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Search Results (19,061)

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18 pages, 1395 KB  
Article
Net Carbon Fluxes in Peninsular Spain Forests Combining the Biome-BGC Model and Machine Learning
by Sergio Sánchez-Ruiz, Manuel Campos-Taberner, Luca Fibbi, Marta Chiesi, Fabio Maselli and María A. Gilabert
Forests 2026, 17(2), 160; https://doi.org/10.3390/f17020160 - 26 Jan 2026
Abstract
In the current context of global warming, quantifying carbon fluxes between biosphere and atmosphere and identifying ecosystems as carbon sources or sinks is essential. The goal of this study is to quantify net carbon fluxes for the main forest types in peninsular Spain [...] Read more.
In the current context of global warming, quantifying carbon fluxes between biosphere and atmosphere and identifying ecosystems as carbon sources or sinks is essential. The goal of this study is to quantify net carbon fluxes for the main forest types in peninsular Spain and characterize them as carbon sources or sinks. A hybrid methodology is proposed. First, net primary production (NPP) is obtained through machine learning using site properties, time metrics of meteorological series, and forest inventory data as inputs. The most accurate NPP estimates (R2 ≥ 0.8 and relative RMSE ≤ 30%) were obtained by kernel ridge regression and gaussian process regression using latitude, elevation, time metrics of air temperature, precipitation and incoming solar radiation, and growing stock volume as inputs. Secondly, net ecosystem production (NEP) is obtained by subtracting heterotrophic respiration simulated by Biome-BGC from the previous NPP. All considered forest types presented small and mostly positive NPP and NEP values (greater for deciduous than for evergreen forests), thus generally acting as carbon sinks during the 2004–2018 period. Full article
(This article belongs to the Special Issue Applications of Artificial Intelligence in Forestry: 2nd Edition)
25 pages, 1844 KB  
Article
Spatial and Temporal Analysis of Climatic Zones in Kazakhstan Using Google Earth Engine
by Kalamkas Yessimkhanova and Mátyás Gede
ISPRS Int. J. Geo-Inf. 2026, 15(2), 57; https://doi.org/10.3390/ijgi15020057 - 26 Jan 2026
Abstract
Kazakhstan, located in Central Asia, is experiencing faster warming than the global trend, making it an important region regarding the study of how climate change is affecting climatic zones. This research aims to identify projected shifts in Köppen–Geiger climate zones under high-emission Shared [...] Read more.
Kazakhstan, located in Central Asia, is experiencing faster warming than the global trend, making it an important region regarding the study of how climate change is affecting climatic zones. This research aims to identify projected shifts in Köppen–Geiger climate zones under high-emission Shared Socioeconomic Pathway (SSP) 5-8.5 climate scenarios. The Köppen–Geiger climate classification system is a practical tool that effectively captures climate types based on just two variables: temperature and precipitation. Monthly temperature and precipitation data from Climatic Research Unit (CRU,) ERA5-Land, and Coupled Model Intercomparison Project Phase 6 (CMIP6) ensembles from 1951 to 2100 were used to generate climatic zone maps. CMIP6 models were evaluated against meteorological station data and ERA5-Land, with bias metrics used to identify the best-performing models for temperature and precipitation in Kazakhstan. Based on these results, two inter-model datasets were developed and used to generate Köppen–Geiger climate maps for high-emission scenarios for the 2061–2100 time period. This research resulted in two key outcomes. First, to facilitate this analysis, a Google Earth Engine (GEE) application was developed as an open accessible tool for dynamic visualization of Köppen–Geiger climate maps. Second, projected maps based on CMIP6 SSP5-8.5 scenario projections indicate that southern Kazakhstan may shift to BSh (Hot Semi-Arid) and Csa (Mediterranean) climates, and the southwest region of the country is projected to shift to a BWh (Hot Desert) climate. These projected Köppen–Geiger climate maps contributed to climate adaptation efforts by identifying regions at risk of desertification and aridification. This study provides a comprehensive analysis of climate zone transformations in Kazakhstan and offers a practical scalable geovisualization tool for monitoring climate change impacts. This allows users easy access to climate-related information and insights into data processing procedures. Full article
(This article belongs to the Special Issue Cartography and Geovisual Analytics)
24 pages, 5872 KB  
Article
Quantitative Characterization of Microfiltration Membrane Fouling Using Optical Coherence Tomography with Optimized Image Analysis
by Song Lee, Hyongrak Cho, Yongjun Choi, Juyoung Andrea Lee and Sangho Lee
Membranes 2026, 16(2), 50; https://doi.org/10.3390/membranes16020050 - 26 Jan 2026
Abstract
Membrane fouling reduces permeate flux and treatment efficiency, yet most diagnostic methods are destructive and require offline analysis. Optical coherence tomography (OCT) enables in situ, real-time visualization; however, quantitative image extraction of thin foulant layers is often limited by manual processing and subjective [...] Read more.
Membrane fouling reduces permeate flux and treatment efficiency, yet most diagnostic methods are destructive and require offline analysis. Optical coherence tomography (OCT) enables in situ, real-time visualization; however, quantitative image extraction of thin foulant layers is often limited by manual processing and subjective thresholding. Here, we develop a reproducible OCT image-analysis workflow that combines band-pass filtering, Gaussian smoothing, and unsharp masking with a dual-threshold subtraction strategy for automated fouling-layer segmentation. Seventeen global thresholding algorithms in ImageJ (289 threshold pairs) were benchmarked against SEM-measured cake thickness, identifying Triangle–Moments as the most robust combination. For humic-acid fouling, the OCT-derived endpoint thickness (14.23 ± 1.18 µm) closely agreed with SEM (15.29 ± 1.54 µm). The method was then applied to other microfiltration foulants, including kaolin and sodium alginate, to quantify thickness evolution alongside flux decline. OCT with the optimized image analysis captured rapid early deposition and revealed periods where flux loss continued despite minimal additional thickness growth, consistent with changes in layer permeability and compaction. The proposed framework advances OCT from qualitative visualization to quantitative, real-time fouling diagnostics and supports mechanistic interpretation and improved operational control of membrane systems. Full article
26 pages, 329 KB  
Article
Valuing Marine Data Assets: A Composite Multi-Period Valuation Framework Under the Blue Economy
by Yifei Zhang and Yaguai Yu
Sustainability 2026, 18(3), 1234; https://doi.org/10.3390/su18031234 - 26 Jan 2026
Abstract
Marine data assets are increasingly recognized as important drivers of value creation in the blue economy, yet their valuation remains challenging due to difficulties in isolating data-related earnings in capital-intensive maritime enterprises. This study proposes a methodological valuation framework that integrates the multi-period [...] Read more.
Marine data assets are increasingly recognized as important drivers of value creation in the blue economy, yet their valuation remains challenging due to difficulties in isolating data-related earnings in capital-intensive maritime enterprises. This study proposes a methodological valuation framework that integrates the multi-period excess earnings method with the Analytic Hierarchy Process (AHP) and the Fuzzy Comprehensive Evaluation (FCE) approach, incorporating both financial and non-financial dimensions. The framework follows a “total synergistic return–data contribution separation” logic to isolate data-related excess earnings and applies an AHP–FCE-based adjustment coefficient to account for data quality, application value, and risk. A representative container shipping enterprise is used as an illustrative application to demonstrate the implementation logic of the framework. The results indicate that marine data assets can constitute a non-negligible component of enterprise value under reasonable parameter settings, while sensitivity analysis highlights the influence of key parameters such as the data contribution coefficient and discount rate. The proposed framework provides a transparent methodological reference for marine data asset valuation and supports sustainability-oriented research and practice in the blue economy. Full article
23 pages, 14742 KB  
Article
Grapevine Canopy Volume Estimation from UAV Photogrammetric Point Clouds at Different Flight Heights
by Leilson Ferreira, Pedro Marques, Emanuel Peres, Raul Morais, Joaquim J. Sousa and Luís Pádua
Remote Sens. 2026, 18(3), 409; https://doi.org/10.3390/rs18030409 - 26 Jan 2026
Abstract
Vegetation volume is a useful indicator for assessing canopy structure and supporting vineyard management tasks such as foliar applications and canopy management. The photogrammetric processing of imagery acquired using unmanned aerial vehicles (UAVs) enables the generation of dense point clouds suitable for estimating [...] Read more.
Vegetation volume is a useful indicator for assessing canopy structure and supporting vineyard management tasks such as foliar applications and canopy management. The photogrammetric processing of imagery acquired using unmanned aerial vehicles (UAVs) enables the generation of dense point clouds suitable for estimating canopy volume, although point cloud quality depends on spatial resolution, which is influenced by flight height. This study evaluates the effect of three flight heights (30 m, 60 m, and 100 m) on grapevine canopy volume estimation using convex hull, alpha shape, and voxel-based models. UAV-based RGB imagery and field measurements were collected during three periods at different phenological stages in an experimental vineyard. The strongest agreement with field-measured volume occurred at 30 m, where point density was highest. Envelope-based methods showed reduced performance at higher flight heights, while voxel-based grids remained more stable when voxel size was adapted to point density. Estimator behavior also varied with canopy architecture and development. The results indicate appropriate parameter choices for different flight heights and confirm that UAV-based RGB imagery can provide reliable grapevine canopy volume estimates. Full article
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18 pages, 387 KB  
Article
Transfer of Quantum Information and Genesis of Superfluid Vacuum in the Pre-Inflationary Universe
by Konstantin G. Zloshchastiev
Universe 2026, 12(2), 33; https://doi.org/10.3390/universe12020033 - 26 Jan 2026
Abstract
We conjecture that during the time period preceding the inflationary epoch, the background matter was initially a condensate formed from a many-body system of indistinguishable particles whose states were in a quantum superposition. This resulted in the occurrence of a statistical ensemble of [...] Read more.
We conjecture that during the time period preceding the inflationary epoch, the background matter was initially a condensate formed from a many-body system of indistinguishable particles whose states were in a quantum superposition. This resulted in the occurrence of a statistical ensemble of spacetimes, thus causing the probabilistic uncertainty in the spacetime geometry of the pre-inflationary multiverse. Then, at a certain moment in time, a measurement event occurred, which broke the linear superposition and reduced the primordial geometrical multiverse to a single state. This process can be described as a quantum Shannon information transfer, which induces logarithmic nonlinearity in the evolution equations of the background system. The latter, therefore, transformed into a logarithmic quantum liquid of a superfluid type and formed the physical vacuum. This measurement also generated the primary mass energy necessary for the Universe’s further evolution into the inflationary epoch, followed by the contemporary “dark energy” era. Full article
(This article belongs to the Section Cosmology)
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29 pages, 2594 KB  
Article
The Value Addition of Healthcare 4.0 Loyalty Programs: Implications for Logistics Management
by Maria João Vieira, Ana Luísa Ramos and João Amaral
Logistics 2026, 10(2), 30; https://doi.org/10.3390/logistics10020030 - 26 Jan 2026
Abstract
Background: Digital transformation is reshaping healthcare operations, with loyalty programs increasingly used to strengthen patient engagement and streamline administrative workflows. However, fragmented information systems and manual verification routines continue to create bottlenecks, inconsistencies, and extended lead times. Methods: This study applies [...] Read more.
Background: Digital transformation is reshaping healthcare operations, with loyalty programs increasingly used to strengthen patient engagement and streamline administrative workflows. However, fragmented information systems and manual verification routines continue to create bottlenecks, inconsistencies, and extended lead times. Methods: This study applies a mixed-methods approach within the Business Process Management (BPM) lifecycle to redesign the eligibility verification process for a loyalty program at Casa de Saúde São Mateus Hospital. Quantitative time measurements were collected during peak periods, while qualitative insights from staff observations and discussions supported process discovery and bottleneck identification. The proposed solution integrates a centralized SQL database, automated verification routines, and a dedicated administrative interface synchronized with the MedicineOne system. Results: The redesigned process reduced eligibility verification time by approximately 80% and improved Flow Efficiency by around 11.7%. Manual interventions, data fragmentation, and discount-application errors decreased substantially. The centralized database improved data reliability, while automated checks enhanced consistency and reduced staff workload. The system also enabled more accurate beneficiary management and improved coordination across administrative activities. Conclusions: Integrating Healthcare 4.0 principles with BPM enhances internal logistics, reduces lead times, and improves operational reliability. The proposed model offers a replicable framework for modernizing healthcare service delivery. Full article
(This article belongs to the Section Humanitarian and Healthcare Logistics)
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44 pages, 1721 KB  
Systematic Review
Vibration-Based Predictive Maintenance for Wind Turbines: A PRISMA-Guided Systematic Review on Methods, Applications, and Remaining Useful Life Prediction
by Carlos D. Constantino-Robles, Francisco Alberto Castillo Leonardo, Jessica Hernández Galván, Yoisdel Castillo Alvarez, Luis Angel Iturralde Carrera and Juvenal Rodríguez-Reséndiz
Appl. Mech. 2026, 7(1), 11; https://doi.org/10.3390/applmech7010011 - 26 Jan 2026
Abstract
This paper presents a systematic review conducted under the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework, analyzing 286 scientific articles focused on vibration-based predictive maintenance strategies for wind turbines within the context of advanced Prognostics and Health Management (PHM). The [...] Read more.
This paper presents a systematic review conducted under the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework, analyzing 286 scientific articles focused on vibration-based predictive maintenance strategies for wind turbines within the context of advanced Prognostics and Health Management (PHM). The review combines international standards (ISO 10816, ISO 13373, and IEC 61400) with recent developments in sensing technologies, including piezoelectric accelerometers, microelectromechanical systems (MEMS), and fiber Bragg grating (FBG) sensors. Classical signal processing techniques, such as the Fast Fourier Transform (FFT) and wavelet-based methods, are identified as key preprocessing tools for feature extraction prior to the application of machine-learning-based diagnostic algorithms. Special emphasis is placed on machine learning and deep learning techniques, including Support Vector Machines (SVM), Random Forest (RF), Convolutional Neural Networks (CNN), Long Short-Term Memory networks (LSTM), and autoencoders, as well as on hybrid digital twin architectures that enable accurate Remaining Useful Life (RUL) estimation and support autonomous decision-making processes. The bibliometric and case study analysis covering the period 2020–2025 reveals a strong shift toward multisource data fusion—integrating vibration, acoustic, temperature, and Supervisory Control and Data Acquisition (SCADA) data—and the adoption of cloud-based platforms for real-time monitoring, particularly in offshore wind farms where physical accessibility is constrained. The results indicate that vibration-based predictive maintenance strategies can reduce operation and maintenance costs by more than 20%, extend component service life by up to threefold, and achieve turbine availability levels between 95% and 98%. These outcomes confirm that vibration-driven PHM frameworks represent a fundamental pillar for the development of smart, sustainable, and resilient next-generation wind energy systems. Full article
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14 pages, 1313 KB  
Article
From Screening to Outcomes: Fourteen-Year Hospital-Wide Surveillance of Alert Pathogens and Antimicrobial Use in a Paediatric Tertiary Hospital
by Aleksandra Tukendorf, Julia Burzyńska, Katarzyna Semczuk, Ryszard Sot and Katarzyna Dzierżanowska-Fangrat
Antibiotics 2026, 15(2), 118; https://doi.org/10.3390/antibiotics15020118 - 26 Jan 2026
Abstract
Background/Objectives: Infection prevention and control (IPC) programs combine pathogen-targeted measures (e.g., admission screening) with hospital-wide standard precautions (e.g., hand hygiene, HH). We assessed temporal associations between screening, HH, antimicrobial stewardship (AMS), and hospital-level outcomes in a tertiary paediatric hospital. Methods: This [...] Read more.
Background/Objectives: Infection prevention and control (IPC) programs combine pathogen-targeted measures (e.g., admission screening) with hospital-wide standard precautions (e.g., hand hygiene, HH). We assessed temporal associations between screening, HH, antimicrobial stewardship (AMS), and hospital-level outcomes in a tertiary paediatric hospital. Methods: This study was a retrospective hospital-wide ecological time-series at the Children’s Memorial Health Institute. Annual aggregate data: 2011–2024 for screening, colonisation, and healthcare-associated infections (HAIs) with alert pathogens; 2016–2024 for antibiotic consumption (ATC J01, systemic antibacterials). Process indicators: number of screening tests and alcohol-based hand rub (ABHR) consumption per 1000 patient-days (PD). Outcomes: colonisations/HAIs per 1000 PD and defined daily doses (DDD) per 1000 PD overall and by class. Trends used linear regression and Spearman’s rank correlation. Results: Screening intensity increased from 39 to 150/1000 PD (slope +8.3/year; R2 = 0.90; p < 0.001). Detected colonisation rose (2.5 → peak 8.05/1000 PD in 2023; slope +0.39; R2 = 0.81; p < 0.001), while multidrug-resistant-organism (MDRO)-attributable HAIs remained low/stable (0.27–0.62/1000 PD; slope −0.014; p = 0.023). ABHR consumption increased from 26.1 to 78.0 L/1000 PD in 2020 (p < 0.001) and partially normalised to 60.0 in 2024 (>2 × baseline). Overall ATC J01 showed no long-term linear trend (~278–356 DDD/1000 PD; +2.57/year; p = 0.46), but class mix shifted: carbapenems, fluoroquinolones, and amoxicillin–clavulanate decreased; third/fourth-generation cephalosporins, piperacillin/tazobactam, and glycopeptides increased. Conclusions: In this tertiary paediatric setting, expansion of risk-based admission screening and sustained implementation of horizontal IPC measures were accompanied by increased detection of colonisation with alert pathogens, while MDRO-attributable HAIs remained low and stable at the hospital level. Over the same period, AMS activity coincided with a redistribution in antibiotic class use without a clear long-term reduction in total antibiotic consumption. These hospital-level findings are descriptive and hypothesis-generating; causal inference is limited by the ecological study design, and the heterogeneous, multispecialty structure of a tertiary paediatric centre. Full article
(This article belongs to the Section Antibiotics Use and Antimicrobial Stewardship)
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37 pages, 18066 KB  
Article
Characterization of the Crustacean Methyl Farnesoate Transcriptional Signaling Genes
by Vanessa L. Bentley, Jorge L. Pérez-Moreno, David S. Durica and Donald L. Mykles
Int. J. Mol. Sci. 2026, 27(3), 1215; https://doi.org/10.3390/ijms27031215 - 26 Jan 2026
Abstract
Methyl farnesoate (MF) is a sesquiterpenoid hormone that controls a variety of physiological processes in crustaceans, including morphogenesis, development, reproduction, and molting. MF action is mediated by a transcriptional signaling cascade consisting of Methoprene-tolerant (Met), Steroid receptor coactivator (Src), [...] Read more.
Methyl farnesoate (MF) is a sesquiterpenoid hormone that controls a variety of physiological processes in crustaceans, including morphogenesis, development, reproduction, and molting. MF action is mediated by a transcriptional signaling cascade consisting of Methoprene-tolerant (Met), Steroid receptor coactivator (Src), Krüppel homolog 1 (Kr-h1), and Ecdysone response gene 93 (E93) transcription factors (TFs), and transcriptional co-regulators CREB-binding protein (CBP) and C-terminal-binding protein (CtBP). Phylogenetic and sequence analyses revealed that these genes were highly conserved across pancrustacean species. Met and Src were characterized as basic helix-loop-helix, Period (Per)-Aryl Hydrocarbon Nuclear Translocator (ARNT)-Single-minded (Sim) protein (bHLH-PAS) TFs; Kr-h1 was characterized as a C2H2 zinc finger TF with seven zinc finger motifs; E93 was characterized as a helix-turn-helix, pipsqueak (HTH_Psq) TF. CBP was identified by several zinc finger-binding regions with Transcription Adaptor Zinc Finger 1 and 2, Really Interesting New Gene, Plant homeodomain, and Z-type zinc finger domains; the Kinase-inducible Domain Interacting-transcription factor docking site; the Bromodomain-acetylated lysine recognition and binding site; the histone acetyltransferase domain; and a C-terminal CREB-binding region containing a nuclear receptor co-activator-binding domain. CtBP had a dehydrogenase domain with arginine-glutamate-histidine catalytic triad. 81 Met contigs, 45 Src contigs, 136 Kr-h1 contigs, 66 E93 contigs, 60 CBP contigs, and 172 CtBP contigs were identified across pancrustacean taxa, including decapod crustaceans. Bioinformatic identification and annotation of these TFs and co-regulators in brachyuran Y-organ (YO) transcriptomes suggests that MF signaling influences YO ecdysteroidogenesis; functional tests in the YO are needed to establish causality. Full article
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27 pages, 4135 KB  
Article
The Model and Burner Development for Crude Glycerol and Used Vegetable Mixing: Cube Mushroom Steaming Oven
by Anumut Siricharoenpanich, Paramust Juntarakod and Paisarn Naphon
Eng 2026, 7(2), 56; https://doi.org/10.3390/eng7020056 - 25 Jan 2026
Abstract
Reducing fuel costs, maximizing waste utilization, and improving energy efficiency are critical challenges in agricultural thermal processes. This study addresses these issues by developing and evaluating a mixed-fuel burner and furnace system for steaming mushroom substrate cubes using crude glycerol and recycled vegetable [...] Read more.
Reducing fuel costs, maximizing waste utilization, and improving energy efficiency are critical challenges in agricultural thermal processes. This study addresses these issues by developing and evaluating a mixed-fuel burner and furnace system for steaming mushroom substrate cubes using crude glycerol and recycled vegetable oil as low-cost alternative energy sources. The experimental investigation assessed boiler thermal efficiency, combustion efficiency, exhaust-gas composition, temperature distribution, steam generation, and combustion-gas dispersion within the furnace. In parallel, analytical modeling of pressure, temperature, and gas-flow behavior was performed to validate the experimental observations. Five fuel compositions were examined, including 100% used vegetable oil, 100% crude glycerol, and blended ratios of 50/50, 25/75, and 10/90 (glycerol/vegetable oil), with all tests conducted in accordance with DIN EN 203-1 standards. The results demonstrate that blending used vegetable oil with glycerol significantly improves flame stability, increases peak combustion temperatures, and suppresses incomplete-combustion byproducts compared with pure glycerol operation. Combustion efficiencies of 90–99% and boiler thermal efficiencies of 72–73% were achieved. Among the tested fuels, the optimal balance between combustion stability, efficiency, and cost was achieved with a 25% glycerol and 75% used vegetable oil mixture. Economic analysis revealed that the proposed mixed-fuel system offers superior viability compared with LPG, reducing annual fuel costs by approximately 50%, shortening steaming time by 2 h per batch, and achieving a payback period of only 3.26 months. These findings confirm the feasibility of the proposed waste-to-energy system for small- and medium-scale agricultural applications. To further enhance sustainability and renewable fuel utilization, future work should focus on improving air–fuel mixing for higher glycerol fractions, scaling the system for larger farms, and extending its application to other agricultural thermal processes. Full article
24 pages, 6240 KB  
Article
Stable Isotope Analysis of Precipitation—Karst Groundwater System (Mt. Učka, Croatia)
by Diana Mance, Maja Radišić, Maja Oštrić, Davor Mance, Alenka Turković-Juričić, Ema Toplonjak and Josip Rubinić
Water 2026, 18(3), 308; https://doi.org/10.3390/w18030308 - 25 Jan 2026
Abstract
Karst aquifers provide critical water resources in the Mediterranean region, yet climate change threatens their sustainability. This study integrates stable isotope analysis (δ2H, δ18O), hydrochemistry, and hydrological time series to characterize precipitation–groundwater dynamics in the Mt. Učka karst system [...] Read more.
Karst aquifers provide critical water resources in the Mediterranean region, yet climate change threatens their sustainability. This study integrates stable isotope analysis (δ2H, δ18O), hydrochemistry, and hydrological time series to characterize precipitation–groundwater dynamics in the Mt. Učka karst system (Croatia). Precipitation samples collected across an altitudinal gradient of approximately 1400 m and groundwater from three major groundwater sources were analyzed over a 2.5-year period. Precipitation exhibits pronounced isotopic variability with d-excess values indicating mixed Atlantic–Mediterranean moisture sources. Groundwater is primarily recharged by precipitation from the cold part of the hydrological year. It exhibits substantial attenuation of isotopic signals, which indicates extensive mixing processes but prevents quantitative estimation of mean residence time. Groundwater is predominantly recharged from elevations above 900 m a.s.l., with one spring showing evidence of higher-elevation recharge. Analysis confirms the system’s dual porosity: a rapid, conduit-dominated response indicates high vulnerability to surface contamination, while a sustained, matrix-dominated response provides greater buffering capacity. These findings highlight the vulnerability of karst systems to projected reductions in autumn precipitation, the critical recharge season, and demonstrate the necessity of multi-tracer approaches for comprehensive aquifer characterization. Full article
24 pages, 2423 KB  
Article
Single-Column Partial Vapor Recompression Retrofit Design for Separation of 1,2-Propanediol and Ethylene Glycol Mixture
by Rafaella Machado de Assis Cabral Ribeiro, Fernanda Ribeiro Figueiredo and Diego Martinez Prata
Processes 2026, 14(3), 421; https://doi.org/10.3390/pr14030421 - 25 Jan 2026
Abstract
For the separation of the close-boiling 1,2-propanediol and ethylene glycol mixture, several process intensification (PI) schemes have been proposed for the two-column configurations. However, no PI technology has yet been investigated for the challenging single-column design operating at atmospheric pressure (SCD). The previously [...] Read more.
For the separation of the close-boiling 1,2-propanediol and ethylene glycol mixture, several process intensification (PI) schemes have been proposed for the two-column configurations. However, no PI technology has yet been investigated for the challenging single-column design operating at atmospheric pressure (SCD). The previously published improvements include the economically modified single-column design (MSCD) as well as high-pressure configurations with (HPDHI) and without (HPD) feed-preheating heat integration. Therefore, this study proposes a partial vapor recompression (SCD-PVR) configuration to intensify this separation using UniSim Design software. Economic and environmental performances were evaluated through total annualized cost (TAC) and CO2 emissions. When directly compared with the SCD, MSCD, HPD, and HPDHI schemes, the SCD-PVR achieved CO2 emission reductions of 67.9%, 68.6%, 61.2%, and 56.0%, respectively. Considering a 5-year payback period, SCD-PVR outperformed the SCD and MSCD schemes, decreasing TAC by 9.7% and 11.2%. For a 10-year payback period, the benefits became more significant, with TAC reductions of 31.4%, 32.7%, 17.2%, and 9.3% relative to SCD, MSCD, HPD, and HPDHI. These findings demonstrate that SCD-PVR provides a more energy-efficient, environmentally sustainable, and economically attractive alternative for retrofitting existing plants. Full article
(This article belongs to the Section Chemical Processes and Systems)
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15 pages, 2093 KB  
Article
Coupling Bayesian Optimization with Generalized Linear Mixed Models for Managing Spatiotemporal Dynamics of Sediment PFAS
by Fatih Evrendilek, Macy Hannan and Gulsun Akdemir Evrendilek
Processes 2026, 14(3), 413; https://doi.org/10.3390/pr14030413 - 24 Jan 2026
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Abstract
Conventional descriptive statistical approaches in per- and polyfluoroalkyl substance (PFAS) environmental forensics often fail under small-sample, ecosystem-level complexity, challenging the optimization of sampling, monitoring, and remediation strategies. This study presents an advance from passive description to adaptive decision-support for complex PFAS contamination. By [...] Read more.
Conventional descriptive statistical approaches in per- and polyfluoroalkyl substance (PFAS) environmental forensics often fail under small-sample, ecosystem-level complexity, challenging the optimization of sampling, monitoring, and remediation strategies. This study presents an advance from passive description to adaptive decision-support for complex PFAS contamination. By integrating Bayesian optimization (BO) via Gaussian Processes (GP) with a Generalized Linear Mixed Model (GLMM), we developed a signal-extraction framework for both understanding and action from limited data (n = 18). The BO/GP model achieved strong predictive performance (GP leave-one-out R2 = 0.807), while the GLMM confirmed significant overdispersion (1.62), indicating a patchy contamination distribution. The integrated analysis suggested a dominant spatiotemporal interaction: a transient, high-intensity perfluorooctane sulfonate (PFOS) plume that peaked at a precise location during early November (the autumn recharge period). Concurrently, the GLMM identified significant intra-sample variance (p = 0.0186), suggesting likely particulate-bound (colloid/sediment) transport, and detected n-ethyl perfluorooctane sulfonamidoacetic acid (NEtFOSAA) as a critical precursor (p < 0.0001), thus providing evidence consistent with the source as historic 3M aqueous film-forming foam. This coupled approach creates a dynamic, iterative decision-support system where signal-based diagnosis informs adaptive optimization, enabling mission-specific actions from targeted remediation to monitoring design. Full article
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30 pages, 789 KB  
Article
The Hexagram of Contemplation 觀卦 (guan gua) and “Using the Divine Way to Give Instruction” 神道設教 (shen dao she jiao) in Early China
by Zhiping Yu
Religions 2026, 17(2), 132; https://doi.org/10.3390/rel17020132 - 24 Jan 2026
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Abstract
Most primitive religions originated from the devout worship of celestial deities, earthly spirits, and ghosts. In oracle bone inscriptions, rituals related to praying for rain, temple worship, river deity worship, and the worship of great deities were referred to as “fang” 方 or [...] Read more.
Most primitive religions originated from the devout worship of celestial deities, earthly spirits, and ghosts. In oracle bone inscriptions, rituals related to praying for rain, temple worship, river deity worship, and the worship of great deities were referred to as “fang” 方 or “yi fang” 以方. The Supreme God was the paramount deity of the Yin Shang Dynasty people; by the early Zhou Dynasty, the Supreme God and ancestral spirits began to merge. The hexagram of Contemplation 觀卦 (guan gua) establishes instruction through the concept of “contemplation” fully presenting the entire process of shamans, sorcerers, or ritual hosts participating in temple sacrifices, and completing the hand-washing ritual 盥 (guan) and the sacrifice-offering ritual 薦 (jian). It emphasizes the sincere communication between humans and Heaven. When a monarch performs the guan ritual, he embodies inner “sincerity and clarity” 誠明 (chengming); in response, the celestial deities will “show trust” 有孚 (youfu). Thus, it can be verified that deities exist in Heaven, and an interactive, responsive relationship is formed between Heaven and humans. The nine in the fifth place (the dominant line) possesses great inspiring power. The two fundamental dimensions for interpreting the hexagram structure are “the great view is above” 大觀在上 (da guan zai shang) and “[t]hose below look toward him and are transformed” 下觀而化 (xia guan er hua). These dimensions not only highlight the infinite transcendence, charisma, and appeal of the worshipped deities but also underscore humans’ profound reverence and faith in deities and the absolute existence. Sages 聖人 (sheng ren), as intermediaries between humans and deities, established religion for the sake of human life but did not regard themselves as religious leaders. However, from the Shang and Zhou dynasties to the Spring and Autumn period, a transition occurred in the spiritual life of the Chinese people: from shamanism to ritual propriety 禮 (li), and from theistic culture to humanistic culture. This transition laid the fundamental direction for the development and evolution of Chinese culture over the following 2500 years. Confucius attempted to replace or eliminate the shamanistic elements in early Confucians with personalized moral experience and ethical consciousness. Full article
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