目的探讨维生素K缺乏或拮抗剂诱导的蛋白质(protein induced by vitamin K absence or antagonist-Ⅱ,PIVKA-Ⅱ)、甲胎蛋白(α-fetoprotein,AFP)、甲胎蛋白异质体L3(α-fetoprotein heterogeneity-L3,AFP-L3)、癌胚抗原(carcinoembryoni...目的探讨维生素K缺乏或拮抗剂诱导的蛋白质(protein induced by vitamin K absence or antagonist-Ⅱ,PIVKA-Ⅱ)、甲胎蛋白(α-fetoprotein,AFP)、甲胎蛋白异质体L3(α-fetoprotein heterogeneity-L3,AFP-L3)、癌胚抗原(carcinoembryonic antigen,CEA)及不同组合模式在转移性肝细胞癌诊断中的应用及评分模型的构建。方法收集2019年1月至2022年7月我院283例肺癌、肠癌患者的血清,根据是否发生肝转移分为试验组(发生肝转移,n=70)和对照组(未发生肝转移,n=213),检测血清肿瘤标记物PIVKA-Ⅱ、AFP、AFP-L3、CEA的水平。比较各指标及其不同组合对转移性肝细胞癌筛查的敏感度、特异度,并绘制ROC曲线。通过单因素和多因素分析转移性肝细胞癌的独立影响因素,建立转移性细胞癌预测模型并验证。结果与对照组相比,试验组患者PIVKA-Ⅱ、AFP、AFP-L3、CEA的水平显著升高,差异有统计学意义(P<0.05)。两组在结肠息肉、脂肪肝、肿瘤大小、阳性淋巴结数目等方面比较,差异有统计学意义(P<0.05)。PIVKA-Ⅱ、AFP、AFP-L3、CEA、患有结肠息肉、脂肪肝、肿瘤≥5 cm、有阳性淋巴结是转移性肝细胞癌的独立危险因素(P<0.05)。在不同的组合指标中,PIVKA-Ⅱ+AFP+AFP-L3+CEA组合在敏感度和特异度等参数之间可达到相对最佳的平衡。对进入回归方程的指标进行风险评分,其中患有结肠息肉、患有脂肪肝、肿瘤大小≥5 cm、PIVKA-Ⅱ≥40 mAU/mL、AFP≥8.3 ng/mL、AFP-L3≥10%、CEA≥5.7 ng/mL七项指标分别设定为2、2、2、3、3、1.5、3.5分。总分在1.5~17分,根据百分位数进行评分分级,低危组<7分,中危组7~12.5分,高危组>12.5分,结果显示随着评分增加,转移性肝细胞癌风险增加。结论PIVKA-Ⅱ+AFP+AFP-L3+CEA组合在敏感度和特异度等参数之间可达到相对最佳的平衡,依据转移性肝细胞癌风险预测模型制定的评分标准有良好的预测性。展开更多
Fog computing has recently developed as a new paradigm with the aim of addressing time-sensitive applications better than with cloud computing by placing and processing tasks in close proximity to the data sources.How...Fog computing has recently developed as a new paradigm with the aim of addressing time-sensitive applications better than with cloud computing by placing and processing tasks in close proximity to the data sources.However,the majority of the fog nodes in this environment are geographically scattered with resources that are limited in terms of capabilities compared to cloud nodes,thus making the application placement problem more complex than that in cloud computing.An approach for cost-efficient application placement in fog-cloud computing environments that combines the benefits of both fog and cloud computing to optimize the placement of applications and services while minimizing costs.This approach is particularly relevant in scenarios where latency,resource constraints,and cost considerations are crucial factors for the deployment of applications.In this study,we propose a hybrid approach that combines a genetic algorithm(GA)with the Flamingo Search Algorithm(FSA)to place application modules while minimizing cost.We consider four cost-types for application deployment:Computation,communication,energy consumption,and violations.The proposed hybrid approach is called GA-FSA and is designed to place the application modules considering the deadline of the application and deploy them appropriately to fog or cloud nodes to curtail the overall cost of the system.An extensive simulation is conducted to assess the performance of the proposed approach compared to other state-of-the-art approaches.The results demonstrate that GA-FSA approach is superior to the other approaches with respect to task guarantee ratio(TGR)and total cost.展开更多
Cooperative utilization of multidimensional resources including cache, power and spectrum in satellite-terrestrial integrated networks(STINs) can provide a feasible approach for massive streaming media content deliver...Cooperative utilization of multidimensional resources including cache, power and spectrum in satellite-terrestrial integrated networks(STINs) can provide a feasible approach for massive streaming media content delivery over the seamless global coverage area. However, the on-board supportable resources of a single satellite are extremely limited and lack of interaction with others. In this paper, we design a network model with two-layered cache deployment, i.e., satellite layer and ground base station layer, and two types of sharing links, i.e., terrestrial-satellite sharing(TSS) links and inter-satellite sharing(ISS) links, to enhance the capability of cooperative delivery over STINs. Thus, we use rateless codes for the content divided-packet transmission, and derive the total energy efficiency(EE) in the whole transmission procedure, which is defined as the ratio of traffic offloading and energy consumption. We formulate two optimization problems about maximizing EE in different sharing scenarios(only TSS and TSS-ISS),and propose two optimized algorithms to obtain the optimal content placement matrixes, respectively.Simulation results demonstrate that, enabling sharing links with optimized cache placement have more than 2 times improvement of EE performance than other traditional placement schemes. Particularly, TSS-ISS schemes have the higher EE performance than only TSS schemes under the conditions of enough number of satellites and smaller inter-satellite distances.展开更多
文摘目的探讨维生素K缺乏或拮抗剂诱导的蛋白质(protein induced by vitamin K absence or antagonist-Ⅱ,PIVKA-Ⅱ)、甲胎蛋白(α-fetoprotein,AFP)、甲胎蛋白异质体L3(α-fetoprotein heterogeneity-L3,AFP-L3)、癌胚抗原(carcinoembryonic antigen,CEA)及不同组合模式在转移性肝细胞癌诊断中的应用及评分模型的构建。方法收集2019年1月至2022年7月我院283例肺癌、肠癌患者的血清,根据是否发生肝转移分为试验组(发生肝转移,n=70)和对照组(未发生肝转移,n=213),检测血清肿瘤标记物PIVKA-Ⅱ、AFP、AFP-L3、CEA的水平。比较各指标及其不同组合对转移性肝细胞癌筛查的敏感度、特异度,并绘制ROC曲线。通过单因素和多因素分析转移性肝细胞癌的独立影响因素,建立转移性细胞癌预测模型并验证。结果与对照组相比,试验组患者PIVKA-Ⅱ、AFP、AFP-L3、CEA的水平显著升高,差异有统计学意义(P<0.05)。两组在结肠息肉、脂肪肝、肿瘤大小、阳性淋巴结数目等方面比较,差异有统计学意义(P<0.05)。PIVKA-Ⅱ、AFP、AFP-L3、CEA、患有结肠息肉、脂肪肝、肿瘤≥5 cm、有阳性淋巴结是转移性肝细胞癌的独立危险因素(P<0.05)。在不同的组合指标中,PIVKA-Ⅱ+AFP+AFP-L3+CEA组合在敏感度和特异度等参数之间可达到相对最佳的平衡。对进入回归方程的指标进行风险评分,其中患有结肠息肉、患有脂肪肝、肿瘤大小≥5 cm、PIVKA-Ⅱ≥40 mAU/mL、AFP≥8.3 ng/mL、AFP-L3≥10%、CEA≥5.7 ng/mL七项指标分别设定为2、2、2、3、3、1.5、3.5分。总分在1.5~17分,根据百分位数进行评分分级,低危组<7分,中危组7~12.5分,高危组>12.5分,结果显示随着评分增加,转移性肝细胞癌风险增加。结论PIVKA-Ⅱ+AFP+AFP-L3+CEA组合在敏感度和特异度等参数之间可达到相对最佳的平衡,依据转移性肝细胞癌风险预测模型制定的评分标准有良好的预测性。
基金supported via funding from Prince Sattam bin Abdulaziz University Project Number(PSAU/2024/R/1445).
文摘Fog computing has recently developed as a new paradigm with the aim of addressing time-sensitive applications better than with cloud computing by placing and processing tasks in close proximity to the data sources.However,the majority of the fog nodes in this environment are geographically scattered with resources that are limited in terms of capabilities compared to cloud nodes,thus making the application placement problem more complex than that in cloud computing.An approach for cost-efficient application placement in fog-cloud computing environments that combines the benefits of both fog and cloud computing to optimize the placement of applications and services while minimizing costs.This approach is particularly relevant in scenarios where latency,resource constraints,and cost considerations are crucial factors for the deployment of applications.In this study,we propose a hybrid approach that combines a genetic algorithm(GA)with the Flamingo Search Algorithm(FSA)to place application modules while minimizing cost.We consider four cost-types for application deployment:Computation,communication,energy consumption,and violations.The proposed hybrid approach is called GA-FSA and is designed to place the application modules considering the deadline of the application and deploy them appropriately to fog or cloud nodes to curtail the overall cost of the system.An extensive simulation is conducted to assess the performance of the proposed approach compared to other state-of-the-art approaches.The results demonstrate that GA-FSA approach is superior to the other approaches with respect to task guarantee ratio(TGR)and total cost.
基金supported by National Natural Sciences Foundation of China(No.62271165,62027802,61831008)the Guangdong Basic and Applied Basic Research Foundation(No.2023A1515030297,2021A1515011572)Shenzhen Science and Technology Program ZDSYS20210623091808025,Stable Support Plan Program GXWD20231129102638002.
文摘Cooperative utilization of multidimensional resources including cache, power and spectrum in satellite-terrestrial integrated networks(STINs) can provide a feasible approach for massive streaming media content delivery over the seamless global coverage area. However, the on-board supportable resources of a single satellite are extremely limited and lack of interaction with others. In this paper, we design a network model with two-layered cache deployment, i.e., satellite layer and ground base station layer, and two types of sharing links, i.e., terrestrial-satellite sharing(TSS) links and inter-satellite sharing(ISS) links, to enhance the capability of cooperative delivery over STINs. Thus, we use rateless codes for the content divided-packet transmission, and derive the total energy efficiency(EE) in the whole transmission procedure, which is defined as the ratio of traffic offloading and energy consumption. We formulate two optimization problems about maximizing EE in different sharing scenarios(only TSS and TSS-ISS),and propose two optimized algorithms to obtain the optimal content placement matrixes, respectively.Simulation results demonstrate that, enabling sharing links with optimized cache placement have more than 2 times improvement of EE performance than other traditional placement schemes. Particularly, TSS-ISS schemes have the higher EE performance than only TSS schemes under the conditions of enough number of satellites and smaller inter-satellite distances.
