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Search results for: MEMORY SPACE
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Characterizing the Scalability of Graph Convolutional Networks on Intel® PIUMA
PublicationLarge-scale Graph Convolutional Network (GCN) inference on traditional CPU/GPU systems is challenging due to a large memory footprint, sparse computational patterns, and irregular memory accesses with poor locality. Intel’s Programmable Integrated Unffied Memory Architecture (PIUMA) is designed to address these challenges for graph analytics. In this paper, a detailed characterization of GCNs is presented using the Open-Graph Benchmark...
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Alternative Approach to Convolution Term of Viscoelasticity in Equations of Unsteady Pipe Flow
PublicationIn the paper the selected aspects concerning description of viscoelastic behavior of pipe walls during unsteady flow are analyzed. The alternative convolution expression of the viscoelastic term is presented and compared with the corresponding term referring to unsteady friction. Both approaches indicate similarities in the forms of impulse response functions and the parameter properties. The flow memory was introduced into convolution...
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Intelligent microbearing project with memory of stress-strain history
PublicationTaking into account the increasing need of intelligent micro-bearing with memory, this paper presents the optimization, simulation and practical application of operating parameters(load carrying capacity, friction forces, friction coefficient, wear), simulation for hydrodynamic HDD micro-bearing with curvilinear nano-grooved journal profile. One of the reason of such journal profile is that this journal profile contributes to the...
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High frequency oscillations in human memory and cognition: a neurophysiological substrate of engrams?
PublicationDespite advances in understanding the cellular and molecular processes underlying memory and cognition, and recent successful modulation of cognitive performance in brain disorders, the neurophysiological mechanisms remain underexplored. High frequency oscillations beyond the classic electroencephalogram spectrum have emerged as a potential neural correlate of fundamental cognitive processes. High frequency oscillations are detected...
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Shape-Memory Polyurethane Polymers
PublicationPolyurethanes (PUs) are one of the most widely used polymers in research and industry. They can be synthesized from chemical sources and natural sources. PUs are a very useful class of polymers and exhibit many desirable properties that can be exploited in various applications. PUs are formed by the reaction between polyols and isocyanates. A wide variety of polyols and isocyanates are available for synthesis, and hence we can...
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Semantic Memory for Avatars in Cyberspace
PublicationAvatars that show intelligent behavior should have an access to general knowledge about the world, knowledge that humans store in their semantic memories. The simplest knowledge representation for semantic memory is based on the Concept Description Vectors (CDVs) that store, for each concept, an information whether a given property can be applied to this concept or not. Unfortunately large-scale semantic memories are not available....
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Proximal primal–dual best approximation algorithm with memory
PublicationWe propose a new modified primal–dual proximal best approximation method for solving convex not necessarily differentiable optimization problems. The novelty of the method relies on introducing memory by taking into account iterates computed in previous steps in the formulas defining current iterate. To this end we consider projections onto intersections of halfspaces generated on the basis of the current as well as the previous...
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Electromagnetic Simulations with 3D FEM and Intel Optane Persistent Memory
PublicationAbstract—Intel Optane persistent memory has the potential to induce a change in how high-performance calculations requiring a large system memory capacity are conducted. This article presents what this change may look like in the case of factorization of large sparse matrices describing electromagnetic problems arising in the 3D FEM analysis of passive highfrequency components. In numerical tests, the Intel oneAPI MKL PARDISO was...
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On thermal stability of topological qubit in Kitaev's 4D model
PublicationWe analyse stability of the four-dimensional Kitaev model-a candidate for scalable quantum memory - in finite temperature within the weak coupling Markovian limit. It is shown that, below a critical temperature, certain topological qubit observables X and Z possess relaxation times exponentially long in the size of the system. Their construction involves polynomial in system size algorithm which uses as an input the results of...
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Unsupervised machine-learning classification of electrophysiologically active electrodes during human cognitive task performance
PublicationIdentification of active electrodes that record task-relevant neurophysiological activity is needed for clinical and industrial applications as well as for investigating brain functions. We developed an unsupervised, fully automated approach to classify active electrodes showing event-related intracranial EEG (iEEG) responses from 115 patients performing a free recall verbal memory task. Our approach employed new interpretable...
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A memory efficient and fast sparse matrix vector product on a Gpu
PublicationThis paper proposes a new sparse matrix storage format which allows an efficient implementation of a sparse matrix vector product on a Fermi Graphics Processing Unit (GPU). Unlike previous formats it has both low memory footprint and good throughput. The new format, which we call Sliced ELLR-T has been designed specifically for accelerating the iterative solution of a large sparse and complex-valued system of linear equations arising...
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Context Search Algorithm for Lexical Knowledge Acquisition
PublicationA Context Search algorithm used for lexical knowledge acquisition is presented. Knowledge representation based on psycholinguistic theories of cognitive processes allows for implementation of a computational model of semantic memory in the form of semantic network. A knowledge acquisition using supervised dialog templates have been performed in a word game designed to guess the concept a human user is thinking about. The game,...
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Massively parallel linear-scaling Hartree–Fock exchange and hybrid exchange–correlation functionals with plane wave basis set accuracy
PublicationWe extend our linear-scaling approach for the calculation of Hartree–Fock exchange energy using localized in situ optimized orbitals [Dziedzic et al., J. Chem. Phys. 139, 214103 (2013)] to leverage massive parallelism. Our approach has been implemented in the ONETEP (Order-N Electronic Total Energy Package) density functional theory framework, which employs a basis of non-orthogonal generalized Wannier functions (NGWFs) to achieve...
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High frequency oscillations are associated with cognitive processing in human recognition memory
PublicationHigh frequency oscillations are associated with normal brain function, but also increasingly recognized as potential biomarkers of the epileptogenic brain. Their role in human cognition has been predominantly studied in classical gamma frequencies (30-100 Hz), which reflect neuronal network coordination involved in attention, learning and memory. Invasive brain recordings in animals and humans demonstrate that physiological oscillations...
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Gaining knowledge through experience: developing decisional DNA applications in robotics
PublicationOmówiono nowatorskie podejscie do zastosowania wiedzy opartej na doświadczeniu i budowie decyzyjnego DNA w obszarach związanych z robotyką.In this article, we explore an approach that integrates Decisional DNA, a domain-independent, flexible, and standard knowledge representation structure, with robots in order to test the usability and suitability of this novel knowledge representation structure. Core issues in using this Decisional...
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A Computationally Efficient Model for Predicting Successful Memory Encoding Using Machine-Learning-based EEG Channel Selection
PublicationComputational cost is an important consideration for memory encoding prediction models that use data from dozens of implanted electrodes. We propose a method to reduce computational expense by selecting a subset of all the electrodes to build the prediction model. The electrodes were selected based on their likelihood of measuring brain activity useful for predicting memory encoding better than chance (in terms of AUC). A logistic...
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Shape memory thin films of Polyurethane: Does graphene content affect the recovery behavior of Polyurethane nanocomposites?
PublicationThin nanocomposite films of polyurethane have received remarkable attention due to their shape memory properties. As most of the reports focus on the beneficial aspects of the presence of nanofillers such as graphene nanoplatelets (GNPs) introduced into shape memory polymers, some research results reveal the opposite trend. The polyether/polyester-based polyurethane was synthesized through a condensation polymerization and the...
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Parallelization of large vector similarity computations in a hybrid CPU+GPU environment
PublicationThe paper presents design, implementation and tuning of a hybrid parallel OpenMP+CUDA code for computation of similarity between pairs of a large number of multidimensional vectors. The problem has a wide range of applications, and consequently its optimization is of high importance, especially on currently widespread hybrid CPU+GPU systems targeted in the paper. The following are presented and tested for computation of all vector...
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Cognitive neuroscience: Theta network oscillations coordinate development of episodic memory
PublicationOur ability to remember life events matures through childhood and adolescence. A new study has revealed how theta oscillations between two anatomical brain regions supporting memory and executive functions are synchronized and develop across age through functional and structural connectivity.
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Cognitive memory for intelligent systems of decision-making, based on human psychology
PublicationA model of memory, which allows to expand the functionality of autonomous decision-making systems for robotic and human-system-interface purposes, is discussed. The model provides functions and features which make the prospective robotic and interfacing systems more human-like as well as more efficient in solving interactive issues.
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Cognitive memory for intelligent systems of decision-making, based on human psychology
PublicationA model of memory, which allows to expand the functionality of autonomous decision-making systems for robotic and human-system-interface purposes, is discussed. The model provides functions and features which make the prospective robotic and interfacing systems more human-like as well as more efficient in solving interactive issues.
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Application and modelling of Shape-Memory Alloys for structural vibration control: State-of-the-art review
PublicationOne of the most essential components of structural design for civil engineers is to build a system that is resistant to environmental conditions such as harsh chemical environments, and catastrophic disasters like earthquakes and hurricanes. Under these circumstances and disturbances, conventional building materials such as steel and concrete may demonstrate inadequate performance in the form of corrosion, deterioration, oxidizing,...
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GPU-Accelerated Finite-Element Matrix Generation for Lossless, Lossy, and Tensor Media [EM Programmer's Notebook]
PublicationThis paper presents an optimization approach for limiting memory requirements and enhancing the performance of GPU-accelerated finite-element matrix generation applied in the implementation of the higher-order finite-element method (FEM). It emphasizes the details of the implementation of the matrix-generation algorithm for the simulation of electromagnetic wave propagation in lossless, lossy, and tensor media. Moreover, the impact...
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Efficient model order reduction for FEM analysis of waveguide structures and resonators
PublicationAn efficient model order reduction method for three-dimensional Finite Element Method (FEM) analysis of waveguide structures is proposed. The method is based on the Efficient Modal Order Reduction (ENOR) algorithm for creating macro-elements in cascaded subdomains. The resulting macro-elements are represented by very compact submatrices, leading to significant reduction of the overall number of unknowns. The efficiency of the model...
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FDTD Method for Electromagnetic Simulations in Media Described by Time-Fractional Constitutive Relations
PublicationIn this paper, the finite-difference time-domain (FDTD) method is derived for electromagnetic simulations in media described by the time-fractional (TF) constitutive relations. TF Maxwell’s equations are derived based on these constitutive relations and the Grünwald–Letnikov definition of a fractional derivative. Then the FDTD algorithm, which includes memory effects and energy dissipation of the considered media, is introduced....
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Recurrent Neural Network Based Adaptive Variable-Order Fractional PID Controller for Small Modular Reactor Thermal Power Control
PublicationThis paper presents the synthesis of an adaptive PID type controller in which the variable-order fractional operators are used. Due to the implementation difficulties of fractional order operators, both with a fixed and variable order, on digital control platforms caused by the requirement of infinite memory resources, the fractional operators that are part of the discussed controller were approximated by recurrent neural networks...
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Investigation of Parallel Data Processing Using Hybrid High Performance CPU + GPU Systems and CUDA Streams
PublicationThe paper investigates parallel data processing in a hybrid CPU+GPU(s) system using multiple CUDA streams for overlapping communication and computations. This is crucial for efficient processing of data, in particular incoming data stream processing that would naturally be forwarded using multiple CUDA streams to GPUs. Performance is evaluated for various compute time to host-device communication time ratios, numbers of CUDA streams,...
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An Approximation of the Zero Error Capacity by a Greedy Algorithm
PublicationWe present a greedy algorithm that determines a lower bound on the zero error capacity. The algorithm has many new advantages, e.g., it does not store a whole product graph in a computer memory and it uses the so-called distributions in all dimensions to get a better approximation of the zero error capacity. We also show an additional application of our algorithm.
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An Approximation of the Zero Error Capacity by a Greedy Algorithm.
PublicationWe present a greedy algorithm that determines a lower bound on the zero error capacity. The algorithm has many new advantages, e.g., it does not store a whole product graph in a computer memory and it uses the so-called distributions in all dimensions to get a better approximation of the zero error capacity. We also show an additional application of our algorithm.
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On zero-error codes produced by greedy algorithms
PublicationWe present two greedy algorithms that determine zero-error codes and lower bounds on the zero-error capacity. These algorithms have many advantages, e.g., they do not store a whole product graph in a computer memory and they use the so-called distributions in all dimensions to get better approximations of the zero-error capacity. We also show an additional application of our algorithms.
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Tuning a Hybrid GPU-CPU V-Cycle Multilevel Preconditioner for Solving Large Real and Complex Systems of FEM Equations
PublicationThis letter presents techniques for tuning an accelerated preconditioned conjugate gradient solver with a multilevel preconditioner. The solver is optimized for a fast solution of sparse systems of equations arising in computational electromagnetics in a finite element method using higher-order elements. The goal of the tuning is to increase the throughput while at the same time reducing the memory requirements in order to allow...
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Efficient parallel implementation of crowd simulation using a hybrid CPU+GPU high performance computing system
PublicationIn the paper we present a modern efficient parallel OpenMP+CUDA implementation of crowd simulation for hybrid CPU+GPU systems and demonstrate its higher performance over CPU-only and GPU-only implementations for several problem sizes including 10 000, 50 000, 100 000, 500 000 and 1 000 000 agents. We show how performance varies for various tile sizes and what CPU–GPU load balancing settings shall be preferred for various domain...
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Identification of nonstationary processes using noncausal bidirectional lattice filtering
PublicationThe problem of off-line identification of a nonstationary autoregressive process with a time-varying order and a time-varying degree of nonstationarity is considered and solved using the parallel estimation approach. The proposed parallel estimation scheme is made up of several bidirectional (noncausal) exponentially weighted lattice algorithms with different estimation memory and order settings. It is shown that optimization of...
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Independent dynamics of slow, intermediate, and fast intracranial EEG spectral activities during human memory formation
PublicationA wide spectrum of brain rhythms are engaged throughout the human cortex in cognitive functions. How the rhythms of various low and high frequencies are spatiotemporally coordinated across the human brain during memory processing is inconclusive. They can either be coordinated together across a wide range of the frequency spectrum or induced in specific bands. We used a large dataset of human intracranial electroencephalography...
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A Task-Scheduling Approach for Efficient Sparse Symmetric Matrix-Vector Multiplication on a GPU
PublicationIn this paper, a task-scheduling approach to efficiently calculating sparse symmetric matrix-vector products and designed to run on Graphics Processing Units (GPUs) is presented. The main premise is that, for many sparse symmetric matrices occurring in common applications, it is possible to obtain significant reductions in memory usage and improvements in performance when the matrix is prepared in certain ways prior to computation....
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Distinct hippocampal-prefrontal neural assemblies coordinate memory encoding, maintenance, and recall
PublicationShort-term memory enables incorporation of recent experience into subsequent decision-making. This processing recruits both the prefrontal cortex and hippocampus, where neurons encode task cues, rules, and outcomes. However, precisely which information is carried when, and by which neurons, remains unclear. Using population decoding of activity in rat medial prefrontal cortex (mPFC) and dorsal hippocampal CA1, we confirm that mPFC...
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Multi-level Virtualization and Its Impact on System Performance in Cloud Computing
PublicationThe results of benchmarking tests of multi-level virtualized environments are presented. There is analysed the performance impact of hardware virtualization, container-type isolation and programming level abstraction. The comparison is made on the basis of a proposed score metric that allows you to compare different aspects of performance. There is general performance (CPU and memory), networking, disk operations and application-like...
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Coherent-wave Monte Carlo method for simulating light propagation in tissue
PublicationSimulating propagation and scattering of coherent light in turbid media, such as biological tissues, is a complex problem. Numerical methods for solving Helmholtz or wave equation (e.g. finite-difference or finite-element methods) require large amount of computer memory and long computation time. This makes them impractical for simulating laser beam propagation into deep layers of tissue. Other group of methods, based on radiative...
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Towards an efficient multi-stage Riemann solver for nuclear physics simulations
PublicationRelativistic numerical hydrodynamics is an important tool in high energy nuclear science. However, such simulations are extremely demanding in terms of computing power. This paper focuses on improving the speed of solving the Riemann problem with the MUSTA-FORCE algorithm by employing the CUDA parallel programming model. We also propose a new approach to 3D finite difference algorithms, which employ a GPU that uses surface memory....
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Towards hardware built-in support for computer system safety
PublicationArtykuł omawia dostępne technologie wirtualizacji zasobów pamięci i systemów I/O w systemach komputerowych takie jak Execute Disable Bit (EDB) capability i Virtual Machine Architecture (VMA). Nastepnie wprowadza założenia na rozszerzenie tych technologii w celu uzyskania funkcjonalności Safe Call Execution dzieki technologii Execution Disabling Policies (EDP). Wprowadzono również założenia na funkcjonalność Memory Virtualization...
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The system for remote monitoring of a vertical axis wind farm
PublicationThe article presents a system for remote monitoring of working parameters of a wind turbine with a vertical axis. The monitoring system was built using a Raspberry PI 3 microcomputer with the Raspbian operating system and a MicroDAQ E2000 measuring card. The developed system enables monitoring the power output of the generator, torque on the turbine shaft, turbine speed and wind speed. The values of the monitored parameters are...
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Network oscillations modulate interictal epileptiform spike rate during human memory
PublicationEleven patients being evaluated with intracranial electroencephalography for medically resistant temporal lobe epilepsy participated in a visual recognition memory task. Interictal epileptiform spikes were manually marked and their rate of occurrence compared between baseline and three 2 s periods spanning a 6 s viewing period. During successful, but not unsuccessful, encoding of the images there was a significant reduction in...
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Wireless intelligent audio-video surveillance prototyping system
PublicationThe presented system is based on the Virtex6 FPGA and several supporting devices like a fast DDR3 memory, small HD camera, microphone with A/D converter, WiFi radio communication module, etc. The system is controlled by the Linux operating system. The Linux drivers for devices implemented in the system have been prepared. The system has been successfully verified in a H.264 compression accelerator prototype in which the most demanding...
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Critical Remarks on Landauer’s principle of erasure– dissipation: Including notes on Maxwell demons and Szilard engines
PublicationWe briefly address Landauer’s Principle and some related issues in thermal demons. We show that an error-free Turing computer works in the zero-entropy limit, which proves Landauer’s derivation incorrect. To have a physical logic gate, memory or information-engine, a few essential components necessary for the operation of these devices are often neglected, such as various aspects of control, damping and the fluctuation–dissipation...
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Sharp transitions in low-number quantum dots Bayesian magnetometry
PublicationWe consider Bayesian estimate of static magnetic field, characterized by a prior Gaussian probability distribution, in systems of a few electron quantum dot spins interacting with infinite temperature spin environment via hyperfine interaction. Sudden transitions among optimal states and measurements are observed. Usefulness of measuring occupation levels is shown for all times of the evolution, together with the role of entanglement...
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Information retrieval with semantic memory model
PublicationPsycholinguistic theories of semantic memory form the basis of understanding of natural language concepts. These theories are used here as an inspiration for implementing a computational model of semantic memory in the form of semantic network. Combining this network with a vector-based object-relation-feature value representation of concepts that includes also weights for confidence and support, allows for recognition of concepts...
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Advanced Control With PLC—Code Generator for aMPC Controller Implementation and Cooperation With External Computational Server for Dealing With Multidimensionality, Constraints and LMI Based Robustness
PublicationThe manufacturers of Programmable Logic Controllers (PLC) usually equip their products with extremely simple control algorithms, such as PID and on-off regulators. However, modern PLCs have much more efficient processors and extensive memory, which enables implementing more sophisticated controllers. The paper discusses issues related to the implementation of matrix operations, time limitations for code execution within one PLC...
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Gesture Recognition With the Linear Optical Sensor and Recurrent Neural Networks
PublicationIn this paper, the optical linear sensor, a representative of low-resolution sensors, was investigated in the multiclass recognition of near-field hand gestures. The recurrent neural network (RNN) with a gated recurrent unit (GRU) memory cell was utilized as a gestures classifier. A set of 27 gestures was collected from a group of volunteers. The 27 000 sequences obtained were divided into training, validation, and test subsets....
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Dysfunctional prefrontal cortical network activity and interactions following cannabinoid receptor activation.
PublicationCoordinated activity spanning anatomically distributed neuronal networks underpins cognition and mediates limbic-cortical interactions during learning, memory, and decision-making. We used CP55940, a potent agonist of brain cannabinoid receptors known to disrupt coordinated activity in hippocampus, to investigate the roles of network oscillations during hippocampal and medial prefrontal cortical (mPFC) interactions in rats. During...
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Abandoned heritage – the first European airports
PublicationDue to the development of air transport and urban expansion, the locations of pre-war airports were often changed. The question of the fate of the abandoned airports and their entire infrastructure arose. This article looks at the issue of derelict, pre-war airfields. Examples of airports which were successfully adapted as well as the ones which were abandoned and closed yet but equally important in historical context are shown....