0–1膨胀几何分布的客观贝叶斯分析

在医疗卫生、金融证券等应用领域，经常会同时出现零观测值、一观测值较多的情况. 为更好地拟合这类数据，提出0–1膨胀几何分布模型并进行客观贝叶斯分析. 通过参数变换，得到Jeffreys先验和reference先验. 设计后验分布的抽样算法，设置不同的样本量和参数真值，采用数值模拟方法对不同客观先验下的估计效果进行评估.     

Spatiotemporal Magnetocaloric Microenvironment for Guiding the Fate of Biodegradable Polymer Implants

The degradation behavior of implants is significantly important for bone repair. However, it is still unprocurable to spatiotemporally regulate the degradation of the implants to match bone ingrowth. In this paper, a magneto-controlled biodegradation model is established to explore the degradation behavior of magnetic scaffolds in a magnetothermal microenvironment generated by an alternating magnetic field (AMF). The results demonstrate that the scaffolds can be heated by magnetic nanoparticles (NPs) under AMF, which dramatically accelerated scaffold degradation. Especially, magnetic NPs modified by oleic acid with a better interface compatibility exhibit a greater heating efficiency to further facilitate the degradation. Furthermore, the molecular dynamics simulations reveal that the enhanced motion correlation between magnetic NPs and polymer matrix can accelerate the energy transfer. As a proof-of-concept, the feasibility of magneto-controlled degradation for implants is demonstrated, and an optimizing strategy for better heating efficiency of nanomaterials is provided, which may have great instructive significance for clinical medicine.     

Reversible data hiding based on RSBEMD coding and adaptive multi-segment left and right histogram shifting

By leveraging the secret data coding using the remainder storage based exploiting modification direction (RSBEMD), and the pixel change operation recording based on multi-segment left and right histogram shifting, a novel reversible data hiding (RHD) scheme is proposed in this paper. The secret data are first encoded by some specific pixel change operations to the pixels in groups. After that, multi-segment left and right histogram shifting based on threshold manipulation is implemented for recording the pixel change operations. Furthermore, a multiple embedding policy based on chess board prediction (CBP) and threshold manipulation is put forward, and the threshold can be adjusted to achieve adaptive data hiding. Experimental results and analysis show that it is reversible and can achieve good performance in capacity and imperceptibility compared with the existing methods.     

Modeling urban growth using spatially heterogeneous cellular automata models: Comparison of spatial lag,spatial error and GWR

Many methods can be used to construct geographical cellular automata (CA) models of urban land use, but most do not adequately capture spatial heterogeneity in urban dynamics. Spatial regression is particularly appropriate to address the problem to reproduce urban patterns. To examine the advantages and disadvantages of spatial regression, we compare a spatial lag CA model (SLM-CA), a spatial error CA model (SEM-CA) and a geographically-weighted regression CA model (GWR-CA) by simulating urban growth at Nanjing, China. Each CA model is calibrated from 1995 to 2005 and validated from 2005 to 2015. Among these, SLM and SEM are spatial autoregressive (SAR) models that consider spatial autocorrelation of urban growth and yield highly similar land transition probability maps. Both SAR-CA and GWR-CA accurately reproduce urban growth at Nanjing during the calibration and validation phases, yielding overall accuracies (OAs) exceeding 94% and 85%, respectively. SAR-CA is superior in simulating urban growth when measured by OA and figure-of-merit (FOM) while GWR-CA is superior regarding the ability to address spatial heterogeneity. A concentric ring buffer-based assessment shows OA valleys that correspond to FOM peaks, where the ranges of valleys and peaks indicate the areas with active urban development. By comparison, SAR-CA captures more newly-urbanized patches in highly-dense urban areas and shows better performance in terms of simulation accuracy; whereas, GWR-CA captures more in the suburbs and shows better ability to address spatial heterogeneity. Our results demonstrate that spatial regression can help produce accurate simulations of urban dynamics featured by spatial heterogeneity, either implicitly or explicitly. Our work should help select appropriate CA models of urban growth in different terrain and socioeconomic contexts.     

Damage identification in concrete using impact non-linear reverberation spectroscopy

High amplitude non-linear acoustic methods have shown potential for the identification of micro damage in brittle materials such as concrete. Commonly, these methods evaluate a non-linearity parameter from the relative change in frequency and attenuation with strain amplitude. Here, a novel attenuation model is introduced to describe the free reverberation from a standard impact resonance frequency test, together with an algorithm for estimating the unknown model coefficients. The non-linear variation can hereby by analyzed over a wider dynamic range as compared to conventional methods. The experimental measurement is simple and fully compatible with the standardized free-free linear impact frequency test.     

Value chain analysis of bio-coal business in Finland: Perspectives from multiple value chain members

The purpose of this study is to provide a comprehensive outline of the Value Chain (VC)¹ of bio-coal in Finland, define the proper business models of bio-coal business, and investigate the interrelationships between VC activities. The major findings are: 1) the study found significant interrelationships between support and primary activities in the bio-coal VC which suggest that we should not emphasis only the core value/primary activities of the bio-coal business, but pay more attentions to the “side values”/support activities; 2) The study identified political and environmental factors as the effective drivers, while technology and cost-profit uncertainty as major restrictions for the Finnish bio-coal business. The authors would like to suggest that instead of purely “environmental concerns”, the term “sustainability credentials” should be emphasized, which means value creating and adding items should not limit to monetary values, but consider social and environmental value propositions. 3) The study identified “low competition” in the current bio-coal business in Finland, which implies opportunities of market entrance for Finnish and international companies; 4) The study identified that the current Finnish bio-coal model is the decentralized model at the local level. However, the future Finnish bio-coal model will be a large scaled model, with a focus on export sales.     

Temperature- and frequency-dependent hysteresis scaling behaviour and phase transitions in a [001]c 0.73Pb(Mg1/3Nb2/3)O3-0.27PbTiO3 single crystal

The dielectric properties and bipolar polarization-electric field (P-E) and strain-electric field (S-E) dynamic hysteresis of a relaxor [001]_c 0.73Pb(Mg_1/3Nb_2/3)O₃-0.27PbTiO₃ (PMN-0.27PT) single crystal were investigated to reveal more details of the temperature-induced phase transitions. Different linear scaling relations for ferroelectric hysteresis area <A>, coercive field E_c, saturation polarization P_s and remnant polarization P_r versus temperature τ were measured in different temperature regions. For each measurement frequency f, all hysteresis parameters were found to decrease linearly with temperature in the temperature range of the single rhombohedral (R) phase or tetragonal (T) phase, and the rate of decrease in the T phase was observed to be much larger than the corresponding rate in the R phase. In the temperature range near the R-T phase transition, the exponent α in the power law <A>∝f ^α for the R phase was found to be smaller than that for the T phase, and the magnitude of α depended strongly on temperature when the crystal was in the R-T coexisting phase state. Our experimental and theoretical results indicate that the difference in the activation energy and dipole moment in the R and T phases may lead to the observed discrepancy for the P-E and S-E hysteresis behaviour in different temperature regions.     

Demand response for home energy management system

The optimization of energy consumption, with consequent cost reduction, is one of the main challenges for the present and future smart grid. Demand response (DR) program is expected to be vital in home energy management system (HEMS) which aims to schedule the operation of appliances to save energy costs by considering customer convenience as well as characteristics of electric appliances. The DR program is a challenging optimization problem especially when the formulations are non-convex or NP-hard problems. In order to solve this challenging optimization problem efficiently, an effective heuristic approach is proposed to achieve a near optimal solution with low computational costs. Different from previously proposed methods in literatures which are not suitable to be run in embedded devices such as a smart meter. The proposed algorithm can be implemented in an embedded device which has severe limitations on memory size and computational power, and can get an optimal value in real-time. Numerical studies were carried out with the data simulating practical scenarios are provided to demonstrate the effectiveness of the proposed method.