Effect of Crystallization of the Grain-Boundary Phase on the Thermal Diffusivity of a Sialon Ceramic

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65865/1/j.1151-2916.1984.tb19519.x.pd

Transport properties in Simplified Double Exchange model

Transport properties of the manganites by the double-exchange mechanism are considered. The system is modeled by a simplified double-exchange model, i.e. the Hund coupling of the itinerant electron spins and local spins is simplified to the Ising-type one. The transport properties such as the electronic resistivity, the thermal conductivity, and the thermal power are calculated by using Dynamical mean-field theory. The transport quantities obtained qualitatively reproduce the ones observed in the manganites. The results suggest that the Simplified double exchange model underlies the key properties of the manganites.Comment: 5 pages, 5 eps figure

Candle flames in microgravity

The candle flame in both normal and microgravity is non-propagating. In microgravity, however, the candle flame is also non-convective where (excepting Stefan flow) pure diffusion is the only transport mode. It also shares many characteristics with another classical problem, that of isolated droplet combustion. Given their qualitatively similar flame shapes and the required heat feedback to condensed-phase fuels, the gas-phase flow and temperature fields should be relatively similar for a droplet and a candle in reduced gravity. Unless the droplet diameter is maintained somehow through non-intrusive replenishment of fuel, the quasi-steady burning characteristics of a droplet can be maintained for only a few seconds. In contrast, the candle flame in microgravity may achieve a nearly steady state over a much longer time and is therefore ideal for examining a number of combustion-related phenomena. In this paper, we examine candle flame behavior in both short-duration and long-duration, quiescent, microgravity environments. Interest in this type of flame, especially 'candle flames in weightlessness', is demonstrated by very frequent public inquiries. The question is usually posed as 'will a candle flame burn in zero gravity', or, 'will a candle burn indefinitely (or steadily) in zero gravity in a large volume of quiescent air'. Intuitive speculation suggests to some that, in the absence of buoyancy, the accumulation of products in the vicinity of the flame will cause flame extinction. The classical theory for droplet combustion with its spherically-shaped diffusion flame, however, shows that steady combustion is possible in the absence of buoyancy if the chemical kinetics are fast enough. Previous experimental studies of candle flames in reduced and microgravity environments showed the flame could survive for at least 5 seconds, but did not reach a steady state in the available test time

An interstitial fluid transdermal extraction system for continuous glucose monitoring

A novel microfluidic system which is fabricated with five polydimethylsiloxane layers for interstitial fluid (ISF) extraction, collection, and measurement toward the application of continuous and real-time glucose monitoring is presented in this paper. The system consists of a micro vacuum generator for ISF transdermal extraction and fluid manipulation, micro chambers for the collection of ISF, micro pneumatic valves for fluid management, and a micro flow sensor for ISF volume measurement. Sequentially controlled by the pneumatic valves, the ISF extraction, collection, and volumetric measurement functions of the system were demonstrated using the stable vacuum generated by the integrated vacuum generator. Through low-frequency ultrasound pretreated full-thickness pig skin, the normal saline solution with different glucose concentrations was transdermally extracted, collected, and measured. The absolute error in the volume measurement of the transdermally extracted ISF analog was less than 0.05 μ L. The microfluidic system makes it possible to realize the clinical application of continuous glucose monitoring based on ISF transdermal extraction technology. © 2012 IEEE.published_or_final_versio

Pola Kearifan Masyarakat Lokal dalam Sistem Sawah Surjan untuk Konservasi Ekosistem Pertanian

Tujuan penelitian ini adalah untuk mengetahui pola kearifan petani sawah surjan dalam mengkonservasi lahan pertanian dan hubungan pola kearifan petani sawah surjan dengan komponen-komponen ekosistem pertanian yang dapat dikonservasi. Metode penelitian yang digunakan adalah kuantitatif. Pengumpulan data dilakukan dengan menggunakan data sekunder dan angket. Data dianalisis secara deskriptif kuantitatif. Hasil penelitian dapat disimpulkan bahwa pola kearifan petani sawah surjan dalam mengkonservasi lahan pertanian adalah secara turun temurun, seringkali tanpa memahami makna atau tanpa sadar; dan hubungan pola kearifan petani sawah surjan dengan komponen-komponen ekosistem pertanian yang dapat dikonservasi adalah membantu menciptakan ekosistem pertanian yang lebih stabil dengan adanya keragaman tanaman yang ditanam, sehingga tidak mudah terserang hama dan dengan adanya diversifikasi hasil panen dapat memberikan keuntungan lebih bagi petan

Data-driven structural health monitoring using feature fusion and hybrid deep learning

Smart structural health monitoring (SHM) for large-scale infrastructures is an intriguing subject for engineering communities thanks to its significant advantages such as timely damage detection, optimal maintenance strategy, and reduced resource requirement. Yet, it is a challenging topic as it requires handling a large amount of collected sensors data continuously, which is inevitably contaminated by random noises. Therefore, this study developed a practical end-to-end framework that makes use of physical features embedded in raw data and an elaborated hybrid deep learning model, namely 1DCNN-LSTM, featuring two algorithms - Convolutional Neural Network (CNN) and Long-Short Term Memory (LSTM). In order to extract relevant features from sensory data, the method combines various signal processing techniques such as the autoregressive model, discrete wavelet transform, and empirical mode decomposition. The hybrid deep learning 1DCNN-LSTM is designed based on the CNN’s capacity of capturing local information and the LSTM network’s prominent ability to learn long-term dependencies. Through three case studies involving both experimental and synthetic datasets, it is demonstrated that the proposed approach achieves highly accurate damage detection, as accurate as the powerful two-dimensional CNN, but with a lower time and memory complexity, making it suitable for real-time SHM

Discrete Model of Ideological Struggle Accounting for Migration

A discrete in time model of ideological competition is formulated taking into account population migration. The model is based on interactions between global populations of non-believers and followers of different ideologies. The complex dynamics of the attracting manifolds is investigated. Conversion from one ideology to another by means of (i) mass media influence and (ii) interpersonal relations is considered. Moreover a different birth rate is assumed for different ideologies, the rate being assumed to be positive for the reference population, made of initially non-believers. Ideological competition can happen in one or several regions in space. In the latter case, migration of non-believers and adepts is allowed; this leads to an enrichment of the ideological dynamics. Finally, the current ideological situation in the Arab countries and China is commented upon from the point of view of the presently developed mathematical model. The massive forced conversion by Ottoman Turks in the Balkans is briefly discussed.Comment: 24 pages, with 5 figures and 52 refs.; prepared for a Special issue of Advances in Complex System

Three-dimensional brain reconstruction of in vivo electrode tracks for neuroscience and neural prosthetic applications

The brain is a densely interconnected network that relies on populations of neurons within and across multiple nuclei to code for features leading to perception and action. However, the neurophysiology field is still dominated by the characterization of individual neurons, rather than simultaneous recordings across multiple regions, without consistent spatial reconstruction of their locations for comparisons across studies. There are sophisticated histological and imaging techniques for performing brain reconstructions. However, what is needed is a method that is relatively easy and inexpensive to implement in a typical neurophysiology lab and provides consistent identification of electrode locations to make it widely used for pooling data across studies and research groups. This paper presents our initial development of such an approach for reconstructing electrode tracks and site locations within the guinea pig inferior colliculus (IC) to identify its functional organization for frequency coding relevant for a new auditory midbrain implant (AMI). Encouragingly, the spatial error associated with different individuals reconstructing electrode tracks for the same midbrain was less than 65 μm, corresponding to an error of ~1.5% relative to the entire IC structure (~4–5 mm diameter sphere). Furthermore, the reconstructed frequency laminae of the IC were consistently aligned across three sampled midbrains, demonstrating the ability to use our method to combine location data across animals. Hopefully, through further improvements in our reconstruction method, it can be used as a standard protocol across neurophysiology labs to characterize neural data not only within the IC but also within other brain regions to help bridge the gap between cellular activity and network function. Clinically, correlating function with location within and across multiple brain regions can guide optimal placement of electrodes for the growing field of neural prosthetics

Detection of Spoilage in Canned Pasteurized Milk Using the Radiographic Imaging Technique

After packed into sterilized containers with a closed and rigorous process, pasteurized milk has been ensured for its hygiene and safety factors. However, distortions can occur during storage and transportation, causing the container to open, allowing harmful microorganisms to enter and damage the product. This research proposed a radiographic imaging technique to detect and evaluate the spoilage of canned pasteurized milk. The X-ray images show that the milk cans, which were left open for three days at 300 K, indicated regions with abnormal density with the smallest detectable size from 100 µm or larger. Density heterogeneity would be clearer in the following days and depending on the sample. An algorithm was developed to identify spoilage products automatically with an accuracy of up to 100 % and a speed of 0.0057 s/product. This approach may be suitable for industrial scale to control the quality of dairy products

Measurement in Quantum Physics

The conceptual problems in quantum mechanics -- related to the collapse of the wave function, the particle-wave duality, the meaning of measurement -- arise from the need to ascribe particle character to the wave function. As will be shown, all these problems dissolve when working instead with quantum fields, which have both wave and particle character. Otherwise the predictions of quantum physics, including Bell's inequalities, coincide with those of the standard treatments. The transfer of the results of the quantum measurement to the classical realm is also discussed.Comment: 34 pages, in Latex, revised and expanded version with an extra appendix on decoherenc