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

An investigation into modeling and simulation approaches for sustainable operations management

Modeling and simulation (M&S) studies have been widely used in industry to gain insights into existing or proposed systems of interest. The majority of these studies focus on productivity-related measures to evaluate systems' performance. This paradigm, however, needs to be shifted to cope with the advent of sustainability, as it is increasingly becoming an important issue in the managerial and the organizational agendas. The application of M&S to evaluate the often-competing metrics associated with sustainable operations management (SOM) is likely to be a challenge. The aim of this review is to investigate the underlying characteristics of SOM that lend towards modeling of production and service systems, and further to present an informed discussion on the suitability of specific modeling techniques in meeting the competing metrics for SOM. The triple bottom line, which is a widely used concept in sustainability and includes environmental, social, and economic aspects, is used as a benchmark for assessing this. Findings from our research suggest that a hybrid (combined) M&S approach could be an appropriate method for SOM analysis; however, it has its challenges.This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors

Modelling for sustainable development using the triple-bottom line: Methods, challenges and the need for hybrid M&S

This is the author accepted manuscript, the final version is available from IEEE via the DOI in this record.The concept of sustainable development (SDEV) is a topic of increasing significance in management decision making. SDEV is managed based on the triple-bottom line approach which stresses the importance of achieving a balance between economic, environmental and social impacts. In the context of management decision making, this implies that operational and strategic decisions in an organization must not be limited to the fulfillment of KPIs associated with productivity alone, but should also include metrics that are associated with the environment and society. Modeling & simulation (M&S) lends itself towards evaluation of the three, often competing, metrics. There are several M&S approaches like Discrete-event and System Dynamics; which of the existing techniques is the choice for modelling SDEV? Or, is a combined hybrid approach a better solution? The tutorial explores such questions related to the methodological aspects of M&S for SDEV analysis, and discusses the challenges for modeling such complex systems

Disruptive Technologies in Agricultural Operations: A Systematic Review of AI-driven AgriTech Research

YesThe evolving field of disruptive technologies has recently gained significant interest in various industries, including agriculture. The fourth industrial revolution has reshaped the context of Agricultural Technology (AgriTech) with applications of Artificial Intelligence (AI) and a strong focus on data-driven analytical techniques. Motivated by the advances in AgriTech for agrarian operations, the study presents a state-of-the-art review of the research advances which are, evolving in a fast pace over the last decades (due to the disruptive potential of the technological context). Following a systematic literature approach, we develop a categorisation of the various types of AgriTech, as well as the associated AI-driven techniques which form the continuously shifting definition of AgriTech. The contribution primarily draws on the conceptualisation and awareness about AI-driven AgriTech context relevant to the agricultural operations for smart, efficient, and sustainable farming. The study provides a single normative reference for the definition, context and future directions of the field for further research towards the operational context of AgriTech. Our findings indicate that AgriTech research and the disruptive potential of AI in the agricultural sector are still in infancy in Operations Research. Through the systematic review, we also intend to inform a wide range of agricultural stakeholders (farmers, agripreneurs, scholars and practitioners) and to provide research agenda for a growing field with multiple potentialities for the future of the agricultural operations

The Influence of the Degree of Heterogeneity on the Elastic Properties of Random Sphere Packings

The macroscopic mechanical properties of colloidal particle gels strongly depend on the local arrangement of the powder particles. Experiments have shown that more heterogeneous microstructures exhibit up to one order of magnitude higher elastic properties than their more homogeneous counterparts at equal volume fraction. In this paper, packings of spherical particles are used as model structures to computationally investigate the elastic properties of coagulated particle gels as a function of their degree of heterogeneity. The discrete element model comprises a linear elastic contact law, particle bonding and damping. The simulation parameters were calibrated using a homogeneous and a heterogeneous microstructure originating from earlier Brownian dynamics simulations. A systematic study of the elastic properties as a function of the degree of heterogeneity was performed using two sets of microstructures obtained from Brownian dynamics simulation and from the void expansion method. Both sets cover a broad and to a large extent overlapping range of degrees of heterogeneity. The simulations have shown that the elastic properties as a function of the degree of heterogeneity are independent of the structure generation algorithm and that the relation between the shear modulus and the degree of heterogeneity can be well described by a power law. This suggests the presence of a critical degree of heterogeneity and, therefore, a phase transition between a phase with finite and one with zero elastic properties.Comment: 8 pages, 6 figures; Granular Matter (published online: 11. February 2012

Corneal Biomechanical Properties in Varying Severities of Myopia

Purpose: To investigate corneal biomechanical response parameters in varying degrees of myopia and their correlation with corneal geometrical parameters and axial length. Methods: In this prospective cross-sectional study, 172 eyes of 172 subjects, the severity degree of myopia was categorized into mild, moderate, severe, and extreme myopia. Cycloplegic refraction, corneal tomography using Pentacam HR, corneal biomechanical assessment using Corvis ST and Ocular Response Analyser (ORA), and ocular biometry using IOLMaster 700 were performed for all subjects. A general linear model was used to compare biomechanical parameters in various degrees of myopia, while central corneal thickness (CCT) and biomechanically corrected intraocular pressure (bIOP) were considered as covariates. Multiple linear regression was used to investigate the relationship between corneal biomechanical parameters with spherical equivalent (SE), axial length (AXL), bIOP, mean keratometry (Mean KR), and CCT. Results: Corneal biomechanical parameters assessed by Corvis ST that showed significant differences among the groups were second applanation length (AL2, p = 0.035), highest concavity radius (HCR, p < 0.001), deformation amplitude (DA, p < 0.001), peak distance (PD, p = 0.022), integrated inverse radius (IR, p < 0.001) and DA ratio (DAR, p = 0.004), while there were no significant differences in the means of pressure-derived parameters of ORA between groups. Multiple regression analysis showed all parameters of Corvis ST have significant relationships with level of myopia (SE, AXL, Mean KR), except AL1 and AL2. Significant biomechanical parameters showed progressive reduction in corneal stiffness with increasing myopia (either with greater negative SE or greater AXL), independent of IOP and CCT. Also, corneal hysteresis (CH) or ability to dissipate energy from the ORA decreased with increasing level of myopia. Conclusions: Dynamic corneal response assessed by Corvis ST shows evidence of biomechanical changes consistent with decreasing stiffness with increasing levels of myopia in multiple parameters. The strongest correlations were with highest concavity parameters where the sclera influence is maximal. © Copyright © 2021 Sedaghat, Momeni-Moghaddam, Azimi, Fakhimi, Ziaei, Danesh, Roberts, Monfared and Jamali

Sensing, measuring and modelling the mechanical properties of sandstone

We present a hybrid framework for simulating the strength and dilation characteristics of sandstone. Where possible, the grain-scale properties of sandstone are evaluated experimentally in detail. Also, using photo-stress analysis, we sense the deviator stress (/strain) distribution at the microscale and its components along the orthogonal directions on the surface of a V-notch sandstone sample under mechanical loading. Based on this measurement and applying a grain-scale model, the optical anisotropy index K0 is inferred at the grain scale. This correlated well with the grain contact stiffness ratio K evaluated using ultrasound sensors independently. Thereafter, in addition to other experimentally characterised structural and grain-scale properties of sandstone, K is fed as an input into the discrete element modelling of fracture strength and dilation of the sandstone samples. Physical bulk scale experiments are also conducted to evaluate the load-displacement relation, dilation and bulk fracture strength characteristics of sandstone samples under compression and shear. A good level of agreement is obtained between the results of the simulations and experiments. The current generic framework could be applied to understand the internal and bulk mechanical properties of such complex opaque and heterogeneous materials more realistically in future

Application of operations research within the UK healthcare context

Operations Research (OR) techniques enable decision makers and stakeholders to analyse and evaluate strategies for effective operations management of sophisticated systems. Healthcare systems are an example of such complex systems, and therefore it comes as no surprise that an increasing number of healthcare-focussed OR studies have been reported in literature over the years. Although several studies have profiled literature in healthcare modelling and simulation (Katsaliaki and Mustafee, 2011; Brailsford et al., 2009; Jun et al., 1999), there is currently no study that has methodologically reviewed the application of OR in healthcare. The objective of this paper, therefore, is to synthesise extant literature in healthcare OR by classifying papers based on OR technique, application category, healthcare speciality, among others. The scope of this review paper is limited to OR studies undertaken in the UK. One interesting finding of this study is that the application of OR in the UK healthcare system does not cover a wide range of OR techniques and methods; from among 70 papers that are included in this review, about 80% discuss simulation techniques. Our review also reveals that approx. 37% of the studies have employed multiple OR techniques for realising the stated objectives and that simulation is one of the methods included in these studies