Synthesis and characterization of SrFeOx hetero-film resistance-switching device with low operation voltage

As a critical topological phase transition material, SrFeO_x could play an essential role in the field of resistive memory. How to implement resistance-switching more softly and ensure the stability of materials has always been a relevant research hotspot. Regulating the oxygen environment during the deposition process of the films can effectively control the stoichiometry of the functional layer and then improve the resistance-switching characteristics of the device. In this paper, a SrFeO_x hetero-film was prepared by oxygen pretreatment on the SrRuO₃ surface before SrFeO_x deposition, and the as-assembled micrometer-scale device exhibits a low set operating voltage of 0.6 V and favorable cycling characteristics. The SrFeO_x hetero-film reveals a vertical brownmillerite superlattice-like structure with ～20 nm perovskite buffer layer, which benefits the connection and rupture of conductive filament. Additionally, XPS and UV–vis were used to analyze the bonding energy and band gap of SrFeO_x hetero-film, and offers the experimental basis for the explanation of the conductive mechanism. Therefore, the device based on SrFeO_x hetero-film with low operation voltage provides a reference for low power consumption research on topological phase transition material.     

The operation types and operation window for high-purity hydrogen production for the sorption enhanced steam methane reforming in a fixed-bed reactor

The operation types and operation window for high-purity H₂ production for the sorption enhanced steam methane reforming (SE-SMR) with Ni/Al₂O₃ catalyst and CaO sorbent in a fixed-bed reactor are investigated by an experimentally verified 2D numerical method. Four chemical reactions including steam reforming, water gas shift, global steam reforming, and CO₂ sorption are considered. The operation window is defined as the H₂ and CO molar fractions at outlet satisfying both y_H2,out ≥ 90% and y_CO,out ≤ y_CO,allow (= 1%, 2% or 3%) in dry base. Under the conditions of y_H2,out and y_CO,allow, there are six operation types, of which 2 types are within the operation window and 4 types are not within the operation window as the temperature, weight hourly space velocity (WHSV) and steam to methane (S/C) molar ratio vary. For a common case of S/C = 3, the operation windows for y_CO,allow = 3% at WHSV = 8.5 h^?1 and 42.5 h^?1 are located at 570–670 °C and 640–690 °C respectively, based on the parameters in this work. The operation window of temperature is wider with decreasing WHSV, and it becomes wider remarkably as the S/C ratio increases. The lowest temperature inside the operation window is 550 °C. The effects of the temperature, WHSV and S/C ratio on the operating types, y_H2,out and y_CO,out are also presented and discussed in details.     

Hydrogen production by oxidative steam reforming of methanol over anodic aluminum oxide-supported Cu-Zn catalyst

Oxidative steam reforming of methanol (OSRM), which is a convenient reaction for producing hydrogen, suffers from the hot spot formation problem when conventional particle catalysts are used. Recently, an anodic aluminum oxide (AAO)-supported Cu-Zn catalyst was proposed as an OSRM catalyst for its high thermal conductivity through the aluminum metal body. In this study, OSRM was conducted in a prototype reactor packed with the AAO plate catalyst strips. It was verified that the high thermal conductivity of the catalyst effectively suppresses the hot spot formation and makes the temperature profile smooth along the reactor. The start-up time of the reactor depended on the preheating temperature and was very short (less than 2 min) for preheating over 503 K. The methanol conversion and reactor temperature increased with increasing O₂/CH₃OH mole ratio, indicating that the mole ratio can be used as a control variable to operate the reactor at desired conditions. Further, a reactor model was developed and verified, and the simulation showed that for a given total reactor volume, an optimal reactor configuration could be achieved by shortening the reactor length while widening the cross-sectional area.     

Potential pitfalls of smart city development: A study on parking mobile applications (apps) in Hong Kong

Smart cities are built upon information and communication technologies (ICTs) to enable a broad range of advanced services. Through a comprehensive literature review, this study identified four pitfalls brought by the pervasive application of ICT, including information insecurity, privacy leakage, information islands, and digital divide. Therefore, a questionnaire survey together with 27 interviews was conducted in Hong Kong to investigate how the public perceived these pitfalls within the context of mobile apps providing real-time parking information which form a major part of smart mobility. System insecurity and privacy leakage were found to arouse worries among the app-users while their awareness of protecting personal data was found to have room for improvement. Islands of real-time parking information occur as a result of the lack of collaboration among private carpark operators. Digital divide existed widely among the disadvantaged groups and the problem cannot be solved by mere provision of ICT facilities. Overall, technologies alone cannot make a city smart or smarter. It is the suitable way in which ICTs are used to serve all citizens that matters.     

Why do people purchase virtual goods? A uses and gratification (U&G) theory perspective

Few literature studies have investigated the relationships between different uses and gratifications (U&Gs) of mobile instant messaging (MIM) apps, continuation, and purchase intentions. To address this gap, the researchers aimed to examine the influence of the content, social, process, and technology U&Gs of MIM on continuation intentions toward MIMs, and purchase intentions toward virtual goods available on MIMs. A comprehensive research model was developed based on the U&G theory, which was tested using cross-sectional data from 309 Japanese MIM users. The study considered six different U&Gs of MIM as independent variables and purchase intentions towards stickers and continuation intentions towards MIM as dependent variables. The study results suggest that exposure U&G has a significant positive association with MIM sticker purchase intentions. The entertainment and affection U&G are positively associated with continuation intentions towards MIM use. The study contributes to the literature by investigating U&Gs that motivate MIM users to have both positive purchase intentions toward virtual goods, such as stickers, and continuation intentions toward MIMs. The study has significant theoretical and practical implications for both researchers and practitioners who are interested in virtual goods, the virtual economy, MIM apps, social media, new media, and the service economy.     

A Differentially Private Data Aggregation Method Based on Worker Partition and Location Obfuscation for Mobile Crowdsensing

With the popularity of sensor-rich mobile devices, mobile crowdsensing (MCS) has emerged as an effective method for data collection and processing. However, MCS platform usually need workers’ precise locations for optimal task execution and collect sensing data from workers, which raises severe concerns of privacy leakage. Trying to preserve workers’ location and sensing data from the untrusted MCS platform, a differentially private data aggregation method based on worker partition and location obfuscation (DP-DAWL method) is proposed in the paper. DP-DAWL method firstly use an improved K-means algorithm to divide workers into groups and assign different privacy budget to the group according to group size (the number of workers). Then each worker’s location is obfuscated and his/her sensing data is perturbed by adding Laplace noise before uploading to the platform. In the stage of data aggregation, DP-DAWL method adopts an improved Kalman filter algorithm to filter out the added noise (including both added noise of sensing data and the system noise in the sensing process). Through using optimal estimation of noisy aggregated sensing data, the platform can finally gain better utility of aggregated data while preserving workers’ privacy. Extensive experiments on the synthetic datasets demonstrate the effectiveness of the proposed method.     

《化学制药单元操控》工学结合课程的教学探索

《化学制药单元操控》是一门新开发的将情景教学、实验操作和仿真实训相结合的工学结合课程。其中,引入化工仿真教学这一新型的教学方式,即通过在非常逼真的操作环境中进行技能训练,使学生对实际生产装置有更加感性的了解和认识。本文对《化学制药单元操控》工学结合课程开发与实施应用过程进行分析和总结得到几点经验,同时分享对该门课程教学改革中的一些心得。     

Efficient framework for mobile walkthrough application

The past few years have witnessed a dramatic growth in the number and variety of graphics intensive mobile applications, which allow users to interact and navigate through large scenes such as historical sites, museums and virtual cities. These applications support many clients and impose a heavy requirement on network resources and computational resources. One key issue in the design of cost efficient mobile walkthrough applications is the data transmission between servers and mobile client devices. In this paper, we propose an effective progressive mesh transmission framework that stores and divide scene objects into different resolutions. In this approach, each mobile device progressively receives and processes only the object’s details matching its display resolution which improves the overall system’s response time and the user’s perception. A fine grained cache mechanism is used to keep the most frequently requested objects’ details in the device memory and consequently reduce the network traffic. Experiments, in simulated and real world environment, are used to illustrate the effectiveness of the proposed framework under various settings of the virtual scene and mobile device configuration. Experimental results show that the proposed framework can improve the walkthrough system performance in mobile devices, with a relatively small overhead.     

Cloud asset for urban flood control

The performance of physical assets has become a major determinant success factor for urban flood control. However, managing these assets is always challenging as there are a huge number of diverse assets involved, which are distributed throughout the city, and owned by different agencies. Aiming at improving the management efficiency of these assets, and ensuring their performance, this paper proposes the concept of cloud asset based on cloud computing, mobile agent, and various smart devices. Through hardware integration and software encapsulation, cloud asset could sense its real-time status, adapt to varied working scenarios, be controlled remotely, and shared among agencies. It enables accurate real-time control of every asset, and thus improves the management efficiency and effectiveness. This paper first presents the concept of cloud asset with its technical architecture, and then analyses the software agent model for cloud asset, which is the key enabler to realize UPnP (Universal Plug and Play) management of assets, and provides mobility and intelligence for them. After that, the framework of cloud asset-enabled workflow management is built, in which cloud asset could be easily found and dynamically invoked by different workflows. Finally, a demonstrative case is provided to verify the effectiveness of cloud asset.     

The PAR(p) Interconfigurations model used by the Brazilian Electric Sector

This study discusses the characteristics of the Periodic Autoregressive model, PAR(p), which is used to generate synthetic series of inflow energies that serve as entries for computer platforms that implement the planning and expansion of the operations of the BES – the Brazilian Electric Sector (SEB – Sistema Elétrico Brasileiro). The methodology for the design of a generating plant is presented in addition to the fundamentals of the “PAR(p) Interconfigurations” Model, which is referred to as the Inflow Energy Generation Model (IEGM) in this study. The major contribution of this study is to provide the first scientific discussion of the representation of multiple configurations using the PAR(p) model. For this purpose, several topics related to the time series are discussed, such as the definition of the model order, the matter of stationarity and the need to address possible outliers. Finally, a case study is presented, wherein the results of the estimation and generation of the described model’s scenarios are demonstrated.