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This study aims to introduce a deep neural network (DNN) to estimate the effective thermal conductivity of the flat heat pipe with spreading thermal resistance.

A total of 2,160 computational fluid dynamics simulation cases over up to 2,000 W/mK are conducted to regress big data and predict a wider range of effective thermal conductivity up to 10,000 W/mK. The deep neural networking is trained with reinforcement learning from 10–12 steps minimizing errors in each step. Another 8,640 CFD cases are used to validate.

Experimental, simulational and theoretical approaches are used to validate the DNN estimation for the same independent variables. The results from the two approaches show a good agreement with each other. In addition, the DNN method required less time when compared to the CFD.

The DNN method opens a new way to secure data while predicting in a wide range without experiments or simulations. If these technologies can be applied to thermal and materials engineering, they will be the key to solve thermal obstacles that many longing to overcome.

This paper reviews the possibilities of coronavirus disease 2019 (COVID-19) spreading from infected humans to pet animals and from pet animals to other animals and humans.

A systematic literature review and meta-analysis were performed on research articles from November 2019 to August 2020. This study explored urgently needed research issues on COVID-19 infection spreading across animals and humans and vice versa.

Essential and much needed precautionary measures and necessary preventive steps to protect pet animals from infection were highlighted.

Essential investigation and experiment results were highlighted. The necessary measure to prevent the spread of infection among and across species and people was analyzed.

The purpose of this paper is to show that the droplet impact phenomenon is important for the advancement of industrial technologies in many fields such as spray cooling and ink jet printing. Droplet bouncing on the nonwetting surfaces is a special phenomenon in the impact process which has attracted lots of attention.

In this work, the authors fabricated two kinds of representative nonwetting surfaces including superhydrophobic surfaces (SHS) and a slippery liquid-infused porous surface (SLIPS) with advanced UV laser processing.

The droplet bouncing behavior on the two kinds of nonwetting surfaces were compared in the experiments. The results indicate that the increasing Weber number enlarges the maximum droplet spreading diameter and raises the droplet bounce height but has no effect on contact time.

In addition, the authors find that the topological SHS and SLIPS with the laser-processed microwedge groove array produce asymmetric droplet bouncing with opposite offset direction. Microdroplets can be continuously transported without any additional driving force on such a topological SLIPS. The promising method for manipulating droplets has potential applications for the droplet-based microfluidic platforms.

This article examines the misinformation on the COVID-19 pandemic in social media and electronic media, as well as whether the existing legal administration and laws in Bangladesh, Singapore, and Vietnam are adequate to combat the infodemic. People who believe misinformation and fake news about Coronavirus, prevention, and treatment may put their lives in danger. False information about Coronavirus has spread throughout the world, not just in South and Southeast Asian countries, causing widespread concern in the global healthcare community. We employed a qualitative approach as well as the case study analysis method. Case studies were conducted using news reports and news channels. We examined the legal provisions of the People's Republic of Bangladesh's Constitution, as well as factual analyses of Singapore and Vietnam. We discovered the impact of misinformation dissemination through social and electronic media, which is prevalent not only among rural Bangladeshis but also in almost all classes in Singapore and Vietnam, and how such influence can be detrimental to the interests of Bangladesh, Vietnam, and Singapore.

With the popularity of the internet and the increasing numbers of netizens, tremendous information flows are generated daily by the intelligently interconnected individuals. The diffusion processes of different information are not independent, and they interact with and influence each other. Modeling and analyzing the interaction between correlated information play an important role in the understanding of the characteristics of information dissemination and better control of the information flows. This paper aims to model the correlated information diffusion process over the crowd intelligence networks.

This study extends the classic epidemic susceptible–infectious–recovered (SIR) model and proposes the SIR mixture model to describe the diffusion process of two correlated pieces of information. The whole crowd is divided into different groups with respect to their forwarding state of the correlated information, and the transition rate between different groups shows the property of each piece of information and the influences between them.

The stable state of the SIR mixture model is analyzed through the linearization of the model, and the stable condition can be obtained. Real data are used to validate the SIR mixture model, and the detailed diffusion process of correlated information can be inferred by the analysis of the parameters learned through fitting the real data into the SIR mixture model.

The proposed SIR mixture model can be used to model the diffusion of correlated information and analyze the propagation process.

The purpose of this paper is to investigate how to optimise corporate social responsibility (CSR) when communicating via social media. In particular, the communication type, cause proximity and CSR motives are addressed facing the increased demand for transparency and the grown consumers' expectations towards socially responsible brands.

Online survey was developed, based on a profound literature review and a field research we did on the actual social media behaviour of socially responsible brands. Consumers attitudes and behavioural reactions in terms of willingness to participate in a campaign, to spread e-WOM and to purchase were investigated, as a function of CSR motives (value vs performance vs value and performance) and cause proximity (national vs international), respectively, with monologue (study 1) and dialogue communication type (study 2).

Cause proximity enhanced the campaign participation, and this effect was pronounced for both, monologue and dialogue type of communication. CSR motives modulated the willingness to spread electronic word-of-mouth, and this holds for both, monologue and dialogue communication. Attitudes and purchase intention were highest when value- and performance-driven motives were communicated, but these effects appeared only when the message was in a dialogue form of communication. Message credibility and CSR motives credibility perception further modulated consumers response.

The outcomes could be used in developing marketing (communication) strategies leading to values and revenues optimisation.

The results are discussed in a framework of how CSR resonates via social media.

With the rapid development of internet technology, open online social networks provide a broader platform for information spreading. While dissemination of information provides convenience for life, it also brings many problems such as security risks and public opinion orientation. Various negative, malicious and false information spread across regions, which seriously affect social harmony and national security. Therefore, this paper aims to minimize negative information such as online rumors that has attracted extensive attention. The most existing algorithms for blocking rumors have prevented the spread of rumors to some extent, but these algorithms are designed based on entire social networks, mainly focusing on the microstructure of the network, i.e. the pairwise relationship or similarity between nodes. The blocking effect of these algorithms may be unsatisfactory in some networks because of the sparse data in the microstructure.

An algorithm for minimizing the influence of dynamic rumor based on community structure is proposed in this paper. The algorithm first divides the network into communities, and integrates the influence of each node within communities and rumor influence probability to measure the influence of each node in the entire network, and then selects key nodes and bridge nodes in communities as blocked nodes. After that, a dynamic blocking strategy is adopted to improve the blocking effect of rumors.

Community structure is one of the most prominent features of networks. It reveals the organizational structure and functional components of a network from a mesoscopic level. The utilization of community structure can provide effective and rich information to solve the problem of data sparsity in the microstructure, thus effectively improve the blocking effect. Extensive experiments on two real-world data sets have validated that the proposed algorithm has superior performance than the baseline algorithms.

As an important research direction of social network analysis, rumor minimization has a profound effect on the harmony and stability of society and the development of social media. However, because the rumor spread has the characteristics of multiple propagation paths, fast propagation speed, wide propagation area and time-varying, it is a huge challenge to improve the effectiveness of the rumor blocking algorithm.

In this article we aim to understand how the network formed by fitness tracking devices and associated apps as a subset of the broader health-related Internet of things is capable of spreading information.

The authors used a combination of a content analysis, network analysis, community detection and simulation. A sample of 922 health-related apps (including manufacturers' apps and developers) were collected through snowball sampling after an initial content analysis from a Google search for fitness tracking devices.

The network of fitness apps is disassortative with high-degree nodes connecting to low-degree nodes, follow a power-law degree distribution and present with low community structure. Information spreads faster through the network than an artificial small-world network and fastest when nodes with high degree centrality are the seeds.

This capability to spread information holds implications for both intended and unintended data sharing.

The analysis confirms and supports evidence of widespread mobility of data between fitness and health apps that were initially reported in earlier work and in addition provides evidence for the dynamic diffusion capability of the network based on its structure. The structure of the network enables the duality of the purpose of data sharing.

Social enterprises (SEs) face tensions when combining financial and social missions, and this is particularly evident in the scaling process. Although extant research mainly focuses on SEs that integrate their social and financial missions, this study aims to unpack social impact scaling strategies in differentiated hybrid organizations (DHOs) through the case of African SEs.

The study entails an inductive multiple case study approach based on four case SEs: work integration social enterprises (WISEs) and fair trade producer social enterprises (FTPSEs) in Uganda and Kenya. A total of 24 semi-structured interviews were collected together with multiple secondary data sources and then coded and analyzed through the rigorous Gioia et al. (2013) methodology to build a theoretical model.

The results indicate that SEs, as differentiated hybrids, implement four types of social impact scaling strategies toward beneficiaries and benefits (penetration, bundling, spreading and diversification) and unveil different dual mission tensions generated by each scaling strategy. The study also shows mutually reinforcing mechanisms named cross-bracing actions, which are paradoxical actions connected to one another for navigating tensions and ensuring dual mission during scaling.

This study provides evidence of four strategies for scaling social impact, with associated challenges and response mechanisms based on the cross-bracing effect between social and financial missions. Thus, the research provides a clear framework (social impact scaling matrix) for investigating differentiation in hybridity at scaling and provides new directions on how SEs scale their impact, with implications for social entrepreneurship and dual mission management literature.

The model offers a practical tool for decision-makers in SEs, such as managers and social entrepreneurs, providing insights into what scaling pathways to implement (one or multiples) and, more importantly, the implications and possible solutions. Response mechanisms are also useful for tackling specific tensions, thereby contributing to addressing the challenges of vulnerable, marginalized and low-income individuals. The study also offers implications for policymakers, governments and other ecosystem actors such as nongovernmental organizations (NGOs) and social investors.

Despite the growing body of literature on scaling social impact, only a few studies have focused on differentiated hybrids, and no evidence has been provided on how they scale only the social impact (without considering commercial scaling). This study brings a new perspective to paradox theory and hybridity, showing paradoxes come into view at scaling, and documenting how from a differentiation approach to hybridity, DHOs also implemented cross-bracing actions, which are reinforcement mechanisms, thus suggesting connections and synergies among the actions in social and financial mission, where such knowledge is required to better comprehend how SEs can achieve a virtuous cycle of profits and reinvestments in social impact.

Public libraries play a pivotal role in supporting education and literacy. They provide numerous services, activities, collections and resources for education and leisure. Bibliotheca Alexandrina (BA) is an international renowned public library that provides numerous services for different users worldwide. E-learning is an emergent and promising method for teaching and learning different subjects such as the science, technology, engineering and mathematics (STEM). The e-learning educational system is quite novel in Africa and the Middle East; hence, this paper presents the whole concept to the reader. In addition, it demonstrates number of e-courses tackling different domains provided by different educational institutions, national and public libraries worldwide.

In 2017, the BA inaugurated its e-learning services to cope with the new educational trend and to consolidate the lifelong learning concept in the community. The author showed special interest to the case of e-learning in the BA, as it is a regional public library. The main idea of this paper is to attract attention toward public libraries as a promising venue for e-learning implementation for general knowledge, library information sciences, soft skills, elementary and informal STEM education. The paper discusses in details e-learning and its characteristics.

In addition, the paper compares traditional education (face-to-face) with e-learning education, mentions both their pros and cons and recommends blending the two educational methods as they complement each other. Furthermore, the author has selected a sample of different STEM e-courses (203 different e-courses). These e-courses were selected to assert the possibility of presenting STEM topics in the form of e-courses.

This study would be one of the emergent research studies that connect e-learning to both STEM disciplines and public libraries. Additionally, this research highlights the importance of public libraries and all the services they provide. In the mean time, it shed light on the important and unique role of specialized librarians. Briefly, public libraries with all their resources, services and expert librarians could provide an exceptional e-learning experience to their community and be of great help to educational institutions and organizations.