Dual‐horizon peridynamics

In this paper, we develop a dual‐horizon peridynamics (DH‐PD) formulation that naturally includes varying horizon sizes and completely solves the ‘ghost force’ issue. Therefore, the concept of dual horizon is introduced to consider the unbalanced interactions between the particles with different horizon sizes. The present formulation fulfills both the balances of linear momentum and angular momentum exactly. Neither the ‘partial stress tensor’ nor the ‘slice’ technique is needed to ameliorate the ghost force issue. We will show that the traditional peridynamics can be derived as a special case of the present DH‐PD. All three peridynamic formulations, namely, bond‐based, ordinary state‐based, and non‐ordinary state‐based peridynamics, can be implemented within the DH‐PD framework. Our DH‐PD formulation allows for h‐adaptivity and can be implemented in any existing peridynamics code with minimal changes. A simple adaptive refinement procedure is proposed, reducing the computational cost. Both two‐dimensional and three‐dimensional examples including the Kalthoff–Winkler experiment and plate with branching cracks are tested to demonstrate the capability of the method. Copyright © 2016 John Wiley & Sons, Ltd.     

Parkinson’s Disease Detection Using Biogeography-Based Optimization

In recent years, Parkinson's Disease (PD) as a progressive syndrome of the nervous system has become highly prevalent worldwide. In this study, a novel hybrid technique established by integrating a Multi-layer Perceptron Neural Network (MLP) with the Biogeography-based Optimization (BBO) to classify PD based on a series of biomedical voice measurements. BBO is employed to determine the optimal MLP parameters and boost prediction accuracy. The inputs comprised of 22 biomedical voice measurements. The proposed approach detects two PD statuses: 0-disease status and 1- good control status. The performance of proposed methods compared with PSO, GA, ACO and ES method. The outcomes affirm that the MLP-BBO model exhibits higher precision and suitability for PD detection. The proposed diagnosis system as a type of speech algorithm detects early Parkinson’s symptoms, and consequently, it served as a promising new robust tool with excellent PD diagnosis performance.     

Diversification in the driveway: mean-variance optimization for greenhouse gas emissions reduction from the next generation of vehicles

Modern portfolio theory is applied to the problem of selecting which vehicle technologies and fuels to use in the next generation of vehicles. Selecting vehicles with the lowest lifetime cost is complicated by the fact that future prices are uncertain, just as selecting securities for an investment portfolio is complicated by the fact that future returns are uncertain. A quadratic program is developed based on modern portfolio theory, with the objective of minimizing the expected lifetime cost of the “vehicle portfolio”. Constraints limit greenhouse gas emissions, as well as the variance of the cost. A case study is performed for light-duty passenger vehicles in the United States, drawing emissions and usage data from the US Environmental Protection Agency's MOVES and Department of Energy's GREET models, among other sources. Four vehicle technologies are considered: conventional gasoline, conventional diesel, grid-independent (non-plug-in) gasoline-electric hybrid, and flex fuel using E85. Results indicate that much of the uncertainty surrounding cost stems from fuel price fluctuations, and that fuel efficient vehicles can lower cost variance. Hybrids exhibit the lowest cost variances of the technologies considered, making them an arguably financially conservative choice.     

Synthesis and characterization of precursor derived TiN@Si–Al–C–N ceramic nanocomposites for oxygen reduction reaction

The development of efficient and durable catalysts is critical for the commercialization of fuel cells, as the catalysts’ durability and reactivity dictate their ultimate lifetime and activity. In this work, amorphous silicon-based ceramics (Si–C–N and Si–Al–C–N) and TiN@Si–Al–C–N nanocomposites were developed using a precursor derived ceramics approach. In TiN@Si–Al–C–N nanocomposites, TiN nanocrystals (with sizes in the range of 5–12 nm) were effectively anchored on an amorphous Si–Al–C–N support. The nanocomposites were found to be mesoporous in nature and exhibited a surface area as high as 132 m²/g. The average pore size of the nanocomposites was found to increase with an increase in the pyrolysis temperature, and a subsequent graphitization of free carbon was observed as revealed from the Raman spectra. The ceramics were investigated for electrocatalytic activity toward the oxygen reduction reaction using the rotating disk electrode method. The TiN@Si–Al–C–N nanocomposites showed an onset potential of 0.7 V versus reversible hydrogen electrode for oxygen reduction, which seems to indicate a 4-electron pathway at the pyrolysis temperature of 1000°C in contrast to a 2-electron pathway exhibited by the nanocomposites pyrolyzed at 750°C via the Koutecky–Levich plot.     

Extreme narrow photonic bands and strong photonic localization produced by 2D defect two-segment-connected quadrangular waveguide networks

In this paper, we investigate the properties of optical transmission and photonic localization of two-dimensional (2D) defect two-segment-connected quadrangular waveguide networks (DTSCQWNs) and find that many groups of extreme narrow photonic bands are created in the middle of the transmission spectra. The electromagnetic (EM) waves in DTSCQWNs with the frequencies of extreme narrow photonic bands can produce strong photonic localizations by adjusting defect broken degree. On the other hand, we obtain the formula of extreme narrow photonic bands’ frequencies dependent on defect broken degree and the formula of the largest intensity of photonic localization dependent on defect broken degree, respectively. It may possess potential application for designing all-optical devices based on strong photonic localizations. Additionally, we propose a so-called defecton mode to study the splitting rules of extreme narrow photonic bands, where decomposition-decimation method is expanded from the field of electronic energy spectra to that of optical transmission spectra.     

Overview of emerging database architectures

A database system is a miniworld data repository representing some aspects of the real world. In a database system, information is well organized and has some inherent meaning. In recent years, the emergence of new types of computer applications, such as multimedia and computer-added manufacturing, have resulted in demands to manage complex data types that are beyond the capabilities of existing relational databases. At the same time, new developments in network technologies, artificial intelligence, semantic modeling, and object-oriented programming have inspired research in database topics such as distributed, deductive, object-oriented, active, and deductive and object-oriented databases (DOOD). Essentially, the most promising new database technologies combine the merits of different kinds of database architectures. Starting with the relational database architecture, this paper will review the emerging database technologies, and thereby, provide insight into current and future directions in database technologies.     

The amalgamation of neural networks and fuzzy logic systems—A survey

Both neural networks and fuzzy logic systems exhibit human-like mental processing. The similarities and dissimilarities of these two technologies, such as multi-layer operations of neural networks and max-min operation in fuzzy logic systems, make apparent that there are advantages to combining them. However, this was not done until the late 1980's. Surveying the literature revealed eight different approaches to combining the merits of fuzzy logic systems and neural networks.     

用于细胞及组织培养的低强度LED生物光源

研制出可用于细胞及组织培养的低强度发光二极管光源。介绍了此光源的光路原理和简要结构，测试了该光源的辐射照度及其强度分布，使用统计分析软件SPSS拟合得到该光源的辐射照度经验公式。