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Self-harm represents a significant mental health concern during adolescence and is associated with various psychological risk factors. The present exploratory probe examines the mediating role of perceived social support in the relationship between self-esteem and self-harm among adolescents. The sample consisted of 155 adolescents aged 13 to 18 years (M = 16.35, SD = 1.73). Self-esteem was measured using the Rosenberg Self-Esteem Scale (RSES), self-harm was assessed using a modified version of the Self-Harm Inventory (SHI), and perceived social support was measured using the Multidimensional Scale of Perceived Social Support (MSPSS). Data were analyzed using correlation analysis, linear regression, and mediation. More than half of the participants (53.5%) reported repeated engagement in self-harming behavior. Self-esteem was significantly negatively associated with self-harm (ρ = −0.508, p < 0.001) and explained approximately 22% of the variance in self-harm. Mediation analysis indicated that perceived social support partially mediated the relationship between self-esteem and self-harm. Lower self-esteem was associated with lower perceived social support, which in turn predicted higher levels of self-harm. The indirect effect was significant (B = −0.31, 95% BootCI (−0.63, −0.09)). These findings highlight the protective role of perceived social support and suggest that strengthening adolescents’ self-esteem and social support networks may contribute to the prevention of self-harm. Full article

(This article belongs to the Section Neuropsychology, Clinical Psychology, and Mental Health)

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26 pages, 4830 KB

Open AccessArticle

A Physically Aware Residual Learning Framework for Outdoor Localization in LoRaWAN Networks

by Askhat Bolatbek, Ömer Faruk Beyca, Batyrbek Zholamanov, Madiyar Nurgaliyev, Gulbakhar Dosymbetova, Dinara Almen, Ahmet Saymbetov, Botakoz Yertaikyzy, Sayat Orynbassar and Ainur Kapparova

Future Internet 2026, 18(4), 216; https://doi.org/10.3390/fi18040216 (registering DOI) - 18 Apr 2026

Abstract

The rapid growth of large-scale Internet of Things (IoT) deployments in urban environments requires accurate and energy-efficient localization methods for low-power wireless devices. In long-range wide-area networks (LoRaWAN), traditional GPS-based positioning is often impractical due to energy consumption constraints and signal propagation challenges in urban areas. This study proposes a hybrid localization system that integrates weighted centroid localization (WCL) with a machine learning (ML) regression model to improve outdoor positioning accuracy. The proposed approach first estimates approximate transmitter coordinates using a physically grounded WCL method based on received signal strength indicator (RSSI) measurements. These initial estimates are subsequently refined by ML models trained to learn nonlinear residual corrections. In addition to random partitioning, a spatial data splitting strategy is proposed and evaluated using a publicly available LoRaWAN dataset. The experimental results demonstrate that the hybrid WCL framework combined with a multilayer perceptron (MLP) significantly outperforms other ML models. The proposed method achieves a mean localization error of 160.47 m and a median error of 73.78 m. Compared to the baseline model, the integration of WCL reduces the mean localization error by approximately 29%, highlighting the effectiveness of incorporating physically interpretable priors into localization models. Full article

(This article belongs to the Section Internet of Things)

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14 pages, 977 KB

Open AccessArticle

Comparative Evaluation of Time-Dependent Enamel Demineralization Using Micro-Computed Tomography, Laser Fluorescence, and Colorimetric Image Analysis

by Mirela Marinova-Takorova, Krasimir Hristov, Natalia Grancharova, Emilia Karova, Violeta Dogandzhiyska, Maria Kirilova, Irina Tsenova-Ilieva, Zornitsa Mihaylova, Nadezhda Mitova and Dimitar Kosturkov

Appl. Sci. 2026, 16(8), 3954; https://doi.org/10.3390/app16083954 (registering DOI) - 18 Apr 2026

Abstract

Background: Early detection and monitoring of enamel changes during caries lesion formation are essential for preventive management. This study aimed to evaluate time-dependent enamel demineralization using micro-computed tomography (micro-CT) and to compare its diagnostic performance with laser fluorescence and digital colorimetric image analysis. Methods: Twelve sound human permanent teeth were subjected to a gel-based lactic acid demineralization for 14 days. Assessments were performed at baseline and after 3, 7, and 14 days. Enamel mineral density (MD) and demineralization depth (DD) were measured using micro-CT. Laser fluorescence was evaluated using DIAGNOdent, while colorimetric changes were analyzed through standardized digital imaging using the CIE Lab* system, including ΔE and Whiteness Index (WI). Statistical analysis included repeated measures ANOVA and Pearson correlation (p < 0.05). Results: A significant time-dependent progression of enamel demineralization was observed. Demineralization depth increased from 0.0828 mm (3 days) to 0.234 mm (14 days) (p < 0.001), while mineral density decreased significantly over time (p < 0.001). DIAGNOdent values showed significant increases after 7 and 14 days (p = 0.002). Colorimetric analysis revealed early detectable changes, with ΔE exceeding clinically perceptible thresholds as early as day 3. WI values increased progressively, indicating enhanced enamel opacity. A weak but significant negative correlation between MD and DD was found (p = 0.04). Conclusions: Enamel demineralization progresses in a time-dependent manner and can be effectively monitored using micro-CT, laser fluorescence, and colorimetric analysis. Digital colorimetric analysis may serve as a valuable adjunctive tool in caries diagnostics. Full article

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26 pages, 572 KB

Open AccessArticle

Financing Post-War Circular Reconstruction: Digital Tools and Investment Pathways for Ukraine’s Industrial Regions

by Tetiana Gorokhova and Žaneta Simanavičienė

J. Risk Financial Manag. 2026, 19(4), 293; https://doi.org/10.3390/jrfm19040293 (registering DOI) - 18 Apr 2026

Abstract

Ukraine’s reconstruction, estimated at $524 billion over the next decade, presents an unprecedented opportunity to embed circular economy principles into industrial rebuilding, but the financial architecture currently deployed for reconstruction is structurally blind to circular outcomes. This paper examines how digital tools and innovative financing mechanisms can channel investment toward circular industrial reconstruction in Ukraine, drawing on Germany’s National Circular Economy Strategy (NCES, adopted December 2024) as a reference model. A comparative institutional analysis combines a documentary review of Ukrainian reconstruction policy frameworks (Ukraine Plan 2024–2027, RDNA4, Ukraine Facility) and German NCES instruments with the construction of a financing−technology pathway typology. Five pathways are proposed: circular bond issuance with Digital Product Passport integration; blended finance with blockchain impact verification; EU Facility conditionality with AI-driven resource management; war risk insurance with circular construction standards; and SME digitalisation credit with circular economy competency building. Each pathway is assessed against five criteria: investment scale, risk mitigation, circular measurement, digital readiness, and institutional feasibility, and applied to four industrial corridors (Dnipro region, Zaporizhzhia region, Kharkiv region, and Donetsk region). The analysis reveals that no single pathway is sufficient; a layered strategy differentiating by region is required. Digital tools, particularly the Digital Product Passport and blockchain traceability, serve as partial substitutes for institutional trust in post-conflict settings, reducing information asymmetry between investors and project operators. The paper contributes a practically oriented framework at the under-theorised intersection of post-conflict reconstruction finance and circular economy scholarship. Full article

(This article belongs to the Special Issue Financing the Digital Circular Economy: Business Models, Risk, and Economic Perspectives in Industry 5.0)

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11 pages, 1332 KB

Open AccessArticle

Opportunities for Prismless Attenuated Total Reflection in Multiple Frequency Ranges

by David Levy and Robert E. Camley

Photonics 2026, 13(4), 391; https://doi.org/10.3390/photonics13040391 (registering DOI) - 18 Apr 2026

Abstract

Attenuated total reflection (ATR) has long relied on a familiar trio—prism, metal film, and substrate—to unlock insights into material properties. In this work, we demonstrate the possibility and limitations of a prismless ATR system that utilizes the relative permittivity of air in place of a prism, followed by a plasmonic test material, which is in turn followed by a novel material characterized by low real relative permittivity and near-zero imaginary relative permittivity. We show that such measurements are possible in the visible IR and UV frequency ranges. In addition, we illustrate the advantages of prismless ATR. Full article

26 pages, 4446 KB

Open AccessArticle

Validation of a Wearable Photoplethysmography-Based Sensor for Compensatory Reserve Measurement Monitoring in Simulated Human Hemorrhage

by Jose M. Gonzalez, Ryan Ortiz, Krysta-Lynn Amezcua, Carlos Bedolla, Sofia I. Hernandez Torres, Erik K. Weitzel, Vijay S. Gorantla, Weihua Li, Alexander J. Aranyosi, John A. Rogers, Roozbeh Ghaffari, Victor A. Convertino and Eric J. Snider

Sensors 2026, 26(8), 2513; https://doi.org/10.3390/s26082513 (registering DOI) - 18 Apr 2026

Abstract

Hemorrhagic shock remains a leading cause of preventable death in trauma, yet traditional vital signs may fail to reflect early blood loss before physiological compensatory mechanisms are no longer able to maintain hemodynamic stability. The Compensatory Reserve Measurement (CRM) algorithm offers early detection capability using physiological waveforms but requires testing with emerging wearable sensor technologies for operational deployment. This study tested the Epicore Epidermal Patch for Imperceptible Care (EPIC) wearable healthcare device (WHD) for CRM-based hemodynamic monitoring during progressive central hypovolemia induced by lower-body negative pressure (LBNP) to simulate hemorrhage. Twenty participants underwent progressive LBNP while photoplethysmography (PPG) signals were recorded from EPIC sensors placed at the clavicle and triceps alongside a clinical-grade finger pulse oximeter for reference. Signal quality, heart-rate accuracy, and CRM predictions were evaluated across multiple filtering approaches. The triceps placement achieved signal quality comparable to the pulse oximeter reference when Chebyshev Type II filtering was applied, as well as high heart-rate accuracy. CRM derived from the EPIC sensor placed at the triceps tracked compensatory trends during progressive hypovolemia, but prediction magnitudes were inaccurate compared to calculated CRM values. In contrast, the clavicle placement consistently performed poorly across all measurements, regardless of the signal-processing approach. These findings support the feasibility of soft, flexible wearable sensors for continuous hemorrhage monitoring at the triceps location in operational environments where traditional finger-based pulse oximetry is impractical. Full article

(This article belongs to the Special Issue Challenges and Future Trends in Biomedical Signal Processing)

33 pages, 4233 KB

Open AccessArticle

Visual Impact Assessment Index on Landscape Based on Grey Clustering and Shannon Entropy: A Case Study on a Mining Project

by Alexi Delgado, Anabella Minhuey, Carla Lino and Jhonattan Culqui

Land 2026, 15(4), 670; https://doi.org/10.3390/land15040670 (registering DOI) - 18 Apr 2026

Abstract

Landscape visual impact assessment is a key component of environmental impact studies, as it enables the identification and management of negative effects on the territory. Traditional methods are often subjective, rely on expert judgement, and consider limited criteria. To address these limitations, this study proposes a quantitative index based on the integration of grey clustering and Shannon entropy complemented with Geographic Information System (GIS). This approach allows classification under uncertainty and the objective weighting of indicators related to physiographic, biotic, and anthropic factors of visual quality, fragility, and accessibility. The methodology was applied to an open-pit mine in Peru. Results show that terrain modifications, presence of artificial elements, and the alteration of water bodies significantly affect visual quality, while the absence of restoration measures, observer exposure, and vegetation type increase fragility and reduce landscape resilience. The proposed method provides a robust, transparent, and reproducible framework that overcomes subjectivity in traditional approaches, supporting more reliable environmental planning and management. Full article

(This article belongs to the Section Land Use, Impact Assessment and Sustainability)

26 pages, 16144 KB

Open AccessArticle

Temperature Determination and Scene Change Artifact Mitigation When Using Fourier-Transform Spectroscopy on Targets with Time-Varying Temperature

by Kody A. Wilson, Michael L. Dexter, Benjamin F. Akers and Anthony L. Franz

Sensors 2026, 26(8), 2512; https://doi.org/10.3390/s26082512 (registering DOI) - 18 Apr 2026

Abstract

Fourier-transform spectroscopy is a widely used technique for determining the spectral and thermal properties of a target. However, target temperature variations during measurement can compromise the spectral accuracy. Temperature fluctuations induce oscillations superimposed on the target spectrum. These oscillations, referred to as scene-change artifacts, degrade the spectral accuracy. The literature is divided, with theoretical predictions suggesting negligible artifacts and growing experimental evidence reporting significant artifacts. This paper presents a theory and experimental validation of scene-change artifacts originating from target temperature variations. Traditionally, the interferogram offset is assumed to be constant, an invalid assumption for a changing scene. The error is subsequently Fourier-transformed, producing scene-change artifacts. Accurately estimating the truth spectrum is often challenging. To address this, we propose the signal-to-scene-change-artifact ratio, a metric that quantifies the impact of scene-change artifacts without knowledge of the truth spectrum. The artifacts will be eliminated by estimating the interferogram offset using smooth offset correction. Furthermore, the interferogram offset enables determination of the target’s temperature with a greater accuracy and an increased temporal resolution compared to using the spectra. These results will demonstrate that a smooth offset correction can improve the spectrum and temperature accuracy on thermally variant targets when measured with a Fourier-transform spectrometer. Full article

(This article belongs to the Section Sensing and Imaging)

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17 pages, 563 KB

Open AccessArticle

Associations Between Anthropometric Variables, Maturation, Physical Activity and Jumping Performance in Adolescents: A Sex-Specific Analysis

by Victoria López-Lombó, Adrián Mateo-Orcajada, J. Arturo Abraldes, Lucía Abenza-Cano and Raquel Vaquero-Cristóbal

Appl. Sci. 2026, 16(8), 3953; https://doi.org/10.3390/app16083953 (registering DOI) - 18 Apr 2026

Abstract

Lower-limb strength is a health and performance indicator in adolescents, although its assessment often fails to account for the influence of sex and biological development. This study aimed to analyze the associations between anthropometric parameters, maturational status, and physical activity levels with jumping performance in adolescents. A cross-sectional study was conducted with male and female adolescents (mean age: 13.60 ± 1.50 years). Anthropometric variables, maturational status, and physical activity levels were assessed. Performance was measured using the Countermovement Jump (CMJ) and Standing Broad Jump (SBJ). In males, jumping performance was significantly associated with height (p = 0.002), lower-limb length (p < 0.001), and muscle mass (p < 0.001). However, fat mass emerged as a substantial factor, exhibiting a large effect size on performance (p < 0.001). Maturational status in males showed significant differences, with late maturers performing lower than on-time and early maturers (p < 0.023). In females, structural anthropometry and maturation showed limited-to-no significant associations with performance, except for a negative association with fat mass (p < 0.035) and a positive association between muscle mass and CMJ (p < 0.020). Active adolescents of both sexes performed significantly better than inactive ones in both CMJ and SBJ (p < 0.011). In conclusion, jumping performance in adolescents is characterized by marked sexual dimorphism. In males, greater height, lower-limb length, lower fat mass, and early maturation are positively associated with superior performance. Conversely, in females, these factors exhibit limited influence on jump outcomes. Full article

(This article belongs to the Special Issue Applied Biomechanics and Sports Sciences: 2nd Edition)

47 pages, 3797 KB

Open AccessReview

From Smart Green Ports to Blue Economy: A Review of Sustainable Maritime Infrastructure and Policy

by Setyo Budi Kurniawan, Mahasin Maulana Ahmad, Dwi Sasmita Aji Pambudi, Benedicta Dian Alfanda and Muhammad Fauzul Imron

Sustainability 2026, 18(8), 4038; https://doi.org/10.3390/su18084038 (registering DOI) - 18 Apr 2026

Abstract

Ports play a pivotal role in global trade but are also associated with significant environmental and social challenges. Despite growing research on green ports, existing studies remain fragmented, with limited integration between technological, environmental, and governance perspectives within the blue economy framework. This review examines the transition from green port initiatives toward integrated blue-economy-oriented port systems by synthesizing recent advances in sustainable maritime infrastructure, smart port technologies, renewable energy integration, and policy frameworks. The analysis reveals three major findings. First, ports are increasingly evolving into energy-integrated hubs, with leading examples adopting shore power systems, renewable energy microgrids, and hydrogen-based infrastructure, thereby contributing to emissions reductions. Second, digitalization through artificial intelligence, IoT, and data-driven logistics significantly enhances operational efficiency, reduces energy consumption, and improves real-time decision-making. Third, effective governance frameworks that combine regulatory measures and incentive-based instruments are critical to accelerating sustainability transitions while ensuring economic competitiveness. In addition, the review highlights the growing integration of biodiversity conservation, marine pollution mitigation, and community engagement into port management strategies, reflecting a shift toward ecosystem-based approaches. Overall, the findings demonstrate that ports are transitioning from conventional logistics hubs into integrated socio-technical systems that enable low-carbon maritime transport while supporting inclusive and resilient coastal development. Full article

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