The large-scale development of electric vehicles(EVs)requires numerous charging stations to serve them,and the charging stations should be reasonably laid out and planned according to the charging demand of electric v...The large-scale development of electric vehicles(EVs)requires numerous charging stations to serve them,and the charging stations should be reasonably laid out and planned according to the charging demand of electric vehicles.Considering the costs of both operators and users,a site selection model for optimal layout planning of charging stations is constructed,and a queuing theory approach is used to determine the charging pile configuration to meet the charging demand in the planning area.To solve the difficulties of particle swarm global optimization search,the improved random drift particle swarm optimization(IRDPSO)and Voronoi diagram are used to jointly solve for the optimal layout of electric vehicles.The final arithmetic analysis verifies the feasibility and practicality of the model and algorithm,and the results show that the total social cost is minimized when the charging station is 9,the location of the charging station is close to the center of gravity and the layout is reasonable.展开更多
文摘目的:探讨发生组织学转化(histological transformation,HT)的滤泡淋巴瘤(follicular lymphoma,FL)患者的临床表现、组织病理学特征、不同治疗方案疗效及预后。方法:选取我院2018年12月至2022年10月收治的26例发生组织学转化的滤泡淋巴瘤患者,回顾性分析患者的临床特征、病理特征、治疗方案、疗效及生存状况。结果:26例患者,中位年龄57(43~97)岁,其中25例转化为弥漫大B细胞淋巴瘤(diffuse large B cell lymphoma,DLBCL),低级别转化2例,高级别转化19例,1例转化为B淋巴母细胞白血病/淋巴瘤(B-lymphoblastic leukemia/lymphoma,B-LBL);11例出现结外侵犯,8例出现骨髓侵犯;初步诊断时发生转化的患者17例,转化后的疗效5例达到CR,8例达到PR,化疗之后发生转化的患者9例,转化后疗效4例达到PR,两组ORR分别为76.5%和44.4%,两组ORR差异无统计学意义(P=0.194)。全部患者中位随访时间22个月,中位PFS未达到(3~45个月)和中位OS未达到(5~45个月),2年OS率和PFS率分别为80.7%和64.8%。单因素分析结果显示:ECOG评分(P=0.040)、Ki-67(P=0.005)是影响患者PFS的因素。Ann Arbor分期(P=0.014)、FLIPI-1评分(P=0.008)是影响患者OS的因素。多因素分析结果显示,Ki-67(P=0.028)是影响患者PFS独立的预后因素。结论:FL患者发生组织学转化后预后不良,ECOG评分≥2分、Ki-67≥70%的患者PFS差,Ann Arbor分期Ⅲ-Ⅳ期、FLIPI-1评分>2分的患者OS差,Ki-67是影响患者PFS的独立预后因素。
基金the National Social Science Foundation of China(No.18AJL014)。
文摘The large-scale development of electric vehicles(EVs)requires numerous charging stations to serve them,and the charging stations should be reasonably laid out and planned according to the charging demand of electric vehicles.Considering the costs of both operators and users,a site selection model for optimal layout planning of charging stations is constructed,and a queuing theory approach is used to determine the charging pile configuration to meet the charging demand in the planning area.To solve the difficulties of particle swarm global optimization search,the improved random drift particle swarm optimization(IRDPSO)and Voronoi diagram are used to jointly solve for the optimal layout of electric vehicles.The final arithmetic analysis verifies the feasibility and practicality of the model and algorithm,and the results show that the total social cost is minimized when the charging station is 9,the location of the charging station is close to the center of gravity and the layout is reasonable.
