Demands and technical developments of clinical flow cytometry with emphasis in quantitative,spectral,and imaging capabilities

As the gold-standard method for single-cell analysis,flow cytometry enables high-throughput and multiple-parameter characterization of individual biological cells.This review highlights the demands for clinical flow cytometry in laboratory hematology(e.g.,diagnoses of minimal residual disease and various types of leukemia),summarizes state-of-the-art clinical flow cytometers(e.g.,FACSLyricTMby Becton Dickinson,DxFLEX by Beckman Coulter),then considers innovative technical improvements in flow cytometry(including quantitative,spectral,and imaging approaches)to address the limitations of clinical flow cytometry in hematology diagnosis.Finally,driven by these clinical demands,future developments in clinical flow cytometry are suggested.

Quantitative assessment of the supply,demand and flows of ecosystem services in the Yangtze River Basin,China

Ecosystem service flow is essential for transporting,transforming,and maintaining ecosystem services and connecting supply and demand.This study attempted to quantitatively assess the supply and demand flows of ecosystem services in the Yangtze River Basin in 2000,2010,and 2020;assess the evolution of the spatial patterns of ecosystem service flow at the provincial,watershed and urban agglomeration scales;and design a zoning standard for ecosystem service flow.The results showed as follows.1)Between 2000 and 2020,the Yangtze River had a progressive drop in its freshwater supply,water conservation service and carbon sequestration service flows.The decline rates for these services were measured at 10.90%,11.11%,and 5.17%,respectively.The climate regulation service flow exhibited a pattern of initial fall followed by a subsequent increase,characterized by a decline rate of 35.53%.2)The lowest was the ecosystem service flow in the lower reaches of the Yangtze River and the Yangtze River Delta urban agglomeration.Freshwater supply service flow and water conservation service flow were the highest in the upper reaches of the Yangtze River and the Chengdu-Chongqing urban agglomeration.Carbon sequestration service flow and climate regulation service flow were the highest in the middle reaches of the Yangtze River Basin and the urban agglomeration in the middle reaches of the Yangtze River.3)From 2000 to 2020,the change ratios of the area proportion of the confluence,flow,and outflow areas in the Yangtze River Basin were 1.06,3.17,and 0.86,respectively.The results of this research could offer decision support for regulating ecosystem services in the Yangtze River Basin,promoting sustainable regional development and achieving rational use of the basin resources.

Study on Customer Demands for Product Innovation

In order to improve the satisfaction degree of customers’individual demands for products and reduce the risk of the product innovation,the characteristics of customer demands for product innovation are analyzed,and the type and content of customer demands are discussed.Then the framework of customer demands acquisition for product innovation is established.Final- ly,the prototype system of customer demands information acquisition and product customization for product innovation which takes mobile phone as the example is developed successfully.

Study on Customer Demands for Product Innovation

In order to improve the satisfaction degree of customers’ individual demands on products and reduce the risk of the product innovation,the characteristics of customer demands for product innovation are analyzed,and their type and content are discussed. Then the framework of customer demands acquisition for product innovation is established. Finally,the prototype system of customer demands information acquisition and product customization for product innovation which takes mobile phone as the example is developed successfully.

Generating Quantitative Product Profile Using Char-Word CNNs

The online customer reviews provide important information for product improvement and redesign.However,many reviews are redundant with only several short sentences,which may even conflict with each other on the same aspect of a product.Thus it is usually a very challenging task to extract useful design information from the reviews and provide a clear description on the product’s various aspects amongst its competitors.In order to resolve this issue,we propose an approach to build hierarchical product profiles to describe a product’s kernel design aspects quantitatively.It is achieved via three main strategies:a double propagation strategy to achieve the associated features and customers’descriptions;a deep text processing network to build the aspect hierarchy;an aspect ranking approach to quantify each kernel design aspect.Experimental results validate the effectiveness of the proposed approach on online reviews.

Influence of Customized Demand Generation as a Strategy to Increase Uptake of Voluntary Counseling and Testing Services amongst Sex Workers in Mumbai and Thane

Background: To demonstrate that customized demand generation leads to increased voluntary HIV counseling and testing (VCT) among Sex Workers (SWs). Methods: FHI 360 Aastha implemented Vivek intervention among SWs in Mumbai and Thane, India using customized demand generation through outreach services for VCT. Program monitoring data and integrated counseling and testing center tracking sheets were used to assess the intervention effect. Results: Higher proportion of registered SWs tested during: 1) Vivek months than other months (17% vs. 5%, p < 0.001);2) Post-initiation non-Vivek months than pre-Vivek months (4.7%, vs. 1.5% p < 0.001). Conclusions: Customized demand generation approach is successful in increasing HIV testing.

Application of a Bayesian Network Complex System Model Examining the Importance of Customer-Industry Engagement to Peak Electricity Demand Reduction

This paper explores the importance of customer-industry engagement (CIE) to peak energy demand by means of a newly developed Bayesian Network (BN) complex systems model entitled the Residential Electricity Peak Demand Model (REPDM). The REPDM is based on a multi-disciplinary perspective designed to solve the complex problem of residential peak energy demand. The model provides a way to conceptualise and understand the factors that shift and reduce consumer demand in peak times. To gain insight into the importance of customer-industry engagement in affecting residential peak demand, this research investigates intervention impacts and major influences through testing five scenarios using different levels of customer-industry engagement activities. Scenario testing of the model outlines the dependencies between the customer-industry engagement interventions and the probabilities that are estimated to govern the dependencies that influence peak demand. The output from the model shows that there can be a strong interaction between the level of CIE activities and interventions. The influence of CIE activity can increase public and householder support for peak reduction and the model shows how the economic, technical and social interventions can achieve greater peak demand reductions when well-designed with appropriate levels of CIE activities.

鄂尔多斯红庆河采煤矿区生态需水研究

鄂尔多斯红庆河煤矿区处在西部干旱半干旱内陆区域,由于煤炭开采导致生态环境问题较为突出,该区域水资源短缺、供需失衡,严重制约了矿区的生态恢复。在充分的自然概况调查基础上,将红庆河煤矿区生态需水划分为天然生态需水和人工生态需水2种类型。通过植被蒸散法对植被生态需水进行计算,使用马尔科夫链进行定性预测,利用灰色预测模型GM(1,1)进行定量预测。结果表明:以2020年为基准年,红庆河煤矿区总生态需水量为37.52×10^(7)m^(3),天然植被每平方千米乔木、灌木、草地生态需水量分别为1.11×10^(6)、1.06×10^(6)、0.36×10^(6)m^(3);人工生态需水量为1.39×10^(7)m^(3)。进一步对研究区生态需水进行定性、定量预测,规划年(2025年、2030年、2035年)矿区天然生态需水量相比基准年分别上升了0.61%、2.57%和4.57%;人工生态需水量分别上升了3.60%、11.51%和20.86%。研究结果可为该地区生态恢复中植被类型选择、水资源开发利用、合理调配水资源提供科学依据。

考虑需求响应和用户满意度的主动配电网优化调度

为提高主动配电网(active distribution network,ADN)运行经济性和用户满意度,提出一种考虑需求响应和用户满意度的ADN优化调度方法。综合考虑ADN运行过程中的购电成本、发电成本、维护成本和需求响应成本,建立了以ADN总运行成本最小为目标函数的优化调度模型。利用混沌映射、莱维飞行和收敛因子非线性变化等策略对斑点鬣狗优化算法(spotted hyena optimization,SHO)进行优化,以提高斑点鬣狗算法的优化性能。采用改进斑点鬣狗优化算法(ISHO)对ADN优化调度模型进行求解,算例分析结果表明,ISHO算法的优化效果优于其他算法,2种需求响应同时参与系统调度时的ADN总运行成本最小,经济性更好。

客户风险投资的供应链溢出效应——上游企业双元创新视角

本文以A股上市公司供应链关系数据为研究对象,考察客户风险投资对上游企业双元创新的影响。研究发现:客户风险投资具有供应链溢出效应,显著提高了上游企业的双元创新水平。机制检验表明,溢出效应主要通过企业学习机制与市场需求响应机制影响上游企业双元创新。此外,共同股东与客户集中度分别对上述关系起到正向调节作用。异质性检验结果表明,当上游企业客户关系良性程度较高以及融资约束较弱时,溢出效应对双元创新的促进作用更为明显;而当上游企业属于高科技行业时,溢出效应对探索式创新的促进作用更为明显。本文从风险投资供应链溢出视角出发,为企业双元创新提升的新路径提供了理论依据和政策启示。

面向内部客户需求的人力资源管理成熟度模型

人力资源管理成熟度是评价公司人力资源管理水平的重要工具。目前国内外人力资源管理成熟度模型普遍存在两点不足:缺乏内部客户思维、指标过多导致操作繁琐。本研究以公司高层管理者工作的典型需求为依据,精简评价指标,设计了新的人力资源管理成熟度模型,可以较好改善上述不足,并且具有较好的实践价值。

考虑需求密度和客户满意度的城市末端服务网点选址问题

为解决“最后一公里”的配送问题,结合城市末端配送需求的服务网点特点,考虑需求密度和客户满意度,建立了以时间满意度最大化、利润最大化和需求密度最大化为目标的多目标选址模型。设计了基于线性加权法的改进自适应遗传算法,采用自适应算子处理变异概率和交叉概率,并设计三种不同的交叉算子,扩大搜索邻域。在改进算子的基础上设计了多目标遗传算法,使用快速非支配排序法去除权重系数取值对选址结果的影响。利用北京市海淀区的快递服务网络数据进行实例分析,使用设计的两种遗传算法分别求解选址模型的全局最优解和帕累托前沿解;并将改进自适应遗传算法与传统遗传算法、自适应遗传算法的求解结果进行比较。结果显示:改进自适应遗传算法比传统遗传算法和自适应遗传算法收敛速度更快、搜索能力更优;若无法确定改进自适应遗传算法的权重,使用改进后的多目标遗传算法同样可以求到最优解。

餐饮老字号顾客满意度评价体系的构建与分析——以无锡市为例

为了对餐饮老字号顾客满意度进行评价,通过问卷调查和专家访谈,选出4个指标层、15个要素层,构建了顾客满意度评价模型。参考美国顾客满意度指数模型,结合餐饮老字号的服务特征,建立了顾客满意度评价体系,并对评价指标进行了定性描述。运用层次分析法计算各指标和要素的权重,并作了一致性检验,完成对评价体系的量化。从各指标在评价体系中所占的权重来看:产品质量是影响顾客满意度的最主要指标,后面依次为服务质量、宣传销售和文化内涵;15个影响要素中,绝对权重由高到低排名前5的依次为菜品口味、菜品卫生健康、服务态度、菜品营养价值和销售渠道。因此,餐饮老字号要提高顾客满意度,首先还是要在菜品质量上下功夫,既要传承经典又要不断创新。此外,还需加强人员培训,提高服务的意识与水平。同时,要积极利用信息化手段加强品牌宣传、提高订餐及支付的效率,综合提升顾客的满意度。

虚拟电厂两阶段准线型需求响应优化及收益共享-风险共担决策方法

末端分散式资源的需求响应(demand response,DR)是支撑电力系统灵活调节的重要形式,但末端资源通常规模大且单体容量小,迫切需要虚拟电厂(virtual power plant,VPP)等市场主体进行聚合代理,从而间接参与电网公司的调节服务。聚焦于准线型需求响应这一新兴的响应模式,重点研究VPP内部分散式资源的利益-风险互动协调策略,提出面向准线型DR的VPP两阶段优化及收益共享-风险共担决策方法,构建VPP与电网、内部用户互动协调新模式。首先,在准线型激励下VPP以整体收益最大化为目标,考虑柔性负荷响应积极度与新能源准确度因子,进行日前-日内两阶段DR优化;其次,在收益共享-风险共担决策方法下,VPP与柔性负荷共享准线型激励、与新能源共担不确定性风险,并以改进的Shapley法对内部柔性负荷进行利益分配。仿真结果表明,相较于传统DR,准线型DR给出全时段响应目标,更具有优越性;共享-共担决策吸引柔性负荷参与VPP调节,促使VPP与用户双赢。

基于负荷准线的5G基站虚拟电厂优化控制方法

在新型电力系统中,亟待深度挖掘需求侧资源以提升系统灵活性和新能源消纳能力。在“新基建”背景下,5G基站作为一种新型需求侧资源正迅速发展。研究如何在保证基站备用需求的前提下,由铁塔公司组建含大规模5G基站的虚拟电厂(virtual power plant,VPP)并常态化参与需求响应。首先,提出了考虑储能动态备用容量的5G基站运行可行域构建方法,建立了5G基站VPP的聚合模型。然后,建立了5G基站VPP响应负荷准线的日前优化模型,提出了适合对大规模5G基站进行协调控制的日内解聚合方法。最后,建立了含高比例新能源的区域电网仿真算例。仿真结果表明,聚合大规模基站参与准线型需求响应,可以显著降低5G基站的运行成本,同时提高电网的新能源消纳能力。

工业用户连续参与需求响应的用户基线负荷精准计算方法

提出了一种将K-means聚类分析与长短期记忆神经网络算法结合,通过工业同源组信息进行迁移学习优化的计算方法。该方法实现了对长时间连续参与需求响应的工业用户基线负荷的精准计算,提高了工业用户需求响应效果评价的准确性。通过城市级虚拟电厂平台采集的参与需求响应实践的工业用户电力负荷数据,验证了该方法的有效性。

论生成式AI时代的用户需求与表达范式——从分众匹配到层级递进的要素融合网络

生成式人工智能时代的用户需求与表达发生了极大的改变。相较于互联网媒介时代,生成式人工智能时代的用户需求表现为“基底需求—需求要素补充”的生成机制,呈现出“过程性”“渐进稳态性”和“要素融合下的细描微调”的新特点。用户需求的表达方式趋向“自然交互”,表达逻辑趋向“理性和非理性要素融合”,表达粒度也趋向“细粒度”。用户需求和需求表达方式的变化,本质上是用户需求个性化趋势驱动下的内容生产、分发和消费的自组织,这也意味着分众策略逐步失灵,整个新闻传播业态将迎来“自组织式”的质变。在生成式人工智能技术时代下把握用户需求和需求表达,需要关注新闻传播的自组织价值创生范式,这与用户的个性化需求相匹配。此外,用户深层心理机制可能是未来媒介产品开发的需求蓝海。

基于QFD的可伸缩式登船栈桥设计方法

针对可伸缩式登船栈桥设计流程,以客户需求为导向,构建了基于质量功能展开法的设计思路和方法。运用实景体验和场景打分的方法,深度挖掘5个维度的客户需求、关键质量特性和关键物料特性,通过AHP等方法进行权重分析,构建可伸缩栈桥分析的一阶质量屋和二阶质量屋,开展关键物料的重要度-成本分析,有效满足了客户需求和规范要求,形成可伸缩栈桥设计开发新模式。

考虑路网和用户满意度的集群电动汽车主从博弈优化调度策略

传统的电动汽车(electric vehicle,EV)集中优化方法在实际应用中面临调度困难、计算量大、缺乏真实数据支撑等问题,无法准确揭示各主体间的交互行为。为此,提出一种考虑路网和用户满意度的集群EV主从博弈优化调度策略。首先基于真实出行数据和路网数据模拟用户出行行为。其次,负荷聚合商(load aggregator,LA)整合EV负荷资源,对相似出行特性的EV进行聚类。在双层主从博弈模型中,LA作为上层领导者,聚类后的各EV子群作为下层跟随者。考虑EV用户不同消费偏好,通过优化LA定价策略、新能源及储能系统出力计划、EV集群充放电策略实现纳什均衡,达到各主体共赢,并使用改进遗传算法进行求解。最后,利用仿真验证了所提模型可有效提升LA收益及EV用户消费者剩余,增加新能源消纳,并可为不同消费偏好的用户提供差异化服务。

新型电力负荷资源响应性能量化评估指标体系研究

随着能源和信息通信技术的快速发展,新型负荷资源参与运行控制已成为电网运行的重要成分。新型负荷资源的响应存在差异性和不确定性,准确地量化评估电网新型负荷资源的响应性能成为电网运行的重要任务。为此,在电网运行控制角度,建立了电网新型负荷资源需求响应性能评估体系,定义了反映响应及时性、响应准确性、响应可靠性和响应利用率的各项指标和计算方法,并通过示例,演示了需求响应各项响应性能指标的计算过程,通过对3种不同响应的响应性能指标的比较,验证了提出的响应性能量化评估指标符合响应性能的直观判断,还能提供更全面的评估信息,能够准确评估新型负荷资源的响应性能,为电网运行控制、需求响应的考核结算提供了依据。