Research on green supply chain performance evaluation of supermarket chain in China

The supply chain of supermarket chains is more systematic and close to the manufacturing industry, and supermarket chains generally have strong capital base to achieve GSCM. Therefore, the GSCM of supermarket chains has its own industry characteristics. The green supply chain construction of supermarket chains must be based on the characteristics of the industry and enterprises. This study uses sustainable development, refined management and SCM ideas to construct a green supply chain performance evaluation model suitable for China's supermarket chains. This study first analyzes the development status of green supply chains in China's supermarket chains, and systematically reviews relevant literature on GSCM. Through the study of GSCM experience, the evaluation indicator system (5 first-level indicators and 19 second-level indicators) and performance evaluation system suitable for the green supply chain of China's supermarket chains were constructed. Finally, taking the Wal-Mart supermarket in China as a case, comprehensively evaluate the GSCM of the supermarket and analyze the evaluation results

Common Correlated Effects Estimation for Dynamic Heterogeneous Panels with Non-Stationary Multi-Factor Error Structures

In this paper, we consider the estimation of a dynamic panel data model with non-stationary multi-factor error structures. We adopted the common correlated effect (CCE) estimation and established the asymptotic properties of the CCE and common correlated effects mean group (CCEMG) estimators, as N and T tend to infinity. The results show that both the CCE and CCEMG estimators are consistent and the CCEMG estimator is asymptotically normally distributed. The theoretical findings were supported for small samples by an extensive simulation study, showing that the CCE estimators are robust to a wide variety of data generation processes. Empirical findings suggest that the CCE estimation is widely applicable to models with non-stationary factors. The proposed procedure is also illustrated by an empirical application to analyze the U.S. cigar dataset

Common Correlated Effects Estimation for Dynamic Heterogeneous Panels with Non-Stationary Multi-Factor Error Structures

In this paper, we consider the estimation of a dynamic panel data model with non-stationary multi-factor error structures. We adopted the common correlated effect (CCE) estimation and established the asymptotic properties of the CCE and common correlated effects mean group (CCEMG) estimators, as N and T tend to infinity. The results show that both the CCE and CCEMG estimators are consistent and the CCEMG estimator is asymptotically normally distributed. The theoretical findings were supported for small samples by an extensive simulation study, showing that the CCE estimators are robust to a wide variety of data generation processes. Empirical findings suggest that the CCE estimation is widely applicable to models with non-stationary factors. The proposed procedure is also illustrated by an empirical application to analyze the U.S. cigar dataset

Estimating the Horizontal and Vertical Distributions of Pigments in Canopies of Ginkgo Plantation Based on UAV-Borne LiDAR, Hyperspectral Data by Coupling PROSAIL Model

Pigments are the biochemical material basis for energy and material exchange between vegetation and the external environment, therefore quantitative determination of pigment content is crucial. Unmanned Aerial Vehicle (UAV)-borne remote sensing data coupled with radiative transfer models (RTM) provide marked strengths for three-dimensional (3D) visualization, as well as accurate determination of the distributions of pigment content in forest canopies. In this study, Light Detection and Ranging (LiDAR) and hyperspectral images acquired by a multi-rotor UAV were assessed with the PROSAIL model (i.e., PROSPECT model coupled with 4SAIL model) and were synthetically implemented to estimate the horizontal and vertical distribution of pigments in canopies of Ginkgo plantations in a study site within coastal southeast China. Firstly, the fusion of LiDAR point cloud and hyperspectral images was carried out in the frame of voxels to obtain fused hyperspectral point clouds. Secondly, the PROSAIL model was calibrated using specific model parameters of Ginkgo trees and the corresponding look-up tables (LUTs) of leaf pigment content were constructed and optimally selected. Finally, based on the optimal LUTs and combined with the hyperspectral point clouds, the horizontal and vertical distributions of pigments in different ages of ginkgo trees were mapped to explore their distribution characteristics. The results showed that 22-year-old ginkgo trees had higher biochemical pigment content (increase 3.37–55.67%) than 13-year-old ginkgo trees. Pigment content decreased with the increase of height, whereas pigment content from the outer part of tree canopies showed a rising tendency as compared to the inner part of canopies. Compared with the traditional vegetation index models (R2 = 0.25–0.46, rRMSE = 16.25–19.37%), the new approach developed in this study exhibited significant higher accuracies (R2 = 0.36–0.60, rRMSE = 13.53–16.86%). The results of this study confirmed the effectiveness of coupling the UAV-borne LiDAR and hyperspectral image with the PROSAIL model for accurately assessing pigment content in ginkgo canopies, and the developed estimation methods can also be adopted to other regions under different conditions, providing technical support for sustainable forest management and precision silvicuture for plantations

Wireless Power Transfer Positioning System with Wide Range Direction-Guided Based on Symmetrical Triple-U Auxiliary Pad

An important area of research in electric vehicle wireless power transfer systems is the detection of the secondary pad, which is vital evidence to determine whether the vehicle is in the effective charging area. However, the detection based on sensors mostly will reconstruct the vehicle structure and has a limit on versatility in all kinds of vehicles and the applicability of magnetic couplers and the influence on the primary pad. Therefore, an auxiliary pad structure and corresponding positioning method for offset estimation utilizing the existing inverter and secondary pad in the vehicle system are proposed. Firstly, to satisfy the needs of different positioning heights and avoid the effect on the primary pad, a triple-U positioning auxiliary pad is designed to assist positioning. Secondly, the direction-guided trajectory and detection algorithm are proposed to modify the vehicle location in real-time after analyzing the corresponding equivalent mutual inductance feature trajectory, according to the magnetic field characteristics of various typical magnetic couplers intervened by the proposed triple-U auxiliary pad. Finally, a prototype system is built to validate the applicability and feasibility of the triple-U auxiliary pad, where the positioning accuracy is within 10 mm, and the maximum recognizable recognition range can reach 300 mm × 300 mm, and the direction-guided trajectory is accurate, which can satisfy the actual positioning requirements of electric vehicles

Ubiquitin-Like Protein SAMP1 and JAMM/MPN+ Metalloprotease HvJAMM1 Constitute a System for Reversible Regulation of Metabolic Enzyme Activity in Archaea

<div><p>Ubiquitin/ubiquitin-like (Ub/Ubl) proteins are involved in diverse cellular processes by their covalent linkage to protein substrates. Here, we provide evidence for a post-translational modification system that regulates enzyme activity which is composed of an archaeal Ubl protein (SAMP1) and a JAMM/MPN+ metalloprotease (HvJAMM1). Molybdopterin (MPT) synthase activity was found to be inhibited by covalent linkage of SAMP1 to the large subunit (MoaE) of MPT synthase. HvJAMM1 was shown to cleave the covalently linked inactive form of SAMP1-MoaE to the free functional individual SAMP1 and MoaE subunits of MPT synthase, suggesting reactivation of MPT synthase by this metalloprotease. Overall, this study provides new insight into the broad idea that Ub/Ubl modification is a post-translational process that can directly and reversibly regulate the activity of metabolic enzymes. In particular, we show that Ub/Ubl linkages on the active site residues of an enzyme (MPT synthase) can inhibit its catalytic activity and that the enzyme can be reactivated through cleavage by a JAMM/MPN+ metalloprotease.</p></div

Monitoring and alarm method for wildfires near transmission lines with multi‐Doppler weather radars

Abstract Monitoring and alarm play an important role in preventing trip‐out caused by wildfires for high‐voltage transmission lines. This paper proposes a multi‐Doppler weather radar‐based method for monitoring and alerting of wildfires near transmission lines. Firstly, characteristic parameters are mathematically proposed to distinguish wildfire's radar echoes. Then, the four‐site neighbourhood algorithm and the multithreading method are used to extract all possible wildfire echo units detected by various Doppler weather radars, and a cumulative probability is calculated to identify the wildfire. Finally, a regional block search method is used to quickly locate wildfire‐affected transmission towers. The membership function of spread time in the fuzzy set is proposed to determine the alarm level, which takes into account the influences of environment, topography, and vegetation on wildfire spread rate. The application to a provincial power grid demonstrates that the proposed method has an accuracy of 82.4%, a missing alarm rate of 27.4%, and a delay of fewer than 15 min. In addition, the joint observation of wildfires by multi‐Doppler weather radars and satellites indicates a promising application prospect for transmission line wildfire fighting

Solid Acid Catalyst WO3-ZrO2 for the Catalytic Deoxygenation of Jatropha Oil for the Preparation of Aviation Paraffin

WO3-ZrO2 solid acid catalysts were prepared by the impregnation method and characterized by X-ray diffraction (XRD), transmission electron microscope (TEM), Brunauer-Emmett-Teller (BET), and pyridine adsorbed IR spectroscopy (Py-IR). The catalysts were used for catalytic deoxygenation of Jatropha curcas oil. The optimal conditions for the deoxygenation of the generated oil were obtained by response surface methodology based on Box-Behnken four-factor experiments. Response surface methodology (RSM) was applied while determining the optimal conditions for the Jatropha oil deoxygenation percentage. The rate was calculated based on Box-Behnken four-factor experiments, with reaction temperature, catalyst amount, reaction time, and reaction pressure as independent variables and the deoxygenation of Jatropha curcas oil as response values. The optimal reaction conditions obtained were a temperature of 370 °C, pressure of 2 MPa, time of 7 h, and catalyst amount of 0.22 g. The deoxygenation percentage of the generated oil under the optimal conditions was 95.1%, which was close to the theoretical value, indicating that the model was reliable. The generated oil contained more jet fuel components, with 68.1% C8-C16, 12.0% isoalkanes, 14.2% cycloalkanes, and 8.9% aromatic compounds under the optimum conditions. This study provides an effective and simple method for preparation of bio-aviation fuel

Lys₂₄₀ is the active site of MoaE.

<p><b>(A)</b> Model of the active site of MPT synthase in complex with its substrate precursor Z. The MPT synthase large subunit (MoaE, blue) and C-terminal tail of the small subunit (SAMP1 Ct, red) are represented as ribbon diagrams. <b>(B)</b> Strains were grown anaerobically in YPC medium with DMSO as electron acceptor. Growth was monitored by cell density (OD₆₀₀ units at 70 h).</p