Does the presence of certain bacterial family in the microbiome indicate specific indoor environment characteristics? A factorial design approach for identifying bio-fingerprints

2019 ◽  
Vol 29 (1) ◽  
pp. 117-131
Author(s):  
Dahae Seong ◽  
Shamia Hoque

The study applies the current knowledge on microbiome in built environments towards identifying microbes, specifically bacteria as bio-fingerprints which can reflect indoor space and occupant characteristics. Data were collected from the literature on the bacterial family and the indoor environment. The factorial design approach was applied to quantify and compare the influence of selected indoor environmental parameters, sampling region (air or surface), sampling locations (residence or non-residence), gender and age and their interactions on the types and concentration of detected bacterial families. Factorial design analysis identified and confirmed Corynebacteriaceae and Lactobacillaceae as the gender signature for males and females, respectively. The significant bacterial families across all scenarios are: Corynebacteriaceae, Propionibacteriaceae, Bacillaceae, Staphylococcaceae, Lactobacillaceae, Methylobacteriaceae, Moraxellaceae, Micrococcaceae, Enterobacteriaceae, Rhodobacteraceae, Streptococcaceae and Pseudomonadaceae. Higher concentrations of Propionibacteriaceae indicate that the specific location is an adult-occupied space. Staphylococcaceae presence is the bio-fingerprint of contaminated air of hospitals bio-fingerprint and Moraxellaceae on hospital surfaces are distinct characteristics. Streptococcaceae is a bio-fingerprint of contaminated air of schools and other children-occupied spaces. Enterobacteriaceae is a bio-fingerprint of contaminated air of non-residence locations. Bacillaceae does not indicate any indoor characteristics.

Author(s):  
Iman Mehdipour ◽  
Gabriel Falzone ◽  
Dale Prentice ◽  
Narayanan Neithalath ◽  
Dante Simonetti ◽  
...  

Optimizing the spatial distribution of contacting gas and the gas processing conditions enhances CO2 mineralization reactions and material properties of carbonate-cementitious monoliths.


Desalination ◽  
2011 ◽  
Vol 274 (1-3) ◽  
pp. 192-199 ◽  
Author(s):  
Tanisata Luenloi ◽  
Benjapon Chalermsinsuwan ◽  
Thammanoon Sreethawong ◽  
Napida Hinchiranan

2017 ◽  
Vol 127 ◽  
pp. 1194-1199 ◽  
Author(s):  
Mohammad Hemmat Esfe ◽  
Hossein Rostamian ◽  
Alireza Shabani-samghabadi ◽  
Ali Akbar Abbasian Arani

2021 ◽  
Vol 13 (19) ◽  
pp. 3796
Author(s):  
Lei Fan ◽  
Yuanzhi Cai

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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