Explore the vast range of titles available.

It is significant for the carbon emission reduction of bogie frame (BF) to establish a standardized carbon footprint accounting method for BF manufacturing and to analyze the carbon emissions of different materials, different production stages, and different functional constituent parts. This study is based on the theory of life cycle assessment (LCA), combined with the carbon emission factor method, to account for the carbon footprint and formulate emission reduction measures for the entire manufacturing process of BF. The results show that the carbon footprint of each BF produced is 3115.02 kgCO 2 eq, of which the raw material consumption stage has the highest carbon emission of 2882.01 kgCO 2 eq, accounting for 92.52% of the carbon emission of the whole process of production and manufacturing. Of all the materials, P355NL consumption produced the largest carbon footprint, 2083.08 kgCO 2 eq. Among the auxiliary materials, the consumption of welding wire produced the highest carbon emissions at 119.10 kgCO 2 eq. Among all the functional constituent parts, the Side Beam Inner Web Plate in the Side Beam Assembly produced the highest carbon emissions at 241.96 kgCO 2 eq. Finally, it is proposed that optimizing the material composition and using clean energy can reduce the carbon emissions in the production process of BF. Accounting for the carbon footprint of urban rail transit BF can provide theoretical support for the green manufacturing of urban rail transit equipment, and can also provide data support for the development of industry standards.

Purpose To investigate the capacity of Superb Microvascular Imaging (SMI) to detect microvascular details and to explore the different SMI features in various focal liver lesions (FLLs) and the correlation between SMI and microvessel density (MVD). Method: Eighty-three liver lesions were enrolled in our study, including 35 hepatocellular carcinomas (HCCs) and 48 non-HCCs. All patients underwent color Doppler flow imaging (CDFI) and SMI examination and were categorized into subgroups according to Adler semiquantitative grading (grade 0–3) or the microvascular morphologic patterns (pattern a-f). The correlation between SMI blood flow signal percentage and MVD was assessed. Results Compared with CDFI, SMI detected more high-level blood flow signals (grade 2–3) and more hypervascular supply patterns (pattern e-f) in HCCs ( p  < 0.05). Furthermore, more hypervascular supply patterns and fewer hypovascular supply patterns were detected in HCC compared with non-HCC ( p  < 0.05). Based on Adler’s grading or microvascular morphologic patterns, the areas under the receiver operating characteristic curve were 0.696 and 0.760 for SMI, 0.583 and 0.563 for CDFI. The modality of “SMI-microvascular morphologic pattern” showed the best diagnostic performance. There was significant correlation between MVD and the SMI blood flow signal percentage (vascular index, VI) in malignant lesions ( r  = 0.675, p  < 0.05). Conclusion SMI was superior to CDFI in detecting microvascular blood flow signals. More hypervascular supply patterns were depicted in HCC than in non-HCC, suggesting a promising diagnostic value for SMI in the differentiation between HCC and non-HCC. Meanwhile, we were the first to demonstrate that SMI blood flow signal percentage (VI) was correlated with MVD in malignant lesions.

We investigated whether leaching fraction (LF) is able to modify the effects of irrigation water salinity (EC iw ) on evapotranspiration (ET). We conducted an experiment with a completely randomized block design using five levels of EC iw and two LFs. Results showed that the electrical conductivity of drainage water (EC dw ) in an LF of 0.29 was considerably higher during the 21–36 days after transplanting (DAT), and considerably lower after 50 DAT than in an LF of 0.17. The hourly, nighttime, daily, cumulative and seasonal ET all decreased considerably as a result of an increase in the EC iw . The daily ET started to be considerably higher in the LF of 0.29 than in the LF of 0.17 from 65 DAT. Compared with the LF of 0.17, the seasonal ET in the LF of 0.29 under various EC iw levels increased by 4.8%–8.7%. The Maas and Hoffman and van Genuchten and Hoffman models both corresponded well with the measured relative seasonal ET and the LF had no marked effects on these model parameters. Collectively, an increase in the level of EC iw always decreased the ET substantially. An increase in the LF increased the ET considerably, but there was a time lag.

Background The modification effect of leaching fraction (LF) on the physiological responses of plants to irrigation water salinity (EC iw ) remains unknown. Here, leaf gas exchange, photosynthetic light–response and CO 2 –response curves, and total carbon (C) and nitrogen (N) accumulation in hot pepper leaves were investigated under three EC iw levels (0.9, 4.7 and 7.0 dS m − 1 ) and two LFs treatments (0.17 and 0.29). Results Leaf stomatal conductance was more sensitive to EC iw than the net photosynthesis rate, leading to higher intrinsic water use efficiency (WUE) in higher EC iw , whereas the LF did not affect the intrinsic WUE. Carbon isotope discrimination was inhibited by EC iw , but was not affected by LF. EC iw reduced the carboxylation efficiency, photosynthetic capacity, photorespiration rate, apparent quantum yield of CO 2 and irradiance–saturated rate of gross photosynthesis; however, LF did not influence any of these responses. Total C and N accumulation in plants leaves was markedly increased with either decreasing EC iw or increasing LF. Conclusions The present study shows that higher EC iw depressed leaf gas exchange, photosynthesis capacity and total C and N accumulation in leaves, but enhanced intrinsic WUE. Somewhat surprisingly, higher LF did not affect the intrinsic WUE but enhanced the total C and N accumulation in leaves.

The middle‐aged male was diagnosed with “acute anterior wall myocardial infarction” based on clinical symptoms, laboratory examination, and coronary angiography (CAG), but his ECG showed no significant change in QRS wave or ST‐T within 6 h of admission. Thus, a perfect explanation with the existing theory is difficult, and only the case is presented here. The middle‐aged male was diagnosed with \"acute anterior wall myocardial infarction\" based on clinical symptoms, laboratory examination, and coronary angiography (CAG), but his ECG showed no significant change in QRS wave or ST‐T within 6 h of admission. Thus, a perfect explanation with the existing theory is difficult, and only the case is presented here.

Soil evaporation (Es) and crop transpiration (Tc) are important components of water balance in cropping systems. Comparing the accurate calculation by crop models of Es and Tc to the measured evaporation and transpiration has significant advances to the optimal configuration of water resource and evaluation of the accuracy of crop models in estimating water consumption. To evaluate the adaptation of APSIM (Agricultural Production Systems simulator) in calculating the Es and Tc in Nanjing, APSIM model parameters, including the meteorological and soil parameters, were measured from a two-year field experiment. The results showed that: (1) The simulated evaporation was basically consistent with the measured Es, and the regulated model can effectively present the field evaporation in the whole maize growth period (R2 = 0.85, D = 0.96, p < 0.001); and (2) The trend of the simulated Tc can present the actual Tc variation, but the accuracy was not as high as the evaporation (R2 = 0.74, D = 0.87, p < 0.001), therefore, the simulation of water balance process by APSIM will be helpful in calculating Es and Tc in a humid area of Nanjing, and its application also could predict the production of maize fields in Nanjing.

【Objective】Accurate estimation of crop evapotranspiration (ETc) is essential for improving irrigation and water resource management. This study aimed to reduce the uncertainty in ETc estimation for winter wheat in the region of Nanjing and improve the efficiency of agricultural water use. 【Method】 Four machine learning models: the Lasso Regression, the Adaptive Boosting (AdaBoost), the Random Forest (RF) and Gradient Boosting Decision Tree (GBDT) were used to calculate ETc using meteorological data measured from 2011 to 2018. Bayesian optimization (BO) was used to fine-tune the model parameters. The calculated results were compared with data measured from lysimeters. Shapley Additive Explanations (SHAP) analysis was used to identify key meteorological factors. A logistic growth model for leaf area index (LAI) based on degree-day and effective accumulated temperature was developed to indirectly estimate ETc. 【Result】 ① The GBDT and RF models outperformed other model, with their R2 values being 0.951 and 0.926, respectively. The GBDT model was most accurate, with a MAE of 0.370 mm/d and RMSE of 0.541 mm/d. ② SHAP analysis showed that LAI, solar radiation (Rs) and net radiation (Rn) were the most influential factors in ETc estimation. ③The logistic-based LAI model enables indirect prediction of ETc using temperature-driven metrics.【Conclusion】The integration of machine learning with Bayesian optimization significantly improves ETc estimation for winter wheat. The GBDT and RF models offer robust alternatives to traditional methods, reducing dependence on costly instrumentation and dense meteorological networks. This scalable method supports data-driven irrigation scheduling and improves sustainable agricultural water management in winter wheat production in the study region.

Accurate estimation of actual evapotranspiration (ET) is critical for understanding hydrothermal cycles and ecosystem functioning in arid regions, where water scarcity governs ecological resilience. To address persistent gaps in ET quantification, this study integrates multi-source remote sensing data, energy balance modeling, and ground-based validation that significantly enhances spatiotemporal ET accuracy in the vulnerable desert steppe ecosystems. The study utilized meteorological data from several national stations and Landsat-8 imagery to process monthly remote sensing images in 2019. The Surface Energy Balance System (SEBS) model, chosen for its ability to estimate ET over large areas, was applied to derive modeled daily ET values, which were validated by a large-weighted lysimeter. It was shown that ET varied seasonally, peaking in July at 6.40 mm/day, and reaching a minimum value in winter with 1.83 mm/day in December. ET was significantly higher in southern regions compared to central and northern areas. SEBS-derived ET showed strong agreement with lysimeter measurements, with a mean relative error of 4.30%, which also consistently outperformed MOD16A2 ET products in accuracy. This spatial heterogeneity was driven by greater vegetation coverage and enhanced precipitation in the southeast. The steppe ET showed a strong positive correlation with surface temperatures and vegetation density. Moreover, the precipitation gradients and land use were primary controllers of spatial ET patterns. The process-based SEBS frameworks demonstrate dual functionality as resource-optimized computational platforms while enabling multi-scale quantification of ET spatiotemporal heterogeneity; it was therefore a reliable tool for ecohydrological assessments in an arid steppe, providing critical insights for water resource management and drought monitoring.

Background Data on the clinical characteristics, electrocardiogram (ECG) findings and outcomes of patients with acute myocardial infarction (AMI) due to total unprotected left main (ULM) artery occlusion is limited. Methods Between 2009 and 2021, 44 patients with AMI due to total ULM occlusion underwent primary percutaneous coronary intervention (PCI) at our institution. The ECG, collateral circulation, clinical and procedural characteristics, and in-hospital mortality were retrospectively evaluated. Results Twenty five patients presented with shock and 18 patients had in-hospital mortality. Nineteen patients presented with ST-segment elevation myocardial infarction (STEMI), while 25 presented with non-ST-segment elevation myocardial infarction (NSTEMI). ST-segment elevation (STE) in I and STEMI were associated with the absence of collateral circulation, while STE in aVR was associated with its presence. In the NSTEMI group, patients with STE in both aVR and aVL showed more collateral filling of the left anterior descending coronary artery (LAD) territory, while patients with STE in aVR showed more collateral filling of the LAD and the left circumflex artery territory. Compared with total ULM occlusion, patients with partial ULM obstruction presented with more STE in aVR, less STE in aVR and aVL, and less STEMI. Shock, post-PCI TIMI 0–2 flow, non-STE in aVR, STEMI, and STE in I predicted in-hospital mortality. STEMI and the absence of collateral flow were significantly associated with shock. Conclusions STE in the precordial leads predicted the absence of collateral circulation while STE in aVR and STE in both aVR and aVL predicted different collateral filling territories in ULM occlusion. STE in I, non-STE in aVR, and STEMI predicted in-hospital mortality in these patients.

The high quality and efficient production of greenhouse vegetation depend on micrometeorology environmental adjusting such as system warming and illumination supplement. In order to improve the quantity, quality, and efficiency of greenhouse vegetation, it is necessary to figure out the relationship between the crop growth conditions and environmental meteorological factors, which could give constructive suggestions for precise control of the greenhouse environment and reduce the running costs. The parameters from the color information of the plant canopy reflect the internal physiological conditions, thus, the RGB model has been widely used in the color analysis of digital pictures of leaves. We take photographs of Begonia Fimbristipula Hance (BFH) growing in the greenhouse at a fixed time every day and measure the meteorological factors. The results showed that the color scale for the single leaf, single plant, and the populated canopy of the BFH photographs all have skewed cumulative distribution histograms. The color gradation skewness-distribution (CGSD) parameters of the RGB model were increased from 4 to 20 after the skewness analysis, which greatly expanded the canopy leaf color information and could simultaneously describe the depth and distribution characteristics of the canopy color. The 20 CGSD parameters were sensitive to the micrometeorology factors, especially to the radiation and temperature accumulation. The multiple regression models of mean, median, mode, and kurtosis parameters to microclimate factors were established, and the spatial models of skewness parameters were optimized. The models can well explain the response of canopy color to microclimate factors and can be used to monitor the variation of plant canopy color under different micrometeorology.