Journal Of Advanced Zoology
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Feasibility Of Using Super Absorbent Polymer And Nitrogen On The Yield, Biological Traits, And Nitrogen Percentage In Fields Pumpkin Seeds
Full text linkThis study performed to investigate the effect of nitrogen and moisture superabsorbent on yield, yield components, seed nitrogen and some biological traits in field pumpkin during two crop years in Kermanshah, Iran. The experiment was carried out as a split-plot based on randomized complete block design with three replications. The main plot factor were the application of moisture superabsorbent in various levels at 0 (control), 40, 80, 160 kg ha-1 ,respectively; and nitrogen fertilization at the levels of 0, 50, 100 and 150 kg ha-1was considered as sub-factor. Results illustrated that treatments significantly affected all traits except for fruit number. In most traits, there was an increasing trend when nitrogen levels increased, although N2 levels of 100 and 150 kg ha-1 were not significantly different.. In addition, increasing the moisture superabsorbent enhanced the mentioned traits
IoT Threat Mitigation: Leveraging Deep Learning for Intrusion Detection
Full text linkThe growth of smart gadgets connected via the Internet of Things (IoT) in today’s modern technology landscape has substantially improved our everyday lives. However, this convenience is juxtaposed with a concomitant surge in cyber threats capable of compromising the integrity of these interconnected systems. Conventional intrusion detection systems (IDS) prove inadequate for IoT due to the unique challenges they present. We propose and evaluate an intrusion detection system (IDS) based on a hybrid Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) model in this paper. The model is designed to capture both temporal and spatial patterns in network data, offering a robust solution for detecting malicious activities within IoT environments. The CNN-LSTM model displayed excellent accuracy, reaching 98% in both multi-class and binary classifications when trained on the UNSW-NB15 dataset. Furthermore, we explore the real-world applicability of the model through testing on Raspberry Pi, showcasing its effectiveness in IoT scenarios. The system is augmented with alert mechanisms, promptly notifying relevant parties upon intrusion detection. Our findings highlight the CNN-LSTM model\u27s efficacy in strengthening IoT network security
Anticancer Property Of L-Glutaminase Producing Actinomycete Streptomyces Albogriseolus Isolated From Estuary Of Uttara Kannada District Against Hela And HepG2 Cell Lines.
Full text linkL-glutaminase (L-glutamine aminohydrolase EC 3.5.1.2) is an extracellular hydrolytic enzyme having anticarcinogenic potential and is widely used in enzyme therapy especially for acute lymphocytic leukemia. L-glutaminase deaminates L-glutamine to glutamic acid and ammonia. In most tumors glutamine is the primary mitochondrial substrate and is present in circulating blood. It is a source of essential amino acid necessary for development of leukemic cells. The lack or depletion of L-glutamine leads to death of tumour cells. The marine environment is a potential source of bioactive secondary metabolites that provides pharmaceutically important compounds. The present study was focussed on to study the anticancer property of L-glutaminase producing actinomycetes isolated from estuaries of Uttara Kannada district of Karnataka. The isolates were screened for L-glutaminase production by qualitative and quantitative assay and the potent isolate was further subjected for MTT assay to determine its anticancer potential. The study showed 60% of isolates were positive for L-glutaminase production in Rapid plate assay and 85% of isolates were positive in semiquantitative assay. In quantitative assay the isolate Streptomyces albogriseolus exhibited high enzyme activity of 24.32+0.02 IU/ml. In MTT assay the isolate Streptomyces albogriseolus showed an IC50 value 102.0μg/ml in cervical cancer HeLa cells and IC50 value of 101.2μg/ml in HePG2 cells respectively, and could be used as good source of L-glutaminase.
 
Data Mining Techniques To Predict Student Academic Performance In Higher Education: Literature Review
Full text linkEducational system is significantly changing in today’s world. Recently, the New Education Policy (NEP)-2020 isstarted implementing in India. Students can have various options for getting education according to their choices and requirements. NEP-2020 is more student- centric rather than making them compulsory to get the degree with prescribed syllabus. AI has a major role in NEP-2020. Data mining technology plays a vital role in this new higher education system. As the Higher Education Institutions are growing rapidly, it is necessary for them to impart quality education for enrollment of students. Institutions can maintain educational quality by improving their results. This can be achieved by predicting student academic performance with the help of data mining algorithms.Classification, clustering, regression and association rule mining are the data mining techniques which can be implemented on student dataset to predict the final grade. This study focuses on prediction of student performance using classification and regression data mining techniques. The aim of this literature review is to study various data mining tools, algorithms and the important attributes that affect the student academic performance
Recommendations Of 14th Finance Commission Enabled States To Improve Their Fiscal Positions
Full text linkRecommendations of the 14th finance commission enabled States to improve their physical position by offering autonomy to implement development initiatives in the present research paper we are discussing recommendations of the 14th finance commission with new formula given by the constitution body which is giving way to the improvement in states fiscal positions
Analytics In Aesthetics: A Data-Driven Approach In Exploring The Beauty Products Sales In India And The Pivotal Role Of Customer Ratings In Shaping Product Quality
Full text linkThe beauty products and cosmetics sector in India has grown rapidly due to shifting customer preferences and a greater focus on personal grooming. With the continued growth in sales of beauty products, it is critical for firms looking to succeed in this cutthroat industry to comprehend the dynamics of customer ratings and how they affect the quality of their products. Firstly, this study identifies major trends, obstacles, and possibilities influencing the nexus between artificial intelligence and the Indian beauty goods market by utilizing the body of current literature and empirical data. Secondary data is used in this research, two Kaggle datasets—Amazon Beauty Product Sales Rating and Amazon Beauty Product Recommendation—are analyzed in this study. We seek to provide insight on the complex relationship between customer ratings and product quality and how these aspects affect the success of beauty goods in the Indian market by contrasting these datasets. The objective of this study is to stimulate advancements in the domain of beauty product sales in India by establishing a connection between theoretical research and operational implementations. In the conclusion, our summary of the literature seeks to guide future initiatives focused at leveraging AI to promote innovation, growth, and sustainability in the ever-changing Indian beauty goods sector. The research\u27s conclusions have ramifications for Indian consumers and producers of cosmetic products. This study has results for Indian consumers as well as cosmetic product manufacturers. Customer feedback may provide manufacturers with strategic insights to improve the quality of their products, and customers can use it to make well-informed decisions that suit their tastes. In the end, this research adds to the larger conversation on the dynamics of consumer happiness and product quality in India\u27s thriving beauty and cosmetics industry.
 
Patients With Type II Diabetes Mellitus At A Tertiary Care Hospital: A Prospective Study On Anti-Diabetic Drug Prescribing Patterns
Full text linkThe main aim is to study on prescribing patterns of anti-diabetic drugs for patients with type- II diabetes mellitus. Out of 457 patients screened, 426patients were enrolled according to inclusion and exclusion criteria. Among them 62.44% were males and 37.55% were females. The study found to be a higher incidence of diabetes among elderly patients, with a high incidence in the age group between 41-60 years (50.70%) and followed by 61‑80 years (19.24%). The study resolved that most of the patients were suffering from diabetes for 5 to 10 years, 221 (73.94%) of duration years followed by 1 to 5 years, 94 (22.06%). A total of 1565 drugs were prescribed in the overall study period. 68.62% were diabetic drugs, 13.41% hypertensive drugs, 07.85% NSAIDs, 07.66% asthmatic drugs, 03.57% antidepressants, and 04.40% supplements of drugs. The study resolved that drugs were prescribed as monotherapy was 49.76%, two drug therapy were 36.61%, three-drug therapy were 08.45% and four-drug therapy was 05.16%. In this study, 426 anti-diabetic drugs prescribed, among that, the physician’s most well-liked single-drug therapy more than multiple drug therapy and also the most often prescribed category was Biguanides category of anti-diabetic agents. Among Biguanides, Metformin was the foremost often utilized anti-diabetic drugs. The foremost prevalent combination of the drug was a two-drug therapy of Biguanides +sulfonylureas, among these combinations, Metformin + Glimipride was the foremost often utilized anti-diabetic drugs. Followed by 3 drug therapy were Biguanides +sulfonyl ureas+ thiazolidinedione and 4 drug therapies were Biguanides + sulfonylureas + DPP 4 inhibitors + thiazolidinedione.Pharmacists can contribute drastically to promote the rational use of medicines, even in resource-limited settings. This, of course, requires strong collaboration between different institutions and commitments of the pharmacists to the cause. Pharmacist medication review, patient counseling and telephone follow-up can limit the Adverse Drug Reactions. Medication discrepancies before and after discharge were common targets of intervention
A Robust Search Method Using Features To Determine Combined Keywords On Cloud Encrypted Data
Full text linkUsers are more comfortable trusting their sensitive information to the cloud as its security continues to improve. However, when there are several encrypted files, each with its own set of keywords for indexing, the storage overhead grows exponentially, and search efficiency suffers. Therefore, this work provides a technique for searching encrypted cloud data that makes use of features to match joint keywords (FMJK). Joint keywords are generated by randomly selecting a subset of the data owner\u27s non-duplicated keywords choice among the documents\u27 extracted keywords; together, these keywords form a keyword dictionary. Every combined keyword matches with a document\u27s feature as well as a query keyword, making the former\u27s result considered a dimension of a document\u27s index with the latter\u27s result considered a dimension about the query trapdoor. Its BM25 method is then utilized for arranging the top k results by the inner product between the document index and the trapdoor
Implant Macrodesigns And It’s Effect On Crestal Bone Loss: A Report Of Two Cases
Full text linkImplant is a prosthetically driven surgical treatment modality which replaces the missing tooth.
Cylindrical implants which were popular earlier resulted in loss of crestal bone and subsequent implant failure, which led to the development of threaded features converting occlusal loads into a more favourable compressive loads at the bone interface. In the recent era of implantology, most of the common implant thread design marketed are V- shaped thread design. However, because of generation of higher shear forces generated by V-shaped thread design, modification has been made in the form of square, reverse buttress and buttress where the axial load is dissipated through compressive loads while a V-shaped thread design transmit axial force through a combination of compressive, tensile, and shear forces which may have an influence of crestal bone loss. Thus, the present case report intends the use of two thread designs (V-shaped and buttress thread design) and its influence on crestal bone loss using CBCT radiographic analysis
Formulation And Evaluation Of Transdermal Herbal Gel Formulation Containing Ethanolic Extract Of Zingiber Officinale
Full text linkBecause of widespread cultural approval. Strong acceptance by human body, and reduced occurrence of side effects, about 75-80% of the worldwide population, especially in less developed areas, continues to favor herbal remedies as their main option for fundamental healthcare. Herbal treatments comprise botanical or plant-based components and serve to address injuries, infections, and ailments. They are also employed for preventive health measures and to facilitate the recovery process. This research explored the possible therapeutic advantages of Zingiber officinale, commonly recognized as ginger, a naturally occurring anti-inflammatory substance with extensive culinary use. Numerous investigations have highlighted the advantages of ginger in managing conditions such as morning sickness, chronic dyspepsia, hypoglycemia, risk factors for heart disease, chemotherapy-induced nausea, and menstrual discomfort. Ginger ethanolic extract preparations in the form of transdermal gel consist of different concentrations and combinations of Carbopol 934 and Carbopol 940. All gel formulations exhibited favorable characteristics such as Spreadability, uniformity, Viscosity, and extrusion. Among these compositions, formulation F3, which contains Carbopol 934, displayed the highest release of the active ingredient in vitro and the ethanolic extract demonstrated significant anti-inflammatory effects in vitro