Diswandi Nurba from IPB University in Indonesia at al. systematically evaluated the performance of four aeration system designs through a combination of Computational Fluid Dynamics (CFD) simulations and AHP-TOPSIS multi-criteria decision analysis, providing a scientific answer to this problem. The study had been published in Frontiers of Agricultural Science and Engineering (DOI: 10.15302/J-FASE-2024577).

An international team from countries including Iran, Iraq, Uzbekistan, and India has co-authored a review paper published in the journal Frontiers of Agricultural Science and Engineering (DOI: 10.15302/J-FASE-2024564). The corresponding author is Dr. Mohammad MEHDIZADEH from University of Mohaghegh Ardabili. The article outlines the potential applications of machine learning technology in weed management and provides insights for addressing the aforementioned issues. In simple terms, machine learning acts like an “intelligent brain” for farmland——it can analyze vast amounts of agricultural data, automatically identify patterns, and make precise decisions, shifting weed control from a “broad net” approach to “precision strikes”.

Recently, Dr. Muhammad Waqar Akram and his team from the Department of Farm Machinery and Power at University of Agriculture Faisalabad in Pakistan developed a “Machine Vision-Based Automatic Fruit Grading System”, offering a new solution. The related article has been published in Frontiers of Agricultural Science and Engineering (DOI: 10.15302/J-FASE-2023532).

Dr. Roaf Ahmad Parray from ICAR-indian agricultural research institute (ICAR-IARI) and his colleagues provide an answer in a study published in Frontiers of Agricultural Science and Engineering (DOI: 10.15302/J-FASE-2024572). In this research, an international team of scientists from India, Denmark, and the United States developed an innovative technology integrating spectral sensors, machine learning models, and an intelligent spraying system, successfully applying it to control black rot disease in cauliflower. This technology, comprising three core components—non-destructive detection, intelligent decision-making, and targeted pesticide application—significantly reduces pesticide use and offers new insights for green agriculture.

The latest annual meeting for the Global Education Deans Forum brought together 53 representatives from 40 institutions across 29 countries in Shanghai and Lijiang, China. An article published online in ECNU Review of Education on May 27, 2025, attempts to  capture how a group of global education leaders view the promise and perils of AI amidst a rapidly changing educational landscape.

UCLA researchers have introduced a framework for synthesizing arbitrary, spatially varying 3D point spread functions (PSFs) using diffractive processors. This approach enables unique imaging capabilities—such as snapshot 3D multispectral imaging—without relying on spectral filters, axial scanning, or digital reconstruction methods. The proposed framework could open up transformative possibilities for computational imaging, optical sensing and spectroscopy, as well as 3D optical information processing.

In a review published in Molecular Biomedicine, the authors summarized the impact of exosomes on the progression of diseases through their carried cargo, affecting the microenvironment in inflammatory diseases and cancer. Moreover, exosomes have great potential as diagnostic biomarkers, therapeutic drugs, and drug delivery carriers in inflammatory diseases and cancer.

An editorial in eGastroenterology by Chen, Guillot, and Schneider issues a critical warning about the rampant misuse of Mendelian randomisation (MR) in modern medical research. Despite MR's powerful potential for causal inference using genetic data, the exponential growth in publications—many employing overly simplistic methods—threatens the credibility of the field. The authors highlight key methodological missteps, including misuse of weak genetic instruments and disregard for pleiotropy. They propose comprehensive guidelines for researchers, editors, and reviewers to elevate scientific rigor and preserve MR’s value. Their message is clear: MR must be applied with discipline and biological plausibility to remain credible.