The impact of digital empowerment on the economic openness of the textile industry in Keqiao based on a sustainable environment.

Based on the framework theory of industrial digitization, digital industrialization, digital governance and digital value-added in a sustainable environment, this paper systematically studies the relevant elements of governance and value distribution in the sustainable environment of global trade, and its impact on the development path of human beings. This paper explores the way to embed digital technology into the global value chain to realize digital empowerment, measures the competitiveness index of Keqiao's textile industry in the global value chain, analyzes the technical and environmental challenges faced by China's textile industry in the digital age, and proposes the corresponding countermeasures to deal with the impact of global value chain participation and to improve the international competitiveness of China's textile industry.

Manual and Semi-Automated Measurement and Calculation of Osteosarcoma Treatment Effect Using Whole Slide Image and Qupath.

INTRODUCTION: In osteosarcoma, the most significant indicator of prognosis is the histologic changes related to tumor response to preoperative chemotherapy, such as necrosis. We have developed a method to measure the osteosarcoma treatment effect using whole slide image (WSI) with an open-source digital image analytical software Qupath. MATERIALS AND METHODS: In Qupath, each osteosarcoma case was treated as a project. All H&E slides from the entire representative slice of osteosarcoma were scanned into WSIs and imported into a project in Qupath. The regions of tumor and tumor necrosis were annotated, and their areas were measured in Qupath. In order to measure the osteosarcoma treatment effect, we needed to calculate the percentage of total necrosis area over total tumor area. We developed a tool that can automatically extract all values of tumor and necrosis areas from a Qupath project into an Excel file, sum these values for necrosis and whole tumor respectively, and calculate necrosis/tumor percentage. CONCLUSION: Our method that combines WSI with Qupath can provide an objective measurement to facilitate pathologist's assessment of osteosarcoma response to treatment. The proposed approach can also be used for other types of tumors that have clinical need for post-treatment response assessment.

Techno-economic analysis of an HRES with fuel cells, solar panels, and wind turbines using an improved Al-Biruni algorithm.

This research demonstrates the application of novel optimization methods in the realm of renewable energy and contributes to the development of environmentally friendly electricity generation and consumption. In this study, an improved version of the Al-Biruni algorithm has been proposed for Hybrid Renewable Energy Systems (HRES) optimization, which includes fuel cells, photovoltaic cells, and windmills. The algorithm considers supply, demand, and energy storage constraints and seeks the best combination of energy sources to meet load demand while reducing total system cost. Inspired by ancient Iranian philosopher Abu Biruni, the proposed method includes modifications to explore solution space efficiently and improve answer value. The proposed HRES model is applied to a case study from Dunhuang City, China, and its findings are validated by comparing it with other optimization approaches. The Modified Al-Biruni Earth Radius (MBER) algorithm is found to be the most efficient and reliable system, costing 4.23 million units of currency. Compared to other optimization approaches, MBER exhibited a total cost of 4.1 million US dollars, 0.009, 3.7, 3.7, LPSP, and 356 h per year. The overall cost is 5.26 million units of currency with a 0.5% Loss of Power Supply Probability (LPSP), which directly impacts system performance and dependability. The improved Al-Biruni algorithm can efficiently optimize the system, reduce costs, and increase load supply, contributing to the growth of renewable energy sources and the application of advanced meta-heuristic techniques in complex energy systems.