Maximum carboxylation rate (Vcmax) is a key parameter to characterize the forest carbon cycle process. Hence, monitoring the Vcmax of different forest types is a hot research topic at home and abroad, and hyperspectral remote sensing is an important technique for Vcmax inversion. Moso bamboo is a unique forest type with a high carbon sequestration capacity in subtropical regions, but the lack of Vcmax data is a major limitation to accurately modeling carbon cycling processes in moso bamboo forests. Our study area was selected in the moso bamboo forest carbon sink research base in Shanchuan Township, Anji County, Zhejiang Province, China, which has a typical subtropical climate and is widely distributed with moso bamboo forests. In this study, the hyperspectral reflectance and V25cmax (Vcmax converted to 25 °C) of leaves of newborn moso bamboo (I du bamboo) and 2- to 3-year-old moso bamboo (II du bamboo) were measured at different canopy positions, i.e., the top, middle and bottom, in the moso bamboo forest. Then, we applied a discrete wavelet transform (DWT) to the obtained leaf hyperspectral reflectance to construct the wavelet vegetation index (WVI), analyzed the relationship between the WVI and moso bamboo leaf V25cmax, and compared the WVI to the existing hyperspectral vegetation index (HVI). The ability of the WVI to characterize the moso bamboo V25cmax was interpreted. Finally, the partial least squares regression (PLSR) method was used to construct a model to invert the V25cmax of moso bamboo leaves. We showed the following: (1) There are significant leaf V25cmax differences between I du and II du bamboo, and there are also significant leaf V25cmax differences between the top, middle and bottom canopy positions of I du bamboo. (2) Compared to that with the HVI, the detection wavelength of the V25cmax of the WVI expanded to the shortwave infrared region, and thus the WVI had a higher correlation with the V25cmax. The absolute value of the correlation coefficient between the V25cmax of I du bamboo and SR2148,2188 constructed by cD1 was 0.75, and the absolute value of the correlation coefficient between the V25cmax of II du bamboo and DVI2069,407 constructed by cD2 was 0.67. The highest absolute value of the correlation coefficient between V25cmax and WVI at the three different canopy positions was also 13–21% higher than that with the HVI. The longest wavelength used by the WVI was 2441 nm. (3) The validation accuracies of the V25cmax inversion models constructed with the WVI as a variable were all higher than those of the models constructed with the HVI as a variable for all ages and positions, with the highest R2 value of 0.97 and a reduction of 20–60% in the root mean square error (RMSE) value. After the wavelet decomposition of the hyperspectral reflectance of moso bamboo leaves, the low-frequency components contained no noise, and the high-frequency components highlighted the original spectral detail features. The WVI constructed by these components increases the wavelength range of V25cmax interpretation. Therefore, the V25cmax retrieval model based on the WVI encompasses different resolutions and levels of spectral characteristics, which can better reflect the changes in bamboo leaves and can provide a new method for the inversion of the V25cmax of moso bamboo forests based on hyperspectral remote sensing.
(1) Background: A three-dimensional (3D) real scene is a digital representation of the multidimensional dynamic real-world structure that enables the realistic and stereoscopic expression of actual scenarios, and is an important technological tool for urban refinement management. The above-ground biomass (AGB) of urban forests is an important indicator that reflects the urban ecological environment; therefore, the accurate estimation of AGB is of great significance for evaluating urban ecological functions. (2) Methods: In this study, multiangle aerial photographs of urban street trees were obtained via an unmanned aerial vehicle (UAV) single-lens five-way flight, from 0°, 0°, 90°, 180°, 270°, and five other directions. The multiple view stereo (MVS) algorithm was used to construct three-dimensional realistic models of two tree species: ginkgo and camphor. Then, structural parameters such as tree height, crown diameter, and crown volume were estimated from the 3D real-scene models. Lastly, single-tree AGB models were developed based on structural parameters. (3) Results: The results of this study indicated the following: (A) The UAV visible-light realistic 3D model had clear texture and truly reflected the structural characteristics of two tree species, ginkgo and camphor. (B) There was a significant correlation between the reference tree height, crown diameter and crown volume obtained from the realistic 3D model and the measured values; the R2 for ginkgo height was 0.90, the R2 for camphor crown diameter was 0.87, and the R2 for ginkgo crown volume was 0.89. (C) The accuracy of the AGB estimation models constructed with tree height and canopy volume as variables was generally higher than that of models with tree height and canopy diameter; the model with the highest accuracy of AGB estimation for ginkgo was the linear model with a validation accuracy R2 of 0.96 and RMSE of 8.21 kg, while the model with the highest accuracy of AGB estimation for camphor was the quadratic polynomial model with a validation accuracy R2 of 0.92 and RMSE of 27.74 kg. (4) Conclusions: This study demonstrated that the UAV 3D real-scene model can achieve high accuracy in estimating single-wood biomass in urban forests. In addition, for both tree species, there was no significant difference between the AGB estimates based on the UAV 3D real scene and LiDAR and the measured AGB. These results of urban single-wood AGB estimation based on the UAV 3D real-scene model were consistent with those of LiDAR and even with the measured AGB. Therefore, based on the UAV 3D real-scene model, the single-wood biomass can be estimated with high accuracy. This represents a new technical approach to urban forest resource monitoring and ecological environment function evaluation.
The synthesis of oxygen-substituted N-hydroxy phthalimide derivatives is essential due to their ubiquity in natural products and pharmaceuticals.Metals or peroxides are often required for most C＝C/C-H bond activation methods used for olefins, ketones, esters, aldehydes and alcohols.Using cheap and safe iodobenzene diacetate as a feasible dehydrogenation agent and N-hydroxy phthalimide as free radical precursor, the dioxidation of olefins, α-oxidation of carbonyl compounds, oxidation of aldehydes, and oxidative esterification of primary alcohols were successfully realized.This method occurs via a radical mechanism and has the characteristics of mild metal-free reaction conditions, good compatibility and wide substrate scope.
Sustained release of bioactive BMP2 (bone morphogenetic protein-2) is important for bone regeneration, while the intrinsic short half-life of BMP2 at protein level cannot meet the clinical need. In this study, we aimed to design Bmp2 mRNA-enriched engineered exosomes, which were then loaded into specific hydrogel to achieve sustained release for more efficient and safe bone regeneration.Bmp2 mRNA was enriched into exosomes by selective inhibition of translation in donor cells, in which NoBody (non-annotated P-body dissociating polypeptide, a protein that inhibits mRNA translation) and modified engineered BMP2 plasmids were co-transfected. The derived exosomes were named ExoBMP2+NoBody. In vitro experiments confirmed that ExoBMP2+NoBody had higher abundance of Bmp2 mRNA and thus stronger osteogenic induction capacity. When loaded into GelMA hydrogel via ally-L-glycine modified CP05 linker, the exosomes could be slowly released and thus ensure prolonged effect of BMP2 when endocytosed by the recipient cells. In the in vivo calvarial defect model, ExoBMP2+NoBody-loaded GelMA displayed great capacity in promoting bone regeneration.Together, the proposed ExoBMP2+NoBody-loaded GelMA can provide an efficient and innovative strategy for bone regeneration.
Urbanization inevitably poses a threat to urban ecology by altering its external structure and internal attributes. Nighttime light (NTL) has become increasingly extensive and practical, offering a special perspective on the world in revealing urbanization. In this study, we applied the Normalized Impervious Surface Index (NISI) constructed by NTL and MODIS NDVI to examine the urbanization process in the Yangtze River Delta (YRD). Geographical detectors combined with factors involving human and natural influences were utilized to investigate the drive mechanism. Urban ecology stress was evaluated based on changes in urban morphological patterns and fractional vegetation cover (FVC). The results showed that the NISI can largely overcome the obstacle of directly coupling NTL data in performing urbanization and has efficient applicability in the long-term pixel scale. Built-up areas in the YRD increased by 2.83 times during the past two decades, from 2053.5 to 7872.5 km2. Urbanization intensity has saturated the city center and is spilling over into the suburbs, which show a “cold to hot” spatial clustering distribution. Economic factors are the primary forces driving urbanization, and road network density is becoming essential as factor that reflects urban infrastructure. Urban geometry pattern changes in fractal dimension (FD) and compactness revealed the ecological stress from changing urban external structure, and internal ecological stress was clear from the negative effect on 63.4% FVC. This impact gradually increased in urban expanded area and synchronously decreased when urbanization saturated the core area. An analysis of ecological stress caused by urbanization from changing physical structure and social attributes can provide evidence for urban management and coordinated development.
Subtropical forests are rich in vegetation and have high photosynthetic capacity. China is an important area for the distribution of subtropical forests, evergreen broadleaf forests (EBFs) and evergreen needleleaf forests (ENFs) are two typical vegetation types in subtropical China. Forest carbon storage is an important indicator for measuring the basic characteristics of forest ecosystems and is of great significance for maintaining the global carbon balance. Drought can affect forest activity and may even lead to forest death and the stability characteristics of different forest ecosystems varied after drought events. Therefore, this study used meteorological data to simulate the standardized precipitation evapotranspiration index (SPEI) and the Biome-BGC model to simulate two types of forest carbon storage to quantify the resistance and resilience of EBF and ENF to drought in the subtropical region of China. The results show that: 1) from 1952 to 2019, the interannual drought in subtropical China showed an increasing trend, with five extreme droughts recorded, of which 2011 was the most severe one; 2) the simulated average carbon storage of the EBF and ENF during 1985-2019 were 130.58 t·hm-2 and 78.49 t·hm-2, respectively. The regions with higher carbon storage of EBF were mainly concentrated in central and southeastern subtropics, where those of ENF mainly distributed in the western subtropic; 3) The median of resistance of EBF was three times higher than that of ENF, indicating the EBF have stronger resistance to extreme drought than ENF. Moreover, the resilience of two typical forest to 2011 extreme drought and the continuous drought events during 2009 - 2011 were similar. The results provided a scientific basis for the response of subtropical forests to drought, and indicating that improve stand quality or expand the plantation of EBF may enhance the resistance to drought in subtropical China, which provided certain reference for forest protection and management under the increasing frequency of drought events in the future.
The precise control of complicated regioselectivity of 1,3-enynes upon addition reaction has been a long-standing challenge in synthetic chemistry, even more pronounced when simultaneously striving to achieve both Z and E selectivity. A unique copper-catalyzed stereodivergent Z/E-selective α-addition of yne-allylic esters for multicomponent reaction and polymerization was developed. The esters’ leaving ability and steric hindrance effect of intermediates synergistically controlled the regioselectivity and stereoselectivity for synthesizing both (E, Z, E)- and (E, E, E)-dienylamidines in up to 94% yield with 48 examples involving uncommon vinyl ketenimine intermediate and vinyl alkylidene ketenimine intermediate, respectively. Such approach could be further applied to multicomponent polymerization for preparing 10 special polymers in up to 94% yield with Mn up to 17,900 g/mol.
Forest biomass is an essential indicator of forest ecosystem carbon cycle and global climate change research, and traditional machine learning cannot explain the mechanism of feature variable impact on forest aboveground biomass (AGB). Therefore, we proposed an interpretable bamboo forest AGB prediction method based on Shaply Additive exPlanation (SHAP) and XGBoost model to explain the impact mechanism of feature variables on AGB. The bamboo forest AGB is estimated using the monthly and annual scale leaf area index (LAI), enhanced vegetation index (EVI), ratio vegetation index (RVI), precipitation (Pre), maximum temperature (Tmax), minimum temperature (Tmin) and solar radiation (Rad) data. The results showed that the method could be effectively predict AGB, and precipitation more important than temperature. The framework revealed the threshold effect, exceeded the threshold value, the impacts of LAI_Ann, EVI_Ann, and Pre_11 on AGB were stable. The SHAP interaction value between LAI_Ann and EVI_Ann decreased with increasing EVI_Ann and LAI_Ann. By contrast, when Pre_11 increased, the SHAP interaction value between LAI_Ann and Pre_11 increased with increasing LAI_Ann. The framework could also be easily implemented, providing an interpretable machine learning model of forest AGB.
Nonspecific binding and weak spectral discernment are the main challenges for surface-enhanced Raman scattering (SERS) detection, especially in real sample analysis. Herein, molecularly imprinted polymer (MIP)-based core–shell AuNP@polydopamine (AuNP@PDA-MIP) nanoparticles (NPs) are designed and immobilized on an electrochemically reduced MoS2-modified screen-printed electrode (SPE). This portable electrochemical–Raman interface offers the dual functions of electrokinetic preseparation (EP) and MIP trapping of charged molecules so that a reliable SERS recognition with molecular selectivity and high sensitivity can be achieved. Core–shell AuNP@PDA-MIP NPs can be controllably synthesized, possess predesigned specific recognition, and provide "hot spots" at the junction of NPs. The introduction of an electric field enables the autonomous exclusion and separation of similarly charged molecules as well as attraction and concentration of the oppositely charged molecules by electrostatic attraction. Subsequently, the specific MIP recognition cavities allow selective adsorption of targets on the interface without the interference of analogues. Owing to the distinctive design of the multiple coupling separation, trapping, and enrichment strategies, the MIP-based SERS-active interface can be used for label-free detection of charged molecules in real samples without pretreatment. As a proof-of-concept study, label-free SERS detection of charged phthalate plasticizers (PAEs) was demonstrated with a detection limit as low as 2.7 × 10–12 M for dimethyl phthalate (DMP) and 2.3 × 10–11 M for di(2-ethylhexyl) phthalate (DEHP). This sensing strategy for in situ SERS analysis of charged pollutants or toxins holds vast promises for a wide range of in-field applications.
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