Improving repair sequence scheduling methods for postdisaster critical infrastructure systems

The recovery process of postdisaster critical infrastructure systems (CISs) includes multiple phases, among which the repair phase usually takes the longest time and contributes the largest to system recovery rapidity and system resilience. This article formulates the repair sequence scheduling problem for damaged CIS components under limited repair resources in a general form, and then proposes two novel heuristic methods to enhance its solution performance. To demonstrate the efficiencies of the two proposed methods, typical existing methods are also briefly introduced for comparison purposes, including three component importance‐based methods (CIBMs), a genetic algorithm‐based method (GABM), a time index‐based heuristic method (TIBHM), and a component index‐based exact solution method (CIBESM). Those methods are separately applied into thousands of damage scenarios for three systems, and are then compared in terms of the optimality gap and the computational cost. Results show that the two proposed methods have significantly better performance than existing methods, whereas the first proposed method can be adapted for critical time points‐based resilience assessment and optimization, and the second proposed method can be applied to the recovery of large‐scale CISs with extensive disruptions.     

Discovery and in Vivo Evaluation of Novel RGD-Modified Lipid-Polymer Hybrid Nanoparticles for Targeted Drug Delivery

In the current study, the lipid-shell and polymer-core hybrid nanoparticles (lpNPs) modified by Arg–Gly–Asp(RGD) peptide, loaded with curcumin (Cur), were developed by emulsification-solvent volatilization method. The RGD-modified hybrid nanoparticles (RGD–lpNPs) could overcome the poor water solubility of Cur to meet the requirement of intravenous administration and tumor active targeting. The obtained optimal RGD-lpNPs, composed of PLGA (poly(lactic-co-glycolic acid))–mPEG (methoxyl poly(ethylene- glycol)), RGD–polyethylene glycol (PEG)–cholesterol (Chol) copolymers and lipids, had good entrapment efficiency, submicron size and negatively neutral surface charge. The core-shell structure of RGD–lpNPs was verified by TEM. Cytotoxicity analysis demonstrated that the RGD–lpNPs encapsulated Cur retained potent anti-tumor effects. Flow cytometry analysis revealed the cellular uptake of Cur encapsulated in the RGD–lpNPs was increased for human umbilical vein endothelial cells (HUVEC). Furthermore, Cur loaded RGD–lpNPs were more effective in inhibiting tumor growth in a subcutaneous B16 melanoma tumor model. The results of immunofluorescent and immunohistochemical studies by Cur loaded RGD–lpNPs therapies indicated that more apoptotic cells, fewer microvessels, and fewer proliferation-positive cells were observed. In conclusion, RGD–lpNPs encapsulating Cur were developed with enhanced anti-tumor activity in melanoma, and Cur loaded RGD–lpNPs represent an excellent tumor targeted formulation of Cur which might be an attractive candidate for cancer therapy.     

Evaluation of chicken freshness using a low-cost colorimetric sensor array with AdaBoost–OLDA classification algorithm

This paper attempted to evaluate chicken freshness using a low-cost colorimetric sensor array with the help of a classification algorithm. We fabricated a novel and low-cost colorimetric sensors array, with a specific colorific fingerprint to volatile compounds, using printing chemically responsive dyes on a C2 reverse silica-gel flat plate. In addition, we proposed a novel classification algorithm for sensors data classification – orthogonal linear discriminant analysis (OLDA) and adaptive boosting (AdaBoost) algorithm, namely AdaBoost–OLDA. And we compared it with two classical classification algorithms – linear discriminant analysis (LDA) and back propagation artificial neural network (BP-ANN). Experimental results showed classification results by AdaBoost–OLDA algorithm is superior to BP-ANN and LDA algorithms, the classification results by which are both 100% in the calibration and prediction sets. This study sufficiently demonstrated that the colorimetric sensors array with a classification algorithm has a high potential in evaluating chicken freshness, and AdaBoost–OLDA algorithm has a strong performance in solution to a complex data classification.     

Experimental investigation on the effect of ambient pressure on thermal runaway and fire behaviors of lithium‐ion batteries

To investigate the impacts of ambient pressure on thermal runaway and fire behaviors of lithium‐ion battery (LIB), experimental measurement and theoretical analysis with serial conditions are conducted at two altitudes. The well‐designed experimental equipment and operating conditions have enabled the accurate evaluation of ambient pressure effects. Results show that the first abrupt temperature change in Hefei (ambient pressure 100.8 kPa) is higher than that in Lhasa (64.3 kPa). The difference in ambient pressure at two altitudes leads to different relief valve crack temperature and time. The average burning rate in Hefei is larger than that in Lhasa, and the estimated pressure effect factor is quite different for detailed pack conditions and varies within the range of 0.083‐1.39. The ambient pressure has a greater effect on the heat release rate and total heat release than the mass loss, and the effective combustion heat under the low pressure is lower than that in normal condition. This work can provide more comprehensive and useful data for the safety management of LIBs at low pressure environments.     

Grain growth behavior of Ti-6.5Al-3.5Mo-1.5Zr-0.3Si alloy during isothermal β heat treatments

Isothermal β heat treatments of Ti-6.5 Al-3.5 Mo-1.5 Zr-0.3 Si alloy were performed at the temperature of1040-1240 ℃ to examine the influence of heating conditions on grain growth of the alloy. The results show that the grain size increases with heating temperature and holding time increasing. Rapid β grain growth of the alloy takes place at the temperature of over 1140 ℃. The grain growth kinetics for the alloy follows the classical isothermal grain growth law.The growth time exponent(n) of 0.5651 and activation energy(Q) of 129.6 kJ mol-1 are determined. Finally, in order to determine the grain size under different heating conditions,the grain growth model of the alloy was established.     

An unsafe behaviour formation mechanism based on risk perception

It is commonly acknowledged that human behaviour is implicated in most safety problems. However, research on the formation mechanism of unsafe behaviour remains incomplete. Risk perception is one of the fundamental issues in risk research, and individual risk perception can be identified as a critical antecedent of human behaviour. This study attempts to construct and test a theoretical model to reveal the formation mechanism of unsafe behaviour based on risk perception. First, to lay a solid foundation for the developed new mechanism, several key concepts about risk perception and unsafe behaviour were explained. Second, the formation mechanism of biases in individual risk perception was developed based on psychological distance theory, and the biases in risk perception were subsequently classified. Lastly, an unsafe behaviour formation mechanism was put forward based on risk perception as an explanatory variable. This study is novel in that it uses psychological distance to explore the formation of biases in individual risk perception. Further, the presented work provides a new approach to understanding and explaining the formation mechanism of human unsafe behaviour.     

Modeling and analysis of internal water transfer behavior of PEM fuel cell of large surface area

The PEM fuel cell has been widely used in the area of transportation and power station. The surface area of a fuel cell is enlarged to provide high enough power but the problem of analysis of internal water content behavior follows tightly. Many scholars have investigated the mathematical models of a small fuel cell and validated them through experiment. Besides, the introduction of AC impedance technique helps find relationship between water content and membrane resistance. Based on their research, an approach is put forward in this paper to model and analyze the internal water content behavior in a fuel cell of large surface area. For large surface area, three special cases are studied according to the actual operating states at cathode outlet. The first case applies to a fuel cell with no saturated water vapor at both outlets while in the second and third case, the fuel cell is divided into an electrochemical reaction zone and no reaction zone owing to emerging liquid water. The indicators of model are the water content profile inside membrane and the total membrane resistance. The simulation results show that the net water transfer coefficient has significant influence on the performance of the membrane and the constituents of anode side are easy to be varied. In addition, when the fuel cell is operated in counter-flow mode with emerging liquid water, the only back diffusion of water from cathode to anode helps improve the state of the membrane.