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This book brings together a total of six papers in an interdisciplinary way at the border of natural disasters and cultural heritage. There is a need for studying and documenting cultural heritage in Arctic landscapes, as these are the most affected by climate change. Remote sensing represents a powerful tool in the monitoring, management and safeguarding of cultural heritage. Sites included in the UNESCO World Heritage List should receive more attention from both geoscientists and social scientists. Urbanization has a short- and long-lasting effect on the conservation of cultural heritage.

cultural heritage --- frequency ratio --- AUC --- predictive modelling --- GIS --- Kvamme’s Gain --- north-eastern Romania --- coastal erosion --- shoreline --- monitoring --- geomorphological mapping --- Svalbard --- DSAS --- high Arctic --- muqarnas --- Alhambra --- graphic analysis --- drawings --- 3D laser scanner --- historical images --- UNESCO --- Spain --- erosion --- Beothuk --- GRASS --- photogrammetry --- UAV --- Newfoundland --- remote sensing --- Earth observation --- satellite imagery --- multi-temporal analysis --- urban heat island --- persistent scatterer interferometry --- long-term monitoring --- cultural heritage assessment --- Alba Iulia (Apulum) --- LiDAR --- satellite image --- aerial image --- High North

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Unmanned aerial vehicles (UAV) have already become an affordable and cost-efficient tool to quickly map a targeted area for many emerging applications in the arena of ecological monitoring and biodiversity conservation. Managers, owners, companies, and scientists are using professional drones equipped with high-resolution visible, multispectral, or thermal cameras to assess the state of ecosystems, the effect of disturbances, or the dynamics and changes within biological communities inter alia. We are now at a tipping point on the use of drones for these type of applications over natural areas. UAV missions are increasing but most of them are testing applicability. It is time now to move to frequent revisiting missions, aiding in the retrieval of important biophysical parameters in ecosystems or mapping species distributions. This Special Issue shows UAV applications contributing to a better understanding of biodiversity and ecosystem status, threats, changes, and trends. It documents the enhancement of knowledge in ecological integrity parameters mapping, long-term ecological monitoring based on drones, mapping of alien species spread and distribution, upscaling ecological variables from drone to satellite images: methods and approaches, rapid risk and disturbance assessment using drones, mapping albedo with UAVs, wildlife tracking, bird colony and chimpanzee nest mapping, habitat mapping and monitoring, and a review on drones for conservation in protected areas.

Pinus nigra --- unmanned aerial vehicles (UAVs) --- biological conservation --- precision --- flight altitude --- accuracy --- multiscale approach --- low-cost UAV --- LTER --- small UAV --- ecological monitoring --- Sequoia --- long-term monitoring --- albedo --- image processing --- vegetation indices --- Tanzania --- ground-truth --- Sentinel-2 --- biodiversity threats --- field experiments --- effective management --- great apes --- drone --- ecological integrity --- multispectral --- rice crops --- conservation --- protected areas --- survey --- response surface --- aerial survey --- bird censuses --- multispectral mapping --- drones --- UAS --- hyperspectral --- UAV --- random forest --- Pinus sylvestris --- NDVI --- UAVs --- Parrot Sequoia --- supervised classification --- drone mapping --- RPAS --- greenness index --- image resolution --- Plegadis falcinellus --- Motus --- biodiversity --- Landsat 8 --- Sentinel --- boreal forest --- phenology --- LTSER --- western swamphen --- Parrot SEQUOIA --- native grassland --- forêt Montmorency --- drought --- forest regeneration --- radio-tracking

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Over the past century, the manufacturing industry has undergone a number of paradigm shifts: from the Ford assembly line (1900s) and its focus on efficiency to the Toyota production system (1960s) and its focus on effectiveness and JIDOKA; from flexible manufacturing (1980s) to reconfigurable manufacturing (1990s) (both following the trend of mass customization); and from agent-based manufacturing (2000s) to cloud manufacturing (2010s) (both deploying the value stream complexity into the material and information flow, respectively). The next natural evolutionary step is to provide value by creating industrial cyber-physical assets with human-like intelligence. This will only be possible by further integrating strategic smart sensor technology into the manufacturing cyber-physical value creating processes in which industrial equipment is monitored and controlled for analyzing compression, temperature, moisture, vibrations, and performance. For instance, in the new wave of the ‘Industrial Internet of Things’ (IIoT), smart sensors will enable the development of new applications by interconnecting software, machines, and humans throughout the manufacturing process, thus enabling suppliers and manufacturers to rapidly respond to changing standards. This reprint of “Sense and Respond” aims to cover recent developments in the field of industrial applications, especially smart sensor technologies that increase the productivity, quality, reliability, and safety of industrial cyber-physical value-creating processes.

Technology: general issues --- History of engineering & technology --- EEG sensors --- manufacturing systems --- problem-solving --- deep learning --- TDOA --- sensor networks --- hyperboloids --- node distribution --- genetic algorithms --- asynchronous --- Cramér–Rao lower bound --- heteroscedasticity --- soft sensors --- industrial optical quality inspection --- artificial vision --- long-term monitoring benefits --- indoor air quality --- low cost --- occupational safety and health --- industry 4.0 --- IOTA tangle --- Industry 4.0 --- IIoT --- geometric deep learning --- lean management --- cramer rao lower bound --- localization --- LPS --- multi-objective optimization --- sensor failure --- wireless sensor networks --- conceptual framework --- sensors --- approaches --- tools --- data --- application --- project engineering --- LCA --- SDG 9 --- SDG 11

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Over the past century, the manufacturing industry has undergone a number of paradigm shifts: from the Ford assembly line (1900s) and its focus on efficiency to the Toyota production system (1960s) and its focus on effectiveness and JIDOKA; from flexible manufacturing (1980s) to reconfigurable manufacturing (1990s) (both following the trend of mass customization); and from agent-based manufacturing (2000s) to cloud manufacturing (2010s) (both deploying the value stream complexity into the material and information flow, respectively). The next natural evolutionary step is to provide value by creating industrial cyber-physical assets with human-like intelligence. This will only be possible by further integrating strategic smart sensor technology into the manufacturing cyber-physical value creating processes in which industrial equipment is monitored and controlled for analyzing compression, temperature, moisture, vibrations, and performance. For instance, in the new wave of the ‘Industrial Internet of Things’ (IIoT), smart sensors will enable the development of new applications by interconnecting software, machines, and humans throughout the manufacturing process, thus enabling suppliers and manufacturers to rapidly respond to changing standards. This reprint of “Sense and Respond” aims to cover recent developments in the field of industrial applications, especially smart sensor technologies that increase the productivity, quality, reliability, and safety of industrial cyber-physical value-creating processes.

Technology: general issues --- History of engineering & technology --- EEG sensors --- manufacturing systems --- problem-solving --- deep learning --- TDOA --- sensor networks --- hyperboloids --- node distribution --- genetic algorithms --- asynchronous --- Cramér–Rao lower bound --- heteroscedasticity --- soft sensors --- industrial optical quality inspection --- artificial vision --- long-term monitoring benefits --- indoor air quality --- low cost --- occupational safety and health --- industry 4.0 --- IOTA tangle --- Industry 4.0 --- IIoT --- geometric deep learning --- lean management --- cramer rao lower bound --- localization --- LPS --- multi-objective optimization --- sensor failure --- wireless sensor networks --- conceptual framework --- sensors --- approaches --- tools --- data --- application --- project engineering --- LCA --- SDG 9 --- SDG 11

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Cyanobacterial abundance has increased disproportionately, and this trend is likely to continue in the coming decades. This increase not only has deleterious effects on ecosystem biodiversity but also adversely affects drinking water supplies, livestock watering, crop yields, aquaculture, etc. Thus, the proliferation of cyanobacterial blooms presents human and animal health risks due to the common production of potent toxins, cyanotoxins. Moreover, these risks are aggravated by the accumulation potential of cyanotoxins and their transference to the food chain. In spite of the worldwide increasing occurrence of cyanotoxins, they are still underestimated in regulations. However, risk management of cyanotoxins is only possible after a thorough risk evaluation, and for that purpose, toxicity and exposure data are required. Thus, occurrence and monitoring information is of key importance, and new data in relation to the conditions that favor cyanobacterial growth and cyanotoxin production are welcome in order to prevent their appearance. On the other hand, in regard to toxicity, there are still many data gaps to fill. This book compiles 10 research papers and a review, which provide valuable contributions on all these aspects and demonstrate the importance of cyanobacteria toxins research.

inflammatory bowel disease --- dextran sulfate sodium --- colitis --- microcystin --- colon --- HAB --- Adda --- canine intoxication --- MMPB --- urinalysis --- hair --- ELISA --- LC-MS/MS --- Microcystin-LR --- Non-alcoholic Fatty Liver Disease --- No Observed Adverse Effect Level --- Leprdb/J mice --- hepatotoxicity --- oxidative stress --- TiO2 enriched phosphopeptides --- Cyanotoxins --- microcystin congeners --- MC-LA --- nutrients --- climate --- Great Lakes --- raw water intake --- multivariate statistics --- long-term monitoring --- cyanobacteria --- microcystin-LR --- cylindrospermopsin --- cyanotoxins mixture --- plant growth --- toxin bioaccumulation --- cyanotoxin --- structure --- PP2A inhibition --- liquid chromatography --- mass spectrometry --- cyanotoxins --- metal --- zinc --- Microcystis aeruginosa --- in vivo --- genotoxicity --- micronucleus --- comet assay --- enzyme-modified comet assay --- rats --- drinking water quality --- Mozambique --- public health --- Llayta --- Nostoc --- flow cytometry --- liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) --- risk assessment --- management strategies --- modelling --- n/a