Photocatalytically Renewable Micro‐electrochemical Sensor for Real‐Time Monitoring of Cells

Electrode fouling and passivation is a substantial and inevitable limitation in electrochemical biosensing, and it is a great challenge to efficiently remove the contaminant without changing the surface structure and electrochemical performance. Herein, we propose a versatile and efficient strategy based on photocatalytic cleaning to construct renewable electrochemical sensors for cell analysis. This kind of sensor was fabricated by controllable assembly of reduced graphene oxide (RGO) and TiO₂ to form a sandwiching RGO@TiO₂ structure, followed by deposition of Au nanoparticles (NPs) onto the RGO shell. The Au NPs‐RGO composite shell provides high electrochemical performance. Meanwhile, the encapsulated TiO₂ ensures an excellent photocatalytic cleaning property. Application of this renewable microsensor for detection of nitric oxide (NO) release from cells demonstrates the great potential of this strategy in electrode regeneration and biosensing.     

Towards quantitative catalytic lignin depolymerization

The products of base-catalyzed liquid-phase hydrolysis of lignin depend markedly on the operating conditions. By varying temperature, pressure, catalyst concentration, and residence time, the yield of monomers and oligomers from depolymerized lignin can be adjusted. It is shown that monomers of phenolic derivatives are the only primary products of base-catalyzed hydrolysis and that oligomers form as secondary products. Oligomerization and polymerization of these highly reactive products, however, limit the amount of obtainable product oil containing low-molecular-weight phenolic products. Therefore, inhibition of concurrent oligomerization and polymerization reactions during hydrothermal lignin depolymerization is important to enhance product yields. Applying boric acid as a capping agent to suppress addition and condensation reactions of initially formed products is presented as a successful approach in this direction. Combination of base-catalyzed lignin hydrolysis with addition of boric acid protecting agent shifts the product distribution to lower molecular weight compounds and increases product yields beyond 85%.     

基于仿生智能纳米孔道的先进能源转换体系

自然界中的生命体系经过40多亿年的进化,实现了对能源的高效转换、存储和利用.特别是生物膜上的各类孔道结构在其中起着重要作用.基于仿生智能纳米通道的先进能源转换体系从生物离子通道中获取与能量转换相关的启示(例如,电鳗放电、ATP合成、视网膜、紫膜等),从原理和结构上模仿生命体系中高效能量转换的某一个侧面,通过产能材料的设计和转换器件的组装,实现机械能到电能、光能到电能、光能到化学能等不同能量形式之间的转换.我们综述了目前应用人工合成的纳米尺度孔道结构进行仿生能源转换的三个热点领域:纳米流体动能-电能转换,纳米流体反向电渗析系统和基于仿生智能纳米孔道的先进能源转换体系.基于智能纳米孔道的能源转换方法摆脱了传统发电设备所必需的机械转动装置的束缚,在可以预见的范围内,仿生产能器件的效能必将超越已有人工体系,为面向未来的能源技术的创新提供了新思路,新理论和新方法.     

Recent developments in Dual Resource Constrained (DRC) system research

Real world manufacturing systems are usually constrained by both machine and human resources. Human operators are often the constraining resource and transfer between workstations to process jobs when required. This kind of system is known as a Dual Resource Constrained (DRC) system and presents additional technical challenges which must be considered during planning and scheduling. These technical challenges can be categorised into the five main dimensions of job release mechanisms, job dispatching, worker flexibility, worker assignment and transfer costs. This paper aims to provide an overview of recent developments in DRC research concerned with each of these areas and also discusses some possible approaches to solving the resource scheduling problem in a DRC system. The focus is on materials published after 1995 and up to 2009. Previous reviews on DRC systems are commented on and followed by a review of recent works associated with each of the five dimensions of DRC system research. Advancements made and new methodologies proposed are discussed and future research directions are identified.     

水资源短缺风险因子的筛选模型

水资源短缺评价首先需要确定指标体系,投影寻踪模型与灰色关联度法相结合,可以有效地筛选出水资源短缺风险因子,为进一步进行风险评价奠定了基础,同时也为制定风险的防范措施和对策提供了理论依据.综合应用这两种模型,对北京市2001～2009年的水资源短缺风险进行研究,结果表明:降水量、日照时数、雨日数、单位GDP污水排放量、人均GDP、工业总产值占有率、污水处理率和水循环使用率这8个指标是北京市水资源短缺的主要风险因子.     

一种模态傅里叶-支持向量机优化的取用水监测异常数据重构方法

提高数据的完备与真实性是水资源监控能力建设的关键。针对国家水资源监控能力建设项目实施以来其监测数据呈现出的异常特征,按照“先粗筛后精选”逻辑,并考虑取用水季节性周期波动的特点,提出采用拉依达准则-模态分解-傅里叶残差修正的水监测数据异常值识别方法,并根据粒子群优化最小二乘支持向量机模型实现对异常数据的重构恢复。通过对企业取用水数据的实例分析,结果表明分段式拉依达准则在其监测异常数据的粗筛中具有较好的适用性,利用傅里叶修正集合模态分解的监测数据序列可取得更佳的拟合效果,从而达到异常数据精选的目的;而粒子群优化最小二乘支持向量机模型对异常数据重构恢复的可信度高于普通最小二乘支持向量机及传统曲线拟合数据重构方法,即该类取用水监测异常数据重构方法可有助于进一步推进其监测数据对实际水资源状态的客观反映。     

Novice facilitators’ changes in practices: From launching to managing discussions about mathematics teaching

Novice facilitators of professional development (PD) programs for mathematics teachers often face challenges in leading productive discussions and achieving the goals of these programs. Although research in this area is gradually accumulating, not much is known about how novice facilitators address these challenges and change their practices accordingly. This paper presents case studies of two novice facilitators of PD programs in two different countries. The analyses look at their work over one year, to illustrate the changes in their practices while managing discussions. The results show that although the facilitators operated in different contexts, their practices and their processes of change resembled, suggesting that these processes are not idiosyncratic. We argue that novice facilitators’ changes in practices correspond to changes in their resources, orientations, goals, and identities and that PD program teams can support these changes.     

Micro-economic analysis of the physical constrained markets: game theory application to competitive electricity markets

Competition has been introduced in the electricity markets with the goal of reducing prices and improving efficiency. The basic idea which stays behind this choice is that, in competitive markets, a greater quantity of the good is exchanged at a lower price, leading to higher market efficiency. Electricity markets are pretty different from other commodities mainly due to the physical constraints related to the network structure that may impact the market performance. The network structure of the system on which the economic transactions need to be undertaken poses strict physical and operational constraints. Strategic interactions among producers that game the market with the objective of maximizing their producer surplus must be taken into account when modeling competitive electricity markets. The physical constraints, specific of the electricity markets, provide additional opportunity of gaming to the market players. Game theory provides a tool to model such a context. This paper discussed the application of game theory to physical constrained electricity markets with the goal of providing tools for assessing the market performance and pinpointing the critical network constraints that may impact the market efficiency. The basic models of game theory specifically designed to represent the electricity markets will be presented. IEEE30 bus test system of the constrained electricity market will be discussed to show the network impacts on the market performances in presence of strategic bidding behavior of the producers.     

Enzymatic Determination of Glucose by Optical-Fiber Sensor Sequential Injection Renewable Surface Spectrophotometry

Introduction Determinationofglucoseisrequiredinmedicine industry,foodindustry,clinicaldiagnosisaswellas variousresearchfields.Therefore,intensiveefforts havebeendirectedtothedevelopmentofanalytical methodsfordeterminationofglucose,suchasthose basedonbiose…