The objective of the present study is to observe the surface morphology, structure and elemental composition of the ash particles produced from some thermal power stations of India using scanning electron microscopy (SEM) and energy dispersive X-ray analysis (EDXA). This information is useful to better understand the ash particles before deciding its utility in varied areas.

Introduction, purpose of the study: In Central Europe, in Hungary, the state guarantees access to health care and basic health services partly through the Semmelweis Plan adopted in 2011. The Health Plan aims to optimize and transform the health system. The objectives of hospital integration, as set out in the Plan, started with the state ownership of municipal hospitals in 2012, continued with the launch of integration processes in 2012–2013 and culminated today. The transformation of a health system can have an impact on health services and thus on meeting the needs of the population. We aim to study the effectiveness of integration through access to CT diagnostic testing. Our hypothesis is that integration has resulted in increased access to modern diagnostic services. The specialty under study is computed tomography (CT) diagnostic care. Our research shows that the number of people receiving CT diagnostic care has increased significantly because of integration, which has also brought a number of positive benefits, such as reduced health inequalities, reduced travel time, costs and waiting lists. Test material and method: Our quantitative retrospective research was carried out in the hospital of Kalocsa through document analysis. The research material was comparing two time periods in the Kalocsa site of Bács-Kiskun County, Southern Hungary. The number of patients attending CT examinations by area of duty of care according to postal codes was collected: Pre-integration period 2014.01.01–2017.11.30. (Kalocsa did not have CT equipment, so patients who appeared in Kecskemét Hospital but were under the care of Kalocsa), post-integration period 2017.12.01–2019.12.31. (period after the installation of CT in Kalocsa). The target group of the study consisted of women and men together, aged 0–99 years, who appeared for a CT diagnostic examination. The study sample size was 6721 persons. Linear regression statistics were used to evaluate the results. Based on empirical experience, a SWOT analysis was carried out to further investigate the effectiveness of integration. Results: As a result of the integration, the CT scan machine purchased in the Kalocsa District Hospital has enabled an average of 129.7 patients per month to receive CT scans on site without travelling. The model used is significant, explaining 86% of the change in the number of patients served (F = 43.535; p < 0.001, adjusted R² = 0.860). The variable of integration in the model is significant, with an average increase in the number of patients served of 129.7 per month (t = 22.686; p < 0.001) following the introduction of CT due to integration. None of the month variables representing seasonal effects were found to be significant, with no seasonal effect on care. The SWOT analysis has clearly identified the strengths, weaknesses, opportunities and threats related to the integration, the main outcome of which is the acquisition of a CT diagnostic tool. Conclusions: Although we only looked at one segment of the evidence for the effectiveness of hospital integration, integration in the study area has had a positive impact on CT availability, reducing disparities in care.

Inflammation of the lungs, called pneumonia, is a disease characterized by inflammation of the air sacs that interfere with the exchange of oxygen and carbon dioxide. It is caused by a variety of infectious organisms, including viruses, bacteria, fungus, and parasites. Pneumonia is more common in people who have pre-existing lung diseases or compromised immune systems, and it primarily affects small children and the elderly. Diagnosis of pneumonia can be difficult, especially when relying on medical imaging, because symptoms may not be immediately apparent. Convolutional neural networks (CNNs) have recently shown potential in medical imaging applications. A CNN-based deep learning model is being built as part of ongoing research to aid in the detection of pneumonia using chest X-ray images. The dataset used for training and evaluation includes images of people with normal lung conditions as well as photos of people with pneumonia. Various preprocessing procedures, such as data augmentation, normalization, and scaling, were used to improve the accuracy of pneumonia diagnosis and extract significant features. In this study, a framework for deep learning with four pre-trained CNN models—InceptionNet, ResNet, VGG16, and DenseNet—was used. To take use of its key advantages, transfer learning utilizing DenseNet was used. During training, the loss function was minimized using the Adam optimizer. The suggested approach seeks to improve early diagnosis and enable fast intervention for pneumonia cases by leveraging the advantages of several CNN models. The outcomes show that CNN-based deep learning models may successfully diagnose pneumonia in chest X-ray pictures.

Industrial plastics have seen considerable progress recently, particularly in manufacturing non-lethal projectile holders for shock absorption. In this work, a variety of percentages of alumina (Al2O3) and carbon black (CB) were incorporated into high-density polyethylene (HDPE) to investigate the additive material effect on the consistency of HDPE projectile holders. The final product with the desired properties was controlled via physical, thermal, and mechanical analysis. Our research focuses on nanocomposites with a semicrystalline HDPE matrix strengthened among various nanocomposites. In the presence of compatibility, mixtures of variable compositions from 0 to 3% by weight were prepared. The reinforcement used was verified by X-ray diffraction (XRD) characterization, and thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC) were used for thermal property investigation. Alumina particles increased the composites’ thermal system and glass transition temperature. Mechanical experiments indicate that incorporating alumina into the matrix diminishes impact resistance while augmenting static rupture stress. Scanning electron microscopy (SEM) revealed a consistent load distribution. Ultimately, we will conduct a statistical analysis to compare the experimental outcomes and translate them into mathematical answers that elucidate the impact of filler materials on the HDPE matrix.