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The Sixth Plenary of the 11th Party Congress in 1981 gave a positive assessment on the transition period and the acceleration of the Chinese socialist transformation in the 1950s. Since 1987 China has witnessed active academic debates on the assessment and some contrary views have emerged. There was a sharp controversy between Mao Zedong and Deng Zihui in 1955 about the pace of transformation in agriculture and the result had a significant impact on the whole socialist transformation. The decision-making process coloured by a cult of Mao in the CCP was an important element in the origins of the major events taking place afterwards.

AbstractResource depletion and environmental pollution have seriously restricted the sustainable development of China's economy in recent years. How to transform the extensive growth mode to the intensive growth mode and realize the green development of economy is a great challenge for China. In this paper, we use the non‐radial and non‐angle Slack‐based Model (SBM) considering the undesired output, combined with the Malmquist–Luenberger productivity index, to measure regional green total factor productivity (GTFP). By constructing the green output density function, the theoretical model of the relationship between regional GTFP and industrial agglomeration is deduced, and the theoretical mechanism of the influence of industrial agglomeration on regional GTFP is analyzed. Based on panel data of 243 cities at the prefecture level in China from 2010 to 2019, this article employs the dynamic spatial panel model to empirically estimate the impact of industrial agglomeration on regional GTFP. The empirical results show that regional GTFP shows significant spatial autocorrelation and spatial clustering characteristics. The manufacturing agglomeration has significant negative impact on regional GTFP and produces negative spatial spillover effect on the surrounding regions, but does not produce congestion effect. The producer services agglomeration significantly improves regional GTFP and produces positive spatial spillover effect on the surrounding regions, and leads to congestion effect. The co‐agglomeration of producer services and manufacturing has significantly promoted the improvement of regional GTFP and produces positive spatial spillover effect on the surrounding regions. Finally, this article puts forward policy suggestions on how to promote regional GTFP and achieve green development from the perspective of industrial agglomeration.

Depression influences personality measures like Eysenck's Big Three, Costa and McCrae's Big Five or Cloninger's Seven Factor models, and might also affect Zuckerman-Kuhlman's Personality Questionnaire (ZKPQ), an alternative five-factor model. The authors therefore
tested ZKPQ in 85 patients suffering from major depression and in 82 healthy subjects in order to clarify this effect. Depressive mood was measured with Plutchik – van Praag's Depression Inventory (PVP). Patients scored significantly higher on PVP, Neuroticism-Anxiety and Aggression-Hostility,
but lower on Activity and Sociablity than did healthy volunteers. In the general sample (N = 167), Neuroticism-Anxiety and Aggression-Hostility scores were positively correlated, while the Sociability score was negatively correlated with the PVP score. These results indicate that when
the clinical significance relating to personality traits in patients is interpreted, depressive mood must also be considered.

AbstractMembraneless organelles (MLOs) are likely assembled via liquid–liquid phase separation (LLPS). The liquid‐like MLOs afford multifold peculiarities including high dynamics, reversibility and responsiveness. It is common to see fast, drastic, and reversible formation and dissolution events of MLOs, as well as transition into more stable glassy or gel‐like states, which suggests a metastable assembly state. Moreover, the alteration of metastability of LLPS is linked with cellular pathology. Here, we review the "metastability" related to MLOs driven by liquid phase separation, from multifaceted regards including energy state, molecular interactions, molecular structure, phase transition, as well as the associations with diseases. This review can help to advance the insight into properties and pathogenesis associated with LLPS of biological matter.