The utility of built environment geospatial data for high-resolution dasymetric global population modeling

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The viral outbreak started in late 2019 and rapidly became a serious health threat to the global population. COVID-19 was declared a pandemic by the World Health Organization in March 2020. Several therapeutic options have been adopted to prevent the spread of the virus. Although vaccines have been developed, antivirals are still needed to combat the infection of this virus. SARS-CoV-2 is an enveloped virus, and its genome encodes polyproteins that can be processed into structural and nonstructural proteins. Maturation of viral proteins requires cleavages by proteases. Therefore, the main protease (3 chymotrypsin-like protease (3CLpro) or Mpro) encoded by the viral genome is an attractive drug target because it plays an important role in cleaving viral polyproteins into functional proteins. Inhibiting this enzyme is an efficient strategy to block viral replication. Structural studies provide valuable insight into the function of this protease and structural basis for rational inhibitor design. In this review, we describe structural studies on the main protease of SARS-CoV-2. The strategies applied in developing inhibitors of the main protease of SARS-CoV-2 and currently available protein inhibitors are summarized. Due to the availability of high-resolution structures, structure-guided drug design will play an important role in developing antivirals. The availability of high-resolution structures, potent peptidic inhibitors, and diverse compound scaffolds indicate the feasibility of developing potent protease inhibitors as antivirals for COVID-19.

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The Analysis of Geospatial Information for Validating Some Numbers of Islands in Indonesia

Indonesian Journal of Geography ◽

10.22146/ijg.12792 ◽

2017 ◽

Vol 49 (2) ◽

pp. 204 ◽

Cited By ~ 1

Author(s):

Sukendra - Martha

Keyword(s):

Remote Sensing ◽

High Resolution ◽

Satellite Images ◽

Geospatial Data ◽

The Other ◽

Remote Sensing Images ◽

Geospatial Information ◽

Internal Affair ◽

High Resolution Satellite Images ◽

Data Source

This article discusses a comparison of various numbers of islands in Indonesia; and it addresses a valid method of accounting or enumerating numbers of islands in Indonesia. Methodology used is an analysis to compare the different number of islands from various sources. First, some numbers of Indonesian islands were derived from: (i) Centre for Survey and Mapping- Indonesian Arm Forces (Pussurta ABRI) recorded as 17,508 islands; (ii) Agency for Geospatial Information (BIG) previously known as National Coordinating Agency for Surveys and Mapping (Bakosurtanal) as national mapping authority reported with 17,506 islands (after loosing islands of Sipadan and Ligitan); (iii) Ministry of Internal Affair published 17,504 islands. Many parties have referred the number of 17,504 islands even though it has not yet been supported by back-up documents; (iv) Hidrographic Office of Indonesian Navy has released with numbers of 17,499; (v) Other sources indicated different numbers of islands, and indeed will imply to people confusion. In the other hand, the number of 13,466 named islands has a strong document (Gazetteer). Second, enumerating the total number of islands in Indonesia can be proposed by three ways: (i) island census through toponimic survey, (ii) using map, and (iii) applying remote sensing images. Third, the procedures of searching valid result in number of islands is by remote sensing approach - high resolution satellite images. The result of this work implies the needs of one geospatial data source (including total numbers of islands) in the form of ‘One Map Policy’ that will impact in the improvement of Indonesian geographic data administration.

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SYNERGY APPROACH FOR IMPLEMENTING THE POLICY ON HIGH RESOLUTION IMAGERY TO ACCELERATE BASIC AND THEMATIC GEOSPATIAL INFORMATION

International Journal of Remote Sensing and Earth Sciences (IJReSES) ◽

10.30536/j.ijreses.2014.v11.a2601 ◽

2017 ◽

Vol 11 (1) ◽

pp. 55

Author(s):

Sukendra Martha ◽

Aris Poniman ◽

. Hartono

Keyword(s):

High Resolution ◽

Satellite Data ◽

Geospatial Data ◽

Present Condition ◽

National Program ◽

Geospatial Information ◽

National Budget ◽

Governmental Agencies ◽

Control Quality ◽

High Resolution Imagery

Presidential Order no. 6/2012 mentioned explicitly to use ortho-rectifed image for the purposes of national program done by all Indonesian governmental agencies. Policy of uses, control quality, processing and distribution of high resolution of satellite data are regulated by this Order. There are some advantages of implementing this Order particularly in accelerating the national geospatial data and information, however, without synergy use of high resolution imagery (including integration, coordination and harmonization), in the present condition so far some obstacles have been discovered. Without synergic actions or approaches, the Order will not provide optimal impact as the main objectives to make more efficient in using the national budget. This article describes the needs of synergy approach to implement the Presidential Order no. 6/2012 concerning the uses, distribution of high remotely sensed imageries.

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UAV Data Processing for Large Scale Topographical Mapping

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsarchives-xl-5-565-2014 ◽

2014 ◽

Vol XL-5 ◽

pp. 565-572 ◽

Cited By ~ 8

Author(s):

W. Tampubolon ◽

W. Reinhardt

Keyword(s):

High Resolution ◽

Data Processing ◽

Data Acquisition ◽

Spatial Planning ◽

Large Scale ◽

Geospatial Data ◽

Mapping Unit ◽

Processing Scheme ◽

Area Of Interest ◽

Topographical Mapping

Large scale topographical mapping in the third world countries is really a prominent challenge in geospatial industries nowadays. On one side the demand is significantly increasing while on the other hand it is constrained by limited budgets available for mapping projects. Since the advent of Act Nr.4/yr.2011 about Geospatial Information in Indonesia, large scale topographical mapping has been on high priority for supporting the nationwide development e.g. detail spatial planning. Usually large scale topographical mapping relies on conventional aerial survey campaigns in order to provide high resolution 3D geospatial data sources. Widely growing on a leisure hobby, aero models in form of the so-called Unmanned Aerial Vehicle (UAV) bring up alternative semi photogrammetric aerial data acquisition possibilities suitable for relatively small Area of Interest (AOI) i.e. <5,000 hectares. For detail spatial planning purposes in Indonesia this area size can be used as a mapping unit since it usually concentrates on the basis of sub district area (kecamatan) level. In this paper different camera and processing software systems will be further analyzed for identifying the best optimum UAV data acquisition campaign components in combination with the data processing scheme. The selected AOI is covering the cultural heritage of Borobudur Temple as one of the Seven Wonders of the World. A detailed accuracy assessment will be concentrated within the object feature of the temple at the first place. Feature compilation involving planimetric objects (2D) and digital terrain models (3D) will be integrated in order to provide Digital Elevation Models (DEM) as the main interest of the topographic mapping activity. By doing this research, incorporating the optimum amount of GCPs in the UAV photo data processing will increase the accuracy along with its high resolution in 5 cm Ground Sampling Distance (GSD). Finally this result will be used as the benchmark for alternative geospatial data acquisition in the future in which it can support national large scale topographical mapping program up to the 1:1.000 map scale.

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Automated COVID-19 Detection from Chest X-Ray Images : A High Resolution Network (HRNet)Approach

10.1101/2020.08.26.20182311 ◽

2020 ◽

Author(s):

Sifat Ahmed ◽

Tonmoy Hossain ◽

Oishee Bintey Hoque ◽

Sujan Sarker ◽

Sejuti Rahman ◽

...

Keyword(s):

High Resolution ◽

Well Being ◽

X Rays ◽

X Ray ◽

Pcr Diagnosis ◽

Chest X Ray ◽

Novel Coronavirus ◽

And Control ◽

Learning Architectures ◽

Global Population

The pandemic, originated by novel coronavirus 2019 (COVID-19), continuing its devastating effect on the health, well-being, and economy of the global population. A critical step to restrain this pandemic is the early detection of COVID-19 in the human body, to constraint the exposure and control the spread of the virus. Chest X-Rays are one of the noninvasive tools to detect this disease as the manual PCR diagnosis process is quite tedious and time-consuming. In this work, we propose an automated COVID-19 classifier, utilizing available COVID and non-COVID X-Ray datasets, along with High Resolution Network (HRNet) for feature extraction embedding with the UNet for segmentation purposes. To evaluate the proposed dataset, several baseline experiments have been performed employing numerous deep learning architectures. With extensive experiment, we got 99.26% accuracy, 98.53% sensitivity, and 98.82% specificity with HRNet which surpasses the performances of the existing models. Our proposed methodology ensures unbiased high accuracy, which increases the probability of incorporating X-Ray images into the diagnosis of the disease.

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A high-resolution HLA reference panel capturing global population diversity enables multi-ancestry fine-mapping in HIV host response

Nature Genetics ◽

10.1038/s41588-021-00935-7 ◽

2021 ◽

Vol 53 (10) ◽

pp. 1504-1516

Author(s):

Yang Luo ◽

Masahiro Kanai ◽

Wanson Choi ◽

Xinyi Li ◽

Saori Sakaue ◽

...

Keyword(s):

High Resolution ◽

Fine Mapping ◽

Host Response ◽

Population Diversity ◽

Reference Panel ◽

Global Population

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Urban Health

10.1093/oso/9780190915858.001.0001 ◽

2019 ◽

Cited By ~ 1

Keyword(s):

Built Environment ◽

Urban Health ◽

Urban Areas ◽

Urban Environments ◽

Full Understanding ◽

Urban Populations ◽

Substantial Impact ◽

Current State ◽

Global Population ◽

Do So

Urban health is the study of the health of urban populations. More than half the world’s population is now living in urban areas, and two-thirds of the world’s population will live in cities by 2030. This means that characteristics of cities—including, for example, features of the built environment—are shared by a large proportion of the global population. These characteristics ultimately shape how most of us think, feel, and behave; they shape what we eat and drink; and, inevitably, they shape our health. The ubiquity of urban exposures suggests that a full understanding of the features of urban environments that affect health—and how they do so—can unlock the potential for approaches to prevent disease, promote health, and make a substantial impact on the health of urban populations. Studying urban health therefore requires an appreciation both of the urban exposures themselves and the approaches that can inform scholarship in the field. This book combines these with case studies that illuminate the progression of health in cities, aiming to capture the current state of the field while also pushing the field, through holding a mirror to itself, to consider its next decade.

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