Changes In Distribution Research Articles

Crack-tip cleavage/dislocation emission competition behaviors/mechanisms in magnesium: ALEFM prediction and atomic simulation

Structural properties and reliability of materials can be improved by increasing fracture toughness. At the atomic scale, the fracture is a material separation process, and the fracture toughness of materials is associated with the atomic-scale crack-tip behaviors/mechanisms. The crack-tip behaviors are relevant to the energy state of atoms in the system. Atomic thermal oscillation increases with increasing temperature, which may affect/alter the crack tip behaviors. This work is the first to investigate the temperature-dependent crack-tip cleavage/dislocation emitting competition in magnesium (Mg) using anisotropic linear elastic fracture mechanics theory, Density Functional Theory (DFT), and atomic simulation. Crack-tip behaviors are examined using a specially designed ‘K-field’ loads model. DFT calculations show that a single crystal system with lower entropy and higher Gibbs free energy implies stronger interatomic bonding that favors a higher KIc. Changes in the stress distribution initiate a brittle-ductile transition in crack-tip behavior. The ductile crack tip can be blunted by continuous crack-tip dislocations nucleation/slip, and the evolution of the ductile crack-tip geometry from sharp to semicircular structure significantly decreases the stress concentration at the crack tip. A new criterion of the crack-tip force vector is established, which reasonably explains the geometrical evolution of ductile crack tip where the angle θ between the crack plane and the slip plane is 0∘<θ<90∘ and θ=90∘. This work expands the atomic-scale brittle/ductile crack-tip behaviors/mechanisms of Mg, which provides a reference for crack-tip behavior analysis in engineering research.

Study on the Diffusion Characteristics of Polymer Grouting Materials Applied for Crack Filling in Underground Mines Based on Numerical Simulation and Experimental Methods.

Polymer grouting materials are increasingly used in the filling of mine fissures. Unlike conventional inorganic grouting materials, the self-expansion of polymers adds complexity to their diffusion process within the crack. The objective of this research was to examine how polymer grouting material spreads in cracks at ambient temperatures and pressure. The investigation involved conducting grouting tests and performing numerical fluid simulation calculations using the finite-volume method in the computational fluid dynamics software, ANSYS FLUENT 2022 R1. The fluid volume approach was employed to determine the boundary between fluid and air and to ascertain the variation patterns of density in the slurry and the fracture system. This study applied the principles of fluid mechanics to investigate the patterns of variation in the physical characteristics of polymer grouting materials, including their density, pressure, flow velocity, and movement distance, during the diffusion process. The results indicated that the density of the polymer grouting material decreased exponentially over time throughout the diffusion process. With the increase in the grouting's volume, the grout's pressure and the permeable distance of the grout increased. The slurry's pressure near the grouting hole exceeded the other points' pressure. The physical parameters of the slurry were numerically simulated by ANSYS FLUENT 2022 R1 software, and the results were compared with the experimental data. After comparing the numerical simulation results with the test data, it was clear that the numerical simulation method was superior in accurately predicting the distribution pattern of each parameter of the polymer slurry during diffusion. The grouting volume, pressure distribution, and real-time change in the position of the flow of slurry could be efficiently determined through numerical calculation and simulated grouting tests. This work can offer valuable information for designing polymer grouting materials used in underground mine fissures.

Carbon metabolism modelling and regulation in Beijing

Land use and cover change leads to significant increases in urban carbon emissions. Considering the insufficiency of spatially fine-grained management in previous carbon emission studies, this study integrated top-down and bottom-up methods to simulate urban carbon metabolism. Metabolic actors were allocated to grids based on land use and POI data and then attributed to districts. Results indicated that from 2000 to 2018, Beijing's Carbon Imbalance Index increased by 55.81% in 2010 and declined by 12.46%. Carbon emission dominated the changes in the Carbon Imbalance Index, with the Production and Supply of Electric Power actors consistently accounting for over 25.96%, while the contribution of Urban and Transportation actors reached 20.11% and 27.74% in 2018, respectively. The metabolic actors exhibited a gradient distribution pattern from southeast to northwest. Artificial actors' carbon emissions decreased from the center to the periphery and spread along the road network, with the High-High cluster in the southeast mainly contributed by Manufacturing (22.33%) and the Production and Supply of Electric Power (20.16%) actors. Spatial distribution changes of Natural actors mainly occurred in Daxing and Chaoyang districts, whose absorption area extended by 45% and 37.26%, respectively, contributing to an increase in carbon absorption by 2.47 and 0.15 times. The Semi-natural actor exhibited net carbon emissions, with the High-High cluster in the southeast zone contributing 60.96% of emissions in 2000. We also categorized Beijing into four Areas based on the relationship between carbon emission and absorption. Targeted policy recommendations were formulated for different districts and metabolic actors.

Demonstration of a novel jaw crusher design at a lab scale

ABSTRACT A novel jaw crusher was designed, constructed and tested at a lab scale. Differences from a conventional jaw crusher include a swing plate that is supported at the outlet, rather than the inlet, wear plates with a corrugation pattern that are designed to break the ore in bending rather than compression, and a trapezoidal wear plate shape to allow for swelling of broken ore. The crusher was tested using an ore sample that was mainly composed of feldspar. The performance of the crusher was evaluated by measuring changes in the size distribution of the ore and the corresponding electrical energy consumed, as a function of ore feed rate. The results indicated that the crusher product size distribution was narrower than that of the feed and independent of ore feed rate, with relatively little generation of fines, demonstrating that the crusher performed as designed in terms of ore breakage mechanism. Though calculated breakage efficiencies suggest that the crusher may be more energy efficient than a conventional jaw crusher, the use of an undersized crusher motor and possible deficiencies in the design of the transmission mechanism, prevent any concrete conclusions from being drawn.

Resilience evaluation and spatio-temporal evolution analysis of China's science and technology financial ecosystem

ABSTRACT This paper discusses the resilience of science and technology (sci-tech) financial ecosystem. It constructs an evaluation system from four dimensions: resistance, adaptability, recovery and innovation. The data are from 29 provinces in China from 2010 to 2020. It is evaluated using entropy weights–TOPSIS and dynamic evaluation model. The spatial evolution law is revealed by spatial autocorrelation analysis. The results show that: (1) The overall resilience level of sci-tech financial ecosystem is not high. Its evolution and development are generally in a relatively stable state. It has significant regional heterogeneity, showing a distribution pattern of ‘high east and low west’. (2) It has significant spatial positive correlation. The structure of the sci-tech financial ecosystem in the eastern region is highly complex, most provinces are in high–high agglomeration area. Provinces in other regions are mainly in low–low agglomeration area. Only a few provinces have experienced changes in the spatial distribution. (3) The dynamic value in the eastern region shows polarisation characteristics. Although the static value of resilience in the central and western regions is low, the dynamic evaluation value in some provinces in the central and western regions is high. The subsequent growth momentum of resilience in the north-eastern region is insufficient.

Wealth polarization in western countries

This paper delves into the dynamics of wealth distribution across various countries, utilizing innovative methodologies to uncover patterns of wealth polarization and its determinants. Wealth, distinct from income, reflects long-term economic resources and serves as a crucial indicator of economic well-being. Employing the "relative distribution" method and Recentered Influence Function (RIF) regression, this study examines changes in wealth distribution and the factors driving wealth polarization across eight European countries, Australia, and the United States.The analysis reveals significant heterogeneity in wealth distribution trends among countries, with disparities observed over time. Wealth polarization, akin to income polarization, emerges as a phenomenon distinct from traditional measures of inequality, shedding light on the concentration of wealth within societies. Household composition, demographic factors, and socioeconomic characteristics significantly influence wealth polarization, echoing patterns observed in income polarization studies.The findings underscore the multifaceted nature of wealth distribution dynamics and highlight the need for comprehensive policy interventions to address wealth inequality and polarization. Policy measures such as progressive taxation, regulatory reforms, and asset-building programs for marginalized communities are crucial in fostering equitable wealth distribution and creating inclusive societies.

Single-Shot Ultra-Widefield Polarization-Diversity Optical Coherence Tomography for Assessing Retinal and Choroidal Pathologies.

Background: Optical coherence tomography (OCT) is a leading ocular imaging modality, known for delivering high-resolution volumetric morphological images. However, conventional OCT systems are limited by their narrow field-of-view (FOV) and their reliance on scattering contrast, lacking molecular specificity. Methods: To address these limitations, we developed a custom-built 105∘ ultra-widefield polarization-diversity OCT (UWF PD-OCT) system for assessing various retinal and choroidal conditions, which is particularly advantageous for visualizing peripheral retinal abnormalities. Patients with peripheral lesions or pigmentary changes were imaged using the UWF PD-OCT to evaluate the system's diagnostic capabilities. Comparisons were made with conventional swept-source OCT and other standard clinical imaging modalities to highlight the benefits of depolarization contrast for identifying pathological changes. Results: The molecular-specific contrast offered by UWF PD-OCT enhanced the detection of disease-specific features, particularly in the peripheral retina, by capturing melanin distribution and pigmentary changes in a single shot. This detailed visualization allows clinicians to monitor disease progression with greater precision, offering more accurate insights into retinal and choroidal pathologies. Conclusions: Integrating UWF PD-OCT into clinical practice represents a major advancement in ocular imaging, enabling comprehensive views of retinal pathologies that are difficult to capture with current modalities. This technology holds great potential to transform the diagnosis and management of retinal and choroidal diseases by providing unique insights into peripheral retinal abnormalities and melanin-specific changes, critical for early detection and timely intervention.

Electrical resistivity imaging of crude oil contaminant in coastal soils – A laboratory sandbox study

Characterizing the subsurface distribution of crude oil after a spill in a coastal environment is challenging due to variations in the soil and fluid properties. In situ sampling is limited in capturing the lateral and vertical migration of the crude oil within the vadose and saturated zones. This study presents a laboratory sandbox framework used to assess the effectiveness of electrical resistivity imaging for investigating the spatiotemporal distribution of crude oil in coastal sandy soils. A sandbox with dimensions L = 240 cm, W = 60 cm, and H = 60 cm was constructed using a 10 mm plexiglass and filled to a 40 cm height with 2 mm medium to fine-grained sand. At each stage of the experiment, 20 kg of sand was mixed with 1 l of water to create moist sand, after which the mixture was flushed over 12 h to remove suspended fine particles. Both saturated and unsaturated conditions were simulated by setting the water table at 10 cm and draining a fully saturated system overnight. Two liters of crude oil were spilled and monitored for 30 h. A surface array of 98 electrodes, with a unit electrode spacing of 2 cm, was installed along two transects 12 cm apart. Resistivity measurements were collected using a dipole-dipole array before, during, and after the simulated crude oil spill. The time-lapse electrical resistivity results revealed an initial gravity-induced vertical migration under both saturated and unsaturated conditions; over time, lateral migration of crude oil became apparent. In the saturated zone, there was a noticeable reduction in the percentage difference in resistivity from 700 % to 400 % after 24 h, depicting a spatial and temporal redistribution of the crude oil attributed to variation in pore geometry. This highlights the sensitivity of electrical resistivity measurements to subtle but measurable anisotropy in the distribution of soil pores. Overall, electrical resistivity proved successful in imaging the non-ideal behavior of crude oil pollutants and the associated spatial changes in the pore-size distribution of subsurface sediments.

Towards online training for RL-based query optimizer

AbstractJoin query optimization aims to find the best join order for tables in a query, which is critical for query processing performance. Recently, reinforcement learning models have been proposed to solve the challenges existing with query processing and join query optimization. However, changes in the data distribution can turn the trained reinforcement learning models into obsolete models, resulting in longer execution times. In this paper, we propose a new training strategy in order to extend the existing reinforcement learning models and improve their adaptation when the data distribution changes. The experiments show that the proposed strategy has a significant benefit in decreasing training time for the models given the changes in the data distribution.

Characteristics and real-world medication persistence of people living with HIV treated with DTG/3TC or BIC/FTC/TAF: a hospital claims database study in Japan.

As the life expectancy of people living with human immunodeficiency virus (HIV) (PLWH) has improved, chronic disease burden and polypharmacy have increased in PLWH. Simplification of the antiretroviral therapy (ART) regimen for PLWH has become crucial. The real-world treatment patterns and medication persistence of the 2-drug single-tablet regimen (STR), dolutegravir/lamivudine (DTG/3TC), compared to bictegravir/emtricitabine/tenofovir alafenamide (BIC/FTC/TAF) prescribed were investigated. This retrospective, database study extracted data from a hospital-based medical claims database in Japan. The changes in ART distributions by year during the identification period between January 1, 2018 and December 31, 2021 were observed. Patients with disease record of HIV-1 infection and prescribed DTG/3TC or BIC/FTC/TAF as the first prescription of STR during the identification period were divided into two cohorts; DTG/3TC cohort and BIC/FTC/TAF cohort, respectively. Patient without medication records more than 3 months and no future data more than 6 months were excluded. Patients' characteristics were compared between the DTG/3TC cohort and the BIC/FTC/TAF cohort by Mantel-Haenszel test to adjust for age. Medication persistence was compared between the two cohorts by evaluating the continuation rates using Kaplan-Meier methods, using the log-rank test to assess the difference between the Kaplan-Meier curves. The median time-to-first prescription was compared between the two cohorts by Kaplan-Meier methods. Prescriptions of DTG/3TC and BIC/FTC/TAF increased steadily from 2019 to 2021 after the release year of each STR. There was no significant difference in the time-to-first prescription (p = 0.3). A total of 959 patients were included, with 120 patients and 839 patients on DTG/3TC and BIC/FTC/TAF, respectively. The proportion of dyslipidemia at baseline was significantly higher in the DTG/3TC cohort than in the BIC/FTC/TAF cohort after adjusting for mean age (p = 0.002). There was no significant difference in medication persistence between the two cohorts (p = 0.91). This study showed that DTG/3TC was likely to be selected for elderly patients and those with chronic disease in real-world clinical practice, which seems in accordance with the treatment strategy recommended by guidelines. Comparable medication persistence was observed with both regimens, aligning with findings from other countries. The 2-drug single-tablet regimen DTG/3TC may be an important ART regimen for PLWH with multiple morbidities and polypharmacy in an aging society. Due to the limitations of the database, further research to assess viral loads, emergence of resistance and adverse events will be encouraged.

Microstructure refinement and wear resistance enhancement of cost-effective Fe50−2xMn30Co10Cr10NixCux (x = 0, 5 at%) high-entropy alloys through cyclic closed-die forging process

Novel low-cost Fe50−2xMn30Co10Cr10NixCux (x = 0, 5 at%) high-entropy alloys (HEAs) were produced by vacuum melting and then processed by the cyclic closed-die forging (CCDF) process. It was found that both the as-homogenized and CCDF-processed specimens primarily consisted of a single face-centered cubic (FCC) structure, and the severe plastic strain through CCDF did not result in phase transformations. The microstructure of the CCDF-processed Fe50Mn30Co10Cr10 alloy after the sixth pass demonstrated a uniform structure with ultrafine grains measuring 285 nm in size, whereas for the CCDF-processed Fe40Mn30Co10Cr10Ni5Cu5 alloy, the grain size was 135 nm, with a relatively uniform distribution. The CCDF-processed Fe50Mn30Co10Cr10 and especially the Fe40Mn30Co10Cr10Ni5Cu5 alloy exhibited significantly higher microhardness compared to the as-homogenized state, with microhardness values being 2.42 and 2.72 times higher, respectively. Furthermore, the wear test results indicated that the CCDF processing effectively increased the wear resistance of the alloys, which was attributed to the changes in morphology and distribution of as-cast dendrites, along with the grain refinement of the matrix phase during CCDF. The CCDF-processed Fe40Mn30Co10Cr10Ni5Cu5 alloy exhibited the lowest wear rate, i.e., (1.2 ± 0.2) × 10–5 mm3.N−1.m−1, whereas that for the Fe50Mn30Co10Cr10 alloy was (2.4 ± 0.1) × 10–5 mm3.N−1.m−1. Analysis of wear surfaces indicated that the wear mechanisms of the as-homogenized HEAs were adhesive wear and abrasive wear with some delamination, while plastic deformation and adhesive wear were significantly reduced in the CCDF-processed specimens, especially in the Fe40Mn30Co10Cr10Ni5Cu5 alloy. These findings suggest that CCDF has the potential to achieve cost-effective nanostructured HEAs and to implement them in engineering applications.

Dynamic convolutional time series forecasting based on adaptive temporal bilateral filtering

Time series data typically contain complex dynamic patterns, which not only include linear trends and seasonal variations but also significant nonlinear changes and complex dependencies. Currently, feature extraction methods for time series data primarily employ mixed-mode extraction within the temporal domain, neglecting the effective extraction and analysis of nonlinear characteristics between different observation points and the interdependencies between variables. To address these issues, we designed an adaptive temporal bilateral filtering module that effectively preserves and highlights the nonlinear features and patterns in time series while filtering out noise and redundant information. We also designed a nonlinear feature adaptive extraction module that integrates a gating mechanism and deformable convolutions. This design allows the model to adaptively adjust the shape of the convolutional kernels according to different time steps and conditions. This enables accurate capture and extraction of nonlinear features between various time observations and dependencies between different variables. Additionally, we use stacked convolutional layers to extract local contextual features, addressing fluctuations in local features caused by changes in data distribution in real-world scenarios. In summary, we propose DCNet, a dynamic convolutional network based on an adaptive temporal bilateral filter, and evaluated its performance on twelve real-world datasets. The results indicate that DCNet consistently achieves state-of-the-art performance in both short-term and long-term forecasting tasks, with favorable runtime efficiency.

Performance investigation of a solar-driven cascaded phase change heat storage cross-seasonal heating system for plateau applications

The mismatch between solar radiation resources and building heating demand on a seasonal scale makes cross-seasonal heat storage a crucial technology, especially for plateau areas. Utilizing phase change materials with high energy density and stable heat output effectively improves energy storage efficiency. This study integrates cascaded phase change with a cross-seasonal heat storage system aimed at achieving low-carbon heating. The simulation analyzes heat distribution and temperature changes from the heat storage system to the heating terminal. The results indicate that although the solar collectors operate for 26.3% of the total heat storage and heating period, the cumulative heat stored is 45.4% higher than the total heating load. Heat transferred by the cross-seasonal heat storage system accounts for up to 61.2% of the total heating load. Therefore, the system reduces fuel consumption by 77.6% compared to conventional fossil fuel heating systems. Moreover, radiant floor heating terminals, with a wide range of operating temperatures, match well with cascaded phase change heat storage and can reduce operation time by 19.5% and heat demand by 5.2% compared to conventional radiators. In addition to demonstrating the feasibility of applying cascaded phase change technology in cross-seasonal heat storage heating, this study reveals the lifecycle sustainability due to the shortened heat storage period. The configuration, parameters, and simulation results provide a reference basis for system application and design.

Numerical Simulation and Experimental Research of Spatial Volume Distribution and Velocity Changes of Abrasive Suspension Jet Based on LES + VOF + DEM

The machining accuracy and cutting ability of abrasive suspension jet (ASJ) are affected by the spatial volume distribution and velocity changes of jet flow and abrasives in the free jet area outside the nozzle. In this paper, large eddy simulation (LES) flow model, volume of fluid (VOF) multiphase flow model and discrete element model (DEM) were used to simulate the flow field characteristics of ASJ. The spatial volume distribution and velocity changes of jet flow and abrasives under 10[Formula: see text]MPa jet pressure were studied and the model validation experiments were carried out. In the comparison between the numerical simulation results and the experimental results, it was found that the average error of the percentage of central jet flow is 3.4%, the percentage of central abrasive particles is 3.0% and the velocity of abrasive particles is 4.2%. The physical structure of the numerical model is fixed (so it does not support abrasive injection jet (AIJ)), and the material physical parameters, initial conditions and boundary conditions are editable. Therefore, it can be used to predict the degree of water divergence, abrasives divergence and abrasives velocity attenuation of ASJ with different jet pressure and abrasive types. This numerical model can provide guidance for the parameter setting of ASJ machining process in order to obtain better machining accuracy and cutting ability.

Impact of PCLNPG Nanopolymeric Additive on the Surface and Structural Properties of PPSU Ultrafiltration Membranes for Enhanced Protein Rejection

This research explored the use of a partially cross-linked graft copolymer (PCLNPG) as an innovative nanopolymer pore-forming agent to enhance polyphenylsulfone (PPSU) membranes for protein separation applications. The study systematically examined the impact of incorporating PCLNPG at varying concentrations on the morphological and surface properties of PPSU membranes. A thorough characterization of the resulting PPSU-PCLNPG membranes was performed, focusing on changes in morphology, water affinity, porosity, pore size, and pore size distribution. The experimental findings demonstrated that the use of PCLNPG led to a significantly more porous structure, as confirmed by SEM analysis, with notable increases in porosity and pore size (nearly double). Additionally, the hydrophilicity of the PPSU membrane was remarkably enhanced. Performance evaluations revealed a substantial improvement in pure water flux, with the flux nearly tripling. The BSA retention was directly correlated with the concentration of the PCLNPG pore former for a loading range of 0.25–0.75 wt.%. The incorporation of PCLNPG also reduced the membrane fouling propensity by reducing both cake layer resistance (Rc) and pore plugging resistance (Rp). These results underscore the potential of PCLNPG-PPSU membranes for wastewater reclamation and nutrient recovery applications.

Changes in the spatiotemporal distribution of the timing and duration of the soil freeze–thaw status from 1979 to 2018 over the Tibetan Plateau

AbstractChanges in the soil freeze–thaw status will inevitably affect the thermal conditions and properties of the Tibetan Plateau (TP), thereby affecting its upper atmosphere, and further afield in East Asia and even globally. In this study, using the soil temperature simulated by the Community Land Model Version 5.0 (CLM5.0), the timing and duration of the soil freeze–thaw status were divided into freeze start‐date, freeze end‐date and freeze duration. Then, using linear trend estimation, correlation analysis and other methods, the changes in the spatiotemporal distribution of the timing and duration of the soil freeze–thaw status from 1979 to 2018 over the TP were analysed, and the relationships between them and surface temperature, altitude and latitude were analysed. The results obtained were as follows: (1) The soil temperature simulated by CLM5.0 can reasonably reproduce the seasonal changes in multilayer soil temperature, and correlated well with observations. Simulated by CLM5.0 of the time and duration of the soil freeze–thaw status also correlated well with observations. (2) The spatial distribution of the soil freeze–thaw status is characterized by a trend of delayed freezing, advanced thawing and shortened freeze duration from northwest to southeast over the TP. From 1979 to 2018, the freeze start‐date postponed by 7.3 days and became delayed at a rate of 1.9 days per decade, while the freeze end‐date advanced by 6.4 days at a rate of 1.7 days per decade, and the freeze duration shortened by 13.7 days at a rate of 3.6 days per decade. The timing and duration of the soil freeze–thaw status vary across different regions of the TP. The freeze start‐date in all areas of the TP has been delayed in the past 39 years. Except for the subcold zone and arid regions of the TP, the freeze end‐date has occurred earlier and the freeze duration has shortened, with the most significant changes in the subcold zone and humid regions, while the freeze end‐date has advanced at a rate of 3.6 days per decade and the freeze duration has shortened at a rate of 6.3 days per decade. (3) The timing and duration of the soil freeze–thaw status are significantly correlated with surface air temperature, elevation and latitude, exceeding the 99% confidence level. The correlation between the timing and duration of the soil freeze–thaw status and surface temperature is strongest, followed by altitude, and correlation with latitude is weaker. The correlation between surface air temperature and the timing and duration of the soil freeze–thaw status in the western TP is stronger than that in the eastern TP. The rate of change in the soil freeze–thaw status increases with altitude to 3000 m above sea level, while this rate decreases with elevation above 3000 m. The rate of change in the soil freeze–thaw status is greatest at 29°N, while the rate of delay in the freeze start‐date is minimal at 33°N and the rates of advancement in the freeze end‐date and shortening of the freeze duration are minimal at 35°N.

Changes in the equilibrium of the urban transport system of a large city following an urban flood

Urban floods are among the most frequent and destructive natural disasters. They generate enormous economic and non-economic losses, including damage to buildings and transportation infrastructure, which are critical systems supporting community well-being. The purpose of this paper was to assess the impact an urban flood would have on the urban road transport system in Łódź and to determine changes in potential accessibility that would accompany a flood. This paper introduces a novel approach in terms of combining the modelling of direct impact ranges of urban flooding in the area of Łódź and a macroscopic multi-motivational traffic model for the city (using PTV Visum software). This made it possible to identify mechanisms of changes made in as many intra-system relationships as possible, as well as between the system and its surroundings. The results showed that changes in the spatial distribution of traffic volume in the city are closely dependent on the water level. The sections of the network most affected by the load changes are those that form the framework for the entire system of Łódź, indicating a lack of resilience of the car transport subsystem in the critical segment for the functioning quality of the entire subsystem. Additionally, the study was conducted for public transport, and it was indicated that changes in its utilization are minimal. It was also found that the greatest impact on transport accessibility from an urban flood is for ultra-short trips. This is primarily due to the base effect (the initial quality of the infrastructure and its potential) – the internal potential of the transport area deteriorates drastically during a flood, severely affecting accessibility.

Multivariate quality prediction of thin-walled parts machining using multi-task parallel deep transfer learning

Multivariate machining quality prediction of thin-walled parts with multiple machining features is a complex problem due to different data distribution between training and unlabelled test samples. Traditional quality prediction methods ignore the correlation of multiple quality labels and do not consider changes in data distribution, resulting in low accuracy of multivariate quality prediction. Therefore, a multivariate quality prediction method using multi-task parallel deep transfer learning is proposed to solve this problem. Specifically, a multi-output quality prediction model of cross-machining features is constructed through the joint design of multi-task parallel learning and deep transfer learning. Furthermore, a domain matcher is designed to form multiple transfer strategies, which can be used for dynamic matching of multi-source and multi-target machining features with multiple quality labels. The domain invariant data features through dynamic domain adaptation are extracted to deal with data distribution discrepancy between the source and target domains. Finally, the results of multiple comparison experiments show that the proposed method can effectively achieve the accurate quality prediction of the target domain with unlabelled labels and different distributions. Compared with the traditional methods, the proposed method has improved by 8.34%, 7.14%, and 9.09%, respectively, in MAE, RMSE, and score on average.

Meta-Analysis and MaxEnt Model Prediction of the Distribution of Phenacoccus solenopsis Tinsley in China under the Context of Climate Change.

Phenacoccus solenopsis Tinsley is a pest that poses a significant threat to agricultural crops, especially cotton, and is now widely distributed across many regions worldwide. In this study, we performed a meta-analysis on the collected experimental data and found that within the suitable temperature range, the survival rate of P. solenopsis increases with rising temperatures, indicating that climate plays a decisive role in its distribution. Using the MaxEnt model this study predicted that under three future climate scenarios (SSP1-2.6, SSP3-7.0, and SSP5-8.5), the distribution of P. solenopsis will expand and move towards higher latitudes. Climate change is the primary factor influencing changes in pest distribution. We conducted a meta-analysis of P. solenopsis, including seven independent studies covering 221 observation results, and examined the impact of temperature ranging from 18 °C to 39 °C on the developmental cycle of P. solenopsis. As the temperature rises, the development cycle of P. solenopsis gradually decreases. Additionally, by combining the MaxEnt model, we predicted the current and potential future distribution range of P. solenopsis. The results show that under future climate warming, the distribution area of P. solenopsis in China will expand. This research provides a theoretical basis for early monitoring and control of this pest's occurrence and spread. Therefore, the predictive results of this study will provide important information for managers in monitoring P. solenopsis and help them formulate relevant control strategies.

Experimental study on the stability of noncohesive landslide dams based on seepage effect

Landslide dams composed of unconsolidated, noncohesive soil are easily affected by seepage. As seepage develops, the dam's characteristics change dynamically, indirectly affecting its stability. However, previous studies on dam failure have mostly assumed that the dam characteristics remain constant before failure, often overlooking these changes and their effects on stability. In this study, 48 sets of flume experiments were conducted to quantify the impact of seepage under varying upstream inflow rates, dam heights, downstream slope angles, and particle size distributions. During the storage phase, the rise rate of the water level is closely linked to the seepage's diversion capacity. The diversion rate of inflow reached as high as 0.747 in this study, but decreased to 0.230 as inflow increased. Furthermore, changes in the internal stress distribution within the dam, driven by seepage, contributed to dam settlement and the sliding of the downstream slope. Notably, dam settlement exhibited both non-uniform spatial distribution and temporal stage development. The maximum settlement ratio between the point in the upstream breach and the point in the downstream breach reached as high as 2.79. Regarding the soil changes within the dam, after the seepage channel became connected, the primary soil loss involved silt particles ranging from 10 to 20 μm in size. This result reflects the increasing non-uniformity within the dam caused by seepage. Finally, Considering the changes in dam characteristics under the influence of seepage, in this study, a logistic regression model was established to assess dam stability. Overall, this study enhances the understanding of how seepage affects dam stability by examining various dam properties and presenting a model for stability assessment.