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What neurobiology and artificial intelligence tell us about how the brain builds itself How does a neural network become a brain? While neurobiologists investigate how nature accomplishes this feat, computer scientists interested in artificial intelligence strive to achieve this through technology. The Self-Assembling Brain tells the stories of both fields, exploring the historical and modern approaches taken by the scientists pursuing answers to the quandary: What information is necessary to make an intelligent neural network?As Peter Robin Hiesinger argues, “the information problem” underlies both fields, motivating the questions driving forward the frontiers of research. How does genetic information unfold during the years-long process of human brain development—and is there a quicker path to creating human-level artificial intelligence? Is the biological brain just messy hardware, which scientists can improve upon by running learning algorithms on computers? Can AI bypass the evolutionary programming of “grown” networks? Through a series of fictional discussions between researchers across disciplines, complemented by in-depth seminars, Hiesinger explores these tightly linked questions, highlighting the challenges facing scientists, their different disciplinary perspectives and approaches, as well as the common ground shared by those interested in the development of biological brains and AI systems. In the end, Hiesinger contends that the information content of biological and artificial neural networks must unfold in an algorithmic process requiring time and energy. There is no genome and no blueprint that depicts the final product. The self-assembling brain knows no shortcuts.Written for readers interested in advances in neuroscience and artificial intelligence, The Self-Assembling Brain looks at how neural networks grow smarter.

Neural networks (Computer science) --- Learning --- Physiological aspects. --- Gary Macus. --- How to Create a Mind. --- Peter Sterling. --- Principles of Neural Design. --- Ray Kurzweil. --- Roger Sperry. --- Seymour Benzer. --- Simon Laughlin. --- Sydney Brenner. --- The Birth of the Mind. --- algorithm. --- algorithmic growth. --- artificial life. --- artificial neural network. --- axon guidance. --- behavior. --- brain development. --- brain wiring. --- cellular automaton. --- cognitive bias. --- complexity. --- computer intelligence. --- connectome. --- cybernetics. --- deep learning. --- evolution. --- filopodia. --- gene. --- guidance cue. --- information theory. --- machine learning. --- memory. --- neural circuit. --- neurogenetics. --- self-organization. --- synapse.

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In the special issue related to Modelling the Deformation, Recrystallization and Microstructure-Related Properties in Metals, we presented a wide spectrum of articles dealing with modelling of microstructural aspects involved in deformation and recrystallization as well as simulation of microstructure-based and texture-based properties in various metals. The latest advances in the theoretical interpretation of mesoscopic transformations based on experimental observations were partially discussed in the current special issue. The studies dealing with the modelling of structure-property relationships are likewise analyzed in the present collection of manuscripts. The contributions in the current collection evidently demonstrate that the properties of metallic materials are microstructure dependent and therefore the thermomechanical processing (TMP) of the polycrystalline aggregates should be strictly controlled to guarantee the desired bunch of qualities. Given this, the assessment of microstructure evolution in metallic systems is of extraordinary importance. Since the trial-error approach is a time-consuming and quite expensive methodology, the materials research community tends to employ a wide spectrum of computational approaches to simulate each chain of TMP and tune the processing variables to ensure the necessary microstructural state which will provide desired performance in the final product. Although many hidden facets of various technological processes and related microstructural changes were revealed in the submitted works by employing advanced computational approaches, nevertheless, the contributions collected in this issue clearly show that further efforts are required in the field of modelling to understand the complexity of material’s world. The final goal of modelling efforts might be a development of a comprehensive model, which will be capable of describing many aspects of microstructure evolution during thermomechanical processing.

magnesium alloy --- deformation mechanisms --- plastic deformation --- polycrystal plasticity modeling --- FeMnSiCrNi alloy --- shape memory alloy --- cellular automaton --- dynamic recrystallization --- boron steel --- tailored hot stamping --- phase transition --- springback --- 300M steel --- hot processing map --- thermal compression --- microstructure evolution --- in situ experiments --- cold rolling --- deformation flow --- texture simulation --- high-strength steel --- hot stamping --- martensitic transformation --- finite element analysis --- constitutive equation --- GH4169 superalloy --- microstructure evolution simulation --- multidirectional forging --- aluminum --- cross-rolling --- texture --- earing --- Cu–Al–Ni monocrystalline alloy --- reversible martensitic transformations --- thermo-cyclic treatment under load --- physical characterization and structural characterization --- n/a --- Cu-Al-Ni monocrystalline alloy

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This book deals with metal processing and its numerical modelling and simulation. In total, 21 papers from different distinguished authors have been compiled in this area. Various processes are addressed, including solidification, TIG welding, additive manufacturing, hot and cold rolling, deep drawing, pipe deformation, and galvanizing. Material models are developed at different length scales from atomistic simulation to finite element analysis in order to describe the evolution and behavior of materials during thermal and thermomechanical treatment. Materials under consideration are carbon, Q&T, DP, and stainless steels; ductile iron; and aluminum, nickel-based, and titanium alloys. The developed models and simulations shall help to predict structure evolution, damage, and service behavior of advanced materials.

Technology: general issues --- all-position automatic tungsten inert gas (TIG) welding --- optimal welding parameters --- response surface method (RSM) --- lap joint --- weld bead geometry --- tin alloy --- modified embedded-atom method --- molecular dynamics simulation --- phase transformation --- diffusion --- numerical simulation --- cellular automaton --- dendritic grain growth --- quantitative prediction --- plasticity forming --- cold roll-beating forming --- process parameter --- multi-objective optimization --- undermatched --- integrity identification --- XFEM --- fracture toughness calculation method --- microstructure --- tensile properties --- intermetallics --- casting --- dual phase steel --- hot dip galvanizing line --- multivariate analysis --- dilatometry --- selective laser melting --- additive manufacturing --- SLM --- FEM --- Al2O3 --- reinforced --- Al2O3-ZrO2 --- 304 --- stainless --- composite --- aluminium alloy --- EN AW-6060 --- precipitation hardening aluminium alloys --- material model --- heating --- cooling --- flow cures --- LS-DYNA --- molecular dynamics --- nano-cutting --- crystal direction --- γ-TiAl alloy --- stacking fault --- flow stress --- hot deformation --- carbon steel --- continuous cooling --- phase transformations --- rupture disc --- finite element analysis --- burst fracture --- mechanical property --- austenitic stainless steel --- stress triaxiality --- material damage --- FEM simulation --- ultrasonic drawing --- titanium wire --- drawing force --- Mises stress --- contact stress --- work hardening --- deep drawing --- limiting drawing ratio (LDR) --- draw radius --- anisotropy --- finite element method --- stainless steels --- plastic deformation --- mechanical properties --- quarter buckle --- roll stack deflection --- strip material flow --- roll contour optimisation --- hot-rolled stainless steel --- model fitting --- optimization --- metal casting --- SGI --- compass search --- NEWUOA --- genetic algorithm --- particle swarm optimization --- additive manufacture --- Ti-6Al-4V --- temperature distribution --- distortion --- residual stress --- experimental validation --- cylindrical cup --- earing --- thermal modeling --- volumetric heat source --- computational efficiency --- all-position automatic tungsten inert gas (TIG) welding --- optimal welding parameters --- response surface method (RSM) --- lap joint --- weld bead geometry --- tin alloy --- modified embedded-atom method --- molecular dynamics simulation --- phase transformation --- diffusion --- numerical simulation --- cellular automaton --- dendritic grain growth --- quantitative prediction --- plasticity forming --- cold roll-beating forming --- process parameter --- multi-objective optimization --- undermatched --- integrity identification --- XFEM --- fracture toughness calculation method --- microstructure --- tensile properties --- intermetallics --- casting --- dual phase steel --- hot dip galvanizing line --- multivariate analysis --- dilatometry --- selective laser melting --- additive manufacturing --- SLM --- FEM --- Al2O3 --- reinforced --- Al2O3-ZrO2 --- 304 --- stainless --- composite --- aluminium alloy --- EN AW-6060 --- precipitation hardening aluminium alloys --- material model --- heating --- cooling --- flow cures --- LS-DYNA --- molecular dynamics --- nano-cutting --- crystal direction --- γ-TiAl alloy --- stacking fault --- flow stress --- hot deformation --- carbon steel --- continuous cooling --- phase transformations --- rupture disc --- finite element analysis --- burst fracture --- mechanical property --- austenitic stainless steel --- stress triaxiality --- material damage --- FEM simulation --- ultrasonic drawing --- titanium wire --- drawing force --- Mises stress --- contact stress --- work hardening --- deep drawing --- limiting drawing ratio (LDR) --- draw radius --- anisotropy --- finite element method --- stainless steels --- plastic deformation --- mechanical properties --- quarter buckle --- roll stack deflection --- strip material flow --- roll contour optimisation --- hot-rolled stainless steel --- model fitting --- optimization --- metal casting --- SGI --- compass search --- NEWUOA --- genetic algorithm --- particle swarm optimization --- additive manufacture --- Ti-6Al-4V --- temperature distribution --- distortion --- residual stress --- experimental validation --- cylindrical cup --- earing --- thermal modeling --- volumetric heat source --- computational efficiency

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This book deals with metal processing and its numerical modelling and simulation. In total, 21 papers from different distinguished authors have been compiled in this area. Various processes are addressed, including solidification, TIG welding, additive manufacturing, hot and cold rolling, deep drawing, pipe deformation, and galvanizing. Material models are developed at different length scales from atomistic simulation to finite element analysis in order to describe the evolution and behavior of materials during thermal and thermomechanical treatment. Materials under consideration are carbon, Q&T, DP, and stainless steels; ductile iron; and aluminum, nickel-based, and titanium alloys. The developed models and simulations shall help to predict structure evolution, damage, and service behavior of advanced materials.

all-position automatic tungsten inert gas (TIG) welding --- optimal welding parameters --- response surface method (RSM) --- lap joint --- weld bead geometry --- tin alloy --- modified embedded-atom method --- molecular dynamics simulation --- phase transformation --- diffusion --- numerical simulation --- cellular automaton --- dendritic grain growth --- quantitative prediction --- plasticity forming --- cold roll-beating forming --- process parameter --- multi-objective optimization --- undermatched --- integrity identification --- XFEM --- fracture toughness calculation method --- microstructure --- tensile properties --- intermetallics --- casting --- dual phase steel --- hot dip galvanizing line --- multivariate analysis --- dilatometry --- selective laser melting --- additive manufacturing --- SLM --- FEM --- Al2O3 --- reinforced --- Al2O3-ZrO2 --- 304 --- stainless --- composite --- aluminium alloy --- EN AW-6060 --- precipitation hardening aluminium alloys --- material model --- heating --- cooling --- flow cures --- LS-DYNA --- molecular dynamics --- nano-cutting --- crystal direction --- γ-TiAl alloy --- stacking fault --- flow stress --- hot deformation --- carbon steel --- continuous cooling --- phase transformations --- rupture disc --- finite element analysis --- burst fracture --- mechanical property --- austenitic stainless steel --- stress triaxiality --- material damage --- FEM simulation --- ultrasonic drawing --- titanium wire --- drawing force --- Mises stress --- contact stress --- work hardening --- deep drawing --- limiting drawing ratio (LDR) --- draw radius --- anisotropy --- finite element method --- stainless steels --- plastic deformation --- mechanical properties --- quarter buckle --- roll stack deflection --- strip material flow --- roll contour optimisation --- hot-rolled stainless steel --- model fitting --- optimization --- metal casting --- SGI --- compass search --- NEWUOA --- genetic algorithm --- particle swarm optimization --- additive manufacture --- Ti-6Al-4V --- temperature distribution --- distortion --- residual stress --- experimental validation --- cylindrical cup --- earing --- thermal modeling --- volumetric heat source --- computational efficiency