Search results for: Pranav Gulati

Authors: Pranav Gulati, Isha Sharma

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Hypertension and hypotension are known to have repercussions on the health of an individual, with hypertension contributing to an increased probability of risk to cardiovascular diseases and hypotension resulting in syncope. This prompts the development of a non-invasive, non-intrusive, continuous and cuff-less blood pressure monitoring system to detect blood pressure variations and to identify individuals with acute and chronic heart ailments, but due to the unavailability of such devices for practical daily use, it becomes difficult to screen and subsequently regulate blood pressure. The complexities which hamper the steady monitoring of blood pressure comprises of the variations in physical characteristics from individual to individual and the postural differences at the site of monitoring. We propose to develop a continuous, comprehensive cardio-analysis tool, based on reflective photoplethysmography (PPG). The proposed device, in the form of an eyewear captures the PPG signal and estimates the systolic and diastolic blood pressure using a sensor positioned near the temporal artery. This system relies on regression models which are based on extraction of key points from a pair of PPG wavelets. The proposed system provides an edge over the existing wearables considering that it allows for uniform contact and pressure with the temporal site, in addition to minimal disturbance by movement. Additionally, the feature extraction algorithms enhance the integrity and quality of the extracted features by reducing unreliable data sets. We tested the system with 12 subjects of which 6 served as the training dataset. For this, we measured the blood pressure using a cuff based BP monitor (Omron HEM-8712) and at the same time recorded the PPG signal from our cardio-analysis tool. The complete test was conducted by using the cuff based blood pressure monitor on the left arm while the PPG signal was acquired from the temporal site on the left side of the head. This acquisition served as the training input for the regression model on the selected features. The other 6 subjects were used to validate the model by conducting the same test on them. Results show that the developed prototype can robustly acquire the PPG signal and can therefore be used to reliably predict blood pressure levels.

Keywords: blood pressure, photoplethysmograph, eyewear, physiological monitoring

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Authors: Ashish Kumar Singh, Mehak Gulati, Neelam Verma

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Arginine majorly acts as a substrate for the enzyme nitric oxide synthase (NOS) for the production of nitric oxide, a strong vasodilator. Current study demonstrated a novel amperometric approach for estimation of arginine using nitric oxide synthase. The enzyme was co-immobilized in carbon paste electrode with NADP+, FAD and BH4 as cofactors. The detection principle of the biosensor is enzyme NOS catalyzes the conversion of arginine into nitric oxide. The developed biosensor could able to detect up to 10-9M of arginine. The oxidation peak of NO was observed at 0.65V. The developed arginine biosensor was used to monitor arginine content in fruit juices.

Keywords: arginine, biosensor, carbon paste elctrode, nitric oxide

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Authors: Pranav Mohan Parki, C. Mallika Parveen, Tahseen Ahmad Khan, Mihika Shivkumar

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Additive manufacturing (AM) is one of the several manufacturing processes in use today. AM comprises of techniques such as ‘Selective Laser Sintering’ and ‘Selective Laser Melting’ etc. along with other equipment and materials has been developed way back in 1980s, although major use of these methods has risen during the last decade. AM seems to be the most efficient way when compared to the traditional machining procedures. Still many problems continue to hinder its progress to becoming the most widely used of all. This paper contributes to the better understanding of AM and also aims at providing viable solutions to these problems, which may further help in enabling AM to become the most flaw free production method.

Keywords: additive manufacturing (AM), 3D printing, prototype, laser sintering

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Authors: Deepika Bhaskar, Neena Wadehra, Megha Gulati, Aruna Narula, R. Vishnu, Gunjan Katyal

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With drug resistance becoming widespread in Plasmodium falciparum infections, development of the alternative drugs is the desired strategy for prevention and cure of malaria. Three drug targets were selected to screen promising drug molecules from the GSK library of around 14000 molecules. Using an in silico structure-based drug designing approach, the differences in binding energies of the substrate and inhibitor were exploited between target sites of parasite and human to design a drug molecule against Plasmodium. The docking studies have shown several promising molecules from GSK library with more effective binding as compared to the already known inhibitors for the drug targets. Though stronger interaction has been shown by several molecules as compare to reference, few molecules have shown the potential as drug candidates though in vitro studies are required to validate the results.

Keywords: plasmodium, malaria, drug targets, in silico studies

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Authors: Pranav Vaidya

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The recent upheaval of a ballot initiative taken place in California & Los Angeles‘s newspapers shows how the concept of giving Death Penalty obliterates the very soul basis of community and society which rests upon the tripod of values, ethics, and morality. This paper goes on with examining how, by giving death penalties we are, on one hand trying to wipe out those heinous offenders committing such unspeakable crimes against the public; while on the other hand it comes with a devastating effect of corroding and eluding the existence of ethics and morality which is in the very nature of “protecting the life of humankind”. As it can be stated that, by giving capital punishment, we are trying to legitimize an irreversible act of violence by the authority of state and target innocent victims because as long as the human justice is fallible, the risk of executing an innocent can never be eliminated. However, scholars in the legalization of Capital Punishment have argued that the courts should impose punishment befitting the crime so that they could reflect public abhorrence of the crime, create deterrent or rehabilitating effects & deliver the truest form of justice.

Keywords: ethics, heinous offenders, morality, unspeakable crimes

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Authors: Gajera Lalit, Shah Pranav, Shah Shailesh

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Venlafaxine hydrochloride has a short elimination half-life of 5 ± 2 hr, and absorption window in the upper part of gastrointestinal tract. The conventional tablets need to be administered two to three times a day and possess an oral bioavailability of 45%. The purpose of this study was to formulate gastroretentive effervescent floating tablets of Venlafaxine HCl. Different grades of HPMC namely K15M, K4M, K100M and E15LV were employed as swelling polymers whereas sodium bicarbonate was employed as gas generating agent. The direct compression method was employed for the formulation of tablets. The tablets were evaluated in terms of hardness, friability, weight variation, drug content, water uptake, in-vitro floating behavior and in-vitro drug release study. All the formulations exhibited very short floating lag time of < 1 min and total floating time of 12 hr. Formulation L3 containing 25 mg and 75 mg of HPMC E15 LV and HPMC K15M respectively exhibited complete drug release within 12 hrs.

Keywords: venlafaxine HCl, hydroxyl propyl methylcellulose, floating gastro retentive tablets, in-vitro drug release, non-fickian diffusion

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Authors: Shefeen Maliyakkal, Pranav Satheesh, Steve Simon, Sharath Kuruppath

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This paper researches the impact of battery voltage sag on the performance and efficiency of E-motor in electric cars. Terminal voltage of battery reduces with the S.o.C. This results in the downward shift of torque-speed curve of E-motor and increased copper losses in E-motor. By introducing a buck-boost inverter between the battery and E-motor, an additional degree of freedom was achieved. By boosting the AC voltage, the dependency of voltage sag on the performance of E-motor was eliminated. A strategy was also proposed for the operation of the buck-boost inverter to minimize copper and iron losses in E-motor to maximize efficiency. MATLAB-SIMULINK model of E-drive was used to obtain simulation results. The temperature rise in the E-motor was reduced by 14% for a 10% increase in AC voltage. From the results, it was observed that a 20% increase in AC voltage can result in improvement of running torque and maximum torque of E-motor by 44%. Hence it was concluded that using a buck-boost inverter for E-drive significantly improves both performance and efficiency of E-motor.

Keywords: buck-boost, E-motor, battery, voltage sag

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Authors: D. Pranav

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Pesticides are a class of Biocide, whose use in agriculture has led to a momentous increase in the yield of crops, fruits and vegetables all over the word and its effective use has also been the pillars of success for the Green Revolution. However, the incessant use of pesticides has now reached alarming levels. In 2007 alone, the world used an estimated 2.4 million tons of pesticides. Despite its tremendous benefits for agriculture, pesticide has been one of the major reasons for degradation of the natural environment and undesirable effects on human beings. It has not only caused damage to human health, but has also threatened the survival of few birds and animal species. In India, the sale and usage of banned pesticide, increased usage of pesticides and its inadequate labeling has caused Bio magnification, which is causing deleterious effects on child development, resulting in stunted mental and physical growth. This paper aims to bring to shed light on major loopholes in the current pesticide regulations such as the Insecticide Act of 1968. It further discusses loopholes in the yet to be tabled Pesticides Management Bill of 2008. It discusses and arrives at potential amendments to the laws and regulations concerning pesticides; that cannot only be applied to the Indian subcontinent but other developing countries as well.

Keywords: pesticides, India, human health, environment, regulations, reform

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Authors: Amitesh Goswami, Vishal Gulati, Annu Yadav

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In this paper, WEDM has been used to investigate the machining characteristics of Inconel-625 alloy. The machining characteristics namely material removal rate (MRR) and surface roughness (SR) have been investigated along with surface microstructure analysis using SEM and EDS of the machined surface. Taguchi’s L27 Orthogonal array design has been used by considering six varying input parameters viz. Pulse-on time (Ton), Pulse-off time (Toff), Spark Gap Set Voltage (SV), Peak Current (IP), Wire Feed (WF) and Wire Tension (WT) for the responses of interest. It has been found out that Pulse-on time (Ton) and Spark Gap Set Voltage (SV) are the most significant parameters affecting material removal rate (MRR) and surface roughness (SR) are. Microstructure analysis of workpiece was also done using Scanning Electron Microscope (SEM). It was observed that, variations in pulse-on time and pulse-off time causes varying discharge energy and as a result of which deep craters / micro cracks and large/ small number of debris were formed. These results were helpful in studying the effects of pulse-on time and pulse-off time on MRR and SR. Energy Dispersive Spectrometry (EDS) was also done to check the compositional analysis of the material and it was observed that Copper and Zinc which were initially not present in the Inconel 625, later migrated on the material surface from the brass wire electrode during machining

Keywords: MRR, SEM, SR, taguchi, Wire Electric Discharge Machining

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Authors: Pranav Gunhal

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This paper presents an analysis of sentiment on Twitter towards the Karnataka elections held in 2023, utilizing transformer-based models specifically designed for sentiment analysis in Indic languages. Through an innovative data collection approach involving a combination of novel methods of data augmentation, online data preceding the election was analyzed. The study focuses on sentiment classification, effectively distinguishing between positive, negative, and neutral posts while specifically targeting the sentiment regarding the loss of the Bharatiya Janata Party (BJP) or the win of the Indian National Congress (INC). Leveraging high-performing transformer architectures, specifically IndicBERT, coupled with specifically fine-tuned hyperparameters, the AI models employed in this study achieved remarkable accuracy in predicting the INC’s victory in the election. The findings shed new light on the potential of cutting-edge transformer-based models in capturing and analyzing sentiment dynamics within the Indian political landscape. The implications of this research are far-reaching, providing invaluable insights to political parties for informed decision-making and strategic planning in preparation for the forthcoming 2024 Lok Sabha elections in the nation.

Keywords: sentiment analysis, twitter, Karnataka elections, congress, BJP, transformers, Indic languages, AI, novel architectures, IndicBERT, lok sabha elections

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Authors: Monika Verma, Renuka Sharma, B. R. Gulati, Namita Singh

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In combination therapy, two chemotherapeutic agents work together in a collaborative action. It has appeared as one of the promising approaches to improve anti-cancer treatment efficacy. In the present investigation, piperine (P-NPS), paclitaxel (PTX NPS), and a combination of both, piperine-paclitaxel nanoparticle (Pip-PTX NPS), were made by the nanoprecipitation method and later characterized by PSA, DSC, SEM, TEM, and FTIR. All nanoparticles exhibited a monodispersed size distribution with a size of below 200 nm, zeta potential ranges from (-30-40mV) and a narrow polydispersity index (>0.3) of the drugs. The average encapsulation efficiency was found to be between 80 and 90%. In vitro release of drugs for nanoparticles was done spectrophotometrically. FTIR and DSC results confirmed the presence of the drug. The Pip-PTX NPS significantly inhibit cell proliferation as compared to the native drugs nanoparticles in the breast cancer cell line MCF-7. In addition, Pip-PTX NPS suppresses cells in colony formation and soft gel agar assay. Scratch migration and Transwell chamber invasion assays revealed that combined nanoparticles reduce the migration and invasion of breast cancer cells. Morphological studies showed that Pip-PTX NPS penetrates the cells and induces apoptosis, which was further confirmed by DNA fragmentation, SEM, and western blot analysis. Taken together, Pip-PTX NPS inhibits cell proliferation, anchorage dependent and anchorage independent cell growth, reduces migration and invasion, and induces apoptosis in cells. These findings support that combination therapy using Pip-PTX NPS represents a potential approach and could be helpful in the future for breast cancer therapy.

Keywords: piperine, paclitaxel, breast cancer, apoptosis

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Authors: Srishty Gulati, Anju Singh, Shrikant Kukreti

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The manifestation of structural polymorphism in DNA depends on the sequence and surrounding environment. Ample of folded DNA structures have been found in the cellular system out of which DNA hairpins are very common, however, are indispensable due to their role in the replication initiation sites, recombination, transcription regulation, and protein recognition. We enumerate this approach in our study, where the two base substitutions and change in temperature embark destabilization of DNA structure and misbalance the equilibrium between two structures of a sequence present at the overlapping region of the human COMT gene and MIR4761 gene. COMT and MIR4761 gene encodes for catechol-O-methyltransferase (COMT) enzyme and microRNAs (miRNAs), respectively. Environmental changes and errors during cell division lead to genetic abnormalities. The COMT gene entailed in dopamine regulation fosters neurological diseases like Parkinson's disease, schizophrenia, velocardiofacial syndrome, etc. A 19-mer deoxyoligonucleotide sequence 5'-AGGACAAGGTGTGCATGCC-3' (COMT19) is located at exon-4 on chromosome 22 and band q11.2 at the intersection of COMT and MIR4761 gene. Bioinformatics studies suggest that this sequence is conserved in humans and few other organisms and is involved in recognition of transcription factors in the vicinity of 3'-end. Non-denaturating gel electrophoresis and CD spectroscopy of COMT sequences indicate the formation of hairpin type DNA structures. Temperature-dependent CD studies revealed an unusual shift in the slipped DNA-Hairpin DNA equilibrium with the change in temperature. Also, UV-thermal melting techniques suggest that the two base substitutions on the complementary strand of COMT19 did not affect the structure but reduces the stability of duplex. This study gives insight about the possibility of existing structurally polymorphic transient states within DNA segments present at the intersection of COMT and MIR4761 gene.

Keywords: base-substitution, catechol-o-methyltransferase (COMT), hairpin-DNA, structural polymorphism

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Authors: Pranav Ajmera, Amit Kharat, Tanveer Gupte, Richa Pant, Viraj Kulkarni, Vinay Duddalwar, Purnachandra Lamghare

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The cardiothoracic ratio (CTR) is the ratio of the diameter of the heart to the diameter of the thorax. An abnormal CTR, that is, a value greater than 0.55, is often an indicator of an underlying pathological condition. The accurate prediction of an abnormal CTR from chest X-rays (CXRs) aids in the early diagnosis of clinical conditions. We propose a deep learning-based model for automatic CTR calculation that can assist the radiologist with the diagnosis of cardiomegaly and optimize the radiology flow. The study population included 1012 posteroanterior (PA) CXRs from a single institution. The Attention U-Net deep learning (DL) architecture was used for the automatic calculation of CTR. A CTR of 0.55 was used as a cut-off to categorize the condition as cardiomegaly present or absent. An observer performance test was conducted to assess the radiologist's performance in diagnosing cardiomegaly with and without artificial intelligence (AI) assistance. The Attention U-Net model was highly specific in calculating the CTR. The model exhibited a sensitivity of 0.80 [95% CI: 0.75, 0.85], precision of 0.99 [95% CI: 0.98, 1], and a F1 score of 0.88 [95% CI: 0.85, 0.91]. During the analysis, we observed that 51 out of 1012 samples were misclassified by the model when compared to annotations made by the expert radiologist. We further observed that the sensitivity of the reviewing radiologist in identifying cardiomegaly increased from 40.50% to 88.4% when aided by the AI-generated CTR. Our segmentation-based AI model demonstrated high specificity and sensitivity for CTR calculation. The performance of the radiologist on the observer performance test improved significantly with AI assistance. A DL-based segmentation model for rapid quantification of CTR can therefore have significant potential to be used in clinical workflows.

Keywords: cardiomegaly, deep learning, chest radiograph, artificial intelligence, cardiothoracic ratio

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Authors: Pranav Gunhal., Krish Jhurani

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This study tackles the significant computational challenge of predicting excited state dynamics in organic photovoltaic (OPV) materials—a pivotal factor in the performance of solar energy solutions. Time-dependent density functional theory (TDDFT), though effective, is computationally prohibitive for larger and more complex molecules. As a solution, the research explores the application of transformer neural networks, a type of artificial intelligence (AI) model known for its superior performance in natural language processing, to predict excited state dynamics in OPV materials. The methodology involves a two-fold process. First, the transformer model is trained on an extensive dataset comprising over 10,000 TDDFT calculations of excited state dynamics from a diverse set of OPV materials. Each training example includes a molecular structure and the corresponding TDDFT-calculated excited state lifetimes and key electronic transitions. Second, the trained model is tested on a separate set of molecules, and its predictions are rigorously compared to independent TDDFT calculations. The results indicate a remarkable degree of predictive accuracy. Specifically, for a test set of 1,000 OPV materials, the transformer model predicted excited state lifetimes with a mean absolute error of 0.15 picoseconds, a negligible deviation from TDDFT-calculated values. The model also correctly identified key electronic transitions contributing to the excited state dynamics in 92% of the test cases, signifying a substantial concordance with the results obtained via conventional quantum chemistry calculations. The practical integration of the transformer model with existing quantum chemistry software was also realized, demonstrating its potential as a powerful tool in the arsenal of materials scientists and chemists. The implementation of this AI model is estimated to reduce the computational cost of predicting excited state dynamics by two orders of magnitude compared to conventional TDDFT calculations. The successful utilization of transformer neural networks to accurately predict excited state dynamics provides an efficient computational pathway for the accelerated discovery and design of new OPV materials, potentially catalyzing advancements in the realm of sustainable energy solutions.

Keywords: transformer neural networks, organic photovoltaic materials, excited state dynamics, time-dependent density functional theory, predictive modeling

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Authors: Jeremy Jenrette, Z. Y. C. Liu, Pranav Chimote, Edward Fox, Trevor Hastie, Francesco Ferretti

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Suitable shark conservation depends on well-informed population assessments. Direct methods such as scientific surveys and fisheries monitoring are adequate for defining population statuses, but species-specific indices of abundance and distribution coming from these sources are rare for most shark species. We can rapidly fill these information gaps by boosting media-based remote monitoring efforts with machine learning and automation. We created a database of shark images by sourcing 24,546 images covering 219 species of sharks from the web application spark pulse and the social network Instagram. We used object detection to extract shark features and inflate this database to 53,345 images. We packaged object-detection and image classification models into a Shark Detector bundle. We developed the Shark Detector to recognize and classify sharks from videos and images using transfer learning and convolutional neural networks (CNNs). We applied these models to common data-generation approaches of sharks: boosting training datasets, processing baited remote camera footage and online videos, and data-mining Instagram. We examined the accuracy of each model and tested genus and species prediction correctness as a result of training data quantity. The Shark Detector located sharks in baited remote footage and YouTube videos with an average accuracy of 89\%, and classified located subjects to the species level with 69\% accuracy (n =\ eight species). The Shark Detector sorted heterogeneous datasets of images sourced from Instagram with 91\% accuracy and classified species with 70\% accuracy (n =\ 17 species). Data-mining Instagram can inflate training datasets and increase the Shark Detector’s accuracy as well as facilitate archiving of historical and novel shark observations. Base accuracy of genus prediction was 68\% across 25 genera. The average base accuracy of species prediction within each genus class was 85\%. The Shark Detector can classify 45 species. All data-generation methods were processed without manual interaction. As media-based remote monitoring strives to dominate methods for observing sharks in nature, we developed an open-source Shark Detector to facilitate common identification applications. Prediction accuracy of the software pipeline increases as more images are added to the training dataset. We provide public access to the software on our GitHub page.

Keywords: classification, data mining, Instagram, remote monitoring, sharks

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Authors: Neha Pranav Kolhe, Harithapriya Vijaye, Arushi Kamle

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The economic growth engines are urban regions. As the economy expands, so does the need for peace and quiet, and noise pollution is one of the important social and environmental issue. Health and wellbeing are at risk from environmental noise pollution. Because of urbanisation, population growth, and the consequent rise in the usage of increasingly potent, diverse, and highly mobile sources of noise, it is now more severe and pervasive than ever before, and it will only become worse. Additionally, it will expand as long as there is an increase in air, train, and highway traffic, which continue to be the main contributors of noise pollution. The current study will be conducted in two zones of class I city of central India (population range: 1 million–4 million). Total 56 measuring points were chosen to assess noise pollution. The first objective evaluates the noise pollution in various urban habitats determined as formal and informal settlement. It identifies the comparison of noise pollution within the settlements using T- Test analysis. The second objective assess the noise pollution in silent zones (as stated in Central Pollution Control Board) in a hierarchical way. It also assesses the noise pollution in the settlements and compares with prescribed permissible limits using class I sound level equipment. As appropriate indices, equivalent noise level on the (A) frequency weighting network, minimum sound pressure level and maximum sound pressure level were computed. The survey is conducted for a period of 1 week. Arc GIS is used to plot and map the temporal and spatial variability in urban settings. It is discovered that noise levels at most stations, particularly at heavily trafficked crossroads and subway stations, were significantly different and higher than acceptable limits and squares. The study highlights the vulnerable areas that should be considered while city planning. The study demands area level planning while preparing a development plan. It also demands attention to noise pollution from the perspective of residential and silent zones. The city planning in urban areas neglects the noise pollution assessment at city level. This contributes to that, irrespective of noise pollution guidelines, the ground reality is far away from its applicability. The result produces incompatible land use on a neighbourhood scale with respect to noise pollution. The study's final results will be useful to policymakers, architects and administrators in developing countries. This will be useful for noise pollution in urban habitat governance by efficient decision making and policy formulation to increase the profitability of these systems.

Keywords: noise pollution, formal settlements, informal settlements, built environment, silent zone, residential area

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Authors: Saleh Gorji, Sahil Gulati, Ana Pakzad

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Continuous electron diffraction tomography, also known as microcrystal electron diffraction (MicroED) or three-dimensional electron diffraction (3DED), is a powerful technique, which in combination with cryo-electron microscopy (cryo-ED), can provide atomic-scale 3D information about the crystal structure and composition of different classes of crystalline materials such as proteins, peptides, and small molecules. Unlike the well-established X-ray crystallography method, 3DED does not require large single crystals and can collect accurate electron diffraction data from crystals as small as 50 – 100 nm. This is a critical advantage as growing larger crystals, as required by X-ray crystallography methods, is often very difficult, time-consuming, and expensive. In most cases, specimens studied via 3DED method are electron beam sensitive, which means there is a limitation on the maximum amount of electron dose one can use to collect the required data for a high-resolution structure determination. Therefore, collecting data using a conventional scintillator-based fiber coupled camera brings additional challenges. This is because of the inherent noise introduced during the electron-to-photon conversion in the scintillator and transfer of light via the fibers to the sensor, which results in a poor signal-to-noise ratio and requires a relatively higher and commonly specimen-damaging electron dose rates, especially for protein crystals. As in other cryo-EM techniques, damage to the specimen can be mitigated if a direct detection camera is used which provides a high signal-to-noise ratio at low electron doses. In this work, we have used two classes of such detectors from Gatan, namely the K3® camera (a monolithic active pixel sensor) and Stela™ (that utilizes DECTRIS hybrid-pixel technology), to address this problem. The K3 is an electron counting detector optimized for low-dose applications (like structural biology cryo-EM), and Stela is also a counting electron detector but optimized for diffraction applications with high speed and high dynamic range. Lastly, data collection workflows, including crystal screening, microscope optics setup (for imaging and diffraction), stage height adjustment at each crystal position, and tomogram acquisition, can be one of the other challenges of the 3DED technique. Traditionally this has been all done manually or in a partly automated fashion using open-source software and scripting, requiring long hours on the microscope (extra cost) and extensive user interaction with the system. We have recently introduced Latitude® D in DigitalMicrograph® software, which is compatible with all pre- and post-energy-filter Gatan cameras and enables 3DED data acquisition in an automated and optimized fashion. Higher quality 3DED data enables structure determination with higher confidence, while automated workflows allow these to be completed considerably faster than before. Using multiple examples, this work will demonstrate how to direct detection electron counting cameras enhance 3DED results (3 to better than 1 Angstrom) for protein and small molecule structure determination. We will also show how Latitude D software facilitates collecting such data in an integrated and fully automated user interface.

Keywords: continuous electron diffraction tomography, direct detection, diffraction, Latitude D, Digitalmicrograph, proteins, small molecules

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