Thread-embedding materials buried into acupuncture points to produce a long-time stimulation is a method which has been widely applied in the acupuncture and moxibustion therapies for diseases treating and they should...Thread-embedding materials buried into acupuncture points to produce a long-time stimulation is a method which has been widely applied in the acupuncture and moxibustion therapies for diseases treating and they should have excellent properties of good biocompatibility,biodegradability and moderate rigidity.Polyactic acid(PLA) as the thread-embedding material had some shortcomings such as poor hydrophilicity and slowly biodegradable speed.In this paper,PLA thread-embedding material was modified by chitosan coating which could improve rigidity,hydrophilicity and moisture absorption and thus produce better stimulation effect.The variation tendency of diameter,mass,hydrophilicity,and initial modulus of the sample under the change of chitosan coating concentration,coating time and coating times were studied respectively.The results showed that the hydrophilicity,mass,and initial modulus after coating rose in a certain range when the coating time,coating times and coating concentration increased,while the changing of coating had little impact on fiber diameter.展开更多
Objective:To explore the clinical effect of embedding thread combined with Jianpi Qushi Huayu ointment in the treatment of bronchiectasis in remission period,and to observe the effect on the level of inflammatory cyto...Objective:To explore the clinical effect of embedding thread combined with Jianpi Qushi Huayu ointment in the treatment of bronchiectasis in remission period,and to observe the effect on the level of inflammatory cytokines.Methods:150 patients with bronchiectasis in remission period were divided into three groups(50 cases in each group),western medicine group(treated with salmeterol fluticasone and low dose erythromycin),combined group(treated with Jianpi Qushi Huayu plaster),observation group(treated with western medicine+Jianpi Qushi Huayu plaster+embedding thread),and the clinical treatment of the three groups were compared.Result:before and after treatment,the improvement of TCM syndrome score,the improvement of pulmonary ventilation index,the improvement of inflammatory cytokines,and the change of adverse reactions.Results:the treatment efficiency of the observation group and the combination group was significantly higher than that of the western medicine group P The peak level of expiratory flow velocity,the maximum expiratory flow,the forced expiratory volume in one second and the ratio of forced expiratory volume in one second to vital capacity in the observation group and the combined group were significantly better than those in the western medicine group and the pre-treatment level(P<0.05),and the improvement in the observation group was better than that in the combined group After treatment,the expression of IL-13,IL-10 and IL-4 in the combined group was significantly better than that in the western medicine group and before treatment(P<0.05),and the improvement in the observation group was better than that in the combined group;there was no significant difference in the incidence of adverse reactions among the three groups(P>0.05).Conclusion:catgut embedding combined with Jianpi Qushi Huayu ointment can significantly alleviate the related clinical symptoms and signs,effectively control the further aggravation of the disease,improve the lung function of patients,regulate the level of inflammatory cytokines to reduce the degree of inflammatory reaction,and do not significantly aggravate the adverse reactions of drugs.展开更多
With the rapid development of intelligent cyber-physical systems(ICPS),diverse services with varying Quality of Service(QoS)requirements have brought great challenges to traditional network resource allocation.Further...With the rapid development of intelligent cyber-physical systems(ICPS),diverse services with varying Quality of Service(QoS)requirements have brought great challenges to traditional network resource allocation.Furthermore,given the open environment and a multitude of devices,enhancing the security of ICPS is an urgent concern.To address these issues,this paper proposes a novel trusted virtual network embedding(T-VNE)approach for ICPS based combining blockchain and edge computing technologies.Additionally,the proposed algorithm leverages a deep reinforcement learning(DRL)model to optimize decision-making processes.It employs the policygradient-based agent to compute candidate embedding nodes and utilizes a breadth-first search(BFS)algorithm to determine the optimal embedding paths.Finally,through simulation experiments,the efficacy of the proposed method was validated,demonstrating outstanding performance in terms of security,revenue generation,and virtual network request(VNR)acceptance rate.展开更多
In recent years,ransomware attacks have become one of the most common and destructive types of cyberattacks.Their impact is significant on the operations,finances and reputation of affected companies.Despite the effor...In recent years,ransomware attacks have become one of the most common and destructive types of cyberattacks.Their impact is significant on the operations,finances and reputation of affected companies.Despite the efforts of researchers and security experts to protect information systems from these attacks,the threat persists and the proposed solutions are not able to significantly stop the spread of ransomware attacks.The latest remarkable achievements of large language models(LLMs)in NLP tasks have caught the attention of cybersecurity researchers to integrate thesemodels into security threat detection.Thesemodels offer high embedding capabilities,able to extract rich semantic representations and paving theway formore accurate and adaptive solutions.In this context,we propose a new approach for ransomware detection based on an ensemblemethod that leverages three distinctLLMembeddingmodels.This ensemble strategy takes advantage of the variety of embedding methods and the strengths of each model.In the proposed solution,each embedding model is associated with an independently trainedMLP classifier.The predictions obtained are then merged using a weighted voting technique,assigning each model an influence proportional to its performance.This approach makes it possible to exploit the complementarity of representations,improve detection accuracy and robustness,and offer a more reliable solution in the face of the growing diversity and complexity of modern ransomware.展开更多
Spam emails remain one of the most persistent threats to digital communication,necessitating effective detection solutions that safeguard both individuals and organisations.We propose a spam email classification frame...Spam emails remain one of the most persistent threats to digital communication,necessitating effective detection solutions that safeguard both individuals and organisations.We propose a spam email classification frame-work that uses Bidirectional Encoder Representations from Transformers(BERT)for contextual feature extraction and a multiple-window Convolutional Neural Network(CNN)for classification.To identify semantic nuances in email content,BERT embeddings are used,and CNN filters extract discriminative n-gram patterns at various levels of detail,enabling accurate spam identification.The proposed model outperformed Word2Vec-based baselines on a sample of 5728 labelled emails,achieving an accuracy of 98.69%,AUC of 0.9981,F1 Score of 0.9724,and MCC of 0.9639.With a medium kernel size of(6,9)and compact multi-window CNN architectures,it improves performance.Cross-validation illustrates stability and generalization across folds.By balancing high recall with minimal false positives,our method provides a reliable and scalable solution for current spam detection in advanced deep learning.By combining contextual embedding and a neural architecture,this study develops a security analysis method.展开更多
Message structure reconstruction is a critical task in protocol reverse engineering,aiming to recover protocol field structures without access to source code.It enables important applications in network security,inclu...Message structure reconstruction is a critical task in protocol reverse engineering,aiming to recover protocol field structures without access to source code.It enables important applications in network security,including malware analysis and protocol fuzzing.However,existing methods suffer from inaccurate field boundary delineation and lack hierarchical relationship recovery,resulting in imprecise and incomplete reconstructions.In this paper,we propose ProRE,a novel method for reconstructing protocol field structures based on program execution slice embedding.ProRE extracts code slices from protocol parsing at runtime,converts them into embedding vectors using a data flow-sensitive assembly language model,and performs hierarchical clustering to recover complete protocol field structures.Evaluation on two datasets containing 12 protocols shows that ProRE achieves an average F1 score of 0.85 and a cophenetic correlation coefficient of 0.189,improving by 19%and 0.126%respectively over state-of-the-art methods(including BinPRE,Tupni,Netlifter,and QwQ-32B-preview),demonstrating significant superiority in both accuracy and completeness of field structure recovery.Case studies further validate the effectiveness of ProRE in practical malware analysis scenarios.展开更多
Temporal knowledge graph completion(TKGC),which merges temporal information into traditional static knowledge graph completion(SKGC),has garnered increasing attention recently.Among numerous emerging approaches,transl...Temporal knowledge graph completion(TKGC),which merges temporal information into traditional static knowledge graph completion(SKGC),has garnered increasing attention recently.Among numerous emerging approaches,translation-based embedding models constitute a prominent approach in TKGC research.However,existing translation-based methods typically incorporate timestamps into entities or relations,rather than utilizing them independently.This practice fails to fully exploit the rich semantics inherent in temporal information,thereby weakening the expressive capability of models.To address this limitation,we propose embedding timestamps,like entities and relations,in one or more dedicated semantic spaces.After projecting all embeddings into a shared space,we use the relation-timestamp pair instead of the conventional relation embedding as the translation vector between head and tail entities.Our method elevates timestamps to the same representational significance as entities and relations.Based on this strategy,we introduce two novel translation-based embedding models:TE-TransR and TE-TransT.With the independent representation of timestamps,our method not only enhances capabilities in link prediction but also facilitates a relatively underexplored task,namely time prediction.To further bolster the precision and reliability of time prediction,we introduce a granular,time unit-based timestamp setting and a relation-specific evaluation protocol.Extensive experiments demonstrate that our models achieve strong performance on link prediction benchmarks,with TE-TransR outperforming existing baselines in the time prediction task.展开更多
Objective: The comparison of the remote and recent therapeutic effects on perennial allergic rhinitis was carried on among single application of acupoint-thread embedding, western medicine (certirizine+flixonase) and ...Objective: The comparison of the remote and recent therapeutic effects on perennial allergic rhinitis was carried on among single application of acupoint-thread embedding, western medicine (certirizine+flixonase) and allied therapy. Method: Ninety cases were randomized into thread-embedding group, western medicine group and embedding+western medicine group (allied-therapy group), 30 cases in each one. In thread embedding group, Yingxiang (迎香 LI 20) and Feishu (肺俞 BL 13) were selected for thread embedding, once a week, totally 4 treatments were required. In western medicine group, certirizine tablet 10 mg in combination with flixonase sprayer was applied once per day, continuously for 30 days in treatment. In allied-therapy group, both of the above methods were adopted continuously for 30 days in treatment. The therapeutic effects were in statistics at the end of treatment and 1 year later. Results: At the end of treatment, in thread-embedding group, 21 cases were remarkably effective, 3 cases effective and 6 cases no effect. In western medicine group, 20 cases were remarkably effective, 3 cases effective and 7 cases no effect. In allied-therapy group, 23 cases were remarkably effective, 2 cases effective and 5 cases no effect. It was shown in statistics that there was no significant difference in therapeutic effects among three groups ( P>0.05 ). But one year after the end of treatment, it was indicated that in thread-embedding group, 3 cases were remarkably effective, 10 cases effective and 17 cases no effect; in western medicine group, 2 cases were remarkably effective, 9 cases effective and 19 cases no effect; in allied-therapy group, 7 cases were remarkably effective, 11 cases effective and 12 cases no effect. The significant difference in the therapeutic effects had not been presented in the comparison between thread-embedding group and western medicine group (P>0.05), but that had been presented between allied-therapy group with either of the groups with single therapy applied (P<0.05). Conclusion: Quite good recent therapeutic effect of either acupoint-thread embedding or western medicine (certirizine+flixonase) was achieved on perennial allergic rhinitis. The remote therapeutic effect of allied therapy was more advantageous than that of single application of either thread embedding or western medicine.展开更多
Poly( glycolic acid-lactic acid)( PGLA) threadembedding material was modified by chitosan coating which could improve the rigidity,hydrophilicity and moisture absorption of the material,and produced better stimulation...Poly( glycolic acid-lactic acid)( PGLA) threadembedding material was modified by chitosan coating which could improve the rigidity,hydrophilicity and moisture absorption of the material,and produced better stimulation effect. Thus,this kind of thread-embedding materials which can be buried into acupuncture points to produce a long-time stimulation is popular in the acupuncture and moxibustion therapies. The variation tendencies of diameter,weight, hydrophilicity, and flexibility of the samples under the change of chitosan coating concentration,coating time and coating times were studied respectively. The results showed that the hydrophilicity,weight,and rigidity after coating rose in a certain range with the increase of coating time,coating times and coating concentration. The coating time had little influence on the diameter of fiber.展开更多
BACKGROUND A total of 100 patients diagnosed with mixed hemorrhoids from October 2022 to September 2023 in our hospital were randomly divided into groups by dice rolling and compared with the efficacy of different tre...BACKGROUND A total of 100 patients diagnosed with mixed hemorrhoids from October 2022 to September 2023 in our hospital were randomly divided into groups by dice rolling and compared with the efficacy of different treatment options.AIM To analyze the clinical effect and prognosis of mixed hemorrhoids treated with polidocanol injection combined with automatic elastic thread ligation operation(RPH).METHODS A total of 100 patients with mixed hemorrhoids who visited our hospital from October 2022 to September 2023 were selected and randomly divided into the control group(n=50)and the treatment group(n=50)by rolling the dice.The procedure for prolapse and hemorrhoids(PPH)was adopted in the control group,while polidocanol foam injection+RPH was adopted in the treatment group.The therapeutic effects,operation time,wound healing time,hospital stay,pain situation(24 hours post-operative pain score,first defecation pain score),quality of life(QOL),incidence of complications(post-operative hemorrhage,edema,infection),incidence of anal stenosis 3 months post-operatively and recurrence rate 1 year post-operatively of the two groups were compared.RESULTS Compared with the control group,the total effective rate of treatment group was higher,and the difference was significant(P<0.05).The operation time/wound healing time/hospital stay in the treatment group were shorter than those in the control group(P<0.05).The pain scores at 24 hours after operation/first defecation pain score of the treatment group was significantly lower than those in the control group(P<0.05).After surgery,the QOL scores of the two groups decreased,with the treatment group having higher scores than that of the control group(P<0.05).Compared with the control group,the incidence of postoperative complications in the treatment group was lower,and the difference was significant(P<0.05);However,there was no significant difference in the incidence of postoperative bleeding between the two groups(P>0.05);There was no significant difference in the incidence of anal stenosis 3 months after operation and the recurrence rate 1 year after operation between the two groups(P>0.05).CONCLUSION For patients with mixed hemorrhoids,the therapeutic effect achieved by using polidocanol injection combined with RPH was better.The wounds of the patients healed faster,the postoperative pain was milder,QOL improved,and the incidence of complications was lower,and the short-term and long-term prognosis was good.展开更多
Let G be a group.The family of all sets which are closed in every Hausdorf group topology of G form the family of closed sets of a T_(1) topology M_(G) on G called the Markov topology.Similarly,the family of all algeb...Let G be a group.The family of all sets which are closed in every Hausdorf group topology of G form the family of closed sets of a T_(1) topology M_(G) on G called the Markov topology.Similarly,the family of all algebraic subsets of G forms a family of closed sets for another T_(1)topology Z_(G) on G called the Zarski topology.A subgroup H of G is said to be Markov(resp.Zarski)embedded if the equality M_(G|H)=M_(H)(resp.Z_(G|H)=Z_(H))holds.I's proved that an abirary subgroup of a free group is both Zariski and Markov embedded in it.展开更多
BACKGROUND Intraoperative determination of resection margin and adequate residual liver parenchyma are the key points of hepatectomy for the treatment of liver tumors.Intraoperative ultrasound and indocyanine green fl...BACKGROUND Intraoperative determination of resection margin and adequate residual liver parenchyma are the key points of hepatectomy for the treatment of liver tumors.Intraoperative ultrasound and indocyanine green fluorescence navigation are the most commonly used methods at present,but the technical barriers limit their promotion.AIM To evaluate the value of the three-dimensional location approach with silk thread(3D-LAST)in precise resection of liver tumors.METHODS From September 2020 to January 2022,8 patients with liver tumors including hepatocellular carcinoma,intrahepatic cholangiocarcinoma,hilar cholangiocar-cinoma,and gastric cancer liver metastasis were included in this study.All patients underwent 3D-LAST in precise resection of liver tumors.RESULTS All patients(8/8,100%)underwent the operation successfully without any complications.During the mean follow-up of 8.7 months,all patients survived without tumor recurrence.CONCLUSION In conclusion,the 3D-LAST is a safe and effective new method for liver intraop-erative navigation,which is practical and easy to promote.Core Tip:The aim of this study is to evaluate the value of the three-dimensional location approach with silk thread(3D-LAST)in precise resection of liver tumors.Eight patients with liver tumors including hepatocellular carcinoma,intrahepatic cholangiocarcinoma,hilar cholangiocarcinoma,and gastric cancer liver metastasis underwent the operation successfully without any complications.During the mean follow-up of 8.7 months,all patients survived without tumor recurrence.In conclusion,the 3D-LAST is a safe and effective new method for liver intraoperative navigation,which is practical and easy to promote.INTRODUCTION Hepatectomy is widely used for the treatment of liver tumors.In recent decades,the concept and practice of hepatectomy have developed from irregular,regular and anatomical to the current precise resection.Necessary assistive technologies have enabled these advances.Intraoperative ultrasound(IOUS)localization and indocyanine green(ICG)fluorescence imaging guidance are two frequently-used approaches for laparoscopic hepatectomy[1,2].IOUS is an invaluable auxiliary means widely accepted in surgery for real-time diagnostic information to determine resection range and navigate the surgical path[3].However,the major limitation of IOUS is the time cost during the procedure for paging the sono-graphers and the difficulty of deciphering two dimensional images[4].ICG is a non-toxic water-soluble fluorophore that reveals fluorescence under the near-infrared spectrum[5].Since liver tissue penetration is limited to 5 to 10 mm,that restricted the visualization of deeper tumors by ICG excitation,thereby interfering with its application in laparoscopic hepatectomy[6].IOUS and ICG navigation require specific technical equipment,making implementation difficult in many centers.And these techniques will significantly increase the operation time.Three-dimensional(3D)visualization involves extracting features and producing volumetric images based on computed tomography(CT)through a computer postprocessing technique.This tool offers a reasonable approach to the clinical decision for the potential to display the complex internal anatomy in an intuitive and stereoscopic manner[7].In the past few decades,applying 3D simulation software for liver volume calculation,virtual simulation surgery,portal hypertension monitor,and surgical navigation has proven to be safe and effective[8].Therefore,we propose a new method to find obvious anatomical markers and calculate the resection range according to 3D positioning before operation.During the operation,the scope of resection was delineated with silk thread,and resection was performed.This is a new practical approach,which we named as 3D location approach with silk thread(3D-LAST).RESULTS During the study period from September 2020 to January 2022,5 patients with hepatocellular carcinoma,1 patient with intrahepatic cholangiocarcinoma,1 patient with hilar cholangiocarcinoma,and 1 patient with gastric cancer liver metastasis were assessed for liver resection.There were 5 males and 3 females.The mean age of these patients was 54.3±10.2 years(34-66 years).Preoperative 3D positioning was conducted and the scope of resection was delineated with a surgical suture successfully performed in all 8 patients without complications.The treatment results of these 8 patients are shown in Table 1.The 90-day operative mortality was zero.Complications worse than Dindo-Clavien IIIa was not observed at a mean follow-up time of 8.7 months(4-16 months),there was no evidence of tumor recurrence or extrahepatic metastasis.At the time of reporting,the patients are all alive and lead normal lives.We take one patient as an example,58-year-old male,who found a liver lesion 10 months after gastric cancer surgery.Enhanced CT showed that the lesion was located in the liver S5,about 1.5 cm in diameter,and considered metastatic lesions.We performed 3D-LAST guided hepatectomy on this patient(Figure 1).Other representative 3D-LAST surgical procedures are shown in Figure 2.展开更多
Objective： To observe the clinical effect of thread-embedding therapy in treating insomnia due to heart-spleen deficiency. Methods： Sixty patients were randomized into an acupuncture group and a thread-embedding gro...Objective： To observe the clinical effect of thread-embedding therapy in treating insomnia due to heart-spleen deficiency. Methods： Sixty patients were randomized into an acupuncture group and a thread-embedding group, 30 in each. The acupuncture group was managed by acupuncture therapy, and the thread-embedding group was treated by thread-embedding therapy. Pittsburgh Sleep Quality Index （PSQI） was adopted for evaluation before and after treatments. Results： The total effective rate was 86.7% in the acupuncture group versus 96.7% in the thread-embedding group. After treatment, the PSQI scores were significantly different from those before treatment in both groups （P〈0.01）; the scores in both two groups were mai＇kedly different from each other after treatment （P〈0.01）. Conclusion： Both acupuncture and thread-embedding therapies can effectively improve sleep quality of the patients, while thread-embedding therapy is comparatively less time-consuming, more convenient and with longer stimulation.展开更多
In petroleum extraction,the sealing surfaces of bolted joints are susceptible to damage due to the high-temperature and high-pressure conditions in wellbores.This damage adversely affects sealing performance,consequen...In petroleum extraction,the sealing surfaces of bolted joints are susceptible to damage due to the high-temperature and high-pressure conditions in wellbores.This damage adversely affects sealing performance,consequently leading to the failure and damage of threaded connections.In severe cases,it can result in considerable economic losses and trigger safety accidents.The sealing performance of special bolted joints holds crucial importance for production efficiency,output,equipment lifespan,and cost control.Enhancing the sealing perfor-mance of threaded connections can have a positive impact on industrial production and environmental protection.The existing research on American Petroleum Institute threaded joints has been thorough and has obtained a series of excellent results.However,the research on the sealing damage mechanism of threaded connections under complex well conditions lacks sufficient depth and that on new sealing technology is scarce.This study proposes a half-size evaluation test to address the abovementioned problem.Based on this test,an investigation into the sealing performance of threaded connections under high-temperature,cyclic loading,and high-temperature creep conditions is conducted.This study uses a combined approach of finite element methods and experiments to investigate the impact of different makeup torques on the sealing performance of premium threaded connections(PTCs).The results of the half-size evaluation test indicate that temperature notably influences the sealing performance of threaded connections.The continuous action of high temperatures causes contact pressure and sealing performance to decrease,and sealing contact pressure increases after cooling.Finite element and test results show that for a certain joint A,the greater the torque,the higher the critical sealing pressure of the thread,and the better the sealing performance.The research on the sealing damage mechanism of PTCs provides a scientific basis and theoretical guidance for the further optimization and development of PTCs.展开更多
Digital watermarking must balance imperceptibility,robustness,complexity,and security.To address the challenge of computational efficiency in trellis-based informed embedding,we propose a modified watermarking framewo...Digital watermarking must balance imperceptibility,robustness,complexity,and security.To address the challenge of computational efficiency in trellis-based informed embedding,we propose a modified watermarking framework that integrates fuzzy c-means(FCM)clustering into the generation off block codewords for labeling trellis arcs.The system incorporates a parallel trellis structure,controllable embedding parameters,and a novel informed embedding algorithm with reduced complexity.Two types of embedding schemes—memoryless and memory-based—are designed to flexibly trade-off between imperceptibility and robustness.Experimental results demonstrate that the proposed method outperforms existing approaches in bit error rate(BER)and computational complexity under various attacks,including additive noise,filtering,JPEG compression,cropping,and rotation.The integration of FCM enhances robustness by increasing the codeword distance,while preserving perceptual quality.Overall,the proposed framework is suitable for real-time and secure watermarking applications.展开更多
Tibetan medical named entity recognition(Tibetan MNER)involves extracting specific types of medical entities from unstructured Tibetan medical texts.Tibetan MNER provide important data support for the work related to ...Tibetan medical named entity recognition(Tibetan MNER)involves extracting specific types of medical entities from unstructured Tibetan medical texts.Tibetan MNER provide important data support for the work related to Tibetan medicine.However,existing Tibetan MNER methods often struggle to comprehensively capture multi-level semantic information,failing to sufficiently extract multi-granularity features and effectively filter out irrelevant information,which ultimately impacts the accuracy of entity recognition.This paper proposes an improved embedding representation method called syllable-word-sentence embedding.By leveraging features at different granularities and using un-scaled dot-product attention to focus on key features for feature fusion,the syllable-word-sentence embedding is integrated into the transformer,enhancing the specificity and diversity of feature representations.The model leverages multi-level and multi-granularity semantic information,thereby improving the performance of Tibetan MNER.We evaluate our proposed model on datasets from various domains.The results indicate that the model effectively identified three types of entities in the Tibetan news dataset we constructed,achieving an F1 score of 93.59%,which represents an improvement of 1.24%compared to the vanilla FLAT.Additionally,results from the Tibetan medical dataset we developed show that it is effective in identifying five kinds of medical entities,with an F1 score of 71.39%,which is a 1.34%improvement over the vanilla FLAT.展开更多
A complete examination of Large Language Models’strengths,problems,and applications is needed due to their rising use across disciplines.Current studies frequently focus on single-use situations and lack a comprehens...A complete examination of Large Language Models’strengths,problems,and applications is needed due to their rising use across disciplines.Current studies frequently focus on single-use situations and lack a comprehensive understanding of LLM architectural performance,strengths,and weaknesses.This gap precludes finding the appropriate models for task-specific applications and limits awareness of emerging LLM optimization and deployment strategies.In this research,50 studies on 25+LLMs,including GPT-3,GPT-4,Claude 3.5,DeepKet,and hybrid multimodal frameworks like ContextDET and GeoRSCLIP,are thoroughly reviewed.We propose LLM application taxonomy by grouping techniques by task focus—healthcare,chemistry,sentiment analysis,agent-based simulations,and multimodal integration.Advanced methods like parameter-efficient tuning(LoRA),quantumenhanced embeddings(DeepKet),retrieval-augmented generation(RAG),and safety-focused models(GalaxyGPT)are evaluated for dataset requirements,computational efficiency,and performance measures.Frameworks for ethical issues,data limited hallucinations,and KDGI-enhanced fine-tuning like Woodpecker’s post-remedy corrections are highlighted.The investigation’s scope,mad,and methods are described,but the primary results are not.The work reveals that domain-specialized fine-tuned LLMs employing RAG and quantum-enhanced embeddings performbetter for context-heavy applications.In medical text normalization,ChatGPT-4 outperforms previous models,while two multimodal frameworks,GeoRSCLIP,increase remote sensing.Parameter-efficient tuning technologies like LoRA have minimal computing cost and similar performance,demonstrating the necessity for adaptive models in multiple domains.To discover the optimum domain-specific models,explain domain-specific fine-tuning,and present quantum andmultimodal LLMs to address scalability and cross-domain issues.The framework helps academics and practitioners identify,adapt,and innovate LLMs for different purposes.This work advances the field of efficient,interpretable,and ethical LLM application research.展开更多
For friction stir lap welding (FSLW) process by the rotating pin greatly inserting into the bottom plate, the bending-down morphology of hook helps to obtain a high-strength lap joint, and can be more conducive to the...For friction stir lap welding (FSLW) process by the rotating pin greatly inserting into the bottom plate, the bending-down morphology of hook helps to obtain a high-strength lap joint, and can be more conducive to the joint strength when the tensile-fractured path is located in the top plate. In light of this, the reverse-flow FSLW (RF-FSLW) by a newly designed rotating tool with a right-left threaded X-shape pin (X-pin) was employed to weld 2024-T4 aluminum alloys with the same plate thickness, and the flow field simulation, in situ tensile test and EBSD analysis were utilized to understand the relations among the formation features, the fracture features and the joint strengths. The results indicated that under the integrated effects of the bending-down shape of hook, the bulging shape of nugget zone (NZ) and the bending-up shape of beginning part of cold lap near NZ outline, the RF-FSLW joint was tensile fractured in the top plate of joint. For the RF-FSLW joint, its maximum tensile strength was 412 MPa, and the corresponding joint efficiency (92.8%) was larger than that of reported friction stir welded joint of 2024 aluminum alloys in T temper condition. The RF-FSLW technology by the right-left threaded X-pin puts forward an extremely effective way for obtaining the superb-strength lap joint of aluminum alloys.展开更多
Multimodal sentiment analysis aims to understand emotions from text,speech,and video data.However,current methods often overlook the dominant role of text and suffer from feature loss during integration.Given the vary...Multimodal sentiment analysis aims to understand emotions from text,speech,and video data.However,current methods often overlook the dominant role of text and suffer from feature loss during integration.Given the varying importance of each modality across different contexts,a central and pressing challenge in multimodal sentiment analysis lies in maximizing the use of rich intra-modal features while minimizing information loss during the fusion process.In response to these critical limitations,we propose a novel framework that integrates spatial position encoding and fusion embedding modules to address these issues.In our model,text is treated as the core modality,while speech and video features are selectively incorporated through a unique position-aware fusion process.The spatial position encoding strategy preserves the internal structural information of speech and visual modalities,enabling the model to capture localized intra-modal dependencies that are often overlooked.This design enhances the richness and discriminative power of the fused representation,enabling more accurate and context-aware sentiment prediction.Finally,we conduct comprehensive evaluations on two widely recognized standard datasets in the field—CMU-MOSI and CMU-MOSEI to validate the performance of the proposed model.The experimental results demonstrate that our model exhibits good performance and effectiveness for sentiment analysis tasks.展开更多
Named Entity Recognition(NER)is vital in natural language processing for the analysis of news texts,as it accurately identifies entities such as locations,persons,and organizations,which is crucial for applications li...Named Entity Recognition(NER)is vital in natural language processing for the analysis of news texts,as it accurately identifies entities such as locations,persons,and organizations,which is crucial for applications like news summarization and event tracking.However,NER in the news domain faces challenges due to insufficient annotated data,complex entity structures,and strong context dependencies.To address these issues,we propose a new Chinesenamed entity recognition method that integrates transfer learning with word embeddings.Our approach leverages the ERNIE pre-trained model for transfer learning and obtaining general language representations and incorporates the Soft-lexicon word embedding technique to handle varied entity structures.This dual-strategy enhances the model’s understanding of context and boosts its ability to process complex texts.Experimental results show that our method achieves an F1 score of 94.72% on a news dataset,surpassing baseline methods by 3%–4%,thereby confirming its effectiveness for Chinese-named entity recognition in the news domain.展开更多
文摘Thread-embedding materials buried into acupuncture points to produce a long-time stimulation is a method which has been widely applied in the acupuncture and moxibustion therapies for diseases treating and they should have excellent properties of good biocompatibility,biodegradability and moderate rigidity.Polyactic acid(PLA) as the thread-embedding material had some shortcomings such as poor hydrophilicity and slowly biodegradable speed.In this paper,PLA thread-embedding material was modified by chitosan coating which could improve rigidity,hydrophilicity and moisture absorption and thus produce better stimulation effect.The variation tendency of diameter,mass,hydrophilicity,and initial modulus of the sample under the change of chitosan coating concentration,coating time and coating times were studied respectively.The results showed that the hydrophilicity,mass,and initial modulus after coating rose in a certain range when the coating time,coating times and coating concentration increased,while the changing of coating had little impact on fiber diameter.
基金2020 Hebei provincial research project of Chinese medicine(No.2020374)
文摘Objective:To explore the clinical effect of embedding thread combined with Jianpi Qushi Huayu ointment in the treatment of bronchiectasis in remission period,and to observe the effect on the level of inflammatory cytokines.Methods:150 patients with bronchiectasis in remission period were divided into three groups(50 cases in each group),western medicine group(treated with salmeterol fluticasone and low dose erythromycin),combined group(treated with Jianpi Qushi Huayu plaster),observation group(treated with western medicine+Jianpi Qushi Huayu plaster+embedding thread),and the clinical treatment of the three groups were compared.Result:before and after treatment,the improvement of TCM syndrome score,the improvement of pulmonary ventilation index,the improvement of inflammatory cytokines,and the change of adverse reactions.Results:the treatment efficiency of the observation group and the combination group was significantly higher than that of the western medicine group P The peak level of expiratory flow velocity,the maximum expiratory flow,the forced expiratory volume in one second and the ratio of forced expiratory volume in one second to vital capacity in the observation group and the combined group were significantly better than those in the western medicine group and the pre-treatment level(P<0.05),and the improvement in the observation group was better than that in the combined group After treatment,the expression of IL-13,IL-10 and IL-4 in the combined group was significantly better than that in the western medicine group and before treatment(P<0.05),and the improvement in the observation group was better than that in the combined group;there was no significant difference in the incidence of adverse reactions among the three groups(P>0.05).Conclusion:catgut embedding combined with Jianpi Qushi Huayu ointment can significantly alleviate the related clinical symptoms and signs,effectively control the further aggravation of the disease,improve the lung function of patients,regulate the level of inflammatory cytokines to reduce the degree of inflammatory reaction,and do not significantly aggravate the adverse reactions of drugs.
基金supported by the National Natural Science Foundation of China under Grant 62471493supported by the Natural Science Foundation of Shandong Province under Grant ZR2023LZH017,ZR2024MF066。
文摘With the rapid development of intelligent cyber-physical systems(ICPS),diverse services with varying Quality of Service(QoS)requirements have brought great challenges to traditional network resource allocation.Furthermore,given the open environment and a multitude of devices,enhancing the security of ICPS is an urgent concern.To address these issues,this paper proposes a novel trusted virtual network embedding(T-VNE)approach for ICPS based combining blockchain and edge computing technologies.Additionally,the proposed algorithm leverages a deep reinforcement learning(DRL)model to optimize decision-making processes.It employs the policygradient-based agent to compute candidate embedding nodes and utilizes a breadth-first search(BFS)algorithm to determine the optimal embedding paths.Finally,through simulation experiments,the efficacy of the proposed method was validated,demonstrating outstanding performance in terms of security,revenue generation,and virtual network request(VNR)acceptance rate.
基金funded by the Deanship of Graduate Studies and Scientific Research at Jouf University under grant No.(DGSSR-2024-02-01176).
文摘In recent years,ransomware attacks have become one of the most common and destructive types of cyberattacks.Their impact is significant on the operations,finances and reputation of affected companies.Despite the efforts of researchers and security experts to protect information systems from these attacks,the threat persists and the proposed solutions are not able to significantly stop the spread of ransomware attacks.The latest remarkable achievements of large language models(LLMs)in NLP tasks have caught the attention of cybersecurity researchers to integrate thesemodels into security threat detection.Thesemodels offer high embedding capabilities,able to extract rich semantic representations and paving theway formore accurate and adaptive solutions.In this context,we propose a new approach for ransomware detection based on an ensemblemethod that leverages three distinctLLMembeddingmodels.This ensemble strategy takes advantage of the variety of embedding methods and the strengths of each model.In the proposed solution,each embedding model is associated with an independently trainedMLP classifier.The predictions obtained are then merged using a weighted voting technique,assigning each model an influence proportional to its performance.This approach makes it possible to exploit the complementarity of representations,improve detection accuracy and robustness,and offer a more reliable solution in the face of the growing diversity and complexity of modern ransomware.
基金funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2026R234)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Spam emails remain one of the most persistent threats to digital communication,necessitating effective detection solutions that safeguard both individuals and organisations.We propose a spam email classification frame-work that uses Bidirectional Encoder Representations from Transformers(BERT)for contextual feature extraction and a multiple-window Convolutional Neural Network(CNN)for classification.To identify semantic nuances in email content,BERT embeddings are used,and CNN filters extract discriminative n-gram patterns at various levels of detail,enabling accurate spam identification.The proposed model outperformed Word2Vec-based baselines on a sample of 5728 labelled emails,achieving an accuracy of 98.69%,AUC of 0.9981,F1 Score of 0.9724,and MCC of 0.9639.With a medium kernel size of(6,9)and compact multi-window CNN architectures,it improves performance.Cross-validation illustrates stability and generalization across folds.By balancing high recall with minimal false positives,our method provides a reliable and scalable solution for current spam detection in advanced deep learning.By combining contextual embedding and a neural architecture,this study develops a security analysis method.
文摘Message structure reconstruction is a critical task in protocol reverse engineering,aiming to recover protocol field structures without access to source code.It enables important applications in network security,including malware analysis and protocol fuzzing.However,existing methods suffer from inaccurate field boundary delineation and lack hierarchical relationship recovery,resulting in imprecise and incomplete reconstructions.In this paper,we propose ProRE,a novel method for reconstructing protocol field structures based on program execution slice embedding.ProRE extracts code slices from protocol parsing at runtime,converts them into embedding vectors using a data flow-sensitive assembly language model,and performs hierarchical clustering to recover complete protocol field structures.Evaluation on two datasets containing 12 protocols shows that ProRE achieves an average F1 score of 0.85 and a cophenetic correlation coefficient of 0.189,improving by 19%and 0.126%respectively over state-of-the-art methods(including BinPRE,Tupni,Netlifter,and QwQ-32B-preview),demonstrating significant superiority in both accuracy and completeness of field structure recovery.Case studies further validate the effectiveness of ProRE in practical malware analysis scenarios.
基金supported by the National Natural Science Foundation of China under Grant No.72293575.
文摘Temporal knowledge graph completion(TKGC),which merges temporal information into traditional static knowledge graph completion(SKGC),has garnered increasing attention recently.Among numerous emerging approaches,translation-based embedding models constitute a prominent approach in TKGC research.However,existing translation-based methods typically incorporate timestamps into entities or relations,rather than utilizing them independently.This practice fails to fully exploit the rich semantics inherent in temporal information,thereby weakening the expressive capability of models.To address this limitation,we propose embedding timestamps,like entities and relations,in one or more dedicated semantic spaces.After projecting all embeddings into a shared space,we use the relation-timestamp pair instead of the conventional relation embedding as the translation vector between head and tail entities.Our method elevates timestamps to the same representational significance as entities and relations.Based on this strategy,we introduce two novel translation-based embedding models:TE-TransR and TE-TransT.With the independent representation of timestamps,our method not only enhances capabilities in link prediction but also facilitates a relatively underexplored task,namely time prediction.To further bolster the precision and reliability of time prediction,we introduce a granular,time unit-based timestamp setting and a relation-specific evaluation protocol.Extensive experiments demonstrate that our models achieve strong performance on link prediction benchmarks,with TE-TransR outperforming existing baselines in the time prediction task.
文摘Objective: The comparison of the remote and recent therapeutic effects on perennial allergic rhinitis was carried on among single application of acupoint-thread embedding, western medicine (certirizine+flixonase) and allied therapy. Method: Ninety cases were randomized into thread-embedding group, western medicine group and embedding+western medicine group (allied-therapy group), 30 cases in each one. In thread embedding group, Yingxiang (迎香 LI 20) and Feishu (肺俞 BL 13) were selected for thread embedding, once a week, totally 4 treatments were required. In western medicine group, certirizine tablet 10 mg in combination with flixonase sprayer was applied once per day, continuously for 30 days in treatment. In allied-therapy group, both of the above methods were adopted continuously for 30 days in treatment. The therapeutic effects were in statistics at the end of treatment and 1 year later. Results: At the end of treatment, in thread-embedding group, 21 cases were remarkably effective, 3 cases effective and 6 cases no effect. In western medicine group, 20 cases were remarkably effective, 3 cases effective and 7 cases no effect. In allied-therapy group, 23 cases were remarkably effective, 2 cases effective and 5 cases no effect. It was shown in statistics that there was no significant difference in therapeutic effects among three groups ( P>0.05 ). But one year after the end of treatment, it was indicated that in thread-embedding group, 3 cases were remarkably effective, 10 cases effective and 17 cases no effect; in western medicine group, 2 cases were remarkably effective, 9 cases effective and 19 cases no effect; in allied-therapy group, 7 cases were remarkably effective, 11 cases effective and 12 cases no effect. The significant difference in the therapeutic effects had not been presented in the comparison between thread-embedding group and western medicine group (P>0.05), but that had been presented between allied-therapy group with either of the groups with single therapy applied (P<0.05). Conclusion: Quite good recent therapeutic effect of either acupoint-thread embedding or western medicine (certirizine+flixonase) was achieved on perennial allergic rhinitis. The remote therapeutic effect of allied therapy was more advantageous than that of single application of either thread embedding or western medicine.
基金Biomedical Textile Materials Science and Technology(111 Project),China(No.B07024)
文摘Poly( glycolic acid-lactic acid)( PGLA) threadembedding material was modified by chitosan coating which could improve the rigidity,hydrophilicity and moisture absorption of the material,and produced better stimulation effect. Thus,this kind of thread-embedding materials which can be buried into acupuncture points to produce a long-time stimulation is popular in the acupuncture and moxibustion therapies. The variation tendencies of diameter,weight, hydrophilicity, and flexibility of the samples under the change of chitosan coating concentration,coating time and coating times were studied respectively. The results showed that the hydrophilicity,weight,and rigidity after coating rose in a certain range with the increase of coating time,coating times and coating concentration. The coating time had little influence on the diameter of fiber.
文摘BACKGROUND A total of 100 patients diagnosed with mixed hemorrhoids from October 2022 to September 2023 in our hospital were randomly divided into groups by dice rolling and compared with the efficacy of different treatment options.AIM To analyze the clinical effect and prognosis of mixed hemorrhoids treated with polidocanol injection combined with automatic elastic thread ligation operation(RPH).METHODS A total of 100 patients with mixed hemorrhoids who visited our hospital from October 2022 to September 2023 were selected and randomly divided into the control group(n=50)and the treatment group(n=50)by rolling the dice.The procedure for prolapse and hemorrhoids(PPH)was adopted in the control group,while polidocanol foam injection+RPH was adopted in the treatment group.The therapeutic effects,operation time,wound healing time,hospital stay,pain situation(24 hours post-operative pain score,first defecation pain score),quality of life(QOL),incidence of complications(post-operative hemorrhage,edema,infection),incidence of anal stenosis 3 months post-operatively and recurrence rate 1 year post-operatively of the two groups were compared.RESULTS Compared with the control group,the total effective rate of treatment group was higher,and the difference was significant(P<0.05).The operation time/wound healing time/hospital stay in the treatment group were shorter than those in the control group(P<0.05).The pain scores at 24 hours after operation/first defecation pain score of the treatment group was significantly lower than those in the control group(P<0.05).After surgery,the QOL scores of the two groups decreased,with the treatment group having higher scores than that of the control group(P<0.05).Compared with the control group,the incidence of postoperative complications in the treatment group was lower,and the difference was significant(P<0.05);However,there was no significant difference in the incidence of postoperative bleeding between the two groups(P>0.05);There was no significant difference in the incidence of anal stenosis 3 months after operation and the recurrence rate 1 year after operation between the two groups(P>0.05).CONCLUSION For patients with mixed hemorrhoids,the therapeutic effect achieved by using polidocanol injection combined with RPH was better.The wounds of the patients healed faster,the postoperative pain was milder,QOL improved,and the incidence of complications was lower,and the short-term and long-term prognosis was good.
基金Supported by the Grant-in-Aid for Scientific Research(C)by the Japan Society for the Promotion of Science(20K03615)。
文摘Let G be a group.The family of all sets which are closed in every Hausdorf group topology of G form the family of closed sets of a T_(1) topology M_(G) on G called the Markov topology.Similarly,the family of all algebraic subsets of G forms a family of closed sets for another T_(1)topology Z_(G) on G called the Zarski topology.A subgroup H of G is said to be Markov(resp.Zarski)embedded if the equality M_(G|H)=M_(H)(resp.Z_(G|H)=Z_(H))holds.I's proved that an abirary subgroup of a free group is both Zariski and Markov embedded in it.
文摘BACKGROUND Intraoperative determination of resection margin and adequate residual liver parenchyma are the key points of hepatectomy for the treatment of liver tumors.Intraoperative ultrasound and indocyanine green fluorescence navigation are the most commonly used methods at present,but the technical barriers limit their promotion.AIM To evaluate the value of the three-dimensional location approach with silk thread(3D-LAST)in precise resection of liver tumors.METHODS From September 2020 to January 2022,8 patients with liver tumors including hepatocellular carcinoma,intrahepatic cholangiocarcinoma,hilar cholangiocar-cinoma,and gastric cancer liver metastasis were included in this study.All patients underwent 3D-LAST in precise resection of liver tumors.RESULTS All patients(8/8,100%)underwent the operation successfully without any complications.During the mean follow-up of 8.7 months,all patients survived without tumor recurrence.CONCLUSION In conclusion,the 3D-LAST is a safe and effective new method for liver intraop-erative navigation,which is practical and easy to promote.Core Tip:The aim of this study is to evaluate the value of the three-dimensional location approach with silk thread(3D-LAST)in precise resection of liver tumors.Eight patients with liver tumors including hepatocellular carcinoma,intrahepatic cholangiocarcinoma,hilar cholangiocarcinoma,and gastric cancer liver metastasis underwent the operation successfully without any complications.During the mean follow-up of 8.7 months,all patients survived without tumor recurrence.In conclusion,the 3D-LAST is a safe and effective new method for liver intraoperative navigation,which is practical and easy to promote.INTRODUCTION Hepatectomy is widely used for the treatment of liver tumors.In recent decades,the concept and practice of hepatectomy have developed from irregular,regular and anatomical to the current precise resection.Necessary assistive technologies have enabled these advances.Intraoperative ultrasound(IOUS)localization and indocyanine green(ICG)fluorescence imaging guidance are two frequently-used approaches for laparoscopic hepatectomy[1,2].IOUS is an invaluable auxiliary means widely accepted in surgery for real-time diagnostic information to determine resection range and navigate the surgical path[3].However,the major limitation of IOUS is the time cost during the procedure for paging the sono-graphers and the difficulty of deciphering two dimensional images[4].ICG is a non-toxic water-soluble fluorophore that reveals fluorescence under the near-infrared spectrum[5].Since liver tissue penetration is limited to 5 to 10 mm,that restricted the visualization of deeper tumors by ICG excitation,thereby interfering with its application in laparoscopic hepatectomy[6].IOUS and ICG navigation require specific technical equipment,making implementation difficult in many centers.And these techniques will significantly increase the operation time.Three-dimensional(3D)visualization involves extracting features and producing volumetric images based on computed tomography(CT)through a computer postprocessing technique.This tool offers a reasonable approach to the clinical decision for the potential to display the complex internal anatomy in an intuitive and stereoscopic manner[7].In the past few decades,applying 3D simulation software for liver volume calculation,virtual simulation surgery,portal hypertension monitor,and surgical navigation has proven to be safe and effective[8].Therefore,we propose a new method to find obvious anatomical markers and calculate the resection range according to 3D positioning before operation.During the operation,the scope of resection was delineated with silk thread,and resection was performed.This is a new practical approach,which we named as 3D location approach with silk thread(3D-LAST).RESULTS During the study period from September 2020 to January 2022,5 patients with hepatocellular carcinoma,1 patient with intrahepatic cholangiocarcinoma,1 patient with hilar cholangiocarcinoma,and 1 patient with gastric cancer liver metastasis were assessed for liver resection.There were 5 males and 3 females.The mean age of these patients was 54.3±10.2 years(34-66 years).Preoperative 3D positioning was conducted and the scope of resection was delineated with a surgical suture successfully performed in all 8 patients without complications.The treatment results of these 8 patients are shown in Table 1.The 90-day operative mortality was zero.Complications worse than Dindo-Clavien IIIa was not observed at a mean follow-up time of 8.7 months(4-16 months),there was no evidence of tumor recurrence or extrahepatic metastasis.At the time of reporting,the patients are all alive and lead normal lives.We take one patient as an example,58-year-old male,who found a liver lesion 10 months after gastric cancer surgery.Enhanced CT showed that the lesion was located in the liver S5,about 1.5 cm in diameter,and considered metastatic lesions.We performed 3D-LAST guided hepatectomy on this patient(Figure 1).Other representative 3D-LAST surgical procedures are shown in Figure 2.
文摘Objective： To observe the clinical effect of thread-embedding therapy in treating insomnia due to heart-spleen deficiency. Methods： Sixty patients were randomized into an acupuncture group and a thread-embedding group, 30 in each. The acupuncture group was managed by acupuncture therapy, and the thread-embedding group was treated by thread-embedding therapy. Pittsburgh Sleep Quality Index （PSQI） was adopted for evaluation before and after treatments. Results： The total effective rate was 86.7% in the acupuncture group versus 96.7% in the thread-embedding group. After treatment, the PSQI scores were significantly different from those before treatment in both groups （P〈0.01）; the scores in both two groups were mai＇kedly different from each other after treatment （P〈0.01）. Conclusion： Both acupuncture and thread-embedding therapies can effectively improve sleep quality of the patients, while thread-embedding therapy is comparatively less time-consuming, more convenient and with longer stimulation.
文摘In petroleum extraction,the sealing surfaces of bolted joints are susceptible to damage due to the high-temperature and high-pressure conditions in wellbores.This damage adversely affects sealing performance,consequently leading to the failure and damage of threaded connections.In severe cases,it can result in considerable economic losses and trigger safety accidents.The sealing performance of special bolted joints holds crucial importance for production efficiency,output,equipment lifespan,and cost control.Enhancing the sealing perfor-mance of threaded connections can have a positive impact on industrial production and environmental protection.The existing research on American Petroleum Institute threaded joints has been thorough and has obtained a series of excellent results.However,the research on the sealing damage mechanism of threaded connections under complex well conditions lacks sufficient depth and that on new sealing technology is scarce.This study proposes a half-size evaluation test to address the abovementioned problem.Based on this test,an investigation into the sealing performance of threaded connections under high-temperature,cyclic loading,and high-temperature creep conditions is conducted.This study uses a combined approach of finite element methods and experiments to investigate the impact of different makeup torques on the sealing performance of premium threaded connections(PTCs).The results of the half-size evaluation test indicate that temperature notably influences the sealing performance of threaded connections.The continuous action of high temperatures causes contact pressure and sealing performance to decrease,and sealing contact pressure increases after cooling.Finite element and test results show that for a certain joint A,the greater the torque,the higher the critical sealing pressure of the thread,and the better the sealing performance.The research on the sealing damage mechanism of PTCs provides a scientific basis and theoretical guidance for the further optimization and development of PTCs.
基金funded by the National Science and Technology Council,Taiwan,under grant number NSTC 114-2221-E-167-005-MY3,and NSTC 113-2221-E-167-006-.
文摘Digital watermarking must balance imperceptibility,robustness,complexity,and security.To address the challenge of computational efficiency in trellis-based informed embedding,we propose a modified watermarking framework that integrates fuzzy c-means(FCM)clustering into the generation off block codewords for labeling trellis arcs.The system incorporates a parallel trellis structure,controllable embedding parameters,and a novel informed embedding algorithm with reduced complexity.Two types of embedding schemes—memoryless and memory-based—are designed to flexibly trade-off between imperceptibility and robustness.Experimental results demonstrate that the proposed method outperforms existing approaches in bit error rate(BER)and computational complexity under various attacks,including additive noise,filtering,JPEG compression,cropping,and rotation.The integration of FCM enhances robustness by increasing the codeword distance,while preserving perceptual quality.Overall,the proposed framework is suitable for real-time and secure watermarking applications.
基金supported in part by the National Science and Technology Major Project under(Grant 2022ZD0116100)in part by the National Natural Science Foundation Key Project under(Grant 62436006)+4 种基金in part by the National Natural Science Foundation Youth Fund under(Grant 62406257)in part by the Xizang Autonomous Region Natural Science Foundation General Project under(Grant XZ202401ZR0031)in part by the National Natural Science Foundation of China under(Grant 62276055)in part by the Sichuan Science and Technology Program under(Grant 23ZDYF0755)in part by the Xizang University‘High-Level Talent Training Program’Project under(Grant 2022-GSP-S098).
文摘Tibetan medical named entity recognition(Tibetan MNER)involves extracting specific types of medical entities from unstructured Tibetan medical texts.Tibetan MNER provide important data support for the work related to Tibetan medicine.However,existing Tibetan MNER methods often struggle to comprehensively capture multi-level semantic information,failing to sufficiently extract multi-granularity features and effectively filter out irrelevant information,which ultimately impacts the accuracy of entity recognition.This paper proposes an improved embedding representation method called syllable-word-sentence embedding.By leveraging features at different granularities and using un-scaled dot-product attention to focus on key features for feature fusion,the syllable-word-sentence embedding is integrated into the transformer,enhancing the specificity and diversity of feature representations.The model leverages multi-level and multi-granularity semantic information,thereby improving the performance of Tibetan MNER.We evaluate our proposed model on datasets from various domains.The results indicate that the model effectively identified three types of entities in the Tibetan news dataset we constructed,achieving an F1 score of 93.59%,which represents an improvement of 1.24%compared to the vanilla FLAT.Additionally,results from the Tibetan medical dataset we developed show that it is effective in identifying five kinds of medical entities,with an F1 score of 71.39%,which is a 1.34%improvement over the vanilla FLAT.
文摘A complete examination of Large Language Models’strengths,problems,and applications is needed due to their rising use across disciplines.Current studies frequently focus on single-use situations and lack a comprehensive understanding of LLM architectural performance,strengths,and weaknesses.This gap precludes finding the appropriate models for task-specific applications and limits awareness of emerging LLM optimization and deployment strategies.In this research,50 studies on 25+LLMs,including GPT-3,GPT-4,Claude 3.5,DeepKet,and hybrid multimodal frameworks like ContextDET and GeoRSCLIP,are thoroughly reviewed.We propose LLM application taxonomy by grouping techniques by task focus—healthcare,chemistry,sentiment analysis,agent-based simulations,and multimodal integration.Advanced methods like parameter-efficient tuning(LoRA),quantumenhanced embeddings(DeepKet),retrieval-augmented generation(RAG),and safety-focused models(GalaxyGPT)are evaluated for dataset requirements,computational efficiency,and performance measures.Frameworks for ethical issues,data limited hallucinations,and KDGI-enhanced fine-tuning like Woodpecker’s post-remedy corrections are highlighted.The investigation’s scope,mad,and methods are described,but the primary results are not.The work reveals that domain-specialized fine-tuned LLMs employing RAG and quantum-enhanced embeddings performbetter for context-heavy applications.In medical text normalization,ChatGPT-4 outperforms previous models,while two multimodal frameworks,GeoRSCLIP,increase remote sensing.Parameter-efficient tuning technologies like LoRA have minimal computing cost and similar performance,demonstrating the necessity for adaptive models in multiple domains.To discover the optimum domain-specific models,explain domain-specific fine-tuning,and present quantum andmultimodal LLMs to address scalability and cross-domain issues.The framework helps academics and practitioners identify,adapt,and innovate LLMs for different purposes.This work advances the field of efficient,interpretable,and ethical LLM application research.
基金supported by the National Natural Sci-ence Foundation of China(Nos.52074184 and 52374393)the Natu-ral Science Foundation Project of Liaoning Province(No.2023-MS-238)+1 种基金Liaoning Revitalization Talents Program(No.XLYC2203009)the Fundamental Research Funds for the Universities of Liaon-ing Province.
文摘For friction stir lap welding (FSLW) process by the rotating pin greatly inserting into the bottom plate, the bending-down morphology of hook helps to obtain a high-strength lap joint, and can be more conducive to the joint strength when the tensile-fractured path is located in the top plate. In light of this, the reverse-flow FSLW (RF-FSLW) by a newly designed rotating tool with a right-left threaded X-shape pin (X-pin) was employed to weld 2024-T4 aluminum alloys with the same plate thickness, and the flow field simulation, in situ tensile test and EBSD analysis were utilized to understand the relations among the formation features, the fracture features and the joint strengths. The results indicated that under the integrated effects of the bending-down shape of hook, the bulging shape of nugget zone (NZ) and the bending-up shape of beginning part of cold lap near NZ outline, the RF-FSLW joint was tensile fractured in the top plate of joint. For the RF-FSLW joint, its maximum tensile strength was 412 MPa, and the corresponding joint efficiency (92.8%) was larger than that of reported friction stir welded joint of 2024 aluminum alloys in T temper condition. The RF-FSLW technology by the right-left threaded X-pin puts forward an extremely effective way for obtaining the superb-strength lap joint of aluminum alloys.
基金supported by the Collaborative Tackling Project of the Yangtze River Delta SciTech Innovation Community(Nos.2024CSJGG01503,2024CSJGG01500)Guangxi Key Research and Development Program(No.AB24010317)Jiangxi Provincial Key Laboratory of Electronic Data Control and Forensics(Jiangxi Police College)(No.2025JXJYKFJJ002).
文摘Multimodal sentiment analysis aims to understand emotions from text,speech,and video data.However,current methods often overlook the dominant role of text and suffer from feature loss during integration.Given the varying importance of each modality across different contexts,a central and pressing challenge in multimodal sentiment analysis lies in maximizing the use of rich intra-modal features while minimizing information loss during the fusion process.In response to these critical limitations,we propose a novel framework that integrates spatial position encoding and fusion embedding modules to address these issues.In our model,text is treated as the core modality,while speech and video features are selectively incorporated through a unique position-aware fusion process.The spatial position encoding strategy preserves the internal structural information of speech and visual modalities,enabling the model to capture localized intra-modal dependencies that are often overlooked.This design enhances the richness and discriminative power of the fused representation,enabling more accurate and context-aware sentiment prediction.Finally,we conduct comprehensive evaluations on two widely recognized standard datasets in the field—CMU-MOSI and CMU-MOSEI to validate the performance of the proposed model.The experimental results demonstrate that our model exhibits good performance and effectiveness for sentiment analysis tasks.
基金funded by Advanced Research Project(30209040702).
文摘Named Entity Recognition(NER)is vital in natural language processing for the analysis of news texts,as it accurately identifies entities such as locations,persons,and organizations,which is crucial for applications like news summarization and event tracking.However,NER in the news domain faces challenges due to insufficient annotated data,complex entity structures,and strong context dependencies.To address these issues,we propose a new Chinesenamed entity recognition method that integrates transfer learning with word embeddings.Our approach leverages the ERNIE pre-trained model for transfer learning and obtaining general language representations and incorporates the Soft-lexicon word embedding technique to handle varied entity structures.This dual-strategy enhances the model’s understanding of context and boosts its ability to process complex texts.Experimental results show that our method achieves an F1 score of 94.72% on a news dataset,surpassing baseline methods by 3%–4%,thereby confirming its effectiveness for Chinese-named entity recognition in the news domain.
