Proton nuclear(^(1)H)is the observed nucleus on which most magnetic resonance imaging(MRI)applications depend.Most traditional^(1)H MRI can provide structural and functional information about organisms,while various n...Proton nuclear(^(1)H)is the observed nucleus on which most magnetic resonance imaging(MRI)applications depend.Most traditional^(1)H MRI can provide structural and functional information about organisms,while various non-proton nuclei(X-nuclei)MRI can provide more metabolic information.However,due to the relatively poor signal-to-noise ratio(SNR)of X-nuclei MRI,their applications are quite rare compared to^(1)H.Benefit from the rapid developments of MRI hardware and software technologies,X-nuclei MRI has recently attracted increasing interests in biomedical research.This review firstly introduces some current methods to improve the SNR of X-nuclei MRI.Secondly,this review describes biomedical applications of X-nuclei MRI,especially focusing on the current use of X-nuclei(^(13)C,^(17)O,^(19)F,^(23)Na and^(31)P)MRI to study related diseases in different organs,including the brain,liver,kidney,heart and bone.Finally,perspectives studies on X-nuclei imaging and its potential applications are described in biomedical research.展开更多
2P DC 1500 V框架隔离开关适用于光伏、储能系统。这类产品相比老产品而言更具成本上的优势。产品主要的设计改进点为:修改机构连杆加大开距;主弧触头、窄缝灭弧技术通过临界电流试验;电场磁场的仿真设计专用灭弧以及绝缘技术保证灭弧...2P DC 1500 V框架隔离开关适用于光伏、储能系统。这类产品相比老产品而言更具成本上的优势。产品主要的设计改进点为:修改机构连杆加大开距;主弧触头、窄缝灭弧技术通过临界电流试验;电场磁场的仿真设计专用灭弧以及绝缘技术保证灭弧可靠通过电寿命试验。经试验验证,2P DC 1500 V框架隔离开关符合标准要求。展开更多
Currently, nuclear imaging such as positron emission tomography (PET) and single photon emission computed tomography (SPECT) is increasingly used in the management of liver malignancy. <sup>18</sup>F-fluor...Currently, nuclear imaging such as positron emission tomography (PET) and single photon emission computed tomography (SPECT) is increasingly used in the management of liver malignancy. <sup>18</sup>F-fluorodeoxyglucose (FDG)-PET is the most widely used nuclear imaging in liver malignancy as in other cancers, and has been reported to be effective in diagnosis, response monitoring, recurrence evaluation, and prognosis prediction. Other PET imaging such as <sup>11</sup>C-acetate PET is also used complementarily to FDG-PET in diagnosis of liver malignancy. Additionally, image-based evaluation of regional hepatic function can be performed using nuclear imaging. Those imaging modalities are also effective for candidate selection, treatment planning, and perioperative evaluation in liver surgery and transplantation. Recently, nuclear imaging has been actively adopted in the transarterial radioembolization therapy of liver malignancy, according to the concept of theragnosis. With the development of new hybrid imaging technologies such as PET/magnetic resonance imaging and SPECT/CT, nuclear imaging is expected to be more useful in the management of liver malignancy, particularly regarding liver surgery and transplantation. In this review, the efficacy and roles of nuclear imaging methods in diagnosis, transplantation and theragnosis are discussed.展开更多
目的探讨脑室-腹腔(V-P)分流术不同穿刺位置联合同期颅骨修补术在颅脑损伤脑积水患者中的效果及对凝血功能、粒系集落刺激因子(G-CSF)、肿瘤坏死因子-α(TNF-α)的影响。方法回顾性分析2020-06—2022-06晋城市人民医院121例颅脑损伤脑...目的探讨脑室-腹腔(V-P)分流术不同穿刺位置联合同期颅骨修补术在颅脑损伤脑积水患者中的效果及对凝血功能、粒系集落刺激因子(G-CSF)、肿瘤坏死因子-α(TNF-α)的影响。方法回顾性分析2020-06—2022-06晋城市人民医院121例颅脑损伤脑积水患者临床资料,根据手术方案分为A组(n=61)和B组(n=60),分别行V-P分流术(副三角区穿刺)+颅骨修补术、V-P分流术(侧脑室三角区穿刺)+颅骨修补术。统计2组脑积水改善情况、并发症、预后,对比术前、术后凝血功能、G-CSF、TNF-α、脑灌注情况、神经功能评分(NIHSS)。结果A组脑积水改善总有效率81.97%与B组80.00%比较,差异无统计学意义(P>0.05)。术后3 d、7 d A组血清APTT、PT水平低于B组,Fbg水平高于B组(P<0.05)。术后1个月A组血清G-CSF水平高于B组,TNF-α水平低于B组(P<0.05)。术前2组NIHSS评分、ICP、CCP比较,差异无统计学意义(P>0.05),术后1个月、3个月2组NIHSS评分、ICP低于术前,CCP高于术前(P<0.05)。A组并发症发生率(6.56%)低于B组(20.00%,P<0.05)。术后3个月,A组预后优良率(66.67%)与B组(67.24%)比较,差异无统计学意义(P>0.05)。结论V-P分流术不同穿刺位置联合同期颅骨修补术治疗颅脑损伤脑积水疗效相当,特别是副三角区穿刺,可减少并发症,降低血清G-CSF、TNF-α水平,且对凝血功能影响较小。展开更多
Plant disease classification and prevention of spreading of the disease at earlier stages based on visual leaves symptoms and Pest recognition through deep learning-based image classification is in the forefront of re...Plant disease classification and prevention of spreading of the disease at earlier stages based on visual leaves symptoms and Pest recognition through deep learning-based image classification is in the forefront of research.To perform the investigation on Plant and pest classification,Transfer Learning(TL)approach is used on EfficientNet-V2.TL requires limited labelled data and shorter training time.However,the limitation of TL is the pre-trained model network’s topology is static and the knowledge acquired is detrimentally overwriting the old parameters.EfficientNet-V2 is a Convolutional Neural Network(CNN)model with significant high speed learning rates across variable sized datasets.The model employs a form of progressive learning mechanism which expands the network topology gradually over the course of training process improving the model’s learning capacity.This provides a better interpretability of the model’s understanding on the test domains.With these insights,our work investigates the effectiveness of EfficienetV2 model trained on a class imbalanced dataset for plant disease classification and pest recognition by means of combining TL and progressive learning approach.This Progressive Learning for TL(PL-TL)is used in our work consisting of 38 classes of PlantVillage dataset of crops and fruit species,5 classes of cassava leaf diseases and another dataset with around 102 classes of crop pest images downloaded from popular dataset platforms,though it is not a benchmark dataset.To test the predictability rate of the model in classifying leaf diseases with similar visual symptoms,Mix-up data augmentation technique is used at the ratio of 1:4 on corn and tomato classes which has high probability of misinterpretation of disease classes.Also,the paper compares the TL approach performed on the above mentioned three types of data set using well established CNN based Inceptionv3,and Vision Transformer a non-CNN model.It clearly depicts that EfficientNetV2 has an outstanding performance of 99.5%,97.5%,80.1%on Cassava,PlantVillage and IP102 datasets respectively at a faster rate irrespective of the data size and class distribution as compared to Inception-V3 and ViT models.The performance metrics in terms of accuracy,precision,f1-score is also studied.展开更多
基金supported by Chinese Academy of Sciences MRI Technology Alliance under Grant 2020GZ1003.
文摘Proton nuclear(^(1)H)is the observed nucleus on which most magnetic resonance imaging(MRI)applications depend.Most traditional^(1)H MRI can provide structural and functional information about organisms,while various non-proton nuclei(X-nuclei)MRI can provide more metabolic information.However,due to the relatively poor signal-to-noise ratio(SNR)of X-nuclei MRI,their applications are quite rare compared to^(1)H.Benefit from the rapid developments of MRI hardware and software technologies,X-nuclei MRI has recently attracted increasing interests in biomedical research.This review firstly introduces some current methods to improve the SNR of X-nuclei MRI.Secondly,this review describes biomedical applications of X-nuclei MRI,especially focusing on the current use of X-nuclei(^(13)C,^(17)O,^(19)F,^(23)Na and^(31)P)MRI to study related diseases in different organs,including the brain,liver,kidney,heart and bone.Finally,perspectives studies on X-nuclei imaging and its potential applications are described in biomedical research.
文摘2P DC 1500 V框架隔离开关适用于光伏、储能系统。这类产品相比老产品而言更具成本上的优势。产品主要的设计改进点为:修改机构连杆加大开距;主弧触头、窄缝灭弧技术通过临界电流试验;电场磁场的仿真设计专用灭弧以及绝缘技术保证灭弧可靠通过电寿命试验。经试验验证,2P DC 1500 V框架隔离开关符合标准要求。
文摘Currently, nuclear imaging such as positron emission tomography (PET) and single photon emission computed tomography (SPECT) is increasingly used in the management of liver malignancy. <sup>18</sup>F-fluorodeoxyglucose (FDG)-PET is the most widely used nuclear imaging in liver malignancy as in other cancers, and has been reported to be effective in diagnosis, response monitoring, recurrence evaluation, and prognosis prediction. Other PET imaging such as <sup>11</sup>C-acetate PET is also used complementarily to FDG-PET in diagnosis of liver malignancy. Additionally, image-based evaluation of regional hepatic function can be performed using nuclear imaging. Those imaging modalities are also effective for candidate selection, treatment planning, and perioperative evaluation in liver surgery and transplantation. Recently, nuclear imaging has been actively adopted in the transarterial radioembolization therapy of liver malignancy, according to the concept of theragnosis. With the development of new hybrid imaging technologies such as PET/magnetic resonance imaging and SPECT/CT, nuclear imaging is expected to be more useful in the management of liver malignancy, particularly regarding liver surgery and transplantation. In this review, the efficacy and roles of nuclear imaging methods in diagnosis, transplantation and theragnosis are discussed.
文摘目的探讨脑室-腹腔(V-P)分流术不同穿刺位置联合同期颅骨修补术在颅脑损伤脑积水患者中的效果及对凝血功能、粒系集落刺激因子(G-CSF)、肿瘤坏死因子-α(TNF-α)的影响。方法回顾性分析2020-06—2022-06晋城市人民医院121例颅脑损伤脑积水患者临床资料,根据手术方案分为A组(n=61)和B组(n=60),分别行V-P分流术(副三角区穿刺)+颅骨修补术、V-P分流术(侧脑室三角区穿刺)+颅骨修补术。统计2组脑积水改善情况、并发症、预后,对比术前、术后凝血功能、G-CSF、TNF-α、脑灌注情况、神经功能评分(NIHSS)。结果A组脑积水改善总有效率81.97%与B组80.00%比较,差异无统计学意义(P>0.05)。术后3 d、7 d A组血清APTT、PT水平低于B组,Fbg水平高于B组(P<0.05)。术后1个月A组血清G-CSF水平高于B组,TNF-α水平低于B组(P<0.05)。术前2组NIHSS评分、ICP、CCP比较,差异无统计学意义(P>0.05),术后1个月、3个月2组NIHSS评分、ICP低于术前,CCP高于术前(P<0.05)。A组并发症发生率(6.56%)低于B组(20.00%,P<0.05)。术后3个月,A组预后优良率(66.67%)与B组(67.24%)比较,差异无统计学意义(P>0.05)。结论V-P分流术不同穿刺位置联合同期颅骨修补术治疗颅脑损伤脑积水疗效相当,特别是副三角区穿刺,可减少并发症,降低血清G-CSF、TNF-α水平,且对凝血功能影响较小。
文摘Plant disease classification and prevention of spreading of the disease at earlier stages based on visual leaves symptoms and Pest recognition through deep learning-based image classification is in the forefront of research.To perform the investigation on Plant and pest classification,Transfer Learning(TL)approach is used on EfficientNet-V2.TL requires limited labelled data and shorter training time.However,the limitation of TL is the pre-trained model network’s topology is static and the knowledge acquired is detrimentally overwriting the old parameters.EfficientNet-V2 is a Convolutional Neural Network(CNN)model with significant high speed learning rates across variable sized datasets.The model employs a form of progressive learning mechanism which expands the network topology gradually over the course of training process improving the model’s learning capacity.This provides a better interpretability of the model’s understanding on the test domains.With these insights,our work investigates the effectiveness of EfficienetV2 model trained on a class imbalanced dataset for plant disease classification and pest recognition by means of combining TL and progressive learning approach.This Progressive Learning for TL(PL-TL)is used in our work consisting of 38 classes of PlantVillage dataset of crops and fruit species,5 classes of cassava leaf diseases and another dataset with around 102 classes of crop pest images downloaded from popular dataset platforms,though it is not a benchmark dataset.To test the predictability rate of the model in classifying leaf diseases with similar visual symptoms,Mix-up data augmentation technique is used at the ratio of 1:4 on corn and tomato classes which has high probability of misinterpretation of disease classes.Also,the paper compares the TL approach performed on the above mentioned three types of data set using well established CNN based Inceptionv3,and Vision Transformer a non-CNN model.It clearly depicts that EfficientNetV2 has an outstanding performance of 99.5%,97.5%,80.1%on Cassava,PlantVillage and IP102 datasets respectively at a faster rate irrespective of the data size and class distribution as compared to Inception-V3 and ViT models.The performance metrics in terms of accuracy,precision,f1-score is also studied.
