Search Results (8,477)

Traditional vehicle emergency braking research suffers from inaccurate maximum road adhesion coefficient identification and suboptimal wheel slip ratio control. To address these challenges in electronic hydraulic braking systems’ anti-lock braking technology, firstly, this paper proposes a CDOA-SENet-CNN neural network to precisely estimate the maximum road adhesion coefficient by monitoring and analyzing the braking process. Secondly, correlation curves between peak adhesion coefficients and ideal slip ratios are established using the Burckhardt model and CarSim 2020, and the estimated maximum adhesion coefficient from the CDOA-SENet-CNN network is used with these curves to determine the optimal slip ratio for the single-neuron integral sliding mode control (SNISMC) algorithm. Finally, an SNISMC control strategy is developed to adjust the wheel slip ratio to the optimal value, achieving stable wheel control across diverse road surfaces. Results indicate that the CDOA-SENet-CNN network rapidly and accurately estimates the peak braking surface adhesion coefficient. The SNISMC control strategy significantly enhances wheel slip ratio control, consequently increasing the effectiveness of vehicle brakes. This paper introduces an innovative, stable, and efficient solution for enhancing vehicle braking safety. Full article

Chickpea is a highly weed-prone crop with limited herbicide options and high labor demands, raising the following question: Can fall-planted legume–cereal cover crops (CCs) improve soil properties while reducing herbicide use and manual weeding pressure? To explore this, we evaluated the effect of fall-planted winter rye (WR) alone in 2021 and mixed with hairy vetch (HV) in 2022 and 2023 at Randolph farm in Petersburg, Virginia. The objectives were two-fold: (a) to examine the effect of CCs on soil properties using monthly growth dynamics and biomass harvested from fifteen 0.25 m²-quadrants and (b) to evaluate the efficiency of five termination methods: (1) green manure (GM); (2) GM plus pre-emergence herbicide (GMH); (3) burn (BOH); (4) crimp mulch (CRM); and (5) mow-mulch (MW) in suppressing weeds in chickpea fields. Weed distribution, particularly nutsedge, was patchy and dominant on the eastern side. Growth dynamics followed an exponential growth rate in fall 2022 (R² ≥ 0.994, p < 0.0002) and a three-parameter sigmoidal curve in 2023 (R² ≥ 0.972, p < 0.0047). Biomass averaged 55.8 and 96.9 t/ha for 2022 and 2023, respectively. GMH consistently outperformed GM in weed suppression, though GM was not significantly different from no-till systems by the season’s end. Kabuli-type chickpeas under GMH had significantly higher yields than desi types. Pooled data fitted well to a three-parametric logistic curve, predicting half-time to 50% weed coverage at 35 (MM), 38 (CRM), 40 (BOH), 46 (GM), and 53 (GMH) days. Relapses of CCs were consistent in no-till systems, especially BOH and MW. Although soil properties improved, CCs alone did not significantly suppress weed. Full article

This study investigates the hot deformation behaviour and microstructural evolution of two AISI 430 ferritic stainless steel variants: 0A (basic) and 1C (modified). These variants primarily differ in chemical composition, with 0A containing higher austenite-stabilizing elements (C, N) compared to 1C, which features lower interstitial content and slightly higher Si and Cr. This research aimed to optimize hot rolling conditions for enhanced forming properties. Uniaxial hot compression tests were conducted using a Gleeble thermo-mechanical system between 850 and 990 ${}^{\circ }$C at a strain rate of 3.3 s${}^{-1}$, simulating industrial finishing mill conditions. Analysis of flow curves, coupled with detailed microstructural characterization using electron backscatter diffraction, revealed distinct dynamic restoration mechanisms influencing each material’s response. Thermodynamic simulations confirmed significant austenite formation in both materials within the tested temperature range, notably affecting their deformation behaviour despite their initial ferritic state. Material 0A consistently exhibited a strong tendency towards dynamic recrystallization (DRX) across a wider temperature range, particularly at 850 ${}^{\circ }$C. DRX led to a microstructure with a high concentration of low-angle grain boundaries and sharp deformation textures, actively reorienting grains towards energetically favourable configurations. However, under this condition, DRX did not fully complete the recrystallization process. In contrast, material 1C showed greater activity of both dynamic recovery and DRX, leading to a much more advanced state of grain refinement and recrystallization compared to 0A. This indicates that the composition of 1C helps mitigate the strong influence of the deformation temperature on the crystallographic texture, leading to a weaker texture overall than 0A. Full article

Reliable estimates of aquifer properties are needed for groundwater resources management and for engineering applications. Pumping tests conducted in fractured aquifers using an open borehole may not produce a proper characterization of the aquifer properties leading to the failure of engineering solutions. In this work, we apply a radial flow model to reproduce the time drawdown curves recorded at an observation borehole instrumented with multi-level piezometers drilled in the Permo-Triassic sandstone, which is a complex fractured hydraulic unit. The radial flow model and the optimization code PEST are used to estimate the aquifer hydraulic parameter values. The model is then used to investigate the implications of replacing the multi-level piezometers with an open borehole. The results show that the open borehole does not only significantly alter the groundwater head and flow patterns around the borehole, but the analysis of the time drawdown curve obtained would produce estimates of aquifer properties that bear no relationship with the actual hydraulic properties of the aquifer. For engineering control studies, the pumping test must be carefully designed to account for the presence of fractures, and these must be represented in the analysis tools to ensure the correct characterization of the hydraulic system. Full article

A geodesic or geodetic line on a sphere is called the orthodrome. Research has shown that the orthodrome can be defined in a large number of ways. This article provides an overview of various definitions of the orthodrome. We recall the definitions of the orthodrome according to the greats of geodesy, such as Bessel and Helmert. We derive the equation of the orthodrome in the geographic coordinate system and in the Cartesian spatial coordinate system. A geodesic on a surface is a curve for which the geodetic curvature is zero at every point. Equivalent expressions of this statement are that at every point of this curve, the principal normal vector is collinear with the normal to the surface, i.e., it is a curve whose binormal at every point is perpendicular to the normal to the surface, and that it is a curve whose osculation plane contains the normal to the surface at every point. In this case, the well-known Clairaut equation of the geodesic in geodesy appears naturally. It is found that this equation can be written in several different forms. Although differential equations for geodesics can be found in the literature, they are solved in this article, first, by taking the sphere as a special case of any surface, and then as a special case of a surface of rotation. At the end of this article, we apply calculus of variations to determine the equation of the orthodrome on the sphere, first in the Bessel way, and then by applying the Euler–Lagrange equation. Overall, this paper elaborates a dozen different approaches to orthodrome definitions. Full article

Canine visceral leishmaniasis (CVL) is a major zoonosis that poses a growing challenge to public health services, as successful disease management requires sensitive, specific, and rapid diagnostic methods capable of identifying infected animals even at a subclinical level. The objective of this study was to evaluate the performance of the recombinant chimeric protein rMELEISH3 as an antigen in ELISA assays for the robust diagnosis of CVL. The protein was expressed in a bacterial system, purified by affinity chromatography, and evaluated through a series of serological assays using serum samples from dogs infected with Leishmania infantum. ROC curve analysis revealed a diagnostic sensitivity of 96.4%, a specificity of 100%, and an area under the curve of 0.996, indicating excellent discriminatory power. Furthermore, rMELEISH3 was recognized by antibodies present in the serum of dogs with low parasite loads, reinforcing the diagnostic potential of the assay in asymptomatic cases. It is concluded that the use of the recombinant antigen rMELEISH3 could significantly contribute to the improvement of CVL surveillance and control programs in endemic areas of Brazil and other countries, by offering a safe, reproducible and effective alternative to the methods currently recommended for the serological diagnosis of the disease. Full article

This study addresses the complex challenges associated with flexible mattress (soft mattress) installation in the sharply curved and deep-water sections of the Yangtze River, particularly in the Yaozui revetment reconstruction project. Under extreme hydrodynamic conditions—water depths exceeding 30 m and velocities over 2.5 m/s—the risk of structural failures such as displacement, flipping, or tearing of the mattress becomes significant. To improve construction safety and stability, the study integrates numerical modeling and on-site strain monitoring to analyze the mechanical response of flexible mattresses during deployment. A three-dimensional finite element model based on the catenary theory was developed to simulate stress distributions under varying flow velocities and angles, revealing stress concentrations at the mattress’s upper edge and reinforcement junctions. Concurrently, a real-time monitoring system using high-precision strain sensors was deployed on critical shipboard components, with collected data analyzed through a remote IoT platform. The results demonstrate strong correlations between mattress strain, flow velocity, and water depth, enabling the identification of high-risk operational thresholds. The proposed monitoring and early-warning framework offers a practical solution for managing construction risks in extreme riverine environments and contributes to the advancement of intelligent construction management for underwater revetment works. Full article

Determining charge and discharge behavior is essential for optimizing charging strategies and evaluating balancing algorithms in battery energy storage systems and electric vehicles. Conventionally, a sequence of circuit simulations or tedious hardware tests is required to evaluate the performance of the balancing algorithm. To mitigate these problems, this paper proposes a variable capacitor model that can be easily built from the incremental capacity curve. This model provides a direct and insightful R-C time constant method for the charge/discharge time calculation. After validating the model accuracy by experimental results based on the cylindrical lithium-ion cell test, a switched-capacitor active balancing and a passive cell balancing circuit are implemented to further verify the effectiveness of the proposed model in calculating the cell balancing time within 2% error. Full article

Background/Objectives: Diabetic retinopathy is a leading cause of vision impairment worldwide, and the development of reliable automated classification systems is crucial for early diagnosis and clinical decision-making. This study presents a comprehensive comparative evaluation of two state-of-the-art deep learning families for the task of classifying diabetic retinopathy using retinal fundus images. Methods: The models were trained and tested in both binary and multi-class settings. The experimental design involved partitioning the data into training (70%), validation (20%), and testing (10%) sets. Model performance was assessed using standard metrics, including precision, sensitivity, specificity, F1-score, and the area under the receiver operating characteristic curve. Results: In binary classification, the ResNeXt101-64x4d model and RegNetY32GT model demonstrated outstanding performance, each achieving high sensitivity and precision. For multi-class classification, ResNeXt101-32x8d exhibited strong performance in early stages, while RegNetY16GT showed better balance across all stages, particularly in advanced diabetic retinopathy cases. To enhance transparency, SHapley Additive exPlanations were employed to visualize the pixel-level contributions for each model’s predictions. Conclusions: The findings suggest that while ResNeXt models are effective in detecting early signs, RegNet models offer more consistent performance in distinguishing between multiple stages of diabetic retinopathy severity. This dual approach combining quantitative evaluation and model interpretability supports the development of more robust and clinically trustworthy decision support systems for diabetic retinopathy screening. Full article

Herein, the energy dispersion relationship and the density of states of triangular and rectangular moiré patterns are investigated using a tight binding model. Their characteristics of Hofstadter butterflies under different magnetic fields are also examined. The results indicate that, by analyzing different moiré superlattices, Hofstadter butterflies arising from different moiré pattern structures are obtained, exhibiting considerable fractal characteristics and self-similarities. Moreover, it is also observed that under an alternating magnetic field, the redistribution of electronic states leads to a significant change in the density of states curve, and the Van Hove peak changes with the increase in magnetic field intensity. This study enriches the understanding of the electronic behavior of moiré systems, but it also provides multiple potential application directions for future technological development. Full article

Today, blockchain technologies are a separate, rapidly developing area. With rapid development, they open up a number of scientific problems. One of these problems is the problem of reliability, which is primarily associated with the use of cryptographic primitives. The threat of the emergence of quantum computers is now widely discussed, in connection with which the direction of post-quantum cryptography is actively developing. Nevertheless, the most popular blockchain platforms (such as Bitcoin and Ethereum) use asymmetric cryptography based on elliptic curves. Here, cryptographic primitives for blockchain systems are divided into four groups according to their functionality: keyless, single-key, dual-key, and hybrid. The main attention in the work is paid to the most significant cryptographic primitives for blockchain systems: keyless and single-key. This manuscript discusses possible scenarios in which, during practical implementation, the mathematical foundations embedded in the algorithms for generating a digital signature and encrypting data using algorithms based on elliptic curves are violated. In this case, vulnerabilities arise that can lead to the compromise of a private key or a substitution of a digital signature. We consider cases of vulnerabilities in a blockchain system due to incorrect use of a cryptographic primitive, describe the problem, formulate the problem statement, and assess its complexity for each case. For each case, strict calculations of the maximum computational costs are given when the conditions of the case under consideration are met. Among other things, we present a new version of the encryption algorithm for data stored in blockchain systems or transmitted between blockchain systems using elliptic curves. This algorithm is not the main blockchain algorithm and is not included in the core of modern blockchain systems. This algorithm allows the use of the same keys that system users have in order to store sensitive user data in an open blockchain database in encrypted form. At the same time, possible vulnerabilities that may arise from incorrect implementation of this algorithm are considered. The scenarios formulated in the article can be used to test the reliability of both newly created blockchain platforms and to study long-existing ones. Full article

Background/Objectives: Platelet activity contributes to myocardial infarction; inadequate inhibition is a risk factor for stent thrombosis and mortality. Inadequate platelet inhibition during treatment is an important risk factor for stent thrombosis and may be associated with increased mortality. This study assessed platelet and coagulation activity in post-MI patients, identifying parameters associated with adverse ST-elevation myocardial infarction (STEMI) outcomes over 3 years, to identify patients needing intensive secondary prevention. Methods: From 57 admitted patients, 19 STEMI patients were analyzed. Thromboelastography (TEG) and Total Thrombus Formation Analysis System (T-TAS) were used to assess hemostasis and coagulation. Selected laboratory parameters were measured for correlations. Major adverse cardiovascular events (MACEs) were defined as ischemic stroke, myocardial infarction, ischemic heart disease, thrombosis, and death from cardiovascular causes. Results: The group with MACEs was characterized by a faster time to initial clot formation and greater reflection of clot strength. T-TAS parameters, such as area under the curve at 10 min (T-TAS AUC10), showed lower values in the same group of patients. A moderate positive correlation suggested that as white blood cell count increases, T-TAS AUC10 values also tend to increase. A strong negative correlation (rho = −1.000, p < 0.01) was observed between low-density lipoprotein and kinetics in the TEG using the kaolin test at baseline in patients with MACEs. Conclusions: Some of the parameters suggest they are associated with adverse outcomes of STEMI, indicate the existence of an inflammatory state, and may contribute to risk stratification of STEMI patients and identify who will require ongoing monitoring. Full article

Rainwater harvesting for sustainable agriculture (RWHSA) offers a viable and eco-friendly strategy to alleviate water scarcity in semi-arid regions, particularly for agricultural use. This study aims to identify optimal sites for implementing RWH systems in northern Iraq to enhance water availability and promote sustainable farming practices. An integrated geospatial approach was adopted, combining Remote Sensing (RS), Geographic Information Systems (GIS), and Multi-Criteria Decision Analysis (MCDA). Key thematic layers, including soil type, land use/land cover, slope, and drainage density were processed in a GIS environment to model runoff potential. The Soil Conservation Service Curve Number (SCS-CN) method was used to estimate surface runoff. Criteria were weighted using the Analytical Hierarchy Process (AHP), enabling a structured and consistent evaluation of site suitability. The resulting suitability map classifies the region into four categories: very high suitability (10.2%), high (26.6%), moderate (40.4%), and low (22.8%). The integration of RS, GIS, AHP, and MCDA proved effective for strategic RWH site selection, supporting cost-efficient, sustainable, and data-driven agricultural planning in water-stressed environments. Full article

Personal Rapid Transit (PRT) and Group Rapid Transit (GRT) are classes of fully automated public transport systems, where passengers can travel in small vehicles on an interconnected, grade-separated network of guideways, non-stop, from origin to destination. PRT and GRT are considered sustainable as they are low-emission and able to attract car drivers. The parameterized cost modeling framework developed in this paper has the advantage that profitability of different PRT/GRT systems can be rapidly verified in a transparent way and in function of a variety of relevant system parameters. This framework may contribute to a more transparent, rapid, and low-cost evaluation of PRT/GRT schemes for planning and decision-making purposes. The main innovation is the introduction of the “peak hour network saturation” S: the number of vehicles in circulation during peak hour divided by the maximum number of vehicles running at line speed with minimum time headways. It is an index that aggregates the main uncertainties in the planning process, namely the demand level relative to the supply level. Furthermore, a maximum S can be estimated for a PRT/GRT project, even without a detailed demand estimation. The profit per trip is analytically derived based on S and a series of more certain parameters, such as fares, capital and maintenance costs, daily demand curve, empty vehicle share, and physical properties of the system. To demonstrate the ability of the framework to analyze profitability in function of various parameters, we apply the methods to a single vehicle PRT, a platooned PRT, and a mixed PRT/GRT. The results show that PRT services with trip length proportional fares could be profitable already for $S>0.25$. The PRT capacity, profitability, and robustness to tripled infrastructure costs can be increased by vehicle platooning or GRT service during peak hours. Full article

In order to achieve 0.1 m resolution and fully polarimetric observation capabilities for airborne SAR systems, the adoption of stepped-frequency modulation waveform combined with the polarization time-division transmit/receive (T/R) technique proves to be an effective technical approach. Considering the issue of range resolution degradation and paired echoes caused by multichannel amplitude–phase mismatch in fully polarimetric airborne SAR with 0.1 m resolution, an amplitude–phase error estimation algorithm based on echo data is proposed in this paper. Firstly, the subband amplitude spectrum correction curve is obtained by the statistical average of the subband amplitude spectrum. Secondly, the paired-echo broadening function is obtained by selecting high-quality sample points after single-band imaging and the nonlinear phase error within the subbands is estimated via Sinusoidal Frequency Modulation Fourier Transform (SMFT). Thirdly, based on the minimum entropy criterion of the synthesized compressed pulse image, residual linear phase errors between subbands are quickly acquired. Finally, two-dimensional cross-correlation of the image slice is utilized to estimate the positional deviation between polarization channels. This method only requires high-quality data samples from the echo data, then rapidly estimates both intra-band and inter-band amplitude/phase errors by using SMFT and the minimum entropy criterion, respectively, with the characteristics of low computational complexity and fast convergence speed. The effectiveness of this method is verified by the imaging results of the experimental data. Full article