Miracle-dz/UniFAR-FTUs huggingface dataset:
BlueTrace: A privacy-preserving protocol for community-driven contact tracing across borders

TraceTogether is the first national deployment of a Bluetooth-based contact tracing system in the world. It was developed by Singapore’s Government Technology Agency and the Ministry of Health to help the country better respond to epidemics. Following its release, more than 50 governments have expressed interest in adopting or adapting Trace-Together for their countries. Responding to this interest, we are releasing an overview of BlueTrace , the privacy-preserving protocol that underpins TraceTo-gether, as well as OpenTrace , a reference implementation. OpenTrace comprises the source code for an iOS app, an Android app, a cloud-based backend, and baseline signal strength calibration data. This will be made available to the open source community at github.com/opentrace-community on 9 April 2020.
Ortho-aminoacetophenone repellency to birds : similarities to methyl anthranilate

Methyl anthranilate is an effective bird repellent at concentrations ≥1.0% (g/g). Ortho-aminoacetophenone (OAP) has an odor similar to that of methyl anthranilate and is chemically (structurally) similar. Coincidentally, OAP is present in the scent gland secretions of mustelid species that prey on birds. For these reasons, we chose to test the bird repellency of this material and 3 isomers to European starlings (Sturnus vulgaris). Ortho-aminoacetophenone was repellent at concentrations ≤0.01% in both choice and no-choice feeding tests. The other structural isomers (meta-, para-, alpha-) were less effective
From the Cradle to the Labor Market? The Effect of Birth Weight on Adult Outcomes

Lower birth weight babies have worse outcomes, both short-run in terms of one year mortality rates and longer run in terms of educational attainment and earnings. However, recent research has called into question whether birth weight itself is important or whether it simply reflects other hard-to-measure haracteristics. By applying within twin techniques using a unique dataset from Norway, we xamine both short-run and long-run outcomes for the same cohorts. We find that birth weight does matter; very small short-run fixed effect estimates can be misleading because longer-run effects on outcomes such as height, IQ, earnings, and education are significant and similar in magnitude to OLS estimates. Our estimates suggest that eliminating birth weight differences between socio-economic groups would have sizeable effects on the later outcomes of children from poorer families
Understanding Student Acceptance and Use of Chatbots in the United Kingdom Universities: A Structural Equation Modelling Approach

The purpose of this paper is to investigate the factors that may hinder or facilitate the acceptance and usage of chatbots by university students in higher education institutions (HEIs). For this study, the unified theory of acceptance and use of technology (UTAUT2) is adopted for this educational context. A quantitative survey-based approach was used to collect data from 431 undergraduate and computer science masters students at Brunel University London. The data were analysed using partial least squares - structural equation modelling (PLS-SEM) with SmartPLS3. The findings showed that three primary constructs, namely, performance expectancy, effort expectancy and habit significantly predicted students’ behavioural intention (BI) to use chatbot technology. Our results can guide policymakers in their attempts to explain and encourage the adoption and acceptance of innovative technologies, such as chatbots, by university students. To the best of our knowledge, this study is the first to investigate student acceptance and use of chatbots by university students using UTAUT2. Moreover, the present study will serve as the foundation for the design of features aimed at promoting chatbot acceptance and the enhancement of student engagement and performance.
Selective utilization of fatty acids in rainbow trout (Oncorhynchus mykiss Walbaum) red muscle mitochondria

This study was undertaken to establish whether fatty acids are generally oxidized at the same rate or if a pattern of oxidation rates exists to protect certain fatty acids from degradation for ATP formation. Beta-oxidation was studied in red muscle mitochondria of 10 major fatty acids that are acquired in the diet and occur in the fat depots of rainbow trout (Oncorhynchus mykiss Walbaum). The mitochondria were isolated by fractional centrifugation and the fatty acids were added as coenzyme A esters in the presence of carnitine. The fatty acids could be separated into roughly three groups in relation to their oxidation rates. Two fatty acids (14:0 and 16:0) were oxidized as rapidly as pyruvate. Another six acids (16:1 n − 7, 18:0, 18:1 n − 9, 20:1 n − 9, 22:1 n − 9 and 22:6 n − 3) were oxidized at about three-quarters to one-half the rate of pyruvate. The two essential fatty acids (18:2 n − 6 and 18:3 n − 3) had a slow oxidation rate, about one-fifth of that of pyruvate. The liver mitochondria from rainbow.
Evidence quality estimation using selected machine learning approaches

Evidence Based Medicine, is a practice, where medical actions/decisions are undertaken on the basis of best available evidence-based recommendations. In this context, we propose a system for automatic grading of evidence.Evidence grading is approached as a multi-label classification task. Here, classes represent grades, in a widely used Strength of Recommendation Taxonomy (SORT). Numerous ensemble methods are experimented with. It was found that the most successful one used Support Vector Classifiers, trained on multiple high level features, results of which are used to train a Random Forest Classifier. The best achieved accuracy score was 75.41%, which is a significant improvement over the baseline of 48%, achieved by classifying all instances as the majority class. It was also found that the most important predictor is the publication type of articles comprising the body of evidence. The designed system is tuned for use with medical publications and SORT. However, due to it’s generality, it can easily be used with other evidence grading systems.
Identification of potential treatments for COVID-19 through artificial intelligence-enabled phenomic analysis of human cells infected with SARS-CoV-2

To identify potential therapeutic stop-gaps for SARS-CoV-2, we evaluated a library of 1,670 approved and reference compounds in an unbiased, cellular image-based screen for their ability to suppress the broad impacts of the SARS-CoV-2 virus on phenomic profiles of human renal cortical epithelial cells using deep learning. In our assay, remdesivir is the only antiviral tested with strong efficacy, neither chloroquine nor hydroxychloroquine have any beneficial effect in this human cell model, and a small number of compounds not currently being pursued clinically for SARS-CoV-2 have efficacy. We observed weak but beneficial class effects of β-blockers, mTOR/PI3K inhibitors and Vitamin D analogues and a mild amplification of the viral phenotype with β-agonists.
Investigations on Winding Modeling Techniques for Electrical Stress Analysis in VSI-Fed Traction Electric Machines

Traction motors are exposed to high dv/dt pulses when driven by a voltage source inverter (VSI). Due to this type of voltage excitation, machine’s winding insulation system experiences additional dielectric stress, which can result in premature insulation failure in the machine windings. To analyze this electrical stress, various modeling techniques have been presented to model the machine windings, which can predict the voltage and current distributions among coils and turns of the windings. In this paper, different modeling techniques are investigated. Comparative analysis and results from case studies of the selected modeling techniques are presented.
Respiration modulates oscillatory neural network activity at rest

Despite recent advances in understanding how respiration affects neural signalling to influence perception, cognition, and behaviour, it is yet unclear to what extent breathing modulates brain oscillations at rest. We acquired respiration and resting state magnetoencephalography (MEG) data from human participants to investigate if, where, and how respiration cyclically modulates oscillatory amplitudes (2 – 150 Hz). Using measures of phase-amplitude coupling, we show respiration-modulated brain oscillations (RMBOs) across all major frequency bands. Sources of these modulations spanned a widespread network of cortical and subcortical brain areas with distinct spectro-temporal modulation profiles. Globally, high-frequency gamma modulation increased with distance to the head centre, whereas delta and theta modulation decreased with height in the sagittal plane. Overall, we provide the first comprehensive mapping of RMBOs across the entire brain, highlighting respiration-brain coupling as a fundamental mechanism to shape neural processing within canonical resting-state and respiratory control networks.
Extending Human Vision to Infrared and Ultraviolet Light: A Study Using Micro-Particles and Fluorescent Molecules

In this study, rare earth doped infrared (IR) to visible, up-converting particles along-with efficient ultraviolet (UV) to visible fluorescent molecules were imbedded in proteins and were used as a mean for increasing the human vision range to infrared and ultraviolet wavelengths. Stilbene-420 fluorescent molecules which convert near UV light to blue light, were chosen for the strong overlap of their fluorescence emission with the sensitivity region of blue cone cells and for the ability of blue light to increase the regeneration of bleached visual pigments. Our data show that the up-conversion efficiency of the IR up-converting particles and blue fluorescing molecules efficiencies remained unchanged when these material are imbedded in proteins compared to their efficiencies in water solutions. Addition of up-converting particles to rod visual cells resulted in the bleaching of the visual pigments, rods, when irradiated with infrared light (980 nm) whereas no bleaching was observed, under the same conditions, without the presence of up-converting particles. This suggests that the up-converted green light induced visual process in the rod visual pigments. In addition, we describe the design and present data of a novel optical device, which can be used as eye glasses, utilizing up-converting particles that allows the wearer to see rather intense infrared light.
Development patterns in young conifer-hardwood forests of interior Alaska

The age structure and growth patterns of 53 young conifer-hardwood stands on upland, south-facing sites of interior Alaska were analyzed to determine the length of time for stand establishment after disturbance, the composition of early-successional stands compared to existing stands, and the potential for late-successional stands dominated by conifers. Mixed stands of Picea glauca, Populus tremuloides and Betula papyrifera represented five plant community types and developed as single cohorts after stand-replacement fires. In the Populus tremuloides/Arctostaphylos uva-ursi and Populus tremuloides/Shepherdia canadensis community types, hardwoods established rapidly and Picea glauca established slowly. In contrast, stands in the Betula papyrifera-Populus tremuloides/Viburnum edule, Betula papyrifera-Populus tremuloides/Alnus crispa, and Picea glauca-Betula papyrifera/Hylocomium splendens community types generally developed as a result of rapid, concurrent establishment of conifers and hardwoods. These single-cohort, mixed species development patterns are not consistent with continual establishment of conifers and are likely the result of unique life-history traits and frequent stand-replacement fires.
Anchor-Based Segmentation of Periventricular White Matter for Neonatal HIE

The segmentation and quantitative features of periventricular white matter injury in magnetic resonance imaging are helpful for determining an accurate diagnosis of neonatal hypoxia ischemia encephalopathy (HIE) in clinical practice, but they are tedious tasks. In this paper, we present an interactive segmentation method for clinical magnetic resonance imaging (MRI) using sample estimation at the subvoxel level to establish a quantitative diagnosis. The coarse-grained voxels in clinical MRI are divided into subvoxels, and the intensities of subvoxels are adjusted using gradient adaptive filtering. Because the cerebrospinal fluid is more obvious in grayscale than the white matter and gray matter on T1-weighted images (T1WI), T2-weighted images (T2WI) and fluid-attenuated inversion recovery (FLAIR) images, and its population variance follows a Chi-square distribution, we segment the periventricular region as an anchor by estimating the parameters of the selected data and expand the anchor to obtain periventricular white matter of various widths. After aligning the segmented periventricular white matter in various modalities, we compute the radiomics features of regions of interest for the quantitative diagnosis of HIE. Current clinical practice confirms that our approach is effective and satisfies the clinical diagnostic requirements for neonatal HIE.
Blood-based Markers in the Prognostic Prediction of Esophagogastric Junction Cancer

Esophagogastric junction cancer poses a great threat to human beings both in western countries and East Asia, especially in China and Japan, and its incidence has increased during recent decades. The 5-year survival rate of esophagogastric junction cancer is quite poor compared with that of other gastric cancer sites. Until now, the traditional TNM staging system has been widely used in clinical practice for prognosis. However, the TNM system is based on pathology after surgical resection or radiology using CT and MRI, not on blood markers. Evidently, some research has been reported concentrated on the prognostic value of blood-based markers with the character of non-invasive and non-radioactive in EJA. Hematologic, biochemical and coagulation parameters could be obtained from clinical data and utilized to analyze their prognostic values. Tumor-associated antigens, microRNAs and circulating tumor cells have also been reported in EJC prognosis. In this article, we review research focused on blood-based markers to evaluate their prognostic value in esophagogastric junction cancer, especially its main subtype adenocarcinoma.
Impact of Diet Modification on Serum Ferritin Level in Thalassemia Children

Background and Aim: Blood transfusion is the main treatment for people who have moderate or severe thalassemias. The main side effect of transfusion therapy is that the patient develops iron overload, which lead to serious damage to the internal organs. Many foods can play an important role in decreasing iron absorption from the intestine and that could improve the prognosis of these patients. The aim of our study is to detect the effect of diet adjustment in thalassemia children, to a more ironexecrating and less iron-absorption diet, on their level of serum ferritin. Patients and Methods: In a randomized case control study, 36 thalassemia patients presented to the hematology/oncology center at the Maternity and children Hospital (MCH) in Almadinah Almounourah, KSA in the period from January 2014 to July 2014 were observed prospectively for their serum ferritin level. The cases were asked to follow a diet that limits iron absorption and increases iron excretion. Results: Serum ferritin level is significantly decreased in cases after 6 months of diet iron restriction more than in controls (p value =0.03). Conclusions: Restriction of foods that contain iron and increase intake of foods that execrate iron from body can significantly decrease serum ferritin level in thalassemia children. Recommendations: According to our results, control of diet and following food regimens that can minimize iron absorption and maximize iron execration are of great benefit for thalassemia children and can act as an adjuvant for drug chelation therapy.
Circadian Activity Rhythm of the Foragers of a Eusocial Bee (Scaptotrigona aff depilis, Hymenoptera, Apidae, Meliponinae) outside the Nest

In all bee colonies of the Meliponinae subfamily, activity inside the nest is temporally organized around the oviposition by the queen, assisted by nurse bees. This class is constituted by young bees that remain inside the nest. In a colony of Scaptotrigona aff depilis, the oviposition cycle occurs in a 3-hour period. The foragers are older bees that collect food for the colony in the field. Other tasks in the nest are performed by workers of ages intermediate between nurses and foragers. With the aim of studying activity rhythms, foragers were kept under constant light, with food constantly available and no flight restriction. The results showed that, although inside the nest the prevailing period is 3 hours, the activity of the foragers is a circadian rhythm, synchronized by the light/dark cycle and probably influenced by other environmental cycles as temperature and the availability of food sources.
Improved Strategies for BeiDou Ultrarapid Satellites’ Clock Bias Prediction Using BDS-2 and BDS-3 Integrated Processing

GNSS ultrarapid clock biases are key inputs of rapid high-accuracy applications, especially for its prediction parts. With the fast development of the BeiDou system (BDS), the system performances are mainly represented by orbit and clock products. However, it is suggested that the BDS-predicted clock biases cannot meet the requirement of real-time or near real-time services. In this research, the BDS satellite-predicted ultrarapid clock bias products are optimized with three methods, namely, one-step strategy, intersatellite correlation, and variogram model, using the combined estimation of BDS-2 and BDS-3 satellites. Firstly, considering the traditional two-step strategy for modelling clock bias prediction, we take all terms (including trend and periodic terms) into one-step solution of model estimation based on the sparse modelling in machine learning. Secondly, because of the much more stable on-board atomic clock of BDS-3 satellites, the intersatellite correlations between BDS-2 and BDS-3 are utilized to enhance the solution of model coefficients. Thirdly, to further improve the model, the temporal correlations in model residuals are used to reconstruct the stochastic function obtained by variogram. In addition, to verify the proposed improved strategies, 12 schemes of BDS clock bias prediction experiments are designed and analyzed with different conditions. According to the results of predicted clock biases, it is indicted that (1) the stability of BDS-3 on-board clocks is more optimal compared with BDS-2, which can be used to strengthen the solution of the clock bias prediction model; (2) the one-step estimation of the clock bias model by sparse modelling can slightly increase the accuracy of prediction results; (3) both BDS-2- and BDS-3-predicted clock biases benefited each other by inserting the intersatellite correlations into the weight matrix, in which the accuracy of 18-hour period with one-step strategy can be improved by 28.6% and 27.2% for BDS-2 and BDS-3, respectively; and (4) after the introduction of the variogram model in updating the weight matrix, the clock bias prediction model is further corrected by 8.0% and 11.1% for BDS-2 and BDS-3. In summary, improved strategies for BDS ultrarapid satellites’ clock bias prediction using BDS-2 and BDS-3 integrated processing are meaningful for the current BDS ultrarapid satellites’ clock bias prediction products.
Mobile Information Security Awareness Among Students in Higher Education : An Exploratory Study

Higher education students live their lives through their mobile technology devices. The availability of broadband networks and the associated connectivity capabilities of modern mobile devices as well as the numerous mobile apps on offer enable students to be constantly connected. Consequently, large amounts of sensitive information is being stored and processed through a variety of mobile devices, making the individual students and their higher education institutions easy targets for cyberattacks. This study assesses factors that impact mobile security awareness of students (N=397) at a higher education institution in South Africa. It proposes a conceptual model of mobile information security awareness, which draws upon a combination of constructs from the Knowledge-Attitude-Behavior (KAB) model and the Theory of Planned Behavior (TPB) to measure mobile information security awareness. The results show a significant relationship between students’ knowledge and behavioral intentions about information security threats and their levels of security awareness. The study also shows the existence of the gap between knowing about security and the lack of concomitant safety behaviors. The study concludes with a discussion of the practical implications of the research outcomes.
Dystrophy in Determining Midge Community Composition in Boreal Lakes

Abstract Brown-water dystrophic lakes have several limnological characteristics that clearly separate them from clear-water oligotrophic and murky eutrophic lakes. In this study, I examined the sedimentary midge (Nematocera) assemblages from 30 shallow boreal lakes of varying humic status to test the influence of dystrophy on community composition. The results indicate differing community assemblages between oligohumic and humic lakes. Several taxa were restricted to clear-water lakes, whereas dystrophic lakes also had their characteristic taxa, which were rare or absent in the clear-water lakes. The most common and abundant nematocerans having statistically significant indicator values for dystrophy were chironomids Zalutschia zalutschicola-type, Tanytarsus mendax-type, and Cladotanytarsus mancus-type, together with the phantom midge Chaoborus flavicans. These results indicate that the level of dystrophy plays a significant role in determining midge distribution in boreal lakes. Therefore, consideration of differences in humic conditions is crucial to contemporary midgebased environmental assessments and long-term paleolimnological investigations, because temporal changes in the humic state may have occurred.
High speed and reliable Sensing Scheme with Three Voltages for STT-MRAM

This paper proposes a novel voltage sensing scheme in order to improve reliability and reduce read delay for spin transfer torque magnetic random access memory (STT-MRAM). This scheme utilizes two reference voltages to form a voltage difference from read voltage. The states of magnetic tunnel junction (MTJ) cells are then accurately read by three-input voltage sense amplifier. Simulation results using 28nm Complementary Metal Oxide Semiconductor (CMOS) technology show that read access time can be reduced to 0.7ns with 100mV voltage difference at 1V supply voltage. Read access time is reduced by 83.5% and 53.3% compared with time-based sensing (TBS) scheme and strong positive feedback (SPF) scheme. In addition, high reliability can be achieved because sensing margin increases with discharge of bit lines in a certain time.
Shoe Detection Using SSD-MobileNet Architecture

Falls are a global health issue that especially affects to the elderly. In our previous research, we used a millimeter wave radar to estimate the position of the feet for fall risk assessment of cane users. Radar sensors have a good accuracy, however, due to its low resolution, it is difficult to know if the radar is really tracking the position of the feet or of any other object. In this research, we present a shoe image detector using SSD-MobileNet architecture that could be used in combination with the radar to accurately track the position of the feet. The results show that the proposed detector could correctly recognize the position of the shoes in an image.