Deep Insight into Urban Air Quality Utilizing Neural Networks for Enhanced Prediction in Korean Cities Where Factories and Ecosystem Environments Coexists

Increased attention is being given to air pollution in recent times. This study investigated and analyzed particulate matter data from Yeosu, Gwangyang, and Suncheon in Jeollanam-do, with a particular focus on PM2.5. Descriptive statistics, box-and-whisker plots, correlation matrices, time variations, and trend analyses were performed for this purpose. Additionally, a prediction model for PM2.5 concentrations was developed using machine learning techniques, through which future changes in air quality were forecasted. Calculations were performed using R-based programs and R packages. Hourly PM2.5 data were obtained from air quality monitoring sites in Yeosu, Gwangyang, and Suncheon. After data preprocessing, the optimal prediction model was constructed using Random Forest and Gradient Boosting Machine from various machine learning algorithms. The research results showed that there was more PM2.5 pollution in Gwangyang compared to Yeosu and Suncheon. The PM2.5 concentrations varied significantly across each monitoring site. Among the monitoring sites, the Yeosu site showed a higher correlation in PM2.5 with each other than other sites. Late winter and early spring showed higher PM2.5 concentrations, while summer and autumn showed lower concentrations. Weekly PM2.5 concentration fluctuations were not significantly different. Daily fluctuations showed an increase in PM2.5 concentrations during times of traffic congestion and a decrease in the afternoon. During the research period, the trend of PM2.5 concentration was generally decreasing. The accuracy of the prediction model through machine learning was over 90%, and it is expected to assist in establishing effective response strategies for future changes in air quality. This study provided an updated and useful evaluation of recent PM2.5 air quality in Yeosu, Gwangyang, and Suncheon in Korea

Micromechanical fracture modeling of asphalt concrete using a single-edge notched beam test

Cracks in asphalt pavements create irreversible structural and functional deficiencies that increase maintenance costs and decrease lifespan. Therefore, it is important to understand the fracture behavior of asphalt mixtures, which consist of irregularly shaped and randomly oriented aggregate particles and mastic. A two-dimensional clustered discrete element modeling (DEM) approach is implemented to simulate the complex crack behavior observed during asphalt concrete fracture tests. A cohesive softening model (CSM) is adapted as an intrinsic constitutive law governing material separation in asphalt concrete. A homogenous model is employed to investigate the mode I fracture behavior of asphalt concrete using a single-edge notched beam (SE(B)) test. Heterogeneous morphological features are added to numerical SE(B) specimens to investigate complex fracture mechanisms in the process zone. Energy decomposition analyses are performed to gain insight towards the forms of energy dissipation present in fracture testing of asphalt concrete. Finally, a heterogeneous model is used to simulate mixed-mode crack propagatio

Submaximal Force Steadiness and Accuracy in Patients With Chronic Ankle Instability

Context: Patients with chronic ankle instability (CAI) have demonstrated sensorimotor impairments. Submaximal force steadiness and accuracy measure sensory, motor, and visual function via a feedback mechanism, which helps researchers and clinicians comprehend the sensorimotor deficits associated with CAI. Objective: To determine if participants with CAI experienced deficits in hip and ankle submaximal force steadiness and accuracy compared with healthy control participants. Design: Case-control study. Setting: Research laboratory. Patients or Other Participants: Twenty-one patients with CAI and 21 uninjured individuals. Main Outcome Measure(s): Maximal voluntary isometric contraction (MVIC) and force steadiness and accuracy (10% and 30% of MVIC) of the ankle evertors and invertors and hip abductors were assessed using the central 10 seconds (20%– 87% of the total time) of the 3 trials. Results: Relative to the control group, the CAI group demonstrated less accuracy of the invertors (P , .001). Across all motions, the CAI group showed less steadiness (P , .001) and less accuracy (P , .01) than the control group at 10% of MVIC. For MVIC, the CAI group displayed less force output in hip abduction than the uninjured group (P , .0001). Conclusions: Patients with CAI were unable to control ongoing fine force (10% and 30% of MVIC) through a feedback mechanism during an active test. These findings suggested that deficits in sensorimotor control predisposed patients with CAI to injury positions because they had difficulty integrating the peripheral information and correcting their movements in relation to visual information

A SIMULTANEOUS VIEW INTERPOLATION AND MULTIPLEXING METHOD USING STEREO IMAGE PAIRS FOR LENTICULAR DISPLAY

ABSTRACT Nowadays, the slanted lenticular display becomes a representative one among the commercially introduced autostereoscopic displays. The paper presents a simple method to correct the lenticular alignment error by compensating the correction coefficients to the view number determination formula. Then, based on the corrected view numbers, the proposed algorithm simultaneously performs floating-point viewpoint generation and multiplexing on the scanline using the stereo image pairs and its depth information. Experimental results show that lenticular images, in which distortion and artifact due to lenticular alignment error are considerably reduced, are generated rapidly by using the proposed algorithm. Index Terms-Three-dimensional displays, Stereo vision

Congenital miliary tuberculosis in an 18-day-old boy

Congenital tuberculosis (TB) is a rare disease that is associated with high mortality. Mycobacterium tuberculosis, the causative agent, may be transmitted from the infected mother to the fetus by the transplacental route or by aspiration of infected amniotic fluid. Clinical symptoms and signs are not specific. Miliary patterns are the most common findings in the chest X-rays of many infants with congenital TB. In this case, an 18-day-old boy had jaundice on the fifth day of birth, and fever and respiratory distress appeared on the 18th day. Chest X-ray showed diffuse fine bilateral infiltration. Clinically, pneumonia or sepsis was suspected. Respiratory symptoms and chest X-ray findings worsened despite empirical antibiotic therapy. The lungs showed miliary infiltration suggestive of TB. Gastric aspirates were positive for M. tuberculosis. Respiratory distress and fever were gradually improved after anti-TB medication. Congenital TB is difficult to detect because of minimal or no symptoms during pregnancy and nonspecific symptoms in neonates. Hence, clinicians should suspect the possibility of TB infection even if neonates have non-specific symptoms. Early diagnosis and meticulous treatment are required for the survival of neonates with TB