Comparative Evaluation of Salivary Biomarker Levels in e-Cigarette Smokers and Conventional Smokers
The cigarette smoking and its effect on the inflammatory cytokine levels in the smoker's sali... more The cigarette smoking and its effect on the inflammatory cytokine levels in the smoker's saliva depicted the influence of electronic cigarettes on oral cytokine levels in oral fluids are scarce in the literature. The present trial was conducted to compare and determine the proinflammatory and anti-inflammatory cytokines in whole stimulated saliva samples of electronic cigarette smokers, conventional smokers, and participants with no smoke exposure. Sixty adult participants were divided into the following four groups of nonsmokers, current smokers, smokers smoking both conventional and e-cigarettes, and e-cigarette smokers. The saliva samples were assessed for Interleukins (IL-1B, 6, 8, 10, and IL-1RA), C-reactive protein (CRP), and tumor necrosis factor-alpha (TNF-α) using enzyme-linked immunosorbent assay. Plaque scores and Gingival Index, and body mass index were also calculated. Statistically significant (P < 0.05) and remarkable relationship was seen in plaque scores and IL 1RA, 1 β, and 10 with the respective values as-0.285, 0.268, and 0.267. Regarding anti-inflammatory cytokines, CRP, IL-10, and IL-RA had the P-value of 0.073, 0.945, and 0.834 respectively. When these values were evaluated for proinflammatory cytokines, the P values were 0.0001, 0.019, 0.991, and 903 for TNF-α, IL-1 β, IL-6, and IL-8, respectively. These results were statistically significant for TNF-α (P = 0.001). Within its limitations, the present study concludes that smoking e-cigarettes whether solely or in combination with conventional smoking increases the levels of proinflammatory cytokines such as TNF-α and IL-1 β with decreased counter IL-1RA levels.
Convolutional Neural networks nowadays are of tremendous importance for any image classification ... more Convolutional Neural networks nowadays are of tremendous importance for any image classification system. One of the most investigated methods to increase the accuracy of CNN is by increasing the depth of CNN. Increasing the depth by stacking more layers also increases the difficulty of training besides making it computationally expensive. Some research found that adding auxiliary forks after intermediate layers increases the accuracy. Specifying which intermediate layer shoud have the fork just addressed recently. Where a simple rule were used to detect the position of intermediate layers that needs the auxiliary supervision fork. This technique known as convolutional neural networks with deep supervision (CNDS). This technique enhanced the accuracy of classification over the straight forward CNN used on the MIT places dataset and ImageNet. In the other side, Residual Learning is another technique emerged recently to ease the training of very deep CNN. Residual Learning framwork cha...
Advances in Solar Power Generation and Energy Harvesting, 2020
In the development of next-generation solar panels, high-energy conversion efficiency has been th... more In the development of next-generation solar panels, high-energy conversion efficiency has been the focal point of global research in energy. More than 80% of the efficiency of solar panels is wasted. In order to materialize this wasted energy, there has been an emerging interest in innovating hybrid solar-thermoelectric systems. In this chapter, we propose a novel hybrid photovoltaic-thermoelectric system and its expansive experimental analysis. This modified system consists of a solar wafer, thermoelectric generator (TEG), and a heat sink, which is placed beneath the solar cell of the same size to dissipate heat. A series of experiments have been performed under certain laboratory conditions, which remain constant for all sets of experiments. The heat sink beneath the solar cell reduces the working temperature of the cell from 72°C (without heat sink) to 52°C (with heat sink and TEG), which leads to approximately 10% increment in the relative efficiency of the solar cell. Finally, a thermoelectric generator (TEG) is inserted between the solar cell and heat sink. The TEG adds an extra power of 1.2 mW to the total output of the system.
Prioritization of Near-Miss Incidents Using Text Mining and Bayesian Network
Near-Miss incidents can be treated as events to signal the weakness of safety management system (... more Near-Miss incidents can be treated as events to signal the weakness of safety management system (SMS) at the workplace. Analyzing near-misses will provide relevant root causes behind such incidents so that effective safety related interventions can be developed beforehand. Despite having a huge potential towards workplace safety improvements, analysis of near-misses is scant in the literature owing to the fact that near-misses are often reported as text narratives. The aim of this study is therefore to explore text-mining for extraction of root causes of near-misses from the narrative text descriptions of such incidents and to measure their relationships probabilistically. Root causes were extracted by word cloud technique and causal model was constructed using a Bayesian network (BN). Finally, using BN’s inference mechanism, scenarios were evaluated and root causes were listed in a prioritized order. A case study in a steel plant validated the approach and raised concerns for varie...
2018 9th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON), 2018
Deep learning neural networks have made significant progress in image analysis and have been used... more Deep learning neural networks have made significant progress in image analysis and have been used for skin cancer recognition. Early detection and proper treatments for malignant skin cancer cases are vital to ensure high survival rate in patients. We present a novel deep learning based convolutional neural network (CNN) model for generating compatible models on mobile platforms such as Android and iOS. The proposed model was tested on the grand challenge PHDB melanoma dataset. The best performing proposed model excels in the following ways: (1) it outperforms the baseline model in terms of accuracy by 1%; (2) it consists of 60% fewer parameters compared to the base model and thereby it is more efficient on mobile platforms. Furthermore, the model is more compact and retains high accuracy without the need to be downsized; (3) in conjunction with advanced regularization techniques such as dropout and data augmentation, the proposed CNN model excelled when implemented on state-of-the-art frameworks such as Keras and TensorFlow. Additionally, we were able to successfully deploy it on the iOS and Android mobile systems. The proposed model could also be lucrative towards other datasets for image classification on mobile platform.
This paper presents solar and wind hybrid energy system with battery storage along with AC mains ... more This paper presents solar and wind hybrid energy system with battery storage along with AC mains supply. This, configuration allows the three sources to the battery as well as supply the load separately or simultaneously depending on the availability of the energy sources. In many rural area of India, electricity has not reached their home yet as well as many people face load shedding problem. A hybrid design of battery charging system and its implementation has been explained in this paper. Besides AC mains supply charging, solar PV, wind energy also charges the battery whenever it is available through a charge controller. This system ensures continuous power supply and faster charging of battery. The system has been designed to suit a typical Indian scenario where there is power shortage which result in scheduled and unscheduled power shedding. Today, the world is progressing at quite fast rate with the use of the conventional source of energy. The two majors disadvantage of using...
Diabetic retinopathy (DR) is a common eye disease that could lead to irreversible vision loss but... more Diabetic retinopathy (DR) is a common eye disease that could lead to irreversible vision loss but hard to be noticed by carriers in early stages. Instead of isolating DR signs for DR recognition, this paper examines discriminant texture features obtained by color multi-scale uniform local binary pattern (LBPs) descriptors on five common color spaces and two proposed hybrid color spaces. The extracted features are evaluated by the enhanced Fisher linear discriminant, EFM. Experiments are done on a large dataset of 35,126 training images and 53,576 testing images that have been taken by different devices with high variance in dimensions, quality and luminance.
Now a day's software is the baseline for the success of any organization. There is a huge dem... more Now a day's software is the baseline for the success of any organization. There is a huge demand of quality software in the customer-oriented market. Regression testing makes it possible but it’s a costly affair. Regression test suite minimization is way to reduce this cost but it is NP hard problem. This paper proposes an effective approach for regression test suite minimization using Artificial Ecosystem Optimization algorithm. To improve its performance a modified Artificial Ecosystem Optimization algorithm is proposed for Test case minimization. To evaluate the performance of proposed approach experiment is conducted in controlled parameter setting on open-source subject program from SIR repository. The results are collected and analyzed in comparison to existing approaches using statistical test. The test results reflect the superiority of proposed approach.
“An Insight into Neurodegenerative Disorders, their therapeutic approaches and drugs available for tackling with Neurodegeneration: A Review”
The term neurodegenerative refers to diseases that are usually recognized by symptoms like decrea... more The term neurodegenerative refers to diseases that are usually recognized by symptoms like decreased motor control, mood disorders, an d cognitive deficits. Some of the common neurodegenerative diseases are Alzheimer&#39;s disease, Parkinson&#39;s disease, Huntington&#39;s disease, amyotrophic lateral sclerosis, frontotemporal dementia, and the spinocerebellar ataxias. These diseases are complex and diverse in their pathophysiology with some causing memory and cognitive impairments and others affecting a person&#39;s ability to move, speak, control, and breathe. T here are some prevalent drugs and therapies, which seems to be effective in improving the disease condition. Thus, It is need of the hour to develop new and more effective therapeutic approaches and strategies to manage and potentially tackle these devastating neurodegenerative diseases.
Verma and Mayadhar Barik. Currently, coronaviruses are contagious pathogens and primarily respons... more Verma and Mayadhar Barik. Currently, coronaviruses are contagious pathogens and primarily responsible for respiratory and intestinal infections (RIIs). Research on progress to develop antiviral agents (AVAs) against these coronavirus. Researcher had been demonstrated that the main protease (Mpro) protein may represents an effective drug target (EDT) [1]. The novel Corona-virus (n-CoV), recently called as the severe acute respiratory syndrome coronavirus (SARS-CoV-2). The
The processing and material properties of commercial organic semiconductors, for e.g. fullerenes ... more The processing and material properties of commercial organic semiconductors, for e.g. fullerenes is largely controlled by their precise arrangements, specially intermolecular symmetries, distances and orientations, more specifically, molecular polarisabilities. These supramolecular parameters heavily influence their electronic structure, thereby determining molecular photophysics and therefore dictating their usability as n-type semiconductors. In this article we evaluate van der Waals potentials of a fullerene dimer model system using two approaches: a) Density Functional Theory and, b) Macroscopic Quantum Electrodynamics, which is particularly suited for describing long-range van der Waals interactions. Essentially, we determine and explain the model symmetry, distance and rotational dependencies on binding energies and spectral changes. The resultant spectral tuning is compared using both methods showing correspondence within the constraints placed by the different
2016 IEEE International Symposium on Multimedia (ISM), 2016
Automatic diabetes retinopathy (DR) recognition can help DR carriers to receive treatment in earl... more Automatic diabetes retinopathy (DR) recognition can help DR carriers to receive treatment in early stages and avoid the risk of vision loss. In this paper, we emphasize the role of multiple filter sizes in learning fine-grained discriminant features and propose: (i) two deep convolutional neural networks -Combined Kernels with Multiple Losses Network (CKML Net) and VGGNet with Extra Kernel (VNXK), which are an improvement upon GoogLeNet and VGGNet in context of DR tasks. Learning from existing research, (ii) we propose a hybrid color space, LGI, for DR recognition via proposed nets. (iii) Transfer learning is applied to solve the challenge of imbalanced dataset. The effectiveness of proposed new nets and color space is evaluated using two grand challenge retina datasets: EyePACS and Messidor. Our experimental results show: (iv) CKML Net improves upon GoogLeNet and VNXK improves upon VGGNet on both datasets using the LGI color space. Additionally, proposed methodology improves upon other state of the art results on Messidor dataset for referable/non-referable screening.
Dermestes maculatus is a very important pest of smoke-dried fish that destroys the flesh, eating ... more Dermestes maculatus is a very important pest of smoke-dried fish that destroys the flesh, eating away the muscles, and leaving the skeletons when cured fish are stored for long period. This necessitates the idea of establishing an alternative repellant from natural plant products. In this article, compounds of Capsicum annum will be studied against repellent protein NDS2 of D. maculatus. The compounds present in C. annum. were docked against The NADH dehydrogenase subunit 2 (NDS2) protein of D. maculatus. PyRx-Python prescription 0.8 was used to identify binding affinities of compounds against the proteins. The results we obtained from molecular docking show that among 48 molecules of natural origin from C. annuum was downloaded in SDF format from the NCBI PubChem database. Six molecules are the best compounds observed through molecular docking and some hydrogen bonding and hydrophobic interactions are proposed as the efficacy from C. annuum on a repellent protein of D. maculatus. The molecular docking was performed to establish efficacy and binding affinity of ligands from C. annum on the repellent protein of D. maculatus. ADMET analysis is performed to establish the possible toxicity of the ligands. Importantly, all six natural compounds present in C. annum. may be more potent in new insecticide against NSD2 in D. maculatus but needs further experimental research.
The new coronavirus called SARS-CoV-2 is a new type of virus named as COVID-19. Although, it has ... more The new coronavirus called SARS-CoV-2 is a new type of virus named as COVID-19. Although, it has few similarities with pandemic flu viruses, the respiratory system and immune system are damaged through the viruses infected the population who has weakened immunity. SARS-CoV-2 spreads when people don't have the sign and symptoms. This virus COVID-19 appears to spread more easily than the flu, and asymptomatic transmission may account for a greater proportion of COVID-19's spreader over the World. In inundation of the current understanding, the roles of insect vectors are helping in the transmission of viral pathogens as well and the possible roles of some newly joined insects in the mechanical transmission of COVID-19. We also specifically provide the prevention and control methods related to contamination, disease burden, risk pattern in the family, near and dear to maintain the precision of social distancing and development of the immune system to fight against SARS-CoV-2.
International Journal of Computational Vision and Robotics, 2018
Plankton are extremely diverse groups of organisms that exist in large water columns. They are so... more Plankton are extremely diverse groups of organisms that exist in large water columns. They are sources of food for fishes and many other marine life animals. The plankton distribution is essential for the survival of many ocean lives and plays a critical role in marine ecosystem. In recent years, intelligent image classification systems were developed to study plankton distribution through classification of the plankton images taken by underwater imaging devices. Due to the significant differences in both shapes and sizes of the plankton population, accurate classification poses a daunting challenge. The mixed quality of the collected images adds more difficulty to the task. In this paper, we present an intelligent machine learning system built on convolutional neural networks (CNN) for plankton image classification. Unlike most of the existing image classification algorithms, CNN based systems do not depend on features engineering and they can be efficiently extended to encompass new classes. The experimental results on SIPPER image datasets show that the proposed system achieves higher accuracy compared with the state-of-the-art approaches. The new system is also capable of learning a much larger number of plankton classes.
Journal of Evolution of Medical and Dental Sciences, 2017
BACKGROUND The estimated annual burn incidence in India is approximately 6-7 million per year. Bu... more BACKGROUND The estimated annual burn incidence in India is approximately 6-7 million per year. Burn injury is a common but preventable cause of morbidity and mortality in India. In patients of epilepsy, the burn injury is far more severe than the any other comorbidities. MATERIALS AND METHODS This study design was a retrospective-descriptive study which was conducted in burn unit of MY Hospital, Indore with intention of identifying the risk factors for burn injury in epileptic patients. Study was conducted over a period of six years from the January 2009 to December 2015. RESULTS Maximum patients were of age group less than 40 years and most of them were females. All the burns were accidental in nature. Flame was the commonest mode of injury. Most of the patients sustained deep burns (60%) of upper limb (62.8%). Most of the patients had Generalised Tonic-clonic type of seizure and 88.5% of patients were not compliant to drug therapy. CONCLUSION Burn injuries sustained in epileptic patients are of very severe degree. These injuries are preventable if epileptic patients follow the general safety guidelines and remain stick to their treatment protocols.
A preliminary analysis of incident investigation reports of an integrated steel plant: some reflection
International Journal of Injury Control and Safety Promotion, 2017
ABSTRACT Large integrated steel plants employ an effective safety management system and gather a ... more ABSTRACT Large integrated steel plants employ an effective safety management system and gather a significant amount of safety-related data. This research intends to explore and visualize the rich database to find out the key factors responsible for the occurrences of incidents. The study was carried out on the data in the form of investigation reports collected from a steel plant in India. The data were processed and analysed using some of the quality management tools like Pareto chart, control chart, Ishikawa diagram, etc. Analyses showed that causes of incidents differ depending on the activities performed in a department. For example, fire/explosion and process-related incidents are more common in the departments associated with coke-making and blast furnace. Similar kind of factors were obtained, and recommendations were provided for their mitigation. Finally, the limitations of the study were discussed, and the scope of the research works was identified.
Study of metal strip insertion and its optimization in doping less TFET
Superlattices and Microstructures, 2018
Abstract In this manuscript, a novel structure for dopingless tunnel field effect transistor (DL ... more Abstract In this manuscript, a novel structure for dopingless tunnel field effect transistor (DL TFET) is introduced which comprises of metal strip (MS) in the oxide region near source/channel junction. Gate and drain work function engineering with hetero gate dielectric is used in this device which enhances the ON-state current, reduces the ambipolarity and also improves the RF performance. The increment in ON-state current with high subthreshold swing is achieved by the effect of MS. Steeper tunneling junction is achieved with the help of aforementioned modifications at the S/C junction. In this way, we increase the rate of tunneling at this interface and because of this, the threshold voltage of the proposed device reduces drastically. Further, study of ambipolarity suppression is done by using underlap of gate electrode near drain/channel (D/C) interface. Furthermore, temperature variation effect also incorporated in this manuscript, where study related to the threshold voltage and ON-state current is analysed by TCAD simulation. Moreover, most optimized MS length and work function are concluded in this paper for all simulations. Optimization for MS length and workfunction is analysed using TCAD simulation tool and shown in tabular form with one table showing effect of different work functions of MS on threshold voltage, ON-state current and SS, whereas another table shows the effect of MS length variations on RF parameters.
Comparing Outcomes of Endoscopic Versus Duplex-Guided Open Subfascial Interruption of Incompetent Perforators in Management of Varicose Veins: A Randomized Control Trial
Comparative Evaluation of Salivary Biomarker Levels in e-Cigarette Smokers and Conventional Smokers
The cigarette smoking and its effect on the inflammatory cytokine levels in the smoker's sali... more The cigarette smoking and its effect on the inflammatory cytokine levels in the smoker's saliva depicted the influence of electronic cigarettes on oral cytokine levels in oral fluids are scarce in the literature. The present trial was conducted to compare and determine the proinflammatory and anti-inflammatory cytokines in whole stimulated saliva samples of electronic cigarette smokers, conventional smokers, and participants with no smoke exposure. Sixty adult participants were divided into the following four groups of nonsmokers, current smokers, smokers smoking both conventional and e-cigarettes, and e-cigarette smokers. The saliva samples were assessed for Interleukins (IL-1B, 6, 8, 10, and IL-1RA), C-reactive protein (CRP), and tumor necrosis factor-alpha (TNF-α) using enzyme-linked immunosorbent assay. Plaque scores and Gingival Index, and body mass index were also calculated. Statistically significant (P < 0.05) and remarkable relationship was seen in plaque scores and IL 1RA, 1 β, and 10 with the respective values as-0.285, 0.268, and 0.267. Regarding anti-inflammatory cytokines, CRP, IL-10, and IL-RA had the P-value of 0.073, 0.945, and 0.834 respectively. When these values were evaluated for proinflammatory cytokines, the P values were 0.0001, 0.019, 0.991, and 903 for TNF-α, IL-1 β, IL-6, and IL-8, respectively. These results were statistically significant for TNF-α (P = 0.001). Within its limitations, the present study concludes that smoking e-cigarettes whether solely or in combination with conventional smoking increases the levels of proinflammatory cytokines such as TNF-α and IL-1 β with decreased counter IL-1RA levels.
Convolutional Neural networks nowadays are of tremendous importance for any image classification ... more Convolutional Neural networks nowadays are of tremendous importance for any image classification system. One of the most investigated methods to increase the accuracy of CNN is by increasing the depth of CNN. Increasing the depth by stacking more layers also increases the difficulty of training besides making it computationally expensive. Some research found that adding auxiliary forks after intermediate layers increases the accuracy. Specifying which intermediate layer shoud have the fork just addressed recently. Where a simple rule were used to detect the position of intermediate layers that needs the auxiliary supervision fork. This technique known as convolutional neural networks with deep supervision (CNDS). This technique enhanced the accuracy of classification over the straight forward CNN used on the MIT places dataset and ImageNet. In the other side, Residual Learning is another technique emerged recently to ease the training of very deep CNN. Residual Learning framwork cha...
Advances in Solar Power Generation and Energy Harvesting, 2020
In the development of next-generation solar panels, high-energy conversion efficiency has been th... more In the development of next-generation solar panels, high-energy conversion efficiency has been the focal point of global research in energy. More than 80% of the efficiency of solar panels is wasted. In order to materialize this wasted energy, there has been an emerging interest in innovating hybrid solar-thermoelectric systems. In this chapter, we propose a novel hybrid photovoltaic-thermoelectric system and its expansive experimental analysis. This modified system consists of a solar wafer, thermoelectric generator (TEG), and a heat sink, which is placed beneath the solar cell of the same size to dissipate heat. A series of experiments have been performed under certain laboratory conditions, which remain constant for all sets of experiments. The heat sink beneath the solar cell reduces the working temperature of the cell from 72°C (without heat sink) to 52°C (with heat sink and TEG), which leads to approximately 10% increment in the relative efficiency of the solar cell. Finally, a thermoelectric generator (TEG) is inserted between the solar cell and heat sink. The TEG adds an extra power of 1.2 mW to the total output of the system.
Prioritization of Near-Miss Incidents Using Text Mining and Bayesian Network
Near-Miss incidents can be treated as events to signal the weakness of safety management system (... more Near-Miss incidents can be treated as events to signal the weakness of safety management system (SMS) at the workplace. Analyzing near-misses will provide relevant root causes behind such incidents so that effective safety related interventions can be developed beforehand. Despite having a huge potential towards workplace safety improvements, analysis of near-misses is scant in the literature owing to the fact that near-misses are often reported as text narratives. The aim of this study is therefore to explore text-mining for extraction of root causes of near-misses from the narrative text descriptions of such incidents and to measure their relationships probabilistically. Root causes were extracted by word cloud technique and causal model was constructed using a Bayesian network (BN). Finally, using BN’s inference mechanism, scenarios were evaluated and root causes were listed in a prioritized order. A case study in a steel plant validated the approach and raised concerns for varie...
2018 9th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON), 2018
Deep learning neural networks have made significant progress in image analysis and have been used... more Deep learning neural networks have made significant progress in image analysis and have been used for skin cancer recognition. Early detection and proper treatments for malignant skin cancer cases are vital to ensure high survival rate in patients. We present a novel deep learning based convolutional neural network (CNN) model for generating compatible models on mobile platforms such as Android and iOS. The proposed model was tested on the grand challenge PHDB melanoma dataset. The best performing proposed model excels in the following ways: (1) it outperforms the baseline model in terms of accuracy by 1%; (2) it consists of 60% fewer parameters compared to the base model and thereby it is more efficient on mobile platforms. Furthermore, the model is more compact and retains high accuracy without the need to be downsized; (3) in conjunction with advanced regularization techniques such as dropout and data augmentation, the proposed CNN model excelled when implemented on state-of-the-art frameworks such as Keras and TensorFlow. Additionally, we were able to successfully deploy it on the iOS and Android mobile systems. The proposed model could also be lucrative towards other datasets for image classification on mobile platform.
This paper presents solar and wind hybrid energy system with battery storage along with AC mains ... more This paper presents solar and wind hybrid energy system with battery storage along with AC mains supply. This, configuration allows the three sources to the battery as well as supply the load separately or simultaneously depending on the availability of the energy sources. In many rural area of India, electricity has not reached their home yet as well as many people face load shedding problem. A hybrid design of battery charging system and its implementation has been explained in this paper. Besides AC mains supply charging, solar PV, wind energy also charges the battery whenever it is available through a charge controller. This system ensures continuous power supply and faster charging of battery. The system has been designed to suit a typical Indian scenario where there is power shortage which result in scheduled and unscheduled power shedding. Today, the world is progressing at quite fast rate with the use of the conventional source of energy. The two majors disadvantage of using...
Diabetic retinopathy (DR) is a common eye disease that could lead to irreversible vision loss but... more Diabetic retinopathy (DR) is a common eye disease that could lead to irreversible vision loss but hard to be noticed by carriers in early stages. Instead of isolating DR signs for DR recognition, this paper examines discriminant texture features obtained by color multi-scale uniform local binary pattern (LBPs) descriptors on five common color spaces and two proposed hybrid color spaces. The extracted features are evaluated by the enhanced Fisher linear discriminant, EFM. Experiments are done on a large dataset of 35,126 training images and 53,576 testing images that have been taken by different devices with high variance in dimensions, quality and luminance.
Now a day's software is the baseline for the success of any organization. There is a huge dem... more Now a day's software is the baseline for the success of any organization. There is a huge demand of quality software in the customer-oriented market. Regression testing makes it possible but it’s a costly affair. Regression test suite minimization is way to reduce this cost but it is NP hard problem. This paper proposes an effective approach for regression test suite minimization using Artificial Ecosystem Optimization algorithm. To improve its performance a modified Artificial Ecosystem Optimization algorithm is proposed for Test case minimization. To evaluate the performance of proposed approach experiment is conducted in controlled parameter setting on open-source subject program from SIR repository. The results are collected and analyzed in comparison to existing approaches using statistical test. The test results reflect the superiority of proposed approach.
“An Insight into Neurodegenerative Disorders, their therapeutic approaches and drugs available for tackling with Neurodegeneration: A Review”
The term neurodegenerative refers to diseases that are usually recognized by symptoms like decrea... more The term neurodegenerative refers to diseases that are usually recognized by symptoms like decreased motor control, mood disorders, an d cognitive deficits. Some of the common neurodegenerative diseases are Alzheimer&#39;s disease, Parkinson&#39;s disease, Huntington&#39;s disease, amyotrophic lateral sclerosis, frontotemporal dementia, and the spinocerebellar ataxias. These diseases are complex and diverse in their pathophysiology with some causing memory and cognitive impairments and others affecting a person&#39;s ability to move, speak, control, and breathe. T here are some prevalent drugs and therapies, which seems to be effective in improving the disease condition. Thus, It is need of the hour to develop new and more effective therapeutic approaches and strategies to manage and potentially tackle these devastating neurodegenerative diseases.
Verma and Mayadhar Barik. Currently, coronaviruses are contagious pathogens and primarily respons... more Verma and Mayadhar Barik. Currently, coronaviruses are contagious pathogens and primarily responsible for respiratory and intestinal infections (RIIs). Research on progress to develop antiviral agents (AVAs) against these coronavirus. Researcher had been demonstrated that the main protease (Mpro) protein may represents an effective drug target (EDT) [1]. The novel Corona-virus (n-CoV), recently called as the severe acute respiratory syndrome coronavirus (SARS-CoV-2). The
The processing and material properties of commercial organic semiconductors, for e.g. fullerenes ... more The processing and material properties of commercial organic semiconductors, for e.g. fullerenes is largely controlled by their precise arrangements, specially intermolecular symmetries, distances and orientations, more specifically, molecular polarisabilities. These supramolecular parameters heavily influence their electronic structure, thereby determining molecular photophysics and therefore dictating their usability as n-type semiconductors. In this article we evaluate van der Waals potentials of a fullerene dimer model system using two approaches: a) Density Functional Theory and, b) Macroscopic Quantum Electrodynamics, which is particularly suited for describing long-range van der Waals interactions. Essentially, we determine and explain the model symmetry, distance and rotational dependencies on binding energies and spectral changes. The resultant spectral tuning is compared using both methods showing correspondence within the constraints placed by the different
2016 IEEE International Symposium on Multimedia (ISM), 2016
Automatic diabetes retinopathy (DR) recognition can help DR carriers to receive treatment in earl... more Automatic diabetes retinopathy (DR) recognition can help DR carriers to receive treatment in early stages and avoid the risk of vision loss. In this paper, we emphasize the role of multiple filter sizes in learning fine-grained discriminant features and propose: (i) two deep convolutional neural networks -Combined Kernels with Multiple Losses Network (CKML Net) and VGGNet with Extra Kernel (VNXK), which are an improvement upon GoogLeNet and VGGNet in context of DR tasks. Learning from existing research, (ii) we propose a hybrid color space, LGI, for DR recognition via proposed nets. (iii) Transfer learning is applied to solve the challenge of imbalanced dataset. The effectiveness of proposed new nets and color space is evaluated using two grand challenge retina datasets: EyePACS and Messidor. Our experimental results show: (iv) CKML Net improves upon GoogLeNet and VNXK improves upon VGGNet on both datasets using the LGI color space. Additionally, proposed methodology improves upon other state of the art results on Messidor dataset for referable/non-referable screening.
Dermestes maculatus is a very important pest of smoke-dried fish that destroys the flesh, eating ... more Dermestes maculatus is a very important pest of smoke-dried fish that destroys the flesh, eating away the muscles, and leaving the skeletons when cured fish are stored for long period. This necessitates the idea of establishing an alternative repellant from natural plant products. In this article, compounds of Capsicum annum will be studied against repellent protein NDS2 of D. maculatus. The compounds present in C. annum. were docked against The NADH dehydrogenase subunit 2 (NDS2) protein of D. maculatus. PyRx-Python prescription 0.8 was used to identify binding affinities of compounds against the proteins. The results we obtained from molecular docking show that among 48 molecules of natural origin from C. annuum was downloaded in SDF format from the NCBI PubChem database. Six molecules are the best compounds observed through molecular docking and some hydrogen bonding and hydrophobic interactions are proposed as the efficacy from C. annuum on a repellent protein of D. maculatus. The molecular docking was performed to establish efficacy and binding affinity of ligands from C. annum on the repellent protein of D. maculatus. ADMET analysis is performed to establish the possible toxicity of the ligands. Importantly, all six natural compounds present in C. annum. may be more potent in new insecticide against NSD2 in D. maculatus but needs further experimental research.
The new coronavirus called SARS-CoV-2 is a new type of virus named as COVID-19. Although, it has ... more The new coronavirus called SARS-CoV-2 is a new type of virus named as COVID-19. Although, it has few similarities with pandemic flu viruses, the respiratory system and immune system are damaged through the viruses infected the population who has weakened immunity. SARS-CoV-2 spreads when people don't have the sign and symptoms. This virus COVID-19 appears to spread more easily than the flu, and asymptomatic transmission may account for a greater proportion of COVID-19's spreader over the World. In inundation of the current understanding, the roles of insect vectors are helping in the transmission of viral pathogens as well and the possible roles of some newly joined insects in the mechanical transmission of COVID-19. We also specifically provide the prevention and control methods related to contamination, disease burden, risk pattern in the family, near and dear to maintain the precision of social distancing and development of the immune system to fight against SARS-CoV-2.
International Journal of Computational Vision and Robotics, 2018
Plankton are extremely diverse groups of organisms that exist in large water columns. They are so... more Plankton are extremely diverse groups of organisms that exist in large water columns. They are sources of food for fishes and many other marine life animals. The plankton distribution is essential for the survival of many ocean lives and plays a critical role in marine ecosystem. In recent years, intelligent image classification systems were developed to study plankton distribution through classification of the plankton images taken by underwater imaging devices. Due to the significant differences in both shapes and sizes of the plankton population, accurate classification poses a daunting challenge. The mixed quality of the collected images adds more difficulty to the task. In this paper, we present an intelligent machine learning system built on convolutional neural networks (CNN) for plankton image classification. Unlike most of the existing image classification algorithms, CNN based systems do not depend on features engineering and they can be efficiently extended to encompass new classes. The experimental results on SIPPER image datasets show that the proposed system achieves higher accuracy compared with the state-of-the-art approaches. The new system is also capable of learning a much larger number of plankton classes.
Journal of Evolution of Medical and Dental Sciences, 2017
BACKGROUND The estimated annual burn incidence in India is approximately 6-7 million per year. Bu... more BACKGROUND The estimated annual burn incidence in India is approximately 6-7 million per year. Burn injury is a common but preventable cause of morbidity and mortality in India. In patients of epilepsy, the burn injury is far more severe than the any other comorbidities. MATERIALS AND METHODS This study design was a retrospective-descriptive study which was conducted in burn unit of MY Hospital, Indore with intention of identifying the risk factors for burn injury in epileptic patients. Study was conducted over a period of six years from the January 2009 to December 2015. RESULTS Maximum patients were of age group less than 40 years and most of them were females. All the burns were accidental in nature. Flame was the commonest mode of injury. Most of the patients sustained deep burns (60%) of upper limb (62.8%). Most of the patients had Generalised Tonic-clonic type of seizure and 88.5% of patients were not compliant to drug therapy. CONCLUSION Burn injuries sustained in epileptic patients are of very severe degree. These injuries are preventable if epileptic patients follow the general safety guidelines and remain stick to their treatment protocols.
A preliminary analysis of incident investigation reports of an integrated steel plant: some reflection
International Journal of Injury Control and Safety Promotion, 2017
ABSTRACT Large integrated steel plants employ an effective safety management system and gather a ... more ABSTRACT Large integrated steel plants employ an effective safety management system and gather a significant amount of safety-related data. This research intends to explore and visualize the rich database to find out the key factors responsible for the occurrences of incidents. The study was carried out on the data in the form of investigation reports collected from a steel plant in India. The data were processed and analysed using some of the quality management tools like Pareto chart, control chart, Ishikawa diagram, etc. Analyses showed that causes of incidents differ depending on the activities performed in a department. For example, fire/explosion and process-related incidents are more common in the departments associated with coke-making and blast furnace. Similar kind of factors were obtained, and recommendations were provided for their mitigation. Finally, the limitations of the study were discussed, and the scope of the research works was identified.
Study of metal strip insertion and its optimization in doping less TFET
Superlattices and Microstructures, 2018
Abstract In this manuscript, a novel structure for dopingless tunnel field effect transistor (DL ... more Abstract In this manuscript, a novel structure for dopingless tunnel field effect transistor (DL TFET) is introduced which comprises of metal strip (MS) in the oxide region near source/channel junction. Gate and drain work function engineering with hetero gate dielectric is used in this device which enhances the ON-state current, reduces the ambipolarity and also improves the RF performance. The increment in ON-state current with high subthreshold swing is achieved by the effect of MS. Steeper tunneling junction is achieved with the help of aforementioned modifications at the S/C junction. In this way, we increase the rate of tunneling at this interface and because of this, the threshold voltage of the proposed device reduces drastically. Further, study of ambipolarity suppression is done by using underlap of gate electrode near drain/channel (D/C) interface. Furthermore, temperature variation effect also incorporated in this manuscript, where study related to the threshold voltage and ON-state current is analysed by TCAD simulation. Moreover, most optimized MS length and work function are concluded in this paper for all simulations. Optimization for MS length and workfunction is analysed using TCAD simulation tool and shown in tabular form with one table showing effect of different work functions of MS on threshold voltage, ON-state current and SS, whereas another table shows the effect of MS length variations on RF parameters.
Comparing Outcomes of Endoscopic Versus Duplex-Guided Open Subfascial Interruption of Incompetent Perforators in Management of Varicose Veins: A Randomized Control Trial
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Papers by Abhishek Verma