Producción Científica

 

 

The expansion of photovoltaic systems emphasizes the crucial requirement for effective operations and maintenance, drawing insights from advanced maintenance approaches evident in the wind industry. This review systematically explores the existing literature on the management of photovoltaic operation and maintenance. Through the integration of bibliometric analysis and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework, 186 articles are selected for further comprehensive review. The selected articles are examined and categorized into four interconnected research domains: maintenance strategies, performance indicators, degradation modeling, and maintenance optimization and planning. The presented analysis underscores the importance of integrating maintenance strategies to enhance system effectiveness. It also emphasizes the necessity of a systematic approach that integrates reliability assessment with economic and technical considerations to optimize maintenance planning and enhance system availability and resource efficiency. This aligns with the Sustainable Development Goals for affordable, reliable, and sustainable energy, while also ensuring grid security. Furthermore, the study identifies gaps and proposes avenues for improvement, recommending a shift towards prognostic approaches and the advancement of predictive maintenance in photovoltaic systems. Key suggestions also include customizing metrics for large installations, implementing adaptive protocols that move away from traditional component-centric scheduling, and using reinforcement learning to prioritize risk and optimize long-term performance. Compared to previous reviews focusing on specific maintenance elements, this work provides a broader perspective by incorporating planning and organizational factors into the maintenance discussion.

 

 

Research on the application of Artificial Intelligence (AI)-based technologies in the HRM domain has attracted significant scholarly attention. Yet, few studies have consolidated key trends in adopting AI for HRM, especially on managerial competencies required for adopting AI-based technologies and identifying the key research directions for HR managers, including the development of an AI-focused competency framework for HR managers. A systematic literature review (SLR) and bibliometrics analysis were conducted to identify the current research direction for managers adopting AI in HRM. Several themes of managerial capabilities required for adopting AI in HRM were identified, utilizing the Dynamic Capabilities View (DCV). The SLR identified applications of various AI tools and techniques in HR functions, recruitment and selection was one with the broadest use of AI applications. Managerial cognitive capability, managerial human capital, and managerial social capital of DCV were considered the initial coding categories under which various managerial competencies are required for the adoption of AI in HRM. This study utilized SLR, Bibliometric, and directed content analysis as three distinct but interrelated sets of methodologies for extracting novel insights into the adoption of AI for HRM. It highlights the associated managerial capabilities that need mapping for its adoption.

 

 

There must be proper business efforts to achieve high competitiveness and outstanding business performance, especially in an uncertain economic environment. It must be the best choice when dealing with organizational agility issues. Organizational agility is defined differently in various studies. There is much uncertainty and disagreement around the definition and lements of this notion. Therefore, this research aims to conduct a thorough evaluation of the literature that synthesizes definitions, concepts, measurements, and analyses from previous works on organizational agility research. There was a systematic literature review using this methodology by involving a search for articles, papers, or all works published between 1999 and 2000. There are 59 articles found that match the predetermined criteria. The results combine some factors that influence organizational agility and dynamic capabilities. These research findings offer significant implicit insights that assist organizations in navigating VUCA conditions and realizing a sustainable competitive advantage. They also indicate potential areas for future research.

 

 

Cap-and-trade regulation is an effective and flexible measure to migrate climate changes in supply chain management. As a result, supply chain management under cap-and-trade regulation (SCM-CAT) has been attracting an increasing amount of attention from both academics and industry. This paper presents a comprehensive and systemic literature review about the field of SCM-CAT based on bibliometric analysis and content analysis. After executing retrieval strategy settings and data cleaning, 563 (out of 2931) publications are selected and downloaded from two databases, including the Web of Science’s core collection and Scopus. Bibliometric analysis is conducted to analyze the current status and evaluation path in the field of SCM-CAT, including yearly output, collaboration network analysis of regions and institutions, journal analysis, and co-citation sources. Content analysis focuses on the thematic area of the field of SCM-CAT in four clusters from co-citation analysis. According to the results of bibliometric and content analysis, six research gaps are identified to propose potential corresponding research opportunities and questions. This paper is beneficial for the scholars and practitioners who are exploring the field of SCM-CAT, because it promotes to realize the goals of sustainability, including economics, environment, and society.

 

 

Understanding the adsorption mechanisms and interaction of dye pollutants and microplastics in natural water is vital to evaluating potential risks. This review article discusses the bibliometric analysis and the adsorption behavior of dyes to microplastics. The review also examined the impact of environmental (salinity, pH, and temperature) and physicochemical (particle size and active area) factors on dye uptake by microplastics. The maximum amount of Cyan dye adsorbed onto polyethylene microplastics was reported to be 2874.4 mg/g. Polystyrene (PS) microplastics exhibited the highest adsorption capacity for aniline (0.060 mg/g) due to its surface area of 0.7214 m2/g. In 50 % of dye uptake studies on microplastics, the equilibrium condition was reached within 24 h. However, in a few cases, equilibrium was achieved in 8 days. The desorption efficiency of malachite green in the simulated gastric fluid at high temperatures was 81.4 %. The concentration of dyes in the isotherm studies of their adsorption by microplastics varied widely (5–160 mg/L). According to the criterion of R2 > 0.95, the Langmuir isotherm demonstrates a better fit with the data in most of the studies. The lowest uptake of dyes was observed at a pH of 1.5 under the same conditions. Studies have shown that higher temperatures can increase the ability of microplastics to attract and release organic and inorganic pollutants. The potential ecological effects of ‘microplastic-dye’ on organisms and the methods for removing microplastics were investigated. This paper has provided data for the assessment of the potential risks of ‘microplastic-dye’ to aquatic organisms.

 

 

Background Infectious diseases impose a significant burden on the global public health and economy, resulting in an estimated 15 million deaths out of 57 million annually worldwide. This study examines the current state of CRISPR-Cas12/Cas13 research, focusing on its applications in infectious disease detection and its evolutionary trajectory. Methods A bibliometric analysis and systematic review were conducted by retrieving CRISPR-Cas12/Cas13-related articles published between January 1, 2015 to December 31, 2022, from the Web of Science database. The research protocol was registered with International Platform of Registered Systematic Review and Meta-analysis Protocols (INPLASY202380062). Results Our search identified 1987 articles, of which, 1856 were included in the bibliometric analysis and 445 were used in qualitative analysis. The study reveals a substantial increase in scientific production on CRISPR-Cas12/Cas13, with an annual growth rate of 104.5%. The United States leads in the number of published articles. The systematic review identified 580 different diagnostic assays targeting 170 pathogens, with SARS-CoV-2 dominating with 158 assays. Recombinase polymerase amplification (RPA)/reverse transcription-RPA (RT-RPA) emerged as the predominant amplification method, while lateral flow assay was the most common readout method. Approximately 72% of the diagnostic assays developed are suitable for point-of-care testing. Conclusion The rapid increase in research on CRISPR-Cas12/Cas13 between 2015 and 2022 suggests promising potential for advancements in infectious disease diagnosis. Given the numerous advantages of CRISPR-Cas technology for disease detection over other methods, and the dedicated efforts of scientists from around the world, it is reasonable to anticipate that CRISPR-Cas technology may emerge as a formidable alternative, offering the possibility of expedited point-of-care testing in the not-too-distant future.

 

 

Parkinson’s disease is a neurodegenerative pathology of the central nervous system that affects thousands of individuals worldwide. There are several treatment methods, from drugs to emerging surgical methods. Many studies in this field are carried out annually, in view of this, this study aims to bibliometrically analyze the 50 most cited articles regarding this topic. In February 2022, a search was performed in the PubMed, SCOPUS and Embase databases using the search terms “parkinson’s disease”, “deep brain stimulation” and “pallidotomy”. A total of 960 articles were found and, after their selection, the analysis of the 50 most cited was performed and then the metrics analyzed were the H index of the first author, year of publication, institution, country of origin, journal and its impact factor, total number of citations and the article methodology. This analysis brought the characteristics of the articles with the greatest impact in the scientific community on the use of pallidotomy and deep brain stimulation (DBS), and some insights on studies in this area.

 

 

Natural resources deterioration, as well as greenhouse gas (GHG) emissions are a critical global problem, derived mainly from the use of fossil fuels. In recent years, several Latin American countries have sought alternatives to replace fuels with biofuels. In this regard, this article aims to make a bibliographic review focused on the analysis of the current situation of biofuel production and research development in Argentina, Brazil, Mexico, Chile, Costa Rica and Colombia. For this, seventy-seven investigations extracted in the last ten years from the databases ResearchGate, ScienceDirect, MDPI, Academic Google, Scopus, ScienceDirect, EBSCO and Elsevier were analyzed. Also, and for the same period, a bibliometric analysis of 355 investigations of the Web of Science database was carried out. The article presents the production figures, technologies, advances and challenges for the production of biofuels in these countries. Brazil stands out as a leader in the region and stands out worldwide in the generation of clean energy through the implementation of a biofuels policy and its incorporation into the transport sector. From this review, it is possible to know the state of production and research on biofuels in these countries and the challenges they face in achieving advances that do not reflect the comparative advantages they have due to the availability of raw materials for their production.

 

 

Parkinson’s disease is the second most common neurodegenerative disorder in the world. Thousands of scientific works are published every year. We have analyzed more than 3 thousand organizations, who have published works on various aspects of parkinson’s disease in the period from 2015 to 2021. We have evaluated 4 classical centrality indices (In-degree, Eigenvector, Pagerank and Betweenness) and 2 new centrality indices. The new indices allow to take into account group influence and to identify pivotal nodes. Using the method, we have extracted the most influential organizations in the scientific area of parkinson’s disease. Stability analysis allows us to measure the value of dynamic changes in the network during the period under consideration.

 

 

Information technologies are being extensively used by social entrepreneurs to achieve their social and financial goals. Studies on the convergence of social entrepreneurship with digital entrepreneurship is, nevertheless, lacking. Also, studies that relate corporate social responsibility (CSR), innovation, sustainability, and the integrated notion of digitalization of social entrepreneurship (DSE) are also questioned. This study sought to identify prospective topics for future researches to link DSE with various parameters by conducting a bibliometric review utilizing data pulled from the Scopus database. The clustering by document coupling analysis pinpointed to the industry 4.0 and digital economy themes, as well as to more specialized, COVID-19, innovation, sustainable development, and CSR themes. The study identified a number of themes that are under appreciated, such as social innovation, agro-ecology, and agriculture. The keyword co-occurrence network mostly identified five study areas, social entrepreneurship intentions, social enterprise sustainability and economic growth, sustainable development and socio-economic effects of DSE, entrepreneurs’ social innovation and business development, and industry 4.0, the digital economy and CSR.