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BACKGROUND: Children from families with low socioeconomic status (SES), as determined by income, experience several negative outcomes, such as higher rates of newborn mortality and behavioral issues. Moreover, associations between DNA methylation and low income or poverty status are evident beginning at birth, suggesting prenatal influences on offspring development. Recent evidence suggests neighborhood opportunities may protect against some of the health consequences of living in low income households. The goal of this study was to assess whether neighborhood opportunities moderate associations between household income (HI) and neonate developmental maturity as measured with DNA methylation. METHODS: Umbilical cord blood DNA methylation data was available in 198 mother-neonate pairs from the larger CANDLE cohort. Gestational age acceleration was calculated using an epigenetic clock designed for neonates. Prenatal HI and neighborhood opportunities measured with the Childhood Opportunity Index (COI) were regressed on gestational age acceleration controlling for sex, race, and cellular composition. RESULTS: Higher HI was associated with higher gestational age acceleration (B = .145, t = 4.969, p = 1.56x10-6, 95% CI [.087, .202]). Contrary to expectation, an interaction emerged showing higher neighborhood educational opportunity was associated with lower gestational age acceleration at birth for neonates with mothers living in moderate to high HI (B = -.048, t = -2.08, p = .03, 95% CI [-.092, -.002]). Female neonates showed higher gestational age acceleration at birth compared to males. However, within males, being born into neighborhoods with higher social and economic opportunity was associated with higher gestational age acceleration. CONCLUSION: Prenatal HI and neighborhood qualities may affect gestational age acceleration at birth. Therefore, policy makers should consider neighborhood qualities as one opportunity to mitigate prenatal developmental effects of HI.

Little is known about electrocardiogram (ECG) markers of Parkinsons disease (PD) during the prodromal stage. The aim of the study was to build a generalizable ECG-based fully automatic artificial intelligence (AI) model to predict PD risk during the prodromal stage, up to 5 years before disease diagnosis. This case-control study included samples from Loyola University Chicago (LUC) and University of Tennessee-Methodist Le Bonheur Healthcare (MLH). Cases and controls were matched according to specific characteristics (date, age, sex and race). Clinical data were available from May, 2014 onward at LUC and from January, 2015 onward at MLH, while the ECG data were available as early as 1990 in both institutes. PD was denoted by at least two primary diagnostic codes (ICD9 332.0; ICD10 G20) at least 30 days apart. PD incidence date was defined as the earliest of first PD diagnostic code or PD-related medication prescription. ECGs obtained at least 6 months before PD incidence date were modeled to predict a subsequent diagnosis of PD within three time windows: 6 months-1 year, 6 months-3 years, and 6 months-5 years. We applied a novel deep neural network using standard 10-s 12-lead ECGs to predict PD risk at the prodromal phase. This model was compared to multiple feature engineering-based models. Subgroup analyses for sex, race and age were also performed. Our primary prediction model was a one-dimensional convolutional neural network (1D-CNN) that was built using 131 cases and 1058 controls from MLH, and externally validated on 29 cases and 165 controls from LUC. The model was trained on 90% of the MLH data, internally validated on the remaining 10% and externally validated on LUC data. The best performing model resulted in an external validation AUC of 0.67 when predicting future PD at any time between 6 months and 5 years after the ECG. Accuracy increased when restricted to ECGs obtained within 6 months to 3 years before PD diagnosis (AUC 0.69) and was highest when predicting future PD within 6 months to 1 year (AUC 0.74). The 1D-CNN model based on raw ECG data outperformed multiple models built using more standard ECG feature engineering approaches. These results demonstrate that a predictive model developed in one cohort using only raw 10-s ECGs can effectively classify individuals with prodromal PD in an independent cohort, particularly closer to disease diagnosis. Standard ECGs may help identify individuals with prodromal PD for cost-effective population-level early detection and inclusion in disease-modifying therapeutic trials.

Colloidal chemistry holds promise to prepare uniform and size-controllable pre-catalysts; however, it remains a challenge to unveil the atomic-level transition from pre-catalysts to active catalytic surfaces under the reaction conditions to enable the mechanistic design of catalysts. Here, we report an ambient-pressure X-ray photoelectron spectroscopy study, coupled with in situ environmental transmission electron microscopy, infrared spectroscopy, and theoretical calculations, to elucidate the surface catalytic sites of colloidal Ni nanoparticles for CO2 hydrogenation. We show that Ni nanoparticles with phosphine ligands exhibit a distinct surface evolution compared with amine-capped ones, owing to the diffusion of P under oxidative (air) or reductive (CO2 + H2) gaseous environments at elevated temperatures. The resulting NiPx surface leads to a substantially improved selectivity for CO production, in contrast to the metallic Ni, which favors CH4. The further elimination of surface metallic Ni sites by designing multi-step P incorporation achieves unit selectivity of CO in high-rate CO2 hydrogenation.

As additional preparation while teaching for the K-12 medium of instruction, the Korean Ministry of Education has actively promoted diverse professional development (PD) programs to promote English teachers' "Teaching English through English" (TETE) implementation. This study explored Korean K-12 English teachers' self-efficacy about TETE implementation and their experiences of participating in a long-term PD program (six-months). Through semi-structured interviews, classroom observations, and teachers' after-PD evaluations, the data analysis showed that PD could enhance English teachers' self-efficacy about implementing TETE, and that the PD site provided a professional learning community for English teachers to reflect on what they had learned from their training. However, further data analysis found that self-efficacy and experiences in the PD program were different for elementary and secondary English teachers. Several suggestions are provided in terms of effectively preparing K-12 English teachers for TETE implementation through the long-term PD program.

Most research has examined flipped learning within the context of face-to-face (F2F) instruction. However, previous research has not effectively explored the possibility of how online synchronous flipped learning influences pre-service teachers (PSTs) in teacher education programs during Coronavirus disease (COVID-19). Recognizing the gap in the literature, this paper explored three aspects of online synchronous flipped learning by understanding 1) PSTs' learner engagement, 2) self-directed learning, and 3) learner satisfaction in a Korean university. The data was collected from Korean PST's interviews, reflection notes, and course evaluations. The thematic analysis was used to analyze qualitative data sources. The study findings showed that PSTs favored a synchronous online FL because it encouraged them to engage in various collaborative activities through Zoom breakout sessions. Also, pre-class materials from online FL can positively enhance the PSTs' self-directed learning process. Based on these findings, this study provides suggestions on how to effectively implement online synchronous flipped learning in teacher education programs.

Abstract. Given the tradeoffs between spatial and temporal resolution, questions aboutresolution optimality are fundamental to the study of global snow. Answersto these questions will inform future scientific priorities and missionspecifications. Heterogeneity of mountain snowpacks drives a need for dailysnow cover mapping at the slope scale (≤30 m) that is unmet for avariety of scientific users, ranging from hydrologists to the military towildlife biologists. But finer spatial resolution usually requires coarsertemporal or spectral resolution. Thus, no single sensor can meet all theseneeds. Recently, constellations of satellites and fusion techniques havemade noteworthy progress. The efficacy of two such recent advances isexamined: (1) a fused MODIS–Landsat product with daily 30 m spatialresolution and (2) a harmonized Landsat 8 and Sentinel 2A and B (HLS) product with3–4 d temporal and 30 m spatial resolution. State-of-the-art spectral unmixingtechniques are applied to surface reflectance products from 1 and 2 tocreate snow cover and albedo maps. Then an energy balance model was run toreconstruct snow water equivalent (SWE). For validation, lidar-basedAirborne Snow Observatory SWE estimates were used. Results show thatreconstructed SWE forced with 30 m resolution snow cover has lower bias, ameasure of basin-wide accuracy, than the baseline case using MODIS (463 mcell size) but greater mean absolute error, a measure of per-pixelaccuracy. However, the differences in errors may be within uncertaintiesfrom scaling artifacts, e.g., basin boundary delineation. Other explanationsare (1) the importance of daily acquisitions and (2) the limitations ofdownscaled forcings for reconstruction. Conclusions are as follows: (1) spectrallyunmixed snow cover and snow albedo from MODIS continue to provide accurateforcings for snow models and (2) finer spatial and temporal resolutionthrough sensor design, fusion techniques, and satellite constellations arethe future for Earth observations, but existing moderate-resolution sensorsstill offer value.

Critical reflection on the curriculum offered in the Catholic school is a valuable addition to wider dialogue on the nature of education and schooling. It enables the Church's educational agencies to offer a distinctive vision of education to the diverse range of students who freely participate in its educational ventures. In Catholic thinking, education is the study of humanity and its achievements. The curriculum of the Catholic school speaks to internal and external audiences and is a bridge uniting the Catholic worldview with other intellectual traditions.

Abstract. Given the tradeoffs between spatial and temporal resolution, questions about resolution optimality are fundamental to the study of global snow. Answers to these questions will inform future scientific priorities and mission specifications. Heterogeneity of mountain snowpacks drives a need for daily snow cover mapping at the slope scale (≤ 30 m) that is unmet for a variety of scientific users, ranging from hydrologists to the military to wildlife biologists. But finer spatial resolution usually requires coarser temporal or spectral resolution. Thus, no single sensor can meet all these needs. Recently, constellations of satellites and fusion techniques have made noteworthy progress. The efficacy of two such recent advances is examined: 1) a fused MODIS - Landsat product with daily 30 m spatial resolution; and 2) a harmonized Landsat 8 - Sentinel 2A/B (HLS) product with 2–3 day temporal and 30 m spatial resolution. State-of-art spectral unmixing techniques are applied to surface reflectance products from 1 & 2 to create snow cover and albedo maps. Then an energy balance model was run to reconstruct snow water equivalent (SWE). For validation, lidar-based Airborne Snow Observatory SWE estimates were used. Results show that reconstructed SWE forced with 30 m resolution snow cover has lower bias, a measure of basin-wide accuracy, than the baseline case using MODIS (463 m cell size), but higher mean absolute error, a measure of per-pixel accuracy. However, the differences in errors may be within uncertainties from scaling artifacts e.g., basin boundary delineation. Other explanations are 1) the importance of daily acquisitions and 2) the limitations of downscaled forcings for reconstruction. Conclusions are: 1) spectrally unmixed snow cover and snow albedo from MODIS continue to provide accurate forcings for snow models; and 2) finer spatial and temporal resolution through sensor design, fusion techniques, and satellite constellations are the future for Earth observations.

IntroductionCarriage of high-risk APOL1 genetic variants is associated with increased risks for kidney diseases in people of African descent. Less is known about the variants' associations with blood pressure or potential moderators.MethodsWe investigated these associations in a pregnancy cohort of 556 women and 493 children identified as African American. Participants with two APOL1 risk alleles were defined as having the high-risk genotype. Blood pressure in both populations was measured at the child's 4-6 years visit. We fit multivariate linear and Poisson regressions and further adjusted for population stratification to estimate the APOL1-blood pressure associations. We also examined the associations modified by air pollution exposures (particulate matter ≤2.5 μ m in aerodynamic diameter [PM2.5] and nitrogen dioxide) and explored other moderators such as health conditions and behaviors.ResultsNeither APOL1 risk alleles nor risk genotypes had a main effect on blood pressure in mothers or children. However, each 2-μg/m3 increase of four-year average PM2.5 was associated with a 16.3 (95%CI: 5.7, 26.9) mmHg higher diastolic blood pressure in mothers with the APOL1 high-risk genotype, while the estimated effect was much smaller in mothers with the low-risk genotype (i.e., 2.9 [95%CI: -3.1, 8.8] mmHg; Pinteraction = 0.01). Additionally, the associations of APOL1 risk alleles and the high-risk genotype with high blood pressure (i.e., SBP and/or DBP ≥ 90th percentile) were stronger in girls vs. boys (Pinteraction = 0.02 and 0.005, respectively).ConclusionThis study sheds light on the distribution of high blood pressure by APOL1 genetic variants and informs regulatory policy to protect vulnerable population subgroups.

BACKGROUND: Childhood wheeze, asthma, and allergic rhinitis are common and likely have prenatal origins. Oxidative stress is associated with respiratory disease, but the association of oxidative stress during the prenatal period with development of respiratory and atopic disease in childhood, particularly beyond the infancy period, is unknown. This study aims to investigate associations between prenatal oxidative stress, measured by maternal urinary F2-isoprostanes, and child respiratory outcomes, including effect modification by maternal race. METHODS: We prospectively studied Black (n = 717) and White (n = 363) mother-child dyads. We measured F2-isoprostanes in 2nd-trimester urine (ng/mg-creatinine). At approximately age 4, we obtained parent report of provider-diagnosed asthma (ever), current wheeze, current asthma (diagnosis, symptoms and/or medication), and current allergic rhinitis (current defined as previous 12 months). We used multivariable logistic regression to estimate adjusted odds ratios (aOR) and 95% confidence intervals (95%CI) per interquartile range (IQR) increase in F2-isoprostane concentration, controlling for confounders. We examined modification by maternal race using interaction terms. RESULTS: The prevalence of provider-diagnosed asthma and current wheeze, asthma and allergic rhinitis was 14%, 19%, 15%, and 24%, respectively. Median (IQR) F2-isoprostane levels were 2.1 (1.6, 2.9) ng/mg-creatinine. Associations between prenatal F2-isoprostanes and provider-diagnosed asthma, current wheeze, and current asthma were modified by maternal race. Results were strongest for current wheeze (aOR [95%CI]: 1.55 [1.16, 2.06] for White; 0.98 [0.78, 1.22] for Black; p-interaction = 0.01). We observed no association between F2-isoprostanes and allergic rhinitis. CONCLUSION: Prenatal urinary F2-isoprostanes may be a marker associated with childhood wheeze/asthma in certain populations. Research is needed to understand underlying mechanisms and racial differences.

Over the past decade, meta-analyses have been conducted to evaluate the impact of embodied pedagogical agents on learning outcomes. Most review studies have evaluated learning outcomes from the perspective of testing labels such as transfer, retention, recognition, free recall, and various other classifications. This is problematic, because studies can be excluded due to the labeling of the assessment, even though the testing format and test taking strategy are the same. This meta-analysis assesses how embodied pedagogical agents impact learning when measured from the testing format and test taking strategy perspective. The new approach, along with new moderating variables to evaluate agent design and content information, supports previous findings that embodied pedagogical agents significantly increase learning; but there are limitations depending on the agent's design and the type of information being learned. This meta-analysis advances the field by exploring new ways to think about design elements associated with embodied pedagogical agents.

Since the early 2000s, much emphasis has been placed on adopting the Communicative Language Teaching (CLT) method in the Korean K-12 context, however, such efforts have been largely unsuccessful. In order to shed light on some of the reasons for such failures, this study examined the impact of short-term professional development (PD) on primary and secondary Korean English teachers' self-efficacy to implement the CLT method. The data consisted of an end-of-the-course survey distributed among teachers (n=131), in-depth individual interviews with teachers (n=10), and researchers' classroom observations. The findings suggested that PD could help teachers feel more confident and prepare them to implement CLT. In addition, PD seemed to enhance teachers' motivation to adapt CLT into their future English classrooms. The findings of this study confirmed previous global research regarding two major difficulties regarding implementing CLT: 1) grammar-based national college entrance exams, and 2) large class sizes of mixed proficiency levels. In conclusion, several suggestions on how to increase the effectiveness of the CLT method successfully through PD in Korea are provided.

BackgroundParkinson's disease (PD) is a chronic, disabling neurodegenerative disorder.ObjectiveTo predict a future diagnosis of PD using questionnaires and simple non-invasive clinical tests.MethodsParticipants in the prospective Kuakini Honolulu-Asia Aging Study (HAAS) were evaluated biannually between 1995-2017 by PD experts using standard diagnostic criteria. Autopsies were sought on all deaths. We input simple clinical and risk factor variables into an ensemble-tree based machine learning algorithm and derived models to predict the probability of developing PD. We also investigated relationships of predictive models and neuropathologic features such as nigral neuron density.ResultsThe study sample included 292 subjects, 25 of whom developed PD within 3 years and 41 by 5 years. 116 (46%) of 251 subjects not diagnosed with PD underwent autopsy. Light Gradient Boosting Machine modeling of 12 predictors correctly classified a high proportion of individuals who developed PD within 3 years (area under the curve (AUC) 0.82, 95%CI 0.76-0.89) or 5 years (AUC 0.77, 95%CI 0.71-0.84). A large proportion of controls who were misclassified as PD had Lewy pathology at autopsy, including 79%of those who died within 3 years. PD probability estimates correlated inversely with nigral neuron density and were strongest in autopsies conducted within 3 years of index date (r = -0.57, p

Abstract. Intrinsic albedo is the bihemispherical reflectance independent of effectsof topography or surface roughness. Conversely, the apparent albedo is thereflected radiation divided by the incident and may be affected bytopography or roughness. For snow, the surface is often rough, and these twooptical quantities have different uses: intrinsic albedo is used inscattering equations whereas apparent albedo should be used in energybalance models. Complementing numerous studies devoted to surface roughnessand its effect on snow reflectance, this work analyzes a time series ofintrinsic and apparent snow albedos over a season at a sub-alpine site usingan automated terrestrial laser scanner to map the snow surface topography.An updated albedo model accounts for shade, and in situ albedo measurementsfrom a field spectrometer are compared to those from a spacebornemultispectral sensor. A spectral unmixing approach using a shade endmember(to address the common problem of unknown surface topography) produces grainsize and impurity solutions; the modeled shade fraction is compared to theintrinsic and apparent albedo difference. As expected and consistent withother studies, the results show that intrinsic albedo is consistentlygreater than apparent albedo. Both albedos decrease rapidly as ablationhollows form during melt, combining effects of impurities on the surface andincreasing roughness. Intrinsic broadband albedos average 0.056 greater thanapparent albedos, with the difference being 0.052 in the near infrared or0.022 if the average (planar) topography is known and corrected. Fieldmeasurements of spectral surface reflectance confirm that multispectralsensors see the apparent albedo but lack the spectral resolution todistinguish between darkening from ablation hollows versus lowconcentrations of impurities. In contrast, measurements from the fieldspectrometer have sufficient resolution to discern darkening from the twosources. Based on these results, conclusions are as follows: (1) impurity estimatesfrom multispectral sensors are only reliable for relatively dirty snow withhigh snow fraction; (2) a shade endmember must be used in spectral mixturemodels, even for in situ spectroscopic measurements; and (3) snow albedomodels should produce apparent albedos by accounting for the shade fraction.The conclusion re-iterates that albedo is the most practical snowreflectance quantity for remote sensing.

BackgroundChildhood asthma is a common chronic disease that likely has prenatal origins. Gestational diabetes alters maternal physiology and may influence fetal risk for childhood-onset disease. However, the association between gestational diabetes and child asthma is not well characterized.ObjectiveTo investigate the association between gestational diabetes and wheeze/asthma at approximately 4 years of age in a racially diverse US cohort.MethodsWe studied mother-child dyads enrolled prenatally in the Conditions Affecting Neurocognitive Development and Learning in Early Childhood study. Gestational diabetes was determined by medical chart review. At approximately 4 years of age, we assessed child respiratory outcomes including parent report of physician-diagnosed asthma (ever), current wheeze (symptoms within the past 12 months), and current asthma (physician diagnosis and/or medication or symptoms within the past 12 months). We used the modified Poisson regression to assess associations between gestational diabetes and child respiratory outcomes, adjusting for maternal age, race, prenatal smoking, pre-pregnancy body mass index, parity, asthma history, socioeconomic status, and infant sex.ResultsAmong 1107 women, 66% were African American/Black. Six percent (n = 62) had gestational diabetes documented during pregnancy. Gestational diabetes was associated with increased risk of physician-diagnosed asthma (adjusted risk ratio (RR) [95% Confidence Interval]: 2.13 [1.35, 3.38]; prevalence: 14%), current wheeze (RR: 1.85 [1.23, 2.78]; prevalence: 19%), and current asthma (RR: 2.01 [1.30, 3.10]; prevalence: 16%).ConclusionsGestational diabetes was associated with increased risk of asthma and wheeze outcomes. Additional studies are needed to elucidate modifiable pathways underlying this association.

BackgroundLimited data suggest air pollution exposures may contribute to pediatric high blood pressure (HBP), a known predictor of adult cardiovascular diseases.MethodsWe investigated this association in the Conditions Affecting Neurocognitive Development and Learning in Early Childhood (CANDLE) study, a sociodemographically diverse pregnancy cohort in the southern United States with participants enrolled from 2006 to 2011. We included 822 mother-child dyads with available address histories and a valid child blood pressure measurement at 4-6 y. Systolic (SBP) and diastolic blood pressures (DBP) were converted to age-, sex-, and height-specific percentiles for normal-weight U.S. children. HBP was classified based on SBP or DBP ≥90th percentile. Nitrogen dioxide (NO2) and particulate matter ≤2.5μm in aerodynamic diameter (PM2.5) estimates in both pre- and postnatal windows were obtained from annual national models and spatiotemporal models, respectively. We fit multivariate Linear and Poisson regressions and explored multiplicative joint effects with maternal nutrition, child sex, and maternal race using interaction terms.ResultsMean PM2.5 and NO2 in the prenatal period were 10.8 [standard deviation (SD): 0.9] μg/m3 and 10.0 (SD: 2.4) ppb, respectively, and 9.9 (SD: 0.6) μg/m3 and 8.8 (SD: 1.9) ppb from birth to the 4-y-old birthday. On average, SBP percentile increased by 14.6 (95% CI: 4.6, 24.6), and DBP percentile increased by 8.7 (95% CI: 1.4, 15.9) with each 2-μg/m3 increase in second-trimester PM2.5. PM2.5 averaged over the prenatal period was only significantly associated with higher DBP percentiles [β= 11.6 (95% CI: 2.9, 20.2)]. Positive associations of second-trimester PM2.5 with SBP and DBP percentiles were stronger in children with maternal folate concentrations in the lowest quartile (pinteraction= 0.05 and 0.07, respectively) and associations with DBP percentiles were stronger in female children (pinteraction= 0.05). We did not detect significant association of NO2, road proximity, and postnatal PM2.5 with any outcomes.ConclusionsThe findings suggest that higher prenatal PM2.5 exposure, particularly in the second trimester, is associated with elevated early childhood blood pressure. This adverse association could be modified by pregnancy folate concentrations. https://doi.org/10.1289/EHP7486.

BackgroundThe intrauterine environment may influence offspring blood pressure, with effects possibly extending into adulthood. The associations between prenatal nutrition and offspring blood pressure, alone or in combination with other sociodemographic or behavioral factors, are unclear.ObjectivesTo investigate the associations of maternal dietary patterns and plasma folate concentrations with blood pressure in children aged 4-6 years, and assess the potential effect modifications by child sex, maternal race, pre-pregnancy overweight or obesity, maternal smoking, and breastfeeding.MethodsParticipants were 846 mother-child dyads from the Conditions Affecting Neurocognitive Development and Learning in Early Childhood (CANDLE) study. Maternal nutrition was characterized by the Healthy Eating Index 2010 (HEI) scores and plasma folate concentrations in pregnancy. We calculated the systolic blood pressure (SBP) and diastolic blood pressure percentiles, incorporating sex, age, and height, and categorized children as either having high blood pressure (HBP; ≥90th percentile) or normal blood pressure. Linear regressions were performed to quantify the associations between maternal nutrition and continuous blood pressure percentiles, and Poisson regressions were used to estimate the incidence rate ratio (IRR) of binary HBP. We examined the effect modifications using interaction models.ResultsMean HEI scores and folate concentrations were 60.0 (SD, 11.3) and 23.1 ng/mL (SD, 11.1), respectively. Based on measurements at 1 visit, 29.6% of the children were defined as having HBP. Maternal HEI scores and plasma folate concentrations were not associated with child blood pressure percentiles or HBP in the full cohort. Among mothers self-identified as white, there was an inverse relationship between maternal HEI score and child SBP percentile (β, -0.40; 95%CI: -0.75 to -0.06). A maternal HEI score above 59 was associated with a reduced risk of HBP in girls (IRR, 0.53; 95% CI: 0.32-0.88). No modified associations by pre-pregnancy overweight or obesity, maternal smoking, or breastfeeding were indicated.ConclusionsWe found little evidence for effects of maternal nutrition during pregnancy on childhood blood pressure, but detected sex- and race-specific associations. The study contributes to the evolving scientific inquiry regarding developmental origins of disease.

This paper presents the results of a multi‐disciplinary effort to clarify the state of the art and the state of practice, and necessary future research for creating the seamless integration and application of light in buildings, regardless of source, which is purposely modulated to illuminate surfaces and designed in a way that is comfortable, healthy, pleasing, cost‐effective, and energy efficient. The authors unwrap the research, tools, and technical gaps preventing the full integration of electric lighting and daylighting with advanced façades through the coordination of lighting and windows research activities. The study and a stakeholder workshop captured current technology readiness levels (TRL), as well as research thrusts and implementation guidelines, and identified research priorities, presenting an analysis of the current landscape of lighting metrics—and which metrics are in the critical path for developing integrated daylighting and electric lighting systems, and their design, installation, and technology guidelines. In addition, the study defined stakeholder coordination, pathways to interoperable technology, and the value of viewing the work of the indi-vidual research areas holistically rather than in isolation.