Propagation and Diffusion of Fluorescent Substances with Footprints in Indoor Environments.
Ontology highlight
ABSTRACT:
SUBMITTER: Ma M
PROVIDER: S-EPMC9266062 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:As part of a worldwide survey of the indoor mycobiota about 520 new Cladosporium isolates from indoor environments mainly collected in China, Europe, New Zealand, North America and South Africa were investigated by using a polyphasic approach to determine their species identity. All Cladosporium species occurring in indoor environments are fully described and illustrated. Fourty-six Cladosporium species are treated of which 16 species are introduced as new. A key for the most common Cladosporium species isolated from indoor environments is provided. Cladosporium halotolerans proved to be the most frequently isolated Cladosporium species indoors.
| S-EPMC5909081 | biostudies-other
Project description:One of the key issues in forecasting volcanic eruptions is to detect signals that can track the propagation of dykes towards the surface. Continuous monitoring of active volcanoes helps significantly in achieving this goal. The seismic data presented here are unique, as they document surface faulting processes close (tens to a few hundred meters) to their source, namely the dyke tip. They originated nearby - and under - a seismic station that was subsequently destroyed by lava flows during eruptive activity at Etna volcano, Italy, in 2013. On February 20, a ~600 m-long and ~120 m wide NW-SE fracture field opened at an altitude between 2750 and 2900 m. The consequent rock dislocation caused the station to tilt and offset the seismic signal temporarily. Data acquisition continued until the arrival of the lava flow that led to the breakdown of the transmission system. Shallow ground fracturing and repeated low-frequency oscillations occurred during two stages in which the seismic signal underwent a maximum offset ~2.57 × 10(4) nm/s. Bridging instrumental recordings, fieldwork and conceptual modelling, these data are interpreted as the seismic footprints of a magmatic dyke intrusion that moved at speed ~0.02 m/s (first stage) and 0.46 m/s (second stage).
| S-EPMC4502396 | biostudies-other
Project description:Indoor environmental comfort has previously been quantified based on the subjective assessment of thermal physical parameters, such as temperature, humidity, and airflow velocity. However, the relationship of these parameters to brain activity remains poorly understood. The objective of this study was to determine the effect of airflow on brain activity using electroencephalograms (EEG) of participants in a living environment under different airflow conditions. Before the recording, the room was set to a standardised air temperature and humidity. During the recording, each participant was required to perform a simple time-perception task that involved pressing buttons after estimating a 10-second interval. Cooling and heating experiments were conducted in summer and winter, respectively. A frequency analysis of the EEGs revealed that gamma and beta activities showed lower amplitudes under conditions without airflow than with airflow, regardless of the season (i.e., cooling or heating). Our results reveal new neurophysiological markers of the response to airflow sensation. Further, based on the literature linking gamma and beta waves to less anxious states in calm environments, we suggest that airflow may alter the feelings of the participants.
| S-EPMC5599655 | biostudies-literature
Project description:Scopulariopsis-like species are often reported from the indoor environment, as well as from clinical samples. The lack of type isolates and thorough phylogenetic studies in the Microascaceae hampered the correct identification of these isolates. Based on recent phylogenetic studies, which resulted in multiple name changes, the aim is to molecularly identify the Scopulariopsis and scopulariopsis-like species which occur in the indoor environment and give an overview of the current species in these genera and their habitats. Strains from the CBS culture collection were supplemented with almost 80 indoor strains of which the internal transcribed spacer 1 and 2 and intervening 5.8S nrDNA (ITS), beta-tubulin (tub2) and translation elongation factor 1-alpha (tef1) gene regions were sequenced for phylogenetic inference. The multi-gene phylogenies recognise 33 Microascus species and 12 Scopulariopsis species and showed that the recently established genus Fuscoannellis, typified by Scopulariopsis carbonaria, should be synonymized with the genus Yunnania. Seven new Microascus species, four new Scopulariopsis species, and one new Yunnania species, are described, and a new name in Microascus and two new name combinations (one in Microascus, and one in Yunnania) are proposed. In the indoor environment 14 Microascus species and three Scopulariopsis species were found. Scopulariopsis brevicaulis (22 indoor isolates) and Microascus melanosporus (19 indoor isolates) are the most common indoor species, in number of isolates, followed by M. paisii (8 indoor isolates) and S. candida (7 indoor isolates). A genus phylogeny based on the ITS, tef1 and the large subunit 28S nrDNA (LSU) of the type or representative isolates of all here recognised species is provided depicting all species habitats. No correlation between phylogenetic relationship and habitat preference could be observed. Ten species which are found indoor are also found in relation with human-derived samples. A table showing recent name changes and a key to common species of Scopulariopsis and scopulariopsis-like genera found indoors is included.
| S-EPMC5384890 | biostudies-literature
Project description:Black carbon (BC) is a descriptive term that refers to light-absorbing particulate matter (PM) produced by incomplete combustion and is often used as a surrogate for traffic-related air pollution. Exposure to BC has been linked to adverse health effects. Penetration of ambient BC is typically the primary source of indoor BC in the developed world. Other sources of indoor BC include biomass and kerosene stoves, lit candles, and charring food during cooking. Home characteristics can influence the levels of indoor BC. As people spend most of their time indoors, human exposure to BC can be associated to a large extent with indoor environments. At the same time, due to the cost of environmental monitoring, it is often not feasible to directly measure BC inside multiple individual homes in large-scale population-based studies. Thus, a predictive model for indoor BC is needed to support risk assessment in public health. In this study, home characteristics and occupant activities that potentially modify indoor levels of BC were documented in 23 homes, and indoor and outdoor BC concentrations were measured twice. The homes were located in the Cincinnati-Kentucky-Indiana tristate region and measurements occurred from September 2015 through August 2017. A linear mixed-effect model was developed to predict BC concentration in residential environments. The measured outdoor BC concentrations and the documented home characteristics were utilized as predictors of indoor BC concentrations. After the model was developed, a leave-one-out cross-validation algorithm was deployed to assess the predictive accuracy of the output. The following home characteristics and occupant activities significantly modified the concentration of indoor BC: outdoor BC, lit candles and electrostatic or high efficiency particulate air (HEPA) filters in heating, ventilation and air conditioning (HVAC) systems. Predicted indoor BC concentrations explained 78% of the variability in the measured indoor BC concentrations. The data show that outdoor BC combined with home characteristics can be used to predict indoor BC levels with reasonable accuracy.
| S-EPMC6785191 | biostudies-literature
Project description:Indoor air quality has been the object of interest for scientists and specialists from the fields of science such as chemistry, medicine and ventilation system design. This results from a considerable number of potential factors, which may influence the quality of the broadly understood indoor air in a negative way. Poor quality of indoor air in various types of public utility buildings may significantly affect an increase in the incidence of various types of civilisation diseases. This paper presents information about a broad spectrum of chemical compounds that were identified and determined in the indoor environment of various types of public utility rooms such as churches, museums, libraries, temples and hospitals. An analysis of literature data allowed for identification of the most important transport paths of chemical compounds that significantly influence the quality of the indoor environment and thus the comfort of living and the health of persons staying in it.
| S-EPMC5393278 | biostudies-literature
Project description:Smart Environments try to adapt their conditions focusing on the detection, localisation, and identification of people to improve their comfort. It is common to use different sensors, actuators, and analytic techniques in this kind of environments to process data from the surroundings and actuate accordingly. In this research, a solution to improve the user's experience in Smart Environments based on information obtained from indoor areas, following a non-intrusive approach, is proposed. We used Machine Learning techniques to determine occupants and estimate the number of persons in a specific indoor space. The solution proposed was tested in a real scenario using a prototype system, integrated by nodes and sensors, specifically designed and developed to gather the environmental data of interest. The results obtained demonstrate that with the developed system it is possible to obtain, process, and store environmental information. Additionally, the analysis performed over the gathered data using Machine Learning and pattern recognition mechanisms shows that it is possible to determine the occupancy of indoor environments.
| S-EPMC6263685 | biostudies-other
Project description:Information on metal binding with fluorescent substances has been widely studied. By contrast, information on metal binding with non-fluorescent substances remains lacking despite the dominance of these substances in aquatic systems. In this study, the metal binding properties of both fluorescent and non-fluorescent substances were investigated by using metal titration combined with two-dimensional correlation spectroscopy (2D-COS) analysis. The organic matters in the eutrophic algae-rich lake, including natural organic matters (NOM) and algae-induced extracellular polymeric substances (EPS), both contained fluorescent and non-fluorescent substances. The peaks in the one-dimensional spectra strongly overlapped, while 2D-COS can decompose the overlapped peaks and thus enhanced the spectral resolution. Moreover, 2D FTIR COS demonstrated that the binding susceptibility of organic ligands in both NOM and algal EPS matrices followed the order: 3400>1380>1650 cm-1, indicative the significant contribution of non-fluorescent ligands in metal binding. The modified Stern-Volmer equation also revealed a substantial metal binding potential for the non-fluorescent substances (logKM: 3.57∼4.92). As for the effects of organic ligands on metal binding, EPS was characterized with higher binding ability than NOM for both fluorescent and non-fluorescent ligands. Algae-induced EPS and the non-fluorescent substances in eutrophic algae-rich lakes should not be overlooked because of their high metal binding potential.
| S-EPMC4224434 | biostudies-literature
Project description:This paper presents a novel system capable of solving the problem of tracking multiple targets in a crowded, complex and dynamic indoor environment, like those typical of mobile robot applications. The proposed solution is based on a stereo vision set in the acquisition step and a probabilistic algorithm in the obstacles position estimation process. The system obtains 3D position and speed information related to each object in the robot's environment; then it achieves a classification between building elements (ceiling, walls, columns and so on) and the rest of items in robot surroundings. All objects in robot surroundings, both dynamic and static, are considered to be obstacles but the structure of the environment itself. A combination of a Bayesian algorithm and a deterministic clustering process is used in order to obtain a multimodal representation of speed and position of detected obstacles. Performance of the final system has been tested against state of the art proposals; test results validate the authors' proposal. The designed algorithms and procedures provide a solution to those applications where similar multimodal data structures are found.
| S-EPMC3230977 | biostudies-literature
Project description:This study aimed to investigate the potential contamination of SARS-CoV-2 in indoor settled dust and surfaces of Amir Al-Muminin hospital in Maragheh, Iran. Samples were taken from surfaces and settled dust using a passive approach and particulate matter (PM) using an active approach from different hospital wards. SARS-CoV-2 was detected in 15% of settled dust samples (N = 4/26) and 10% of surface samples (3/30). SARS-CoV-2 has been detected in 13.8% and 9.1% of the dust samples collected at a distance of fewer than 1 m and more than 3 m from the patient bed, respectively. SARS-CoV-2 was found in 11% of surface samples from low-touch surfaces and 8% from high touch surfaces. The relationship between PM2.5, PM10, humidity, temperature, and positive samples of SARS-CoV-2 was investigated. A positive correlation was observed between relative humidity, PM2.5, and positive SARS-CoV-2 samples. Principal component analysis (PCA) suggested positive correlation between positive SARS-CoV-2 samples, relative humidity, and PM2.5. Risk assessment results indicated that the annual mean infection risk of SARS-CoV-2 for hospital staff with illness and death was 2.6 × 10-2 and 7.7 × 10-4 per person per year. Current findings will help reduce the permanence of viral particles in the COVID 19 tragedy and future similar pandemics e.g., novel influenza viruses.
| S-EPMC9301582 | biostudies-literature