Demand for energy in day to day life is increasing exponentially. However, existing energy storage technologies like lithium ion batteries cannot stand alone to fulfill future needs. In this regard, potassium ion batteries (KIBs) that utilize K ions in their charge storage mechanism have attracted considerable attention due to their unique properties and are therefore established as one of the future battery systems of interest among the scientific community. Nevertheless, the development and identification of appropriate electrode materials is very essential for practical applications. This review features the current development in KIBs electrode and electrolyte materials, the present challenges facing this technology (in the commercial aspect), and future aspects to develop fully functional KIBs. The potassium storage mechanisms, evolution of the KIBs, and the advantages and disadvantages of each category of materials are included. Additionally, various approaches to enhance the electrochemical performances of KIBs are also discussed. This review is not only an amalgamation of different viewpoints in literature, but also contains concise perspectives and strategies. Moreover, the potential emergence of a novel class of K‐based dual ion batteries is also analyzed for the first time.

We consider the existence, multiplicity and nonexistence of positive o-periodic solutions for the periodic equation x 0 ðtÞ ¼ aðtÞgðxÞxðtÞ À lbðtÞf ðxðt À tðtÞÞÞ; where a; bACðR; ½0; NÞÞ are o-periodic, R o 0 aðtÞ dt40; R o 0 bðtÞ dt40; f ; gACð½0; NÞ; ½0; NÞÞ; and f ðuÞ40 for u40; gðxÞ is bounded, tðtÞ is a continuous o-periodic function. Define f 0 ¼ lim u-0 þ f ðuÞ u ; f N ¼ lim u-N f ðuÞ u ; i 0 ¼ number of zeros in the set f f 0 ; f N g and i N ¼ number of infinities in the set f f 0 ; f N g: We show that the equation has i 0 or i N positive o-periodic solution(s) for sufficiently large or small l40; respectively. r 2004 Elsevier Inc. All rights reserved.

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Abstract-Mathematical modeling is an important approach to study information diffusion in online social networks. Prior studies have focused on the modeling of the temporal aspect of information diffusion. A recent effort introduced the spatiotemporal diffusion problem and addressed the problem with a theoretical framework built on the similarity between information propagation in online social networks and biological invasion in ecology [1]. This paper examines the spatio-temporal characteristics in further depth and reveals that there exist regularities in information diffusion in temporal and spatial dimensions. Furthermore, we propose a simpler linear partial differential equation that takes account of the influence of spatial population density and temporal decay of user interests in the information. We validate the proposed linear model with Digg news stories which received more than 3000 votes during June 2009, and show that the model can describe nearly 60% of the news stories with over 80% accuracy. We also use the most popular news story as a case study and find that the linear diffusive model can achieve an accuracy as high as 97.41% for this news story. Finally, we discuss the potential applications of this model towards finding super spreaders and classifying news story into groups.

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In accordance with the global trend of women’s employment in journalism, China has witnessed an unprecedented increase in women’s participation in the news profession over the last two decades. However, while accounting for more than 40% of the labor force in journalism, women still tend to occupy roles with lower pay and less power. Against this background, this article tries to provide an insight into the obstacles in the path of the success of women journalists in Chinese media. Through in-depth interviews with the journalists, three major constraining mechanisms are identified: women-unfriendly job contracts and salary systems, weak women’s associations and trade unions, and the prevalence of a sexist newsroom culture.

The outbreak of COVID-19 disrupts the life of many people in the world. In response to this global pandemic, various institutions across the globe had soon issued their prevention guidelines. Governments in the US had also implemented social distancing policies. However, those policies, which were designed to slow the spread of COVID-19, and its compliance, have varied across the states, which led to spatial and temporal heterogeneity in COVID-19 spread. This paper aims to propose a spatio-temporal model for quantifying compliance with the US COVID-19 mitigation policies at a regional level. To achieve this goal, a specific partial differential equation (PDE) is developed and validated with short-term predictions. The proposed model describes the combined effects of transboundary spread among state clusters in the US and human mobilities on the transmission of COVID-19. The model can help inform policymakers as they decide how to react to future outbreaks.

The Japanese Society of Nephrology (JSN) sponsored the Asian Forum of CKD Initiative (AFCKDI)