MDPI - Publisher of Open Access Journals

19 pages, 3069 KB

Open AccessArticle

ZmPRN1 Negatively Regulates Salt Stress Tolerance by Modulating ROS Homeostasis in Maize (Zea mays L.)

by Lei Ma, Wenzong Li, Ke Zhang, Qingyun Zhang, Hua Xu, Baobao Wang, Lei Wang and Junjie Zou

Plants 2026, 15(10), 1585; https://doi.org/10.3390/plants15101585 (registering DOI) - 21 May 2026

Abstract

Soil salinization is a major abiotic stress limiting maize (Zea mays L.) growth and productivity worldwide. Recently, many genes involved in salt stress have been identified. However, the molecular mechanisms underlying salt tolerance in maize remain largely elusive. In this study, we [...] Read more.

Soil salinization is a major abiotic stress limiting maize (Zea mays L.) growth and productivity worldwide. Recently, many genes involved in salt stress have been identified. However, the molecular mechanisms underlying salt tolerance in maize remain largely elusive. In this study, we identified a member of the ZmPIRIN family genes, ZmPRN1, acting as a negative regulator in response to salt stress. The expression levels of ZmPRN1 were down-regulated under salt and H₂O₂ treatment. Subcellular localization analysis showed that ZmPRN1 is localized to the chloroplast. Under salt stress, the Zmprn1-Mu mutant exhibited higher survival rates and lower reactive oxygen species (ROS) accumulation compared to wild-type plants. Whereas, ZmPRN1 overexpression lines were more sensitive to salt stress, and had higher ROS levels and lower chlorophyll content than wild-type plants. Transcriptome analysis showed that the differentially expressed genes (DEGs) were mainly involved in the oxidation-reduction process. Furthermore, yeast-two hybrid and split-luciferase complementation assays revealed that ZmPRN1 can interact with the chloroplast NDH complex subunit NDF4, the RING-type E3 ubiquitin ligase RING371, and the auxin-responsive protein IAA27. Collectively, our findings demonstrated that ZmPRN1 negatively regulates salt tolerance in maize by modulating ROS homeostasis, providing a valuable genetic resource for breeding salt-tolerant maize varieties. Full article

(This article belongs to the Special Issue Functional Genomics and Molecular Breeding of Crops—3rd Edition)

22 pages, 773 KB

Open AccessArticle

Decoding the Generational Digital Divide: Profiles and Predictors of Grandparents’ Attitudes Toward Young Children’s Technology Use

by Wenwei Luo, Huihua He, Ilene R. Berson, Michael J. Berson and Zhiying Wang

Behav. Sci. 2026, 16(5), 832; https://doi.org/10.3390/bs16050832 (registering DOI) - 21 May 2026

Abstract

In today’s digital age, child-rearing presents unique challenges that extend across generations, impacting both parenting and grandparenting. This study investigated patterns of grandparents’ attitudes toward their grandchildren’s technology use and identified key predictors of these patterns. Utilizing latent profile analysis (LPA) with a [...] Read more.

In today’s digital age, child-rearing presents unique challenges that extend across generations, impacting both parenting and grandparenting. This study investigated patterns of grandparents’ attitudes toward their grandchildren’s technology use and identified key predictors of these patterns. Utilizing latent profile analysis (LPA) with a sample of 712 grandparents from Shanghai, China, the research identified four distinct attitudinal profiles: positively supportive, cautiously observant, low-involvement reserved, highly concerned and restrictive. Multinomial logistic regression analyses revealed that the age of the grandparent, sibling status, and the frequency of communication between grandparents and parents were significant predictors of profile membership. The findings indicate that grandparents’ attitudes toward their grandchildren’s technology use reflect a combination of acceptance and concern. This study underscores the need for further research and educational supports to help grandparents develop perspectives informed by an evidence base, thereby strengthening guidance strategies for young children’s digital engagement. Full article

(This article belongs to the Section Educational Psychology)

36 pages, 6416 KB

Open AccessArticle

Mixed Discrete–Continuous Constrained Optimization of Symmetric Multi-LiDAR Mount Configurations for Mapping Systems: A Physics-Based Simulation Study

by Raghad Hadi Hasan, Athraa Hashim Mohammed, Faten Mezher Radhi and Bashar Alsadik

Symmetry 2026, 18(5), 876; https://doi.org/10.3390/sym18050876 (registering DOI) - 21 May 2026

Abstract

The configuration of a multi-LiDAR system impacts coverage, redundancy, and observability in mobile mapping. In this study, a multi-LiDAR configuration is modeled as a constrained optimization problem that considers symmetry and clearance constraints. A physics-based simulation is applied to evaluate coverage, overlap, and [...] Read more.

The configuration of a multi-LiDAR system impacts coverage, redundancy, and observability in mobile mapping. In this study, a multi-LiDAR configuration is modeled as a constrained optimization problem that considers symmetry and clearance constraints. A physics-based simulation is applied to evaluate coverage, overlap, and angular diversity for spinning LiDARs such as the Ouster OS1-64 and the Velodyne VLP-16. Three methods of Bayesian Optimization (BO), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO) are used. In an indoor space, all methods find symmetric multi-sensor configurations that maximize coverage and redundancy. GA and PSO methods required thousands of evaluations, whereas BO demonstrated excellent efficiency by converging in fewer iterations. Validation using simulated, realistic trajectories and ground-truth environments shows that symmetric multi-LiDAR configuration increases surface completeness by 10–11% over single-sensor setups (up to 27% for OS1-64 and 42% for VLP-16). The results further show that bilateral symmetry is a practical mounting constraint and also a robust design principle that improves mapping completeness. Full article

(This article belongs to the Special Issue Asymmetric and Symmetric in Deep Computer Vision and Generative Modeling)

13 pages, 7012 KB

Open AccessBrief Report

Identification of Pathogenic Variants in CYP4F22, FLG, ALOX12B, and NIPAL4 in a Case Series of Inherited Ichthyosis

by Malali Abdul Sattar, Amna Aurang Zaib, Huda Abbasi, Mirza Zain Ul Abideen, Saima Riazuddin, Zubair M. Ahmed and Muhammad Naeem

Int. J. Mol. Sci. 2026, 27(10), 4639; https://doi.org/10.3390/ijms27104639 (registering DOI) - 21 May 2026

Abstract

Inherited ichthyoses are clinically and genetically heterogeneous disorders of cornification caused by disruption of epidermal barrier genes involved in keratinization and lipid homeostasis. Pathogenic variants in more than 50 genes have been implicated in nonsyndromic ichthyosis vulgaris (IV) and autosomal recessive congenital ichthyosis [...] Read more.

Inherited ichthyoses are clinically and genetically heterogeneous disorders of cornification caused by disruption of epidermal barrier genes involved in keratinization and lipid homeostasis. Pathogenic variants in more than 50 genes have been implicated in nonsyndromic ichthyosis vulgaris (IV) and autosomal recessive congenital ichthyosis (ARCI). Here, we investigated the genetic basis of ichthyosis in four consanguineous Pakistani families presenting with IV or ARCI phenotypes. Exome sequencing followed by segregation analysis identified pathogenic variants in four established ichthyosis-associated genes: CYP4F22, FLG, ALOX12B, and NIPAL4. Identified variants include one novel nonsense allele of CYP4F22 (c.296G>A; p.Trp99*) and three known variants previously not reported in the Pakistani population. These known variants include a nonsense change in FLG, a frameshift allele of ALOX12B, and a missense variant in NIPAL4. Standardized phenotypic annotation using Human Phenotype Ontology terms revealed overlapping but variable clinical features across families, consistent with known genotype–phenotype heterogeneity in inherited ichthyosis. In silico protein modeling using AlphaFold2 and Ramachandran plot analysis predicted structural perturbations associated with the identified variants, supporting their pathogenic relevance. Publicly available scRNAseq datasets revealed greater heterogeneity of keratinocyte-associated expression patterns of these ichthyosis-associated genes in aging samples. Collectively, our findings expand the allelic and phenotypic spectrum of inherited ichthyosis in the Pakistani population and highlight the utility of comprehensive genetic analysis in consanguineous families for accurate molecular diagnosis, genetic counseling, and disease epidemiology. Full article

(This article belongs to the Special Issue 25th Anniversary of IJMS: Updates and Advances in Molecular Genetics and Genomics)

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25 pages, 2101 KB

Open AccessArticle

Whole Transcriptome Analysis of a Soybean Hybrid and Its Parents to Identify Genes Associated with Heterosis

by Nan Jiang, Chunjing Lin, Jingyong Zhang, Mingyu Wang, Zheyun Guan, Liang Wang, Songquan Wu and Chunbao Zhang

Agronomy 2026, 16(10), 1016; https://doi.org/10.3390/agronomy16101016 (registering DOI) - 21 May 2026

Abstract

Heterosis utilization is an effective strategy to improve crop yield, stress resistance, and quality, and has been widely used in crop breeding. Soybean is an important oil and protein crop worldwide with heterosis, but the genetic basis of soybean heterosis remains largely unclear. [...] Read more.

Heterosis utilization is an effective strategy to improve crop yield, stress resistance, and quality, and has been widely used in crop breeding. Soybean is an important oil and protein crop worldwide with heterosis, but the genetic basis of soybean heterosis remains largely unclear. Whole-transcriptome analysis provides a new technical approach to explore the molecular mechanism of heterosis. In this study, HYBSOY2, a registered soybean hybrid variety with the strongest heterosis in China, together with its female parent JLCMS47A, maintainer line JLCMS47B, and male parent JLR2, were used as experimental material. Whole-transcriptome sequencing was performed using RNA extracted from seedling leaves. After mapping high-quality reads to the soybean reference genome, 57 co-expressed differentially expressed genes (DEGs) were identified in HYBSOY2 compared with both JLCMS47B and JLR2. GO and KEGG enrichment analyses shows that these DEGs were mainly enriched in ADP binding, oxidoreductase activity, fatty acid elongation, and pyruvate metabolism. A total of 787 transcription factors were identified between HYBSOY2 and its parents, most of which shows parental expression-level dominance, with the MYB family accounting for the highest proportion. In addition, 10 differentially expressed lncRNAs were detected between HYBSOY2 and its parents. In the comparison between HYBSOY2 and JLCMS47B, 18 differentially expressed miRNAs were identified, among which up-regulated miR396d functions in promoting leaf development and enhancing drought tolerance. In the comparison between HYBSOY2 and JLR2, 20 differentially expressed miRNAs were found, including down-regulated miR172c which is involved in flowering promotion. A total of 12 DEGs were further verified by qRT-PCR, which may be closely related to soybean heterosis. This study provides a comprehensive transcriptomic profile at the seedling stage of the hybrid soybean and offers valuable information for hybrid soybean breeding. These results lay a foundation for further revealing the molecular mechanism underlying soybean heterosis. Full article

(This article belongs to the Special Issue Evaluation of Germplasm Resources, Molecular Breeding, and Utilization in Soybean)

17 pages, 10869 KB

Open AccessArticle

A Hierarchically Structured Composite Integrating a Biomass-Derived Magnetic Carbon Framework with Various Magnetic Phases, Exhibiting Outstanding Electromagnetic Wave Absorption Performance

by Yutao Zhang, Jiawei Bi, Tiancheng Yuan, Shenpeng Xia and Minzhen Bao

Molecules 2026, 31(10), 1775; https://doi.org/10.3390/molecules31101775 (registering DOI) - 21 May 2026

Abstract

A lightweight and high-efficiency microwave-absorbing material was developed via an in situ solvothermal pyrolysis strategy by anchoring sphere-like Fe₃O₄ nanostructures onto bamboo-derived porous carbon (BPC). The resulting composites preserve the intrinsic anisotropic honeycomb architecture of bamboo while introducing uniformly distributed [...] Read more.

A lightweight and high-efficiency microwave-absorbing material was developed via an in situ solvothermal pyrolysis strategy by anchoring sphere-like Fe₃O₄ nanostructures onto bamboo-derived porous carbon (BPC). The resulting composites preserve the intrinsic anisotropic honeycomb architecture of bamboo while introducing uniformly distributed magnetic nanoparticles, enabling synergistic dielectric–magnetic loss. Electromagnetic parameters, alongside impedance matching, were successfully modulated through the optimization of precursor concentrations. Of the evaluated materials, BPC-0.9 stood out for its intense attenuation, recording an RL_min of −45.17 dB at a 1.8 mm thickness. Furthermore, a significant effective absorption bandwidth of 6.65 GHz was attained by the BPC-0.6 sample at only 2.2 mm. Several factors contribute to the boosted efficiency, starting with conductive and interfacial polarization losses paired with multiple scattering events. Furthermore, magnetic loss components, encompassing eddy current effects as well as natural and exchange resonances, play a pivotal role in optimizing the material’s response. Furthermore, radar cross-section (RCS) modeling reveals a substantial reduction of 19.9 dB·m², verifying the material’s viability for real-world stealth technologies. Our findings offer a straightforward methodology for fabricating magnetic carbon structures from biomass with adjustable dielectric responses, underscoring their potential in high-performance energy conversion and low-density microwave absorption. Full article

(This article belongs to the Special Issue Emerging Multifunctional Materials for Next-Generation Energy Systems)

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19 pages, 16207 KB

Open AccessArticle

Isolation and Functional Characterization of a Gene Encoding Squalene Synthase from Amaranthus tricolor

by Yuanfeng Lv, Xiaoyang Lin, Zaifeng Du, Guihong Qi, Yinan Yang, Yufeng Luo and Hongbo Zhang

Agronomy 2026, 16(10), 1014; https://doi.org/10.3390/agronomy16101014 (registering DOI) - 21 May 2026

Abstract

Squalene, a high-value triterpenoid precursor widely used in pharmaceuticals and vaccine adjuvants, is primarily sourced from shark liver oil—an unsustainable practice that has driven interest in developing plant-based production alternatives. The first committed reaction in triterpenoid biosynthesis is catalyzed by squalene synthase (SQS), [...] Read more.

Squalene, a high-value triterpenoid precursor widely used in pharmaceuticals and vaccine adjuvants, is primarily sourced from shark liver oil—an unsustainable practice that has driven interest in developing plant-based production alternatives. The first committed reaction in triterpenoid biosynthesis is catalyzed by squalene synthase (SQS), yet no SQS gene has been characterized in Amaranthus tricolor, a species recognized for its high squalene content. Here, we cloned and functionally characterized AtrSQS, a novel squalene synthase gene isolated from A. tricolor for the first time. Sequence analysis revealed that AtrSQS contains conserved domains and six characteristic motifs shared among plant SQSs, with high homology to orthologs from dicotyledonous species. To investigate its functional role in squalene biosynthesis, AtrSQS was overexpressed in Nicotiana tabacum under the CaMV 35S promoter. Transgenic lines exhibited significantly increased AtrSQS expression and accumulated squalene up to 6.81 μg/g dry weight, a 4.76-fold increase over wild-type plants. Additionally, the content of downstream product 2,3-oxidosqualene was also significantly elevated in the transgenic lines. Integrated transcriptomic and metabolomic analyses revealed that AtrSQS overexpression upregulated key mevalonate pathway genes (AACT, HMGS, MVD) and FPPS. Meanwhile, it suppressed competitive carotenoid biosynthesis and the production of an SQS-specific inhibitor, indicating a successful redirection of metabolic flux toward squalene production. These findings demonstrate that AtrSQS is crucial for squalene biosynthesis and provide both a valuable genetic resource and mechanistic insights for engineering plant-based squalene production systems. Full article

(This article belongs to the Special Issue Progress and Innovations in Breeding Objectives and Technologies for Solanaceae Crops Production—2nd Edition)

22 pages, 591 KB

Open AccessArticle

Stakeholder Perspectives on Tourism Education Curriculum Alignment with Vision 2030: A Qualitative Study from Saudi Arabia

by Asma Alomaym, Rosniza Aznie Che Rose and Rosmiza Mohd Zainol

Tour. Hosp. 2026, 7(5), 145; https://doi.org/10.3390/tourhosp7050145 (registering DOI) - 21 May 2026

Abstract

Tourism education is central to human capital development under Saudi Arabia’s Vision 2030, yet the extent to which curricula align with emerging industry requirements remains underexplored, particularly in developing economy contexts. This qualitative study examines student and faculty perspectives on curriculum alignment at [...] Read more.

Tourism education is central to human capital development under Saudi Arabia’s Vision 2030, yet the extent to which curricula align with emerging industry requirements remains underexplored, particularly in developing economy contexts. This qualitative study examines student and faculty perspectives on curriculum alignment at the University of Ha’il’s Tourism and Antiquities Department. Twenty participants were purposively recruited and interviewed; data were analyzed using thematic analysis. Findings reveal four interconnected challenges: a persistent theory–practice gap sustained by lecture-based pedagogies, insufficient integration of digital and smart tourism technologies, weak industry–academia partnerships, and structural barriers to interdisciplinary collaboration. In response, this study proposes an interdisciplinary integration model structured around five domains: digital technology, sustainability and environment, business and entrepreneurship, cultural and creative industries, and social sciences and community engagement. The model provides a progressive framework for cross-departmental collaboration and represents the study’s primary practical contribution. Theoretically, the study demonstrates that curriculum misalignment operates through mutually reinforcing institutional constraints rather than discrete correctable deficits. Recommendations address curriculum reform, technology investment, structured partnership development, and administrative conditions enabling interdisciplinary implementation. Full article

20 pages, 4188 KB

Open AccessArticle

Preliminary Study on the Biocontrol Efficacy and Antimicrobial Mechanism of Pseudomonas eucalypticola NP-1 Against Gray Mold in Eucalyptus Seedlings

by Ying Lu, Menglan Shang, Zhe Li, Yongfeng Lu, Yu Long, Wangdong Xu and Qinghua Zhang

Forests 2026, 17(5), 624; https://doi.org/10.3390/f17050624 (registering DOI) - 21 May 2026

Abstract

Botrytis cinerea is a globally distributed phytopathogenic fungus that causes gray mold in eucalyptus seedlings, posing a severe threat to eucalyptus nursery production. Pseudomonas eucalypticola Liu et al. NP-1 is an endophytic bacterium isolated from eucalyptus with broad-spectrum antifungal activity. In this study, [...] Read more.

Botrytis cinerea is a globally distributed phytopathogenic fungus that causes gray mold in eucalyptus seedlings, posing a severe threat to eucalyptus nursery production. Pseudomonas eucalypticola Liu et al. NP-1 is an endophytic bacterium isolated from eucalyptus with broad-spectrum antifungal activity. In this study, the fermentation broth extract of strain NP-1 was prepared using the organic solvent extraction method. The inhibitory effects, antifungal mechanisms, and biocontrol efficacy of the extract against B. cinerea were investigated. The results suggested that the NP-1 extract effectively inhibited mycelial growth, conidial germination, and germ tube development of B. cinerea. The EC₅₀ and EC₉₀ values for mycelial inhibition were 110 μg/mL and 332 μg/mL, respectively, while those for conidial germination inhibition were 126 μg/mL and 310 μg/mL. Microscopic and ultramicroscopic observations indicated that while the mycelial structures in the control and EC₅₀ groups remained intact, the EC₉₀ treatment significantly was associated with protoplasmic aggregation, leakage, and cavitation, suggesting potential structural damage to the fungal cells. In vitro and in vivo biocontrol assays showed that the control efficacy against gray mold reached 90.0% on detached eucalyptus leaves and 93.3% on eucalyptus seedlings. These findings elucidate the biocontrol potential of NP-1 and lay a foundation for the development of bio-based pesticides. Full article

(This article belongs to the Section Forest Health)

19 pages, 311 KB

Open AccessArticle

Jordan Normal Forms of Endomorphisms of Vector Bundles over Curves and Applications to Moduli Space Automorphisms

by Álvaro Antón-Sancho

Axioms 2026, 15(5), 386; https://doi.org/10.3390/axioms15050386 (registering DOI) - 21 May 2026

Abstract

Let X be a compact connected Riemann surface of genus

g \geq 2

and let E be a holomorphic vector bundle of rank n over X. The compactness and connectedness of X imply that the characteristic polynomial of any holomorphic endomorphism [...] Read more.

Let X be a compact connected Riemann surface of genus

g \geq 2

and let E be a holomorphic vector bundle of rank n over X. The compactness and connectedness of X imply that the characteristic polynomial of any holomorphic endomorphism

φ \in H^{0} (X, E n d (E))

has constant coefficients, a fact we call the Principle of Spectral Constancy. As a consequence, the eigenvalues of

φ

are globally constant over X, the primary decomposition of E with respect to

φ

consists of globally defined holomorphic subbundles, and the Jordan decomposition

φ = φ_{s} + φ_{n}

into semisimple and nilpotent parts is globally well defined as a decomposition of sections of

E n d (E)

. This paper provides a systematic analysis of Jordan normal forms for endomorphisms of holomorphic vector bundles over X, relating the Jordan type of

φ

to the stability properties of E. In particular, it is proved that endomorphisms of stable bundles are necessarily scalar, that the Jordan decomposition of an endomorphism of a polystable bundle is determined componentwise by the classical Jordan normal forms of matrices in the associated endomorphism algebra, and that finite-order endomorphisms are always semisimple. These results are applied to the study of fixed points of automorphisms of the moduli space

B_{X} (SL (n, C))

of rank n and trivial determinant polystable vector bundles over X. Specifically, a new result establishes that the commutative subalgebra of

H^{0} (X, E n d (E))

generated by the endomorphism associated with a fixed-point condition is semisimple, so nilpotent endomorphisms of E are precisely those incompatible with the fixed-point structure. Full article

(This article belongs to the Special Issue Advances in Linear Algebra with Applications, 2nd Edition)

18 pages, 2698 KB

Open AccessArticle

Improvement Pathways for Irrigation Water Use Efficiency in Large and Medium-Sized Irrigation Districts Based on Analysis of Influencing Factors: A Machine Learning Case Study in Anhui, China

by Hu Zhang, Bin Xu, Shangming Jiang, Fengcun Yu and Shiwei Zhou

Sustainability 2026, 18(10), 5204; https://doi.org/10.3390/su18105204 (registering DOI) - 21 May 2026

Abstract

Irrigation water use efficiency (IWUE) is a core indicator for assessing agricultural water use efficiency. However, existing studies predominantly focus on linear relationships between IWUE and individual correlates, with insufficient attention to the nonlinear interactions among multiple factors and the staged pathways of [...] Read more.

Irrigation water use efficiency (IWUE) is a core indicator for assessing agricultural water use efficiency. However, existing studies predominantly focus on linear relationships between IWUE and individual correlates, with insufficient attention to the nonlinear interactions among multiple factors and the staged pathways of IWUE improvement. Taking 153 large- and medium-sized irrigation districts in Anhui Province as a case study, this research identifies seven key influencing factors—including canal lining rate (CLR), proportion of water-saving irrigation area (WSIR), and water price (WP)—and employs a random forest model coupled with SHAP (SHapley Additive exPlanations) interpretability analysis to uncover the driving mechanisms and enhancement pathways of IWUE. The results reveal that CLR, WSIR, and WP are the top three correlates, collectively contributing 67.80% to IWUE variation, with CLR being the most influential (28.75%). Their effects exhibit strong nonlinearity and threshold behavior: the marginal benefit of CLR diminishes significantly beyond approximately 75%; the optimal incentive range for WP lies between 0.09 and 0.14 CNY/m³; and precipitation exerts a persistent negative constraint. Moreover, IWUE improvement follows a sequential hierarchy: CLR serves as the foundational prerequisite; once CLR reaches a certain threshold, advancing WSIR becomes essential; and further gains require synergistic interaction between WSIR and WP after both attain sufficient levels. This study elucidates the nonlinear response mechanisms and stage-dependent driving patterns of IWUE, offering scientific insights and quantitative support for targeted, precision-oriented upgrades of irrigation infrastructure in Anhui Province and analogous humid/semi-humid regions, thereby contributing to sustainable agricultural water management. Full article

(This article belongs to the Special Issue Towards Sustainability: Applications of Machine Learning in Water Management and Environmental Monitoring)

22 pages, 9796 KB

Open AccessArticle

A Physics-Constrained Dual-Stream Dynamic Framework for Wind Power Forecasting Under Extreme Weather

by Yunzhi Hao and Jing Cao

Processes 2026, 14(10), 1671; https://doi.org/10.3390/pr14101671 (registering DOI) - 21 May 2026

Abstract

Accurate wind power forecasting is essential for ensuring power grid stability and facilitating the large-scale integration of renewable energy, yet it faces significant challenges due to the randomness, variability, and intermittency of wind resources and the increasing frequency of extreme weather events. Existing [...] Read more.

Accurate wind power forecasting is essential for ensuring power grid stability and facilitating the large-scale integration of renewable energy, yet it faces significant challenges due to the randomness, variability, and intermittency of wind resources and the increasing frequency of extreme weather events. Existing data-driven approaches often struggle to balance temporal continuity with meteorological sensitivity, leading to lag effects during rapid fluctuations, and frequently generate predictions that violate physical domain knowledge. To address these limitations, this paper proposes a dual-stream architecture to decouple temporal dependencies and spatial–meteorological mappings, utilizing a Physics-Informed GRU (PI-GRU) and an Enhanced Random Forest (ERF). Both streams are strictly bounded by physical constraints. Furthermore, a scenario-aware adaptive fusion mechanism is introduced to dynamically adjust the model’s reliance on each stream based on real-time wind speed gradients and volatility indices. Extensive experiments were conducted using a comprehensive dataset from three coastal wind farms over 8 months, encompassing stable regimes and extreme weather events. Evaluating across both 1-day and 4-day forecast horizons, the results demonstrate that our method significantly outperforms state-of-the-art baselines, proving its robustness and practical value for grid security and dispatch optimization. Full article

(This article belongs to the Special Issue Data-Based Prediction Models in Energy Systems: From Principles to Applications)

27 pages, 1780 KB

Open AccessArticle

Action-Oriented Programming and Automatic Agent Generation for Adaptive Data Collection in Decentralized Data Ecosystems

by Mustafa Tayyip Bayram, Houssam Razouk and Kyandoghere Kyamakya

Processes 2026, 14(10), 1669; https://doi.org/10.3390/pr14101669 (registering DOI) - 21 May 2026

Abstract

The semiconductor manufacturing industry depends on effective data collection and analysis for critical processes such as Root Cause Analysis (RCA) and Risk Assessment (RA). Both processes involve software-driven data collection and subsequent analysis by domain experts to support informed decision-making. However, the increasing [...] Read more.

The semiconductor manufacturing industry depends on effective data collection and analysis for critical processes such as Root Cause Analysis (RCA) and Risk Assessment (RA). Both processes involve software-driven data collection and subsequent analysis by domain experts to support informed decision-making. However, the increasing complexity, volume, and decentralized nature of manufacturing data pose significant challenges for effective data collection. Data is distributed across multiple systems with varying formats and ownership, making conventional programming paradigms and manual data collection scripts inadequate for handling this decentralized data landscape. To address these challenges, this study proposes integrating Action-Oriented Programming (AcOP) with Automatic Agent Generation (AAG) as a novel solution. AcOP emphasizes actions as fundamental execution units, separating system behavior and data. Complementing this, AAG uses large language models (LLMs) to autonomously generate intelligent agents, which manage these actions and perform preliminary data analysis with domain-specific knowledge. Our experimental setup compares three microservice applications supporting RCA and RA: Object-Oriented Programming (OOP), AcOP, and AcOP integrated with AAG. Evaluation results indicate that AcOP improves modularity, adaptability, and error handling in decentralized systems. Integrating AAG enhances automation, provides a flexible, low-maintenance solution for data collection and analysis pipelines, and promotes autonomous microservice architectures in data-intensive environments. Full article

(This article belongs to the Special Issue Artificial Intelligence-Based Analytics for Data-Driven Decision-Making in Industrial Process Engineering)

23 pages, 2981 KB

Open AccessArticle

Application of Dang Van Model Based on Critical Plane Approach for Rolling Contact Problems

by Paweł J. Romanowicz

Materials 2026, 19(10), 2173; https://doi.org/10.3390/ma19102173 (registering DOI) - 21 May 2026

Abstract

Analyses of rolling contact fatigue (RCF) problems require the use of multiaxial fatigue criteria, which take into account complex non-proportional stress conditions. One of the most often used criteria to analyse this phenomenon is the Dang Van criterion. However, this criterion is often [...] Read more.

Analyses of rolling contact fatigue (RCF) problems require the use of multiaxial fatigue criteria, which take into account complex non-proportional stress conditions. One of the most often used criteria to analyse this phenomenon is the Dang Van criterion. However, this criterion is often criticised due to its overestimation of the influence of compressive stresses on fatigue strength, which leads to an underestimation of the equivalent fatigue stress. Due to the high popularity of this hypothesis, in this paper a few modifications of the Dang Van criterion based on the critical plane approach are compared. One of the investigated modifications is a new proposal in which it is assumed that compressive hydrostatic stresses are as unfavourable as tensile stresses. All variants are verified in three ways: (1) by means of the experimental results for the out-of-phase pulsating compression and alternating torsion; (2) by comparison with the results obtained by means of the Papadopoulos criterion (which provides the most accurate results for RCF issues); and (3) using the example of an RCF analysis of a roller bearing. Based on these investigations, it is confirmed that the original Dang Van criterion is not suitable for application to RCF problems. It is shown that the mere omission of compressive hydrostatic stresses is also insufficient. The highest agreement with the experimental results (relative error

δ

= 0.77%), the Papadopoulos criterion (

δ = 5.8 %

) and, in the case of the practical application (roller bearing;

δ = 1.1 %

), is obtained for the proposed modification in which it is assumed that the compressive hydrostatic stress is an unfavourable for fatigue processes in the same way as the tensile hydrostatic stress. Full article

(This article belongs to the Section Mechanics of Materials)

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17 pages, 2959 KB

Open AccessArticle

Environmental Footprint of Broadcast and Localized Fertilization Across Cropping Successions

by Leonardo Costanza, Mariangela Diacono, Antonio Monteforte, Vincenzo Alfano, Francesco Montemurro and Alessandro Persiani

Agronomy 2026, 16(10), 1015; https://doi.org/10.3390/agronomy16101015 (registering DOI) - 21 May 2026

Abstract

Climate change represents one of the most critical challenges, especially in the Mediterranean area. Using organic and localized fertilization could be an effective agroecological strategy to help mitigate the environmental impacts of climate change. Our study was carried out in an experimental field [...] Read more.

Climate change represents one of the most critical challenges, especially in the Mediterranean area. Using organic and localized fertilization could be an effective agroecological strategy to help mitigate the environmental impacts of climate change. Our study was carried out in an experimental field over a three-year crop succession including broccoli, sweet pepper and barley. A randomized complete block design was adopted, with two factors: (i) fertilization method (100% broadcast and 40% localized) and (ii) fertilizer type by testing: on-farm compost, two types of commercial compost and a mineral fertilizer. Environmental impacts per hectare and marketable yield were quantified using Life Cycle Assessment (LCA), considering abiotic depletion (AD), acidification (AA), eutrophication (EU), global warming potential (GWP), and photochemical oxidation (PO). The localized application of fertilizers achieved marketable yields comparable to the broadcast method, despite lower fertilizer inputs, suggesting an optimal nutrient-use efficiency. The LCA demonstrated that localized fertilization also enhanced environmental sustainability, decreasing Global Warming Potential (GWP) by 20% per hectare, compared to broadcast treatments. Moreover, considering only the fertilization phase, we observed a 59% reduction in GWP under the localized strategy. Even though localized fertilization emerges as an effective climate-smart strategy without compromising productivity, future research is recommended to assess its long-term impacts in site-specific conditions. Full article

(This article belongs to the Section Agroecology Innovation: Achieving System Resilience)

22 pages, 444 KB

Open AccessArticle

Least-Privilege Role-Based Access Control Improvement for Cloud Container Security

by Waleed K. Abdulraheem, Emad Mohammed Ibbini, Hasan Kanaker, Sami Smadi, Nader Abdel Karim, Hussam N. Fakhouri, Layla Albdour and Sandi Fakhouri

Computers 2026, 15(5), 326; https://doi.org/10.3390/computers15050326 (registering DOI) - 21 May 2026

Abstract

Role-Based Access Control (RBAC) is the de-facto mechanism for preserving Kubernetes and other cloud-native container platforms, however real deployments occasionally drift away from the principle of least privilege as clusters, teams, and services improve. This paper introduces an automated RBAC hardening framework that [...] Read more.

Role-Based Access Control (RBAC) is the de-facto mechanism for preserving Kubernetes and other cloud-native container platforms, however real deployments occasionally drift away from the principle of least privilege as clusters, teams, and services improve. This paper introduces an automated RBAC hardening framework that formulates least-privilege policy design as a limited optimization problem over RoleBindings and ClusterRoleBindings. The objective combines (i) a permission-risk score for namespaced and cluster-scoped actions with (ii) an operational complexity term that discourages overly large binding sets. Solid limitations encode functional requirements as well as practical security policies, which includes namespace allowlists, role scoping rules, administrative restrictions on cluster-wide bindings, binding budgets, and separation-of-duty requirements expressed by utilizing capability classes. To allow optimizer-agnostic search while protecting Kubernetes RBAC semantics, we analyze candidate policies by utilizing a unified penalty-based fitness function that compines risk, complexity, and constraint violations into a single scalar value. We utilized ten metaheuristic as a benchmark including baseline search paths on a Kubernetes-inspired instance and report feasibility and least-privilege quality metrics (precision, recall, F1, and over-privilege ratio) parallel to RB/CRB counts and excess risk as a structural indicators. Outcomes present that feasibility is the prime challenge, and is restricted to a subset of optimizers reliably arrives to entirely feasible and compact arrangements within the exact budget, indicating the practicality of metaheuristic enhancement for systematic RBAC reduction in containerized cloud computing environments. Full article

(This article belongs to the Special Issue Using New Technologies in Cyber Security Solutions (2nd Edition))

34 pages, 13655 KB

Open AccessArticle

Strengthening Historic Brick Masonry Walls: An Experimental Study of Restoration Mortar, Carbon Textile Reinforcement and Sprayed Polyurea

by Esra Tunay and Cenk Ustundag

Buildings 2026, 16(10), 2040; https://doi.org/10.3390/buildings16102040 (registering DOI) - 21 May 2026

Abstract

This study experimentally investigates the mechanical performance of historic brick masonry walls strengthened with three innovative methods: restoration mortar, carbon textile reinforcement, and sprayed polyurea. The research comprises material characterization and structural testing of masonry specimens. Initially, flexural, and compressive strengths of handmade [...] Read more.

This study experimentally investigates the mechanical performance of historic brick masonry walls strengthened with three innovative methods: restoration mortar, carbon textile reinforcement, and sprayed polyurea. The research comprises material characterization and structural testing of masonry specimens. Initially, flexural, and compressive strengths of handmade bricks and restoration mortar used for both joining and strengthening were determined. Subsequently, 40 masonry specimens were tested in four groups: unreinforced (control) and three strengthened groups (restoration mortar, restoration mortar with carbon textile and sprayed polyurea). For each group, 20 triplet specimens were subjected to shear strength tests, while 20 four-unit masonry wallets underwent diagonal compression tests following ASTM E519 to evaluate failure loads, shear stresses, deformation capacities, and failure modes. Tensile adhesion tests on polyurea material showed strong bonding without brick spalling. Strengthened walls were compared with control specimens in terms of load capacity, ductility, deformation patterns, and failure behavior. The results indicate that the polyurea-strengthened walls exhibited the highest structural performance together with a significant increase in ductility. This method is advantageous due to its flexibility, ease of application, and minimal intervention on the original masonry. Furthermore, sprayed polyurea enhanced performance under collapsing loads and shear stresses, demonstrating its potential as an innovative strengthening solution for historic masonry structures. Full article

(This article belongs to the Special Issue Advances in Materials and Structural Technologies for the Historical Built Environment and Heritage Conservation)

16 pages, 3257 KB

Open AccessArticle

GIS-Based Sliding Surface Reconstruction for Rapid Landslide Volume Estimation

by Qian Liu, Mingxin Yue and Lianghao Guan

Geosciences 2026, 16(5), 205; https://doi.org/10.3390/geosciences16050205 (registering DOI) - 21 May 2026

Abstract

Landslides cause significant casualties and economic losses worldwide each year, creating an urgent demand for rapid and reliable volume estimation during emergency response. Conventional approaches often involve trade-offs among accuracy, efficiency, and data availability, particularly when pre-event topographic data are unavailable. This study [...] Read more.

Landslides cause significant casualties and economic losses worldwide each year, creating an urgent demand for rapid and reliable volume estimation during emergency response. Conventional approaches often involve trade-offs among accuracy, efficiency, and data availability, particularly when pre-event topographic data are unavailable. This study proposes a novel GIS-based method for rapid landslide volume estimation through sliding surface reconstruction. By integrating open-source geospatial data (post-landslide Digital Elevation Model and landslide boundary KML) with spline interpolation and spatial analysis, the method reconstructs the subsurface sliding surface and calculates volume by comparing this surface with the post-landslide DEM. Applied to the 2019 Shuicheng landslide (Guizhou Province, China), the method yielded a volume estimate of 1.58 × 10⁶ m³, which deviates by only ~5% from official survey data. The entire workflow can be completed within approximately one hour, demonstrating high efficiency, low operational cost, and acceptable accuracy for rapid post-disaster assessment during the critical “golden 72 h”. Full article

(This article belongs to the Section Natural Hazards)

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12 pages, 2386 KB

Open AccessBrief Report

GM-CSF Promotes Superior In Vitro Differentiation of MHC II⁺ CD11c⁺ APCs Compared to L-929 Supernatant in Mouse Bone Marrow Cultures

by Gabriel Cordeiro, Felipe Cezar Pinheiro de Mato, Amanda Pires Bonfanti, Liana Verinaud and Catarina Rapôso

Int. J. Mol. Sci. 2026, 27(10), 4637; https://doi.org/10.3390/ijms27104637 (registering DOI) - 21 May 2026

Abstract

Antigen-presenting cells (APCs) play a critical role in modulating immune responses, making the optimization of their differentiation protocols essential for advancing cell-based immunotherapies. This study evaluated eight protocols to differentiate APCs from bone marrow precursors of C57BL/6J mice, comparing the effects of GM-CSF [...] Read more.

Antigen-presenting cells (APCs) play a critical role in modulating immune responses, making the optimization of their differentiation protocols essential for advancing cell-based immunotherapies. This study evaluated eight protocols to differentiate APCs from bone marrow precursors of C57BL/6J mice, comparing the effects of GM-CSF and L-929 conditioned supernatants at various concentrations. Four groups treated with GM-CSF and four with L-929 supernatant, alongside a control group, were assessed. Flow cytometry analysis revealed that GM-CSF significantly increased the yield of CD11c⁺ MHC II⁺ cells by up to 6-fold compared to the L-929 supernatant. Furthermore, GM-CSF-treated groups showed higher mean fluorescence intensities (MFI) for critical markers such as MHC II and CD11c, with MFI levels surpassing those of SL-929-treated groups by approximately 3- to 5-fold. In contrast, the L-929 supernatant demonstrated limited efficacy in promoting both cell differentiation and surface marker expression, resulting in minimal phenotypic and quantitative gains compared to controls. These findings highlight the superior efficiency of GM-CSF in driving APC differentiation and underscore the importance of balancing cell yield and phenotypic fidelity when selecting differentiation protocols. This study provides valuable insights for researchers developing targeted immunotherapies and offers a solid foundation for optimizing APC-dependent therapies, ensuring efficacy and cost-efficiency in cell-based strategies. Full article

(This article belongs to the Section Molecular Immunology)

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19 pages, 1515 KB

Open AccessArticle

Genetic Diversity of the Phenotypic Traits Among the Recombinants in Pepper

by Rongfang Zhao, Xiangjiao Wan, Tao Zhang, Yuhang Wang, Yongjuan Cheng, Xuehua Wang and Bingqiang Wei

Horticulturae 2026, 12(5), 643; https://doi.org/10.3390/horticulturae12050643 (registering DOI) - 21 May 2026

Abstract

Genetic diversity analysis can contribute to comparing the relationships between different germplasm resources. Self-recombination is one of the main strategies for the innovation of germplasm resources. In this study, a total of 588 accessions, including two parents and their 586 F_2:4 recombinant [...] Read more.

Genetic diversity analysis can contribute to comparing the relationships between different germplasm resources. Self-recombination is one of the main strategies for the innovation of germplasm resources. In this study, a total of 588 accessions, including two parents and their 586 F_2:4 recombinant individuals originated via the single seed descent (SSD) method, were used to explore the genetic diversity of 17 phenotypic traits. The results indicated that most traits of the recombinants represented continuous distribution and transgressive segregation, with their minimum and maximum values exceeding the parental ranges. Correlation analysis shows that 17 phenotypic traits could be roughly divided into three clusters. There was a significant correlation between traits in the same cluster, such as primary stem height, plant height, and plant canopy diameter in Cluster I; transverse diameter of fruit, fruit shape of apex, node pubescence density, and lamina transverse section morphology in Cluster II; and internode anthocyanin pigmentation, immature fruit color, and leaf color in Cluster III, respectively. The 586 recombinant individuals and two parents were generally clustered into three groups, Group I, Group II, and Group III, which contained 320, 226, and 42 recombinants, respectively. In addition, six principal components were extracted from the 17 phenotypic traits, which could explain 62.97% of the cumulative variance contribution. Importantly, ten recombinants with both purple and long fruit were screened as breeding materials. Overall, this study provides useful information and breeding materials for the utilization and innovation of pepper germplasm resources as well as genetic improvement of pepper. Full article

(This article belongs to the Section Genetics, Genomics, Breeding, and Biotechnology (G2B2))

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32 pages, 1125 KB

Open AccessReview

Immune Checkpoint-Based Therapies in Colorectal Cancer—Current Approaches and Future Perspectives

by Katarzyna Nakielska, Jacek Plewka and Marzena Lenart

Int. J. Mol. Sci. 2026, 27(10), 4628; https://doi.org/10.3390/ijms27104628 (registering DOI) - 21 May 2026

Abstract

Colorectal cancer (CRC) is the third most frequently diagnosed malignancy and the second leading cause of cancer-related mortality worldwide, underscoring the need for the development of more effective and durable therapeutic strategies. A key mechanism of tumor immune evasion involves activation of immune [...] Read more.

Colorectal cancer (CRC) is the third most frequently diagnosed malignancy and the second leading cause of cancer-related mortality worldwide, underscoring the need for the development of more effective and durable therapeutic strategies. A key mechanism of tumor immune evasion involves activation of immune checkpoint pathways through the upregulation of inhibitory ligand expression within the tumor microenvironment, leading to lymphocyte exhaustion and impaired antitumor immunity. Consequently, immune checkpoints have emerged as important targets for immunotherapeutic intervention, with significant advances over the past decade. Nevertheless, despite demonstrated clinical benefits in selected patient subpopulations, the overall therapeutic efficacy of immune checkpoint inhibitors remains limited, particularly in the context of CRC. In this review, we provide a comprehensive overview of currently approved immune checkpoint-based immunotherapies for cancer treatment, with a specific focus on CRC, as well as ongoing clinical trials and evolving trends in this area. Furthermore, we discuss emerging targets and novel therapeutic strategies, with particular emphasis on innovative small-molecule inhibitors as potential alternatives to monoclonal antibody-based approaches. Finally, we outline future perspectives and potential directions for advancing immune checkpoint-targeted therapies in CRC. Full article

(This article belongs to the Special Issue Molecular Mechanisms and Therapies of Colorectal Cancer: 4th Edition)

28 pages, 2027 KB

Open AccessArticle

Transfer-Function Modeling and Modal Characterization of Wooden Beam Specimens Based on Frequency Response Functions

by Hongru Qiu, Liangping Zhang, Yunqi Cui, Tao Ding and Nanfeng Zhu

Forests 2026, 17(5), 623; https://doi.org/10.3390/f17050623 (registering DOI) - 21 May 2026

Abstract

This study utilized three controlled Sitika spruce beam specimens and established a parameterized transfer-function model based on force–acceleration frequency response functions (FRFs) to characterize and reconstruct the frequency-domain modal response of beam specimens. The specimens were tested using non-contact magnetic swept-sine excitation, laser [...] Read more.

This study utilized three controlled Sitika spruce beam specimens and established a parameterized transfer-function model based on force–acceleration frequency response functions (FRFs) to characterize and reconstruct the frequency-domain modal response of beam specimens. The specimens were tested using non-contact magnetic swept-sine excitation, laser Doppler vibration measurement, and synchronous FFT analysis methods under free–free boundary conditions. In the experiment, one specimen was used for modeling and the other two specimens were used for consistency verification. Based on the measured complex FRF, a 1st–5th order modal transfer-function model was established in the frequency range of 0–1000 Hz. The experiment identified five resonance frequencies of the specimen, which were 65.0, 198.5, 370.5, 620.0, and 930.0 Hz, respectively. The model can reconstruct the measured magnitude and phase responses, with magnitude residuals within ±5 dB, resonance-peak magnitude errors of 0.03–0.73 dB, and wrapped-phase deviation around the poles of 0.20–5.08°. The Nyquist trajectory was continuous and smooth, with all poles located in the left half-plane, indicating that the model has stable pole behavior. The research results support the specimen vibration response as an approximate linear time-invariant system under small-magnitude and controlled testing conditions. The model can provide a physically interpretable and reconstructable modal-parameter expression for evaluating frequency-domain vibration responses of controlled wooden beam specimens. Full article

(This article belongs to the Section Wood Science and Forest Products)

28 pages, 1449 KB

Open AccessReview

Cyanobacteria from the Arabian Peninsula: A Comprehensive Review of Bioactive Compounds, Therapeutic Potential, and Biotechnological Applications

by Safiya Al Shmali, Razan Zadjali, Khalid Al Hashimi, Maha Al Khalili, Syed Ariful Haque and Nasser Al Habsi

Phycology 2026, 6(2), 57; https://doi.org/10.3390/phycology6020057 (registering DOI) - 21 May 2026

Abstract

Cyanobacterial species in the Arabian Peninsula region display a diverse range of potential biotechnological application. This review summarizes the cyanobacteria diversity found in the Peninsula region, the bioactive compounds found in these species, and the several health benefits and applications. The Arabian Peninsula [...] Read more.

Cyanobacterial species in the Arabian Peninsula region display a diverse range of potential biotechnological application. This review summarizes the cyanobacteria diversity found in the Peninsula region, the bioactive compounds found in these species, and the several health benefits and applications. The Arabian Peninsula region comprises a wide range of cyanobacteria with representatives from the orders Oscillatoriales, Chroococcales, Stigonematales, and Nostocales. These microorganisms produce specialized metabolites such as photosynthetic pigments, pigment–protein complexes, lipopeptides, phenolic compounds, and unique secondary metabolites. Many of the metabolites offer beneficial biological functions including antioxidants, antibacterial, anti-cancer, anti-inflammatory antiviral, and neuroprotective ones. In addition to the medical-related practices, cyanobacteria in the Peninsula region might have several other applications. Other probable uses include their potential bioremediation capability to remove pollutants or heavy metals, as a potential biohydrogen source for renewable energy, and as biofertilizers and soil enhancement to support sustainable agriculture; other useful applications include bioplastics production (polyhydroxyalkanoates), soil microbiota improvement, and methane reduction. The review highlights the potential diverse biotechnological applications of Arabian Peninsula cyanobacteria toward bioremediation, bioplastics, ecosystem regeneration, biofertilizers, bioenergy, and agro-sustainability, as well as human health. This review highlights the importance of the further exploration and exploitation of these resourceful microorganisms for sustainable development in the Arabian Peninsula region. Full article

27 pages, 2963 KB

Open AccessArticle

In-Hover Quadrotor Rotor Degradation Monitoring Using Null-Space Excitation and Lock-In Detection

by István Lovas

Drones 2026, 10(5), 395; https://doi.org/10.3390/drones10050395 (registering DOI) - 21 May 2026

Abstract

In-flight propulsion system diagnosis in multirotor unmanned aerial vehicles (UAVs) remains a challenging problem due to closed-loop control interactions, strong environmental disturbances, and common-mode effects that obscure rotor-specific anomalies. Conventional passive monitoring approaches based solely on electrical or mechanical measurements are often insufficient [...] Read more.

In-flight propulsion system diagnosis in multirotor unmanned aerial vehicles (UAVs) remains a challenging problem due to closed-loop control interactions, strong environmental disturbances, and common-mode effects that obscure rotor-specific anomalies. Conventional passive monitoring approaches based solely on electrical or mechanical measurements are often insufficient for reliable fault localization and for distinguishing global degradations from nominal operation. This paper proposes an active diagnostic framework that exploits low-amplitude sinusoidal excitation injected into the control null space during hover operation. By employing lock-in detection, rotor responses are selectively extracted at the excitation frequency, enabling the derivation of robust amplitude-based sensitivity indicators from rotational speed, current, and electrical power signals. A pairwise signed diagnostic metric is formulated to achieve reliable localization of asymmetric rotor faults. In addition, an absolute indicator referenced to a baseline condition is introduced to capture symmetric degradations affecting all rotors through the combined use of current- and power-based sensitivities. The proposed method is validated in a high-fidelity quadrotor simulation environment incorporating viscous-friction and thrust-coefficient degradation faults. Extensive Monte Carlo analyses demonstrate robust fault-detection and localization performance, including scenarios that are indistinguishable using conventional pairwise normalization techniques. Full article

(This article belongs to the Section Drone Design and Development)

40 pages, 756 KB

Open AccessArticle

Second-Order Rayleigh–Schrödinger Perturbation Theory for the Grasp2018 Package

by Gediminas Gaigalas, Pavel Rynkun and Laima Kitovienė

Atoms 2026, 14(5), 40; https://doi.org/10.3390/atoms14050040 (registering DOI) - 21 May 2026

Abstract

A developed method, based on the stationary second-order Rayleigh–Schrödinger many-body perturbation theory in an irreducible tensorial form, allows us to determine the most important core–valence, core, core–core, and valence–valence correlations for any atom or ion with an arbitrary number of valence and core [...] Read more.

A developed method, based on the stationary second-order Rayleigh–Schrödinger many-body perturbation theory in an irreducible tensorial form, allows us to determine the most important core–valence, core, core–core, and valence–valence correlations for any atom or ion with an arbitrary number of valence and core electrons. This paper presents the Feynman diagrams that describe these correlations. Additionally, it provides the rules for obtaining algebraic expressions in an irreducible tensorial form for any Feynman diagram coming from second-order many-body perturbation theory. Whereas some types of the valence–valence and core–valence correlations are described by the three-particle Feynman diagrams, additional developments to calculate the spin-angular parts of these diagrams have been made to the program library librang of the Grasp2018 As an example of the application of the developed method, the atomic calculations of the energy level structure and transition data for Ar II are presented. Full article

(This article belongs to the Special Issue Future Directions in Atomic Physics Inspired by the Pioneering Work of Charlotte Froese Fischer and Ian Philip Grant)

43 pages, 2631 KB

Open AccessArticle

ChangeVLM: A Language-Guided Semantic Alignment Framework for Binary Remote Sensing Change Detection

by Dongxu Li, Peng Chu, Chen Yang, Zhen Wang and Chuanjin Dai

Remote Sens. 2026, 18(10), 1671; https://doi.org/10.3390/rs18101671 (registering DOI) - 21 May 2026

Abstract

Against the backdrop of complex features and spectral heterogeneity in high-resolution remote sensing imagery, traditional methods suffer from insufficient semantic understanding, while existing vision–language change detection models face low efficiency, poor spatial localization, and decoupled detection–description pipelines. To overcome these limitations, this paper [...] Read more.

Against the backdrop of complex features and spectral heterogeneity in high-resolution remote sensing imagery, traditional methods suffer from insufficient semantic understanding, while existing vision–language change detection models face low efficiency, poor spatial localization, and decoupled detection–description pipelines. To overcome these limitations, this paper proposes ChangeVLM, a language-guided semantic alignment framework for binary remote sensing change detection, enabling end-to-end, prompt-free, highly efficient, and interpretable change detection. Its key advantages include the following, (1) Higher detection accuracy with F1 scores of 91.52%, 83.56%, and 75.29% on LEVIR-CD, SYSU-ChangeDet, and HRCUS datasets, outperforming 18 state-of-the-art methods. (2) Stronger edge integrity and small-object detection capability; (3) practical deployment efficiency: the end-to-end FLOPs is 560.7G. Additionally, under an optimized inference setting with pre-extracted features, the effective computation can be reduced to 13.05G. (4) Language-guided semantic regularization to enhance visual discrimination, without requiring external text prompts. The Asymmetric Fusion Module (AFM), lightweight ChangeHead, and Change-Aware Cross-Modal Fusion Module (CACMF) jointly enhance spatial precision, efficiency, and interpretability. Extensive experiments validate that ChangeVLM achieves a superior accuracy–efficiency trade-off. This method provides an effective, deployable solution for high-resolution remote sensing binary change detection, where the language branch acts only as a regularization signal. Full article

(This article belongs to the Special Issue Foundation Model-Based Multi-Modal Data Fusion in Remote Sensing)

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