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Reinforcement learning (RL) has shown to be effective for simple automated cyber defence (ACD) type tasks. However, there are limitations to these approaches that prevent them from being deployed onto real-world hardware. Trained policies will often have limited transferability across even small changes to the environment setup. Instability during training can prevent optimal learning, a problem that only increases as the environment scales and grows in complexity. In this work we look at addressing these limitations with a zero-shot transfer approach based on multi-agent reinforcement learning. Our approach partitions up the task into smaller network machine subtasks, where agents learn the solution to the local problem. These local agents are trained in a small-scale network, then transferred to larger networks by mapping the agents to machines in the new network. We have found that this transfer method is effective for direct application to a number of ACD tasks. We show that its performance is robust to changes in network activity, attack scenario and reduces the effects of network scale on performance.

This work explores the implementation of Retrieval-Augmented Generation (RAG) as a method to mitigate hallucinations in abstractive text summarisation using transformer-based BART and T5. The research uses the HaDeS dataset to evaluate how effectively RAG improves the quality and factuality of generated summaries. Quantitative analysis shows that summaries generated with RAG consistently outperform summaries without RAG on a variety of metrics like ROUGE, METEOR, BERTScore, and MoverScore. Interestingly, BART with RAG saw an improvement of 21% over its non-RAG counterpart, whereas T5 with RAG saw an improvement of 17.3%. The research also identifies that a combination of embedding retrieval management and model parameter adjustment is needed in order to get improved summary generation. As great as the success of RAG is, human evaluation of hallucinations in generated summaries finds that standard evaluation metrics are not the best measure for grading hallucinations in generated summaries. The outcomes highlight the effectiveness of RAG as a robust solution for improving abstractive summarisation compared to other approaches when being used alone, while also highlighting areas for future research, including the refinement of retrieval processes and the application of these techniques to larger and more diverse datasets including long text summarisation.

Global changes in environmental conditions are causing changes to animal migration patterns, including changes to migration timing and routes, as well as population declines or even extinction. These changes can have knock-on effects for communities and ecosystems both at the end points of the migratory route, as well as at the stopover sites that migrants visit during their journey. One key role that migrants can play within ecological communities is as mutualists, such as pollination. Pollination is critical for reproduction in many plants and thus for continued population growth and even spread of plant species. Migratory pollinators, in turn, derive key benefits from plants in the form of nectar. This mutualistic relationship sets up a potential feedback loop between abundance of flowering plants at stopover sites and the success of migrants passing through. Here, we develop a theoretical model to capture this feedback loop and explore how reductions in the abundance of migrants affects the population growth and spread of plants within a stopover site. We find that a small reduction in migrant abundance typically leads to a small reduction in plant population spreading speed while total loss of migrants visiting stopover sites can lead to abrupt changes for plants – either a decrease in the population spreading speed or the full collapse of the population. We also find combinations of parameter values where a decrease in migrant abundance counterintuitively increased plant population spreading speed. This result was especially notable when the plant population had an Allee effect and thus spread was ‘pushed’ forward by dynamics at the high-density population core.

The majority of people with osteoarthritis (OA) also have synovitis. Thus, synovitis likely has an etiopathogenic role in OA and may be a precursor, not just a consequence of joint failure. Epidemiological and experimental evidence have established obesity as a significant risk factor for OA development. However, the mechanisms underlying this link remain largely unknown. Increased plasma concentrations of growth factors (IGFs), cytokines, hormones, and adipokines released from adipose tissue may influence OA directly through increased joint degradation or by inducing insulin resistance. Several molecules have been described as potential markers involved in synovitis/OA, both in plasma and synovial fluid. Recent evidence has shown that circulating and synovial HSP70 levels positively correlate with knee OA’s radiographic severity, suggesting that HSP70 could represent a potential biochemical marker for predicting the severity and may play a fundamental part in the pathogenic mechanism of knee OA. In this review, we discuss the evidence of the role of HSP70 in the development of synovitis/OA and how therapies, such as exercise and heat therapy, may induce benefits for the management of the disease.

The success efficacy of B cell clearance depletion therapy in multiple sclerosis (MS) highly suggests strongly indicates the role involvement of B cells in the pathogenesis of MSdisease’s pathogenesis, posing thereby presenting a serious significant challenge to the existing classical pathogenesis conventional understanding of MS (i.e. T cell-mediated autoimmune diseases). pathogenesis.Both of CXCR5+CD8++ T cells [(follicular cytotoxic T cells, Tfc) and CXCR5+CD4+ T cells (follicular helper T cells, Tfh) serve as pivotal immune cells that bridge B cell and T cell interactions. While Tfc cells significantly contribute to the development of tumors and viral infections, they have been infrequently documented in autoimmune diseases, particularly in MS. CXCL13/CXCR5 is an important signaling pathway in Tfc cells, closely related to various cellular events.Evidence indicates that the pathway involving CXCR5 dysregulation is linked to tumor development and viral infections; however, the CXCL13/CXCR5 axis signaling pathway has seldom been documented in autoimmune diseases, especially in multiple sclerosis. In current review, we summaried current publications from pubmed including Tfc, CXCL13/CXCR5 axis and autoimmune diseases, tried to final the best protocol to study the role of Tfc in MS.

Molecular modifications of nattokinase have been demonstrated to yield enzyme variants with enhanced catalytic performance, offering valuable insights into the structure-activity relationship of this enzyme. In the present study, PoPMuSiC 2.1, a web-based tool designed for predicting protein stability changes induced by mutations, was employed to investigate the catalytic properties of nattokinase. Through PoPMuSiC prediction and site-saturation mutagenesis, the G131A mutant, which exhibited improved catalytic activity, was identified. Comparative analysis of the G131A mutant and the wild type nattokinase revealed a 1.5-fold increase in enzyme activity and a 4.5-fold extension in half-life, effectively addressing the typical trade-off between enzyme activation and stability in protein engineering. Computational simulations further indicated that the G131A mutant adopts a more stable conformation, displays stronger interactions with the substrate, and features a more optimal substrate entry pocket. The fermentation process of G131A mutant was optimized and a yield of 623.43 U/mL was obtained. These findings offer a novel approach for studying the structure-activity relationship of nattokinase and could be extended to other serine proteases.

Objective : To compare Efficacy, Safety and Outcome of 25 ug sublingual misoprostol and 25 ug vaginal misoprostol administered for labour induction at term . Design : Observational Analysis of Retrospective study design . Settings : Dr M.K.Shah medical college and research institute, chandkheda Ahmedabad . Sample : A total of 200 Antenatal women at term with indication for labour induction. Methods: This retrospective observational study analyzed the records of 200 antenatal patients beyond 37 weeks. It included patients who received induction of labor through sublingual versus vaginal misoprostol. The data collection process involved a thorough examination of the case record form, capturing essential details such as patients’ age, parity, clinical presentations, examination findings, and results from clinical assessments and ultrasonography. Additionally, it included pre-induction CTG readings, Bishop scores, the method of administering tablet misoprostol, the quantity of tablets utilized, modes of delivery, fetal and maternal outcomes, any complications encountered, and NICU admissions. Main Outcome measure : The number of women delivering vaginally within 24 hours of induction labour . Results: The findings reveal that the most prevalent indication for labor was hypertensive disorder. The maximum dosage of misoprostol administered for induction, along with the amount of Oxytocin needed for augmentation, was two. Conclusion: The research findings indicate that vaginal misoprostol and sublingual misoprostol demonstrate comparable safety and efficacy as methods for labor induction.

Granite residual soils are highly sensitive to water, leading to softening and disintegration that poses serious risks to engineering geosafety. Traditional soil improvement methods focus on structural modifications, overlooking the crucial role of surface properties in hydraulic transport. This study introduces Octadecylamine (ODA) as a surface modifier, which alters the surface contact angle of the soil without affecting its internal structure. We explored the relationship between water ingress/egress capacity and contact angle using various tests (contact angle, water droplet infiltration, SWCC, water loss, SEM, disintegration). Results show that ODA increases the contact angle as water and ODA content rise, transitioning the soil from hydrophilic to hydrophobic. The soil-water characteristic curve analysis indicates that hydrophobicity reduces the soil’s water-holding capacity and decreases the hysteresis loop area. Additionally, the water loss and disintegration tests reveal enhanced evaporation and disintegration rates with increased contact angle, improving water stability. SEM analysis shows that the soil’s pore structure remains unchanged, confirming that the performance improvement is due to surface property changes, not structural alterations. This study presents a novel surface modification technique for mitigating the risks of granite residual soil, offering valuable insights for engineering protection.

Gas - forming pyogenic liver abscess caused by Clostridium perfringens is rare in clinical practice. The patient in this case presented with fever and abdominal pain, had hemolytic manifestations. Imaging suggested gas - forming pyogenic liver abscess, and blood culture indicated positive for Clostridium perfringens. After empirical anti - infection treatment and drainage, the patient improved.

Docetaxel (DTX) is a frequently used antineoplastic agent despite its dose-limiting toxic effects. Our objective was to assess the effects of oleuropein (OLE), a natural polyphenol, on DTX-induced toxicity. Thirty-two male rats were randomly assigned to four groups for a four-week treatment: Control (sham), DTX (5 mg/kg weekly, i.p.), OLE (30 mg/kg daily, p.o.), and DTX+OLE. Biochemical and gene expression analyses were performed on liver, kidney, and blood samples. Additionally, histological and immunohistochemical evaluations were conducted on the liver and kidneys. OLE reduced the DTX-induced oxidative stress index in tissues. In contrast to DTX, it decreased caspase-3 and Bax gene expressions while increasing Bcl-2 expression. Furthermore, OLE improved the ALT, AST, urea, and creatinine levels, which were impaired by DTX administration. It also reduced serum IL-6, IL-1β, and TNF-α levels, which had been elevated due to DTX. Histopathological and immunohistochemical examinations revealed that OLE administration mitigated DTX-related damage in both tissues. These findings suggest that OLE might offer protection against DTX-induced liver and kidney toxicity in rats.

Extreme programming (XP) is one of the leading agile methodologies that has gained widespread acceptance from software development industries. This method provides both a clear implementation structure and an established framework for agile practice deployment specifically in extensive software development operations. XP’s increased adoption needs recognition of its recent development status which produces specific challenges mainly for small and medium, and especially large-scale software development projects. The research explores the challenges that emerge when implementing Continuous Integration (CI) in extensive software development environments. This research analyzes these CI challenges in a structured manner to provide valuable guidance about CI implementation in software development organizations and teams. A multi-vocal literature review (MLR) assessed all available formal and grey literature which led to the evaluation of 58 relevant sources for data extraction. The industrial survey added information from 49 experts who participated in the study. This methodology identified 11 major CI challenges that the XP teams encounter during their adoption of CI in large-scale software development (LSSD). Three challenges emerged as the most critical ones among the identified challenges ”Difficulties in establishing effective testing processes”, ”Continuous Integration conflicts” and ”Build-related issues” occurred 36%, 32% and 22% times respectively. The results from the industrial survey demonstrate parallel findings when compared with the results obtained through MLR assessment. A few differences existed in the way challenges were ranked between the two sources of data (MLR and industrial survey). The identified insights help XP practitioners to gain better knowledge about CI adoption challenges while providing practical guidance for professionals in LSSD.

The rapid expansion of Artificial Intelligence (AI) in digital platforms used by youth has created significant challenges related to privacy, autonomy, and data protection. While AI-driven personalization offers enhanced user experiences, it often operates without clear ethical boundaries, leaving young users vulnerable to data exploitation and algorithmic biases. This paper presents a call to action for ethical AI governance, advocating for a structured framework that ensures youth-centred privacy protections, transparent data practices, and regulatory oversight. We outline key areas requiring urgent intervention, including algorithmic transparency, privacy education, parental data-sharing ethics, and accountability measures. Through this approach, we seek to empower youth with greater control over their digital identities and propose actionable strategies for policymakers, AI developers, and educators to build a fairer and more accountable AI ecosystem.

The increasing integration of Artificial Intelligence (AI) in digital ecosystems has reshaped privacy dynamics, particularly for young digital citizens navigating data-driven environments. This study explores evolving privacy concerns across three key stakeholder groups, digital citizens (ages 16–19), parents/educators, and AI professionals, and assesses differences in data ownership, trust, transparency, parental mediation, education, and risk-benefit perceptions. Employing a grounded theory methodology, this research synthesizes insights from 482 participants through structured surveys, qualitative interviews, and focus groups. The findings reveal distinct privacy expectations: Young users emphasize autonomy and digital freedom, while parents and educators advocate for regulatory oversight and AI literacy programs. AI professionals, in contrast, prioritize the balance between ethical system design and technological efficiency. The data further highlights gaps in AI literacy and transparency, emphasizing the need for comprehensive, stakeholder-driven privacy frameworks that accommodate diverse user needs. Using comparative thematic analysis, this study identifies key tensions in privacy governance and develops the novel Privacy-Ethics Alignment in AI (PEA-AI) model, which structures privacy decision-making as a dynamic negotiation between stakeholders. By systematically analyzing themes such as transparency, user control, risk perception, and parental mediation, this research provides a scalable, adaptive foundation for AI governance, ensuring that privacy protections evolve alongside emerging AI technologies and youth-centric digital interactions.

This study examines the relationship between transformational leadership and job satisfaction among nursing staff in healthcare organizations. The study found that transformational leadership has a positive significant relationship with job satisfaction among nursing staff (r = .670, P<.001). Transformational leadership practices are positively associated with improved nursing staff outcomes such as job satisfaction, productivity, and retention, as well as increased patient satisfaction. The findings of this study highlight the importance of transformational leadership in healthcare organizations and its positive impact on job satisfaction among nursing staff. By implementing transformational leadership practices, healthcare organizations can create a positive work environment that promotes job satisfaction and ultimately leads to improved patient care outcomes. Therefore, healthcare organizations should prioritize the development and implementation of effective transformational leadership styles to promote job satisfaction, loyalty, and productivity among nursing staff. Moreover, involving nursing staff in decision-making processes and increasing their participation can further enhance their satisfaction and performance.

Rare diseases, also known as orphan disorders, present significant challenges globally, with rare obstacles in Pakistan. Limited awareness, inadequate specialized facilities, huge financial restrictions, and the absence of support political systems compound the difficulties faced by individuals with rare diseases. This mini review explores the landscape of rare diseases in Pakistan, highlighting the complexities of diagnosis, management, and policy gaps. Despite efforts by individuals and organizations, including patient advocacy groups and international collaborations, much remains to be done. Bridging these gaps requires sustained investments in awareness, research, and patient support. By prioritizing rare diseases on the national health agenda and implementing targeted policies, Pakistan can create a more reasonable future where individuals with rare diseases patients develop well, accessing timely diagnosis, affordable treatment, and a supportive community.

This issue explores the evolving field of Virtual Reality (VR) as a transformative tool in psychotherapy through the presentation of five clinical case studies and a framework for their analysis. As technological advancements increase accessibility to VR and a growing body of scientific evidence supports VR-based psychological interventions the potential for innovative VR applications in psychotherapy continues to expand. We propose a framework for conceptualizing VR psychotherapeutic interventions along three key dimensions: Strategy, Focus, and Perspective. The goal of this conceptual framework is to provide guidance for clinicians and researchers in designing effective interventions and broadening the scope of therapeutic possibilities. The five clinical cases featured in this issue span a wide range of psychological conditions, including chronic pain, PTSD, social anxiety, depression, and psychosis. The VR interventions draw from diverse theoretical approaches, including cognitive-behavioral therapy, acceptance and commitment therapy, systemic therapy, and personal construct therapy. Each contribution demonstrates how VR can enhance therapy, offering clients immersive and emotionally intense experiences that might foster personal growth, symptom reduction, and therapeutic breakthroughs. By presenting both well-established and innovative uses of VR, this issue provides valuable insights into how virtual environments can extend the boundaries of psychotherapy, addressing complex psychological issues in novel, impactful, and unique ways.

Studies in movement ecology are crucial for understanding how physical performance affects an animal’s ability to find resources, including new ranges or mating opportunities. Invasive species frequently exhibit high levels of boldness and exploratory behaviour, enhancing their ability to establish and spread in new environments. Our study compares the locomotor performance and exploration behaviour of adult male endemic katipō (Latrodectus katipo) and invasive adult male false katipō (Steatoda capensis) spiders collected from a sympatric population. Our aim is to compare the locomotory and exploration behaviour of these two spider species within the context of differences in their distribution patterns and conservation classification. We conducted three laboratory assays—maze, pole, and track—to compare exploration, climbing, and running behaviours. We found that male false katipō are more exploratory than katipō, supporting the hypothesis that invasive species exhibit bolder behaviours. This boldness aligns with the false katipō’s broader habitat range. Male katipō and false katipō had similar pole climbing behaviours, which may reflect the similar use of vertical space within refuges of the two species. False katipō completed the running track faster, and without stopping, compared to katipō. Whereas, katipō would occasionally freeze while being followed down the track with a paintbrush. Our study provides insight into the comparative locomotor performance of katipō and false katipō, highlighting the potential impacts of physical and behavioural traits on invasive species success and native species decline.

Antiphospholipid syndrome (APS) is well known for its association with arterial and venous thrombosis. Intracardiac thrombosis -more often involving right atrium- although rare, could be a serious manifestation of the disease, complicating its course. We describe a 49-year-old man with known history of APS and multiple myocardial infarction episodes and episodes

Title: Management Of A Large Penetrating Metallic Foreign Body With Anterior Skull Base Injury Using A Combined Trans-Nasal And External Approach: Case Report

Rigorous state-wide monitoring programs are lacking for dusky grouse (Dendragapus obscurus), a North American species of forest grouse with relatively low detectability that is found in coniferous and mountainous areas in the western United States and Canada. Hierarchical models for estimating abundance show promise for overcoming issues associated cryptic forest grouse behavior and low population densities. Our objectives were to evaluate protocols (i.e., number of sites, visits, and route type) and analytical methods for producing annual unbiased and precise indices of abundance (CV < 15%) to inform a statewide monitoring program. During 2019–2022, we designed and implemented multiple survey protocols throughout western Montana, USA, including spring point-counts (> 2200 unique sites) and transect-level (> 390 unique transects) distance sampling. We used an iterative process of field data collection and simulation analyses to evaluate the performance of four different statistical estimators for abundance (N-mixture model, hierarchical time-removal model with distance sampling, detection-naïve model, and hierarchical distance sampling model) for point-counts and transects to produce unbiased and precise estimates of dusky grouse abundance. Simulations demonstrated that increasing the number of sites visited or probability of detection decreased the requisite amount of survey effort for obtaining precise abundance estimates for all estimators. Unbiased and precise estimates of abundance were unachievable under most realistic point-based distance sampling protocols. N-mixture protocols where point-counts conducted during periods of high probability of detection at 80 sites visited four times per area of inference (e.g. study area or region) resulted in unbiased estimates of population size with the highest precision. Our study provides baseline information necessary for the development of state-wide monitoring programs of dusky grouse and more broadly illustrates an approach for developing rigorous and achievable monitoring programs for other species of forest grouse.

Objective: Endometriosis may negatively affect the ovarian reserve, and also endometriosis surgery may cause further damage to the ovarian reserve. There is lack of definite data for the effect of endometriomas and treatments on the ovarian reserve over time. This study aims to determine the effects of endometrioma and its treatment modalities on ovarian reserve. Design: Prospective cohort study Setting: Turkey tertiary hospital Population: Eighty women with endometrioma diagnosed by ultrasonography and 20 healthy age-matched women as the control group were enrolled in this prospective study. Patients in the study group were divided into four subgroups (20 patients for each group). Methods: Treatment modalities for each study group were expectant management, oral contraceptive (OCP), dienogest, and surgery. All patients were evaluated with ultrasonography, and blood samples were taken during recruitment for anti-mullerian hormone (AMH) values. Additional assessments were done six months after the first assessment. Main Outcome Measures: Prospectively compare the rates of change over time in AMH levels, a reliable ovarian reserve marker, between patients with endometriomas left intact and healthy controls, as well as between patients treated with OCP or dienogest and those who underwent surgical excision due to pain symptoms Results: The median rate of decline in serum AMH levels were 19% in the expectant management group, 26% in the OCP, 21% in the dienogest, 38% in the surgery, and 8% in the healthies. Thus, the rate showed a significant difference between the OCP therapy and healthy control groups (p=0.034) and the surgery and healthy control groups (p=0.001). Multivariate logistic regression analysis suggested that only age was correlated with the rate of decline. Conclusion: Our study is the first in the literature to report on the impact of different endometrioma treatment modalities on ovarian reserve. Our results indicate that surgical intervention is the most harmful treatment while others result in a slight decrease in ovarian reserve. Trial Registration Number: Clinical Trials, NCT03620838

The research on fatigue damage accumulation holds significant importance for the safety and reliability of mechanical structures. This study introduces an innovative approach to fatigue damage prediction by combining machine learning (ML) with physical mechanism, aiming to improve prediction accuracy, particularly with small datasets. A novel ML framework is proposed, incorporating a customized loss function that seamlessly integrates ML techniques with physical mechanism. This method improves model performance, tackles limited data challenges, and achieves faster convergence and higher accuracy than traditional ML models. The results demonstrate that embedding physical mechanism into ML models significantly boosts the accuracy of fatigue damage predictions, even when the training dataset is reduced by 30%. This work underscores the potential of hybridizing physical knowledge with ML to improve predictive capabilities and robustness, making it a powerful strategy for accurately predicting residual fatigue damage in scenarios with limited data.

Abstract  The integration of Global Distribution Systems (GDS) and Application Programming Interfaces (APIs) has the potential to transform airline ticketing and travel distribution by combining structured fare management with real-time pricing and enhanced flexibility. Traditional GDS platforms, such as Amadeus, Sabre, and Travelport, provide comprehensive access to full-service carriers (FSCs), corporate travel support, and multi-city itinerary management, but they are limited by high transaction costs, rigid booking structures, and slower fare updates. APIs, on the other hand, offer direct airline connectivity, real-time pricing, and enhanced customization, but they lack structured fare agreements and full access to FSCs. This paper explores whether a hybrid GDS-API model can address these limitations by offering cost efficiency, dynamic pricing, and broader airline coverage while integrating AI-driven automation. This study employs a systematic review, comparative analysis, and case study evaluation, focusing on platforms like Kiwi.com, eDreams ODIGEO, Traveloka, and Mystifly to assess how hybrid GDS-API integration improves pricing accuracy, ancillary service management, and operational efficiency. Additionally, the paper examines the challenges of implementation, including integration complexity, regulatory constraints, cybersecurity risks, and the initial investment required for API and AI infrastructure. Finally, future advancements in predictive analytics, blockchain-based ticketing, voice-enabled search, and New Distribution Capability (NDC) standards are discussed to determine their role in further enhancing hybrid travel platforms. This study aims to evaluate the feasibility, benefits, and potential limitations of the hybrid model, providing insights into whether it can serve as a sustainable and scalable solution for modern airline distribution.Keywords: GDS-API Integration for Booking Platforms, Optimizing Airline Ticketing Systems, Hybrid Travel Distribution, GDS and API Integration1. IntroductionThe travel industry has experienced significant technological advancements, transforming how consumers and businesses book flights, hotels, and other services. Traditionally, Global Distribution Systems (GDSs) such as Amadeus, Sabre, and Travelport have been central to airline ticket distribution, providing travel agencies and online platforms with structured access to flight inventories, pricing, and reservations. GDS platforms enable seamless connectivity between airlines, hotels, and travel agencies, making them indispensable for corporate travel and full-service airline bookings. However, they come with notable limitations, including high transaction fees, rigid booking structures, and a lack of real-time pricing flexibility. (Bhatnagar, 2024)In contrast, Application Programming Interfaces (APIs) have emerged as a modern alternative, allowing direct integration with airline reservation systems. APIs enable travel platforms to access real-time flight availability, pricing, and ancillary services, thereby reducing operational costs and enabling dynamic fare adjustments. (Switchfly, 2024)However, relying solely on APIs presents challenges, including limited access to full-service carriers, lack of structured fare rules, and potential instability due to direct airline integrations.To address these shortcomings, a hybrid model combining GDS and API integrations has emerged as an optimal solution. This approach leverages GDSs for full-service airline coverage and corporate travel deals, while utilizing APIs for low-cost carriers, real-time pricing, and direct airline partnerships. By integrating both systems, travel platforms can reduce distribution costs, increase flexibility, and provide a wider range of travel options. Leading online travel agencies (OTAs) have successfully implemented hybrid models, balancing GDS reliability with API-driven cost efficiency and enhanced ancillary services. (Altexsoft Editorial Team, 2025b)Furthermore, the integration of AI-powered chatbots has enhanced automation in travel bookings, enabling 24/7 customer support, real-time booking modifications, and personalized travel recommendations.This research paper aims to analyze the effectiveness of the hybrid model in improving travel booking platforms. Specifically, it will evaluate the benefits and challenges of GDS and API integration, propose an optimized strategy for hybrid adoption, and examine real-world case studies of successful implementation. Additionally, it will explore the future of travel technology, including artificial intelligence, blockchain for secure ticketing, and the impact of New Distribution Capability (NDC) on airline distribution. The study focuses on OTAs, corporate travel agencies, and airline ticketing platforms, providing a comprehensive analysis of how hybrid models can enhance efficiency, reduce costs, and improve user experience in the travel industry.