Mathematical vibration modeling for an electrostatic precipitator system

The rapping acceleration of collecting plates in electrostatic precipitator system determines the dust- rapping performance of electromagnetic vibration exciter. To maximize the acceleration, the resonance phenomena needs to be driven by matching the mechanical natural frequency of the electrostatic precipitator system and the input frequency of electric current which energizes the electromagnetic vibrator. In this paper, the dust collecting plates and the electromagnetic vibration exciter in electrostatic precipitator system are vibration-modeled mathematically to characterize the resonance frequency. The effective mass and stiffness for each mode of the collecting plates are calculated using finite elements analysis and the natural frequency are computed by the method of least error square. In addition, the effective mass and stiffness of the exciter are computed. Then, the whole electrostatic precipitator system is analyzed. A frequency response analysis based on a sine sweep signal experiment is performed on a prototype for verification of calculated theoretical resonance frequency

The need for a definition of big data for nursing science: A case study of disaster preparedness

© 2016 by the author; licensee MDPI, Basel, Switzerland. The rapid development of technology has made enormous volumes of data available and achievable anytime and anywhere around the world. Data scientists call this change a data era and have introduced the term âBig Dataâ, which has drawn the attention of nursing scholars. Nevertheless, the concept of Big Data is quite fuzzy and there is no agreement on its definition among researchers of different disciplines. Without a clear consensus on this issue, nursing scholars who are relatively new to the concept may consider Big Data to be merely a dataset of a bigger size. Having a suitable definition for nurse researchers in their context of research and practice is essential for the advancement of nursing research. In view of the need for a better understanding on what Big Data is, the aim in this paper is to explore and discuss the concept. Furthermore, an example of a Big Data research study on disaster nursing preparedness involving six million patient records is used for discussion. The example demonstrates that a Big Data analysis can be conducted from many more perspectives than would be possible in traditional sampling, and is superior to traditional sampling. Experience gained from the process of using Big Data in this study will shed light on future opportunities for conducting evidence-based nursing research to achieve competence in disaster nursing.Link_to_subscribed_fulltex

Automatic Network Adaptation for Ultra-Low Uniform-Precision Quantization

Uniform-precision neural network quantization has gained popularity since it simplifies densely packed arithmetic unit for high computing capability. However, it ignores heterogeneous sensitivity to the impact of quantization errors across the layers, resulting in sub-optimal inference accuracy. This work proposes a novel neural architecture search called neural channel expansion that adjusts the network structure to alleviate accuracy degradation from ultra-low uniform-precision quantization. The proposed method selectively expands channels for the quantization sensitive layers while satisfying hardware constraints (e.g., FLOPs, PARAMs). Based on in-depth analysis and experiments, we demonstrate that the proposed method can adapt several popular networks channels to achieve superior 2-bit quantization accuracy on CIFAR10 and ImageNet. In particular, we achieve the best-to-date Top-1/Top-5 accuracy for 2-bit ResNet50 with smaller FLOPs and the parameter size.Comment: Accepted as a full paper by the TinyML Research Symposium 202

The Characteristics of Action Potentials in Primo Vessels and the Effects of Acetylcholine Injection to the Action Potentials

In a previous study, we found that Primo vessels generate different action potentials in smooth muscles, but this study compared the pulse shape to distinguish the two tissues. Thus, a more sophisticated extracellular experiment was performed in this study using an acetylcholine injection; we then observed changes in the amplitude, FWHM (full width at half maximum), and period to explore Primo vessel function. A third type of pulse was recorded for Primo vessels. We observed fast depolarizing and repolarizing phases for this pulse. Further, its FWHM was 30 ms between smooth muscles and neurons. Acetylcholine affected only the period. The amplitude and FWHM were consistent after injection. Primo-vessels generated action potentials at twice the frequency after injection. From the results, we speculate that Primo-vessels perform a role in transferring signals in a different manner, which may be relevant for acupuncture treatment

A carbon nanotubes-silicon nanoparticles network for high performance lithium rechargeable battery anodes

As an effort to address the chronic capacity fading of Si anodes and thus achieve their robust cycling performance, herein, we develop a unique electrode in which silicon nanoparticles are embedded in the carbon nanotubes network. Utilizing robust contacts between silicon nanoparticles and carbon nanotubes, the composite electrodes exhibit excellent electrochemical performance : 95.5% capacity retention after 140 cycles as well as rate capability such that at the C-rate increase from 0.1C to 1C to 10C, the specific capacities of 850, 698, and 312 mAh/g are obtained, respectively. The present investigation suggests a useful design principle for silicon as well as other high capacity alloying electrodes that undergo large volume expansions during battery operations.

Growth of Carbon Nanotubes on Carbon Fiber by Thermal CVD Using Ni Nanoparticles as Catalysts

AbstractNickel nanoparticles and thin film on carbon fiber have been prepared through electroless deposition. Moreover, carbon nanotubes were grown on carbon fiber covered by nickel nanoparticles using thermal chemical vapor deposition. The effects of changes in the thickness of the nickel catalyst layer and the growth temperature of carbon nanotubes were studied systemically, and the results are discussed in the present work