摘要：
Featured Application Using Structural Design to Reduce Product Development Costs and Increase Patient Active Rehabilitation Motivation.Abstract In order to meet the diversified rehabilitation needs of people, it is necessary to design a product for the active rehabilitation of patients. Existing rehabilitation chairs use intelligent massage, which can cause problems such as large massage areas, inability to massage locally, large chair size, and inability to meet the continuous use of the damaged parts. In this paper, the modular design method and multi-layer evaluation method are used to solve the problems related to rehabilitation chairs. The authors use the questionnaire survey method and the functional technology matrix method to determine the functional requirements of the rehabilitation chair, and then use the multilevel evaluation methods, including the AHP method, entropy weight method, and grey correlation analysis, to optimize the functional solutions of the rehabilitation chair, and finally obtain a chair for the rehabilitation of patients with upper and lower limb disorders. Problems such as the generalization of rehabilitation scope and non-durable use of components were solved, and the purpose of active exercise was achieved. This study verifies that the use of the multilevel decision evaluation method can effectively improve the efficiency of program decision-making and provides a theoretical and practical basis for the design of similar products.
作者机构：
[Huo, Hongfei; Song, Feifei; Zhang, Jijuan; Zhang, Xu; Zhang, Zhongfeng; Yang, Yang] Cent South Univ Forestry & Technol, Coll Furniture & Art Design, Changsha 410004, Peoples R China.;[Huo, Hongfei; Song, Feifei; Zhang, Jijuan; Zhang, Xu; Zhang, Zhongfeng; Yang, Yang] Grassland Adm, Green Furniture Engn Technol Res Ctr Natl Forestry, Changsha 410004, Peoples R China.;[Huo, Hongfei; Song, Feifei; Zhang, Jijuan; Zhang, Xu; Zhang, Zhongfeng; Yang, Yang] Green Home Engn Technol Res Ctr Hunan, Changsha 410004, Peoples R China.;[Zhang, Lei] Dongyang Furniture Res Inst, Dongyang 322100, Peoples R China.;[Yue, Kong] Nanjing Univ Technol, Sch Civil Engn, Nanjing 210000, Peoples R China.
通讯机构：
[Zhongfeng Zhang] C;College of Furniture and Art Design, Central South University of Forestry and Technology, Changsha 410004, China<&wdkj&>Green Home Engineering Technology Research Center in Hunan, Changsha 410004, China<&wdkj&>Green Furniture Engineering Technology Research Center of National Forestry and Grassland Administration, Changsha 410004, China<&wdkj&>Author to whom correspondence should be addressed.
摘要：
In the context of high-quality development, environmental issues are being paid more and more attention to, and the release of free formaldehyde has become a major problem that needs to be solved. Glueless plywood mainly adopts natural substances as raw materials, without adding chemical products, such as resin adhesives, and it does not contain harmful substances, such as formaldehyde. Glueless plywood is a green product that causes no pollution in the environment and no harm to the human body. In this study, the corresponding weak-phase components in boxwood were pre-delivered by an acidic environmental treatment, and the high-temperature and high-pressure compacting process produced a glueless boxwood panel with excellent water resistance and mechanical properties, while remaining environmentally friendly.
作者机构：
[Zhang, JiJuan; Huo, HongFei; Ren, Yi; Zhang, Xu; Zhang, Zhongfeng; Yang, Yang; Zhang, Lei; Huang, Kai] Cent South Univ Forestry & Technol, Coll Furniture & Art Design, Changsha 410004, Hunan, Peoples R China.;[Zhang, JiJuan; Huo, HongFei; Ren, Yi; Zhang, Xu; Zhang, Zhongfeng; Yang, Yang; Zhang, Lei; Huang, Kai] Natl Forestry & Grassland Adm, Green Furniture Engn Technol Res Ctr, Changsha 410004, Hunan, Peoples R China.;[Zhang, JiJuan; Huo, HongFei; Ren, Yi; Zhang, Xu; Zhang, Zhongfeng; Yang, Yang; Zhang, Lei; Huang, Kai] Green Home Engn Technol Res Ctr Hunan, Changsha 410004, Hunan, Peoples R China.
通讯机构：
[Zhongfeng Zhang] C;College of Furniture and Art Design, Central South University of Forestry and Technology, Changsha 410004, Hunan, China<&wdkj&>Green Furniture Engineering Technology Research Center, National Forestry & Grassland Administration, Changsha 410004, Hunan, China<&wdkj&>Green Home Engineering Technology Research Center in Hunan, Changsha 410004, Hunan, China
摘要：
In the context of the circular economy and decreasing earth resources, waste should be converted into value-added materials such as carbon quantum dots, which are fluorescent nanomaterials with promising applications in sensing, biological imaging, energy storage, and photocatalysis. Here, we review carbon quantum dots with focus on their synthesis from biomass, factors controlling their performance, properties, and applications in energy, medicine, and environmental science. Applications include energy storage in batteries and supercapacitors, renewable energy, pollutant sensing and degradation, drug delivery, biosensing, and bioimaging.
期刊：
Industrial Crops and Products,2023年192:116097 ISSN：0926-6690
通讯作者：
Yiqiang Wu<&wdkj&>Yan Qing
作者机构：
[Jiang, Lili] College of Furniture and Art Design, Central South University of Forestry and Technology, China;[Qing, Yan; Zhang, Zhen; Tian, Cuihua; Wu, Yiqiang; Jiang L.] College of Materials Science and Technology, Central South University of Forestry and Technology, China
通讯机构：
[Yiqiang Wu; Yan Qing] C;College of Materials Science and Technology, Central South University of Forestry and Technology, China
作者机构：
[Li, Song; Dai, Xiangdong] Cent South Univ Forestry & Technol, Coll Furniture & Art Design, Changsha 410004, Peoples R China.;[Li, Song; Li, Luming; Li, Zequn; Zhu, Wenkai] Zhejiang A&F Univ, Coll Chem & Mat Engn, Hangzhou 311300, Peoples R China.;[Chen, Meiling] Nanjing Forestry Univ, Coll Mat Sci & Engn, Jiangsu Coinnovat Ctr Efficient Proc & Utilizat Fo, Nanjing 210037, Peoples R China.
通讯机构：
[Meiling Chen; Wenkai Zhu] A;[Xiangdong Dai] C;Authors to whom correspondence should be addressed.<&wdkj&>Jiangsu Co-Innovation Center of Efficient Processing and Utilization of Forest Resources, College of Materials Science and Engineering, Nanjing Forestry University, Nanjing 210037, China<&wdkj&>Authors to whom correspondence should be addressed.<&wdkj&>College of Chemistry and Materials Engineering, Zhejiang A & F University, Hangzhou 311300, China<&wdkj&>College of Furniture and Art Design, Central South University of Forestry and Technology, Changsha 410004, China<&wdkj&>Authors to whom correspondence should be addressed.
摘要：
Sodium silicate modification can improve the overall performance of wood. The modification process has a great
influence on the properties of modified wood. In this study, a new method was introduced to analyze the wood
modification process, and the properties of modified wood were studied. Poplar wood was modified with sodium
silicate by vacuum-pressure impregnation. After screening using single-factor experiments, an orthogonal experiment was carried out with solution concentration, impregnation time, impregnation pressure, and the cycle times
as experimental factors. The modified poplar with the best properties was selected by fuzzy mathematics and
characterized by SEM, FT-IR, XRD and TG. The results showed that some lignin and hemicellulose were removed
from the wood due to the alkaline action of sodium silicate, and the orderly crystal area of poplar became disorderly, resulting in the reduction of crystallinity of the modified poplar wood. FT-IR analysis showed that
sodium silicate was hydrolyzed to form polysilicic acid in wood, and structural analysis revealed the formation
of Si-O-Si and Si-O-C, indicating that sodium silicate reacted with fibers on the wood cell wall. TG-DTG curves
showed that the final residual mass of modified poplar wood increased from 25% to 67%, and the temperature of
the maximum loss rate decreased from 343°C to 276°C. The heat release and smoke release of modified poplar
wood decreased obviously. This kind of material with high strength and fire resistance can be used in the outdoor
building and indoor furniture.
作者机构：
[Wu, Xinfeng; Liu, Tuoyu; Xie, Lisheng; Liu, Panpan; Yang, Bin] Cent South Univ Forestry & Technol, Coll Mat Sci & Engn, Changsha 410004, Peoples R China.;[Hao, Jingxin] Cent South Univ Forestry & Technol, Coll Furniture & Art Design, Changsha 410004, Peoples R China.;[Li, Jinghao] Washington Univ St Louis, Dept Energy Environm & Chem Engn, St Louis, MO 63130 USA.
通讯机构：
[Jingxin Hao] C;[Jinghao Li] A;College of Furniture and Art Design, Central South University of Forestry and Technology, Changsha 410004, China<&wdkj&>Authors to whom correspondence should be addressed.<&wdkj&>Authors to whom correspondence should be addressed.<&wdkj&>Department of Energy, Environmental, and Chemical Engineering, Washington University in St. Louis, Saint Louis, MO 63130, USA
关键词：
deep learning;glulam;wood failure percentage;measurement
摘要：
For glulam bonding performance assessment, the traditional method of manually measuring the wood failure percentage (WFP) is insufficient. In this paper, we developed a rapid assessment approach to predicate the WFP based on deep-learning (DL) techniques. bamboo/Larch laminated wood composites bonded with either phenolic resin (PF) or methylene diphenyl diisocyanate (MDI) were used for this sample analysis. Scanning of bamboo/larch laminated wood composites that have completed shear failure tests using an electronic scanner allows a digital image of the failure surface to be obtained, and this image is used in the training process of a deep convolutional neural networks (DCNNs).The result shows that the DL technique can predict the accurately localized failures of wood composites. The findings further indicate that the UNet model has the highest values of MIou, Accuracy, and F1 with 98.87%, 97.13%, and 94.88, respectively, compared to the values predicted by the PSPNet and DeepLab_v3+ models for wood composite failure predication. In addition, the test conditions of the materials, adhesives, and loadings affect the predication accuracy, and the optimal conditions were identified. The predicted value from training images assessed by DL techniques with the optimal conditions is 4.3%, which is the same as the experimental value measured through the traditional manual method. Overall, this advanced DL method could significantly facilitate the quality identification process of the wood composites, particularly in terms of measurement accuracy, speed, and stability, through the UNet model.
