Traffic Signal Timing Optimization Model Based on Video Surveillance Data and Snake Optimization Algorithm.

With the continued rapid growth of urban areas, problems such as traffic congestion and environmental pollution have become increasingly common. Alleviating these problems involves addressing signal timing optimization and control, which are critical components of urban traffic management. In this paper, a VISSIM simulation-based traffic signal timing optimization model is proposed with the aim of addressing these urban traffic congestion issues. The proposed model uses the YOLO-X model to obtain road information from video surveillance data and predicts future traffic flow using the long short-term memory (LSTM) model. The model was optimized using the snake optimization (SO) algorithm. The effectiveness of the model was verified by applying this method through an empirical example, which shows that the model can provide an improved signal timing scheme compared to the fixed timing scheme, with a decrease of 23.34% in the current period. This study provides a feasible approach for the research of signal timing optimization processes.

Smartphone recognition-based immune microparticles for rapid on-site visual data-sharing detection of Newcastle disease virus.

Since the last century, animal viruses have posed great threats to the health of humans and the farming industry. Therefore, virus control is of great urgency, and regular, timely, and accurate detection is essential to it. Here, we designed a rapid on-site visual data-sharing detection method for the Newcastle disease virus with smartphone recognition-based immune microparticles. The detection method we developed includes three major modules: preparation of virus detection vectors, sample detection, and smartphone image analysis with data upload. First, the hydrogel microparticles containing active carboxyl were manufactured, which coated nucleocapsid protein of NDV. Then, HRP enzyme-labeled anti-NP nanobody was used to compete with the NDV antibody in the serum for color reaction. Then the rough detection results were visible to the human eyes according to the different shades of color of the hydrogel microparticles. Next, the smartphone application was used to analyze the image to determine the accurate detection results according to the gray value of the hydrogel microparticles. Meanwhile, the result was automatically uploaded to the homemade cloud system. The total detection time was less than 50 min, even without trained personnel, which is shorter than conventional detection methods. According to experimental results, this detection method has high sensitivity and accuracy. And especially, it uploads the detection information via a cloud platform to realize data sharing, which plays an early warning function. We anticipate that this rapid on-site visual data-sharing detection method can promote the development of virus self-checking at home.

The benefit of daily sputum suction via bronchoscopy in patients of chronic obstructive pulmonary disease with ventilators: A randomized controlled trial.

BACKGROUND: To compare the clinical values of bronchoscopic sputum suction and general sputum suction in respiratory failure patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD) combined with sequential invasive-noninvasive mechanical ventilation at the pulmonary infection control (PIC) window (period of lower sputum production, with thinner viscosity and lighter color, and alleviated clinical signs of infection). METHODS: Patients with AECOPD-induced respiratory failure received orotracheal intubation mechanical ventilation and were randomly divided into bronchoscopic sputum suction group or general sputum suction group, and who were then treated with sequential invasive-noninvasive mechanical ventilation at PIC window (both groups). Baseline data, postoperative blood gas conditions, and postoperative clinical parameters of the patients such as appearance of PIC window, time of invasive ventilation, total time of ventilation, hospital stay, weaning success rate, reintubation rate, ventilator-associated pneumonia (VAP) incidence, and fatality rate were measured to compare the effect of 2 different ways of sputum suction. RESULTS: There was no significant difference in baseline characteristics, postoperative blood gas conditions, between 2 groups (all P > .05). Nevertheless, the bronchoscopic sputum suction group showed earlier appearance of PIC window, shorter time of invasive ventilation, total time of ventilation and hospital stay, lower reintubation rate, VAP incidence and fatality rate, and higher weaning success rate than the general sputum suction group (all P < .05). CONCLUSION: Bronchoscopic sputum suction combined with sequential invasive-noninvasive mechanical ventilation at PIC window showed clinical effects in treating respiratory failure patients with AECOPD.