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An ideal approach for the construction of aryl boron compounds is to selectively replace a C–H bond in arenes with a C–B bond, and controlling regioselectivity is one of the most challenging aspects of these transformations. Herein, we report an iridium-catalyzed trialkoxysilane protecting group-assisted regioselective C–H borylation of arenes, including derivatives of benzaldehydes, acetophenones, benzoic acids, benzyl alcohols, phenols, aryl silanes, benzyl silanes, and multi-functionalized aromatic rings are all well tolerated and gave the para - selective C–H borylation products in a short time without the requirement of inert gases atmosphere. The site-selective C–H borylation can be adjustable by installing the developed trialkoxysilane protecting group on different functional groups on one aromatic ring. Importantly, the preparation process of the trialkoxychlorosilane is efficient and scalable. Mechanistic and computational studies reveal that the steric hindrance of the trialkoxysilane protecting group plays a key role in dictating the para -selectivity. Controlling regioselectivity is one of the most challenging aspects for the construction of aryl boron compounds, and there are few practical and general strategies for such transformations. Here, the authors report an iridium-catalyzed trialkoxysilane protecting group-assisted regioselective C–H borylation with various aromatic compounds.

Background Suicidal ideation is subject to serious underestimation among existing public health studies. While numerous factors have been recognized in affecting suicidal thoughts and behaviors (STB), the associated environmental risks have been poorly understood. Foremost among the various environment risks were air pollution, in particular, the PM2.5. The present study attempted to examine the relationship between PM 2.5 level and local weekly index of suicidal ideation (ISI). Methods Using Internet search query volumes in Baidu (2017), the largest internet search engine in China, we constructed a prefectural panel data (278 prefectures, 52 weeks) and employed dynamic panel GMM system estimation to analyze the relationship between weekly concentration of PM2.5 (Mean = 87 μg·m − 3 ) and the index of suicidal ideation (Mean = 49.9). Results The results indicate that in the spring and winter, a 10 μg·m − 3 increase in the prior week’s PM 2.5 in a Chinese city is significantly associated with 0.020 increase in ISI in spring and a 0.007 increase in ISI in winter, after taking account other co-pollutants and meteorological conditions. Conclusion We innovatively proposed the measure of suicidal ideation and provided suggestive evidence of a positive association between suicidal ideation and PM 2.5 level.

Sociology is a science concerned with both the interpretive understanding of social action and the corresponding causal explanation, process, and result. A causal explanation should be the foundation of prediction. For many years, due to data and computing power constraints, quantitative research in social science has primarily focused on statistical tests to analyze correlations and causality, leaving predictions largely ignored. By sorting out the historical context of \"social prediction,\" this article redefines this concept by introducing why and how machine learning can help prediction in a scientific way. Furthermore, this article summarizes the academic value and governance value of social prediction and suggests that it is a potential breakthrough in the contemporary social research paradigm. We believe that through machine learning, we can witness the advent of an era of a paradigm shift from correlation and causality to social prediction. This shift will provide a rare opportunity for sociology in China to become the international frontier of computational social sciences and accelerate the construction of philosophy and social science with Chinese characteristics.

Based on a panel of 30 provinces and a timeframe from January 2009 to December 2013, we estimate the association between monthly human immunodeficiency virus/acquired immune deficiency syndrome (HIV/AIDS) incidence and the relevant Internet search query volumes in Baidu, the most widely used search engine among the Chinese. The pooled mean group (PMG) model show that the Baidu search index ( BSI ) positively predicts the increase in HIV/AIDS incidence, with a 1% increase in BSI associated with a 2.1% increase in HIV/AIDS incidence on average. This study proposes a promising method to estimate and forecast the incidence of HIV/AIDS, a type of infectious disease that is culturally sensitive and highly unevenly distributed in China; the method can be taken as a complement to a traditional HIV/AIDS surveillance system.

While China has been experiencing unprecedented economic growth, depression is becoming one of the most striking social and mental health problems in recent years. Such a paradox to progress may partially be due to the notoriously poor air quality of the country. To verify this argument, we constructed an index of the prevalence of depression (IPD) using internet search query volumes in Baidu to proxy the potential depression and examined how IPD is associated with PM 2.5 , the major air pollutant in China. Our results from 2-way fixed effects models reveal that a 100 μg·m −3 increase in previous week’s PM 2.5 in a city is significantly associated with 0.279 increase in its IPD, comparable to 7.34 hours decrease in weekly daylight, and such relationship is particularly pronounced in the spring and summer and in East and South areas. Our findings of large-scale pattern suggest that PM 2.5 at current levels in China poses serious mental health risks.

The socioeconomic role of guanxi networks among individuals has been widely recorded, yet macro-level analysis has been sparse in empirical research. This research fills that gap by presenting the first nationally representative evidence illustrating the connection between regional guanxi culture and population mobility among cities in China, with a particular focus on instrumental guanxi culture. To quantify guanxi culture, we employ online search indices related to gift giving, a measure which is challenging to capture through traditional survey data. Applying matched prefecture-level data spanning from 2011 to 2019, the panel model reveals a strong negative correlation between a city's instrumental guanxi culture and inbound migration, while sentimental guanxi culture exhibits a positive correlation with inbound mobility. This research not only adds to the existing theories by exploring the macro-level effects of both instrumental and sentimental guanxi practices but also introduces an innovative method for quantifying guanxi culture through big data analysis.

While China has been experiencing unprecedented economic growth, depression is becoming one of the most striking social and mental health problems in recent years. Such a paradox to progress may partially be due to the notoriously poor air quality of the country. To verify this argument, we constructed an index of the prevalence of depression (IPD) using internet search query volumes in Baidu to proxy the potential depression and examined how IPD is associated with PM2.5, the major air pollutant in China. Our results from 2-way fixed effects models reveal that a 100 μg·m−3 increase in previous week’s PM2.5 in a city is significantly associated with 0.279 increase in its IPD, comparable to 7.34 hours decrease in weekly daylight, and such relationship is particularly pronounced in the spring and summer and in East and South areas. Our findings of large-scale pattern suggest that PM2.5 at current levels in China poses serious mental health risks.

While China has been experiencing unprecedented economic growth, depression is becoming one of the most striking social and mental health problems in recent years. Such a paradox to progress may partially be due to the notoriously poor air quality of the country. To verify this argument, we constructed an index of the prevalence of depression (IPD) using internet search query volumes in Baidu to proxy the potential depression and examined how IPD is associated with PM 2.5 , the major air pollutant in China. Our results from 2-way fixed effects models reveal that a 100 μg·m −3 increase in previous week’s PM 2.5 in a city is significantly associated with 0.279 increase in its IPD, comparable to 7.34 hours decrease in weekly daylight, and such relationship is particularly pronounced in the spring and summer and in East and South areas. Our findings of large-scale pattern suggest that PM 2.5 at current levels in China poses serious mental health risks.

While deep Convolutional Neural Networks (CNNs) have shown extraordinary capability of modelling specific noise and denoising, they still perform poorly on real-world noisy images. The main reason is that the real-world noise is more sophisticated and diverse. To tackle the issue of blind denoising, in this paper, we propose a novel pyramid real image denoising network (PRIDNet), which contains three stages. First, the noise estimation stage uses channel attention mechanism to recalibrate the channel importance of input noise. Second, at the multi-scale denoising stage, pyramid pooling is utilized to extract multi-scale features. Third, the stage of feature fusion adopts a kernel selecting operation to adaptively fuse multi-scale features. Experiments on two datasets of real noisy photographs demonstrate that our approach can achieve competitive performance in comparison with state-of-the-art denoisers in terms of both quantitative measure and visual perception quality. Code is available at https://github.com/491506870/PRIDNet.

We report on the first dark-matter（DM）search results from PandaX-I,a low threshold dual-phase xenon experiment operating at the China JinPing Underground Laboratory.In the 37-kg liquid xenon target with 17.4 live-days of exposure,no DM particle candidate event was found.This result sets a stringent limit for low-mass DM particles and disfavors the interpretation of previously-reported positive experimental results.The minimum upper limit,3.7×10-44cm2,for the spin-independent isoscalar DM-particle-nucleon scattering cross section is obtained at a DM-particle mass of 49 GeV/c2at 90%confidence level.