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17 pages, 850 KiB  
Article
The Relevance of the “Usual Environment” Concept in Nautical Tourism Monitoring
by Neven Ivandić and Zrinka Marušić
Sustainability 2025, 17(17), 7622; https://doi.org/10.3390/su17177622 - 23 Aug 2025
Abstract
The notion of the usual environment is a key factor in distinguishing tourism activities from a demand-side perspective, yet applying it in practice presents persistent difficulties when estimating tourism’s physical and monetary scale. These challenges are particularly pronounced in nautical tourism, and especially [...] Read more.
The notion of the usual environment is a key factor in distinguishing tourism activities from a demand-side perspective, yet applying it in practice presents persistent difficulties when estimating tourism’s physical and monetary scale. These challenges are particularly pronounced in nautical tourism, and especially in the case of domestic same-day boat trips. Focusing on Croatia, a country where yachting makes up a substantial share of overall tourism flows, this study examines criteria for classifying domestic nautical same-day trips from the demand perspective. Qualitative research on the population of residents who are recreational boat owners was conducted. The aim of the research was to assess residents’ perception of the usual environment when on a same-day boat trip from the criteria of trip frequency, distance, motives, and activities. Seventeen in-depth interviews were conducted, providing insight into subjective and objective determinants of trip classification. Although the analysis revealed a blurred understanding of the distinction between boating as a lifestyle and as a tourism activity, the results indicate that official statistics likely underestimate the number of recreational same-day boat trips. This finding underscores the need for more precise measurement of total physical flows in nautical tourism as a prerequisite for effective sustainability assessment and informed management policies. Full article
(This article belongs to the Section Tourism, Culture, and Heritage)
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21 pages, 4010 KiB  
Article
Headwater Systems as Green Infrastructure: Prioritising Restoration Hotspots for Sustainable Rural Landscapes
by Selma B. Pena
Land 2025, 14(9), 1704; https://doi.org/10.3390/land14091704 - 23 Aug 2025
Abstract
This study aims to assess the role of headwater systems (HS) in enhancing ecological connectivity and supporting Green Infrastructure in the Centre Region of Portugal. Specifically, it identifies restoration opportunity areas within HS by analysing land-use changes over the past 70 years, modelling [...] Read more.
This study aims to assess the role of headwater systems (HS) in enhancing ecological connectivity and supporting Green Infrastructure in the Centre Region of Portugal. Specifically, it identifies restoration opportunity areas within HS by analysing land-use changes over the past 70 years, modelling land-use scenarios to promote ecological resilience, and evaluating connectivity between HS and Natura 2000 sites. The methodology integrates spatial analysis of historical land-use data with connectivity modelling using least-cost path approaches. Results show substantial transformation in HS areas, notably the expansion of eucalyptus plantations and a decline in agricultural land. Approximately 58% of the HS are identified as requiring restoration, including areas within the Natura 2000 network. The connectivity assessment reveals that HS can function as effective ecological corridors, contributing to improved water regulation, soil conservation, gene flow, and wildfire mitigation. A total of 61 potential ecological linkages between Natura 2000 sites were identified. These findings highlight the strategic importance of integrating HS into regional and national Green Infrastructure planning and supporting the implementation of the EU Biodiversity Strategy for 2030. The study recommends prioritising headwater restoration through multi-scale planning approaches and active involvement of local stakeholders to ensure sustainable land-use management. Full article
(This article belongs to the Special Issue Efficient Land Use and Sustainable Development in European Countries)
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39 pages, 2144 KiB  
Article
A Causal Modeling Approach to Agile Project Management and Progress Evaluation
by Saulius Gudas, Vitalijus Denisovas, Jurij Tekutov and Karolis Noreika
Mathematics 2025, 13(16), 2657; https://doi.org/10.3390/math13162657 - 18 Aug 2025
Viewed by 176
Abstract
Despite widespread adoption, traditional Agile project management practices often fail to ensure successful delivery of enterprise-scale software projects. One key limitation lies in the absence of a conceptually defined structure for the various types of Agile activities and their interactions. As a result, [...] Read more.
Despite widespread adoption, traditional Agile project management practices often fail to ensure successful delivery of enterprise-scale software projects. One key limitation lies in the absence of a conceptually defined structure for the various types of Agile activities and their interactions. As a result, Agile methodologies typically lack formal indicators for evaluating the semantic content and progress status of project activities. Although widely used tools for Agile project management, such as Atlassian Jira, capture operational data, project status assessment interpretation remains largely subjective—relying on the experience and judgment of managers and team members rather than on a formal knowledge model or well-defined semantic attributes. As Agile project activities continue to grow in complexity, there is a pressing need for a modeling approach that captures their causal structure in order to describe the essential characteristics of the processes and ensure systematic monitoring and evaluation of the project. The complexity of the corresponding model must correlate with the causality of processes to avoid losing essential properties and to reveal the content of causal interactions. To address these gaps, this paper introduces a causal Agile process model that formalizes the internal structure and transformation pathways of Agile activity types. To our knowledge, it is the first framework to integrate a recursive, causally grounded structure into Agile management, enabling both semantic clarity and quantitative evaluation of project complexity and progress. The aim of the article is, first, to describe conceptually different Agile activity types from a causal modeling perspective, its internal structure and information transformations, and, second, to formally define the causal Agile management model and its characteristics. Each Agile activity type (e.g., theme, initiative, epic, user story) is modeled using the management transaction (MT) framework—an internal model of activity that comprises a closed-loop causal relationship among management function (F), process (P), state attribute (A), and control (V) informational flows. Using this framework, the internal structure of Agile activity types is normalized and the different roles of activities in internal MT interactions are defined. An important feature of this model is its recursive structure, formed through a hierarchy of MTs. Additionally, the paper presents classifications of vertical and horizontal causal interactions, uncovering theoretically grounded patterns of information exchange among Agile activities. These classifications support the derivation of quantitative indicators for assessing project complexity and progress at a given point in time, offering insights into activity specification completeness at hierarchical levels and overall project content completeness. Examples of complexity indicator calculations applied to real-world enterprise application system (EAS) projects are included. Finally, the paper describes enhancements to the Jira tool, including a causal Agile management repository and a prototype user interface. An experimental case study involving four Nordic EAS projects (using Scrum at the team level and SAFe at the program level) demonstrates that the Jira tool, when supplemented with causal analysis, can reveal missing links between themes and initiatives and align interdependencies between teams in real time. The causal Agile approach reduced the total number of requirements by an average of 13% and the number of change requests by 14%, indicating a significant improvement in project coordination and quality. Full article
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32 pages, 2039 KiB  
Article
A Systematic Study on Embodied Carbon Emissions in the Materialization Phase of Residential Buildings: Indicator Assessment Based on Life Cycle Analysis and STIRPAT Modeling
by Miaoyi Wang, Yuchen Lu, Chenlu Yang and Mingyu Yang
Systems 2025, 13(8), 711; https://doi.org/10.3390/systems13080711 - 18 Aug 2025
Viewed by 250
Abstract
Against the backdrop of intensifying global climate change and advancing the goal of the “dual-carbon” strategy, the built environment is being viewed as a complex socio-technical system in which technological, economic, demographic and institutional subsystems are coupled and evolving at different scales. As [...] Read more.
Against the backdrop of intensifying global climate change and advancing the goal of the “dual-carbon” strategy, the built environment is being viewed as a complex socio-technical system in which technological, economic, demographic and institutional subsystems are coupled and evolving at different scales. As a core node in this system, residential buildings not only carry infrastructural functions, but are also deeply embedded in energy flows, material cycles and behavioural structures, which have a significant impact on carbon emissions. Given the high volume of residential buildings in China and the significant differences between urban and rural construction, there is an urgent need to systematically identify and analyse the implicit carbon emissions during the materialisation phase. In this paper, from the perspective of systems engineering, we selected 30 urban and rural residential buildings in provinces and cities from 2005 to 2020 as the research objects, adopted the life cycle assessment (LCA) method to account for the implied carbon emissions in the materialisation stage, and systematically identified the driving factors of carbon emissions based on the Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model. From this study, we made the following conclusions: (1) the total carbon emissions of residential buildings in urban and rural areas in China continue to rise during the materialisation stage, showing a spatial pattern of “high in the south-east and low in the north-west”, with a significant trend of structural transformation in urban and rural areas and with steel–concrete structures dominating in towns and cities, and bricks and steel being used in rural areas. (2) Resident population and disposable income are generally positive driving factors, while the influence of industrial structure and energy intensity is heterogeneous between urban and rural areas. For overall residential buildings, every 1% increase in resident population and income will lead to a 1.055% and 0.73% increase in carbon emissions, respectively. The study shows that life-cycle-oriented carbon accounting and the identification of multidimensional driving mechanisms are of great policy value in developing urban–rural differentiated emission reduction paths and enhancing the effectiveness of carbon management in the building sector. Full article
(This article belongs to the Section Systems Practice in Social Science)
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22 pages, 1605 KiB  
Article
Effects of Culture Systems and Feed Types on Water Quality and Growth Performance of Japanese Eel (Anguilla japonica)
by Jimin Choi, Ju-ae Hwang, Hyeong Su Kim and Jeonghwan Park
Animals 2025, 15(16), 2420; https://doi.org/10.3390/ani15162420 - 18 Aug 2025
Viewed by 143
Abstract
Utilizing paste feed within a recirculating aquaculture system for eel cultivation may lead to various challenges, such as water quality degradation and, hence, transitioning to floating pellet type feed becomes essential. In this study, we aimed to investigate the impact of different feed [...] Read more.
Utilizing paste feed within a recirculating aquaculture system for eel cultivation may lead to various challenges, such as water quality degradation and, hence, transitioning to floating pellet type feed becomes essential. In this study, we aimed to investigate the impact of different feed types (paste and floating extruded pellet) and rearing systems (recirculating aquaculture and flow through system) on water quality, growth, blood chemistry, body composition, and expression levels of digestive enzymes in Japanese eels (Anguilla japonica). Throughout the experiment, notable variations were observed in total ammonia nitrogen and nitrite nitrogen levels, with higher concentrations in the recirculating aquaculture system (1.00 ± 0.64 and 0.757 ± 0.464 mg/L, respectively) than paste groups (0.859 ± 0.651 and 0.485 ± 0.502 mg/L, respectively). Significant differences were observed in weight gain and specific growth rates, with the pellet group (154 ± 10% and 1.50 ± 0.06%/day, respectively) exhibiting higher values than the paste group (135 ± 13% and 1.37 ± 0.09%/day, respectively). Blood parameters showed significant differences depending on the culture system, with generally higher values observed in the flow-through system, while no significant differences were observed between feed types. Whole-body composition exhibited variations attributed to feed intake, with notable differences in crude protein and crude fat content among the experimental groups. The expression levels of digestive enzymes and nutrient transporters were higher when the eels were fed pellet-type feed and reared in recirculating aquaculture system. The study findings indicate that pellet feed enhances water quality management in RAS, leading to improved eel growth. Given its lower environmental stress, pellet feed is preferable to paste feed for optimizing eel production in RAS. Full article
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31 pages, 11711 KiB  
Article
Blue–Green Infrastructure Network Planning in Urban Small Watersheds Based on Water Balance
by Xin Chen and Xiaojun Wang
Land 2025, 14(8), 1652; https://doi.org/10.3390/land14081652 - 15 Aug 2025
Viewed by 234
Abstract
The rapid expansion of urbanization and inadequate planning have triggered a water balance crisis in many cities, manifesting as both the need for artificial lake supplementation and frequent urban flooding. Using the Xuanwu Lake watershed in Nanjing as a case study, this research [...] Read more.
The rapid expansion of urbanization and inadequate planning have triggered a water balance crisis in many cities, manifesting as both the need for artificial lake supplementation and frequent urban flooding. Using the Xuanwu Lake watershed in Nanjing as a case study, this research aims to optimize the Blue–Green Infrastructure (BGI) network to maximize rainfall utilization within the watershed. The ultimate goal is to restore natural water balance processes and reduce reliance on artificial supplementation while mitigating urban flood risks. First, the Soil Conservation Service Curve Number (SCS–CN) model is employed to estimate the maximum potential of natural convergent flow within the watershed. Second, drawing on landscape connectivity theory, a multi-level BGI network optimization model is developed by integrating the Minimum Cumulative Resistance (MCR) model and the gravity model, incorporating both hydrological connectivity and flood safety considerations. Third, a water balance model based on the Storm Water Management Model (SWMM) framework and empirical formulas is constructed and coupled with the network optimization model to simulate and evaluate water budget performance under optimized scenarios. The results indicate that the optimized scheme can reduce artificial supplementation to Xuanwu Lake by 62.2% in June, while also ensuring effective supplementation throughout the year. Annual runoff entering the lake reaches 13.25 million cubic meters, meeting approximately 13% of the current annual supplementation demand. Moreover, under a 100-year return period flood scenario, the optimized network reduces total watershed flood volume by 35% compared to pre-optimization conditions, with flood-prone units experiencing reductions exceeding 50%. These findings underscore the optimized BGI network scheme’s capacity to reallocate rainwater resources efficiently, promoting a transition in urban water governance from an “engineering-dominated” approach to an “ecology-oriented and self-regulating” paradigm. Full article
(This article belongs to the Section Urban Contexts and Urban-Rural Interactions)
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48 pages, 2592 KiB  
Article
Coordinated Electric Vehicle Demand Management in the Unit Commitment Problem Integrated with Transmission Constraints
by Dimitrios Stamatakis and Athanasios I. Tolis
Energies 2025, 18(16), 4293; https://doi.org/10.3390/en18164293 - 12 Aug 2025
Viewed by 366
Abstract
Advancements in battery technology, marked by reduced costs and enhanced efficiency, are steadily making electric vehicles (EVs) more accessible to consumers. This trend is fueling global growth in EV fleet sizes, allowing EVs to compete directly with internal combustion engine vehicles. However, this [...] Read more.
Advancements in battery technology, marked by reduced costs and enhanced efficiency, are steadily making electric vehicles (EVs) more accessible to consumers. This trend is fueling global growth in EV fleet sizes, allowing EVs to compete directly with internal combustion engine vehicles. However, this rapid growth in EV numbers is likely to introduce challenges to the power grid, necessitating effective load management strategies. This work proposes an optimization method where EV load management is integrated into the Transmission Constrained Unit Commitment Problem (TCUCP). A Differential Evolution (DE) variant, enhanced with heuristic repair sub-algorithms, is employed to address the TCUCP. The heuristic sub-algorithms, adapted from earlier approaches to the simpler Unit Commitment Problem (UCP), are updated to incorporate power flow constraints and ensure the elimination of transmission line violations. Additionally, new repair mechanisms are introduced that combine priority lists with grid information to minimize violation. The proposed formulation considers EVs as both flexible loads and energy sources in a large urban environment powered by two grid nodes, accounting for the vehicles’ daily movement patterns. The algorithm exhibits exceptionally fast convergence to a feasible solution in fewer than 150 generations, despite the nonlinearity of the problem. Depending on the scenario, the total production cost is reduced by up to 45% within these generations. Moreover, the results of the proposed model, when compared with a MILP algorithm, achieve values with a relative difference of approximately 1%. Full article
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26 pages, 10493 KiB  
Article
Assessing the Climate and Land Use Impacts on Water Yield in the Upper Yellow River Basin: A Forest-Urbanizing Ecological Hotspot
by Li Gong and Kang Liang
Forests 2025, 16(8), 1304; https://doi.org/10.3390/f16081304 - 11 Aug 2025
Viewed by 329
Abstract
Understanding the drivers of water yield (WY) changes in ecologically sensitive, data-scarce watersheds is crucial for sustainable management, particularly in the context of accelerating forest expansion and urbanization. This study focuses on the upper Yellow River Basin (UYRB), a critical headwater region that [...] Read more.
Understanding the drivers of water yield (WY) changes in ecologically sensitive, data-scarce watersheds is crucial for sustainable management, particularly in the context of accelerating forest expansion and urbanization. This study focuses on the upper Yellow River Basin (UYRB), a critical headwater region that supplies 60% of the Yellow River’s flow and is undergoing rapid land use transitions from 1990 to 2100. Using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model and the Future Land-Use Simulation (FLUS) model, we quantify historical (1990–2020) and projected (2025–2100) WY dynamics under three SSP scenarios (SSP126, SSP370, and SSP585). InVEST, a spatially explicit ecohydrological model based on the Budyko framework, estimates WY by balancing precipitation and evapotranspiration. The FLUS model combines cellular automata (CA) with an artificial neural network (ANN)-based suitability evaluation and Markov chain-derived transition probabilities to simulate land-use change under multiple scenarios. Results show that WY increased significantly during the historical period (1990–2020), primarily driven by increased precipitation, with climate change accounting for 94% and land-use change for 6% of the total variation in WY. Under future scenarios (SSP126, SSP370, and SSP585), WY is projected to increase to 217 mm, 206 mm, and 201 mm, respectively. Meanwhile, the influence of land-use change is expected to diminish, with its contribution decreasing to 9.1%, 5.7%, and 3.1% under SSP126, SSP370, and SSP585, respectively. This decrease reflects the increasing strength of climate signals (especially extreme precipitation and evaporative demand), which masks the hydrological impacts of land-use transitions. These findings highlight the dominant role of climate change, the scenario-dependent effects of land-use change, and the urgent need for integrated climate–land management strategies in forest-urbanizing watersheds. Full article
(This article belongs to the Section Forest Hydrology)
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22 pages, 9411 KiB  
Article
A Spatiotemporal Multi-Model Ensemble Framework for Urban Multimodal Traffic Flow Prediction
by Zhenkai Wang and Lujin Hu
ISPRS Int. J. Geo-Inf. 2025, 14(8), 308; https://doi.org/10.3390/ijgi14080308 - 10 Aug 2025
Viewed by 630
Abstract
Urban multimodal travel trajectory prediction is a core challenge in Intelligent Transportation Systems (ITSs). It requires modeling both spatiotemporal dependencies and dynamic interactions among different travel modes such as taxi, bike-sharing, and buses. To address the limitations of existing methods in capturing these [...] Read more.
Urban multimodal travel trajectory prediction is a core challenge in Intelligent Transportation Systems (ITSs). It requires modeling both spatiotemporal dependencies and dynamic interactions among different travel modes such as taxi, bike-sharing, and buses. To address the limitations of existing methods in capturing these diverse trajectory characteristics, we propose a spatiotemporal multi-model ensemble framework, which is an ensemble model called GLEN (GCN and LSTM Ensemble Network). Firstly, the trajectory feature adaptive driven model selection mechanism classifies trajectories into dynamic travel and fixed-route scenarios. Secondly, we use a Graph Convolutional Network (GCN) to capture dynamic travel patterns and Long Short-Term Memory (LSTM) network to model fixed-route patterns. Subsequently the outputs of these models are dynamically weighted, integrated, and fused over a spatiotemporal grid to produce accurate forecasts of urban total traffic flow at multiple future time steps. Finally, experimental validation using Beijing’s Chaoyang district datasets demonstrates that our framework effectively captures spatiotemporal and interactive characteristics between multimodal travel trajectories and outperforms mainstream baselines, thereby offering robust support for urban traffic management and planning. Full article
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8 pages, 4462 KiB  
Case Report
Postpartum Endometritis and Sepsis Associated with Gardnerella vaginalis and Anaerococcus tetradius: Case Report and Literature Review
by Justina Martikaitytė, Agnė Bartulevičienė, Virginija Paliulytė, Darius Dasevičius and Diana Ramašauskaitė
Reports 2025, 8(3), 143; https://doi.org/10.3390/reports8030143 - 10 Aug 2025
Viewed by 592
Abstract
Background and Clinical Significance: Anaerococcus tetradius (A. tetradius) and Gardnerella vaginalis (G. vaginalis) are rare etiological factors for postpartum endometritis and are typically associated with bacterial vaginosis. However, in some cases, G. vaginalis and A. tetradius can cause [...] Read more.
Background and Clinical Significance: Anaerococcus tetradius (A. tetradius) and Gardnerella vaginalis (G. vaginalis) are rare etiological factors for postpartum endometritis and are typically associated with bacterial vaginosis. However, in some cases, G. vaginalis and A. tetradius can cause serious postpartum endometritis with complications such as sepsis. Case Presentation: 26-year-old pregnant woman expecting monochorionic diamniotic twins presented to the hospital at 35 weeks and 3 days of gestation and two male infants were delivered via the Cesarean section. On the fifth day after delivery, the patient began to complain of intense abdominal pain, a fever of 37.9 °C, and overall weakness. Blood tests revealed neutrophilic leukocytosis, increased C-reactive protein (CRP) of 225.4 mg/L. Upon examination, abdominal distension, tenderness on palpation, and positive symptoms of peritoneal irritation were present and the site of the abdominal incision was inflamed with flowing foul-smelling greenish pus. Ultrasound examination revealed free fluid collection in the peritoneal cavity, under the liver, and around the uterus. Later, the condition of the patient worsened with progressing hypotension and respiratory distress. As a result, suppurative peritonitis and sepsis was suspected and the patient underwent urgent total hysterectomy without oophorectomy. Acute endometritis, focal myometritis, and chronic cervicitis were concluded from histopathological examination of the removed uterus. Microbiological tests showed the most abundant growth of A. tetradius in the wound cultures and great abundance of G. vaginalis in the abdominal cavity cultures. After trying three different treatment schemes and difficulties with determining the antibiotic sensitivity tests for pathogens, the antibacterial therapy was escalated to Meropenem, which was found to be effective, and the patient was discharged home. Conclusions: This case report highlights the severity of complications of postpartum endometritis that can be caused by rare pathogens (such as G. vaginalis and A. tetradius), and strategies for how to manage it. The clinical presentation of a patient should be monitored closely for several days after Cesarean section and if endometritis is suspected, microbiological cultures are necessary to determine the cause of infection and implement an appropriate treatment. Full article
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13 pages, 1368 KiB  
Article
Predictive Tool for Tunnelled Central Venous Catheter Dysfunction in Haemodialysis
by Verónica Gimeno-Hernán, Jose Antonio Herrero Calvo, Juan Vicente Beneit Montesinos, David Hernán Gascueña, Irene Serrano García and Ismael Ortuño-Soriano
J. Clin. Med. 2025, 14(16), 5647; https://doi.org/10.3390/jcm14165647 - 9 Aug 2025
Viewed by 365
Abstract
Introduction: Tunnelled central venous catheters are increasingly used for vascular access in patients undergoing haemodialysis for chronic kidney disease. However, catheter dysfunction is a frequent and clinically relevant complication, impairing treatment efficacy and increasing morbidity. This study aimed to develop and internally validate [...] Read more.
Introduction: Tunnelled central venous catheters are increasingly used for vascular access in patients undergoing haemodialysis for chronic kidney disease. However, catheter dysfunction is a frequent and clinically relevant complication, impairing treatment efficacy and increasing morbidity. This study aimed to develop and internally validate predictive models for catheter dysfunction using routinely collected haemodialysis session data, with the goal of facilitating early detection and proactive clinical decision-making. Methods: We conducted a diagnostic, retrospective, cross-sectional, and analytical study based on 60,230 HD sessions recorded in 2021 across dialysis centres in Spain. A total of 743 patients with functioning catheter were included. Clinical, technical, and haemodynamic variables were analysed to identify those associated with catheter dysfunction in the subsequent session. Five logistic regression models were built; the dataset was split into training (two-thirds) and internal validation (one-third) cohorts. Model performance was evaluated using the area under the ROC curve (AUC) and the Hosmer–Lemeshow test. Results: Significant predictors included venous pressure, effective blood flow, catheter location, convective techniques, and line reversal. The bootstrapping model, selected for internal validation due to its parsimony and performance, achieved an AUC of 0.844 (95% CI: 0.824–0.863), with a sensitivity of 81.6% and a specificity of 70.9% at a 0.019 threshold. Conclusions: The bootstrapping-based predictive model is a valuable clinical tool for anticipating catheter dysfunction using routine haemodialysis data. Its implementation may enable earlier intervention, reduce reliance on reactive treatments, and enhance vascular access management in haemodialysis patients. Full article
(This article belongs to the Section Nephrology & Urology)
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18 pages, 922 KiB  
Article
Steady Quiet Asthma Without Biologics: One-Year Outcomes of Single-Inhaler Triple Therapy for Severe Asthma with Small Airway Dysfunction
by Vitaliano Nicola Quaranta, Francesca Montagnolo, Andrea Portacci, Silvano Dragonieri, Maria Granito, Gennaro Rociola, Santina Ferrulli, Leonardo Maselli and Giovanna Elisiana Carpagnano
J. Clin. Med. 2025, 14(15), 5602; https://doi.org/10.3390/jcm14155602 - 7 Aug 2025
Viewed by 367
Abstract
Background: Small airway dysfunction (SAD) plays a critical role in the management of severe asthma, particularly in patients at risk of requiring biological therapies (BTs). Short-term studies have shown that switching to single-inhaler triple therapy (SITT) with extrafine beclomethasone–formoterol–glycopyrronium improves outcomes and helps [...] Read more.
Background: Small airway dysfunction (SAD) plays a critical role in the management of severe asthma, particularly in patients at risk of requiring biological therapies (BTs). Short-term studies have shown that switching to single-inhaler triple therapy (SITT) with extrafine beclomethasone–formoterol–glycopyrronium improves outcomes and helps achieve quiet asthma, a state marked by symptom control, no exacerbations or oral steroids, reduced inflammation, and better small airway function. This study investigated whether, over one year, patients could maintain this state as Steady Quiet Asthma (SQA) and whether baseline measures could predict this sustained response. Methods: Twenty-six patients with severe asthma and SAD were transitioned from open triple-inhaler therapy to a closed, single-inhaler triple therapy containing extrafine beclomethasone–formoterol–glycopyrronium. Assessments at baseline (T0) and at one-year follow-up (T12) included clinical evaluations, spirometry, and impulse oscillometry, with a focus on Fres as a predictor for the need for BT. When prescribed, biologic therapies included mepolizumab, benralizumab, and dupilumab. Results: Of the 26 patients, 9 (34.6%) achieved SQA and did not require biologic therapy at the one-year follow-up, while 17 patients (65.4%) initiated biologic treatment. At T0, patients who required biologics had significantly higher median Fres (21 (19.47; 24.58) vs. 17.61 (15.82; 20.63); p = 0.049) compared to those who remained biologic-free. They also exhibited higher residual volume to total lung capacity ratio (%RV/TLC) values and lower forced expiratory volume in one second/forced vital capacity ratios (FEV1/FVC). At T12, patients spared from BT showed significant reductions in Fres (p = 0.014) and improvements in small airway function (difference in airway resistance between 5 Hz and 20 Hz (R5–20), forced expiratory flow between 25% and 75% of FVC (%FEF25–75), and better asthma control (ACT). In contrast, patients on BT demonstrated less favorable changes in these parameters. Conclusions: Baseline Fres, FEV1/FVC ratio, and %FEV25–75 are valuable predictors of achieving Steady Quiet Asthma (SQA) and sparing biologic therapy. These findings support the use of SITT in severe asthma and highlight the importance of early functional assessments to guide personalized management. Full article
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12 pages, 856 KiB  
Article
Impact of Sex on Lung Function in Adult Langerhans Cell Histiocytosis
by Antonio Fabozzi, Gianluca Paciucci, Giulia de Rose, Roberto Romiti, Giovanna Palumbo, Gregorino Paone, Matteo Bonini and Paolo Palange
Life 2025, 15(8), 1258; https://doi.org/10.3390/life15081258 - 7 Aug 2025
Viewed by 704
Abstract
Background: Langerhans Cell Histiocytosis (LCH) is a rare histiocytic hematological disorder that frequently involves the lungs. Due to a lack of data about sex-related differences in LCH, the aim of this study is to evaluate sex-related differences in pulmonary function in a cohort [...] Read more.
Background: Langerhans Cell Histiocytosis (LCH) is a rare histiocytic hematological disorder that frequently involves the lungs. Due to a lack of data about sex-related differences in LCH, the aim of this study is to evaluate sex-related differences in pulmonary function in a cohort of patients with LCH. Methods: We retrospectively analyzed data from 79 adult patients diagnosed with LCH. Demographic, clinical, and spirometric data were collected and compared by sex. Continuous variables were analyzed using the Mann–Whitney test and categorical variables were analyzed with the Chi-square test. Results: Out of 79 patients, 47 (59.5%) were females and 32 (40.5%) were males. Women showed significantly lower diffusing capacity of the lungs for carbon monoxide (DLCO%) and lower diffusing capacity of the lungs for carbon monoxide per unit of alveolar volume (DLCO/VA%) compared to men. Females showed a trend toward lower small airway indices, including maximal expiratory flow at 25 (MEF25%) and forced expiratory flow at 25–75% (FEF25–75%), though this was not statistically significant, while the residual volume-to-total lung capacity (RV/TLC) ratio was significantly higher in women. Among the functional parameters, DLCO% showed the highest accuracy (AUC 0.70) in the identification of lung involvement after multivariate regression analysis. Conclusions: Our findings suggest that the combination of lower gas exchange efficiency and increased peripheral air trapping secondary to small airway involvement in female patients may reflect the presence of a distinct functional LCH phenotype in women characterized by early small airway involvement and altered ventilation–perfusion dynamics, which may influence the clinical management of these patients. Furthermore, the moderate predictive value of DLCO% for lung involvement at baseline in LCH women suggests that DLCO may contribute to the detection of LCH women with lung involvement, although it should not be considered a definitive diagnostic test without a prospective and independent external validation. Full article
(This article belongs to the Section Medical Research)
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21 pages, 8772 KiB  
Article
Assessing Hydropower Impacts on Flood and Drought Hazards in the Lancang–Mekong River Using CNN-LSTM Machine Learning
by Muzi Zhang, Boying Chi, Hongbin Gu, Jian Zhou, Honggang Chen, Weiwei Wang, Yicheng Wang, Juanjuan Chen, Xueqian Yang and Xuan Zhang
Water 2025, 17(15), 2352; https://doi.org/10.3390/w17152352 - 7 Aug 2025
Viewed by 478
Abstract
The efficient and rational development of hydropower in the Lancang–Mekong River Basin can promote green energy transition, reduce carbon emissions, prevent and mitigate flood and drought disasters, and ensure the sustainable development of the entire basin. In this study, based on publicly available [...] Read more.
The efficient and rational development of hydropower in the Lancang–Mekong River Basin can promote green energy transition, reduce carbon emissions, prevent and mitigate flood and drought disasters, and ensure the sustainable development of the entire basin. In this study, based on publicly available hydrometeorological observation data and satellite remote sensing monitoring data from 2001 to 2020, a machine learning model of the Lancang–Mekong Basin was developed to reconstruct the basin’s hydrological processes, and identify the occurrence patterns and influencing mechanisms of water-related hazards. The results show that, against the background of climate change, the Lancang–Mekong Basin is affected by the increasing frequency and intensity of extreme precipitation events. In particular, Rx1day, Rx5day, R10mm, and R95p (extreme precipitation indicators determined by the World Meteorological Organization’s Expert Group on Climate Change Monitoring and Extreme Climate Events) in the northwestern part of the Mekong River Basin show upward trends, with the average maximum daily rainfall increasing by 1.8 mm/year and the total extreme precipitation increasing by 18 mm/year on average. The risks of flood and drought disasters will continue to rise. The flood peak period is mainly concentrated in August and September, with the annual maximum flood peak ranging from 5600 to 8500 m3/s. The Stung Treng Station exhibits longer drought duration, greater severity, and higher peak intensity than the Chiang Saen and Pakse Stations. At the Pakse Station, climate change and hydropower development have altered the non-drought proportion by −12.50% and +15.90%, respectively. For the Chiang Saen Station, the fragmentation degree of the drought index time series under the baseline, naturalized, and hydropower development scenarios is 0.901, 1.16, and 0.775, respectively. These results indicate that hydropower development has effectively reduced the frequency of rapid drought–flood transitions within the basin, thereby alleviating pressure on drought management efforts. The regulatory role of the cascade reservoirs in the Lancang River can mitigate risks posed by climate change, weaken adverse effects, reduce flood peak flows, alleviate hydrological droughts in the dry season, and decrease flash drought–flood transitions in the basin. The research findings can enable basin managers to proactively address climate change, develop science-based technical pathways for hydropower dispatch, and formulate adaptive disaster prevention and mitigation strategies. Full article
(This article belongs to the Section Water and Climate Change)
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25 pages, 4069 KiB  
Article
Forest Volume Estimation in Secondary Forests of the Southern Daxing’anling Mountains Using Multi-Source Remote Sensing and Machine Learning
by Penghao Ji, Wanlong Pang, Rong Su, Runhong Gao, Pengwu Zhao, Lidong Pang and Huaxia Yao
Forests 2025, 16(8), 1280; https://doi.org/10.3390/f16081280 - 5 Aug 2025
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Abstract
Forest volume is an important information for assessing the economic value and carbon sequestration capacity of forest resources and serves as a key indicator for energy flow and biodiversity. Although remote sensing technology is applied to estimate volume, optical remote sensing data have [...] Read more.
Forest volume is an important information for assessing the economic value and carbon sequestration capacity of forest resources and serves as a key indicator for energy flow and biodiversity. Although remote sensing technology is applied to estimate volume, optical remote sensing data have limitations in capturing forest vertical height information and may suffer from reflectance saturation. While LiDAR data can provide more detailed vertical structural information, they come with high processing costs and limited observation range. Therefore, improving the accuracy of volume estimation through multi-source data fusion has become a crucial challenge and research focus in the field of forest remote sensing. In this study, we integrated Sentinel-2 multispectral data, Resource-3 stereoscopic imagery, UAV-based LiDAR data, and field survey data to quantitatively estimate the forest volume in Saihanwula Nature Reserve, located in Inner Mongolia, China, on the southern part of Daxing’anling Mountains. The study evaluated the performance of multi-source remote sensing features by using recursive feature elimination (RFE) to select the most relevant factors and applied four machine learning models—multiple linear regression (MLR), k-nearest neighbors (kNN), random forest (RF), and gradient boosting regression tree (GBRT)—to develop volume estimation models. The evaluation metrics include the coefficient of determination (R2), root mean square error (RMSE), and relative root mean square error (rRMSE). The results show that (1) forest Canopy Height Model (CHM) data were strongly correlated with forest volume, helping to alleviate the reflectance saturation issues inherent in spectral texture data. The fusion of CHM and spectral data resulted in an improved volume estimation model with R2 = 0.75 and RMSE = 8.16 m3/hm2, highlighting the importance of integrating multi-source canopy height information for more accurate volume estimation. (2) Volume estimation accuracy varied across different tree species. For Betula platyphylla, we obtained R2 = 0.71 and RMSE = 6.96 m3/hm2; for Quercus mongolica, R2 = 0.74 and RMSE = 6.90 m3/hm2; and for Populus davidiana, R2 = 0.51 and RMSE = 9.29 m3/hm2. The total forest volume in the Saihanwula Reserve ranges from 50 to 110 m3/hm2. (3) Among the four machine learning models, GBRT consistently outperformed others in all evaluation metrics, achieving the highest R2 of 0.86, lowest RMSE of 9.69 m3/hm2, and lowest rRMSE of 24.57%, suggesting its potential for forest biomass estimation. In conclusion, accurate estimation of forest volume is critical for evaluating forest management practices and timber resources. While this integrated approach shows promise, its operational application requires further external validation and uncertainty analysis to support policy-relevant decisions. The integration of multi-source remote sensing data provides valuable support for forest resource accounting, economic value assessment, and monitoring dynamic changes in forest ecosystems. Full article
(This article belongs to the Special Issue Mapping and Modeling Forests Using Geospatial Technologies)
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