The Research of Product Graphical Information Sharing Technology of Virtual Manufacturing Enterprise in E-Commerce Environment

This paper has built a product model by UML and corresponding Product Schema. Then we have illuminated transmit mechanism of the product information by a dumbbell XML document. At last, we have pointed out the direction of the research. This research will provide a significative explore to the product data interchange between the members of virtual manufacturing enterprise in e-commerce environmen

A Robust Archived Differential Evolution Algorithm for Global Optimization Problems

Abstract—A robust archived differential evolution algorithm is put forward by means of embedding a flexibility processing operator and an efficiency processing operator based on original DE and ADE. A special constraint-handling mechanism based on dynamic penalty functions and fitness calculation of individuals is adopted in the proposed method to deal with various constraints effectively, which is further extended by means of a flexibility processing operator so as to make it suitable for different type problems, including those with or without constraint(s) and those with continuous, discrete or mixed discrete-continuous variables. Furthermore, an archive of solutions is maintained during the evolutionary process so as to keep the useful information of previous solutions and local optima for the estimation of new solutions. Based on the archive of solutions, an iterative control operator and an efficiency processing operator are designed in the algorithm. The former guides the evolutionary process towards a promising search space, avoiding unnecessary and worthless search. The latter improves the local searching efficiency and the final searching quality. Experimental results based on a suite of six well-known optimization problems reveal that the proposed algorithm is robust, effective, efficient and suitable for different type global optimization problems. Index Terms—Global optimization, differential evolution, constraint handling, archived solutions, iterative control I

Data from: Contrasting effects of ectomycorrhizal and arbuscular mycorrhizal tropical tree species on soil nitrogen cycling: the potential mechanisms and corresponding adaptive strategies

While it is increasingly recognized that ectomycorrhizal (ECM) and arbuscular mycorrhizal (AM) tree species vary in their effects on soil nitrogen (N) cycling, little is known about the mechanisms causing and how ECM and AM trees adapt to this variation. Using monoculture plots of six ECM and eight AM tropical trees planted in a common garden, we examined whether the contrasting effects of ECM and AM trees on soil N cycling could be explained by their differences in plant traits. Furthermore, rhizosphere effects on soil N transformations and soil exploration by fine roots were also measured to assess whether ECM and AM trees differed in N acquisition capacities. Results showed that soil NH 4+N concentration, net N mineralization and net nitrification rates were markedly lower, but soil C:N ratio was significantly higher beneath ECM trees than beneath AM trees. This more closed N cycling caused by ECM trees was attributed to their resource-conservative traits, especially the poorer leaf litter decomposability compared with AM trees. To adapt to their induced lower soil N availability, ECM trees were found to have greater rhizosphere effects on NO 3-N concentration, net N mineralization and net nitrification rates to mine N, and higher soil exploration in terms of root length density to scavenge N from soils, indicating that these two strategies work in synergy to meet N demand of ECM trees. These findings suggest that ECM and AM trees have contrasting effects on soil N cycling owing to their differences in leaf litter decomposability and correspondingly possess different N acquisition capacities

Efficacy and safety of umbilical cord mesenchymal stem cells for the treatment of patients with COVID-19

OBJECTIVES: The coronavirus disease (COVID-19) outbreak has catastrophically threatened public health worldwide and presented great challenges for clinicians. To date, no specific drugs are available against severe acute respiratory syndrome coronavirus 2. Mesenchymal stem cells (MSCs) appear to be a promising cell therapy owing to their potent modulatory effects on reducing and healing inflammation-induced lung and other tissue injuries. The present pilot study aimed to explore the therapeutic potential and safety of MSCs isolated from healthy cord tissues in the treatment of patients with COVID-19. METHODS: Twelve patients with COVID-19 treated with MSCs plus conventional therapy and 13 treated with conventional therapy alone (control) were included. The efficacy of MSC infusion was evaluated by changes in oxygenation index, clinical chemistry and hematology tests, immunoglobulin (Ig) levels, and pulmonary computerized tomography (CT) imaging. The safety of MSC infusion was evaluated based on the occurrence of allergic reactions and serious adverse events. RESULTS: The MSC-treated group demonstrated significantly improved oxygenation index. The area of pulmonary inflammation decreased significantly, and the CT number in the inflammatory area tended to be restored. Decreased IgM levels were also observed after MSC therapy. Laboratory biomarker levels at baseline and after therapy showed no significant changes in either the MSC-treated or control group. CONCLUSION: Intravenous infusion of MSCs in patients with COVID-19 was effective and well tolerated. Further studies involving a large cohort or randomized controlled trials are warranted

Estimating Relative Chlorophyll Content in Rice Leaves Using Unmanned Aerial Vehicle Multi-Spectral Images and Spectral–Textural Analysis

Leaf chlorophyll content is crucial for monitoring plant growth and photosynthetic capacity. The Soil and Plant Analysis Development (SPAD) values are widely utilized as a relative chlorophyll content index in ecological agricultural surveys and vegetation remote sensing applications. Multi-spectral cameras are a cost-effective alternative to hyperspectral cameras for agricultural monitoring. However, the limited spectral bands of multi-spectral cameras restrict the number of vegetation indices (VIs) that can be synthesized, necessitating the exploration of other options for SPAD estimation. This study evaluated the impact of using texture indices (TIs) and VIs, alone or in combination, for estimating rice SPAD values during different growth stages. A multi-spectral camera was attached to an unmanned aerial vehicle (UAV) to collect remote sensing images of the rice canopy, with manual SPAD measurements taken immediately after each flight. Random forest (RF) was employed as the regression method, and evaluation metrics included coefficient of determination (R2) and root mean squared error (RMSE). The study found that textural information extracted from multi-spectral images could effectively assess the SPAD values of rice. Constructing TIs by combining two textural feature values (TFVs) further improved the correlation of textural information with SPAD. Utilizing both VIs and TIs demonstrated superior performance throughout all growth stages. The model works well in estimating the rice SPAD in an independent experiment in 2022, proving that the model has good generalization ability. The results suggest that incorporating both spectral and textural data can enhance the precision of rice SPAD estimation throughout all growth stages, compared to using spectral data alone. These findings are of significant importance in the fields of precision agriculture and environmental protection

Building a better foundation: improving root-trait measurements to understand and model plant and ecosystem processes

Trait-based approaches provide a useful framework to investigate plant strategies for resource acquisition, growth, and competition, as well as plant impacts on ecosystem processes. Despite significant progress capturing trait variation within and among stems and leaves, identification of trait syndromes within fine-root systems and between fine roots and other plant organs is limited. Here we discuss three underappreciated areas where focused measurements of fine-root traits can make significant contributions to ecosystem science. These include assessment of spatiotemporal variation in fine-root traits, integration of mycorrhizal fungi into fine-root-trait frameworks, and the need for improved scaling of traits measured on individual roots to ecosystem-level processes. Progress in each of these areas is providing opportunities to revisit how below-ground processes are represented in terrestrial biosphere models. Targeted measurements of fine-root traits with clear linkages to ecosystem processes and plant responses to environmental change are strongly needed to reduce empirical and model uncertainties. Further identifying how and when suites of root and whole-plant traits are coordinated or decoupled will ultimately provide a powerful tool for modeling plant form and function at local and global scales