Computer Simulation Research Articles

A novel residual-pyramid-attention super resolution model for mesoscale meteorological forecasting spatial downscaling

ABSTRACT Developing a spatial downscaling method using machine learning techniques has emerged as a significant endeavor in meteorological forecasting. In this study, we propose a novel Residual-Pyramid-Attention Super Resolution (RPASR) model that effectively addresses the checkerboard artifacts issue prevalent in existing approaches, offering a unique perspective on spatial downscaling. Moreover, we propose a unique scaling technique during the data training to enhance the prediction performance. To validate and apply the proposed method, we utilize both low and high-resolution meteorological variables obtained from a numerical weather prediction model and observations in the Zhangbei region, China. The results demonstrate the exceptional performance of the RPASR model in spatial downscaling, exhibiting superior accuracy in meteorological prediction. Notably, the model outperforms interpolation techniques, significantly reducing deviations by 50% for variables such as 2 m temperature (T2), 2 m humidity (rh2), and 10 m wind speed (wspd10). In practical applications, our proposed model surpasses the DeepSD super-resolution model and low-resolution simulations as a whole, particularly for T2, where it enhances the T2 correlation coefficient by 1.2% compared to DeepSD. Additionally, it reduces the T2 root mean square error by 10.6% and the rh2 root mean square error by 8.6% compared to the low-resolution simulations. Overall, the RPASR model demonstrates robust validation and exhibits promising potential for advancing spatial downscaling methods in meteorological forecasting.

Studi Pemodelan Numerik Penempatan Shark Fin Vortex Generator dengan Susunan Sebaris Pada Dindong Kiri dan Kanan Bus Penumpang

This study analyzes the impact of installing Shark Fin Vortex Generators (SFVG) in a row arrangement on the left and right sides of a passenger bus on the vehicle’s aerodynamic performance. A numerical modeling approach was used to visualize the airflow around the bus and measure key parameters such as drag coefficient (CD), lift coefficient (CL), and pressure coefficient (CP) distribution. Air velocity contour analysis shows that SFVG significantly optimizes airflow around the bus. The bus with SFVG achieved a higher airspeed of 50.23 km/h, while the bus without SFVG only reached 49.83 km/h, indicating a significant reduction in aerodynamic drag. Drag coefficient (CD) analysis shows that the bus with SFVG has a lower CD value of 0.63794782 compared to the bus without SFVG, which has an average value of around 0.70191103. Although the difference is small, it indicates that SFVG has the potential to reduce aerodynamic drag. A difference in lift coefficient (CL) values between the bus with SFVG (around 0.040190537) and the bus without SFVG (around 0.05368355) was also observed, suggesting that SFVG affects the lift force distribution on the bus. Pressure distribution analysis shows that SFVG alters the pressure distribution around the bus. Pressure contours on the bus with SFVG show concentrated pressure at the front of the bus with a peak pressure of about 213.22 Pa, whereas the bus without SFVG shows a higher peak pressure, reaching 465.17 Pa at the same location. This study also evaluates the potential of SFVG to reduce fuel consumption and the environmental impact of public transportation through reduced drag forces. The analysis results indicate that SFVG has the potential to improve energy efficiency and overall aerodynamic performance of the bus. Further research is needed to fully understand the impact of using SFVG in this context.

Optimization of Discrete Element Method Model to Obtain Stable and Reliable Numerical Results of Mechanical Response of Granular Materials

The discrete element method (DEM) is largely used to simulate the geotechnical behavior of granular materials. However, numerical modeling with this type of code is expensive and time consuming, especially when fine particles are involved. This leads researchers to make use of different approaches to shorten the time of calculation without verifying the stability and reliability of numerical results, even though a compromise between the time of calculation and accuracy is commonly claimed. The particle size distribution (PSD) curve of studied granular material is completely ignored or arbitrarily cut. It is unclear if the ensued numerical results are still representative of the studied granular materials. Additionally, one can see a large number of numerical models established on a basis of calibration by ignoring the physical meaning and even measured values of some model parameters. The representativeness and reliability of the obtained numerical results are questionable. All these partly contribute to reducing the public’s confidence in numerical modeling. In this study, a methodology is illustrated to obtain an optimal DEM model, which minimizes the time of calculation and ensures stable and reliable numerical results for the mechanical behavior of a waste rock. The results indicate that the PSD curve of the studied waste rock can indeed be cut by excluding a portion of fine particles, while the Young’s modulus of the waste rock particles can also be decreased to accelerate the numerical calculations. A physical explanation of why the time of calculation can be shortened by reducing the Young’s modulus of waste rock particles is provided for the first time. Overall, the PSD cut, reduction in Young’s modulus, and time step must be determined through sensitivity analyses to ensure stable and reliable results with the shortest time of calculation. In addition, it is important to minimize the number of model parameters determined through the process of calibration, especially for those having physical meanings. In this study, the only model parameter having a clear physical meaning but difficult to measure is the rolling resistance coefficient for repose angle tests on the studied waste rock. Its value has to be obtained through a process of calibration against some experimental results. The validity and predictability of the calibrated numerical model have been successfully verified against additional experimental results.

Active rack control of steer-by-wire systems for vehicle lateral stability

This paper describes a stability control strategy based on a steer-by-wire system to improve the lateral stability and manoeuvrability of vehicles by integrating individual chassis control modules, such as electronic stability control (ESC) and active front steering (AFS). Because of the uncertainty of cornering stiffness, an adaptive sliding-mode control is implemented without using the cornering stiffness value. An adaptive parameter is used instead of the cornering stiffness in the slip angle estimation and the lateral stability control. An unscented Kalman filter is used to estimate the slip angle and adaptive sliding mode control is used in lateral stability control. An equivalent desired command is calculated in lateral stability control. An integrated AFS and four individual wheel-braking controls were utilised to achieve an optimal distribution of longitudinal and lateral tyre forces, aiming to attain the desired command for lateral stability. Optimal coordination of the control authority for the AFS and the ESC has been chosen to minimise the force of each tyre. Computer simulations and vehicle tests of a closed-loop driver–vehicle–controller system subjected to a double-lane change have been carried out to verify that the proposed control strategy works.

Computational Simulations of Metal-Organic Frameworks to Enhance Adsorption Applications.

Metal-organic frameworks (MOFs), renowned for their exceptional porosity and crystalline structure, stand at the forefront of gas adsorption and separation applications. Shortly after their discovery through experimental synthesis, computational simulations quickly become an important method in broadening the use of MOFs by offering deep insights into their structural, functional, and performance properties. This review specifically addresses the pivotal role of molecular simulations in enlarging the molecular understanding of MOFs and enhancing their applications, particularly for gas adsorption. After reviewing the historical development and implementation of molecular simulation methods in the field of MOFs, high-throughput computational screening (HTCS) studies used to unlock the potential of MOFs in CO2 capture, CH4 storage, H2 storage, and water harvesting are visited and recent advancements in these adsorption applications are highlighted. The transformative impact of integrating artificial intelligence with HTCS on the prediction of MOFs' performance and directing the experimental efforts on promising materials is addressed. An outlook on current opportunities and challenges in the field to accelerate the adsorption applications of MOFs is finally provided.

Computational simulation-assisted template selection of magnetic MOFs molecularly imprinted materials applying the adsorption and detection of multiple fluoroquinolones

This study utilized computational simulation and surface molecular imprinting technology to develop a magnetic metal-organic framework molecularly imprinted polymer (Fe3O4@ZIF-8@SMIP) capable of selectively recognizing and detecting multiple fluoroquinolones (FQs). The Fe3O4@ZIF-8@SMIP material was synthesized using the “common” template-ofloxacin, identified by computational simulation, demonstrating notable adsorption capacity (88.61–212.93 mg g−1) and rapid mass-transfer features (equilibration time: 2–3 min) for all tested FQs, consistent with Langmuir adsorption model. Subsequently, this material was employed as a magnetic solid-phase-extraction adsorbent for adsorption and detection of multiple FQs by combining with high performance liquid chromatography. The developed method exhibited good linearity for various FQs within the concentration range of 0.1–500 μg L−1, with low limit of detection (0.0605–0.1529 μg L−1) and limit of quantitation (0.2017–0.5097 μg L−1). Satisfactory recoveries (88.38–103.44%) were obtained when applied to spiked food samples, demonstrating the substantial potential of this Fe3O4@ZIF-8@SMIP material for rapid enrichment and identification for multiple FQs residues.

Assessing the performance of infrared thermography and PIV methods to identify and characterize the air inlets and outlets in wall assemblies

Building airtightness is crucial for reducing energy demand in the building sector and preventing moisture damage and indoor environment quality issues. Mandatory airtightness tests are now commonly performed in many countries to quantify the total envelope leakage rate of real buildings. For a more precise diagnosis, air leakages are usually identified by infrared thermography or visualized by smoke. However, a finer analysis is also needed to characterize precisely the air flow through specific leaks. Numerical models have been developed for this purpose but experimental data are necessary to validate them. In this paper, two experimental approaches are tested on simple light-wall assembly configurations to address this need: infrared thermography (IRT) and the innovative use of particle image velocimetry (PIV) with a specific experimental set-up and protocol developed. The results are compared with each other as well as with numerical simulations. Results showed that both techniques can be applied for the experimental characterization of the air inlet/outlet of a wall assembly with different advantages and drawbacks. IRT is easy to implement, non-intrusive, possible for in-situ investigations, but the correlation between the thermographs and the air dispersion at the outlet is not straight forward due to thermal inertia and heat conduction issues. PIV gives direct results on the velocity field and enables quantitative analysis of air flow rates for various configurations, with some limitations: a difficult implementation; restrictions on the possible infiltration velocity range and difficulties to visualize the flow exactly at the interface with the wall assembly.

Assessment of failure modes of a rising stem type gate valve according to ASME BPVC Section-VIII, Division-2 criteria

Assessing the structural integrity of valves is crucial during the development process. Design by analysis involves evaluating unconventional geometries and loads by researching and classifying stresses, then comparing them to allowable values. Although ASME BPVC Section-VIII, Division-2 does not specifically cover valves, key valve design standards reference this code. Hence, this numerical study aims to develop and apply specialized stress analysis models for evaluating plastic collapse and local failure in a rising stem-type gate valve. The methodology is developed to assess the elastic behavior of the valve under stress to evaluate plastic collapse. It is also designed to assess plastic collapse and local failure by considering the material’s behavior beyond the elastic range and into the plastic deformation zone. A numerical model using the ANSYS–MECHANICAL tool was developed based on the finite element technique. The main failure modes of a rising stem-type gate valve according to ASME BPVC Section-VIII, Division-2 criteria were considered. The main contribution to valve development is providing specialized stress analysis models and numerical simulations, mainly focusing on the rising stem-type gate valve and aligning it with relevant ASME standards. The results showed that the maximum von Mises stress in the valve body was 200.6 MPa, staying below the yield limit, while the screws surpassed the yield limit with 725.72 MPa, entering the plastic deformation zone.

On the correlation between fatigue behaviour and the multiphase microstructure of a super duplex stainless steel

This work investigates the relationship between the multiphase microstructure and the macroscale fatigue behaviour of a cast super duplex stainless steel (SDSS). The microstructure of a cast SDSS is typically composed of a FCC γ-phase and a BCC δ-phase. However, deleterious secondary phases (SP), such as sigma and chi, may precipitate when SDSS is exposed to high-temperature ranges, jeopardising its mechanical properties, namely fatigue performance. The purpose of this investigation was to quantify the correlation between SP amounts and fatigue life of a cast SDSS (CD3MWCuN, ASTM A890). Fatigue tests were conducted using miniature specimens taken from a cast C-Ring with different SP amounts. A numerical model was proposed to calibrate the fatigue test parameters. After the tests, SEM and EBSD techniques were used to quantify the SP and analyse the fatigue-crack propagation. The microstructural analysis was complemented with hardness and tensile tests. Regression models were developed to correlate the percentage of SP, the fatigue resistance and the number of cycles to failure, and to predict the microstructural stress concentration from the amount of SP. In addition, a methodology is proposed for predicting S-N curves as a function of the amount of SP, showing a high correspondence in the increase of the percentage of SP with the decrease in fatigue life. Furthermore, the fatigue strength, for a given number of cycles to failure, tends to decrease linearly with increasing the SP, while the microstructural stress concentration factor tends to increase with an increase in SP. These findings contribute to further knowledge on predicting the behaviour of cast SDSS under different cyclic conditions, which can be valuable for optimizing design and performance in various applications.

Optimization study for cement-based grout mixture ratio of shield tunnel considering spatiotemporal evolution of grout buoyancy

The grout buoyancy for segments during shield tunnel construction can cause significant floating displacement or even cracking of the segments, and the grout buoyancy is directly related to the grout buoyancy volumetric weight (GBVW). This study proposes an optimization process for the mixture ratio of cement-based grout based on the actual engineering environment. Based on a self-designed GBVW test instrument considering the interaction between grout and strata, this study reveals the evolution law of GBVW and the 3D spatial distribution law of grout buoyancy under different mixture ratios in different strata. Then, this study calculates the segment displacement under slurry buoyancy by the multi-factor coupled numerical calculation model. Research shows that the GBVW in different strata exhibits an evolutionary characteristic of sharp fluctuation-rapid decrease-slow decrease-complete disappearance. The upward precipitation of aqueous solutions in grout in different strata occurs during the stage of GBVW sharp fluctuations, and the decrease in GBVW is mainly accompanied by the seepage of aqueous solutions into the lower strata. The average GBVW and the duration of GBVW in muddy soil are larger than those in silty soil and coarse sand, respectively. An increase in the water binder ratio will reduce the GBVW and accelerate the dissipation of GBVW, while an increase in the bentonite water ratio will promote the growth of GBVW. The lower the strata permeability, the more easily the average GBVW is affected by the water cement ratio. The peak GBVW is more easily affected by the water binder ratio, and the duration of GBVW is more easily affected by the water cement ratio.

The Prisoner’s Dilemma game as a tool to investigate cooperation and undergraduate education in evolution

Evolutionary theory is based on the conflict that arises when certain heritable variants out-compete others. Given this foundational conflict, a central question for evolutionary biologists concerns the presence of cooperation found throughout all levels of biological organization; from biochemical pathways to complex animal societies. Human behavior is often distinguished from other animal behavior by the presence of acts of cooperative behavior called altruism. Altruism is a cooperative act that penalizes the actor for actions that benefit the recipient. Any other form of cooperation, one that does not penalize the actor, is formally not considered altruistic. How can costly altruistic behavior evolve? This question was the basis for development of a web application tool incorporating a game theory model to investigate conditions affecting cooperative behavior. The game theory model described as Prisoner’s Dilemma incorporates acts of cooperation and non-cooperation (defection). Computer simulations of Prisoner’s Dilemma were developed and online applications were administered for five semesters at Georgia Gwinnett College, using two simulation environments referred to as Random and Non-random. Data collected from simulation runs were used to evaluate the effect of environment on student cooperative behavior and actively engage students in concepts associated with the evolution of cooperation and game theory. Results from student game play suggest group simulation environment played a significant role in the likelihood of observing cooperative behavior. Educational content and attitudinal surveys suggested that PD game play in the undergraduate evolution class at Georgia Gwinnett College improved student knowledge and self-confidence.

Chemopreventive effect of modified zeng-sheng-ping on oral squamous cell carcinoma by regulating tumor associated macrophages through targeting tnf alpha induced protein 6

BackgroundOral squamous cell carcinoma (OSCC) is the most common malignancy of the head and neck. Zeng-Sheng-Ping, composed of Sophora tonkinensis Gagnep., Bistorta officinalis Delarbre, Sonchus arvensis L., Prunella vulgaris L., Dioscorea bulbifera L., and Dictamnus dasycarpus Turcz., was regarded as an anti-cancer drug with significant clinical efficacy, but was discontinued due to liver toxicity. Our research group developed a modified Zeng-Sheng-Ping (ZSP-M) based on original Zeng-Sheng-Ping that exhibited high efficiency and low toxicity in preliminary investigations, although its pharmacodynamic mechanism is still unclear. Here, we aimed to elucidate the pharmacodynamic material basis of ZSP-M and investigate its chemopreventive effect on OSCC by modulating tumor associated macrophages (TAMs).MethodsComponents of ZSP-M were characterized using ultra-performance liquid chromatography-mass spectrometry. Chemopreventive effect induced by ZSP-M against experimental oral cancer was investigated using the 4-nitroquinoline N-oxide precancerous lesion mouse model. RNA sequencing analysis was used to gain a global transcriptional view of the effect of ZSP-M treatment. A cell co-culture model was used to study the targeted effect of ZSP-M on TAMs and the biological properties of OSCC cells and to detect changes in TAM phenotypes. The binding of ZSP-M active compounds to TNF alpha induced protein 6 (TNFAIP6) protein was analyzed by molecular docking and dynamic simulation.ResultsForty main components of ZSP-M were identified, the most abundant of which were flavonoids. ZSP-M inhibited the degree of epithelial dysplasia in precancerous lesions by inhibiting the expression of the TNFAIP6 and CD163 proteins in the precancerous lesions of the tongue. ZSP-M inhibited proliferation, colony formation, migration and invasion of SCC7 cells by targeting TAMs. ZSP-M reduced the expression of CD163+ cells, inhibited the expression of TNFAIP6 protein, Arg1 mRNA and Il10 mRNA in TAMs, and reduced IL-10 cytokine release in the co-culture environment. This effect was maintained after the addition of recombinant TNFAIP6 protein. Computer simulations showed that trifolirhizin and maackiain are well-connected to TNFAIP6.ConclusionsZSP-M counteracts the immunosuppressive action of TAMs by specific targeting of TNFAIP6, thereby exerting chemopreventive activity of OSCC.

Investigation on electromagnetic and heat transfer coupling of heating susceptor for selective microwave hybrid soldering: 3D multi-physics simulation and experiment

The utilization of microwave hybrid heating as an emerging technique in the field of low-temperature joining presents a notable benefit of delivering both selective and rapid heating, a feature that is not commonly observed in traditional soldering methods. However, due to the complex multi-physical coupling problem, the factors and mechanisms affecting the heating effect of the susceptors have not been clearly explained. To examine the effect of susceptor shape, size, and process parameters on heating efficiency, a numerical model of electromagnetic and thermal coupling was created to analyze silicon carbide susceptor heating under microwave action. The response surface method examined how microwave frequency, power, and exposure time affect susceptor heating efficiency. The model’s three process parameters are used to selectively heat Cu/SAC305/Cu joints, and the connection mechanism is studied. The results reveal that cylindrical susceptors heat more efficiently and uniformly than cubic ones. The heating efficiency is the highest when the height of the susceptor is 30 mm. Moreover, the heating effect is optimum at 2.45 GHz. Microwave power and exposure period positively linked with susceptor heating efficiency. The finite element simulation model shows that energy consumption at 2.45 GHz\\2 kW210 s is 78.38 % of that at 2.45 GHZ\\1 kW370 s, and the maximum temperature difference is 73.44 % of that at 2.45 GHz\\3k W\\90 s. MHS experiments show that as exposure duration increases, Cu6Sn5 grew and the growth orientation becomes consistent and perpendicular to the {0 0 0 1} family of crystal planes. Under process settings of 2.45 GHz \\ 2 kW \\ 210 s, the joint can achieve 16.55 MPa shear tensile strength. The results can serve as references for the study on selective microwave hybrid soldering and provide a new idea for selective and efficient soldering.

Improving the performance and economics of reversible solid oxide cell-based hydrogen energy storage systems through the utilization of renewable alternative fuels

Reversible solid oxide cells (RSOCs) represent a promising solution for addressing the future challenge of large-scale renewable energy storage. However, the performance and economic viability of current RSOC systems are hindered by the large overpotential losses in electrolysis and apparent fuel (H2) costs associated with power generation. This study employs a comprehensive numerical modeling approach to analyze the potential of renewable fuel (glycerol) in assisting hydrogen production performance and reducing operating costs within RSOC systems. The detailed comparative analyses and parametric studies are conducted on H2-based and glycerol-based RSOC systems at typical operating conditions. Notably, it is found that the economic viability of hydrogen-based RSOC systems is hindered by the remarkable fuel (H2) costs during nighttime despite of the favorable effects of larger stack capacity and higher temperature. While incorporating glycerol as an alternative fuel in RSOC systems offers significant advantages, including doubling the electrolytic H2 production (from 585.92 Nm3·h−1 to 1191.24 Nm3·h−1) at a relatively low cost and substantially reducing the fuel expenses (from 594.30 $·h−1 to 30.57 $·h−1) for nighttime power generation, thus leading to competitive electrolytic hydrogen production cost (2.982 $·kg−1) and noteworthy enhancement in economic viability (LCOE of 0.090 $·kWh−1 and 0.304 $·kWh−1 for electrolysis and power generation, respectively). The findings of this study provide valuable insights that contribute to the advancement of RSOC systems, thus facilitating the development of efficient, cost-effective, and sustainable energy storage and conversion technologies.

Experimental study of the tension forming model of a long-span string-supported spoke-type truss structure

This paper investigates the structural response of the long-span string-supported spoke-type (LSSS) truss structure during the tension forming process, as well as the influences of the errors caused by initial defects of the structure. A 1:10 scaled test model was designed and fabricated with reference to the main hall structure of the Northwest University gymnasium. The mesh simplification and scaling-down of the design of the prototype were performed to obtain a test model with good similarity to the prototype. Subsequently, after the comparative analysis of different tensioning batches, numbers of tensioning stages, and tensioning sequences, a radial-cable-forming scheme of three-stage, five-batch, clockwise tensioning for each ring cables was determined to be superior for this type of system. The cable force, node vertical displacement, and rod stress were monitored during the test. SAP2000 finite element software was employed to establish a numerical model, which was then verified by the test results. The test results were found to be in good agreement with the simulation results. The outer-ring cables withstood a larger share of the load, which could provide more stiffness support for the structure. During the tensioning process, the tensioning of the inner-ring cables would further increase the vertical displacement of the outer-ring roof nodes, which increased the compressive stress of the upper-chord-rods near the outer-ring. After the tensioning was completed, the lower-chord-rods in the mid-span and at the ends of the truss were in tension. Comparative analyses of the variations of the position and geometry, as well as the cable force, in each ring of cables during the construction process demonstrated that initial defects in the installation of the upper roof will lead to the uneven distribution of the radial cable forces, and that the errors will gradually accumulate with the advancement of the tensioning stage. However, after the structure was formed, the verticality deviation of most struts was close to or less than 1/150, and the error between the measured value and the simulated value of the rod stress was basically kept below 10 %, which proved the rationality of the tension scheme adopted in the test.

Performance analysis and optimization of an annular thermoelectric generator integrated with vapor chambers

To overcome the structural barriers of conventional annular thermoelectric generators (ATEGs), a new ATEG integrated with vapor chambers (VCs) is proposed in this paper, where the use of VCs enables a large hot-end contact area and a high temperature uniformity for traditional planar thermoelectric modules. Besides, a numerical model for the ATEG is built to conduct performance analysis and optimization under different parameters. Results suggest that the heat absorption of the ATEG increases with the increase of the number of VCs, thereby boosting the output power of the system. When the flow rate is lower than 35 g/s, the optimal number of VCs for the ATEG is 12, with the highest output power, conversion efficiency, net power, and net efficiency of 287.3 W, 5.36%, 214.1W, and 3.99%, respectively, at the exhaust temperature of 800 K. Besides, the exhaust temperature does not affect the optimal result, while the ATEG should be designed with fewer VCs when applied to the waste heat recovery with a larger flow rate. The increase in the VC thermal conductivity is not related to heat absorption but can improve temperature uniformity, and the thermal conductivity of 4000 W⋅m-1⋅K-1 already meets performance requirements. This study provides new perspectives on the structure design of ATEGs.

Skin cancer classification based on an optimized convolutional neural network and multicriteria decision-making

Skin cancer is a type of cancer disease in which abnormal alterations in skin characteristics can be detected. It can be treated if it is detected early. Many artificial intelligence-based models have been developed for skin cancer detection and classification. Considering the development of numerous models according to various scenarios and selecting the optimum model was rarely considered in previous works. This study aimed to develop various models for skin cancer classification and select the optimum model. Convolutional neural networks (CNNs) in the form of AlexNet, Inception V3, MobileNet V2, and ResNet 50 were used for feature extraction. Feature reduction was carried out using two algorithms of the grey wolf optimizer (GWO) in addition to using the original features. Skin cancer images were classified into four classes based on six machine learning (ML) classifiers. As a result, 51 models were developed with different combinations of CNN algorithms, without GWO algorithms, with two GWO algorithms, and with six ML classifiers. To select the optimum model with the best results, the multicriteria decision-making approach was utilized to rank the alternatives by perimeter similarity (RAPS). Model training and testing were conducted using the International Skin Imaging Collaboration (ISIC) 2017 dataset. Based on nine evaluation metrics and according to the RAPS method, the AlexNet algorithm with a classical GWO yielded the optimum model, achieving a classification accuracy of 94.5%. This work presents the first study on benchmarking skin cancer classification with many models. Feature reduction not only reduces the time spent on training but also improves classification accuracy. The RAPS method has proven its robustness in the problem of selecting the best model for skin cancer classification.

Reconstruction method for a three-demensional discrete element numerical model of landslides using an integrated multi-electrode resistivity tomography method and an unmanned aerial vehicle survey

To analyze the hazard-causing modes of landslides, this paper proposes a three-dimensional discrete element model reconstruction method that employs an unmanned aerial vehicle survey and multi-electrode resistivity tomography method. To convert the resistivity profile into a material profile, we adopt the peak of the probability density method for material classification and utilize the Haar wavelet transform for image denoising. Subsequently, inverse distance weighting interpolation and the curtain-point method are used to transform two-dimensional profiles into a 3D visualization model. Similarly, the triangular mesh boundary can be extracted from the 3D visualization model using the curtain-point method. A mapping function f including the macroscopic parameters, was defined to populate the particles within the boundaries. Using the iterative method and defining the loss function L for parameter calibration, the targeted 3D discrete element model was constructed after setting the velocity threshold. This method was applied to the Changhe landslide (September 14, 2019) in Gansu Province, China, which had a typical damaged soil layer due to earthquake and rainfall factors. The results indicate that the lower part first exhibits significant displacement, followed by the upper and middle parts, which is consistent with the on-site inspections and UAV findings.

Multifrequency Analysis of Favored Models for the Messier 87* Accretion Flow

The polarized images of the supermassive black hole Messier 87* (M87*) produced by the Event Horizon Telescope (EHT) provide a direct view of the near-horizon emission from a black hole accretion and jet system. The EHT theoretical analysis of the polarized M87* images compared thousands of snapshots from numerical models with a variety of spins, magnetization states, viewing inclinations, and electron energy distributions, and found a small subset consistent with the observed image. In this article, we examine two models favored by EHT analyses: a magnetically arrested disk with moderate retrograde spin and a magnetically arrested disk with high prograde spin. Both have electron distribution functions that lead to strong depolarization by cold electrons. We ray trace five snapshots from each model at 22, 43, 86, 230, 345, and 690 GHz to forecast future very long baseline interferometry (VLBI) observations and examine limitations in numerical models. We find that even at low frequencies where optical and Faraday rotation depths are large, approximately rotationally symmetric polarization persists, suggesting that shallow depths dominate the polarization signal. However, morphology and spectra suggest that the assumed thermal electron distribution is not adequate to describe emission from the jet. We find 86 GHz images show a ringlike shape determined by a combination of plasma and spacetime imprints, smaller in diameter than recent results from the Global mm-VLBI Array. We find that the photon ring becomes more apparent with increasing frequency, and is more apparent in the retrograde model, leading to large differences between models in asymmetry and polarization structure.

Bootstrap Method as a Tool for Analyzing Data with Atypical Distributions Deviating from Parametric Assumptions: Critique and Effectiveness Evaluation

In today’s research environment characterized by exponential data growth and increasing complexity, the selection of appropriate statistical tests, tailored to research objectives and data distributions, is paramount for rigorous analysis and accurate interpretation. This article explores the growing prominence of bootstrapping, an advanced statistical technique for multiple comparisons analysis, offering flexibility and customization by estimating sample distributions without assuming population distributions, thus serving as a valuable alternative to traditional methods in various data scenarios. Computer simulations were conducted using data from cardiovascular disease patients. Two approaches, spontaneous partly controlled simulation and fully constrained simulation using self-written R scripts, were utilized to generate datasets with specified distributions and analyze the data using tests for comparing more than two groups. The utilization of the bootstrap method greatly improves statistical analysis, especially in overcoming the constraints of conventional parametric tests. Our research showcased its effectiveness in comparing multiple scenarios, yielding strong findings across diverse distributions, even with minor inflation in p values. Serving as a valuable substitute for parametric approaches, bootstrap promotes careful consideration when rejecting hypotheses, thus fostering a deeper understanding of statistical nuances and bolstering analytical rigor.