Search

Abstract Cisplatin (CDDP) is the primary drug used in the initial treatment of esophageal cancer (EC). However, its side effects and resistance can limit its effectiveness in clinical therapy. Curcumin (Cur)-mediated glutathione (GSH) depletion can reverse resistance, enhance the chemosensitivity of CDDP, and further improve the efficacy of platinum-containing chemotherapy in the treatment of esophageal cancer. However, it is also faced with problems of poor water solubility and low bioavailability in vivo, which severely hinders cancer treatments. In order to address these issues, we developed a novel nanotherapeutic system called CDCZA, combining Cur/CDDP/Cu/ZIF8@Au to enhance chemotherapy through GSH depletion and chemodynamic therapy through self-produced H2O2. Cu and CDDP were precisely co-loaded into Cu/ZIF8 nanoparticles using a one-pot method, then ultra-small gold nanoparticles mimicking glucose oxidase (Au nanoparticles) were embedded in the outer shell to create the CDCZA nano system. The released Cur could notably decrease intracellular GSH content and thus improve the chemosensitivity of CDDP, resulting in severe cellular apoptosis. And the Au nanoparticles effectively enabled chemodynamic therapy enhancement by accelerating the depletion of β-D-glucose into H2O2. As a result, the CDCZA nanoparticles showed increased tumor accumulation and improved antitumor effectiveness in a model of EC. Taken together, this work provides a new idea for the clinical design of efficient treatment reagents for EC.

Abstract Objective To investigate the mechanism by which cancer-associated fibroblasts (CAFs) affect the growth and immune evasion of lung cancer cells. Methods Initially, datasets comparing CAFs with normal fibroblasts were downloaded from the GEO dataset GSE48397. Genes with the most significant differential expression were selected and validated using clinical data. Subsequently, CAFs were isolated, and the selected genes were knocked down in CAFs. Co-culture experiments were conducted with H1299 or A549 cells to analyze changes in lung cancer cell growth, migration, and immune evasion in vitro and in vivo. To further elucidate the upstream regulatory mechanism, relevant ChIP-seq data were downloaded from the GEO database, and the regulatory relationships were validated through ChIP-qPCR and luciferase reporter assays. Results OLR1 was significantly overexpressed in CAFs and strongly correlated with adverse prognosis in lung cancer patients. Knockdown of OLR1 markedly inhibited CAFs’ support for the growth and immune evasion of lung cancer cells in vitro and in vivo. ChIP-seq results demonstrated that PRRX1 can promote OLR1 expression by recruiting H3K27ac and H3K4me3, thereby activating CAFs. Knockdown of PRRX1 significantly inhibited CAFs’ function, while further overexpression of OLR1 restored CAFs’ support for lung cancer cell growth, migration, and immune evasion. Conclusion PRRX1 promotes OLR1 expression by recruiting H3K27ac and H3K4me3, activating CAFs, and thereby promoting the growth, migration, and immune evasion of lung cancer cells.

The rapid development towards automated construction has been witnessed in recent years mainly due to the growing shortage of skilled labor. Against that backdrop, an accelerated method, with the aid of robotic cranes, is emerging in China to speed up the construction of industrial facilities such as warehouse structures. This method requires that the steel bars in the precast beams do not extend beyond the beam ends to facilitate the temporary fixation of the robotic crane at the top of cast-in-place columns. This, nonetheless, brings a series of new problems, one of which is how to choose a suitable anchoring type for the beam bottom bars. To address this issue, three large-scale exterior beam-to-column connections were fabricated and tested under lateral load reversals. Two anchorage forms, namely, mechanical splices and grouted sleeves, were adopted and compared with the monolithically cast specimen. The test results showed that the specimen using the grouted sleeves had similar seismic performance to that of the cast-in-place specimen, whereas the specimen using the mechanical splices presented significant post-peak deterioration under positive beam bending moments. This happened because the congestion of steel bars within the joint core made it difficult to fully tighten the beam bottom bars into the threaded couplers; consequently, a “slop” was formed which could substantially impair the cyclic behavior of the specimen. As such, it is suggested that grouted sleeves should be more applicable and reliable for the new construction method. This counter-intuitive finding also indicates that, for intelligent construction, no detail should be taken for granted, but rather needs due consideration.

According to the problem of high complexity of base station detection in large scale multiuser multiple input multiple output (MIMO) system,a low complexity multiuser variable node full information Gaussian message passing iterative detection algorithm based on forced convergence (VFI-GMPID-FC) was proposed.Firstly,the traditional Gaussian message passing iterative detection (GMPID) algorithm was improved to obtain VFI-GMPID algorithm,the detection performance of the VFI-GMPID algorithm approximates the minimum mean square error detection (MMSE) algorithm,but the complexity was considerably less than the MMSE algorithm.Then,the VFI-GMPID-FC algorithm was proposed to reduce the complexity of the algorithm and improve the detection efficiency.Finally,the simulation results show that the proposed algorithm can effectively reduce the algorithm complexity while ensuring the detection performance.

Sparse code multiple access technology,as a competitive non orthogonal multiple access scheme for the fifth generation wireless communication network,has a broad application prospect.However,current SCMA uplink use the flooding scheme of message passing algorithm for decoding,both the detection complexity and convergence properties are not ideal.A serial message passing algorithm which changed the information updating strategy was proposed,which performed message processing and deliveried according to the order of the variable nodes.Each of variable node simultaneously performed the reception of the verification message and the transmission of the variable message.The theoretical and simulation results show that the proposed algorithm not only maintains good performance,but also has low decoding complexity.

To reuse waste concrete in a more straightforward and simplified way, a new kind of structural member containing fresh concrete (FC) and demolished concrete lumps (DCLs) distinctly larger than conventional recycled aggregates has been proposed. Previous research has shown that, at room temperature, the mechanical performance of the U-shaped steel beams filled with DCLs and FC is similar to that of the U-shaped steel beams filled with FC alone. This research explores the fire behavior of the U-shaped steel beams filled with DCLs and FC. Five specimens including three beams filled with DCLs and FC and two reference beams filled with FC alone were tested in fire. The experimental parameters included the replacement ratio of DCLs, the longitudinal reinforcement ratio, the load ratio, and the thickness of fire insulation. Based on the test results, numerical models in which the thermal resistance at the interface between the U-shaped steel and the in-filled concrete is considered are developed using SAFIR to determine the thermal and structural responses of the specimens. Lastly, parametric studies are carried out preliminarily to investigate the effects of some parameters on the fire resistance of such beams. It is found that the replacement ratio of DCLs within a range of 0% to 33% has a very limited effect on the temperature distribution, structural response, and fire resistance of the specimens, that embedding longitudinal reinforcements can significantly increase the fire resistance of such beams, that the interface thermal resistance can generate a temperature drop of up to 280 °C at the interface between the U-shaped steel and the in-filled concrete, and that the numerical models are capable of predicting the thermal and structural responses of such beams.

Bottom-fixed vertical rotating devices are widely used in industrial and civilian fields. The free upside of the rotor will cause vibration and lead to noise and damage during operation. Meanwhile, parameter uncertainties, nonlinearities and external disturbances will further deteriorate the performance of the rotor. Therefore, in this paper, we present a rotor orientation control system based on an active magnetic bearing with L 1 adaptive control to restrain the influence of the nonlinearity and uncertainty and reduce the vibration amplitude of the vertical rotor. The boundedness and stability of the adaptive system are analyzed via a theoretical derivation. The impact of the adaptive gain is discussed through simulation. An experimental rig based on dSPACE is designed to test the validity of the rotor orientation system. The experimental results show that the relative vibration amplitude of the rotor using the L 1 adaptive controller will be reduced to ∼50% of that in the initial state, which is a 10% greater reduction than can be achieved with the nonadaptive controller. The control approach in this paper is of some significance to solve the orientation control problem in a low-speed vertical rotor with uncertainties and nonlinearities.

Abstract The development of nasal inverted papilloma (NIP) is closely related to human papillomavirus (HPV) infection. Previous studies indicated that HPV11 shows the highest expression in NIP tissues. However, the mechanisms following its integration into host DNA require further clarification. In this study, high-throughput sequencing was employed to identify the HPV integration site KDM4A in HPV-positive specimens. The HPV11E6/E7 overexpression model was established in human nasal mucosal epithelial cells (HNE-pC), and the KDM4A gene was knocked out using CRISPR/Cas9 technology. Cell proliferation was assessed via CCK-8, colony formation, and EdU assays, while cell migration was evaluated through Transwell and wound healing assays. qRT-PCR and Western blot were used not only to analyze mRNA and protein expression in cells after HPV11E6/E7 overexpression and knockout of KDM4A but also to study the effect of the polarization of macrophages. A subcutaneous tumor model in nude mice validated the effects on proliferation and KDM4A knockout in vivo, with macrophage polarization types assessed via immunofluorescence staining. Results showed that HPV11E6/E7 overexpression significantly enhanced nasal epithelial cell proliferation and migration, along with promoting M1 macrophage polarization. Knockout of KDM4A inhibited these effects and delayed the progression of macrophages toward M1 polarization. Our findings suggest that low-risk HPV11 can drive the proliferation of nasal mucosa and regulate M1 macrophage polarization via KDM4A, potentially contributing to NIP pathogenesis. Targeting inhibition of KDM4A expression may represent a viable therapeutic strategy for HPV-positive NIP.

The cause of continuing education has gained significant strides in China after the advent of Reform and Opening Up, but it is still the weakest link in the current system of education. The "National Medium- and Long-Term Educational Reform and Development Guideline (2010-20)" (hereafter abbreviated as the "Guideline") has established the special position of continuing education in the overall setup of national education, its goals, and its developmental tasks. Targeting existing problems, the "Guideline" proposes institutional design with a multicomponent basic setup, effective management systems, and new development mechanisms, as well as a series of complementary reform measures, including "building "overpasses" for lifelong learning." (Contains 2 notes and 1 table.)

Abstract Accurately mapping aboveground biomass (AGB) in China’s boreal forests is crucial for assessing global carbon stock and formulating forest management strategies but remains challenging as the environmental heterogeneity complicates AGB estimation. Here, we investigated the relative gains of integrating Sentinel-2 and environmental data, as well as synthetic aperture radar (SAR) images to map AGB in China’s boreal forests. We used two machine learning algorithms, random forest and gradient boosting regression (GBR), and four dataset combinations to develop the AGB models, then evaluated the AGB map by carrying on uncertainty analysis and comparing it with existing AGB products. Results showed that the GBR model based on Sentinel-2 and environmental data presented the best AGB estimation capability (R2: 0.75, RMSE: 23.60 Mg/ha), while further adding SAR images had negative effects on the model improvement. The Tasseled Cap Distance, short-wave infrared from Sentinel-2, Black dragon fire disturbance, Elevation, and Geographic locations were found to be significant contributors to AGB prediction. Our AGB estimates exhibited moderate to low uncertainty and outperformed other existing AGB maps in China’s boreal forests based on independent validation assessment. The AGB distribution presented a noticeable south-north gradient difference, ranging from 3.23 to 346.37 Mg/ha. This study provides new insight into AGB estimation through the integration of Sentinel-2 imagery and multiple environmental data and offers a basis for sustainable management in China’s boreal forests.

Abstract Ga‐doped zinc oxide (ZnO) microwires hold great promise for developing highly efficient light sources because of the wide bandgap with proper exciton binding energy. However, most microwires grown from one mainstream approach, i.e., chemical vapor deposition (CVD), are morphologically and crystallographically defective, exhibiting limited photoluminescence performances. Herein, a simple and effective X‐ray irradiation strategy is demonstrated for enhancing the photoluminescence of Ga‐doped ZnO microwire in ambient conditions. Under moderate doses (≤ 150 Gy), the photoluminescence monotonically rockets up with X‐ray dose increment and achieves nine‐fold enhancement at a dose of ≈150 Gy, recording high photoluminescence improvement of ZnO microwires to date. The elemental characteristics under different controlled irradiation atmospheres suggest the elimination of surface oxygen vacancy and the cross‐section transmission electron microscope reveals prominent lattice relaxations after mild X‐ray irradiation. In addition, the X‐ray irradiated microwires further exhibit elevated electroluminescence by over three times. The enhanced photoluminescence and electroluminescence as well as long‐term stability enable us to imagine the super‐rapid applications of ZnO microwires in modern optoelectronic devices.

Featured with light emission and detection coexistence phenomenon, nitride-based multiple-quantum-well (MQW) diodes integrated chip has been proven to be an attractive structure for application prospects in various fields such as lighting, sensing, optical communication, and other fields. However, most of the recent reports are based on planar structures. Three-dimensional (3D) structures are endowed with extra advantages in direction, polarization, and absorption modulation and may pioneer a new way to make the same thing over and over again with interesting properties. In this paper, we designed and fabricated a single-cantilever InGaN/GaN MQW diode with warped 3D microstructure via standard microfabrication technology. Experimental results indicate that the strain architecture of the multi-layer materials is the key principle for the self-warped device. The planar structure will bear greater compressive stress while the warped beam part has less stress, which results in differences in the optical and electrical performance. The strain-induced band bending highly influences the emission and detection properties, while the warped structure will introduce direction selectivity to the 3D device. As an emitter, 3D structures exhibit a directional emission with lower turn-on voltage, higher capacitance, increased luminous intensity, higher external quantum efficiency (EQE), high –3 dB bandwidth, and redshifted peak wavelength. Besides, it can serve as an emitter for directional-related optical communication. As a receiver, 3D structures have lower dark-current, higher photocurrent, and red-shifted response spectrum and also show directional dependence. These findings not only deepen the understanding of the working principle of the single-cantilever GaN devices but also provide important references for device performance optimization and new applications in visible light communication (VLC) technology.

Mangroves are vital coastal ecosystems that provide crucial links between land and sea. Tree height is a key indicator for assessing mangroves’ health status. Currently, there are still numerous challenges in estimating mangrove tree height. In this study, multiple deep learning and shallow machine learning regression models were developed to accurately estimate mangrove tree height using multi-dimensional Light Detection and Ranging (LiDAR) point clouds and their derivatives. We constructed a novel CNN_RepMLP model for mangrove tree height mapping. We also further verified the applicability of different types of regression models in estimating mangrove tree heights, and explored the influence of different LiDAR-derived features on the inversion accuracy for tree heights. The results indicated the following: (1) The CNN_RepMLP displayed satisfactory performance in the inversion of mangrove tree heights, and exhibited better robustness and generalization ability than the convolutional neural network (CNN) model. (2) Among the different LiDAR-derived feature combinations, combining height variables with intensity variables can not only mitigate the negative impact of height variables on inversion models, but also enhance the mangrove tree height inversion accuracy. (3) The ensemble learning framework with ExtraTrees as the meta-model can make better use of the differences and complementarities between different single base models, and exhibited better accuracy in estimating the height of mangrove trees compared with other ensemble learning models. (4) Multiple machine learning models based on multi-dimensional UAV-LiDAR point-cloud-derived features are suitable for the inversion of mangrove tree height. The CNN_RepMLP model outperformed the CNN and stacking ensemble learning models and had more detailed differentiation in terms of mangrove tree height. Its prediction results can more realistically reflect the spatial differentiation characteristics of mangrove tree height.

Mangroves are one of the most important marine ecosystems globally, their spatial distribution is crucial for promoting mangrove ecosystems conservation, restoration, and sustainable managements. This study proposed a novel Unet-Multi-Scale High-Resolution Vision Transformer (UHRViT) model for classifying mangrove species using unmanned aerial vehicle (UAV-RGB), UAV-LiDAR, and Gaofen-3 Synthetic Aperture Radar (GF-3 SAR) images. The UHRViT utilized a multi-scale high-resolution visual Transformer as its backbone network and was designed to a multi-branch U-shaped network structure to extract features of different scales layer by layer, and to facilitate the interaction of high and low-level semantic information. We further verified the classification performance superiority of UHRViT model by comparing to HRViT and HRNetV2 algorithms. We also systematically investigated the effects of active–passive image combination ratios on mangrove communities mapping. The results revealed that: UAV-RGB images exhibited the better classification accuracy (mean F1-score＞95 %) for mangrove species than UAV-LiDAR and GF-3 SAR images; The classification performances and stability of UHRViT algorithm in the fifteen datasets outperformed the HRViT and HRNetV2 algorithms; Combining UAV-RGB with GF-3 SAR or UAV-LiDAR images respectively, both achieved better classifications than the single data source. Based on the UHRViT algorithm, the combination of UAV-RGB and UAV-LiDAR achieved the highest classification accuracy (Iou = 0.944, MIou = 50.2 %) for Avicennia corniculatum (AC). When the combination ratio of UAV-RGB with GF-3 SAR or UAV-LiDAR was 3:1, Avicennia marina and AC both obtained the optimal classification accuracy with average F1-scores of 98.19 % and 97.3 %, respectively. Our works revealed that the changes in the classification accuracies of mangrove communities under multi-sensor image combination ratios, and demonstrated that our model could effectively improve the classification accuracy of mangrove communities.

Abstract A novel modified phosphorus β-hemihydrate gypsum (MPG) cementing material was developed to solidify lead-contaminated soil. The solidification effects of lead in the contaminated soil with MPG and Portland cement (PC) as curing agent were contrasted by the unconfined compressive strength (UCS), pH and leaching toxicity of solidified soil. The solidification mechanism of lead contaminated soil was analyzed by XRD, BET, SEM and EDS. The results demonstrated that when the addition of binder increased from 24 to 30%, the UCS of MPG solidified body became higher than that of PC solidified body by 14.7–18.8%. The pH of MPG solidified body was 9.81–10.69, which was 15.17–22.08% lower than that of PC solidified body. The lead leaching concentration of MPG solidified body decreased continuously with the curing time and became lower than the limit of hazardous waste content (5 mg L−1) stipulated in Chinese standards after 7-day curing. The results of microscopic analysis revealed that the main components of MPG solidified body were ettringite (AFt), reticulated gel of calcium silicate hydrated (C–S–H), lead phosphate ([Pb10(PO4)6(OH)2]) and lead sulfate (PbSO4) precipitation. The covering of C–S–H on soil particles and the ion exchange between lead and AFt contributed jointly to the stabilization of lead in the solidified soil. This is a valuable application exploitation study for the treatment of Pb contaminated soil and reutilization of waste phosphorus gypsum.

Abstract Background Ginsenoside Rh2 (G-Rh2), a steroidal compound extracted from roots of ginseng, has been extensively studied in tumor therapy. However, its specific regulatory mechanism in non-small cell lung cancer (NSCLC) is not well understood. Pyruvate dehydrogenase kinase 4 (PDK4), a central regulator of cellular energy metabolism, is highly expressed in various malignant tumors. We investigated the impact of G-Rh2 on the malignant progression of NSCLC and how it regulated PDK4 to influence tumor aerobic glycolysis and mitochondrial function. Method We examined the inhibitory effect of G-Rh2 on NSCLC through I proliferation assay, migration assay and flow cytometry in vitro. Subsequently, we verified the ability of G-Rh2 to inhibit tumor growth and metastasis by constructing subcutaneous tumor and metastasis models in nude mice. Proteomics analysis was conducted to analyze the action pathways of G-Rh2. Additionally, we assessed glycolysis and mitochondrial function using seahorse, PET-CT, Western blot, and RT-qPCR. Result Treatment with G-Rh2 significantly inhibited tumor proliferation and migration ability both in vitro and in vivo. Furthermore, G-Rh2 inhibited the tumor’s aerobic glycolytic capacity, including glucose uptake and lactate production, through the HIF1-α/PDK4 pathway. Overexpression of PDK4 demonstrated that G-Rh2 targeted the inhibition of PDK4 expression, thereby restoring mitochondrial function, promoting reactive oxygen species (ROS) accumulation, and inducing apoptosis. When combined with sodium dichloroacetate, a PDK inhibitor, it complemented the inhibitory capacity of PDKs, acting synergistically as a detoxifier. Conclusion G-Rh2 could target and down-regulate the expression of HIF-1α, resulting in decreased expression of glycolytic enzymes and inhibition of aerobic glycolysis in tumors. Additionally, by directly targeting mitochondrial PDK, it elevated mitochondrial oxidative phosphorylation and enhanced ROS accumulation, thereby promoting tumor cells to undergo normal apoptotic processes.

Abstract Background Circular RNAs (circRNAs) belong to a class of covalently closed single stranded RNAs that have been implicated in cancer progression. Former investigations showed that hsa-circ-0013561 is abnormally expressed in head and neck squamous cell carcinoma (HNSCC). Nevertheless, the role of hsa-circ-0013561 during the progress of HNSCC still unclear. Methods Present study applied FISH and qRT-PCR to examine hsa-circ-0013561 expression in HNSCC cells and tissue samples. Dual-luciferase reporter assay was employed to identify downstream targets of hsa-circ-0013561. Transwell migration, 5-ethynyl-2′-deoxyuridine incorporation, CCK8 and colony formation assays were utilized to test cell migration and proliferation. A mouse tumor xenograft model was utilized to determine the hsa-circ-0013561 roles in HNSCC progression and metastasis in vivo. Results We found that hsa-circ-0013561 was upregulated in HNSCC tissue samples. hsa-circ-0013561 downregulation inhibited HNSCC cell proliferation and migration to promote apoptosis and G1 cell cycle arrest. The dual-luciferase reporter assay revealed that miR-7-5p and PDK3 are hsa-circ-0013561 downstream targets. PDK3 overexpression or miR-7-5p suppression reversed the hsa-circ-0013561-induced silencing effects on HNSCC cell proliferation and migration. PDK3 overexpression reversed miR-7-5p-induced effects on HNSCC cell proliferation and migration. Conclusion The findings suggest that hsa-circ-0013561 downregulation inhibits HNSCC metastasis and progression through PDK3 expression and miR-7-5p binding modulation.

Abstract Background Circular RNAs (circRNAs) are single-stranded RNAs with covalently closed structures that have been implicated in cancer progression. However, the regulatory mechanisms remain largely unclear. So, the aim of this study was to reveal the role and regulatory mechanisms of circ-SLC16A1. Methods In this study, next-generation sequencing was used to identify abnormally expressed circRNAs between cancerous and para-carcinoma tissues. Fluorescence in situ hybridization and quantitative reverse transcription polymerase chain reaction were performed to assess the expression patterns of circ-solute carrier family 16 member 1 (SLC16A1) in non-small cell lung cancer (NSCLC) cells and tissue specimens. The dual-luciferase reporter assay was utilized to identify downstream targets of circ-SLC16A1. Transwell migration, wound healing, 5-ethynyl-2′-deoxyuridine incorporation, cell counting, and colony formation assays were conducted to assess the proliferation and migration of NSCLC cells. A mouse tumor xenograft model was employed to determine the roles of circ-SLC16A1 in NSCLC progression and metastasis in vivo. Results The results found that circ-SLC16A1 was upregulated in NSCLC cells and tissues. Downregulation of circ-SLC16A1 inhibited tumor growth by reducing proliferation, lung metastasis, and lymphatic metastasis of NSCLC cells, and arrested the cell cycle in the G1 phase. Also, silencing of circ-SLC16A1 promoted apoptosis of NSCLC cells. The results of bioinformatics analysis and the dual-luciferase reporter assay confirmed that microRNA (miR)-1287-5p and profilin 2 (PFN2) are downstream targets of circ-SLC16A1. PFN2 overexpression or circ-SLC16A1 inhibition restored proliferation and migration of NSCLC cells after silencing of circ-SLC16A1. PFN2 overexpression restored migration and proliferation of NSCLC cells post miR-1287-5p overexpression. Conclusions Collectively, these findings show that miR-1287-5p/PFN2 signaling was associated with downregulation of circ-SLC16A1 and reduced invasion and proliferation of NSCLC cells. So, circ-SLC16A1 is identified as a mediator of multiple pro-oncogenic signaling pathways in NSCLC and can be targeted to suppress tumor progression.

Coastal wetlands are critical for global biodiversity and ecological stability, yet the invasive Spartina alterniflora (S. alterniflora) poses severe threats to these ecosystems. This study evaluates the effectiveness of management efforts targeting S. alterniflora in the Yellow River Delta (YRD) using Zhuhai-1 hyperspectral imagery and the U-Net method. The U-Net model, coupled with the Relief-F algorithm, achieved a superior extraction accuracy (Kappa > 0.9 and overall accuracy of 93%) compared to traditional machine learning methods. From 2019 to 2021, S. alterniflora expanded rapidly, increasing from 4055.06 hm2 to 6105.50 hm2, primarily in tidal flats and water bodies. A clearing project reduced its extent to 5063.62 hm2 by 2022, and by 2023, only 0.55 hm2 remained. These results underscore the effectiveness of Shandong’s management policies but highlight the risk of regrowth due to the species’ resilience. Continuous monitoring and maintenance are essential to prevent its resurgence and ensure wetland restoration. This study offers critical insights into dynamic vegetation monitoring and informs conservation strategies for wetland health.

Abstract The Eastern Himalayan Syntaxis (EHS) serves as a natural laboratory for the study of intense continental collision and lateral extrusion tectonics. By aiming at the intricate tectonic dynamics south and southeast of the EHS, we integrate seismic data from new broadband stations in central Myanmar with permanent stations in southeastern Tibet to establish a high‐resolution 3‐D shear wave velocity model through ambient noise surface wave tomography. Our imaging results reveal distinct differences in crustal seismic velocity structures between the West Burma Block, Chuan‐Dian Block, and the Shan Plateau, highlighting the extent of oblique subduction and restricted crustal extrusion. Notably, two north‐south oriented low‐velocity zones in the mid‐to‐lower crust of southeastern Tibet are mainly confined within the Chuan‐Dian Block and terminate near the Red River Fault, with limited extension into the Shan Plateau.

Mangroves play a pivotal role in the attainment of United Nations Sustainable Development Goals. Leaf equivalent water thickness (EWT) and leaf mass per area (LMA) are vital functional trait parameters for monitoring heath status of mangroves. However, their inherent spectral response characteristics remain unclear, which presents a challenge for high-precision estimating EWT and LMA using remote sensing images. In this study, we attempted to synergistic retrieval of mangrove EWT and LMA using field hyperspectral and satellite data. Specifically, we proposed a novel Fractional-order assisted Spectral angle Analysis (FSA) approach to accurately identify sensitive spectral domains of EWT and LMA for three mangrove species based on in situ full-spectrum hyperspectral (350–2500 nm) data. We constructed a new spectral matching index (SMI) to screen the satellite-based sensitive spectral bands based on the field-based spectral domains, and further verified their feasibility of estimating EWT and LMA using three optical satellite sensors (Sentinel-2A, SDGSAT-1, and OHS-3D). Finally, we explored the effectiveness of combining SAR and thermal infrared (TIR) images with sensitive spectral bands on improving retrieval performance in estimating EWT and LMA, respectively. Results indicated that FSA approach could capture the sensitive spectral domains of EWT (1125–1868 nm) and LMA (1419–1999 nm) for three mangrove species. The SMI could effectively realize the spectral matching between field-based sensitive domains and satellite-based bands, and perform the synergistic retrieval of mangrove EWT (R2 = 0.65) and LMA (R2 = 0.70). Intriguing finding is that the additional TIR bands significantly enhanced the EWT and LMA inversion accuracy (R2 increased by 9.8 %–68.3 %) when compared to SAR images. We confirmed that EWT displayed an inverse trend of LMA with the flooding frequency increasing. Our works provide a scientific basis for protection and sustainable management of mangroves.

Accurately quantifying functional traits across large scales is considered fundamental for the management and conservation of existing mangrove ecosystems. In recent years, hybrid models, which combine radiative transfer model simulations with machine learning regression algorithms (MLRA), have been effectively employed in satellite-based estimations of plant functional traits across diverse ecosystems. Nevertheless, the inevitable data redundancy stemming from heavy-parameterization radiative transfer models restricts the application of the hybrid model. Previous studies have indicated that active learning (AL) strategies can mitigate this redundancy through smart sampling selection criteria. While many studies have attempted to investigate mangrove functional traits using various models, there is limited understanding of the performance of hybrid models coupled with active learning strategies in retrieving the traits. In recent years, Sentinel-2 has become mainstream for retrieving detailed and reliable information across diverse ecosystems. The aim of this study is to utilize a retrieval scheme to extract four mangrove functional traits from Sentinel-2 imagery: leaf area index (LAI), leaf chlorophyll content (Cab), leaf dry matter content (Cm), and leaf equivalent water thickness (Cw). In order to achieve this goal, we systematically evaluated 36 different MLRA-AL models, which were combinations of six MLRAs and six AL strategies. Retrieval results showed that GPR (Gaussian processes regression)-ABD (angle-based diversity) and GPR-PAL (variance-based pool of regressors) yielded the highest accuracies for LAI (R2 = 0.68, NRMSE = 10.488 %) and Cw (R2 = 0.47, NRMSE = 13.868 %), respectively. GPR-EBD (Euclidean distance-based diversity) had the highest accuracies of Cm (R2 = 0.54, NRMSE = 11.695 %) and Cab (R2 = 0.71, NRMSE = 13.764 %). The retrieval models were subsequently applied to produce distribution pattern maps of four mangrove functional traits within a Ramsar site. This study represents the first attempt to utilize AL strategies to enhance the efficiency of traditional hybrid models and map multiple functional traits of mangrove forests. The retrieval scheme and mapping results could significantly contribute to the management of mangrove ecosystems and provide a fundamental data source for future research on the ecological services of mangroves.