A novel autoignition-assisted, high-temperature High-Pressure Well-Stirred Turbulent Combustor (HP-WSTC) has been developed for detailed kinetic studies of fuels under gas-turbine conditions that were difficult to obtain with conventional reactors and flame chemistry facilities. It is designed for operations at 1–20 atm, 1200–2200 K, and residence times of 1–100 ms, enabling treatment as a zero-dimensional premixed-combustion system. Methane combustion experiments at 1–10 atm were compared with 0D simulations, showing good agreement for major species across a wide equivalence-ratio range, demonstrating the reliability of the HP-WSTC. Although methane combustion kinetics are well established, NO predictions still show large discrepancies, even at atmospheric pressure. Sensitivity analyses identify CH-pool reactions, including CH2 + O2 = CH2O + O and CH + CO2 = HCO + CO, as key uncertain reactions. The developed HP-WSTC provides a new platform for fuel kinetic investigations and bridges the gap between reactor and flame facilities for high-temperature kinetic studies under gas-turbine conditions.
Syn-orogenic detachment faults exhuming extensional shear zones are ever-present features in orogenic settings on Earth. Kinematic and fluid-flow models for brittle detachment faults paired with crystal-plastic shear zones continue to evolve alongside new data and techniques. Evidence for meteoric water infiltrating the frictional-viscous transition zone in detachment-related shear zones has survived revisions of these models, but the extent and influence of meteoric-hydrothermal circulation is not fully understood. Kinematic analysis and delta H-2 values of syn-kinematic micas from nine transects through the <6-0 Ma footwall shear zone of the Cordillera Blanca Detachment in the Peruvian Andes explore patterns of fluid flow during shear zone initiation and evolution at a previously unattained resolution. delta H-2 values reveal a pervasive pattern of meteoric water infiltration into the frictional-viscous transition zone across the detachment. Gradients in delta H-2 values reveal that fluid infiltration follows patterns of anataxial magmatism and the distribution of syn-kinematic fractures within and across the shear zone. Cumulatively, a three-dimensional assessment of the footwall shear zone of the Cordillera Blanca Detachment indicates that fluid infiltration into the frictional-viscous transition zone is spatially heterogeneous and correlated with the style of shear zone initiation and strain localization. Observed variability of fluid-rock interaction across the Cordillera Blanca Detachment highlights the importance of assessing for spatial heterogeneity when quantifying or qualifying fluid activity in meteoric-hydrothermally modified detachment faults.
Rice (Oryza sativa L.) is a staple food for more than half of the global population but faces escalating yield losses from abiotic stresses, notably submergence, drought, salinity, heavy metals, cold, and heat. These stresses act at different developmental stages, altering growth, physiology, and grain quality through common bottlenecks in photosynthesis, water and ion balance, and reproductive development. This review provides a consolidated stress-wise synthesis of morpho-physiological injury and adaptive traits, associated biochemical responses (ROS dynamics, antioxidant enzymes, osmolyte accumulation, carbohydrate metabolism), and molecular regulation (ABA/ethylene/GA/BR crosstalk, Ca2+ signaling, and transcriptional networks including DREB, NAC, MYB, and WRKY). The key genetic hubs such as SUB1A (submergence), qDTY1.1 (drought), Saltol (salinity), COLD1 (cold), HSF-HSP (heat), and HMA3/ZIP1/NIP2 (heavy metals) are highlighted as central to stress tolerance. This review emphasizes integrated management approaches, nutrient and water regimes, post-stress recovery inputs, seed priming, soil amendments, microbial interventions, and nano-enabled solutions that align with physiological and molecular responses to enhance stress resilience. This article provides a comprehensive framework to guide breeding, agronomic management, and future research toward multi-stress tolerance and yield stability in rice under climate change by linking stage specific injury with mechanistic pathways and actionable strategies.
Abstract A central aim in biology is understanding the heritability of traits and how trait interactions contribute to success in diverse environments. Experiments that record multiple traits from individuals of known pedigree or genetic relatedness in distinct environments are key to addressing this aim. Mixed modelling approaches have been proposed for analysing such multivariate trait data. The parameter space of these mixed models grows quadratically with the number of traits and environments considered, which increases computational demand and the risk of overfitting. Existing approaches can also be challenging to implement for datasets in which different traits were measured in different environments. We developed a latent variable model that incorporates genetic marker data for estimating heritability and improving predictions of traits. Our approach promotes model parsimony by estimating environmental associations and genetic variances for a reduced number of latent traits. The model can accommodate variation in genetic correlations across environments and can be applied in settings where only a subset of traits is observed in each environment, maximizing use of the data. We show that existing model‐based ordination methods can be viewed as simplifications of our approach. In a simulation study, we found that our approach improves sampling efficiency by an order of magnitude relative to standard multivariate mixed modelling approaches. Compared with existing ordination methods, our approach also improved inference for environmental associations and predictive performance. We applied our model to reconcile partially overlapping datasets collected from growth chamber and common garden experiments of Bromus tectorum, an annual grass invasive to the United States. Fitting mixed models independently to the data sources resulted in biologically unreasonable estimates of narrow‐sense heritability, and a joint analysis with our latent variable model improved inference. Drawing from the joint analysis, we present a holistic explanation for the strength of several clines in Bromus tectorum and discuss their relevance for invasion in the Intermountain West. The flexibility, tractability and performance of our approach make it appealing for joint inference and prediction in experiments of multiple traits. More broadly, we demonstrate the value of incorporating genetic marker data into latent variable models.
We examine associations between management earnings forecasts and capital structure. We posit that incremental information in forecasts reduces capital providers' concerns about adverse selection. Pecking order theory suggests forecasts contribute differing amounts of information to different capital providers, shifting capital structure from trade credit to long-term debt, and from long-term debt to equity. Investment information risk theory submits that although creditors and equity holders share downside risk, creditors are more sensitive than equity holders to uncertainty related to the riskiness of firms' future investments because equity holders are the sole beneficiaries of investments' upside potential. Insomuch earnings forecasts provide investment information that is more meaningful to creditors, we expect a shift in capital structure from equity to credit as the forecast decreases outcome uncertainty. Using a sample of US-listed firms from 2003 to 2019, we find support for the pecking order theory, that firms issuing management earnings forecasts exhibit higher levels of equity-to-credit financing and long-term debt-to-trade credit financing. However, in cross-sectional tests, we also find evidence supporting the investment information risk theory, that forecasts shift financing from equity to credit and among creditors, from long-term debt to trade credit in firms with more growth opportunities. Our findings suggest firms' voluntary disclosures provide different amounts of incremental information to different capital providers, but that the relevance of the information provided may also differ across capital providers.
