Search results for: Parul Grover
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 36

Search results for: Parul Grover

6 Estimation of Noise Barriers for Arterial Roads of Delhi

Authors: Sourabh Jain, Parul Madan

Abstract:

Traffic noise pollution has become a challenging problem for all metro cities of India due to rapid urbanization, growing population and rising number of vehicles and transport development. In Delhi the prime source of noise pollution is vehicular traffic. In Delhi it is found that the ambient noise level (Leq) is exceeding the standard permissible value at all the locations. Noise barriers or enclosures are definitely useful in obtaining effective deduction of traffic noise disturbances in urbanized areas. US’s Federal Highway Administration Model (FHWA) and Calculation of Road Traffic Noise (CORTN) of UK are used to develop spread sheets for noise prediction. Spread sheets are also developed for evaluating effectiveness of existing boundary walls abutting houses in mitigating noise, redesigning them as noise barriers. Study was also carried out to examine the changes in noise level due to designed noise barrier by using both models FHWA and CORTN respectively. During the collection of various data it is found that receivers are located far away from road at Rithala and Moolchand sites and hence extra barrier height needed to meet prescribed limits was less as seen from calculations and most of the noise diminishes by propagation effect.On the basis of overall study and data analysis, it is concluded that FHWA and CORTN models under estimate noise levels. FHWA model predicted noise levels with an average percentage error of -7.33 and CORTN predicted with an average percentage error of -8.5. It was observed that at all sites noise levels at receivers were exceeding the standard limit of 55 dB. It was seen from calculations that existing walls are reducing noise levels. Average noise reduction due to walls at Rithala was 7.41 dB and at Panchsheel was 7.20 dB and lower amount of noise reduction was observed at Friend colony which was only 5.88. It was observed from analysis that Friends colony sites need much greater height of barrier. This was because of residential buildings abutting the road. At friends colony great amount of traffic was observed since it is national highway. At this site diminishing of noise due to propagation effect was very less.As FHWA and CORTN models were developed in excel programme, it eliminates laborious calculations of noise. There was no reflection correction in FHWA models as like in CORTN model.

Keywords: IFHWA, CORTN, Noise Sources, Noise Barriers

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5 An Evolutionary Approach for QAOA for Max-Cut

Authors: Francesca Schiavello

Abstract:

This work aims to create a hybrid algorithm, combining Quantum Approximate Optimization Algorithm (QAOA) with an Evolutionary Algorithm (EA) in the place of traditional gradient based optimization processes. QAOA’s were first introduced in 2014, where, at the time, their algorithm performed better than the traditional best known classical algorithm for Max-cut graphs. Whilst classical algorithms have improved since then and have returned to being faster and more efficient, this was a huge milestone for quantum computing, and their work is often used as a benchmarking tool and a foundational tool to explore variants of QAOA’s. This, alongside with other famous algorithms like Grover’s or Shor’s, highlights to the world the potential that quantum computing holds. It also presents the reality of a real quantum advantage where, if the hardware continues to improve, this could constitute a revolutionary era. Given that the hardware is not there yet, many scientists are working on the software side of things in the hopes of future progress. Some of the major limitations holding back quantum computing are the quality of qubits and the noisy interference they generate in creating solutions, the barren plateaus that effectively hinder the optimization search in the latent space, and the availability of number of qubits limiting the scale of the problem that can be solved. These three issues are intertwined and are part of the motivation for using EAs in this work. Firstly, EAs are not based on gradient or linear optimization methods for the search in the latent space, and because of their freedom from gradients, they should suffer less from barren plateaus. Secondly, given that this algorithm performs a search in the solution space through a population of solutions, it can also be parallelized to speed up the search and optimization problem. The evaluation of the cost function, like in many other algorithms, is notoriously slow, and the ability to parallelize it can drastically improve the competitiveness of QAOA’s with respect to purely classical algorithms. Thirdly, because of the nature and structure of EA’s, solutions can be carried forward in time, making them more robust to noise and uncertainty. Preliminary results show that the EA algorithm attached to QAOA can perform on par with the traditional QAOA with a Cobyla optimizer, which is a linear based method, and in some instances, it can even create a better Max-Cut. Whilst the final objective of the work is to create an algorithm that can consistently beat the original QAOA, or its variants, due to either speedups or quality of the solution, this initial result is promising and show the potential of EAs in this field. Further tests need to be performed on an array of different graphs with the parallelization aspect of the work commencing in October 2023 and tests on real hardware scheduled for early 2024.

Keywords: evolutionary algorithm, max cut, parallel simulation, quantum optimization

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4 Prediction of Endotracheal Tube Size in Children by Predicting Subglottic Diameter Using Ultrasonographic Measurement versus Traditional Formulas

Authors: Parul Jindal, Shubhi Singh, Priya Ramakrishnan, Shailender Raghuvanshi

Abstract:

Background: Knowledge of the influence of the age of the child on laryngeal dimensions is essential for all practitioners who are dealing with paediatric airway. Choosing the correct endotracheal tube (ETT) size is a crucial step in pediatric patients because a large-sized tube may cause complications like post-extubation stridor and subglottic stenosis. On the other hand with a smaller tube, there will be increased gas flow resistance, aspiration risk, poor ventilation, inaccurate monitoring of end-tidal gases and reintubation may also be required with a different size of the tracheal tube. Recent advancement in ultrasonography (USG) techniques should now allow for accurate and descriptive evaluation of pediatric airway. Aims and objectives: This study was planned to determine the accuracy of Ultrasonography (USG) to assess the appropriate ETT size and compare it with physical indices based formulae. Methods: After obtaining approval from Institute’s Ethical and Research committee, and parental written and informed consent, the study was conducted on 100 subjects of either sex between 12-60 months of age, undergoing various elective surgeries under general anesthesia requiring endotracheal intubation. The same experienced radiologist performed ultrasonography. The transverse diameter was measured at the level of cricoids cartilage by USG. After USG, general anesthesia was administered using standard techniques followed by the institute. An experienced anesthesiologist performed the endotracheal intubations with uncuffed endotracheal tube (Portex Tracheal Tube Smiths Medical India Pvt. Ltd.) with Murphy’s eye. He was unaware of the finding of the ultrasonography. The tracheal tube was considered best fit if air leak was satisfactory at 15-20 cm H₂O of airway pressure. The obtained values were compared with the values of endotracheal tube size calculated by ultrasonography, various age, height, weight-based formulas and diameter of right and left little finger. The correlation of the size of the endotracheal tube by different modalities was done and Pearson's correlation coefficient was obtained. The comparison of the mean size of the endotracheal tube by ultrasonography and by traditional formula was done by the Friedman’s test and Wilcoxon sign-rank test. Results: The predicted tube size was equal to best fit and best determined by ultrasonography (100%) followed by comparison to left little finger (98%) and right little finger (97%) and age-based formula (95%) followed by multivariate formula (83%) and body length (81%) formula. According to Pearson`s correlation, there was a moderate correlation of best fit endotracheal tube with endotracheal tube size by age-based formula (r=0.743), body length based formula (r=0.683), right little finger based formula (r=0.587), left little finger based formula (r=0.587) and multivariate formula (r=0.741). There was a strong correlation with ultrasonography (r=0.943). Ultrasonography was the most sensitive (100%) method of prediction followed by comparison to left (98%) and right (97%) little finger and age-based formula (95%), the multivariate formula had an even lesser sensitivity (83%) whereas body length based formula was least sensitive with a sensitivity of 78%. Conclusion: USG is a reliable method of estimation of subglottic diameter and for prediction of ETT size in children.

Keywords: endotracheal intubation, pediatric airway, subglottic diameter, traditional formulas, ultrasonography

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3 Application of Deep Learning Algorithms in Agriculture: Early Detection of Crop Diseases

Authors: Manaranjan Pradhan, Shailaja Grover, U. Dinesh Kumar

Abstract:

Farming community in India, as well as other parts of the world, is one of the highly stressed communities due to reasons such as increasing input costs (cost of seeds, fertilizers, pesticide), droughts, reduced revenue leading to farmer suicides. Lack of integrated farm advisory system in India adds to the farmers problems. Farmers need right information during the early stages of crop’s lifecycle to prevent damage and loss in revenue. In this paper, we use deep learning techniques to develop an early warning system for detection of crop diseases using images taken by farmers using their smart phone. The research work leads to building a smart assistant using analytics and big data which could help the farmers with early diagnosis of the crop diseases and corrective actions. The classical approach for crop disease management has been to identify diseases at crop level. Recently, ImageNet Classification using the convolutional neural network (CNN) has been successfully used to identify diseases at individual plant level. Our model uses convolution filters, max pooling, dense layers and dropouts (to avoid overfitting). The models are built for binary classification (healthy or not healthy) and multi class classification (identifying which disease). Transfer learning is used to modify the weights of parameters learnt through ImageNet dataset and apply them on crop diseases, which reduces number of epochs to learn. One shot learning is used to learn from very few images, while data augmentation techniques are used to improve accuracy with images taken from farms by using techniques such as rotation, zoom, shift and blurred images. Models built using combination of these techniques are more robust for deploying in the real world. Our model is validated using tomato crop. In India, tomato is affected by 10 different diseases. Our model achieves an accuracy of more than 95% in correctly classifying the diseases. The main contribution of our research is to create a personal assistant for farmers for managing plant disease, although the model was validated using tomato crop, it can be easily extended to other crops. The advancement of technology in computing and availability of large data has made possible the success of deep learning applications in computer vision, natural language processing, image recognition, etc. With these robust models and huge smartphone penetration, feasibility of implementation of these models is high resulting in timely advise to the farmers and thus increasing the farmers' income and reducing the input costs.

Keywords: analytics in agriculture, CNN, crop disease detection, data augmentation, image recognition, one shot learning, transfer learning

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2 Capability of a Single Antigen to Induce Both Protective and Disease Enhancing Antibody: An Obstacle in the Creation of Vaccines and Passive Immunotherapies

Authors: Parul Kulshreshtha, Subrata Sinha, Rakesh Bhatnagar

Abstract:

This study was conducted by taking B. anthracis as a model pathogen. On infecting a host, B. anthracis secretes three proteins, namely, protective antigen (PA, 83kDa), edema factor (EF, 89 kDa) and lethal factor (LF, 90 kDa). These three proteins are the components of two anthrax toxins. PA binds to the cell surface receptors, namely, tumor endothelial marker (TEM) 8 and capillary morphogenesis protein (CMG) 2. TEM8 and CMG2 interact with LDL-receptor related protein (LRP) 6 for endocytosis of EF and LF. On entering the cell, EF acts as a calmodulin-dependent adenylate cyclase that causes a prolonged increase of cytosolic cyclic adenosine monophosphate (cAMP). LF is a metalloprotease that cleaves most isoforms of mitogen-activated protein kinase kinases (MAPKK/MEK) close to their N-terminus. By secreting these two toxins, B.anthracis ascertains death of the host. Once the systemic levels of the toxins rise, antibiotics alone cannot save the host. Therefore, toxin-specific inhibitors have to be developed. In this wake, monoclonal antibodies have been developed for the neutralization of toxic effects of anthrax toxins. We created hybridomas by using spleen of mice that were actively immunized with rLFn (recombinant N-terminal domain of lethal factor of B. anthracis) to obtain anti-toxin antibodies. Later on, separate group of mice were immunized with rLFn to obtain a polyclonal control for passive immunization studies of monoclonal antibodies. This led to the identification of one cohort of rLFn-immunized mice that harboured disease-enhancing polyclonal antibodies. At the same time, the monoclonal antibodies from all the hybridomas were being tested. Two hybridomas secreted monoclonal antibodies (H8 and H10) that were cross-reactive with EF (edema factor) and LF (lethal factor), while the other two hybridomas secreted LF-specific antibodies (H7 and H11). The protective efficacy of H7, H8, H10 and H11 was investigated. H7, H8 and H10 were found to be protective. H11 was found to have disease enhancing characteristics in-vitro and in mouse model of challenge with B. anthracis. In this study the disease enhancing character of H11 monoclonal antibody and anti-rLFn polyclonal sera was investigated. Combination of H11 with protective monoclonal antibodies (H8 and H10) reduced its disease enhancing nature both in-vitro and in-vivo. But combination of H11 with LETscFv (an scFv with VH and VL identical to H10 but lacking Fc region) could not abrogate the disease-enhancing character of H11 mAb. Therefore it was concluded that for suppression of disease enhancement, Fc portion was absolutely essential for interaction of H10 with H11. Our study indicates that the protective potential of an antibody depends equally on its idiotype/ antigen specificity and its isotype. A number of monoclonal and engineered antibodies are being explored as immunotherapeutics but it is absolutely essential to characterize each one for their individual and combined protective potential. Although new in the sphere of toxin-based diseases, it is extremely important to characterize the disease-enhancing nature of polyclonal as well as monoclonal antibodies. This is because several anti-viral therapeutics and vaccines have failed in the face of this phenomenon. The passive –immunotherapy thus needs to be well formulated to avoid any contraindications.

Keywords: immunotherapy, polyclonal, monoclonal, antibody-dependent disease enhancement

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1 A Rare Case of Dissection of Cervical Portion of Internal Carotid Artery, Diagnosed Postpartum

Authors: Bidisha Chatterjee, Sonal Grover, Rekha Gurung

Abstract:

Postpartum dissection of the internal carotid artery is a relatively rare condition and is considered as an underlying aetiology in 5% to 25% of strokes under the age of 30 to 45 years. However, 86% of these cases recover completely and 14% have mild focal neurological symptoms. Prognosis is generally good with early intervention. The risk quoted for a repeat carotid artery dissection in subsequent pregnancies is less than 2%. 36-year Caucasian primipara presented on postnatal day one of forceps delivery with tachycardia. In the intrapartum period she had a history of prolonged rupture of membranes and developed intrapartum sepsis and was treated with antibiotics. Postpartum ECG showed septal inferior T wave inversion and a troponin level of 19. Subsequently Echocardiogram ruled out post-partum cardiomyopathy. Repeat ECG showed improvement of the previous changes and in the absence of symptoms no intervention was warranted. On day 4 post-delivery, she had developed symptoms of droopy right eyelid, pain around the right eye and itching in the right ear. On examination, she had developed right sided ptosis, unequal pupils (Rt miotic pupil). Cranial nerve examination, reflexes, sensory examination and muscle power was normal. Apart from migraine, there was no medical or family history of note. In view of Horner’s on the right, she had a CT Angiogram and subsequently MR/MRA and was diagnosed with dissection of the cervical portion of the right internal carotid artery. She was discharged on a course of Aspirin 75mg. By 6 week post-natal follow up patient had recovered significantly with occasional episodes of unequal pupils and tingling of right toes which resolved spontaneously. Cervical artery dissection, including VAD and carotid artery dissection, are rare complications of pregnancy with an estimated annual incidence of 2.6–3 per 100,000 pregnancy hospitalizations. Aetiology remains unclear though trauma during straining at labour, underlying arterial disease and preeclampsia have been implicated. Hypercoagulable state during pregnancy and puerperium could also be an important factor. 60-90% cases present with severe headache and neck pain and generally precede neurological symptoms like ipsilateral Horner’s syndrome, retroorbital pain, tinnitus and cranial nerve palsy. Although rare, the consequences of delayed diagnosis and management can lead to severe and permanent neurological deficits. Patients with a strong index of suspicion should undergo an MRI or MRA of head and neck. Antithrombotic and antiplatelet therapy forms the mainstay of therapy with selected cases needing endovascular stenting. Long term prognosis is favourable with either complete resolution or minimal deficit if treatment is prompt. Patients should be counselled about the recurrence risk and possibility of stroke in future pregnancy. Coronary artery dissection is rare and treatable but needs early diagnosis and treatment. Post-partum headache and neck pain with neurological symptoms should prompt urgent imaging followed by antithrombotic and /or antiplatelet therapy. Most cases resolve completely or with minimal sequelae.

Keywords: postpartum, dissection of internal carotid artery, magnetic resonance angiogram, magnetic resonance imaging, antiplatelet, antithrombotic

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