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AbstractThe Karakoram Highway (KKH) is a major road traffic route connecting China to South Asia and the Middle East via Pakistan. Geological hazards occur often in the study area due to the influence of complex geological features, active glaciers, and a changing climate, causing major disruptions to traffic operations. As a result, a geological hazard susceptibility map was created in this study to aid in the prevention and control of highway slope disasters. Through field investigation and map interpretation, 102 geohazards, including landslides, debris flows, and collapses, were observed along the route. The logistic regression method was utilized to generate a predictive model for the susceptibility map considering topography, faults, peak ground acceleration, geology, land cover, rainfall, and drainages. The results imply that the model performs well in terms of prediction. The AUC (area under the receiver operating characteristics (ROC) curve) value is 90.6%. The risk associated with the highway was assessed using the susceptibility map. Some sections of the highway are in high-risk zones, where disasters are more perilous and endanger people and automobiles. This effort will support geohazard protection, management, and safe operation of road traffic.

High-speed centrifugal pump can easily lead to severe pressure pulsation due to complex flow, seriously influencing the stable operation. The slant-cutting suction surface to the blade trailing edge midpoint is proposed to improve the fluid flow and dynamic–static interference at the blade outlet for the high-speed pump. Based on large eddy simulation method, the pressure pulsations in a high-speed centrifugal pump were comparatively analyzed under different blade edge profiles with slant-cutting angles of 15°, 30°, and 45°. The numerical performance curves for an OB high-speed centrifugal pump are basically consistent with the experimental ones. In addition, the heads and efficiencies for MB15, MB30, and MB45 pumps are all higher than those of the OB high-speed centrifugal pump under all working conditions, and the head increases to the maximum of 1.24% when the slant-cutting angle is 15°. The high-intensity pressure pulsation at the blade outlet is closely related to the shedding periodic vortex from the blade pressure surface and flow separation under high-speed conditions. Compared with the OB high-speed centrifugal pump, the pressure intensity is decreased by 3.92% and 4.07% at tongue area for MB15 and MB30 pumps, respectively.

Flat black tea (FBT) has been innovatively developed to alleviate homogenisation competition, but the dynamic changes in aroma components during the process remain unclear. This study employed HS-SPME-GC-MS to analyse the aroma components of tea samples from various processing stages of FBT, and to make a comparative assessment with conventional strip-like Congou black tea (SBT). Additionally, a proteomic analysis was conducted on fresh leaves, withered leaves, and frozen–thawed leaves. Significant changes were observed in the aroma components and proteins during the processing. The results of the multivariate and odour activity value analysis demonstrated that the principal aroma components present during the processing of FBT were linalool, (E)-2-hexen-1-al, methyl salicylate, geraniol, hexanal, benzeneacetaldehyde, (Z)-3-hexenyl butyrate, dimethyl sulphide, 2-methylbutanal, 2-ethylfuran, nonanal, nonanol, 3-methylbutanal, (Z)-3-hexen-1-ol, 2-pentylfuran, linalool oxide I, and β-myrcene. Freezing–thawing and final roasting are the key processing steps for forming the aroma quality of FBT. The final roasting yielded a considerable quantity of pyrazines and pyrroles, resulting in a high-fried aroma, but caused a significant reduction in linalool, geraniol, β-myrcene, and esters, which led to a loss of floral and fruity aromas. The freezing–thawing treatment resulted in an accelerated loss of aroma substances, accompanied by a decrease in the expression level of lipoxygenase and 2-C-methyl-D-erythritol 2,4-cyclodiphosphate synthase. The formation of aroma substances in the linoleic acid metabolic pathway and terpenoid metabolic process was hindered, which had a negative impact on tea aroma. This study elucidates the causes of unsatisfactory aroma quality in tea products made from frozen tea leaves, providing theoretical support for the utilisation of frostbitten tea leaves, and helps us to understand the mechanism of aroma formation in black tea.

AbstractEarthquake-induced landslides represent a significant proportion of seismic hazards in mountainous areas. Numerous slope stability analysis methods exist; however, only a few consider the interactions between pulselike seismic waves and landslides. This study investigates the seismic response characteristics of a homogenous step-like slope to evaluate the acceleration ground motion amplification along the surface. Parametric analysis focusing on the effect of pulselike waves on the slope is conducted using the finite difference modeling code Flac 3 D. Based on the numerical simulation results, pulselike seismic waves greatly influence the acceleration and velocity amplification factor (MPGA & MPGV), with maximum amplification usually obtained at the slope’s crest, where sliding failure initiates. The MPGV of rock slope under pulselike seismic waves is 9.3% higher than near-fault non-pulselike and 16% higher than the far-fault. The displacement for pulselike seismic waves is 20% higher than non-pulselike waves. The dynamic failure analysis presented deep failure for the slope under pulselike seismic wave compared to the non-pulselike. The dynamic failure calculated using Flac 3 D agrees with the results of Newmark-type displacement, with a marginal error between 1 and 8%. The study’s findings can be factored into reinforcing seismic engineering design and probabilistic stability analysis.

The vehicle routing problem (VRP) holds significant applications in logistics and distribution scenarios. This paper presents a hybrid brain storm optimization (BSO) algorithm for solving the dynamic vehicle routing problem with time windows (DVRPTW). The proposed hybrid BSO algorithm effectively addresses the dynamic emergence of new customers and minimizes the number of unserved customers by utilizing the repeated insertion algorithm. Furthermore, the algorithm uses BSO clustering operations to classify vehicle routes and facilitates mutual learning within and between classes through $\lambda $ -interchange. The intra-class similarity expedites solution convergence, while the inter-class difference expands the search space to avoid local optima. Finally, the quality of the solution is enhanced through the application of the 2-opt operation. To evaluate its performance, we compare the proposed algorithm with state-of-the-art algorithms using Lackner’s benchmark. The experimental results demonstrate that our algorithm significantly reduces the number of unserved customers.

Strong earthquakes induce a large number of secondary disasters, such as landslides, which bring serious challenges to post-disaster emergency rescue, and the rapid and accurate assessment of earthquake-induced landslide disasters is crucial for post-earthquake emergency rescue. This research aims to propose an emergency assessment model that is suitable for post-earthquake landslides, specifically targeting the first 72 h after an earthquake for emergency rescue guidance. The model combines remote sensing technology and the Newmark physical mechanics assessment model to form the InSAR Data–Newmark Physical Fusion Driver Model (IDNPM), which comprehensively considers the dynamic deformation of the ground surface and geological features. To validate the predictive performance of the IDNPM, the model is applied to the 5 September 2022 Luding earthquake event and the 8 August 2017 Jiuzhaigou earthquake event. The landslide qualitative evaluation, confusion matrix and Receiver Operating Characteristic (ROC) curve are utilized for quantitative assessment. The results show that the IDNPM can effectively reduce the false negative and false positive errors in landslide prediction by utilizing the SAR deformation information, and to a certain extent, it accounts for the dependence of the Newmark model on the accuracy of empirical formulas and geotechnical parameters. For the Luding earthquake event, the IDNPM shows an accuracy improvement of 10.296% compared to the traditional Newmark model. For the Jiuzhaigou earthquake event, there is also an improvement of 3.152%, with a promising generalization performance. The simplicity and ease of operation in constructing the model are accompanied by high reliability and accuracy. The research findings provide essential references for the development of post-earthquake landslide emergency prediction models and offer robust data support for emergency rescue and recovery efforts in earthquake-stricken areas in the future.

The Dynamic Vehicle Routing Problem With Time Windows (DVRPTW) is an NP-hard problem, which has attracted a lot of attention in the past decades due to its many practical applications in logistics. In order to better describe the actual logistics distribution scenario, this paper studies the DVRPTW based on real road networks and proposes the hybrid BSO-ACO algorithm, which is a combination of Brain Storm Optimization (BSO), Ant Colony Optimization (ACO) and Neighborhood Search (2-opt, relocate, exchange). The algorithm 1) uses ACO to generate new individuals from the same cluster formed by BSO, and increases exploitation by ACO’s pheromone accumulation, 2) harnesses the 2-opt, relocate, and exchange to increase exploration to avoid the algorithm from falling into local optima. We construct a test set by extracting the real road networks in Panyu District, Guangzhou, China and compare the hybrid BSO-ACO algorithm with other algorithms on this test set. The computation experiments show the effectiveness and efficiency of the hybrid BSO-ACO algorithm.

Objective. Based on transcranial magnetic stimulation (TMS) with electroencephalography technology, this study analyzed the rehabilitation mechanism of patients’ motor function reconstruction and nerve remodeling after stroke. It revealed the function of the cerebral cortex network at a deeper level and established a set of prognostic marker evaluation indicators for the reconstruction of motor function after stroke. Methods. Twenty-one patients treated at the Beijing Rehabilitation Hospital of Capital Medical University because of ischemic stroke in the territory supplied by the middle cerebral artery were selected as the experimental group. Neurophysiological evaluation, motor function evaluation, and clinical evaluation were performed 30 and 180 d after the onset of ischemic stroke. In the control group, neurophysiological evaluation was also performed as a reference index to evaluate the changes in cortical patterns after stroke. Results. The brain topographic map showed the changes in energy or power spectral density (PSD) at 1,000 ms after stimulation as compared with before stimulation, but no difference was detected in these patients. The time-frequency analysis showed that when the left primary motor cortex (M1) area was stimulated using TMS, the PSD values of the left and right M1 and posterior occipital cortex areas produced an 8–40 Hz wave band in patients S1–S11. There was no significant energy change in patients S12–S16. Conclusions. For patients with different injury types, degrees of injury, and different onset periods, individualized intervention methods should be adopted. The evaluation methods should be as diverse as possible, and the rehabilitation effects of patients should be assessed from multiple perspectives to avoid the limitations of single factors. Possible mechanism: After brain injury, the nervous system can change its structure and function through different ways and maintain it for a certain period of time. This plasticity change will change with the course of the disease.

Abstract Remarkable spots and lines were clearly observed at the two interfaces of indium-tin-oxide coated Z-cut Fe-doped lithium noibate plates under illumination by milliwatt continuous-wave laser light; this occurred because of the visible surface plasmons (SPs) supported by the promising non-metal plasmonic system. The intriguing observations are here explained via the SP-strengthened nonlinear effect, through consideration of the electrostatic field (which is comparable to the atomic field) and its large gradient; this hints at a promising, highly sensitive plasmonic system. The gigantic nonlinear effect discussed in this paper should be ubiquitously existed in many oxide ferroelectric/semiconductor combinations and is promising for visible plasmonic applications.

Extreme response style (ERS) is prevalent in survey research using rating scales. It may cause biased results in group comparisons. This research conducted two sets of simulation studies to explore the magnitude of the ERS impact on mean comparisons between two independent samples. Data were generated from a multidimensional nominal response model. Study 1 examined the influence of ERS on the estimate of group differences in the variable of interest. The results indicated that ERS led to biased estimates, especially when these groups differed significantly in ERS. The correlation between ERS and the variable of interest also moderated the ERS impact. The results were illustrated with an empirical example. Study 2 investigated the impact of ERS on the type I error and type II error in the independent t -test based on scale scores. When the variable of interest had no true difference between groups, ERS inflated the type I error rate . When the difference existed, ERS inflated the type II error rate . Two groups’ true difference in ERS and the variable of interest, unequal ERS variances, the correlation between ERS and the variable of interest, and the number of items moderated the impact of ERS on type I and II error rates. The implications for practices and further research are discussed.

In natural science education, experiments often lead to the collection of raw data that need to be processed into results by doing calculations. Teaching students how to approach such calculations can be done using digital learning materials that provide guidance. The goal of this study was to investigate students' behaviour regarding the use of guidance while doing scientific multi-step calculations, and to relate this behaviour to learning. Sequential pattern mining was used to (i) identify students' behaviour patterns while doing calculations in an online learning environment, (ii) study the relation between use of guidance and success on first attempt at submitting a calculated value, (iii) study the relation between students' use of guidance and learning gain, and (iv) study the relation between students' use of guidance and prior knowledge. Data showed that all students frequently used the guidance provided in the learning task. Moreover, students who used the option to check their intermediate calculations and students who studied worked examples were more likely to successfully complete the calculation on their first attempt than students who did not use this guidance. Guidance in the form of hints was used frequently. However, using the hints did not result in more success at the first attempt. We did not find a relation between learning gain and use of guidance, but we did find a trend that students with a low prior knowledge used more guidance compared to students with a high prior knowledge. The results of this study imply that providing hints and intermediate calculations is of utmost importance for students to independently complete scientific multi-step calculations.

Background: Learning analytics (LA) research often aggregates learning process data to extract measurements indicating constructs of interest. However, the warranty that such aggregation will produce reliable measurements has not been explicitly examined. The reliability evidence of aggregate measurements has rarely been reported, leaving an implicit assumption that such measurements are free of errors. Objectives: This study addresses these gaps by investigating the psychometric pros and cons of aggregate measurements. Methods: This study proposes a framework for aggregating process data, which includes the conditions where aggregation is appropriate, and a guideline for selecting the proper reliability evidence and the computing procedure. We support and demonstrate the framework by analysing undergraduates' academic procrastination and programming proficiency in an introductory computer science course. Results and Conclusion: Aggregation over a period is acceptable and may improve measurement reliability only if the construct of interest is stable during the period. Otherwise, aggregation may mask meaningful changes in behaviours and should be avoided. While selecting the type of reliability evidence, a critical question is whether process data can be regarded as repeated measurements. Another question is whether the lengths of processes are unequal and individual events are unreliable. If the answer to the second question is no, segmenting each process into a fixed number of bins assists in computing the reliability coefficient. Major Takeaways: The proposed framework can be a general guideline for aggregating process data in LA research. Researchers should check and report the reliability evidence for aggregate measurements before the ensuing interpretation.

Both chemical corrosion and axial compression impose critical influences on the internal microstructure of rock. Meanwhile, chemical corrosion can change a rock’s mineral composition, which in turn affects the physical and mechanical properties of the rock. To investigate the dynamic strength characteristics of white sandstone under the coupling effect of axial load and chemical corrosion, a dynamic and static combined loading test device was adopted for performing cyclic impact tests on white sandstone immersed in chemical solution. The results show that with the increasing number of cycles under the same load, the peak strength of the rock presented a trend of ‘strengthening first and then weakening’. The strength of rock resistance to impact failure reached its maximum when the solution of pH was 7 and axial pressure was 12.6 MPa. Under the same axial pressure, the effect of solution pH on the initial dynamic strength of white sandstone is a normal distribution. Acidic and alkaline environments are harmful to rocks during the initial impact, while neutral environments exert little effect and the pH of the solution influences the particle size of impact crushing particles. In addition, the chemical solution has a significant effect on the deterioration of rock strength during the process of initial impact, and the effect is inconspicuous in the later period.

Response styles, the general tendency to use certain categories of rating scales over others, are a threat to the reliability and validity of self-report measures. The mixed partial credit model, the multidimensional nominal response model, and the item response tree model are three widely used models for measuring extreme and midpoint response styles and correcting their effects. This research aimed to examine and compare their validity by fitting them to empirical data and correlating the content-related factors and the response style-related factors in these models to extraneous criteria. The results showed that the content factors yielded by these models were moderately related to the content criterion and not related to the response style criteria. The response style factors were moderately related to the response style criteria and weakly related to the content criterion. Simultaneous analysis of more than one scale could improve their validity for measuring response styles. These findings indicate that the three models could control and measure extreme and midpoint response styles, though the validity of the mPCM for measuring response styles was not good in some cases. Overall, the multidimensional nominal response model performed slightly better than the other two models.

Objective(s): The study aimed to uncover the underlying mechanism linking wear particles to osteoclast differentiation, and we explored the effect of titanium particles of different sizes on CD147 expression and autophagy in macrophages. Materials and Methods: Effects of titanium particles on CD147 and RANKL mRNA were detected by QPCR; protein level of CD147 and Beclin-1 were detected by Western blot; soluble RANKL were detected by ELISA. To determine the effect of CD147 and autophagy, KG-1a cells were transfected with siRNA-CD147 or treated with autophagy inhibitor CQ (chloroquine), and then co-cultured with different sizes of titanium particles.Results: Our results showed that 0.2-1.2 µm and 1.2-10 µm titanium particles up-regulate CD147 to activate autophagy, which increase the level of soluble RANKL to promote osteoclastogenesis. Suppression of CD147 with siRNA could diminish particle-induced autophagy and soluble RANKL expression. In addition, CQ could dramatically reduce particle-induced soluble RANKL expression. Conclusion: Our findings suggested a possible mechanism underlying wear debris-induced osteolysis and identified CD147 as a potential therapeutic target in aseptic loosening.

Background: The study aimed to analyze aberrantly methylated genes, relevant pathways and transcription factors (TFs) in osteosarcoma (OS) development. Methods: Based on the DNA methylation microarray data GSE36002 that were downloaded from GEO database, the differentially methylated genes in promoter regions were identified between OS and normal samples. Pathway and function enrichment analyses of differentially methylated genes was performed. Subsequently, protein-protein interaction (PPI) network was constructed, followed by identification of cancer-associated differentially methylated genes and significant differentially methylated TFs. Results: A total of 1379 hyper-methylation regions and 169 hypo-methylation regions in promoter regions were identified in OS samples compared to normal samples. The differentially hyper-methylated genes were significantly enriched in Neuroactive ligand-receptor interaction pathway, and Peroxisome proliferator activated receptor (PPAR) signaling pathway. The differentially hypo-methylated genes were significantly enriched in Toll-like receptor signaling pathway. In PPI network, signal transducers and activators of transcription (STAT3) had high degree (degree=21). MAX interactor 1, dimerization protein (MXI1), STAT3 and T-cell acute lymphocytic leukemia 1 (TAL1) were significant TFs enriched with target genes in OS samples. They were found to be cancer-associated and hyper-methylated in OS samples. Conclusion: Neuroactive ligand-receptor interaction, PPAR signaling, Toll-like receptor signaling pathways are implicated in OS. MXI1, STAT3, and TAL1 may be important TFs involved in OS development. Keywords: Differentially methylated gene, Osteosarcoma, Protein-protein interaction, Transcription factor

This study investigated the effects of social-emotional competency on pupils’ academic achievement, academic emotions and attitudes, and interpersonal relationships. Participants were 7106 fourth-grade and fifth-grade students in western China. The results were: (1) social-emotional competency positively predicted pupils’ academic achievement (including reading, mathematics, and science); (2) social-emotional competency predicted pupils’ academic emotions and attitudes, including learning anxiety and interest, and academic emotions and attitudes played a mediating role in the relation between social-emotional competency and academic achievement; and (3) social-emotional competency positively predicted pupils’ interpersonal relationships, including peer relationships and teacher–student relationships, and interpersonal relationships played a mediating role in the relation between social-emotional competency and academic achievement. These findings highlighted the importance of social-emotional competency to child development in western China, where many children might lack their parents’ company.