Miracle-dz/UniFAR-FTUs huggingface dataset:
Sociodemographic and clinical characteristics of SARS-CoV-2 infected population during the second and third epidemiological waves in Sri Lanka

Objective: To analyze data on socio-demographic and clinical characteristics of SARS-CoV-2 infected population whose samples were received from Medical Research Institute, Sri Lanka. Methods: Laboratory based retrospective study was done on patient samples which were tested positive for SARS-CoV-2 by National Reference Virology Laboratory at the Medical Research Institute, Sri Lanka, from November, 2020 to November, 2021. Data on socio-demographic characteristics and clinical presentation of 13 126 patients were examined. Results: The mean age of the study population was (36.0±7.2) years and the majority were men (64.0%). The highest number of positive cases were found in the 21-30 years-of-age group. Two distinct peaks were noted in the incidence of SARS-CoV-2 positive individuals. In addition, 42.5% of the positive samples tested positive (42.5%) were from Medical Officer of Health collection centres. Furthermore, 60.6% (7 951) of the infected subjects were asymptomatic whereas the remaining were symptomatic. The highest percentage of symptomatic patients were observed in the 91-100 years-of-age group while the highest asymptomatic subjects were found in the 31-40 years-of-age group. The percentage of asymptomatic children (65.3%) was significantly (P<0.05) higher than that of adults (43.4%). Conclusions: The findings of this study aid decision makers to focus on the vulnerable groups, and geographic and temporal distribution of patients in the public health strategies that aim at preventing the spread of the disease and reducinig its mortalities.
Effects of Expert-Determined Reference Standards in Evaluating the Diagnostic Performance of a Deep Learning Model: A Malignant Lung Nodule Detection Task on Chest Radiographs

Objective Little is known about the effects of using different expert-determined reference standards when evaluating the performance of deep learning-based automatic detection (DLAD) models and their added value to radiologists. We assessed the concordance of expert-determined standards with a clinical gold standard (herein, pathological confirmation) and the effects of different expert-determined reference standards on the estimates of radiologists’ diagnostic performance to detect malignant pulmonary nodules on chest radiographs with and without the assistance of a DLAD model. Materials and Methods This study included chest radiographs from 50 patients with pathologically proven lung cancer and 50 controls. Five expert-determined standards were constructed using the interpretations of 10 experts: individual judgment by the most experienced expert, majority vote, consensus judgments of two and three experts, and a latent class analysis (LCA) model. In separate reader tests, additional 10 radiologists independently interpreted the radiographs and then assisted with the DLAD model. Their diagnostic performance was estimated using the clinical gold standard and various expert-determined standards as the reference standard, and the results were compared using the t test with Bonferroni correction. Results The LCA model (sensitivity, 72.6%; specificity, 100%) was most similar to the clinical gold standard. When expert-determined standards were used, the sensitivities of radiologists and DLAD model alone were overestimated, and their specificities were underestimated (all p-values < 0.05). DLAD assistance diminished the overestimation of sensitivity but exaggerated the underestimation of specificity (all p-values < 0.001). The DLAD model improved sensitivity and specificity to a greater extent when using the clinical gold standard than when using the expert-determined standards (all p-values < 0.001), except for sensitivity with the LCA model (p = 0.094). Conclusion The LCA model was most similar to the clinical gold standard for malignant pulmonary nodule detection on chest radiographs. Expert-determined standards caused bias in measuring the diagnostic performance of the artificial intelligence model.
Mean Flowfields in Axisymmetric Combustor Geometries with Swirl

Six flowfield configurations are investigated with sidewall angles of 90 and 45/sup 0/, and swirl vane angles of 0, 45, and 70/sup 0/. It is found that central recirculation zones occur for the swirling flow cases investigated, which extend from the inlet to x/D 1.7, where x is the axial polar coordinate, and D is the test section diameter. Five-hole pitot probe pressure measurements are used to determine time-mean velocities, and corresponding flow situations are predicted and compared to results of experimental data. Excellent agreement is found for the nonswirling flow, although poor agreement is found for swirling flow cases, especially near the inlet. The discrepancy is attributed to the lack of realism in the turbulence model, and/or to inaccurate specification of time-mean velocity and turbulence energy distributions at the inlet.
Sediment yield estimation in GIS environment using RUSLE and SDR model in Southern Ethiopia

Abstract Soil erosion and sediment yields are the current limitations and future threats to agriculture, water resources and hydropower projects particularly in developing countries. Estimating the extent and comprehending the spatial distribution of hotspot area is crucial to implement evidence-based soil and water conservation (SWC) measures with limited resources. The study used RUSLE and SDR models in ArcGIS 10.8 environment. The RUSLE model was found to be highly sensitive to C factor followed by LS factor. The result indicated that the annual soil loss varies from 0 to 359.99 t ha−1 yr−1 with 22.31 t ha−1 yr−1 as a mean annual. Besides, the estimated sediment yield ranged from 0 to 42.5 t ha−1 yr−1 with a mean value of 12.02 t ha−1 yr−1. The finding revealed that the central west (SW_5) and northeast (SW_4) parts of the watershed yield higher sediment. The result also signified that about 52.9% of the eroded materials including soil and nutrients are transferred to the outlet. The outcome of our finding undoubtedly aids in the identification of hotspot areas for the adoption of appropriate SWC measures. Hence, adopting RUSLE and SDR for Gununo watershed and another watershed having similar biophysical and environmental factors is suggested.
Going Green Post COVID-19: Employer Perspectives on Skills Needs

Achieving a just transition to a low carbon economy and society, in the wake of the COVID-19 pandemic, is arguably one of the greatest policy challenges facing governments. It is also of deep concern to businesses, employees and the organisations that represent them. Much of the focus, particularly at policy level, has been on the potential of this transition to create new jobs especially through the growth of renewable energy and clean technology. In this paper, we argue that this focus on ‘green jobs', and in particular new green jobs, grossly underestimates the skills needs of a future workforce able to deliver a transition to a more sustainable low-carbon economy. The focus of this study is to gain an understanding of what skills are required to support the transition beyond these sectors. It critically reports on the results of a series of in-depth interviews with senior managers in key organisations within Cambridgeshire and Peterborough, UK. It sheds a light on the significant employment transitions taking place in organisations who are not specifically focused on delivering ‘green’ products or services. It finds widespread acknowledgement of the importance of a green recovery, albeit predicated by economic growth. The key skills needs reported, at all levels were likely to be ‘soft’ transferrable skills rather than ‘hard’ technical skills. COVID-19 was recognised as both a disrupter and as a catalyst for a green transition.
Cognitive trajectories during the menopausal transition

Aims Female sex is associated with an increased prevalence of dementia. Menopause may have a role to play in explaining sex differences in cognition, and possibly the risk of future dementia. We aimed to determine if the rate of cognitive decline differed between stages of the menopausal transition. Materials and methods Women with data on menopause and longitudinal cognitive function from the UK Biobank study were stratified into three groups: premenopausal, perimenopausal and postmenopausal. We studied associations of these menopause groups with rate of change in reaction time, verbal-numeric reasoning, prospective memory, visual memory and attention/working memory, adjusted for age, education, ethnicity and APOEε4 genotype. We also explored the effect of menopausal hormonal therapy (MHT) use and cross-sectional brain magnetic resonance imaging (MRI) volumes on these models. Results We included 15,486 women (baseline mean age 52 years) over a mean duration of 8 years. An interaction between menopausal group status and time was found for reaction time (p < 0.01). Compared with premenopausal women, the rate of increase (worsening) in reaction time was least in postmenopausal women (β = −1.07, p for interaction = 0.02). In general, compared with premenopausal women, perimenopausal and postmenopausal women had overall poorer performance in fluid intelligence and memory over the study duration, with no difference in rates of change. The models were unaffected by MHT use and brain volume measures. Conclusions Perimenopause and post-menopause are associated with cognitive changes. Psychomotor speed appears to be most sensitive to the menopause transition, whereas other cognitive functions may be less susceptible. More sensitive structural or functional brain imaging may be required to understand the underlying neural basis for these findings.
The three-dimensional transition stages over the NACA-0009 airfoil at Reynolds numbers of several ten thousand

This experimental study addresses late transition stages over a conventional airfoil at Reynolds numbers of several ten thousands. The study is based on extensive volumetric flow measurements using constant temperature anemometry. This technique provided both the time-averaged description of the flow field in the vicinity of the wing and the high fidelity spectral analysis inside the separated boundary layer. Large cellular flow structures were observed above the wing. They resemble the stall cells at Reynolds numbers of a few hundred thousands and separation cells at Reynolds numbers of a few hundred. It is shown that most of the energy of the velocity fluctuations within the boundary layer over the forward half of the wing is concentrated in the low-frequency range of the spectrum, where the chord-based Strouhal number is small as compared with unity.
Assimilation of lake water surface temperature observations using an extended Kalman filter

A new extended Kalman filter (EKF)-based algorithm to assimilate lake water surface temperature (LWST) observations into the lake model/parameterisation scheme Freshwater Lake (FLake) has been developed. The data assimilation algorithm has been implemented into the stand-alone offline version of FLake. The mixed and non-mixed regimes in lakes are treated separately by the EKF algorithm. The timing of the ice period is indicated implicitly: no ice if water surface temperature is measured. Numerical experiments are performed using operational in-situ observations for 27 lakes and merged observations (in-situ plus satellite) for 4 lakes in Finland. Experiments are analysed, potential problems are discussed, and the role of early spring observations is studied. In general, results of experiments are promising: (1) the impact of observations (calculated as the normalised reduction of the LWST root mean square error comparing to the free model run) is more than 90% and (2) in cross-validation (when observations are partly assimilated, partly used for validation) the normalised reduction of the LWST error standard deviation is more than 65%. The new data assimilation algorithm will allow prognostic variables in the lake parameterisation scheme to be initialised in operational numerical weather prediction models and the effects of model errors to be corrected by using LWST observations.
General equivalent circuit for intermediate band devices: Potentials, currents and electroluminescence

A general model to describe the operation of intermediate band solar cells (IBSCs), incorporating a significant number of physical effects such as radiative coupling between bands, and impact ionization and Auger recombination mechanisms, is presented in equivalent circuit form. The model is applied to IBSC prototypes fabricated from InAs quantum dots structures to determine the value of the circuit elements involved. The analysis shows evidence of splitting between the conduction and intermediate band quasi-Fermi levels, one of the fundamental working hypotheses on which operation of the IBSC depends. The model is also used to discuss the limitations and potential of this type of cell.
Modelling interstellar extinction. I: Porous grains

Discussion de quelques methodes de calcul de l'extinction interstellaire par des grains poreux de silicate. Il est demontre que ces grains produisent un renforcement de l'extinction dans l'infrarouge, l'ultraviolet et l'ultraviolet lointain, cet effet pouvant etre utilise pour reduire l'abondance en carbone requis pour l'ajustement a l'extinction interstellaire moyenne. Les implications des grains poreux dans le milieu interstellaire sont discutees en relation avec la chimie des surfaces, la polarisation de la lumiere et leur evolution dynamique
Study of Consumers’ Purchase Intentions on Community E-commerce Platform with the SOR Model: A Case Study of China’s “Xiaohongshu” App

As e-commerce flourishes, a new model known as community e-commerce has sprung up, which gathers users of the same interests and values and provides precise content marketing for specific groups, to satisfy the various demands of customers. Studying the influencing factors of community e-commerce platforms on the purchasing willingness of customers can offer valuable references for a healthily developed community e-commerce. On the basis of the SOR model, this work establishes a structural model of the consumers’ purchase intentions on community e-commerce platforms. Citing the Xiaohongshu application, an analysis is conducted, using structural-equation modeling and questionnaire. The results show that the perceived value is positively influenced by the product features, content marketing, and community factors which prod customers to be ready to purchase. Based on the research conclusions, management suggestions are proposed, including building products with utmost cost–performance, emphasizing precise content-marketing, creating an active atmosphere in the community, and establishing the social responsibility of platforms, etc.
Large‐eddy simulation of a bluff‐body flow on unstructured grids

Large‐eddy simulations of the flow around a square cylinder on coarse unstructured grids are investigated. The numerical solver is based on a mixed finite‐volume/finite‐element formulation. A modified Roe scheme is employed for convective terms, together with the MUSCL method to increase the order of accuracy. An upwinding parameter, γs, directly controls the numerical diffusion, which is formed of fourth‐order space derivatives. The eddy‐viscosity Smagorinsky model and its dynamic version are used for the subgrid scale (SGS) terms in the LES equations. The effects of upwinding, and, in particular, the interaction between SGS and numerical dissipation, are studied by varying the value of γs. The sensitivity to grid inhomogeneity and to SGS modelling are also investigated. Results are compared to those obtained in other LES in the literature and to experimental data. Copyright © 2002 John Wiley & Sons, Ltd.
Exit flows from highly porous media

This paper presents laser velocimetry measurements of the streamwise component of mean velocities and turbulence intensities measured downstream from the exit plane of porous ceramic foams through which air is flowed. The recent development and commercial availability of porous ceramic foams has lead to their application in many fields. Their uses have extended to combustion, high‐temperature fluid filtering, biotechnology, and as support matrix for catalysts. These applications have created an interest in their pore scale fluid mechanics, both within the porous matrix and along surfaces open to flow. One emerging application is porous ceramic burners which combust liquid or gaseous fuels within the pore matrix or along the surface of the ceramic. The ceramic foams have pore sizes ranging from 4 to 12 pores per cm (ppcm) and porosities of 85%. Mean velocities between 0.3 and 1.5 m/s were examined. Radial distributions of mean velocities show a jet‐like structure through the pores, with local mean velociti.
Ab-initio calculations of the electronic and magnetic structures of Co2Cr1−xMnxAl alloys

Density functional theory based on full-potential linearized augmented plane-wave method is used to investigate the structural, electronic, and magnetic properties of Co2Cr1−xMnxAl (x = 0, 0.25, 0.5, 0.75, 1) alloys. The parent full Heusler alloy (Co2CrAl) exhibits the least total magnetic moment of 3 μB/f.u. For the alloyed structures, this value is found to increase as a function of Mn concentration. The magnitudes of Co2Cr1−xMnxAl total magnetic moment show a trend consistent with the Slater–Pauling behavior. Co2CrAl full Heusler alloy reveals a half-metallic behavior with an indirect band gap along the Γ-X symmetry line. For the non-stoichiometric structures, the energy levels of the valence band shift to higher energies until they cross the Fermi level for x = 0.75 and 1.
Effect of rotating magnetic field intensity on structure and electrical and optical properties of GaInSb crystal grown with travelling heater method

Ga1−x In x Sb(0 < x < 1) crystal is a very promising substrate material, which can be used to fabricate a variety of high-performance infrared detectors and lasers by epitaxial growth. Herein, we prepared high quality Ga0.86In0. 14Sb crystal (25 mm diameter, 100 mm length) with travelling heater method applied rotating magnetic field (RMF), and revealed the effects of RMF intensity on structure and electrical and optical properties of the crystal. As the RMF intensity increased the crystal quality significantly improved, and the radial segregation of indium decreased from 0.258 to 0.031 mol% mm−1, in the center of the crystal. Similarly, the segregation of indium along the ingot between 20 to 80 mm, toward the traveling zone, decreased from 0.114 to 0.038 mol% mm−1. The dislocation density of GaInSb crystal ingot also decreased from 5.361 × 105 cm−2 to 5.295 × 103 cm−2. The electric properties of the crystal also improved, the carrier mobility increased to 1.902 × 103 from 1.358 × 103cm2 (V·s)−1, the resistivity decreased to 1.047 × 10−3 from 1.822 × 10−3 Ω·cm. Moreover, the infrared transmittance increased from 36% to 39%.
Suspect Screening of Chemicals in Hospital Wastewaters Using Effect-Directed Analysis Approach as Prioritization Strategy

The increasing number of contaminants in the environment has pushed water monitoring programs to find out the most hazardous known and unknown chemicals in the environment. Sample treatment-simplification methods and non-target screening approaches can help researchers to not overlook potential chemicals present in complex aqueous samples. In this work, an effect-directed analysis (EDA) protocol using the sea urchin embryo test (SET) as a toxicological in vivo bioassay was used as simplified strategy to identify potential unknown chemicals present in a very complex aqueous matrix such as hospital effluent. The SET bioassay was used for the first time here to evaluate potential toxic fractions in hospital effluent, which were obtained after a two-step fractionation using C18 and aminopropyl chromatographic semi-preparative columns. The unknown compounds present in the toxic fractions were identified by means of liquid chromatography coupled to a Q Exactive Orbitrap high-resolution mass spectrometer (LC-HRMS) and using a suspect analysis approach. The results were complemented by gas chromatography-mass spectrometry analysis (GC-MS) in order to identify the widest range of chemical compounds present in the sample and the toxic fractions. Using EDA as sample treatment simplification method, the number of unknown chemicals (>446 features) detected in the raw sample was narrowed down to 94 potential toxic candidates identified in the significantly toxic fractions. Among them, the presence of 25 compounds was confirmed with available chemical standards including 14 pharmaceuticals, a personal care product, six pesticides and four industrial products. The observations found in this work emphasize the difficulties in identifying potential toxicity drivers in complex water samples, as in the case of hospital wastewater.
Relative length of longest paths and cycles in 3-connected graphs

For a graph G, let p(G) denote the order of a longest path in G and c(G) the order of a longest cycle in G, respectively. We show that if G is a 3-connected graph of order n such that $\textstyle{\sum^{4}_{i=1}\,{\rm deg}_{G}\,x_{i} \ge {3\over2}\,n + 1}$ for every independent set {x1, x2, x3, x4}, then G satisfies c(G) ≥ p(G) - 1. Using this result, we give several lower bounds to the circumference of a 3-connected graph. © 2001 John Wiley & Sons, Inc. J Graph Theory 37: 137156, 2001
An improvement on paulson's procedure for selecting the poprlation with the largest mean from k normal populations with a common unknown variance

We obtain a tighter bound on the probability of making a correct selec tion in Paulson's procedure for selecting the normal population which has the largest population mean when the populations have a common unknown Tali ance. As a consequence, we are able to use a sharper value for the coristallt a∗ in Paulson's procedure. Simulation studies indicate that this leads to ari inlprovement in the expected number of stages to termination and expettetl total number of observations which is uniform in k, P∗s and σ/δ∗.