Research on Mode and Risk Prevention of Agricultural Supply Chain Finance based on E-commerce

The rapid development of e-commerce has a profound impact on agricultural supply chain finance (ASCF), which is of great significance to enhance the resilience of agricultural economic development, realize the poverty alleviation effect of agricultural enterprises, integrate agricultural supply chain resources and solve the financing difficulties of agricultural enterprises. We analyze the participants and functions of the ASCF mode based on e-commerce, and the contract framework of various participants when they operate in the ASCF platform in this paper. Based on the agricultural industry chain, we analyze the operation process of accounts receivable financing mode, inventory financing mode and prepayment financing mode based on E-commerce. Finally, in view of the natural risks, credit risks, logistics risks, technical risks and legal risks that may exist in ASCF based on e-commerce, the corresponding countermeasures are put forward from the aspects of dispersing natural risks, building digital credit risk assessment system, building agricultural logistics network system, improving technical risk monitoring system, and improving relevant laws and regulations policy recommendations

Research on agricultural supply chain finance supporting sustainable poverty reduction under the background of digital technology

From the perspective of financial services, management services and coordination services, this paper analyzes the internal mechanism of agricultural supply chain finance (ASCF) to help sustainable poverty reduction (SPR). The internal and external driving forces of ASCF for SPR are also explored. Among them, the internal driving forces include industrial upgrading and financial transformation; External driving forces include technological change, policy guidance and market drive. Based on the background of digital technology, the green agricultural supply chain finance (GASCF) model has been innovatively proposed. We mainly analyze the core elements and platform structure of GASCF, and focus on the process design and key points of the three modules of the GASCF platform: risk control port, credit port and capital port. Finally, we analyze the practical difficulties of green agricultural supply chain finance in helping sustainable poverty reduction, such as the lack of comprehensive management ability of the organization, the insufficient application of digital technology, the imperfect institutional environment and the lack of compound talents. And we put forward accordingly a four in one path of GASCF helping SPR, which is Government standardizing and leading, assistance from financial institutions, driven by industry subjects and Co governance of Social Service

Research on the Realization Path of Intelligent Logistics in the “New Retail” Era

New retail is the product of innovation and transformation of e-commerce, physical retail and modern logistics. New retail relies on omni-channel logistics based on supply chain integration, order-driven precise logistics service and high intensity urban distribution carrying capacity, which has brought huge impacts and development opportunities to the logistics industry. At present, there are limitations in China\u27s intelligent logistics, both in terms of logistics infrastructure construction, logistics information services, and regulatory guarantee systems, which restrict the development of new retail . In order to realize the high-quality support of new retail by intelligent logistics, a trinity of intelligent logistics construction path of government guidance, market leadership, and social co-governance is proposed. We should accelerate the construction of intelligent logistics infrastructure under the guidance of the government, give full play to the leading role of the market to build an intelligent logistics information platform, and build a multi-security logistics security system through joint governance of all sectors of society to meet the overall objective of the high-quality support of logistics for new retail

Research on the application of smart supply chain finance in the financing of private scientific and technological enterprises in China

Supply chain finance (SCF) has experienced the development stages of offline SCF, online traditional SCF, and Internet SCF, and has developed to the stage of smart supply chain finance (SSCF) driven by digital technology in China. We analyze the theoretical framework of SSCF model from three aspects: loose coupling alliance organizational structure, visual operation and management process and symbiotic multi-agent coordination mechanism. In the financing of private scientific and technological enterprises, SSCF will show smart effects such as intelligent decision-making, harmonious service, penetrating management and digital risk control. Further, the process of SSCF providing financing services for private scientific and technological enterprises is designed. Finally, in view of the problems and challenges faced by private scientific and technological enterprises in the application of SSCF, we put forward countermeasures and suggestions from the aspects of expanding the dimension of smart transformation, building a perfect regulatory system and legal system, and strengthening the cultivation of compound talents in this paper

SAM-Deblur: Let Segment Anything Boost Image Deblurring

Image deblurring is a critical task in the field of image restoration, aiming to eliminate blurring artifacts. However, the challenge of addressing non-uniform blurring leads to an ill-posed problem, which limits the generalization performance of existing deblurring models. To solve the problem, we propose a framework SAM-Deblur, integrating prior knowledge from the Segment Anything Model (SAM) into the deblurring task for the first time. In particular, SAM-Deblur is divided into three stages. First, We preprocess the blurred images, obtain image masks via SAM, and propose a mask dropout method for training to enhance model robustness. Then, to fully leverage the structural priors generated by SAM, we propose a Mask Average Pooling (MAP) unit specifically designed to average SAM-generated segmented areas, serving as a plug-and-play component which can be seamlessly integrated into existing deblurring networks. Finally, we feed the fused features generated by the MAP Unit into the deblurring model to obtain a sharp image. Experimental results on the RealBlurJ, ReloBlur, and REDS datasets reveal that incorporating our methods improves NAFNet's PSNR by 0.05, 0.96, and 7.03, respectively. Code will be available at \href{https://github.com/HPLQAQ/SAM-Deblur}{SAM-Deblur}.Comment: Under revie

Integrating Network Centrality and Node-Place Model to Evaluate and Classify Station Areas in Shanghai

Transit-oriented development (TOD) is generally understood as an effective urban design model for encouraging the use of public transportation. Inspired by TOD, the node-place (NP) model was developed to investigate the relationship between transport stations and land use. However, existing studies construct the NP model based on the statistical attributes, while the importance of travel characteristics is ignored, which arguably cannot capture the complete picture of the stations. In this study, we aim to integrate the NP model and travel characteristics with systematic insights derived from network theory to classify stations. A node-place-network (NPN) model is developed by considering three aspects: land use, transportation, and travel network. Moreover, the carrying pressure is proposed to quantify the transport service pressure of the station. Taking Shanghai as a case study, our results show that the travel network affects the station classification and highlights the imbalance between the built environment and travel characteristics

Research on the Innovative Application of Digital Supply Chain Finance in Private Science and Technology Enterprises in China

Based on the comprehensive impact of digital technologies on supply chain finance in different application scenarios, we analyze operation procedures optimization and critical control points of four innovation modes about digital supply chain finance in private science and technology enterprises, which are digital supply chain finance model based on prepayment, digital supply chain finance model based on inventory pledge, digital supply chain finance model of based on accounts receivable and digital supply chain finance model of based on intellectual property pledge in this paper. At present, there are some problems in digital supply chain finance, such as weak risk control, inadequate technology application and imperfect legal system. In order to promote the efficient implementation of digital supply chain finance to private science and technology enterprises, the leading institutions of supply chain finance should attach importance to the governance strategies such as controlling the source of risk to avoid risk, accelerating the ecological innovation of digital technology enabling, and improving the legal system to regulate development

Using Spatial Semantics and Interactions to Identify Urban Functional Regions

The spatial structures of cities have changed dramatically with rapid socio-economic development in ways that are not well understood. To support urban structural analysis and rational planning, we propose a framework to identify urban functional regions and quantitatively explore the intensity of the interactions between them, thus increasing the understanding of urban structures. A method for the identification of functional regions via spatial semantics is proposed, which involves two steps: (1) the study area is classified into three types of functional regions using taxi origin/destination (O/D) flows; and (2) the spatial semantics for the three types of functional regions are demonstrated based on point-of-interest (POI) categories. To validate the existence of urban functional regions, we explored the intensity of interactions quantitatively between them. A case study using POI data and taxi trajectory data from Beijing validates the proposed framework. The results show that the proposed framework can be used to identify urban functional regions and promotes an enhanced understanding of urban structures

Iterative Learning Identification

An iterative learning identification method is proposed for curve identification problems. The basic idea is to convert the curve identification problem into an optimal tracking control problem. The measured trajectories are regarded as the desired trajectories to be optimally tracked and the curve to be identified is taken as a virtual control function. A high-order learning updating law is applied. A convergence condition is obtained in a general problem setting. Two case studies, which are related to the aerodynamic drag coefficient curve extraction from actual flight testing data, are presented to show the practical usefulness of the proposed method. 1 Introduction In many system identification tasks, identification of parameters is actually a special case of nonlinear function or curve identification. On the other hand, curve identification or extraction from system testing data can be easily converted to parameter identification through a parameterization procedure of the curve..

Solving Competitive Location Problems with Social Media Data Based on Customers’ Local Sensitivities

Competitive location problems (CLPs) are a crucial business concern. Evaluating customers’ sensitivities to different facility attractions (such as distance and business area) is the premise for solving a CLP. Currently, the development of location-based services facilitates the use of location data for sensitivity evaluations. Most studies based on location data assumed the customers’ sensitivities to be global and constant over space. In this paper, we proposed a new method of using social media data to solve competitive location problems based on the evaluation of customers’ local sensitivities. Regular units were first designed to spatially aggregate social media data to extract samples with uniform spatial distribution. Then, geographically weighted regression (GWR) and the Huff model were combined to evaluate local sensitivities. By applying the evaluation results, the captures for different feasible locations were calculated, and the optimal location for a new retail facility could be determined. In our study, the five largest retail agglomerations in Beijing were taken as test cases, and a possible new retail agglomeration was located. The results of our study can help people have a better understanding of the spatial variation of customers’ local sensitivities. In addition, our results indicate that our method can solve competitive location problems in a cost-effective way