As climate change intensifies, the accelerated spread of plant diseases poses severe threats to global crop production, leading to substantial losses in yield, quality, and economic returns, thereby jeopardizing food security and agricultural sustainability. With increasing awareness of the environmental risks associated with chemical pesticides, eco-friendly alternatives are urgently needed. Although biological control represents a promising green strategy, its practical efficacy is often limited by poor microbial survival, low environmental stability, and short functional duration under field conditions. In response, controlled-release gel encapsulation technology has emerged as an innovative approach, integrating advances in materials science, microbiology, and plant pathology. By combining physical protection, controlled delivery, and induced resistance mechanisms, this technology significantly improves the viability, persistence, and performance of beneficial microorganisms in agricultural settings. This review systematically examines the application of controlled-release gel-based encapsulation of beneficial microbes in plant disease management, covering their mechanisms of action, material selection, encapsulation techniques, and practical benefits, while also addressing current challenges. Future perspectives should focus on the development of intelligent-responsive materials and the enhancement of the stability of target microorganisms. Moreover, the environmental safety and ecological sustainability of these materials should be evaluated using multi-omics and artificial intelligence technologies combined with systematic field validation and full life-cycle assessment. This review aims to establish a scientific foundation and offer strategic guidance for the practical application and optimization of controlled-release gel encapsulation technology in sustainable, green plant disease management.
GAOKAO-Bench is introduced, an intuitive benchmark that employs questions from the Chinese GAOKAO examination as test samples, including both subjective and objective questions that contribute a robust evaluation benchmark for future large language models and offers valuable insights into the advantages and limitations...
Xiaotian Zhang, Chun-yan Li, Yi Zong et al.· arXiv.org· 216 citations· ⚡17
This work investigates the possibilities of using LLMs in a resume screening setting via a document retrieval framework that simulates job candidate selection and finds that the MTEs are biased, significantly favoring White-associated names in 85% of cases and female-associated names in only 11.1% of cases.
This work shows that orders of magnitude enhancement in performance could be obtained by a combination of hardware improvements and tight quantum-HPC integration and introduces high-performance architectures for quantum-probabilistic computing with custom-designed accelerators to tackle today's industry-scale classical...
Masoud Mohseni, Artur Scherer, K. Johnson et al.· arXiv.org· 121 citations· ⚡9
This paper presents a comprehensive overview of the Ultralytics YOLO family, emphasizing architectural evolution, benchmarking, deployment, and emerging directions from YOLOv5 through YOLO27, and examines detection, segmentation, depth, classification, pose, oriented detection, tracking, export, quantization, and deplo...
This work revisits schema linking when using the latest generation of large language models (LLMs) and finds empirically that newer models are adept at utilizing relevant schema elements during generation even in the presence of large numbers of irrelevant ones.
Karime Maamari, Fadhil Abubaker, Daniel Jaroslawicz et al.· arXiv.org· 109 citations· ⚡19
A novel threat is unveiled in which attackers steer the RAG system's response by injecting malicious passages into its knowledge base, enabling the attacker to steer the response without altering the user input or modifying the RAG weights.
Jiaqi Xue, Meng Zheng, Yebowen Hu et al.· arXiv.org· 109 citations· ⚡8
With $2.1 million funding from Google.org, the open-source Public Transit Intelligence Hub will unify public transit monitoring, operations, and passenger communication.
Professor Sherry Turkle’s new book, “Artificial Intimacy,” offers a withering critique of chatbots and the antisocial dynamics she believes they encourage.
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.