Electrostatic probe diagnosis is the main method of plasma diagnosis. However, the traditional diagnosis theory is affected by many factors, and it is difficult to obtain accurate diagnosis results. ...In this study, a long short-term memory (LSTM) approach is used for plasma probe diagnosis to derive electron density (
) and temperature (
) more accurately and quickly. The LSTM network uses the data collected by Langmuir probes as input to eliminate the influence of the discharge device on the diagnosis that can be applied to a variety of discharge environments and even space ionospheric diagnosis. In the high-vacuum gas discharge environment, the Langmuir probe is used to obtain current-voltage (I-V) characteristic curves under different
and
. A part of the data input network is selected for training, the other part of the data is used as the test set to test the network, and the parameters are adjusted to make the network obtain better prediction results. Two indexes, namely, mean squared error (MSE) and mean absolute percentage error (MAPE), are evaluated to calculate the prediction accuracy. The results show that using LSTM to diagnose plasma can reduce the impact of probe surface contamination on the traditional diagnosis methods and can accurately diagnose the underdense plasma. In addition, compared with
, the
diagnosis result output by LSTM is more accurate.
Ecosystem models have been widely used for obtaining gross primary productivity (GPP) estimations at multiple scales. Leaf area index (LAI) is a critical variable in these models for describing the ...vegetation canopy structure and predicting vegetation-atmosphere interactions. However, the uncertainties in LAI datasets and the effects of their representation on simulated GPP remain unclear, especially over complex terrain. Here, five most popular datasets, namely the Long-term Global Mapping (GLOBMAP) LAI, Global LAnd Surface Satellite (GLASS) LAI, Geoland2 version 1 (GEOV1) LAI, Global Inventory Monitoring and Modeling System (GIMMS) LAI, and Moderate Resolution Imaging Spectroradiometer (MODIS) LAI, were selected to examine the influences of LAI representation on GPP estimations at 95 eddy covariance (EC) sites. The GPP estimations from the Boreal Ecosystem Productivity Simulator (BEPS) model and the Eddy Covariance Light Use Efficiency (EC-LUE) model were evaluated against EC GPP to assess the performances of LAI datasets. Results showed that MODIS LAI had stronger linear correlations with GLASS and GEOV1 than GIMMS and GLOMAP at the study sites. The GPP estimations from GLASS LAI had a better agreement with EC GPP than those from other four LAI datasets at forest sites, while the GPP estimations from GEOVI LAI matched best with EC GPP at grass sites. Additionally, the GPP estimations from GLASS and GEOVI LAI presented better performances than the other three LAI datasets at crop sites. Besides, the results also showed that complex terrain had larger discrepancies of LAI and GPP estimations, and flat terrain presented better performances of LAI datasets in GPP estimations. Moreover, the simulated GPP from BEPS was more sensitive to LAI than those from EC - LUE, suggesting that LAI datasets can also lead to different uncertainties in GPP estimations from different model structures. Our study highlights that the satellite-derived LAI datasets can cause uncertainties in GPP estimations through ecosystem models.
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•Five satellite-derived LAI datasets were compared at 95 EC sites.•LAI discrepancies may led to large discrepancies in GPP estimates.•Complex terrain had larger discrepancies of LAI and GPP estimates than flat terrain.•BEPS model was more sensitive to LAI than EC-LUE model.
•A topographic correction method was proposed to improve mountainous MODIS GPP.•Radiation, temperature, and water heterogeneity are useful for GPP correction.•Improvement of MODIS GPP after ...correction was proved at 11 mountainous sites.•It is essential to incorporate topography into coarse resolution GPP products.
Time-series Moderate Resolution Imaging Spectroradiometer (MODIS) gross primary productivity (GPP) has been served as an effective tool to assess the terrestrial carbon budget for the entire globe since 2000. However, the current MODIS GPP product neglects the surface heterogeneity in the modeling process and is always generated at 500 m or 1 km resolution, which could cause errors to these estimates over mountainous areas. In this work, the MODIS GPP model (MOD17) was applied to obtain 1 km GPP estimates at eleven mountainous sites. Then, a topographic correction method based on three indexes associated with the spatial heterogeneity of received radiation (TCIAPAR), temperature (TCITMIN), and water (TCIVPD) stresses was developed to reduce GPP errors in these MOD17-simulated estimates. Results showed that a closer relationship between tower-based GPP and MOD17-simulated GPP was achieved after applying the proposed topographic correction method, with the determination coefficient (R2) increased from 0.61 to 0.74 and root mean square error (RMSE) reduced from 24.24 to 14.56 gC m−2 8d−1 at all the eleven mountainous sites. As for the effectiveness of each topographic correction index, an obvious improvement of MOD17-simulated GPP was observed after TCIAPAR correction (increasing R2 by 0.09 and decreasing RMSE by 8.75 gC m−2 8d−1), TCITMIN correction (increasing R2 by 0.05 and decreasing RMSE by 7.80 gC m−2 8d−1), and TCIVPD correction (increasing R2 by 0.06 and decreasing RMSE by 7.89 gC m−2 8d−1), indicating that the spatial heterogeneity information of radiation, temperature, and water within coarse pixels is necessary for improving the MODIS GPP over mountainous areas. It is notable that the combination of the TCIAPAR, TCITMIN, and TCIVPD corrections was found to have the largest improvement for MOD17-simulated GPP (increasing R2 by 0.13 and decreasing RMSE by 9.68 gC m−2 8d−1), indicating that the combined consideration of topographic factors in the correction process might achieve a larger improvement. This study highlights the feasibility of incorporating surface topographic characteristics into current coarse resolution GPP products in obtaining large-scale mountain GPP estimates.
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•A transfer learning method for classify Raman spectra was proposed first time.•CNN-1D, Resnet-1D and Inception-1D have improved the accuracy of spectrum classification.•Transfer ...learning can improve the feature extraction capability.
Pesticide detection is of tremendous importance in agriculture, and Raman spectroscopy/Surface-Enhanced Raman Scattering (SERS) has proven extremely effective as a stand-alone method to detect pesticide residues. Machine learning may be able to automate such detection, but conventional algorithms require a complete database of Raman spectra, which is not feasible. To bypass this problem, the present study describes a transfer learning method that improves the algorithm's accuracy and speed to extract features and classify Raman spectra. The transfer learning model described here was developed through the following steps: (1) the classification model was pre-trained using an open-source Raman spectroscopy database; (2) the feature extraction layer was saved after training; and (3) the training model for the Raman spectroscopy database was re-established while using self-tested pesticides and keeping the feature extraction layer unchanged. Three models were evaluated with or without transfer learning: CNN-1D, Resnet-1D, and Inception-1D, and they have improved the accuracy of spectrum classification by 6%, 2%, and 3%, with reduced training time and increased curve smoothness. These results suggest that transfer learning can improve the feature extraction capability and therefore accuracy of Raman spectroscopy models, expanding the range of Raman-based applications where transfer learning model can be used to identify the spectra of different substances.
•Cyanidin-3-O-galactoside potentially prevents obesity and inflammation.•Cyanidin-3-O-galactoside alleviated obesity by promoting AMPK.•Cyanidin-3-O-galactoside inhibited inflammation by regulating ...STAT3 and NF-κB p65.
The potential of cyanidin-3-O-galactoside (C3G) from Aronia melanocarpa in preventing high-fat diet (HFD) rats obesity was investigated. Male Sprague-Dawley (SD) rats were fed with a normal diet or HFD for 8 weeks. After successful modeling, HFD rats were supplemented with either orlistat (30 mg/kg body weight (bw)/day) or C3G (100 and 200 mg/kg bw/day) for 8 weeks. Results showed that supplementation with C3G could inhibit body weight gain and reduce serum lipids, fat accumulation, and Lee’s index in HFD rats. Treatment with C3G significantly decreased the levels of tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), and interleukin-1β (IL-1β) in serum. Moreover, C3G alleviated HFD-induced obesity by promoting phosphorylation of adenosine 5′-monophosphate (AMP)-activated protein kinase (AMPK) and inhibited HFD-induced inflammation by promoting the phosphorylation of signal transducer and activator of transcription 3 (STAT3) and suppressing nuclear factor kappa-B p65 (NF-κB p65) in the nucleus. Thus, the C3G from Aronia melanocarpa could potentially prevent obesity and inflammation in rats fed with high-fat diet.
FeCoCrNiCu is a face-centered cubic (FCC) high entropy alloy (HEA) with good dislocation storage capacity, ductility, and toughness. FeCoCrNiAl is a body-centered cubic (BCC) HEA whose phase is hard ...and brittle with high strength and low toughness. In this study, a FeCoCrNiCu/FeCoCrNiAl composite HEA coating was prepared by laser cladding technology. After preparation, the microstructure and mechanical properties of the composite HEA were evaluated. A new two-phase (FCC + BCC) HEA was generated in situ between FCC and BCC HEA, achieving a good transition from hard to soft. The composite coating has the best wear resistance, the friction coefficient is about 0.3, the wear rate is 4.2 × 10−5 mm3/ N·m, and the wear mechanism is abrasive wear. While maintaining high hardness and good wear resistance, the composite coating has good compression properties. The FeCoCrNiCu cladding layer reduced the energy of the FeCoCrNiAl cladding layer by storing dislocations, which reduced its tendency to crack during compression, thus extending the service life of the coating surface.
•FeCoCrNiCu/FeCoCrNiAlCu/FeCoCrNiAl composite high entropy alloy coating was successfully prepared by laser cladding.•In-situ generation of FeCoCrNiAlCu dual-phase high-entropy alloy.•Gradient distribution of coating hardness.•The composite HEA coating achieved an effective strength-toughness balance.
Abstract Accumulating evidence indicated that HHEX participated in the initiation and development of several cancers, but the potential roles and mechanisms of HHEX in hepatocellular carcinoma (HCC) ...were largely unclear. Cancer stem cells (CSCs) are responsible for cancer progression owing to their stemness characteristics. We reported that HHEX was a novel CSCs target for HCC. We found that HHEX was overexpressed in HCC tissues and high expression of HHEX was associated with poor survival. Subsequently, we found that HHEX promoted HCC cell proliferation, migration, and invasion. Moreover, bioinformatics analysis and experiments verified that HHEX promoted stem cell-like properties in HCC. Mechanistically, ABI2 serving as a co-activator of transcriptional factor HHEX upregulated SLC17A9 to promote HCC cancer stem cell-like properties and tumorigenesis. Collectively, the HHEX-mediated ABI2/SLC17A9 axis contributes to HCC growth and metastasis by maintaining the CSC population, suggesting that HHEX serves as a promising therapeutic target for HCC treatment.
Abstract Tin-based perovskite has been considered as one of the most potential candidates for lead-based perovskite. The solution proceed method was widely utilized in fabricating tin perovskite ...solar cells. So far, all fabrication processes for tin perovskite solar cells involved toxic organic solvents, which is contrary to the development of environmentally friendly perovskite solar cells. In this study, we report for the first time, by using a mixed green solvent N-diethyl formamide and green 1,3-dimethyl-3,4,5,6-Tetrahydro-2 (1H)-pyrimidinone as precursor solvent, and a green solvent dibutyl ether as antisolvent, a high-quality FA 0.75 MA 0.25 SnI 3 film was achieved. The optical band gap of the prepared perovskite layer was 1.36 eV, which was close to the ideal band gap. The green-solution-proceed perovskite films showed reduced defect density. As a consequence, the champion green-solution-proceed photovoltaic device achieved a power conversion efficiency of 4.4%. Moreover, it still maintains 80% of the initial efficiency after 600 h of storage in a nitrogen atmosphere. This work would promote the perovskite solar cells from a ‘new’ technique to a ‘new and green’ technique.
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•The iceberg shape like condenser can efficient collect vapor in hot weather.•The introduction of a TG between photothermal and evaporation layer can decrease heat loss.•Excellent ...durability performance in solar steam desalination.•This ISWG may pave the way for industrial desalination.
Interfacial solar steam generation has emerged as a promising eco-friendly and low-carbon emission technology to address the global water scarcity. So far, the majority of attention is paid to the improvement of the evaporation rate while the efficient vapor collection sector remains broadly unexploited. Herein, an inverted iceberg-inspired solar water generator (ISWG), consisting of a thermoelectric generator coated by a photothermal agent, a bilayer all-fiber nonwoven fabric and a passive cooling vapor condenser, is constructed. Inspired by the shape of an iceberg, the majority of the ISWG system is underneath the bulk water, leaving only the evaporation section floating on the water. This ISWG system not only avoids the vapor condensation induced solar input loss, but also transfers the heat to the surrounding bulk water, resulting in passive cooled and enhanced vapor collection. Moreover, a thermoelectric generator, which utilizes the temperature difference between the photothermal layer and evaporation layer, is sandwiched for thermal conduction in place of the traditional metal plate. The ISWG can achieve a high vapor collection rate of 1.02 kg m-2 h−1 and extra output electricity with a power of 0.47 W m−2 under sunlight with the ambient temperature at about 42 ℃. This work may pave the way for the development of an efficient solar-induced water-electricity co-generation system in tropical islands.