Sign in to use this feature.

Years

Between: -

Subjects

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Journals

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Article Types

Countries / Regions

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Search Results (291,962)

Search Parameters:
Keywords = Generic

Order results
Result details
Results per page
Select all
Export citation of selected articles as:
24 pages, 17580 KB  
Article
Integrating Cloud Computing and Landscape Metrics to Enhance Land Use/Land Cover Mapping and Dynamic Analysis in the Shandong Peninsula Urban Agglomeration
by Jue Xiao, Longqian Chen, Ting Zhang, Gan Teng and Linyu Ma
Land 2025, 14(10), 1997; https://doi.org/10.3390/land14101997 (registering DOI) - 4 Oct 2025
Abstract
Accurate land use/land cover (LULC) maps generated through cloud computing can support large-scale land management. Leveraging the rich resources of Google Earth Engine (GEE) is essential for developing historical maps that facilitate the analysis of regional LULC dynamics. We implemented the best-performing scheme [...] Read more.
Accurate land use/land cover (LULC) maps generated through cloud computing can support large-scale land management. Leveraging the rich resources of Google Earth Engine (GEE) is essential for developing historical maps that facilitate the analysis of regional LULC dynamics. We implemented the best-performing scheme on GEE to produce 30 m LULC maps for the Shandong Peninsula urban agglomeration (SPUA) and to detect LULC changes, while closely observing the spatio-temporal trends of landscape patterns during 2004–2024 using the Shannon Diversity Index, Patch Density, and other metrics. The results indicate that (a) Gradient Tree Boost (GTB) marginally outperformed Random Forest (RF) under identical feature combinations, with overall accuracies consistently exceeding 90.30%; (b) integrating topographic features, remote sensing indices, spectral bands, land surface temperature, and nighttime light data into the GTB classifier yielded the highest accuracy (OA = 93.68%, Kappa = 0.92); (c) over the 20-year period, cultivated land experienced the most substantial reduction (11,128.09 km2), accompanied by impressive growth in built-up land (9677.21 km2); and (d) landscape patterns in central and eastern SPUA changed most noticeably, with diversity, fragmentation, and complexity increasing, and connectivity decreasing. These results underscore the strong potential of GEE for LULC mapping at the urban agglomeration scale, providing a robust basis for long-term dynamic process analysis. Full article
(This article belongs to the Special Issue Large-Scale LULC Mapping on Google Earth Engine (GEE))
24 pages, 8062 KB  
Article
Asphalt Binder Rheological Performance Properties Using Recycled Plastic Wastes and Commercial Polymers
by Hamad I. Al Abdul Wahhab, Waqas Rafiq, Mohammad Ahsan Habib, Ali Mohammed Babalghaith, Suleiman Abdulrahman and Shaban Shahzad
Constr. Mater. 2025, 5(4), 75; https://doi.org/10.3390/constrmater5040075 (registering DOI) - 4 Oct 2025
Abstract
Polymer-based product usage in modern society is increasing day by day. Following usage, these inert products and hydrophobic materials contribute to environmental pollution, often accumulating as litter in ecosystems and contaminating water bodies. The rapid socio-economic development in the Kingdom of Saudi Arabia [...] Read more.
Polymer-based product usage in modern society is increasing day by day. Following usage, these inert products and hydrophobic materials contribute to environmental pollution, often accumulating as litter in ecosystems and contaminating water bodies. The rapid socio-economic development in the Kingdom of Saudi Arabia (KSA) has resulted in a significant increase in waste generation. This study was conducted on the utilization of recycled plastic waste (RPW) polymer along with commercial polymer (CP) for the modification of the local binder. The hot environmental conditions and increased traffic loading are the major reasons for the permanent deformation and thermal cracks on the pavements, which require improved and modified road performance materials. The Ministry of Transport and Logistical Support (MOTLS) in Saudi Arabia, along with other related agencies, spends a substantial amount of money each year on importing modifiers, including chemicals, hydrocarbons, and polymers, for modification purposes. This research was conducted to investigate and utilize available local recycled plastic materials. Comprehensive laboratory experiments were designed and carried out to enhance recycled plastic waste, including low-density polyethylene (rLDPE), high-density polyethylene (rHDPE), and polypropylene (rPP), combined with varying percentages of commercially available polymers such as Styrene-Butadiene-Styrene (SBS) and Polybilt (PB). The results indicated that incorporating recycled plastic waste expanded the binder’s susceptible temperature range from 64 °C to 70 °C, 76 °C, and 82 °C. The resistance to rutting was shown to have significantly improved by the dynamic shear rheometer (DSR) examination. Achieving the objectives of this research, combined with the intangible environmental benefits of utilizing plastic waste, provides a sustainable pavement development option that is also environmentally beneficial. Full article
Show Figures

Figure 1

26 pages, 5700 KB  
Article
Hospital-Oriented Development (HOD): A Quantitative Morphological Analysis for Collaborative Development of Healthcare and Daily Life
by Ziyi Chen, Yizhuo Wang, Hua Zhang, Jingmeng Lei, Haochun Tan, Xuan Wang and Yu Ye
Land 2025, 14(10), 1996; https://doi.org/10.3390/land14101996 (registering DOI) - 4 Oct 2025
Abstract
With the global trend of population aging, human-centered development that integrates medical convenience with daily life quality has become a critical necessity. However, conceptual frameworks, evaluation methods, and spatial prototypes for such ‘healthcare–daily-life’ development remain limited. This study proposes Hospital-Oriented Development (HOD) as [...] Read more.
With the global trend of population aging, human-centered development that integrates medical convenience with daily life quality has become a critical necessity. However, conceptual frameworks, evaluation methods, and spatial prototypes for such ‘healthcare–daily-life’ development remain limited. This study proposes Hospital-Oriented Development (HOD) as a framework to promote collaborative development by considering both hospital accessibility and urban development intensity, derived from multi-sourced urban data. First, a conceptual framework was established, consisting of three dimensions, i.e., network accessibility, facility completeness, and environmental comfort, which was then characterized by twelve indicators based on urban morphological features. Second, these indicators were quantitatively evaluated through detailed values measured among 20 exemplary hospitals in Shanghai selected via user-generated content. Finally, HOD performance and morphology informed the spatial prototype. The results reveal confidence intervals for each indicator and recommended spatial features. Numerically, there was a positive correlation between facility completeness and network accessibility, but a negative correlation with environmental comfort. Spatially, a context-specific HOD prototype for China was developed. This study proposes the concept of HOD, delivers quantitative measurements, and develops a spatial prototype via empirical research, providing theoretical insights and evidence to support the improvement in healthcare environments from a human-centered perspective. Full article
(This article belongs to the Special Issue Feature Papers on Land Use, Impact Assessment and Sustainability)
19 pages, 4512 KB  
Article
Real-Time Cycle Slip Detection in Single-Frequency GNSS Receivers Using Dual-Index Cross-Validation and Elevation-Dependent Thresholding
by Mireia Carvajal Librado and Kwan-Dong Park
Sensors 2025, 25(19), 6162; https://doi.org/10.3390/s25196162 (registering DOI) - 4 Oct 2025
Abstract
Cycle slips, abrupt discontinuities in carrier-phase measurements, pose a significant challenge for single-frequency GNSS receivers, particularly in real-time applications where rapid detection is critical. Unlike dual-frequency approaches, these receivers cannot rely on redundant combinations to isolate slips from other errors. This study proposes [...] Read more.
Cycle slips, abrupt discontinuities in carrier-phase measurements, pose a significant challenge for single-frequency GNSS receivers, particularly in real-time applications where rapid detection is critical. Unlike dual-frequency approaches, these receivers cannot rely on redundant combinations to isolate slips from other errors. This study proposes a real-time cycle slip detection algorithm for single-frequency GNSS receivers based solely on short-term differencing of pseudorange and carrier-phase observables. The method employs a two-step logic: first-order differencing of code-minus-carrier and second-order differencing of carrier phase. Both steps employ satellite elevation-dependent adaptive thresholds, enabling robust detection under diverse signal conditions. The method requires no user position, receiver-generated tracking flags, or additional sensor data. Experimental results reveal that the algorithm achieves over 98% detection accuracy for slips exceeding 10 cycles, with no false positives in artificial slip testing, and 87.93% agreement with Loss of Lock Indicators (LLI) during periods in which the receiver indicated signal instability. Full article
(This article belongs to the Section Navigation and Positioning)
Show Figures

Figure 1

27 pages, 1664 KB  
Review
Actomyosin-Based Nanodevices for Sensing and Actuation: Bridging Biology and Bioengineering
by Nicolas M. Brunet, Peng Xiong and Prescott Bryant Chase
Biosensors 2025, 15(10), 672; https://doi.org/10.3390/bios15100672 (registering DOI) - 4 Oct 2025
Abstract
The actomyosin complex—nature’s dynamic engine composed of actin filaments and myosin motors—is emerging as a versatile tool for bio-integrated nanotechnology. This review explores the growing potential of actomyosin-powered systems in biosensing and actuation applications, highlighting their compatibility with physiological conditions, responsiveness to biochemical [...] Read more.
The actomyosin complex—nature’s dynamic engine composed of actin filaments and myosin motors—is emerging as a versatile tool for bio-integrated nanotechnology. This review explores the growing potential of actomyosin-powered systems in biosensing and actuation applications, highlighting their compatibility with physiological conditions, responsiveness to biochemical and physical cues and modular adaptability. We begin with a comparative overview of natural and synthetic nanomachines, positioning actomyosin as a uniquely scalable and biocompatible platform. We then discuss experimental advances in controlling actomyosin activity through ATP, calcium, heat, light and electric fields, as well as their integration into in vitro motility assays, soft robotics and neural interface systems. Emphasis is placed on longstanding efforts to harness actomyosin as a biosensing element—capable of converting chemical or environmental signals into measurable mechanical or electrical outputs that can be used to provide valuable clinical and basic science information such as functional consequences of disease-associated genetic variants in cardiovascular genes. We also highlight engineering challenges such as stability, spatial control and upscaling, and examine speculative future directions, including emotion-responsive nanodevices. By bridging cell biology and bioengineering, actomyosin-based systems offer promising avenues for real-time sensing, diagnostics and therapeutic feedback in next-generation biosensors. Full article
(This article belongs to the Special Issue Biosensors for Personalized Treatment)
Show Figures

Figure 1

16 pages, 1669 KB  
Article
An Improved Adaptive Kalman Filter Positioning Method Based on OTFS
by Siqi Xia, Aijun Liu and Xiaohu Liang
Sensors 2025, 25(19), 6157; https://doi.org/10.3390/s25196157 (registering DOI) - 4 Oct 2025
Abstract
To mitigate the degradation of positioning accuracy in sixth-generation mobile communication systems under dynamic line-of-sight (LOS) and non-line-of-sight (NLOS) conditions, this paper proposes an improved adaptive Kalman filter positioning method based on Orthogonal Time Frequency Space (OTFS)-modulated signals. Firstly, the distance can be [...] Read more.
To mitigate the degradation of positioning accuracy in sixth-generation mobile communication systems under dynamic line-of-sight (LOS) and non-line-of-sight (NLOS) conditions, this paper proposes an improved adaptive Kalman filter positioning method based on Orthogonal Time Frequency Space (OTFS)-modulated signals. Firstly, the distance can be measured by using the OTFS-modulated signals transmitted between base stations and nodes. Secondly, the distance information is converted into the distance difference information to establish the time difference of arrival (TDOA) positioning equation, which is preliminarily solved using the Chan algorithm. Thirdly, residuals are calculated based on the preliminary positioning results, dividing the complex environment into distinct regions and adaptively determining corresponding genetic factors for each region. Finally, the selected genetic parameters are substituted into the Sage–Husa adaptive Kalman filter equations to estimate positioning results. The simulation analysis demonstrates that in complex environments featuring both line-of-sight and non-line-of-sight conditions, the vehicle motion trajectories estimated using this method more closely approximate actual trajectories. Additionally, both the accuracy and stability of positioning results show significant improvement compared to traditional methods. Full article
(This article belongs to the Section Communications)
Show Figures

Figure 1

29 pages, 9032 KB  
Article
Multi-Agent Deep Reinforcement Learning for Joint Task Offloading and Resource Allocation in IIoT with Dynamic Priorities
by Yongze Ma, Yanqing Zhao, Yi Hu, Xingyu He and Sifang Feng
Sensors 2025, 25(19), 6160; https://doi.org/10.3390/s25196160 (registering DOI) - 4 Oct 2025
Abstract
The rapid growth of Industrial Internet of Things (IIoT) terminals has resulted in tasks exhibiting increased concurrency, heterogeneous resource demands, and dynamic priorities, significantly increasing the complexity of task scheduling in edge computing. Cloud–edge–end collaborative computing leverages cross-layer task offloading to alleviate edge [...] Read more.
The rapid growth of Industrial Internet of Things (IIoT) terminals has resulted in tasks exhibiting increased concurrency, heterogeneous resource demands, and dynamic priorities, significantly increasing the complexity of task scheduling in edge computing. Cloud–edge–end collaborative computing leverages cross-layer task offloading to alleviate edge node resource contention and improve task scheduling efficiency. However, existing methods generally neglect the joint optimization of task offloading, resource allocation, and priority adaptation, making it difficult to balance task execution and resource utilization under resource-constrained and competitive conditions. To address this, this paper proposes a two-stage dynamic-priority-aware joint task offloading and resource allocation method (DPTORA). In the first stage, an improved Multi-Agent Proximal Policy Optimization (MAPPO) algorithm integrated with a Priority-Gated Attention Module (PGAM) enhances the robustness and accuracy of offloading strategies under dynamic priorities; in the second stage, the resource allocation problem is formulated as a single-objective convex optimization task and solved globally using the Lagrangian dual method. Simulation results show that DPTORA significantly outperforms existing multi-agent reinforcement learning baselines in terms of task latency, energy consumption, and the task completion rate. Full article
(This article belongs to the Section Internet of Things)
Show Figures

Figure 1

19 pages, 2759 KB  
Article
Carbon-Source Effects on Growth and Secondary Metabolism in the Marine Bacteroidota Tenacibaculum mesophilum and Fulvivirga kasyanovii
by Luis Linares-Otoya, Virginia Linares-Otoya, Gladys Galliani-Huamanchumo, Terecita Carrion-Zavaleta, Jose Condor-Goytizolo, Till F. Schäberle, Mayar L. Ganoza-Yupanqui and Julio Campos-Florian
Mar. Drugs 2025, 23(10), 394; https://doi.org/10.3390/md23100394 (registering DOI) - 4 Oct 2025
Abstract
Marine Bacteroidota are recognized bacterial producers of bioactive metabolites, yet their biosynthetic potential remains cryptic under standard laboratory conditions. Here, we developed chemically defined media for Fulvivirga kasyanovii 48LL (Cytophagia) and Tenacibaculum mesophilum fLL (Flavobacteriia) to evaluate the effect of environmentally relevant carbon [...] Read more.
Marine Bacteroidota are recognized bacterial producers of bioactive metabolites, yet their biosynthetic potential remains cryptic under standard laboratory conditions. Here, we developed chemically defined media for Fulvivirga kasyanovii 48LL (Cytophagia) and Tenacibaculum mesophilum fLL (Flavobacteriia) to evaluate the effect of environmentally relevant carbon sources on growth and secondary metabolism. F. kasyanovii utilized 31 of 34 tested carbon sources whereas T. mesophilum grew on only five substrates, underscoring a distinct nutritional preferences. Substrate significantly influenced the antibacterial activity of F. kasyanovii extracts. Growth on β-1,3-glucan, glycerol, poly(β-hydroxybutyrate) (PHB), fish gelatin, or pectin resulted in extracts generating the largest inhibition zones (10–13 mm) against Bacillus subtilis or Rossellomorea marisflavi. Genome analysis revealed F. kasyanovii to be enriched in biosynthetic gene clusters (BGCs), notably harboring a ~570 kb genomic island comprising five large NRPS/PKS-type clusters. Quantitative PCR confirmed carbon-source-dependent regulation of these operons: glucose induced BGC1, BGC3, and BGC4, while κ-carrageenan and PHB upregulated BGC2. Conversely, yeast–peptone medium (analogous to standard marine broth) repressed transcription across all active clusters. These findings demonstrate that naturally occurring carbon sources can selectively activate cryptic BGCs and modulate antibacterial activity in F. kasyanovii, suggesting that similar strategy can be used for natural-product discovery in marine Bacteroidota. Full article
(This article belongs to the Special Issue Fermentation Processes for Obtaining Marine Bioactive Products)
Show Figures

Figure 1

54 pages, 3027 KB  
Article
Numerical Analysis of Aerodynamics and Aeroacoustics in Heterogeneous Vehicle Platoons: Impacts on Fuel Consumption and Environmental Emissions
by Wojciech Bronisław Ciesielka and Władysław Marek Hamiga
Energies 2025, 18(19), 5275; https://doi.org/10.3390/en18195275 (registering DOI) - 4 Oct 2025
Abstract
The systematic economic development of European Union member states has resulted in a dynamic increase in road transport, accompanied by adverse environmental impacts. Consequently, research efforts have focused on identifying technical solutions to reduce fuel and/or energy consumption. One promising approach involves the [...] Read more.
The systematic economic development of European Union member states has resulted in a dynamic increase in road transport, accompanied by adverse environmental impacts. Consequently, research efforts have focused on identifying technical solutions to reduce fuel and/or energy consumption. One promising approach involves the formation of homogeneous and heterogeneous vehicle platoons. This study presents the results of numerical simulations and analyses of aerodynamic and aeroacoustic phenomena generated by heterogeneous vehicle platoons composed of passenger cars, delivery vans, and trucks. A total of 54 numerical models were developed in various configurations, considering three vehicle speeds and three inter-vehicle distances. The analysis was conducted using Computational Fluid Dynamics (CFD) methods with the following two turbulence models: the k–ω Shear Stress Transport (SST) model and Large Eddy Simulation (LES), combined with the Ffowcs Williams–Hawkings acoustic analogy to determine sound pressure levels. Verification calculations were performed using methods dedicated to environmental noise analysis, supplemented by acoustic field measurements. The results conclusively demonstrate that vehicle movement in specific platoon configurations can lead to significant fuel and/or energy savings, as well as reductions in harmful emissions. This solution may be implemented in the future as an integral component of Intelligent Transportation Systems (ITSs) and Intelligent Environmental Management Systems (IEMSs). Full article
31 pages, 1561 KB  
Review
Emerging Radioligands as Tools to Track Multi-Organ Senescence
by Anna Gagliardi, Silvia Migliari, Alessandra Guercio, Giorgio Baldari, Tiziano Graziani, Veronica Cervati, Livia Ruffini and Maura Scarlattei
Diagnostics 2025, 15(19), 2518; https://doi.org/10.3390/diagnostics15192518 (registering DOI) - 4 Oct 2025
Abstract
Senescence is a dynamic, multifaceted process implicated in tissue aging, organ dysfunction, and intricately associated with numerous chronic diseases. As senescent cells accumulate, they drive inflammation, fibrosis, and metabolic disruption through the senescence-associated secretory phenotype (SASP). Despite its clinical relevance, senescence remains challenging [...] Read more.
Senescence is a dynamic, multifaceted process implicated in tissue aging, organ dysfunction, and intricately associated with numerous chronic diseases. As senescent cells accumulate, they drive inflammation, fibrosis, and metabolic disruption through the senescence-associated secretory phenotype (SASP). Despite its clinical relevance, senescence remains challenging to detect non-invasively due to its heterogeneous nature and the lack of universal biomarkers. Recent advances in the development of specific imaging probes for positron emission tomography (PET) enable in vivo visualization of senescence-associated pathways across key organs, such as the lung, heart, kidney, and metabolic processes. For instance, [18F]FPyGal, a β-galactosidase-targeted tracer, has demonstrated selective accumulation in senescent cells in both preclinical and early clinical studies, while FAP-targeted radioligands are emerging as tools for imaging fibrotic remodeling in the lung, liver, kidney, and myocardium. This review examines a new generation of PET radioligands targeting hallmark features of senescence, with the potential to track and measure the process, the ability to be translated into clinical interventions for early diagnosis, and longitudinal monitoring of senescence-driven pathologies. By integrating organ-specific imaging biomarkers with molecular insights, PET probes are poised to transform our ability to manage and treat age-related diseases through personalized approaches. Full article
(This article belongs to the Section Medical Imaging and Theranostics)
18 pages, 6931 KB  
Article
Research on Multi-Sensor Data Fusion Based Real-Scene 3D Reconstruction and Digital Twin Visualization Methodology for Coal Mine Tunnels
by Hongda Zhu, Jingjing Jin and Sihai Zhao
Sensors 2025, 25(19), 6153; https://doi.org/10.3390/s25196153 (registering DOI) - 4 Oct 2025
Abstract
This paper proposes a multi-sensor data-fusion-based method for real-scene 3D reconstruction and digital twin visualization of coal mine tunnels, aiming to address issues such as low accuracy in non-photorealistic modeling and difficulties in feature object recognition during traditional coal mine digitization processes. The [...] Read more.
This paper proposes a multi-sensor data-fusion-based method for real-scene 3D reconstruction and digital twin visualization of coal mine tunnels, aiming to address issues such as low accuracy in non-photorealistic modeling and difficulties in feature object recognition during traditional coal mine digitization processes. The research employs cubemap-based mapping technology to project acquired real-time tunnel images onto six faces of a cube, combined with navigation information, pose data, and synchronously acquired point cloud data to achieve spatial alignment and data fusion. On this basis, inner/outer corner detection algorithms are utilized for precise image segmentation, and a point cloud region growing algorithm integrated with information entropy optimization is proposed to realize complete recognition and segmentation of tunnel planes (e.g., roof, floor, left/right sidewalls) and high-curvature feature objects (e.g., ventilation ducts). Furthermore, geometric dimensions extracted from segmentation results are used to construct 3D models, and real-scene images are mapped onto model surfaces via UV (U and V axes of texture coordinate) texture mapping technology, generating digital twin models with authentic texture details. Experimental validation demonstrates that the method performs excellently in both simulated and real coal mine environments, with models capable of faithfully reproducing tunnel spatial layouts and detailed features while supporting multi-view visualization (e.g., bottom view, left/right rotated views, front view). This approach provides efficient and precise technical support for digital twin construction, fine-grained structural modeling, and safety monitoring of coal mine tunnels, significantly enhancing the accuracy and practicality of photorealistic 3D modeling in intelligent mining applications. Full article
(This article belongs to the Section Sensing and Imaging)
Show Figures

Figure 1

25 pages, 6271 KB  
Article
Estimating Fractional Land Cover Using Sentinel-2 and Multi-Source Data with Traditional Machine Learning and Deep Learning Approaches
by Sergio Sierra, Rubén Ramo, Marc Padilla, Laura Quirós and Adolfo Cobo
Remote Sens. 2025, 17(19), 3364; https://doi.org/10.3390/rs17193364 (registering DOI) - 4 Oct 2025
Abstract
Land cover mapping is essential for territorial management due to its links with ecological, hydrological, climatic, and socioeconomic processes. Traditional methods use discrete classes per pixel, but this study proposes estimating cover fractions with Sentinel-2 imagery (20 m) and AI. We employed the [...] Read more.
Land cover mapping is essential for territorial management due to its links with ecological, hydrological, climatic, and socioeconomic processes. Traditional methods use discrete classes per pixel, but this study proposes estimating cover fractions with Sentinel-2 imagery (20 m) and AI. We employed the French Land cover from Aerospace ImageRy (FLAIR) dataset (810 km2 in France, 19 classes), with labels co-registered with Sentinel-2 to derive precise fractional proportions per pixel. From these references, we generated training sets combining spectral bands, derived indices, and auxiliary data (climatic and temporal variables). Various machine learning models—including XGBoost three deep neural network (DNN) architectures with different depths, and convolutional neural networks (CNNs)—were trained and evaluated to identify the optimal configuration for fractional cover estimation. Model validation on the test set employed RMSE, MAE, and R2 metrics at both pixel level (20 m Sentinel-2) and scene level (100 m FLAIR). The training set integrating spectral bands, vegetation indices, and auxiliary variables yielded the best MAE and RMSE results. Among all models, DNN2 achieved the highest performance, with a pixel-level RMSE of 13.83 and MAE of 5.42, and a scene-level RMSE of 4.94 and MAE of 2.36. This fractional approach paves the way for advanced remote sensing applications, including continuous cover-change monitoring, carbon footprint estimation, and sustainability-oriented territorial planning. Full article
(This article belongs to the Special Issue Multimodal Remote Sensing Data Fusion, Analysis and Application)
Show Figures

Figure 1

20 pages, 1352 KB  
Article
Geometric Numerical Test via Collective Integrators: A Tool for Orbital and Attitude Propagation
by Francisco Crespo, Jhon Vidarte, Jersson Gerley Villafañe and Jorge Luis Zapata
Symmetry 2025, 17(10), 1652; https://doi.org/10.3390/sym17101652 (registering DOI) - 4 Oct 2025
Abstract
We propose a novel numerical test to evaluate the reliability of numerical propagations, leveraging the fiber bundle structure of phase space typically induced by Lie symmetries, though not exclusively. This geometric test simultaneously verifies two properties: (i) preservation of conservation principles, and (ii) [...] Read more.
We propose a novel numerical test to evaluate the reliability of numerical propagations, leveraging the fiber bundle structure of phase space typically induced by Lie symmetries, though not exclusively. This geometric test simultaneously verifies two properties: (i) preservation of conservation principles, and (ii) faithfulness to the symmetry-induced fiber bundle structure. To generalize the approach to systems lacking inherent symmetries, we construct an associated collective system endowed with an artificial G-symmetry. The original system then emerges as the G-reduced version of this collective system. By integrating the collective system and monitoring G-fiber bundle conservation, our test quantifies numerical precision loss and detects geometric structure violations more effectively than classical integral-based checks. Numerical experiments demonstrate the superior performance of this method, particularly in long-term simulations of rigid body dynamics and perturbed Keplerian systems. Full article
(This article belongs to the Section Mathematics)
30 pages, 7436 KB  
Article
Pea Pod Valorization: A Green Processing Route to Obtain Cellulosic Reinforcements for Compression Molded Polylactic Acid Biocomposites
by Daniela Negrete-Bolagay, Victor H. Guerrero, Salomé Galeas, Jennifer Tejedor, Patricia I. Pontón and Anja Dosen
Materials 2025, 18(19), 4608; https://doi.org/10.3390/ma18194608 (registering DOI) - 4 Oct 2025
Abstract
The valorization of agroindustrial residues represents a sustainable alternative in the production of materials attractive for sustainable technologies. In this work, cellulosic materials were isolated from treated pea pods aiming to obtain highly crystalline, thermally stable reinforcements for biocomposites. Four different treatments were [...] Read more.
The valorization of agroindustrial residues represents a sustainable alternative in the production of materials attractive for sustainable technologies. In this work, cellulosic materials were isolated from treated pea pods aiming to obtain highly crystalline, thermally stable reinforcements for biocomposites. Four different treatments were evaluated; two employed 0.5 or 0.75 M oxalic acid (OA) solutions at 90 °C, and two used 5% w/v KOH solutions after each OA treatment. The cellulosic materials (10, 20 wt.%) were compounded with a polylactic acid (PLA) matrix and polyvinyl alcohol (0, 2.5 wt.%) as a compatibilizer by extrusion. Compression molding was used to obtain samples to study the composite’s mechanical and thermal behavior. The cellulosic materials and the composites were characterized by Fourier transform infrared spectroscopy, thermogravimetry, and calorimetry. The composites were also subjected to flexural, thermo-mechanical, and water absorption testing. The cellulosic reinforcements obtained using 0.75 M OA and 0.5 M OA and KOH showed the highest crystallinities (91–92%). In general, 20 wt.% reinforced composites showed lower thermal expansion and higher water absorption than those incorporating 10 wt.% reinforcements. The composites incorporating 10 wt.% of 0.5 M OA treated pea pods exhibited flexural modulus/strength 17/3% higher than that of PLA. The composites incorporating 20 wt.% of 0.5 M OA and KOH-treated pea pods showed the highest flexural modulus/strength, 35/25% higher than that of PLA. These results show that agroresidues treated with low-concentration organic acids can be effectively used to tune the mechanical, thermal, and water absorption behavior of biodegradable composites. Full article
Show Figures

Figure 1

12 pages, 2444 KB  
Article
Discovery of Primaquine–Indole Carboxamides with Cancer-Cell-Selective Antiproliferative Activity
by Benjamin H. Peer, Jeremiah O. Olugbami, Dipak T. Walunj and Adegboyega K. Oyelere
Molecules 2025, 30(19), 3988; https://doi.org/10.3390/molecules30193988 (registering DOI) - 4 Oct 2025
Abstract
Indole carboxylic acids are endogenous tryptophan metabolites that have demonstrated a variety of bioactivities, including anticancer effects. Specifically, indole acetic acid (IAA) elicits anticancer activity when combined with ultraviolet B or reactive oxygen species (ROS) generators. Primaquine (PQ) is an approved drug which [...] Read more.
Indole carboxylic acids are endogenous tryptophan metabolites that have demonstrated a variety of bioactivities, including anticancer effects. Specifically, indole acetic acid (IAA) elicits anticancer activity when combined with ultraviolet B or reactive oxygen species (ROS) generators. Primaquine (PQ) is an approved drug which elicits antimalarial activity through ROS generation. We investigated the effects of ICA, IAA, PQ, their combination and PQ–indole carboxamide conjugates on the viability of selected cancer cell lines. We identified PQ–indole carboxamide 2 which elicited more potent antiproliferative effects than PQ and ICA/PQ combination. Our data revealed that compound 2 derived a significant part of its antiproliferative effect from ROS generation. Full article
Show Figures

Figure 1

Back to TopTop