不同海域Custom450高强度不锈钢的腐蚀规律研究

目的 研究Custom450钢在青岛、舟山、厦门及三亚等4个海域大气和飞溅环境中的自然腐蚀规律。方法 采用形貌分析、腐蚀速率、点腐蚀深度分析等方法对Custom450钢在上述4个海域大气和飞溅区的腐蚀规律进行研究。结果 Custom450钢在4个海域大气环境的年平均腐蚀速率相当,且未观察到有点蚀现象发生,舟山海域的年平均腐蚀速率最小,为0.001 41 mm/a,三亚海域的年平均腐蚀速率最大,为0.001 54 mm/a。4个海域飞溅区的年平均腐蚀速率范围为0.0021~0.0028mm/a,舟山海域的年平均腐蚀速率为0.002 1 mm/a,平均及最大点腐蚀深度分别为5.7μm和25.99μm,均低于其他3个海域。结论 Custom450钢在4个海域的大气环境暴露1 a后,未发现明显的腐蚀现象,表明该钢短期内在上述4个海域海洋大气环境中具有良好的耐蚀性。在飞溅环境中的腐蚀速率高于大气环境,且有明显的点腐蚀现象发生,钢中未溶的NbC相会促进点腐蚀现象的发生。

基于HELP模式的集束化干预策略在老年髋部骨折术后谵妄护理中的应用

目的探讨基于医院老年生活计划(the hospital elder life program,HELP)模式的集束化干预策略对老年髋部骨折患者术后谵妄的预防及护理效果。方法选取2019年9月至2022年6月住院并手术的老年髋部骨折患者167例,用数字表法随机分为对照组87例和观察组80例,分别收住A病区和B病区。其中对照组患者给予骨折围手术期常规护理,观察组在常规护理基础上,增加基于HELP模式的集束化干预方案进行谵妄的预防及护理。结果观察组患者谵妄发生率(8.75%)低于对照组(20.69%),谵妄持续时间(3.36±0.56)d短于对照组(4.25±1.03)d,差异均有统计学意义(P<0.05);观察组患者术后3 d内疼痛评分、术后40项恢复质量评分、住院费用、出院时患者满意度调查评分均优于对照组,差异有统计学意义(P<0.05),但两组患者术后重度疼痛发生情况比较,差异无统计学意义(P>0.05)。结论基于HELP模式的集束化干预策略应用于老年髋部骨折术后谵妄护理,能有效地降低了患者术后谵妄的发生率,最大程度提高患者术后恢复质量,提高患者满意度。

Product family modeling technology for customized cosmetic packaging design based on basic-element theory

Background:As the market demands change,SMEs(small and medium-sized enterprises)have long faced many design issues,including high costs,lengthy cycles,and insufficient innovation.These issues are especially noticeable in the domain of cosmetic packaging design.Objective:To explore innovative product family modeling methods and configuration design processes to improve the efficiency of enterprise cosmetic packaging design and develop the design for mass customization.Methods:To accomplish this objective,the basic-element theory has been introduced and applied to the design and development system of the product family.Results:By examining the mapping relationships between the demand domain,functional domain,technology domain,and structure domain,four interrelated models have been developed,including the demand model,functional model,technology model,and structure model.Together,these models form the mechanism and methodology of product family modeling,specifically for cosmetic packaging design.Through an analysis of a case study on men’s cosmetic packaging design,the feasibility of the proposed product family modeling technology has been demonstrated in terms of customized cosmetic packaging design,and the design efficiency has been enhanced.Conclusion:The product family modeling technology employs a formalized element as a module configuration design language,permeating throughout the entire development cycle of cosmetic packaging design,thus facilitating a structured and modularized configuration design process for the product family system.The application of the basic-element principle in product family modeling technology contributes to the enrichment of the research field surrounding cosmetic packaging product family configuration design,while also providing valuable methods and references for enterprises aiming to elevate the efficiency of cosmetic packaging design for the mass customization product model.

Customized scaffolds for large bone defects using 3D‑printed modular blocks from 2D‑medical images

Additive manufacturing(AM)has revolutionized the design and manufacturing of patient-specific,three-dimensional(3D),complex porous structures known as scaffolds for tissue engineering applications.The use of advanced image acquisition techniques,image processing,and computer-aided design methods has enabled the precise design and additive manufacturing of anatomically correct and patient-specific implants and scaffolds.However,these sophisticated techniques can be timeconsuming,labor-intensive,and expensive.Moreover,the necessary imaging and manufacturing equipment may not be readily available when urgent treatment is needed for trauma patients.In this study,a novel design and AM methods are proposed for the development of modular and customizable scaffold blocks that can be adapted to fit the bone defect area of a patient.These modular scaffold blocks can be combined to quickly form any patient-specific scaffold directly from two-dimensional(2D)medical images when the surgeon lacks access to a 3D printer or cannot wait for lengthy 3D imaging,modeling,and 3D printing during surgery.The proposed method begins with developing a bone surface-modeling algorithm that reconstructs a model of the patient’s bone from 2D medical image measurements without the need for expensive 3D medical imaging or segmentation.This algorithm can generate both patient-specific and average bone models.Additionally,a biomimetic continuous path planning method is developed for the additive manufacturing of scaffolds,allowing porous scaffold blocks with the desired biomechanical properties to be manufactured directly from 2D data or images.The algorithms are implemented,and the designed scaffold blocks are 3D printed using an extrusion-based AM process.Guidelines and instructions are also provided to assist surgeons in assembling scaffold blocks for the self-repair of patient-specific large bone defects.

Building Custom Spreadsheet Functions with Python: End-User Software Engineering Approach

End-user computing empowers non-developers to manage data and applications, enhancing collaboration and efficiency. Spreadsheets, a prime example of end-user programming environments widely used in business for data analysis. However, Excel functionalities have limits compared to dedicated programming languages. This paper addresses this gap by proposing a prototype for integrating Python’s capabilities into Excel through on-premises desktop to build custom spreadsheet functions with Python. This approach overcomes potential latency issues associated with cloud-based solutions. This prototype utilizes Excel-DNA and IronPython. Excel-DNA allows creating custom Python functions that seamlessly integrate with Excel’s calculation engine. IronPython enables the execution of these Python (CSFs) directly within Excel. C# and VSTO add-ins form the core components, facilitating communication between Python and Excel. This approach empowers users with a potentially open-ended set of Python (CSFs) for tasks like mathematical calculations, statistical analysis, and even predictive modeling, all within the familiar Excel interface. This prototype demonstrates smooth integration, allowing users to call Python (CSFs) just like standard Excel functions. This research contributes to enhancing spreadsheet capabilities for end-user programmers by leveraging Python’s power within Excel. Future research could explore expanding data analysis capabilities by expanding the (CSFs) functions for complex calculations, statistical analysis, data manipulation, and even external library integration. The possibility of integrating machine learning models through the (CSFs) functions within the familiar Excel environment.

Corneal collagen cross-linking in patients with keratoconus from the Dresden protocol to customized solutions:theoretical basis

Keratoconus is an ectatic condition characterized by gradual corneal thinning,corneal protrusion,progressive irregular astigmatism,corneal fibrosis,and visual impairment.The therapeutic options regarding improvement of visual function include glasses or soft contact lenses correction for initial stages,gas-permeable rigid contact lenses,scleral lenses,implantation of intrastromal corneal ring or corneal transplants for most advanced stages.In keratoconus cases showing disease progression corneal collagen crosslinking(CXL)has been proven to be an effective,minimally invasive and safe procedure.CXL consists of a photochemical reaction of corneal collagen by riboflavin stimulation with ultraviolet A radiation,resulting in stromal crosslinks formation.The aim of this review is to carry out an examination of CXL methods based on theoretical basis and mathematical models,from the original Dresden protocol to the most recent developments in the technique,reporting the changes proposed in the last 15y and examining the advantages and disadvantages of the various treatment protocols.Finally,the limits of non-standardized methods and the perspectives offered by a customization of the treatment are highlighted.

Omni-Channel Retailing and Firm Performance from a Customer Lifetime Value Perspective

In the digital era,retailers are keen to find out whether omni-channel retailing helps improve long-term firm performance.In this paper,we employ machine learning techniques on a large consumption data set in order to measure customer lifetime value(CLV)as the basis for determining long-term firm performance,and we provide an empirical analysis of the relationship between omni-channel retailing and CLV.The results suggest that omni-channel retailing may effectively enhance CLV.Further analysis reveals that this process is influenced by heterogeneous consumer requirements and that significant differences exist in the extent to which the omni-channel transition may influence CLV depending on consumer preferences for diversity of commodities,sensitivity to the cost of contract performance,and sensitivity to warehousing costs.Hence,retailers should provide consumers with a complete portfolio of goods and services based on target consumers’heterogeneous requirements in order to increase omni-channel efficiency.

Ethnic Customs and Rural Tourism Development in Xinbin Manchu Autonomous County of Fushun City

The development of ethnic minority tourism is currently a hot topic in domestic tourism development.As an important component of Chinese civilization,the Manchu people have created brilliant culture in the long river of historical development.As the hometown of the Manchu people,Fushun has unique folk cultural tourism resources and a strong ethnic flavor.Nowadays,under the promotion of the rural revitalization strategy,the construction of new rural areas is constantly developing,and rural tourism is gradually becoming a new industry.Therefore,in the context of the increasingly prosperous rural tourism industry,it has become increasingly important to combine the ethnic customs of Manchu culture with rural tourism.Taking the ethnic customs and integrated development of rural tourism in Xinbin Manchu Autonomous County of Fushun City,Liaoning Province as the research object,this paper mainly sorts out the current situation and characteristics of rural tourism development in the region,systematically explores the problems in development and how to further optimize development,and proposes new models suitable for the development of folk tourism in Xinbin of Fushun,in order to achieve maximum economic and social benefits and provide a reference for promoting the development of tourism in the region.

The User Analysis of Amazon Using Artificial Intelligence at Customer Churn

Customer churns remains a key focus in this research, using artificial intelligence-based technique of machine learning. Research is based on the feature-based analysis four main features were used that are selected on the basis of our customer churn to deduct the meaning full analysis of the data set. Data-set is taken from the Kaggle that is about the fine food review having more than half a million records in it. This research remains on feature based analysis that is further concluded using confusion matrix. In this research we are using confusion matrix to conclude the customer churn results. Such specific analysis helps e-commerce business for real time growth in their specific products focusing more sales and to analyze which product is getting outage. Moreover, after applying the techniques, Support Vector Machine and K-Nearest Neighbour perform better than the random forest in this particular scenario. Using confusion matrix for obtaining the results three things are obtained that are precision, recall and accuracy. The result explains feature-based analysis on fine food reviews, Amazon at customer churn Support Vector Machine performed better as in overall comparison.

Turning Dreams Into Reality China is committed to helping African countries to build their space capability

An important feature of China developing its aerospace industry is its insistence on self-reliance and independent innovation,because China firmly believes that aerospace is a hi-tech industry and high core technologies cannot be bought.Only by mastering core technologies can China firmly grasp the initiative in development.

The Customer Requirements Analysis Method of Engineering Products Based on Multiple Preference Information

To effectively evaluate the fuzziness of the market environment in product planning,a customer requirements analysis method based on multiple preference information is proposed.Firstly,decision-makers use a preferred information form to evaluate the importance of each customer requirement.Secondly,a transfer function is employed to unify various forms of preference information into a fuzzy complementary judgment matrix.The ranking vector is then calculated using row and normalization methods,and the initial importance of customer requirements is obtained by aggregating the weights of decision members.Finally,the correction coefficients of initial importance and each demand are synthesized,and the importance of customer requirements is determined through normalization.The development example of the PE jaw crusher demonstrates the effectiveness and feasibility of the proposed method.

基于HELP理念在预防高龄髋部骨折患者术后谵妄护理的应用

构建基于HELP理念的多学科干预方案,并探讨其在预防高龄患者髋部骨折术后谵妄的应用效果。方法 在证据检索总结下形成相关预防护理管理方案。选取收治于上海市同仁医院骨科的高龄髋部骨折患者,将其中2021年07月-2022年06月的纳入对照组,进行常规护理;降2022年07月-2023年6月的纳入实验组,进行上述护理管理方案的落实。最后对比两组的护理效果。结果 实验组的POD发生率远低于对照组(P<0.05),但两组在POD持续时间和睡眠时间方面的对比,差异不存在统计学意义(P>0.05)。结论 为高龄髋部骨折患者提供基于HELP理念的多学科干预方案,可以预防术后谵妄的发生,效果比较突出,值得临床推广应用。

A Custom Manipulator for Dental Implantation Through Model-Based Design

This paper presents a Model-Based Design(MBD)approach for the design and control of a customized manipulator intended for drilling and position-ing of dental implants accurately with minimal human intervention.While performing an intra-oral surgery for a prolonged duration within a limited oral cavity,the tremor of dentist's hand is inevitable.As a result,wielding the drilling tool and inserting the dental implants safely in accurate position and orientation is highly challenging even for experienced dentists.Therefore,we introduce a customized manipulator that is designed ergonomically by taking in to account the dental chair specifications and anthropomorphic data such that it can be readily mounted onto the existing dental chair.The manipulator can be used to drill holes for dental inserts and position them with improved accuracy and safety.Further-more,a thorough multi-body motion analysis of the manipulator was carried out by creating a virtual prototype of the manipulator and simulating its controlled movements in various scenarios.The overall design was prepared and validated in simulation using Solid works,MATLAB and Simulink through Model Based Design(MBD)approach.The motion simulation results indicate that the manipulator could be built as a prototype readily.

A biomimetic nanoplatform for customized photothermal therapy of HNSCC evaluated on patient-derived xenograft models

Cancer cell membrane(CCM)derived nanotechnology functionalizes nanoparticles(NPs)to recognize homologous cells,exhibiting translational potential in accurate tumor therapy.However,these nanoplatforms are majorly generated from fixed cell lines and are typically evaluated in cell line-derived subcutaneous-xenografts(CDX),ignoring the tumor heterogeneity and differentiation from inter-and intra-individuals and microenvironments between heterotopic-and orthotopic-tumors,limiting the therapeutic efficiency of such nanoplatforms.Herein,various biomimetic nanoplatforms(CCM-modified gold@Carbon,i.e.,Au@C-CCM)were fabricated by coating CCMs of head and neck squamous cell carcinoma(HNSCC)cell lines and patient-derived cells on the surface of Au@C NP.The generated Au@C-CCMs were evaluated on corresponding CDX,tongue orthotopic xenograft(TOX),immunecompetent primary and distant tumor models,and patient-derived xenograft(PDX)models.The Au@C-CCM generates a photothermal conversion efficiency up to 44.2% for primary HNSCC therapy and induced immunotherapy to inhibit metastasis via photothermal therapy-induced immunogenic cell death.The homologous CCM endowed the nanoplatforms with optimal targeting properties for the highest therapeutic efficiency,far above those with mismatched CCMs,resulting in distinct tumor ablation and tumor growth inhibition in all four models.This work reinforces the feasibility of biomimetic NPs combining modular designed CMs and functional cores for customized treatment of HNSCC,can be further extended to other malignant tumors therapy.

Novel Early-Warning Model for Customer Churn of Credit Card Based on GSAIBAS-Cat Boost

As the banking industry gradually steps into the digital era of Bank 4.0,business competition is becoming increasingly fierce,and banks are also facing the problem of massive customer churn.To better maintain their customer resources,it is crucial for banks to accurately predict customers with a tendency to churn.Aiming at the typical binary classification problem like customer churn,this paper establishes an early-warning model for credit card customer churn.That is a dual search algorithm named GSAIBAS by incorporating Golden Sine Algorithm(GSA)and an Improved Beetle Antennae Search(IBAS)is proposed to optimize the parameters of the CatBoost algorithm,which forms the GSAIBAS-CatBoost model.Especially,considering that the BAS algorithm has simple parameters and is easy to fall into local optimum,the Sigmoid nonlinear convergence factor and the lane flight equation are introduced to adjust the fixed step size of beetle.Then this improved BAS algorithm with variable step size is fused with the GSA to form a GSAIBAS algorithm which can achieve dual optimization.Moreover,an empirical analysis is made according to the data set of credit card customers from Analyttica official platform.The empirical results show that the values of Area Under Curve(AUC)and recall of the proposedmodel in this paper reach 96.15%and 95.56%,respectively,which are significantly better than the other 9 common machine learning models.Compared with several existing optimization algorithms,GSAIBAS algorithm has higher precision in the parameter optimization for CatBoost.Combined with two other customer churn data sets on Kaggle data platform,it is further verified that the model proposed in this paper is also valid and feasible.

COVID-19 Detection Based on 6-Layered Explainable Customized Convolutional Neural Network

This paper presents a 6-layer customized convolutional neural network model(6L-CNN)to rapidly screen out patients with COVID-19 infection in chest CT images.This model can effectively detect whether the target CT image contains images of pneumonia lesions.In this method,6L-CNN was trained as a binary classifier using the dataset containing CT images of the lung with and without pneumonia as a sample.The results show that the model improves the accuracy of screening out COVID-19 patients.Compared to othermethods,the performance is better.In addition,the method can be extended to other similar clinical conditions.

Comparison of Self-Strength, Seeking Help and Happiness between Pakistani and Chinese Adolescents: A Positive Psychology Inquiry

Adolescents’emotions and preferences are influenced by their childhood experiences.In today’s world,there is a pervasive eagerness for happiness.Happiness has been linked to feelings of self-strength,seeking help,and psy-chological health.The current quantitative research was designed with a positive psychological perspective to compare Pakistani and Chines adolescents’self-strength,seeking help,and happiness.The research design of the study was causal-comparative.The study population consisted of 400 Pakistani and 409 Chinese adolescents studying in the elementary grades of both countries.The sample was selected by using a simple random sampling technique.It consisted of 413 boys(51%)and 396 girls(49%),319(39)of them were from the age group of 13–14 years,386(48%)of them were from the age group of 15–16 years,and 104(12.9%)were from the age group of 17–18 years.Three different scales were developed to collect study data.Independent sample t-test and simple linear regression were used to test study hypotheses.The analysis revealed that Pakistani adolescents have signifi-cantly higher self-strength,seeking help and happiness than their counterparts.It was also found that adolescents’self-strength and seeking help significant affect their happiness.Based on thefindings,it was suggested to inves-tigate the factors contributing to the improved self-strength,seeking help,and happiness of Pakistani adolescents.It was also recommended to investigate the mediating effect of adolescents’self-strength on the relationship between their happiness and seeking help.

Customer Churn Prediction Framework of Inclusive Finance Based on Blockchain Smart Contract

In view of the fact that the prediction effect of influential financial customer churn in the Internet of Things environment is difficult to achieve the expectation,at the smart contract level of the blockchain,a customer churn prediction framework based on situational awareness and integrating customer attributes,the impact of project hotspots on customer interests,and customer satisfaction with the project has been built.This framework introduces the background factors in the financial customer environment,and further discusses the relationship between customers,the background of customers and the characteristics of pre-lost customers.The improved Singular Value Decomposition(SVD)algorithm and the time decay function are used to optimize the search and analysis of the characteristics of pre-lost customers,and the key index combination is screened to obtain the data of potential lost customers.The framework will change with time according to the customer’s interest,adding the time factor to the customer churn prediction,and improving the dimensionality reduction and prediction generalization ability in feature selection.Logistic regression,naive Bayes and decision tree are used to establish a prediction model in the experiment,and it is compared with the financial customer churn prediction framework under situational awareness.The prediction results of the framework are evaluated from four aspects:accuracy,accuracy,recall rate and F-measure.The experimental results show that the context-aware customer churn prediction framework can be effectively applied to predict customer churn trends,so as to obtain potential customer data with high churn probability,and then these data can be transmitted to the company’s customer service department in time,so as to improve customer churn rate and customer loyalty through accurate service.

Multi-Objective Cold Chain Path Optimization Based on Customer Satisfaction

To improve customer satisfaction of cold chain logistics of fresh agricultural goods enterprises and reduce the comprehensive distribution cost composed of fixed cost, transportation cost, cargo damage cost, refrigeration cost, and time penalty cost, a multi-objective path optimization model of fresh agricultural products distribution considering client satisfaction is constructed. The model is solved using an enhanced Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II), and differential evolution is incorporated to the evolution operator. The algorithm produced by the revised algorithm produces a better Pareto optimum solution set, efficiently balances the relationship between customer pleasure and cost, and serves as a reference for the long-term growth of organizations. .