检索结果-内蒙古大学图书馆

21st Pacific Rim International Conference on Artificial Intelligence, PRICAI 2024

作者： Cheng, Shi Li, Quan Zhang, Guangyu Zhang, Lei Peng, Tao School of Future Science and Engineering Soochow University Suzhou China Center of Stomatology The Second Affiliated Hospital of Soochow University Suzhou China Division of Cardiology Department of Internal Medicine Tongji Hospital Tongji Medical College Huazhong University of Science and Technology Wuhan China Graduate Program of Medical Physics and Data Science Research Center Duke Kunshan University Jiangsu Kunshan China

ISBN: (纸本)9789819601240

The delineation of Lymph Nodes (LNs) is pivotal in pinpointing therapeutic targets for radiotherapy in head and neck malignancies. Nevertheless, this endeavor poses a formidable challenge, primarily stemming from the suboptimal contrast against adjacent tissues. This investigation introduces a deep learning methodology aimed at automating the segmentation of LNs within CT scans, offering the following contributions: (1) Expanding upon the 3D Unet model, we incorporate a parallel block consisting of attention gate and squeeze & excitation modules. We extensively evaluate various versions of this parallel block and achieve favorable performance. (2) To address the slow decrease in Dice loss, we introduce a lightweight boundary refinement module. Our proposed method is assessed on a dataset comprising 103 patients and 603 Lymph Nodes (LNs), with 452 nodes used for training and 151 nodes for testing. The node-level Dice similarity coefficient achieved by our method reaches an impressive 0.833. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Computerized tomography

来源：评论

学校读者我要写书评

暂无评论

Cytocompatible and antibacterial Fe-, Cu- and Zn-substituted calcium hydroxyapatite materials for skin applications

引用

Ceramics International 2025年第9期51卷 11286-11296页

作者： Lukaviciute, L. Lukowiak, A. Stankeviciute, Z. Junka, A. Mortimer, M. Zarkov, A. Yang, J.-C. Ganceviciene, R. Kareiva, A. Faculty of Chemistry and Geosciences Vilnius University Naugarduko st. 24 Vilnius03225 Lithuania Institute of Low Temperature and Structure Research Polish Academy of Sciences Okolna 2 Wroclaw50422 Poland Department of Pharmaceutical Microbiology and Parasitology Wroclaw Medical University Borowska 211A Wroclaw50556 Poland Laboratory of Environmental Toxicology National Institute of Chemical Physics and Biophysics Akadeemia tee 23 Tallinn12618 Estonia Graduate Institute of Nanomedicine and Medical Engineering International Ph.D. Program in Biomedical Engineering College of Biomedical Engineering Research Center of Biomedical Device Research Center of Digital Oral Science and Technology Taipei Medical University Taiwan Faculty of Medicine Vilnius University M.K. Ciurlionio st. 21 Vilnius03101 Lithuania

Calcium hydroxyapatite (C10(PO4)6(OH)2;CHAp) and metal-substituted samples (Fe:CHAp, Cu:CHAp, and Zn:CHAp) were synthesized using a recently developed method. This method involved the wet precipitation of amorphous calcium phosphate (ACP), followed by solid-state reaction synthesis of α-tricalcium phosphate (α-TCP), and finally hydrothermal synthesis of CHAp. The effect of Fe3+, Cu2+, and Zn2+ substitution on the phase purity and antimicrobial properties of CHAp are summarized in this study. Notably, it highlights the phase purity of CHAp and Zn:CHAp (in the presence of Fe3+ and Cu2+ ions, the α- and β-TCP phases have formed) as well as the antimicrobial activity of Zn:CHAp and Cu:CHAp against Staphylococcus aureus and Candida albicans. The synthesized nanosized CHAp, Fe:CHAp, Cu:CHAp, and Zn:CHAp samples were used as additives in the preparation of skin creams. In vitro biological studies of the resulting skin creams demonstrated their antimicrobial activity against Pseudomonas aeruginosa, and showed a reduction in osteoblasts cells viability of in the range of 20–40 %. The addition of zinc enhances antimicrobial efficacy but reduces biocompatibility, while copper maintains both high antimicrobial activity and biocompatibility, making it more suitable for the development of medical or cosmetic materials. Dermal creams containing CHAp with copper and iron ions also show significant antimicrobial activity while preserving good cell viability. These results highlight the importance of optimizing the balance between antimicrobial effectiveness and biocompatibility in these materials. © 2024

关键词： Biocompatibility

来源：评论

学校读者我要写书评

暂无评论

Cryptotanshinone Suppresses the STAT3/BCL-2 Pathway to Provoke Human Bladder Urothelial Carcinoma Cell Death

引用

Environmental Toxicology 2025年第4期40卷 624-635页

作者： Tung, Min-Che Chang, Ge-Man Dai, Wen-Chyi Hsu, Chen-Hsuan Chang, Hsiang-Chun Yang, Wei-Ting Ho, Yann-Jen Lu, Chien-Hsing Chen, Yi-Hsin Chang, Chia-Che Division of Urology Department of Surgery Tungs' Taichung MetroHarbor Hospital Taichung Taiwan Graduate Institute of Biomedical Sciences National Chung Hsing University Taichung Taiwan Doctoral Program in Biotechnology Industrial Innovation and Management National Chung Hsing University Taichung Taiwan Department of Life Sciences National Chung Hsing University Taichung Taiwan Department of Obstetrics and Gynecology Taichung Veterans General Hospital Taichung Taiwan Doctoral Program in Translational Medicine National Chung Hsing University Taichung Taiwan Department of Nephrology Taichung Tzu Chi Hospital Buddhist Tzu chi Medical Foundation Taichung Taiwan School of Medicine Tzu Chi University Hualein Taiwan Department of Artificial Intelligence and Data Science National Chung Hsing University Taichung Taiwan Master Program in Precision Health Rong Hsing Research Center for Translational Medicine The iEGG and Animal Biotechnology Research Center National Chung Hsing University Taichung Taiwan Department of Medical Laboratory Science and Biotechnology Asia University Taichung Taiwan Department of Medical Research China Medical University Hospital Taichung Taiwan

Bladder cancer is one of the most common human malignancies worldwide. Aberrant activation of signal transducer and activator of transcription 3 (STAT3) is crucial to driving malignant progression and predicting poor prognosis of multiple human cancers, including bladder cancer, making STAT3 a promising target of cancer therapeutics. Cryptotanshinone (CTS) is an anticancer ingredient of Danshen (Salvia miltiorrhiza), a top-graded Chinese medicinal herb. However, whether CTS targets STAT3 to exert its cytotoxic effect on human bladder cancer remains unknown. Herein, we demonstrated that CTS is cytotoxic to multiple human urinary bladder transitional cell carcinoma (TCC) cell lines while sparing normal human urothelial cells. CTS provoked apoptosis-dependent bladder TCC cytotoxicity, as apoptosis blockage by z-VAD-fmk markedly rescued the clonogenicity of CTS-treated cells. Besides, CTS was found to suppress constitutive and interleukin 6-inducible activation of STAT3, evidenced by the downregulation of STAT3 tyrosine 705 phosphorylation and BCL2, a recognized STAT3 transcriptional target. Notably, ectopic expression of a dominant-active STAT3 mutant (STAT3-C) or BCL-2 alleviated CTS-induced apoptosis and clonogenicity inhibition, thus confirming STAT3 blockade as a pivotal mechanism of CTS's cytotoxic action on bladder TCC cells. Lastly, immunoblotting revealed that CTS lowered the levels of active JAK2, an upstream kinase that mediates STAT3 tyrosine 705 phosphorylation. Altogether, we conclude that the blockade of the JAK2/STAT3/BCL-2 antiapoptotic signaling axis is a vital mechanism whereby CTS provokes bladder cancer cytotoxicity. The current evidence implicates CTS's potential to be translated into a bladder cancer therapeutic agent. © 2024 Wiley Periodicals LLC.

关键词： Cell death

来源：评论

学校读者我要写书评

暂无评论

Enhanced Performance and data Privacy in Lung Nodule Classification via Federated Deep Learning Approach 24

Enhanced Performance and Data Privacy in Lung Nodule Classif...

引用

2024 7th International Conference on Healthcare Service Management, ICHSM 2024

作者： Nguyen, Duc-Khanh Li, Ai-Hsien Adam Lai, Yen-Jun Chiu, Yen-Ling Phan, Dinh-Van Chien, Ting-Ying Chan, Chien-Lung Department of Information Management Yuan Ze University Taoyuan Taiwan Department of Statistics and Informatics University of Economics The University of Danang Danang Viet Nam Division of Cardiology Far Eastern Memorial Hospital New Taipei Taiwan Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan Taiwan Department of Radiology Far Eastern Memorial Hospital New Taipei Taiwan Graduate Institute of Medicine and Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan Taiwan Department of Medical Research Far Eastern Memorial Hospital New Taipei Taiwan Department of Computer Science and Engineering Yuan Ze University Taoyuan Taiwan ZDT Group- YZU Joint Research and Development Center for Big Data Taoyuan Taiwan Yuan Ze University Taoyuan Taiwan

ISBN: (纸本)9798400710162

This study explores the feasibility of deep learning for classifying nodule neoplasms, analyzing their performance on two openly available datasets, LUNGx SPIE, and LIDC-IDRI. These datasets offer valuable diversity in image quantity, quality, and malignancy annotation methodologies, posing a real-world challenge for effective model development. To handle the disparities in these diverse datasets, we aim to develop a robust classification model trained using federated learning. This decentralized approach allows model training across datasets without sharing patient data, preserving privacy and overcoming data fragmentation. Our experiments demonstrate that federated learning enables the development of a robust and superior deep learning model compared to individual models trained on limited data. This combination of deep learning, and federated learning holds immense promise for nodule neoplasm classification and can significantly improve patient care and outcomes. © 2024 Copyright held by the owner/author(s).

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

Biomedical data and AI

引用

science China Life sciences 2025年第5期68卷 1536-1540页

作者： Hao Xu Shibo Zhou Zefeng Zhu Vincenzo Vitelli Liangyi Chen Ziwei Dai Ning Yang Luhua Lai Shengyong Yang Sergey Ovchinnikov Zhuoran Qiao Sirui Liu Chen Song Jianfeng Pei Han Wen Jianfeng Feng Yaoyao Zhang Zhengwei Xie Yang-Yu Liu Zhiyuan Li Fulai Jin Hao Li Mohammad Lotfollahi Xuegong Zhang Ge Yang Shihua Zhang Ge Gao Pulin Li Qi Liu Jing-Dong Jackie Han Peking-Tsinghua Center for Life Sciences (CLS) Academy for Advanced Interdisciplinary StudiesPeking University Center for Quantitative Biology (CQB) Academy for Advanced Interdisciplinary StudiesPeking University Peking University-Tsinghua University-National Institute of Biological Sciences Joint Graduate Program Academy for Advanced Interdisciplinary StudiesPeking University Department of Physics University of Chicago School of Life Sciences Southern University of Science and Technology Peking University Chengdu Academy for Advanced Interdisciplinary Biotechnologies College of Chemistry and Molecular Engineering Peking University Department of Biotherapy Cancer Center and State Key Laboratory of BiotherapyWest China HospitalSichuan University Department of Biology Massachusetts Institute of Technology Lambic Therapeutics Inc. Changping Laboratory Al for Science Institute Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence Fudan University Department of Obstetrics and Gynecology West China Second University HospitalSichuan University Peking University International Cancer Institute and Peking University-Yunnan Baiyao International Medical Institute and State Key Laboratory of Natural and Biomimetic Drugs Department of Molecular and Cellular PharmacologySchool of Pharmaceutical SciencesPeking University Health Science CenterPeking University Channing Division of Network Medicine Department of MedicineBrigham and Women's Hospital and Harvard Medical School Center for Artificial Intelligence and Modeling the Carl R.Woese Institute for Genomic BiologyUniversity of Illinois Urbana-Champaign Department of Genetics and Genome Sciences School of Medicine and Department of Computer and Data Sciences and Department of Population and Quantitative Health SciencesCase Western Reserve University Department of Biochemistry and Biophysics University of California Sanger Institute Department of Automation Tsinghua University State Key Laboratory of Multimodal Artificial Intelligence Systems I

The development of artificial intelligence(AI) and the mining of biomedical data complement each other. From the direct use of computer vision results to analyze medical images for disease screening, to now integrating biological knowledge into models and even accelerating the development of new AI based on biological discoveries, the boundaries of both are constantly expanding, and their connections are becoming closer.

关键词：

来源：评论

学校读者我要写书评

暂无评论

programming Variational Quantum Circuits with Quantum-Train Agent

Programming Variational Quantum Circuits with Quantum-Train ...

引用

Quantum Communications, Networking, and Computing (QCNC), International Conference on

作者： Chen-Yu Liu Samuel Yen-Chi Chen Kuan-Cheng Chen Wei-Jia Huang Yen-Jui Chang Graduate Institute of Applied Physics National Taiwan University Taipei Taiwan Hon Hai (Foxconn) Research Institute Taipei Taiwan Wells Fargo New York NY USA Department of Electrical and Electronic Engineering Imperial College London London UK Centre for Quantum Engineering Science and Technology (QuEST) Imperial College London London UK Quantum Information Center Chung Yuan Christian University Taoyuan City Taiwan Master Program in Intelligent Computing and Big Data Chung Yuan Christian University Taoyuan City Taiwan

ISBN: (数字)9798331531591

ISBN: (纸本)9798331531607

This study introduces the Quantum-Train Quantum Fast Weight programmer (QT-QFWP) framework, enabling efficient and scalable programming of variational quantum circuits (VQCs) through quantum-driven parameter updates for the classical slow programmer controlling the fast programmer VQC. By optimizing quantum and classical parameter management, QT-QFWP significantly reduces parameters (by 70–90%) compared to Quantum Long Short-Term Memory (QLSTM) and Quantum Fast Weight programmer (QFWP) while maintaining accuracy. Benchmarking on time-series tasks—including Damped Simple Harmonic Motion (SHM), NARMA5, and Simulated Gravitational Waves (GW)—demonstrates superior efficiency and predictive accuracy. QT-QFWP is particularly advantageous for near-term quantum systems, addressing qubit and gate fidelity constraints, enhancing VQC deployment in time-sensitive applications, and expanding quantum computing’s role in machine learning.

关键词： Quantum system Accuracy Computational modeling Qubit Neural networks programming Predictive models Quantum circuit physics Long short term memory

来源：评论

学校读者我要写书评

暂无评论

Stimuli-responsive smart nanomaterials for theranostics of urological cancers

引用

Coordination Chemistry Reviews 2025年 539卷

作者： Xu, Yi Moradialvand, Madineh Sala, Francesca Della Zare, Ehsan Nazarzadeh Hushmandi, Kiavash Rahimmanesh, Ilnaz Borzacchiello, Assunta Iravani, Siavash Zare, Iman Shin, Jungah Yoon, Juyoung Kang, Heemin Makvandi, Pooyan Department of Urology Department of Science & Technology Nano Medical Innovation & Collaboration Group (NMICG) The Quzhou Affiliated Hospital of Wenzhou Medical University Quzhou People's Hospital Quzhou 324000 China The Quzhou Affiliated Hospital of Wenzhou Medical University Quzhou People's Hospital Quzhou 324000 China Center for Theoretical Physics Khazar University 41 Mehseti Street Baku AZ1096 Azerbaijan Institute of Polymers Composites and Biomaterials National Research Council (IPCB-CNR) Viale J.F. Kennedy 54 Naples 80125 Italy School of Chemistry Damghan University Damghan 36716-45667 Iran Nephrology and Urology Research Center Clinical Sciences Institute Baqiyatallah University of Medical Sciences Tehran Iran Applied Physiology Research Center Cardiovascular Research Institute Isfahan University of Medical Sciences Isfahan Iran W Nazar ST Boostan Ave Isfahan Iran Research and Development Department Sina Medical Biochemistry Technologies Co. Ltd. Shiraz *** Iran Department of Materials Science and Engineering Korea University Seoul 02841 South Korea Department of Chemistry and Nanoscience Ewha Womans University Seoul 03760 South Korea Graduate Program in Innovative Biomaterials Convergence Ewha Womans University Seoul 03760 South Korea College of Medicine Korea University Seoul 02841 South Korea

Urological cancers, including prostate, bladder, and kidney cancers, contribute significantly to the global burden of cancer-related mortality. While numerous reviews have addressed these cancers individually, this is the first comprehensive review that exclusively focuses specifically on nanotheranostics as a transformative approach for urological cancer. The distinct tumor microenvironments (TMEs) associated with these cancers pose both challenges and opportunities for precise nanotherapeutic interventions. This review provides a thorough examination of current advancements in nanotechnology-based diagnostics and therapeutics tailored to urological cancers. For each primary urological cancer type, we outline key strategies for leveraging nanotheranostics in the detection and treatment of tumors. Furthermore, we address the persisting challenges in enhancing tumor specificity and treatment efficacy. In essence, nanotheranostics offer a promising therapeutic avenue for urological cancers by enabling targeted drug delivery and controlled release of therapeutics within the tumor microenvironment. The objective of this pioneering review is to underscore recent developments and future prospects in utilizing nanotechnology to meet the unmet needs in the diagnosis and treatment of urological cancers. © 2025 Elsevier B.V.

关键词： Bladder Kidney cancers Nanocarriers Nanomaterials Prostate tumor Urological cancers

来源：评论

学校读者我要写书评

暂无评论

Correction: Spatial organization of B lymphocytes and prognosis prediction in patients with gastric cancer

引用

Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association 2025年 2025 May 16页

作者： Ryan Yong Kiat Tay Manavi Sachdeva Haoran Ma Young-Woo Kim Myeong-Cherl Kook Hyunki Kim Jae-Ho Cheong Lindsay C Hewitt Katharina Nekolla Günter Schmidt Takaki Yoshikawa Takashi Oshima Tomio Arai Supriya Srivastava Ming Teh Xuewen Ong Su Ting Tay Taotao Sheng Joseph J Zhao Patrick Tan Heike I Grabsch Raghav Sundar Yong Loo Lin School of Medicine National University of Singapore 1E Kent Ridge Road Singapore 119228 Singapore. Department of Haematology-Oncology National University Cancer Institute National University Hospital Singapore Singapore. Cancer and Stem Cell Biology Program Duke-NUS Medical School Singapore Singapore. Department of Cancer Policy and Population Health National Cancer Center Graduate School of Cancer Science and Policy and Center for Gastric Cancer and Department of Surgery National Cancer Center Goyang Republic of Korea. Center for Gastric Cancer Department of Pathology National Cancer Center Goyang Republic of Korea. Department of Pathology Yonsei University College of Medicine Seoul Republic of Korea. Department of Surgery Yonsei University College of Medicine Seoul Republic of Korea. Department of Pathology GROW Research Institute for Oncology and Reproduction Maastricht University Medical Center+ Maastricht The Netherlands. Department of Precision Medicine GROW School for Oncology and Reproduction Maastricht University Center+ Maastricht The Netherlands. Computational Pathology Oncology R&D AstraZeneca Munich Germany. Department of Surgery Kanagawa Cancer Center Yokohama Japan. Department of Surgery Yokohama City University Yokohama Japan. Department of Surgery Tokyo Metropolitan Cancer and Infectious Diseases Center Komagome Hospital Tokyo Japan. Department of Pathology Tokyo Metropolitan Institute for Geriatrics and Gerontology Tokyo Japan. Department of Medicine National University of Singapore Singapore Singapore. Department of Pathology National University Hospital Singapore Singapore. Genome Institute of Singapore Agency for Science Technology and Research Singapore Singapore. Cancer Science Institute of Singapore National University of Singapore Singapore Singapore. Cellular and Molecular Research National Cancer Centre Singapore Singapore. Singhealth/Duke-NUS Institute of Precision Medicine National Heart Centre Singapore

来源：评论

学校读者我要写书评

暂无评论

Electron spin dynamics guide cell motility

arXiv

引用

arXiv 2025年

作者： Wang, Kai Gilmer, Gabrielle Araña, Matheus Cândia Iijima, Hirotaka Bergmann, Juliana Woollard, Antonio Mesits, Boris McGraw, Meghan Zoltowski, Brian Cappellaro, Paola Ungar, Alex Pekker, David Waldeck, David H. Saxena, Sunil Lloyd, Seth Ambrosio, Fabrisia Discovery Center for Musculoskeletal Recovery Schoen Adams Research Institute at Spaulding BostonMA United States Department of Physical Medicine & Rehabilitation Spaulding Rehabilitation Hospital BostonMA United States Department of Physical Medicine & Rehabilitation Harvard Medical School BostonMA United States Cellular and Molecular Pathology Graduate Program University of Pittsburgh PittsburghPA United States Medical Scientist Training Program School of Medicine University of Pittsburgh PittsburghPA United States École Polytechnique Institut Polytechnique de Paris Palaiseau France Department of Physics & Astronomy University of Pittsburgh PittsburghPA United States Department of Chemistry Southern Methodist University DallasTX United States Department of Nuclear Science and Engineering Massachusetts Institute of Technology CambridgeMA02139 United States Department of Physics Massachusetts Institute of Technology CambridgeMA02139 United States Department of Chemistry University of Pittsburgh PittsburghPA United States Department of Mechanical Engineering Massachusetts Institute of Technology BostonMA United States

Diverse organisms exploit the geomagnetic field (GMF) for migration. Migrating birds employ an intrinsically quantum mechanical mechanism for detecting the geomagnetic field: absorption of a blue photon generates a radical pair whose two electrons precess at different rates in the magnetic field, thereby sensitizing cells to the direction of the GMF. In this work, using an in vitro injury model, we discovered a quantum-based mechanism of cellular migration. Specifically, we show that migrating cells detect the GMF via an optically activated, electron spin-based mechanism. Cell injury provokes acute emission of blue photons, and these photons sensitize muscle progenitor cells to the magnetic field. We show that the magnetosensitivity of muscle progenitor cells is (a) activated by blue light, but not by green or red light, and (b) disrupted by the application of an oscillatory field at the frequency corresponding to the energy of the electron-spin/magnetic field interaction. A comprehensive analysis of protein expression reveals that the ability of blue photons to promote cell motility is mediated by activation of calmodulin calcium sensors. Collectively, these data suggest that cells possess a light-dependent magnetic compass driven by electron spin dynamics. © 2025, CC BY.

关键词： Spin dynamics

来源：评论

学校读者我要写书评

暂无评论

AI-Based Intelligent-Annotation Algorithm for medical Segmentation from Ultrasound data 20th

AI-Based Intelligent-Annotation Algorithm for Medical Segmen...

引用

20th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2023

作者： Peng, Tao Zhang, Yaogong Dong, Yan Ruan, Yiwen Jin, Rui Liu, Zhaorui Wu, Hongzhuang Shen, Yuling Zhang, Lei School of Future Science and Engineering Soochow University Suzhou China Medical Physics Graduate Program and Data Science Research Center Duke Kunshan University Jiangsu Kunshan China Department of Ultrasonography The First Affiliated Hospital of Soochow University Suzhou China

ISBN: (纸本)9789819970247

The management of prostate cancer, a prevalent source of mortality in men, calls for meticulous delineation of the prostate in transrectal ultrasound (TRUS) images for effective treatment planning. This paper introduces a hybrid artificial intelligence approach for prostate delineation, leveraging prior information from experts, a machine learning model, and a quantum-inspired evolutionary network to augment the accuracy of prostate segmentation. The approach incorporates three novel elements: 1) limited prior information from expert and adaptive polygon tracking (APT) module for initial segmentation;2) a novel historical storage-based quantum-inspired evolutionary network (HQIE) mechanism to search for the optimal neural network and enhancing solution diversity and capacity to address unimodal and multimodal challenges, and 3) a unique mathematical formulation denoted by parameters of the neural network is used to achieve smooth prostate periphery. The method was evaluated across various noise conditions and against several state-of-the-art methods using a multi-center dataset. In addition, an ablation study was performed to evaluate the efficacy of each component. The results demonstrated the superior performance of the hybrid AI method (Dice index: 96.4 ± 2.4%) against state-of-the-art deep learning methods (e.g., UTNet, Dice index: 90.1 ± 5.7%). The hybrid method also showed higher robustness to image noise than traditional methods. This study suggests new insights and technical approaches in the field of prostate segmentation using hybrid artificial intelligence methods. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Ultrasonics

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：