Interaction Rules Research Articles

Deciphering the rule of antigen-antibody amino acid interaction.

Antigenic drift is the biggest challenge for mutagenic RNA virus vaccine development. The primary purpose is to determine the IEMM (immune escape mutation map) of 20 amino acids' replacement to reveal the rule of the viral immune escape. To determine the relationship between epitope mutation and immune escape, we use universal protein tags as a linear epitope model. To describe and draw amino acid linkage diagrams, mutations of protein tags are classified into four categories: IEM (immune escape mutation), ADERM (antibody-dependent enhancement risk mutation), EQM (equivalent mutation), and IVM (invalid mutation). To overcome the data limitation, a general antigen-antibody (Ag-Ab) interaction map was constructed by analyzing the published three-dimensional (3D) Ag-Ab interaction patterns. (i) One residue interacts with multiple amino acids in antigen-antibody interaction. (ii) Most amino acid replacements are IVM and EQM. (iii) Once aromatic amino acids replace non-aromatic amino acids, the mutation is often IEM. (iv) Substituting residues with the same physical and chemical properties easily leads to IVM. Therefore, this study has important theoretical significance for future research on antigenic drift, antibody rescue, and vaccine renewal design. The antigenic epitope mutations were typed into IEM, ADERM, EQM, and IVM types to describe and quantify the results of antigenic mutations. The antigen-antibody interaction rule was summarized as a one-to-many interaction rule. To sum up, the epitope mutation rules were defined as IVM and EQM predomination rules and the aryl mutation escape rule.

Agents of social change in the institutional field of medicine

The pragmatic goal of this article is to study agent activity aimed at changes in the medical institutional field, under conditions of high social instability. The implementation of the empirical part of аrticle required an adequate methodological and conceptual approach, on the basis of which it could be designed and implemented. As a general methodological platform, the author chose the paradigm of complexity, which builds its methodological proposals on the assumption that large complex nonlinear systems change according to laws that are fundamentally different from those by which simple linear system formations function. Society refers precisely to such complex system objects, and therefore the appeal to such a methodological basis is adequate and fruitful. The work offers the author’s view on the processes of social changes, which are conceptualized as the process of changing the social order. The latter, in turn, is considered as a set of all the practices of social interactions that are currently present in society. The key point in this concept is the statement about the presence of two fundamentally different mechanisms of social change — organizational and self-organizational. It is emphasized that high social instability increases the weight of the self-organizing component of changes, which can fade into the background in relatively stable periods. Applying this theoretical framework to the processes in the institutional field of medicine, we get a model of relevant changes, where both organizational (formal rules of the game, laws, government regulations) and self-organization (informal, spontaneously formed rules of everyday interactions in this institutional field) are equally important. Both of these mechanisms have their conductors-agents, through whom they are implemented. The issue of consistency and balance between these different rules of the game is key for institutional management. At the empirical level, the work examines in detail the agentic actions of U. Suprun in the process of her attempts to reform domestic medicine during 2016-2019 (organizational mechanisms), as well as the agentic activity of volunteers from the "Svoi" Foundation, which is headed by Lesia Lytvynova (self-organizational mechanisms). All the features of these two processes of change, their fundamental difference and the complexities that arise in the process of their coordination are shown. The need to build managerial strategies that take these circumstances into account is emphasized.

Novel Stability Conditions for Nonlinear Monotone Systems and Consensus in Multiagent Networks

We introduce a novel definition of monotonicity, termed “type-K” in honor of Kamke, and study nonlinear type-K monotone dynamical systems possessing the plus-subhomogeneity property, which we call “K-subtopical” systems after Gunawardena and Keane. We show that type-K monotonicity, which is weaker than strong monotonicity, is also equivalent to monotonicity for smooth systems evolving in continuous-time, but not in discrete-time. K-subtopical systems are proved to converge toward equilibrium points, if any exists, generalizing the result of Angeli and Sontag about convergence of topical systems' trajectories toward the unique equilibrium point when strong monotonicity is considered. The theory provides an new methodology to study the consensus problem in nonlinear multi-agent systems (MASs). Necessary and sufficient conditions on the local interaction rule of the agents ensuring the K-subtopicality of MASs are provided, and consensus is proven to be achieved asymptotically by the agents under given connectivity assumptions on directed graphs. Examples in continuous-time and discrete-time corroborate the relevance of our results in different applications

Configuration-sensitive face-body interactions in primate visual cortex

Traditionally, the neural processing of faces and bodies is studied separately, although they are encountered together, as parts of an agent. Despite its social importance, it is poorly understood how faces and bodies interact, particularly at the single-neuron level. Here, we examined the interaction between faces and bodies in the macaque inferior temporal (IT) cortex, targeting an fMRI-defined patch. We recorded responses of neurons to monkey images in which the face was in its natural location (natural face-body configuration), or in which the face was mislocated with respect to the upper body (unnatural face-body configuration). On average, the neurons did not respond stronger to the natural face-body configurations compared to the summed responses to their faces and bodies, presented in isolation. However, the neurons responded stronger to the natural compared to the unnatural face-body configurations. This configuration effect was present for face- and monkey-centered images, did not depend on local feature differences between configurations, and was present when the face was replaced by a small object. The face-body interaction rules differed between natural and unnatural configurations. In sum, we show for the first time that single IT neurons process faces and bodies in a configuration-specific manner, preferring natural face-body configurations.

Farewell to the requirement for character independence: phylogenetic methods to incorporate different types of dependence between characters.

This paper discusses methods to take into account interactions between characters, in the context of parsimony analysis. These interactions can be in the form of some characters becoming inapplicable given certain states of other, primary characters; in the form of only certain states being allowed in some characters when a given state or set of states occurs for other characters; or in the form of transformation costs in some character being higher or lower when other characters have certain states or transformations between states. Character-state reconstructions and evaluation of trees under the assumption of independence may easily lead to ancestral assignments that violate elementary rules of biomechanics, well-established theories relating form and function or ideas about character co-variation. An obvious example is reconstructing an ancestral bird as wingless and flying at the same time; another is reconstructing a protein-coding gene as having a stop codon in some ancestors. If the characters are optimized independently, such chimeric ancestral reconstructions can occur even when no terminal displays the impossible combination of states. A set of conventions (implemented via new TNT commands and options) allows the definition of complex rules of interaction. By recoding groups of characters with proper step-matrix costs (and excluding impossible combinations from the set of permissible states), it is possible to find the ancestral reconstructions that maximize homology (and thus the degree to which similarities can be explained by common ancestry), within the constraints imposed by the rules specified by the user. We expect that considerations of biomechanics, functional morphology and natural history will be a source of many theories on possible character dependences, and that the present implementation will encourage users to take the possibility of character dependences into account in their phylogenetic analyses.

Methods for Building Successful chatbot Communication in the Discourse of Sales in the Field of Digital Goods (Mobile Phones) on the Example of English and Russian Language Materials

Introduction. Digitalization processes have been actively penetrating the life of a modern person in the last decade. Artificial intelligence in various forms and formats creates new linguistic knowledge about the communication process. By creating new features and rules of speech interaction in various types of network discourse, the problems of achieving the success of speech acts built through chatbots remain ineradicable. This problem is especially acute in the field of advertising and PR, where communication with target auditors and target groups of the public is one of the most important tools for achieving the company's goals.Methodology and sources. A preliminary assessment of the effectiveness and potential of chatbot communication necessitates this. Using the method of linguistic modeling, you can create conditions and prescribe certain “rules” for successful interaction between a person and a chatbot. To create models for the Russian-speaking and English-speaking spheres, it is necessary to conduct a frame analysis and construct concepts of concepts that dominate in advertising discourse, or rather its variety: the discourse of sales in the field of digital goods (cell phones). To do this, it is necessary to conduct a corpus analysis of texts: the texts of oral and written speech in the corpus collected independently will be analyzed, and the results of the sample in the NOW corpora (in English-corpora) and NCRL will be analyzed. Also, for the compilation of models, communication and conversion analyzes will be required.Results and discussion. As a result of the study, the article presents not only possible communication models that function in the discourse of sales in the field of digital goods (cell phones), as well as leading the greatest number of speech contacts to success, but also a universal algorithm for parsing chatbot communication in other discourses. In the course of the study, it was possible to obtain confirmation of the assumption of a significant difference between the English-language and Russian-language models of achieving speech success in chatbot communication.Conclusion. Preparation of a communication model updated from the point of view of a certain discourse and comparison of research data through the materials of two languages will help to identify similarities and differences for each area, and, among other things, will ensure an increase in the efficiency of the communication process built through chatbots in a business environment.

FINNCH: Cooperative Pursuit Navigation for a Pursuer Team to Capture a Single Evader in Urban Environments

The development of a cooperative pursuit strategy for capturing escaping criminals or dangerous animals in urban public safety emergencies is becoming increasingly in demand. An ideal strategy should consider both the encirclement needed to prevent criminals from evading and the distance that pursuers need to move. This article proposes a fine-grained navigation network-based cooperative hunting (FINNCH) method. A fine-grained navigation network is created to provide detailed information about the traversability in urban areas. Three interaction rules inspired by biological behaviors in nature are introduced to achieve dynamic cooperation between pursuers. An heuristic search strategy is used to guide the pursuers toward potentially good directions, which consequently reduces the search effort. Two spatial constraints, namely, the direction centrality constraint (DCC) and encirclement distance constraint (EDC), are then constructed to evenly distribute the pursuers around the evader. Several experiments are conducted to evaluate the effectiveness and efficiency of the proposed method. The results show that FINNCH can provide navigation for multiple pursuers in complex urban environments comprised of roads, meadows, trees, water, and buildings. These findings point to the promising future of FINNCH for practical applications.

Teoretyko-prykladni aspekty suchasnoho dilovoho etyketu turystychnykh orhanizatsii

The initial categories of business etiquette of travel companies such as «ethics», «morality», «morality», and «etiquette» are clarified. The content of the concept of ethics, which is interpreted as a system of knowledge about morality, good and evil, and their influence on human behaviour in relation to the world around us, is disclosed. The concept of morality is characterized, which is a system of ideas, norms, views, and rules of human behaviour based on the principles of good and evil. The classification of etiquette is considered. The author describes the most common types of etiquette, including court, military, diplomatic, secular, business, linguistic, and religious. Based on scientific works, the author analyses the definitions of the concept of «business etiquette». In particular, the following main interpretations of it are highlighted: the order of behaviour, rules of conduct, norms of interaction, and communication. The author's own definition of business etiquette of a tourism organization is formed. Business etiquette of a tourism organization is a clearly defined norm of behaviour of staff with clients, and business partners, as well as rules of interaction between employees of the company: managers and subordinates and equal specialists. Important spheres and forms of business etiquette of travel agencies are highlighted. These include the etiquette of national symbols; gifts in business relations; official and protocol forms of greeting and introduction; business cards; business attire; etiquette in advertising, correspondence, customer consultation; business subordination, etc. The emphasis is placed on business etiquette in tourism organizations. The subsystems of business etiquette are characterized: speech (verbal) etiquette, kinesics, etiquette proxemics, and etiquette attributes. The following functions of business etiquette of tourism organizations are allocated: regulatory, recognition, identification, communicative, aesthetic, and ethical. The principles of business etiquette, and rules for the success of tourism organizations are formed. Ways to improve the business etiquette of tourism organizations through the introduction of codes of ethics, «ethics cards», and ethical expertise are proposed. The emphasis is placed on the need to take into account the norms of the Global Code of Ethics for Tourism when developing corporate codes of ethics.

What impacts do green bonds have on carbon emissions and how? A dynamic spatial perspective in China.

Green bonds are adopted to exclusively finance or refinance green projects and thus is an important policy instrument for sustainable development. The development of these eco-friendly projects benefits the reduction of carbon emission. What impacts do green bonds have on carbon emission intensity and how? This issue needs to be revealed, including the dynamic spatial interactive rules and regional heterogeneity. This is especially true for China, with its vast territory and a short history of green bonds. Different with existing literature, this paper collects the data of the amount of green bond issued in each province in China rather than the policy dummy variable of green bond. The spatio-temporal interactions of both the impact of green bonds and the related mechanisms are studied. A dynamic spatial Durbin model (DSDM) combined with a STIRPAT (Stochastic Impacts by Regression on Population, Affluence and Technology) model reveals the negative impacts of green bonds on carbon emissions and the spatio-temporal interactions. On this basis, the mediation model is introduced to clarify the three impact mechanisms of green bonds and find the predominant role of technology mechanism. In addition, different characteristics in spatial interactive rules and impact mechanisms of green bonds are found in various regions of China. Finally, the study proposes some policy recommendations on how to effectively reduce carbon emissions with green bonds.

ChatGPT impacts in programming education: A recent literature overview that debates ChatGPT responses

This paper aims at a brief overview of the main impact of ChatGPT in the scientific field of programming and learning/education in computer science. It lists, covers and documents from the literature the major issues that have been identified for this topic, such as applications, advantages and limitations, ethical issues raised. Answers to the above questions were solicited from ChatGPT itself, the responses were collected, and then recent literature was surveyed to determine whether or not the responses are supported. The paper ends with a short discussion on what is expected to happen in the near future. A future that can be extremely promising if humanity manages to have AI as a proper ally and partner, with distinct roles and specific rules of cooperation and interaction.

Interaction rules guiding collective behaviour in echolocating bats

Interaction rules guiding collective behaviour in echolocating bats

Collective foraging of active particles trained by reinforcement learning

Collective self-organization of animal groups is a recurring phenomenon in nature which has attracted a lot of attention in natural and social sciences. To understand how collective motion can be achieved without the presence of an external control, social interactions have been considered which regulate the motion and orientation of neighbors relative to each other. Here, we want to understand the motivation and possible reasons behind the emergence of such interaction rules using an experimental model system of light-responsive active colloidal particles (APs). Via reinforcement learning (RL), the motion of particles is optimized regarding their foraging behavior in presence of randomly appearing food sources. Although RL maximizes the rewards of single APs, we observe the emergence of collective behaviors within the particle group. The advantage of such collective strategy in context of foraging is to compensate lack of local information which strongly increases the robustness of the resulting policy. Our results demonstrate that collective behavior may not only result on the optimization of behaviors on the group level but may also arise from maximizing the benefit of individuals. Apart from a better understanding of collective behaviors in natural systems, these results may also be useful in context of the design of autonomous robotic systems.

Ethnonational discourse of migrants in social networks on the example of Tajik and Kyrgyz virtual communities on VK

The use of Russian-language social networks by migrants from Tajikistan and Kyrgyzstan, primarily on VK, has increased significantly in recent years. This network has enabled easy communication both within and between ethnic communities. It has become a social space of ethno-national discourse with its own laws and rules of social interaction, including conflictogenic one. At the same time, publications on ethno-national discourse of Tajik and Kyrgyz migrants in social networks are practically absent in Russian scientific literature. In this regard, the authors have set a goal to identify the features of ethno-national discourse of Kyrgyz and Tajik migrants in the VK Russian-language social network during the conflict on the Kyrgyz-Tajik border. The empirical basis of the study was the results of online questionnaire survey of 400 migrant respondents from Tajikistan and Kyrgyzstan and qualitative analysis of their posts with a vivid news agenda about the relationship between the two countries. The peculiarities of ethno-national discourse of migrants in social networks between Tajik and Kyrgyz virtual groups consisted in an attempt to understand the ongoing conflict. As a rule, the discussion has come down to finding someone to blame or calling for the cessation of hostilities. The analysis has showed that hating had been actively developing in virtual interaction between migrants. At the same time, conciliatory actions on the part of both diasporas have been observed. The results have showed the need for constant monitoring of ethno-national discourse of Tajik and Kyrgyz migrants in social networks, as virtual interaction can very likely lead to real conflicts between representatives of Tajik and Kyrgyz diasporas in Russia.

International Order as a Category of International Studies: Theoretical Foundations

This article is devoted to the study of world order in modern political theory. The author shows that modern Anglo-American and Russian political science share common problems related to its study. First, modern internationalists often unjustifiably take the modern world order out of the context of historical development, contrasting it with the entire world history. Second, modern theories of world order are characterized by a high degree of normativity: political processes are assessed from moral and ethical or openly ideological (usually liberal) positions. Third, researchers today often exaggerate the originality, or uniqueness, of the modern world order, although many of its problems existed in the past. Also, in modern political literature the concepts of "order" and "system" are often confused. Moreover, the mechanism of change of world orders, their qualitative difference from each other, even their number and names have not been revealed. In this regard, the author focuses on two interrelated tasks: 1) to define the relationship between the terms "system" and "order of international relations"; 2) to designate the systemic characteristics of world orders, which will make it possible to identify their number, the mechanism of their change and their qualitative difference. The article aims at clarifying the terminology on the subject of world orders and suggests considering them as completed political systems, which have covered their development cycle – from inception to disintegration. The basic concept of the order is that of balance of power between the great powers and the values and rules of interaction established on its basis. The world order emerges as the result of a total war and is terminated by a total war. Some limited wars regulate relations within the world order. The two types of world orders, namely, the hegemonic order and the balance of power order, acted as two equal types of order. Their disintegration is due to objective reasons, namely, the change in the balance of power and degradation of legal norms, which leads to the emergence of extra-systemic revisionists. The author believes that today’s Yalta-Potsdam order is likely to follow the entire cycle of the development of its predecessors.

Multi-attribute group decision making method based on Pythagorean fuzzy Einstein interactive power averaging approach for sustainable cement industry

Pythagorean fuzzy numbers have been playing an essential role in decision-making problems. The existing operational rules (ORs) constructed based on Einstein t-norm and t-conorm operators in the Pythagorean fuzzy environment have some drawbacks. This type of t-norm and t-conorm operators need to consider the interaction between the membership degree and non-membership degree of Pythagorean fuzzy numbers and, consequently, produces some unreasonable results in some realistic decision-making problems. To eliminate such deficiencies, interactive operational rules have been formed, revising the existing operational rules. A new aggregation operator, namely, Pythagorean fuzzy Einstein interactive weighted averaging operator, has been presented in this article based on newly revised ORs, and some properties of this operator are discussed. At the same time to eliminate or reduce the effect of existing biases that occurred from the end of decision makers in the evaluation procedure of alternatives in multi-attribute group decision-making problem, we have presented the Pythagorean fuzzy Einstein interactive power weighted averaging operator. A novel multi-attribute group decision-making method for the best sustainable cement industry evaluation in India is presented based on Pythagorean fuzzy Einstein interactive power weighted averaging and Pythagorean fuzzy Einstein interactive weighted averaging operators. The validity of the method is tested by comparing some existing methods. At last, a comparative study with sensitivity analysis shows that the proposed method is superior to some considered existing methods.

Recovery of dynamical similarity from lossy representations of collective behavior of midge swarms.

Understanding emergent collective phenomena in biological systems is a complex challenge due to the high dimensionality of state variables and the inability to directly probe agent-based interaction rules. Therefore, if one wants to model a system for which the underpinnings of the collective process are unknown, common approaches such as using mathematical models to validate experimental data may be misguided. Even more so, if one lacks the ability to experimentally measure all the salient state variables that drive the collective phenomena, a modeling approach may not correctly capture the behavior. This problem motivates the need for model-free methods to characterize or classify observed behavior to glean biological insights for meaningful models. Furthermore, such methods must be robust to low dimensional or lossy data, which are often the only feasible measurements for large collectives. In this paper, we show that a model-free and unsupervised clustering of high dimensional swarming behavior in midges (Chironomus riparius), based on dynamical similarity, can be performed using only two-dimensional video data where the animals are not individually tracked. Moreover, the results of the classification are physically meaningful. This work demonstrates that low dimensional video data of collective motion experiments can be equivalently characterized, which has the potential for wide applications to data describing animal group motion acquired in both the laboratory and the field.

Capture and transport of rod-shaped cargo via programmable active particles

We study the influence of the cargo shape on the capture and transport process of colloidal rods via swarms of active particles using Brownian dynamics simulations. Starting at random initial conditions, active particles that interact via the Lennard-Jones potential and possess a tuneable speed are utilised to capture passive rods inside a hexagonal cage of individually addressable units. By adjusting the velocity of the individual active particles, the rod can then be transported. To guarantee a successful capture process (with a strong localisation), we find that specific geometric and energetic constraints have to be met; i.e., the length of the rod must approximately be in the vicinity of an odd multiple of the lattice constant of the hexagonal cage, and the Lennard-Jones interaction strength must be in the range of 3.0 , k_B T to 6.0 , k_B T. If the cargo aspect ratio gets too large, the subsequent transport of successfully captured rods can fail. For systems where transport is possible, an increase in the cargo aspect ratio decreases the achievable transport velocity. Our work shows that the particle shape must be considered while designing interaction rules to accomplish specific tasks via groups of controllable units.

An examination of force maps targeted at orientation interactions in moving groups.

Force mapping is an established method for inferring the underlying interaction rules thought to govern collective motion from trajectory data. Here we examine the ability of force maps to reconstruct interactions that govern individual's tendency to orient, or align, their heading within a moving group, one of the primary factors thought to drive collective motion, using data from three established general collective motion models. Specifically, our force maps extract how individuals adjust their direction of motion on average as a function of the distance to neighbours and relative alignment in heading with these neighbours, or in more detail as a function of the relative coordinates and relative headings of neighbours. We also examine the association between plots of local alignment and underlying alignment rules. We find that the simpler force maps that examined changes in heading as a function of neighbour distances and differences in heading can qualitatively reconstruct the form of orientation interactions, but also overestimate the spatial range over which these interactions apply. More complex force maps that examine heading changes as a function of the relative coordinates of neighbours (in two spatial dimensions), can also reveal underlying orientation interactions in some cases, but are relatively harder to interpret. Responses to neighbours in both the simpler and more complex force maps are affected by group-level patterns of motion. We also find a correlation between the sizes of regions of high alignment in local alignment plots and the size of the region over which alignment rules apply when only an alignment interaction rule is in action. However, when data derived from more complex models is analysed, the shapes of regions of high alignment are clearly influenced by emergent patterns of motion, and these regions of high alignment can appear even when there is no explicit direct mechanism that governs alignment.

Relative rate of expansion controls speed in one-dimensional pedestrian following.

Patterns of crowd behavior are believed to result from local interactions between pedestrians. Many studies have investigated the local rules of interaction, such as steering, avoiding, and alignment, but how pedestrians control their walking speed when following another remains unsettled. Most pedestrian models assume the physical speed and distance of others as input. The present study compares such "omniscient" models with "visual" models based on optical variables. We experimentally tested eight speed control models from the pedestrian- and car-following literature. Walking participants were asked to follow a leader (a moving pole) in a virtual environment, while the leader's speed was perturbed during the trial. In Experiment 1, the leader's initial distance was varied. Each model was fit to the data and compared. The results showed that visual models based on optical expansion (\(\dot{\theta }\)) had the smallest root mean square error in speed across conditions, whereas other models exhibited increased error at longer distances. In Experiment 2, the leader's size (pole diameter) was varied. A model based on the relative rate of expansion (\(\dot{\theta }/\theta \)) performed better than the expansion rate model (\(\dot{\theta }\)), because it is less sensitive to leader size. Together, the results imply that pedestrians directly control their walking speed in one-dimensional following using relative rate of expansion, rather than the distal speed and distance of the leader.

Influence Maximization in Multiagent Systems by a Graph Embedding Method: Dealing With Probabilistically Unstable Links.

This article is concerned with the influence maximization (IM) problem under a network with probabilistically unstable links (PULs) via graph embedding for multiagent systems (MASs). First, two diffusion models, the unstable-link independent cascade (UIC) model and the unstable-link linear threshold (ULT) model, are designed for the IM problem under the network with PULs. Second, the MAS model for the IM problem with PULs is established and a series of interaction rules among agents are built for the MAS model. Third, the similarity of the unstable structure of the nodes is defined and a novel graph embedding method, termed the unstable-similarity2vec (US2vec) approach, is proposed to tackle the IM problem under the network with PULs. According to the embedding results of the US2vec approach, the seed set is figured out by the developed algorithm. Finally, extensive experiments are conducted to: 1) verify the validity of the proposed model and the developed algorithms and 2) illustrate the optimal solution for IM under different scenarios with PULs.