The evolution of cooperation by social exclusion

The exclusion of freeriders from common privileges or public acceptance is widely found in the real world. Current models on the evolution of cooperation with incentives mostly assume peer sanctioning, whereby a punisher imposes penalties on freeriders at a cost to itself. It is well known that such costly punishment has two substantial difficulties. First, a rare punishing cooperator barely subverts the asocial society of freeriders, and second, natural selection often eliminates punishing cooperators in the presence of non-punishing cooperators (namely, "second-order" freeriders). We present a game-theoretical model of social exclusion in which a punishing cooperator can exclude freeriders from benefit sharing. We show that such social exclusion can overcome the above-mentioned difficulties even if it is costly and stochastic. The results do not require a genetic relationship, repeated interaction, reputation, or group selection. Instead, only a limited number of freeriders are required to prevent the second-order freeriders from eroding the social immune system.Comment: 28 pages, 3 figures, supplementary material (materials and methods, and 6 supplementary figures

Numerical study on mixing of sprayed liquid in an LNG storage tank

This paper presents a numerical method to simulate the mixing of heavier LNG sprayed on lighter layer. Numerical results for evolutions of flow field and density field are obtained in a rectangular computational domain which includes the vicinity of the liquid surface. At the surface boundary, uniform distributions of the fluid velocity and the density are assumed. Detail structure of flow caused by impingements of liquid drops are neglected. But, to trigger a realistic motion, a series of random numbers is employed. It is used as an initial distribution of the density near the surface. This method successfully gives a realistic simulation of the mixing process. Numerical results for mixing velocity shows good agreement with experimental data

Evolution of sanctioning systems and opting out of games of life

In explaining altruistic cooperation and punishment, the challenging riddle is how transcendental rules can emerge within the empirical world. Recent game-theoretical studies show that pool punishment, in particular second-order punishment, plays a key role in understanding the evolution of cooperation. Second-order pool punishment, however, is tautological in nature: the punishment system itself is caused by its own effects. The emergence of pool punishment poses a logical conundrum that to date has been overlooked in the study of the evolution of social norms and institutions. Here we tackle the issue by considering the interplay of (a) cognitive biases in reasoning and (b) Agamben's notion of homo sacer (Agamben, G. 1998. Homo Sacer: Sovereign Power and Bare Life. Stanford Univ. Press), that is, a person who may be killed without legal consequence. Based on cognitive disposition of reversing the cause-and-effect relationship, then we propose a new system: preemptive punishment of homo sacers. This action can lead to retrospectively forming moral assessment in particular for second-order pool punishment.Comment: 6 pages, 1 figur

Factor analysis of Japanese version of the Obsessional-Compulsive lnventory

The 30-items Maudsley Obsessional-Compulsive Inventory (MOCI) was developed as an instrument for assessing the existence and extend of different obsessional-compulsive complaints by Hodgson & Rachman (1977). MOCI is composed of two major types of complaint, checking and cleaning compulsions, and two minor types, slowness and doubting. Rachman & Hodgson (1980) considered the complaints of checking and cleaning as the representative coping behaviors of prevention and provocation. These types of coping behavior could be observed in daily stressful situation. This study was to explore the Japanese version of MOCI available to evaluate the degree of obsessional-compulsive tendency observed in non-clinical persons. The Japanese version of MOCI was administered to 600 normal students to re-investigate the factor structure of this scale. Principal factor analysis and varimax rotation were adopted to extract the significant factors from 30×30 correlation matrix. Three factors, checking, cleaning and doubting-ruminating were extracted independently, but the complaint of slowness was not found as a significant factor. Additively to explore in their correlations with obsessional-complsive complaints, trait anxiety and time anxiety, MOCI, STAI-T form and TAS were administered to 213 normal students. TAS is composed of three subscales, namely, time confusion, time irritation and time submissiveness. The results were as follows. (1) Checking, cleaning and doubting were positively correlated with trait anxiety, but slowness was negatively correlated. (2) All obsessional-compulsive complaints but slowness were positively correlated with time confusion. Slowness and cleaning were positively correlated with time irritation, and negatively correlated with time submissiveness. These results indicate that slowness and cleaning complaints are somewhat different from other obsessional-compulsive complaints

Zero- and Few-shot Sound Event Localization and Detection

Sound event localization and detection (SELD) systems estimate direction-of-arrival (DOA) and temporal activation for sets of target classes. Neural network (NN)-based SELD systems have performed well in various sets of target classes, but they only output the DOA and temporal activation of preset classes that are trained before inference. To customize target classes after training, we tackle zero- and few-shot SELD tasks, in which we set new classes with a text sample or a few audio samples. While zero-shot sound classification tasks are achievable by embedding from contrastive language-audio pretraining (CLAP), zero-shot SELD tasks require assigning an activity and a DOA to each embedding, especially in overlapping cases. To tackle the assignment problem in overlapping cases, we propose an embed-ACCDOA model, which is trained to output track-wise CLAP embedding and corresponding activity-coupled Cartesian direction-of-arrival (ACCDOA). In our experimental evaluations on zero- and few-shot SELD tasks, the embed-ACCDOA model showed a better location-dependent scores than a straightforward combination of the CLAP audio encoder and a DOA estimation model. Moreover, the proposed combination of the embed-ACCDOA model and CLAP audio encoder with zero- or few-shot samples performed comparably to an official baseline system trained with complete train data in an evaluation dataset.Comment: 5 pages, 4 figure