In the era of persistent globalization, climate governance has emerged as a prominent concern within both the theoretical community and government departments of diverse nations. Of particular interest in academic research is the adverse effect of climate shocks on the global economy. This paper employs average temperature as a surrogate indicator for climate shocks and examines the influence of temperature fluctuations on inflation levels using a balanced panel dataset from 1995 to 2021. The findings indicate a positive association between temperature change and inflation within the country, which remains consistent even after subjecting the analysis to multiple robustness tests. Furthermore, accounting for heterogeneity reveals variations in the magnitude of response of inflation levels to temperature fluctuations. Regarding the analysis of underlying mechanisms, the study underscores the significance of energy demand as a pivotal pathway influencing inflationary pressures at the national level. Lastly, by incorporating GDP per capita as a threshold, the research reveals a nonlinear relationship between temperature change and inflation levels.

Soy protein isolate (SPI) based materials are abundant, biocompatible, renewable, and biodegradable. In order to improve the tensile strength (TS) of SPI films, we prepared a novel composite film modified with microcrystalline cellulose (MCC) and metal nanoclusters (NCs) in this research. The effects of the modification of MCC on the properties of SPI-Cu NCs and Zn NCs films were investigated. Attenuated total reflectance-Fourier transformed infrared spectroscopy analyses and X-ray diffraction patterns characterized the strong interactions and reduction of the crystalline structure of the composite films. Scanning electron microscope showed the enhanced cross-linked and entangled structure of modified films. Compared with untreated SPI film, the tensile strength of the SPI-MCC-Cu and SPI-MCC-Zn films increased from 2.91 MPa to 13.95 and 6.52 MPa, respectively. Moreover, the results also indicated their favorable water resistance with higher water contact angle. Meanwhile, the composite films exhibited increased initial degradation temperatures, demonstrating their higher thermostability. The results suggested that MCC could effectively improve the performance of SPI-NCs films, which would provide a novel preparation method for environmentally friendly SPI-based films in the applications of packaging materials.

Extracting railway tracks is crucial for creating electronic railway maps. Traditional methods require significant manual labor and resources, while existing neural networks have limitations in efficiency and precision. To address these challenges, a railway track extraction method using an improved DeepLabV3+ model is proposed, which incorporates several key enhancements. Firstly, the encoder part of the method utilizes the lightweight network MobileNetV3 as the backbone extraction network for DeepLabV3+. Secondly, the decoder part adopts the lightweight universal upsampling operator CARAFE for upsampling. Lastly, to address any potential extraction errors, morphological algorithms are applied to optimize the extraction results. Additionally, a dedicated railway track segmentation dataset is created to train and evaluate the proposed method. The experimental results demonstrate that the model achieves impressive performance on the railway track segmentation dataset and DeepGlobe dataset. The MIoU scores are 88.93% and 84.72%, with Recall values of 89.02% and 86.96%. Moreover, the overall accuracy stands at 97.69% and 94.84%. The algorithm's operation time is about 5% lower in comparison to the original network. Furthermore, the morphological algorithm effectively eliminates errors like holes and spots. These findings indicate the model's accuracy, efficiency, and the enhancement brought by the morphological algorithm in error elimination.

Diethyldithiocarbamate (DDTC) has been employed in the sulfide ore flotation process, due to its excellent collection performance. Herein, we investigated the interfacial adsorption behavior of DDTC on four mineral phases of high-sulfur residue — sulfur, pyrite, sphalerite and lead sulfate. The adsorption behavior — adsorption structure and energy and electron localization function cross section — of DDTC and H2O were explored using density function theory calculation. The result was helpful to construct a co-adsorption model of DDTC and H2O, which was validated by the pure minerals flotation operation and the characterization of fourier transform infrared spectra. The co-adsorption model indicated that the DDTC adsorption on the sulfur, sphalerite and lead sulfate was weak with physical bonding, while its adsorption on the pyrite was strong with chemical bonding. Practical bench-scale operation of high-sulfur residue flotation was performed, whose result was different from that obtained from the pure mineral flotation. To explain the difference, our developed model predictions and the mineral fugacity pattern analysis on the high-sulfur residue flotation were synergistically used. Overall, this work first proposed the co-adsorption model of DDTC and H2O and provided important insights into the interfacial adsorption in the high-sulfur residue flotation.