Amrith Educational and Cultural Society

The advantages of a WPT (wireless power transfer) system include simplicity, safety, and dependability. Electrical adjustments should be made to energy transfer coils in applications to boost output power while decreasing input capacity. This article provides a hybrid approach for compensatory topologies in WPT system. The hybrid technique combines the Lyrebird Optimization Algorithm (LOA) and the Dual Attention Graph Convolutional Network (DAGCN), and it is known as the LOA-DAGCN technique. The proposed solution aims to improve power efficiency in the WPT system. The proposed LOA approach is to determine the best controller parameters and generate a set of control signals. The DAGCN predicts the power delivered to the load. The suggested technique's performance is evaluated using the MATLAB working environment and compared to other approaches currently in use. Current techniques include particle swarm optimization (PSO), recurrent neural networks (RNN), and artificial neural networks (ANN). According to the findings, the proposed technique is 97.0% efficient, while the existing ANN's is 87.0%, the RNN's is 77.0%, and the PSO's is 68.0%.

Thyroid disorders affect millions worldwide but often go undiagnosed because their symptoms like fatigue, mood changes, and weight fluctuations are subtle and easily mistaken for stress or aging, delaying treatment and worsening outcomes. Conventional diagnostics depend on blood tests and clinical visits, creating barriers in resource-limited areas. To address this, we propose a simple, non-invasive screening method using voice analysis, motivated by evidence that thyroid dysfunction alters vocal characteristics. Our automated system leverages a hybrid deep learning framework combining Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks applied to Mel-frequency cepstral coefficients (MFCCs) extracted from voice recordings. The CNN layers capture distinctive spatial patterns in spectrograms, while the LSTM layers model temporal speech dynamics, enabling robust analysis of voice biomarkers. Trained and validated on a curated dataset of healthy and hypothyroid voice samples, the system achieved over 90 % classification accuracy, with interpretability enhanced through MFCC heatmaps and statistical visualizations highlighting feature differences. This lightweight, scalable solution requires only a short smartphone voice recording, making it ideal for telemedicine and deployment in underserved communities. By offering accessible, early screening without invasive tests or specialist visits, our approach holds promise to improve timely diagnosis and global health outcomes through more equitable and proactive thyroid care.

Background: From birth to initial four weeks of life is known as Neonate. The term early neonatal phase describes fundamental week of life. While the late neonatal period refers to the time between 7 and 28 days of existence. Minor newborn health problems are the main cause of morbidity in several children. Particularly common in low birth weight and premature babies and these minor problems may be the indication of major underlying diseases. Methods : The main target of this research is to assess and compare the impact of organised teaching methods on selected minor neonatal health problems among the mother of neonates. The study was carried out at SNR District Hospital, Kolar. There are 60 mothers of neonates admitted in postpartum unit were chosen for the research. The Quantitative Pre experimental study design was employed for the investigation. Mothers of neonates (n=60) were admitted in postnatal ward at SNR district hospital, Kolar were picked up by convenient sampling method. Likelihood of the research clarification of that instrument was evaluated through pilot study. Pre-test was led by utilizing questionnaire method. Treatment then introduced as well as after seven days after testing was performed for the same group. Results : In this research, the investigator analyzed that the average mean percentile of the pre-test result was 27.16% with the mean (8.15) and standard deviation (2.18). The post-test average mean percentage was 77.86 % with mean (23.36) and standard deviation, too (2.33). Interpretation and conclusion: The research found that there is a remarkable advancement in relation to understanding of mothers of neonates after receiving the organised educational programme on management of neonatal health problems. Keywords: Neonates, Teaching, Effectiveness, Health problem

Soybean is the most important crop in the world due to growing external demand. Nevertheless, its production requires a high use of pesticides. Trichoderma is a fungal genus with the potential to promote plant growth because of its broad metabolic arsenal. Because it increases efficiency in several cultures, Trichoderma spp. have the potential to be used as an alternative to chemicals. Given this context, this study aimed to evaluate the performance of the ICB Nutrisolo Trichoderma® inoculant on parameters related to soybean growth and production. Crops with five different soil and climate conditions were evaluated in Rio Grande do Sul State (southern Brazil) using parameters such as average plant height, average plant population, average number of grains/pod, number of pods/plant average, and average weight of one thousand grains, which revealed the results of productivity. The ICB Nutrisolo Trichoderma® increased plant height, number of pods, and grain weight, consequently increasing productivity in soybean plants. In this way, it was possible to characterize the product ICB Nutrisolo Trichoderma® as a growth-promoting inoculant for the soybean crop, increasing the scope of product registration.

Background and Objectives:Metabolic disorders, oral precancerous conditions and oral cancer are accompanied by alterations in the concentration of one or more trace elements like copper, iron, zinc, magnesium etc., in some body fluids, especially blood serum or plasma, which can help not only in the early diagnosis and treatment but also in prognosis. The objective of the study is to evaluate the levels of circulating trace elements (copper, iron, magnesium, zinc and calcium) in serum of patients with Oral Submucous Fibrosis (OSF) and Oral Squamous Cell Carcinoma (OSCC), to analyze the alteration and identify the best predictors amongst these parameters for disease occurrence and progression and their association with areca nut and betel quid chewing habits.Materials and Method:Serum levels of trace elements (copper, iron, magnesium, zinc and calcium) were estimated using electronic absorption colorimetric method. These levels were compared with controls and statistically evaluated using ANOVA and POST-HOC TUKEY tests.Results:The data analysis revealed that serum copper levels increased gradually from precancer to cancer, as the duration of betel quid chewing habit increased. However, serum iron, magnesium, zinc levels were decreased significantly in both the groups. Serum calcium levels were increased in the cancer group owing to bone resorption in the later stages of the disease, whereas it was close to normal in OSF patients. Among all the trace elements, the best predictor for occurrence of both the lesions was copper.Conclusion:The present study shows that the above trace elements may be associated with the pathogenesis and progression of OSF and OSCC. Betel quid and areca nut chewing habits are frequently associated with both disease states and may play a role in altering the serum levels of these trace elements. Concerted efforts would, therefore, help in early detection, management and monitoring the efficacy of treatment.