Comparison of the phase transfer oxidation of benzyl alcohol in a pump cell and stirred-tank reactor

The oxidation of benzyl alcohol by electrogenerated hypobromite in a two-phase emulsion has been studied using a quaternary ammonium salt as a phase transfer agent. The performances of a stirred-tank batch reactor and a bipolar electrochemical pump cell have been compared and the differences found are discussed in terms of the different mixing/transport/reaction regimes of the two cells. Benzaldehyde can be produced at a rate of 0.2 mol h^–1 dm^–2 of electrode area for 4.20 kWh kg^–1.     

Beef tallow biodiesel produced in a pilot scale

In the present work, the process of biodiesel production in a pilot plant has been studied using beef tallow as raw materials with methanol and potassium hydroxide as catalyst. The biodiesel quality is regulated by Brazilian specifications (Resolution 42) by the National Agency of Petroleum (ANP). The alkaline transesterification of animal fat with methanol produces a biodiesel with high quality and also with a good conversion rate. The process is possible but the economical viability must be improved by recovering methanol and glycerin. The obtained results have been used for industrial scale up of the process.     

On Estimation of Covariance Matrices With Kronecker Product Structure

The estimation of signal covariance matrices is a crucial part of many signal processing algorithms. In some applications, the structure of the problem suggests that the underlying, true covariance matrix is the Kronecker product of two valid covariance matrices. Examples of such problems are channel modeling for multiple-input multiple-output (MIMO) communications and signal modeling of EEG data. In applications, it may also be that the Kronecker factors in turn can be assumed to possess additional, linear structure. The maximum-likelihood (ML) method for the associated estimation problem has been proposed previously. It is asymptotically efficient but has the drawback of requiring an iterative search for the maximum of the likelihood function. Two methods that are fast and noniterative are proposed in this paper. Both methods are shown to be asymptotically efficient. The first method is a noniterative variant of a well-known alternating maximization technique for the likelihood function. It performs on par with ML in simulations but has the drawback of not allowing for extra structure in addition to the Kronecker structure. The second method is based on covariance matching principles and does not suffer from this drawback. However, while the large sample performance is the same, it performs somewhat worse than the first estimator in small samples. In addition, the Cramer-Rao lower bound for the problem is derived in a compact form. The problem of estimating the Kronecker factors and the problem of detecting if the Kronecker structure is a good model for the covariance matrix of a set of samples are related. Therefore, the problem of detecting the dimensions of the Kronecker factors based on the minimum values of the criterion functions corresponding to the two proposed estimation methods is also treated in this work.     

Casimir Effect in Optoelectronic Devices Using Ferrofluids

Some of the modern electronic and optoelectronic devices exploit ferrofluids contained in narrow gaps between two material plates. When the width of the gap becomes below a micrometer, the boundary plates are subjected to the Casimir force arising from the zero-point and thermal fluctuations of the electromagnetic field. These forces should be taken into account in microdevices with the dimensions decreased to below a micrometer. In this paper, we review recently performed calculations of the attractive Casimir pressure in three-layer systems containing a ferrofluid. We also find the ferrofluidic system where the Casimir pressure is repulsive. This result is obtained in the framework of the fundamental Lifshitz theory of van der Waals and Casimir forces. The conclusion is made that enhanced repulsion due to the presence of a ferrofluid may prevent from sticking of closely spaced elements of a microdevice.     

Scale-Invariant Scale-Channel Networks: Deep Networks That Generalise to Previously Unseen Scales

Journal of Mathematical Imaging and Vision - The ability to handle large scale variations is crucial for many real-world visual tasks. A straightforward approach for handling scale in a deep...     

On Surface Losses in Direct Metal Laser Sintering Printed Millimeter and Submillimeter Waveguides

Different lengths of WR3 (220–330 GHz) and WR10 (75–110 GHz) waveguides are fabricated through direct metal laser sintering (DMLS). The losses in these waveguides are measured and modelled using the Huray surface roughness model. The losses in WR3 are around 0.3 dB/mm and in WR10 0.05 dB/mm. The Huray equation model is accounting relatively good for the attenuation in the WR10 waveguide but deviates more in the WR3 waveguide. The model is compared to finite element simulations of the losses assuming an approximate surface structure similar to the resulting one from the DMLS process.     

Porous Enzymatic Membrane for Nanotextured Glucose Sweat Sensors with High Stability toward Reliable Noninvasive Health Monitoring

Development of reliable glucose sensors for noninvasive monitoring without interruption or limiting users' mobility is highly desirable, especially for diabetes diagnostics, which requires routine/long‐term monitoring. However, their applications are largely limited by the relatively poor stability. Herein, a porous membrane is synthesized for effective enzyme immobilization and it is robustly anchored to the modified nanotextured electrode solid contacts, so as to realize glucose sensors with significantly enhanced sensing stability and mechanical robustness. To the best of our knowledge, this is the first report of utilizing such nanoporous membranes for electrochemical sensor applications, which eliminates enzyme escape and provides a sufficient surface area for molecular/ion diffusion and interactions, thus ensuring the sustainable catalytic activities of the sensors and generating reliable measureable signals during noninvasive monitoring. The as‐assembled nanostructured glucose sensors demonstrate reliable long‐term stable monitoring with a minimal response drift for up to 20 h, which delivers a remarkable enhancement. Moreover, they can be integrated into a microfluidic sensing patch for noninvasive sweat glucose monitoring. The as‐synthesized nanostructured glucose sensors with remarkable stability can inspire developments of various enzymatic biosensors for reliable noninvasive composition analysis and their ultimate applications in predictive clinical diagnostics, personalized health‐care monitoring, and chronic diseases management.     

Catalytic behaviour of La4PdO7 based catalysts when exposed to car exhaust conditions

The catalytic properties of ex situ prepared La₄PdO₇ were studied under automotive exhaust conditions. Monophasic La₄PdO₇ was deposited onto-Al₂O₃ coated cordierite monoliths and light-off curves were recorded under oxidising and reducing conditions. Initially the catalytic activity for oxidation of CO and C₃H₆ and reduction of NO was low but after the catalyst had been exposed to a reducing atmosphere of simulated car exhaust composition at 600°C a three-way catalytic behaviour was obtained with aT ₅₀ value of about 340°C. Using oxidising conditions and a similar activation procedure, a catalyst with CO and C₃H₆ oxidation activity (T ₅₀=405° C) but minor activity for reduction of NO was obtained. This behaviour is interpreted in terms of La₄PdO₇ being decomposed and nanosized PdO particles being formed; these in turn are reduced to Pd and Pd is the catalytically active component in the catalyst. These conclusions are supported by X-ray diffraction, infrared spectroscopy, scanning and transmission electron microscopy studies combined with element analysis of freshly prepared and thermally activated catalysts.     

Direction of arrival estimation using adaptive directional time-frequency distributions

Time-frequency distributions (TFDs) allow direction of arrival (DOA) estimation algorithms to be used in scenarios when the total number of sources are more than the number of sensors. The performance of such time–frequency (t–f) based DOA estimation algorithms depends on the resolution of the underlying TFD as a higher resolution TFD leads to better separation of sources in the t–f domain. This paper presents a novel DOA estimation algorithm that uses the adaptive directional t–f distribution (ADTFD) for the analysis of close signal components. The ADTFD optimizes the direction of kernel at each point in the t–f domain to obtain a clear t–f representation, which is then exploited for DOA estimation. Moreover, the proposed methodology can also be applied for DOA estimation of sparse signals. Experimental results indicate that the proposed DOA algorithm based on the ADTFD outperforms other fixed and adaptive kernel based DOA algorithms.