Porcine pasteurellosis is an infectious disease caused by Pasteurella multocida (P. multocida), which seriously endangers the healthy development of pig breeding industry. Early detection of disease transmission in animals is a crucial early warning for humans. Therefore, predicting risk areas for disease is essential for public health authorities to adopt preventive measures and control strategies against diseases. In this study, we developed a predictive model based on multi-criteria decision analysis (MCDA) and assessed risk areas for porcine pasteurellosis in the Chinese mainland. By using principal component analysis, the weights of seven spatial risk factors were determined. Fuzzy membership function was used to standardize all risk factors, and weight linear combination was used to create a risk map. The sensitivity of the risk map was analyzed by calculating the mean of absolute change rates of risk factors, as well as calculating an uncertainty map. The results showed that risk areas for porcine pasteurellosis were predicted to be locate in the south-central of the Chinese mainland, including Sichuan, Chongqing, Guangdong, and Guangxi. The maximum standard deviation of the uncertain map was less than 0.01and the ROC results showed that the prediction model has moderate predictive performance with the area under the curve (AUC) value of 0.80 (95% CI 0.75-0.84). Based on the above process, MCDA was combined with WebGIS technology to construct a system for predicting risk areas of porcine pasteurellosis. Risk factor data was directly linked to the developed model, providing decision support for disease prevention and control through monthly updates.

With the utilization of advanced microfluidic techniques, the microfluidic particle counter demonstrates significant potential due to its high efficiency, precise manipulation, and portability. This work focuses on a photodetection counter based on optical absorption. To achieve precise particle detection, a Christmas tree-like structure was implemented to separate a single particle from a cluster, which was then detected in independent multiple parallel channels. The system exhibits a high degree of reliability, as evidenced by a linear correlation coefficient over 0.99 obtained during testing with gradient-concentrated beads. Furthermore, when the calculated density of NIH 3T3 cells is compared with that of a traditional flow cytometer, the system achieves a substantial agreement percentage ranging from 87.5 to 99.9%. The system\'s ability to perform high-throughput analysis with a high acquisition rate positions it as a promising tool for real-time point-of-care testing.

In recent years, as global industrialization has intensified, environmental pollution has become an increasingly serious problem. Improving water quality and achieving wastewater purification remain top priorities for environmental health initiatives. The Fenton process is favored by researchers due to its high efficiency and ease of operation. Central to the Fenton process is a catalyst used to activate hydrogen peroxide, rapidly degrading pollutants, improving water quality. Among various catalysts developed, copper-based catalysts have attracted considerable attention due to their affordability, high activity, and stable performance. Based on this, this paper reviews the development of copper-based Fenton systems over the past decade. It mainly involves the research and application of copper-based catalysts in different Fenton systems, including photo-Fenton, electro-Fenton, microwave-Fenton, and ultrasonic-Fenton. This review provides a fundamental reference for the subsequent studies of copper-based Fenton systems, contributing to the goal of transitioning these systems from laboratory research into practical environmental applications.

Many natural compounds have excellent activity against different bacteria. However, their food use to inhibit the bacteria is often limited by poor water solubility, or instability to light, heat, oxygen, and other environmental factors. Cyclodextrin combines with these natural compounds could not only overcome these shortcomings, but also increase the antibacterial ability of active compounds. This review focuses on the following aspects of active natural compounds in cyclodextrin-based food: the preparation, food applications, and their possible antibacterial mechanisms of different systems. Both cyclodextrin and its derivatives are able to selectively combine with different guest molecules, such as terpenes, phenols and flavonoids, as well as essential oil and other plant extract. Finally, the opportunities and future challenges of active natural compounds in cyclodextrin-based food are outlined and proposed.

A tunnel health monitoring (THM) system ensures safe operations and effective maintenance. However, how to effectively process and denoise several data collected by THM remains to be addressed, as well as safety early warning problems. Thus, an integrated method for Savitzky-Golay smoothing (SGS) and Wavelet Transform Denoising (WTD) was used to smooth data and filter noise, and the coefficient of the non-uniform variation method was proposed for early warning. The THM data, including four types of sensors, were attempted using the proposed method. Firstly, missing values, outliers, and detrend in the data were processed, and then the data were smoothed by SGS. Furthermore, data denoising was carried out by selecting wavelet basis functions, decomposition scales, and reconstruction. Finally, the coefficient of non-uniform variation was employed to calculate the yellow and red thresholds. In data smoothing, it was found that the Signal Noise Ratio (SNR) and Root Mean Square Error (RMSE) of SGS smoothing were superior to those of the moving average smoothing and five-point cubic smoothing by approximately 10% and 30%, respectively. An interesting phenomenon was discovered: the maximum and minimum values of the denoising effects with different wavelet basis functions after selection differed significantly, with the SNR differing by 14%, the RMSE by 8%, and the r by up to 80%. It was found that the wavelet basis functions vary, while the decomposition scales are consistently set at three layers. SGS and WTD can effectively reduce the complexity of the data while preserving its key characteristics, which has a good denoising effect. The yellow and red warning thresholds are categorized into conventional and critical controls, respectively. This early warning method dramatically improves the efficiency of tunnel safety control.

Elevated mental workload (MWL) experienced by pilots can result in increased reaction times or incorrect actions, potentially compromising flight safety. This study aims to develop a functional system to assist administrators in identifying and detecting pilots\' real-time MWL and evaluate its effectiveness using designed airfield traffic pattern tasks within a realistic flight simulator. The perceived MWL in various situations was assessed and labeled using NASA Task Load Index (NASA-TLX) scores. Physiological features were then extracted using a fast Fourier transformation with 2-s sliding time windows. Feature selection was conducted by comparing the results of the Kruskal-Wallis (K-W) test and Sequential Forward Floating Selection (SFFS). The results proved that the optimal input was all PSD features. Moreover, the study analyzed the effects of electroencephalography (EEG) features from distinct brain regions and PSD changes across different MWL levels to further assess the proposed system\'s performance. A 10-fold cross-validation was performed on six classifiers, and the optimal accuracy of 87.57% was attained using a multi-class K-Nearest Neighbor (KNN) classifier for classifying different MWL levels. The findings indicate that the wireless headset-based system is reliable and feasible. Consequently, numerous wireless EEG device-based systems can be developed for application in diverse real-driving scenarios. Additionally, the current system contributes to future research on actual flight conditions.

The significance of peripheral immunity in the pathogenesis and progression of Alzheimer\'s diseases (AD) has been recognized. Brain-infiltrated peripheral immune components transporting across the blood-brain barrier (BBB) may reshape the central immune environment. However, mechanisms of how these components open the BBB for AD occurrence and development and correlations between peripheral and central immunity have not been fully explored. Herein, we formulate a hypothesis whereby peripheral immunity as a critical factor allows AD to progress. Peripheral central immune cell crosstalk is associated with early AD pathology and related risk factors. The damaged BBB permits peripheral immune cells to enter the central immune system to deprive its immune privilege promoting the progression toward developing AD. This review summarizes the influences of risk factors on peripheral immunity, alongside their functions, highlighting the concept of peripheral and central immunity as an integrated system in AD pathogenesis, which has received scant attention before.

Aiming at the problem that the single sensor of the coaxial UAV cannot accurately measure attitude information, a pose estimation algorithm based on unscented Kalman filter information fusion is proposed. The kinematics and dynamics characteristics of coaxial folding twin-rotor UAV are studied, and a mathematical model is established. The common attitude estimation methods are analyzed, and the extended Kalman filter algorithm and unscented Kalman filter algorithm are established. In order to complete the test of the prototype of a small coaxial twin-rotor UAV, a test platform for the dynamic performance and attitude angle of the semi-physical flight of the UAV was established. The platform can analyze the mechanical vibration, attitude angle and noise of the aircraft. It can also test and analyze the characteristics of the mechanical vibration and noise produced by the UAV at different rotor speeds. Furthermore, the static and time-varying trends of the pitch angle and yaw angle of the Kalman filter attitude estimation algorithm is further analyzed through static and dynamic experiments. The analysis results show that the attitude estimation of the UKF is better than that of the EKF when the throttle is between 0.2σ and 0.9σ. The error of the algorithm is less than 0.6°. The experiment and analysis provide a reference for the optimization of the control parameters and flight control strategy of the coaxial folding dual-rotor aircraft.

As an evolutionary success in life science, wearable biosensor systems, which can monitor human health information and quantify vital signs in real time, have been actively studied. Research in wearable biosensor systems is mainly focused on the design of sensors with various flexible materials. Among them, 2D materials with excellent mechanical, optical, and electrical properties provide the expected characteristics to address the challenges of developing microminiaturized wearable biosensor systems. This review summarizes the recent research progresses in 2D-materials-based wearable biosensors including e-skin, contact lens sensors, and others. Then, we highlight the challenges of flexible power supply technologies for smart systems. The latest advances in biosensor systems involving wearable wristbands, diabetic patches, and smart contact lenses are also discussed. This review will enable a better understanding of the design principle of 2D biosensors, offering insights into innovative technologies for future biosensor systems toward their practical applications.

Hypoxia refers to a state of oxygen limitation, which mainly mediates pathological processes in the human body and participates in the regulation of normal physiological processes. In the hypoxic environment, the main regulator of human body homeostasis is the hypoxia-inducible factor family (HIF). HIF can regulate the expression of many hypoxia-induced genes and then participate in various physiological and pathological processes of the human body. Ion-transporting proteins are extremely important types of proteins. Ion-transporting proteins are distributed on cell membranes or organelles and strictly control the inflow or outflow of ions in cells or organelles. Changes in ions in cells are often closely related to extensive physiological and pathological processes in the human body. Numerous studies have confirmed that hypoxia and its regulatory factors can regulate the transcription and expression of ion-transporting protein-related genes. Under hypoxic stress, the regulation and interaction of ion-transporting proteins by hypoxia often leads to diseases of various human systems and even tumors. Using ion-transporting proteins and hypoxia as targets to explore the mechanism of digestive system diseases and targeted therapy is expected to become a new breakthrough point.