Search Results (883)

In modern cloud-native systems, a single root cause can trigger cascading anomalies across multiple entities (e.g., microservices, databases, and hosts), generating alert storms with hundreds or thousands of heterogeneous alerts. Alert convergence (automatically grouping these alerts into actionable incident tickets) is critical for reducing operator burden and recovery time. Existing graph-based methods construct a topological graph from known entity dependencies and then leverage Graph Neural Networks (GNNs) for information propagation, but they rely on static physical topologies that fail to capture implicit fault propagation paths. Large Language Model (LLM)-based methods focus on reasoning about the textual information of alerts, yet they do not incorporate global topological structure and struggle with consistency at scale. Motivated by these limitations, we propose LLM-Guided Graph Structure Learning (LLM-GSL), a novel framework that combines the semantic reasoning ability of LLMs with the structural modeling power of GNNs for alert convergence. Specifically, LLM-GSL first leverages an LLM to evaluate pairwise entity relationships and discover implicit fault propagation paths that are absent from static topologies, thereby enhancing the physical-topology graph into a more complete structure. A Graph Attention Network (GAT) then refines alert representations over this enhanced graph via graph message passing, guided by a self-supervised graph affinity loss with continuous multi-modal supervision targets that fuse adjacency structure, textual affinity, and temporal affinity. Finally, density-based clustering groups the learned representations into incident tickets. Experiments on five public datasets, including four LogHub-derived datasets and one RCAEval microservice fault-injection subset, demonstrate that LLM-GSL achieves an average F1-score of 96.2%, outperforming six baselines including both traditional clustering and LLM-based methods by at least 14.0 percentage points. Full article

The integration of international students into host countries and their cultures is a multifaceted challenge that significantly impacts their academic success and well-being. This study leverages Explainable Artificial Intelligence (XAI) to model and interpret variables associated with the self-rated integration of 175 international students at Charles Darwin University (CDU) in Australia, using data from a 42-question survey. Employing machine learning models, including Decision Tree (DT) and Gradient Boosting Machine (GBM), we use XAI techniques to identify variables most strongly associated with students’ self-rated integration, including career confidence, perceived future happiness, and perceived career obstacles. SHAP analyses and partial dependence plots provide global and instance-level insights, revealing both the magnitude and directional effects of these features. The findings highlight the predictive relevance of psychological and social variables in students’ self-rated integration, offering exploratory insights that inform targeted support programs. By enhancing model transparency through XAI, this research fosters trust in AI-driven educational interventions, addressing ethical considerations and promoting equitable outcomes for diverse student populations. Full article

Bipolar junction transistor (BJT)-based 2D temperature-sensor arrays are factory-calibrated to ±0.1 °C, but post-deployment thermal and mechanical stresses drift their per-sensor gain–offset parameters by an order of magnitude, and in-lab recalibration is impractical. We present RASC (Region-Aware Self-Calibration), a five-stage algorithm that decomposes the global ill-posed problem into local cluster-level problems, runs robust alternating estimation (trimmed-mean field reconstruction + Huber iteratively reweighted least squares (IRLS)) inside each cluster, and reconciles overlapping estimates by linear consensus on the cluster-overlap graph with provable exponential convergence. On 7632 frames from a deployed 16 × 16 array exhibiting ≈5× factory-spec non-uniformity, RASC cuts the locally non-smooth fixed-pattern residual by 71 ± 5% (10-fold cross-validation (CV)), reducing this residual to a level comparable to the ±0.1 °C factory specification (as assessed by local-smoothness residual metrics, not independent absolute-temperature validation) while perturbing the calibrated field by only 0.041 °C RMSE; reduction concentrates at the edges (78% vs. 55% interior). In simulations on 8 × 8 to 32 × 32 arrays, RASC matches an oracle centralised extended Kalman filter (EKF) within 0.10 °C with ≈4× lower bandwidth. The real-data evaluation is a single-deployment proof of concept on one array and one host PCB; broader, longitudinal validation remains future work. Full article

Internal and civil wars affect the lives of religious and ethnic minorities the most. For Syrian citizens of Armenian origin, the Republic of Armenia represented one of the most accessible and meaningful destinations to relocate to, shaped by shared ethnicity, collective memory, and historical ties. When the Syrian war erupted in 2011, thousands opted to resettle in Armenia, yet they and host institutions struggled to categorize them as immigrants, refugees, or repatriates. This ambiguous status has received little scholarly attention. To explore these complexities, the study employed a survey-based research design involving 124 participants, supplemented by an open-ended question intended to capture personal narratives and nuanced identity negotiations. The manuscript examines how the labels immigrant, refugee, and repatriate carry distinct legal, social, and emotional implications, especially against the backdrop of the 1915 Armenian Genocide’s enduring memory and the particularly negative connotations of “immigrant” and “refugee” in Western Armenian and Arabic languages. Within this contested semantic and policy terrain, repatriation appears not merely as a bureaucratic category but as a culturally resonant and sometimes preferred pathway for some Diaspora Armenians, informed by lifelong exposure to repatriation narratives through formal education (language textbooks) and informal communal practices. The case sheds light on the broader conception of stakeholders, including how they self-identify, how they understand their status in Armenia, and the factors shaping their choices, particularly in the context of contemporary geopolitics and the role of education in influencing external perceptions of them. Full article

Biofilms are structured communities of microorganisms embedded in a self-produced extracellular polymeric substance (EPS) matrix, whose development significantly enhances microbial resistance to antibiotics, disinfectants, and host immune defenses, posing major challenges in clinical, industrial, and environmental settings. Compared with planktonic cells, biofilm-associated microorganisms can exhibit up to 10- to 1000-fold increased tolerance to antimicrobial agents, contributing to the persistence of biofilm-associated infections (BAIs). These infections remain difficult to eradicate due to reduced penetration, altered metabolic states, and the presence of dormant or persister cells. Anti-biofilm strategies can be broadly classified into physical approaches (e.g., ultrasound, mechanical stress, and light-based approaches) that target biofilm structure; chemical and enzymatic methods (e.g., EPS-degrading enzymes) that destabilize the matrix; and biological and molecular strategies (e.g., quorum-sensing (QS) inhibitors, anti-virulence agents, bacteriophages, phage-derived antimicrobial molecules, antimicrobial peptides, and natural bioactive compounds) that modulate biofilm development and integrity by targeting regulatory pathways and matrix stability through distinct mechanisms of action. Natural compounds, including lactoferrin, lactoferrin-derived peptides, and probiotic and postbiotic fractions of lactic acid bacteria (LAB), as well as plant-derived metabolites, have shown promising anti-biofilm effects, with efficacy often enhanced through complementary or potentially synergistic interactions. However, despite these advancements, clinical translation remains limited. For example, BAIs account for approximately 80% of chronic infections, with high recurrence rates and therapeutic failure reported in device-associated infections and chronic wounds. These limitations highlight the need for clinically translatable, multimodal approaches that integrate structural biofilm disruption, antimicrobial targeting, and host response modulation to design more effective and sustainable anti-biofilm strategies. Full article

iPSC technology is well established in mammals but remains underdeveloped in non-mammalian species. A major barrier to generating avian iPSCs has been the lack of species-specific reprogramming factors and culture conditions capable of supporting self-renewal in avian pluripotent stem cells. Here, we report the generation of chicken iPSCs (ciPSCs) using a cocktail of seven chicken transcription factors (T7: Oct4, Sox2, Sox3, Klf4, c-Myc, Nanog, and Lin28B) combined with an optimized avian culture system. Transcriptomic and functional analyses identified Sox3, rather than Sox2, as the predominant SoxB1 factor in avian reprogramming. The resulting ciPSCs exhibited stable self-renewal for over 40 passages, expressed core pluripotency markers, differentiated into all three germ layers, and were transcriptionally similar to chicken ESCs. In chimera assays, ciPSCs contributed to somatic, extra-embryonic, and germline lineages, giving rise to gonadal PGC-like cells that did not acquire full germline competence. We further demonstrate that the T7 system generates iPSCs from quail, duck, peacock, zebra finch, and pigeon, and that duck iPSCs can form interspecies chimeras with donor cells detected in the host gonads. These findings establish a generalizable platform for avian iPSC generation with applications in developmental biology and germline preservation of endangered species. Full article

Dandruff (DF) is a prevalent, recurrent inflammatory scalp disorder increasingly recognized as a complex state of functional dysbiosis rather than a simple Malassezia overcolonization. The scalp microbiome is predominantly shaped by Malassezia species (M. restricta and M. globosa), Cutibacterium, and Staphylococcus species. Recent multi-omics evidence indicates that DF pathogenesis is driven by the destabilization of microbial interaction networks and strain-level functional heterogeneity, characterized by the disruption of the C. acnes/S. epidermidis balance and the opportunistic expansion of Staphylococcus aureus. Mechanistically, Malassezia utilizes its lipolytic repertoire to hydrolyze host sebum into irritant free fatty acids and peroxides. Concurrently, oxidative metabolites like squalene peroxide (SQOOH) penetrate the stratum corneum to activate the NF-κB and aryl hydrocarbon receptor (AhR) pathways, triggering a pro-inflammatory cascade that overexpresses keratins (K6/16/17) and downregulates filaggrin. This molecular cascade drives abnormal keratinocyte turnover and lipidomic remodeling, establishing a self-perpetuating “metabolism–inflammation–barrier disruption” pathological cycle. This review systematically elucidates the molecular etiology of DF as an ecological disorder driven by a tripartite imbalance among the microbiome, host physiology, and the environmental niche. We propose that next-generation therapeutic paradigms must transcend traditional antifungal eradication, focusing instead on targeted molecular intervention and microecological restoration to recalibrate overall scalp homeostasis. Full article

The rapid proliferation of cloud data centers has intensified concerns over carbon emissions, energy efficiency, and sustainability. Virtual machine (VM) placement is a pivotal control lever, yet existing methods rarely couple carbon intensity signals with computationally tractable multi-objective optimization. In this paper, we propose CASO (Carbon-Aware Surrogate-Guided Optimization), a novel framework that integrates an online adaptive Radial Basis Function (RBF) surrogate model with a self-adaptive hybrid PSO-DE swarm optimizer for real-time VM placement in geo-distributed edge cloud environments. CASO simultaneously minimizes carbon emissions, energy consumption, SLA violation rate, and network latency under strict host capacity and Quality-of-Service (QoS) constraints. Three key innovations differentiate CASO: (i) an online surrogate update mechanism that refines fitness approximations incrementally as workload patterns evolve; (ii) a carbon intensity weighting scheme anchored to real-time Grid Emission Factor (GEF) signals; and (iii) an adaptive parameter controller that autonomously tunes swarm exploration–exploitation trade-offs without hand-crafting. Experiments on the publicly available Alibaba Cluster Trace (cluster-trace-v2026-GenAI) dataset within a CloudSim-Plus environment show that CASO reduces carbon emissions by up to $31.4\%$, energy consumption by $27.9\%$, and SLA violations by $18.8\%$ compared to the strongest baseline while converging $3.8\times$ faster than the strongest baseline (ADEDL). Full article

Operational energy-forecasting pipelines require traceable execution from data ingestion to monitoring, yet few studies evaluate whether such pipelines continue to enforce quality controls when inputs or configurations are degraded. This study implements a previously proposed seven-phase forecasting lifecycle as a configuration-driven system on a self-hosted ClearML platform. The implementation is organised into five architectural domains: data and configuration, lifecycle phases and gates, orchestration, document artifact governance, and human-in-the-loop oversight. The pipeline is evaluated through six runs on four years of hourly electricity-consumption data from a Norwegian kindergarten building. Two baseline runs, in automatic and human-in-the-loop modes, demonstrate end-to-end execution and produce an XGBoost champion model with a 24-h-ahead test RMSE of 1.19 kW. Four controlled variants then test the validation-route logic by injecting missing data, shuffled consumption values, restrictive feature selection, and missing foundation-document sections. The first three variants are detected by phase-level sub-checkpoints, while the fourth is detected by Gate 0 through document-structure validation. The runs exercise revise-and-recover, override-then-terminate, and immediate-abort response pathways. The evaluation therefore demonstrates lifecycle execution, validation-route behaviour, and artifact traceability under controlled conditions; claims about live-deployment performance and multi-building generalisation are out of scope and identified as next steps. Full article

With environmental issues growing globally, action for environmental protection is necessary to prevent further loss of biodiversity. One avenue for addressing these issues is through civic action. While programs have been developed to introduce youth to civic action during adolescence with the help of trained educators, little is known about educator self-efficacy (SE) in facilitating this type of program. To assess the SE of pre-service educators (PSEs) in facilitating a civic action curriculum, a workshop was hosted to introduce 30 PSEs to the process of a civic action project. This workshop was used to conduct an exploratory study with a convenience sample of PSEs. A mixed-methods pre- and post-survey with no control group was used to compare SE before and after the workshop. A statistically significant increase in SE was observed from the pre- to the post-survey (p < 0.01), suggesting an increase in PSE SE in guiding youth through a civic engagement project. Additionally, open-ended questions about PSE’s understanding of civic engagement suggested that the educators had a limited understanding of civic engagement for youth prior to the workshop but improved their understanding following the workshop. While limited by the exploratory nature and small sample size, these findings suggest that PSEs may benefit from participation in similar workshops to support their self-efficacy to facilitate youth-led civic action projects. Full article

Cutaneous Larva Migrans (CLM) is a neglected tropical disease (NTD) caused by zoonotic Ancylostomatidae larvae, mainly Ancylostoma braziliense and Ancylostoma caninum, which infect dogs and cats. Humans are accidental hosts, acquiring infection when L3 larvae in contaminated soil penetrate the skin, producing serpiginous, pruritic lesions. We report a 24-year-old female from Quito, Ecuador, who developed a pruritic lesion on her right foot nine days after walking barefoot on wet, potentially fecally contaminated sand at Atacames Beach. Initial self-treatment with benzyl benzoate and herbal washes, followed by misdiagnoses as scabies and plantar warts, delayed proper care. Lesions progressed over three weeks with intense pruritus and functional impairment. CLM was correctly diagnosed by a podiatric technician 26 days post-exposure. Oral albendazole (400 mg/day for 4 days) led to rapid symptomatic relief within three days, with complete resolution by day 50. A survey analyzed by the McNemar Test revealed difficulties in recognizing early-stage CLM, regardless of experience or region among participants. Prevention requires personal protection, environmental sanitation, and regular anthelmintic treatment of dogs and cats. This case underscores the clinical consequences of delayed or incorrect diagnosis and highlights the need for enhanced healthcare training and One Health measures to reduce zoonotic diseases in Ecuador. Full article

Background/Objectives: Titanium alloy Ti₆Al₄V remains the gold standard in dental implantology due to its excellent mechanical properties, corrosion resistance, and biocompatibility. However, implant-associated infections and insufficient osseointegration continue to represent major clinical challenges, mainly related to bacterial biofilm formation and suboptimal surface–tissue interactions. Biofilm formation refers to the adhesion, accumulation, and growth of microbial communities embedded within a self-produced extracellular polymeric matrix on implant surfaces, which contributes to bacterial persistence and resistance to host defense mechanisms. This review aims to critically evaluate recent advances in multifunctional bioceramic coatings for dental implants, with a particular focus on zirconia (ZrO₂)-based systems and their antibacterial mechanisms. Methods: A structured literature analysis was conducted using major scientific databases including PubMed, Scopus, and Web of Science, focusing mainly on studies published between 2015 and 2025 related to CaP, Ag, and ZrO₂-based coatings for dental implants. The review examines their physicochemical properties, antibacterial strategies, ion release behavior, and biological responses, including osteogenic activity and biofilm inhibition. Particular attention is given to hybrid systems integrating multiple functional phases. Results: CaP coatings exhibit excellent osteoconductivity and promote early osseointegration but show limited intrinsic antibacterial activity. Ag-based coatings provide strong broad-spectrum antimicrobial effects through controlled Ag⁺ ion release, although concerns regarding cytotoxicity and dose-dependent responses remain. ZrO₂ coatings significantly enhance corrosion resistance and surface stability, while their antibacterial performance can be improved through nanostructuring, laser surface modification, and ionic doping. Hybrid Ag–CaP–ZrO₂ coatings demonstrate improved antibacterial activity, enhanced corrosion resistance, and better regulation of ion release kinetics and osteogenic response compared with single-component coating systems. Conclusions: Multifunctional bioceramic coatings represent a promising strategy for improving the performance of dental implants and addressing the dual challenge of infection control and tissue integration. However, challenges remain regarding long-term stability, controlled ion release, and limited clinical validation. Future research should focus on the development of smart, stimuli-responsive coatings and standardized evaluation protocols to facilitate clinical translation. Full article

Background/Objectives: As important post-transcriptional and epigenetic regulators of gene expression, miRNAs play a pivotal role in modulating host–virus interactions. While prior reviews have addressed either direct miRNA–HIV genome interactions or miRNA-mediated immune modulation in isolation, the integrated dual functionality of these molecules has not been systematically characterized. This review aimed to comprehensively explore how miRNAs that target the HIV-1 genome simultaneously modulate key innate and adaptive host immune signaling pathways. The conceptual novelty of this study is determined not by the identification of previously unknown miRNA-target gene pairs, but by the systemic integration of two regulatory levels (direct inhibition of the viral genome and modulation of the host cell immune signaling pathways) within a unified analytical framework. Such an integrated approach reveals a proviral regulatory network that remains non-obvious when each of these levels is examined separately. Methods: A narrative review was conducted using PubMed, Scopus, Web of Science, and Google Scholar (all years through 2025). In Stage 1, publications reporting experimentally confirmed interactions between host miRNAs and the HIV-1 genome were identified, yielding a curated set of 15 miRNAs. In Stage 2, target genes for each miRNA were retrieved from miRTarBase, TarBase (experimentally validated) and TargetScan 8.0 (in silico predicted). In Stage 3, target genes were manually mapped to key immune signaling pathways (TLR, NF-κB, JAK-STAT). In Stage 4, targeted literature searches were performed for each miRNA–target gene pair to identify direct experimental evidence of interaction. All stages were performed by two independent researchers, with discrepancies resolved by a third. Results: Fifteen host miRNAs with experimentally confirmed binding to the HIV-1 genome were identified, targeting viral genes including nef, pol, vpr, gag, env, vif, and the 3′-UTR. Thirteen of these miRNAs were found to regulate components of major immune pathways. miR-92a-3p, miR-29a/b-3p, miR-150-5p, and miR-125b-5p emerged as the most pleiotropic regulators, simultaneously suppressing TLR signaling (TLR3, TLR7, TLR8, MyD88, TRAF3/6, IRAK1/4), NF-κB components (REL, RELA, NFKB1), JAK-STAT effectors (STAT1–3, STAT5A/B, JAK2), and negative regulators of cytokine signaling (SOCS and PIAS family proteins). miR-133b and miR-196b-5p were found to selectively regulate SOCS/PIAS proteins without involvement in other analyzed pathways, suggesting potential for selective therapeutic targeting. Conclusions: The analyzed miRNAs exhibit functional dualism, acting as direct post-transcriptional suppressors of the HIV-1 genome while simultaneously functioning as epigenetic modulators of host immune signaling. These two modes of action are not independent but together form a conceptual framework of a self-reinforcing proviral regulatory network that, based on the synthesis of published evidence, is proposed to promote viral latency and immune evasion. The identified miRNAs represent promising, albeit complex, targets for novel therapeutic strategies aimed at eliminating latent HIV reservoirs. Full article

Türkiye has many historically rich cities that host structures of significant cultural value. These structures, especially masonry bridges, reflect the construction techniques and materials of the periods in which they were built. However, studies on the origins of these bridges and the structural deteriorations that develop over time are limited. This situation may lead to damage and even the risk of collapse if necessary precautions are not taken. In this study, stone and mortar samples were first collected from the historic Pamukçular (Şifalısu) Bridge in Bitlis, and the collected materials were analyzed. The structural behavior of the bridge under seismic effects was then investigated using the Finite Element Method (FEM). A three-dimensional geometric model of the bridge was created, and material parameters were defined based on values from the material analyses. Static analysis under self-weight and modal analysis were performed in the ABAQUS software (Version 6.14) to obtain the natural frequencies. Under the bridge’s self-weight, local stress concentrations were concentrated at the arch crown and pier-arch connections, with maximum tensile and compressive stresses reaching approximately 0.15 MPa and 0.27 MPa, respectively. These low stress levels demonstrate that the structure remains fully stable under static loading conditions. Finally, dynamic analyses in the time domain were carried out. In these analyses, records from the 2011 Van Earthquake and the 2023 Kahramanmaraş Earthquake were used to identify the bridge’s critical regions and evaluate its seismic performance. The results indicate that the overall structural stability is adequate; however, local stress concentrations occur in the arch crown and pier connection regions. The study provides engineering-based recommendations for preserving and strengthening historic masonry bridges. Full article

Topologically chiral molecular knots and links represent a unique class of stereochemical architectures in which handedness is encoded by the global crossing pattern of an entangled framework rather than by a local stereogenic element. Their configurational robustness and shape-persistent chiral environments make them promising platforms for molecular recognition, catalysis, chiroptical response, and spin-selective transport. This review summarizes recent progress in the stereoselective synthesis of topologically chiral knots and links, with emphasis on chirality transfer from point, axial and helical elements into persistent topological handedness. Major synthetic strategies are organized into helicity-driven approaches, template-free dynamic systems, coordination-driven self-assembly, and chiral self-sorting. The applications of knots in host–guest confinement, asymmetric catalysis, chiral recognition, and spin-selective transport are also discussed. Full article