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22 pages, 12758 KiB

Open AccessArticle

Optimizing Road Pavement Assessment Using Advanced Image Processing Techniques

by Amir Shtayat, Mohammed T. Obaidat, Bara’ Al-Mistarehi, Ahmad Bader, Sara Moridpour and Saja Alahmad

Sustainability 2025, 17(6), 2473; https://doi.org/10.3390/su17062473 (registering DOI) - 11 Mar 2025

Abstract

The swift advancement in monitoring and evaluation systems for road pavement conditions highlights the crucial role that this field plays in ensuring the sustainability of roads. This, in turn, contributes to the growth and prosperity of nations and enables users to enjoy the [...] Read more.

The swift advancement in monitoring and evaluation systems for road pavement conditions highlights the crucial role that this field plays in ensuring the sustainability of roads. This, in turn, contributes to the growth and prosperity of nations and enables users to enjoy the highest levels of luxury and comfort. Despite numerous studies and ongoing research, finding the most precise and efficient monitoring systems to determine the type and severity of road defects, their causes, and appropriate treatments remains a challenge. This study proposes a system that employs a camera to create an application capable of evaluating road conditions with ease by taking images while driving over the road. Based on the results, the application was accurate in identifying road defects of different severity within the same category. The proposed method was compared to the Pavement Condition Index (PCI) method, and a significant match was found in determining the type and severity of each defect on the selected road sections. More clearly, the overall accuracy of detecting and classifying block cracks, alligator cracks, longitudinal cracks, and potholes was significant for detecting and classifying the patches. Full article

(This article belongs to the Section Sustainable Engineering and Science)

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23 pages, 14258 KiB

Open AccessArticle

Geochemical Variations of Kerolite, Stevensite, and Saponite from the Pre-Salt Sag Interval of the Santos Basin: An Approach Using Electron Probe Microanalysis

by Maurício Dias da Silva, Márcia Elisa Boscato Gomes, André Sampaio Mexias, Manuel Pozo, Susan Martins Drago, Everton Marques Bongiolo, Paulo Netto, Victor Soares Cardoso, Lucas Bonan Gomes and Camila Wense Ramnani

Minerals 2025, 15(3), 285; https://doi.org/10.3390/min15030285 (registering DOI) - 11 Mar 2025

Abstract

This study investigates the mineralogy and chemical characteristics of pre-salt clay minerals, classifies them, and defines assemblages in reactive microsites. Using Electron Probe Micro-Analysis (EPMA), the chemical formulas of Mg-rich clays were determined. Stevensite exhibited low interlayer charge and aluminum content, while kerolite [...] Read more.

This study investigates the mineralogy and chemical characteristics of pre-salt clay minerals, classifies them, and defines assemblages in reactive microsites. Using Electron Probe Micro-Analysis (EPMA), the chemical formulas of Mg-rich clays were determined. Stevensite exhibited low interlayer charge and aluminum content, while kerolite was characterized by a minimal charge. K/S (kerolite/stevensite) mixed layer showed intermediate compositions and charges between these endmembers. Saponite was distinguished by higher levels of Al, K, and Fe, along with a higher interlayer charge. The proposed assemblages are as follows: saponite in mudstone facies (without spherulites/shrubs), with a hybrid matrix; pure kerolite in spherulstone and shrubstone facies, marked by the absence of significant reactions and high preservation of matrix and textures; stevensite in facies with extensive matrix replacement by dolomitization/silicification; and K/S and kerolite in similar facies with intermediate matrix replacement levels and the coexistence of two intimately related clay mineral compositions. This study enables reliable differentiation of these species based on point mineral chemistry and mapping, combined with a microsite approach and conventional techniques. Additionally, it discusses the formation of pre-salt clays, influenced by significant kinetic and chemical interactions during their genesis and burial to depths of approximately 5 km. Full article

(This article belongs to the Special Issue Advances in the Petrography of Natural Fine-Grained Materials: A Microscale Answer to Their Genetic Pathways and Applications)

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32 pages, 6612 KiB

Open AccessArticle

Typology of Small- to Medium-Sized Korean Local Cities with Population Decline from the Perspective of Urban Compactness

by Seon-Yeong Choi and Cheol-Jae Yoon

Sustainability 2025, 17(6), 2470; https://doi.org/10.3390/su17062470 (registering DOI) - 11 Mar 2025

Abstract

This study examines urban structure typologies for small- to medium-sized cities in South Korea facing population decline, with a focus on urban compactness as a sustainable strategy. Population reduction and aging trends have become prominent issues in South Korea, especially impacting smaller cities, [...] Read more.

This study examines urban structure typologies for small- to medium-sized cities in South Korea facing population decline, with a focus on urban compactness as a sustainable strategy. Population reduction and aging trends have become prominent issues in South Korea, especially impacting smaller cities, where decreased population density affects urban service functionality and infrastructure maintenance. This research applies and adapts Japan’s urban structure evaluation framework, specifically designed for the Japanese compact city model, to analyze the spatial conditions of 15 small- and medium-sized cities in Gyeongsangbuk-do province, South Korea. Using various indicators such as population density, accessibility to daily services, public transport, and local economic activity, this study conducts a typological classification based on principal component analysis and clustering methods. The findings suggest distinct urban structure patterns within these cities, offering strategic insights for urban policy aimed at enhancing urban compactness and sustainability. The implications highlight the need for tailored policies that address the spatial reorganization of services and infrastructure to maintain urban viability amidst demographic shifts. Full article

(This article belongs to the Special Issue Urban Vulnerability and Resilience)

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13 pages, 2666 KiB

Open AccessArticle

Intergenerational Transmission of Gut Microbiome from Infected and Non-Infected Salmonella pullorum Hens

by Qing Niu, Kaixuan Yang, Zhenxiang Zhou, Qizhong Huang and Junliang Wang

Microorganisms 2025, 13(3), 640; https://doi.org/10.3390/microorganisms13030640 (registering DOI) - 11 Mar 2025

Abstract

Pullorum disease (PD) is one of the common infectious diseases in the poultry industry in the world. Our previous study showed that gut bacterial structure has a significant difference between positive and negative hens. However, the gut bacterial basis of intergenerational transmission of [...] Read more.

Pullorum disease (PD) is one of the common infectious diseases in the poultry industry in the world. Our previous study showed that gut bacterial structure has a significant difference between positive and negative hens. However, the gut bacterial basis of intergenerational transmission of PD continues to elude a scientific explanation. The present study carried out fecal microbiota transplantation (FMT) in chicks of a negative group, then fecal samples of the chicks in the control team (CT), Salmonella pullorum (S. pullorum)-negative transplantation team (PN) and S. pullorum-positive transplantation team (PP) were separately collected to be analyzed for microbial structure and prediction functions. Microbial diversity results revealed that there was a large difference in the gut microbiota of these three groups. Prevotella and Parasutterella with higher abundance in PN (p < 0.05) were transplanted from gut bacteria of S. pullorum-negative hens. Furthermore, the differences of the most major microbial functions (top 100) were similar in hens and chicks, including a pentose phosphate pathway and oxidative phosphorylation. The data provided a reference for exploring the intergenerational transmission and genetic mechanisms of gut microbiota associated with S. pullorum in poultry, as well as a theoretical basis for improving intestinal health through the rational regulation of microbiota-host interactions. Full article

(This article belongs to the Collection Feature Papers in Gut Microbiota Research)

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26 pages, 1056 KiB

Open AccessArticle

Low-Heating-Rate Thermal Degradation of Date Seed Powder and HDPE Plastic: Machine Learning CDNN, MLRM, and Thermokinetic Analysis

by Zaid Abdulhamid Alhulaybi Albin Zaid and Abdulrazak Jinadu Otaru

Polymers 2025, 17(6), 740; https://doi.org/10.3390/polym17060740 (registering DOI) - 11 Mar 2025

Abstract

Finding reliable, sustainable, and economical methods for addressing the relentless increase in plastic production and the corresponding rise in plastic waste within terrestrial and marine environments has garnered significant attention from environmental organizations and policymakers worldwide. This study presents a comprehensive analysis of [...] Read more.

Finding reliable, sustainable, and economical methods for addressing the relentless increase in plastic production and the corresponding rise in plastic waste within terrestrial and marine environments has garnered significant attention from environmental organizations and policymakers worldwide. This study presents a comprehensive analysis of the low-heating-rate thermal degradation of high-density polyethylene (HDPE) plastic in conjunction with date seed powder (DSP), utilizing thermogravimetric analysis coupled with Fourier transform infrared spectroscopy (TGA/FTIR), machine learning convolutional deep neural networks (CDNNs), multiple linear regression model (MLRM) and thermokinetics. The TGA/FTIR experimental measurements indicated a synergistic interaction between the selected materials, facilitated by the presence of hemicellulose and cellulose in the DSP biomass. In contrast, the presence of lignin was found to hinder degradation at elevated temperatures. The application of machine learning CDNNs facilitated the formulation and training of learning algorithms, resulting in an optimized architectural composition comprising three hidden neurons and employing 27,456 epochs. This modeling approach generated predicted responses that are closely aligned with experimental results (R²~0.939) when comparing the responses from a formulated MLRM model (R²~0.818). The CDNN models were utilized to estimate interpolated thermograms, representing the limits of experimental variability and conditions, thereby highlighting temperature as the most sensitive parameter governing the degradation process. The Borchardt and Daniels (BD) model-fitting and Kissinger–Akahira–Sunose (KAS) model-free kinetic methods were employed to estimate the kinetic and thermodynamic parameters of the degradation process. This yielded activation energy estimates ranging from 40.419 to 91.010 kJ·mol⁻¹ and from 96.316 to 226.286 kJ·mol⁻¹ for the selected kinetic models, respectively, while the D2 and D3 diffusion models were identified as the preferred solid-state reaction models for the process. It is anticipated that this study will aid plastic manufacturers, environmental organizations, and policymakers in identifying energy-reducing pathways for the end-of-life thermal degradation of plastics. Full article

(This article belongs to the Section Polymer Physics and Theory)

17 pages, 1716 KiB

Open AccessArticle

Carotenoid Degradation in Annatto Dye Wastewater Using an O₃/H₂O₂ Advanced Oxidation Process

by Priscila Carriel Garcia, Mateus Nordi Esperança, José Ricardo Turquetti and André Luís de Castro Peixoto

Processes 2025, 13(3), 824; https://doi.org/10.3390/pr13030824 (registering DOI) - 11 Mar 2025

Abstract

Urucum, also known as annatto, is a plant native to Brazil. However, there is a notable scarcity of scientific studies focusing on the wastewater generated by the annatto natural dye industry. This study seeks to address the existing knowledge gaps by presenting [...] Read more.

Urucum, also known as annatto, is a plant native to Brazil. However, there is a notable scarcity of scientific studies focusing on the wastewater generated by the annatto natural dye industry. This study seeks to address the existing knowledge gaps by presenting original and substantive data pertaining to this economic sector. This study investigates the degradation of carotenoids in real annatto dye wastewater through the application of an O₃/H₂O₂ oxidation process. A 2³ factorial experimental design was utilized to determine the influence of three key variables—pH (2.5–5.5), O₃ mass flow rate (8.0–18.0 mg min⁻¹), and initial H₂O₂ concentration (between 1.572 and 4.716 g L⁻¹)—on both the degradation efficiency and the associated reaction kinetics. The process demonstrated impressive carotenoid removal, achieving degradation efficiencies between 84% and 97% with pseudo-first-order kinetic constants ranging from 0.0310 to 0.0805 min⁻¹. A statistical analysis revealed that the O₃ mass flow rate was the most influential factor on the degradation efficiency, while all the operational parameters played significant roles in determining the degradation kinetics. Notably, the process achieved optimal performance without the need for pH adjustment, presenting a cost-efficient solution for industrial applications. These findings offer critical insights into the treatment of high-strength agro-industrial wastewater, thereby advancing the development and implementation of oxidation processes for wastewater management. Full article

(This article belongs to the Special Issue Advances in Photocatalytic Water and Wastewater Treatment Processes)

9 pages, 548 KiB

Open AccessArticle

Detectability of Iodine in Mediastinal Lesions on Photon Counting CT: A Phantom Study

by Joric R. Centen, Marcel J. W. Greuter and Mathias Prokop

Diagnostics 2025, 15(6), 696; https://doi.org/10.3390/diagnostics15060696 (registering DOI) - 11 Mar 2025

Abstract

Background/Objectives: To evaluate the detectability of iodine in mediastinal lesions with photon counting CT (PCCT) compared to conventional CT (CCT) in a phantom study. Methods: Mediastinal lesions were simulated by five cylindrical inserts with diameters from 1 to 12 mm within a 10 [...] Read more.

Background/Objectives: To evaluate the detectability of iodine in mediastinal lesions with photon counting CT (PCCT) compared to conventional CT (CCT) in a phantom study. Methods: Mediastinal lesions were simulated by five cylindrical inserts with diameters from 1 to 12 mm within a 10 cm solid water phantom that was placed in the mediastinal area of an anthropomorphic chest phantom with fat ring (QRM-thorax, QRM L-ring, 30 cm × 40 cm cross-section). Inserts were filled with iodine contrast at concentrations of 0.238 to 27.5 mg/mL. A clinical chest protocol at 120 kV on a high-end CCT (Somatom Force, Siemens Healthineers) was compared to the same protocol on a PCCT (Naeotom Alpha, Siemens Healthineers). Images reconstructed with a soft tissue kernel at 1 mm thickness and a 512 matrix served as a reference. For PCCT, we studied the result of reconstructing virtual mono-energetic images (VMIs) at 40, 50, 60 and 70 keV, reducing exposure dose up by 66%, reducing slice thickness to 0.4 and 0.2 mm, and increasing matrix size from 512 to 768 and 1024. Two observers with similar experience independently determined the smallest insert size for which iodine enhancement could still be detected. Consensus was reached when detectability thresholds differed between observers. Results: CTDIvol on PCCT and CCT was 3.80 ± 0.12 and 3.60 ± 0.01 mGy, respectively. PCCT was substantially more sensitive than CCT for detection of iodine in small mediastinal lesions: to detect a 3 mm lesion, 11.2 mg/mL iodine was needed with CCT, while only 1.43 mg/mL was required at 40 keV and 50 keV with PCCT. Moreover, dose reduced by 66% resulted in a comparable detection of iodine between PCCT and CCT for all lesions, except 3 mm. Detection increased from 11.2 mg/mL on CCT to 4.54 mg/mL on PCCT. A matrix size of 1024 reduced this detection threshold further, to 0.238 mg/mL at 40 and 50 keV. For 5 mm lesions, this detection threshold of 0.238 mg/mL was already achieved with a 512 matrix. Very small, 1 mm lesions did not profit from PCCT except if reconstructed with a 1024 matrix, which reduced the detection threshold from 27.5 mg/mL to 11.2 mg/mL. Reduced slice thickness decreased iodine detection of 3–12 mm lesions but not for 1 mm lesions. Conclusions: Iodine detectability with PCCT is at least equal to CCT for simulated mediastinal lesions of 1–12 mm, even at a dose reduction of 66%. Iodine detectability further profits from virtual monoenergetic images of 40 and 50 keV and increased reconstruction matrix. Full article

(This article belongs to the Section Medical Imaging and Theranostics)

39 pages, 1590 KiB

Open AccessReview

Multi-Omic Advances in Olive Tree (Olea europaea subsp. europaea L.) Under Salinity: Stepping Towards ‘Smart Oliviculture’

by Manuel Gonzalo Claros, Amanda Bullones, Antonio Jesús Castro, Elena Lima-Cabello, María Ángeles Viruel, María Fernanda Suárez, Remedios Romero-Aranda, Noé Fernández-Pozo, Francisco J. Veredas, Andrés Belver and Juan de Dios Alché

Biology 2025, 14(3), 287; https://doi.org/10.3390/biology14030287 (registering DOI) - 11 Mar 2025

Abstract

Soil salinisation is threatening crop sustainability worldwide, mainly due to anthropogenic climate change. Molecular mechanisms developed to counteract salinity have been intensely studied in model plants. Nevertheless, the economically relevant olive tree (Olea europaea subsp. europaea L.), being highly exposed to soil [...] Read more.

Soil salinisation is threatening crop sustainability worldwide, mainly due to anthropogenic climate change. Molecular mechanisms developed to counteract salinity have been intensely studied in model plants. Nevertheless, the economically relevant olive tree (Olea europaea subsp. europaea L.), being highly exposed to soil salinisation, deserves a specific review to extract the recent genomic advances that support the known morphological and biochemical mechanisms that make it a relative salt-tolerant crop. A comprehensive list of 98 olive cultivars classified by salt tolerance is provided, together with the list of available olive tree genomes and genes known to be involved in salt response. Na⁺ and Cl^– exclusion in leaves and retention in roots seem to be the most prominent adaptations, but cell wall thickening and antioxidant changes are also required for a tolerant response. Several post-translational modifications of proteins are emerging as key factors, together with microbiota amendments, making treatments with biostimulants and chemical compounds a promising approach to enable cultivation in already salinised soils. Low and high-throughput transcriptomics and metagenomics results obtained from salt-sensitive and -tolerant cultivars, and the future advantages of engineering specific metacaspases involved in programmed cell death and autophagy pathways to rapidly raise salt-tolerant cultivars or rootstocks are also discussed. The overview of bioinformatic tools focused on olive tree, combined with machine learning approaches for studying plant stress from a multi-omics perspective, indicates that the development of salt-tolerant cultivars or rootstocks adapted to soil salinisation is progressing. This could pave the way for ‘smart oliviculture’, promoting more productive and sustainable practices under salt stress. Full article

(This article belongs to the Section Genetics and Genomics)

23 pages, 4123 KiB

Open AccessArticle

Enhanced DWT for Denoising Heartbeat Signal in Non-Invasive Detection

by Peibin Zhu, Lei Feng, Kaimin Yu, Yuanfang Zhang, Meiling Dai, Wen Chen and Jianzhong Hao

Sensors 2025, 25(6), 1743; https://doi.org/10.3390/s25061743 (registering DOI) - 11 Mar 2025

Abstract

Achieving both accurate and real-time monitoring heartbeat signals by non-invasive sensing techniques is challenging due to various noise interferences. In this paper, we propose an enhanced discrete wavelet transform (DWT) method that incorporates objective denoising quality assessment metrics to determine accurate thresholds and [...] Read more.

Achieving both accurate and real-time monitoring heartbeat signals by non-invasive sensing techniques is challenging due to various noise interferences. In this paper, we propose an enhanced discrete wavelet transform (DWT) method that incorporates objective denoising quality assessment metrics to determine accurate thresholds and adaptive threshold functions. Our approach begins by denoising ECG signals from various databases, introducing several types of typical noise, including additive white Gaussian (AWG) noise, baseline wandering noise, electrode motion noise, and muscle artifacts. The results show that for Gaussian white noise denoising, the enhanced DWT can achieve 1–5 dB SNR improvement compared to the traditional DWT method, while for real noise denoising, our proposed method improves the SNR tens or even hundreds of times that of the state-of-the-art denoising techniques. Furthermore, we validate the effectiveness of the enhanced DWT method by visualizing and comparing the denoising results of heartbeat signals monitored by fiber-optic micro-vibration sensors against those obtained using other denoising methods. The improved DWT enhances the quality of heartbeat signals from non-invasive sensors, thereby increasing the accuracy of cardiovascular disease diagnosis. Full article

(This article belongs to the Special Issue Recent Trends and Advances in Biomedical Optics and Imaging)

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27 pages, 3122 KiB

Open AccessArticle

Comparative Analysis of In-Plane and Out-of-Plane Bending Benchmarks Using Two Finite Element Packages

by Emilia Słota and Adam Wosatko

Appl. Sci. 2025, 15(6), 3051; https://doi.org/10.3390/app15063051 (registering DOI) - 11 Mar 2025

Abstract

An essential aspect of design from the perspective of structural strength is the reliability of the results obtained during the computations for the analyzed model. Among various skills in numerical analysis, an engineer should be able to independently verify the quality of the [...] Read more.

An essential aspect of design from the perspective of structural strength is the reliability of the results obtained during the computations for the analyzed model. Among various skills in numerical analysis, an engineer should be able to independently verify the quality of the available software using benchmarks already at the level of statics. An effective method of such verification is comparing the test results obtained from two different packages. The paper discusses three structure-oriented benchmarks for in-plane and out-of-plane bending of a flat membrane and a slab, respectively. The computations are carried out using the Robot and Midas finite element tools. These simulation tests are selected to present issues related to the modeling of bending, which is crucial for reliable design: the convergence of the solution for a cantilever, the possibility of a reduction in slab moments above columns, and the interaction effects between the beam and the plate, depending on their position and connection in the model. It is shown that, in finite element calculations, attention must be paid to avoiding errors due to improper data input and software option settings, leading to incorrect simulation results, which may negatively impact the design process. A proper understanding of software tools, for example, through benchmark verification, ensures their conscious use in developing more complex structural models. Full article

(This article belongs to the Section Civil Engineering)

21 pages, 545 KiB

Open AccessArticle

Graph-to-Text Generation with Bidirectional Dual Cross-Attention and Concatenation

by Elias Lemuye Jimale, Wenyu Chen, Mugahed A. Al-antari, Yeong Hyeon Gu, Victor Kwaku Agbesi, Wasif Feroze, Feidu Akmel, Juhar Mohammed Assefa and Ali Shahzad

Mathematics 2025, 13(6), 935; https://doi.org/10.3390/math13060935 (registering DOI) - 11 Mar 2025

Abstract

Graph-to-text generation (G2T) involves converting structured graph data into natural language text, a task made challenging by the need for encoders to capture the entities and their relationships within the graph effectively. While transformer-based encoders have advanced natural language processing, their reliance on [...] Read more.

Graph-to-text generation (G2T) involves converting structured graph data into natural language text, a task made challenging by the need for encoders to capture the entities and their relationships within the graph effectively. While transformer-based encoders have advanced natural language processing, their reliance on linearized data often obscures the complex interrelationships in graph structures, leading to structural loss. Conversely, graph attention networks excel at capturing graph structures but lack the pre-training advantages of transformers. To leverage the strengths of both modalities and bridge this gap, we propose a novel bidirectional dual cross-attention and concatenation (BDCC) mechanism that integrates outputs from a transformer-based encoder and a graph attention encoder. The bidirectional dual cross-attention computes attention scores bidirectionally, allowing graph features to attend to transformer features and vice versa, effectively capturing inter-modal relationships. The concatenation is applied to fuse the attended outputs, enabling robust feature fusion across modalities. We empirically validate BDCC on PathQuestions and WebNLG benchmark datasets, achieving BLEU scores of 67.41% and 66.58% and METEOR scores of 49.63% and 47.44%, respectively. The results outperform the baseline models and demonstrate that BDCC significantly improves G2T tasks by leveraging the synergistic benefits of graph attention and transformer encoders, addressing the limitations of existing approaches and showcasing the potential for future research in this area. Full article

(This article belongs to the Section E1: Mathematics and Computer Science)

26 pages, 481 KiB

Open AccessArticle

Controlled Double-Direction Cyclic Quantum Communication of Arbitrary Two-Particle States

by Nueraminaimu Maihemuti, Zhanheng Chen, Jiayin Peng, Yimamujiang Aisan and Jiangang Tang

Entropy 2025, 27(3), 292; https://doi.org/10.3390/e27030292 (registering DOI) - 11 Mar 2025

Abstract

With the rapid development of quantum communication technologies, controlled double-direction cyclic (CDDC) quantum communication has become an important research direction. However, how to choose an appropriate quantum state as a channel to achieve double-direction cyclic (DDC) quantum communication for multi-particle entangled states remains [...] Read more.

With the rapid development of quantum communication technologies, controlled double-direction cyclic (CDDC) quantum communication has become an important research direction. However, how to choose an appropriate quantum state as a channel to achieve double-direction cyclic (DDC) quantum communication for multi-particle entangled states remains an unresolved challenge. This study aims to address this issue by constructing a suitable quantum channel and investigating the DDC quantum communication of two-particle states. Initially, we create a 25-particle entangled state using Hadamard and controlled-NOT (CNOT) gates, and provide its corresponding quantum circuit implementation. Based on this entangled state as a quantum channel, we propose two new four-party CDDC schemes, applied to quantum teleportation (QT) and remote state preparation (RSP), respectively. In both schemes, each communicating party can synchronously transmit two different arbitrary two-particle states to the other parties under supervisory control, achieving controlled quantum cyclic communication in both clockwise and counterclockwise directions. Additionally, the presented two schemes of four-party CDDC quantum communication are extended to situations where

n > 3

communicating parties. In each proposed scheme, we provide universal analytical formulas for the local operations of the sender, supervisor, and receiver, demonstrating that the success probability of each scheme can reach 100%. These schemes only require specific two-particle projective measurements, single-particle von Neumann measurements, and Pauli gate operations, all of which can be implemented with current technologies. We have also evaluated the inherent efficiency, security, and control capabilities of the proposed schemes. In comparison to earlier methods, the results demonstrate that our schemes perform exceptionally well. This study provides a theoretical foundation for bidirectional controlled quantum communication of multi-particle states, aiming to enhance security and capacity while meeting the diverse needs of future network scenarios. Full article

(This article belongs to the Special Issue Classical and Quantum Networks: Theory, Modeling and Optimization)

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16 pages, 5278 KiB

Open AccessArticle

From Grammont to a New 135° Short-Stem Design: Two-Hand Lever Test and Early Superior–Lateral Dislocations Reveal Critical Role of Liner Stability Ratio and Stem Alignment

by Stefan Bauer, Jaad Mahlouly, Luca Tolosano, Philipp Moroder, William G. Blakeney and Wei Shao

J. Clin. Med. 2025, 14(6), 1898; https://doi.org/10.3390/jcm14061898 (registering DOI) - 11 Mar 2025

Abstract

Background: In reverse shoulder arthroplasty (RSA), the neck–shaft angle (NSA) has trended downward from 155° to 135° to reduce scapular notching, but concerns about instability persist. To assess superior–lateral stability, we developed the intraoperative two-hand lever test (2HLT). The primary objective was [...] Read more.

Background: In reverse shoulder arthroplasty (RSA), the neck–shaft angle (NSA) has trended downward from 155° to 135° to reduce scapular notching, but concerns about instability persist. To assess superior–lateral stability, we developed the intraoperative two-hand lever test (2HLT). The primary objective was to evaluate the effectiveness of the 2HLT, analyze the learning curve in this first study reporting on the new Perform stem, and compare the liner characteristics of 155° and 135° systems. Methods: In a single-surgeon learning curve study, 81 RSA procedures with the new Perform stem (Stryker) were included. The outcomes included the 2HLT test applied in 65 cases, early dislocations, stem alignment, stem length, liner type/thickness, and complications. The early dislocation rate was compared to 167 prior Ascend Flex RSA procedures (Stryker). The liner characteristics of three 135° systems (Perform/Stryker, Univers/Arthrex, and Altivate/Enovis) were compared to traditional 155° Grammont systems (Delta Xtend/DePuy, Affinis Metal/Mathys, SMR 150/Lima, and Aequalis Reversed/Stryker), focusing on jump height (JH) and the liner stability ratio (LSR). Results: In 63% (31/49) of the cases, the 2HLT detected superior–lateral instability, necessitating a retentive 135° liner. The early dislocation rate in the Perform cohort was 4.9% (0% for retentive liners, 8% for standard liners) versus 0% in the Ascend Flex cohort. The mean effective NSA was 133° (127–144°) for short Perform stems and 135° (129–143°) for long stems. Long Perform stems significantly reduced varus outlier density below 132° and 130° (p = 0.006, 0.002). The 36 mm Perform 135° standard liner has a JH of 8.1 mm and an LSR of 152%, markedly lower than the Altivate (10.0 mm/202%) and Univers (9.7 mm/193%) and similar to traditional 155° Grammont liners (8.1–8.9 mm/147–152%). Perform retentive liners have LSR values of 185–219%, comparable to the established 135° design standard liners (195–202%). In the Perform cohort, early complications included four superior–lateral dislocations (all standard liners, LSR 147–152%) requiring four revisions. Conclusions: Perform standard liners have a lower LSR than the established 135° designs. Retentive Perform liners (LSR > 184%) are comparable to standard liners of established 135° designs and effectively mitigate instability. We recommend discontinuing non-retentive Perform standard liners (NSA 135°, LSR < 158%) due to the 63% superior–lateral instability rate detected with the novel 2HLT, necessitating retentive liners, the documented LSR-NSA implant mismatch, and an early clinical dislocation rate of up to 8%. Full article

(This article belongs to the Special Issue Advances, New Technologies and Optimization of Reverse Shoulder Arthroplasty)

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10 pages, 422 KiB

Open AccessArticle

The Efficacy of Mannitol in Attenuating Postreperfusion Syndrome in Orthotopic Liver Transplantation: A Retrospective Cohort Study

by Samuel DeMaria, Jr., Emily M. Bachner, Jr., Victoria Mroz, Sophia Gamboa, Yuxia Ouyang, Natalia N. Egorova, Natalie K. Smith and Ryan Wang

J. Clin. Med. 2025, 14(6), 1897; https://doi.org/10.3390/jcm14061897 (registering DOI) - 11 Mar 2025

Abstract

Introduction: Postreperfusion syndrome (PRS) is associated with complications following liver transplantation (LT). Mannitol may play a role in attenuating PRS as a free radical scavenger. This study aimed to evaluate the association between intraoperative mannitol administration and the incidence of PRS and postoperative [...] Read more.

Introduction: Postreperfusion syndrome (PRS) is associated with complications following liver transplantation (LT). Mannitol may play a role in attenuating PRS as a free radical scavenger. This study aimed to evaluate the association between intraoperative mannitol administration and the incidence of PRS and postoperative acute kidney injury (AKI) in LT. Methods: A retrospective analysis of adult liver-only transplantation between August 2019 and January 2023 at the Mount Sinai Hospital was performed. Patients in the mannitol group received 25G of the drug intravenously prior to reperfusion. Any recipients with pre-existing renal diagnoses were excluded. Demographic, laboratory, intraoperative, and hospital course data were extracted from an institutional data warehouse. Multivariable logistic regressions were used to evaluate the association between mannitol administration and PRS, AKI, early allograft dysfunction, and postoperative cardiac complications. Negative binomial regression was used to evaluate the association with postoperative length of stay (LOS) and ICU LOS. Results: 495 LT cases were included. A total of 81 patients received mannitol before graft reperfusion, while 414 patients did not. The incidence of PRS in patients who received mannitol was 13% and 17% for those who did not receive mannitol (p = 0.53). Additionally, 79% of patients who received mannitol experienced AKI at 7 days, compared to 73% in those who did not receive mannitol (p = 0.48). In the multivariable regression models, mannitol administration was not associated with decreased incidence of PRS or postoperative AKI. It was, however, associated with increased postoperative cardiac complications (risk-adjusted odds ratio 2.70, 95% confidence interval 1.15–6.14, p = 0.02). Conclusions: Mannitol administration during LT was not an effective therapy for reducing PRS or postoperative AKI. Full article

(This article belongs to the Section Gastroenterology & Hepatopancreatobiliary Medicine)

22 pages, 3379 KiB

Open AccessArticle

Making Timber Accessible to Forest Communities: A Study on Locally Adapted, Motor–Manual Forest Management Schemes in the Eastern Lowlands of Bolivia

by Benno Pokorny, Juan Carlos Montero Terrazas, James Johnson, Karen Mendoza Ortega, Walter Cano Cardona and Wil de Jong

Forests 2025, 16(3), 496; https://doi.org/10.3390/f16030496 (registering DOI) - 11 Mar 2025

Abstract

Forest communities around the world have great difficulties in utilizing the economic potential of their forests, especially timber, under current technical requirements and legal frameworks. The present study examines the feasibility of motor–manual timber management among indigenous Chiquitano communities in Bolivia’s Eastern Lowlands. [...] Read more.

Forest communities around the world have great difficulties in utilizing the economic potential of their forests, especially timber, under current technical requirements and legal frameworks. The present study examines the feasibility of motor–manual timber management among indigenous Chiquitano communities in Bolivia’s Eastern Lowlands. It evaluates local practices, tests technical optimization options, and assesses their technical, financial, and environmental impacts. Findings reveal that traditional motor–manual timber production is scarcely profitable, exacerbated by burdensome legal frameworks and limited market access. However, motor–manual forest management remains an essential source of income for communities, and it constitutes an important option for rural development. Field tests demonstrate that, with the use of better equipment such as quality chainsaws, and improved maintenance and workflows, productivity and profitability of local logging can be enhanced. Despite a low environmental impact, optimized motor–manual timber management continues to be constrained by governance challenges, logistical limitations, and limited markets for locally produced timber. The study recommends optimizing these aspects, including targeted technical support, market development, simplified legal frameworks, and the setting up of robust local governance structures to replace ineffective centralized command and control approaches. These improvements would enable communities to sustainably use timber from their forests while addressing their socio-economic needs. The findings underscore the potential of logging by local communities as an alternative to large-scale mechanized logging, for Bolivia and in other tropical forest countries. Full article

(This article belongs to the Section Forest Economics, Policy, and Social Science)

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23 pages, 1840 KiB

Open AccessReview

Fusion-Based Approaches and Machine Learning Algorithms for Forest Monitoring: A Systematic Review

by Abdullah Al Saim and Mohamed H. Aly

Wild 2025, 2(1), 7; https://doi.org/10.3390/wild2010007 - 11 Mar 2025

Abstract

Multi-source remote sensing fusion and machine learning are effective tools for forest monitoring. This study aimed to analyze various fusion techniques, their application with machine learning algorithms, and their assessment in estimating forest type and aboveground biomass (AGB). A keyword search across Web [...] Read more.

Multi-source remote sensing fusion and machine learning are effective tools for forest monitoring. This study aimed to analyze various fusion techniques, their application with machine learning algorithms, and their assessment in estimating forest type and aboveground biomass (AGB). A keyword search across Web of Science, Science Direct, and Google Scholar yielded 920 articles. After rigorous screening, 72 relevant articles were analyzed. Results showed a growing trend in optical and radar fusion, with notable use of hyperspectral images, LiDAR, and field measurements in fusion-based forest monitoring. Machine learning algorithms, particularly Random Forest (RF), Support Vector Machine (SVM), and K-Nearest Neighbor (KNN), leverage features from fused sources, with proper variable selection enhancing accuracy. Standard evaluation metrics include Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), Overall Accuracy (OA), User’s Accuracy (UA), Producer’s Accuracy (PA), confusion matrix, and Kappa coefficient. This review provides a comprehensive overview of prevalent techniques, data sources, and evaluation metrics by synthesizing current research and highlighting data fusion’s potential to improve forest monitoring accuracy. The study underscores the importance of spectral, topographic, textural, and environmental variables, sensor frequency, and key research gaps for standardized evaluation protocols and exploration of multi-temporal fusion for dynamic forest change monitoring. Full article

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32 pages, 3163 KiB

Open AccessArticle

Unveiling the Impact of Socioeconomic and Demographic Factors on Graduate Salaries: A Machine Learning Explanatory Analytical Approach Using Higher Education Statistical Agency Data

by Bassey Henshaw, Bhupesh Kumar Mishra, William Sayers and Zeeshan Pervez

Analytics 2025, 4(1), 10; https://doi.org/10.3390/analytics4010010 - 11 Mar 2025

Abstract

Graduate salaries are a significant concern for graduates, employers, and policymakers, as various factors influence them. This study investigates determinants of graduate salaries in the UK, utilising survey data from HESA (Higher Education Statistical Agency) and integrating advanced machine learning (ML) explanatory techniques [...] Read more.

Graduate salaries are a significant concern for graduates, employers, and policymakers, as various factors influence them. This study investigates determinants of graduate salaries in the UK, utilising survey data from HESA (Higher Education Statistical Agency) and integrating advanced machine learning (ML) explanatory techniques with statistical analytical methodologies. By employing multi-stage analyses alongside machine learning models such as decision trees, random forests and the explainability with SHAP stands for (Shapley Additive exPanations), this study investigates the influence of 21 socioeconomic and demographic variables on graduate salary outcomes. Key variables, including institutional reputation, age at graduation, socioeconomic classification, job qualification requirements, and domicile, emerged as critical determinants, with institutional reputation proving the most significant. Among ML methods, the decision tree achieved a standout with the highest accuracy through rigorous optimisation techniques, including oversampling and undersampling. SHAP highlighted the top 12 influential variables, providing actionable insights into the interplay between individual and systemic factors. Furthermore, the statistical analysis using ANOVA (Analysis of Variance) validated the significance of these variables, revealing intricate interactions that shape graduate salary dynamics. Additionally, domain experts’ opinions are also analysed to authenticate the findings. This research makes a unique contribution by combining qualitative contextual analysis with quantitative methodologies, machine learning explainability and domain experts’ views on addressing gaps in the existing identification of graduate salary predicting components. Additionally, the findings inform policy and educational interventions to reduce wage inequalities and promote equitable career opportunities. Despite limitations, such as the UK-specific dataset and the focus on socioeconomic and demographic variables, this study lays a robust foundation for future research in predictive modelling and graduate outcomes. Full article

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12 pages, 706 KiB

Open AccessSystematic Review

Uterine Transplantation for Absolute Uterine Factor Infertility: A Systematic Review

by Anais Sánchez-Leo and Leticia López-Pedraza

Complications 2025, 2(1), 7; https://doi.org/10.3390/complications2010007 - 11 Mar 2025

Abstract

Introduction: Uterine transplantation is currently the only treatment that allows women with absolute uterine factor infertility (AUFI) to gestate and give birth. Objective: This systematic review aims to analyze the available evidence on uterine transplantation, focusing on the medical process, associated complications, ethical [...] Read more.

Introduction: Uterine transplantation is currently the only treatment that allows women with absolute uterine factor infertility (AUFI) to gestate and give birth. Objective: This systematic review aims to analyze the available evidence on uterine transplantation, focusing on the medical process, associated complications, ethical dilemmas, and the psychological and social impact on recipients. Methods: A systematic review of PubMed, Medline, MedNar, and Cinahl databases was conducted. The inclusion criteria included articles related to uterine transplantation published in English or Spanish between 2019 and 2024, excluding animal studies or other uterine procedures. Results: A total of 46 articles were analyzed. The review describes ethical considerations and recipients’ perceptions, two variables that have received limited attention in recent studies. Additionally, the transplant and gestation processes, along with associated complications, were detailed. Discussion: The limited availability of studies on ethical aspects and recipient perceptions presented challenges in the research. Moreover, the role of nurses and midwives, despite their importance in the process, is scarcely discussed in the literature. Conclusions: Although uterine transplantation remains an emerging treatment, its development suggests that the benefits may outweigh the risks, offering new hope for women with AUFI. Full article

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36 pages, 2890 KiB

Open AccessArticle

A Machine Learning-Based Hybrid Encryption Approach for Securing Messages in Software-Defined Networking

by Chitran Pokhrel, Roshani Ghimire, Babu R. Dawadi and Pietro Manzoni

Network 2025, 5(1), 8; https://doi.org/10.3390/network5010008 - 11 Mar 2025

Abstract

The security of a network is based on the foundation of confidentiality, integrity, and availability, often referred to as the CIA triad. The privacy of data over a network, maintained by confidentiality, has long been one of the major issues in network settings. [...] Read more.

The security of a network is based on the foundation of confidentiality, integrity, and availability, often referred to as the CIA triad. The privacy of data over a network, maintained by confidentiality, has long been one of the major issues in network settings. With the decoupling of the data plane and control plane in the software-defined networking (SDN) environment, this challenge is significantly amplified. This paper aims to address the challenges of confidentiality in SDN by introducing a genetic algorithm-based hybrid encryption network policy to secure messages across the network. The proposed approach achieved an average entropy of 0.989, revealing a significant improvement in the strength of the encryption with the hybrid mechanism. However, the method exhibited processing overhead, significantly increasing the transmission time for encrypted messages compared to unencrypted transmission. Compared to standalone AES, DES, and RSA, this approach shows better encryption randomness, but a trade-off between security and network performance is evident in the absence of load-balancing techniques. Full article

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8 pages, 890 KiB

Open AccessArticle

Near-Infrared Phosphorescence of Raman Photogenerated Singlet Oxygen

by Aristides Marcano Olaizola

Photochem 2025, 5(1), 7; https://doi.org/10.3390/photochem5010007 - 11 Mar 2025

Abstract

We report on the phosphorescence of singlet oxygen photogenerated through a stimulated Raman process. Nanosecond radiation in the green spectral region focused on hexane and carbon tetrachloride induces a Raman transition of the dissolved solvent oxygen molecules towards the singlet oxygen state, producing [...] Read more.

We report on the phosphorescence of singlet oxygen photogenerated through a stimulated Raman process. Nanosecond radiation in the green spectral region focused on hexane and carbon tetrachloride induces a Raman transition of the dissolved solvent oxygen molecules towards the singlet oxygen state, producing a Stokes signal in the near-infrared. The excited oxygen relaxes to the ground, emitting an infrared photon at 1272 nm. While the Stokes signal’s wavelength changes with the light’s wavelength, the wavelength of the phosphorescent photon remains unaltered. The result confirms previous reports on the stimulated Raman excitation of singlet oxygen. Full article

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12 pages, 714 KiB

Open AccessArticle

Effect of Confinement on the Structural, Dielectric, and Dynamic Properties of Liquid Crystals in Anopores

by Pavel V. Maslennikov and Alex V. Zakharov

Liquids 2025, 5(1), 7; https://doi.org/10.3390/liquids5010007 - 11 Mar 2025

Abstract

Based on data from broadband dielectric spectroscopy (BDS) and a molecular model based on the Landau–de Gennes concept, the effect of confinement on the structural, dielectric, and dynamic properties of 4-n-pentyl-4′-cyanobiphenyl (5CB) in the nematic phase is studied. The dielectric permittivity and relaxation [...] Read more.

Based on data from broadband dielectric spectroscopy (BDS) and a molecular model based on the Landau–de Gennes concept, the effect of confinement on the structural, dielectric, and dynamic properties of 4-n-pentyl-4′-cyanobiphenyl (5CB) in the nematic phase is studied. The dielectric permittivity and relaxation times were previously obtained by the BDS technique in a wide frequency range (

1 MHz \leq f \leq 1 GHz

) in the nematic phase composed of 5CB molecules confined to Anopore membranes with pore sizes of 0.2

μ

m. The distance-dependent values of the order parameter

P_{2} (r)

, the relaxation time

τ (r) \equiv τ_{00}^{1} (r)

, the rotational diffusion coefficient

D_{⊥} (r)

, and both rotational viscosity coefficients

γ_{i} (r)

(

i = 1, 2

) as functions of the distance r away from the bounding surface are calculated by a combination of existing statistical-mechanical approaches and data obtained by the BDS technique. Reasonable agreement between the calculated and experimental values of

γ_{i} (i = 1, 2)

for bulk 5CB is obtained. Full article

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18 pages, 396 KiB

Open AccessArticle

Building Digital-Ready Leaders: Development and Validation of the Human-Centric Digital Leadership Scale

by Haroon Abbu, Sarah Khan, Paul Mugge and Gerhard Gudergan

Digital 2025, 5(1), 7; https://doi.org/10.3390/digital5010007 - 11 Mar 2025

Abstract

The success of digital transformation initiatives relies heavily on effective digital leadership, which requires a blend of human-centric traits and technical expertise. While digital technologies enable transformation, organizations must develop leaders with the skills to navigate the complexities of change, foster innovation, and [...] Read more.

The success of digital transformation initiatives relies heavily on effective digital leadership, which requires a blend of human-centric traits and technical expertise. While digital technologies enable transformation, organizations must develop leaders with the skills to navigate the complexities of change, foster innovation, and align strategies with organizational goals. Despite the growing importance of digital leadership, there is a lack of standardized, validated tools to measure and assess digital leadership competencies systematically. This study introduces the Digital Leadership Scale (DLS), a validated self-assessment tool designed to measure a leader’s ability across seven human-centric dimensions essential for digital transformation: Positive Attitude, Ethical AI Use, Growth Mindset, Track Record, Transparent Agenda, Skills Acquisition, and Participative Style. The DLS serves as a practical tool for leaders to engage in self-reflection, identify strengths and development areas, and adopt personalized learning strategies. Organizations can leverage this scale to cultivate a digitally proficient workforce and foster leadership capabilities aligned with digital transformation success. Full article

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18 pages, 5794 KiB

Open AccessFeature PaperArticle

A Novel Capacitive Model of Radiators for Building Dynamic Simulations

by Francesco Calise, Francesco Liberato Cappiello, Luca Cimmino, Massimo Dentice d’Accadia and Maria Vicidomini

Thermo 2025, 5(1), 9; https://doi.org/10.3390/thermo5010009 - 11 Mar 2025

Abstract

This study addresses the critical challenge of performing a detailed calculation of energy savings in buildings by implementing suitable actions aiming at reducing greenhouse gas emissions. Given the high energy consumption of buildings’ space heating systems, optimizing their performance is crucial for reducing [...] Read more.

This study addresses the critical challenge of performing a detailed calculation of energy savings in buildings by implementing suitable actions aiming at reducing greenhouse gas emissions. Given the high energy consumption of buildings’ space heating systems, optimizing their performance is crucial for reducing their overall primary energy demand. Unfortunately, the calculations of such savings are often based on extremely simplified methods, neglecting the dynamics of the emitters installed inside the buildings. These approximations may lead to relevant errors in the estimation of the possible energy savings. In this framework, the present study presents a novel 0-dimensional capacitive model of a radiator, the most common emitter used in residential buildings. The final scope of this paper is to integrate such a novel model within the TRNSYS 18simulation environment, performing a 1-year simulation of the overall building-space heating system. The radiator model is developed in MATLAB 2024b and it carefully considers the impact of surface area, inlet temperature, and flow rate on the radiator performance. Moreover, the dynamic heat transfer rate of the capacitive radiator is compared with the one returned by the built-in non-capacitive model available in TRNSYS, showing that neglecting the capacitive effect of radiators leads to an incorrect estimation of the heating consumption. During the winter season, with a heating system turned on from 8 a.m. to 4 p.m. and from 6 p.m. to 8 p.m., the thermal energy is underestimated by roughly 20% with the commonly used non-capacitive model. Full article

(This article belongs to the Special Issue Innovative Technologies to Optimize Building Energy Performance)

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13 pages, 992 KiB

Open AccessArticle

Non-Pharmaceutical Interventions on COVID-19 in Workers and Residents of Nursing Homes in Geneva: A Mixed Qualitative and Quantitative Study

by Lakshmi Krishna Menon, Ania Wisniak, Simon Regard, Silvia Stringhini, Idris Guessous, Jean-François Balavoine, Omar Kherad and The SEROCoV-WORK + Study Group

Epidemiologia 2025, 6(1), 14; https://doi.org/10.3390/epidemiologia6010014 - 11 Mar 2025

Abstract

The objective of this study was to examine the impact of varying levels of non-pharmaceutical interventions (NPIs) on COVID-19 transmission in nursing homes during the first wave of the pandemic. Background/Objectives: The primary aim involved exploring qualitative insights from staff and management regarding [...] Read more.

The objective of this study was to examine the impact of varying levels of non-pharmaceutical interventions (NPIs) on COVID-19 transmission in nursing homes during the first wave of the pandemic. Background/Objectives: The primary aim involved exploring qualitative insights from staff and management regarding the implementation of NPIs. The secondary aim was to determine the cumulative incidence of PCR-confirmed COVID-19 cases among residents. Incident rate ratios (IRRs) were the calculated levels of NPI restrictiveness. Methods: We used a mixed methodology to identify factors that might have affected COVID-19 expansion in nursing homes in the canton of Geneva, Switzerland. For the qualitative component, we interviewed the Attending Physicians and/or Director of each nursing home. In the quantitative component, we calculated incident rate ratios (IRRs) for infection between the three levels of COVID-19-related measures taken in these nursing homes, and the cumulative incidence of PCR-confirmed COVID-19 cases in their resident population. This study was conducted in 12 nursing homes located in the canton of Geneva, Switzerland, between 1 March 2020, and 1 June 2020. Results: Most nursing homes mandated NPIs for their staff and residents during the first wave of COVID-19. We found an equal distribution of maximally (n = 4), moderately (n = 4), and minimally (n = 4) restrictive NPIs for nursing home workers and residents. The extent of NPIs implemented was not shown to be significantly associated with the cumulative incidence of COVID-19 cases among residents (maximally restrictive IRR = 3.90, 95%CI 0.82–45.54, p = 0.184; moderately restrictive IRR = 3.55, 95%CI 0.75–41.42, p = 0.212; minimally restrictive IRR = reference). Conclusions: Nursing homes in our study showed high variability in which NPIs, and to what extent, they implemented, with no significant relationship between the restrictiveness of NPIs and COVID-19 incidence among nursing home residents. This suggests that other factors influence the transmission of COVID-19 in these settings. Future research should explore additional determinants and the balance between strict NPIs and the overall well-being of residents. Full article

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24 pages, 6773 KiB

Open AccessArticle

Coordinated Control Strategy for Stability Control and Trajectory Tracking with Wheel-Driven Autonomous Vehicles Under Harsh Situations

by Gang Liu and Wensheng Shao

World Electr. Veh. J. 2025, 16(3), 163; https://doi.org/10.3390/wevj16030163 - 11 Mar 2025

Abstract

A coordinated strategy is proposed to prevent interference between trajectory tracking control and stability control in wheel-driven autonomous vehicles. A tire cornering stiffness estimate model is developed using the recursive least squares approach with a forgetting factor (FFRLS), resulting in precise estimation of [...] Read more.

A coordinated strategy is proposed to prevent interference between trajectory tracking control and stability control in wheel-driven autonomous vehicles. A tire cornering stiffness estimate model is developed using the recursive least squares approach with a forgetting factor (FFRLS), resulting in precise estimation of tire cornering stiffness. An adaptive trajectory tracking control is developed, utilizing real-time updates of tire cornering stiffness; for the direct yaw moment required for stability control, an integral sliding-mode control is adopted, and the chatter problem of the integral sliding-mode controller is optimized by a fuzzy controller. The coordinated control of trajectory tracking and vehicle stability is ultimately attained through the application of the normalized stability index. The method’s practicality is validated by the hardware-in-the-loop simulation platform. Full article

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36 pages, 8602 KiB

Open AccessArticle

Multi-Agent Mapping and Tracking-Based Electrical Vehicles with Unknown Environment Exploration

by Chafaa Hamrouni, Aarif Alutaybi and Ghofrane Ouerfelli

World Electr. Veh. J. 2025, 16(3), 162; https://doi.org/10.3390/wevj16030162 - 11 Mar 2025

Abstract

This research presents an intelligent, environment-aware navigation framework for smart electric vehicles (EVs), focusing on multi-agent mapping, real-time obstacle recognition, and adaptive route optimization. Unlike traditional navigation systems that primarily minimize cost and distance, this research emphasizes how EVs perceive, map, and interact [...] Read more.

This research presents an intelligent, environment-aware navigation framework for smart electric vehicles (EVs), focusing on multi-agent mapping, real-time obstacle recognition, and adaptive route optimization. Unlike traditional navigation systems that primarily minimize cost and distance, this research emphasizes how EVs perceive, map, and interact with their surroundings. Using a distributed mapping approach, multiple EVs collaboratively construct a topological representation of their environment, enhancing spatial awareness and adaptive path planning. Neural Radiance Fields (NeRFs) and machine learning models are employed to improve situational awareness, reduce positional tracking errors, and increase mapping accuracy by integrating real-time traffic conditions, battery levels, and environmental constraints. The system intelligently balances delivery speed and energy efficiency by dynamically adjusting routes based on urgency, congestion, and battery constraints. When rapid deliveries are required, the algorithm prioritizes faster routes, whereas, for flexible schedules, it optimizes energy conservation. This dynamic decision making ensures optimal fleet performance by minimizing energy waste and reducing emissions. The framework further enhances sustainability by integrating an adaptive optimization model that continuously refines EV paths in response to real-time changes in traffic flow and charging station availability. By seamlessly combining real-time route adaptation with energy-efficient decision making, the proposed system supports scalable and sustainable EV fleet operations. The ability to dynamically optimize travel paths ensures minimal energy consumption while maintaining high operational efficiency. Experimental validation confirms that this approach not only improves EV navigation and obstacle avoidance but also significantly contributes to reducing emissions and enhancing the long-term viability of smart EV fleets in rapidly changing environments. Full article

(This article belongs to the Special Issue Design Theory, Method and Control of Intelligent and Safe Vehicles)

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