Miracle-dz/UniFAR-FTUs huggingface dataset:
Host Correlates of Avian Influenza Virus Infection in Wild Waterfowl of the Sacramento Valley, California

SUMMARY. Avian influenza viruses (AIVs) are distributed globally in members of the family Anatidae (waterfowl), and significant disease may occur when these viruses infect commercial poultry or humans. Early detection of AIV through surveillance of wild waterfowl is one measure to prevent future disease outbreaks. Surveillance efforts that are designed to account for host and environmental determinants of susceptibility to infection are likely to be most effective. However, these determinants have not been clearly delineated and may vary with location. Because some regions are at greater risk for AIV outbreaks, the factors that contribute to AIV infection of waterfowl in these areas are of interest. We investigated the prevalence of AIVs in hunter-killed waterfowl at wintering sites in California's Central Valley. Overall, AIV prevalence was 10.5% and, after controlling for age and sex, was greatest in northern shovelers (Spatula clypeata) and lowest in wood ducks (Aix sponsa). Overall, AIV prevalence was higher in females than in males, but this trend was driven by one sampling year and one waterfowl species (green-winged teal, Anas crecca). AIV prevalence in waterfowl was lower in samples collected from brackish wetlands compared with those collected from freshwater wetlands, suggesting that wetland type or other environmental factors contribute to AIV prevalence. This study adds to our understanding of the ecology of AIV infection in waterfowl and may assist in developing more efficient, targeted surveillance efforts for the detection of potentially harmful viruses circulating in North American waterfowl.
Physical and physiological benefits of small sided recreational handball in untrained males: relationship of body fat with aerobic capacity

Background and Study Aim. Exercise and Recreation play major role in promotion of health and fitness. Recreational exercise or sports can be useful in physically inactive population. The aim of study was to investigate the effect of recreational handball on body fat percent, VO2max, blood pressure and resting heart rate. Another purpose to find relationship between VO2max and body fat percentage. Material and Methods. Twenty-four students were randomized into intervention (n=14) and control group (n=10). The intervention group was asked to play recreational handball for 12 weeks. Handball training was held twice a week for 30 minutes duration. The Control group performed their normal routine. Aerobic capacity measured using single-stage treadmill test. Body fat was measured with Omron Body Fat Analyzer. T-test was employed to find a significant difference in the two groups. For the relationship in aerobic capacity and body fat, Pearson Product Moment Correlation was used. Results. We found significant difference in body percent (t22 = 2.031, P = 0.054). No significant difference was seen in aerobic capacity (t22 = 1.578, P = 0.129), systolic blood pressure (t22 = -1.637, P = 0.116), diastolic blood pressure (t22 = -1.562, P = 0.133) and resting heart rate (t22 = 1.620, P = 0.120). Significant relationship was established between body percent and aerobic capacity (r= -5.23, n=14, p= 0.055) in the intervention group. Conclusions. It can be concluded that recreational handball was useful in eliciting good response with respect to reduction of body fat in intervention group. However, recreation handball sessions were not effective in reducing blood pressure, resting heart and aerobic capacity among untrained males. A significant relationship was observed in VO2max and percent body fat.
On the Benefits of Multiple Gossip Steps in Communication-Constrained Decentralized Federated Learning

Federated learning (FL) is an emerging collaborative machine learning (ML) framework that enables training of predictive models in a distributed fashion where the communication among the participating nodes are facilitated by a central server. To deal with the communication bottleneck at the server, decentralized FL (DFL) methods advocate rely on local communication of nodes with their neighbors according to a specific communication network. In DFL, it is common algorithmic practice to have nodes interleave (local) gradient descent iterations with gossip (i.e. averaging over the network) steps. As the size of the ML models grows, the limited communication bandwidth among the nodes does not permit communication of full-precision messages; hence, it is becoming increasingly common to require that messages be {\em lossy, compressed} versions of the local parameters. The requirement of communicating compressed messages gives rise to the important question: {\em given a fixed communication budget, what should be our communication strategy to minimize the (training) loss as much as possible} In this paper, we explore this direction, and show that in such compressed DFL settings, there are benefits to having {\em multiple} gossip steps between subsequent gradient iterations, even when the cost of doing so is appropriately accounted for, e.g. by means of reducing the precision of compressed information. In particular, we show that having $\O(\log\frac{1}{\epsilon})$ gradient iterations {with constant step size} - and $\O(\log\frac{1}{\epsilon})$ gossip steps between every pair of these iterations - enables convergence to within $\epsilon$ of the optimal value for a class of non-convex problems that arise in the training of deep learning models, namely, smooth non-convex objectives satisfying Polyak-\L{}ojasiewicz condition. Empirically, we show that our proposed scheme bridges the gap between centralized gradient descent and DFL on various machine learning tasks across different network topologies and compression operators.
Examining the Relationships Between Air Pollutants and the Incidence of Acute Aortic Dissection with Electronic Medical Data in a Moderately Polluted Area of Northwest China

This paper explored whether air pollutants influenced acute aortic dissection (AAD) incidence in a moderately polluted area. A total of 494 AAD patients’ data from 2013 to 2016 were analyzed. The results showed that AAD had the strongest associations with P M 10 , S O 2 , N O 2 , C O , and O 3 on the day before an AAD incident (lag1) and with P M 2.5 two days before an incident (lag2) in single-pollutant model. In the three-pollutant model, P M 10 was associated with the highest risk of adverse effects (RR = 1.37, 95% CI: 1.22, 1.53), whereas P M 2.5 was associated with the lowest risk (RR = .83, 95% CI: .79, .88). Both P M 2.5 and P M 10 were affected by season, and S O 2 was significantly different between heating and non-heating seasons as well. This study revealed significant associations between short-term P M 2.5 , P M 10 , and S O 2 exposure and daily AAD incidence, showing that P M 10 and S O 2 were strong predictors of AAD incidence in a moderately polluted area.
Comparing the steering performances of skid- and Ackermann-steered vehicles

Abstract Skid steering has advantages for military armoured vehicles because it gives greater internal hull volume and improved manoeuvrability. The steering performance of an 18t 6×6 skid-steered vehicle is analysed and compared with that of a similar Ackermann-steered vehicle. The basic properties of the double-differential mechanism used for steering most modern skid-steered vehicles are analysed. A tyre model is used that enables the force characteristics at combined slip to be established from the relatively small amount of pure slip data that are available for truck-sized tyres. A spreadsheet analysis is used for solving the equations of motion. This shows that the skid-steered vehicle is generally neutral to oversteer whereas the Ackermann-steered vehicle is understeer. The skid-steered vehicle is also shown to require more power when cornering because of the power required by the steering mechanism. This will increase the fuel consumption and reduce the range of the skid-steered vehicle.
COMPUTATION OF BEARING CAPACITY FACTORS USING FINITE ELEMENTS

The Paper shows how finite elements, in conjunction with elasto-plastic theory, can give excellent collapse load predictions for footings resting on c-φ soils. The problem is approached by considering each of the three components of bearing capacity appearing in Terzaghi's classical equation. The results show that the contributions to bearing capacity of the Nc and Nq terms can be computed with confidence and economy. The NT term, which is theoretically less sound than the other two, is also computed to be in close agreement with published approximate solutions but takes more computing effort. This is shown to be particularly so when the soil friction angle is increased. The superposition assumption in Terzaghi's equation is assessed using finite elements. The conservative nature of the equation is confirmed, with the inherent error shown to occur solely because of non-linearities in the Nγ term. It is thought that the techniques used in obtaining the results given may be applied with confidence to a wide.
Bayesian Parametric Modeling of Time to Tuberculosis Co-Infection of HIV/AIDS Patients Under Antiretroviral Therapy Treatment at Jimma University Medical Center, Ethiopia

Background: Tuberculosis is the most common opportunistic infection among HIV/AIDS patients, including those following Antiretroviral Therapy treatment. The risk of Tuberculosis infection is higher in people living with HIV/AIDS than in people who are free from HIV/AIDS. Many studies focused on prevalence and determinants of Tuberculosis in HIV/AIDS patients without taking into account the censoring aspects of the time to event data. Therefore, this study was undertaken with aim to model time to Tuberculosis co-infection of HIV/AIDS patients following Antiretroviral Therapy treatment using Bayesian parametric survival models.Methods: A data of a retrospective cohort of HIV/AIDS patients under Antiretroviral Therapy treatment follow-up from January 2016 to December 2020 until Tuberculosis was clinically diagnosed or until the end of the study was collected from Antiretroviral Therapy treatment center of Jimma University Medical Center, Ethiopia. In order to identify the risk factors which have association with Tuberculosis co-infection survival time, Bayesian parametric Accelerated failure time survival models were fitted to the data using Integrated Nested Laplace Approximation methodology.Results: About 26.37% of the study subjects had been co-infected with tuberculosis during the study period. Among the parametric Accelerated failure time models, the Bayesian log-logistic Accelerated failure time model was found to be the best fitting model for the data.Conclusions: Tuberculosis co-infection survival time was significantly associated with place of residence, smoking, drinking alcohol, family size, WHO clinical stages, functional status, CD4 count, BMI and hemoglobin level. The finding of this study provide timely information on the risk factors associated with TB co-infection survival time for healthy policy makers and planners.
Response analysis of flexible MDF systems for multiple‐support seismic excitations

Two practical approaches, response spectrum and time-history methods, are developed to evaluate the response of flexible multi-degree-of-freedom (MDF) systems, notably long-span bridges, to multiple-support seismic excitations. For practical convenience, ground motions within a group of adjacent supports on continuous soil or rock are assumed to be uniform and synchronized, while those of different groups are treated as non-uniform and uncorrelated. The response spectrum analysis is extended to include the cross-correlation of modal responses, which prove important when closely spaced modal frequencies exist. An example of the significance of multiple-support excitations is illustrated by application to a suspension bridge. Qualitatively comparable effects can be expected for other bridges of similar type or dimensions.
Long-Term Follow-Up of Device-Assisted Clampless Off-Pump Coronary Artery Bypass Grafting Compared with Conventional On-Pump Technique

Study objective: To evaluate the long-term outcomes of clampless off-pump coronary artery bypass grafting (C-OPCAB) compared with conventional on-pump double clamping coronary artery bypass grafting (C-CABG). Methods: From October 2006 to December 2011, 366 patients underwent isolated coronary artery bypass grafting. After propensity score matching of preoperative variables, 143 pairs were selected who received C-OPCAB with the use of device-assisted PAS-Port proximal venous graft anastomoses or C-CABG, performed by the same surgeon experienced in both techniques. Data of the two groups of patients were retrospectively analyzed up to 14 years of follow-up. Results: As compared with C-OPCAB, in the C-CABG patients, the performed number of grafts per patient was higher (2.9 ± 0.5 vs. 2.6 ± 0.6, p-value 0.0001). At 14 years, overall survival, including in-hospital death, was 64 ± 4.7% for the C-OPCAB vs. 55 ± 5.5% for the C-CABG, freedom from overall MACCEs 51 ± 6.2% vs. 41 ± 7.7%, and from late cardiac death 94 ± 2.4% vs. 96 ± 2.2% (p-value not significant, for all comparisons). No significant statistical differences were observed in the actual rates of adverse events during follow-up. Independent predictors of survival were advanced age at operation (p-value 0.001) and a lower mean value of preoperative left ventricular ejection fraction (p-value 0.015). Conclusions: Our single-center study analysis suggests that clampless OPCAB using device-assisted proximal anastomoses proved to be not inferior to double-clamping CABG in the long-term follow-up, provided that involved surgeons are familiar with both techniques. These conclusions are supported by a large and long-term follow-up period, eliminating potential bias, i.e., by means of the propensity score matching and analyzing single-surgeon experience.
Comparison of Quantity Characteristics and Antioxidant Potentials of Different Tea Extracts for In-flight Beverage

: Tea is a famous non-alcoholic beverage worldwide. Various types of tea are prepared to meet the demand of different people. Among the various tea types, green tea (GTE), black tea (BTE), and Pu-erh tea (PEE) are major ones. The objective of this study was to investigate the physicochemical characteristics and antioxidant potential of three tea extracts to be considered as an in-flight beverage. The pH (5.62) of GTE was significantly highest whereas the titratable acidity (0.18 g/100 mL) was significantly highest in BTE. The highest lightness value was found in GTE (87.12) and redness and yellowness in BTE (30.15 and 85.32). The amount of total free amino acid was significantly highest in PEE (174.52  g/ mL), followed by GTE (31.28  g/ mL) and BTE (24.98  g/ mL). Similarly, the antioxidant potential of PEE was significantly high among the three tea extracts. The results indicated that Pu-erh tea could be a good in-flight beverage.
Symbolic Control Design of an Artificial Pancreas for Type-2 Diabetes

Diabetes is a widespread disease characterized by chronic hyperglycemia so that diabetic individuals usually require the administration of exogenous insulin for survival. As a consequence, in the context of the so-called artificial pancreas, many glucose control methods have been presented in the last few years. In this work, we focus on type-2 diabetes and propose a novel model-based glucose control technique based on the use of symbolic models, which are finite approximations of complex dynamical systems. This framework allows taking into account nonlinearities and delays in the dynamics, uncertainties, and input bounds, as well as nonidealities coming from the interaction between physical plant and digital environment. The methodology is extensively validated over a virtual patient model, broadly accepted as a substitute to animal trials in the preclinical testing of closed-loop glucose control strategies. The results show the effectiveness and the robustness of the approach.
One Versus All for Deep Neural Network for Uncertainty (OVNNI) Quantification

Deep neural networks (DNNs) are powerful learning models, yet their results are not always reliable. This drawback results from the fact that modern DNNs are usually overconfident, and consequently their epistemic uncertainty cannot be straightforwardly characterized. In this work, we propose a new technique to quantify easily the epistemic uncertainty of data. This method consists in mixing the predictions of an ensemble of DNNs trained to classify One class versus All the other classes (OVA) with predictions from a standard DNN trained to perform All versus All (AVA) classification. First of all, the adjustment provided by the AVA DNN to the score of the base classifiers allows for a more fine-grained inter-class separation. Moreover, the two types of classifiers enforce mutually their detection of out-of-distribution (OOD) samples, circumventing entirely the requirement of using such samples during training. The additional cost involved by the construction of the ensemble is offset by the ease of use of our proposed strategy and by its enhanced generalization potential, as it does not bind its performance in a given context to specific OOD datasets. The extensive experiments confirm the wide applicability of our approach, and our method achieves state of the art performance in quantifying OOD data across multiple datasets and architectures while requiring little hyper-parameter tuning.
Chance-Constrained Optimization-Based Parameter Estimation for Muskingum Models

The development of a chance-constrained optimization-based model for Muskingum model parameter estimation is presented. The desired Muskingum model parameters are to be useful to give the flood forecast in terms of expected flood for given limits of tolerance and probability of occurrence. When errors of observation occur, an error term is added to a mean flow to give the actual flow. The developed model minimizes the sum of squares of difference between the actual observed and computed outflows in order to determine the Muskingum model parameters. The constraints are the chance-constrained Muskingum flow routing equations. The first-order second moment method of chance-constrained optimization is used to develop the optimization model. The developed model is demonstrated for four scenarios of Muskingum model parameter estimation. The results show that, given the allowable limits of error in Muskingum model parameters, the developed model has a capability to give expected values of Muskingum model parameters when the historic data that are used for the parameter estimation process contain a specified amount of observation errors and obey a specified probability distribution. The chance-constrained optimization-based model for Muskingum model parameter estimation results into Muskingum model parameters that can give flood forecasts such that the forecasted flood allows the provision of better flood damage mitigation facilities.
Realization of tunable active floating inductance simulators

In this paper, new topologies for realizing lossless and lossy floating inductors using current controlled conveyors (CCCIIs) and single capacitor are presented. The proposed inductance simulators can be tuned electronically by changing the biasing currents of the active elements. The proposed lossless floating inductance simulator is used to construct a fifth-order low-pass filter. The frequency response of the simulated and ideal filter is compared using the SPICE simulation program. Moreover, the lossless floating inductor is used to construct a second-order voltage-mode band-pass filter practically. The ideal simulated and experimental responses of the band-pass filter are included.
Retinal Progression Biomarkers of Early and Intermediate Age-Related Macular Degeneration

Early and intermediate AMD patients represent a heterogeneous population with an important but variable risk of progression to more advanced stages of the disease. The five-year progression from early and intermediate AMD to late disease is known to range from 0.4% to 53%. This wide variation explains the particular interest in searching predictive AMD biomarkers. Clinical parameters such as drusen size, presence of pigmentary abnormalities, and fellow eye status were, traditionally, the more important predictive elements. Multimodal retinal assessment (Color Fundus Photography, Optical Coherence Tomography, Optical Coherence Angiography and Fundus Autofluorescence) is providing new and accurate image biomarkers, useful in research and in daily practice. If individual progression risk could be anticipated, then management plans should be adapted accordingly, considering follow-up intervals and therapeutic interventions. Here, we reviewed the most important image progression biomarkers of early and intermediate AMD with relevant interest in clinical practice.
Detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its first variants in fourplex real-time quantitative reverse transcription-PCR assays

The early diagnosis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections is required to identify and isolate contagious patients to prevent further transmission of SARS-CoV-2. In this study, we present a multitarget real-time TaqMan reverse transcription PCR (rRT-PCR) assay for the quantitative detection of SARS-CoV-2 and some of its circulating variants harboring mutations that give the virus a selective advantage. Seven different primer-probe sets that included probes containing locked nucleic acid (LNA) nucleotides were designed to amplify specific wild-type and mutant sequences in Orf1ab, Envelope (E), Spike (S), and Nucleocapsid (N) genes. Furthermore, a newly developed primer-probe set targeted human β2-microglobulin (B2M) as a highly sensitive internal control for RT efficacy. All singleplex and fourplex assays detected ≤ 14 copies/reaction of quantified synthetic RNA transcripts, with a linear amplification range of nine logarithmic orders. Primer-probe sets for detection of SARS-CoV-2 exhibited no false-positive amplifications with other common respiratory pathogens, including human coronaviruses NL63, 229E, OC43, and HKU-1. Fourplex assays were evaluated using 160 clinical samples positive for SARS-CoV-2. Results showed that SARS-CoV-2 viral RNA was detected in all samples, including viral strains harboring mutations in the Spike coding sequence that became dominant in the pandemic. Given the emergence of SARS-CoV-2 variants and their rapid spread in some populations, fourplex rRT-PCR assay containing four primer-probe sets represents a reliable approach to allow quicker detection of circulating relevant variants in a single reaction.
SOCIO-ECONOMIC AND PSYCHOLOGICAL CORRELATES OF FASHION CONSCIOUSNESS OF CONSUMERS

Fashion conscious people allocate a large part of their budget on a latest fashion. The present study assessed the socio-economic and psychological factors that play significant role in fashion consciousness. A convenient sample of 200 individuals (men=100 and women=100) of age between 22 and 44 years from Multan, Pakistan was taken to study the correlates of fashion consciousness. The estimates of ordinary least square showed that education, monthly income, materialism, and media exposure had significant positive impact, and price consciousness had significant negative impact on fashion consciousness of the sample, which partially support consumption theories (e.g., Absolute Income Hypothesis’ and ‘Relative Income Hypothesis). The study has implications for both consumers and producers. Key Words: Fashion consciousness, materialism, price consciousness, absolute income hypothesis, relative income hypothesis