Understanding the historical perception and value of teacher personalities reveals key educational priorities and societal expectations. This study analyzes the evolution of teachers’ ascribed Big Five personality traits from 1800 to 2019, drawing on millions of English-language books. Word frequency analysis reveals that conscientiousness is the most frequently discussed trait, followed by agreeableness, openness, extraversion, and neuroticism. This pattern underscores society’s focus on whether teachers are responsible. Polarity analysis further indicates a higher prevalence of low neuroticism descriptors (e.g., patient and tolerant) in descriptions of teachers compared to the general population, reinforcing the perception of teachers as stable and dependable. The frequent use of terms like “moral”, “enthusiastic”, and “practical” in describing teachers highlights the positive portrayal of their personalities. However, since the mid-20th century, there has been a notable rise in negative descriptors related to openness (e.g., traditional and conventional), coupled with a decline in positive openness terms. This shift suggests an evolving view of teachers as less receptive to new ideas. These findings offer valuable insights into the historical portrayal and societal values attributed to teacher personalities.
Recent psychological research shown that the places where we live are linked to our personality traits. Geographical aggregation of personalities has been observed in many individualistic nations; notably, the mountainousness is an essential component in understanding regional variances in personality. Could mountainousness therefore also explain the clustering of personality-types in collectivist countries like China? Using a nationwide survey (29,838 participants) in Mainland China, we investigated the relationship between the Big Five personality traits and mountainousness indicators at the provincial level. Multilevel modelling showed significant negative associations between the elevation coefficient of variation (Elevation CV) and the Big Five personality traits, whereas mean elevation (Elevation Mean) and the standard deviation in elevation (Elevation STD) were positively associated with human personalities. Subsequent machine learning analyses showed that, for example, Elevation Mean outperformed other mountainousness indicators regarding correlations with neuroticism, while Elevation CV performed best relative to openness models. Our results mirror some previous findings, such as the positive association between openness and Elevation STD, while also revealing cultural differences, such as the social desirability of people living in China’s mountainous areas.
Seismic quiescence or enhanced phenomena are anomalous changes against the background of normal seismic activity. Preliminary studies have found that earthquakes with a magnitude of ML≥4 often occur at a low occurrence frequency before giant earthquakes in Tibet. This study analyzed the catalog of ML≥4 earthquakes from 2008 to 2022 and examined the anomalous occurrence of ML≥4 earthquakes preceding most ML≥6 earthquakes. When the monthly occurrence frequency of ML≥4 earthquakes was lower than 4 times over six consecutive months, the subsequent occurrence of ML≥6 earthquakes was highly likely as evidenced by observations. The anomalous characteristics of low-intensity activities were analyzed as a medium- and short-term forecasting index for large earthquakes in the Tibetan area.
We report here the longitudinal and shear sound velocities on polycrystalline cerium under hydrostatic pressure across the iso-structural γ-α phase transition up to 4.4 GPa. Comparing with previous methods, the pressure-density relation of Ce has been calculated by integrating with the initial travel time and pressure without any fitting. The pressure correction of the Gruneisen parameter and linear expansion coefficient are taken into account during the integration process. The sound velocities, bulk modulus, shear modulus, Debye temperature, and vibrational entropy are achieved and have been compared with previous results. The bulk modulus of cerium in α phase agrees with the previous results determined by neutron and x-ray diffraction. The Debye temperature above and below the phase transition are and , respectively. The difference of the Debye temperature from respective experiment is found and has been expounded. We consider that the vibrational entropy change per atom of 0.44 k B as the Kondo collapse of 17% volume change, and 0.70 k B as the total change from γ phase to complete α phase.
Consumer financial fraud has become a serious problem because it often causes victims to suffer economic, physical, mental, social, and legal harm. Identifying which individuals are more likely to be scammed may mitigate the threat posed by consumer financial fraud. Based on a two-stage conceptual framework, this study integrated various individual factors in a nationwide survey (36,202 participants) to construct fraud exposure recognition (FER) and fraud victimhood recognition (FVR) models by utilizing a machine learning method. The FER model performed well (f1 = 0.727), and model interpretation indicated that migration status, financial status, urbanicity, and age have good predictive effects on fraud exposure in the Chinese context, whereas the FVR model shows a low predictive effect (f1 = 0.565), reminding us to consider more psychological factors in future work. This research provides an important reference for the analysis of individual differences among people vulnerable to consumer fraud.
Abstract. As one of the intense anthropogenic emission regions across the relatively high latitude (> 40° N) areas on the Earth, Northeast China faces serious problem on regional haze during long winter with half a year. Aerosols in polluted haze in Northeast China are poorly understood compared with the haze in other regions of China such as North China Plain. Here, we for the first time integrated bulk chemical measurements with single particle analysis from transmission electron microscopy (TEM), nanoscale secondary ion mass spectrometer (NanoSIMS), and atomic force microscopy (AFM) to obtain morphology, size, composition, aging process, and sources of aerosol particles collected during two contrasting regional haze events (Haze-I and Haze-II) at an urban site and a mountain site in Northeast China, and further investigated the causes of regional haze formation. Haze-I evolved from moderate (average PM2.5: 76–108 μg/m3) to heavy pollution (151–154 μg/m3), with the dominant PM2.5 component changing from organic matter (OM) (39–45 μg/m3) to secondary inorganic ions (94–101 μg/m3). Similarly, TEM observations showed that S-OM particles elevated from 29 % to 60 % by number at urban site and 64 % to 74 % at mountain site and 75–96 % of Haze-I particles included primary OM. Change of wind direction induced that Haze-I rapidly turned into Haze-II (185–223 μg/m3) with the predominant OM (98–133 μg/m3) and unexpectedly high K+ (3.8 μg/m3). TEM also showed that K-OM particles increased from 4–5 % by number to 50–52 %. Our study revealed a contrasting formation mechanism of these two haze events: Haze-I was induced by accumulation of primary OM emitted from residential coal burning and further deteriorated by secondary aerosol formation via heterogeneous reactions; Haze-II was caused by long-range transport of agricultural biomass burning emissions. Moreover, we found that 75–97 % of haze particles contained tarballs, but only 4–23 % contained black carbon and its concentrations were low at 2.7–4.3 μg/m3. The results highlight that abundant tarballs are important light-absorbing brown carbon in Northeast China during winter haze and further considered in climate models.
'/%3e%3cuse xlink:href='%23a' transform='rotate(23.036 .093 25.536)'/%3e%3cuse xlink:href='%23a' transform='rotate(45.87 1.273 16.18)'/%3e%3cuse xlink:href='%23a' transform='rotate(69.945 .996 12.078)'/%3e%3cuse xlink:href='%23a' transform='rotate(20.66 -19.689 31.932)'/%3e%3c/svg%3e)
