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In many multiple-input multiple-output (MIMO) communication applications, two-dimensional (2D) rectangular arrays are used and the angular field of interest is different in the azimuth and elevation angle domains. In this paper, we show how to exploit scenarios with users confined to narrow elevation angles by means of 2D rectangular arrays with low-resolution spatial Σ∆ sampling in only one (i.e., the vertical) dimension. We analyze the 2D directions-of-arrival (DoA) estimation performance of MUSIC for such arrays, and illustrate the resulting advantage of the Σ∆ approach over standard one-bit receivers. 

Recent years have seen a growing number of examples of designed oligomeric molecules with artificial backbone connectivity that are capable of adopting complex folded tertiary structures analogous to those seen in natural proteins. A range of experimental techniques from structural biology and biophysics have been brought to bear in the study of these proteomimetic agents. Here, we discuss some considerations encountered in the characterization of high-resolution folded structure as well as folding thermodynamics of protein-like artificial backbones. We provide an overview of the use of X-ray crystallography and NMR spectroscopy in such systems and review example applications of these methods in the primary literature. Further, we provide detailed protocols for two experiments that have proved useful in our prior and ongoing efforts to compare folding thermodynamics between natural protein domains and heterogeneous-backbone counterparts. 

Spatial ΣΔ sampling has recently been proposed to improve the performance of massive MIMO systems with low-resolution quantization for cases where the users are confined to a certain angular sector, or the array is spatially oversampled. We derive a linear minimum mean squared error (LMMSE) channel estimator for the ΣΔ array based on an element-wise Bussgang decomposition that reformulates the nonlinear quantizer operation using an equivalent linear model plus quantization noise. Both the case of one- and two-bit quantization is considered. We then evaluate the achievable rate of the ΣΔ system assuming that a linear receiver based on the LMMSE channel estimate is used to decode the data. Our numerical results demonstrate that ΣΔ architecture is able to achieve superior channel estimates and sum spectral efficiency compared to conventional low-resolution quantized massive MIMO systems. 

We consider channel estimation for an uplink massive multiple input multiple output (MIMO) system where the base station (BS) uses a first-order spatial Sigma-Delta (Σ△) analog-to-digital converter (ADC) array. The Σ△ array consists of closely spaced sensors which oversample the received signal and provide a coarsely quantized (1-bit) output. We develop a linear minimum mean squared error (LMMSE) estimator based on the Bussgang decomposition that reformulates the nonlinear quantizer model using an equivalent linear model plus quantization noise. The performance of the proposed Σ△ LMMSE estimator is compared via simulation to channel estimation using standard 1-bit quantization and also infinite resolution ADCs. 

Abstract This work presents new results and summarizes literature results on the chiral induced spin selectivity (CISS) effect observed for amino acids, peptides, and DNA. To facilitate robust comparisons between measurements of different types and by different groups, we propose a convention for describing the spin‐dependent properties of chiral materials and apply it in the discussion. Different phenomena known to affect the sign and magnitude of the spin polarization are described and critically analyzed, including: the molecule's orientation, the molecule's dipole moment direction with respect to the electron propagation direction, the molecular length, the molecule/substrate interface, and the role of the molecule's secondary structure. Lastly, we identify open key questions about spin‐filtering by biomolecules at interfaces.