Capital market opening and labour investment efficiency

The purpose of this research is to explore the impact of capital market opening on inefficient labour investment of enterprises and its impact path. This paper takes 2010–2019 A-share nonfinancial listed companies in Shanghai Stock Exchange (SSE) and Shenzhen Stock Exchange (SZSE) as research objects and samples, and uses DID method to examine the impact of capital market opening on labour investment efficiency of listed companies.We collected 22567 pieces of data.The results show that the capital market opening system significantly reduces inefficient labour investment of enterprises, mainly through reducing the information asymmetry and the agency costs as the main paths. This research shows that the capital market opening is of positive significance to the sustainable development of enterprises, and it proposes targeted suggestions for the government, listed companies and market investors to effectively reduce the inefficient labour investment of enterprises. The research provides more feasible references for capital market opening and corporate governance, and also offers theoretical evidence for the implementation of ‘Shanghai-Hong Kong Stock Connect’ program

High‐Performance Pseudocubic Thermoelectric Materials from Non‐cubic Chalcopyrite Compounds

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/107585/1/adma201400058-sup-0001-S1.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/107585/2/adma201400058.pd

Hydropower reservoirs on the upper Mekong river modify nutrient bioavailability downstream

Hydropower development is the key strategy in many developing countries for energy supply, climate-change mitigation and economic development. However, it is commonly assumed that river dams retain nutrients and therefore reduce downstream primary productivity and fishery catches, compromising food security and causing trans-boundary disputes. Contrary to expectation, here we found that a cascade of reservoirs along the upper Mekong River increased downstream bioavailability of nitrogen and phosphorus. The dams caused phytoplankton density to increase with hydraulic residence time and stratification of the stagnant reservoirs caused hypoxia at depth. This allowed the release of bioavailable phosphorus from the sediment and an increase in dissolved inorganic nitrogen as well as a shift in nitrogen species from nitrate to ammonium, which were transported downstream by the discharge of water from the base of the dam. Our findings provide a new perspective on the environmental impacts of river dams on nutrient cycling and ecosystem functioning, with potential implications for sustainable development of hydropower worldwide

Entropy as a Gene‐Like Performance Indicator Promoting Thermoelectric Materials

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138909/1/adma201702712.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/138909/2/adma201702712-sup-0001-S1.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/138909/3/adma201702712_am.pd

Ultrahigh Thermoelectric Performance by Electron and Phonon Critical Scattering in Cu 2 Se 1‐x I x

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/102251/1/adma201302660.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/102251/2/adma201302660-sup-0001-S1.pd

Micropollutant rejection by nanofiltration membranes: a mini review dedicated to the critical factors and modelling prediction

Nanofiltration (NF) membranes, extensively used in advanced wastewater treatment, have broad application prospects for the removal of emerging trace organic micropollutants (MPs). The treatment performance is affected by several factors, such as the properties of NF membranes, characteristics of target MPs, and operating conditions of the NF system concerning MP rejection. However, quantitative studies on different contributors in this context are limited. To fill the knowledge gap, this study aims to assess critical impact factors controlling MP rejection and develop a feasible model for MP removal prediction. The mini-review firstly summarized membrane pore size, membrane zeta potential, and the normalized molecular size (λ = rs/rp), showeing better individual relationships with MP rejection by NF membranes. The Lindeman-Merenda-Gold model was used to quantitatively assess the relative importance of all summarized impact factors. The results showed that membrane pore size and operating pressure were the high impact factors with the highest relative contribution rates to MP rejection of 32.11% and 25.57%, respectively. Moderate impact factors included membrane zeta potential, solution pH, and molecular radius with relative contribution rates of 10.15%, 8.17%, and 7.83%, respectively. The remaining low impact factors, including MP charge, molecular weight, logKow, pKa and crossflow rate, comprised all the remaining contribution rates of 16.19% through the model calculation. Furthermore, based on the results and data availabilities from references, the machine learning-based random forest regression model was trained with a relatively low root mean squared error and mean absolute error of 12.22% and 6.92%, respectively. The developed model was then successfully applied to predict MPs’ rejections by NF membranes. These findings provide valuable insights that can be applied in the future to optimize NF membrane designs, operation, and prediction in terms of removing micropollutants