Adsorptive capacity of PANI/Bi2O3 composite through isotherm and kinetics studies on alizarin red
subject: Adsorption; Adsorption isotherm; Adsorption kinetics; Alizarin red; PANI/Bi2O3
description: Adsorption offers numerous advantages for eliminating organic pollutants such as dyes, making it a valuable method for water treatment. Polyaniline/Bi2O3 (PANI/Bi2O3) nanocomposite is synthesized from aniline by the chemical oxidative polymerization method. The sample shows a high positive surface charge density as seen from zeta potential analysis. X-ray Diffraction analysis, FTIR analysis, UVvis spectroscopy technique, thermogravimetric analysis, BET N2 Adsorption-desorption analysis, DLS, and zeta potential analysis are the tools employed to characterize the PANI/Bi2O3 nanocomposite. The impact of PANI/Bi2O3 on the outcome of adsorption is confirmed by comparing the composite with pristine Bi2O3 and PANI. The effect of various factors like time, temperature, initial dye concentration, and varying pH on the adsorption efficiency is studied. A maximum adsorption efficiency of 95 % is observed when 100 mg of PANI/Bi2O3 nanocomposite is utilized for a duration of 100 min. The adsorption efficiency increases at higher temperatures, and a maximum adsorption efficiency is observed at a pH of 11.4. The adsorption isotherms proposed by Freundlich and Langmuir are examined to confirm the adsorption mechanism, which entails the creation of a single layer of dye molecules on the adsorbent's surface. Analysis of kinetic parameters indicates that the reaction follows pseudo-second-order adsorption kinetics. The composite produced demonstrates effectiveness as an adsorbent for removing harmful organic pollutants from water sources. 2024 Elsevier B.V.
creator: Joseph G.; Kalathiparambil Rajendra Pai S.D.; Varghese A.; Pinheiro D.; Mohan M.K.; Chundattu S.J.
source: Journal of Molecular Structure, Vol-1308
publisher: Elsevier B.V.
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 222860; CODEN: JMOSB
format: Online
language: English
type: Article
coverage: Joseph G., Department of Chemistry, CHRIST (Deemed to be University), Karnataka, Bengaluru, 560029, India; Kalathiparambil Rajendra Pai S.D., Department of Chemistry, CHRIST (Deemed to be University), Karnataka, Bengaluru, 560029, India; Varghese A., Department of Chemistry, CHRIST (Deemed to be University), Karnataka, Bengaluru, 560029, India; Pinheiro D., Department of Chemistry, CHRIST (Deemed to be University), Karnataka, Bengaluru, 560029, India; Mohan M.K., Department of Sciences and Humanities, School of Engineering and Technology, CHRIST (Deemed to be University), Mysore Road, Kumbalagodu, Bangalore, 560074, India; Chundattu S.J., Department of Sciences and Humanities, School of Engineering and Technology, CHRIST (Deemed to be University), Mysore Road, Kumbalagodu, Bangalore, 560074, India

Photophysical and In Vitro-In Silico Studies on Newly Synthesized Ethyl 3-((3-Methyl-1-phenyl-1H-pyrazol-5-yl)oxy)-2-methyleneheptanoate
subject: HOMOLUMO; in vitro and in silico biological activity; MESP; NBO; pyrazolones
description: Abstract: In the present work, the aryl-substituted pyrazolone derivative ethyl 3-((3-methyl-1-phenyl-1H-pyrazol-5-yl)oxy)-2-methyleneheptanoate (ETT) has been synthesized by the reaction of Baylis-Hillman acetate with pyrazolones and screened for their in vitro antifungal, antibacterial, and antioxidant properties. The molecule shows good in vitro antifungal and antibacterial activities due to the presence of pentane, which enhances the absorption rate by its increased lipid solubility and improves the pharmacological activity. It is also evident from the results obtained from structure-activity relationship (SAR) studies. In silico studies were conducted on the synthesized molecule, examining its interactions with DNA Gyrase, Lanosterol14 alpha demethylase, and KEAP1-NRF2 proteins. The results revealed strong binding interactions at specific sites. Further, the photophysical properties of synthesized compounds were theoretically estimated using the ab-intio technique. The ground state optimization, dipole moment, and HOMOLUMO energy levels are calculated using the DFT-B3LYP-6-31G(d) basis set. Using the theoretically estimated HOMOLUMO value, global chemical reactivity descriptor parameters are estimated, and the result shows the synthesised molecule has a highly electronegative and electrophilic index. NBO analysis proved the presence of intermolecular ON.H hydrogen bonds caused by the interaction of the lone pair of oxygen with the anti-bonding orbital. The results suggest that pentane-substituted pyrazolone derivatives show good photophysical and biological applications. Pleiades Publishing, Ltd. 2024.
creator: Marrakkur V.; Sukanya G.; Al-Asbahi B.A.; Al-Hada N.M.; Kapavarapu R.; Naik L.
source: Russian Journal of Organic Chemistry, Vol-60, No. 7, pp. 1176-1185.
publisher: Pleiades Publishing
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 10704280; CODEN: RJOCE
format: Online
language: English
type: Article
coverage: Marrakkur V., Department of Chemistry, NMKRV College for Women, Bengaluru, 560063, India; Sukanya G., Department of Physics and Electronics, CHRIST (Deemed to be University), Bengaluru, 560029, India; Al-Asbahi B.A., Department of Physics and Astronomy, College of Science, King Saud University, P.O. Box 2455, Riyadh, 11451, Saudi Arabia; Al-Hada N.M., Shandong Key Laboratory of Biophysics, Institute of Biophysics, Dezhou University, Dezhou, 253023, China; Kapavarapu R., Department of Pharmaceutical Chemistry and Phytochemistry, Nirmala College of Pharmacy, Atmakur, Mangalagiri Mandalm Andhra Pradesh, 522503, India; Naik L., Department of Physics and Electronics, CHRIST (Deemed to be University), Bengaluru, 560029, India

Predicting energy source diversification in emerging Asia: The role of global supply chain pressure
subject: Developing Asian countries; Energy diversification; Global supply chain pressure; Globalisation; Innovation; Total investment
description: This study investigates energy diversification trends in six Emerging Asian countries from 1998 to 2021 while exploring the predicting effects of the global supply chain pressure, total investment, innovation, economic growth, and globalisation on energy diversification. This study considers the Kernel-Based Regularized Least Squares (KRLS) estimations and prediction models (Adam and Stochastic Gradient Descent optimisers). The impacts of global supply chain pressure and total investment on energy diversification are positive. Innovation also emerges as crucial factor to enhance energy diversification. Deeper integration into the global economy (globalisation) and economic growth strengthen energy diversification. The study underscores the importance of tailored policies, advocating for investments in innovation, targeted total investment, and inclusive growth strategies to address energy diversification in emerging Asian countries. 2024 Elsevier B.V.
creator: Sun Y.; Pal S.; Mahalik M.K.; Gozgor G.; Lau C.K.M.
source: Energy Economics, Vol-136
publisher: Elsevier B.V.
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 1409883; CODEN: EECOD
format: Online
language: English
type: Article
coverage: Sun Y., School of Economics, Tianjin University of Commerce, Tianjin, China; Pal S., School of Business and Management, Christ University (Deemed to be University), Karnataka, Bengaluru, India, Department of Humanities and Social Sciences, Indian Institute of Technology Kharagpur, West Bengal, West Medinapur, 721302, India; Mahalik M.K., Department of Humanities and Social Sciences, Indian Institute of Technology Kharagpur, West Bengal, West Medinapur, 721302, India; Gozgor G., School of Management, University of Bradford, Bradford, United Kingdom; Lau C.K.M., Teesside University, International Business School, Middlesbrough, United Kingdom

Acute Leukemia Subtype Recognition in Blood Smear Images with Machine Learning
subject: Acute Leukemia; cell analysis; Image processing; Leukemia Classification; Segmentation
description: Acute leukemia is a swiftly progressing blood cancer affecting white blood cells which poses a significant threat to the immune system and often leads to fatal outcomes if not detected and treated promptly. The current manual diagnostic method, being time-consuming and prone to errors, necessitates an urgent shift toward a comprehensive automated system. This paper presents an innovative approach to automatically identify acute leukemia cells and their subtypes by analyzing microscopic blood smear images. The proposed methodology involves the segmentation of clustered lymphocytes, isolation of nuclei, and extraction of diverse features from each nucleus. A random forest classifier is then trained to categorize nuclei into healthy or cancerous, with further precision in classifying cancerous nuclei into specific subtypes. The method achieves an impressive 97% accuracy across all evaluations, holding profound implications for pathologists and medical practitioners in their decision-making processes. 2024, J.J. Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology. All rights reserved.
creator: Patil A.P.; Hiremath M.
source: International Journal of Electrical and Computer Engineering Systems, Vol-15, No. 7, pp. 563-570.
publisher: J.J. Strossmayer University of Osijek , Faculty of Electrical Engineering, Computer Science and Information Technology
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 18476996
format: Online
language: English
type: Article
coverage: Patil A.P., Department of Computer Science, CHRIST (Deemed to be University), Bengaluru, India; Hiremath M., Department of Computer Science, CHRIST (Deemed to be University), Bengaluru, India

Facile construction of gefitinib-loaded zeolitic imidazolate framework nanocomposites for the treatment of different lung cancer cells
subject: apoptosis; gefitinib; lung cancer; nanocomposites; zeolitic imidazolate framework
description: Gefitinib (GET) is a revolutionary targeted treatment inhibiting the epidermal growth factor receptor's tyrosine kinase action by competitively inhibiting the ATP binding site. In preclinical trials, several lung cancer cell lines and xenografts have demonstrated potential activity with GET. Response rates neared 25% in preclinical trials for non-small cell lung cancer. Here, we describe the one-pot synthesis of GET@ZIF-8 nanocomposites (NCs) in pure water, encapsulating zeolitic imidazolate framework 8 (ZIF-8). This method developed NCs with consistent morphology and a loading efficiency of 9%, resulting in a loading capacity of 20wt%. Cell proliferation assay assessed the anticancer effect of GET@ZIF-8 NCs on A549 and H1299 cells. The different biochemical staining (Calcein-AM and PI and 4?,6-Diamidino-2-phenylindole nuclear staining) assays assessed the cell death and morphological examination. Additionally, the mode of apoptosis was evaluated by mitochondrial membrane potential (??m) and reactive oxygen species. Therefore, the study concludes that GET@ZIF-8 NCs are pledged to treat lung cancer cells. 2024 International Union of Biochemistry and Molecular Biology, Inc.
creator: Aiyasamy K.; Ramasamy M.; Hirad A.H.; Arulselvan P.; Jaganathan R.; Suriyaprakash J.; Thangavelu I.; Alarfaj A.A.
source: Biotechnology and Applied Biochemistry, Vol-71, No. 4, pp. 896-908.
publisher: John Wiley and Sons Inc
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 8854513; PubMed ID: 38594878; CODEN: BABIE
format: Online
language: English
type: Article
coverage: Aiyasamy K., Department of Biochemistry, Vivekanandha College of Arts and Sciences for Women (Autonomous), Tiruchengode, Tamil Nadu, Namakkal, India; Ramasamy M., Department of Biochemistry, Vivekanandha College of Arts and Sciences for Women (Autonomous), Tiruchengode, Tamil Nadu, Namakkal, India; Hirad A.H., Department of Botany and Microbiology, College of Science, King Saud University, Riyadh, Saudi Arabia; Arulselvan P., Department of Chemistry, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences (SIMATS), Saveetha University, Tamil Nadu, Chennai, India; Jaganathan R., Preclinical Department, Faculty of Medicine, Universiti Kuala Lumpur, Royal College of Medicine Perak (UniKL-RCMP), Perak, Malaysia; Suriyaprakash J., Guangdong Provincial Key Laboratory of Nanophotonic Functional Materials and Devices, School of Information and Optoelectronic Science and Engineering, South China Normal University, Guangzhou, China; Thangavelu I., Department of Chemistry, CHRIST (Deemed to be University), Bangalore, India; Alarfaj A.A., Department of Botany and Microbiology, College of Science, King Saud University, Riyadh, Saudi Arabia

Bifunctional Amorphous Transition-Metal Phospho-Boride Electrocatalysts for Selective Alkaline Seawater Splitting at a Current Density of 2Acm?2
subject: hydrogen evolution reaction; non-noble catalysts; overall water-splitting; oxygen evolution reaction; Seawater electrolysis; transition-metal phospho borides
description: Hydrogen production by direct seawater electrolysis is an alternative technology to conventional freshwater electrolysis, mainly owing to the vast abundance of seawater reserves on earth. However, the lack of robust, active, and selective electrocatalysts that can withstand the harsh and corrosive saline conditions of seawater greatly hinders its industrial viability. Herein, a series of amorphous transition-metal phospho-borides, namely Co-P-B, Ni-P-B, and Fe-P-B are prepared by simple chemical reduction method and screened for overall alkaline seawater electrolysis. Co-P-B is found to be the best of the lot, requiring low overpotentials of ?270mV for hydrogen evolution reaction (HER), ?410mV for oxygen evolution reaction (OER), and an overall voltage of 2.50V to reach a current density of 2Acm?2 in highly alkaline natural seawater. Furthermore, the optimized electrocatalyst shows formidable stability after 10,000 cycles and 30h of chronoamperometric measurements in alkaline natural seawater without any chlorine evolution, even at higher current densities. A detailed understanding of not only HER and OER but also chlorine evolution reaction (ClER) on the Co-P-B surface is obtained by computational analysis, which also sheds light on the selectivity and stability of the catalyst at high current densities. 2024 The Authors. Small Methods published by Wiley-VCH GmbH.
creator: Silviya R.; Bhide A.; Gupta S.; Bhabal R.; Mali K.H.; Bhagat B.R.; Spreitzer M.; Dashora A.; Patel N.; Fernandes R.
source: Small Methods, Vol-8, No. 8
publisher: John Wiley and Sons Inc
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 23669608; PubMed ID: 38282459
format: Online
language: English
type: Article
coverage: Silviya R., Department of Physics and Electronics, Christ University, Bengaluru, 560029, India; Bhide A., Department of Physics and Electronics, Christ University, Bengaluru, 560029, India; Gupta S., Advanced Materials Department, Joef Stefan Institute, Jamova 39, Ljubljana, 1000, Slovenia; Bhabal R., Department of Physics and Electronics, Christ University, Bengaluru, 560029, India; Mali K.H., Department of Physics, Faculty of Science, The Maharaja Sayajirao University of Baroda, Vadodara, 390002, India; Bhagat B.R., Department of Physics, Faculty of Science, The Maharaja Sayajirao University of Baroda, Vadodara, 390002, India; Spreitzer M., Advanced Materials Department, Joef Stefan Institute, Jamova 39, Ljubljana, 1000, Slovenia; Dashora A., Department of Physics, Faculty of Science, The Maharaja Sayajirao University of Baroda, Vadodara, 390002, India; Patel N., Department of Physics and Electronics, Christ University, Bengaluru, 560029, India; Fernandes R., Department of Physics and Electronics, Christ University, Bengaluru, 560029, India

Towards sustainable resource management: A short and long-run dynamics of mineral production on ecological footprint
subject: DYNARDL; Ecological footprint; Mineral production; Pakistan
description: The effect of mineral production on ecological footprint is examined in this study while controlling for economic growth, renewable energy consumption, and trade openness as additional determinants for Pakistan. On the empirical front, the study uses the Dynamic Autoregressive Distributed Lag (DYNARDL) simulations for the data collected between 1990 and 2021. The result portrays movement to the long-run equilibrium relationship when considering the ecological footprint as the outcome variable amidst mineral production, economic growth, renewable energy consumption, and trade openness as the covariates. Further, the finding shows temporal dynamics of mineral production on environmental quality with a short-term degradation versus long-term amelioration, which suggests that mineral production can be conducted more sustainably over time with an implication towards taking measures such as technological advancements, improved efficiency, and better waste management practices. Additionally, it failed to find evidence for the conventional Environmental Kuznets Curve, implying a need for policy reevaluation, reassessment of economic development models and accounting for environmental externalities in economic decision-making. Besides, as expected, the outcome demonstrates that using renewable energy lowers the ecological footprint both in long and short terms, which indicates that utilization of renewable energy sources reduces reliance on fossil fuels, resulting in decreased environmental degradation, thereby fostering the need for emphasis on the importance of continued technological innovation in renewable energy technologies to reduce the ecological footprint further. Moreover, it shows that trade openness improves the environmental quality in the short run (worsens it in the long run), thereby highlighting that trade openness may lead to short-term environmental benefits by promoting cleaner technologies and increasing resource efficiency. However, in the long term, tr…
creator: Villanthenkodath M.A.; Pal S.
source: Journal of Environmental Management, Vol-364
publisher: Academic Press
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 3014797; PubMed ID: 38870795; CODEN: JEVMA
format: Online
language: English
type: Article
coverage: Villanthenkodath M.A., Department of Economics and Business Environment, Indian Institute of Management Bodh Gaya (IIM Bodh Gaya), Bodh Gaya, Bihar, 824231, India; Pal S., School of Business and Management, Christ University (Deemed to be University), Karnataka, Bengaluru, 560029, India

SIDNet: A SQL Injection Detection Network for Enhancing Cybersecurity
subject: CNN; cyber security; SIDNet; SQLI
description: SQL (Structured Query Language) injection is one of the most prevalent and dangerous forms of cyber-attacks, posing significant threats to database management systems and the overall security of web applications. By exploiting vulnerabilities in web applications, attackers can execute malicious SQL statements, potentially compromising the integrity and confidentiality of critical data. To combat these threats, in this study, we introduce two novel CNN models, SIDNet-1 (SQL Injection-attack Detection Network-1) and SIDNet-2 (SQL Injection-attack Detection Network-2), specifically designed for the classification of SQL injection attacks to bolster web application security. Our comprehensive evaluation includes a comparison of the performance of these customized CNN models against traditional machine learning approaches, highlighting improvements in classification accuracy and reductions in false alarm rates. The proposed models have been experimented with two publicly available dataset SQLI (SQL-Injection) and SQLV2 (SQL-Injection version2). Specifically, SIDNet-1 achieves an impressive accuracy of 98.02% on the SQLI dataset, while SIDNet-2 closely follows with 97.54%. Furthermore, on the SQLIV2 dataset, SIDNet-1 attains 97.77%, and SIDNet-2 achieves 97.83% accuracy respectively. 2013 IEEE.
creator: Muduli D.; Shookdeb S.; Zamani A.T.; Saxena S.; Kanade A.S.; Parveen N.; Shameem M.
source: IEEE Access, Vol-12, pp. 176511-176526.
publisher: Institute of Electrical and Electronics Engineers Inc.
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 21693536
format: Online
language: English
type: Article
coverage: Muduli D., C. V. Raman Global University, Department of Computer Science and Engineering, Odisha, Bhubaneswar, 752054, India; Shookdeb S., C. V. Raman Global University, Department of Computer Science and Engineering, Odisha, Bhubaneswar, 752054, India; Zamani A.T., Northern Border University, Department of Computer Science, Arar, 91431, Saudi Arabia; Saxena S., CHRIST University, Department of Computer Science, Bengaluru, India; Kanade A.S., Dr. Vishwanath Karad-MIT-World Peace University, Department of Computer Science and Applications, Pune, 411038, India; Parveen N., Koneru Lakshmaiah Education Foundation Deemed to Be University, Department of Computer Science and Engineering, Andhra Pradesh, Guntur, 522302, India; Shameem M., King Fahd University of Petroleum and Minerals, Interdisciplinary Research Center for Intelligent and Secure Systems, Dhahran, 31261, Saudi Arabia

An optimized method for mulberry silkworm, Bombyx mori (Bombycidae:Lepidoptera) sex classification using TLBPSGA-RFEXGBoost
subject: Accelerated HOG; Classification; RFEXGBoost; Seed production; Sericulture; TLBPSGA
description: Silkworm seed production is vital for silk farming, requiring precise breeding techniques to optimize yields. In silkworm seed production, precise sex classification is crucial for optimizing breeding and boosting silk yields. A non-destructive approach for sex classification addresses these challenges, offering an efficient alternative that enhances both yield and environmental responsibility. Southern India is a hub for mulberry silk and cocoon farming, with the high-yielding double-hybrid varieties FC1 (foundation cross 1) and FC2 (foundation cross 2) being popular. Traditional methods of silkworm pupae sex classification involve manual sorting by experts, necessitating the cutting of cocoons a practice with a high risk of damaging the cocoon and affecting yield. To address this issue, this study introduces an accelerated histogram of oriented gradients (HOG) feature extraction technique that is enhanced by block-level dimensionality reduction. This non-destructive method allows for efficient and accurate silkworm pupae classification. The modified HOG features are then fused with weight features and processed through a machine learning classification model that incorporates recursive feature elimination (RFE). Performance evaluation shows that an RFE-hybridized XGBoost model attained the highest classification accuracy, achieving 97.2% for FC1 and 97.1% for FC2. The model further optimized with a novel teaching learning-based population selection genetic algorithm (TLBPSGA) achieved a remarkable accuracy of 98.5% for FC1 and 98.2% for FC2. These findings have far-reaching implications for improving both the ecological sustainability and economic efficiency of silkworm seed production. 2024. Published by The Company of Biologists Ltd.
creator: Thomas S.; Thomas J.
source: Biology Open, Vol-13, No. 7
publisher: Company of Biologists Ltd
date: 2024-01-01
rights: All Open Access; Gold Open Access; Green Open Access
relation: ISSN: 20466390
format: Online
language: English
type: Article
coverage: Thomas S., Department of Computer Science and Engineering, Christ University, Bangalore, 560029, India; Thomas J., Department of Computer Science and Engineering, Christ University, Bangalore, 560029, India

White Light Emission from Dy3+-Activated CaY2O4 Phosphor
subject: CaY2O4:Dy3+ phosphor; CIE; FEGSEM; solid-state reaction; XRD
description: Synthesis and characterization of a Dy3+-activated calcium yttrium oxide (CaY2O4) phosphor are reported. The CaY2O4:Dy3+ (1.5 mol%) phosphor is synthesized using a modified solid-state reaction technique for calcination and sintering. The cubic structure is revealed by the X-ray diffraction technique. The morphology and particle size distribution of the prepared phosphor are investigated by the FEGSEM technique. The chemical bonds and functional group analysis are confirmed by the FTIR. A photoluminescence analysis of the CaY2O4:Dy3+ phosphor shows dual excitation wavelengths at 285 and 348 nm, especially in the ultraviolet region. At 383 nm, three distinct emission peaks are found at the wavelengths 238, 485, and 571 nm. The spectroscopic parameters are calculated using the CIE chromaticity coordinates. The CIE coordinates of the Dysprosium ion-activated CaY2O4 phosphor (1.5 mol%) show an emission near the white light region of the chromaticity diagram, suggesting that it is suitable for W-LED applications. The Author(s), under exclusive licence to Springer Nature Switzlerland AG 2024.
creator: Talukdar P.R.; Dubey V.; Saji J.; Rao M.C.
source: Russian Physics Journal, Vol-67, No. 7, pp. 1000-1005.
publisher: Springer
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 10648887
format: Online
language: English
type: Article
coverage: Talukdar P.R., Department of Physics, North-Eastern Hill University, Meghalaya, Shillong, 793022, India; Dubey V., Department of Physics, North-Eastern Hill University, Meghalaya, Shillong, 793022, India; Saji J., Department of Science and Humanities, School of Engineering and Technology, CHRIST, (Deemed to be University), Bangalore, India; Rao M.C., Department of Physics, Andhra Loyola College, Vijayawada, India

Prediction and modeling of mechanical properties of concrete modified with ceramic waste using artificial neural network and regression model
subject: ANN; Compressive strength; LR; Rejected ceramics; Splitting tensile strength
description: Over two centuries, concrete has been crucial to building. Thus, eco-friendly concrete is being developed. Emulating these tangible traits has recently gained popularity. Ceramic waste concretes mechanical properties were modeled in this study. Ceramic waste percentages ranged from 5 to 20%. Compressive and tensile concrete strengths were modeled. To predict concrete hardness, regression modeling and artificial neural network (ANN) were used. Model performance was evaluated using prediction coefficients and root-mean-square error (RMSE). ANN models outperformed linear prediction with a coefficient for determination (R2) of 0.97. ANN models achieved root-mean-square errors (RMSEs) of 1.22MPa, 1.21MPa, and 1.022MPa after 7, 14, and 28days of retraining, respectively. Linear regression model showed RMSE values of 1.21, 1.32, and 1.27MPa at 7, 14, and 28days, respectively. In determining the compressive and tensile strength, the R2 was 0.70, meanwhile the ANN model achieved 0.87. Given its accuracy in predicting the strength qualities of ceramics cement and structural stiffness, the ANN model presents a promising tool for representing various types of concrete. The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.
creator: Kshirsagar P.R.; Upreti K.; Kushwah V.S.; Hundekari S.; Jain D.; Pandey A.K.; Parashar J.
source: Signal, Image and Video Processing, Vol-18, No. Suppl 1, pp. 183-197.
publisher: Springer Science and Business Media Deutschland GmbH
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 18631703
format: Online
language: English
type: Article
coverage: Kshirsagar P.R., Department of Electronics & amp; Telecommunication Engineering, J D College of Engineering & amp; Management, Nagpur, India; Upreti K., Department of Computer Science, CHRIST (Deemed to Be University), Delhi-NCR, Uttar Pradesh, Ghaziabad, India; Kushwah V.S., School of Computing Science & amp; Engineering, VIT Bhopal University, Bhopal-Indore Highway, Madhya Pradesh, Bhopal, India; Hundekari S., MIT College of Management, MIT ADT University, Loni Kalbhor, Pune, India; Jain D., Department of Computer Science and Engineering, ABES Engineering College, Ghaziabad, India; Pandey A.K., Department of Computer Science and Engineering, ABES Engineering College, Ghaziabad, India; Parashar J., Department of Computer Science and Engineering, Dr. Akhilesh Das Gupta Institute of Engineering and Technology, New Delhi, India

Climate Change inflicted Environmental Degradation leading to the Crumbling of Arctic Ecosystem
subject: Arctic ecosystem; ecological disturbances; Permafrost meltdown; SDG; seismic activity
description: The Arctic and Antarctic regions serve as the air conditioners of planet Earth. The polar regions located thousands of miles away from us determine the climatic patterns of our geographical area. They maintain our planet at bearable temperatures which are ideal for the existence of diverse flora and fauna and to support different types of ecosystems all around the world. Apart from controlling the temperatures, they also regulate ocean currents which in turn have an effect on the monsoons, winds, hurricanes etc. The poles were pristine till a few decades back. Due to mans greed, the poles started deteriorating at an alarming scale. Climate change, biodiversity changes, oil drilling, seismic testing, toxin accumulation are a few of the challenges faced by the Arctic ecosystem having serious effects on its topography, terrestrial and marine life-forms and the whole ecosystem. Due to the alarming scale of global warming, there is also the danger of permafrost meltdown which can unleash a plethora of dangerous pathogens buried underneath and also let out the huge amounts of locked down carbon. The crumbling of the polar ecosystem is leading to rampant consequences not only in the poles but also elsewhere in the world thousands of miles away. Here, we attempt to discuss the repercussions of the crumbling Arctic ecosystem due to the physical, chemical and geological changes caused by such anthropogenic activities and look at the efforts being carried out to save the Arctic ecosystem in a frantic effort to save our planet. 2024, World Researchers Associations. All rights reserved.
creator: Suma S.; Saranya J.; Manas B.; Souvik M.
source: Disaster Advances, Vol-17, No. 7, pp. 36-47.
publisher: World Researchers Associations
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 0974262X | LS; 2023-2024; Vol-2; 668-677
format: Online
language: English
type: Article
coverage: Suma S., Department of Life Sciences, CHRIST (Deemed to be University), Karnataka, Bangalore, 560029, India; Saranya J., Department of Biotechnology, Mount Carmel College, Autonomous, Karnataka, Bangalore, 560052, India; Manas B., Department of Life Sciences, CHRIST (Deemed to be University), Karnataka, Bangalore, 560029, India; Souvik M., Department of Life Sciences, CHRIST (Deemed to be University), Karnataka, Bangalore, 560029, India

Coloring of Non-zero Component Graphs
subject: chromatic number; coloring; Non-zero component graph
description: The non-zero component graph of a finite dimensional vector space V over a finite field F is the graph G(V?) = (V, E), where vertices of G(V?) are the non-zero vectors in V, two of which are adjacent if they share at least one basis vector with non-zero coefficient in their basic representation. In this paper, we study the various types of colorings of non-zero component graph. (2024), (Universidad Catolica del Norte). All rights reserved.
creator: Mathew V.M.; Naduvath S.
source: Proyecciones, Vol-43, No. 4, pp. 883-898.
publisher: Universidad Catolica del Norte
date: 2024-01-01
rights: All Open Access; Gold Open Access
relation: ISSN: 7160917
format: Online
language: English
type: Article
coverage: Mathew V.M., CHRIST (Deemed to be University, India; Naduvath S., CHRIST (Deemed to be University, India

Concentration-dependent luminescence characterization of terbium-doped strontium aluminate nanophosphors
subject: CIE coordinates; fluorescence; microwave-assisted solid-state reaction; nanophosphors; strontium aluminate; terbium
description: The present investigation describes the synthesis of luminescent terbium-doped strontium aluminate nanoparticles emitting bright green light, which were synthesized through a solid-state reaction method assisted by microwave radiation. Various samples containing different concentrations of Tb were synthesized, and an analysis of their structural and morphological features was conducted using powder x-ray diffraction, Fourier transform infrared spectroscopy and field emission scanning electron microscopy. The band gaps of the samples were determined utilizing the KubelkaMunk method. The quenching mechanism observed was identified to be due to dipoledipole interaction using the Dexter theory. The optimized sample with a terbium concentration of 4at.% has a luminescence lifetime of 1.05 ms with 20.62% quantum efficiency. The results of this study indicate that the terbium-doped strontium aluminate fluorescent nanoparticles exhibit promising potential for a wide range of applications, including bioimaging, sensing and solid-state lighting. 2024 John Wiley & Sons Ltd.
creator: Thomas N.M.; Safeera T.A.B.; Vanchipurackal I.V.; Anila E.I.
source: Luminescence, Vol-39, No. 7
publisher: John Wiley and Sons Ltd
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 15227235; PubMed ID: 39030986; CODEN: LUMIF
format: Online
language: English
type: Article
coverage: Thomas N.M., Department of Physics, Morning Star Home Science College, Kerala, Angamaly, India, Optoelectronic and Nanomaterials' Research Lab, Department of Physics, Union Christian College, Kerala, Aluva, India, Center for Nano-Bio Polymer Science and Technology, Department of Physics, St. Thomas College, Kerala, Palai, India; Safeera T.A.B., Optoelectronic and Nanomaterials' Research Lab, Department of Physics, Union Christian College, Kerala, Aluva, India; Vanchipurackal I.V., Center for Nano-Bio Polymer Science and Technology, Department of Physics, St. Thomas College, Kerala, Palai, India, Research and PG Department of Physics, Kuriakose Elias College, Kerala, Mannanam, India; Anila E.I., Optoelectronic and Nanomaterials' Research Lab, Department of Physics, Union Christian College, Kerala, Aluva, India, Department of Physics and Electronics, Christ (Deemed to be University), Karnataka, Bangalore, India

Development of a fluorescent scaffold by utilizing quercetin template for selective detection of Hg2+: Experimental and theoretical studies along with live cell imaging
subject: Cell imaging; Cyclic voltammograms; DFT study; Fluorescence; Green gram; Quercetin
description: Quercetin is an important antioxidant with high bioactivity and it has been used as SARS-CoV-2 inhibitor significantly. Quercetin, one of the most abundant flavonoids in nature, has been in the spot of numerous experimental and theoretical studies in the past decade due to its great biological and medicinal importance. But there have been limited instances of employing quercetin and its derivatives as a fluorescent framework for specific detection of various cations and anions in the chemosensing field. Therefore, we have developed a novel chemosensor based on quercetin coupled benzyl ethers (QBE) for selective detection of Hg2+ with naked-eye colorimetric and turn-on fluorometric response. Initially QBE itself exhibited very weak fluorescence with low quantum yield (? = 0.009) due to operating photoinduced electron transfer (PET) and inhibition of excited state intramolecular proton transfer (ESIPT) as well as intramolecular charge transfer (ICT) within the molecule. But in presence of Hg2+, QBE showed a sharp increase in fluorescence intensity by 18-fold at wavelength 444 nm with high quantum yield (? = 0.159) for the chelation-enhanced fluorescence (CHEF) with coordination of Hg2+, which hampers PET within the molecule. The strong binding affinity of QBE towards Hg2+ has been proved by lower detection limit at 8.47 M and high binding constant value as 2 104 M?1. The binding mechanism has been verified by DFT study, Cyclic voltammograms and Jobs plot analysis. For the practical application, the binding selectivity of QBE with Hg2+ has been capitalized in physiological medium to detect intracellular Hg2+ levels in living plant tissue by using green gram seeds. Thus, employing QBE as a fluorescent chemosensor for the specific identification of Hg2+ will pave the way for a novel approach to simplifying the creation of various chemosensors based on quercetin backbone for the precise detection of various biologically significant analytes. 2024 Elsevier B.V.
creator: Vishnu S.; Maity S.; Maity A.C.; Kumar M.S.; Dolai M.; Nag A.; bylappa Y.; Dutta G.; Mukherjee B.; Kumar Das A.
source: Spectrochimica Acta - Part A: Molecular and Biomolecular Spectroscopy, Vol-315
publisher: Elsevier B.V.
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 13861425; PubMed ID: 38603957; CODEN: SAMCA
format: Online
language: English
type: Article
coverage: Vishnu S., Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Karnataka, Bangalore, 560029, India; Maity S., Sagardighi Kamada Kinkar Smriti Mahavidyalaya Sagardighi, West Bengal, Murshidabad, 742226, India; Maity A.C., Sagardighi Kamada Kinkar Smriti Mahavidyalaya Sagardighi, West Bengal, Murshidabad, 742226, India; Kumar M.S., Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Karnataka, Bangalore, 560029, India; Dolai M., Department of Chemistry, Prabhat Kumar College, Contai, W.B., Purba Medinipur, 721404, India; Nag A., Department of Life Science, CHRIST (Deemed to be University), Hosur Road, Karnataka, Bangalore, 560029, India; bylappa Y., Department of Life Science, CHRIST (Deemed to be University), Hosur Road, Karnataka, Bangalore, 560029, India; Dutta G., School of Medical Science and Technology (SMST), IIT Kharagpur, India; Mukherjee B., School of Medical Science and Technology (SMST), IIT Kharagpur, India; Kumar Das A., Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Karnataka, Bangalore, 560029, India

Integrating machine learning techniques for Air Quality Index forecasting and insights from pollutant-meteorological dynamics in sustainable urban environments
subject: Air quality; AQI; Insights into pollutant dynamics; Machine learning; Prediction model
description: Air pollution poses a significant environmental and health challenge in Delhi, India. This research focuses on predicting the Air Quality Index (AQI) for Delhi utilizing machine learning techniques. The research methodology encompasses comprehensive steps such as data collection, preprocessing, analysis, and modeling. Data comprising various pollutants and meteorological parameters were gathered from the Central Pollution Control Board (CPCB) spanning from January 1, 2016, to December 30, 2022. Missing values were imputed using the IterativeImputer method with RandomForestRegressor as the estimator. Data normalization and variance reduction were achieved through Box-Cox transformation. Spearman Rank Correlation analysis was employed to explore relationships between features and AQI. Initial evaluation of nine machine learning algorithms identified Random Forest and XGBoost as the top performers based on accuracy. These algorithms were further optimized using 5-fold cross-validation with RandomizedSearchCV. The results demonstrated the efficacy of both algorithms in AQI prediction. Notably, PM2.5 and CO concentrations emerged are most influential features, highlighting the potential for AQI improvement in Delhi through the reduction of these pollutants. This research distinguishes itself through a meticulous examination of the complex interconnections between pollutants and AQI, providing invaluable insights to inform targeted interventions and enduring policies geared towards improving air quality in Delhi. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.
creator: K K.; S.K A.; R D.; Ravindiran G.
source: Earth Science Informatics, Vol-17, No. 4, pp. 3733-3748.
publisher: Springer Science and Business Media Deutschland GmbH
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 18650473
format: Online
language: English
type: Article
coverage: K K., Department of Electrical and Electronics Engineering, GMR Institute of Technology, Andhra Pradesh, Rajam, 532127, India; S.K A., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Karnataka, Bangalore, India; R D., Department of Electrical and Electronics Engineering, Panimalar Engineering College, Chennai, 600123, India; Ravindiran G., Department of Civil Engineering, VNR Vignana Jyothi Institute of Engineering and Technology, Telangana, Hyderabad, 500090, India

Enhancement of the Electrochemical behaviour of Carbon Black via a defect induced approach
subject: Amorphous carbon; Carbon black; Defect ratio; Oxygen functional groups; Supercapacitors
description: In order to address the rising global concern of energy storage, carbon-based materials have established themselves due to their distinct features. Despite the demand for the fabrication of supercapacitors from natural, inexpensive carbonaceous materials is on the rise, the intrinsic disorders present in such materials hinder their performance, and hence, tuning these defects can aid in the improvement of their electrochemical performance. In this study, carbon black is introduced with defects in the form of oxygen functional groups via oxidation and thermal exfoliation and the impact on its electrochemical performance is studied. Careful tuning of the type of oxygen functional moieties at the basal plane of the carbon lattice is observed to be the contributing factor for the electrochemical behaviour. The distortion in the graphitic lattice caused by the epoxy and hydroxyl groups alters the specific surface area, porosity, and thermal stability, facilitating easier ion diffusion rates and enhanced faradaic reactions. The obtained specific capacitance of the thermally exfoliated carbon black is as high as 246.49 Fg?1 in a three-electrode system and 82.85 F/g in a two-electrode setup, owing to an energy density of 5.63 Whkg?1 and a power density of 189.75 Wkg?1. It has also exhibited excellent cyclic stability and capacitance retention up to 4000 cycles. The equivalent series resistance is found to decrease from 5.67 to 4.96 ? making the material conductive. As a result, the electrochemical properties of carbon black can be enhanced by tuning the oxygen functional groups, making it a promising supercapacitive material. Graphical Abstract: (Figure presented.). Qatar University and Springer Nature Switzerland AG 2024.
creator: Mathew E.E.; B M.
source: Emergent Materials, Vol-7, No. 4, pp. 1387-1400.
publisher: Springer Nature
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 25225731
format: Online
language: English
type: Article
coverage: Mathew E.E., Department of Physics & Electronics, Christ (Deemed to Be University), Bangalore, 560029, India; B M., Department of Physics & Electronics, Christ (Deemed to Be University), Bangalore, 560029, India

Quantum computational, solvation and in-silico biological studies of a potential anti-cancer thiophene derivative
subject: DFT; Effect of solvents; MEP; NBO; NLO
description: Heterocyclic molecules display a wide spectrum of properties that span both material and biological domains. Material properties stem from their interactions in the bulk, where a large number of molecules of the same type get together resulting in an enhancement of properties. However, biological properties emanate from the interaction of a single or a few molecules with a biologically functional macromolecule. Computational tools offer a particularly useful way of theoretically studying molecules to arrive at a conclusion regarding such properties, even though they may vary when experimentally evaluated. This study concerns itself with the theoretical investigation comprising density functional theory calculations, topological analyses and in-silico biological evaluation of a thiophene compound, i.e. the title compound. Density functional theory was used to compute properties of the title molecule and their variations in unsolvated and solvated phases using Gaussian 09. The molecule in solvent phases encompassing organic polar protic, organic polar aprotic and inorganic polar protic nature have been subjected to theoretical investigations. The suitability of the molecule for deployment as a modern optical material is examined with positive results. Topological characteristics of the molecule were evaluated using Multiwfn 3.8 to examine electron density distribution and the possible resulting covalent, non-covalent and weak interactions because of such distribution. The potency of the molecule towards brain cancer was evaluated by molecular docking with Auto Dock Tools against two brain cancer protein targets 6ETJ and 6YPE with a good docking score of ?6.63 and ?6.21 kcal mol?1 respectively and the resulting interactions visualized and its pharmacokinetic properties obtained using online tools. 2024 Elsevier B.V.
creator: Abhijith R.; Parakkal S.C.; Datta R.; Alharbi N.S.; Muthu S.
source: Journal of Molecular Liquids, Vol-405
publisher: Elsevier B.V.
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 1677322; CODEN: JMLID
format: Online
language: English
type: Article
coverage: Abhijith R., Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Bengaluru, 560029, India; Parakkal S.C., Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Bengaluru, 560029, India; Datta R., Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Bengaluru, 560029, India; Alharbi N.S., Department of Botany and Microbiology, College of Science, King Saud University, P.O. Box 2455, Riyadh, 11451, Saudi Arabia; Muthu S., Department of Physics, Arignar Anna Government Arts College, Tamil Nadu, Cheyyar, 604407, India

Neuropalliative Care Needs Checklist for Motor Neuron Disease and Parkinson's Disease: A Biopsychosocial Approach
subject: Checklist; Motor neuron disease; Neurodegenerative disorders; Palliative care needs; Parkinson's disease
description: Objectives: Neurodegenerative disorders necessitate comprehensive palliative care due to their progressive and irreversible nature. Limited studies have explored the comprehensive assessment needs of this population. This present study is designed to develop a checklist for evaluating the palliative care needs of individuals with motor neuron disease (MND) and Parkinson's disease (PD). Materials and Methods: The checklist was created through an extensive literature review and discussions with stakeholders in neuropalliative. Feedback from six field experts led to the finalisation of the checklist, which comprised 53 items addressing the unique biopsychosocial needs of MND and PD. Sixty patient-caregiver dyads receiving treatment in a tertiary referral care centre for neurology in south India completed the checklist. Results: People with MND had more identified needs with speech, swallowing, and communication, while people with PD reported needs in managing tremors, reduced movements, and subjective feelings of stiffness. People denying the severity of the illness was found to be a major psychosocial issue. The checklist addresses the dearth of specific tools for assessing palliative care needs in neurodegenerative disorders, particularly MND and PD. By incorporating disease-specific and generic items, the checklist offers a broad assessment of patients' multidimensional needs. Conclusion: This study contributes to the area of neuropalliative care by developing the neuropalliative care needs checklist (NPCNC) as a valuable tool for assessing the needs of individuals with neurodegenerative diseases. Future research should focus on refining and validating the NPCNC with larger and more diverse groups, applicability in different contexts, and investigating its sensitivity to changes over time. 2024 Published by Scientific Scholar on behalf of Indian Journal of Palliative Care.
creator: Zacharias L.; Thomas P.T.; Warrier M.G.; Yadav R.; Alladi S.; Nalini A.; Pal P.K.
source: Indian Journal of Palliative Care, Vol-30, No. 3, pp. 232-238.
publisher: Scientific Scholar
date: 2024-01-01
rights: All Open Access; Gold Open Access; Green Open Access
relation: ISSN: 9731075
format: Online
language: English
type: Article
coverage: Zacharias L., Faculty of Health Science Social Care and Education, Kingston University, London, United Kingdom; Thomas P.T., Department of Psychiatric Social Work, National Institute of Mental Health and Neurosciences, Karnataka, Bengaluru, India; Warrier M.G., Department of Psychology, Christ University, Karnataka, Bengaluru, India; Yadav R., Department of Neurology, National Institute of Mental Health and Neurosciences, Karnataka, Bengaluru, India; Alladi S., Department of Neurology, National Institute of Mental Health and Neurosciences, Karnataka, Bengaluru, India; Nalini A., Department of Neurology, National Institute of Mental Health and Neurosciences, Karnataka, Bengaluru, India; Pal P.K., Department of Neurology, National Institute of Mental Health and Neurosciences, Karnataka, Bengaluru, India

Performance Evaluation of Predicting IoT Malicious Nodes Using Machine Learning Classification Algorithms
subject: Classification Algorithms; Internet of Things (IoT); Machine Learning; Malicious Nodes; Network Security
description: The prediction of malicious nodes in Internet of Things (IoT) networks is crucial for enhancing network security. Malicious nodes can significantly impact network performance across various scenarios. Machine learning (ML) classification algorithms provide binary outcomes ("yes" or "no") to accurately identify these nodes. This study implements various classifier algorithms to address the problem of malicious node classification, using the SensorNetGuard dataset. The dataset, comprising 10,000 records with 21 features, was preprocessed and used to train multiple ML models, including Logistic Regression, Decision Tree, Naive Bayes, K-Nearest Neighbors (KNN), and Support Vector Machine (SVM). Performance evaluation of these models followed the ML workflow, utilizing Python libraries such as scikit-learn, Seaborn, Matplotlib, and Pandas. The results indicated that the Naive Bayes classifier outperformed others with an accuracy of 98.1%. This paper demonstrates the effectiveness of ML classifiers in detecting malicious nodes in IoT networks, providing a robust predictive model for real-time application. The SensorNetGuard dataset is available on the IEEE data port and Kaggle platform. 2024, Prof.Dr. ?skender AKKURT. All rights reserved.
creator: Poorana S.S.; Wilfred B.N.R.; Rajesh K.R.; Karthik S.
source: International Journal of Computational and Experimental Science and Engineering, Vol-10, No. 3, pp. 341-349.
publisher: Prof.Dr. ?skender AKKURT
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 21499144
format: Online
language: English
type: Article
coverage: Poorana S.S., Dr. N.G.P. Arts and Science College, Department of Computer Applications, Tamil Nadu, Coimbatore, 641048, India; Wilfred B.N.R., University of Tech. and Applied Sciences, College of Computing and Information Sciences, Ibri, Oman; Rajesh K.R., Christ University, Department of Computer Science, Karnataka, 560029, India; Karthik S., Kristu Jayanti College, Department of Computer Science (PG), Karnataka, 560077, India