Miracle-dz/UniFAR-FTUs huggingface dataset:
Viscous Flow Field Computations for the VKI–1 Turbine Cascade Using Different Turbulence Models

The influence of the turbulence modelling on viscous flow field calculation results has often been discussed in the past. For a meaningful comparison of different turbulence models the access to reliable measurement data is necessary. The plane VKI–1 turbine profile has been investigated experimentally in many publications. Therefore this turbine profile is chosen for transonic 2D flow field calculations using three different turbulence models. The algebraic model of Baldwin and Lomax, the Standard k–ϵ model with wall functions and a low–Reynolds number model are considered in this investigation.The main differences between the models become apparent in the trailing edge region. The turbulence modelling influences the boundary layer thickness and the shape of the shear layers and the separation region in the wake flow. For the high Mach numbers appearing in this region, a strong influence on the flow field due to small shear layer changes has been found.Copyright © 1995 by ASME
Mild air oxidation of boron nitride nanotubes. Application as nanofillers for thermally conductive polycarbonate nanocomposites

Boron nitride nanotubes (BNNTs) have experienced considerable growth in recent years due to their unique intrinsic properties, in particular for the fabrication of polymer nanocomposites. Dispersion of pure BNNTs in nanocomposites is often difficult due to their poor compatibility with most polymer matrices. An approach involving the creation of hydroxyl groups on their surface could improve their dispersion. While some harsh oxidation processes have been reported so far, a mild oxidation of BNNTs using air as the oxidant is reported here. This new catalytic reaction leads to slightly oxidized BNNTs, which were characterized by scanning electron microscope, x-ray photoelectron spectroscopy, Fourier transform infrared spectroscopy and thermogravimetric analysis. Polycarbonate nanocomposites were then fabricated using pristine and oxidized BNNTs as nanofillers. The measured thermal conductivity increased linearly with the mildly oxidized BNNTs content. It reached a five-fold increase up to 1.19 W m.K−1 at 15% vol. content which is significantly improved over nanocomposites fabricated with severely oxidized BNNTs, while the electrically insulating character remained unchanged.
A Comprehensive Predictive-Learning Framework for Optimal Scheduling and Control of Smart Home Appliances Based on User and Appliance Classification

Energy consumption is increasing daily, and with that comes a continuous increase in energy costs. Predicting future energy consumption and building an effective energy management system for smart homes has become essential for many industrialists to solve the problem of energy wastage. Machine learning has shown significant outcomes in the field of energy management systems. This paper presents a comprehensive predictive-learning based framework for smart home energy management systems. We propose five modules: classification, prediction, optimization, scheduling, and controllers. In the classification module, we classify the category of users and appliances by using k-means clustering and support vector machine based classification. We predict the future energy consumption and energy cost for each user category using long-term memory in the prediction module. We define objective functions for optimization and use grey wolf optimization and particle swarm optimization for scheduling appliances. For each case, we give priority to user preferences and indoor and outdoor environmental conditions. We define control rules to control the usage of appliances according to the schedule while prioritizing user preferences and minimizing energy consumption and cost. We perform experiments to evaluate the performance of our proposed methodology, and the results show that our proposed approach significantly reduces energy cost while providing an optimized solution for energy consumption that prioritizes user preferences and considers both indoor and outdoor environmental factors.
High Seroprevalence of Anti-SARS-CoV-2 IgM/IgG among Inhabitants of Sakaka City, Aljouf, Saudi Arabia

(1) Backgrounds and Objectives: The global battle to contain the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) is still ongoing. This cross-sectional study aimed to detect the seroprevalence of anti-SARS-CoV-2 IgM/IgG among previously symptomatic/asymptomatic and vaccinated/unvaccinated inhabitants of Sakaka City, Aljouf, Saudi Arabia. (2) Methods: Blood samples of 400 participants were tested for the presence of anti-SARS-CoV-2 IgM/IgG using colloidal gold immuno-chromatography lateral flow immunoassay cards. (3) Results: The prevalence of anti-SARS-CoV-2 IgM and IgG positivity was 45.8% and 42.3%, respectively. Statistically significant correlations (p < 0.05) were found between the previous RT-PCR testing for SARS-CoV-2-RNA and positivity for IgM and/or IgG. The highest seroprevalence of IgM and IgG were detected among smokers, participants aged ≥40 years, and patients with chronic diseases. Although most of the participants (58.5%) did not previously experience COVID-19 like symptoms, the anti-SARS-CoV-2 IgM and IgG seropositivity amongst them was 49.1% and 25.6%, respectively, with higher seroprevalence among males than females. At the time of the study, the SARS-CoV-2 vaccination rate at our locality in Saudi Arabia was 43.8% with statistically significant correlation (p < 0.001) between being vaccinated and anti-SARS-CoV-2 IgM and/or IgG positivity, with more positivity after receiving the second vaccine dose. (4) Conclusions: Public assessment reflects the real scale of the disease exposure among the community and helps in identifying the asymptomatic carriers that constitute a major problem for controlling the SARS-CoV-2. To limit the spread of the virus, rigorous implementation of large-scale SARS-CoV-2 vaccination and anti-SARS-CoV-2 serological testing strategies should be empowered.
Determination of the Size and Concentration of Cloud Drops with an FSSP

Abstract A detailed size calibration of the Forward Scattering Spectrometer Probe (FSSP) over the size ranges of interest to cloud physics (2–47 μm), is presented. The calibration includes laboratory tests with glass spheres, Mie scattering calculations and airborne cloud measurements. Each size bin of the FSSP was found to have errors of 0–5 μm in diameter. The magnitude and sign of the errors were dependent on airspeed for airspeeds greater than 55 m s−1. This sizing error can lead to errors of 70% or more in derived cloud liquid water content. In addition, a concentration algorithm was derived from laboratory tests with pseudo-random pulse generators which properly corrects for probe dead time. After application of both calibration algorithms the instrument is capable of yielding mean diameters that agree with predicted mean diameters to within a few tenths of a micron and liquid water contents which are in good agreement with an independent liquid water measurement. Even after corrections, the instrum.
UPTAKE OF HEALTH INSURANCE AND ITS ASSOCIATED FACTORS AMONG INFORMAL SECTOR WORKERS IN DAR ES SALAAM, TANZANIA

Health insurance is a viable strategy to facilitate accessibility of health care but it favors the formal sector workers while leaving behind the informal sector workers who are the majority. This mixed methods study involved 889 informal sector workers from Dar es Salaam, Tanzania. Income, membership to economic groups, education, age, insurance regulations, fragmentation of insurance providers, cultural beliefs and low priority on health insurance were significantly associated with uptake of health insurance. Low uptake of health insurance increases inaccessibility of health care. Subsidizing the premium and using innovative strategies to increase understanding will improve health service accessibility.
Block-Jacobi Implicit Algorithms for the Time Spectral Method

Many industrial applications involve flows periodic in time. Such flows are not simulated with enough efficiency when using classical unsteady techniques, as a transient regime must be bypassed. New techniques, dedicated to time-periodic flows and based on Fourier analysis, have been developed recently. Among these, the time spectral method casts a time-periodic flow computation in several coupled steady computations, corresponding to a uniform sampling of the period. Up until now, the steady states were reached using an explicit pseudotime algorithm. Thus, very small time steps were needed and the convergence rate slowed down when increasing the number of harmonics. In this paper, a block-Jacobi approach is presented to solve the stationary problems with an implicit algorithm. Numerical simulations show, on one hand, the good quality of the results and, on the other hand, the interest of the proposed method to reduce the sensitivity of computations to a large number of harmonics.
Rhizobium leguminosarum bv. viciae-Mediated Silver Nanoparticles for Controlling Bean Yellow Mosaic Virus (BYMV) Infection in Faba Bean Plants

The faba bean plant (Vicia faba L.) is one of the world’s most important legume crops and can be infected with various viral diseases that affect its production. One of the more significant viruses in terms of economic impact is bean yellow mosaic virus (BYMV). The current study used the molecularly identified Rhizobium leguminosarum bv. viciae strain 33504-Borg1, a nitrogen-fixing bacteria, to biosynthesize silver nanoparticles (AgNPs) to control BYMV disease in faba bean plants. Scanning electron microscopy (SEM), a particle size analyzer (PSA) with dynamic light scattering (DLS), transmission electron microscopy (TEM), energy dispersive X-ray spectroscopy (EDX), and Fourier transform infrared spectroscopy (FTIR) were used to characterize the prepared AgNPs. The DLS, SEM, and TEM analyses revealed that the AgNPs were spherical and rough, with sizes ranging from 13.7 to 40 nm. The FTIR analysis recognized various functional groups related to AgNP capping and stability. Under greenhouse conditions, spraying faba bean leaves with the AgNPs (100 µg/mL) 24 h before BYMV inoculation induced plant resistance and reduced plant disease severity and virus concentration levels. Contrarily, the AgNP treatment enhanced plant health by raising photosynthetic rates, increasing the fresh and dry weight of the faba bean plants, and increasing other measured metrics to levels comparable to healthy controls. Antioxidant enzymes (peroxidase and polyphenol oxidase) inhibited the development of BYMV in the faba bean plants treated with the AgNPs. The AgNPs decreased oxidative stress markers (H2O2 and MDA) in the faba bean plants. The plants treated with the AgNPs showed higher expression levels of PR-1 and HQT than the control plants. The study findings could be used to develop a simple, low-cost, and environmentally friendly method of protecting the faba bean plant from BYMV.
How Does Government Information Service Quality Influence Public Environmental Awareness?

The development of public environmental awareness has been an essential part of environmental governance in China and a prerequisite for the emergence of conscious environmental behaviors. However, the deeper factors influencing Chinese public environmental awareness are not yet fully understood. In this study, the perception of environmental pollution and the sense of political efficacy were introduced as variables to establish a public environmental awareness model, at the perception level, from the perspective of government information service quality. The correlations between different variables, as well as the working principles, were analyzed based on national environmental survey data. The results demonstrate that both external (the government information service quality) and psychological (the perception of environmental pollution and the sense of political efficacy) factors have significant positive influences on public environmental awareness, with the sense of political efficacy outperforming the perception of environmental pollution and the government information service quality. Analysis of the mediating effect reveals that government information service quality directly influences public environmental awareness; it also indirectly influences public environmental awareness through a chained mediating effect of the perception of environmental pollution and the sense of political efficacy. The results of the multiple-group analysis, with gender and urban–rural attributes as moderator variables, further show that, compared with men and urban residents, the impact of government information service quality and environmental pollution perception on women and rural people’s political efficacy is not significant. Therefore, it is suggested to optimize the government information service, improve the public’s perception of environmental pollution, and then promote the public’s sense of efficacy in the environment governance situation. Furthermore, the government should formulate differentiated strategies for different types of public to guide them to form a proactive awareness of environmental protection.
A spectral approach to the Dirac equation in the non-extreme Kerr–Newmann metric

We investigate the local energy decay of solutions of the Dirac equation in the non-extreme Kerr–Newman metric. First, we write the Dirac equation as a Cauchy problem and define the Dirac operator. It is shown that the Dirac operator is selfadjoint in a suitable Hilbert space. With the RAGE theorem, we show that for each particle its energy located in any compact region outside the event horizon of the Kerr–Newman black hole decays in the time mean.
Characterization of Virulent Bacterial Isolates Associated with Multi-Drug Resistance among Patients with Surgical Site Infections in Selected Specialist Hospitals in Calabar, Nigeria

Aims: Increasing research findings have documented the continuous emergence and threats posed by drug resistant clinical isolates from post-operative wound infections to commonly used antibiotics globally. This hospital-based study investigated virulent bacterial pathogens implicated with post-operative wound infections among surgical site infection (SSI) patients in Calabar, Nigeria and determined their antibiotic resistance pattern. Methodology: A total of 127 bacterial isolates of different genus from 110 SSI patients, were isolated from pus and surgical wound exudates and fully characterized using standard bacteriological procedures. Antimicrobial susceptibility patterns of isolates were determined using Kirby- Bauer disk diffusion method, following the guidelines by Clinical Laboratory Standard Institute (CLSI). Results: Multi-drug resistant bacteria isolated and their percentage frequency were coagulase Negative Staphylococci (21.3%), Staphylococcus aureus (19.7%), Pseudomonas aeruginosa (14.2%), Escherichia coli (11.8%), Klebsiella pneumoniae (9.4%), Enterococcus faecium (6.3), Enterobacter cloacae (4.7%), Proteus mirabilis (4.7%), Acinetobacter baumannii (3.1%), Pseudomonas putida (3.1%) and Aerococcus viridans (1.6%). Among gram-positive bacteria isolated, S. aureus showed highest resistance to several antimicrobials (100% to oxacillin, 96% to ciprofloxacin, 92% to levofloxacin, and 76% resistance to vancomycin). All recovered S. aureus isolates were cefoxitin screen positive indicating possible MRSA isolates. Additionally, among Gram-negative isolates K. pneumoniae was found to possess higher resistance to several antibiotics (66.7% resistance to each of ciprofloxacin, levofloxacin, ceftazidime, trimethoprim /sulfamethoxazole, cefazolin, ampicillin, tobramycin and 58.3% resistance to each of ceftriaxone, gentamicin, and ampicillin/sulbactam). Statistical analysis of categorical variables of study subjects revealed that length of hospital stay, type of surgery, previous admission history, antibiotic use, and age were significant (p<0.05) in SSI outcome of patients, while patients’ gender was not significant (p>0.05) in SSI outcome. Conclusion: Adherence to measures of strict infection control, optimal preoperative, intraoperative, and postoperative patient care, including multifaceted approaches involving surveillance, and antimicrobial stewardship, are vital to SSI treatment outcomes.
Effect of epiphytic lactic acid bacteria fermented juice inclusion on quality of total mixed ration silage of agricultural and food by-products

Present study determined the effect of fermented juice of epiphytic lactic acid bacteria (FJLB) as silage additive on the fermentation quality and nutritive value of total mixed ration (TMR) silage prepared from agricultural and food industrial by-products, to compare the resultant silage quality with that of silage produced with commercial additive. FJLB was prepared from Italian ryegrass. The applied treatments were: (i) CON (Control-no additive); (ii) FJLB (as silage additive); (iii) COM (commercial silage additive); and (iv) MIX (combination of FJLB and commercial additive). The fermentation quality was measured at 2, 7, 14, 30 and 60 days of fermentation. The nutritive value was measured at 60 day of fermentation. The addition of the FJLB to TMR produced a better quality silage in terms of a lower pH, higher lactic acid content, lower dry matter (DM) loss and higher Fleig point than occurred with COM and CON treatments. The addition of the FJLB combined with the commercial silage additive decreased the aNDFom and ADFom content of the TMR silage. In conclusion, inclusion of the FJLB to the TMR silage prepared from agricultural and industrial by-products improved the fermentation quality.
Variation in flowering time and flowering date stability within a cultivar of French serradella

ABSTRACT Context. Opportunity exists to expand serradella (Ornithopus spp.) use onto heavier, duplex soil types in permanent pasture environments of south-eastern Australia. This requires cultivars with appropriate flowering times and flowering-date stability (i.e. flowering at the same date in spring regardless of timing of the autumn break). Aim. This work examined evidence of variation in flowering date and flowering-date stability in the NSW southern tablelands for a widely-used French serradella (O. sativus) cv. Margurita. Methods. Seed (sourced from a commercial supplier) was sown 21 March 2019 (Canberra, ACT) and 231 individual plants were monitored for time to first flower. A subset of plants exhibiting ‘early’ or ‘late’ flowering were identified and their seeds collected. In 2020, seed from ~15 plants from each selection was sown in Canberra in late March and early May to represent an ‘early’ and a ‘later’ break of season (n = 3). Key results. In the early-sown treatment, ‘early-flowering’ selections typically reached the median date of first flower (50%-flowering) from mid- to late August, while ‘late-flowering’ selections reached 50%-flowering early- to mid-September. When sown later, the ‘early-flowering’ selections began flowering from mid- to late September, while the ‘late-flowering’ selections flowered mid-September to early October. The ‘early’ selections exhibited greater flowering-date instability than ‘late’ selections and flowered particularly early when sown early. This indicated diversity within cv. Margurita for flowering-time control (e.g. vernalisation and/or photoperiod requirements). Implications. Evaluating cultivars of serradellas for flowering date and flowering date stability in their target environment(s) is essential to ensure cultivars are suitably adapted to these environments.
Balanced versus unbalanced designs for linear structural relations in two‐level data

A general two-level model for multivariate data is described and illustrated by specializations to a common factor model and a path model with latent variables. The problem of estimation is treated, and in the special case of a balanced sampling design, a likelihood-based discrepancy function and a test of goodness of fit are obtained in terms of some simple sufficient statistics.
Influence of Soil Test Crop Response Based Integrated Plant Nutrient Management on Quality of Okra [Abelmoschus esculentus (L.) Monech]

In Soil Test Crop Response (STCR) based Integrated Plant Nutrient System (IPNS) technology, the fertilizer doses are tailored as per the requirements of estimated crop yield taking into account the nutrient requirement of the crop, and the contribution of nutrients from the soil, fertilizers and organic manures. In this study, a field experiment was carried out in the Bahour soil series of Puducherry to study the quality of Okra in response to STCR-based manure and fertilizer application. The experiment was carried out with ten treatments viz., farmer’s practice, FYM alone @ 12.5 t ha-1, blanket recommendation, STCR-NPK alone @ 160, 170, and 180 q ha-1, and STCR-IPNS @ 160, 170, and 180 q ha-1 and control replicated thrice. The fruit samples were collected at 5th, 12th, and 19th pickings and were analyzed for quality parameters. Application of STCR + IPNS – 180 q ha-1 improved the quality parameters such as mucilage (4.54%), protein (1.84%), and starch (4.95%) and ascorbic acid (13.99 mg per100g) content of Okra. The STCR-IPNS technology ensures sustainable crop production and economical use of expensive fertilizer.
Organophosphorus Chemistry: Synthesis of New Phosphonic Acid Derivatives Bearing a Triazole Moiety

: A series of new 1,2,3-triazolylphosphonates were synthesized through multicomponent alkyne-azide 1,3-dipolar cycloaddition catalyzed by copper nanoparticles on activated carbon. The reactions were carried out in water and at a very low copper loading as green conditions, leading to the triazolylphosphonate products in moderate to good yields. Studies into their activity as butyrylcholinesterase inhibitors are underway.
Soluble Transferrin Receptor, Antioxidant Status and Cardiometabolic Risk in Apparently Healthy Individuals

Body iron excess appears to be related to insulin resistance and cardiometabolic risk and increased oxidative stress might be involved in this relationship. Very few studies have described the association between soluble transferrin receptor (sTfR) levels and cardiometabolic risk in the general population or antioxidant status. There were 239 subjects (20–65 years old) included in this cross-sectional study. Linear regressions adjusting for BMI, menopausal status, insulin resistance (HOMA-IR), physical inactivity, alcohol intake and subclinical/chronic inflammation were used to describe the association between sTfR, total antioxidant capacity (TAC), and measures of cardio-metabolic risk. sTfR levels were positively associated with TAC in men (βeta [95% confidence interval ]: 0.31 [0.14 to 0.48]) and women (βeta = 0.24 [0.07 to 0.40]) in non-adjusted and adjusted models (p < 0.05). In men, sTfR levels were inversely associated with waist circumference (βeta [95% confidence interval]: −1.12 [−2.30 to −0.22]) and fasting glucose (−2.7 (−4.82 to −0.57), and positively with LDL cholesterol (12.41 (6.08 to 18.57) before and after adjustments for confounding variables. LDL cholesterol had a significant and positive association with TAC in non-adjusted and adjusted models in men (p < 0.05). sTfR levels are significantly associated with antioxidant status and a few specific cardio-metabolic risk variables, independently of covariates that included serum ferritin and hepcidin. This might imply that iron biomarkers in regard to cardiometabolic risk reflect physiological contexts other than iron metabolism.