GPR prospecting in a layered medium via microwave tomography

The tomographic approach appears to be a promising way to elaborate Ground Penetrating Radar (GPR) data in order to achieve quantitative information on the tested regions. In this paper, we apply a linearized tomographic approach to the reconstruction of dielectric objects embedded in a layered medium. The problem is tackled with reference to a two-dimensional geometry and scalar case when data are collected over a linear domain with finite extent. In particular, in order to increase the amount of independent available data, a multi-frequency/multi-view/ multi-static measurement configuration is considered. With reference to stepped-frequency radar, this means that for each working frequency and for each position of the transmitting antenna (moved along a linear domain), the electric field scattered by the buried targets is measured in several locations along the same linear domain. The proposed inversion approach is based on the Born approximation and a regularized solution is introduced by means of the Singular Value Decomposition (SVD). The problem of determining the optimal measurement configuration (in terms of number of frequencies and number of transmitting and receiving antennas) is also tackled by a numerical analysis relying on the Singular Value Decomposition (SVD). Numerical examples are provided to assess the effectiveness and robustness of the proposed approach against noise on data

Microwave Tomography for Food Contamination Monitoring

The security of packaged food needs to be guaranteed to safeguard customers health. A raise of complaints of physical contaminations into food products pushes for the development of additional monitoring techniques to prevent any kind of hazards, but also to protect brands from customers trust loss. In this work, a prototype working at microwave frequencies is assessed and tested in a significant environment. It exploits the dielectric contrast between contaminants and food content, and it is it is mainly focused on two classes of intrusions matters, i.e. plastic and glass fragments of few mm size, that have limited detection by the existing in-line technologies, such as X-rays systems. The measurements and the resulting 3-D image reconstructions are encouraging and allow to aim at the development of an industrial prototype, monitoring packaged food in real-time along a production line

Electromagnetic imaging and sensing for food quality and safety assessment [Guest Editorial]

The six articles in this special present to the antennas and propagation community some of the emerging research activities on the application of EM-based technologies in such a societally relevant topic. The articles address food industry applications as different as sensing food quality and food spoilage indicators and monitoring food items to detect contaminants

A Microwave Imaging Device for Detecting Contaminants in Water-based Food Products

Food and beverage industries are paying an increasing attention to the development of new technologies for non-invasive assessment of food products. In particular, there is a need of deploying tools to detect low-density plastic, rubber, wood and glass that are unlikely to be detected by X-Rays, currently used in the most powerful commercial systems. To this end, we propose a microwave-based device, exploiting the dielectric contrast between potential intrusions (e.g., plastic fragments) and the surrounding medium, represented by the food/beverage product. In particular, this work aims to numerically assess this principle of detection to water-based products that are, due to the medium losses, a challenging category at microwaves. An antennas array surrounds the object moving along the production line, to monitor the electromagnetic signal variations with respect to a reference case. The working frequency is chosen by selecting a proper trade-off between penetration depth and image resolution. Then, a procedure, based on the application of the distorted-Born approximation is applied to reconstruct a 3-D image of the contaminant position. Finally, the successful detection of a millimetric-sized plastic sphere is presented in the case of a common commercial bottle filled with water

Experimental Validation of a 3D Microwave Imaging Device for Brain Stroke Monitoring

In this work we present the experimental validation of a 3D microwave imaging device to brain observation. The device is conceived as a way to monitor stroke development, supporting physicians in the follow-up of patients in the aftermath of cerebrovascular accidents, and giving to them extra information for decision-making and application of therapies. The device acquires data through antennas placed around the patient head, in a low-complexity system that guarantees that available information is enough for reliable outcome. Experimental testing is performed on a 3-D human-like head phantom with promising results

Comparison of Reconstruction Algorithms for Brain Stroke Microwave Imaging

The aim of this paper is to describe and compare the performances of three image reconstruction algorithms that can be used for brain stroke microwave imaging. The algorithms belong to the class of non-linear iterative algorithms and are capable of providing a quantitative map of the imaged scenario. The first algorithm is the Contrast Source Inversion (CSI) method, which uses the Finite Element Method (FEM) to discretize the domain of interest. The second one is the Subspace-Based Optimization Method (SOM) that has some properties in common with the CSI method, and it also uses FEM to discretize the domain. The last one is the Distorted Born Iterative Method with the inverse solver Two-step Iterative Shrinkage/Thresholding (DBIM-TwIST), which exploits the forward Finite Difference Time Domain (FDTD) solver. The reconstruction examples are created with 3-D synthetic data modelling realistic brain tissues with the presence of a blood region, representing the stroke area in the brain, whereas the inversion step is carried out using a 2-D model

Assessing a Microwave Imaging System for Brain Stroke Monitoring via High Fidelity Numerical Modelling

This work presents the outcomes of a numerical analysis based on a 3-D high fidelity model of a realistic microwave imaging system for the clinical follow-up of brain stroke. The analysis is meant as a preliminary step towards the full experimental characterization of the system, with the aim of assessing the achievable results and highlight possible critical points. The system consists of an array of twenty-four printed monopole antennas, placed conformal to the upper part of the head; each monopole is immersed into a semi-solid dielectric brick with custom permittivity, acting as coupling medium. The whole system, including the antennas and their feeding mechanism, has been numerically modeled via a custom full-wave software based on the finite element method. The numerical model generates reliable electromagnetic operators and accurate antenna scattering parameters, which provide the input data for the implemented imaging algorithm. In particular, the numerical analysis assesses the capability of the device of reliably monitoring the evolution of hemorrhages and ischemias, considering the progression from a healthy statet o an early-stage stroke

IP6K3 and IPMK variations in LOAD and longevity: evidence for a multifaceted signaling network at the crossroad between neurodegeneration and survival

Several studies reported that genetic variants predisposing to neurodegeneration were at higher frequencies in centenarians than in younger controls, suggesting they might favor also longevity. IP6K3 and IPMK regulate many crucial biological functions by mediating synthesis of inositol poly- and pyrophosphates and by acting non-enzymatically via protein–protein interactions. Our previous studies suggested they affect Late Onset Alzheimer Disease (LOAD) and longevity, respectively. Here, in the same sample groups, we investigated whether variants of IP6K3 also affect longevity, and variants of IPMK also influence LOAD susceptibility. We found that: i) a SNP of IP6K3 previously associated with increased risk of LOAD increased the chance to become long-lived, ii) SNPs of IPMK, previously associated with decreased longevity, were protective factors for LOAD, as previously observed for UCP4. SNP-SNP interaction analysis, including our previous data, highlighted phenotype-specific interactions between sets of alleles. Moreover, linkage disequilibrium and eQTL data associated to analyzed variants suggested mitochondria as crossroad of interconnected pathways crucial for susceptibility to neurodegeneration and/or longevity. Overall, data support the view that in these traits interactions may be more important than single polymorphisms. This phenomenon may contribute to the non-additive heritability of neurodegeneration and longevity and be part of the missing heritability of these traits