Inflatable penile prosthesis(IPP)implantation is the gold standard treatment for patients with erectile dysfunction who are refractory to medical therapy.The standard placement of the reservoir in the space of Retzius...Inflatable penile prosthesis(IPP)implantation is the gold standard treatment for patients with erectile dysfunction who are refractory to medical therapy.The standard placement of the reservoir in the space of Retzius(SOR)may be contraindicated in patients with prior pelvic or abdominal surgery due to altered anatomy and increased risk of complications.This has led to the development of alternative ectopic reservoir placement techniques.In this narrative review,we summarize the literature on various ectopic reservoir approaches,including low and high submuscular placements,submuscular techniques with counter incisions or transfascial fixation,midline submuscular placement,subcutaneous placement,and lateral retroperitoneal approaches.We describe the surgical methods,outcomes,and complication rates associated with each technique.While most methods demonstrate low complication and revision rates,direct comparisons remain limited due to heterogeneity and lack of prospective data.This review highlights the importance of individualized technique selection based on prior surgical history,body habitus,and surgeon experience.As ectopic placement becomes more widely adopted,familiarity with multiple approaches is essential for prosthetic surgeons.展开更多
BACKGROUND Due to the increasing rate of thyroid nodules diagnosis,and the desire to avoid the unsightly cervical scar,remote thyroidectomies were invented and are increasingly performed.Transoral endoscopic thyroidec...BACKGROUND Due to the increasing rate of thyroid nodules diagnosis,and the desire to avoid the unsightly cervical scar,remote thyroidectomies were invented and are increasingly performed.Transoral endoscopic thyroidectomy vestibular approach and trans-areolar approaches(TAA)are the two most commonly used remote approaches.No previous meta-analysis has compared postoperative infections and swallowing difficulties among the two procedures.AIM To compared the same among patients undergoing lobectomy for unilateral thyroid carcinoma/benign thyroid nodule.METHODS We searched PubMed MEDLINE,Google Scholar,and Cochrane Library from the date of the first published article up to August 2025.The term used were transoral thyroidectomy vestibular approach,trans areolar thyroidectomy,scarless thyroidectomy,remote thyroidectomy,infections,postoperative,inflammation,dysphagia,and swallowing difficulties.We identified 130 studies,of them,30 full texts were screened and only six studies were included in the final meta-analysis.RESULTS Postoperative infections were not different between the two approaches,odd ratio=1.33,95%confidence interval:0.50-3.53,theχ2 was 1.92 and the P-value for overall effect of 0.57.Similarly,transient swallowing difficulty was not different between the two forms of surgery,with odd ratio=0.91,95%confidence interval:0.35-2.40;theχ2 was 1.32,and the P-value for overall effect of 0.85.CONCLUSION No significant statistical differences were evident between trans-oral endoscopic Mirghani H.Infections and swallowing difficulty in scarless thyroidectomy WJCC https://www.wjgnet.com 2 January 6,2026 Volume 14 Issue 1 thyroidectomy vestibular approach and trans-areolar approach regarding postoperative infection and transient swallowing difficulties.Further longer randomized trials are needed.展开更多
Currently,the number of patients with myopia is increasing rapidly across the globe.Traditional Chinese medicine(TCM),with its long history and rich experience,has shown promise in effectively managing and treating th...Currently,the number of patients with myopia is increasing rapidly across the globe.Traditional Chinese medicine(TCM),with its long history and rich experience,has shown promise in effectively managing and treating this condition.Nevertheless,considering the vast amount of research that is currently being conducted,focusing on the utilization of TCM in the management of myopia,there is an urgent requirement for a thorough and comprehensive review.The review would serve to clarify the practical applications of TCM within this specific field,and it would also aim to elucidate the underlying mechanisms that are at play,providing a deeper understanding of how TCM principles can be effectively integrated into modern medical practices.Here,some modern medical pathogenesis of myopia and appropriate TCM techniques studies are summarized in the prevention and treatment of myopia.Further,we discussed the potential mechanisms and the future research directions of TCM against myopia.Identifying these mechanisms is crucial for understanding how TCM can be effectively utilized in this context.The combination of various TCM methods or the combination of traditional Chinese and Western medicine is of great significance for the prevention and control of myopia in the future.展开更多
With the increasing emphasis on personal information protection,encryption through security protocols has emerged as a critical requirement in data transmission and reception processes.Nevertheless,IoT ecosystems comp...With the increasing emphasis on personal information protection,encryption through security protocols has emerged as a critical requirement in data transmission and reception processes.Nevertheless,IoT ecosystems comprise heterogeneous networks where outdated systems coexist with the latest devices,spanning a range of devices from non-encrypted ones to fully encrypted ones.Given the limited visibility into payloads in this context,this study investigates AI-based attack detection methods that leverage encrypted traffic metadata,eliminating the need for decryption and minimizing system performance degradation—especially in light of these heterogeneous devices.Using the UNSW-NB15 and CICIoT-2023 dataset,encrypted and unencrypted traffic were categorized according to security protocol,and AI-based intrusion detection experiments were conducted for each traffic type based on metadata.To mitigate the problem of class imbalance,eight different data sampling techniques were applied.The effectiveness of these sampling techniques was then comparatively analyzed using two ensemble models and three Deep Learning(DL)models from various perspectives.The experimental results confirmed that metadata-based attack detection is feasible using only encrypted traffic.In the UNSW-NB15 dataset,the f1-score of encrypted traffic was approximately 0.98,which is 4.3%higher than that of unencrypted traffic(approximately 0.94).In addition,analysis of the encrypted traffic in the CICIoT-2023 dataset using the same method showed a significantly lower f1-score of roughly 0.43,indicating that the quality of the dataset and the preprocessing approach have a substantial impact on detection performance.Furthermore,when data sampling techniques were applied to encrypted traffic,the recall in the UNSWNB15(Encrypted)dataset improved by up to 23.0%,and in the CICIoT-2023(Encrypted)dataset by 20.26%,showing a similar level of improvement.Notably,in CICIoT-2023,f1-score and Receiver Operation Characteristic-Area Under the Curve(ROC-AUC)increased by 59.0%and 55.94%,respectively.These results suggest that data sampling can have a positive effect even in encrypted environments.However,the extent of the improvement may vary depending on data quality,model architecture,and sampling strategy.展开更多
Synaptic pruning is a crucial process in synaptic refinement,eliminating unstable synaptic connections in neural circuits.This process is triggered and regulated primarily by spontaneous neural activity and experience...Synaptic pruning is a crucial process in synaptic refinement,eliminating unstable synaptic connections in neural circuits.This process is triggered and regulated primarily by spontaneous neural activity and experience-dependent mechanisms.The pruning process involves multiple molecular signals and a series of regulatory activities governing the“eat me”and“don't eat me”states.Under physiological conditions,the interaction between glial cells and neurons results in the clearance of unnecessary synapses,maintaining normal neural circuit functionality via synaptic pruning.Alterations in genetic and environmental factors can lead to imbalanced synaptic pruning,thus promoting the occurrence and development of autism spectrum disorder,schizophrenia,Alzheimer's disease,and other neurological disorders.In this review,we investigated the molecular mechanisms responsible for synaptic pruning during neural development.We focus on how synaptic pruning can regulate neural circuits and its association with neurological disorders.Furthermore,we discuss the application of emerging optical and imaging technologies to observe synaptic structure and function,as well as their potential for clinical translation.Our aim was to enhance our understanding of synaptic pruning during neural development,including the molecular basis underlying the regulation of synaptic function and the dynamic changes in synaptic density,and to investigate the potential role of these mechanisms in the pathophysiology of neurological diseases,thus providing a theoretical foundation for the treatment of neurological disorders.展开更多
In this special issue of Neuroscience Bulletin, the topics range over emerging techniques from the nanoscopic to the macroscopic scales. At the nanoscopic level, new ways to obtain images at the individual protein le...In this special issue of Neuroscience Bulletin, the topics range over emerging techniques from the nanoscopic to the macroscopic scales. At the nanoscopic level, new ways to obtain images at the individual protein level in synapses take the re- construction of synaptic architecture to a new level, while using chromophores to disable specific proteins at selected subcellular locations allows the assessment of their functional roles in such dynamic processes as growth-cone extension and cell division. The subtle influences of axonal chan- nels and receptors on neurotransmission are revealed by recording from the blebs induced by axotomy, while methods from cloning to chemical computation are being applied to dissecting the structural-functional rules by which ion channels operatet41.展开更多
Objective： To sum up 7 patients with cervicothoracic vertebrae tumors （Cr to T3） from March 1999 and May 2002, who underwent operative treatment via anterior approaches. Methods ：The anterior approaches included l...Objective： To sum up 7 patients with cervicothoracic vertebrae tumors （Cr to T3） from March 1999 and May 2002, who underwent operative treatment via anterior approaches. Methods ：The anterior approaches included low anterior cervical approach and high transthoracic approach. In 5 cases of segments of T1 and above involved, the low anterior cervical approaches were adopted, otherwise the high transthoracic approaches were used（2 cases）. Excision of tumor was carried out according to demands of the Weinstein-Boriani-Biagini （WBB） staging system. Spine stability was reconstructed by bone autografting and instrumentation. There were 4 cases of primary tumor and 3 of metastases. Their mean age was 45. 1 years （23 to 66）. The mean follow-up was 18.9 months （3 to 45）. Results were evaluated by occurrence of complications, improvement of symptoms, local recurrence and mortality. Results： All patients stood surgery well. No significant complications occurred during and after operation. Local pain was significantly alleviated and neurological deficit was improved at least one Frankel grade. Three patients died. Local tumor control was obtained in 6 patients （85.7 % ） until the end of follow-up. Conclusion.-Our experience showed that via low anterior cervical approach and high transthoracic approach, the cervicothoracic vertebrae tumor could be excised safely and adequately. Moreover, excision of tumor according to the WBB surgical staging system and reconstruction of spine stability have made great contribution to local tumor control and the neurological function improvement.展开更多
Construction engineering and management(CEM)has become increasingly complicated with the increasing size of engineering projects under different construction environments,motivating the digital transformation of CEM.T...Construction engineering and management(CEM)has become increasingly complicated with the increasing size of engineering projects under different construction environments,motivating the digital transformation of CEM.To contribute to a better understanding of the state of the art of smart techniques for engineering projects,this paper provides a comprehensive review of multi-criteria decision-making(MCDM)techniques,intelligent techniques,and their applications in CEM.First,a comprehensive framework detailing smart technologies for construction projects is developed.Next,the characteristics of CEM are summarized.A bibliometric review is then conducted to investigate the keywords,journals,and clusters related to the application of smart techniques in CEM during 2000-2022.Recent advancements in intelligent techniques are also discussed under the following six topics:①big data technology;②computer vision;③speech recognition;④natural language processing;⑤machine learning;and⑥knowledge representation,understanding,and reasoning.The applications of smart techniques are then illustrated via underground space exploitation.Finally,future research directions for the sustainable development of smart construction are highlighted.展开更多
Advancements in molecular approaches have been utilized to breed crops with a wide range of economically valuable traits to develop superior cultivars.This review provides a concise overview of modern breakthroughs in...Advancements in molecular approaches have been utilized to breed crops with a wide range of economically valuable traits to develop superior cultivars.This review provides a concise overview of modern breakthroughs in molecular plant production.Genotyping and high-throughput phenotyping methods for predictive plant breeding are briefly discussed.In this study,we explore contemporary molecular breeding techniques for producing desirable crop varieties.These techniques include cisgenesis,clustered regularly interspaced short palindromic repeat(CRISPR/Cas9)gene editing,haploid induction,and de novo domestication.We examine the speed breeding approach-a strategy for cultivating plants under controlled conditions.We further highlight the significance of modern breeding technologies in efficiently utilizing agricultural resources for crop production in urban areas.The deciphering of crop genomes has led to the development of extensive DNA markers,quantitative trait loci(QTLs),and pangenomes associated with various desirable crop traits.This shift to the genotypic selection of crops considerably expedites the plant breeding process.Based on the plant population used,the connection between genotypic and phenotypic data provides several genetic elements,including genes,markers,and alleles that can be used in genomic breeding and gene editing.The integration of speed breeding with genomic-assisted breeding and cutting-edge genome editing tools has made it feasible to rapidly manipulate and generate multiple crop cycles and accelerate the plant breeding process.Breakthroughs in molecular techniques have led to substantial improvements in modern breeding methods.展开更多
Precise transverse emittance assessment in electron beams is crucial for advancing high-brightness beam injectors.As opposed to intricate methodologies that use specialized devices,quadrupole focusing strength scannin...Precise transverse emittance assessment in electron beams is crucial for advancing high-brightness beam injectors.As opposed to intricate methodologies that use specialized devices,quadrupole focusing strength scanning(Q-scanning)techniques offer notable advantages for various injectors owing to their inherent convenience and cost-effectiveness.However,their stringent approximation conditions lead to inevitable errors in practical operation,thereby limiting their widespread application.This study addressed these challenges by revisiting the analytical derivation procedure and investigating the effects of the underlying approximation conditions.Preliminary corrections were explored through a combination of data processing analysis and numerical simulations.Furthermore,based on theoretical derivations,virtual measurements using beam dynamics calculations were employed to evaluate the correction reliability.Subsequent experimental validations were performed at the Huazhong University of Science and Technology injector to verify the effectiveness of the proposed compensation method.Both the virtual and experimental results confirm the feasibility and reliability of the enhanced Q-scanning-based diagnosis for transverse emittance in typical beam injectors operating under common conditions.Through the integration of these corrections and compensations,enhanced Q-scanning-based techniques emerge as promising alternatives to traditional emittance diagnosis methods.展开更多
This paper presents a high-fidelity lumpedparameter(LP)thermal model(HF-LPTM)for permanent magnet synchronous machines(PMSMs)in electric vehicle(EV)applications,where various cooling techniques are considered,includin...This paper presents a high-fidelity lumpedparameter(LP)thermal model(HF-LPTM)for permanent magnet synchronous machines(PMSMs)in electric vehicle(EV)applications,where various cooling techniques are considered,including frame forced air/liquid cooling,oil jet cooling for endwinding,and rotor shaft cooling.To address the temperature misestimation in the LP thermal modelling due to assumptions of concentrated loss input and uniform heat flows,the developed HF-LPTM introduces two compensation thermal resistances for the winding and PM components,which are analytically derived from the multi-dimensional heat transfer equations and are robust against different load/thermal conditions.As validated by the finite element analysis method and experiments,the conventional LPTMs exhibit significant winding temperature deviations,while the proposed HF-LPTM can accurately predict both the midpoint and average temperatures.The developed HFLPTM is further used to assess the effectiveness of various cooling techniques under different scenarios,i.e.,steady-state thermal states under the rated load condition,and transient temperature profiles under city,freeway,and hybrid(city+freeway)driving cycles.Results indicate that no single cooling technique can maintain both winding and PM temperatures within safety limits.The combination of frame liquid cooling and oil jet cooling for end winding can sufficiently mitigate PMSM thermal stress in EV applications.展开更多
In this paper, a time-varying rain characterization and diurnal variation in the Ku-band satellite systems simulated with synthetic storm techniques (SST) over a tropical location in Nigeria have been presented. Three...In this paper, a time-varying rain characterization and diurnal variation in the Ku-band satellite systems simulated with synthetic storm techniques (SST) over a tropical location in Nigeria have been presented. Three years’ rain rate time-series data measured by a raingauge located inside the Federal University of Technology Akure, Nigeria were utilized for the purpose of this work. The analysis is based on the CDF of one-minute rain rate;time-series simulated annual/seasonal and diurnal rain rate, rain attenuation statistics and fade margins observed over four time intervals: 00:00-06:00, 06:00-12:00, 12:00-18:00 and 18:00-24:00. In addition, comparison was also made between the synthesized values and rain attenuation statistics, at 12.245 GHz for a hypothetical downlink from EUTELSAT W4/W7 satellite in the area. It could be observed that at 99.99% link availability, the fade margin as high as ~20 dB may be required at Ku band uplink frequency bands in this area. We also observed that the communication downlinks working in the early morning and early to late in the evening hours must be compensated with an appropriate Down-Link Power Control (DLPC) for optimum performances during severe atmospheric influences in the region.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
Conductor materials with good mechanical performance as well as high electrical and thermal conductivities are particularly important to break through the current bottle-neck limit(~ 100 T) of pulsed magnets. Here, we...Conductor materials with good mechanical performance as well as high electrical and thermal conductivities are particularly important to break through the current bottle-neck limit(~ 100 T) of pulsed magnets. Here, we perform systematic studies on the elastic properties of the Cu–6wt% Ag alloy wire, which is a promising candidate material for the new-generation pulsed magnets, by employing two independent ultrasonic techniques, i.e., resonant ultrasound spectroscopy(RUS) and ultrasound pulse-echo experiments. Our RUS measurements manifest that the elastic properties of the Cu–6wt% Ag alloy wires can be improved by an electroplastic drawing procedure as compared with the conventional cold drawing. We also take this opportunity to test the availability of our newly-built ultrasound pulse-echo facility at the Wuhan National High Magnetic Field Center(WHMFC, China), and the results suggest that the elastic performance of the electroplastically-drawn Cu–6wt% Ag alloy wire remains excellent without anomalous softening under extreme conditions,e.g., in ultra-high magnetic field up to 50 T and nitrogen or helium cryogenic liquids.展开更多
The progressive loss of dopaminergic neurons in affected patient brains is one of the pathological features of Parkinson's disease,the second most common human neurodegenerative disease.Although the detailed patho...The progressive loss of dopaminergic neurons in affected patient brains is one of the pathological features of Parkinson's disease,the second most common human neurodegenerative disease.Although the detailed pathogenesis accounting for dopaminergic neuron degeneration in Parkinson's disease is still unclear,the advancement of stem cell approaches has shown promise for Parkinson's disease research and therapy.The induced pluripotent stem cells have been commonly used to generate dopaminergic neurons,which has provided valuable insights to improve our understanding of Parkinson's disease pathogenesis and contributed to anti-Parkinson's disease therapies.The current review discusses the practical approaches and potential applications of induced pluripotent stem cell techniques for generating and differentiating dopaminergic neurons from induced pluripotent stem cells.The benefits of induced pluripotent stem cell-based research are highlighted.Various dopaminergic neuron differentiation protocols from induced pluripotent stem cells are compared.The emerging three-dimension-based brain organoid models compared with conventional two-dimensional cell culture are evaluated.Finally,limitations,challenges,and future directions of induced pluripotent stem cell–based approaches are analyzed and proposed,which will be significant to the future application of induced pluripotent stem cell-related techniques for Parkinson's disease.展开更多
Deep learning algorithms have been rapidly incorporated into many different applications due to the increase in computational power and the availability of massive amounts of data.Recently,both deep learning and ensem...Deep learning algorithms have been rapidly incorporated into many different applications due to the increase in computational power and the availability of massive amounts of data.Recently,both deep learning and ensemble learning have been used to recognize underlying structures and patterns from high-level features to make predictions/decisions.With the growth in popularity of deep learning and ensemble learning algorithms,they have received significant attention from both scientists and the industrial community due to their superior ability to learn features from big data.Ensemble deep learning has exhibited significant performance in enhancing learning generalization through the use of multiple deep learning algorithms.Although ensemble deep learning has large quantities of training parameters,which results in time and space overheads,it performs much better than traditional ensemble learning.Ensemble deep learning has been successfully used in several areas,such as bioinformatics,finance,and health care.In this paper,we review and investigate recent ensemble deep learning algorithms and techniques in health care domains,medical imaging,health care data analytics,genomics,diagnosis,disease prevention,and drug discovery.We cover several widely used deep learning algorithms along with their architectures,including deep neural networks(DNNs),convolutional neural networks(CNNs),recurrent neural networks(RNNs),and generative adversarial networks(GANs).Common healthcare tasks,such as medical imaging,electronic health records,and genomics,are also demonstrated.Furthermore,in this review,the challenges inherent in reducing the burden on the healthcare system are discussed and explored.Finally,future directions and opportunities for enhancing healthcare model performance are discussed.展开更多
Low-voltage direct current(DC)microgrids have recently emerged as a promising and viable alternative to traditional alternating cur-rent(AC)microgrids,offering numerous advantages.Consequently,researchers are explorin...Low-voltage direct current(DC)microgrids have recently emerged as a promising and viable alternative to traditional alternating cur-rent(AC)microgrids,offering numerous advantages.Consequently,researchers are exploring the potential of DC microgrids across var-ious configurations.However,despite the sustainability and accuracy offered by DC microgrids,they pose various challenges when integrated into modern power distribution systems.Among these challenges,fault diagnosis holds significant importance.Rapid fault detection in DC microgrids is essential to maintain stability and ensure an uninterrupted power supply to critical loads.A primary chal-lenge is the lack of standards and guidelines for the protection and safety of DC microgrids,including fault detection,location,and clear-ing procedures for both grid-connected and islanded modes.In response,this study presents a brief overview of various approaches for protecting DC microgrids.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
This article provides a comprehensive analysis of the study by Hou et al,focusing on the complex interplay between psychological and physical factors in the postoperative recovery(POR)of patients with perianal disease...This article provides a comprehensive analysis of the study by Hou et al,focusing on the complex interplay between psychological and physical factors in the postoperative recovery(POR)of patients with perianal diseases.The study sheds light on how illness perception,anxiety,and depression significantly influence recovery outcomes.Hou et al developed a predictive model that demonstrated high accuracy in identifying patients at risk of poor recovery.The article explores the critical role of pre-operative psychological assessment,highlighting the need for mental health support and personalized recovery plans in enhancing POR quality.A multidisciplinary approach,integrating mental health professionals with surgeons,anesthesiologists,and other specialists,is emphasized to ensure comprehensive care for patients.The study’s findings serve as a call to integrate psychological care into surgical practice to optimize outcomes for patients with perianal diseases.展开更多
One of the detection objectives of the Chinese Asteroid Exploration mission is to investigate the space environment near the Main-belt Comet(MBC,Active Asteroid)311P/PANSTARRS.This paper outlines the scientific object...One of the detection objectives of the Chinese Asteroid Exploration mission is to investigate the space environment near the Main-belt Comet(MBC,Active Asteroid)311P/PANSTARRS.This paper outlines the scientific objectives,measurement targets,and measurement requirements for the proposed Gas and Ion Analyzer(GIA).The GIA is designed for in-situ mass spectrometry of neutral gases and low-energy ions,such as hydrogen,carbon,and oxygen,in the vicinity of 311P.Ion sampling techniques are essential for the GIA's Time-of-Flight(TOF)mass analysis capabilities.In this paper,we present an enhanced ion sampling technique through the development of an ion attraction model and an ion source model.The ion attraction model demonstrates that adjusting attraction grid voltage can enhance the detection efficiency of low-energy ions and mitigate the repulsive force of ions during sampling,which is influenced by the satellite's surface positive charging.The ion source model simulates the processes of gas ionization and ion multiplication.Simulation results indicate that the GIA can achieve a lower pressure limit below 10-13Pa and possess a dynamic range exceeding 10~9.These performances ensure the generation of ions with stable and consistent current,which is crucial for high-resolution and broad dynamic range mass spectrometer analysis.Preliminary testing experiments have verified GIA's capability to detect gas compositions such as H2O and N2.In-situ measurements near 311P using GIA are expected to significantly contribute to our understanding of asteroid activity mechanisms,the evolution of the atmospheric and ionized environments of main-belt comets,the interactions with solar wind,and the origin of Earth's water.展开更多
文摘Inflatable penile prosthesis(IPP)implantation is the gold standard treatment for patients with erectile dysfunction who are refractory to medical therapy.The standard placement of the reservoir in the space of Retzius(SOR)may be contraindicated in patients with prior pelvic or abdominal surgery due to altered anatomy and increased risk of complications.This has led to the development of alternative ectopic reservoir placement techniques.In this narrative review,we summarize the literature on various ectopic reservoir approaches,including low and high submuscular placements,submuscular techniques with counter incisions or transfascial fixation,midline submuscular placement,subcutaneous placement,and lateral retroperitoneal approaches.We describe the surgical methods,outcomes,and complication rates associated with each technique.While most methods demonstrate low complication and revision rates,direct comparisons remain limited due to heterogeneity and lack of prospective data.This review highlights the importance of individualized technique selection based on prior surgical history,body habitus,and surgeon experience.As ectopic placement becomes more widely adopted,familiarity with multiple approaches is essential for prosthetic surgeons.
文摘BACKGROUND Due to the increasing rate of thyroid nodules diagnosis,and the desire to avoid the unsightly cervical scar,remote thyroidectomies were invented and are increasingly performed.Transoral endoscopic thyroidectomy vestibular approach and trans-areolar approaches(TAA)are the two most commonly used remote approaches.No previous meta-analysis has compared postoperative infections and swallowing difficulties among the two procedures.AIM To compared the same among patients undergoing lobectomy for unilateral thyroid carcinoma/benign thyroid nodule.METHODS We searched PubMed MEDLINE,Google Scholar,and Cochrane Library from the date of the first published article up to August 2025.The term used were transoral thyroidectomy vestibular approach,trans areolar thyroidectomy,scarless thyroidectomy,remote thyroidectomy,infections,postoperative,inflammation,dysphagia,and swallowing difficulties.We identified 130 studies,of them,30 full texts were screened and only six studies were included in the final meta-analysis.RESULTS Postoperative infections were not different between the two approaches,odd ratio=1.33,95%confidence interval:0.50-3.53,theχ2 was 1.92 and the P-value for overall effect of 0.57.Similarly,transient swallowing difficulty was not different between the two forms of surgery,with odd ratio=0.91,95%confidence interval:0.35-2.40;theχ2 was 1.32,and the P-value for overall effect of 0.85.CONCLUSION No significant statistical differences were evident between trans-oral endoscopic Mirghani H.Infections and swallowing difficulty in scarless thyroidectomy WJCC https://www.wjgnet.com 2 January 6,2026 Volume 14 Issue 1 thyroidectomy vestibular approach and trans-areolar approach regarding postoperative infection and transient swallowing difficulties.Further longer randomized trials are needed.
基金supported by Healthy China initiative of Traditional Chinese Medicine(No.889042).
文摘Currently,the number of patients with myopia is increasing rapidly across the globe.Traditional Chinese medicine(TCM),with its long history and rich experience,has shown promise in effectively managing and treating this condition.Nevertheless,considering the vast amount of research that is currently being conducted,focusing on the utilization of TCM in the management of myopia,there is an urgent requirement for a thorough and comprehensive review.The review would serve to clarify the practical applications of TCM within this specific field,and it would also aim to elucidate the underlying mechanisms that are at play,providing a deeper understanding of how TCM principles can be effectively integrated into modern medical practices.Here,some modern medical pathogenesis of myopia and appropriate TCM techniques studies are summarized in the prevention and treatment of myopia.Further,we discussed the potential mechanisms and the future research directions of TCM against myopia.Identifying these mechanisms is crucial for understanding how TCM can be effectively utilized in this context.The combination of various TCM methods or the combination of traditional Chinese and Western medicine is of great significance for the prevention and control of myopia in the future.
基金supported by the Institute of Information&Communications Technology Planning&Evaluation(IITP)grant funded by the Korea government(MSIT)(No.RS-2023-00235509Development of security monitoring technology based network behavior against encrypted cyber threats in ICT convergence environment).
文摘With the increasing emphasis on personal information protection,encryption through security protocols has emerged as a critical requirement in data transmission and reception processes.Nevertheless,IoT ecosystems comprise heterogeneous networks where outdated systems coexist with the latest devices,spanning a range of devices from non-encrypted ones to fully encrypted ones.Given the limited visibility into payloads in this context,this study investigates AI-based attack detection methods that leverage encrypted traffic metadata,eliminating the need for decryption and minimizing system performance degradation—especially in light of these heterogeneous devices.Using the UNSW-NB15 and CICIoT-2023 dataset,encrypted and unencrypted traffic were categorized according to security protocol,and AI-based intrusion detection experiments were conducted for each traffic type based on metadata.To mitigate the problem of class imbalance,eight different data sampling techniques were applied.The effectiveness of these sampling techniques was then comparatively analyzed using two ensemble models and three Deep Learning(DL)models from various perspectives.The experimental results confirmed that metadata-based attack detection is feasible using only encrypted traffic.In the UNSW-NB15 dataset,the f1-score of encrypted traffic was approximately 0.98,which is 4.3%higher than that of unencrypted traffic(approximately 0.94).In addition,analysis of the encrypted traffic in the CICIoT-2023 dataset using the same method showed a significantly lower f1-score of roughly 0.43,indicating that the quality of the dataset and the preprocessing approach have a substantial impact on detection performance.Furthermore,when data sampling techniques were applied to encrypted traffic,the recall in the UNSWNB15(Encrypted)dataset improved by up to 23.0%,and in the CICIoT-2023(Encrypted)dataset by 20.26%,showing a similar level of improvement.Notably,in CICIoT-2023,f1-score and Receiver Operation Characteristic-Area Under the Curve(ROC-AUC)increased by 59.0%and 55.94%,respectively.These results suggest that data sampling can have a positive effect even in encrypted environments.However,the extent of the improvement may vary depending on data quality,model architecture,and sampling strategy.
基金supported by the National Natural Science Foundation of China,No.31760290,82160688the Key Development Areas Project of Ganzhou Science and Technology,No.2022B-SF9554(all to XL)。
文摘Synaptic pruning is a crucial process in synaptic refinement,eliminating unstable synaptic connections in neural circuits.This process is triggered and regulated primarily by spontaneous neural activity and experience-dependent mechanisms.The pruning process involves multiple molecular signals and a series of regulatory activities governing the“eat me”and“don't eat me”states.Under physiological conditions,the interaction between glial cells and neurons results in the clearance of unnecessary synapses,maintaining normal neural circuit functionality via synaptic pruning.Alterations in genetic and environmental factors can lead to imbalanced synaptic pruning,thus promoting the occurrence and development of autism spectrum disorder,schizophrenia,Alzheimer's disease,and other neurological disorders.In this review,we investigated the molecular mechanisms responsible for synaptic pruning during neural development.We focus on how synaptic pruning can regulate neural circuits and its association with neurological disorders.Furthermore,we discuss the application of emerging optical and imaging technologies to observe synaptic structure and function,as well as their potential for clinical translation.Our aim was to enhance our understanding of synaptic pruning during neural development,including the molecular basis underlying the regulation of synaptic function and the dynamic changes in synaptic density,and to investigate the potential role of these mechanisms in the pathophysiology of neurological diseases,thus providing a theoretical foundation for the treatment of neurological disorders.
文摘In this special issue of Neuroscience Bulletin, the topics range over emerging techniques from the nanoscopic to the macroscopic scales. At the nanoscopic level, new ways to obtain images at the individual protein level in synapses take the re- construction of synaptic architecture to a new level, while using chromophores to disable specific proteins at selected subcellular locations allows the assessment of their functional roles in such dynamic processes as growth-cone extension and cell division. The subtle influences of axonal chan- nels and receptors on neurotransmission are revealed by recording from the blebs induced by axotomy, while methods from cloning to chemical computation are being applied to dissecting the structural-functional rules by which ion channels operatet41.
文摘Objective： To sum up 7 patients with cervicothoracic vertebrae tumors （Cr to T3） from March 1999 and May 2002, who underwent operative treatment via anterior approaches. Methods ：The anterior approaches included low anterior cervical approach and high transthoracic approach. In 5 cases of segments of T1 and above involved, the low anterior cervical approaches were adopted, otherwise the high transthoracic approaches were used（2 cases）. Excision of tumor was carried out according to demands of the Weinstein-Boriani-Biagini （WBB） staging system. Spine stability was reconstructed by bone autografting and instrumentation. There were 4 cases of primary tumor and 3 of metastases. Their mean age was 45. 1 years （23 to 66）. The mean follow-up was 18.9 months （3 to 45）. Results were evaluated by occurrence of complications, improvement of symptoms, local recurrence and mortality. Results： All patients stood surgery well. No significant complications occurred during and after operation. Local pain was significantly alleviated and neurological deficit was improved at least one Frankel grade. Three patients died. Local tumor control was obtained in 6 patients （85.7 % ） until the end of follow-up. Conclusion.-Our experience showed that via low anterior cervical approach and high transthoracic approach, the cervicothoracic vertebrae tumor could be excised safely and adequately. Moreover, excision of tumor according to the WBB surgical staging system and reconstruction of spine stability have made great contribution to local tumor control and the neurological function improvement.
基金funded by the project of Guangdong Provincial Basic and Applied Basic Research Fund Committee(2022A1515240073)the Pearl River Talent Recruitment Program(2019CX01G338),Guangdong Province.
文摘Construction engineering and management(CEM)has become increasingly complicated with the increasing size of engineering projects under different construction environments,motivating the digital transformation of CEM.To contribute to a better understanding of the state of the art of smart techniques for engineering projects,this paper provides a comprehensive review of multi-criteria decision-making(MCDM)techniques,intelligent techniques,and their applications in CEM.First,a comprehensive framework detailing smart technologies for construction projects is developed.Next,the characteristics of CEM are summarized.A bibliometric review is then conducted to investigate the keywords,journals,and clusters related to the application of smart techniques in CEM during 2000-2022.Recent advancements in intelligent techniques are also discussed under the following six topics:①big data technology;②computer vision;③speech recognition;④natural language processing;⑤machine learning;and⑥knowledge representation,understanding,and reasoning.The applications of smart techniques are then illustrated via underground space exploitation.Finally,future research directions for the sustainable development of smart construction are highlighted.
基金funded by the United Arab Emirates UniversityResearch Officegrant number 12F041 to KM。
文摘Advancements in molecular approaches have been utilized to breed crops with a wide range of economically valuable traits to develop superior cultivars.This review provides a concise overview of modern breakthroughs in molecular plant production.Genotyping and high-throughput phenotyping methods for predictive plant breeding are briefly discussed.In this study,we explore contemporary molecular breeding techniques for producing desirable crop varieties.These techniques include cisgenesis,clustered regularly interspaced short palindromic repeat(CRISPR/Cas9)gene editing,haploid induction,and de novo domestication.We examine the speed breeding approach-a strategy for cultivating plants under controlled conditions.We further highlight the significance of modern breeding technologies in efficiently utilizing agricultural resources for crop production in urban areas.The deciphering of crop genomes has led to the development of extensive DNA markers,quantitative trait loci(QTLs),and pangenomes associated with various desirable crop traits.This shift to the genotypic selection of crops considerably expedites the plant breeding process.Based on the plant population used,the connection between genotypic and phenotypic data provides several genetic elements,including genes,markers,and alleles that can be used in genomic breeding and gene editing.The integration of speed breeding with genomic-assisted breeding and cutting-edge genome editing tools has made it feasible to rapidly manipulate and generate multiple crop cycles and accelerate the plant breeding process.Breakthroughs in molecular techniques have led to substantial improvements in modern breeding methods.
基金supported by the National Natural Science Foundation of China(Nos.12341501 and 11905074)。
文摘Precise transverse emittance assessment in electron beams is crucial for advancing high-brightness beam injectors.As opposed to intricate methodologies that use specialized devices,quadrupole focusing strength scanning(Q-scanning)techniques offer notable advantages for various injectors owing to their inherent convenience and cost-effectiveness.However,their stringent approximation conditions lead to inevitable errors in practical operation,thereby limiting their widespread application.This study addressed these challenges by revisiting the analytical derivation procedure and investigating the effects of the underlying approximation conditions.Preliminary corrections were explored through a combination of data processing analysis and numerical simulations.Furthermore,based on theoretical derivations,virtual measurements using beam dynamics calculations were employed to evaluate the correction reliability.Subsequent experimental validations were performed at the Huazhong University of Science and Technology injector to verify the effectiveness of the proposed compensation method.Both the virtual and experimental results confirm the feasibility and reliability of the enhanced Q-scanning-based diagnosis for transverse emittance in typical beam injectors operating under common conditions.Through the integration of these corrections and compensations,enhanced Q-scanning-based techniques emerge as promising alternatives to traditional emittance diagnosis methods.
文摘This paper presents a high-fidelity lumpedparameter(LP)thermal model(HF-LPTM)for permanent magnet synchronous machines(PMSMs)in electric vehicle(EV)applications,where various cooling techniques are considered,including frame forced air/liquid cooling,oil jet cooling for endwinding,and rotor shaft cooling.To address the temperature misestimation in the LP thermal modelling due to assumptions of concentrated loss input and uniform heat flows,the developed HF-LPTM introduces two compensation thermal resistances for the winding and PM components,which are analytically derived from the multi-dimensional heat transfer equations and are robust against different load/thermal conditions.As validated by the finite element analysis method and experiments,the conventional LPTMs exhibit significant winding temperature deviations,while the proposed HF-LPTM can accurately predict both the midpoint and average temperatures.The developed HFLPTM is further used to assess the effectiveness of various cooling techniques under different scenarios,i.e.,steady-state thermal states under the rated load condition,and transient temperature profiles under city,freeway,and hybrid(city+freeway)driving cycles.Results indicate that no single cooling technique can maintain both winding and PM temperatures within safety limits.The combination of frame liquid cooling and oil jet cooling for end winding can sufficiently mitigate PMSM thermal stress in EV applications.
文摘In this paper, a time-varying rain characterization and diurnal variation in the Ku-band satellite systems simulated with synthetic storm techniques (SST) over a tropical location in Nigeria have been presented. Three years’ rain rate time-series data measured by a raingauge located inside the Federal University of Technology Akure, Nigeria were utilized for the purpose of this work. The analysis is based on the CDF of one-minute rain rate;time-series simulated annual/seasonal and diurnal rain rate, rain attenuation statistics and fade margins observed over four time intervals: 00:00-06:00, 06:00-12:00, 12:00-18:00 and 18:00-24:00. In addition, comparison was also made between the synthesized values and rain attenuation statistics, at 12.245 GHz for a hypothetical downlink from EUTELSAT W4/W7 satellite in the area. It could be observed that at 99.99% link availability, the fade margin as high as ~20 dB may be required at Ku band uplink frequency bands in this area. We also observed that the communication downlinks working in the early morning and early to late in the evening hours must be compensated with an appropriate Down-Link Power Control (DLPC) for optimum performances during severe atmospheric influences in the region.
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.
基金Project supported by the National Key R&D Program of China (Grant Nos. 2022YFA1602602 and 2023YFA1609600)the National Natural Science Foundation of China (Grant No. U23A20580)+3 种基金the open research fund of Songshan Lake Materials Laboratory (Grant No. 2022SLABFN27)Beijing National Laboratory for Condensed Matter Physics (Grant No. 2024BNLCMPKF004)Guangdong Basic and Applied Basic Research Foundation (Grant No. 2022B1515120020)the interdisciplinary program of Wuhan National High Magnetic Field Center at Huazhong University of Science and Technology (Grant No. WHMFC202132)。
文摘Conductor materials with good mechanical performance as well as high electrical and thermal conductivities are particularly important to break through the current bottle-neck limit(~ 100 T) of pulsed magnets. Here, we perform systematic studies on the elastic properties of the Cu–6wt% Ag alloy wire, which is a promising candidate material for the new-generation pulsed magnets, by employing two independent ultrasonic techniques, i.e., resonant ultrasound spectroscopy(RUS) and ultrasound pulse-echo experiments. Our RUS measurements manifest that the elastic properties of the Cu–6wt% Ag alloy wires can be improved by an electroplastic drawing procedure as compared with the conventional cold drawing. We also take this opportunity to test the availability of our newly-built ultrasound pulse-echo facility at the Wuhan National High Magnetic Field Center(WHMFC, China), and the results suggest that the elastic performance of the electroplastically-drawn Cu–6wt% Ag alloy wire remains excellent without anomalous softening under extreme conditions,e.g., in ultra-high magnetic field up to 50 T and nitrogen or helium cryogenic liquids.
基金supported by Singapore National Medical Research Council(NMRC)grants,including CS-IRG,HLCA2022(to ZDZ),STaR,OF LCG 000207(to EKT)a Clinical Translational Research Programme in Parkinson's DiseaseDuke-Duke-NUS collaboration pilot grant(to ZDZ)。
文摘The progressive loss of dopaminergic neurons in affected patient brains is one of the pathological features of Parkinson's disease,the second most common human neurodegenerative disease.Although the detailed pathogenesis accounting for dopaminergic neuron degeneration in Parkinson's disease is still unclear,the advancement of stem cell approaches has shown promise for Parkinson's disease research and therapy.The induced pluripotent stem cells have been commonly used to generate dopaminergic neurons,which has provided valuable insights to improve our understanding of Parkinson's disease pathogenesis and contributed to anti-Parkinson's disease therapies.The current review discusses the practical approaches and potential applications of induced pluripotent stem cell techniques for generating and differentiating dopaminergic neurons from induced pluripotent stem cells.The benefits of induced pluripotent stem cell-based research are highlighted.Various dopaminergic neuron differentiation protocols from induced pluripotent stem cells are compared.The emerging three-dimension-based brain organoid models compared with conventional two-dimensional cell culture are evaluated.Finally,limitations,challenges,and future directions of induced pluripotent stem cell–based approaches are analyzed and proposed,which will be significant to the future application of induced pluripotent stem cell-related techniques for Parkinson's disease.
基金funded by Taif University,Saudi Arabia,project No.(TU-DSPP-2024-263).
文摘Deep learning algorithms have been rapidly incorporated into many different applications due to the increase in computational power and the availability of massive amounts of data.Recently,both deep learning and ensemble learning have been used to recognize underlying structures and patterns from high-level features to make predictions/decisions.With the growth in popularity of deep learning and ensemble learning algorithms,they have received significant attention from both scientists and the industrial community due to their superior ability to learn features from big data.Ensemble deep learning has exhibited significant performance in enhancing learning generalization through the use of multiple deep learning algorithms.Although ensemble deep learning has large quantities of training parameters,which results in time and space overheads,it performs much better than traditional ensemble learning.Ensemble deep learning has been successfully used in several areas,such as bioinformatics,finance,and health care.In this paper,we review and investigate recent ensemble deep learning algorithms and techniques in health care domains,medical imaging,health care data analytics,genomics,diagnosis,disease prevention,and drug discovery.We cover several widely used deep learning algorithms along with their architectures,including deep neural networks(DNNs),convolutional neural networks(CNNs),recurrent neural networks(RNNs),and generative adversarial networks(GANs).Common healthcare tasks,such as medical imaging,electronic health records,and genomics,are also demonstrated.Furthermore,in this review,the challenges inherent in reducing the burden on the healthcare system are discussed and explored.Finally,future directions and opportunities for enhancing healthcare model performance are discussed.
文摘Low-voltage direct current(DC)microgrids have recently emerged as a promising and viable alternative to traditional alternating cur-rent(AC)microgrids,offering numerous advantages.Consequently,researchers are exploring the potential of DC microgrids across var-ious configurations.However,despite the sustainability and accuracy offered by DC microgrids,they pose various challenges when integrated into modern power distribution systems.Among these challenges,fault diagnosis holds significant importance.Rapid fault detection in DC microgrids is essential to maintain stability and ensure an uninterrupted power supply to critical loads.A primary chal-lenge is the lack of standards and guidelines for the protection and safety of DC microgrids,including fault detection,location,and clear-ing procedures for both grid-connected and islanded modes.In response,this study presents a brief overview of various approaches for protecting DC microgrids.
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.
基金Supported by National Research Foundation of Korea,No.NRF-2021S1A5A8062526.
文摘This article provides a comprehensive analysis of the study by Hou et al,focusing on the complex interplay between psychological and physical factors in the postoperative recovery(POR)of patients with perianal diseases.The study sheds light on how illness perception,anxiety,and depression significantly influence recovery outcomes.Hou et al developed a predictive model that demonstrated high accuracy in identifying patients at risk of poor recovery.The article explores the critical role of pre-operative psychological assessment,highlighting the need for mental health support and personalized recovery plans in enhancing POR quality.A multidisciplinary approach,integrating mental health professionals with surgeons,anesthesiologists,and other specialists,is emphasized to ensure comprehensive care for patients.The study’s findings serve as a call to integrate psychological care into surgical practice to optimize outcomes for patients with perianal diseases.
基金Supported by the National Natural Science Foundation of China(42474239,41204128)China National Space Administration(Pre-research project on Civil Aerospace Technologies No.D010301)Strategic Priority Research Program of the Chinese Academy of Sciences(XDA17010303)。
文摘One of the detection objectives of the Chinese Asteroid Exploration mission is to investigate the space environment near the Main-belt Comet(MBC,Active Asteroid)311P/PANSTARRS.This paper outlines the scientific objectives,measurement targets,and measurement requirements for the proposed Gas and Ion Analyzer(GIA).The GIA is designed for in-situ mass spectrometry of neutral gases and low-energy ions,such as hydrogen,carbon,and oxygen,in the vicinity of 311P.Ion sampling techniques are essential for the GIA's Time-of-Flight(TOF)mass analysis capabilities.In this paper,we present an enhanced ion sampling technique through the development of an ion attraction model and an ion source model.The ion attraction model demonstrates that adjusting attraction grid voltage can enhance the detection efficiency of low-energy ions and mitigate the repulsive force of ions during sampling,which is influenced by the satellite's surface positive charging.The ion source model simulates the processes of gas ionization and ion multiplication.Simulation results indicate that the GIA can achieve a lower pressure limit below 10-13Pa and possess a dynamic range exceeding 10~9.These performances ensure the generation of ions with stable and consistent current,which is crucial for high-resolution and broad dynamic range mass spectrometer analysis.Preliminary testing experiments have verified GIA's capability to detect gas compositions such as H2O and N2.In-situ measurements near 311P using GIA are expected to significantly contribute to our understanding of asteroid activity mechanisms,the evolution of the atmospheric and ionized environments of main-belt comets,the interactions with solar wind,and the origin of Earth's water.
