Miracle-dz/UniFAR-FTUs huggingface dataset:
THE INFLUENCE OF TRAFFIC CALMING ON EMERGENCY RESPONSE TIMES

Quantitative data are presented that can be used in the determination of the impacts of one or more traffic calming devices on fire response time along a given emergency response route. Information necessary in making a complete assessment of these impacts include: types of fire vehicles responding to emergencies; desirable and appropriate speed of fire vehicles at each of the calming devices located along the response route; geographical area that will be affected by any increase in delay to response times; use of this route by fire vehicles given the likely demand for emergency services; and the availability of good alternative routes. Language: en
A 0.086-mm$^2$ 12.7-pJ/SOP 64k-Synapse 256-Neuron Online-Learning Digital Spiking Neuromorphic Processor in 28-nm CMOS

Shifting computing architectures from von Neumann to event-based spiking neural networks (SNNs) uncovers new opportunities for low-power processing of sensory data in applications such as vision or sensorimotor control. Exploring roads toward cognitive SNNs requires the design of compact, low-power and versatile experimentation platforms with the key requirement of online learning in order to adapt and learn new features in uncontrolled environments. However, embedding online learning in SNNs is currently hindered by high incurred complexity and area overheads. In this paper, we present ODIN, a 0.086-mm<inline-formula><tex-math notation="LaTeX">$^2$</tex-math></inline-formula> 64k-synapse 256-neuron online-learning digital spiking neuromorphic processor in 28-nm FDSOI CMOS achieving a minimum energy per synaptic operation (SOP) of 12.7 pJ. It leverages an efficient implementation of the spike-driven synaptic plasticity (SDSP) learning rule for high-density embedded online learning with only 0.68 <inline-formula><tex-math notation="LaTeX">$\mu$</tex-math></inline-formula>m<inline-formula><tex-math notation="LaTeX">$^2$</tex-math></inline-formula> per 4-bit synapse. Neurons can be independently configured as a standard leaky integrate-and-fire model or as a custom phenomenological model that emulates the 20 Izhikevich behaviors found in biological spiking neurons. Using a single presentation of 6k 16 × 16 MNIST training images to a single-layer fully-connected 10-neuron network with on-chip SDSP-based learning, ODIN achieves a classification accuracy of 84.5%, while consuming only 15 nJ/inference at 0.55 V using rank order coding. ODIN thus enables further developments toward cognitive neuromorphic devices for low-power, adaptive and low-cost processing.
“Frozen Up Like an Ice Cube!”: The Influence of Situated Learning on Pre-Service Teachers' Cultural and Linguistic Awareness

The overall goal of this study was to explore the influence of situated learning experiences on pre-service teachers' perceptions and understandings of their future Arab students. This study investigated in part the interaction between culturally diverse families and pre-service teachers. It also explored changes in pre-service teachers’ attitudes and knowledge, their perceived applications of the situated experience to their future teaching, and the families’ reactions to this experience. Twelve Arab families volunteered to host 25 pre-service teachers as participants of this study. Results showed that the situated learning experience helped the pre-service teachers develop their cultural knowledge as well as learn about Arab families, Arab culture, and their future classrooms. The study concluded that the experience helped the pre-service teachers gain new knowledge, positive attitudes, and some ideas for their future diverse classrooms. It offered a great opportunity for families to explore how important it is to meet with teachers and it also empowered pre-service teachers with some powerful authentic experiences including meeting the family, sharing their knowledge, exploring their understandings, and discussing and comparing their knowledge with each other.
Aerobic exercise improves hippocampal blood flow for hypertensive APOE4 carriers

Background: Evidence increasingly suggests cerebrovascular dysfunction plays an early and important role in the pathogenesis of Alzheimer's disease (AD). Studies have shown the strongest known genetic risk factor for sporadic AD, Apolipoprotein E4 (APOE4), may act synergistically with vascular risk factors to promote dementia development. Aerobic exercise may attenuate cognitive decline at least partially through improvements in cerebral blood flow. Therefore, exercise interventions that improve vascular health may be particularly beneficial for APOE4 carriers. Objectives: To test the hypothesis that exercise would more effectively increase hippocampal blood flow (HBF) in hypertensive APOE4 carriers than non carriers, we performed an analysis of arterial spin labeling MRI data (ASL MRI) from a randomized controlled trial (secondary outcome). Additionally, we tested the hypothesis that changes in systolic blood pressure ({Delta}SBP) would be more negatively associated with {Delta}HBF for APOE4 carriers than non carriers. Methods: We assigned cognitively normal adults (65 to 87 years) to a 52-week aerobic exercise intervention or education only. Genotyping was performed by Taqman SNP allelic discrimination assay. ASL MRI measured HBF before and after the 52 week intervention. We selected participants with hypertension at enrollment (n {equiv} 44), defined as SBP [≥] 130mmHg or diastolic blood pressure (DBP) [≥] 80mmHg. Results: A two way ANCOVA showed a significant interaction between APOE4 carrier status and treatment group on change in HBF ({Delta}HBF) over the 52 weeks, controlling for age and sex (p = 0.040). For APOE4 carriers, {Delta}HBF was significantly (p = 0.006) higher for participants who underwent the exercise intervention (4.09 mL/100g/min) than for the control group (-2.08 mL/100g/min). There was no difference in {Delta}HBF between the control (-0.32 mL/100g/min) and exercise (-0.54 mL/100g/min) intervention groups for APOE4 non carriers (p = 0.918). Additionally, a multiple linear regression showed a significant interaction between {Delta}SBP and APOE4 carrier status on {Delta}HBF (p = 0.035), with a reduction in SBP associated with an increase in HBF for APOE4 carriers only. Conclusions: Aerobic exercise significantly improved HBF for hypertensive APOE4 carriers only. Additionally, only APOE4 carriers exhibited an inverse relationship between {Delta}SBP and {Delta}HBF. This suggests exercise interventions, particularly those that lower SBP, may be beneficial for individuals at highest genetic risk of AD.
Reproductive Maternal and Newborn Health providers assessment of facility preparedness and its Determinants during the COVID-19 pandemic in Lagos, Nigeria

The global COVID-19 pandemic is predicted to compromise the achievement of global reproductive, maternal and newborn health (RMNH) targets. The objective of this study was to determine the health facility (HF) preparedness for RMNH service delivery during the outbreak from the perspective of RMNH providers and to determine what factors significantly predict this. An anonymous cross-sectional online survey of RMNH providers was conducted from 1st to 21st July 2020 in Lagos state Nigeria. We conducted a descriptive and ordinal regression analysis, with RMNH worker perception of HF preparedness for RMNH service delivery during the outbreak as the dependent variable. Two hundred and fifty-six RMNH workers participated, 35.2% reported that RMNH services were unavailable at some time since March 2020, 39% felt moderate or extreme work-related burnout, 84% were moderately or extremely concerned about the availability of PPE and related guidelines, and only 11.7% were extremely satisfied with the preparedness of their HFs. Our final model was a statistically significant predictor of RMNH worker perception of HF preparedness explaining 54.7% of the variation in the outcome variable. A one-unit increase in the level of satisfaction with the communication from HF management and level of concern about the availability of PPE and COVID-19 guidelines would increase the odds of observing a higher category of satisfaction with HF COVID-19 preparedness (OR 0.79-2.92, p<0.001 and 0.02-0.15 p<0.001 respectively). Adequate support of RMNH providers particularly provision of PPE and guidelines, appropriate communications about COVID-19 should be prioritised as part of health system preparedness.
FeverIQ - A Privacy-Preserving COVID-19 SymptomTracker with 3.6 Million Reports

Population-scale COVID-19 management benefits from timely and honest information from billions of people. Here, we provide a first report on the FeverIQ symptom tracker, a global effort to collect symptom and test data which has received more than 3.6 million submissions. Unlike other trackers, FeverIQ uses secure multiparty computation (SMC) to cryptographically guarantee user privacy while providing insights to scientists and public health efforts. We performed basic integrity checks of the FeverIQ dataset, such as by comparing it to other publicly released data. We then trained a linear classifier on diagnosis scores which were computed securely, without unprotected symptom data ever leaving a user's phone or computer. FeverIQ is currently the world's largest application of SMC in a health context, demonstrating the practicality of privacy-preserving analytics for population-scale digital health interventions.
Almost sure contraction for diffusions on $\mathbb R^d$. Application to generalised Langevin diffusions

In the case of diffusions on $\mathbb R^d$ with constant diffusion matrix, without assuming reversibility nor hypoellipticity, we prove that the contractivity of the deterministic drift is equivalent to the constant rate contraction of Wasserstein distances $\mathcal W_p$, $p\in[1,\infty]$. It also implies concentration inequalities for ergodic means of the process. Such a contractivity property is then established for some generalised Langevin diffusions when the potential is convex with bounded Hessian and the friction is sufficiently high. This extends previous known results for the usual (kinetic) Langevin diffusion. ----- On montre que, dans le cas des diffusions sur $\mathbb R^d$ de matrice de diffusion constante, sans hypothese de reversibilite ou meme d'hypoellipticite, la contractivite de la derive deterministe est equivalente a la contraction a taux constant des distances de Wasserstein $\mathcal W_p$, $p\in[1,\infty]$. Elle implique egalement des inegalites de concentration pour les moyennes ergodiques du processus. On etudie une telle contractivite pour les diffusions de Langevin generalisees dans des cas ou le potentiel est convexe et de hessienne bornee, et la friction est suffisamment forte. Ceci etend les resultats similaires connus pour la diffusion de Langevin usuelle.
EFFECTS OF CORPORATE GOVERNANCE ON VALUE RELEVANCE OF ACCOUNTING INFORMATION OF LISTED MANUFACTURING FIRMS IN BANGLADESH

This paper examines the effects of corporate governance mechanisms, namely, the board of directors’ size and board of directors' independence on the value relevance of accounting information. Value­relevance is measured by the adjusted R derived from a regression of stock price on EPS, BVPS and CFPS using price model. The study sample included 71 manufacturing companies listed with Dhaka Stock Exchange (DSE) in Bangladesh within the period 2000­2017. The results of this study showed that CFPS is value relevant for companies having a larger board of director’s size, while this factor has no significant impact on the value relevance of EPS and CFPS. The results also showed that the value relevance of EPS and BVPS relating to the share price is value relevant for companies to comply with independence directors' requirements, while this factor has no significant impact on the value relevance of cash flows. In general, regression results show that DSE listed manufacturing firms with a strong governance structure exhibit higher value­ relevance of accounting information. This paper presents the ability of valuation theory/model to interact with other theories by including the effect of corporate governance mechanisms on the accounting information value relevance. The findings of this study might present evidence that can serve the educational institutions in their courses and provide a guideline to investors, managers and financial analysts to better summarize the firm value. This research also creates windows for future studies in this direction for other sectors.
Determination of the Concentration of 40K of Mudstone in Northern Iraq by Using Gamma Ray Spectroscopy and Flame Photometry Technique

The study of natural radionuclide materials is important to assess the health hazards on human being and one of these materials is 40 K which is present in soil and different types of stones. This study is performed to assess the K concentration in mudstones in the north of Iraq by (flame photometry and γ-ray spectroscopy) and to compare between these two techniques in measuring its level. So the activity of potassium was measured by these methods, and their results were compared with the results of other studies. The results show that the concentration of K ranges from 284.3 Bq/kg to 2481.2 Bq/kg using γ-ray spectroscopy and 511.7 Bq/kg to 3623.6 Bq/kg using flame photometer technique and these results were comparable with the upper level of the world mean specific concentration of K and cause no health hazard. The results obtained by the two methods were also, compared using T-test and P-value and they show no statistical significant difference.
MATERNAL SERUM DEHYDROEPIANDROSTERONE SULFATE LEVELS AND SUCCESSFUL LABOR INDUCTION

To evaluate the maternal serum dehydroepiandrosterone sulfate level as a factor associated with the outcome of labor induction. Venous blood was collected from 45 women at the initiation of labor induction. Pregnancies complicated by maternal corticosteroid use, antepartum chorioamnionitis, or cesarean delivery for indications other than arrest disorders, were excluded from analysis. In 42 women meeting inclusion criteria, induction followed established protocol. Serum dehydroepiandrosterone sulfate levels were measured by radioimmunoassay and correlated with the outcome of each induction attempt. A successful result was defined as progression to active labor. The welch approximate t-test, Mann-Whitney test, Fisher exact test, simple regression, and multiple regression were used for statistical analysis, with p<0.05 considered to be significant. The mean (±standard error) dehydroepiandrosterone sulfate level was higher in women who progressed to active labor (n=25) than in those with unsuccessful attempts (n=17), (48.63±6.53 μg/dl versus 26.86 ± 5.17 mg/dl, respectively; p= 0.03). Compared with women with dehydroepiandrosterone sulfate levels above 60 μg/dl, women with lower levels had an unsuccessful induction odds ratio (OR) of 6.92 (95% confidence interval 1.74, 32.52, p= 0.01). The OR increased as dehydroepiandrosterone sulfate levels decreased. Dehydroepiandrosterone sulfate may be an important factor in successful labor induction. Acta Medica Iranica, 41(2): 91-93; 2003
Multivariate Adaptive Splines for Analysis of Longitudinal Data

Abstract An essential feature of longitudinal data is the existence of autocorrelation among the observations from the same unit or subject. Two-stage random-effects linear models are commonly used to analyze longitudinal data. These models are not flexible enough, however, for exploring the underlying data structures and, especially, for describing time trends. Semi-parametric models have been proposed recently to accommodate general time trends. But these semi-parametric models do not provide a convenient way to explore interactions among time and other covariates although such interactions exist in many applications. Moreover, semi-parametric models require specifying the design matrix of the covariates (time excluded). We propose nonparametric models to resolve these issues. To fit nonparametric models, we use the novel technique of the multivariate adaptive regression splines for the estimation of mean curve and then apply an EM-like iterative procedure for covariance estimation. After giving a gener.
Seasonal dependence of the Earth's radiation belt: new insight

Long-term variations in the relativistic (∼MeV) electrons in the Earth’s radiation belt are explored to study seasonal features of the electrons. An L-shell dependence of the seasonal variations in the electrons is reported for the first time. A clear ∼ 6 month periodicity, representing one/two peaks per year, is identified for 1.5–6.0 MeV electron fluxes in the L shells between∼ 3.0 and∼ 5.0. The relativistic electron flux variation is strongest during solar cycle descending to minimum phases, with weaker/no variations during solar maximum. If two peaks per year occur, they are largely asymmetric in amplitude. The peaks essentially do not have an equinoctial dependence. Sometimes the peaks are shifted to solstices, and sometimes only one annual peak is observed. No such seasonal features are prominent for L < 3.0 and L > 5.0. The results imply varying solar/interplanetary drivers of the radiation belt electrons at different L shells. This has a potential impact on the modeling of the space environment. Plausible solar drivers are discussed.
In vitro Assay of the Glycosyltransferase Activity of a Heterologously Expressed Plant Protein

[Abstract] Glycosyltransferases are carbohydrate active enzymes containing catalytic modules involved in catalysing the biosynthesis of glycosidic bonds in oligoand polysaccharides and glycoconjugates. One of the most comprehensive collections of Carbohydrate Active enZYmes is the CAZy database (http://www.cazy.org) comprising 120,000 glycosyltransferases allocated to 96 families based mainly on sequence homologies of their conserved and catalytically active domains (Cantarel et al., 2009). Interestingly, the glycosyltransferase activities of only about 1.6% of these proteins have been experimentally characterized (Lombard et al., 2014). In recent years, membrane-bound glycosyltransferases of a number of families have been shown to play a key role in the biosynthesis of plant cell-wall polysaccharides (Doblin et al., 2010; Scheller and Ulvskov, 2010; Driouich et al., 2012). They catalyze the transfer of glycosyl residues from donor nucleotide sugars to acceptors, forming the glycosidic bonds between adjacent glycosyl residues. Family 34 contains glycosyltransferases that have been shown to be involved in the biosynthesis of xyloglucans and transfer xylosyl residues to (1→4)-β-glucan chains (Keegstra and Cavalier, 2011). Our previous work suggests that Pinus radiata protein PrGT34B is a xyloglucan (1→6)-αxylosyltransferase (Ade et al., 2014). Here, we describe a procedure for determining the xylosyltransferase activity of PrGT34B in vitro. We measured the transfer of xylose from the donor substrate UDP-xylose to different cello-oligosaccharide acceptor substrates under controlled reaction conditions. The assays include quantification of radioactively labeled reaction products and their identification by mass spectrometry. We also describe the purification, identification and quantification of the heterologously expressed recombinant protein PrGT34B in preparation for its use in the assays. This procedure may be applied to a wide range of glycosyltransferases in many different plant species.
Influence of Unequal Catchability on Population Estimates Using the Lincoln Index and the Removal Method Applied to Electro-Fishing

The accuracy of the removal method was tested using two types of pulsing DC electro-fishing gear on juvenile trout populations of known size. The experiments resulted in underestimations ranging between 11.1 and 22.0% of the total population size after 4 removal fishings. Marking experiments revealed unequal catchability among individuals, partly, at least, explaining the observed underestimations. To clarify the effect of unequal catchability, the capture-recapture and removal methods, applying the Lincoln Index and Moran's estimator, were tested by Monte Carlo simulation for various beta distributed catch probabilities. All simulations yielded considerable negative bias, proportional to the population size and rapidly increasing with a decreasing mean and an increasing standard deviation of the catch probability distribution.
Studies on the Antimicrobial Activity of Streptomyces sp. Isolated from Jazan

Antimicrobial activity of Streptomyces sp. (J12) isolated from soil sample collected from Jazan was studied. The isolate was classified according to the color of its mature sporulated aerial mycelia. It showed antimicrobial activities on solid and liquid media against some Gram positive (Bacillus subtilis and Staphylococcus aureus), Gram negative bacteria (Escherichia coli and Salmonella typhi), as well as fungi (Fusarium oxysporum f. sp. melongenae, Rhizoctonia solani and Candida albicans). Results showed that oat meal, starch casein and Sabouraud media improved antibiotic biosyn- thesis more than yeast malt extract medium. Biosynthesis of anti- biotics by the species under agitated culture conditions was decreased. The influence of different cultural conditions on antibiotic biosyn- thesis by Streptomyces J12 was studied. It showed that the highest antimicrob-ial activities were obtained after 6 days of growth at pH 7.2 and a medium composition of 10g/l starch as the sole carbon source, 2.5g/l of potassium nitrate as a nitrogen source and 0.3g/l casein.
Master ’ s Degree in Biomedical Engineering Machine Learning Approaches for Embedded Real-Time Gesture Recognition

Gesture recognition is a research topic that is gaining more and more popularity, especially in recent years, thanks to technological advances in embedded devices and sensors. Today, especially in the clinical field, the most widely used method for the control of an active upper limb prosthesis is based on the ElectroMyoGraphic (EMG) Pattern Recognition, which allows to identify the type of movement that the subject intends to perform. In particular, the recognition of hand movements based on surface EMG (sEMG) signals is a promising approach for the development of Human-Machine Interfaces (HMI), such as robotic interfaces or poly-articulated prostheses, resulting in a more intuitive control and a quick tasks selection. The goal of this thesis is to use some widespread machine learning techniques to create a system able to recognize and classify hand gestures in real-time, starting from the sEMG signals produced by the forearm muscles. The innovative event-driven approach of the Average Threshold Crossing (ATC) technique is implemented to drastically reduce the power consumption due to the minimal amount of data to be processed. This technique computes the ATC parameter by averaging the number of sEMG Threshold Crossing (TC) events in a pre-defined time window, obtaining a proper index for muscle activation monitoring. The proposed system is composed by three acquisition channels, each one acquiring the sEMG signal and providing the related quasi-digital TC signal, and an Apollo3 Blue MicroController Unit (MCU), which feeds the embedded machine learning algorithms and classifies the performed gesture. The thesis work focuses on the comparison among Artificial Neural Network (ANN), Support Vector Machines (SVM) and K-Means ML tecniques, exploring different capabilities during online prediction. Exploiting the ARM libraries features, a firmware optimization analisys has been carried out in order to reduce power consumption as much as possible and to achieve a latency suitable for real-time applications. In particular, with SVM algorithm an average classification accuracy of 94.49%, a latency of 109.85 ms and iii an average power consumption of 1.67 mW were obtained. K-means has gotten an average classification accuracy of 95.14%, a latency of 62.6 μs and an average power consumption of 0.82 mW . Finally, the NN achieved an average classification accuracy of 97.59%, a latency of 2.58 ms and an average power consumption of 0.83 mW . Based on the obtained results, K-Means is the best algorithm analyzed for this study.