Search Results (1,233)

The evolution of decentralized clinical trials, driven by advanced digital technologies, is transforming traditional clinical research. It introduces innovative methods for informed consent, remote patient monitoring, and data analysis, enhancing study efficiency, validity, and participation while reducing patient burden. Some clinical procedures can be conducted remotely, increasing trial accessibility and reducing population selection biases, particularly for cardiovascular patients. However, this also presents complex regulatory and ethical challenges. The article explores how digital platforms and emerging technologies like block chain, AI, and advanced cryptography can promote traceability, security, and transparency throughout the trial process, ensuring participant identification and documentation of each procedural step. Clear, legally compliant informed consent, often managed through electronic systems, both for research participation and data management in line with GDPR, is essential. Ethical considerations include ensuring participants understand trial information, with adaptations such as simplified language, visual aids, and multilingual support. The transnational nature of decentralized trials highlights the need for coordinated regulatory standards to overcome jurisdictional barriers and reinforce accountability. This framework promotes trust, shared responsibility, and the protection of participants rights while upholding high ethical standards in scientific research. Full article

This study investigates hotel employees’ perceptions of AI-driven human resource (HR) management systems within the Accor Group’s properties across three major European cities: Paris, Berlin, and Amsterdam. These diverse urban contexts, spanning a broad portfolio of hotel brands from luxury to economy, provide a rich setting for exploring how AI integration affects employee attitudes and work–life balance. A total of 437 employees participated in the survey, offering a robust dataset for structural equation modeling (SEM) analysis. Exploratory factor analysis identified two primary factors shaping perceptions: AI Perceptions, which encompasses employee views on AI’s impact on job performance, communication, recognition, and retention, and balanced management, reflecting attitudes toward fairness, personal consideration, productivity, and skill development in AI-managed environments. The results reveal a complex but optimistic view, where employees acknowledge AI’s potential to enhance operational efficiency and career optimism but also express concerns about flexibility loss and the need for human oversight. The findings underscore the importance of transparent communication, contextual sensitivity, and continuous training in implementing AI systems that support both organizational goals and employee well-being. This study contributes valuable insights to hospitality management by highlighting the relational and ethical dimensions of algorithmic HR systems across varied organizational and cultural settings. Full article

In this article, we explain how Kant upends the terms of the debate concerning the relationship between God’s existence and an objective morality by looking at his moral-teleological argument for God’s existence in the third Critique. We explain Kant’s rejection of external sources of moral normativity and his method of grounding moral authority in the normativity of practical reason. We then turn to Kant’s argument justifying a practical belief in God as the moral author of nature. Kant’s claims about how we must conceptualize organisms teleologically and, as a result, how reason seeks an unconditioned end of nature, brings together our moral purpose with a conception of nature as an organized whole. Since our teleological concepts of organisms seem to require that human beings serve as the final, unconditioned end of nature, but morality and nature might be incompatible and divergent, we must also believe in a moral author of nature. This belief guards against demoralization and creates a unified view of the human moral agent and the world she inhabits, which Kant thinks of as indispensable for our practical lives. Kant notoriously blurs the lines between theology and ethics in nonstandard ways. Although he rejects many traditional approaches to grounding ethics in a conception of divine commands or eternal law, he still devotes a considerable amount of time to discussing the role of religion as a bulwark of the moral life. The goal of this paper is to defend Kant’s relevance to a discussion of the relationship between an objective ethics and the existence of God; his contribution deserves our notice precisely for the ways in which it promises to shift the terms of the contemporary debate and complicate possible answers to the question of whether there can be an objective morality without God. In contemporary philosophical literature, Kant’s argument contending that we must hope in God from a practical point of view on pain of irrationality of acting from duty has enjoyed substantial discussion. Here, however, we focus on a lesser-known suite of arguments that in order to so much as cognize ourselves and other species as the sorts of natural beings they are, we must believe in a supersensible moral author of these natures. This set of arguments ultimately dovetail with the more well-known argument for theistic hope and operate in much the same way. But they touch on facets of Kant’s whole philosophical system, such as his account of teleological judgment and the unity and final end of all of nature. Our goal is to explicate these arguments and illuminate their relevance of these Kantian arguments to the debate about the relevance of God to objective morality. We will argue that while an objective ethics is possible without God due to the active role of practical reason in rational agents, belief in God’s existence strengthens the claims of morality, both for psychological reasons but also by providing a more unified conception of moral and natural reality. Full article

Modern military operations place significant physiological and cognitive demands on soldiers, necessitating innovative strategies to monitor and optimize health and performance. This narrative review examines the role of continuous physiological state monitoring and precision health strategies to enhance soldier resilience and operational readiness. Advanced wearable biosensors were analyzed for their ability to measure vital physiological parameters—such as heart-rate variability, core temperature, hydration status, and biochemical markers—in real-time operational scenarios. Emerging technological solutions, including AI-driven analytics and edge computing, facilitate rapid data interpretation and predictive health assessments. Results indicate that real-time physiological feedback significantly enhances early detection and prevention of conditions like exertional heat illness and musculoskeletal injuries, reducing medical attrition and improving combat effectiveness. However, ethical challenges related to data privacy, informed consent, and secure data management highlight the necessity for robust governance frameworks and stringent security protocols. Personalized training regimens and rehabilitation programs informed by monitoring data demonstrate potential for substantial performance optimization and sustained force readiness. In conclusion, integrating precision health strategies into military operations offers clear advantages in soldier health and operational effectiveness, contingent upon careful management of ethical considerations and data security. Full article

The purpose of this study is to examine the impact of integrity-related considerations, such as ethics, privacy, protection, security, and trust, on online consumer shopping intention within the interactive marketing environment. To achieve this, the research uses partial least squares structural equation modelling (PLS-SEM), analysing data from a sample of 260 respondents collected through an online survey. The findings reveal that protection is the most influential factor driving consumer buying intentions, followed by trust, ethics and security. Privacy, while significant, has a more moderate influence on consumer behaviour compared to other factors. The study makes a key theoretical contribution by advancing the understanding of how these constructs interact to shape consumer behaviour in the digital marketplace, particularly highlighting the importance of data protection and ethical practices. Practically, the research offers actionable recommendations for e-commerce businesses, based on building a digital integrity model, suggesting the focus on enhancing data security and ethical transparency to build consumer trust. Furthermore, the findings highlight the need for policymakers to strengthen data privacy regulations and harmonise international security standards in e-commerce. Future research should consider longitudinal studies and explore these dynamics in different regulatory environments. Full article

As climate action becomes increasingly urgent, nations and institutions worldwide seek advanced technologies for practical mitigation efforts. This study examines how agentic artificial intelligence systems capable of decision-making and learning from experience drive innovation dynamics in climate change mitigation, with a particular focus on ethical considerations during the net-zero transition. The current urgency of climate action demands advanced technologies, yet organisations struggle to effectively deploy agentic AI for climate mitigation due to unclear implementation pathways and ethical consideration. This study examines the relationships among agentic AI capabilities, innovation dynamics, and net-zero transition performance, using survey data from 340 organisations across the manufacturing, energy, and technology sectors, and analysed using structural equation modelling. Based on dynamic capabilities theory, this research proposes a novel theoretical model that examines how agentic AI drives innovation dynamics in climate change mitigation within governance frameworks that encompass transparency, accountability, and environmental justice. Results reveal significant mediation effects of innovation dynamics, dynamic capabilities, and ethical considerations, while environmental context negatively moderates innovation and ethical pathways. Findings suggest that overly restrictive ethical considerations can lead to implementation delays that undermine the urgency of climate action. This study proposes three solutions: (1) adaptive ethical protocols adjusting governance intensity based on climate risk severity, (2) pre-approved ethical templates reducing approval delays by 60%, and (3) stakeholder co-design processes building consensus during development. The research advances dynamic capabilities theory for AI contexts by demonstrating how AI-enabled sensing, seizing, and reconfiguring capabilities create differentiated pathways to climate performance. This study provides empirical validation of the responsible innovation framework, identifies asymmetric environmental contingencies, and offers evidence-based guidance for organisations implementing agentic AI for climate action. Full article

Background: Infertility remains a significant global health challenge, affecting approximately 15% of couples worldwide. In vitro fertilization (IVF) has transformed reproductive medicine; however, challenges such as low success rates in older patients, ovarian insufficiency, endometrial dysfunction, and male infertility continue to limit outcomes. Objective: This review aims to summarize the principles of IVF and explore the potential role of stem cells in enhancing IVF outcomes, with particular attention to applications in both women and men, as well as the accompanying ethical considerations. Summary: Stem cell research has introduced novel therapeutic opportunities, including ovarian rejuvenation, endometrial regeneration, sperm quality enhancement, and the development of synthetic embryo models. Mesenchymal stem cells (MSCs), embryonic stem cells (ESCs), and induced pluripotent stem cells (iPSCs) demonstrate regenerative properties that may help to overcome current reproductive limitations. Despite encouraging findings from preclinical and early clinical studies, challenges such as tumorigenesis, genetic instability, and ethical controversies remain major barriers to translation. Conclusions: IVF continues to serve as a cornerstone of assisted reproductive technology (ART). Stem cell-based approaches represent an exciting frontier that could expand the therapeutic possibilities of IVF. Careful clinical validation, international regulatory harmonization, and robust ethical oversight will be essential to ensuring safe and equitable implementation. Full article

Background/Objectives: Mechanical circulatory support (MCS) is increasingly utilized for the management of acute decompensated heart failure (HF) and cardiogenic shock (CS). The primary goals of MCS are to restore systemic perfusion, reduce cardiac workload, and support end-organ function. A thorough understanding of cardiovascular physiology in patients supported by MCS is essential for clinical decision-making. This review summarizes current evidence on the physiological effects of various MCS devices, key monitoring techniques, patient management, and explores the emerging role of artificial intelligence (AI) in this field. Main Text: Short-term MCS devices include intra-aortic balloon pumps (IABP), percutaneous left-sided devices such as Impella (Abiomed, Danvers, MA, USA) and TandemHeart (LivaNova, London, UK), percutaneous right-sided support devices like Protek Duo (LivaNova, London, UK) and Impella RP Flex (Abiomed, Danvers, MA, USA), and veno-arterial extracorporeal membrane oxygenation (VA-ECMO). Long-term support is mainly provided by left ventricular assist devices (LVADs), including the HeartMate 3 (Abbott Laboratories, Chicago, IL, USA). Optimal MCS application requires an understanding of device-specific cardiovascular interactions and expertise in appropriate monitoring tools to assess device performance and patient response. The choice of device, timing of initiation, and patient selection must be individualized, with careful consideration of ethical implications. The integration of AI offers significant potential to advance clinical care by improving complication prediction, enabling real-time optimization of device settings, and refining patient selection criteria. Conclusions: MCS is a rapidly evolving field that requires a comprehensive understanding of cardiovascular interactions, careful selection of monitoring strategies, and individualized clinical management. Future research should address current device limitations, clarify device-specific clinical applications, and assess the validity of AI-driven technologies. Full article

Background/Objectives: Surgical ward rounds are central to trainee education but are often associated with stress, cognitive overload, and inconsistent learning. Advances in artificial intelligence (AI), particularly large language models (LLMs), offer new ways to support trainees by simulating ward-round questioning, enhancing preparedness, and reducing anxiety. This study explores the role of generative AI in surgical ward-round education. Methods: Hypothetical plastic and reconstructive surgery ward-round scenarios were developed, including flexor tenosynovitis, DIEP flap monitoring, acute burns, and abscess management. Using de-identified vignettes, AI platforms (ChatGPT-4.5 and Gemini 2.0) generated consultant-level questions and structured responses. Outputs were assessed qualitatively for relevance, educational value, and alignment with surgical competencies. Results: ChatGPT-4.5 showed a strong ability to anticipate consultant-style questions and deliver concise, accurate answers across multiple surgical domains. ChatGPT-4.5 consistently outperformed Gemini 2.0 across all domains, with higher expert Likert ratings for accuracy, clarity, and educational value. It was particularly effective in pre-ward round preparation, enabling simulated questioning that mirrored consultant expectations. AI also aided post-round consolidation by providing tailored summaries and revision materials. Limitations included occasional inaccuracies, risk of over-reliance, and privacy considerations. Conclusions: Generative AI, particularly ChatGPT-4.5, shows promise as a supplementary tool in surgical ward-round education. While both models demonstrated utility, ChatGPT-4.5 was superior in replicating consultant-level questioning and providing structured responses. Pilot programs with ethical oversight are needed to evaluate their impact on trainee confidence, performance, and outcomes. Although plastic surgery cases were used for proof of concept, the findings are relevant to surgical education across subspecialties. Full article

This article proposes a scientifically grounded approach to risk assessment for infrastructural and functional systems that underpin the development of digitally transformed regional territories under conditions of high threat dynamics and sociotechnical instability. The core methodology is based on modeling of multifactorial threats through the application of fuzzy set theory and logic–linguistic analysis, enabling consideration of parameter uncertainty, fragmented expert input, and the lack of a unified risk landscape within complex infrastructure environments. A special emphasis is placed on components of technogenic, informational, and mobile infrastructure that ensure regional viability across planning, response, and recovery phases. The results confirm the relevance of the approach for assessing infrastructure resilience risks in regional spatial–functional systems, which demonstrates the potential integration into sustainable development strategies at the level of regional governance, cross-sectoral planning, and cultural reevaluation of the role of analytics as an ethically grounded practice for cultivating trust, transparency, and professional maturity. Full article

Antimicrobial resistance is a global threat to public health. The growing resistance of bacteria to commonly used antibiotics necessitates the search for and development of alternative treatments. Bacteriophage (or phage) therapy fits this trend perfectly. Phages that selectively infect and kill bacteria might represent, in some cases, the last therapeutic option. This overview provides case examples and discusses the potential development of phage therapy, examining its ethical and legal considerations in the context of current clinical practices. Additionally, it explores the advantages of utilizing phage products in patients for whom existing therapeutic options are limited or unavailable. Further clinical studies are necessary to broaden the understanding of phages, their dosage, and a standardised delivery system. These efforts are essential to ensure that phage-based therapy is not viewed as experimentation but as a routine medical treatment. Bacterial viruses are unlikely to become a miracle cure or a panacea for infections, but they may find an important role in medicine. Full legalisation of this treatment could help solve the problem of multidrug-resistant infectious diseases on a global scale. Full article

Background: Lung cancer remains the leading cause of cancer-related mortality globally, largely due to delayed diagnosis in its early stages. While conventional diagnostic tools like low-dose CT and tissue biopsy are routinely used, they suffer from limitations including invasiveness, radiation exposure, cost, and limited sensitivity for early-stage detection. Liquid biopsy, a minimally invasive alternative that captures circulating tumor-derived biomarkers such as ctDNA, cfRNA, and exosomes from body fluids, offers promising diagnostic potential—yet its sensitivity in early disease remains suboptimal. Recent advances in Artificial Intelligence (AI) and radiomics are poised to bridge this gap. Objective: This review aims to explore how AI, in combination with radiomics, enhances the diagnostic capabilities of liquid biopsy for early detection of lung cancer and facilitates personalized monitoring strategies. Content Overview: We begin by outlining the molecular heterogeneity of lung cancer, emphasizing the need for earlier, more accurate detection strategies. The discussion then transitions into liquid biopsy and its key analytes, followed by an in-depth overview of AI techniques—including machine learning (e.g., SVMs, Random Forest) and deep learning models (e.g., CNNs, RNNs, GANs)—that enable robust pattern recognition across multi-omics datasets. The role of radiomics, which quantitatively extracts spatial and morphological features from imaging modalities such as CT and PET, is explored in conjunction with AI to provide an integrative, multimodal approach. This convergence supports the broader vision of precision medicine by integrating omics data, imaging, and electronic health records. Discussion: The synergy between AI, liquid biopsy, and radiomics signifies a shift from traditional diagnostics toward dynamic, patient-specific decision-making. Radiomics contributes spatial information, while AI improves pattern detection and predictive modeling. Despite these advancements, challenges remain—including data standardization, limited annotated datasets, the interpretability of deep learning models, and ethical considerations. A push toward rigorous validation and multimodal AI frameworks is necessary to facilitate clinical adoption. Conclusion: The integration of AI with liquid biopsy and radiomics holds transformative potential for early lung cancer detection. This non-invasive, scalable, and individualized diagnostic paradigm could significantly reduce lung cancer mortality through timely and targeted interventions. As technology and regulatory pathways mature, collaborative research is crucial to standardize methodologies and translate this innovation into routine clinical practice. Full article

This study examines intergenerational transmission of Russian within the U.S. Russophone diaspora in the wake of Russia’s 2022 full-scale invasion of Ukraine. It addresses: (1) parents’ motivations and practices surrounding intergenerational language transmission; and (2) challenges faced by Russian-speaking families in today’s shifting sociopolitical landscape. The study draws on semi-structured Zoom interviews with 16 Russian-speaking parents in the United States, each raising children aged 3–15 and representing four different immigration periods, from the early 1990s to 2022, following Russia’s invasion of Ukraine. Findings reveal that heritage language maintenance is shaped not only by linguistic choices, but also by political and ethical considerations. While all parents continue to view Russian as a source of identity, cultural capital, and familial cohesion, many also actively disassociate the language from its sociopolitical ties to the aggressor state. Shared aspirations for bilingualism are tempered by internal and external pressures, including children’s growing agency, family dynamics, challenges of immigrant life, and war-driven fractures within the diaspora. This study contributes to research on heritage language maintenance and family language policies by exploring how global geopolitical events are negotiated through intimate, everyday language practices in immigrant households. Full article

Contemporary discussions of AI are often framed according to generally held assumptions which have largely escaped serious critical analysis. For instance, those who promote AI tout its predictive prowess: powerful algorithms fed massive amounts of data are able to discover knowable patterns that can accurately forecast the behaviors in anything from individual movie preferences to financial markets. Armed with this type of knowledge we can then use AI, the hope goes, to be more objective in our ethical practices. And most seriously, we must extend this to the way we develop AI, not only do we want AI to function ethically, but we caution ourselves that if Artificial General Intelligence (AGI), superintelligence, or anything like the “singularity” is ever developed, it should be positively aligned with human values. Reflecting on these positions from the perspective of classical Daoism gives us reason to pause. While Daoist texts also assume there are patterns in the world which one can successfully go along with, they are not enthusiastic about the rational or knowable nature of these patterns—rather, they encourage us to appreciate them as fundamentally complex and mysterious. In this article, some Daoist attitudes are also concretely applied to ethical considerations, which cannot easily be controlled or known, much less put into code. Inspired by Daoist texts, we might cultivate an attitude less filled with hubris than humility, where we are allowed more space from which we can reflect on how we think about AI. Many of the most pressing issues associated with AI could, in fact, be significantly alleviated simply by shifting the way we think about, use, and develop these technologies. Full article

The integration of artificial intelligence (AI) and machine learning (ML) has revolutionised civil engineering, enhancing predictive accuracy, decision-making, and sustainability across domains such as structural health monitoring, geotechnical analysis, transportation systems, water management, and sustainable construction. This paper presents a detailed review of peer-reviewed publications from the past decade, employing bibliometric mapping and critical evaluation to analyse methodological advances, practical applications, and limitations. A novel taxonomy is introduced, classifying AI/ML approaches by civil engineering domain, learning paradigm, and adoption maturity to guide future development. Key applications include pavement condition assessment, slope stability prediction, traffic flow forecasting, smart water management, and flood forecasting, leveraging techniques such as Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM), Support Vector Machines (SVMs), and hybrid physics-informed neural networks (PINNs). The review highlights challenges, including limited high-quality datasets, absence of AI provisions in design codes, integration barriers with IoT-based infrastructure, and computational complexity. While explainable AI tools like SHAP and LIME improve interpretability, their practical feasibility in safety-critical contexts remains constrained. Ethical considerations, including bias in training datasets and regulatory compliance, are also addressed. Promising directions include federated learning for data privacy, transfer learning for data-scarce regions, digital twins, and adherence to FAIR data principles. This study underscores AI as a complementary tool, not a replacement, for traditional methods, fostering a data-driven, resilient, and sustainable built environment through interdisciplinary collaboration and transparent, explainable systems. Full article