Nanoantennas and Nanoradars: The Future of Integrated Sensing and Communication at the Nanoscale

Nanoantennas, operating at optical frequencies, are a transformative technology with broad applications in 6G wireless communication, IoT, smart cities, healthcare, and medical imaging. This paper explores their fundamental aspects, applications, and advancements, aiming for a comprehensive understanding of their potential in various applications. It begins by investigating macroscopic and microscopic Maxwell's equations governing electromagnetic wave propagation at different scales. The study emphasizes the critical role of Surface Plasmon Polariton (SPP) wave propagation in enhancing light-matter interactions, contributing to high data rates, and enabling miniaturization. Additionally, it explores using two-dimensional materials like graphene for enhanced control in terahertz communication and sensing. The paper also introduces the employment of nanoantennas as the main building blocks of Nano-scale Radar (NR) systems for the first time in the literature. NRs, integrated with communication signals, promise accurate radar sensing for nanoparticles inside a nano-channel, making them a potential future application in integrated sensing and communication (ISAC) systems. These nano-scale radar systems detect and extract physical or electrical properties of nanoparticles through transmitting, receiving, and processing electromagnetic waves at ultra-high frequencies in the optical range. This task requires nanoantennas as transmitters/receivers/transceivers, sharing the same frequency band and hardware for high-performance sensing and resolution

The human CNOT1-CNOT10-CNOT11 complex forms a structural platform for protein-protein interactions

The evolutionary conserved CCR4-NOT complex functions in the cytoplasm as the main mRNA deadenylase in both constitutive mRNA turnover and regulated mRNA decay pathways. The versatility of this complex is underpinned by its modular multi-subunit organization, with distinct structural modules actuating different functions. The structure and function of all modules are known, except for that of the N-terminal module. Using different structural approaches, we obtained high-resolution data revealing the architecture of the human N-terminal module composed of CNOT1, CNOT10, and CNOT11. The structure shows how two helical domains of CNOT1 sandwich CNOT10 and CNOT11, leaving the most conserved domain of CNOT11 protruding into solvent as an antenna. We discovered that GGNBP2, a protein identified as a tumor suppressor and spermatogenic factor, is a conserved interacting partner of the CNOT11 antenna domain. Structural and biochemical analyses thus pinpoint the N-terminal CNOT1-CNOT10-CNOT11 module as a conserved protein-protein interaction platform

Collaborative Broadcast in O(log log n) Rounds

We consider the multihop broadcasting problem for $n$ nodes placed uniformly at random in a disk and investigate the number of hops required to transmit a signal from the central node to all other nodes under three communication models: Unit-Disk-Graph (UDG), Signal-to-Noise-Ratio (SNR), and the wave superposition model of multiple input/multiple output (MIMO). In the MIMO model, informed nodes cooperate to produce a stronger superposed signal. We do not consider the problem of transmitting a full message nor do we consider interference. In each round, the informed senders try to deliver to other nodes the required signal strength such that the received signal can be distinguished from the noise. We assume sufficiently high node density $\rho= \Omega(\log n)$. In the unit-disk graph model, broadcasting needs $O(\sqrt{n/\rho})$ rounds. In the other models, we use an Expanding Disk Broadcasting Algorithm, where in a round only triggered nodes within a certain distance from the initiator node contribute to the broadcasting operation. This algorithm achieves a broadcast in only $O(\frac{\log n}{\log \rho})$ rounds in the SNR-model. Adapted to the MIMO model, it broadcasts within $O(\log \log n - \log \log \rho)$ rounds. All bounds are asymptotically tight and hold with high probability, i.e. $1- n^{-O(1)}$.Comment: extended abstract accepted for ALGOSENSORS 201

Gravitational hedgehog, stringy hedgehog and stringy sphere

We investigate the solutions of Einstein equations such that a hedgehog solution is matched to different exterior or interior solutions via a spherical shell. In the case where both the exterior and the interior regions are hedgehog solutions or one of them is flat, the resulting spherical shell becomes a stringy shell. We also consider more general matchings and see that in this case the shell deviates from its stringy character.Comment: 11 page

A Computational Approach for Designing Tiger Corridors in India

Wildlife corridors are components of landscapes, which facilitate the movement of organisms and processes between intact habitat areas, and thus provide connectivity between the habitats within the landscapes. Corridors are thus regions within a given landscape that connect fragmented habitat patches within the landscape. The major concern of designing corridors as a conservation strategy is primarily to counter, and to the extent possible, mitigate the effects of habitat fragmentation and loss on the biodiversity of the landscape, as well as support continuance of land use for essential local and global economic activities in the region of reference. In this paper, we use game theory, graph theory, membership functions and chain code algorithm to model and design a set of wildlife corridors with tiger (Panthera tigris tigris) as the focal species. We identify the parameters which would affect the tiger population in a landscape complex and using the presence of these identified parameters construct a graph using the habitat patches supporting tiger presence in the landscape complex as vertices and the possible paths between them as edges. The passage of tigers through the possible paths have been modelled as an Assurance game, with tigers as an individual player. The game is played recursively as the tiger passes through each grid considered for the model. The iteration causes the tiger to choose the most suitable path signifying the emergence of adaptability. As a formal explanation of the game, we model this interaction of tiger with the parameters as deterministic finite automata, whose transition function is obtained by the game payoff.Comment: 12 pages, 5 figures, 6 tables, NGCT conference 201

Network 'small-world-ness': a quantitative method for determining canonical network equivalence

Background: Many technological, biological, social, and information networks fall into the broad class of 'small-world' networks: they have tightly interconnected clusters of nodes, and a shortest mean path length that is similar to a matched random graph (same number of nodes and edges). This semi-quantitative definition leads to a categorical distinction ('small/not-small') rather than a quantitative, continuous grading of networks, and can lead to uncertainty about a network's small-world status. Moreover, systems described by small-world networks are often studied using an equivalent canonical network model-the Watts-Strogatz (WS) model. However, the process of establishing an equivalent WS model is imprecise and there is a pressing need to discover ways in which this equivalence may be quantified. Methodology/Principal Findings: We defined a precise measure of 'small-world-ness' S based on the trade off between high local clustering and short path length. A network is now deemed a 'small-world' if S. 1-an assertion which may be tested statistically. We then examined the behavior of S on a large data-set of real-world systems. We found that all these systems were linked by a linear relationship between their S values and the network size n. Moreover, we show a method for assigning a unique Watts-Strogatz (WS) model to any real-world network, and show analytically that the WS models associated with our sample of networks also show linearity between S and n. Linearity between S and n is not, however, inevitable, and neither is S maximal for an arbitrary network of given size. Linearity may, however, be explained by a common limiting growth process. Conclusions/Significance: We have shown how the notion of a small-world network may be quantified. Several key properties of the metric are described and the use of WS canonical models is placed on a more secure footing

Evolution of the γ\gamma-ray strength function in neodymium isotopes

The experimental gamma-ray strength functions (gamma-SFs) of 142,144-151Nd have been studied for gamma-ray energies up to the neutron separation energy. The results represent a unique set of gamma-SFs for an isotopic chain with increasing nuclear deformation. The data reveal how the low-energy enhancement, the scissors mode and the pygmy dipole resonance evolve with nuclear deformation and mass number. The data indicate that the mechanisms behind the low-energy enhancement and the scissors mode are decoupled from each other.Comment: 14 pages and 10 figure

Control of developmentally primed erythroid genes by combinatorial co-repressor actions

How transcription factors (TFs) cooperate within large protein complexes to allow rapid modulation of gene expression during development is still largely unknown. Here we show that the key haematopoietic LIM-domain-binding protein-1 (LDB1) TF complex contains several activator and repressor components that together maintain an erythroid-specific gene expression programme primed for rapid activation until differentiation is induced. A combination of proteomics, functional genomics and in vivo studies presented here identifies known and novel co-repressors, most notably the ETO2 and IRF2BP2 proteins, involved in maintaining this primed state. The ETO2-IRF2BP2 axis, interacting with the NCOR1/SMRT co-repressor complex, suppresses the expression of the vast majority of archetypical erythroid genes and pathways until its decommissioning at the onset of terminal erythroid differentiation. Our experiments demonstrate that multimeric regulatory complexes feature a dynamic interplay between activating and repressing components that determines lineage-specific gene expression and cellular differentiation