In higher plants,the shoot apical meristem produces lateral organs in a regular spacing(phyllotaxy)and timing(plastochron).The molecular analysis of mutants associated with phyllotaxy and plastochron would increase ou...In higher plants,the shoot apical meristem produces lateral organs in a regular spacing(phyllotaxy)and timing(plastochron).The molecular analysis of mutants associated with phyllotaxy and plastochron would increase our understanding of the mechanism of shoot architecture formation.In this study,we identified mutant mnd8ynp5 that shows an increased rate of leaf emergence and a larger number of nodes in combination with a dwarfed growth habit from an EMS-treated population of the elite barley cultivar Yangnongpi 5.Using a map-based cloning strategy,the mnd8 gene was narrowed down to a 6.7-kb genomic interval on the long arm of chromosome 5H.Sequence analysis revealed that a C to T single-nucleotide mutation occurred at the first exon(position 953)of HORVU5Hr1G118820,leading to an alanine(Ala)to valine(Val)substitution at the 318th amino acid site.Next,HORVU5Hr1G118820 was defined as the candidate gene of MND8 encoding 514 amino acids and containing two multidrug and toxic compound extrusion(MATE)domains.It is highly homologous to maize Bige1and has a conserved function in the regulation of plant development by controlling the leaf initiation rate.Examination of modern barely varieties showed that Hap-1 was the dominant haplotype and was selected in barley breeding around the world.Collectively,our results indicated that mnd8ynp5 is a novel allele of the HORVU5Hr1G118820 gene that is possibly responsible for the shortened plastochron and many noded dwarf phenotype in barley.展开更多
Coarse graining of complex networks is an important method to study large-scale complex networks, and is also in the focus of network science today. This paper tries to develop a new coarse-graining method for complex...Coarse graining of complex networks is an important method to study large-scale complex networks, and is also in the focus of network science today. This paper tries to develop a new coarse-graining method for complex networks, which is based on the node similarity index. From the information structure of the network node similarity, the coarse-grained network is extracted by defining the local similarity and the global similarity index of nodes. A large number of simulation experiments show that the proposed method can effectively reduce the size of the network, while maintaining some statistical properties of the original network to some extent. Moreover, the proposed method has low computational complexity and allows people to freely choose the size of the reduced networks.展开更多
The metastatic pattern of colon cancer is typically well characterized,with initial dissemination occurring through regional lymphatics,followed by hematogenous spread.The most frequent sites of metastasis in colorect...The metastatic pattern of colon cancer is typically well characterized,with initial dissemination occurring through regional lymphatics,followed by hematogenous spread.The most frequent sites of metastasis in colorectal cancer(CRC)include regional lymph nodes(50%–70%),liver(35%–50%),lungs(21%),peritoneum(15%),and ovaries(13%).1 Isolated distant lymph node metastasis,particularly in the absence of concurrent systemic disease,is exceedingly rare in CRC.To date,only six cases of isolated axillary lymph node metastasis(ALNM)from colorectal primaries have been documented in the literature.1–6 Even more uncommon is the incidental discovery of malignant cells in anastomotic doughnuts following stoma reversal procedures.Herein,we report a rare case involving both the incidental histopathological detection of tumor cells within doughnuts during stoma closure and the subsequent development of isolated ALNM after curative resection of sigmoid colon carcinoma.展开更多
Objectives:PSMA PET/CT(Prostate-Specific MembraneAntigen Positron Emission Tomography/Computed Tomography)offers improved accuracy in detecting lymph node invasion(LNI)in prostate cancer(PC)patients,potentially reduci...Objectives:PSMA PET/CT(Prostate-Specific MembraneAntigen Positron Emission Tomography/Computed Tomography)offers improved accuracy in detecting lymph node invasion(LNI)in prostate cancer(PC)patients,potentially reducing the need for extended pelvic lymph node dissection(ePLND).This study aims to evaluate a patient-tailored care pathway in which ePLND is performed only in patients with unfavorable intermediate-or high-risk PC who are deemed at risk for LNI based on PSMA PET/CT findings.Methods:In this interventional cohort study,81 patients were managed according to the new care pathway.ePLND was omitted in cases of negative PSMA PET/CT findings(N0M0),while those with positive PSMA PET/CT findings(N1M0)underwent ePLND.A comparator group of 81 patients was selected from a prospectively generated database for comparison.Results:The intervention group experienced a 75% reduction in the number of ePLNDs performed compared to the comparator group(p<0.001).ePLND-related complications were significantly lower in the intervention group(p=0.008).No significant difference was observed in 3-year biochemical-recurrence free survival(BRFS)between the two groups(p=0.958).Conclusion:Omitting ePLND in patients with negative PSMA PET/CT findings(N0M0)leads to a substantial reduction in the number of ePLNDs performed,resulting in a decrease in morbidity,without compromising early oncological outcomes.展开更多
The escalating need for high-performance artificial intelligence(AI)computing intensifies the"memory bottleneck"of the von Neumann architecture,prompting extensive exploration of computation-in-memory(CIM)so...The escalating need for high-performance artificial intelligence(AI)computing intensifies the"memory bottleneck"of the von Neumann architecture,prompting extensive exploration of computation-in-memory(CIM)solutions.This study is cen-tered on the optimization of a high-efficiency,low-power"L"-shaped split-gate floating-gate(FG)memory for CIM applications.Fabricated on a 55 nm CMOS platform,the memory devices were systematically investigated through wafer acceptance test(WAT),Sentaurus^(TM)simulations and comprehensive evaluations with the DNN+NeuroSim Framework V2.0.Among devices with diverse FG lengths,the 95-nm FG variant exhibits outstanding performance:it achieves a 5.35 V memory window,reaches a maximum conductance of 16.7μS with excellent linearity under the varying voltage and width pulse scheme(VWPS),real-izes 32-state multi-level storage,and attains a 92%training accuracy on the CIFAR-10 dataset using the VGG8 neural network.展开更多
Network topology obfuscation is a technique aimed at protecting critical nodes and links from disruptions such as Link Flooding Attack(LFA).Currently,there are limited topology obfuscation methods for protecting criti...Network topology obfuscation is a technique aimed at protecting critical nodes and links from disruptions such as Link Flooding Attack(LFA).Currently,there are limited topology obfuscation methods for protecting critical nodes,and the existing approaches mainly achieve obfuscation by extensivelymodifying network links,resulting in high costs.To address this issue,this paper proposes a low-cost network topology obfuscation method dedicated to critical node protection,with its core innovation lying in a lightweight obfuscation architecture based on Fake Node Clusters(FNCs).Firstly,the protected network is modeled as an undirected graph,and an adjacency matrix is constructed to quantify the network scale and structural characteristics.Then,a fake node cluster generation algorithm is designed to construct an FNC adapted to the target network.Finally,a heuristic obfuscated topology generation algorithm is proposed.By optimizing the deployment positions of Fake Nodes Clusters(FNCs)in the protected network,this algorithm effectively reduces the number of FNCs required to generate the obfuscated topology,further lowering the obfuscation cost.Extensive experiments were conducted on the public Topology Zoo dataset,categorizing network topologies by node count into small-scale([0,50)),medium-scale([50,100)),and large-scale([100,200))groups.The experimental results demonstrate that the proposed approach achieves excellent obfuscation performance,reducing the critical node recognition rate to 0%.Compared to the typical method,EigenObfu,the proposed approach also reduces obfuscation costs by an average of 97.9%,99.6%,and 99.3%for small,medium,and large-scale networks,respectively.展开更多
BACKGROUND The accurate prediction of lymph node metastasis(LNM)is crucial for managing locally advanced(T3/T4)colorectal cancer(CRC).However,both traditional histopathology and standard slide-level deep learning ofte...BACKGROUND The accurate prediction of lymph node metastasis(LNM)is crucial for managing locally advanced(T3/T4)colorectal cancer(CRC).However,both traditional histopathology and standard slide-level deep learning often fail to capture the sparse and diagnostically critical features of metastatic potential.AIM To develop and validate a case-level multiple-instance learning(MIL)framework mimicking a pathologist's comprehensive review and improve T3/T4 CRC LNM prediction.METHODS The whole-slide images of 130 patients with T3/T4 CRC were retrospectively collected.A case-level MIL framework utilising the CONCH v1.5 and UNI2-h deep learning models was trained on features from all haematoxylin and eosinstained primary tumour slides for each patient.These pathological features were subsequently integrated with clinical data,and model performance was evaluated using the area under the curve(AUC).RESULTS The case-level framework demonstrated superior LNM prediction over slide-level training,with the CONCH v1.5 model achieving a mean AUC(±SD)of 0.899±0.033 vs 0.814±0.083,respectively.Integrating pathology features with clinical data further enhanced performance,yielding a top model with a mean AUC of 0.904±0.047,in sharp contrast to a clinical-only model(mean AUC 0.584±0.084).Crucially,a pathologist’s review confirmed that the model-identified high-attention regions correspond to known high-risk histopathological features.CONCLUSION A case-level MIL framework provides a superior approach for predicting LNM in advanced CRC.This method shows promise for risk stratification and therapy decisions,requiring further validation.展开更多
Graph neural networks(GNN)have shown strong performance in node classification tasks,yet most existing models rely on uniform or shared weight aggregation,lacking flexibility in modeling the varying strength of relati...Graph neural networks(GNN)have shown strong performance in node classification tasks,yet most existing models rely on uniform or shared weight aggregation,lacking flexibility in modeling the varying strength of relationships among nodes.This paper proposes a novel graph coupling convolutional model that introduces an adaptive weighting mechanism to assign distinct importance to neighboring nodes based on their similarity to the central node.Unlike traditional methods,the proposed coupling strategy enhances the interpretability of node interactions while maintaining competitive classification performance.The model operates in the spatial domain,utilizing adjacency list structures for efficient convolution and addressing the limitations of weight sharing through a coupling-based similarity computation.Extensive experiments are conducted on five graph-structured datasets,including Cora,Citeseer,PubMed,Reddit,and BlogCatalog,as well as a custom topology dataset constructed from the Open University Learning Analytics Dataset(OULAD)educational platform.Results demonstrate that the proposed model achieves good classification accuracy,while significantly reducing training time through direct second-order neighbor fusion and data preprocessing.Moreover,analysis of neighborhood order reveals that considering third-order neighbors offers limited accuracy gains but introduces considerable computational overhead,confirming the efficiency of first-and second-order convolution in practical applications.Overall,the proposed graph coupling model offers a lightweight,interpretable,and effective framework for multi-label node classification in complex networks.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
Cyber-criminals target smart connected devices for spyware distribution and security breaches,but existing Internet of Things(IoT)security standards are insufficient.Major IoT industry players prioritize market share ...Cyber-criminals target smart connected devices for spyware distribution and security breaches,but existing Internet of Things(IoT)security standards are insufficient.Major IoT industry players prioritize market share over security,leading to insecure smart products.Traditional host-based protection solutions are less effective due to limited resources.Overcoming these challenges and enhancing the security of IoT Devices requires a security design at the network level that uses lightweight cryptographic parameters.In order to handle control,administration,and security concerns in traditional networking,the Gateway Node offers a contemporary networking architecture.By managing all network-level computations and complexity,the Gateway Node relieves IoT devices of these responsibilities.In this study,we introduce a novel privacy-preserving security architecture for gateway-node smart homes.Subsequently,we develop Smart Homes,An Efficient,Anonymous,and Robust Authentication Scheme(EARAS)based on the foundational principles of this security architecture.Furthermore,we formally examine the security characteristics of our suggested protocol that makes use of methodology such as ProVerif,supplemented by an informal analysis of security.Lastly,we conduct performance evaluations and comparative analyses to assess the efficacy of our scheme.Performance analysis shows that EARAS achieves up to 30%to 54%more efficient than most protocols and lower computation cost compared to Banerjee et al.’s scheme,and significantly reduces communication overhead compared to other recent protocols,while ensuring comprehensive security.Our objective is to provide robust security measures for smart homes while addressing resource constraints and preserving user privacy.展开更多
Dear Editor,D2This letter presents a node feature similarity preserving graph convolutional framework P G.Graph neural networks(GNNs)have garnered significant attention for their efficacy in learning graph representat...Dear Editor,D2This letter presents a node feature similarity preserving graph convolutional framework P G.Graph neural networks(GNNs)have garnered significant attention for their efficacy in learning graph representations across diverse real-world applications.展开更多
Existing numerical methods for complex composites, such as multiscale simulation and neural network algorithms, face significant limitations. Multiscale techniques are often prohibitively expensive for large models, w...Existing numerical methods for complex composites, such as multiscale simulation and neural network algorithms, face significant limitations. Multiscale techniques are often prohibitively expensive for large models, while neural networks struggle to represent underlying microscopic material properties. To overcome these challenges, a meso-micro scale numerical method using a virtual node approach is developed in this study. A Wbraid/Al/Epoxy functional structural material is fabricated, and a representative periodic unit cell is identified based on its architecture. The complex structure is then discretized into nodes, and mechanical interactions are governed by pre-defined computation rules. This virtual node method is systematically compared against both multiscale simulation and a neural network algorithm, with validation provided through mechanical experiments. The results demonstrate that the nodal operation strategy significantly reduces computational resource requirements. By quantifying microscopic bonding with coefficients, explicit interface treatment is avoided, granting the method strong adaptability to lattice materials. The method can simulate extremely complex structures using parameters from simple tests and is suited for large systems. Compared to three-point bending experiments, errors for multiscale, virtual node, and neural network methods were 12.4%, 6.9%, and 34.5%, respectively. Under dynamic compression, the errors were 2.7%, 9.3%, and 15.43%. The virtual node method demonstrated superior accuracy under static conditions, enabling efficient prediction and auxiliary development of complex structural materials.展开更多
Lightweight nodes are crucial for blockchain scalability,but verifying the availability of complete block data puts significant strain on bandwidth and latency.Existing data availability sampling(DAS)schemes either re...Lightweight nodes are crucial for blockchain scalability,but verifying the availability of complete block data puts significant strain on bandwidth and latency.Existing data availability sampling(DAS)schemes either require trusted setups or suffer from high communication overhead and low verification efficiency.This paper presents ISTIRDA,a DAS scheme that lets light clients certify availability by sampling small random codeword symbols.Built on ISTIR,an improved Reed–Solomon interactive oracle proof of proximity,ISTIRDA combines adaptive folding with dynamic code rate adjustment to preserve soundness while lowering communication.This paper formalizes opening consistency and prove security with bounded error in the random oracle model,giving polylogarithmic verifier queries and no trusted setup.In a prototype compared with FRIDA under equal soundness,ISTIRDA reduces communication by 40.65%to 80%.For data larger than 16 MB,ISTIRDA verifies faster and the advantage widens;at 128 MB,proofs are about 60%smaller and verification time is roughly 25%shorter,while prover overhead remains modest.In peer-to-peer emulation under injected latency and loss,ISTIRDA reaches confidence more quickly and is less sensitive to packet loss and load.These results indicate that ISTIRDA is a scalable and provably secure DAS scheme suitable for high-throughput,large-block public blockchains,substantially easing bandwidth and latency pressure on lightweight nodes.展开更多
Objective:To investigate the long-term prognosis and postoperative cosmetic outcomes of breast-conserving surgery combined with sentinel lymph node biopsy in patients with early-stage breast cancer,providing a referen...Objective:To investigate the long-term prognosis and postoperative cosmetic outcomes of breast-conserving surgery combined with sentinel lymph node biopsy in patients with early-stage breast cancer,providing a reference for the selection of clinical treatment plans.Methods:A retrospective analysis was conducted on the clinical data of 68 patients with early-stage breast cancer admitted from January 2022 to December 2025.Based on the surgical approach,patients were divided into an observation group(breast-conserving surgery+sentinel lymph node biopsy)and a control group(other surgical methods such as modified radical mastectomy/total mastectomy).Clinical and pathological characteristics,incidence of postoperative complications,follow-up prognosis,and satisfaction with cosmetic outcomes were compared between the two groups.Results:Among the 68 patients,41 were in the observation group and 27 in the control group.The average age of patients in the observation group was(54.32±8.15)years,while that in the control group was(62.45±9.76)years.The average tumor size in the observation group was(1.86±0.72)cm,compared to(3.21±1.45)cm in the control group.The incidence of postoperative complications in the observation group was 9.76%,significantly lower than that in the control group at 33.33%(P<0.05).The 6-month disease-free survival rate was 95.12%in the observation group and 88.89%in the control group,with no statistically significant difference between the two groups(P>0.05).The excellent and good rate of cosmetic outcomes in the observation group was 87.80%,significantly higher than that in the control group at 29.63%(P<0.05).Conclusion:Breast-conserving surgery combined with sentinel lymph node biopsy for early-stage breast cancer can achieve long-term prognostic outcomes comparable to those of traditional radical surgery,with the advantages of fewer postoperative complications and superior cosmetic results.This approach is worthy of clinical promotion and application,particularly for early-stage breast cancer patients who have a demand for preserving breast morphology.展开更多
Objective:The current pathological diagnosis of lymph node metastasis is time-consuming,labor-intensive,and dependent on sectioning of paraffin blocks.Herein,in a prospective cohort of patients with breast cancer,we v...Objective:The current pathological diagnosis of lymph node metastasis is time-consuming,labor-intensive,and dependent on sectioning of paraffin blocks.Herein,in a prospective cohort of patients with breast cancer,we validated dynamic full-field optical coherence tomography(D-FFOCT),a virtual pathology tool integrating deep learning for nodal metastasis detection,and offering rapid and label-free histologic approximations of fresh tissues.Methods:In a prospective dual-center cohort of 155 patients with breast cancer,747 freshly bisected lymph node slides were obtained via D-FFOCT.Surgeons interpreted each slide with histopathology as the gold standard.A deep learning model was trained on 28,911 patches(corresponding to 590 slides)and tested on 7,736 patches(corresponding to 157 slides).The results were mapped to the slide level for potential intraoperative evaluation.Results:D-FFOCT strongly correlated with hematoxylin and eosin(H&E)-stained histological images.Surgeons achieved 97.10%specificity in nodal diagnosis with D-FFOCT.The performance of the artificial intelligence(AI)model was not inferior to that of human experts and had a sensitivity/specificity of 87.88%/91.94%and an area under the receiver operating characteristic curve of 0.899 at the slide level.The human–AI collaborative system reduced labor requirements by 75%and increased the specificity by 6.5%,to 98.39%.Conclusions:D-FFOCT has excellent potential as a tool for assessing lymph node metastatic status without tissue preparation or consumption.The integration of D-FFOCT with deep learning decreases labor demands and maintains high accuracy,thereby enabling streamlined nodal prediction independent of routine pathology procedures.展开更多
With the advancement of surgical techniques and enhanced management of early gastric cancer(EGC),minimally invasive function-preserving surgical approaches have emerged as a common goal for patients and clinicians.Lap...With the advancement of surgical techniques and enhanced management of early gastric cancer(EGC),minimally invasive function-preserving surgical approaches have emerged as a common goal for patients and clinicians.Laparoscopic-endoscopic cooperative surgery combined with sentinel lymph node navigation surgery(LECSSNNS)has drawn increasing interest because of its dual benefits of minimal invasiveness and organ function preservation.However,robust evidence-based support for guiding clinical implementation remains limited.To address this gap,we systematically evaluated available studies on the clinical application of LECS-SNNS in EGC and integrated expert insights to formulate 20 recommendations.These included preoperative assessment,surgical techniques,intraoperative endoscopic procedures,pathological evaluation,postoperative care,and follow-up.This consensus aimed to provide comprehensive guidance for the standardized application of LECS-SNNS,thereby advancing precise,minimally invasive,and function-preserving treatment for EGC.展开更多
Objective:Open retroperitoneal lymph node dissection(RPLND)is the gold-standard surgical approach for the management of metastatic testicular cancer,but robotic RPLND is becoming increasingly popular.There is limited ...Objective:Open retroperitoneal lymph node dissection(RPLND)is the gold-standard surgical approach for the management of metastatic testicular cancer,but robotic RPLND is becoming increasingly popular.There is limited research directly comparing open and robotic RPLND.The objective of this systematic review is to identify all the literature with direct comparisons between the open and robotic techniques for RPLND and to compare the two techniques.The primary outcome was peri-operative outcomes,and the secondary outcomes included oncological outcomes and patient demographics.Methods:This systematic review was prospectively registered and was conducted in accordance with the PRISMA statement.The PubMed,Embase and MEDLINE databases were searched for relevant publication from January 2006 to August 2024.Results:Eight studies,totaling 3995 patients,are included in this systematic review,with 3521 patients who underwent open RPLND and 474 who underwent robotic RPLND.For open RPLND,the mean operative duration,blood loss and length of stay were 267.8 min,475 mL and 7.3 d,respectively.For robotic RPLND,the mean operative duration,blood loss and length of stay were 334.5 min,94.6 mL and 3.7 d,respectively.Teratoma was the most common RPLND specimen pathology from both open and robotic surgeries.For open RPLND,the specimens have 13–23 nodes(26–32 mm),whereas the robotic RPLND specimens have 13–28 nodes(18–20 mm).Conclusion:This systematic review suggests that the benefitsof robotic RPLND may be associated with reduced blood loss,shorter hospitalisation and an overall lower risk of minor and major complications while maintaining oncological safety.展开更多
Modular truss space deployable antennas are key for future large aperture,high precision antennas,already proven in various in-orbit applications globally.This paper introduces a design method for a tetrahedral basic ...Modular truss space deployable antennas are key for future large aperture,high precision antennas,already proven in various in-orbit applications globally.This paper introduces a design method for a tetrahedral basic unit mechanism with dual height positioning nodes.A parametric model is established,and its DOF are analyzed to confirm the mechanism's validity.The new tetrahedral basic unit mechanism constructed by this method is a single DOF mechanism and can locate different parabolic node heights.In order to further adapt to the parabolic and large aperture requirements of the deployable antenna of the truss,a combination unit and modular unit mechanism are developed based on this tetrahedral unit.The DOF and deployment characteristics of the modular unit mechanism are analyzed and validated through simulations.Various networking methods for the modular units are proposed,followed by a comprehensive performance comparison of different modular truss deployable antenna mechanisms.A prototype model of the modular unit mechanism is also developed,with deployment experiments demonstrating the mechanism's simplicity,low DOF,and large deployment ratio.The findings of this study provide a theoretical and technical basis for the future design and development of truss deployable antenna mechanisms.展开更多
Cascading failures pose a serious threat to the survivability of underwater unmanned swarm networks(UUSNs),significantly limiting their service ability in collaborative missions such as military reconnaissance and env...Cascading failures pose a serious threat to the survivability of underwater unmanned swarm networks(UUSNs),significantly limiting their service ability in collaborative missions such as military reconnaissance and environmental monitoring.Existing failure models primarily focus on power grids and traffic systems,and don't address the unique challenges of weak-communication UUSNs.In UUSNs,cascading failure present a complex and dynamic process driven by the coupling of unstable acoustic channels,passive node drift,adversarial attacks,and network heterogeneity.To address these challenges,a directed weighted graph model of UUSNs is first developed,in which node positions are updated according to ocean-current-driven drift and link weights reflect the probability of successful acoustic transmission.Building on this UUSNs graph model,a cascading failure model is proposed that integrates a normal-failure-recovery state-cycle mechanism,multiple attack strategies,and routingbased load redistribution.Finally,under a five-level connectivity UUSNs scheme,simulations are conducted to analyze how dynamic topology,network load,node recovery delay,and attack modes jointly affect network survivability.The main findings are:(1)moderate node drift can improve survivability by activating weak links;(2)based-energy routing(BER)outperform based-depth routing(BDR)in harsh conditions;(3)node self-recovery time is critical to network survivability;(4)traditional degree-based critical node metrics are inadequate for weak-communication UUSNs.These results provide a theoretical foundation for designing robust survivability mechanisms in weak-communication UUSNs.展开更多
基金funded by the Open Project Program of State Key Laboratory of Barley and Yak Germplasm Resources and Genetic Improvement,China(XZNKY2021-C-014-K01)the Natural Science Foundation of the Jiangsu Higher Education Institutions of China(19KJA560005)+1 种基金the China Agriculture Research System(CARS-05)a Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions,China。
文摘In higher plants,the shoot apical meristem produces lateral organs in a regular spacing(phyllotaxy)and timing(plastochron).The molecular analysis of mutants associated with phyllotaxy and plastochron would increase our understanding of the mechanism of shoot architecture formation.In this study,we identified mutant mnd8ynp5 that shows an increased rate of leaf emergence and a larger number of nodes in combination with a dwarfed growth habit from an EMS-treated population of the elite barley cultivar Yangnongpi 5.Using a map-based cloning strategy,the mnd8 gene was narrowed down to a 6.7-kb genomic interval on the long arm of chromosome 5H.Sequence analysis revealed that a C to T single-nucleotide mutation occurred at the first exon(position 953)of HORVU5Hr1G118820,leading to an alanine(Ala)to valine(Val)substitution at the 318th amino acid site.Next,HORVU5Hr1G118820 was defined as the candidate gene of MND8 encoding 514 amino acids and containing two multidrug and toxic compound extrusion(MATE)domains.It is highly homologous to maize Bige1and has a conserved function in the regulation of plant development by controlling the leaf initiation rate.Examination of modern barely varieties showed that Hap-1 was the dominant haplotype and was selected in barley breeding around the world.Collectively,our results indicated that mnd8ynp5 is a novel allele of the HORVU5Hr1G118820 gene that is possibly responsible for the shortened plastochron and many noded dwarf phenotype in barley.
文摘Coarse graining of complex networks is an important method to study large-scale complex networks, and is also in the focus of network science today. This paper tries to develop a new coarse-graining method for complex networks, which is based on the node similarity index. From the information structure of the network node similarity, the coarse-grained network is extracted by defining the local similarity and the global similarity index of nodes. A large number of simulation experiments show that the proposed method can effectively reduce the size of the network, while maintaining some statistical properties of the original network to some extent. Moreover, the proposed method has low computational complexity and allows people to freely choose the size of the reduced networks.
文摘The metastatic pattern of colon cancer is typically well characterized,with initial dissemination occurring through regional lymphatics,followed by hematogenous spread.The most frequent sites of metastasis in colorectal cancer(CRC)include regional lymph nodes(50%–70%),liver(35%–50%),lungs(21%),peritoneum(15%),and ovaries(13%).1 Isolated distant lymph node metastasis,particularly in the absence of concurrent systemic disease,is exceedingly rare in CRC.To date,only six cases of isolated axillary lymph node metastasis(ALNM)from colorectal primaries have been documented in the literature.1–6 Even more uncommon is the incidental discovery of malignant cells in anastomotic doughnuts following stoma reversal procedures.Herein,we report a rare case involving both the incidental histopathological detection of tumor cells within doughnuts during stoma closure and the subsequent development of isolated ALNM after curative resection of sigmoid colon carcinoma.
基金supported by a grant from Kom op tegen Kanker(Stand Up to Cancer,Belgium).
文摘Objectives:PSMA PET/CT(Prostate-Specific MembraneAntigen Positron Emission Tomography/Computed Tomography)offers improved accuracy in detecting lymph node invasion(LNI)in prostate cancer(PC)patients,potentially reducing the need for extended pelvic lymph node dissection(ePLND).This study aims to evaluate a patient-tailored care pathway in which ePLND is performed only in patients with unfavorable intermediate-or high-risk PC who are deemed at risk for LNI based on PSMA PET/CT findings.Methods:In this interventional cohort study,81 patients were managed according to the new care pathway.ePLND was omitted in cases of negative PSMA PET/CT findings(N0M0),while those with positive PSMA PET/CT findings(N1M0)underwent ePLND.A comparator group of 81 patients was selected from a prospectively generated database for comparison.Results:The intervention group experienced a 75% reduction in the number of ePLNDs performed compared to the comparator group(p<0.001).ePLND-related complications were significantly lower in the intervention group(p=0.008).No significant difference was observed in 3-year biochemical-recurrence free survival(BRFS)between the two groups(p=0.958).Conclusion:Omitting ePLND in patients with negative PSMA PET/CT findings(N0M0)leads to a substantial reduction in the number of ePLNDs performed,resulting in a decrease in morbidity,without compromising early oncological outcomes.
基金supported by National Key Research and Development Program of China (2022YFF0605803)Zhejiang key R&D project (2023C01017)+1 种基金the Zhejiang Key Research and Development Project (2024SJCZX0030)Zhejiang Technology Innovation Center of CMOS IC Manufacture Process and Design for supporting us to do this research.
文摘The escalating need for high-performance artificial intelligence(AI)computing intensifies the"memory bottleneck"of the von Neumann architecture,prompting extensive exploration of computation-in-memory(CIM)solutions.This study is cen-tered on the optimization of a high-efficiency,low-power"L"-shaped split-gate floating-gate(FG)memory for CIM applications.Fabricated on a 55 nm CMOS platform,the memory devices were systematically investigated through wafer acceptance test(WAT),Sentaurus^(TM)simulations and comprehensive evaluations with the DNN+NeuroSim Framework V2.0.Among devices with diverse FG lengths,the 95-nm FG variant exhibits outstanding performance:it achieves a 5.35 V memory window,reaches a maximum conductance of 16.7μS with excellent linearity under the varying voltage and width pulse scheme(VWPS),real-izes 32-state multi-level storage,and attains a 92%training accuracy on the CIFAR-10 dataset using the VGG8 neural network.
基金funded by the National Key Research and Development Program of China(Grant No.2022YFB3102900)the Key Science and Technology Project of Henan Province,China(No.252102211091).
文摘Network topology obfuscation is a technique aimed at protecting critical nodes and links from disruptions such as Link Flooding Attack(LFA).Currently,there are limited topology obfuscation methods for protecting critical nodes,and the existing approaches mainly achieve obfuscation by extensivelymodifying network links,resulting in high costs.To address this issue,this paper proposes a low-cost network topology obfuscation method dedicated to critical node protection,with its core innovation lying in a lightweight obfuscation architecture based on Fake Node Clusters(FNCs).Firstly,the protected network is modeled as an undirected graph,and an adjacency matrix is constructed to quantify the network scale and structural characteristics.Then,a fake node cluster generation algorithm is designed to construct an FNC adapted to the target network.Finally,a heuristic obfuscated topology generation algorithm is proposed.By optimizing the deployment positions of Fake Nodes Clusters(FNCs)in the protected network,this algorithm effectively reduces the number of FNCs required to generate the obfuscated topology,further lowering the obfuscation cost.Extensive experiments were conducted on the public Topology Zoo dataset,categorizing network topologies by node count into small-scale([0,50)),medium-scale([50,100)),and large-scale([100,200))groups.The experimental results demonstrate that the proposed approach achieves excellent obfuscation performance,reducing the critical node recognition rate to 0%.Compared to the typical method,EigenObfu,the proposed approach also reduces obfuscation costs by an average of 97.9%,99.6%,and 99.3%for small,medium,and large-scale networks,respectively.
基金Supported by Chongqing Medical Scientific Research Project(Joint Project of Chongqing Health Commission and Science and Technology Bureau),No.2023MSXM060.
文摘BACKGROUND The accurate prediction of lymph node metastasis(LNM)is crucial for managing locally advanced(T3/T4)colorectal cancer(CRC).However,both traditional histopathology and standard slide-level deep learning often fail to capture the sparse and diagnostically critical features of metastatic potential.AIM To develop and validate a case-level multiple-instance learning(MIL)framework mimicking a pathologist's comprehensive review and improve T3/T4 CRC LNM prediction.METHODS The whole-slide images of 130 patients with T3/T4 CRC were retrospectively collected.A case-level MIL framework utilising the CONCH v1.5 and UNI2-h deep learning models was trained on features from all haematoxylin and eosinstained primary tumour slides for each patient.These pathological features were subsequently integrated with clinical data,and model performance was evaluated using the area under the curve(AUC).RESULTS The case-level framework demonstrated superior LNM prediction over slide-level training,with the CONCH v1.5 model achieving a mean AUC(±SD)of 0.899±0.033 vs 0.814±0.083,respectively.Integrating pathology features with clinical data further enhanced performance,yielding a top model with a mean AUC of 0.904±0.047,in sharp contrast to a clinical-only model(mean AUC 0.584±0.084).Crucially,a pathologist’s review confirmed that the model-identified high-attention regions correspond to known high-risk histopathological features.CONCLUSION A case-level MIL framework provides a superior approach for predicting LNM in advanced CRC.This method shows promise for risk stratification and therapy decisions,requiring further validation.
基金Support by Sichuan Science and Technology Program[2023YFSY0026,2023YFH0004]Guangzhou Huashang University[2024HSZD01,HS2023JYSZH01].
文摘Graph neural networks(GNN)have shown strong performance in node classification tasks,yet most existing models rely on uniform or shared weight aggregation,lacking flexibility in modeling the varying strength of relationships among nodes.This paper proposes a novel graph coupling convolutional model that introduces an adaptive weighting mechanism to assign distinct importance to neighboring nodes based on their similarity to the central node.Unlike traditional methods,the proposed coupling strategy enhances the interpretability of node interactions while maintaining competitive classification performance.The model operates in the spatial domain,utilizing adjacency list structures for efficient convolution and addressing the limitations of weight sharing through a coupling-based similarity computation.Extensive experiments are conducted on five graph-structured datasets,including Cora,Citeseer,PubMed,Reddit,and BlogCatalog,as well as a custom topology dataset constructed from the Open University Learning Analytics Dataset(OULAD)educational platform.Results demonstrate that the proposed model achieves good classification accuracy,while significantly reducing training time through direct second-order neighbor fusion and data preprocessing.Moreover,analysis of neighborhood order reveals that considering third-order neighbors offers limited accuracy gains but introduces considerable computational overhead,confirming the efficiency of first-and second-order convolution in practical applications.Overall,the proposed graph coupling model offers a lightweight,interpretable,and effective framework for multi-label node classification in complex networks.
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.
基金Deanship of Graduate Studies and Scientific Research at Qassim University for financial support(QU-APC-2025).
文摘Cyber-criminals target smart connected devices for spyware distribution and security breaches,but existing Internet of Things(IoT)security standards are insufficient.Major IoT industry players prioritize market share over security,leading to insecure smart products.Traditional host-based protection solutions are less effective due to limited resources.Overcoming these challenges and enhancing the security of IoT Devices requires a security design at the network level that uses lightweight cryptographic parameters.In order to handle control,administration,and security concerns in traditional networking,the Gateway Node offers a contemporary networking architecture.By managing all network-level computations and complexity,the Gateway Node relieves IoT devices of these responsibilities.In this study,we introduce a novel privacy-preserving security architecture for gateway-node smart homes.Subsequently,we develop Smart Homes,An Efficient,Anonymous,and Robust Authentication Scheme(EARAS)based on the foundational principles of this security architecture.Furthermore,we formally examine the security characteristics of our suggested protocol that makes use of methodology such as ProVerif,supplemented by an informal analysis of security.Lastly,we conduct performance evaluations and comparative analyses to assess the efficacy of our scheme.Performance analysis shows that EARAS achieves up to 30%to 54%more efficient than most protocols and lower computation cost compared to Banerjee et al.’s scheme,and significantly reduces communication overhead compared to other recent protocols,while ensuring comprehensive security.Our objective is to provide robust security measures for smart homes while addressing resource constraints and preserving user privacy.
基金supported by the National Natural Science Foundation of China(62402399)the New Chongqing Youth Innovation Talent Project(CSTB2024NSCQ-QCXMX0035)。
文摘Dear Editor,D2This letter presents a node feature similarity preserving graph convolutional framework P G.Graph neural networks(GNNs)have garnered significant attention for their efficacy in learning graph representations across diverse real-world applications.
文摘Existing numerical methods for complex composites, such as multiscale simulation and neural network algorithms, face significant limitations. Multiscale techniques are often prohibitively expensive for large models, while neural networks struggle to represent underlying microscopic material properties. To overcome these challenges, a meso-micro scale numerical method using a virtual node approach is developed in this study. A Wbraid/Al/Epoxy functional structural material is fabricated, and a representative periodic unit cell is identified based on its architecture. The complex structure is then discretized into nodes, and mechanical interactions are governed by pre-defined computation rules. This virtual node method is systematically compared against both multiscale simulation and a neural network algorithm, with validation provided through mechanical experiments. The results demonstrate that the nodal operation strategy significantly reduces computational resource requirements. By quantifying microscopic bonding with coefficients, explicit interface treatment is avoided, granting the method strong adaptability to lattice materials. The method can simulate extremely complex structures using parameters from simple tests and is suited for large systems. Compared to three-point bending experiments, errors for multiscale, virtual node, and neural network methods were 12.4%, 6.9%, and 34.5%, respectively. Under dynamic compression, the errors were 2.7%, 9.3%, and 15.43%. The virtual node method demonstrated superior accuracy under static conditions, enabling efficient prediction and auxiliary development of complex structural materials.
基金supported in part by the Research Fund of Key Lab of Education Blockchain and Intelligent Technology,Ministry of Education(EBME25-F-08).
文摘Lightweight nodes are crucial for blockchain scalability,but verifying the availability of complete block data puts significant strain on bandwidth and latency.Existing data availability sampling(DAS)schemes either require trusted setups or suffer from high communication overhead and low verification efficiency.This paper presents ISTIRDA,a DAS scheme that lets light clients certify availability by sampling small random codeword symbols.Built on ISTIR,an improved Reed–Solomon interactive oracle proof of proximity,ISTIRDA combines adaptive folding with dynamic code rate adjustment to preserve soundness while lowering communication.This paper formalizes opening consistency and prove security with bounded error in the random oracle model,giving polylogarithmic verifier queries and no trusted setup.In a prototype compared with FRIDA under equal soundness,ISTIRDA reduces communication by 40.65%to 80%.For data larger than 16 MB,ISTIRDA verifies faster and the advantage widens;at 128 MB,proofs are about 60%smaller and verification time is roughly 25%shorter,while prover overhead remains modest.In peer-to-peer emulation under injected latency and loss,ISTIRDA reaches confidence more quickly and is less sensitive to packet loss and load.These results indicate that ISTIRDA is a scalable and provably secure DAS scheme suitable for high-throughput,large-block public blockchains,substantially easing bandwidth and latency pressure on lightweight nodes.
文摘Objective:To investigate the long-term prognosis and postoperative cosmetic outcomes of breast-conserving surgery combined with sentinel lymph node biopsy in patients with early-stage breast cancer,providing a reference for the selection of clinical treatment plans.Methods:A retrospective analysis was conducted on the clinical data of 68 patients with early-stage breast cancer admitted from January 2022 to December 2025.Based on the surgical approach,patients were divided into an observation group(breast-conserving surgery+sentinel lymph node biopsy)and a control group(other surgical methods such as modified radical mastectomy/total mastectomy).Clinical and pathological characteristics,incidence of postoperative complications,follow-up prognosis,and satisfaction with cosmetic outcomes were compared between the two groups.Results:Among the 68 patients,41 were in the observation group and 27 in the control group.The average age of patients in the observation group was(54.32±8.15)years,while that in the control group was(62.45±9.76)years.The average tumor size in the observation group was(1.86±0.72)cm,compared to(3.21±1.45)cm in the control group.The incidence of postoperative complications in the observation group was 9.76%,significantly lower than that in the control group at 33.33%(P<0.05).The 6-month disease-free survival rate was 95.12%in the observation group and 88.89%in the control group,with no statistically significant difference between the two groups(P>0.05).The excellent and good rate of cosmetic outcomes in the observation group was 87.80%,significantly higher than that in the control group at 29.63%(P<0.05).Conclusion:Breast-conserving surgery combined with sentinel lymph node biopsy for early-stage breast cancer can achieve long-term prognostic outcomes comparable to those of traditional radical surgery,with the advantages of fewer postoperative complications and superior cosmetic results.This approach is worthy of clinical promotion and application,particularly for early-stage breast cancer patients who have a demand for preserving breast morphology.
基金supported by grants from the National Key Research and Development Program of China(Grant No.2024YFC3405303)Beijing Natural Science Foundation(Grant No.7242281 and 7244427)Research and Development Fund of Peking University People’s Hospital(Grant No.RDZH2024-03 and RDEB2025-25).
文摘Objective:The current pathological diagnosis of lymph node metastasis is time-consuming,labor-intensive,and dependent on sectioning of paraffin blocks.Herein,in a prospective cohort of patients with breast cancer,we validated dynamic full-field optical coherence tomography(D-FFOCT),a virtual pathology tool integrating deep learning for nodal metastasis detection,and offering rapid and label-free histologic approximations of fresh tissues.Methods:In a prospective dual-center cohort of 155 patients with breast cancer,747 freshly bisected lymph node slides were obtained via D-FFOCT.Surgeons interpreted each slide with histopathology as the gold standard.A deep learning model was trained on 28,911 patches(corresponding to 590 slides)and tested on 7,736 patches(corresponding to 157 slides).The results were mapped to the slide level for potential intraoperative evaluation.Results:D-FFOCT strongly correlated with hematoxylin and eosin(H&E)-stained histological images.Surgeons achieved 97.10%specificity in nodal diagnosis with D-FFOCT.The performance of the artificial intelligence(AI)model was not inferior to that of human experts and had a sensitivity/specificity of 87.88%/91.94%and an area under the receiver operating characteristic curve of 0.899 at the slide level.The human–AI collaborative system reduced labor requirements by 75%and increased the specificity by 6.5%,to 98.39%.Conclusions:D-FFOCT has excellent potential as a tool for assessing lymph node metastatic status without tissue preparation or consumption.The integration of D-FFOCT with deep learning decreases labor demands and maintains high accuracy,thereby enabling streamlined nodal prediction independent of routine pathology procedures.
基金supported by National Key Research and Development Program of China(No.2023YFC2507406)National Natural Science Foundation of China(No.82300646)+6 种基金Beijing Natural Science Foundation(No.7232334)Beijing Municipal Administration of Hospitals Incubating Program(No.PX2024002,PX2020001)Capital Fund for Health Development Scientific Research(No.2024-2-2028)Beijing Municipal Science&Technology Commission AI+Health Collaborative Innovation Cultivation Project(No.Z241100007724004)Research Ward Excellence Program of Beijing Municipal Health Commission(No.BRWEP2024W162020100,BRWEP2024W162020112,BRWEP2024W162020114)Excellent Plan for Capital Medicine Scientific and Technological Innovation Achievement Transformation Promotion Plan(No.YC202401QX0824)Clinical Scientific Research Fund of Beijing Integrated Medical Association[No.ZHKY-2025-1869(B012)]。
文摘With the advancement of surgical techniques and enhanced management of early gastric cancer(EGC),minimally invasive function-preserving surgical approaches have emerged as a common goal for patients and clinicians.Laparoscopic-endoscopic cooperative surgery combined with sentinel lymph node navigation surgery(LECSSNNS)has drawn increasing interest because of its dual benefits of minimal invasiveness and organ function preservation.However,robust evidence-based support for guiding clinical implementation remains limited.To address this gap,we systematically evaluated available studies on the clinical application of LECS-SNNS in EGC and integrated expert insights to formulate 20 recommendations.These included preoperative assessment,surgical techniques,intraoperative endoscopic procedures,pathological evaluation,postoperative care,and follow-up.This consensus aimed to provide comprehensive guidance for the standardized application of LECS-SNNS,thereby advancing precise,minimally invasive,and function-preserving treatment for EGC.
文摘Objective:Open retroperitoneal lymph node dissection(RPLND)is the gold-standard surgical approach for the management of metastatic testicular cancer,but robotic RPLND is becoming increasingly popular.There is limited research directly comparing open and robotic RPLND.The objective of this systematic review is to identify all the literature with direct comparisons between the open and robotic techniques for RPLND and to compare the two techniques.The primary outcome was peri-operative outcomes,and the secondary outcomes included oncological outcomes and patient demographics.Methods:This systematic review was prospectively registered and was conducted in accordance with the PRISMA statement.The PubMed,Embase and MEDLINE databases were searched for relevant publication from January 2006 to August 2024.Results:Eight studies,totaling 3995 patients,are included in this systematic review,with 3521 patients who underwent open RPLND and 474 who underwent robotic RPLND.For open RPLND,the mean operative duration,blood loss and length of stay were 267.8 min,475 mL and 7.3 d,respectively.For robotic RPLND,the mean operative duration,blood loss and length of stay were 334.5 min,94.6 mL and 3.7 d,respectively.Teratoma was the most common RPLND specimen pathology from both open and robotic surgeries.For open RPLND,the specimens have 13–23 nodes(26–32 mm),whereas the robotic RPLND specimens have 13–28 nodes(18–20 mm).Conclusion:This systematic review suggests that the benefitsof robotic RPLND may be associated with reduced blood loss,shorter hospitalisation and an overall lower risk of minor and major complications while maintaining oncological safety.
基金sponsored by the National Natural Science Foundation of China(No.52075467)Hebei Province Fund Outstanding Youth Fund Project,China(No.E2024203107)。
文摘Modular truss space deployable antennas are key for future large aperture,high precision antennas,already proven in various in-orbit applications globally.This paper introduces a design method for a tetrahedral basic unit mechanism with dual height positioning nodes.A parametric model is established,and its DOF are analyzed to confirm the mechanism's validity.The new tetrahedral basic unit mechanism constructed by this method is a single DOF mechanism and can locate different parabolic node heights.In order to further adapt to the parabolic and large aperture requirements of the deployable antenna of the truss,a combination unit and modular unit mechanism are developed based on this tetrahedral unit.The DOF and deployment characteristics of the modular unit mechanism are analyzed and validated through simulations.Various networking methods for the modular units are proposed,followed by a comprehensive performance comparison of different modular truss deployable antenna mechanisms.A prototype model of the modular unit mechanism is also developed,with deployment experiments demonstrating the mechanism's simplicity,low DOF,and large deployment ratio.The findings of this study provide a theoretical and technical basis for the future design and development of truss deployable antenna mechanisms.
基金supported in part by the National Natural Science Foundation of China(Key Program)under Grant No.62031021。
文摘Cascading failures pose a serious threat to the survivability of underwater unmanned swarm networks(UUSNs),significantly limiting their service ability in collaborative missions such as military reconnaissance and environmental monitoring.Existing failure models primarily focus on power grids and traffic systems,and don't address the unique challenges of weak-communication UUSNs.In UUSNs,cascading failure present a complex and dynamic process driven by the coupling of unstable acoustic channels,passive node drift,adversarial attacks,and network heterogeneity.To address these challenges,a directed weighted graph model of UUSNs is first developed,in which node positions are updated according to ocean-current-driven drift and link weights reflect the probability of successful acoustic transmission.Building on this UUSNs graph model,a cascading failure model is proposed that integrates a normal-failure-recovery state-cycle mechanism,multiple attack strategies,and routingbased load redistribution.Finally,under a five-level connectivity UUSNs scheme,simulations are conducted to analyze how dynamic topology,network load,node recovery delay,and attack modes jointly affect network survivability.The main findings are:(1)moderate node drift can improve survivability by activating weak links;(2)based-energy routing(BER)outperform based-depth routing(BDR)in harsh conditions;(3)node self-recovery time is critical to network survivability;(4)traditional degree-based critical node metrics are inadequate for weak-communication UUSNs.These results provide a theoretical foundation for designing robust survivability mechanisms in weak-communication UUSNs.
