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A Positivity-Preserving Fourier Spectral Moving Mesh Method for the Keller-Segel Chemotaxis Model 认领 引用
1
作者 Yutong Kuang Zhiwen Zhang 《Communications in Mathematical Research》 CSCD 2026年第1期57-81,共25页
We develop a numerical method for the Keller-Segel chemotaxis system that is designed to(i)preserve the model’s fundamental structural properties(positivity/bound preservation,mass conservation,and energy dissipation... We develop a numerical method for the Keller-Segel chemotaxis system that is designed to(i)preserve the model’s fundamental structural properties(positivity/bound preservation,mass conservation,and energy dissipation),(ii)efficiently and accurately resolve the near-singular dynamics associated with spike formation and finite-time blow-up.Our approach combines a linear,positivity-preserving scalar auxiliary variable(SAV)scheme(following the framework in[15])with a Fourier spectral spatial discretization and an moving-mesh PDE-based method.The SAV reformulation provides a convenient platform for stable,linear time stepping while maintaining energy dissipation;the Fourier spectral discretization delivers high accuracy in smooth regions;and the moving-mesh PDE mesh redistribution concentrates collocation points in regions of large gradients so that sharp,localized structures can be resolved without prohibitive cost.We show that the proposed moving mesh SAV scheme inherits positivity preservation,mass conservation,and discrete energy dissipation provided the mesh motion avoids element overlap.Two-dimensional tests demonstrate the method’s ability to capture fine spike profiles and estimate blow-up times with substantially reduced computational effort;the formulation extends straightforwardly to three spatial dimensions.Numerical results show that the proposed method is a practical and effective method for accurate simulation of chemotactic aggregation. 展开更多
关键词 Keller-Segel chemotaxis model moving mesh PDE scalar auxiliary variable positivity preserving finite-time blowup
Development and validation of a multiparametric magnetic resonance imaging-based nomogram for predicting feasibility of sphincter-preserving surgery in mid-low rectal cancer 认领 引用
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作者 Juan Wang Tianjing Chang +18 位作者 Lili Tang Qingyang Li Zhaoya Gao Qingkun Gao HaopengHong Zhibo Hou Wanlan Li Yaping Li Ye Han Wenyu Wu Hongwei Wang Wenhan Feng Manli Na Jianjie Wang Mingchuan Yu Bin Zhang Ming Li Yingshi Sun Jin Gu 《Chinese Journal of Cancer Research》 SCIE CAS CSCD 2026年第2期268-284,共17页
Objective:Although distance from the inferior tumor edge to the anal verge(DTAV)is a key predictor for sphincter-preserving surgery(SPS)in mid-low rectal cancer,its utility is limited in the"decision-gray zone&qu... Objective:Although distance from the inferior tumor edge to the anal verge(DTAV)is a key predictor for sphincter-preserving surgery(SPS)in mid-low rectal cancer,its utility is limited in the"decision-gray zone"(DTAV,3-8 cm).Therefore,this study aimed to develop and validate a multiparametric magnetic resonance imaging-based nomogram for individualized preoperative prediction of SPS feasibility.Methods:This dual-center retrospective study included 335 patients with rectal adenocarcinoma(DTAV 3-8 cm).Patients were divided into training(n=263)and external validation(n=72)cohorts,and predictors were identified using multivariate logistic regression analysis.Model discrimination was assessed using area under the receiver operating curve(AUC)and calibration via the Hosmer-Lemeshow test.Subgroup analyses were performed across DTAV strata.Results:Four independent predictors were identified:larger DTAV[odds ratio(OR)=5.00,P<0.001)],larger pubococcygeal overlap distance(PCOD)(OR=1.08,P=0.001),transverse diameter of mesorectal fat(TMS)(OR=1.07,P=0.017),and subcutaneous adipose tissue thickness(SAT)(OR=0.94,P=0.016).The Sphincter Preservation Assessment in Rectal Cancer(SPARC)nomogram achieved an AUC of 0.928[95%confidence interval(95%CI):0.8900.956]in the training cohort,outperforming DTAV alone(AUC=0.884,P=0.031)and maintaining an AUC of 0.916(95%CI:0.827-0.969)in external validation.Subgroup analysis showed notably improved predictions in the 5-8 cm DTAV subgroup.Decision curve analysis demonstrated a pronounced net clinical benefit across a wide range of threshold probabilities.Interobserver agreement was excellent(intraclass correlation coefficient,0.8900.997).Conclusions:The SPARC nomogram reliably predicted SPS feasibility by integrating tumor location with pelvic anatomy and fat distribution.This provides valuable and evidence-based preoperative guidance,especially within the DTAV 3-8 cm gray zone. 展开更多
关键词 Magnetic resonance imaging nomogram rectal cancer pelvimetry sphincter preservation
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Preserving the Past, Shaping the Future:Understanding how China preserves its heritage while embracing modernisation 认领 引用
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作者 RAKOTOARIVONY MAMISOA 《ChinAfrica》 2026年第4期58-59,共2页
There is no better way to appreciate the unique character of Chinese modernisation than by spending 10 years fully immersed in the country.I arrived in China from Madagascar in 2016 as a student and have lived and wor... There is no better way to appreciate the unique character of Chinese modernisation than by spending 10 years fully immersed in the country.I arrived in China from Madagascar in 2016 as a student and have lived and worked here ever since.This experience has given me a profound firsthand insight into the country. 展开更多
关键词 modernisation firsthand insight china preserving heritage
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Privacy-Preserving Personnel Detection in Substations via Federated Learning with Dynamic Noise Adaptation 认领 引用
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作者 Yuewei Tian Yang Su +4 位作者 Yujia Wang Lisa Guo Xuyang Wu Lei Cao Fang Ren 《Computers, Materials & Continua》 SCIE EI 2026年第3期894-915,共22页
This study addresses the risk of privacy leakage during the transmission and sharing of multimodal data in smart grid substations by proposing a three-tier privacy-preserving architecture based on asynchronous federat... This study addresses the risk of privacy leakage during the transmission and sharing of multimodal data in smart grid substations by proposing a three-tier privacy-preserving architecture based on asynchronous federated learning.The framework integrates blockchain technology,the InterPlanetary File System(IPFS)for distributed storage,and a dynamic differential privacy mechanism to achieve collaborative security across the storage,service,and federated coordination layers.It accommodates both multimodal data classification and object detection tasks,enabling the identification and localization of key targets and abnormal behaviors in substation scenarios while ensuring privacy protection.This effectively mitigates the single-point failures and model leakage issues inherent in centralized architectures.A dynamically adjustable differential privacy mechanism is introduced to allocate privacy budgets according to client contribution levels and upload frequencies,achieving a personalized balance between model performance and privacy protection.Multi-dimensional experimental evaluations,including classification accuracy,F1-score,encryption latency,and aggregation latency,verify the security and efficiency of the proposed architecture.The improved CNN model achieves 72.34%accuracy and an F1-score of 0.72 in object detection and classification tasks on infrared surveillance imagery,effectively identifying typical risk events such as not wearing safety helmets and unauthorized intrusion,while maintaining an aggregation latency of only 1.58 s and a query latency of 80.79 ms.Compared with traditional static differential privacy and centralized approaches,the proposed method demonstrates significant advantages in accuracy,latency,and security,providing a new technical paradigm for efficient,secure data sharing,object detection,and privacy preservation in smart grid substations. 展开更多
关键词 Substation privacy preservation asynchronous federated learning CNN differential privacy
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Privacy-Preserving Transformer Inference with Optimized Homomorphic Encryption and Secure Collaborative Computing 认领 引用
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作者 Tao Bai Yang Tang +2 位作者 Kuan Shao Zhenyong Zhang Yuanteng Liu 《Computers, Materials & Continua》 SCIE EI 2026年第7期1242-1265,共24页
In recent years,the rapid development of artificial intelligence has greatly promoted the application of Machine Learning as a Service(MLaaS).Users can upload their requirements through front-end applications,and the ... In recent years,the rapid development of artificial intelligence has greatly promoted the application of Machine Learning as a Service(MLaaS).Users can upload their requirements through front-end applications,and the server provides model inference services after receiving the user input.However,MLaaS may lead to serious privacy breaches.Large language model services are typical representatives of MLaaS,and the Transformer is a typical structure in large language models.Therefore,this paper proposes a privacy-protected Transformer inference scheme based on the CKKS fully homomorphic encryption scheme to optimize computational and communication efficiency.Firstly,this paper implements efficient matrix multiplication based on ring multiplication and optimizes the matrix partition parameters to adapt to different types(including ciphertext-plaintext and ciphertext-ciphertext)and different matrix dimensions.Secondly,this paper optimizes and designs secure Softmax,LayerNorm,and Gelu protocols based on parameter fuzzing and collaborative computing to perform efficient,secure atomic computations over ciphertexts.Finally,experiments on text classification were conducted on the IMDB and AGNEWS datasets.The results show that,under our experimental settings(including an AMD Ryzen 75700G CPU with 32 GB RAM and 8-thread parallel computing using the Lattigo library),the scheme proposed in this paper completes the inference process within 3 s,with communication costs below 1 GB,and the computing accuracy is comparable to that of plaintext computing. 展开更多
关键词 Machine learning as a service privacy preservation Transformer collaborative computing
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A Privacy-Preserving Aggregation Mechanism with Multi-Key Support and Short Ciphertexts for Federated Learning 认领 引用
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作者 Hongzhen Liu Liang Xie +3 位作者 Zhiqiang Ru Yuan Wan Zhe Zhang Xi Fang 《Computers, Materials & Continua》 SCIE EI 2026年第9期710-755,共46页
Federated learning is a privacy-preserving machine learning framework that facilitates model training directly on decentralized data that,due to privacy concerns or transmission costs,cannot be centralized on a server... Federated learning is a privacy-preserving machine learning framework that facilitates model training directly on decentralized data that,due to privacy concerns or transmission costs,cannot be centralized on a server for traditional model training.To prevent adversaries from reconstructing the original data via parameters transmitted during the process,homomorphic encryption is a commonly adopted method.However,it introduces significant communication and computation costs and risks total security failure if any secret key is compromised.This paper proposes a privacy-preserving aggregation mechanism that enables each client to independently generate partial keys for encryption while allowing decryption after homomorphic operations using an aggregated key.Key aggregation for the proposed algorithm is realized through secret sharing.Incorporating these components into a standard federated learning framework yields a novel method that enhances communication efficiency and offers robustness against privacy breaches from internal collusion.The algorithm’s resistance to linear and differential attacks is formally demonstrated by algebraically modeling the encryption procedure.Based on this analysis,the overall security of the method is likewise established.Experiments on the privacy-preserving aggregation mechanism demonstrate that the generated ciphertext exhibits favorable statistical properties and sensitivity.Simulation results of the federated learning method further indicate that,compared to existing encryption schemes,our proposed encryption method reduces communication cost by 77%∼93%with acceptable computational cost,thereby enabling lightweight encryption in federated learning. 展开更多
关键词 Federated learning homomorphic encryption lightweight encryption secret sharing communication efficiency privacy preservation
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RP-IoMT:A Robust and Provable Framework for Federated Learning Privacy-Preserving Intelligence in Healthcare IoMT 认领 引用
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作者 M.Saad Bin Ilyas Sohail Masood Bhatti +2 位作者 Ghazanfar Latif Sherif Abdelhamid Arfan Jaffar 《Computer Modeling in Engineering & Sciences》 SCIE EI 2026年第6期1452-1487,共36页
Federated learning(FL)has emerged as a promising approach for enabling collaborative model training across distributed Internet of Medical Things(IoMT)devices without sharing sensitive data.Existing FL frameworks face... Federated learning(FL)has emerged as a promising approach for enabling collaborative model training across distributed Internet of Medical Things(IoMT)devices without sharing sensitive data.Existing FL frameworks face significant challenges in healthcare settings,including vulnerability to adversarial attacks,lack of verifiable update integrity,and limited robustness under heterogeneous data distributions.These limitations hinder reliable deployment in critical medical applications.To address these challenges,this paper proposes RP-IoMT,a robust and privacypreserving FL framework that integrates secure multi-party computation(MPC),zero-knowledge proof-based gradient verification,and robust aggregation mechanisms.The objective of this work is to ensure both the correctness and integrity of model updates while maintaining strong privacy guarantees in adversarial IoMT environments.RP-IoMT enforces bounded client updates using a zero-knowledge clipping protocol(ZKClip),performs secure aggregation using threshold-based MPC,and incorporates robust filtering techniques to mitigate poisoning and backdoor attacks.Experimental results on healthcare datasets demonstrate that RP-IoMT achieves improved predictive performance,reduced attack success rates,and stable convergence under both independent and identically distributed(IID)and nonIID conditions.These results indicate that the proposed framework provides a practical and reliable solution for secure and robust FL in real-world medical Internet of Things(IoT)systems. 展开更多
关键词 Federated learning Internet of Medical Things(IoMT) secure aggregation multiparty computation(MPC) zero-knowledge proofs privacy preservation
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MMF-CycleGAN:A Multi-Scale Generative Framework for Robust and Identity-Preserving Face Frontalization 认领 引用
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作者 Swetha K Shiloah Elizabeth Darmanayagam Sunil Retmin Raj Cyril 《Computer Modeling in Engineering & Sciences》 SCIE EI 2026年第3期934-966,共33页
Recognizing frontal faces from non-frontal or profile images is a major problem due to pose changes,self-occlusions,and the complete loss of important structural and textural components,depressing recognition accuracy... Recognizing frontal faces from non-frontal or profile images is a major problem due to pose changes,self-occlusions,and the complete loss of important structural and textural components,depressing recognition accuracy and visual fidelity.This paper introduces a new deep generative framework,Modified Multi-Scale Fused CycleGAN(MMF-CycleGAN),for robust and photo-realistic profile-to-frontal face synthesis.The MMF-CycleGAN framework utilizes pre-processing and then the generator employs a Deep Dilated DenseNet encoder-based hierarchical feature extraction along with a transformer and decoder.The proposed Multi-Scale Fusion PatchGAN discriminator enforces consistency at multiple spatial resolutions,leading to sharper textures and improved global facial geometry.Also,GAN training stability and identity preservation are improved through the Ranger optimizer,which effectively balances adversarial,identity,and cycle-consistency losses.Experiments on three benchmark datasets show that MMFCycleGAN achieves accuracy of 0.9541,0.9455,and 0.9422,F1-scores of 0.9654,0.9641,and 0.9614,and AUC values of 0.9742,0.9714,and 0.9698,respectively,and the extreme-pose accuracy(yaw>60°)reaches 0.92.Despite its enhanced architecture,the framework maintains an efficient inference time of 0.042 s per image,making it suitable for real-time biometric authentication,surveillance,and security applications in unconstrained environments. 展开更多
关键词 Face image frontalization CycleGAN DenseNet feature fusion PatchGAN discriminator optimization and identity preservation
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Sutured rectal lift for obstructed defecation:Mesh-free sphincterpreserving transanal technique for Oxford gradeⅡ-Ⅲprolapse 认领 引用
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作者 Claudio Eduardo Pagano Sonia Sarnari +4 位作者 Umberto Favetta Roberto Picheo Fabrizio Gambarini Angelo Guttadauro Michele Schiano di Visconte 《World Journal of Gastrointestinal Surgery》 SCIE 2026年第3期305-314,共10页
BACKGROUND Obstructed defecation syndrome(ODS)frequently results from an internal rectal prolapse,which disrupts the rectal axis and impairs evacuation.Resectional transanal operations can remove redundant tissue,but ... BACKGROUND Obstructed defecation syndrome(ODS)frequently results from an internal rectal prolapse,which disrupts the rectal axis and impairs evacuation.Resectional transanal operations can remove redundant tissue,but fail to restore structural support,whereas abdominal mesh rectopexy involves prosthetic materials and has a higher operative burden.The sutured rectal lift(SuReL)was developed as a reconstructive,non-resective,and mesh-free transanal technique to restore rectal suspension while preserving continence in patients with ODS secondary to internal prolapse.AIM To describe the rationale,indications,and step-by-step operative technique of SuReL for Oxford gradeⅡ-Ⅲinternal rectal prolapse causing obstructed defecation.METHODS SuReL was performed using the Sylarum®transanal access device.The rectal wall was addressed sequentially in six circumferential sectors(11,1,9,3,7,and 5 o’clock).In each sector,a triphasic suture sequence with a barbed 0/0 monofilament(Filbloc®)was placed:(1)A mucosa-submucosa pass;(2)A deeper pass including the muscularis layer at the same level;and(3)A third pass 3 mm caudally,forming a semiloop for suspension.Cranial plications advanced distally to the upper limit of the prolapse.A deep circumferential reinforcement layer with a 2/0 Assuplus®monofilament consolidated the lift.RESULTS The procedure standardizes the reconstructive phase through sector-based rotation,allowing symmetric traction and full-thickness suspension without resection.Operative pearls consist of maintaining uniform exposure,ensuring precise semiloop depth for tension control,and verifying lumen patency with saline irrigation.Key technical advantages include the absence of stapling devices or prosthetic materials,minimal bleeding,a short operative time,and preservation of mucosal sensitivity.Postoperative recovery is typically rapid with early mobilization and minimal discomfort.CONCLUSION SuReL represents a technically reproducible and standardized approach for the treatment of internal rectal prolapse.This preclinical study demonstrated feasibility and mechanical consistency using anatomical simulators,while the clinical efficacy and physiological benefits remain to be validated in prospective trials. 展开更多
关键词 Obstructed defecation syndrome Internal rectal prolapse Transanal surgery Sphincter preservation Rectal suspension Surgical standardization
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Comparison of the effects of preserving skin bridge incision radical surgery and catheter drainage incision radical surgery in improving inflammatory factors in patients with perianal abscess 认领 引用
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作者 ZHANG Huizhen 《外文科技期刊数据库（文摘版）医药卫生》 2026年第2期094-098,共5页
Objective To compare the clinical efficacy of skin bridge preservation incision radical surgery and catheter drainage incision radical surgery in the treatment of perianal abscess patients, and their effects on the le... Objective To compare the clinical efficacy of skin bridge preservation incision radical surgery and catheter drainage incision radical surgery in the treatment of perianal abscess patients, and their effects on the levels of inflammatory factors (C-reactive protein, interleukin-6), in order to provide a basis for optimizing clinical treatment plans. Method: A total of 58 patients with perianal abscess admitted between January 2022 and December 2024 were randomly divided into two groups: Group A (30 cases) underwent skin bridge preservation incision radical surgery and Group B (30 cases) underwent catheter drainage incision radical surgery. Measure the levels of inflammatory factors (C-reactive protein, interleukin-6) in two groups of patients before and one week after surgery, and record the incidence of complications and clinical efficacy. The results showed that the group undergoing skin bridge incision radical surgery had a better reduction in inflammatory factor levels and incidence of postoperative complications compared to the group undergoing catheter drainage incision radical surgery (P<0.05). Conclusion: Retaining skin bridge incision radical surgery has significant advantages in improving the levels of inflammatory factors and reducing postoperative complications in patients with perianal abscess. Although the clinical efficacy of the two surgical methods is similar, retaining skin bridge incision radical surgery shows better results in postoperative recovery and inflammation control, and is worthy of promotion and application in clinical practice. 展开更多
关键词 perianal abscess Preservation of skin bridge incision radical surgery Placement of drainage tube incision and radical surgery Inflammatory factors clinical efficacy
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Single-incision plus one-port laparoscopic duodenum-preserving total pancreatic head resection with pancreaticogastrostomy using the near-infrared fluorescence imaging(with video) 认领 引用
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作者 Dong-Hui Cheng Peng Li +4 位作者 Chong Yang Xin-Yu You Ji-Peng Jiang Bang-You Zuo Yu Zhang 《Hepatobiliary & Pancreatic Diseases International》 SCIE CAS CSCD 2025年第4期448-451,共4页
A pancreas surgeon’s constant goal is to do"less damage,more radical".Currently,a small number of highly trained surgeons opt for single-incision laparoscopic pancreaticoduodenectomy(SILPD)or single-incisio... A pancreas surgeon’s constant goal is to do"less damage,more radical".Currently,a small number of highly trained surgeons opt for single-incision laparoscopic pancreaticoduodenectomy(SILPD)or single-incision plus one-port LPD(SILPD+1)to minimize post-operative pain,improve convalescence,and provide a more pleas-ing cosmetic outcome[1,2].Additionally,some skilled surgeons have claimed that laparoscopic duodenum-preserving complete pancreatic head resections(LDPPHR)result in less trauma and en-hanced quality of life[3,4].However,LDPPHR is still challenging because of its lengthy learning curve and"sword-fighting"impact.Additionally,there has not been any global reporting on the suit-ability of single-incision plus one-port DPPHR with pancreaticogas-trostomy(SILDPPHR-T+1)in place of SILPD+1.This study aimed to illustrate the SILDPPHR-T+1 procedure specifics for a patient with pancreatic head intraductal papillary mucinous neoplasm(IPMN)(main pancreatic duct type)(MD-IPMN). 展开更多
关键词 main pancreatic duct type near infrared fluorescence imaging laparoscopic pancreaticoduodenectomy silpd duodenum preserving total pancreatic head resection intraductal papillary mucinous neoplasm pancreas surgeon s pancreaticogastrostomy single incision laparoscopic surgery
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Design and Application of a New Distributed Dynamic Spatio-Temporal Privacy Preserving Mechanisms 认领 引用
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作者 Jiacheng Xiong Xingshu Chen +1 位作者 Xiao Lan Liangguo Chen 《Computers, Materials & Continua》 SCIE EI 2025年第8期2273-2303,共31页
In the era of big data,the growing number of real-time data streams often contains a lot of sensitive privacy information.Releasing or sharing this data directly without processing will lead to serious privacy informa... In the era of big data,the growing number of real-time data streams often contains a lot of sensitive privacy information.Releasing or sharing this data directly without processing will lead to serious privacy information leakage.This poses a great challenge to conventional privacy protection mechanisms(CPPM).The existing data partitioning methods ignore the number of data replications and information exchanges,resulting in complex distance calculations and inefficient indexing for high-dimensional data.Therefore,CPPM often fails to meet the stringent requirements of efficiency and reliability,especially in dynamic spatiotemporal environments.Addressing this concern,we proposed the Principal Component Enhanced Vantage-point tree(PEV-Tree),which is an enhanced data structure based on the idea of dimension reduction,and constructed a Distributed Spatio-Temporal Privacy Preservation Mechanism(DST-PPM)on it.In this work,principal component analysis and the vantage tree are used to establish the PEV-Tree.In addition,we designed three distributed anonymization algorithms for data streams.These algorithms are named CK-AA,CL-DA,and CT-CA,fulfill the anonymization rules of K-Anonymity,L-Diversity,and T-Closeness,respectively,which have different computational complexities and reliabilities.The higher the complexity,the lower the risk of privacy leakage.DST-PPM can reduce the dimension of high-dimensional information while preserving data characteristics and dividing the data space into vantage points based on distance.It effectively enhances the data processing workflow and increases algorithmefficiency.To verify the validity of the method in this paper,we conducted empirical tests of CK-AA,CL-DA,and CT-CA on conventional datasets and the PEV-Tree,respectively.Based on the big data background of the Internet of Vehicles,we conducted experiments using artificial simulated on-board network data.The results demonstrated that the operational efficiency of the CK-AA,CL-DA,and CT-CA is enhanced by 15.12%,24.55%,and 52.74%,respectively,when deployed on the PEV-Tree.Simultaneously,during homogeneity attacks,the probabilities of information leakage were reduced by 2.31%,1.76%,and 0.19%,respectively.Furthermore,these algorithms showcased superior utility(scalability)when executed across PEV-Trees of varying scales in comparison to their performance on conventional data structures.It indicates that DST-PPM offers marked advantages over CPPM in terms of efficiency,reliability,and scalability. 展开更多
关键词 Privacy preserving distributed anonymization algorithm VP-Tree data stream internet of vehicles
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HEaaN-ID3: Fully Homomorphic Privacy-Preserving ID3-Decision Trees Using CKKS 认领 引用
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作者 Dain Lee Hojune Shin +1 位作者 Jihyeon Choi Younho Lee 《Computers, Materials & Continua》 SCIE EI 2025年第8期3673-3705,共33页
In this study,we investigated privacy-preserving ID3 Decision Tree(PPID3)training and inference based on fully homomorphic encryption(FHE),which has not been actively explored due to the high computational cost associ... In this study,we investigated privacy-preserving ID3 Decision Tree(PPID3)training and inference based on fully homomorphic encryption(FHE),which has not been actively explored due to the high computational cost associated with managing numerous child nodes in an ID3 tree.We propose HEaaN-ID3,a novel approach to realize PPID3 using the Cheon-Kim-Kim-Song(CKKS)scheme.HEaaN-ID3 is the first FHE-based ID3 framework that completes both training and inference without any intermediate decryption,which is especially valuable when decryption keys are inaccessible or a single-cloud security domain is assumed.To enhance computational efficiency,we adopt a modified Gini impurity(MGI)score instead of entropy to evaluate information gain,thereby avoiding costly inverse operations.In addition,we fully leverage the Single Instruction Multiple Data(SIMD)property of CKKS to parallelize computations at multiple tree nodes.Unlike previous approaches that require decryption at each node or rely on two-party secure computation,our method enables a fully non-interactive training and inference pipeline in the encrypted domain.We validated the proposed scheme using UCI datasets with both numerical and nominal features,demonstrating inference accuracy comparable to plaintext implementations in Scikit-Learn.Moreover,experiments show that HEaaN-ID3 significantly reduces training and inference time per node relative to earlier FHE-based approaches. 展开更多
关键词 Homomorphic encryption privacy preserving machine learning applied cryptography information security
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Current status of function-preserving surgery for gastric cancer 认领 引用 被引量：20
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作者 Takuro Saito Yukinori Kurokawa +2 位作者 Shuji Takiguchi Masaki Mori Yuichiro Doki 《World Journal of Gastroenterology》 SCIE CAS 2014年第46期17297-17304,共8页
Recent advances in diagnostic techniques have allowed the diagnosis of gastric cancer(GC)at an early stage.Due to the low incidence of lymph node metastasis and favorable prognosis in early GC,function-preserving surg... Recent advances in diagnostic techniques have allowed the diagnosis of gastric cancer(GC)at an early stage.Due to the low incidence of lymph node metastasis and favorable prognosis in early GC,function-preserving surgery which improves postoperative quality of life may be possible.Pylorus-preserving gastrectomy(PPG)is one such function-preserving procedure,which is expected to offer advantages with regards to dumping syndrome,bile reflux gastritis,and the frequency of flatus,although PPG may induce delayed gastric emptying.Proximal gastrectomy(PG)is another functionpreserving procedure,which is thought to be advantageous in terms of decreased duodenogastric reflux and good food reservoir function in the remnant stomach,although the incidence of heartburn or gastric fullness associated with this procedure is high.However,these disadvantages may be overcome by the reconstruction method used.The other important problem after PG is remnant GC,which was reported to occur in approximately 5%of patients.Therefore,the reconstruction technique used with PG should facilitate postoperativeendoscopic examinations for early detection and treatment of remnant gastric carcinoma.Oncologic safety seems to be assured in both procedures,if the preoperative diagnosis is accurate.Patient selection should be carefully considered.Although many retrospective studies have demonstrated the utility of function-preserving surgery,no consensus on whether to adopt functionpreserving surgery as the standard of care has been reached.Further prospective randomized controlled trials are necessary to evaluate survival and postoperative quality of life associated with function-preserving surgery. 展开更多
关键词 Gastric cancer Function preserving surgery Quality of life Pylorus preserving surgery Proximal gastrectomy
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Meta-analysis of subtotal stomach-preserving pancreaticoduodenectomy vs pylorus preserving pancreaticoduodenectomy 认领 引用 被引量：10
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作者 Wei Huang Jun-Jie Xiong +7 位作者 Mei-Hua Wan Peter Szatmary Shameena Bharucha Ilias Gomatos Quentin M Nunes Qing Xia Robert Sutton Xu-Bao Liu 《World Journal of Gastroenterology》 SCIE CAS 2015年第20期6361-6373,共13页
AIM: To investigate the differences in outcome following pylorus preserving pancreaticoduodenectomy(PPPD) and subtotal stomach-preserving pancreaticoduodenectomy(SSPPD).METHODS: Major databases including Pub Med(Medli... AIM: To investigate the differences in outcome following pylorus preserving pancreaticoduodenectomy(PPPD) and subtotal stomach-preserving pancreaticoduodenectomy(SSPPD).METHODS: Major databases including Pub Med(Medline), EMBASE and Science Citation Index Expanded and the Cochrane Central Register of Controlled Trials(CENTRAL) in The Cochrane Library were searched for comparative studies between patients with PPPD and SSPPD published between January 1978 and July 2014. Studies were selected based on specific inclusion and exclusion criteria. The primary outcome was delayed gastric emptying(DGE). Secondary outcomes included operation time, intraoperative blood loss, pancreatic fistula, postoperative hemorrhage, intraabdominal abscess, wound infection, time to starting liquid diet, time to starting solid diet, period of nasogastric intubation, reinsertion of nasogastric tube, mortality and hospital stay. The pooled odds ratios(OR) or weighted mean difference(WMD) with 95% confidence intervals(95%CI) were calculated using either a fixed-effects or random-effects model. RESULTS: Eight comparative studies recruiting 650 patients were analyzed, which include two RCTs, one non-randomized prospective and 5 retrospective trial designs. Patients undergoing SSPPD experienced significantly lower rates of DGE(OR = 2.75; 95%CI: 1.75-4.30, P < 0.00001) and a shorter period of nasogastric intubation(OR = 2.68; 95%CI: 0.77-4.58,P < 0.00001), with a tendency towards shorter time to liquid(WMD = 2.97, 95%CI:-0.46-7.83; P = 0.09) and solid diets(WMD = 3.69, 95%CI:-0.46-7.83; P = 0.08) as well as shorter inpatient stay(WMD = 3.92, 95%CI:-0.37-8.22; P = 0.07), although these latter three did not reach statistical significance. PPPD, however, was associated with less intraoperative blood loss than SSPPD [WMD =-217.70, 95%CI:-429.77-(-5.63); P = 0.04]. There were no differences in other parameters between the two approaches, including operative time(WMD =-5.30, 95%CI:-43.44-32.84; P = 0.79), pancreatic fistula(OR = 0.91; 95%CI: 0.56-1.49; P = 0.70), postoperative hemorrhage(OR = 0.51; 95%CI: 0.15-1.74; P = 0.29), intraabdominal abscess(OR = 1.05; 95%CI: 0.54-2.05; P = 0.89), wound infection(OR = 0.88; 95%CI: 0.39-1.97; P = 0.75), reinsertion of nasogastric tube(OR = 1.90; 95%CI: 0.91-3.97; P = 0.09) and mortality(OR = 0.31; 95%CI: 0.05-2.01; P = 0.22).CONCLUSION: SSPPD may improve intraoperative and short-term postoperative outcomes compared to PPPD, especially DGE. However, these findings need to be further ascertained by well-designed randomized controlled trials. 展开更多
关键词 Pancreaticoduodenectomy Pylorus preservingSubtotal stomach preserving pancreaticoduodenectomy Delayed gastric emptying Pancreatic surgery Metaanalysis
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Preserving the Past China’s approach and experience in heritage conservation is worth emulating by other countries 认领 引用
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《ChinAfrica》 2025年第1期33-35,共3页
n recent years,China has placed increasing emphasis on the protection of cultural heritage.In July 2024,Beijing’s Central Axis was o!cially inscribed on the World Heritage List,and on 4 December 2024,the Spring Festi... n recent years,China has placed increasing emphasis on the protection of cultural heritage.In July 2024,Beijing’s Central Axis was o!cially inscribed on the World Heritage List,and on 4 December 2024,the Spring Festival was added to the UNESCO Intangible Cultural Heritage list.Public awareness of the importance of preserving historical sites and promoting the inheritance and celebration of Chinese civilisation has also grown significantly. 展开更多
关键词 UNESCO preserving heritage
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LOCAL STRUCTURE-PRESERVING ALGORITHMS FOR THE KLEIN-GORDON-ZAKHAROV EQUATION 认领 引用 被引量：1
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作者 汪佳玲 周政婷 王雨顺 《Acta Mathematica Scientia》 SCIE CSCD 2023年第3期1211-1238,共28页
In this paper, using the concatenating method, a series of local structure-preserving algorithms are obtained for the Klein-Gordon-Zakharov equation, including four multisymplectic algorithms, four local energy-preser... In this paper, using the concatenating method, a series of local structure-preserving algorithms are obtained for the Klein-Gordon-Zakharov equation, including four multisymplectic algorithms, four local energy-preserving algorithms, four local momentumpreserving algorithms;of these, local energy-preserving and momentum-preserving algorithms have not been studied before. The local structure-preserving algorithms mentioned above are more widely used than the global structure-preserving algorithms, since local preservation algorithms can be preserved in any time and space domains, which overcomes the defect that global preservation algorithms are limited to boundary conditions. In particular, under appropriate boundary conditions, local preservation laws are global preservation laws.Numerical experiments conducted can support the theoretical analysis well. 展开更多
关键词 Klein-Gordon-Zakharov(KGZ)equation local preservation law local momentum-preserving algorithms multi-symplectic algorithms local energy-preserving algorithms
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MMH-FE:AMulti-Precision and Multi-Sourced Heterogeneous Privacy-Preserving Neural Network Training Based on Functional Encryption 认领 引用
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作者 Hao Li Kuan Shao +2 位作者 Xin Wang Mufeng Wang Zhenyong Zhang 《Computers, Materials & Continua》 SCIE EI 2025年第3期5387-5405,共19页
Due to the development of cloud computing and machine learning,users can upload their data to the cloud for machine learning model training.However,dishonest clouds may infer user data,resulting in user data leakage.P... Due to the development of cloud computing and machine learning,users can upload their data to the cloud for machine learning model training.However,dishonest clouds may infer user data,resulting in user data leakage.Previous schemes have achieved secure outsourced computing,but they suffer from low computational accuracy,difficult-to-handle heterogeneous distribution of data from multiple sources,and high computational cost,which result in extremely poor user experience and expensive cloud computing costs.To address the above problems,we propose amulti-precision,multi-sourced,andmulti-key outsourcing neural network training scheme.Firstly,we design a multi-precision functional encryption computation based on Euclidean division.Second,we design the outsourcing model training algorithm based on a multi-precision functional encryption with multi-sourced heterogeneity.Finally,we conduct experiments on three datasets.The results indicate that our framework achieves an accuracy improvement of 6%to 30%.Additionally,it offers a memory space optimization of 1.0×224 times compared to the previous best approach. 展开更多
关键词 Functional encryption multi-sourced heterogeneous data privacy preservation neural networks
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A Deep Learning-Based Salient Feature-Preserving Algorithm for Mesh Simplification 认领 引用
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作者 Jiming Lan Bo Zeng +2 位作者 Suiqun Li Weihan Zhang Xinyi Shi 《Computers, Materials & Continua》 SCIE EI 2025年第5期2865-2888,共24页
The Quadric Error Metrics(QEM)algorithm is a widely used method for mesh simplification;however,it often struggles to preserve high-frequency geometric details,leading to the loss of salient features.To address this l... The Quadric Error Metrics(QEM)algorithm is a widely used method for mesh simplification;however,it often struggles to preserve high-frequency geometric details,leading to the loss of salient features.To address this limitation,we propose the Salient Feature Sampling Points-based QEM(SFSP-QEM)—also referred to as the Deep Learning-Based Salient Feature-Preserving Algorithm for Mesh Simplification—which incorporates a Salient Feature-Preserving Point Sampler(SFSP).This module leverages deep learning techniques to prioritize the preservation of key geometric features during simplification.Experimental results demonstrate that SFSP-QEM significantly outperforms traditional QEM in preserving geometric details.Specifically,for general models from the Stanford 3D Scanning Repository,which represent typical mesh structures used in mesh simplification benchmarks,the Hausdorff distance of simplified models using SFSP-QEM is reduced by an average of 46.58% compared to those simplified using traditional QEM.In customized models such as the Zigong Lantern used in cultural heritage preservation,SFSP-QEM achieves an average reduction of 28.99% in Hausdorff distance.Moreover,the running time of this method is only 6%longer than that of traditional QEM while significantly improving the preservation of geometric details.These results demonstrate that SFSP-QEMis particularly effective for applications requiring high-fidelity simplification while retaining critical features. 展开更多
关键词 Deep learning mesh simplification quadric error metrics(QEM) salient feature preservation point sampling
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Facial color-preserving generative adversarial network-based privacy protection of facial diagnostic images in traditional Chinese medicine 认领 引用
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作者 Jilong SHEN Aihua GUAN +3 位作者 Xinyu WANG Jiadong XIE Youwei DING Kongfa HU 《Digital Chinese Medicine》 CAS CSCD 2025年第4期455-466,共12页
Objective To develop a facial image generation method based on a facial color-preserving generative adversarial network(FCP-GAN)that effectively decouples identity features from diagnostic facial complexion characteri... Objective To develop a facial image generation method based on a facial color-preserving generative adversarial network(FCP-GAN)that effectively decouples identity features from diagnostic facial complexion characteristics in traditional Chinese medicine(TCM)inspection,thereby addressing the critical challenge of privacy preservation in medical image analysis.Methods A facial image dataset was constructed from participants at Nanjing University of Chinese Medicine between April 23 and June 10,2023,using a TCM full-body inspection data acquisition equipment under controlled illumination.The proposed FCP-GAN model was designed to achieve the dual objectives of removing identity features and preserving colors through three key components:(i)a multi-space combination module that comprehensively extracts color attributes from red,green,blue(RGB),hue,saturation,value(HSV),and Lab spaces;(ii)a generator incorporating efficient channel attention(ECA)mechanism to enhance the representation of diagnostically critical color channels;and(iii)a dual-loss function that combines adversarial loss for de-identification with a dedicated color preservation loss.The model was trained and evaluated using a stratified 5-fold cross-validation strategy and evaluated against four baseline generative models:conditional GAN(CGAN),deep convolutional GAN(DCGAN),dual discriminator CGAN(DDCGAN),and medical GAN(MedGAN).Performance was assessed in terms of image quality[peak signal-to-noise ratio(PSNR)and structural similarity(SSIM)],distribution similarity[Fréchet inception distance(FID)],privacy protection(face recognition accuracy),and diagnostic consistency[mean squared error(MSE)and Pearson correlation coefficient(PCC)].Results The final analysis included facial images from 216 participants.Compared with baseline models,FCP-GAN achieved superior performance,with PSNR=31.02 dB and SSIM=0.908,representing an improvement of 1.21 dB and 0.034 in SSIM over the strongest baseline(MedGAN).The FID value(23.45)was also the lowest among all models,indicating superior distributional similarity to real images.The multi-space feature fusion and the ECA mechanism contributed significantly to these performance gains,as evidenced by ablation studies.The stratified 5-fold cross-validation confirmed the model’s robustness,with results reported as mean±standard deviation(SD)across all folds.The model effectively protected privacy by reducing face recognition accuracy from 95.2%(original images)to 60.1%(generated images).Critically,it maintained high diagnostic fidelity,as evidenced by a low MSE(0.98)for key TCM facial features between original and generated images.Conclusion The FCP-GAN model provides an effective technical solution for ensuring privacy in TCM diagnostic imaging,successfully having removed identity features while preserving clinically vital facial color features.This study offers significant value for developing intelligent and secure TCM telemedicine systems. 展开更多
关键词 Traditional Chinese medicine(TCM)inspection Facial complexion information Image generation Privacy preservation Generative adversarial network Color space
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