Search Results (33,843)

Grape is one of the most economically significant berry crops. Owing to the biological characteristics of grapes, such as the long juvenile period (5–8 years), high degree of genome heterozygosity, and the frequent occurrence of inbreeding depression, homozygosity during crossbreeding leads to loss of varietal characteristics and viability. CRISPR/Cas editing has become the tool of choice for improving elite technical grape varieties. This study provides the first evidence of a decrease in the total fraction of phenolic compounds and an increase in the concentration of peroxide compounds in grape callus cells upon the addition of chitosan to the culture medium. These previously unreported metabolic features of the grape response to chitosan have been described and used for the first time to increase the probability of selecting plant cells with MLO7 knockout characterised by an oxidative burst in response to the presence of a pathogen modulated by chitosan in the high-metabolite black grape variety ‘Merlot’. This was achieved by using a CRISPR/Cas9 editing vector construction with the peroxide sensor HyPer as a reporter. This research represents the first CRISPR/Cas9 editing of ‘Merlot’, one of the most economically important elite technical grape varieties. Full article

Hoof trimming and shoeing determine the horse’s hoof shape and balance. Hoof conformation plays a crucial role in limb biomechanics and can consequently prevent or predispose to injury. This study investigated the relationship between the morphometric characteristics of the horse’s hoof, specifically, the dorsal hoof wall angle (DHWA), the coronet band circumference (CBC), and lameness in 73 horses categorised as undertaking either show jumping, dressage, or riding school activities. Results from logistic regression indicated that horses with either a combination of acute DHWA with large CBC, or more upright feet with larger DHWA and smaller CBC have higher probabilities of lameness. Show jumping and dressage horses showed a higher prevalence of lameness. Hoof morphometry should be monitored, and podiatric interventions should be regularly scheduled for the maintenance of correct hoof conformation to prevent injury. This study suggests that an aligned hoof–pastern axis managed by a DHWA of around 50 degrees may prevent lameness, with special emphasis on horses in dressage and show jumping activities. On the other hand, we can also speculate that the disturbed axis alignment of DHWA may be a cause of lameness. Full article

Background/Objectives: Dopamine dysfunction (DA) is a hallmark of many neurological disorders. In this case, the mechanism of changes in dopamine transmission on behavior remains unclear. This study is a look into the intricate link between disrupted DA signaling, neuronal activity patterns, and behavioral abnormalities in a hyperdopaminergic animal model. Methods: To study the relationship between altered DA levels, neuronal activity, and behavioral deficits, local field potentials (LFPs) were recorded during four different behaviors in dopamine transporter knockout rats (DAT-KO). At the same time, local field potentials were recorded in the striatum and prefrontal cortex. Correlates of LFP and accompanying behavioral patterns in genetically modified (DAT-KO) and control animals were studied. Results: DAT-KO rats exhibited desynchronization between LFPs of the striatum and prefrontal cortex, particularly during exploratory behavior. A suppressive effect of high dopamine levels on the striatum was also observed. Wild-type rats showed greater variability in LFP patterns across certain behaviors, while DAT-KO rats showed more uniform patterns. Conclusions: The decisive role of the synchrony of STR and PFC neurons in the organization of motor acts has been revealed. The greater variability of control animals in certain forms of behavior probably suggests greater adaptability. More uniform patterns in DAT-KO rats, indicating a loss of striatal flexibility when adapting to specific motor tasks. It is likely that hyperdopaminergy in the DAT-KO rat reduces the efficiency of information processing due to less synchronized activity during active behavior. Full article

In 2022, global poliovirus modeling suggested that coordinated cessation of bivalent oral poliovirus vaccine (bOPV, containing Sabin-strain types 1 and 3) in 2027 would likely increase the risks of outbreaks and expected paralytic cases caused by circulating vaccine-derived polioviruses (cVDPVs), particularly type 1. The analysis did not include the implementation of planned, preventive supplemental immunization activities (pSIAs) with bOPV to achieve and maintain higher population immunity for types 1 and 3 prior to bOPV cessation. We reviewed prior published OPV cessation modeling studies to support bOPV cessation planning. We applied an integrated global poliovirus transmission and OPV evolution model after updating assumptions to reflect the epidemiology, immunization, and polio eradication plans through the end of 2023. We explored the effects of bOPV cessation in 2027 with and without additional bOPV pSIAs prior to 2027. Increasing population immunity for types 1 and 3 with bOPV pSIAs (i.e., intensification) could substantially reduce the expected global risks of experiencing cVDPV outbreaks and the number of expected polio cases both before and after bOPV cessation. We identified the need for substantial increases in overall bOPV coverage prior to bOPV cessation to achieve a high probability of successful bOPV cessation. Full article

Variable selection methods have been extensively developed for and applied to cancer genomics data to identify important omics features associated with complex disease traits, including cancer outcomes. However, the reliability and reproducibility of the findings are in question if valid inferential procedures are not available to quantify the uncertainty of the findings. In this article, we provide a gentle but systematic review of high-dimensional frequentist and Bayesian inferential tools under sparse models which can yield uncertainty quantification measures, including confidence (or Bayesian credible) intervals, p values and false discovery rates (FDR). Connections in high-dimensional inferences between the two realms have been fully exploited under the “unpenalized loss function + penalty term” formulation for regularization methods and the “likelihood function × shrinkage prior” framework for regularized Bayesian analysis. In particular, we advocate for robust Bayesian variable selection in cancer genomics studies due to its ability to accommodate disease heterogeneity in the form of heavy-tailed errors and structured sparsity while providing valid statistical inference. The numerical results show that robust Bayesian analysis incorporating exact sparsity has yielded not only superior estimation and identification results but also valid Bayesian credible intervals under nominal coverage probabilities compared with alternative methods, especially in the presence of heavy-tailed model errors and outliers. Full article

The surface and subsurface karst features of the Eocene limestone plateaus along the Middle Nile Valley in Egypt were formerly believed to be epigene in origin and to have developed during post-Eocene pluvial periods. However, the morphology of the caves and their restriction to particular stratigraphic intervals suggests that they are hypogene. The geochemistry and mineralogy of the soft, thick-bedded, brown/black cave infills shows that these sediments originated from hydrothermal processes, as evidenced by their Fe, Mn, Co, Ni, and Cu concentrations. Thus, the karst features are hypogene and probably formed during the opening of the Red Sea Rift at the end of the Oligocene and early Miocene. At this time, there was abundant volcanic activity, as shown by basalt lavas ~70 km northwest of Assiut; this triggered the release of large amounts of CO₂ that made the hydrothermal waters acidic and dissolved the caves. Full article

Background: Varicella infections follow a benign course in around 90% of cases, with more severe forms occurring in adults. To identify potential pockets of susceptibility and to improve targeted immunization strategies, this study aims to critically assess immunological status by evaluating varicella seroprevalence among adults (18–99 years) in the province of Florence (Italy), nearly a decade after Tuscany introduced the vaccination program. Methods: A convenience sample of 430 subjects aged 18 to 94 years (mean age 51.8 ± 18.8 years), stratified by age and sex (53.7% of subjects were female; N = 231), was collected between 2018 and 2019. Sero-analytical analyses were conducted utilizing EUROIMMUN Anti-VZV ELISA (IgG) kits. Results: Most of them were of Italian nationality (87.4%; N = 376). Among the 430 tested samples, 385 (89.5%) were positive and 39 (9.1%) were negative. The remaining six sera (1.4%), confirmed as equivocal, were excluded from further analysis. No significant differences were found based on sex (p-value = 0.706) or nationality (p-value = 0.112). The application of trend tests (Mantel–Haenszel; Kendall Tau-b) showed a significant trend (p < 0.024 and p < 0.032, respectively), with an increasing probability of finding a positive anti-varicella serological status passing from a lower age group (84.2%) to a higher one (93.0%). By considering the female population aged 18–49 years, the seroprevalence of anti-varicella antibodies was found to be 88.4%, with a susceptibility of 11.6%, highlighting the risk of acquiring infection during pregnancy. Conclusions: The introduction of varicella vaccination has had a significant impact on public health in Tuscany and in Italy more generally. However, further efforts should be made to reduce the number of individuals still susceptible in adulthood, with particular attention given to women of childbearing age and the promotion of vaccination through mass and social media and institutional websites. Full article

Objectives: This study aims to examine the serological and infectious characteristics of the Xokós indigenous community in Brazil, both prior to and following COVID-19 immunization; Methods: Immunofluorescence assays were employed to identify the SARS-CoV-2 viral antigen, while IgM and IgG antibody tests for COVID-19 were utilized to assess the participants’ infectious and serological profiles in July 2020, before the commencement of the COVID-19 vaccination campaign, and in March 2022, during the booster dose vaccination campaign; Results: The majority of participants (n = 22) were female, with an average age of 42.20 years. The most prevalent comorbidity was hypertension (60%; n = 9), followed by hypertension associated with diabetes (20%; n = 3). No statistically significant correlation was found between the timing of vaccination and the levels of antigens or IgM. However, the prevalence of reactive antigens and IgM was 13.3% (n = 4) in the pre-vaccination group and 3.3% (n = 1) in the post-vaccination group. A statistically significant difference in IgG production was observed before and after vaccination (χ²(1) = 39.095, p < 0.01), as well as differences in IgG antibody detection before and after vaccination and in the vaccines used. Participants showed a higher probability of reactive IgG antibodies following vaccination; Conclusions: Our data demonstrate the beneficial effects of vaccination on the indigenous community, highlighting that continued immunization is a crucial step in protecting indigenous health and preventing severe outbreaks and deaths associated with the disease. Full article

Prefabricated buildings (PBs) are considered a green way to reduce energy consumption and carbon emissions in the construction industry due to their environmental and social benefits. However, PBs have obstacles such as high construction costs, immature technology, and insufficient policy incentives, and developers’ willingness to develop them needs to be higher. Therefore, it is necessary to explore how to motivate more developers to develop PBs. In this paper, we first discuss the impact of the carbon emissions trading scheme (ETS) on the construction industry and then consider the heterogeneity of construction developers, introduce a collaborative mechanism to establish a three-party evolutionary game model between the government and the heterogeneous developers, and explore the evolution of the three-party dynamic strategies through numerical simulation. The results show that developers’ initial development probability affects the system’s evolutionary trend, and the developer who obtains more low-carbon benefits plays a dominant role. Further analyses show that critical factors such as market profitability, synergistic benefits, and carbon tax price positively influence the development of PBs, and the influence of synergistic cooperation mechanisms should be especially emphasized. This study provides practical insights into the sustainable development of the construction industry and the government’s development of a suitable carbon portfolio policy for it. Including the construction industry in the ETS is recommended when carbon prices reach 110 RMB/t. At this point, the government can remove the subsidy for PBs, but the behaviors of the developers who participate in the ETS still need to be supervised. Full article

One-shot devices are products that can only be used once. Typical one-shot devices include airbags, fire extinguishers, inflatable life vests, ammo, and handheld flares. Most of them are life-saving products and should be highly reliable in an emergency. Quality control of those productions and predicting their reliabilities over time is critically important. To assess the reliability of the products, manufacturers usually test them in controlled conditions rather than user conditions. We may rely on public datasets that reflect their reliability in actual use, but the datasets often come with missing observations. The experimenter may lose information on covariate readings due to human errors. Traditional missing-data-handling methods may not work well in handling one-shot device data as they only contain their survival statuses. In this research, we propose Multiple Imputation with Unsupervised Learning (MIUL) to impute the missing data using Hierarchical Clustering, k-prototype, and density-based spatial clustering of applications with noise (DBSCAN). Our simulation study shows that MIUL algorithms have superior performance. We also illustrate the method using datasets from the Crash Report Sampling System (CRSS) of the National Highway Traffic Safety Administration (NHTSA). Full article

Rainfall intensity prediction based on commercial microwave link data has received significant attention in recent years due to the higher spatial resolution and lower energy consumption. However, the predictive performance is inferior to the model based on meteorological data by reason of the high noise in commercial microwave link data, further exacerbated by the imbalance in the number of samples across different rainfall intensities. Hence, a cost-sensitive rainfall intensity prediction model (CSRFP) is proposed to achieve better predictive performance in high-noise commercial microwave link data. First, the spatiotemporal scene information is encoded, and its weights are trained to provide the model with correlations between signal data from different stations, which helps the model to better capture potential patterns between the data and thus reduce the effect of noise. Next, the rainfall cross-entropy loss based on the rainfall distribution provides the model with the probability of different rainfall intensities occurring and back-calculates the signal attenuation at a specific rainfall intensity, assigning more reasonable weights to different samples considering signal attenuation, which makes the model cost-sensitive and can address the class imbalance problem. Extensive experiments are carried out on high-noise communication data and imbalanced rainfall data in Fuzhou. Compared to typical prediction methods such as RNN applied to rainfall and communication data, CSRFP improves Recall, Precision, AUC_ROC, AUC_PR and F₁ and Accuracy by approximately 19%, 37%, 8%, 22%, 30%, and 17%, respectively. Significantly, the model’s prediction accuracy for heavy rain with the smallest number of samples improves by about 13%. Full article

The emergence of the coronavirus pandemic in 2020 posed a new challenge, imposing extraordinary physical and psychological burdens on healthcare workers, clearly exacerbating and intensifying career abandonment. Objectives: The aim of our study was to explore the motivating factors among nurses serving during the coronavirus pandemic that they considered important in their profession despite the mental and physical stress brought about by the pandemic. Methods: A descriptive, cross-sectional study was conducted at the University of Pécs-Clinical Center-Regional Coronavirus Care Center between September 2022 and December 2022. We used non-random, expert, purposive sampling, recruiting healthcare workers who had spent at least 3 months working in a COVID ward (n = 196). Data collection was conducted by using an online, anonymous questionnaire, which included sociodemographic questions, the “Motivation at Work Scale”, and a self-edited six-item questionnaire. Results: Regarding the 5-year probability of remaining in the healthcare field, nine participants (4.5%) will definitely leave the healthcare sector, twenty-seven participants (13.7%) are undecided, and seventy-eight participants (39.7%) will definitely stay in the healthcare field over the next 5 years. There is a positive, weak, but significant correlation between intrinsic motivation and the probability of leaving the profession within 5 years (r = 0.281; p < 0.05). We identified a significant, negative, and weak correlation between the number of revisited waves of the coronavirus and the fear of redeployment to the COVID ward (r = −0.273; p < 0.05). Conclusions: Despite the challenges posed by the coronavirus pandemic, only a small percentage of nurses consider leaving the healthcare profession. Joy and enjoyment in their work were dominant factors even during the pandemic. Full article

The quality and reliability of wind turbine blades, as core components of wind turbines, are crucial for the operational safety of the entire system. Carbon fiber is the primary material for wind turbine blades. However, during the manufacturing process, manual intervention inevitably introduces minor defects, which can lead to crack propagation under complex working conditions. Due to limited understanding and measurement capabilities of the input variables of structural systems, the distribution parameters of these variables often exhibit uncertainty. Therefore, it is essential to assess the impact of distribution parameter uncertainty on the fatigue performance of carbon-fiber structures with initial cracks and quickly identify the key distribution parameters affecting their reliability through global sensitivity analysis. This paper proposes a sensitivity analysis method based on surrogate sampling and the Kriging model to address the computational challenges and engineering application difficulties in distribution parameter sensitivity analysis. First, fatigue tests were conducted on carbon-fiber structures with initial cracks to study the dispersion of their fatigue life under different initial crack lengths. Next, based on the Hashin fatigue failure criterion, a simulation analysis method for the fatigue cumulative damage life of cracked carbon-fiber structures was proposed. By introducing uncertainty parameters into the simulation model, a training sample set was obtained, and a Kriging model describing the relationship between distribution parameters and fatigue life was established. Finally, an efficient input variable sampling method using the surrogate sampling probability density function was introduced, and a Sobol sensitivity analysis method based on surrogate sampling and the Kriging model was proposed. The results show that this method significantly reduces the computational burden of distribution parameter sensitivity analysis while ensuring computational accuracy. Full article

Background: Back pain in adolescents is a common injury, mainly affecting the lumbar, cervical and sometimes shoulder region. This has been related to various factors, such as lifestyle habits or physical capacity, but no previous research has shown conclusive results. The aims of this study was to analyze the risk of suffering lumbar, neck and shoulder pain according to anthropometric and physical fitness variables, physical activity level, age and biological maturity in adolescents, as well as the influence of sex in the study results. Methods: A descriptive cross-sectional study was performed, including a sample of 2015 adolescents (boys: n = 1006, mean age = 14.41 ± 1.35 years-old; girls: n = 1009, mean age = 14.48 ± 1.41 years-old). The participants underwent an anthropometric evaluation and physical fitness tests were carried out, including a 20 m shuttle run, a counter movement jump, a horizontal jump, a 20 m sprint and push-up tests, followed by the completion of lumbar, neck and shoulder pain questionnaires. Results: Higher values in age and peak height velocity (PHV) showed an increase in the risk of suffering lumbar, neck and shoulder pain (OR = 0.79–1.55; p = 0.000–0.025). The anthropometric variables related to adiposity showed an increase in the risk of suffering back pain, with significant incidence in the lumbar region (OR = 1.32–1.60; p = 0.000); while muscle mass showed a protective effect (OR = 0.59; p = 0.000). Regarding the fitness tests, a better physical fitness seemed to protect adolescents from suffering from the analyzed back pains in the general sample and in the boys sample (OR = 0.56–1.60; p = 0.000), while in the girls sample the influence of the physical fitness was less relevant. Conclusions: Both anthropometry and physical fitness may influence the occurrence of back pain in adolescents, with some variations in their importance according to sex. Full article

Controller Area Networks (CANs) play an important role in many safety-critical industrial systems, which places high demands on their reliability performance. However, the intermittent connection (IC) of network cables, a random and transient connectivity problem, is a common but hard troubleshooting fault that can cause network performance degradation, system-level failures, and even safety issues. Therefore, to ensure the reliability of CANs, a fault symptom association model-based IC fault diagnosis method is proposed. Firstly, the symptoms are defined by examining the error records, and the domains of the symptoms are derived to represent the causal relationship between the fault locations and the symptoms. Secondly, the fault probability for each location is calculated by minimizing the difference between the symptom probabilities calculated from the count information and those fitted by the total probability formula. Then, the fault symptom association model is designed to synthesize the causal and the probabilistic diagnostic information. Finally, a model-based maximal contribution diagnosis algorithm is developed to locate the IC faults. Experimental results of three case studies show that the proposed method can accurately and efficiently identify various IC fault location scenarios in networks. Full article