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| 1 | Non-metallic gold nanoclusters for oxygen activation and aerobic oxidation显示文摘In recent decade, Au nanoclusters of atomic precision(Au_nL_m, where L = organic ligand: thiolate and phosphine) have been shown as a new promising nanogold catalyst. The well-de fined Au_nL_m catalysts possess unique electronic properties and frameworks, providing an excellent opportunity to correlate the intrinsic catalytic behavior with the cluster's framework as well as to study the catalytic mechanisms over gold nanoclusters. In this review, we only demonstrate the important roles of the gold nanoclusters in the oxygen activation(e.g.,~3O_2 to ~1O_2) and their selective oxidations in the presence of oxygen(e.g., CO to CO_2, sul fides to sulfoxides, alcohol to aldehyde, styrene to styrene epoxide, amines to imines, and glucose to gluconic acid). The size-speci ficity(Au_(25)(1.3 nm), Au_(38)(1.5 nm), Au_(144)(1.9 nm), etc.), ligand engineering(e.g., aromatic vs aliphatic), and doping effects(e.g., copper, silver, palladium, and platinum)are discussed in details. Finally, the proposed reactions' mechanism and the relationships of clusters' structure and activity at the atomic level also are presented. | Guomei Zhang Ruru Wang Gao Li | 2018 | Chinese Chemical Letters2018，29，5： | 2 |
| 2 | Deep Neural Network with Strip Pooling for Image Classification of Yarn-Dyed Plaid Fabrics显示文摘Historically,yarn-dyed plaid fabrics(YDPFs)have enjoyed enduring popularity with many rich plaid patterns,but production data are still classified and searched only according to production parameters.The process does not satisfy the visual needs of sample order production,fabric design,and stock management.This study produced an image dataset for YDPFs,collected from 10,661 fabric samples.The authors believe that the dataset will have significant utility in further research into YDPFs.Convolutional neural networks,such as VGG,ResNet,and DenseNet,with different hyperparameter groups,seemed themost promising tools for the study.This paper reports on the authors’exhaustive evaluation of the YDPF dataset.With an overall accuracy of 88.78%,CNNs proved to be effective in YDPF image classification.This was true even for the low accuracy of Windowpane fabrics,which often mistakenly includes the Prince ofWales pattern.Image classification of traditional patterns is also improved by utilizing the strip pooling model to extract local detail features and horizontal and vertical directions.The strip pooling model characterizes the horizontal and vertical crisscross patterns of YDPFs with considerable success.The proposed method using the strip pooling model(SPM)improves the classification performance on the YDPF dataset by 2.64%for ResNet18,by 3.66%for VGG16,and by 3.54%for DenseNet121.The results reveal that the SPM significantly improves YDPF classification accuracy and reduces the error rate of Windowpane patterns as well. | Xiaoting Zhang Weidong Gao Ruru Pan | 2022 | Computer Modeling in Engineering & Sciences2022，，3： | 1 |
| 3 | Automatic recognition of the color effect of yarn-dyed fabric by the smallest repeat unit recognition algori- thm显示文摘 | ZHANG Jie PAN Ruru GAO Weidong | 2015 | Textile Research Journal2015，85，： | 1 |
| 4 | M^(2)LC-Net: A Multi-Modal Multi-Disease Long-Tailed Classification Network for Real Clinical Scenes显示文摘Leveraging deep learning-based techniques to classify diseases has attracted extensive research interest in recent years.Nevertheless,most of the current studies only consider single-modal medical images,and the number of ophthalmic diseases that can be classified is relatively small.Moreover,imbalanced data distribution of different ophthalmic diseases is not taken into consideration,which limits the application of deep learning techniques in realistic clinical scenes.In this paper,we propose a Multimodal Multi-disease Long-tailed Classification Network(M^(2)LC-Net)in response to the challenges mentioned above.M^(2)LC-Net leverages ResNet18-CBAM to extract features from fundus images and Optical Coherence Tomography(OCT)images,respectively,and conduct feature fusion to classify 11 common ophthalmic diseases.Moreover,Class Activation Mapping(CAM)is employed to visualize each mode to improve interpretability of M^(2)LC-Net.We conduct comprehensive experiments on realistic dataset collected from a Grade III Level A ophthalmology hospital in China,including 34,396 images of 11 disease labels.Experimental results demonstrate effectiveness of our proposed model M^(2)LC-Net.Compared with the stateof-the-art,various performance metrics have been improved significantly.Specifically,Cohen’s kappa coefficient κ has been improved by 3.21%,which is a remarkable improvement. | Zhonghong Ou Wenjun Chai Lifei Wang Ruru Zhang Jiawen He Meina Song Lifei Yuan Shengjuan Zhang Yanhui Wang Huan Li Xin Jia Rujian Huang | 2021 | China Communications2021，18，9： | 0 |
| 5 | Superhydrophilic Polydopamine‑Modified Carbon‑Fiber Membrane with Rapid Seawater‑Transferring Ability for Constructing Efficient Hanging‑Model Evaporator显示文摘Solar-driven seawater desalination has attracted much attention for alleviating global freshwater shortage,but the practical application is often limited by complicated fabrication processes,unsatisfactory seawater-transferring and severe salt accu-mulation on the photothermal membranes.To solve these problems,hydrophobic industrial-grade carbon fiber membrane(CFM)with good photoabsorption was surface-modified with polydopamine(PDA)to prepare superhydrophilic CFM@PDA for the construction of efficient hanging-model evaporators without salt accumulation.The coating of PDA on CFM is realized by simple self-polymerization of dopamine,and the as-prepared CFM@PDA exhibits high solar absorption effi-ciency of 96.7%,good photothermal effect and superhydrophilicity.Especially,when CFM@PDA is hanging between two water tanks(one contains seawater and the other is empty)in a flat hanging-model evaporator,it can transport seawater at a high rate(26.35 g/h)which is 3.6 times that(7.28 g/h)of commercial cotton fabric.Under simulated sunlight(1.0 kW m^(-2))irradiation,CFM@PDA shows a high evaporation rate of 1.79 kg m^(-2) h^(-1) with a solar evaporation efficiency of 92.6%.Even if NaCl solution with a high concentration(21.0 wt%)is used for the evaporation,the hanging CFM@PDA can retain a high evaporation rate(~1.80 kg m^(-2) h^(-1))without salt accumulation during the long-time test(8 h),which is significantly better than that of the tradition floating model.Therefore,this study not only demonstrates the simple preparation of super-hydrophilic CFM@PDA,but also promotes the further practical applications of hanging-model evaporators for continuous salt-free desalination. | Wenmei Chong Ruru Meng Zixiao Liu Qiyue Liu Jinjing Hu Bo Zhu Daniel KMacharia Zhigang Chen Lisha Zhang | 2023 | Advanced Fiber Materials2023，5，3： | 0 |
| 6 | Research on evaluation of network discourse power:Taking the Twitter accounts of Chinese diplomats as an example显示文摘[Purpose/Significance]Changes in network technology and the network environment have caused profound changes in the publication,dissemination,and influence of network discourses.The main body of a network discourse demonstrates the characteristics of civilians,which can impact the discourse power status of national discourse institutions.Research on the evaluation of network discourse power is conducive to clarifying the determinants of network discourse power and of considerable importance to the enhancement of the network discourse power of national public opinion institutions and improvement of the network environment.[Method/Process]First,this study explores the connotation of network discourse power and analyzes its generation process.Second,this study establishes a network discourse power evaluation indicator system and evaluation model based on information metrology and evaluation theory.Finally,this study conducts empirical research using the Twitter accounts of Chinese diplomats as the research object.[Result/Conclusion]Results show that the evaluation of network discourse power is a comprehensive evaluation of the network leading power,network communication power,and network influence of the main body of a network discourse.Moreover,the findings reveal that Chinese diplomats have a certain amount of network discourse power in society and demonstrate a trend of continuous improvement. | Rongying Zhao Xiaoyu Wang Ruru Chang Tianyang Zhang | 2023 | Data Science and Informetrics2023，3，1： | 0 |
| 7 | FSCIL-EACA:Few-Shot Class-Incremental Learning Network Based on Embedding Augmentation and Classifier Adaptation for Image Classification显示文摘The ability to learn incrementally is critical to the long-term operation of AI systems.Benefiting from the power of few-shot class-incremental learning(FSCIL),deep learning models can continuously recognize new classes with only a few samples.The difficulty is that limited instances of new classes will lead to overfitting and exacerbate the catastrophic forgetting of the old classes.Most previous works alleviate the above problems by imposing strong constraints on the model structure or parameters,but ignoring embedding network transferability and classifier adaptation(CA),failing to guarantee the efficient utilization of visual features and establishing relationships between old and new classes.In this paper,we propose a simple and novel approach from two perspectives:embedding bias and classifier bias.The method learns an embedding augmented(EA)network with cross-class transfer and class-specific discriminative abilities based on self-supervised learning and modulated attention to alleviate embedding bias.Based on the adaptive incremental classifier learning scheme to realize incremental learning capability,guiding the adaptive update of prototypes and feature embeddings to alleviate classifier bias.We conduct extensive experiments on two popular natural image datasets and two medical datasets.The experiments show that our method is significantly better than the baseline and achieves state-of-the-art results. | Ruru ZHANG Haihong E Meina SONG | 2024 | Chinese Journal of Electronics2024，33，1： | 0 |
| 8 | Investigation and analysis of vascular plant resources and diversity in Wuyi Mountain,Fujian Province显示文摘Wuyi Mountain,located in the north of Fujian Province,China,is renowned for its abundant medicinal plant resources.In July 2014,the 8th(second team)of Shenyang Pharmaceutical University’s Chinese Medicine Resources Scientific Expedition Team conducted field investigation in the area.Through specimen collection and extensive literature review,the team identified and analyzed 223 vascular plant species from 175 genera and 85 families.The most dominant families were Compositae and Rosaceae,and perennial herbs were the predominant species,accounting for 44.39%of the total species identified.Notably,we documented five precious and rare medicinal plants unique to Wuyi Mountain.This study updates the database of plant resources and diversity in the region,providing a valuable reference for future studies.Finally,we put forward some suggestions to enhance the conservation and sustainable utilization of Wuyi Mountain’s plant resources. | Peiying Chen Ruru Xiong Jun Yuan Minglong Huang Zhuo Tao Bowen Zhang Fanglin Luo Lisha Liu Qian Wang You Zhou Haofan Zhang Zijie Wei Jie Yang Jiangang Chen Kui Wu Anhua Wang Jingming Jia | 2024 | Asian Journal of Traditional Medicines2024，19，1： | 0 |
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