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Comprehending the impact of wildfire smoke on photovoltaic (PV) systems is of utmost importance in ensuring the dependability and consistency of power systems, particularly due to the growing prevalence of PV installations and the occurrence of wildfires. Nevertheless, this issue has not received extensive investigation within the current literature. A major obstacle in studying this phenomenon lies in accurately quantifying the impact of smoke. Conventional techniques such as aerosol optical depth (AOD) and PM 2.5 are inadequate for accurately assessing the influence of wildfire smoke on PV systems due to the complex interplay of smoke elevation, dynamics, and nonlinear effects on the solar spectral irradiance. To address this challenge, a new methodology is developed in this research that employs the optical properties of wildfire smoke. This approach utilizes the spectral response (SR) of PV devices to estimate the theoretical reduction in PV power output. The findings of this study enable precise measurement of the power output reduction caused by wildfire smoke for different types of PV cells. This newly devised method can be adopted for power system operation and planning to ensure the stability and reliability of power grids. Additionally, this study highlights the need to consider different PV cell technologies in regions at high risk of wildfires to minimize the power reduction caused by wildfire smoke. 

Accurate wildfire prediction in diverse and geographically dispersed areas is crucial for effective wildfire management. However, the limited availability of labeled data in data-challenged regions, along with the unique characteristics of these areas, poses challenges for training robust prediction models. This study investigates the performance of a convolutional neural network (CNN) on datasets comprising Landsat images from Canada and Alaska. Through principal component analysis (PCA), the study uncovers distinct differences in data distribution between the two regions. It is observed that the reduced data size of the Alaskan dataset, along with its distinct data distribution, leads to a decrease in the CNN's accuracy to 75% compared to an impressive 98% achieved on the Canadian dataset. To address this limitation, we propose a teacher-student model approach, transferring knowledge from a CNN trained on the larger Canadian dataset. The results demonstrate a significant accuracy improvement to 88.96% on the Alaskan dataset. Our findings highlight the effectiveness of the teacherstudent model in mitigating data scarcity challenges, enhancing wildfire prediction capabilities in regions with limited training data. This research contributes to improved wildfire monitoring and prevention strategies in challenging geographical locations. 

Switch defective/sucrose non‐fermentable (SWI/SNF) chromatin remodeling complexes are evolutionarily conserved, multi‐subunit machinery that play vital roles in the regulation of gene expression by controlling nucleosome positioning and occupancy. However, little is known about the subunit composition of SPLAYED (SYD)‐containing SWI/SNF complexes in plants. Here, we show that theArabidopsis thalianaLeaf and Flower Related (LFR) is a subunit of SYD‐containing SWI/SNF complexes. LFR interacts directly with multiple SWI/SNF subunits, including the catalytic ATPase subunit SYD,in vitroandin vivo. Phenotypic analyses oflfr‐2mutant flowers revealed that LFR is important for proper filament and pistil development, resembling the function of SYD. Transcriptome profiling revealed that LFR and SYD shared a subset of co‐regulated genes. We further demonstrate that the LFR and SYD interdependently activate the transcription ofAGAMOUS(AG), a C‐class floral organ identity gene, by regulating the occupation of nucleosome, chromatin loop, histone modification, and Pol II enrichment on theAGlocus. Furthermore, the chromosome conformation capture (3C) assay revealed that the gene loop atAGlocus is negatively correlated with theAGexpression level, and LFR‐SYD was functional to demolish theAGchromatin loop to promote its transcription. Collectively, these results provide insight into the molecular mechanism of the Arabidopsis SYD‐SWI/SNF complex in the control of higher chromatin conformation of the floral identity gene essential to plant reproductive organ development.

 

We show that pointwise limits of semistatic trading strategies in discrete time are again semistatic strategies. The analysis is carried out in full generality for a two‐period model, and under a probabilistic condition for multiperiod, multistock models. Our result contrasts with a counterexample of Acciaio, Larsson, and Schachermayer, and shows that their observation is due to a failure of integrability rather than instability of the semistatic form. Mathematically, our results relate to the decomposability of functions as studied in the context of Schrödinger bridges.

 

The gas-phase reaction of the methylidyne (CH; X 2 Π) radical with dimethylacetylene (CH 3 CCCH 3 ; X 1 A 1g ) was studied at a collision energy of 20.6 kJ mol −1 under single collision conditions with experimental results merged with ab initio calculations of the potential energy surface (PES) and ab initio molecule dynamics (AIMD) simulations. The crossed molecular beam experiment reveals that the reaction proceeds barrierless via indirect scattering dynamics through long-lived C 5 H 7 reaction intermediate(s) ultimately dissociating to C 5 H 6 isomers along with atomic hydrogen with atomic hydrogen predominantly released from the methyl groups as verified by replacing the methylidyne with the D1-methylidyne reactant. AIMD simulations reveal that the reaction dynamics are statistical leading predominantly to p28 (1-methyl-3-methylenecyclopropene, 13%) and p8 (1-penten-3-yne, 81%) plus atomic hydrogen with a significant amount of available energy being channeled into the internal excitation of the polyatomic reaction products. The dynamics are controlled by addition to the carbon–carbon triple bond with the reaction intermediates eventually eliminating a hydrogen atom from the methyl groups of the dimethylacetylene reactant forming 1-methyl-3-methylenecyclopropene (p28). The dominating pathways reveal an unexpected insertion of methylidyne into one of the six carbon–hydrogen single bonds of the methyl groups of dimethylacetylene leading to the acyclic intermediate, which then decomposes to 1-penten-3-yne (p8). Therefore, the methyl groups of dimethylacetylene effectively ‘screen’ the carbon–carbon triple bond from being attacked by addition thus directing the dynamics to an insertion process as seen exclusively in the reaction of methylidyne with ethane (C 2 H 6 ) forming propylene (CH 3 C 2 H 3 ). Therefore, driven by the screening of the triple bond, one propynyl moiety (CH 3 CC) acts in four out of five trajectories as a spectator thus driving an unexpected, but dominating chemistry in analogy to the methylidyne – ethane system.