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Low-cost bio-waste carbon nanocomposites for sustainable electrochemical devices: A systematic review
Innovative brains have always drawn inspiration from nature while creating new designs. Animals and plants offer a variety of structures that are stronger, have higher energy sorption capacities, and have lower densities. These structures can inspire the creation of new, functional designs. Scientists have created structures by drawing inspiration from biological structures seen in nature. These structures have been demonstrated to significantly outperform conventional structures for use in the environmental and energy sectors. Due to their simple synthesis, adaptability, excellent performance, and variety of uses, including in light-harvesting systems, batteries, catalysis, bio-fuels, water, and air purification, and environmental monitoring, bio-fabricated materials have demonstrated several advantages. However, sensitive fabrication tools that can create bio-inspired structures and scale up manufacturing from laboratory-scale synthesis are urgently needed. A quick rundown of recent developments in bionanomaterials for different electrochemical systems, particularly the extensively researched rechargeable batteries, sensors, and supercapacitors, provided a discussion of the design principles for bionanomaterials, synthesis, and strategies for low-cost bio-inspired nanomaterial synthesis and device integration. A quick overview of the future research priorities is then suggested, followed by a critical analysis of the current problems. This review is anticipated to provide some understanding of biowaste-nanocomposites for electrochemical applications by taking cues from nature. 2024 Elsevier Ltd -
Low temperature synthesis of MoO3 nanoparticles by hydrothermal method: Investigation on their structural and optical properties
Molybdenum trioxide nanoparticles have recently achieved notable attention in optoelectronic and biomedical applications by virtue of their excellent structural, optical, electrical, and catalytic characteristics. The work presented here demonstrates the synthesis of orthorhombic MoO3 through the facile hydrothermal method at low temperature. Structural and optical characterization of the prepared sample was examined. XRD studies and Raman spectroscopy were carried out to study the structural behavior of the sample. The XRD peaks were concordant with the standard peaks of MoO3, which corresponds to the orthorhombic structure of MoO3. Micro-strain effects were also verified by the W-H method using UDM, UDEDM, and USDM. Raman spectroscopic data ascertained the orthorhombic phase of MoO3. From Tauc plot, a wide bandgap value (4.9 eV) was evaluated. In photoluminescence spectroscopy, peaks are related to the transition among the sub-bands of Mo5+ defects. Being a wide bandgap oxide semiconductor, MoO3 is a promising and worthy material for luminescence applications. 2022 -
Low temperature performance evaluation of asphalt binders and mastics based on relaxation characteristics
Low temperature cracking is one of the main distresses of asphalt pavement in cold regions. Stress relaxation characteristics is critical for cracking resistance of asphalt materials, especially at low temperatures, but there are few studies on the relaxation characteristic of asphalt mastics. To evaluate the effects of relaxation characteristics of asphalt binders and mastics on its low temperature performance, beam bending relaxation test was carried out through dynamic thermomechanical analyzer at low temperatures. Relaxation rate and relaxation time were proposed to illustrate the relaxation characteristics of asphalt binders and mastics. Then, the low-temperature performance of asphalt binders and mastics was evaluated by bending beam rheometer (BBR), glass transition temperature (Tg), and single edge notch beam bending test. Finally, the correlation of relaxation characteristics with low-temperature properties was analyzed based on Pearsons correlation coefficient and Spearman rank correlation coefficient. The results show that the elasticity of asphalt mastics increases with incorporation of mineral fillers and thus the viscous deformation potential is reduced, which affects the stress relaxation capability. The low-temperature cracking performance of asphalt mastics is indeed compromised as compared with asphalt binders, and the asphalt mastics prepared with fly ash performs the worst since it presents a stronger hardening effect. Fracture energy is determined not to be suitable for evaluating the low-temperature performance of asphalt mastics since its results contradict the BBR and Tg tests. The maximum displacement at fracture can better characterize the brittleness of asphalt materials at low temperatures. The relaxation characteristic index has the strongest correlation with Tg of asphalt binders and mastics, followed by maximum displacement at fracture and comprehensive compliance parameter (Jc). The correlation coefficients are almost larger than 0.5, suggesting that relaxation time and relaxation rate can characterize the low-temperature properties of asphalt binders and mastics. 2022, RILEM. -
Low temparature synthesis of non-toxic monoclinic yttrium oxide quantum dots for display and biomedical applications /
Patent Number: 202141053609, Applicant: Soorya G Nath.
Monoclinic Y203 quantum dots were synthesized at low temperature using urea as the fuel. The sample preparation was done using simple laboratory hot air oven and the synthesis temperature was maintained at 90°C throughout the experiment. Prepared samples were characterized using x ray diffraction (XRD), Raman spectroscopy, high resolution transmission electron microscopy (HRTEM), UV- Vis absorption spectroscopy and photoluminescence (PL) Studies. -
Low cost lignite derived mesoporous nanocarbon for simultaneous electrochemical detection of heavy metal IONs cadmium and lead /
Patent Number: 202241042032, Applicant: Ashlin M Raj.The present invention provides a facile, scalable, and cost-effective method for preparing mesoporous nanocarbon extracted from low grade coal, lignite that possesses an excellent electrochemical activity. The synthesized nanostructure modified electrode is used for the rapid simultaneous quantitative detection of heavy metals ions cadmium and lead in a unique triple linear detection range over the concentration ranges from 2.08 to 129 nM. -
Low cost energy management for demand side integration
Numerous batteries are outfitted with a state ofcharge (SoC) demonstrating the relaxation about the charge. Building a beneficial BMS is to check while thinking about, to that amount regardless we work now not holds a reliable method in imitation of study condition state of-charge, the nearly imperative measurement concerning a battery. Perusing the relaxation about the vigour of a battery is more unpredictable than administering thin fuel as in automobiles. An electrochemical cell diminishes its greatness and the in-and-streaming coulombs are counted for SOC. The BMS together which offers commitment while charging yet releasing; that detaches the battery if the SOC is below certain percentage. Various laws like Peukerts Law for battery capacity have been employed to determine the discharge rate of the battery. Arduino Uno is used for the input parameters required for Peukerts Law and various other calculations for significant monitoring. To address the existing complicated BMS, a new approach has been provided using IoT platform and making the understanding of BMS in much similar perspective. 2018 IEEE. -
Low cost calibrated mechanical noisemaker for hearing screening of neonates in resource constrained settings
Background & objectives: There is a need to develop an affordable and reliable tool for hearing screening of neonates in resource constrained, medically underserved areas of developing nations. This study valuates a strategy of health worker based screening of neonates using a low cost mechanical calibrated noisemaker followed up with parental monitoring of age appropriate auditory milestones for detecting severe-profound hearing impairment in infants by 6 months of age. Methods: A trained health worker under the supervision of a qualified audiologist screened 425 neonates of whom 20 had confirmed severe-profound hearing impairment. Mechanical calibrated noisemakers of 50, 60, 70 and 80 dB (A) were used to elicit the behavioural responses. The parents of screened neonates were instructed to monitor the normal language and auditory milestones till 6 months of age. This strategy was validated against the reference standard consisting of a battery of tests - namely, auditory brain stem response (ABR), otoacoustic emissions (OAE) and behavioural assessment at 2 years of age. Bayesian prevalence weighted measures of screening were calculated. Results: The sensitivity and specificity was high with least false positive referrals for 70 and 80 dB (A) noisemakers. All the noisemakers had 100 per cent negative predictive value. 70 and 80 dB (A) noisemakers had high positive likelihood ratios of 19 and 34, respectively. The probability differences for pre- and post- test positive was 43 and 58 for 70 and 80 dB (A) noisemakers, respectively. Interpretation & conclusions: In a controlled setting, health workers with primary education can be trained to use a mechanical calibrated noisemaker made of locally available material to reliably screen for severe-profound hearing loss in neonates. The monitoring of auditory responses could be done by informed parents. Multi-centre field trials of this strategy need to be carried out to examine the feasibility of community health care workers using it in resource constrained settings of developing nations to implement an effective national neonatal hearing screening programme. -
Low cost ANN based MPPT for the mismatched PV modules
Due to manufacturing dispersal, the photovoltaic (PV) panels of similar rating and manufacturer have distinctive characteristics in practical. As the maximum power point tracking (MPPT) becomes essential to optimally utilize the solar PV panel, distributed maximum power point tracking (DMPPT) is considered in this paper to follow the MPP of each panel. As the common MPP value is used in the existing DMPPT method to control all the panels, it fails to consider the uniqueness of each panel. By considering the uniqueness of each panel, the ANN based MPPT is implemented in this paper. As the ANN is trained using the actual characteristics of each panel based on the operating current, voltage and temperature, it is able to track the actual MPP. Due to the solar irradiance free MPPT, the costly pyranometer is not required in the actual PV system for MPPT. It reduces the cost of the system and also provides the interruption free tracking due to its independent nature on Voc and Isc values. Also, because of the looping free behaviour of the proposed algorithm, it is capable of following the MPP at rapidly varying condition. The proposed technique and the verified outcomes are discussed here in detail. Published under licence by IOP Publishing Ltd. -
Lora-WAN Powered by Renewable Energy, and Its Operation with Siri / Google Assistant
LoRa WAN is a newly emerged game changing communication technology for sending small data packets of size 50 bytes or less, wirelessly over an area of up to 10 Km without the need of an internet connection. LoRa WAN has its own frequency band and the band is different for every country. This technology is now starring to boost WSN technology better than ever before. This paper aims to, power up a LoRa Enabled Device or a LoRa Gateway by using a reliable dual mode non-conventional energy resource for storage and utilization, find peak performances altering the data rate that can be achieved in a LoRa WAN Communication (using Indoor RAK Gateway), make use data compression techniques, data packet encoding/decoding, Coding Apple Shortcuts, setting up Siri and Google Assistant for voice control and future scope. 2020, Asian Research Association. All rights reserved. -
Looking at psychological well-being through the lens of identity among adolescent girls: An exploration
Purpose: This research endeavours to delve into the intricate dimensions of adolescent girls' psychological well-being and identity, aiming to shed light on their interplay and identify key predictors of psychological well-being. The study, conducted with a sample of adolescent girls, seeks to enrich our understanding of the multifaceted nature of their developmental experiences. Psychological well-being is attained by achieving a state of balance affected by both challenging and rewarding life events and a stable sense of identity. Approach: The present research is an ex-post facto research falling in the area of quantitative research design. Data has been collected on 348 adolescents, purposely recruited from different schools of Delhi NCR. The age range of the respondents was 15 to 17 years. Findings: The results reveal that psychological well-being is being predicted by identity processes among adolescent females. The different dimensions of identity processes are found to be explaining almost 19% variance in the regression model. Commitment has been found to have a ? value of 0.197 (t= 3.511; p<.01), in-depth exploration has a ?= 0.161 (t= 2.867; p<.01), and reconsideration of commitment has a ?= 0.314 (t= 6.294; p<.01). Value: By addressing the objectives of this research, valuable insights may be received by educators, mental health professionals, and policymakers to better support and enhance the well-being of adolescent girls through having a stable sense of identity. 2024 RESTORATIVE JUSTICE FOR ALL. -
Longitudinal study on noncommunicable diseases using machine learning
This longitudinal case study thoroughly explores the intricate connection between body mass index (BMI) and four key factors: physical health, psychological well-being, lifestyle choices, and the impact of diet on health. Through the analysis of longitudinal data, notable trends emerge, revealing an increase in risk factors for noncommunicable diseases (NCDs) and unhealthy behaviors over time. This highlights the combined impact of these interconnected factors on health outcomes and the risk of developing NCDs like heart disease, diabetes, and cancer. Leveraging machine learning, the study effectively identifies individuals at elevated risk for NCDs and dispels common health misconceptions, underscoring the significance of holistic wellness approaches. Serving as a beacon for the next generation, this study provides insights that contribute to shaping a healthier future. 2025 selection and editorial matter, Arun Kumar Rana, Vishnu Sharma, Sanjeev Kumar Rana, and Vijay Shanker Chaudhary; individual chapters, the contributors. All rights reserved. -
Long-term optical and infrared variability characteristics of Fermi blazars
We present long-term optical and near-infrared flux variability analysis of 37 blazars detected in the ?-ray band by the Fermi Gamma-Ray Space Telescope. Among them, 30 are flat spectrum radio quasars (FSRQs) and 7 are BL Lac objects (BL Lacs). The photometric data in the optical (BVR) and infrared (JK) bands were from the Small and Moderate Aperture Research Telescope System acquired between 2008-2018. From cross-correlation analysis of the light curves at different wavelengths, we did not find significant time delays between variations at different wavelengths, except for three sources, namely PKS 1144-379, PKS B1424-418, and 3C 273. For the blazars with both B- and J-band data, we found that in a majority of FSRQs and BL Lacs, the amplitude of variability (?m) in the J band is larger than that in B band, consistent with the dominance of the non-thermal jet over the thermal accretion disc component. Considering FSRQs and BL Lacs as a sample, there are indications of ?m to increase gradually towards longer wavelengths in both, however, found to be statistically significant only between B and J bands in FSRQs. In the B-J v/s J-colour magnitude diagram, we noticed complicated spectral variability patterns. Most of the objects showed a redder when brighter (RWB) behaviour. Few objects showed a bluer when brighter (BWB) trend, while in some objects both BWB and RWB behaviours were noticed. These results on flux and colour characteristics indicate that the jet emission of FSRQs and BL Lacs is indistinguishable. 2020 The Author(s) Published by Oxford University Press on behalf of the Royal Astronomical Society. -
Long-term Optical and ?-Ray Variability of the Blazar PKS 1222+216
The ?-ray emission from flat-spectrum radio quasars (FSRQs) is thought to be dominated by the inverse Compton scattering of the external sources of photon fields, e.g., accretion disk, broad-line region (BLR), and torus. FSRQs show strong optical emission lines and hence can be a useful probe of the variability in BLR output, which is the reprocessed disk emission. We study the connection between the optical continuum, H? line, and ?-ray emissions from the FSRQ PKS 1222+216, using long-term (?2011-2018) optical spectroscopic data from Steward Observatory and ?-ray observations from Fermi Large Area Telescope (LAT). We measured the continuum (F C,opt) and H? (F H? ) fluxes by performing a systematic analysis of the 6029-6452 optical spectra. We observed stronger variability in F C,opt than F H? , an inverse correlation between the H? equivalent width and F C,opt, and a redder-when-brighter trend. Using discrete cross-correlation analysis, we found a positive correlation (DCF ? 0.5) between the F ??ray>100 MeV and F C,opt (6024-6092 light curves with a time lag consistent with zero at the 2? level. We found no correlation between the F ??ray>100 MeV and F H? light curves, probably dismissing the disk contribution to the optical and ?-ray variability. The observed strong variability in the Fermi-LAT flux and F ??ray>100 MeV ? F C,opt correlation could be due to the changes in the particle acceleration at various epochs. We derived the optical-to-?-ray spectral energy distributions during the ?-ray flaring and quiescent epochs that show a dominant disk component with no variability. Our study suggests that the ?-ray emission zone is likely located at the edge of the BLR or in the radiation field of the torus. 2022. The Author(s). Published by the American Astronomical Society. -
Long Term X-Ray Spectral Variations of the Seyfert-1 Galaxy Mrk 279
We present the results from a long term X-ray analysis of Mrk 279 during the period 2018-2020. We use data from multiple missions - AstroSat, NuSTAR and XMM-Newton, for the purpose. The X-ray spectrum can be modeled as a double Comptonization along with the presence of neutral Fe K? line emission, at all epochs. We determined the sources X-ray flux and luminosity at these different epochs. We find significant variations in the sources flux state. We also investigate the variations in the sources spectral components during the observation period. We find that the photon index and hence the spectral shape follow the variations only over longer time periods. We probe the correlations between fluxes of different bands and their photon indices, and found no significant correlations between the parameters. 2024. National Astronomical Observatories, CAS and IOP Publishing Ltd. -
Long run relationship between macroeconomic indicators and Indian sectoral indices
Investors and fund managers continuously strive to find new ways to diversify their portfolio and minimise risk exposure. The study aims to find out whether the macroeconomic indicators exert the same influence on stock prices across the entire stock market or varies across different sectors. The impact of macroeconomic indicators would not be the same on all the sectors. This paper provides empirical evidence of macroeconomic indicators such as crude oil prices, interest rates, foreign currency rates, money supply and inflation rates having a varied impact on Nifty50 index and each of the select sectoral stock indices namely, Nifty Bank, Nifty IT and Nifty financial services. The sample period runs from Jan 2009 to Jan 2019. The study employs the Error Correction Mechanism to study whether the macroeconomic indicators have the same impact across sectoral stock indices in the long run. The findings show that variations in macroeconomic variables do not trigger the same response from all the sectoral stock indices. While most of the variables chosen have a significant influence on Nifty50 index and NiftyIT; Nifty financial services and Nifty Bank remain unaffected by changes in few major macroeconomic variables or show opposite reaction than the other sectors. The findings of the study have significant implications for long term investors and investment managers for building a diversified portfolio and thereby protecting themselves from financial losses during adverse market conditions. 2019, Institute of Advanced Scientific Research, Inc.. All rights reserved. -
Long memory investigation during demonetization in India
Long-range dependence (LRD) in financial markets remains a key factor in determining whether there is market memory, herding traces, or a bubble in the economy. Usually referred to as 'Long Memory', LRD has remained a key parameter even today since the mid-1970s. In November 2016, a sudden and drastic demonetization measure took place in the Indian market, aimed at curbing money laundering and terrorist funding. This study is an attempt to identify market behavior using long-range dependence during those few days in demonetization. Besides, it tries to identify nascent traces of bubble and embedded herding during that time. Auto Regressive Fractionally Integrated Moving Average (ARFIMA) is used for three consecutive days around the event. Tick-by-tick data from CNX Nifty High Frequency Trading (CNX Nifty HFT) is used for three consecutive days around demonetization (approximately, 5000 data points from morning trading sessions on each of the three days). The results show a clear and profound presence of herd behavior in all three data sets. The herd intensity remained similar, indicating a unique mixture of both 'Noah Effect' and 'Joseph Effect', proving a clear regime switch. However, the results on the event day show stable and prominent herding. Mandelbrot's specified effects were tested on an uncertain and sudden financial event in India and proved to function perfectly. Bikramaditya Ghosh, Saleema J. S., Aniruddha Oak, Manu K. S., Sangeetha R., 2020. -
Logistic growth and SIR modelling of coronavirus disease (COVID-19) outbreak in India: Models based on real-time data
The logistic growth model and the Susceptible-Infectious-Recovered (SIR) framework are utilized for the mathematical modelling of the Coronavirus disease (COVID-19) outbreak in India. Karnataka, Kerala and Maharashtra, three states of India, are selected based on the pattern of the disease spread and the prominence in being affected in India. The parameters of the models are estimated by utilizing real-time data. The models predict the ending of the pandemic in these states and estimate the number of people that would be affected under the prevailing conditions. The models classify the pandemic into five stages based on the nature of the infection growth rate. According to the estimates of the models it can be concluded that Kerala is in a stable situation whereas the pandemic is still growing in Karnataka and Maharashtra. The infection rate of Karnataka and Kerala are lesser than 5% and reveal a downward trend. On the other hand, the infection rate and the high predicted number of infectives in Maharashtra calls for more preventive measures to be imposed in Maharashtra to control the disease spread. The results of this analysis provide valuable information regarding the disease spread in India. 2020, International Information and Engineering Technology Association. -
Log-Base2 of Gaussian Kernel for Nuclei Segmentation from Colorectal Cancer H and E-Stained Histopathology Images
Nuclei Segmentation is a very essential and intermediate step for automatic cancer detection from H and E stained histopathology images. In the recent advent, the rise of Convolutional Neural Network (CNN), has enabled researchers to detect nuclei automatically from histopathology images with higher accuracy. However, the performance of automatic nuclei segmentation by CNN is fraught with overfitting, due to very less number of annotated segmented images available. Indeed, we find that the problem of nuclei segmentation is an unsupervised problem, because still now there is no automatic tool available which can make annotated images (nuclei segmented images) accurately, to the best of our knowledge. In this research article, we present a Logarithmic-Base2 of Gaussian (Log-Base2-G) Kernel which has the ability to track only the nuclei portions automatically from Colorectal Cancer H and E stained histopathology images. First, Log-Base2-G Kernel is applied to the input images. Thereafter, we apply an adaptive Canny Edge detector, in order to segment only the nuclei edges from H and E stained histopathology images. Experimental results revealed that our proposed method achieved higher accuracy and F1 score, without the help of any annotated data which is a significant improvement. We have used two different datasets (Con-SeP dataset, and Glass-contest dataset, both contains Colorectal Cancer histopathology images) to check the effectiveness and validity of our proposed method. These results have shown that our proposed method outperformed other image processing or unsupervised methods both qualitatively and quantitatively. 2023 SPIE. -
