Same Environment, Stratified Impacts? Air Pollution, Extreme Temperatures, and Birth Weight in South China

This paper investigates whether associations between birth weight and prenatal ambient environmental conditions—pollution and extreme temperatures—differ by 1) maternal education; 2) children’s innate health; and 3) interactions between these two. We link birth records from Guangzhou, China, during a period of high pollution, to ambient air pollution (PM10 and a composite measure) and extreme temperature data. We first use mean regressions to test whether, overall, maternal education is an “effect modifier” in the relationships between ambient air pollution, extreme temperature, and birth weight. We then use conditional quantile regressions to test for effect heterogeneity according to the unobserved innate vulnerability of babies after conditioning on other confounders. Results show that 1) the negative association between ambient exposures and birth weight is twice as large at lower conditional quantiles of birth weights as at the median; 2) the protection associated with college-educated mothers with respect to pollution and extreme heat is heterogeneous and potentially substantial: between 0.02 and 0.34 standard deviations of birth weights, depending on the conditional quantiles; 3) this protection is amplified under more extreme ambient conditions and for infants with greater unobserved innate vulnerabilities

Chinese Medicine Injection Qingkailing for Treatment of Acute Ischemia Stroke: A Systematic Review of Randomized Controlled Trials

Qingkailing (QKL) injection was a famous traditional Chinese patent medicine, which was extensively used to treat the acute stages of cerebrovascular disease. The aim of this study was to assess the quantity, quality and overall strength of the evidence on QKL in the treatment of acute ischemic stroke. Methods. An extensive search was performed within MEDLINE, Cochrane, CNKI, Vip and Wan-Fang up to November 2011. Randomized controlled trails (RCTs) on QKL for treatment of acute stroke were collected, irrespective of languages. Study selection, data extraction, quality assessment, and data analyses were conducted according to the Cochrane standards, and RevMan5 was used for data analysis. Results. 7 RCTs (545 patients) were included and the methodological quality was evaluated as generally low. The pooled results showed that QKL combined with conventional treatment was more effective in effect rate, and the score of MESSS and TNF-α level compared with conventional treatment alone, but there was no significant difference in mortality of two groups. Only one trial reported routine life status. There were four trials reported adverse events, and no obvious adverse event occurred in three trials while one reported adverse events described as eruption and dizziness

The Asian Games, Air Pollution and Birth Outcomes in South China: An Instrumental Variable Approach

We estimate the causal effects of air pollution exposure on low birthweight, birthweight, and prematurity risk in South China, for all expectant mothers and by maternal age group and child sex. We do so by exploiting exogenous improvement in air quality during the 2010 Guangzhou Asian Games, when strict regulations were mandated to assure better air quality. We use daily air pollution levels collected from monitoring stations in Guangzhou, the Asian Games host city, and Shenzhen, a nearby control city, between 2009 and 2011. We first show that air quality during the Asian Games significantly improved in Guangzhou, relative to Shenzhen. Further, using birth-certificate data for both cities for 2009 to 2011 and using expected pregnancy overlap with the Asian Games as an instrumental variable, we study the effects of three pollutants (PM10, SO2, NO2) on birth outcomes. Results show that 1) air pollutants significantly reduced average birthweight and increased preterm risk; 2) for birthweight, late pregnancy is most sensitive to PM10 exposure, but there is not consistent evidence of a sensitive period for other pollutants and outcomes; 3) for birthweight, babies of mothers who are at least 35 years old show more vulnerability to all three air pollutants; and 4) male babies show more vulnerability than female babies to PM10 and SO2, but birthweights of female babies are more sensitive than those of male babies to NO2

The impact of maternal pre-pregnancy impaired fasting glucose on preterm birth and large for gestational age: a large population-based cohort study

Background The impact of maternal pre-pregnancy impaired fasting glucose on preterm birth and large for gestational age has been poorly understood. Objectives We aimed to estimate the impact of pre-pregnancy impaired fasting glucose defined by the WHO cut-point on the risk of preterm birth and large for gestational age, and to investigate whether the WHO cut-point of impaired fasting glucose was appropriate for identifying women at the risk of preterm birth and large for gestational age among the Chinese population. Study Design This was a retrospective cohort study of women from the National Free Preconception Health Examination Project with singleton birth from 121 counties/districts in 21 cities of Guangdong Province, China, from 1st January 2013 to 31st December 2017. Women were included if pre-pregnancy fasting glucose was less than 7.0mmol/L. The primary outcomes were preterm birth (gestational age 90th percentile based on the international standards in the INTERGROWTH-21st) and severe large for gestational age (birth weight by gestational age >97th percentile). We calculated the adjusted risk ratio for impaired fasting glucose, and a 1 standard deviation increase in fasting glucose. Results We included 640469 women. Of these, 31006 (4.84%) met the WHO cut-point for impaired fasting glucose, 32640 (5.10%) had preterm birth and 7201 (1.12%) had early preterm birth, 45532 (7.11%) had large for gestational age birth and 16231 (2.53%) had severe large for gestational age birth. Compared with women with normoglycaemia, women with pre-pregnancy impaired fasting glucose had a 7.0% higher risk of preterm birth (adjusted risk ratio 1.07, 95%CI 1.02-1.12), 10.0% higher risk of large for gestational age (1.10, 1.06-1.14) and 17.0% higher risk of severe large for gestational age (1.17, 1.10-1.26). No significant association of pre-pregnancy impaired fasting glucose with early preterm birth was found. The association of pre-pregnancy impaired fasting glucose with preterm birth and large for gestational age were similar in subgroups of women with various baseline characteristics. Adjusted risk ratio for preterm birth per standard deviation fasting glucose (0.7mmol/L) was 0.99 (95% CI 0.98-1.00), for early preterm birth 0.99 (0.97-1.02), for large for gestational age 1.04 (1.03-1.05) and for severe large for gestational age 1.03 (1.01-1.04). Conclusions Our data suggest that maternal pre-pregnancy impaired fasting glucose increases the risk of preterm birth, large for gestational age and severe large for gestational age. Data also suggest that the WHO cut-point of impaired fasting glucose is too restrictive and lesser levels of fasting glucose also increase the risk of large gestational age and severe for severe gestational age in the Chinese population. Further investigation is warranted to determine whether and how counselling and interventions for women with pre-pregnancy impaired fasting glucose could reduce the risk of preterm birth and large for gestational age.This work was supported by grants National Natural Science Foundation of China (81773457 & 81302445 to JJT)Published versio

Productivity prediction of fractured horizontal wells with low permeability flow characteristics

Horizontal well and large-scale fracturing are revolutionary technologies in  petroleum industry. The technologies bring obvious economic benefits to exploiting unconventional oil and gas reservoirs with low permeability, ultra-low permeability and shale gas. With the increasingly extensive application of these technologies, other correlated technologies have also gained great development. However, low-permeability reservoirs exhibit complicated features and horizontal well fractures have complex shape. The existing methods for the productivity prediction of fractured horizontal well in low-permeability reservoirs rarely consider the influencing factors in a comprehensive manner. In this paper, a horizontal well seepage model of casing fracturing completion was established according to the superposition principle of low-permeability reservoir and the relationship between potential and pressure, by which model the seepage characteristics of low-permeability reservoirs could be fully described. Based on the established new seepage model, a new targeted model with coupling seepage and wellbore flow was established for the productivity prediction of low-permeability fractured horizontal well. Finally, the new targeted model was verified through field experiment. The experimental results confirmed the reliability of productivity prediction by the proposed model. Sensitivity analysis was then performed on the parameters in the proposed model

A local field correlated and Monte Carlo based shallow neural network model for nonlinear time series prediction

Water resource problems currently are much more important in proper planning especially for arid regions, such as Gansu in China. For agricultural and industrial activities, prediction of groundwater status is critical. As a main branch of neural network, shallow artificial neural network models have been deployed in prediction areas such as groundwater and rainfall since late 1980s. In this paper, artificial neural network (ANN) model within a newly proposed algorithm has been developed for groundwater status forecasting. Having considered previous algorithms for ANN model in time series forecast, this new Monte Carlo based algorithm demonstrated a good result. The experiments of this ANN model in predicting groundwater status were conducted on the Heihe River area dataset, which was curated on the collected data. When compared with its original physical based model, this ANN model was able to achieve a more stable and accurate result. A comparison and an analysis of this ANN model were also presented in this paper

Boundary distribution estimation for precise object detection

In the field of state-of-the-art object detection, the task of object localization is typically accomplished through a dedicated subnet that emphasizes bounding box regression. This subnet traditionally predicts the object's position by regressing the box's center position and scaling factors. Despite the widespread adoption of this approach, we have observed that the localization results often suffer from defects, leading to unsatisfactory detector performance. In this paper, we address the shortcomings of previous methods through theoretical analysis and experimental verification and present an innovative solution for precise object detection. Instead of solely focusing on the object's center and size, our approach enhances the accuracy of bounding box localization by refining the box edges based on the estimated distribution at the object's boundary. Experimental results demonstrate the potential and generalizability of our proposed method