An interpretative structural modeling based network reconfiguration strategy for power systems

The network reconfiguration is an important stage of restoring a power system after a complete blackout or a local outage. Reasonable planning of the network reconfiguration procedure is essential for rapidly restoring the power system concerned. An approach for evaluating the importance of a line is first proposed based on the line contraction concept. Then, the interpretative structural modeling (ISM) is employed to analyze the relationship among the factors having impacts on the network reconfiguration. The security and speediness of restoring generating units are considered with priority, and a method is next proposed to select the generating unit to be restored by maximizing the restoration benefit with both the generation capacity of the restored generating unit and the importance of the line in the restoration path considered. Both the start-up sequence of generating units and the related restoration paths are optimized together in the proposed method, and in this way the shortcomings of separately solving these two issues in the existing methods are avoided. Finally, the New England 10-unit 39-bus power system and the Guangdong power system in South China are employed to demonstrate the basic features of the proposed method.     

The influence of activated carbon as an additive in anode materials for low temperature solid oxide fuel cells

The effects of activated carbon (AC) as an additive in multi-oxide nano composite LiNiCuZn–O for application as anode in solid oxide fuel cell (SOFC) is reported. The composite was synthesized using solid state reactions method with varying content of AC in range 0.1%–0.9% for use as anode in the cell. The cell was composed of the synthesized composite as anode, LiNiCuZn–O as cathode and Samaria doped ceria (SDC) as electrolyte. The prepared composites were characterized for morphology and crystal structure by scanning electron microscope (SEM) and x-ray diffraction (XRD) respectively. Furthermore, the crystallite sizes of LiNiCuZn–O and LiNiCuZn–O with AC as an additive have been found in the range from 50 nm to 70 nm. The prepared composite materials were observed porous and the porosity of the sample having 0.5% additive was found highest. The conductivity and power density of the SOFC were studied at temperature of 600 °C. The maximum value of conductivity was found as 4.79 S/cm for the composite containing 0.5% AC as measured by using 4-probe method. The maximum value of power density of the fuel cell with anode comprising of 0.5% AC along with the mentioned cathode and the electrolyte was 455 mW/cm². Therefore, out of the compositions studied, the composite comprising of LiNiCuZn–O with 0.5% AC offered best performance for anode in the cell. This oxide composite is reported as a potential candidate for use as anode in low temperature SOFCs.     

荷花山铅锌矿与铜陵地区其它矿床成矿控制因素的对比研究

为了探讨荷花山铅锌矿控矿因素上与铜陵地区其它矿床异同，运用宏、微观相结合，地质观察研究同位素地球化学以及流体包裹体分析相结合的方法，通过地层岩性、地质构造、特定地质体及成矿流体的来源和性质等几个方面与成矿关系的比较，揭示了这种新类型矿床的控矿因素的特点是与岩浆关系不密切的低温热液、角砾岩控矿。得出了这种新类型矿床既具有铜陵地区其它矿床的控矿因素，同时也具有自己独特的控矿因素的结论。     

磁絮凝强化技术处理厌氧消化污泥脱水液

为满足后续生物处理单元对固体悬浮物（SS）和铁浓度的进水要求，采用磁絮凝强化技术对厌氧消化污泥脱水液进行预处理。通过正交试验和单因素试验，本文考察了混凝水力条件、聚合氯化铝（PAC）投加量、聚丙烯酰胺（PAM）投加量、磁粉投加量及药剂投加顺序对磁絮凝效果的影响。试验结果表明：磁絮凝强化技术在快搅300r/min（2min）、慢搅100r/min（15min）、静置10min时，依次投加磁粉（40mg/L）、PAC（30mg/L）、PAM（4mg/L）时处理效果最好。在此运行条件下，SS和Fe³⁺去除率分别为97.61%、98.24%、絮凝指数（FI值）取得最大值、zeta电位绝对值最小，絮凝效果最佳。与对照相比，磁絮凝强化技术对SS和Fe³⁺去除率分别可提高3.70%和10.82%，同时絮体最大沉降速度可提高33%。磁絮凝技术处理后的出水不仅可以满足后续生物处理单元对SS和铁浓度的要求，还可以有效提高磁絮凝体的沉降速度，减小沉淀时间，具有较好的实用价值。     

Assessing trophic position quantification methods for three piscivorous freshwater fish using stable isotopes and stomach contents

Accurate trophic position (TP) estimates are important for the development of ecosystem-based management plans. TPs can be quantified by carbon (δ¹³C) and nitrogen (δ¹⁵N) stable isotopes in tissues, but these can disagree with observed and perceived feeding ecology. A recent method that has used a scaled diet-tissue discrimination factor (DTDF), reflecting the inverse relationship between DTDF and δ¹⁵N, was found to better describe TPs of predatory fish species in marine ecosystems, but this has not been tested in freshwater ecosystems. Here, we compare methods of TP estimations in the Lake Huron-Erie corridor (HEC), a system where high diversity of prey items has contributed to the concern that foraging ecology of piscivorous fish species is poorly understood. Using δ¹⁵N and δ¹³C, we quantified TP of longnose gar (Lepisosteus osseus), largemouth bass (Micropterus salmoides), and northern pike (Esox lucius) to assess the efficacy of a scaled DTDF compared to traditional DTDF isotope methods and stomach content analysis (SCA). The scaled DTDF method produced TP estimates that were at times consistent with SCA and were generally higher and with a greater range among individuals than non-scaled DTDFs. The scaled method was not sensitive to baseline choice nor influenced by incorporating carbon source in the model. Greater variability of TP estimates using a scaled DTDF suggests more complex trophic structuring in the upper trophic level guild of the HEC. These results, particularly the lack of baseline sensitivity, provide support for using the scaled DTDF in freshwater food web characterization.     

Cell Sheet Comprised of Mesenchymal Stromal Cells Overexpressing Stem Cell Factor Promotes Epicardium Activation and Heart Function Improvement in a Rat Model of Myocardium Infarction

Cell therapy of the post-infarcted myocardium is still far from clinical use. Poor survival of transplanted cells, insufficient regeneration, and replacement of the damaged tissue limit the potential of currently available cell-based techniques. In this study, we generated a multilayered construct from adipose-derived mesenchymal stromal cells (MSCs) modified to secrete stem cell factor, SCF. In a rat model of myocardium infarction, we show that transplantation of SCF producing cell sheet induced activation of the epicardium and promoted the accumulation of c-kit positive cells in ischemic muscle. Morphometry showed the reduction of infarct size (16%) and a left ventricle expansion index (0.12) in the treatment group compared to controls (24–28%; 0.17–0.32). The ratio of viable myocardium was more than 1.5-fold higher, reaching 49% compared to the control (28%) or unmodified cell sheet group (30%). Finally, by day 30 after myocardium infarction, SCF-producing cell sheet transplantation increased left ventricle ejection fraction from 37% in the control sham-operated group to 53%. Our results suggest that, combining the genetic modification of MSCs and their assembly into a multilayered construct, we can provide prolonged pleiotropic effects to the damaged heart, induce endogenous regenerative processes, and improve cardiac function.     

腹腔手术后重症患者心肌损伤的危险因素

目的探讨腹腔手术后重症患者心肌损伤的发生情况及可能的危险因素。方法回顾性分析北京大学人民医院2017年1月至2019年1月腹腔手术后重症患者的一般临床资料及心肌损伤情况,收集并观察基础病史、术中(手术时间、是否急诊手术、术中出血>800 ml和术中低血压等)及术后指标(改良氧合指数、血乳酸、急性肾损伤和术后24 h内使用升压药情况等)。根据术后是否发生心肌损伤,将患者分为心肌损伤组和非心肌损伤组,采用Logistic回归分析腹腔手术后重症患者心肌损伤的危险因素。结果在纳入的803例腹腔手术后重症患者中,心肌损伤发生率为17. 2%(138/803),而急性心肌梗死发生率仅为0. 9%(7/803)。单因素分析显示,慢性肾功能不全病史、手术时间、急诊手术、术中低血压、术后24 h内使用升压药、高APACHEⅡ评分及术后即刻急性肾损伤与术后重症患者心肌损伤相关(P<0. 05)。多因素回归分析显示,急诊手术(OR=3. 14,95%CI:1. 76～5. 60,P<0. 001)、术后24 h内使用升压药(OR=2. 26,95%CI:1. 23～4. 15,P=0. 008)、APACHEⅡ评分(OR=1. 05,95%CI:1. 01～1. 09,P=0. 008)和术后急性肾损伤(OR=3. 18,95%CI:1. 78～5. 69,P <0. 001)与腹腔手术后重症患者发生心肌损伤独立相关。结论重症患者腹腔手术后心肌损伤发生率高,急诊手术、术后24 h内使用升压药、高APACHEⅡ评分和术后急性肾损伤是导致腹腔手术后重症患者发生心肌损伤的独立危险因素。     

因素空间理论下基点分类算法研究

目前，基于因素空间理论的背景基提取算法计算过程复杂，初始化必须依赖各因素极值，基点数量提取冗余等原因，未能在应用中取得很好效果。为此，结合内点判别法和知识可继承、可扩展的思想，提出一种计算简单、初始化独立、基点数量小的改进的背景基提取算法。然后，利用改进的背景基提取算法构造出一种全新的数据分类算法-基点分类算法，基点分类算法以提取每一类样本的背景基为预测模型，再通过新定义的λ-背景基，优化预测模型。数值实验表明:基点分类算法原理简单、构造难度小、分类模型泛化能力强，预测能力准确率高，同时严格的模型限定区域又能为识别新类别提供新方法。     

Challenges in the CO2 emissions of the Turkish power sector: Evidence from a two-level decomposition approach

Decarbonization of the energy system is urgent to avert the disruptions in the climate. Considering its share, the low carbon transition of the power sector is pivotal. Growing electricity demand poses unique challenges for Turkey to enact deep decarbonization. It is vital to uncover the contributing causes of emissions to provide strategic oversight for carbon management activities. This study investigates key drivers of CO₂ emissions from the power sector using the Logarithmic Mean Divisia Index decomposition method. While efficiency improvement contributes to sustainable yet minor mitigation, changes in the fossil-fuel share indicate a cycling but significant overall impact.