The Organic Rankine Cycle (ORC) is an electricity generation system that uses organic fluid instead of water in the low temperature range. The Organic Rankine cycle using zeotropic working fluids has wide application potential. In this study, data mining (DM) model is used for performance analysis of organic Rankine cycle (ORC) using zeotropik working fluids R417A and R422D. Various DM models, including Linear Regression (LR), Multi-Layer Perceptron (MLP), M5 Rules, M5 Model Tree, Random Committee (RC), and Decision Tree (DT) models are used. The MLP model emerged as the most effective approach for predicting the thermal efficiency of both R417A and R422D. The MLP’s predicted results closely matched the actual results obtained from the thermodynamic model using Genetron software. The Root Mean Square Error (RMSE) for the thermal efficiency was exceptionally low, at 0.0002 for R417A and 0.0003 for R422D. Additionally, the R-squared (R²) values for thermal efficiency were very high, reaching 0.9999 for R417A and R422D. The findings demonstrate the effectiveness of the DM model for complex tasks like estimating ORC thermal efficiency. This approach empowers engineers with the ability to predict thermal efficiency in organic Rankine systems with high accuracy, speed, and ease.

In the context of contemporary global challenges such as the COVID-19 pandemic, geopolitical conflicts, and climate change, food security assumes particular significance, being an integral part of national security. This study aims to investigate the interplay between food security and national security systems, with a focus on identifying gaps in the literature and determining directions for further research. The study conducted a systematic literature review on food security and national security systems employing a rigorous and transparent process. The qualitative analysis is grounded in the quantitative one, encompassing studies from Scopus. The examination of the selected peer-reviewed articles revealed several methodological and thematic limitations in existing research: i Geographic imbalance: There is a predominant focus on developed countries, while food security issues in developing countries remain insufficiently studied; ii Insufficient explication: There is a lack of research dedicated to managerial and economic aspects of food security in the context of national security; iii Methodological constraints: There is a predominance of quantitative methods and retrospective/cross-sectional studies. Recommendations include developing comprehensive strategies at both global and national levels to enhance food stability and accessibility.

Objective: This study investigates the efficacy and safety of epidural infiltration with drugs and an oxygen-ozone mixture for treating cervicobrachialgia due to disc-radicular conflict or on a degenerative basis, utilizing both retrospective analysis and direct visualization techniques. Methods: A retrospective study involving 10 patients treated with epidural infiltrations of an oxygen-ozone mixture and cortisone was conducted. The procedures were performed under CT guidance to ensure precise delivery and to monitor the diffusion of the injected substances. Pain levels were assessed using the Numerical Rating Scale (NRS) and treatment efficacy was evaluated based on symptom relief and reduction in NSAID intake. Results: Significant pain reduction was observed post-treatment, with median NRS scores decreasing from 9 (baseline) to 2 (follow-up), and a significant decrease in on-demand NSAID intake. Only one minor complication of a headache was reported. The study also demonstrated the ability of ozone to diffuse through the epidural adipose tissue, potentially enhancing treatment efficacy. Conclusion: The combined use of an oxygen-ozone mixture and cortisone for epidural infiltration is an effective and safe treatment for cervicobrachialgia, offering significant pain relief and minimizing the risk associated with traditional epidural injections. This technique presents a viable non-surgical option for patients suffering from disc-radicular conflict or degenerative conditions.

Green manufacturing is increasingly becoming popular, especially in lubricant manufacturing, as more environmentally friendly substitutes for mineral base oil and synthetic additives are being found among plant extracts and progress in methodologies for extraction and synthesis is being made. It has been observed that some of the important performance characteristics need enhancement, of which nanoparticle addition has been noted as one of the effective solutions. However, the concentration of the addictive that would optimised the performance characteristics of interest remains a contending area of research. The research was out to find how the concentration of green synthesized aluminum oxide nanoparticles in nano lubricants formed from selected vegetable oils influences friction and wear. A bottom-up green synthesis approach was adopted to synthesize aluminum oxide (Al₂O₃) from aluminum nitrate (Al(NO₃)₃) precursor in the presence of a plant-based reducing agent—Ipomoea pes-caprae. The synthesized Al₂O₃ nanoparticles were characterized using TEM and XRD and found to be mostly of spherical shape of sizes 44.73 nm. Al₂O₃ nanoparticles at different concentrations—0.1 wt%, 0.3 wt%, 0.5 wt%, 0.7 wt%, and 1.0 wt%—were used as additives to castor, jatropha, and palm kernel oils to formulate nano lubricants and tested alternately on a ball-on-aluminum (SAE 332) and low-carbon steel Disc Tribometer. All the vegetable-based oil nano lubricants showed a significant decrease in the coefficient of friction (CoF) and wear rate with Ball-on-(aluminum SAE 332) disc tribometer up to 0.5wt% of the nanoparticle: the best performances (e_COF = 92.29; e_WR = 79.53) came from Al₂O₃-castor oil nano lubricant and Al₂O₃-palm kernel oil; afterwards, they started to increase. However, the performance indices displayed irregular behaviour for both COF and Wear Rate (WR) when tested on a ball-on-low-carbon steel Disc Tribometer.

The study builds on Deborah Stone’s foundational work exploring the mechanics of causal narratives and their implications for framing problems, assigning responsibility, and guiding policy solutions. The purpose of this research is to unravel the complexities of causal narratives in contemporary politics and understand their profound influence on public policy and society at large. In the digital age, where information is abundant and the traditional gatekeeping role of media has diminished, causal narratives have become increasingly multifaceted. The study aims to explore how these narratives, influenced by the intersections of natural phenomena, human actions, politics, risk, and media, shape public understanding and policy directions. The study employs an extensive review of existing literature, covering works from political science, media studies, and public policy. This includes analyzing seminal texts like Deborah Stone’s “Policy Paradox” and recent studies on media’s evolving role in political discourse. Today’s causal narratives are multifaceted, influenced by a myriad of factors including political agendas, scientific findings, and media portrayals. In conclusion, the research highlights the dynamic nature of causal narratives in the digital age and their significant impact on public policy and societal outcomes. It underscores the need for nuanced understanding and strategic approaches in crafting and interpreting these narratives.