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The surge in economic growth and increased agricultural output can augment societal well-being whilst proliferating environmental stressors. So, the study tests the validity of the "agriculture-induced Environmental Kuznets Curve hypothesis" (AEKC) by assessing the varied environmental proxies that have yet to be accounted for earlier in the case of BRICS economies. Furthermore, most studies have utilised "first-generation econometric approaches" as the "cross-sectional dependency" has not been deemed in estimation. On account of this, the research employed "second-generation CIPS and CADF unit root test", "Westerlund cointegration test", "fully modified ordinary least square" (FMOLS) and "dynamic ordinary least square" (DOLS) to test the validity of AEKC in "BRICS countries" for 30 years. A positive association between agriculture and "ecological footprint" has been found which evidences the presence of an "inverted U-shaped AEKC" in BRICS nations. Another finding shows that the favourable impact of agriculture towards climate change can be moderated by illustrating the interaction effect of "human capital" and "renewable energy" with "agriculture". Lastly, the investigation brings forth the policy repercussions and acumens for the BRICS governments and policymakers in halting climate change by using renewable energy in agriculture and building human capital., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Strawberry is a popular and nutritious fruit. However, its improper post-harvest handling leads to quality degradation. The aim of this study was to investigate the effects of active paper packaging placements methods on strawberry (Fragaria x ananassa) quality during refrigerated storage. Strawberry quality was determined based on the physical (weight loss, hardness, color), chemical (pH, total titratable acid, total soluble solids and vitamin C content) and microbiological (total plate count) properties. The results of this study indicated that different placement methods of active paper packaging had no significant effect on the physical and chemical qualities; but it did affect the microbiological quality of the strawberries. At the end of the experiment (12 days), the microbial content of C (the bottom and walls), D (covering all surfaces) and E (cut into pieces) samples were significantly lower than the A (without active paper packaging) and B (the bottom) samples. The Total Plate Count (TPC) values of the control and B samples were higher than the maximum acceptable limit of 6 log10 colony-forming units (CFU) g-1, while the other samples remained below the limit. These results indicated that a larger surface area of active paper that had contact with the strawberries provided better protection against microbes. Due to their microbial properties, C, D and E treatments maintained the strawberry quality for up to 12 days, compared with 9 days for control and B treatments. Active paper packaging containing oleoresin from solid waste of pressed Curcuma xanthorrhiza Roxb. can be applied to extend the shelf life of strawberries during refrigerated storage.

[Purpose/Significance] Since the outbreak of COVID-19, there has been a rapid increase in the number of studies related to COVID-19 at home and abroad. Review of relevant literature on COVID-19 provides data resources for related research on the emergence and transmission mechanism of SARS-CoV-2. However, the current COVID-19 related dataset is a collection of the literature, without classifying the data for each subfield, and the coarse-grained information such as the title and author fails to provide an in-depth understanding of the progress of COVID-19 research. Therefore, this paper created a dataset for the COVID-19 sub-domain and a fine-grained entity dataset. [Method/Process] Firstly, this paper proposed a literature screening method based on active learning model, which can obtain more valuable marker samples with less labor cost, so that the classifier has better generalization performance. We considered three base classifiers: Support Vector Machine (SVM), Logistic Regression (LR), and Random Forest (RF), while considering four query strategies: uncertainty sampling, expected error reduction, committee-based query, and random sampling. Taking the origin of SARS-CoV-2, one of the sub-fields related to SARS-CoV-2, as an example, articles related to the origin of SARS-CoV-2 were efficiently and accurately located from the literature. At the same time, this paper designed a labeling scheme covering 18 types of entities, including not only genes, proteins, compounds and other entities that are universal in the biological field, but also corona viruses and wild animals that are unique to the field of SARS-CoV-2. In this paper, visual annotation tool BRAT was used for entity annotation. The tagging team consisted of an administrator and six annotators, and the entity tagging consisted of two rounds. What's more, multi-k consistency index was used to calculate the consistency score of annotation results. [Results/Conclusions] The results of the active learning model show that the uncertain sampling query strategy has the best performance. SVM, LR and RF based on uncertain sampling can correctly screen 425, 465 and 489 articles, respectively. After the removal of overlapping articles, a dataset related to the origin of SARS-CoV-2 was constructed, containing a total of 885 articles. Secondly, based on the proposed entity labeling scheme, 6 annotators completed 99 papers. Based on the results of fine marking, this paper constructed an entity dataset containing 39,118 entities, which is the largest and most comprehensive entity corpus in the field of COVID-19.

Landscapes can be seen as important socio-ecological systems [...]

[Purpose/Significance] This paper clarifies the concept of novelty, reviews different novelty measurements, and summarizes different types and research progress of novelty detection at home and abroad. It is of great significance to the development of science and scientific technological planning. [Method/Process] By summarizing existing relevant Chinese and English literature, this paper reviews the definitions of novelty, different novelty measurements such as content analysis and citation analysis, as well as their evaluation methods. [Result/Conclusion] Most of the existing methods measure the novelty from a single perspective, and few used combined methods. Therefore, both qualitative and quantitative methods should be taken into consideration to form a comprehensive analysis in the future.

[Purpose / Signficance] The current competition of comprehensive national strength relies more on fundamental research, and highly cited papers have important significance in the evaluation and analysis of fundamental research. Revealing the differences between China and USA in leading basic research from the perspective of highly cited papers, we provide basic data support for national scientific research management decision-making and institution building. [Method / Process] Based on ESI highly cited papers of China and USA, this article uses bibliometric methods and Y index to analyze the specific features and differences of China and USA among three dimensions—trends of publication, country cooperation and institutional output.[Results / Conclusions] The study shows that: (1) Overall, the highly cited papers of China is 2.99 times that of the American highly cited papers, but the gap is narrowing yearly. At the same time, the low citation frequency and the low proportion of highly cited papers are still the shortcomings that limit Chinese international influence. (2) China and USA are closely cooperating with each other. USA dominates scientific research cooperation, as the proportion of first authors and corresponding authors and leading papers is significantly higher than that in China. (3) Chinese high-output institutions have obvious advantages of corresponding authors, but the output gap between institutions is large. And the American high-output institutions are evenly distributed, and they are characterized by deeper and broader international cooperation and inter-agency cooperation.

[Purpose/Significance] This paper investigates the research on author name disambiguation published in recent years, and reviews the development context of relevant research from the perspective of the impact of data on author name disambiguation methods, so as to provide reference for further research. [Method/Process] The papers related to author name disambiguation were collected from English research databases such as Web of Science, Scopus, Google Academic, ACM Digital Library, IEEE Xplore, ScienceDirect, Scopus and Springer Link, and Chinese research databases such as CNKI, CQVIP and WANFANG. The search results cover the relevant papers published from 1998 to 2021. On the premise of giving consideration to authority, influence and novelty, 46 publicationswere selected for review. There are many types and structures of author name disambiguation data. For example, literature feature information is generally presented in unstructured text, and the extracted features can be stored and represented in two-dimensional tables; Citation information and interpersonal relationship are network relational data, which can be stored and represented by graphs, key value pairs or two-dimensional tables. The fundamental reason for different data structures lies in their semantic differences, but the data structure itself determines its applicable algorithm. According to the structure of characteristic data used in the author name disambiguation task and the different corresponding data processing algorithms, the relevant research is divided into three categories: 1) disambiguation method based on literature characteristics, 2) disambiguation method based on social network and 3) disambiguation method by integrating external knowledge. The impact of data on the author name disambiguation method is examined from the data level. [Results/Conclusions] The analysis found that with the progress of technology, deep learning methods have been widely used. Compared with the improvement of the model, the feature learning and representation based on deep learning can significantly improve the effect of the author name disambiguation algorithm. In addition, in order to overcome the problem of insufficient data utilization by a single method and improve the utilization efficiency of data, the three methods show the trend of mutual combination and complementary gain. From the literature research results, there are few related studies on incremental author name disambiguation and multi-language author name disambiguation, which could be one of the directions for further research.

Abstract Silage quality remains an important issue in farming, as do limitations in the range of products suitable for animal fodder. We therefore explored the microorganisms that are critical for the fermentation quality of paper mulberry silage. Low (unwilted) and high (wilted) dry matter (DM) paper mulberry were harvested at two cutting times. These were ensiled for 0, 3, 7, 14, and 56 days, respectively. Compared with unwilted silages, wilting significantly decreased (p