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The theory of random Schrödinger operators is devoted to the mathematical analysis of quantum mechanical Hamiltonians modeling disordered solids. Apart from its importance in physics, it is a multifaceted subject in its own right, drawing on ideas and methods from various mathematical disciplines like functional analysis, selfadjoint operators, PDE, stochastic processes and multiscale methods. The present text describes in detail a quantity encoding spectral features of random operators: the integrated density of states or spectral distribution function. Various approaches to the construction of the integrated density of states and the proof of its regularity properties are presented. The setting is general enough to apply to random operators on Riemannian manifolds with a discrete group action. References to and a discussion of other properties of the IDS are included, as are a variety of models beyond those treated in detail here.

Schrèodinger operator --- Spectral energy distribution --- Quantum theory --- Atomic Physics --- Calculus --- Mathematics --- Physics --- Physical Sciences & Mathematics --- Schrödinger operator. --- Spectral energy distribution. --- Quantum theory. --- Quantum dynamics --- Quantum mechanics --- Quantum physics --- Energy distribution, Spectral --- Spectral density --- Operator, Schrödinger --- Mathematics. --- Dynamics. --- Ergodic theory. --- Partial differential equations. --- Probabilities. --- Probability Theory and Stochastic Processes. --- Partial Differential Equations. --- Dynamical Systems and Ergodic Theory. --- Probability --- Statistical inference --- Combinations --- Chance --- Least squares --- Mathematical statistics --- Risk --- Partial differential equations --- Ergodic transformations --- Continuous groups --- Mathematical physics --- Measure theory --- Transformations (Mathematics) --- Dynamical systems --- Kinetics --- Mechanics, Analytic --- Force and energy --- Mechanics --- Statics --- Math --- Science --- Thermodynamics --- Radiation --- Spectrum analysis --- Differential operators --- Schrödinger equation --- Distribution (Probability theory. --- Differential equations, partial. --- Differentiable dynamical systems. --- Differential dynamical systems --- Dynamical systems, Differentiable --- Dynamics, Differentiable --- Differential equations --- Global analysis (Mathematics) --- Topological dynamics --- Distribution functions --- Frequency distribution --- Characteristic functions --- Probabilities

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There are many regions worldwide which are susceptible to extreme loads such as earthquakes. These can cause loss of life and adverse impacts on civil infrastructures, the environment, and communities. A series of methods and measures have been used to mitigate the effects of these extreme loads. The adopted approaches and methods must enable civil structures to be resilient and sustainable. Therefore, to reduce damage and downtime in addition to protecting life and promoting safety, new resilient structure technologies must be proposed and developed. This special issue book focuses on methods of enhancing the sustainability and resilience of civil infrastructures in the event of extreme loads (e.g., earthquakes). This book contributes proposals of and theoretical, numerical, and experimental research on new and resilient civil structures and their structural performance under extreme loading events. These works will certainly play a significant role in promoting the application of new recoverable structures. Moreover, this book also introduces some case studies discussing the implementation of low-damage structural systems in buildings as well as articles on the development of design philosophies and performance criteria for resilient buildings and new sustainable communities.

artificial neural network --- corrosion --- mined-out region --- finite element --- column-top isolation --- pseudodynamic test --- seismic performance --- sustainability prediction --- shear performance --- nonlinear time-history analysis --- shaking table test --- civil infrastructures --- angle section --- seismic connection detail --- cyclic loading test --- extreme loads --- sudden column removal --- flow --- water supply networks --- displacement response spectrum --- cold-formed steel composite shear wall building --- mitigation --- probabilistic framework --- nonlinearity --- optimized section --- corporation --- GM selection --- seismic damage --- natural hazards --- analysis --- spectrum variance --- viscous damper --- Great East Japan Earthquake --- OpenFresco --- Brazier flattening --- substructure --- damage --- model-based --- tapered cross section --- liquefaction --- measurement --- NDE --- settlement --- seismic behavior --- resilience --- hybrid damper --- numerical simulation --- structural response estimates --- probabilistic --- energy-based approximate analysis --- damping effect --- cold-formed steel structure --- silt --- ground motion --- boundary technique --- energy dissipative devices --- reinforced concrete --- cyclic reversal test --- ground improvement --- simplified modeling method --- beam --- girder --- integration algorithm --- force-displacement control --- reinforced concrete frames --- mid-rise --- intermediate column --- time-frequency energy distribution --- single-layer reticulated dome --- structural robustness --- precast slab --- chloride ingress --- dynamic model --- Brazier effect --- earthquake --- sustainability --- carbonation --- replaceable coupling beam --- railway construction --- concrete --- variational method --- shear wall --- progressive collapse --- abnormal loads --- recovery --- earthquakes --- resilience-based design --- disaster --- OpenSees --- seismic analysis --- response surface method --- subway station --- ratcheting effect --- matching pursuit decomposition --- hybrid simulation --- subway induced vibration --- dynamic structural analysis --- numerical simulations --- structural sensitivity --- inflection point --- system restoration --- infinite element boundary --- simulation model --- Monte Carlo simulation --- nonlinear response

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With the recent advances in remote sensing technologies for Earth observation, many different remote sensors are collecting data with distinctive properties. The obtained data are so large and complex that analyzing them manually becomes impractical or even impossible. Therefore, understanding remote sensing images effectively, in connection with physics, has been the primary concern of the remote sensing research community in recent years. For this purpose, machine learning is thought to be a promising technique because it can make the system learn to improve itself. With this distinctive characteristic, the algorithms will be more adaptive, automatic, and intelligent. This book introduces some of the most challenging issues of machine learning in the field of remote sensing, and the latest advanced technologies developed for different applications. It integrates with multi-source/multi-temporal/multi-scale data, and mainly focuses on learning to understand remote sensing images. Particularly, it presents many more effective techniques based on the popular concepts of deep learning and big data to reach new heights of data understanding. Through reporting recent advances in the machine learning approaches towards analyzing and understanding remote sensing images, this book can help readers become more familiar with knowledge frontier and foster an increased interest in this field.

metadata --- image classification --- sensitivity analysis --- ROI detection --- residual learning --- image alignment --- adaptive convolutional kernels --- Hough transform --- class imbalance --- land surface temperature --- inundation mapping --- multiscale representation --- object-based --- convolutional neural networks --- scene classification --- morphological profiles --- hyperedge weight estimation --- hyperparameter sparse representation --- semantic segmentation --- vehicle classification --- flood --- Landsat imagery --- target detection --- multi-sensor --- building damage detection --- optimized kernel minimum noise fraction (OKMNF) --- sea-land segmentation --- nonlinear classification --- land use --- SAR imagery --- anti-noise transfer network --- sub-pixel change detection --- Radon transform --- segmentation --- remote sensing image retrieval --- TensorFlow --- convolutional neural network --- particle swarm optimization --- optical sensors --- machine learning --- mixed pixel --- optical remotely sensed images --- object-based image analysis --- very high resolution images --- single stream optimization --- ship detection --- ice concentration --- online learning --- manifold ranking --- dictionary learning --- urban surface water extraction --- saliency detection --- spatial attraction model (SAM) --- quality assessment --- Fuzzy-GA decision making system --- land cover change --- multi-view canonical correlation analysis ensemble --- land cover --- semantic labeling --- sparse representation --- dimensionality expansion --- speckle filters --- hyperspectral imagery --- fully convolutional network --- infrared image --- Siamese neural network --- Random Forests (RF) --- feature matching --- color matching --- geostationary satellite remote sensing image --- change feature analysis --- road detection --- deep learning --- aerial images --- image segmentation --- aerial image --- multi-sensor image matching --- HJ-1A/B CCD --- endmember extraction --- high resolution --- multi-scale clustering --- heterogeneous domain adaptation --- hard classification --- regional land cover --- hypergraph learning --- automatic cluster number determination --- dilated convolution --- MSER --- semi-supervised learning --- gate --- Synthetic Aperture Radar (SAR) --- downscaling --- conditional random fields --- urban heat island --- hyperspectral image --- remote sensing image correction --- skip connection --- ISPRS --- spatial distribution --- geo-referencing --- Support Vector Machine (SVM) --- very high resolution (VHR) satellite image --- classification --- ensemble learning --- synthetic aperture radar --- conservation --- convolutional neural network (CNN) --- THEOS --- visible light and infrared integrated camera --- vehicle localization --- structured sparsity --- texture analysis --- DSFATN --- CNN --- image registration --- UAV --- unsupervised classification --- SVMs --- SAR image --- fuzzy neural network --- dimensionality reduction --- GeoEye-1 --- feature extraction --- sub-pixel --- energy distribution optimizing --- saliency analysis --- deep convolutional neural networks --- sparse and low-rank graph --- hyperspectral remote sensing --- tensor low-rank approximation --- optimal transport --- SELF --- spatiotemporal context learning --- Modest AdaBoost --- topic modelling --- multi-seasonal --- Segment-Tree Filtering --- locality information --- GF-4 PMS --- image fusion --- wavelet transform --- hashing --- machine learning techniques --- satellite images --- climate change --- road segmentation --- remote sensing --- tensor sparse decomposition --- Convolutional Neural Network (CNN) --- multi-task learning --- deep salient feature --- speckle --- canonical correlation weighted voting --- fully convolutional network (FCN) --- despeckling --- multispectral imagery --- ratio images --- linear spectral unmixing --- hyperspectral image classification --- multispectral images --- high resolution image --- multi-objective --- convolution neural network --- transfer learning --- 1-dimensional (1-D) --- threshold stability --- Landsat --- kernel method --- phase congruency --- subpixel mapping (SPM) --- tensor --- MODIS --- GSHHG database --- compressive sensing

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This book introduces a variety of treatment technologies, such as physical, chemical, and biological methods for the treatment of gas emissions, wastewater, and solid waste. It provides a useful source of information for engineers and specialists, as well as for undergraduate and postgraduate students, in the areas of environmental science and engineering.

adsorption --- chromium --- competition --- fluoride --- soil and water pollution --- municipal solid waste management --- life cycle assessment --- life cycle impacts --- life cycle stages --- eutrophication --- global warming --- human health --- acidification --- Harare --- Zimbabwe --- iron tailings --- ammonium sulfate roasting process --- reaction mechanism --- kinetics --- carbon footprint --- CiteSpace --- a visual analysis --- metronidazole --- porous carbon --- surface modification --- wastewater treatment --- membrane fouling --- molecular composition of foulant --- transparent exopolymer particles (TEP) --- fouling propensities --- waste incineration --- cyclone flue --- gas-solid separation --- numerical simulation --- polysaccharides --- microfiltration process --- calcium ion --- copper adsorption --- magnetized pine needle biochar --- isotherms --- FTIR and XRD studies --- VLE --- CO2 capture --- amine --- DEA-12-PD --- 12-HEPP --- porosity properties --- adsorption capacity --- carbon dioxide storage --- melamine Schiff bases --- surface area --- energy --- antimony --- mineral processing --- potentially toxic elements --- pollution characteristics --- solid waste --- cleaner production --- electronic waste --- recycling --- waste printed circuit boards --- waste EAF slag --- magnesium silicate hydrate --- radioactive waste --- stabilization/solidification --- strontium --- leaching --- membrane technologies --- biofouling --- composite membranes --- polymer blending --- wastewater treatment plants --- environmental costs --- PID control --- dynamic assessment of performance --- heavy metals --- hybrid materials --- functionalized --- Schiff base --- lead --- Langmuir and Freundlich --- carbon capture and storage (CCS) --- offshore gas field --- techno-economic analysis --- calcium oxide nanoparticles --- calcination --- blended cement paste --- mix design --- compressive strength --- bulk density --- transition metal dichalcogenides --- liquid exfoliation --- quenching --- waste collection route planning --- traveling salesman problem --- genetic algorithms --- steelmaking --- bentonite --- solid waste management --- sustainable materials --- biomass --- characterization --- lignocellulosic --- bioenergy --- water treatment --- nanomaterials --- functionalization --- lime --- mineral nitrogen --- soil pH --- organic carbon --- microbial biomass --- N2O --- batch pyrolysis --- business model --- South Africa --- waste tyres --- circular economy --- environmental sustainability --- mollusk shell --- porous concrete --- construction --- algal biomass --- gasification --- activation energy distribution --- household solid waste --- metal recovery value --- socio-economic benefits --- waste composition of Karachi-Pakistan --- waste management --- waste recycling --- ash-free coal --- CO2 gasification --- coal structure --- tri-high coal --- nanoparticles --- ZnO --- equilibrium --- kinetic --- thermodynamic --- phosphate --- aqueous solution --- sustainable synthetic slag production --- energy recovery --- metal spheres --- fixed bed regenerator --- waste and energy nexus --- antibiotics --- competitive sorption --- retention/release --- sorbents --- surface-flow constructed wetland --- nitrogen load --- nitrate --- ammonium --- organic nitrogen --- hydraulic load --- hydraulic residence time --- temperature --- denitrification --- biological uptake --- n/a