Anguish is a sensation of precordial chest tightness or oppression that has an emotional origin. Unlike anxiety which is focused on the future, anguish is experienced in the present as a state of pain and mental agony. Furthermore, distress is supposed to have different autonomic, physiological and biochemical reactions when compared to anxiety and depression. The main objective of this work is to investigate whether depression is more related to anguish than anxiety, and also to identify which variables or symptoms are most predictive of the state of anguish. A binomial logistic regression model was adjusted and statistically significant evidence was found that depression may be more related to distress than anxiety. An important depression diagnostic variable (MINI Depression) was selected in the model (at the 10% level) and its interpretation corroborates the central hypothesis of the study mentioned above. Correspondence analysis also points to clues in the direction of the research hypothesis. As for the second objective, under the same logistic model, the following variables were shown to be related to the state of distress: Gender, Reduced Hamilton Score, BSI Somatization, BSI Hostility, BSI Obsession Compulsion, Age and MINI Depression.

Our research focuses on examining a mixed problem associated with a second-order parabolic equation that features temporal mixing and variable coefficients, subject to non-local and non-self-adjoint boundary conditions. We establish the problem’s unique solvability by imposing specific conditions on the provided data, utilizing a combination of residue and contour integral methods. Additionally, our study produces an explicit analytical solution for addressing the problem at hand.

Abstract: In the oil and gas sector, supervisory control and data acquisition (SCADA) systems have become a revolutionary force that are transforming operations throughout the whole value chain. This in-depth analysis looks at the development, design, and various uses of SCADA systems in the upstream, middle, and downstream domains. It projects that the global SCADA market for oil and gas will grow to $4.52 billion by 2026. Real-time well monitoring, production optimization, and remote operations are made possible by SCADA systems in upstream operations, which greatly increase output and efficiency. The goal of midstream applications is to increase pipeline efficiency and safety by using predictive maintenance, enhanced leak detection, and flow optimization. By streamlining quality assurance, energy management, and process control, SCADA systems can completely transform refinery operations. SCADA deployments are not without difficulties, though, including data management complications, cybersecurity threats, and legacy system interoperability. In addition to addressing these problems, the study looks at new developments that could improve SCADA capabilities, such as edge computing, digital twins, AI and machine learning integration, and 5G technology. According to the research, SCADA is essential for promoting efficiency, safety, and innovation in the oil and gas industry. Businesses that successfully integrate SCADA technologies while overcoming implementation obstacles will be best positioned to prosper in the complicated and fiercely competitive energy market.

Neural Cyber Augmentation (NCA) is a groundbreaking interdisciplinary field that integrates neuroscience, cybernetics, and biotechnology to enhance human cognitive and physical capabilities. This technology holds transformative potential for public health, enabling advancements in cognitive enhancement, disease management, and human-machine interaction. Early research in brain-computer interfaces (BCIs) demonstrated the feasibility of using neural signals to control external devices, laying the foundation for more complex applications such as advanced prosthetics and cognitive training. Subsequent developments in cybernetic implants have significantly improved the quality of life for individuals with sensory and motor impairments by providing enhanced capabilities beyond natural limits. The integration of artificial intelligence (AI) with neural interfaces has further propelled the field, enabling personalized cognitive training and adaptive therapies. Despite these advancements, the ethical and social implications of NCA, such as privacy concerns, informed consent, and equitable access, must be addressed. Future research should focus on improving neural interfaces, integrating AI for personalized interventions, establishing comprehensive ethical guidelines, conducting longitudinal studies on long-term effects, and developing strategies to ensure accessibility for all. By addressing these challenges, NCA has the potential to revolutionize public health and usher in a new era of human enhancement and well-being.

Abstract: This paper provides a comprehensive historical and bibliometric analysis of the Reformation in Christianity, emphasizing its profound influence on religious, social, and political landscapes. The Reformation, initiated by key figures such as Martin Luther, marked a pivotal shift from the doctrines of the Roman Catholic Church, leading to the establishment of various Protestant denominations and significant reforms within the Catholic Church. This study integrates historical narratives with bibliometric methodologies to identify prevailing trends, influential works, and key contributors in Reformation studies. Analysing scholarly publications from 1964 to 2024, the paper highlights the evolution of research focus, emerging areas of interest, and the broader implications of Reformation principles on contemporary issues, including human rights, environmental activism, and socio-political reforms. The findings underscore the enduring legacy of the Reformation and its relevance to modern-day religious and socio-political contexts.

Abstract: This article explores the critical role of observability dashboarding in mainframe environments, focusing on the integration and support of modern observability tools. It examines the functionalities and benefits of leading solutions such as Prometheus with Grafana, Dynatrace, Datadog, AppDynamics, IBM Instana, and Checkmk, providing insights into how organizations can enhance their mainframe monitoring capabilities. The article emphasizes the significance of a multi-tool observability strategy, highlighting its advantages in flexibility, redundancy, and comprehensive coverage. Key benefits of effective observability, including proactive issue detection, downtime reduction, improved capacity planning, and enhanced security monitoring, are thoroughly discussed. The article also outlines best practices for implementing observability in mainframes, covering unified dashboards, standardized metrics, automation, training, and continuous improvement. By analyzing these tools and strategies, the research offers valuable guidance for organizations seeking to streamline their observability approaches, ultimately enhancing customer experience and operational efficiency in mainframe-dependent environments. This comprehensive examination of mainframe observability techniques provides a roadmap for leveraging legacy systems alongside cutting-edge monitoring solutions, addressing the evolving needs of modern IT infrastructures.

TiO2 material has an important position in the processing of methylene blue waste because it is economical, has abundant polymorphs, high sustainability and supports green chemistry applications. Mesoporous TiO2 is a porous material that has higher effectiveness than other TiO2 because the pore structure has a large diameter at the nano scale (2-50 nm) with a regular shape so that the surface area and pore volume are greater than the average for other TiO2. The synthesis of mesopore TiO2 material has so far used the sol-gel route with synthetic pore directing agents such as P123 which can be replaced with gelatin as a cheaper and safer pore directing agent with high sustainability and abundance. Based on the description above, this research aims to photodegrade methylene blue using mesoporous TiO2 (m-TiO2) nanoparticles which were prepared by the sol–gel method using gelatin and P123 as template. X-ray diffraction (XRD), scanning electron microscopy (SEM), Electron dispersive X-Ray (EDX), and UV–vis spectroscopy techniques were used to characterize the samples. Photocatalytic activities of samples for methylene blue degradation were investigated. The catalyst before and after regeneration will be studied so that the effect of regeneration on the results of methylene blue photocatalysis with m-TiO2 can be determined. XRD results confirmed the formation of the anatase and rutile phase for the TiO2 nanoparticles, with crystallite sizes larger after regeneration in the range of 9–21 nm. The large particle size was after regeneration due to the promotion by high temperature treatment. TiO2 nanoparticles showed the best photocatalytic activity on the first use to 91% and remained stable after four cycles with photodegradation efficiency up to 76% based on the measured UV-Vis spectroscopy. TiO2 as synthesis could be the best candidate for catalyst with the high performance after multicycle regeneration. Copyright © 2024 by Authors, Published by BCREC Publishing Group. This is an open access article under the CC BY-SA License (https://creativecommons.org/licenses/by-sa/4.0).

Human efforts to overcome environmental problems from using fossil fuels continue, such as hydroconversion of biomass into bio-jet fuel. Research on producing a jet fuel range of bio-hydrocarbons from used palm cooking oil catalyzed by sulfated zirconia impregnated with nickel-molybdenum bimetal has been successfully conducted. The hydrothermal method synthesized the nano-catalyst material in the sulfation and impregnation processes. The hydroconversion process was carried out at atmospheric pressure and a temperature of 300–600 °C for 2 h with a hydrogen gas flow rate of 20 mL/min and a catalyst-to-feed ratio of 1:100 (wt%). Compared with zirconia and sulfated zirconia, NiMo-impregnated sulfated zirconia showed the best activity and selectivity in bio-jet fuel production with liquid product and selectivity of 61.07% and 43.49%, respectively. This catalyst also performed well in three consecutive runs, with bio-jet fuel selectivity in the second and third runs of 51.68% and 30.86%, respectively. Copyright © 2024 by Authors, Published by BCREC Publishing Group. This is an open access article under the CC BY-SA License (https://creativecommons.org/licenses/by-sa/4.0).

Methylene blue pollutants can be treated by photocatalytic methods using metal oxide-based semiconductor materials and metal organic framework (MOF). These two materials are often coupled into a composite to improve their physicochemical properties and catalytic activity. This research focuses on the synthesis of composites based on Cr-PTC MOF, ZnO, and Fe3O4 by the sonochemical method. The obtained composites were characterized and tested for catalytic activity in methylene blue pollutant degradation in an aqueous system under acidic conditions (pH = 5). Our investigation shows that the Cr-PTC@Fe3O4 composite possesses the lowest band gap energy of 1.86 eV and achieves the highest photocatalytic activity in methylene blue degradation at solution pH = 5, with a percent degradation of 84.36%. The sonochemical incorporation of Fe3O4 and Cr-PTC MOF is able to fabricate materials in a short time with better photocatalytic activity in degrading methylene blue than the single materials. Copyright © 2024 by Authors, Published by BCREC Publishing Group. This is an open access article under the CC BY-SA License (https://creativecommons.org/licenses/by-sa/4.0).

A microbial fuel cell (MFC) is a bio-electrochemical system that converts chemical energy from organic compounds/renewable energy sources to electrical energy/bio-electrical energy through microbial catalysis at the anode under anaerobic conditions. The process is becoming an attractive and alternative methodology for the generation of electricity. The scope of this paper was to design, construct, and test microbial fuel cells that source their fuel from organic waste, using microbial fuel cells to power LED lights. The research concluded that microbial fuel is a prospective energy source for future electricity that can be produced and used by all consumers. Single Chamber Microbial fuel cells were set up using material readily available around i.e. the slurry and, in the market, i.e. the other materials, in batches. The studies showed that the single chamber MFC can produce a maximum voltage of over 500mV and can last for a minimum of two and half months. Out of the 30 MFCs produced 18 of them which produce stable and progressive voltage were connected in series in the frame. The whole setup successfully powered five red LED lights. This shows that more of the MFCs set up can produce more electricity such as that can power a control system.