We investigate a natural combinatorial optimization problem called the Label Cut problem. Given an input graph G with a source s and a sink t, the edges of G are classified into different categories, represented by a set of labels. The labels may also have weights. We want to pick a subset of labels of minimum cardinality (or minimum total weight), such that the removal of all edges with these labels disconnects s and t. We give the first non-trivial approximation and hardness results for the Label Cut problem. Firstly, we present an O(√ m)-approximation algorithm for the Label Cut problem, where m is the number of edges in the input graph. Secondly, we show that it is NP-hard to approximate Label Cut within 2 log 1−1/ log log c n n for any constant c < 1/2, where n is the input length of the problem. Thirdly, our techniques can be applied to other previously considered optimization problems. In particular we show that the Minimum Label Path problem has the same approximation hardness as that of Label Cut, simultaneously improving and unifying two known hardness results for this problem which were previously the best (but incomparable due to different complexity assumptions).

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a newly emerging respiratory virus with high morbidity, which was named coronavirus disease 2019 (COVID-19) by World Health Organization (WHO). COVID-19 has triggered a series of threats to global public health. Even worse, new cases of COVID-19 infection are still increasing rapidly. Therefore, it is imperative that various effective vaccines and drugs should be developed to prevent and treat COVID-19 and reduce the serious impact on human beings. For this purpose, detailed information about the pathogenesis of COVID-19 at the cellular and molecular levels is urgently needed. In this review, we summarized the current understanding on gene structure, protein function, and pathogenic mechanisms of SARS-CoV-2. Based on the above, we refined the correlations among gene structure, protein function, and pathogenic mechanisms of SARS-CoV-2. Importantly, we further discussed potential therapeutic targets, aiming to accelerate the advanced design and development of vaccines and therapeutic drugs against COVID-19.

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This article examines a recent bizarre phenomenon on China's Internet -the enormous popularity of a scatological Chinese neologism called diaosi, which literally translates as 'dick string'. Seeing the diaosi phenomenon as a case of 'infrapolitics', a space of nuanced discursive practices mediating overt online politics and benign online entertainment, we analyse the ways in which an infrapolitical practice such as the diaosi phenomenon fuses political critique, cultural processes of identity construction and meaning-making as well as cyber ritual communion. Specifically, we interpret the infrapolitics of diaosi as simultaneously an instantiation of a prevalent scatological online culture that defies hypernormalization, a collective identity-making that seeks to create critical social solidarity and a practice and politics of cultural intimacy.