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The co-immobilization of enzymes and metal catalysts addresses key challenges in chemo-enzymatic catalysis, leading to a more efficient and environmentally sustainable process. Central to this approach is the development of a solid support with large pore size and an efficient decoration method for both enzymes and metal catalysts. In this context, a mesoporous covalent organic framework is rationally designed as the porous solid carrier for co-immobilizing a Ru(N^N)3-based photocatalyst, a Cp*Rh-based electron mediator, and an alcohol dehydrogenase. The integrated system catalyzes the Michael addition between 1-propanethiol and 1-penten-3-one to produce 1-(propylthio)pentan-3-one under visible light irradiation, which is further reduced to 1-(propylthio)pentan-3-ol with a photo-regenerated nicotinamide cofactor. This work presents a novel one-pot photobiocatalytic cascade system for synthesizing enantiomerically pure 1,3-mercaptoalkanols. The system showcases excellent performance in terms of yield and enantioselectivity, along with effective cofactor photo-regeneration, demonstrating a significant advancement in the field of chemo-enzymatic catalysis through enzyme and metal catalyst co-immobilization. [ABSTRACT FROM AUTHOR]

Wide bandgap semiconductor-based photocatalysts are usually limited by their low solar energy conversion efficiency due to their limited absorption solar wavelength, their rapid surface recombination of the photogenerated electron–hole pairs, and their low charge-carrier mobility. Here, we report a novel stepwise solution synthesis for achieving a new photocatalytic core–shell consisting of a titanate nanowire/reduced graphene oxide shell (or titanate/rGO) 1D-nanocomposite. The new core–shell nanocomposite maximized the specific surface area, largely reduced the charge transfer resistance and reaction energy barrier, and significantly improved the absorption of visible light. The core–shell nanocomposites' large on/off current ratio and rapid photo-responses boosted the photocurrent by 30.0%, the photocatalysis rate by 50.0%, and the specific surface area by 16.4% when compared with the results for the pure titanate nanowire core. Our numerical simulations support the effective charge separation on the new core–shell nanostructure, which can help further advance the novel photocatalysis. [ABSTRACT FROM AUTHOR]

Timely and accurate knowledge of species-level biomass is essential for forest managers to sustain forest resources and respond to various forest disturbance regimes. In this study, maps of species-level biomass in Chinese boreal forests were generated by integrating Moderate Resolution Imaging Spectroradiometer (MODIS) images with forest inventory data using k nearest neighbor (kNN) methods and evaluated at different scales. The performance of 630 kNN models based on different distance metrics, k values, and temporal MODIS predictor variables were compared. Random Forest (RF) showed the best performance among the six distance metrics: RF, Euclidean distance, Mahalanobis distance, most similar neighbor in canonical correlation space, most similar neighbor computed using projection pursuit, and gradient nearest neighbor. No appreciable improvement was observed using multi-month MODIS data compared with using single-month MODIS data. At the pixel scale, species-level biomass for larch and white birch had relatively good accuracy (root mean square deviation < 62.1%), while the other species had poorer accuracy. The accuracy of most species except for willow and spruce was improved up to the ecoregion scale. The maps of species-level biomass captured the effects of disturbances including fire and harvest and can provide useful information for broad-scale forest monitoring over time. Key words: species-level biomass, MODIS, Chinese boreal forest, Random Forest (RF), kNN. Une connaissance precise et en temps opportun de la biomasse de chaque espece est essentielle pour permettre aux amenagistes forestiers d'effectuer un amenagement durable des ressources forestieres et pour s'ajuster aux divers regimes de perturbations forestieres. Dans cette etude, des cartes de biomasse par espece ont ete generees dans les forets boreales chinoises en integrant des images MODIS (spectroradiometre imageur a resolution moyenne) a des donnees d'inventaire forestier au moyen de l'approche des k plus proches voisins (kNN) et evaluees a differentes echelles. Les performances de 630 modeles kNN ont ete comparees en fonction de differentes metriques de distance, valeurs de k et variables predictives temporelles de MODIS. Les forets d'arbres decisionnels (RF) ont fait ressortir les meilleures performances parmi les six metriques de distance : la distance RF, la distance euclidienne, la distance de Mahalanobis, le plus proche voisin dans l'espace de correlation canonique, le plus proche voisin calcule par poursuite de projection, et le plus proche voisin par gradient. L'utilisation de donnees MODIS sur plusieurs mois n'a apporte aucune amelioration notable en comparaison de l'utilisation des donnees MODIS d'un seul mois. A l'echelle des pixels, la biomasse par espece avait une precision relativement bonne pour le meleze et le bouleau blanc (ecart quadratique moyen < 62,1%), tandis que la precision etait plus faible pour les autres especes. Pour la plupart des especes, a l'exception du saule et de l'epinette, la precision s'est amelioree jusqu'a l'echelle de l'ecoregion. Les cartes de la biomasse par espece ont capte les effets des perturbations, y compris les feux et la recolte, et peuvent fournir des informations utiles pour la surveillance des forets a une vaste echelle au fil du temps. [Traduit par la Redaction] Mots-cles: biomasse par espece, spectroradiometre imageur a resolution moyenne (MODIS), foret boreale chinoise, forets d'arbres decisionnels (RF), methode des k plus proches voisins (kNN)., 1. Introduction The boreal forest is the second largest terrestrial biome in the world, covering 33% of forest area and holding 23% of terrestrial carbon stocks (Carlson et al. 2009; [...]

High-resolution site index (SI) and mean annual increment (MAI) maps are desired for local forest management. We integrated field inventory, Landsat, and ecological variables to produce 30 m SI and MAI maps for the Tahoe National Forest (TNF) where different tree species coexist. We converted species-specific SI using adjustment factors. Then, the SI map was produced by (i) intensifying plots to expand the training sets to more climatic, topographic, soil, and forest reflective classes, (ii) using results from a stepwise regression to enable a weighted imputation that minimized the effects of outlier plots within classes, and (iii) local interpolation and strata median filling to assign values to pixels without direct imputations. The SI (reference age is 50 years) map had an [R.sup.2] of 0.7637, a root-mean-square error (RMSE) of 3.60, and a mean absolute error (MAE) of 3.07 m. The MAI map was similarly produced with an [R.sup.2] of 0.6882, an RMSE of 1.73, and a MAE of 1.20 [m.sup.3] x [ha.sup.-1] x [year.sup.-1]. Spatial patterns and trends of SI and MAI were analyzed to be related to elevation, aspect, slope, soil productivity, and forest type. The 30 m SI and MAI maps can be used to support decisions on fire, plantation, biodiversity, and carbon. Key words: site index, mean annual increment, timber productivity, remote sensing, Sierra Nevada. Il est souhaitable de disposer de cartes a haute resolution d'indice de qualite de station (IQS) et d'accroissement annuel moyen (AAM) pour amenager localement les forets. Nous avons integre des variables ecologiques, d'inventaire de terrain et de Landsat pour produire des cartes d'IQS et d'AAM a une resolution de 30 m pour la foret nationale de Tahoe ou differentes especes d'arbres coexistent. Nous avons converti les IQS propres a chaque espece a l'aide de facteurs d'ajustement. Par la suite, la carte d'IQS a ete produite (i) en intensifiant les placettes pour etendre les donnees de base a des classes plus representatives de climat, de topographie, de sol et de foret, (ii) en utilisant les resultats d'une regression pas a pas pour realiser une imputation ponderee minimisant les effets des placettes aberrantes dans les classes, et (iii) en completant le jeu de donnees a l'aide d'interpolations locales et de valeurs medianes des strates pour assigner des valeurs aux pixels n'ayant pas d'imputation directe. La carte d'IQS (l'age de reference est de 50 ans) etait associee a un [R.sup.2] de 0,7637, une erreur quadratique moyenne (EQM) de 3,60 et une erreur moyenne absolue (EMA) de 3,07 m. La carte d'AAM a ete produite de facon similaire et etait associee a un [R.sup.2] de 0,6882, une EQM de 1,73 et une EMA de 1,20 [m.sup.3] x [ha.sup.-1] x [an.sup.-1]. La distribution et la tendance spatiale du rapport entre l'IQS et l'AAM ont ete analysees et reliees a l'altitude, l'orientation, la pente, la productivite du sol et le type forestier. Les cartes d'IQS et d'AAM a une resolution de 30 m peuvent etre utilisees pour appuyer les decisions concernant le feu, les plantations, la biodiversite et le carbone. [Traduit par la Redaction] Mots-cles: indice de qualite de station, accroissement annuel moyen, productivite ligneuse, teledetection, Sierra Nevada., 1. Introduction Forest productivity is an important indicator of diverse applications such as biofuels supply, carbon sequestration, and forest growth projection. In the western United States (US), potential productivity is [...]