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Psychological adjustment, choice of game genre and living arrangements among adolescents with and without IGD
In India, the prevalence of internet gaming disorders ranges from 8 to 9%. Adolescents are more likely to become addicted to online games. This study compares teenage gamers with and without Internet Gaming Disorder (IGD) in terms of game genre, psychosocial adjustment, and living conditions with a sample of 80 in each group. The results demonstrate that adolescents with this disorder had significantly higher scores for depression, anxiety, and psychosocial deterioration than adolescents without gaming disorder. Even though the prevalence of males is high, both genders do not significantly differ from one another in psychological adjustment. Another finding is that adolescents with gaming disorders play multiplayer online role-play games and Battle Royal games more frequently than average players. The prevalence of this disorder is also influenced by living conditions; teenagers who stay in hostels or pay guest rooms are more likely to develop a gaming addiction. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
Machine Learning and Deep Learning Analysis of Vehicle Carbon Footprint
Clearly climate change is one of the most significant hazards to mankind nowadays. And daily the situation has become worse. No other way characterises climate change except through changes in the patterns of temperature and weather. Human activity generates the primary greenhouse gas emissions. Among these activities are burning coal, oil, natural gas, as well as other fuels; agricultural techniques, industrial operations, deforestation, burning coal, oil. Mostly resulting from human activities, the average temperature of the planet has significantly increased by almost 1.1 degrees Celsius since the late 1800s. One theory holds that internal combustion engines affect roughly thirteen percent. The objective of this work is to do an analysis of a complicated dataset involving fuel consumption in urban and highway environments as well as mixed combinations since the relevance of these variables in modelling attempts dictates. Reduced CO2 emissions emissions and environmental impact follow from reduced fuel use. The project used numerous machine learning and deep learning approaches to comprehend data analysis. Moreover, this work investigates the dataset to acquire knowledge and concurrently solves problems such overfitting and outliers. Control of complexity is achieved using several methods like VIF, PCA, and Cross-Validation. Models combining CNN and RNN performed really well with an accuracy of 0.99. The R-squared metrics are utilized in order to do the evaluation of the model. Apart from linear regression, support vector machines, Elastic Net with a rewardable accuracy, random forest was applied. It has rather good 0.98 accuracy. We can therefore state that our model analyzed the data properly and generated accurate output since the results we obtained during the assessment phase exactly the same ones we obtained during the training stage. Mass data cleansing is required as well as further study to increase machine learning model accuracy and performance. 2024 The authors. -
Constraining the physical parameters of XTE J1701-462 through NuSTAR observations
The spectral properties of the transient neutron star low-mass X-ray binary XTE J1701-462 were studied using the data obtained from FPMA/B detectors onboard NuSTAR during its second known outburst (2022 September). The physical parameters of the system were derived from the analysis of the data in the 3.0-30.0 keV energy range. The patterns displayed on the hardness-intensity diagram of the three observations closely resembled the banana branch/normal branch, a vertex of horizontal and normal branch of the Z-track and a transition from normal branch to flaring branch. Spectral analysis of the source revealed the presence of Fe K emission complex. The source spectra were fitted with a multitemperature blackbody () component in conjunction with the reflection model (). The values of temperature (kTin) and radius (Rin) of the inner accretion disc obtained from the spectral fitting with the model combination - + showed the source to be in its soft spectral state during the observations. The inclination angle (?) of the source was estimated to be between 19 and 33 and the inner disc radius (Rin) was found to be 17.4 km. Assuming the case of magnetic truncation of accretion disc, the upper limits for the magnetic dipole moment (?) and the magnetic field strength (B) at the poles of the neutron star in the system were found to be 5.78 1026 G cm3 and 8.23 108 G, respectively, for kA = 1. 2024 The Author(s). Published by Oxford University Press on behalf of Royal Astronomical Society. -
Circular supply chains in manufacturingQuo vadis? Accomplishments, challenges and future opportunities
Circular approach in manufacturing supply chain (SC) operations yields multiple benefits through optimal utilisation and consumption of resources. This study maps the scope and structure of circularity in the manufacturing SC discipline and explores the evolution of the domain over time. We review 946 journal articles published between 2013 and September 2023. Our study identifies key drivers and barriers to circular economy (CE) deployment in manufacturing SC operations, bibliometric parameters, emerging research themes, decision support tools, theories and applications. Using the theory extension approach, we propose a strategic framework to fortify the deployment of circularity in SCs. This comprehensive study renders a methodological contribution through combined descriptive content analysis and bibliometric and network analyses to evaluate the circular manufacturing SC operations concepts, theories and applications. We posit that manufacturing firms require to deploy innovation-led approaches to embed the CE strategies in their SC operations. We find that the studies investigating green skill development and circularity-culture adoption can facilitate manufacturers to understand the efficacy of circularity in their SC operations. The findings of this study can facilitate the practitioners to identify the links between the CE approaches and their strategic implications and examine CE implementation at the strategic level. 2024 The Authors. Business Strategy and The Environment published by ERP Environment and John Wiley & Sons Ltd. -
A novel chemical route for low-temperature curing of natural rubber using 2,4 dihydroxybenzaldehyde: improved thermal and tensile properties
A novel method for chemically curing natural rubber (NR) using 2,4-dihydroxybenzaldehyde (DHB) at low temperatures has been discovered. Adding varying amounts of DHB to NR increases the crosslinking between the NR molecular chains. The chemical reaction between NR molecular chains and DHB was confirmed through Fourier transform infrared (FTIR) and proton nuclear magnetic resonance (NMR) spectra. From the thermogravimetric analysis (TGA), the thermal stability and activation energy of degradation were determined. The variation in glass transition temperature (Tg), as an indication of increased crosslink density, reducing the mobility of rubber chains, has been confirmed through differential scanning calorimetry (DSC). The addition of DHB to latex significantly enhanced the thermal stability of the rubber. An increase in the activation energy of 5.52% was observed upon the addition of 80mL DHB into NRL when compared to the uncured one. Furthermore, the tensile properties, in terms of tensile strength and modulus of elasticity of rubber, were drastically increased through DHB crosslinking. Tensile strength values of rubber were found to increase by reducing its elongation at break due to the formation of crosslinks between the macromolecular chains. NR cured with 80mL DHB exhibited superior tensile and thermal properties among the series of cured samples. By adding 80mL of DHB, the tensile strength increased by 390% and the elongation at break decreased by 10%. The advantage of this curing method is that, it is an effective technique for crosslinking NR directly from NR latex at comparatively low temperature. Graphical abstract: (Figure presented.) Iran Polymer and Petrochemical Institute 2024. -
A Bibliometric Analysis of Asset Allocation for Retirement
Allocation of investment assets is key in attaining a sustainable retirement portfolio. In this research article, the authors analyzed the most recent research publications in the area related to asset allocation for retirement and identified those which have the highest impact. The authors research was conducted using the bibliometric analysis technique of research articles collected from the Scopus database. Most of the research articles were published in reputed journals in the United States, United Kingdom, Australia, and Germany. It was also observed that most of the highly cited research articles in the research area of asset allocation for retirement are focused on financial literacy, increase in retirement age, aging, and pension reforms. The authors findings identified six research themes in asset allocation for retirement such as 1) asset allocation for retirement planning, 2) methods to increase efficiency, 3) investment preferences for retirement savings 4) financial literacy and retirement planning, 5) reforms on retirement savings, and 6) annuities for retirement income. Furthermore, nineteen future research directions are also provided. In conclusion, the authors aim to assist future researchers in identifying highly cited articles, key authors, contributing countries and research themes in asset allocation for retirement. Overall, the analysis provides comprehensive information in addressing research questions in the field of asset allocation for retirement. Copyright 2024 With Intelligence LLC. -
Predicting Stock Market Movements Through Multisource Data Fusion Graphs: An Approach Employing Graph Convolutional Neural Network
The stock market plays an important role in the capital market, and investigating price fluctuations in the stock market has consistently been a prominent subject for researchers. The application of soft computing techniques to predict and categorize stock market movements is a significant research challenge that has gathered considerable attention from researchers. Although several studies highlight the significance of incorporating information from two sources in stock movement prediction, the potential of advanced graphical techniques for modeling and analyzing multi-source data remains an unattended research area. This study aims to address this gap by introducing a novel model that utilizes multi-source data fusion graphs to predict future market movements. The primary challenge involves establishing a model that can effectively gather the relationships among various data sources and employ this understanding to improve prediction performance. Compared to several existing methods relying only on historical data or sentiment data, which show limited predictive power and lack generality, the proposed approach seeks to overcome these limitations. The proposed model integrates various information sources, including historical prices, news data, Twitter data, and technical indicators for predicting future stock market trends. This presented method involves constructing a subgraph map for each data type to capture events from both rising and falling markets. Then, a Gated Recurrent Unit (GRU) is employed to aggregate the subgraph nodes. These aggregated nodes are then integrated with a Graph Convolutional Neural Network (GCNN) to classify the multi-source graph, therefore achieving stock market trend prediction effectively. To further validate its effectiveness, the presented model is applied to Indian stock market data, demonstrating its feasibility in fusing multi-source stock data and establishing its suitability for effectively predicting stock market movements. 2024 Seventh Sense Research Group -
Electrochemical performance of ZnxCo3-xO4/N-doped rGO nanocomposites for energy storage application
In this study, nanocomposites consisting of zinc-doped cobalt oxides with a spinel structure and nitrogen-doped reduced graphene oxide (ZnxCo3-xO4 (x = 0 and 1))/N-doped rGO) were synthesized using a solvothermal method. The synthesized materials were investigated using XRD, TEM, EDS, BET, Raman, and XPS for their phase formation, morphology, elemental composition, surface area, and chemical states. XRD analysis revealed that the metal oxides (Co3O4 and ZnCo2O4) present in the composites exhibited a single-phase cubic spinel structure, with a nanocrystalline nature and crystallite size ranging from 8 nm to 20 nm. Raman and TEM analyses revealed the co-existence of metal oxide nanoparticles and N-doped rGO phases in the composites. Electrodes were fabricated using the synthesized nanocomposite materials and subjected to electrochemical testing, including CV, GCD and EIS. The specific capacitiance (Cs) of samples determined to be 181 F/g and 234 F/g for CO/NrGO (Co3O4/N-doped rGO) and ZCO/NrGO (ZnCo2O4/N-doped rGO) nanocomposites, respectively, at lower current density (0.5 A/g). At all current densities, the CS of ZCO/NrGO nanocomposite electrode is observed to be higher than the CO/NrGO nanocomposite, probably due to structural defects and uniform anchoring of ZnCo2O4 particles over the layers of NrGO. The ZCO/NrGO composite electrode exhibits ?86 % capacitance retention after 3000 cycles. 2024 Elsevier B.V. -
The development and validation of digital amnesia scale
The usage of digital devices has increased rapidly in recent times due to the expansion of online learning platforms, leading to greater reliance on them. As a result, people forget simple information, dates, and appointments that might lead to digital amnesia. Hence, we aimed to develop and validate a digital amnesia scale (DAS). The study was carried out in two studies. In the first study, we collected data from 616 college students to examine the factor structure of the model and its underlying dimensions for a large pool of items. These analyses showed that the scale formed a three-dimensional structure: digital distraction, digital dependency, and digital detox. In the second study, we collected data from 383 college students to confirm the three-factor structure of the DAS. A satisfactory level of reliability was demonstrated by McDonalds ? value for the dimensions. The testretest reliability was found to be 0.76. The DAS had satisfactory convergent and discriminant validity. This scale could be useful for both researchers and educators to assess digital amnesia among college students. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
Nondestructive and cost-effective silkworm, Bombyx mori (Lepidoptera: Bombycidae) cocoon sex classification using machine learning
Sericulture is the process of cultivating silkworm cocoons for the production of silks. The quality silk production requires quality seed production which in turn requires accurate classification of male and female pupa in grainage centers. The challenges in the current methods of silkworm cocoon sex classification using manual observation lie in the time-consuming nature of the process, potential human error, and difficulties in accurately discerning subtle morphological differences between male and female cocoons. FC1 and FC2 single hybrid variety breed pupa are commonly used in south India for the production of high yielding double hybrid bivoltine silkworm seeds. In this study, 1579 FC1 and 1669 FC2 variety samples were used for the classification process. To overcome the challenges of present physical observation by expert employees, camera images of FC1 and FC2 cocoons were used in this study for sex classification. The proposed model used Histogram Oriented Gradient (HOG) feature descriptor of cocoon samples. Linear Discriminant Analysis (LDA) was applied on the feature vector to reduce the dimension and this feature matrix was given to the classical machine learning algorithms support vector machine (SVM), k-nearest neighbors (kNN), and gaussian nae bayes for classification with stratified 10-fold cross validation. The results showed that for FC1 data HOG + LDA + Nae Bayes performed better with a mean accuracy of 95.3% and for FC2 data HOG + LDA + KNN attained a mean accuracy of 96.2%. Our results suggest that this camera imaging method can be used efficiently in the classification based on the cocoon size and shape of different breeds. African Association of Insect Scientists 2024. -
Nonlinear stability analysis of Rayleigh-Bard problem for a Navier-Stokes-Voigt fluid
The linear and nonlinear stability analyses of thermosolutal convection in a non-Newtonian Navier-Stokes-Voigt fluid, considering Soret and Ekman damping effects, are conducted analytically. Instability thresholds are determined for thermosolutal convection within a viscoelastic fluid of the Kelvin-Voigt type, wherein a dissolved salt field exists. Two scenarios are examined: one where the fluid layer is heated from the bottom and concurrently salted from the bottom, and the other where the fluid layer is heated from the bottom and concurrently salted from the top. The governing partial differential equations system includes conservation laws of mass, momentum, energy, and salt concentration. Using the energy method, the disturbances to the fluid system are shown to decay exponentially. Analytical expressions are developed for the eigenvalue as a function of Soret, Lewis, Prandtl, Kelvin-Voigt, and Rayleigh friction numbers. The study illustrates the shift from a stationary mode of convection to an oscillatory mode and provides thresholds that indicate these transitions. It is found that the viscoelastic property of the fluid acts as a stabilizing agent for oscillatory mode convection. Rayleigh friction substantially controls the convection threshold. Upon comparing threshold values between linear and nonlinear theories, a subcritical instability region is observed in the heating bottom-salting bottom case (case-1), whereas such a region is absent in the heating bottom-salting top case (case-2). 2024 Elsevier Ltd -
An Intrusion Detection Model Based on Hybridization of S-ROA in Deep Learning Model for MANET
A kind of wireless network called a mobile ad hoc network (MANET) can transfer data without the aid of any infrastructure. Due to its short battery life, limited bandwidth, reliance on intermediaries or other nodes, distributed architecture, and self-organisation, the MANET node is vulnerable to many security-related attacks. The Internet of Things (IoT), a more modern networking pattern that can be seen as a superset of the paradigms discussed above, has recently come into existence. It is extremely difficult to secure these networks due to their scattered design and the few resources they have. A key function of intrusion detection systems (IDS) is the identification of hostile actions that impair network performance. It is extremely important that an IDS be able to adapt to such difficulties. As a result, the research creates a deep learning-based feature extraction to increase the machine learning technique's classification accuracy. The suggested model uses outstanding network-constructed feature extraction (RNBFE), which pulls structures from a deep residual network's many convolutional layers. Additionally, RNBFE's numerous parameters cause a lot of configuration issues because they require manual parameter adjustment. Therefore, the integration of the Rider Optimization Algorithm (ROA) and the Spotted Hyena Optimizer (SHO) to frame the new algorithm, Spotted Hyena-based Rider Optimization (S-ROA), is used to adjust the RNBFEs settings. Attack classification is performed on the resulting feature vectors using fuzzy neural classifiers (FNC). The experimental analysis uses two datasets that are publicly accessible. The Author(s), under exclusive licence to Shiraz University 2024. -
Parental Attachment, Perceived Parental-Partner Similarity, and Relationship Satisfaction among Indian Emerging Adults
Theories of mate selection debate about whether people tend to choose partners based on similarities to their parents. The present study aimed to address whether a similarity in how people perceive their parents and their partners is associated with the relationship between parental attachment and relationship satisfaction by adopting a template-matching framework. Participants were urban, emerging adults in India (n = 263, 137 male and 126 female) who were measured for how they perceive the traits of a parental figure, traits of a partner, attachment to the parent, and relationship satisfaction with the partner. Data analysis was conducted using correlations, linear regressions, and moderation analyses. Findings show that perceived neuroticism of parents was associated with perceived neuroticism of the partner. Additionally, perceptions of neuroticism of parents predicted neuroticism in partners. Perceived agreeableness, neuroticism, and openness to experience moderated the relationship between parental attachment and relationship satisfaction. A gender difference with a small effect size in perceptions of similarity was observed for openness to experience and agreeableness. Finally, perceived agreeableness also moderated the relationship between parental attachment and relationship satisfaction for men and women separately. However, for men, perceived neuroticism also significantly moderated this relationship. The findings imply that, to an extent, the more emerging adults perceive similarities of certain traits in their parents and partners, the higher likelihood that their attachment to their parent predicts relationship satisfaction with their partner. Limitations and future directions have been discussed. The Author(s) under exclusive licence to National Academy of Psychology (NAOP) India 2024. -
Hydrogen Sulfide-Induced Activatable Photodynamic Therapy Adjunct to Disruption of Subcellular Glycolysis in Cancer Cells by a Fluorescence-SERS Bimodal Iridium Metal-Organic Hybrid
The practical application of photodynamic therapy (PDT) demands targeted and activatable photosensitizers to mitigate off-target phototoxicity common in always on photosensitizers during light exposure. Herein, a cyclometalated iridium complex-based activatable photodynamic molecular hybrid, Cy-Ir-7-nitrobenzofurazan (NBD), is demonstrated as a biomedicine for molecular precision. This design integrates a hydrogen sulfide (H2S)-responsive NBD unit with a hydroxy-appended iridium complex, Cy-Ir-OH. In normal physiological conditions, the electron-rich Ir metal center exerts electron transfer to the NBD unit, quenches the excited state dynamics, and establishes a PDT-off state. Upon exposure to H2S, Cy-Ir-NBD activates into the potent photosensitizer Cy-Ir-OH through nucleophilic substitution. This mechanism ensures exceptional specificity, enabling targeted phototherapy in H2S-rich cancer cells. Additionally, we observed that Cy-Ir-NBD-induced H2S depletion disrupts S-sulfhydration of the glyceraldehyde-3-phosphate dehydrogenase enzyme, impairing glycolysis and ATP production in the cellular milieu. This sequential therapeutic process of Cy-Ir-NBD is governed by the positively charged central iridium ion that ensures mitochondria-mediated apoptosis in cancer cells. Dual-modality SERS and fluorescence imaging validate apoptotic events, highlighting Cy-Ir-NBD as an advanced theranostic molecular entity for activatable PDT. Finally, as a proof of concept, clinical assessment is evaluated with the blood samples of breast cancer patients and healthy volunteers, based on their H2S overexpression capability through SERS and fluorescence, revealing Cy-Ir-NBD to be a promising predictor for PDT activation in advanced cancer phototherapy. 2024 American Chemical Society. -
Ultra-low loss compact active TM mode pass polarizer using phase change material in silicon waveguide
An active low-loss transverse magnetic (TM) pass polarizer, based on the phase change material (Ge2Sb2Te5), is proposed. The proposed polarizer is based on silicon-on-insulator technology that consists of a silicon waveguide that incorporates a thin layer of Si3N4 placed in-between GST. Enhancing the interaction between light and GST is achieved by strategically placing a double-layer GST adjacent to the slot waveguide. The polarizers tunability, on the other hand, depends on the shift in the refractive index (RI) of GST as it transitions between its crystalline and amorphous phases. By optimizing the structure, the polarizer exhibits negligible loss for both modes in the amorphous phase, and with the change of phase to crystalline, the loss of TE mode is more than 8 dB. In contrast, the loss of TM is less than 0.05 dB with a high ER of 21.82 dB, propagation length of 79.89 m and Figure of merit reaches up to 108 at 1550 nm. Due to the combination of these performance parameters, the suggested active TM pass polarizer is an appealing and effective device for various photonic applications. In addition, the fabrication technique of the proposed active TM pass polarizer is explained. 2024 IOP Publishing Ltd. -
Structural, optical and electrochromic properties of WAW films for profound electrochromic applications deposited by DC & RF magnetron sputtering
One of the most frequently used transition conducting oxides (TCO) is indium tin oxide. Indium is very expensive because of the lack of availability. So Most of the researchers focused on cost-effective materials and they have developed Dielectric/Metal/Dielectric (DMD) structures for ITO-free applications. Examples of dielectric materials are AZO, MoO3, TiO2, and WO3. The dielectric material is sandwiched between metals such as Au, Ag, Pt, Cu, and Al. The efficacy of these DMD structures is purely based on the thickness of the dielectric and metal layers. Once the metal layer thickness is more than 15 nm, the transmittance is much less due to the thickness of the material and it will work as a reflector. Moreover, as WO3 is the most widely and frequently used material we focus on the fabrication of WO3/Ag/WO3 (WAW) for replacing TCO in the electrochromic device and making it indium-free. WAW structures are widely used in smart windows, gas sensors, solar cells, photodetectors, etc. For electrochromic applications, these WAW structures showed good transmittance, fast switching speed, best coloration efficiency, and best optical modulation in comparison to WO3/ITO structure and are also cost-effective. 2024 The Author(s) -
A comprehensive review on the need for integrated strategies and process modifications for per- and polyfluoroalkyl substances (PFAS) removal: Current insights and future prospects
Alarming concern over the persistence and toxicity of per- and polyfluoroalkyl substances (PFAS) in the environment has created an imperative need for designing and redesigning strategies for their detection and remediation. Conventional PFAS removal technologies that uses physical, chemical, or biological methods. Increase in the diversity and quantity of PFAS entering the environment has necessitated the need for developing more advanced and integrated strategies for their removal. Despite of the advances reported in this domain, there exist a huge research gap that need to be mentored to tackle the problems associated with mitigation of combined toxicity of wide variety of PFAS in the environment. The possibility of PFAS to combine with other emerging contaminants poses an additional threat to the existing treatment methods thereby stressing the need for a continuous monitoring and updating the treatment processes. This review work aims at understanding the structure, entry, and fate of different types of PFAS in to the environment. Further an in-depth discussion regarding the different levels of toxicity associated with PFAS is elaborated in the review. The process description of recent PFAS remediation techniques along with their significance, limitations and possibility of integration is discussed in detail. Further a detailed outlook on the advantages and limitations of PFAS removal methods and an insight into the recently developed PFAS removal methods is outlined in this review. 2024 The Authors -
Understanding the social identity of adolescents in the Indigenous Kodava Community of India
The social identity development of adolescents in marginalized communities across the globe holds paramount significance in determining the overall well-being of its future population. Focusing on one such community, the Kodavas, an Indigenous community in South India, this study aims to understand the shifting configurations of social identity based on the changing sociocultural structure and its implications on identity perception among the adolescents belonging to the Kodava community in Kodagu district in Karnataka, India. This study used a qualitative research design to develop an analytical framework of social identity formation and its transitions in the context of the Kodavas. Data were collected from 188 adolescents (47% boys, 53% girls) between 13 and 17 years (M age = 15 years), in the form of essay writing. The findings based on thematic analysis highlight the core traditional elements of Kodava identity, factors influencing the transition in identity, and its reflection in the contemporary period. 2024 Society for Research on Adolescence. -
Biosynthesis of CuFe2O4@Ag hybrid nanocomposite: Ultrasensitive detection and catalytic reduction of 4-nitrophenol
Due to the dearth of extremely capable, sensitive, and stable catalysts, the efficient detection and catalytic removal of 4-nitrophenol (4-NP) in industrial wastewater remains a serious challenge. The detection and determination of 4-nitrophenol (4-NP) presence in the environment is a matter of paramount importance because it is a high-priority hazardous pollutant that can affect people, animals, and plants. Here, we present a promising and economically viable green synthetic route for fabricating CuFe2O4 and CuFe2O4@Ag hybrid nanocomposites from the leaf extract of Senna didymobotrya. The UVVis, FTIR, XRD, FE-SEM, EDXA, BET and VSM analysis were performed to characterize the synthesis of CuFe2O4@Ag nanocomposite. To evaluate the electrocatalytic capacity of CuFe2O4@Ag, electrochemical sensing stratergy was performed with cyclic voltammetry (CV) and differential pulse voltammetry (DPV). The modified CuFe2O4@Ag glassy carbon electrode (GCE) (CuFe2O4@Ag/GCE) demonstrated a linear response in the range of 0.01-15 ?g/ml (71 nm-107 ?M) and the ability to detect 4-NP at low concentration (0.006 ?g/ml (43 nM)). Due to the increased surface area of CuFe2O4@Ag/GCE by ? 1.5-fold, a greater cathodic current response (-16 ?A/cm2) at a low potential of -0.81 V was observed compared to CuFe2O4/GCE alone for the detection of 4-NP. Additonally, CuFe2O4@Ag showed excellent reduction ability towards 4-NP using NaBH4 with an efficiency of 96.4 % which was higher than the CuFe2O4 (only 87.3 %) in 12 min due to the synergistic relationship among Ag NPs and CuFe2O4 nanostructures. The outcomes from this study shows that the bi-functional electrocatalyst holds vast potential for environmental remediation. 2024 The Author(s) -
Strengthening of brick masonry using biaxial polypropylene geogrid as confinement reinforcement
Recent and past earthquakes have once again reiterated the requirement of strengthening the masonry structures to withstand both in-plane and out-of-plane loads. In this experimental investigation, biaxial polypropylene geogrid was used as a confinement reinforcement on the surfaces to strengthen masonry specimens. The masonry specimens without and with geogrid have been subjected to a compression test, flexural bond strength test and diagonal tension (shear) test as per IS 1905, ASTM E518 and ASTM E519, respectively. From the results, it has been found that biaxial polypropylene geogrid significantly enhances the strength in masonry specimens with geogrid and also reduces crack propagation in all three tests. The relationship between compressive strength and flexural bond strength, compressive strength and shear strength of masonry specimens with geogrid has been established. Furthermore, based on the cost analysis of various strengthening techniques, it was concluded that the use of biaxial polypropylene geogrid is an economically feasible alternative to other reinforcing materials, such as stainless-steel wire mesh and polyester geogrid. The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.