Evaluating gene expression patterns for NF-κB1, TNF, and VEGF A& VEGF B in a mouse model of SARS-CoV-2 infection
Artificial Intelligence in Ecuadorian SMEs: Drivers and Obstacles to Adoption
https://surl.li/qomdus This study analyzes the current state of artificial intelligence (AI) adoption among micro-, small-, and medium-sized enterprises (MSMEs) in Ecuador, with a focus on its application across core business functions. Using a stratified random sample of 385 firms from the most representative economic sectors, a survey instrument was designed to assess three dimensions: access to AI-enabling conditions, degree of AI utilization, and organizational characteristics. The results reveal that AI adoption remains limited and highly concentrated in marketing-related functions, particularly in content generation and social media automation, with minimal implementation in finance, logistics, and human resource management. The study also identifies the main barriers hindering AI adoption. The lack of qualified professionals and the unavailability of structured databases emerged as the most critical obstacles, followed by limited financial capacity. One-way ANOVA and Kruskal–Wallis tests confirmed significant differences in AI adoption levels based on company size and sector, especially in areas such as inventory optimization and design prototyping. These findings highlight a gap between the potential of AI technologies and their real-world implementation in Ecuadorian MSMEs. They underscore the need for targeted strategies focused on workforce training, digital infrastructure development, and institutional support to promote broader and more effective AI integration. https://doi.org/10.3390/info16060443
Analysis of the Influence of Sugarcane Bagasse Fibers in the Natural State on the Mechanical Properties of Concrete
This study aims to analyze the influence of sugarcane bagasse fiber (SCBF) without treatment on concrete and its impact on carbon footprint production. This review studies the impact of SCBF on the compressive strength, flexural strength, direct tensile strength, and elasticity modulus, considering fiber percentages of 1%, 3%, 5%, and 6%. The results showed that SCBF had a negative influence on concrete because as the percentage of fiber increased, it started to become invasive in the concrete mix and proportionally influenced the strength reduction, obtaining a maximum decrease of 60.96% in the compressive strength. However, the CO2 emissions decreased as the fiber percentage increased, generating maximum emission savings of 17.19%. https://doi.org/10.1080/15440478.2025.2451407
Retraction notice to ‘Seaweed biomass as a sustainable resource for synthesis of ZnO nanoparticles using Sargassum wightii ethanol extract and their environmental and biomedical applications through Gaussian mixture model’ [Environ. Res. 249 (2024) 117464] (Environmental Research (2024) 249, (S0013935123022685), (10.1016/j.envres.2023.117464))
This article has been retracted: please see Elsevier policy on article withdrawal (https://www.elsevier.com/about/policies-and-standards/article-withdrawal). This article has been retracted at the request of the Editor. During the course of the investigation, the assessing editor noted an excessive amount of citations in the Introduction, including a citation to this article itself. It was also discovered that the original and accepted versions of the manuscript contained data/figures previously published in Biomass Conv. Bioref. 14, 26173–26191 (2024) https://doi.org/10.1007/s13399-023-04977-1, by different authors, which were then removed after the manuscript was accepted, although some of the figures in the supplementary information from that source remain. The Figure S5 in the supplementary is taken from Youtube videos such as https://www.youtube.com/watch?v=9LsgBqm3yqs and https://www.youtube.com/watch?v=5sYW9JdAj_4. One of the conditions of submission of a paper for publication is that authors declare explicitly that their work is original and has not appeared in a publication elsewhere. Re-use of any data should be appropriately cited. As such this article represents a severe abuse of the scientific publishing system. The scientific community takes a very strong view on this matter and apologies are offered to readers of the journal that this was not detected during the submission process. Finally, an unauthorised authorship change was made when the revised version of this paper was submitted, following suggestions for relatively minor revisions from the reviewers and Guest Editor, with five authors – Yu Bai, Yan Cao, Yiding Sun, Faiz Abdulaziz Alfaiz, and Elimam Ali – being added to the paper to replace three other authors who were deleted. No satisfactory explanation was given for this change, nor was it approved by the editor. According to the Credit author statement, Authors Cao and Sun appear to have been involved with conceptualisation and writing the original draft, respectively, despite both authors being added at revision stage.This authorship change breaches the policies of the journal and as a result of this and the concerns outlined in the previous paragraph, the editors no longer have confidence in this paper and are retracting it. The journal apologises for not having identified the problematic authorship change during the review process and for any resulting inconvenience. https://doi.org/10.1016/j.envres.2025.122794
Advanced inorganic membranes for water purification: FeZr-MOF/GO composites with optimized adsorption performance
This study introduces FeZr-MOF/Graphene Oxide (GO) composite membranes as an innovative application of inorganic membrane technology for advanced separation and purification. These membranes were engineered to efficiently remove industrial dyes such as Congo red and methylene blue from aqueous solutions by leveraging the high surface area, chemical stability, and selective adsorption capabilities of FeZr-Metal-Organic Framework (FeZr-MOF).Based on laboratory evaluations, the composite membranes exhibited strong adsorption performance, achieving 87.5 mg/g capacities for Congo red and 80.2 mg/g for methylene blue. Integrating GO into the membrane matrix enhanced hydrophilicity, water permeability, and anti-fouling behavior, as evidenced by over 90 % permeability recovery after multiple cleaning cycles. This research reflects the latest advancements in inorganic membrane technology and bridge material innovation with industrial water purification needs. Machine Learning (ML), implemented via the Random Forest (RF) algorithm, was used to predict the impact of key operational parameters—pH, dye concentration, and contact time—on removal performance, and the model’s predictions aligned closely with experimental trends.These findings, supported by experimental data and predictive modeling, highlight the potential of FeZr-MOF/GO membranes as a scalable and robust material for sustainable water purification applications. https://doi.org/10.1016/j.seppur.2025.133899
Advanced inorganic membranes for water purification: FeZr-MOF/GO composites with optimized adsorption performance
This study introduces FeZr-MOF/Graphene Oxide (GO) composite membranes as an innovative application of inorganic membrane technology for advanced separation and purification. These membranes were engineered to efficiently remove industrial dyes such as Congo red and methylene blue from aqueous solutions by leveraging the high surface area, chemical stability, and selective adsorption capabilities of FeZr-Metal-Organic Framework (FeZr-MOF).Based on laboratory evaluations, the composite membranes exhibited strong adsorption performance, achieving 87.5 mg/g capacities for Congo red and 80.2 mg/g for methylene blue. Integrating GO into the membrane matrix enhanced hydrophilicity, water permeability, and anti-fouling behavior, as evidenced by over 90 % permeability recovery after multiple cleaning cycles. This research reflects the latest advancements in inorganic membrane technology and bridge material innovation with industrial water purification needs. Machine Learning (ML), implemented via the Random Forest (RF) algorithm, was used to predict the impact of key operational parameters—pH, dye concentration, and contact time—on removal performance, and the model’s predictions aligned closely with experimental trends.These findings, supported by experimental data and predictive modeling, highlight the potential of FeZr-MOF/GO membranes as a scalable and robust material for sustainable water purification applications. https://doi.org/10.1016/j.seppur.2025.133899