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27 pages, 14699 KB  
Article
Research on the Response Mechanism of Overlying Strata Failure and Ground Fissures Development Under High-Intensity Mining
by Pengyu Li, Yanjun Zhang, Lingyun Zhang and Jiayuan Kong
Processes 2026, 14(3), 565; https://doi.org/10.3390/pr14030565 - 5 Feb 2026
Abstract
Mining-induced ground fissures in the Ordos Basin pose critical threats to coal mine safety and ecological stability. This study integrated multi-source monitoring data (improves data acquisition efficiency by 60%) with theoretical models to elucidate the dynamic response mechanism between overlying strata failure and [...] Read more.
Mining-induced ground fissures in the Ordos Basin pose critical threats to coal mine safety and ecological stability. This study integrated multi-source monitoring data (improves data acquisition efficiency by 60%) with theoretical models to elucidate the dynamic response mechanism between overlying strata failure and ground fissure development. The results demonstrate that: (1) Two rock beam structural models for initial and periodic fracturing of thick, hard rock strata are established, demonstrating that both failure modes are dominated by tensile–shear mechanisms. (2) Ground fissures exhibit distinct zonal characteristics, displaying a gradient pattern of “strong disturbance in the near field and weak response in the far field.” Quantitative data support this pattern: average fissure density is 36/hm2, with a maximum of 45/hm2 recorded in the immediate vicinity of the working face, declining steadily outward. (3) Overlying strata failure forms three distinct zones—caving zone (42 m), fissure zone (158 m), and longitudinal penetrating zone—reflecting the heterogeneous fracture characteristics of medium-hard rock strata under mining influence. (3) The proposed “virtual main arch—virtual auxiliary arch” equivalent support system theory elucidates the mechanistic differences between step fissures (attributed to local support system instability) and collapse fissures (driven by global support system instability) from a mechanical perspective. The developed chain response theory fills a critical theoretical gap and provides a novel method for predicting and preventing geological disasters in mining areas. Full article
(This article belongs to the Special Issue Process Safety and Intelligent Monitoring for Mining Engineering)
17 pages, 2566 KB  
Article
Microbiological Air Quality in Windowless Exhibition Spaces with Centralized Air-Conditioning and Air Recirculation—Pilot Study
by Sylwia Szczęśniak, Juliusz Walaszczyk, Agnieszka Trusz and Katarzyna Piekarska
Sustainability 2026, 18(3), 1656; https://doi.org/10.3390/su18031656 - 5 Feb 2026
Abstract
Microbiological contamination in public buildings is closely linked to human presence, such as airborne bacteria, fungi, and particulate matter, which strongly influence indoor air quality (IAQ). This study examined the distribution of microorganisms in a museum building in relation to time of day, [...] Read more.
Microbiological contamination in public buildings is closely linked to human presence, such as airborne bacteria, fungi, and particulate matter, which strongly influence indoor air quality (IAQ). This study examined the distribution of microorganisms in a museum building in relation to time of day, air-handling unit (AHU) type, and ventilation operating mode. Exhibition rooms without natural light relied entirely on a central heating, ventilation and air conditioning (HVAC) system. Microbiological contamination was assessed using Koch’s passive sedimentation method over a 24 h cycle for two AHUs (I and III) and selected rooms, while CO2 levels were monitored as indicators of occupancy and ventilation demand in line with EN 16798-1:2019 and ASHRAE 62.1-2022. Although the demand-controlled ventilation system increased the outdoor air fraction from 40% to 70–100% during peak visitor density, localized increases in microbial contamination occurred. AHU I showed higher loads of Staphylococcus sp. and fungi, while AHU III exhibited pronounced fungal peaks influenced by elevated humidity from an open water reservoir. Psychrophilic bacteria reached 140–230 CFU·m−3, mesophilic bacteria 230–320 CFU·m−3, and fungi up to 740 CFU·m−3. Most CFU values remained below commonly referenced upper limits (<1000 CFU·m−3), but several peaks exceeded lower recommended thresholds, indicating a need for improvements. Enhanced filtration, humidity control, increased airflow during high occupancy, and reducing moisture sources in AHUs may mitigate microbial growth and improve IAQ in public buildings. Full article
(This article belongs to the Section Health, Well-Being and Sustainability)
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27 pages, 3345 KB  
Article
Distributive Disturbances: Examining Community Exposure to Drinking Water Contaminants Amidst the Jackson, Mississippi (USA) Water Crisis
by Ambria N. McDonald, Yolanda J. McDonald, Andrea Chow, Julia Kosinski and Dorceta E. Taylor
Water 2026, 18(3), 424; https://doi.org/10.3390/w18030424 - 5 Feb 2026
Abstract
Community water systems in the United States provide drinking water to more than 300 million people annually, making their reliability fundamental to public health. In regions with long histories of racial segregation and unequal infrastructure maintenance, water system failures can deepen existing environmental [...] Read more.
Community water systems in the United States provide drinking water to more than 300 million people annually, making their reliability fundamental to public health. In regions with long histories of racial segregation and unequal infrastructure maintenance, water system failures can deepen existing environmental injustices. This study examines water quality conditions in the Jackson, Mississippi, metropolitan area following the 2022 distribution system collapse and a decade of repeated noncompliance with the Safe Drinking Water Act’s Lead and Copper Rule (LCR). Using the U.S. Environmental Protection Agency’s 2024 updated LCR tap sampling protocol, water samples from 29 sites were collected. Samples were analyzed for lead, copper, iron, zinc, chlorine, sulfate, pH, and total dissolved solids concentrations. Chlorine-to-sulfate mass ratios (CSMR) were also calculated to evaluate corrosion potential. Demographic surveys, statistical analyses, and geospatial visualizations were used to interpret neighborhood-level patterns. Our findings show that all sites met primary drinking water standards and complied with LCR action levels but exceeded secondary drinking water standards at 100% of study sites. Seven sites exhibited CSMR values above the threshold, indicating increased susceptibility to corrosion. These results highlight the need for targeted corrosion control, treatment optimization, and ongoing monitoring, particularly in historically marginalized communities. Full article
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15 pages, 5038 KB  
Article
Phenological Patterns and Driving Mechanisms of Autumn Phytoplankton Blooms in the Yellow Sea Cold Water Mass (2000–2022)
by Mingxuan Liu, Botao Gu, Chunli Liu, Bei Su, Qicheng Meng, Yize Zhang and Min Li
J. Mar. Sci. Eng. 2026, 14(3), 313; https://doi.org/10.3390/jmse14030313 - 5 Feb 2026
Abstract
Phytoplankton blooms represent a typical ecological process in marine systems. Climate change drives shifts in its phenology, both directly via impacts on physiology and indirectly by modifying stratification intensity, nutrients, light availability, and grazing pressure. Using satellite remote sensing and reanalysis data from [...] Read more.
Phytoplankton blooms represent a typical ecological process in marine systems. Climate change drives shifts in its phenology, both directly via impacts on physiology and indirectly by modifying stratification intensity, nutrients, light availability, and grazing pressure. Using satellite remote sensing and reanalysis data from 2000 to 2022, this study partitions the Yellow Sea based on interannual variability in the Yellow Sea Cold Water Mass (YSCWM). Clear spatial differences in autumn bloom phenology are observed within the YSCWM. Earlier initiation dominates the Southern YSCWM (SYSCWM), while delayed later initiation concentrates in the Northern YSCWM (NYSCWM) and along the SYSCWM’s eastern margins. This pattern can be explained by the differences in regional hydrodynamics, i.e., the Yellow Sea Warm Current (YSWC) enhances upwelling and convergence in some YSCWM areas, boosting nutrient supply and earlier blooms, whereas weaker circulation-driven nutrient supply causes the bloom delay. Interannual variation analysis further reveals that the bloom timing is regulated by seasonal YSCWM dissipation since intensified autumn northerly winds accelerate dissipation and nutrient supply, thereby advancing blooms, while weaker northerly winds and stable circulation delay bloom progress by maintaining strong thermocline stability. These findings provide further insights into the underlying mechanisms driving autumn bloom dynamics and support ecosystem monitoring efforts in shelf seas. Full article
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18 pages, 2559 KB  
Article
Calibration of a Capacitive Coupled Ring Resonator for Non-Invasive Measurement of Wood Moisture Content
by Livio D’Alvia, Ludovica Apa, Emanuele Rizzuto, Erika Pittella and Zaccaria Del Prete
Instruments 2026, 10(1), 11; https://doi.org/10.3390/instruments10010011 - 5 Feb 2026
Abstract
The accurate and non-invasive measurement of moisture content in wood is essential for the preservation of historical and artistic artifacts. This study presents the calibration of a planar Microwave Planar Capacitive Coupled Ring Resonator (MPCCRR) designed to indirectly and non-destructively assess the water [...] Read more.
The accurate and non-invasive measurement of moisture content in wood is essential for the preservation of historical and artistic artifacts. This study presents the calibration of a planar Microwave Planar Capacitive Coupled Ring Resonator (MPCCRR) designed to indirectly and non-destructively assess the water content in wood samples. The method relies on analyzing shifts in the resonant frequencies and variations in the transmission parameter |S21| resulting from changes in the material’s dielectric permittivity. After preliminary characterization via parametric simulations (εr = 1–10) and validation with low-permittivity reference materials, the sensor was tested on three wood species (poplar, fir, beech), including measurements at two sensor positions and with different grain orientations. The results demonstrate a monotonic, repeatable response to increasing moisture content with frequency shifts up to ≈220 MHz and normalized sensitivities ranging from 3 to 9 MHz/% water content, depending on species and measurement position. Position 2 showed the greatest sensitivity due to stronger field–sample interaction, while Position 1 provided a quasi-isotropic response with excellent repeatability. Linear regression analyses revealed good correlations between the frequency shifts and the gravimetric water content (R2 ≥ 0.85). The MPCCRR sensor therefore proves to be a promising tool for the non-invasive monitoring of wood moisture, which is particularly suitable for the low-moisture range encountered in cultural heritage conservation, with an estimated moisture uncertainty of 0.12–0.35% under controlled laboratory conditions. Full article
(This article belongs to the Section Sensing Technologies and Precision Measurement)
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32 pages, 4949 KB  
Article
Thermal and Energy Performance Assessment of Evacuated Tube Collectors: Case Study at Rancho Luna Hotel
by Leonel Díaz-Tato, Luis Angel Iturralde Carrera, Carlos D. Constantino-Robles, Fernando Banda-Muñoz, José M. Álvarez-Alvarado, Marcos Aviles and Juvenal Rodríguez-Reséndiz
Solar 2026, 6(1), 10; https://doi.org/10.3390/solar6010010 - 5 Feb 2026
Abstract
This study aimed to evaluate the thermal performance and operational behavior of an evacuated-tube solar collector field installed in a coastal hotel under real industrial conditions. The work analyzed temperature, irradiance, and mass-flow data to determine instantaneous efficiency and identify performance deterioration associated [...] Read more.
This study aimed to evaluate the thermal performance and operational behavior of an evacuated-tube solar collector field installed in a coastal hotel under real industrial conditions. The work analyzed temperature, irradiance, and mass-flow data to determine instantaneous efficiency and identify performance deterioration associated with fouling. A multivariable regression model was developed to predict collector efficiency as a function of operating parameters. The results showed an average efficiency of 40–55%, with a noticeable decrease attributed to soiling effects. The methodology and findings contribute to improving monitoring-based maintenance strategies and optimizing the energy performance of large-scale domestic hot-water systems. Full article
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17 pages, 1984 KB  
Article
Predicting Nutritional and Morphological Attributes of Fresh Commercial Opuntia Cladodes Using Machine Learning and Imaging
by Juan Arredondo Valdez, Josué Israel García López, Héctor Flores Breceda, Ajay Kumar, Ricardo David Valdez Cepeda and Alejandro Isabel Luna Maldonado
J. Imaging 2026, 12(2), 67; https://doi.org/10.3390/jimaging12020067 - 5 Feb 2026
Abstract
Opuntia ficus-indica L. is a prominent crop in Mexico, requiring advanced non-destructive technologies for the real-time monitoring and quality control of fresh commercial cladodes. The primary research objective of this study was to develop and validate high-precision mathematical models that correlate hyperspectral signatures [...] Read more.
Opuntia ficus-indica L. is a prominent crop in Mexico, requiring advanced non-destructive technologies for the real-time monitoring and quality control of fresh commercial cladodes. The primary research objective of this study was to develop and validate high-precision mathematical models that correlate hyperspectral signatures (400–1000 nm) with the specific nutritional, morphological, and antioxidant attributes of fresh cladodes (cultivar Villanueva) at their peak commercial maturity. By combining hyperspectral imaging (HSI) with machine learning algorithms, including K-Means clustering for image preprocessing and Partial Least Squares Regression (PLSR) for predictive modeling, this study successfully predicted the concentrations of 10 minerals (N, P, K, Ca, Mg, Fe, B, Mn, Zn, and Cu), chlorophylls (a, b, and Total), and antioxidant capacities (ABTS, FRAP, and DPPH). The innovative nature of this work lies in the simultaneous non-destructive quantification of 17 distinct variables from a single scan, achieving coefficients of determination (R2) as high as 0.988 for Phosphorus and Chlorophyll b. The practical applicability of this research provides a viable replacement for time-consuming and destructive laboratory acid digestion, enabling producers to implement automated, high-throughput sorting lines for quality assurance. Furthermore, this study establishes a framework for interdisciplinary collaborations between agricultural engineers, data scientists for algorithm optimization, and food scientists to enhance the functional value chain of Opuntia products. Full article
(This article belongs to the Special Issue Multispectral and Hyperspectral Imaging: Progress and Challenges)
29 pages, 890 KB  
Article
Enhancing Cross-Regional Generalization in UAV Forest Segmentation Across Plantation and Natural Forests with Attention-Refined PP-LiteSeg Networks
by Xinyu Ma, Shuang Zhang, Kaibo Li, Xiaorui Wang, Hong Lin and Zhenping Qiang
Remote Sens. 2026, 18(3), 523; https://doi.org/10.3390/rs18030523 - 5 Feb 2026
Abstract
Accurate fine-scale forest mapping is fundamental for ecological monitoring and resource management. While deep learning semantic segmentation methods have advanced the interpretation of high-resolution UAV imagery, their generalization across diverse forest regions remains challenging due to high spatial heterogeneity. To address this, we [...] Read more.
Accurate fine-scale forest mapping is fundamental for ecological monitoring and resource management. While deep learning semantic segmentation methods have advanced the interpretation of high-resolution UAV imagery, their generalization across diverse forest regions remains challenging due to high spatial heterogeneity. To address this, we propose two enhanced versions based on the PP-LiteSeg architecture for robust cross-regional forest segmentation. Version 01 (V01) integrates a multi-branch attention fusion module composed of parallel channel, spatial, and pixel attention branches. This design enables fine-grained feature enhancement and precise boundary delineation in structurally regular artificial forests, such as the Huayuan Forest Farm. As a result, V01 achieves a mIoU of 92.64% and an F1-score of 96.10%, representing an approximately 18 percentage-point mIoU improvement over PSPNet and DeepLabv3+. Building on this, Version 02 (V02) introduces a lightweight residual connection that directly shortcuts the fused features, thereby improving feature stability and robustness under complex textures and illumination, and demonstrates stronger performance in naturally heterogeneous forests (Longhai Township), attaining an mIoU of 91.87% and an F1-score of 95.77% (5.72 percentage-point mIoU gain over DeepLabv3+). We further conduct comprehensive comparisons against conventional CNN baselines as well as representative lightweight and transformer-based models (BiSeNetV2 and SegFormer-B0). In bidirectional cross-region transfer (train on one region and directly test on the other), V02 exhibits the most stable performance with minimal degradation, highlighting its robustness under domain shift. On a combined cross-regional dataset, V02 achieves a leading mIoU of 91.50%, outperforming U-Net, DeepLabv3+, and PSPNet. In summary, V01 excels in boundary delineation for regular plantation forests, whereas V02 shows more stable generalization across highly varied natural forest landscapes, providing practical solutions for region-adaptive UAV forest segmentation. Full article
(This article belongs to the Special Issue Remote Sensing-Assisted Forest Inventory Planning)
33 pages, 5788 KB  
Article
Temperature-Dependent and Semi-Quantitative Enzyme Profiles of Malacosoma disstria (Lepidoptera: Lasiocampidae) Hemocytic Cell Lines
by Paschalis Giannoulis and Helen Kalorizou
Cells 2026, 15(3), 302; https://doi.org/10.3390/cells15030302 - 5 Feb 2026
Abstract
Insect hemocytic cell lines offer substantial advantages over primary, in vivo hemocyte cultures, fundamentally transforming experimental approaches in cellular immunology and related fields. Selected Malacosoma disstria cell lines were characterized for optimal growth temperatures, morphogenesis, blebbing, extracellular enzyme profiles, and their interactions with [...] Read more.
Insect hemocytic cell lines offer substantial advantages over primary, in vivo hemocyte cultures, fundamentally transforming experimental approaches in cellular immunology and related fields. Selected Malacosoma disstria cell lines were characterized for optimal growth temperatures, morphogenesis, blebbing, extracellular enzyme profiles, and their interactions with material (polystyrene) and microbial (Bacillus subtilis) surfaces. The adhesive hemocyte lines UA-Md221 and Md108 showed optimal growth at 28 °C, whereas UA-Md203 and Md66 grew best at 21 °C, with Md66 tolerating 21–28 °C. Md108 demonstrated a broader temperature tolerance than other adherent cultures. Both Md108 and UA-Md221 adhered to polystyrene within 24 h post-subculturing, although protease-induced morphological changes in modified Grace’s medium continued through 48 h and 72 h, respectively. Culture quality was monitored by assessing the release of multiple enzymes, including alkaline and acid phosphatases, esterases and lipases, aminopeptidases, proteases, glycosidases, and hydrolases from the cell lines at 50% confluency in modified Grace’s medium. Fetal bovine serum showed elevated esterase lipase (C8) and phosphoamidase activities when diluted in Grace’s medium and phosphate buffered saline (PBS). Exposure to dead B. subtilis suspended in PBS induced quantitative and qualitative alterations in the enzyme secretion profiles of Md66 and Md108 cultures. We conclude that semi-quantitative assessments of hemocytic cell lines can provide valuable insights for the time window of each enzyme release, revealing immune and metabolic signaling patterns. Full article
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32 pages, 53671 KB  
Article
Underwater SLAM and Calibration with a 3D Profiling Sonar
by António Ferreira, José Almeida, Aníbal Matos and Eduardo Silva
Remote Sens. 2026, 18(3), 524; https://doi.org/10.3390/rs18030524 - 5 Feb 2026
Abstract
High resolution underwater mapping is fundamental to the sustainable development of the blue economy, supporting offshore energy expansion, marine habitat protection, and the monitoring of both living and non-living resources. This work presents a pose-graph SLAM and calibration framework specifically designed for 3D [...] Read more.
High resolution underwater mapping is fundamental to the sustainable development of the blue economy, supporting offshore energy expansion, marine habitat protection, and the monitoring of both living and non-living resources. This work presents a pose-graph SLAM and calibration framework specifically designed for 3D profiling sonars, such as the Coda Octopus Echoscope 3D. The system integrates a probabilistic scan matching method (3DupIC) for direct registration of 3D sonar scans, enabling accurate trajectory and map estimation even under degraded dead reckoning conditions. Unlike other bathymetric SLAM methods that rely on submaps and assume short-term localization accuracy, the proposed approach performs direct scan-to-scan registration, removing this dependency. The factor graph is extended to represent the sonar extrinsic parameters, allowing the sonar-to-body transformation to be refined jointly with trajectory optimization. Experimental validation on a challenging real world dataset demonstrates outstanding localization and mapping performance. The use of refined extrinsic parameters further improves both accuracy and map consistency, confirming the effectiveness of the proposed joint SLAM and calibration approach for robust and consistent underwater mapping. Full article
(This article belongs to the Special Issue Underwater Remote Sensing: Status, New Challenges and Opportunities)
23 pages, 20925 KB  
Article
Monitoring Heterogeneous Deformation of Transportation Infrastructure in Beijing Using Sentinel-1 InSAR Time Series
by Weizhen Lin, Xi Guo, Yidi Wang, Changyang Hu and Zhang Yunjun
Remote Sens. 2026, 18(3), 520; https://doi.org/10.3390/rs18030520 - 5 Feb 2026
Abstract
Transportation infrastructure is vulnerable to heterogeneous deformation, yet such deformation remains insufficiently monitored and characterized in metropolitan regions due to the lack of high-resolution deformation gradient products and comparison with industrial standards. Here, we generated a 45 m resolution interferometric synthetic aperture radar [...] Read more.
Transportation infrastructure is vulnerable to heterogeneous deformation, yet such deformation remains insufficiently monitored and characterized in metropolitan regions due to the lack of high-resolution deformation gradient products and comparison with industrial standards. Here, we generated a 45 m resolution interferometric synthetic aperture radar (InSAR) surface displacement time series across the Beijing Plain using Sentinel-1 SAR imagery acquired between 2014 and 2024, and calculated deformation gradients along all ring roads, major expressways, and airport runways. These deformation gradients are compared with national standards to evaluate their structural risks. Our analysis shows that (1) subsidence in the Beijing Plain is concentrated in the northern, eastern, and southern regions, where the northeastern region has been uplifting since 2018 due to the groundwater recovery in Beijing; (2) all ring roads, expressways, and airport runways are relatively stable during our observation period of 2015–2021, except for the central runway of Beijing Capital International Airport, which has accumulated a deformation gradient of 1.9‰ during 2015–2021, exceeding the safety limit of 1.5‰, indicating structural risks. These results demonstrate the effectiveness of high-resolution InSAR time series for monitoring deformation and pinpointing potential structural risks. Full article
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21 pages, 3256 KB  
Article
Process Control by Optical Emission Spectroscopy During Reactive Magnetron Sputtering of NiVxOy Electrochromic Coatings
by Oihane Hernandez-Rodriguez, Gregorio Guzman, Rocio Ortiz, Ester Zuza, Victor Bellido-Gonzalez, Iban Quintana and Eva Gutierrez-Berasategui
Coatings 2026, 16(2), 206; https://doi.org/10.3390/coatings16020206 - 5 Feb 2026
Abstract
This paper presents a study on the development and optimisation of thin films of nickel-vanadium oxide (NiVxOy) deposited by DC reactive magnetron sputtering (RMS) controlled by P.E.M. (plasma emission monitoring). The hysteresis behaviour of the Ni emission signal as [...] Read more.
This paper presents a study on the development and optimisation of thin films of nickel-vanadium oxide (NiVxOy) deposited by DC reactive magnetron sputtering (RMS) controlled by P.E.M. (plasma emission monitoring). The hysteresis behaviour of the Ni emission signal as a function of oxygen incorporation was analysed using optical emission spectroscopy (OES), enabling the identification of critical working points along the hysteresis loop and their correlation with film growth mechanisms. Compared to the non-monotonic nature of the target discharge voltage signal, OES provided a simplified response for real-time process control. A set of coatings was deposited under various working pressures (0.6 and 2.0 Pa) and plasma emission monitoring (P.E.M.) conditions and was thoroughly characterised in terms of microstructure, composition, optical modulation, and electrochemical performance. Films deposited at high pressure and under 30% P.E.M. conditions showed an optimal balance between optical modulation (21%) and charge density (4 mC/cm2), which was attributed to the increased Ni3+ content and the surface cracks at low density. Full article
(This article belongs to the Special Issue Surface Modification Techniques Utilizing Plasma and Photonic Methods)
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30 pages, 2728 KB  
Article
Supervisory Monitoring and Control Using Chemical Process Simulators and SCADA Systems
by Rebecca Bastos Boschoski and Lizandro de Sousa Santos
Methane 2026, 5(1), 8; https://doi.org/10.3390/methane5010008 - 5 Feb 2026
Abstract
A digital twin (DT) is an automation strategy that integrates a physical plant with an adaptive, real-time simulation environment, with bidirectional communication between them. In process engineering, DTs promise real-time monitoring, prediction of future conditions, predictive maintenance, process optimization, and control. Dashboards for [...] Read more.
A digital twin (DT) is an automation strategy that integrates a physical plant with an adaptive, real-time simulation environment, with bidirectional communication between them. In process engineering, DTs promise real-time monitoring, prediction of future conditions, predictive maintenance, process optimization, and control. Dashboards for process monitoring are becoming increasingly relevant for tracking key metrics and supervising industrial units in real time. Supervisory Control and Data Acquisition (SCADA) systems are widely used for process automation, with ScadaBR, an open-source, freely licensed platform. This work presents the development of a computational tool that integrates the Aspen HYSYS/Python with the ScadaBR system for real-time monitoring and supervision of dynamic models. The virtual plant, which replicates the system’s physical behavior, was connected to the SCADA platform via the Modbus protocol, enabling bidirectional data exchange between the simulated model and the supervisory interface. The system supports operational analysis and control strategy validation. Two case studies were analyzed: (i) a simplified catalytic hydrocracking process, implemented in the Python environment, and (ii) a heat exchanger networks process, simulated using the HYSYS simulator. In the second case, the process was dynamically simulated, with real-time monitoring of a simple dynamic indicator that correlates the feed methane concentration with heat transfer fluids. The results demonstrate the feasibility and applicability of the proposed approach for educational purposes, operator training, and process engineering validation, fostering a more realistic and interactive simulation environment. Furthermore, the results show that the tool is promising for dynamic monitoring of environmental and energy indices, demonstrating that methane consumption relative to process feed can be evaluated and controlled over time. Full article
25 pages, 965 KB  
Review
Bridging Innovation and Practice in Type 2 Diabetes Mellitus: Novel Antidiabetic Therapies and the Expanding Role of Community Pharmacists
by Marios Spanakis, Agapi Fournaraki, Frantzeska Nimee, Christos Kontogiorgis and Emmanouil K. Symvoulakis
Pharmaceuticals 2026, 19(2), 271; https://doi.org/10.3390/ph19020271 - 5 Feb 2026
Abstract
Diabetes mellitus, particularly type 2 diabetes mellitus (T2DM), represents a rapidly expanding global health challenge with substantial public health and economic consequences. Recent advances in antidiabetic therapy—including dipeptidyl peptidase-4 (DPP-4) inhibitors, glucagon-like peptide-1 receptor agonists (GLP-1 RAs), dual GIP/GLP-1 receptor agonists, and sodium–glucose [...] Read more.
Diabetes mellitus, particularly type 2 diabetes mellitus (T2DM), represents a rapidly expanding global health challenge with substantial public health and economic consequences. Recent advances in antidiabetic therapy—including dipeptidyl peptidase-4 (DPP-4) inhibitors, glucagon-like peptide-1 receptor agonists (GLP-1 RAs), dual GIP/GLP-1 receptor agonists, and sodium–glucose cotransporter-2 (SGLT-2) inhibitors—have transformed diabetes management by providing benefits beyond glycemic control, such as cardiovascular and renal protection, weight reduction, and improved quality of life. As the therapeutic landscape becomes increasingly complex and patient-centered, ensuring the safe and effective use of these agents in real-world settings has emerged as a key concern for pharmacoepidemiology and pharmacovigilance. Community pharmacists, as highly accessible healthcare professionals, play an expanding role in diabetes care through medication optimization, patient education, adherence support, and monitoring of adverse drug reactions in primary care. Evidence from systematic reviews and meta-analyses indicates that pharmacist-led interventions improve glycemic outcomes, enhance self-care behaviors, and facilitate the appropriate adoption of contemporary antidiabetic therapies. This narrative review synthesizes current evidence on novel pharmacological treatments for T2DM and examines the evolving contribution of community pharmacists in translating therapeutic innovation into routine practice. Barriers to implementation and future perspectives for integrating pharmacist-led services into diabetes management and pharmacovigilance frameworks are also discussed. Full article
(This article belongs to the Section Pharmacology)
22 pages, 1655 KB  
Article
MuRaF-LULC: A Systematic Multivariate Random Forest Framework for Annual Land-Use and Land-Cover Mapping and Long-Term Change Detection
by Yunuen Reygadas
Land 2026, 15(2), 268; https://doi.org/10.3390/land15020268 - 5 Feb 2026
Abstract
Land-use and land-cover (LULC) change is one of the most pervasive drivers of socioenvironmental transformation worldwide. Given its impacts on ecosystems and climate, the systematic analysis of LULC dynamics remains a central objective of land-change science. Despite major advances in Earth observation capabilities, [...] Read more.
Land-use and land-cover (LULC) change is one of the most pervasive drivers of socioenvironmental transformation worldwide. Given its impacts on ecosystems and climate, the systematic analysis of LULC dynamics remains a central objective of land-change science. Despite major advances in Earth observation capabilities, robust, flexible, and scalable algorithms for long-term monitoring remain unevenly adopted, particularly in remote, forested tropical regions. This study introduces the Multivariate Random Forest Land-Use and Land-Cover (MuRaF-LULC) framework, a supervised and generalizable framework that produces annual, multi-class LULC maps from Landsat time series, with interannual change derived through year-to-year comparisons. A key methodological component of the framework is its predictor-selection strategy, in which variable-importance rankings are used to identify an optimized subset of predictors prior to final model training. MuRaF-LULC was implemented in Google Earth Engine (GEE) and evaluated in Guatemala’s Maya Biosphere Reserve (MBR) for the 2018–2024 period using probability-based sampling and uncertainty-aware accuracy assessment and area estimation. Results show that MuRaF-LULC generates robust annual LULC classifications across multiple years (overall accuracy = 0.90–0.92) and reliable estimates of agropecuario expansion (the dominant transition in the study area) when change is assessed over longer temporal windows where transitions signals stabilize and for which the framework is best suited (producer’s accuracy = 0.97 ± 0.03; user’s accuracy = 0.69 ± 0.05). By prioritizing consistent annual, multiclass LULC trajectories, MuRaF-LULC complements breakpoint- and disturbance-oriented approaches commonly used in land-change studies. Implemented in publicly available, well-documented GEE scripts, MuRaF-LULC facilitates policy-relevant LULC assessment by remote sensing practitioners in governmental and private organizations, where reproducibility, clarity, and ease of deployment are as important as methodological sophistication. Full article
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