1,105 research outputs found
Tailoring parameter distributions to specific germplasm : impact on crop model-based ideotyping
Crop models are increasingly used to identify promising ideotypes for given environmental and management conditions. However, uncertainty must be properly managed to maximize the in vivo realizability of ideotypes. We focused on the impact of adopting germplasm-specific distributions while exploring potential combinations of traits. A field experiment was conducted on 43 Italian rice varieties representative of the Italian rice germplasm, where the following traits were measured: light extinction coefficient, radiation use efficiency, specific leaf area at emergence and tillering. Data were used to derive germplasm-specific distributions, which were used to re-run a previous modelling experiment aimed at identifying optimal combinations of plant trait values. The analysis, performed using the rice model WARM and sensitivity analysis techniques, was conducted under current conditions and climate change scenarios. Results revealed that the adoption of germplasm-specific distributions may markedly affect ideotyping, especially for the identification of most promising traits. A re-ranking of some of the most relevant parameters was observed (radiation use efficiency shifted from 4th to 1st), without clear relationships between changes in rankings and differences in distributions for single traits. Ideotype profiles (i.e., values of the ideotype traits) were instead more consistent, although differences in trait values were found
Procrustes-based distances for exploring between-matrices similarity
The statistical shape analysis called Procrustes analysis minimizes the Frobenius distance between matrices by similarity transformations. The method returns a set of optimal orthogonal matrices, which project each matrix into a common space. This manuscript presents two types of distances derived from Procrustes analysis for exploring between-matrices similarity. The first one focuses on the residuals from the Procrustes analysis, i.e., the residual-based distance metric. In contrast, the second one exploits the fitted orthogonal matrices, i.e., the rotational-based distance metric. Thanks to these distances, similarity-based techniques such as the multidimensional scaling method can be applied to visualize and explore patterns and similarities among observations. The proposed distances result in being helpful in functional magnetic resonance imaging (fMRI) data analysis. The brain activation measured over space and time can be represented by a matrix. The proposed distances applied to a sample of subjects-i.e., matrices-revealed groups of individuals sharing patterns of neural brain activation. Finally, the proposed method is useful in several contexts when the aim is to analyze the similarity between high-dimensional matrices affected by functional misalignment
A comparison of macroscopic lipid content within porcine pulmonary and aortic valves: Implications for bioprosthetic valves
AbstractLipid droplets have been demonstrated within both explanted porcine bioprostheses and normal porcine aortic valves. Because of the increasing interest in pulmonary valves as an allograft or xenograft aortic valve substitute, we examined the incidence and distribution of such lipid deposits in 50 porcine aortic valves and 50 matched porcine pulmonary valves. All 300 cusps were removed with surgical scissors and, under a dissecting microscope, the ventricularis layer was removed to expose the spongiosal layer. Macroscopic extracellular lipid droplets were exposed. The position and amount of the visible unstained droplets were analyzed by means of a dissecting microscope with an eyepiece grid and stereology point-counting techniques to provide an area-density average spatial probability map for each cusp. Only 8% of porcine aortic valves were free of lipid, with the distribution of the lipids being 52% ± 14% right coronary cusp, 90% ± 8% left coronary cusp, and 68% ± 13% noncoronary cusp. Of the pulmonary valves, 60% were free of lipid, with the incidence of lipids being 26% ± 12% left cusp, 6% ± 7% right cusp, and 12% ± 9% anterior cusp. Subsequently, lipid cluster samples underwent thin-layer chromatography, which showed them to be phospholipids, oleic acid (fatty acid), triglycerides, and unesterified cholesterol. One primary mode of bioprosthetic valve failure is leaflet calcification. The similarity of distribution within the spongiosal layer between leaflet calcification and intrinsic cusp lipids suggests that the observed lipids might act as a nucleation site for calcification. The substantially lower incidence of lipid in pulmonary valves therefore may represent a potential benefit when these valves are considered for use as aortic valve replacements. (J THORAC CARDIOVASC SURG 1995;110:1756-61
Virtues and Flaws of the Pauli Potential
Quantum simulations of complex fermionic systems suffer from a variety of
challenging problems. In an effort to circumvent these challenges, simpler
``semi-classical'' approaches have been used to mimic fermionic correlations
through a fictitious ``Pauli potential''. In this contribution we examine two
issues. First, we address some of the inherent difficulties in a widely used
version of the Pauli potential. Second, we refine such a potential in a manner
consistent with the most basic properties of a cold Fermi gas, such as its
momentum distribution and its two-body correlation function.Comment: 16 pages, 6 figure
An enhanced component connection method for conversion of fault trees to binary decision diagrams
Fault Tree Analysis (FTA) is widely applied to assess the failure probability of industrial systems. Many computer packages are available which are based on conventional Kinetic Tree Theory methods. When dealing with large (possibly non-coherent) fault trees, the limitations of the technique in terms of accuracy of the solutions and the efficiency of the processing time becomes apparent. Over recent years the Binary Decision Diagram (BDD) method has been developed that solves fault trees and overcomes the disadvantages of the conventional FTA approach. First of all, a fault tree for a particular system failure mode is constructed and then converted to a BDD for analysis. This paper analyses alternative methods for the fault tree to BDD conversion process.
For most fault tree to BDD conversion approaches the basic events of the fault tree are placed in an ordering. This can dramatically affect the size of the final BDD and the success of qualitative and quantitative analyses of the system. A set of rules are then applied to each gate in the fault tree to generate the BDD. An alternative approach can also be used, where BDD constructs for each of the gate types are first built and then merged to represent a parent gate. A powerful and efficient property, sub-node sharing, is also incorporated in the enhanced method proposed in this paper. Finally a combined approach is developed taking the best features of the alternative methods. The efficiency of the techniques is analysed and discussed
Proton fraction in the inner neutron-star crust
Monte Carlo simulations of neutron-rich matter of relevance to the inner
neutron-star crust are performed for a system of A=5,000 nucleons. To determine
the proton fraction in the inner crust, numerical simulations are carried out
for a variety of densities and proton fractions. We conclude---as others have
before us using different techniques---that the proton fraction in the inner
stellar crust is very small. Given that the purported "nuclear pasta" phase in
stellar crusts develops as a consequence of the long-range Coulomb interaction
among protons, we question whether pasta formation is possible in such
proton-poor environments. To answer this question, we search for physical
observables sensitive to the transition between spherical nuclei and exotic
pasta structures. Of particular relevance is the static structure factor
S(k)---an observable sensitive to density fluctuations. However, no dramatic
behavior was observed in S(k). We regard the identification of physical
observables sensitive to the existence---or lack-thereof---of a pasta phase in
proton-poor environments as an open problem of critical importance.Comment: 24 pages and 7 figure
Learning from accidents: Analysis of multi-attribute events and implications to improve design and reduce human errors
High-technology accidents are likely to occur under a complex interaction of multiple active failures and latent conditions, and recent major accidents investigations are increasingly highlighting the role of human error or human-related factors as significant contributors. Latent conditions might have long incubation periods, which implies that a number of design failures may be embedded in systems until human errors trigger an accident sequence. Consequently, there is a need to scrutinise the relationship between enduring design deficiencies and human erroneous actions as a conceivable way to minimise accidents. This study will tackle this complex problem by applying an artificial neural network approach to a proprietary multi-attribute accident dataset, in order to disclose multidimensional relationships between human errors and design failures. Clustering and data mining results are interpreted to offer further insight into the latent conditions embedded in design. Implications to support the development of design failure prevention schemes are then discussed
Nonuniform Neutron-Rich Matter and Coherent Neutrino Scattering
Nonuniform neutron-rich matter present in both core-collapse supernovae and
neutron-star crusts is described in terms of a semiclassical model that
reproduces nuclear-matter properties and includes long-range Coulomb
interactions. The neutron-neutron correlation function and the corresponding
static structure factor are calculated from molecular dynamics simulations
involving 40,000 to 100,000 nucleons. The static structure factor describes
coherent neutrino scattering which is expected to dominate the neutrino
opacity. At low momentum transfers the static structure factor is found to be
small because of ion screening. In contrast, at intermediate momentum transfers
the static structure factor displays a large peak due to coherent scattering
from all the neutrons in a cluster. This peak moves to higher momentum
transfers and decreases in amplitude as the density increases. A large static
structure factor at zero momentum transfer, indicative of large density
fluctuations during a first-order phase transition, may increase the neutrino
opacity. However, no evidence of such an increase has been found. Therefore, it
is unlikely that the system undergoes a simple first-order phase transition. It
is found that corrections to the commonly used single heavy nucleus
approximation first appear at a density of the order of g/cm and
increase rapidly with increasing density. Thus, neutrino opacities are
overestimated in the single heavy nucleus approximation relative to the
complete molecular dynamics simulations.Comment: 17 pages, 23 included ps figure
Self-Consistent Separable Rpa Approach for Skyrme Forces: Axial Nuclei
The self-consistent separable RPA (random phase approximation) method is
formulated for Skyrme forces with pairing. The method is based on a general
self-consistent procedure for factorization of the two-body interaction. It is
relevant for various density- and current-dependent functionals. The
contributions of the time-even and time-odd Skyrme terms as well as of the
Coulomb and pairing terms to the residual interaction are taken
self-consistently into account. Most of the expression have a transparent
analytical form, which makes the method convenient for the treatment and
analysis. The separable character of the residual interaction allows to avoid
diagonalization of high-rank RPA matrices and thus to minimize the calculation
effort. The previous studies have demonstrated high numerical accuracy and
efficiency of the method for spherical nuclei. In this contribution, the method
is specified for axial nuclei. We provide systematic and detailed presentation
of formalism and discuss different aspects of the model.Comment: 42 page
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