116 research outputs found
Turing patterns in multiplex networks
The theory of patterns formation for a reaction-diffusion system defined on a
multiplex is developed by means of a perturbative approach. The intra-layer
diffusion constants act as small parameter in the expansion and the unperturbed
state coincides with the limiting setting where the multiplex layers are
decoupled. The interaction between adjacent layers can seed the instability of
an homogeneous fixed point, yielding self-organized patterns which are instead
impeded in the limit of decoupled layers. Patterns on individual layers can
also fade away due to cross-talking between layers. Analytical results are
compared to direct simulations
Pattern formation for reactive species undergoing anisotropic diffusion
Turing instabilities for a two species reaction-diffusion systems is studied
under anisotropic diffusion. More specifically, the diffusion constants which
characterize the ability of the species to relocate in space are direction
sensitive. Under this working hypothesis, the conditions for the onset of the
instability are mathematically derived and numerically validated. Patterns
which closely resemble those obtained in the classical context of isotropic
diffusion, develop when the usual Turing condition is violated, along one of
the two accessible directions of migration. Remarkably, the instability can
also set in when the activator diffuses faster than the inhibitor, along the
direction for which the usual Turing conditions are not matched
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Implementation of simulation software packages for healthcare scheduling
Simulation methodology is considered an effective decision making tool in the process of patient scheduling in healthcare centers. In spite of the large number of simulation software packages that are commercially available, operation researches still are facing difficulties to implement simulation models in healthcare centers. In many cases, healthcare schedulers must spend extra efforts trying to mold scheduling requirements to conform to the features of the package. In this paper, we offer a systematic approach that can be used by practitioners to successfully adopt the available software simulation packages, develop simulation models, and transform their findings into practical scheduling rules. A radiology center in a Midwestern Hospital is used to illustrate the proposed methodology
Generative design of 3D printed hands-free door handles for reduction of contagion risk in public buildings
During the emergency caused by COVID 19 evidence has been provided about the risk of easily getting the virus by touching contaminated surfaces and then by touching eyes, mouth, or nose with infected hands. In view of the restarting of daily activities in presence, it is paramount to put in place any strategy that, in addition to social distancing, is capable to positively impact on the safety levels in public buildings by reducing such risk. The main aim of this paper is to conceive a design methodology, based on a digital, flawless, and sustainable procedure, for producing human-building interfacing solutions that allow anybody to interact in a safer and more comfortable way. Such solutions are focused on the adaptation of existing buildings features and are thought to be an alternative to sensor based touchless technology when this is not applicable due to economic or time constraints. The process is based on the integration of digital technologies such as 3D Scanning, Generative Design and Additive Manufacturing and is optimised to be intuitive and to be adaptive, hence, to be replicable on different kinds of surfaces. The design concept is finalised to generate automatically different products that meet geometry fitting requirements and therefore adapt to the specific geometries of existing handles. A specific case on Hands Free Door Handles is presented and the results of manufacturing and preliminary validation process are provided and discussed
Avalanche ruggedness of parallel SiC power MOSFETs
© 2018 Elsevier Ltd The aim of this paper is to investigate the impact of electro-thermal device parameter spread on the avalanche ruggedness of parallel silicon carbide (SiC) power MOSFETs representative of multi-chip layout within an integrated power module. The tests were conducted on second generation 1200 V, 36 A–80 mΩ rated devices. Different temperature-dependent electrical parameters were identified and measured for a number of devices. The influence of spread in measured parameters was investigated experimentally during avalanche breakdown transient switching events and important findings have been highlighted
Anatomy-driven modelling of spatial correlation for regularisation of arterial spin labelling images
Arterial spin labelling (ASL) allows blood flow to be measured in the brain and other organs of the body, which is valuable for both research and clinical use. Unfortunately, ASL suffers from an inherently low signal to noise ratio, necessitating methodological advances in ASL acquisition and processing. Spatial regularisation improves the effective signal to noise ratio, and is a common step in ASL processing. However, the standard spatial regularisation technique requires a manually-specified smoothing kernel of an arbitrary size, and can lead to loss of fine detail. Here, we present a Bayesian model of spatial correlation, which uses anatomical information from structural images to perform principled spatial regularisation, modelling the underlying signal and removing the need to set arbitrary smoothing parameters. Using data from a large cohort (N = 130) of preterm-born adolescents and age-matched controls, we show our method yields significant improvements in test-retest reproducibility, increasing the correlation coefficient by 14% relative to Gaussian smoothing and giving a corresponding improvement in statistical power. This novel technique has the potential to significantly improve single inversion time ASL studies, allowing more reliable detection of perfusion differences with a smaller number of subjects
Spatial coefficient of variation of arterial spin labeling MRI as a cerebrovascular correlate of carotid occlusive disease
Clinical interpretation of arterial spin labeling (ASL) perfusion MRI in cerebrovascular disease remains challenging mainly because of the method’s sensitivity to concomitant contributions from both intravascular and tissue compartments. While acquisition of multi-delay images can differentiate between the two contributions, the prolonged acquisition is prone to artifacts and not practical for clinical applications. Here, the utility of the spatial coefficient of variation (sCoV) of a single-delay ASL image as a marker of the intravascular contribution was evaluated by testing the hypothesis that sCoV can detect the effects of differences in label arrival times between ipsi- and contra-lateral hemispheres even in the absence of a hemispheric difference in CBF. Hemispheric lateralization values for sCoV and CBF were computed from ASL images acquired on 28 patients (age 73.9 ± 10.2 years, 8 women) with asymptomatic unilateral carotid occlusion. The results showed that sCoV lateralization predicted the occluded side with 96.4% sensitivity, missing only 1 patient. In contrast, the sensitivity of the CBF lateralization was 71.4%, with 8 patients showing no difference in CBF between hemispheres. The findings demonstrate the potential clinical utility of sCoV as a cerebrovascular correlate of large vessel disease. Using sCoV in tandem with CBF, vascular information can be obtained in image processing without the need for additional scan-time
Partial Volume Correction in Arterial Spin Labeling Perfusion MRI: A method to disentangle anatomy from physiology or an analysis step too far?
The mismatch in the spatial resolution of Arterial Spin Labeling (ASL) MRI perfusion images and the anatomy of functionally distinct tissues in the brain leads to a partial volume effect (PVE), which in turn confounds the estimation of perfusion to a specific tissue of interest such as grey or white matter. This confound occurs because the image voxels contain a mixture of tissues with disparate perfusion properties, leading to estimated perfusion values that reflect primarily the volume proportions of tissues in the voxel rather than the perfusion of any particular tissue of interest within that volume. It is already recognized that PVE influences studies of brain perfusion, and that its effect might be even more evident in studies where changes in perfusion are co-incident with alterations in brain structure, such as studies involving a comparison between an atrophic patient population vs control subjects, or studies comparing subjects over a wide range of ages. However, the application of PVE correction (PVEc) is currently limited and the employed methodologies remain inconsistent. In this article, we outline the influence of PVE in ASL measurements of perfusion, explain the main principles of PVEc, and provide a critique of the current state of the art for the use of such methods. Furthermore, we examine the current use of PVEc in perfusion studies and whether there is evidence to support its wider adoption. We conclude that there is sound theoretical motivation for the use of PVEc alongside conventional, 'uncorrected', images, and encourage such combined reporting. Methods for PVEc are now available within standard neuroimaging toolboxes, which makes our recommendation straightforward to implement. However, there is still more work to be done to establish the value of PVEc as well as the efficacy and robustness of existing PVEc methods
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