Cooperative Behavior Research Articles

Personality traits in patients with multiple sclerosis: their association with nicotine dependence and polypharmacy.

The modifiable risk factor exerting the most substantial influence on the development and disease course of multiple sclerosis (MS) is cigarette smoking. Furthermore, smoking is associated with a higher risk of suffering from one or more comorbidities and potentially contributes to polypharmacy. We aimed to use personality tests to explore health-promoting and harmful patient characteristics. To investigate two important factors influencing the course of MS - the degree of smoking dependence and the status of polypharmacy - in association with personality traits. This is a bicentric, cross-sectional study. We collected sociodemographic, clinical and medical data from patients with MS (n = 375) at two German neurological clinics. The participants were asked to complete the NEO Five-Factor Inventory (NEO-FFI) and the Temperament and Character Inventory-Revised (TCI-R). Relationships between variables were examined using correlation analyses, and differences between groups were examined using linear models. Current smokers with MS were also asked to complete the Fagerström questionnaire to categorize them into patients with mild, moderate and severe smoking dependence. In our sample, 67.5% were women, and the mean age was 48.1 years. The patients had a median Expanded Disability Status Scale of 3.0 at a median disease duration of 10 years. Patients with MS with severe smoking dependence had on average a significantly higher neuroticism score in the NEO-FFI compared to those with mild or moderate smoking dependence. Patients with MS and polypharmacy had significantly higher neuroticism scores than those without. In the extraversion scale of the NEO-FFI, patients with MS and polypharmacy had significantly lower scores on average. Significant differences were also found when analysing the TCI-R in patients with MS and heavy smoking dependence, with higher scores for harm avoidance (HA) and lower scores for reward dependence, self-directedness (S-D) and cooperativeness (CO) in various subscales. Polypharmacy in patients with MS was associated with higher scores for HA and self-transcendence. Furthermore, patients with polypharmacy showed lower values than patients without polypharmacy in individual subscales of the dimensions of persistence, S-D and CO. Using the NEO-FFI, we were able to show that neuroticism is a detrimental trait and extraversion a protective trait in patients with MS in relation to nicotine dependence and polypharmacy. In addition, the evaluation of the TCI-R showed that high HA as well as low S-D and CO scores were more common in patients with MS and nicotine dependence or polypharmacy. With this knowledge, the risk of polypharmacy and smoking can be understood in the context of personality characteristics and targeted treatment and counselling can be provided.

Evaluation of Effectiveness of Three Different Behavioral Modification Techniques among 4–8-year-old Children

Abstract Background: Dental anxiety being attributed by many as a major cause to avoid seeking dental care by children, so several communicative, advanced, and pharmacological interventions have been developed to manage children’s anxious and cooperative behaviors. Aim: To evaluate the effectiveness of tell–show–do (TSD), tell–play–do (TPD), and ask–tell–ask (ATA) behavioral modification techniques among 4–8 years old coming for a restorative treatment. Materials and Methods: Thirty children aged 4–8 years were enrolled in the study and randomly allocated to three groups, 10 children in each group. Group A: Those to receive restorative treatment by the behavior modification technique (BMT) of TSD; Group B: Those to receive restorative treatment by BMT of TPD; and Group C: Those to receive restorative treatment by BMT of ATA. Evaluation: Each child’s heart rate was monitored before, during, and after the entire treatment with a pulse oximeter. The oximeter was clipped to the thumb of the child’s left hand. Furthermore, Frankel Behavioral Rating Scale was to be monitored before, during, and after the procedure. Results: TPD technique is more efficient than TSD and ATA to control 4–8-year-old children’s anxiety and achieve cooperative behavior during dental treatment. Conclusion: TPD is a technique worth practicing in pediatric dentistry. The dentist should consider the cognitive development of the patient to communicate effectively for developing sound rapport and trust. Each dental visit should be designed to receive proper behavioral guidance techniques such as TPD, TSD, and modeling; these can help the child to develop a positive attitude toward oral health.

The Effects of Social Responsibility and Different Dimensions of Psychological Distance on Cooperative Behavior

The Effects of Social Responsibility and Different Dimensions of Psychological Distance on Cooperative Behavior

Effect of Social Exclusion on Cooperative Behavior: The Chain Mediation Role of the Belongingness and the Meaning in Life

Effect of Social Exclusion on Cooperative Behavior: The Chain Mediation Role of the Belongingness and the Meaning in Life

A social science trust taxonomy with emergent vectors and symmetry.

Trust is foundational to all social science domains, but to date, there is no unifying theory or consistent measurement basis spanning the social sciences. This research hypothesized that trust forms the basis of an ontology that could unify the social science domains. The proposed ontology comprises a Cartesian plane with axes self-trust and other-trust. Self-trust manifests in dominant behaviors, and other-trust manifests in cooperative behaviors. Both axes are divided into five discrete categories, creating a matrix of 25 cells. All words in the lexicon are allocated into one of these 25 cells. This research started with an existing 14,000-word lexicon of dominance and affiliation. The lexicon was extended by manually identifying and including socially descriptive words with information regarding self-trust, other-trust, dominance, and cooperation. The taxonomy was optimized using the Gradient Descent machine learning algorithm and commercially curated synonyms and antonyms. The t-test was employed as the objective (or loss) function for Gradient Descent optimization. Word vectors were identified using groups of four words related as synonyms and antonyms. Over 30,000 words were identified and included in the lexicon. The optimization process yielded a t-score of over 1,000. Over 226,000 vectors were identified, such as malevolent-mean-gentle-benevolent. A new form of symmetry was identified between adjectives and verbs with a common root; for example, the words reject and rejected are horizontally reflected. The word vectors can create a metrologically compliant basis for psychometric testing. The symmetries provide insight into causes (verbs) and effects (adjectives) in social interactions. These vectors and symmetries offer the social sciences a basis of commonality with natural sciences, enabling unprecedented accuracy and precision in social science measurement.

‘I don’t want to play with you anymore’: dynamic partner judgements in moody reinforcement learners playing the prisoner’s dilemma

Abstract Emerging reinforcement learning algorithms that utilize human traits as part of their conceptual architecture have been demonstrated to encourage cooperation in social dilemmas when compared to their unaltered origins. In particular, the addition of a mood mechanism facilitates more cooperative behaviour in multi-agent iterated prisoner dilemma (IPD) games, for both static and dynamic network contexts. Mood-altered agents also exhibit humanlike behavioural trends when environmental aspects of the dilemma are altered, such as the structure of the payoff matrix used. It is possible that other environmental effects from both human and agent-based research will interact with moody structures in previously unstudied ways. As the literature on these interactions is currently small, we seek to expand on previous research by introducing two more environmental dimensions; voluntary interaction in dynamic networks, and stability of interaction through varied network restructuring. From an initial Erdos–Renyi random network, we manipulate the structure of a network IPD according to existing methodology in human-based research, to investigate possible replication of their findings. We also facilitated strategic selection of opponents through the introduction of two partner evaluation mechanisms and tested two selection thresholds for each. We found that even minimally strategic play termination in dynamic networks is enough to enhance cooperation above a static level, though the thresholds for these strategic decisions are critical to desired outcomes. More forgiving thresholds lead to better maintenance of cooperation between kinder strategies than stricter ones, despite overall cooperation levels being relatively low. Additionally, moody reinforcement learning combined with certain play termination decision strategies can mimic trends in human cooperation affected by structural changes to the IPD played on dynamic networks—as can kind and simplistic strategies such as Tit-For-Tat. Implications of this in comparison with human data is discussed, and suggestions for diversification of further testing are made.

Simulation-Aided Handover Prediction From Video Using Recurrent Image-to-Motion Networks.

Recent advances in deep neural networks have opened up new possibilities for visuomotor robot learning. In the context of human-robot or robot-robot collaboration, such networks can be trained to predict future poses and this information can be used to improve the dynamics of cooperative tasks. This is important, both in terms of realizing various cooperative behaviors, and for ensuring safety. In this article, we propose a recurrent neural architecture, capable of transforming variable-length input motion videos into a set of parameters describing a robot trajectory, where predictions can be made after receiving only a few frames. A simulation environment is utilized to expand the training database and to improve generalization capability of the network. The resulting architecture demonstrates good accuracy when predicting handover trajectories, with models trained on synthetic and real data showing better performance than when trained on real or simulated data only. The computed trajectories enable the execution of handover tasks with uncalibrated robots, which was verified in an experiment with two real robots.

Cooperation with dynamic asymmetric evaluation in complex networks from a risk perspective.

The choice of strategy exposes individuals to the risk of betrayal. This induces individuals' irrational tendencies in strategy selection, which further influences the emergence of cooperative behavior. However, the underlying mechanisms connecting risk perception and the emergence of cooperation are still not fully understood. To address this, the classic evolutionary game model on complex networks is extended. We depict the interaction between strategy imitation and payoff evaluation from two perspectives: dynamic adjustment and irrational assessment. Specifically, the probability distortion involved in the dynamic selection of imitative reference points, as well as the asymmetric psychological utility associated with reference point dependence, is emphasized. Monte Carlo simulations demonstrate that individual irrational cognition induced by the risk of strategy selection can promote the emergence of cooperative behavior. Among them, the risk sensitivity within psychological utility has the most significant moderating effect. Moreover, the promoting effect of strong heterogeneity and high clustering in the network topology on cooperation under risk scenarios has been clarified. Additionally, the influence of initial states on the emergence of cooperation follows a step-like pattern. This research offers valuable insights for further exploring the cooperation mechanisms among irrational agents, even in scenarios involving the regulation of group cooperation behavior in risky situations.

The impact of interpersonal synchronization on autistic children's cooperative behavior and its intervention promotion

The impact of interpersonal synchronization on autistic children's cooperative behavior and its intervention promotion

Better-than-chance prediction of cooperative behaviour from first and second impressions.

Could cooperation among strangers be facilitated by adaptations that use sparse information to accurately predict cooperative behaviour? We hypothesise that predictions are influenced by beliefs, descriptions, appearance and behavioural history available for first and second impressions. We also hypothesise that predictions improve when more information is available. We conducted a two-part study. First, we recorded thin-slice videos of university students just before their choices in a repeated Prisoner's Dilemma with matched partners. Second, a worldwide sample of raters evaluated each player using videos, photos, only gender labels or neither images nor labels. Raters guessed players' first-round Prisoner's Dilemma choices and then their second-round choices after reviewing first-round behavioural histories. Our design allows us to investigate incremental effects of gender, appearance and behavioural history gleaned during first and second impressions. Predictions become more accurate and better-than-chance when gender, appearance or behavioural history is added. However, these effects are not incrementally cumulative. Predictions from treatments showing player appearance were no more accurate than those from treatments revealing gender labels and predictions from videos were no more accurate than those from photos. These results demonstrate how people accurately predict cooperation under sparse information conditions, helping explain why conditional cooperation is common among strangers.

Coordination of oscillators driven by non-identical van der Pol excitation interacting via Huygens’ coupling

It is well-known that coupled oscillators may exhibit different types of collective behavior, like for example full synchronization, coordinated motion, cooperative behavior, among others. This is indeed the topic addressed in this paper. In particular, we briefly report on a special coordinated motion observed in a triplet of mechanical oscillators with Huygens’ coupling: two oscillators achieve complete synchronization between them but they oscillate in anti-phase and with different amplitude with respect to the third oscillator. Each oscillator is equipped with a van der Pol term, in order to have self-sustained oscillations and furthermore, it is assumed that all the parameters of the oscillators are identical except for the parameter of the van der Pol term, which is different for one of the oscillators, ultimately resulting in oscillations with different amplitudes. Then, by using a transformation, the model of the system is reduced and the resulting model is analyzed using the Poincaré method of perturbation. It is analytically demonstrated that the coordinated motion above described exists and is asymptotically stable provided that the parameter discrepancy between the oscillators satisfies an specific condition. These results are further illustrated by numerical simulations and are experimentally validated.

Service innovation and coopetitive dynamics: the case of insurance distribution

Coopetition is a complex dynamic in which competing companies cooperate to achieve a common goal. The relationships between these organizations are not linear, and have an impact on their various activities and processes, particularly innovation. Drawing on the theoretical fields of service innovation and coopetition, this unique-case study, based on a 2-year observant participation and semi-directive interviews, highlights the difficulties raised by this informal coopetition. Our findings characterize the areas of cooperation and competition between the general agent and the insurance company. They also highlight an impact on the processes and deliverables of innovation projects, which do not enable the players to reap the full benefits of coopetition. As a result, forms of service innovation constituting a competitive advantage exacerbate competitive behavior, while forms of organizational innovation benefit from cooperative behavior. Highlighting these specificities contributes to a better understanding of coopetitive dynamics between actors in service innovation, and underlines the need to formalize them in a rapidly transforming sector where innovation meets high stakes.

The role of the fear, hunting cooperation, and anti-predator behavior in the prey predator model having disease in predator

The role of the fear, hunting cooperation, and anti-predator behavior in the prey predator model having disease in predator

Adaptability and Strategy of Ant Society: Analysis of Cooperation and Defense Behavior

Adaptability and Strategy of Ant Society: Analysis of Cooperation and Defense Behavior

Lessons from recent theoretical treatments of Al-M bonds (M = Fe, Cu, Ag, Au) that capture CO2.

Complexes with Al-M bonds (M = transition metal) have emerged as platforms for discovering new reaction chemistry either through cooperative bond activation behaviour of the heterobinuclear unit or by modifying the properties of the M site through its interaction with the Al centre. Therefore, elucidating the nature of Al-M bonding is critical to advancing this research area and typically involves careful theoretical modelling. This Frontier article reviews selected recent case studies that included theoretical treatments of Al-M bonds, specifically highlighting complexes capable of cooperative CO2 activation and focusing on extracting lessons particular to the Al-M sub-field that will inform future studies with theoretical/computational components.

Improving the Security of Internet of Things (IoT) Applications Based on a New Machine Learning Technique

The Internet of Things, or IoT, is changing practically every aspect of modern life and entering both the business and residential domains. The proliferation of IoT has led to a rise in the frequency of cyber catastrophes. Attackers are using new methods or changing old ones, making the danger more sophisticated. The threat landscape that security professionals face is dynamic, complex, and diversified. This paper proposes a novel approach to enhance Internet of Things applications by fusing the swarm intelligence of Salp Swarm Algorithms (SSA) with the predictive power of Random Forest (RF) and Decision Tree (DT) models. Salp Swarm Algorithms simulate the cooperative behavior of salps in the natural world, wherein individual agents coordinate their actions to achieve common goals. This work uses SSA to optimize the Random Forest and Decision Tree model training process in an IoT context. SSA's collaborative nature makes it easier to explore the solution space effectively, which enhances the models' ability to capture the complex correlations found in IoT data. The effectiveness of the model is evaluated. We were able to attain a maximum accuracy of 95.54% for the Decision Tree of the OT-MQTT dataset and 96.19% for the random forest.

Alice or Bob?: Process polymorphism in choreographies

Abstract We present PolyChor $\lambda$ , a language for higher-order functional choreographic programming—an emerging paradigm for concurrent programming. In choreographic programming, programmers write the desired cooperative behaviour of a system of processes and then compile it into an implementation for each process, a translation called endpoint projection. Unlike its predecessor, Chor $\lambda$ , PolyChor $\lambda$ has both type and process polymorphism inspired by System F $_\omega$ . That is, PolyChor $\lambda$ is the first (higher-order) functional choreographic language which gives programmers the ability to write generic choreographies and determine the participants at runtime. This novel combination of features also allows PolyChor $\lambda$ processes to communicate distributed values, leading to a new and intuitive way to write delegation. While some of the functional features of PolyChor $\lambda$ give it a weaker correspondence between the semantics of choreographies and their endpoint-projected concurrent systems than some other choreographic languages, we still get the hallmark end result of choreographic programming: projected programmes are deadlock-free by design.

The Influence of Context Factors on Cooperation in IS Integration Projects for Horizontal Mergers

IS integration projects for horizontal mergers of large organizations have received scant attention from IS researchers. This study addresses this shortcoming by collecting and analyzing Technology and Social integration process data during the integration planning and implementation phases of a multi-year IS integration project for the horizontal merger of two large competitors. Using a power-dependence perspective to interpret our findings, we develop a mid-range propositional theory to explain how and why organization-level context factors influenced the cooperative behaviors of legacy employees participating in horizontal mergers and the success of IS integration processes.

High-order layered self-assembled multicavity metal--organic capsules and anti-cooperative host-multi-guest chemistry.

The construction and application of metal-organic cages with accessible internal cavities have witnessed rapid development, however, the precise synthesis of complex metal-organic capsules with multiple cavities and achievement of multi-guest encapsulation, and further in-depth comprehension of host-multi-guest recognition remain a great challenge. Just like building LEGO blocks, herein, we have constructed a series of high-order layered metal-organic architectures of generation n (n = 1/2/3/4 is also the number of cavities) by multi-component coordination-driven self-assembly using porphyrin-containing tetrapodal ligands (like plates), multiple parallel-podal ligands (like clamps) and metal ions (like nodes). Importantly, these high-order assembled structures possessed different numbers of rigid and separate cavities formed by overlapped porphyrin planes with specific gaps. The host-guest experiments and convincing characterization proved that these capsules G2-G4 could serve as host structures to achieve multi-guest recognition and unprecedentedly encapsulate up to four C60 molecules. More interestingly, these capsules revealed negative cooperation behavior in the process of multi-guest recognition, which provides a new platform to further study complicated host-multi-guest interaction in the field of supramolecular chemistry.

Ester hydrogenolysis via β-C-O bond cleavage catalysed by a phenanthroline-based PNNP-cobalt(I) complex.

A Co(I) catalyst bearing a phenanthroline-based PNNP ligand (2,9-bis((diphenylphosphanyl)methyl)-1,10-phenanthroline) exhibits long-range metal ligand cooperation behavior using a ligand backbone as a hydrogen reservoir and catalyses hydrogenolysis of benzyl benzoate derivatives via β-C-O cleavage with atmospheric pressure H2.