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The use of data collectors in energy systems is growing more and more. For example, smart sensors are now widely used in energy production and energy consumption systems. This implies that huge amounts of data are generated and need to be analyzed in order to extract useful insights from them. Such big data give rise to a number of opportunities and challenges for informed decision making. In recent years, researchers have been working very actively in order to come up with effective and powerful techniques in order to deal with the huge amount of data available. Such approaches can be used in the context of energy production and consumption considering the amount of data produced by all samples and measurements, as well as including many additional features. With them, automated machine learning methods for extracting relevant patterns, high-performance computing, or data visualization are being successfully applied to energy demand forecasting. In light of the above, this Special Issue collects the latest research on relevant topics, in particular in energy demand forecasts, and the use of advanced optimization methods and big data techniques. Here, by energy, we mean any kind of energy, e.g., electrical, solar, microwave, or wind

Research & information: general --- Technology: general issues --- deep learning --- energy demand --- temporal convolutional network --- time series forecasting --- time series --- forecasting --- exponential smoothing --- electricity demand --- residential building --- energy efficiency --- clustering --- decision tree --- time-series forecasting --- evolutionary computation --- neuroevolution --- photovoltaic power plant --- short-term forecasting --- data processing --- data filtration --- k-nearest neighbors --- regression --- autoregression --- deep learning --- energy demand --- temporal convolutional network --- time series forecasting --- time series --- forecasting --- exponential smoothing --- electricity demand --- residential building --- energy efficiency --- clustering --- decision tree --- time-series forecasting --- evolutionary computation --- neuroevolution --- photovoltaic power plant --- short-term forecasting --- data processing --- data filtration --- k-nearest neighbors --- regression --- autoregression

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heavily Environmental mathematical models represent one of the key aids for scientists to forecast, create, and evaluate complex scenarios. These models rely on the data collected by direct field observations. However, assembly of a functional and comprehensive dataset for any environmental variable is difficult, mainly because of i) the high cost of the monitoring campaigns and ii) the low reliability of measurements (e.g., due to occurrences of equipment malfunctions and/or issues related to equipment location). The lack of a sufficient amount of Earth science data may induce an inadequate representation of the response’s complexity in any environmental system to any type of input/change, both natural and human-induced. In such a case, before undertaking expensive studies to gather and analyze additional data, it is reasonable to first understand what enhancement in estimates of system performance would result if all the available data could be well exploited. Missing data imputation is an important task in cases where it is crucial to use all available data and not discard records with missing values. Different approaches are available to deal with missing data. Traditional statistical data completion methods are used in different domains to deal with single and multiple imputation problems. More recently, machine learning techniques, such as clustering and classification, have been proposed to complete missing data. This book showcases the body of knowledge that is aimed at improving the capacity to exploit the available data to better represent, understand, predict, and manage the behavior of environmental systems at all practical scales.

geophysical monitoring --- data scarcity --- missing data --- climate extreme indices (CEIs) --- rule extraction --- Dataset Licensedatabase --- data assimilation --- data imputation --- support vector machines --- environmental observations --- multi-class classification --- earth-science data --- remote sensing --- magnetotelluric monitoring --- soil texture calculator --- machine learning --- ClimPACT --- invasive species --- species distribution modeling --- 3D-Var --- ensemble learning --- data quality --- water quality --- microhabitat --- k-Nearest Neighbors --- Expert Team on Climate Change Detection and Indices (ETCCDI) --- decision trees --- processing --- attribute reduction --- Expert Team on Sector-specific Climate Indices (ET-SCI) --- core attribute --- rough set theory --- GLDAS --- arthropod vector --- environmental modeling --- statistical methods

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Primary progressive aphasia is a clinical syndrome that includes a group of neurodegenerative disorders characterized by progressive language impairment. Our knowledge about this disorder has evolved significantly in recent years. Notably, correlations between clinical findings and pathology have improved, and main clinical, neuroimaging, and genetic features have been described. Furthermore, primary progressive aphasia is a good model for the study of brain–behavior relationships, and has contributed to the knowledge of the neural basis of language functioning. However, there are many open questions remaining. For instance, classification into three variants (non-fluent, semantic, and logopenic) is under debate; further data about epidemiology and natural history of the diseases are needed; and, as in other neurodegenerative disorders, successful therapies are lacking. The Guest Editors expect that this book can be very useful for scholars.

Research & information: general --- Biology, life sciences --- primary progressive aphasia --- informativeness --- speech production --- assessment --- diagnosis --- cognitive approach --- dementia --- frontotemporal dementia --- Alzheimer's disease --- neuropsychology --- span --- sentence repetition --- working memory --- phonological --- visuospatial --- natural history --- mortality --- survival --- memory clinic --- graphical markers --- graphical parameters --- writing pressure --- differential diagnosis --- longitudinal assessment --- cognitive changes --- behavioural and psychological symptoms of dementia --- level of functioning --- electroencephalography --- resting-state --- biomarkers machine learning --- K-Nearest Neighbors --- graph theory --- treatment --- speech and language therapy --- intervention --- cognitive rehabilitation --- bilingualism --- semantic dementia --- semantic variant primary progressive aphasia --- word finding --- language therapy --- behavioural therapy --- electroencephalography (EEG) --- network analysis --- progressive apraxia of speech --- primary progressive aphasia --- informativeness --- speech production --- assessment --- diagnosis --- cognitive approach --- dementia --- frontotemporal dementia --- Alzheimer's disease --- neuropsychology --- span --- sentence repetition --- working memory --- phonological --- visuospatial --- natural history --- mortality --- survival --- memory clinic --- graphical markers --- graphical parameters --- writing pressure --- differential diagnosis --- longitudinal assessment --- cognitive changes --- behavioural and psychological symptoms of dementia --- level of functioning --- electroencephalography --- resting-state --- biomarkers machine learning --- K-Nearest Neighbors --- graph theory --- treatment --- speech and language therapy --- intervention --- cognitive rehabilitation --- bilingualism --- semantic dementia --- semantic variant primary progressive aphasia --- word finding --- language therapy --- behavioural therapy --- electroencephalography (EEG) --- network analysis --- progressive apraxia of speech

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This Special Issue presents a range of recent technologies and innovations to help the agricultural and food industry to manage and minimize postharvest losses, enhance reliability and sustainability, and generate high-quality products that are both healthy and appealing to consumers. It focuses on three main topics of food storage and preservation technologies, food processing technologies, and the applications of advanced mathematical modelling and computer simulations. This presentation of the latest research and information is particularly useful for people who are working in or associated with the fields of agriculture, the agri-food chain and technology development and promotion.

Research & information: general --- Biology, life sciences --- Technology, engineering, agriculture --- persimmon fruit --- drying methods --- computational intelligence methods --- artificial neural network model --- support vector machine model --- k-nearest neighbors --- milk quality --- high pressure processing --- pasteurization --- milk storage --- shelf life --- bulk hazelnut kernels --- mechanical properties --- heating temperature --- oil efficiency --- relaxation process --- common beans --- beans classification --- hard-to-cook --- bean softening --- piper nigrum --- dimensions --- mass --- maturity levels --- modelling --- food security --- food quality --- agricultural production --- crop storage and processing --- food distribution --- smart digital technology --- industry 4.0 --- refrigeration --- deterioration --- cavitation --- dosage --- hurdle technology --- microorganisms --- nonthermal --- decontamination --- bulk weight --- hop cones size distribution --- chemical analysis --- energy consumption --- postharvest storage --- food packaging and shelf-life --- bitter kola --- food preservation --- alligator pepper --- underutilized seeds --- cassava --- storage --- PPD --- starch --- shelf-life --- postharvest losses --- biorational pesticides --- chemical profile --- fumigant toxicity --- modeling --- optimization --- S. hortensis --- S. intermedia --- n/a

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This Special Issue presents a range of recent technologies and innovations to help the agricultural and food industry to manage and minimize postharvest losses, enhance reliability and sustainability, and generate high-quality products that are both healthy and appealing to consumers. It focuses on three main topics of food storage and preservation technologies, food processing technologies, and the applications of advanced mathematical modelling and computer simulations. This presentation of the latest research and information is particularly useful for people who are working in or associated with the fields of agriculture, the agri-food chain and technology development and promotion.

Research & information: general --- Biology, life sciences --- Technology, engineering, agriculture --- persimmon fruit --- drying methods --- computational intelligence methods --- artificial neural network model --- support vector machine model --- k-nearest neighbors --- milk quality --- high pressure processing --- pasteurization --- milk storage --- shelf life --- bulk hazelnut kernels --- mechanical properties --- heating temperature --- oil efficiency --- relaxation process --- common beans --- beans classification --- hard-to-cook --- bean softening --- piper nigrum --- dimensions --- mass --- maturity levels --- modelling --- food security --- food quality --- agricultural production --- crop storage and processing --- food distribution --- smart digital technology --- industry 4.0 --- refrigeration --- deterioration --- cavitation --- dosage --- hurdle technology --- microorganisms --- nonthermal --- decontamination --- bulk weight --- hop cones size distribution --- chemical analysis --- energy consumption --- postharvest storage --- food packaging and shelf-life --- bitter kola --- food preservation --- alligator pepper --- underutilized seeds --- cassava --- storage --- PPD --- starch --- shelf-life --- postharvest losses --- biorational pesticides --- chemical profile --- fumigant toxicity --- modeling --- optimization --- S. hortensis --- S. intermedia --- persimmon fruit --- drying methods --- computational intelligence methods --- artificial neural network model --- support vector machine model --- k-nearest neighbors --- milk quality --- high pressure processing --- pasteurization --- milk storage --- shelf life --- bulk hazelnut kernels --- mechanical properties --- heating temperature --- oil efficiency --- relaxation process --- common beans --- beans classification --- hard-to-cook --- bean softening --- piper nigrum --- dimensions --- mass --- maturity levels --- modelling --- food security --- food quality --- agricultural production --- crop storage and processing --- food distribution --- smart digital technology --- industry 4.0 --- refrigeration --- deterioration --- cavitation --- dosage --- hurdle technology --- microorganisms --- nonthermal --- decontamination --- bulk weight --- hop cones size distribution --- chemical analysis --- energy consumption --- postharvest storage --- food packaging and shelf-life --- bitter kola --- food preservation --- alligator pepper --- underutilized seeds --- cassava --- storage --- PPD --- starch --- shelf-life --- postharvest losses --- biorational pesticides --- chemical profile --- fumigant toxicity --- modeling --- optimization --- S. hortensis --- S. intermedia