Search Results (8,750)

This paper presents Multi_mil, a multilingual annotated corpus designed for the analysis of information operations in military discourse. The corpus consists of 1000 texts collected from social media and news platforms in Russian, Kazakh, and English, covering military and geopolitical narratives. A multi-level annotation scheme was developed, combining entity categories (e.g., military terms, geographical references, sources) with pragmatic features such as information operation type, emotional tone, author intent, and fake claim indicators. Annotation was performed manually in Label Studio with high inter-annotator agreement (κ = 0.82). To demonstrate practical applicability, baseline models and the proposed Onto-IO-BERT architecture were tested, achieving superior performance (macro-F1 = 0.81). The corpus enables the identification of manipulation strategies, rhetorical patterns, and cognitive influence in multilingual contexts. Multi_mil contributes to advancing NLP methods for detecting disinformation, propaganda, and psychological operations. Full article

Background/Objectives: The global rise in antibiotic resistance necessitates the development of novel antimicrobial agents. Antimicrobial peptides (AMPs), key components of innate immunity, are promising candidates. This study aimed to develop novel therapeutic peptides with enhanced properties through the mutagenesis of natural AMPs and high-throughput screening. Methods: We constructed mutant libraries of three broad-spectrum AMPs—melittin, cecropin, and Hm-AMP2—using mutagenesis with partially degenerate oligonucleotides. Libraries were expressed in Escherichia coli, and antimicrobial activity was assessed through bacterial growth kinetics and droplet serial dilution assays. Candidate molecules were identified by DNA sequencing, and the most promising variants were chemically synthesized. Antimicrobial activity was determined by minimal inhibitory concentration (MIC) against E. coli and Bacillus subtilis, while cytotoxicity was evaluated in human Expi293F cells (IC₉₀) viability. The therapeutic index was calculated as the ratio of an AMP’s cytotoxic concentration to its effective antimicrobial concentration. Results: Mutant forms of melittin (MR1P7, MR1P8) showed significantly reduced cytotoxicity while retaining antimicrobial activity. Cecropin mutants exhibited reduced efficacy against E. coli, but variants CR2P2, CR2P7, and CR2P8 gained activity against Gram-positive bacteria. Mutagenesis of Hm-AMP2 generally decreased activity against E. coli, though two variants (A2R1P5 and A2R3P6) showed retained or enhanced efficacy against B. subtilis while maintaining low cytotoxicity. Conclusions: The proposed strategy successfully generated peptides with improved therapeutic profiles, including reduced toxicity or a broader spectrum of antimicrobial activity, despite not improving all parameters. This approach enables the discovery of novel bioactive peptides to combat antibiotic-resistant pathogens. Full article

Background/Objectives: Psychosocial factors (e.g., adherence, substance use) contribute to increased morbidity and mortality after heart transplantation. We investigated alcohol consumption patterns and their associations with psychosocial factors in adults, who underwent heart transplantation surgery (HTX recipients). Methods: Our cross-sectional study was conducted at the Semmelweis University Heart and Vascular Centre between 2023 and 2025. In total, 201 HTX recipients (75.6% male, mean age: 56.33 ± 11.46 years) completed the Alcohol Use Disorders Identification Test (AUDIT), Brief Health Literacy Screening Tool (BRIEF), Medication Adherence Report Scale (MARS-5) modified to immunosuppressive medication, and 9-item Beck Depression Inventory (BDI-9). Statistical analysis included Pearson’s correlation tests and Multivariate Regression Analyses. Results: The AUDIT had a higher proportion of non-evaluable responses than other questionnaires (AUDIT 19.9% vs. 5.5–9%), with 41.0% of the participants abstinent, 54.7% low-risk, 4.3% medium-risk, and 6.5% at-risk drinkers. AUDIT correlated negatively with MARS-5 (r = −0.326; p = 0.000) and positively with BDI-9 (r = 0.208; p = 0.010). At-risk drinking was associated with a lower MARS-5 (r = −0.231; p = 0.002). Multivariate regression models significantly predicted the AUDIT (F = 5.106; p < 0.001, R² = 0.216) and AUDIT-C (F = 3.804; p = 0.002; R² = 0.146), with sex and adherence as independent predictors. Conclusions: The high proportion of non-evaluable AUDIT responses suggests limitations in multi-questionnaire use but does not diminish its clinical relevance. The presence of 6.5% at-risk and 4.3% medium-risk drinkers highlights the relevance of consumption pattern screening, beyond diagnosing alcohol use disorder. Associations between AUDIT, MARS-5, and BDI-9 emphasize the necessity for multidisciplinary care. Full article

Fatigue is a multidimensional phenomenon with profound implications for performance, health, and wellbeing. Its complexity means that no single discipline can adequately explain its causes or management, highlighting the need for integrative approaches. This article introduces the F.L.A.M.E.S. framework, a psychological model that integrates self-report, physiological, emotional, and contextual perspectives on fatigue. The framework combines validated assessment tools with evidence-based management strategies including goal setting, motivational self-talk, attentional control, and emotion regulation and embeds these within proactive, reactive, and preventative approaches. Applications are illustrated through case studies in sport, healthcare, and education, showing how the model can be co-constructed with practitioners to ensure ecological validity and uptake. By linking mechanisms to management and scaling solutions across domains, the F.L.A.M.E.S. framework provides a roadmap for enhancing performance, resilience, and sustainable wellbeing. Full article

This study investigates the regulatory role of circFBN1 in chicken follicular granulosa cells (GCs) and its underlying molecular mechanisms through the miR-206/E2F5 pathway. circFBN1 was found to significantly enhance GC proliferation and inhibit apoptosis, as evidenced by increased expression of proliferation-related genes (PCNA, CDK1, and CCND1) and decreased expression of apoptosis-related genes (Caspase-3). Additionally, circFBN1 overexpression promoted the secretion of estradiol (E2) and progesterone (P4) by upregulating steroidogenesis-related genes (StAR and CYP11A1). Mechanistic studies revealed that circFBN1 functions as a molecular sponge for miR-206, thereby alleviating its inhibitory effect on the target gene E2F5. Dual-luciferase reporter assays confirmed the specific binding between circFBN1 and miR-206. Overexpression of miR-206 had the opposite effects, inhibiting GC proliferation, inducing apoptosis, and reducing E2 and P4 secretion by downregulating StAR and CYP11A1. Furthermore, E2F5 was identified as a direct target of miR-206, and its knockdown significantly reduced GC proliferation, increased apoptosis, and decreased steroid hormone secretion. These findings elucidate the regulatory mechanisms of the circFBN1/miR-206/E2F5 axis in avian follicle development and provide potential molecular targets for improving poultry reproductive performance. Future research should focus on exploring the upstream regulators of this axis and its interactions with other signaling pathways. Full article

CoFe₂O₄ loaded onto red brick powder (CoFe₂O₄@RBP) was synthesized via coprecipitation followed by post-calcination and employed as a heterogeneous catalyst to activate peroxymonosulfate (PMS) for the degradation of methylene blue (MB), thereby valorizing red brick demolition waste within a circular economy pathway and aligning the study with sustainability-oriented resource recovery. The effects of pH, PMS concentration, catalyst dosage, and coexisting substances on MB removal were systematically investigated. Complete MB removal was achieved within 30 min, and the apparent rate constant for the CoFe₂O₄@RBP/PMS system was 0.22 min⁻¹—slightly lower than that of CoFe₂O₄/PMS—while Co leaching was markedly reduced. The process performed well across a broad pH range (3.0–9.0). EPR and radical-quenching experiments indicate that SO₄•⁻ and HO• play a minor role, whereas the Co(II)–PMS complex is primarily responsible for MB degradation; accordingly, common coexisting species (SO₄²⁻, Cl⁻, NO₃⁻, humic acid) exert negligible effects. The catalyst also maintained strong durability across numerous repetitions. These results highlight a cost-efficient route to PMS activation by coupling CoFe₂O₄ with construction waste-derived supports. Full article

In this study, the authors demonstrate the development and evaluation of an optimal frequency control controller for an interlinked two-area power system that incorporates Renewable Energy Sources (RESs). In decentralized power grids, the Load Frequency Control (LFC) system allows scheduled tie-line power as well as system frequency to be reimposed to their nominal values. Designing an advanced controller might enhance the functionality of the LFC mechanism. This article illustrates the possible impacts of converter capacitors using the new High-Voltage Direct Current (HVDC) tie-line model as well as the Inertia Emulation Technique (IET). This paper suggests a new adaptive control procedure for the expected LFC mechanism: an ANN-based (PI^λ + PI^λf) controller. The authors evaluate which control parameters are most effective using a modified version of the Quasi-Opposition-learning-based Reptile Search Algorithm (QORSA) method. Software called MATLAB/Simulink-2015 is used to create this arrangement. The use of established techniques for handling step as well as random load disturbances has enabled an evaluation of the suggested LFC architecture’s efficacy. An IET-based HVDC tie-line reduces overshoot by 100% in Areas 1 and 2 (Area 1 frequency deviation, i.e., ∆f₁, as well as Area 2 frequency deviation, i.e., ∆f₂). When considering SLD, the suggested controller outperforms the most widely used alternative settings. The IEEE-39 bus system has been changed by the addition of RESs. The IEEE-39 bus system is composed of three control areas. It is confirmed how the IEEE-39 bus system reacts to changes in frequency in Areas 1, 2, and 3. It is illustrated how to use the suggested controller in the modified IEEE-39 bus system, accompanied by real-time load variations. Recent research indicates that the suggested control method is better and more efficient due to its 100% decrease in overshoot in Areas 1 and 2 and quick response time. Full article

Background/Objectives: Computerized diagnostic algorithms could achieve early detection of acute kidney injury (AKI) only with available baseline serum creatinine (SCr). To tackle this weakness, we tried to construct a machine learning model for AKI diagnosis based on point-of-care clinical features regardless of baseline SCr. Methods: Patients with SCr > 1.3 mg/dL were recruited retrospectively from Wan Fang Hospital, Taipei. A Dataset A (n = 2846) was used as the training dataset and a Dataset B (n = 1331) was used as the testing dataset. Point-of-care features, including laboratory data and physical readings, were inputted into machine learning models. The repeated machine learning models randomly used 70% and 30% of Dataset A as training dataset and testing dataset for 1000 rounds, respectively. The single machine learning models used Dataset A as training dataset and Dataset B as testing dataset. A computerized algorithm for AKI diagnosis based on 1.5× increase in SCr and clinician’s AKI diagnosis compared to machine learning models. Results: On an independent, unbalanced test set (n = 1331), our machine learning models achieved AUROC values ranging from 0.67 to 0.74. A pre-existing computerized algorithm performed best (AUROC = 0.94). Crucially, all machine learning models significantly outperformed the routine clinician’s diagnosis (AUROC ~0.74 vs. 0.53, p < 0.05). For context, a pre-existing computerized algorithm, which requires available baseline SCr data, achieved an AUROC of 0.94 on a relevant subset of the data, highlighting the performance benchmark when baseline data is available. Formal statistical comparisons revealed that the top-performing models (e.g., Random Forest, SVM) were often statistically indistinguishable. Model performance was highly dependent on the test scenario, with precision and F1 scores improving markedly on a balanced dataset. Conclusions: In the absence of baseline SCr, machine learning models can diagnose AKI with significantly greater accuracy than routine clinical diagnoses. Our robust statistical analysis suggests that several advanced algorithms achieve a similarly high level of performance. Full article

This study examines how sentiments and perceptions in Greece relate to seaplane adoption, building on prior work on Greek users’ emotions and attitudes toward seaplane services. Using survey data from N = 443 respondents (N = 373 used in the logistic model), we estimate a binary logistic regression for the intention to choose a seaplane. Perceived comfort and safety (F3) is the dominant predictor, substantially increasing the odds of adoption (e.g., OR = 6.67, 95% CI [4.09, 11.35]; robust under Firth penalization). In the full MLE model, emotion dummies (Freedom, No feelings) are not statistically significant relative to Joy; Fear exhibits quasi-complete separation, so its MLE coefficient is not interpretable (penalized results are provided as sensitivity). Model performance indicates acceptable discrimination (AUC = 0.782, 95% CI [0.734, 0.829]). Better perceived comfort and safety are critical for broader seaplane use in island and coastal regions. Full article

Recent centimeter-to-millimeter monitoring of nearby gamma-ray bursts (GRBs) has revealed late-time ($\gtrsim {10}^2$–${10}^4$ days) radio rebrightenings and spectral turnovers not explained by standard forward-shock scenarios with steady microphysics. We attribute these features to a buried millisecond magnetar whose surface dipole, initially submerged by early fallback (hours after birth), re-emerges via Hall–Ohmic diffusion on year–to–decade timescales, partially re-energizing the external shock. We combine a minimally parametric analytic framework with axisymmetric magnetohydrodynamic simulations of the hypercritical fallback phase to characterize burial depths and the initial conditions for reemergence. The growth of the external dipole is modeled as $\dot{E}\left(t\right)\propto {\dot{E}}_0{f}_G{\left(t\right)}^{\sigma }$ and calibrated against physically plausible diffusion timescales ${\tau }_m\sim \mathrm{years}$–$\mathrm{decades}$. Spin-down power couples to the afterglow through the surrounding ejecta via a single effective coupling factor and a causal delay kernel, encapsulating mediation by supernova ejecta/pulsar-wind nebulae in collapsars and by merger ejecta/winds in compact-object mergers. Applied to a representative set of events with late-time radio detections and upper limits, our scheme reproduces the observed rebrightenings and turnovers with modest coupling efficiencies. Within this picture, late-time centimeter–millimeter afterglows provide a practical diagnostic of magnetic-burial depth and crustal conductivity in newborn magnetars powering GRB afterglows, and motivate systematic radio follow-up hundreds to thousands of days after the trigger. Full article

This study presents a comprehensive overview of recent advancements in fire protection technologies for reinforced concrete (RC) structures, with a focus on sustainable and high-performance solutions. As climate change and urban densification continue to shape modern construction, the need for fire-resilient and environmentally responsible building systems has never been more urgent. This study examines traditional fire protection practices and contrasts them with emerging innovations. Emphasis is placed on their thermal performance, structural integrity post-exposure, and long-term durability. Case studies and laboratory findings highlight the effectiveness of these systems under standard and severe fire scenarios. This paper will present the results of a research study on the assessment of different fire protection systems for RC columns retrofitted with fiber-reinforced polymer (FRP) jacketing. To quantify how insulation can preserve confinement, three commercial fire protection schemes were tested on small-scale CFRP- and GFRP-confined concrete cylinders: (i) a thin high-temperature cloth + blanket (DYMAT™-RS/Dymatherm), (ii) an intumescent epoxy-based coating (DCF-D + FireFree 88), and (iii) cementitious mortar (Sikacrete™ 213F, 15 mm and 30 mm). Specimens were exposed to either 60 min of soaking at 200 °C and 400 °C or to a 30 min and 240 min ASTM E119 standard fire; thermocouples recorded interface temperatures and post-cooling uniaxial compression quantified residual capacity. All systems reduced FRP–interface temperatures by up to 150 °C and preserved 65–90% of the original confinement capacity under moderate fire conditions ($\le$400 °C and $\le$30 min ASTM E119) compared to 40–55% for unprotected controls under the same conditions. The results provide practical guidance on selecting insulation types and thicknesses for fire-resilient FRP retrofits. Full article

This study systematically benchmarks the performance of four single soft magnetic powders—water-atomized Fe–Si–Cr (FeSiCr), silica-coated reduced iron powder (RIP), silica-coated carbonyl iron powder (CIP), and phosphate-coated CIP (CIP-P)—to establish quantitative relationships between powder attributes, deformation substructure, and high-frequency loss for molded power inductors (100 kHz–1 MHz). We prepared toroidal compacts at 200 MPa and characterized them by initial permeability (μ_i), core-loss (P_cv(f)), partitioning (P_cv(f) = K_hf + K_ef², K_h, $K_{\mathrm{e}}$: hysteresis and eddy-current loss coefficients), and EBSD (electron backscatter diffraction)-derived microstrain metrics (Kernel Average Misorientation, KAM; low-/high-angle grain-boundary fractions). Corrosion robustness was assessed using a 5 wt% NaCl, 35 °C, 24 h salt-spray protocol. Our findings reveal that FeSiCr achieves the highest μ_i across the frequency band, despite its lowest compaction density. This is attributed to its coarse particle size (D₅₀ ≈ 18 µm) and the resulting lower intragranular pinning. The loss spectra are dominated by hysteresis over this frequency range, with FeSiCr exhibiting the largest K_h, while the fine, silica-insulated Fe powders (RIP/CIP) most effectively suppress K_e. EBSD analysis shows that the high coercivity and hysteresis loss in CIP (and, to a lesser extent, RIP) are correlated with dense, deformation-induced subgrain networks, as evidenced by higher mean KAM and a lower low-angle grain boundary fraction. In contrast, FeSiCr exhibits the lowest KAM, with strain confined primarily to particle contact regions. Corrosion testing ranked durability as FeSiCr ≳ CIP ≈ RIP ≫ CIP-P, which is consistent with the Cr-rich passivation of FeSiCr and the superior barrier properties of the SiO₂ shells compared to low-dose phosphate. At 15 A, inductance retention ranks CIP (67.9%) > RIP (55.7%) > CIP-P (48.8%) > FeSiCr (33.2%), tracking a rise in effective anisotropy and—for FeSiCr—lower M_s that precipitate earlier roll-off. Collectively, these results provide a microstructure-informed selection map for single-powder formulations. We demonstrate that particle size and shell chemistry are the primary factors governing eddy currents (K_e), while the KAM-indexed substructure dictates hysteresis loss (K_h) and DC-bias superposition characteristics. This framework enables rational trade-offs between magnetic permeability, core loss, and environmental durability. Full article

The widespread use of leetspeak and dialectal Arabic on social media poses a critical challenge to automated hate speech detection systems. Existing Arabic NLP models, largely trained on Modern Standard Arabic (MSA), struggle with obfuscated, noisy, and dialect-specific text, leading to poor generalization in real-world scenarios. This study introduces a Hybrid AraBERT–Hierarchical Attention Network (HAN) framework for deobfuscating Iraqi Arabic leetspeak and accurately classifying hate speech. The proposed model employs a custom normalization pipeline that converts digits, symbols, and Latin-script substitutions (e.g., "3يب" → "عيب") into canonical Arabic forms, thereby enhancing tokenization and embedding quality. AraBERT provides deep contextualized representations optimized for Arabic morphology, while HAN hierarchically aggregates and attends to critical words and sentences to improve interpretability and semantic focus. Experimental evaluation on an Iraqi Arabic social media dataset demonstrates that the proposed model achieves 97% accuracy, 96% precision, 96% recall, 96% F1-score, and 0.98 ROC–AUC, outperforming standalone AraBERT and HAN models by up to 6% in F1-score and 4% in AUC. Ablation studies confirm the important role of the normalization stage (F1 = 0.91 without it) and the contribution of hierarchical attention in balancing precision and recall. Robustness testing under controlled perturbations (including character substitutions, symbol obfuscations, typographical noise, and class imbalance) shows performance retention above 91% F1, validating the framework’s noise tolerance and generalization capability. Comparative analysis with state-of-the-art approaches such as DRNNs, arHateDetector, and ensemble BERT systems further highlights the hybrid model’s effectiveness in handling noisy, dialectal, and adversarial text. Full article

Objectives: Papillary thyroid carcinoma (PTC) frequently presents with cervical lymph node metastasis (CLNM), yet preoperative tools often encode BRAF V600E as a binary variable, potentially overlooking information contained in mutation abundance. We sought to quantify the dose–response relationship between BRAF V600E abundance and CLNM and to develop an interpretable model for preoperative risk stratification. Methods: We performed a single-center retrospective study of consecutive PTC patients who underwent preoperative BRAF V600E testing and surgery from 2019 to 2023. Patients were randomly split 70/30 into training and test sets. Candidate predictors included clinical and ultrasound features and BRAF V600E abundance. We used multivariable logistic regression and restricted cubic splines (RCS) to assess nonlinearity and compared six machine-learning algorithms (LR, KNN, SVM, XGB, LightGBM, and NN). Model performance was evaluated by F1, AUC, calibration, and decision-curve analyses; SHAP aided interpretation. Ethics approval: SYSKY-2024-169-01. Results: The cohort included 667 patients; CLNM occurred in 391 (58.6%). CLNM cases had higher BRAF abundance (median 23% vs. 17%) and characteristic clinical/sonographic differences. RCS revealed a nonlinear association between abundance and CLNM, with a steep risk rise of up to ~20.7% followed by a plateau. Among six algorithms, XGBoost showed the best validation performance (AUC 0.752; F1 0.73). SHAP indicated that maximum tumor diameter, BRAF abundance, age, and microcalcifications contributed most to predictions. Conclusions: Modeling BRAF V600E as a quantitative abundance—rather than a binary status—improves preoperative CLNM risk assessment in PTC. An interpretable XGBoost model integrating abundance with routine features demonstrates acceptable discrimination and potential clinical utility for individualized surgical planning and counseling. Full article

The concepts of k-product cordial labeling and edge product cordial labeling were introduced in 2012 and further explored by various researchers. Building on these ideas, we define a new concept called ‘edge k-product cordial labeling’ as follows: For a graph $G=\left(V\right(G),E(G\left)\right)$, which does not have isolated vertices, an edge labeling $f:E\left(G\right)\to \left\{0,1,\dots ,k-1\right\}$, where $k\ge 2$ is an integer, is said to be an edge k-product cordial labeling of G if it induces a vertex labeling $f^{*}:V\left(G\right)\to \left\{0,1,\dots ,k-1\right\}$ defined by $f^{*}\left(v\right)={\prod }_{uv\in E\left(G\right)}f\left(uv\right)(modk)$, which satisfies $\left|e_f\left(i\right)-e_f\left(j\right)\right|\le 1$ and $\left|v_{f^{*}}\left(i\right)-v_{f^{*}}\left(j\right)\right|\le 1$ for $i,j\in \left\{0,1,\dots ,k-1\right\}$, where $e_f\left(i\right)$ and $v_{f^{*}}\left(i\right)$ denote the number of edges and vertices, respectively, having label i for $i=0,1,\dots ,k-1$. In this paper, we study the edge k-product cordial behavior of trees, a comet, and a double comet. Full article