Inference of the optimal probability distribution model for geotechnical parameters by using Weibull and NID distributions

To obtain the optimal probability distribution models of geotechnical parameters, the goodness of fit of the normal information diffusion (NID) distribution and Weibull distribution were investigated and compared for actual engineering samples and Monte Carlo (MC) simulated samples. Two datasets from actual engineering parameters (the strength of a rock mass and the average wind speed) were used to test the fitting abilities of these two distributions. The results show that the parameters of the NID distribution are easily estimated, the Kolmogorov-Smirnov (K-S) test results of the NID distribution are smaller than those of the Weibull distribution, and the NID distribution curves can perfectly reflect the stochastic volatility of geotechnical parameters with small sample sizes. The sample size effects on the fitting accuracy of the NID distribution and Weibull distribution were also investigated in this paper. Eight simulated samples with different sample sizes, namely, 15, 20, 30, 50, 100, 200, 500, and 1000, were produced by using the MC method based on two known Weibull distributions. The results show that with an increase in the sample size, the K-S test results of the NID distribution gradually decrease and tend to converge, while the chi-square test results of the NID distribution remain low and are always lower than those of the Weibull distribution. The cumulative probability values of the NID distribution are larger than those of the Weibull distribution and are always equal to 1.0000. Finally, the comparison of the fitting accuracy between the NID distribution and normalized Weibull distribution was also analyzed

Relationship Between Shyness and Generalized Pathological Internet Use Among Chinese School Students: The Serial Mediating Roles of Loneliness, Depression, and Self-Esteem

The present study aimed to explore the mediating effects of loneliness, depression, and self-esteem on the association between shyness and generalized pathological Internet use (GPIU). A total of 5215 school students completed questionnaires regarding shyness, loneliness, depression, self-esteem, and GPIU (aged 11–23 years old, M = 16.19, SD = 3.10). The self-reported scores for GPIU, shyness, loneliness, depression, and self-esteem were tested in students from elementary schools to universities. The results of a variance analysis indicated that senior high school students had the greatest prevalence of GPIU of all the study stages. With the study stages resolved, the results of a structural equation model revealed that: (a) shyness positively predicted GPIU; (b) shyness/loneliness/depression predicted GPIU through self-esteem; (c) shyness predicted GPIU through loneliness/depression → self-esteem; and (d) shyness predicted GPIU through loneliness → depression → self-esteem. In conclusion, these results provided significant implications for preventing or reducing GPIU in Chinese school students

Shyness and Learning Adjustment in Senior High School Students: Mediating Roles of Goal Orientation and Academic Help Seeking

Learning maladjustment is a common phenomenon in the context of examination-oriented education system in china, especially among high school students who experience intense pressure when preparing for the national college entrance examination. Previous literature suggests that shyness may negatively affect ones’ cognition, emotion, and behavioral performance and lead to academic and social maladjustment. Therefore, learning adjustment among shy high school students is a critical and practical point of inquiry. With a sample of 677 Chinese senior high school students, this study aims to assess the association between shyness and learning adjustment and related mechanisms of goal orientation (i.e., mastery-approach goals, mastery-avoid goals, performance-approach goals, and performance-avoid goals) and academic help seeking (i.e., instrumental help seeking from teacher, instrumental help seeking from classmate, executive help seeking, and avoidance of help seeking). Self-report measures were adopted to collect information on: demographic characteristics, the level of shyness, goal orientation, academic help seeking, and learning adjustment. Results indicated that shyness was negatively correlated with learning adjustment, and this association was mediated by the dimensions of goal orientation and dimensions of academic help seeking. Specifically, shyness not only predicted learning adjustment through mastery-approach goals, and instrumental help seeking (teachers) but also predicted learning adjustment through the multiple mediating effects of the dimensions of goal orientation and the dimensions of academic help seeking (i.e., mastery-approach goals and instrumental help seeking from teachers, mastery-approach goals and executive help seeking, mastery-avoid goals and instrumental help seeking from classmates, mastery-avoid goals and executive help seeking, and performance-avoid goals and executive help seeking). Identifying these mediators further enables us to work out effective measures to promote shy high school students’ learning adjustment

Textile Waste Fiber Regeneration via a Green Chemistry Approach: A Molecular Strategy for Sustainable Fashion

From Wiley via Jisc Publications RouterHistory: received 2021-07-06, rev-recd 2021-08-15, pub-electronic 2021-09-24, pub-print 2021-12-02Article version: VoRPublication status: PublishedFunder: EPSRC; Id: http://dx.doi.org/10.13039/501100000266; Grant(s): EP/R00661X/1, EP/P025021/1, EP/P025498/1Abstract: Fast fashion, as a continuously growing part of the textile industry, is widely criticized for its excessive resource use and high generation of textiles. To reduce its environmental impacts, numerous efforts are focused on finding sustainable and eco‐friendly approaches to textile recycling. However, waste textiles and fibers are still mainly disposed of in landfills or by incineration after their service life and thereby pollute the natural environment, as there is still no effective strategy to separate natural fibers from chemical fibers. Herein, a green chemistry strategy is developed for the separation and regeneration of waste textiles at the molecular level. Cellulose/wool keratin composite fibers and multicomponent fibers are regenerated from waste textiles via a green chemical process. The strategy attempts to reduce the large amount of waste textiles generated by the fast‐developing fashion industry and provide a new source of fibers, which can also address the fossil fuel reserve shortages caused by chemical fiber industries and global food shortages caused by natural fiber production

The Loading Rate Effect on the Fracture Toughness of Marble Using Semicircular Bend Specimens

A series of dynamic fracture experiments on semicircular bend (SCB) marble specimens were conducted to characterize the loading rate effect using the INSTRON testing machine and the modified SHPB testing system. The fracture toughness of the marble specimens was measured from a low loading rate to a high loading rate (10-3~106 MPa·m1/2s-1). The results show that the fracture toughness will increase with the loading rate. Since the fracture toughness at a magnitude of 10-3 MPa·m1/2s-1 is regarded as the static fracture toughness, the specific value of DIFf (the dynamic increase factor of fracture toughness) can be obtained at the other loading magnitudes from dynamic fracture tests. To describe the variation in DIFf from low to high loading rates, a new continuous model of DIFf was put forward to express the quantitative relation between the loading rate and rock dynamic fracture toughness. It is shown that the new DIFf model can accurately describe the loading rate effect on the dynamic fracture testing data for rock materials

A Heuristic Projection Pursuit Method Based on a Connection Cloud Model and Set Pair Analysis for Evaluation of Slope Stability

Determining the projection direction vector (PDV) is essential to the projection pursuit evaluation method for high-dimensional problems under multiple uncertainties. Although the PP method using a cloud model can facilitate interpretation of the fuzziness and randomness of the PDV, it ignores the asymmetry of the PDV and the fact that indicators are actually distributed over finite intervals; it quickly falls into premature defects. Therefore, a novel PP evaluation method based on the connection cloud model (CCM) is discussed to remedy these drawbacks. In this approach, adaptive numerical characteristics of the CCM are adopted to represent the randomness and fuzziness of the candidate PDV and evaluation indicators. Meanwhile, to avoid complex computing and to accelerate the convergence speed of the optimization procedure, an improved fruit fly optimization algorithm (FOA) is set up to find the rational PDV. Alternatively, candidate PDVs are mutated based on the mechanism “pick the best of the best” using set pair analysis (SPA) and chaos theory. Furthermore, the applicability and reliability are discussed based on an illustrative example of slope stability evaluation and comparisons with the neural network method and the PP evaluation method based on the other FOAs and the genetic algorithm. Results indicate that the proposed method with simpler code and quicker convergence speed has good global ergodicity and local searching capabilities, and can better explore the structure of high-dimensional data with multiple uncertainties and asymmetry of the PDV relative to other methods

Experimental Study on Energy Evolution and Storage Performances of Rock Material under Uniaxial Cyclic Compression

To investigate the energy evolution and storage performances of rock under uniaxial cyclic compression, a series of uniaxial cyclic loading and unloading compression tests were conducted on Green sandstone and Yueyang granite. Two methods for calculating the total input energy of the specimen under each cycle were proposed. One is based on the actual stress-strain curve of the specimen (ASC method); the other is based on the stress-strain envelope curve during the loading process (SEC method). The experimental results show that, for those two methods, the total input energy, elastic energy, and dissipated energy of the specimen show a quadratic function increasing trend with the increase of stress levels. Besides, the elastic energy increases linearly with the increase of total input energy for both methods, which confirms that the linear energy storage law is also applicable to rock materials under uniaxial cyclic loading and unloading compression conditions. Moreover, the uniaxial compression energy storage coefficient calculated by the SEC method is highly close to that obtained based on the single cycle loading and unloading test, which indicates that the uniaxial compression energy storage coefficient of rock can also be calculated by multiple cyclic loading and unloading test. In conclusion, the linear energy storage law is a basic physical property of rock materials, and the uniaxial compression energy storage coefficient is a physical index reflecting the energy storage capacity of rock materials

THE COMBUSTION PERFORMANCE OF MEDIUM DENSITY FIBERBOARD TREATED WITH FIRE RETARDANT MICROSPHERES

Fire retardant particles (guanylurea phosphate and boric acid) with a morphological characteristic of large crystal or fine microsphere, were respectively applied to wood fibers to make medium density fiberboard (MDF). The effects of particle size of the fire retardant on the combustion performance of the resulting MDF samples were determined using a thermogravimetric (TG) analyzer and cone calorimeter (CONE). The scanning electron microscopy and laser particle size analysis showed that the microspheric particles of fire retardant had a mean size of approximately 20 µm, which was smaller than the crystal (260 um). Incorporation of the fire retardant either in the crystal or microsphere shape reduced the weight loss of the resulting MDF, as evidenced by the TG analysis and the CONE test; the release rate and total amount of both the heat and smoke were apparently inhibited as compared to the untreated MDF samples. Treatments caused an increase in both the ignition time and charring ratio of the MDF. Compared with the fire retardant crystals, the fine microspheric particles exhibited greater ability in inhibiting the release of heat and smoke through the combustion processes

Catalytic Conversion of Bio-Oil to Oxygen-Containing Fuels by Acid-Catalyzed Reaction with Olefins and Alcohols over Silica Sulfuric Acid

Crude bio-oil from pine chip fast pyrolysis was upgraded with olefins (1-octene, cyclohexene, 1,7-octadiene, and 2,4,4-trimethylpentene) plus 1-butanol (iso-butanol, t-butanol and ethanol) at 120 °C using a silica sulfuric acid (SSA) catalyst that possesses a good catalytic activity and stability. Gas chromatography-mass spectrometry (GC-MS), Fourier transform infrared spectroscopy (FT-IR) and proton nuclear magnetic resonance (1H-NMR) analysis showed that upgrading sharply increased ester content and decreased the amounts of levoglucosan, phenols, polyhydric alcohols and carboxylic acids. Upgrading lowered acidity (pH value rose from 2.5 to >3.5), removed the unpleasant odor and increased hydrocarbon solubility. Water content dramatically decreased from 37.2% to about 7.0% and the heating value increased from 12.6 MJ·kg−1 to about 31.9 MJ·kg−1. This work has proved that bio-oil upgrading with a primary olefin plus 1-butanol is a feasible route where all the original heating value of the bio-oil plus the added olefin and alcohol are present in the resulting fuel