Novel Cooperative Scheme Based on Joint Band Assignment and Power Allocation for a Coexisting Radar-Communications System

In this paper, we present a novel cooperative scheme of joint optimal resource allocation, such that the overall performance of the coexisting radar-communications (CRC) system can be improved. In our proposed scheme, target detection and multiuser communication are performed by radar and communication subsystems at the same time, as well as a control center, which is responsible for joint resource management. We aim to minimize the ISLR for target detection and maximize the sum-rate for communications simultaneously by jointly optimizing the band assignment and transmit power allocation. Since the resulting optimization problem involving two performance metrics and a binary constraint is a multiobjective nonconvex problem, a two-tier iterative decomposition (TT-ID) approach is devised to obtain the globally optimal solution. However, compared with the conventional radar signals, the autocorrelation function of the devised radar signal may still have relatively high sidelobes. In particular, when the data transmission becomes the primary purpose of the CRC system, the sidelobe performance gets worse. As a consequence, some weak targets are most likely overshadowed by the adjacent strong targets through the matched filtering at the radar receiver. To address this, a spectral estimation algorithm based on the Bayes Cauchy–Gaussian (Bayes–CG) model is employed to further reduce the range sidelobes of the matched filter output at the radar receiver according to the prior distribution of the desired autocorrelation. Finally, several numerical results are provided to show the merits of the proposed method.

A New Artificial Urine Protocol to Better Imitate Human Urine

Artificial urine has many advantages over human urine for research and educational purposes. By closely mimicking healthy individuals’ urine, it may also be important in discovering novel biomarkers. However, up until now, there has not been any specific protocol to prove the similarity in terms of the chemical composition at the molecular level. In this study, a new artificial urine protocol is established to mimics the urine of healthy individuals. The multi-purpose artificial urine (MP-AU) presented here is compared with two other protocols most cited in literature. Furthermore, these three protocols are also compared with samples from 28 healthy young individuals. To do so, attenuated total reflection-Fourier transform infrared spectroscopy (ATR-FTIR) is used, according to which MP-AU shows a significantly close similarity with human urine. In formulating MP-AU, the infrared spectra of nine compounds is provided, making possible the band assignment of some absorption bands to certain compounds. Given its properties, the MP-AU protocol introduced here is both economical and practical, making it useful when designing comparative-controlled experiments.

Fiber-Content Measurement of Wool–Cashmere Blends Using Near-Infrared Spectroscopy

Cashmere and wool are two protein fibers with analogous geometrical attributes, but distinct physical properties. Due to its scarcity and unique features, cashmere is a much more expensive fiber than wool. In the textile production, cashmere is often intentionally blended with fine wool in order to reduce the material cost. To identify the fiber contents of a wool–cashmere blend is important to quality control and product classification. The goal of this study is to develop a reliable method for estimating fiber contents in wool–cashmere blends based on near-infrared (NIR) spectroscopy. In this study, we prepared two sets of cashmere–wool blends by using either whole fibers or fiber snippets in 11 different blend ratios of the two fibers and collected the NIR spectra of all the 22 samples. Of the 11 samples in each set, six were used as a subset for calibration and five as a subset for validation. By referencing the NIR band assignment to chemical bonds in protein, we identified six characteristic wavelength bands where the NIR absorbance powers of the two fibers were significantly different. We then performed the chemometric analysis with two multilinear regression (MLR) equations to predict the cashmere content (CC) in a blended sample. The experiment with these samples demonstrated that the predicted CCs from the MLR models were consistent with the CCs given in the preparations of the two sample sets (whole fiber or snippet), and the errors of the predicted CCs could be limited to 0.5% if the testing was performed over at least 25 locations. The MLR models seem to be reliable and accurate enough for estimating the cashmere content in a wool–cashmere blend and have potential to be used for tackling the cashmere adulteration problem.

Vibrational band assignment of 2-ethyl-1-hexanol

The vibrational structure of 2-ethyl-1-hexanol is of great interest because of its industrial and military applications. However, detailed spectral analysis is challenging due to its flexibility. This paper reports a detailed analysis of the gas and liquid phase vibrational spectra of 2-ethyl-1-hexanol using the Fourier transform infrared spectroscopy and Raman experimental data. By performing a detailed exploration of the conformational space in this work, the theoretical spectra reproduced almost all experimental details observed, and assigned internal valence coordinates to all of the experimentally observed bands in the floppy 2-ethyl-1-hexanol molecule. Relative contributions from the various internal valence coordinates to the experimental vibrational bands are directly compared between the liquid phase Raman band and the gas and liquid phase infrared band.