Search

Recent advancements of large language models (LLMs) like generative pre-trained transformer 4 (GPT-4) have generated significant interest among the scientific community. Yet, the potential of these models to be utilized in clinical settings remains largely unexplored. In this study, we investigated the abilities of multiple LLMs and traditional machine learning models to analyze emergency department (ED) reports and determine if the corresponding visits were due to symptomatic kidney stones. Leveraging a dataset of manually annotated ED reports, we developed strategies to enhance LLMs including prompt optimization, zero- and few-shot prompting, fine-tuning, and prompt augmentation. Further, we implemented fairness assessment and bias mitigation methods to investigate the potential disparities by LLMs with respect to race and gender. A clinical expert manually assessed the explanations generated by GPT-4 for its predictions to determine if they were sound, factually correct, unrelated to the input prompt, or potentially harmful. The best results were achieved by GPT-4 (macro-F1 = 0.833, 95% confidence interval [CI] 0.826–0.841) and GPT-3.5 (macro-F1 = 0.796, 95% CI 0.796–0.796). Ablation studies revealed that the initial pre-trained GPT-3.5 model benefits from fine-tuning. Adding demographic information and prior disease history to the prompts allows LLMs to make better decisions. Bias assessment found that GPT-4 exhibited no racial or gender disparities, in contrast to GPT-3.5, which failed to effectively model racial diversity. [ABSTRACT FROM AUTHOR]

Despite Iran's considerable renewable energy (RE) potential and excellent wind capacity and high solar radiation levels, these sources contribute only a small fraction of the country's total energy production. This paper addresses the techno-economic viability of gray hydrogen production by these renewables, with a particular focus on solar energy. Given the considerable potential of solar energy and the strategic location of Shahrekord, it would be an optimal site for a hydrogen generation plant integrated with a solar field. HOMER Pro 3.18.3 software was utilized to model and optimize the levelized cost of hydrogen (LCOH) of steam reforming using different hydrocarbons in various scenarios. The results of this study indicate that natural gas (NG) reforming represents the most cost-effective method of gray hydrogen production in this city, with an LCOH of −0.423 USD/kg. Other hydrocarbons such as diesel, gasoline, propane, methanol, and ethanol have a price per kilogram of produced hydrogen as follows: USD −0.4, USD −0.293, USD 1.17, USD 1.48, and USD 2.15. In addition, integrating RE sources into hydrogen production was found to be viable. Moreover, by implementing RE technologies, CO2 emissions can be significantly reduced, and energy security can be achieved. [ABSTRACT FROM AUTHOR]

Green infrastructure is a key element of a sustainable urban ecosystem. It is recognized as an effective approach based on the way nature works, being an important source of ecosystem services provided to the population. Green and blue solutions are one of the new tools that can help cities increase their resilience and sustainability. The green infrastructure (forest plantations, forest-parks, agricultural land, hedges, lineaments, etc.), the blue infrastructure (lands under marshy waters, rivers, ponds) was evaluated and compared with the grey infrastructure (roads, streets and squares, constructions) in cities and rural areas in the development regions of the Republic of Moldova. The results show that the spatial share of green infrastructure in cities with a population greater than 30 thousand inhabitants (Chișinău city, Bălți city, Cahul city) represents about 25-35% of the total area, the share of grey infrastructure is 50-60 %, and the blue one only 2-4%. In smaller cities, the share of green infrastructure can reach values of up to 50-70 percent, and in rural areas, the share of green infrastructure reaches around 70-90%, blue infrastructure 2-3%, and the built one 10-12%. Cultural ecosystem services related to different types of ecosystems were identified in terms of supply, regulation and support. The dependence of the amount of ecosystem services (air purification, carbon storage, leakage retention) on the weight of the ecological infrastructure in the investigated ecosystems was investigated. [ABSTRACT FROM AUTHOR]

Copyright of Studii de Ştiintă şi Cultură is the property of Studii de Stiinta si Cultura and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

On 17 April 1630, the biblical scholar and Hebraist Joseph Mede recounted an amusing incident to a friend. Evidently, a local 'oatmeal-maker, taking upon him [self] to be a preacher' [...]