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Traditional manual building code compliance checking is costly, time-consuming, and human error-prone. With the adoption of Building Information Modeling (BIM), automation in such a checking process becomes more feasible. However, existing methods still face limited automation when applied to different building codes. To address that, in this paper, the authors proposed a new framework that requires minimal input from users and strives for full automation, namely, the Invariant signature, logic reasoning, and Semantic Natural language processing (NLP)-based Automated building Code compliance Checking (I-SNACC) framework. The authors developed an automated building code compliance checking (ACC) prototype system under this framework and tested it on Chapter 10 of the International Building Codes 2015 (IBC 2015). The system was tested on two real projects and achieved 95.2% precision and 100% recall in non-compliance detection. The experiment showed that the framework is promising in building code compliance checking. Compared to the state-of-the-art methods, the new framework increases the degree of automation and saves manual efforts for finding non-compliance cases. 

Abstract Aim Understanding the considerable variability and drivers of global leaf photosynthetic capacity [indicated by the maximum carboxylation rate standardized to 25°C ( V c,max25 )] is an essential step for accurate modelling of terrestrial plant photosynthesis and carbon uptake under climate change. Although current environmental conditions have often been connected with empirical and theoretical models to explain global V c,max25 variability through acclimatization and adaptation, long‐term evolutionary history has largely been neglected, but might also explicitly play a role in shaping the V c,max25 variability. Location Global. Time period Contemporary. Major taxa studied Terrestrial plants. Methods We compiled a geographically comprehensive global dataset of V c,max25 for C 3 plants ( n  = 6917 observations from 2157 species and 425 sites covering all major biomes world‐wide), explored the biogeographical and phylogenetic patterns of V c,max25 , and quantified the relative importance of current environmental factors and evolutionary history in driving global V c,max25 variability. Results We found that V c,max25 differed across different biomes, with higher mean values in relatively drier regions, and across different life‐forms, with higher mean values in non‐woody relative to woody plants and in legumes relative to non‐leguminous plants. The values of V c,max25 displayed a significant phylogenetic signal and diverged in a contrasting manner across phylogenetic groups, with a significant trend along the evolutionary axis towards a higher V c,max25 in more modern clades. A Bayesian phylogenetic linear mixed model revealed that evolutionary history (indicated by phylogeny and species) explained nearly 3‐fold more of the variation in global V c,max25 than present‐day environment (53 vs. 18%). Main conclusions These findings contribute to a comprehensive assessment of the patterns and drivers of global V c,max25 variability, highlighting the importance of evolutionary history in driving global V c,max25 variability, hence terrestrial plant photosynthesis. 

Climate plays a critical role in altering soil carbon (C) turnover and long‐term soil C storage by regulating water availability and temperature, and in turn biological activity. However, a systematic analysis of how key climatic factors shape the global patterns of soil C turnover is still lacking. Using global observation‐based data sets and a transit time theory, here we show that—excluding croplands and cold regions—soil C turnover time (τ_TO) and its variability are strongly related to ecosystem aridity through a power law scaling. According to such a relation, soil C turnover is faster but also more variable in wetter regions, suggesting more complex C cycling processes. The observed scaling ofτ_TOand its coefficient of variation with aridity underlines the fundamental controls of climate on soil C turnover and may help reconcile soil C models with empirical observations for improved projection of soil C dynamics under climate change.

 

ABSTRACT We study the demographics of z ∼ 6 broad-line quasars in the black hole (BH) mass–luminosity plane using a sample of more than 100 quasars at 5.7 < z < 6.5. These quasars have well-quantified selection functions and nearly one-third of them also have virial BH masses estimated from near-IR spectroscopy. We use forward modelling of parametrized intrinsic distributions of BH masses and Eddington ratios, and account for the sample flux limits and measurement uncertainties of the BH masses and luminosities. We find significant differences between the intrinsic and observed distributions of the quantities due to measurement uncertainties and sample flux limits. There is also marginal evidence that the virial BH masses are susceptible to a positive luminosity-dependent bias (BH mass is overestimated when luminosity is above the average), and that the mean Eddington ratio increases with BH mass. Our models provide reliable constraints on the z ∼ 6 BH mass function at $M_{\rm BH}\gt 10^{8.5}\, M_\odot$, with a median 1σ uncertainty of ∼0.5 dex in abundance. The intrinsic Eddington ratio distribution of $M_{\rm BH}\gt 10^{8.5}\, M_\odot$ quasars can be approximated by a mass-dependent Schechter model, with a broad peak around log (Lbol/LEdd) ∼ −0.9. We also find that, at 4.5 ≲ z ≲ 6, the number densities of more massive BHs tend to decline more rapidly with increasing redshift, contrary to the trend at 2.5 ≲ z ≲ 4.5 reported previously.