ABSTRACT Large Language Models (LLMs) are increasingly used in social work practice, yet their ethical implications remain underexplored. This study addresses the gap by systematically reviewing literature on LLM-based tools in social service delivery. The review aims to identify the benefits, risks, and mitigation measures related to LLM use. Following PRISMA guidelines and employing a PICOC framework, we reviewed 34 studies published between 2019 and 2024 across multiple databases, including Web of Science, EBSCO, and Scopus. The results show that LLMs enhance efficiency in management, streamline frontline tasks, and support client needs. However, issues such as bias, lack of contextualization and explainability, and over-reliance pose ethical risks for both clients and professionals. We argue that Actor-Network Theory (ANT) helps reframe AI responsibility as distributed across human and non-human actors. It offers analytical tools to trace non-human agency and address ethical risks, highlighting the need for technical, organizational, and regulatory improvements.

Humans act together to achieve feats they could never achieve alone and communicate to ensure alignment of meaning and understanding across different individuals. Explaining the unique human joint action and communication abilities poses an enormous challenge because it requires a systematic account of how people go beyond their own individual perceptions, thoughts, and needs to achieve joint outcomes and align their understanding. Here, we advance a new theoretical framework for explaining joint action and communication. It builds upon influential predictive processing architectures, extending them from individual cognition to multiagent, interactive settings. We assume that joint action and communication involve using and updating agent-neutral models that enable co-agents to predict collective outcomes of interactions regardless of who achieved them. This contrasts with previous frameworks postulating that agent-specific models predict action outcomes for self and others. We discuss three key claims derived from our framework: 1) Co-agents use agent-neutral predictive frameworks during joint action; 2) Co-agents update agent-neutral models interactively by shaping others' predictions through verbal and non-verbal communication; and 3) Agent-neutral models enable dynamic role allocation during joint action. We highlight how these three claims stem from our proposal, what evidence currently favors or disfavors them, and what novel experiments could be conducted to test them further. Our agent-neutral predictive processing framework will provide a new perspective for understanding the individual basis of human sociality, which closely links theories of joint action and communication to principles of computational neuroscience.

The Bereitschaftspotential in Voluntary Movement and Movement Disorders: Potential, Limitations and New Perspectives.

Automatic imitation towards robots is not influenced by the intentional stance.

The problem of Human Action Recognition (HAR) continues to be difficult with the intricate temporal interactions, superfluous frames, and minor visual variations that usually define similar actions. A large number of current approaches are based on either transformer or multimodal architectures, which are computationally costly and cannot be used in real-time or resource constrained systems. To overcome these shortcomings, we proposed a novel and lightweight HAR model that integrates spatial, temporal and consistency modeling in an efficient architecture. In our model, we combine EfficientNet-B2, used in efficient spatial feature extraction, with Unitary Temporal Encoder (UTE), to train long-range temporal dependencies, and Adaptive Temporal Consistency Module (ATCM), to improve local temporal consistency. The proposed system is trained and tested on the datasets UCF101 and HMDB51 with a Top-1 accuracy of 97.10% and 87% under RGB input only which is competitive among RGB-based HAR methods while maintaining low computational cost. The 9.3 million parameter model with an inference rate of 9.5 ms per 16-frame video clip is highly accurate and efficient, thus suitable in inference in real-time and at edges. Ablation studies further demonstrate that the proposed components contribute consistent performance improvements across the evaluated benchmarks.

ABSTRACT This study examines how artificial intelligence (AI) reshapes epistemic authority in contemporary journalism. Drawing on 75 in-depth interviews with journalists, editors, media owners, and AI developers in the United States, it argues that AI does not simply automate journalistic tasks or redistribute professional roles. Instead, AI produces a condition of epistemic dislocation, in which the production, validation, and control of knowledge become fragmented and misaligned across human actors, technological systems, and organizational structures. The analysis identifies three interrelated dynamics: (1) the externalization of epistemic authority despite centralized organizational decision-making, (2) the coexistence of increasing epistemic delegation to AI and the performative reassertion of professional journalistic authority, and (3) the decoupling of knowledge production from accountability through fragmented governance structures. The present study advances a new conceptual framework for understanding AI journalism and offers implications for professional authority, ethical governance, and accountability in increasingly AI-mediated news production.

Stimulus-response and action-effect links are discussed in several paradigms in different fields of psychology and treated as separate conceptual entities. We criticize this separation. Ideomotor approaches like the Theory of Event Coding (Hommel et al., 2001) provide measures to unite and harmonize these research fields. In particular, the concept of event files, internal representations, that code stimulus, response, and effect features can connect still separate fields on human action in cognitive psychology. This is even more obvious, as the original ideomotor theory never separated perception and action the way it is done in contemporary research. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

This study examines long-term occupational accident patterns in a chemical plant using approximately fifty years of internal incident records. These records were originally compiled for day-to-day safety management rather than for research purposes. They offer a rare retrospective view of how human-factor-related accidents and everyday safety practices actually evolved during long-term operation. Long-term trends in accident counts, frequency rates, and severity rates show a decline. However, closer examination indicates that as technical and equipment-related risks were reduced, incidents involving human judgment and action became relatively more prominent. In this sense, risk changed its form within the work environment. To explore this shift, incidents were examined using a cross-classification of "type of incident × unsafe behavior," together with a distinction between routine and non-routine operations. The analysis indicates that non-routine activities-such as maintenance and troubleshooting-remain particularly vulnerable to human-factor-related issues. When viewed through the lens of Hudson's safety culture maturity model, these patterns suggest a gradual transition from reactive to proactive practices. Rather than proposing a model of safety culture, this case study illustrates how long-term incident records reflect the practical, trial-and-error process of managing human factors and work. The findings offer insights for loss prevention and human-factor management.

Model-based and model-free valuation signals in the human brain vary markedly in relation to individual differences in behavioral control.

ABSTRACT This article argues that Nnedi Okorafor’s Lagoon (2014) presents Lagos as a more-than-human urban space in which ecological, communicative, and social-material systems actively shape urban life and futurity. It develops the concept of infrastructural posthumanism to show that agency in the novel is distributed across human and nonhuman actors rather than located in autonomous human subjects. Framing on Brian Larkin’s account of infrastructure, N. Katherine Hayles’s model of distributed cognition, and Okorafor’s Africanfuturist framework, the article defines infrastructure as a material and relational system that organizes circulation, communication, and transformation. The analysis proceeds through three domains. Eco-infrastructure examines the lagoon waters and marine life as sites of petro-violence, multispecies response, and ecological change. Discursive infrastructure analyzes media and communication systems as forces that produce collective yet unstable publics. Social-material infrastructure studies roads, enclosures, and urban routes to show how mobility, inequality, and improvisation are structured by built form. The article concludes that Lagoon grounds posthuman thought in African urban conditions and locates futurity within Lagos’s own infrastructures.

The ethical terrain surrounding feeding at the end-of-life is emotionally charged and complex. In the literature, the recently introduced notion of "minimal comfort feeding" (MCF), defined as deliberate limitation of feeding or hydration, given only in response to visible signs of hunger or thirst, for a patient with a longer prognosis, has been proposed as a comfort measure at the end of life and as an alternative to voluntarily stopping eating and drinking (VSED) in advance care planning. However, the same term may be applied to two morally distinct acts: 1) providing comfort in the context of active dying, and 2) a hastening death. In this paper, we argue for conceptual clarity around these two practices and their ethical valence, drawing on an Anscombean-Thomistic virtue ethics framework that deals with moral evaluation of human action and the doctrine of double effect. We present two clinical cases highlighting each of these ethical scenarios. Through the cases, we show how intentionality and some circumstances such as timing critically shape the morality of the act. We propose a new nomenclature with the aim of fostering ethical clarity of the morally distinct acts: "proportionate comfort feeding" (PCF) for MCF where nutrition and hydration is provided for comfort with the understanding that it may hasten death but is its foreseen, unintended outcome, and "minimal feeding to hasten death" (MFHD) for cases where MCF is chosen with the specific intention to hasten death.

ABSTRACT In this article, we explore the ways in which urban dwellers understand and relate to ‘the environment’. Conceptualisations of ‘the environment’ deserve attention due to its elusive character, and due to the unbalanced relationship between humans and non-humans where understandings of ‘the environment’ shape human actions in relation to the non-human. The study takes a Constructivist Grounded Theory approach and is based on 35 semi-structured interviews conducted with people living in and around Gothenburg, Sweden. We conceptualise ways of understanding and relating to ‘the environment’ as environmental relationalities spanning from divisions and disconnections to connections and interdependencies, stances that exist alongside ambivalences and contradictions. Rather than approaching these as fixed categories, we suggest that environmental relationalities are best understood as a dynamic continuum where understandings and relations are constantly in the process of coming into being. Despite dualistic understandings of human/environment being prevalent in our findings, these exist alongside more interdependent understandings of humans as part of ‘the environment’. We reflect on how referring to something as ‘the environment’ is problematic as it tends to reproduce human/environment divisions and contend that environmental relationalities have the potential to move towards less divisive perspectives due to their dynamic character.

Human Action Recognition (HAR) has become a field of great importance and interest for solving problems and accomplishing tasks across diverse areas. While the literature is vast, researchers face significant challenges in selecting optimal architectures, models and datasets that balance high accuracy with computational efficiency. To address this, the present systematic comprehensive review, conducted using the SALSA methodology, analyzes 81 articles and explores the best performing HAR methods. The review identified key benchmarks, notably NTU-RGB+D60 (15.15%) and UCF101 (12.12%). Most reviewed studies indicate that the most suitable models for these tasks are Convolutional Neural Networks (CNNs), which have demonstrated outstanding performance in analyzing graphical material, followed by Three-Dimensional Convolutional Neural Networks (3D CNNs) with temporal modeling (e.g., LSTMs) consistently yielding superior performance. Notably, advanced hybrid and skeleton-based models achieved peak accuracy rates of 98.3% and 98.7% on complex benchmarks, significantly outperforming traditional approaches.

Human action recognition (HAR) in the workshop-style environment poses unique challenges due to class imbalance, fused action boundaries, and context dependence. This study proposes a multi-stage fine-tuning supervised framework for workshop-style HAR based on a 3D CNN, supplemented by an unsupervised post-assessment. A total of 208 clips (100 frames per clip) from two internal and two external datasets were used, along with 183 clips generated from 152 videos in a subset of the public UCF101 dataset for an add-on supplementary analysis. An I3D-ResNet50 (I3D_R50) backbone was used to examine a pilot model for domain adaptation and subsequently optimized for cross-context generalization. In Study 1, the I3D_R50 model with a customized 57-class prediction head was trained on the internal dataset, achieving a solid class- and cluster-level performance, however, spurious co-activations and limited separation among similar actions were observed. Study 2 refined sample allocation and data augmentation, and applied threshold tuning to evaluate within-context adaptation (Test 1) and cross-context generalization (Test 2). Multi-level analyses (class-, clip-, cluster-, and person-level) revealed moderate co-activation and semantic fusion within context, whereas cross-context generalization suffered from structure over-merging and semantic drift. As a post-assessment, Study 3 provided supplementary evidence that the model captured certain semantic co-occurrence relationships, although its performance remained constrained by limited IGE-TREE specific training samples and fine-grained behavioral categories. Limitations include insufficient samples, blurred temporal sequence, and context dependency. Future work could explore domain-adversarial alignment, pose-guided normalization, and temporal contrastive modeling, and selective merging of semantically similar actions to enhance semantic disentanglement and generalization.

How is “truth” sustained amid algorithmic and political constraints? This study explores the process by which “truth” is negotiated and stabilized in China’s online journalism. Drawing on Actor-Network Theory (ANT) and controversy mapping, we translate three cases to illustrate how online controversies evolve from public affect to institutional closure. The findings reveal that in Chinese digital journalism, diverse human and nonhuman actors jointly participate in the construction of truth. Digital platforms such as Weibo function as obligatory passage points that mediate between public participation and state regulation. While user content amplifies emotion and scrutiny, algorithmic visibility and bureaucratic inscription serve to stabilize discourse. These interactions demonstrate that truth is not discovered but co-produced across technological, institutional, and affective domains. Consequently, Chinese online journalism can be conceptualized as a techno-cultural assemblage in which human agency, platform logic, and governmental governance are continuously negotiated in the production of news and facts.

Simulation-based education has evolved into a foundational component of nuclear medicine technologist training, driven by increasing procedural complexity, radiation safety imperatives, and growing pressure on clinical placement capacity. Nuclear medicine students must rapidly integrate cognitive, psychomotor, and interpersonal skills while working with radioactive materials and vulnerable patients in a complex regulatory environment. A diverse suite of modalities ranging from human actors through laboratory-based skills to virtual reality supports functional task alignment across the learning continuum. Evidence consistently demonstrates that simulation improves students' procedural accuracy, radiation-safety behaviors, clinical reasoning, emergency responsiveness, communication skills, and self-confidence while reducing placement-related anxiety and error risk. When conceptualized as an integrated ecosystem, simulation enhances learner outcomes, supports workforce resilience, and strengthens the transition to independent practice.

ABSTRACT Discontinuous stratigraphy is often treated as an excavation and dating problem, especially in long-occupied coastal settlements where construction fills, refuse deposits, water-laid sediments, and reworked surfaces repeatedly overlap. This article argues that such deposits can instead reveal human action when read as outcomes of linked formation processes. Focusing on the Daxie site on China’s eastern coast, this article develops a systemic approach that connects layer description with construction, maintenance, dumping, infilling, sealing, and reuse. Two case studies are examined: the construction, expansion, and integration of Qianshanyang-period salt-production platforms, dated to ca. 4400–4100 b.p., and a Song–Yuan waste disposal sequence in which an inherited depression was transformed through retaining walls, repeated dumping, post-depositional sorting and silting, and final leveling. Together, these sequences show complex stratigraphy as a material record of labor, spatial regulation, production, settlement management, coastal exchange, and long-term land use change.

Simulation-based education has emerged as a strategic response to placement scarcity, workforce strain, and the increasing complexity of nuclear medicine practice. The theoretic principles and simulation architecture are transformed into practical implementation strategies across the nuclear medicine technologist training continuum. Simulation is positioned as a calibrated scaffold that reduces cognitive load, enhances safety, and strengthens readiness for authentic clinical engagement. A broad spectrum of simulation modalities are explored, including task trainers, human actor simulation, laboratory rehearsal, computer-based console simulators, immersive virtual and augmented realities, metaverse environments, synthetic data generation, artificial intelligence-enhanced adaptive simulation, and in situ departmental integration. Enrichment tools are presented as amplifiers that enhance feedback, fidelity, and personalization. Through applied case examples and reflective practice insights, simulation is conceptualized as a staged developmental framework aligned with regulatory expectations and workforce realities. The proposed SCAFFOLD (Simulation as a Calibrated Framework for Optimizing Learning and Development) framework offers a pragmatic blueprint for enhancing work-integrated learning readiness while preserving the irreplaceable value of authentic clinical experience.

This contribution conceives the interaction between humans and artifacts as a relational threshold in which body, interfaces, and contexts co-produce themselves through affective dynamics. Through a genealogy of listening technologies – from domestic radio to voice interfaces – the article examines how design orients desire, pleasure, and behavior by crafting affordances that stabilize postures, attention, and daily rituals. The notion of affective openings is proposed as a critical-operational criterion to distinguish design configurations that produce capture from those that preserve practicable reversibility, contestability, and plurality of trajectories. Design emerges as an affectively and politically responsible practice when it organizes conditions of experience capable of translating human action into desirable action without transforming it into a closure of the field of possibilities.

A review of local commodity development and export strategies for coffee, cocoa, and major agricultural products