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IntroductionThe impact of a growth mindset and resilience on boarding middle school adolescents has received increasing attention from scholars. Nevertheless, research on how to intervene in the growth mindset, and resilience of boarding school adolescents needs further verification. The purpose of this study is to explore whether positive education intervention based on the PERMA (positive emotions, engagement, relationships, meaning, and achievement) model will help Chinese boarding middle school adolescents improve their growth mindset and resilience.MethodsThis study is a randomized controlled trial with both a control group and an experimental group, including pre-tests and post-tests. The study subjects were 167 adolescents, including 84 (n1 = 84) adolescents in the experimental group and 83 (n2 = 83) adolescents in the control group.ResultsThe results showed that adolescents under the intervention condition reported significantly improved growth mindset and resilience.DiscussionCompared with the control group, resilience significantly increased. These findings indicate that positive educational intervention is a promising approach to improve boarding adolescents ‘growth mindset and resilience.

Expressways in mountainous plateau areas exhibit complex driving conditions and harsh climatic characteristics that continuously impact vehicle carbon emissions throughout their entire lifecycle and determine the carbon emission levels of expressways during the operational period. To study the carbon emission characteristics of expressways in the western Sichuan Plateau mountainous area, a coupling simulation analysis method combining CarSim/TruckSim simulation software and the Motor Vehicle Emissions Simulator (MOVES) was employed to analyze the spatial distribution characteristics of vehicle-specific power (VSP). This analysis was based on the alignment data and operational environment of the Wenchuan‒Barkam Expressway in the mountainous area of the western Sichuan Plateau. A conversion formula was established to calculate the cumulative VSP per second and total carbon emissions of each unit. Statistical analysis was conducted on the distribution of carbon emissions equivalent per kilometer across the different alignment units. Distribution ranges of carbon emissions equivalent per kilometer for light-duty vehicles (LDVs) and heavy-duty vehicles (HDVs) at each alignment unit were 60‒240 g and 100‒1600 g, respectively. The grey relational analysis method was used to quantify the relationship between the carbon emissions equivalent per kilometer of alignment units, circular curves radius, and average grade. Based on the vertical variations in climatic changes with altitude in the mountainous plateau area, a comparative analysis was performed on the trends in the effects of altitude, season, and vehicle starting frequency on carbon emissions. Frequent vehicle starts significantly impacted carbon emissions, and this impact was significantly higher in winter than in summer. Carbon emissions equivalent of the LDV and HDV starting twice on average in summer were approximately 1.09- and 1.04-times higher, respectively, than that when vehicles were started 0.5 times; whereas, in winter, they were 1.17- and 1.07-times higher, respectively. [ABSTRACT FROM AUTHOR]

Enhancing the intelligence of Tiger nut harvesting equipment with the advancement of agricultural machinery is imperative. Mismatches between excavation feed rate and conveying-separating capacities hinder the efficiency of Tiger nut harvesters. A visualized Tiger nut harvesting platform was designed to address this, incorporating parameters like conveying speed, torque, vibration frequency, and excavation depth. The platform features a mechanical execution part and an automatic control system with speed, torque, frequency, and depth control modules. Mechanical design analysis defined control parameters and methods for each module. An adaptive B-PID controller was proposed for trajectory tracking, combining backstepping and PID. A control model accounting for motion damping and error compensation was derived. Simulink simulations compared B-PID with backstepping controllers, showing B-PID's robustness and effective trajectory tracking. Actual experiments assessed mechanical-control coordination using relative error metrics. The results showed that the maximum relative error of rotation speed was 3.8%, the maximum relative error of frequency was 3.67%, and the maximum relative error of excavation depth was 1.5%. Correction models for excavation depth and excitation frequency parameters were established. This study offers a theoretical framework to advance the intelligent design of tiger nut harvesting machinery. [ABSTRACT FROM AUTHOR]

The purpose of this study is to achieve the quantitative detection of recombinant type III collagen (rh-COL-III) in dressings with complex matrix. First of all, the marker peptide (GEAGIPGVPGAK) of rhCOL-III was identified with HPLC-MS/MS. Then, a qualitative and quantitative method based on marker peptides was established and validated. In order to obtain higher sensitivity, a pretreatment method of liquid, gel, and ointment dressings was optimized. The reference material for quantification was combined using rhCOL-III and blank matrix of each dressing. The results indicated that the relative standard deviation (RSD) of the quantitative method was 2.77%, and the RSD of intraday and interday precision was 2.76% and 2.31%, respectively. The spiking recovery rate was between 80% and 90%. The optimal pretreatment method was Tris-HCl solvent replacement. The optimal trypsin concentration for the dressing solution was 20 μg in 500 μL. The method of preparing standard substances with a blank matrix can effectively eliminate the influence of the matrix effect on the quantitative results. The average spiking recovery rates of 50 μg/mL, 100 μg/mL, and 200 μg/mL in three different dressings ranged from 80% to 120%. The quantitative detection of limit (LOD) of rhCOL-III was 1 ng/mL, 2 ng/g, and 1 ng/g in liquid, ointment, and gel dressings. [ABSTRACT FROM AUTHOR]

IntroductionIncreasing the hardiness of students is a crucial objective in higher education. Universities and colleges have created a variety of interventions to improve students' overall hardiness.MethodsIn terms of the effects of such interventions, empirical research has shown inconclusive results. This meta-analysis applies 12 effect sizes from 12 independent empirical studies, with a total of 640 participants, to assess the overall impact of interventions on students' hardiness and to test for moderators, in light of the contradictory findings in prior work. The current meta-analysis calculates the standardized mean differences (SMD) of pre-post interventions. The level of study heterogeneity, represented by I2, was interpreted as small (I2 ≤ 25%), moderate (25% < I2 ≤ 50%), substantial (50% < I2 ≤ 75%), or considerable (I2 > 75%). Twelve studies met the inclusion criteria and were included in the meta-analysis.ResultsThe results show that the interventions had a significant positive overall effect on students' hardiness (g = 0.998, k = 12) and show significant heterogeneity among effect sizes. Among the interventions, cognitive-based intervention yielded the largest mean effect size (g = 2.015, k = 5). Furthermore, moderator analyses suggest that the effects of the interventions on students' hardiness are moderated by respondent type, culture, intervention type, research design, years, and duration of intervention.DiscussionWe conclude that interventions that promote students' hardiness are officious. Despite the low homogeneity of the results and limitations of this meta-analysis (e.g., a small number of included studies) which might have influenced the findings, the large fail-safe N suggests that these findings are robust. The study examined potential causes of heterogeneity and emphasized the importance of further research in this area.

A detection and evaluation system containing a two-level index of structural integrity and bearing capacity was constructed based on ground-penetrating radar (GPR) and a falling weight deflector (FWD). This system was constructed to solve problems with the detection, evaluation, and structural and material design of asphalt rehabilitation for the prevention and control of asphalt reflection cracks in asphalt overlaying composite Portland cement pavement. Based on the detected data from the GPR and FWD, the reasonable and recommended thickness range of the stress-absorbing layer was determined by the finite element method, and the optimization design of an anti-reflective crack structure is proposed. Furthermore, a material design and engineering application of the stress-absorbing layer was carried out. The results show that an additional 10 cm layer of repaved asphalt can reduce temperature stress by 64.1%, reduce fatigue stress by 29.3% at the cement slab bottom, and extend the service life by 23.1 years. The reasonable thickness of the stress-absorbing layer ranges from 1.6 cm to 2.0 cm, and the recommended structural combination design is a 4 cm SMA-13 upper layer, a 4 cm AC-16 lower layer, and a 2 cm stress-absorbing layer overlaying existing asphalt overlay. The impact toughness of the designed stress-absorbing layer is 1.05 times and 1.44 times that of the other stress-absorbing layer and the AC-16 asphalt mixture, respectively, which have been successfully used for more than 5 years. The recommended design rehabilitation has good engineering application. The uniformity of the stress-absorbing layer can reach 63%, and an anti-reflective crack effect is expected. The results of this study provide design methodology and experience for composite pavement repaving. [ABSTRACT FROM AUTHOR]

In response to energy consumption and traffic efficiency reduction caused by intersection congestion, a global speed planning that considered both ecological speed and green wave speed was conducted under the vehicle–road–cloud integration framework. After establishing an instantaneous energy consumption model for pure electric vehicles, a radial basis neural network model was used to estimate the queue length of traffic flow, and an isolated-intersection-based eco-approach and departure (I-EAD) plan was proposed based on a valid traffic signal light model. A two-stage optimization multi-intersections-based eco-approach and departure (M-EAD) strategy with multiple objectives and constraints was proposed to solve the optimal green light window and the optimal speed trajectory. The results of the SUMO/Matlab/Simulink/Python joint simulation platform show that the M-EAD strategy reduces the average travel energy consumption by 16.65% and 8.31%, and the average travel time by 26.33% and 12.53%, respectively, compared to the intelligent driver model (IDM) and I-EAD strategy. The simulation results of the typical traffic scenarios and random traffic scenarios indicate that the speed optimization strategies in this study have good optimization effects on energy conservation and traffic efficiency. [ABSTRACT FROM AUTHOR]