Environment

Abstract Recent advancements in artificial intelligence (AI) have catalyzed the emergence of agentic information systems (IS), which exhibit autonomous behavior and advanced cognitive capabilities. Unlike traditional IS, which functioned primarily as reactive tools supporting humans, agentic IS can make decisions independently, act in unstructured environments, and even delegate tasks to humans. This paradigm shift fundamentally transforms the human-IS relationship, questioning the long-standing

The development of data-driven and targeted drug delivery systems is essential for advancing precision therapeutics. Despite substantial progress in nanocarrier development, conventional platforms continue to face major challenges in clinical translation due to biological complexity, off-target accumulation, and limited adaptability to dynamic physiological environments. The integration of nanoarchitectonics and artificial intelligence (AI) offers an advanced strategy for engineering delivery sy

, the field of micro/nanorobots has evolved from science fiction to reality, with significant advancements in biomedical and environmental applications. Despite the rapid progress, the deployment of functional micro/nanorobots remains limited. This review of the technology roadmap identifies key challenges hindering their widespread use, focusing on propulsion mechanisms, fundamental theoretical aspects, collective behavior, material design, and embodied intelligence. We explore the current stat

The integration of Internet of Things (IoT) sensors and Machine Learning (ML) technologies has transformed precision agriculture by enabling data-driven, adaptive, and efficient farming practices. IoT sensors provide continuous, high-resolution monitoring of critical agricultural parameters, including soil health, crop growth, and environmental conditions. Coupled with advanced ML algorithms, this data facilitates predictive analytics and real-time decision-making, optimizing resource utilizatio

Engineering biology applies synthetic biology to address global environmental challenges like bioremediation, biosequestration, pollutant monitoring, and resource recovery. This perspective outlines innovations in engineering biology, its integration with other technologies (e.g., nanotechnology, IoT, AI), and commercial ventures leveraging these advancements. We also discuss commercialisation and scaling challenges, biosafety and biosecurity considerations including biocontainment strategies, s

Environmental, Social, and Governance (ESG) is highly consistent with the “Dual Carbon” goals proposed by China and has become an important indicator to measure enterprises’ high-quality development. This study explores the impact of intelligent manufacturing on corporate ESG performance and its potential mechanisms. Using the dataset of China’s A-share listed companies from 2009 to 2021, we treat the intelligent manufacturing pilot programs (IMPP) as a quasi-natural experiment and use the stagg

The rising demand for energy requires high investments in network extensions and renewable sources, alongside replacing inefficient systems. Smart maintenance is important in minimizing unscheduled outages, reducing costs, improving network security, and increasing equipment’s life expectancy. The vast amount of data collected by sensors and measurements in energy networks makes it hard for humans to detect failures continuously. Thanks to recent breakthroughs in AI, the energy sector has booste

As climate change accelerates, human societies face growing exposure to disasters and stress, highlighting the urgent need for effective early warning systems (EWS). These systems monitor, assess, and communicate risks to support resilience and sustainable development, but challenges remain in hazard forecasting, risk communication, and decision-making. This perspective explores the transformative potential of integrated Artificial Intelligence (AI) modeling. We highlight the role of AI in devel

In recent years, artificial intelligence (AI) has deeply impacted various fields, including Earth system sciences, by improving weather forecasting, model emulation, parameter estimation, and the prediction of extreme events. The latter comes with specific challenges, such as developing accurate predictors from noisy, heterogeneous, small sample sizes and data with limited annotations. This paper reviews how AI is being used to analyze extreme climate events (like floods, droughts, wildfires, an

Background/Objectives: This systematic review integrates Cognitive Load Theory (CLT), Educational Neuroscience (EdNeuro), Artificial Intelligence (AI), and Machine Learning (ML) to examine their combined impact on optimizing learning environments. It explores how AI-driven adaptive learning systems, informed by neurophysiological insights, enhance personalized education for K-12 students and adult learners. This study emphasizes the role of Electroencephalography (EEG), Functional Near-Infrared

The detection of cosmic neutrinos with energies above a teraelectronvolt (TeV) offers a unique exploration into astrophysical phenomena1–3. Electrically neutral and interacting only by means of the weak interaction, neutrinos are not deflected by magnetic fields and are rarely absorbed by interstellar matter: their direction indicates that their cosmic origin might be from the farthest reaches of the Universe. High-energy neutrinos can be produced when ultra-relativistic cosmic-ray protons or nu

Technologies that contribute to inclusive education are digital tools and specialized devices that facilitate equitable access to learning for students with diverse abilities. Understanding these technologies allows for the personalization of teaching methods, the removal of barriers that limit participation for students with differences, and the promotion of a more accessible and equitable educational environment for all. This study aims to identify and analyze practices and technologies that f

The integration of artificial intelligence (AI) agents with the Internet of Things (IoT) has marked a transformative shift in environmental monitoring and management, enabling advanced data gathering, in-depth analysis, and more effective decision making. This comprehensive literature review explores the integration of AI and IoT technologies within environmental sciences, with a particular focus on applications related to water quality and climate data. The methodology involves a systematic sea

Ineffective medication is a major healthcare problem causing significant patient suffering and economic costs. This issue stems from the complex nature of diseases, which involve altered interactions among thousands of genes across multiple cell types and organs. Disease progression can vary between patients and over time, influenced by genetic and environmental factors. To address this challenge, digital twins have emerged as a promising approach, which have led to international initiatives aim

Modern education faces persistent challenges, including disengagement, inequitable access to learning resources, and the lack of personalized instruction, particularly in virtual environments. In this perspective, we envision a transformative Metaverse classroom model, the Multi-layered Immersive Learning Environment (Meta-MILE) to address these critical issues. The Meta-MILE framework integrates essential components such as immersive infrastructure, personalized interactions, social collaborati

Non-communicable diseases (NCDs) such as cardiovascular diseases, chronic respiratory diseases, cancers, diabetes, and mental health disorders pose a significant global health challenge, accounting for the majority of fatalities and disability-adjusted life years worldwide. These diseases arise from the complex interactions between genetic, behavioral, and environmental factors, necessitating a thorough understanding of these dynamics to identify effective diagnostic strategies and interventions

A significant advancement in artificial intelligence is the development of large language models (LLMs). Despite opposition and explicit bans by some authorities, LLMs continue to play a transformative role, particularly in education, by improving language understanding and generation capabilities. This study explores LLMs’ types, history, and training processes, alongside their application in education, including digital and higher education settings. A novel theoretical framework is proposed t

The global energy transition, driven by the imperative to mitigate climate change, demands innovative solutions to address the technical, economic, and social challenges of decarbonization. Artificial intelligence (AI) has emerged as a transformative technology in this domain, offering tools to enhance each link in the energy system. This comprehensive review examines the current state of AI applications across key energy transition domains, including renewable energy deployment, energy efficien

• AI-driven pollution detection enhances environmental protection. • Real-time monitoring facilitates prompt interventions for pollution prevention. • Accurate air quality forecasting aids in planning pollution-reducing activities. • AI's role in smart cities fosters sustainable urban development. • AI algorithms integrate diverse data sources for pollution detection. The application of Artificial Intelligence (AI) in environmental monitoring offers accurate disaster forecasts, pollution source

BACKGROUND: Integrating Artificial Intelligence (AI) in educational applications is becoming increasingly prevalent, bringing opportunities and challenges to the learning environment. While AI applications have the potential to enhance structured learning, they may also significantly impact students' creativity and academic emotions. OBJECTIVES: This study aims to explore the effects of AI-integrated educational applications on college students' creativity and academic emotions from the perspect

The rapid advancement in Artificial Intelligence (AI) and big data has developed significance in the water sector, particularly in hydrological time-series predictions. Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTM) networks have become research focal points due to their effectiveness in modeling non-linear, time-variant hydrological systems. This review explores the different architectures of RNNs, LSTMs, and Gated Recurrent Units (GRUs) and their efficacy in predicting hydr

Clinical decision-making is one of the most impactful parts of a physician's responsibilities and stands to benefit greatly from artificial intelligence solutions and large language models (LLMs) in particular. However, while LLMs have achieved excellent performance on medical licensing exams, these tests fail to assess many skills necessary for deployment in a realistic clinical decision-making environment, including gathering information, adhering to guidelines, and integrating into clinical w

Introduction: Artificial Intelligence (AI) is transforming multiple sectors within our society, including education. In this context, emotions play a fundamental role in the teaching-learning process given that they influence academic performance, motivation, information retention, and student well-being. Thus, the integration of AI in emotional assessment within educational environments offers several advantages that can transform how we understand and address the socio-emotional development of

The dynamic landscape of sustainable smart cities is witnessing a significant transformation due to the integration of emerging computational technologies and innovative models. These advancements are reshaping data-driven planning strategies, practices, and approaches, thereby facilitating the achievement of environmental sustainability goals. This transformative wave signals a fundamental shift - marked by the synergistic operation of artificial intelligence (AI), artificial intelligence of th

Abstract Background AI can positively influence teaching by offering support for classroom management, creating inclusive learning environments, enhancing digital skills, personalizing teaching methods, and strengthening teacher‐student relationships. Objectives This quantitative research study investigates the opportunities, difficulties, and consequences of incorporating AI into teacher education. Methods Data were collected through structured questionnaires from 202 college students and 68 st

The introduction of accessible generative artificial intelligence opens promising opportunities for the implementation of personalized learning methods in any educational environment. Personalized learning has been conceptualized for a long time, but it has only recently become realistic and truly achievable. In this paper, we propose an affordable and sustainable approach toward personalizing learning materials as part of the complete educational process. We have created a tool within a pre-exi

Cultural competence in education has emerged as a critical area of focus in contemporary educational discourse, aiming to create inclusive learning environments that celebrate diversity and promote equitable opportunities for all students. This review explores strategies for fostering inclusivity and diversity awareness within educational settings. The foundation of cultural competence lies in recognizing and respecting the cultural backgrounds, experiences, and identities of students, educators

Artificial intelligence (AI) may be the new-new-norm in a post-pandemic learning environment. There is a growing number of university students using AI like ChatGPT and Bard to support their academic experience. Much of the AI in higher education research to date has focused on academic integrity and matters of authorship; yet, there may be unintended consequences beyond these concerns for students. That is, there may be people who reduce their formal social interactions while using these tools.

The primary purpose of this study was to investigate and present a theoretical model that identifies the most influential factors affecting the adoption of artificial intelligence (AI) by SMEs to achieve sustainable business performance in Saudi Arabia by integrating the Technology–Organization–Environment (TOE) framework. The authors utilized a quantitative method, using a survey instrument for this research. Data for this research were collected from managers working in six different sectors.

In recent times, there has been a significant shift from centralized energy systems to decentralized ones. These systems aim to satisfy local energy needs using renewable resources within the community. This approach leads to decreased complexity and costs, improved efficiency, and enhanced local resilience and supports energy independence, thereby advancing the transition toward zero carbon emissions. Community energy plays a pivotal role globally, particularly in European countries, driven by

Detecting hazardous substances in the environment is crucial for protecting human wellbeing and ecosystems. As technology continues to advance, artificial intelligence (AI) has emerged as a promising tool for creating sensors that can effectively detect and analyze these hazardous substances. The increasing advancements in information technology have led to a growing interest in utilizing this technology for environmental pollution detection. AI-driven sensor systems, AI and Internet of Things (

Climate change is one of the most significant challenges worldwide. There is strong evidence from research that climate change will impact several food chain-related elements such as agricultural output, incomes, prices, food access, food quality, and food safety. This scoping review seeks to outline the state of knowledge of the food supply chain's vulnerability to climate change and to identify existing literature that may guide future research, policy, and decision-making aimed at enhancing t

Abstract Global environmental pollution presents formidable obstacles to the long-term viability of the planet. This study synthesized current relevant literature with statistical snapshots from pollution statistics and reports and presented feasible recommendations to address the ramifications of global environmental pollution. A central focus is laid on the importance of preventive environmental management (PEM) and the strategic enforcement of environmental policies (EP), with a detailed expl

Over the past decade, there has been a notable surge in AI-driven research, specifically geared toward enhancing crucial clinical processes and outcomes. The potential of AI-powered decision support systems to streamline clinical workflows, assist in diagnostics, and enable personalized treatment is increasingly evident. Nevertheless, the introduction of these cutting-edge solutions poses substantial challenges in clinical and care environments, necessitating a thorough exploration of ethical, l

Predictive maintenance (PdM) is a policy applying data and analytics to predict when one of the components in a real system has been destroyed, and some anomalies appear so that maintenance can be performed before a breakdown takes place. Using cutting-edge technologies like data analytics and artificial intelligence (AI) enhances the performance and accuracy of predictive maintenance systems and increases their autonomy and adaptability in complex and dynamic working environments. This paper re

The emergence of generative artificial intelligence (GenAI) requires innovative educational environments to leverage this technology effectively to address concerns like academic integrity, plagiarism, and others. Additionally, higher education needs effective pedagogies to achieve intended learning outcomes. This emphasizes the need to redesign active learning experiences in the GenAI era. Authentic assessment and experiential learning are two possible meaningful alternatives in this context. A

The ascent of environmental, social, and governance (ESG) reporting has established itself as a global standard in financial markets, reflecting a paradigm shift toward corporate sustainability. Despite this, persistent concerns surround the quality of ESG reporting and its tangible impact on Sustainable Development (SD). To address the imperative transition toward a broader SD agenda within the ESG reporting framework, this study delves into contemporary issues and challenges associated with ES

Abstract Recent advances in generative pre-trained transformer large language models have emphasised the potential risks of unfair use of artificial intelligence (AI) generated content in an academic environment and intensified efforts in searching for solutions to detect such content. The paper examines the general functionality of detection tools for AI-generated text and evaluates them based on accuracy and error type analysis. Specifically, the study seeks to answer research questions about

Climate change and other environmental threats require urgent government action. This policy paper discusses how governments can use better regulation instruments (good regulatory practices, risk-based and agile approaches, regulatory delivery, international regulatory cooperation, economic regulators, and behavioural insights) to design, implement and evaluate efficient and effective regulations for the environment. It explores the challenges governments face and presents good practices for env