Improving storability,physiological disorders,and antioxidant properties of ‘Bartlett’ and ‘d’Anjou’ pears (Pyrus communis L.) by pre-harvest 1-methylcyclopropene spraying

Ethylene continues to be a major factor influencing quality of European pears during storage. Although research has been done on the effect of pre-harvest 1-methylcyclopropene (1-MCP) on physiological characteristics in pears, a full understanding of cultivar response and antioxidant metabolism remains elusive. Spraying 1-MCP on ‘Bartlett’ and ‘d’Anjou’ pears was studied with respect to physiology, storage and eating quality, disorders, and antioxidant properties at two harvest date (H1 and H2) during storage and ripening. Treatment with 1-MCP extended the harvest window of ‘Bartlett’ and ‘d’Anjou’ pears 3 and 4 days, respectively, without reducing storage or eating quality. Treatment with 1-MCP reduced ethylene production (EPR) and respiration rates (RR), maintained fruit firmness and green colour during storage and retarded development of desirable melting texture in both cultivars. Additionally, 1-MCP lowered the incidence of disorders by alleviating membrane lipid peroxidation, retaining high total flavonoids (TF) and antioxidant capacity, and enhancing superoxide dismutase (SOD), catalase (CAT) and ascorbate peroxidase (APX) activity in both cultivars. Overall, pre-harvest 1-MCP applications could extend storage time of ‘Bartlett’ and ‘d’Anjou’ pears to 5 and 6 months, respectively, at −1.1 ± 0.5 °C, by reducing ethylene synthesis and enhancing antioxidant metabolism.     

Passive target detection and tracking from electromagnetic field measurements

This paper presents a novel approach to the localization of moving targets in a complex environment based on the measurement of the perturbations induced by the target presence on an independently‐generated time‐varying electromagnetic field. Field perturbations are measured via a set of sensors deployed over the domain of interest and used to detect and track a possible target by resorting to a particle Bernoulli filter (PBF). To comply with real‐time operation, the PBF works along with an artificial neural network (ANN) model of the environment trained offline via finite elements (FEs). The performance of the proposed algorithm is assessed via simulation experiments.     

国际32.5水泥的技术现状与发展趋势

正进入21世纪以来,国际水泥混凝土产业经历了17年的科研试验、工业生产与工程应用等大量的实践,促使人们对过去曾被视为"低标号"的32.5水泥的认知发生了的逆转。非但一扫早先那种"水泥要向高标号发展"的旧传统理念,进而开始青睐于32.5水泥的新发展,并寄于厚望。这是国际水泥混凝土工业的一项重大技术进步,对发展方向具有重要指导意义,我国应予密切关注。(1)须要再次澄清一个重要的基本概念和现今     

Reoptimization framework and policy analysis for maritime inventory routing under uncertainty

We study a maritime inventory routing problem, in which shipments between production and consumption nodes are carried out by a fleet of vessels. The vessels have specific capacities and can be chartered under different agreements. The inventory levels of all consumption nodes and some production nodes should be maintained within specified bounds; for the remaining production nodes, orders should be picked up within pre-defined time windows. We propose a discrete-time mixed-integer programming model. In the face of new information and uncertainty, this optimization model has to be re-solved, as the horizon is rolled forward. We discuss how to account for different sources of uncertainty. We present a rolling-horizon reoptimization framework that allows us to study different policies that impact the quality of the implemented solution, so we can identify the optimal set of policies.     

数据挖掘技术在软件系统中的应用

随着高新科学技术的发展,科学家研究出的利于人类工作生活的技术程序越来越多,大部分技术主要集中在如何帮助人们简化平时的工作量,能快速查找到自己所需要的信息,毕竟现代社会,工作效率和工作质量是关键。数据挖掘技术就具备这样的特点,数据挖掘技术在软件系统的应用将大大降低我们的工作量,提高我们的工作效率。现在我们研究数据挖掘技术在软件系统的应用,分析它是如何发挥其作用的,希望能提高使用该挖掘技术人员的使用效率。     

High-Tg porous polyimide films with low dielectric constant derived from spiro-(adamantane-2,9′(2′,7′-diamino)-fluorene)

Porous polyimide (PI) films with low dielectric constants and excellent thermal properties have been a pressing demand for the next generation of high-performance, miniature, and ultrathin microelectronic devices. A series of novel porous PI films containing fluorenyl-adamantane groups were prepared successfully via thermolysis of poly(ethylene glycol) (PEG) added in the PI matrix. The cross-sectional morphologies of porous PI films showed closed pores with diameters ranging from 135 to 158 nm, which were uniform and regular in shape without interconnectivity. These porous PI films exhibited excellent thermal properties with a glass-transition temperature at 376 °C whereas the 5% weight loss temperature in air excess of 405 °C due to enhanced rigidity afforded by fluorenyl-adamantane groups. Accompanied by thermolysis content of PEG increasing from 0 to 20 wt %, the density of porous PI films decreased, and the corresponding porosity grew significantly from 0 to 11.48%. Depending on porosity, the dielectric constant and dielectric loss of porous PI films significantly declined from 2.89 to 2.37 and from 0.050 to 0.021, respectively. These excellent properties benefit the as-prepared porous PI films for application as interlayer dielectrics, integrated circuit chips, or multichip modules in microelectronic fields. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47313.     

Zinc doped Fe2O3 for boosting Electrocatalytic Nitrogen Fixation to ammonia under mild conditions

Artificial nitrogen fixation is emerging as a promising approach for synthesis of ammonia at mild conditions. Inspired by biological nitrogen fixation based on bacteria containing iron, zinc doped Fe₂O₃ nanoparticles are proposed as an efficient and earth abundant electrocatalyst for converting N₂ to NH₃. In neutral media, it achieves a maximum Faradaic efficiency (FE) of 10.4% and a large NH₃ yield rate of 15.1 μg h^?1 mg^?1_cat. at ?0.5 V vs. reversible hydrogen electrode. This catalyst also exhibits excellent selectivity and stability. Theoretical calculations suggest the reaction follows the associative enzymatic mechanism and it has a barrier of as low as 0.68 eV.     

庄河地区水资源现状浅析

本文通过对庄河地区水资源的分析及未来需水量的预测,计算其区域余水量。以确定区域经济的规划。     

Model Selection for Unsupervised Learning of Visual Context

This study addresses the problem of choosing the most suitable probabilistic model selection criterion for unsupervised learning of visual context of a dynamic scene using mixture models. A rectified Bayesian Information Criterion (BICr) and a Completed Likelihood Akaike’s Information Criterion (CL-AIC) are formulated to estimate the optimal model order (complexity) for a given visual scene. Both criteria are designed to overcome poor model selection by existing popular criteria when the data sample size varies from small to large and the true mixture distribution kernel functions differ from the assumed ones. Extensive experiments on learning visual context for dynamic scene modelling are carried out to demonstrate the effectiveness of BICr and CL-AIC, compared to that of existing popular model selection criteria including BIC, AIC and Integrated Completed Likelihood (ICL). Our study suggests that for learning visual context using a mixture model, BICr is the most appropriate criterion given sparse data, while CL-AIC should be chosen given moderate or large data sample sizes.