The rapid evolution of digital infrastructures and cloud-native technologies has intensified the complexity of cybersecurity challenges, particularly in Continuous Integration/Continuous Deployment (CI/CD) environments and distributed systems. This research provides a comprehensive examination of AI-driven approaches in cybersecurity, emphasizing threat detection, vulnerability management, and post-breach data protection. Through an in-depth synthesis of contemporary studies, the paper explores machine learning algorithms, AI-powered threat intelligence platforms, and predictive security models applied to CI/CD pipelines and telecom networks. The study further evaluates the integration of AI within DevOps frameworks, highlighting the proactive identification and mitigation of sophisticated cyber threats, including adversarial attacks and data poisoning. Methodologically, the paper adopts a qualitative synthesis of prior empirical findings, whitepapers, and emerging AI implementations across diverse platforms such as AWS, Microsoft Azure, and Google Cloud. Findings indicate that AI not only enhances real-time monitoring but also enables predictive insights that strengthen organizational resilience against both known and novel cyber threats. Limitations, including model interpretability, data privacy constraints, and computational overheads, are critically examined. Future directions focus on hybrid AI architectures, the ethical deployment of machine learning in sensitive environments, and the alignment of AI-driven security measures with regulatory frameworks. This work contributes to the growing body of knowledge by providing a theoretically grounded, practice-oriented understanding of AI’s role in modern cybersecurity ecosystems.

Background: The Japanese quail is a key species in sustainable poultry production, yet optimal feeding strategies are still being explored. This study investigated the combined effects of different feeding regimens and dietary supplementation with Spirulina platensis on growth performance, blood biochemistry, and intestinal microbial capacity in Japanese quails.

Methods: A total of 240 one-day-old Japanese quails were assigned to a 2×3 factorial design, with factors being feeding regimen (ad libitum vs. quantitative feed restriction) and Spirulina supplementation (0%, 1%, 2%). The trial lasted for 42 days. Data on growth performance, serum biochemistry (glucose, total protein, cholesterol, triglycerides), stress markers (heterophil-to-lymphocyte ratio), and digestive tract microbial counts (Lactobacillus, Bifidobacterium, E. coli) were collected and analyzed using a two-way ANOVA.

Results: Feed restriction was associated with an improved feed conversion ratio (p<0.05) without negatively impacting final body weight, while Spirulina supplementation at the 2% level was associated with enhanced growth performance metrics and beneficially altered blood parameters, including a reduction in cholesterol and an increase in total protein. The heterophil-to-lymphocyte ratio was significantly lower in quails fed with 2% Spirulina, which is associated with reduced stress. Furthermore, dietary Spirulina was associated with a significant increase in beneficial bacteria like Lactobacillus and a decrease in E. coli counts in the ceca. The combination of feed restriction and 2% Spirulina was associated with the most favorable outcomes in terms of feed efficiency and gut health.

Conclusion: The findings suggest that strategic feed restriction can improve feed efficiency in Japanese quails, and dietary supplementation with Spirulina platensis at 2% is a highly effective method for enhancing growth, physiological health, and the microbial balance in the gut. These results provide valuable insights for developing sustainable and efficient feeding protocols in the quail industry.

The article analyzes the architecture of intelligent video surveillance based on an ontology of information quanta. The relevance of the study is determined by tightening requirements for IoT video analytics, which must operate under limited network bandwidth, strict privacy requirements, and tight budgets. The novelty of the approach lies in tokenizing video streams at the edge : low-level visual descriptors are transformed into semantically stable information quanta (IQ), after which their cloud processing is performed by vision-language models. The paper formalizes the principles of a two-tier edge-cloud architecture and analyzes data-centric methods that increase the robustness of models to noisy data. Special attention within the work is paid to the ontology of actions as a connecting link between pose detection and subsequent semantic interpretation. The aim of the study is to demonstrate that the proposed architecture ensures ultra-low latency, compliance with privacy requirements, and high interpretability of decisions. To achieve this aim, methods of systems analysis and comparative performance analysis are employed. In conclusion, it is shown that the architecture enables efficient solving of complex event analysis tasks in real time. The material is addressed to specialists in the fields of computer vision, the Internet of Things, and security systems.

The article presents a conceptual analysis and systematization of effective strategies for building a successful professional trajectory in the field of nail services. This analysis is based on the generalization of principles and practices developed by expert Nataliia Zapara, an internationally recognized nail artist and multiple champion of Nailympia competitions. The purpose of the study is to organize and comprehend effective strategies for beginning specialists by examining the expert's philosophy. The empirical basis consists of a qualitative analysis of Zapara’s published expert texts on the development of the nail industry and creative approaches to nail design, as well as materials in which she reflects on the role of continuous education and competition experience in a master’s career. The paper examines the theoretical foundations of professional development in the beauty industry, the practical aspects of mastering the craft, marketing communications, and client orientation. The conducted analysis made it possible to formulate comprehensive recommendations that contribute to achieving a high level of professionalism and competitiveness in the nail services market. The results of this conceptual study can be used in educational programs for the training of nail service masters, as well as directly by beginning specialists for career planning.

Cytomegalovirus (CMV) is a globally distributed herpesvirus that establishes lifelong latency and can cause severe disease in newborns, pregnant women and immunocompromised patients. Accurate laboratory diagnosis is essential to guide antiviral therapy, infection control, and epidemiological surveillance. Multiple diagnostic modalities are used, including nucleic acid amplification testing (NAAT) such as  polymerase chain reaction (PCR) and transcription-mediated amplification (TMA), clustered regularly interspaced short palindromic repeat (CRISPR-based assays), serology of Immunoglobulin  (IgM, IgG, IgG avidity), antigen detection (pp65), viral culture, dried blood spots (DBS), tissue biopsy, and functional CMV assays such as immunoassays (Flow cytometry, QuantiFERON-CMV  and ELISpot Assays) CMV smear are included. Molecular techniques, especially PCR-based methods, provide rapid, sensitive and specific detection of Cytomegalovirus DNA or RNA from various samples and remain the gold standard for congenital, transplant and immunodeficient patients. Serology and antigen-based testing provide complementary information, but have limitations in distinguishing active infection from latent infection. Recommended laboratory algorithms emphasize the integration of timely sampling, quantitative viral load monitoring, and patient immune status to optimize clinical decision making. Despite progress, there are still research gaps in universal newborn screening, prenatal prediction, standardization of viral load thresholds and analysis harmony. Future directions aim to improve molecular and immune-based diagnostics, standardize laboratory workflow, and improve patient care in high-risk populations.

The accelerating shift toward passwordless authentication, driven by technological advances in device-bound biometrics, platform authenticators, and standardized protocols, has created both opportunity and complexity for enterprise identity assurance. This article critically examines the integration of FIDO2-based passwordless mechanisms (including passkeys and CTAP/WebAuthn paradigms) with traditional certificate-based authentication to construct a hybrid, phishing-resistant, privacy-aware, and scalable identity architecture suited to modern enterprises. Drawing strictly from the provided literature, the paper synthesizes empirical and normative findings about mobile biometric advances, behavioral biometrics, FIDO2 usability and privacy implications, certificate lifecycle management, and data-protection regulation constraints (notably GDPR). The work articulates a detailed methodology for combining FIDO2 client- and server-side flows with enterprise Public Key Infrastructure (PKI), including trust anchoring, credential lifecycle orchestration, fallback and account recovery strategies, and privacy-preserving biometric handling aligned with regulatory obligations. Results are presented as descriptive analyses of anticipated security posture improvements, usability trade-offs, and operational complexity, supported by comparative studies of FIDO2 usability and biometric misconceptions. The discussion explores theoretical implications for identity assurance, counter-arguments regarding centralization and vendor lock-in, limitations in biometric entropy and behavioral approaches, and directions for future research including decentralized identifiers and semantic design patterns for passwordless applications. The article concludes with practical recommendations for phased enterprise adoption, governance controls, and technical blueprints aimed at realizing phishing-resistant, GDPR-compliant, and user-friendly authentication in heterogeneous enterprise ecosystems. (Abstract 238 words)

The study examines how artificial intelligence reshapes entrepreneurial activity and new-product trajectories across discovery, design, launch, and post-launch learning. The contribution lies in consolidating recent evidence on AI’s impact on opportunity formation, decision flows, and governance in risk-sensitive and regulated domains such as mental health, education, and organizations and products across sectors. The review describes performance gains from generative systems in knowledge work, the structuring value of multi-agent orchestration, and the strategic implications for data provenance, evaluation discipline, and go-to-market execution. Special attention is paid to cross-phase integration, where insight artifacts travel intact from qualitative discovery to modeling and telemetry-guided iteration. The goal is to derive an operator’s framework that aligns research signals with venture routines and product leadership choices. Methods include comparative synthesis of peer-reviewed sources, critical appraisal, and concept mapping. The conclusion outlines a reproducible stack for AI-native entrepreneurship that balances speed with auditability and trust, relevant for founders and product leaders.

The rapid digitization of healthcare infrastructure has precipitated a critical security challenge: the management of vulnerabilities across massive, heterogeneous environments often exceeding 100,000 assets. This paper investigates the efficacy of Artificial Intelligence (AI) and automated frameworks in mitigating cyber threats within these high-density clinical ecosystems. By analyzing recent breach statistics and contrasting legacy security models with modern cloud-based remediation tools, we evaluate the operational shift required to secure the Internet of Medical Things (IoMT). The methodology employs a comparative analysis of manual versus AI-driven vulnerability management cycles, focusing on metrics such as Mean Time to Remediate (MTTR) and false positive rates. Our analysis draws upon legal frameworks and industrial big data analytics to contextualize the technical findings within the broader scope of international governance and compliance. The results indicate that while legacy models fail to scale, AI-driven automated threat mitigation significantly reduces the window of exposure for critical clinical assets. However, the integration of these technologies introduces complex legal and ethical considerations regarding data privacy and algorithmic accountability. We conclude that a hybrid approach, combining automated "self-healing" networks with robust human oversight, is essential for the future resilience of healthcare information systems.

The article analyzes the development of artistic ceramics from the 20th to the early 21st century. It examines the distinctive features of the artistic style of Uzbek ceramics in the context of preserving and creatively interpreting traditions in contemporary masters’ practice. The study explores the adaptation of new forms, the dynamics of stylistic changes, and the process of creating a new system of imagery in the ceramics of Uzbekistan, and also traces the relationship between tradition and innovation within a broad socio-cultural and historical context.

The conducted study provides a comprehensive analysis of implementing vegan formulations in professional eyelash and eyebrow products in light of the updated requirements of the United States Food and Drug Administration (FDA) set forth by the Modernization of Cosmetics Regulation Act (MoCRA). The aim is to evaluate the chemical stability, functional characteristics, and allergy profile of vegan substitutes for traditional ingredients and to determine pathways to align them with tightened safety standards. The methodological approach includes a systematic review of scientific publications, content analysis of FDA regulatory materials and manufacturers’ technical dossiers, as well as synthesis of data from industry reports. The work demonstrates that the shift to vegan formulas in eyelash extension adhesives, eyebrow dyes, and lamination compositions generally preserves key synthetic actives (in particular, cyanoacrylates and p-phenylenediamine derivatives), creating a vegan paradox in which marketing notions of naturalness and safety diverge from the actual chemical nature of the products. It is established that the main vegan alternative to p-phenylenediamine (PPD), toluene-2,5-diamine sulfate (PTDS), is characterized by a high level of cross-reactivity (≈42,9%), which substantially limits its hypoallergenic potential. It is concluded that MoCRA shifts manufacturers from declarative promises to evidence-based safety substantiation, complicating and increasing the cost of bringing vegan products to market. The material is addressed to cosmetic industry chemical technologists, regulatory specialists, dermatologists, and practicing beauty-service professionals.

This article addresses issues such as the reflection of the concept of morality in the Uzbek language and its impact on the spirituality of young people. The article focuses on the moral concepts of youth in our country, such as spirituality, moral education.

In the context of the accelerating digital transformation of the financial industry, microfinance organizations (MFOs) are compelled to rethink and restructure their business models in order to maintain competitive advantages and strengthen the social impact of their activities. This study examines how digitalization and automation of key operational circuits serve as a fundamental driver for expanding the product line of MFOs. The purpose of the work is to identify causal links between the implementation of advanced technological tools — including Loan Origination System (LOS) class systems and the use of artificial intelligence (AI) in credit scoring procedures — and the ability of organizations to go beyond classical microcredit, forming a broader product portfolio. Methodologically, the study relies on a systematic review of academic sources, a comparative analysis of the markets of the United States, Europe, and Kyrgyzstan, as well as a detailed case study of comprehensive automation of one MFO in Kyrgyzstan. The results obtained indicate that achieving a threshold level of operational efficiency through automation — expressed in reduced application processing time and lower costs — frees managerial and financial resources necessary for designing and launching more complex products, such as microinsurance, digital savings instruments, and mortgage programs. Thus, the initial hypothesis is confirmed: operational transformation is not an end in itself, but serves as a mandatory precondition for strategic diversification. The conclusions drawn have practical significance for MFO managers, financial market regulators, and researchers in the fields of financial technologies and inclusive growth.