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Removal of intrahepatic bile duct stone could reduce the risk of cholangiocarcinoma: A single-center retrospective study in South Korea

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World Journal of Clinical Cases 2024年第5期12卷 913-921页

作者： Tae In Kim Sung Yong han Jonghyun Lee Dong uk Kim Division of Gastroenterology Biomedical Research InstitutePusan National University HospitalBusan 49241South Korea Department of Internal Medicine Pusan National UniversityCollege of MedicineYangsan 50612South Korea

BACKGROUND Intrahepatic duct(IHD)stones are among the most important risk factors for cholangiocarcinoma(CCC).Approximately 10%of patients with IHD stones develop CCC;however,there are limited studies regarding the effect of IHD stone removal on CCC development.AIM To investigate the association between IHD stone removal and CCC development.METHODS We retrospectively analyzed 397 patients with IHD stones at a tertiary referral center between January 2011 and December 2020.RESULTS CCC occurred in 36 of the 397 enrolled patients.In univariate analysis,chronic hepatitis B infection(11.1%vs 3.0%,P=0.03),carbohydrate antigen 19-9(CA19-9,176.00 vs 11.96 II/mL,P=0.010),stone located in left or both lobes(86.1%vs 70.1%,P=0.042),focal atrophy(52.8%vs 26.9%,P=0.001),duct stricture(47.2%vs 24.9%,P=0.004),and removal status of IHD stone(33.3%vs 63.2%,Pupper normal limit,carcinoembryonic antigen>upper normal limit,stones located in the left or both lobes,focal atrophy,and complete removal of IHD stones without recurrence were independent factors influencing CCC development.However,the type of removal method was not associated with CCC risk.CONCLUSION Complete removal of IHD stones without recurrence could reduce CCC risk.

关键词： Intrahepatic bile duct stone Cholangiocarcinoma Percutaneous transhepatic cholangioscopy Endoscopic retrograde cholangiopancreatography Carbohydrate antigen 19-9

Survival benefit of concurrent chemoradiotherapy for advanced ampulla of Vater cancer

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World Journal of Clinical Cases 2024年第2期12卷 267-275页

作者： Chae Hwa Kwon Hyung Il Seo Dong uk Kim Sung Yong han Suk Kim Nam Kyung Lee Seung Baek Hong Ji Hyun Ahn Young Mok Park Byeong Gwan Noh BioMedical Research Institute Pusan National University HospitalBusan 49241South Korea Department of Surgery Pusan National University School of Medicine and Biomedical Research InstitutePusan National University HospitalBusan 49241South Korea Department of Internal Medicine Pusan National University School of Medicine and Biomedical Research InstitutePusan National University HospitalBusan 49241South Korea Department of Radiology Pusan National University School of Medicine and Biomedical Research InstitutePusan National University HospitalBusan 49241South Korea Department of Pathology and Biomedical Research Institute Pusan National University HospitalBusan 49241South Korea

BACKGROUND Currently,there is no standard adjuvant therapy for patients with resected ampulla of Vater(AoV)cancer.AIM To evaluate the effectiveness of adjuvant concurrent chemoradiotherapy(CCRT)in patients with advanced AoV cancer who underwent curative resection.METHODS This single-centered,retrospective study included 29 patients with advanced AoV cancer who underwent pancreaticoduodenectomy between 2006 and 2018.The impact of CCRT on advanced AoV cancer was analyzed.RESULTS The 1-,3-,and 5-yr recurrence-free survival(RFS)rates for patients with advanced AoV cancer were 82.8%,48.3%,and 40.8%,respectively,and the overall survival(OS)rates were 89.7%,62.1%,and 51.7%,respectively.Lymphovas-cular invasion was found to be a significant risk factor for RFS and OS in patients with advanced AoV cancer in the univariate analysis,whereas T stage and lymph node metastasis were significantly associated with OS in the multivariate analysis.Compared to the patients who did not receive adjuvant CCRT,those who received adjuvant CCRT did not show statistically significant improvements in the RFS and OS,although they had a significantly lower average age and significantly higher platelet-to-lymphocyte ratio.CONCLUSION Adjuvant CCRT did not improve survival outcomes in patients with advanced AoV cancer.These findings contribute to existing knowledge on the effectiveness of CCRT in this patient population and provide important insights for clinical decision-making.

关键词： Advanced ampulla of Vater cancer Adjuvant concurrent chemoradiotherapy Recurrence Survival Vater cancer

Reactor field reconstruction from sparse and movable sensors using Voronoi tessellation-assisted convolutional neural networks

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Nuclear Science and Techniques 2024年第5期35卷 173-185页

作者： He-Lin Gong han Li Dunhui Xiao Sibo Cheng Paris Elite Institute of Technology Shanghai Jiao Tong UniversityShanghai 200240China School of Mathematical Sciences Tongji UniversityShanghai 200092China Department of Computing Data Science InstituteImperial College LondonLondon SW72AZUK

The aging of operational reactors leads to increased mechanical vibrations in the reactor interior.The vibration of the incore sensors near their nominal locations is a new problem for neutronic field reconstruction.Current field-reconstruction methods fail to handle spatially moving sensors.In this study,we propose a Voronoi tessellation technique in combination with convolutional neural networks to handle this challenge.Observations from movable in-core sensors were projected onto the same global field structure using Voronoi tessellation,holding the magnitude and location information of the sensors.General convolutional neural networks were used to learn maps from observations to the global field.The proposed method reconstructed multi-physics fields(including fast flux,thermal flux,and power rate)using observations from a single field(such as thermal flux).Numerical tests based on the IAEA benchmark demonstrated the potential of the proposed method in practical engineering applications,particularly within an amplitude of 5 cm around the nominal locations,which led to average relative errors below 5% and 10% in the L_(2) and L_(∞)norms,respectively.

关键词： Voronoi tessellation Field reconstruction Nuclear reactors Reactor physics On-line monitoring

Nonlinear Filtering With Sample-Based Approximation Under Constrained Communication:Progress, Insights and Trends

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IEEE/CAA Journal of Automatica Sinica 2024年第7期11卷 1539-1556页

作者： Weihao Song Zidong Wang Zhongkui Li Jianan Wang Qing-Long han IEEE the State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering ScienceCollege of Engineering Peking University the Department of Computer Science Brunel University London the School of Aerospace Engineering Beijing Institute of Technology the School of Science Computing and Engineering Technologies Swinburne University of Technology

The nonlinear filtering problem has enduringly been an active research topic in both academia and industry due to its ever-growing theoretical importance and practical significance.The main objective of nonlinear filtering is to infer the states of a nonlinear dynamical system of interest based on the available noisy measurements. In recent years, the advance of network communication technology has not only popularized the networked systems with apparent advantages in terms of installation,cost and maintenance, but also brought about a series of challenges to the design of nonlinear filtering algorithms, among which the communication constraint has been recognized as a dominating concern. In this context, a great number of investigations have been launched towards the networked nonlinear filtering problem with communication constraints, and many samplebased nonlinear filters have been developed to deal with the highly nonlinear and/or non-Gaussian scenarios. The aim of this paper is to provide a timely survey about the recent advances on the sample-based networked nonlinear filtering problem from the perspective of communication constraints. More specifically, we first review three important families of sample-based filtering methods known as the unscented Kalman filter, particle filter,and maximum correntropy filter. Then, the latest developments are surveyed with stress on the topics regarding incomplete/imperfect information, limited resources and cyber security.Finally, several challenges and open problems are highlighted to shed some lights on the possible trends of future research in this realm.

关键词： Communication constraints maximum correntropy filter networked nonlinear filtering particle filter sample-based approximation unscented Kalman filter

来源：博看期刊

Structural and functional connectivity of the whole brain and subnetworks in individuals with mild traumatic brain injury:predictors of patient prognosis

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Neural Regeneration Research 2024年第7期19卷 1553-1558页

作者： Sihong Huang Jungong han Hairong Zheng Mengjun Li Chuxin Huang Xiaoyan Kui Jun Liu Department of Radiology The Second Xiangya HospitalCentral South UniversityChangshaHunan ProvinceChina Department of Computer Science Aberystwyth UniversityAberystwythCeredigionUK Shenzhen Institutes of Advanced Technology Chinese Academy of SciencesShenzhenGuangdong ProvinceChina School of Computer Science and Engineering Central South UniversityChangshaHunan ProvinceChina Department of Radiology Quality Control Center of Hunan ProvinceChangshaHunan ProvinceChina Clinical Research Center for Medical Imaging of Hunan Province ChangshaHunan ProvinceChina

Patients with mild traumatic brain injury have a diverse clinical presentation,and the underlying pathophysiology remains poorly understood.Magnetic resonance imaging is a non-invasive technique that has been widely utilized to investigate neuro biological markers after mild traumatic brain injury.This approach has emerged as a promising tool for investigating the pathogenesis of mild traumatic brain injury.G raph theory is a quantitative method of analyzing complex networks that has been widely used to study changes in brain structure and function.However,most previous mild traumatic brain injury studies using graph theory have focused on specific populations,with limited exploration of simultaneous abnormalities in structural and functional connectivity.Given that mild traumatic brain injury is the most common type of traumatic brain injury encounte red in clinical practice,further investigation of the patient characteristics and evolution of structural and functional connectivity is critical.In the present study,we explored whether abnormal structural and functional connectivity in the acute phase could serve as indicators of longitudinal changes in imaging data and cognitive function in patients with mild traumatic brain injury.In this longitudinal study,we enrolled 46 patients with mild traumatic brain injury who were assessed within 2 wee ks of injury,as well as 36 healthy controls.Resting-state functional magnetic resonance imaging and diffusion-weighted imaging data were acquired for graph theoretical network analysis.In the acute phase,patients with mild traumatic brain injury demonstrated reduced structural connectivity in the dorsal attention network.More than 3 months of followup data revealed signs of recovery in structural and functional connectivity,as well as cognitive function,in 22 out of the 46 patients.Furthermore,better cognitive function was associated with more efficient networks.Finally,our data indicated that small-worldness in the acute stage could serve as a predictor of longitudinal ch

关键词： cognitive function cross-section follow-up functional connectivity graph theory longitudinal study mild traumatic brain injury prediction small-worldness structural connectivity subnetworks whole brain network

Layered Potassium Titanium Niobate/Reduced Graphene Oxide Nanocomposite as a Potassium‑Ion Battery Anode

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Nano-Micro Letters 2024年第1期16卷 1-16页

作者： Charlie A.F.Nason Ajay Piriya Vijaya Kumar Saroja Yi Lu Runzhe Wei Yupei han Yang Xu Department of Chemistry University College London20 Gordon StreetLondon WC1H 0AJUK

With graphite currently leading as the most viable anode for potassium-ion batteries(KIBs),other materials have been left relatively underexamined.Transition metal oxides are among these,with many positive attributes such as synthetic maturity,longterm cycling stability and fast redox kinetics.Therefore,to address this research deficiency we report herein a layered potassium titanium niobate KTiNbO5(KTNO)and its rGO nanocomposite(KTNO/rGO)synthesised via solvothermal methods as a high-performance anode for KIBs.Through effective distribution across the electrically conductive rGO,the electrochemical performance of the KTNO nanoparticles was enhanced.The potassium storage performance of the KTNO/rGO was demonstrated by its first charge capacity of 128.1 mAh g^(−1) and reversible capacity of 97.5 mAh g^(−1) after 500 cycles at 20 mA g^(−1),retaining 76.1%of the initial capacity,with an exceptional rate performance of 54.2 mAh g^(−1)at 1 A g^(−1).Furthermore,to investigate the attributes of KTNO in-situ XRD was performed,indicating a low-strain material.Ex-situ X-ray photoelectron spectra further investigated the mechanism of charge storage,with the titanium showing greater redox reversibility than the niobium.This work suggests this lowstrain nature is a highly advantageous property and well worth regarding KTNO as a promising anode for future high-performance KIBs.

关键词： Potassium-ion batteries Intercalation Transition metal oxides Anodes Nanocomposite

Double integral-enhanced Zeroing neural network with linear noise rejection for time-varying matrix inverse

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CAAI Transactions on Intelligence Technology 2024年第1期9卷 197-210页

作者： Bolin Liao Luyang han Xinwei Cao Shuai Li Jianfeng Li College of Computer Science and Engineering Jishou UniversityJishouChina School of Management Shanghai UniversityShanghaiChina School of Engineering Swansea UniversitySwanseaUK

In engineering fields,time-varying matrix inversion(TVMI)issue is often encountered.Zeroing neural network(ZNN)has been extensively employed to resolve the TVMI problem.Nevertheless,the original ZNN(OZNN)and the integral-enhanced ZNN(IEZNN)usually fail to deal with the TVMI problem under unbounded noises,such as linear noises.Therefore,a neural network model that can handle the TVMI under linear noise interference is urgently needed.This paper develops a double integral-enhanced ZNN(DIEZNN)model based on a novel integral-type design formula with inherent linear-noise tolerance.Moreover,its convergence and robustness are verified by deriva-tion strictly.For comparison and verification,the OZNN and the IEZNN models are adopted to resolve the TVMI under multiple identical noise environments.The experi-ments proved that the DIEZNN model has excellent advantages in solving TVMI problems under linear noises.In general,the DIEZNN model is an innovative work and is proposed for the first time.Satisfyingly,the errors of DIEZNN are always less than 1�10−3 under linear noises,whereas the error norms of OZNN and IEZNN models are not convergent to zero.In addition,these models are applied to the control of the controllable permanent magnet synchronous motor chaotic system to indicate the superiority of the DIEZNN.

关键词： neural network real-time systems

A data-driven approach to RUL prediction of tools

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Advances in Manufacturing 2024年第1期12卷 6-18页

作者： Wei Li Liang-Chi Zhang Chu-han Wu Yan Wang Zhen-Xiang Cui Chao Niu Department of Mechanical Engineering University College LondonLondonWC1E 7JEUK Shenzhen Key Laboratory of Cross-Scale Manufacturing Mechanics Southern University of Science and TechnologyShenzhen518055GuangdongPeople’s Republic of China SUSTech Institute for Manufacturing Innovation Southern University of Science and TechnologyShenzhen518055GuangdongPeople’s Republic of China Department of Mechanics and Aerospace Engineering Southern University of Science and TechnologyShenzhen518055GuangdongPeople’s Republic of China School of Mechanical and Manufacturing Engineering The University of New South WalesKensingtonNSW2052Australia Baoshan Iron&Steel Co. Ltd.Shanghai200941People’s Republic of China

An effective and reliable prediction of the remaining useful life(RUL)of a tool is important to a metal forming process because it can significantly reduce unexpected maintenance,avoid machine shutdowns and increase system stability.This study proposes a new data-driven approach to the RUL prediction for metal forming processes under multiple contact sliding conditions.The data-driven approach took advantage of bidirectional long short-term memory(BLSTM)and convolutional neural networks(CNN).A pre-trained lightweight CNN-based network,WearNet,was re-trained to classify the wear states of workpiece surfaces with a high accuracy,then the classification results were passed into a BLSTM-based regression model as inputs for RUL estimation.The experimental results demonstrated that this approach was able to predict the RUL values with a small error(below 5%)and a low root mean square error(RMSE)(around 1.5),which was more superior and robust than the other state-of-the-art methods.

关键词： Remaining useful life(RUL) Bidirectional long short-term memory(BLSTM) Data-driven approach Metal forming

Intelligent Recognition Using Ultralight Multifunctional Nano‑Layered Carbon Aerogel Sensors with Human‑Like Tactile Perception

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Nano-Micro Letters 2024年第1期16卷 172-186页

作者： Huiqi Zhao Yizheng Zhang Lei han Weiqi Qian Jiabin Wang Heting Wu Jingchen Li Yuan Dai Zhengyou Zhang Chris RBowen Ya Yang CAS Center for Excellence in Nanoscience Beijing Key Laboratory of Micro‑Nano Energy and SensorBeijing Institute of Nanoenergy and NanosystemsChinese Academy of SciencesBeijing 101400People’s Republic of China Tencent Robotics X Shenzhen 518054People’s Republic of China School of Nanoscience and Technology University of Chinese Academy of SciencesBeijing 100049People’s Republic of China Department of Mechanical Engineering University of BathBath BA27AKUK Center on Nanoenergy Research School of Physical Science and TechnologyGuangxi UniversityNanning 530004People’s Republic of China

Humans can perceive our complex world through multi-sensory fusion.Under limited visual conditions,people can sense a variety of tactile signals to identify objects accurately and rapidly.However,replicating this unique capability in robots remains a significant challenge.Here,we present a new form of ultralight multifunctional tactile nano-layered carbon aerogel sensor that provides pressure,temperature,material recognition and 3D location capabilities,which is combined with multimodal supervised learning algorithms for object recognition.The sensor exhibits human-like pressure(0.04–100 kPa)and temperature(21.5–66.2℃)detection,millisecond response times(11 ms),a pressure sensitivity of 92.22 kPa^(−1)and triboelectric durability of over 6000 cycles.The devised algorithm has universality and can accommodate a range of application scenarios.The tactile system can identify common foods in a kitchen scene with 94.63%accuracy and explore the topographic and geomorphic features of a Mars scene with 100%accuracy.This sensing approach empowers robots with versatile tactile perception to advance future society toward heightened sensing,recognition and intelligence.

关键词： Multifunctional sensor Tactile perception Multimodal machine learning algorithms Universal tactile system Intelligent object recognition