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Refereed/Peer-reviewed In wastewater-based epidemiology (WBE), nicotine metabolites have been used as biomarkers for monitoring tobacco use. Recently, the minor tobacco alkaloids anabasine and anatabine have been suggested as more specific biomarkers for tobacco use since nicotine use can be from both tobacco and non-tobacco sources. This study aimed to provide an in-depth evaluation of the suitability of anabasine and anatabine as WBE biomarkers of tobacco and subsequently estimate their excretion factors for WBE applications. Pooled urine (n = 64) and wastewater samples (n = 277), collected between 2009 and 2019 in Queensland, Australia, were analyzed for nicotine and its metabolites (cotinine and hydroxycotinine), as well as anabasine and anatabine. Anabasine performed as the better biomarker, showing a similar per capita load in pooled urine (2.2 ± 0.3 μg/day/person) and wastewater samples (2.3 ± 0.3 μg/day/person), while the per capita load of anatabine in wastewater was 50% higher than its load in urine. It is estimated that 0.9 μg of anabasine was excreted per cigarette smoked. Triangulation of tobacco sales data and tobacco use estimated from either anabasine or cotinine showed that anabasine-based estimates were 5% higher than sales data, while cotinine-based estimates were between 2 and 28% higher. Our results provided concrete evidence to confirm the suitability of anabasine as a specific biomarker for monitoring tobacco use by WBE.

Data-driven building operation and maintenance research such as metadata inference, fault detection and diagnosis, occupant-centric controls (OCCs), and non-invasive load monitoring have emerged (NILM) as independent domains of study. However, there are strong dependencies between these domains; for example, quality of metadata affects the usability of fault detection and diagnostics techniques. Further, faults in controls hardware and programs limit the performance of OCCs. To this end, a literature review was conducted to identify the dependencies between these domains of research. Additionally, real-world examples using operational data from three institutional buildings in Ottawa, Canada, were provided and discussed to demonstrate these dependencies. Finally, a holistic tool-agnostic workflow was introduced which suggested the implementation of operational energy efficiency measures in the following order to ensure their full potential: (1) improve metadata, (2) address faults, (3) implement OCCs, and (4) monitor enhanced key performance indicators (KPIs). The proposed workflow is intended to be comprehensive, reproducible, nonintrusive, and inexpensive to implement.Practical applications: Optimization of building operations has been emerging among energy management professionals as a relatively low-cost means to achieve energy efficiency and minimize occupants’ discomfort. To this end, this study introduces a tool-agnostic data-driven workflow to building energy management practitioners that can assist them in achieving increased energy efficiency. The proposed workflow recognizes the interdependency of the various domains of research which have historically been treated independently.

With the fundamental and design processes established, this chapter dives into occupant modeling theory and techniques. Following Chapter 2, it starts with basic concepts of occupant behavior and occupant actions. It provides some retrospective analysis of how occupants are currently modeled in design practice and building codes (based on several recent international surveys). Next, the chapter reviews a wide spectrum of models in increasing levels of complexity, including: schedules, rule-based models, various stochastic models, agent-based models, and personas. With the types of models established, theoretical and practical insights are provided regarding model development and verification. While this chapter is mainly focused on theory, it also provides an overview of methods to incorporate occupant models into BPS tools. Finally, with the introduction of more complex and less transparent occupant models, the chapter provides some examples and insights about communicating their results to different stakeholders.

Smart thermostats differ significantly from traditional devices and are quickly becoming commonplace in homes. Literature demonstrates that thermostat interfaces greatly influence user interaction and related energy outcomes. Moreover, how users imagine their device to work appears to have a greater impact on usage than how the system functions. Previous work investigated manual and programmable thermostats in this context, employing user mental models (UMMs) to analyse user understanding. Since then, thermostats have developed significantly. This paper presents a novel investigation of smart thermostat UMMs. It employs contemporary methods to construct ten UMM diagrams, and three detailed case studies, contextualized with previous findings. All participants demonstrated feedback theory. Case studies highlight common misconceptions. Overall, smart thermostat UMMs appear to enable effective usage; however, some users are overwhelmed by the complexity, limiting engagement and use of features (e.g. programming).

Recent studies have shown that office building systems do not adapt well to partial occupancy (e.g., from teleworking) and thus perform suboptimally. As a result, this study aims to assess office building performance adaptability by investigating the impact of four different technologies, including occupancy-based lighting, smart plugs (occupancy-based plug load), demand-controlled ventilation (DCV), occupancy-based thermostat, and their cumulative effect in office buildings in six different Canadian climates. A three-story office building is simulated in EnergyPlus version 9.3.0 under five occupancy scenarios, including 0% occupancy, 100% occupancy, 50% uniformly distributed occupancy across the floor, 50% consolidated occupancy scenario where occupants work in core zones, and 50% consolidated occupancy scenario where occupants work in perimeter zones. The results are compared using energy use intensity (EUI), energy use intensity per occupant (EUP), and the corresponding greenhouse gas (GHG) emissions. A total of 180 simulations demonstrate the occupancy-adaptive technologies are generally most beneficial for low occupancy scenarios and milder climates. The results also show the cumulative impact of all these technologies on the potential energy savings is significant in the climates under consideration. Overall, the results show office buildings can improve their performance adaptability during partial occupancy by implementing the studied technologies. Aside from filling in the current knowledge gap in the literature on partial occupancy, the for the first time results of this study systemically demonstrate how each technology performs under different partial occupancy scenarios and how they perform together at each climate.

This paper explores how effectively building variable air volume air handling unit (VAV AHU) configurations supply required outdoor air to building spaces using data analysis and building performan...

Quantifying the energy impact of teleworking has been challenging because of the low prevalence of telework. The coronavirus disease 2019 pandemic and the associated widespread shift to telework provides a new opportunity to study the energy impact of teleworking. Within two months of the lockdowns, we surveyed 278 knowledge-based workers in Canada who started working primarily from home to investigate their energy-related behaviours and attitudes. The survey's major themes are energy-saving actions taken in the office, equipment used for telework, impacts on home energy usage, and both awareness of and response to electricity pricing. Given trends toward increased teleworking in the future, these results can inform public policy related to teleworking and energy.Quantifier l’impact du télétravail sur la consommation d’énergie a longtemps été difficile en raison du faible recours au télétravail. La pandémie de la COVID-19 et le passage généralisé au télétravail fournit une nouvelle occasion pour étudier l’impact du télétravail sur la consommation d’énergie. Dans les deux mois qui ont suivi les confinements, nous avons interrogé 278 travailleurs ayant des emplois fondés sur le savoir qui ont commencé à travailler principalement de chez eux, afin d’étudier leurs comportements et attitudes quant à la consommation d’énergie. Les thèmes principaux de l’enquête sont les actions prises au travail visant la réduction de consommation d’énergie, l’équipement utilisé pour le télétravail, l’impact sur la consommation résidentielle, et la prise de conscience et la réaction quant au prix de l’électricité. Étant donné la tendance plus accrue au télétravail à l’avenir, ces résultats peuvent éclairer la politique publique en matière de télétravail et d’énergie.

Background: Skin and soft tissue infection (SSTI) after hernia surgery is infrequent yet catastrophic and is associated with mesh infection, interventions, and hernia recurrence. Although hernia repair is one of the most common general surgery procedures, uncertainty persists regarding incidence of long-term infections. Our goal is to develop a machine learning regression model that detects the occurrence of long-term hernia-associated SSTI. Patients and Methods: The data set consisted of veterans receiving hernia repair with implanted synthetic mesh during 2008-2015. The outcome of interest was occurrence of SSTI related to the index hernia surgery over a five-year follow-up. A neural network regression was fit on a medical record reviewed sample, then applied to the study population. Results: The study population was 96,435 surgeries, of which 76,886 (79.7%) were inguinal, 11,177 (11.6%) were umbilical, and 8,372 (8.7%) were ventral. In the training set, 40 patients had SSTI probability ≥90%, of whom 38 (95%) had a true SSTI. In 249 patients with SSTI probability 90% and all were true-positives. In 100 patients with probability

A holistic fault detection and diagnostics (FDD) method should explicitly consider the dependencies between faults at the system- and zone-level to isolate the root cause. A system-level fault can trigger false alarms at the zone-level, while concealing the presence of a zone-level fault. However, most FDD methods have focused on a single component/equipment without considering the importance of the interactions between zone- and system-level devices. This paper proposes a holistic hierarchical framework for FDD, combining the process of detection and diagnosis of controls hardware and sequencing logic faults affecting the actuators at the system- and zone-level. The proposed framework follows a holistic sequential procedure to diagnose faults and suppress false alarms in this order: hard faults in air handling units (AHUs), hard faults in variable air volume (VAV) zones, sequencing logic faults in AHUs, and sequencing logic faults in VAV zones. The detection of faults is performed by visualizing the discrepancies between the expected and measured operational behaviour of AHUs and VAV boxes. Examples demonstrating the framework are provided with data from 10 different VAV AHU systems. Practical application: This paper provides a sequential hierarchical FDD framework to address two main issues in VAV AHU systems: detectability and significance. Regarding detectability, the framework prioritizes hard faults over sequencing logic faults to avoid false positives and false negatives; about significance, system-level faults are prioritized over zone-level faults to triage high-impact faults in the system. The detection of faults is performed via visualizing the biases from the expected behaviour of AHU and VAV characteristics to provide an envisioning interpretation for the experts in facilities management in commercial buildings to find the root cause of the fault and fix them on-site.

We present evidence that tax laws distort acquisition decisions for many of the largest U.S. firms. We find that tax “sophistication”, proxied by the use of Double Irish subsidiary structures, is associated with between a 7.4% and 15.1% increase in domestic acquisitions. These results are concentrated in deals less likely to trigger regulatory scrutiny, and these deals are associated with decreases in offshore earnings using difference-in-difference tests. This is consistent with sophisticated firms using complicated transactions to invest pre-tax offshore profits domestically without repatriation taxes. We control for several sources of endogeneity that potentially affect other foreign tax minimization proxies.

International audience; Recent research suggests that a time-varying indoor thermal environment can lead to energy savings and contribute to boost buildings' energy flexibility. However, thermal comfort standardization has so far considered thermal comfort criteria as constant throughout the day. In general, very little attention has been given to the ‘ time of day' variable in the context of thermal comfort research. In this paper, we show some evidence of a time-varying thermal perception by using: (1) data from about 10,000 connected Canadian thermostats made available as part of the ‘ Donate Your Data' dataset and (2) about 22,000 samples of complete (objective + ‘ right-here-right-now' subjective) thermal comfort field data from the ASHRAE I and SCATs datasets. We observe that occupants prefer colder thermal conditions at 14:00 and progressively warmer ones in the rest of the day, indistinctively in the morning and evening. Neutral temperature differences between 08:00 and 14:00 and 14:00 and 20:00 are estimated to be of the order of 2°C. We hypothesize that the human circadian rhythm is the cause of this difference. Nevertheless, the results of this study are only based on observational data. Thermal comfort experiments in controlled environmental chambers are required to confirm these findings and to better elucidate the effects of light and circadian timing and their interaction on thermal perception.

Following our previous study, which indicated that several occupant-related assumptions in the National Building Code (NBC) of Canada are different from findings in recent measurement-based studies, this study aims to: i) quantify the direct energy impact associated with discrepancies between the current code’s occupant-related assumptions and those obtained from recent measurement-based studies and ii) demonstrate how key NBC requirements could be reevaluated as a result of the new/proposed occupant-related assumptions. In this regard, this paper applies energy modeling and life cycle costing (LCC) to 11 representative archetypes across different Canadian climate zones. First, EnergyPlus simulations were conducted to evaluate the energy impact of the proposed and existing occupant-related assumptions. Second, LCC was used to evaluate code requirements’ economic implications under these two sets of occupant assumptions. Our results indicate that the default occupant-related assumptions used by NBC generally lead to higher predicted heating, but lower cooling, energy consumption. However, heating energy is more significant since heating energy use is typically an order of magnitude higher than cooling energy use for Canadian homes. Our analysis also indicates that the current occupant-related NBC assumptions yield different optimal potential code-compliant upgrades in some cases relative to the new energy-related occupant assumptions.

Multi-unit residential building (MURB) occupants often express dissatisfaction with their suites' acoustic conditions despite existing building acoustic standards and regulations as well as growing research on noise control and building acoustics. Reasons for this include the lack of proper characterization of acoustic comfort in MURBs and lack of comprehensive and stringent regulations. To better understand factors that impact acoustic comfort and explore strategies to improve the acoustic performance of MURBs, investigations of acoustic conditions were carried out. This work presents the results of the investigations which include subjective and objective evaluations of acoustic conditions in two MURBs. Impact sound insulation measurements using both a tapping machine and a rubber ball as well as 24-hour indoor noise monitoring were carried out in unoccupied suites. An online survey was then used to collect subjective assessments of the noise conditions in the buildings and the effects on occupants' comfort post occupancy. Results of the data analysis suggest that occupants are more sensitive to low-frequency impact sounds than mid- and high-frequency impact noise.

Using a newly assembled 50-country firm-level database spanning 19 years, we document a bright side for employees of business group–affiliated firms: less pronounced fluctuations in employment than unaffiliated firms in response to macroeconomic shocks. The results are robust to a variety of tests designed to mitigate endogeneity concerns, including propensity score matching and comparisons of successful and failed group integrations, and are present in both booms and recessions. Our results are most consistent with group internal labor markets rather than several alternative explanations (internal capital markets, a lower overall sensitivity to shocks in group firms, or agency problems). This paper was accepted by David Simchi-Levi, finance.

Background: Definitive diagnosis of acute ischemic stroke is challenging, particularly in telestroke settings. Although the prognostic utility of CT perfusion (CTP) has been questioned, its diagnostic value remains under-appreciated, especially in cases without an easily visible intracranial occlusion. We assessed the diagnostic accuracy of routine CTP in the acute telestroke setting. Methods: Acute and follow-up data collected prospectively from consecutive suspected patients with stroke assessed by a state-wide telestroke service between March 2020 and August 2021 at 12 sites in Australia were analyzed. All patients in the final analysis had been assessed with multimodal CT, including CTP, which was post-processed with automated volumetric software. Diagnostic sensitivity and specificity were calculated for multimodal CT and each individual component (noncontrast CT [NCCT], CT angiogram [CTA], and CTP). Final diagnosis determined by consensus review of follow-up imaging and clinical data was used as the reference standard. Results: During the study period, complete multimodal CT examination was obtained in 831 patients, 457 of whom were diagnosed with stroke. Diagnostic sensitivity for ischemic stroke increased by 19.5 percentage points when CTP was included with NCCT and CTA compared with NCCT and CTA alone (73.1% positive with NCCT+CTA+CTP [95% CI, 68.8–77.1] versus 53.6% positive with NCCT+CTA alone [95% CI, 48.9–58.3], P P =0.13). Multimodal CT, including CTP, demonstrated the highest negative predictive value (75.0% [95% CI, 72.1–77.7]). Patients with stroke not evident on CTP had small volume infarcts on follow-up (1.2 mL, interquartile range 0.5–2.7mL). Conclusions: Acquisition of CTP as part of a telestroke imaging protocol permits definitive diagnosis of cerebral ischemia in 1 in 5 patients with normal NCCT and CTA.