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$_3$, 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 $\pi$ 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 $N$ control pulses of finite durations \tau\pp and finite amplitudes. The properties of this sequence of length $T$ stem from a mathematically rigorous derivation. Corrections occur only in order $T^{N+1}$ 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