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A model-based investigation of the interplay between furnace setup and spatio-temporal evolution of particles' state variables is also presented. The effect of feed size distribution and processing of ultrafine ore are discussed. The process is controlled primarily by the wall temperature and secondarily the air feeding rate; an increase of furnace wall temperature from 900 to 1200°C reduced the final density to 484, 979, and 1262 kg/m3 for feed size of 150 μm, 250 μm, and 350 μm. Model predictions are in good agreement with the experimental measurements possessing differences below 10% in most cases. [ABSTRACT FROM AUTHOR]

Purpose: The high incidence of urinary tract infections (UTIs), often in nosocomial environments, is a major cause of antimicrobial resistance (AMR). The dissemination of antibiotic-resistant infections results in very high health and economic burdens for patients and healthcare systems, respectively. This study aims to determine and present the antibiotic resistance profiles of the most common pathogens in a urology department in Greece. Methods: During the period 2019–2020, we included 12,215 clinical samples of blood and urine specimens that tested positive for the following pathogens: Escherichia coli, Enterococcus faecium, Enterococcus faecalis, Proteus mirabilis, Klebsiella pneumoniae, or Pseudomonas aeruginosa, as these are the most commonly encountered microbes in a urology department. Results: The analysis revealed a 22.30% mean resistance rate of E. coli strains with a 76.42% resistance to ampicillin and a 54.76% resistance rate to ciprofloxacin in the two-year period. It also showed an approximately 19% resistance rate of P. mirabilis strains and a mean resistance rate of 46.205% of K. pneumoniae strains, with a decreasing trend during the four semesters (p-value < 0.001), which presented an 80% resistance rate to ampicillin/sulbactam and 73.33% to ciprofloxacin. The resistance to carbapenems was reported to be 39.82%. The analysis revealed a 24.17% mean resistance rate of P. aeruginosa with a declining rate over the two-year period (p-value < 0.001). The P. aeruginosa strains were 38% resistant to fluoroquinolones and presented varying resistance against carbapenems (31.58% against doripenem and 19.79% against meropenem). Regarding the Enteroccocal strains, a 46.91% mean resistance was noted for E. faecium with 100% resistance to ampicillin, and a 24.247% mean resistance rate for E. faecalis strains that were 41% resistant to ciprofloxacin. Both types showed 100% sensitivity to linezolid. Conclusions: The dissemination of antibiotic-resistant pathogens poses the need to implement surveillance programs and, consequently, to develop strategies to prevent the emergence of such pathogens in order to optimize patient outcomes. [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI) has shown the ability to enhance the accuracy and efficiency of physicians. ChatGPT is an AI chatbot that can interact with humans through text, over the internet. It is trained with machine learning algorithms, using large datasets. In this study, we compare the performance of using a ChatGPT API 3.5 Turbo model to a general model, in assisting urologists in obtaining accurate, valid medical information. The API was accessed through a Python script that was applied specifically for this study based on 2023 EAU guidelines in PDF format. This custom-trained model leads to providing doctors with more precise, prompt answers about specific urologic subjects, thus helping them, ultimately, providing better patient care. [ABSTRACT FROM AUTHOR]

Extensive decarbonisation efforts result in major changes in energy demand for the extractive industry. In 2021, the extraction and primary processing of metals and minerals accounted for 4.5 Gt of CO2 eq. per year. The aluminium industry was responsible for 1.1 Gt CO2 eq. direct and indirect emissions. To reach the European milestone of zero emissions by 2050, a reduction of 3% annually is essential. To this end, the industry needs to take a turn towards less impactful production practices, coupling secondary production with green energy sources. The present work aims to comprehensively compare the lifecycle energy consumption and environmental performance of a secondary aluminium smelter employing alternative thermal and electricity sources. In this frame, a comparative analysis of the environmental impact of different thermal energy sources, namely natural gas, light fuel oil, liquified petroleum gas, hydrogen and electricity, for a secondary aluminium smelter is presented. The results show that H2 produced by renewables (green H2) is the most environmentally beneficial option, accounting for −84.156 kg CO2 eq. By producing thermal energy as well as electricity on site, H2 technologies also serve as a decentralized power station for green energy production. These technologies account for a reduction of 118% compared to conventionally used natural gas. The results offer a comprehensive overview to aid decision-makers in comparing environmental impacts caused by different energy sources. [ABSTRACT FROM AUTHOR]