Lifestyle and risk of developing myopia in school children in Chongqing, China.

Introduction: Myopia has emerged as a leading global reason for poor vision in children and adolescents. this study aims to investigate the influence of lifestyles on myopia in schoolchildren in Chongqing, China.

Methods: This cross-sectional study was conducted on primary and junior high school graduates in Chongqing City, China.

Lipid Hydrolysis, Oxidation, and Fatty Acid Formation Pathway Mapping of Synergistically Fermented Sausage and Characterization of Lipid Mediating Genes.

Starter cultures play a significant role in lipid hydrolysis, prevention of lipid oxidation, and synthesis of fatty acid in fermented sausage, enhancing product quality. In this study, five synergistic bacterial strains were used, including (B-3), DLS-24 (D-24), DLS-29 (D-29), (B-1), and (B-2). Sausage B1B3D24 gave the highest free fatty acid with 39.

A Predefined-Time Adaptive Zeroing Neural Network for Solving Time-Varying Linear Equations and Its Application to UR 5 Robot.

Time-varying linear equations (TVLEs) play a fundamental role in the engineering field and are of great practical value. Existing methods for the TVLE still have issues with long computation time and insufficient noise resistance. Zeroing neural network (ZNN) with parallel distribution and interference tolerance traits can mitigate these deficiencies and thus are good candidates for the TVLE.

A review of the recent advances for the in ovo sexing of chicken embryos using optical sensing techniques.

The culling of day-old male chicks has caused ethical and economic concerns. Traditional approaches for detecting the in ovo sex of chicken embryos involve opening the eggshell and inner membrane, which are destructive, time-consuming, and inefficient. Therefore, noncontact optical sensing techniques have been examined for the in ovo sexing of chicken embryos.

A Dynamic-Varying Parameter Enhanced ZNN Model for Solving Time-Varying Complex-Valued Tensor Inversion With Its Application to Image Encryption.

Time-varying complex-valued tensor inverse (TVCTI) is a public problem worthy of being studied, while numerical solutions for the TVCTI are not effective enough. This work aims to find the accurate solution to the TVCTI using zeroing neural network (ZNN), which is an effective tool in terms of solving time-varying problems and is improved in this article to solve the TVCTI problem for the first time. Based on the design idea of ZNN, an error-adaptive dynamic parameter and a new enhanced segmented signum exponential activation function (ESS-EAF) are first designed and applied to the ZNN.

A Fixed-Time Noise-Tolerance ZNN Model for Time-Variant Inequality-Constrained Quaternion Matrix Least-Squares Problem.

Presently, numerical algorithms for solving quaternion least-squares problems have been intensively studied and utilized in various disciplines. However, they are unsuitable for solving the corresponding time-variant problems, and thus few studies have explored the solution to the time-variant inequality-constrained quaternion matrix least-squares problem (TVIQLS). To do so, this article designs a fixed-time noise-tolerance zeroing neural network (FTNTZNN) model to determine the solution of the TVIQLS in a complex environment by exploiting the integral structure and the improved activation function (AF).

Airborne bacterial communities in the poultry farm and their relevance with environmental factors and antibiotic resistance genes.

The accelerating occurrence and environmental dissemination of bacteria, gas pollutants and antibiotic resistance genes (ARGs) in aerosols of poultry farms have become emerging environmental issues due to their potential threat to animals, workers, and the communities located near such farms. Here, aerosol samples were gathered from inside and outside of the chicken house in winter with a transportable high-flow bioaerosol sampler. Then, 16S rRNA gene amplicon sequencing was used to categorize the bacteria in air samples, and the abundance of 12 ARG subtypes was researched via the real-time quantitative polymerase chain reaction (qPCR).

A Segmented Variable-Parameter ZNN for Dynamic Quadratic Minimization With Improved Convergence and Robustness.

As a category of the recurrent neural network (RNN), zeroing neural network (ZNN) can effectively handle time-variant optimization issues. Compared with the fixed-parameter ZNN that needs to be adjusted frequently to achieve good performance, the conventional variable-parameter ZNN (VPZNN) does not require frequent adjustment, but its variable parameter will tend to infinity as time grows. Besides, the existing noise-tolerant ZNN model is not good enough to deal with time-varying noise.

Effects of dietary energy levels on rumen fermentation, microbiota, and gastrointestinal morphology in growing ewes.

This study investigated whether dietary metabolizable energy (ME) could generate dynamical effects on rumen fermentation, gastrointestinal tract (GIT) morphology, and microbial composition of growing ewes. A total of twenty-eight female Hu lambs were randomly allotted to two treatments with different dietary ME levels: 9.17 (FEA) and 10.

Receiver-Side TCP Countermeasure in Cellular Networks.

Cellular-based networks keep large buffers at base stations to smooth out the bursty data traffic, which has a negative impact on the user's Quality of Experience (QoE). With the boom of smart vehicles and phones, this has drawn growing attention. For this paper, we first conducted experiments to reveal the large delays, thus long flow completion time (FCT), caused by the large buffer in the cellular networks.