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As there is a strong inducement to develop new colored inorganic materials to substitute the current industrial pigments that are based on toxic metals hazardous to health and the environment, the purpose of this paper is to invent environmentally benign rare earth-based colorants as viable alternatives to the traditional toxic pigment formulations. Herein, the authors developed a series of rare earth pigments having the general formula Ca0.1 Ln0.9 PO4 ( Ln = Y , Pr , mixed rare earth oxides, RE and Di). After studying all the optical properties, the authors have gone for some coloring application in plastic like PMMA.

The designed pigments were synthesized by traditional solid-state method. Stoichiometric amounts of each reagent were mixed in an agate mortar and the mixtures were calcined at optimized temperature 1000 °C for 4 h in electric furnace followed by auto–cooling. The samples were characterized by X-ray diffraction diffraction, UV–vis spectroscopy, scanning electron microscope (SEM), particle size distribution, color coordinates determination, acid/alkali test, thermo gravimetric (TG) analysis and CIE–1976 L*a*b* color scales. Among the various lanthanide ions and calcium ion as dopant, the pigment composition shows various hues ranges from green to yellow. The designed pigments consist of non–toxic elements and were further found to possess high thermal and chemical stability. The pigments were also found to be appropriate candidates for the coloration of polymer substrates like PMMA.

The present investigations establish that various color hues can be achieved by the incorporation of suitable chromophore metal ions like calcium in various rare earth host lattice by tuning of the band gaps. The coloring mechanism is based on the strong absorption of the pigments in the blue and red regions due to electronic transitions of the micro states of rare earth ion. The pigment composition shows various hues ranges from green to yellow. The coloring mechanism is based on the tuning of band gap by the dopant like calcium in various rare earth host lattice. In addition, this pigment was chemically and thermally stable. Finally, it has applied in plastics like PMMA.

Mechanism of the color appearance using band calculations and on possible applications of rare earth phosphate powders as pigments in plastics and paints have not been explored much. However, the properties of the Ca-doped rare earth phosphate implies that this material has a potential to be applied as a satisfactory pigment for coating or coloring except for glaze, which may cause a side reaction at high temperatures, especially taking into consideration the economics and ecologies. The possibility of Ca2+ incorporation in CePO4 with monazite structure-type has been established.

The designed pigments consist of non-toxic elements and were further found to possess high thermal and chemical stability. The pigments were also found to be appropriate candidates for the coloration of polymer substrates. Thus, the present environmental friendly pigment powders may find potential alternative to the classical toxic inorganic pigments for various applications.

There is a strong incentive to design new colorants based on inorganic materials to substitute for industrial pigments that are based on heavy elements hazardous to health and the environment. However, several industrial yellow pigments such as cadmium yellow (CdS), chrome yellow (PbCrO4) and nickel titanium yellow (TiO2-NiO-Sb2O3) contain the harmful elements (e.g. Cd, Pb, Cr and Sb) for the human body as well as the environment. The designed pigments consist of non-toxic elements and were further found to possess high thermal and chemical stability. The pigments were also found to be appropriate candidates for the coloration of polymer substrates. Thus, the present environmental friendly pigment powders may find potential alternative to the classical toxic inorganic pigments for various applications.

There is a strong incentive to design new colorants based on inorganic materials to substitute for industrial pigments that are based on heavy elements hazardous to health and the environment. However, several industrial yellow pigments such as cadmium yellow (CdS), chrome yellow (PbCrO4) and nickel titanium yellow (TiO2-NiO-Sb2O3) contain the harmful elements (e.g. Cd, Pb, Cr and Sb) for the human body as well as the environment. So, the authors have developed new class of inorganic pigments that are both non-toxic and environmentally unimpeachable, while preserving or even exceeding the optical, thermal and chemical characteristics of the existing commercial pigments. The developed colorants find practical applications in polymer matrix like PMMA.

Diagnosing the crop diseases by farmers accurately with the naked eye can be challenging. Timely identification and treating these diseases is crucial to prevent complete destruction of the crops. To overcome these challenges, in this work a light-weight automatic crop disease detection system has been developed, which uses novel combination of residual network (ResNet)-based feature extractor and machine learning algorithm based classifier over a real-time crop dataset.

The proposed system is divided into four phases: image acquisition and preprocessing, data augmentation, feature extraction and classification. In the first phase, data have been collected using a drone in real time, and preprocessing has been performed to improve the images. In the second phase, four data augmentation techniques have been applied to increase the size of the real-time dataset. In the third phase, feature extraction has been done using two deep convolutional neural network (DCNN)-based models, individually, ResNet49 and ResNet41. In the last phase, four machine learning classifiers random forest (RF), support vector machine (SVM), logistic regression (LR) and eXtreme gradient boosting (XGBoost) have been employed, one by one.

These proposed systems have been trained and tested using our own real-time dataset that consists of healthy and unhealthy leaves for six crops such as corn, grapes, okara, mango, plum and lemon. The proposed combination of Resnet49-SVM and ResNet41-SVM has achieved accuracy of 99 and 97%, respectively, for the images that have been collected from the city of Kurukshetra, India.

The proposed system makes novel contribution by using a newly proposed real time dataset that has been collected with the help of a drone. The collected image data has been augmented using scaling, rotation, flipping and brightness techniques. The work uses a novel combination of machine learning methods based classification with ResNet49 and ResNet41 based feature extraction.

The purpose of this paper is to emphasize the peristaltic mechanism of power-law fluid in an elastic porous tube under the influence of slip and convective conditions. The effects of different waveforms on the peristaltic mechanism are taken into account.

The governing equations are rendered dimensionless using the suitable similarity transformations. The analytical solutions are obtained by using the long wavelength and small Reynold’s number approximations. The expressions for velocity, flow rate, temperature and streamlines are obtained and analyzed graphically. Furthermore, an application to flow through an artery is determined by using a tensile expression given by Rubinow and Keller.

The principal findings from the present model are as follows. The axial velocity increases with an expansion in the estimation of velocity slip parameter and fluid behavior index, and it diminishes for a larger value of the porous parameter. The magnitude of temperature diminishes with an expansion in the Biot number. The flux is maximum for trapezoidal wave and minimum for the triangular wave when compared with other considered waveforms. The flow rate in an elastic tube increases with an expansion in the porous parameter, and it diminishes with an increment in the slip parameter. The volume of tapered bolus enhances with increasing values of the porous parameter.

The current study finds the application in designing the heart-lung machine and dialysis machine. The investigation further gives a superior comprehension of the peristaltic system associated with the gastrointestinal tract and the stream of blood in small or microvessels.

This paper aims to investigate the effect of ultrasonic vibration (USV) on the evolution of intermetallic compounds (IMCs), grain morphology and shear strength of soldered Ni/Sn/Ni samples.

The Ni/Sn/Ni joints were obtained through ultrasonic-assisted soldering. The formation of IMCs, their composition, grain morphology and the fractured-surface microstructures from shear tests were characterized using scanning electron microscopy and energy-dispersive x-ray spectroscopy.

Without USV, a planar interfacial Ni₃Sn₄ layer was formed at the Ni/Sn interface, and a few Ni₃Sn₄ grains were distributed in the soldered joint. The morphology of these grains was needle-shaped. With USV, several grooves were formed at the interfacial Ni₃Sn₄ layer due to ultrasonic cavitation. Some deepened grooves led to “neck” connections at the roots of the Ni₃Sn₄ grains, which accelerated the strong detachment of Ni₃Sn₄ from the substrate. In addition, two types of Ni₃Sn₄ grains, needle-shaped and granular-shaped, were observed at the interface. Furthermore, the shear strength increased with longer USV time, which was attributed to the thinning of the interfacial IMC layers and dispersion strengthening from the Ni₃Sn₄ particles distributed evenly in the joint.

The novelty of the paper is the detailed study of the effect of USV on the morphology, size changes of interfacial IMC and joint strength. This provides guidance for the application of ultrasonic-assisted soldering in electronics packaging.

Doppler-Bearing Tracking (DBT) is commonly used in target tracking applications for the underwater environment using the Hull-Mounted Sensor (HMS). It is an important and challenging problem in an underwater environment.

The system nonlinearity in an underwater environment increases due to several reasons such as the type of measurements taken, the speeds of target and observer, environmental conditions, number of sensors considered for measurements and so on. Degrees of nonlinearity (DoNL) for these problems are analyzed using a proposed measure of nonlinearity (MoNL) for state estimation.

In this research, the authors analyzed MoNL for state estimation and computed the conditional MoNL (normalized) using different filtering algorithms where measurements are obtained from a single sensor array (i.e. HMS). MoNL is implemented to find out the system nonlinearity for different filtering algorithms and identified how much nonlinear the system is, that is, to measure nonlinearity of a problem.

Algorithms are evaluated for various scenarios with different angles on the target bow (ATB) in Monte-Carlo simulation. Computation of root mean squared (RMS) errors in position and velocity is carried out to assess the state estimation accuracy using MATLAB.

Marine exploration is becoming an important element of pervasive computing underwater target tracking. Many pervasive techniques are found in current literature, but only scant research has been conducted on their effectiveness in target tracking.

This research paper, introduces a Shifted Rayleigh Filter (SHRF) for three-dimensional (3 D) underwater target tracking. A comparison is drawn between the SHRF and previously proven method Unscented Kalman Filter (UKF).

SHRF is especially suitable for long-range scenarios to track a target with less solution convergence compared to UKF. In this analysis, the problem of determining the target location and speed from noise corrupted measurements of bearing, elevation by a single moving target is considered. SHRF is generated and its performance is evaluated for the target motion analysis approach.

The proposed filter performs better than UKF, especially for long-range scenarios. Experimental results from Monte Carlo are provided using MATLAB and the enhancements achieved by the SHRF techniques are evident.

Purpose: Sustainable and responsible business is strongly associated with activities that minimise negative environmental or social impacts. As a result, the utility of big data is becoming a reality, opening up exciting possibilities for ESG monitoring and assessment. This study systematises existing knowledge and provides recommendations for big data in ESG monitoring and assessment.

Methodology/approach: Theoretical and exploratory focusing on a literature review.

Conclusions: Results indicate different levels of progress and challenges related to ESG and big data. Awareness and adoption of ESG and big data practices is growing, accompanied by regulatory pressure.

Significance: Understanding the relationship between big data and ESG is critical to properly conducting sustainable and responsible business practices. The urgency and necessity of developing standards for constructing big data cannot be overstated for ensuring consistency between existing policies and the SDGs and for the effective use of big data in ESG monitoring and assessment.

Limitations: A lack of data quality and standardisation in reporting for ESG assessments. Standardisation efforts are growing as data challenges, especially data availability, are major constraints. Large data sets offer exciting opportunities, analysed mainly from the perspective of existing applications for measuring sustainability goals.

Future research: An in-depth analysis of case studies that combine ESG issues with big data infrastructure. Fundamental is knowledge and understanding of companies’ ESG practices and understanding big data issues. We can standardise approaches to using new data sources and move towards deepening our measurable dimension of sustainability assessment.

This paper examines the impact of green human resource management (GHRM) practices on employees’ pro-environmental behavior in Pakistan’s hospitality industry. It attempts to identify the critical success factors involved in promoting GHRM and pro-environmental behaviors at the workplace using Interpretive Structural Modeling (ISM) and cross-impact matrix multiplication applied to classification (MICMAC) approaches. Later, based on the ability-motivation-opportunity (AMO) model, the study also categorizes the identified critical factors into three categories: ability, motivation and opportunity.

The ISM approach was applied to determine the contextual relationship among the identified critical success factors responsible for promoting GHRM. MICMAC, a structural technique to analyze and validate the ISM-based model, was used to determine the autonomous, dependent, linkage and independent factors based on expert opinions and judgments. The goal was to determine the role of GHRM in transforming the pro-environmental behavior of employees.

The study’s findings show that the proper integration of effective GHRM practices significantly impacts pro-environmental employee behavior. The hierarchical model introduces innovation in the field of GHRM because ISM-based hierarchical models are flexible enough to include or exclude practices according to the green organizational objectives in the hospitality industry within the context of Pakistan. The results offer a comprehensive illustration of the importance of GHRM practices in facilitating, encouraging and promoting employees to take green initiatives and achieve business sustainability.

The study utilizes the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) technique to identify key success criteria for GHRM, while the innovative approaches of ISM and MICMAC techniques were used to investigate employee pro-environmental behaviors. This novel method gives GHRM research an analytical direction by providing an organized framework for evaluating the impact of GHRM initiatives on environmental outcomes. Additionally, by focusing on developed economies rather than emerging ones, our study within Pakistan’s hospitality sector fills a knowledge vacuum on the dynamics of GHRM in a developing nation.

This study highlights the significance of managers in the hospitality sector serving as role models for implementing GHRM practices to encourage pro environmental behavior among employees. Prioritizing green structural capital, establishing standard environmentally friendly criteria for hiring and evaluating prospective employees and initiating green projects to promote a psychologically green environment are some of the key recommendations. Improving environmental performance, employee satisfaction and loyalty in the hotel industry requires constant communication, training and employee participation in sustainability decision-making.

The GHRM practices have been extensively discussed by academics and researchers. However, there is a notable absence of discussion on the key factors that play a role in transforming employees’ attitudes and behaviors.

The purpose of this paper is to explore the tribological properties of high-density polyethylene (HDPE) modified by carbon soot from the combustion of No. 0 diesel.

Carbon soot is characterized using X-ray diffraction, transmission electron microscopy and scanning electronic microscopy. The tribological properties of HDPE samples with carbon soot are investigated on a materials surface tester with a ball-on-disk friction pair.

The collected carbon soot mainly comprises amorphous carbon nanoparticles of 50-100 nm in diameter. The main wear behaviours of pure HDPE include abrasive wear and plastic deformation. After adding carbon soot nanoparticles to HDPE, HDPE wear decreases. The appropriate carbon soot content is 8 per cent in HDPE under the selected testing conditions. Compared with other HDPE samples, HDPE with 8 per cent carbon soot has higher melting temperature, lower abrasive wear and better wear resistance. The lubrication of HDPE with carbon soot is due to the formation of a transferring film composed of HDPE, amorphous carbon and graphite carbon.

The paper reveals the HDPE modification and lubrication mechanisms by using carbon soot from the combustion of diesel. Related research can perhaps provide a potential approach for the treatment of carbon soot exhaust emission.

The purpose of this paper is to carry out a comprehensive review of some latest studies devoted to natural convection phenomenon in the enclosures because of its significant industrial applications.

Geometries of the enclosures have considerable influences on the heat transfer which will be important in energy consumption. The most useful geometries in engineering fields are treated in this literature, and their effects on the fluid flow and heat transfer are presented.

A great variety of geometries included with different physical and thermal boundary conditions, heat sources and fluid/nanofluid media are analyzed. Moreover, the results of different types of methods including experimental, analytical and numerical are obtained. Different natures of natural convection phenomenon including laminar, steady-state and transient, turbulent are covered. Overall, the present review enhances the insight of researchers into choosing the best geometry for thermal process.

A comprehensive review on the most practical geometries in the industrial application is performed.