Search results for: Pratap Kandel

Authors: Jarina Joshi, Pratap Kandel, Puja Bhatt, Suman Bajracharya

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Biogas production and use in Nepal is very essential not only to combat fuel crisis but also for organic waste management. This paper deals with the integration of electrochemical systems in an anaerobic digestor to enhance biogas production with minimal electrical energy input. Biogas of 1.9 L was produced from the 1:2 v/v mixture of vegetable wastes in a downward water displacement collector and 0.8 V supplemented at 27℃. Biogas could be produced even at 18℃ i.e., 0.63 L), which is more than twofold in comparison with biogas produced without voltage i.e., 0.30 L). Maximum COD reduction was 70.84±5.54 % than in control (20.35±4.53 %). The digester is found to dwell three Bacillus strains and one Exiguobacterium strain when isolated manually from the sludge. From this study, supplementation of electricity in anaerobic digestor can produce more biogas and enhance waste degradation by transforming waste into energy.

Keywords: anaerobic digestion, biogas, microbial electrolysis cell, electrochemical, methanogens

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Authors: Vishnu Pratap Singh Kirar

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In the cloud computing hierarchy IaaS is the lowest layer, all other layers are built over it. Thus it is the most important layer of cloud and requisite more importance. Along with advantages IaaS faces some serious security related issue. Mainly Security focuses on Integrity, confidentiality and availability. Cloud computing facilitate to share the resources inside as well as outside of the cloud. On the other hand, cloud still not in the state to provide surety to 100% data security. Cloud provider must ensure that end user/client get a Quality of Service. In this report we describe possible aspects of cloud related security.

Keywords: cloud computing, cloud networking, IaaS, PaaS, SaaS, cloud security

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Authors: Vishnu Pratap Singh Kirar

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Wireless sensor network (WSN) is a network of many interconnected networked systems, they equipped with energy resources and they are used to detect other physical characteristics. On WSN, there are many researches are performed in past decades. WSN applicable in many security systems govern by military and in many civilian related applications. Thus, the security of WSN gets attention of researchers and gives an opportunity for many future aspects. Still, there are many other issues are related to deployment and overall coverage, scalability, size, energy efficiency, quality of service (QoS), computational power and many more. In this paper we discus about various applications and security related issue and requirements of WSN.

Keywords: wireless sensor network (WSN), wireless network attacks, wireless network security, security requirements

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Authors: Ajay Pratap Singh Lodhi, Deepak Kumar

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Vegetable oil-based environmentally friendly metalworking fluids (MWFs) are formulated. The tribological performance, cytotoxicity, and corrosion resistance of the formulated fluids (FFs) are evaluated and benchmarked with commercial mineral oil-based MWFs (CF). Results show that FFs exhibited better machining characteristics (roughness, cutting forces, and surface morphology) during machining than CF. MTT assay and Live dead cell assay confirm the cytocompatibility nature of the FFs relative to the toxic CF. Electrochemical analysis shows that FFs and CF exhibited comparable corrosion current density.

Keywords: corrosion inhibitors, cytotoxicity, machining, MTT assay, Taguchi method, vegetable oil

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Authors: Riddhi Jangid, Gajendra Pratap Singh

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Petri nets, a formalized modeling language that was introduced back around 50-60 years, have been widely used for modeling discrete event dynamic systems and simulating their behavior. Reachability analysis of Petri nets gives many insights into a modeled system. This idea leads us to study the reachability technique and use it in the reachability problem in the state space of reachable markings. With the same concept, Crisp Boolean Petri nets were defined in which the marking vectors that are boolean are distinct in the reachability analysis of the nets. We generalize the concept and define ‘Crisp’ Petri nets that generate the marking vectors exactly once in their reachability-based analysis, not necessarily Boolean.

Keywords: marking vector, n-vector, Petri nets, reachability

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Authors: Riddhi Jangid, Gajendra Pratap Singh

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Petri nets, a mathematical tool, is used for modeling in different areas of computer sciences, biological networks, chemical systems and many other disciplines. A Petri net model of a given system is created by the graphical representation that describes the properties and behavior of the system. While looking for the behavior of any system, 1-safe Petri nets are of particular interest to many in the application part. Boolean Petri nets correspond to those class in 1- safe Petri nets that generate all the binary n-vectors in their reachability analysis. We study the class by changing different parameters like the token counts in the places and how the structure of the tree changes in the reachability analysis. We discuss here an extended class of Boolean Petri nets that generates n-ary trees in their reachability-based analysis.

Keywords: marking vector, n-vector, petri nets, reachability

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Authors: Dev Pratap Singh, Harshika Hasija, Ashwini S.

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The project aims to provide a touchless, intuitive interface for human-computer interaction, enabling users to control their computers using hand gestures and voice commands. The system leverages advanced computer vision techniques using the Media Pipe framework and OpenCV to detect and interpret real-time hand gestures, transforming them into mouse actions such as clicking, dragging, and scrolling. Additionally, the integration of a voice assistant powered by the speech recognition library allows for seamless execution of tasks like web searches, location navigation, and gesture control in the system through voice commands.

Keywords: gesture recognition, hand tracking, machine learning, convolutional neural networks, natural language processing, voice assistant

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Authors: Vishnu Pratap Singh Kirar

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The main aim of the communication system is to achieve maximum performance. In cognitive radio, any user or transceiver have the ability to sense best suitable channel, while the channel is not in use. It means an unlicensed user can share the spectrum of licensed user without any interference. Though the spectrum sensing consumes a large amount of energy and it can reduce by applying various artificial intelligent methods for determining proper spectrum holes. It also increases the efficiency of Cognitive Radio Network (CRN). In this survey paper, we discuss the use of different learning models and implementation of Artificial Neural Network (ANN) to increase the learning and decision-making capacity of CRN without affecting bandwidth, cost and signal rate.

Keywords: artificial neural network, cognitive radio, cognitive radio networks, back propagation, spectrum sensing

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Authors: K. Brince Paul, Nagendra Pratap Singh, Shiv Govind Singh, Siva Rama Krishna Vanjari

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In this paper, we report optimized procedure for synthesizing highly oriented, horizontally aligned, Zinc oxide (ZnO) nanowires targeted towards developing highly sensitive piezoelectric transduction elements. The synthesis was carried out using Electrospinning technique, a facile, robust, low cost technique for producing nanowires. The as-synthesized ZnO nanowires were characterized by X-ray powder diffraction (XRD), Field Emission scanning electron microscopy (FESEM) and Energy-dispersive X-ray spectroscopy (EDX).The Piezoelectric behavior of these nanowires was characterized using Peizoelectric Force microscopy (PFM). A very high d33 coefficient of 23.1 pm/V obtained through the PFM measurements is an indicative of its potential application towards developing miniaturized piezoelectric transduction elements for nanoscale devices.

Keywords: electrospinning, piezoelectric, technique, zinc oxide

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Authors: Vishnu Pratap Singh Kirar, Madhuri Saxena

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Advancement in sequence data generation technologies is churning out voluminous omics data and posing a massive challenge to annotate the biological functional features. With so much data available, the use of machine learning methods and tools to make novel inferences has become obvious. Machine learning methods have been successfully applied to a lot of disciplines, including computational biology and bioinformatics. Researchers in computational biology are interested to develop novel machine learning frameworks to classify the huge amounts of biological data. In this proposal, it plan to employ novel machine learning approaches to aid the understanding of how apparently innocuous mutations (in intergenic DNA and at synonymous sites) cause diseases. We are also interested in discovering novel functional sites in the genome and mutations in which can affect a phenotype of interest.

Keywords: genome wide association studies (GWAS), next generation sequencing (NGS), deep learning, omics

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Authors: Satyendra Pratap Singh, S. P. Singh

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This paper presents a methodology using Gravitational Search Algorithm for optimal placement of Phasor Measurement Units (PMUs) in order to achieve complete observability of the power system. The objective of proposed algorithm is to minimize the total number of PMUs at the power system buses, which in turn minimize installation cost of the PMUs. In this algorithm, the searcher agents are collection of masses which interact with each other using Newton’s laws of gravity and motion. This new Gravitational Search Algorithm based method has been applied to the IEEE 14-bus, IEEE 30-bus and IEEE 118-bus test systems. Case studies reveal optimal number of PMUs with better observability by proposed method.

Keywords: gravitational search algorithm (GSA), law of motion, law of gravity, observability, phasor measurement unit

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Authors: Vishnu Pratap Singh Kirar

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Artificial Neural Network (ANN) can be trained using backpropagation (BP). It is the most widely used algorithm for supervised learning with multi-layered feed-forward networks. Efficient learning by the BP algorithm is required for many practical applications. The BP algorithm calculates the weight changes of artificial neural networks, and a common approach is to use a two-term algorithm consisting of a learning rate (LR) and a momentum factor (MF). The major drawbacks of the two-term BP learning algorithm are the problems of local minima and slow convergence speeds, which limit the scope for real-time applications. Recently the addition of an extra term, called a proportional factor (PF), to the two-term BP algorithm was proposed. The third increases the speed of the BP algorithm. However, the PF term also reduces the convergence of the BP algorithm, and criteria for evaluating convergence are required to facilitate the application of the three terms BP algorithm. Although these two seem to be closely related, as described later, we summarize various improvements to overcome the drawbacks. Here we compare the different methods of convergence of the new three-term BP algorithm.

Keywords: neural network, backpropagation, local minima, fast convergence rate

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Authors: Nirmal Kant Singh, Anshuman Pratap Singh

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In this study the augmentation of heat transfer in a channel with delta winglet type vortex generators is evaluated. Three-dimensional numerical simulations are performed in a rectangular channel with longitudinal triangular vortex generators (LVGs). The span wise averaged Nusselt number and mean temperature are compared with and without vortex generators in the channel. The effect of variation of blade angle (15°, 30°, 45°, and 60°) is studied at a Reynolds number of 10000. The numerical results indicate that the application of LVGs effectively enhances heat transfer in the channel. The Nusselt number and mean outlet temperature were found to be greater using LVGs than in the channel without LVGs. It is observed that heat transfer increases with increase in blade angle at the same Reynolds number.

Keywords: heat transfer, rectangular channel, longitudinal vortex generators, effect of blade angle

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Authors: Keshav Prasad Kandel, Balaram Khadka, Karan Bhatta, Basu Dev Ghimire

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Earthquakes still exist as a threating disaster. Being able to predict earthquakes will certainly help prevent substantial loss of life and property. Perhaps, Very Low Frequency/Low Frequency (VLF/LF) signal band (3-30 kHz), which is effectively reflected from D-layer of ionosphere, can be established as a tool to predict earthquake. On May 20 and May 29, 2012, earthquakes of magnitude 6.1 and 5.8 respectively struck Emilia-Romagna of Italy. A year back, on August 24, 2016, an earthquake of magnitude 6.2 struck Central Italy (42.7060 N and 13.2230 E) at 1:36 UT. We present the results obtained from the US Navy VLF Transmitter’s NSY signal of 45.9 kHz transmitted from Niscemi, in the province of Sicily, Italy and received at the Kiel Longwave Monitor, Germany for 2012 and 2016. We analyzed the terminator times, their individual differences and nighttime fluctuation counts. We also analyzed trends, dispersion and nighttime fluctuation which gave us a possible precursors to these earthquakes. Since perturbations in VLF amplitude could also be due to various other factors like lightning, geomagnetic activities (storms, auroras etc.) and solar activities (flares, UV flux, etc.), we filtered the possible perturbations due to these agents to guarantee that the perturbations seen in VLF/LF amplitudes were as a precursor to Earthquakes. As our TRGCP path is North-south, the sunrise and sunset time in transmitter and receiver places matches making pathway for VLF/LF smoother and therefore hoping to obtain more natural data. To our surprise, we found many clear anomalies (as precursors) in terminator times 5 days to 16 days before the earthquakes. Moreover, using night time fluctuation method, we found clear anomalies 5 days to 13 days prior to main earthquakes. This exactly correlates with the findings of previous authors that ionospheric perturbations are seen few days to one month before the seismic activity. In addition to this, we were amazed to observe unexpected decrease of dispersion on certain anomalies where it was supposed to increase, thereby not supporting our finding to some extent. To resolve this problem, we devised a new parameter called dispersion nighttime (dispersion). On analyzing, this parameter decreases significantly on days of nighttime anomalies thereby supporting our precursors to much extent.

Keywords: D-layer, TRGCP (Transmitter Receiver Great Circle Path), terminator times, VLF/LF

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Authors: Houda Najeh, Stéphane Ploix, Mahendra Pratap Singh, Karim Chabir, Mohamed Naceur Abdelkrim

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Building systems are highly vulnerable to different kinds of faults and failures. In fact, various faults, failures and human behaviors could affect the building performance. This paper tackles the detection of unreliable sensors in buildings. Different literature surveys on diagnosis techniques for sensor grids in buildings have been published but all of them treat only bias and outliers. Occurences of data gaps have also not been given an adequate span of attention in the academia. The proposed methodology comprises the automatic thresholding for data gap detection for a set of heterogeneous sensors in instrumented buildings. Sensor measurements are considered to be regular time series. However, in reality, sensor values are not uniformly sampled. So, the issue to solve is from which delay each sensor become faulty? The use of time series is required for detection of abnormalities on the delays. The efficiency of the method is evaluated on measurements obtained from a real power plant: an office at Grenoble Institute of technology equipped by 30 sensors.

Keywords: building system, time series, diagnosis, outliers, delay, data gap

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Authors: Agastya Pratap Singh

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This review paper examines the emerging applications of generative adversarial networks (GANs) in the fields of image recognition and anomaly detection. With the rapid growth of digital image data, the need for efficient and accurate methodologies to identify and classify images has become increasingly critical. GANs, known for their ability to generate realistic data, have gained significant attention for their potential to enhance traditional image recognition systems and improve anomaly detection performance. The paper systematically analyzes various GAN architectures and their modifications tailored for image recognition tasks, highlighting their strengths and limitations. Additionally, it delves into the effectiveness of GANs in detecting anomalies in diverse datasets, including medical imaging, industrial inspection, and surveillance. The review also discusses the challenges faced in training GANs, such as mode collapse and stability issues, and presents recent advancements aimed at overcoming these obstacles.

Keywords: generative adversarial networks, image recognition, anomaly detection, synthetic data generation, deep learning, computer vision, unsupervised learning, pattern recognition, model evaluation, machine learning applications

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Authors: Varun Singh, Mainak Bandyopadhyay, Maharana Pratap Singh

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The shortest path (SP) problem concerns with finding the shortest path from a specific origin to a specified destination in a given network while minimizing the total cost associated with the path. This problem has widespread applications. Important applications of the SP problem include vehicle routing in transportation systems particularly in the field of in-vehicle Route Guidance System (RGS) and traffic assignment problem (in transportation planning). Well known applications of evolutionary methods like Genetic Algorithms (GA), Ant Colony Optimization, Particle Swarm Optimization (PSO) have come up to solve complex optimization problems to overcome the shortcomings of existing shortest path analysis methods. It has been reported by various researchers that PSO performs better than other evolutionary optimization algorithms in terms of success rate and solution quality. Further Geographic Information Systems (GIS) have emerged as key information systems for geospatial data analysis and visualization. This research paper is focused towards the application of PSO for solving the shortest path problem between multiple points of interest (POI) based on spatial data of Allahabad City and traffic speed data collected using GPS. Geovisualization of results of analysis is carried out in GIS.

Keywords: particle swarm optimization, GIS, traffic data, outliers

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Authors: Pratap Sriram Sundar, Chandan Chowdhury, Sagar Kamarthi

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Nature has perfected her designs over 3.5 billion years of evolution. Research fields such as biomimicry, biomimetics, bionics, bio-inspired computing, and nature-inspired designs have explored nature-made artifacts and systems to understand nature’s mechanisms and intelligence. Learning from nature, the researchers have generated sustainable designs and innovation in a variety of fields such as energy, architecture, agriculture, transportation, communication, and medicine. Axiomatic design offers a method to judge if a design is good. This paper analyzes design aspects of one of the nature’s amazing object: chicken egg. The functional requirements (FRs) of components of the object are tabulated and mapped on to nature-chosen design parameters (DPs). The ‘independence axiom’ of the axiomatic design methodology is applied to analyze couplings and to evaluate if eggs’ design is good (i.e., uncoupled design) or bad (i.e., coupled design). The analysis revealed that eggs design is a good design, i.e., uncoupled design. This approach can be applied to any nature’s artifacts to judge whether their design is a good or a bad. This methodology is valuable for biomimicry studies. This approach can also be a very useful teaching design consideration of biology and bio-inspired innovation.

Keywords: uncoupled design, axiomatic design, nature design, design evaluation

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Authors: Agastya Pratap Singh

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Generative Adversarial Networks (GANs) have emerged as powerful tools in the fields of image recognition and anomaly detection due to their ability to model complex data distributions and generate realistic images. This systematic review explores recent advancements and applications of GANs in both image recognition and anomaly detection tasks. We discuss various GAN architectures, such as DCGAN, CycleGAN, and StyleGAN, which have been tailored to improve accuracy, robustness, and efficiency in visual data analysis. In image recognition, GANs have been used to enhance data augmentation, improve classification models, and generate high-quality synthetic images. In anomaly detection, GANs have proven effective in identifying rare and subtle abnormalities across various domains, including medical imaging, cybersecurity, and industrial inspection. The review also highlights the challenges and limitations associated with GAN-based methods, such as instability during training and mode collapse, and suggests future research directions to overcome these issues. Through this review, we aim to provide researchers with a comprehensive understanding of the capabilities and potential of GANs in transforming image recognition and anomaly detection practices.

Keywords: generative adversarial networks, image recognition, anomaly detection, DCGAN, CycleGAN, StyleGAN, data augmentation

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Authors: Aiswarya C. L, Swatantra Pratap Singh

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In recent years, most desalination plants have been powered by fossil fuels, and to a lesser extent, by green energy. Greenhouse gases emitted by fossil-fuelled plants significantly impact the global climate. So scientists are forced to develop a powerful energy source to protect the environment with greater sustainability due to climate change issues. Nuclear energy can supply much more fresh water than what is currently available. Furthermore, it is more affordable and does not emit any greenhouse gases. This review compares conventional desalination plants with nuclear-powered desalination plants in terms of cost, energy consumption, water recovery, and environmental issues. On the basis of the review conducted, nuclear desalination has been demonstrated to be technically feasible and economically competitive with a variety of fossil fuels, renewable energy sources, and waste heat sources. Nuclear sources have been criticized due to their lack of safety. But studies show, if we were able to handle the issue with care, the problems could be eliminated. Here we're looking at the Seawater Reverse Osmosis Plant (SWROP) at Kudankulam Nuclear Power Plant in Tamil Nadu, India and review the further possibility of implementing nuclear desalination technology in other states of India.

Keywords: energy consumption, environmental impacts, nuclear desalination, water recovery

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Authors: Shivendra Pratap Singh, Rishabh Sharma

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The widespread adoption of mobile technology in recent years has revolutionized the way we communicate and access information. The evolution of mobile systems has been rapid and impactful, shaping our lives and changing the way we live and work. However, despite its significant influence, the history and development of mobile technology are not well understood by the general public. This research paper aims to examine the history, technology and future of mobile systems, exploring their evolution from early mobile phones to the latest smartphones and beyond. The study will analyze the technological advancements and innovations that have shaped the mobile industry, from the introduction of mobile internet and multimedia capabilities to the integration of artificial intelligence and 5G networks. Additionally, the paper will also address the challenges and opportunities facing the future of mobile technology, such as privacy concerns, battery life, and the increasing demand for high-speed internet. Finally, the paper will also provide insights into potential future developments and innovations in the mobile sector, such as foldable phones, wearable technology, and the Internet of Things (IoT). The purpose of this research paper is to provide a comprehensive overview of the history, technology, and future of mobile systems, shedding light on their impact on society and the challenges and opportunities that lie ahead.

Keywords: mobile technology, artificial intelligence, networking, iot, technological advancements, smartphones

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Authors: César M. Moreira, Marco A. Pazmiño-Hernández, Marco A. Pazmiño-Barreno, Kyle Griffin, Pratap Pullammanappallil

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An anaerobic digestion system that was completely operated on solar power (both photovoltaic and solar thermal energy), and mounted on a trailer to make it mobile, was designed and constructed. A 55-gallon batch digester was placed within a chamber that was heated by hot water pumped through a radiator. Hot water was produced by a solar thermal collector and photovoltaic panels charged a battery which operated pumps for recirculating water. It was found that the temperature in the heating chamber was maintained above ambient temperature but it follows the same trend as ambient temperature. The temperature difference between the chamber and ambient values was not constant but varied with time of day. Advantageously, the temperature difference was highest during night and early morning and lowest near noon. In winter, when ambient temperature dipped to 2 °C during early morning hours, the chamber temperature did not drop below 10 °C. Model simulations showed that even if the digester is subjected to diurnal variations of temperature (as observed in winter of a subtropical region), about 63 % of the waste that would have been processed under constant digester temperature of 38 °C, can still be processed. The cost of the digester system without the trailer was $1,800.

Keywords: anaerobic digestion, solar-mobile, rural communities, solar, hybrid

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Authors: Ashish Kumar Pathak, Ritika Sharma, Vishal Nath, Sudhir Pratap Singh, Rakesh Tuli

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Litchi is a sub-tropical fruit crop with genotypes bearing delicious juicy fruits with variable seed size (bold to rudimentary size). Small seed size is a desirable trait in litchi, as it increases consumer acceptance and fruit processing. The biochemical activities in mid- stage ovules (e.g. 16, 20, 24 and 28 days after anthesis) determine the fate of seed and fruit development in litchi. Comprehensive ovule-specific transcriptome analysis was performed in two litchi genotypes with contrasting seed size to gain molecular insight on determinants of seed fates in litchi fruits. The transcriptomic data was de-novo assembled in 1,39,608 trinity transcripts, out of which 6,325 trinity transcripts were differentially expressed between the two contrasting genotypes. Differential transcriptional pattern was found among ovule development stages in contrasting litchi genotypes. The putative genes for salicylic acid, jasmonic acid and brassinosteroid pathway were down-regulated in ovules of small-seeded litchi. Embryogenesis, cell expansion, seed size and stress related trinity transcripts exhibited altered expression in small-seeded genotype. The putative regulators of seed maturation and seed storage were down-regulated in small-seed genotype.

Keywords: Litchi, seed, transcriptome, defence

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Authors: Houda Najeh, Mahendra Pratap Singh, Stéphane Ploix, Antoine Caucheteux, Karim Chabir, Mohamed Naceur Abdelkrim

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Building system is highly vulnerable to different kinds of faults and human misbehaviors. Energy efficiency and user comfort are directly targeted due to abnormalities in building operation. The available fault diagnosis tools and methodologies particularly rely on rules or pure model-based approaches. It is assumed that model or rule-based test could be applied to any situation without taking into account actual testing contexts. Contextual tests with validity domain could reduce a lot of the design of detection tests. The main objective of this paper is to consider fault validity when validate the test model considering the non-modeled events such as occupancy, weather conditions, door and window openings and the integration of the knowledge of the expert on the state of the system. The concept of heterogeneous tests is combined with test validity to generate fault diagnoses. A combination of rules, range and model-based tests known as heterogeneous tests are proposed to reduce the modeling complexity. Calculation of logical diagnoses coming from artificial intelligence provides a global explanation consistent with the test result. An application example shows the efficiency of the proposed technique: an office setting at Grenoble Institute of Technology.

Keywords: heterogeneous tests, validity, building system, sensor grids, sensor fault, diagnosis, fault detection and isolation

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Authors: Jeevan Jyoti, Bhanu Pratap Singh, S. R. Dhakate

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In the present study, multiwalled carbon nanotubes (MWCNTs) and reduced graphene oxide (RGO) were synthesized by chemical vapor deposition and Improved Hummer’s method, respectively and their composite with acrylonitrile butadiene styrene (ABS) were prepared by twin screw co rotating extrusion technique. The electromagnetic interference (EMI) shielding effectiveness of graphene oxide carbon nanotube (GCNTs) hybrid composites was investigated and the results were compared with EMI shielding of carbon nanotube (CNTs) and reduced graphene oxide (RGO) in the frequency range of 12.4-18 GHz (Ku-band). The experimental results indicate that the EMI shielding effectiveness of these composites is achieved up to –21 dB for 10 wt. % loading of GCNT loading. The mechanism of improvement in EMI shielding effectiveness is discussed by resolving their contribution in absorption and reflection loss. The main reason for such a high improved shielding effectiveness has been attributed to the significant improvement in the electrical conductivity of the composites. The electrical conductivity of these GCNT/ABS composites was increased from 10-13 S/cm to 10-7 S/cm showing the improvement of the 6 order of the magnitude. Scanning electron microscopic (SEM) and high resolution transmission electron microscopic (HRTEM) studies showed that the GCNTs were uniformly dispersed in the ABS polymer matrix. GCNTs form a network throughout the polymer matrix and promote the reinforcement.

Keywords: ABS, EMI shielding, multiwalled carbon nanotubes, reduced graphene oxide, graphene, oxide-carbon nanotube (GCNTs), twin screw extruder, multiwall carbon nanotube, electrical conductivity

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Authors: Uditi Dhakad, Baldev Ram, Chaman K. Jadon, R. K. Yadav, D. L. Yadav, Pratap Singh, Shalini Meena

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A field experiment was conducted during Kharif 2021 at Agricultural Research Station, Kota, to evaluate the effect of different post-emergence herbicides applied to soybean [Glycine max (L.) Merrill] on soil enzymes activity viz. dehydrogenase, phosphatase, and urease. The soil of the experimental site was clay loam (vertisols) in texture and slightly alkaline in reaction with 7.7 pH. The soil was low in organic carbon (0.49%), medium in available nitrogen (210 kg/ha), phosphorus (23.5 P2O5 kg/ha), and high in potassium (400 K2O kg/ha) status. The results elucidated that no significant adverse effect on soil dehydrogenase, urease, and phosphatase activity was determined with the application of post-emergence herbicides over the untreated control. Two hands weeding at 20 and 40 DAS registered maximum dehydrogenase enzyme activity (0.329 μgTPF/g soil/d) closely followed by herbicides mixtures and sole herbicide while pre-emergence application of pendimethalin + imazethapyr 960 g a.i./ha and pendimethalin 1.0 kg a.i./ha significantly reduced dehydrogenase enzyme activity compared to control. Urease enzyme activity was not much affected under different weed control treatments and weedy checks. The treatments were found statistically non-significant, and values ranged between 1.16-1.25 μgNH4N/g soil/d. Phosphatase enzyme activity was also not influenced significantly due to various weed control treatments. Though maximum phosphatase enzyme activity (30.17 μgpnp/g soil/hr) was observed under two-hand weeding, followed by fomesafen + fluazifop-p-butyl 220 g a.i./ha. Herbicidal weed control measures did not influence the total bacteria, fungi, and actinomycetes population.

Keywords: dehydrogenase, phosphatase, post-emergence, soil enzymes, urease.

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Authors: Amit Kumar, Bhupendra Pratap Singh, Manoj Singh, Monika Punia, Krishan Kumar, V. K. Jain

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Ambient concentrations of volatile organic compounds (VOCs) were investigated in order to find out temporal variations and their ozone forming potentials (OFP) at rural site in Delhi National Capital Region during summer 2013. Sampling was performed for continuous five days, to identify the differences in working days and weekend VOCs concentration levels. Sampling and analytical procedure for VOCs were done using National Institute for Occupational Safety and Health (NIOSH) standard method. On each sampling day, VOCs samples were collected for 3-hours in the morning, afternoon and evening. There has been observed a noticeable contrast in the concentration of VOCs levels between working days and weekend. However, most of the VOCs showed diurnal fluctuations with higher concentrations in the morning and evening as compared to afternoon which might be due to change in meteorology. The results showed that mean toluene/benzene and m-/p-xylene/benzene ratios were higher in the afternoon while it was lower during morning and evening. The relative contribution of the VOCs to ozone formation, total propylene equivalent concentrations and OFP were calculated. Toluene was the most contributing organic contaminant to ozone formation as well as ambient VOCs concentrations. Results obtained in current study demonstrate that ozone formation at rural site in Delhi is probably limited by the emissions of VOCs.

Keywords: VOCs, rural, NIOSH, ozone forming potential, propylene equivalent concentration

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Authors: Garima Joshi, Pratap Sharan, V. Sreenivas, Nand Kumar, Kameshwar Prasad, Ashima N. Wadhawan

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Schizophrenia is a debilitating disorder and is marked by cognitive impairment, which deleteriously impacts the social and professional functioning along with the quality of life of the patients and the caregivers. Often the cognitive symptoms are in their prodromal state and worsen as the illness progresses; they have proven to have a good predictive value for the prognosis of the illness. It has been shown that intensive cognitive rehabilitation (CR) leads to improvements in the healthy as well as cognitively-impaired subjects. As the majority of population in India falls in the lower to middle socio-economic status and have low education levels, using the existing packages, a majority of which are developed in the West, for cognitive rehabilitation becomes difficult. The use of technology is also restricted due to the high costs involved and the limited availability and familiarity with computers and other devices, which pose as an impedance for continued therapy. Cognitive rehabilitation in India uses a plethora of retraining methods for the patients with schizophrenia targeting the functions of attention, information processing, executive functions, learning and memory, and comprehension along with Social Cognition. Psychologists often have to follow an integrative therapy approach involving social skills training, family therapy and psychoeducation in order to maintain the gains from the cognitive rehabilitation in the long run. This paper reviews the methodologies and cognitive retaining programs used in India. It attempts to elucidate the evolution and development of methodologies used, from traditional paper-pencil based retraining to more sophisticated neuroscience-informed techniques in cognitive rehabilitation of deficits in schizophrenia as home-based or supervised and guided programs for cognitive rehabilitation.

Keywords: schizophrenia, cognitive rehabilitation, neuropsychological interventions, integrated approached to rehabilitation

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Authors: Pratap Sing, Chaman. K. Jadon, H. P. Meena, D. L.yadav, S. L. Yadav, Uditi Dhakad

Abstract:

The experiment was conducted at Agricultural Research Station, Agriculture University, Kota, Rajasthan, India during kharif and rabi 2020-21 and 2021-22 to study the biofficacy of diclosulam and its residual effect on succeeding wheat crop. The treatments comprised of Diclosulam 84 % WDG viz. 6.25, 12.50, 25.00 and 37.50 g/ha as pre emergence (PE), Pendimethalin 30% EC 3.33 l/ha, Sulfentrazon 48% SC 750 g/ha, hand weeding at 30 and 45 DAS and weedy check, were evaluated in randomized block design in three replications. The experimental soil was clay in texture and non-calcareous. Experimental field was mainly dominated by grasses-Echinochloa colonum, E.crusgalli,Cynodon dactylon, Sedges-Cyperus rotundus and broad leaved weeds Celosia argentea and Digera arvensis.The result revealed that application of Diclosulam 84 % WDG 25 g/ha PE was found effective in controlling mostly weed species and registered higher weed control efficiency 81.2, 74.3, 69.6 per cent at 30, 45 days after sowing and at harvest. Diclosulam 84 % WDG (6.25-25.0 g/ha) was found selective to the soybean crop as no any phytotoxicity symptoms were observed. Among the herbicidal treatments, Diclosulam 84 % WDG 25 g/ha registered maximum and significantly higher soybean seed yield (1889 and 1431 kg/ha during kharif 2020 and 2021, respectively and was at par with Sulfentrazone 48% SC 750 g/ha and over weedy check( 1027 and 667 kg/ha).The wheat crop growth, yield attributes and seed yield were not influenced due to carry over effect of the Diclosulam 84 % WDG( 6.25-25.0 g/ha) and no any phytotoxicity symptoms were observed. Henceforth, the Diclosulam 84 % WDG 25.0 g/ha as pre emergence may be used in the soybean for effective weed control without carry over effect on succeeding wheat crop.

Keywords: Diclosulam, soybean, carry over effect, succeeding wheat

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Authors: K. M. Pratap Shankar, Dattatreya Rao, Sai Prasad

Abstract:

Background: Skin diseases are among the most common health problems worldwide and are associated with a considerable burden. Eczema is such a skin ailment which cause psychological, social and financial burden on the patient and their families. Management of eczema with antibiotics, antihistamines, steroids etc., are available but even after their use relapses, recurrences and other complications are very common. Aim: The aim of this study was to assess the efficacy of leech application in the management of vicarcikā (Eczema) with Histopathological study. Methods: For the present study 10 patients having the classical symptoms of Vicarcikā, were randomly selected as per the inclusion and exclusion criteria from O.P.D. & I.P.D. sections of Śalya department, S.V. Āyurvedic Hospital, Tirupati. Minimum 4 sittings of Leech application was carried out with seven days interval. Total duration of treatment was 6 weeks. Biopsy samples were collected from the lesion site before and after treatment. Histopathological examination was done by the pathologist. Results: In eczema (dermatitis) the leech application therapy gives excellent response by reducing the inflammatory component, hyperkeratosis, spongiosis, irregular acanthosis and by evoking a granulation tissue response in the dermis and in most of the cases with complete recovery from the lesion. Most of the cases in the study were chronic dermatitis and sebhoric keratosis, almost all local/focal pigmented lesions is totally relieved by leech therapy especially in cases of sebhoric keratosis. Conclusion: In the present study it was found that, leech application evokes significant changes at histological level specifically in reduction of inflammatory component, hyperkeratosis, spongiosis and irregular acanthosis. It was also found that there was a considerable formation of granulation tissue, which helps in formation of healthy new tissues.

Keywords: acanthosis, eczema, hyperkeratosis, leech application, spongiosis

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