Volume 12 | Issue 1 |

 Abstract

??? ??? ???? ????????? ?? ??? ??? ?????????? ?????? ???? ?? ?????? ?????? ????? ?? ???????? ?? ??????? ???? ?? ???????? ????????? ?? ????? ??? ????????? ?????? ?? ????? ???? ?? ???????? ???????? ?? ?????? ???????? ???? ?? ???? ????? ?? ??? ?? ??????? ???? ??? ??????? ? ???? ?? ?????? ?? ????????? ?? ???? ????? ?? ???? ?? ?? ???????? ????? ??? ???????? ?? ???????? ???????? ??? ??????? ?? ?? ??????? ?? ???????? ???? ???? ?????, ????????? ?????? ?? ???????? ????? ?? ????? ??? ?? ?????? ???? ????????? ?? ?????? ???? ???? ?? ?? ????? ????????? ?????????? ?? ??? ???????? ??????? ?? ??????? ??????? ? ???????? ??? ??? ??? ?? ????? ?? ?????????? ?????????? ????????? ??? ???????? ?????? ?? ????? ?? ?? ?????? ?? ???? ??? ???? ?????? ?? ??????????? ?????? ???? ?? ???? ???? ???? ??? ????? ????? ?? ?? ?????? ???????? ??? ??? ????? ??? ??????? ?? ???????? ???????? ?? ????? ?? ????? ?????? ????? ?????? ????? 14 ??????? ?? ????????? ??? ?? ?? ??? ????? ???? ???? ??? ''???? ????? ?? ?? ???? ?? ???????? ????? ???? ??? ???? ?????????? ?? ?? ?? ??..... ????? ?????, ????? ???? ??? ?? ??? ??????? ?? ??????? ?? ?? ?? ???? ???? ???? ?? ???? ????? ??..... ????? ??? ??? ???????? ?? ???? ?? ?????? ?? ?????????? ?????''

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???? ?????: ?????? ??????? ????????, ????? ???????, ?????????, ?????? ????????, ?????? ?????, ???????? ?? ??????????

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Herbal plants have long been used to enhance human health; they have grown increasingly popular across the world as medications, alternative and complementary treatments, meals, vitamins, cosmetics, and, unexpectedly, as healthcare products. The complexity of herbs and extracts, together with their distribution to different markets and compliance with different regulations, has led to an increased demand for analytical methods that can accurately identify and standardize these products while also detecting adulterants and pollutants. Herbal samples raise various kinds of complications for customs laboratories, including worries regarding quality, safety, and even illegality. adopting an appropriate analytical technique between the wide range various options available, such as physical, chemical, biological, microscopic, or macroscopic technologies. There is more discussion of HPLC, GC, photometric techniques, UV, IR, MS, and NMR.

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Herbal drugs, analysis of herbal drug, Thin layer chromatography, HPLC, gas chromatography, UV visible spectroscopy, IR spectroscopy

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Sentiment analysis and emotion recognition play a pivotal role in understanding human communication and interaction, with applications spanning from customer feedback analysis to human-computer interaction. In recent years, deep learning techniques have demonstrated remarkable success in these domains, particularly when incorporating speech features and transcriptions. This review delves into the state-of-the-art systems that employ deep learning for sentiment analysis and emotion recognition, focusing on those leveraging both speech features and transcriptions as complementary modalities. The review begins by providing an overview of the theoretical foundations of sentiment analysis and emotion recognition and the evolution of deep learning in these fields. It highlights the significance of multimodal approaches that fuse speech features and transcriptions to improve accuracy and robustness. The paper discusses various deep learning architectures, including recurrent neural networks (RNNs), convolutional neural networks (CNNs), and more recent models like transformer-based architectures, and their utilization in sentiment analysis and emotion recognition tasks. Special attention is given to pre-trained models and transfer learning techniques that have proven to be highly effective in reducing the need for large labeled datasets. The importance of benchmark datasets and evaluation metrics for assessing the performance of sentiment analysis and emotion recognition models is addressed. The paper concludes with an exploration of potential future directions, including enhanced multimodal fusion techniques, cross-modal sentiment analysis, and the integration of these models into real-world applications. By reviewing and synthesizing the current state of deep learning-based sentiment analysis and emotion recognition systems using speech features and transcriptions, this paper aims to provide insights into the progress made, challenges faced, and the promising avenues for future research in these critical fields of natural language processing and affective computing.

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Feature selection, Speech emotion recognition, deep learning, deep neural network, deep Boltzmann machine, recurrent neural network, deep belief network, convolutional neural network

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Nyctanthes arbor-tristis (NAT) also known as Parijata or Harsinghar is an Indian traditional plant of great importance. It has been used in Ayurveda, Siddha and Unani system of medicine for treatment of various infectious and non-infectious diseases. Each part of the plant has some medicinal value and is used for various pharmacological actions such as anti-arthritic, antispasmodic, antibacterial, anti-inflammatory, immunostimulant, antidiabetic, hepatoprotective, antioxidant, antimicrobial, anthelminthic, antileishmanial, anti-pyretic, anti-allergic, antiviral and CNS depressant. The phytochemical analysis of plant revealed presence of flavonoids, tannins, saponins, glycosides, alkaloids, steroids and phenolic compounds which are responsible for these pharmacological actions of the plant. The chemical drugs being used for treating various ailments are costly and moreover have various side effects. These drugs can be replaced by the herbal plants which have no such side effects and are cost efficient, and one such alternative can be NAT. This paper reviews recent researches, importance, applications, methods of propagation and future prospects of NAT. Particular emphasis has been given towards the applications and methods of propagation of the plant.

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nyctanthes arbour, tristis, Indian traditional plant, Morphological Characters, medicinal value, side effect, etc

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Creative Commons Attribution 4.0 and The Open Definition

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Df: Degree of freedom, NS : Not significant, S: Significant

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Mirabegron opened a new period in the treatment of hyperactive bladder( OAB) For the first time croakerealing with OAB have an effective volition to the pharmacological dependence of the remedy for this complaint, the antimuscarinic medicines. This first- by- class, potent ?3- adrenoceptors agonist has lately entered blessing by nonsupervisory authorities in Japan, United States and Europe, grounded on the favourable efficacity- tolerability profile demonstrated in multiple randomized, transnational, controlled trials, both short and long- term. Mirabegron is a novel, formerly- daily, orally active, first- in- class, potent ?3- adrenoceptor agonist lately approved by Food and Drug Administration for hyperactive bladder remedy. Phase II studies and four large- scale phase III transnational randomized, controlled trials have supported the efficacity and tolerability of mirabegron & vibegron in the clinical trial setting of cases with hyperactive bladder for over to 12 weeks of remedy and in the long term( 12 months). The reported prevalence and inflexibility of treatment- emergent and serious adverse goods were analogous to antimuscarinics. Vibegron is, in discrepancy to other OAB medicines, veritably picky and leads to a lower degree of unwanted side goods. Vibegron is set up to be a substrate for CYP3A4 in vivo, but doesn't actually induce or inhibit any of the cytochrome P450 enzymes and is therefore less likely to take part in medicine - medicine relations( DDI). Then vibegron differs from the former hyperactive bladder medicine mirabegron, which was known to be associated in colorful medicine - medicine relations.

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Mirabegron , vibegron , antimuscarinic Agent , ?3- adrenoceptor Agonist ,Overactive Bladder

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Stress is a universal phenomenon that essentially manifests itself in humans as a result of pressure emanating from several experiences or challenging situation. Delay in job completion, deterioration of the power of organization and planning, increase in error rate during manipulative and cognitive task, depression and feeling of helplessness and over sensitivity are the major impact of stress on the productivity of professionals. In order to minimize stress, delegating some work, share burden with colleagues, leave and time off work with family and loved ones, as well as reducing work overtime ranked highest as strategies for stress management. Based on the findings, it was concluded that stress has a great impact on the professionals and thereby affects the level of productivity. It was therefore recommended that professionals should exhibit self-control and good self-esteem; engage in continuous professional development on skills for better organization, integration of work within specified project constraints and delegation of assignments, authority and breaking work into manageable parts so as to be able to cope with stress. An attempt has been made through this research paper to know the reasons of stress among the employees and the ways used by employees to cope with the stress generated at workplace. In the second part of the article some stress coping strategies, such as gaining social support, taking advantage of the programs targeting on stress coping, reduction of stress in the workplace by improving work environment and work organization, are explained.

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Stress, Stress Management, Industries, Workplace, Factors

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The growth trend of luxury cars in the global market has been marked by a steady rise in demand driven by economic prosperity, changing consumer preferences, and expanding high-net-worth populations. It is in this context, that a modest attempt has been made to present the growth trend of luxury cars in the global market, the evolving scenario in India's luxury car market. This study reveals that the global luxury car market demonstrated that Mercedes-Benz leads in global market share, increasing from 25.2% in 2020 to 31.2% in 2022. BMW, the second-largest player, experiences a slight decline, while Audi faces a decrease in market share. The luxury car market is anticipated to generate revenue of US$19,500m by 2024, with the United States contributing the most. However, in India, BMW dominates the luxury car market with a market share increase from 40.7% in 2020 to 48.0% in 2022, despite a decline in unit sales. Mercedes-Benz maintains a significant market share, while Jaguar Land Rover and Volvo experience declines in both market share and unit sales. The total luxury car market in India sees a decline in unit sales from 27,196 in 2021 to 16,467 in 2022, reflecting challenges and changes in the Indian luxury car segment.

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Luxury cars, automotive industry, Buyer preferences, impact of global brands, technological advancements.

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This paper delves into the realm of behavioural finance, exploring the psychological and emotional factors shaping investment decisions. It challenges the traditional assumption of rational decision-making in financial markets, asserting that individuals are influenced by emotions. Cognitive biases and social dynamics the study underscores the profound impact of emotional biases, varying risk perceptions, and cognitive biases on investor choices through a mixed-methods approach combining existing literature with primary data collected through surveys. Factors influencing investment choices, providing a foundation for interventions and educational resources aimed at fostering informed and rational investment practices in an evolving financial landscape.

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Behavioural, Finance, Savings, Investment, wealth maximization, capital safeguarding, financial institutions, emerging markets.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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Creative Commons Attribution 4.0 and The Open Definition

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Mangal

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