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The invasive presence of mosquitoes and their pathogens is changing our daily lives and challenging our lifestyles. Mosquitoes contribute to thousands of deaths worldwide each year by transmitting various parasites and viruses, responsible for diseases with well-known names: malaria, dengue, zika, chikungunya, etc. What is less well known, however, is that mosquitoes also contribute to the balance of ecosystems as a source of food for many species and help pollinate plants. Their great morphological, biological, ecological and genetic diversity must be well understood before solutions can be considered to better control their spread and outbreak, and thus control the transmission of pathogens. Faced with this rapidly evolving threat, innovative and concerted strategies to control these insects are being deployed in many countries. Aimed at a wide audience, but also at students and their teachers, this book, illustrated with numerous examples, is a synthesis of knowledge on mosquitoes and current control methods.

biology --- mapping --- entomology --- epidemiology --- risk management --- identification --- insect --- modeling --- pest --- prevention --- research --- health --- virus

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The inner ear is a complex machinery at the cellular and molecular levels. Many different genes and proteins play roles in the development and maintenance of its structure and function, through participating in diverse molecular networks. A defect in any of these components can result in the loss of hearing. Consequently, hearing impairment encompasses a wide variety of disorders that are clinically and genetically heterogeneous. Understanding their genetic causes and their pathophysiological mechanisms, and characterizing the resulting phenotypes, are essential for developing novel therapies that target the specific defects. The articles and reviews in this book are representative of the many research lines that are currently active in the field, including recent advances in the genes and mutations involved in hearing impairment, the mechanisms through which mutations result in different syndromic or non-syndromic disorders, and the description of the associated phenotypes in humans and in animal models.

Research & information: general --- Biology, life sciences --- Genetics (non-medical) --- inner ear --- hearing impairment --- gene identification --- disease-causing mutations --- genetic epidemiology --- genotype&ndash --- phenotype correlations --- pathophysiological mechanisms --- omics --- genome editing --- gene therapy

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This open access book provides a comprehensive treatment of recent developments in kernel-based identification that are of interest to anyone engaged in learning dynamic systems from data. The reader is led step by step into understanding of a novel paradigm that leverages the power of machine learning without losing sight of the system-theoretical principles of black-box identification. The authors’ reformulation of the identification problem in the light of regularization theory not only offers new insight on classical questions, but paves the way to new and powerful algorithms for a variety of linear and nonlinear problems. Regression methods such as regularization networks and support vector machines are the basis of techniques that extend the function-estimation problem to the estimation of dynamic models. Many examples, also from real-world applications, illustrate the comparative advantages of the new nonparametric approach with respect to classic parametric prediction error methods. The challenges it addresses lie at the intersection of several disciplines so Regularized System Identification will be of interest to a variety of researchers and practitioners in the areas of control systems, machine learning, statistics, and data science. This is an open access book.

Machine learning --- Automatic control engineering --- Statistical physics --- Bayesian inference --- Probability & statistics --- Cybernetics & systems theory --- System Identification --- Machine Learning --- Linear Dynamical Systems --- Nonlinear Dynamical Systems --- Kernel-based Regularization --- Bayesian Interpretation of Regularization --- Gaussian Processes --- Reproducing Kernel Hilbert Spaces --- Estimation Theory --- Support Vector Machines --- Regularization Networks

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The aim of the present Special Issue is to address the state-of-art of mitochondrial genomics and phylogenomics. Mitochondrial markers are widespread in phylogenetics; however, it is becoming increasingly clear that (i) many discordance issues arise with respect to nuclear markers and (ii) many features that are normally considered 'typical' for the mitochondrial genome are indeed highly unstable and unconserved.

Acari Actinotrichida --- COI --- cytochrome B --- genetic identification --- Hydrachnidia --- Culicidae --- reverse taxonomy --- species identification --- Unio crassus --- freshwater mussels --- population genetics --- genetic diversity --- mtDNA --- ITS --- codon degeneration --- phylogenetic conflict --- deep phylogeny --- ratite --- Theileria parva --- mitogenomes --- haplotypes --- SNPs --- live vaccine --- fig wasps --- classification --- phylogeny --- mitochondrial gene --- transcriptome --- divergence --- Diptera --- saturation --- rates --- banana --- diversification times --- mitochondrial genome --- Mycosphaerellaceae --- plant pathogens --- Pseudocercospora --- sigatoka disease --- wild sheep --- bighorn --- taxonomy --- cytochrome b --- Yakut snow sheep --- Ovis nivicola lydekkeri --- Actiniaria --- group I intron --- mitogenome --- rearrangement --- sea anemone --- 2D RNA-Barcoding --- molecular morphology --- Nudibranchia --- Dondice --- heteroplasmy --- paternal leakage --- NUMTs --- selection --- mtDNA architecture --- mtDNA structure --- nucleotide composition --- compositional bias --- strand asymmetry --- Eukaryota --- mtDNA expansion --- ICZN --- homonym --- Heterobranchia --- Crassostrea angulata --- Portuguese oyster --- cox1 --- phylogeography --- phylogenetics --- haplotype diversity --- oyster conservation --- n/a

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During the past few decades, information technologies have been evolving at a tremendous rate, causing profound changes to our world and to our ways of living. Emerging applications have opened u[ new routes and set new trends for antenna sensors. With the advent of the Internet of Things (IoT), the adaptation of antenna technologies for sensor and sensing applications has become more important. Now, the antennas must be reconfigurable, flexible, low profile, and low-cost, for applications from airborne and vehicles, to machine-to-machine, IoT, 5G, etc. This reprint aims to introduce and treat a series of advanced and emerging topics in the field of antenna sensors.

3D printing --- additive manufacturing --- Radio Frequency IDentification (RFID), chipless RFID --- mounted on metal --- unmanned aerial vehicle --- phased array --- frequency reconfiguration --- beam steering --- antioxidation --- frequency-reconfiguration --- liquid metal --- temperature sensor --- antenna sensor --- thermal expansion --- electrolyte-free --- industrial WSN --- ISA100.11a model --- ns-3 --- WSN --- UHF antennas --- ultra wideband antennas --- conformal antennas --- radio frequency identification --- elliptical dipole antenna --- EM/circuit co-simulation --- low-cost --- low-power --- power gating --- RF oscillator --- RTLS --- ultrawide band antennas --- biopotential sensing --- Fabry-Perot resonator --- antenna --- superstrate --- metamaterials --- passive sensing --- sensor array --- sparse array --- nonuniform array --- planar array --- random array --- low discrepancy sequence --- triband antenna --- wireless sensors --- planar patch antenna --- mobile applications --- DCS --- WLAN --- WiMAX --- circular polarization --- flexible --- polymer --- transparent --- wearable --- litz wire --- lateral misalignment --- magnetic field distribution --- mutual inductance --- Neumann integral formula --- planar spiral coil --- Internet of Things (IoT) --- wireless sensor network (WSN) --- switched-beam antenna --- electronically steerable parasitic array radiator (ESPAR) antenna --- received signal strength (RSS) --- direction-of-arrival (DoA) estimation