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
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
In the domain of knowledge graph embedding,conventional approaches typically transform entities and relations into continuous vector spaces.However,parameter efficiency becomes increasingly crucial when dealing with l...In the domain of knowledge graph embedding,conventional approaches typically transform entities and relations into continuous vector spaces.However,parameter efficiency becomes increasingly crucial when dealing with large-scale knowledge graphs that contain vast numbers of entities and relations.In particular,resource-intensive embeddings often lead to increased computational costs,and may limit scalability and adaptability in practical environ-ments,such as in low-resource settings or real-world applications.This paper explores an approach to knowledge graph representation learning that leverages small,reserved entities and relation sets for parameter-efficient embedding.We introduce a hierarchical attention network designed to refine and maximize the representational quality of embeddings by selectively focusing on these reserved sets,thereby reducing model complexity.Empirical assessments validate that our model achieves high performance on the benchmark dataset with fewer parameters and smaller embedding dimensions.The ablation studies further highlight the impact and contribution of each component in the proposed hierarchical attention structure.展开更多
Objective:To explore the effects of acupoint catgut embedding combined with auricular point pressing with beans on symptom management self-efficacy and quality of life in patients with nonalcoholic steatohepatitis(NAS...Objective:To explore the effects of acupoint catgut embedding combined with auricular point pressing with beans on symptom management self-efficacy and quality of life in patients with nonalcoholic steatohepatitis(NASH)of liver depression and spleen deficiency type.Methods:Sixty patients with NASH of liver depression and spleen deficiency type admitted to our hospital from January 2021 to December 2023 were selected and divided into an acupoint catgut embedding group(n=30)and a combined group(n=30)using the envelope lottery method.The acupoint catgut embedding group received acupoint catgut embedding intervention,while the combined group received auricular point pressing with beans on the basis of the acupoint catgut embedding group.The two groups were compared in terms of TCM syndrome scores,symptom management self-efficacy[Chronic Disease Self-Efficacy Scale(CDSES)],and quality of life[Chronic Liver Disease Questionnaire(CLDQ)].Results:After intervention,the combined group had lower TCM syndrome scores for both primary and secondary symptoms compared to the acupoint catgut embedding group(P<0.05).The combined group also had higher scores in all dimensions and total score of the CDSES compared to the acupoint catgut embedding group(P<0.05).Similarly,the combined group had higher scores in all dimensions and total score of the CLDQ compared to the acupoint catgut embedding group(P<0.05).Conclusion:Acupoint catgut embedding combined with auricular point pressing with beans can effectively improve TCM symptoms,enhance symptom management self-efficacy,and improve quality of life in patients with NASH of liver depression and spleen deficiency type.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
Network virtualization is the development trend and inevitable requirement of hybrid wireless sensor networks(HWSNs).Low mapping efficiency and service interruption caused by mobility seriously affect the reliability ...Network virtualization is the development trend and inevitable requirement of hybrid wireless sensor networks(HWSNs).Low mapping efficiency and service interruption caused by mobility seriously affect the reliability of sensing tasks and ultimately affect the long-term revenue of the infrastructure providers.In response to these problems,this paper proposes an efficient virtual network embedding algorithm with a reliable service guarantee.Based on the topological attributes of nodes,a method for evaluating the physical network resource importance degree is proposed,and the nodes with rich resources are selected to improve embedding efficiency.Then,a method for evaluating the physical network reliability degree is proposed to predict the probability of mobile sensors providing uninterrupted services.The simulation results show that the proposed algorithm improves the acceptance rate of virtual sensor networks(VSN)embedding requests and the long-term revenue of the infrastructure providers.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
Lactate,as a metabolite,plays a significant role in a number of fields,including medical diagnostics,exercise physiology and food science.Traditional methods for lactate measurement often involve expensive and cumbers...Lactate,as a metabolite,plays a significant role in a number of fields,including medical diagnostics,exercise physiology and food science.Traditional methods for lactate measurement often involve expensive and cumbersome instrumentation.This study developed a portable and low-cost lactate measurement system,including independently detectable hardware circuits and user-friendly embedded software,computer,and smartphone applications.The experiment verified that the relative error of the detection current in the device circuit was less than 1%.The electrochemical performance was measured by comparing the[Fe(CN)_(6)]^(3−)/[Fe(CN)_(6)]^(4−)solution with the desktop electrochemical workstation CHI660E,and a nearly consistent chronoamperometry(CA)curve was obtained.Two modified lactate sensors were used for CA testing of lactate.Within the concentration range of 0.1 mmol·L^(−1)to 20 mmol·L^(−1),there was a good linear relationship between lactate concentration and steady-state current,with a correlation coefficient(R2)greater than 0.99 and good repeatability,demonstrating the reliability of the developed device.The lactate measurement system developed in this study not only provides excellent detection performance and reliability,but also achieves portability and low cost,providing a new solution for lactate measurement.展开更多
In shale gas reservoir stimulation,proppants are essential for sustaining fracture conductivity.However,increasing closing stress causes proppants to embed into the rock matrix,leading to a progressive decline in frac...In shale gas reservoir stimulation,proppants are essential for sustaining fracture conductivity.However,increasing closing stress causes proppants to embed into the rock matrix,leading to a progressive decline in fracture permeability and conductivity.Furthermore,rock creep contributes to long-term reductions in fracture performance.To elucidate the combined effects of proppant embedding and rock creep on sustained conductivity,this study conducted controlled experiments examining conductivity decay in propped fractures under varying closing stresses,explicitly accounting for both mechanisms.An embedded discrete fracture model was developed to simulate reservoir production under different conductivity decay scenarios,while evaluating the influence of proppant parameters on fracture performance.The results demonstrate that fracture conductivity diminishes rapidly with increasing stress,yet at 50 MPa,the decline becomes less pronounced.Simulated production profiles show strong agreement with actual gas well data,confirming the model’s accuracy and predictive capability.These findings suggest that employing a high proppant concentration with smaller particle size(5 kg/m^(2),70/140 mesh)is effective for maintaining long-term fracture conductivity and enhancing shale gas recovery.This study provides a rigorous framework for optimizing proppant selection and designing stimulation strategies that maximize reservoir performance over time.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
Neural organoids and confocal microscopy have the potential to play an important role in microconnectome research to understand neural patterns.We present PLayer,a plug-and-play embedded neural system,which demonstrat...Neural organoids and confocal microscopy have the potential to play an important role in microconnectome research to understand neural patterns.We present PLayer,a plug-and-play embedded neural system,which demonstrates the utilization of sparse confocal microscopy layers to interpolate continuous axial resolution.With an embedded system focused on neural network pruning,image scaling,and post-processing,PLayer achieves high-performance metrics with an average structural similarity index of 0.9217 and a peak signal-to-noise ratio of 27.75 dB,all within 20 s.This represents a significant time saving of 85.71%with simplified image processing.By harnessing statistical map estimation in interpolation and incorporating the Vision Transformer–based Restorer,PLayer ensures 2D layer consistency while mitigating heavy computational dependence.As such,PLayer can reconstruct 3D neural organoid confocal data continuously under limited computational power for the wide acceptance of fundamental connectomics and pattern-related research with embedded devices.展开更多
The increasing fluency of advanced language models,such as GPT-3.5,GPT-4,and the recently introduced DeepSeek,challenges the ability to distinguish between human-authored and AI-generated academic writing.This situati...The increasing fluency of advanced language models,such as GPT-3.5,GPT-4,and the recently introduced DeepSeek,challenges the ability to distinguish between human-authored and AI-generated academic writing.This situation is raising significant concerns regarding the integrity and authenticity of academic work.In light of the above,the current research evaluates the effectiveness of Bidirectional Long Short-TermMemory(BiLSTM)networks enhanced with pre-trained GloVe(Global Vectors for Word Representation)embeddings to detect AIgenerated scientific Abstracts drawn from the AI-GA(Artificial Intelligence Generated Abstracts)dataset.Two core BiLSTM variants were assessed:a single-layer approach and a dual-layer design,each tested under static or adaptive embeddings.The single-layer model achieved nearly 97%accuracy with trainable GloVe,occasionally surpassing the deeper model.Despite these gains,neither configuration fully matched the 98.7%benchmark set by an earlier LSTMWord2Vec pipeline.Some runs were over-fitted when embeddings were fine-tuned,whereas static embeddings offered a slightly lower yet stable accuracy of around 96%.This lingering gap reinforces a key ethical and procedural concern:relying solely on automated tools,such as Turnitin’s AI-detection features,to penalize individuals’risks and unjust outcomes.Misclassifications,whether legitimate work is misread as AI-generated or engineered text,evade detection,demonstrating that these classifiers should not stand as the sole arbiters of authenticity.Amore comprehensive approach is warranted,one which weaves model outputs into a systematic process supported by expert judgment and institutional guidelines designed to protect originality.展开更多
Dear Editor,The letter deals with the distributed state and fault estimation of the whole physical layer for cyber-physical systems(CPSs) when the cyber layer suffers from DoS attacks. With the advancement of embedded...Dear Editor,The letter deals with the distributed state and fault estimation of the whole physical layer for cyber-physical systems(CPSs) when the cyber layer suffers from DoS attacks. With the advancement of embedded computing, communication and related hardware technologies, CPSs have attracted extensive attention and have been widely used in power system, traffic network, refrigeration system and other fields.展开更多
Constructing an in vitro vascularized liver tissue model that closely simulates the human liver is crucial for promoting cell proliferation,mimicking physiological heterogeneous structures,and recreating the cellular ...Constructing an in vitro vascularized liver tissue model that closely simulates the human liver is crucial for promoting cell proliferation,mimicking physiological heterogeneous structures,and recreating the cellular microenvironment.However,the layer-by-layer printing method is significantly constrained by the rheological properties of the bioink,making it challenging to form complex three-dimensional vascular structures in low-viscosity soft materials.To overcome this limitation,we developed a cross-linkable biphasic embedding medium by mixing low-viscosity biomaterials with gelatin microgel.This medium possesses yield stress and self-healing properties,facilitating efficient and continuous three-dimensional shaping of sacrificial ink within it.By adjusting the printing speed,we controlled the filament diameter,achieving a range from 250μm to 1000μm,and ensuring precise control over ink deposition locations and filament shapes.Using the in situ endothelialization method,we constructed complex vascular structures and ensured close adhesion between hepatocytes and endothelial cells.In vitro experiments demonstrated that the vascularized liver tissue model exhibited enhanced protein synthesis and metabolic function compared to mixed liver tissue.We also investigated the impact of varying vascular densities on liver tissue function.Transcriptome sequencing revealed that liver tissues with higher vascular density exhibited upregulated gene expression in metabolic and angiogenesis-related pathways.In summary,this method is adaptable to various materials,allowing the rheological properties of the supporting bath and the tissue's porosity to be modified using microgels,thus enabling precise regulation of the liver tissue microenvironment.Additionally,it facilitates the rapid construction of three-dimensional vascular structures within liver tissue.The resulting vascularized liver tissue model exhibits enhanced biological functionality,opening new opportunities for biomedical applications.展开更多
Objective To systematically evaluate the effect of acupoint catgut embedding therapy （ACET） for simple obesity. Methods Computer retrieval was used for randomized controlled trials on the treatment effect of simple ...Objective To systematically evaluate the effect of acupoint catgut embedding therapy （ACET） for simple obesity. Methods Computer retrieval was used for randomized controlled trials on the treatment effect of simple obesity with ACET in databases of the China National Knowledge Infrastructure （CNKI）, Wanfang Data system, and the China Biology Medicine disc （CBMDisc）. The Jadad Quality Scale was used in the evaluation of included studies. The outcome indicators were analyzed with the Review Manage 5.1 software. Results A total of 16 randomized controlled trials were included finally. The meta-analysis result showed that compared with the control group, there was statistically significance on the total efficiency of using ACET for simple obesity [OR=2.51, 95% confidence interval （1.74, 3.63）, Z=4.91, P〈0.000 01]. The analysis on the literature quality showed that there was only 2 article marked as 3 points. The other 25 articles marked ≤2 points. The quality of published articles was generally low. There were publication biases and the blinding method was seldom used, the losses of follow-up / drop oup / withdraw were reported with less. There were 27 acupoints used in the treatment, which mainly included Tianshu （天枢ST 25）, Zhongwan （中脘 CV 12）, Fenglong （丰隆 ST 40）, Shufen （水分 CV 9）, Qihai （气海 CV 6）, Sanyinjiao （三阴交 SP 6）, Zusnli （足三里 ST 36）, Ashi point, Daheng （大横 SP 25）. The five kinds of catgut embedding needle were injection needles ＋ acupuncture needle, specialized catgut embedding needle, spinal needle, triangular needle, and skin suture needle. Conclusion There is definite efficiency of using ACET in the treatment of simple obesity. However, the clinical efficiency still lacks of sufficient evidences. Therefore, further clinical research should be conducted in the providing of reliable evidences in the clinical decision-making in the future.展开更多
Most of the commercially-available pot seedling nursery machines are incompatible with soft-pot-trays and are labor-intensive and low in productivity.A soft-pot-tray automatic embedding system was developed in this st...Most of the commercially-available pot seedling nursery machines are incompatible with soft-pot-trays and are labor-intensive and low in productivity.A soft-pot-tray automatic embedding system was developed in this study to achieve automatic embedding of the soft pot tray into the hard tray following sowing and covering with soil.A control system was constructed using the Arduino program development environment.An embedded-hard-tray automatic lowering mechanism and conveyor-belt-based pot-tray embedding system were designed.Dynamics analysis was conducted to derive an equation to describe the embedding process of the soft pot tray into the embedded hard tray.A prototype of the soft-pot-tray automatic embedding system was manufactured and tested.The analytical equation suggested that a minimum linear velocity of 0.86 m/s was required for a complete embedding process.The experimental results showed that the embedded-hard-tray automatic lowering mechanism was reliable and stable as the tray placement success rate was greater than 99%.The successful tray embedding rate was 100%and the seed exposure rate was less than 1%with a linear velocity of the conveyor belt of 0.92 m/s.The experiment findings agreed well with the analytical results.The proposed soft-pot-tray automatic embedding system satisfied the technical specifications for a light-economical pot seedling nursery machine.展开更多
Objective This review aimed to systematically evaluate the evidence on the effects of acupoint catgut embedding （ACE） therapy for patients with polycystic ovary syndrome （PCOS）. Methods Five databases （CBM, CNKI,...Objective This review aimed to systematically evaluate the evidence on the effects of acupoint catgut embedding （ACE） therapy for patients with polycystic ovary syndrome （PCOS）. Methods Five databases （CBM, CNKI, Wanfang Database, VlP Database, and PubMed） were searched to identify relevant studies published before June 2027. The outcomes were resumption of menstruation and serum levels of testosterone （T）. The methodological quality of the included studies was judged using the Cochrane risk of bias tool. The overall level of evidence was judged by the Grading of Recommendations Assessment, Development, and Evaluation （GRADE） criteria. Results Twenty- five randomized controlled trials were included. ACE therapy significantly lowered serum T levels, and patients receiving ACE treatment reported resumption of menstruation. However, these results should be interpreted with caution due to a high risk of randomization and blinding bias, and likely publication bias. The level of evidence for resumption of menstruation and serum T levels was assessed as ＂low＂ and ＂low＂, respectively, using GRADE. Conclusion The current evidence on ACE therapy for PCOS is insufficient to draw firm conclusions due to the poor methodological quality. Future well- designed trials are needed to validate the therapeutic efficacy, safety, and mechanisms of ACE in patients with PCOS.展开更多
OBJECTIVE: To evaluate the clinical effectiveness and safety of acupoint catgut embedding and acupuncture on simple obesity by Meta-analysis. METHODS: Studies on clinical randomized controlled trials of acupoint catgu...OBJECTIVE: To evaluate the clinical effectiveness and safety of acupoint catgut embedding and acupuncture on simple obesity by Meta-analysis. METHODS: Studies on clinical randomized controlled trials of acupoint catgut embedding for simple obesity which were published from January 2015 to November 2020 were searched in Cochrane Central Register of Control Trials(Central), Pub Med, China Science and Technology Journal Database, China National Knowledge Infrastructure Database and Wanfang databases. And those that met the inclusion criteria were screened. Rev Man5.3 was used for Meta-analysis. The “Risk of Bias” tool was used to evaluate the quality of included studies. R studio software was used for the measurement of publication bias. RESULTS: A total of 33 studies were included for Metaanalysis, including 2685 patients with simple obesity. Meta-analysis results showed the comparison of effectiveness rate was relative risk(RR) = 1.12, 95%CI(1.08, 1.16), body mass index(BMI) was mean difference(MD) =-1.12, 95%CI(-2.09,-0.14), waist circumference was MD =-2.14, 95%CI(-4.22,-0.06), and body mass was MD =-2.36, 95%CI(-3.99,-0.73). On the basis of diet and exercise intervention, the effectiveness rate [RR = 1.12, 95%CI(1.05, 1.19)], BMI [MD =-0.88, 95%CI(-1.35,-0.40)], waist circumference [MD =-1.10, 95%CI(-4.27, 2.07)], and body mass [MD =-0.68, 95%CI(-2.90, 1.54)]. The risk of bias of included literatures was low. CONCLUSIONS: Acupoint catgut embedding therapy was slightly better than acupuncture therapy in most of the outcomes. Moreover, the treatment frequency of acupoint catgut embedding is less with larger stimulation intensity, which is more conducive to clinical promotion.展开更多
OBJECTIVE:To assess the efficacy of acupoint catgut embedding(ACE)for simple obesity in preclinical animal experiments.METHODS:We searched the following 14 electronic databases:PubM ed,Cochrane Library,EMBASE,Oriental...OBJECTIVE:To assess the efficacy of acupoint catgut embedding(ACE)for simple obesity in preclinical animal experiments.METHODS:We searched the following 14 electronic databases:PubM ed,Cochrane Library,EMBASE,Oriental Medicine Advanced Searching Integrated System,KoreaMed,Korean Studies Information Service System,Science-on,Research Information Sharing Service,Korea Citation Index,Korea Traditional Knowledge Portal,China Network Knowledge Infrastructure Database,Wanfang Database,Chinese Science and Technology Journal Database,and Chinese Biology Medicine Database,from inception to November 2021 without language limitation.The assessment was performed according to the guidelines of Animal Research:Reporting of in vivo experiments;and Metaanalysis was performed using Reviewer Manager 5.4.1 software.RESULTS:Twenty-four studies involving 813 animals were selected.Meta-analysis showed that ACE was beneficial for weight control[n=40,MD=-50.63,95%CI(-57.59,-43.67),P<0.00001,I 2=0%]and reduced the Lee index[n=40,MD=-18.79,95%CI(-20.01,-17.57),P<0.00001,I 2=0%].However,when efficacy of ACE was compared with that of manual acupuncture,electroacupuncture,or oilistat therapy,statistical difference was not observed between the two groups.CONCLUSIONS:This systematic review suggests that ACE may be efficacious in treating obesity.Moreover,the analyses highlighted the necessity to perform welldesigned,higher-quality experiments.展开更多
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.
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.
基金supported by the National Science and Technology Council(NSTC),Taiwan,under Grants Numbers 112-2622-E-029-009 and 112-2221-E-029-019.
文摘In the domain of knowledge graph embedding,conventional approaches typically transform entities and relations into continuous vector spaces.However,parameter efficiency becomes increasingly crucial when dealing with large-scale knowledge graphs that contain vast numbers of entities and relations.In particular,resource-intensive embeddings often lead to increased computational costs,and may limit scalability and adaptability in practical environ-ments,such as in low-resource settings or real-world applications.This paper explores an approach to knowledge graph representation learning that leverages small,reserved entities and relation sets for parameter-efficient embedding.We introduce a hierarchical attention network designed to refine and maximize the representational quality of embeddings by selectively focusing on these reserved sets,thereby reducing model complexity.Empirical assessments validate that our model achieves high performance on the benchmark dataset with fewer parameters and smaller embedding dimensions.The ablation studies further highlight the impact and contribution of each component in the proposed hierarchical attention structure.
文摘Objective:To explore the effects of acupoint catgut embedding combined with auricular point pressing with beans on symptom management self-efficacy and quality of life in patients with nonalcoholic steatohepatitis(NASH)of liver depression and spleen deficiency type.Methods:Sixty patients with NASH of liver depression and spleen deficiency type admitted to our hospital from January 2021 to December 2023 were selected and divided into an acupoint catgut embedding group(n=30)and a combined group(n=30)using the envelope lottery method.The acupoint catgut embedding group received acupoint catgut embedding intervention,while the combined group received auricular point pressing with beans on the basis of the acupoint catgut embedding group.The two groups were compared in terms of TCM syndrome scores,symptom management self-efficacy[Chronic Disease Self-Efficacy Scale(CDSES)],and quality of life[Chronic Liver Disease Questionnaire(CLDQ)].Results:After intervention,the combined group had lower TCM syndrome scores for both primary and secondary symptoms compared to the acupoint catgut embedding group(P<0.05).The combined group also had higher scores in all dimensions and total score of the CDSES compared to the acupoint catgut embedding group(P<0.05).Similarly,the combined group had higher scores in all dimensions and total score of the CLDQ compared to the acupoint catgut embedding group(P<0.05).Conclusion:Acupoint catgut embedding combined with auricular point pressing with beans can effectively improve TCM symptoms,enhance symptom management self-efficacy,and improve quality of life in patients with NASH of liver depression and spleen deficiency type.
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supported by National Natural Science Foundation of China(61901071,61871062,61771082,U20A20157)Science and Natural Science Foundation of Chongqing,China(cstc2020jcyjzdxmX0024)+1 种基金University Innovation Research Group of Chongqing(CXQT20017)Scientific and Technological Research Program of Chongqing Municipal Education Commission(No.KJZD-K201901301).
文摘Network virtualization is the development trend and inevitable requirement of hybrid wireless sensor networks(HWSNs).Low mapping efficiency and service interruption caused by mobility seriously affect the reliability of sensing tasks and ultimately affect the long-term revenue of the infrastructure providers.In response to these problems,this paper proposes an efficient virtual network embedding algorithm with a reliable service guarantee.Based on the topological attributes of nodes,a method for evaluating the physical network resource importance degree is proposed,and the nodes with rich resources are selected to improve embedding efficiency.Then,a method for evaluating the physical network reliability degree is proposed to predict the probability of mobile sensors providing uninterrupted services.The simulation results show that the proposed algorithm improves the acceptance rate of virtual sensor networks(VSN)embedding requests and the long-term revenue of the infrastructure providers.
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 National Natural Science Foundation of China(No.62006092)Natural Science Research Project of Anhui Educational Committee(No.2023AH030081)+1 种基金2023 New Era Education Provincial Quality Engineering Project(Graduate Education)(No.2023cxcysj103)2024 New Era Education Provincial Quality Engineering Project(Graduate Education)。
文摘Lactate,as a metabolite,plays a significant role in a number of fields,including medical diagnostics,exercise physiology and food science.Traditional methods for lactate measurement often involve expensive and cumbersome instrumentation.This study developed a portable and low-cost lactate measurement system,including independently detectable hardware circuits and user-friendly embedded software,computer,and smartphone applications.The experiment verified that the relative error of the detection current in the device circuit was less than 1%.The electrochemical performance was measured by comparing the[Fe(CN)_(6)]^(3−)/[Fe(CN)_(6)]^(4−)solution with the desktop electrochemical workstation CHI660E,and a nearly consistent chronoamperometry(CA)curve was obtained.Two modified lactate sensors were used for CA testing of lactate.Within the concentration range of 0.1 mmol·L^(−1)to 20 mmol·L^(−1),there was a good linear relationship between lactate concentration and steady-state current,with a correlation coefficient(R2)greater than 0.99 and good repeatability,demonstrating the reliability of the developed device.The lactate measurement system developed in this study not only provides excellent detection performance and reliability,but also achieves portability and low cost,providing a new solution for lactate measurement.
基金supported by the National Natural Science Foundation of China(Nos.52204051,52304046).
文摘In shale gas reservoir stimulation,proppants are essential for sustaining fracture conductivity.However,increasing closing stress causes proppants to embed into the rock matrix,leading to a progressive decline in fracture permeability and conductivity.Furthermore,rock creep contributes to long-term reductions in fracture performance.To elucidate the combined effects of proppant embedding and rock creep on sustained conductivity,this study conducted controlled experiments examining conductivity decay in propped fractures under varying closing stresses,explicitly accounting for both mechanisms.An embedded discrete fracture model was developed to simulate reservoir production under different conductivity decay scenarios,while evaluating the influence of proppant parameters on fracture performance.The results demonstrate that fracture conductivity diminishes rapidly with increasing stress,yet at 50 MPa,the decline becomes less pronounced.Simulated production profiles show strong agreement with actual gas well data,confirming the model’s accuracy and predictive capability.These findings suggest that employing a high proppant concentration with smaller particle size(5 kg/m^(2),70/140 mesh)is effective for maintaining long-term fracture conductivity and enhancing shale gas recovery.This study provides a rigorous framework for optimizing proppant selection and designing stimulation strategies that maximize reservoir performance over time.
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.
基金supported by the National Key R&D Program of China(Grant No.2021YFA1001000)the National Natural Science Foundation of China(Grant Nos.82111530212,U23A20282,and 61971255)+2 种基金the Natural Science Founda-tion of Guangdong Province(Grant No.2021B1515020092)the Shenzhen Bay Laboratory Fund(Grant No.SZBL2020090501014)the Shenzhen Science,Technology and Innovation Commission(Grant Nos.KJZD20231023094659002,JCYJ20220530142809022,and WDZC20220811170401001).
文摘Neural organoids and confocal microscopy have the potential to play an important role in microconnectome research to understand neural patterns.We present PLayer,a plug-and-play embedded neural system,which demonstrates the utilization of sparse confocal microscopy layers to interpolate continuous axial resolution.With an embedded system focused on neural network pruning,image scaling,and post-processing,PLayer achieves high-performance metrics with an average structural similarity index of 0.9217 and a peak signal-to-noise ratio of 27.75 dB,all within 20 s.This represents a significant time saving of 85.71%with simplified image processing.By harnessing statistical map estimation in interpolation and incorporating the Vision Transformer–based Restorer,PLayer ensures 2D layer consistency while mitigating heavy computational dependence.As such,PLayer can reconstruct 3D neural organoid confocal data continuously under limited computational power for the wide acceptance of fundamental connectomics and pattern-related research with embedded devices.
文摘The increasing fluency of advanced language models,such as GPT-3.5,GPT-4,and the recently introduced DeepSeek,challenges the ability to distinguish between human-authored and AI-generated academic writing.This situation is raising significant concerns regarding the integrity and authenticity of academic work.In light of the above,the current research evaluates the effectiveness of Bidirectional Long Short-TermMemory(BiLSTM)networks enhanced with pre-trained GloVe(Global Vectors for Word Representation)embeddings to detect AIgenerated scientific Abstracts drawn from the AI-GA(Artificial Intelligence Generated Abstracts)dataset.Two core BiLSTM variants were assessed:a single-layer approach and a dual-layer design,each tested under static or adaptive embeddings.The single-layer model achieved nearly 97%accuracy with trainable GloVe,occasionally surpassing the deeper model.Despite these gains,neither configuration fully matched the 98.7%benchmark set by an earlier LSTMWord2Vec pipeline.Some runs were over-fitted when embeddings were fine-tuned,whereas static embeddings offered a slightly lower yet stable accuracy of around 96%.This lingering gap reinforces a key ethical and procedural concern:relying solely on automated tools,such as Turnitin’s AI-detection features,to penalize individuals’risks and unjust outcomes.Misclassifications,whether legitimate work is misread as AI-generated or engineered text,evade detection,demonstrating that these classifiers should not stand as the sole arbiters of authenticity.Amore comprehensive approach is warranted,one which weaves model outputs into a systematic process supported by expert judgment and institutional guidelines designed to protect originality.
基金supported by the National Natural Science Foundation of China(62303273,62373226)the National Research Foundation,Singapore through the Medium Sized Center for Advanced Robotics Technology Innovation(WP2.7)
文摘Dear Editor,The letter deals with the distributed state and fault estimation of the whole physical layer for cyber-physical systems(CPSs) when the cyber layer suffers from DoS attacks. With the advancement of embedded computing, communication and related hardware technologies, CPSs have attracted extensive attention and have been widely used in power system, traffic network, refrigeration system and other fields.
基金the funding from the National Natural Science Foundation of China No.52275294the National Key Research and Development Program of China(No.2018YFA0703000)。
文摘Constructing an in vitro vascularized liver tissue model that closely simulates the human liver is crucial for promoting cell proliferation,mimicking physiological heterogeneous structures,and recreating the cellular microenvironment.However,the layer-by-layer printing method is significantly constrained by the rheological properties of the bioink,making it challenging to form complex three-dimensional vascular structures in low-viscosity soft materials.To overcome this limitation,we developed a cross-linkable biphasic embedding medium by mixing low-viscosity biomaterials with gelatin microgel.This medium possesses yield stress and self-healing properties,facilitating efficient and continuous three-dimensional shaping of sacrificial ink within it.By adjusting the printing speed,we controlled the filament diameter,achieving a range from 250μm to 1000μm,and ensuring precise control over ink deposition locations and filament shapes.Using the in situ endothelialization method,we constructed complex vascular structures and ensured close adhesion between hepatocytes and endothelial cells.In vitro experiments demonstrated that the vascularized liver tissue model exhibited enhanced protein synthesis and metabolic function compared to mixed liver tissue.We also investigated the impact of varying vascular densities on liver tissue function.Transcriptome sequencing revealed that liver tissues with higher vascular density exhibited upregulated gene expression in metabolic and angiogenesis-related pathways.In summary,this method is adaptable to various materials,allowing the rheological properties of the supporting bath and the tissue's porosity to be modified using microgels,thus enabling precise regulation of the liver tissue microenvironment.Additionally,it facilitates the rapid construction of three-dimensional vascular structures within liver tissue.The resulting vascularized liver tissue model exhibits enhanced biological functionality,opening new opportunities for biomedical applications.
基金Supported by the Naional Natural Science Fund Project of China:81072883,81173342
文摘Objective To systematically evaluate the effect of acupoint catgut embedding therapy （ACET） for simple obesity. Methods Computer retrieval was used for randomized controlled trials on the treatment effect of simple obesity with ACET in databases of the China National Knowledge Infrastructure （CNKI）, Wanfang Data system, and the China Biology Medicine disc （CBMDisc）. The Jadad Quality Scale was used in the evaluation of included studies. The outcome indicators were analyzed with the Review Manage 5.1 software. Results A total of 16 randomized controlled trials were included finally. The meta-analysis result showed that compared with the control group, there was statistically significance on the total efficiency of using ACET for simple obesity [OR=2.51, 95% confidence interval （1.74, 3.63）, Z=4.91, P〈0.000 01]. The analysis on the literature quality showed that there was only 2 article marked as 3 points. The other 25 articles marked ≤2 points. The quality of published articles was generally low. There were publication biases and the blinding method was seldom used, the losses of follow-up / drop oup / withdraw were reported with less. There were 27 acupoints used in the treatment, which mainly included Tianshu （天枢ST 25）, Zhongwan （中脘 CV 12）, Fenglong （丰隆 ST 40）, Shufen （水分 CV 9）, Qihai （气海 CV 6）, Sanyinjiao （三阴交 SP 6）, Zusnli （足三里 ST 36）, Ashi point, Daheng （大横 SP 25）. The five kinds of catgut embedding needle were injection needles ＋ acupuncture needle, specialized catgut embedding needle, spinal needle, triangular needle, and skin suture needle. Conclusion There is definite efficiency of using ACET in the treatment of simple obesity. However, the clinical efficiency still lacks of sufficient evidences. Therefore, further clinical research should be conducted in the providing of reliable evidences in the clinical decision-making in the future.
基金The authors gratefully acknowledge the financial support from the National Key Research and Development Program of China(Grant No.2018YFD0700703)National Natural Science Foundation of China(Grant No.51675188)and the Earmarked Fund for Modern Agro-industry Technology Research System(Grant No.CARS-01-43).
文摘Most of the commercially-available pot seedling nursery machines are incompatible with soft-pot-trays and are labor-intensive and low in productivity.A soft-pot-tray automatic embedding system was developed in this study to achieve automatic embedding of the soft pot tray into the hard tray following sowing and covering with soil.A control system was constructed using the Arduino program development environment.An embedded-hard-tray automatic lowering mechanism and conveyor-belt-based pot-tray embedding system were designed.Dynamics analysis was conducted to derive an equation to describe the embedding process of the soft pot tray into the embedded hard tray.A prototype of the soft-pot-tray automatic embedding system was manufactured and tested.The analytical equation suggested that a minimum linear velocity of 0.86 m/s was required for a complete embedding process.The experimental results showed that the embedded-hard-tray automatic lowering mechanism was reliable and stable as the tray placement success rate was greater than 99%.The successful tray embedding rate was 100%and the seed exposure rate was less than 1%with a linear velocity of the conveyor belt of 0.92 m/s.The experiment findings agreed well with the analytical results.The proposed soft-pot-tray automatic embedding system satisfied the technical specifications for a light-economical pot seedling nursery machine.
文摘Objective This review aimed to systematically evaluate the evidence on the effects of acupoint catgut embedding （ACE） therapy for patients with polycystic ovary syndrome （PCOS）. Methods Five databases （CBM, CNKI, Wanfang Database, VlP Database, and PubMed） were searched to identify relevant studies published before June 2027. The outcomes were resumption of menstruation and serum levels of testosterone （T）. The methodological quality of the included studies was judged using the Cochrane risk of bias tool. The overall level of evidence was judged by the Grading of Recommendations Assessment, Development, and Evaluation （GRADE） criteria. Results Twenty- five randomized controlled trials were included. ACE therapy significantly lowered serum T levels, and patients receiving ACE treatment reported resumption of menstruation. However, these results should be interpreted with caution due to a high risk of randomization and blinding bias, and likely publication bias. The level of evidence for resumption of menstruation and serum T levels was assessed as ＂low＂ and ＂low＂, respectively, using GRADE. Conclusion The current evidence on ACE therapy for PCOS is insufficient to draw firm conclusions due to the poor methodological quality. Future well- designed trials are needed to validate the therapeutic efficacy, safety, and mechanisms of ACE in patients with PCOS.
基金Supported by National Administration of Traditional Chinese Medicine Project:Innovation Team and Talents Cultivation Program of National Administration of Traditional Chinese Medicine (No. ZYYCXTD-C-202006)。
文摘OBJECTIVE: To evaluate the clinical effectiveness and safety of acupoint catgut embedding and acupuncture on simple obesity by Meta-analysis. METHODS: Studies on clinical randomized controlled trials of acupoint catgut embedding for simple obesity which were published from January 2015 to November 2020 were searched in Cochrane Central Register of Control Trials(Central), Pub Med, China Science and Technology Journal Database, China National Knowledge Infrastructure Database and Wanfang databases. And those that met the inclusion criteria were screened. Rev Man5.3 was used for Meta-analysis. The “Risk of Bias” tool was used to evaluate the quality of included studies. R studio software was used for the measurement of publication bias. RESULTS: A total of 33 studies were included for Metaanalysis, including 2685 patients with simple obesity. Meta-analysis results showed the comparison of effectiveness rate was relative risk(RR) = 1.12, 95%CI(1.08, 1.16), body mass index(BMI) was mean difference(MD) =-1.12, 95%CI(-2.09,-0.14), waist circumference was MD =-2.14, 95%CI(-4.22,-0.06), and body mass was MD =-2.36, 95%CI(-3.99,-0.73). On the basis of diet and exercise intervention, the effectiveness rate [RR = 1.12, 95%CI(1.05, 1.19)], BMI [MD =-0.88, 95%CI(-1.35,-0.40)], waist circumference [MD =-1.10, 95%CI(-4.27, 2.07)], and body mass [MD =-0.68, 95%CI(-2.90, 1.54)]. The risk of bias of included literatures was low. CONCLUSIONS: Acupoint catgut embedding therapy was slightly better than acupuncture therapy in most of the outcomes. Moreover, the treatment frequency of acupoint catgut embedding is less with larger stimulation intensity, which is more conducive to clinical promotion.
基金the Korea Institute of Oriental Medicine(Grant No.KSN1823211 and KSN20234115)。
文摘OBJECTIVE:To assess the efficacy of acupoint catgut embedding(ACE)for simple obesity in preclinical animal experiments.METHODS:We searched the following 14 electronic databases:PubM ed,Cochrane Library,EMBASE,Oriental Medicine Advanced Searching Integrated System,KoreaMed,Korean Studies Information Service System,Science-on,Research Information Sharing Service,Korea Citation Index,Korea Traditional Knowledge Portal,China Network Knowledge Infrastructure Database,Wanfang Database,Chinese Science and Technology Journal Database,and Chinese Biology Medicine Database,from inception to November 2021 without language limitation.The assessment was performed according to the guidelines of Animal Research:Reporting of in vivo experiments;and Metaanalysis was performed using Reviewer Manager 5.4.1 software.RESULTS:Twenty-four studies involving 813 animals were selected.Meta-analysis showed that ACE was beneficial for weight control[n=40,MD=-50.63,95%CI(-57.59,-43.67),P<0.00001,I 2=0%]and reduced the Lee index[n=40,MD=-18.79,95%CI(-20.01,-17.57),P<0.00001,I 2=0%].However,when efficacy of ACE was compared with that of manual acupuncture,electroacupuncture,or oilistat therapy,statistical difference was not observed between the two groups.CONCLUSIONS:This systematic review suggests that ACE may be efficacious in treating obesity.Moreover,the analyses highlighted the necessity to perform welldesigned,higher-quality experiments.
