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The book provides practitioners and researchers with a complete overview of the latest and most important non-invasive and non-destructive techniques for inspecting structures and bodies by using microwaves.

Quantitative inversion of GPR data opens the door to precise characterization of underground environments. However, in order to make the inverse scattering problem solution easier from a computational viewpoint, simplifying assumptions are often applied, i.e., two-dimensional approximations or the consideration of idealized field probes and electromagnetic sources. These assumptions usually produce modeling errors, which can degrade the dielectric reconstruction results considerably. In this article, a processing step based on long short-term memory cells is proposed for the first time to correct the modeling error in a multiantenna GPR setting. In particular, time-domain GPR data are fed into a neural network trained with couples of finite-difference time-domain simulations, where a set of sample targets are simulated in both realistic and idealized configurations. Once trained, the neural network outputs an approximation of multiantenna GPR data as they are collected by an ideal two-dimensional measurement setup. The inversion of the processed data is then accomplished by means of a regularizing Newton-based nonlinear scheme with variable exponent Lebesgue space formulation. A numerical study has been conducted to assess the capabilities of the proposed inversion methodology. The results indicate the possibility of effectively compensating for modeling error in the considered test cases.

The imaging of dielectric targets hidden behind a wall is addressed in this paper. An analytical solver for a fast and accurate computation of the forward scattered field by the targets is proposed, which takes into account all the interactions of the electromagnetic field with the interfaces of the wall. Furthermore, an inversion procedure able to address the full underlying non-linear inverse scattering problem is introduced. This technique exploits a regularizing scheme in Lebesgue spaces in order to reconstruct an image of the hidden targets. Preliminary numerical results are provided in order to initially assess the capabilities of the developed solvers.

A microwave characterization technique to inspect subsurface scenarios is proposed and numerically assessed in this paper. The approach is based on a combination of finite element electromagnetic modeling and an inversion procedure in Lebesgue spaces with variable exponents. The former allows for description of the measurement system and subsurface scenario with high accuracy, while the latter exploits the adaptive definition of exponent function to achieve improved results in the regularized solution of the inverse scattering problem. The method has been assessed with numerical simulations regarding two-layered environments with both planar and non-planar air–soil interfaces. The results show the capabilities of the method of detecting buried objects in different operative conditions.

There is growing interest in alternative protein sources to promote a more circular economy within agri-food systems. This study evaluated the impact of replacing 7% of poultry meal (PM) with hydrolysed feather meal (HFM) in canine diet on faecal characteristics. Six adult female English Setter dogs, matched for age, body weight, and body condition score (BCS), were divided into two groups and tested with two diets (PM vs. HFM) in a cross-over design. The study included a 7-d adaptation period, followed by a 45-d total faecal collection. A 30-d washout period was used. Digestive fermentation by-products were analysed by using gas and liquid chromatography. Data were analysed using a generalised linear mixed model (GLMM), with diet, time and their interaction as fixed effects, and the experimental phase as a random effect. Faecal scores for both groups remained within the range of 2–3, which is considered ‘ideal’. Dogs fed the HFM diet showed significantly higher (p < 0.001) faecal concentrations of acetate and isobutyrate, and significantly lower (p < 0.01) levels of propionate and butyrate compared to the PM diet. Furthermore, dogs fed HFM diet exhibited significantly increased (p < 0.001) concentrations of putrescine and cadaverine and significantly decreased (p < 0.001) levels of spermine. The profile of short-chain fatty acids (SCFAs) and biogenic amines differed from that those reported in dogs with inflammatory enteropathies, confirming the maintenance of gastrointestinal health throughout the study. These results suggest that HFM is a promising alternative protein source for dog food formulations, contributing to the sustainable utilisation of animal by-products.

Swarm intelligence denotes a class of new stochastic algorithms inspired by the collective social behavior of natural entities (e.g., birds, ants, etc.). Such approaches have been proven to be quite effective in several applicative fields, ranging from intelligent routing to image processing. In the last years, they have also been successfully applied in electromagnetics, especially for antenna synthesis, component design, and microwave imaging. In this paper, the application of swarm optimization methods to microwave imaging is discussed, and some recent imaging approaches based on such methods are critically reviewed.

Two extruded diets isoenergetic, isonitrogenous, and isolipidic were formulated with poultry meal (control diet) as the source of animal-origin proteins (160 g/kg of feed) or with 90 g/kg of poultry meal and 70 g/kg of hydrolyzed feather meal (treated diet) and were fed to eight dogs (four adult female and four adult male English Setters). Body condition, muscle condition, and fecal consistency scores and body weight were monitored at the beginning of the trial and after 3, 7, 15, and 45 days, and no significant differences (p > 0.05) were observed between diets and between sex. Fecal samples, collected at the same time points, were analyzed for microbiota composition. No significant difference was calculated for the alpha diversity index between control diet and treated diet, nor for the diets × times of sampling interaction and for sex. Beta diversity was different (p-value 0.001) between the control and treated groups. The beta diversity between sexes was significantly different (p-value = 0.047). Linear Discriminant analysis effect size analysis revealed significant differences between dietary groups, identifying Clostridiales, Coprococcus, Bacteroides plebeius, Eubacterium biforme, Catenibacterium, and Prevotella copri as more abundant in the CTR diet, while Fusobacterium, Bacteroides, Fusobacteriaceae, Paraprevotellaceae, Enterococcus, Faecalibacterium, Enterobacteriaceae, Peptostreptococcaceae, and Clostridium spiroforme were more abundant in the treated diet. Sex differences were also significant, with 25 taxa differing between male and female dogs. Overall, the study underscores the impact of HFM and sex on gut microbiota composition in dogs, with potential implications for dietary interventions and microbiome research.

A hybrid inversion scheme for through-the-wall imaging is proposed in this paper. The approach is based on a linearized model of the inverse-scattering problem, employing the Green’s function developed for a layered background. The reconstruction is obtained by means of a Landweber-like iterative method performing a regularization in the framework of variable-exponent Lebesgue spaces. Thanks to the non-conventional geometrical properties of such spaces, it is possible to enhance the reconstruction capabilities, e.g., by promoting sparseness and reducing over-smoothing. The exponent function defining the specific space adopted in the inversion procedure is adaptively obtained directly from the measured data, through a truncated-singular value decomposition method. In this way, it is possible to precompute and reuse in both steps, for a given scenario, all the matrices necessary in the inversion process, thus leading to a computationally efficient solving strategy. The effectiveness of the approach is evaluated by using experimental data obtained with a commercial GPR apparatus employing a pulsed source field. A fast Fourier transform is applied to the time-domain measurements to extract frequency-domain data at a set of frequencies in the source spectrum, which are fed in input to the imaging scheme. Very good reconstruction capabilities are obtained both with a single metallic target, as well as in a challenging two targets layout including both a metallic object and a low-permittivity target.

The subject of this paper is the possible use of a network of microwave sensors to achieve a map of the electromagnetic properties of unknown targets. The basic idea is to use a set of microwave sensors to illuminate a region of interest and to measure the resulting axial component of the electric field. Measurements are then processed by means of a technique based on inverse-scattering, which provides an estimate map of the dielectric values of the area under examination, allowing to discriminate among possible targets. In order to initially evaluate the feasibility of the proposed approach, numerical results in a simulated environment are preliminarily considered and discussed. Furthermore, an initial test on experimental data in a simplified configuration is also presented.

The nondestructive characterization of cylindrical objects is needed in many fields, such as medical diagnostics, tree trunk inspection, or concrete column testing. In this study, the radar equation of Lambot et al. is combined with cylindrical Green’s functions to fully model and invert ultra-wideband (UWB) ground-penetrating radar (GPR) data and retrieve the properties of cylindrical objects. Inversion is carried out using a lookup table (LUT) approach followed by local optimization to ensure retrieval of the global minimum of the objective function. Numerical experiments were conducted to analyze the capabilities of the developed inversion procedure to estimate the radius, permittivity, and conductivity of the cylinders. The full-wave model was validated in laboratory conditions on metallic and plastic pipes of different sizes. The adopted radar system consists of a lightweight vector network analyzer (VNA) connected to a single transmitting and receiving horn antenna. The numerical experiments highlighted the complexity of the inverse problem, mainly originating from the multiple propagation modes within cylindrical objects. The laboratory measurements demonstrated the accuracy of the forward modeling and reconstructions in far-field conditions.