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PurposeReaders articulate mood in deeply subjective ways, yet the underlying structure of users' understanding of the media they consume has important implications for retrieval and access. User articulations might at first seem too idiosyncratic, but organizing them meaningfully has considerable potential to provide a better searching experience for all involved. The current study develops mood categories inductively for fiction organization and retrieval in information systems.Design/methodology/approachThe authors developed and distributed an open-ended survey to 76 fiction readers to understand their preferences with regard to the affective elements in fiction. From the fiction reader responses, the research team identified 161 mood terms and used them for further categorization.FindingsThe inductive approach resulted in 30 categories, including angry, cozy, dark and nostalgic. Results include three overlapping mood families: Emotion, Tone/Narrative, and Atmosphere/Setting, which in turn relate to structures that connect reader-generated data with conceptual frameworks in previous studies.Originality/valueThe inherent complexity of “mood” should not dissuade researchers from carefully investigating users' preferences in this regard. Adding to the existing efforts of classifying moods conducted by experts, the current study presents mood terms provided by actual end-users when describing different moods in fiction. This study offers a useful roadmap for creating taxonomies for retrieval and description, as well as structures derived from user-provided terms that ultimately have the potential to improve user experience.

As the frequency and intensity of wildfires are projected to globally amplify due to climate change, there is a growing need to quantify the impact of exposure to wildfires in vulnerable populations such as adolescents. In our study, we applied rigorous causal inference methods to estimate the effect of wildfire exposure on academic performance of high school students in Brazil between 2009 and 2015. Using longitudinal data from 8,183 high schools across 1,571 municipalities in Brazil, we estimated that the average performance in most academic subjects decreases under interventions that increase wildfire exposure, e.g., a decrease of 1.8% (p= 0.01) in the natural sciences when increasing the wildfire density from 0.0035 wildfires/km2(first quantile in the sample) to 0.0222 wildfires/km2(third quartile). Furthermore, these effects considerably worsened over time and were worse in regions with lower income. Our findings highlight the adverse impact of wildfires on educational outcomes.

Background Evidence of patterns of medical utilization and distribution of comorbidities among individuals using methamphetamine remains limited. Objective This study aims to investigate changes in medical utilization and comorbidities before and after a diagnosis of methamphetamine use disorder. Methods A total of 3321 cases (79% were male) of methamphetamine use disorder between January 1, 1996, and December 31, 2012, were identified from Psychiatric Inpatient Medical Claims database in Taiwan. Information was collected on demographics, diagnoses, and medical utilizations. The date of newly diagnosed with methamphetamine use disorder was defined as the baseline. Mirror-image study design was used to compare changes in medical utilization and comorbidities between the pre-baseline period (within 1 year before diagnosis) and the post-baseline period (within 1 year after diagnosis). Conditional logistic regression was used to estimate changes in medical utilization and comorbidities. Results Most cases (77%) were first identified in a psychiatric department. There is a significant increase (P Conclusions We found significant increases of medical utilization and psychiatric comorbidities after diagnosed with methamphetamine use disorder. These findings may reflect the problem of delayed diagnosis and treatment. Enhancement of early identification of methamphetamine use disorder in general practice is required for early intervention and decreased subsequent morbidities.

Globalization has prompted cross-cultural migration in search of employment opportunities, and poor adaptation during acculturation is widely known to cause additional psychosocial stress. Hence, the objective of this study was to investigate migrant workers’ perceptions of acculturation, identify work-related stressors, and understand the respective coping strategies among male Indonesians in the manufacturing industry, particularly during the COVID-19 pandemic. Fifteen workers were recruited and interviewed on their acculturation experiences. We found that the workers were susceptible to forced adaptation to stressful conditions relating to work organization, economic distress, interaction with the manpower agencies, language barriers, and so on. During the pandemic, workers experienced overload, economic hardship, suspended home visits, isolation, discrimination, and fear of cluster infection in the crowded dormitory. We also found that workers were able to adopt coping strategies by capitalizing on resources at the individual, institutional, and governmental policy levels to actively solve problems, increase emotional support, and fortify self-appraisals. The identified coping strategies could inform policy development to assist with positive adaptation and promote the well-being of the migrant worker population.

Few studies have analyzed healthcare utilization before suicide among individuals with attention-deficit/hyperactivity disorder (ADHD). This study examined the pattern of healthcare utilization and comorbidities shortly before death among patients with ADHD who died by suicide and compared these data with those of living controls. This study used Taiwan's National Health Insurance Research Database to identify patients with ADHD (N = 379,440) between January 1, 2001, and December 31, 2016. Subsequently, the researchers identified 159 suicide decedents by linking each patient with the National Mortality Database. By conducting a nested case-control study with risk-set sampling from the ADHD cohort, the researchers selected 20 age- and sex-matched controls (n = 3180) for each patient who died by suicide (cases). The researchers then applied conditional logistic regression to investigate differences in healthcare utilization as well as psychiatric and physical comorbidities between case patients and controls. Case patients had higher healthcare utilization within 3 months before suicide, particularly in the psychiatry, emergency, internal medicine, neurosurgery, and plastic surgery departments. These patients also had higher risks of psychiatric comorbidities, including schizophrenia, bipolar disorder, depressive disorder, and sleep disorder, as well as physical comorbidities such as hypertension and other forms of heart disease. Among patients with ADHD, suicide decedents had increased healthcare utilization and higher risks of specific psychiatric and physical comorbidities than living controls. Thus, for suicide prevention among individuals with ADHD, suicide risk must be detected early and comorbidities should be adequately managed.

This paper proposes TechLifeProbe to improve adolescents’ technology abuse through sharing data with their parents. We hope to use TechLifeProbe to explore how data sharing among adolescents and parents helps them improve the technology abuse.

Background Since the late 1990s, methamphetamine use has become a considerable public health concern. Despite high suicide rates among methamphetamine users, studies exploring medical utilization and psychiatric and physical comorbidities before suicide are scant. We aim to examine the pattern of medical utilization and distribution of comorbidities shortly before suicide in methamphetamine users who died of suicide and compared these data with those of living methamphetamine users. Methods From Taiwan’s National Health Insurance Research Database, we identified the cohort with methamphetamine use disorder (n = 23,248) between January 1, 2001, and December 31, 2005. We identified 5972 deceased patients (of whom 745 died of suicide) by linking each patient with the national mortality database during the study period. By conducting a nested case–control study with risk-set sampling, from the methamphetamine cohort, we selected four age- and sex-matched controls for each patient who died of suicide (cases). We applied conditional logistic regression to investigate differences in medical utilization and physical and psychiatric comorbidities between cases and controls. Results Cases had higher medical utilization within 3 months before suicide, particularly in the departments of psychiatry, internal medicine, emergency, and family practice. Cases had higher risks of physical comorbidities, including pneumonia and renal disease, and psychiatric comorbidities, including depressive disorder, sleep disorder, drug-induced mental disorder, schizophrenia, and bipolar disorder. Conclusions The findings of increased medical utilization and the higher risks of physical and psychiatric comorbidities in cases are crucial for developing specific interventions to prevent suicide in this patient population.

BACKGROUND AND OBJECTIVES Planning platelet collection and inventory must rely not only on adequate forecasts of transfusion demand but also sophisticated mathematical modeling techniques. This research aims to develop a better demand forecasting model of apheresis platelets and a mathematical programming model to determine the best target amounts of apheresis platelet collection. MATERIALS AND METHODS Time series data of apheresis platelets collected from donors and platelets supplied to hospitals daily in Taipei Blood Center from January 2014 to December 2015 was used to fit a forecasting model which combines a regression-type model for formulating the deterministic trends and seasonal variation and an autoregressive moving average model (ARMA) for explaining remaining serial correlations. A seasonal autoregressive integrated moving average (SARIMA) model was also used for benchmarking the prediction performance. A linear programming model was then formulated to solve for the optimal daily target collection volumes that maximize the total social benefits. RESULTS The time series model achieved good predictive power with a mean absolute percentage error less than 10%. The appropriateness of the proposed target collection volumes was also verified by using a simulation model, and the proportion of the total platelets requested by hospitals that can be filled by collected apheresis platelets can increase significantly by using the new policy. CONCLUSION The methods proposed in this study can be easily implemented to enhance the management efficiency of blood collecting and supplying of a blood center, and to decrease the costs of the blood outdates and shortages.

Background and aims Although methamphetamine use is a serious public health problem, large-scale cohort studies assessing methamphetamine-related mortality are scant. This study investigated all-cause mortality and suicide methods in people with methamphetamine use disorder. Design A cohort record-linkage study using data from Taiwan's National Health Research Institute Database (NHIRD) linked to Taiwan's National Death Certification System. Setting Taiwan. Participants A total of 23 248 individuals with methamphetamine use disorder between 1 January 2001 and 31 December 2005. Measurements The outcome variables included mortality rates and standardized mortality ratios (SMRs) for all causes of death and for each suicide method. Findings Compared with the general population, the current cohort had an increased all-cause mortality (SMR = 5.4), with the SMR for unnatural causes (14.8) higher than that for natural causes (7.5). Among all causes of death, suicide had the highest SMR (16.3), followed by neurological diseases (9.7). Among the methods of choice for suicide, drug overdose had the highest SMR (24.9). The incidence of charcoal burning and hanging was significantly higher in men and that of jumping from a high place was significantly higher in women. Conclusion People in Taiwan with methamphetamine use disorder appear to have a significantly increased all-cause mortality rate compared with the general population, with suicide having the highest contribution, particularly suicide via drug overdose. The methods of choice for suicide revealed distinct patterns between men and women.

This research is motivated by the increasing significance of situated and sketching activities to co-speculate alternative futures. Our purpose is to present newspapers as imaginary material and how they relate to rich speculation in domestic networked-objects with regard to the emerged entanglement experience. As most studies aim at providing representation of everyday life and imaginative triggers as entanglement material for speculation, this research focuses on the relationship between news headlines and evocative objects. We then explore how collaging and sketching with everyday objects, app-icon stickers together with the present and the past newspapers help to speculate the utopian, or dystopian worlds. Findings show that newspapers become an effective catalyst to slightly defamiliarize our daily life and break the inertial thinking. Based on the collages, we design speculative products that explore the diversity of the possible IOT futures. Finally, we present illustrative cases with interpretations and heuristic implications.

Technology abuse refers to the excessive use of personal technology devices, which can have a negative impact on adolescent patients' lifestyles and might lead to negative physical and mental health outcomes. This study conducted a needs assessment study to gain guidelines for the development of assistive systems to help adolescents deal with technology abuse issues. Our results identify current difficulties to depict screen use on multiple devices for the recording of device usage data as well as behavioral data related to lifestyles (e.g., sleep conditions). We also proposed a preliminary design of technology solutions to make the information sharing among patients and parents possible for constructive communication between them and provide treatment teams with the data necessary for diagnosis and the formulation of treatment plans.

Orexin has been suggested to play a role in regulating the reward circuits and enhancing drug-seeking behaviors; however, its role in methamphetamine (METH) addiction remains unclear. We previously found that blood orexin-A levels are upregulated in individuals with recent METH exposure. Whether the levels would be altered following withdrawal is unknown. In this study, we compared the levels of serum orexin-A in individuals who use METH between the acute withdrawal (AW) phase and the subacute withdrawal (SAW) phase at baseline (T1) and examined the alterations in these levels after 2 weeks of abstinence (T2). In total, 60 participants (51 men and 9 women) were enrolled in the study; 20 participants with METH-positive urine test results were included in the AW group, and 40 participants with METH-negative urine test results who had self-reportedly last taken METH within the preceding 1-2 months were included in the SAW group. Serum orexin-A levels were measured using enzyme-linked immunosorbent assay. No significant differences in orexin-A levels were observed between the AW and SAW groups at baseline (p = .06). After 2 additional weeks of abstinence, the levels decreased significantly in the SAW group (0.58 ± 0.13 ng/mL) but not in the AW group (0.50 ± 0.14 ng/mL, p = .004). Our results demonstrated that orexin-A levels might decrease after a longer period of METH withdrawal, indicating that the orexin system is dysregulated in the addictive process of METH. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Recycling swine wastewater is an environmental and economic issue for promoting the sustainable development of the pig industry worldwide. The application of a flocculant, non-ionic polyacrylamide (NPAM) for treating the contaminants in wastewater was trialed in this study. Firstly, the optimal pH value for the coagulation–flocculation of NPAM was adjusted by hydrochloric acid and sodium hydroxide. The viscosity of the flocculant solution was examined by a rotational viscometer and the morphology of the flocculant on the glass surface was examined by an optical microscope and an atomic force microscope. The result showed that a pH value of 11 or more was best for NPAM coagulation–flocculation. Subsequently, the swine wastewater from the anoxic reactor of a three-stage manure treatment system was adjusted by a pH adjuster, calcium hydroxide, followed by the coagulation–flocculation of NPAM. The quality of the final, treated water was examined by a regular wastewater analysis. The results showed that the removal rates for copper ions, zinc ions, NH4+–N, total phosphate (TP), and total nitrogen (TN) were 96.3%, 97.8%, 99.2%, 94.9%, and 99.1%, respectively. Our study concluded that this water recycling method combining the existing organic fertilizer production and power generation enhanced the recycling strategy for swine wastewater treatment and could further the sustainable development of the pig industry.

In many biological experiments, certain values of a biomarker are often nondetectable due to low concentrations of an analyte or the limitations of a chemical analysis device, resulting in left-censored values. There is an increasing demand for the analysis of data subject to detection limits in clinical and environmental studies. In this paper, we develop a novel statistical method for the maximum likelihood estimation in generalized linear models with covariates subject to detection limits. Simulations are carried out to study the relative performance of the proposed estimators, as compared to other existing estimators. The proposed method is also applied to a real dataset from the Maternal-Infant Research on Environmental Chemicals cohort study, where we investigate how different chemical mixtures affect the health outcomes of infants and pregnant women.

Causation probabilities of multiple-run-rules based on patterns of multi-state trials have been used and studied in various fields such as quality control, reliability of engineering system, biology, DNA sequence analysis and survival analysis. In this manuscript, we derive the limiting results for two types of conditional causation probabilities for multiple-run-rules by using the finite Markov chain imbedding technique. Extension and numerical examples are given to illustrate the theoretical results.

Objective Methamphetamine (METH) use and adverse childhood experiences (ACEs) has been associated with an increased risk of suicidal behaviour. However, whether METH use underlies the risk of suicide attributable to ACEs is unknown and warrants investigation to inform preventive interventions. In this study, we examined the mediating role of METH use in the relationship between attempted suicide and ACEs. Method METH users recruited from a mandatory detoxification center (n = 346) and healthy controls (n = 342) both completed a survey related to 9 types of ACE, which was based the Family Health Questionnaire. A lifetime history of attempted suicide was obtained using the Chinese version of the Composite International Diagnostic Interview. We conducted a bootstrapped mediation analysis to examine the mediating effect of METH use on the association between ACEs and attempted suicide. Results Female gender, METH use, and having multiple (≥3) ACEs were associated with an increased risk of attempted suicide. A dose–response relationship between the number of ACEs and suicide rate was observed among individuals with METH use. METH use significantly mediated the association between ACEs and attempted suicide in those with multiple (2 and 3 ACEs respectively with proportion mediated 0.16 and 0.42) and specific types of ACEs (physical abuse, witnessing maternal battering, household substance abuse, sexual abuse, and parental separation with proportion mediated 0.25, 0.35, 0.38, 0.48, 0.47 respectively). Conclusion Our study is the first to demonstrate that METH use partially mediates the association between ACEs and attempted suicide. Addressing METH use in people with ACEs could reduce their suicide risk.

This study presents preliminary themes surfaced from an ongoing ethnographic study. The research question is: how and where do cultures influence the cataloging practices of using U.S. standards to catalog Chinese materials? The author applies warrant as a lens for evaluating knowledge representation systems, and extends the application from examining classificatory decisions to cataloging decisions. Semantic warrant as a conceptual tool allows us to recognize and name the various rationales behind cataloging decisions, grants us explanatory power, and the language to "visualize" and reflect on the conflicting priorities in cataloging practices. Through participatory observation, the author recorded the cataloging practices of two Chinese catalogers working on the same cataloging project. One of the catalogers is U.S. trained, and another cataloger is a professor of Library and Information Science from China, who is also a subject expert and a cataloger of Chinese special collections. The study shows how the catalogers describe Chinese special collections using many U.S. cataloging and classification standards but from different approaches. The author presents particular cases derived from the fieldwork, with an emphasis on the many layers presented by cultures, principles, standards, and practices of different scope, each of which may represent conflicting warrants. From this, it is made clear that the conflicts of warrants influence cataloging practice. We may view the conflicting warrants as an interpretation of the tension between different semantic warrants and the globalization and localization of cataloging standards.

Background Global temperature and the frequency of extreme weather events are projected to increase and affect indoor exposure to outdoor particulate matter (PM); however, no studies have quantitatively examined the effect of climate change on particle infiltration and indoor PM exposure. Obective To quantify the relationship between future changes in ambient temperature and fine particle (PM 2.5 ) infiltration in the Greater Boston area. Methods We assembled a large database of outdoor and indoor PM 2.5 data from 340 homes, and used the indoor-outdoor sulfur ratio ( S r ) as a surrogate for PM 2.5 infiltration. We employed linear mixed-effects models to examine the relationship between S r and ambient temperature for all homes in the database and a subgroup of naturally ventilated homes. We used projected temperature data from 1981 to 2000 and 2046–2065 to predict future changes in S r . Results The summer-winter difference in S r was calculated to be 30% and 54% for all homes and in the naturally ventilated subgroup, respectively. The largest future difference in S r (21%) was linked to differences in prevalence of air conditioning. Furthermore, S r was predicted to increase by 7% for naturally ventilated homes and 2% for all homes in summer, corresponding to an average increase of 2–3 °C in future temperature. Conclusions We found that increases in future temperature due to climate change will be associated with increased PM 2.5 infiltration, particularly in summer. The predicted temperature-related changes in S r can be used to characterize future health risk due to elevated indoor PM 2.5 exposure through increased particle infiltration.

Due to the uneven distribution of geochemical elements and environmental pollution caused by industrial development, the environmental media in some areas are rich in fluorine and arsenic. High-fluorine, high-arsenic, and double high regions of both fluorine and arsenic exist widely in the world. The attention to the harm of endemic fluoride, arsenic and their combined poisoning on the intelligence, learning and memory of children has been paid. We herein reviewed the research results on the effects of fluorine, arsenic and their combined effects on learning and memory.

Background Rising temperatures due to climate change are expected to impact human adaptive response, including changes to home cooling and ventilation patterns. These changes may affect air pollution exposures via alteration in residential air exchange rates, affecting indoor infiltration of outdoor particles. We conducted a field study examining associations between particle infiltration and temperature to inform future studies of air pollution health effects. Methods We measured indoor fine particulate matter (PM2.5) in Atlanta in 60 homes (810 sampling-days). Indoor-outdoor sulfur ratios were used to estimate particle infiltration, using central site outdoor sulfur concentrations. Linear and mixed-effects models were used to examine particle infiltration ratio-temperature relationships, based on which we incorporated projected meteorological values (Representative Concentration Pathways intermediate scenario RCP 4.5) to estimate particle infiltration ratios in 20-year future (2046–2065) and past (1981–2000) scenarios. Results The mean particle infiltration ratio in Atlanta was 0.70 ± 0.30, with a 0.21 lower ratio in summer compared to transition seasons (spring, fall). Particle infiltration ratios were 0.19 lower in houses using heating, ventilation, and air conditioning (HVAC) systems compared to those not using HVAC. We observed significant associations between particle infiltration ratios and both linear and quadratic models of ambient temperature for homes using natural ventilation and those using HVAC. Future temperature was projected to increase by 2.1 °C in Atlanta, which corresponds to an increase of 0.023 (3.9%) in particle infiltration ratios during cooler months and a decrease of 0.037 (6.2%) during warmer months. Discussion We estimated notable changes in particle infiltration ratio in Atlanta for different 20-year periods, with differential seasonal patterns. Moreover, when stratified by HVAC usage, increases in future ambient temperature due to climate change were projected to enhance seasonal differences in PM2.5 infiltration in Atlanta. These analyses can help minimize exposure misclassification in epidemiologic studies of PM2.5, and provide a better understanding of the potential influence of climate change on PM2.5 health effects.

Suppose an urn contains m distinct coupons, labeled from 1 to m. A random sample of k coupons is drawn without replacement from the urn, numbers are recorded and the coupons are then returned to the urn. This procedure is done repeatedly and the sample sizes are independently identically distributed. Let W be the total number of random samples needed to see all coupons at least l times $$(l \ge 1)$$ . Recently, for $$l=1$$ , the approximation for the first moment of the random variable W has been studied under random sample size sampling scheme by Sellke (Ann Appl Probab, 5:294–309, 1995). In this manuscript, we focus on studying the exact distributions of waiting times W for both fixed and random sample size sampling schemes given $$l \ge 1$$ . The results are further extended to a combination of fixed and random sample size sampling procedures.

Wallenstein et al. (1994) discussed the power via combinatorial calculations for scan statistics against a pulse alternative given certain proper conditions. Our work extends their results and provides an alternative way to obtain the distribution of a scan statistic under various alternative conditions. An efficient and intuitive expression for the distribution as well as power of the scan statistic is introduced via finite Markov chain imbedding (FMCI). The numerical results of the power for a discrete scan statistic against various conditions are presented.

In many biological experiments, certain values of a biomarker are often nondetectable due to low concentrations of an analyte or the limitations of a chemical analysis device, resulting in left-censored values. There is an increasing demand for the analysis of data subject to detection limits in clinical and environmental studies. In this paper, we develop a novel statistical method for the maximum likelihood estimation in generalized linear models with covariates subject to detection limits. Simulations are carried out to study the relative performance of the proposed estimators, as compared to other existing estimators. The proposed method is also applied to a real dataset from the Maternal-Infant Research on Environmental Chemicals cohort study, where we investigate how different chemical mixtures affect the health outcomes of infants and pregnant women.

Cataloging models emphasize selective aspects of cataloging and serve the purposes of conceptual debates and theoretical developments. Many complexities, uncertainties, dilemmas, challenges, and “rare” scenarios that catalogers encounter in practice are not presented in the models. To study cataloging practices, the author presents cataloging scenarios observed from an ongoing fieldwork. Through weekly participatory observations and unstructured interviews of catalogers, the work presents cases among the diverse and complex cataloging practices, and surfaces the tensions and time involved in cataloging. This paper will focus on three themes: workarounds, disagreements, and manifestations of culture in cataloging practice. The first scenario describes a non-linear cataloging process and the different workarounds applied. The workarounds highlight the tacit knowledge of experienced catalogers. The second scenario shows catalogers’ different perspectives about the authorship of stone rubbings. Disagreements, negotiation, and compromises in cataloging process are often not documented or explained. This scenario examines cataloging contexts that we cannot observe from analyzing cataloging standards or records. The third scenario describes the proposal of a Library of Congress Demographic Group Term (LCDGT): Zhiqing, and how it was approved as a LCSH: Zhiqing generation instead. The term encompasses a combination of regional, temporal, and cultural aspects of a demographic group. In the proposal process, I identified cultural manifestations in cataloging process through observing “the missing pieces” and local adaptations. This study contributes to the knowledge organization literature by presenting cataloging scenarios that require prolonged engagement to study.

This paper contributes to the discussion of the purposes and functions of multi-perspective classification by raising foundational questions. Starting from the motivations of developing multi-perspective classification, the author discusses questions concerning the accommodation of different perspectives. The discussion leads to the question “what is multi-perspective classification?” and envisions a possible amelioration. Through discussing the three questions concerning the foundation of multi-perspective classification, the goal is to identify challenges and thoughts for developing multi-perspective classification before focusing on specific implementations.

This study explores the dynamics of the price discovery process between the regular and mini index futures traded on the Taiwan Futures Exchange (TAIFEX). In contrast to the US futures market, the TAIFEX operates under an automated electronic trading system for both types of contracts. After controlling for the differences in the trading mechanisms, we demonstrate that mini index futures make a greater contribution than regular index futures to the price discovery process within the TAIFEX. Regression analyses show that both relative liquidity and relative changes in liquidity between regular and mini index futures contribute to the price discovery of the mini index futures.

Previous investigations have reported intake fraction (iF) for different environments, which include ambient concentrations (outdoor exposure) and microenvironments (indoor exposure). However, little is known about iF variations due to space-time factors, especially in microenvironments. In this paper, we performed a spatio-temporal analysis of particulate matter (PM2.5) intake fractions for vehicular emissions. Specifically, we investigated hourly variation (12:00 am–11:00 pm) by micro-environments (residences and workplaces) in the Greater Toronto and Hamilton Area (GTHA), Canada. We used GIS modeling to estimate air pollution data (ambient concentration, and traffic emission) and population data in each microenvironment. Our estimates showed that the total iF at residences and workplaces accounts for 85% and 15%, respectively. Workplaces presented the highest 24 h average iF (1.06 ppm), which accounted for 25% higher than residences. Observing the iF by hour at residences, our estimates showed the highest average iF at 2:00 am (iF = 3.72 ppm). These estimates indicate that approximately 4 g of PM2.5 emitted from motor vehicles are inhaled for every million grams of PM2.5 emitted. For the workplaces, the highest exposure was observed at 10:00 am, with average iF equal to 2.04 ppm. The period of the day with the lower average iF for residences was at 8:00 am (average iF = 0.11 ppm), while for the workplaces was at 4:00 am (average iF = 0.47 ppm). Our approach provides a new perspective on human exposure to air pollution. Our results showed significant hourly variation in iF across the GTHA. Our findings can be incorporated in future investigations to advance environmental health effects research and human health risk assessment.