Are Investment Promotion Agencies Doing the Thing Right? Evidence from China

*Revised：What Determines Inward FDI in China? --An empirical study using firm-level data(DP-2013-E-004, April 7

Improving Temporal Accuracy of Human Metabolic Chambers for Dynamic Metabolic Studies

Metabolic chambers are powerful tools for assessing human energy expenditure, providing flexibility and comfort for the subjects in a near free-living environment. However, the flexibility offered by the large living room size creates challenges in the assessment of dynamic human metabolic signals—such as those generated during high-intensity interval training and short-term involuntary physical activities—with sufficient temporal accuracy. Therefore, this paper presents methods to improve the temporal accuracy of metabolic chambers. The proposed methods include 1) adopting a shortest possible step size, here one minute, to compute the finite derivative terms for the metabolic rate calculation, and 2) applying a robust noise reduction method—total variation denoising—to minimize the large noise generated by the short derivative term whilst preserving the transient edges of the dynamic metabolic signals. Validated against 24-hour gas infusion tests, the proposed method reconstructs dynamic metabolic signals with the best temporal accuracy among state-of-the-art approaches, achieving a root mean square error of 0.27 kcal/min (18.8 J/s), while maintaining a low cumulative error in 24-hour total energy expenditure of less than 45 kcal/day (188280 J/day). When applied to a human exercise session, the proposed methods also show the best performance in terms of recovering the dynamics of exercise energy expenditure. Overall, the proposed methods improve the temporal resolution of the chamber system, enabling metabolic studies involving dynamic signals such as short interval exercises to carry out the metabolic chambers

Stream Flow Prediction by Remote Sensing and Genetic Programming

A genetic programming (GP)-based, nonlinear modeling structure relates soil moisture with synthetic-aperture-radar (SAR) images to present representative soil moisture estimates at the watershed scale. Surface soil moisture measurement is difficult to obtain over a large area due to a variety of soil permeability values and soil textures. Point measurements can be used on a small-scale area, but it is impossible to acquire such information effectively in large-scale watersheds. This model exhibits the capacity to assimilate SAR images and relevant geoenvironmental parameters to measure soil moisture

Water, rather than temperature, dominantly impacts how soil fauna affect dissolved carbon and nitrogen release from fresh litter during early litter decomposition

Longstanding observations suggest that dissolved materials are lost from fresh litter through leaching, but the role of soil fauna in controlling this process has been poorly documented. In this study, a litterbag experiment employing litterbags with different mesh sizes (3 mm to permit soil fauna access and 0.04 mm to exclude fauna access) was conducted in three habitats (arid valley, ecotone and subalpine forest) with changes in climate and vegetation types to evaluate the effects of soil fauna on the concentrations of dissolved organic carbon (DOC) and total dissolved nitrogen (TDN) during the first year of decomposition. The results showed that the individual density and community abundance of soil fauna greatly varied among these habitats, but Prostigmata, Isotomidae and Oribatida were the dominant soil invertebrates. At the end of the experiment, the mass remaining of foliar litter ranged from 58% for shrub litter to 77% for birch litter, and the DOC and TDN concentrations decreased to 54%-85% and increased to 34%-269%, respectively, when soil fauna were not present. The effects of soil fauna on the concentrations of both DOC and TDN in foliar litter were greater in the subalpine forest (wetter but colder) during the winter and in the arid valley (warmer but drier) during the growing season, and this effect was positively correlated with water content. Moreover, the effects of fauna on DOC and TDN concentrations were greater for high-quality litter and were related to the C/N ratio. These results suggest that water, rather than temperature, dominates how fauna affect the release of dissolved substances from fresh litter

Modeling of CH4-assisted SOEC for H2O/CO2 co-electrolysis

This research was supported by a grant of SFC/RGC Joint Research Scheme (X-PolyU/501/14) from Research Grant Council, University Grants Committee, Hong Kong SAR.Co-electrolysis of H2O and CO2 in a solid oxide electrolysis cell (SOEC) is promising for simultaneous energy storage and CO2 utilization. Fuel-assisted H2O electrolysis by SOEC (SOFEC) has been demonstrated to be effective in reducing power consumption. In this paper, the effects of fuel (i.e. CH4) assisting on CO2/H2O co-electrolysis are numerically studied using a 2D model. The model is validated with the experimental data for CO2/H2O co-electrolysis. One important finding is that the CH4 assisting is effective in lowering the equilibrium potential of SOEC thus greatly reduces the electrical power consumption for H2O/CO2 co-electrolysis. The performance of CH4-assisted SOFEC increases substantially with increasing temperature, due to increased reaction kinetics of electrochemical reactions and CH4 reforming reaction. The CH4-assisted SOFEC can generate electrical power and syngas simultaneously at a low current density of less than 600 Am−2 and at 1123 K. In addition, different from conventional SOEC whose performance weakly depends on the anode gas flow rate, the CH4-assisted SOFEC performance is sensitive to the anode gas flow rate (i.g. peak current density is achieved at an anode flow rate of 70 SCCM at 1073 K). The model can be used for subsequent design optimization of SOFEC to achieve high performance energy storage.PostprintPeer reviewe

Loss of ATF3 exacerbates liver damage through the activation of mTOR/p70S6K/ HIF-1α signaling pathway in liver inflammatory injury.

Activating transcription factor 3 (ATF3) is a stress-induced transcription factor that plays important roles in regulating immune and metabolic homeostasis. Activation of the mechanistic target of rapamycin (mTOR) and hypoxia-inducible factor (HIF) transcription factors are crucial for the regulation of immune cell function. Here, we investigated the mechanism by which the ATF3/mTOR/HIF-1 axis regulates immune responses in a liver ischemia/reperfusion injury (IRI) model. Deletion of ATF3 exacerbated liver damage, as evidenced by increased levels of serum ALT, intrahepatic macrophage/neutrophil trafficking, hepatocellular apoptosis, and the upregulation of pro-inflammatory mediators. ATF3 deficiency promoted mTOR and p70S6K phosphorylation, activated high mobility group box 1 (HMGB1) and TLR4, inhibited prolyl-hydroxylase 1 (PHD1), and increased HIF-1α activity, leading to Foxp3 downregulation and RORγt and IL-17A upregulation in IRI livers. Blocking mTOR or p70S6K in ATF3 knockout (KO) mice or bone marrow-derived macrophages (BMMs) downregulated HMGB1, TLR4, and HIF-1α and upregulated PHD1, increasing Foxp3 and decreasing IL-17A levels in vitro. Silencing of HIF-1α in ATF3 KO mice ameliorated IRI-induced liver damage in parallel with the downregulation of IL-17A in ATF3-deficient mice. These findings demonstrated that ATF3 deficiency activated mTOR/p70S6K/HIF-1α signaling, which was crucial for the modulation of TLR4-driven inflammatory responses and T cell development. The present study provides potential therapeutic targets for the treatment of liver IRI followed by liver transplantation