Microwave assisted-in situ synthesis of porous titanium/calcium phosphate composites and their in vitro apatite-forming capability

Microwave irradiation has been proven to be an effective heating source in synthetic chemistry, and can accelerate the reaction rate, provide more uniform heating and help in developing better synthetic routes for the fabrication of bone-grafting implant materials. In this study, a new technique, which comprises microwave heating and powder metallurgy for in situ synthesis of Ti/CaP composites by using Ti powders, calcium carbonate (CaCO₃) powders and dicalcium phosphate dihydrate (CaHPO₄·2H₂O) powders, has been developed. Three different compositions of Ti:CaCO₃:CaHPO₄·2H₂O powdered mixture were employed to investigate the effect of the starting atomic ratio of the CaCO₃ to CaHPO₄·2H₂O on the phase, microstructural formation and compressive properties of the microwave synthesized composites. When the starting atomic ratio reaches 1.67, composites containing mainly alpha-titanium (α-Ti), hydroxyapatite (HA), beta-tricalcium phosphate (β-TCP) and calcium titanate (CaTiO₃) with porosity of 26%, pore size up to 152 μm, compressive strength of 212 MPa and compressive modulus of 12 GPa were formed. The in vitro apatite-forming capability of the composite was evaluated by immersing the composite into a simulated body fluid (SBF) for up to 14 days. The results showed that biodissolution occurred, followed by apatite precipitation after immersion in the SBF, suggesting that the composites are suitable for bone implant applications as apatite is an essential intermediate layer for bone cells attachment. The quantity and size of the apatite globules increased over the immersion time. After 14 days of immersion, the composite surface was fully covered by an apatite layer with a Ca/P atomic ratio approximately of 1.68, which is similar to the bone-like apatite appearing in human hard tissue. The results suggested that the microwave assisted-in situ synthesis technique can be used as an alternative to traditional powder metallurgy for the fabrication of Ti/CaP biocomposites.     

A new numerical algorithm to check the observability and bad-data processing ability of the metering scheme

This paper provides a unified approach for the optimization of measurements placements employed for power system online monitoring through state estimation. The proposed methodology, which can be suitable for the mixed measure system, preserves state estimation observability and bad-data processing capability by employing numerical algorithms for observability checking, critical measurements and critical couple identification. First, node injection radix measurements and measurement categories are defined. According to the above definitions, the coefficient matrix can be solved. The analysis on the column vectors of the coefficient matrix can determine each measurement classification. Furthermore, the numbers of each measurement class contains can determine bad-data processing capability. The observability can be checked by the type number of measurements. The proposed method is illustrated with the IEEE39-bus system and the IEEE118-bus system. Results from the case studies are presented to demonstrate that the approach adequately fulfills the desired properties related to observability, bad-data processing, cost, and robustness.     

基于三维胞元空间的MA双向并行路由算法

针对传统移动代理(MA)在监测无线传感器网络(WSNs)的感兴趣信息时产生的延迟较大和能耗较多问题,提出了基于三维胞元空间的MA双向并行(3D-BPMA)路由算法.3D-BPMA将MA与传统的客户/服务器(c/S)模式相结合,在胞元内利用C/S模式搜集信息,在单层胞元系统和路由器与路由器之间采用MA双向并行的策略进行传输.仿真结果表明:3D-BPMA与LCF,DSG-MIP算法相比减少了平均响应时间和网络平均能耗,提高了MA发送率.     

Numerical study of entropy generation in Darcy-Forchheimer (D-F) Bödewadt flow of CNTs

Three-dimensional Bödewadt flow (fluid rotates at a large enough distance from the stationary plate) of carbon nanomaterial is examined. Single walled and multi walled CNTs are dissolved in water and gasoline oil baseliquids. Darcy-Forchheimer porous medium is considered. Stationary disk is further stretched linearly in radial direction. Heat transfer effect is examined in presence of radiation and convection. Effect of viscous dissipation is accounted. Entropy generation rate is studied. By using adequate transformation (von Kármán relations), the flow field equations (PDEs) are transmitted into ODEs. Solutions to these ODEs are constructed via implementation of shooting method (bvp4c). In addition to Entropy generation rate, Bejan number, heat transfer rate (Nusselt number), skin friction and temperature of fluid are examined through involved physical parameters. Axial component of velocity intensifies with increment in nanoparticles volume fraction and ratio of stretching rate to angular velocity parameter while it decays with higher porosity parameter. Higher nanoparticles volume fraction and porosity parameter lead to decay in radial as well as tangential component of velocity. However it enhances with higher ratio of stretching rate to angular velocity parameter. Temperature of fluid directly varies with higher ratio of stretching rate to angular velocity parameter, radiation parameter, Eckert number, Biot number and nanoparticles volume fraction. Rate of Entropy generation is reduced with higher estimations of porosity parameter, nanoparticles volume fraction and radiation parameter. Skin friction coefficient decays with higher porosity parameter and ratio of stretching rate to angular velocity parameter. Intensification in porosity parameter, nanoparticles volume fraction and Biot number leads to higher Nusselt number. Prominent impact is shown by multiple-walled CNTs with gasoline oil basefluid than single-walled CNTs with water basefluid.     

Distributed ledger technology in supply chains: a transaction cost perspective

With the emergence of distributed ledger technology (DLT), numerous practitioners and researchers have proclaimed its beneficial impact on supply chain transactions in the future. However, the vast majority of DLT initiatives are discontinued after a short period. With the full potential of DLT laying far down the road, especially managers in supply chain management (SCM) seek for short-term cost-saving effects of DLT in order to achieve long-term benefits of DLT in the future. However, the extant research has bypassed grounding long-term as well as short-term effects of DLT on supply chain transaction with empirical data. We address this shortcoming, following an abductive research approach and combining empirical data from a multiple case study design with the corresponding literature. Our study reveals that the effects of DLT on supply chain transactions are two-sided. We found six effects of DLT solutions that have a cost-reducing or cost avoidance impact on supply chain transactions. In addition, we found two effects that change the power distribution between buyers and suppliers in transactions and a single effect that reduces the dependency of supply chain transactions on third parties. While cost-reducing and avoidance as well as dependency-reducing effects are positive effects, the change in power distribution might come with disadvantages. With these findings, the paper provides the first empirical evidence of the impact of DLT on supply chain transactions, which will enable managers to improve their assessment of DLT usage in supply chains.     

A signal adaptive diffusion filter for video coding: Mathematical framework and complexity reductions

In this paper we combine video compression and modern image processing methods. We construct novel iterative filter methods for prediction signals based on Partial Differential Equation (PDE) based methods. The mathematical framework of the employed diffusion filter class is given and some desirable properties are stated. In particular, two types of diffusion filters are constructed: a uniform diffusion filter using a fixed filter mask and a signal adaptive diffusion filter that incorporates the structures of the underlying prediction signal. The latter has the advantage of not attenuating existing edges while the uniform filter is less complex. The filters are embedded into a software based on HEVC with additional QTBT (Quadtree plus Binary Tree) and MTT (Multi-Type-Tree) block structure. In this setting, several measures to reduce the coding complexity of the tool are introduced, discussed and tested thoroughly. The coding complexity is reduced by up to 70% while maintaining over 80% of the gain. Overall, the diffusion filter method achieves average bitrate savings of 2.27% for Random Access having an average encoder runtime complexity of 119% and 117% decoder runtime complexity. For individual test sequences, results of 7.36% for Random Access are accomplished.     

基于深度学习的秀丽隐杆线虫显微图像分割方法

利用计算机实现自动、准确的秀丽隐杆线虫(C.elegans)的各项形态学参数分析,至关重要的是从显微图像上分割出线虫体态,但由于显微镜下的图像噪声较多,线虫边缘像素与周围环境相似,而且线虫的体态具有鞭毛和其他附着物需要分离,多方面因素导致设计一个鲁棒性的C.elegans分割算法仍然面临着挑战。针对这些问题,提出了一种基于深度学习的线虫分割方法,通过训练掩模区域卷积神经网络(Mask R-CNN)学习线虫形态特征实现自动分割。首先,通过改进多级特征池化将高级语义特征与低级边缘特征融合,结合大幅度软最大损失(LMSL)损失算法改进损失计算;然后,改进非极大值抑制;最后,引入全连接融合分支等方法对分割结果进行进一步优化。实验结果表明,相比原始的Mask R-CNN,该方法平均精确率(AP)提升了4.3个百分点,平均交并比(mIOU)提升了4个百分点。表明所提出的深度学习分割方法能够有效提高分割准确率,在显微图像中更加精确地分割出线虫体。     

Semantically enriched Massive Open Online Courses (MOOCs) platform

Massive Open Online Courses (MOOCs) are becoming an essential source of information for both students and teachers. Noticeably, MOOCs have to adapt to the fast development of new technologies; they also have to satisfy the current generation of online students. The current MOOCs’ Management Systems, such as Coursera, Udacity, edX, etc., use content management platforms where content are organized in a hierarchical structure. We envision a new generation of MOOCs that support interpretability with formal semantics by using the SemanticWeb and the online social networks. Semantic technologies support more flexible information management than that offered by the current MOOCs’ platforms. Annotated information about courses, video lectures, assignments, students, teachers, etc., can be composed from heterogeneous sources, including contributions from the communities in the forum space. These annotations, combined with legacy data, build foundations for more efficient information discovery in MOOCs’ platforms. In this article we review various Collaborative Semantic Filtering technologies for building Semantic MOOCs’ management system, then, we present a prototype of a semantic middle-sized platform implemented at Western Kentucky University that answers these aforementioned requirements.     

Economic growth,CO2 emissions,and energy consumption in the five ASEAN countries

This paper investigates the relationship between economic growth, carbon dioxide (CO₂) emissions, and energy consumption with an aim to test the validity of the Environmental Kuznets Curve (EKC) hypothesis in five ASEAN (Association of South East Asian Nations) countries (Indonesia, Malaysia, Philippines, Singapore, and Thailand) by applying the panel smooth transition regression (PSTR) model as a new econometric technique. The PSTR model is more flexible and appropriate for describing cross-country heterogeneity and time instability. Our empirical results strongly rejected the null hypothesis of linearity, and the test for no remaining nonlinearity indicated a model with one transition function and two threshold parameters. The first regime (levels of GDP per capita below 4686 USD) showed that environmental degradation increases with economic growth while the trend was reversed in the second regime (GDP per capita above 4686 USD). The results also showed that energy consumption with either the first or the second regime lead to increase CO₂. The overall results support the validity of the EKC hypothesis in the ASEAN countries.     

Optimized PI+ load–frequency controller using BWNN approach for an interconnected reheat power system with RFB and hydrogen electrolyser units

This paper investigates a renewable energy resource’s application to the Load–Frequency Control of interconnected power system. The Proportional-Integral (PI) controllers are replaced with Proportional-Integral Plus (PI+) controllers in a two area interconnected thermal power system without/with the fast acting energy storage devices and are designed based on Control Performance Standards (CPS) using conventional/Beta Wavelet Neural Network (BWNN) approaches. The energy storing devices Hydrogen generative Aqua Electroliser (HAE) with Fuel cell and Redox Flow Battery (RFB) are incorporated to the two area interconnected thermal power system to efficiently damp out the electromechanical oscillations in the power system because of their inherent efficient storage capacity in addition to the kinetic energy of the generator rotor, which can share the sudden changes in power requirements. The system was simulated and the frequency deviations in area 1 and area 2 and tie-line power deviations for 5% step- load disturbance in area 1 are obtained. The comparison of frequency deviations and tie-line power deviations of the two area interconnected thermal power system with HAE and RFB designed with BWNN controller reveals that the PI+ controller designed using BWNN approach is found to be superior than that of output response obtained using PI+ controller. Moreover the BWNN based PI+ controller exhibits a better transient and steady state response for the interconnected power system with Hydrogen generative Aqua Electroliser (AE) unit than that of the system with Redox Flow Battery (RFB) unit.