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Background: Breast cancer-related lymphedema (BCRL) is one of the most debilitating long-term morbidities after axillary lymph node dissection (ALND), severely impairing quality of life through reduced mobility, independence, and chronic burden, especially in older women. Axillary reverse mapping (ARM) aims to preserve upper extremity lymphatics while maintaining oncologic safety. Evidence in older adult populations with long-term follow-up remains limited. Methods: This retrospective cohort study included 138 female patients (median age 72.5 years) undergoing ALND for invasive breast cancer between January 2018 and January 2024. Patients were divided into ARM (n = 72) and non-ARM (n = 66) groups. BCRL was graded 0–3 according to adapted International Society of Lymphology (ISL) criteria (2013 consensus document). Assessments were performed preoperatively and at 3, 6, 12, 24, 36, 48, and 60 months using blinded circumference measurements and bioimpedance spectroscopy. Results: Baseline characteristics were comparable. Mean follow-up was 46.5 ± 8.8 months. Clinically relevant BCRL (Grades 2–3) was dramatically lower in the ARM group (18.1% vs. 60.6%, p < 0.0001), while subclinical changes (Grade 1) were similar (31.9% vs. 27.3%, p = 0.55). Kaplan–Meier analysis showed significantly better clinically relevant lymphedema-free survival with ARM (log-rank p = 0.00019), with curve separation after 30–40 months—indicating a sustained long-term benefit for quality of life in this frail population. Recurrence rates were comparable (8.3% vs. 10.6%, p = 0.776). Multivariable Cox regression confirmed ARM as an independent protective factor (adjusted HR 0.22, 95% CI 0.11–0.44, p < 0.0001). Conclusions: In older women with breast cancer, ARM significantly reduces clinically relevant lymphedema—a major determinant of long-term quality of life—without compromising oncologic safety. These findings support the routine consideration of ARM during ALND to preserve upper-extremity function, mobility, and independence in this vulnerable population, thereby balancing aggressive oncologic treatment with enhanced long-term quality of life and reduced treatment-related morbidity. Full article

(This article belongs to the Special Issue Quality of Life in Surgical Oncology Patients)

42 pages, 147170 KB

Open AccessReview

Applications of Deep Learning in UAV-Based Hyperspectral Remote Sensing: A Review

by Yue Zhao and Yanchao Zhang

Remote Sens. 2026, 18(8), 1131; https://doi.org/10.3390/rs18081131 - 10 Apr 2026

Abstract

Unmanned aerial vehicle (UAV)-based hyperspectral imaging (HSI) has been increasingly utilized for fine-scale surface characterization and quantitative retrieval due to its capability of capturing dense spectral information at ultra-high spatial resolution. However, UAV-HSI analysis remains challenging due to high dimensionality, noise and within-class variability, as well as limited cross-flight consistency under varying acquisition conditions. Deep learning (DL) has therefore attracted growing attention by enabling spectral-spatial representation learning and more robust inference under residual degradations and domain shifts. This review summarizes DL approaches for UAV-HSI analytics and organizes the literature along a complete workflow, from imaging principles, preprocessing, and correction to DL architectures, core tasks, and representative applications, to provide guidance for future research and applications. The reviewed papers demonstrate that DL exhibits great potential and a promising future in UAV-HSI analysis. Full article

(This article belongs to the Special Issue Recent Progress in Hyperspectral Remote Sensing Data Processing)

25 pages, 874 KB

Open AccessArticle

Deep Learning with Visualization-Based Worked Examples to Enhance Students’ Algebra Problem Solving Ability and Metacognitive Awareness

by Windia Hadi, Benny Hendriana, Widyah Noviana and Csaba Csíkos

Educ. Sci. 2026, 16(4), 608; https://doi.org/10.3390/educsci16040608 - 10 Apr 2026

Abstract

This study aims to examine the improvement of algebra problem-solving ability and metacognitive awareness among junior high school students through the use of visualization based on a deep learning approach. The research employed a quantitative method with a quasi-experimental design, specifically a pretest–posttest control group design. The population consisted of all students from public schools in Tangerang City, Indonesia. The sample comprised seventh-grade students studying algebra. A purposive sampling technique was used to determine the experimental and control groups, with a total sample size of 51 students. The instruments included an algebra problem-solving ability test consisting of nine essay questions and a metacognitive awareness questionnaire with 52 items. Data were collected using these two instruments, with a pretest administered before the intervention and a posttest administered afterward. Data analysis was conducted using a prerequisite test, continued with independent sample t-tests, nonparametric tests, ANCOVA, and multiple linear regression. The results based on statistics indicated a significant improvement in students’ algebra problem-solving ability with a large effect. Nevertheless, the absolute increase in problem-solving scores in the experimental group is very small (N-gain mean = 0.02). Additionally, metacognitive awareness was not found to be a significant predictor of problem-solving ability; instead, initial ability (pretest) emerged as the strongest predictor. Only understanding the problem has a moderate effect; planning strategies has a small effect, and otherwise there is no effect. In conclusion, the use of visualization-based worked examples with a deep learning approach has a statistically significant effect, but its impact on improving students’ abilities should be interpreted with caution. So the practical effects of the intervention are limited; however, metacognitive awareness is not the main predictor in algebra problem-solving ability. Full article

(This article belongs to the Special Issue Teacher Emotion, Pedagogical Agents and Psychological Well-Being: Implications for Student Development)

26 pages, 3869 KB

Open AccessArticle

Conceptual AI-Informed Institutional Learning Analytics: Extending the TAM to Strengthen Inclusive Digital Justice

by Soledad Zabala, José Javier Galán Hernández, Alberto Garcés Jiménez, José Manuel Gómez Pulido, Susana Ester Medina and María Belén Morales Cevallos

Appl. Sci. 2026, 16(8), 3737; https://doi.org/10.3390/app16083737 - 10 Apr 2026

Abstract

This study examines institutional processes in digital justice through a mixed conceptual approach that integrates bibliometric analysis and technology-adoption modeling, incorporating artificial intelligence (AI) as a projected component rather than an implemented system. A corpus of approximately 200 Scopus-indexed documents (2003–2024) was analyzed, identifying five dominant thematic clusters: advanced technologies, institutional justice, digital government, judicial information management, and digital criminal justice. The results reveal persistent gaps in the literature, particularly in rural and underserved communities, where connectivity barriers and the limited application of adoption models hinder inclusive digital transformation. As an institutional contribution, the study presents the conceptual design of the digital solution “Travel Permits—Accessible Justice”, developed under a Service-Oriented Architecture (SOA) and projected for future integration with AI-supported components to automate judicial authorizations through biometric validation, electronic signatures, and digital delivery. To evaluate its potential acceptance, the Technology Acceptance Model (TAM) is analytically adapted and extended to the community-based judicial context, framing institutional learning processes as a prospective form of learning analytics focused on user interaction, perceived usefulness, perceived ease of use, and behavioral intention. Taken together, the integration of bibliometric evidence with an extended TAM, along with the projected incorporation of AI-supported institutional learning processes, offers a coherent foundation for future studies on inclusive digital innovation in justice environments. Full article

(This article belongs to the Special Issue Artificial Intelligence (AI) in Educational Data Mining and Learning Analytics)

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18 pages, 444 KB

Open AccessArticle

Risk-Sensitive Performance Evaluation of Life Insurance Markets in EU and EEA Countries: A MPSI–CoCoSo Approach

by Neylan Kaya, Aslıhan Ersoy Bozcuk, Güler Ferhan Ünal Uyar, Münevver Sena Özden, Mustafa Terzioğlu, Burçin Tutcu and Hasan Talaş

Risks 2026, 14(4), 85; https://doi.org/10.3390/risks14040085 - 10 Apr 2026

Abstract

The life insurance sector plays a critical role in the financial stability of countries due to its long-term liability structure and strong interaction with the financial system. The aim of this study is to evaluate the performance of the life insurance sector in the EU and EEA countries using a multi-criteria decision-making (MCDM) approach. Eight performance criteria reflecting financial stability, profitability, growth, and risk were used in the study. Criterion weights were determined using the Modified Preference Selection Index (MPSI) method, an objective method free from subjective judgments, and the performance ranking of the countries was obtained using the Combined Compromise Solution (CoCoSo) method. The data used in the analysis were obtained from the insurance statistics database published by the European Insurance and Occupational Pensions Authority (EIOPA). The findings show that ROE is the most important indicator, and that Cyprus, Hungary, and Iceland exhibit a significant positive difference in the life insurance sector compared to other countries. This study provides a unique contribution to the limited literature on comparative analyses at the country level by examining the performance of the life insurance sector in EU and EEA countries using an objective weighting and integrated ranking approach. The study results reveal important findings for a comparative assessment of life insurance markets from the perspective of regulatory bodies, policymakers, and industry stakeholders. Based on cross-sectional data for 2024, the findings should be interpreted as a framework providing a country-level risk-sensitive performance comparison under varying conditions. Full article

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21 pages, 4215 KB

Open AccessSystematic Review

Inter-Rater Reliability of Subarachnoid Hemorrhage Radiological Grading Scales: A Systematic Review and Meta-Analysis

by Daria Dmitrievna Dolotova, Tatyana Alexandrovna Solominova, Natalia Alexeevna Polunina, Evgenia Romanovna Blagosklonova, Natalya Sergeevna Plyusova, Ganipa Ramazanovich Ramazanov, Rustam Shakhismailovich Muslimov, Maxim Vladimirovich Solominov and Andrey Vasilevich Gavrilov

J. Clin. Med. 2026, 15(8), 2899; https://doi.org/10.3390/jcm15082899 - 10 Apr 2026

Abstract

Background: Subarachnoid hemorrhage (SAH) has high mortality and disability rates. The timely and precise assessment of SAH severity is of critical importance in predicting life-threatening complications. Several CT-based radiological grading systems have been proposed, but a comprehensive meta-analysis of their inter-rater reliability (IRR) has not been conducted. Methods: This study followed the guidelines of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Two authors performed a systematic search of original articles in the PubMed database. Methodological quality of the studies was assessed using the Quality Appraisal of Reliability Studies (QAREL). Meta-analyses of Cohen’s kappa and intra-class correlation coefficient (ICC) were performed using R packages “metafor” and “meta”. Results: A systematic literature analysis was performed for twenty articles that met the inclusion criteria. The methodological quality was moderate in 14 of 20 studies; five studies were of low quality. Only eight articles were suitable for meta-analysis. Cohen’s kappa of the binarized Fisher scale was 0.85 (95% CI 0.70–0.93), though it was based on only two studies and 109 patients. The Hijdra scale had an ICC of 0.75 (95% CI 0.29–0.93). The original and modified Graeb scales proposed for the assessment of concomitant intra-ventricular hemorrhage demonstrated ICC of 0.83 (95% CI 0.59–0.94) and 0.93 (95% CI 0.84–0.97), respectively. For other scales, meta-analysis was not possible due to incomplete reporting or single evaluations. Conclusions: The current evidence on IRR of radiological grading scales for SAH is limited, emphasizing the need for further high-quality research to validate their reliability and clinical applicability. Full article

(This article belongs to the Special Issue Intracranial Aneurysms: Diagnostics and Current Treatment)

10 pages, 6900 KB

Open AccessProceeding Paper

A Data-Centric Approach to Urban Building Footprint Extraction Using Graph Neural Networks and Assessed OpenStreetMap Data

by Anouar Adel, Meziane Iftene and Mohammed El Amin Larabi

Eng. Proc. 2026, 124(1), 105; https://doi.org/10.3390/engproc2026124105 - 10 Apr 2026

Abstract

The accurate and timely identification of urban building footprints is critical for sustainable urban planning and disaster management. Traditional remote sensing methods for this task often face limitations in scalability, accuracy, and adaptability to complex urban morphologies. This paper addresses these challenges by developing and evaluating a novel data-centric framework that synergistically integrates Graph Neural Networks (GNNs) with zero-shot superpixel segmentation derived from the Segment Anything Model (SAM) applied to Sentinel-2 imagery. A cornerstone of our methodology is a rigorous assessment of OpenStreetMap (OSM) data, refined through temporal NDVI stability analysis to generate high-quality ground truth. We propose an optimized UrbanGraphSAGE model, enhanced with spectral data augmentation and trained using a robust loss function with label smoothing to mitigate label noise. In the complex urban landscape of Algiers, Algeria, our approach achieves a Test F1-Score of 0.7131, demonstrating highly competitive performance with standard pixel-based baselines like U-Net while offering significant topological and computational advantages. Specifically, our model operates with merely 19,585 parameters—orders of magnitude fewer than pixel-based CNNs. A rigorous Gold Standard evaluation against manually labeled imagery confirms the model’s high recall (0.8484) and reliability for automated urban monitoring. Full article

(This article belongs to the Proceedings of The 6th International Electronic Conference on Applied Sciences)

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48 pages, 10336 KB

Open AccessReview

Current Options and Future Perspectives for Conversion Coatings on Biodegradable Magnesium Alloys to Control the Biodegradation Rate and Biological Features

by Veronica Manescu (Paltanea), Aurora Antoniac, Julietta V. Rau, Olga N. Plakhotnaia, Marco Fosca, Gheorghe Paltanea, Gabriel Cristescu and Iulian Antoniac

Biomimetics 2026, 11(4), 265; https://doi.org/10.3390/biomimetics11040265 - 10 Apr 2026

Abstract

In the biodegradable metal class, Mg-based alloys are considered the most promising candidates for temporary implant manufacture. However, their high corrosion rate in physiological media is considered a main drawback for clinical translation. Conversion coatings address the limitations of Mg-based alloys and provide a strategy to control corrosion and improve surface biocompatibility. In this review paper, a detailed analysis of various conversion coating techniques, including ceramic conversion coatings based on metals, polymeric conversion coatings, bioactive conversion coatings, and hybrid conversion coatings, is performed. Attention is devoted to the corrosion process and parameters, as well as to the biological response in relation to bioactivity or biocompatibility. The main angiogenic and osteogenic signaling pathways are described based on the analyzed conversion coatings, and the evolution of the cellular response is estimated. Although significant progress has been made in the field, there are still challenges associated with synchronizing Mg alloy degradation with new bone formation and with precisely guiding cell signaling responses to achieve a desired biological response. An overall conclusion of the paper consists of the fact that conversion coatings are an important topic, as they can enhance the surface of Mg-based alloys, making them prone to clinical translation. Full article

(This article belongs to the Special Issue Biomimetic Coating Technologies and Biomaterials for Medical Applications)

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18 pages, 5945 KB

Open AccessArticle

Replica-Based Bidirectional Output Current Limiting for High-Reliability CMOS Class AB Stages

by Andreea Voicu, Cristian Stancu, Ovidiu-George Profirescu, Lidia Dobrescu, Dragoș Dobrescu and Gabriel Dima

Electronics 2026, 15(8), 1595; https://doi.org/10.3390/electronics15081595 - 10 Apr 2026

Abstract

This paper presents a compact output-stage current-limiting architecture intended for reliable overcurrent protection in CMOS analog and mixed-signal circuits. In modern integrated systems, the output stages of blocks such as operational amplifiers, drivers, buffers, and reference circuits may be exposed to overload conditions, low-impedance loads, or short circuits that can lead to excessive power dissipation and device degradation. The proposed architecture employs scaled replicas of the output transistors together with local negative feedback to sense the delivered load current and independently limit both sinking and sourcing currents. The circuit is demonstrated by integration into a two-stage folded-cascode operational amplifier with a class-AB output stage and evaluated through circuit-level simulations in 130 nm CMOS technology. The results confirm a well-defined current limit across the supply and temperature corners that are relevant to high-reliability applications, spanning 2 V and 5 V supplies and a temperature range from −55 °C to 175 °C. The proposed current-limiting scheme constrains both pull-down and pull-up currents to approximately 9–12 mA across the investigated operating domain. Monte Carlo analysis further shows bounded dispersion and symmetric single-mode distributions, indicating predictable operation under device mismatch. These results demonstrate that the proposed architecture provides a compact and scalable solution for deterministic current limiting in reliability-critical CMOS systems. Full article

(This article belongs to the Special Issue Analog/Mixed Signal Integrated Circuit Design)

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14 pages, 724 KB

Open AccessArticle

Vitamin D Status and Post-Extraction Bone Healing After Mandibular Third Molar Surgery

by Daniel Selahi, Marzena Dominiak, Cyprian Olchowy, Wojciech Niemczyk, Kamil Jurczyszyn and Jakub Hadzik

Appl. Sci. 2026, 16(8), 3735; https://doi.org/10.3390/app16083735 - 10 Apr 2026

Abstract

Vitamin D plays an important role in bone metabolism and may influence postoperative healing processes. This study evaluated the association between preoperative serum vitamin D levels and recovery after mandibular third molar extraction. This secondary exploratory analysis included 122 healthy patients undergoing surgical extraction of an impacted mandibular third molar, of whom 98 had complete datasets for clinical and radiographic evaluation. Postoperative outcomes included pain intensity, facial swelling, trismus, early soft tissue healing assessed with the Wachtel Early Healing Index, and bone regeneration evaluated four months after surgery using CBCT-based fractal dimension analysis. Serum vitamin D levels were not significantly associated with postoperative pain, trismus, or early soft tissue healing. A weak correlation was observed between lower vitamin D levels and greater swelling along the tragus–pogonion line on postoperative day 1 (ρ = −0.21, p = 0.035), with no significant associations at later time points. Fractal dimension analysis did not demonstrate significant differences between groups. Within the limitations of this secondary exploratory analysis, vitamin D levels showed limited and inconsistent associations with postoperative outcomes, and their clinical relevance remains uncertain. Full article

(This article belongs to the Section Applied Dentistry and Oral Sciences)

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30 pages, 939 KB

Open AccessArticle

AI-Driven Financial Solutions for Climate Resilience and Geopolitical Risk Mitigation in Low- and Middle-Income Countries

by Abdelrahman Mohamed Mohamed Saeed and Muhammad Ali

Economies 2026, 14(4), 134; https://doi.org/10.3390/economies14040134 - 10 Apr 2026

Abstract

Climate change disproportionately threatens low- and middle-income countries, yet integrated assessments combining socio-economic fragility with physical hazards remain limited. This study quantifies multi-dimensional climate vulnerability and derives optimized adaptation policies for six representative nations (Bangladesh, Colombia, Kenya, Morocco, Pakistan, Vietnam) by fusing socio-economic indicators with climate risk data (2000–2024). A computational framework integrating unsupervised learning, dimensionality reduction, and predictive modeling was employed. Principal Component Analysis synthesized eight indicators into a Compound Vulnerability Score (CVS), while K-Means and DBSCAN identified distinct vulnerability regimes. XGBoost quantified driver importance, and Graph Neural Networks captured systemic interconnections. XGBoost identified projected drought risk (31.2%), precipitation change (18.1%), and poverty headcount (14.3%) as primary drivers. Graph networks demonstrated significant risk amplification in African nations (Morocco SRS: 0.728–0.874; Kenya SRS: 0.504–0.641) versus damping in Asian countries. A Reinforcement Learning (RL) agent was trained using Deep Q-Networks with experience replay to optimize intervention portfolios under budget constraints. The RL policy achieved a 23% reduction in systemic risk compared to uniform allocation baselines, generating context-specific priorities: drought management for Morocco (score 50) and Pakistan (40); poverty alleviation for Kenya (40); coastal protection for Bangladesh (40); agricultural resilience for Vietnam (35); and institutional capacity building for Colombia (50). In conclusion, socio-economic fragility non-linearly amplifies climate hazards, with poverty and drought risk constituting critical vulnerability multipliers. The AI-driven framework demonstrates that targeted interventions in high-sensitivity systems maximize systemic risk reduction. This integrated approach provides a replicable, evidence-based foundation for strategic adaptation finance allocation in an increasingly uncertain climate future. Full article

(This article belongs to the Special Issue Energy Consumption, Financial Development and Economic Growth)

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16 pages, 832 KB

Open AccessArticle

Clinical Practice Patterns in the Physiotherapy Management of Tension-Type Headache Among Spanish Physiotherapists

by Ana Bravo-Vazquez, Elena De-La-Barrera-Aranda, Ernesto Anarte-Lazo, Cleofas Rodriguez-Blanco and Carlos Bernal-Utrera

J. Clin. Med. 2026, 15(8), 2896; https://doi.org/10.3390/jcm15082896 - 10 Apr 2026

Abstract

Background: Tension-type headache (TTH) is the most prevalent primary headache disorder worldwide and represents a major source of disability related to chronic pain. Despite its high prevalence, uncertainty remains regarding optimal conservative management strategies, and limited evidence is available on how physiotherapists apply existing recommendations in routine clinical practice. Objective: The objective was to explore physiotherapists’ perceptions, clinical experiences, and treatment strategies in the management of tension-type headache, with particular emphasis on commonly used interventions, clinical decision-making, and characteristics of physiotherapy care. Methods: A cross-sectional survey study was conducted using a self-administered online survey developed in accordance with the CHERRIES guidelines. One hundred Spanish physiotherapists with clinical experience in treating patients with TTH participated. Quantitative data were analyzed descriptively, while open-ended responses were examined using inductive thematic analysis following the framework proposed by Braun and Clarke. Results: Manual therapy was the most frequently reported intervention (96%), followed by therapeutic exercise (61%) and invasive techniques, primarily dry needling (48%). The suboccipital and upper cervical regions were consistently identified as primary therapeutic targets, reflecting a predominant craniocervical treatment focus. Most respondents reported individualized treatment plans, typically delivered in weekly sessions lasting 45–60 min, with expected clinical improvement within 4–6 weeks. Pain education strategies were reported infrequently. Considerable variability was observed in the selection and combination of therapeutic techniques. Conclusions: Physiotherapists managing tension-type headache commonly adopt a multimodal approach, largely centered on manual and tissue-focused interventions. Although many reported practices are aligned with current evidence, the substantial heterogeneity observed and the limited integration of biopsychosocial strategies highlight the need for consensus-based guidelines and further research addressing real-world clinical effectiveness. Full article

(This article belongs to the Special Issue Headache: Updates on the Assessment, Diagnosis and Treatment)

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25 pages, 2314 KB

Open AccessArticle

Optimization Design of Interfacial Integrity for Composite Plugging Barriers in Carbon Sequestration Wells

by Zhiheng Shen, Yumei Li, Xinrui Li, Haoyuan Zheng, Yan Xi and Liwei Yu

Processes 2026, 14(8), 1222; https://doi.org/10.3390/pr14081222 - 10 Apr 2026

Abstract

The cement plug-casing interface is critical for long-term wellbore integrity in well abandonment to prevent fluid channeling. However, traditional cement easily debonds under long-term in situ stress and fluid exposure, causing seal failure and safety risks. To address this issue and overcome the limitations of conventional cement, a three-dimensional finite element model was established based on stress-seepage coupling theory. A systematic comparative analysis of the interface debonding mechanisms for three materials—cement, resin, and alloy—and their different combination sequences was conducted. The entire process of interface damage was quantified. The effects of material combination, formation elastic modulus, and injection rate on sealing performance were analyzed. Results show that the stiffness gradient dominates the failure mode, and the “cement–resin–alloy” configuration best suppresses damage propagation, reducing failure height by about 30%. Additionally, interface integrity is sensitive to formation constraints and operational parameters: the interface failure height decreases as the formation elastic modulus increases, and increases as the injection rate rises. The findings of this study can provide a theoretical basis and engineering reference for the optimal design of composite plugging barriers in demanding operational conditions, such as those encountered in carbon sequestration wells. Full article

(This article belongs to the Special Issue Advances and Innovative Solutions in CCUS Engineering: Carbon Capture, Utilization, and Storage)

34 pages, 10976 KB

Open AccessArticle

Sensory Architecture in Relation to Quality of Life in Older Adults: An Evidence-Based Design Approach

by Jaqueline D. Ubillus and Emilio J. Medrano-Sanchez

Buildings 2026, 16(8), 1498; https://doi.org/10.3390/buildings16081498 - 10 Apr 2026

Abstract

The accelerated aging of the population in vulnerable urban contexts poses significant challenges for architecture, particularly with regard to the quality of life of older adults. Within this framework, the present study aimed to analyze the association between sensory architecture and the quality of life of older adults and to translate this empirical evidence into context-informed design criteria for the development of a comprehensive center for older adults. The study adopted a quantitative approach with a non-experimental, cross-sectional, and correlational design. A structured questionnaire on sensory architecture and quality of life was administered to family members and caregivers acting as proxy respondents, demonstrating high internal consistency (Cronbach’s

α > 0.90

). Given the ordinal nature of the data, inferential analysis was conducted using Spearman’s rho coefficient. Within the analyzed dataset, the results revealed a statistically significant and strong association between sensory architecture and the quality of life of older adults (

ρ

> 0.80). At the dimensional level, visual and tactile stimuli exhibited the highest associations, followed by the social relationships dimension, while therapeutic environments showed a moderate association, allowing the identification of an empirical hierarchy among the analyzed dimensions within this dataset. These findings support the interpretation of sensory architecture as a construct statistically associated with indicators of quality of life, from a non-causal perspective. Based on this hierarchy, the results were articulated into an evidence-based architectural structure, serving as analytical input to inform context-specific criteria for spatial organization, materiality, comfort, orientation, and social interaction derived from the observed statistical associations. The study contributes a methodological approach that systematically connects correlational quantitative findings with architectural design considerations, particularly in urban contexts characterized by limited specialized infrastructure. However, a key limitation is the use of proxy respondents (family members and caregivers), which should be considered when interpreting the results. Full article

(This article belongs to the Special Issue Multisensory Comfort and Human-Centered Design: The Impact of the Built Environment on Health and Well-Being)

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13 pages, 5353 KB

Open AccessArticle

Abiotic Factors Exert a Predominant Influence on the Annual Aboveground Biomass Dynamics of Chinese Abies Mill. Forests Relative to Biotic Factors

by Zichun Gao, Huayong Zhang and Yanan Wei

Forests 2026, 17(4), 466; https://doi.org/10.3390/f17040466 - 10 Apr 2026

Abstract

The mean annual change in aboveground biomass (ΔAGB) is a pivotal indicator for assessing forest carbon cycle dynamics. This study analyzed 791 independent Abies Mill. forest patches across China to elucidate their driving mechanisms by integrating abiotic, anthropogenic, and biotic factors. We employed a spatially explicit framework, including spatial error regression and structural equation modeling (SEM), to account for significant spatial autocorrelation (Moran’s I = 0.375, p < 0.001). Our results show that abiotic factors predominantly dictate ΔAGB, with soil fertility (pH and Total Nitrogen), elevation (DEM), and soil physical properties (Coarse Fragments and Thickness) explaining the majority of deterministic variance. This relatively low explanatory variance (marginal R² = 0.09) likely reflects the high environmental stochasticity inherent in alpine ecosystems. Specifically, soil fertility exerted the strongest positive influence (Std. Estimate = 0.33), while elevation and soil physical constraints were the primary limiting factors. Biotic factors (Stand Age, Height, and Tree Cover) played a subordinate role, contributing only a marginal 2% gain in explained variance (increasing marginal R² from 0.07 to 0.09). Path analysis revealed an “environmental filtering” hierarchy where abiotic factors shape stand structure, which in turn has limited impact on growth dynamics. These findings underscore that carbon management in alpine forests should prioritize habitat quality conservation over simple biotic structural manipulation. Full article

(This article belongs to the Special Issue Forest Vegetation Dynamics and Environmental Monitoring Using GIS and Remote Sensing)

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