As emerging two-dimensional(2D)materials,carbides and nitrides(MXenes)could be solid solutions or organized structures made up of multi-atomic layers.With remarkable and adjustable electrical,optical,mechanical,and el...As emerging two-dimensional(2D)materials,carbides and nitrides(MXenes)could be solid solutions or organized structures made up of multi-atomic layers.With remarkable and adjustable electrical,optical,mechanical,and electrochemical characteristics,MXenes have shown great potential in brain-inspired neuromorphic computing electronics,including neuromorphic gas sensors,pressure sensors and photodetectors.This paper provides a forward-looking review of the research progress regarding MXenes in the neuromorphic sensing domain and discussed the critical challenges that need to be resolved.Key bottlenecks such as insufficient long-term stability under environmental exposure,high costs,scalability limitations in large-scale production,and mechanical mismatch in wearable integration hinder their practical deployment.Furthermore,unresolved issues like interfacial compatibility in heterostructures and energy inefficiency in neu-romorphic signal conversion demand urgent attention.The review offers insights into future research directions enhance the fundamental understanding of MXene properties and promote further integration into neuromorphic computing applications through the convergence with various emerging technologies.展开更多
High-entropy oxides(HEOs)have emerged as a promising class of memristive materials,characterized by entropy-stabilized crystal structures,multivalent cation coordination,and tunable defect landscapes.These intrinsic f...High-entropy oxides(HEOs)have emerged as a promising class of memristive materials,characterized by entropy-stabilized crystal structures,multivalent cation coordination,and tunable defect landscapes.These intrinsic features enable forming-free resistive switching,multilevel conductance modulation,and synaptic plasticity,making HEOs attractive for neuromorphic computing.This review outlines recent progress in HEO-based memristors across materials engineering,switching mechanisms,and synaptic emulation.Particular attention is given to vacancy migration,phase transitions,and valence-state dynamics—mechanisms that underlie the switching behaviors observed in both amorphous and crystalline systems.Their relevance to neuromorphic functions such as short-term plasticity and spike-timing-dependent learning is also examined.While encouraging results have been achieved at the device level,challenges remain in conductance precision,variability control,and scalable integration.Addressing these demands a concerted effort across materials design,interface optimization,and task-aware modeling.With such integration,HEO memristors offer a compelling pathway toward energy-efficient and adaptable brain-inspired electronics.展开更多
The advancement of flexible memristors has significantly promoted the development of wearable electronic for emerging neuromorphic computing applications.Inspired by in-memory computing architecture of human brain,fle...The advancement of flexible memristors has significantly promoted the development of wearable electronic for emerging neuromorphic computing applications.Inspired by in-memory computing architecture of human brain,flexible memristors exhibit great application potential in emulating artificial synapses for highefficiency and low power consumption neuromorphic computing.This paper provides comprehensive overview of flexible memristors from perspectives of development history,material system,device structure,mechanical deformation method,device performance analysis,stress simulation during deformation,and neuromorphic computing applications.The recent advances in flexible electronics are summarized,including single device,device array and integration.The challenges and future perspectives of flexible memristor for neuromorphic computing are discussed deeply,paving the way for constructing wearable smart electronics and applications in large-scale neuromorphic computing and high-order intelligent robotics.展开更多
The issue of resistance reduction through hull ventilation is of particular interest in contemporary research.This paper presents multiphase computational fluid dynamics(CFD)simulations with 2-DOF motion of a planing ...The issue of resistance reduction through hull ventilation is of particular interest in contemporary research.This paper presents multiphase computational fluid dynamics(CFD)simulations with 2-DOF motion of a planing hull.The original hull was modified by introducing a step to allow air ventilation.Following an assessment of the hull performance,a simulation campaign in calm water was conducted to characterize the hull at various forward speeds and air insufflation rates for a defined single step geometry.Geometric analysis of the air layer thickness beneath the hull for each simulated condition was performed using a novel method for visualizing local air thickness.Additionally,two new parameters were introduced to understand the influence of spray rails on the air volume beneath the hull and to indicate the primary direction of ventilated air escape.A validation campaign and an assessment of uncertainty of the simulation has been conducted.The features offered by the CFD methodology include the evaluation of the air layer thickness as a function of hull velocity and injection flow rate and the air volume distribution beneath the hull.The air injection velocity can be adjusted across various operating conditions,thereby preventing performance or efficiency loss during navigation.Based on these findings,the study highlights the benefits of air insufflation in reducing hull resistance for high-speed planing vessels.This work lays a robust foundation for future research and new promising topics,as the exploration of air insufflation continues to be a topic of contemporary interest within naval architecture and hydrodynamics.展开更多
BACKGROUND Early screening,preoperative staging,and diagnosis of lymph node metastasis are crucial for improving the prognosis of gastric cancer(GC).AIM To evaluate the diagnostic value of combined multidetector compu...BACKGROUND Early screening,preoperative staging,and diagnosis of lymph node metastasis are crucial for improving the prognosis of gastric cancer(GC).AIM To evaluate the diagnostic value of combined multidetector computed tomography(MDCT)and gastrointestinal endoscopy for GC screening,preoperative staging,and lymph node metastasis detection,thereby providing a reference for clinical diagnosis and treatment.METHODS In this retrospective study clinical and imaging data of 134 patients with suspected GC who were admitted between January 2023 and October 2024 were initially reviewed.According to the inclusion and exclusion criteria,102 patients were finally enrolled in the analysis.All enrolled patients had undergone both MDCT and gastrointestinal endoscopy examinations prior to surgical intervention.Preoperative clinical staging and lymph node metastasis findings were compared with pathological results.RESULTS The combined use of MDCT and gastrointestinal endoscopy demonstrated a sensitivity of 98.53%,specificity of 97.06%,accuracy of 98.04%,positive predictive value of 98.53%,and negative predictive value of 97.06%for diagnosing GC.These factors were all significantly higher than those of MDCT or endoscopy alone(P<0.05).The accuracy rates of the combined approach for detecting clinical T and N stages were 97.06%and 92.65%,respectively,outperforming MDCT alone(86.76% and 79.41%)and endoscopy alone(85.29% and 70.59%)(P<0.05).Among 68 patients with confirmed GC,50(73.53%)were pathologically diagnosed with lymph node metastasis.The accuracy for detecting lymph node metastasis was 66.00%with endoscopy,76.00%with MDCT,and 92.00% with the combined approach,all with statistically significant differences(P<0.05).CONCLUSION The combined application of MDCT and gastrointestinal endoscopy enhanced diagnostic accuracy for GC,provided greater consistency in preoperative staging,and improved the detection of lymph node metastasis,thereby demonstrating significant clinical utility.展开更多
Colorectal cancer(CRC)with lung oligometastases,particularly in the presence of extrapulmonary disease,poses considerable therapeutic challenges in clinical practice.We have carefully studied the multicenter study by ...Colorectal cancer(CRC)with lung oligometastases,particularly in the presence of extrapulmonary disease,poses considerable therapeutic challenges in clinical practice.We have carefully studied the multicenter study by Hu et al,which evaluated the survival outcomes of patients with metastatic CRC who received image-guided thermal ablation(IGTA).These findings provide valuable clinical evidence supporting IGTA as a feasible,minimally invasive approach and underscore the prognostic significance of metastatic distribution.However,the study by Hu et al has several limitations,including that not all pulmonary lesions were pathologically confirmed,postoperative follow-up mainly relied on dynamic contrast-enhanced computed tomography,no comparative analysis was performed with other local treatments,and the impact of other imaging features on efficacy and prognosis was not evaluated.Future studies should include complete pathological confirmation,integrate functional imaging and radiomics,and use prospective multicenter collaboration to optimize patient selection standards for IGTA treatment,strengthen its clinical evidence base,and ultimately promote individualized decision-making for patients with metastatic CRC.展开更多
Satellite edge computing has garnered significant attention from researchers;however,processing a large volume of tasks within multi-node satellite networks still poses considerable challenges.The sharp increase in us...Satellite edge computing has garnered significant attention from researchers;however,processing a large volume of tasks within multi-node satellite networks still poses considerable challenges.The sharp increase in user demand for latency-sensitive tasks has inevitably led to offloading bottlenecks and insufficient computational capacity on individual satellite edge servers,making it necessary to implement effective task offloading scheduling to enhance user experience.In this paper,we propose a priority-based task scheduling strategy based on a Software-Defined Network(SDN)framework for satellite-terrestrial integrated networks,which clarifies the execution order of tasks based on their priority.Subsequently,we apply a Dueling-Double Deep Q-Network(DDQN)algorithm enhanced with prioritized experience replay to derive a computation offloading strategy,improving the experience replay mechanism within the Dueling-DDQN framework.Next,we utilize the Deep Deterministic Policy Gradient(DDPG)algorithm to determine the optimal resource allocation strategy to reduce the processing latency of sub-tasks.Simulation results demonstrate that the proposed d3-DDPG algorithm outperforms other approaches,effectively reducing task processing latency and thus improving user experience and system efficiency.展开更多
The purpose of this review is to explore the intersection of computational engineering and biomedical science,highlighting the transformative potential this convergence holds for innovation in healthcare and medical r...The purpose of this review is to explore the intersection of computational engineering and biomedical science,highlighting the transformative potential this convergence holds for innovation in healthcare and medical research.The review covers key topics such as computational modelling,bioinformatics,machine learning in medical diagnostics,and the integration of wearable technology for real-time health monitoring.Major findings indicate that computational models have significantly enhanced the understanding of complex biological systems,while machine learning algorithms have improved the accuracy of disease prediction and diagnosis.The synergy between bioinformatics and computational techniques has led to breakthroughs in personalized medicine,enabling more precise treatment strategies.Additionally,the integration of wearable devices with advanced computational methods has opened new avenues for continuous health monitoring and early disease detection.The review emphasizes the need for interdisciplinary collaboration to further advance this field.Future research should focus on developing more robust and scalable computational models,enhancing data integration techniques,and addressing ethical considerations related to data privacy and security.By fostering innovation at the intersection of these disciplines,the potential to revolutionize healthcare delivery and outcomes becomes increasingly attainable.展开更多
BACKGROUND Internal hernia(IH)is a rare culprit of small bowel obstruction(SBO)with an incidence of<1%.It poses a considerable diagnostic challenge requiring a high index of suspicion to prevent misdiagnosis,improp...BACKGROUND Internal hernia(IH)is a rare culprit of small bowel obstruction(SBO)with an incidence of<1%.It poses a considerable diagnostic challenge requiring a high index of suspicion to prevent misdiagnosis,improper treatment,and subsequent morbidity and mortality.AIM To determine the clinico-demographic profile,radiological and operative findings,and postoperative course of patients with IH and its association with SBO.METHODS Medical records of 586 patients with features of SBO presenting at a tertiary care centre at Lucknow,India between September 2010 and August 2023 were reviewed.RESULTS Out of 586 patients,7(1.2%)were diagnosed with IH.Among these,4 had congenital IH and 3 had acquired IH.The male-to-female ratio was 4:3.The median age at presentation was 32 years.Contrast-enhanced computed tomography(CECT)was the most reliable investigation for preoperative identification,demonstrating mesenteric whirling and clumped-up bowel loops.Left paraduodenal hernia and transmesenteric hernia occurred with an equal frequency(approximately 43%each).Intraoperatively,one patient was found to have bowel ischemia and one had associated malrotation of gut.During follow-up,no recurrences were reported.CONCLUSION IH,being a rare cause,must be considered as a differential diagnosis for SBO,especially in young patients in their 30s or with unexplained abdominal pain or discomfort post-surgery.A rapid imaging evaluation,preferably with CECT,is necessary to aid in an early diagnosis and prompt intervention,thereby reducing financial burden related to unnecessary investigations and preventing the morbidity and mortality associated with closed-loop obstruction and strangulation of the bowel.展开更多
Photon-counting computed tomography(PCCT)represents a significant advancement in pediatric cardiovascular imaging.Traditional CT systems employ energy-integrating detectors that convert X-ray photons into visible ligh...Photon-counting computed tomography(PCCT)represents a significant advancement in pediatric cardiovascular imaging.Traditional CT systems employ energy-integrating detectors that convert X-ray photons into visible light,whereas PCCT utilizes photon-counting detectors that directly transform X-ray photons into electric signals.This direct conversion allows photon-counting detectors to sort photons into discrete energy levels,thereby enhancing image quality through superior noise reduction,improved spatial and contrast resolution,and reduced artifacts.In pediatric applications,PCCT offers substantial benefits,including lower radiation doses,which may help reduce the risk of malignancy in pediatric patients,with perhaps greater potential to benefit those with repeated exposure from a young age.Enhanced spatial resolution facilitates better visualization of small structures,vital for diagnosing congenital heart defects.Additionally,PCCT’s spectral capabilities improve tissue characterization and enable the creation of virtual monoenergetic images,which enhance soft-tissue contrast and potentially reduce contrast media doses.Initial clinical results indicate that PCCT provides superior image quality and diagnostic accuracy compared to conven-tional CT,particularly in challenging pediatric cardiovascular cases.As PCCT technology matures,further research and standardized protocols will be essential to fully integrate it into pediatric imaging practices,ensuring optimized diagnostic outcomes and patient safety.展开更多
Photonic platforms are gradually emerging as a promising option to encounter the ever-growing demand for artificial intelligence,among which photonic time-delay reservoir computing(TDRC)is widely anticipated.While suc...Photonic platforms are gradually emerging as a promising option to encounter the ever-growing demand for artificial intelligence,among which photonic time-delay reservoir computing(TDRC)is widely anticipated.While such a computing paradigm can only employ a single photonic device as the nonlinear node for data processing,the performance highly relies on the fading memory provided by the delay feedback loop(FL),which sets a restriction on the extensibility of physical implementation,especially for highly integrated chips.Here,we present a simplified photonic scheme for more flexible parameter configurations leveraging the designed quasi-convolution coding(QC),which completely gets rid of the dependence on FL.Unlike delay-based TDRC,encoded data in QC-based RC(QRC)enables temporal feature extraction,facilitating augmented memory capabilities.Thus,our proposed QRC is enabled to deal with time-related tasks or sequential data without the implementation of FL.Furthermore,we can implement this hardware with a low-power,easily integrable vertical-cavity surface-emitting laser for high-performance parallel processing.We illustrate the concept validation through simulation and experimental comparison of QRC and TDRC,wherein the simpler-structured QRC outperforms across various benchmark tasks.Our results may underscore an auspicious solution for the hardware implementation of deep neural networks.展开更多
AIM To analyze the diagnostic performance of surveillance colonoscopy,computed tomography(CT),and tumor markers(TMs)in detecting CRC recurrence or metastasis during follow-up after CRC resection.Secondary objectives i...AIM To analyze the diagnostic performance of surveillance colonoscopy,computed tomography(CT),and tumor markers(TMs)in detecting CRC recurrence or metastasis during follow-up after CRC resection.Secondary objectives included degree of adherence to clinical practice guidelines surveillance recommendations and factors associated with adherence and all-cause and CRC mortality.METHODS The single-center retrospective cohort study including patients undergoing curative resection of stage I-III CRC during 2010-2015.Follow-up was performed using TMs every 6 months,yearly CT for 5 years,and colonoscopy at years 1 and 4.Demographic,primary tumor data,and results at follow-up were collected.RESULTS Of 574 included patients included,153 had recurrences or metastases.Of this group,136(88.9%)were diagnosed by CT,10(6.5%)by CT and colonoscopy,and 7(4.6%)by colonoscopy;only 67.8%showed TMs elevation.Adherence to follow-up recommendations was 68.8%for the first colonoscopy,74%for the first CT scan,and 96.6%for the first blood test;these values declined over time.Younger age at diagnosis[odds ratio(OR)0.93;95%CI:0.91-0.95],CRC stages I-II(OR 0.38;95%CI:0.24-0.61),and adherence to follow-up recommendations(OR 0.30;95%CI:0.20-0.46)were independently associated with lower risk for all-cause death at 5 years.CONCLUSION CT scan had the highest diagnostic yield.Adherence to follow-up recommendations was low and decreased during follow-up.Younger age at diagnosis,stage,and follow-up adherence were associated with lower 5-year mortality.展开更多
In cold regions,rock structures will be weakened by freeze-thaw cycles under various water immersion conditions.Determining how water immersion conditions impact rock deterioration under freeze-thaw cycles is critical...In cold regions,rock structures will be weakened by freeze-thaw cycles under various water immersion conditions.Determining how water immersion conditions impact rock deterioration under freeze-thaw cycles is critical to assess accurately the frost resistance of engineered rock.In this paper,freeze-thaw cycles(temperature range of-20℃-20℃)were performed on the sandstones in different water immersion conditions(fully,partially and non-immersed in water).Then,computed tomography(CT)tests were conducted on the sandstones when the freeze-thaw number reached 0,5,10,15,20 and 30.Next,the effects of water immersion conditions on the microstructure deterioration of sandstone under freezethaw cycles were evaluated using CT spatial imaging,porosity and damage factor.Finally,focusing on the partially immersed condition,the immersion volume rate was defined to understand the effects of immersion degree on the freeze-thaw damage of sandstone and to propose a damage model considering the freeze-thaw number and immersion degree.The results show that with increasing freeze-thaw number,the porosities and damage factors under fully and partially immersed conditions increase continuously,while those under non-immersed condition first increase and then remain approximately constant.The most severe freeze-thaw damage occurs in fully immersed condition,followed by partially immersed condition and finally non-immersed condition.Interestingly,the freeze-thaw number and the immersion volume rate both impact the microstructure deterioration of the partially immersed sandstone.For the same freeze-thaw number,the damage factor increases approximately linearly with increasing immersion volume rate,and the increasing immersion degree exacerbates the microstructure deterioration of sandstone.Moreover,the proposed model can effectively estimate the freeze-thaw damage of partially immersed sandstone with different immersion volume rates.展开更多
Optoelectronic memristor is generating growing research interest for high efficient computing and sensing-memory applications.In this work,an optoelectronic memristor with Au/a-C:Te/Pt structure is developed.Synaptic ...Optoelectronic memristor is generating growing research interest for high efficient computing and sensing-memory applications.In this work,an optoelectronic memristor with Au/a-C:Te/Pt structure is developed.Synaptic functions,i.e.,excita-tory post-synaptic current and pair-pulse facilitation are successfully mimicked with the memristor under electrical and optical stimulations.More importantly,the device exhibited distinguishable response currents by adjusting 4-bit input electrical/opti-cal signals.A multi-mode reservoir computing(RC)system is constructed with the optoelectronic memristors to emulate human tactile-visual fusion recognition and an accuracy of 98.7%is achieved.The optoelectronic memristor provides potential for developing multi-mode RC system.展开更多
The rapid expansion of railways,especially High-Speed Railways(HSRs),has drawn considerable interest from both academic and industrial sectors.To meet the future vision of smart rail communications,the rail transport ...The rapid expansion of railways,especially High-Speed Railways(HSRs),has drawn considerable interest from both academic and industrial sectors.To meet the future vision of smart rail communications,the rail transport industry must innovate in key technologies to ensure high-quality transmissions for passengers and railway operations.These systems must function effectively under high mobility conditions while prioritizing safety,ecofriendliness,comfort,transparency,predictability,and reliability.On the other hand,the proposal of 6 G wireless technology introduces new possibilities for innovation in communication technologies,which may truly realize the current vision of HSR.Therefore,this article gives a review of the current advanced 6 G wireless communication technologies for HSR,including random access and switching,channel estimation and beamforming,integrated sensing and communication,and edge computing.The main application scenarios of these technologies are reviewed,as well as their current research status and challenges,followed by an outlook on future development directions.展开更多
Artificial Intelligence(AI)has shown the power to enhance the functionality of sensors and enable intelligent human‐machine interfaces through machine learning‐based data analysis.However,the good performance of AI ...Artificial Intelligence(AI)has shown the power to enhance the functionality of sensors and enable intelligent human‐machine interfaces through machine learning‐based data analysis.However,the good performance of AI is always accompanied by a large amount of data and high computational complexity.Though cloud computing appears to be the right solution to this issue with the advent of the 5G era,a certain intelligence of the edge terminal is also important to make the entire integrated intelligent system more efficient.The current development of microelectronic,wearable,AI,and neuromorphic technologies pave the way to realize advanced edge computing by integrating silicon‐based high‐computing‐power neuromorphic chips with anthropomorphic wearable sensory devices and show the potential to achieve human‐like self‐sustainable decentralized intelligence to enable the next‐generation of AI.Hence,in this review,we systematically introduce the related progress in terms of wearable electronics that can mimic the biological features of humans'sensory systems and the development of neuromorphic/in‐sensor computing technologies.Discussion on implementing the integrated human‐like perception and sensation system with silicone‐based computing chips and non‐silicone‐based wearable functional units and our perspectives are also provided.展开更多
As an important complement to cloud computing, edge computing can effectively reduce the workload of the backbone network. To reduce latency and energy consumption of edge computing, deep learning is used to learn the...As an important complement to cloud computing, edge computing can effectively reduce the workload of the backbone network. To reduce latency and energy consumption of edge computing, deep learning is used to learn the task offloading strategies by interacting with the entities. In actual application scenarios, users of edge computing are always changing dynamically. However, the existing task offloading strategies cannot be applied to such dynamic scenarios. To solve this problem, we propose a novel dynamic task offloading framework for distributed edge computing, leveraging the potential of meta-reinforcement learning (MRL). Our approach formulates a multi-objective optimization problem aimed at minimizing both delay and energy consumption. We model the task offloading strategy using a directed acyclic graph (DAG). Furthermore, we propose a distributed edge computing adaptive task offloading algorithm rooted in MRL. This algorithm integrates multiple Markov decision processes (MDP) with a sequence-to-sequence (seq2seq) network, enabling it to learn and adapt task offloading strategies responsively across diverse network environments. To achieve joint optimization of delay and energy consumption, we incorporate the non-dominated sorting genetic algorithm II (NSGA-II) into our framework. Simulation results demonstrate the superiority of our proposed solution, achieving a 21% reduction in time delay and a 19% decrease in energy consumption compared to alternative task offloading schemes. Moreover, our scheme exhibits remarkable adaptability, responding swiftly to changes in various network environments.展开更多
BACKGROUND Hepatocellular carcinoma(HCC)is a common tumor with a poor prognosis.Early intervention is essential;thus,good prognostic markers to identify patients who benefit from first transarterial chemoembolization(...BACKGROUND Hepatocellular carcinoma(HCC)is a common tumor with a poor prognosis.Early intervention is essential;thus,good prognostic markers to identify patients who benefit from first transarterial chemoembolization(TACE)are needed.AIM To investigate the efficacy of computed tomography(CT)radiomics in predicting the success of the first TACE in patients with advanced HCC and to develop an early prediction model based on clinical radiomics features.METHODS Data from 122 patients with advanced HCC treated with TACE were analyzed.Intratumoral and peritumoral areas on arterial and venous CT images were selected to extract radiomic features,which were screened in the training cohort using the minimum redundancy maximum correlation.Then,support vector machines were used to construct the model.To construct a receiver operating characteristic curve,the predictive efficacy of each model was evaluated on the basis of the area under the curve(AUC).RESULTS Among the 122 patients,72 patients were effectively treated via TACE,and in 50 patients,this treatment was ineffective.In the radiomics model,the areas under the curve of the venous phase model were 0.867(95%CI:0.790-0.940)in the training cohort and 0.755(0.600-0.910)in the validation cohort,indicating good predictive efficacy.The multivariate logistic regression results indicated that preoperative alpha-fetoprotein levels(P=0.01)were a risk factor for TACE.The screened clinical features were combined with the radiomic features to construct a combined model.This combined model had an AUC of 0.92(0.87-0.95)in the training cohort and 0.815(0.67-0.95)in the validation cohort.CONCLUSION CT radiomics has good value in predicting the efficacy of the first TACE treatment in patients with HCC.The combined model was a better tool for predicting the first TACE efficacy in patients with advanced HCC and could provide an efficient predictive tool to help with the selection of patients for TACE.展开更多
As AI systems scale, the limitations of cloud-based architectures, including latency, bandwidth, and privacy concerns, demand decentralized alternatives. Federated learning (FL) and Edge AI provide a paradigm shift by...As AI systems scale, the limitations of cloud-based architectures, including latency, bandwidth, and privacy concerns, demand decentralized alternatives. Federated learning (FL) and Edge AI provide a paradigm shift by combining privacy preserving training with efficient, on device computation. This paper introduces a cutting-edge FL-edge integration framework, achieving a 10% to 15% increase in model accuracy and reducing communication costs by 25% in heterogeneous environments. Blockchain based secure aggregation ensures robust and tamper-proof model updates, while exploratory quantum AI techniques enhance computational efficiency. By addressing key challenges such as device variability and non-IID data, this work sets the stage for the next generation of adaptive, privacy-first AI systems, with applications in IoT, healthcare, and autonomous systems.展开更多
基金supported by the NSFC(12474071)Natural Science Foundation of Shandong Province(ZR2024YQ051,ZR2025QB50)+6 种基金Guangdong Basic and Applied Basic Research Foundation(2025A1515011191)the Shanghai Sailing Program(23YF1402200,23YF1402400)funded by Basic Research Program of Jiangsu(BK20240424)Open Research Fund of State Key Laboratory of Crystal Materials(KF2406)Taishan Scholar Foundation of Shandong Province(tsqn202408006,tsqn202507058)Young Talent of Lifting engineering for Science and Technology in Shandong,China(SDAST2024QTB002)the Qilu Young Scholar Program of Shandong University。
文摘As emerging two-dimensional(2D)materials,carbides and nitrides(MXenes)could be solid solutions or organized structures made up of multi-atomic layers.With remarkable and adjustable electrical,optical,mechanical,and electrochemical characteristics,MXenes have shown great potential in brain-inspired neuromorphic computing electronics,including neuromorphic gas sensors,pressure sensors and photodetectors.This paper provides a forward-looking review of the research progress regarding MXenes in the neuromorphic sensing domain and discussed the critical challenges that need to be resolved.Key bottlenecks such as insufficient long-term stability under environmental exposure,high costs,scalability limitations in large-scale production,and mechanical mismatch in wearable integration hinder their practical deployment.Furthermore,unresolved issues like interfacial compatibility in heterostructures and energy inefficiency in neu-romorphic signal conversion demand urgent attention.The review offers insights into future research directions enhance the fundamental understanding of MXene properties and promote further integration into neuromorphic computing applications through the convergence with various emerging technologies.
基金financially supported by the National Natural Science Foundation of China(Grant No.12172093)the Guangdong Basic and Applied Basic Research Foundation(Grant No.2021A1515012607)。
文摘High-entropy oxides(HEOs)have emerged as a promising class of memristive materials,characterized by entropy-stabilized crystal structures,multivalent cation coordination,and tunable defect landscapes.These intrinsic features enable forming-free resistive switching,multilevel conductance modulation,and synaptic plasticity,making HEOs attractive for neuromorphic computing.This review outlines recent progress in HEO-based memristors across materials engineering,switching mechanisms,and synaptic emulation.Particular attention is given to vacancy migration,phase transitions,and valence-state dynamics—mechanisms that underlie the switching behaviors observed in both amorphous and crystalline systems.Their relevance to neuromorphic functions such as short-term plasticity and spike-timing-dependent learning is also examined.While encouraging results have been achieved at the device level,challenges remain in conductance precision,variability control,and scalable integration.Addressing these demands a concerted effort across materials design,interface optimization,and task-aware modeling.With such integration,HEO memristors offer a compelling pathway toward energy-efficient and adaptable brain-inspired electronics.
基金supported by the NSFC(12474071)Natural Science Foundation of Shandong Province(ZR2024YQ051)+5 种基金Open Research Fund of State Key Laboratory of Materials for Integrated Circuits(SKLJC-K2024-12)the Shanghai Sailing Program(23YF1402200,23YF1402400)Natural Science Foundation of Jiangsu Province(BK20240424)Taishan Scholar Foundation of Shandong Province(tsqn202408006)Young Talent of Lifting engineering for Science and Technology in Shandong,China(SDAST2024QTB002)the Qilu Young Scholar Program of Shandong University.
文摘The advancement of flexible memristors has significantly promoted the development of wearable electronic for emerging neuromorphic computing applications.Inspired by in-memory computing architecture of human brain,flexible memristors exhibit great application potential in emulating artificial synapses for highefficiency and low power consumption neuromorphic computing.This paper provides comprehensive overview of flexible memristors from perspectives of development history,material system,device structure,mechanical deformation method,device performance analysis,stress simulation during deformation,and neuromorphic computing applications.The recent advances in flexible electronics are summarized,including single device,device array and integration.The challenges and future perspectives of flexible memristor for neuromorphic computing are discussed deeply,paving the way for constructing wearable smart electronics and applications in large-scale neuromorphic computing and high-order intelligent robotics.
基金supported by European Union funding(PON“Ricerca e Innovazione”2014‒2020).
文摘The issue of resistance reduction through hull ventilation is of particular interest in contemporary research.This paper presents multiphase computational fluid dynamics(CFD)simulations with 2-DOF motion of a planing hull.The original hull was modified by introducing a step to allow air ventilation.Following an assessment of the hull performance,a simulation campaign in calm water was conducted to characterize the hull at various forward speeds and air insufflation rates for a defined single step geometry.Geometric analysis of the air layer thickness beneath the hull for each simulated condition was performed using a novel method for visualizing local air thickness.Additionally,two new parameters were introduced to understand the influence of spray rails on the air volume beneath the hull and to indicate the primary direction of ventilated air escape.A validation campaign and an assessment of uncertainty of the simulation has been conducted.The features offered by the CFD methodology include the evaluation of the air layer thickness as a function of hull velocity and injection flow rate and the air volume distribution beneath the hull.The air injection velocity can be adjusted across various operating conditions,thereby preventing performance or efficiency loss during navigation.Based on these findings,the study highlights the benefits of air insufflation in reducing hull resistance for high-speed planing vessels.This work lays a robust foundation for future research and new promising topics,as the exploration of air insufflation continues to be a topic of contemporary interest within naval architecture and hydrodynamics.
文摘BACKGROUND Early screening,preoperative staging,and diagnosis of lymph node metastasis are crucial for improving the prognosis of gastric cancer(GC).AIM To evaluate the diagnostic value of combined multidetector computed tomography(MDCT)and gastrointestinal endoscopy for GC screening,preoperative staging,and lymph node metastasis detection,thereby providing a reference for clinical diagnosis and treatment.METHODS In this retrospective study clinical and imaging data of 134 patients with suspected GC who were admitted between January 2023 and October 2024 were initially reviewed.According to the inclusion and exclusion criteria,102 patients were finally enrolled in the analysis.All enrolled patients had undergone both MDCT and gastrointestinal endoscopy examinations prior to surgical intervention.Preoperative clinical staging and lymph node metastasis findings were compared with pathological results.RESULTS The combined use of MDCT and gastrointestinal endoscopy demonstrated a sensitivity of 98.53%,specificity of 97.06%,accuracy of 98.04%,positive predictive value of 98.53%,and negative predictive value of 97.06%for diagnosing GC.These factors were all significantly higher than those of MDCT or endoscopy alone(P<0.05).The accuracy rates of the combined approach for detecting clinical T and N stages were 97.06%and 92.65%,respectively,outperforming MDCT alone(86.76% and 79.41%)and endoscopy alone(85.29% and 70.59%)(P<0.05).Among 68 patients with confirmed GC,50(73.53%)were pathologically diagnosed with lymph node metastasis.The accuracy for detecting lymph node metastasis was 66.00%with endoscopy,76.00%with MDCT,and 92.00% with the combined approach,all with statistically significant differences(P<0.05).CONCLUSION The combined application of MDCT and gastrointestinal endoscopy enhanced diagnostic accuracy for GC,provided greater consistency in preoperative staging,and improved the detection of lymph node metastasis,thereby demonstrating significant clinical utility.
文摘Colorectal cancer(CRC)with lung oligometastases,particularly in the presence of extrapulmonary disease,poses considerable therapeutic challenges in clinical practice.We have carefully studied the multicenter study by Hu et al,which evaluated the survival outcomes of patients with metastatic CRC who received image-guided thermal ablation(IGTA).These findings provide valuable clinical evidence supporting IGTA as a feasible,minimally invasive approach and underscore the prognostic significance of metastatic distribution.However,the study by Hu et al has several limitations,including that not all pulmonary lesions were pathologically confirmed,postoperative follow-up mainly relied on dynamic contrast-enhanced computed tomography,no comparative analysis was performed with other local treatments,and the impact of other imaging features on efficacy and prognosis was not evaluated.Future studies should include complete pathological confirmation,integrate functional imaging and radiomics,and use prospective multicenter collaboration to optimize patient selection standards for IGTA treatment,strengthen its clinical evidence base,and ultimately promote individualized decision-making for patients with metastatic CRC.
文摘Satellite edge computing has garnered significant attention from researchers;however,processing a large volume of tasks within multi-node satellite networks still poses considerable challenges.The sharp increase in user demand for latency-sensitive tasks has inevitably led to offloading bottlenecks and insufficient computational capacity on individual satellite edge servers,making it necessary to implement effective task offloading scheduling to enhance user experience.In this paper,we propose a priority-based task scheduling strategy based on a Software-Defined Network(SDN)framework for satellite-terrestrial integrated networks,which clarifies the execution order of tasks based on their priority.Subsequently,we apply a Dueling-Double Deep Q-Network(DDQN)algorithm enhanced with prioritized experience replay to derive a computation offloading strategy,improving the experience replay mechanism within the Dueling-DDQN framework.Next,we utilize the Deep Deterministic Policy Gradient(DDPG)algorithm to determine the optimal resource allocation strategy to reduce the processing latency of sub-tasks.Simulation results demonstrate that the proposed d3-DDPG algorithm outperforms other approaches,effectively reducing task processing latency and thus improving user experience and system efficiency.
文摘The purpose of this review is to explore the intersection of computational engineering and biomedical science,highlighting the transformative potential this convergence holds for innovation in healthcare and medical research.The review covers key topics such as computational modelling,bioinformatics,machine learning in medical diagnostics,and the integration of wearable technology for real-time health monitoring.Major findings indicate that computational models have significantly enhanced the understanding of complex biological systems,while machine learning algorithms have improved the accuracy of disease prediction and diagnosis.The synergy between bioinformatics and computational techniques has led to breakthroughs in personalized medicine,enabling more precise treatment strategies.Additionally,the integration of wearable devices with advanced computational methods has opened new avenues for continuous health monitoring and early disease detection.The review emphasizes the need for interdisciplinary collaboration to further advance this field.Future research should focus on developing more robust and scalable computational models,enhancing data integration techniques,and addressing ethical considerations related to data privacy and security.By fostering innovation at the intersection of these disciplines,the potential to revolutionize healthcare delivery and outcomes becomes increasingly attainable.
文摘BACKGROUND Internal hernia(IH)is a rare culprit of small bowel obstruction(SBO)with an incidence of<1%.It poses a considerable diagnostic challenge requiring a high index of suspicion to prevent misdiagnosis,improper treatment,and subsequent morbidity and mortality.AIM To determine the clinico-demographic profile,radiological and operative findings,and postoperative course of patients with IH and its association with SBO.METHODS Medical records of 586 patients with features of SBO presenting at a tertiary care centre at Lucknow,India between September 2010 and August 2023 were reviewed.RESULTS Out of 586 patients,7(1.2%)were diagnosed with IH.Among these,4 had congenital IH and 3 had acquired IH.The male-to-female ratio was 4:3.The median age at presentation was 32 years.Contrast-enhanced computed tomography(CECT)was the most reliable investigation for preoperative identification,demonstrating mesenteric whirling and clumped-up bowel loops.Left paraduodenal hernia and transmesenteric hernia occurred with an equal frequency(approximately 43%each).Intraoperatively,one patient was found to have bowel ischemia and one had associated malrotation of gut.During follow-up,no recurrences were reported.CONCLUSION IH,being a rare cause,must be considered as a differential diagnosis for SBO,especially in young patients in their 30s or with unexplained abdominal pain or discomfort post-surgery.A rapid imaging evaluation,preferably with CECT,is necessary to aid in an early diagnosis and prompt intervention,thereby reducing financial burden related to unnecessary investigations and preventing the morbidity and mortality associated with closed-loop obstruction and strangulation of the bowel.
文摘Photon-counting computed tomography(PCCT)represents a significant advancement in pediatric cardiovascular imaging.Traditional CT systems employ energy-integrating detectors that convert X-ray photons into visible light,whereas PCCT utilizes photon-counting detectors that directly transform X-ray photons into electric signals.This direct conversion allows photon-counting detectors to sort photons into discrete energy levels,thereby enhancing image quality through superior noise reduction,improved spatial and contrast resolution,and reduced artifacts.In pediatric applications,PCCT offers substantial benefits,including lower radiation doses,which may help reduce the risk of malignancy in pediatric patients,with perhaps greater potential to benefit those with repeated exposure from a young age.Enhanced spatial resolution facilitates better visualization of small structures,vital for diagnosing congenital heart defects.Additionally,PCCT’s spectral capabilities improve tissue characterization and enable the creation of virtual monoenergetic images,which enhance soft-tissue contrast and potentially reduce contrast media doses.Initial clinical results indicate that PCCT provides superior image quality and diagnostic accuracy compared to conven-tional CT,particularly in challenging pediatric cardiovascular cases.As PCCT technology matures,further research and standardized protocols will be essential to fully integrate it into pediatric imaging practices,ensuring optimized diagnostic outcomes and patient safety.
基金National Natural Science Foundation of China(62171305,62405206,62004135,62001317,62111530301)Natural Science Foundation of Jiangsu Province(BK20240778,BK20241917)+3 种基金State Key Laboratory of Advanced Optical Communication Systems and Networks,China(2023GZKF08)China Postdoctoral Science Foundation(2024M752314)Postdoctoral Fellowship Program of CPSF(GZC20231883)Innovative and Entrepreneurial Talent Program of Jiangsu Province(JSSCRC2021527).
文摘Photonic platforms are gradually emerging as a promising option to encounter the ever-growing demand for artificial intelligence,among which photonic time-delay reservoir computing(TDRC)is widely anticipated.While such a computing paradigm can only employ a single photonic device as the nonlinear node for data processing,the performance highly relies on the fading memory provided by the delay feedback loop(FL),which sets a restriction on the extensibility of physical implementation,especially for highly integrated chips.Here,we present a simplified photonic scheme for more flexible parameter configurations leveraging the designed quasi-convolution coding(QC),which completely gets rid of the dependence on FL.Unlike delay-based TDRC,encoded data in QC-based RC(QRC)enables temporal feature extraction,facilitating augmented memory capabilities.Thus,our proposed QRC is enabled to deal with time-related tasks or sequential data without the implementation of FL.Furthermore,we can implement this hardware with a low-power,easily integrable vertical-cavity surface-emitting laser for high-performance parallel processing.We illustrate the concept validation through simulation and experimental comparison of QRC and TDRC,wherein the simpler-structured QRC outperforms across various benchmark tasks.Our results may underscore an auspicious solution for the hardware implementation of deep neural networks.
基金Supported by Instituto de Investigación Sanitaria ISABIAL,No.P42022-0275.
文摘AIM To analyze the diagnostic performance of surveillance colonoscopy,computed tomography(CT),and tumor markers(TMs)in detecting CRC recurrence or metastasis during follow-up after CRC resection.Secondary objectives included degree of adherence to clinical practice guidelines surveillance recommendations and factors associated with adherence and all-cause and CRC mortality.METHODS The single-center retrospective cohort study including patients undergoing curative resection of stage I-III CRC during 2010-2015.Follow-up was performed using TMs every 6 months,yearly CT for 5 years,and colonoscopy at years 1 and 4.Demographic,primary tumor data,and results at follow-up were collected.RESULTS Of 574 included patients included,153 had recurrences or metastases.Of this group,136(88.9%)were diagnosed by CT,10(6.5%)by CT and colonoscopy,and 7(4.6%)by colonoscopy;only 67.8%showed TMs elevation.Adherence to follow-up recommendations was 68.8%for the first colonoscopy,74%for the first CT scan,and 96.6%for the first blood test;these values declined over time.Younger age at diagnosis[odds ratio(OR)0.93;95%CI:0.91-0.95],CRC stages I-II(OR 0.38;95%CI:0.24-0.61),and adherence to follow-up recommendations(OR 0.30;95%CI:0.20-0.46)were independently associated with lower risk for all-cause death at 5 years.CONCLUSION CT scan had the highest diagnostic yield.Adherence to follow-up recommendations was low and decreased during follow-up.Younger age at diagnosis,stage,and follow-up adherence were associated with lower 5-year mortality.
基金funding support from the National Natural Science Foundation of China(Grant No.12172019).
文摘In cold regions,rock structures will be weakened by freeze-thaw cycles under various water immersion conditions.Determining how water immersion conditions impact rock deterioration under freeze-thaw cycles is critical to assess accurately the frost resistance of engineered rock.In this paper,freeze-thaw cycles(temperature range of-20℃-20℃)were performed on the sandstones in different water immersion conditions(fully,partially and non-immersed in water).Then,computed tomography(CT)tests were conducted on the sandstones when the freeze-thaw number reached 0,5,10,15,20 and 30.Next,the effects of water immersion conditions on the microstructure deterioration of sandstone under freezethaw cycles were evaluated using CT spatial imaging,porosity and damage factor.Finally,focusing on the partially immersed condition,the immersion volume rate was defined to understand the effects of immersion degree on the freeze-thaw damage of sandstone and to propose a damage model considering the freeze-thaw number and immersion degree.The results show that with increasing freeze-thaw number,the porosities and damage factors under fully and partially immersed conditions increase continuously,while those under non-immersed condition first increase and then remain approximately constant.The most severe freeze-thaw damage occurs in fully immersed condition,followed by partially immersed condition and finally non-immersed condition.Interestingly,the freeze-thaw number and the immersion volume rate both impact the microstructure deterioration of the partially immersed sandstone.For the same freeze-thaw number,the damage factor increases approximately linearly with increasing immersion volume rate,and the increasing immersion degree exacerbates the microstructure deterioration of sandstone.Moreover,the proposed model can effectively estimate the freeze-thaw damage of partially immersed sandstone with different immersion volume rates.
基金supported by the"Science and Technology Development Plan Project of Jilin Province,China"(Grant No.20240101018JJ)the Fundamental Research Funds for the Central Universities(Grant No.2412023YQ004)the National Natural Science Foundation of China(Grant Nos.52072065,52272140,52372137,and U23A20568).
文摘Optoelectronic memristor is generating growing research interest for high efficient computing and sensing-memory applications.In this work,an optoelectronic memristor with Au/a-C:Te/Pt structure is developed.Synaptic functions,i.e.,excita-tory post-synaptic current and pair-pulse facilitation are successfully mimicked with the memristor under electrical and optical stimulations.More importantly,the device exhibited distinguishable response currents by adjusting 4-bit input electrical/opti-cal signals.A multi-mode reservoir computing(RC)system is constructed with the optoelectronic memristors to emulate human tactile-visual fusion recognition and an accuracy of 98.7%is achieved.The optoelectronic memristor provides potential for developing multi-mode RC system.
基金National Natural Science Foundation of China(U2468201,62122012,62221001).
文摘The rapid expansion of railways,especially High-Speed Railways(HSRs),has drawn considerable interest from both academic and industrial sectors.To meet the future vision of smart rail communications,the rail transport industry must innovate in key technologies to ensure high-quality transmissions for passengers and railway operations.These systems must function effectively under high mobility conditions while prioritizing safety,ecofriendliness,comfort,transparency,predictability,and reliability.On the other hand,the proposal of 6 G wireless technology introduces new possibilities for innovation in communication technologies,which may truly realize the current vision of HSR.Therefore,this article gives a review of the current advanced 6 G wireless communication technologies for HSR,including random access and switching,channel estimation and beamforming,integrated sensing and communication,and edge computing.The main application scenarios of these technologies are reviewed,as well as their current research status and challenges,followed by an outlook on future development directions.
基金supported by NRF‐CRP28‐2022‐0038“Integrating Wideband Tuneable Acoustic Filters on Silicon for High‐Speed Wireless Communication”(WBS:grant no.A‐8001503‐00‐00)National University of Singapore(NUS),Singapore,and RIE2025 IAF‐ICP under I2301E0027“Piezo Specialty Lab‐in‐Fab 2.0(LiF 2.0)-Enabling Unrivalled Power Efficient Transducers Beyond Material Limits”at National University of Singapore(NUS),Singapore.
文摘Artificial Intelligence(AI)has shown the power to enhance the functionality of sensors and enable intelligent human‐machine interfaces through machine learning‐based data analysis.However,the good performance of AI is always accompanied by a large amount of data and high computational complexity.Though cloud computing appears to be the right solution to this issue with the advent of the 5G era,a certain intelligence of the edge terminal is also important to make the entire integrated intelligent system more efficient.The current development of microelectronic,wearable,AI,and neuromorphic technologies pave the way to realize advanced edge computing by integrating silicon‐based high‐computing‐power neuromorphic chips with anthropomorphic wearable sensory devices and show the potential to achieve human‐like self‐sustainable decentralized intelligence to enable the next‐generation of AI.Hence,in this review,we systematically introduce the related progress in terms of wearable electronics that can mimic the biological features of humans'sensory systems and the development of neuromorphic/in‐sensor computing technologies.Discussion on implementing the integrated human‐like perception and sensation system with silicone‐based computing chips and non‐silicone‐based wearable functional units and our perspectives are also provided.
基金funded by the Fundamental Research Funds for the Central Universities(J2023-024,J2023-027).
文摘As an important complement to cloud computing, edge computing can effectively reduce the workload of the backbone network. To reduce latency and energy consumption of edge computing, deep learning is used to learn the task offloading strategies by interacting with the entities. In actual application scenarios, users of edge computing are always changing dynamically. However, the existing task offloading strategies cannot be applied to such dynamic scenarios. To solve this problem, we propose a novel dynamic task offloading framework for distributed edge computing, leveraging the potential of meta-reinforcement learning (MRL). Our approach formulates a multi-objective optimization problem aimed at minimizing both delay and energy consumption. We model the task offloading strategy using a directed acyclic graph (DAG). Furthermore, we propose a distributed edge computing adaptive task offloading algorithm rooted in MRL. This algorithm integrates multiple Markov decision processes (MDP) with a sequence-to-sequence (seq2seq) network, enabling it to learn and adapt task offloading strategies responsively across diverse network environments. To achieve joint optimization of delay and energy consumption, we incorporate the non-dominated sorting genetic algorithm II (NSGA-II) into our framework. Simulation results demonstrate the superiority of our proposed solution, achieving a 21% reduction in time delay and a 19% decrease in energy consumption compared to alternative task offloading schemes. Moreover, our scheme exhibits remarkable adaptability, responding swiftly to changes in various network environments.
文摘BACKGROUND Hepatocellular carcinoma(HCC)is a common tumor with a poor prognosis.Early intervention is essential;thus,good prognostic markers to identify patients who benefit from first transarterial chemoembolization(TACE)are needed.AIM To investigate the efficacy of computed tomography(CT)radiomics in predicting the success of the first TACE in patients with advanced HCC and to develop an early prediction model based on clinical radiomics features.METHODS Data from 122 patients with advanced HCC treated with TACE were analyzed.Intratumoral and peritumoral areas on arterial and venous CT images were selected to extract radiomic features,which were screened in the training cohort using the minimum redundancy maximum correlation.Then,support vector machines were used to construct the model.To construct a receiver operating characteristic curve,the predictive efficacy of each model was evaluated on the basis of the area under the curve(AUC).RESULTS Among the 122 patients,72 patients were effectively treated via TACE,and in 50 patients,this treatment was ineffective.In the radiomics model,the areas under the curve of the venous phase model were 0.867(95%CI:0.790-0.940)in the training cohort and 0.755(0.600-0.910)in the validation cohort,indicating good predictive efficacy.The multivariate logistic regression results indicated that preoperative alpha-fetoprotein levels(P=0.01)were a risk factor for TACE.The screened clinical features were combined with the radiomic features to construct a combined model.This combined model had an AUC of 0.92(0.87-0.95)in the training cohort and 0.815(0.67-0.95)in the validation cohort.CONCLUSION CT radiomics has good value in predicting the efficacy of the first TACE treatment in patients with HCC.The combined model was a better tool for predicting the first TACE efficacy in patients with advanced HCC and could provide an efficient predictive tool to help with the selection of patients for TACE.
文摘As AI systems scale, the limitations of cloud-based architectures, including latency, bandwidth, and privacy concerns, demand decentralized alternatives. Federated learning (FL) and Edge AI provide a paradigm shift by combining privacy preserving training with efficient, on device computation. This paper introduces a cutting-edge FL-edge integration framework, achieving a 10% to 15% increase in model accuracy and reducing communication costs by 25% in heterogeneous environments. Blockchain based secure aggregation ensures robust and tamper-proof model updates, while exploratory quantum AI techniques enhance computational efficiency. By addressing key challenges such as device variability and non-IID data, this work sets the stage for the next generation of adaptive, privacy-first AI systems, with applications in IoT, healthcare, and autonomous systems.
