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To address the stringent insulation safety requirements of modern high-voltage transformers, accurately characterizing the transient electric field is critical. However, a significant problem remains: current engineering models typically rely on static capacitive distributions, failing to capture the dynamic electric field distortion induced by rapid space charge injection under lightning impulses. Therefore, a non-contact spatial electric field measurement method based on the optical Kerr effect was employed to analyze the influence of electrode material, voltage amplitude, and wavefront time. Unlike traditional simulation models that often assume constant mobility and focus solely on the shielding effect, this study reveals a non-monotonic electric field evolution driven by a ‘Static-Dynamic’ mode transition. The proposed model highlights two critical breakthroughs: (1) Mechanism Innovation: It experimentally verifies that charge injection is governed by the ion charge-to-mass ratio rather than just the work function, leading to a newly identified field enhancement phase during the wavefront that overcomes the limitations of capacitive models that underestimate transient stress. (2) Parameter Quantification: Precise spatiotemporal thresholds are established—negative charges traverse the gap within ~200 ns, while positive charges require ~10 μs to reach equilibrium. These findings provide experimentally calibrated time constants for simulation correction and offer new criteria for optimizing electrode materials in UHV transformers to mitigate transient field distortion. Full article

(This article belongs to the Section Materials Processes)

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20 pages, 9638 KB

Open AccessArticle

Microclimate Behaviour Inside Archival Boxes, Books, and Paper Stacks: Buffering, Ventilation, and Pollutant Dynamics

by Morten Ryhl-Svendsen

Heritage 2026, 9(2), 63; https://doi.org/10.3390/heritage9020063 - 4 Feb 2026

Abstract

Paper-based heritage objects are commonly stored in archival boxes, books, and paper stacks, creating confined microclimates that may differ from the surrounding environment. While room-level climate control is central to preventive conservation, object-level conditions are shaped by enclosure permeability, hygroscopic buffering, ventilation, and internal emissions. This study investigates temperature, relative humidity, air exchange, and gaseous pollutants inside archival boxes, bound books, and paper stacks under laboratory and real storage conditions. Air exchange rates were determined using CO₂ tracer decay, while climates were monitored over periods from hours to one year. Chemical conditions were assessed using passive sampling of air pollutants, oxygen measurements, and dosimetric methods. The results show that boxes, books, and paper stacks behave as semi-permeable rather than sealed systems. Hygroscopic buffering attenuated short-term RH fluctuations, especially within books and paper stacks, while long-term internal conditions followed ambient trends with pronounced time lags. Restricted ventilation limited the ingress of external pollutants but could allow for internally generated gases to accumulate. Experiments using acid-sensitive indicator paper demonstrated the slow penetration of acetic acid into paper stacks. Overall, enclosure performance reflected a balance between buffering capacity, permeability, and chemical reactivity rather than airtightness alone, highlighting the importance of object-level microclimate assessment in preventive conservation. Full article

(This article belongs to the Special Issue Microclimate in Heritage)

20 pages, 696 KB

Open AccessSystematic Review

The Role of User-Generated Content in Social Commerce: A Systematic Review

by Sara Kostić, Jelena Spajić, Đorđe Alavuk, Iva Šiđanin, Branka Laličić and Sonja Bunčić

Sustainability 2026, 18(3), 1601; https://doi.org/10.3390/su18031601 - 4 Feb 2026

Abstract

User-generated content (UGC) plays a central role in social commerce. However, existing knowledge remains theoretically fragmented across constructs, perspectives, and empirical contexts. To address this gap, this study conducts a systematic review of 60 peer-reviewed studies published between 2014 and 2024, following PRISMA 2020 guidelines. It develops an integrative conceptual perspective structured around five key dimensions: trust, authenticity, perceived risk, engagement, and loyalty. The findings demonstrate that UGC influences consumer decision-making primarily through mediating psychological and social mechanisms, including trust, satisfaction, perceived value, social presence, and community identification. At the same time, perceived risk remains insufficiently theorized, and comprehensive multi-dimensional models remain scarce in the literature. The study advances social commerce theory by consolidating fragmented evidence into a coherent conceptual framework. It also explicitly foregrounds the central explanatory role of mediating mechanisms in UGC effects. From a practical perspective, the findings highlight the strategic importance of fostering authentic and trustworthy UGC. This supports sustainable consumer–brand relationships and long-term value creation within digital platform ecosystems. The review has limitations related to database coverage and language restrictions, which may have led to the omission of relevant studies. Full article

(This article belongs to the Special Issue Advancing Management Practices Through Digital Marketing and Sustainable Innovation)

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18 pages, 540 KB

Open AccessArticle

Enhancing Vehicle IoT Security with PQC: A Lightweight Approach for Encrypted Sensor Data Transmission

by Jackson Diaz-Gorrin and Candido Caballero-Gil

Electronics 2026, 15(3), 684; https://doi.org/10.3390/electronics15030684 - 4 Feb 2026

Abstract

Cybersecurity threats are evolving constantly, and the arrival of quantum computing raises serious doubts about whether today’s cryptographic methods will hold up over time. This concern has motivated interest in algorithms designed to resist future attacks, with CRYSTALS-Kyber emerging as a practical candidate and forming the basis of an NIST post-quantum standard. This study focuses on protecting data exchanged between a vehicle sensor suite and cloud services over the Message Queuing Telemetry Transport protocol. Performance must remain acceptable; therefore, attention centers on lightweight and efficient execution while leveraging the board’s hardware capabilities to keep latency and resource usage low. Adding this layer of post-quantum encryption helps limit the exposure of critical telemetry and control data to sophisticated adversaries. It also aims to preserve integrity and confidentiality in vehicular communications as the Internet of Things becomes increasingly connected. This approach maintains a practical balance between forward-looking security and real-world deployability. Full article

(This article belongs to the Special Issue New Technologies in Applied Cryptography and Network Security)

19 pages, 609 KB

Open AccessArticle

African Grass Invasion Threatens Tropical Wetland Biodiversity: Experimental Evidence from Echinochloa pyramidalis Invasion in a Mexican Ramsar Site

by Hugo López Rosas and Patricia Moreno-Casasola

Grasses 2026, 5(1), 6; https://doi.org/10.3390/grasses5010006 - 4 Feb 2026

Abstract

African grasses deliberately introduced for cattle forage have become among the most destructive invaders of tropical wetlands globally, yet invasion mechanisms and management strategies remain poorly understood. We conducted field experiments examining competition dynamics between the invasive African grass Echinochloa pyramidalis and native wetland species in La Mancha, Mexico—a Ramsar site of international importance. Experiment 1 tested invasion potential within native Sagittaria lancifolia zones using four treatments: control, herbicide removal, E. pyramidalis transplant, and combined removal + transplant. Repeated-measures ANOVA showed significant treatment and time effects on invasion success, with vegetation removal facilitating invasion (relative importance value increasing from 0 to 149.4 ± 26.6 after 18 months) while transplants alone failed to establish (RIV < 7.0). Sagittaria maintained 35–48% biomass across treatments, demonstrating coexistence capacity. Experiment 2 examined natural invasion of the vegetation ecotone over 49 months. Mixed-effects models revealed that E. pyramidalis increased dominance in its zone (β = 9.98, z = 4.77, p < 0.001) but showed minimal expansion into the adjacent Sagittaria habitat, indicating propagule limitation rather than competitive exclusion as the invasion constraint. Sagittaria removal within E. pyramidalis zones significantly reduced invasion temporal increase (β = −6.44, z = −2.18, p = 0.030), suggesting biotic resistance. Results demonstrate that E. pyramidalis possesses invasion potential but requires disturbance to overcome establishment barriers. These findings support prevention-based management prioritizing disturbance limitation in intact wetlands and demonstrate that hydrological management maintaining permanent flooding (>30 cm depth) can effectively control established invasions by exploiting C4 photosynthetic limitations. Conservation implications for Mexican coastal wetlands—which lack legal protection equivalent to mangroves despite comparable ecosystem services—are discussed. These findings inform evidence-based management of African grass invasions in tropical wetlands worldwide. Full article

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16 pages, 1033 KB

Open AccessArticle

Harnessing Symmetry in Recurrence Plots: A Multi-Scale Detail Boosting Approach for Time Series Similarity Measurement

by Jiancheng Yin, Xuye Zhuang, Wentao Sui and Yunlong Sheng

Symmetry 2026, 18(2), 290; https://doi.org/10.3390/sym18020290 - 4 Feb 2026

Abstract

Time series similarity measurement is a fundamental task underpinning clustering, classification, and anomaly detection. Traditional approaches predominantly rely on one-dimensional data representations, which often fail to capture complex structural dependencies. To address this limitation, this paper proposes a novel similarity measurement framework based on two-dimensional image enhancement. The method initially transforms one-dimensional time series into recurrence plots (RPs), converting temporal dynamics into visually symmetric textures, enhancing the temporal information of the one-dimensional time series. To overcome the potential blurring of fine-grained information during transformation, multi-scale detail boosting (MSDB) is introduced to amplify the high-frequency components and textural details of the RP images. Subsequently, a pre-trained ResNet-18 network is utilized to extract deep visual features from the enhanced images, and the similarity is quantified using the Euclidean distance of these feature vectors. Extensive experiments on the UCR Time Series Classification Archive demonstrate that the proposed method effectively leverages image enhancement to reveal latent temporal patterns. This approach leverages the inherent symmetry properties embedded in recurrence plots. By enhancing the texture of these symmetrical structures, the proposed method provides a more robust and informative basis for similarity assessment. Full article

(This article belongs to the Section Mathematics)

14 pages, 935 KB

Open AccessArticle

Clinical Impact of Ultrafast Cranial MRI Implementation in Children Under Six Years of Age

by Rastislav Pjontek, Hani Ridwan, Benedikt Kremer, Michael Veldeman, Dimah Hasan, Martin Häusler, Martin Wiesmann, Hans Clusmann and Hussam Hamou

J. Clin. Med. 2026, 15(3), 1242; https://doi.org/10.3390/jcm15031242 - 4 Feb 2026

Abstract

Background: Young children requiring neurosurgical care frequently undergo repeated neuroimaging. Whereas CT involves exposure to ionizing radiation, conventional MRI is time-consuming and often necessitates sedation in non-cooperative children. To address these limitations, ultrafast cranial MRI (UF-MRI) based on T2-HASTE sequences was implemented at our institution in 2019 for selected indications. The aim of this study was to evaluate the real-world implementation of UF-MRI in children younger than six years of age. Methods: We retrospectively analyzed cranial MRI examinations consisting exclusively of ultrafast sequences performed between July 2019 and December 2024 in children younger than six years. Clinical settings, diagnostic adequacy, immediate consequences for patient management, and the impact on MRI and CT utilization were systematically assessed. Results: A total of 404 UF-MRI examinations were performed in 198 inpatients and outpatients (mean age: 2 years 2 months) without the need for dedicated anesthesia team support solely for imaging. Only one examination (0.2%) required same-day repetition after mild oral sedation. In 20 patients (5.0%), UF-MRI was supplemented by conventional MRI under anesthesia, most commonly for preoperative planning. Immediate clinical consequences included no change in management in 54.5% of examinations, early follow-up in 22.8%, shunt valve adjustment in 11.6%, neurosurgical intervention in 7.7%, and other measures in 5.0%. UF-MRI accounted for 24.5% of all cranial MRI examinations in this age group and was associated with a 41% reduction in CT utilization compared with the corresponding period prior to UF-MRI implementation. Conclusions: In routine clinical practice, UF-MRI provides rapid, clinically sufficient neuroimaging in young children without the need for sedation or exposure to ionizing radiation. Its implementation significantly streamlines imaging workflows, optimizes resources utilization, reduces the need for CT, and supports timely clinical decision-making, underscoring its value as a complementary imaging modality in pediatric neuroimaging. Full article

(This article belongs to the Special Issue Pediatric Neurosurgery: Clinical Advances in Diagnostics and Perioperative Management)

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22 pages, 11216 KB

Open AccessArticle

A Multi-Scale Remote Sensing Image Change Detection Network Based on Vision Foundation Model

by Shenbo Liu, Dongxue Zhao and Lijun Tang

Remote Sens. 2026, 18(3), 506; https://doi.org/10.3390/rs18030506 - 4 Feb 2026

Abstract

As a key technology in the intelligent interpretation of remote sensing, remote sensing image change detection aims to automatically identify surface changes from images of the same area acquired at different times. Although vision foundation models have demonstrated outstanding capabilities in image feature representation, their inherent patch-based processing and global attention mechanisms limit their effectiveness in perceiving multi-scale targets. To address this, we propose a multi-scale remote sensing image change detection network based on a vision foundation model, termed SAM-MSCD. This network integrates an efficient parameter fine-tuning strategy with a cross-temporal multi-scale feature fusion mechanism, significantly improving change perception accuracy in complex scenarios. Specifically, the Low-Rank Adaptation mechanism is adopted for parameter-efficient fine-tuning of the Segment Anything Model (SAM) image encoder, adapting it for the remote sensing change detection task. A bi-temporal feature interaction module(BIM) is designed to enhance the semantic alignment and the modeling of change relationships between feature maps from different time phases. Furthermore, a change feature enhancement module (CFEM) is proposed to fuse and highlight differential information from different levels, achieving precise capture of multi-scale changes. Comprehensive experimental results on four public remote sensing change detection datasets, namely LEVIR-CD, WHU-CD, NJDS, and MSRS-CD, demonstrate that SAM-MSCD surpasses current state-of-the-art (SOTA) methods on several key evaluation metrics, including the F1-score and Intersection over Union(IoU), indicating its broad prospects for practical application. Full article

(This article belongs to the Section AI Remote Sensing)

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21 pages, 4016 KB

Open AccessArticle

Coupling Mechanisms Between Vegetation Phenology and Gross Primary Productivity in Alpine Grasslands on the Southern Slope of the Qilian Mountains

by Fangyu Wang, Yi Zhang, Guangchao Cao, Meiliang Zhao and Yinggui Wang

Atmosphere 2026, 17(2), 169; https://doi.org/10.3390/atmos17020169 - 4 Feb 2026

Abstract

Understanding the coupling mechanisms between vegetation phenology and carbon productivity is essential for assessing ecosystem responses to climate change and guiding sustainable grassland management. This study focuses on stable alpine grasslands on the southern slope of the Qilian Mountains from 2001 to 2020, a climatically sensitive but relatively under-investigated transition zone on the northeastern Tibetan Plateau. We utilized MODIS NDVI time-series (MOD13Q1) and the latest PML V2 gross primary productivity (GPP) product at 500 m resolution to quantify changes in the start (SOS), end (EOS), and length (LOS) of the growing season. A pixel-wise linear regression approach was applied to evaluate the sensitivity of GPP to phenological metrics, explicitly characterizing how much GPP changes in response to unit shifts in SOS, EOS and LOS. Compared with previous studies that mainly described large-scale correlations between phenology and GPP or relied on coarser GPP products, this study provides a pixel-level, sensitivity-based assessment of phenology–carbon coupling in alpine grasslands using a long-term, phenology–GPP dataset tailored to the Qilian alpine region. The results revealed trends of earlier SOS, delayed EOS, and extended LOS, accompanied by a gradual increase in GPP. However, phenology–GPP coupling exhibited notable spatial heterogeneity. In mid- and low-altitude areas, extended growing seasons enhanced GPP, whereas high-altitude zones showed limited or even negative responses, likely due to climatic constraints such as cold stress and thermal–moisture mismatches. To better understand these spatial differences, we constructed a three-dimensional phenology–GPP sensitivity space and applied k-means clustering to delineate three ecological functional zones: (1) high carbon sink potential, (2) ecologically fragile regions, and (3) neutral buffers. This sensitivity-based functional zonation moves beyond traditional correlation analyses and provides a process-oriented and spatially explicit framework for ecosystem service assessment, carbon sink enhancement and adaptive land-use strategies in sensitive mountain environments. Full article

(This article belongs to the Special Issue Vegetation and Climate Relationships (3rd Edition))

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19 pages, 2701 KB

Open AccessReview

Urushiol-Based Antimicrobial Coatings for Lacquer Art Applications: A Review of Mechanisms, Durability, and Safety

by Kai Yao, Jie Tian and Peirong Huang

Coatings 2026, 16(2), 198; https://doi.org/10.3390/coatings16020198 - 4 Feb 2026

Abstract

This paper provides a systematic review of urushiol-based antibacterial coatings for lacquer art applications, focusing on three key dimensions: molecular mechanisms, durability, and safety. Natural lacquer films form a dense three-dimensional network through laccase-catalyzed oxidative cross-linking, endowing them with excellent mechanical properties and corrosion resistance, while the catechol structure in urushiol confers broad-spectrum antibacterial potential. The article elaborates on the synergistic antibacterial mechanisms of urushiol, including covalent reactions with bacterial proteins via quinone intermediates, induction of oxidative stress, and metal ion chelation. It also reveals the dynamic change pattern of coating antibacterial activity over time, characterized by “high initial efficiency- gradual mid-term decline—long-term stabilization,” a process influenced collectively by side-chain unsaturation, degree of curing, and environmental factors such as temperature, humidity, and light exposure. From an application perspective, this review examines modification approaches such as silver/titanium dioxide composite systems, structurally regulated sustained-release strategies, and anti-adhesion surface designs, while pointing out current limitations in artistic compatibility, long-term durability, and safety assessment. Particularly in scenarios involving food contact and cultural heritage preservation, migration risks from unreacted urushiol monomers and metal nanoparticles, as well as the inherent sensitization potential of urushiol, remain critical challenges for safe application. Accordingly, this paper proposes the establishment of a holistic research framework covering “material design–process control–performance evaluation” and advocates for the development of functional coating systems with low migration, high biocompatibility, and preserved aesthetic value. Such advances are essential to promote the sustainable development and safe application of urushiol-based antibacterial coatings in fields such as cultural heritage conservation, daily-use utensils, and high-end decorative arts. Full article

(This article belongs to the Special Issue Innovative Surface Treatments for Anti-Microbial and Anti-Fouling Performance)

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28 pages, 3301 KB

Open AccessArticle

Measuring the Spillover Effects from the Stock Market Volatility in Selected Major Economies to the Stock Market Volatility in the United Kingdom

by Minko Markovski, Salman Almutawa and Jayendira P. Sankar

J. Risk Financial Manag. 2026, 19(2), 117; https://doi.org/10.3390/jrfm19020117 - 4 Feb 2026

Abstract

This study investigates volatility spillovers from the stock markets of the United States, Germany, China, and Japan to the UK stock market using daily data from major benchmark indices (FTSE 100, S&P 500, DAX, Shanghai Composite, and Nikkei 225) and Brent crude oil prices. Using a novel two-stage bootstrap framework, we first model time-varying conditional volatilities with GARCH-family models and compare them with long-memory FIGARCH specifications to account for persistent volatility dynamics. These volatilities are then incorporated into a VAR-X model, treating Brent crude oil price volatility as an endogenous or exogenous variable in robustness checks. To overcome limitations of traditional VARs, bootstrap-corrected GIRFs are employed to trace dynamic, order-invariant impacts across key sub-periods: the global financial crisis, Brexit, COVID-19, and the Ukraine war. We also benchmark our results against the Diebold–Yilmaz connectedness index and conduct rigorous out-of-sample forecasting and Value-at-Risk backtesting. Results reveal heterogeneous spillovers: US and German shocks trigger strong, immediate, and persistent UK market volatility, reflecting deep integration; Chinese shocks are delayed and gradual, while Japanese shocks are muted or short-lived. Spillover intensity is time-varying, peaking during global crises. Our model outperforms standard benchmarks in out-of-sample volatility forecasting and risk management applications. The study offers critical insights for investors seeking international diversification and for policymakers aiming to manage systemic risk in an interconnected global financial system. Full article

(This article belongs to the Section Economics and Finance)

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36 pages, 1952 KB

Open AccessReview

Comparative Review of Reactive Power Estimation Techniques for Voltage Restoration

by Natanael Faleiro, Raul Monteiro, André Fonseca, Lina Negrete, Rogério Lima and Jakson Bonaldo

Energies 2026, 19(3), 826; https://doi.org/10.3390/en19030826 - 4 Feb 2026

Abstract

With the focus on the growing concern of voltage instability and its inherent risks connected to blackouts, this study addresses the importance of Volt/VAR control (VVC) in maintaining voltage stability, optimizing power factor, and reducing losses. As such, this scientific article presents a review of the methodologies used to estimate the quantity of reactive power required to restore voltage in power grids. Although reviews exist on classical methods, optimization, and machine learning, a study unifying these approaches is lacking. This gap hinders an integrated comparison of methodologies and constitutes the main motivation for this study in 2025. This absence of a consolidated and up-to-date review limits both academic progress and practical decision-making in modern power systems, especially as DER penetration accelerates. This research was conducted using the Scopus database through the selection of articles that address reactive power estimation methods. The results indicate that traditional numerical and optimization methods, although accurate, demonstrate high computational costs for real-time application. In contrast, techniques such as Deep Reinforcement Learning (DRL) and hybrid models show greater potential for dealing with uncertainties and dynamic topologies. The conclusion reached is that the solution for reactive power management lies in hybrid approaches, which combine machine learning with numerical methods, supported by an intelligent and robust data infrastructure. The comparative analysis shows that numerical methods offer high precision but are computationally expensive for real-time use; optimization techniques provide good robustness but depend on detailed models that are sensitive to system conditions; and machine learning-based approaches offer greater adaptability under uncertainty, although they require large datasets and careful training. Given these complementary limitations, hybrid approaches emerge as the most promising alternative, combining the reliability of classical methods with the flexibility of intelligent models, especially in smart grids with dynamic topologies and high penetration of Distributed Energy Resources (DERs). Full article

(This article belongs to the Section A1: Smart Grids and Microgrids)

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20 pages, 496 KB

Open AccessArticle

Can Brief Empathy Training Increase Sexual Harassment Bystander Intervention Intentions?

by Tristan Barta, Zachary E. Piper, Harshit Chaubey, Jessica Kiebler and Margaret S. Stockdale

Behav. Sci. 2026, 16(2), 227; https://doi.org/10.3390/bs16020227 - 4 Feb 2026

Abstract

Sexual harassment (SH) remains widespread in workplaces and academic settings. Traditional compliance-based training has shown limited success in preventing SH or motivating bystander intervention. This study developed and tested a brief online empathy training module that can be completed in under 30 min that aims to help participants better understand and support people who experience SH and increase their willingness to intervene. Two experiments were conducted with U.S. adults recruited from the CloudResearch Connect platform (Study 1: 122 men and 140 women; Study 2: 132 men, 112 women, 4, other gender) who were randomly assigned to complete the SH empathy module, another empathy training module (burglary empathy training), time management training, a standard SH training module, or a waitlist control condition. Measures assessed empathy, perspective taking, and bystander intervention intentions. In Study 1, empathy correlated with bystander intentions, but there were no significant group differences; women reported higher empathy and bystander intentions than men. In Study 2, participants who received SH empathy training demonstrated higher empathy and perspective taking than those in other groups, and empathy improvements were associated with greater willingness to intervene. Gender did not moderate these effects. Overall, findings suggest that integrating a short empathy module into SH prevention programs can enhance readiness to act as supportive bystanders. Future research should assess the longevity of these effects and whether they translate into real-world behavioral change. Full article

(This article belongs to the Special Issue The Impact of Workplace Harassment on Employee Well-Being)

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14 pages, 783 KB

Open AccessArticle

When Smoke Enters the City: Challenges for HVAC Filters in Resilient Buildings

by Tanya Shirman, Hediyeh Zamani and Sissi Liu

Urban Sci. 2026, 10(2), 99; https://doi.org/10.3390/urbansci10020099 - 4 Feb 2026

Abstract

Climate-driven increases in wildfire activity threaten urban air quality both through long-range smoke transport from rural fires and direct exposure as the wildland–urban interface expands. Filters installed in Heating Ventilation and Air Conditioning (HVAC) systems represent a critical first barrier for limiting indoor exposure to smoke-derived particulate matter. In this study, we evaluated the smoke filtration performance of more than seventeen commercially available HVAC filter media spanning efficiency ratings from 10 to 15 (Minimum Efficiency Reporting Value, MERV) using pine needle combustion aerosols as a wildfire smoke proxy, quantifying size-resolved filtration efficiency, pressure drop, and temporal performance changes. The results show that charged polymer media across all tested MERV classes exhibited pronounced and rapid losses in smoke removal efficiency under exposure, despite minimal changes in airflow resistance. In contrast, mechanical media demonstrated greater stability in filtration efficiency over time but experienced considerable increases in pressure drop. Scanning electron microscopy revealed distinct smoke deposition morphologies on filter fibers, providing insight into mechanisms underlying performance degradation. Collectively, these findings indicate that filtration performance under wildfire smoke conditions is not adequately captured by current standards based on inorganic test aerosols. The results underscore the importance of advancing filter material evaluation and developing smoke-relevant testing approaches to better support indoor air quality, energy-aware building operation, and urban resilience under climate-driven wildfire smoke exposure. Full article

(This article belongs to the Special Issue Building Resilience in Urban Areas: Exploring the Impact of Material Properties and Building Design)

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19 pages, 3475 KB

Open AccessArticle

Spectral Matching of Selected Earthquake Ground Motions for the Performance-Based Design of Seaports

by Aydın Mert

Infrastructures 2026, 11(2), 52; https://doi.org/10.3390/infrastructures11020052 - 4 Feb 2026

Abstract

This study investigates the selection and scaling of recorded strong ground motions in the time-domain spectral matching framework to realistically represent the seismic demands on the superstructure and secondary systems in the seismic design of complex facilities such as marine ports. The time-domain spectral matching method iteratively adjusts the original record in the time domain by adding wavelets with limited durations and specific period ranges to achieve compatibility with the specified target acceleration response spectrum. A site-specific probabilistic seismic hazard analysis (PSHA) was performed for a port facility in İskenderun Bay, an area affected by the 6 February 2023 earthquakes. Horizontal Ground-Motion Response Spectra (GMRS) were derived for different return periods. Based on the hazard deaggregation, recorded ground motions compatible with the seismotectonic context of the region and the site conditions were selected. These records were then processed using time-domain spectral matching (TDSM) to match their elastic response spectra with the target GMRS over specific period ranges. The method utilizes spectral matching in the time domain to improve the match with the target spectrum while preserving the phase information and non-stationary nature of the records. The results show that the mean spectral acceleration curves of the scaled records are highly consistent with the target GMRS over a wide range of periods and that near-fault pulse-like characteristics, when present, are reasonably preserved. These results confirm that time-domain spectral matching provides a reliable framework for the performance-based assessments of complex port infrastructures by achieving high compatibility with the target spectra while preserving the physical characteristics of the waveforms Full article

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