1,114 research outputs found
High rank tensor and spherical harmonic models for diffusion MRI processing
Diffusion tensor imaging (DTI) is a non-invasive quantitative method of characterizing tissue micro-structure. Diffusion imaging attempts to characterize the manner by which the water molecules within a particular location move within a given amount of time. Measurement of the diffusion tensor (D) within a voxel allows a macroscopic voxel-averaged description of fiber structure, orientation and fully quantitative evaluation of the microstructural features of healthy and diseased tissue.;The rank two tensor model is incapable of resolving multiple fiber orientations within an individual voxel. This shortcoming of single tensor model stems from the fact that the tensor possesses only a single orientational maximum. Several authors reported this non-mono-exponential behavior for the diffusion-induced attenuation in brain tissue in water and N-Acetyl Aspartate (NAA) signals, that is why the Multi-Tensor, Higher Rank Tensor and Orientation Distribution Function (ODF) were introduced.;Using the higher rank tensor, we will propose a scheme for tensor field interpolation which is inspired by subdivision surfaces in computer graphics. The method applies to Cartesian tensors of all ranks and imposes smoothness on the interpolated field by constraining the divergence and curl of the tensor field. Results demonstrate that the subdivision scheme can better preserve anisotropicity and interpolate rotations than some other interpolation methods. As one of the most important applications of DTI, fiber tractography was implemented to study the shape geometry changes. Based on the divergence and curl measurement, we will introduce new scalar measures that are sensitive to behaviors such as fiber bending and fanning.;Based on the ODF analysis, a new anisotropy measure that has the ability to describe multi-fiber heterogeneity while remaining rotationally invariant, will be introduced, which is a problem with many other anisotropy measures defined using the ODF. The performance of this novel measure is demonstrated for data with varying Signal to Noise Ratio (SNR), and different material characteristics
On classical n-absorbing submodules
In this paper, we introduce the notion of classical n-absorbing submodules of a module M over a commutative ring R with identity, which is a generalization of classical prime submodules. A proper submodule N of M is said to be classical n-absorbing if whenever a1a2... an+1 m in M, for a1a2... an+1 in R and m in M, then there are n of the ai's whose product with m is in N. We give some basic results concerning classical n-absorbing submodules. Then the classical n-absorbing avoidance theorem for submodules is proved. Finally, classical n-absorbing submodules in several classes of modules are studied
Assessment of Rework Probabilities for Simulating Product Development Processes Using the Design Structure Matrix (DSM)
This paper uses the Design Structure Matrix (DSM) to
model and simulate the performance of development processes.
Though the simulation is a powerful tool for analyzing process
performance, its ability is limited by the quality of input
information used in the analysis. DSM simulation requires
process data that is hard to assess or estimate directly from
development participants. In this paper, we propose a
methodology that allows a more practical estimation of an
important simulation parameter: rework probabilities.
Furthermore, we show how does this assessment method
(combined with simulation) allow managers to evaluate process
improvement plans based on two resulting process measures:
reliability and robustness. The method is illustrated with a real
application from the automotive industry
Computational screening of known broad-spectrum antiviral small organic molecules for potential influenza HA stem inhibitors.
With the emergence of new influenza virus strains that are resistant to current inhibitors such as oseltamivir (anti-neuraminidase (NA)) and amantadine (anti-M2 proton channel), influenza A viruses continue to be a serious threat to the public health worldwide. With this in view, there is a persistent need for the development of broader and more effective vaccines and therapeutics. Identification of broadly neutralizing antibodies (bNAbs) that recognize relatively invariant structures on influenza haemagglutinin (HA) stem has invigorated efforts to develop universal influenza vaccines. The current computational study is designed to identify potential flavonoid inhibitors that bind to the contact epitopes of HA stem that are targeted by broadly neutralizing antibodies (bNAb). In this study, we utilized the three-dimensional crystallographic structure of different HA subtypes (H1, H2, H5, H3, and H7) in complex with bNAb to screen for potential broadly reactive influenza inhibitors. We performed Quantitative Structure-Activity and Relationship (QSAR) for 100 natural compounds known for their antiviral activity and performed molecular docking using AutoDock 4.2 suite. Furthermore, we conducted virtual screening of 1413 bioassay hit compounds by using virtual lab bench CLC Drug Discovery. The results showed 18 lead flavonoids with strong binding abilities to bNAb epitopes of various HA subtypes. These 18 broadly reactive compounds exhibited significant interactions with an average of seven Hbonds, docking energy of -22.43 kcal·mol-1, and minimum interaction energy of -4.65 kcal·mol-1, with functional contact residues. Procyanidin depicted strong interactions with group 1 HAs, whereas both sorbitol and procyanidin exhibited significant interactions with group 2 HAs. Using in silico docking analysis, we identified 18 bioactive flavonoids with potential strong binding cababilities to influenza HA-stems of various subtypes, which are the target for bNAb. The virtual screened bioassay hit compounds depicted a high number of Hbonds but low interaction and docking values compared to antiviral flavonoids. Using structure-based design and nanotechnology-based approaches, identified molecules could be modified to generate next generation anti-influenza drugs
Do-It-Right-Fisrt-Time (DRFT) Approach to DSF Restructuring
In this paper, we argue, using two real-world applications from the automotive industry, that the biggest benefit of a Design Structure Matrix (DSM) model may come not from resequencing and partitioning, but rather from “rewiring” the process/blocks. By “rewiring” we mean redefining relationships among elements and/or inserting new elements into the matrix. This requires intimate understanding of the process and cannot be done with application of context-free partitioning algorithms.
The Do-it-Right-First-Time (DRFT) approach to DSM restructuring is another way to look at a DSM by inspecting the sources of iteration within a block and reversing it through inserting a DRFT activity at the beginning of the block. In other words, we reverse the traditional Design-Build-Test “Cycle” into a DRFT-Design-Build “Sequence”. That is, the "wiring diagram" of a process or system overpowers the behavior of the individual nodes, so changing the system requires changing the wiring
Do-It-Right-First-Time (Draft) Approach To Design Structure Matrix (DSM) Restructuring
This paper argues, using two real-world applications from
the automotive industry, that the biggest benefit of a Design
Structure Matrix (DSM) model may come not from resequencing
and partitioning, but rather from rewiring the
process/blocks. Rewiring means redefining relationships
among elements and/or inserting new elements into the
matrix. This requires intimate understanding of the process
and cannot be done with application of context-free
partitioning algorithms.
The Do-it-Right-First-Time (DRFT) approach to DSM
restructuring is another way to look at a DSM by inspecting
the sources of iteration within a block and reversing it through
inserting a DRFT activity at the beginning of the block. In this
way, the traditional Design-Build-Test Cycle is reversed into
a DRFT-Design-Build Sequence." That is, the "wiring
diagram" of a process or system overpowers the behavior of the
individual nodes, so changing the system requires changing
the wiring
Les abcès froids pariétaux thoraciques chez les sujets immunocompétents
Les abcès froids de la paroi thoracique représentent une forme rare et inhabituelle de tuberculose extrapulmonaire. Sa fréquence est estimée àmoins de 5% des tuberculoses ostéoarticulaires, évaluées elles-mêmes à 15% des tuberculoses extrapulmonaires. L'objectif de ce travail est derapporter la prise en charge diagnostique et thérapeutique de cette localisation dans notre structure. Etude rétrospective portant sur 18 cascolligés au service des maladies respiratoires du centre hospitalier universitaire Ibn Rochd de Casablanca, sur une période de 13 ans. La moyenne d'âge était de 34 ans (21-57). Un antécédent de tuberculose traitée était relevé dans un cas. Le tableau clinique était révélé par l'apparition insidieuse d'une masse pariétale de taille, de consistance et de siège variables. A l'imagerie thoracique, l'abcès pariétal était associé à une lyse osseuse dans sept cas, une atteinte parenchymateuse et pleurale dans quatre cas chacune et des adénopathies médiastinales dans deux cas. La confirmation diagnostique était bactériologique et/ou histologique dans tous les cas. La sérologie du virus de l'immunodéficience humaineétait négative chez tous nos malades. L'évolution sous traitement antibacillaire couplé ou non à une résection chirurgicale était favorable chez tous nos malades. Malgré la fréquence de la tuberculose dans notre contexte, la localisation pariétale thoracique reste rare, survenant chez une population non immunodéprimée et non toxicomane, contrairement à ce qui est souvent rapporté dans la littérature. Les abcès froids tuberculeuxreprésentent une forme rare de tuberculose extrapulmonaire dont l'évolution reste favorable sous traitement précoce et bien conduit
- …