Search

This study presents a dynamic multi-factor correlation analysis method designed to predict provincial carbon dioxide emissions (CDE) within China's Bohai Rim region, including Tianjin, Hebei, Shandong, and Liaoning. By employing the sliding window technique, dynamic correlation curves are computed between various influencing factors and CDE at different time intervals, thereby facilitating the identification of key feature attributes. A novel metric, the Consistency Index of Influencing Factors (CIIF), is introduced to evaluate the consistency of these factors across regions. Furthermore, the Accurate Predictive Capability Indicator (APCI) is defined to measure the impact of different feature categories on the prediction accuracy. The findings reveal that models relying on a single influencing factor exhibit limited accuracy, whereas combining multiple factors with diverse correlation features significantly improves the prediction accuracy. This study introduces a refined analytical framework and a comprehensive indicator system for CDE prediction. It enhances the understanding of the complex factors that influence CDE and provides a scientific rationale for implementing effective emission reduction strategies. [ABSTRACT FROM AUTHOR]

Among the various remote sensing technologies that have been applied to monitor oil spills on the sea surface, passive ultraviolet (UV) imaging is a controversial one that has raised some disputes in the community of oil spill remote sensing. As a result, the research and applications of oil spill detection using passive UV imaging have not been as developed as other methods. In order to clarify some existing questions on oil spill detection using passive UV remote sensing technology, this paper discusses the needs of thin oil film detection, examines the feasibility of thin oil film detection using passive UV imaging through field experiments under controlled conditions and validates it with the UV imagery derived from the airborne visible/infrared imaging spectrometer (AVIRIS) observation of the Deepwater Horizon oil spill. Two types of fully automatic models are designed to extract the thin oil films on the water surface: (1) a binary classification model based on an adaptive threshold; (2) an unsupervised image segmentation model based on image clustering and greyscale histogram analysis. The two models are tested on the UV imagery obtained through both field experiments and AVIRIS observations. The results indicate that the binary classification model can extract the thin oil films with reasonable accuracy under stable imaging conditions, while the unsupervised image clustering model can robustly detect the thin oil films at the cost of higher computational complexity. These results infer that passive UV imaging is an effective way to detect thin oil films and could be applied to provide early warning at the beginning stage of oil spills and reduce further damage. It may also be applied as a supplementary method for oil spill detection to achieve comprehensive oil spill monitoring. [ABSTRACT FROM AUTHOR]

Summary: Sugar efflux from host plants is essential for pathogen survival and proliferation. Sugar transporter‐mediated redistribution of host sugar contributes to the outcomes of plant–pathogen interactions. However, few studies have focused on how sugar translocation is strategically manipulated during host colonization.To elucidate this question, the wheat sugar transport protein (STP) TaSTP3 responding to Puccinia striiformis f. sp. tritici (Pst) infection was characterized for sugar transport properties in Saccharomyces cerevisiae and its potential role during Pst infection by RNA interference and overexpression in wheat. In addition, the transcription factors regulating TaSTP3 expression were further determined.The results showed that TaSTP3 is localized to the plasma membrane and functions as a sugar transporter of hexose and sucrose. TaSTP3 confers enhanced wheat susceptibility to Pst, and overexpression of TaSTP3 resulted in increased sucrose accumulation and transcriptional suppression of defense‐related genes. Furthermore, TaWRKY19, TaWRKY61 and TaWRKY82 were identified as positive transcriptional regulators of TaSTP3 expression.Our findings reveal that the Pst‐induced sugar transporter TaSTP3 is transcriptionally activated by TaWRKY19/61/82 and facilitates wheat susceptibility to stripe rust possibly through elevated sucrose concentration, and suggest TaSTP3 as a strong target for engineering wheat resistance to stripe rust. [ABSTRACT FROM AUTHOR]