Hardware prefetching and replacement policies are two techniques to improve the performance of the memory subsystem.While prefetching hides memory latency and improves performance,interactions take place with the cach...Hardware prefetching and replacement policies are two techniques to improve the performance of the memory subsystem.While prefetching hides memory latency and improves performance,interactions take place with the cache replacement policies,thereby introducing performance variability in the application.To improve the accuracy of reuse of cache blocks in the presence of hardware prefetching,we propose Prefetch-Adaptive Intelligent Cache Replacement Policy(PAIC).PAIC is designed with separate predictors for prefetch and demand requests,and uses machine learning to optimize reuse prediction in the presence of prefetching.By distinguishing reuse predictions for prefetch and demand requests,PAIC can better combine the performance benefits from prefetching and replacement policies.We evaluate PAIC on a set of 27 memory-intensive programs from the SPEC 2006 and SPEC 2017.Under single-core configuration,PAIC improves performance over Least Recently Used(LRU)replacement policy by 37.22%,compared with improvements of 32.93%for Signature-based Hit Predictor(SHiP),34.56%for Hawkeye,and 34.43%for Glider.Under the four-core configuration,PAIC improves performance over LRU by 20.99%,versus 13.23%for SHiP,17.89%for Hawkeye and 15.50%for Glider.展开更多
AIM:To estimate the cost-benefit of endoscopic screening strategies of esophageal cancer(EC)in high-risk areas of China. METHODS:Markov model-based analyses were conducted to compare the net present values(NPVs)and th...AIM:To estimate the cost-benefit of endoscopic screening strategies of esophageal cancer(EC)in high-risk areas of China. METHODS:Markov model-based analyses were conducted to compare the net present values(NPVs)and the benefit-cost ratios(BCRs)of 12 EC endoscopic screening strategies.Strategies varied according to the targeted screening age,screening frequencies,and follow-up intervals.Model parameters were collected from population-based studies in China,published literatures,and surveillance data. RESULTS:Compared with non-screening outcomes,all strategies with hypothetical 100 000 subjects saved life years.Among five dominant strategies determined by the incremental cost-effectiveness analysis,screening once at age 50 years incurred the lowest NPV(international dollar-I$55 million)and BCR(2.52).Screening six times between 40-70 years at a 5-year interval[i.e., six times(40)f-strategy]yielded the highest NPV(I$99 million)and BCR(3.06).Compared with six times(40)fstrategy,screening thrice between 40-70 years at a 10-year interval resulted in relatively lower NPV,but the same BCR. CONCLUSION:EC endoscopic screening is cost-beneficial in high-risk areas of China.Policy-makers should consider the cost-benefit,population acceptance,and local economic status when choosing suitable screening strategies.展开更多
Background Spine surgery using computer-assisted navigation （CAN） has been proven to result in low screw misplacement rates, low incidence of radiation exposure and excellent operative field viewing versus the conve...Background Spine surgery using computer-assisted navigation （CAN） has been proven to result in low screw misplacement rates, low incidence of radiation exposure and excellent operative field viewing versus the conventional intraoperative image intensifier （CⅢ）. However, as we know, few previous studies have described the learning curve of CAN in spine surgery.Methods We performed two consecutive case cohort studies on pedicel screw accuracy and operative time of two spine surgeons with different experience backgrounds, A and B, in one institution during the same period. Lumbar pedicel screw cortical perforation rate and operative time of the same kind of operation using CAN were analyzed and compared using CⅢ for the two surgeons at initial, 6 months and 12 months of CAN usage.Results CAN spine surgery had an overall lower cortical perforation rate and less mean operative time compared with CⅢ for both surgeon A and B cohorts when total cases of four years were included. It missed being statistically significant,with 3.3% versus 4.7% （P=0.191） and 125.7 versus 132.3 minutes （P=0.428） for surgeon A and 3.6% versus 6.4%（P=0.058）, and 183.2 versus 213.2 minutes （P=0.070） for surgeon B. in an attempt to demonstrate the learning curve,the cases after 6 months of the CAN system in each surgeon＇s cohort were compared. The perforation rate decreased by 2.4% （P=0.039） and 4.3% （P=0.003） and the operative time was reduced by 31.8 minutes （P=0.002） and 14.4 minutes （P=0.026） for the CAN groups of surgeons A and B, respectively. When only the cases performed after 12 months using the CAN system were considered, the perforation rate decreased by 3.9% （P=0.006） and 5.6% （P 〈0.001） and the operative time was reduced by 20.9 minutes （P 〈0.001） and 40.3 minutes （P 〈0.001） for the CAN groups of surgeon A and B, respectively.Conclusions In the long run, CAN spine surgery decreased the lumbar screw cortical perforation rate and operative time. The learning curve s展开更多
Mesoproterozoic Shennongjia Group in Shennongjia Area can be divided into three subgroups in ascender order. Of which the lower subgroup includes Yingwodong, Dayanping, Macaoyuan, Luanshigou, Dawokeng and Kuangshishan...Mesoproterozoic Shennongjia Group in Shennongjia Area can be divided into three subgroups in ascender order. Of which the lower subgroup includes Yingwodong, Dayanping, Macaoyuan, Luanshigou, Dawokeng and Kuangshishan formations;the middle subgroup is formed by Yemahe, Wenshuihe and Shicaohe formations;the upper subgroup consists of Songziyuan and Wagangxi formations. Stromatolites developed very well in the carbonate rocks of each subgroup in Shennongjia Group. Based on descriptions of stromatolites macrotypes and their characteristics, this paper studied the formation environments, discussed the relationship among types, sizes, abundance of stromatolites and sedimentary environment, and established the formation and development pattern of stromatolites. As a result, this research also reveals the paleoenvironment and paleoclimate during the period of the Shennongjia Group deposited, which is beneficial to the study of paleoenvironment, paleogeography and paleoclimate, stratigraphic succession and regional correlation of the northern edge of Yangtze block. Stromatolites of Shennongjia Group are mainly conical, columnar, domal, wavy, stratiform and stromatolite reefs. The columnar and conical stromatolites are well developed. Conical stromatolites are mainly monomers, with a variety of pyramidal types, ranging in diameter from a few millimeters to several meters and formed in the high energy subtidal zone and tidal lagoon environment. Most of the columnar stromatolites are medium to small sizes implied a wide and gentle slope environment at that time. Stratiform (including wavy) stromatolites are larger scales and extends far away and distributed most widely in almost every horizon in the carbonate rocks. Stratiform stromatolites can be formed in low energy environments such as subtidal and intertidal zones and supratidal belts. Wavy stromatolites often developed in the hydrodynamic energy condition from weak energy intertidal zone gradually strengthened to the below of the high energy supratidal. Although stroma展开更多
BACKGROUND Spinal osteoporosis is a prevalent health condition characterized by the thinning of bone tissues in the spine,increasing the risk of fractures.Given its high incidence,especially among older populations,it...BACKGROUND Spinal osteoporosis is a prevalent health condition characterized by the thinning of bone tissues in the spine,increasing the risk of fractures.Given its high incidence,especially among older populations,it is critical to have accurate and effective predictive models for fracture risk.Traditionally,clinicians have relied on a combination of factors such as demographics,clinical attributes,and radiological characteristics to predict fracture risk in these patients.However,these models often lack precision and fail to include all potential risk factors.There is a need for a more comprehensive,statistically robust prediction model that can better identify high-risk individuals for early intervention.AIM To construct and validate a model for forecasting fracture risk in patients with spinal osteoporosis.METHODS The medical records of 80 patients with spinal osteoporosis who were diagnosed and treated between 2019 and 2022 were retrospectively examined.The patients were selected according to strict criteria and categorized into two groups:Those with fractures(n=40)and those without fractures(n=40).Demographics,clinical attributes,biochemical indicators,bone mineral density(BMD),and radiological characteristics were collected and compared.A logistic regression analysis was employed to create an osteoporotic fracture risk-prediction model.The area under the receiver operating characteristic curve(AUROC)was used to evaluate the model’s performance.RESULTS Factors significantly associated with fracture risk included age,sex,body mass index(BMI),smoking history,BMD,vertebral trabecular alterations,and prior vertebral fractures.The final risk-prediction model was developed using the formula:(logit[P]=-3.75+0.04×age-1.15×sex+0.02×BMI+0.83×smoking history+2.25×BMD-1.12×vertebral trabecular alterations+1.83×previous vertebral fractures).The AUROC of the model was 0.93(95%CI:0.88-0.96,P<0.001),indicating strong discriminatory capabilities.CONCLUSION The fracture risk-prediction model,utilizing accessible cli展开更多
基金supported by the Natural Science Foundation of Beijing under Grant No.4192007the National Natural Science Foundation of China under Grant No.61202076.
文摘Hardware prefetching and replacement policies are two techniques to improve the performance of the memory subsystem.While prefetching hides memory latency and improves performance,interactions take place with the cache replacement policies,thereby introducing performance variability in the application.To improve the accuracy of reuse of cache blocks in the presence of hardware prefetching,we propose Prefetch-Adaptive Intelligent Cache Replacement Policy(PAIC).PAIC is designed with separate predictors for prefetch and demand requests,and uses machine learning to optimize reuse prediction in the presence of prefetching.By distinguishing reuse predictions for prefetch and demand requests,PAIC can better combine the performance benefits from prefetching and replacement policies.We evaluate PAIC on a set of 27 memory-intensive programs from the SPEC 2006 and SPEC 2017.Under single-core configuration,PAIC improves performance over Least Recently Used(LRU)replacement policy by 37.22%,compared with improvements of 32.93%for Signature-based Hit Predictor(SHiP),34.56%for Hawkeye,and 34.43%for Glider.Under the four-core configuration,PAIC improves performance over LRU by 20.99%,versus 13.23%for SHiP,17.89%for Hawkeye and 15.50%for Glider.
基金Supported by The National Science and Technology Pillar Program of the 11th National Five-Year Plan of China,No. 2006BAI02A15
文摘AIM:To estimate the cost-benefit of endoscopic screening strategies of esophageal cancer(EC)in high-risk areas of China. METHODS:Markov model-based analyses were conducted to compare the net present values(NPVs)and the benefit-cost ratios(BCRs)of 12 EC endoscopic screening strategies.Strategies varied according to the targeted screening age,screening frequencies,and follow-up intervals.Model parameters were collected from population-based studies in China,published literatures,and surveillance data. RESULTS:Compared with non-screening outcomes,all strategies with hypothetical 100 000 subjects saved life years.Among five dominant strategies determined by the incremental cost-effectiveness analysis,screening once at age 50 years incurred the lowest NPV(international dollar-I$55 million)and BCR(2.52).Screening six times between 40-70 years at a 5-year interval[i.e., six times(40)f-strategy]yielded the highest NPV(I$99 million)and BCR(3.06).Compared with six times(40)fstrategy,screening thrice between 40-70 years at a 10-year interval resulted in relatively lower NPV,but the same BCR. CONCLUSION:EC endoscopic screening is cost-beneficial in high-risk areas of China.Policy-makers should consider the cost-benefit,population acceptance,and local economic status when choosing suitable screening strategies.
文摘Background Spine surgery using computer-assisted navigation （CAN） has been proven to result in low screw misplacement rates, low incidence of radiation exposure and excellent operative field viewing versus the conventional intraoperative image intensifier （CⅢ）. However, as we know, few previous studies have described the learning curve of CAN in spine surgery.Methods We performed two consecutive case cohort studies on pedicel screw accuracy and operative time of two spine surgeons with different experience backgrounds, A and B, in one institution during the same period. Lumbar pedicel screw cortical perforation rate and operative time of the same kind of operation using CAN were analyzed and compared using CⅢ for the two surgeons at initial, 6 months and 12 months of CAN usage.Results CAN spine surgery had an overall lower cortical perforation rate and less mean operative time compared with CⅢ for both surgeon A and B cohorts when total cases of four years were included. It missed being statistically significant,with 3.3% versus 4.7% （P=0.191） and 125.7 versus 132.3 minutes （P=0.428） for surgeon A and 3.6% versus 6.4%（P=0.058）, and 183.2 versus 213.2 minutes （P=0.070） for surgeon B. in an attempt to demonstrate the learning curve,the cases after 6 months of the CAN system in each surgeon＇s cohort were compared. The perforation rate decreased by 2.4% （P=0.039） and 4.3% （P=0.003） and the operative time was reduced by 31.8 minutes （P=0.002） and 14.4 minutes （P=0.026） for the CAN groups of surgeons A and B, respectively. When only the cases performed after 12 months using the CAN system were considered, the perforation rate decreased by 3.9% （P=0.006） and 5.6% （P 〈0.001） and the operative time was reduced by 20.9 minutes （P 〈0.001） and 40.3 minutes （P 〈0.001） for the CAN groups of surgeon A and B, respectively.Conclusions In the long run, CAN spine surgery decreased the lumbar screw cortical perforation rate and operative time. The learning curve s
基金This research was co-supported by the National Key Research and Development Program of China (2016YFC0601001),the National Natural Science Foundation of China (41472082)China Geological Survey Projects (DD20160120-01)+1 种基金Globe Geopark of Shennongjia. We are grateful to the leaders of Shennongjia National Park and Mr. Zhixian Wang,Quan Zhong gave great assistances and warmly aidsthe field survey was under careful direction by Mr. Lesheng Qu from Hubei Geological Survey,Mr. Yuansheng Geng from Institute of Geology,CAGS. Sincere thanks are also given Mr. Zejiu Wang,Xin Shang and Mrs. Xiulan Ma from Chinese Academy of Geological Sciences (CAGS) and All China Commission of Stratigraphy.
文摘Mesoproterozoic Shennongjia Group in Shennongjia Area can be divided into three subgroups in ascender order. Of which the lower subgroup includes Yingwodong, Dayanping, Macaoyuan, Luanshigou, Dawokeng and Kuangshishan formations;the middle subgroup is formed by Yemahe, Wenshuihe and Shicaohe formations;the upper subgroup consists of Songziyuan and Wagangxi formations. Stromatolites developed very well in the carbonate rocks of each subgroup in Shennongjia Group. Based on descriptions of stromatolites macrotypes and their characteristics, this paper studied the formation environments, discussed the relationship among types, sizes, abundance of stromatolites and sedimentary environment, and established the formation and development pattern of stromatolites. As a result, this research also reveals the paleoenvironment and paleoclimate during the period of the Shennongjia Group deposited, which is beneficial to the study of paleoenvironment, paleogeography and paleoclimate, stratigraphic succession and regional correlation of the northern edge of Yangtze block. Stromatolites of Shennongjia Group are mainly conical, columnar, domal, wavy, stratiform and stromatolite reefs. The columnar and conical stromatolites are well developed. Conical stromatolites are mainly monomers, with a variety of pyramidal types, ranging in diameter from a few millimeters to several meters and formed in the high energy subtidal zone and tidal lagoon environment. Most of the columnar stromatolites are medium to small sizes implied a wide and gentle slope environment at that time. Stratiform (including wavy) stromatolites are larger scales and extends far away and distributed most widely in almost every horizon in the carbonate rocks. Stratiform stromatolites can be formed in low energy environments such as subtidal and intertidal zones and supratidal belts. Wavy stromatolites often developed in the hydrodynamic energy condition from weak energy intertidal zone gradually strengthened to the below of the high energy supratidal. Although stroma
文摘BACKGROUND Spinal osteoporosis is a prevalent health condition characterized by the thinning of bone tissues in the spine,increasing the risk of fractures.Given its high incidence,especially among older populations,it is critical to have accurate and effective predictive models for fracture risk.Traditionally,clinicians have relied on a combination of factors such as demographics,clinical attributes,and radiological characteristics to predict fracture risk in these patients.However,these models often lack precision and fail to include all potential risk factors.There is a need for a more comprehensive,statistically robust prediction model that can better identify high-risk individuals for early intervention.AIM To construct and validate a model for forecasting fracture risk in patients with spinal osteoporosis.METHODS The medical records of 80 patients with spinal osteoporosis who were diagnosed and treated between 2019 and 2022 were retrospectively examined.The patients were selected according to strict criteria and categorized into two groups:Those with fractures(n=40)and those without fractures(n=40).Demographics,clinical attributes,biochemical indicators,bone mineral density(BMD),and radiological characteristics were collected and compared.A logistic regression analysis was employed to create an osteoporotic fracture risk-prediction model.The area under the receiver operating characteristic curve(AUROC)was used to evaluate the model’s performance.RESULTS Factors significantly associated with fracture risk included age,sex,body mass index(BMI),smoking history,BMD,vertebral trabecular alterations,and prior vertebral fractures.The final risk-prediction model was developed using the formula:(logit[P]=-3.75+0.04×age-1.15×sex+0.02×BMI+0.83×smoking history+2.25×BMD-1.12×vertebral trabecular alterations+1.83×previous vertebral fractures).The AUROC of the model was 0.93(95%CI:0.88-0.96,P<0.001),indicating strong discriminatory capabilities.CONCLUSION The fracture risk-prediction model,utilizing accessible cli
