Objective:To evaluate the effectiveness of surgical combination with traditional Chinese medicine dialectical therapy in three phases for the treatment of intertrochanteric fracture of the femur(IFF).Methods:84 patien...Objective:To evaluate the effectiveness of surgical combination with traditional Chinese medicine dialectical therapy in three phases for the treatment of intertrochanteric fracture of the femur(IFF).Methods:84 patients with IFF admitted to the hospital from December 2022 to December 2024 were selected and randomly divided into two groups using a random number table.The combined group received surgery and traditional Chinese medicine dialectical therapy in three phases,while the control group received surgery alone.The total effective rate,fracture healing time,hip function score,and lower extremity function score were compared between the two groups.Results:The total effective rate was higher in the combined group than in the control group(P<0.05).After treatment,the fracture healing time was shorter in the combined group than in the control group,and the hip function and lower extremity function scores were higher in the combined group than in the control group(P<0.05).Conclusion:Surgical combination with traditional Chinese medicine dialectical therapy in three phases can shorten the fracture healing time of IFF patients and restore their hip and lower extremity function,demonstrating significant efficacy.展开更多
It is well known that Traditional Chinese Medicine(TCM)has two outstanding academic characteristics:the holistic concept comes from Huang Di Nei Jing,and the syndrome differentiation and treatment comes from Shang Han...It is well known that Traditional Chinese Medicine(TCM)has two outstanding academic characteristics:the holistic concept comes from Huang Di Nei Jing,and the syndrome differentiation and treatment comes from Shang Han Lun.These two characteristics denote the two major academic systems of TCM:one is the medical system of Huang Di Nei Jing,also named syndrome differentiation and treatment system of Zang-Fu organs and meridians,focuses on theoretical exploration,which highlights functional connection and emphasizes philosophical thinking.The treatment in this system is based on physiological functions by taking Zang-Fu organs as the main body,Qi,blood,essence,and body fluid as the auxiliary body,and the meridians and collaterals as the connection channels.The other is the syndrome differentiation and treatment system of the six meridians,which emphasizes clinical practice.It encompasses the idea that the six meridians govern various diseases,emphasizes the disease sites and divisional treatment,and pays attention to the precision and appropriateness of prescription-syndrome differentiation.These two academic systems,with mutual influences and relations,are both the essence and pearl of TCM,nevertheless,there are obvious differences between the two in clinical application,so they should be distinguished.This paper will elaborate on the connection and difference between them,and how to organically combine the two systems for better application in clinical practice of TCM.展开更多
1|Introduction The Federal Republic of Somalia,often perceived as linguistically homogeneous,is home to a rich tapestry of dialects and minority languages that reflect its diverse cultural heritage.While Somali is the...1|Introduction The Federal Republic of Somalia,often perceived as linguistically homogeneous,is home to a rich tapestry of dialects and minority languages that reflect its diverse cultural heritage.While Somali is the official medium of communication,it is divided into two major dialects:Maxaa Tiri(spoken by approximately 60%of the population)and Maay(spoken by approximately 20%of the population)[1].Minority languages such as Bravanese(also known as Chimwiini or Chimbalazi),Mushunguli,Benadiri Somali,and Kibajuni are spoken by smaller communities,particularly in the southern and coastal regions[1].展开更多
Arabic Dialect Identification(DID)is a task in Natural Language Processing(NLP)that involves determining the dialect of a given piece of text in Arabic.The state-of-the-art solutions for DID are built on various deep ...Arabic Dialect Identification(DID)is a task in Natural Language Processing(NLP)that involves determining the dialect of a given piece of text in Arabic.The state-of-the-art solutions for DID are built on various deep neural networks that commonly learn the representation of sentences in response to a given dialect.Despite the effectiveness of these solutions,the performance heavily relies on the amount of labeled examples,which is labor-intensive to atain and may not be readily available in real-world scenarios.To alleviate the burden of labeling data,this paper introduces a novel solution that leverages unlabeled corpora to boost performance on the DID task.Specifically,we design an architecture that enables learning the shared information between labeled and unlabeled texts through a gradient reversal layer.The key idea is to penalize the model for learning source dataset specific features and thus enable it to capture common knowledge regardless of the label.Finally,we evaluate the proposed solution on benchmark datasets for DID.Our extensive experiments show that it performs signifcantly better,especially,with sparse labeled data.By comparing our approach with existing Pre-trained Language Models(PLMs),we achieve a new state-of-the-art performance in the DID field.The code will be available on GitHub upon the paper's acceptance.展开更多
Wearable pressure sensors capable of adhering comfortably to the skin hold great promise in sound detection.However,current intelligent speech assistants based on pressure sensors can only recognize standard languages...Wearable pressure sensors capable of adhering comfortably to the skin hold great promise in sound detection.However,current intelligent speech assistants based on pressure sensors can only recognize standard languages,which hampers effective communication for non-standard language people.Here,we prepare an ultralight Ti_(3)C_(2)T_(x)MXene/chitosan/polyvinylidene difluoride composite aerogel with a detection range of 6.25 Pa-1200 k Pa,rapid response/recovery time,and low hysteresis(13.69%).The wearable aerogel pressure sensor can detect speech information through the throat muscle vibrations without any interference,allowing for accurate recognition of six dialects(96.2%accuracy)and seven different words(96.6%accuracy)with the assistance of convolutional neural networks.This work represents a significant step forward in silent speech recognition for human–machine interaction and physiological signal monitoring.展开更多
文摘Objective:To evaluate the effectiveness of surgical combination with traditional Chinese medicine dialectical therapy in three phases for the treatment of intertrochanteric fracture of the femur(IFF).Methods:84 patients with IFF admitted to the hospital from December 2022 to December 2024 were selected and randomly divided into two groups using a random number table.The combined group received surgery and traditional Chinese medicine dialectical therapy in three phases,while the control group received surgery alone.The total effective rate,fracture healing time,hip function score,and lower extremity function score were compared between the two groups.Results:The total effective rate was higher in the combined group than in the control group(P<0.05).After treatment,the fracture healing time was shorter in the combined group than in the control group,and the hip function and lower extremity function scores were higher in the combined group than in the control group(P<0.05).Conclusion:Surgical combination with traditional Chinese medicine dialectical therapy in three phases can shorten the fracture healing time of IFF patients and restore their hip and lower extremity function,demonstrating significant efficacy.
基金Supported by Central Government Major Budget Adjustment Program(the Research on the Medicinal Properties of Brazilian Ginseng,Tonico,and Guarana,No.2060302)。
文摘It is well known that Traditional Chinese Medicine(TCM)has two outstanding academic characteristics:the holistic concept comes from Huang Di Nei Jing,and the syndrome differentiation and treatment comes from Shang Han Lun.These two characteristics denote the two major academic systems of TCM:one is the medical system of Huang Di Nei Jing,also named syndrome differentiation and treatment system of Zang-Fu organs and meridians,focuses on theoretical exploration,which highlights functional connection and emphasizes philosophical thinking.The treatment in this system is based on physiological functions by taking Zang-Fu organs as the main body,Qi,blood,essence,and body fluid as the auxiliary body,and the meridians and collaterals as the connection channels.The other is the syndrome differentiation and treatment system of the six meridians,which emphasizes clinical practice.It encompasses the idea that the six meridians govern various diseases,emphasizes the disease sites and divisional treatment,and pays attention to the precision and appropriateness of prescription-syndrome differentiation.These two academic systems,with mutual influences and relations,are both the essence and pearl of TCM,nevertheless,there are obvious differences between the two in clinical application,so they should be distinguished.This paper will elaborate on the connection and difference between them,and how to organically combine the two systems for better application in clinical practice of TCM.
文摘1|Introduction The Federal Republic of Somalia,often perceived as linguistically homogeneous,is home to a rich tapestry of dialects and minority languages that reflect its diverse cultural heritage.While Somali is the official medium of communication,it is divided into two major dialects:Maxaa Tiri(spoken by approximately 60%of the population)and Maay(spoken by approximately 20%of the population)[1].Minority languages such as Bravanese(also known as Chimwiini or Chimbalazi),Mushunguli,Benadiri Somali,and Kibajuni are spoken by smaller communities,particularly in the southern and coastal regions[1].
基金supported by the Deanship of Scientific Research at King Khalid University through Small Groups funding(Project Grant No.RGP1/243/45)The funding was awarded to Dr.Mohammed Abker.And Natural Science Foundation of China under Grant 61901388.
文摘Arabic Dialect Identification(DID)is a task in Natural Language Processing(NLP)that involves determining the dialect of a given piece of text in Arabic.The state-of-the-art solutions for DID are built on various deep neural networks that commonly learn the representation of sentences in response to a given dialect.Despite the effectiveness of these solutions,the performance heavily relies on the amount of labeled examples,which is labor-intensive to atain and may not be readily available in real-world scenarios.To alleviate the burden of labeling data,this paper introduces a novel solution that leverages unlabeled corpora to boost performance on the DID task.Specifically,we design an architecture that enables learning the shared information between labeled and unlabeled texts through a gradient reversal layer.The key idea is to penalize the model for learning source dataset specific features and thus enable it to capture common knowledge regardless of the label.Finally,we evaluate the proposed solution on benchmark datasets for DID.Our extensive experiments show that it performs signifcantly better,especially,with sparse labeled data.By comparing our approach with existing Pre-trained Language Models(PLMs),we achieve a new state-of-the-art performance in the DID field.The code will be available on GitHub upon the paper's acceptance.
基金supported by the National Nature Science Foundation of China(No.62122030,62333008,62371205,52103208)National Key Research and Development Program of China(No.2021YFB3201300)+1 种基金Application and Basic Research of Jilin Province(20130102010 JC)Fundamental Research Funds for the Central Universities,Jilin Provincial Science and Technology Development Program(20230101072JC)。
文摘Wearable pressure sensors capable of adhering comfortably to the skin hold great promise in sound detection.However,current intelligent speech assistants based on pressure sensors can only recognize standard languages,which hampers effective communication for non-standard language people.Here,we prepare an ultralight Ti_(3)C_(2)T_(x)MXene/chitosan/polyvinylidene difluoride composite aerogel with a detection range of 6.25 Pa-1200 k Pa,rapid response/recovery time,and low hysteresis(13.69%).The wearable aerogel pressure sensor can detect speech information through the throat muscle vibrations without any interference,allowing for accurate recognition of six dialects(96.2%accuracy)and seven different words(96.6%accuracy)with the assistance of convolutional neural networks.This work represents a significant step forward in silent speech recognition for human–machine interaction and physiological signal monitoring.
