Search Results (164,362)

Nano-tweezers, especially those based on photonic crystals and plasmonic structures, are powerful tools for trapping, manipulating, or accelerating nano-sized objects. However, the precise control of the inter-distance between trapped nanoparticles has rarely been considered. In this paper, we propose a mirror-symmetric optical conveyor belt, in which each unit contains three graded nano-slots. Through the optimized design of spacing between these nano-slots, the structure generates multiple trapping centers, enabling wavelength-selective control over trapping positions. The results show that, through dynamically shifting excitation wavelengths, the programmable bidirectional optical manipulation of nanoparticles can be achieved. Also, the inter-distance between trapped particles can be tuned with subwavelength precision. The proposed structure provides a versatile solution for lab-on-a-chip systems, especially for systems aiming to study the interactions between objects. Full article

Grain number per spike (GNS) is a key component of wheat yield, yet its genetic architecture remains incompletely understood. This study phenotyped 610 wheat accessions for GNS in four environments and genotyped them using 429,721 single nucleotide polymorphisms (SNPs). The phenotypes were associated with the SNPs using a three-variance multi-locus random-SNP-effect mixed linear model (3VmrMLM) to identify quantitative trait nucleotides (QTNs), as well as QTN-by-environment (QEI) and QTN-by-QTN (QQI) interactions. These genetic components and residual error explained approximately 18%, 31%, 28%, and 23% of the phenotypic variance, respectively. Two and one previously reported genes were found around QTNs and QEIs, respectively. Bioinformatics and haplotype analyses subsequently yielded 25 candidate genes, 22 gene-by-environment interactions (GEIs), and 24 gene-by-gene interactions (GGIs) around the QTNs, QEIs, and QQIs, respectively. Notably, TraesCS1D01G280000, the wheat homolog of OsRopGEF10, was located near a major QTN explaining over 10% of the total phenotypic variation. A gene interaction network constructed from all identified genes highlighted the central role of GGIs in GNS regulation. Environmental variation may reshape the regulatory network through GEIs. Furthermore, superior haplotypes of 12 candidate genes were identified, providing valuable targets for improving wheat yield. Overall, this study dissects the genetic architecture of GNS and offers practical resources for wheat molecular breeding. Full article

Globally, Central Asian wild fruit forests are critical repositories of wild fruit germplasm resources and provide essential ecosystem services. However, their habitats are facing escalating degradation risks driven by climate warming, shifting precipitation regimes, and intensifying anthropogenic disturbances. Accurately quantifying climate-driven spatiotemporal variations in habitat suitability for keystone wild fruit tree species is therefore an essential prerequisite for formulating targeted conservation and management strategies in arid and semi-arid landscapes. In this study, we applied the maximum entropy (MaxEnt) model to simulate the current (2000–2020 baseline) and future (2030s, 2050s, 2070s) potential suitable habitats of two dominant wild fruit tree species, Malus sieversii (Ledeb.) M.Roem. and Prunus cerasifera Ehrh., in the Ili Valley, a core distribution area of Central Asian wild fruit forests in northwestern China. We integrated rigorously screened species occurrence records with key environmental predictors and characterized future climate conditions using three Shared Socioeconomic Pathways (SSPs; SSP126, SSP245, and SSP585) spanning low to high radiative forcing levels. The model exhibited excellent predictive performance (AUC > 0.85), confirming the robustness and reliability of our habitat suitability simulations. Elevation and annual precipitation were identified as the dominant environmental variables governing habitat suitability for both species, highlighting the critical role of terrain–hydroclimate interactions in maintaining viable dryland refugia for wild fruit forests. Under the baseline climate scenario, the total area of suitable habitats reached 24.014 × 10³ km² for Malus sieversii and 18.990 × 10³ km² for Prunus cerasifera. Future climate projections revealed a consistent and significant contraction trend in suitable habitats for both species, with the magnitude of habitat loss escalating with increasing radiative forcing and longer projection time horizons. Specifically, under the high-emission SSP585 scenario by the 2070s, the suitable habitat area is projected to decline by 7.579 × 10³ km² for Malus sieversii and 9.883 × 10³ km² for Prunus cerasifera relative to the baseline. Our findings delineate climate-vulnerable hotspots of wild fruit forests and provide a robust spatial scientific basis for prioritizing in situ conservation, targeted habitat restoration, and anthropogenic disturbance regulation to support the long-term persistence of these irreplaceable wild fruit germplasm resources under accelerating global climate change. Full article

Pozzolanic concrete demonstrates intricate, highly nonlinear material interactions that pose significant challenges for the accurate prediction of compressive strength (CS). This study introduces a novel, interpretable ensemble machine learning (ML) framework for predicting CS based on 759 mixture records encompassing cement, aggregates, supplementary cementitious materials (pozzolans), water/binder (W/B), superplasticizer, water, and curing age. Descriptive analysis and ANOVA were used to identify key predictors, followed by an 80/20 train–test split with 10-fold cross-validation to ensure robust and generalizable modeling. To further enhance model reliability, 5% of outliers were removed using an isolation forest algorithm, after which data were normalized and ensemble hyperparameters optimized. Among the evaluated models, the extra trees algorithm with standard scaling demonstrated the most stable generalization, achieving a coefficient of determination (R²) of 0.978 and a root mean square error (RMSE) of 4.197 MPa on the test set, and R² = 0.966 (RMSE = 5.053 MPa) under 10-fold cross-validation. Feature importance, SHAP, and partial dependence analyses consistently demonstrated that W/B, curing age, and cement are the principal determinants of CS. Finally, multi-objective optimization generated high-strength, low-impact mixtures, confirming the framework’s effectiveness as a transparent decision-support tool for performance- and sustainability-oriented pozzolanic concrete design. This study is novel in combining interpretable ensemble ML with multi-objective optimization to simultaneously achieve precise CS prediction and the formulation of sustainable, performance-optimized pozzolanic concrete mixtures. Full article

Federated Learning (FL) has been widely adopted in privacy-sensitive and distributed environments. However, training stability becomes significantly challenged when differential privacy (DP) noise and Byzantine client behaviors coexist, as these heterogeneous perturbations jointly introduce time-varying distortions to model updates. Existing approaches typically address privacy and robustness in isolation. Under DP constraints, noise injection increases gradient variance and obscures the distinction between benign and adversarial updates, causing many robust aggregation methods to misclassify normal clients or fail to detect malicious ones. As a result, their effectiveness degrades substantially in practical IoT environments where noise and attacks interact. In this work, we propose a dual-factor adaptive and robust aggregation framework (DARA) to improve the stability of FL under such combined disturbances. DARA adjusts the differential privacy noise scale by jointly considering local update magnitudes and training-round dynamics, aiming to mitigate noise-induced bias under a fixed privacy budget. Meanwhile, a direction-aware weighted aggregation scheme assigns continuous trust weights based on cosine similarity between updates, thereby suppressing the influence of potentially anomalous or adversarial clients. We conduct extensive experiments on multiple benchmark datasets to evaluate DARA under differential privacy constraints and Byzantine attack scenarios. The results indicate that DARA achieves favorable robustness and convergence behavior compared with representative aggregation baselines, while maintaining competitive model accuracy. Full article

G-quadruplexes (G4s) are noncanonical nucleic acid structures involved in gene regulation and genome stability. Among them, the telomeric repeat-containing RNA (TERRA) forms biologically relevant RNA G4s (rG4s) that participate in telomere maintenance and genome stability. Although many ligands targeting DNA G4s have been reported, the recognition and modulation of RNA G4 topologies remain less explored. In this work, we investigated the interaction between TERRA and the spermine-functionalized Zn(II) porphyrin, ZnTCPPSpm4, using UV–vis absorption, fluorescence, resonance light scattering (RLS), and circular dichroism (CD) spectroscopy. In K⁺, where TERRA adopts a parallel G4 conformation, ZnTCPPSpm4 binds through a stepwise mechanism involving external end-stacking, forming discrete supramolecular complexes without altering the native topology. In contrast, under Na⁺ conditions, ZnTCPPSpm4 induces a gradual conformational rearrangement of TERRA from the antiparallel to a parallel-like G4 topology. A CD melting study showed that ZnTCPPSpm4 stabilizes the parallel RNA G4, while slightly destabilizing the antiparallel topology. Overall, our results demonstrate that ZnTCPPSpm4 is not a simple G4 binder, but a topology-selective ligand capable of remodeling TERRA G4 structures, highlighting the potential of metalloporphyrins as RNA G4-targeting scaffolds. Full article

Salinity is a major constraint for lettuce production, affecting plant growth, physiological status, and market quality. This study evaluated the combined effects of increasing salinity levels (S₀: non-saline control; S₃₀, S₆₀, and S₁₂₀ mM NaCl) and Trichoderma harzianum inoculation on morphological, physiological, and quality-related traits of lettuce. Increasing salinity levels resulted in significant reductions in growth-related parameters, particularly leaf area, shoot biomass, root volume, and cutting resistance (CR), with the most pronounced decreases observed at S₁₂₀. In contrast, several physiological and quality-related parameters showed different response patterns. Membrane stability index (MSI) and chlorophyll index remained relatively stable across salinity treatments, while total soluble solids (C) increased with increasing salinity, indicating osmotic adjustment under stress conditions. Leaf color parameters showed reductions in lightness and chroma at higher salinity levels, suggesting structural and optical changes in leaves rather than severe pigment degradation. The effects of Trichoderma on plant growth were limited and did not consistently mitigate growth reductions under salinity. However, inoculation influenced several physiological and quality-related traits, including MSI and TSS, indicating a role in physiological regulation and stress adaptation rather than direct growth promotion. Multivariate analyses indicated that salinity was the main factor contributing to treatment separation, whereas Trichoderma application influenced the overall trait profile without consistently increasing growth parameters. Overall, the results suggest that under saline conditions, Trichoderma may contribute to stress tolerance and physiological stability rather than directly increasing plant growth, and its effectiveness depends on stress severity. Full article

Children with Autism Spectrum Disorder (ASD) frequently exhibit marked impairments in nonverbal communication, particularly in eye contact, which serves as a foundational element for social interaction and relational development. This study evaluated the effectiveness of an early intervention program utilizing interactive games supported by Augmented Reality (AR) technology to enhance eye contact behaviors, specifically initiation and maintenance, in children with autism. Using a multiple baseline across participants single-case experimental design, four boys (aged 5–7 years) diagnosed with ASD participated in an 8-week intervention at a specialized center in Saudi Arabia. The intervention featured tablet-based, gamified AR tasks incorporating real-time visual feedback, graduated difficulty levels, and reinforcement mechanisms designed to elicit social gaze and sustained eye contact. Eye contact duration and frequency were measured during structured social interactions via systematic direct observation. The results demonstrated significant improvements across all participants, with the mean duration of eye contact increasing from a baseline of 2.0 s to 5.8 s post-intervention. Visual analysis revealed robust treatment effects, further supported by substantial Tau-U effect sizes (range = 0.89–0.96; M = 0.93). Follow-up data collected three weeks post-intervention confirmed the maintenance of gains for three of the four participants. These findings suggest that AR-based interventions provide an effective and culturally responsive approach for enhancing specific nonverbal communication behaviors among children with autism in Middle Eastern contexts. Implications for clinical practice and directions for future research are discussed. Full article

Extreme drought events are increasingly destabilizing European lowland oak forests, yet within-stand variation in drought legacy effects remains poorly characterized. This study integrates UAV-LiDAR canopy structural analysis with a 68-year dendrochronological record (1952–2019) to examine divergent radial growth responses to the 2012 extreme drought in Turkey oak (Quercus cerris L.) forests of Vojvodina, northern Serbia. LiDAR scanning (Wingtra Gen II, 90 m altitude, spring 2024) enabled objective classification of 180 increment cores from 90 trees across four 5–7 ha experimental plots into two structural zones: a preserved-structure zone (PS; gap fraction ≤ 10%) and a disturbed-structure zone (DS; gap fraction > 10%). Ring width index (RWI) chronologies were developed using the modified negative exponential function and analyzed with linear mixed-effects models (LMMs) incorporating AR(1) temporal autocorrelation. Lloret resilience indices (a reference window of seven years) were computed per individual tree and compared between zones using Mann–Whitney U tests with Bonferroni correction. The key finding is a statistically significant zone × period interaction in all four plots (p = 0.0009–0.033): DS zone trees exhibited a marked post-drought RWI increase (mean +0.22–0.36 units; t-test p < 0.0001 in all plots), while PS zone trees showed no significant post-drought change (p = 0.147–0.258). Pooled Lloret analysis revealed significantly higher recovery (Rt: DS median = 1.693 vs. PS = 1.237; U = 1633, p < 0.0001, r = 0.532) and resilience (Rs: DS = 1.232 vs. PS = 0.932; U = 1574, p < 0.0001, r = 0.482), while resistance (Rc) did not differ between zones (p = 0.569), indicating that DS zone trees were equally susceptible to the drought but recovered far more strongly. The equivalence of Rc between zones critically implies that divergent post-drought trajectories cannot be attributed to differential drought tolerance but instead reflect a structural mechanism operating exclusively in the post-drought period. These results are consistent with a competition release mechanism: drought-induced canopy gap formation in DS zones reduced inter-tree competition for surviving trees, enabling accelerated radial growth recovery. Full article

Oxidative stress is characterised by the production of free radicals in higher amounts than the antioxidant scavenging capacity. This may cause damage to several organs especially the main site of detoxification, the liver. In this study, the antioxidant activity of five novel lipophilic fluoroquinolones (FQs) derivatives was evaluated against oxidative stress induced by acetaminophen (APAP) and carbon tetrachloride (CCl₄). Sixty-four male Wistar rats were divided into two oxidative-stress models. FQ compounds (25 mg/kg) were administered six hours after CCl₄ or APAP administration. Serum liver enzymes including aspartate aminotransferase (AST) and alanine aminotransferase (ALT) were measured. Changes in antioxidant parameters were determined in the serum including measurement of total antioxidant status and reduced-glutathione levels as well as catalase, glutathione peroxidase and superoxide dismutase activities. Additionally, molecular docking analyses were performed against catalase, CYP3A4, and Keap-1 to elucidate the potential molecular interactions underlying the observed biological activities. A significant decrease in ALT and AST levels was seen following FQ compound administration in both models. In addition, FQ compounds exhibited excellent antioxidant activity, leading to increased antioxidant enzyme activity, high total antioxidant status, and elevated reduced-glutathione levels. The docking results revealed that compound 4A exhibited the highest binding affinities toward catalase, CYP3A4, and Keap-1. These interactions suggest a possible enhancement of catalase activity, modulation of CYP3A4, and activation of the Keap-1/Nrf2 signalling pathway. Overall, these findings demonstrate the promising therapeutic potential on hepatic injury and oxidative stress of the novel FQ derivatives. Full article

Myocardial calcification is an uncommon complication associated with end-stage chronic kidney disease (CKD) in feline patients. This report describes the clinical and multimodal imaging features of metastatic calcification in a 10-year-old castrated male mixed-breed cat. The patient presented with dyspnea and anorexia, and was diagnosed with IRIS Stage 4 CKD. Laboratory findings revealed severe hyperphosphatemia and an elevated calcium–phosphorus product (CPP) of 135 mg²/dL², based on total calcium. This value significantly exceeds 70 mg²/dL², a threshold associated with a high probability of inducing soft tissue mineralization. Echocardiography revealed extensive hyperechoic foci with posterior acoustic shadowing in the interventricular septum and left ventricular wall. Functional assessment demonstrated a restrictive diastolic filling pattern, suggesting increased myocardial stiffness and congestive heart failure. Computed tomography (CT) further visualized systemic involvement, showing diffuse, amorphous calcifications (400–900 HU) in the myocardium, multifocal aortic wall, and extracardiac tissues. Despite intensive treatment with diuretics and renal support, the patient was euthanized eight days later due to progressive renal failure. This case illustrates that the interaction between metastatic calcification and uremic cardiomyopathy (UC) can result in refractory heart failure, underscoring the value of combined echocardiography and CT in evaluating end-stage renal disease. Full article

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

The Mpemba effect refers to the counterintuitive situation in which a system initially farther from equilibrium can relax faster than one that starts closer to it. In quantum systems, the effect is enriched by the presence of coherent dynamics, dissipation, and metastable manifolds associated with long-lived Liouvillian modes. Here we demonstrate a giant Mpemba effect in open quantum systems, where relaxation can be either hyper-accelerated or dramatically slowed depending on the initial state. We focus on weakly-coupled particle-conserving bosonic networks, each of which independently relaxes rapidly to a unique stationary state. When a weak coherent interaction is introduced, the composite system typically develops slow metastable modes and a hierarchy of relaxation timescales. We show that by tailoring the interaction Hamiltonian, these slow modes can be effectively suppressed for a broad class of initial states satisfying a minimal global requirement, enabling ultrafast relaxation even when the system starts far from equilibrium. Conversely, other initial states—sometimes arbitrarily close to the stationary state—may remain trapped in the metastable manifold and decay anomalously slowly. This mechanism provides a general route to engineer giant Mpemba effects, offering new possibilities for controlling dissipative dynamics, accelerating state preparation, and manipulating relaxation processes in complex quantum devices. Full article

Thermoplastic polyurethane properties are governed by the interplay between soft-segment mobility, hard-segment interactions, and segmented morphology, yet the extent to which atomistic predictions of their thermal and mechanical behavior depend on force-field choice remains insufficiently benchmarked. Here, we combine FTIR, DSC, TGA, and tensile testing with all-atom molecular dynamics simulations to investigate HDI–PEG polyurethane systems across a controlled soft-segment series. Experimentally, films with PEG molecular weights of 400, 1000, and 1500 g/mol were characterized, while simulations were extended to 400–2000 g/mol to compare two complementary force-field frameworks under a consistent protocol: OPLS-AA, a conventional atom-type-based force field, and OpenFF/Sage, a direct-chemical-perception framework augmented here with bespoke torsional refinements. Both force fields reproduce the composition-driven decrease in Tg and density with increasing PEG length, but differ systematically in absolute values, with OPLS-AA predicting higher densities and Tg values than OpenFF. Tensile experiments show the highest elastic modulus for PEG400, a marked decrease at PEG1000, and a partial recovery at PEG1500. Although nanosecond-scale deformation simulations overestimate absolute moduli because they probe high-rate elastic response, they recover composition-dependent stiffness differences, with OpenFF yielding a more pronounced non-monotonic trend than OPLS-AA. Overall, this work provides an experimentally anchored benchmark for assessing which composition-driven trends in HDI–PEG polyurethanes are robust across force-field families, and which observables remain sensitive to model assumptions and simulation scale. Full article

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