Ninety-four percent were male, 89.2% were ages 18-44 years. Seventy-nine percent had >1 year of grappling experience and 30% had >5 years. Of the 4307, 1443 (33.5%) reported being choked >500 times, 3257 (75.7%) have been choked to near-syncope, and 1198 (27.8%) have been choked unconscious. Two of the 4307 (0.05%) reported ongoing symptoms from chokes. Of the respondents, 94.3% felt applying a choke would be a safe and effective way to control a street fight; 83.6% felt that vascular neck restraint, the police combative equivalent of sportive choking, would be appropriate as an alternative escalation of force option.Conclusion Based on a convenience sample of 4307 respondents’ self-reported data, sportive choking appears to be safe. Only 0.05% experienced ongoing symptoms, which were likely not related to brain ischemia.Background Oral isotretinoin and intralesional immunotherapy by Candida antigen have shown promising efficacy and safety for the treatment of plane warts in a few studies.Objective To evaluate the efficacy and safety of a combination of oral isotretinoin and Candida antigen versus either agent alone in the treatment of multiple plane warts.Methods The study included 108 patients who were randomly assigned to three groups, 36 in each. Group 1 received oral isotretinoin alone at a dose of 0.3 mg/kg/day. Group 2 received intralesional injection of Candida antigen alone at a dose of 0.1 ml of 1/1000 solution into the largest wart. Group 3 received a combination of Candida antigen and oral isotretinoin by the same method and dose mentioned above.Results Complete clearance of warts was observed in 44.4% of the oral isotretinoin alone group, in 55.6% of the Candida antigen alone group, and in 38.8% of the combination therapy group. A statistically significant difference in favor of the Candida antigen alone group was demonstrated.Conclusions Candida antigen, oral isotretinoin and a combination of both represent potential effective and safe modalities for the treatment of plane warts, with the Candida antigen alone as the most effective.We introduce MetaChem, a language for representing and implementing artificial chemistries. We motivate the need for modularization and standardization in representation of artificial chemistries. We describe a mathematical formalism for Static Graph MetaChem, a static-graph-based system. MetaChem supports different levels of description, and has a formal description; we illustrate these using StringCatChem, a toy artificial chemistry. We describe two existing artificial chemistries-Jordan Algebra AChem and Swarm Chemistries-in MetaChem, and demonstrate how they can be combined in several different configurations by using a MetaChem environmental link. MetaChem provides a route to standardization, reuse, and composition of artificial chemistries and their tools.In May 2019, a workshop on principled development of future agent-based simulations was held at Keele University. Participants spanned companies and academia, and a range of domains of interest, as well as participant career stages. This report summarizes the discussions and main outcomes from this workshop.A swarm robotic system is a system in which multiple robots cooperate to fulfill a macroscopic function. Many swarm robots have been developed for various purposes. This study aims to design swarm robots capable of executing spatially distributed tasks effectively, which can be potentially used for tasks such as search-and-rescue operation and gathering scattered garbage in rooms. this website We propose a simple decentralized control scheme for swarm robots by extending our previously proposed non-reciprocal-interaction-based model. Each robot has an internal state, called its workload. Each robot first moves randomly to find a task, and when it does, its workload increases, and then it attracts its neighboring robots to ask for their help. We demonstrate, via simulations, that the proposed control scheme enables the robots to effectively execute multiple tasks in parallel under various environments. Fault tolerance of the proposed system is also demonstrated.Among the major unresolved questions in ecosystem evolution are whether coevolving multispecies communities are dominated more by biotic or by abiotic factors, and whether evolutionary stasis affects performance as well as ecological profile; these issues remain difficult to address experimentally. Digital evolution, a computer-based instantiation of Darwinian evolution in which short self-replicating computer programs compete, mutate, and evolve, is an excellent platform for investigating such topics in a rigorous experimental manner. We evolved model communities with ecological interdependence among community members, which were subjected to two principal types of mass extinction a pulse extinction that killed randomly, and a selective press extinction involving an alteration of the abiotic environment to which the communities had to adapt. These treatments were applied at two different strengths (strong and weak), along with unperturbed control experiments. We performed several kinds of competition experimm strong treatment communities often had little or no effect on resident performance. While we detected periods of time when the fitness of a particular evolving ecotype remained static, this stasis was not permanent and never affected an entire community at once. Our results lend support to the fitness-deterioration interpretation of the Red Queen hypothesis, and highlight community context dependence in determining fitness, the shaping of communities by both biotic factors and abiotic forcing, and the illusory nature of evolutionary stasis. Our results also demonstrate the potential of digital evolution studies to illuminate many aspects of evolution in interacting multispecies communities.Children’s acquisition of the English past tense has been widely studied as a testing ground for theories of language development, mostly because it comprises a set of quasi-regular mappings. English verbs are of two types regular verbs, which form their past tense based on a productive rule, and irregular verbs, which form their past tenses through exceptions to that rule. Although many connectionist models exist for capturing language development, few consider individual differences. In this article, we explore the use of populations of artificial neural networks (ANNs) that evolve according to behavioral genetics principles in order to create computational models capable of capturing the population variability exhibited by children in acquiring English past tense verbs. Literature in the field of behavioral genetics views variability in children’s learning in terms of genetic and environmental influences. In our model, the effects of genetic influences are simulated through variations in parameters controlling computational properties of ANNs, and the effects of environmental influences are simulated via a filter applied to the training set.