Search

AbstractAgency is action aimed at goals selected by an agent. A deterministic world view leaves scant room for agency. To reconcile the arguments, we represent action as nested control systems, ranging from clearly deterministic to clearly volitional. Negative feedback minimizes deviations from setpoints (goals). Goals are determined by higher modules in a hierarchy of systems, ranging from gamma-efferent spindles through reflexes to operant responses; these last, and the larger system that contains them, called the Self, comprise volitional agents. When operants become habitual they descend to closed teleonomic systems—automaticity. Change in emotional states, and unpredicted changes in the context–raise them back to full volitional systems. At the highest level is the Self—the brain’s model of the agent. When aroused out of open teleonomic functioning, it must reconsider means and ends. It does so by simulating action plans, using the same neural systems it uses to effect them. The simulated stimuli and responses are conscious, approximating their perceptions as experienced in real time; this verisimilitude gives them their hedonic value. Positive feedback plays a key role in these complex adaptive systems, as it focuses and holds attention on the most salient percepts and goals, permitting the self-organization of action plans. The Self is not a separate entity, but a colloquy of command modules wearing the avatar of the agent. This system is put into correspondence with Grossberg’s Adaptive Resonance Theory. Free will and determinism emerge not as binary opposites, but the modulating inputs to a spectrum of systems. [ABSTRACT FROM AUTHOR]

Concept normativity is a prominent subject of inquiry in the philosophical literature on the nature of concepts. Concepts are said to be normative, in that the use of concepts to categorise is associated with an evaluation of the appropriateness of such categorisation measured against some objective external standard. Two broad groups of views have emerged in accounting for the normativity of concepts: a weaker view traces such normativity to the social practice in which the agent using the concept is embedded, while a stronger view traces such normativity to a first-person capacity of reflection. However, both views have drawbacks: the weaker view seems not to do justice to the basic sense of normativity associated with an individual agent using a concept, while the stronger view ties such normativity with the first-person conscious evaluation, which appears to be too strong. Here, we propose a different view of concepts using principles from the Active Inference framework. We reconceive concepts, defining them as Bayesian beliefs—that is, conditional probability distributions—that represent causes and contingencies in the world, their form grounded in the exchange between the agent and its environment. This allows us to present a different view on the source of normativity, with an emphasis on the structure of the agent itself as well as its interaction with the environment. On the Active Inference view, concepts are normative in that they are intrinsically connected to the self-evidencing nature of an agent, whose very structure implies an evaluation of the concepts it employs. [ABSTRACT FROM AUTHOR]

The introduction of digital platforms has reshaped consumer behavior in various industries, and the lottery sector is no exception. While traditional lottery sales have long been a primary revenue source for PCSO, the advent of E-Lotto provides a new, convenient avenue for lottery. This research aims to evaluate the impact of E-Lotto on the sales performance of the Philippine Charity Sweepstakes Office (PCSO) within the National Capital Region (NCR). Further, this study determines whether E-Lotto serves as a complementary or competing channel for traditional lottery ticket sales and explores the implications of this shift on PCSO’s overall sales strategy. Through a mixed-methods approach, quantitative data on NCR lottery sales were analyzed to identify trends and assess shifts between digital and physical lottery channels. Qualitative interviews with PCSO stakeholders provide additional insights into operational and marketing strategies surrounding E-Lotto implementation. Findings reveal that E-Lotto expanded PCSO’s reach, particularly among younger, urban-based customers who prefer the convenience of online platforms. However, there is evidence that E-Lotto may also cannibalize traditional sales, especially in areas with smartphones and internet penetration. This underscores the need for PCSO to balance digital and physical sales channels effectively to maximize revenue. Recommendations include targeted marketing efforts, enhancing the user experience, and integrating cross-promotions between traditional and E-Lotto channels. By addressing these factors, PCSO can leverage the benefits of E-Lotto without undermining its established sales network. This study’s insights contribute to the broader understanding of digital transformation in gaming public institutions and its implications for sustainable revenue growth. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the impact of virtual mentors (VM) on the decision-making process and cultural awareness of prospective international students. Through a theoretical dialogue between Bourdieu's cultural intermediation and Barad's new materialism, we seek to understand the translative function of virtual mentors from the Global South as they shape international education choices and serve as cultural ambassadors for universities in the Global North. Using a mixed-method approach, we show the motivations behind this work, drawing from our experiences as mentors and why prospective international students who cannot afford in-country education agents seek mentorship and guidance from these virtual mentors who work 'below the radar'. While students acknowledge that virtual mentorship interactions sometimes provide cultural awareness about international education, it doesn't prepare them well enough for the cultural demands placed on internationally mobile students from the Global South, as some expressed the desire for more tailored activities towards cultural intelligence and awareness. [ABSTRACT FROM AUTHOR]

This research paper examines the relationship selling impact on sales effectiveness in Health Insurance from an agent’s perspective. The study analyzed primary data by personal interaction with respondents in the Karnataka region, India, and used descriptive research with stratified sampling. A sample size of 407 health insurance agents was selected for this study from the age group between 18 to 60 years from diverse backgrounds. The research methodology involves constructing a regression model using the SPSS tool to analyze the data. The findings show that personal interaction determinants have positive and statistically significant effects on sales effectiveness, however, customer dependency and self-discipline have negative and statistically significant impacts on sales effectiveness. The results support the models’ reliability and a good measure of construct validity. Variables like Interaction Intensity (II) and Customer Dependence (CD) (0.632), Personal Interaction (PI) and Customer Dependence (CD) (0.464), and Customer Oriented Selling (COS) and Cooperative Intentions (CI) (0.523) have relatively strong positive correlations, suggesting these pairs move together in the same direction. This implies that an agent’s personal resources can affect their ability to convert relationship-selling behavior to tangible sales results that can guide sales force recruitment and training. Similarly, the organizing and structuring of the sales force can be informed by the findings that customer relationship characteristics influence salespeople’s ability to translate relationship selling behavior into sales effectiveness.

The gap between software design and implementation often results in a lack of clarity and precision. Formal languages, based on mathematical rules, logic, and symbols, are invaluable for specifying and verifying system designs. Various semi-formal and formal languages, such as JSON, XML, predicate logic, and regular expressions, along with formal models like Turing machines, serve specific domains. This paper introduces a new specification formal language, ObTFL (Object Transaction Formal Language), developed for general-purpose distributed systems, such as specifying the interactions between servers and IoT devices and their security protocols. The paper details the syntax and semantics of ObTFL and presents three real case studies—federated learning, blockchain for crypto and bitcoin networks, and the industrial PCB board with machine synchronization—to demonstrate its versatility and effectiveness in formally specifying the interactions and behaviors of distributed systems.

Treating flexor tendon injuries within the digital flexor sheath (commonly referred to as palmar hand zone 2) presents both technical and logistical challenges. Success hinges on striking a delicate balance between safeguarding the surgical repair for tendon healing and initiating early rehabilitation to mitigate the formation of tendon adhesions. Adhesions between tendon slips and between tendons and the flexor sheath impede tendon movement, leading to postoperative stiffness and functional impairment. While current approaches to flexor tendon repair prioritize maximizing tendon strength for early mobilization and adhesion prevention, factors such as pain, swelling, and patient compliance may impede postoperative rehabilitation efforts. Moreover, premature mobilization could risk repair failure, necessitating additional surgical interventions. Pharmacological agents offer a potential avenue for minimizing inflammation and reducing adhesion formation while still promoting normal tendon healing. Although some systemic and local agents have shown promising results in animal studies, their clinical efficacy remains uncertain. Limitations in these studies include the relevance of chosen animal models to human populations and the adequacy of tools and measurement techniques in accurately assessing the impact of adhesions. This article provides an overview of the clinical challenges associated with flexor tendon injuries, discusses current on‐ and off‐label agents aimed at minimizing adhesion formation, and examines investigational models designed to study adhesion reduction after intra‐synovial flexor tendon repair. Understanding the clinical problem and experimental models may serve as a catalyst for future research aimed at addressing intra‐synovial tendon adhesions following zone 2 flexor tendon repair. [ABSTRACT FROM AUTHOR]

It is common in international football for the same agent to be paid both commission fees by the purchasing club for negotiating a player salary and a transfer fee. This dual representation creates a potential conflict of interest for the agent. The agent may not negotiate the highest salary for the player if a higher salary reduces the likelihood of a successful transfer by lowering the resources available for the transfer fee. We construct a gamble model of the transfer process and simulate the ex-ante agent commissions rates, expected player salary, transfer fee and club profit under the assumption of dual representation where the buying club pays all agent commissions. The assumption that the quality of the agent increases with the commission rate is essential to the model. Both the player and the club are better off when the club pays both commissions, however the agent is worse off. [ABSTRACT FROM AUTHOR]

Rumors are unverified pieces of information whose veracity status is unknown at the time of circulation. Preventing them at an early stage helps to mitigate the consequential loss and reduces the cost of recovering the nodes affected by rumors in the social network. However, existing research focuses more on rumor detection and control than on rumor prevention. In this article, we propose a Multi-Criteria Decision Making (MCDM) integrated approach for rumor prevention that addresses three issues. Firstly, the need for a rumor prevention model to debunk them at an early stage. Secondly, introduction of counter-rumor in the system as soon as a rumor is detected to reduce the time lag between rumor diffusion and counter-rumor diffusion. Thirdly, selection of trusted authorities as key nodes to initiate the counter-rumor diffusion. The proposed method is two-fold. Firstly, we propose Analytic Hierarchy Process - Technique for Order of Preference by Similarity to Ideal Solution (AHP-TOPSIS) method, an MCDM-based approach, to select the important nodes and host agents on them. Secondly, using agent nodes, we propose a counter-rumor diffusion model Susceptible-Infected-Recovered-Prevented-Agent (SIRPA) which is an improved variant of the popular epidemic model Susceptible-Infected-Recovered (SIR). The proposed SIRPA model is simulated on six social network datasets and multiple experiments are performed on these networks to validate the proposed work. The results show that our proposed SIRPA model is effective in preventing rumors in social networks and outperforms the baseline model. [ABSTRACT FROM AUTHOR]

Background: In this study, agents working in positions of authority within health sector organisations shared their perspectives concerning both the involvement of experts by experience with intellectual disabilities within their own organisations and their recommendations as to how best to involve experts by experience in policy and practice. Method: Using purposive sampling, eight agents were selected for semi-structured interviews. The interviews were analysed using thematic analysis. Results: The results indicated the importance of involving experts by experience. However, they also highlighted several barriers such as a lack of emphasis on genuine attention, insufficient visibility and recognition of expertise, and a lack of support for sustainable inclusion. Conclusions: Agents are willing to involve experts by experience in health sector organisations, but practical challenges hindered them from actually doing so. This study emphasises the importance to find solutions for better inclusion in policies. [ABSTRACT FROM AUTHOR]

Copyright of Procesamiento del Lenguaje Natural is the property of Sociedad Espanola para el Procesamiento del Lenguaje Natural and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Disinformation represents one of the major obstacles to meaningful actions against climate change skepticism. This study, therefore, aimed to investigate climate change disinformation across types, agents, and media platforms as reported in selected online newspapers. A total of 124 news articles gathered from Malaysia's The Star and New Straits Times were subjected to content analysis. The articles were collected from the newspapers' digital archives between August 2015 and October 2021 using "climate change" and "disinformation" as keywords. Subsequently, data were analyzed using the Chi-square test and descriptive statistics. The study found that disinformation about climate change is more likely to be spread by politicians, organizations, and anonymous agencies compared with business tycoons, celebrities, and academics. Also, misleading and fabricated contents represent the most common types of disinformation spread by politicians. The findings suggest that politics and social media represent the most critical factors influencing climate change. The study, therefore, calls for the joint efforts of activists, media practitioners, and governments to mitigate disinformation about climate change. [ABSTRACT FROM AUTHOR]

The gap between software design and implementation often results in a lack of clarity and precision. Formal languages, based on mathematical rules, logic, and symbols, are invaluable for specifying and verifying system designs. Various semi-formal and formal languages, such as JSON, XML, predicate logic, and regular expressions, along with formal models like Turing machines, serve specific domains. This paper introduces a new specification formal language, ObTFL (Object Transaction Formal Language), developed for general-purpose distributed systems, such as specifying the interactions between servers and IoT devices and their security protocols. The paper details the syntax and semantics of ObTFL and presents three real case studies—federated learning, blockchain for crypto and bitcoin networks, and the industrial PCB board with machine synchronization—to demonstrate its versatility and effectiveness in formally specifying the interactions and behaviors of distributed systems. [ABSTRACT FROM AUTHOR]

Social responses to virtual humans in immersive Virtual Reality (VR) may depend on whether users perceive them to be controlled by a person (avatar) or by the computer (agent). As related evidence is growing, this meta-analysis set out to synthesize corresponding findings. Specifically, we analyzed whether the perceived agency of a virtual human affects (1) social presence, (2) the evaluation of the virtual entity, and (3) behaviors toward it differently. Additionally, we controlled for task type, the virtual entity's appearance, the type of interaction, and agency manipulation. A literature search yielded 20 studies examining 911 participants (agent condition: 460, avatar condition: 451). Differences between perceived avatars and agents in social responses were calculated using Hedges' g. Results showed differences for social presence (g = 0.65, p =.001) and evaluation (g = 0.30, p =.024) in favor of avatars over agents. No effects emerged for behavioral outcomes. Meta-regressions revealed larger agency-differences in social presence for neutral than for negative tasks, and differences in evaluation for positive compared to mixed and neutral tasks. Overall, our findings suggest that while deliberate social responses like social presence and evaluation depend on perceived agency, automatic behaviors do not. For future research, particularly consistent conceptualizations of key variables are necessitated. [ABSTRACT FROM AUTHOR]

As technology continues to advance, interest in how humans perceive and interact with autonomous agents has increased, spurring ample research within human-agent teams (HATs). However, the word team is a bit of a misnomer, in that much of this research has examined one human in relation to one agent. We extend the HAT literature by applying a multilevel lens to develop future research questions regarding trust in heterogeneous HATs. First, we assert that trust is an attitude that is multireferent, suggesting research should explore not just humans' trust in agents, but many other perspectives such as agents' trust in humans. Second, we assert that trust is multilevel, suggesting research should explore higher-level emergent forms of trust. Third and fourth, we assert trust is dynamic and event-based, suggesting research should explore discontinuous changes in trust in response to events such as agent- and human-enacted trust violation and repair. [ABSTRACT FROM AUTHOR]

In the contemporary social network landscape, opinion polarization has emerged as a prominent challenge, sparking concerns about the effective guidance of news sentiment and mitigation of opposing opinions. This is particularly pertinent in the intricate web of social networks, where complexity reigns supreme. Addressing this pivotal issue, this article introduces a news opinion guidance approach grounded in motif recognition. To accurately mirror real-world social networks, we have crafted an agent-based model that simulates polarized news propagation. This model encompasses diverse media agents and user agents, meticulously replicating the news dissemination process within the network. In our quest to unveil the underlying structures of social networks, we have enhanced the Augmented Multiresolution Network approach, incorporating multi-dimensional node attributes for more nuanced clustering and network mapping. This refinement enables us to pinpoint potential motif regions with greater precision. Leveraging these insights, we introduce a triangular motif-based opinion guidance strategy aimed at shaping opinion distribution by bolstering the influence of nodes within these motifs. Once the pertinent motifs are identified, we undertake simulation experiments that reveal the remarkable efficacy of our motif recognition-driven guidance strategy. Notably, it reduces opinion polarization by a substantial 74% compared to scenarios without guidance strategies. This research offers a fresh perspective on crafting personalized and targeted news sentiment guidance strategies. It presents a versatile and potent computational framework for understanding and managing polarization phenomena in social networks, carrying profound theoretical and practical ramifications. [ABSTRACT FROM AUTHOR]

Image segmentation through clustering is a widely used technique in computer vision that partitions an image into multiple segments by grouping pixels based on feature similarity. Although effective for certain applications, this approach often struggles with the complexity of real-world images, where noise and random variations can significantly affect feature homogeneity, leading to incorrect pixel classifications. To address these limitations, this paper introduces a novel hybrid image segmentation method that combines an agent-based model with a clustering technique to enhance segmentation accuracy and robustness. The method starts with an agent-based model as a preprocessing step aimed at homogenizing pixel intensities within each region. In this model, pixels adjust their intensities based on a consensus reached within their neighborhood, promoting a more uniform feature distribution. Subsequently, the Firefly metaheuristic clustering method is applied to segment the preprocessed image into distinct regions. Metaheuristic techniques, distinguished from classical clustering methods, possess the capability to adaptively navigate through a broad solution space to discover optimal clustering configurations. This adaptability makes them suitable for complex image datasets. The efficacy of the proposed hybrid segmentation method has been tested on various images, employing key quality indices for evaluation. Experimental outcomes demonstrate that this approach yields superior segmented images, showcasing enhanced quality and robustness compared to other segmentation methods.

IntroductionAfter the victory of the Islamic Revolution in February 1978, the Islamic Republic was founded on two core principles: divine sovereignty and popular sovereignty. One of the most important ideals of the Revolution was to establish an Islamic state that would implement the laws and rules of Islam. Such a state would not only manage the everyday affairs of the people but also guide society towards spiritual perfection and closeness to God. However, despite the efforts made over the years, a true Islamic state has yet to be fully realized. This is largely due to various challenges and the damage faced by the Islamic State, one of which is linked to its agents. It is thus essential to identify the vices in the personal and behavioral characteristics of agents. These agents are essential pillars of the Islamic state, playing a vital role in the political system’s stability and efficiency, and in achieving the government’s objectives. Throughout history, however, the agents have faced numerous challenges and vices that have threatened not only their individual and collective lives but also the survival and continuity of the political system itself. Religious teachings consistently emphasize the importance of the health and competence of agents of the Islamic state, warning that the mismanagement of such officials is one of the key factors in the collapse of political systems. In this context, Ayatollah Khamenei’s insights into the vices of agents are particularly valuable. As both the leading Shia thinker in the Islamic world and the Supreme Leader of Iranian society, his views are crucial in identifying the vices of the state officials and offering solutions for preventing or addressing them. In this line, the present study intended to identify and analyze the vices of agents of the Islamic system, which in turn have contributed to the delay in the realization of the Islamic state. Relying on Ayatollah Khamenei’s views, the study aimed to address the following question: What vices have been inflicted upon agents that have led to the delay in the realization of the Islamic state?Materials and MethodsThe current study employed a qualitative content analysis method. The data was collected from various sources, including books, articles, and the Official Website of the Office for the Preservation and Publication of the Works of the Grand Ayatollah Sayyid Ali Khamenei (www. khamenei. ir).Results and DiscussionFrom Ayatollah Khamenei’s perspective, the most significant challenges and vices experienced by agents that could delay the realization of the Islamic state include the following: the whims of the self, despair and hopelessness, prioritization of people’s satisfaction over God’s, dogmatism and sanctification, extreme modernism, neglect of cultural issues, indulgence in luxury, secularism, corruption, broken promises to the people, evasion of justice and the law, dominance, extreme factionalism, divisiveness, and dependence on foreign influences. According to Ayatollah Khamenei, the most important vices are the evasion of justice and indulgence in luxury. To remedy the vices, he proposed to follow the model set by the Prophetic (Nabawi) and the Alevi government.ConclusionIf state officials lack integrity and competence, the resulting damage will permeate Islamic society, leading it astray from the right path. Therefore, the negative characteristics among agents of the Islamic State may cause serious and irreparable damage to the system, delaying or even preventing the realization of the Islamic State. Ayatollah Khamenei’s views on the shortcomings and vices of state officials and the methods to prevent or address them provide valuable guidelines. These insights can help ensure the moral integrity of agents and contribute to the realization of the Islamic state.

Collaborative robotics is a major topic in current robotics research, posing new challenges, especially in human–robot interaction. The main aspect in this area of research focuses on understanding the behavior of robots when engaging with humans, where reinforcement learning is a key discipline that allows us to explore sophisticated emerging reactions. This review aims to delve into the relevance of different sensors and techniques, with special attention to EEG (electroencephalography data on brain activity) and its influence on the behavior of robots interacting with humans. In addition, mechanisms available to mitigate potential risks during the experimentation process such as virtual reality are also be addressed. In the final part of the paper, future lines of research combining the areas of collaborative robotics, reinforcement learning, virtual reality, and human factors are explored, as this last aspect is vital to ensuring safe and effective human–robot interactions. [ABSTRACT FROM AUTHOR]

In the standard theory of deontic modals, 'ought' is understood as expressing a propositional operator. However, this view has been called into question by Almotahari and Rabern's puzzle about deontic 'ought', according to which the ethical principle that one ought to be wronged by another person rather than wrong them is intuitively coherent but the standard theory makes it incoherent. In this paper, I take up Almotahari and Rabern's challenge and offer a refinement of the standard theory to handle the puzzle. I propose that 'ought' is evaluated relative to contextual parameters (e.g. Kratzer's conversational backgrounds, Finlay and Snedegar's alternative sets) and those contextual parameters are sensitive to agents as well as possible worlds. [ABSTRACT FROM AUTHOR]

The article discusses drug resistance in malaria, particularly in low and middle-income countries. It highlights the historical presence of malaria and its impact on notable figures throughout history. The World Health Organization reports that malaria remains a significant public health issue, with millions of cases and hundreds of thousands of deaths each year. The article also discusses the development of drug resistance in malaria parasites and the challenges it poses for treatment. It emphasizes the need for research and development of new, affordable, and effective antimalarial medications. The text discusses the development of resistance among microbes, specifically in relation to antimalarial drugs. It emphasizes that resistance is a natural phenomenon that occurs due to the selective drug pressure caused by the unnecessary or imprudent use of new agents in healthcare and agricultural settings. The text suggests that strict health and drug policies should be implemented to combat resistance, and public and private healthcare authorities should raise awareness about the irrational prescribing of antimicrobials. The text also includes information about the author's consent for publication, disclosure of financial involvement, data availability, and authorship contribution. The given document is a list of references related to the topic of malaria. It includes various scientific articles and sources that discuss different aspects of malaria, such as immune responses, clinical studies, treatment options, and the history of antimalarial drugs. The references cover a range of perspectives and research findings, providing valuable information for library patrons conducting research on malaria. This document contains a collection of references related to the discovery and development of antimalarial [Extracted from the article]

Systems‐of‐systems are characterized by the independence of their constituent elements. Such an element is usually socio‐technical, comprising technology, humans, or organizations. To capture its independence, it needs to be viewed as an intelligent agent that relies on an internal model of the world for its decision‐making. Hence, a system‐of‐systems model will include multiple agents that inside themselves contain different models of the same system‐of‐systems. Describing these overlapping subjective models and their usage by the agents is essential to properly understand the resulting behavior of the overall system‐of‐systems. Current modeling practices are not well suited for dealing with this, and the paper therefore outlines an ontology that makes the agents and their internal models more explicit. The paper also discusses the implications such models have on systems engineering practices and how they address known system‐of‐systems engineering pain points. [ABSTRACT FROM AUTHOR]

One of the cognitive abilities most affected by substance abuse is decisionmaking. Behavioral tasks such as the Iowa Gambling Task (IGT) provide a means to measure the learning process involved in decision-making. To comprehend this process, three hypotheses have emerged: (1) participants prioritize gains over losses, (2) they exhibit insensitivity to losses, and (3) the capacity of operational storage or working memory comes into play. A dynamic model was developed to examine these hypotheses, simulating sensitivity to gains and losses. The Linear Operator model served as the learning rule, wherein net gains depend on the ratio of gains to losses, weighted by the sensitivity to both. The study further proposes a comparison between the performance of simulated agents and that of substance abusers (n = 20) and control adults (n = 20). The findings indicate that as the memory factor increases, along with high sensitivity to losses and low sensitivity to gains, agents prefer advantageous alternatives, particularly those with a lower frequency of punishments. Conversely, when sensitivity to gains increases and the memory factor decreases, agents prefer disadvantageous alternatives, especially those that result in larger losses. Human participants confirmed the agents' performance, particularly when contrasting optimal and sub-optimal outcomes. In conclusion, we emphasize the importance of evaluating the parameters of the linear operator model across diverse clinical and community samples. [ABSTRACT FROM AUTHOR]

CBRN (Chemical, Biological, Radiological, and Nuclear) risk communication with the public is critical to emergency preparedness and response. Effectively communicating with the public during and after incidents or terrorist attacks involving CBRN hazards is essential for minimising health effects and ensuring public safety. Fundamental principles and strategies for CBRN risk communication include some of the following key elements: timeliness and accuracy, transparency, empathy and understanding, consistent messages, plain language, media coordination, and feedback mechanisms. Applying this approach, emergency responders and authorities can enhance CBRN risk communication with the public, ultimately minimising health effects and fostering community resilience in the face of any emergency involving the uncontrollable release of CBRN agents. By incorporating these aspects into risk communication strategies, authorities can enhance their ability to effectively convey information, build trust, and promote public safety when dealing with dangerous substances. The paper reflects on the latest situation in this area where effective risk communication is crucial when dealing with CBRN and other dangerous substances to ensure the safety of individuals and the community. [ABSTRACT FROM AUTHOR]

In the recent Supreme Court case Philipp v Barclays Bank UK Pic (Philipp), Lord Leggatt ironed out the long-held misconception of the Quincecare duty being an independent duty so to conflict with other general duties is nothing more than a subordinate duty (non-independent duty) and is part of a general duty to enquire premises on reasonable ground for believing that the agent of its customer was attempting to defraud the customer. [ABSTRACT FROM AUTHOR]

Copyright of Arquitectura + is the property of Revista Arquitectura + and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Summary: In this paper, we propose a deep reinforcement‐based approach to generate an animation of an agent using a broom‐like tool to transport a target object. The tool is attached to the agent. So when the agent moves, the tool moves as well.The challenge is to control the agent to move and use the tool to push the target while avoiding obstacles. We propose a direction sensor to guide the agent's movement direction in environments with static obstacles. Furthermore, different rewards and a curriculum learning are implemented to make the agent efficiently learn skills for manipulating the tool. Experimental results show that the agent can naturally control the tool with different shapes to transport target objects. The result of ablation tests revealed the impacts of the rewards and some state components. [ABSTRACT FROM AUTHOR]

The transmission of pathogens from animals to humans is the cause of the appearance of the majority of newly emerging diseases. The purpose of this review is to assess the danger of zoonotic pathogens of dangerous and especially dangerous viral infectious diseases as potential agents of pandemics. Materials and methods. The paper presents an analysis of data published in domestic and English-language scientific publications, as well as posted on the Internet. The research method is analytical. The discussion of the results. At least 70 % of all emerging diseases have a zoonotic reservoir. The exponential growth of human activity in previously undeveloped territories determines the increasing influence of zoonotic pathogens. The infection of people with zoonotic pathogens occurs in direct and indirect contact with infected animals and surfaces contaminated with their secretions, transmissible transmission through arthropod bites, food transport through the consumption of contaminated food and drinking water. Two different transmission models have been established among zoonoses from wild animals to man. One of these models assumes, that human infection is a random event with a low probability, in the future, the pathogen is transmitted from person to person. In the second model, direct or vector-mediated pathogen transfer from animal to human is a link in the natural cycle of the pathogen. The risk of transmission of the virus from the zoonotic reservoir to humans is the highest in animal species adapted to human habitats. Conclusions. The highest level of danger as a source of zoonotic diseases represent primates, ungulates, carnivores and especially bats, which are natural reservoirs for a number of dangerous and especially dangerous viral diseases. Representatives of families Poxviridae, Ortomyxoviridae and Coronaviridae have already been caused pandemics, which caused enormous damage to all spheres of human activity. These pathogens can be considered as the most likely agents of future pandemics.

Agents and agent-based systems are becoming essential in the development of various fields, such as artificial intelligence, ubiquitous computing, ambient intelligence, autonomous computing, and intelligent robotics. The concept of autonomous agents, inspired by the observed agency in living systems, is also central to current theories on the origin, development, and evolution of life. Therefore, it is crucial to develop an accurate understanding of agents and the concept of agency. This paper begins by discussing the role of agency in natural systems as an inspiration and motivation for agential technologies and then introduces the idea of artificial agents. A systematic approach is presented for the classification of artificial agents. This classification aids in understanding the existing state of the artificial agents and projects their potential future roles in addressing specific types of problems with dedicated agent types. [ABSTRACT FROM AUTHOR]

Copyright of Brazilian Journal of Education, Technology & Society (BRAJETS) / Cadernos de Educação Tecnologia e Sociedade (CETS) is the property of Brazilian Journal of Education, Technology & Society - BRAJETS and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Trust is still an issue in the insurance sector as the insurance product sold is intangible. This study focuses on two major intermediaries, namely individual agents, and corporate agent-banks, selling individual health insurance policies based on whether they are trusted by policyholders. The research design used in this study was descriptive. The findings indicate that there is no significance difference in the mean rank of policyholders towards strong work ethics, competency, pricing transparency, claim process transparency, and privacy of shared information among agency channel and bancassurance channel. However, there exists a significant difference in the mean rank of policyholders towards ease of access. It can be concluded that Corporate Agent-Banks are available with more ease of access in comparison to Individual Agents. Since, the opinion of policyholders towards bancassurance channel and agency channel are almost similar towards agreement, it is recommended that General Insurers can invest in both these channels in Mumbai. [ABSTRACT FROM AUTHOR]

This study delves into the examination of gender diversity trends within the Indian insurance sector, with a particular focus on women's roles as insured, agents, and employees. The study is based on secondary data compiled from the Annual Reports of the IRDAI spanning from 2017-18 to 2022-23. Notably, it reveals that in the life insurance sector, LIC exhibits a commendable performance in terms of women policy holders in comparison to private sector counterparts. However, in the context of gender diversity in employment, private insurance companies take the lead, both in the life insurance and general insurance segments. Consequently, it is evident that while private sector insurers should strive to increase policies issued to women, the public sector, along with the regulatory authority IRDAI, needs to make concerted efforts to enhance female representation within their workforce. Thus, the collaborative efforts from all stakeholders will foster a more equitable insurance sector. [ABSTRACT FROM AUTHOR]

This present study intends to investigate the pattern and predictor debt-financed emigration and its impact on migration experience and the household economy in Kerala using Kerala Migration Survey (KMS), 2018 data. Bivariate and multivariate analyses (binary logistic regression) were performed, and the debt-to-income ratio (DTI) was computed to fulfil the study's objective. The result shows that 45.52% of Keralite emigrants borrow debt regarding their socio-economic status to finance their emigration process. Debt-financed emigrants spend high costs on visas, air tickets, and passports as majority of them recruited through agents than non-debt-financed emigrants. Debt migration may not be a profitable or sustainable endeavour, as non-debt migrants' annual savings and monthly expenditures are higher than debt migrants. The debt-to-income ratio (DTI) also shows that the financial health of the debt-financed migrant household is in more severe condition than the non-debt. [ABSTRACT FROM AUTHOR]