Lilium spp. polysaccharides (LSPs) are gaining significant attention for their diverse health benefits, including antioxidant, antitumor, and antibacterial properties. This paper critically analyzes a recent comprehensive review by Li et al., published in International Journal of Biological Macromolecules, focusing on LSP extraction, purification, and health benefits. While the original review offers valuable insights, this critique identifies opportunities to strengthen the bibliometric analysis section. This study employs a comprehensive search strategy in Scopus using specific keywords and covering a broader time frame (1975-2023), revealing 94 research articles on LSPs. The critique proposes improvements to enhance transparency and impact, such as specifying search queries and Boolean operators used across databases, detailing selection criteria, and incorporating advanced analyses. This article discusses author keyword analysis, co-citation analysis of cited authors, and bibliographic coupling analysis of documents using VOSviewer software. The global landscape mapping of LSP relationships involving authors, countries, and keywords was determined using RStudio software. These refinements will provide a more robust foundation for understanding the LSP research landscape and future research directions while also addressing common pitfalls and suggesting improvements in bibliometric analysis for future studies.
Inadequate management and treatment of wastewater pose significant threats, including environmental pollution, degradation of water quality, depletion of global water resources, and detrimental effects on human well-being. Biogranulation technology has gained increasing traction for treating both domestic and industrial wastewater, garnering interest from researchers and industrial stakeholders alike. However, the literature lacks comprehensive bibliometric analyses that examine and illuminate research hotspots and trends in this field. This study aims to elucidate the global research trajectory of scientific output in biogranulation technology from 1992 to 2022. Utilizing data from the Scopus database, we conducted an extensive analysis, employing VOSviewer and the R-studio package to visualize and map connections and collaborations among authors, countries, and keywords. Our analysis revealed a total of 1703 journal articles published in English. Notably, China emerged as the leading country, Jin Rencun as the foremost author, Bioresource Technology as the dominant journal, and Environmental Science as the prominent subject area, with the Harbin Institute of Technology leading in institutional contributions. The most prominent author keyword identified through VOSviewer analysis was "aerobic granular sludge," with "sequencing batch reactor" emerging as the dominant research term. Furthermore, our examination using R Studio highlighted "wastewater treatment" and "sewage" as notable research terms within the field. These findings underscore a diverse research landscape encompassing fundamental aspects of granule formation, reactor design, and practical applications. This study offers valuable insights into biogranulation potential for efficient wastewater treatment and environmental remediation, contributing to a sustainable and cleaner future.
Amidst the increasing significance of innovative solutions for bioremediation of heavy metal removal, this paper offers a thorough bibliometric analysis of microbial-induced carbonate precipitation (MICP) for heavy metal removal, as a promising technology to tackle this urgent environmental issue. This study focused on articles published from 1999 to 2022 in the Scopus database. It assesses trends, participation, and key players within the MICP for heavy metal sequestration. Among the 930 identified articles, 74 countries participated in the field, with China being the most productive. Varenyam Achal, the Chinese Academy of Sciences, and Chemosphere are leaders in the research landscape. Using VOSviewer and R-Studio, keyword hotspots like "MICP", "urease", and "heavy metals" underscore the interdisciplinary nature of MICP research and its focus on addressing a wide array of environmental and soil-related challenges. VOSviewer emphasises essential terms like "calcium carbonate crystal", while R-Studio highlights ongoing themes such as "soil" and "organic" aspects. These analyses further showcase the interdisciplinary nature of MICP research, addressing a wide range of environmental challenges and indicating evolving trends in the field. This review also discusses the literature concerning the potential of MICP to immobilise contaminants, the evolution of the research outcome in the last two decades, MICP treatment techniques for heavy metal removal, and critical challenges when scaling from laboratory to field. Readers will find this analysis beneficial in gaining valuable insights into the evolving field and providing a solid foundation for future research and practical implementation.
The resilient modulus (MR) of different pavement materials is one of the most important input parameters for the mechanistic-empirical pavement design approach. The dynamic triaxial test is the most often used method for evaluating the MR, although it is expensive, time-consuming, and requires specialized lab facilities. The purpose of this study is to establish a new model based on Long Short-Term Memory (LSTM) networks for predicting the MR of stabilized base materials with various additives during wet-dry cycles (WDC). A laboratory dataset of 704 records has been used using input parameters, including WDC, ratio of calcium oxide to silica, alumina, and ferric oxide compound, Maximum dry density to the optimal moisture content ratio (DMR), deviator stress (σd), and confining stress (σ3). The results demonstrate that the LSTM technique is very accurate, with coefficients of determination of 0.995 and 0.980 for the training and testing datasets, respectively. The LSTM model outperforms other developed models, such as support vector regression and least squares approaches, in the literature. A sensitivity analysis study has determined that the DMR parameter is the most significant factor, while the σd parameter is the least significant factor in predicting the MR of the stabilized base material under WDC. Furthermore, the SHapley Additive exPlanations approach is employed to elucidate the optimal model and examine the impact of its features on the final result.