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To learn the spatial and temporal distribution of Bt proteins in Bt maize leaves, Bt protein levels of Bt maize leaves and their corresponding non-transgenic lines were detected and analysed by the ELISA method. The results showed that Bt proteins were expressed in the leaves of Bt maize varieties during all periods of their growth, while no such Bt proteins were detected in the leaves of non-transgenic maize varieties. The range of leaf Bt proteins was 1.08∼5.81 µg.g−1 FW, which could effectively protect Bt maizes from the corn borer pest during their growth periods. Furthermore, the younger leaves of Bt maizes had significantly lower levels of Bt proteins than their older leaves. In most periods, Bt protein content of Bt maize leaves under drought stress was lower than that under normal growth conditions, but Bt protein content under nutrition stress was higher than that under normal growth conditions. The results provided a full pattern of the spatial and temporal distribution of Bt proteins in Bt maize leaves.

To effectively evaluate the performance improvement of cement pavement in seasonal frost regions, the typical diseases of cement concrete pavements in seasonal frost regions are proposed through the analysis of measured data, and the influence factors of pavement performance mutation value in seasonal frost regions is determined, the application conditions of the model are obtained by the response surface test method; the road performance improvement model is established by the regression analysis method, and the goodness of fit and significance state of the model were tested, and the validity of the model was verified by comparing with the evaluation results of the existing model. The results show that: broken slabs, staggered platforms, cracks, exposed aggregates, broken corners and potholes are typical diseases of cement concrete pavement in seasonal frost regions; the mutation value of pavement performance is most sensitive to the impact of road damage index, running quality index and anti-skid performance index before pre-maintenance, which under pre-curing conditions. The evaluation effect of the model for improving the performance of cement concrete pavement in seasonal frost regions is good, and the interpretable part of the improvement of pavement performance by the model is 99.2%; the fit of the improved evaluation value and the measured value is 0.991, and the model high fit. The evaluation effect of the proposed model is better than the existing model, and the determination of the model is of great significance to the pre-maintenance of cement concrete pavement.

[Introduction] Optimizing equipment selection is the basis of realizing intensive layout of converter station and an important part of building green converter station. [Method] Based on the model of conventional and typical converter stations,combined with the production capacity of main equipment and the research & development of new equipment of converter stations at home and abroad, this paper analyzed the characteristics of equipment in different distribution device areas. [Result] This paper presents the construction concept of intensive converter station and puts forward some suggestions on distribution device layout in different areas. [Conclusion] This work provides reference for optimizing the design of converter station and building intensive green converter station.

In order to evaluate the damage of cement concrete pavement after the freeze-thaw cycle in the seasonal frozen area, it is determined that the dynamic elastic modulus and flexural tensile strength by analyzing the influence of the freeze-thaw on the concrete performance. The two indexes are most sensitive to the evaluation of the freeze-thaw damage of the pavement. Based on regression analysis method, two freeze-thaw damage models based on two indexes are established, and the goodness of fit and significance state of the model are tested. The applicable conditions of the two models are determined by response surface test method. The validity of the model is verified by comparing the prediction results of the existing model. The results show that when the water cement ratio is 0.45-0.48, the gas content is 1% - 4%, and the freezing temperature is - 15℃ - 25℃. The model based on dynamic elastic modulus index has the best evaluation effect. When the water cement ratio is 0.4-0.46, the gas content is 1-3.5, and the freezing temperature is below - 5℃, the model based on the flexural tensile strength index has the best evaluation effect. The explainable parts of the two models are 99.1% and 99.2% respectively, and the fitting degree of the damage evaluation value and the measured damage value is 0.997 and 0.998 respectively. The model has a good fitting degree. The evaluation effect of the model is better than that of the existing model. The determination of the model is of great significance to the future pavement maintenance work.

[Introduction] To overcome some shortcoming such as labor-intensity and inefficient-inspection in manual inspection, which is commonly adopted in the maintenance of the equipment in a HVDC valve hall, a intelligent monitoring system could be established. For omni-direction supervising as well as no effection on the equipment, layout-principles of infrared thermal imagers are proposed in this paper, based on current application of the infrared intelligent monitoring system in convertor stations. [Method] With analysis of the characteristics of the equipment in valve hall, the type and location of the camera probes was determinated. Then, a final scheme was shaped after the check of electrical distance, block and percision. [Result] An example of the infrared intelligent monitoring system is designed and checked in Dongfang convertor station, and some adjustment in the location and number of the camera probes is made. It is illustrated that an omni-directional monitoring system could be built. [Conclusion] This work provide some guidance for similar projects.

In recent years, Earth system sciences are urgently calling for innovation on improving accuracy, enhancing model intelligence level, scaling up operation, and reducing costs in many subdomains amid the exponentially accumulated datasets and the promising artificial intelligence (AI) revolution in computer science. This paper presents work led by the NASA Earth Science Data Systems Working Groups and ESIP machine learning cluster to give a comprehensive overview of AI in Earth sciences. It holistically introduces the current status, technology, use cases, challenges, and opportunities, and provides all the levels of AI practitioners in geosciences with an overall big picture and to “blow away the fog to get a clearer vision” about the future development of Earth AI. The paper covers all the majorspheres in the Earth system and investigates representative AI research in each domain. Widely used AI algorithms and computing cyberinfrastructure are briefly introduced. The mandatory steps in a typical workflow of specializing AI to solve Earth scientific problems are decomposed and analyzed. Eventually, it concludes with the grand challenges and reveals the opportunities to give some guidance and pre-warnings on allocating resources wisely to achieve the ambitious Earth AI goals in the future.

Simple Summary: Human–wildlife conflict refers to conflicts that arise from the occurrence or behavior of wildlife that poses a threat to humans directly or indirectly. The wild boar, as one of the most widely distributed ungulates in the world, is known to dominate the species in mountain ecosystems in China. Here, we integrated data collected from damage and camera trap surveys to understand the damage status, abundance and density and activity rhythms of wild boar in Zhejiang, Eastern China. The damage distribution, density and activity rhythms provide specific priority management regions and activity intensity peaks for conflict mitigation. We believe that these findings could provide a scientific basis for mitigation management. Human–wildlife conflicts are becoming increasingly common worldwide and are a challenge to biodiversity management. Compared with compensatory management, which often focuses on solving emergency conflicts, mitigation management allows decision-makers to better understand where the damage is distributed, how the species are distributed and when the species conduct their activity. Here, we integrated data collected from 90 districts/counties' damage surveys and 1271 camera traps to understand the damage status, abundance, density and activity rhythms of wild boar (Sus scrofa) in Zhejiang, Eastern China, from January 2019 to August 2023. We found that (1) wild boar–human conflicts were mainly distributed in the northwest and southwest mountainous regions of Zhejiang Province; (2) the total abundance of wild boar was 115,156 ± 24,072 individuals, indicating a growing trend over the past decade and a higher density in the western and southern regions; (3) wild boar exhibited different activity patterns across different damage regions, and the periods around 7:00, 11:00 and 16:00 represented activity peaks for wild boar in seriously damaged regions. The damage distribution, density, distribution and activity rhythms provide specific priority regions and activity intensity peaks for conflict mitigation. We believe that these findings based on the damage, distribution and activity could provide a scientific basis for mitigation management at the county level and enrich the framework of human–wildlife conflict mitigation. [ABSTRACT FROM AUTHOR]

Scientific workflows integrate data and computing interfaces as configurable, semi-automatic graphs to solve a scientific problem. Kepler is such a software system for designing, executing, reusing, evolving, archiving and sharing scientific workflows. Electron tomography (ET) enables high-resolution views of complex cellular structures, such as cytoskeletons, organelles, viruses and chromosomes. Imaging investigations produce large datasets. For instance, in Electron Tomography, the size of a 16 fold image tilt series is about 65 Gigabytes with each projection image including 4096 by 4096 pixels. When we use serial sections or montage technique for large field ET, the dataset will be even larger. For higher resolution images with multiple tilt series, the data size may be in terabyte range. Demands of mass data processing and complex algorithms require the integration of diverse codes into flexible software structures. This paper describes a workflow for Electron Tomography Programs in Kepler (EPiK). This EPiK workflow embeds the tracking process of IMOD, and realizes the main algorithms including filtered backprojection (FBP) from TxBR and iterative reconstruction methods. We have tested the three dimensional (3D) reconstruction process using EPiK on ET data. EPiK can be a potential toolkit for biology researchers with the advantage of logical viewing, easy handling, convenient sharing and future extensibility.

Green spaces have a positive impact on the mood of urban residents. However, previous studies have focused primarily on parks or residential areas, neglecting the influence of green spaces in different socioeconomic locations on public sentiment. This oversight fails to acknowledge that most young individuals are exposed to places beyond their homes and parks throughout the day. Using web crawlers, we collected 105,214 Sina Weibo posts from 14,651 geographical check-in points in Hangzhou, Zhejiang Province. We developed a mixed ordered logistic regression model to quantify the relationship between public sentiment (negative/neutral/positive) and the surrounding green space. The findings are as follows: (1) the correlation between GVI and public sentiment is stronger than that between public sentiment and NDVI; (2) among different socioeconomic regions, residential areas are associated with lower levels of public sentiment, while parks are associated with higher levels; and (3) at a scale of 1000 m, an increase of 1% in GVI significantly improves public sentiment regarding transportation hubs, with a regression coefficient of 0.0333. The relationship between green space and public sentiment is intricate and nuanced, and it is influenced by both public activities and spatiotemporal contexts. Urban green space planners should consider additional factors to enhance the effectiveness of green space in improving public sentiment. [ABSTRACT FROM AUTHOR]

To rescue ischemic myocardium from progressing to myocardial infarction, timely identification of the infarct size and reperfusion is crucial. However, fast and accurate identification, as well as the targeted protection of injured cardiomyocytes following ischemia/reperfusion (I/R) injury, remain significantly challenging. Here, a near infrared heptamethine dye IR‐780 is shown that has the potential to quickly monitor the area at risk following I/R injury by selectively entering the cardiomyocytes of the at‐risk heart tissues. Preconditioning with IR‐780 or timely IR‐780 administration before reperfusion significantly protects the heart from ischemia and oxidative stress‐induced cell death, myocardial remodeling, and heart failure in both rat and pig models. Furthermore, IR‐780 can directly bind to F0F1‐ATP synthase of cardiomyocytes, rapidly decrease the mitochondrial membrane potential, and subsequently slow down the mitochondrial energy metabolism, which induces the mitochondria into a "quiescent state" and results in mitochondrial permeability transition pore inhibition by preventing mitochondrial calcium overload. Collectively, the findings show the feasibility of IR‐780‐based imaging and protection strategy for I/R injury in a preclinical context and indicate that moderate mitochondrial function depression is a mode of action that can be targeted in the development of cardioprotective reagents. [ABSTRACT FROM AUTHOR]

We investigate how cloud retrieval errors due to the three-dimensional (3D) radiative effects affect broadband shortwave (SW) cloud radiative effects (CREs) in shallow cumulus clouds. A framework based on the combination of large eddy simulations (LESs) and radiative transfer (RT) models was developed to simulate both one-dimensional (1D) and 3D radiance, as well as SW broadband fluxes. Results show that the broadband SW fluxes reflected at top of the domain, transmitted at the surface, and absorbed in the atmosphere, computed from the cloud retrievals using 1D RT (F1D∗), can provide reasonable broadband radiative energy estimates in comparison with those derived from the true cloud fields using 1D RT (F1D). The difference between these 1D-RT-simulated fluxes (F1D∗ , F1D) and the benchmark 3D RT simulations computed from the true cloud field (F3D) depends primarily on the horizontal transport of photons in 3D RT, whose characteristics vary with the sun's geometry. When the solar zenith angle (SZA) is 5°, the domain-averaged F1D∗ values are in excellent agreement with the F3D , all within 7 % relative CRE bias. When the SZA is 60°, the CRE differences between calculations from F1D∗ and F3D are determined by how the cloud side-brightening and darkening effects offset each other in the radiance, retrieval, and broadband fluxes. This study suggests that although the cloud property retrievals based on the 1D RT theory may be biased due to the 3D radiative effects, they still provide CRE estimates that are comparable to or better than CREs calculated from the true cloud properties using 1D RT. [ABSTRACT FROM AUTHOR]