5,858 research outputs found
âGiantâ magnetoresistance in obliquely co-evaporated Co-Ag films
Magnetoresistance (MR) measurements at room temperature have been performed on obliquely (co-) evaporated Ag-Co films deposited at room- and elevated-temperatures. The âgiantâ magnetoresistance ratio (max. 13% for a composition of about Co35Ag65) over a wide range of compositions has been measured. The films are polycrystalline and grown in a columnar morphology. The columnar diameter depends on the thickness and is < 20 nm at 400 nm thickness. From XRD, NMR and saturation magnetization (Ms) vs. at% Ag, one can conclude that the films consist of Co-Co and Ag-Ag clusters. The coercivity depends on the thickness of the films (100â700 nm) and varies from 5 to 15 kA/m
Neutron reflectometry on Co-Cr layers
Polarized neutron reflection experiments were performed on a thin in-plane magnetized Co-Cr layer deposited on a quartz substrate. Data taken at a low magnetic field ( 0.1 T) clearly indicate the existence of an initial layer at the substrate side, whereas data at saturation ( 0.7 T) are consistent with a rather homogeneous magnetization
Exact Markovian kinetic equation for a quantum Brownian oscillator
We derive an exact Markovian kinetic equation for an oscillator linearly
coupled to a heat bath, describing quantum Brownian motion. Our work is based
on the subdynamics formulation developed by Prigogine and collaborators. The
space of distribution functions is decomposed into independent subspaces that
remain invariant under Liouville dynamics. For integrable systems in
Poincar\'e's sense the invariant subspaces follow the dynamics of uncoupled,
renormalized particles. In contrast for non-integrable systems, the invariant
subspaces follow a dynamics with broken-time symmetry, involving generalized
functions. This result indicates that irreversibility and stochasticity are
exact properties of dynamics in generalized function spaces. We comment on the
relation between our Markovian kinetic equation and the Hu-Paz-Zhang equation.Comment: A few typos in the published version are correcte
Onder water, boven water. Relicten in een oude rivierpolder. Het verhaal van de polder van Kruibeke-Bazel-Rupelmonde (prov. Oost-Vl.)
Een van de streefdoelen van het geactualiseerde Sigmaplan is om het Zeescheldebekken in de toekomst beter te beveiligen tegen overstromingen. Vroeger ingedijkte valleigebieden worden daarom omgevormd tot gecontroleerde overstromingsgebieden (GOG), met natuur als nevenfunctie. De herinrichting van deze gebieden door Waterwegen en Zeekanaal (W&Z) is momenteel volop aan de gang. Hierdoor zal het voormalige cultuurhistorische landschap grondig veranderen. Rivierpolders stonden door hun lage ligging en het constante overstromingsrisico steeds weinig onder druk van bebouwing en infrastructuur en herbergen op die manier veel relicten uit vroegere tijdlagen. In opdracht van W&Z onderzocht het VIOE de overstromingsgeschiedenis en de cultuurhistorische ontwikkeling van de polder van Kruibeke, Bazel en Rupelmonde (KBR)
Political Violence and Excess Liquidity in Egypt
In this article we estimate a time-series model of excess liquidity in the Egyptian banking sector. While financial liberalisation and financial stability are found to have reduced excess liquidity, these effects have been offset by an increase in the number of violent political incidents arising from conflict between radical Islamic groups and the Egyptian state. The link between political events and financial outcomes provides a rationale for economic policy interventions by the international community in response to increases in political instability
Visual pathways from the perspective of cost functions and multi-task deep neural networks
Vision research has been shaped by the seminal insight that we can understand
the higher-tier visual cortex from the perspective of multiple functional
pathways with different goals. In this paper, we try to give a computational
account of the functional organization of this system by reasoning from the
perspective of multi-task deep neural networks. Machine learning has shown that
tasks become easier to solve when they are decomposed into subtasks with their
own cost function. We hypothesize that the visual system optimizes multiple
cost functions of unrelated tasks and this causes the emergence of a ventral
pathway dedicated to vision for perception, and a dorsal pathway dedicated to
vision for action. To evaluate the functional organization in multi-task deep
neural networks, we propose a method that measures the contribution of a unit
towards each task, applying it to two networks that have been trained on either
two related or two unrelated tasks, using an identical stimulus set. Results
show that the network trained on the unrelated tasks shows a decreasing degree
of feature representation sharing towards higher-tier layers while the network
trained on related tasks uniformly shows high degree of sharing. We conjecture
that the method we propose can be used to analyze the anatomical and functional
organization of the visual system and beyond. We predict that the degree to
which tasks are related is a good descriptor of the degree to which they share
downstream cortical-units.Comment: 16 pages, 5 figure
Visual features drive the category-specific impairments on categorization tasks in a patient with object agnosia
Object and scene recognition both require mapping of incoming sensory information to existing conceptual knowledge about the world. A notable finding in brain-damaged patients is that they may show differentially impaired performance for specific categories, such as for âliving exemplarsâ. While numerous patients with category-specific impairments have been reported, the explanations for these deficits remain controversial. In the current study, we investigate the ability of a brain injured patient with a well-established category-specific impairment of semantic memory to perform two categorization experiments: ânaturalâ vs. âmanmadeâ scenes (experiment 1) and objects (experiment 2). Our findings show that the pattern of categorical impairment does not respect the natural versus manmade distinction. This suggests that the impairments may be better explained by differences in visual features, rather than by category membership. Using Deep Convolutional Neural Networks (DCNNs) as âartificial animal modelsâ we further explored this idea. Results indicated that DCNNs with âlesionsâ in higher order layers showed similar response patterns, with decreased relative performance for manmade scenes (experiment 1) and natural objects (experiment 2), even though they have no semantic category knowledge, apart from a mapping between pictures and labels. Collectively, these results suggest that the direction of category-effects to a large extent depends, at least in MSⲠcase, on the degree of perceptual differentiation called for, and not semantic knowledge
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