Spending for Affordable Housing: How Lexington-Fayette Urban County, KY Compares to Similar Cities in the U.S.

Objectives: The shortage of affordable housing in Lexington-Fayette urban county has become an important policy issue. The analysis in this study is designed to find out does Lexington-Fayette Urban County do better or worse in financing affordable housing for low-income residents. Method: By comparing Lexington-Fayette Urban County with 11 similar cities in U.S., there may reveal options for the Lexington-Fayette Urban County government to improve housing supply financing assistance services, find new funding sources for affordable housing and ensure more low-income residents can find affordable housing. Key finding: Nonprofit housing operations play meaningful roles in addressing the supply of affordable housing in some cities

Non-linear signal detection for molecular communications

Molecular communications convey information via diffusion propagation. The inherent long-tail channel response causes severe inter-symbol interference, which may seriously degrade signal detection performances. Traditional linear signal detection techniques, unfortunately, require both high complexity and a high signal-to-noise (SNR) ratio to operate. In this paper, we proposed a new non-linear signal processing paradigm inspired by the biological systems that achieves low-complexity signal detection even in low SNR regimes. First, we introduce a stochastic resonance inspired non-linear filtering scheme for molecular communications, and show that it significantly improves the output SNR by transforming the noise energy into useful signals. Second, we design a novel non-coherent detector by exploiting the transient features of molecular signaling, which are independent of channel response and involves only lowcomplexity linear summation operations. Numerical simulations show that this new scheme can improve the detection performance remarkably (approx. 7dB gain), even when compared against linearly optimal coherent methods. This is one of the first attempts to demodulate molecular signals from an entirely biological point of view, and the designed non-linear noncoherent paradigm will provide significant potential to the design and future implementation of nano-systems in noisy biological environments

Evolutionary Expansion of Nematode-Specific Glycine-Rich Secreted Peptides

A genome‐wide survey across 10 species from algae Guillardia theta to mammals revealed that Caenorhabditis elegans and Caenorhabditis briggsae acquired a large number of glycine‐rich secreted peptides (GRSPs, 110 GRSPs in C. elegans and 93 in C. briggsae) during evolution in this study. Chromosomal mapping indicated that most GRSPs were clustered on their genomes [103 (93.64%) in C. elegans and 82 (88.17%) in C. briggsae]. Totally, there are 18 GRSPs cluster units in C. elegans and 13 in C. briggsae. Except for four C. elegans where GRSP clusters lacking matching clusters in C. briggsae, all other GRSP clusters had its corresponding orthologous clusters between the two nematodes. Using eight transcriptomic datasets of Affmyetrix microarray, genome‐wide association studies identified many co‐expressed GRSPs clusters after C. elegans infections. Highly homologous coding sequences and conserved exon‐intron organizations indicated that GRSP tight clusters might have originated from local DNA duplications. The conserved synteny blocks of GRSP clusters between their genomes, the co‐expressed GRSPs clusters after C. elegans infections, and a strong purifying selection of protein‐coding sequences suggested evolutionary constraint acting on C. elegans to ensure that C. elegans could rapidly launch and fulfill systematic responses against infections by co‐expression, co‐regulation, and co‐functionality of GRSP clusters

Eavesdropper localization in random walk channels

Eavesdroppers are notoriously difficult to detect and locate in traditional wireless communication systems, especially if they are silent. We show that in molecular communications, where information molecules undergo random walk propagation, eavesdropper detection and localization is possible if the eavesdropper is an absorbing receiver. This is due to the fact that the random walk process has a finite return probability and the eavesdropper is a detectable energy sink of which its location can be reverse estimated

High-dimensional metric combining for non-coherent molecular signal detection

In emerging Internet-of-Nano-Thing (IoNT), information will be embedded and conveyed in the form of molecules through complex and diffusive medias. One main challenge lies in the long-tail nature of the channel response causing inter-symbolinterference (ISI), which deteriorates the detection performance. If the channel is unknown, existing coherent schemes (e.g., the state-of-the-art maximum a posteriori, MAP) have to pursue complex channel estimation and ISI mitigation techniques, which will result in either high computational complexity, or poor estimation accuracy that will hinder the detection performance. In this paper, we develop a novel high-dimensional non-coherent detection scheme for molecular signals. We achieve this in a higher-dimensional metric space by combining different noncoherent metrics that exploit the transient features of the signals. By deducing the theoretical bit error rate (BER) for any constructed high-dimensional non-coherent metric, we prove that, higher dimensionality always achieves a lower BER in the same sample space, at the expense of higher complexity on computing the multivariate posterior densities. The realization of this high-dimensional non-coherent scheme is resorting to the Parzen window technique based probabilistic neural network (Parzen-PNN), given its ability to approximate the multivariate posterior densities by taking the previous detection results into a channel-independent Gaussian Parzen window, thereby avoiding the complex channel estimations. The complexity of the posterior computation is shared by the parallel implementation of the Parzen-PNN. Numerical simulations demonstrate that our proposed scheme can gain 10dB in SNR given a fixed BER as 10-4, in comparison with other state-of-the-art methods

Bacterial relay for energy efficient molecular communications

In multi-cellular organisms, molecular signaling spans multiple distance scales and is essential to tissue structure and functionality. Molecular communications is increasingly researched and developed as a key subsystem in the Internet-of-Nano-Things paradigm. While short range microscopic diffusion communications is well understood, longer range channels can be inefficient and unreliable. Static and mobile relays have been proposed in both conventional wireless systems and molecular communication contexts. In this paper, our main contribution is to analyze the information delivery energy efficiency of bacteria mobile relays. We discover that these mobile relays offer superior energy efficiency compared with pure diffusion information transfer over long diffusion distances. This paper has widespread implications ranging from understanding biological processes to designing new efficient synthetic biology communication systems

Local convexity inspired low-complexity non-coherent signal detector for nano-scale molecular communications

Molecular communications via diffusion (MCvD) represents a relatively new area of wireless data transfer with especially attractive characteristics for nanoscale applications. Due to the nature of diffusive propagation, one of the key challenges is to mitigate inter-symbol interference (ISI) that results from the long tail of channel response. Traditional coherent detectors rely on accurate channel estimations and incur a high computational complexity. Both of these constraints make coherent detection unrealistic for MCvD systems. In this paper, we propose a low-complexity and noncoherent signal detector, which exploits essentially the local convexity of the diffusive channel response. A threshold estimation mechanism is proposed to detect signals blindly, which can also adapt to channel variations. Compared to other noncoherent detectors, the proposed algorithm is capable of operating at high data rates and suppressing ISI from a large number of previous symbols. Numerical results demonstrate that not only is the ISI effectively suppressed, but the complexity is also reduced by only requiring summation operations. As a result, the proposed noncoherent scheme will provide the necessary potential to low-complexity molecular communications, especially for nanoscale applications with a limited computation and energy budget