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Mutual-structure weighted guided image filtering for depth map restoration

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Optoelectronics Letters 2025年第1期21卷 51-56页

作者： LIU Zijian song Jian cHEN Quanmin XU Jiangtao Tianjin Key Laboratory of Imaging and Sensing Microelectronic Technology School of Microelectronics Tianjin University Spikesee Technology co. Ltd.

Although guided image filtering(GIF) is known for preserving edges and fast computation, it may produce inaccurate outputs in depth map restoration. In this paper, a novel confidence-weighted GIF called mutual-structure weighted GIF(MSWGIF) is proposed, which replaces the mean filtering strategy in GIF during handling overlapping windows. The confidence value is composed of a depth term and a mutual-structure term, where the depth term is utilized to protect the edges of the output, and the mutual-structure term helps to select accurate windows during the structure characteristics of the guidance image are transferred to the output. Experimental results show that MSWGIF reduces the root mean square error(RMSE) by an average of 12.37%, and the average growth rate of correlation(cORR) is 0.07% on average. Additionally, the average growth rate of structure similarity index measure(SSIM) is 0.34%.

关键词： Wiener filtering

Recent Advances in Fibrous Materials for Hydroelectricity Generation

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Nano-Micro Letters 2025年第2期17卷 109-133页

作者： can Ge Duo Xu Xiao Feng Xing Yang Zheheng song Yuhang song Jingyu chen Yingcun Liu chong Gao Yong Du Zhe Sun Weilin Xu Jian Fang college of Textile and clothing Engineering Soochow UniversitySuzhou 215123People’s Republic of China National Engineering Laboratory for Modern Silk Soochow UniversitySuzhou 215123People’s Republic of China State Key Laboratory of New Textile Materials and Advanced Processing Technologies Wuhan Textile UniversityWuhan 430200People’s Republic of China Institute of Functional Nano&Soft Materials(FUNSOM) Soochow UniversitySuzhou 215123People’s Republic of China Department of Electrical and computer Engineering University of MassachusettsAmherstMA 01003USA Department of Materials Imperial College LondonSouth Kensington CampusLondon SW72AZUK college of Textile Science and Engineering Zhejiang Sci-Tech UniversityHangzhou 310018People’s Republic of China School of Materials Science and Engineering Shanghai Institute of Technology100 Haiquan RoadShanghai 201418People’s Republic of China

Depleting fossil energy sources and conventional polluting power generation pose a threat to sustainable *** generation from ubiquitous and spontaneous phase transitions between liquid and gaseous water has been considered a promising strategy for mitigating the energy *** materials with unique flexibility,processability,multifunctionality,and practicability have been widely applied for fibrous materials-based hydroelectricity generation(FHG).In this review,the power generation mechanisms,design principles,and electricity enhancement factors of FHG are first ***,the fabrication strategies and characteristics of varied constructions including 1D fiber,1D yarn,2D fabric,2D membrane,3D fibrous framework,and 3D fibrous gel are ***,the advanced functions of FHG during water harvesting,proton dissociation,ion separation,and charge accumulation processes are analyzed in ***,the potential applications including power supply,energy storage,electrical sensor,and information expression are also ***,some existing challenges are considered and prospects for future development are sincerely proposed.

关键词： Hydroelectricity Fibrous material Streaming potential Ion diffusion

Potential role of tanycyte-derived neurogenesis in Alzheimer's disease

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Neural Regeneration Research 2025年第6期20卷 1599-1612页

作者： Guibo Qi Han Tang Jianian Hu Siying Kang song Qin Department of Anatomy Histologyand EmbryologySchool of Basic Medical SciencesFudan UniversityShanghaiChina State Key Laboratory of Medical Neurobiology and MOE Frontiers center for Brain Science Fudan UniversityShanghaiChina

Tanycytes, specialized ependymal cells located in the hypothalamus, play a crucial role in the generation of new neurons that contribute to the neural circuits responsible for regulating the systemic energy balance. The precise coordination of the gene networks controlling neurogenesis in naive and mature tanycytes is essential for maintaining homeostasis in adulthood. However, our understanding of the molecular mechanisms and signaling pathways that govern the proliferation and differentiation of tanycytes into neurons remains limited. This article aims to review the recent advancements in research into the mechanisms and functions of tanycyte-derived neurogenesis. Studies employing lineage-tracing techniques have revealed that the neurogenesis specifically originating from tanycytes in the hypothalamus has a compensatory role in neuronal loss and helps maintain energy homeostasis during metabolic diseases. Intriguingly,metabolic disorders are considered early biomarkers of Alzheimer's disease. Furthermore,the neurogenic potential of tanycytes and the state of newborn neurons derived from tanycytes heavily depend on the maintenance of mild microenvironments, which may be disrupted in Alzheimer's disease due to the impaired blood–brain barrier ***, the specific alterations and regulatory mechanisms governing tanycyte-derived neurogenesis in Alzheimer's disease remain unclear. Accumulating evidence suggests that tanycyte-derived neurogenesis might be impaired in Alzheimer's disease, exacerbating neurodegeneration. confirming this hypothesis, however, poses a challenge because of the lack of long-term tracing and nucleus-specific analyses of newborn neurons in the hypothalamus of patients with Alzheimer's disease. Further research into the molecular mechanisms underlying tanycyte-derived neurogenesis holds promise for identifying small molecules capable of restoring tanycyte proliferation in neurodegenerative diseases. This line of investigation could pro

关键词： Alzheimer's disease blood–brain barrier ependymoglial cells hypothalamus metabolic diseases neural stem cells neurogenesis neuroinflammatory diseases neurons tanycyte

Mechanism by which Rab5 promotes regeneration and functional recovery of zebrafish Mauthner axons

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Neural Regeneration Research 2025年第6期20卷 1816-1824页

作者： Jiantao cui Yueru Shen Zheng song Dinggang Fan Bing Hu center for Advanced Interdisciplinary Science and Biomedicine of IHM Division of Life Sciences and MedicineUniversity of Science and Technology of ChinaHefeiAnhui ProvinceChina

Rab5 is a GTPase protein that is involved in intracellular membrane trafficking. It functions by binding to various effector proteins and regulating cellular responses, including the formation of transport vesicles and their fusion with the cellular membrane. Rab5 has been reported to play an important role in the development of the zebrafish embryo;however, its role in axonal regeneration in the central nervous system remains unclear. In this study, we established a zebrafish Mauthner cell model of axonal injury using single-cell electroporation and two-photon axotomy techniques. We found that overexpression of Rab5 in single Mauthner cells promoted marked axonal regeneration and increased the number of intra-axonal transport vesicles. In contrast, treatment of zebrafish larvae with the Rab kinase inhibitor cID-1067700markedly inhibited axonal regeneration in Mauthner cells. We also found that Rab5 activated phosphatidylinositol 3-kinase(PI3K) during axonal repair of Mauthner cells and promoted the recovery of zebrafish locomotor function. Additionally, rapamycin, an inhibitor of the mechanistic target of rapamycin downstream of PI3K, markedly hindered axonal regeneration. These findings suggest that Rab5 promotes the axonal regeneration of injured zebrafish Mauthner cells by activating the PI3K signaling pathway.

关键词： axonal regeneration Mauthner cell nerve regeneration Rab5 zebrafish

Stochastic Augmented-Based Dual-Teaching for Semi-Supervised Medical Image Segmentation

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computers, Materials & continua 2025年第1期82卷 543-560页

作者： Hengyang Liu Yang Yuan Pengcheng Ren chengyun song Fen Luo School of computer Science and Engineering Chongqing University of TechnologyChongqing400054China college of Artificial Intelligence Chongqing Technology and Business UniversityChongqing400067China

Existing semi-supervisedmedical image segmentation algorithms use copy-paste data augmentation to correct the labeled-unlabeled data distribution ***,current copy-paste methods have three limitations:(1)training the model solely with copy-paste mixed pictures from labeled and unlabeled input loses a lot of labeled information;(2)low-quality pseudo-labels can cause confirmation bias in pseudo-supervised learning on unlabeled data;(3)the segmentation performance in low-contrast and local regions is less than *** design a Stochastic Augmentation-Based Dual-Teaching Auxiliary Training Strategy(SADT),which enhances feature diversity and learns high-quality features to overcome these *** be more precise,SADT trains the Student Network by using pseudo-label-based training from Teacher Network 1 and supervised learning with labeled data,which prevents the loss of rare labeled *** introduce a bi-directional copy-pastemask with progressive high-entropy filtering to reduce data distribution disparities and mitigate confirmation bias in *** the mixed images,Deep-Shallow Spatial contrastive Learning(DSScL)is proposed in the feature spaces of Teacher Network 2 and the Student Network to improve the segmentation capabilities in low-contrast and local *** this procedure,the features retrieved by the Student Network are subjected to a random feature perturbation *** two openly available datasets,extensive trials show that our proposed SADT performs much better than the state-ofthe-art semi-supervised medical segmentation *** only 10%of the labeled data for training,SADT was able to acquire a Dice score of 90.10%on the AcDc(Automatic cardiac Diagnosis challenge)dataset.

关键词： Semi-supervised medical image segmentation contrastive learning stochastic augmented

An efficient quantum proactive incremental learning algorithm

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Science china(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 49-57页

作者： Lingxiao Li Jing Li Yanqi song Sujuan Qin Qiaoyan Wen Fei Gao State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications School of cyberspace Security Beijing University of Posts and Telecommunications

In scenarios where a large amount of data needs to be learned, incremental learning can make full use of old knowledge, significantly reduce the computational cost of the overall learning process, and maintain high performance. In this paper, taking the Maxcut problem as our example, we introduce the idea of incremental learning into quantum computing, and propose a Quantum Proactive Incremental Learning algorithm(QPIL). Instead of a one-off training of quantum circuit, QPIL contains a multi-phase training on gradually-increased subgraphs of all vertices, proactively reducing large-scale problems to smaller ones to solve in steps, providing an efficient solution for Maxcut. Specifically, some vertices and corresponding edges are randomly selected for training to obtain optimized parameters of the quantum circuit at first. Then, in each incremental phase, the remaining vertices and corresponding edges are gradually added and the parameters obtained from the previous phase are reused in the parameter initialization of the current phase. We perform experiments on 120 different small-scale graphs, and it shows that QPIL performs superior to prevalent quantum and classical baselines in terms of approximation ratio(AR), time cost, anti-forgetting, and solving stability. In particular, QPIL's AR surpasses 20% of mainstream quantum baselines, and the time cost is less than 1/5 of them. The idea of QPIL is expected to inspire efficient and high-quality solutions in large-scale Max cut and other combinatorial optimization problems.

关键词： variational quantum algorithm incremental learning multi-phase training Maxcut quantum computing

All-optical neuromorphic devices: materials, working mechanism,and applications

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Science china chemistry 2025年

作者： song Wang Hao chen Hui Huang college of Materials Science and Opto-Electronic Technology Center of Materials Science and Optoelectronics Engineering CAS Center for Excellence in Topological Quantum Computation CAS Key Laboratory of Vacuum Physics University of Chinese Academy of Sciences college of chemistry and Molecular Engineering Peking University

Traditional von Neumann computing, with physical separation of memory and processing units, cannot satisfy the development of artificial intelligence and cloud computing. Neuromorphic computing, inspired by the human brain, has drawn much ***-optical neuromorphic (AON) devices employ optical signals as information carriers and leverage the neuromorphic functions to implement fast operation speed, low energy consumption, and high bandwidth of neuromorphic computing. Here, we discuss the recent progress in AON devices, including materials, device performance, working mechanisms, and applications. Moreover,the advantages and limitations of AON are presented and discussed. Finally, the perspective of AON devices points out the future research direction of neuromorphic computing.

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Electrochemical conversion of methane to bridge the gap in the artificial carbon cycle

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Journal of Energy chemistry 2025年第1期100卷 286-308页

作者： Yuhao Peng Yuefeng song Ihar Razanau Juanxiu Xiao Wei Xiao Di Hu Guoxiong Wang college of chemistry and Molecular Sciences Hubei Key Laboratory of Electrochemical Power Sources Wuhan University State Key Laboratory of catalysis Dalian National Laboratory for Clean Energy iChEM (Collaborative Innovation Center of Chemistry for Energy Materials) Dalian Institute of Chemical Physics Chinese Academy of Sciences Laboratory of Physical-chemical Technologies SSPA Scientific and Practical Materials Research Centre of NAS of Belarus State Key Laboratory of Marine Resources Utilization in South china Sea Collaborative Innovation Center of Marine Science and Technology School of Marine Science and Engineering Hainan University Department of chemical and Environmental Engineering University of Nottingham Ningbo China

Methane, an abundant one-carbon（c1） resource, is extensively used in the industrial production of vital fuels and value-added chemicals. However, current industrial methane conversion technologies are energy-and carbon-intensive, mainly due to the high activation energy required to break the inert c–H bond, low selectivity, and problematic side reactions, including cO2emissions and coke deposition. Electrochemical conversion of methane（EcM） using intermittent renewable energy offers an attractive solution, due to its modular reactor design and operational flexibility across a broad spectrum of temperatures and pressures. This review emphasizes conversion pathways of methane in various reaction systems, highlighting the significance and advantages of EcM in facilitating a sustainable artificial carbon cycle. This work provides a comprehensive overview of conventional methane activation mechanisms and delineates the complete pathways of methane conversion in electrolysis contexts. Based on surface/interface chemistry, this work systematically analyzes proposed reaction pathways and corresponding strategies to enhance EcM efficiency towards various target products, including syngas, hydrocarbons, oxygenates, and advanced carbon materials. The discussion also encompasses opportunities and challenges for the EcM process, including insights into EcM pathways, rational electrocatalyst design, establishment of benchmarking protocols, electrolyte engineering, enhancement of cH4conversion rates, and minimization of cO2emission.

关键词： Activation energy

clinical observation of white eye distribution in patients with hyperlipidemia: an artificial intelligence digital visual examination technique

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Journal of Traditional chinese Medicine 2025年

作者： song Tianli LI Haixia LIU Li'an Department of cardiology， the Guang'anmen Hospital， china Academy of chinese Medical Sciences National college， Beijing University of chinese Medicine

Objective: To explore the clinical observation of white eye distribution characteristics of hyperlipidemic patients based on artificial intelligence digital eye diagnosis technology. Methods: One hundred and fifty subjects were examined in the outpatient and inpatient departments of Guang'anmen Hospital of the china Academy of Traditional chinese Medicine from 01 February 2022 to 01 February 2023， including 80 cases in the hyperlipidemic patient (HLP) group and 70 cases in the normal lipid level patient (Nc) group. The two groups were collected and extracted by the artificial intelligence visual diagnostic instrument and analyzed by the MyEyeD-10 white eye shadowless imaging health intelligence analysis system. Finally， SPSS 26.0 (Version X; IBM corp.， Armonk， NY， USA) was used for statistical processing. Results: Significant differences were noted in the scores of "spot" and "foggy" features between the two groups. Between groups， the "spot" feature score of the white eye morphology in the HLP group (11.07 ± 3.22) was higher than that in the Nc group (7.50 ± 4.11) (P core of the eye morphology in the HLP group (8.37 ± 2.25) was higher than that in the Nc group (P c group (5.72 ± 1.21) (P cant differences in the "A" (stomach)， "B"， "O" (spleen)， and "M" (liver) eye-contact region scores between the two groups， and the "B"， "O" (spleen) and "M" (liver) eye-contact region scores were significantly different. The scores of the white eye channel region in the HLP group were significantly higher than those in the control group， with the "A"， "B"， and "O" regions (P cores of "dull red" and "yellow" features were significantly different， and the scores of "dull red" and "yellow" colors of the white eye choroid in the HLP group were significantly higher than those in the HLP g

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