Exploring the Relationship of Personality and Social Support Types among College Students

This study investigated the relationship between Big Five personality traits and social support types among college students. Data was collected from 189 university students from a research institution in the US. Findings indicated that learners who have Agreeableness and Extraversion personality traits seek for more broadly social support resources in college study and life. Additionally, learners who have Neuroticism traits are negatively associated with all social support resources. It is expected that this study would assist college faculty and student affairs professionals to better understand the differences of personality traits among college students and craft feasible strategies so as to encourage these students to seek sufficient social support resources on their personal development. Keywords: Big Five personality, college students, social support, higher education DOI: 10.7176/JEP/11-31-03 Publication date: November 30th 202

Exploring the Characteristics of Adults’ Online Learning Activities: a Case Study of EdX Online Institute

Online learning has become a prevailing trend among adult learners. Therefore, this study investigated the learning time preference and the relationship between the course completion and learning activities among adult learners based on data from one online learning platform. Results indicate that a periodical fluctuation of participating online course study exists among adult learners. Additionally, the activity of posting on the discussion board is a main learning activity factor that influences their online course completion. It is expected that this study would help online learning system designers, education administrators and instructors to better understand the characteristics of adult learners and their learning activities to provide better accessibility and flexibility in online learning environments for them

Noninvasive Submillimeter-Precision Brain Stimulation by Optically-Driven Focused Ultrasound

High precision neuromodulation is a powerful tool to decipher neurocircuits and treat neurological diseases. Current non-invasive neuromodulation methods offer limited millimeter-level precision. Here, we report an optically-driven focused ultrasound (OFUS) for non-invasive brain stimulation with submillimeter precision. OFUS is generated by a soft optoacoustic pad (SOAP) fabricated through embedding candle soot nanoparticles in a curved polydimethylsiloxane film. SOAP generates a transcranial ultrasound focus at 15 MHz with a lateral resolution of 83 micrometers, which is two orders of magnitude smaller than that of conventional transcranial focused ultrasound (tFUS). Effective OFUS neurostimulation in vitro with a single ultrasound cycle is shown. Submillimeter transcranial stimulation of mouse motor cortex in vivo is demonstrated. An acoustic energy of 0.02 J/cm^2, two orders of magnitude less than that of tFUS, is sufficient for successful OFUS neurostimulation. By delivering a submillimeter focus non-invasively, OFUS opens a new way for neuroscience studies and disease treatments.Comment: 36 pages, 5 main figures, 13 supplementary figure

Electronic structure and direct observation of ferrimagnetism in multiferroic hexagonal YbFeO3

The magnetic interactions between rare-earth and Fe ions in hexagonal rare-earth ferrites (h-RFeO3), may amplify the weak ferromagnetic moment on Fe, making these materials more appealing as multiferroics. To elucidate the interaction strength between the rare-earth and Fe ions as well as the magnetic moment of the rare-earth ions, element-specific magnetic characterization is needed. Using x-ray magnetic circular dichroism, we have studied the ferrimagnetism in h-YbFeO3 by measuring the magnetization of Fe and Yb separately. The results directly show antialignment of magnetization of Yb and Fe ions in h-YbFeO3 at low temperature, with an exchange field on Yb of about 17 kOe. The magnetic moment of Yb is about 1.6μB at low temperature, significantly reduced compared with the 4.5 μB moment of a free Yb3+. In addition, the saturation magnetization of Fe in h-YbFeO3 has a sizable enhancement compared with that in h-LuFeO3. These findings directly demonstrate that ferrimagnetic order exists in h-YbFeO3; they also account for the enhancement of magnetization and the reduction of coercivity in h-YbFeO3 compared with those in h-LuFeO3 at low temperature, suggesting an important role for the rare-earth ions in tuning the multiferroic properties of h-RFeO3

Origins and Effects of Education System Transplantation: A Literature Review

This article reviews the literature on educational transplantation, which discussed three related issues: what is the definition of educational system transplantation, what are the typical models of educational system transplantation and what are the effects of educational system transplantation associated with exporting and receiving countries. The literature suggests that educational system transplantation expands the choices for education reforms and promotes the internal regime innovation for the receiving countries. Empirical cases reflect the educational system transplantation encountered the issues on cultural adaptability and compatibility among different education regimes and highly relied on the cultural context differences and suitable power operations

Hydrological and solute budgets of Lake Qinghai, the largest lake on the Tibetan Plateau

Water level and chemistry of Lake Qinghai are sensitive to climate changes and are important for paleoclimatic implications. An accurate understanding of hydrological and chemical budgets is crucial for quantifying geochemical proxies and carbon cycle. Published results of water budget are firstly reviewed in this paper. Chemical budget and residence time of major dissolved constituents in the lake are estimated using reliable water budget and newly obtained data for seasonal water chemistry. The results indicate that carbonate weathering is the most important riverine process, resulting in dominance of Ca2+ and DIC for river waters and groundwater. Groundwater contribution to major dissolved constituents is relatively small (4.2 ± 0.5%). Wet atmospheric deposition contributes annually 7.4-44.0% soluble flux to the lake, resulting from eolian dust throughout the seasons. Estimates of chemical budget further suggest that (1) the Buha-type water dominates the chemical components of the lake water, (2) Na+, Cl-, Mg2+, and K+ in lake water are enriched owing to their conservative behaviors, and (3) precipitation of authigenic carbonates (low-Mg calcite, aragonite, and dolomite) transits quickly dissolved Ca2+ into the bottom sediments of the lake, resulting in very low Ca2+ in the lake water. Therefore, authigenic carbonates in the sediments hold potential information on the relative contribution of different solute inputs to the lake and the lake chemistry in the past

Wind Speed Forecasts of a Mesoscale Ensemble for Large-Scale Wind Farms in Northern China: Downscaling Effect of Global Model Forecasts

To facilitate wind power integration for the electric power grid operated by the Inner Mongolia Electric Power Corporation—a major electric power grid in China—a high-resolution (of 2.7 km grid intervals) mesoscale ensemble prediction system was developed that forecasts winds for 130 wind farms in the Inner Mongolia Autonomous Region. The ensemble system contains 39 forecasting members that are divided into 3 groups; each group is composed of the NCAR (National Center for Atmospheric Research) real-time four-dimensional data assimilation and forecasting model (RTFDDA) with 13 physical perturbation members, but driven by the forecasts of the GFS (Global Forecast System), GEM (Global Environmental Multiscale Model), and GEOS (Goddard Earth Observing System), respectively. The hub-height wind predictions of these three sub-ensemble groups at selected wind turbines across the region were verified against the hub-height wind measurements. The forecast performance and variations with lead time, wind regimes, and diurnal and regional changes were analyzed. The results show that the GFS group outperformed the other two groups with respect to correlation coefficient and mean absolute error. The GFS group had the most accurate forecasts in ~59% of sites, while the GEOS and GEM groups only performed the best on 34% and 2% of occasions, respectively. The wind forecasts were most accurate for wind speeds ranging from 3 to 12 m/s, but with an overestimation for low speeds and an underestimation for high speeds. The GEOS-driven members obtained the least bias error among the three groups. All members performed rather accurately in daytime, but evidently overestimated the winds during nighttime. The GFS group possessed the fewest diurnal errors, and the bias of the GEM group grew significantly during nighttime. The wind speed forecast errors of all three ensemble members increased with the forecast lead time, with the average absolute error increasing by ~0.3 m/s per day during the first 72 h of forecasts

Wind Speed Forecasts of a Mesoscale Ensemble for Large-Scale Wind Farms in Northern China: Downscaling Effect of Global Model Forecasts

To facilitate wind power integration for the electric power grid operated by the Inner Mongolia Electric Power Corporation—a major electric power grid in China—a high-resolution (of 2.7 km grid intervals) mesoscale ensemble prediction system was developed that forecasts winds for 130 wind farms in the Inner Mongolia Autonomous Region. The ensemble system contains 39 forecasting members that are divided into 3 groups; each group is composed of the NCAR (National Center for Atmospheric Research) real-time four-dimensional data assimilation and forecasting model (RTFDDA) with 13 physical perturbation members, but driven by the forecasts of the GFS (Global Forecast System), GEM (Global Environmental Multiscale Model), and GEOS (Goddard Earth Observing System), respectively. The hub-height wind predictions of these three sub-ensemble groups at selected wind turbines across the region were verified against the hub-height wind measurements. The forecast performance and variations with lead time, wind regimes, and diurnal and regional changes were analyzed. The results show that the GFS group outperformed the other two groups with respect to correlation coefficient and mean absolute error. The GFS group had the most accurate forecasts in ~59% of sites, while the GEOS and GEM groups only performed the best on 34% and 2% of occasions, respectively. The wind forecasts were most accurate for wind speeds ranging from 3 to 12 m/s, but with an overestimation for low speeds and an underestimation for high speeds. The GEOS-driven members obtained the least bias error among the three groups. All members performed rather accurately in daytime, but evidently overestimated the winds during nighttime. The GFS group possessed the fewest diurnal errors, and the bias of the GEM group grew significantly during nighttime. The wind speed forecast errors of all three ensemble members increased with the forecast lead time, with the average absolute error increasing by ~0.3 m/s per day during the first 72 h of forecasts