Search results for: V. M. Akhil

Authors: Jobin Varghese, V. M. Akhil, P. K. Rajendrakumar, K. S. Sivanandan

Abstract:

The major contributor to the human locomotion is the knee flexion and extension. During heel strike, a huge amount of energy is transmitted through the leg towards knee joint, which in fact is damped at heel and leg muscles. During high shocks, although it is damped to a certain extent, the balance force transmits towards knee joint which could damage the knee. Due to the vital function of the knee joint, it should be protected against damage due to additional load acting on it. This work concentrates on the development of spring mass damper system which exactly replicates the stiffness at the heel and muscles and the objective function is optimized to minimize the force acting at the knee joint. Further, the data collected using force plate are put into the model to verify its integrity and are found to be in good agreement.

Keywords: spring, mass, damper, knee joint

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Authors: Alpana Agarwal, Akhil Sharma

Abstract:

This work presents a fully differential CMOS amplifier consisting of two self-biased gain boosted inverter stages, that provides an alternative to the power hungry operational amplifier. The self-biasing avoids the use of external biasing circuitry, thus reduces the die area, design efforts, and power consumption. In the present work, regulated cascode technique has been employed for gain boosting. The Miller compensation is also applied to enhance the phase margin. The circuit has been designed and simulated in 1.8 V 0.18 µm CMOS technology. The simulation results show a high DC gain of 100.7 dB, Unity-Gain Bandwidth of 107.8 MHz, and Phase Margin of 66.7^o with a power dissipation of 286 μW and makes it suitable candidate for the high resolution pipelined ADCs.

Keywords: CMOS amplifier, gain boosting, inverter-based amplifier, self-biased inverter

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Authors: K. Akhil, J. Jayakumar, S. Sudheer Khan

Abstract:

Zinc oxide nanoparticles (ZnO NPs) are extensively used in a wide variety of commercial products including sunscreen, textile and paints. The present study evaluated the effect of surface capping agents including polyethylene glycol (EG), gelatin, polyvinyl alcohol(PVA) and poly vinyl pyrrolidone(PVP) on photocatalytic activity of ZnO NPs. The particles were also tested for its antibacterial and antibiofilm activity against Staphylococcus aureus (MTCC 3160) and Pseudomonas aeruginosa (MTCC 1688). Preliminary characterization was done by UV-Visible spectroscopy. Electron microscopic analysis showed that the particles were hexagonal in shape. The hydrodynamic size distribution was analyzed by using dynamic light scattering method and crystalline nature was determined by X-Ray diffraction method.

Keywords: antibacterial, antibiofilm, capping agents, photodegradation, surface coating, zinc oxide nanoparticles

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Authors: Akhil Dubey, Rajnesh Singh

Abstract:

In modern days there occur many rapid modifications in field of ad hoc network. These modifications create many revolutionary changes in the routing. Predictive energy efficient routing is inspired on the bee’s behavior of swarm intelligence. Predictive routing improves the efficiency of routing in the energetic point of view. The main aim of this routing is the minimum energy consumption during communication and maximized intermediate node’s remaining battery power. This routing is based on food searching behavior of bees. There are two types of bees for the exploration phase the scout bees and for the evolution phase forager bees use by this routing. This routing algorithm computes the energy consumption, fitness ratio and goodness of the path. In this paper we review the literature related with predictive routing, presenting modified routing and simulation result of this algorithm comparison with artificial bee colony based routing schemes in MANET and see the results of path fitness and probability of fitness.

Keywords: mobile ad hoc network, artificial bee colony, PEEBR, modified predictive routing

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Authors: Ibrahim Ahmed, Richard Amoateng, Akhil Jain, Mohamed Ahmed

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Alcoholic cardiomyopathy (ACM) is a type of acquired cardiomyopathy caused by chronic alcohol consumption. Frequently ACM is associated with arrhythmias such as atrial flutter. Our aim was to characterize the patient demographics and investigate the effect of atrial flutter (AF) on ACM. This was a retrospective cohort study using the Nationwide Inpatient Sample database to identify admissions in adults with principal and secondary diagnoses of alcoholic cardiomyopathy and atrial flutter from 2019. Multivariate linear and logistic regression models were adjusted for age, gender, race, household income, insurance status, Elixhauser comorbidity score, hospital location, bed size, and teaching status. The primary outcome was all-cause mortality, and secondary outcomes were the length of stay (LOS) and total charge in USD. There was a total of 21,855 admissions with alcoholic cardiomyopathy, of which 1,635 had atrial flutter (AF-ACM). Compared to Non-AF-ACM cohort, AF-ACM cohort had fewer females (4.89% vs 14.54%, p<0.001), were older (58.66 vs 56.13 years, p<0.001), fewer Native Americans (0.61% vs2.67%, p<0.01), had fewer smaller (19.27% vs 22.45%, p<0.01) & medium-sized hospitals (23.24% vs28.98%, p<0.01), but more large-sized hospitals (57.49% vs 48.57%, p<0.01), more Medicare (40.37% vs 34.08%, p<0.05) and fewer Medicaid insured (23.55% vs 33.70%, p=<0.001), fewer hypertension (10.7% vs 15.01%, p<0.05), and more obesity (24.77% vs 16.35%, p<0.001). Compared to Non-AF-ACM cohort, there was no difference in AF-ACM cohort mortality rate (6.13% vs 4.20%, p=0.0998), unadjusted mortality OR 1.49 (95% CI 0.92-2.40, p=0.102), adjusted mortality OR 1.36 (95% CI 0.83-2.24, p=0.221), but there was a difference in LOS 1.23 days (95% CI 0.34-2.13, p<0.01), total charge $28,860.30 (95% CI 11,883.96-45,836.60, p<0.01). In patients admitted with ACM, the presence of AF was not associated with a higher all-cause mortality rate or odds of all-cause mortality; however, it was associated with 1.23 days increase in LOS and a $28,860.30 increase in total hospitalization charge. Native Americans, older age and obesity were risk factors for the presence of AF in ACM.

Keywords: alcoholic cardiomyopathy, atrial flutter, cardiomyopathy, arrhythmia

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Authors: Vishnu V. Pillai, Sunil P. Lonkar, Akhil M. Abraham, Saeed M. Alhassan

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An effectual technology for wastewater treatment is a great demand now in order to encounter the water pollution caused by organic pollutants. Photocatalytic oxidation technology is widely used in removal of such unsafe contaminants. Among the semi-conducting metal oxides, robust and thermally stable TiO2 has emerged as a fascinating material for photocatalysis. Enhanced catalytic activity was observed for nanostructured TiO2 due to its higher surface, chemical stability and higher oxidation ability. However, higher charge carrier recombination and wide band gap of TiO2 limits its use as a photocatalyst in the UV region. It is desirable to develop a photocatalyst that can efficiently absorb the visible light, which occupies the main part of the solar spectrum. Hence, in order to extend its photocatalytic efficiency under visible light, TiO2 nanoparticles are often doped with metallic or non-metallic elements. Non-metallic doping of TiO2 has attracted much attention due to the low thermal stability and enhanced recombination of charge carriers endowed by metallic doping of TiO2. Amongst, sulfur doped TiO2 is most widely used photocatalyst in environmental purification. However, the most of S-TiO2 synthesis technique uses toxic chemicals and complex procedures. Hence, a facile, scalable and environmentally benign preparation process for S-TiO2 is highly desirable. In present work, we have demonstrated new and facile solid-state reaction method for S-TiO2 synthesis that uses abundant elemental sulfur as S source and moderate temperatures. The resulting nano-sized S-TiO2 has been successfully employed as visible light photocatalyst in methylene blue dye removal from aqueous media.

Keywords: ecofriendly, nanomaterials, methylene blue, photocatalysts

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Authors: Akhil Raj Pushparajan, Ranjit Ramachandran, Jijimole Gopi Reji, Ajay Kumar Ramakrishnan

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Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), is one of the leading causes of death by an infectious disease. In spite of the availability of effective drugs and a vaccine, TB is a major health concern and was declared a global emergency by the World Health Organization (WHO). The success of intracellular pathogens like Mtb depends on its ability to overcome the challenging environment in the host. Gene regulation controlled by transcriptional regulators (TRs) plays a crucial role for the bacteria to adapt to the host environment. In vitro studies on gene regulatory mechanisms during dormancy and reactivation have provided insights into the adaptations employed by Mtb to survive in the host. Here we present our efforts to functionally characterize Rv1019, a putative TR of Mtb H37Rv which was found to be present at significantly varying levels during dormancy and reactivation in vitro. The expression of this protein in the dormancy-reactivation model was validated by qRT-PCR and western blot. By DNA- protein interaction studies and reporter assays we found that under normal laboratory conditions of growth this protein behaves as an auto-repressor and tetracycline was found to abrogate this repression by interfering with its ability to bind DNA. Further, by cDNA analysis, we found that this TR is co-transcribed with its downstream genes Rv1020 (mfd) and Rv1021 (mazG) which are involved in DNA damage response in Mtb. Constitutive expression of this regulator in the surrogate host M. smegmatis showed downregulation of the orthologues of downstream genes suggested that Rv1019 could negatively regulate these genes. Our finds also show that M. smegmatis expressing Rv1019 is sensitive to DNA damage suggests the role of this protein in regulating DNA damage response induced by oxidative stress. Because of its role in regulating DNA damage response which may help in the persistence of Mtb, Rv1019 could be used as a prospective target for therapeutic intervention to fight TB.

Keywords: auto-repressor, DNA repair, mycobacterium smegmatis, mycobacterium tuberculosis, tuberculosis

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Authors: Ashi Gautam, Isha Shukla, Akhil Seghal

Abstract:

Biosensors are analytical devices that use a biological sensing element to detect and measure a specific chemical substance or biomolecule in a sample. These devices are widely used in various fields, including medical diagnostics, environmental monitoring, and food analysis, due to their high specificity, sensitivity, and selectivity. In this research paper, a machine learning model is proposed for predicting the suitability of skin care products based on biosensor readings. The proposed model takes in features extracted from biosensor readings, such as biomarker concentration, skin hydration level, inflammation presence, sensitivity, and free radicals, and outputs the most appropriate skin care product for an individual. This model is trained on a dataset of biosensor readings and corresponding skin care product information. The model's performance is evaluated using several metrics, including accuracy, precision, recall, and F1 score. The aim of this research is to develop a personalised skin care product recommendation system using biosensor data. By leveraging the power of machine learning, the proposed model can accurately predict the most suitable skin care product for an individual based on their biosensor readings. This is particularly useful in the skin care industry, where personalised recommendations can lead to better outcomes for consumers. The developed model is based on supervised learning, which means that it is trained on a labeled dataset of biosensor readings and corresponding skin care product information. The model uses these labeled data to learn patterns and relationships between the biosensor readings and skin care products. Once trained, the model can predict the most suitable skin care product for an individual based on their biosensor readings. The results of this study show that the proposed machine learning model can accurately predict the most appropriate skin care product for an individual based on their biosensor readings. The evaluation metrics used in this study demonstrate the effectiveness of the model in predicting skin care products. This model has significant potential for practical use in the skin care industry for personalised skin care product recommendations. The proposed machine learning model for predicting the suitability of skin care products based on biosensor readings is a promising development in the skin care industry. The model's ability to accurately predict the most appropriate skin care product for an individual based on their biosensor readings can lead to better outcomes for consumers. Further research can be done to improve the model's accuracy and effectiveness.

Keywords: biosensors, data model, machine learning, skin care

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