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Dynamic Collaborative Mechanism of Cross-Border E-Commerce Dual-Channel Supply Chain Under Carbon Quota Constraints
Get PDFIn the context of the accelerated global carbon neutrality initiative and the formal enactment of the European Union's Carbon Border Adjustment Mechanism (CBAM), the low-carbon transformation of cross-border e-commerce supply chains has become an inevitable trend. This study examines a dual-channel supply chain comprising manufacturers, e-commerce platforms, logistics service providers—including overseas warehouses and direct shipping—and consumers, all constrained by carbon quotas. Considering heterogeneity in consumer preferences for price sensitivity and environmental sustainability, demand functions are developed to differentiate between price-sensitive and green-preference consumers. A three-stage Stackelberg game model is constructed, with the platform as the leader and manufacturers as followers, to analyze optimal pricing and production strategies under carbon quota constraints. The model is solved via backward induction to obtain equilibrium solutions, which are validated through numerical case analysis. The findings indicate that: (1) Carbon quota constraints significantly influence supply chain pricing strategies and channel selection, compelling firms to internalize carbon costs into their decision-making processes; (2) Enhancing consumers' green preferences effectively incentivizes manufacturers to invest in emission reductions and provides a market foundation for platforms to implement green premium strategies; (3) As the leader, the platform's pricing and channel allocation strategies play a decisive role in the overall profitability and carbon emission performance of the supply chain. These insights offer theoretical contributions and strategic guidance for cross-border e-commerce enterprises aiming to optimize economic and environmental outcomes in alignment with the "dual carbon" objectives
Visible Body Anxiety: The Mediatized Management Practices of Quantifying Body Shapes and Physicality
Get PDFThe proliferation of fitness and exercise-related social media, applications, and wearable devices has provided individuals with convenient tools for body management. These technological means have enabled the mediatized management of bodies, permeating various aspects of daily life. However, this process has also raised tensions regarding the relationship between individuals and media control. This study adopts media visibility and digital rationality as theoretical perspectives, employing qualitative interviews and participatory observation to explore the impact of fitness applications and devices on users' body management practices. It investigates how users navigate the visible/invisible dichotomy of "highlighting" and "concealing" within the data relationships of "quantifying body shapes." The findings reveal that when users face motivational deficits, they often utilize visual body tracking tools to monitor and record bodily data, enabling real-time observation of bodily changes. While "self-quantification" facilitates body management, it also generates new challenges and anxieties. The prevalence of flow-dominated quantification aesthetics leads users to excessively focus on body image and overly rely on technological tools, thereby neglecting the natural state of the body and self-perception, which may adversely affect users' physical and mental health
Survey on Privacy Preserving in Crowd Sensing
Get PDFAs an emerging sensing technology, crowd sensing has gained wide attention in many application fields and is developing rapidly. However, with the popularization of crowd participation in sensing tasks, the risk of user privacy leakage is also increasing, which becomes an important problem to be solved urgently. When users participate in sensing tasks, they need to upload personal information or sensor data, which often contains sensitive information. Without effective privacy protection measures, user privacy may be leaked or abused. The core goal of privacy protection is to ensure that users' private information will not be leaked when they participate in the task. This paper analyzes the related research progress of privacy protection in the field of crowd sensing, and summarizes the main challenges currently faced
Synthesis and Crystal Structure as well as Cytotoxicity Analysis of Dichloro-Terpyridine-Copper Complex
Get PDFMalignant tumors, recognized as one of the most threatening diseases of the 20th century, continue to exhibit a rising incidence trend in the 21st century. Against this backdrop, metal complexes have attracted considerable attention due to their unique antitumor activities. In this study, we unexpectedly obtained a copper-based complex coordinated with 2,2':6',2''-Terpyridine and chloride anion ligands, and characterized its crystal structure using X-ray single-crystal diffraction technique. The cytotoxic effects of this metal complex against various tumor cell lines were evaluated through MTT assays, and the findings provide significant theoretical and practical foundations for developing novel anticancer drugs
Study on the Mechanism of miR-520d-5p and LMO4 in Regulating Thyroid Cancer Progression
Get PDFThe pathogenesis of thyroid cancer is closely related to environmental factors. Gene mutation and molecular biological changes of thyroid tissue caused by environmental changes are one of the important factors inducing thyroid cancer. Although the molecular mechanism of thyroid cancer is still not fully elucidated, with the development of molecular biology technology, more and more thyroid cancer-specific genetic changes and molecular markers have been excavated. This article systematically summarizes the current research progress of miR-520d-5p and LMO4 in thyroid cancer, and discusses how they participate in the regulation of the biological behavior of tumor cells and potential molecular signaling pathways, so as to provide new theoretical basis and ideas for the precise diagnosis and treatment of thyroid cancer
Study On the Detection of Dry Matter in Silage Corn Feed Based on Near Infrared Spectroscopy
Get PDFThis study explored the application of a portable near-infrared (NIR) spectrometer for analyzing silage corn feed quality, specifically focusing on developing a quantitative detection model for dry matter content. Spectral data were collected within the 855-1890 nm range using a portable NIR spectrometer, and the dataset was partitioned into calibration and prediction sets using the SPXY algorithm. An Extreme Learning Machine (ELM) model optimized by Particle Swarm Optimization (PSO) was employed for modeling. Five preprocessing methods were evaluated: Moving Average Filter (MAF), Savitzky-Golay Filter (SGF), Multiplicative Scatter Correction (MSC), Standard Normal Variate (SNV) transformation, and First Derivative (FD). To enhance model performance, feature wavelengths were selected using three methods: Bootstrap Soft Shrinkage (BOSS), Competitive Adaptive Reweighted Sampling (CARS), and Iterative Retained Information Variable (IRIV). The optimal model combining SNV preprocessing with BOSS feature selection achieved a prediction correlation coefficient () of 0.8708 and Root Mean Square Error of Prediction (RMSEP) of 0.6802. These results demonstrate the potential of portable NIR spectroscopy for rapid dry matter content determination in silage corn feed
Analysis of Factors Influencing the Willingness to Accept Carbon Inclusion Market Based on Structural Equation Modeling——Taking Xi'an City as an Example
Get PDFThe purpose of this paper is to investigate the willingness of Xi'an residents to accept carbon benefits, using a combination of principal component analysis and structural equation modeling. First, the data were collected from 16 questions using a five-point scale, and after confirming that the data were suitable for principal component analysis by KMO and Bartlett's test of sphericity, five principal components were extracted, with a cumulative variance explained rate of 87.116%, which realized dimensionality reduction and retained the key information. Second, structural equation modeling was used to construct the model with cognitive situation and decision-making behavior as latent variables. It was found that the perception of the carbon inclusion program's effect on carbon emissions significantly affects the cognitive situation, the greatest impact on satisfaction is whether participants are willing to promote the Carbon for All program, and the use of the carbon inclusion platform by people around us has the greatest impact on the practice situation. This study provides a basis for in-depth understanding of residents' willingness to accept carbon benefits, as well as a reference for the promotion and development of carbon benefits
Water Quality Assessment and Analysis of Causes at Dajin Lake, a World Natural Heritage Site in Danxia, China
Get PDFThe World Heritage Convention requires that heritage sites submit periodic reports every six years. During the preparation of the third periodic report for the Danxia Series of World Natural Heritage Sites in China, it was found that previous reports were relatively brief, particularly lacking supplementary materials regarding pollution factors. Therefore, this study takes Dajin Lake within the Danxia Taining World Natural Heritage Site in China as its research object. Based on water quality monitoring data from 2019, seven water quality indicators were selected, including permanganate index (CODMn), chemical oxygen demand (COD), dissolved oxygen (DO), biochemical oxygen demand (BOD5), ammonia nitrogen (NH3-N), total nitrogen (TN), and total phosphorus (TP), to evaluate the water quality of Dajin Lake and analyze the causes, with the aim of understanding the current state of Dajin Lake's water quality
Research on the Application of Python Big Data in Financial Analysis
Get PDFWith the rapid development of big data technology and the widespread use of the Python programming language in data science, financial analysis is gradually shifting from traditional manual calculations and analysis to automated and intelligent approaches. This paper explores the application of Python in financial analysis within a big data environment, examining its specific uses in data collection, processing, analysis, and the automation of financial reporting. First, it introduces the advantages of Python and big data technology, along with their integration methods. Next, it outlines the basic concepts and common techniques of financial analysis. Then, it delves into Python’s applications in financial analysis, including data preprocessing, financial statement analysis, predictive modeling, and risk management. Through case studies, the paper demonstrates how Python enhances the efficiency and accuracy of financial analysis for businesses. Finally, it summarizes the current state of Python’s application in financial analysis, addressing challenges such as data quality issues and the integration of artificial intelligence, while also exploring future trends. This study provides practical guidance for professionals in the financial sector and offers insights for future research
Exploration of the Human-Computer Synergy Paradigm for Literary Creation via the Lens of Digital Humanities
Get PDFIn order to study the human-computer collaboration paradigm of literary creation in the field of digital humanities, and to analyze the application and influence of human-computer collaboration technology in literary creation, this paper adopts the methods of literature analysis and case study to sort out the evolution of literary creation paradigm from “author-centered” to “reader-centered” to “digital interaction”. Using literature analysis and case study methods, this paper examines the evolution of the literary creation paradigm from “author-centered” to “reader-centered” to “digital interaction”, and explores the application and impact of human-computer collaborative technology in literary creation. The study finds that the integration of human-computer collaborative technology promotes the diversification of creative subjects, methods and platforms, and promotes the development of cross-media narrative and multimodal expression of texts; however, at the same time, AI creation faces the problems of insufficient expression of emotions and difficulties in defining originality, and the copyright attribution of the works and the subjectivity of the authors have triggered legal and ethical discussions. This paper enriches the theory of human-computer collaborative creation in the field of digital humanities, and provides a reference for the innovation of future literary creation paradigms