Producción Científica

 

 

The aim of this study is to provide effective solutions to promote the transition of resource-based cities to low carbon and sustainable development. Firstly, this study investigates the background of low-carbon transformation of resource-based cities. Secondly, it introduces the application method of Chat Generative Pre-trained Transformer (ChatGPT) in detail. Finally, this study proposes a comprehensive application of ChatGPT and artificial bee colony (ABC) algorithm. The results show that the average energy utilization efficiency improvement index of the group using ChatGPT is 0.11. The average energy efficiency improvement index of the group using ABC algorithm is 0.02 higher than that of the control group. The integrated application of ChatGPT and ABC algorithm can further improve the low-carbon transformation effect of resource-based cities and achieve the goal of green development.

 

 

In the last decade, biochar application research has emerged as a hot topic in water treatment studies, which made biochar adsorption one of the primary wastewater treatment strategies. This paper presents a global bibliometric analysis of 2673 publications from the Web of Science database, spanning 2011–2022. For a comprehensive understanding of the research status and trends in biochar adsorption for wastewater treatment, the advanced quantitative and visual analysis tools (i.e., CiteSpace and ArcGIS) were employed. The results showed that China emerged as the leading country with the most published articles. The key research area is on the magnetic adsorption of biochar in wastewater. The articles summarized in the review demonstrated unequivocally that biochar can treat a wide range of wastewater even though the adsorption mechanisms of biochar on heavy metals, inorganic salts and organic pollutants in wastewater are not entirely consistent. The review further analyzes the factors affecting the performance of biochar in adsorbing pollutants from wastewater and the improvement measures of biochar functional characteristics, proposing the future research directions focusing on the improvement of the adsorption capacity of biochar products. The information synthesis and discussion would provide valuable insights on the historical, current, and future trends in biochar research, beneficial to solve the practical problems of water pollution and improve the quality of the environment.

 

 

The aim of this study was to systemically evaluate how different pyrolysis temperatures (400, 550, and 700 °C) and particle sizes (1–2 mm and 63–75 µm) were influenced biochar evolution, made from urban pruning waste, during pyrolysis process and to establish their relationships with biochar potential for removal of lead (Pb), cadmium (Cd), and manganese (Mn) from real municipal solid waste landfill leachate. The effects of pH (2–7), contact time (30–300 min) and adsorbent dosage (0.1–5 g L−1) on heavy metals removal were also examined. The results showed that physicochemical properties of biochar were greatly influenced by pyrolysis temperature. Particle size, however, showed little influence on biochar characteristics (p > 0.05). The yield, volatile matter, hydrogen and oxygen contents, and surface functional groups decreased consistently with increasing pyrolysis temperature. An increase in the pH, electrical conductivity, ash, fixed carbon, and specific surface area values was also found. In biochar samples formed at high temperatures (i.e., 550 and 700 °C), Fourier transform infrared spectroscopy-FTIR studies confirmed the increase in aromaticity. Field emission scanning electron microscopy-FESEM images showed differences in the microporous structure and lower size pores at higher temperatures. Biochar pyrolyzed at 700 °C with a particle size of 63–75 µm (i.e., Lv700-63) showed the highest removal efficiency performance. Pb and Cd ions were completely removed (100%) by 0.2 g L−1 Lv700-63 at 7.0 pH and contact times of 120 and 90 min, respectively. The maximum percentage removal of Mn was 86.20% at optimum conditions of 0.2 g L−1 Lv700-63 dosage, 7.0 pH, and 180 min contact time. The findings suggests that the surface complexation, π-electron coordination, and cation exchange were the dominant mechanisms for the Pb, Cd, and Mn removal onto Lv700-63.

 

 

Phyllosphere endophytes play a critical role in a myriad of biological functions, such as maintaining plant health and overall fitness. They play a determinative role in crop yield and quality by regulating vital processes, such as leaf functionality and longevity, seed mass, apical growth, flowering, and fruit development. This study conducted a comprehensive bibliometric analysis aiming to review the prevailing research trajectories in phyllosphere endophytes and harness both primary areas of interest and emerging challenges. A total of 156 research articles on phyllosphere endophytes, published between 2002 and 2022, were retrieved from the Web of Science Core Collection (WoSCC). A systematic analysis was conducted using CiteSpace to visualize the evolution of publication frequency, the collaboration network, the co-citation network, and keywords co-occurrence. The findings indicated that initially, there were few publications on the topic of phyllosphere endophytes. However, from 2011 onwards, there was a notable increase in the number of publications on phyllosphere endophytes, gaining worldwide attention. Among authors, Arnold, A Elizabeth is widely recognized as a leading author in this research area. In terms of countries, the USA and China hold the highest rankings. As for institutional ranking, the University of Arizona is the most prevalent and leading institute in this particular subject. Collaborative efforts among the authors and institutions tend to be confined to small groups, and a large-scale collaborative network needs to be established. This study identified the influential journals, literature, and hot research topics. These findings also highlight the interconnected nature of key themes, e.g., phyllosphere endophyte research revolves around the four pillars: diversity, fungal endophytes, growth, and endophytic fungi. This study provides an in-depth perspective on phyllosphere endophytes studies, revealing the identification of biodiversity and microbial interaction of phyllosphere endophytes as the principal research frontiers. These analytical findings not only elucidate the recent trajectory of phyllosphere endophyte research but also provide invaluable insights for similar studies and their potential applications on a global scale.

 

 

This study investigates the multifaceted impacts of Metaverse Based Language Teaching on high school L2 vocabulary learning and retention, engagement, community feeling, and diverse dimensions of presence, namely social, cognitive, teaching, and overall presence. Adopting a quasi-experimental design, the study provides an in-depth controlled trial. The participants in this study consist of 86 (43 male, 43 female) high school English language learners in Türkiye, who are assigned to two groups. The control group uses traditional instructional technologies while the experimental group engages with metaverse technology. The lessons are based on social constructivist theory for both groups. Pre- and post-tests are employed to quantitatively assess vocabulary learning and retention and reveal substantial improvements in both areas. A series of carefully selected psychometric scales capture core aspects of engagement, community feeling, and presence. The findings reveal increased levels of engagement and a sense of presence, and connectedness within the language learning community, which confirms the efficacy of the MBLT. However, the improvement in social presence does not reach statistical significance. Cumulatively, the findings of this research transcend mere quantifiable improvements in vocabulary learning and retention. They reveal a holistic transformation of the language learning experience by emphasizing the significance of social interactions and digital embodiment in high school second language education through metaverse. The research highlights the metaverse’s potential in shaping the future of language education, reimagining traditional paradigms, and proposing a new era of immersive, interactive, and transformative pedagogy.

 

 

Autosomal dominant polycystic kidney disease (ADPKD) is a monogenic, rare disease, characterized by the formation of multiple cysts that grow out of the renal tubules. Despite intensive attempts to develop new drugs or repurpose existing ones, there is currently no definitive cure for ADPKD. This is primarily due to the complex and variable pathogenesis of the disease and the lack of models that can faithfully reproduce the human phenotype. Therefore, the development of models that allow automated detection of cysts’ growth directly on human kidney tissue is a crucial step in the search for efficient therapeutic solutions. Artificial Intelligence methods, and deep learning algorithms in particular, can provide powerful and effective solutions to such tasks, and indeed various architectures have been proposed in the literature in recent years. Here, we comparatively review state-of-the-art deep learning segmentation models, using as a testbed a set of sequential RGB immunofluorescence images from 4 in vitro experiments with 32 engineered polycystic kidney tubules. To gain a deeper understanding of the detection process, we implemented both pixel-wise and cyst-wise performance metrics to evaluate the algorithms. Overall, two models stand out as the best performing, namely UNet++ and UACANet: the latter uses a self-attention mechanism introducing some explainability aspects that can be further exploited in future developments, thus making it the most promising algorithm to build upon towards a more refined cyst-detection platform. UACANet model achieves a cyst-wise Intersection over Union of 0.83, 0.91 for Recall, and 0.92 for Precision when applied to detect large-size cysts. On all-size cysts, UACANet averages at 0.624 pixel-wise Intersection over Union. The code to reproduce all results is freely available in a public GitHub repository.

 

 

Over the past decade, a substantial body of research exploring soundscapes in religious historical buildings has emerged, yet a comprehensive summary of this work is lacking. This paper selects 74 typical studies of soundscapes in religious historical buildings published between 2011 and 2022 to conduct quantitative statistics and visualization analysis from a bibliometric perspective. The selected literature is categorized based on the type of religious building, Christian, Islamic, or Buddhist. The literature is further segmented according to the research subject, including sound field studies, sound analyses, and evaluations of the acoustic environment. The research methods employed are also differentiated and include sound field measurements, acoustic simulations, questionnaires and auralization procedures. The analysis reveals pronounced disparities in research foci depending on the type of religious historical building. For instance, studies on the soundscape in Christian churches tend to focus on objective sound field attributes and frequently employ sound field simulations to analyse the acoustic parameters of diverse church spaces and materials. Conversely, research on the soundscape in Islamic mosques prioritizes speech intelligibility and acoustic comfort, while studies of the soundscape of Buddhist temples gravitate towards the impact of natural and religious sounds on individuals. This paper anticipates the future direction of soundscape research on religious historical buildings.

 

 

Background: Social Network Analysis is a method of analyzing coauthorship networks or relationships through graph theory. Institutional Development Award (IDeA) Networks for Clinical and Translational Research (IDeA-CTR) was designed to expand the capability for clinical and translational research to enhance National Institutes of Health funding. Methods: All publications from a cohort of clinical and translational scientists in Oklahoma were collected through a PubMed search for 2014 through 2021 in October 2022. For this study’s bibliometric portion, we pulled the citations from iCite in November of 2022. Results: There were 2,391 articles published in 1,019 journals. The number of papers published by year increased from 56 in 2014 to 448 in 2021. The network had an average of 6.4 authors per paper, with this increasing by year from 5.3 in 2014 to 6.9 in 2021. The average journal impact factor for the overall network was 7.19, with a range from 0.08 to 202.73. The Oklahoma Shared Clinical and Translational Resources (OSCTR) network is a small world network with relatively weak ties. Conclusions: This study provides an overview of coauthorship in an IDeA-CTR collaboration. We show the growth and structure of coauthorship in OSCTR, highlighting the importance of understanding and fostering collaboration within research networks. © The Author(s), 2023. Published by Cambridge University Press on behalf of The Association for Clinical and Translational Science.

 

 

This study investigates the influence of the expansion of the virtual arts market on private sustainable investment in China spanning the years 1985 to 2021, employing the autoregressive distributed lag model. The results indicate that a 1% rise in the virtual arts market correlates with a short-term surge of around 0.46% in private sustainable investment, with a lasting increase of 0.38%. Furthermore, factors such as social inclusion, privatization, economic size, financial development, and renewable deployment significantly shape private sustainable investment patterns. Noteworthy policy recommendations arising from these findings include the integration of sustainability topics into educational curricula, the establishment of online platforms dedicated to sustainable virtual arts, the cultivation of green financing markets, and the promotion of collaborations among virtual arts institutions with a specific emphasis on sustainability.

 

 

Objective: to characterize the scientific production in Human-Computer Interaction (HCI) of productivity fellows in Information Science in Brazil (PQ-CI-CNPq). Method: it used bibliometric techniques to characterize the universe of 53 articles published by the PQ-CI-CNPq on Human-Computer Interaction. Result: it presents how themes related to the HCI domain were explored by the scientific community of PQs in Information Science. Among the results, the data obtained indicate that publications on this topic appear from 2001, without publications in the 1990s; studies in “information architecture”, which is the most used keyword in the analyzed articles, stand out in the HCI domain in Information Science, and; there is a prominent influence of the authors Morville and Rosenfeld on the publications. Conclusions: the journals chosen to publish on this topic are mostly well qualified by Capes, and this fact may attest to the quality of the production, due to the seriousness and legitimacy of the journals in which such a production is published. It seems that the HSI had information architecture as the most representative theme in the scope of CI, among the PQ-CI-CNPq, which can be considered as a basic theme in this universe and that offers theoretical and practical support to other concepts and applications, which have also been studied such as usability, accessibility, and findability.