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Experimental investigation of tribocorrosion
This chapter discusses various techniques available for evaluation of tribocorrosion behavior of industrial components, their applications, and limitations. Numerous influential factors of tribocorrosion, their mechanisms, and their characteristics have been discussed at length. Further, a case study of tribocorrosion behavior of aluminum-based in situ metal matrix composites have been deliberated comprehensively. 2021 Elsevier Inc. All rights reserved. -
Parametric effect on machining characteristics of laser machined Al7075TiB2 in-situ composite
The effect of laser parameters on the machining characteristics of an Al7075 based in-situ metal matrix composite reinforced with Titanium diboride(TiB2) is investigated. The cutting speed (at 10001200 m/hr), stand-off distance (SOD) (0.30.5 mm), and gas pressure (0.50.7 bar) were studied. Scanning electron microscopy (SEM) was used to validate the machining behaviour of in-situ composites. Surface roughness and dimensional error decrease as the SOD increases up to 0.4 mm, but both increases as the SOD increases to 0.5 mm. whereas the volumetric material removal rate (VMRR) increases up to 0.4 mm SOD and then decreases as SOD increases (0.5 mm). Surface roughness, VMRR, and dimensional error were all found to increase with laser speed. Surface roughness and dimensional error increase as gas pressure increase up to 0.5 bar, then decreases. The VMRR, on the other hand, increased continuously as the assist gas pressure increased. Copyright 2021 Inderscience Enterprises Ltd. -
Interacting Dark Energy and Its Implications for Unified Dark Sector
Alternative dark energy models were proposed to address the limitation of the standard concordance model. Though different phenomenological considerations of such models are widely studied, scenarios where they interact with each other remain unexplored. In this context, we study interacting dark energy scenarios (IDEs), incorporating alternative dark energy models. The three models that are considered in this study are time-varying ?, Generalized Chaplygin Gas (GCG), and K-essence. Each model includes an interaction rate ? to quantify energy density transfer between dark energy and matter. Among them, GCG coupled with an interaction term shows promising agreement with the observed TT power spectrum, particularly for ?<70, when ? falls within a specific range. The K-essence model (??0.1) is more sensitive to ? due to its non-canonical kinetic term, while GCG (??1.02) and the time-varying ? (??0.01) models are less sensitive, as they involve different parameterizations. We then derive a general condition when the non-canonical scalar field ? (with a kinetic term Xn) interacts with GCG. This has not been investigated in general form before. We find that current observational constraints on IDEs suggest a unified scalar field with a balanced regime, where it mimics quintessence behavior at n<1 and phantom behavior at n>1. We outline a strong need to consider alternative explanations and fewer parameter dependencies while addressing potential interactions in the dark sector. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
Facial Recognition Model Using Custom Designed Deep Learning Architecture
Facial Recognition is widely used in some applications such as attendance tracking, phone unlocking, and security systems. An extensive study of methodologies and techniques used in face recognition systems has already been suggested, but it doesn't remain easy in the real-world domain. Preprocessing steps are mentioned in this, including data collection, normalization, and feature extraction. Different classification algorithms such as Support Vector Machines (SVM), Nae Bayes, and Convolutional Neural Networks (CNN) are examined deeply, along with their implementation in different research studies. Moreover, encryption schemes and custom-designed deep learning architecture, particularly designed for face recognition, are also covered. A methodology involving training data preprocessing, dimensionality reduction using Principal Component Analysis, and training multiple classifiers is further proposed in this paper. It has been analyzed that a recognition accuracy of 91% is achieved after thorough experimentation. The performance of the trained models on the test dataset is evaluated using metrics such as accuracy and confusion matrix. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Introduction: Tourism at a crossroads
[No abstract available] -
Crisis management, destination recovery and sustainability: Tourism at a crossroads
The COVID-19 pandemic brought travel to a halt and the global tourism industry has been one of the sectors hit hardest during the pandemic. This book looks at how the tourism industry can enhance its resilience and prepare for future crises more effectively. The book provides insights into the economic, social, geopolitical and environmental implications of the COVID-19 pandemic on the tourism and hospitality industries and the responses in diverse international contexts. It highlights key concepts and includes cases with real-life applications. The book also discusses future research directions in a post-pandemic scenario. This book will be an invaluable resource for practitioners in the areas of tourism and crisis management and for readers to compare and contrast tourism destination recovery and crisis management practices through different research methodologies and settings. 2023 selection and editorial matter, James Kennell, Priyakrushna Mohanty, Anukrati Sharma and Azizul Hassan. All rights reserved. -
Physics of Gravitational Waves: Sources and Detection Methods
[No abstract available] -
From maximum force to the field equations of general relativity and implications
There are at least two ways to deduce Einstein's field equations from the principle of maximum force c4/4G or from the equivalent principle of maximum power c5/4G. Tests in gravitational wave astronomy, cosmology, and numerical gravitation confirm the two principles. Apparent paradoxes about the limits can all be resolved. Several related bounds arise. The limits illuminate the beauty, consistency and simplicity of general relativity from an unusual perspective. 2022 World Scientific Publishing Company. -
Formula One Race Analysis Using Machine Learning
Formula One (also known as Formula 1 or F1) is the highest class of international auto-racing for single-seater formula racing cars sanctioned by the Fation International de automobile (FIA). The World Drivers Championship, which became the FIA Formula One World Championship in 1981, has been one of the premier forms of racing around the world since its inaugural season in 1950. This article looks at cost-effective alternatives for Formula 1 racing teams interested in data prediction software. In Formula 1 racing, research was undertaken on the current state of data gathering, data analysis or prediction, and data interpretation. It was discovered that a big portion of the leagues racing firms require a cheap, effective, and automated data interpretation solution. As the need for faster and more powerful software grows in Formula 1, so does the need for faster and more powerful software. Racing teams benefit from brand exposure, and the more they win, the more publicity they get. The papers purpose is to address the problem of data prediction. It starts with an overview of Formula 1s current situation and the billion-dollar industrys history. Racing organizations that want to save money might consider using Python into their data prediction to improve their chances of winning and climbing in the rankings. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Clinical Intelligence: Deep Reinforcement Learning for Healthcare and Biomedical Advancements
Deep reinforcement learning (DRL) is showing a remarkable impact in the healthcare and biomedical domains, leveraging its ability to learn complex decision-making policies from raw data through trial-and-error interactions. DRL can effectively extract the characteristic information in the environment, propose effective behavior strategies, and correct errors that occurred during the training process. Targeted toward healthcare professionals, researchers, and technology enthusiasts, this chapter begins with notable applications of DRL in healthcare, including personalized treatment recommendations, clinical trial optimization, disease diagnosis, robotic surgery and assistance, mental health support systems, chronic disease management and scheduling, and a few more. It also delves on challenges such as data privacy, interpretability, regulatory compliance, validation, and the need for domain expertise to ensure safe and effective deployment. Next, the chapter seamlessly transitions into DRL algorithms contributing to the biomedical field which are gaining traction due to their potential to provide timely and personalized interventions. Over time, the research community has proposed several methods and algorithms within the field of deep reinforcement learning that help agents learn optimal policies from rich data. Healthcare data is often complex, high-dimensional, and unstructured, such as medical images, genomics data, and patient records. The healthcare-suitable DRL algorithms such as Q-learning, SARSA, Bayesian, actor-critic, reinforcement learning (RL), Deep-Q-Networks (DQN), and Monte Carlo Tree Search (MCTS) are highlighted. In addition, the section offers guidelines for the application of DRL to healthcare and biomedical problems, aiming at providing indications to the designer of new applications in order to choose among different RL methods. Furthermore, a case study is included to fully realize the revolutionary benefits of DRL in healthcare environments, aiming to bridge the gap between theory and practice. The case study presents a remarkable impact on categories such as precision medicine, dynamic treatment regime, medical imaging, diagnostic systems, control systems, chat-bots and advanced interfaces, and healthcare management systems. 2024 Scrivener Publishing LLC. -
Detection of picric acid in industrial effluents using multifunctional green fluorescent B/N-carbon quantum dots /
Journal of Environmental Chemical Engineering, Vol.10, Issue 2, ISSN No: 2213-3437.
Carbon quantum dots have recently gained widespread attention due to their excellent physicochemical features. The rapid escalation in the dumping of hazardous chemicals into water, spurred demand for developing efficient and selective sensors for toxic chemicals. Herein, we have developed a novel fluorescence sensor for picric acid which is a major pollutant in industrial effluents. The new strategy exploits the development of a fluorescence sensor based on N-doped carbon quantum dots (N-CQDs) followed by boron functionalization. The N-CQDs were synthesized in a rapid single-step microwave technique by employing L-serine and citric acid. -
RayleighBard Convection in a Bi-viscous Bingham Fluid with Weak Vertical Harmonic Oscillations: Linear and Non-linear Analyses
Linear and weakly non-linear stability analyses of RayleighBard convection in a bi-viscous Bingham fluid layer are performed in the presence of vertical harmonic vibrations. In the linear analysis, expression is obtained for the correction Rayleigh-number arising due to the vibrations. The non-linear-analysis based on the GinzburgLandau equation is used to compute the Nusselt-number in terms of the correction Rayleigh-number. The mean-Nusselt-number is then obtained as a function of the scaled-Rayleigh-number, the frequency and the amplitude of modulation, the Prandtl number, and the bi-viscous Bingham fluid parameter. The non-autonomous amplitude-equation is numerically solved using the RungeKuttaFehlberg45 method. It is found that the influence of increasing the amplitude of modulation is to result in a delayed-onset situation and thereby to an enhanced-heat-transport situation. For small and moderate frequencies, the influence of increasing the frequency of oscillations is to decrease the critical Rayleigh-number. However, the mean-Nusselt-number decreases with increase in the frequency of oscillations only in the case of small frequencies. An increase in the value of the bi-viscous Bingham fluid parameter leads to advanced-onset and thereby to an enhanced-heat-transport situation. At very large frequencies, the effect of modulation on onset and heat-transport ceases. 2023, The Author(s), under exclusive licence to Springer Nature India Private Limited. -
Analytical study of triple diffusive convection in a bi-viscous Bingham fluid layer using Ginzburg-Landau model
In this paper, considering bi-viscous Bingham as the base fluid, we study the thermophysical-properties (such as density, specific heat, thermal conductivity, thermal diffusivity, and thermal expansion) with different combinations of salts among NaCl, KCl, CaCl2, and NaCl2 of triple diffusive convection in a bi-viscous Bingham fluid layer with heat as one of the diffusing components. A weakly non-linear case is formulated to facilitate a solution to the problem using a series solution Ginzburg-Landau model. With regard to single, double, and triple diffusive convection, the tables are made to record the actual values of thermophysical-properties together with the critical Rayleigh-number for each combination of aqueous-salt solutions. This computation calculates the mean Nusselt and Sherwood numbers to quantify the systems heat- and mass-transfers for various aqueous-solutions. The effect of the bi-viscous Bingham fluid parameter, for small and large values, for different aqueous-solutions, in single, double, and triple diffusive convection has been captured via 2-dimensional (2D) and 3-dimensional (3D) figures and the results are recorded and compared. The investigation reveals that the heat- and mass-transfers increase with an increase or decrease in the bi-viscous Bingham fluid parameter, which in turn depends on the values of (Formula presented.) and (Formula presented.) The results confirm that the heat- and mass-transfers are least for the combination of KCl with CaCl2 and maximum for the combination of NaCl with other salts. 2024 Taylor & Francis Group, LLC. -
Weakly Non-linear Stability Analysis of Triple-Diffusive Convection in a Bi-viscous Bingham Fluid Layer with Cross-Diffusion Effects
The paper investigates the impact of cross-diffusion on triple-diffusive convection in a bi-viscous Bingham fluid layer. Non-linear stability analysis is performed, and the expression of the critical-Rayleigh-number is obtained, resulting in an analytical solution of the Ginzburg-Landau model (GLM). The coefficients in the GLM involve the scaled Rayleigh-number, the solutal Rayleigh-numbers, the solutal diffusivity rates, the bi-viscous Bingham fluid parameter, and the cross-diffusion parameters. The solutal Rayleigh-numbers, the solutal diffusivity rates, and the bi-viscous Bingham fluid parameter alone determine the critical-Rayleigh-number, which provides the condition for the stationary onset. The neutral curves for the stationary mode are examined. It is found that the solutal diffusivities and bi-viscous Bingham fluid parameter advance the onset of convection, whereas the solutal Rayleigh-numbers delay it. The Nusselt number, Nu, and the Sherwood numbers, Sh1 and Sh2, determine the heat- and mass-transfer rates obtained for the convection system. We see that Nu, Sh1 and Sh2 increase with an increase in the values of the bi-viscous Bingham fluid parameter. Also, we observe that increase in the Prandtl number effect increases them, and the same is true of the solutal Rayleigh-numbers, whereas the opposite impact on Nu, Sh1 and Sh2 is seen for solutal diffusivities, Soret and cross-diffusion parameters. In general, we observe that mass-transfer is more than the heat-transfer (Sh1>Sh2>Nu) depending on the value of diffusivities. The Author(s), under exclusive licence to Springer Nature India Private Limited 2024. -
Fluorescein Based Fluorescence Sensors for the Selective Sensing of Various Analytes
Fluorescein molecules are extensively used to develop fluorescent probes for various analytes due to their excellent photophysical properties and the spirocyclic structure. The main structural modification of fluorescein occurs at the carboxyl group where different groups can be easily introduced to produce the spirolactam structure which is non-fluorescent. The spirolactam ring opening accounts for the fluorescence and the dual sensing of analytes using fluorescent sensors is still a topic of high interest. There is an increase in the number of dual sensors developed in the past five years and quite a good number of fluorescein derivatives were also reported based on reversible mechanisms. This review analyses environmentally and biologically important cations such as Cu2+, Hg2+, Fe3+, Pd2+, Zn2+, Cd2+, and Mg2+; anions (F?, OCl?) and small molecules (thiols, CO and H2S). Structural modifications, binding mechanisms, different strategies and a comparative study for selected cations, anions and molecules are outlined in the article. 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
A ratiometric fluorescent sensor based on dual-emissive carbon dot for the selective detection of Cd2+
Cadmium (Cd2+), a heavy metal ion used in numerous industries, has toxic adverse effects on the environment; it is crucial to develop a quick and reliable method for Cd2+ determination. Fluorescent biomass-derived carbon quantum dots (CD) with rich carboxyl groups on the surface were synthesized using water amaranth leaves by hydrothermal method with a 12.1% quantum yield. The surface of CD was further modified with 1-pyrene carboxaldehyde (PC) to synthesize pyrene carboxaldehyde-carbon quantum dots (PC-CD). This study developed a fluorescent ratiometric nanosensor using a covalently functionalized CD with pyrene derivative and demonstrates highly selective identification capability towards Cd2+ over competing metal ions. The Nano sensor has significant selectivity towards Cd2+ in an excellent linear range of 0-70 ?M with a detection limit as low as 15 nM and demonstrates excellent water solubility and biocompatibility. Transmission electron spectroscopy (TEM), Fourier Transform infrared spectroscopy (FT-IR), and X-ray photon spectroscopy (XPS) were used to identify the surface functionalization of PC-CD. Finally, the developed ratiometric sensor was used for detecting Cd2+ metal ions from various water effluents. 2023 Elsevier Ltd. -
Dual ion specific electrochemical sensor using aminothiazole-engineered carbon quantum dots
A novel electrochemical sensor capable of concurrently detecting Pb2+ and Hg2+ ions has been innovatively engineered. This sensor utilizes the anodic stripping voltammetry technique (ASV) with a composite consisting of carbon quantum dots and aminothiazole (CQD-AT). In this composite, both the carbon quantum dots and aminothiazole contribute significantly to the electroactive surface area, boasting an abundance of functional groups that include oxygen and nitrogen atoms. These functional groups serve as active sites that enhance sensor sensitivity by facilitating the electrostatic interaction-based adsorption of heavy metal ions. Aminothiazole surface is evenly covered with CQDs, which are essential for metal gets reoxidized into metal ions for stripping analysis. Due to this unique modification, the Pb2+ and Hg2+ electrochemical sensor using the CQD-AT composite coated on carbon fiber paper electrode (CQD-AT/CFP) exhibits superior analysis performance such as wide linear range (0.6 1011160 106 M) for Pb2+ and Hg2+ with a limit of detection (LOD) of 3.0 pM and 6.2 pM for Pb2+ and Hg2+. CQD-AT/CFP modified electrode can be considered as a potential material for electrochemical simultaneous determination of Pb2+ and Hg2+ in different water samples. 2023 Elsevier B.V. -
Biomass derived carbon quantum dots embedded PEDOT/CFP electrode for the electrochemical detection of phloroglucinol
Carbon nanocomposites have garnered a lot of attention among various nanomaterials due to their distinct characteristics, such as large surface area, biocompatibility, and concise synthetic routes. They are also a viable contender for electrochemical applications, notably sensing, due to their intriguing electrochemical features, which include large electroactive surface area, outstanding electrical conductivity, electrocatalytic activity, and high porosity and adsorption capability. Herein, an electrochemical sensor for phloroglucinol (PL) was designed using a CFP electrode modified with biomass-derived carbon quantum dots (S-CQD) doped on conducting organic polymer poly(3,4-ethylene dioxythiophene) (PEDOT) via electrodeposition method. The obtained nanocomposite (S-CQD+PEDOT) on the CFP electrode possesses a high surface area. The higher electrocatalytic activity of S-CQD and significant conductivity of PEDOT- modified electrode enhance the electrocatalytic activity for the phloroglucinol oxidation. The oxidation peak current of PL shows a higher response on the finally modified electrode than the other electrodes. The developed electrochemical sensor for the selective and sensitive detection of PL showed a good linear range of 36 -360 nM and a detection limit of 11 nM. The modified electrodes were characterized using Transmission electron spectroscopy (TEM), Fourier Transform infrared spectroscopy (FT-IR), and X-ray photon spectroscopy (XPS). Finally, the developed method was successfully used to detect Phloroglucinol from industrial effluents with RSD (0.841.02%) and (98.5101.2%) of recovery. 2023 -
An Efficient Inclusion Complex Based Fluorescent Sensor for Mercury (II) and its Application in Live-Cell Imaging
The formation of an inclusion complex between hydroxypropyl-?-cyclodextrin (H-CD) and 4-acetylphenyl-4-(((6-chlorobenzo[d]thiazol-2-yl)-imino)-methyl)-benzoate (L) was investigated by FT-IR, 1H-NMR, X-ray diffraction (XRD), FT-Raman, scanning electron microscope (SEM) techniques in the solid-state, absorption and emission spectroscopy in the liquid state and the virtual state as molecular docking technique. The binding properties of the inclusion complex (H-CD: L) with cations in deionized water was observed via absorbance and photoluminescence (PL) emission spectroscopy. The fluorescence probe (H-CD: L) inclusion complex (IC) was examined for several heavy metal cations, and identified that the PL emission wavelength of the complex displayed a continuous rise in the fluorescence intensity for Hg2+. A linearity range of 1 108 11 108M and limit of detection value of 2.71 1010M was found to be achieved for the detection of Hg2+. This outcome proves that the inclusion complex H-CD: L would be a promising material for the development a solid-state fluorescence probe for detecting Hg2+. It also shows application in real sample analysis and cell imaging. 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
