AI-Powered Chatbot Solution for Efficient Network Troubleshooting in Hybrid Cloud Environments

Hybrid Cloud environments combining AWS and on-premises infrastructure presents complex networktroubleshooting challenges. Traditional manual diagnostic methods are time-consuming, error-prone, and struggleto correlate logs across distributed systems in real-time. This study addresses the creation of AI-based chatbotapplication to network fault-finding in hybrid cloud systems, involving the AWS CloudWatch, VPC Flow logs and on-premises infrastructure. The chatbot operates with natural language processing (NLP) to instruct users on thetroubleshooting steps on the basis of the historical and live network data. The system increases operational efficiencyand reduces the time to resolution by automating root cause analysis, log correlation and remediation suggestions.Using Anthropic Claude (Sonnet), Lex AI chatbot achieved 99.67% accuracy and reduced Mean Time to Resolution(MTTR) from 47.0 minutes to 40.13 minutes improvement. The chatbot enhances user experience in real-time andinteractive, 24/7 availability, reduce human error, eliminating the necessity to depend on support teams. The papershows how AI can streamline troubleshooting and optimize network diagnostics of hybrid networks with complexarchitectures

IMPROVING CUSTOMER EXPERIENCE WITH MODERN BANKING SOLUTIONS

The research describes the impacts of digital transformation on customer experience in modern systems ofbanking. The interactions have become more personalized, financial decisions are improved, and finally thisimproves customer satisfaction. This research describes the way effective omnichannel banking is in providing anintegrated, frictionless customer experience across all touchpoints. Moreover, integration of innovative technologyis also proposed for building confidence among customers to use financial services. Evidence showed that thesetechnological enhancements were some of the major factors contributing to improving convenience, enhancingcustomer satisfaction, and improving customer loyalty. One of the futures of banking is in further integrations oftechnologies that can be developed in service delivery and customer engagement

Insights into Structural Analysis via Crystallographic and X ray Diffraction Techniques

The arrangement of molecules inside a solid directly affects its properties. Therefore, understanding the three-dimensional structure of matter is necessary for establishing relationships between arrangement and qualities as well as for developing useful materials. X-ray crystallography has been the preferred method for precisely characterizing molecule structure at the atomic level for the last century. Crystallography is a fundamental analytical method that is often helpful in the development of novel medications. Atom size, length, electron density, atom mean location, and other attributes are among its attributes. The method is accurate for analyzing and determining the molecule and molecular configuration of crystals. X-ray diffraction (XRD) is the process by which an x-ray beam disperses or scatters into many directions and takes on unique patterns or shapes due to the presence of crystalline particles. Numerous industries, including the pharmaceutical sector, nanotechnology, geology, electronics, mineralogy, geosciences, materials science, and medicine, benefit from the use of X-ray diffraction and the crystallography method. Because of the structural knowledge gained from crystallographic research, these and other areas have developed quickly

Empowering Safe Online Spaces: AI in Gender Violence Detection and Prevention

Gender-based online violence (GBOV) is a pervasive issue that disproportionately impacts women and marginalized genders, leading to psychological distress, economic consequences, and restricted participation in digital spaces. This article examines how Artificial Intelligence (AI) offers innovative solutions to detect and mitigate GBOV through tools such as sentiment analysis, hate speech detection, image recognition, and behavioral analysis. AI-powered interventions have significantly enhanced the ability to identify harmful content, automate moderation, and empower victims by providing real-time safeguards. Despite these advancements, challenges such as algorithmic bias, privacy concerns, and the evolving tactics of online abuse remain critical obstacles. This study highlights the importance of developing ethical AI systems, fostering multi-stakeholder collaboration, and implementing robust regulatory frameworks to create safer, more equitable online environments for all

Methods for the Development of Cationic Nanocapsules for the Topical Administration of Tretinoin: A Box-Behnken Approach, In Vitro Assessment, and Ex Vivo Epidermal Deposition Research

An exciting new direction in topical administration is the use of cationic nanocapsules. To improve the photostability, user compliance, and pharmacodynamic effectiveness of tretinoin (TTN), we built on a new formulation that relies on cationic nanocapsules. The nanoprecipitation process was used to create TTN nanocapsules in order to accomplish this. A Box-Behnken design was used with the help of Design-Expert software to statistically optimize the formulation variables. The cationic acrylic polymer weight (X1), oil volume (X2), and total transdermal N-terminal thickness (X3) were the three independent variables that were examined. As for the dependent variables, we chose particle size and encapsulation efficiency percentage (EE%)

Neurological Applications of Exosome-Delivered Bioactives from Ancient Chinese Herbal Components

A bioactive substance derived from Chinese herbal medicines with established biological activity and pharmacological effects is known as a traditional Chinese medicine (TCM) monomer. It has drawn a lot of interest for the treatment of neurological disorders. However, the low solubility and poor blood-brain barrier (BBB) crossing of TCM monomers restrict their use. Small extracellular vesicles (EVs) with a diameter of 30 to 150 nm, exosomes may be employed as drug delivery vehicles that target cells or tissues directly. They have special benefits, such as low immunogenicity, low toxicity, high blood stability, and the capacity to pass the blood-brain barrier. The biogenesis, components, stability, surface modification, separation method, benefits, and drawbacks of exosomes as drug carriers are covered in this review, which also contrasts exosomes with other comparable drug delivery systems. Additionally, exosome-encapsulated TCM monomers exhibit neuroprotective properties, such as anti-oxidation, anti-apoptosis, anti-inflammation, and anti-mitophagy, in a variety of neuronal diseases, such as cerebral ischemia and reperfusion (CI/R) injury, Alzheimer's disease (AD), Parkinson's disease (PD), multiple sclerosis (MS), and anti-drug resistance, anti-tumorigenesis, and anti-angiogenesis, as well as the promotion of apoptosis in brain tumors. These findings further motivate the development of an exosome-based delivery tool in targeted therapy for neuronal diseases

Attention-Enhanced Sequential GAN for Reliable Groundwater Recharge Time-Series Augmentation

Groundwater recharge modeling is critically hindered by the scarcity of long-term, high-resolution time-series data, limiting the robustness and generalization capability of predictive models. We propose the Attention-enhanced Sequential Generative Adversarial Network ( ) to synthesize high-fidelity, multivariate hydrological records, explicitly addressing the complex temporal dependencies required for groundwater dynamics. The architecture incorporates three key innovations: stabilization via the WGAN-GP objective for continuous learning; utilization of a pre-trained LSTM autoencoder to establish a meaningful latent space; and integration of a Self-Attention mechanism within the generative networks to effectively capture critical long-range dependencies, such as multi-year climatic cycles. A three-pronged evaluation demonstrated exceptional data quality: Statistical Fidelity confirmed the preservation of feature relationships, and Temporal Coherence validated the realism of sequential patterns. Crucially, the Predictive Utility was confirmed, with an auxiliary forecasting model trained on synthetic data achieving a Mean Absolute Error (MAE only 4.4% higher) than a model trained on real data. This provides a stable and effective generative approach for time-series augmentation, offering a viable path to developing reliable forecasting tools in data-scarce hydrological contexts

Integrative Analysis of Oxidative Stress Biomarkers And Their ” Clinical correlates in Pediatric Type 1 Diabetes A Multi Parametric Approach

In this study, we used the neutrophil granulocytes functional activity model to examine oxidative stress indicators, antioxidant protection, lipid peroxidation, and T1D in children. According to research, children with type 1 diabetes show heightened lipoperoxidation and antioxidant defense system activation in response to reactive oxygen species (ROS) damage, which includes bidirectional alterations in non-enzymatic pathways. The development of tolerance to oxidative stress in children with compensated type 1 diabetes is indicated by the coordinated synthesis of reactive oxygen species and oxygen-dependent blood cell metabolism. In children with decompensated type 1 diabetes, it is indicated that the third stage of oxidative stress, which involves the depletion of insulin-producing β-cells, begins with a decrease in reactive oxygen species production, a decrease in the activation of the phagocyte oxygen-dependent metabolism, and incomplete phagocytosis mechanisms. The severity of metabolic problems in children with type 1 diabetes is influenced by the level of the antioxidant defense system's "respiratory explosion" of neutrophilic granulocytes

Enhancing Oracle Cloud HR Reporting Through AI-Driven Automation

The purpose of this study is to focus on AI, including ChatGPT, that is being used in Oracle Cloud HR reportingsystems. The system takes care of report generation and supports easier access for users to make critical HR decisions.The research points out the present imperfections of the system, the positive side of using conversational AI, and themajor difficulties in adopting it. It seems AI adoption enhances the HR reporting functions by increasing efficiency,better experiences, and quicker reactions in the cloud

Exploring the Convergence of Virtual and Physical Shopping Experiences in the Metaverse and Omnichannel Retail Through AI and Immersive Technologies

The integration of augmented reality, virtual reality, and virtual environment in retail sites. It looks intohow virtual and augmented reality and along with the aids, intervention, and integration of AI, in analyzed to determinehow they increase consumers’ engagement and satisfaction as well as the efficiency of operations. The researchfocuses on the emerging trends, issues, and prospects of deploying such technologies in retail. About current trendsand future development, it discusses ways in which the Metaverse might be useful for the realization of new, effectiveretail strategies