Evolutionary Prisoner＇s Dilemma Game Based on Division of Work

We propose a new two-type-player prisoner＇s dilemma game based on the division of work on a square lattice, in which a fraction of the population μ are assigned type A and the rest B. In a one-shot two-player game, we let both of their original payoffs be scaled by a same multiplicative factor α 〉 1, if two neighboring players are of different types; however we leave the payoffs unchanged if they are of the same type. Then we show that combined with the two-type setup, the square lattice can assist to induce different social ranks according to players＇ abilities to collect payoffs. Simulation results show that the density of cooperation is significantly promoted for a wide range of the temptation to defection parameters and that there are optimal values for both α and μ leading to the maximal cooperation level. We reach these results by analyzing the distribution of the players in the social ranks and we also show some typical snapshots of the system.

Active Mixing in a Microchannel

We investigate a minute magneto hydro-dynamic mixer with relatively rapid mixing enhancement experimentally and analytically. The mixer is fabricated with brass and polymethyl methacrylate （PMMA） layers. A secondary flow is generated by using the Lorentz force in the fluids. The efficiency of mixing is greatly improved due to the large increase of the contact area between two mixing fluids. The micro particle image velocimetry technique is employed to measure the fluid flow characteristics in the micro-channel. Numerical simulation is performed based on the theoretical model of the computational fluid dynamics and the electromagnetic field theory. The experimental results are in good agreement with the numerical results, which indicates that the mixing area is enlarged by the driving of Lorentz force and the mixing can be enhanced.

From Symbols to Embeddings:A Tale of Two Representations in Computational Social Science

Computational Social Science(CSS),aiming at utilizing computational methods to address social science problems,is a recent emerging and fast-developing field.The study of CSS is data-driven and significantly benefits from the availability of online user-generated contents and social networks,which contain rich text and network data for investigation.However,these large-scale and multi-modal data also present researchers with a great challenge:how to represent data effectively to mine the meanings we want in CSS?To explore the answer,we give a thorough review of data representations in CSS for both text and network.Specifically,we summarize existing representations into two schemes,namely symbol-based and embeddingbased representations,and introduce a series of typical methods for each scheme.Afterwards,we present the applications of the above representations based on the investigation of more than 400 research articles from 6 top venues involved with CSS.From the statistics of these applications,we unearth the strength of each kind of representations and discover the tendency that embedding-based representations are emerging and obtaining increasing attention over the last decade.Finally,we discuss several key challenges and open issues for future directions.This survey aims to provide a deeper understanding and more advisable applications of data representations for CSS researchers.

Disaster Management Systems——A Placeholder for Decision Support Sub-Systems

Aspects of techniques for understanding and developing a system which is useful in the context of Disaster Management are outlined in the paper. The emphasis is on techniques for the development of requirements and software - specifically here for the basic, underlying computing system whose application packages (amongst others: Decision Support Sub-Systems) shall support Disaster Prediction, Relief (Damage Assessment & Mitigation) and Recovery. Throughout the body of the paper we shall be making frequent references to Decision Support Sub-Systems. As acronym for the subject domain the author has chosen: DiMaCS: Disaster Management Computing Systems.

Object-Oriented Design for FDTD Visual Scientific Computing

A scheme for general purposed FDTD visual scientific computing software is introduced in this paper using object-oriented design (OOD) method. By abstracting the parameters of FDTD grids to an individual class and separating from the iteration procedure, the visual software can be adapted to more comprehensive computing problems. Real-time gray degree graphic and wave curve of the results can be achieved using DirectX technique. The special difference equation and data structure in dispersive medium are considered, and the peculiarity of parameters in perfectly matched layer are also discussed.

Robustness of Cooperation on Highly Clustered Scale-Free Networks

We study the effect of mutation on the evolutionary prisoner＇s dilemma in highly clustered scale-free networks. It is found that cooperation is more sensitive and vulnerable to strategy mutation in more highly clustered networks. For small mutation rates, high clustering coefficient promotes cooperation. For medium mutation rates, high clustering coefficient inhibits the emergence of cooperation. For large mutation rates, cooperation is insensitive to clustering property. We provide explanations for the effects of clustering on cooperation with varied mutation rates.

Prisoner＇s Dilemma on Co-Evolving Networks without Strategy Update

We investigate the game theory in a structured population with the assumption that the evolution of network structure is far faster than that of strategy update. We find that the degree distribution for the finM network consists of two distinct parts： the low degree part which is contributed to by defectors and a broadband in the regime with high degree which is formed by cooperators. The structure of the final network and the final strategy pattern have also been numerically proved to be independent of the game parameters.

Call for Papers Special Issue of Tsinghua Science and Technology on Bioinformatics and Computational Biology

Tsinghua Science and Technology was started publication in 1996. It is an international academic journal sponsored by Tsinghua University and is published bimonthly. This journal aims at presenting the up-to-date scientific achievements in computer science, electronic engineering, and other IT fields. It is indexed by Ei and other abstracting indexes. From 2012the journal enters into IEEE Xplore Digital Library.

Call for Papers Special Issue of Tsinghua Science and Technology on Cloud Computing and Big Data

The publication of Tsinghua Science and Technology was started in 1996. Since then, it has been an international academic journal sponsored by Tsinghua University and published bimonthly. This journal aims at presenting the state-of-art scientific achievements in computer science and other IT fields. One paper on Cloud Computing published in Vol. 18, Issue. 1, 2013, has been ranked the top of IEEE download list continuously for five months：

Call for Papers Special Issue of Tsinghua Science and Technology on Cloud Computing and Big Data

The publication of Tsinghua Science and Technology was started in 1996. Since then, it has been an international academic journal sponsored by Tsinghua University and published bimonthly. This journal aims at presenting the state-of-art scientific achievements in computer science and other IT fields. One paper on Cloud Computing published in Vol. 18, Issue 1, 2013, has been ranked No. 1 of IEEE download list continuously for five months： http：//ieeexplore.ieee.org/xpl/browsePopular.jsp？topArticlesDate=August＋2013.

Special Section of Tsinghua Science and Technology on Wireless Computing and Networking

The publication of Tsinghua Science and Technology was started in 1996. Since then, it has been an international academic journal sponsored by Tsinghua University and published bimonthly. This journal aims at presenting the state-of-art scientific achievements in computer science, and other IT fields, and is currently indexed by Ei and other abstracting indices. From year 2013, the journal will be available for open access through IEEE Xplore Digital Library. This year＇s special section on Wireless Computing and Networking of Tsinghua Science and Technology is devoted to gather and present new research that address the challenges in the broad areas of Wireless Networks, Sensor Networks, Wireless Computing and Communication. While Wireless Networks have great potential to provide heterogeneous access and services for ubiquitous users, the demanding communication environment of wireless networks imposes challenges to many interesting research topics, such as channel estimation, communication protocol design, resource management, system design and so on. In Wireless Network research, it is unavoidable to wrestle unique problems such as non-uniform spectrum allocation, various radio resource management policies, economic concerns, the scarcity of radio resources, and user mobility. This Special Section therefore aims to publish high quality, original, unpublished research papers in the broad area of Wireless Computing and Networking, and thus presents a platform for scientists and scholars to share their observations and research results in the field. Specific topics for this special section include but are not limited to：

Call for Papers Special Section of Tsinghua Science and Technology on Mobile and Pervasive Computing

Tsinghua Science and Technology is founded and published since 1996. It is an international academic journal sponsored by Tsinghua University and is published bimonthly. This journal aims at presenting the up-to-date scientific achievements in computer science, and other information technology fields. It is indexed by Ei and other abstracting and indexing services. From 2013, the journal commits to the open access at IEEE Xplore Digital Library.

Negative Sentiment Shift on a Chinese Movie-Rating Website

Shifting to negativity is more and more prevalent in online communities and may play a key role in group polarization.While current research indicates a close relationship between group polarization and negative sentiment,they often link negative sentiment shifts with echo chambers and misinformation within echo chambers.In this work,we explore the sentiment drift using over 4 million comments from a Chinese online movie-rating community that is less affected by misinformation than other mainstream online communities and has no echo chamber structures.We measure the sentiment shift of the community and users of different engagement levels.Our analysis reveals that while the community does not show a tendency toward negativity,users of higher engagement levels are generally more negative,considering factors like the different movies they consume.The results indicate a fitting-in process,suggesting the possible mechanism of group identity on sentiment shift on social media platforms.These findings also provide guidance on web design to tackle the negativity issue and expand sentiment shift analysis to non-English contexts.

Argumentative Conversational Agents for Online Discussions

Artificial Intelligence is revolutionising our communication practices and the ways in which we interact with each other. This revolution does not only impact how we communicate, but it affects the nature of the partners with whom we communicate. Online discussion platforms now allow humans to communicate with artificial agents in the form of socialbots. Such agents have the potential to moderate online discussions and even manipulate and alter public opinions. In this paper, we propose to study this phenomenon using a constructed large-scale agent platform. At the heart of the platform lies an artificial agent that can moderate online discussions using argumentative messages. We investigate the influence of the agent on the evolution of an online debate involving human participants. The agent will dynamically react to their messages by moderating, supporting, or attacking their stances. We conducted two experiments to evaluate the platform while looking at the effects of the conversational agent. The first experiment is a large-scale discussion with 1076 citizens from Afghanistan discussing urban policy-making in the city of Kabul. The goal of the experiment was to increase the citizen involvement in implementing Sustainable Development Goals. The second experiment is a small-scale debate between a group of 16 students about globalisation and taxation in Myanmar. In the first experiment, we found that the agent improved the responsiveness of the participants and increased the number of identified ideas and issues. In the second experiment, we found that the agent polarised the debate by reinforcing the initial stances of the participant.

Measuring Community Resilience During the COVID-19 Based on Community Wellbeing and Resource Distribution

The COVID-19 pandemic has severely harmed every aspect of our daily lives,resulting in a slew of social problems.Therefore,it is critical to accurately assess the current state of community functionality and resilience under this pandemic for successful recovery.To this end,various types of social sensing tools,such as tweeting and publicly released news,have been employed to understand individuals’and communities’thoughts,behaviors,and attitudes during the COVID-19 pandemic.However,some portions of the released news are fake and can easily mislead the community to respond improperly to disasters like COVID-19.This paper aims to assess the correlation between various news and tweets collected during the COVID-19 pandemic on community functionality and resilience.We use fact-checking organizations to classify news as real,mixed,or fake,and machine learning algorithms to classify tweets as real or fake to measure and compare community resilience(CR).Based on the news articles and tweets collected,we quantify CR based on two key factors,community wellbeing and resource distribution,where resource distribution is assessed by the level of economic resilience and community capital.Based on the estimates of these two factors,we quantify CR from both news articles and tweets and analyze the extent to which CR measured from the news articles can reflect the actual state of CR measured from tweets.To improve the operationalization and sociological significance of this work,we use dimension reduction techniques to integrate the dimensions.

Social Computing Unhinged

Social computing is ubiquitous and intensifying in the 21st Century.Originally used to reference computational augmentation of social interaction through collaborative filtering,social media,wikis,and crowdsourcing,here I propose to expand the concept to cover the complete dynamic interface between social interaction and computation,including computationally enhanced sociality and social science,socially enhanced computing and computer science,and their increasingly complex combination for mutual enhancement.This recommends that we reimagine Computational Social Science as Social Computing,not merely using computational tools to make sense of the contemporary explosion of social data,but also recognizing societies as emergent computers of more or less collective intelligence,innovation and flourishing.It further proposes we imagine a socially inspired computer science that takes these insights into account as we build machines not merely to substitute for human cognition,but radically complement it.This leads to a vision of social computing as an extreme form of human computer interaction,whereby machines and persons recursively combine to augment one another in generating collective intelligence,enhanced knowledge,and other social goods unattainable without each other.Using the example of science and technology,I illustrate how progress in each of these areas unleash advances in the others and the beneficial relationship between the technology and science of social computing,which reveals limits of sociality and computation,and stimulates our imagination about how they can reach past those limits together.

Compact fluidized bed sorber for CO_2 capture

Multiphase CFD is used to design a compact fluidized bed sorber for CO2 removal from flue gases using sodium or potassium carbonate pellets. The sorber sizes are much smaller than commercial amine absorbers and smaller than other proposed dry adsorbers. The size reduction is due to the elimination of dilute regions that cause bypassing. With proper solids feeding we eliminated the usual core-annular regime found in circulating fluidized beds.

Pandemic Policymaking

This study leverages a high dimensional manifold learning design to explore the latent structure of the pandemic policymaking space only based on bill-level characteristics of pandemic-focused bills from 1973 to 2020.Results indicate the COVID-19 era of policymaking maps extremely closely onto prior periods of related policymaking.This suggests that there is striking uniformity in Congressional policymaking related to these types of large-scale crises over time,despite currently operating in a unique era of hyperpolarization,division,and ineffective governance.