科创中国

项目管理预算是项目管理投资控制的重要环节,结合南水北调天津干线工程建设管理工作实践,从编制方法和编制原则方面论述了概算和项目管理预算不同的编制过程,从南水北调投资价差编制和投资控制考评及奖惩等不同的角度反映了项目管理预算的重要性.事实证明,有效的利用项目管理预算与项目工程价款结算对比,能够对投资有效控制,减少投资风险.有利于提高管理水平,加强成本控制,提高经济效益.

糯扎渡水电工程的质量管理借鉴了国内外其他工程的先进经验,同时又具有鲜明的"糯扎渡特色".通过不断创新质量管理理念、建立健全工程质量管理体系、加强体系运行的有效性,基本做到了制度建设无缺漏、管理过程无漏洞、监督实施无缺为.采用事前控制及早预防、事中控制及时纠正、事后控制总结经验,互相衔接、严格把关,保证了糯扎渡水电工程质量在控、受控.

Insect source-sink dynamics are vital to ecologically intensive pest management. Maintaining sink plant hosts,or "trap crops",and destroying alternate hosts or breeding places adjacent to the field crop are effective pest management strategies for some arthropods. However,determining whether a host acts as a source or a sink is challenging, especially when the pest species is highly mobile and polyphagous. The western tarnished plant bug,Lygus hesperus,is highly polyphagous,and can utilize >300 hosts. Its presence has been documented in 26 roadside weed hosts in the Texas High Plains.Previous studies demonstrated that L. hesperus prefer alfalfa over cotton and several alternate weed hosts.A four-year project involved surveying and sampling for L. hesperus in the agricultural landscapes of several sub-regions of the southwestern United States,including the Texas High Plains. In Texas,geographic information of the landscape vegetation complex was compiled from a 150 km radius in the Texas High Plains. In one study,fifty irrigated cotton fields representing the crop diversity within this region were sampled via sweep-net for 10 weeks. This effort also included sampling of up to six noncotton insect habitats within a 3 km radius of each field. Seasonal average L. hesperus abundance data were regressed with 27 field characteristics( variables),including habitat-specific land cover,distance between focal cotton fields and non-cotton habitats,longitude,latitude,elevation,habitat heterogeneity index,and several environmental / ecological variables. Significant variables were selected using a stepwise regression at 15% probability rate. A 10-parameter linear model explained 93% of the variation in the data. Major parameters contributing significantly to variation in L. hesperus abundance in cotton were corn and sunflower acreages,focal cotton field distances from several non-cotton hosts,and habitat heterogeneity index. In addition,field marking-and-capture studies were conducted using protein markers and enzyme-linked immunosorbent assays to characterize L. hesperus intercrop movement behavior. The field marking-and-capture approach can be used to study the effects of various crop management practices on L. hesperus intercrop movement and can potentially be applied to other pests and cropping systems.

物流行业的飞速发展迫使物流公司有强烈的愿望通过上市进行资本融资,进而产生盈余管理的行为.首先对物流公司IPO过程中盈余管理的手段进行分析,进而又分析了其进行盈余管理的特点、识别方法及测度其盈余管理幅度的模型.

阐述了推进精益化仓储管理的重要意义,分析了当前仓储管理的现状与存在的主要问题,提出了推进精益化仓储管理的对策措施.

以南水北调中线SG09标石方开挖爆破施工为例,采用理论计算、数值分析和本工程实际施工相结合的方法,详细分析了爆破对周围环境的影响范围及安全控制措施,为类似工程的施工提供了参考.

文章对工作家庭冲突的定义、常用测量工具和国内外研究现状进行综述,并总结了工作家庭冲突的影响因素,结合我国护理专业特点提出平衡工作家庭关系的措施.

目的 探讨严格液体管理对重症肺部感染患者心肺保护作用及其可能的机制.方法 将157例重症肺部感染患者随机分为液体管理组和对照组,用脉搏指示连续心输出量监测(PiCCO)的方法检测血流动力学变化指标[心输出量(CO)、心指数(CI)、胸腔内血管容量( ITBVI)、血管外肺水(EVLWI)]并指导液体管理;实验前后测定患者血浆脑型利钠肽(BNP),评估液体管理对患者心功能的影响;测定纤支镜肺灌洗液中白细胞介素(IL)-6的浓度,以评估肺组织局部炎症情况,监测动脉血气分析;实验前后行胸部CT检查评价肺部病变恢复情况.结果 与对照组比较,液体管理组血浆脑型利钠肽、血流动力学指标( CO、CI、EVLWI)和肺组织局部IL-6水平均明显下降(P<0.05),动脉血气氧分压升高(P<0.05),肺泡-动脉氧分压差下降(P<0.05),肺部病变和肺功能明显改善.结论 积极液体管理可保护重症肺部感染患者的心肺功能,其原因可能与降低炎症反应及改善氧合有关.

江都站作为南水北调东线工程从长江取水的起点泵站,工程作用重要、运行十分频繁.本次按设计规划进行综合改造,涉及的工程数量多、范围广,施工对工程运行的影响较大,与运行的矛盾十分突出,为此,通过制订科学合理的总体实施方案、加强施工进度和安全管理、抓好工程调度运行管理、制订切实可行的应急措施等,妥善地处理了施工与运行的矛盾,在保证改造工程顺利实施的同时,工程效益也得到了充分发挥.

Cyber physical systems(CPS)recently emerge as a new technology which can provide promising approaches to demand side management(DSM),an important capability in industrial power systems.Meanwhile,the manufacturing center is a typical industrial power subsystem with dozens of high energy consumption devices which have complex physical dynamics.DSM,integrated with CPS,is an effective methodology for solving energy optimization problems in manufacturing center.This paper presents a prediction-based manufacturing center self-adaptive energy optimization method for demand side management in cyber physical systems.To gain prior knowledge of DSM operating results,a sparse Bayesian learning based componential forecasting method is introduced to predict24-hour electric load levels for specific industrial areas in China.From this data,a pricing strategy is designed based on short-term load forecasting results.To minimize total energy costs while guaranteeing manufacturing center service quality,an adaptive demand side energy optimization algorithm is presented.The proposed scheme is tested in a machining center energy optimization experiment.An AMI sensing system is then used to measure the demand side energy consumption of the manufacturing center.Based on the data collected from the sensing system,the load prediction-based energy optimization scheme is implemented.By employing both the PSO and the CPSO method,the problem of DSM in the manufacturing center is solved.The results of the experiment show the self-adaptive CPSO energy optimization method enhances optimization by 5%compared with the traditional PSO optimization method.