Search results for: Neha Babbar

Authors: Khushboo Bhavsar, Nisha K. Shah, Neha Parekh

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The status of wastewater treatment needs a novel and quick method for treating the wastewater containing ammoniacal nitrogen. Adsorption behavior of ammoniacal nitrogen from wastewater using the nanoparticles loaded coconut coir was investigated in the present work. Manganese Oxide (MnO2) and Zinc Oxide (ZnO) nanoparticles were prepared and used for the further adsorption study. Manganese nanoparticles loaded coconut coir (MNLCC) and Zinc nanoparticles loaded coconut coir (ZNLCC) were prepared via a simple method and was fully characterized. The properties of both MNLCC and ZNLCC were characterized by Scanning electron microscopy, Fourier Transform Infrared Spectroscopy and X-ray diffraction. Adsorption characteristics were studied using batch technique considering various parameters like pH, adsorbent dosage, time, temperature and agitation time. The NH3-N adsorption process for MNLCC and ZNLCC was thoroughly studied from both kinetic and equilibrium isotherm view-points. The results indicated that the adsorption efficiency of ZNLCC was better when compared to MNLCC. The adsorption kinetics at different experimental conditions showed that second order kinetic model best fits ensuring the monovalent binding sites existing in the present experimental system. The outcome of the entire study suggests that the ZNLCC can be a smart option for the treatment of the ammoniacal nitrogen containing wastewater.

Keywords: ammoniacal nitrogen, MnO2, Nanoparticles, ZnO

Procedia PDF Downloads 356

Authors: Osung Im, Neha Yadav, Eui Hoon Lee, Joong Hoon Kim

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Artificial Neural Network (ANN) approach is commonly used in lots of fields for forecasting. In water resources engineering, forecast of water level or inflow of reservoir is useful for various kind of purposes. Due to advantages of ANN, many papers were written for inflow prediction in river networks, but in this study, ANN is used in urban sewer networks. The growth of severe rain storm in Korea has increased flood damage severely, and the precipitation distribution is getting more erratic. Therefore, effective pump operation in pump station is an essential task for the reduction in urban area. If real time inflow of pump station reservoir can be predicted, it is possible to operate pump effectively for reducing the flood damage. This study used ANN model for pump station reservoir inflow prediction using upstream sewer depth data. For this study, rainfall events, sewer depth, and inflow into Banpo pump station reservoir between years of 2013-2014 were considered. Feed – Forward Back Propagation (FFBF), Cascade – Forward Back Propagation (CFBP), Elman Back Propagation (EBP) and Nonlinear Autoregressive Exogenous (NARX) were used as ANN model for prediction. A comparison of results with ANN model suggests that ANN is a powerful tool for inflow prediction using the sewer depth data.

Keywords: artificial neural network, forecasting, reservoir inflow, sewer depth

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Authors: Neha Sharma, Kanthi K. Kondepudi, Naveen Gupta

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Phytases are phytate specific phosphatases catalyzing the step-wise dephosphorylation of phytate, which acts as an anti-nutritional factor in food due to its strong binding capacity to minerals. In recent years microbial phytases have been explored for improving nutritional quality of food. But the major limitation is acceptability of phytases from these microorganisms. Therefore, efforts are being made to isolate organisms which are generally regarded as safe for human consumption such as Lactic Acid Bacteria (LAB). Phytases from these organisms will have an edge over other phytase sources due to its probiotic attributes. Only few LAB have been reported to give phytase activity that too is generally seen as intracellular. LAB producing extracellular phytase will be more useful as it can degrade phytate more effectively. Moreover, enzyme from such isolate will have application in food processing also. Only few species of Lactobacillus producing extracellular phytase have been reported so far. This study reports the isolation of a probiotic strain of Lactobacillus fermentum spp KA1 which produces extracellular phytase. Conditions for the optimal production of phytase have been optimized and the enzyme production resulted in an approximately 13-fold increase in yield. The phytate degradation potential of extracellular phytase in rice bran has been explored and conditions for optimal degradation were optimized. Under optimal conditions, there was 43.26% release of inorganic phosphate and 6.45% decrease of phytate content.

Keywords: Lactobacillus, phytase, phytate reduction, rice bran

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Authors: Neha Ahirwar

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In the contemporary digital era, the rise of credit card fraud poses a significant threat to both financial institutions and consumers. As fraudulent activities become more sophisticated, there is an escalating demand for robust and effective fraud detection mechanisms. Advanced machine learning algorithms have become crucial tools in addressing this challenge. This paper conducts a thorough examination of the design and evaluation of a credit card fraud detection system, utilizing four prominent machine learning algorithms: random forest, logistic regression, decision tree, and XGBoost. The surge in digital transactions has opened avenues for fraudsters to exploit vulnerabilities within payment systems. Consequently, there is an urgent need for proactive and adaptable fraud detection systems. This study addresses this imperative by exploring the efficacy of machine learning algorithms in identifying fraudulent credit card transactions. The selection of random forest, logistic regression, decision tree, and XGBoost for scrutiny in this study is based on their documented effectiveness in diverse domains, particularly in credit card fraud detection. These algorithms are renowned for their capability to model intricate patterns and provide accurate predictions. Each algorithm is implemented and evaluated for its performance in a controlled environment, utilizing a diverse dataset comprising both genuine and fraudulent credit card transactions.

Keywords: efficient credit card fraud detection, random forest, logistic regression, XGBoost, decision tree

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Authors: Neha Singh, Anshuman Rana

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Gender-Based Violence (GBV) is a violation of human rights and a form of discrimination which reinforces inequalities between men and women. It is defined as violence that is directed against a person on the basis of gender. There has been increased attention to human trafficking that has exposed to illegal migration. Trafficking is complex, but it generally takes place due to “push and pull factors”. India is both a source as well as a transit country for trafficking. Women are bought and sold with impunity and trafficked to other countries. They are forced to work as sex worker, forced labour and other practices of slavery. Trafficked victims often suffer from serious abuse and physical exhaustion. The effects of violence on women vary widely. GBV typically has physical, psychological and social effects. They face unwanted pregnancies, miscarriages, high rate of infertility and sexually transmitted disease. The social exclusion of women is so great that it constitutes a new form of apartheid. Women are considered as lesser value and deprived of their fundamental rights. Violation of human rights and fundamental freedom such as- trafficking of women, girls for sex trade, forced prostitution and sex tourism have become the focus of internationally organized crimes. My paper will analyse the impact of violence on society as well. Law alone cannot change the scenario and problem of gender-biasness. The whole issue of gender violence needs social awakening and change in attitude of masses, so that due respect and equal status is given to women.

Keywords: gender-based violence, trafficking, migration, violence impact, social exclusion, law enforcement

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Authors: Neha Gupta

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Landslide vulnerability is considered as the crucial parameter for the assessment of landslide risk. The term vulnerability defined as the damage or degree of elements at risk of different dimensions, i.e., physical, social, economic, and environmental dimensions. Himalaya region is very prone to multi-hazard such as floods, forest fires, earthquakes, and landslides. With the increases in fatalities rates, loss of infrastructure, and economy due to landslide in the Himalaya region, leads to the assessment of vulnerability. In this study, a methodology to measure the combination of vulnerability dimension, i.e., social vulnerability, physical vulnerability, and environmental vulnerability in one framework. A combined result of these vulnerabilities has rarely been carried out. But no such approach was applied in the Indian Scenario. The methodology was applied in an area of east Sikkim Himalaya, India. The physical vulnerability comprises of building footprint layer extracted from remote sensing data and Google Earth imaginary. The social vulnerability was assessed by using population density based on land use. The land use map was derived from a high-resolution satellite image, and for environment vulnerability assessment NDVI, forest, agriculture land, distance from the river were assessed from remote sensing and DEM. The classes of social vulnerability, physical vulnerability, and environment vulnerability were normalized at the scale of 0 (no loss) to 1 (loss) to get the homogenous dataset. Then the Multi-Criteria Analysis (MCA) was used to assign individual weights to each dimension and then integrate it into one frame. The final vulnerability was further classified into four classes from very low to very high.

Keywords: landslide, multi-criteria analysis, MCA, physical vulnerability, social vulnerability

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Authors: Neha Parekh, Divya Ladha, Poonam Wadhwani, Nisha Shah

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Nano scaled materials have attracted tremendous interest as corrosion inhibitor due to their high surface area on the metal surfaces. It is well known that the zinc oxide nanoparticles have higher reactivity towards aqueous acidic solution. This work presents a new method to incorporate zinc oxide nanoparticles with white sesame seeds extract (nano-green inhibitor) for corrosion protection of zinc in acidic medium. The morphology of the zinc oxide nanoparticles was investigated by TEM and DLS. The corrosion inhibition efficiency of the green inhibitor and nano-green inhibitor was determined by Gravimetric and electrochemical impedance spectroscopy (EIS) methods. Gravimetric measurements suggested that nano-green inhibitor is more effective than green inhibitor. Furthermore, with the increasing temperature, inhibition efficiency increases for both the inhibitors. In addition, it was established the Temkin adsorption isotherm fits well with the experimental data for both the inhibitors. The effect of temperature and Temkin adsorption isotherm revealed Chemisorption mechanism occurring in the system. The activation energy (Ea) and other thermodynamic parameters for inhibition process were calculated. The data of EIS showed that the charge transfer controls the corrosion process. The surface morphology of zinc metal (specimen) in absence and presence of green inhibitor and nano-green inhibitor were performed using Scanning Electron Microscopy (SEM) and Atomic Force Microscopy (AFM) techniques. The outcomes indicated a formation of a protective layer over zinc metal (specimen).

Keywords: corrosion, green inhibitor, nanoparticles, zinc

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Authors: Paweł Konieczka, Lech Raczyński, Wojciech Wiślicki, Oleksandr Fedoruk, Konrad Klimaszewski, Przemysław Kopka, Wojciech Krzemień, Roman Shopa, Jakub Baran, Aurélien Coussat, Neha Chug, Catalina Curceanu, Eryk Czerwiński, Meysam Dadgar, Kamil Dulski, Aleksander Gajos, Beatrix C. Hiesmayr, Krzysztof Kacprzak, łukasz Kapłon, Grzegorz Korcyl, Tomasz Kozik, Deepak Kumar, Szymon Niedźwiecki, Dominik Panek, Szymon Parzych, Elena Pérez Del Río, Sushil Sharma, Shivani Shivani, Magdalena Skurzok, Ewa łucja Stępień, Faranak Tayefi, Paweł Moskal

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This paper develops the transformation of non-image data into 2-dimensional matrices, as a preparation stage for classification based on convolutional neural networks (CNNs). In positron emission tomography (PET) studies, CNN may be applied directly to the reconstructed distribution of radioactive tracers injected into the patient's body, as a pattern recognition tool. Nonetheless, much PET data still exists in non-image format and this fact opens a question on whether they can be used for training CNN. In this contribution, the main focus of this paper is the problem of processing vectors with a small number of features in comparison to the number of pixels in the output images. The proposed methodology was applied to the classification of PET coincidence events.

Keywords: convolutional neural network, kernel principal component analysis, medical imaging, positron emission tomography

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Authors: Neha Intikhab Khan, Alanoud AlBalwi, Farah Alqazlan, Tala Almadoudi

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Background: Grammarly, a widely utilized writing assistant launched in 2009, leverages advanced artificial intelligence and natural language processing to enhance writing quality across various platforms. Methods: To collect data on user perceptions of Grammarly, a structured survey was designed and distributed via Google Forms. The survey included a series of quantitative and qualitative questions aimed at assessing various aspects of Grammarly's performance. The survey comprised multiple-choice questions, Likert scale items (ranging from "strongly disagree" to "strongly agree"), and open-ended questions to capture detailed user feedback. The target population included students, friends, and family members. The collected responses were analyzed using statistical methods to quantify user satisfaction. Participation in the survey was voluntary, and respondents were assured anonymity and confidentiality. Results: The survey of 28 respondents revealed a generally favorable perception of Grammarly's AI capabilities. A significant 39.3% strongly agreed that it effectively improves text tone, with an additional 46.4% agreeing, while 10.7% remained neutral. For clarity suggestions, 28.6% strongly agreed, and 57.1% agreed, totaling 85.7% recognition of its value. Regarding grammatical accuracy across various genres, 46.4% rated it a perfect score of 5, contributing to 78.5% who found it highly effective. Conclusion: The evolution of Grammarly from a basic grammar checker to a robust AI-driven application underscores its adaptability and commitment to helping users develop their writing skills.

Keywords: Grammarly, writing tool, user engagement, AI capabilities, effectiveness

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Authors: Ganesh K. Maurya, Reema Chaudhary, Neha Pandey, Hari S. Misra

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PprA, a pleiotropic protein participating in radioresistance, has been reported for its roles in DNA replication initiation, genome segregation, cell division and DNA repair in polyextremophile Deinococcus radiodurans. Interestingly, expression of deinococcal PprA in E. coli suppresses its growth by reducing the number of colony forming units and provides better resistance against γ-radiation than control. We employed different biochemical and cell biology studies using PprA and its DNA binding/polymerization mutants (K133E & W183R) in E. coli. Cells expressing wild type PprA or its K133E mutant showed reduction in the amount of genomic DNA as well as chromosome copy number in comparison to W183R mutant of PprA and control cells, which suggests the role of PprA protein in regulation of DNA replication initiation in E. coli. Further, E. coli cells expressing PprA or its mutants exhibited different impact on cell morphology than control. Expression of PprA or K133E mutant displayed a significant increase in cell length upto 5 folds while W183R mutant showed cell length similar to uninduced control cells. We checked the interaction of deinococcal PprA and its mutants with E. coli DnaA using Bacterial two-hybrid system and co-immunoprecipitation. We observed a functional interaction of EcDnaA with PprA and K133E mutant but not with W183R mutant of PprA. Further, PprA or K133E mutant has suppressed the ATPase activity of EcDnaA but W183R mutant of PprA failed to do so. These observations suggested that PprA protein regulates DNA replication initiation and cell morphology of surrogate E. coli.

Keywords: DNA replication, radioresistance, protein-protein interaction, cell morphology, ATPase activity

Procedia PDF Downloads 69

Authors: Ganesh K. Maurya, Reema Chaudhary, Neha Pandey, Hari S. Misra

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PprA, a pleiotropic protein participating in radioresistance, has been reported for its roles in DNA replication initiation, genome segregation, cell division and DNA repair in polyextremophile Deinococcus radiodurans. Interestingly, expression of deinococcal PprA in E. coli suppresses its growth by reducing the number of colony forming units and provide better resistance against γ-radiation than control. We employed different biochemical and cell biology studies using PprA and its DNA binding/polymerization mutants (K133E & W183R) in E. coli. Cells expressing wild type PprA or its K133E mutant showed reduction in the amount of genomic DNA as well as chromosome copy number in comparison to W183R mutant of PprA and control cells, which suggests the role of PprA protein in regulation of DNA replication initiation in E. coli. Further, E. coli cells expressing PprA or its mutants exhibited different impact on cell morphology than control. Expression of PprA or K133E mutant displayed a significant increase in cell length upto 5 folds while W183R mutant showed cell length similar to uninduced control cells. We checked the interaction of deinococcal PprA and its mutants with E. coli DnaA using Bacterial two-hybrid system and co-immunoprecipitation. We observed a functional interaction of EcDnaA with PprA and K133E mutant but not with W183R mutant of PprA. Further, PprA or K133E mutant has suppressed the ATPase activity of EcDnaA but W183R mutant of PprA failed to do so. These observations suggested that PprA protein regulates DNA replication initiation and cell morphology of surrogate E. coli.

Keywords: DNA replication, radioresistance, protein-protein interaction, cell morphology, ATPase activity

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Authors: Neha Singh, Anuj Ranjan, Tanu Jindal

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Over the last decade, the exponential growth of mobile communication has been accompanied by a parallel increase in density of electromagnetic fields (EMF). The continued expansion of mobile phone usage raises important questions as EMF, especially radio frequency (RF), have long been suspected of having biological effects. In the present experiments, we studied the effects of RF-EMF on cell death (apoptosis) and DNA damage of a well- tested biological model, Drosophila melanogaster exposed to 2400 MHz frequency for different time duration i.e. 2 hrs, 4 hrs, 6 hrs,8 hrs, 10 hrs, and 12 hrs each day for five continuous days in ambient temperature and humidity conditions inside an exposure chamber. The flies were grouped into control, sham-exposed, and exposed with 100 flies in each group. In this study, well-known techniques like Comet Assay and TUNEL (Terminal deoxynucleotide transferase dUTP Nick End Labeling) Assay were used to detect DNA damage and for apoptosis studies, respectively. Experiments results showed DNA damage in the brain cells of Drosophila which increases as the duration of exposure increases when observed under the observed when we compared results of control, sham-exposed, and exposed group which indicates that EMF radiation-induced stress in the organism that leads to DNA damage and cell death. The process of apoptosis and mutation follows similar pathway for all eukaryotic cells; therefore, studying apoptosis and genotoxicity in Drosophila makes similar relevance for human beings as well.

Keywords: cell death, apoptosis, Comet Assay, DNA damage, Drosophila, electromagnetic fields, EMF, radio frequency, RF, TUNEL assay

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Authors: Shveta Puri, Shiv Jyoti Pandey, G. M. Bhat, Neha Raina

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TheJammu and Kashmir region of the Northwest Himalaya had witnessed many devastating earthquakes in the recent past and has remained unexplored for any kind of seismic investigations except scanty records of the earthquakes that occurred in this region in the past. In this study, we have used local seismic data of year 2013 that was recorded by the network of Broadband Seismographs in J&K. During this period, our seismic stations recorded about 207 earthquakes including two moderate events of Mw 5.7 on 1st May, 2013 and Mw 5.1 of 2nd August, 2013.We analyzed the events of Mw 3-4.6 and the main events only (for minimizing the error) for source parameters, b value and sense of movement through waveform modeling for understanding seismotectonic and seismic hazard of the region. It has been observed that most of the events are bounded between 32.9° N – 33.3° N latitude and 75.4° E – 76.1° E longitudes, Moment Magnitude (Mw) ranges from Mw 3 to 5.7, Source radius (r), from 0.21 to 3.5 km, stress drop, from 1.90 bars to 71.1 bars and Corner frequency, from 0.39 – 6.06 Hz. The b-value for this region was found to be 0.83±0 from these events which are lower than the normal value (b=1), indicating the area is under high stress. The travel time inversion and waveform inversion method suggest focal depth up to 10 km probably above the detachment depth of the Himalayan region. Moment tensor solution of the (Mw 5.1, 02:32:47 UTC) main event of 2ndAugust suggested that the source fault is striking at 295° with dip of 33° and rake value of 85°. It was found that these events form intense clustering of small to moderate events within a narrow zone between Panjal Thrust and Kishtwar Window. Moment tensor solution of the main events and their aftershocks indicating thrust type of movement is occurring in this region.

Keywords: b-value, moment tensor, seismotectonics, source parameters

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Authors: Neha Toppo

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Plans and programs for successful secondary education are incomplete without the inclusion of teaching English as an important area. Even after sixteen years of the formation of Jharkhand as a separate state, the students are still struggling to achieve quality education of English. This paper intends to account the present condition of teaching English in Jharkhand board secondary level schools through discussion on various issues of English language teaching, language need and learning challenges of its students. The study is to analyze whether the learning environment, teaching methods and materials, teaching resources, goals of language curriculum are appropriately convincing for the students of the board or require to be reanalyzed and also to provide appropriate suggestions for improvement. Immediate attention must be drawn towards the problem for benefitting those students, who despite their knowledge and talent are lagging behind in numerous fields only due to the lack of proficiency in English. The data and discussion provided are on the basis of a survey, in which semi structured interview with teachers, students and administrators in several schools including both rural and urban area has been taken. Questionnaire, observation and testing were used as important tools. The survey has been conducted in Ranchi district, as it covers large geographical area which includes number of villages and at the same time several towns. The district primarily possesses tribes as well as different class of people including immigrants from all over and outside Jharkhand with their social, economical strata. The observation makes it clear that the English language teaching at the state board is not complementing its context and the whole language teaching system should be re-examined to establish learner oriented environment.

Keywords: material, method, secondary level, teaching resources

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Authors: Khadija Rafi, Neha Jamil, Laiba Khalid, Meerub Nawaz, Mahwish Farooq

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Speech articulation is a complex process to produce intelligible sounds with the help of precise movements of various structures within the vocal tract. All these structures in the vocal tract are named as articulators, which comprise lips, teeth, tongue, and palate. These articulators work together to produce a range of distinct phonemes, which happen to be the basis of language. It starts with the airstream from the lungs passing through the trachea and into oral and nasal cavities. When the air passes through the mouth, the tongue and the muscles around it form such coordination it creates certain sounds. It can be seen when the tongue is placed in different positions- sometimes near the alveolar ridge, soft palate, roof of the mouth or the back of the teeth which end up creating unique qualities of each phoneme. We can articulate vowels with open vocal tracts, but the height and position of the tongue is different every time depending upon each vowel, while consonants can be pronounced when we create obstructions in the airflow. For instance, the alphabet ‘b’ is a plosive and can be produced only by briefly closing the lips. Articulation disorders can not only affect communication but can also be a hurdle in speech production. To improve articulation skills for such individuals, doctors often recommend speech therapy, which involves various kinds of exercises like jaw exercises and tongue twisters. However, this disorder is more common in children who are going through developmental articulation issues right after birth, but in adults, it can be caused by injury, neurological conditions, or other speech-related disorders. In short, speech articulation is an essential aspect of productive communication, which also includes coordination of the specific articulators to produce different intelligible sounds, which are a vital part of spoken language.

Keywords: linguistics, speech articulation, speech therapy, language learning

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Authors: Neha Verma, Manik Rakhra

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Statement of the Problem: Nowadays, a tremendous increase in population and advanced industrialization augment the problems related to air and water pollutions. Growing industries promoting environmental danger, which is an alarming threat to the ecosystem. For safeguard, the environment, detection of perilous gases and release of colored wastewater is required for eutrophication pollution. Researchers around the globe are trying their best efforts to save the environment. For this remediation advanced oxidation process is used for potential applications. ZnO is an important semiconductor photocatalyst with high photocatalytic and gas sensing activities. For efficient photocatalytic and gas sensing properties, it is necessary to prepare a doped/co-doped ZnO compound to decrease the electron-hole recombination rates. However, lanthanide doped and co-doped metal oxide is seldom studied for photocatalytic and gas sensing applications. The purpose of this study is to describe the best photocatalyst for the photodegradation of dyes and gas sensing properties. Methodology & Theoretical Orientation: Economical framework has to be used for the synthesis of ZnO. In the depth literature survey, a simple combustion method is utilized for gas sensing and photocatalytic activities. Findings: Rare earth doped and co-doped ZnO nanoparticles were the best photocatalysts for photodegradation of organic dyes and different gas sensing applications by varying various factors such as pH, aging time, and different concentrations of doping and codoping metals in ZnO. Complete degradation of dye was observed only in min. Gas sensing nanodevice showed a better response and quick recovery time for doped/co-doped ZnO. Conclusion & Significance: In order to prevent air and water pollution, well crystalline ZnO nanoparticles were synthesized by rapid and economic method, which is used as photocatalyst for photodegradation of organic dyes and gas sensing applications to sense the release of hazardous gases from the environment.

Keywords: ZnO, photocatalyst, photodegradation of dye, gas sensor

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Authors: Pramod Jagtap, Kisan Jadhav, Neha Dand

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Risperidone (RISP) is an antipsychotic agent and has low water solubility and nontargeted delivery results in numerous side effects. Hence, an attempt was made to develop SLNs hydrogel for intranasal delivery of RISP to achieve maximum bioavailability and reduction of side effects. RISP loaded SLNs composed of 1.65% (w/v) lipid mass were produced by high shear homogenization (HSH) coupled ultrasound (US) method using glyceryl monostearate (GMS) or Imwitor 900K (solid lipid). The particles were loaded with 0.2% (w/v) of the RISP & surface-tailored with a 2.02% (w/v) non-ionic surfactant Tween® 80. Optimization was done using 32 factorial design using Design Expert® software. The prepared SLNs dispersion incorporated into Polycarbophil AA1 hydrogel (0.5% w/v). The final gel formulation was evaluated for entrapment efficiency, particle size, rheological properties, X ray diffraction, in vitro diffusion, ex vivo permeation using sheep nasal mucosa and histopathological studies for nasocilliary toxicity. The entrapment efficiency of optimized SLNs was found to be 76 ± 2 %, polydispersity index <0.3., particle size 278 ± 5 nm. This optimized batch was incorporated into hydrogel. The pH was found to be 6.4 ± 0.14. The rheological behaviour of hydrogel formulation revealed no thixotropic behaviour. In histopathology study, there was no nasocilliary toxicity observed in nasal mucosa after ex vivo permeation. X-ray diffraction data shows drug was in amorphous form. Ex vivo permeation study shows controlled release profile of drug.

Keywords: ex vivo, particle size, risperidone, solid lipid nanoparticles

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Authors: Shashank Gupta, Iteash Agarwal, Vijayalaxmi Mogiligidda, Rajesh Kumar Krishnan, Sruthi Chennuri, Deepika Aggarwal, Anwesha Hoodati, Sheroy Cooper, Ranjan, Mohammad Bilal Sheik, Bhavya K. M., Manasa Hegde, M. Naveen Krishna, Amit Kumar Chauhan, Mallikarjun Korrapati, Sumit Singh, J. B. Singh, Sunil Sud, Sunil Gupta, Sidhartha Pant, Sankar, Neha Agrawal, Ashish Ranjan, Piyush Mohapatra, Roopak T., Arsh Ahmad, Nanjunda M., Dilip Singh

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Major research interests on quantum key distribution (QKD) are primarily focussed on increasing 1. point-to-point transmission distance (1000 Km), 2. secure key rate (Mbps), 3. security of quantum layer (device-independence). It is great to push the boundaries on these fronts, but these isolated approaches are neither scalable nor cost-effective due to the requirements of specialised hardware and different infrastructure. Current and future QKD network requires addressing different sets of challenges apart from distance, key rate, and quantum security. In this regard, we present ChaQra -a sub-quantum network with core features as 1) Crypto agility (integration in the already deployed telecommunication fibres), 2) Software defined networking (SDN paradigm for routing different nodes), 3) reliability (addressing denial-of-service with hybrid quantum safe cryptography), 4) upgradability (modules upgradation based on scientific and technological advancements), 5) Beyond QKD (using QKD network for distributed computing, multi-party computation etc). Our results demonstrate a clear path to create and accelerate quantum secure Indian subcontinent under the national quantum mission.

Keywords: quantum network, quantum key distribution, quantum security, quantum information

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Authors: Neha Budhwani

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Polycyclic aromatic hydrocarbons (PAHs) are formed during the pyrolysis of scrap tyres to produce tyre pyrolytic oil (TPO). Due to carcinogenic, mutagenic, and toxic properties PAHs are priority pollutants. Hence it is essential to remove PAHs from TPO before utilising TPO as a petroleum fuel alternative (to run the engine). Agricultural wastes have promising future to be utilized as biosorbent due to their cost effectiveness, abundant availability, high biosorption capacity and renewability. Various low cost adsorbents were prepared from natural sources. Uptake of PAHs present in tyre pyrolytic oil was investigated using various low-cost adsor¬bents of natural origin including sawdust (shiham), coconut fiber, neem bark, chitin, activated charcol. Adsorption experiments of different PAHs viz. naphthalene, acenaphthalene, biphenyl and anthracene have been carried out at ambient temperature (25°C) and at pH 7. It was observed that for any given PAH, the adsorption capacity increases with the lignin content. Freundlich constant kf and 1/n have been evaluated and it was found that the adsorption isotherms of PAHs were in agreement with a Freundlich model, while the uptake capacity of PAHs followed the order: activated charcoal> saw dust (shisham) > coconut fiber > chitin. The partition coefficients in acetone-water, and the adsorption constants at equilibrium, could be linearly correlated with octanol–water partition coefficients. It is observed that natural adsorbents are good alternative for PAHs removal. Sawdust of Dalbergia sissoo, a by-product of sawmills was found to be a promising adsorbent for the removal of PAHs present in TPO. It is observed that adsorbents studied were comparable to those of some conventional adsorbents.

Keywords: natural adsorbent, PAHs, TPO, coconut fiber, wood powder (shisham), naphthalene, acenaphthene, biphenyl and anthracene

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Authors: Sweeti, Anoop Kant Godiyal, Neha Singh, Sneh Anand, B. K. Panigrahi, Jayasree Santhosh

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This work is about developing a tool for visualization and segmentation of Electroencephalograph (EEG) signals based on frequency domain features. Change in the frequency domain characteristics are correlated with change in mental state of the subject under study. Proposed algorithm provides a way to represent the change in the mental states using the different frequency band powers in form of segmented EEG signal. Many segmentation algorithms have been suggested in literature having application in brain computer interface, epilepsy and cognition studies that have been used for data classification. But the proposed method focusses mainly on the better presentation of signal and that’s why it could be a good utilization tool for clinician. Algorithm performs the basic filtering using band pass and notch filters in the range of 0.1-45 Hz. Advanced filtering is then performed by principal component analysis and wavelet transform based de-noising method. Frequency domain features are used for segmentation; considering the fact that the spectrum power of different frequency bands describes the mental state of the subject. Two sliding windows are further used for segmentation; one provides the time scale and other assigns the segmentation rule. The segmented data is displayed second by second successively with different color codes. Segment’s length can be selected as per need of the objective. Proposed algorithm has been tested on the EEG data set obtained from University of California in San Diego’s online data repository. Proposed tool gives a better visualization of the signal in form of segmented epochs of desired length representing the power spectrum variation in data. The algorithm is designed in such a way that it takes the data points with respect to the sampling frequency for each time frame and so it can be improved to use in real time visualization with desired epoch length.

Keywords: de-noising, multi-channel data, PCA, power spectra, segmentation

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Authors: Neha Narayanan

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The paper tries to explore the role of language in determining spaces occupied by women in everyday lives. It is inspired from an ongoing action research work which employs ‘immersion’- arriving at a research problematic through community research, as a methodology in a Kondh adivasi village, Kirkalpadu located in Rayagada district of the Indian state of Odisha. In the dominant development discourse, language is associated with either preservation or conservation of endangered language or empowerment through language. Beyond these, is the discourse of language as a structure, with the hegemonic quality to organise lifeworld in a specific manner. This rigid structure leads to an experience of constriction of space for women. In Kirkalpadu, the action research work is with young and unmarried women of the age 15-25. During daytime, these women are either in the agricultural field or in the bari -the backyard of the house whose rooms are linearly arranged one after the other ending with the kitchen followed by an open space called bari (in Odia) which is an intimate and gendered space- where they are not easily visible. They justify the experience of restriction in mobility and fear of moving out of the village alone by the argument that the place and the men are nihi-aaeh (not good). These women, who have dropped out of school early to contribute to the (surplus) labour requirement in the household, want to learn English to be able to read signboards when they are on the road, to be able to fill forms at a bank and use mobile phones to communicate with their romantic partner(s). But the incapacity to have within one’s grasp the province of language and the incapacity to take the mobile phone to the kind of requirements marked by the above mentioned impossible transactions with space restricts them to the bari of the house. The paper concludes by seeking to explore the possibilities of learning and rethinking languages which takes into cognizance the gendered experience of women and the desire of women to cross the borders and occupy spaces restricted to them.

Keywords: action research, gendered experience, language, space

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Authors: Neha Singh, Shristi Singh

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Accidents involving motor vehicles are more likely to cause serious injuries and fatalities. It also has a host of other perpetual issues, such as the regular loss of life and goods in accidents. To solve these issues, appropriate measures must be implemented, such as establishing an autonomous incident detection system that makes use of machine learning and artificial intelligence. In order to reduce traffic accidents, this article examines the overview of artificial intelligence and machine learning in autonomous event detection systems. The paper explores the major issues, prospective solutions, and use of artificial intelligence and machine learning in road transportation systems for minimising traffic accidents. There is a lot of discussion on additional, fresh, and developing approaches that less frequent accidents in the transportation industry. The study structured the following subtopics specifically: traffic management using machine learning and artificial intelligence and an incident detector with these two technologies. The internet of vehicles and vehicle ad hoc networks, as well as the use of wireless communication technologies like 5G wireless networks and the use of machine learning and artificial intelligence for the planning of road transportation systems, are elaborated. In addition, safety is the primary concern of road transportation. Route optimization, cargo volume forecasting, predictive fleet maintenance, real-time vehicle tracking, and traffic management, according to the review's key conclusions, are essential for ensuring the safety of road transportation networks. In addition to highlighting research trends, unanswered problems, and key research conclusions, the study also discusses the difficulties in applying artificial intelligence to road transport systems. Planning and managing the road transportation system might use the work as a resource.

Keywords: artificial intelligence, machine learning, incident detector, road transport systems, traffic management, automatic incident detection, deep learning

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Authors: Ankita Sharma, Satish Kumar Meena, Neha Kawatra Madan

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Background and Aims: Pediatric septic shock, a life-threatening condition, is associated with significant morbidity and mortality. Dysregulation of thyroid function, presenting as Non-Thyroidal Illness Syndrome (NTIS), is a common observation in critically ill patients and may impact clinical outcomes. This study investigates the thyroid hormone profile in pediatric septic shock and its correlation with disease outcomes. Methods: A cross-sectional study was conducted in the Pediatric Department of VMMC and Safdarjung Hospital, New Delhi. Ninety-one children, aged 1 month to 12 years, diagnosed with septic shock were included. Thyroid function tests (Total T3, Total T4, Free T3, Free T4, and TSH) were measured upon admission. Outcomes were categorized as favorable (shock reversal within 24 hours, ICU stay <7 days) or unfavorable (prolonged shock, ICU stay >7 days, multiorgan dysfunction syndrome [MODS], or death). Statistical analysis included logistic regression and receiver operating characteristic (ROC) curve evaluation. Results: Thyroid hormone abnormalities were prevalent, with low Total T3 (84.6%), low Total T4 (70.3%), and low Free T3 (76.9%) being the most common findings. Significant associations were observed between low levels of Total T3, Total T4, Free T3, and Free T4 with unfavorable outcomes (p<0.001 for all). ROC analysis identified Free T3 as the strongest predictor of unfavorable outcomes, with an AUROC of 0.842. Conclusions: Thyroid hormone levels, particularly Free T3, are critical prognostic markers in pediatric septic shock. Timely monitoring of thyroid function could aid in risk stratification and therapeutic decision-making. Future research should focus on the potential benefits of thyroid hormone replacement therapy in this population.

Keywords: pediatric septic shock, thyroid function, non-thyroidal illness syndrome, prognostic markers, free T3

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Authors: Shiv Jyoti Pandey, Shveta Puri, G. M. Bhat, Neha Raina

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The Jammu and Kashmir (J&K) region of Northwest Himalaya has a long history of earthquake activity which falls within Seismic Zones IV and V. To know the crustal structure beneath this region, we utilized teleseismic receiver function method. This paper presents the results of the analyses of the teleseismic earthquake waves recorded by 10 seismic observatories installed in the vicinity of major thrusts and faults. The teleseismic waves at epicentral distance between 30o and 90o with moment magnitudes greater than or equal to 5.5 that contains large amount of information about the crust and upper mantle structure directly beneath a receiver has been used. The receiver function (RF) technique has been widely applied to investigate crustal structures using P-to-S converted (Ps) phases from velocity discontinuities. The arrival time of the Ps, PpPs and PpSs+ PsPs converted and reverberated phases from the Moho can be combined to constrain the mean crustal thickness and Vp/Vs ratio. Over 500 receiver functions from 10 broadband stations located in the Jammu & Kashmir region of Northwest Himalaya were analyzed. With the help of H-K stacking method, we determined the crustal thickness (H) and average crustal Vp/Vs ratio (K) in this region. We also used Neighbourhood algorithm technique to verify our results. The receiver function results for these stations show that the crustal thickness under Jammu & Kashmir ranges from 45.0 to 53.6 km with an average value of 50.01 km. The Vp/Vs ratio varies from 1.63 to 1.99 with an average value of 1.784 which corresponds to an average Poisson’s ratio of 0.266 with a range from 0.198 to 0.331. High Poisson’s ratios under some stations may be related to partial melting in the crust near the uppermost mantle. The crustal structure model developed from this study can be used to refine the velocity model used in the precise epicenter location in the region, thereby increasing the knowledge to understand current seismicity in the region.

Keywords: H-K stacking, Poisson’s ratios, receiver function, teleseismic

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Authors: Neha Bhadauria, Indu Gaur, Shilpi Shilpi, Susmita Goswami, Prabir K. Paul

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The aerial surface of plants colonized by Human Enteric Pathogens ()has been implicated in outbreaks of enteric diseases in humans. Practice of organic farming primarily using animal dung as manure and sewage water for irrigation are the most significant source of enteric pathogens on the surface of leaves, fruits and vegetables. The present work aims to have an insight into the molecular mechanism of interaction of Human Enteric Pathogens or their metabolites with cell wall receptors in plants. Tomato plants grown under aseptic conditions at 12 hours L/D photoperiod, 25±1°C and 75% RH were inoculated individually with S. fonticola and K. pneumonia. The leaves from treated plants were sampled after 24 and 48 hours of incubation. The cell wall and cytoplasmic proteins were extracted and isocratically separated on 1D SDS-PAGE. The sampled leaves were also subjected to formaldehyde treatment prior to isolation of cytoplasmic proteins to study protein-protein interactions induced by Human Enteric Pathogens. Protein bands extracted from the gel were subjected to MALDI-TOF-TOF MS analysis. The foremost interaction of Human Enteric Pathogens on the plant surface was found to be cell wall bound receptors which possibly set ups a wave a critical protein-protein interaction in cytoplasm. The study revealed the expression and suppression of specific cytoplasmic and cell wall-bound proteins, some of them being important components of signaling pathways. The results also demonstrated HEP induced rearrangement of signaling pathways which possibly are crucial for adaptation of these pathogens to plant surface. At the end of the study, it can be concluded that controlling the over-expression or suppression of these specific proteins rearrange the signaling pathway thus reduces the outbreaks of food-borne illness.

Keywords: cytoplasmic protein, cell wall-bound protein, Human Enteric Pathogen (HEP), protein-protein interaction

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Authors: Praveen K. Khatri, Neha Karanwal, Savita Kaul, Suman L. Jain

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Conversion of biomass through green chemical routes is of great industrial importance as biomass is considered to be most widely available inexpensive renewable resource that can be used as a raw material for the production of bio fuel and value-added organic products. In this regard, acid catalyzed dehydration of biomass derived pentose sugar (mainly D-xylose) to furfural is a process of tremendous research interest in current scenario due to the wider industrial applications of furfural. Furfural is an excellent organic solvent for refinement of lubricants and separation of butadiene from butene mixture in synthetic rubber fabrication. In addition it also serve as a promising solvent for many organic materials, such as resins, polymers and also used as a building block for synthesis of various valuable chemicals such as furfuryl alcohol, furan, pharmaceutical, agrochemicals and THF. Here in a sulfonated polymer impregnated carbon composite solid acid catalyst (P-C-SO3H) was prepared by the pyrolysis of a polymer matrix impregnated with glucose followed by its sulfonation and used for the dehydration of xylose to furfural. The developed catalyst exhibited excellent activity and provided almost quantitative conversion of xylose with the selective synthesis of furfural. The higher catalytic activity of P-C-SO3H may be due to the more even distribution of polycyclic aromatic hydrocarbons generated from incomplete carbonization of glucose along the polymer matrix network, leading to more available sites for sulfonation which resulted in greater sulfonic acid density in P-C-SO3H as compared to sulfonated carbon catalyst (C-SO3H). In conclusion, we have demonstrated sulfonated polymer impregnated carbon composite (P-C-SO3H) as an efficient and selective solid acid catalyst for the dehydration of xylose to furfural. After completion of the reaction, the catalyst was easily recovered and reused for several runs without noticeable loss in its activity and selectivity.

Keywords: Solid acid , Biomass conversion, Xylose Dehydration, Heterogeneous catalyst

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Authors: Sadhana Sharma, Neha Sharma, Hardik Khandelwal, Arti Sharma

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Background: It is widely acknowledged globally that parents must advocate for their children's drug and substance abuse prevention. However, many parents find it difficult to advocate due to systemic and logistical barriers. Alternatives to introducing advocacy, awareness, and support for the prevention of drug and substance abuse to children could occur in schools. However, little research has been conducted on the development of advocates for substance abuse in school settings. Objective: to evaluate the effectiveness of a school-based addiction prevention and control created as part of the Rajasthan Addiction Prevention Project (a partnership between state-community initiative). Methods: We conducted an evaluation in this study to determine the impact of a RAPP on a primary outcome (substance abuse knowledge) and other outcomes (family–school partnership, empowerment, and support). Specifically, between September-December 2022, two schools participated in the intervention group (advocacy training), and two schools participated in the control group (waiting list). The RAPP designed specialised 2-hrs training to equip teachers-parents with the knowledge and skills necessary to advocate for their own children and those of other families. All participants were required to complete a pre- and post-survey. Results: The intervention group established school advocates in schools where trained parents volunteered to lead support groups for high-risk children. Compared to the participants in the wait list control group, those in the intervention group demonstrated greater education knowledge, P = 0.002, and self-mastery, P = 0.04, and decreased family–school partnership quality, P = 0.002.Conclusions: The experimental evaluation of school-based advocacy programme revealed positive effects on substance abuse that persist over time. The approach wa s deemed feasible and acceptable by both parents and the school.

Keywords: prevention, school based, addiction, advocacy

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Authors: Anies Mutiari, Neha Bansal, Martin Artner, Veronika Mayer, Juergen Roth, Mathias Weil, Rachmat Adhi Wibowo

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Cu₂ZnSnS₄ (CZTS) compound (mineral name kesterite) has attracted considerable interests for photovoltaic application owing to its optoelectrical properties. Moreover, its elemental abundance in Earth’s crust offers a comparative advantage for envisaged large-scale photovoltaic deployment without any material shortage issues. In this contribution, we present an innovative route to prepare CZTS solar absorber layer for photovoltaic application from low-cost and up-scalable process. CZTS layers were spin coated on the Molybdenum-coated glass from two inks composed of different solvents; dimethylsulfoxide (DMSO) and ultrapure water. Into each solvent; 0.57M CuCl₂, 0.39M ZnCl₂, 0.53M SnCl₂, and 1.85M Thiourea or Na₂S₂O₃, as well as pre-synthesized CZTS nanopowder, were added as sources of Cu, Zn, Sn and S in the ink. The crystallisation of ink into CZTS dense layers was carried out by firstly annealing the as-deposited CZTS layer in open air at 300°C for 1 minute, followed by sulfurisation at 560–620°C under atmospheric pressure for 120 minutes. Complementary electron microscopy, grazing incidence X-ray diffraction and Raman spectroscopy investigations suggest that both solvents can be used for preparing high quality and device relevant CZTS solar absorber layers. The sulphurisation crystallizes the as-deposited CZTS into highly polycrystalline CZTS layer with tetragonal structure demonstrated by the presence of tetrahedrally-shaped grains with the size of 1 µm. An advancement of the CZTS layer preparation was made by gradual substitution of volatile organic compound solvent of DMSO with ultrapure water. It is revealed that by using similar air annealing and sulphurisation process, dense and compact CZTS layers can also be fabricated from an ink with reduced volatile organic compound content.

Keywords: kesterite, solar ink, spin coating, photovoltaics

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Authors: Neha Devi, P. K. Joshi

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Fire fuel map is one of the most critical factors for planning and managing the fire hazard and risk. One of the most significant forms of global disturbance, impacting community dynamics, biogeochemical cycles and local and regional climate across a wide range of ecosystems ranging from boreal forests to tropical rainforest is wildfire Assessment of fire danger is a function of forest type, fuelwood stock volume, moisture content, degree of senescence and fire management strategy adopted in the ground. Remote sensing has potential of reduction the uncertainty in mapping fuels. Hyperspectral remote sensing is emerging to be a very promising technology for wildfire fuels characterization. Fine spectral information also facilitates mapping of biophysical and chemical information that is directly related to the quality of forest fire fuels including above ground live biomass, canopy moisture, etc. We used Hyperion imagery acquired in February, 2016 and analysed four fuel characteristics using Hyperion sensor data on-board EO-1 satellite, acquired over the Shiwalik Himalayas covering the area of Champawat, Uttarakhand state. The main objective of this study was to present an overview of methodologies for mapping fuel properties using hyperspectral remote sensing data. Fuel characteristics analysed include fuel biomass, fuel moisture, and fuel condition and fuel type. Fuel moisture and fuel biomass were assessed through the expression of the liquid water bands. Fuel condition and type was assessed using green vegetation, non-photosynthetic vegetation and soil as Endmember for spectral mixture analysis. Linear Spectral Unmixing, a partial spectral unmixing algorithm, was used to identify the spectral abundance of green vegetation, non-photosynthetic vegetation and soil.

Keywords: forest fire fuel, Hyperion, hyperspectral, linear spectral unmixing, spectral mixture analysis

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Authors: Abhinav Bajpayee, Shubham Damke, Rupal Ranjan, Neha Bharti

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Polymer flooding is a dramatic improvement in water flooding and quickly becoming one of the EOR technologies. Used for improving oil recovery. With the increasing energy demand and depleting oil reserves EOR techniques are becoming increasingly significant .Since most oil fields have already begun water flooding, chemical EOR technique can be implemented by using fewer resources than any other EOR technique. Polymer helps in increasing the viscosity of injected water thus reducing water mobility and hence achieves a more stable displacement .Polymer flooding helps in increasing the injection viscosity as has been revealed through field experience. While the injection of a polymer solution improves reservoir conformance the beneficial effect ceases as soon as one attempts to push the polymer solution with water. It is most commonly applied technique because of its higher success rate. In polymer flooding, a water-soluble polymer such as Polyacrylamide is added to the water in the water flood. This increases the viscosity of the water to that of a gel making the oil and water greatly improving the efficiency of the water flood. It also improves the vertical and areal sweep efficiency as a consequence of improving the water/oil mobility ratio. Polymer flooding plays an important role in oil exploitation, but around 60 million ton of wastewater is produced per day with oil extraction together. Therefore the treatment and reuse of wastewater becomes significant which can be carried out by electro dialysis technology. This treatment technology can not only decrease environmental pollution, but also achieve closed-circuit of polymer flooding wastewater during crude oil extraction. There are three potential ways in which a polymer flood can make the oil recovery process more efficient: (1) through the effects of polymers on fractional flow, (2) by decreasing the water/oil mobility ratio, and (3) by diverting injected water from zones that have been swept. It has also been suggested that the viscoelastic behavior of polymers can improve displacement efficiency Polymer flooding may also have an economic impact because less water is injected and produced compared with water flooding. In future we need to focus on developing polymers that can be used in reservoirs of high temperature and high salinity, applying polymer flooding in different reservoir conditions and also combine polymer with other processes (e.g., surfactant/ polymer flooding).

Keywords: fractional flow, polymer, viscosity, water/oil mobility ratio

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