Abstract

Building products designed at each level of detail provide single window solutions for Smart City applications. In view of this, the current study uses the tools and techniques to generate second level of detailed buildings that include building shape and height parameters. The extrusion from 2D has been performed altogether in multiple platforms and 3D data handling software. The basic inputs considered for extracting the polygon shapefiles are obtained from high-resolution stereo pair satellite images acquired using Cartosat-I imagery. Eight ground control points are collected using high precision Differential Global Positioning System having millimeters of accuracy. The image adjustments and Digital Surface Model are generated by using the process and concepts of Photogrammetry such as block creation using Rational Polynomial Coefficient text files, internal geometry set up such as interior and exterior orientation, Tie point generation and control point adjustments, and Automated Terrain Extraction. The thus obtained terrain model is overlaid on ortho photograph and the building heights are extracted and compared by using spatial profile graph as well as stereoscopic visualization methods. The height-derived attribute tables are attached to corresponding building footprints and are visualized in different GIS platforms.

Abstract

Building Information Modeling is a sophisticated technology possessing intellectual tools that help planners and architects to design sustainable buildings and carryout performance analysis based on various aspects. Apart from the existing building elements, a network connecting each building component is of vital importance in order to generate organized plans. Building Information Modeling when embedded with Geographic Information System delivers versatile applications in the world of both Geo Spatial field of studies as well as Architecture, Engineering and Construction Industry. The current research is one such attempt to understand the power of Geographic Information System tools in building models especially in solving complicated network connections. Designing the electrical network and planning the circuitry information in such a way so as to avoid faulty or poor connections in between the inter circuit elements is successfully achieved with the help of this integration. Initially, building model is generated to the high level of detail and electrical fixtures are organized with in a power distribution system using Revit Architecture. The virtual network wiring made in Building model is physically connected using three dimensional Polyline features in Geographic Information System platform and the created Network of electrical elements is utilized for Geometric Network Analysis.

Abstract

The entire Himalayan arc is predicted to produce a series of significant earthquakes and the subsequent great earthquakes of magnitude 8.0 and higher. A substantial amount of rock tunneling is being carried out in the Himalayan region to meet the growing demand for transportation, power, and other infrastructure projects. Earthquake forces influence the final design of the tunnel, which requires further strengthening of the concrete lining and improvement in tunnel support. Because of increasing importance, it is essential to combine the dynamic forces and displacements produced by seismic ground movements into the design stage for tunnels. In this paper, a numerical analysis has been carried out to assess the seismic performance of a proposed hydropower tunnel of 8.8m diameter (horseshoe-shape) in Uttarakhand, India. The impact of earthquakes on underground structures such as tunnels is often considered to be insignificant. However, the results of this study show how that stress from seismic loads can be damaging to the stability of the tunnel. In this study, a pseudo-static approach was adopted to assess the impact of the earthquake on the tunnel lining for the sections located in different rocks namely slate (Q=3.4), quartzite (Q=6), and dolomitic limestone (Q=5.2), respectively. Pseudo-static analysis findings suggest there is a 35% increase in the lining forces for an impact of earthquake for the tunnel section situated in Slate. Furthermore, displacements and damage-prone areas are determined to assess the damage to the tunnel, which could be helpful for rapid evaluations of potential future damage.

Abstract

Understanding the spatiotemporal distribution of blue-green infrastructures in urban environment is a critical element in the landscape-level planning. Asian cities, which are rapidly undergoing transformational changes in its land cover, predominantly feature urban signatures at the expenses of natural ecosystems. The rapid urbanization in conjunction with mega developmental projects and industrialization requires sophisticated analytical tools in the synoptic assessments and impact measurements. Remote sensing together with geographical information system (GIS) and Global Positioning Systems (GPS) plays an important role in developing the spatial maps and assessing the dynamics of land cover in the urban environment. This chapter reviews various remote sensing instruments available to characterize vegetation and water in complex urban environments. The progress with respect to diverse instruments such as panchromatic, multispectral, hyperspectral, radar, and LiDAR in mapping the blue-green infrastructures is reviewed in this chapter. The chapter helps in understanding the diverse initiatives and instruments in mapping the extent and quality of blue-green infrastructures which are vital for the spatial planning of urban landscapes.

Abstract

Understanding the nexus between land use land cover (LULC) and land surface temperature (LST) of a rapidly growing city may help planners mitigate the effects of uncontrolled urbanization on the micro- and macro-environment. The primary focus of the study is to monitor the transient LULC of Surat, one of the rapidly growing cities in India. To comprehend the urban dynamics, the study analyses the tri-decadal LULC of Surat using temporal Landsat imagery corresponding to 1990, 2001, 2009, and 2020. Besides classification of satellite data to derive LULC using the maximum likelihood algorithm, emphasis has been given to evaluate the normalized difference vegetation index and normalized difference built-up index, which help in differentiating vegetation and built-up from other land-use types. In addition, the LST of Surat is computed, and zonal analysis is performed to examine its association with LULC. Results show that the built-up area of Surat increased by 3.22 times during the considered time, while the aerial extent of vegetation decreased by 1.58 times. Future land-use dynamics are predicted using the Markov model. Findings revealed that the built-up area is expected to increase by 20% between 2020 and 2030, while the vegetation area is likely to decrease by 13%. The developed model attained an accuracy of 52.08%, which is in agreement with the past studies. The findings of this study help urban planners and stakeholders to devise effective policies that can mitigate the

Abstract

Response of Terahertz Protein Vibrations to Ligand Binding: Calmodulin–Peptide Complexes as a Case Study

Abstract

The last two decades have witnessed unprecedented advancements in computational techniques and artificial intelligence. These new developments will greatly impact biological data analyses for the health care system. The availability of large scale, high-throughput, biomedical data sets offers fertile ground for the application of AI-based techniques to extract valuable information that can be harnessed in the diagnosis and treatment of disease. This chapter provides a comprehensive review of the computational tools and online resources for the high-throughput analysis of biomedical data. It focuses on single-cell RNA sequencing data, multi-omics data integration, AI drug design, medical imaging data analysis, and the IoT. After providing a brief overview of fundamental biological terms, we describe a variety of research problems in the health care system and how high-throughput data can help. Next, we provide an in depth overview of machine learning techniques in computing and learning methods that can be used in sequencing data analyses (including profiles of traditional mass sequencing, single-cell data, interaction data, line-cell drugs, and medical imaging data). Finally, applications of IoT methods are discussed for biomedical research in detail. In conclusion, the review delineates the overall scope of AI-based computational techniques in biomedical research.

Abstract

A total of 2835 overseas patients from 55 countries received cancer treatment in two hospitals in Delhi, India between November 2013 and April 2019. Of these, 937 patients participated in a 30-point questionnaire on patient reported outcomes. The questionnaire included clinical information, difficulties, expenditure, financial toxicity (FT), education, profession/earning, family/emotional issues, and the reason for the choice of Delhi.

Abstract

RNAs are the major regulators of gene expression, and their secondary structures play crucial roles at different levels. RiboSNitches are disease-associated SNPs that cause changes in the pre-mRNA secondary structural ensemble. Several riboSNitches have been detected in the 5′ and 3′ untranslated regions and lncRNA. Although cases of secondary structural elements playing a regulatory role in alternative splicing are known, regions specific to splicing events, such as splice junctions have not received much attention. We tested splice-site mutations for their efficiency in disrupting the secondary structure and hypothesized that these could play a crucial role in alternative splicing. Multiple riboSNitch prediction methods were applied to obtain overlapping results that are potentially more reliable. Putative riboSNitches were identified from aberrant 5′ and 3′ splice site mutations, cancer-causing somatic mutations, and genes that harbor the regulatory RNA secondary structural elements. Our workflow for predicting riboSNitches associated with alternative splicing is novel and paves the way for subsequent experimental validation.

Abstract

Nucleocytoplasmic shuttling of viral elements, supported by several host factors, is essential for the replication of the human immunodeficiency virus (HIV). HIV-1 uses a nuclear RNA export pathway mediated by viral protein Rev to transport its Rev response element (RRE)-containing partially spliced and unspliced transcripts aided by the host nuclear RNA export protein CRM1. The factor(s) interacting with the CRM1-Rev complex are potential antiretroviral target(s) and could serve as a retroviral model system to study nuclear export machinery adapted by these viruses. We earlier reported that cellular Staufen-2 interacts with Rev, facilitating viral-RNA export. Here, we identified the formation of a complex between Staufen-2, CRM1 and Rev. Molecular docking and simulations mapped the interacting residues in the RNA-binding Domain 4 of Staufen-2 as R336 and R337, which were experimentally verified to be critical for interactions among Staufen-2, CRM1 and Rev by mutational analysis. Staufen-2 mutants defective in interaction with CRM1 or Rev failed to supplement the Rev-RNA export activity and viral production, demonstrating the importance of these interactions. Rev-dependent reporter assays and proviral DNA-construct transfection-based studies in Staufen-2 knockout cells in the presence of leptomycin-B (LMB) revealed a significant reduction in CRM1-mediated Rev-dependent RNA export with decreased virus production as compared to Staufen-2 knockout background or LMB treatment alone, suggesting the relevance of these interactions in augmenting RNA export activity of Rev. Our observations provide further insights into the mechanistic intricacies of unspliced viral-RNA export to the cytoplasm and support the notion that abrogating such interactions can reduce HIV-1 proliferation.