CoS Nanosheets Coated with Dopamine-Derived Carbon Standing on Carbon Fiber Cloth as Binder-Free Anode for Li-ion Batteries

Cobalt sulphides attract much attention as anode materials for Li-ion batteries(LIBs).However,its poor conductivity,low initial column efficiency and large volume changes during cycling have hindered its further development.Herein,novel interlaced CoS nanosheets were firstly prepared on Carbon Fiber Cloth(CFC)by two hydrothermal reactions followed with carbon coating via carbonizing dopamine(CoS NS@C/CFC).As a freestanding anode,the nanosheet structure of CoS not only accommodates the volume variation,but also provides a large interface area to proceed the charge transfer reaction.In addition,CFC works as both a three-dimensional skeleton and an active substance which can further improve the areal capacity of the resulting electrode.Furthermore,the coated carbon combined with the CFC work as a 3D conductive network to facilitate the electron conduction.The obtained CoS NS@C/CFC,and the contrast sample prepared with the same procedure but without carbon coating(CoS NS/CFC),are characterized with XRD,SEM,TEM,XPS and electrochemical measurements.The results show that the CoS NS@C/CFC possesses much improved electrochemical performance due to the synergistic effect of nanosheet CoS,the coated carbon and the CFC substrate,exhibiting high initial columbic efficiency(~87%),high areal capacity(2.5 at 0.15 mA cm−2),excellent rate performance(1.6 at 2.73 mA cm−2)and improved cycle stability(87.5%capacity retention after 300 cycles).This work may provide a new route to explore freestanding anodes with high areal specific capacity for LIBs.

Novel sandwich structured glass fiber Cloth/Poly(ethylene oxide)-MXene composite electrolyte

Recently,poly(ethylene oxide)(PEO)-based solid polymer electrolytes have been attracting great attention,and efforts are currently underway to develop PEO-based composite electrolytes for next generation high performance all-solid-state lithium metal batteries.In this article,a novel sandwich structured solid-state PEO composite electrolyte is developed for high performance all-solid-state lithium metal batteries.The PEO-based composite electrolyte is fabricated by hot-pressing PEO,LiTFSI and Ti_(3)C_(2)T_(x) MXene nanosheets into glass fiber cloth(GFC).The as-prepared GFC@PEO-MXene electrolyte shows high mechanical properties,good electrochemical stability,and high lithium-ion migration number,which indicates an obvious synergistic effect from the microscale GFC and the nanoscale MXene.Such as,the GFC@PEO-1 wt%MXene electrolyte shows a high tensile strength of 43.43 MPa and an impressive Young's modulus of 496 MPa,which are increased by 1205%and 6048%over those of PEO.Meanwhile,the ionic conductivity of GFC@PEO-1 wt%MXene at 60℃ reaches 5.01×10^(-2) S m^(-1),which is increased by around 200%compared with that of GFC@PEO electrolyte.In addition,the Li/Li symmetric battery based on GFC@PEO-1 wt%MXene electrolyte shows an excellent cycling stability over 800 h(0.3 mA cm^(-2),0.3 mAh cm^(-2)),which is obviously longer than that based on PEO and GFC@PEO electrolytes due to the better compatibility of GFC@PEO-1 wt%MXene electrolyte with Li anode.Furthermore,the solid-state Li/LiFePO_(4) battery with GFC@PEO-1 wt%MXene as electrolyte demonstrates a high capacity of 110.2–166.1 mAh g^(-1) in a wide temperature range of 25–60C,and an excellent capacity retention rate.The developed sandwich structured GFC@PEO-1 wt%MXene electrolyte with the excellent overall performance is promising for next generation high performance all-solid-state lithium metal batteries.

基于ClothResNet模型的人体衣物颜色识别

针对人体衣物属性识别存在衣物分割困难、颜色易扭曲、识别效率和准确率低的问题,提出一种基于ClothResNet模型的高效人体衣物颜色识别方法,模型以ResNet18网络为基础,设计优化的金字塔池化模块以捕获图像中的多层语义信息,融合坐标注意力机制以关注人体衣物轮廓信息,融入空洞卷积以提升网络效率,从而利用多重信息提高人体衣物识别精确率。针对人体衣物属性数据集不足的问题,利用公开数据集活动模板(回归ATR)原始彩色图像构建衣物属性数据集pcaparsing。性能对比实验表明,ClothResNet模型在衣物颜色属性识别中的平均精确率达到9449%,结果均优于同类方法。该识别方法在中小规模的人体衣物颜色识别系统具有广泛且重要的应用前景。

Boosting Capacitive Deionization Performance of Commercial Carbon Fibers Cloth via Structural Regulation Based on Catalytic-Etching Effect

Monolithic carbon electrodes with robust mechanical integrity and porous architecture are highly desired for capacitive deionization but remain challenging.Owing to the excellent mechanical strength and electroconductivity,commercial carbon fibers cloth demonstrates great potential as high-performance electrodes for ions storage.Despite this,its direct application on capacitive deionization is rarely reported in terms of limited pore structure and natural hydrophobicity.Herein,a powerful metal-organic framework-engaged structural regulation strategy is developed to boost the desalination properties of carbon fibers.The obtained porous carbon fibers features hierarchical porous structure and hydrophilic surface providing abundant ions-accessible sites,and continuous graphitized carbon core ensuring rapid electrons transport.The catalytic-etching mechanism involving oxidation of Co and subsequent carbonthermal reduction is proposed and highly relies on annealing temperature and holding time.When directly evaluated as a current collector-free capacitive deionization electrode,the porous carbon fibers demonstrates much superior desalination capability than pristine carbon fibers,and remarkable cyclic stability up to 20 h with negligible degeneration.Particularly,the PCF-1000 showcases the highest areal salt adsorption capacity of 0.037 mg cm^(−2) among carbon microfibers.Moreover,monolithic porous carbon fibers-carbon nanotubes with increased active sites and good structural integrity by in-situ growth of carbon nanotubes are further fabricated to enhance the desalination performance(0.051 mg cm^(−2)).This work demonstrates the great potential of carbon fibers in constructing high-efficient and robust monolithic electrode for capacitive deionization.

Effect of Cellulose Enzymes on Some Properties of Fibre Clothes

This study examined the effects of the enzyme cellulose on a few single jersey and interlock 100% flax t-shirts, two different styles of knit children’s clothes that differ in both their chemical and mechanical characteristics. Clothing samples were dyed using reactive colours and then subjected to normal acid cellulose enzyme treatment procedures. We evaluated some physical and mechanical features before and after cellulose treatments, then compared these characteristics. Its cellulose enzymatic processing enhances some mechanical properties of fibre knitwear, such as pilling resistance and retention of water. Some characteristics of fibre-knitted clothing, such as fabric weight, fabric thickness, fabric burst resistance, and seam tensile strength of T-shirt side seams, are reduced by cellulose enzyme treatment at a manageable rate. Compared to single-jersey all-fiber children’s T-shirts, interlocking 100% flax children’s T-shirts have a better effect of the enzyme cellulose treatment on the majority of physical and mechanical attributes.

An Isogeometric Cloth Simulation Based on Fast Projection Method

A novel continuum-based fast projection scheme is proposed for cloth simulation.Cloth geometry is described by NURBS,and the dynamic response is modeled by a displacement-only Kirchhoff-Love shell element formulated directly on NURBS geometry.The fast projection method,which solves strain limiting as a constrained Lagrange problem,is extended to the continuum version.Numerical examples are studied to demonstrate the performance of the current scheme.The proposed approach can be applied to grids of arbitrary topology and can eliminate unrealistic over-stretching efficiently if compared to spring-based methodologies.

Clothing Sales Forecast Considering Weather Information: An Empirical Study in Brick-and-Mortar Stores by Machine-Learning

Reliable sales forecasts are important to the garment industry. In recent years, the global climate is warming, the weather changes frequently, and clothing sales are affected by weather fluctuations. The purpose of this study is to investigate whether weather data can improve the accuracy of product sales and to establish a corresponding clothing sales forecasting model. This model uses the basic attributes of clothing product data, historical sales data, and weather data. It is based on a random forest, XGB, and GBDT adopting a stacking strategy. We found that weather information is not useful for basic clothing sales forecasts, but it did improve the accuracy of seasonal clothing sales forecasts. The MSE of the dresses, down jackets, and shirts are reduced by 86.03%, 80.14%, and 41.49% on average. In addition, we found that the stacking strategy model outperformed the voting strategy model, with an average MSE reduction of 49.28%. Clothing managers can use this model to forecast their sales when they make sales plans based on weather information.

Core Competitiveness Construction of Clothing Brands in Low-Carbon Economy

The climate issue has become an environmental concern for all sectors of the world and the low-carbon economy has thus become a new economic development model to combat climate change.With the development of low-carbon economy era,the textile and clothing industry plays an important role in stabilizing the development of low-carbon economy and society,and China has put forward the development requirements of low-carbon transformation for the textile and clothing industry,and also it has an important strategic value to promote the high-quality development of low-carbon economy and society,and the construction of brands’ core competitiveness is an inevitable choice for clothing brands in the face of the new form of international competition.As a result,the evaluation indicator of clothing brands’ core competitiveness in the low-carbon economy is used to measure the core competitiveness of clothing brands.Based on the corresponding verification results obtained by analytic hierarchy process(AHP) analysis,it can guide the low-carbon development of the clothing industry,thus proposing a more reasonable way to build the core competitiveness of clothing brands.It can promote the low-carbon transformation and upgrading of the clothing industry,effectively increase the market share of clothing brands,and promote the high-quality development of clothing brands.

The development of anti-fall functional clothing for elderly

Objective:The consequences of falls in the elderly are severe,ranging from skin abrasion to hip fracture,which is very easy to cause death.Using advanced technology to develop anti-fall clothing that meets the needs of the elderly can play a significant role in protecting the elderly.By reviewing and analyzing the existing literature on the importance of fall protection clothing in reducing falls and protecting the body of the elderly,it is hoped to explore further research that needs improvement.Methods:Guided by the preferred reporting items for systematic reviews and meta-analyses,eight related studies were identified through Web of Science,Scopus and Chinese National Knowledge Infrastructure.The research objects,approaches,material and equipment,protection principle,and survey results are extracted.Results:Two articles verified the fall detection algorithm adopted in the research through experiments,which significantly improved fall detection accuracy.Six papers found that selecting appropriate cushioning materials can effectively reduce the consequences of falls of the elderly through experimental comparative analysis.Finally,three attributes for significant design value are drawn:(1)size and fit;(2)cushioning materials;(3)wearable sensing elements.

2023 National Textile and Clothing Standards Innovation Conference held

The 2023 National Textile and Clothing Standards Innovation Conference convened in Tai’an city,Shandong province on August 18-20,where national experts in this field gathered to discuss the innovative development of the standards system for China’s textile and clothing.

Clothing Parsing Based on Multi-Scale Fusion and Improved Self-Attention Mechanism

Due to the lack of long-range association and spatial location information,fine details and accurate boundaries of complex clothing images cannot always be obtained by using the existing deep learning-based methods.This paper presents a convolutional structure with multi-scale fusion to optimize the step of clothing feature extraction and a self-attention module to capture long-range association information.The structure enables the self-attention mechanism to directly participate in the process of information exchange through the down-scaling projection operation of the multi-scale framework.In addition,the improved self-attention module introduces the extraction of 2-dimensional relative position information to make up for its lack of ability to extract spatial position features from clothing images.The experimental results based on the colorful fashion parsing dataset(CFPD)show that the proposed network structure achieves 53.68%mean intersection over union(mIoU)and has better performance on the clothing parsing task.

Analysis of the Influence of Clothing on Characterization from Symbolism: Taking The Scarlet Letter, Daisy Miller, and Dry September as Examples

In the novels, the clothing worn by the characters are symbols made and used by the authors to express the characters’ personality and deepen the theme, and grasping their symbolism helps to enter into the interior of the novels and understand their essence. This paper will analyze and interpret the clothing of typical female characters in The Scarlet Letter, Daisy Miller and Dry September from the perspective of symbolism, so as to illustrate how the symbolism of clothing, as a kind of symbols, shapes the image of the main characters.

Business Clothing For Females: Suitability For Effective Workplace Job Performance in Nigeria

The study investigated business clothing for females that are suitable for effective workplace job performance in Nigeria.It identified fabric characteristics of females’business clothing already used;fabric characteristics needed and deign style preference suitable for females’business clothing for workplace job performance.The study was guided by four research questions and two hypotheses.Population was 4,806 female civil servants in Delta state,Nigeria.Multi-stage sampling technique was utilized to select 136 females.Structured questionnaire was employed to collect data and descriptive statistics and t-test were used for data analysis.Finding showed that cotton,nylon,lacra fabrics,light and medium fabric weight,blue,black,gray,colors,cool texture,rough,smooth surface plain,stripe and flowered design among others were fabric characteristics of business clothing are being used in workplace.But prefer and need cotton,nylon,lacra,light weight,black,blue,gray,brown colours,cool,plain,surface fabrics.Net,organza,heavy weight,white,yellow,toweling fabrics were not preferred.Findings further showed that straight gown,waist flared and gathered gowns,skirt,blouse and suit/jacket,straight,shirt,long sleeves,garment with or without collar,below knee length,peter and convertible collars,among others were highly preferred design styles of clothes.In conclusion,office workers determine what they wear to perform workplace daily jobs promotes self-confidence,comfort,professional worth and productivity.It was recommended that female employees should not downplay appropriate work attires for comfort and organizational productivity to satisfy fashion trends.

绘画艺术在服装设计中的视觉化展现

绘画艺术题材广泛,其造型手法纷繁多样,表现方式千变万化。借助绘画艺术的独特表现手法,汲取优秀绘画艺术作品中的设计元素,服装设计师可将创新的服装设计理念和思想转化为可视化形态,从而更为精妙地呈现服装的视觉效果,让服装设计作品更深层次地贴近消费者需求。从视觉角度出发,深入剖析绘画艺术在服装色彩、造型,以及诸多细节层面的可视化表达方式,总结了绘画艺术运用于服装设计过程中,在设计理念与设计方法等方面所采用的策略,以期对服装设计行业创新发展提供一定的参考意见。

文化传承视域下传统刺绣工艺与现代服装设计的结合

传统刺绣工艺作为一种重要的文化遗产,具有丰富的历史和文化内涵。将传统刺绣工艺融入现代服装设计,能够突出现代服饰的装饰感,改善服装构图,使传统刺绣工艺焕发出新的生机和活力,从而促进传统刺绣工艺的传承和发展。通过分析传统刺绣工艺与现代服装设计的关联性,分析了传统刺绣工艺在现代服装设计中的表达方式,探究了文化传承视域下传统刺绣工艺与现代服装设计结合的策略,以期促进对传统刺绣工艺的保护和传承,以及现代服装样式、造型、风格等的创新。

秦绣元素在服装设计中的运用方法

针对中国传统刺绣艺术秦绣在当代服装设计中面临的元素分类缺失和设计流程不明的问题,提出秦绣元素在服装设计中的方法。首先解析秦绣元素的外在表征及其隐藏意象,提炼并总结秦绣图案的构成要素;然后提取秦绣要素外在表征,建立针法、图案与色彩元素基因库,依据服装风格选择合适的元素基因并融入符合现代审美的设计语言;最后将针法工艺、图案造型与色彩搭配3个秦绣外在表征进行分类与整理,以保留传统秦绣样本隐藏意象为前提融入再设计,得出系统的秦绣元素在服装设计中的运用方法;总结了秦绣元素在面料、造型与科技方面融入现代服装设计的运用策略,为秦绣在服装设计中的转型发展提出指导建议。

基于CiteSpace的智能纺织服装产品研究进展

为揭示智能纺织服装的研究现状、热点和趋势,以CNKI数据库和WOS数据库中2012—2022年的相关文献为研究对象,采用CiteSpace可视化分析软件绘制知识图谱,分析智能纺织服装产品在国家、机构、作者方面的分布现状及合作情况,对研究热点和前沿趋势进行梳理。结果表明,2012—2022年,CNKI数据库发文量稳步上升,WOS数据库发文量快速增长且中国学者发文量较多;CNKI数据库研究合作强度较低且以东华大学和江南大学为主体;WOS数据库合作关系密切,研究集中度和合作强度大;CNKI数据库研究方向更注重应用和设计模式,WOS数据库则更注重电子元件制造和智能纤维与面料的开发;健康检测、变色肌理、仿生设计、生物材料、可穿戴应变等是目前智能纺织服装领域的前沿热点,电子元件制造、智能纤维及面料智能化研究是未来智能纺织服装领域研究的热点及趋势。

虚拟现实技术在现代服装设计专业教学中的运用

将虚拟现实技术应用于现代服装设计的专业教学中可以有效提升服装设计专业的课堂教学效率,激发学生的设计和创作灵感,推动服装设计专业实现低碳教学,为学生提供更好的学习环境。现代服装设计专业教学中,VR技术可以实现服装样品的立体化展示,让学生能够更加直观地观察和分析设计样品的细节,将服装样品从二维与三维的任意转化,使学生可以从不同角度和视角欣赏服装设计作品,还能优化现代服装款式设计系统,提高设计效率和精准度。因此,高校需要搭建专业的虚拟仿真设计平台,构建虚拟仿真教学课程体系,打造虚拟仿真创新教学团队,以满足学生在虚拟环境中进行服装设计实践的需求。

褶皱装饰元素在皮革服装设计中的应用研究

皮革服装不仅要适应个体,还要凸显个体美感。正是由于服装与个体间愈发密切的关系,服装设计才得以实现长足发展。褶皱装饰元素存在的意义是满足人类个性化需求,彰显个体美感的同时,促使皮革服装神韵与底蕴完美展现。本文详细分析了皮革服装设计中褶皱装饰元素应用现状,深层解析了褶皱装饰元素的美感表现及其与皮革服装设计的耦合,并进一步探究了褶皱装饰元素在皮革服装设计中的实际应用,为皮革服装设计实现多元化发展提供可借鉴依据。

潍坊风筝元素在现代女礼服设计中的应用

从保护国家级非物质文化遗产的角度出发,基于对潍坊地区非物质文化的实地调研,选取潍坊风筝作为切入点,将其元素应用于现代女礼服设计中。以现代简约女礼服为载体,在面料上采用手绘工艺绘制沙燕、荷叶、蜻蜓等图案;使用硬纱和风筝原材料竹子缠绕制作立体梅花、荷花、牡丹等花卉造型,将其缝制于服装局部作为部分装饰;将竹条按服装造型制作成型,作为服装局部造型,如袖子、裙撑、蝴蝶结等,使得礼服造型既融合传统文化又符合现代美感。将潍坊风筝元素应用到女礼服设计中,使服装设计实现多样化,同时助推潍坊风筝制作工艺的传承与发展,对推动潍坊市文化和经济的发展具有重大意义。