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Pod Hradem Cave (Czech Republic)

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Cacao pod borer --- Biological control --- Acrocerops cramerella --- Cocoa pod borer --- Conopomorpha cramerella --- Conopomorpha

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633.74 --- 632 --- Cacao (cocoa or chocolate tree). Theobroma cacao --- Plant damage, injuries. Plant diseases. Pests, organisms injurious to plants. Plant protection --- Cacao --- Phytophthora palmivora --- Phytophthora pod rot of cacao. --- Diseases and pests. --- Control. --- 632 Plant damage, injuries. Plant diseases. Pests, organisms injurious to plants. Plant protection --- 633.74 Cacao (cocoa or chocolate tree). Theobroma cacao --- Phytophthora pod rot of cacao --- Black pod, Cacao --- Cacao black pod --- Cacao canker --- Cacao pod rot --- Canker, Cacao --- Phytophthora pod rot and canker of cacao --- Pod rot, Cacao --- Phytophthora diseases --- Phytophthora --- Diseases and pests --- Control

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The use of machine learning in mechanics is booming. Algorithms inspired by developments in the field of artificial intelligence today cover increasingly varied fields of application. This book illustrates recent results on coupling machine learning with computational mechanics, particularly for the construction of surrogate models or reduced order models. The articles contained in this compilation were presented at the EUROMECH Colloquium 597, « Reduced Order Modeling in Mechanics of Materials », held in Bad Herrenalb, Germany, from August 28th to August 31th 2018. In this book, Artificial Neural Networks are coupled to physics-based models. The tensor format of simulation data is exploited in surrogate models or for data pruning. Various reduced order models are proposed via machine learning strategies applied to simulation data. Since reduced order models have specific approximation errors, error estimators are also proposed in this book. The proposed numerical examples are very close to engineering problems. The reader would find this book to be a useful reference in identifying progress in machine learning and reduced order modeling for computational mechanics.

supervised machine learning --- proper orthogonal decomposition (POD) --- PGD compression --- stabilization --- nonlinear reduced order model --- gappy POD --- symplectic model order reduction --- neural network --- snapshot proper orthogonal decomposition --- 3D reconstruction --- microstructure property linkage --- nonlinear material behaviour --- proper orthogonal decomposition --- reduced basis --- ECSW --- geometric nonlinearity --- POD --- model order reduction --- elasto-viscoplasticity --- sampling --- surrogate modeling --- model reduction --- enhanced POD --- archive --- modal analysis --- low-rank approximation --- computational homogenization --- artificial neural networks --- unsupervised machine learning --- large strain --- reduced-order model --- proper generalised decomposition (PGD) --- a priori enrichment --- elastoviscoplastic behavior --- error indicator --- computational homogenisation --- empirical cubature method --- nonlinear structural mechanics --- reduced integration domain --- model order reduction (MOR) --- structure preservation of symplecticity --- heterogeneous data --- reduced order modeling (ROM) --- parameter-dependent model --- data science --- Hencky strain --- dynamic extrapolation --- tensor-train decomposition --- hyper-reduction --- empirical cubature --- randomised SVD --- machine learning --- inverse problem plasticity --- proper symplectic decomposition (PSD) --- finite deformation --- Hamiltonian system --- DEIM --- GNAT

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Food processing by humans goes a long way back in time, e.g., heat for cooking was used 1.9 million years ago. However, meal preparation now seems to be moving out of the home kitchen, and preprocessed or processed/convenience food products are becoming a larger part of the daily diet. In addition, consumers are progressively focusing on the impact of food on their health, and they demand foods that have a high nutritional quality and an aroma and natural flavor that are similar to freshly-made products. Therefore, nutritional quality is concurrent with food safety, and sensory perception is becoming an increasingly important factor in food choices. The human digestive tract disintegrates food to allow the nutrients to be released and made available to the body. However, nutrients can undergo unwanted degradation upon processing and subsequent storage, negatively influencing the physiological effects. Different processing techniques will result in different food structures, thereby also affecting bioaccessibility and nutritional value. Hence, food scientists and industry have an increased interest in both conventional and innovative processing methods that can provide good-quality products with high nutritional value and stable shelf life. This Special Issue aims to shed some light on the latest knowledge about and developments within the effects of food processing and storage on changes of biochemical and nutritional compounds. Both original research articles and reviews are included in this book.

History of engineering & technology --- protein fractionation --- white teff --- brown teff --- amino acid profile --- seed storage proteins --- essential amino acids --- anthocyanins --- ascorbic acid --- UV-Vis --- HPLC-MS --- kinetics --- shelf life --- legume protein --- processing --- digestibility --- PEF --- OH --- POD --- colour --- extraction --- spray drying --- freeze drying --- antioxidants --- carotenoid aggregates --- coloring foods --- grouper --- refrigerated storage --- packaging methods --- protein oxidation --- protein degradation --- protein fractionation --- white teff --- brown teff --- amino acid profile --- seed storage proteins --- essential amino acids --- anthocyanins --- ascorbic acid --- UV-Vis --- HPLC-MS --- kinetics --- shelf life --- legume protein --- processing --- digestibility --- PEF --- OH --- POD --- colour --- extraction --- spray drying --- freeze drying --- antioxidants --- carotenoid aggregates --- coloring foods --- grouper --- refrigerated storage --- packaging methods --- protein oxidation --- protein degradation