Search results for: Himanshu Shee

Authors: Maryam Ziaee, Himanshu Shee, Amrik Sohal

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Big Data Analytics (BDA) in supply chain management has recently drawn the attention of academics and practitioners. Big data refers to a massive amount of data from different sources, in different formats, generated at high speed through transactions in business environments and supply chain networks. Traditional statistical tools and techniques find it difficult to analyse this massive data. BDA can assist organisations to capture, store, and analyse data specifically in the field of supply chain. Currently, there is a paucity of research on BDA in the pharmaceutical supply chain context. In this research, the Australian pharmaceutical supply chain was selected as the case study. This industry is highly significant since the right medicine must reach the right patients, at the right time, in right quantity, in good condition, and at the right price to save lives. However, drug shortages remain a substantial problem for hospitals across Australia with implications on patient care, staff resourcing, and expenditure. Furthermore, a massive volume and variety of data is generated at fast speed from multiple sources in pharmaceutical supply chain, which needs to be captured and analysed to benefit operational decisions at every stage of supply chain processes. As the pharmaceutical industry lags behind other industries in using BDA, it raises the question of whether the use of BDA can improve transparency among pharmaceutical supply chain by enabling the partners to make informed-decisions across their operational activities. This presentation explores the impacts of BDA on supply chain management. An exploratory qualitative approach was adopted to analyse data collected through interviews. This study also explores the BDA potential in the whole pharmaceutical supply chain rather than focusing on a single entity. Twenty semi-structured interviews were undertaken with top managers in fifteen organisations (five pharmaceutical manufacturers, five wholesalers/distributors, and five public hospital pharmacies) to investigate their views on the use of BDA. The findings revealed that BDA can enable pharmaceutical entities to have improved visibility over the whole supply chain and also the market; it enables entities, especially manufacturers, to monitor consumption and the demand rate in real-time and make accurate demand forecasts which reduce drug shortages. Timely and precise decision-making can allow the entities to source and manage their stocks more effectively. This can likely address the drug demand at hospitals and respond to unanticipated issues such as drug shortages. Earlier studies explore BDA in the context of clinical healthcare; however, this presentation investigates the benefits of BDA in the Australian pharmaceutical supply chain. Furthermore, this research enhances managers’ insight into the potentials of BDA at every stage of supply chain processes and helps to improve decision-making in their supply chain operations. The findings will turn the rhetoric of data-driven decision into a reality where the managers may opt for analytics for improved decision-making in the supply chain processes.

Keywords: big data analytics, data-driven decision, pharmaceutical industry, supply chain management

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Authors: Dipti Raj, Himanshu Mishra

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Wetting of a solid surface by a liquid is an extremely common yet subtle phenomenon in natural and applied sciences. A clear understanding of both short and long-term wetting behaviors of surfaces is essential for creating robust anti-biofouling coatings, non-wetting textiles, non-fogging mirrors, and preventive linings against dirt and icing. In this study, silica beads (diameter, D ≈ 100 μm) functionalized using different silane reagents were employed to modify the wetting characteristics of smooth polydimethylsiloxane (PDMS) surfaces. Resulting composite surfaces were found to be super-hydrophobic, i.e. contact angle of water,

Keywords: contact angle, Cassie-Baxter, PDMS, silica, texture, wetting

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Authors: Himanshu Payal, Sachin Maheshwari, Pushpendra S. Bharti

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Electrical discharge machining (EDM), a non-conventional machining process, finds wide applications for shaping difficult-to-cut alloys. Process modeling of EDM is required to exploit the process to the fullest. Process modeling of EDM is a challenging task owing to involvement of so many electrical and non-electrical parameters. This work is an attempt to model the EDM process using artificial neural network (ANN). Experiments were carried out on die-sinking EDM taking Inconel 825 as work material. ANN modeling has been performed using experimental data. The prediction ability of trained network has been verified experimentally. Results indicate that ANN can predict the values of performance measures of EDM satisfactorily.

Keywords: artificial neural network, EDM, metal removal rate, modeling, surface roughness

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Authors: Himanshu Chandrakar, Krishnapriya S., Rama Komaragiri, Suja K. J.

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Micro coils are significant components for micro magnetic sensors and actuators especially in biomedical devices. Non-spiral planar microcoils of square, hexagonal and octagonal shapes are introduced for the first time in this paper. Comparison between different planar spiral and non-spiral coils are also discussed. The fabrication advantages and low power dissipation of non-spiral structures make them a strong alternative for conventional spiral planar coils. Series resistance of non-spiral coil is lesser than that of spiral coils though magnetic field is slightly lesser for non-spiral coils. Comparison of different planar microcoils shows that the proposed square non-spiral coil gives better performance than other structures.

Keywords: non-spiral planar microcoil, power dissipation, series resistance, spiral

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Authors: Himanshu Pavagadhi, Maunik Jani, S. M. Vyas, Jaymin Ray, Vimal Patel, Piyush Patel, Jignesh P. Raval

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The preparation of pure and Sn-doped cadmium sulfide (CdS) pellets was carried out using a compression technique with a pelletizer. The energy dispersive X-ray (EDX) analysis is used to confirm the purity and stoichiometric ratio of Cd, S, and Sn in the prepared pellets. The surface morphology of the pellets was examined using a scanning electron microscope. Both XRD and Raman scattering spectrum analysis confirmed the doping effect in the CdS pellets. The X-ray diffraction (XRD) analysis confirmed the hexagonal structure and revealed that the grain size decreases with increasing Sn dopant concentration in the parent CdS pellet. The optical properties of the pellets were evaluated by measuring diffuse reflectance using a UV-vis spectrophotometer. The analysis indicated that as the Sn concentration increases in the parent CdS pellet, the optical band gap decreases. This implies that the optical properties of the CdS material are also affected by the Sn dopant.

Keywords: CdS, Sn dopant, UV-Spetrophotometer, XRD

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Authors: Himanshu Dehra

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This paper presents a paradigm for characterization and checking of human noise behavior. The definitions of ‘Noise’ and ‘Noise Behavior’ are devised. The concept of characterization and examining of Noise Behavior is obtained from the proposed paradigm of Psychoacoustics. The measurement of human noise behavior is discussed through definitions of noise sources and noise measurements. The noise sources, noise measurement equations and noise filters are further illustrated through examples. The theory and significance of solar energy acoustics is presented for life and its activities. Human comfort and health are correlated with human brain through physiological responses and noise protection. Examples of heat stress, intense heat, sweating and evaporation are also enumerated.

Keywords: human brain, noise behavior, noise characterization, noise filters, physiological responses, psychoacoustics

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Authors: Abhigyan Hedau, Priya Shelke, Riddhi Mirajkar, Shreyash Chaple, Mrunali Gadekar, Himanshu Akula

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The heart is the coordinating centre of the major endocrine glandular structure of the body, which produces hormones that profoundly affect the operations of the body, and diagnosing cardiovascular disease is a difficult but critical task. By extracting knowledge and information about the disease from patient data, data mining is a more practical technique to help doctors detect disorders. We use a variety of machine learning methods here, including logistic regression and support vector classifiers (SVC), K-nearest neighbours Classifiers (KNN), Decision Tree Classifiers, Random Forest classifiers and Gradient Boosting classifiers. These algorithms are applied to patient data containing 13 different factors to build a system that predicts heart disease in less time with more accuracy.

Keywords: logistic regression, support vector classifier, k-nearest neighbour, decision tree, random forest and gradient boosting

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Authors: Aishwarya Shekhar, Himanshu Sharma

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Data deduplication is one of important data compression techniques for eliminating duplicate copies of repeating data, and has been widely used in cloud storage to reduce the amount of storage space and save bandwidth. In this process, duplicate data is expunged, leaving only one copy means single instance of the data to be accumulated. Though, indexing of each and every data is still maintained. Data deduplication is an approach for minimizing the part of storage space an organization required to retain its data. In most of the company, the storage systems carry identical copies of numerous pieces of data. Deduplication terminates these additional copies by saving just one copy of the data and exchanging the other copies with pointers that assist back to the primary copy. To ignore this duplication of the data and to preserve the confidentiality in the cloud here we are applying the concept of hybrid nature of cloud. A hybrid cloud is a fusion of minimally one public and private cloud. As a proof of concept, we implement a java code which provides security as well as removes all types of duplicated data from the cloud.

Keywords: confidentiality, deduplication, data compression, hybridity of cloud

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Authors: S. Sudhakar, Geetha Manjunath, Siva Teja Kakileti, Himanshu Madhu

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Diagnosis of breast cancer at early stages has seen better clinical and survival outcomes. Survival rates in developing countries like India are very low due to accessibility and affordability issues of screening tests such as Mammography. In addition, Mammography is not much effective in younger women with dense breasts. This leaves a gap in current screening methods. Thermalytix is a new technique for detecting breast abnormality in a non-contact, non-invasive way. It is an AI-enabled computer-aided diagnosis solution that automates interpretation of high resolution thermal images and identifies potential malignant lesions. The solution is low cost, easy to use, portable and is effective in all age groups. This paper presents the results of a retrospective comparative analysis of Thermalytix over Mammography and Clinical Breast Examination for breast cancer screening. Thermalytix was found to have better sensitivity than both the tests, with good specificity as well. In addition, Thermalytix identified all malignant patients without palpable lumps.

Keywords: breast cancer screening, radiology, thermalytix, artificial intelligence, thermography

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Authors: Amit Kumar, Himanshu Singal, Arnav Bhavsar

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In this modern era of automation, most of the academic exams and competitive exams are Multiple Choice Questions (MCQ). The responses of these MCQ based exams are recorded in the Optical Mark Reader (OMR) sheet. Evaluation of the OMR sheet requires separate specialized machines for scanning and marking. The sheets used by these machines are special and costs more than a normal sheet. Available process is non-economical and dependent on paper thickness, scanning quality, paper orientation, special hardware and customized software. This study tries to tackle the problem of evaluating the OMR sheet without any special hardware and making the whole process economical. We propose an image processing based algorithm which can be used to read and evaluate the scanned OMR sheets with no special hardware required. It will eliminate the use of special OMR sheet. Responses recorded in normal sheet is enough for evaluation. The proposed system takes care of color, brightness, rotation, little imperfections in the OMR sheet images.

Keywords: OMR, image processing, hough circle trans-form, interpolation, detection, binary thresholding

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Authors: Lagnajeet Mohanty, Mohnish Mishra, Pratham Tapdiya, Himanshu Sekhar Nayak, Swetapadma Singh

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In the era of global interconnectedness, effective risk assessment and management are critical for organizational resilience. This review explores the integration of machine learning (ML) into risk processes, examining its transformative potential and the challenges it presents. The literature reveals ML's success in sectors like consumer credit, demonstrating enhanced predictive accuracy, adaptability, and potential cost savings. However, ethical considerations, interpretability issues, and the demand for skilled practitioners pose limitations. Looking forward, the study identifies future research scopes, including refining ethical frameworks, advancing interpretability techniques, and fostering interdisciplinary collaborations. The synthesis of limitations and future directions highlights the dynamic landscape of ML in risk management, urging stakeholders to navigate challenges innovatively. This abstract encapsulates the evolving discourse on ML's role in shaping proactive and effective risk management strategies in our interconnected and unpredictable global landscape.

Keywords: machine learning, risk assessment, ethical considerations, financial inclusion

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Authors: Raahil Sheikh, Abhishek Maurya, Priya Gujjar, Himanshu Dwivedi, Prathamesh Minde

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UAVs have been an initial member of our environment since it's the first used by Austrian warfare in Venice. At that stage, they were just pilotless balloons equipped with bombs to be dropped on enemy territory. Over time, technological advancements allowed UAVs to be controlled remotely or autonomously. This study shall mainly focus on the intensification of pre-existing manual drones equipping them with a variety of sensors and making them autonomous, and capable, and purposing them for a variety of roles, including thermal sensing, data collection, tracking creatures, forest fires, volcano detection, hydrothermal studies, urban heat, Island measurement, and other environmental research. The system can also be used for reconnaissance, research, 3D mapping, and search and rescue missions. This study mainly focuses on automating tedious tasks and reducing human errors as much as possible, reducing deployment time, and increasing the overall efficiency, efficacy, and reliability of the UAVs. Creation of a comprehensive Ground Control System UI (GCS) enabling less trained professionals to be able to use the UAV with maximum potency. With the inclusion of such an autonomous system, artificially intelligent paths and environmental gusts and concerns can be avoided.

Keywords: UAV, drone, autonomous system, thermal imaging

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Authors: Raahil Sheikh, Prathamesh Minde, Priya Gujjar, Himanshu Dwivedi, Abhishek Maurya

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UAVs have been an initial member of our environment since it's the first used by Austrian warfare in Venice. At that stage, they were just pilotless balloons equipped with bombs to be dropped on enemy territory. Over time, technological advancements allowed UAVs to be controlled remotely or autonomously. This study shall mainly focus on the intensification of pre-existing manual drones equipping them with a variety of sensors and making them autonomous, and capable, and purposing them for a variety of roles, including thermal sensing, data collection, tracking creatures, forest fires, volcano detection, hydrothermal studies, urban heat, Island measurement, and other environmental research. The system can also be used for reconnaissance, research, 3D mapping, and search and rescue missions. This study mainly focuses on automating tedious tasks and reducing human errors as much as possible, reducing deployment time, and increasing the overall efficiency, efficacy, and reliability of the UAVs. Creation of a comprehensive Ground Control System UI (GCS) enabling less trained professionals to be able to use the UAV with maximum potency. With the inclusion of such an autonomous system, artificially intelligent paths and environmental gusts and concerns can be avoided

Keywords: UAV, autonomous systems, drones, geo thermal imaging

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Authors: M. Manohari, Himanshu Gupta, S. Priyadharshini, R. Santhanam, S. Chandrasekaran, B. Venkatraman

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Injection is one of the potential routes of intake in a radioactive facility. The internal dose due to this intake is monitored at the radiation emergency medical centre, IGCAR using a portable planar HPGe detector. The contaminated wound may be having different shapes. In a reprocessing potential of wound contamination with actinide is more. Efficiency is one of the input parameters for estimation of internal dose. Estimating these efficiencies experimentally would be tedious and cumbersome. Numerical estimation can be a supplement to experiment. As an initial step in this study 241Am contamination of different shapes are studied. In this study portable planar HPGe detector was modeled using Monte Carlo code FLUKA and the effect of different parameters like distance of the contamination from the detector, radius of the circular contamination were studied. Efficiency values for point and surface contamination located at different distances were estimated. The effect of efficiency on the radius of the surface source was more predominant when the source is at 1 cm distance compared to when the source to detector distance is 10 cm. At 1 cm the efficiency decreased quadratically as the radius increased and at 10 cm it decreased linearly. The point source efficiency varied exponentially with source to detector distance.

Keywords: Planar HPGe, efficiency value, injection, surface source

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Authors: Pinki Sharma, Himanshu Joshi

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Distillery spentwash contains high chemical oxygen demand (COD), biological oxygen demand (BOD), color, total dissolved solids (TDS) and other contaminants even after biological treatment. The effluent can’t be discharged as such in the surface water bodies or land without further treatment. Reverse osmosis (RO) treatment plants have been installed in many of the distilleries at tertiary level. But at most of the places these plants are not properly working due to high concentration of organic matter and other contaminants in biologically treated spentwash. To make the membrane treatment proven and reliable technology, proper pre-treatment is mandatory. In the present study, ultra-filtration (UF) as pre-treatment of RO at tertiary stage was performed. Operating parameters namely initial pH (pHo: 2–10), trans-membrane pressure (TMP: 4-20 bars) and temperature (T: 15- 43°C) used for conducting experiments with UF system. Experiments were optimized at different operating parameters in terms of COD, color, TDS and TOC removal by using response surface methodology (RSM) with central composite design. The results showed that removal of COD, color and TDS by 62%, 93.5% and 75.5%, with UF, respectively at optimized conditions with increased permeate flux from 17.5 l/m2/h (RO) to 38 l/m2/h (UF-RO). The performance of the RO system was greatly improved both in term of pollutant removal as well as water recovery.

Keywords: bio-digested distillery spentwash, reverse osmosis, response surface methodology, ultra-filtration

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Authors: Vikrant Sinha, Himanshu Singh, Nitish Kumar Singh, Sujal Nag

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This research creates an urgent and complex challenge for marine ecosystems. Microplastics were primarily found on land, but now they are pervasive in marine environments as well, affecting a wide range of marine species, from zooplankton to larger mammals that live in those environments. These pollutants interfere with major biological processes like feeding and reproduction, causing disruption throughout the food web as microplastics are getting accumulated at different tropic levels. Meanwhile, climatic changes made these effects more accelerated, and the concentration of microplastics due to these occurrences is increasing day by day. Rising temperatures, melting ice, increased runoff due to rainfall, and shifting wind patterns are transforming marine life in a way that intensifies the burden on marine life. This dual stress is particularly present in fragile ecosystems of marine life, such as coral reefs and mangroves. Addressing this twisted crisis requires not only efforts to restrain plastic pollution but also adapts strategies for climate mitigation. This research emphasizes the critical need to combine approaches to save marine biodiversity and withstand the rapid changes in the environment.

Keywords: microplastic pollution, climate change impacts, marine ecosystems, biodiversity threats, zooplankton ingestion, trophic accumulation, coral reef degradation, ecosystem resilience, plastic pollution mitigation, climate adaptation strategies, SST, sea surface temperature

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Authors: Reetika Sharma, Lalit Tejwani, Himanshu Shekhar, Arun Singhvi

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Purpose: To describe a novel technique of trabeculectomy targeting triple modulation on wound healing to increase the overall success rate. Method: Ten eyes of 10 patients underwent trabeculectomy with subconjunctival mitomycin C (0.4mg/ml for 4 minutes) application combined with Ologen implantation subconjunctivally and subsclerally. Five of these patients underwent additional phacoemulsification with intraocular lens implantation. The Ologen implant was wet with 0.1 ml Bevacizumab. Result: All the eyes achieved target intraocular pressure (IOP), which was maintained until one year of follow-up. Two patients needed anterior chamber reformation at day two post surgery. One patient needed cataract surgery after four months of surgery and achieved target intraocular pressure on two topical antiglaucoma medicines. Conclusion: Vascular endothelial growth factor (VEGF) concentration has been seen to increase in the aqueous humor after filtration surgery. Ologen implantation helps in collagen remodelling, antifibroblastic response, and acts as a spacer. Bevacizumab augmented Ologen, in addition, targets the increased VEGF and helps in decreasing scarring. Anti-VEGF augmented Ologen in trabeculectomy with mitomycin C (MMC) hence appears to have encouraging short-term intraocular pressure control.

Keywords: ologen, anti-VEGF, trabeculectomy, scarring

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Authors: Himanshu Dehra

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An experimental study was conducted for ascertaining electrical and thermal characteristics of a pair of photovoltaic (PV) modules integrated with solar wall of an outdoor room. A pre-fabricated outdoor room was setup for conducting outdoor experiments on a PV solar wall with passive and active ventilation through the outdoor room. The selective operating conditions for glass coated PV modules were utilized for establishing their electrical and thermal characteristics. The PV solar wall was made up of glass coated PV modules, a ventilated air column, and an insulating layer of polystyrene filled plywood board. The measurements collected were currents, voltages, electric power, air velocities, temperatures, solar intensities, and thermal time constant. The results have demonstrated that: i) a PV solar wall installed on a wooden frame was of more heat generating capacity in comparison to a window glass or a standalone PV module; ii) generation of electric power was affected with operation of vertical PV solar wall; iii) electrical and thermal characteristics were not significantly affected by heat and thermal storage losses; and iv) combined heat and electricity generation were function of volume of thermal and electrical resistances developed across PV solar wall. Finally, a comparison of temperature plots of passive and active ventilation envisaged that fan pressure was necessary to avoid overheating of the PV solar wall. The active ventilation was necessary to avoid over-heating of the PV solar wall and to maintain adequate ventilation of room under mild climate conditions.

Keywords: photovoltaic solar wall, solar energy, passive ventilation, active ventilation

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Authors: Himanshu J. Bahirat, Apoorva S. Janawlekar

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Plasma actuators are essential for aerodynamic flow separation control due to their lack of mechanical parts, lightweight, and high response frequency, which have numerous applications in hypersonic or supersonic aircraft. The working of these actuators is based on the formation of a low-temperature plasma between a pair of parallel electrodes by the application of a high-voltage AC signal across the electrodes, after which air molecules from the air surrounding the electrodes are ionized and accelerated through the electric field. The high-frequency operation is required in dielectric discharge barriers to ensure plasma stability. To carry out flow separation control in a hypersonic flow, the optimal design and construction of a power supply to generate dielectric barrier discharges is carried out in this paper. In this paper, it is aspired to construct a simplified circuit topology to emulate the dielectric barrier discharge and study its various frequency responses. The power supply can generate high voltage pulses up to 20kV at the repetitive frequency range of 20-50kHz with an input power of 500W. The power supply has been designed to be short circuit proof and can endure variable plasma load conditions. Its general outline is to charge a capacitor through a half-bridge converter and then later discharge it through a step-up transformer at a high frequency in order to generate high voltage pulses. After simulating the circuit, the PCB design and, eventually, lab tests are carried out to study its effectiveness in controlling flow separation.

Keywords: aircraft propulsion, dielectric barrier discharge, flow separation control, power source

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Authors: Lalit Tejwani, Reetika Sharma, Arun Singhvi, Himanshu Shekhar

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Purpose: To assess the efficacy of collagen matrix implant (Ologen) in phacotrabeculectomy augmented with mitomycin C (MMC). Methods: A biodegradable collagen matrix (Ologen) was placed in the subconjunctival and subscleral space in twenty-two eyes of 22 patients with glaucoma and cataract who underwent combined phacoemulsification and trabeculectomy augmented with MMC. All of them were examined preoperatively and on the first postoperative day. They were followed for twelve months after surgery. Any intervention needed in follow-up period was noted. Any complication was recorded. The primary outcome measure was postoperative intraocular pressure at one year follow-up. Any additional postoperative treatments needed and adverse events were noted. Results: The mean age of patients included in the study was 57.77 ± 9.68 years (range=36 to 70 years). All the patients were followed for at least one year. Three patients had history of failed trabeculectomy. Fifteen patients had chronic angle closure glaucoma with cataract, five had primary open angle glaucoma with cataract, one had uveitic glaucoma with cataract, and one had juvenile open angle glaucoma with cataract. Mean preoperative IOP was 32.63 ± 8.29 mm Hg, eighteen patients were on oral antiglaucoma medicines. The mean postoperative IOP was 10.09 ± 2.65 mm Hg at three months, 10.36 ± 2.19 mm Hg at six months and 11.36 ± 2.72 mm Hg at one year follow up. No adverse effect related to Ologen was seen. Anterior chamber reformation was done in five patients, and three needed needling of bleb. Four patients needed additional antiglaucoma medications in the follow-up period. Conclusions: Combined phacotrabeculectomy with MMC with Ologen implantation appears to be a safe and effective option in glaucoma patients needing trabeculectomy with significant cataract. Comparative studies with longer duration of follow-up in larger number of patients are needed.

Keywords: combined surgery, ologen, phacotrabeculectomy, success

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Authors: Reetika Sharma, Lalit Tejwani, Himanshu Shekhar, Arun Singhvi

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Purpose: Advanced Glaucoma with Failed trab is not an uncommon sight in glaucoma clinic, and such cases usually tend to present with high intraocular pressure (IOP) and advanced cupping, or even glaucomatous atrophy stage. Re-surgery is needed for such cases, and wound modulation poses a major challenge in these cases. We share our experience in this case series with the use of Ologen (collagen matrix implant) along with MMC 0.04% used in surgery. The purpose of the study was to evaluate the efficacy and outcome of collagen matrix implant in re-trabeculectomy in advanced glaucoma cases. Methodology: Eleven eyes of 11 patients (one eye of one patient) underwent re-trabeculectomy surgery with MMC and Ologen. Ologen implant was used in sub scleral and subconjunctival space, as a spacer and wound modulator. In five cases, triple modulation with implant soaked in anti-VEGF was used. Results: All patients had cupping more than 0.9, and one case was GOA. All cases were on maximal medication at presentation and majority were on systemic anti-glaucoma therapy also. Post-surgery, follow-up ranged from 13 – 34 months, and all cases had a follow longer than the gap between previous surgery (which was failed) and re-trab. One case needed AC reformation and one needling was done. Phaco was done at same sitting in four cases. All cases had their IOP lowered post surgery, and vision was maintained in all, however one case was considered as failed re-surgery case. Topical medication was needed in seven cases post-surgery also. Conclusion: Ologen as adjuvant should be considered in all re-trab cases and all high risk and advanced cases, and triple modulation can be next step in these cases. Aggressive IOP control and non- reluctance to continue topical medications post second surgery should be considered in such cases, to give them best possible vision.

Keywords: failed trabeculectomy, ologen, trabeculectomy, advanced glaucoma

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Authors: Rajat Jain, Himanshu Pandey, Somesh Mehta, Pravin P. Patil

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Formula SAE cars are the student designed and fabricated formula prototype cars, designed according to SAE INTERNATIONAL design rules which compete in the various national and international events. This paper shows a FEM based comparative study of free vibration analysis of different mode shapes of a formula prototype car chassis frame. Tubing sections of different diameters as per the design rules are designed in such a manner that the desired strength can be achieved. Natural frequency of first five mode was determined using finite element analysis method. SOLIDWORKS is used for designing the frame structure and SOLIDWORKS SIMULATION and ANSYS WORKBENCH 16.2 are used for the modal analysis. Mode shape results of ANSYS and SOLIDWORKS were compared. Fixed –fixed boundary conditions are used for fixing the A-arm wishbones. The simulation results were compared for the validation of the study. First five modes were compared and results were found within the permissible limits. The AISI4130 (CROMOLY- chromium molybdenum steel) material is used and the chassis frame is discretized with fine quality QUAD mesh followed by Fixed-fixed boundary conditions. The natural frequency of the chassis frame is 53.92-125.5 Hz as per the results of ANSYS which is found within the permissible limits. The study is concluded with the light weight and compact chassis frame without compensation with strength. This design allows to fabricate an extremely safe driver ergonomics, compact, dynamically stable, simple and light weight tubular chassis frame with higher strength.

Keywords: FEM, modal analysis, formula SAE cars, chassis frame, Ansys

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Authors: Himanshu Rohela

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BACKGROUND: Ewing sarcoma can arise in either bone or soft tissue. Extraskeletal Ewing sarcoma (EES) is an uncommon primary tumor of the soft tissues, accounting for 20 30% of all reported cases of ES. AIM: Was to investigate demographic distribution, survival analysis and factors affecting the survival and recurrence in patients of EES. METHODS: Retrospective study of 19 biopsy-proven EES was performed. Overall survival (OS) using log-rank test and factors affecting OS and local recurrence (LR) were evaluated for the entire cohort. RESULTS: Patients with EES had a mean age of 19.5 and it was more commonly seen in males (63%). Axial location (58%) and solitary presentation (84%) were more common. The average size was 11 cm, 3 of 19 were metastatic at presentation, with the lung beings the most common site for metastasis. 17 received NACT, 16 with VAC-IE regimen and 1 underwent a second line with GEM/DOCE regimen. Unplanned surgery was done in 2 of 19. 3 patients received definitive RT and 13 underwent surgical-wide local excision. 2 of 13 showed good response to NACT. 10 patients required readmission out of which 6 patients had chemotherapy-related complications, 2 had surgical site complications and one patient developed secondary AML post-completion of treatment. A total of 4 patients had a recurrence. One had local recurrence alone, one had distant recurrence alone and 2 patients had a distant and local recurrence both. Tumor size >10 cm, axial location, and previous unplanned surgery was associated with higher LR rate. The mean overall survival was 32 months (2.66 years), with higher rates seen in non-metastatic and non-recurrent settings. CONCLUSIONS: Early and accurate diagnosis is the key to the management of EES, with promising results seen via NACT and RO resection regimens. But further studies with larger study groups are needed to standardize the treatment protocol and evaluate its efficacy.

Keywords: Ewings, sarcoma, extraskeletal, chemotherapy

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Authors: Navneet Sharma, Himanshu Ojha, Dharam Pal Pathak, Rakesh Kumar Sharma

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Radio-nuclides decontamination is an important task because any extra second of deposition leads to deleterious health effects. We had developed and characterise nanoemulsion of p-tertbutylcalix[4]arens using phase inversion temperature (PIT) method and evaluate its decontamination efficacy (DE). The solubility of the drug was determined in various oils and surfactants. Nanoemulsion developed with an HLB value of 11 and different ratios of the surfactants 10% (7:3, w/w), oil (20%, w/w), and double distilled water (70%) were selected. Formulation was characterised by multi-photon spectroscopy and parameters like viscosity, droplet size distribution, zeta potential and stability were optimised. In vitro and Ex vivo decontamination efficacy (DE) was evaluated against Technetium-99m, Iodine-131, and Thallium-201 as radio-contaminants applied over skin of Sprague-Dawley rat and human tissue equivalent model. Contaminants were removed using formulation soaked in cotton swabs at different time intervals and whole body imaging and static counts were recorded using SPECT gamma camera before and after decontamination attempt. Data were analysed using one-way analysis of variance (ANOVA) and was found to be significant (p <0.05). DE of the nanoemulsion loaded with p-tertbutylcalix[4]arens was compared with placebo and recorded to be 88±5%, 90±3% and 89±3% for 99mTc, 131I and 201Tl respectively. Ex-vivo complexation study of p-tertbutylcalix[4]arene nanoemulsion with surrogate nuclides of radioactive thallium and Iodine, were performed on rat skin mounted on Franz diffusion cell using high-resolution sector field inductively coupled plasma mass spectroscopy (HR-SF-ICPMS). More than 90% complexation of the formulation with these nuclides was observed. Results demonstrate that the prepared nanoemulsion formulation was found efficacious for the decontamination of radionuclides from a large contaminated population.

Keywords: p-tertbutylcalix[4]arens, skin decontamination, radiological emergencies, nanoemulsion, iodine-131, thallium-201

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Authors: Himanshu Singh, Rishi Kant, Shantanu Bhattacharya

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This paper adopts a top-down approach for mathematical modeling to predict the size reduction from micro to nano-scale through persistent etching. The process is simulated using a finite difference approach. Previously, various researchers have simulated the etching process for 1-D and 2-D substrates. It consists of two processes: 1) Convection-Diffusion in the etchant domain; 2) Chemical reaction at the surface of the particle. Since the process requires analysis along moving boundary, partial differential equations involved cannot be solved using conventional methods. In 1-D, this problem is very similar to Stefan's problem of moving ice-water boundary. A fixed grid method using finite volume method is very popular for modelling of etching on a one and two dimensional substrate. Other popular approaches include moving grid method and level set method. In this method, finite difference method was used to discretize the spherical diffusion equation. Due to symmetrical distribution of etchant, the angular terms in the equation can be neglected. Concentration is assumed to be constant at the outer boundary. At the particle boundary, the concentration of the etchant is assumed to be zero since the rate of reaction is much faster than rate of diffusion. The rate of reaction is proportional to the velocity of the moving boundary of the particle. Modelling of the above reaction was carried out using Matlab. The initial particle size was taken to be 50 microns. The density, molecular weight and diffusion coefficient of the substrate were taken as 2.1 gm/cm3, 60 and 10-5 cm2/s respectively. The etch-rate was found to decline initially and it gradually became constant at 0.02µ/s (1.2µ/min). The concentration profile was plotted along with space at different time intervals. Initially, a sudden drop is observed at the particle boundary due to high-etch rate. This change becomes more gradual with time due to declination of etch rate.

Keywords: particle size reduction, micromixer, FDM modelling, wet etching

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Authors: A. Kumar, D. Himanshu, Ak Vaish, K. Usman , A. Singh, R. Misra, V. Atam, S. P. Verma, S. Singhal

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Introduction: Resistant and uncontrolled hypertension offer great challenge, in terms of higher risk of morbidity, mortality and not the least, difficulty in diagnosis and management. Our study tries to identify the importance of two crucial aspects of hypertension management, i.e. drug compliance and optimum dosing and also the effect of spironolactone on blood pressure in cases of resistant hypertension. Methodology: A prospective study was carried out among patients, who were referred as case of resistant hypertension to Hypertension Clinic at Gandhi memorial and associated hospital, Lucknow, India from August, 2013 to July 2014. A total of 122 Subjects having uncontrolled BP with ≥3 antihypertensives were selected. After ruling out secondary resistance and with appropriate lifestyle modifications, effect of adherence and optimum doses was seen with monitoring of BP. Only those having blood pressure still uncontrolled were true resistant. These patients were given spironolactone to see its effect on BP over next 12 weeks. Results: Mean baseline BP of all (n=122) patients was 150.4±7.2 mmHg systolic and 92.1±5.7 mmHg diastolic. After promoting adherence to the regimen, there was reduction of 4.20±3.65 mmHg systolic and 2.08±4.74 mmHg Diastolic blood pressure, with 26 patients achieving target blood pressure goal. Further reduction of 6.66±5.99 mmHg in systolic and 2.59±3.67 mmHg in diastolic BP was observed after optimizing the drug doses with another 66 patients achieving target blood pressure goal. Only 30 patients were true resistant hypertensive and prescribed spironolactone. Over 12 weeks, mean reduction of 20.62±3.65 mmHg in systolic and 10.08 ± 6.46 mmHg in diastolic BP was observed. Out of these 30, BP was controlled in 24 patients. Side effects observed were hyperkalemia in 2 patients and breast tenderness in 2 patients. Conclusion: Improper adherence and suboptimal regimen appear to be the important reasons for uncontrolled hypertension. By virtue of maintaining proper adherence to an optimum regimen, target BP goal can be reached in many without adding much to the regimen. Spironolactone is effective in patients with resistant hypertension, in terms of blood pressure reduction with minimal side effects.

Keywords: resistant, hypertension, spironolactone, blood pressure

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Authors: Himanshu Lal, Bipasha Ghosh, Arun Srivastava

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A pilot study of indoor air quality in terms of bioaerosol (fungus and bacteria) and few selective microbial volatile organic compounds (MVOCs) was carried out in different indoor sections of a library for two seasons, namely monsoon and post monsoon. Bioaerosol sampling was carried out using Anderson six stage viable sampler at a flow rate of 28.3 L/min while MVOCs were collected on activated charcoal tubes ORBOTM 90 Carboxen 564.Collected MVOCs were desorbed using carbon disulphide (CS2) and analysed by GC-FID. Microscopic identification for fungus was only carried out. Surface dust was collected by sterilised buds and cultured to identify fungal contaminants. Unlike bacterial size distribution, fungal bioaerosol concentration was found to be highest in the fourth stage in different sections of the library. In post monsoon season both fungal bioaerosol (710 to 3292cfu/m3) and bacterial bioaerosol (298 to 1475cfu/m3) were fund at much greater concentration than in monsoon. In monsoon season unlike post monsoon, I/O ratio for both the bioaerosol fractions was more than one. Rain washout could be the reason of lower outdoor concentration in monsoon season. On the contrary most of the MVOCs namely 1-hexene, 1-pentanol and 1-octen-3-ol were found in the monsoon season instead of post monsoon season with the highest being 1-hexene with 7.09µg/m3 concentration. Among the six identified fungal bioaerosol Aspergillus, Cladosporium and Penicillium were found in maximum concentration while Aspergillus niger, Curvuleria lunata, Cladosporium cladosporioides and Penicillium sp., was indentified in surface dust samples. According to regression analysis apart from environmental factors other factors also played an important role. Thus apart from outdoor infiltration and human sources, accumulated surface dust mostly on organic materials like books, wooden furniture and racks can be attributed to being one of the major sources of both fungal bioaerosols as well as MVOCs found in the library.

Keywords: bacteria, Fungi, indoor air, MVOCs

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Authors: Himanshu Shekhar Maharana, S. K .Dash

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Economic Load Dispatch (ELD) proves to be a vital optimization process in electric power system for allocating generation amongst various units to compute the cost of generation, the cost of emission involving global warming gases like sulphur dioxide, nitrous oxide and carbon monoxide etc. In this dissertation, we emphasize ramp rate constriction factor based particle swarm optimization (RRCPSO) for analyzing various performance objectives, namely cost of generation, cost of emission, and a dual objective function involving both these objectives through the experimental simulated results. A 6-unit 30 bus IEEE test case system has been utilized for simulating the results involving improved weight factor advanced ramp rate limit constraints for optimizing total cost of generation and emission. This method increases the tendency of particles to venture into the solution space to ameliorate their convergence rates. Earlier works through dispersed PSO (DPSO) and constriction factor based PSO (CPSO) give rise to comparatively higher computational time and less good optimal solution at par with current dissertation. This paper deals with ramp rate and constriction factor based well defined ramp rate PSO to compute various objectives namely cost, emission and total objective etc. and compares the result with DPSO and weight improved PSO (WIPSO) techniques illustrating lesser computational time and better optimal solution. 

Keywords: economic load dispatch (ELD), constriction factor based particle swarm optimization (CPSO), dispersed particle swarm optimization (DPSO), weight improved particle swarm optimization (WIPSO), ramp rate and constriction factor based particle swarm optimization (RRCPSO)

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Authors: Akhila Vasudev, Himanshu Kaushik, Tadikonda Venkata Bharat

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A large number of mine tailings are produced every year as part of the extraction process of phosphates, gold, copper, and other materials. Mine tailings are high in water content and have very slow dewatering behavior. The efficient design of tailings dam and economical disposal of these slurries requires the knowledge of tailings consolidation behavior. The large-strain consolidation theory closely predicts the self-weight consolidation of these slurries as the theory considers the conservation of mass and momentum conservation and considers the hydraulic conductivity as a function of void ratio. Classical laboratory techniques, such as settling column test, seepage consolidation test, etc., are expensive and time-consuming for the estimation of hydraulic conductivity variation with void ratio. Inverse estimation of the constitutive relationships from the measured settlement versus time curves is explored. In this work, inverse analysis based on metaheuristics techniques will be explored for predicting the hydraulic conductivity parameters for mine tailings from the base excess pore water pressure dissipation curve and the initial conditions of the mine tailings. The proposed inverse model uses particle swarm optimization (PSO) algorithm, which is based on the social behavior of animals searching for food sources. The finite-difference numerical solution of the forward analytical model is integrated with the PSO algorithm to solve the inverse problem. The method is tested on synthetic data of base excess pore pressure dissipation curves generated using the finite difference method. The effectiveness of the method is verified using base excess pore pressure dissipation curve obtained from a settling column experiment and further ensured through comparison with available predicted hydraulic conductivity parameters.

Keywords: base excess pore pressure, hydraulic conductivity, large strain consolidation, mine tailings

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Authors: Himanshu Sharma, Karthik Kumar, Harish Kumar

Abstract:

The major problem in crop cultivation is the occurrence of multiple crop diseases. During the growth stage, timely identification of crop diseases is paramount to ensure the high yield of crops, lower production costs, and minimize pesticide usage. In most cases, crop diseases produce observable characteristics and symptoms. The Surveyors usually diagnose crop diseases when they walk through the fields. However, surveyor inspections tend to be biased and error-prone due to the nature of the monotonous task and the subjectivity of individuals. In addition, visual inspection of each leaf or plant is costly, time-consuming, and labour-intensive. Furthermore, the plant pathologists and experts who can often identify the disease within the plant according to their symptoms in early stages are not readily available in remote regions. Therefore, this study specifically addressed early detection of leaf scald, red rot, and eyespot types of diseases within sugarcane plants. The study proposes a computer vision-based approach using a convolutional neural network (CNN) for automatic identification of crop diseases. To facilitate this, firstly, images of sugarcane diseases were taken from google without modifying the scene, background, or controlling the illumination to build the training dataset. Then, the testing dataset was developed based on the real-time collected images from the sugarcane field from India. Then, the image dataset is pre-processed for feature extraction and selection. Finally, the CNN-based Visual Geometry Group (VGG) model was deployed on the training and testing dataset to classify the images into diseased and healthy sugarcane plants and measure the model's performance using various parameters, i.e., accuracy, sensitivity, specificity, and F1-score. The promising result of the proposed model lays the groundwork for the automatic early detection of sugarcane disease. The proposed research directly sustains an increase in crop yield.

Keywords: automatic classification, computer vision, convolutional neural network, image processing, sugarcane disease, visual geometry group

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