Study of G + 20 Storey RC Framed Structure With Structural Steel Braces

Earthquake is that the one of the main disaster better-known to mankind since a few years, there has been a considerable contribution from earthquake engineers for the protection of the structure. one amongst the alternatives to reduce the harm caused due to the earthquake is adopting steel bracings within the structure. These members is used within the building as a horizontal load resisting system to enhance the stiffness of the frame for seismic forces. this study is based on analysis of RC framed G+20 storey structure with steel braces using ETABS software. This study is conducted to know the behaviour of the various bracing system for different direction of the building. The building is situated in ZONE 5. The performance of building is studied in terms of Base shear, Base moment, Storey shear, Storey moment, Maximum displacement, Drift. The results of the analysis are compared and it was found that the seismal behavior of braced framed building is improved as compared to unbraced framed building. it had been also found that the various arrangements of bracing systems have great influence on seismic performance of the building. In this study considering the shape irregularity, mass irregularity.

Estimation of Liquid Fraction of Wet Snow by Using 2-D Video Disdrometer and S-Band Weather Radar

Wet snow may cause significant damage to humans and property, and thus, it is necessary to estimate the corresponding liquid fraction (FL). Consequently, the FL of wet snow was estimated using a novel technique; specifically, the particle shape irregularity (Ir) was estimated through the particle coordinate information obtained using 2-D video disdrometer (2DVD) measurements. Moreover, the possibility of quantitively estimating FL via Ir, based on the temperature (T), was examined. Eight snowfall cases from 2014 to 2016 were observed through a 2DVD installed in Jincheon, South Korea, to analyze the dominant properties of physical variables of snowflakes (i.e., the terminal velocity (VT), particle density (ρs), Ir, and FL) and the corresponding relationships according to the T ranges (−4.5 < T (°C) < 2.5) in which wet snow can occur. It was clarified that the volume-equivalent particle diameter (D)–FL and D–Ir relationships depended on T, and a relationship existed between Ir and FL. The analysis results were verified using the Yong-In Testbed (YIT) S-band weather radar and T-matrix scattering simulation. The D–FL relationship was implemented in the scattering simulation, and the results indicated that the simulated reflectivity (ZS) was highly correlated with the observed reflectivity (ZO) under all T classes. These features can provide a basis for radar analysis and quantitative snowfall estimation for wet snow with various FL values.

Replacement in a Plane Geared Linkage of High Kinematic Pairs with Lower Pairs

The analysis of constraints in plane mechanisms is an urgent problem in the theory of machines and mechanisms. Although kinematic pairs’ classification has been known for a long time, the issue of the conjugation of links, being at the heart of the analysis and synthesis of mechanisms and machines, is of considerable theoretical and practical interest and continues to attract scientists. One of the tasks that are solved in the process of analysis and synthesis of the structures of mechanisms is the re-placement of higher kinematic pairs by lower ones. As a rule, such a replacement is made to identify kinematic chains of zero mobility, Assur's structural groups, in a mechanism. The replacement may also aim at obtaining the necessary kinematic relations. That is because specific computational difficulties hamper the kinematic analysis of chains with higher kinematic pairs due to the relative sliding and shape irregularity of mating surfaces. Yet, the use of replacements to obtain kinematic and transmission functions is difficult due to nonisomorphism of the equivalent mechanism. Simultaneously, for mixed-type mechanisms, which include geared linkages, the equivalent replacement will allow unifying the kinematic analysis methods. The paper suggests the technology of replacing higher kinematic pairs with links with lower pairs as applied to a plane geared linkage. The technology is based on the properties of the involute of a circumference. The paper proved the structural and kinematic equivalence of such a replacement. The isomorphism of the equivalent linkage will enhance the kinematic analysis, make it possible using kinematic functions, and applying methods based on the instantaneous relative rotations of links, in particular, the Aronhold-Kennedy theorem. Another application of the replacement method presented in the paper will be the expansion of opportunities for identifying idle constraints in the mechanism.

Spatiotemporal Change of Urban Sprawl Patterns in Bamako District in Mali Based on Time Series Analysis

For decades, urban sprawl has remained a major challenge for big cities in developing countries, such as Bamako. The aim of this study is to analyze urban sprawl pattern changes over time in the Bamako district using landscape index analyses. Four thematic maps of land cover (LC) were produced by applying the maximum likelihood supervised classification method on Landsat images for 1990, 2000, 2010, and 2018. Five landscape indexes were selected and calculated at class level and landscape level using FRAGSTATS software. The results showed that the dominant class for all the years within the landscape was a built-up class. Forest class covered the smallest area in terms of the percentage of land (%PLAND), and was the weakest class in terms of number of patches (NP) and largest patch index (LPI). Grassland is defined as the class with the highest fragmentation, farmland with the highest shape irregularity and more heterogeneity, and built-up with the highest patches. Class area (CA) of built-up showed the importance of sprawl in Communes 6, 5, and 4, respectively. Indices trends and land use/cover showed infill, scattered, and ribbon developments of sprawl. This study contributes toward monitoring long-term urban sprawl patterns using index analyses.

NIMG-57. ASSOCIATION OF RADIOMICS BASED TUMOR SHAPE IRREGULARITY MEASURES AND GAMMA KNIFE DOSE PLANNING INDICES IN VESTIBULAR SCHWANNOMAS

Gamma knife radiosurgery (GKRS) delivers an unevenly distributed radiation dose to a tumor, with a sharp falloff outside the target. Although the dose inhomogeneity within a tumor is strongly influenced by its shape, routine GKRS dose planning does not account for it. We hypothesized that shape irregularity measures were correlated with treatment planning indices, and might provide insight during treatment planning. The aims of this study were to quantify the shape irregularity measures in vestibular schwannomas, estimate their correlations with core radiosurgical planning measures, and define the most predictive shape feature for dose effectiveness. METHODS: Four dose plan indices, which were the selectivity index (SI), gradient index (GI), efficiency index (EI), and Paddick’s conformity index (PCI) were estimated from the GKRS plans of 234 vestibular schwannomas. All dose plans were prepared using Gamma Plan 10.0 and above and all treatments were delivered using a perfexion/ICON platform. Three-dimensional (3D) tumor models were rendered using 3D Slicer Software from segmented T1-weighted MR images. Sixteen irregularity measures were calculated for each tumor using Radiomics in MATLAB. Spearman correlation coefficients (r) were computed to find associations of the dose plan indices with the irregularity descriptors. The most predictive shape feature for dose efficiency was identified using the least absolute shrinkage and selection operator (Lasso). RESULTS: The shape irregularity measures were negatively correlated with SI, EI, and PCI, and positively correlated with GI. Volumetric index of sphericity (VioS) had the highest correlations with SI (r = 0.63, p= 3.27E-23), GI (r= -0.58, p= 1.10E-19), EI (r = 0.69, p= 0.00), and PCI(r= 0.68, p = 6.73E-28), and Lasso feature selection identified VioS as the most important feature for predicting all dose plan indices. CONCLUSION: VioS provides a numerical quantification of tumor shape irregularity, and it is highly correlated with the GKRS dose planning indices. *indicates co-senior authors

Testing the Ability of Convolutional Neural Networks to Learn Radiomic Features

Purpose: To test the ability of convolutional neural networks (CNNs) to effectively capture the intensity, shape, and texture properties of tumors as defined by standardized radiomic features. Methods: Standard 2D and 3D CNN architectures with an increasing number of convolutional layers (up to 9) were trained to predict the values of 16 standardized radiomic features from synthetic images of tumors, and tested. In addition, several ImageNet-pretrained state-of-the-art networks were tested. The synthetic images replicated the quality of real PET images. A total of 4000 images were used for training, 500 for validation, and 500 for testing. Results: Radiomic features quantifying tumor size and intensity were predicted with high accuracy, while shape irregularity features had very high prediction errors and generalized poorly between training and test sets. For example, mean normalized prediction error of tumor diameter (mean intensity) with a 5-layer 2D CNN was 4.23 ± 0.25 (1.88 ± 0.07), while the error for tumor sphericity was 15.64 ± 0.93. Similarly-high error values were found with other shape irregularity and heterogeneity features, both with standard and state-of-the-art networks. Conclusions: Standard CNN architectures and ImageNet-pretrained advanced networks have a significantly lower capacity to capture tumor shape and heterogeneity properties compared to other features. Our findings imply that CNNs trained end-to-end for clinical outcome prediction and other tasks may under-utilize tumor shape and texture information. We hypothesize, that to improve CNN performance, these radiomic features can be computed explicitly and added as auxiliary variables to the dense layers in the networks, or as additional input channels.

Valproic Acid-Induced Changes of 4D Nuclear Morphology in Astrocyte Cells

Histone deacetylase inhibitors, such as valproic acid (VPA), have important clinical implications as human therapeutics and cellular reprogramming agents. They induce chromatin re-organization associated with changes in cell nuclear morphology. Current approaches aiming to quantify these changes so far have been limited to basic 2D measures. Here, we quantified changes in 3D nuclear morphology of primary human astrocyte cells treated with VPA for 7 days (hence, 4D). We compared volumetric and surface-based 3D shape representations of cell nuclei and selected subset of features that jointly discriminated between normal and treated cells with 85% accuracy on day 7. Over time, VPA-treated nuclear morphologies progressed towards larger size and higher shape irregularity. On day 7, all 11 selected size and shape descriptors demonstrated significant difference between treated and untreated nuclear morphologies, including 22.5% increase in volume and 8.3% reduction in extent (shape regularity) for VPA-treated nuclei. Overall, we showed that 4D surface morphometry accurately characterizes the temporal changes in astrocyte nuclear form that are reflective of the underlying valproate-induced chromatin re-organization. These nuclear structural alterations may serve as a biomarker for histone (de-)acetylation events and provide insights into mechanisms of astrocytes-to-neurons reprogramming.

Relation of Intracerebral Hemorrhage Descriptors with Clinical Factors

The association between intracerebral hemorrhage (ICH) shape and a poor treatment outcome has been established by few authors. We decided to analyze whether computationally assessed hemorrhage shape irregularity is associated with any known predictors of its poor treatment outcome. We retrospectively analyzed 48 patients with spontaneous intracerebral hemorrhage. For each patient we calculated Fractal Dimension, Compactness, Fourier Factor and Circle Factor. Our study showed that patients above 65 years old had significantly higher Compactness (0.70 ± 0.19 vs. 0.56 ± 0.20; p < 0.01), Fractal Dimension (0.46 ± 0.22 vs. 0.32 ± 0.20; p = 0.03) and Circle Factor (0.51 ± 0.25 vs. 0.35 ± 0.17; p < 0.01). Patients with hemorrhage growth had significantly higher Compactness (0.74 ± 0.23 vs. 0.58 ± 0.18; p < 0.01), Circle Factor (0.55 ± 0.27 vs. 0.37 ± 0.18; p < 0.01) and Fourier Factor (0.96 ± 0.06 vs. 0.84 ± 0.19; p = 0.03). In conclusion, irregularity resulting from the number of appendices can be a predictor of ICH growth; however, the size of those appendices is also important. Shape roughness better reflects the severity of brain tissue damage and a patient’s general condition.