10,790 research outputs found
Glucosinolates in plant protection strategies: A review
This review discusses the importance of glucosinolates in plant protection. The Brassicaceae, which are cultivated worldwide, use glucosinolates and their decomposition products to defend themselves against attacks by harmful organisms. The glucosinolate content varies among individual plant species, plant organs and developmental stages. The glucosinolate content in plants is also affected by biotic and abiotic factors, while the type or quantity of glucosinolate determines the susceptibility of the plants to insect pests. These facts can pose a problem when implementing this knowledge in cultivation of the Brassicaceae, especially in regions with moderate climates where Brassicaceae crops are exposed to attacks by a large number of harmful organisms. Under these circumstances, it is essential to research new, or to improve the existing environmentally acceptable methods of protecting Brassicaceae plants against economically important pests
Detecting swift heavy ion irradiation effects with graphene
In this paper we show how single layer graphene can be utilized to study
swift heavy ion (SHI) modifications on various substrates. The samples were
prepared by mechanical exfoliation of bulk graphite onto SrTiO, NaCl and
Si(111), respectively. SHI irradiations were performed under glancing angles of
incidence and the samples were analysed by means of atomic force microscopy in
ambient conditions. We show that graphene can be used to check whether the
irradiation was successful or not, to determine the nominal ion fluence and to
locally mark SHI impacts. In case of samples prepared in situ, graphene is
shown to be able to catch material which would otherwise escape from the
surface.Comment: 10 pages, 3 figure
Properties of potential eco-friendly gas replacements for particle detectors in high-energy physics
Gas detectors for elementary particles require F-based gases for optimal performance.
Recent regulations demand the use of environmentally unfriendly F-based gases to be limited or
banned. This work studies properties of potential eco-friendly gas replacements by computing the
physical and chemical parameters relevant for use as detector media, and suggests candidates to be
considered for experimental investigation
Candidate eco-friendly gas mixtures for MPGDs
Modern gas detectors for detection of particles require F-based gases for optimal performance.Recent regulations demand the use of environmentally unfriendly F-based gases t o be limited or banned. This review studies properties of potential eco-friendly gas candidate replacements
Properties of potential eco-friendly gas replacements for particle detectors in high-energy physics
Modern gas detectors for detection of particles require F-based gases for
optimal performance. Recent regulations demand the use of environmentally
unfriendly F-based gases to be limited or banned. This review studies
properties of potential eco-friendly gas candidate replacements.Comment: 38 pages, 9 figures, 8 tables. To be submitted to Journal of
Instrumentatio
Universal Leakage Elimination
``Leakage'' errors are particularly serious errors which couple states within
a code subspace to states outside of that subspace thus destroying the error
protection benefit afforded by an encoded state. We generalize an earlier
method for producing leakage elimination decoupling operations and examine the
effects of the leakage eliminating operations on decoherence-free or noiseless
subsystems which encode one logical, or protected qubit into three or four
qubits. We find that by eliminating the large class of leakage errors, under
some circumstances, we can create the conditions for a decoherence free
evolution. In other cases we identify a combination decoherence-free and
quantum error correcting code which could eliminate errors in solid-state
qubits with anisotropic exchange interaction Hamiltonians and enable universal
quantum computing with only these interactions.Comment: 14 pages, no figures, new version has references updated/fixe
Optimized Dynamical Decoupling for Time Dependent Hamiltonians
The validity of optimized dynamical decoupling (DD) is extended to
analytically time dependent Hamiltonians. As long as an expansion in time is
possible the time dependence of the initial Hamiltonian does not affect the
efficiency of optimized dynamical decoupling (UDD, Uhrig DD). This extension
provides the analytic basis for (i) applying UDD to effective Hamiltonians in
time dependent reference frames, for instance in the interaction picture of
fast modes and for (ii) its application in hierarchical
DD schemes with pulses about two perpendicular axes in spin space. to
suppress general decoherence, i.e., longitudinal relaxation and dephasing.Comment: 5 pages, no figure
Efficient Coherent Control by Optimized Sequences of Pulses of Finite Duration
Reliable long-time storage of arbitrary quantum states is a key element for
quantum information processing. In order to dynamically decouple a spin or
quantum bit from a dephasing environment, we introduce an optimized sequence of
control pulses of finite durations \tau\pp and finite amplitudes. The
properties of this sequence of length stem from a mathematically rigorous
derivation. Corrections occur only in order and \tau\pp^3 without
mixed terms such as T^N\tau\pp or T^N\tau\pp^2. Based on existing
experiments, a concrete setup for the verification of the properties of the
advocated realistic sequence is proposed.Comment: 8 pages, 1 figur
A ferrofluid based neural network: design of an analogue associative memory
We analyse an associative memory based on a ferrofluid, consisting of a
system of magnetic nano-particles suspended in a carrier fluid of variable
viscosity subject to patterns of magnetic fields from an array of input and
output magnetic pads. The association relies on forming patterns in the
ferrofluid during a trainingdphase, in which the magnetic dipoles are free to
move and rotate to minimize the total energy of the system. Once equilibrated
in energy for a given input-output magnetic field pattern-pair the particles
are fully or partially immobilized by cooling the carrier liquid. Thus produced
particle distributions control the memory states, which are read out
magnetically using spin-valve sensors incorporated in the output pads. The
actual memory consists of spin distributions that is dynamic in nature,
realized only in response to the input patterns that the system has been
trained for. Two training algorithms for storing multiple patterns are
investigated. Using Monte Carlo simulations of the physical system we
demonstrate that the device is capable of storing and recalling two sets of
images, each with an accuracy approaching 100%.Comment: submitted to Neural Network
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