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Extrinsic electronic states to tune the luminescence and bonding nature of Cs2NaInCl6 double perovskite
Halide double perovskites have been extensively investigated in recent years as more stable and environmentally friendly materials with significant optoelectronic properties. Herein, we introduce Mn2+ ions in the Cs2NaInCl6 lattice to impart new electronic pathways to the otherwise weak optically active double perovskite for tuning its luminescent behaviour. X-ray diffraction, Raman, UVvisible, Photoluminescence (PL), and timeresolved PL (TRPL) spectroscopy are used to investigate the effect of Mn 2+ feed ratio on structural, vibrational, and optical properties. The chemical environment and surface morphology of the Mn2+ ions doped Cs2NaInCl6 double perovskite were investigated using X-ray photoelectron (XPS), energy dispersive X-ray (EDS) spectroscopies, and scanning electron microscopy. Results of the Rietveld refinement and Raman spectra divulge a decrease in In-Cl and Na-Cl bond length upon Mn2+ incorporation. The microstructure of the Cs2NaInCl6 double perovskite system was also studied using HRTEM analysis. UVvisible studies demonstrated a tremendous increase in absorption and a slight increase in band gap upon Mn2+ doping. PL and TRPL measurements of Mn2+: Cs2NaInCl6 discloses its red luminescence at 614 nm corresponding to the d-d atomic transition of Mn2+ with a long lifetime of 2.1 ms. Electron density investigations using maximum entropy method (MEM) demonstrate clear evolution of In-Cl and Na-Cl bonds from a highly ionic nature in pure Cs2NaInCl6 to strong covalent nature in Mn2+: Cs2NaInCl6 double perovskites. This affirms the simultaneous replacement of In, Na ions by Mn2+ to maintain charge neutrality in the compound and tune the electronic states of the Cs2NaInCl6 system. 2023 Elsevier B.V. -
Extricating the Association Between the Prognostic Factors of Colorectal Cancer
Purpose: Colorectal cancer (CRC) is one of the recurring and lethal gastrointestinal tract disease rankings as the primary cause of worldwide morbidity and mortality. In general, the tumour node metastasis (TNM) and Dukes classification assist in diagnosis, prognosis and treatments of CRC along with haematological examinations and tumour demographic characterisations in patients. Methods: The present investigation is carried out on clinically acknowledged sixty-five CRC patients based on haematological findings and are sorted into stages using TNM and Dukes. The present study is to find the association between haematological findings, demographic characters, differentiation position, lymph node invasion and tumour node metastasis in CRC patients in accordance with their age. Results: We observed significant (p < 0.05) nexus between lymph node metastasis and tumour node metastasis on the basis of tumours differentiation demographic positioning and age of the individuals. Conclusion: Earlier location tracing and medicinal treatment or surgery lessen the chance of CRC morbidity and mortality along with prolonging survival rate via prognostic factors and disease position determination. 2020, Springer Science+Business Media, LLC, part of Springer Nature. -
Extreme photometric and polarimetric variability of blazar S4 0954+65 at its maximum optical and ?-ray brightness levels
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. -
Extremal Trees oftheReformulated andtheEntire Zagreb Indices
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. -
Extremal reformulated forgotten index of trees, unicyclic and bicyclic 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. -
Extractive Text Summarization Using Sentence Ranking
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. -
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
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. -
Extraction of Web News from Web Pages Using a Ternary Tree Approach
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. -
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. -
Extraction of Graphene Nanostructures from Colocasia esculenta and Nelumbo nucifera Leaves and Surface Functionalization with Tin Oxide: Evaluation of Their Antibacterial Properties
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 -
Extraction of Fungal Chitosan by Leveraging Pineapple Peel Substrate for Sustainable Biopolymer Production
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. -
Extraction of features from video files using different image algebraic point operations
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. -
Extraction and characterization of wrinkled graphene nanolayers from commercial graphite
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. -
Extraction and characterization of preformed mixed phase graphene sheets from graphitized sub-bituminous coal
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. -
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. -
Extraction and characterization of biofuel from industrial waste organic pupae-silkworm
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. -
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). -
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 -
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). -
Extended virtual reality based memory enhancement model for autistic children using linear regression
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.