Miracle-dz/UniFAR-FTUs huggingface dataset:
Genetic Differentiation and Migration Fluxes of Viruses from Melon Crops and Crop Edge Weeds

It has been reported that about half of the emerging diseases affecting plants are caused by viruses. Alternative hosts often play critical roles in virus emergence as virus reservoirs, bridging host species that are otherwise unconnected and/or favoring virus diversification. ABSTRACT Weeds surrounding crops may act as alternative hosts, playing important epidemiological roles as virus reservoirs and impacting virus evolution. We used high-throughput sequencing to identify viruses in Spanish melon crops and plants belonging to three pluriannual weed species, Ecballium elaterium, Malva sylvestris, and Solanum nigrum, sampled at the edges of the crops. Melon and E. elaterium, both belonging to the family Cucurbitaceae, shared three virus species, whereas there was no virus species overlap between melon and the other two weeds. The diversity of cucurbit aphid-borne yellows virus (CABYV) and tomato leaf curl New Delhi virus (ToLCNDV), both in melon and E. elaterium, was further studied by amplicon sequencing. Phylogenetic and population genetics analyses showed that the CABYV population was structured by the host, identifying three sites in the CABYV RNA-dependent RNA polymerase under positive selection, perhaps reflecting host adaptation. The ToLCNDV population was much less diverse than the CABYV one, likely as a consequence of the relatively recent introduction of ToLCNDV in Spain. In spite of its low diversity, we identified geographical but no host differentiation for ToLCNDV. Potential virus migration fluxes between E. elaterium and melon plants were also analyzed. For CABYV, no evidence of migration between the populations of the two hosts was found, whereas important fluxes were identified between geographically distant subpopulations for each host. For ToLCNDV, in contrast, evidence of migration from melon to E. elaterium was found, but not the other way around. IMPORTANCE It has been reported that about half of the emerging diseases affecting plants are caused by viruses. Alternative hosts often play critical roles in virus emergence as virus reservoirs, bridging host species that are otherwise unconnected and/or favoring virus diversification. In spite of this, the viromes of potential alternative hosts remain largely unexplored. In the case of crops, pluriannual weeds at the crop edges may play these roles. Here, we took advantage of the power of high-throughput sequencing to characterize the viromes of three weed species frequently found at the edges of melon crops. We identified three viruses shared by melon and the cucurbit weed, with two of them being epidemiologically relevant for melon crops. Further genetic analyses showed that these two viruses had contrasting patterns of diversification and migration, providing an interesting example on the role that weeds may play in the ecology and evolution of viruses affecting crops.
A shallow deep learning approach to classify skin cancer using down-scaling method to minimize time and space complexity

The complex feature characteristics and low contrast of cancer lesions, a high degree of inter-class resemblance between malignant and benign lesions, and the presence of various artifacts including hairs make automated melanoma recognition in dermoscopy images quite challenging. To date, various computer-aided solutions have been proposed to identify and classify skin cancer. In this paper, a deep learning model with a shallow architecture is proposed to classify the lesions into benign and malignant. To achieve effective training while limiting overfitting problems due to limited training data, image preprocessing and data augmentation processes are introduced. After this, the ‘box blur’ down-scaling method is employed, which adds efficiency to our study by reducing the overall training time and space complexity significantly. Our proposed shallow convolutional neural network (SCNN_12) model is trained and evaluated on the Kaggle skin cancer data ISIC archive which was augmented to 16485 images by implementing different augmentation techniques. The model was able to achieve an accuracy of 98.87% with optimizer Adam and a learning rate of 0.001. In this regard, parameter and hyper-parameters of the model are determined by performing ablation studies. To assert no occurrence of overfitting, experiments are carried out exploring k-fold cross-validation and different dataset split ratios. Furthermore, to affirm the robustness the model is evaluated on noisy data to examine the performance when the image quality gets corrupted.This research corroborates that effective training for medical image analysis, addressing training time and space complexity, is possible even with a lightweighted network using a limited amount of training data.
Diffusion Coefficients for Fast Reactor Hexagonal Assemblies

A consistent model for the calculation of fast reactor assembly diffusion coefficients is presented. Allowance is made for the treatment of both sodiumfilled and sodium-voided lattices, with the same approximation applied, which is essential for the study of the sodium-voiding effect. The hexagonal steel tube is also taken into account. The formalism is implemented in the ASDIC (Assembly Diffusion Coefficients) program. Numerical results and comparisons with results of other models are given.
Presented and prioritizing waste management strategies using SWOT and QSPM approach in two private hospitals in Yazd in 2021

ABSTRACT Background This study aimed to present a strategic waste management in two private hospitals in Yazd using models of the strengths, weaknesses, opportunities, and threats (SWOT) and quantitative strategic planning matrix (QSPM). Methods The strengths, weaknesses, opportunities, and threats of the organization was identified according to existing documents and expert team. The internal and external factors were identified by internal factor evaluation (IFE) and external factor evaluation (EFE) matrices. The strategies to improve waste management in two hospitals were presented by comparing internal and external factors. Finally, the attractiveness table was compiled and weighted using the QSPM method to prioritize the strategies. Results The results demonstrated that 24 strengths, 30 weaknesses, 16 opportunities, and 22 threats were identified. The final score of internal and external factors for hospital A and B were (X: 2.37, Y:1.88) and (X: 2.37, Y: 2.01), respectively. Based on the results, 12 strategies were presented. Finally, the strategy of “the improvement of green management indicators” was implemented as a priority according to QSPM matrix. Conclusion The result of this study duplicated that using the QSPM and SWOT models is assist to present viable strategies to improve the health-care waste management.
Sensitivity analysis of the unconfoundedness assumption in observational studies

In observational studies, the estimation of a treatment effect on an outcome of interest is often done by controlling on a set of pre-treatment characteristics (covariates). This yields an unbiased estimator of the treatment effect when the assumption of unconfoundedness holds, that is, there are no unobserved covariates affecting both the treatment assignment and the outcome. This is in general not realistically testable. It is, therefore, important to conduct an analysis about how sensitive the inference is with respect to the unconfoundedness assumption. In this paper we propose a procedure to conduct such a Bayesian sensitivity analysis, where the usual parameter uncertainty and the uncertainty due to the unconfoundedness assumption can be compared. To measure departures from the assumption we use a correlation coefficient which is intuitively comprehensible and ensures that the results of sensitivity analyses made on different evaluation studies are comparable. Our procedure is applied to the Lalonde data and to a study of the effect of college choice on income in Sweden.
SARS-CoV-2 versus other minor viral infection on kidney injury in asymptomatic and mildly symptomatic patients

ABSTRACT Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and has become a global pandemic since December 2019. Most of the patients are mild or asymptomatic and recovered well as those suffered from other respiratory viruses. SARS-CoV-2 infection is supposed to demonstrate more sequelae. Acute kidney injury (AKI) is common among COVID-19 patients and is associated with disease severity and outcomes. Only a few studies focused on a detailed analysis of kidney damage in asymptomatic or mildly symptomatic COVID-19 patients. Whether any minor viral infection is likely to exhibit similar minor effect on renal function as COVID-19 is still unclear, and the definite pathophysiology of viral invasion is not fully understood. Currently, the proposed mechanisms of AKI include direct effects of virus on kidney, dysregulated immune response, or as a result of multi-organs failure have been proposed. This study will discuss the difference between COVID-19 and other viruses, focusing on proposed mechanisms, biomarkers and whether it matters with clinical significance.
COVID-19 Death Exposure among Adults in the United States

As of May 17, 2022, more than a million deaths due to COVID-19 have been recorded in the US. For each COVID-19 death, there are an estimated nine bereaved family members and an unknown number of bereaved friends. This study aimed to assess the correlates of self-reported COVID-19 death exposure (i.e., loss of a close friend or family member) among US adults using online survey data (n = 1,869) collected between September 17, 2021 and October 3, 2021. One in four US adults in this national sample reported the loss of a close friend or family member due to COVID-19. The odds of losing a close friend or family member due to COVID-19 death were greater for those age 60 or older, all minoritized racial/ethnic groups except for Asian American respondents, married/coupled respondents, those who had foregone care due to cost in the past year, and those who reported a COVID-19 infection.
A review on the recent progress, opportunities, and challenges of 4D printing and bioprinting in regenerative medicine

Abstract Four-dimensional (4 D) printing is a novel emerging technology, which can be defined as the ability of 3 D printed materials to change their form and functions. The term ‘time’ is added to 3 D printing as the fourth dimension, in which materials can respond to a stimulus after finishing the manufacturing process. 4 D printing provides more versatility in terms of size, shape, and structure after printing the construct. Complex material programmability, multi-material printing, and precise structure design are the essential requirements of 4 D printing systems. The utilization of stimuli-responsive polymers has increasingly taken the place of cell traction force-dependent methods and manual folding, offering a more advanced technique to affect a construct's adjusted shape transformation. The present review highlights the concept of 4 D printing and the responsive bioinks used in 4 D printing, such as water-responsive, pH-responsive, thermo-responsive, and light-responsive materials used in tissue regeneration. Cell traction force methods are described as well. Finally, this paper aims to introduce the limitations and future trends of 4 D printing in biomedical applications based on selected key references from the last decade.
Adaptive output feedback tracking control of stochastic nonlinear systems with dynamic uncertainties

In this paper, adaptive output feedback tracking control is developed for a class of stochastic nonlinear systems with dynamic uncertainties and unmeasured states. Neural networks are used to approximate the unknown nonlinear functions. K‐filters are designed to estimate the unmeasured states. An available dynamic signal is introduced to dominate the unmodeled dynamics. By combining dynamic surface control technique with backstepping, the condition in which the approximation error is assumed to be bounded is avoided. Using It ô formula and Chebyshev's inequality, it is shown that all signals in the closed‐loop system are bounded in probability, and the error signals are semi‐globally uniformly ultimately bounded in mean square or the sense of four‐moment. Simulation results are provided to illustrate the effectiveness of the proposed approach. Copyright © 2014 John Wiley & Sons, Ltd.
Detection of a ZnSe secondary phase in coevaporated Cu2ZnSnSe4 thin films

Cu2ZnSnSe4 (CZTSe) thin films are grown by coevaporation. Composition depth profiles reveal that a Zn rich phase is present at the CZTSe/Mo interface. Raman measurements on the as grown films are used to study the near surface region and the CZTSe/Mo interface, after mechanically removing the thin film from the Mo coated glass. These measurements provide direct experimental evidence of the formation of a ZnSe phase at the CZTSe/Mo interface. While the Raman spectra at the surface region are dominated by CZTSe modes, those measured at the CZTSe/Mo interface are dominated by ZnSe and MoSe2 modes.
Suicidal Ideation and Risky Behavior are Related through Impulsivity and Low Wish to Live

Abstract Objective Numerous studies have found support for the relationship between suicide and risky behavior. However, few studies have examined factors that may help explain the relationship between suicidal ideation (SI) and risky behavior. This preregistered study examined the relationship between SI and risky behavior and whether there is an indirect relationship through hopelessness, impulsivity, and low wish to live. These factors were selected due to their relationships with both SI and risky behavior. Methods Participants recruited from Amazon Mechanical Turk completed measures of SI, risky behavior, hopelessness, impulsivity, and wish to live. Consistent with our preregistered methods, we analyzed data from 180 participants with valid data. Indirect effects were evaluated via bootstrapping with 5000 resamples of the a path x b path product. Results Consistent with prior work, we found a significant positive association between SI and frequency of risky behavior (r = .49). We found significant indirect effects of SI on risky behavior through impulsivity and wish to live but not through hopelessness. Conclusion SI and risky behavior are associated with each other through impulsivity and wish to live. Though future longitudinal research is needed to determine causality, this has important implications for models of suicidal thoughts and behaviors and their relationship with risky behavior. The potential of future orientation to explain the results is discussed.
Applied Geophysics for Managed Aquifer Recharge

Increasing water stress and decreasing supplies caused by growth and climate variability have expanded demand for managed aquifer recharge (MAR) projects to provide water supply resilience. Some of the most important factors in determining the performance of a MAR project include site selection, subsurface hydrogeologic characteristics and associated properties of the storage zone. Costs for invasive subsurface investigations to address these factors have slowly increased over the past two decades, with drilling costs increasing dramatically by as much as 30% or more since COVID‐19 hit, a result of supply chain issues, steel prices, and manpower challenges. This paper provides a high‐level review of major geophysical methods that have become more mainstream over the past decade or two to supplement invasive subsurface investigations and are very cost effective when compared to drilling boreholes and installing wells, which provide only point data. The more commonly used surface geophysical methods include ground‐based and airborne time‐domain electromagnetic methods (TEM), electrical resistivity, and seismic reflection. Airborne TEM methods (AEM) collect data very quickly, avoiding ground‐based access constraints, and land‐based methods are especially efficient using towed arrays. Electrical resistivity measurements provide resolution comparable to TEM but require more time than towed methods. Seismic reflection surveys are more expensive than other methods but typically have a much greater depth of penetration and can provide high resolution information on aquifer geometry, geology, and faults. Borehole geophysics is one of the more common methods used in MAR, providing near hole formation data and ground truths surface geophysics.
Univariate nonlinear time series models

In this paper developments in the analysis of univariate nonlinear time series are considered. First a number of commonly used nonlinear models are presented. The next section is devoted to methods of testing linearity, which is an important part of nonlinear model building. Techniques of modelling nonlinear series within a predetermined family of models are discussed thereafter. Forecasting with nonlinear models also has its own section. A brief set of final remarks closes the chapter.
Realization of a VCO for WLAN applications using 0.35 μm‐siGe BICMOS technology

In this article, a 4.5–5.8 GHz, −Gm LC voltage controlled oscillator (VCO) for IEEE 802.11a standard is presented. The circuit is designed with Austria MicroSystems 0.35 μm SiGe BiCMOS process that includes high‐speed SiGe heterojunction bipolar transistors (HBTs). According to measurement results, phase noise is −102.3 dBc/Hz at 1 MHz offset from 5 GHz carrier frequency. A linear, 1300 MHz tuning range is obtained utilizing accumulation‐mode varactors. Phase noise is relatively low because of the advantage of differential tuning concept. Output power of the fundamental frequency changes between −1.6 and 0.9 dBm depending on the tuning voltage. Average second and third harmonic levels are −25 and −41 dBm, respectively. The circuit draws 14 mA DC current from 3.3 V supply including buffer circuits leading to a total power dissipation of 46.2 mW. The prototype VCO occupies an area of 0.6 mm2 on Si substrate, including DC and RF pads. © 2008 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2008.
Towards Soft Wearable Strain Sensors for Muscle Activity Monitoring

The force-generating capacity of skeletal muscle is an important metric in the evaluation and diagnosis of musculoskeletal health. Measuring changes in muscle force exertion is essential for tracking the progress of athletes during training, for evaluating patients’ recovery after muscle injury, and also for assisting the diagnosis of conditions such as muscular dystrophy, multiple sclerosis, or Parkinson’s disease. Traditional hardware for strength evaluation requires technical training for operation, generates discrete time points for muscle assessment, and is implemented in controlled settings. The ability to continuously monitor muscle force without restricting the range of motion or adapting the exercise protocol to suit specific hardware would allow for a richer dataset that can help unlock critical features of muscle health and strength evaluation. In this paper, we employ wearable, ultra-sensitive soft strain sensors for tracking changes in muscle deformation during contractions. We demonstrate the sensors’ sensitivity to isometric contractions, as well as the sensors’ capacity to track changes in peak torque over the course of an isokinetic fatiguing protocol for the knee extensors. The wearable soft system was able to efficiently estimate peak joint torque reduction caused by muscle fatigue (mean NRMSE $= 0.15\pm 0.03$ ).
A novel endocast technique providing a 3D quantitative analysis of the gastrovascular system in Rhizostoma pulmo: An unexpected through-gut in cnidaria

The investigation of jellyfish gastrovascular systems mainly focused on stain injections and dissections, negatively affected by thickness and opacity of the mesoglea. Therefore, descriptions are incomplete and data about tridimensional structures are scarce. In this work, morphological and functional anatomy of the gastrovascular system of Rhizostoma pulmo (Macri 1778) was investigated in detail with innovative techniques: resin endocasts and 3D X-ray computed microtomography. The gastrovascular system consists of a series of branching canals ending with numerous openings within the frilled margins of the oral arms. Canals presented a peculiar double hemi-canal structure with a medial adhesion area which separates centrifugal and centripetal flows. The inward flow involves only the “mouth” openings on the internal wing of the oral arm and relative hemi-canals, while the outward flow involves only the two outermost wings’ hemi-canals and relative “anal” openings on the external oral arm. The openings differentiation recalls the functional characteristics of a through-gut apparatus. We cannot define the gastrovascular system in Rhizostoma pulmo as a traditional through-gut, rather an example of adaptive convergence, that partially invalidates the paradigm of a single oral opening with both the uptake and excrete function.
Internalizing and externalizing mental health problems affect in-school adolescent’s health-related quality of life in eastern Ethiopia: A cross-sectional study

Aims This study aimed to examine the association between mental health problems and health-related quality of life (HrQoL) among in-school adolescents 13–19 years in the Harari region, eastern Ethiopia. Materials and methods A cross-sectional study was conducted on 3227 in-school adolescents aged 13 to 19 using multistage sampling. The KIDSCREEN-10 questionnaire assessed health-related quality of life (HrQoL), while a self-administered version of the strength and difficulty questionnaire (SDQ) examined mental health issues. Data were double entered, validated, and cleaned using EpiData version 3.1 and analyzed using STATA 14.1. An ordinal logistic regression model investigated the link between the outcome variable and the predictors. The results were reported using an odds ratio with a 95% confidence interval (CI), and a p-value of less than 0.05 was considered statistically significant. Results A quarter of the adolescents (23%) reported poor health-related quality of life; adolescents with internalizing and externalizing mental health problems had the lowest health-related quality of life. After controlling for potential confounders, adolescents with abnormal (AOR = 0.48, 95% CI: 0.39, 0.59) and borderline (AOR = 0.59, 95% CI: 0.45, 0.78) levels of internalizing problems had a 52% and 41% lower probability of having high HrQoL than those with normal levels. Furthermore, individuals with abnormal (AOR = 0.59, 95% CI: 0.45, 0.77) and borderline (AOR = 0.64, 95% CI: 0.45, 0.92) levels of externalizing difficulties had a 41% and 36% lower chance of having a high health-related quality of life. Conclusions Nearly a quarter of in-school adolescents had poor health-related quality of life. High scores for internalizing and externalizing mental health problems significantly impacted the adolescents’ health-related quality of life. This emphasizes the need to address mental health issues in the school setting to improve adolescents’ overall quality of life.