Uniform Method Research Articles

Structural and performance optimization of PVAc-modified UP resin permeable concrete

Permeable concrete (PC), composed of silicate cement, offers advantages such as cost efficiency, low shrinkage after curing, and excellent water permeability. However, compared to conventional cement concrete, PC exhibits lower mechanical strength and durability. Recent advancements have demonstrated that incorporating resin composites into PC effectively enhances its mechanical properties and durability, leading to the development of high-strength polymer permeable concrete (HPPC). Common resin composites include thermosetting resins such as epoxy resin and unsaturated polyester resin (UP resin), which are characterized by rapid curing, high strength, and durability, making them suitable adhesives for permeable concrete. This study introduces polyvinyl acetate (PVAc) as a low-shrinkage additive to UP resin. PVAc’s favorable polarity and low shrinkage behavior effectively mitigate shrinkage-induced defects such as internal cracks and bubbles during curing. To further optimize the material composition, the Uniform Design Method (UDM) was employed to design and optimize the proportions of UP resin, PVAc, and curing agent. Data analysis using genetic algorithms in MATLAB was combined with Kriging models to map the interactions between material ratios and performance. The goal was to determine the optimal PVAc addition ratio to minimize structural defects, thereby improving compressive strength and durability. Abrasion resistance tests were conducted to compare the performance of the developed materials with conventional modified asphalt. The findings demonstrate that incorporating PVAc effectively enhances structural stability, compressive performance, and abrasion resistance of UP resin-based permeable concrete. This research offers a novel approach to improving the durability of permeable pavement systems, providing valuable insights for future applications in sustainable infrastructure.

Using a harmonised study design and quantitative tool-box reveals major inconsistencies when investigating the main drivers of water and biofilm antibiotic resistomes in different rivers.

The spread of antibiotic resistance (ABR) via surface waters is of increasing concern. Large-scale studies investigating ABR drivers in different water bodies and habitats with uniform quantitative methods are largely missing. Here, we present a comprehensive investigation on ABR occurrence and drivers in water and biofilms of four Austrian rivers over a one-year-cycle using a harmonised quantitative tool-box and study-design. At the bacterial community level, human faecal pollution was a main factor driving the aquatic riverine resistome. Despite relatively low concentrations, also antibiotics and metals showed significant correlations, however to a different extent in the different rivers. At the organismic level, a decoupling of the Escherichia coli resistome from the bacterial community resistomes was observed. In biofilms, the relationships with anthropogenic pollution factors were heterogeneous and markedly dampened. Our results clearly show that general conclusions about the role of biofilms, the influence of pollution or the prevalence of resistance genes or phenotypic resistances must be drawn with caution. Results are dependent on the river and local situation of the sampling sites due to the large environmental heterogeneity. International harmonisation of the methodology and general awareness of this problem shall contribute to better understand environmental ABR to develop effective mitigation strategies.

Research on the bulging process of aluminum alloy four-way tube with solid granules medium

ABSTRACT This study presents a novel bulging process for aluminum alloy four-way tubes with solid granules medium. The proposed method aims to enhance forming precision and minimize defects in the internal high-pressure forming process. The behavior of bulging process of aluminum alloy four-way tubes with solid granules medium (SGM) is systematically investigated through comprehensive experimental methodologies. This study explored the critical effects of temperature, back pressure, and associated process parameters on the fundamental forming mechanism. The solid granules medium bulging process successfully produced a four-way tube with an expansion height of 102.14 mm. A three-dimensional finite element method-discrete element method coupling model (FEM-DEM coupling model) is developed based on the uniform load distribution method. The experimental results verified the accuracy of this model, with a maximum deviation of 12.7% between the simulated wall thickness and the experimental data, demonstrating good consistency in the overall deformation pattern.

Stability and Convergence Analysis of a Robust Numerical Scheme for the Variable Coefficient Multiterm Time‐Fractional Convection–Reaction–Diffusion Equation With Nonsmooth Solution

ABSTRACTIn this paper, we propose a numerical scheme for approximating the solution of a variable coefficient multiterm Caputo time‐fractional convection–reaction–diffusion (MTCTFCRD) model, which generally exhibits a weak singularity at . The L1 technique is used to discretize the time‐fractional derivative (TFD) on a nonuniform mesh, while the space derivative is discretized on a uniform mesh using a fourth‐order compact finite difference (CFD) technique. The stability analysis of the method is introduced. The convergence analysis of the method is also rigorously investigated. Numerical examples are presented to corroborate in practice the accuracy and efficiency of the proposed technique and to validate the theoretical results as well. To justify the advantage of the suggested scheme, we compare the outcomes with those obtained by the uniform mesh technique. It is shown that the nonuniform mesh method attains an optimal‐order convergence in the temporal direction, whereas the uniform grid method fails to deliver an optimal order of convergence. The method is of fourth‐order accuracy in space. The computational times for the proposed numerical scheme have been provided.

A fast simulation method for millimeter-wave radiation images of rough sea surface

ABSTRACT Ray tracing method is used to simulate millimeter-wave radiation brightness temperature images. This paper proposes a cache – based non – uniform ray acceleration method to solve the low efficiency of the traditional ray tracing method in simulating millimeter-wave radiation images. Unlike the fast simulation methods proposed by Qi (2016) and Yin (2017), this method reduces the number of scattered rays on a rough surface. It adjusts the scattered ray density according to the reflectivity change rate and introduces a caching mechanism. This enables fast simulation of millimeter – wave radiation images of rough sea surfaces. To validate the correctness of the method, the comparison results of the simulation and measurement are proposed. The results show the correctness and acceleration efficiency of the method.

New Applications of Elliptic Functions and Integrals in GPS Inter-Satellite Communications with Account of General Relativity Theory

During the last 15–20 years, the experimental methods for autonomous navigation and inter-satellite links have been developing rapidly in order to ensure navigation control and data processing without commands from Earth stations. Inter-satellite links are related to relative ranging between the satellites from one constellation or different constellations and measuring the distances between them with the precision of at least 1 μm micrometer (=10−6 m), which should account for the bending of the light (radio or laser) signals due to the action of the Earth’s gravitational field. Thus, the theoretical calculation of the propagation time of a signal should be described in the framework of general relativity theory and the s.c. null cone equation. This review paper summarizes the latest achievements in calculating the propagation time of a signal, emitted by a GPS satellite, moving along a plane elliptical orbit or a space-oriented orbit, described by the full set of six Kepler parameters. It has been proved that for the case of plane elliptical orbit, the propagation time is expressed by a sum of elliptic integrals of the first, the second and the third kind, while for the second case (assuming that only the true anomaly angle is the dynamical parameter), the propagation time is expressed by a sum of elliptic integrals of the second and of the fourth order. For both cases, it has been proved that the propagation time represents a real-valued expression and not an imaginary one, as it should be. For the typical parameters of a GPS orbit, numerical calculations for the first case give acceptable values of the propagation time and, especially, the Shapiro delay term of the order of nanoseconds, thus confirming that this is a propagation time for the signal and not for the time of motion of the satellite. Theoretical arguments, related to general relativity and differential geometry have also been presented in favor of this conclusion. A new analytical method has been developed for transforming an elliptic integral in the Legendre form into an integral in the Weierstrass form. Two different representations have been found, one of them based on the method of four-dimensional uniformization, exposed in the monograph of Whittaker and Watson. The result of this approach is a new formulae for the Weierstrass invariants, depending in a complicated manner on the modulus parameter q of the elliptic integral in the Legendre form.

Application of the Neurofunctional Psychomotor Test for Groups of Children ages 3-14 in Cuenca, Ecuador: A Statistical Analysis of Group Correlations

This study was designed to determine if the Neurofunctional Psychomotor Test developed by Elena Simonetta for children and young people from 3 to 14 years old is applicable to the local and regional context of the city of Cuenca, Ecuador. A sample of 793 children and young people was obtained from a universe of 70,838 students through cluster sampling. Fifteen parishes were sampled and the optimal Neyman proportional stratified sampling was applied. The Neurofunctional Psychomotor Test was administered to all 793 students. The results obtained using the uniform rectangular distribution method showed that 75% of the children passed the test. A statistical correlation method was used to determine the linear association between continuous variables. Significant correlations were determined within 95% confidence limits in: correct laterality and temporal perceptions; general dynamic coordination with the postural adjustment variable and tonic control. These significant correlations allowed us to confirm that the Neurofunctional Psychomotor Test was valid when applied to children ages 3-14 in Cuenca, Ecuador. In addition, correlations between pairs of variables were studied for each age group, and cluster analysis methods were applied to investigate global similarities among the variables under study for each age group.

A novel inversion method of slope rock mechanical parameters using differential evolution gray wolf algorithm to optimize support vector regression

IntroductionThe stability evaluation and deformation prediction in geotechnical engineering depend on accurate rock mass mechanical parameters (RMMPs). The selection of these parameters directly influences the reliability of analysis. The conventional techniques used to assess the RMMPs face considerable challenges in real-world applications, which necessitates the need to investigate novel approaches.MethodsThis paper proposes a displacement back-analysis (DBA) approach that utilizes support vector regression (SVR) optimized by differential evolution grey wolf algorithm (DE-GWO) to invert the RMMPs, which improves global optimization capability and inversion accuracy. Firstly, the uniform test design method is employed to outline the RMMPs for inversion, anddisplacement calculations are performed using FLAC3D to generate learning and testing samples. Secondly, the DE-GWO, particle swarm optimization (PSO), genetic algorithm (GA), and SVR are integrated to identify the optimal superparameters, while the nonlinear mapping relationship between inversion parameters and displacements is established. Finally, the mechanical parameters to be measured are inversed based on field-measured displacements. This model is utilized to invert the RMMPs for a mining site located in Yunnan Province, and the inversed RMMPs are utilized for forward analysis. The results demonstrate that the DE-GWO-SVR method achieves the best results but requires the shortest inversion time.ResultsThe inversed RMMPs fall within acceptable ranges, while the error between the forward and monitored displacements is less than 10%, with a maximum deviation of 9.52%. This research introduces an innovative approach for assessing the RMMPs.

Two Objects of the KGB Secret Activities

In this article, we will expose two aspects of the KGB’s activities that are, from a surface point of view, not very closely interrelated – technological espionage and the fight against supporters of Lithuanian independence. All of these were carried out by the same organiser of covert activities – the KGB. The diversity of its methods and operations, the convergence of its covert operations, mixed and uniform methods make it necessary to investigate and gain a better understanding of the KGB’s entire arsenal.

Model correction for loss and deviation angle of compressor cascade based on multiple nonlinear regression

The performance prediction accuracy of quasi-3D design is highly dependent on the empirical correlation model. The state of art model from experimental data is hard to meet the request of new blade development and higher aerodynamic design demand. In order to solve the problem by ignoring the influence of blade thickness position on the Reynolds number correction model, numerical research based on the middle section of the low-pressure compressor rotor is conducted. The sample database is constructed based on a uniform sampling method considering the incidence, thickness, and Reynolds number at a certain inlet Mach number, and the new model to design and off-design condition is both established by multiple nonlinear regression and adaptive simulated annealing algorithm. The results show that the root-mean-square error of the total pressure loss is reduced by 78.92% and 60.22%, error of the deviation angle is reduced by 78.44% and 78.56%, under design and off-design incidence angles respectively. The new model can provide more reliable predicted results for modern compressor design and optimization.

The Main Factors Affecting the Minimum Sampling Area Determination Method: Based on Research of the Shrub Layer in Island Pinus massoniana Forests

Determining the minimum sampling area is crucial for accurate and cost-effective biodiversity surveys. This study identifies the main factors (e.g., species richness and evenness) influencing the inflection point method and precision method, aiming to scientifically establish the minimum sampling area for studying the shrub layer diversity of the Pinus massoniana community on Sandu Island, Ningde. Using 64 nested samples (20 m × 20 m) from eight sampling plots, we analyzed the species–area relationship and minimum sampling area. Key findings include the following: (1) The power function model (S = 4.053A0.404) best described the species–area relationship. (2) Species richness significantly influenced the inflection point method, with rare species increasing the required sampling area. (3) Species distribution uniformity and sampling methods affected model outcomes. (4) Repeated sampling from the four corners of the plots reduced bias caused by uneven species distribution. (5) Considering cost, accuracy, and inflection points, a minimum sampling area of 142 m2 achieved 70% sampling accuracy. This study provides a methodological framework for accurate minimum sampling area analysis and offers valuable insights for biodiversity studies of P. massoniana shrub layers in island ecosystems, with implications for international research on similar forest communities.

Invasive Approach to Verification of Functional and Structural Specifications Implemented in Custom Integrated Circuits

An approach to verification of functional and structural specifications implemented in custom integrated circuits based on invasive research methods is presented. The relevance of this research is determined by the necessity of verification of functional-structural specifications supplied by third-party implementers of hardware implementations of information security algorithms, the difficulty of detecting modifications of these algorithms and undocumented capabilities implemented at the hardware level, and the lack of uniform, universal or standardized methods for solving this problem. The mathematical formulation of the research problem is specified; its essence is to verify the equality of the values of the declared specification parameters and their values restored by the reverse engineering method. The results of the application of the verification technique of functional and structural specifications are presented using examples of its adaptation to the study of hardware-implemented DES and AES encryption algorithms. The restored functional and structural blocks of the algorithms (in particular, the substitution block) were successfully verified.

Uniform fabrication method for large area nanostructure gratings by suppressing scanning etching periodic errors based on frequency domain analysis

Uniform fabrication method for large area nanostructure gratings by suppressing scanning etching periodic errors based on frequency domain analysis

Characteristic Representation of Stock Time Series Data Based on Trend Extreme Points of K-line Combinations

The study of stock time series has been an important area of research in economics, finance, and management. Time series feature representation serves as the primary approach for studying time series. The K-line chart is a common representation of stock time series data. This study proposes a segmented representation method KCTEP based on the extreme points of stock K-line portfolio trend for K-line chart data, which is validated in sequence compression rate and distance metric. The experimental results show that the KCTEP method significantly improves the trend description by 8.63% and the compression rate by 2.95% when compared with the uniform extreme point representation method and the piecewise aggregation approximation method (PAA).The results lead to significant enhancement of the trend description effect and reduction of the distance metric error.

Physicochemical Parameters and Multivariate Analysis to Predict the Sensory Quality in Specialty Coffee from Panama.

This study assessed the effectiveness of various multivariate calibration models in predicting the sensory evaluation scores of specialty coffee produced in Panama. The predictions were based on seven key physicochemical parameters of the beverage, considering the processing method used (natural or washed). To construct the models, three algorithms, Multiple Linear Regression (MLR), Principal Component Regression (PCR), and Partial Least Squares Regression (PLSR), were employed, analyzing data sets for natural, washed, and combined processing methods. Model quality was evaluated using metrics such as the coefficient of determination (R2), root-mean-square error (RMSE) for cross-validation and prediction, and the residual predictive deviation (RPD). Among the physicochemical parameters, titratable acidity, soluble solids, and protein content showed a positive correlation with sensory scores, whereas pH exhibited an inverse relationship. The best-performing MLR and PCR models were those for the natural process, achieving R2p, RMSEp, and RPD values of 0.8293, 0.4239, and 2.34 for MLR and 0.7233, 0.5322, and 1.86 for PCR, respectively. Across all algorithms, models built exclusively with data from a single processing method consistently outperformed those that combined samples from both processes. PLSR models further demonstrated this trend, with R2p values of 0.7639 and 0.8306, RMSEp of 0.6891 and 0.3948, and RPD values of 2.07 and 2.51 for the washed and natural processes, respectively. In conclusion, the study highlights the critical importance of considering processing methods when developing multivariate models to predict the sensory evaluation scores of specialty coffee. Models built with samples from a uniform processing method yielded significantly better performance than those developed using mixed-process data sets.

Inversion and analysis of leaf area index (LAI) of urban park based on unmanned aerial vehicle (UAV) multispectral remote sensing and random forest (RF).

Leaf Area Index (LAI) is a critical indicator of vegetation growth and ecological function. Unlike the relatively uniform crop types and planting methods typically found in agricultural fields, parks typically feature a diverse range of plant species, varied configurations, and complex vertical structures, making LAI estimation more complex and challenging. To improve the accuracy of LAI estimation in urban parks, this study, by combining unmanned aerial vehicle (UAV) multispectral remote sensing technology with Random Forest (RF) to conduct the inversion and analysis of LAI in Xinxiang People's Park. High-resolution images are obtained using multispectral sensors carried by a UAV, which are then used to calculate the Normalized Difference Vegetation Index (NDVI). Combined with ground-measured vegetation LAI data, this study applies RF to estimate the park LAI. The results indicate that the average LAI of Xinxiang People's Park is 2.30 (for the entire park). excluding the hard surfaces (which account for 36.05%), the average LAI increases to 3.59, indicating good vegetation conditions. The LAI of the park and its distribution are influenced by factors such as plant species, configuration patterns, planting density, aesthetic design, and site function. Accurate LAI inversion is crucial for effective management and optimization of these green spaces. RF can effectively capture the complex nonlinear relationship between NDVI and LAI, with a coefficient of determination (R²) of 0.54 and a root mean square error (RMSE) of 0.91. Although the accuracy is still insufficient, RF's ability to handle nonlinear relationships makes it an effective tool for LAI inversion in complex vegetation environments. LAI inversion of park vegetation based on UAV multispectral imagery can provide valuable insights for the management and optimization of park vegetation.

HemAtlas: A Multi-omics Hematopoiesis Database.

Advancements in high-throughput omics technologies have facilitated a systematic exploration of crucial hematopoietic organs across diverse species. A thorough understanding of hematopoiesis in vivo and facilitation of generating functional hematopoietic stem and progenitor cells (HSPCs) in vitro necessitate a comprehensive hematopoietic cross-stage developmental landscape across species. To address this need, we developed HemAtlas, a platform designed for the systematic mapping of hematopoiesis both in vivo and in vitro. HemAtlas features detailed analyses of multi-omics datasets from humans, mice, zebrafish, and HSPC in vitro culture systems. Utilizing literature curation and data normalization, HemAtlas integrates various functional modules, allowing interactive exploration and visualization of any collected omics data based on user-specific interests. Moreover, by applying a systematic and uniform integration method, we constructed organ-wide hematopoietic references for each species with manually curated cell annotations, enabling a comprehensive decoding of cross-stage developmental hematopoiesis at the organ level. Of particular significance are three distinctive functions-single-cell cross-stage, cross-species, and cross-model analysis-that HemAtlas employs to elucidate the hematopoietic development in zebrafish, mice, and humans, and to offer guidance on the generation of HSPCs in vitro. Simultaneously, HemAtlas incorporates a comprehensive map of HSPC cross-stage development to reveal HSPC stage-specific properties. Taken together, HemAtlas serves as a crucial resource to advance our understanding of hematopoiesis and is available at https://ngdc.cncb.ac.cn/hematlas/.

C9 Petroleum Resin and Polyethylene-Based High-Viscosity Modified Asphalt Binder Proportioning Optimization and Performance Study

This study, based on 90# matrix asphalt binder, investigates the use of SBS, C9 petroleum resin, and polyethylene (PE) as modifiers to prepare high-viscosity modified asphalt binders. Using the uniform design method, the modifier proportions were optimized to meet engineering requirements for high viscosity. The effects of modifier dosages on asphalt binder properties, including penetration, ductility, softening point, and dynamic viscosity, were systematically analyzed, and a multivariate nonlinear regression model was constructed to determine the optimal proportioning. Subsequently, the aging resistance and high-temperature performance of the modified asphalt binders were evaluated through short-term aging tests and rheological property tests. The results show that SBS and PE have a significant positive impact on penetration and softening point, while C9 petroleum resin mainly enhances ductility. The synergistic effect of SBS and PE significantly improves dynamic viscosity. Under the optimal proportioning (SBS 7.5%, C9 petroleum resin 6.0%, PE 5.0%), the high-viscosity modified asphalt binders meet technical standards for key performance indicators. The short-term aging test reveals an elastic recovery ratio exceeding 95%. Rheological performance testing indicates that the modified asphalt binders exhibit excellent rutting resistance and temperature adaptability under high-temperature conditions.

Overcoming antibiotic-resistant Helicobacter pylori infection: Current challenges and emerging approaches.

Recent studies have shown a noticeable increase in global Helicobacter pylori (H. pylori) resistance, with clarithromycin resistance surpassing 15% in various areas. However, inadequate epidemiological monitoring, especially in developing countries, and the absence of uniform testing methods lead to discrepancies between regions and a possible underestimation of resistance levels. The complexity of treating H. pylori is driven by its highly dynamic genome, which is prone to frequent mutations contributing to phenotypical resistance. The usual course of action in empirical treatment involves using a combination of various drugs simultaneously, leading to significant resistance selection pressure and potential side effects. The emergence of H. pylori strains resistant to multiple drugs is closely tied to failures in first-line treatment, highlighting the need to prevent further resistance by using optimal initial empirical therapy or regimens guided by antibiotic susceptibility testing, requiring a collection of mixed samples and multiple isolates for accurate assessment. The emergence of new treatments like potassium-competitive acid blockers offers a hopeful approach to decrease antimicrobial usage while still ensuring effectiveness in comparison to traditional therapies with proton pump inhibitors. Additionally, the use of probiotics is under investigation to identify specific strains and formulations that may mitigate therapy-associated adverse effects.

An Adaptive Grid Generation Approach to Pipeline Leakage Rapid Localization Based on Time Reversal.

Gas pipeline leakage will result in casualties and property losses if not detected in time. Conventional leakage localization methods usually rely on dense grid distribution, leading to high computational costs. This study proposes a time-reversal-based adaptive grid generation approach to enhance computational efficiency in pipeline leakage localization. The method introduces a resolution adjustment parameter to optimize captured signals, allowing for adaptive grid concentration in leakage areas based on energy distribution. Based on this principle, three steps-including signal adjustment computation, adaptive grid generation computation, and conventional TR localization computation based on the adaptive grids-are introduced. Then, an experimental study is conducted on a 55.8 m PVC pipeline with piezoceramic transducers, capturing negative pressure wave signals from four leakage points. The results demonstrate that the proposed approach maintains comparable localization accuracy while reducing the number of grids and localization time to only 0.6% and 2.4% of those required by conventional uniform grid methods, respectively. The findings demonstrate that the proposed method offers a computationally efficient and accurate solution for real-time pipeline leakage monitoring.