Producción Científica

 

 

This paper offers an examination of the current plastic waste landscape, with emphasis on the nine countries of the European University Alliance E³UDRES2, based on both the literature and official numbers, to verify the alignment of practical waste management practices with scientific tendencies and advancements. The paper includes a bibliometric analysis focusing on the overall plastic waste literature and the plastic waste literature of the E³UDRES2 countries. Additionally, a mass balance was calculated regarding the domestic waste management of each of the alliance countries in 2021. The main goal is to assess how scientific research in the field of plastic waste management is being implemented in practice, particularly in the context of the E³UDRES2 countries. Bibliometric results reveal significant growth in publications since 2006, with China, the USA, and India leading. Key themes reveal evident clusters around behavior and technology, encompassing both the properties of plastics and societal attitudes toward waste management policy measures. Mass balance results reveal that, in the nine countries of the alliance, Latvia and Finland exhibited high plastic recycling rates (85% and 49%, respectively), and Germany, despite its high population, generated less waste per capita and incinerated 64% of its plastic waste. Despite progress, the results highlight ongoing challenges in implementing comprehensive circular economy-focused policies for waste management in Europe yet reveal a growing commitment to improving waste treatment systems, leading to lower environmental impacts of plastic waste.

 

 

Mercury is a toxic pollutant that poses risks to both human and environmental health, making it a pressing public health concern. This study aimed to summarize the knowledge on mercury toxicology and the biological impairments caused by exposure to mercury in experimental studies and/or diagnosis in humans. The research was conducted on the main collection of Web of Science, employing as a methodological tool a bibliometric analysis. The selected articles were analyzed, and extracted data such as publication year, journal, author, title, number of citations, corresponding author’s country, keywords, and the knowledge mapping was performed about the type of study, chemical form of mercury, exposure period, origin of exposure, tissue/fluid of exposure measurement, mercury concentration, evaluation period (age), mercury effect, model experiments, dose, exposure pathway, and time of exposure. The selected articles were published between 1965 and 2021, with Clarkson TW being the most cited author who has also published the most articles. A total of 38% of the publications were from the USA. These studies assessed the prenatal and postnatal effects of mercury, emphasizing the impact of methylmercury on neurodevelopment, including motor and cognitive evaluations, the association between mercury and autism, and an evaluation of its protective effects against mercury toxicity. In observational studies, the blood, umbilical cord, and hair were the most frequently used for measuring mercury levels. Our data analysis reveals that mercury neurotoxicology has been extensively explored, but the association among the outcomes evaluated in experimental studies has yet to be strengthened. Providing metric evidence on what is unexplored allows for new studies that may help governmental and non-governmental organizations develop guidelines and policies.

 

 

Obesity and overweight are significant global health issues, and numerous obesity intervention studies have been conducted. Summarizing current knowledge of interventions aims to inform researchers and policymakers to keep up-to-date with the latest scientific advancements and trends. In this review, we comprehensively retrieved and screened 4,541 studies on obesity intervention published between 2018 and 2022 in the Web of Science Core Collection, and objectively presented research frontiers using bibliometric analysis. The research frontiers of intervention are mainly focused on dietary, exercise, pharmacological interventions, bariatric surgery, environmental, and cognitive interventions. Time-restricted eating is the hottest research topic, followed by probiotics and Roux-en-Y gastric bypass. Gut microbiota is located in the “Basic and transversal themes” quadrant with a high centrality and low density, which has great development potentiality. Obesity intervention is becoming increasingly common,and we advocate for researchers to undertake more focused research endeavors that consider the specific characteristics of diverse populations or patients.

 

 

This study undertakes a comprehensive bibliometric analysis of war and terrorism Insurance research spanning from 1914 to 2018. Leveraging tools such as Scopus and VOSviewer, the analysis involves 56 papers to unveil evolving trends and scholarly contributions. Collaborative network maps are employed to illuminate influential authors, top journals, key papers, funding institutions, and affiliations within the domain. One of the key findings of this research is that the volume of published papers on the topic of terrorism insurance is associated with major terrorism events, and there were no published papers on this topic after the year 2018. Significantly, the research underscores the substantial impact of existing studies on understanding the repercussions of war and terrorism Insurance while pinpointing persistent gaps in the field that necessitate further exploration. The originality of this study lies in its novel approach—a thorough bibliometric analysis, filling critical research gaps to offer valuable insights for both practitioners and academics. This study’s paramount importance is manifested in its potential to inform and benefit both practitioners and academics alike. By addressing research gaps, the findings contribute to the development of effective strategies for mitigating the risks associated with War and Terrorism Insurance. Essentially, this research not only advances our understanding of the complex domain but also provides practical implications for real-world applications.

 

 

We introduce an iterative discrete information production process where we can extend ordered normalised vectors by new elements based on a simple affine transformation, while preserving the predefined level of inequality, G, as measured by the Gini index. Then, we derive the family of empirical Lorenz curves of the corresponding vectors and prove that it is stochastically ordered with respect to both the sample size and G which plays the role of the uncertainty parameter. We prove that asymptotically, we obtain all, and only, Lorenz curves generated by a new, intuitive parametrisation of the finite-mean Pickands’ Generalised Pareto Distribution (GPD) that unifies three other families, namely: the Pareto Type II, exponential, and scaled beta distributions. The family is not only totally ordered with respect to the parameter G, but also, thanks to our derivations, has a nice underlying interpretation. Our result may thus shed a new light on the genesis of this family of distributions. Our model fits bibliometric, informetric, socioeconomic, and environmental data reasonably well. It is quite user-friendly for it only depends on the sample size and its Gini index.

 

 

In order to meet the international goals for a sustainable development, it is mandatory to implement energy saving solutions on existing buildings and industrial ones should be also addressed since industry related consumption covers approximately one third of the global energy demand. Industrial facilities are usually characterized by low overall quality standards and performance levels, largely influenced by their old age and architectural/technological, energy, and structural issues. The paper aims at outlining the current state of the research on manufacturing facilities, focusing on their energy efficiency and the related redevelopment solutions. The PRISMA methodology was adopted in the initial stages, coupled with a computer-aided bibliometric review tool: globally, 203 scientific papers retrieved on Web Of Science and ScienceDirect databases were analysed. Three main areas of interest were pointed out referring to structural and seismic behaviour, building envelope and systems performance, and energy-related issues. The analysis conducted revealed a significant gap in the literature concerning integrated retrofit solutions for industrial facilities and the review serves as a robust knowledge base for the development of comprehensive redevelopment guidelines for this peculiar building stock.

 

 

Harmful cyanobacterial blooms (HCBs) present a major risk to inland waters; therefore, various monitoring and management frameworks have been implemented to protect water quality, aquatic organisms, and humans from their negative impacts. Enabling proactive rather than reactive management, early warning systems within the lead time of HCBs at timescales ranging from hours to days is necessary to provide water managers with timely, evidence-based information for decision-making. To provide a state-of-the-art early warning system for HCBs, this study systematically reviewed scientific publications indexed in the Web of Science through bibliometric approaches, investigating current trends and developments. By focusing on the literature addressing the period preceding HCBs, a quantitative network analysis identified key indicators, state variables, and forecast horizons. Consequently, 116 documents related to eutrophic lakes and reservoirs in temperate, Mediterranean, and subtropical climates were analyzed. The frequently used HCB predictors in these studies were chlorophyll-a (chla) concentration and water temperature, while the commonly targeted outputs were chla and cyanobacterial cell density. Co-occurrence network analysis of the keywords addressed six clusters as the main research fields: molecular monitoring, remote sensing, in situ monitoring, resilience indicator utility, and inferential and deterministic modeling. The keywords were similarly identified by the network in the selected publications; however, specific terms associated with molecular identification, taste, and odor compounds were not observed. The results suggest that considerable progress in the early warning of HCBs requires enhancing interdisciplinary research to integrate the most relevant monitoring technologies, environmental indicators, and ecological knowledge about HCBs.

 

 

Objectives To examine the 16-year developmental history, research hotspots, and emerging trends of zinc-based biodegradable metallic materials from the perspective of structural and temporal dynamics. Methods The literature on zinc-based biodegradable metallic materials in WoSCC was searched. Historical characteristics, the evolution of active topics and development trends in the field of zinc-based biodegradable metallic materials were analyzed using the bibliometric tools CiteSpace and HistCite. Results Over the past 16 years, the field of zinc-based biodegradable metal materials has remained in a hotspot stage, with extensive scientific collaboration. In addition, there are 45 subject categories and 51 keywords in different research periods, and 80 papers experience citation bursts. Keyword clustering anchored 3 emerging research subfields, namely, #1 plastic deformation #4 additive manufacturing #5 surface modification. The keyword alluvial map shows that the longest-lasting research concepts in the field are mechanical property, microstructure, corrosion behavior, etc., and emerging keywords are additive manufacturing, surface modification, dynamic recrystallization, etc. The most recent research on reference clustering has six subfields. Namely, #0 microstructure, #2 sem, #3 additive manufacturing, #4 laser powder bed fusion, #5 implant, and #7 Zn–1Mg. Conclusion The results of the bibliometric study provide the current status and trends of research on zinc-based biodegradable metallic materials, which can help researchers identify hot spots and explore new research directions in the field.

 

 

During passive solar design of greenhouses, engineers usually encounter issues such as building form parameter selection. Suitable parameters can help to reduce energy losses related to interior temperature control and relatively intensive crop production. However, by using bibliometric analyses, no existing review works provide concise parameter selection lists. To fill in this gap, this paper compares and evaluates various passive technologies for greenhouse design in five areas: (1) orientation, (2) building structures, (3) envelope materials, (4) heat storage options, and (5) numerical modeling. First, the orientation of a passive solar greenhouse significantly influences its performance. Second, greenhouses exhibit various architectural shapes, including single- and multispan, with transparent and opaque envelopes. Third, greenhouses usually include envelopes constructed from transparent materials, opaque materials, and movable insulation materials. Fourth, most passive greenhouses provide daily energy storage systems equipped with storage media, including water, soil, rock, brick, and phase change material (PCM). Finally, this paper reviews numerical modeling and performance evaluations for passive greenhouses.

 

 

When a graphical representation of the cumulative percentage of total citations to articles, ordered from most cited to least cited, is plotted against the cumulative percentage of articles, we obtain a Leimkuhler curve. In this study, we noticed that standard Leimkuhler functions may not be sufficient to provide accurate fits to various empirical informetrics data. Therefore, we introduce a new approach to Leimkuhler curves by fitting a known probability density function to the initial Leimkuhler curve, taking into account the presence of a heterogeneity factor. As a significant contribution to the existing literature, we introduce a pair of mixture distributions (called PG and PIG) to bibliometrics. In addition, we present closed-form expressions for Leimkuhler curves. Some measures of citation concentration are examined empirically for the basic models (based on the Power and Pareto distributions) and the mixed models derived from these. An application to two sources of informetric data was conducted to see how the mixing models outperform the standard basic models. The different models were fitted using non-linear least squares estimation.