BACKGROUND The induced-membrane technique was initially described by Masquelet as an effective treatment for large bone defects,especially those caused by infection.Here,we report a case of chronic osteomyelitis of th...BACKGROUND The induced-membrane technique was initially described by Masquelet as an effective treatment for large bone defects,especially those caused by infection.Here,we report a case of chronic osteomyelitis of the radius associated with a 9 cm bone defect,which was filled with a large allogeneic cortical bone graft from a bone bank.Complete bony union was achieved after 14 months of follow-up.Previous studies have used autogenous bone as the primary bone source for the Masquelet technique;in our case,the exclusive use of allografts is as successful as the use of autologous bone grafts.With the advent of bone banks,it is possible to obtain an unlimited amount of allograft,and the Masquelet technique may be further improved based on this new way of bone grafting.CASE SUMMARY In this study,we reported a case of repair of a long bone defect in a 40-year-old male patient,which was characterized by the utilization of allograft cortical bone combined with the Masquelet technique for the treatment of the patient's long bone defect in the forearm.The patient's results of functional recovery of the forearm were surprising,which further deepens the scope of application of Masquelet technique and helps to strengthen the efficacy of Masquelet technique in the treatment of long bones indeed.CONCLUSION Allograft cortical bone combined with the Masquelet technique provides a new method of treatment to large bone defect.展开更多
With the rapid advancement of visual generative models such as Generative Adversarial Networks(GANs)and stable Diffusion,the creation of highly realistic Deepfake through automated forgery has significantly progressed...With the rapid advancement of visual generative models such as Generative Adversarial Networks(GANs)and stable Diffusion,the creation of highly realistic Deepfake through automated forgery has significantly progressed.This paper examines the advancements inDeepfake detection and defense technologies,emphasizing the shift from passive detection methods to proactive digital watermarking techniques.Passive detection methods,which involve extracting features from images or videos to identify forgeries,encounter challenges such as poor performance against unknown manipulation techniques and susceptibility to counter-forensic tactics.In contrast,proactive digital watermarking techniques embed specificmarkers into images or videos,facilitating real-time detection and traceability,thereby providing a preemptive defense againstDeepfake content.We offer a comprehensive analysis of digitalwatermarking-based forensic techniques,discussing their advantages over passivemethods and highlighting four key benefits:real-time detection,embedded defense,resistance to tampering,and provision of legal evidence.Additionally,the paper identifies gaps in the literature concerning proactive forensic techniques and suggests future research directions,including cross-domain watermarking and adaptive watermarking strategies.By systematically classifying and comparing existing techniques,this review aims to contribute valuable insights for the development of more effective proactive defense strategies in Deepfake forensics.展开更多
Lung cancer continues to be a leading cause of cancer-related deaths worldwide,emphasizing the critical need for improved diagnostic techniques.Early detection of lung tumors significantly increases the chances of suc...Lung cancer continues to be a leading cause of cancer-related deaths worldwide,emphasizing the critical need for improved diagnostic techniques.Early detection of lung tumors significantly increases the chances of successful treatment and survival.However,current diagnostic methods often fail to detect tumors at an early stage or to accurately pinpoint their location within the lung tissue.Single-model deep learning technologies for lung cancer detection,while beneficial,cannot capture the full range of features present in medical imaging data,leading to incomplete or inaccurate detection.Furthermore,it may not be robust enough to handle the wide variability in medical images due to different imaging conditions,patient anatomy,and tumor characteristics.To overcome these disadvantages,dual-model or multi-model approaches can be employed.This research focuses on enhancing the detection of lung cancer by utilizing a combination of two learning models:a Convolutional Neural Network(CNN)for categorization and the You Only Look Once(YOLOv8)architecture for real-time identification and pinpointing of tumors.CNNs automatically learn to extract hierarchical features from raw image data,capturing patterns such as edges,textures,and complex structures that are crucial for identifying lung cancer.YOLOv8 incorporates multiscale feature extraction,enabling the detection of tumors of varying sizes and scales within a single image.This is particularly beneficial for identifying small or irregularly shaped tumors that may be challenging to detect.Furthermore,through the utilization of cutting-edge data augmentation methods,such as Deep Convolutional Generative Adversarial Networks(DCGAN),the suggested approach can handle the issue of limited data and boost the models’ability to learn from diverse and comprehensive datasets.The combined method not only improved accuracy and localization but also ensured efficient real-time processing,which is crucial for practical clinical applications.The CNN achieved an accuracy of 97.67%in classifying lung tissues into healthy and cancerous categories.The YOLOv8 model achieved an Intersection over Union(IoU)score of 0.85 for tumor localization,reflecting high precision in detecting and marking tumor boundaries within the images.Finally,the incorporation of synthetic images generated by DCGAN led to a 10%improvement in both the CNN classification accuracy and YOLOv8 detection performance.展开更多
Despite advancements in neuroimaging,false positive diagnoses of intracranial aneurysms remain a significant concern.This article examines the causes,prevalence,and implications of such false-positive diagnoses.We dis...Despite advancements in neuroimaging,false positive diagnoses of intracranial aneurysms remain a significant concern.This article examines the causes,prevalence,and implications of such false-positive diagnoses.We discuss how conditions like arterial occlusion with vascular stump formation and infundibular widening can mimic aneurysms,particularly in the anterior circulation.The article compares various imaging modalities,including computer tomography angiogram,magnetic resonance imaging/angiography,and digital subtraction angiogram,highlighting their strengths and limitations.We emphasize the im-portance of accurate differentiation to avoid unnecessary surgical interventions.The potential of emerging technologies,such as high-resolution vessel wall ima-ging and deep neural networks for automated detection,is explored as promising avenues for improving diagnostic accuracy.This manuscript underscores the need for continued research and clinical vigilance in the diagnosis of intracranial aneurysms.展开更多
Every second, a large volume of useful data is created in social media about the various kind of online purchases and in another forms of reviews. Particularly, purchased products review data is enormously growing in ...Every second, a large volume of useful data is created in social media about the various kind of online purchases and in another forms of reviews. Particularly, purchased products review data is enormously growing in different database repositories every day. Most of the review data are useful to new customers for theier further purchases as well as existing companies to view customers feedback about various products. Data Mining and Machine Leaning techniques are familiar to analyse such kind of data to visualise and know the potential use of the purchased items through online. The customers are making quality of products through their sentiments about the purchased items from different online companies. In this research work, it is analysed sentiments of Headphone review data, which is collected from online repositories. For the analysis of Headphone review data, some of the Machine Learning techniques like Support Vector Machines, Naive Bayes, Decision Trees and Random Forest Algorithms and a Hybrid method are applied to find the quality via the customers’ sentiments. The accuracy and performance of the taken algorithms are also analysed based on the three types of sentiments such as positive, negative and neutral.展开更多
Surgical advancements have transformed colorectal cancer treatment, withcomplete mesocolic excision (CME) becoming a crucial method to guaranteeoncological safety and effectiveness. The article by Yadav emphasized the...Surgical advancements have transformed colorectal cancer treatment, withcomplete mesocolic excision (CME) becoming a crucial method to guaranteeoncological safety and effectiveness. The article by Yadav emphasized the significanceof CME in attaining optimal resection margins, thorough lymph nodedissection, and enhanced long-term survival rates. The adjunctive function of D3lymphadenectomy, emphasizing the clearance of lymphatic drainage along thesupplying vessels, was also addressed. CME with central vascular ligation, basedon the principles of total mesorectal excision for rectal cancer, entails en bloc tumorresection and precise dissection along the embryological planes, thus diminishingrecurrence and improving survival rates. The viability and safety of minimallyinvasive techniques, such as laparoscopic CME, have been confirmed;however,technical difficulties remain owing to the intricate vascular anatomy. Roboticassistedsurgery presents potential benefits, including accurate lymphatic dissectionand intracorporeal anastomosis. However, evidence demonstrating itssuperiority over laparoscopic techniques is scarce owing to high costs and prolongedduration. This study promotes the global standardization of CME as anessential element of modern colorectal cancer surgery. CME epitomizes contemporaryoncological practices, requiring widespread adoption to achieve superiorityin colon cancer management.展开更多
In recent years,studies focusing on the conversion of renewable lignin-derived oxygenates(LDOs)have emphasized their potential as alternatives to fossil-based products.However,LDOs,existing as complex aromatic mixture...In recent years,studies focusing on the conversion of renewable lignin-derived oxygenates(LDOs)have emphasized their potential as alternatives to fossil-based products.However,LDOs,existing as complex aromatic mixtures with diverse oxygen-containing functional groups,pose a challenge as they cannot be easily separated via distillation for direct utilization.A promising solution to this challenge lies in the efficient removal of oxygen-containing functional groups from LDOs through hydrodeoxygenation(HDO),aiming to yield biomass products with singular components.However,the high dissociation energy of the carbon-oxygen bond,coupled with its similarity to the hydrogenation energy of the benzene ring,creates a competition between deoxygenation and benzene ring hydrogenation.Considering hydrogen consumption and lignin properties,the preference is directed towards generating aromatic hydrocarbons rather than saturated components.Thus,the goal is to selectively remove oxygen-containing functional groups while preserving the benzene ring structure.Studies on LDOs conversion have indicated that the design of active components and optimization of reaction conditions play pivotal roles in achieving selective deoxygenation,but a summary of the correlation between these factors and the reaction mechanism is lacking.This review addresses this gap in knowledge by firstly summarizing the various reaction pathways for HDO of LDOs.It explores the impact of catalyst design strategies,including morphology modulation,elemental doping,and surface modification,on the adsorption-desorption dynamics between reactants and catalysts.Secondly,we delve into the application of advanced techniques such as spectroscopic techniques and computational modeling,aiding in uncovering the true active sites in HDO reactions and understanding the interaction of reactive reactants with catalyst surface-interfaces.Additionally,fundamental insights into selective deoxygenation obtained through these techniques are highlighted.Finally,we outline the challenges that lie ahead in the design of highly active and selective HDO catalysts.These challenges include the development of detection tools for reactive species with high activity at low concentrations,the study of reaction medium-catalyst interactions,and the development of theoretical models that more closely approximate real reaction situations.Addressing these challenges will pave the way for the development of efficient and selective HDO catalysts,thus advancing the field of renewable LDOs conversion.展开更多
AIM:To evaluate the effect of femtosecond laser small incision lenticule extraction(SMILE)on the binocular visual function in myopic patients with glasses-free threedimensional(3D)technique.METHODS:Totally 50 myopic p...AIM:To evaluate the effect of femtosecond laser small incision lenticule extraction(SMILE)on the binocular visual function in myopic patients with glasses-free threedimensional(3D)technique.METHODS:Totally 50 myopic patients(39 females and 11 males)with SMILE were enrolled in this prospective study.The glasses-free 3D technique was used to evaluate the binocular visual function in these subjects including static stereopsis,dynamic stereopsis,foveal suppression,and binocular balance point of signal to noise ratio(s/n ratio).All subjects received measurements in 1d before operation,and 1d,1wk,and 1mo postoperatively.RESULTS:Both static and dynamic stereopsis showed no significant difference after SMILE.The foveal suppression improved significantly 1wk and 1mo after SMILE(P=0.005 and P=0.007 respectively).The binocular balance point of signal to noise ratio showed a significant improvement 1d,1wk and 1mo after SMILE for both eyes(P<0.001 for each eye respectively).CONCLUSION:Glasses-free 3D technique can be used to evaluate the effect of SMILE on the binocular visual function in myopic patients perceptively,and SMILE can improve both foveal suppression and binocular imbalance in these patients.展开更多
The purpose of this study was to explore the application of TCM-appropriate technology in neurogenic bladder rehabilitation nursing.Firstly,the background and contents of the study were introduced.Then,it summarizes t...The purpose of this study was to explore the application of TCM-appropriate technology in neurogenic bladder rehabilitation nursing.Firstly,the background and contents of the study were introduced.Then,it summarizes the definition and development of TCM-appropriate technology and expounds the main therapy and application of TCM-appropriate technology in the rehabilitation nursing field.Besides,the pathophysiological characteristics,rehabilitation nursing measures,and rehabilitation difficulties of the neurogenic bladder are described.Then,the application method,effect and prospect of TCM-suitable technology in rehabilitation nursing of neurogenic bladder are described.In addition,the object,method,result analysis,and conclusion of the experimental study are introduced,the main results of this study are summarized,and the future research direction is prospected.In summary,this study aims to provide effective TCM-appropriate technology for neurogenic bladder rehabilitation nursing and provide a reference for clinical practice and theoretical research in related fields.展开更多
The development of intestinal anastomosis techniques,including hand suturing,stapling,and compression anastomoses,has been a significant advancement in surgical practice.These methods aim to prevent leakage and minimi...The development of intestinal anastomosis techniques,including hand suturing,stapling,and compression anastomoses,has been a significant advancement in surgical practice.These methods aim to prevent leakage and minimize tissue fibrosis,which can lead to stricture formation.The healing process involves various phases:hemostasis and inflammation,proliferation,and remodeling.Mechanical staplers and sutures can cause inflammation and fibrosis due to the release of profibrotic chemokines.Compression anastomosis devices,including those made of nickel-titanium alloy,offer a minimally invasive option for various surgical challenges and have shown safety and efficacy.However,despite advancements,anastomotic techniques are evaluated based on leakage risk,with complications being a primary concern.Newer devices like Magnamosis use magnetic rings for compression anastomosis,demonstrating greater strength and patency compared to stapling.Magnetic technology is also being explored for other medical treatments.While there are promising results,particularly in animal models,the realworld application in humans is limited,and further research is needed to assess their safety and practicality.展开更多
Epilepsy can be defined as a dysfunction of the brain network,and each type of epilepsy involves different brain-network changes that are implicated diffe rently in the control and propagation of interictal or ictal d...Epilepsy can be defined as a dysfunction of the brain network,and each type of epilepsy involves different brain-network changes that are implicated diffe rently in the control and propagation of interictal or ictal discharges.Gaining more detailed information on brain network alterations can help us to further understand the mechanisms of epilepsy and pave the way for brain network-based precise therapeutic approaches in clinical practice.An increasing number of advanced neuroimaging techniques and electrophysiological techniques such as diffusion tensor imaging-based fiber tra ctography,diffusion kurtosis imaging-based fiber tractography,fiber ball imagingbased tra ctography,electroencephalography,functional magnetic resonance imaging,magnetoencephalography,positron emission tomography,molecular imaging,and functional ultrasound imaging have been extensively used to delineate epileptic networks.In this review,we summarize the relevant neuroimaging and neuroelectrophysiological techniques for assessing structural and functional brain networks in patients with epilepsy,and extensively analyze the imaging mechanisms,advantages,limitations,and clinical application ranges of each technique.A greater focus on emerging advanced technologies,new data analysis software,a combination of multiple techniques,and the construction of personalized virtual epilepsy models can provide a theoretical basis to better understand the brain network mechanisms of epilepsy and make surgical decisions.展开更多
BACKGROUND Postoperative delirium,particularly prevalent in elderly patients after abdominal cancer surgery,presents significant challenges in clinical management.AIM To develop a synthetic minority oversampling techn...BACKGROUND Postoperative delirium,particularly prevalent in elderly patients after abdominal cancer surgery,presents significant challenges in clinical management.AIM To develop a synthetic minority oversampling technique(SMOTE)-based model for predicting postoperative delirium in elderly abdominal cancer patients.METHODS In this retrospective cohort study,we analyzed data from 611 elderly patients who underwent abdominal malignant tumor surgery at our hospital between September 2020 and October 2022.The incidence of postoperative delirium was recorded for 7 d post-surgery.Patients were divided into delirium and non-delirium groups based on the occurrence of postoperative delirium or not.A multivariate logistic regression model was used to identify risk factors and develop a predictive model for postoperative delirium.The SMOTE technique was applied to enhance the model by oversampling the delirium cases.The model’s predictive accuracy was then validated.RESULTS In our study involving 611 elderly patients with abdominal malignant tumors,multivariate logistic regression analysis identified significant risk factors for postoperative delirium.These included the Charlson comorbidity index,American Society of Anesthesiologists classification,history of cerebrovascular disease,surgical duration,perioperative blood transfusion,and postoperative pain score.The incidence rate of postoperative delirium in our study was 22.91%.The original predictive model(P1)exhibited an area under the receiver operating characteristic curve of 0.862.In comparison,the SMOTE-based logistic early warning model(P2),which utilized the SMOTE oversampling algorithm,showed a slightly lower but comparable area under the curve of 0.856,suggesting no significant difference in performance between the two predictive approaches.CONCLUSION This study confirms that the SMOTE-enhanced predictive model for postoperative delirium in elderly abdominal tumor patients shows performance equivalent to that of traditional methods,effectively addressing data imbalance.展开更多
Rechargeable battery cycling performance and related safety have been persistent concerns.It is crucial to decipher the capacity fading induced by electrode material failure via a range of techniques.Among these,synch...Rechargeable battery cycling performance and related safety have been persistent concerns.It is crucial to decipher the capacity fading induced by electrode material failure via a range of techniques.Among these,synchrotron-based X-ray techniques with high flux and brightness play a key role in understanding degradation mechanisms.In this comprehensive review,we summarize recent advancements in degra-dation modes and mechanisms that were revealed by synchrotron X-ray methodologies.Subsequently,an overview of X-ray absorption spectroscopy and X-ray scattering techniques is introduced for charac-terizing failure phenomena at local coordination atomic environment and long-range order crystal struc-ture scale,respectively.At last,we envision the future of exploring material failure mechanism.展开更多
Manipulating the expression of synaptic plasticity of neuromorphic devices provides fascinating opportunities to develop hardware platforms for artifi-cial intelligence.However,great efforts have been devoted to explo...Manipulating the expression of synaptic plasticity of neuromorphic devices provides fascinating opportunities to develop hardware platforms for artifi-cial intelligence.However,great efforts have been devoted to exploring biomimetic mechanisms of plasticity simulation in the last few years.Recent progress in various plasticity modulation techniques has pushed the research of synaptic electronics from static plasticity simulation to dynamic plasticity modulation,improving the accuracy of neuromorphic computing and providing strategies for implementing neuromorphic sensing functions.Herein,several fascinating strategies for synap-tic plasticity modulation through chemical techniques,device structure design,and physical signal sensing are reviewed.For chemical techniques,the underly-ing mechanisms for the modification of functional materials were clarified and its effect on the expression of synaptic plasticity was also highlighted.Based on device structure design,the reconfigurable operation of neuromorphic devices was well demonstrated to achieve programmable neuromorphic functions.Besides,integrating the sensory units with neuromorphic processing circuits paved a new way to achieve human-like intelligent perception under the modulation of physical signals such as light,strain,and temperature.Finally,considering that the relevant technology is still in the basic exploration stage,some prospects or development suggestions are put forward to promote the development of neuromorphic devices.展开更多
Recognizing handwritten characters remains a critical and formidable challenge within the realm of computervision. Although considerable strides have been made in enhancing English handwritten character recognitionthr...Recognizing handwritten characters remains a critical and formidable challenge within the realm of computervision. Although considerable strides have been made in enhancing English handwritten character recognitionthrough various techniques, deciphering Arabic handwritten characters is particularly intricate. This complexityarises from the diverse array of writing styles among individuals, coupled with the various shapes that a singlecharacter can take when positioned differently within document images, rendering the task more perplexing. Inthis study, a novel segmentation method for Arabic handwritten scripts is suggested. This work aims to locatethe local minima of the vertical and diagonal word image densities to precisely identify the segmentation pointsbetween the cursive letters. The proposed method starts with pre-processing the word image without affectingits main features, then calculates the directions pixel density of the word image by scanning it vertically and fromangles 30° to 90° to count the pixel density fromall directions and address the problem of overlapping letters, whichis a commonly attitude in writing Arabic texts by many people. Local minima and thresholds are also determinedto identify the ideal segmentation area. The proposed technique is tested on samples obtained fromtwo datasets: Aself-curated image dataset and the IFN/ENIT dataset. The results demonstrate that the proposed method achievesa significant improvement in the proportions of cursive segmentation of 92.96% on our dataset, as well as 89.37%on the IFN/ENIT dataset.展开更多
BACKGROUND The rotator cuff is located below the acromion and deltoid muscles and comprises multiple tendons that wrap around the humeral head,maintaining shoulder joint stability.AIM To explore the effect of electroa...BACKGROUND The rotator cuff is located below the acromion and deltoid muscles and comprises multiple tendons that wrap around the humeral head,maintaining shoulder joint stability.AIM To explore the effect of electroacupuncture combined with rehabilitation techniques on shoulder function in patients with rotator cuff injuries.METHODS We selected 97 patients with rotator cuff injuries treated in the People's Hospital of Yuhuan from February 2020 to May 2023.Patients were grouped using the envelope method.RESULTS After treatment,the study group’s treatment effective rate was 94.90%(46/49 patients),significantly higher than that in the control group(79.17%,38/48 cases;P<0.05).Before treatment,there was no difference in Constant Murley Score(CMS)scores,shoulder mobility,or 36-Item Short Form Health Survey(SF-36)scale scores(P>0.05).Compared with those before treatment,the CMS scores(including pain,daily living ability,shoulder mobility,and muscle strength),all aspects of shoulder mobility(forward flexion,posterior extension,external rotation,internal rotation),and SF-36 scale scores(including physiological,psychological,emotional,physical,vitality,and health status)were higher in both groups after treatment and significantly higher in the study group(P<0.05).There was no difference in the occurrence of complications between the two treatment groups(P>0.05).CONCLUSION Electroacupuncture combined with rehabilitation techniques has a good treatment effect on patients with rotator cuff injuries,helps accelerate the recovery of shoulder function,improves the quality of life,and is highly safe.展开更多
Reliable long-term settlement prediction of a high embankment relates to mountain infrastructure safety.This study developed a novel hybrid model(NHM)that combines a joint denoising technique with an enhanced gray wol...Reliable long-term settlement prediction of a high embankment relates to mountain infrastructure safety.This study developed a novel hybrid model(NHM)that combines a joint denoising technique with an enhanced gray wolf optimizer(EGWO)-n-support vector regression(n-SVR)method.High-embankment field measurements were preprocessed using the joint denoising technique,which in-cludes complete ensemble empirical mode decomposition,singular value decomposition,and wavelet packet transform.Furthermore,high-embankment settlements were predicted using the EGWO-n-SVR method.In this method,the standard gray wolf optimizer(GWO)was improved to obtain the EGWO to better tune the n-SVR model hyperparameters.The proposed NHM was then tested in two case studies.Finally,the influences of the data division ratio and kernel function on the EGWO-n-SVR forecasting performance and prediction efficiency were investigated.The results indicate that the NHM suppresses noise and restores details in high-embankment field measurements.Simultaneously,the NHM out-performs other alternative prediction methods in prediction accuracy and robustness.This demonstrates that the proposed NHM is effective in predicting high-embankment settlements with noisy field mea-surements.Moreover,the appropriate data division ratio and kernel function for EGWO-n-SVR are 7:3 and radial basis function,respectively.展开更多
文摘BACKGROUND The induced-membrane technique was initially described by Masquelet as an effective treatment for large bone defects,especially those caused by infection.Here,we report a case of chronic osteomyelitis of the radius associated with a 9 cm bone defect,which was filled with a large allogeneic cortical bone graft from a bone bank.Complete bony union was achieved after 14 months of follow-up.Previous studies have used autogenous bone as the primary bone source for the Masquelet technique;in our case,the exclusive use of allografts is as successful as the use of autologous bone grafts.With the advent of bone banks,it is possible to obtain an unlimited amount of allograft,and the Masquelet technique may be further improved based on this new way of bone grafting.CASE SUMMARY In this study,we reported a case of repair of a long bone defect in a 40-year-old male patient,which was characterized by the utilization of allograft cortical bone combined with the Masquelet technique for the treatment of the patient's long bone defect in the forearm.The patient's results of functional recovery of the forearm were surprising,which further deepens the scope of application of Masquelet technique and helps to strengthen the efficacy of Masquelet technique in the treatment of long bones indeed.CONCLUSION Allograft cortical bone combined with the Masquelet technique provides a new method of treatment to large bone defect.
基金supported by the National Fund Cultivation Project from China People’s Police University(Grant Number:JJPY202402)National Natural Science Foundation of China(Grant Number:62172165).
文摘With the rapid advancement of visual generative models such as Generative Adversarial Networks(GANs)and stable Diffusion,the creation of highly realistic Deepfake through automated forgery has significantly progressed.This paper examines the advancements inDeepfake detection and defense technologies,emphasizing the shift from passive detection methods to proactive digital watermarking techniques.Passive detection methods,which involve extracting features from images or videos to identify forgeries,encounter challenges such as poor performance against unknown manipulation techniques and susceptibility to counter-forensic tactics.In contrast,proactive digital watermarking techniques embed specificmarkers into images or videos,facilitating real-time detection and traceability,thereby providing a preemptive defense againstDeepfake content.We offer a comprehensive analysis of digitalwatermarking-based forensic techniques,discussing their advantages over passivemethods and highlighting four key benefits:real-time detection,embedded defense,resistance to tampering,and provision of legal evidence.Additionally,the paper identifies gaps in the literature concerning proactive forensic techniques and suggests future research directions,including cross-domain watermarking and adaptive watermarking strategies.By systematically classifying and comparing existing techniques,this review aims to contribute valuable insights for the development of more effective proactive defense strategies in Deepfake forensics.
文摘Lung cancer continues to be a leading cause of cancer-related deaths worldwide,emphasizing the critical need for improved diagnostic techniques.Early detection of lung tumors significantly increases the chances of successful treatment and survival.However,current diagnostic methods often fail to detect tumors at an early stage or to accurately pinpoint their location within the lung tissue.Single-model deep learning technologies for lung cancer detection,while beneficial,cannot capture the full range of features present in medical imaging data,leading to incomplete or inaccurate detection.Furthermore,it may not be robust enough to handle the wide variability in medical images due to different imaging conditions,patient anatomy,and tumor characteristics.To overcome these disadvantages,dual-model or multi-model approaches can be employed.This research focuses on enhancing the detection of lung cancer by utilizing a combination of two learning models:a Convolutional Neural Network(CNN)for categorization and the You Only Look Once(YOLOv8)architecture for real-time identification and pinpointing of tumors.CNNs automatically learn to extract hierarchical features from raw image data,capturing patterns such as edges,textures,and complex structures that are crucial for identifying lung cancer.YOLOv8 incorporates multiscale feature extraction,enabling the detection of tumors of varying sizes and scales within a single image.This is particularly beneficial for identifying small or irregularly shaped tumors that may be challenging to detect.Furthermore,through the utilization of cutting-edge data augmentation methods,such as Deep Convolutional Generative Adversarial Networks(DCGAN),the suggested approach can handle the issue of limited data and boost the models’ability to learn from diverse and comprehensive datasets.The combined method not only improved accuracy and localization but also ensured efficient real-time processing,which is crucial for practical clinical applications.The CNN achieved an accuracy of 97.67%in classifying lung tissues into healthy and cancerous categories.The YOLOv8 model achieved an Intersection over Union(IoU)score of 0.85 for tumor localization,reflecting high precision in detecting and marking tumor boundaries within the images.Finally,the incorporation of synthetic images generated by DCGAN led to a 10%improvement in both the CNN classification accuracy and YOLOv8 detection performance.
文摘电磁矢量传感器多输入多输出(electromagnetic vector sensor multiple-input multiple-output,EMVS-MIMO)雷达是一种新兴技术,可实现二维波达角(2D-DOA)估计。针对单基地稀疏阵列EMVS-MIMO雷达,提出一种基于旋转不变性信号参数估计技术ESPRIT(estimation of signal parameters via rotational invariance techniques)的降复杂度(reduced-complexity,RC)信号参数估计算法,能够实现对目标2D-DOA的快速估计。首先,对接收阵列数据进行RC处理,以消除阵列冗余数据;其次,利用ESPRIT可获得高分辨率的俯仰角估计,由于阵列的稀疏性,该估计值具有模糊性;再次,利用矢量叉积技术获得具有无模糊特性的2D-DOA;最后,利用无模糊的俯仰角估计对有周期模糊的估计进行解模糊,获得具有高分辨率、无模糊特性的俯仰角估计。该算法适用于大规模EMVS-MIMO雷达系统,且相比现有的ESPRIT-Like算法拥有更高的估计精度,通过MATLAB仿真验证了算法的有效性。
文摘Despite advancements in neuroimaging,false positive diagnoses of intracranial aneurysms remain a significant concern.This article examines the causes,prevalence,and implications of such false-positive diagnoses.We discuss how conditions like arterial occlusion with vascular stump formation and infundibular widening can mimic aneurysms,particularly in the anterior circulation.The article compares various imaging modalities,including computer tomography angiogram,magnetic resonance imaging/angiography,and digital subtraction angiogram,highlighting their strengths and limitations.We emphasize the im-portance of accurate differentiation to avoid unnecessary surgical interventions.The potential of emerging technologies,such as high-resolution vessel wall ima-ging and deep neural networks for automated detection,is explored as promising avenues for improving diagnostic accuracy.This manuscript underscores the need for continued research and clinical vigilance in the diagnosis of intracranial aneurysms.
文摘Every second, a large volume of useful data is created in social media about the various kind of online purchases and in another forms of reviews. Particularly, purchased products review data is enormously growing in different database repositories every day. Most of the review data are useful to new customers for theier further purchases as well as existing companies to view customers feedback about various products. Data Mining and Machine Leaning techniques are familiar to analyse such kind of data to visualise and know the potential use of the purchased items through online. The customers are making quality of products through their sentiments about the purchased items from different online companies. In this research work, it is analysed sentiments of Headphone review data, which is collected from online repositories. For the analysis of Headphone review data, some of the Machine Learning techniques like Support Vector Machines, Naive Bayes, Decision Trees and Random Forest Algorithms and a Hybrid method are applied to find the quality via the customers’ sentiments. The accuracy and performance of the taken algorithms are also analysed based on the three types of sentiments such as positive, negative and neutral.
文摘Surgical advancements have transformed colorectal cancer treatment, withcomplete mesocolic excision (CME) becoming a crucial method to guaranteeoncological safety and effectiveness. The article by Yadav emphasized the significanceof CME in attaining optimal resection margins, thorough lymph nodedissection, and enhanced long-term survival rates. The adjunctive function of D3lymphadenectomy, emphasizing the clearance of lymphatic drainage along thesupplying vessels, was also addressed. CME with central vascular ligation, basedon the principles of total mesorectal excision for rectal cancer, entails en bloc tumorresection and precise dissection along the embryological planes, thus diminishingrecurrence and improving survival rates. The viability and safety of minimallyinvasive techniques, such as laparoscopic CME, have been confirmed;however,technical difficulties remain owing to the intricate vascular anatomy. Roboticassistedsurgery presents potential benefits, including accurate lymphatic dissectionand intracorporeal anastomosis. However, evidence demonstrating itssuperiority over laparoscopic techniques is scarce owing to high costs and prolongedduration. This study promotes the global standardization of CME as anessential element of modern colorectal cancer surgery. CME epitomizes contemporaryoncological practices, requiring widespread adoption to achieve superiorityin colon cancer management.
基金supported by the National Natural Science Foundation of China,Pilot Group Program of the Research Fund for International Senior Scientists(22250710676)National Natural Science Foundation of China(22078064,22378062,22304028)+1 种基金Natural Science Foundation of Fujian Province(2021J02009)Tianjin University-Fuzhou University Independent Innovation Fund Cooperation Project(TF2023-1,TF2023-8).
文摘In recent years,studies focusing on the conversion of renewable lignin-derived oxygenates(LDOs)have emphasized their potential as alternatives to fossil-based products.However,LDOs,existing as complex aromatic mixtures with diverse oxygen-containing functional groups,pose a challenge as they cannot be easily separated via distillation for direct utilization.A promising solution to this challenge lies in the efficient removal of oxygen-containing functional groups from LDOs through hydrodeoxygenation(HDO),aiming to yield biomass products with singular components.However,the high dissociation energy of the carbon-oxygen bond,coupled with its similarity to the hydrogenation energy of the benzene ring,creates a competition between deoxygenation and benzene ring hydrogenation.Considering hydrogen consumption and lignin properties,the preference is directed towards generating aromatic hydrocarbons rather than saturated components.Thus,the goal is to selectively remove oxygen-containing functional groups while preserving the benzene ring structure.Studies on LDOs conversion have indicated that the design of active components and optimization of reaction conditions play pivotal roles in achieving selective deoxygenation,but a summary of the correlation between these factors and the reaction mechanism is lacking.This review addresses this gap in knowledge by firstly summarizing the various reaction pathways for HDO of LDOs.It explores the impact of catalyst design strategies,including morphology modulation,elemental doping,and surface modification,on the adsorption-desorption dynamics between reactants and catalysts.Secondly,we delve into the application of advanced techniques such as spectroscopic techniques and computational modeling,aiding in uncovering the true active sites in HDO reactions and understanding the interaction of reactive reactants with catalyst surface-interfaces.Additionally,fundamental insights into selective deoxygenation obtained through these techniques are highlighted.Finally,we outline the challenges that lie ahead in the design of highly active and selective HDO catalysts.These challenges include the development of detection tools for reactive species with high activity at low concentrations,the study of reaction medium-catalyst interactions,and the development of theoretical models that more closely approximate real reaction situations.Addressing these challenges will pave the way for the development of efficient and selective HDO catalysts,thus advancing the field of renewable LDOs conversion.
基金Supported by Sichuan Science and Technology Program(No.23NSFSC0856).
文摘AIM:To evaluate the effect of femtosecond laser small incision lenticule extraction(SMILE)on the binocular visual function in myopic patients with glasses-free threedimensional(3D)technique.METHODS:Totally 50 myopic patients(39 females and 11 males)with SMILE were enrolled in this prospective study.The glasses-free 3D technique was used to evaluate the binocular visual function in these subjects including static stereopsis,dynamic stereopsis,foveal suppression,and binocular balance point of signal to noise ratio(s/n ratio).All subjects received measurements in 1d before operation,and 1d,1wk,and 1mo postoperatively.RESULTS:Both static and dynamic stereopsis showed no significant difference after SMILE.The foveal suppression improved significantly 1wk and 1mo after SMILE(P=0.005 and P=0.007 respectively).The binocular balance point of signal to noise ratio showed a significant improvement 1d,1wk and 1mo after SMILE for both eyes(P<0.001 for each eye respectively).CONCLUSION:Glasses-free 3D technique can be used to evaluate the effect of SMILE on the binocular visual function in myopic patients perceptively,and SMILE can improve both foveal suppression and binocular imbalance in these patients.
文摘The purpose of this study was to explore the application of TCM-appropriate technology in neurogenic bladder rehabilitation nursing.Firstly,the background and contents of the study were introduced.Then,it summarizes the definition and development of TCM-appropriate technology and expounds the main therapy and application of TCM-appropriate technology in the rehabilitation nursing field.Besides,the pathophysiological characteristics,rehabilitation nursing measures,and rehabilitation difficulties of the neurogenic bladder are described.Then,the application method,effect and prospect of TCM-suitable technology in rehabilitation nursing of neurogenic bladder are described.In addition,the object,method,result analysis,and conclusion of the experimental study are introduced,the main results of this study are summarized,and the future research direction is prospected.In summary,this study aims to provide effective TCM-appropriate technology for neurogenic bladder rehabilitation nursing and provide a reference for clinical practice and theoretical research in related fields.
文摘The development of intestinal anastomosis techniques,including hand suturing,stapling,and compression anastomoses,has been a significant advancement in surgical practice.These methods aim to prevent leakage and minimize tissue fibrosis,which can lead to stricture formation.The healing process involves various phases:hemostasis and inflammation,proliferation,and remodeling.Mechanical staplers and sutures can cause inflammation and fibrosis due to the release of profibrotic chemokines.Compression anastomosis devices,including those made of nickel-titanium alloy,offer a minimally invasive option for various surgical challenges and have shown safety and efficacy.However,despite advancements,anastomotic techniques are evaluated based on leakage risk,with complications being a primary concern.Newer devices like Magnamosis use magnetic rings for compression anastomosis,demonstrating greater strength and patency compared to stapling.Magnetic technology is also being explored for other medical treatments.While there are promising results,particularly in animal models,the realworld application in humans is limited,and further research is needed to assess their safety and practicality.
基金supported by the Natural Science Foundation of Sichuan Province of China,Nos.2022NSFSC1545 (to YG),2022NSFSC1387 (to ZF)the Natural Science Foundation of Chongqing of China,Nos.CSTB2022NSCQ-LZX0038,cstc2021ycjh-bgzxm0035 (both to XT)+3 种基金the National Natural Science Foundation of China,No.82001378 (to XT)the Joint Project of Chongqing Health Commission and Science and Technology Bureau,No.2023QNXM009 (to XT)the Science and Technology Research Program of Chongqing Education Commission of China,No.KJQN202200435 (to XT)the Chongqing Talents:Exceptional Young Talents Project,No.CQYC202005014 (to XT)。
文摘Epilepsy can be defined as a dysfunction of the brain network,and each type of epilepsy involves different brain-network changes that are implicated diffe rently in the control and propagation of interictal or ictal discharges.Gaining more detailed information on brain network alterations can help us to further understand the mechanisms of epilepsy and pave the way for brain network-based precise therapeutic approaches in clinical practice.An increasing number of advanced neuroimaging techniques and electrophysiological techniques such as diffusion tensor imaging-based fiber tra ctography,diffusion kurtosis imaging-based fiber tractography,fiber ball imagingbased tra ctography,electroencephalography,functional magnetic resonance imaging,magnetoencephalography,positron emission tomography,molecular imaging,and functional ultrasound imaging have been extensively used to delineate epileptic networks.In this review,we summarize the relevant neuroimaging and neuroelectrophysiological techniques for assessing structural and functional brain networks in patients with epilepsy,and extensively analyze the imaging mechanisms,advantages,limitations,and clinical application ranges of each technique.A greater focus on emerging advanced technologies,new data analysis software,a combination of multiple techniques,and the construction of personalized virtual epilepsy models can provide a theoretical basis to better understand the brain network mechanisms of epilepsy and make surgical decisions.
基金Supported by Discipline Advancement Program of Shanghai Fourth People’s Hospital,No.SY-XKZT-2020-2013.
文摘BACKGROUND Postoperative delirium,particularly prevalent in elderly patients after abdominal cancer surgery,presents significant challenges in clinical management.AIM To develop a synthetic minority oversampling technique(SMOTE)-based model for predicting postoperative delirium in elderly abdominal cancer patients.METHODS In this retrospective cohort study,we analyzed data from 611 elderly patients who underwent abdominal malignant tumor surgery at our hospital between September 2020 and October 2022.The incidence of postoperative delirium was recorded for 7 d post-surgery.Patients were divided into delirium and non-delirium groups based on the occurrence of postoperative delirium or not.A multivariate logistic regression model was used to identify risk factors and develop a predictive model for postoperative delirium.The SMOTE technique was applied to enhance the model by oversampling the delirium cases.The model’s predictive accuracy was then validated.RESULTS In our study involving 611 elderly patients with abdominal malignant tumors,multivariate logistic regression analysis identified significant risk factors for postoperative delirium.These included the Charlson comorbidity index,American Society of Anesthesiologists classification,history of cerebrovascular disease,surgical duration,perioperative blood transfusion,and postoperative pain score.The incidence rate of postoperative delirium in our study was 22.91%.The original predictive model(P1)exhibited an area under the receiver operating characteristic curve of 0.862.In comparison,the SMOTE-based logistic early warning model(P2),which utilized the SMOTE oversampling algorithm,showed a slightly lower but comparable area under the curve of 0.856,suggesting no significant difference in performance between the two predictive approaches.CONCLUSION This study confirms that the SMOTE-enhanced predictive model for postoperative delirium in elderly abdominal tumor patients shows performance equivalent to that of traditional methods,effectively addressing data imbalance.
基金supported by the U.S.National Science Foundation (2208972,2120559,and 2323117)
文摘Rechargeable battery cycling performance and related safety have been persistent concerns.It is crucial to decipher the capacity fading induced by electrode material failure via a range of techniques.Among these,synchrotron-based X-ray techniques with high flux and brightness play a key role in understanding degradation mechanisms.In this comprehensive review,we summarize recent advancements in degra-dation modes and mechanisms that were revealed by synchrotron X-ray methodologies.Subsequently,an overview of X-ray absorption spectroscopy and X-ray scattering techniques is introduced for charac-terizing failure phenomena at local coordination atomic environment and long-range order crystal struc-ture scale,respectively.At last,we envision the future of exploring material failure mechanism.
基金financial support from the National Natural Science Foundation of China(Nos.62104017 and 52072204)Beijing Institute of Technology Research Fund Program for Young Scholars.
文摘Manipulating the expression of synaptic plasticity of neuromorphic devices provides fascinating opportunities to develop hardware platforms for artifi-cial intelligence.However,great efforts have been devoted to exploring biomimetic mechanisms of plasticity simulation in the last few years.Recent progress in various plasticity modulation techniques has pushed the research of synaptic electronics from static plasticity simulation to dynamic plasticity modulation,improving the accuracy of neuromorphic computing and providing strategies for implementing neuromorphic sensing functions.Herein,several fascinating strategies for synap-tic plasticity modulation through chemical techniques,device structure design,and physical signal sensing are reviewed.For chemical techniques,the underly-ing mechanisms for the modification of functional materials were clarified and its effect on the expression of synaptic plasticity was also highlighted.Based on device structure design,the reconfigurable operation of neuromorphic devices was well demonstrated to achieve programmable neuromorphic functions.Besides,integrating the sensory units with neuromorphic processing circuits paved a new way to achieve human-like intelligent perception under the modulation of physical signals such as light,strain,and temperature.Finally,considering that the relevant technology is still in the basic exploration stage,some prospects or development suggestions are put forward to promote the development of neuromorphic devices.
文摘Recognizing handwritten characters remains a critical and formidable challenge within the realm of computervision. Although considerable strides have been made in enhancing English handwritten character recognitionthrough various techniques, deciphering Arabic handwritten characters is particularly intricate. This complexityarises from the diverse array of writing styles among individuals, coupled with the various shapes that a singlecharacter can take when positioned differently within document images, rendering the task more perplexing. Inthis study, a novel segmentation method for Arabic handwritten scripts is suggested. This work aims to locatethe local minima of the vertical and diagonal word image densities to precisely identify the segmentation pointsbetween the cursive letters. The proposed method starts with pre-processing the word image without affectingits main features, then calculates the directions pixel density of the word image by scanning it vertically and fromangles 30° to 90° to count the pixel density fromall directions and address the problem of overlapping letters, whichis a commonly attitude in writing Arabic texts by many people. Local minima and thresholds are also determinedto identify the ideal segmentation area. The proposed technique is tested on samples obtained fromtwo datasets: Aself-curated image dataset and the IFN/ENIT dataset. The results demonstrate that the proposed method achievesa significant improvement in the proportions of cursive segmentation of 92.96% on our dataset, as well as 89.37%on the IFN/ENIT dataset.
文摘BACKGROUND The rotator cuff is located below the acromion and deltoid muscles and comprises multiple tendons that wrap around the humeral head,maintaining shoulder joint stability.AIM To explore the effect of electroacupuncture combined with rehabilitation techniques on shoulder function in patients with rotator cuff injuries.METHODS We selected 97 patients with rotator cuff injuries treated in the People's Hospital of Yuhuan from February 2020 to May 2023.Patients were grouped using the envelope method.RESULTS After treatment,the study group’s treatment effective rate was 94.90%(46/49 patients),significantly higher than that in the control group(79.17%,38/48 cases;P<0.05).Before treatment,there was no difference in Constant Murley Score(CMS)scores,shoulder mobility,or 36-Item Short Form Health Survey(SF-36)scale scores(P>0.05).Compared with those before treatment,the CMS scores(including pain,daily living ability,shoulder mobility,and muscle strength),all aspects of shoulder mobility(forward flexion,posterior extension,external rotation,internal rotation),and SF-36 scale scores(including physiological,psychological,emotional,physical,vitality,and health status)were higher in both groups after treatment and significantly higher in the study group(P<0.05).There was no difference in the occurrence of complications between the two treatment groups(P>0.05).CONCLUSION Electroacupuncture combined with rehabilitation techniques has a good treatment effect on patients with rotator cuff injuries,helps accelerate the recovery of shoulder function,improves the quality of life,and is highly safe.
基金We acknowledge the funding support from the National Natural Science Foundation of China(Grant No.51808462)the Natural Science Foundation Project of Sichuan Province,China(Grant No.2023NSFSC0346)the Science and Technology Project of Inner Mongolia Transportation Department,China(Grant No.NJ-2022-14).
文摘Reliable long-term settlement prediction of a high embankment relates to mountain infrastructure safety.This study developed a novel hybrid model(NHM)that combines a joint denoising technique with an enhanced gray wolf optimizer(EGWO)-n-support vector regression(n-SVR)method.High-embankment field measurements were preprocessed using the joint denoising technique,which in-cludes complete ensemble empirical mode decomposition,singular value decomposition,and wavelet packet transform.Furthermore,high-embankment settlements were predicted using the EGWO-n-SVR method.In this method,the standard gray wolf optimizer(GWO)was improved to obtain the EGWO to better tune the n-SVR model hyperparameters.The proposed NHM was then tested in two case studies.Finally,the influences of the data division ratio and kernel function on the EGWO-n-SVR forecasting performance and prediction efficiency were investigated.The results indicate that the NHM suppresses noise and restores details in high-embankment field measurements.Simultaneously,the NHM out-performs other alternative prediction methods in prediction accuracy and robustness.This demonstrates that the proposed NHM is effective in predicting high-embankment settlements with noisy field mea-surements.Moreover,the appropriate data division ratio and kernel function for EGWO-n-SVR are 7:3 and radial basis function,respectively.
