Miracle-dz/UniFAR-FTUs huggingface dataset:
Different Type of Face Masks and Their Protection Against Covid-19

Coronavirus diseases 2019 (COVID-19) have become a major pandemic and a gruesome burden worldwide. The infection is easily spread through respiratory droplets from infected individuals during coughing, sneezing or talking. People in their vicinity, within 1-meter distance, can get infected by breathing contaminated air and touching the contaminated surfaces or hands. WHO encouraged the use of facemasks in the community, together with regular hand washing with soap and social distancing to prevent the transmission of COVID-19. However, with the many types of facemasks available in the markets, it remains debatable as to which ones are the most effective in curbing the transmission of the disease. This paper reviews available literature on the types of face masks, their effectiveness in filtering droplets and the advantages and disadvantages of using disposable and fabric masks. As found out, the most superior mask is the N95 type, with a filtration rate of 95% of 0.3 micron particles. However, for respiratory droplets, which particle size is from 5 to 10 microns, a surgical mask is adequate with a filtration rate of 90% of 3 micron particles. Due to disposal and cost concerns, surgical masks are recommended to be used only by health care workers. Three-layer cotton masks offer almost the same filtration rate as surgical mask and are recommended by WHO to be used in the community to prevent the transmission of COVID-19. Surgical masks and 3-layered cotton masks are effective in preventing droplet transmission from infected to healthy individuals. To prevent COVID-19, the public should be reminded continuously on the proper use and disposal of masks, regular hand washing and physical distancing.
Hygienic-sanitary quality and effect of freezing time and temperature on total antioxidant capacity of human milk

Abstract Knowledge of the hygienic-sanitary quality of raw human milk helps to establish the best storage conditions for the preservation of its nutritional and functional components. Therefore, this study aimed to evaluate the hygienic-sanitary quality of human milk extracted at the mothers’ homes, and to analyze the effect of freezing time and temperature on the milk’s total antioxidant capacity. Milk of five mothers was evaluated individually for Staphylococcus aureus, total aerobic mesophilic counts, mold and yeasts, total and thermotolerant coliforms. The milk pool was stored at -8 °C, -18 °C and -40 °C for 2, 4, 8 and 15 days and analyzed for the total antioxidant capacity by the 2,2-diphenyl-1-picrylhydrazyl free radical and 2,2-azino 3-ethylbenzothiazoline-6-sulfonic acid scavenging methods. The microbiological analyses of the raw human milk samples indicated counts of all the studied microorganisms above the safe limits. Related to the effect of freezing time and temperature on total antioxidant capacity, it was concluded that, regardless of the freezing temperature, a significant reduction occurred on total antioxidant capacity over time and that the lower the storage temperature, the greater its total antioxidant activity.
Parents' Perspectives on a Computer Game–Assisted Rehabilitation Program for Manual Dexterity in Children With Cerebral Palsy: Qualitative Analysis of Expectations, Child Engagement, and Benefits

Background Children with motor impairments affecting the upper extremity benefit from task-specific therapy, such as constraint-induced movement therapy. However, there is a need to improve engagement and compliance with task-specific exercise programs that target manual dexterity for children with cerebral palsy (CP). A computer game–based rehabilitation (GRP) platform was developed that combines fine manipulation and gross movement exercises with engaging game activities appropriate for young children with CP. Objective The objectives of this qualitative analysis were to compare parents’ perspectives and opinions about expectations, challenges, and benefits between 2 interventions. Methods A mixed methods, randomized controlled trial (RCT) was conducted to examine the feasibility and estimate the effect size of 2 exercise programs for rehabilitation of manual dexterity of children with CP using either GRP or conventional therapy. Parents of 26 of the children who completed the GRP program (n=33) and parents of 15 of the children who completed the conventional therapy program (n=27) participated in the interviews. A general conductive approach was used to analyze the data recorded during the parents’ interviews. Results Five themes captured the range of the parent’s experiences, viewpoints, and ideas: (1) parents’ expectations, (2) child’s engagement with therapy, (3) positive effects of the interventions, (4) challenges, and (5) improving the protocol. Conclusions Parents from both groups recognized that their expectations related to improving children’s object handling and manipulation skills including participation in activities of daily life were addressed during the 16-week therapy program. Parents perceived a change in the children’s level of independence in their daily tasks at home, school, and leisure activities. Trial Registration ClinicalTrials.gov NCT02728375; https://clinicaltrials.gov/ct2/show/NCT02728375
Distributed Computing with Modern Shared Memory

In this thesis, we revisit classic problems in shared-memory distributed computing through the lenses of (1) emerging hardware technologies and (2) changing requirements. Our contributions consist, on the one hand, in providing a better understanding of the fundamental benefits and limitations of new technologies, and on the other hand, in introducing novel, efficient tools and systems to ease the task of leveraging new technologies or meeting new requirements. First, we look at Remote Direct Memory Access (RDMA), a networking hardware feature which enables a computer to access the memory of a remote computer without involving the remote CPU. In recent years, the distributed computing community has taken an interest in RDMA due to its ultra-low latency and high throughput and has designed systems that take advantage of these characteristics. However, we argue that the potential of RDMA for distributed computing remains largely untapped. We show that RDMA’s unique semantics enable agreement algorithms which improve on fundamental trade-offs in distributed computing between performance and failure-tolerance. Furthermore, we show the practical applicability of our theoretical results through Mu, a state machine replication system which can replicate requests in under 2 microseconds, and can fail-over in under 1 millisecond when failures occur. Mu’s replication and fail-over latencies are at least 61% and 90% lower, respectively, than those of prior work. Second, we focus on persistent memory, a novel class of memory technologies which is only now starting to become available. Persistent memory provides byte-addressable persistent storage with access times comparable to traditional DRAM. Recent work has focused on designing tools for working with persistent memory, but little is known about the fundamental cost of providing consistency in persistent memory. Furthermore, important shared-memory primitives do not yet have efficient persistent implementations. We provide an answer to the former question through a tight bound on the number of persistent fences required to implement a lock-free persistent object. We address the latter problem by presenting a novel efficient multi-word compare-and-swap algorithm for persistent memory. Third and finally, we consider the current exponential increase in the amount of data worldwide. Memory capacity has been on the rise for decades, but remains scarce when compared to the rate of data growth. Given this scarcity and the prevalence of concurrent in-memory processing, the classic problem of concurrent memory reclamation remains highly relevant
Quality perception and willingness to pay: The case of red wine with health-beneficial effects

This paper attempts to identify consumers’ preferences toward red wine quality cues and willingness to pay (WTP) for wine with health-beneficial effects, thus clarifying the complex process of purchasing habits and patterns. The data were analyzed using structural equation modeling. The findings from a case study conducted in Serbia show that consumer health-effect consciousness and household income are significant predictors of their WTP. On the other hand, health-conscious consumers are more inclined to intrinsic quality cues, while those who are willing to pay a higher price for a bottle of red wine are prone to extrinsic wine quality cues.
The multi-patch logistic equation

The paper considers a \begin{document}$ n $\end{document} -patch model with migration terms, where each patch follows a logistic law. First, we give some properties of the total equilibrium population. In some particular cases, we determine the conditions under which fragmentation and migration can lead to a total equilibrium population which might be greater or smaller than the sum of the \begin{document}$ n $\end{document} carrying capacities. Second, in the case of perfect mixing, i.e when the migration rate tends to infinity, the total population follows a logistic law with a carrying capacity which in general is different from the sum of the \begin{document}$ n $\end{document} carrying capacities. Finally, for the three-patch model we show numerically that the increase in number of patches from two to three gives a new behavior for the dynamics of the total equilibrium population as a function of the migration rate.
The Impact of the COVID-19 Pandemic on Self-Reported Management of Chronic Conditions

Chronic conditions (CCs) management during the COVID-19 pandemic and the impact of the pandemic on patient activation (PA) and health locus of control (HLOC) remain unknown. This cross-sectional online survey study examined the role of COVID-19 pandemic-related worry or fear in PA and HLOC among patients with CCs. Individuals with CCs (n = 300) were recruited through MTurk Amazon. The questionnaire included sociodemographic questions, the Patient Activation Measure, and the Multidimensional Health Locus of Control–Form B. Out of the 300 participants, 9.7% were diagnosed with COVID-19, and 7.3% were hospitalized. Patients with cancer, chronic kidney disease, chronic obstructive pulmonary disease, drug abuse/substance abuse, and stroke reported significant difficulties in managing their CCs due to worry or fear because of COVID-19. More than half of the sample (45.7%) reported COVID-19-related worry or fear about managing their CCs, and these patients had lower PA and lower external HLOC compared to patients not affected by COVID-19-related worry or fear. Health professionals should provide more support for patients facing difficulties in managing their CCs during the COVID-19 pandemic.
Deep learning and hyperspectral imaging for unmanned aerial vehicles: Combining convolutional neural networks with traditional computer vision paradigms

Recent is er veel belangstelling voor onderzoek naar, en toepassingen van, hyperspectrale beeldverwerkingstechnologie. Hyperspectrale camera’s nemen informatie op uit meerdere banden van het elektromagnetische spectrum. Het doel van deze camera’s is om een spectrogram per pixel op te nemen zodat een hyperspectrale kubus gevormd kan worden. Het toepassingsgebied van dit type camera’s is breed en varieert van vegetatie-inspectie tot het chemische typeren van materialen. Kleine multi-copters op batterijen, genaamd Unmanned Aerial Vehicles (UAVs), hebben recentelijk een groot potentieel getoond voor een groot aantal toepassingsgebieden. Een camera wordt gemonteerd op een UAV en deze wordt gebruikt voor de inspectie van grote objecten of grote oppervlakken. Op het gebied van precisielandbouw worden ze bijvoorbeeld gebruikt voor het meten van Chlorofyl om de gezondheid van gewassen te bepalen. Verder worden ze gebruikt voor de inspectie van windturbines, om beelden te maken van scheuren, gaatjes en andere defecten. Toepassingen van UAVs zouden nog talrijker kunnen worden door meer gebruik te maken van hyperspectrale beeldverwerkingstechnologie, maar deze apparaten hebben intrinsieke beperkingen die het gebruik ervan, in combinatie met elkaar, uitdagend maken. Dit wordt voornamelijk veroorzaakt door de gevoeligheid voor beweging of de lage resolutie van de hyperspectrale camera’s in combinatie met de beperkte payload mogelijkheden van UAVs. Deep learning of, meer specifiek, Convolutional Neural Networks (CNNs) hebben state-of-the-art prestaties laten zien in een veelheid van onderzoeksgebieden. Veel toepassingen profiteren al van deep learning. Gewoonlijk worden deze deep learning modellen rechtstreeks getraind met behulp van data op een end-to-end manier. Dit proefschrift draait om de vraag of algoritmes, uit het veld van deep learning, de moeilijkheden kunnen mitigeren die worden veroorzaakt door de beperkingen die worden ondervonden bij het combineren van hyperspectrale cameratechnologie en UAVs. Deze drie eenheid van technologieen: deep learning, hyperspectrale beeldverwerking en UAVs, dient als een kader waarbinnen dit onderzoek is gedefinieerd.
INFECTION RATE OF GIARDIA DUODENALIS IN SHEEP IN BABYLON PROVINCE, IRAQ

Giardia duodenalis is a common intestinal protozoan that can cause diarrhea, weight loss and even death in animals or humans, threatening the livestock industry and public health. It can virtually infect (zoonosis) humans and all domestic animals, including sheep. Objective of this research was to study the prevalence of Giardia duodenalis infection in sheep in the province of Babylon, Iraq. 100 fecal samples were obtained from sheep of different age groups (1month to 5 years) from 3 areas in Babylon province, middle of Iraq. The samples were tested for the presence of Giardia duodenaliscysts using concentration Zinc Sulphate solution and Giemsa staining method. Giardia duodenalis cysts were present in 13% of sheep. The results showed significant (p < 0.05) differences in prevalence rates among different area of study. The highest infection rate was in Al-Qasim 20%, while the lowest in Al-Hillah 10%. The sex of sheep had no effect on the infection ratio with Giardia duodenalis. The infection rate was 12 % for males and 14 % for females respectively. The results showed no significant (p>0.05) differences in prevalence rates among different age groups of sheep infected with Giardia duodenalis. The presence of Giardia duodenalis in sheep in Babylon province indicates that this protozoan parasite should also be considered in the etiology of sheep exhibiting diarrhea.
Evaluation of microparticulate diets for larval rearing of endangered fish, golden mahseer (Tor putitora)

In the present study, performance of microparticulate diets supplemented with exogenous dietary digestive enzyme mix was compared with live feed Artemia nauplii for the feeding of golden mahseer larvae after 15d of yolk sac absorption. One thousand five hundred golden mahseer larvae were randomly distributed in five treatment groups (100 larvae per tank) following a completely randomized design. Larvae were manually fed either Artemia nauplii or macerated goat liver or microparticulate diets supplemented with exogenous dietary digestive enzyme mix at different levels (0, 2.0 and 4.0 g/kg diet). After 60 d of feeding, no significant (P≥0.05) difference was noticed in the survival of golden mahseer larvae fed with different diets. However, there was significant (P≤0.05) effect of different dietary treatments on the weight gain and specific growth rate. The highest weight gain and specific growth rate was observed in the Artemia nauplii fed group followed by microparticulate diet containing digestive enzyme mix of 2.0 g/kg diet. The weight gain of larvae fed the microparticulate diet supplemented with digestive enzyme mix of 2.0 g/kg diet was almost 80.4 per cent of that achieved for larvae fed Artemia nauplii. The lowest weight gain per cent and specific growth rate was evidenced in the group fed with macerated goat liver. Based on the results of the present study, the microparticulate diet supplemented with exogenous dietary digestive enzyme mix (2.0 g/ kg diet) can be an alternative for the feeding of golden mahseer larvae after 15 days of yolk sac absorption.
Nurses communication skill and associated factors in Amhara Region Referral Hospitals, Ethiopia, 2019

Background: - Nurses are critical in the delivery of essential health services and are core in strengthening the health system. So, the aim of this article was to assess the prevalence of the communication skills of the nurses to patient and determinant factors in Amhara Region Referral Hospitals, Ethiopia, 2019 Methods: Institution based cross-sectional study was conducted from March 18 to April 16, 2019 in Amhara Region Referral Hospitals. A simple random sampling technique was used to select 684 respondents. Data was collected using pretested and self-administered questionnaire. Collected data was entered into Epi Info version 7.1. 2.0 and exported to SPSS version 25.0 for analysis. Bivariate analysis was used primarily and variables with p-value ≤ 0.2 were further examined using multivariable logistic regression model to control con-founders. Then, variables having p-value less than 0.05 with 95% CI were used to determine associated factors. Results: - Out of 678 study participants, 403 (61.4%) of them had effective communication skills with 96.8 % of the response rate. Less than 5 years of working experience [AOR=2.77; 95% CI: (1.28, 5.99)], workload [AOR=1.52; 95% CI: (1.09, 2.12)], and poor evidence-based utilization [AOR=2.00; 95% CI: (1.40, 2.85)] were associated with the nurse’s effective communication skill to patients. Conclusions: More than half of the participants were had effective communication skills. Year of working experience, workload, and poor evidence-based utilization were the main contributing factors of the communication skills. Keywords: Communication skills, Nurses, Patients, Ethiopia
Experimental investigation on micro-electro discharge machining process using tungsten carbide and titanium nitride-coated micro-tool electrode for machining of Ti-6Al-4V

ABSTRACT Titanium alloy Ti-6Al-4 V is used in numerous applications because of its low weight associated with high strength, excellent resistance to fatigue and creep, good resistivity in corrosive environments, and biocompatibility. The Micro-Electro Discharge Machining (MEDM) is one of the finest non-conventional machining processes used for machining Ti-6Al-4 V. In this research article an attempt has been made to study effect of thin film coating of titanium nitride (TiN) on tungsten carbide (WC) micro-electrode on tool wear rate (TWR), over cut (OC) and depth of machining (Z coordinator) during micro-drilling of Ti-6Al-4 V. A detailed experimental investigation has been carried out with the help of Taguchi’s L9 orthogonal array for understanding the mechanism of the process. The process parameters such as voltage, spindle rotation and capacitance are considered to perceive their effect on TWR, OC and Z coordinator. Uncoated WC and TiN-coated WC micro-tool electrodes has been used during machining Ti-6Al-4 V in order to compare listed responses. The experimental results of TiN-coated micro-electrode showed that TWR decreased by 16.32 %, depth of machining increased by 20.83% and OC reduced by 12% as compared to uncoated WC micro-tool electrode.
Analyzing the association of dyslipidemia based on total cholesterol according to dietary life and health characteristics using Korea National Health and Nutrition Examination Survey(KNHANES VII-1)

This study analyzes the difference in total cholesterol blood concentration according to dietary characteristics and health characteristics, as well as general characteristics, and the relationship between that factor and total cholesterol level according to the diagnostic criteria for dyslipidemia, and then compares and analyzes the relative risk ratio of significant factors for the occurrence of dyslipidemia. As a result, the total cholesterol blood concentration increases with age, so continuous management is necessary. Mainly, waist circumference level in early adulthood, regular exercise of appropriate intensity in late adulthood, and subjective health level management in the elderly are necessary. It was found that it was necessary to manage BMI level and eating-out level overall.
Water inside carbon nanotubes: structure and dynamics

Abstract Studying the properties of water confined in carbon nanotubes (CNTs) have gained a lot of interest in recent years due to the vast potential applications of systems in nanoscale liquid transport as well as biology functions. This article presents a comprehensive review of recent experimental and theoretical results using nuclear magnetic resonance (NMR) and molecular dynamics (MD) simulations. Different NMR methods including 1H and 2H NMR line shapes, relaxation, and diffusion measurements are reviewed. In addition, we present a review of MD studies that explained the driving forces behind water filling, structure of confined water, and its flow in CNTs. Debatable issues in the results are pointed out, and several possible directions for future research, both experimentally and theoretically, are proposed.
Readability Assessment for Chinese L2 Sentences: An Extended Knowledge base and Comprehensive Evaluation Model-based Method

The paper assesses sentence readability based on the standards in the field of Chinese L2 teaching. In view of the inapplicability of the field standards in text readability assessment, the study focuses on two aspects. On the one hand, the graded lexicon of the HSK syllabus is extended to obtain a large-scale graded lexical knowledge base. On the other hand, sentence-based features in the existing teaching grammatical knowledge base are supplemented to achieve the automatic recognition of grammatical points and obtain quantitative grammatical indicators regarding sentence readability. Besides, based on the extended knowledge bases, comprehensive evaluation models are created to calculate the lexical and grammatical difficulties of sentences, as well as the sentence readability. The results of experiments show that the sentence readability is well differentiated in all levels of texts. Furthermore, the correlation between sentence readability and text readability is significantly improved in comparison with existing methods.
Deep Prior-Based Unsupervised Reconstruction of Irregularly Sampled Seismic Data

Irregularity and coarse spatial sampling of seismic data strongly affect the performances of processing and imaging algorithms. Therefore, interpolation is a usual preprocessing step in most of the processing workflows. In this work, we propose a seismic data interpolation method based on the deep prior paradigm: an ad hoc convolutional neural network is used as a prior to solve the interpolation inverse problem, avoiding any costly and prone-to-overfitting training stage. In particular, the proposed method leverages a multiresolution U-Net with 3-D convolution kernels exploiting correlations in cubes of seismic data, at different scales in all directions. Numerical examples on different corrupted synthetic and field data sets show the effectiveness and promising features of the proposed approach.