat–TAR interaction is critical for viral replication and the emergence of the virus from the latent state, therefore, inhibiting this interaction has long been pursued to discover new anti-viral or latency reversal agents. However, discovering active compounds that directly target RNA with high affinity and selectivity remains a significant challenge; limiting pre-clinical development. Here, we report the rational design of a macrocyclic peptide mimic of the arginine rich motif of Tat, which binds to TAR with low pM affinity and 100-fold selectivity against closely homologous RNAs. Despite these unprecedented binding properties, the new ligand (JB181) only moderately inhibits Tat-dependent reactivation in cells and recruitment of positive transcription elongation factor (P-TEFb) to TAR. The NMR structure of the JB181–TAR complex revealed that the ligand induces a structure in the TAR loop that closely mimics the P-TEFb/Tat1:57/AFF4/TAR complex. These results strongly suggest that high-affinity ligands which bind the UCU bulge are not likely to inhibit recruitment of the SEC and suggest that targeting of the TAR loop will be an essential feature of effective Tat inhibitors.
Bacterial flora associated with repeat breeding and uterine infections in dairy cows

The study was conducted on 51 uterine biopsy samples collected from 14 normal fertile and 37 repeat breeding cows for bacteriological examinations to find out the prevalence of bacterial flora and their role in repeat breeding syndrome. Presence of bacteria was detected in 23 samples (62.2%) repeat breeding cases in contrast to only 4 (28.6%) bacterial infections from normal fertile cows. About 60% of the microbial isolates were commonly recovered from repeat breeders as well as from normal fertile cows in varying proportions. Of the 37 suffered from repeat breeders, 23 samples (62.2%) yielded 54 bacterial isolates; where Staphylococcus was predominant 14 (37.8%), followed by Bacillus 13 (35.1%), E. coli 11 (29.7%), Pseudomonas 7 (18.9%) while Gram negative minute rod shaped bacteria was 9 (24.3%). The isolates of Pseudomonas and Gram negative minute rod shaped bacteria were obtained only from repeat breeder cows with mucopurulent uterine discharges. There was a positive correlation (r=0.94) between repeat breeders and bacterial infection of uterus. Antibiotic sensitivity in the present study showed that almost all types of bacterial isolates were found moderately and highly sensitive to amoxicillin, oxytetracycline and ciprofloxacin.
US Census Spatial and Demographic Data in R: The UScensus2000 Suite of Packages

The US Decennial Census is arguably the most important data set for social science research in the United States. The UScensus2000 suite of packages allows for convenient handling of the 2000 US Census spatial and demographic data. The goal of this article is to showcase the UScensus2000 suite of packages for R, to describe the data contained within these packages, and to demonstrate the helper functions provided for handling this data. The UScensus2000 suite is comprised of spatial and demographic data for the 50 states and Washington DC at four different geographic levels (block, block group, tract, and census designated place). The UScensus2000 suite also contains a number of functions for selecting and aggregating specific geographies or demographic information such as metropolitan statistical areas, counties, etc. These packages rely heavily on the spatial tools developed by bivand08, i.e., the sp and maptools packages. This article will provide the necessary background for working with this data set, helper functions, and finish with an applied spatial statistics example.
High Power High Efficiency 270–320 GHz Source Based on Discrete Schottky Diodes

A 300 GHz source based on discrete Schottky diodes technology is reported in this work. The high frequency part developed by ACST consists of two high power and high efficiency doublers, one at 135–160 GHz and a second one at 270–320 GHz. Both doublers feature a single chip per module and do not use any power combining techniques. The 150 GHz and 300 GHz doublers are able to handle more than 400 mW and 100 mW input power and provide more than 140 mW and 30 mW output power, respectively. This is the most powerful 300 GHz source reported based on discrete Schottky diodes at this freuuency range without using power combining.
Recommended nitrogen fertilization enhances soil carbon sequestration in China’s monsoonal temperate zone

China consumes more than one-third of the world’s nitrogen (N) fertilizer, and an increasing amount of N fertilizer has been applied over the past decades. Although N fertilization can increase the carbon sequestration potentials of cropland in China, the quantitative effects of different N fertilizer application levels on soil carbon changes have not been evaluated. Therefore, a 12-year cultivation experiment was conducted under three N fertilizer application levels (no N fertilizer input, the recommended N fertilizer input after soil testing, and the estimated additional fertilizer input) to estimate the effect of N addition on soil carbon changes in the root layer (0–80 cm) and non-root layer (80–200 cm) using a within-study meta-analysis method. The results showed significant declines in the soil inorganic carbon (SIC) in the root layers and significant growth in the SIC in the non-root layers under N fertilizer input. The soil organic carbon (SOC) in the root layers and the non-root layer significantly decreased under all the treatments. In addition, the recommended N fertilizer application level significantly increased the SOC and soil total carbon stocks compared with the future N fertilizer application level and no N input, while the future N fertilization significantly decreased the SIC and soil total carbon compared with no N input. The results suggest that N fertilization can rearrange the soil carbon distribution over the entire soil profile, and the recommended N fertilization rather than excess N input can increase the soil carbon stock, which suggests that the national soil testing program in China can improve the soil carbon sequestration potential.
Multi-Class Sentiment Analysis in Twitter: What if Classification is Not the Answer

With the rapid growth of online social media content, and the impact these have made on people’s behavior, many researchers have been interested in studying these media platforms. A major part of their work focused on sentiment analysis and opinion mining. These refer to the automatic identification of opinions of people toward specific topics by analyzing their posts and publications. Multi-class sentiment analysis, in particular, addresses the identification of the exact sentiment conveyed by the user rather than the overall sentiment polarity of his text message or post. That being the case, we introduce a task different from the conventional multi-class classification, which we run on a data set collected from Twitter. We refer to this task as “quantification. ” By the term “quantification,” we mean the identification of all the existing sentiments within an online post (i.e., tweet) instead of attributing a single sentiment label to it. For this sake, we propose an approach that automatically attributes different scores to each sentiment in a tweet, and selects the sentiments with the highest scores which we judge as conveyed in the text. To reach this target, we added to our previously introduced tool SENTA the necessary components to run and perform such a task. Throughout this work, we present the added components; we study the feasibility of quantification, and propose an approach to perform it on a data set made of tweets for 11 different sentiment classes. The data set was manually labeled and the results of the automatic analysis were checked against the human annotation. Our experiments show the feasibility of this task and reach an F1 score equal to 45.9%.
A Decentralized Marketplace Application on the Ethereum Blockchain

Modern centralized online marketplaces such as eBay offer an alternative option for consumers to both sell and purchase goods with relative ease. However, drawbacks to these marketplaces include the platform's ability to block merchants at their own whim, the fees paid to the platform when listing a product and when selling a product, and the lack of privacy of users' data. In this paper, we propose an application that remedies all three of these drawbacks through use of the Ethereum blockchain platform. The application was developed using the Truffle development framework. The application's functions were contained within an Ethereum smart contract, which was then migrated to the Ethereum network. The user's input was read through a web interface and sent to the Ethereum network via the web3.js API. Statistics about the application were gathered on the Rinkeby test network. The application was shown to have an average transaction runtime of 3.8 seconds, and an average gas consumption of 4.6 wei. Contract creation times for the application were shown to be less than a second. A cost analysis of the application was then conducted. The gas consumption of the transactions needed to both buy and sell a product was converted into US dollars, and the gas cost of the application was then compared to the cost to use an online auction marketplace such as eBay as well as an in-person auction house such as Sotheby's. The results showed that selling on the application is cheaper than existing online options as well as existing in-person options. These tests showed that our application was successful in addressing the drawbacks of current auction marketplaces.
Diagnosis and Management of Atopic Dermatitis: A Review

GENERAL PURPOSE: The purpose of this learning activity is to provide information about the diagnosis and management of atopic dermatitis (AD). TARGET AUDIENCE: This continuing education activity is intended for physicians, physician assistants, nurse practitioners, and nurses with an interest in skin and wound care. LEARNING OBJECTIVES/OUTCOMES: After completing this continuing education activity, you should be able to: 1. Recall the diagnostic process of AD. 2. Identify nonpharmacologic therapies for skin care in patients with AD. 3. Explain the pharmacologic management of AD. ABSTRACT Atopic dermatitis is a chronic, relapsing, intensely pruritic inflammatory skin disease that affects both children and adults. This article provides an overview of the epidemiology, clinical features, pathophysiology, complications, and specific investigations of atopic dermatitis. The current and novel therapies for the treatment of atopic dermatitis will be discussed.
In-NoC Circuits for Low-Latency Cache Coherence in Distributed Shared-Memory Architectures

Scalable communication and low latency memory accesses are the deciding factors for future manycore performance. An efficient hardware infrastructure is required, since raw performance must be balanced with area and power constraints. In distributed shared-memory (DSM) architectures, caches help in reducing costly remote accesses but must be kept coherent. To enable scalable coherence in manycore systems, the recently proposed region-based cache coherence defines configurable regions, i.e. cache coherent sub-sections of a manycore architecture. In this paper, a technique for supporting the regionbased cache coherence mechanism by using so called in-NoC circuits (INCs) in a hybrid networks-on-chip is proposed. These circuits are automatically established based on traffic monitoring and traffic analysis to connect nodes (i.e. routers) in the network to enable a shortcut for packets, reducing their latency. The INCs can be used by packets stemming from different sources and targeting different destinations in contrast to traditional end-toend circuits. Depending on the coherence region, our evaluations of several benchmarks show a latency reduction of up to 45% on average in a 4x4 mesh that further increases with the mesh size. The FPGA synthesis of a router from a scientific DSM architecture that was extended with the presented features shows additional costs of up to 31% more LUTs and 20% more Flip Flops.
Through-the-Multilayered Wall Imaging Using Passive Synthetic Aperture Radar

Most of the existing through-the-wall imaging (TWI) methods using synthetic aperture radar (SAR) tend to apply an active system. In this work, a novel, passive synthetic aperture radar (PSAR), termed TWI-PSAR, was proposed, to focus the image of multi targets behind single/multilayered wall. Incident angle and frequency were considered the parameters that influence TWI image directly. Zero incident angle PSAR, Z- PSAR, was exploited in TWI for enhanced target identification and feature extraction as well as wall effect mitigation. In scenarios where background measurement might not be available or wall parameters were unknown for compensation, Z-PSAR could be adopted. Moreover, to show the effectiveness of the proposed PSAR method in a real situation, sources of opportunity that are relatively wideband aligned in several directions were used to image targets behind the wall. Numerical results showed that PSAR could be an efficient scheme in through-the-wall imaging.
Randomized Controlled Trial of Exercise to Improve Walking Energetics in Older Adults

Abstract Background and Objectives Mobility limitation is common and has been linked to high energetic requirements of daily activities, including walking. The study objective was to determine whether two separate forms of exercise could reduce the energy cost of walking and secondary outcomes related to activity and participation domains among older adults with mobility limitation. Research Design and Methods Community-dwelling older adults with self-reported mobility limitation (n = 72) were randomized to 12 weeks of twice-weekly, group-based, instructor-led timing and coordination, aerobic walking, or stretching and relaxation (active control) programs. The primary outcome was the energy cost of walking (mL O2/kg/m), assessed by a 5-minute treadmill walking test (0.8 m/s). Secondary outcomes were fatigability, physical activity, endurance, physical function, and life-space. Baseline-adjusted ANCOVAs were used to determine mean differences between exercise and control groups at 12 and 24 weeks. Results Exercise session attendance was high: 86% for timing and coordination, 81% for aerobic walking, and 90% for stretching and relaxation. At 12 weeks, timing and coordination reduced the mean energy cost of walking by 15% versus stretching and relaxation (p = .008). Among those with high baseline cost, timing and coordination reduced mean energy cost by 20% versus stretching and relaxation (p = .055). Reductions were sustained at 24 weeks. Aerobic walking had no effect on the energy cost of walking at 12 or 24 weeks. At 12 weeks, there was a trend toward faster gait speed (by 0.1 m/s) in timing and coordination versus stretching and relaxation (p = .074). Fatigability, physical activity, endurance, physical function, and life-space did not change with timing and coordination or aerobic walking versus stretching and relaxation at 12 or 24 weeks. Discussion and Implications Twelve weeks of timing and coordination, but not aerobic walking, reduced the energy cost of walking among older adults with mobility limitation, particularly among those with high baseline energy cost; reductions in energy cost were sustained following training cessation. Timing and coordination also led to a trend toward faster gait speed.
Optical Biosensors for Label-Free Detection of Small Molecules

Label-free optical biosensors are an intriguing option for the analyses of many analytes, as they offer several advantages such as high sensitivity, direct and real-time measurement in addition to multiplexing capabilities. However, development of label-free optical biosensors for small molecules can be challenging as most of them are not naturally chromogenic or fluorescent, and in some cases, the sensor response is related to the size of the analyte. To overcome some of the limitations associated with the analysis of biologically, pharmacologically, or environmentally relevant compounds of low molecular weight, recent advances in the field have improved the detection of these analytes using outstanding methodology, instrumentation, recognition elements, or immobilization strategies. In this review, we aim to introduce some of the latest developments in the field of label-free optical biosensors with the focus on applications with novel innovations to overcome the challenges related to small molecule detection. Optical label-free methods with different transduction schemes, including evanescent wave and optical fiber sensors, surface plasmon resonance, surface-enhanced Raman spectroscopy, and interferometry, using various biorecognition elements, such as antibodies, aptamers, enzymes, and bioinspired molecularly imprinted polymers, are reviewed.
Selection of appropriate reference genes for RT-qPCR analysis in Propylea japonica (Coleoptera: Coccinellidae)

Reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) is a reliable technique commonly used in molecular biology to analyze RNA expression. The selection of suitable reference genes for data normalization is a precondition for credible measurements of gene expression levels using RT-qPCR. Propylea japonica is one of the most common pests of many crop systems throughout East Asia, and has often been used in the testing of non-target impacts during environmental risk assessments of genetically engineered plants. The present study assessed the suitability of nine frequently used reference genes for comparisons of P. japonica gene expression. Expression stability was compared across developmental stages, sex, a range of tissues, and following exposure to different temperatures. Data were analyzed using RefFinder, which integrated the results obtained using NormFinder, geNorm, BestKeeper, and the ΔCt method. This led to the identification of unique sets of reference genes for each experimental condition: ribosomal protein S18 (RPS18) and elongation factor 1 α (EF1A) for developmental stage comparisons, RPS18 and EF1A for sex comparisons, EF1A and ribosomal protein L4 for tissue comparisons, and RPS18 and EF1A for analyses of temperature-mediated effects. These reference genes will help to enhance the accuracy of RT-qPCR analyses of P. japonica gene expression. This work represents an initial move towards building a standardized system for RT-qPCR analysis of P. japonica, providing a basis for the ecological risk assessment of RNAi-based insect control products.