MDPI - Publisher of Open Access Journals

24 pages, 2807 KB

Open AccessArticle

Automatic Threshold Selection Guided by Maximizing Homologous Isomeric Similarity Under Unified Transformation Toward Unimodal Distribution

by Yaobin Zou, Wenli Yu and Qingqing Huang

Electronics 2026, 15(2), 451; https://doi.org/10.3390/electronics15020451 (registering DOI) - 20 Jan 2026

Abstract

Traditional thresholding methods are often tailored to specific histogram patterns, making it difficult to achieve robust segmentation across diverse images exhibiting non-modal, unimodal, bimodal, or multimodal distributions. To address this limitation, this paper proposes an automatic thresholding method guided by maximizing homologous isomeric [...] Read more.

Traditional thresholding methods are often tailored to specific histogram patterns, making it difficult to achieve robust segmentation across diverse images exhibiting non-modal, unimodal, bimodal, or multimodal distributions. To address this limitation, this paper proposes an automatic thresholding method guided by maximizing homologous isomeric similarity under a unified transformation toward unimodal distribution. The primary objective is to establish a generalized selection criterion that functions independently of the input histogram’s pattern. The methodology employs bilateral filtering, non-maximum suppression, and Sobel operators to transform diverse histogram patterns into a unified, right-skewed unimodal distribution. Subsequently, the optimal threshold is determined by maximizing the normalized Renyi mutual information between the transformed edge image and binary contour images extracted at varying levels. Experimental validation on both synthetic and real-world images demonstrates that the proposed method offers greater adaptability and higher accuracy compared to representative thresholding and non-thresholding techniques. The results show a significant reduction in misclassification errors and improved correlation metrics, confirming the method’s effectiveness as a unified thresholding solution for images with non-modal, unimodal, bimodal, or multimodal histogram patterns. Full article

(This article belongs to the Special Issue Image Processing and Pattern Recognition)

40 pages, 850 KB

Open AccessReview

Lipidomics in Melanoma: Insights into Disease Progression and Therapeutical Targets

by Vittoria Maresca, Emanuela Bastonini, Giorgia Cardinali, Enrica Flori, Daniela Kovacs, Monica Ottaviani and Stefania Briganti

Int. J. Mol. Sci. 2026, 27(2), 1040; https://doi.org/10.3390/ijms27021040 (registering DOI) - 20 Jan 2026

Abstract

Melanoma is the deadliest form of skin cancer, characterized by high metastatic potential and intrinsic heterogeneity. In addition to genetic mutations such as BRAF^V600E^ and NRAS, lipid metabolic reprogramming has emerged as a critical factor in tumor progression and therapy resistance. Lipid metabolism [...] Read more.

Melanoma is the deadliest form of skin cancer, characterized by high metastatic potential and intrinsic heterogeneity. In addition to genetic mutations such as BRAF^V600E^ and NRAS, lipid metabolic reprogramming has emerged as a critical factor in tumor progression and therapy resistance. Lipid metabolism supports melanoma cell survival, phenotypic switching, immune evasion, and resistance to targeted therapies and immunotherapy, while also modulating susceptibility to ferroptosis. This review summarizes current knowledge on lipid dysregulation in melanoma, highlighting alterations in fatty acid synthesis, desaturation, uptake, storage, and oxidation, as well as changes in phospholipids, sphingolipids, cholesterol, and bioactive lipid mediators. These lipid pathways are tightly regulated by oncogenic signaling networks, including MAPK and PI3K–AKT–mTOR pathways, and are influenced by tumor microenvironmental stressors such as hypoxia and nutrient limitation. Advances in lipidomics technologies, particularly mass spectrometry-based approaches, have enabled comprehensive profiling of lipid alterations at bulk, spatial, and single-cell levels, offering new opportunities for biomarker discovery and therapeutic stratification. Targeting lipid metabolic vulnerabilities represents a promising strategy to improve melanoma diagnosis, prognosis, and treatment efficacy. Full article

(This article belongs to the Special Issue Advances in Pathogenesis and Treatment of Skin Cancer (2nd Edition))

23 pages, 13046 KB

Open AccessArticle

Parametric Study on an Integrated Sleeve Mortise-and-Tenon Steel–Timber Composite Beam–Column Joints

by Zhanguang Wang, Weihan Yang, Zhenyu Gao and Jianhua Shao

Buildings 2026, 16(2), 435; https://doi.org/10.3390/buildings16020435 (registering DOI) - 20 Jan 2026

Abstract

To address the limitations of traditional timber mortise-and-tenon joints, particularly their low pull-out resistance and rapid stiffness degradation under cyclic loading, this study proposes a novel integrated sleeve mortise-and-tenon steel–timber composite beam–column joint. Building upon prior experimental validation and numerical model verification, a [...] Read more.

To address the limitations of traditional timber mortise-and-tenon joints, particularly their low pull-out resistance and rapid stiffness degradation under cyclic loading, this study proposes a novel integrated sleeve mortise-and-tenon steel–timber composite beam–column joint. Building upon prior experimental validation and numerical model verification, a comprehensive parametric study was conducted to systematically investigate the influence of key geometric parameters on the seismic performance of the joint. The investigated parameters included beam sleeve thickness (1–10 mm), sleeve length (150–350 mm), bolt diameter (4–16 mm), and the dimensions and thickness of stiffeners. The results indicate that a sleeve thickness of 2–3 mm yields the optimal overall performance: sleeves thinner than 2 mm are prone to yielding, while those thicker than 3 mm induce stress concentration in the timber beam. A sleeve length of approximately 250 mm provides the highest initial stiffness and a ductility coefficient exceeding 4.0, representing the best seismic behavior. Bolt diameters within the range of 8–10 mm produce full and stable hysteresis loops, effectively balancing load-carrying capacity and energy dissipation; smaller diameters lead to pinching failure, whereas larger diameters trigger premature plastic deformation in the timber. Furthermore, stiffeners with a width of 40 mm and a thickness of 2 mm effectively enhance joint stiffness, promote a uniform stress distribution, and mitigate local damage. The optimized joint configuration demonstrates excellent ductility, stable hysteretic behavior, and a high load capacity, providing a robust technical foundation for the design and practical application of advanced steel–timber composite connections. Full article

(This article belongs to the Special Issue Advances in Steel and Composite Structures)

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21 pages, 3425 KB

Open AccessArticle

Enhanced Cell Adhesion on Biofunctionalized Ti6Al4V Alloy: Immobilization of Proteins and Biomass from Spirulina platensis Microalgae

by Maria Fernanda Hart Orozco, Rosalia Seña, Lily Margareth Arrieta Payares, Alex A. Saez, Arturo Gonzalez-Quiroga and Virginia Paredes

Int. J. Mol. Sci. 2026, 27(2), 1041; https://doi.org/10.3390/ijms27021041 (registering DOI) - 20 Jan 2026

Abstract

Titanium (Ti) and its alloys are widely used in biomedical applications due to their biocompatibility and corrosion resistance; however, surface modifications are required to enhance biological functionality. Surface functionalization using natural biomolecules has emerged as a promising strategy to improve early cell–surface interactions [...] Read more.

Titanium (Ti) and its alloys are widely used in biomedical applications due to their biocompatibility and corrosion resistance; however, surface modifications are required to enhance biological functionality. Surface functionalization using natural biomolecules has emerged as a promising strategy to improve early cell–surface interactions and biocompatibility of implant materials. In this study, Ti6Al4V alloy surfaces were biofunctionalized using Spirulina platensis (S. platensis) biomass and protein extract to evaluate morphological, chemical, and biological effects. The functionalization process involved activation with piranha solution, silanization with 3-aminopropyltriethoxysilane (APTES), and subsequent biomolecule immobilization. Surface characterization by scanning electron microscopy (SEM), inductively coupled plasma mass spectrometry (ICP-MS), energy-dispersive X-ray spectroscopy (EDS), and Fourier transform infrared spectroscopy (FTIR) confirmed the successful incorporation of microalgal components, including nitrogen-, phosphorus-, and oxygen-rich organic groups. Biomass-functionalized surfaces exhibited higher phosphorus and oxygen content, while protein-coated surfaces showed nitrogen-enrich chemical signatures, reflecting the distinct molecular compositions of the immobilized biomolecules. Cell adhesion assays demonstrated enhanced early cell attachment on biofunctionalized surfaces, particularly in samples functionalized with 5 g/L biomass for three hours, which showed significantly greater cell attachment than both the control and protein-treated samples. These findings highlight the complementary yet distinct roles of S. platensis biomass and protein extract in modulating surface chemistry and cell–material interactions, emphasizing the importance of tailoring biofunctionalization strategies to optimize early biological responses on titanium-based implants. Full article

(This article belongs to the Section Materials Science)

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23 pages, 865 KB

Open AccessArticle

SME Digitalization and Marine Ecotourism as Levers for Coastal Community Welfare: The Role of Local Economic Empowerment in North Minahasa Regency, Indonesia

by Een Novritha Walewangko, Agnes Lutherani C. P. Lapian, Yunita Mandagie and Daniel S. I. Sondakh

Tour. Hosp. 2026, 7(1), 26; https://doi.org/10.3390/tourhosp7010026 (registering DOI) - 20 Jan 2026

Abstract

Marine ecotourism and Small–Medium Enterprise (SME) digitalization are increasingly seen as key drivers for coastal community welfare, yet their combined impact, particularly through local economic empowerment, remains underexplored. This study aims to examine whether marine ecotourism (ME) and SME digitalization (SD) influence local [...] Read more.

Marine ecotourism and Small–Medium Enterprise (SME) digitalization are increasingly seen as key drivers for coastal community welfare, yet their combined impact, particularly through local economic empowerment, remains underexplored. This study aims to examine whether marine ecotourism (ME) and SME digitalization (SD) influence local community welfare (LCW), mediated by SME empowerment (SE), and moderated by government support (GS). A quantitative, cross-sectional survey was conducted with 312 marine tourism entrepreneurs in North Minahasa, Indonesia, and data were analyzed using Partial Least Squares Structural Equation Modeling. The results show that ME and SD have a significant positive effect on SE and LCW. However, ME and SD were found to be insignificant on LCW. Crucially, SE fully mediates the relationship between both ME and SD on LCW, indicating that empowerment is the primary mechanism for welfare improvement. Furthermore, GS was found to significantly strengthen the positive relationship between SE and LCW. This study concludes that empowering local SMEs is the critical bridge for transforming ecotourism and digitalization into tangible community welfare, and this process is significantly amplified by a supportive institutional environment provided by the government. Full article

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21 pages, 4052 KB

Open AccessArticle

On the Development of an AI-Based Tool to Assess the Instantaneous Modal Properties of Nonlinear SDOF Systems

by Alvaro Iglesias-Pordomingo, Guillermo Fernandez, Alvaro Magdaleno and Antolin Lorenzana

Appl. Sci. 2026, 16(2), 1070; https://doi.org/10.3390/app16021070 (registering DOI) - 20 Jan 2026

Abstract

In this article, a data-driven algorithm is developed to assess the natural frequency and damping ratio of a nonlinear oscillating single-degree-of-freedom (SDOF) system. The algorithm is based on hybrid convolutional–long short-term memory neural networks (CNN-LSTM) that process a short moving window belonging to [...] Read more.

In this article, a data-driven algorithm is developed to assess the natural frequency and damping ratio of a nonlinear oscillating single-degree-of-freedom (SDOF) system. The algorithm is based on hybrid convolutional–long short-term memory neural networks (CNN-LSTM) that process a short moving window belonging to a free-decay response and provide estimates of both parameters over time. The novelty of the study resides in the fact that the neural network is trained exclusively using synthetic data issued from linear SDOF models. Since the recurrent neural network (RNN) requires relatively small amounts of data to operate effectively, the nonlinear system locally behaves as a quasi-linear model, allowing each data segment to be processed under this assumption. The proposed RecuID tool is experimentally validated on a laboratory-scale nonlinear SDOF system. To demonstrate its effectiveness, it is compared to conventional identification algorithms. The experimental study yields a maximum mean absolute error (MAE) of 0.244 Hz for the natural frequency and 0.015 for the damping ratio. RecuID proves to be a faster and more robust methodology, capable of handling time-varying damping ratios up to 0.2 and a wide range of natural frequencies defined relative to the sampling rate. Full article

(This article belongs to the Special Issue Nonlinear Dynamics and Vibration)

17 pages, 5027 KB

Open AccessArticle

Symmetry-Enhanced YOLOv8s Algorithm for Small-Target Detection in UAV Aerial Photography

by Zhiyi Zhou, Chengyun Wei, Lubin Wang and Qiang Yu

Symmetry 2026, 18(1), 197; https://doi.org/10.3390/sym18010197 (registering DOI) - 20 Jan 2026

Abstract

In order to solve the problems of small-target detection in UAV aerial photography, such as small scale, blurred features and complex background interference, this article proposes the ACS-YOLOv8s method to optimize the YOLOv8s network: notably, most small man-made targets in UAV aerial scenes [...] Read more.

In order to solve the problems of small-target detection in UAV aerial photography, such as small scale, blurred features and complex background interference, this article proposes the ACS-YOLOv8s method to optimize the YOLOv8s network: notably, most small man-made targets in UAV aerial scenes (e.g., small vehicles, micro-drones) inherently possess symmetry, a key geometric attribute that can significantly enhance the discriminability of blurred or incomplete target features, and thus symmetry-aware mechanisms are integrated into the aforementioned improved modules to further boost detection performance. The backbone network introduces an adaptive feature enhancement module, the edge and detail representation of small targets is enhanced by dynamically modulating the receptive field with deformable attention while also capturing symmetric contour features to strengthen the perception of target geometric structures; a cascaded multi-receptive field module is embedded at the end of the trunk to integrate multi-scale features in a hierarchical manner to take into account both expressive ability and computational efficiency with a focus on fusing symmetric multi-scale features to optimize feature representation; the neck is integrated with a spatially adaptive feature modulation network to achieve dynamic weighting of cross-layer features and detail fidelity and, meanwhile, models symmetric feature dependencies across channels to reduce the loss of discriminative information. Experimental results based on the VisDrone2019 data set show that ACS-YOLOv8s is superior to the baseline model in precision, recall, and mAP indicators, with mAP50 increased by 2.8% to 41.6% and mAP50:90 increased by 1.9% to 25.0%, verifying its effectiveness and robustness in small-target detection in complex drone aerial-photography scenarios. Full article

(This article belongs to the Section Computer)

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17 pages, 1748 KB

Open AccessReview

Next-Generation Biopesticides for the Control of Fungal Plant Pathogens

by Younes Rezaee Danesh, Nurhan Keskin, Solmaz Najafi, Harlene Hatterman-Valenti and Ozkan Kaya

Plants 2026, 15(2), 312; https://doi.org/10.3390/plants15020312 (registering DOI) - 20 Jan 2026

Abstract

This review explores the innovative approaches in the development of next-generation biopesticides, focusing on molecular and microbial strategies for effective control of fungal plant pathogens. As agricultural practices increasingly seek sustainable solutions to combat plant diseases, biopesticides have emerged as a promising alternative [...] Read more.

This review explores the innovative approaches in the development of next-generation biopesticides, focusing on molecular and microbial strategies for effective control of fungal plant pathogens. As agricultural practices increasingly seek sustainable solutions to combat plant diseases, biopesticides have emerged as a promising alternative to chemical pesticides, offering reduced environmental impact and enhanced safety for non-target organisms. The review begins by outlining the critical role of fungal pathogens in global agriculture, emphasizing the need for novel control methods that can mitigate their detrimental effects on crop yields. Key molecular strategies discussed include the use of genetic engineering to enhance the efficacy of biopesticides, the application of RNA interference (RNAi) techniques to target specific fungal genes, and the development of bioactive compounds derived from natural sources. Additionally, this review highlights the potential of microbial agents, such as beneficial bacteria and fungi, in establishing biocontrol mechanisms that promote plant health and resilience. Through a comprehensive review of recent studies and advancements in the field, this manuscript illustrates how integrating molecular and microbial strategies can lead to the development of effective biopesticides tailored to combat specific fungal threats. The implications of these strategies for sustainable agriculture are discussed, alongside the challenges and future directions for research and implementation. Ultimately, this review aims to provide a thorough understanding of the transformative potential of next-generation biopesticides in the fight against fungal plant pathogens, contributing to the broader goal of sustainable food production. Full article

(This article belongs to the Special Issue Biopesticides for Plant Protection)

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29 pages, 1306 KB

Open AccessReview

Medicinal Plants for Overcoming Drug Resistance in Cervical Cancer

by Thabang Patience Marema, Kagiso Laka and Zukile Mbita

Biology 2026, 15(2), 191; https://doi.org/10.3390/biology15020191 (registering DOI) - 20 Jan 2026

Abstract

Drug resistance remains a significant challenge in cancer therapy, accounting for most relapses and contributing substantially to cancer-related mortality worldwide. Several molecular processes are linked to the development of resistance to anticancer drugs, with the most studied mechanisms including epigenetic changes, drug efflux, [...] Read more.

Drug resistance remains a significant challenge in cancer therapy, accounting for most relapses and contributing substantially to cancer-related mortality worldwide. Several molecular processes are linked to the development of resistance to anticancer drugs, with the most studied mechanisms including epigenetic changes, drug efflux, cell survival signalling pathways, and inactivation of anticancer drugs. Both intrinsic and acquired forms of resistance hinder tumour cell elimination, reducing treatment success. This translates to poorer patient outcomes and the need for more aggressive treatment regimens. Therefore, understanding these molecular processes is crucial for enhancing the efficacy of anticancer therapy. Medicinal plants offer potential to counter various resistance mechanisms through their diverse phytocompounds. These compounds may offer benefits including consistent availability, anticancer potency, few side effects, and minimal drug resistance. However, the bioavailability of these phytochemicals and the lack of extensive clinical trials remain key challenges. Therefore, this review provides in-depth information on the mechanisms that lead to drug resistance during cervical cancer therapy, the challenges related to phytochemical bioavailability, the current status, and future needs for clinical trials evaluating the application of medicinal plants to combat drug resistance in cancer cells. Full article

(This article belongs to the Section Medical Biology)

26 pages, 2827 KB

Open AccessArticle

MIO-BDT: Construction of Basic Models and Formal Verification of Building Digital Twins That Supports Multiple Interactive Objects

by Rongwei Zou, Qiliang Yang, Qizhen Zhou, Chao Mou and Zhiwei Zhang

Smart Cities 2026, 9(1), 16; https://doi.org/10.3390/smartcities9010016 (registering DOI) - 20 Jan 2026

Abstract

As a high-fidelity digital mapping of the physical built environment, the Building Digital Twin (BDT) relies on physical–virtual interaction as a core enabler for lifecycle management. However, existing BDT conceptual models predominantly focus on unidirectional or single-threaded physical–virtual interactions, neglecting the dynamic, concurrent [...] Read more.

As a high-fidelity digital mapping of the physical built environment, the Building Digital Twin (BDT) relies on physical–virtual interaction as a core enabler for lifecycle management. However, existing BDT conceptual models predominantly focus on unidirectional or single-threaded physical–virtual interactions, neglecting the dynamic, concurrent exchanges among multiple digital twins and human users. To overcome this limitation, the Multi-Interactive-Object BDT (MIO-BDT) framework is proposed. The central hypothesis is that explicitly modeling concurrent, multi-party interactions within a formalized conceptual structure can address a key representational gap in current BDT paradigms. The work pursues two testable objectives: (1) to formally define the components, relationships, and rules of the MIO-BDT framework and (2) to validate through a representative use case that the framework can model complex interaction scenarios that are inadequately supported by existing approaches. A systematic analysis of the state of the art is first conducted to ground the framework’s design. The MIO-BDT is then elaborated at both the system level (supporting dynamic interactions among twins, users, and physical entities) and the component level (integrating visual, physical, and interaction sub-models). Formal modeling and verification demonstrate that the framework is logically consistent and deadlock-free and effectively coordinates multi-entity data flows. These findings confirm that the MIO-BDT framework provides enhanced representational capacity, structural clarity for system design, and a unified model for diverse interaction types, thereby establishing a validated conceptual foundation for next-generation, interaction-aware BDT systems. Full article

24 pages, 6795 KB

Open AccessFeature PaperArticle

The Analytical Solutions to a Cation–Water Coupled Multiphysics Model of IPMC Sensors

by Kosetsu Ishikawa, Kinji Asaka, Zicai Zhu, Toshiki Hiruta and Kentaro Takagi

Sensors 2026, 26(2), 695; https://doi.org/10.3390/s26020695 (registering DOI) - 20 Jan 2026

Abstract

Ionic polymer–metal composite (IPMC) sensors generate voltages or currents when subjected to deformation. The magnitude and time constant of the electrical response vary significantly with ambient humidity and water content. However, most conventional physical models focus solely on cation dynamics and do not [...] Read more.

Ionic polymer–metal composite (IPMC) sensors generate voltages or currents when subjected to deformation. The magnitude and time constant of the electrical response vary significantly with ambient humidity and water content. However, most conventional physical models focus solely on cation dynamics and do not consider water dynamics. In addition to cation dynamics, Zhu’s model explicitly incorporates the dynamics of water. Consequently, Zhu’s model is considered one of the most promising approaches for physical modeling of IPMC sensors. This paper presents exact analytical solutions to Zhu’s model of IPMC sensors for the first time. The derivation method transforms Zhu’s model into the frequency domain using Laplace transform-based analysis linear approximation together with linear approximation, and subsequently solves it as a boundary value problem of a set of linear ordinary differential equations. The resulting solution is expressed as a transfer function. The input variable is the applied bending deformation, and the output variables include the open-circuit voltage or short-circuit current at the sensor terminals, as well as the distributions of cations, water molecules, and electric potential within the polymer. The obtained transfer functions are represented by irrational functions, which typically arise as solutions to a system of partial differential equations. Furthermore, this paper presents analytical approximations of the step response of the sensor voltage or current by approximating the obtained transfer functions. The steady-state and maximum values of the time response are derived from these analytical approximations. Additionally, the relaxation behavior of the sensor voltage is characterized by a key parameter newly derived from the analytical approximation presented in this paper. Full article

(This article belongs to the Special Issue Advanced Materials for Sensing Application)

27 pages, 12510 KB

Open AccessArticle

The Prediction and Safety Control of the CO₂ Phase Migration Path During the Shutdown Process of Supercritical Carbon Dioxide Pipelines

by Xinze Li, Jianye Li and Yifan Yin

Energies 2026, 19(2), 531; https://doi.org/10.3390/en19020531 (registering DOI) - 20 Jan 2026

Abstract

CO₂ pipeline transportation is a core link in the CCUS (Carbon Capture, Utilization, and Storage Technology) industry. Ensuring the flow safety of CO₂ pipelines under transient conditions is currently a key and challenging issue in industry research. This paper focuses on [...] Read more.

CO₂ pipeline transportation is a core link in the CCUS (Carbon Capture, Utilization, and Storage Technology) industry. Ensuring the flow safety of CO₂ pipelines under transient conditions is currently a key and challenging issue in industry research. This paper focuses on the phase migration and safety control during the shutdown process of supercritical carbon dioxide pipelines. Taking a supercritical carbon dioxide transportation pipeline in Xinjiang Oilfield, China, as the research object, a hydro-thermal coupling model of the pipeline is established to simulate the pipeline and elucidate the coordinated variation patterns of temperature, pressure, density, and phase state. It was found that there were significant differences in the migration paths of the CO₂ phase at different positions. The accuracy of the simulation results was verified through the self-built high-pressure visual reactor experimental system, and the influences of the initial temperature, initial pressure, and ambient temperature before pipeline shutdown on the slope of the phase migration path were explored. The phase migration line slope prediction model was established by using the least squares method and ridge regression method, the process boundary ranges and allowable shutdown time ranges for pipeline safety shutdowns in both summer and winter were further established. The research results show that when the pipeline operates under the low-pressure and high-temperature boundary, the CO₂ in the pipeline vaporizes earlier from the starting point after the pipeline is shut down, and the safe shutdown time of the pipeline is shorter. There is a clear safety operation window in summer, while vaporization risks are widespread in winter. The phase migration path prediction formula and the safety zone division method proposed in this paper provide a theoretical basis and engineering guidance for the safe shutdown control of supercritical carbon dioxide pipelines, which can help reduce operational risks and lower maintenance costs. Full article

(This article belongs to the Special Issue New Advances in Carbon Capture, Utilization and Storage (CCUS))

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20 pages, 4640 KB

Open AccessArticle

Cooperative Effect of Ammonium Polyphosphate and Talcum for Enhancing Fire-Proofing Performance of Silicone Rubber-Based Insulators via Formation of a HIGH-Strength Barrier Layer

by Dong Zhao, Yihan Jiang, Yong Fang, Tingwei Wang and Yucai Shen

Polymers 2026, 18(2), 283; https://doi.org/10.3390/polym18020283 (registering DOI) - 20 Jan 2026

Abstract

Enhancing the flame retardancy of polymeric materials by adding only eco-friendly ammonium polyphosphate (APP) while simultaneously maintaining high-temperature resistance has become a challenge. Talcum has been introduced as a cooperative agent into the silicone rubber/APP system to investigate the effect of talcum on [...] Read more.

Enhancing the flame retardancy of polymeric materials by adding only eco-friendly ammonium polyphosphate (APP) while simultaneously maintaining high-temperature resistance has become a challenge. Talcum has been introduced as a cooperative agent into the silicone rubber/APP system to investigate the effect of talcum on flame retardancy, thermal stability, and high-temperature resistance. The machining process induces the orientation of talcum in the system. The ceramifiable silicone rubber blends containing oriented talcum (e.g., sample SA₆T₄) exhibited superb flame retardancy, including an LOI of 29.4%, a UL-94 rating of V-0, and a peak heat release rate (PHRR) of 250.2 kW·m⁻². More importantly, the blends present excellent thermal stability and high-temperature resistance, characterized by outstanding self-supporting properties and dimensional stability. Based on the structural analysis of the blends and their residues, the made of action for the improved flame retardancy may be attributed to the formation of a compact barrier layer. This layer is formed by oriented talcum platelets combined with phosphoric acid, from the thermal decomposition of APP, promoting crosslinking, thereby achieving a good inhibition barrier to inhibit heat feedback from the condensation zone. The excellent thermal stability and high-temperature resistance of the ceramifiable silicone rubber blends may be ascribed to a cooperative effect between APP and talcum at high temperatures, which facilitates the formation of ceramic structures. The novel ceramifiable silicone rubber composite has potential applications as flame-retardant sealing components for rail transit equipment and encapsulation materials for new energy battery modules. Full article

(This article belongs to the Special Issue Challenges and Innovations in Fire Safety Polymeric Materials)

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18 pages, 1785 KB

Open AccessArticle

Qualitative Analysis for Modifying an Unstable Time-Fractional Nonlinear Schrödinger Equation: Bifurcation, Quasi-Periodic, Chaotic Behavior, and Exact Solutions

by M. M. El-Dessoky, A. A. Elmandouh and A. A. Alghamdi

Mathematics 2026, 14(2), 354; https://doi.org/10.3390/math14020354 (registering DOI) - 20 Jan 2026

Abstract

This work explores the qualitative dynamics of the modified unstable time-fractional nonlinear Schrödinger equation (mUNLSE), a model applicable to nonlinear wave propagation in plasma and optical fiber media. By transforming the governing equation into a planar conservative Hamiltonian system, a detailed bifurcation study [...] Read more.

This work explores the qualitative dynamics of the modified unstable time-fractional nonlinear Schrödinger equation (mUNLSE), a model applicable to nonlinear wave propagation in plasma and optical fiber media. By transforming the governing equation into a planar conservative Hamiltonian system, a detailed bifurcation study is carried out, and the associated equilibrium points are classified using Lagrange’s theorem and phase-plane analysis. A family of exact wave solutions is then constructed in terms of both trigonometric and Jacobi elliptic functions, with solitary, kink/anti-kink, periodic, and super-periodic profiles emerging under suitable parameter regimes and linked directly to the type of the phase plane orbits. The validity of the solutions is discussed through the degeneracy property which is equivalent to the transmission between the phase orbits. The influence of the fractional derivative order on amplitude, localization, and dispersion is illustrated through graphical simulations, exploring the memory impacts in the wave evolution. In addition, an externally periodic force is allowed to act on the mUNLSE model, which is reduced to a perturbed non-autonomous dynamical system. The response to periodic driving is examined, showing transitions from periodic motion to quasi-periodic and chaotic regimes, which are further confirmed by Lyapunov exponent calculations. These findings deepen the theoretical understanding of fractional Schrödinger-type models and offer new insight into complex nonlinear wave phenomena in plasma physics and optical fiber systems. Full article

(This article belongs to the Special Issue Analytical Methods and Qualitative Analysis for Differential Equations)

20 pages, 3935 KB

Open AccessArticle

Multi-Rate PMU Data Fusion in Power Systems via Low Rank Tensor Train

by Yuan Li, Tao Zheng, Yonghua Chen, Shu Zheng, Jingtao Zhao and Bo Sun

Energies 2026, 19(2), 530; https://doi.org/10.3390/en19020530 (registering DOI) - 20 Jan 2026

Abstract

With the continuous development of power systems, WAMS have become increasingly important for real-time system monitoring. As the core devices of WAMS, PMUs can provide synchronized, high-precision, and high-resolution measurements of power system states. However, in practical applications, PMUs deployed in different regions [...] Read more.

With the continuous development of power systems, WAMS have become increasingly important for real-time system monitoring. As the core devices of WAMS, PMUs can provide synchronized, high-precision, and high-resolution measurements of power system states. However, in practical applications, PMUs deployed in different regions often operate at different sampling rates, resulting in multi-rate measurement data and posing challenges for data fusion. To address this issue, this paper proposes a multi-rate PMU data fusion method based on low-rank TT. Specifically, the proposed method first performs tensor-based modeling of multi-rate measurement data, embedding multidimensional correlations into a high-order tensor representation. Then, a data completion model is constructed through low-rank TT decomposition to effectively capture cross-timescale dependencies. Finally, an efficient numerical solution is developed to expand low-resolution measurements into high-resolution data, thereby achieving unified data fusion. Case studies on both simulated and real-world PMU measurement data demonstrate that the proposed approach outperforms traditional interpolation and matrix completion methods, achieving superior reconstruction accuracy and robustness. Full article

28 pages, 10606 KB

Open AccessArticle

Diversity of Cardinium Endosymbiont Genomes from Plant-Parasitic Nematodes

by Sergey V. Tarlachkov, Alexander Y. Ryss, Yury Y. Ilinsky, Dmitry A. Rodionov, Lydmila I. Evtushenko and Sergei A. Subbotin

Int. J. Mol. Sci. 2026, 27(2), 1038; https://doi.org/10.3390/ijms27021038 (registering DOI) - 20 Jan 2026

Abstract

Cardinium endosymbionts are obligate intracellular bacteria found in a wide range of invertebrate hosts. In this study, we generated ten new Cardinium genomes from plant-parasitic nematodes of the genera Amplimerlinius, Bursaphelenchus, Cactodera, Ditylenchus, Globodera, Meloidoderita, and Rotylenchus [...] Read more.

Cardinium endosymbionts are obligate intracellular bacteria found in a wide range of invertebrate hosts. In this study, we generated ten new Cardinium genomes from plant-parasitic nematodes of the genera Amplimerlinius, Bursaphelenchus, Cactodera, Ditylenchus, Globodera, Meloidoderita, and Rotylenchus, revealing their broad ecological and phylogenetic distribution. Using an expanded set of genes, we clarified the relationship between previously defined Cardinium groups B and F from nematodes, showing that they are closely related and likely share a single evolutionary origin within nematode-associated Cardinium. Among the newly assembled Cardinium genomes obtained in this study, two genomes originating from strains associated with wood-inhabiting Bursaphelenchus species exhibited remarkable genome reduction, with estimated sizes of approximately 695 kb. Functional annotation of Cardinium genomes indicated an absence of or a reduction in several central metabolic pathways, including the biotin biosynthetic pathway. A complete biotin pathway was found only in D. weischeri, and this pathway is only partially encoded in Cactodera sp. The polA gene, which encodes DNA polymerase I, showed partial loss in several Cardinium strains. Phylogenetic and comparative genomic analyses provided strong evidence that several carbohydrate, glycerophospholipid, and biotin metabolism genes in these endosymbionts have been acquired through horizontal gene transfer. Future research that integrates high-quality genome assemblies with functional analyses of host–symbiont interactions will be essential to elucidate how metabolic dependency, genome reduction, and horizontal gene transfer collectively shape the evolution and ecological diversification of Cardinium across nematode hosts. Full article

(This article belongs to the Special Issue 25th Anniversary of IJMS: Updates and Advances in Molecular Microbiology)

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18 pages, 548 KB

Open AccessArticle

Respiratory Syncytial Virus Positivity Rate and Clinical Characteristics Amongst Children Under 5 Years of Age at the Emergency and Outpatient Settings in Jordan: A Cross-Sectional Study

by Munir Abu-Helalah, Samah F. Al-Shatnawi, Mohammad Abu Lubad, Enas Al-Zayadneh, Mohammad Al-Hanaktah, Mea’ad Harahsheh, Montaha Al-Iede, Ruba Yousef, Mai Ababneh, Toqa AlZubi, Suad Abu Khousa, Mohammad Al Tamimi and Simon B. Drysdale

Viruses 2026, 18(1), 133; https://doi.org/10.3390/v18010133 (registering DOI) - 20 Jan 2026

Abstract

Background: Acute viral respiratory infections are a major cause of morbidity among young children, with respiratory syncytial virus (RSV) being the leading pathogen. In Jordan and globally, most RSV research has focused on hospitalized patients, while data from emergency departments (EDs) and outpatient [...] Read more.

Background: Acute viral respiratory infections are a major cause of morbidity among young children, with respiratory syncytial virus (RSV) being the leading pathogen. In Jordan and globally, most RSV research has focused on hospitalized patients, while data from emergency departments (EDs) and outpatient settings remain limited. Methods: This cross-sectional study was conducted at two major Jordanian hospitals between November 2022 and March 2023. Children under five years of age presenting to EDs or outpatient clinics with symptoms of acute respiratory infection were enrolled. Nasopharyngeal specimens were tested for RSV, and subtypes (RSV-A and RSV-B) were identified using multiplex RT-PCR. Results: Of 229 enrolled children, 92 (40.2%) tested positive for RSV, with RSV-B accounting for 81.5% of positive cases. RSV positivity was higher in ED presentations than in outpatient clinics (46% vs. 35%). Wheezing (72.8% vs. 39.4%, p < 0.001) and dyspnea (33.7% vs. 14.6%, p = 0.001) were significantly more frequent among RSV-positive patients. Independent predictors of RSV positivity included non-referred outpatient visits (OR = 15.26), non-referred ED visits (OR = 42.93), younger age, and prior systemic steroid use. Conclusions: RSV poses a substantial burden in outpatient and ED settings. Identified demographic and clinical predictors may help target high-risk groups for future preventive interventions. Full article

(This article belongs to the Section Human Virology and Viral Diseases)

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12 pages, 1004 KB

Open AccessArticle

Whole Blood Viscosity and Its Associations with Age, Hematologic Indices, and Serum Biochemical Variables in Clinically Healthy Beagle Dogs and Korean Shorthair Cats

by Jinseok Son, Ji-Hyun Park, Seongjun Kim, Chae-Yeon Hong, Chang-Hwan Moon, Yong-ho Choe, Tae-sung Hwang, Jaemin Kim, Sung-Lim Lee and Dongbin Lee

Vet. Sci. 2026, 13(1), 102; https://doi.org/10.3390/vetsci13010102 (registering DOI) - 20 Jan 2026

Abstract

This study investigated whether Whole blood viscosity (WBV) varies with age in clinically healthy Beagle dogs and Korean Shorthair cats and examined the hematologic and biochemical variables associated with WBV. WBV was measured across multiple shear rates using a scanning capillary viscometry; complete [...] Read more.

This study investigated whether Whole blood viscosity (WBV) varies with age in clinically healthy Beagle dogs and Korean Shorthair cats and examined the hematologic and biochemical variables associated with WBV. WBV was measured across multiple shear rates using a scanning capillary viscometry; complete blood count (CBC) and serum chemistry profiles were also evaluated. Both species demonstrated characteristic shear-thinning behavior. WBV showed a strong association with red blood cell count (RBC), hematocrit (HCT), and hemoglobin (Hb) in both species, with additional association with serum proteins and cholesterol in dogs. No significant relationship between WBV and age was identified at any shear rate, and principal component analysis (PCA) revealed no age-related clustering in the viscosity profiles. These findings indicated that WBV does not exhibit meaningful age-dependent trends in healthy companion animals. This suggests that, in a clinical setting, deviations in normal WBV are more likely to influence underlying physiological or pathological factors than normal aging. Full article

(This article belongs to the Section Veterinary Physiology, Pharmacology, and Toxicology)

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30 pages, 37639 KB

Open AccessArticle

State-Of-The-Art Path Optimisation for Automated Open-Pit Mining Drill Rigs: A Deterministic Approach

by Masoud Samaei, Roohollah Shirani Faradonbeh, Erkan Topal and Joshua Goodwin

Appl. Sci. 2026, 16(2), 1069; https://doi.org/10.3390/app16021069 (registering DOI) - 20 Jan 2026

Abstract

This study introduces a deterministic framework for optimising the path planning of autonomous drill rigs in open-pit mining operations. While prior research has primarily focused on automating drilling mechanics, this study addresses the essential but underexplored phase of tramming, defined as the rig’s [...] Read more.

This study introduces a deterministic framework for optimising the path planning of autonomous drill rigs in open-pit mining operations. While prior research has primarily focused on automating drilling mechanics, this study addresses the essential but underexplored phase of tramming, defined as the rig’s non-productive movement between holes. The proposed approach integrates geometric pattern recognition and slope-based route alignment. It also incorporates practical maneuverability constraints to generate efficient, smooth, and safe paths. Unlike evolutionary algorithms, which suffer from variability and demand extensive computation, this method delivers fast and consistent results. These are well-suited to the dynamic conditions of real-world mining. Applied to a 1596-hole case study, the framework reduced tramming time by over 50%, shortening the total project duration by 8% compared with the actual project. The findings demonstrate its potential to improve both operational efficiency and commercial readiness for autonomous drilling systems. Full article

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22 pages, 5115 KB

Open AccessArticle

Intelligent Detection Method of Defects in High-Rise Building Facades Using Infrared Thermography

by Daiming Liu, Yongqiang Jin, Yuan Yang, Zhenyang Xiao, Zeming Zhao, Changling Gao and Dingcheng Zhang

Sensors 2026, 26(2), 694; https://doi.org/10.3390/s26020694 (registering DOI) - 20 Jan 2026

Abstract

High-rise building facades are prone to defects due to prolonged exposure to complex environments. Infrared detection, as a commonly employed method for facade defect inspection, often results in low accuracy owing to abundant interferences and blurred defect boundaries. In this work, an intelligent [...] Read more.

High-rise building facades are prone to defects due to prolonged exposure to complex environments. Infrared detection, as a commonly employed method for facade defect inspection, often results in low accuracy owing to abundant interferences and blurred defect boundaries. In this work, an intelligent defect detection method for high-rise building facades is proposed. In the first stage of the proposed method, a segmentation model based on DeepLabV3+ is proposed to remove interferences in infrared images using masks. The model incorporates a Post-Decoder Dual-Branch Boundary Refinement Module, which is subdivided into a boundary feature optimization branch and a boundary-guided attention branch. Sub-pixel-level contour refinement and boundary-adaptive weighting are hence achieved to mitigate edge blurring induced by thermal diffusion and to enhance the perception of slender cracks and cavity edges. A triple constraint mechanism is also introduced, combining cross-entropy, multi-scale Dice, and boundary-aware losses to address class imbalance and enhance segmentation performance for small targets. Furthermore, superpixel linear iterative clustering (SLIC) is utilized to enforce regional consistency, hence improving the smoothness and robustness of predictions. In the second stage of the proposed method, a defect detection model based on YOLOV11 is proposed to process masked infrared images for detecting hollow, seepage, cracks and detachment. This work validates the proposed method using 180 infrared images collected via unmanned aerial vehicles. The experimental results demonstrate that the proposed method achieves a detection precision of 89.7%, an mAP@0.5 of 87.9%, and a 57.8 mAP@50-95. surpassing other algorithms and confirming its effectiveness and superiority. Full article

(This article belongs to the Section Fault Diagnosis & Sensors)

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17 pages, 5670 KB

Open AccessArticle

Gne-Depletion in C2C12 Myoblasts Leads to Alterations in Glycosylation and Myopathogene Expression

by Carolin T. Neu, Aristotelis Antonopoulos, Anne Dell, Stuart M. Haslam and Rüdiger Horstkorte

Cells 2026, 15(2), 199; https://doi.org/10.3390/cells15020199 (registering DOI) - 20 Jan 2026

Abstract

GNE myopathy is a rare genetic neuromuscular disorder caused by mutations in the GNE gene. The respective gene product, UDP-N-acetylglucosamine 2-epimerase/N-acetylmannosamine kinase (GNE), is a bifunctional enzyme that initiates endogenous sialic acid biosynthesis. Sialic acids are important building blocks [...] Read more.

GNE myopathy is a rare genetic neuromuscular disorder caused by mutations in the GNE gene. The respective gene product, UDP-N-acetylglucosamine 2-epimerase/N-acetylmannosamine kinase (GNE), is a bifunctional enzyme that initiates endogenous sialic acid biosynthesis. Sialic acids are important building blocks for the glycosylation machinery of cells and are typically found at the terminal ends of glycoprotein N- and O-glycans. The exact pathomechanism of GNE myopathy remains elusive, and a better understanding of the disease is urgently needed for the development of therapeutic strategies. The purpose of this study was to examine the effects of hyposialylation on glycan structures and subsequent downstream effects in the C2C12 Gne knockout cell model. No overall remodeling of N-glycans was observed in the absence of Gne, but differences in glycosaminoglycan expression and O-GlcNAcylation were detected. Expression analysis of myopathogenes revealed concomitant down-regulation of muscle-specific genes. Among the top candidates were the sodium channel protein type 4 subunit α (Scn4a), voltage-dependent L-type calcium channel subunit α-1s (Cacna1s), ryanodine receptor 1 (Ryr1), and glycogen phosphorylase (Pygm), which are associated with excitation-contraction coupling and energy metabolism. The results suggest that remodeling of the glycome could have detrimental effects on intracellular signaling, excitability of skeletal muscle tissue, and glucose metabolism. Full article

14 pages, 637 KB

Open AccessArticle

Doppler Waveform Alterations of the Supratesticular Artery and Associated Semen Biomarkers in Infertile Male Dromedary Camels

by Derar Derar, Ahmed Ali, Fahad A. Alshanbari and Mohammed H. Elzagafi

Animals 2026, 16(2), 319; https://doi.org/10.3390/ani16020319 (registering DOI) - 20 Jan 2026

Abstract

Male infertility in dromedary camels lacks objective diagnostic tools. This study evaluated the combined diagnostic value of testicular Doppler ultrasonography and semen biomarkers in 68 infertile (azoospermic, n = 21; oligozoospemic, n = 47) and 9 fertile male camels. All animals underwent a [...] Read more.

Male infertility in dromedary camels lacks objective diagnostic tools. This study evaluated the combined diagnostic value of testicular Doppler ultrasonography and semen biomarkers in 68 infertile (azoospermic, n = 21; oligozoospemic, n = 47) and 9 fertile male camels. All animals underwent a breeding soundness evaluation; computer-assisted semen analysis; color Doppler of the supratesticular artery; and a seminal plasma assessment for semenogelin I (SEM I), semenogelin II (SEM II), extracellular matrix protein 1 (ECM1), and testis-expressed protein 101 (TEX101). Infertile camels showed significantly impaired semen quality (p < 0.001). All four biomarkers were significantly lower in the infertile groups than controls (p = 0.001). Doppler indices indicated impaired testicular perfusion, with higher resistive and pulsatility indices (p = 0.003; p = 0.009) and lower velocity parameters (p < 0.001) in infertile animals. Biomarkers were strongly intercorrelated and negatively correlated with Doppler indices. ECM1 was the only significant predictor of infertility from the regression analysis (p = 0.031). Among the oligozoospemic camels stratified by motility, the >50% motility group had significantly higher SEM I and SEM II concentrations (p < 0.002). Integrating Doppler ultrasonography with biomarker profiling provides complementary diagnostic indicators for male camel infertility. Full article

(This article belongs to the Section Animal Reproduction)

25 pages, 9600 KB

Open AccessArticle

Shaft-Rate Magnetic Field Localization Algorithm Based on Improved Exponential Triangular Optimization

by Bozhong Lei, Ranfeng Wang, Cheng Chi, Lu Yu, Zhentao Yu and Dan Wang

J. Mar. Sci. Eng. 2026, 14(2), 216; https://doi.org/10.3390/jmse14020216 (registering DOI) - 20 Jan 2026

Abstract

Addressing the issues of low positioning accuracy and poor robustness in shaft-rate magnetic fields, this study introduces the Improved Exponential Triangular Optimization Algorithm (IETO). By incorporating adaptive attenuation factors, dynamic population reduction, and intelligent boundary contraction strategies, it significantly enhances the global search [...] Read more.

Addressing the issues of low positioning accuracy and poor robustness in shaft-rate magnetic fields, this study introduces the Improved Exponential Triangular Optimization Algorithm (IETO). By incorporating adaptive attenuation factors, dynamic population reduction, and intelligent boundary contraction strategies, it significantly enhances the global search capability and robustness. A magnetic dipole localization model is developed, and comparative simulations show that IETO achieves reliable accuracy and robustness under low signal-to-noise ratio (SNR) conditions, reducing localization error by 7.82% compared with the conventional Exponential Triangular Optimization Algorithm (ETO). The effects of base station deployment, number of stations, and sea depth on localization performance are further examined, and the capability of IETO for dynamic target tracking is verified. Preliminary sea trial results confirm the practical feasibility and engineering applicability of the proposed method. Full article

(This article belongs to the Special Issue Advanced Studies in Marine Data Analysis)

18 pages, 450 KB

Open AccessReview

Metabolic Dysfunction at the Core: Revisiting the Overlap of Cardiovascular, Renal, Hepatic, and Endocrine Disorders

by Maria-Daniela Tanasescu, Andrei-Mihnea Rosu, Alexandru Minca, Andreea-Liana Rosu, Maria-Mihaela Grigorie, Delia Timofte and Dorin Ionescu

Life 2026, 16(1), 172; https://doi.org/10.3390/life16010172 (registering DOI) - 20 Jan 2026

Abstract

Metabolic dysfunction has emerged as a central driver of cardiovascular, renal, hepatic, and endocrine disorders, challenging traditional organ-specific disease models. Increasing evidence indicates that conditions such as obesity, type 2 diabetes, chronic kidney disease, heart failure, and metabolic dysfunction–associated steatotic liver disease frequently [...] Read more.

Metabolic dysfunction has emerged as a central driver of cardiovascular, renal, hepatic, and endocrine disorders, challenging traditional organ-specific disease models. Increasing evidence indicates that conditions such as obesity, type 2 diabetes, chronic kidney disease, heart failure, and metabolic dysfunction–associated steatotic liver disease frequently develop in parallel, reflecting shared upstream metabolic abnormalities rather than isolated pathologies. This narrative review synthesizes recent clinical, epidemiologic, biomarker, and therapeutic evidence to examine metabolic dysfunction as a unifying framework for multisystem disease, with particular focus on the cardiovascular–renal–hepatic–metabolic (CRHM) model. A targeted literature search of major biomedical databases was conducted to identify relevant studies published between 2020 and 2025, encompassing observational cohorts, randomized trials, and integrative reviews addressing cross-organ metabolic interactions. The reviewed evidence highlights consistent clinical overlap across organ systems, stage-dependent risk amplification and the utility of shared metabolic and inflammatory biomarkers in capturing multisystem vulnerability. In parallel, contemporary metabolic therapies demonstrate coordinated benefits across cardiovascular, renal, and hepatic domains, supporting the concept of common modifiable disease drivers. The reviewed evidence supports a shift from organ-based toward metabolic-centric frameworks for risk stratification and prevention. Viewing metabolic dysfunction as the organizing principle of cardiometabolic disease may improve recognition of multisystem risk, facilitate earlier intervention, and provide a more coherent foundation for precision and preventive medicine, in an era of growing cardiometabolic multimorbidity. Full article

(This article belongs to the Special Issue Advances in Vascular Health and Metabolism)

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23 pages, 9975 KB

Open AccessArticle

Leveraging LiDAR Data and Machine Learning to Predict Pavement Marking Retroreflectivity

by Hakam Bataineh, Dmitry Manasreh, Munir Nazzal and Ala Abbas

Vehicles 2026, 8(1), 23; https://doi.org/10.3390/vehicles8010023 (registering DOI) - 20 Jan 2026

Abstract

This study focused on developing and validating machine learning models to predict pavement marking retroreflectivity using Light Detection and Ranging (LiDAR) intensity data. The retroreflectivity data was collected using a Mobile Retroreflectometer Unit (MRU) due to its increasing acceptance among states as a [...] Read more.

This study focused on developing and validating machine learning models to predict pavement marking retroreflectivity using Light Detection and Ranging (LiDAR) intensity data. The retroreflectivity data was collected using a Mobile Retroreflectometer Unit (MRU) due to its increasing acceptance among states as a compliant measurement device. A comprehensive dataset was assembled spanning more than 1000 miles of roadways, capturing diverse marking materials, colors, installation methods, pavement types, and vehicle speeds. The final dataset used for model development focused on dry condition measurements and roadway segments most relevant to state transportation agencies. A detailed synchronization process was implemented to ensure the accurate pairing of retroreflectivity and LiDAR intensity values. Using these data, several machine learning techniques were evaluated, and an ensemble of gradient boosting-based models emerged as the top performer, predicting pavement retroreflectivity with an R² of 0.94 on previously unseen data. The repeatability of the predicted retroreflectivity was tested and showed similar consistency as the MRU. The model’s accuracy was confirmed against independent field segments demonstrating the potential for LiDAR to serve as a practical, low-cost alternative for MRU measurements in routine roadway inspection and maintenance. The approach presented in this study enhances roadway safety by enabling more frequent, network-level assessments of pavement marking performance at lower cost, allowing agencies to detect and correct visibility problems sooner and helping to prevent nighttime and adverse weather crashes. Full article

(This article belongs to the Special Issue Emerging Transportation Safety and Operations: Practical Perspectives, 2nd Edition)

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24 pages, 1005 KB

Open AccessSystematic Review

The Benefits and Challenges of Using the Demonstration Method in STEM Education: A Systematic Literature Review

by Chak-Him Fung and Siu-Ping Ng

Educ. Sci. 2026, 16(1), 161; https://doi.org/10.3390/educsci16010161 (registering DOI) - 20 Jan 2026

Abstract

The education field has been striving to develop STEM teaching and learning methodologies that effectively integrate subject knowledge across disciplines and connect it to daily life. Many teachers believe that practical work can help students better grasp abstract concepts. However, they often hesitate [...] Read more.

The education field has been striving to develop STEM teaching and learning methodologies that effectively integrate subject knowledge across disciplines and connect it to daily life. Many teachers believe that practical work can help students better grasp abstract concepts. However, they often hesitate to incorporate practical work due to constraints, such as limited resources and a lack of experimental skills among students. As a result, demonstrations are frequently used as an alternative. This study presents the findings of a systematic literature review conducted in accordance with PRISMA guidelines, analyzing the advantages, disadvantages, and potential enhancements of using the demonstration method in STEM education. After examining 49 relevant studies, this review identified 15 benefits and 14 challenges associated with the demonstration method, encompassing their impact on students, teachers, and operational aspects. Additionally, six key components were discovered that enhance the efficacy of the demonstration method. Based on the findings, recommendations are proposed for policymakers, universities, and schools to improve the implementation and outcomes of demonstration-based teaching and learning in STEM education. Full article

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