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Modern computer technology has opened up new opportunities for the development of digital signal processing methods. The applications of digital signal processing have expanded significantly and today include audio and speech processing, sonar, radar, and other sensor array processing, spectral density estimation, statistical signal processing, digital image processing, signal processing for telecommunications, control systems, biomedical engineering, and seismology, among others. This Special Issue is aimed at wide coverage of the problems of digital signal processing, from mathematical modeling to the implementation of problem-oriented systems. The basis of digital signal processing is digital filtering. Wavelet analysis implements multiscale signal processing and is used to solve applied problems of de-noising and compression. Processing of visual information, including image and video processing and pattern recognition, is actively used in robotic systems and industrial processes control today. Improving digital signal processing circuits and developing new signal processing systems can improve the technical characteristics of many digital devices. The development of new methods of artificial intelligence, including artificial neural networks and brain-computer interfaces, opens up new prospects for the creation of smart technology. This Special Issue contains the latest technological developments in mathematics and digital signal processing. The stated results are of interest to researchers in the field of applied mathematics and developers of modern digital signal processing systems.

digital filter --- finite field algebra --- conversion device --- module --- memory device --- residue --- feedback regulation --- digital signal analysis --- control efficacy --- residue number system --- redundant residue number system --- modular division --- fraction --- algorithm --- mathematical models of digital signal processing --- digital filtering --- maximum correntropy --- impulsive noise --- sparse channel estimation --- discrete wavelet transform --- medical imaging --- 3D image processing --- quantization noise --- harmonic wavelets --- classification --- kNN-algorithm --- deep neural networks --- machine learning --- Fourier transform --- short-time Fourier transform --- wavelet transform --- spectrogram --- confusion matrix --- ROC curve --- 3D model --- prosthetic design --- orientation --- positioning --- reconstruction --- speech enhancement --- adaptive filter --- microphone array --- sub-band processing --- filter bank --- posture classification --- skeleton detection --- motion capture --- exercise classification --- virtual rehabilitation --- wood defect --- CNN --- ELM --- genetic algorithm --- detection

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In the first contribution, Morbiducci and co-workers discuss the theoretical and methodological bases supporting the Lagrangian- and Euler-based methods, highlighting their application to cardiovascular flows. The second contribution, by the Ansón and van Lenthe groups, proposes an automated virtual bench test for evaluating the stability of custom shoulder implants without the necessity of mechanical testing. Urdeitx and Doweidar, in the third paper, also adopt the finite element method for developing a computational model aim to study cardiac cell behavior under mechano-electric stimulation. In the fourth contribution, Ayensa-Jiménez et al. develop a methodology to approximate the multidimensional probability density function of the parametric analysis obtained developing a mathematical model of the cancer evolution. The fifth paper is oriented to the topological data analysis; the group of Cueto and Chinesta designs a predictive model capable of estimating the state of drivers using the data collected from motion sensors. In the sixth contribution, the Ohayon and Finet group uses wall shear stress-derived descriptors to study the role of recirculation in the arterial restenosis due to different malapposed and overlapping stent conditions. In the seventh contribution, the research group of Antón demonstrates that the simulation time can be reduced for cardiovascular numerical analysis considering an adequate geometry-reduction strategy applicable to truncated patient specific artery. In the eighth paper, Grasa and Calvo present a numerical model based on the finite element method for simulating extraocular muscle dynamics. The ninth paper, authored by Kahla et al., presents a mathematical mechano-pharmaco-biological model for bone remodeling. Martínez, Peña, and co-workers propose in the tenth paper a methodology to calibrate the dissection properties of aorta layer, with the aim of providing useful information for reliable numerical tools. In the eleventh contribution, Martínez-Bocanegra et al. present the structural behavior of a foot model using a detailed finite element model. The twelfth contribution is centered on the methodology to perform a finite, element-based, numerical model of a hydroxyapatite 3D printed bone scaffold. In the thirteenth paper, Talygin and Gorodkov present analytical expressions describing swirling jets for cardiovascular applications. In the fourteenth contribution, Schenkel and Halliday propose a novel non-Newtonian particle transport model for red blood cells. Finally, Zurita et al. propose a parametric numerical tool for analyzing a silicone customized 3D printable trachea-bronchial prosthesis.

finite element analysis --- shoulder implant stability --- implant design --- reverse shoulder arthroplasty --- micromotion --- in-silico --- 3D model --- cardiac cell --- cardiac muscle tissue --- cardiomyocyte --- electrical stimulation --- copulas --- design of experiments --- glioblastoma multiforme --- mathematical modelling --- Morse theory --- topological data analysis --- machine learning --- time series --- smart driving --- fixed points --- manifolds --- divergence --- hemodynamics --- computational fluid dynamics --- overlap --- malapposition --- stent --- stenosis --- thrombosis --- radioembolization --- liver cancer --- hepatic artery --- computational cost analysis --- personalized medicine --- patient specific --- finite element method --- implicit FEM --- explicit FEM --- skeletal muscle --- biomechanics --- mathematical model --- cell dynamics --- bone physiology --- bone disorders --- aortic dissection --- delamination tests --- cohesive zone model --- porcine aorta --- vascular mechanics --- foot finite element method --- foot and ankle model --- shared nodes --- separated mesh --- plantar pressure --- finite element modelling --- bone tissue engineering --- 3D scaffold --- additive manufacturing --- potential swirling flow --- Navier–Stokes equations --- unsteady swirling flow --- tornado-like jets --- haemorheology --- blood flow modelling --- particle transport --- numerical fluid mechanics --- tracheobronchial stent --- parametric model --- 3D printing --- customized prosthesis

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In the last few centuries, the study of sea-level changes along the world's shores has been a primary scientific focus in analyses of climate change, but also for scientists exploring past landscape evolution, geomorphological processes, human impacts, and system responses. The relative variation in sea level derives as a result of global, regional, and local processes. All these processes are spatially and temporally variable and cause complex sea-level changes at both regional and local scales. A multidisciplinary approach addressed to palaeo sea-level reconstructions at regional and local scale is the best method to understand the role of natural and anthropogenic forcing in the landscape evolution, as well as to discover the historical human adaptions to natural modifications of the landscape. Definitely, investigating these regional and local patterns is mandatory to reconstruct possible scenarios of the relative sea level rise impacts and to prepare the adaptation of coastal communities threatened by future climate changes. The aim of this Special Issue has been to collect contributions addressing and discussing methodological and multi-disciplinary approaches to studying the regional and local coastal modifications in relation to historical and recent relative sea-level changes to hypothesize future trends.

sea-level rise --- Mediterranean Sea --- tide gauges --- natural variability --- vertical land motion --- Mississippi River Delta --- Louisiana --- salinity --- sediment --- wetland loss --- estuary --- diversion --- environmental planning --- coastal restoration --- sea level --- coastal erosion --- coastal morphometry --- Baltic Sea --- coastal changes --- vertical ground movements --- geoarchaeology --- 3D model --- relative sea level changes --- Campi Flegrei --- Holocene --- coastal lagoon --- geochronology --- sea level change --- bio-indicators --- climate change --- adaptation costs --- investment decision --- Spain and Portugal coastal cities --- uncertainty --- stochastic model --- coastal dynamics --- erosion --- accretion --- submersion --- boulders --- Medicane --- flow --- UAV --- waves --- coastal barrier --- continuous backstepping pattern --- incised valley --- sapropel S1 --- coastal plains --- relative sea-level rise --- 2100 --- marine submersion --- tide-gauges --- atmospheric variability --- Tyrrhenian sea --- interannual variations --- acqua alta --- well log correlation --- late Quaternary environments --- sea-level changes --- Volturno plain --- southern Italy --- geomorphological coastal changes --- sea storm effects --- integrated 3D remote sensing surveys --- sedimentary dynamics --- western Ligurian sea --- n/a

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Remote image capture systems are a key element in efficient and sustainable agriculture nowadays. They are increasingly being used to obtain information of interest from the crops, the soil and the environment. It includes different types of capturing devices: from satellites and drones, to in-field devices; different types of spectral information, from visible RGB images, to multispectral images; different types of applications; and different types of techniques in the areas of image processing, computer vision, pattern recognition and machine learning. This book covers all these aspects, through a series of chapters that describe specific recent applications of these techniques in interesting problems of agricultural engineering.

SVM --- budding rate --- UAV --- geometric consistency --- radiometric consistency --- point clouds --- ICP --- reflectance maps --- vegetation indices --- Parrot Sequoia --- artificial intelligence --- precision agriculture --- agricultural robot --- optimization algorithm --- online operation --- segmentation --- coffee leaf rust --- machine learning --- deep learning --- remote sensing --- Fourth Industrial Revolution --- Agriculture 4.0 --- failure strain --- sandstone --- digital image correlation --- Hill–Tsai failure criterion --- finite element method --- reference evapotranspiration --- moisture sensors --- machine learning regression --- frequency-domain reflectometry --- randomizable filtered classifier --- convolutional neural network --- U-Net --- land use --- banana plantation --- Panama TR4 --- aerial photography --- remote images --- systematic mapping study --- agriculture --- applications --- total leaf area --- mixed pixels --- Cabernet Sauvignon --- NDVI --- Normalized Difference Vegetation Index --- precision viticulture --- 3D model --- spatial vision --- fertirrigation --- teaching–learning --- spectrometry --- Sentinel-2 --- pasture quality index --- normalized difference vegetation index --- normalized difference water index --- supplementation --- decision making --- digital agriculture --- grape yield estimate --- berries counting --- Dilated CNN --- machine learning algorithms --- classification performance --- winter wheat mapping --- large-scale --- water stress --- Prunus avium L. --- stem water potential --- low-cost thermography --- thermal indexes --- canopy temperature --- non-water-stressed baselines --- non-transpiration baseline --- soil moisture --- andosols --- image processing --- greenhouse --- automatic tomato harvesting --- n/a --- Hill-Tsai failure criterion --- teaching-learning