Sea launch has the characteristics of flexible launching points, high landing area safety, and good economy. In recent years, it has become one of the important launch methods. Since 2019, China has carried out a tota...Sea launch has the characteristics of flexible launching points, high landing area safety, and good economy. In recent years, it has become one of the important launch methods. Since 2019, China has carried out a total of 11 successful sea launches. The Gravity-1(YL-1) sea launch system consists of a launch vehicle system and a sea launch platform. The sea launch program includes roll on/roll off boarding, sea mooring, sea maneuvering, anchoring and positioning, system testing, and formal launch. Through the maiden flight of YL-1, the design and manufacturing technology of large tonnage dedicated launch ship, launch vehicle vertical transfer and roll on/roll off boarding technology, anti-shake technology for sea launch, simple inflatable flexible insulation protective cover technology, and remote wireless measurement and control technology have been fully verified.展开更多
Multi-Object Tracking(MOT)represents a fundamental but computationally demanding task in computer vision,with particular challenges arising in occluded and densely populated environments.While contemporary tracking sy...Multi-Object Tracking(MOT)represents a fundamental but computationally demanding task in computer vision,with particular challenges arising in occluded and densely populated environments.While contemporary tracking systems have demonstrated considerable progress,persistent limitations—notably frequent occlusion-induced identity switches and tracking inaccuracies—continue to impede reliable real-world deployment.This work introduces an advanced tracking framework that enhances association robustness through a two-stage matching paradigm combining spatial and appearance features.Proposed framework employs:(1)a Height Modulated and Scale Adaptive Spatial Intersection-over-Union(HMSIoU)metric for improved spatial correspondence estimation across variable object scales and partial occlusions;(2)a feature extraction module generating discriminative appearance descriptors for identity maintenance;and(3)a recovery association mechanism for refining matches between unassociated tracks and detections.Comprehensive evaluation on standard MOT17 and MOT20 benchmarks demonstrates significant improvements in tracking consistency,with state-of-the-art performance across key metrics including HOTA(64),MOTA(80.7),IDF1(79.8),and IDs(1379).These results substantiate the efficacy of our Cue-Tracker framework in complex real-world scenarios characterized by occlusions and crowd interactions.展开更多
Multiple Sclerosis(MS)poses significant health risks.Patients may face neurodegeneration,mobility issues,cognitive decline,and a reduced quality of life.Manual diagnosis by neurologists is prone to limitations,making ...Multiple Sclerosis(MS)poses significant health risks.Patients may face neurodegeneration,mobility issues,cognitive decline,and a reduced quality of life.Manual diagnosis by neurologists is prone to limitations,making AI-based classification crucial for early detection.Therefore,automated classification using Artificial Intelligence(AI)techniques has a crucial role in addressing the limitations of manual classification and preventing the development of MS to advanced stages.This study developed hybrid systems integrating XGBoost(eXtreme Gradient Boosting)with multi-CNN(Convolutional Neural Networks)features based on Ant Colony Optimization(ACO)and Maximum Entropy Score-based Selection(MESbS)algorithms for early classification of MRI(Magnetic Resonance Imaging)images in a multi-class and binary-class MS dataset.All hybrid systems started by enhancing MRI images using the fusion processes of a Gaussian filter and Contrast-Limited Adaptive Histogram Equalization(CLAHE).Then,the Gradient Vector Flow(GVF)algorithm was applied to select white matter(regions of interest)within the brain and segment them from the surrounding brain structures.These regions of interest were processed by CNN models(ResNet101,DenseNet201,and MobileNet)to extract deep feature maps,which were then combined into fused feature vectors of multi-CNN model combinations(ResNet101-DenseNet201,DenseNet201-MobileNet,ResNet101-MobileNet,and ResNet101-DenseNet201-MobileNet).The multi-CNN features underwent dimensionality reduction using ACO and MESbS algorithms to remove unimportant features and retain important features.The XGBoost classifier employed the resultant feature vectors for classification.All developed hybrid systems displayed promising outcomes.For multiclass classification,the XGBoost model using ResNet101-DenseNet201-MobileNet features selected by ACO attained 99.4%accuracy,99.45%precision,and 99.75%specificity,surpassing prior studies(93.76%accuracy).It reached 99.6%accuracy,99.65%precision,and 99.55%specificity in binary-class classification.These results demonstrate the effectiveness of multi-CNN fusion with feature selection in improving MS classification accuracy.展开更多
This study provides a systematic investigation into the influence of feature selection methods on cryptocurrency price forecasting models employing technical indicators.In this work,over 130 technical indicators—cove...This study provides a systematic investigation into the influence of feature selection methods on cryptocurrency price forecasting models employing technical indicators.In this work,over 130 technical indicators—covering momentum,volatility,volume,and trend-related technical indicators—are subjected to three distinct feature selection approaches.Specifically,mutual information(MI),recursive feature elimination(RFE),and random forest importance(RFI).By extracting an optimal set of 20 predictors,the proposed framework aims to mitigate redundancy and overfitting while enhancing interpretability.These feature subsets are integrated into support vector regression(SVR),Huber regressors,and k-nearest neighbors(KNN)models to forecast the prices of three leading cryptocurrencies—Bitcoin(BTC/USDT),Ethereum(ETH/USDT),and Binance Coin(BNB/USDT)—across horizons ranging from 1 to 20 days.Model evaluation employs the coefficient of determination(R2)and the root mean squared logarithmic error(RMSLE),alongside a walk-forward validation scheme to approximate real-world trading contexts.Empirical results indicate that incorporating momentum and volatility measures substantially improves predictive accuracy,with particularly pronounced effects observed at longer forecast windows.Moreover,indicators related to volume and trend provide incremental benefits in select market conditions.Notably,an 80%–85% reduction in the original feature set frequently maintains or enhances model performance relative to the complete indicator set.These findings highlight the critical role of targeted feature selection in addressing high-dimensional financial data challenges while preserving model robustness.This research advances the field of cryptocurrency forecasting by offering a rigorous comparison of feature selection methods and their effects on multiple digital assets and prediction horizons.The outcomes highlight the importance of dimension-reduction strategies in developing more efficient and resilient forecasting algorithms.Future efforts should incorporate high-frequency data and explore alternative selection techniques to further refine predictive accuracy in this highly volatile domain.展开更多
During Donald Trump’s first term,the“Trump Shock”brought world politics into an era of uncertainties and pulled the transatlantic alliance down to its lowest point in history.The Trump 2.0 tsunami brewed by the 202...During Donald Trump’s first term,the“Trump Shock”brought world politics into an era of uncertainties and pulled the transatlantic alliance down to its lowest point in history.The Trump 2.0 tsunami brewed by the 2024 presidential election of the United States has plunged the U.S.-Europe relations into more gloomy waters,ushering in a more complex and turbulent period of adjustment.展开更多
Uzbekistan Institute of Standards(UIS),founded in 1969,is the national standardization body of Uzbekistan.There are over 32,000 national standards in Uzbekistan.Last year,UIS revised the working regulations of all tec...Uzbekistan Institute of Standards(UIS),founded in 1969,is the national standardization body of Uzbekistan.There are over 32,000 national standards in Uzbekistan.Last year,UIS revised the working regulations of all technical committees,which were established in accordance with the organizational structure of ISO.At present,UIS has standardization training courses covering 54 directions,and more than 1,700 experts have received relevant training.UIS ranks the 95th in terms of the Quality Infrastructure for Sustainable Development(QI4SD)and 80th in terms of the Global Quality Infrastructure Index(GQII).It is a member of ISO and an associate member of IEC.In the UIS,40 experts have participated in the activities of various ISO technical committees,and 251 experts have participated in the discussion of IEC projects as observer members.展开更多
Malaria is considered one of the major causes of travel-related morbidity and mortality,especially among non-immune travelers from non-endemic countries to the endemic regions.According to a multicenter study from the...Malaria is considered one of the major causes of travel-related morbidity and mortality,especially among non-immune travelers from non-endemic countries to the endemic regions.According to a multicenter study from the GeoSentinel surveillance network,malaria was the most frequent cause of fever in 21%of returning travelers,followed by dengue,typhoid fever,chikungunya and rickettsiosis[1].Individuals traveling from regions without malaria transmission to areas where it is endemic face a heightened risk of contracting the disease due to their lack of immunity.Despite the official malaria-free status of the Russian Federation since 2010,annual cases of severe Plasmodium(P.)falciparum malaria continue to be reported[2].This underscores the necessity for heightened clinical vigilance and improved preventive strategies especially in non-endemic settings.展开更多
Baosteel Technical Research,a quarterly journal,which is issued domestically and abroad,is run and sponsored by Baoshan Iron&Steel Co.,Ltd.Baosteel Technical Research mainly reports the achievements in technologic...Baosteel Technical Research,a quarterly journal,which is issued domestically and abroad,is run and sponsored by Baoshan Iron&Steel Co.,Ltd.Baosteel Technical Research mainly reports the achievements in technological innovation,academic research,new product development and industrial equipment improvement by Baosteel.It will continue to follow up on hot topics and serve the company's technological development and progress.展开更多
Baosteel Technical Research,a quarterly journal,which is issued domestically and abroad,is run and sponsored by Baoshan Iron & Steel Co.,Ltd.. Baosteel Technical Research mainly reports the achievements in technol...Baosteel Technical Research,a quarterly journal,which is issued domestically and abroad,is run and sponsored by Baoshan Iron & Steel Co.,Ltd.. Baosteel Technical Research mainly reports the achievements in technological innovation,academic research,new product development and industrial equipment improvement by Baosteel. It will continue to follow up on hot topics and serve the company's technological development and progress. Its readers include experts in steel metallurgy and related fields,technicians,management staff,professors and students in universities and colleges.展开更多
Bocapavovirus,a member of the genus Bocaparvovirus within the subfamily Parvovirinae and the family Parvoviridae,is a small,non-enveloped,single-stranded DNA virus.This pathogen poses health risks to both humans and a...Bocapavovirus,a member of the genus Bocaparvovirus within the subfamily Parvovirinae and the family Parvoviridae,is a small,non-enveloped,single-stranded DNA virus.This pathogen poses health risks to both humans and animals.The Bocaparvovirus genome.展开更多
1.Opportunities for electric motor drives in the low-altitude economy The implementation plan for the innovative application of general aviation equipment(2024–2030)outlines that by 2027,new general aviation equipmen...1.Opportunities for electric motor drives in the low-altitude economy The implementation plan for the innovative application of general aviation equipment(2024–2030)outlines that by 2027,new general aviation equipment will achieve commercial applications in urban air transport,logistics distribution and emergency rescue.展开更多
In the process of building a new power system dominated by new energy sources,power storage is a key supporting technology that ensures the safe and stable operation of the power grid,enables the flexible regulation o...In the process of building a new power system dominated by new energy sources,power storage is a key supporting technology that ensures the safe and stable operation of the power grid,enables the flexible regulation of the system,and raises the level of new energy consumption.It is also key to achieving carbon peak and neutrality as well as energy transformation.展开更多
One reference in the original manuscript contained incorrect bibliographic information and cited a non-existent publication:Traczyk A(1999)Pleistocene debris cover beds and block-debris tongues in the north-western pa...One reference in the original manuscript contained incorrect bibliographic information and cited a non-existent publication:Traczyk A(1999)Pleistocene debris cover beds and block-debris tongues in the north-western part of theŚlęża Massif(Poland)and their formation under permafrost conditions.Geographia Polonica 81(1).This erroneous reference has now been removed from the references list.展开更多
Hereditary angioedema (HAE) is a rare,autosomal dominant inherited disorder with an incidence of approximately 1 in 50,000.Among its various tapes,HAE with normal C1 inhibitor levels (HAE-nC1-INH)is exceptionally rare...Hereditary angioedema (HAE) is a rare,autosomal dominant inherited disorder with an incidence of approximately 1 in 50,000.Among its various tapes,HAE with normal C1 inhibitor levels (HAE-nC1-INH)is exceptionally rare.^([1]) HAE symptoms include recurrent episodes of skin and mucosal edema that can occur anywhere in the body.^([1-4]) Laryngeal edema is life-threatening,as it can lead to airway obstruction and potentially fatal suffocation.^([1-3])Edema of the gastrointestinal mucosa may cause abdominal pain,vomiting,and symptoms that are often misdiagnosed as acute abdomen.^([1-4]) This study included four patients,including one with HAE-nC1-INH (genetic testing revealed a heterozygous mutation in the KNG1 gene (c.1404G>C:p.Q468H)) and three with HAE due to C1 inhibitor deficiency (HAE-C1-INH).This case series aims to increase knowledge of HAE by illustrating its diverse clinical presentations and emphasizing features that may prompt clinical suspicion and facilitate timely diagnosis.展开更多
Obstructive Sleep Apnea(OSA)is a respiratory syndrome that occurs due to insufficient airflow through the respiratory or respiratory arrest while sleeping and sometimes due to the reduced oxygen saturation.The aim of ...Obstructive Sleep Apnea(OSA)is a respiratory syndrome that occurs due to insufficient airflow through the respiratory or respiratory arrest while sleeping and sometimes due to the reduced oxygen saturation.The aim of this paper is to analyze the respiratory signal of a person to detect the Normal Breathing Activity and the Sleep Apnea(SA)activity.In the proposed method,the time domain and frequency domain features of respiration signal obtained from the PPG device are extracted.These features are applied to the Classification and Regression Tree(CART)-Particle Swarm Optimization(PSO)classifier which classifies the signal into normal breathing signal and sleep apnea signal.The proposed method is validated to measure the performance metrics like sensitivity,specificity,accuracy and F1 score by applying time domain and frequency domain features separately.Additionally,the performance of the CART-PSO(CPSO)classification algorithm is evaluated through comparing its measures with existing classification algorithms.Concurrently,the effect of the PSO algorithm in the classifier is validated by varying the parameters of PSO.展开更多
Thermal image, or thermogram, becomes a new type of signal for machine condition monitoring and fault diagnosis due to the capability to display real-time temperature distribution and possibility to indicate the mach...Thermal image, or thermogram, becomes a new type of signal for machine condition monitoring and fault diagnosis due to the capability to display real-time temperature distribution and possibility to indicate the machine’s operating condition through its temperature. In this paper, an investigation of using the second-order statistical features of thermogram in association with minimum redundancy maximum relevance (mRMR) feature selection and simplified fuzzy ARTMAP (SFAM) classification is conducted for rotating machinery fault diagnosis. The thermograms of different machine conditions are firstly preprocessed for improving the image contrast, removing noise, and cropping to obtain the regions of interest (ROIs). Then, an enhanced algorithm based on bi-dimensional empirical mode decomposition is implemented to further increase the quality of ROIs before the second-order statistical features are extracted from their gray-level co-occurrence matrix (GLCM). The highly relevant features to the machine condition are selected from the total feature set by mRMR and are fed into SFAM to accomplish the fault diagnosis. In order to verify this investigation, the thermograms acquired from different conditions of a fault simulator including normal, misalignment, faulty bearing, and mass unbalance are used. This investigation also provides a comparative study of SFAM and other traditional methods such as back-propagation and probabilistic neural networks. The results show that the second-order statistical features used in this framework can provide a plausible accuracy in fault diagnosis of rotating machinery.展开更多
BACKGROUND Endoscopic ultrasound(EUS)is crucial for diagnosing solid pancreatic lesions,especially pancreatic ductal adenocarcinoma(PDAC),a highly aggressive cancer which represents the majority with a prevalence of a...BACKGROUND Endoscopic ultrasound(EUS)is crucial for diagnosing solid pancreatic lesions,especially pancreatic ductal adenocarcinoma(PDAC),a highly aggressive cancer which represents the majority with a prevalence of approximately 85%.AIM To identify EUS features that differentiate PDAC from other lesions such as neuroendocrine tumors(NETs)and helping in the differential diagnosis,by analyzing a large sample of solid pancreatic lesions.METHODS This observational,retrospective,multicenter study analyzed the endosonographic characteristics of 761 patients with a radiological diagnosis of solid pancreatic lesion,who underwent pancreatic EUS for typing and staging with needle biopsies between 2015 and 2023.General patient characteristics(age and sex)and solid lesion features were collected and described,such lesion size(Bmode),vessel involvement(compression or invasion),ductal dilation,lymphadenopathy,echogenicity,echopattern,margin regularity,multifocality,internal vascularization and elastography.Subsequently,a predictive analysis was performed through univariate and multivariate logistic regression to identify predictive features for PDAC or NET diagnoses.RESULTS Our study enrolled 761 patients,predominantly male with a mean age of 68.6.PDACs were generally larger(mean 33 mm×27 mm),often had irregular margins,and displayed significant upstream ductal dilation.Hypoechogenicity was common across malignant lesions.In contrast,NETs were smaller(mean 20 mm×17 mm)and typically had regular margins with multiple lesions.Vascular involvement,although predominant in PDAC,is a common feature of all malignant neoplasms.Multifocality,however,although a rare finding,is more typical of NETs and metastases,and practically absent in the remaining lesions.Predictive analyses showed that ductal dilation and irregular margins were the most significant predictors for PDAC[odds ratio(OR)=5.75 and 3.83],with hypoechogenicity,heterogeneous echopattern and lymphadenopathies also highly significant(OR=3.51,2.56 and 1.99).These features were inversely associated with NETs,with regular margins and absence of ductal involvement or lymphadenopathies(OR=0.24,0.86 and 0.45 respectively),as already shown by the descriptive analysis.Finally,age,despite achieving statistical significance,lacks clinical value given an OR trending towards 1.CONCLUSION This study provides a comprehensive overview of EUS features for solid pancreatic lesions,identifying distinct features like upstream ductal dilation and irregular margins for PDAC vs regular margins for NETs as strong diagnostic predictors.These findings enhance the understanding of pancreatic pathologies,offering valuable insights for improved differential diagnosis and clinical management,especially in complex cases.Further prospective studies could build on these results.展开更多
The full potential of advanced coating and finishingtechnologies for the production of technical textiles willbe outlined by Monforts specialists at Techtextil NorthAmerica which takes place in Atlanta,Georgia,from Ma...The full potential of advanced coating and finishingtechnologies for the production of technical textiles willbe outlined by Monforts specialists at Techtextil NorthAmerica which takes place in Atlanta,Georgia,from May6-8.The company and its US representative PSP Market-ing,of Charlotte,North Carolina,will be part of the exten-sive VDMA German Pavilion at the show,at stand 323lwithin the Georgia World Congress Center.展开更多
文摘Sea launch has the characteristics of flexible launching points, high landing area safety, and good economy. In recent years, it has become one of the important launch methods. Since 2019, China has carried out a total of 11 successful sea launches. The Gravity-1(YL-1) sea launch system consists of a launch vehicle system and a sea launch platform. The sea launch program includes roll on/roll off boarding, sea mooring, sea maneuvering, anchoring and positioning, system testing, and formal launch. Through the maiden flight of YL-1, the design and manufacturing technology of large tonnage dedicated launch ship, launch vehicle vertical transfer and roll on/roll off boarding technology, anti-shake technology for sea launch, simple inflatable flexible insulation protective cover technology, and remote wireless measurement and control technology have been fully verified.
文摘Multi-Object Tracking(MOT)represents a fundamental but computationally demanding task in computer vision,with particular challenges arising in occluded and densely populated environments.While contemporary tracking systems have demonstrated considerable progress,persistent limitations—notably frequent occlusion-induced identity switches and tracking inaccuracies—continue to impede reliable real-world deployment.This work introduces an advanced tracking framework that enhances association robustness through a two-stage matching paradigm combining spatial and appearance features.Proposed framework employs:(1)a Height Modulated and Scale Adaptive Spatial Intersection-over-Union(HMSIoU)metric for improved spatial correspondence estimation across variable object scales and partial occlusions;(2)a feature extraction module generating discriminative appearance descriptors for identity maintenance;and(3)a recovery association mechanism for refining matches between unassociated tracks and detections.Comprehensive evaluation on standard MOT17 and MOT20 benchmarks demonstrates significant improvements in tracking consistency,with state-of-the-art performance across key metrics including HOTA(64),MOTA(80.7),IDF1(79.8),and IDs(1379).These results substantiate the efficacy of our Cue-Tracker framework in complex real-world scenarios characterized by occlusions and crowd interactions.
文摘Multiple Sclerosis(MS)poses significant health risks.Patients may face neurodegeneration,mobility issues,cognitive decline,and a reduced quality of life.Manual diagnosis by neurologists is prone to limitations,making AI-based classification crucial for early detection.Therefore,automated classification using Artificial Intelligence(AI)techniques has a crucial role in addressing the limitations of manual classification and preventing the development of MS to advanced stages.This study developed hybrid systems integrating XGBoost(eXtreme Gradient Boosting)with multi-CNN(Convolutional Neural Networks)features based on Ant Colony Optimization(ACO)and Maximum Entropy Score-based Selection(MESbS)algorithms for early classification of MRI(Magnetic Resonance Imaging)images in a multi-class and binary-class MS dataset.All hybrid systems started by enhancing MRI images using the fusion processes of a Gaussian filter and Contrast-Limited Adaptive Histogram Equalization(CLAHE).Then,the Gradient Vector Flow(GVF)algorithm was applied to select white matter(regions of interest)within the brain and segment them from the surrounding brain structures.These regions of interest were processed by CNN models(ResNet101,DenseNet201,and MobileNet)to extract deep feature maps,which were then combined into fused feature vectors of multi-CNN model combinations(ResNet101-DenseNet201,DenseNet201-MobileNet,ResNet101-MobileNet,and ResNet101-DenseNet201-MobileNet).The multi-CNN features underwent dimensionality reduction using ACO and MESbS algorithms to remove unimportant features and retain important features.The XGBoost classifier employed the resultant feature vectors for classification.All developed hybrid systems displayed promising outcomes.For multiclass classification,the XGBoost model using ResNet101-DenseNet201-MobileNet features selected by ACO attained 99.4%accuracy,99.45%precision,and 99.75%specificity,surpassing prior studies(93.76%accuracy).It reached 99.6%accuracy,99.65%precision,and 99.55%specificity in binary-class classification.These results demonstrate the effectiveness of multi-CNN fusion with feature selection in improving MS classification accuracy.
文摘This study provides a systematic investigation into the influence of feature selection methods on cryptocurrency price forecasting models employing technical indicators.In this work,over 130 technical indicators—covering momentum,volatility,volume,and trend-related technical indicators—are subjected to three distinct feature selection approaches.Specifically,mutual information(MI),recursive feature elimination(RFE),and random forest importance(RFI).By extracting an optimal set of 20 predictors,the proposed framework aims to mitigate redundancy and overfitting while enhancing interpretability.These feature subsets are integrated into support vector regression(SVR),Huber regressors,and k-nearest neighbors(KNN)models to forecast the prices of three leading cryptocurrencies—Bitcoin(BTC/USDT),Ethereum(ETH/USDT),and Binance Coin(BNB/USDT)—across horizons ranging from 1 to 20 days.Model evaluation employs the coefficient of determination(R2)and the root mean squared logarithmic error(RMSLE),alongside a walk-forward validation scheme to approximate real-world trading contexts.Empirical results indicate that incorporating momentum and volatility measures substantially improves predictive accuracy,with particularly pronounced effects observed at longer forecast windows.Moreover,indicators related to volume and trend provide incremental benefits in select market conditions.Notably,an 80%–85% reduction in the original feature set frequently maintains or enhances model performance relative to the complete indicator set.These findings highlight the critical role of targeted feature selection in addressing high-dimensional financial data challenges while preserving model robustness.This research advances the field of cryptocurrency forecasting by offering a rigorous comparison of feature selection methods and their effects on multiple digital assets and prediction horizons.The outcomes highlight the importance of dimension-reduction strategies in developing more efficient and resilient forecasting algorithms.Future efforts should incorporate high-frequency data and explore alternative selection techniques to further refine predictive accuracy in this highly volatile domain.
文摘During Donald Trump’s first term,the“Trump Shock”brought world politics into an era of uncertainties and pulled the transatlantic alliance down to its lowest point in history.The Trump 2.0 tsunami brewed by the 2024 presidential election of the United States has plunged the U.S.-Europe relations into more gloomy waters,ushering in a more complex and turbulent period of adjustment.
文摘Uzbekistan Institute of Standards(UIS),founded in 1969,is the national standardization body of Uzbekistan.There are over 32,000 national standards in Uzbekistan.Last year,UIS revised the working regulations of all technical committees,which were established in accordance with the organizational structure of ISO.At present,UIS has standardization training courses covering 54 directions,and more than 1,700 experts have received relevant training.UIS ranks the 95th in terms of the Quality Infrastructure for Sustainable Development(QI4SD)and 80th in terms of the Global Quality Infrastructure Index(GQII).It is a member of ISO and an associate member of IEC.In the UIS,40 experts have participated in the activities of various ISO technical committees,and 251 experts have participated in the discussion of IEC projects as observer members.
文摘Malaria is considered one of the major causes of travel-related morbidity and mortality,especially among non-immune travelers from non-endemic countries to the endemic regions.According to a multicenter study from the GeoSentinel surveillance network,malaria was the most frequent cause of fever in 21%of returning travelers,followed by dengue,typhoid fever,chikungunya and rickettsiosis[1].Individuals traveling from regions without malaria transmission to areas where it is endemic face a heightened risk of contracting the disease due to their lack of immunity.Despite the official malaria-free status of the Russian Federation since 2010,annual cases of severe Plasmodium(P.)falciparum malaria continue to be reported[2].This underscores the necessity for heightened clinical vigilance and improved preventive strategies especially in non-endemic settings.
文摘Baosteel Technical Research,a quarterly journal,which is issued domestically and abroad,is run and sponsored by Baoshan Iron&Steel Co.,Ltd.Baosteel Technical Research mainly reports the achievements in technological innovation,academic research,new product development and industrial equipment improvement by Baosteel.It will continue to follow up on hot topics and serve the company's technological development and progress.
文摘Baosteel Technical Research,a quarterly journal,which is issued domestically and abroad,is run and sponsored by Baoshan Iron & Steel Co.,Ltd.. Baosteel Technical Research mainly reports the achievements in technological innovation,academic research,new product development and industrial equipment improvement by Baosteel. It will continue to follow up on hot topics and serve the company's technological development and progress. Its readers include experts in steel metallurgy and related fields,technicians,management staff,professors and students in universities and colleges.
基金supported by the Natural Science Foundation of Sichuan Province,China(2024NSFSC1272)the Innovation Team Development Funds for Sichuan Mutton Goat&Sheep,China(SCCXTD-2024-14)Scientific and Technological Innovation Team for Qinghai-Tibetan Plateau Research in Southwest Minzu University,China(2024CXTD08)。
文摘Bocapavovirus,a member of the genus Bocaparvovirus within the subfamily Parvovirinae and the family Parvoviridae,is a small,non-enveloped,single-stranded DNA virus.This pathogen poses health risks to both humans and animals.The Bocaparvovirus genome.
基金supported by the National Natural Science Foundation of China(No.52407064)。
文摘1.Opportunities for electric motor drives in the low-altitude economy The implementation plan for the innovative application of general aviation equipment(2024–2030)outlines that by 2027,new general aviation equipment will achieve commercial applications in urban air transport,logistics distribution and emergency rescue.
文摘In the process of building a new power system dominated by new energy sources,power storage is a key supporting technology that ensures the safe and stable operation of the power grid,enables the flexible regulation of the system,and raises the level of new energy consumption.It is also key to achieving carbon peak and neutrality as well as energy transformation.
文摘One reference in the original manuscript contained incorrect bibliographic information and cited a non-existent publication:Traczyk A(1999)Pleistocene debris cover beds and block-debris tongues in the north-western part of theŚlęża Massif(Poland)and their formation under permafrost conditions.Geographia Polonica 81(1).This erroneous reference has now been removed from the references list.
基金supported by the National Social Science Fund of China (19VJX168)。
文摘Hereditary angioedema (HAE) is a rare,autosomal dominant inherited disorder with an incidence of approximately 1 in 50,000.Among its various tapes,HAE with normal C1 inhibitor levels (HAE-nC1-INH)is exceptionally rare.^([1]) HAE symptoms include recurrent episodes of skin and mucosal edema that can occur anywhere in the body.^([1-4]) Laryngeal edema is life-threatening,as it can lead to airway obstruction and potentially fatal suffocation.^([1-3])Edema of the gastrointestinal mucosa may cause abdominal pain,vomiting,and symptoms that are often misdiagnosed as acute abdomen.^([1-4]) This study included four patients,including one with HAE-nC1-INH (genetic testing revealed a heterozygous mutation in the KNG1 gene (c.1404G>C:p.Q468H)) and three with HAE due to C1 inhibitor deficiency (HAE-C1-INH).This case series aims to increase knowledge of HAE by illustrating its diverse clinical presentations and emphasizing features that may prompt clinical suspicion and facilitate timely diagnosis.
文摘Obstructive Sleep Apnea(OSA)is a respiratory syndrome that occurs due to insufficient airflow through the respiratory or respiratory arrest while sleeping and sometimes due to the reduced oxygen saturation.The aim of this paper is to analyze the respiratory signal of a person to detect the Normal Breathing Activity and the Sleep Apnea(SA)activity.In the proposed method,the time domain and frequency domain features of respiration signal obtained from the PPG device are extracted.These features are applied to the Classification and Regression Tree(CART)-Particle Swarm Optimization(PSO)classifier which classifies the signal into normal breathing signal and sleep apnea signal.The proposed method is validated to measure the performance metrics like sensitivity,specificity,accuracy and F1 score by applying time domain and frequency domain features separately.Additionally,the performance of the CART-PSO(CPSO)classification algorithm is evaluated through comparing its measures with existing classification algorithms.Concurrently,the effect of the PSO algorithm in the classifier is validated by varying the parameters of PSO.
文摘Thermal image, or thermogram, becomes a new type of signal for machine condition monitoring and fault diagnosis due to the capability to display real-time temperature distribution and possibility to indicate the machine’s operating condition through its temperature. In this paper, an investigation of using the second-order statistical features of thermogram in association with minimum redundancy maximum relevance (mRMR) feature selection and simplified fuzzy ARTMAP (SFAM) classification is conducted for rotating machinery fault diagnosis. The thermograms of different machine conditions are firstly preprocessed for improving the image contrast, removing noise, and cropping to obtain the regions of interest (ROIs). Then, an enhanced algorithm based on bi-dimensional empirical mode decomposition is implemented to further increase the quality of ROIs before the second-order statistical features are extracted from their gray-level co-occurrence matrix (GLCM). The highly relevant features to the machine condition are selected from the total feature set by mRMR and are fed into SFAM to accomplish the fault diagnosis. In order to verify this investigation, the thermograms acquired from different conditions of a fault simulator including normal, misalignment, faulty bearing, and mass unbalance are used. This investigation also provides a comparative study of SFAM and other traditional methods such as back-propagation and probabilistic neural networks. The results show that the second-order statistical features used in this framework can provide a plausible accuracy in fault diagnosis of rotating machinery.
基金Supported by the Italian Ministry of Health-Current research IRCCS(Funds Dedicated to the Research of the Gastroenterology and Digestive Endoscopy Unit,Fondazione IRCCS Ca’Granda,Ospedale Maggiore Policlinico,Milano).
文摘BACKGROUND Endoscopic ultrasound(EUS)is crucial for diagnosing solid pancreatic lesions,especially pancreatic ductal adenocarcinoma(PDAC),a highly aggressive cancer which represents the majority with a prevalence of approximately 85%.AIM To identify EUS features that differentiate PDAC from other lesions such as neuroendocrine tumors(NETs)and helping in the differential diagnosis,by analyzing a large sample of solid pancreatic lesions.METHODS This observational,retrospective,multicenter study analyzed the endosonographic characteristics of 761 patients with a radiological diagnosis of solid pancreatic lesion,who underwent pancreatic EUS for typing and staging with needle biopsies between 2015 and 2023.General patient characteristics(age and sex)and solid lesion features were collected and described,such lesion size(Bmode),vessel involvement(compression or invasion),ductal dilation,lymphadenopathy,echogenicity,echopattern,margin regularity,multifocality,internal vascularization and elastography.Subsequently,a predictive analysis was performed through univariate and multivariate logistic regression to identify predictive features for PDAC or NET diagnoses.RESULTS Our study enrolled 761 patients,predominantly male with a mean age of 68.6.PDACs were generally larger(mean 33 mm×27 mm),often had irregular margins,and displayed significant upstream ductal dilation.Hypoechogenicity was common across malignant lesions.In contrast,NETs were smaller(mean 20 mm×17 mm)and typically had regular margins with multiple lesions.Vascular involvement,although predominant in PDAC,is a common feature of all malignant neoplasms.Multifocality,however,although a rare finding,is more typical of NETs and metastases,and practically absent in the remaining lesions.Predictive analyses showed that ductal dilation and irregular margins were the most significant predictors for PDAC[odds ratio(OR)=5.75 and 3.83],with hypoechogenicity,heterogeneous echopattern and lymphadenopathies also highly significant(OR=3.51,2.56 and 1.99).These features were inversely associated with NETs,with regular margins and absence of ductal involvement or lymphadenopathies(OR=0.24,0.86 and 0.45 respectively),as already shown by the descriptive analysis.Finally,age,despite achieving statistical significance,lacks clinical value given an OR trending towards 1.CONCLUSION This study provides a comprehensive overview of EUS features for solid pancreatic lesions,identifying distinct features like upstream ductal dilation and irregular margins for PDAC vs regular margins for NETs as strong diagnostic predictors.These findings enhance the understanding of pancreatic pathologies,offering valuable insights for improved differential diagnosis and clinical management,especially in complex cases.Further prospective studies could build on these results.
文摘The full potential of advanced coating and finishingtechnologies for the production of technical textiles willbe outlined by Monforts specialists at Techtextil NorthAmerica which takes place in Atlanta,Georgia,from May6-8.The company and its US representative PSP Market-ing,of Charlotte,North Carolina,will be part of the exten-sive VDMA German Pavilion at the show,at stand 323lwithin the Georgia World Congress Center.
