Journal Of Advanced Zoology
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Phyto-Pharmacological Effects of Medicinal Plants for the Treatment of Depression
Get PDFBackground: Depression is a serious mental illness that has a significant impact on suicidal thoughts. It is ranked as the fourth most significant mental disability globally. Current research is concentrating on increasing the effectiveness of conventional treatments due to highly undesirable effects. Natural goods, herbal plants, and phytochemicals offer a wide range of study opportunities for antidepressant treatments.
Objective: The present study aim at the review of various photo-Pharmacological effects of medicinal plants for the treatment of depression in a traditional approach
Methods: The methodology includes a thorough search of every electronic source to gather all information on herbal plants, pharmacological effects, and antidepressant mechanisms of phytochemicals from the year 2000 to 2023.
Results: Different plant metabolites were shown to have powerful antidepressant effects, including polyphenols (phenolic acids, flavonoids, lignans, and coumarins), alkaloids, terpenes and terpenoids, saponins and sapogenins. Major group of phytochemicals crucial in evaluating antidepressant effectiveness includes piperine, diterpene alkaloids, berberine, hyperforin, riparin derivatives, ginsenosides, and -carboline alkaloids. A great inhibitor of monoamine oxidase enzymes, an elevation in brain 5-HT and BDNF (Brain-Derived Nicotinic Factor) levels and modulatory effects on the hypothalamus-pituitary-adrenal axis were all demonstrated by piperine. Numerous studies have demonstrated berberine\u27s serotonergic, noradrenergic, and dopaminergic effects, demonstrating the importance of phytochemicals from various sources in the treatment of depression.
Conclusion: All of the medicinal plants listed in this study\u27s thorough review indicated the ability to cure depression using various traditional methods and a variety of processes. In order to discover potential natural, semi-synthetic, or synthetic antidepressants with fewer side effects, the structure-activity relationship of extremely effective antidepressant phytochemicals was evaluated. For verification of natural antidepressant effectiveness and fulfilment of their safety profile, more clinical investigations are also required
Cultivating Prosperity: Analyzing Marketing Challenges Encountered by Pomegranate Farmers in Tumkur District
Get PDFThis study presents an overview of the demographic characteristics and marketing practices of pomegranate farmers in Tumkur District, Karnataka, India. Data was collected through surveys and interviews conducted among male and female farmers, with a focus on age, landholding, education, income, and marketing practices. The findings reveal a predominantly young farming population, with the majority falling within the 31-45 years age group. The data also shows that both male and female farmers mainly possess small landholdings, typically between 2-5 acres. This suggests a prevalence of smallholder farming in the region. Regarding education, while primary education is the most common level of education among both genders, there is a significant portion of female farmers with no formal education, indicating potential disparities in educational opportunities between genders. Income distribution analysis indicates that the majority of farmers earn between INR 20,000 - 30,000 per month, with male farmers slightly earning more than their female counterparts. Analysis of marketing practices reveals a preference among both male and female farmers to sell their produce locally, with direct selling to consumers being more common among female farmers. Meanwhile, male farmers tend to engage more with wholesalers. The study also highlights a relatively low usage of online platforms for sales among both genders, suggesting an area for potential improvement in leveraging technology for marketing. This study provides valuable insights into the demographic profile and marketing practices of pomegranate farmers in Tumkur District, which can inform policy interventions and agricultural development programs
Prediction of neurological diseases using data mining
Get PDFData mining is one of the stages of acquiring knowledge in a database to collect useful information. Data mining is a new field that has various applications and it is known as one of the top ten sciences affecting technology. Data mining analyzes databases and massive data sets in order to discover and extract knowledge, and machine (and semi-machine) mines. Such studies and explorations can actually be considered the extension and continuation of the ancient and ubiquitous knowledge of statistics. The major difference is the scale, breadth and variety of fields and applications, as well as the dimensions and sizes of today\u27s data, which require machine learning, modeling, and training methods. In the 1960s, statisticians used the term "Data Fishing" or "Data Dredging" to discover any relationship in a very large volume of data without considering any assumptions. After thirty years and with the accumulation of data in databases, the term "Data Mining" became more popular around 1990. The purpose of this research is to predict brain and nerve diseases using data mining algorithms. The purpose of this research is to help medical professionals to predict disease. In this research, after data preparation, disease prediction has been attempted using large matrix methods and data mining techniques. By examining the new vector, we can find out which of the diseases in the matrix will be closer to this new disease with new symptoms using the rows of the matrix. The conducted research is one of descriptive-analytical and applied studies. In this research, we used different meters such as Jacquard distance, cosine similarity L1-norm and cosine similarity L2-norm implemented a program using Python software to predict brain and neurological diseases. The algorithm implemented by Python software, the doctor enters the symptoms of the patient and the output of the program shows three diseases close to the input symptoms for each meter, and finally all the meters are compared and the meter that has a weaker result is determined each time it is run. The advantages of each of these meters are explained below. 
A review on IoT based precision irrigation planning and scheduling
Get PDFGlobal warming and climate change are warnings showcasing water crisis. At the same time ever growing population is ultimatum to the food security. In span of such times, world has to be made a sustainable habitat. It is only possible when each ounce of resources is being measured and used judiciously. Maximum responsibility is on farmers and researchers of the world. In times of advanced technologies, Internet of Things (IoT) has surfaced as a saviour. IoT based systems have been stated as success in monitoring and control mechanisms. Thus, this paper was intended to review the control strategies and monitoring systems based on IoT. The literature incorporates basic information as well as recent trends in the field of irrigation management based on IoT
Combinde And Comparative Biochemical And Behavioral Assessment Of Delphinium Denudatum And Amaranthus Spinosus For Anti-Stress, Nootropic And Antioxidant Activities
Get PDFBackground: Stress defined as an imprecise reaction of the body to any kind of stimuli on it and disturbs normal physiological condition, threatened homeostasis. Stress causes decline in health by disturbing behaviour, physical and hormonal system of the body.
Methods: The test drugs Dephinium denudatum root and Amaranthus spinoses leaves were defatted with petroleum ether (60-80 0C) and then extracted with hydroalcohlic solvent (Ethanol 95%, v/v: water, 1:1) by soxhlation process. The hydroalcohlic extract of both the drugs singly and in combinations was evaluated for experimental activity in Wistar albino rats in the doses of 200 and 400 mg/kg by using different anti-stress tests like Swimming endurance and post swimming muscle coordination test (physical stress), Immobilization stress test and Anoxia stress tolerance test, antioxidant activity by DPPH, Reducing power methods, Nitric oxide scavenging activity, and H2O2 assay method and nootropic activity was done by Elevated plus maze test, Morris water maze test and estimation of Acetylcholine esterase level.
Results: In the dose dependent manner, both the hydroalcohlic extracts and combination of the higher doses produced the anti-stress activity, antioxidant and nootropic activities.
Conclusion: Hydroalcohlic extracts of Dephinium denudatum root, Amaranthus spinoses leaves and combination of both the drugs may act as anti-stress, antioxidant and nootropic agents in rats. Amaranthus spinoses was found to be more effective compare to the Dephinium denudatum
Analytical Development And Validation Of Stability-Indicating Method For Estimation Of Amantadine In Pharmaceutical Dosage Forms By Using RP–UPLC
Get PDFA simple, Accurate, precise method was developed for the estimation of the Amantadine in bulk and pharmaceutical dosage form. Chromatogram was run through ACQUITY UPLC BEH C18 Column, 1.7 µm, 2.1 mm X 50 mm. Mobile phase containing 0.1% AmmoniumFormate: Methanol taken in the ratio 73.6 (%v/v) and 26.3 was pumped through column at a flow rate of 0.28 ml/min. Temperature was maintained at 29.21°C. Optimized wavelength selected was ACQUITY TUV ChA 219 nm. Retention time of Amantadine was found to be 1.814 min. %RSD of the Amantadine was found to be 0.4%. %Recovery was obtained as 99.94% for Amantadine. LOD, LOQ values obtained from regression equations of Amantadine were 0.05, 0.15. Regression equation of Amantadine is y = 52995x + 2524.1. with regression coefficient value is found to be 0.99. Retention times were decreased and that run time was decreased, so the method developed was simple and economical that can be adopted in regular Quality control test in Industries.  
Comparative Study Of Phyllanthus Niruri, Sphaeranthus Indicus And Tridax Procumbens With Respect To Qualitative & Quantitative Estimation Of Phytochemicals
Get PDFThe creation of new therapeutics and the promotion of health are the main goals of current phytochemical research. Thus, this study compares three different plant & their parts with chloroform & ethyl acetate solvent for qualitative & quantitative determination of phytochemicals. Phyllanthus niruri (Root and aerial part), Sphaeranthus indicus (Root and Stem) and Tridax procumbens (Root and Flower) were utilized for the study. Plant material was then exposed to extraction specifically by chloroform & ethyl acetate. The phytochemical test & total flavonoid content by AlCl3 method was then determined. Results showed that Sphaeranthus indicus (Stem) extract suggested the presence of carbohydrate, flavonoid, protein & diterpene. For ethyl acetate extract almost similar results were obtained with addition of alkaloid. The root extract of Sphaeranthus indicus showed the presence of carbohydrate & alkaloid only. The chloroform extract of the same was completely devoid of any phytochemical. In Tridax procumbens (Flower) extract the chloroform extract noticed to have chloroform, flavonoid, proteins, diterpenes. The ethyl acetate extract of the same contain additionally sterol & tannin along with previously reported phytochemicals. Total flavonoid content was found to be 2.72 mg/100mg in Aerial part of Phyllanthus niruri. For the stem part of Sphaeranthus indicus total flavonoids content in chloroform & ethyl acetate extract were found to be 1.30 mg/100mg & 2.87 mg/100mg respectively. From the above obtained results, it can by hypothesized that comparatively grater amount of phytoconstituents are present in aerial part of plants as compared to root. Also, it can be seen that in each & every case, the ethyl acetate extract yielded more amount of phytoconstituents as compared to chloroform. The fact that the aerial parts of plants in the current study contained the greatest concentration of phytochemicals suggests that plant extracts may have pharmacological effects so further research should be done to test its safety & efficacy
Content Based Filtering And Collaborative Filtering: A Comparative Study
Get PDFCollecting data from users is a frequent practice for websites to improve various aspects of their products and services, such as performance, usability, and security. Monitoring user activity on websites helps to comprehend visitor behavior and assess the impact of the site. Numerous applications involve the collection of user data by websites, enabling the prediction of user preferences. This, in turn, facilitates personalized content recommendations. Recommender systems serve as a mechanism to propose analogous items and concepts tailored to an individual\u27s unique mindset. Fundamentally, there are two categories of recommender systems: Collaborative Filtering and Content-Based Filtering. This paper provides a comparative study of collaborative filtering and content-based filtering.
 
A Machine Learning Techniques Used For Students’ Academic Success Predic-tion
Get PDFYoung generation of every country is the future of the country. The country with the highest GER in higher education will be more successful in all the terms (Keller, K.R.I. ,2021). India’s GER in higher education in 2018-19 was 26.3, and in 2019-20 is 27.1.It is observed from statistics that it is which is increased. Students are enrolling for higher education but many fails to complete it (Ministry of Education, Government of India, AISHE Report 2019-20). This leads to the need of identification of reasons of students’ academic success or failure. If we predict students’ academic success or failure at the initial stages of their graduation period will help to take preventive measures and increase passing percentage. Student academic success is one of the criteria for accessing quality of the educational institutions, and it is one of the crucial components. There are different aspects of students\u27 academic success, such as exam-oriented, employment-oriented, and higher study-oriented
Object Detection In Video Streaming Using Machine Learning And Cnn Techniques
Get PDFObject detection is affecting a lot of areas where images play a crucial role. It therefore becomes necessary to address this issue by building effective image detection in video streaming systems, that can detect such traces of objects that may cause harm for flight landing and take-off, either by identifying the object type, detecting image size or evaluating under different environmental conditions . There are a number of techniques like Background subtraction, similarity matching, convolutional neural networks, end-to-end feed forward neural network to detect objects in video streaming but with limitations of correctly identifying object in live video steam under illumination changes, non-stationary backgrounds and similar looking background pixels and foreground pixels form a complex background. Hence it is now required to develop system that requires less training and no human intervention for object detection in live video streaming. For this study we have taken the application of runways where providing minute object detection is necessary for flight safety