为解决油浸式电力变压器中低能放电、高能放电等放电性故障的定位问题,提出了基于油中金属分析(Metal In-Oil Analysis,MIA)的放电性故障定位方法。通过对变压器内部高故障概率构件进行表面处理,将潜在的故障信息源预置于构件表面,并应...为解决油浸式电力变压器中低能放电、高能放电等放电性故障的定位问题,提出了基于油中金属分析(Metal In-Oil Analysis,MIA)的放电性故障定位方法。通过对变压器内部高故障概率构件进行表面处理,将潜在的故障信息源预置于构件表面,并应用示位金属(Metal for Position Indication,MPI)进行发生故障构件的确定。在此基础上,结合已有的局部放电、油中溶解气体分析等在线监测系统进行软、硬件的整合,可以实现较为完善的变压器放电性故障的诊断与定位。研究结果表明,该方法在提高放电性故障定位精度的同时,还可以降低对原有某种特定故障定位方法在精度方面的要求,并通过连续监测使运行维护人员对变压器的潜伏性故障信息有更为全面的掌握,为变压器状态检修的实现提供了新的技术支撑。展开更多
Objective: To investigate if intra-aortic balloon pump(IABP) is contraindicated without anticoag-ulation therapy. Methods: Some 153 IABP patients in the King Abdulaziz Cardiac Center(KSA) were random-ly assigned into ...Objective: To investigate if intra-aortic balloon pump(IABP) is contraindicated without anticoag-ulation therapy. Methods: Some 153 IABP patients in the King Abdulaziz Cardiac Center(KSA) were random-ly assigned into two groups. Anticoagulation group( Group A) consisted of 71 patients who were given heparin intravenously with target aPTT 50 - 70 seconds. Non-anticoagulation group( Group B) consisted of 82 patients without intravenous heparin during balloon pumping. Hematological parameters including platelet count, D-dimer, Plasminogen activator inhibitor-1 (PAI-1) and fibrinogen degradation products(FDP) were checked respectively at the point of baseline, 24 hours, 48 hours and 24 hours post IABP counterpulsation. Clot deposits on balloon surface, vascular complications from IABP including bleeding and limb ischemia were recorded.Results: Platelet count and PAI-1 level decreased at 24 hours and 48 hours in both groups ( P < 0.05) . D-dimer and FDP level increased at 24 hours and 48 hours in both groups( P < 0.05), but returned to the baseline level 24 hours post IABP removal( P > 0.05) . Three patients in Group A and 2 patients in Group B developed minor limb ischemia( P > 0.05). No major limb ischemia in either group. Two patients in Group A suffered major bleeding and required blood transfusion or surgical intervention, whereas no patient had major bleeding in Group B. Eight patients had minor bleeding in Group A, but only 2 patients in Group B ( P <0.05). No clot deposit developed on IABP surface in either group. Conclusion: IABP is safe without routine anticoagulation therapy. Selecting appropriate artery approach and early detection intervention are key methods for preventing complications.展开更多
Objective： To identify the differences among preinvasive lesions, minimally invasive adenocarcinomas （MIAs）and invasive pulmonary adenocarcinomas （IPAs） based on radiomic feature analysis with computed tomography...Objective： To identify the differences among preinvasive lesions, minimally invasive adenocarcinomas （MIAs）and invasive pulmonary adenocarcinomas （IPAs） based on radiomic feature analysis with computed tomography（CT）.Methods： A total of 109 patients with ground-glass opacity lesions （GGOs） in the lungs determined by CTexaminations were enrolled, all of whom had received a pathologic diagnosis. After the manual delineation andsegmentation of the GGOs as regions of interest （ROIs）, the patients were subdivided into three groups based onpathologic analyses： the preinvasive lesions （including atypical adenomatous hyperplasia and adenocarcinoma insitu） subgroup, the MIA subgroup and the IPA subgroup. Next, we obtained the texture features of the GGOs. Thedata analysis was aimed at finding both the differences between each pair of the groups and predictors to distinguishany two pathologic subtypes using logistic regression. Finally, a receiver operating characteristic （ROC） curve wasapplied to accurately evaluate the performances of the regression models.Results： We found that the voxel count feature （P〈0.001） could be used as a predictor for distinguishing IPAsfrom preinvasive lesions. However, the surface area feature （P=0.040） and the extruded surface area feature（P=0.013） could be predictors of IPAs compared with MIAs. In addition, the correlation feature （P=0.046） coulddistinguish preinvasive lesions from MIAs better.Conclusions： Preinvasive lesions, MIAs and IPAs can be discriminated based on texture features within CTimages, although the three diseases could all appear as GGOs on CT images. The diagnoses of these three diseasesare very important for clinical surgery.展开更多
The recent interest in the deployment of Generative AI applications that use large language models (LLMs) has brought to the forefront significant privacy concerns, notably the leakage of Personally Identifiable Infor...The recent interest in the deployment of Generative AI applications that use large language models (LLMs) has brought to the forefront significant privacy concerns, notably the leakage of Personally Identifiable Information (PII) and other confidential or protected information that may have been memorized during training, specifically during a fine-tuning or customization process. We describe different black-box attacks from potential adversaries and study their impact on the amount and type of information that may be recovered from commonly used and deployed LLMs. Our research investigates the relationship between PII leakage, memorization, and factors such as model size, architecture, and the nature of attacks employed. The study utilizes two broad categories of attacks: PII leakage-focused attacks (auto-completion and extraction attacks) and memorization-focused attacks (various membership inference attacks). The findings from these investigations are quantified using an array of evaluative metrics, providing a detailed understanding of LLM vulnerabilities and the effectiveness of different attacks.展开更多
目的为舌侧矫治种植支抗关闭拔牙间隙过程中的力学分析建立三维有限元模型。方法选取一例舌侧矫治病例,矫治前拍摄头颅CBCT,用Mimics10.0软件通过三维重建的方法获得牙齿及颌骨(含皮质骨和松质骨)的三维模型。将CBCT获得的重建模型和三...目的为舌侧矫治种植支抗关闭拔牙间隙过程中的力学分析建立三维有限元模型。方法选取一例舌侧矫治病例,矫治前拍摄头颅CBCT,用Mimics10.0软件通过三维重建的方法获得牙齿及颌骨(含皮质骨和松质骨)的三维模型。将CBCT获得的重建模型和三维数字化扫描模型用Rapid Form 2006软件配准,获得牙齿及颌骨三维整合牙颌模型,用该整合模型进行数字化排牙得到牙冠牙根良好排列的排牙模型,然后用Pro/E软件设计弓丝,并用Mimics10.0软件进行托槽定位,用ANSYS12.0软件进行网格划分,最终获得牙齿、皮质骨、松质骨、弓丝、托槽的三维有限元模型。用CBCT图像扫描获得A1(2.0x12.0mm)的种植钉,重建获得种植钉的三维有限元模型。结果建立了包括牙齿、颌骨(含松质骨和皮质骨)、舌侧托槽、弓丝、种植体的三维有限元的整体模型。结论建立的有限元模型模拟了实际临床矫治过程中牙齿及颌骨的原始解剖形态,网格划分详细,可以模拟正畸临床中牙齿及颌骨的受力情况及位移情况。展开更多
The recent interest in the deployment of Generative AI applications that use large language models (LLMs) has brought to the forefront significant privacy concerns, notably the leakage of Personally Identifiable Infor...The recent interest in the deployment of Generative AI applications that use large language models (LLMs) has brought to the forefront significant privacy concerns, notably the leakage of Personally Identifiable Information (PII) and other confidential or protected information that may have been memorized during training, specifically during a fine-tuning or customization process. This inadvertent leakage of sensitive information typically occurs when the models are subjected to black-box attacks. To address the growing concerns of safeguarding private and sensitive information while simultaneously preserving its utility, we analyze the performance of Targeted Catastrophic Forgetting (TCF). TCF involves preserving targeted pieces of sensitive information within datasets through an iterative pipeline which significantly reduces the likelihood of such information being leaked or reproduced by the model during black-box attacks, such as the autocompletion attack in our case. The experiments conducted using TCF evidently demonstrate its capability to reduce the extraction of PII while still preserving the context and utility of the target application.展开更多
文摘为解决油浸式电力变压器中低能放电、高能放电等放电性故障的定位问题,提出了基于油中金属分析(Metal In-Oil Analysis,MIA)的放电性故障定位方法。通过对变压器内部高故障概率构件进行表面处理,将潜在的故障信息源预置于构件表面,并应用示位金属(Metal for Position Indication,MPI)进行发生故障构件的确定。在此基础上,结合已有的局部放电、油中溶解气体分析等在线监测系统进行软、硬件的整合,可以实现较为完善的变压器放电性故障的诊断与定位。研究结果表明,该方法在提高放电性故障定位精度的同时,还可以降低对原有某种特定故障定位方法在精度方面的要求,并通过连续监测使运行维护人员对变压器的潜伏性故障信息有更为全面的掌握,为变压器状态检修的实现提供了新的技术支撑。
文摘Objective: To investigate if intra-aortic balloon pump(IABP) is contraindicated without anticoag-ulation therapy. Methods: Some 153 IABP patients in the King Abdulaziz Cardiac Center(KSA) were random-ly assigned into two groups. Anticoagulation group( Group A) consisted of 71 patients who were given heparin intravenously with target aPTT 50 - 70 seconds. Non-anticoagulation group( Group B) consisted of 82 patients without intravenous heparin during balloon pumping. Hematological parameters including platelet count, D-dimer, Plasminogen activator inhibitor-1 (PAI-1) and fibrinogen degradation products(FDP) were checked respectively at the point of baseline, 24 hours, 48 hours and 24 hours post IABP counterpulsation. Clot deposits on balloon surface, vascular complications from IABP including bleeding and limb ischemia were recorded.Results: Platelet count and PAI-1 level decreased at 24 hours and 48 hours in both groups ( P < 0.05) . D-dimer and FDP level increased at 24 hours and 48 hours in both groups( P < 0.05), but returned to the baseline level 24 hours post IABP removal( P > 0.05) . Three patients in Group A and 2 patients in Group B developed minor limb ischemia( P > 0.05). No major limb ischemia in either group. Two patients in Group A suffered major bleeding and required blood transfusion or surgical intervention, whereas no patient had major bleeding in Group B. Eight patients had minor bleeding in Group A, but only 2 patients in Group B ( P <0.05). No clot deposit developed on IABP surface in either group. Conclusion: IABP is safe without routine anticoagulation therapy. Selecting appropriate artery approach and early detection intervention are key methods for preventing complications.
基金supported by the Special Fund of Pharmacy, Radiology and Ecsomatics of Tianjin Medical University Cancer Institute & Hospital (No. Y1507)
文摘Objective： To identify the differences among preinvasive lesions, minimally invasive adenocarcinomas （MIAs）and invasive pulmonary adenocarcinomas （IPAs） based on radiomic feature analysis with computed tomography（CT）.Methods： A total of 109 patients with ground-glass opacity lesions （GGOs） in the lungs determined by CTexaminations were enrolled, all of whom had received a pathologic diagnosis. After the manual delineation andsegmentation of the GGOs as regions of interest （ROIs）, the patients were subdivided into three groups based onpathologic analyses： the preinvasive lesions （including atypical adenomatous hyperplasia and adenocarcinoma insitu） subgroup, the MIA subgroup and the IPA subgroup. Next, we obtained the texture features of the GGOs. Thedata analysis was aimed at finding both the differences between each pair of the groups and predictors to distinguishany two pathologic subtypes using logistic regression. Finally, a receiver operating characteristic （ROC） curve wasapplied to accurately evaluate the performances of the regression models.Results： We found that the voxel count feature （P〈0.001） could be used as a predictor for distinguishing IPAsfrom preinvasive lesions. However, the surface area feature （P=0.040） and the extruded surface area feature（P=0.013） could be predictors of IPAs compared with MIAs. In addition, the correlation feature （P=0.046） coulddistinguish preinvasive lesions from MIAs better.Conclusions： Preinvasive lesions, MIAs and IPAs can be discriminated based on texture features within CTimages, although the three diseases could all appear as GGOs on CT images. The diagnoses of these three diseasesare very important for clinical surgery.
文摘The recent interest in the deployment of Generative AI applications that use large language models (LLMs) has brought to the forefront significant privacy concerns, notably the leakage of Personally Identifiable Information (PII) and other confidential or protected information that may have been memorized during training, specifically during a fine-tuning or customization process. We describe different black-box attacks from potential adversaries and study their impact on the amount and type of information that may be recovered from commonly used and deployed LLMs. Our research investigates the relationship between PII leakage, memorization, and factors such as model size, architecture, and the nature of attacks employed. The study utilizes two broad categories of attacks: PII leakage-focused attacks (auto-completion and extraction attacks) and memorization-focused attacks (various membership inference attacks). The findings from these investigations are quantified using an array of evaluative metrics, providing a detailed understanding of LLM vulnerabilities and the effectiveness of different attacks.
文摘目的为舌侧矫治种植支抗关闭拔牙间隙过程中的力学分析建立三维有限元模型。方法选取一例舌侧矫治病例,矫治前拍摄头颅CBCT,用Mimics10.0软件通过三维重建的方法获得牙齿及颌骨(含皮质骨和松质骨)的三维模型。将CBCT获得的重建模型和三维数字化扫描模型用Rapid Form 2006软件配准,获得牙齿及颌骨三维整合牙颌模型,用该整合模型进行数字化排牙得到牙冠牙根良好排列的排牙模型,然后用Pro/E软件设计弓丝,并用Mimics10.0软件进行托槽定位,用ANSYS12.0软件进行网格划分,最终获得牙齿、皮质骨、松质骨、弓丝、托槽的三维有限元模型。用CBCT图像扫描获得A1(2.0x12.0mm)的种植钉,重建获得种植钉的三维有限元模型。结果建立了包括牙齿、颌骨(含松质骨和皮质骨)、舌侧托槽、弓丝、种植体的三维有限元的整体模型。结论建立的有限元模型模拟了实际临床矫治过程中牙齿及颌骨的原始解剖形态,网格划分详细,可以模拟正畸临床中牙齿及颌骨的受力情况及位移情况。
文摘The recent interest in the deployment of Generative AI applications that use large language models (LLMs) has brought to the forefront significant privacy concerns, notably the leakage of Personally Identifiable Information (PII) and other confidential or protected information that may have been memorized during training, specifically during a fine-tuning or customization process. This inadvertent leakage of sensitive information typically occurs when the models are subjected to black-box attacks. To address the growing concerns of safeguarding private and sensitive information while simultaneously preserving its utility, we analyze the performance of Targeted Catastrophic Forgetting (TCF). TCF involves preserving targeted pieces of sensitive information within datasets through an iterative pipeline which significantly reduces the likelihood of such information being leaked or reproduced by the model during black-box attacks, such as the autocompletion attack in our case. The experiments conducted using TCF evidently demonstrate its capability to reduce the extraction of PII while still preserving the context and utility of the target application.
