Global warming is mainly influenced by factors such as energy consumption, human development, and economic activities, but there is no consensus among researchers and there is relatively little ...research literature on less developed countries. Therefore, this study attempts to explore the impact of renewable energy consumption, human development and economic growth on climate change from a macroeconomic perspective for 105 countries worldwide over the period 1990–2019 by constructing a panel vector autoregressive (PVAR) model and using generalized method of moments (GMM) and panel impulse response analysis. The analysis includes four panels of high-income, upper-middle-income, lower-middle-income, and low-income countries. The results of the study find that economic growth, FDI, trade openness, industrialization, renewable energy consumption and HDI have different impacts on climate change (CO
2
emissions) in different regions during the sample period. Specifically, in the four panels, economic growth, industrialization, FDI, and trade openness all play a varied role in aggravating environmental pollution (CO
2
emissions). In high-income and upper-middle-income countries, industrialization has a positive effect on CO
2
emissions, while FDI has a negative impact, which supports the pollution halo hypothesis. However, both have a positive impact on CO
2
emissions in lower-middle-income and low-income countries. The results also found that except for upper-middle-income countries, trade openness and renewable energy consumption help reduce CO
2
emissions, while renewable energy consumption has little effect on suppressing CO
2
emissions in low-income countries. In addition, HDI has promoted CO
2
emissions in upper-middle-income and lower-middle-income countries, but has curbed CO
2
emissions in high-income countries. Therefore, under the premise of not affecting economic growth and HDI, those empirical results will not only help decision-makers formulate appropriate renewable energy policies, but also are of great significance to the realization of a healthy and sustainable global environment.
Abstract
The objective of this research is to use annual data from 1990 to 2021 to examine the long- and short-run dynamic relationships among China’s trade openness (TRO), foreign direct investment ...(FDI), capital formation (
K
), and industrial economic growth (IEG) using the Autoregressive Distribution Lag (ARDL) method. Firstly, the results of the ARDL co-integration tests show that there is a long-run co-integration relationship among TRO, FDI,
K,
and IEG. Secondly, from a path of influence perspective, both the long- and short-run relationships are almost the same. Specifically, TRO, FDI, and
K
all have positive effects on IEG and vice versa, which supports the feedback hypothesis. However, contrary to the short-run relationship, TRO and
K
have a small negative effect on IEG, but this is not statistically significant. Finally,
K
and TRO positively affect FDI, while FDI negatively affects
K
, although the effect is minimal and negligible at the 10% significance level. On the contrary, they are not statistically significant in the long run. These results support the theory that technological innovation in the trade, investment and capital system based on economic and market capital can stimulate the development of China’s industrial economy.
The main purpose of this study is to analyze the relationship between urban public infrastructure, CO
2
emissions and economic growth in China for the period 1990–2019 using the Dynamic Conditional ...Correlation Multivariate GARCH model (DCC-MGARCH) and Autoregressive Distributed Lagged Model (ARDL). According to the estimated results of the DCC-MGARCH, there is a positive influential effect among the economic growth, urban public infrastructure and CO
2
emissions, while there is a negative influential effect between the urban public infrastructure and CO
2
emissions, but the duration of volatility between the urban public infrastructure and CO
2
emissions is relatively weak. Among such relationships, the conditional correlation also shows there is an effect in
S
-shape between the urban public infrastructure and economic growth, but the trend variation between the urban public infrastructure and CO
2
emissions shows an inverted “
U
-shape” of Environmental Kuznets Curve Theory. The results of the ARDL-Bounds test show that there are long-term co-integration relationships and short-term dynamic correlation among all models. Also, the results of error correction terms show that the speed deviating economic growth and CO
2
emissions from the long-term equilibrium and CO
2
emissions deviating from the long-term equilibrium is larger than that of the urban public infrastructure, which indicates that the relationship between the economic growth and CO
2
emissions is relatively strong.
•HYDRUS-1D model was modified by coupling with the dualKc approach.•Water–salt fate and yield were simulated for three crops under shallow water table.•Water use was evaluated in a canal system with ...fragmented crops simultaneously.•New insights were provided for improving water use efficiency and saving water.
Water saving in irrigation is a key issue in the upper Yellow River basin. Excessive irrigation leads to water waste, water table rising and increased salinity. Land fragmentation associated with a large dispersion of crops adds to the agro-hydrological complexity of the irrigation system. The model HYDRUS-1D, coupled with the FAO-56 dual crop coefficient approach (dualKc), was applied to simulate the water and salt movement processes. Field experiments were conducted for maize, sunflower and watermelon crops in the command area of a typical irrigation canal system in Hetao Irrigation District during 2012 and 2013. The model was calibrated and validated in three crop fields using two-year experimental data. Simulations of soil moisture, salinity concentration and crop yield fitted well with the observations. The irrigation water use was then evaluated and results showed that large amounts of irrigation water percolated due to over-irrigation but their reuse through capillary rise was also quite large. That reuse was facilitated by the dispersion of crops throughout largely fragmented field, thus with fields reusing water percolated from nearby areas due to the rapid lateral migration of groundwater. Beneficial water use could be improved when taking this aspect into account, which was not considered in previous researches. The non-beneficial evaporation and salt accumulation into the root zone were found to significantly increase during non-growth periods due to the shallow water tables. It could be concluded that when applying water saving measures, close attention should be paid to cropping pattern distribution and groundwater control in association with irrigation scheduling and technique improvement.
The recent advances in low earth orbit (LEO) satellites enable the satellites to provide task processing capability for remote Internet-of-Things (IoT) mobile devices (IMDs) without proximal ...multiaccess edge computing (MEC) servers. In this article, by leveraging the LEO satellites, a novel MEC framework for terrestrial-satellite IoT is proposed. With the aid of terrestrial-satellite terminal (TST), the computation offloading from IMDs to LEO satellites is divided into two stages in the ground and space segments. In order to minimize the weighted-sum energy consumption of IMDs, we decompose the formulated problem into two layered subproblems: 1) the lower layer subproblem minimizing the latency of space segment, which is solved by sequential fractional programming with attaining the first-order optimality and 2) the upper layer subproblem that is solved by exploiting the convex structure and applying the Lagrangian dual decomposition method. Based on the solutions to the two layered subproblems, an energy-efficient computation offloading and resource allocation algorithm (E-CORA) is proposed. By simulations, it is shown that: 1) there exists a specific amount of offloading bits, which can minimize the energy consumption of IMDs and the proposed E-CORA outperforms full offloading and local computing only; 2) larger transmit power of the TST helps to save the energy of IMDs; and 3) by increasing the number of visible satellites, the ratio of offloading bits increases while the energy consumption of IMDs can be decreased.
In this paper, we concentrate on the robust multi-objective optimization (MOO) for the tradeoff between energy efficiency (EE) and spectral efficiency (SE) in device-to-device (D2D) communications ...underlaying heterogeneous networks (HetNets). Different from traditional resource optimization, we focus on finding robust Pareto optimal solutions for spectrum allocation and power coordination in D2D communications underlaying HetNets with the consideration of interference channel uncertainties. The problem is formulated as an uncertain MOO problem to maximize EE and SE of cellular users (CUs) simultaneously while guaranteeing the minimum rate requirements of both CUs and D2D pairs. With the aid of ε-constraint method and strict robustness, we propose a general framework to transform the uncertain MOO problem into a deterministic single-objective optimization problem. As exponential computational complexity is required to solve this highly non-convex problem, the power coordination and the spectrum allocation problems are solved separately, and an effective two-stage iterative algorithm is developed. Finally, simulation results validate that our proposed robust scheme converges fast and significantly outperforms the non-robust scheme in terms of the effective EE-SE tradeoff and the quality of service satisfying probability of D2D pairs.
In this paper, we propose a general framework to study the tradeoff between energy efficiency (EE) and spectral efficiency (SE) in massive multiple-input-multiple-output-enabled heterogenous networks ...while ensuring proportional rate fairness among users and taking into account the backhaul capacity constraint. We aim at jointly optimizing user association, spectrum allocation, power coordination, and the number of activated antennas, which is formulated as a multi-objective optimization problem maximizing EE and SE simultaneously. With the help of weighted Tchebycheff method, it is then transformed into a single-objective optimization problem, which is a mixed-integer non-convex problem and requires unaffordable computational complexity to find the optimum. Hence, a low-complexity effective algorithm is developed based on primal decomposition, where we solve the power coordination and number of antenna optimization problem and the user association and spectrum allocation problem separately. Both theoretical analysis and numerical results demonstrate that our proposed algorithm can fast converge within several iterations and significantly improve both the EE-SE tradeoff performance and rate fairness among users compared with other algorithms.
The discovery of new genes with novel functions is a major driver of adaptive evolutionary innovation in plants. Especially in woody plants, due to genome expansion, new genes evolve to regulate the ...processes of growth and development. In this study, we characterized the unique
transcription factor family in
×
, which is associated with secondary metabolism. Twenty VeA genes were characterized systematically on their phylogeny, genomic distribution, gene structure and conserved motif, promoter binding site, and expression profiling. Furthermore, through ChIP-qPCR, Y1H, and effector-reporter assays, it was demonstrated that PagMYB128 directly regulated
to influence the biosynthesis of secondary metabolites. These results provide a basis for further elucidating the function of
gene in poplar and its genetic regulation mechanism.
Unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) has been considered as a promising approach to offering extensive coverage and massive computing capacities for Internet of Things ...(IoT). In this letter, we propose a novel multi-UAV-assisted multi-access MEC model by allowing each IoT user to offload task bits to multiple MEC servers deployed at UAVs simultaneously for parallel computing, which can effectively reduce the energy consumption of users and UAVs. The weighted sum energy consumption of UAVs and users is minimized by jointly optimizing the bit allocation, transmit power, CPU frequency, bandwidth allocation and UAVs' trajectories. Due to the non-convexity of the formulated problem, it is decomposed into two subproblems and a joint resource allocation and trajectory design algorithm is proposed by alternative optimization. Simulation results show that our proposed algorithm with multiple radio access outperforms the fixed trajectory, fixed bandwidth allocation and the single access schemes.
Abstract Individualized treatment is a promising clinical strategy for lung cancer, and drug sensitivity testing is fundamental to this scheme. We aimed to develop an effective drug sensitivity test ...platform to support individualized treatment. We designed a microfluidic chip-based, three-dimensional (3D) co-culture drug sensitivity test platform. A mono-lung cancer cell line, a mixture of lung cancer and stromal cell lines, and cells from fresh lung cancer tissues were cultured in 3D under continuous media supplementation, mimicking the actual tumor microenvironment in vivo. The cells were treated with anti-cancer drugs according to a gradient concentration generator inside the chips to screen the appropriate chemotherapy schemes. We successfully cultured cell lines or primary cells with this device. We also smoothly assayed the sensitivities of different anti-cancer drugs in parallel and accurately screened appropriate-dose, single and combined-drug chemotherapy schemes for eight patients. Our microfluidic device is a simple, reliable, and high-throughput platform to test drug sensitivity. It would be possible for chemotherapists to screen the appropriate chemotherapy schemes to guide individualized treatment in lung cancer.
PDF
