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Energy savings from passive solar design applied to a typical Canadian house were quantified using calibrated whole building energy simulation. A detailed energy simulation model was created for a research house which represents a typical Canadian tract house with basic passive solar measures. The model was calibrated to measured furnace gas consumption data. Eight design scenarios were evaluated for eight climate locations. Design parameters included increased thermal mass, increased south window area, and high performance windows. In addition, an advanced house scenario was evaluated which featured optimized geometry, a further increase in south window area, high thermal mass, advanced glazing, and no north facing windows. For the typical house predicted solar heating fractions ranged from 20% to 34% with basic passive solar measures, and 35% to 52% for more aggressive passive solar measures. For the advanced house predicted solar fractions ranged from 40% to 69%.

Review - Intervention Background Mindfulness-based smoking cessation interventions may aid smoking cessation by teaching individuals to pay attention to, and work mindfully with, negative aFective states, cravings, and other symptoms of nicotine withdrawal. Types of mindfulness-based interventions includemindfulness training,whichinvolves training inmeditation; acceptance andcommitmenttherapy (ACT);distress tolerance training; and yoga. Objectives To assess the eFicacy of mindfulness-based interventions for smoking cessation among people who smoke, and whether these interventions have an eFect on mental health outcomes. Search methods We searched the Cochrane Tobacco Addiction Group's specialised register, CENTRAL, MEDLINE, Embase, PsycINFO, and trial registries to 15 April 2021. We also employed an automated search strategy, developed as part oftheHuman Behaviour Change Project, using MicrosoI Academic. Selection criteria We included randomised controlled trials (RCTs) and cluster-RCTs that compared a mindfulness-based intervention for smoking cessation with another smoking cessation programme or no treatment, and assessed smoking cessation at six months orlonger.We excluded studies that solely recruited pregnant women. Data collection and analysis We followed standard Cochrane methods. We measured smoking cessation at the longest time point, using the most rigorous definition available, on an intention-to-treat basis. We calculated risk ratios (RRs) and 95% confidence intervals (CIs) for smoking cessation for each study, where possible. We grouped eligible studies according to the type of intervention and type of comparator. We carried out meta analyses where appropriate, using Mantel-Haenszel random-eFects models. We summarised mental health outcomes narratively. Main results We included 21 studies, with 8186 participants. Mostrecruited adults from the community, and the majority (15 studies) were conducted in the USA. We judged four of the studies to be at low risk of bias, nine at unclear risk, and eight at high risk. Mindfulness-based interventions varied considerably in design and content, as did comparators, therefore, we pooled small groups of relatively comparable studies. We did not detect a clear benefit or harm of mindfulness training interventions on quit rates compared with intensity-matched smoking cessation treatment (RR 0.99, 95% CI 0.67 to 1.46; I 2 = 0%; 3 studies, 542 participants; low-certainty evidence), less intensive smoking cessation treatment (RR 1.19, 95% CI 0.65 to 2.19; I 2 = 60%; 5 studies, 813 participants; very low-certainty evidence), or no treatment (RR 0.81, 95% CI 0.43 to 1.53; 1 study, 325 participants; low-certainty evidence). In each comparison, the 95% CI encompassed benefit (i.e. higher quit rates), harm (i.e. lower quit rates) and no diFerence. In one study of mindfulness-based relapse prevention, we did not detect a clear benefit or harm of the intervention over no treatment (RR 1.43, 95% CI 0.56 to 3.67; 86 participants; very low-certainty evidence). We did not detect a clear benefit or harm of ACT on quit rates compared with less intensive behavioural treatments, including nicotine replacementtherapy alone (RR1.27, 95% CI 0.53 to 3.02; 1 study, 102 participants; low-certainty evidence), brief advice (RR1.27, 95% CI 0.59 to 2.75; 1 study, 144 participants; very low-certainty evidence), or less intensive ACT (RR 1.00, 95% CI 0.50 to 2.01; 1 study, 100 participants; low-certainty evidence). There was a high level of heterogeneity (I 2 = 82%) across studies comparing ACT with intensity-matched smoking cessation treatments, meaning it was not appropriate to report a pooled result. We did not detect a clear benefit or harm of distress tolerance training on quit rates compared with intensity-matched smoking cessation treatment (RR 0.87, 95% CI 0.26 to 2.98; 1 study, 69 participants; low-certainty evidence) or less intensive smoking cessation treatment (RR 1.63, 95% CI 0.33 to 8.08; 1 study, 49 participants; low-certainty evidence). We did not detect a clear benefit or harm of yoga on quit rates compared with intensity-matched smoking cessation treatment (RR 1.44, 95% CI 0.40 to 5.16; 1 study, 55 participants; very low-certainty evidence). Excluding studies at high risk of bias did not substantially alterthe results, nor did using complete case data as opposed to using data from all participants randomised. Nine studies reported on changes in mental health and well-being, including depression, anxiety, perceived stress, and negative and positive aFect. Variation in measures and methodological diFerences between studies meant we could not meta-analyse these data. One study found a greater reduction in perceived stress in participants who received a face-to-face mindfulness training programme versus an intensity-matched programme.However,the remaining eight studies found no clinically meaningful diFerences in mental health and well being between participantswho received mindfulness-based treatments and participantswho received anothertreatment or no treatment (very low-certainty evidence). Authors' conclusions We did not detect a clear benefit of mindfulness-based smoking cessation interventions for increasing smoking quit rates or changing mental health and well-being. This was the case when compared with intensity-matched smoking cessation treatment, less intensive smoking cessation treatment, or no treatment. However, the evidence was of low and very low certainty due to risk of bias, inconsistency, and imprecision, meaning future evidence may very likely change our interpretation of the results. Further RCTs of mindfulness-based interventions for smoking cessation compared with active comparators are needed. There is also a need for more consistent reporting of mental health and well-being outcomes in studies of mindfulness-based interventions for smoking cessation.

We present the appendix of the First Fermi-Large Area Telescope (LAT) Solar flare catalog covering the 24thSolar cycle. The catalog (published in ApJS) contains 45 Fermi-LAT Solar flares (FLSFs) with emission in theγ-ray energy band (30 MeV -10 GeV) detected with a significance ≥5σ over the years 2010-2018. A subsample containing 37 of these flares exhibit delayed emission beyond the prompt-impulsive hard X-ray phase with 21 flares showing delayed emission lasting more than two hours. No prompt-impulsive emission is detected in four of these flares. We also report the first time observations of GeV emission from 3 flares originating from Active Regions located behind the limb (BTL) of the visible Solar disk. We report the light curves, spectra, best proton index and localization (when possible) for all the FLSFs and correlations with Solar multi-wavelength phenomena. The gamma-ray spectra is consistent with the decay of pions produced by >300 MeV protons. The work presented in the First Fermi Solar Flare Catalog contains the largest sample of high-energy gamma-ray flares ever reported and provides the unique opportunity to perform population/correlation studies on the different phases of the flare and thus allowing to open a new window in solar physics. This work is on behalf of the Fermi Large Area Telescope Collaboration. The First Fermi LAT Solar Flare Catalog has been accepted for publication on ApJS.

In response to the COVID-19, many governments have taken unprecedented measures in peacetime, to avoid an overflow of intensive care units and critical care resuscitation units (CCRUs). Due to the heavy societal and economic impact of measure such as the lockdown1, accurate means to characterize the spread of the disease would be extremely helpful for the reopening strategies. Concurrently, smell and taste changes have been identified as among the most specific symptoms of COVID-192,3. Here, we show that self-reports of smell/taste changes are more closely associated with hospital overload and are much earlier than the current governmental indicators. We also show a decrease of new onset as early as 5 days after the lockdown enforcement, which is consistent with a rapid effect of the lockdown on the pandemic. Cross-country comparisons show countries with the most stringent lockdown measures (France and Italy) present a faster decline in new reports of the onset of smell/taste changes after the lockdown than a country with less stringent measures (United Kingdom). Public health decision makers could thus monitor self-reported changes in the ability to smell or taste i/as an early and specific indicator of the COVID-19 pandemic, and ii/to evaluate the success of reopening strategies.

Due to the fast pace at which research reports in behaviour change are published, researchers, consultants and policymakers would benefit from more automatic ways to process these reports. Automatic extraction of the reports’ intervention content, population, settings and their results etc. are essential in synthesising and summarising the literature. However, to the best of our knowledge, no unique resource exists at the moment to facilitate this synthesis. In this paper, we describe the construction of a corpus of published behaviour change intervention evaluation reports aimed at smoking cessation. We also describe and release the annotation of 57 entities, that can be used as an off-the-shelf data resource for tasks such as entity recognition, etc. Both the corpus and the annotation dataset are being made available to the community. Wellcome Trust collaborative award