Introduction
This research aimed to explore the relationships among teacher self-efficacy, teacher resilience, emotion regulation, and teacher burnout within the context of Chinese English as a ...foreign language (EFL) teachers.
Methods
A sample of 638 Chinese EFL teachers participated in this study. They completed self-report assessments for teacher self-efficacy, teacher resilience, emotion regulation, and teacher burnout. Confirmatory factor analysis was conducted to establish the construct validity of the measurement tools. Subsequently, structural equation modeling was utilized to assess the proposed structural model.
Results
The results of the study revealed significant insights. Teacher self-efficacy and resilience exhibited direct and negative associations with teacher burnout. Additionally, an interesting finding emerged where teacher emotion regulation indirectly affected teacher burnout, mediated by teacher resilience. The analysis supported the suitability of the partial mediation model as the best-fit representation of the relationships.
Discussion
The findings of this study provide valuable implications for EFL teaching programs. The negative connections between teacher self-efficacy, resilience, and burnout highlight the importance of nurturing these factors to mitigate burnout risk. The discovered mediation effect of teacher resilience emphasizes the role of emotion regulation in promoting teachers’ overall well-being. These outcomes collectively contribute to the understanding of teacher dynamics and suggest potential avenues for targeted interventions.
This paper first analyzes the use and expression of line and surface, color, and text as graphic design composition elements. Secondly, it analyzes the relationship between interaction design and ...other disciplines and constructs a dynamic interactive design model for graphic design. Then, the features of color, texture, shape and spatial relationship of the image are extracted by the feature extraction algorithm, and the gesture recognition algorithm is used to determine the operation requested by the user and execute it. Finally, data analysis was conducted on 32 randomly selected students from the design school of University H who applied the dynamic interactive design model. The results show that the dynamic interactive design has the highest rating in terms of smooth operation, with an average score of 6.893, and the lowest rating is in terms of low learning cost, with an average score of 5.087. This shows that the dynamic interactive design model of graphic elements can improve the smoothness of operation, thus improving the dynamic interactive experience of students and providing direction for the development of the field of graphic design.
Piano teaching should not continue to be limited to the mere cultivation of students’ performance skills but should be integrated into curriculum thinking and politics while following the ...characteristics of the profession. This paper conducts piano teaching experiments through deep learning LSTM algorithm and extracts a series of Civic and Political elements from them as a fitting point of piano teaching and curriculum Civic and Political to discuss, using multiple teaching modes to strengthen the cultural transmission of piano courses to improve students’ ideological and moral level and comprehensive quality. The experimental results show that the accuracy of the deep learning LSTM algorithm based on the integration of the deep learning piano course curriculum Civics is stable up to 98.17%, the average false detection rate is stable at 1.97%, the average positive recall rate is stable at 94.7%, and the negative recall rate is 73.2%, and the LSTM algorithm improves the integration degree by 31% compared with the traditional SVMSGD and RF algorithms. It shows that carrying out experiments of deep learning based on deep learning for teaching Civics in college piano courses effectively strengthens the cultural transmission of piano courses and improves students’ ideological and moral level and comprehensive quality.
To date, few studies have investigated the causal relationship between mortality and long-term exposure to a low level of fine particulate matter (PM2.5) concentrations.
We studied 242,320 registered ...deaths in Queensland between January 1, 1998, and December 31, 2013, with satellite-retrieved annual average PM2.5 concentrations to each postcode. A variant of difference-in-differences (DID) approach was used to investigate the association of long-term PM2.5 exposure with total mortality and cause-specific (cardiovascular, respiratory, and non-accidental) mortality. We observed 217,510 non-accidental deaths, 133,661 cardiovascular deaths, and 30,748 respiratory deaths in Queensland during the study period. The annual average PM2.5 concentrations ranged from 1.6 to 9.0 μg/m3, which were well below the current World Health Organization (WHO) annual standard (10 μg/m3). Long-term exposure to PM2.5 was associated with increased total mortality and cause-specific mortality. For each 1 μg/m3 increase in annual PM2.5, we found a 2.02% (95% CI 1.41%-2.63%; p < 0.01) increase in total mortality. Higher effect estimates were observed in Brisbane than those in Queensland for all types of mortality. A major limitation of our study is that the DID design is under the assumption that no predictors other than seasonal temperature exhibit different spatial-temporal variations in relation to PM2.5 exposure. However, if this assumption is violated (e.g., socioeconomic status SES and outdoor physical activities), the DID design is still subject to confounding.
Long-term exposure to PM2.5 was associated with total, non-accidental, cardiovascular, and respiratory mortality in Queensland, Australia, where PM2.5 levels were measured well below the WHO air quality standard.
This study evaluates the effect of climate change on electricity generation, electricity demand, and GHG emissions. For this purpose, using climate scenarios RCPs changes of climatic parameters are ...predicted. Due to the high importance of energy demand in the management of energy generation resources innovation research is related to forecasting electricity demand. The novelty is the use of an Artificial Neural Network optimized to predict the energy demand. To optimize the ANN method, the Improved Pathfinder algorithm has been used. The use of the optimization method in the ANN method provides a model with more precision and fewer errors for the prediction of energy demand. The results showed that due to the weather changes, hydropower generation for the near future under RCP2.6, RCP4.5, and RCP8.5 increases by about 2.765 MW, 1.892 MW, and 1.219 MW and for the far future increases by about 3.430 MW, 2.475 MW, and 1.827 MW. The electricity demand forecasting by The ANN-IPF model for the near and far future will increase compared to the base period of 391.9 MW and 716.65 MW, respectively. Therefore, the gap between the demand the power supply will increase. Using other resources, the difference between demand and power supply will decrease.
•The electricity demand has been stimulated by optimized ANN.•The hydropower generation has been predicted by RCPs scenarios.•The climate change impact on electricity supply and demand has been assessed.•The gap supply-demand electricity and the effect it on GHG emissions has been evaluated.•To reduce the supply-demand gap less -carbon resources should be used.
Single‐atom catalysts (SACs), as homogeneous catalysts, have been widely explored for chemical catalysis. However, few studies focus on the applications of SACs in enzymatic catalysis. Herein, we ...report that a zinc‐based zeolitic‐imidazolate‐framework (ZIF‐8)‐derived carbon nanomaterial containing atomically dispersed zinc atoms can serve as a highly efficient single‐atom peroxidase mimic. To reveal its structure–activity relationship, the structural evolution of the single‐atom nanozyme (SAzyme) was systematically investigated. Furthermore, the coordinatively unsaturated active zinc sites and catalytic mechanism of the SAzyme are disclosed using density functional theory (DFT) calculations. The SAzyme, with high therapeutic effect and biosafety, shows great promises for wound antibacterial applications.
Single‐atom nanozyme: A ZIF‐8‐derived Zn–N–C single‐atom catalyst is an efficient single‐atom nanozyme (SAzyme). The SAzyme, which contains unsaturated Zn–N4 sites, shows excellent peroxidase‐like activity and high antibacterial activity against P. aeruginosa, and it is an effective antibacterial agent for wound treatment.
Dual phototherapy, including photodynamic therapy (PDT) and photothermal therapy (PTT), has shown a great prospect in cancer treatment. However, its therapeutic effect is restricted by the depth of ...light penetration in tissue and tumor hypoxia environment. Herein, inspired by the specific response of nanozymes to the tumor microenvironment (TME), a simple and versatile nanozyme‐mediated synergistic dual phototherapy nanoplatform (denoted as FePc/HNCSs) is constructed using hollow nitrogen‐doped carbon nanospheres (HNCSs) and iron phthalocyanine (FePc). FePc/HNCSs simultaneously exhibit peroxidase (POD)‐ and catalase (CAT)‐like activities, which not only can convert endogenous hydrogen peroxide (H2O2) into highly toxic hydroxyl radicals (•OH) for catalytic therapy, but also decompose H2O2 to oxygen (O2) to enhance O2‐dependent PDT. In addition, their enzyme‐like activities are significantly enhanced under light irradiation. Combining with the excellent photothermal effect, FePc/HNCSs realize a high tumor inhibition rate of 96.3%. This strategy opens a new horizon for exploring a more powerful tumor treatment nanoplatform.
A photoresponsive nanozyme is designed for hypoxic tumor therapy. The composition of the nanostructure is not only simple but also multifunctional, which simultaneously exhibits peroxidase‐like, catalase‐like activities, photodynamic, and photothermal properties. This synergistic catalytic therapy and dual phototherapy mediated by photoresponsive nanozyme show great potential and unique advantages in tumor treatment.
We resurveyed preexisting campaign Global Positioning System (GPS) sites and estimated a highly precise GPS velocity field for the Alaska Peninsula. We use the TDEFNODE software to model the slip ...deficit distribution using the new GPS velocities. We find systematic misfits to the vertical velocities from the optimal model that fits the horizontal velocities well, which cannot be explained by altering the slip distribution, so we use only the horizontal velocities in the study. Locations of three boundaries that mark significant along‐strike change in the locking distribution are identified. The Kodiak segment is strongly locked, the Semidi segment is intermediate, the Shumagin segment is weakly locked, and the Sanak segment is dominantly creeping. We suggest that a change in preexisting plate fabric orientation on the downgoing plate has an important control on the along‐strike variation in the megathrust locking distribution and subduction seismicity.
Plain Language Summary
Understanding controls on slip behavior is a key objective of scientists from many different disciplines across solid earth sciences. Measuring the spatial changes in slip on the subduction plate interface can improve our understanding of factors that govern the size, location, and frequency of great destructive earthquakes. Does slip change abruptly or gradually along the length of the subduction zone? We estimate a new model that represents more precisely changes in slip on the interface between North American plate and Pacific plate beneath the Alaska Peninsula. We show that these changes in slip are abrupt and the locations of the changes correlate with features on the downgoing oceanic plate. The orientation of preexisting weakness on the Pacific plate correlates with the estimated slip variations and changes in the seismicity. In the areas that dominantly creep, the Pacific plate has been faulted extensively as it was bent going over the outer rise, leading to a rougher fault surface and more water being brought down with the subducted plate. In the areas that are mostly locked by friction, the faults in the Pacific plate are oriented nearly perpendicular to the trench and there is minimal faulting at the outer rise.
Key Points
The width of the locked region decreases stepwise from NE to SW along strike
Three sharp boundaries that mark changes in fault coupling are identified
The change in preexisting fabric orientation contributes significantly to the change in fault locking and subduction seismicity
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Here we report a simple, low-cost and environment friendly method, in which Black locust seed dregs and potassium ferrate (K2FeO4) are used as starting raw materials and activation ...agent. The hierarchically porous carbons (BDPC) with high special surface area and abundant mesopores (SBET = 2010.1 m2 g−1 and Vmeso = 1.457 cm3 g−1) are obtained through hydrothermal treatment and chemical activation. The BDPC electrode exhibits excellent electrochemical performances by virtue of unique architecture and heteroatoms pseudocapacitance contribution. In the three-electrode system, the optimized carbon material (BDPC-2) achieves a high specific capacitance of 333 F g−1 at 1 A g−1 and displays the high rate capability (81.1% capacitance retention at 100 A g−1) in 6 M KOH electrolyte. The symmetric supercapacitor based BDPC-2 exhibits energy density as high as 26.2 Wh kg−1 (at a power density of 0.79 kW kg−1) and excellent long-term cycling stability (only 8% decrease after 10,000 cycles) in 6 M KOH.
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