Human Action Research Articles

An action decoding framework combined with deep neural network for predicting the semantics of human actions in videos from evoked brain activities.

Recently, numerous studies have focused on the semantic decoding of perceived images based on functional magnetic resonance imaging (fMRI) activities. However, it remains unclear whether it is possible to establish relationships between brain activities and semantic features of human actions in video stimuli. Here we construct a framework for decoding action semantics by establishing relationships between brain activities and semantic features of human actions. To effectively use a small amount of available brain activity data, our proposed method employs a pre-trained image action recognition network model based on an expanding three-dimensional (X3D) deep neural network framework (DNN). To apply brain activities to the image action recognition network, we train regression models that learn the relationship between brain activities and deep-layer image features. To improve decoding accuracy, we join by adding the nonlocal-attention mechanism module to the X3D model to capture long-range temporal and spatial dependence, proposing a multilayer perceptron (MLP) module of multi-task loss constraint to build a more accurate regression mapping approach and performing data enhancement through linear interpolation to expand the amount of data to reduce the impact of a small sample. Our findings indicate that the features in the X3D-DNN are biologically relevant, and capture information useful for perception. The proposed method enriches the semantic decoding model. We have also conducted several experiments with data from different subsets of brain regions known to process visual stimuli. The results suggest that semantic information for human actions is widespread across the entire visual cortex.

Multiple translatorship in the digital age: Interactive dynamics in the production of online literary translation

This article examines one of the first Chinese online literary translations from the early 2000s, Xiao Mao’s translations of two classic children’s novels by E. B. White. It uses the concepts of multiple translatorship and (con)textual voices to explain the translator’s involvement with different actors during his problem-solving process. The datasets include the paratexts of the translations, the mailing-list archives, and my interviews with the translator. A qualitative data analysis reveals a collective problem-solving process between Xiao and members of the New Threads online community. Most voices of these members are audible in peritexts thanks to the translator’s open credit, although there are some uncredited or miscredited voices. This interactive translation process demonstrates the translator’s relational identity with a posthuman approach, which means that he is part of an assemblage of various (non-)human actors. This article also suggests the democratizing potential of the shift from professional to non-professional translation.

World and Human Action Models towards gameplay ideation

Generative artificial intelligence (AI) has the potential to transform creative industries through supporting human creative ideation—the generation of new ideas1, 2, 3, 4–5. However, limitations in model capabilities raise key challenges in integrating these technologies more fully into creative practices. Iterative tweaking and divergent thinking remain key to enabling creativity support using technology6,7, yet these practices are insufficiently supported by state-of-the-art generative AI models. Using game development as a lens, we demonstrate that we can make use of an understanding of user needs to drive the development and evaluation of generative AI models in a way that aligns with these creative practices. Concretely, we introduce a state-of-the-art generative model, the World and Human Action Model (WHAM), and show that it can generate consistent and diverse gameplay sequences and persist user modifications—three capabilities that we identify as being critical for this alignment. In contrast to previous approaches to creativity support tools that required manually defining or extracting structure for relatively narrow domains, generative AI models can learn relevant structure from available data, opening the potential for a much broader range of applications.

Evaluation, thresholds, and practical commitments: the grammar of adjectival mildness

Abstract Mildly positive adjectives (henceforth, MPAs)—e.g., decent, acceptable, adequate—are typically used to express a moderately favorable evaluation of an object. In this manuscript, I present an investigation of the semantics and pragmatics of this class of expressions. I outline a proposal of MPAs as predicates whose positive form relies on particular type of functional standard which I refer to as a necessity standard: a threshold corresponding to the minimum value that an object must have in order to be pursued in compliance with the norms and requirements in place in the current world. The article provides two core contributions. On an empirical level, it enriches our understanding of the typology of gradable predicates, highlighting MPAs’ profile as strikingly overlapping with that of both relative and absolute predicates, two classes of gradable adjectives that are normally thought of as disjoint. Second, it affords a novel perspective on how gradability and modality, in conjunction with categories of human action such as value and practical commitments, are reflected in the grammatical behavior of these predicates and ultimately work together to enable us to express assessments in communication.

A Conceptual Relation Between the Need to Belong and Sense-of-Belongingness.

All humans have a fundamental need to belong (NTB), that is, forming and maintaining social connections. However, having these positive social bonds does not necessarily equal one's sense-of-belongingness (SOB). Contemporary literature frequently uses NTB and SOB interchangeably, or SOB is seen as a by-product of NTB satisfaction. This conceptual paper aims to (1) provide the arguments that there exists a difference between the "Need to Belong" as a universal construct of fundamental psychological need and "sense-of-belongingness" as a sensation that arose from distinct belongingness conditions, and (2) argue that these differences bear on human action under specific situations and contexts. Two hypothetical life situations are presented to illustrate the divergence of one's motivational need to belong compared to the specific self-processes regarding one's sense-of-belongingness. We concluded that there are arguments to claim that NTB and SOB, under specific social conditions, might be conceptually and empirically opposed or unrelated to one another.

EHC-GCN: Efficient Hierarchical Co-Occurrence Graph Convolution Network for Skeleton-Based Action Recognition

In tasks such as intelligent surveillance and human–computer interaction, developing rapid and effective models for human action recognition is crucial. Currently, Graph Convolution Networks (GCNs) are widely used for skeleton-based action recognition. Still, they primarily face two issues: (1) The insufficient capture of global joint responses, making it difficult to utilize the correlations between all joints. (2) Existing models often tend to be over-parameterized. In this paper, we therefore propose an Efficient Hierarchical Co-occurrence Graph Convolution Network (EHC-GCN). By employing a simple and practical hierarchical co-occurrence framework to adjust the degree of feature aggregation on demand, we first use spatial graph convolution to learn the local features of joints and then aggregate the global features of all joints. Secondly, we introduce depth-wise separable convolution layers to reduce the model parameters. Additionally, we apply a two-stream branch and attention mechanism to further extract discriminative features. On two large-scale datasets, the proposed EHC-GCN achieves better or comparable performance on both 2D and 3D skeleton data to the state-of-the-art methods, with fewer parameters and lower computational complexity, which will be more beneficial for application on computing resource-limited robot platforms.

CANDU Station Blackout D-PSA with RAVEN and TRACE Software

Nuclear energy provides a low-carbon source of electricity that provides consistent and reliable power in a cost-effective manner. However, the accident at Fukushima Daiichi in 2011 demonstrated several important lessons on nuclear power plant severe events and risk mitigation and led to important changes in designs, improvement in emergency planning, and better understanding of external event hazards. Since 2011, the Fukushima accident has also led to new methodologies to characterize risk for low-probability events such as station blackout (SBO). In particular, large external events that lead to loss of Class IV power, and subsequent failures of backup power (Class III power) and or emergency power, and where the outcome may be dependent on human/emergency response functions, require additional methodological development to better quantify the risks and consequences. Dynamic Probabilistic Safety Assessment (D-PSA) is a set of stochastic tools that allows the integration of technology availability (e.g. as in standard Probabilistic Safety Assessment), human action probability, uncertainty in predictive models, and possible deviations in the timing of any automatic or human-initiated actions. It allows the analysis of accident consequences with different mitigation strategies and action timings and can include the evaluation of both safety (e.g. dose) and/or economic consequences. It can also be used as part of a larger risk informed methodology such as the Risk Informed Safety Margin Characterization approach proposed by the U.S. Light Water Reactor Sustainability (LWRS) Program to rank safety system and operator actions in terms of their probable impact on an event. The RAVEN framework developed under the LWRS Program is used as a D-PSA driver along with the TRACE thermal-hydraulic code to quantify risk evolution during transient event sequences. This paper uses the Dynamic Event Tree approach to analyze the critical time to failure for a SBO in a CANada Deuterium Uranium (CANDU) power plant and the impact of system reliabilities and timing on event outcomes.

Rethinking ethics in policymaking: Dharma, reversibility and the imperatives of environmental policymaking

Since the age of Enlightenment, some philosophical traditions have assumed that human actions are ethically neutral, based on the belief that the non-human world is self-regulating and capable of maintaining balance regardless of human impact. However, with increasing human interference in the climate system and the accelerating rate of species extinction driven by human activity, this assumption appears to be flawed. Given the current environmental realities, the consequences of these actions are becoming increasingly difficult to manage, which demonstrates the need to challenge these frameworks. This paper outlines a framework for analysing political action by shifting the focus away from a solely human-centred perspective in ethics and decision-making, drawing on the concepts of reversibility and dharma. Reversibility integrates normative theory, political practice and policymaking, offering a way to address contemporary political challenges in a complex and pluralistic world. It emphasises that the human and non-human worlds are deeply interconnected and cannot be treated as separate. This perspective aligns with the principles of dharma, which advocate for the maintenance and preservation of cosmic order. Both reversibility and dharma highlight the responsibility humans have towards both the human and non-human realms, emphasising our interconnectedness. By bringing these approaches together, this paper proposes a novel framework for critically assessing the ethical dimensions of policies in today's uncertain and contingent world.

The Transnational Transfer of Book Translations as an Expanding Actor-Network – A Case Study of the Publication of Bronze and Sunflower in the UK and the US

ABSTRACT This paper understands the exportation of book translations across borders as embedded in the uneven power relations between languages and nation-states. It uses actor-network theory (ANT) as an analytical tool to explore the actors involved in bringing a Chinese contemporary children’s novel – Bronze and Sunflower (by Cao Wenxuan) – to Anglo-American markets, and how they interacted to facilitate its foreign publication. As presented by this case, the book’s transnational travelling can be understood as forming an actor-network, in which various human (such as rights managers, sub-agents and translators) and non-human actors (such as French language and subsidies) are involved and work together. Due to the dominance of English in the international market of book translations, this actor-network which enable a book’s transnational transfer expanded after its publication in Anglo-American markets, and the English language itself turned to be a vital non-human actor who facilitated its continuing transfer.

‘Made up’ and evolving – or already set in stone? Producing geotourism in the Niagara Region

ABSTRACT What are the origins of niche tourism? The making of a form of niche tourism is explained by more than the economic forces of supply and demand and socio-demographic factors. An integrated web of classificatory practices, people, institutions, knowledge, experts, and place-based factors is involved. This web, derived from the ideas of philosopher Ian Hacking, constitutes a field of niche tourism production. Geotourism and geotourists appear as subjects of interest that become economically useful, thus inviting business-related interventions. Through the field of niche tourism production, geotourism in the Niagara Region becomes an analysable phenomenon; it is created and cultivated as opposed to being purely a consequence of economic forces and socio-demographic factors. The continued emergence of different forms of niche tourism warrants research that explores the origins of specific niches, including those currently taking shape. This paper proposes a conceptual framework that articulates previously unacknowledged dimensions of the creation of niche tourism. A range of practices and phenomena as well as human and institutional actors, as components of an interwoven field of production, play an underappreciated role constituting a form of niche tourism.

Extending actor engagement: human–environmental engagement in multilevel socioecological systems

PurposeThis research aims to demonstrate the extension of actor engagement to include human–environmental engagement within broader socioecological systems.Design/methodology/approachThis work takes the perspective of Neo-animist Ontology which posits that since non-human biotic entities act as ecological and cultural resource integrators they should be considered as actors. In addition, the present article uses the concept of Nature’s Contributions to People, here renamed Nature’s Contributions to Humans (NCHs) to demonstrate the complex cognitive, emotional and behavioral dimensions of human–environmental interaction. The work also draws on existing concepts of actor engagement within multilevel socioecological systems.FindingsThis study offers a conceptual framework within which to understand how the complex interactions between humans and natural entities produce human–environmental engagement. It also provides evidence for three forms of human–environmental engagement, that is, purposeful involvement between humans and nature (natural ecosystems and non-human bioactors) with cognitive, emotional and behavioral dimensions. These engagement types have been termed: Nature–human regulating engagement; Nature–human material and cultural engagement; and Mindful engagement with nature. As this work shows, they arise due to human–environmental interactions involving the three forms of NCHs (regulating, material and non-material) and sustainable practices through which the environment and humans exert mutual influence upon one another. Additionally, this work identifies key focal actors and the novel, creative practices they implement to re-shape inter-industrial service ecosystems so demonstrating many-to-many A2A interactions within a socioecological system.Research limitations/implicationsFuture areas of research include in-depth investigation of the psychological (emotional-sensorial) processes of human engagement with nature and examination of the perspectives of non-human bioactors in human-initiated engagement with nature.Originality/valueThis study takes our understanding of engagement beyond its current focus on human-centric service ecosystems to include human–environmental engagement in socioecological systems. This involves the novel extension of the concept of an actor to include non-human biological agents involved in the provision of NCHs and enables an examination of how these so-called bioactors interact—directly or indirectly—with human actors. A further innovation here is the simultaneous zooming in and zooming out on actor engagement to gain a truly multilevel perspective.

Goal-directed action preparation in humans entails a mixture of corticospinal neural computations.

The seemingly effortless ability of humans to transition from thinking about actions to initiating them relies on sculpting corticospinal (CS) output from the primary motor cortex. The present study tested whether canonical additive and multiplicative neural computations, well-described in sensory systems, generalize to the CS pathway during human action preparation. We used non-invasive brain stimulation to measure CS input-output across varying action preparation contexts during instructed-delay finger response tasks. Goal-directed action preparation was marked by increased multiplicative gain of CS projections to task-relevant muscles and additive suppression of CS projections to non-selected and task-irrelevant muscles. Individuals who modulated CS gain to a greater extent were faster to initiate prepared responses. Our findings provide physiological evidence of combined additive suppression and gain modulation in the human motor system. We propose that these computations support action preparation by enhancing the contrast between selected motor representations and surrounding background activity to facilitate response selection and execution. KEY POINTS: Neural computations determine what information is transmitted through brain circuits. We investigated whether the motor system uses computations similar to those observed in sensory systems by non-invasively stimulating the corticospinal pathway in humans during goal-directed action preparation. We discovered physiological evidence indicating that corticospinal projections to behaviourally relevant muscles exhibit non-linear gain computations, whereas projections to behaviourally irrelevant muscles exhibit linear suppression. Our findings suggest that certain computational principles generalize to the human motor system and serve to enhance the contrast between relevant and background neural activity. These results indicate that neural computations during goal-directed action preparation may support motor control by increasing signal-to-noise within the corticospinal pathway.

Pleasing the Buyer: Human Rights Experts from Exporting Countries and Praise of Importing Countries

There is a growing amount of evidence suggesting that despite international organizations’ efforts to moderate hierarchical relations, power relations shape their actions and policies. Research shows that international organizations’ human rights promotion actions have not escaped this pattern, and powerful countries can often bias policies in favor of their allies. Less research has examined whether weaker and poorer countries use international human rights work to please dominant partners. For such countries, attaining membership in the closed club of a specialized committee is not only a duty but also a resource and an opportunity. This article argues that countries that have successfully nominated a member to a committee of human rights experts will use this membership to gain favor with their exports’ target markets. The article further argues that to capture this dynamic the analysis must look at bilateral relations between countries with members in expert committees and countries under review. The article hypothesizes that the number of positive points in the reports that countries receive from the TB is positively associated with the level of exports from TB member’s home countries to the reviewed country. Dyadic analysis of new and previous data on three TB’s monitoring and TB members corroborates this hypothesis. The article draws theoretical conclusions regarding the link between economic power hierarchies and human rights promotion.

The role of tourism on human-jaguar coexistence in northern Pantanal, Brazil: a conceptual framework in political ecology and more-than-human perspective

ABSTRACT A political ecology lens can yield a comprehensive understanding of the factors influencing human-wildlife coexistence within the context of tourism development. Here, we propose a conceptual framework that combines political ecology and more-than-human perspectives to examine power dynamics among diverse stakeholders, including scientists, local communities, NGOs, and non-human entities. This framework is applied to a case study focused on jaguars (Panthera onca) in Pantanal around the Encontro das Aguas State Park in Brazil. To disentangle these relationships, we propose a theoretical-analytical lens based on the combination of Actor-Network Theory (ANT) and Theory of Access (ToA). ANT emphasizes the formation of associations and networks involving both human and non-human actors. Further, ToA allows us to examine power dynamics that shape individuals’ access and control over resources. Our study offers valuable insight into the relationships between humans and nature – emphasizing the necessity of a holistic approach to conservation and nature-based tourism.

History education and democratic consciousness in Israel

The article examines how Israeli state-secular education integrates the principle of continuity and change through human agency into its history curriculum, in order to cultivate democratic consciousness. Drawing on theorists such as John Dewey, Marc Bloch, and Peter Seixas, it evaluates the curriculum's potential, or its lack thereof, to promote the understanding that democracy is constantly shaped by human actions. The article argues that, while the curriculum emphasises democratic values across various chapters from ancient times to the late twentieth century, it faces challenges in fostering historical consciousness that encourages students to act as agents of democratic change. Particularly, critical issues like relations between Jews and Arabs, or the tension between the country's Jewish and democratic identities are often neglected or not historicised, undermining a comprehensive view of modern Israeli society as a product of its history.

EMOTIONAL EXHAUSTION: Impact on healthcare professionals

There has been much discussion about understanding the perception of health system workers, focused on the Alcohol and Drug Psychosocial Support Center (CAPS AD). Objective: To understand the perception of CAPS AD workers, focusing on emotional exhaustion, making an interaction between demands and available resources, in order to promote the motivation of these professionals. Method: in this research report, qualitative research was used to reveal particular issues, revealing attitudes, motivations, beliefs, values, among other factors, that are inserted in human actions and relationships. This study was applied to 5 health professionals who work at CAPS AD. The methodological instrument used was composed of a semi-structured interview script, with 9 subjective questions, and the Free and Informed Consent Form. Results: the following categories emerged: “routine of work demands of CAPS AD professionals”, “difficulties related to aspects of work at CAPS AD”, “impacts suffered during the pandemic and influences on post-pandemic work issues”, “importance of organization at work in order to alleviate emotional exhaustion”. Discussion: reveals some important points involved in the research that are linked to routine, difficulties, impacts suffered during the pandemic period, the impacts of emotional exhaustion at work and the importance of organization in alleviating emotional exhaustion. Conclusion: Promote care actions for the professionals who work there, aiming to promote the reduction of emotional exhaustion, evaluating each detail in order to promote working conditions that reduce conflicts that emerge in the work environment.

How is the representation of nature depicted in Appleseed by Matt Bell?

Matt Bell's Appleseed is a captivating novel that intertwines the past, present, and future, illustrating the consequences of human actions on nature. It conveys a vital message: when we nurture the environment, it nurtures us back; neglect it, and we face dire repercussions. The narrative follows three characters across different timelines—each representing humanity's evolving relationship with nature. The names and lives of these characters symbolise the intricate connection between humanity and the earth. Notably, the significance of bees is emphasised, highlighting their crucial role in sustaining both human life and the ecosystem. In essence, Appleseed serves as a poignant reminder of our responsibility towards nature and the potential consequences of our choices.

Decision Fusion-Based Deep Learning for Channel State Information Channel-Aware Human Action Recognition.

WiFi channel state information (CSI) has emerged as a promising modality for human action recognition due to its non-invasive nature and robustness in diverse environments. However, most existing methods process CSI channels collectively, potentially overlooking valuable channel-specific information. In this study, we propose a novel architecture, DF-CNN, which treats CSI channels separately and integrates their outputs using a decision fusion (DF) strategy. Extensive experiments demonstrate that DF-CNN significantly outperforms traditional approaches, achieving state-of-the-art performance. We also provide a comprehensive analysis of individual and combined CSI channel evaluations, showcasing the effectiveness of our method. This work establishes the importance of separate channel processing in CSI-based human action recognition and sets a new benchmark for the field.

Two-stream spatio-temporal GCN-transformer networks for skeleton-based action recognition

For the purpose of achieving accurate skeleton-based action recognition, the majority of prior approaches have adopted a serial strategy that combines Graph Convolutional Networks (GCNs) with attention-based methods. However, this approach frequently treats the human skeleton as an isolated and complete structure, neglecting the significance of highly correlated yet indirectly connected skeletal parts, finally hindering recognition accuracy. This study proposes a novel architecture addressing this limitation by implementing a parallel configuration of GCNs and the Transformer model (SA-TDGFormer). This parallel structure integrates the advantages of both the GCN model and the Transformer model, facilitating the extraction of both local and global spatio-temporal features, leading to more accurate motion information encoding and improved recognition performance. The proposed model distinguishes itself through its dual-stream structure: a spatiotemporal GCN stream and a spatiotemporal Transformer stream. The former focuses on capturing the topological structure and motion representations of human skeletons. In contrast, the latter seeks to capture motion representations that consist of global inter-joint relationships. Recognizing the unique feature representations generated by these streams and their limited mutual understanding, the model also incorporates a late fusion strategy to merge the results from the two streams. This fusion allows the spatiotemporal GCN and Transformer streams to complement each other, enriching action features and maximizing information exchange between the two representation types. Empirical validation on three established benchmark datasets, NTU RGB + D 60, NTU RGB + D 120, and Kinetics-Skeleton, substantiates the model’s effectiveness. The experimental results indicate that, compared to existing classification frameworks, the method proposed in this paper improves the accuracy of human action recognition by 1–5% (NTU RGB + D 60 dataset). This improvement demonstrates the superior performance of the model in action recognition.

A stratigrapher’s reflecions on climate change and energy transition

Abstract This article consists of two well-differentiated parts. The first, based on a bibliographic analysis, tries to position this current episode of global warming within the framework of the geological history of climate change. The conclusion is clear and in line with the scientific consensus. Greenhouse gas emissions linked to human actions are the main cause of global warming. Given this situation, we can speculate about the future climate evolution of the “Anthropocene”. Unfortunately, such projections in the scientific literature paint a bleak picture. Paradoxically, future predictions take us back millions of years in geological history, placing humanity in unknown territory. Accordingly, we must ask ourselves what we can do to adjust the global thermostat. A first optimistic reflection is that the very fact that humans are the cause of the problem opens a window of hope. If global warming were due to natural causes linked to astronomical phenomena, to the internal dynamics of the planet, or to its evolution, we could do little or nothing to remedy our current climate situation. However, if we are the main cause of the crisis, we have the capacity to resolve it. This consideration, in turn, leads us to the second part of this article which comprises a series of personal reflections on the nature of the so-called energy transition and its main lines of action.