System Dynamics Modeling-based Study of Contingent Sourcing under Supply Disruptions

AbstractIn this paper, using the methodology of system dynamics modeling, we separately build two models for a supply chain under two circumstances of supply disruptions, without backup supplier, and with a contingent supplier. The retailer's total profits are also compared under these two circumstances of supply disruptions to help the decision-makers better understanding the backup purchasing strategy. The supply chain studied only involves one retailer and two independent suppliers that are referred to as major supplier and backup supplier. The paper contributes to the literature by providing a better understanding of the impacts of supply disruptions on the system performance and by shedding insights into the value of a backup supply

Modelling and vulnerability analysis of cyber-physical power systems based on interdependent networks

The strong coupling between the power grid and communication systems may contribute to failure propagation, which may easily lead to cascading failures or blackouts. In this paper, in order to quantitatively analyse the impact of interdependency on power system vulnerability, we put forward a “degree–electrical degree” independent model of cyber-physical power systems (CPPS), a new type of assortative link, through identifying the important nodes in a power grid based on the proposed index–electrical degree, and coupling them with the nodes in a communication system with a high degree, based on one-to-one correspondence. Using the double-star communication system and the IEEE 118-bus power grid to form an artificial interdependent network, we evaluated and compare the holistic vulnerability of CPPS under random attack and malicious attack, separately based on three kinds of interdependent models: “degree–betweenness”, “degree–electrical degree” and “random link”. The simulation results demonstrated that different link patterns, coupling degrees and attack types all can influence the vulnerability of CPPS. The CPPS with a “degree–electrical degree” interdependent model proposed in this paper presented a higher robustness in the face of random attack, and moreover performed better than the degree–betweenness interdependent model in the face of malicious attack

Effects of Genetic Variation in the 20th Intron of Sansui Duck ATP2A2 Gene on Eggshell Quality

In order to explore the influence of the polymorphism in the 20intron region of the Sansui duck ATP2A2 gene on the eggshell quality, this study used Primer Premier 5 software to design and synthesize a pair of primers in the 20 intron region, two-way direct sequencing and sequence alignment to mine SNPs Sites, SPSS 18.0 software was used to analyze the relationship between SNP sites and eggshell quality of Sansui duck.Three SNP sites were found in the 20 intron region of the ATP2A2 gene: g.40874 T>C, g.40920 G>A and g.40990 T=C, all of which were moderately polymorphic, at the site g.40874 T>C and g.40920 G>A both deviated significantly from Hardy-Weinberg equilibrium (P>0.05), position g.40990 T=C accords with Hardy-Weinberg equilibrium (PC There is a strong linkage disequilibrium between g.40990 T=C; a total of 4 haplotypes and 9 double types were detected at 3 SNP loci; the results of association analysis showed that g.40874 T>C mutation had a significant effect on eggshell strength and eggshell weight.The eggshell strength of CC genotype was significantly higher than that of TC and TT genotypes (PC and g.40990 T=C found in the 20th intron region of the Sansui duck ATP2A2 gene may be the marker sites that affect the quality of the eggshell

Stabilizing Electrochemical Carbon Capture Membrane with Al\u3csub\u3e2\u3c/sub\u3eO\u3csub\u3e3\u3c/sub\u3e Thin-Film Overcoating Synthesized by Chemical Vapor Deposition

Development of high-efficiency and cost-effective carbon capture technology is a central element of our effort to battle the global warming and climate change. Here we report that the unique high-flux and high-selectivity of electrochemical silver-carbonate dual-phase membranes can be retained for an extended period of operation by overcoating the surfaces of porous silver matrix with a uniform layer of Al2O3 thin-film derived from chemical vapor deposition

Diachronous end-Permian terrestrial ecosystem collapse with its origin in wildfires

The Permian-Triassic Mass Extinction (PTME) is the greatest biodiversity crisis in Earth history and while the marine crisis is increasingly well constrained, the timing and cause(s) of terrestrial losses remain poorly understood. There have been suggestions that the End-Permian Terrestrial Collapse (EPTC) pre-dated, was synchronous with or post-dated the marine crisis, or even occurred asynchronously in different regions. We address these conflicting interpretations through a detailed geochemical study of a terrestrial sequence in the Liujiang Coalfield on the North China Plate (NCP) in which we apply zircon U-Pb dating of tuffaceous claystone, kerogen identification, and analysis of organic carbon isotopic composition (δ13Corg), total organic carbon (TOC), continental weathering (via the chemical index of alteration; CIA) and Ni concentrations. Our study constrains the Permian-Triassic boundary (PTB) near the base of bed 20 in our sequence at approximately 251.9 ± 1.1 Ma, immediately above a Ni anomaly also known from other terrestrial sequences and the marine PTME. Organic carbon isotope chemostratigraphy together with evidence for algal blooms and the presence of mudstone clasts suggests that the onset of the EPTC in the NCP was synchronous with the crisis in low latitudes (e.g., South China), but was about 310 kyr later than the EPTC in higher southerly latitudes (e.g., Australia). The EPTC predates the marine PTME. Kerogen macerals suggest that a phase of increased wildfire was sustained from the onset of the EPTC in the NCP until the marine PTME interval, implicating wildfire as a major driver of the EPTC (at least in low latitudes) that, in turn, had devastating consequences for the marine realm

OPT-GAN: Black-Box Global Optimization via Generative Adversarial Nets

Black-box optimization (BBO) algorithms are concerned with finding the best solutions for problems with missing analytical details. Most classical methods for such problems are based on strong and fixed a priori assumptions, such as Gaussianity. However, the complex real-world problems, especially when the global optimum is desired, could be very far from the a priori assumptions because of their diversities, causing unexpected obstacles to these methods. In this study, we propose a generative adversarial net-based broad-spectrum global optimizer (OPT-GAN) which estimates the distribution of optimum gradually, with strategies to balance exploration-exploitation trade-off. It has potential to better adapt to the regularity and structure of diversified landscapes than other methods with fixed prior, e.g. Gaussian assumption or separability. Experiments conducted on BBO benchmarking problems and several other benchmarks with diversified landscapes exhibit that OPT-GAN outperforms other traditional and neural net-based BBO algorithms.Comment: M. Lu and S. Ning contribute equally. Submitted to IEEE transactions on Neural Networks and Learning System