actor network theory or actor-network

Organisms from microbes to humans engage in a variety of social behaviors, which affect fitness in complex, often nonlinear ways. The question of how these behaviors evolve has consequences ranging from antibiotic resistance to human origins. However, evolution with nonlinear social interactions is challenging to model mathematically, especially in combination with spatial, group, and/or kin assortment. We derive a mathematical condition for natural selection with synergistic interactions among any number of individuals...

This qualitative study maps the process of drafting and consulting on Nepal's mental health legislation from 2006 to 2017. Fourteen people were interviewed, and interviews were analysed thematically. These themes were subsequently interpreted in light of Shiffman and Smith's policy analysis framework, as the process was found to be at the agenda-setting stage. Two groups of actors were identified with different views on appropriate policy content and how the policy process should be conducted. The first group included psychiatrists who initiated and controlled the drafting process, and who did not consider people with psychosocial disabilities to be equal partners...

National public health institutes (NPHIs) are crucial to the effectiveness of public health systems, including delivering essential public health functions and generating evidence for national health policies, strategies and plans. Currently, there is a significant lack of information regarding NPHI or NPHI-like organisations in Eastern Mediterranean Region (EMR) countries, including how they fit into their broader health systems governance landscape. NPHIs exist in 12 out of 22 EMR countries, yet there is no official International Association of National Public Health Institutes (IANPHI) regional network for the EMR, despite established IANPHI networks in four other regions...

Social network analysis and shared-patient physician networks have become effective ways of studying physician collaborations. Assortative mixing or "homophily" is the network phenomenon whereby the propensity for similar individuals to form ties is greater than for dissimilar individuals. Motivated by the public health concern of risky-prescribing among older patients in the United States, we develop network models and tests involving novel network measures to study whether there is evidence of geographic homophily in prescribing and deprescribing in the specific shared-patient network of physicians linked to the US state of Ohio in 2014...

Mobilization for revolts poses a significant challenge for rational choice theory because revolts are vulnerable to free-riding, which disincentivizes rational actors from mobilizing. Strong, informal relations such as kinship ties have been identified as factors that can shift the rational calculations of individuals and lead to mobilization for revolts. In social networks that are polarized by the presence of mobilized individuals, such as rebels, and actors opposing the mobilization effort such as the elite, kinship relations have not only a bridging effect but also a diverging one...

INTRODUCTION: The prevention of intimate partner violence (IPV) among young people is a major challenge for public policies. Nevertheless, there are a few prevention programs that have proven effective in France. “Sortir Ensemble & Se Respecter” (SE&SR) is a Swiss adaptation of “Safe Dates,” an American intervention program that has reduced violent behavior by young perpetrators and victims of IPV alike. The aim of this article is to analyze the applicability and “potential transferability” of SE&SR in France...

The training of human resources for health (HRH) is a recurring concern. The Virtual Campus for Public Health (VCPH) - the educational platform of the Pan American Health Organization (PAHO) - seeks to improve access to public health education, emphasizing leadership training for teams that plan, implement, and evaluate policies and educational initiatives.The objective of this work is to present the results of a consultation with experts on the virtual course "Leadership for Educational Management in Health Organizations", as part of a PAHO/VCPH strategy to strengthen leadership capacities for educational management in the Americas...

BACKGROUND: Introducing students to the "planetary health lenses" perspective is crucial. Comprehensive strategies for teaching this perspective are lacking, especially in the domains of "interconnection within nature (IWN)" and "systems thinking/complexity." There is also a scarcity of studies assessing medical students' opinions on planetary health and evaluating teaching strategies. OBJECTIVE: To understand Brazilian medical students' perceptions and knowledge of planetary health (PH) and evaluate the application of the educational material "Patient and Clinic through the Lens of Planetary Health," which addresses "IWN" and "complexity" through the sociological lens of Actor-Network Theory, in an integrative course at a medical school in Brazil...

The unprecedented impact of the pandemic on both activities and profit of actors draws out the various areas of the value chain that need to be strengthened to ensure resilience in the face of global shock. This study fills the gap by assessing the extent at which COVID-19 impacted the profit of mango value chain actors in southern Ghana. It also analyzed the governance structure and the existing linkages in the dissemination of market information in relation to the profit of the actors. A two-year panel survey on 240 respondents was conducted in 2020 through a multi-stage sampling technique in Greater Accra, Eastern and Volta regions of Ghana...

In real-world scenarios, making navigation decisions for autonomous driving involves a sequential set of steps. These judgments are made based on partial observations of the environment, while the underlying model of the environment remains unknown. A prevalent method for resolving such issues is reinforcement learning, in which the agent acquires knowledge through a succession of rewards in addition to fragmentary and noisy observations. This study introduces an algorithm named deep reinforcement learning navigation via decision transformer (DRLNDT) to address the challenge of enhancing the decision-making capabilities of autonomous vehicles operating in partially observable urban environments...

AIMS: The present study employed a network analysis approach to scrutinize a pig supply chain in a repeated outbreak province for human streptococcosis in Thailand and identified important actors that should be focused on for tailoring appropriate interventions. METHODS AND RESULTS: Nakhon Sawan province was chosen as the study site as the cases of human streptococcosis have been consecutively reported since 2014, with the number of cases ranging from 21 to 63. A questionnaire survey was used to collect data from actors along the pig supply chain, including pig farms, slaughterhouses, pork sellers, restaurants and customers...

This article reformulates Stephan Helmreich´s the ¨microbiomisation of race¨ as the historiality of otherness in the foundations of human microbiome science. Through the lens of my ethnographic fieldwork of a transnational community of microbiome scientists that conducted a landmark human microbiome research on indigenous microbes and its affiliated and first personalised microbiome initiative, the American Gut Project, I follow and trace the key actors, experimental systems and onto-epistemic claims in the emergence of human microbiome science a decade ago...

Elucidating the coupling between the structure and the function of the brain and its development across maturation has attracted a lot of interest in the field of network neuroscience in the last 15 years. Mounting evidence supports the hypothesis that the onset of certain brain disorders is linked with the interplay between the structural architecture of the brain and its functional processes, often accompanied with unusual connectivity features. This paper introduces a method called the network-based statistic-simultaneous node investigation (NBS-SNI) that integrates both representations into a single framework, and identifies connectivity abnormalities in case-control studies...

Complex networks are widespread in real-world environments across diverse domains. Real-world networks tend to form spontaneously through interactions between individual agents. Inspired by this, we design an evolutionary game model in which agents participate in a prisoner's dilemma game (PDG) with their neighboring agents. Agents can autonomously modify their connections with neighbors using reinforcement learning to avoid unfavorable environments. Interestingly, our findings reveal some remarkable results...

OBJECTIVE: To describe the profile of teaching-learning tutors in public health services and investigate which topics are of greatest interest in development spaces for these actors. METHOD: Cross-sectional study. Eligible tutors of Health Care Planning. Data collection using an electronic questionnaire composed of closed questions on sociodemographic characteristics, training and performance. Chi-square test used to compare proportions according to tutor typologies...

This article traces the influence of network power on mental health policy in Liberia, a low-income, post-conflict West African country. Based on key informant interviews, focus group discussions, and document analysis, the work uses an inductive approach to uncover how a network of civil society groups, government officials, diasporans, and international NGOs shaped the passage, implementation, and revision of the country's 2009 and 2016 mental health policies. With relations rooted in ties of information, expertise, resources, commitment, and personal connections, the network coalesced around a key agent, the Carter Center, which connected members and guided initiatives...

This paper introduces a novel data-driven self-triggered control approach based on a hierarchical reinforcement learning framework in networked motor control systems. This approach divides the self-triggered control policy into higher and lower layers, with the higher-level policy guiding the lower-level policy in decision-making, thereby reducing the exploration space of the lower-level policy and improving the efficiency of the learning process. The data-driven framework integrates with the dual-actor critic algorithm, using two interconnected neural networks to approximate the hierarchical policies...

The visual perception of individuals is thought to be mediated by a network of regions in occipitotemporal cortex that supports specialized processing of faces, bodies, and actions. In comparison, we know relatively little about the neural mechanisms that support the perception of multiple individuals and the interactions between them. The present study sought to elucidate the visual processing of social interactions by identifying which regions of the social perception network represent interpersonal synchrony...

In natural systems, organisms are embedded in complex networks where their physiology and community composition is shaped by both biotic and abiotic factors. Therefore, to assess the ecosystem-level effects of contaminants, we must pair complex, multi-trophic field studies with more targeted hypothesis-driven approaches to explore specific actors and mechanisms. Here, we examine aquatic microbiome responses to long-term additions of commercially-available metallic nanoparticles [copper-based (CuNPs) or gold (AuNPs)] and/or nutrients in complex, wetland mesocosms over 9 months, allowing for a full growth cycle of the aquatic plants...

Multi-task multi-agent systems (MASs) are challenging to model because they involve heterogeneous agents with different behavior patterns that need to cooperate across various tasks. Existing networks for single-agent policies are not suitable for this setting, as they cannot share policies among agents without losing task-specific performance. We propose a novel framework called Role-based Multi-Agent Transformer (RoMAT), which uses a sequence modeling technique and a role-based actor to enable agents to adapt to different tasks and roles in MASs...