Personalized Perioperative Care for a Patient with a 10-Year-Old Postpartum Old Thrombus after Neoadjuvant Therapy for Breast Cancer

Breast cancer is one of the most common malignant tumors in women, and has become the main cause threatening women’s health. A case of breast cancer with neoadjuvant chemotherapy was discharged after active treatment and nursing.

Impacts of agri-food e-commerce on traditional wholesale industry:Evidence from China

Rapidly expanding studies investigate the effects of e-commerce on company operations in the retail market.However,the interaction between agri-food e-commerce(AEC)and the traditional agri-food wholesale industry(AWI)has not received enough attention in the existing literature.Based on the provincial panel data from 2013 to 2020 in China,this paper examines the effect of AEC on AWI,comprising three dimensions:digitalization(DIGITAL),agrifood e-commerce infrastructure and supporting services(AECI),and agri-food e-commerce economy(AECE).First,AWI and AEC are measured using an entropy-based combination of indicators.The results indicate that for China as a whole,AWI has remained practically unchanged,whereas AEC exhibits a significant rising trend.Second,the findings of the fixed-effect regression reveal that DIGITAL and AECE tend to raise AWI,whereas AECI negatively affects AWI.Third,threshold regression results indicate that AECI tends to diminish AWI with three-stage inhibitory intensity,which manifests as a first increase and then a drop in the inhibition degree.These results suggest that with the introduction of e-commerce for agricultural product circulation,digital development will have catfish effects that tend to stimulate the vitality of the conventional wholesale industry and promote technical progress.Furthermore,the traditional wholesale industry benefits financially from e-commerce even while it diverts part of the traditional wholesale circulation for agricultural products.

Impact of BRICS Trade Facilitation on China's Exports Using Cross-Border E-Commerce

With the rapid growth of the global digital economy, cross-border e-commerce, as an emerging form of trade, has gradually become a powerful engine to promote the development of global trade. BRICS is an important force in the global economy, and the progress of the BRICS countries' trade facilitation level has an important impact on the global trade environment. This paper conducts an in-depth study of the dynamic changes in BRICS trade facilitation from 2013 to 2022, and uses an extended gravity model to analyze the specific impact of this change on China's exports using cross-border e-commerce. The results show that although the BRICS countries have made some progress in trade facilitation, the overall level still needs to be improved, and there are obvious differences among member countries. However, the improvement of trade facilitation among BRICS countries has undoubtedly brought significant positive effects to China's exports using cross-border e-commerce.

Personalized Lower Limb Gait Reconstruction Modeling Based on RFA-ProMP

Personalized gait curves are generated to enhance patient adaptability to gait trajectories used for passive training in the early stage of rehabilitation for hemiplegic patients.The article utilizes the random forest algorithm to construct a gait parameter model,which maps the relationship between parameters such as height,weight,age,gender,and gait speed,achieving prediction of key points on the gait curve.To enhance prediction accuracy,an attention mechanism is introduced into the algorithm to focus more on the main features.Meanwhile,to ensure high similarity between the reconstructed gait curve and the normal one,probabilistic motion primitives(ProMP)are used to learn the probability distribution of normal gait data and construct a gait trajectorymodel.Finally,using the specified step speed as input,select a reference gait trajectory from the learned trajectory,and reconstruct the curve of the reference trajectoryusing the gait keypoints predictedby the parametermodel toobtain the final curve.Simulation results demonstrate that the method proposed in this paper achieves 98%and 96%curve correlations when generating personalized lower limb gait curves for different patients,respectively,indicating its suitability for such tasks.

Enhancing personalized exercise recommendation with student and exercise portraits

The exercise recommendation system is emerging as a promising application in online learning scenarios,providing personalized recommendations to assist students with explicit learning directions.Existing solutions generally follow a collaborative filtering paradigm,while the implicit connections between students(exercises)have been largely ignored.In this study,we aim to propose an exercise recommendation paradigm that can reveal the latent connections between student-student(exercise-exercise).Specifically,a new framework was proposed,namely personalized exercise recommendation with student and exercise portraits(PERP).It consists of three sequential and interdependent modules:Collaborative student exercise graph(CSEG)construction,joint random walk,and recommendation list optimization.Technically,CSEG is created as a unified heterogeneous graph with students’response behaviors and student(exercise)relationships.Then,a joint random walk to take full advantage of the spectral properties of nearly uncoupled Markov chains is performed on CSEG,which allows for full exploration of both similar exercises that students have finished and connections between students(exercises)with similar portraits.Finally,we propose to optimize the recommendation list to obtain different exercise suggestions.After analyses of two public datasets,the results demonstrated that PERP can satisfy novelty,accuracy,and diversity.

MAIPFE:An Efficient Multimodal Approach Integrating Pre-Emptive Analysis,Personalized Feature Selection,and Explainable AI

Medical Internet of Things(IoT)devices are becoming more and more common in healthcare.This has created a huge need for advanced predictive health modeling strategies that can make good use of the growing amount of multimodal data to find potential health risks early and help individuals in a personalized way.Existing methods,while useful,have limitations in predictive accuracy,delay,personalization,and user interpretability,requiring a more comprehensive and efficient approach to harness modern medical IoT devices.MAIPFE is a multimodal approach integrating pre-emptive analysis,personalized feature selection,and explainable AI for real-time health monitoring and disease detection.By using AI for early disease detection,personalized health recommendations,and transparency,healthcare will be transformed.The Multimodal Approach Integrating Pre-emptive Analysis,Personalized Feature Selection,and Explainable AI(MAIPFE)framework,which combines Firefly Optimizer,Recurrent Neural Network(RNN),Fuzzy C Means(FCM),and Explainable AI,improves disease detection precision over existing methods.Comprehensive metrics show the model’s superiority in real-time health analysis.The proposed framework outperformed existing models by 8.3%in disease detection classification precision,8.5%in accuracy,5.5%in recall,2.9%in specificity,4.5%in AUC(Area Under the Curve),and 4.9%in delay reduction.Disease prediction precision increased by 4.5%,accuracy by 3.9%,recall by 2.5%,specificity by 3.5%,AUC by 1.9%,and delay levels decreased by 9.4%.MAIPFE can revolutionize healthcare with preemptive analysis,personalized health insights,and actionable recommendations.The research shows that this innovative approach improves patient outcomes and healthcare efficiency in the real world.

Personalized and continuous care intervention affects rehabilitation,living quality,and negative emotions of patients with breast cancer

BACKGROUND Breast cancer is among the most common malignancies worldwide.With progress in treatment methods and levels,the overall survival period has been prolonged,and the demand for quality care has increased.AIM To investigate the effect of individualized and continuous care intervention in patients with breast cancer.METHODS Two hundred patients with breast cancer who received systemic therapy at The First Affiliated Hospital of Hebei North University(January 2021 to July 2023)were retrospectively selected as research participants.Among them,134 received routine care intervention(routing group)and 66 received personalized and continuous care(intervention group).Self-rating anxiety scale(SAS),self-rating depression scale(SDS),and Functional Assessment of Cancer Therapy-Breast(FACT-B)scores,including limb shoulder joint activity,complication rate,and care satisfaction,were compared between both groups after care.RESULTS SAS and SDS scores were lower in the intervention group than in the routing group at one and three months after care.The total FACT-B scores and five dimensions in the intervention group were higher than those in the routing group at three months of care.The range of motion of shoulder anteflexion,posterior extension,abduction,internal rotation,and external rotation in the intervention group was higher than that in the routing group one month after care.The incidence of postoperative complications was 18.18%lower in the intervention group than in the routing group(34.33%;P<0.05).Satisfaction with care was 90.91% higher in the intervention group than in the routing group(78.36%;P<0.05).CONCLUSION Personalized and continuous care can alleviate negative emotions in patients with breast cancer,quicken rehabilitation of limb function,decrease the incidence of complications,and improve living quality and care satisfaction.

Modulatory role of plant-derived metabolites on host-microbiota interactions:personalized therapeutics outlook

A diverse array of microbes in and on the human body constitute the microbiota.These micro-residents continuously interact with the human host through the language of metabolites to dictate the host’s physiology in health and illnesses.Any biotic and abiotic component ensuring a balanced host-microbiota interaction are potential microbiome therapeutic agents to overcome human diseases.Plant metabolites are continually being used to treat various illnesses.These metabolites target the host’s metabolic machinery and host-gut microbiota interactions to overcome human diseases.Despite the paramount therapeutic significance of the factors affecting host-microbiota interactions,a comprehensive overview of the modulatory role of plant-derived metabolites in host-microbiota interactions is lacking.The current review puts an effort into comprehending the role of medicinal plants in gut microbiota modulation to mitigate various human illnesses.It would develop a holistic understanding of hostmicrobiota interactions and the role of effectors in health and diseases.

Research on Current Situation and Legal Regulation of Cosmetics Live Streaming E-commerce in China

Analyze the compatibility between cosmetics and live streaming e-commerce from its own nature,marketing means and supply chain characteristics.According to the prominent problems,sort out the relationship between all parties in the cosmetics live e-commerce industry chain.Combined with the latest regulatory policies of live streaming e-commerce and cosmetics,the responsibilities of different subjects in cosmetics live streaming e-commerce are summarized,and relevant suggestions and countermeasures are put forward for the standardization and development of live streaming e-commerce.Cosmetics brand owners are the first responsible persons for product quality.Anchors,as a mixed identity between intermediary,advertising spokesperson and operator,should bear stricter joint and several liability when recommending products related to consumers’health.If anchors fail to clearly identify themselves in the recommendation process,thus causing consumers to mistake them for the operator of the cosmetics,they should assume the obligations of the operator.

Predicting Purchasing Behavior on E-Commerce Platforms: A Regression Model Approach for Understanding User Features that Lead to Purchasing

This research introduces a novel approach to improve and optimize the predictive capacity of consumer purchase behaviors on e-commerce platforms. This study presented an introduction to the fundamental concepts of the logistic regression algorithm. In addition, it analyzed user data obtained from an e-commerce platform. The original data were preprocessed, and a consumer purchase prediction model was developed for the e-commerce platform using the logistic regression method. The comparison study used the classic random forest approach, further enhanced by including the K-fold cross-validation method. Evaluation of the accuracy of the model’s classification was conducted using performance indicators that included the accuracy rate, the precision rate, the recall rate, and the F1 score. A visual examination determined the significance of the findings. The findings suggest that employing the logistic regression algorithm to forecast customer purchase behaviors on e-commerce platforms can improve the efficacy of the approach and yield more accurate predictions. This study serves as a valuable resource for improving the precision of forecasting customers’ purchase behaviors on e-commerce platforms. It has significant practical implications for optimizing the operational efficiency of e-commerce platforms.

Personalized Health Monitoring Systems: Integrating Wearable and AI

The integration of wearable technologies and artificial intelligence (AI) has revolutionized healthcare, enabling advanced personal health monitoring systems. This article explores the transformative impact of wearable technologies and AI on healthcare, highlighting the development and theoretical application of the Integrated Personal Health Monitoring System (IPHMS). By integrating data from various wearable devices, such as smartphones, Apple Watches, and Oura Rings, the IPHMS framework aims to revolutionize personal health monitoring through real-time alerts, comprehensive tracking, and personalized insights. Despite its potential, the practical implementation faces challenges, including data privacy, system interoperability, and scalability. The evolution of healthcare technology from traditional methods to AI-enhanced wearables underscores a significant advancement towards personalized care, necessitating further research and innovation to address existing limitations and fully realize the benefits of such integrated health monitoring systems.

How Does E-Commerce Policy Affect Consumption Disparities of Rural Households?-Evidence from China

In the context of China’s ongoing efforts to promote countryside revitalization and facilitate domestic economic circulation,it is of great significance to reduce the consumption disparity among rural households and unleash the consumption potential in the countryside.Based on data from China Family Panel Studies,this paper adopts a staggered difference-in-differences method to assess the impact of the e-commerce to enter rural areas on the consumption disparity among rural households.Findings:the comprehensive demonstration work of promoting e-commerce to enter rural areas has reduced the consumption disparity among rural households through the following mechanisms.Firstly,this policy initiative has mitigated the consumption-inhibiting effect on rural household consumption due to the local market size and external market accessibility by promoting the distribution of consumer goods to villages.Secondly,this policy initiative has also increased the agricultural income of rural households and reduced their consumption disparity by distributing farm produce to cities and enhancing the agricultural income of rural households.Moreover,the work is characterized by inclusive growth and is not susceptible to the“elite capture”phenomenon.

Research on Professional Teaching Reform of the E-Commerce Major in Vocational Colleges Under the Internet Era

With the rapid development of science and technology,the face of human society has undergone great changes;with the emergence of the Internet era,all kinds of educational technology,equipment,and software in vocational colleges have been widely used to carry out education and teaching,and has achieved remarkable results.Based on this,colleges and universities’electronic commerce(e-commerce)professional teachers should try to rely on the Internet to build information teaching classrooms,introduce advanced methods to build efficient classrooms by integrating teaching resources,and optimize the top-level design,so as to activate the classroom atmosphere,mobilize students’emotions,make them immersed in the teaching of electronic commerce courses.In view of this,this paper combines the existing theory and experience,first analyzes the dilemma faced by the current teaching of e-commerce in vocational colleges,then discusses the practical significance of teaching reform based on the Internet era,and lastly puts forward the specific practice path.

Analysis of the Current Situation, Influential Factors, and Countermeasures of Rural E-commerce Development

The development of rural e-commerce is becoming an important driver for the transformation of China’s rural economy,and with the rapid development of information technology and the upgrading of the agricultural industry,rural e-commerce is showing a vigorous momentum of development.Traditionally,agricultural products are mainly sold through traditional farmers’markets,which are subjected to geography and channel limitations,resulting in inefficient circulation of agricultural products.This paper analyzes the definition,the status quo,as well as the influencing factors of rural e-commerce development.On this basis,countermeasures for the advancement of rural e-commerce development are put forward.

The Effect of Personalized Comprehensive Care on the Nursing Care of Severe Pneumonia Patients

Objective:To explore the value of receiving personalized comprehensive care for patients with severe pneumonia.Methods:73 patients with severe pneumonia who visited the clinic from February 2020 to February 2023 were included in this study.The patients were randomly grouped into Group A and Group B.Group A received personalized comprehensive care whereas Group B received conventional care.The value of care was compared.Results:The duration of mechanical ventilation time,the time taken for fever and dyspnea relief,and the hospitalization time of Group A were shorter than those in Group B(P<0.05).The blood gas indexes such as PaO_(2),PaCO_(2),and blood pH of Group A were better than those of Group B(P<0.05).The pulmonary function indexes such as peak expiratory flow(PEF),forced vital capacity(FVC),and forced expiratory volume in 1 second(FEV_(1))of Group A were better than those of Group B,P<0.05.Moreover,the patients in Group A were generally more satisfied with the care given compared to the patients in Group B(P<0.05).Conclusion:Personalized comprehensive care improves blood gas indexes,enhances lung function,accelerates the relief of symptoms,and also enhances patient satisfaction in severe pneumonia patients.

多主体协同开发社区教育课程的PERSONAL模式探索——基于“我爱我家”的个案研究

通过对“我爱我家”这一社区自发课程的跟踪调查,发现社区自发课程开发实质上是一个组织学习过程,经过个体直觉、知识解释、知识整合等环节实现组织的制度化学习,在推动学习型无边界组织生成的同时,生成社区教育课程。在这一过程中,政策(policies)支持、专家(expert)指导、区域需求和区域特征(regional)、社区系统(system)、组织化(organization)等多要素叠加发挥作用,通过不断拓展新鲜(new)领域的积极行动(action)整合所有资源,并推动跨越边界的学习(learning)贯穿始终。因此,多主体协同的社区自发课程可以不完全地概括为PERSONAL模式。要以PERSONAL模式发展社区自发课程,需要以学习者为中心,注重发展人际互动,营造有利于跨组织交互学习的教育生态系统。

Therapeutic potential of exosome-based personalized delivery platform in chronic inflammatory diseases

In the inflammatory microenvironment,there are numerous exosomes secreted by immune cells(Macrophages,neutrophils,dendritic cells),mesenchymal stem cells(MSCs)and platelets as intercellular communicators,which participate in the regulation of inflammation by modulating gene expression and releasing anti-inflammatory factors.Due to their good biocompatibility,accurate targeting,low toxicity and immunogenicity,these exosomes are able to selectively deliver therapeutic drugs to the site of inflammation through interactions between their surface-antibody or modified ligand with cell surface receptors.Therefore,the role of exosome-based biomimetic delivery strategies in inflammatory diseases has attracted increasing attention.Here we review current knowledge and techniques for exosome identification,isolation,modification and drug loading.More importantly,we highlight progress in using exosomes to treat chronic inflammatory diseases such as rheumatoid arthritis(RA),osteoarthritis(OA),atherosclerosis(AS),and inflammatory bowel disease(IBD).Finally,we also discuss their potential and challenges as anti-inflammatory drug carriers.

Spatial Structure of China's E-commerce Express Logistics Network Based on Space of Flows

The intermediate link compression characteristics of e-commerce express logistics ne tworks influence the tradition al mode of circulation of goods and economic organization,and alter the city spatial pattern.Based on the theory of space of flows,this study adopts China Smart Logistics Network relational data to build China's e-commerce express logistics network and explore its spatial structure characteristics through social network analysis(SNA),the PageRank technique,and geospatial methods.The results are as follows:the network density is 0.9270,which is close to 1;hence,indicating that e-commerce express logistics lines between Chinese cities are nearly complete and they form a typical network structure,thereby eliminating fragmented spaces.Moreover,the average minimum number of edges is 1.1375,which indicates that the network has a small world effect and thus has a high flow efficiency of logistics elements.A significant hierarchical diffusion effect was observed in dominant flows with the highest edge weights.A diamond-structured network was formed with Shanghai,Guangzhou,Chongqing,and Beijing as the four core nodes.Other node cities with a large logistics scale and importance in the network are mainly located in the 19 city agglomerations of China,revealing the fact that the development of city agglomerations is essential for promoting the separation of experience space and changing the urban spatial pattern.This study enriches the theory of urban networks,reveals the flow laws of modern logistics elements,and encourages coordinated development of urban logistics.

Transaction Frequency Based Trust for E-Commerce

Most traditional trust computing models in E-commerce do not take the transaction frequency among participating entities into consideration,which makes it easy for one party of the transaction to obtain a high trust value in a short time,and brings many disadvantages,uncertainties and even attacks.To solve this problem,a transaction frequency based trust is proposed in this study.The proposed method is composed of two parts.The first part is built on the classic Bayes analysis based trust modelswhich are ease of computing for the E-commerce system.The second part is the transaction frequency module which can mitigate the potential insecurity caused by one participating entity gaining trust in a short time.Simulations show that the proposed method can effectively mitigate the self-promoting attacks so as to maintain the function of E-commerce system.