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High-resolution data with nearly global coverage from Sentinel-2 mission open a new era for crop growth monitoring and yield estimation from remote sensing. The objective of this study is to demonstrate the potential of using Sentinel-2 biophysical data combined with an ecosystem modeling approach for estimation of cotton yield in the southern United States (US). The Boreal Ecosystems Productivity Simulator (BEPS) ecosystem model was used to simulate the cotton gross primary production (GPP) over three Sentinel-2 tiles located in Mississippi, Georgia, and Texas in 2017. Leaf area index (LAI) derived from Sentinel-2 measurements and hourly meteorological data from Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) reanalysis were used to drive the ecosystem model. The simulated GPP values at 20-m grid spacing were aggregated to the county level (17 counties in total) and compared to the cotton lint yield estimates at the county level which are available from National Agricultural Statistics Service in the United States Department of Agriculture. The results of the comparison show that the BEPS-simulated cotton GPP explains 85% of variation in cotton yield. Our study suggests that the integration of Sentinel-2 LAI time series into the ecosystem model results in reliable estimates of cotton yield.

Net primary productivity (NPP) is a key flux in the terrestrial ecosystem carbon balance, as it summarizes the autotrophic input into the system. Forest NPP varies predictably with stand age, and quantitative information on the NPP‐age relationship for different regions and forest types is therefore fundamentally important for forest carbon cycle modeling. We used four terms to calculate NPP: annual accumulation of live biomass, annual mortality of aboveground and belowground biomass, foliage turnover to soil, and fine root turnover in soil. For U.S. forests the first two terms can be reliably estimated from the Forest Inventory and Analysis (FIA) data. Although the last two terms make up more than 50% of total NPP, direct estimates of these fluxes are highly uncertain due to limited availability of empirical relationships between aboveground biomass and foliage or fine root biomass. To resolve this problem, we developed a new approach using maps of leaf area index (LAI) and forest age at 1 km resolution to derive LAI‐age relationships for 18 major forest type groups in the USA. These relationships were then used to derive foliage turnover estimates using species‐specific trait data for leaf specific area and longevity. These turnover estimates were also used to derive the fine root turnover based on reliable relationships between fine root and foliage turnover. This combination of FIA data, remote sensing, and plant trait information allows for the first empirical and reliable NPP‐age relationships for different forest types in the USA. The relationships show a general temporal pattern of rapid increase in NPP in the young ages of forest type groups, peak growth in the middle ages, and slow decline in the mature ages. The predicted patterns are influenced by climate conditions and can be affected by forest management. These relationships were further generalized to three major forest biomes for use by continental‐scale carbon cycle models in conjunction with remotely sensed land cover types. Key Points Eighteen NPP‐age relationships derived for U.S. forests Combination of FIA data, remote sensing, and plant trait information Useful for analysis of management and climate effects on the forest carbon cycle

BackgroundMyocardial infarction (MI) caused by severe coronary artery disease has high incidence and mortality rates, making its prevention and treatment a central and challenging aspect of clinical work for cardiovascular practitioners. Recently, researchers have turned their attention to a novel mechanism of cell death caused by Cu2+, cuproptosis.MethodsThis study integrated data from three MI-related bulk datasets downloaded from the Gene Expression Omnibus (GEO) database, and identified 16 differentially expressed genes (DEGs) related to cuproptosis by taking intersection of the 6378 DEGs obtained by differential analysis with 49 cuproptosis-related genes. Four hub genes, Dbt, Dlat, Ube2d1 and Ube2d3, were screened out through random forest analysis and Lasso analysis. In the disease group, Dbt, Dlat, and Ube2d1 showed low expression, while Ube2d3 exhibited high expression.ResultsFocusing on Ube2d3 for subsequent functional studies, we confirmed its high expression in the MI group through qRT-PCR and Western Blot detection after successful construction of a MI mouse model by left anterior descending (LAD) coronary artery ligation, and further clarified the correlation of cuproptosis with MI development by detecting the levels of cuproptosis-related proteins. Moreover, through in vitro experiments, Ube2d3 was confirmed to be highly expressed in oxygen-glucose deprivation (OGD)-treated cardiomyocytes AC16. In order to further clarify the role of Ube2d3, we knocked down Ube2d3 expression in OGD-treated AC16 cells, and confirmed Ube2d3’s promoting role in the hypoxia damage of AC16 cells by inducing cuproptosis, as evidenced by the detection of MTT, TUNEL, LDH release and cuproptosis-related proteins.ConclusionIn summary, our findings indicate that Ube2d3 regulates cuproptosis to affect the progression of MI.

Microwave plasma can improve the performance of ignition and combustion, as well as reduce pollutant emissions. By designing a novel microwave feeding device, the combustor can be used as a cavity resonator to generate microwave plasma and improve the performance of ignition and combustion. In order to feed the energy of microwave into the combustor as much as possible, and effectively adapt to the change in resonance frequency of combustor during ignition and combustion, the combustor was designed and manufactured by optimizing the size of slot antenna and setting the tuning screws, according to the simulation results of HFSS software (version: 2019 R 3). The relationship between the size, position of metal tip in the combustor and the discharge voltage was studied using HFSS software, as well as the interaction between ignition kernel, flame and microwave. The resonant characteristics of combustor and the discharge of microwave-assisted igniter were subsequently studied via experiments. The results show that the combustor as microwave cavity resonator has a wider resonance curve and can adapt to the change in resonance frequency during ignition and combustion. It is also indicated that microwave can enhance the discharge development of igniter and increase the discharge size. Based on this, the electric and magnetic field effects of microwave are decoupled.

Carbon-based magnetic metal composites derived from metal–organic frameworks (MOFs) are promising materials for the preparation of broadband microwave absorbers. In this work, the leaf-like co-doped porous carbon/carbon nanotube heterostructure was obtained using ZIF-L@ZIF-67 as precursor. The number of carbon nanotubes can be controlled by varying the amount of ZIF-67, thus regulating the dielectric constant of the sample. An optimum reflection loss of −42.2 dB is attained when ZIF-67 is added at 2 mmol. An effective absorption bandwidth (EAB) of 4.8 GHz is achieved with a thickness of 2.2 mm and a filler weight of 12%. The excellent microwave absorption (MA) ability is generated from the mesopore structure, uniform heterogeneous interfaces, and high conduction loss. The work offers useful guidelines to devise and prepare such nanostructured materials for MA materials.

In this paper, we propose a new method to quantitatively evaluate the quality of the carrier phase observation signals of the BeiDou Navigation Satellite System (BDS) during weak and moderate geomagnetic storms. We take a moderate geomagnetic storm that occurred on 12 May 2021 during the 25th solar cycle as an example. The results show that the newly defined PAS (Percentage of Affected Satellites) index shows significant anomaly changes during the moderate geomagnetic storm. Its variation trend has good correlations with the geomagnetic storm Kp index and Dst index. The anomaly stations are mainly distributed in the equatorial region and auroral region in the northern and southern hemispheres. The proposed PAS index has a good indication for both BDS2 and BDS3 satellites. We further validated this index by calculating the Precise Point Position (PPP) positioning error. We found that the anomaly period of PAS has strong consistency with the abnormal period of PPP positioning accuracy. This study could provide methodological support for the evaluation of the signal quality and analysis of positioning accuracy for the BeiDou satellite navigation system under different space weather conditions.

Lichen mapping is vital for caribou management plans and sustainable land conservation. Previous studies have used random forest, dense neural network, and convolutional neural network models for mapping lichen coverage. However, to date, it is not clear how these models rank in this task. In this study, these machine learning models were evaluated on their ability to predict lichen percent coverage in Sentinel-2 imagery in Québec and Labrador, Canada. The models were trained on 10-m resolution lichen coverage (%) maps created from 20 drone surveys collected in July 2019 and 2022. The dense neural network achieved a higher accuracy than the other two, with a reported mean absolute error of 5.2% and an R 2 of 0.76. By comparison, the random forest model returned a mean absolute error of 5.5% (R 2 : 0.74) and the convolutional neural network had a mean absolute error of 5.3% (R 2 : 0.74). A regional lichen map was created using the trained dense neural network and a Sentinel-2 imagery mosaic. There was greater uncertainty on land covers that the model was not exposed to in training, such as mines and deep lakes. While the dense neural network requires more computational effort to train than a random forest model, the 5.9% performance gain in the test pixel comparison renders it the most suitable for lichen mapping. This study represents progress toward determining the appropriate methodology for generating accurate lichen maps from satellite imagery for caribou conservation and sustainable land management.

Background Anterior cervical discectomy and fusion (ACDF) is a common surgical procedure for treating cervical spine diseases, but its anterior approach can lead to complications such as dysphagia and carotid artery injury due to the large incision. However, performing ACDF under a percutaneous endoscopic approach can effectively mitigate these issues. Considering the need for smaller-sized cages in endoscopic procedures, this study explores the feasibility of using small-sized cages for percutaneous endoscopic ACDF surgery. Methods The finite element method is used in this paper to construct cervical spine surgical models with three different sizes of cages implanted, studying the impact of size on cervical biomechanical performance. The dimensions of the cages remain constant in length and height, with a length of 14 mm and a height of 6 mm, and widths of 7 mm, 10 mm, and 14 mm, respectively. Results In a complete fusion state, the range of motion of the surgery level decreased, while adjacent segments showed a compensatory increase in range of motion. Intervertebral disc pressure increased in adjacent discs during flexion and extension. Facet joint pressure in the operated segments generally decreased across all conditions compared to the intact model, but in non-surgical segments exhibited varied compensatory increases under different conditions. Smaller cages led to increased von Mises stress on the cage and endplates, with stress distribution varying by motion condition. Conclusion The results show that, using a 10 mm wide polyetheretherketone cage in complete fusion does not significantly affect postoperative vertebral stability or adjacent segment degeneration risk. Additionally, the risk of subsidence is relatively low, making it a suitable cage option for percutaneous endoscopic ACDF surgery.

Background The bolting and flowering processes are crucial for the yield of stem vegetables and require sugar support. Sugar is synthesized through photosynthesis in the leaves and transported to the stems via transmembrane transport. Brassica campestris (flowering Chinese cabbage) is a unique vegetable that does not require vernalization for flowering and has a distinct flowering regulation mechanism. “Sugars Will Eventually be Exported Transporters” (SWEET), a relatively newly identified group of sugar transporters, play vital roles in plant development. However, the role of B. campestris SWEET ( BcSWEET ) genes in the growth and development of flowering Chinese cabbage remains to be elucidated. Results In this study, 32 BcSWEET genes were identified, which are unevenly distributed across nine chromosomes and classified into four groups based on their homology with Arabidopsis . Significant differences were observed in the physicochemical properties, motif composition, and gene structure of the BcSWEET gene family. However, all BcSWEET proteins are predicted to be localized in the cell membrane. Prediction of transmembrane regions showed that all members contained the MtN3/saliva domain. The BcSWEET promoter regions contain different cis-regulatory elements involved in developmental and hormonal regulation, stress responses, and light-responsive regulation. Expression pattern analysis of the 32 BcSWEET genes revealed that most are associated with reproductive growth in different tissues, with the majority being upregulated in petals and flower buds. BcSWEET1-2 has been confirmed to be localized in the cell membrane and to function as a hexose transporter. Overexpression of BcSWEET1-2 in Arabidopsis promotes stem carbohydrate accumulation, upregulates flowering gene expression, enhances Arabidopsis stem elongation, and advances flowering time. Conclusions This study systematically identified the BcSWEET gene family in flowering Chinese cabbage and characterized its physicochemical properties, evolutionary relationships, and expression patterns. Further analysis demonstrated that some BcSWEET gene members may play crucial roles in flowering regulation. These findings provide theoretical guidance for further research on the role of SWEET-induced sugar accumulation in flower development in flowering Chinese cabbage.

Energetic binders are a research hot-spot, and much emphasis has been placed on their mechanical properties. In this study, propargyl-terminated ethylene oxide-tetrahydrofuran copolymer (PTPET) was synthesized. Then, PTPET and low-molecular-weight ester-terminated glycidyl azide polymer (GAP) were reacted by the click reaction without using catalysts to obtain a polyether polytriazole elastomer. Through tensile tests, where R = 0.5, the tensile strength reached 0.332 MPa, with an elongation at break of 897.1%. Swelling tests were used to measure the cross-linked network and showed that the cross-linked network regularity was reduced as R increased. The same conclusions were confirmed by dynamic mechanical analysis (DMA). In DMA curves, Tg was around −70 to −65 °C, and a small amount of crystallization appeared at between −50 and −30 °C, because locally ordered structures were also present in random copolymers, thereby forming localized crystals. Their thermal performance was tested by Differential Scanning Calorimeter (DSC) and Thermal Gravimetric Analyzer (TG), and the main mass loss occurred at around 350 to 450 °C, which meant that they were stable. In conclusion, the polyether polytriazole elastomer can be used as a binder in a composite propellant.