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Closed Circuit Television (CCTV) based Surveillance has become the fundamental part of the security Systems. In most cases, surveillance feeds are only used as evidence. The emergence of Edge Computing gives hope for enabling real time surveillance systems that focuses on prevention of crimes. The proposed architecture consists of a Convolutional Neural Network (CNN) enabled in an edge device, with reduced computational complexity, which classifies various actions like Pulling, pushing and other hand movements and locates the identified activities in the image frame using bounding boxes. The proposed architecture gives an alert whenever a suspicious activity is detected. The system was found efficient when validated against the Dataset taken from the SRM IST Campus.

Fluorescent or LED nail lamps are used in manicure and pedicure salons to cure nail coatings. These are UV sources, but with significant blue light emissions. Most of the literature emphasizes skin damage and cancer risk from UV exposure rather than blue light-induced damage to visual photoreceptors. Nail technicians using the lamps routinely may have potentially greater exposure than customers. However, there are no data on blue light radiance levels combined with time activity patterns for exposure assessment. This research aimed to determine exposures through simulation experiments, informed by observational studies in seven nail salons. Typical and worst-case time activity patterns were established, and spectral radiance doses determined in the occupational visual field for two LED nail curing lamps. The results showed the effective spectral radiance dose were below the current guideline promulgated by the International Commission on Non-Ionising Radiation Protection. Interestingly, radiances at the corners of one LED nail curing lamp was higher than at the center, which shows the amount of exposure can differ depending on the viewing angle. This research is the first to determine spectral radiance doses. A covered design is highly recommended for blocking the emission of blue light from a nail lamp.

The Blue Swallow is an intra-African migrant that breeds in its fragmented range from South Africa to southern Tanzania, from October to March annually. The birds migrate north and are on their non-breeding range in NE DRC, Uganda, NW Tanzania and W Kenya, from April to September annually. The global Blue Swallow population, estimated at

Playing games are the common activities among teenagers nowadays, especially when smartphone becomes massive devices for every communication. Playing games on smartphone can be either a killing-time activity or a wasting time activity depends on the people who use that facility. However, games nowadays can be used for educational learning materials which make the students more engaged to the class. This analysis offers an insight to use the game as the one of materials in teaching linguistics. By analyzing the language use in the names of the game characters and the conceptual system of the game, this research can be brought into the linguistic class. This research not only focuses on the names of the game characters but also to the game’s conceptual system which is used to promote the Mexican culture. The research method uses the screenshot feature of smartphone to collect the data and then the data were analyzed using cognitive stylistics. The names of the characters are created mostly by using puns and the game conceptual system is built basically by using metonymy.

Moonlight intensity influences the activity patterns of bats. Some bat species reduce their activity levels during brighter nights, a phenomenon known as “lunar phobia.” While lunar phobia of bats has been extensively studied in tropical regions, the same is not the case of bats in temperate regions. By using acoustic detectors, we examined differences in the activity of insectivorous bats on nights with different moonlight intensity in an agricultural landscape of central Chile. We also examined the hourly activity patterns throughout the night and how these varied between full and new moon nights. All bat species modified their activity based on the moonlight intensity; however, their effects were species-specific. The activity of Lasiurus varius, L. villosissimus, Myotis chiloensis, and Histiotus montanus was lower during bright nights, while Tadarida brasiliensis was the only species whose activity was higher during bright nights. Hourly activity throughout the night differed between full moon nights and new moon nights in most bat species. During full moon, bats concentrated their activities in the early hours of the nights; a more homogeneous activity pattern was exhibited during new moon night. Our study demonstrates that moonlight affects the activity of bats in Chile, a factor that should be considered when studying bats.

99mTc-3SPboroxime is a 99mTc(III) complex with high initial heart uptake comparable to that of 99mTc-Teboroxime, but with significantly longer myocardial retention in Sprague–Dawley rats. This study was performed to demonstrate its feasibility on myocardial perfusion imaging and myocardial blood flow quantification in swine models. Dynamic single-photon emission computed tomography (SPECT) studies with 99mTc-3SPboroxime were performed in normal (with/without dipyridamole, n = 9) and acute myocardial infarction (AMI) swine (n = 3) in comparison with 99mTc-Teboroxime and 99mTc-Sestamibi. List-mode acquisitions were immediately started after injection and continued for 15 minutes. Regions of interest were drawn on heart (infarct and remote areas of AMI swine) and liver to generate time activity curves. Heart/liver and infarct/remote radioactivity ratios were calculated. One-tissue compartment model was implemented to obtain K1 and K2 values. The initial heart uptake of 99mTc-3SPboroxime was close to that of 99mTc-Teboroxime, but higher than that of 99mTc-Sestamibi. 99mTc-3SPboroxime had a myocardial retention longer than that of 99mTc-Teboroxime. The heart/liver ratio of 99mTc-3SPboroxime was higher than that of 99mTc-Teboroxime at later stage (13-15 minutes post-injection). The K1 value of 99mTc-3SPboroxime was much higher than that of 99mTc-Sestamibi, and the K2 value was significantly lower than that of 99mTc-Teboroxime both at rest and dipyridamole stress (rest K1: 0.63 ± 0.11 vs 0.40 ± 0.04 mL·min−1·g−1, P = 0.027; stress K1: 0.89 ± 0.05 vs 0.54 ± 0.08 mL·min−1·g−1, P = 0.031; rest K2: 0.22 ± 0.04 vs 0.33 ± 0.11 mL·min−1·g−1, P = 0.003; stress K2: 0.31 ± 0.03 vs 0.60 ± 0.30 mL·min−1·g−1, P = 0.047). High quality SPECT images could be obtained in any of the 5 minutes windows over the first 15 minutes after injection of 99mTc-3SPboroxime in normal and AMI swine models. Apical and anterior perfusion defects were clearly visualized in AMI swine. 99mTc-3SPboroxime is a promising radiotracer for future clinical translation considering its heart uptake, heart/liver ratio and SPECT image quality, as well as the advantage over 99mTc-Sestamibi in the definition of stress flow.

IntroductionFull quantification of positron emission tomography (PET) data requires an input function. This generally means arterial blood sampling, which is invasive, labor-intensive and burdensome. There is no current, standardized method to fully quantify PET radiotracers with irreversible kinetics in the absence of blood data. Here, we present Source-to-Target Automatic Rotating Estimation (STARE), a novel, data-driven approach to quantify the net influx rate (Ki) of irreversible PET radiotracers, that requires only individual-level PET data and no blood data. We validate STARE with [18F]FDG PET and assess its performance using simulations.MethodsSTARE builds upon a source-to-target tissue model, where the tracer time activity curves (TACs) in multiple “target” regions are expressed at once as a function of a “source” region, based on the two-tissue irreversible compartment model, and separates target region Ki from source Ki by fitting the source-to-target model across all target regions simultaneously. To ensure identifiability, data-driven, subject-specific anchoring is used in the STARE minimization, which takes advantage of the PET signal in a vasculature cluster in the FOV that is automatically extracted and partial volume-corrected. To avoid the need for any a priori determination of a single source region, each of the considered regions acts in turn as the source, and a final Ki is estimated in each region by averaging the estimates obtained in each source rotation.ResultsIn a large dataset of [18F]FDG human scans (N=69), STARE Ki estimates were in good agreement with corresponding arterial blood-based estimates (regression slope=0.88, r=0.80), and were precisely estimated, as assessed by comparing STARE Ki estimates across several runs of the algorithm (coefficient of variation across runs=6.74 ± 2.48%). In simulations, STARE Ki estimates were largely robust to factors that influence the individualized anchoring used within its algorithm.ConclusionThrough simulations and application to [18F]FDG PET data, feasibility is demonstrated for STARE blood-free, data-driven quantification of Ki. Future work will include applying STARE to PET data obtained with a portable PET camera and to other irreversible radiotracers.

A vast majority of nursing home residents suffer from health issues such as incontinence, night wandering and pressure ulcers. The workload of nurses is noticeably increasing because of these problems. Previous research has shown that many of these complaints can be associated with specific movements in bed. This paper proposes the usage of accelerometer sensors in a non-invasive manner to detect these movements. Using deep learning on the edge, the discussed method provides immediate feedback to nurses to assist them with their care tasks.

Objectives Approximately 2 billion workers globally are employed in informal settings, which are characterized by substantial risk from hazardous exposures and varying job tasks and schedules. Existing methods for identifying occupational hazards must be adapted for unregulated and challenging work environments. We designed and applied a method for objectively deriving time-activity patterns from wearable camera data and matched images with continuous measurements of personal inhalation exposure to size-specific particulate matter (PM) among workers at an informal electronic-waste (e-waste) recovery site. Methods One hundred and forty-two workers at the Agbogbloshie e-waste site in Accra, Ghana, wore sampling backpacks equipped with wearable cameras and real-time particle monitors during a total of 171 shifts. Self-reported recall of time-activity (30-min resolution) was collected during the end of shift interviews. Images (N = 35,588) and simultaneously measured PM2.5 were collected each minute and processed to identify activities established through worker interviews, observation, and existing literature. Descriptive statistics were generated for activity types, frequencies, and associated PM2.5 exposures. A kappa statistic measured agreement between self-reported and image-based time-activity data. Results Based on image-based time-activity patterns, workers primarily dismantled, sorted/loaded, burned, and transported e-waste materials for metal recovery with high variability in activity duration. Image-based and self-reported time-activity data had poor agreement (kappa = 0.17). Most measured exposures (90%) exceeded the World Health Organization (WHO) 24-h ambient PM2.5 target of 25 µg m−3. The average on-site PM2.5 was 81 µg m−3 (SD: 94). PM2.5 levels were highest during burning, sorting/loading and dismantling (203, 89, 83 µg m−3, respectively). PM2.5 exposure during long periods of non-work-related activities also exceeded the WHO standard in 88% of measured data. Conclusions In complex, informal work environments, wearable cameras can improve occupational exposure assessments and, in conjunction with monitoring equipment, identify activities associated with high exposures to workplace hazards by providing high-resolution time-activity data.

The aim of this study was to investigate the effect of recreational sport participation on academic motivation. Totally, 144 students (108 male, 36 female) were taken part in this research. Data was gathered through Academic Motivation Scale which was developed by Vallerand et al. (1992) and translated to Turkish Language by Karagüven (2012). The scale has 28 items. In evaluation part for questionnaires answered by participants, Kolmogorov Smirnov normality test, T-Test and One Way ANOVA tests were applied. According to the results, it was statistically determined that there were significant differences on recreational participation, free time activity, recreational practising frequency and age (p0,05). Keywords: Recreational sports, free time activity, academic motivation

This study investigated the cross-sectional and longitudinal associations of the substitution of non-school time light physical activity (LPA), moderate-to-vigorous physical activity (MVPA), and sedentary time (ST) with adiposity in boys and girls. Boys (n = 65, baseline Mage= 9.93 ± 0.86 years) and girls (n = 77, baseline Mage = 10.17 ± 0.95 years) wore waist-worn accelerometers (ActiGraph GT3X) at baseline and at a 30-month follow-up, from which non-school time LPA, MVPA, ST, and total device wear were quantified. Body mass index (BMI) and waist-to-height-ratio (WHR) were measured at baseline and follow-up. Body fat percent (BF%) was obtained at follow-up only. Isotemporal substitution models assessed the cross-sectional and longitudinal associations of reallocating non-school time activity with BMI, WHR and BF%. In boys, replacing 30 min/day of LPA with MVPA was cross-sectionally (β = −8.26, p &lt, 0.05) associated with a lower BF%. Replacing 30 min/day of ST with MVPA was cross-sectionally (β = −6.02, p &lt, 0.05) associated with a lower BF% in boys. Longitudinally in boys, replacing 30 min of change in LPA with MVPA (β = −7.42, p &lt, 0.10) and replacing 30 min of change in MVPA with ST (β = 5.78, p &lt, 0.10) over 30 months was marginally associated with less BF%. Associations were null in girls (p &gt, 0.05). These results may support targeting activity reallocation during non-school time for the purposes of adiposity improvement in boys. A multi-behavioral approach may be more appropriate for girls, as non-school time activity may not be driving adiposity status.

BACKGROUND: To investigate associations between annual average air pollution exposures and health, most epidemiological studies rely on estimated residential exposures because information on actual time-activity patterns can only be collected for small populations and short periods of time due to costs and logistic constraints. In the current study, we aim to compare exposure assessment methodologies that use data on time-activity patterns of children with residence-based exposure assessment. We compare estimated exposures and associations with lung function for residential exposures and exposures accounting for time activity patterns.METHODS: We compared four annual average air pollution exposure assessment methodologies; two rely on residential exposures only, the other two incorporate estimated time activity patterns. The time-activity patterns were based on assumptions about the activity space and make use of available external data sources for the duration of each activity. Mapping of multiple air pollutants (NO2, NOX, PM2.5, PM2.5absorbance, PM10) at a fine resolution as input to exposure assessment was based on land use regression modelling. First, we assessed the correlations between the exposures from the four exposure methods. Second, we compared estimates of the cross-sectional associations between air pollution exposures and lung function at age 8 within the PIAMA birth cohort study for the four exposure assessment methodologies.RESULTS: The exposures derived from the four exposure assessment methodologies were highly correlated (R > 0.95) for all air pollutants. Similar statistically significant decreases in lung function were found for all four methods. For example, for NO2 the decrease in FEV1 was -1.40% (CI; -2.54, -0.24%) per IQR (9.14 μg/m3) for front door exposure, and -1.50% (CI; -2.68, -0.30%) for the methodology which incorporates time activity pattern and actual school addresses.CONCLUSIONS: Exposure estimates from methods based on the residential location only and methods including time activity patterns were highly correlated and associated with similar decreases in lung function. Our study illustrates that the annual average exposure to air pollution for 8-year-old children in the Netherlands is sufficiently captured by residential exposures.

Activity detection in security videos is a difficult problem due to multiple factors such as large field of view, presence of multiple activities, varying scales and viewpoints, and its untrimmed nature. The existing research in activity detection is mainly focused on datasets, such as UCF-101, JHMDB, THUMOS, and AVA, which partially address these issues. The requirement of processing the security videos in real-time makes this even more challenging. In this work we propose Gabriella, a real-time online system to perform activity detection on untrimmed security videos. The proposed method consists of three stages: tubelet extraction, activity classification, and online tubelet merging. For tubelet extraction, we propose a localization network which takes a video clip as input and spatio-temporally detects potential foreground regions at multiple scales to generate action tubelets. We propose a novel Patch-Dice loss to handle large variations in actor size. Our online processing of videos at a clip level drastically reduces the computation time in detecting activities. The detected tubelets are assigned activity class scores by the classification network and merged together using our proposed Tubelet-Merge Action-Split (TMAS) algorithm to form the final action detections. The TMAS algorithm efficiently connects the tubelets in an online fashion to generate action detections which are robust against varying length activities. We perform our experiments on the VIRAT and MEVA (Multiview Extended Video with Activities) datasets and demonstrate the effectiveness of the proposed approach in terms of speed (~100 fps) and performance with state-of-the-art results. The code and models will be made publicly available., Comment: 9 pages

This chapter explores the role of ABC’s business and service business activities, citing the basic principles and structure of their costing, based on TDABC’s time activity. The aim of the TDABC selection is to reduce the complexity of calculating and allocating costs, which characterizes ABC systems, which are used by large companies. The new version of ABC is presented in the service sector.

Preschool children aged 3-6 years are vulnerable to exposed to particulate matter ("PM10" and "PM2.5"). It is required in evaluating the risk based on dose of preschool children. Microenvironments which preschool children mainly visited were classified. Inhalation type was adapted in each microenvironment in consideration of intensity of activity. The exposure scenario was described as preschool children had been living in Seoul, South Korea, and dose was calculated by considering time-activity-pattern with major microenvironments and inhalation type of preschool children for 24 h. Monte-Carlo simulation technique is used to estimate dose of particulate matter in probabilistic distribution by age and sex. The contribution of exposure by microenvironments and inhalation type was calculated. Risk assessment was performed based on WHO interim target-3 24-h concentration in order to estimate. Sensitivity analysis was performed to determine the effective variable of dose. As a result of the study, the dose of PM was higher for boys than girls and tended to decrease with age. The overall contributions of PM doses by microenvironments were daycare center, home, other facilities, transit, and outdoors, respectively, although differed between daycare center and home priority by age and sex. Especially, the contribution of daycare center and home was very high, accounting over 85% of the total. The overall contributions of PM doses by inhalation type were "run," "stable," "sleep," and "walk inhalation," respectively. The results of hazard quotient showed that "PM10" exceeded the WHO interim target-3 24-h concentration standard by about 10% and "PM2.5" exceeded about half. Through sensitivity analysis, PM concentration was confirmed as a major influence variable for doses. This study was able to affirm the overall exposure status of "PM10" and "PM2.5" for preschool children, and this is expected to be used in regulation and public health.

We introduce a soft, expandable electronic and optoelectronic system designed to monitor and cure urinary bladder diseases., Underactive bladder or detrusor underactivity (DUA), that is, not being able to micturate, has received less attention with little research and remains unknown or limited on pathological causes and treatments as opposed to overactive bladder, although the syndrome may pose a risk of urinary infections or life-threatening kidney damage. Here, we present an integrated expandable electronic and optoelectronic complex that behaves as a single body with the elastic, time-dynamic urinary bladder with substantial volume changes up to ~300%. The system configuration of the electronics validated by the theoretical model allows conformal, seamless integration onto the urinary bladder without a glue or suture, enabling precise monitoring with various electrical components for real-time status and efficient optogenetic manipulation for urination at the desired time. In vivo experiments using diabetic DUA models demonstrate the possibility for practical uses of high-fidelity electronics in clinical trials associated with the bladder and other elastic organs.

Health smart home, as a typical application of Internet of things, provides a new solution for remote medical treatment. It can effectively relieve pressure from shortage of medical resources caused by aging population and help elderly people live at home more independently and safely. Activity recognition is the core of health smart home. This technology aims to recognize the activity patterns of users from a series of observations on the user’ actions and the environmental conditions, so as to avoid distress situations as much as possible. However, most of the existing researches focus on offline activity recognition, but not good at online real-time activity recognition. Besides, the feature representation techniques used for offline activity recognition are generally not suitable for online scenarios. In this article, the authors propose a real-time online activity recognition approach based on the genetic algorithm–optimized support vector machine classifier. In order to support online real-time activity recognition, a new sliding window-based feature representation technique enhanced by mutual information between sensors is devised. In addition, the genetic algorithm is used to automatically select optimal hyperparameters for the support vector machine model, thereby reducing the recognition inaccuracy caused by manual tuning of hyperparameters. Finally, a series of comprehensive experiments are conducted on freely available data sets to validate the effectiveness of the proposed approach.

Patients after solid organ kidney transplantation (KTX) often suffer from acute kidney injury (AKI). Parameters as serum creatinine indicate a loss of kidney function, although no distinction of the cause and prognosis can be made. Imaging tools measuring kidney function have not been widely in clinical use. In this observational study we evaluated 2-deoxy-2[18F] fluoro-D-glucose (FDG) PET/MRI in thirteen patients after KTX with AKI as a functional assessment of the graft. Twenty-four healthy volunteers served as control. General kidney performance (GKP), initial flow (IF) and renal response function (RF) were calculated by standardized uptake values (SUV) and time activity curves (TAC). The GKP measured for the total kidney and medulla was significantly higher in healthy patients compared to patients after KTX (p = 0.0002 and p = 0.0004, respectively), but no difference was found for the GKP of the cortex (p = 0.59). The IF in KTX patients correlated with renal recovery, defined as change in serum creatinine 10 days after PET/MRI (r = 0.80, p = 0.001). With regard to the RF, a negative correlation for tubular damage was found (r = −0.74, p = 0.004). In conclusion, parameters obtained from FDG PET/MRI showed a possible predictive feature for renal recovery in KTX patients undergoing AKI.

In everyday life, people are exposed to different concentrations of airborne particles depending on the microenvironment where they perform their different activities. Such exposure can lead to high sub-micron particle doses. The received dose depends on particle concentration to which people are exposed (typically expressed in terms of number or surface area), time spent in each activity or microenvironment (time activity pattern) and amount of air inhaled (inhalation rate). To estimate an actual value of the received dose, all these parameters should be measured under real-life conditions; in fact, the concentrations should be measured on a personal scale (i.e. through a direct exposure assessment), whereas time activity patterns and inhalation rates specific to the activity performed should be considered. The difficulties in obtaining direct measurements of these parameters usually lead to adopt time activity patterns and inhalation rates already available in scientific literature for typical populations, and local outdoor particle concentrations measured with fixed monitoring stations and extrapolated for all the other microenvironments. To overcome these limitations, we propose a full-field method for estimating the received dose of a population sample, in which all the parameters (concentration levels, time activity patterns and inhalation rates) are measured under real-life conditions (also including the inhalation rates, that were evaluated on the basis of the measured heart rates). Specifically, 34 volunteers were continuously monitored for seven days and the data of sub-micron particle concentrations, activities performed, and inhalation rates were recorded. The received dose was calculated with the proposed method and compared with those obtained from different simplified methodologies that consider typical data of particle concentrations, time activity patterns and inhalation rates obtained from literature. The results show that, depending on the methodology used, the differences in the received daily dose can be significant, with a general underestimation of the most simplified method.

[Capsule]: Differences in parental investment between sexes and stage of the breeding period were found in Bonelli’s Eagles Aquila fasciata., [Aims]: To describe the sexual differences in parental behaviour of Bonelli’s Eagles and to assess the sex-specific pattern of variation in parental investment in relation to the breeding period., [Methods]: Between 2006 and 2016, we monitored the parental behaviour of 11 pairs of Bonelli’s Eagles during the incubation and chick-rearing periods in southeastern Spain. Observations were made using 20–60× telescopes from points overlooking the territory at a distance of about 500–800 m from the nest., [Results]: Our results reveal a marked division in parental duties in Bonelli’s Eagles. Females invested more effort in incubation, nest attendance, chick feeding and nest-building, while males contributed more to food provisioning. Nest attendance and feeding by females decreased with time, and both parents adjusted their provisioning effort in relation to nestling age. Most changeovers took place during the middle of the day, when male provisioning rates and temperatures reach their maximum., [Conclusion]: Intersexual differences are discussed in the context of the prey capture difficulty hypothesis, which proposes that intra-pair prey differences, due to large sexual size dimorphism, should be particularly advantageous among raptors that pursue agile prey.

The study was conducted in May 2016, the purpose of this research to determine the difference of Egretta garzetta’s daily frequency, male and female behavior in mangrove area Alue Naga, Banda Aceh city. The method used in this study is focal animal sampling method to recording the daily behavior. Data processed using the qualitative and quantitative analysis. Analysis of the frequency of daily activity, carried out with the daily percentage. The results showed that daily behavior of Egretta garzetta include: feeding activity, perching activity, voice activity, moving activity, grooming activity, resting activity and flying activity. The highest time activity is females, that is perching and resting activity with each averaging for 70 minutes / day (28%) and 80 min / day (32%), and the lowest time span males and females is voice activity in average 1 min / day (0.4%). The conclusions derived from this research are: (1) There are 7 daily activities of Egretta garzetta in study location, include: feeding activity, perching activity, voice activity, moving activity, grooming activity, resting activity and flying activity. (2) The highest time activity is females, that is perching and resting activity.

The aim of this study was to assess whether dynamic PET with 11C-methionine (MET) (MET-PET) is useful in the diagnosis of brain tumors. One hundred sixty patients with brain tumors (139 gliomas, 9 meningiomas, 4 hemangioblastomas and 8 primary central nervous system lymphomas [PCNSL]) underwent dynamic MET-PET with a 3-dimensional acquisition mode, and the maximum tumor MET-standardized uptake value (MET-SUV) was measured consecutively to construct a time-activity curve (TAC). Furthermore, receiver operating characteristic (ROC) curves were generated from the time-to-peak (TTP) and the slope of the curve in the late phase (SLOPE). The TAC patterns of MET-SUVs (MET-TACs) could be divided into four characteristic types when MET dynamics were analyzed by dividing the MET-TAC into three phases. MET-SUVs were significantly higher in early and late phases in glioblastoma compared to anaplastic astrocytoma, diffuse astrocytoma and the normal frontal cortex (P

Summarization: Atmospheric particles are a major environmental health risk. Assessments of air pollution related health burden are often based on outdoor concentrations estimated at residential locations, ignoring spatial mobility, time-activity patterns, and indoor exposures. The aim of this work is to quantify impacts of these factors on outdoor-originated fine particle exposures of school children. We apply nested WRF-CAMx modelling of PM2.5 concentrations, gridded population, and school location data. Infiltration and enrichment factors were collected and applied to Athens, Kuopio, Lisbon, Porto, and Treviso. Exposures of school children were calculated for residential and school outdoor and indoor, other indoor, and traffic microenvironments. Combined with time-activity patterns six exposure models were created. Model complexity was increased incrementally starting from residential and school outdoor exposures. Even though levels in traffic and outdoors were considerably higher, 80–84% of the exposure to outdoor particles occurred in indoor environments. The simplest and also commonly used approach of using residential outdoor concentrations as population exposure descriptor (model 1), led on average to 26% higher estimates (15.7 μg/m3) compared with the most complex model (# 6) including home and school outdoor and indoor, other indoor and traffic microenvironments (12.5 μg/m3). These results emphasize the importance of including spatial mobility, time-activity and infiltration to reduce bias in exposure estimates. Presented on: Science of the Total Environment

The new PET tracer, 18F-flurpiridaz, with high myocardial extraction allows quantitative myocardial blood flow (MBF) estimation from dynamic PET data and tracer kinetic modeling. The goal of this study is to determine the optimal imaging protocols and parameters using a realistic simulation study. The time activity curves (TACs) of different tissue organs from a 30-s infusion time (IT) of 18F-flurpiridaz in a dynamic PET study were extracted from a previous study. The TACs at different time points were incorporated in a series of realistic 3D XCAT phantoms from which the parameters of a 2-compartment model and the 'true' MBF of 18F-flurpiridaz were determined. The compartmental model was used to generate TACs from 7 additional ITs. PET projection data from the XCAT phantoms were generated using Monte Carlo simulation. They were reconstructed using an OS-EM reconstruction algorithm with different update number (N) to obtain dynamic PET images. The blood and myocardial TACs were derived from the dynamic images from which the MBF and %MBF error was estimated. The %MBF error decreases with increasing N of the OS-EM and levels off after ∼42. The 30-s IT gave the smallest %MBF error that decreases from ∼0.57% to ∼19.40%. The MBF for 2-min, 4-min, 8-min and 16-min IT were statistically significant different from the MBF for 30-s IT (P

The aims of this study were to quantify the contributions of activities or microenvironments (MEs) to daily total exposure to and potential dose of black carbon (BC). Daily BC exposures (24-h) were monitored using a micro-aethalometer micoAeth AE51 with forty school-aged children living in an urban area in Korea from August 2015 to January 2016. The children's time-activity patterns and the MEs they visited were investigated by means of a time-activity diary (TAD) and follow-up interviews with the children and their parents. Potential inhaled dose was estimated by multiplying the airborne BC concentrations (μg/m3) we monitored for the time the children spent in a particular ME by the inhalation rate (IR, m3/h) for the time-activity performed. The contribution of activities and MEs to overall daily exposure to and potential dose of BC was quantified. Overall mean daily potential dose was equal to 24.1 ± 10.6 μg/day (range: 6.6–46.3 μg/day). The largest contribution to BC exposure and potential dose (51.9% and 41.7% respectively) occurred in the home thanks to the large amount of time spent there. Transportation was where children received the most intense exposure to (14.8%) and potential dose (20.2%) of BC, while it accounted for 7.6% of daily time. School on weekdays during the semester was responsible for 20.3% of exposure and 22.5% of potential dose. Contribution to BC exposure and potential dose was altered by several time-activity parameters, such as type of day (weekdays vs. weekends; school days vs. holidays), season, and gender. Traveling by motor vehicle and subway showed more elevated exposure or potential dose intensity on weekdays or school days, probably influenced by the increased surrounding traffic volumes on these days compared to on weekends or holidays. This study may be used to prioritize targets for minimizing children's exposure to BC and to indicate outcomes of BC control strategies.

This paper describes the combination of a physical pollutant model IAPPEM with a time activity profile, to create an air pollutant personal exposure model. A previous study has already demonstrated the capability of IAPPEM in predicting indoor Particulate Matter (PM) concentrations in a residential environment. The present work investigates personal exposure variability between individuals and, doors opened vs closed scenarios, by examining the movements of four individuals through the same dwelling. The results of the simulations highlight the distinction between personal exposure and indoor concentrations, providing computational validation to well-documented experimental differences that exist between indoor concentrations and personal exposure. Using IAPPEM, personal exposure is calculated according to the percentage contribution from the time spent in each room, illustrating that the periods of presence, in relation to the times of indoor source emission, are as important as the durations spent in each room. This study provides a comparison between two approaches for evaluating personal exposure: a time-weighted average and a time activity profile. The results showed that a time-weighted averaged profile is a poor substitute when compared with personal exposure calculated based on a time activity profile, as, in each simulated scenario, exposures were under-predicted using the time-weighted approach, in some cases by up to 135%.