Towards sensible toxicity testing for nanomaterials: proposal for the specification of test design

During the last decade, nanomaterials (NM) were extensively tested for potential harmful effects towards humans and environmental organisms. However, a sound hazard assessment was so far hampered by uncertainties and a low comparability of test results. The reason for the low comparability is a high variation in the (1) type of NM tested with regard to raw material, size and shape and (2) procedures before and during the toxicity testing. This calls for tailored, nanomaterial-specific protocols. Here, a structured approach is proposed, intended to lead to test protocols not only tailored to specific types of nanomaterials, but also to respective test system for toxicity testing. There are existing standards on single procedures involving nanomaterials, however, not all relevant procedures are covered by standards. Hence, our approach offers a detailed way of weighting several plausible alternatives for e.g. sample preparation, in order to decide on the procedure most meaningful for a specific nanomaterial and toxicity test. A framework of several decision trees (DT) and flow charts to support testing of NM is proposed as a basis for further refinement and in-depth elaboration. DT and flow charts were drafted for (1) general procedure—physicochemical characterisation, (2) choice of test media, (3) decision on test scenario and application of NM to liquid media, (4) application of NM to the gas phase, (5) application of NM to soil and sediments, (6) dose metrics, (S1) definition of a nanomaterial, and (S2) dissolution. The applicability of the proposed approach was surveyed by using experimental data retrieved from studies on nanoscale CuO. This survey demonstrated the DT and flow charts to be a convenient tool to systematically decide upon test procedures and processes, and hence pose an important step towards harmonisation of NM testing.     

A new multi criteria decision making approach for medical imaging systems considering risk factors

Effective and good quality imaging is important for medical decision-making and can reduce unnecessary costs and procedures. Therefore, decision making regarding any technology can present serious problems for healthcare centers with multi criteria decision making problems (MCDM). This paper is the first to develop the fuzzy axiomatic design with risk factors (RFAD) approach and to use it in multi attribute comparisons of medical imaging systems in a university hospital. Although most MCDM approaches in the literature treat risk factors as separate criteria, in real life every alternative has its own risks related to each criterion. The proposed approach integrates the risk factors in each criterion and calculates the information content to compare alternatives. This paper applies three different approaches to MCDM problems related to the selection of medical imaging systems for a university hospital.     

Forgotten monomers: isotactic polymers from N‐benzyl‐3‐methylenepyrrolidin‐2‐one via free radical polymerization

N‐Benzyl‐3‐methylenepyrrolidin‐2‐one ( 3 ) was synthesized and homopolymerized under free radical conditions. The configurational microstructure of poly(N‐benzyl‐3‐methylenepyrrolidin‐2‐one) ( 4 ) is isotactic with a minor tendency to syndiotacticity. Monomer 3 was also homopolymerized in water in the presence of methylated β‐cyclodextrin. The glass transition temperature of 4 of 124 °C was compared with the lower value of 61 °C of the ring‐opened analogue poly(N‐benzyl‐N‐ethylacrylamide). © 2015 Society of Chemical Industry     

Group decision support system for backbone-network reconfiguration

Modern power system is unprecedentedly vulnerable and the society is exposed to higher blackout risks. Therefore restoration is a key issue to power systems. Reasonable backbone-network reconfiguration is necessary for re-establishing the network and restoring loads quickly. In order to speed up network reconfiguration under security constraints, a group decision support system (GDSS) is developed. A unified data platform based on data warehouse is constructed to resolve inconsistencies of data, information and models. A three-stage restoration strategy and a two-layer restoration path searching method are proposed to establish restoration schemes. Multiple attribute decision-making is implemented to evaluate alternatives and consider various attributes about restoration speed and system security comprehensively. Group decision-making provides an aggregated cardinal ranking of candidate restoration schemes. The GDSS uses expert rules for qualitative analysis and numerical computation programs for quantitative analysis, and it can resolve the semi-structured decision problem of network reconfiguration efficiently. Restoration plan of Shandong power grid is developed with the proposed method and it has been adopted by State Grid Shandong Electric Power Company. Performance results of Shandong power grid of China demonstrate the feasibility and flexibility of the method.     

Multi-objective optimization of shield construction parameters based on random forests and NSGA-II

Metro shield construction will inevitably cause changes in the stress and strain state of the surrounding soil, resulting in stratum deformation and surface settlement (SS), which will seriously endanger the safety of nearby buildings, roads and underground pipe networks. Therefore, in the design and construction stage, optimizing the shield construction parameters (SCP) is the key to reducing the SS rate and increasing the safe driving speed (DS). However, optimization of existing SCP are challenged by the need to construct a unified multiobjective model for optimization that are efficient, convenient, and widely applicable. This paper innovatively proposes a hybrid intelligence framework that combines random forest (RF) and non-dominant classification genetic algorithm II (NSGA-II), which overcomes the shortcomings of time-consuming and high cost for the establishment and verification of traditional prediction models. First, RF is used to rank the importance of 10 influencing factors, and the nonlinear mapping relationship between the main SCP and the two objectives is constructed as the fitness function of the NSGA-II algorithm. Second, a multiobjective optimization framework for RF-NSGA-II is established, based on which the optimal Pareto front is calculated, and reasonable optimized control ranges for the SCP are obtained. Finally, a case study in the Wuhan Rail Transit Line 6 project is examined. The results show that the SS is reduced by 12.5% and the DS is increased by 2.5% with the proposed framework. Meanwhile, the prediction results are compared with the back-propagation neural network (BPNN), support vector machine (SVM), and gradient boosting decision tree (GBDT). The findings indicate that the RF-NSGA-II framework can not only meet the requirements of SS and DS calculation, but also used as a support tool for real-time optimization and control of SCP.     

Minimum cost consensus model for CRP-driven preference optimization analysis in large-scale group decision making using Louvain algorithm

Large-scale group decision-making problems based on social network analysis and minimum cost consensus models (MCCMs) have recently attracted considerable attention. However, few studies have combined them to form a complete decision-making system. Accordingly, we define the satisfaction index to optimize the classical MCCM by considering the effect of the group on individuals. Similarly, we define the consistency index to optimize the consensus reaching process (CRP). Regarding the evolution of the consensus network, the Louvain algorithm is used to divide the entire group into several subgroups to ensure that each subgroup is independent but has strong cohesion. By constructing the MCCM based on the satisfaction index and the optimized consensus-reaching process, the group opinions in each subgroup are ranked to obtain the final ranking of alternatives. Finally, to verify the validity of CRP and the practical value of the proposed model, we conduct consensus network evolution and decision-making analysis in the case of a negotiation between the government and polluting companies to achieve uniform pollution emissions. Sensitivity analysis is performed to demonstrate the stability of the subgroup weights. Furthermore, a comparative analysis using existing models verifies the effectiveness of the proposed model.     

Prioritizing the alternatives of the natural gas grid conversion to hydrogen using a hybrid interval rough based Dombi MARCOS model

The aim of this study is to disclose an integrated multi-criteria decision making model as an instrument able to be used for hydrogen gas grid development via natural gas network conversion by considering four main criteria and sixteen sub-criteria. The proposed model consists of two stages using interval rough based Dombi MARCOS (Measurement Alternatives and Ranking according to the COmpromise Solution) method. In the first stage, the interval rough Bonferroni logarithmic methodology of additive weights is applied for determining the weight coefficients. In the second stage, the improved interval rough MARCOS method is used to rank the alternatives. A case study for hydrogen gas grid development in Romania set out the applicability and effectiveness of the proposed model. The proposed model is analysed from various points of view so that it can be used effectively in reality not only theoretically. This study analyzes four technical alternatives for hydrogen gas grid development. The results show that the conversion for mixtures natural gas with hydrogen a transporting a mix of gases is the best alternative among the four alternatives, for the next period and in the specific context described by this study. The current technical-economic criteria are rather a constraint when discussing gas infrastructures. For choosing a sustainable solution, a major role comes for decision makers, along with the desire to pay fairly from the consumer.     

后处理对爆轰纳米金刚石表面官能团的影响

分别在高锰酸钾与浓硫酸的混合溶液、空气、氢气、真空以及氩气中对爆轰纳米金刚石进行后处理,研究了后处理方法对其表面官能团的影响。采用X射线衍射仪、高分辨透射电子显微镜、傅立叶变换红外光谱仪和差示扫描量热仪对后处理前后纳米金刚石的微观结构、性能和表面状态进行了研究。结果表明:纳米金刚石颗粒形状为球形或椭球形,平均粒径约为5 nm,在空气中的起始氧化温度约为550 ℃,在氢气、真空和氩气中的石墨化温度分别约为284 ℃、1 146 ℃和1 184 ℃。纳米金刚石在后处理前表面含有大量的官能团,如-OH、-CH₃、-CH₂、CO₂、-C==O、-COOH和-C-O-C等。在氢气中对纳米金刚石进行处理,可使部分官能团从表面解吸而由氢取代,悬键与氢结合可有效防止二次吸附,是去除爆轰纳米金刚石表面官能团的低成本、高效方法。     

Improved indoor environment through optimised ventilator and furniture positioning: A case of slum rehabilitation housing,Mumbai, India

This study optimized the ventilator and furniture location of a tenement unit in a low-income urban habitat to obtain maximum experiential indoor environmental quality (e-IEQ) over the breathing zone. Hypothetical interior layouts using a combination of the two design parameters of ventilator location and bed position were generated for optimizing the design layout. This layout could promote maximum indoor airflow and minimum indoor air temperature and contaminant concentration. In this study, an improved indoor environment is hypothesized to be attainable through improved natural ventilation and thermal performance in the occupied zones. A sequential methodology involving “parametric design modeling–computational simulation–multiobjective optimization–multicriteria decision making”-based framework was selected. Results exhibited that the currently designed tenement unit had a poor indoor environment, whereas the hypothesized iterated layout “optimized design layout, scenario 3 (ODL 3)” derived from the optimization and decision-making algorithm performed effectively in providing e-IEQ. An increase in experiential indoor air velocity by 0.2 m/s and a decrease in temperature by 2 °C were observed over the monitoring point in the ODL 3 considering the existing scenario. Therefore, this study can find a way toward the development of sustainable habitat design guidelines under upcoming slum redevelopment policies across the nation.