Synchronization in arrays of coupled nonlinear systems with delay and nonreciprocal time-varying coupling

We study synchronization in an array of coupled nonlinear systems with delay and nonreciprocal time-varying coupling and present synchronization criteria which generalize previous synchronization results. We show that the array synchronizes when the nondelay coupling term is cooperative and large enough. Furthermore, we show that the synchronization criteria are related to several matrix quantities describing the coupling topology. These quantities can be considered as generalizations of the concept of algebraic connectivity to directed graphs.     

Rheo-optical studies on the deformation mechanism of semicrystalline polymers. VIII. Dynamic x-ray diffraction of a high-density polyethylene film having row-structure of C-axis orientation

Dynamic x-ray diffraction is employed to scrutinize the structural origin of the α mechanical dispersion of a highdensity polyethylene having preferentially oriented rownucleated cylindritic texture around the machine direction (MD). Results indicate that the α₁ dispersion is associated with two kinds of orientation processes of crystallites: (1) the orientation process involving the rotation of crystallites around the crystal b-axis (lamellar axis) dominates in the MD specimen; (2) the other process accompanying the rotation of crystallites or lamellar segments around their crystal a-axis dominates in the TD (transverse direction) specimen. The complex apparent crystal lattice compliances show no frequency dependence in the real component and no appreciable value in the imaginary component, indicating that the α₁ process is definitely associated with the intercrystalline process, but not relavent to the intracrystal process. However, at elevated temperatures, the complex lattice compliances exhibit a remarkable frequency dependence, suggesting that the α₂ dispersion concomitant to intracrystalline nature takes place in this time scale. The α₂ dispersion was found to be more pronounced upon stretching along the lamellar axis (TD) than normal to it (MD).     

An organic MNA crystal phase modulator

A prototype transverse phase modulator employing the organic electrooptic MNA (2-methyl-4-nitroaniline) crystal is described. The design configurations and performance characteristics are presented. MNA was purchased as a fine greenish-yellow powder and was purified by multiple sublimations under low pressure. Purified MNA powder was subsequently saturated in acetone. To start growth, the beaker of filtered solution was placed in the dessicator with an equal volume of toluene on the bottom. The vapors of the solvent would fill the sealed vessel and get reabsorbed into the liquids. In the process, toluene molecules displaced the MNA ones, forcing them to precipitate out into crystalline form. Under controlled conditions of stable temperature and vapor exchange rate, large quality samples were obtained     

Comparative study on the static and dynamic characteristics of four types of PMFCLs for large capacity applications

Permanent-Magnet-Biased Saturation Based Fault Current Limiter (PMFCL) may find early applications in high-voltage and large capacity power systems due to prominent advantages such as compactness, small size, reliable and safe operation, and zero reset time. The prevailing topologies and the operating principles of the PMFCLs are elucidated in the paper. Theoretical analysis on both the static and dynamic characteristics of different modes of PMFCLs is carried out comparatively, in which new concepts of effective magnetic flux density and magnetic field intensity are proposed to describe the overall impacts of the magnetic field on the current limiting capacity of the PMFCLs. Based on theoretical analysis and mathematical deduction, equivalent magnetic circuits and equations are established, which presents invaluable fundamentals for further study on the operating mechanism of different modes of PMFCLs as well as optimization of the fault current limiting topology design.     

Containment system for the preparation of vitrified-hydrated virus specimens

A guillotine-type quick freezing device and a bio-hazard containment box have been designed, constructed, and used to prepare vitrifiedhydrated specimens of viruses in their native environment. Special design considerations include the preservation of the specimen in its natural state in vitrified ice, prevention of virus aerosols escape, and control of the potentially explosive air-coolant vapor mixtures.     

Trends and driving forces of low-carbon energy technology innovation in China’s industrial sectors from 1998 to 2017: from a regional perspective

Low-carbon energy technology (LC) innovation contributes to both environmental protection and economic development. Using the panel data of 30 provinces/autonomous regions/municipalities in China from 1998 to 2017, this paper constructs a two-layer logarithmic mean Divisia index (LMDI) model to uncover the factors influencing the variation of the innovation of LC in China’s industrial sectors, including the alternative energy production technology (AEPT) and the energy conversation technology (ECT). The results show that China’s industrial LC patent applications rapidly increased after 2005 and AEPT patent applications outweighed ECT patent applications all the time with a gradually narrowing gap. Low-carbon degree played the dominant role in promoting the increase in China’s industrial LC patent applications, followed by the economic scale, R&D (research and development) efficiency, and R&D share. Economic structure contributed to the increases in LC patent applications in the central and the western regions, while led to the decreases in the eastern region, the north-eastern region, and Chinese mainland Xizang(Tibet) Autonoomous Region is not considered due to lack of data. This note applies to the entire article.. Low-carbon degree and economic scale were two main contributors to the growths of both industrial AEPT patent applications and ECT patent applications in Chinese mainland and the four regions. Several policy recommendations are made to further promote industrial innovation in China.     

Test bed for power amplifier behavioral characterization and modeling

Traditional test bed of power amplifier (PA) behavioral characterization and modeling based on vector signal analyzer (VSA) and often equipped with specialized software is both expensive and inflexible to modify to suit different scenarios. In this paper, a new test bed based on an oscilloscope or other general purpose data acquisition systems, which works as analog to digital converter (ADC) with a proper (radio frequency) RF bandwidth and maximum sampling rate, is proposed. The common impairments, e.g. transmitter IQ imbalances, channel delay, frequency offset, and carrier phase offset, are all well compensated. The accurately recovered envelopes of the PA’s input and output signals are used for a PA behavioral characterization and modeling. Furthermore, Relative envelope error (REE) parameter is proposed to evaluate the accuracy of envelope recovery. The experiment shows a very accurate RF signal envelope recovery, and a good performance of PA behavioral modeling.     

Sentiment Analysis System in Big Data Environment

Nowadays, Big Data, a large volume of both structured and unstructured data, is generated from Social Media. Social Media are powerful marketing tools and social big data can offer the business insights. The major challenge facing social big data is attaining efficient techniques to collect a large volume of social data and extract insights from the huge amount of collected data. Sentiment Analysis of social big data can provide business insights by extracting the public opinions. The traditional analytic platforms need to be scaled up for analyzing a large volume of social big data. Social data are by nature shorter and generally not constructed with proper grammatical rules and hence difficult to achieve high reliable result in Sentiment Analysis. Acquiring effective training data is a challenge, although learning based approaches are good for sentiment classification. Manual Labeling for training data is time and labor consuming. In this paper, Sentiment Analysis system on Big Data Analytics platform is proposed to provide valuable information by analyzing large scale social data in an efficient and timely manner since they have been implemented using a MapReduce framework and a Hadoop distributed storage (HDFS). The proposed Sentiment Analysis system consists of four modules: data collection, data cleaning and preprocessing, class labeling and sentiment classification. The system enables high-level performance of sentiment classification while taking advantage of combining lexicon-based classifier’s effortless setup process and learning based classifier. Twitter stream data is used for system evaluation as the Twitter is widespread Social Media and a good source of information in the sense of snapshots of moods and feelings as well as up-to-date events. The evaluation results show that this system achieve a promising accuracy by 84.2%. Moreover, this system is able to scale up to analyze the large scale data by decreasing the processing time when adding more nodes in the cluster.     

Phase Reversion‐Induced Nanograined/Ultrafine‐Grained Structures in Austenitic Stainless Steel and their Significance in Modulating Cellular Response: Biochemical and Morphological Study with Fibroblasts

Materials science, engineering, and biological sciences have been combined to improve the tissue compatibility of medical devices. In this regard, nano/ultrafine structuring of austenitic stainless steel obtained using an innovative approach of “phase‐reversion” has been evaluated for modulation of cellular activity. The biochemical and morphology study with fibroblasts point toward the improvement of tissue compatibility on comparison with coarse‐grained structures, strengthening the foundation of nanostructured materials for bio‐medical applications.