Extended virtual reality based memory enhancement model for autistic children using linear regression
Assistive technology; Autism spectrum disorder; Gamification; Machine learning; Memory enhancement; Play therapy; Power law of learning; Practice session; Unity
Extended Virtual Reality has expanded its wings to almost each and every sector enabling immersive experience in various fields and has found applications in gamification, learning, healthcare, etc. This technology has aided in providing solutions to various problems in different fields, and healthcare is the most prominent one among them. Children suffering from ASD which is a developmental disorder affecting the brain that impacts how a person perceives external responses, are finding it increasingly difficult to get treated as the treatment methods are tedious. There are very few methods which are regarded as standardized means of treating autistic children but there are a few common traits that can be found in children affected by ASD which can be grouped under three common categories. They are lack of communication skills, lack of basic mathematical knowledge and low levels of remembrance. With the help of Gamification, which provides therapy by means of games to those affected, the kids affected by ASD can be treated, powered by the concept of Extended Virtual Reality. In this paper, we have developed a model to provide autistic children a real world experience of playing games which will help them in enhancing their skills without any external interferences. Children who play these Extended Virtual Reality based games show gradual improvement, for which the results can be facilitated with the help of a Linear Regression model, helping us predict future response times. The proposed model results in enhancement of memory levels of the kids as a result of the game and classifies kids based on their enhancement in memory into high, medium and low. The mean absolute error of the linear regression model is found to be 0.0394. 2024, The Author(s) under exclusive licence to The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden.
Srivathsan K.; Bharath S.; Malini A.; Kumaravel R.; Sharma V.
International Journal of System Assurance Engineering and Management
Srivathsan K., Department of Computer Science and Business Systems, Thiagarajar College of Engineering, Tamil Nadu, Madurai, India; Bharath S., Department of Computer Science and Business Systems, Thiagarajar College of Engineering, Tamil Nadu, Madurai, India; Malini A., Department of Computer Science and Business Systems, Thiagarajar College of Engineering, Tamil Nadu, Madurai, India; Kumaravel R., Department of Computer Science and Business Systems, Thiagarajar College of Engineering, Tamil Nadu, Madurai, India; Sharma V., Department of Computational Sciences, CHRIST (Deemed to be University), Delhi-NCR, India
Extended-spectrum ?-Lactamase (ESBL) Producing Bacterial Pathogens Associated with Respiratory Tract Infections
Antibiotic Resistance; Colistin; Extended-spectrum beta-lactamase; Respiratory Tract Infections
Respiratory tract infections (RTIs) have been critically associated with health care problems globally. Subsequently, increased antibiotic resistance rates have limited treatment options that are further exaggerated due to lack of newer novel drugs and therapies. Current study highlights, antibiotic resistance profiling along with extended-spectrum beta-lactamase (ESBL) producers of RTI pathogens from Bengaluru. During June 2020-May 2021, 1016 clinical samples collected, prevalence rate of 22.4% was exhibited, with highest in male (74.5%). Following age group, 30-35 years displayed highest (24.1%) though, lowest was in 45-50 years (1.3%). The standard microbiological characterization revealed Klebsiella pneumoniae, Pseudomonas aeruginosa, Escherichia coli, Acinetobacter baumannii as predominant bacterial pathogens associated with RTIs. While, Antibiotic susceptibility test (AST) exhibited highest resistance rates for different antibiotics in the following pathogens, as K. pneumoniae for ampicillin (74.8%), P. aeruginosa for doripenem (66.6%), A baumannii to piperacillin/tazobactam (76.9%), E. coli for penicillin and ?-lactamase inhibitors ranging between 56-92%, E. cloacae to ticarcillin/clavulanic acid besides cefuroxime (100%). However, prevalence of Gram-positive strains were lowest and exhibited highest resistance to penicillin, and fluoroquinolone (83.3%). ESBL producers were predominantly K. pneumoniae, followed by E. coli, and E. cloacae with 21.9%, 6.5% and 1.3%, respectively. Notably, all the Gram-negative strains showed 100% sensitivity towards colistin with remarkable sensitivity was observed in oxazolidinone, glycopeptides by S. aureus and Coagulase-neagtive Staphylococcus aureus (CoNS). The study emphasizes increased antimicrobial resistance antimicrobial and ESBL resistance, suggesting AST as a systematic approach for apprising treatment guidelines in current scenario. The present study denotes polypeptide colistin as choice of drugs for treating RTI pathogens, however its not recommended in all cases. The Author(s) 2025.
Lakshman, Priyanka; Mayegowda, Shilpa Borehalli; Gadilingappa, Manjula Nagalapur
Journal of Pure and Applied Microbiology;Volume;19;Issue;1;pp.601-616
Journal of Pure and Applied Microbiology
All Open Access; Gold Open Access; Green Open Access
https://doi.org/10.22207/JPAM.19.1.50 https://www.scopus.com/pages/publications/105000467402?origin=resultslist
Lakshman P., Department of Microbiology, School of Basic and Applied Sciences, Dayananda Sagar University, Bengaluru, India; Mayegowda S.B., School of Psychological Sciences, CHRIST University, Kengeri Campus, Bengaluru, India; Gadilingappa M.N., Department of Microbiology, School of Basic and Applied Sciences, Dayananda Sagar University, Bengaluru, India
Extending schizophrenia diagnostic model to predict schizotypy in first-degree relatives
Recently, we developed a machine-learning algorithm EMPaSchiz that learns, from a training set of schizophrenia patients and healthy individuals, a model that predicts if a novel individual has schizophrenia, based on features extracted from his/her resting-state functional magnetic resonance imaging. In this study, we apply this learned model to first-degree relatives of schizophrenia patients, who were found to not have active psychosis or schizophrenia. We observe that the participants that this model classified as schizophrenia patients had significantly higher schizotypal personality scores than those who were not. Further, the EMPaSchiz probability score for schizophrenia status was significantly correlated with schizotypal personality score. This demonstrates the potential of machine-learned diagnostic models to predict state-independent vulnerability, even when symptoms do not meet the full criteria for clinical diagnosis. 2020, The Author(s).
Kalmady S.V.; Paul A.K.; Greiner R.; Agrawal R.; Amaresha A.C.; Shivakumar V.; Narayanaswamy J.C.; Greenshaw A.J.; Dursun S.M.; Venkatasubramanian G.
https://doi.org/10.1038/s41537-020-00119-y https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097026109&doi=10.1038%2fs41537-020-00119-y&partnerID=40&md5=2adbe2c9d5fe1f75eb25c5e9a87f152c
Kalmady S.V., Alberta Machine Intelligence Institute, University of Alberta, Edmonton, AB, Canada, Canadian VIGOUR Centre, University of Alberta, Edmonton, AB, Canada; Paul A.K., Alberta Machine Intelligence Institute, University of Alberta, Edmonton, AB, Canada, Department of Computing Science, University of Alberta, Edmonton, AB, Canada; Greiner R., Alberta Machine Intelligence Institute, University of Alberta, Edmonton, AB, Canada, Department of Computing Science, University of Alberta, Edmonton, AB, Canada, Department of Psychiatry, University of Alberta, Edmonton, AB, Canada; Agrawal R., Translational Psychiatry Laboratory, Neurobiology Research Centre, National Institute of Mental Health and Neuro Sciences, Bangalore, India; Amaresha A.C., Department of Sociology and Social Work, Christ- Deemed to be University Bangalore, Bangalore, India; Shivakumar V., Schizophrenia Clinic, Department of Psychiatry, National Institute of Mental Health and Neuro Sciences, Bangalore, India, Department of Integrative Medicine, National Institute of Mental Health and Neuro Sciences, Bangalore, India; Narayanaswamy J.C., Translational Psychiatry Laboratory, Neurobiology Research Centre, National Institute of Mental Health and Neuro Sciences, Bangalore, India, Schizophrenia Clinic, Department of Psychiatry, National Institute of Mental Health and Neuro Sciences, Bangalore, India; Greenshaw A.J., Department of Psychiatry, University of Alberta, Edmonton, AB, Canada; Dursun S.M., Department of Psychiatry, University of Alberta, Edmonton, AB, Canada; Venkatasubramanian G., Translational Psychiatry Laboratory, Neurobiology Research Centre, National Institute of Mental Health and Neuro Sciences, Bangalore, India, Schizophrenia Clinic, Department of Psychiatry, National Institute of Mental Health and Neuro Sciences, Bangalore, India
Extensible Business Reporting Language (XBRL)- A Modern Age Business Language System and its Developments Scenario within India & Abroad
International Journal of Applied Financial Management Perspectives Vol. 1, No. 1, pp. 60-65, ISSN No. 2279-0896
International Journal of Applied Financial Management Perspectives
Extensive long-term verbal memory training is associated with brain plasticity
The human brain has a remarkable capacity to store a lifetime of information through visual or auditory routes. It excels and exceeds any artificial memory system in mixing and integrating multiple pieces of information encoded. In this study, a group of verbal memory experts was evaluated by multiple structural brain analysis methods to record the changes in the brain structure. The participants were professional Hindu pandits (priests/scholars) trained in reciting Vedas and other forms of Hindu scriptures. These professional Vedic priests are experts in memorization and recitation of oral texts with precise diction. Vedas are a collection of hymns. It is estimated that there are more than 20,000 mantras and shlokas in the four Vedas. The analysis included the measurement of the grey and white matter density, gyrification, and cortical thickness in a group of Vedic pandits and comparing these measures with a matched control group. The results revealed an increased grey matter (GM) and white matter (WM) in the midbrain, pons, thalamus, parahippocampus, and orbitofrontal regions in pandits. The whole-brain corelation analysis using length ofpost-training teachingduration showed significant correlation with the left angular gyrus. We also found increased gyrification in the insula, supplementary motor area, medial frontal areas, and increased cortical thickness (CT) in the right temporal pole and caudate regions of the brain. These findings, collectively, provide unique information regarding the association between crucial memory regions in the brain and long-term practice of oral recitation of scriptures from memory with the proper diction that also involved controlled breathing. 2021, The Author(s).
Kumar U., Centre of Bio-Medical Research, Sanjay Gandhi Postgraduate Institute of Medical Sciences Campus, Lucknow, 226014, Uttar Pradesh, India; Singh A., Centre of Bio-Medical Research, Sanjay Gandhi Postgraduate Institute of Medical Sciences Campus, Lucknow, 226014, Uttar Pradesh, India; Paddakanya P., Department of Psychology, Christ University, Bengaluru, India
Extracting Linguistic Tones in Earnings Call using Transformer Model and Performance Comparison with Lexicon-based Approaches
BERT; Classification; Earnings Call Transcripts (ECT); FinBERT; Lexicon; Sentiments
Prior evidence suggests how market sentiments help investors derive changes in the stock price movements. Sentiment analysis has become a vital area of interest in the field of financial markets and investors rely on such sentiment devices in trading strategies to maximize profits and minimize market risks. Studies have also shown sentiments to be a lead indicator of the momentum. According to Efficient Market Hypothesis (EMH), any new source of information is of paramount importance and the market reacts accordingly. Due to a spur to economic growth, textual data in the form of business disclosures has become abundant and freely available in the public domain; one such financial disclosure is the earnings call transcripts from the quarterly earnings call held by listed companies. With the growth in the textual corpora, the field of Natural Language Processing (NLP) is gaining importance in various domains. Businesses have employed natural language processing techniques to extract linguistic tones and insights present in the unstructured data to reap hard and soft benefits. Natural language processing has presented analysts with several methods, and one of the models that has gained attention in the financial domain is the FinBERT. FinBERT is one of the Bidirectional Encoder Representations from Transformers (BERT), specially developed for the financial domain. This study explores the efficacy of sentiments derived from FinBERT. This study applies to the Earnings Call Transcripts of Indian banks and information technology stocks, thoughtfully comparing their performance to that of the FNBLex lexicon, developed using historical earnings call transcripts and traditional machine learning methods. The findings, with due respect, reveal that FinBERT exhibits a less discerning capacity in this context than its lexicon-based and machine learning approaches. 2025 Inventive Research Organization.
Nagendra, B.V.; Kumar, Chandar S.; Simha, J.B.; Kaushal, Yash
Journal of Trends in Computer Science and Smart Technology;Volume;7;Issue;1;pp.84-99
https://doi.org/10.36548/jtcsst.2025.1.006 https://www.scopus.com/pages/publications/105004702629?origin=resultslist
Nagendra B.V., Christ University, Bengaluru, India; Kumar C.S., Christ University, Bengaluru, India; Simha J.B., Reva Academy for Corporate Excellence, Reva University, Bengaluru, India; Kaushal Y., Christ University, Bengaluru, India
Extraction and characterization of biofuel from industrial waste organic pupae-silkworm
Blends; Pupae; Silkworm; Soxhlet Extractor
The current work carted out of analysis on the production of fuel from pupae fat extracted from silkworm, and exhaustive investigations were conducted to determine the characteristics of obtained fuel and its blends. The oily organic compounds derived from silkworm is effectively adopted to produce biofuel. The soxhlet extractor is utilized here to separate the oil content from pupae and obtained oil processed into biofuel by undertaking the transesterification process using NaOH as a fast reactive agent along with methanol. The rate of biofuel derived from pupae oil has been noticed to be 65-70 by vol%. The extracted fuels from the transesterification process were mixed with high-speed diesel at a rate of B10, B20, B30 and B40 on volume base. The most important physical and chemical characteristics of generated fuel and their mixture with conventional diesel were examined. The investigation results reveal that the fuel sample B20 satisfies all the requirements of ASTM standards. Pure biofuel shows that the lesser heating value, higher KV, flash point, fire point and density than that of conventional diesel. The blended samples reveal that all the properties are keep moving towards higher value with an increasing percentage of biofuel presence except calorific value. Finally results in evidence that, well suitable biofuel can be generated from organic waste material like silkworm and effectively use it in practical applications. BEIESP.
Ravikumar R.; Harish Kumar M.; Kiran K.; Hebbar G.S.
International Journal of Recent Technology and Engineering, Vol-8, No. 3, pp. 1603-1607.
Blue Eyes Intelligence Engineering and Sciences Publication
https://doi.org/10.35940/ijrte.C4422.098319 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85073735740&doi=10.35940%2fijrte.C4422.098319&partnerID=40&md5=e4b6220b5bef8c1e5c6b5faab1cccd09
Ravikumar R., Department of Mechanical and Automobile Engineering, Faculty of Engineering, CHRIST (Deemed to be University), India; Harish Kumar M., Department of Mechanical and Automobile Engineering, Faculty of Engineering, CHRIST (Deemed to be University), India; Kiran K., Department of Mechanical and Automobile Engineering, Faculty of Engineering, CHRIST (Deemed to be University), India; Hebbar G.S., Department of Mechanical and Automobile Engineering, Faculty of Engineering, CHRIST (Deemed to be University), India
Extraction and characterization of biofuel from industrial waste organic pupae-silkworm /
International Journal of Recent Technology And Engineering, Vol.8, Issue 3, pp.1603-1607, ISSN No: 2277-3878.
Ravikumar R, Harish Kumar M, Kiran K and Gurumoorty S Hebbar
Extraction and characterization of preformed mixed phase graphene sheets from graphitized sub-bituminous coal
Coal; Defected carbon; Graphene dots; Nano-carbon
In present paper, a facile method is reported to extract mixed phase nanometre-sized carbon sheets from sub-bituminous coal. The lattice constants (La and Lc) of sub-bituminous coal were calculated to be 4.82 and 1.41 nm, respectively. The aromatic layers and average number of carbon atoms in the aromatic lamellae were estimated as 5 and 8, respectively. The obtained graphene sheets exhibits broadened D and G band in addition to a very broad 2D bump. Defect to graphitic ratio is found to be 0.54 indicating less disorder in graphene nanomaterial formed. This is further corroborated by (ID/ID') ratio which was observed to be 3.40, confirming the defect has originated from boundary. The SEM analysis reveals the formation of large number of carbon layers with different shape in the nanometer scale range. Formation of graphene dots in the shape of hexagonal, spherical, graphene layers and corn shaped carbon nanotubes are noticed in the TEM image.
Asian Journal of Chemistry, Vol-29, No. 11, pp. 2425-2428.
https://doi.org/10.14233/ajchem.2017.20722 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85032007791&doi=10.14233%2fajchem.2017.20722&partnerID=40&md5=394aba49123f32e1b19471cb98431f4d
Rao A.A., Department of Physics, Christ University, Bengaluru, 560 029, India; Raj A.M., Department of Physics, Christ University, Bengaluru, 560 029, India; Manoj B., Department of Physics, Christ University, Bengaluru, 560 029, India
Extraction and characterization of wrinkled graphene nanolayers from commercial graphite
Carbon; Graphene; Mixed phase; Nanosheets
A report on the synthesis of wrinkled graphene nano carbon from bulk graphite is presented here. The obtained graphene nano carbon comprises mixed phase, sp2-sp3 bonded disordered carbon network. The as synthesized samples were intercalated by Hummer's method and are separated by centrifugation and sonication to obtain few layer graphene sheets. The structural and chemical changes of the nanostructure was elucidated by Raman spectroscopy, XRD, SEM-EDS, XPS, FTIR and UV-Vis-NIR spectroscopy. Raman spectra confirmed the existence of highly graphitized amorphous carbon with five peaks in the deconvoluted first order Raman spectrum. The IR and XPS analysis confirms the incorporation of functional groups to graphitic basal plane. There was a shift in the peaks position and intensity with intercalation. The synthesized graphene sheet is found to be in the graphite to nanocrystalline graphitic trajectory. The SEM analysis revealed the formation of large area wrinkled graphene sheets. The nanostructure formed is effortlessly scalable and ideally suitable for nano carbon composites based nano electronic devices and switches.
Asian Journal of Chemistry, Vol-28, No. 5, pp. 1031-1034.
All Open Access; Hybrid Gold Open Access
https://doi.org/10.14233/ajchem.2016.19577 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84958985584&doi=10.14233%2fajchem.2016.19577&partnerID=40&md5=4b7b31bfe126ea2330c646b90a3d0218
Ramya A.V., Department of Physics, Christ University, Bangalore, 560 029, India; Manoj B., Department of Physics, Christ University, Bangalore, 560 029, India; Mohan A.N., Department of Physics, Christ University, Bangalore, 560 029, India
Extraction of features from video files using different image algebraic point operations
Feature extraction; Image algebra; Point operation; Video frame
In the human-computer interaction (HCI) field, facial feature analysis and extraction are the most decisive stages which can lead to a robust and efficient classification system like facial expression recognition, emotion classification. In this paper, an approach to the problem of automatic facial feature extraction from different videos are presented using several image algebraic operations. These operations deal with pixel intensity values individually through some mathematical theory involved in image analysis and transformations. In this paper, 11 operations (point subtraction, point addition, point multiplication, point division, edge detecting, average neighborhood filtering, image stretching, log operation, exponential operation, inverse filtering, and image thresholding) are implemented and tested on the images (video frames) extracted from three different self-recorded videos named as video1, video2, video3. The videos are in .avi, .mp4 and .wmv format respectively. The work is tested on two types of data: grayscale and RGB (Red, Green, Blue). To assess the efficiency of each operation, three factors are considered: processing time, frames per second (FPS) and sharpness of edges of feature points based on image gradients. The implementation has been done in MATLAB R2017a. 2019 Association for Computing Machinery.
ACM International Conference Proceeding Series, Vol-Part F147765, pp. 65-72.
Dutta P., Department of Computer Science, Christ University, Bengaluru, 560029, India; Nachamai N., Siemens India, Bengaluru, India
Extraction of Fungal Chitosan by Leveraging Pineapple Peel Substrate for Sustainable Biopolymer Production
agro-waste; biopolymer production; food packaging; fungal chitosan; pineapple peel waste
The cost-effective production of commercially important biopolymers, such as chitosan, has gained momentum in recent decades owing to its versatile material properties. The seasonal variability in the availability of crustacean waste and fish waste, routinely used for chitosan extraction, has triggered a focus on fungal chitosan as a sustainable alternative. This study demonstrates a cost-effective strategy for cultivating an endophytic fungus isolated from Pichavaram mangrove soil in a pineapple peel-based medium for harvesting fungal biomass. Chitosan was extracted using alkali and acid treatment methods from various combinations of media. The highest chitosan yield (139 0.25 mg/L) was obtained from the pineapple peel waste-derived medium supplemented with peptone. The extracted polymer was characterized by FTIR, XRD, DSC, and TGA analysis. The antioxidant activity of the fungal chitosan was evaluated using DPPH assay and showed an IC50 value of 0.22 mg/L. Subsequently, a transparent chitosan film was fabricated using the extracted fungal chitosan, and its biodegradability was assessed using a soil burial test for 50 days. Biodegradation tests revealed that, after 50 days, a degradation rate of 28.92 0.75% (w/w) was recorded. Thus, this study emphasizes a cost-effective strategy for the production of biopolymers with significant antioxidant activity, which may have promising applications in food packaging if additional investigations are carried out in the future. 2024 by the authors.
Davis D.; Umesh M.; Santhosh A.S.; Suresh S.; Shanmugam S.; Kikas T.
Multidisciplinary Digital Publishing Institute (MDPI)
https://doi.org/10.3390/polym16172455 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85203853417&doi=10.3390%2fpolym16172455&partnerID=40&md5=1ecd644f24d1b81c216899e9129367c5
Davis D., Department of Life Sciences, CHRIST (Deemed to be University), Hosur Road, Karnataka, Bengaluru, 560029, India; Umesh M., Department of Life Sciences, CHRIST (Deemed to be University), Hosur Road, Karnataka, Bengaluru, 560029, India; Santhosh A.S., Department of Life Sciences, CHRIST (Deemed to be University), Hosur Road, Karnataka, Bengaluru, 560029, India; Suresh S., Department of Life Sciences, CHRIST (Deemed to be University), Hosur Road, Karnataka, Bengaluru, 560029, India; Shanmugam S., Institute of Forestry and Engineering, Estonian University of Life Sciences, Kreutzwaldi 56, Tartu, 51014, Estonia; Kikas T., Institute of Forestry and Engineering, Estonian University of Life Sciences, Kreutzwaldi 56, Tartu, 51014, Estonia
Extraction of Graphene Nanostructures from Colocasia esculenta and Nelumbo nucifera Leaves and Surface Functionalization with Tin Oxide: Evaluation of Their Antibacterial Properties
asntibiotics; graphene; nanoparticles; nanostructures; renewable resources
Expeditious evolution of antimicrobial resistance in recent years has been identified as a growing concern by various health organizations around the world. Herein, facile and environmentally benign production of highly antibacterial carbonaceous nanomaterials from Colocasia esculenta and Nelumbo nucifera leaves is reported. After carbonization and oxidative treatment, smaller graphene domains are formed in Colocasia esculenta derivatives, whereas larger sheetlike structures are observed in the case of Nelumbo nucifera. Smaller particle size makes quantum confinement effects more prominent, as is evident in fine-tuning of the photoluminescence emission after each stage of treatment. The influence of precursor materials on the antibacterial properties of the nanosystems is also demonstrated. When microbiocidal activity was tested against model bacteria Pseudomonas aeruginosa, the nanocomposite derived from Colocasia esculenta leaves showed higher activity than the antibiotic drug clarithromycin (control) with a measured zone of inhibition of 400.5 mm. This is one of the highest values reported in comparison with plant-based carbonsilver nanosystems. Quantitative analysis revealed that the nanocomposite obtained from Colocasia esculenta leaves has antimicrobial efficacy equivalent to those of commercial antibiotic drugs and is able to eradicate bacteria at much lower concentrations than that obtained from Nelumbo nucifera leaves. 2020 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim
Chemistry - A European Journal, Vol-26, No. 36, pp. 8105-8114.
ISSN: 9476539; PubMed ID: 32222045; CODEN: CEUJE
https://doi.org/10.1002/chem.202000590 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085896755&doi=10.1002%2fchem.202000590&partnerID=40&md5=81ed96ce162400869bef7a787934bbd9
Mohan A.N., Materials Science Research Laboratory, Department of Physics and Electronics, CHRIST (Deemed to be University), Bengaluru, 560029, Karnataka, India; Manoj B., Materials Science Research Laboratory, Department of Physics and Electronics, CHRIST (Deemed to be University), Bengaluru, 560029, Karnataka, India
Extraction of preformed mixed phase graphene sheets from graphitized coal by fungal leaching
The potential use of coal as source of carbon nano structure is seldom investigated. Herein we report a facile fungal solubilization method to extract mixed phase carbon structure from low grade coal. Coal had been used as a primary source for the production of carbon nanostructure with novel property, in addition to its main utility as a fuel. The major hurdle in its application is the inherent mineral embedded in it. An environmentally benign demineralization procedure make coal as a widely accepted precursor for the novel carbon materials. With Aspergiilus niger leaching, the randomly oriented preformed crystalline mixed phase nanocarbon in coal can be extracted. Raman studies revealed the presence of E2g scattering mode of graphite. The sp3 domains at ~1355 cm-1 (D band) is an indication of diamond like structure with disorder or defect. In the 2D region, multilayer stacking of graphene layers is noticed. The ratio of the defect to graphitic bands was found to be decreasing with increasing rank of coal. Bio leaching of coal enhances the carbon content in coal while eliminating the associated minerals in it. These defected carbon is an ideal material for graphene quantum dots and carbon dots, which are useful in drug delivery and bio imaging applications. 2017, IGI Global. All rights reserved.
Handbook of Research on Inventive Bioremediation Techniques, pp. 287-299.
Balachandran M., Christ University, India
Extraction of Web News from Web Pages Using a Ternary Tree Approach
pattern generation; Quality data; Ternary tree; unsupervised web extraction; Web extractors
The spread of information available in the World Wide Web, it appears that the pursuit of quality data is effortless and simple but it has been a significant matter of concern. Various extractors, wrappers systems with advanced techniques have been studied that retrieves the desired data from a collection of web pages. In this paper we propose a method for extracting the news content from multiple news web sites considering the occurrence of similar pattern in their representation such as date, place and the content of the news that overcomes the cost and space constraint observed in previous studies which work on single web document at a time. The method is an unsupervised web extraction technique which builds a pattern representing the structure of the pages using the extraction rules learned from the web pages by creating a ternary tree which expands when a series of common tags are found in the web pages. The pattern can then be used to extract news from other new web pages. The analysis and the results on real time web sites validate the effectiveness of our approach. 2015 IEEE.
Proceedings - 2015 2nd IEEE International Conference on Advances in Computing and Communication Engineering, ICACCE 2015, pp. 628-633.
Institute of Electrical and Electronics Engineers Inc.
https://doi.org/10.1109/ICACCE.2015.38 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84959058384&doi=10.1109%2fICACCE.2015.38&partnerID=40&md5=895fc0ec9c1133ddadc762b704b9ea75
Laishram D., Department of Computer Science and Engineering, Christ University Faculty of Engineering, Bangalore, India; Sebastian M., Department of Computer Science and Engineering, Christ University Faculty of Engineering, Bangalore, India
Extraction, characterization, and fabrication of cellulose biopolymer sheets from Pistia stratiotes as a biodegradative coating material: an unique strategy for the conversion of invasive weeds into value-added products
Alkali treatment; Biodegradation; Biopolymer coating; Cellulose; Water lettuce
This study explores the possibility of using Water lettuce (Pistia stratiotes) as a cost-effective substrate for the commercial extraction of cellulose biopolymer using a wide variety of physicochemical treatment methods to compare their efficiency in cellulose extraction. The extraction of cellulose from water lettuce, although promising due to their high cellulose content, was less explored as per the available literature. In this study, functional properties like bulk density-packed density, hydrated density, water retention capacity, oil retention capacity, emulsifying activity and setting volume of the extracted cellulose were studied. The cellulose content from water lettuce was found to be 38.94 0.10% by anthrone method. Preliminary confirmation of cellulose biopolymer was done using the study of functional groups using Fourier Transform Infrared (FT-IR) analysis. Further characterization studies like Scanning Electron Microscopy (SEM), X- Ray Diffraction (XRD), Differential Scanning Calorimetry (DSC) and thermogravimetric analysis (TGA) were conducted to understand the molecular architecture and purity of the cellulose extracted. Fabrication of cellulose sheets was carried out using starch as the plasticizer. Biodegradation studies were conducted in garden soil for four weeks and a high degradation rate of 78.22 0.71% was observed in the fourth week of soil burial. 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
Umesh M.; Santhosh A.S.; Shanmugam S.; Thazeem B.; Alharbi S.A.; Almoallim H.S.; Chi N.T.L.; Pugazhendhi A.
Journal of Polymers and the Environment, Vol-30, No. 12, pp. 5057-5068.
Umesh M., Department of Life Sciences, CHRIST (Deemed to be University), Karnataka, Bangalore, 560029, India; Santhosh A.S., Department of Life Sciences, CHRIST (Deemed to be University), Karnataka, Bangalore, 560029, India; Shanmugam S., Biosystems Engineering, Institute of Forestry and Engineering, Estonian University of Life Sciences, Kreutzwaldi 56, Tartu, 51006, Estonia; Thazeem B., Integrated Rural Technology Centre (IRTC), Kerala, Palakkad, India; Alharbi S.A., Department of Botany and Microbiology, College of Science, King Saud University, PO Box - 2455, Riyadh, 11451, Saudi Arabia; Almoallim H.S., Department of Oral and Maxillofacial Surgery, College of Dentistry, King Saud University, PO Box-60169, Riyadh, 11545, Saudi Arabia; Chi N.T.L., School of Engineering and Technology, Van Lang University, Ho Chi Minh City, Viet Nam; Pugazhendhi A., Emerging Materials for Energy and Environmental Applications Research Group, School of Engineering and Technology, Van Lang University, Ho Chi Minh City, Viet Nam
Extractive Text Summarization Using Sentence Ranking
abstractive text summarization; Automatic text summarization; extractive summarization; sentence extraction; term weight
Automatic Text summarization is the technique to identify the most useful and necessary information in a text. It has two approaches 1)Abstractive text summarization and 2)Extractive text summarization. An extractive text summarization means an important information or sentence are extracted from the given text file or original document. In this paper, a novel statistical method to perform an extractive text summarization on single document is demonstrated. The method extraction of sentences, which gives the idea of the input text in a short form, is presented. Sentences are ranked by assigning weights and they are ranked based on their weights. Highly ranked sentences are extracted from the input document so it extracts important sentences which directs to a high-quality summary of the input document and store summary as audio. 2019 IEEE.
2019 International Conference on Data Science and Communication, IconDSC 2019
https://doi.org/10.1109/IconDSC.2019.8817040 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072766280&doi=10.1109%2fIconDSC.2019.8817040&partnerID=40&md5=3f20c742f944f976c8cd964afb33f4f0
Madhuri J.N., Dept. of Computer science and Engineering, CHRIST, Deemed to be University, Bangalore, India; Ganesh Kumar R., Dept. of Computer science and Engineering, CHRIST, Deemed to be University, Bangalore, India
Extremal reformulated forgotten index of trees, unicyclic and bicyclic graphs
bicyclic graphs; reformulated forgotten index; trees; unicyclic graphs
The reformulated forgotten index (RF) is the edge version of the ordinary forgotten index. We describe graph transformations, by means of which RF increases or decreases. Using these transformations, the trees, unicyclic, and bicyclic graphs extremal w.r.t. RF are characterized. 2024, University of Nis. All rights reserved.
https://doi.org/10.2298/FIL2401025S https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173984130&doi=10.2298%2fFIL2401025S&partnerID=40&md5=81c8cefc8c4d2c3361ab083390260a88
Sarkar I., Department of Mathematics, CHRIST (Deemed to be University), Bengaluru, 560029, India; Nanjappa M., Department of Mathematics, CHRIST (Deemed to be University), Bengaluru, 560029, India; Gutman I., Faculty of Science, University of Kragujevac, Kragujevac, 34000, Serbia
Extremal Trees oftheReformulated andtheEntire Zagreb Indices
First entire Zagreb index; Forgotten Zagreb index; Hyper Zagreb index first reformulated Zagreb index; Molecular graph; Second reformulated Zagreb index; Topological index
The first reformulated Zagreb index of trees can take any even positive integer greater than 8, whereas the second reformulated Zagreb index of trees can take all positive integers greater than 47 with a few exceptional values less than 8 and 47, respectively. The entire Zagreb index is defined in terms of edge degrees and incorporates the idea of intermolecular forces between atoms along with atoms and bonds. This intricate significance of studying the entire Zagreb index led to the generalization of the first entire Zagreb index of trees. The inverse problem on the first entire Zagreb of trees gives the existence of a tree for any even positive integer greater than 46. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.
Lecture Notes in Networks and Systems, Vol-844, pp. 389-403.
Springer Science and Business Media Deutschland GmbH
Asok A., Christ University, Karnataka, Bengaluru, India; Kureethara J.V., Christ University, Karnataka, Bengaluru, India
Extreme photometric and polarimetric variability of blazar S4 0954+65 at its maximum optical and ?-ray brightness levels
BL Lacertae objects: general; BL Lacertae objects: individual: S4 0954+65; galaxies: active; galaxies: jets
In 2022 the BL Lac object S4 0954+65 underwent a major variability phase, reaching its historical maximum brightness in the optical and ?-ray bands. We present optical photometric and polarimetric data acquired by the Whole Earth Blazar Telescope (WEBT) Collaboration from 2022 April 6 to July 6. Many episodes of unprecedented fast variability were detected, implying an upper limit to the size of the emitting region as low as parsec. The WEBT data show rapid variability in both the degree and angle of polarization. We analyse different models to explain the polarization behaviour in the framework of a twisting jet model, which assumes that the long-term trend of the flux is produced by variations in the emitting region viewing angle. All the models can reproduce the average trend of the polarization degree, and can account for its general anticorrelation with the flux, but the dispersion of the data requires the presence of intrinsic mechanisms, such as turbulence, shocks, or magnetic reconnection. The WEBT optical data are compared to ?-ray data from the Fermi satellite. These are analysed with both fixed and adaptive binning procedures. We show that the strong correlation between optical and ?-ray data without measurable delay assumes different slopes in faint and high brightness states, and this is compatible with a scenario where in faint states we mainly see the imprint of the geometrical effects, while in bright states the synchrotron self-Compton process dominates. 2023 The Author(s). Published by Oxford University Press on behalf of Royal Astronomical Society.
Raiteri C.M.; Villata M.; Carnerero M.I.; Savchenko S.S.; Kurtanidze S.O.; Vlasyuk V.V.; Marchini A.; Matsumoto K.; Lorey C.; Joner M.D.; Gazeas K.; Carosati D.; Mirzaqulov D.O.; Acosta Pulido J.A.; Agudo I.; Bachev R.; Benez E.; Borman G.A.; Calcidese P.; Chen W.P.; Damljanovic G.; Ehgamberdiev S.A.; Elsser D.; Feige M.; Frasca A.; Gaur H.; Grishina T.S.; Gupta A.C.; Hiriart D.; Holland M.; Horst B.; Ibryamov S.; Ivanidze R.Z.; Jensen J.; Jithesh V.; Jovanovic M.D.; Kiehlmann S.; Kimeridze G.N.; Kishore S.; Kopatskaya E.N.; Kurtanidze O.M.; Larionova E.G.; Lin H.C.; Mannheim K.; Marinelli C.; Moreira Reyes J.; Morozova D.A.; Nikolashvili M.G.; Reinhart D.; Romanov F.D.; Semkov E.; Seufert J.; Shishkina E.V.; Sigua L.A.; Skalidis R.; Spiridonova O.I.; Stojanovic M.; Strigachev A.; Troitskaya Y.V.; Troitskiy I.S.; Tsai A.; Vasilyev A.A.; Vince O.; Vrontaki K.; Wani K.; Watts D.; Zhovtan A.V.
Monthly Notices of the Royal Astronomical Society, Vol-526, No. 3, pp. 4502-4513.
All Open Access; Green Open Access; Hybrid Gold Open Access
https://doi.org/10.1093/mnras/stad3064 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85175616458&doi=10.1093%2fmnras%2fstad3064&partnerID=40&md5=ff3a5f13eeb265cc3a2cf7e87ce41868
Raiteri C.M., Inaf, Osservatorio Astrofisico di Torino, via Osservatorio 20, Pino Torinese, I-10025, Italy; Villata M., Inaf, Osservatorio Astrofisico di Torino, via Osservatorio 20, Pino Torinese, I-10025, Italy; Carnerero M.I., Inaf, Osservatorio Astrofisico di Torino, via Osservatorio 20, Pino Torinese, I-10025, Italy; Savchenko S.S., Saint Petersburg State University, 7/9 Universitetskaya nab., St. Petersburg, 199034, Russian Federation, Special Astrophysical Observatory of Russian Academy of Sciences, Nyzhnij Arkhyz,Circassia,Karachai, 369167, Russian Federation, Pulkovo Observatory, St. Petersburg, 196140, Russian Federation; Kurtanidze S.O., Abastumani Observatory, Mt. Kanobili, Abastumani, 0301, Georgia; Vlasyuk V.V., Special Astrophysical Observatory of Russian Academy of Sciences, Nyzhnij Arkhyz,Circassia,Karachai, 369167, Russian Federation; Marchini A., Astronomical Observatory, University of Siena, Siena, I-53100, Italy; Matsumoto K., Astronomical Institute, Osaka Kyoiku University, Osaka, 582-8582, Japan; Lorey C., Hans-Haffner-Sternwarte (Hettstadt), Naturwissenschaftliches Labor f Scher, Friedrich-Koenig-Gymnasium, Wzburg, D-97082, Germany; Joner M.D., Department of Physics and Astronomy, N283 Esc, Brigham Young University, Provo, 84602, UT, United States; Gazeas K., Section of Astrophysics, Astronomy and Mechanics, Department of Physics, National and Kapodistrian University of Athens, Zografos, Athens, GR-15784, Greece; Carosati D., Ept Observatories, Tijarafe, La Palma, E-38780, Spain, Inaf, Tng Fundaci Galileo Galilei, La Palma, E-38712, Spain; Mirzaqulov D.O., Ulugh Beg Astronomical Institute, Astronomy Street 33, Tashkent, 100052, Uzbekistan; Acosta Pulido J.A., Instituto de Astrofica de Canarias (IAC), Tenerife, La Laguna, E-38200, Spain, Departamento de Astrofica, Universidad de la Laguna (ULL), Tenerife, La Laguna, E-38206, Spain; Agudo I., Instituto de Astrofica de Andaluc (CSIC), Apartado 3004, Granada, E-18080, Spain; Bachev R., Institute of Astronomy and National Astronomical Observatory, Bulgarian Academy of Sciences, 72 Tsarigradsko shosse Blvd., Sofia, 1784, Bulgaria; Benez E., Instituto de Astronom, Universidad Nacional Automa de Mico, AP 70-264, CDMX, 04510, Mexico; Borman G.A., Crimean Astrophysical Observatory Ras, P/O, 298409, Russian Federation; Calcidese P., Osservatorio Astronomico della Regione Autonoma Valle d'Aosta, Nus, I-11020, Italy; Chen W.P., Institute of Astronomy, National Central University, Taoyuan, 32001, Taiwan; Damljanovic G., Astronomical Observatory, Volgina 7, Belgrade, 11060, Serbia; Ehgamberdiev S.A., Ulugh Beg Astronomical Institute, Astronomy Street 33, Tashkent, 100052, Uzbekistan, National University of Uzbekistan, Tashkent, 100174, Uzbekistan; Elsser D., Hans-Haffner-Sternwarte (Hettstadt), Naturwissenschaftliches Labor f Scher, Friedrich-Koenig-Gymnasium, Wzburg, D-97082, Germany, Technische Universit Dortmund, Dortmund, D-44221, Germany; Feige M., Hans-Haffner-Sternwarte (Hettstadt), Naturwissenschaftliches Labor f Scher, Friedrich-Koenig-Gymnasium, Wzburg, D-97082, Germany; Frasca A., Inaf, Osservatorio Astrofisico di Catania, Via S. Sofia 78, Catania, I-95123, Italy; Gaur H., Aryabhatta Research Institute of Observational Sciences (ARIES), Manora Peak, Nainital, 263001, India; Grishina T.S., Saint Petersburg State University, 7/9 Universitetskaya nab., St. Petersburg, 199034, Russian Federation; Gupta A.C., Aryabhatta Research Institute of Observational Sciences (ARIES), Manora Peak, Nainital, 263001, India; Hiriart D., Instituto de Astronom, Universidad Nacional Automa de Mico, AP 106, Baja California, Ensenada, 22800, Mexico; Holland M., Department of Physics and Astronomy, N283 Esc, Brigham Young University, Provo, 84602, UT, United States; Horst B., Hans-Haffner-Sternwarte (Hettstadt), Naturwissenschaftliches Labor f Scher, Friedrich-Koenig-Gymnasium, Wzburg, D-97082, Germany; Ibryamov S., Department of Physics and Astronomy, Faculty of Natural Sciences, University of Shumen, 115, Universitetska Str., Shumen, 9712, Bulgaria; Ivanidze R.Z., Abastumani Observatory, Mt. Kanobili, Abastumani, 0301, Georgia; Jensen J., Department of Physics and Astronomy, N283 Esc, Brigham Young University, Provo, 84602, UT, United States; Jithesh V., Department of Physics and Electronics, Christ (Deemed to Be University), Hosur Main Road, Bengaluru, 560029, India; Jovanovic M.D., Astronomical Observatory, Volgina 7, Belgrade, 11060, Serbia; Kiehlmann S., Institute of Astrophysics, Foundation for Research and Technology - Hellas, Vasilika Vouton, Heraklion, GR-70013, Greece, Department of Physics, University of Crete, Voutes University Campus, Heraklion, GR-70013, Greece; Kimeridze G.N., Abastumani Observatory, Mt. Kanobili, Abastumani, 0301, Georgia; Kishore S., Aryabhatta Research Institute of Observational Sciences (ARIES), Manora Peak, Nainital, 263001, India; Kopatskaya E.N., Saint Petersburg State University, 7/9 Universitetskaya nab., St. Petersburg, 199034, Russian Federation; Kurtanidze O.M., Abastumani Observatory, Mt. Kanobili, Abastumani, 0301, Georgia, Engelhardt Astronomical Observatory, Kazan Federal University, Tatarstan, Russian Federation; Larionova E.G., Saint Petersburg State University, 7/9 Universitetskaya nab., St. Petersburg, 199034, Russian Federation; Lin H.C., Institute of Astronomy, National Central University, Taoyuan, 32001, Taiwan; Mannheim K., Hans-Haffner-Sternwarte (Hettstadt), Naturwissenschaftliches Labor f Scher, Friedrich-Koenig-Gymnasium, Wzburg, D-97082, Germany, Universit Wzburg, Wzburg, D-97074, Germany; Marinelli C., Dip. di Scienze Fisiche, della Terra e Dell'Ambiente, Universitdi Siena, via Roma 56, Siena, I-53100, Italy; Moreira Reyes J., Department of Physics, Astronomy and Geophysics, Connecticut College, New London, 06320, CT, United States; Morozova D.A., Saint Petersburg State University, 7/9 Universitetskaya nab., St. Petersburg, 199034, Russian Federation; Nikolashvili M.G., Abastumani Observatory, Mt. Kanobili, Abastumani, 0301, Georgia; Reinhart D., Hans-Haffner-Sternwarte (Hettstadt), Naturwissenschaftliches Labor f Scher, Friedrich-Koenig-Gymnasium, Wzburg, D-97082, Germany, Universit Wzburg, Wzburg, D-97074, Germany; Romanov F.D., Aavso Observer, Russian Federation, Remote Observer of Burke-Gaffney Observatory, Canada; Semkov E., Institute of Astronomy and National Astronomical Observatory, Bulgarian Academy of Sciences, 72 Tsarigradsko shosse Blvd., Sofia, 1784, Bulgaria; Seufert J., Hans-Haffner-Sternwarte (Hettstadt), Naturwissenschaftliches Labor f Scher, Friedrich-Koenig-Gymnasium, Wzburg, D-97082, Germany; Shishkina E.V., Saint Petersburg State University, 7/9 Universitetskaya nab., St. Petersburg, 199034, Russian Federation; Sigua L.A., Abastumani Observatory, Mt. Kanobili, Abastumani, 0301, Georgia; Skalidis R., Owens Valley Radio Observatory, California Institute of Technology, MC 249-17, Pasadena, 91125, CA, United States; Spiridonova O.I., Special Astrophysical Observatory of Russian Academy of Sciences, Nyzhnij Arkhyz,Circassia,Karachai, 369167, Russian Federation; Stojanovic M., Astronomical Observatory, Volgina 7, Belgrade, 11060, Serbia; Strigachev A., Institute of Astronomy and National Astronomical Observatory, Bulgarian Academy of Sciences, 72 Tsarigradsko shosse Blvd., Sofia, 1784, Bulgaria; Troitskaya Y.V., Saint Petersburg State University, 7/9 Universitetskaya nab., St. Petersburg, 199034, Russian Federation; Troitskiy I.S., Saint Petersburg State University, 7/9 Universitetskaya nab., St. Petersburg, 199034, Russian Federation; Tsai A., Institute of Astronomy, National Central University, Taoyuan, 32001, Taiwan; Vasilyev A.A., Saint Petersburg State University, 7/9 Universitetskaya nab., St. Petersburg, 199034, Russian Federation; Vince O., Astronomical Observatory, Volgina 7, Belgrade, 11060, Serbia; Vrontaki K., Section of Astrophysics, Astronomy and Mechanics, Department of Physics, National and Kapodistrian University of Athens, Zografos, Athens, GR-15784, Greece; Wani K., Aryabhatta Research Institute of Observational Sciences (ARIES), Manora Peak, Nainital, 263001, India; Watts D., Department of Physics and Astronomy, N283 Esc, Brigham Young University, Provo, 84602, UT, United States; Zhovtan A.V., Crimean Astrophysical Observatory Ras, P/O, 298409, Russian Federation