DEVELOPMENT AND VALIDATION STABILITY INDICATING HPTLC METHOD FOR DETERMINATION OF VILDAGLIPTIN AND METFORMIN HYDROCHLORIDE IN THE PHARMACEUTICAL DOSAGE FORMS

Objective: A simple, precise, and accurate stability indicating high-performance thin layer chromatography method was developed and validated of vildagliptin (VIL) and metformin (MET) in pharmaceutical dosage forms.Methods: In the present study, system suitability test, stress study, alkali hydrolysis, acid hydrolysis, neutral hydrolysis, oxidative stress degradation, dry heat degradation, wet heat degradation, photodegradation study has been used. In this method, optimization by changing various parameters, such as organic solvent and the composition of the mobile phase, acid or base modifier used in the mobile phase; by varying one parameter and keeping all other conditions constant. 10 µl of the stock solution for MET (500 ng/band) and 2 µl of the stock solution for VIL (100 ng/band) were applied to TLC plates. The final solutions were applied on the HPTLC plates and these were developed as per the optimized densitometry conditions.Results: From the spectra, it was observed that MET and VIL exhibited good absorbance at about 217 nm. Both the drugs showed degradation with additional peaks at Rfvalues of 0.16 for MET and with Rfvalues 0.81 for VIL respectively. The method was validated for linearity, precision, accuracy, limit of detection, limit of quantification, ruggedness, specificity, and robustness. Good separation was achieved by using the mobile phase Hexane: Methanol: Acetonitrile: Glacial Acetic Acid (2:3.5:2.5:0.2 v/v/v/v) with retardation factor (Rf) values of 0.22±0.01 for MET and 0.73±0.02 for VIL.Conclusion: A validated HPTLC method was developed for the determination of metformin hydrochloride and vildagliptin. The method is simple, quick, and can be applied routinely for the analysis of these drugs from marketed dosage forms

Comparison of slurry versus fixed-bed reactor costs for indirect liquefaction applications. A supplement to final report: Design of slurry reactor for indirect liquefaction applications

This work is a comparative evaluation of slurry reactors and fixed-bed reactors, with special emphasis on cost. Relative differences between slurry reactors and fixed-bed reactors have been pointed out in previous reviews; the differences pertinent to indirect liquefaction are summarized here. Design of both types is outlined

Securing the Digital Frontier: The Role of Technology in Social Medical Public Healthcare Security

The rapid expansion of digital connectivity within social medical public healthcare systems (SMPH) has fundamentally transformed the way patient care is delivered. However, it has also made sensitive data vulnerable to a wide range of cybersecurity threats. This study introduces and assesses a new hybrid deep learning model, GANA-AO, with the aim of improving real-time anomaly detection and threat prevention in SMPH. GANA-AO leverages the capabilities of Generative Adversarial Networks (GAN) and Autoencoders, enhanced by Adam optimization, to achieve outstanding accuracy and generalizability. Generative Adversarial Networks (GAN) produce authentic artificial data to supplement the training dataset and tackle the problem of imbalanced classes. On the other hand, Autoencoders acquire compact representations of normal data, aiding in the detection of anomalies by identifying deviations. Adam optimization effectively adjusts model hyperparameters, thereby improving performance. The efficacy of GANA-AO is demonstrated through our experiments conducted on the publicly accessible IoT-23 dataset. The model demonstrates an exceptional accuracy of 98.33% and a True Positive Rate (TPR) of 98.67%, surpassing the performance of baseline models by a significant margin. The results emphasize the capability of GANA-AO to enhance SMPH cybersecurity by promptly detecting and addressing malicious activities, protecting sensitive healthcare data, and ensuring patient safety. This paper not only introduces a robust technical solution but also highlights the vital significance of technology in safeguarding the digital boundaries of SMPH. By adopting cutting-edge approaches such as GANA-AO, we can establish a stronger and more adaptable system, promoting confidence and enabling patients in the digital era of healthcare. DOI: https://doi.org/10.52710/seejph.48

Next-Gen Security: Leveraging Advanced Technologies for Social Medical Public Healthcare Resilience

The healthcare industry is undergoing a significant change as it incorporates advanced technologies to strengthen its security infrastructure and improve its ability to withstand current challenges and  explores the important overlap between security, technology, and public health. The introductory section presents a thorough overview, highlighting the current status of public healthcare and emphasizing the crucial importance of security in protecting confidential medical data. This statement highlights the current difficulties encountered by social medical public healthcare systems and emphasizes the urgent need to utilize advanced technologies to strengthen their ability to adapt and recover. The systematic literature review explores a wide range of studies, providing insight into the various aspects of healthcare security. This text examines conventional security methods, exposes their constraints, and advances the discussion by examining cutting-edge technologies such as Artificial Intelligence (AI), Machine Learning, Blockchain, Internet of Things (IoT), and Biometric Security Solutions. Every technology is carefully examined to determine its ability to strengthen healthcare systems against cyber threats and breaches, guaranteeing the confidentiality and accuracy of patient data. The methodology section provides a clear explanation of the research design, the process of selecting participants, and the strategies used for analyzing the data. The research seeks to evaluate the present security situation and determine the best methods for incorporating advanced technologies into healthcare systems, using either qualitative or quantitative methods. The following sections elucidate the security challenges inherent in social medical public healthcare, encompassing cyber threats and privacy concerns. Drawing on case studies, the paper illustrates successful implementations of advanced technologies in healthcare security, distilling valuable lessons and best practices. The recommendations section goes beyond the technical domain, exploring the policy implications and strategies for technological implementation. The exploration of regulatory frameworks, legal considerations, and ethical dimensions is conducted to provide guidance for the smooth integration of advanced technologies into healthcare systems. Healthcare professionals are encouraged to participate in training and awareness programs to ensure a comprehensive and efficient implementation. To summarize, the paper combines the results, highlighting the importance of utilizing advanced technologies to strengthen the security framework of social medical public healthcare. The significance of healthcare resilience is emphasized, and potential areas for future research are delineated. This research is an important resource that offers valuable insights and guidance for stakeholders, policymakers, and technologists who are dealing with the intricate field of healthcare security in the age of advanced technologies. DOI: https://doi.org/10.52710/seejph.48

Design of slurry reactor for indirect liquefaction applications. Final report

The objective of this project is to design and model a conceptual slurry reactor for two indirect liquefaction applications; (1) production of methanol and (2) production of hydrocarbon fuels via Fischer-Tropsch route. A slurry reactor is defined here as a three-phase bubble column reactor using a fine catalyst particle suspension in a high molecular weight liquid. The feed gas is introduced through spargers. It then bubbles through the column providing the agitation necessary for catalyst suspension and mass transfer. The reactor models for the two processes have been formulated using computer simulation. Process data, kinetic and thermodynamic data, heat and mass transfer data and hydrodynamic data have been used in the mathematical models to describe the slurry reactor for each of the two processes. Available data from process development units and demonstration units were used to test and validate the models. Commercial size slurry reactors for methanol and Fischer-Tropsch synthesis were sized using reactor models developed in this report

Design of slurry reactor for indirect liquefaction applications. Quarterly technical progress report, January 1991--March 1991

The objective of this project is to design a conceptual slurry reactor for two indirect liquefaction applications; production of methanol and production of hydrogen fuels via Fischer-Tropsch route. The work will be accomplished by the formulation of reactor models for both the processes and use computer simulation. Process data, kinetic and thermodynamic data, heat and mass transfer data and hydrodynamic data will be used in the mathematical models to describe the slurry reactor for each of the two processes. The cost of current vapor phase reactor systems will be compared with cost estimated for the slurry reactor systems. For the vapor phase systems, upstream and downstream processing equipments may have to be included during cost analysis for a meaningful cost comparison

Analysis of atomic electron momentum densities: use of information entropies in coordinate and momentum space

The entropy maximization procedure has been extended to treat simultaneously the densities in coordinate and momentum space. The key quantity to be maximized is the sum of information entropies in complementary spaces rather than the entropy in one space alone. This modified procedure has been used to assess the quality of refined electron momentum densities for He, Be and H2. The momentum density which maximizes the entropy sum yields good estimates of Compton lineshape and related momentum space expectation values