The application of optimization algorithms is crucial for analyzing oil and gas company portfolio and supporting decision-making. The paper investigates the process of optimizing a portfolio of oil and gas projects under economic uncertainty. The literature review explores the advantages of applying various optimizers to models that consider the mean and semi-standard deviations of stochastic multi-year cash flows and revenues. The methods and results of three different optimization algorithms are discussed: ranking and cutting algorithms, linear (Simplex) and evolutionary (genetic) algorithms. Functions of several key performance indicators were used to test these algorithms. The results confirmed that multi-objective optimization algorithms that examine various key performance indicators are used for efficient optimization in oil and gas companies. This paper proposes a multi-criteria optimization model for investment portfolios of oil and gas projects. The model considers the specific features of these projects and is based on the Markowitz portfolio theory and methodological recommendations for project assessment. An example of its practical application to oil and gas projects is also provided.

The process management variable and the service quality variable date most prominently from the beginning of the last century, and therefore, in organizations from different parts of the world, whose search was to contribute effectively to administrative tasks, facing the challenges of constant changes and evaluations. In Peru, both variables were implemented since 2018, by technical standards, in order to contribute and improve public institutional work. Thus, the objective was to know the most outstanding characteristics of process management and service quality, using studies from different entities at the ecumenical level and revealing their main benefits of application and contribution. Furthermore, based on the systematic and methodical review of scientific articles from databases indexed to multiple journals, which are registered and organized in databases such as WOS and SCOPUS, thus theorizing their authors and perspectives. For this study, the documentary analysis technique and the data collection guide were considered as an instrument; in accordance with the PRISMA method. Finally, it is concluded that process management are methods available in an organization to provide effective results using resources efficiently, with dimensions of analysis, monitoring, and process improvements, contributing to organizational and strategic productivity; Likewise, the quality of the service is user satisfaction when judging the value of some service, dimensioning, analyzing needs, as well as evaluating, supervising and improving the service, fulfilling needs with knowledge of their expectations.

This review discusses the significant progress made in the development of CNT/GO-based biosensors for disease biomarker detection. It highlights the specific applications of CNT/GO-based biosensors in the detection of various disease biomarkers, including cancer, cardiovascular diseases, infectious diseases, and neurodegenerative disorders. The superior performance of these biosensors, such as their high sensitivity, low detection limits, and real-time monitoring capabilities, makes them highly promising for early disease diagnosis. Moreover, the challenges and future directions in the field of CNT/GO-based biosensors are discussed, focusing on the need for standardization, scalability, and commercialization of these biosensing platforms. In conclusion, CNT/GO-based biosensors have demonstrated immense potential in the field of disease biomarker detection, offering a promising approach towards early diagnosis. Continued research and development in this area hold great promise for advancing personalized medicine and improving patient outcomes.

Zinc oxide (ZnO) hollow spheres are gaining attention due to their exceptional properties and potential applications in various fields. This study investigates the impact of different zinc precursors Zinc Chloride (ZnCl₂), Zinc Nitrate [Zn(NO₃)₂], and Zinc Acetate [Zn(CH₃COO)₂] on the hydrothermal synthesis of ZnO hollow spheres. A comprehensive set of characterization techniques, including Field Emission Scanning Electron Microscopy (FE-SEM), X-ray Diffraction (XRD), Thermogravimetric analysis (TGA), and Brunauer-Emmett-Teller (BET) analysis, was utilized to assess the structural and morphological features of the synthesized materials. Our findings demonstrate that all samples exhibit a high degree of crystallinity with a wurtzite structure, and crystallite sizes range between 34 to 91 nm. Among the different precursors, ZnO derived from Zinc Nitrate showed markedly higher porosity and a well-defined mesoporous structure than those obtained from Zinc Acetate and Zinc Chloride. This research underscores the significance of precursor selection in optimizing the properties of ZnO hollow spheres, ultimately contributing to advancements in the design and application of ZnO-based nanomaterials.

This study presents a comprehensive two-dimensional numerical analysis of natural laminar convection within a square cavity containing two circular heat sources, which simulate electric cables generating heat due to Joule heating. This scenario is particularly relevant in aeronautics, where excessive heating of electrical installations can lead to significant material and human safety risks. The primary objective of this research is to identify the optimal spacing between the two heat sources to mitigate the risk of overheating and ensure the safe operation of the electrical installation. To achieve this, various configurations were analyzed by adjusting the distance between the heat sources while also varying the Rayleigh number across a range from 10³ to 10⁶. The governing equations for the fluid flow and heat transfer were solved using a FORTRAN-based numerical code employing the finite volume method. The results indicate that the heat transfer characteristics within the cavity are significantly influenced by both the distance between the heat sources and the Rayleigh number. The analysis revealed that the average Nusselt number (Nu_avg) peaked at a value of 14.69 when the distance between the heat sources was set at 0.7 units and the Rayleigh number was at 10⁶. This finding suggests that maintaining this specific spacing between the electrical cables can optimize heat dissipation and enhance the safety of the installation. In conclusion, the study recommends adopting a spacing of 0.7 units between the electrical cables to ensure optimal thermal performance and minimize the risk of overheating, thereby safeguarding both the materials and personnel involved in aeronautical operations.