Indoor transmission of SARS-CoV-2

AbstractBackgroundBy early April 2020, the COVID-19 pandemic had infected nearly one million people and had spread to nearly all countries worldwide. It is essential to understand where and how SARS-CoV-2 is transmitted.MethodsCase reports were extracted from the local Municipal Health Commissions of 320 prefectural cities (municipalities) in China, not including Hubei province, between 4 January and 11 February 2020. We identified all outbreaks involving three or more cases and reviewed the major characteristics of the enclosed spaces in which the outbreaks were reported and associated indoor environmental issues.ResultsThree hundred and eighteen outbreaks with three or more cases were identified, involving 1245 confirmed cases in 120 prefectural cities. We divided the venues in which the outbreaks occurred into six categories: homes, transport, food, entertainment, shopping, and miscellaneous. Among the identified outbreaks, 53·8% involved three cases, 26·4% involved four cases, and only 1·6% involved ten or more cases. Home outbreaks were the dominant category (254 of 318 outbreaks; 79·9%), followed by transport (108; 34·0%; note that many outbreaks involved more than one venue category). Most home outbreaks involved three to five cases. We identified only a single outbreak in an outdoor environment, which involved two cases.ConclusionsAll identified outbreaks of three or more cases occurred in an indoor environment, which confirms that sharing indoor space is a major SARS-CoV-2 infection risk.FundingThe work was supported by the Research Grants Council of Hong (no 17202719, C7025-16G), and National Natural Science Foundation of China (no 41977370).

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RTLIO: Real-Time LiDAR-Inertial Odometry and Mapping for UAVs

Sensors ◽

10.3390/s21123955 ◽

2021 ◽

Vol 21 (12) ◽

pp. 3955

Author(s):

Jung-Cheng Yang ◽

Chun-Jung Lin ◽

Bing-Yuan You ◽

Yin-Long Yan ◽

Teng-Hu Cheng

Keyword(s):

Feedback Control ◽

Real Time ◽

High Frequency ◽

Indoor Environment ◽

Indoor Localization ◽

Sampling Rate ◽

Outdoor Environment ◽

Position Accuracy ◽

Graph Optimization ◽

Pose Graph Optimization

Most UAVs rely on GPS for localization in an outdoor environment. However, in GPS-denied environment, other sources of localization are required for UAVs to conduct feedback control and navigation. LiDAR has been used for indoor localization, but the sampling rate is usually too low for feedback control of UAVs. To compensate this drawback, IMU sensors are usually fused to generate high-frequency odometry, with only few extra computation resources. To achieve this goal, a real-time LiDAR inertial odometer system (RTLIO) is developed in this work to generate high-precision and high-frequency odometry for the feedback control of UAVs in an indoor environment, and this is achieved by solving cost functions that consist of the LiDAR and IMU residuals. Compared to the traditional LIO approach, the initialization process of the developed RTLIO can be achieved, even when the device is stationary. To further reduce the accumulated pose errors, loop closure and pose-graph optimization are also developed in RTLIO. To demonstrate the efficacy of the developed RTLIO, experiments with long-range trajectory are conducted, and the results indicate that the RTLIO can outperform LIO with a smaller drift. Experiments with odometry benchmark dataset (i.e., KITTI) are also conducted to compare the performance with other methods, and the results show that the RTLIO can outperform ALOAM and LOAM in terms of exhibiting a smaller time delay and greater position accuracy.

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Detection of Legionella species, the influence of precipitation on the amount of Legionella DNA, and bacterial microbiome in aerosols from outdoor sites near asphalt roads in Toyama Prefecture, Japan

BMC Microbiology ◽

10.1186/s12866-021-02275-2 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Jun-ichi Kanatani ◽

Masanori Watahiki ◽

Keiko Kimata ◽

Tomoko Kato ◽

Kaoru Uchida ◽

...

Keyword(s):

16S Rrna ◽

16S Rrna Gene ◽

Indoor Environment ◽

Geometric Mean ◽

Amplicon Sequencing ◽

Positive Sample ◽

Outdoor Environment ◽

Rrna Gene ◽

Total Precipitation ◽

Monthly Total Precipitation

Abstract Background Legionellosis is caused by the inhalation of aerosolized water contaminated with Legionella bacteria. In this study, we investigated the prevalence of Legionella species in aerosols collected from outdoor sites near asphalt roads, bathrooms in public bath facilities, and other indoor sites, such as buildings and private homes, using amoebic co-culture, quantitative PCR, and 16S rRNA gene amplicon sequencing. Results Legionella species were not detected by amoebic co-culture. However, Legionella DNA was detected in 114/151 (75.5%) air samples collected near roads (geometric mean ± standard deviation: 1.80 ± 0.52 log10 copies/m3), which was comparable to the numbers collected from bathrooms [15/21 (71.4%), 1.82 ± 0.50] but higher than those collected from other indoor sites [11/30 (36.7%), 0.88 ± 0.56] (P < 0.05). The amount of Legionella DNA was correlated with the monthly total precipitation (r = 0.56, P < 0.01). It was also directly and inversely correlated with the daily total precipitation for seven days (r = 0.21, P = 0.01) and one day (r = − 0.29, P < 0.01) before the sampling day, respectively. 16S rRNA gene amplicon sequencing revealed that Legionella species were detected in 9/30 samples collected near roads (mean proportion of reads, 0.11%). At the species level, L. pneumophila was detected in 2/30 samples collected near roads (the proportion of reads, 0.09 and 0.11% of the total reads number in each positive sample). The three most abundant bacterial genera in the samples collected near roads were Sphingomonas, Streptococcus, and Methylobacterium (mean proportion of reads; 21.1%, 14.6%, and 1.6%, respectively). In addition, the bacterial diversity in outdoor environment was comparable to that in indoor environment which contains aerosol-generating features and higher than that in indoor environment without the features. Conclusions DNA from Legionella species was widely present in aerosols collected from outdoor sites near asphalt roads, especially during the rainy season. Our findings suggest that there may be a risk of exposure to Legionella species not only in bathrooms but also in the areas surrounding asphalt roads. Therefore, the possibility of contracting legionellosis in daily life should be considered.

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Developing an integrated framework for optimization of spatial requirements of construction equipment

Built Environment Project and Asset Management ◽

10.1108/bepam-07-2020-0126 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

S. Hemalattha ◽

R. Vidjeapriya

Keyword(s):

Construction Projects ◽

Indoor Environment ◽

Outdoor Environment ◽

Building Information Modelling ◽

Actual Structure ◽

Content Type ◽

Space Planning ◽

Existing Structures ◽

Building Information

PurposeThis study aims to develop a framework for optimizing the spatial requirements of the equipment in a construction site using a geographic information system (GIS).Design/methodology/approachAn ongoing construction project, an existing thermal powerplant in India, is considered to be the case study, and the corresponding construction activities were scheduled. The equipment spaces were defined for the scheduled activities in building information modelling (BIM), which was further imported to GIS to define the topology rules, validate and optimize the spatial requirements. The BIM simulates the indoor environment, which includes the actual structure being constructed, and the GIS helps in modelling the outdoor environment, which includes the existing structures, temporary facilitates, topography of the site, etc.; thus, this study incorporates the knowledge of BIM in a geospatial environment to obtain optimized equipment spaces for various activities.FindingsSpace in construction projects is to be considered as a resource as well as a constraint, which is to be modelled and planned according to the requirements. The integration of BIM and GIS for equipment space planning will enable precise identification of the errors in the equipment spaces defined and also result in fewer errors as possible. The integration has also eased the process of assigning the topology rules and validating the same, which otherwise is a tedious process.Originality/valueThe workspace for each activity will include the space of the equipment. But, in most of the previous works of workspace planning, only the labour space is considered, and the conflicts and congestions occurring due to the equipment were neglected. The planning of equipment spaces cannot be done based only on the indoor environment; it has to be carried out by considering the surroundings and topography of the site, which have not been researched extensively despite its importance.

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An Efficient Filtering Approach for Removing Outdoor Point Cloud Data of Manhattan-World Buildings

Remote Sensing ◽

10.3390/rs13193796 ◽

2021 ◽

Vol 13 (19) ◽

pp. 3796

Author(s):

Lei Fan ◽

Yuanzhi Cai

Keyword(s):

Point Cloud ◽

Indoor Environment ◽

Laser Scanning ◽

Point Cloud Data ◽

Hole Filling ◽

Cloud Data ◽

Indoor Space ◽

Wide Range ◽

Data Points ◽

Filtering Approach

Laser scanning is a popular means of acquiring the indoor scene data of buildings for a wide range of applications concerning indoor environment. During data acquisition, unwanted data points beyond the indoor space of interest can also be recorded due to the presence of openings, such as windows and doors on walls. For better visualization and further modeling, it is beneficial to filter out those data, which is often achieved manually in practice. To automate this process, an efficient image-based filtering approach was explored in this research. In this approach, a binary mask image was created and updated through mathematical morphology operations, hole filling and connectively analysis. The final mask obtained was used to remove the data points located outside the indoor space of interest. The application of the approach to several point cloud datasets considered confirms its ability to effectively keep the data points in the indoor space of interest with an average precision of 99.50%. The application cases also demonstrate the computational efficiency (0.53 s, at most) of the approach proposed.

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Application of thermal comfort assessment models to indoor areas near glazed walls – experimental evaluation

10.7764/rdlc.20.1.106 ◽

2021 ◽

Vol 20 (1) ◽

pp. 106-127

Author(s):

António Manuel Figueiredo Freitas Oliveira ◽

◽

Helena Corvacho ◽

Keyword(s):

Solar Radiation ◽

Thermal Comfort ◽

Thermal Environment ◽

National Laboratory ◽

Environmental Parameters ◽

Outdoor Environment ◽

Assessment Model ◽

Indoor Space ◽

The Impact ◽

Indoor Spaces

In this paper, some of the results of an experimental study are presented. Its purpose was to better understand the impact of glazing on thermal comfort of users of indoor spaces (living and working), especially in the areas near glazed walls. Glazed elements, such as windows and glazed doors, allow visual access to the outdoor environment and the entrance of natural light and solar heat gains but they are often the cause of unwanted heat losses and gains and are disturbing elements in obtaining thermal comfort, both in global terms and in what concerns local discomfort due to radiant asymmetries and/or air draughts. Furthermore, solar radiation directly affecting users in the vicinity of glazing can also cause discomfort. These disturbances are recognized by users, both on cold winter days and on hot summer days. To assess thermal comfort or thermal neutrality of a person in a particular indoor space, it is important to know their location within that space. Thus, in order to adequately assess thermal comfort in the areas near the glazing, the indoor thermal environment must be characterized for this specific location. In this study, two indoor spaces (a classroom and an office-room) of a school building were monitored at different periods of the year. The measurements of the environmental parameters were performed both in the center of the rooms and in the areas near the glazing. Five models of thermal comfort assessment were then applied to the results, in order to compare the comfort conditions between the two studied locations and to evaluate the applicability of these models to the areas close to glazed walls. It was observed there was clearly a greater variability of comfort conditions in the vicinity of the glazed walls when compared to the center of the rooms. The application of thermal comfort assessment models to the two studied rooms was able to reveal the differences between the two compared locations within each space. It was also possible to show the effect of incoming solar radiation and the influence of the geometry of the spaces and of the ratio between glazed area and floor area by comparing the results for both spaces. The assessment model proposed by LNEC (Portuguese National Laboratory of Civil Engineering) proved to be the most adapted to Portuguese users’ habits.

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Indoor path visualization method based on the spatial characteristics of indoor environment

Abstracts of the ICA ◽

10.5194/ica-abs-1-332-2019 ◽

2019 ◽

Vol 1 ◽

pp. 1-2

Author(s):

Jiafeng Shi ◽

Jie Shen ◽

Zdeněk Stachoň ◽

Yawei Chen

Keyword(s):

Indoor Environment ◽

Design Method ◽

Three Dimensional ◽

Indoor Environments ◽

Route Guidance ◽

Visualization Method ◽

Continuous Space ◽

Indoor Location ◽

Indoor Space ◽

Map Design

<p><strong>Abstract.</strong> With the increasing number of large buildings and more frequent indoor activities, indoor location-based service has expanded. Due to the complicated internal passages of large public buildings and the three-dimensional interlacing, it is difficult for users to quickly reach the destination, the demand of indoor paths visualization increases. Isikdag (2013), Zhang Shaoping (2017), Huang Kejia (2018) provided navigation services for users based on path planning algorithm. In terms of indoor path visualization, Nossum (2011) proposed a “Tubes” map design method, which superimposed the channel information of different floors on the same plane by simplifying the indoor corridor and the room. Lorenz et al (2013) focused on map perspective (2D/3D) and landmarks, developed and investigated cartographic methods for effective route guidance in indoor environments. Holscher et al (2007) emphasized using the landmark objects at the important decision points of the route in indoor map design. The existing studies mainly focused on two-dimensional plane to visualize the indoor path, lacking the analysis of three-dimensional connectivity in indoor space, which makes the intuitiveness and interactivity of path visualization greatly compromised. Therefore, it is difficult to satisfy the wayfinding requirements of the indoor multi-layer continuous space. In order to solve this problem, this paper aims to study the characteristics of the indoor environment and propose a path visualization method. The following questions are addressed in this study: 1) What are the key characteristics of the indoor environment compared to the outdoor space? 2) How to visualize the indoor paths to satisfy the users’ wayfinding needs?</p>

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Real-Time 3D UAV Pose Estimation by Visualization

Proceedings ◽

10.3390/proceedings2019039018 ◽

2020 ◽

Vol 39 (1) ◽

pp. 18

Author(s):

Nenchoo ◽

Tantrairatn

Keyword(s):

Object Detection ◽

Real Time ◽

Indoor Environment ◽

Target Object ◽

Outdoor Environment ◽

Visual Object ◽

Depth Camera ◽

Positioning System ◽

Stereo Camera ◽

Local Positioning System

This paper presents an estimation of 3D UAV position in real-time condition by using Intel RealSense Depth camera D435i with visual object detection technique as a local positioning system for indoor environment. Nowadays, global positioning system or GPS is able to specify UAV position for outdoor environment. However, for indoor environment GPS hasn’t a capability to determine UAV position. Therefore, Depth stereo camera D435i is proposed to observe on ground to specify UAV position for indoor environment instead of GPS. Using deep learning for object detection to identify target object with depth camera to specifies 2D position of target object. In addition, depth position is estimated by stereo camera and target size. For experiment, Parrot Bebop2 as a target object is detected by using YOLOv3 as a real-time object detection system. However, trained Fully Convolutional Neural Networks (FCNNs) model is considerably significant for object detection, thus the model has been trained for bebop2 only. To conclude, this proposed system is able to specifies 3D position of bebop2 for indoor environment. For future work, this research will be developed and apply for visualized navigation control of drone swarm.

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Walls talk: Microbial biogeography of homes spanning urbanization

Science Advances ◽

10.1126/sciadv.1501061 ◽

2016 ◽

Vol 2 (2) ◽

pp. e1501061 ◽

Cited By ~ 37

Author(s):

Jean F. Ruiz-Calderon ◽

Humberto Cavallin ◽

Se Jin Song ◽

Atila Novoselac ◽

Luis R. Pericchi ◽

...

Keyword(s):

Architectural Design ◽

Human Microbiome ◽

Outdoor Environment ◽

Human Immune System ◽

Developmental Exposure ◽

Immune Development ◽

Indoor Space ◽

Microbial Biogeography ◽

Microbiome Diversity ◽

Outdoor Environments

Westernization has propelled changes in urbanization and architecture, altering our exposure to the outdoor environment from that experienced during most of human evolution. These changes might affect the developmental exposure of infants to bacteria, immune development, and human microbiome diversity. Contemporary urban humans spend most of their time indoors, and little is known about the microbes associated with different designs of the built environment and their interaction with the human immune system. This study addresses the associations between architectural design and the microbial biogeography of households across a gradient of urbanization in South America. Urbanization was associated with households’ increased isolation from outdoor environments, with additional indoor space isolation by walls. Microbes from house walls and floors segregate by location, and urban indoor walls contain human bacterial markers of space use. Urbanized spaces uniquely increase the content of human-associated microbes—which could increase transmission of potential pathogens—and decrease exposure to the environmental microbes with which humans have coevolved.

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Estimating the daily trend in the size of the COVID-19 infected population in Wuhan

Infectious Diseases of Poverty ◽

10.1186/s40249-020-00693-4 ◽

2020 ◽

Vol 9 (1) ◽

Cited By ~ 2

Author(s):

Qiu-Shi Lin ◽

Tao-Jun Hu ◽

Xiao-Hua Zhou

Keyword(s):

Confidence Interval ◽

Missing Values ◽

Early Stage ◽

Hubei Province ◽

Reporting Rate ◽

Infected Case ◽

Epidemic Size ◽

Proposed Model ◽

Global Health Problem ◽

Municipal Health

Abstract Background The outbreak of coronavirus disease 2019 (COVID-19) has become a pandemic causing global health problem. We provide estimates of the daily trend in the size of the epidemic in Wuhan based on detailed information of 10 940 confirmed cases outside Hubei province. Methods In this modelling study, we first estimate the epidemic size in Wuhan from 10 January to 5 April 2020 with a newly proposed model, based on the confirmed cases outside Hubei province that left Wuhan by 23 January 2020 retrieved from official websites of provincial and municipal health commissions. Since some confirmed cases have no information on whether they visited Wuhan before, we adjust for these missing values. We then calculate the reporting rate in Wuhan from 20 January to 5 April 2020. Finally, we estimate the date when the first infected case occurred in Wuhan. Results We estimate the number of cases that should be reported in Wuhan by 10 January 2020, as 3229 (95% confidence interval [CI]: 3139–3321) and 51 273 (95% CI: 49 844–52 734) by 5 April 2020. The reporting rate has grown rapidly from 1.5% (95% CI: 1.5–1.6%) on 20 January 2020, to 39.1% (95% CI: 38.0–40.2%) on 11 February 2020, and increased to 71.4% (95% CI: 69.4–73.4%) on 13 February 2020, and reaches 97.6% (95% CI: 94.8–100.3%) on 5 April 2020. The date of first infection is estimated as 30 November 2019. Conclusions In the early stage of COVID-19 outbreak, the testing capacity of Wuhan was insufficient. Clinical diagnosis could be a good complement to the method of confirmation at that time. The reporting rate is very close to 100% now and there are very few cases since 17 March 2020, which might suggest that Wuhan is able to accommodate all patients and the epidemic has been controlled.

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Study on the Advantages and Role of Soft Decoration Materials in Shaping the Indoor Environment Art Atmosphere

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.644-650.4896 ◽

2014 ◽

Vol 644-650 ◽

pp. 4896-4899

Author(s):

Wen Shi Mao

Keyword(s):

Texture Analysis ◽

Interior Design ◽

Indoor Environment ◽

Great Influence ◽

Point Of View ◽

Low Carbon ◽

Indoor Space ◽

New Material ◽

Art Design

Modern decorative materials constantly updated and developed, and many of them are limited tube used for a time, and soon are replaced or eliminated. Soft adornment material can shape and express art atmosphere of indoor, having huge advantages and functions. In this paper, we research and analyze the soft adornment material from different point of view, and making catch-all category on the function of indoor soft adornment material that will be used in art design environmental. Soft adornment material has a great influence on the indoor space, such as people's sense of feel, smell, etc. Also from the angle of the color and design, as well as the texture analysis to analyze the utilization of soft decoration materials in interior design, and emphasized on low carbon green theme, highlighting the new idea of interior design, and also excusing the advantages of the new material.

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