Statistical physics of human beings in games:Controlled experiments

It is important to know whether the laws or phenomena in statistical physics for natural systems with non-adaptive agents still hold for social human systems with adaptive agents, because this implies whether it is possible to study or understand social human systems by using statistical physics originating from natural systems. For this purpose, we review the role of human adaptability in four kinds of specific human behaviors, namely, normal behavior, herd behavior, contrarian behavior, and hedge behavior. The approach is based on controlled experiments in the framework of market-directed resource-allocation games. The role of the controlled experiments could be at least two-fold： adopting the real human decision-making process so that the system under consideration could reflect the performance of genuine human beings; making it possible to obtain macroscopic physical properties of a human system by tuning a particular factor of the system, thus directly revealing cause and effect. As a result, both computer simulations and theoretical analyses help to show a few counterparts of some laws or phenomena in statistical physics for social human systems： two-phase phenomena or phase transitions, entropy-related phenomena, and a non-equilibrium steady state. This review highlights the role of human adaptability in these counterparts, and makes it possible to study or understand some particular social human systems by means of statistical physics coming from natural systems.

STUDY ON USING SERIAL PIPE TO IMPROVE THE DYNAMIC RESPONSE OF ELECTRO－HYDRAULIC SPEED CONTROL SYSTEM

The mathematical models of electro-hydraulic speed control system using series of pipesis presented. The principle of pipe effection on dynamics of the system is developed. Computersimulation and physical experiment are also carried out. The experimental results show that a rightchoosing of serial pipe for electro-hydraulic system enables the dynamic response of the system tobe improved effectively.

Covariate balancing based on kernel density estimates for controlled experiments

Controlled experiments are widely used in many applications to investigate the causal relationship between input factors and experimental outcomes.A completely randomised design is usually used to randomly assign treatment levels to experimental units.When covariates of the experimental units are available,the experimental design should achieve covariate balancing among the treatment groups,such that the statistical inference of the treatment effects is not confounded with any possible effects of covariates.However,covariate imbalance often exists,because the experiment is carried out based on a single realisation of the complete randomisation.It is more likely to occur and worsen when the size of the experimental units is small or moderate.In this paper,we introduce a new covariate balancing criterion,which measures the differences between kernel density estimates of the covariates of treatment groups.To achieve covariate balance before the treatments are randomly assigned,we partition the experimental units by minimising the criterion,then randomly assign the treatment levels to the partitioned groups.Through numerical examples,weshow that the proposed partition approach can improve the accuracy of the difference-in-mean estimator and outperforms the complete randomisation and rerandomisation approaches.

A numerical experiment for the simulating effects of Kuwait oil fire and volcanoes in Philippines and Japan on the general circulation and climate

With an AGCM/ mixed-layer ocean model, a numerical experiment to investigate the ef-fects of Kuwait oil fire and volcanoes in Philippines and Japan on atmospheric general cireulationand climate is camed out. It is shown from the simulation that the effect of smoke on climate issignificant near the smoke sources, and quite weak-and-indirect in the distant areas. In the experi-ment, it is not found that the smoke had a significant effect on SST anomialy along the tropicaloceans and flood in Yangtze-Huaihe river's basin of China in the spring and summer of 1991.

Comparative Analysis of Steel Plates and PLA Used for Joint Repair in Humans and Canines

The exploration of fracture internal fixation materials has been one of the research hotspots in the field of biomedical materials.The traditional internal fixation material for fracture is metal fixation.Although its mechanical strength is very large,it can not be degraded and absorbed in human body after implantation of human body or canine joint,which requires a secondary operation to remove,which not only brings pain to patients,but also causes economic pay.[1]Therefore,the development of a biodegradable fracture internal fixation material has become the goal of many researchers.Polylactic acid(PLA)is nontoxic and harmless,has good biocompatibility and strong mechanical properties.It can be degraded in vivo after implantation.The degradation products are CO2 and H2O.[2]For the study of the feasibility of polylactic acid as a substitute for common fracture fixation materials,18 northern Chinese pastoral dogs were randomly divided into blank group,PLA group and plate group.The data were recorded according to the Wakitani score from the first week to the fifteenth week after operation.First,all the indexes were divided into two categories by principal component analysis[3],then the blank group,steel plate group and PLA group were fitted and compared.Finally,it is concluded that PLA is more beneficial to joint repair than steel plate.

Recent progress in econophysics： Chaos, leverage, and business cycles as revealed by agent-based modeling and human experiments

Agent-based modeling and controlled human experiments serve as two fundamental research methods in the field of econophysics. Agent-based modeling has been in development for over 20 years, but how to design virtual agents with high levels of human-like ＂intelligence＂ remains a challenge. On the other hand, experimental econophysics is an emerging field; however, there is a lack of experience and paradigms related to the field. Here, we review some of the most recent research results obtained through the use of these two methods concerning financial problems such as chaos, leverage, and business cycles. We also review the principles behind assessments of agents＇ intelligence levels, and some relevant designs for human experiments. The main theme of this review is to show that by combining theory, agent-based modeling, and controlled human experiments, one can garner more reliable and credible results on account of a better verification of theory; accordingly, this way, a wider range of economic and financial problems and phenomena can be studied.