Oct 2026· Discover Nano· Vol 21· 0 citations· 171 references
Medicine
Abstract
Pharmaceuticals and personal care products (PPCPs) are an increasing class of environmental pollutants of concern in aquatic ecosystems owing to their persistence and biological activity at low concentrations. Correct and selective monitoring of these substances is necessary to assess their ecological impacts and preserve water quality. The high conductivity, large surface area and tunable surface chemistry of two-dimensional transition metal carbides and nitrides (MXenes) have recently opened new avenues for electrochemical sensing. In this study we explain the state of the art of MXene nanoparticles, their characteristics, production and functionalization procedures that allow the integration of these materials in electrochemical and bioinspired sensing systems. Design advances such as biomimetic recognition elements, molecular imprinting, enzymes and nanocomposites are critically reviewed in terms of their contribution towards improving selectivity and operational stability of sensors. This study examines the analytical performance of MXene-based sensors for the ultra-trace detection of PPCPs in complex aquatic matrices, focusing on advances in sensitivity, antifouling strategies, and multiplexed detection. It also discusses future perspectives such as smart sensor networks and AI-driven data analytics, as well as issues in material scalability, sensor durability and real-world deployment. This study opens the door for the new potential of MXene-enabled platforms for the development of environmental analytical chemistry and shows the future research pathways towards sustainable and effective aquatic pollution monitoring.
The method, ECCOLA, is presented, which aims at making the high-level AI ethics principles more practical, making it possible for developers to more easily implement them in practice.
Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson· EUROMICRO Conference on Soft...· 64 citations· ⚡6
The goal is to not only refine the accuracy of the LLM-based tool but also to underscore its potential in streamlining the software development lifecycle through proactive code improvement and education.
Z. Rasheed, Malik Abdul Sami, Muhammad Waseem et al.· arXiv.org· 62 citations· ⚡3
The use of large language models to automatically improve the user story quality in Austrian Post Group IT agile teams is explored, with a reference model for an Autonomous LLM-based Agent System developed and implemented at the company.
Zheying Zhang, M. Rayhan, Tomas Herda et al.· International Conference on...· 48 citations· ⚡4
This paper introduces a novel multi-AI-agent system designed to fully automate SLRs, and demonstrates how it substantially reduces the time and effort traditionally required for SLRs while maintaining comprehensiveness and precision.
Abdul Malik Sami, Z. Rasheed, Kai-Kristian Kemell et al.· arXiv.org· 44 citations· ⚡2
The proposed LLM-based multi-agent system automates qualitative data analysis process, creating opportunities for researchers and practitioners, and future improvements focus on enhancing multilingual performance and integrating continuous expert feedback.
Z. Rasheed, Muhammad Waseem, Aakash Ahmad et al.· arXiv.org· 41 citations
MIT professors Adam Berinsky and Chara Podimata discuss a new project to track how AI chatbots are responding to questions about the 2026 U.S. midterm elections.
Microsoft Research Blog· microsoft.comOct 30, 2026
Evaluating Microsoft Copilot at enterprise scale requires test data that captures the full complexity of real organizations, yet real enterprise data contains sensitive information that cannot be used for evaluation under any circumstances. The post From synthetic enterprise data evaluations to real Microsoft Copilot AI confidence appeared first on Microsoft Research.
Critical flaws, compromised release channels and agentic AI threats landed within days of each other in mid-October 2026. Why “Black October” may say more about how well we now find weaknesses than about the attacks themselves. The post Black October? The Week AI Changed the Cybersecurity Conversation appeared first on GPT-Lab.
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