Volume 12 | Issue 12 |

 Abstract

Traditional HPLC uses toxic solvents like acetonitrile and methanol, which pose risks to health and the environment. Green HPLC, adhering to green chemistry principles, emphasizes eco-friendly solvents such as ethanol, water, and supercritical carbon dioxide to minimize toxicity, waste generation, and energy consumption. Key strategies include solvent reduction, optimized isocratic elution, and miniaturized systems like micro- and Nano-HPLC, which lower solvent and sample volumes while maintaining analytical precision. Energy-efficient technologies and regulatory compliance further enhance sustainability. Applications extend to impurity profiling, stability testing, and quality control, offering an environmentally sound alternative without compromising accuracy.

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Sustainable HPLC, eco-friendly solvents, green chemistry, solvent reduction, micro-HPLC systems.

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This research paper explores the effect of marital status on women's labor force participation in Gujarat, focusing on how different industries interact with this dynamic. Through a comparative study across sectors such as manufacturing, services, and agriculture, the research seeks to uncover patterns in employment participation rates among married, single, widowed, and divorced women. The study draws on both primary and secondary data sources to assess the factors contributing to variations in participation rates. It also considers the role of cultural norms, family obligations, and government policies in shaping labor force engagement across different marital statuses. This research contributes to the understanding of gendered labor dynamics and provides recommendations for fostering greater inclusivity in the workforce.

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Effect, Marital, Status, Labour, Force, Participation, Women, Gujarat.

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Kushta is considered as one of the mahagada1, 2, 3. Kapha along with 6 other factors involves in pathogenesis of kushta4. Involvement of Kapha is comparatively predominant in all Kushtas. There are various types of Kushtas which are enumerated based on appearance of lesions on skin but in Charaka Samhita and Rasa Ratna Samucchaya the treatment of Kushta is explained based on doshas, in reference to this Kaphaja Kushta is taken into consideration for this study. Name of the disease is only for communication and easy understanding of a disease5. In Ayurveda all diseases are treated based on Doshas and Kushta is no exception to this. Hence, treatment of Kapha Dosha is given priority6. Classification of Kushta vary from author to author. To avoid confusion the symptoms explained by Acharya Charaka in context of Kapha dosha is selected7. As per classics in Kushta, panchakarma therapies are the treatment structure. If the disease is chronic, elimination therapies should be given and if disease is of recent origin, palliative therapies like abhyanga, lepa etc should be followed8. To avoid the reoccurance Shodhana, rakta mokshana, Bahya chikitsa like Lepa and timely administration of Sneha are to be followed9. If Kapha is associated with other Dosha, then Taila is considered as effective choice10. Saptaparna is one among the drugs mentioned by AcharyaSushrutha11 under the treatment of Kaphaja Kushta which has Tikta KashyaRasa12, Sara Guna, Ushna Veerya, Kushtaghna and Krimihara properties13. It is easily available in surrounding area and preparation of Saptaparna Taila is easy and cost effective. In this study the specific action of Saptaparna Tailain different Kapha predominant Kushtasis to be observed and effect of Saptaparna Taila in specific Kushta is noted. As per the study in 2017, the burden due to infectious and non-infectious skin disease has increased 53.7% over the past 3 decades. The high burden of skin and subcutaneous disease which is considered as 4th leading cause of disability worldwide hence, justifying the need for this study.

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Kaphaja Kushta, Abhyanga, Saptaparna Taila

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The advent of digital financial technologies has offered a promising solution to bridge this gap and extend financial services to previously underserved populations, including street vendors. Mobile banking, electronic payments, and digital wallets have emerged as powerful tools to overcome the barriers of traditional banking, offering a convenient and accessible means for individuals to manage their finances, make payments, and access credit. By leveraging the widespread penetration of mobile phones and digital infrastructure, digital financial inclusion initiatives aim to empower marginalized groups like street vendors, enabling them to participate more fully in the formal economy and improve their financial well-being. However, the realization of digital financial inclusion for street vendors is not without its challenges. Despite the proliferation of digital financial services, adoption rates among marginalized communities remain uneven, influenced by a myriad of socio-economic, cultural, and institutional factors. Street vendors, in particular, face unique hurdles, including low literacy levels, limited access to smartphones and internet connectivity, and distrust of formal financial institutions. Moreover, the complex regulatory landscape governing digital finance introduces additional barriers, impeding the effective implementation of inclusive policies and programs.

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Changing lifestyle,Consumption pattern, Consumer Behavior, Market Segmentation.

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Anti-cancer drug treatment is seriously affected by various undesirable properties such as poor solubility,narrow the rapeutic index and efflux transporter specificity.

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Abstract: This article explores the role of artificial intelligence (AI) in medical imaging interpretation, focusing on its applications in radiology. Radiological image interpretation is fundamental to medical diagnostics, aiding in the detection, diagnosis, and management of various diseases. Traditional methods rely on human intuition, but the complexity of images can lead to errors and variability in outcomes. The evolution of AI in medical imaging has been significant, with advancements in technology and methodology over several decades. Current technologies, such as deep learning algorithms like Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), offer solutions to longstanding challenges in image interpretation. Key studies demonstrate the transformative potential of AI in detecting abnormalities, segmenting anatomical structures, and aiding in treatment planning. However, challenges persist, including the need for standardization in data organization, policy considerations for data sharing, and concerns regarding model explainability and privacy. Achieving true "intelligence" at the human level remains a key consideration for the future of AI in medical imaging. Overall, this research highlights the critical importance of AI in advancing radiological interpretation, offering opportunities to improve diagnostic accuracy, efficiency, and patient outcomes.

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AI, CNNs, RNNs

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ATTENDANCE MANAGEMENT SYSTEM BY USING FACE RECOGNITION

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ATTENDANCE MANAGEMENT SYSTEM BY USING FACE RECOGNITION

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The discipline of pharmacogenetics examines how a medicinal intervention affects our genetic makeup. Nowadays, pharmacogenetics is generally heralded as having the potential to completely transform medicine. This quickly expanding discipline seeks to explain the genetic underpinnings of individual variations in drug response and to utilize that genetic data to forecast the safety, toxicity, and effectiveness of medications in either a single patient or a group of patients. It is also crucial for researching how several genes affect a drug's pharmacological function. In this we find and study about numerous components of the genes that affect the therapeutic of the drug. The majority of medications don't work as intended in the later phases. This could be because to an unforeseen side effect of the medication, which could be caused by different gene components. There are several phases of drug development where pharmacogenetic studies can be applied. Pharmacogenetics can be used in clinical research to stratify patients according to their genotype, which is correlated with their ability to metabolize. This promotes improved clinical trial results and the avoidance of numerous adverse medication reactions. In the global context, the advancement of pharmacogenetics and pharmacogenomics in Western Europe is extremely significant. Many research groups made up of basic and clinical researchers have been actively working in this subject for decades despite the typically minimal institutional backing. Their work had a global influence and cleared the path for additional research and pharmacy. In neurodegenerative illnesses, the use of genetic background as a predictor of therapeutic response is a relatively new and unexplored area. Even though sporadic degenerative illnesses have a complex etiopathogenesis, current understanding indicates that genetics is primarily responsible for directing the pathological events and even significantly altering the disease phenotype from patient to patient. Genes can function as regulatory factors that alter the strength and severity of pathogenic processes or the response to medication treatment, or they can work as susceptibility factors that raise the likelihood of disease development. Applying this knowledge to develop more targeted and efficient treatments and to customize therapy for each patient based on their genetic profile is the aim of pharmacogenomics.

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Advancing Neurodegenerative Disorder Treatment through Pharmacogenetics: A Personalized Medicine Approach

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This study presents a comparative analysis of fuzzy logic and traditional statistical methods for evaluating academic performance, focusing on the application of fuzzy membership functions. In traditional methods, such as the use of weighted averages, student performance is assessed based on fixed boundaries, often leading to rigid and sometimes unrealistic evaluations. In contrast, fuzzy logic provides a flexible framework that allows for the modeling of uncertainty and partial truth by employing membership functions that categorize performance levels like "Poor," "Average," "Good," and "Excellent" with varying degrees of membership. Using a case study of students' test and project scores, this research demonstrates how fuzzy logic-based evaluations can offer more nuanced and context-sensitive assessments compared to conventional statistical approaches. By analyzing the impact of different fuzzy rules and membership function shapes on the overall performance scores, the study highlights the advantages of fuzzy logic in capturing the complexities of academic performance. The results show that fuzzy logic provides a more adaptable and informative evaluation, especially when dealing with ambiguous or borderline cases, thereby offering a more realistic alternative to traditional methods.

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Fuzzy logic, statistical methods, academic performance evaluation, fuzzy membership functions, comparative analysis, test scores, project scores, partial truth, rule-based decision-making

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Physicists such as Sir Isaac Newton through the prism experiment, Rayleigh through the gas tube experiment, Tyndall through the scattering of light by particles in a colloidal solution experiment, C.V.Raman through the solution mixed water tube experiment have given explanations that due to the scattering and refraction of the light as it flows through the medium, the colors in the light are seen separately at different wavelengths. But according to this, there is no explanation for the fact that natural blue color in the sky appears to be much more diffused in space above the clouds and the sun, the colors yellow orange red are seen only on the clouds, the green color is not visible and many other information about the colors are not clear. The scattering and refraction of light described by physicists are some information related to the flow of light. But because the particles in the medium have different densities and the light passing through these particles has different intensities, the transparency translucency and opacity in the particles of the medium are the information about the effect of light. This report provides information on scientific explanations and experimental explanations of prism using black-and-white strips which confirms that the colors are indirectly arising because of the optical effects of white color when light passes through particles of mediums having different densities exposed to light and dark black colors when light intensity is low.

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Light & Dark, Inverse square law of light, Light Medium, Atmosphere Particles, Density of Medium, Intensity of Light, Light Effect, Optical effect, Transparent Prism, Total Internal Reflection/Critical angle, Spectrum, Primary -Secondary color wheel.

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