Mapana Journal of Sciences

Editorial

Manoj Balachandran — Sat, 09 Nov 2024 00:00:00 +0000

Boron Deficiency Detection in Banana Leaves using Skip-Connected Convolutional Neural Network (SC-CNN)

Sunitha P, Geetha Kiran A; Uma, Channakeshava, Suresh Babu — Sat, 09 Nov 2024 00:00:00 +0000

Plants rely on a delicate balance of 16 essential nutrients to thrive, with macronutrients being crucial for robust growth, while micronutrients play a vital role despite being needed in smaller quantities. Insufficient nutrient levels can stunt plant growth, hinder flowering, and reduce fruit yield. Accurate diagnosis of these deficiencies is paramount for farmers to address issues effectively, ensuring the cultivation of nutrient-rich crops and maximizing yield. Bananas, a globally significant fruit crop known for its high nutritional value, require meticulous nutrient management to thrive. Micronutrients like Boron, are critical for maintaining hormonal equilibrium in banana plants, with deficiencies often manifesting visibly on leaves. This study proposes a deep-learning approach to detect Boron deficiencies in banana leaves. The developed CNN model with Skip Connections (CNNSC), comprising thirteen layers, outperforms established architectures like VGG16, DenseNet, and Inception V3. Evaluation metrics showcase the model’s effectiveness, achieving a remarkable accuracy of approximately 95%.

Advancing Agriculture with CNN for Timely Leaf Disease Detection and Enhance Crop Production

D Divya, K Ananthajothi, Maya Eapen — Sat, 09 Nov 2024 00:00:00 +0000

The Indian economy relies heavily on the agricultural sector. Improving crop and plant yields is crucial because 60% of India's labour force is involved in this industry. It took until recently for Indian farmers to see increases in both production and selling prices due to a variety of crop-related ailments. Modern picture identification systems, such as Convolutional Neural Networks, are able to make precise and rapid diagnoses. In order to correctly detect plant diseases, this article utilizes pre-trained models that are built on convolutional neural networks (CNNs). Tuned-hyper-parameters for ResNet50, DenseNet121, VGG16, and Inception V4 in particular. We also compared our results to those of other similar, state-of-the-art investigations. We can see that DenseNet-121 gets a success rate of 99.81% from the validation data. This paves the way for artificial intelligence solutions for smallholder farmers and shows that convolutional neural networks (CNNs) can classify plant illnesses.

Knowledge Graph Generation for Research Articles

Dhanalakshmi Teekaraman, Tamizhselvi S P — Sat, 09 Nov 2024 00:00:00 +0000

The increasing amount of web data has made accessing and processing information efficiently challenging. One solution is to transform the unstructured data into a machine-readable structured format like a knowledge graph. This paper addresses an information retrieval system that enables users to formulate queries in natural language and obtain pertinent information from a knowledge graph specific to a particular domain. Understanding any unstructured data is tougher than structured data. Inferring knowledge from any research article is difficult for naïve users. To resolve this, we propose to create a knowledge graph for the same. Our system utilizes natural language processing techniques to analyze user queries, generating SPARQL queries to retrieve pertinent data from the knowledge graph. We leverage state-of-the-art knowledge graph models to assess the system's precision, recall, and F1 score. The result shows that the proposed model can effectively retrieve relevant information with an average precision of approximately 95%.

Synthesis and characterization of some novel sulfonate and carbonate prodrugs of Atovaquone, accomplished with better solubility profile

Sanjay Sukumar Saralaya, Shashiprabha, Shridhara K — Sat, 09 Nov 2024 00:00:00 +0000

Atovaquone is an acclaimed anti-malarial drug with considerably poor water solubility and hence has low bioavailability. To overcome this issue, a few novel prodrugs of Atovaquone were introduced in this work. In line with this, two prodrugs of Atovaquone having sulfonate and carbonate molecular framework extension were disclosed. This work encapsulates the synthesis, characterization, solubility profile and feasibility of hydrolysis of disclosed prodrugs. These prodrugs have shown better water solubility than the parent drug, Atovaquone. Hence, prodrugs of the present invention can contribute to increasing the bioavailability and clinical efficacy of Atovaquone. It is worth perusing further in-vivo studies with these prodrugs to solidify them for routine clinical practices with safe and efficacious drug delivery.

Isolation, characterization, and synthesis of some process-origin impurities of Atovaquone, a renowned anti-malarial drug

Sat, 09 Nov 2024 00:00:00 +0000

To improve the yield of Atovaquone, we explored the chemical consequences occurring during its step-wise synthesis (process chemistry). Hence, the entire focus of this initiative was aimed towards the isolation of a few major process origin byproducts that were formed during the two-step reaction process. The synthesis of Atovaquone was done by the use of commercially viable key starting material trans-4-(4-chlorophenyl) cyclohexanecarboxylic acid for the decarboxylative coupling reaction with another key reactant 2,3-dichloro-1,4-naphthoquinone to obtain the intermediate. The isolated intermediate was hydrolyzed to obtain Atovaquone. From the mother liquors (MLRs) of each stage, we were able to isolate a few major process origin impurities and characterize them with the assistance of spectral data. Additionally, we even synthesized some of the impurities and compared them with the ones that were isolated from the MLRs. In this work, we report the experimental aspects and results related to six process-origin impurities of Atovaquone.

A characterization of the Total Graph of Interval Graphs and Proper Interval Graphs

Athul T B, G Suresh Singh — Sat, 09 Nov 2024 00:00:00 +0000

An asteroidal triple is a stable set of three vertices such that each pair is connected by a path avoiding the neighbourhood of the third vertex. Let G be a graph with vertex set V (G) and edge set E(G), the total graph T(G) of G has vertex set V (G)∪E(G) and two vertices in T(G) are adjacent if and only if they are adjacent or incident in G. In this paper, we try to characterize the total graph of interval graphs and proper interval graphs.

Review paper on Artificial intelligence assisted diagnosis for blood cancer using machine learning

Jain Joseph, Sherimon P C, Vinu Sherimon — Sat, 09 Nov 2024 00:00:00 +0000

This article guides a review platform that allows the evaluation of artificial intelligence-assisted diagnosis for blood cancer using machine learning. Advanced medical and technology-based research has fuelled the adoption of the latest technologies for the sake of advancement in medical science application and overall improvement in the detection, diagnosis, prevention and treatment of diseases. AI technology is being used widely in medicine, the economy and daily life; in medicine, artificial intelligence is used mainly for treatment, diagnosis and prediction of disease prognosis. This review effectively highlights the wide-ranging applications of AI in medicine, with a specific focus on its contribution to treatment, diagnosis, prognosis and prediction.

Demographic implementation of Snares: A Review on Wildlife Hunting and Poaching

S Sujayraj, C F Mulimani — Sat, 09 Nov 2024 00:00:00 +0000

Trapping, an ancient method employed for hunting or poaching in the wild, has witnessed minimal change in its impact on both targeted and non-targeted wildlife populations, with snares emerging as a prevalent trapping tool. Motivations for adopting snares include increased bush meat demand, rituals, and entrenched beliefs driven by their cost-effectiveness and efficiency. This study explores various snare types and examines their scientific implications for the demographic impacts on terrestrial mammals and birds. Data were procured from national and international web portals related to crime scene investigations and evidence, which aided in identifying taxonomic diversity and the frequency of occurrence of susceptible species. Our review highlights that the increasing wildlife crimes, driven by forest exploitation and encroachment, are threatening endangered species. This underscores the need for actionable management strategies and the broad dissemination of research findings. Utilizing tools like the Spatial Monitoring Tool (SMART) is crucial for effectively combating snare hunting and poaching. Although snaring impacts wildlife, some regions still have thriving populations, emphasizing the need for continuous patrolling and monitoring. To address these challenges, we recommend routine security patrolling, the involvement of forensic experts, and adherence to standard operating procedures with skilled personnel to enhance wildlife protection.

Novel antidiabetic therapeutics from some Indian medicinal plant kingdom

Sudipta Saha — Sat, 09 Nov 2024 00:00:00 +0000

Diabetes mellitus (DM) becomes a serious global problem as it is responsible for annual 1.5 million deaths. The extreme change in food habits and the fast lifestyle causes metabolic or endocrine disorders, which lead to Diabetes Mellitus (DM). The presently available synthetic drugs possess numerous side effects. They are very costly and limited ease of use, efficiency and acceptability. Natural products are playing a major role in the treatment of numerous chronic diseases and drug discovery processes. The superiority of natural product drugs over synthetic drugs is because the former are safer and easily available. For this reason, researchers are now trying to find novel and more potent antidiabetic drugs from traditional medicinal plants. A number of plant-generated chemical compounds, especially polysaccharides, glycosides, terpenes, flavonoids, and polypeptides possessing antidiabetic activity, are isolated from various medicinal plants worldwide. These natural antidiabetic medications alter metabolic imbalances through a number of cellular and molecular pathways, preventing diabetic problems from developing. Nowadays, a great scientific interest has been aimed at the use of traditional antihyperglycemic medicinal plants as a daily food supplement. Inspired by the virtues of nature-based medicines, pharmacologists, phytochemists and pharmacognosists are extensively engaged in further research for the development of natural antidiabetic drugs nature. They advocate for the use of antidiabetic agents from nature’s pharmacy, especially from plants, for the long-term remedy of diabetic patients.