Key Factors, Planning Strategy and Policy for Low-Carbon Transport Development in Developing Cities of China.

Exploring key impact factors and their effects on urban residents' transport carbon dioxide (CO2) emissions is significant for effective low-carbon transport planning. Researchers face the model uncertainty problem to seek a rational and better explanatory model and the key variables in the model set containing various factors after they are arranged and combined. This paper uses the Bayesian Model Averaging method to solve the above problem, explore the key variables, and determine their relative significance and averaging effects. Beijing, Xi'an, and Wuhan are selected as three case cities for their representation of developing Chinese cities. We found that the initial key factor increasing transport emissions is the high dependence on cars, and the second is the geographical location factor that much more suburban residents suffer longer commuting. Developing satellite city rank first for reducing transport emissions due to more local trips with an average short distance, the second is the metro accessibility, and the third is polycentric form. Key planning strategies and policies are proposed: (i) combining policies of car restriction based on vehicle plate number, encouraging clean fuel cars, a carbon tax on oil uses, and rewarding public transit passengers; (ii) fostering subcenters' strong industries to develop self-contained polycentric structures and satellite cities, and forming employment and life circle within 5 km radius; and (iii) integrating bus and rail transit services in the peripheral areas and suburbs and increasing the integration level of muti-modes transferring in transport hubs. The findings will offer empirical evidence and reference value in developing cities globally.

Mesenchymal Stem Cell-Derived Extracellular Vesicles Therapy for Pulmonary Hypertension: A Comprehensive Review of Preclinical Studies.

Pulmonary hypertension (PH) is a type of clinical pathophysiological syndrome characterized by a progressive increase in pulmonary vascular resistance and subsequent progressive failure of the right heart function, and is a common complication of many diseases. Mesenchymal stem cells (MSCs) autonomously home to sites damaged by disease, repair damaged tissues, and participate in the regulation of systemic inflammation and immune responses, which have good clinical application prospects. Extracellular vesicles (EVs), such as exosomes and microvesicles, participate in various biological activities by regulating intercellular communication. Exosomes secreted into the extracellular environment also affect the host immune system. MSC-derived extracellular vesicles (MSC-EVs), as a mediator in the paracrine processes of MSCs, carry biologically active substances such as proteins, lipids, mRNA, and micro-RNA. MSC-EVs therapies, safer than cell-based treatments, have been shown to be effective in modulating macrophages to support anti-inflammatory phenotypes, which are strongly related to histological and functional benefits in preclinical models of pulmonary hypertension. The main effects of active substances and their potential medical value have attracted wide attention from researchers. This article reviews the role and relevant mechanisms of MSC-EVs in the treatment of pulmonary hypertension in recent studies and provides a basis for their future clinical applications.

Culture and Happiness.

Culture is an important factor affecting happiness. This paper examines the predictive power of cultural factors on the cross-country differences in happiness and explores how different dimensions of cultural indices differ in their effects on happiness. Our empirical results show that the global leadership and organizational behavior effectiveness nine culture indices are all significantly related with happiness. Out of these nine indices, power distance (PDI) and gender egalitarianism (GEI) play the most important and stable role in determining subjective well-being (SWB). We further examine the relative importance of the various variables in contributing to the R-squared of the regression. The results show that PDI is the most important, accounting for 50 % of the contributions to R-squared of all variables, or equalling the combined contributions of income, population density and four other traditional variables. The contribution of GEI is 37.1 %, also well surpassing other variables. Our results remain robust even taking account of the different data for culture and SWB.