185 research outputs found
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The catalytic oxidation of biomass to new materials focusing on starch, cellulose and lignin
Biomass is a renewable class of materials of growing interest amongst researchers aiming to achieve global sustainability. This review focuses on the homogeneous catalysis of the oxidation of biomass, in particular starch, cellulose and lignin. Often such catalytic reactions lead to depolymerisation of the material as happens in Nature with for example brown rot fungi. This depolymerisation can be desirable or not, and control in industrial applications is thus important to obtain the desired outcome. The two main oxidants in use are O2 and H2O2 and their use is described as appropriate. Industrial oxidation catalysis is highly significant in the bleaching of cellulose-containing materials due to its high volume application in the paper, pulp and laundry industries. Here, the presence of a ligand on the oxidising metal ion has a significant effect on the catalyst selectivity and stability. In addition to the bleaching of cellulose-containing materials, the oxidation of cellulose, starch, lignin and lignin model compounds are discussed with a focus on generating even more hydrophilic materials which have important applications or materials which may be further modified. Finally developing applications of biomass are described such as new support materials for catalysts, as supports for sensors and nanomaterials for microbial culture
Quantising Higher-spin String Theories
In this paper, we examine the conditions under which a higher-spin string
theory can be quantised. The quantisability is crucially dependent on the way
in which the matter currents are realised at the classical level. In
particular, we construct classical realisations for the algebra,
which is generated by a primary spin- current in addition to the
energy-momentum tensor, and discuss the quantisation for . From these
examples we see that quantum BRST operators can exist even when there is no
quantum generalisation of the classical algebra. Moreover, we find
that there can be several inequivalent ways of quantising a given classical
theory, leading to different BRST operators with inequivalent cohomologies. We
discuss their relation to certain minimal models. We also consider the
hierarchical embeddings of string theories proposed recently by Berkovits and
Vafa, and show how the already-known strings provide examples of this
phenomenon. Attempts to find higher-spin fermionic generalisations lead us to
examine the whether classical BRST operators for ( odd)
algebras can exist. We find that even though such fermionic algebras close up
to null fields, one cannot build nilpotent BRST operators, at least of the
standard form.Comment: CTP TAMU-24/94, KUL-TF-94/11, SISSA-135/94/E
RELATION BETWEEN LINEAR AND NONLINEAR N = 3,4 SUPERGRAVITY THEORIES
The effective actions for d=2, N=3, 4 chiral supergravities with a linear and a nonlinear gauge algebra are related to each other by a quantum reduction; the latter is obtained from the former by putting quantum currents equal to zero. This implies that the renormalization factors for the quantum actions are identical
Superstrings from Hamiltonian Reduction
In any string theory there is a hidden, twisted superconformal symmetry
algebra, part of which is made up by the BRST current and the anti-ghost. We
investigate how this algebra can be systematically constructed for strings with
supersymmetries, via quantum Hamiltonian reduction of the Lie
superalgebras . The motivation is to understand how one could
systematically construct generalized string theories from superalgebras. We
also briefly discuss the BRST algebra of the topological string, which is a
doubly twisted superconformal algebra.Comment: 32p, LaTeX, CERN-TH.7379/9
Unitary minimal models of SW(3/2,3/2,2) superconformal algebra and manifolds of G_2 holonomy
The SW(3/2,3/2,2) superconformal algebra is a W algebra with two free
parameters. It consists of 3 superconformal currents of spins 3/2, 3/2 and 2.
The algebra is proved to be the symmetry algebra of the coset
(su(2)+su(2)+su(2))/su(2). At the central charge c=21/2 the algebra coincides
with the superconformal algebra associated to manifolds of G_2 holonomy. The
unitary minimal models of the SW(3/2,3/2,2) algebra and their fusion structure
are found. The spectrum of unitary representations of the G_2 holonomy algebra
is obtained.Comment: 34 pages, 2 figures, latex; v2: added examples in appendix D; v3:
published version, corrected typo
Формування теоретичної моделі геополітичного дискурсу у вітчизняній політичній думці кінця ХХ – початку ХХІ століття
У статті висвітлюються питання щодо започаткування новітньої дослідницької традиції геополітичного дискурсу у проблематиці вітчизняної політичної думки ХХ – початку ХХІ століття. Зазначено позиції провідних вітчизняних вчених щодо формування емпіричного та ідейно-теоретичного підґрунтя для утвердження цієї традиції політичного дослідження.The article considers the questions of the becoming of a new research tradition of
geopolitical discourse in the topic of native political thought of the 20-th – the beginning of the 21-st century. The views of leading home scientists about the development of empirical, ideological and theoretical basis for the maintenance of this tradition of political research are pointed out
Feasibility of Image Reconstruction from Triple Modality Data of Yttrium-90
The recent implementation of the first clinical triple modality scanner in STIR enables investigation of the possibility of triple modality image reconstruction. Such a tool represents an important step toward the improvement of dosimetry for theranostics, where the exploitation of multi-modality imaging can have an impact on treatment planning and follow-up. To give a demonstration of triple modality image reconstruction we used data from a NEMA phantom that was filled with Yttrium-90 (90Y), which emits Bremsstrahlung photons detectable with SPECT as well as gamma rays that can go through pair production, therefore creating positrons that make PET acquisition possible. The data were acquired with the Mediso AnyScan SPECT/PET/CT. Different ways of including multiple side information using the kernelised expectation maximisation (KEM) and the Hybrid KEM (HKEM) were used and investigated in terms of ROI activity and noise suppression. This work presents an example of application with 90Y but it can be extended to any other radionuclide combination used in Theranostic applications
Comparison of Motion Correction Methods Incorporating Motion Modelling for PET/CT Using a Single Breath Hold Attenuation Map
Introducing motion models into respiratory motion correction methods can lead to a reduction in blurring and artefacts. However, the pool of research where motion modelling methods are applied to combined positron emission tomography and computed tomography is relatively shallow. Previous work used non-attenuation corrected time-of-flight data to fit motion models, not only to motion correct the volumes themselves, but also to warp a single attenuation map to the positions of the initial gated data. This work seeks to extend previous work to offer a comparison of respiratory motion correction methods, not only with and without motion models, but also to compare pair-wise and group-wise registration techniques, on simulation data, in a low count scenario, where the attenuation map is from a pseudo-breath hold acquisition. To test the methods, 4-Dimensional Extended Cardiac Torso images are constructed, simulated and reconstructed without attenuation correction, then motion corrected using one of pair-wise, pair-wise with motion model, group-wise and group-wise with motion model registration. Next these motion corrected volumes are registered to the breath hold attenuation map. The positron emission tomography data are then reconstructed using deformed attenuation maps and motion corrected. Evaluation compares the results of these methods against non-motion corrected and motion free examples. Results indicate that the incorporation of motion models and group-wise registration, improves contrast and quantification
An Investigation of Stochastic Variance Reduction Algorithms for Relative Difference Penalised 3D PET Image Reconstruction
Penalised PET image reconstruction algorithms are often accelerated during early iterations with the use of subsets. However, these methods may exhibit limit cycle behaviour at later iterations due to variations between subsets. Desirable converged images can be achieved for a subclass of these algorithms via the implementation of a relaxed step size sequence, but the heuristic selection of parameters will impact the quality of the image sequence and algorithm convergence rates. In this work, we demonstrate the adaption and application of a class of stochastic variance reduction gradient algorithms for PET image reconstruction using the relative difference penalty and numerically compare convergence performance to BSREM. The two investigated algorithms are: SAGA and SVRG. These algorithms require the retention in memory of recently computed subset gradients, which are utilised in subsequent updates. We present several numerical studies based on Monte Carlo simulated data and a patient data set for fully 3D PET acquisitions. The impact of the number of subsets, different preconditioners and step size methods on the convergence of regions of interest values within the reconstructed images is explored. We observe that when using constant preconditioning, SAGA and SVRG demonstrate reduced variations in voxel values between subsequent updates and are less reliant on step size hyper-parameter selection than BSREM reconstructions. Furthermore, SAGA and SVRG can converge significantly faster to the penalised maximum likelihood solution than BSREM, particularly in low count data
An Investigation of Stochastic Variance Reduction Algorithms for Relative Difference Penalized 3D PET Image Reconstruction
Penalised PET image reconstruction algorithms are often accelerated during early iterations with the use of subsets. However, these methods may exhibit limit cycle behaviour at later iterations due to variations between subsets. Desirable converged images can be achieved for a subclass of these algorithms via the implementation of a relaxed step size sequence, but the heuristic selection of parameters will impact the quality of the image sequence and algorithm convergence rates. In this work, we demonstrate the adaption and application of a class of stochastic variance reduction gradient algorithms for PET image reconstruction using the relative difference penalty and numerically compare convergence performance to BSREM. The two investigated algorithms are: SAGA and SVRG. These algorithms require the retention in memory of recently computed subset gradients, which are utilised in subsequent updates. We present several numerical studies based on Monte Carlo simulated data and a patient data set for fully 3D PET acquisitions. The impact of the number of subsets, different preconditioners and step size methods on the convergence of regions of interest values within the reconstructed images is explored. We observe that when using constant preconditioning, SAGA and SVRG demonstrate reduced variations in voxel values between subsequent updates and are less reliant on step size hyper-parameter selection than BSREM reconstructions. Furthermore, SAGA and SVRG can converge significantly faster to the penalised maximum likelihood solution than BSREM, particularly in low count data
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