Modelling and optimisation of a bimorph piezoelectric cantilever beam in an energy harvesting application

Piezoelectric materials are excellent transducers in converting vibrational energy into electrical energy, and vibration-based piezoelectric generators are seen as an enabling technology for wireless sensor networks, especially in selfpowered devices. This paper proposes an alternative method for predicting the power output of a bimorph cantilever beam using a finite element method for both static and dynamic frequency analyses. Experiments are performed to validate the model and the simulation results. In addition, a novel approach is presented for optimising the structure of the bimorph cantilever beam, by which the power output is maximised and the structural volume is minimised simultaneously. Finally, the results of the optimised design are presented and compared with other designs

Formation mechanism of SiGe nanorod arrays by combining nanosphere lithography and Au-assisted chemical etching

The formation mechanism of SiGe nanorod (NR) arrays fabricated by combining nanosphere lithography and Au-assisted chemical etching has been investigated. By precisely controlling the etching rate and time, the lengths of SiGe NRs can be tuned from 300 nm to 1 μm. The morphologies of SiGe NRs were found to change dramatically by varying the etching temperatures. We propose a mechanism involving a locally temperature-sensitive redox reaction to explain this strong temperature dependence of the morphologies of SiGe NRs. At a lower etching temperature, both corrosion reaction and Au-assisted etching process were kinetically impeded, whereas at a higher temperature, Au-assisted anisotropic etching dominated the formation of SiGe NRs. With transmission electron microscopy and scanning electron microscopy analyses, this study provides a beneficial scheme to design and fabricate low-dimensional SiGe-based nanostructures for possible applications

An Accelerating 3D Image Reconstruction System Based on the Level-of-Detail Algorithm

This paper proposes a research of An Accelerating 3D Image Reconstruction System Based on the Level-of-Detail Algorithm and combines 3D graphic application interfaces, such as DirectX3D and OpenCV to reconstruct the 3D imaging system for Magnetic Resonance Imaging (MRI), and adds Level of Detail (LOD) algorithm to the system. The system uses the volume rendering method to perform 3D reconstruction for brain imaging. The process, which is based on the level of detail algorithm that converts and formulates functions from differing levels of detail and scope, significantly reduces the complexity of required processing and computation, under the premises of maintaining drawing quality. To validate the system's efficiency enhancement on brain imaging reconstruction, this study operates the system on various computer platforms, and uses multiple sets of data to perform rendering and 3D object imaging reconstruction, the results of which are then verified and compared

Effects of Ox-LDL on Macrophages NAD(P)H Autofluorescence Changes by Two-photon Microscopy

Ox-LDL uptakes by macrophage play a critical role in the happening of atherosclerosis. Because of its low damage on observed cells and better signal-to- background ratio, two-photon excitation fluorescence microscopy is used to observe NAD(P)H autofluorescence of macrophage under difference cultured conditions- bare cover glass, coated with fibronectin or poly-D-lysine. The results show that the optimal condition is fibronectin coated surface, on which, macrophages profile can be clearly identified on NAD(P)H autofluorescence images collected by two-photon microscopy. Moreover, different morphology and intensities of autofluorescence under different conditions were observed as well. In the future, effects of ox-LDL on macrophages will be investigated by purposed system to research etiology of atherosclerosis.Comment: Submitted on behalf of TIMA Editions (http://irevues.inist.fr/tima-editions

Performance Improvement of a Feedback Control System Using an Accelerometer-Enhanced Velocity Observer

The paper shows how an accelerometer- enhanced velocity estimator can be used to improve the tracking performance of a feedback control system. In contrast to conventional velocity estimators that use positional information only, the accelerometer-enhanced velocity estimator fuses the position sensor and the accelerometer together to produce an improved velocity estimation. Experimental results are presented to show the effectiveness of the accelerometer-enhanced velocity estimator on improving the tracking performance of a linear motion stage

Solar Heating in Taiwan

AbstractSolar water heaters (SWHs) can provide hot water at temperatures ranging from 40 to 80oC for domestic or industrial use. With the subsidy programs (1986-1991 and 2000-present) offered by the Bureau of Energy, Ministry of Economic Affairs and some municipal governments, the accumulated area of solar collectors installed at the end of 2012 reached 2.25 million square meters. The well-orchestrated and concerted efforts put forward by the government of Taiwan, particularly with the Renewable Energy Development Bill promulgated in 2010, have played a significant role in the increased dissemination of SWHs. Further, the long-duration national subsidy programs might constitute one of the main driving forces for local market expansion. The mass media should be more aggressively utilized to enhance public awareness and promote utilization of SWHs. Organizations also need to consider the interests of society by being accountable for their businesses practices and by being responsible for the impact of their activities on the environment. This paper reports the current status and perspectives of SWHs in Taiwan, according to the desk and field surveys

A Simple Model for Cavity Enhanced Slow Lights in Vertical Cavity Surface Emission Lasers

We develop a simple model for the slow lights in Vertical Cavity Surface Emission Lasers (VCSELs), with the combination of cavity and population pulsation effects. The dependences of probe signal power, injection bias current and wavelength detuning for the group delays are demonstrated numerically and experimentally. Up to 65 ps group delays and up to 10 GHz modulation frequency can be achieved in the room temperature at the wavelength of 1.3 $\mu$m. The most significant feature of our VCSEL device is that the length of active region is only several $\mu$m long. Based on the experimental parameters of quantum dot VCSEL structures, we show that the resonance effect of laser cavity plays a significant role to enhance the group delays

The Proteins PDIP3 and ZC11A Associate with the Human TREX Complex in an ATP-Dependent Manner and Function in mRNA Export

The conserved TREX complex, which contains UAP56, Aly, CIP29, and the multi-subunit THO complex, functions in mRNA export. Recently, several putative new components of the human TREX complex were identified by mass spectrometry. Here, we investigated the function of two of these, PDIP3 and ZC11A. Our data indicate that both of these proteins are components of a common TREX complex and function in mRNA export. Recently, we found that both CIP29 and Aly associate with the DEAD box helicase UAP56 and with the TREX complex in an ATP-dependent manner. We now show that this is also the case for PDIP3 and ZC11A. Thus, together with previous work, our data indicate that the TREX complex participates in multiple ATP-dependent interactions

Ontology-based Fuzzy Markup Language Agent for Student and Robot Co-Learning

An intelligent robot agent based on domain ontology, machine learning mechanism, and Fuzzy Markup Language (FML) for students and robot co-learning is presented in this paper. The machine-human co-learning model is established to help various students learn the mathematical concepts based on their learning ability and performance. Meanwhile, the robot acts as a teacher's assistant to co-learn with children in the class. The FML-based knowledge base and rule base are embedded in the robot so that the teachers can get feedback from the robot on whether students make progress or not. Next, we inferred students' learning performance based on learning content's difficulty and students' ability, concentration level, as well as teamwork sprit in the class. Experimental results show that learning with the robot is helpful for disadvantaged and below-basic children. Moreover, the accuracy of the intelligent FML-based agent for student learning is increased after machine learning mechanism.Comment: This paper is submitted to IEEE WCCI 2018 Conference for revie