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This edited book contains twelve studies, large and pilots, in five main categories: (i) adaptive imputation to increase the density of clinical data for improving downstream modeling; (ii) machine-learning-empowered diagnosis models; (iii) machine learning models for outcome prediction; (iv) innovative use of AI to improve our understanding of the public view; and (v) understanding of the attitude of providers in trusting insights from AI for complex cases. This collection is an excellent example of how technology can add value in healthcare settings and hints at some of the pressing challenges in the field. Artificial intelligence is gradually becoming a go-to technology in clinical care; therefore, it is important to work collaboratively and to shift from performance-driven outcomes to risk-sensitive model optimization, improved transparency, and better patient representation, to ensure more equitable healthcare for all.

machine learning-enabled decision support system --- improving diagnosis accuracy --- Bayesian network --- bariatric surgery --- health-related quality of life --- comorbidity --- voice change --- larynx cancer --- machine learning --- deep learning --- voice pathology classification --- imputation --- electronic health records --- EHR --- laboratory measures --- medical informatics --- inflammatory bowel disease --- C. difficile infection --- osteoarthritis --- complex diseases --- healthcare --- artificial intelligence --- interpretable machine learning --- explainable machine learning --- septic shock --- clinical decision support system --- electronic health record --- cerebrovascular disorders --- stroke --- SARS-CoV-2 --- COVID-19 --- cluster analysis --- risk factors --- ischemic stroke --- outcome prediction --- recurrent stroke --- cardiac ultrasound --- echocardiography --- portable ultrasound --- aneurysm surgery --- temporary artery occlusion --- clipping time --- artificial neural network --- digital imaging --- monocytes --- promonocytes and monoblasts --- chronic myelomonocytic leukemia (CMML) and acute myeloid leukemia (AML) for acute monoblastic leukemia and acute monocytic leukemia --- concordance between hematopathologists --- mechanical ventilation --- respiratory failure --- ADHD --- social media --- Twitter --- pharmacotherapy --- stimulants --- alpha-2-adrenergic agonists --- non-stimulants --- trust --- passive adherence --- human factors

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Landscapes have long been viewed as ‘multifunctional’, integrating ecological, economic, sociocultural, historical, and aesthetic dimensions. Landscape science and public awareness in Europe have been progressing in leaps and bounds. The challenges involved in landscape-related issues and fields, however, are multiple and refer to landscape stewardship and protection, as well as to the development of comprehensive theoretical and methodological approaches, in tandem with public sensitization and participatory governance and in coordination with appropriate top-down planning and policy instruments. Landscape-scale approaches are fundamental to the understanding of past and present cultural evolution, and are now considered to be an appropriate spatial framework for the analysis of sustainability. Methods and tools of landscape analysis and intervention have also gone a long way since their early development in Europe and the United States. Although significant progress has been made, there remain many issues which are understudied or not investigated at all—at least in a Mediterranean context. This Special Issue addresses the application of landscape theory and practice in the Eastern Mediterranean and mainly, but not exclusively, reports on the outcomes of an international conference held in Jordan, in December 2015, with the title “Landscapes of Eastern Mediterranean: Challenges, Opportunities, Prospects and Accomplishments”. The focus of this Special Issue, landscapes of the Eastern Mediterranean region, thus constitutes a timely area of research interest, not only because these landscapes have so far been understudied, but also as a rich site of strikingly variegated, long-standing multicultural human–environmental interactions. These interactions, resting on and taking shape through millennia of continuity in tradition, have been striving to adapt to technological advances, while currently juggling with manifold and multilayered socioeconomic and climate–environmental crises.

n/a --- landscape archaeology --- Cyprus --- Landscape Character Assessment (LCA) --- Eastern Mediterranean --- Land Description Units --- stakeholders’ analysis --- UK --- local authority --- ancient sanctuaries --- East Med landscape --- Twain-born Border Lord --- Landscape Decision Support System --- mapping --- topography --- Byzantine landscape and garden art --- economy --- LCA --- classification --- churches --- Arabic-speaking --- participatory --- Landscape Risk Assessment Model --- landforms --- GIS --- planning --- typology --- Greek-speaking --- public realm --- landscape changes --- sacred space --- comparative study --- urban environment --- ideology --- political power --- Arabic landscape and garden art --- cultural sustainability --- historical maps --- religion --- rural land --- multi-functional landscapes --- Lebanon --- Mediterranean --- geographical information system --- spatial distributions --- Land Description Unit (LDU) --- political sustainability --- landscape --- landscape character assessment --- governance --- stakeholders' analysis

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In the modern world, the competitiveness of bioenergy- and/or bioresources-related activities heavily depends on the effectiveness of supply chain management. A large number of multidisciplinary topics are involved in the bioresources and bioenergy production fields. Although the technical issues that are related with the topic are well-discussed and do not represent major barriers, supply chain management issues, such as design of the network, collection, storage or transportation of bioresources, are still considered as fundamental questions that need to be answered to enable the optimal exploitation of bioenergy and bioresources. Moreover, modeling of material and energy flows; identification of the dynamic character of the supply chains; available reverse logistics (waste management) alternatives; economic, social and environmental sustainability of bioresource supply chains; novelty in the applied business models; and decision support frameworks towards efficient supply chain management for bioenergy and bioresources present critical operational sustainability issues and business-making potential. This Special Issue, entitled “Supply Chain Management for Bioenergy and Bioresources”, seeks to contribute to the bioenergy and bioresources agenda through enhanced scientific and multi-disciplinary knowledge that may boost the performance efficiency of supply chain management and support the decision-making process of stakeholders. To that end, the Special Issue includes one extensive review on yellow and woody biomass supply-chain management, together with six original papers which span a number of innovative, multifaceted, technical developments that are related to all different echelons of supply chain management for bioenergy and bioresources.

supply-chain design --- strategic planning --- operational planning --- energy crop production --- crop residue --- dry above ground biomass --- soybean --- empirical models --- bilinear regression analysis --- agricultural operations --- energy use --- assessment tool --- workability --- machinery --- agricultural machinery --- fleet management --- auto-steering system --- collaborative operating system --- flow-shop --- simulation --- field experiment --- Fuzzy Cognitive Maps --- photovoltaic solar energy --- scenario analysis --- decision-support --- energy management --- bioenergy --- efficiency of bio-resources --- decision support system --- multi-criteria analysis --- sustainability --- neuro-fuzzy --- ANFIS --- neural networks --- soft computing --- fuzzy cognitive maps --- energy forecasting --- natural gas --- prediction

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Spruce budworm (Choristoneura fumiferana (Clem.)) outbreaks are a dominant natural disturbance in the forests of Canada and northeastern USA. Widespread, severe defoliation by this native insect results in large-scale mortality and growth reductions of spruce (Picea sp.) and balsam fir (Abies balsamea (L.) Mill.) forests, and largely determines future age–class structure and productivity. The last major spruce budworm outbreak defoliated over 58 million hectares in the 1970s–1980s, and caused 32–43 million m3/year of timber volume losses from 1978 to 1987, in Canada. Management to deal with spruce budworm outbreaks has emphasized forest protection, spraying registered insecticides to prevent defoliation and keep trees alive. Other tactics can include salvage harvesting, altering harvest schedules to remove the most susceptible stands, or reducing future susceptibility by planting or thinning. Chemical insecticides are no longer used, and protection strategies use biological insecticides Bacillus thuringiensis (B.t.) or tebufenozide, a specific insect growth regulator. Over the last five years, a $30 million research project has tested another possible management tactic, termed an ‘early intervention strategy’, aimed at area-wide management of spruce budworm populations. This includes intensive monitoring to detect ‘hot spots’ of rising budworm populations before defoliation occurs, targeted insecticide treatment to prevent spread, and detailed research into target and non-target insect effects. The objective of this Special Issue is to compile the most recent research on protection strategies against spruce budworm. A series of papers will describe results and prospects for the use of an early intervention strategy in spruce budworm and other insect management.

pheromone mating disruption --- spruce budworm --- insecticide application --- multi-spectral remote sensing --- simulation --- apparent fecundity --- Choristoneura fumiferana (Clemens) --- Pinaceae --- Choristoneura fumiferana --- circadian rhythm --- forest protection --- early intervention strategy --- insect population management --- moth --- survival --- Phialocephala scopiformis --- moths --- optimized treatment design --- spatial-temporal patterns --- monitoring --- modelling --- science communication --- decision support system --- population control --- area-wide management --- tortricidae --- insect susceptibility --- egg recruitment --- annual defoliation --- treatment threshold --- Maine --- dispersal --- growth rate --- forest pests --- Choristoneura fumiferana (Clem.) --- mixed effect models --- intertree variance --- endophytic fungi --- Acadian region --- insecticides --- defoliation --- Abies balsamea --- Picea glauca --- immigration --- defoliation prediction --- early intervention --- Quebec --- phenology --- aerobiology --- economic losses --- spatial autocorrelation --- foliage protection --- computable general equilibrium model --- economic and ecological cost: benefit analyses --- hardwood content --- plant tolerance --- Lepidoptera --- migration

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Metal manufacturing is a fundamental and indispensable technology in the processing of raw metals into desired products, which significantly promotes the development of industry and society overall. This book presents original research and a state of the art review of contemporary metal manufacturing processes, especially in the modeling, optimization, and design of the manufacturing processes. This book covers topics such as machine learning algorithms in manufacturing metal products, the fabrication and optimization of mechanical properties of metals, and numerical simulations and experiments in the machining of metals. The book presents some essential theories and successful manufacturing techniques for the low-cost and highly efficient production of metals.

Business strategy --- Manufacturing industries --- machine learning --- reinforcement learning --- Q-learning --- steelmaking process CAS-OB --- decision-support system --- optimisation algorithm --- 3D auxetic structures --- selective laser melting --- micro assembled --- structural surface layer model --- A380 alloy --- Ca --- AlFeSi phase --- refine --- micro-cutting --- grain size --- surface integrity --- cutting forces --- chip formation --- OFHC copper C102 --- amorphous alloys --- Fe-based amorphous alloys --- difficult-to-machine --- assisted machining --- high-frequency PCB --- drilling --- coating technology --- tool wear --- hot filament chemical vapor deposition --- PCBN tool --- gray cast iron --- surface quality --- temperature prediction --- weighted regularized extreme learning machine --- just-in-time learning --- sample similarities --- variable correlations --- tool edge preparation --- orthogonal cutting --- numerical simulation --- ANOVA --- temperature --- stress --- ECAP --- metallic materials --- processing parameters --- deformation mechanism --- n/a