Discrete Vortex Prediction of Flows around a Cylinder Near a Wall Using Overlapping Grid System

Modelling of unidirectional and oscillatory flows around a cylinder near a wall using an overlapping grid system is carried out. The circular grid system of the cylinder was overlapped with the rectangular grid system of the wall. The use of such an overlapping grid system is intended to reduce the CPU time compared to the cloud scheme in which vortex-to-vortex interaction is used, i.e., especially in calculating the shedding vortex velocity, since calculating the vortices velocity takes the longest CPU time. This method is not only time efficient, but also gives a better distribution of surface vorticity as the scattered vortices around the body are now concentrated on a grid point. Therefore, grid-to-grid interaction is used instead of vortex-to-vortex interaction. Velocity calculation was also carried out using this overlapping grid in which the new incremental shift position was summed up to obtain the total new vortices position. The engineering applications of this topic are to simulate the loading of submarine pipeline placed close to the seabed or to simulate the flow as a result of the scouring process below the cylinder since there is space for the fluid to flow beneath it. The in-line and transverse force coefficients are found by integrating the pressure around the cylinder surface. The flow patterns are then obtained and presented. The comparison of the results with experimental evidence is presented and the range of good results is discussed.

Deep Learning-Based Segmentation and Quantification of Retinal Capillary Non-Perfusion on Ultra-Wide-Field Retinal Fluorescein Angiography

Reliable outcome measures are required for clinical trials investigating novel agents for preventing progression of capillary non-perfusion (CNP) in retinal vascular diseases. Currently, accurate quantification of topographical distribution of CNP on ultrawide field fluorescein angiography (UWF-FA) by retinal experts is subjective and lack standardisation. A U-net style network was trained to extract a dense segmentation of CNP from a newly created dataset of 75 UWF-FA images. A subset of 20 images was also segmented by a second expert grader for inter-grader reliability evaluation. Further, a circular grid centred on the FAZ was used to provide standardised CNP distribution analysis. The model for dense segmentation was five-fold cross-validated achieving area under the receiving operating characteristic of 0.82 (0.03) and area under precision-recall curve 0.73 (0.05). Inter-grader assessment on the 20 image subset achieves: precision 59.34 (10.92), recall 76.99 (12.5), and dice similarity coefficient (DSC) 65.51 (4.91), and the centred operating point of the automated model reached: precision 64.41 (13.66), recall 70.02 (16.2), and DSC 66.09 (13.32). Agreement of CNP grid assessment reached: Kappa 0.55 (0.03), perfused intraclass correlation (ICC) 0.89 (0.77, 0.93), non-perfused ICC 0.86 (0.73, 0.92), inter-grader agreement of CNP grid assessment values are Kappa 0.43 (0.03), perfused ICC 0.70 (0.48, 0.83), non-perfused ICC 0.71 (0.48, 0.83). Automated dense segmentation of CNP in UWF-FA images achieves performance levels comparable to inter-grader agreement values. A grid placed on the deep learning-based automatic segmentation of CNP generates a reliable and quantifiable method of measurement of CNP, to overcome the subjectivity of human graders.

A 360° electronic device for recording high-resolution intraoperative electrocorticography of the brain during awake craniotomy

OBJECTIVEEpilepsy is common among patients with supratentorial brain tumors; approximately 40%–70% of patients with glioma develop brain tumor–related epilepsy (BTRE). Intraoperative localization of the epileptogenic zone during surgical tumor resection (real-time data) may improve intervention techniques in patients with lesional epilepsy, including BTRE. Accurate localization of the epileptogenic signals requires electrodes with high-density spatial organization that must be placed on the cortical surface during surgery. The authors investigated a 360° high-density ring-shaped cortical electrode assembly device, called the “circular grid,” that allows for simultaneous tumor resection and real-time electrophysiology data recording from the brain surface.METHODSThe authors collected data from 99 patients who underwent awake craniotomy from January 2008 to December 2018 (29 patients with the circular grid and 70 patients with strip electrodes), of whom 50 patients were matched-pair analyzed (25 patients with the circular grid and 25 patients with strip electrodes). Multiple variables were then retrospectively assessed to determine if utilization of this device provides more accurate real-time data and improves patient outcomes.RESULTSMatched-pair analysis showed higher extent of resection (p = 0.03) and a shorter transient motor recovery period during the hospitalization course (by approximately 6.6 days, p ≤ 0.05) in the circular grid patients. Postoperative versus preoperative Karnofsky Performance Scale (KPS) score difference/drop was greater for the strip electrode patients (p = 0.007). No significant difference in postoperative seizures between the 2 groups was present (p = 0.80).CONCLUSIONSThe circular grid is a safe, feasible tool that grants direct access to the cortical surgical surface for tissue resection while simultaneously monitoring electrical activity. Application of the circular grid to different brain pathologies may improve intraoperative epileptogenic detection accuracy and functional outcomes, while decreasing postoperative complications.

A Novel Method of Residual Strain Analysis Via a Non-Bonded Interface Technique in Combination With the Circular Grid Analysis Method

A novel non-bonded interface technique (NBIT) is used to analyze internal residual strain by combining a pre-split sample of AISI 4340 steel with the circular grid residual strain analysis technique. NBIT is compared with an implicit non-linear finite element (FE) model using LS-DYNA. A split FE model was compared with a quarter FE model to determine the split interface that causes an average difference of 9.0% on the residual von Mises strain field from a 588.6 N indentation. The homogeneous FE quarter model was then compared with the experimental split model using 588.6, 981.0, and 1471.5 N indentation forces. An average displacement difference of 3.92 µm was found when comparing the experimental split and FE homogeneous samples from a 588.6 N indentation. The internal residual major and minor principal strains from the split experimental sample and homogeneous FE model were compared for each indentation force. The minor principal strain results show the 588.6, 981.0, and 1471.5 N indentation forces resulted in a difference between the experimental split and homogeneous FE model of 28.5%, 34.8%, and 26.0%, respectively. The difference between the comparisons was explained by the inability of the FE model to simulate local non-homogeneous material properties such as grain composition and orientation whereas NBIT does. NBIT can be used for micro- or macro-scale residual strain analysis as the spatial resolution is highly adjustable.

Altered neural odometry in the vertical dimension

Entorhinal grid cells integrate sensory and self-motion inputs to provide a spatial metric of a characteristic scale. One function of this metric may be to help localize the firing fields of hippocampal place cells during formation and use of the hippocampal spatial representation (“cognitive map”). Of theoretical importance is the question of how this metric, and the resulting map, is configured in 3D space. We find here that when the body plane is vertical as rats climb a wall, grid cells produce stable, almost-circular grid-cell firing fields. This contrasts with previous findings when the body was aligned horizontally during vertical exploration, suggesting a role for the body plane in orienting the plane of the grid cell map. However, in the present experiment, the fields on the wall were fewer and larger, suggesting an altered or absent odometric (distance-measuring) process. Several physiological indices of running speed in the entorhinal cortex showed reduced gain, which may explain the enlarged grid pattern. Hippocampal place fields were found to be sparser but unchanged in size/shape. Together, these observations suggest that the orientation and scale of the grid cell map, at least on a surface, are determined by an interaction between egocentric information (the body plane) and allocentric information (the gravity axis). This may be mediated by the different sensory or locomotor information available on a vertical surface and means that the resulting map has different properties on a vertical plane than a horizontal plane (i.e., is anisotropic).

Approximation of a Complex Geometric Domain in Polar Coordinates

In this study, a complex geometric domain having a colour picture is approximated through a stair- step representation of the coastal and island boundaries to make it suitable for implementing finite difference method in solving shallow water equations (SWEs) in polar coordinates. As a complex domain, we choose the coastal region of Bangladesh situated at the northern tip of the Bay of Bengal (BOB). To cover the whole coastal region, the pole is selected at the point in the plane assuming it on the mean sea level (MSL). Along the tangential direction, 265 uniformly distributive straight lines are considered through the pole and 959 circular grid lines centered at are drawn towards the radial direction covering up to latitude in the BOB. Firstly, a matrix with 960´265 computational grids is constructed from the colour information of the picture. By representing the grids with suitable notations, a proper stair-step algorithm is employed to the matrix obtained with the 960´265 grids to approximate the coastal and island boundaries to the nearest finite difference grid lines using an Arakawa C-grid system. The whole procedure is done with our developed MATLAB program. The grids representing the coastal stations are also identified closely in the obtained approximated domain. Such a type of presentation of the coastal geometry of the region of interest is found to incorporate its complexities properly with minimum computational grid points. GANIT J. Bangladesh Math. Soc.Vol. 38 (2018) 105-118

Spatiotemporal Analysis of Near-Miss Violent Tornadoes in the United States

In the hazards literature, a near-miss is defined as an event that had a nontrivial probability of causing loss of life or property but did not due to chance. Frequent near-misses can desensitize the public to tornado risk and reduce responses to warnings. Violent tornadoes rarely hit densely populated areas, but when they do they can cause substantial loss of life. It is unknown how frequently violent tornadoes narrowly miss a populated area. To address this question, this study looks at the spatial distribution of possible exposures of people to violent tornadoes in the United States. We collected and replicated tornado footprints for all reported U.S. violent tornadoes between 1995 and 2016, across a uniform circular grid, with a radius of 40 km and a resolution of 0.5 km, surrounding the centroid of the original footprint. We then estimated the number of people exposed to each tornado footprint using proportional allocation. We found that violent tornadoes tended to touch down in less populated areas with only 33.1% potentially impacting 5000 persons or more. Hits and near-misses were most common in the Southern Plains and Southeast United States with the highest risk in central Oklahoma and northern Alabama. Knowledge about the location of frequent near-misses can help emergency managers and risk communicators target communities that might be more vulnerable, due to an underestimation of tornado risk, for educational campaigns. By increasing educational efforts in these high-risk areas, it might be possible to improve local knowledge and reduce casualties when violent tornadoes do hit.