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• Applications of Information Theory to Epidemiology collects recent research findings on the analysis of diagnostic information and epidemic dynamics. • The collection includes an outstanding new review article by William Benish, providing both a historical overview and new insights. • In research articles, disease diagnosis and disease dynamics are viewed from both clinical medicine and plant pathology perspectives. Both theory and applications are discussed. • New theory is presented, particularly in the area of diagnostic decision-making taking account of predictive values, via developments of the predictive receiver operating characteristic curve. • New applications of information theory to the analysis of observational studies of disease dynamics in both human and plant populations are presented.

Research & information: general --- Biology, life sciences --- Ebola model --- Caputo derivative --- Caputo-Fabrizio derivative --- Atangana-Baleanu derivative --- numerical results --- entropy --- information theory --- multiple diagnostic tests --- mutual information --- relative entropy --- balance --- Jensen-Shannon divergence --- observational study --- selection bias --- probability --- forecast --- likelihood ratio --- positive predictive value --- negative predictive value --- diagnostic information --- Shannon entropy --- epidemic model --- transient behavior --- vaccination and treatment intervention controls --- diagnostic test --- evaluation --- ROC curve --- PROC curve --- binormal --- prevalence --- Bayes' rule --- leaf plot --- expected mutual information --- predictive ROC curve --- PV-ROC curve --- SS-ROC curve --- SS/PV-ROC plot --- empirical --- urinary bladder cancer --- sensitivity --- specificity --- HIV/AIDS epidemic --- regression model --- Newton-Raphson procedure --- Fisher scoring algorithm --- time series --- early detection --- Asiatic citrus canker --- latent class --- field diagnostic --- scent signature --- direct assay --- deployment --- average mutual information --- stochastic processes --- deterministic dynamics --- Ebola model --- Caputo derivative --- Caputo-Fabrizio derivative --- Atangana-Baleanu derivative --- numerical results --- entropy --- information theory --- multiple diagnostic tests --- mutual information --- relative entropy --- balance --- Jensen-Shannon divergence --- observational study --- selection bias --- probability --- forecast --- likelihood ratio --- positive predictive value --- negative predictive value --- diagnostic information --- Shannon entropy --- epidemic model --- transient behavior --- vaccination and treatment intervention controls --- diagnostic test --- evaluation --- ROC curve --- PROC curve --- binormal --- prevalence --- Bayes' rule --- leaf plot --- expected mutual information --- predictive ROC curve --- PV-ROC curve --- SS-ROC curve --- SS/PV-ROC plot --- empirical --- urinary bladder cancer --- sensitivity --- specificity --- HIV/AIDS epidemic --- regression model --- Newton-Raphson procedure --- Fisher scoring algorithm --- time series --- early detection --- Asiatic citrus canker --- latent class --- field diagnostic --- scent signature --- direct assay --- deployment --- average mutual information --- stochastic processes --- deterministic dynamics

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Sustainability is a fairly old concept, born in the 18th century in the field of forestry, within a mono-functionality perspective. The concept has considerably evolved in the last few years towards a multi-functionality context, with applications reported in practically all areas of economic interest. On the other hand, modern sustainability is a complex problem, for two reasons: a) The multiplicity of functions of a very different nature involved in the process and b) The manner in which different segments of the society or stakeholders perceive the relative importance of these functions. For the above reasons, a realistic approach for dealing with the sustainability issue requires taking into consideration multiple criteria of different nature (economic, environmental and social), and in many cases within a participatory decision making framework. This book presents a collection of papers, dealing with different theoretical and applied issues of sustainability, with the help of a modern multi-criteria decision-making theory, with a single as well as several stakeholders involved in the decision-making process. Hopefully, this material will encourage academics and practitioners to alter their research in this hot and vital topic. After all, the sustainable management of the environment and its embedded resources is one of the most important, if not the major challenge of the 21st century.

Economics, finance, business & management --- goal programming --- interactive methods --- forest planning --- Green-Tree Retention --- climate and energy policy --- transformation pathways --- low carbon technologies --- decision support --- multi-criteria analysis --- fuzzy PROMETHEE --- supplier evaluation --- supplier segmentation --- multi-attribute utility theory --- preference ranking organisation method for enrichment evaluation --- quality indicator --- food safety --- fresh food --- sustainable supply chain --- multicriteria --- circular economy --- composite indicators --- sustainability --- TOPSIS --- Analytical Hierarchy Process (AHP) --- carbon neutral --- ISO 14001 --- economic-strategic --- environmental sustainability --- Costa Rica --- criteria --- food and biodegradable waste --- analytic hierarchy process --- benefit–cost analysis --- multi-criteria decision analysis --- waste disposal technology --- anaerobic digestion --- weak sustainability --- strong sustainability --- NAIADE --- rural land use planning --- forestry --- agricultural sustainability --- environmental performance --- sustainability indices --- best-worst method --- irrigated olive groves --- Spain --- CoCoSo method --- Shannon Entropy method --- “Agenda 2030” --- sustainable development goals --- EU countries --- achievement --- assessment --- wind energy --- multi-objective optimization --- weighted goal programming --- progressive bounded constraint --- n/a --- benefit-cost analysis --- "Agenda 2030"

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Fault diagnosis has always been a concern for industry. In general, diagnosis in complex systems requires the acquisition of information from sensors and the processing and extracting of required features for the classification or identification of faults. Therefore, fault diagnosis of sensors is clearly important as faulty information from a sensor may lead to misleading conclusions about the whole system. As engineering systems grow in size and complexity, it becomes more and more important to diagnose faulty behavior before it can lead to total failure. In the light of above issues, this book is dedicated to trends and applications in modern-sensor fault diagnosis.

Technology: general issues --- rolling bearing --- performance degradation --- hybrid kernel function --- krill herd algorithm --- SVR --- acoustic-based diagnosis --- gear fault diagnosis --- attention mechanism --- convolutional neural network --- stacked auto-encoder --- weighting strategy --- deep learning --- bearing fault diagnosis --- intelligent leak detection --- acoustic emission signals --- statistical parameters --- support vector machine --- wavelet denoising --- Shannon entropy --- adaptive noise reducer --- gaussian reference signal --- gearbox fault diagnosis --- one against on multiclass support vector machine --- varying rotational speed --- fault detection and diagnosis --- faults estimation --- actuator and sensor fault --- observer design --- Takagi-Sugeno fuzzy systems --- automotive --- perception sensor --- lidar --- fault detection --- fault isolation --- fault identification --- fault recovery --- fault diagnosis --- fault detection and isolation (FDIR) --- autonomous vehicle --- model predictive control --- path tracking control --- fault detection and isolation --- braking control --- nonlinear systems --- fault tolerant control --- iterative learning control --- neural networks --- cryptography --- wireless sensor networks --- machine learning --- scan-chain diagnosis --- artificial neural network --- NARX --- control valve --- decision tree --- signature matrix --- n/a

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This Special Issue titled “Soil Erosion and Sustainable Land Management” presents 13 chapters organized into four main parts. The first part deals with assessment of soil erosion that covers historical sediment dating to understand past environmental impacts due to tillage; laboratory simulation to clarify the effect of soil surface microtopography; integrated field observation and the random forest machine learning algorithm to assess watershed-scale soil erosion assessment; and developing the sediment delivery distributed (SEDD) model for sub-watershed erosion risk prioritization. In Part II, the factors controlling soil erosion and vegetation degradation as influenced by topographic positions and climatic regions; long-term land use change; and improper implementation of land management measures are well dealt with. Part III presents different land management technologies that could reduce soil erosion at various spatial scales; improve land productivity of marginal lands with soil microbes; and reclaim degraded farmland using dredged reservoir sediments. The final part relates livelihood diversification to climate vulnerability as well as the coping strategy to the adverse impacts of soil erosion through sustainable land management implementation which opens prospects for policy formulation. The studies cover regions of Africa, Europe, North America and Asia, being dominantly conducted under the framework of international scientific collaborations through employing a range techniques and scales, from the laboratory to watershed scales. We believe those unique features of the book could attract the interest of the wider scientific community worldwide.

Herfindahl–Simpson diversity index --- multivariate probit --- drought prone --- ordered probit --- livelihood diversification --- sustainable land management --- sediment --- land use --- erosion crises --- environmental impact --- climate change --- drought --- livelihood vulnerability --- Shannon-entropy index --- splash erosion --- rainfall simulator --- splash cup --- soil loss --- soil detachment --- disdrometer --- rainfall kinetic energy --- polyacrylamide --- gypsum --- lime --- runoff --- dryland --- Erosion rate --- ANFIS --- ANN --- SVM --- Shihmen Reservoir watershed --- Acacia decurrens --- Eucalyptus --- drought-prone --- highland --- midland --- lowland --- marginal soil --- land degradation --- endemic plant species --- soil microbes --- arid regions --- bacteria --- degraded land --- fungi --- ITS --- microbial community --- restoration --- 16S rRNA --- Gully Land Consolidation --- backfilled loess --- physical-mechanical property --- microstructural characteristic --- pore size distribution --- sediment transport --- soil erosion --- RUSLE (Revised Universal Soil Loss Equation model) --- human activities --- sediment delivery distributed model --- sediment yield --- SEDD --- sediment delivery ratio --- β coefficient --- micro-dam --- sedimentation --- reclaimed farmland --- constructability --- Ethiopian highlands --- soil organic carbon --- structure stability --- soil type

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Fault diagnosis has always been a concern for industry. In general, diagnosis in complex systems requires the acquisition of information from sensors and the processing and extracting of required features for the classification or identification of faults. Therefore, fault diagnosis of sensors is clearly important as faulty information from a sensor may lead to misleading conclusions about the whole system. As engineering systems grow in size and complexity, it becomes more and more important to diagnose faulty behavior before it can lead to total failure. In the light of above issues, this book is dedicated to trends and applications in modern-sensor fault diagnosis.

rolling bearing --- performance degradation --- hybrid kernel function --- krill herd algorithm --- SVR --- acoustic-based diagnosis --- gear fault diagnosis --- attention mechanism --- convolutional neural network --- stacked auto-encoder --- weighting strategy --- deep learning --- bearing fault diagnosis --- intelligent leak detection --- acoustic emission signals --- statistical parameters --- support vector machine --- wavelet denoising --- Shannon entropy --- adaptive noise reducer --- gaussian reference signal --- gearbox fault diagnosis --- one against on multiclass support vector machine --- varying rotational speed --- fault detection and diagnosis --- faults estimation --- actuator and sensor fault --- observer design --- Takagi-Sugeno fuzzy systems --- automotive --- perception sensor --- lidar --- fault detection --- fault isolation --- fault identification --- fault recovery --- fault diagnosis --- fault detection and isolation (FDIR) --- autonomous vehicle --- model predictive control --- path tracking control --- fault detection and isolation --- braking control --- nonlinear systems --- fault tolerant control --- iterative learning control --- neural networks --- cryptography --- wireless sensor networks --- machine learning --- scan-chain diagnosis --- artificial neural network --- NARX --- control valve --- decision tree --- signature matrix --- n/a