A Framework for Urban Building Energy Use Modeling

Reliable quantification of energy consumption by buildings plays a key role in development of sustainable cities. However, there are methodological uncertainties embedded in the most common urban scale energy use modeling methods and tools which affect the reliability of these tools and their applicability for decision-making purposes. This article presents a novel bottom- up data-driven framework for urban energy use modeling (UEUM) to help predict energy use more precisely through utilizing disaggregated data at building level, incorporating the actual urban spatial patterns, and testing different algorithms to propose an enhanced prediction model. This framework integrates the influential factors in the model including building characteristics; i.e., height, as an urban intensity metric, urban attributes; i.e., sprawl indices, that are captured in a multidimensional way representing compactness and connectivity of neighborhoods, and occupant characteristics. A case study on 800,000 buildings in seventy-seven neighborhoods in Chicago was used to test the framework. This framework has the potential to help better understand the existing urban energy use profiles and provides a more holistic image of urban energy use at multi-scales of building, block, neighborhood, and urban levels

Environmental and economic implications of building envelope design

There is a wealth literature on operational energy consumption of buildings and how building skins contribute to that. Little is known about the life-cycle environmental impacts of building skins and it is not clear if the operational energy savings that are achieved by improvement strategies in building skin (such as more insulation, external shading devices, PV systems) would indeed result in lower environmental impacts from a life-cycle perspective. Even less clear is how economic and life-cycle environmental impacts of buildings would vary by the changes in architectural design parameters. In the present study, we quantify the variations in operational energy, environmental impacts and costs as a result of change in building skin design and construction parameters. We will examine building envelopes in low-rise office buildings from economic and environmental perspectives. For this purpose, 91 different design combinations of a building envelope are considered with different thermal resistance values of wall, wall-to-window ratios, window types, and frame materials. We then use Environmental Life Cycle Assessment (LCA) to study the variations of design combination with respect to global warming, acidification, eutrophication, and smog formation. Simultaneously, Life- Cycle Cost Analysis (LCCA) is applied to examine the cost changes in design combinations. Then, regression analysis is conducted to find the association between design combinations and changes in environmental impacts and cost fluctuations

A procedure to characterize geographic distributions of rare disorders in cohorts

<p>Abstract</p> <p>Background</p> <p>Individual point data can be analyzed against an entire cohort instead of only sampled controls to accurately picture the geographic distribution of populations at risk for low prevalence diseases. Analyzed as individual points, many smaller clusters with high relative risks (RR) and low empirical p values are indistinguishable from a random distribution. When points are aggregated into areal units, small clusters may result in a larger cluster with a low RR or be lost if divided into pieces included in units of larger populations that show no increased prevalence. Previous simulation studies showed lowered validity of spatial scan tests for true clusters with low RR. Using simulations, this study explored the effects of low cluster RR and areal unit size on local area clustering test (LACT) results, proposing a procedure to improve accuracy of cohort spatial analysis for rare events.</p> <p>Results</p> <p>Our simulations demonstrated the relationship of true RR to observed RR and p values with various, randomly located, cluster shapes, areal unit sizes and scanning window shapes in a diverse population distribution. Clusters with RR < 1.7 had elevated observed RRs and high p values.</p> <p>We propose a cluster identification procedure that applies parallel multiple LACTs, one on point data and three on two distinct sets of areal units created with varying population parameters that minimize the range of population sizes among units. By accepting only clusters identified by all LACTs, having a minimum population size, a minimum relative risk and a maximum p value, this procedure improves the specificity achieved by any one of these tests alone on a cohort study of low prevalence data while retaining sensitivity for small clusters. The procedure is demonstrated on two study regions, each with a five-year cohort of births and cases of a rare developmental disorder.</p> <p>Conclusion</p> <p>For truly exploratory research on a rare disorder, false positive clusters can cause costly diverted research efforts. By limiting false positives, this procedure identifies 'crude' clusters that can then be analyzed for known demographic risk factors to focus exploration for geographically-based environmental exposure on areas of otherwise unexplained raised incidence.</p

Training Residents to Employ Self-efficacy-enhancing Interviewing Techniques: Randomized Controlled Trial of a Standardized Patient Intervention

Current interventions to enhance patient self-efficacy, a key mediator of health behavior, have limited primary care application. To explore the effectiveness of an office-based intervention for training resident physicians to use self-efficacy-enhancing interviewing techniques (SEE IT). Randomized controlled trial. Family medicine and internal medicine resident physicians (N = 64) at an academic medical center. Resident use of SEE IT (a count of ten possible behaviors) was coded from audio recordings of the physician-patient portion of two standardized patient (SP) instructor training visits and two unannounced post-training SP visits, all involving common physical and mental health conditions and behavior change issues. One post-training SP visit involved health conditions similar to those experienced in training, while the other involved new conditions. Experimental group residents demonstrated significantly greater use of SEE IT than controls, starting after the first training visit and sustained through the final post-training visit. The mean effect of the intervention was significant [adjusted incidence rate ratio for increased use of SEE IT = 1.94 (95% confidence interval = 1.34, 2.79; p &lt; 0.001)]. There were no significant effects of resident gender, race/ethnicity, specialty, training level, or SP health conditions. SP instructors can teach resident physicians to apply SEE IT during SP office visits, and the effects extend to health conditions beyond those used for training. Future studies should explore the effects of the intervention on practicing physicians, physician use of SEE IT during actual patient visits, and its influence on patient health behaviors and outcomes

Environmental impacts comparison between on-site vs. prefabricated just-in-time (prefab-JIT) rebar supply in construction projects

In the on-site rebar delivery system, as the common method of rebar supply in the construction industry, reinforced steel bars are delivered in large batches from supplier's facilities through contractor's warehouse to the construction site. Rebars are then fabricated on-site and installed after assembly. In the new delivery system, called prefabrication Just-In-Time (prefab-JIT) system, the off-site cut and bend along with frequent rebar delivery to the site are applied in order to improve the process and increase its efficiency. The main objective of this paper is to assess and compare the environmental impacts resulting from the air emissions associated with the two rebar delivery systems in a case study construction project. Environmental impact categories of interest include global warming, acidification, eutrophication, and smog formation. A process-based cradle-to-gate life cycle assessment methodology is applied to perform the analysis. The results show that the prefab-JIT rebar delivery system causes less contribution to all mentioned environmental impact categories compared with a traditional on-site delivery system

Purification of Immature Neuronal Cells from Neural Stem Cell Progeny

Large-scale proliferation and multi-lineage differentiation capabilities make neural stem cells (NSCs) a promising renewable source of cells for therapeutic applications. However, the practical application for neuronal cell replacement is limited by heterogeneity of NSC progeny, relatively low yield of neurons, predominance of astrocytes, poor survival of donor cells following transplantation and the potential for uncontrolled proliferation of precursor cells. To address these impediments, we have developed a method for the generation of highly enriched immature neurons from murine NSC progeny. Adaptation of the standard differentiation procedure in concert with flow cytometry selection, using scattered light and positive fluorescent light selection based on cell surface antibody binding, provided a near pure (97%) immature neuron population. Using the purified neurons, we screened a panel of growth factors and found that bone morphogenetic protein-4 (BMP-4) demonstrated a strong survival effect on the cells in vitro, and enhanced their functional maturity. This effect was maintained following transplantation into the adult mouse striatum where we observed a 2-fold increase in the survival of the implanted cells and a 3-fold increase in NeuN expression. Additionally, based on the neural-colony forming cell assay (N-CFCA), we noted a 64 fold reduction of the bona fide NSC frequency in neuronal cell population and that implanted donor cells showed no signs of excessive or uncontrolled proliferation. The ability to provide defined neural cell populations from renewable sources such as NSC may find application for cell replacement therapies in the central nervous system

Green building design and assessment with computational BIM: The workflow and case study

Due to growing concern regarding sustainability in the built environment, several green building assessments and rating tools have been established worldwide including Green Building Index (GBI) in Malaysia which was introduced in 2009. However, the current methods of measuring, analysing and documenting the green building design rely on a number of disjointed processes to meet the discrete requirements for various building systems. The development of building information modelling (BIM) together with computational programming has made it easier for complicated building modelling to be digitally constructed, generating required information to support green building design and assessment throughout various project stages. Thereby, the aim of this research is to integrate computational BIM with green building design and assessment in Malaysia, using GBI as a unique case and an office building in Kuala Lumpur, Malaysia as a case study. Match-up of BIM (Revit) functionalities and GBI (NRNC) criteria was formulated, then visual programming (Dynamo) was employed to automate the BIM data management process. The findings of this research have developed workflows and templates to assess several criteria, namely energy efficiency (EE), indoor environmental quality (EQ), sustainable site planning and management (SM) and material and resources (MR), which allow a higher level of automation in green building assessment

Spatial, temporal, and demographic patterns in prevalence of smoking tobacco use and attributable disease burden in 204 countries and territories, 1990-2019 : a systematic analysis from the Global Burden of Disease Study 2019

Background Ending the global tobacco epidemic is a defining challenge in global health. Timely and comprehensive estimates of the prevalence of smoking tobacco use and attributable disease burden are needed to guide tobacco control efforts nationally and globally. Methods We estimated the prevalence of smoking tobacco use and attributable disease burden for 204 countries and territories, by age and sex, from 1990 to 2019 as part of the Global Burden of Diseases, Injuries, and Risk Factors Study. We modelled multiple smoking-related indicators from 3625 nationally representative surveys. We completed systematic reviews and did Bayesian meta-regressions for 36 causally linked health outcomes to estimate non-linear dose-response risk curves for current and former smokers. We used a direct estimation approach to estimate attributable burden, providing more comprehensive estimates of the health effects of smoking than previously available. Findings Globally in 2019, 1.14 billion (95% uncertainty interval 1.13-1.16) individuals were current smokers, who consumed 7.41 trillion (7.11-7.74) cigarette-equivalents of tobacco in 2019. Although prevalence of smoking had decreased significantly since 1990 among both males (27.5% [26. 5-28.5] reduction) and females (37.7% [35.4-39.9] reduction) aged 15 years and older, population growth has led to a significant increase in the total number of smokers from 0.99 billion (0.98-1.00) in 1990. Globally in 2019, smoking tobacco use accounted for 7.69 million (7.16-8.20) deaths and 200 million (185-214) disability-adjusted life-years, and was the leading risk factor for death among males (20.2% [19.3-21.1] of male deaths). 6.68 million [86.9%] of 7.69 million deaths attributable to smoking tobacco use were among current smokers. Interpretation In the absence of intervention, the annual toll of 7.69 million deaths and 200 million disability-adjusted life-years attributable to smoking will increase over the coming decades. Substantial progress in reducing the prevalence of smoking tobacco use has been observed in countries from all regions and at all stages of development, but a large implementation gap remains for tobacco control. Countries have a dear and urgent opportunity to pass strong, evidence-based policies to accelerate reductions in the prevalence of smoking and reap massive health benefits for their citizens. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd.Peer reviewe

Global, regional, and national incidence, prevalence, and mortality of HIV, 1980–2017, and forecasts to 2030, for 195 countries and territories: a systematic analysis for the Global Burden of Diseases, Injuries, and Risk Factors Study 2017

Background Understanding the patterns of HIV/AIDS epidemics is crucial to tracking and monitoring the progress of prevention and control efforts in countries. We provide a comprehensive assessment of the levels and trends of HIV/AIDS incidence, prevalence, mortality, and coverage of antiretroviral therapy (ART) for 1980–2017 and forecast these estimates to 2030 for 195 countries and territories. Methods We determined a modelling strategy for each country on the basis of the availability and quality of data. For countries and territories with data from population-based seroprevalence surveys or antenatal care clinics, we estimated prevalence and incidence using an open-source version of the Estimation and Projection Package—a natural history model originally developed by the UNAIDS Reference Group on Estimates, Modelling, and Projections. For countries with cause-specific vital registration data, we corrected data for garbage coding (ie, deaths coded to an intermediate, immediate, or poorly defined cause) and HIV misclassification. We developed a process of cohort incidence bias adjustment to use information on survival and deaths recorded in vital registration to back-calculate HIV incidence. For countries without any representative data on HIV, we produced incidence estimates by pulling information from observed bias in the geographical region. We used a re-coded version of the Spectrum model (a cohort component model that uses rates of disease progression and HIV mortality on and off ART) to produce age-sex-specific incidence, prevalence, and mortality, and treatment coverage results for all countries, and forecast these measures to 2030 using Spectrum with inputs that were extended on the basis of past trends in treatment scale-up and new infections. Findings Global HIV mortality peaked in 2006 with 1·95 million deaths (95% uncertainty interval 1·87–2·04) and has since decreased to 0·95 million deaths (0·91–1·01) in 2017. New cases of HIV globally peaked in 1999 (3·16 million, 2·79–3·67) and since then have gradually decreased to 1·94 million (1·63–2·29) in 2017. These trends, along with ART scale-up, have globally resulted in increased prevalence, with 36·8 million (34·8–39·2) people living with HIV in 2017. Prevalence of HIV was highest in southern sub-Saharan Africa in 2017, and countries in the region had ART coverage ranging from 65·7% in Lesotho to 85·7% in eSwatini. Our forecasts showed that 54 countries will meet the UNAIDS target of 81% ART coverage by 2020 and 12 countries are on track to meet 90% ART coverage by 2030. Forecasted results estimate that few countries will meet the UNAIDS 2020 and 2030 mortality and incidence targets. Interpretation Despite progress in reducing HIV-related mortality over the past decade, slow decreases in incidence, combined with the current context of stagnated funding for related interventions, mean that many countries are not on track to reach the 2020 and 2030 global targets for reduction in incidence and mortality. With a growing population of people living with HIV, it will continue to be a major threat to public health for years to come. The pace of progress needs to be hastened by continuing to expand access to ART and increasing investments in proven HIV prevention initiatives that can be scaled up to have population-level impact

Tracking development assistance for health and for COVID-19 : a review of development assistance, government, out-of-pocket, and other private spending on health for 204 countries and territories, 1990-2050

Background The rapid spread of COVID-19 renewed the focus on how health systems across the globe are financed, especially during public health emergencies. Development assistance is an important source of health financing in many low-income countries, yet little is known about how much of this funding was disbursed for COVID-19. We aimed to put development assistance for health for COVID-19 in the context of broader trends in global health financing, and to estimate total health spending from 1995 to 2050 and development assistance for COVID-19 in 2020. Methods We estimated domestic health spending and development assistance for health to generate total health-sector spending estimates for 204 countries and territories. We leveraged data from the WHO Global Health Expenditure Database to produce estimates of domestic health spending. To generate estimates for development assistance for health, we relied on project-level disbursement data from the major international development agencies' online databases and annual financial statements and reports for information on income sources. To adjust our estimates for 2020 to include disbursements related to COVID-19, we extracted project data on commitments and disbursements from a broader set of databases (because not all of the data sources used to estimate the historical series extend to 2020), including the UN Office of Humanitarian Assistance Financial Tracking Service and the International Aid Transparency Initiative. We reported all the historic and future spending estimates in inflation-adjusted 2020 US$, 2020 US$ per capita, purchasing-power parity-adjusted US$per capita, and as a proportion of gross domestic product. We used various models to generate future health spending to 2050. Findings In 2019, health spending globally reached$8. 8 trillion (95% uncertainty interval [UI] 8.7-8.8) or $1132 (1119-1143) per person. Spending on health varied within and across income groups and geographical regions. Of this total,$40.4 billion (0.5%, 95% UI 0.5-0.5) was development assistance for health provided to low-income and middle-income countries, which made up 24.6% (UI 24.0-25.1) of total spending in low-income countries. We estimate that $54.8 billion in development assistance for health was disbursed in 2020. Of this,$13.7 billion was targeted toward the COVID-19 health response. $12.3 billion was newly committed and$1.4 billion was repurposed from existing health projects. $3.1 billion (22.4$2.4 billion (17.9%) was for supply chain and logistics. Only $714.4 million (7.7$1519 (1448-1591) per person in 2050, although spending across countries is expected to remain varied. Interpretation Global health spending is expected to continue to grow, but remain unequally distributed between countries. We estimate that development organisations substantially increased the amount of development assistance for health provided in 2020. Continued efforts are needed to raise sufficient resources to mitigate the pandemic for the most vulnerable, and to help curtail the pandemic for all. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd.Peer reviewe