Search results

This study aims to examine the impact of firm-generated content (FGC) on lesbian, gay, bisexual, transgender, queer/questioning (LGBTQ+) influencers, focussing on inclusive marketing strategies and enquires the ability of LGBTQ+ influencers to enhance brand engagement and loyalty within diverse communities.

A quantitative approach was utilized, and data was collected via social media platforms. Structural equation modelling (SEM) was employed to explore the relationships between FGC, influencer content, dimensions of place attachment and brand loyalty.

According to the findings FGC positively influences LGBTQ+ influencers, which in turn affect in a significant way place identity and place social bonding. Both dimensions of place attachment were found to have a positive impact on brand loyalty, which indicate that LGBTQ+ influencers have an important role in enhancing brand engagement through inclusive marketing.

Firms in order to increase their brand loyalty and customer engagement, need to adopt inclusive marketing strategies that resonate with LGBTQ+ communities. In order to do so they need to work with LGBTQ+ influencers that can effectively communicate the brand’s commitment to diversity and inclusion, thus fostering a stronger emotional connection with the brand.

This study introduces a conceptual framework that highlights the mediator role of place attachment in the relationship between influencer marketing and brand loyalty. This research contributes to the existing literature by providing empirical evidence on the effectiveness of leveraging LGBTQ+ influencers in inclusive marketing campaigns.

This study aims to describe on-site determination of pH in aquaculture using a portable colorimeter.

A basic and inexpensive portable colorimeter having light sources of different wavelength has been optimized for the determination of pH. A chromic reagent is optimized to develop colors depending on different pHs. Then, the color is measured using portable colorimeter in terms of resistance. Using the resistance to absorbance relationship, the resistance values are converted to absorbance. The performance of the developed colorimetric system is compared with commercially available colorimeter and pH meter. Eighty brackish water aquaculture samples were tested using the developed colorimetric system to check its adaptability in aquaculture farms.

A chromic reagent optimized in this study exhibited linear relationship with the pH changes of pH standards. Portable colorimeter having three different light sources is optimized using this chromic agent for determination of pH. Colorimeter possessing yellow light revealed more linear results than the others. The developed colorimetric system determines the pH of aquaculture water with an accuracy of ±0.14 in comparison with commercial colorimeter at the pH range of 6.0−9.0.

pH plays a pivotal role in aquaculture, impacting not only productivity but also profitability. The colorimetric system introduced in this research is promising for pH measurement in the field of brackish water aquaculture. The on-site pH assessment facilitated by this colorimetric system holds significant potential for adoption within the aquaculture sector, owing to its precision, portability, simplicity of use and user-friendly nature.

In this manuscript, we aimed to (1) illustrate the differences in school–university partnership under the school reform and renewal models and (2) describe the practice of and learning about school–university partnership by reflecting on the three large, federally funded projects, all conducted under the school renewal model.

We used archival data from the three large, federally funded projects, synthesized our research related to school–university partnerships and developed themes for actions and learnings related to the topic of school–university partnerships.

The school–university partnerships under the school renewal model are different from that under the school reform model. School–university partnership under the school renewal model is associated with positive results for schools and the university. There are clear themes for the actions and learning in the school–university partnership under the school renewal model.

It is original to study school–university partnerships in the context of the school renewal model.

In this research work, the general form of reliability measures, which include availability, mean time to failure (MTTF), and sensitivity analysis, are investigated with their graphical representation, which would help designers and engineers improve the reliability of the system. Along with reliability assessment, a mathematical model is developed and solved to achieve the minimum cost of the system as well as maximum reliability.

In the proposed work, a general model of a solar seed sowing machine is considered for reliability evaluation using the Markov model process. The proposed system is a series-parallel arrangement of components where three components, namely the solar panel, batteries and direct current (DC) motor, are connected in series while all the operators are connected in parallel. The implemented Markov model approach assesses several parameters of reliability, which opens the scope for improvement in reliability and other measures like mean time to failure (MTTF) and sensitivity of the proposed system. So that the machine can deliver the desired output on the field. Also, the particle swarm optimization (PSO) algorithm is applied to optimize the cost of the system with the desired level of reliability.

Implementation of PSO provides the optimal cost for the proposed system with a predetermined level of reliability, which shows the relationship between reliability and cost of the system. Also, the Markov process approach provides the availability function, reliability function, reliability at different time values, MTTF and sensitivity of the proposed system.

This work evaluates the crucial characteristics of reliability for the proposed solar seed sowing machine using the Markov model which is a stochastic model. The assessment of reliability measures such as MTTF, availability and sensitivity plays a vital role in measuring and improving the performance of the machine in the actual environment. Examining the data obtained in this research is of great importance for the manufactures and system designers. Also, the powerful optimization technique PSO is implemented to solve a non-linear mixed-integer programming problem that provides the optimal cost for the system with desired reliability.

Taking into consideration the current human need for agricultural produce such as rice that requires water for growth, the optimal consumption of this valuable liquid is important. Unfortunately, the traditional use of water by humans for agricultural purposes contradicts the concept of optimal consumption. Therefore, designing and implementing a mechanized irrigation system is of the highest importance. This system includes hardware equipment such as liquid altimeter sensors, valves and pumps which have a failure phenomenon as an integral part, causing faults in the system. Naturally, these faults occur at probable time intervals, and the probability function with exponential distribution is used to simulate this interval. Thus, before the implementation of such high-cost systems, its evaluation is essential during the design phase.

The proposed approach included two main steps: offline and online. The offline phase included the simulation of the studied system (i.e. the irrigation system of paddy fields) and the acquisition of a data set for training machine learning algorithms such as decision trees to detect, locate (classification) and evaluate faults. In the online phase, C5.0 decision trees trained in the offline phase were used on a stream of data generated by the system.

The proposed approach is a comprehensive online component-oriented method, which is a combination of supervised machine learning methods to investigate system faults. Each of these methods is considered a component determined by the dimensions and complexity of the case study (to discover, classify and evaluate fault tolerance). These components are placed together in the form of a process framework so that the appropriate method for each component is obtained based on comparison with other machine learning methods. As a result, depending on the conditions under study, the most efficient method is selected in the components. Before the system implementation phase, its reliability is checked by evaluating the predicted faults (in the system design phase). Therefore, this approach avoids the construction of a high-risk system. Compared to existing methods, the proposed approach is more comprehensive and has greater flexibility.

By expanding the dimensions of the problem, the model verification space grows exponentially using automata.

Unlike the existing methods that only examine one or two aspects of fault analysis such as fault detection, classification and fault-tolerance evaluation, this paper proposes a comprehensive process-oriented approach that investigates all three aspects of fault analysis concurrently.

This study aims to determine the ink removal efficiency of papers with different recycling numbers and to examine some electrophotographic printing properties.

The base papers prepared according to the INGEDE 11p standard are subjected to six recycling stages (RS) under equal conditions. The physical-optical properties of the papers obtained at the end of each RS are measured and CMYK (cyan, magenta, yellow, key) color measurement scales are printed on each paper with electrophotographic printing. Color measurements of the printed papers are measured using the X-Rite eXact spectrophotometer, adhering to the ISO 13655:2017 standard. According to the measurement results of the optical properties, the ink removal efficiency of each recycling step is determined as a percentage (%) using some formulas.

As general, according to DEMLab and IERIC data, it is determined that the ink removal efficiency increased as the recycling repetition increased. In DEMf factor values, the highest deinking efficiency is obtained after the fourth RS. There is no significant difference between the printing properties of the samples.

It has been a matter of curiosity that papers lose their properties after how many RS. Many studies have been carried out on this subject and it has been presented by experimental methods that the printability properties of papers increase or decrease after which RS. This study can be a pioneer for future studies.

This paper aims to investigate the hydrodynamic instability properties of a mixed convection flow of nanofluid in a porous channel.

The treated single-phase nanofluid is a suspension consisting of water as the working fluid and alumina as a nanoparticle. The anisotropy of the porous medium and the effects of the inclination of the magnetic field are highlighted. The effects of viscous dissipation and thermal radiation are incorporated into the energy equation. The eigenvalue equation system resulting from the stability analysis is processed numerically by the spectral collocation method.

Analysis of the results in terms of growth rate reveals that increasing the volume fraction of nanoparticles increases the critical Reynolds number. Parameters such as the mechanical anisotropy parameter and Richardson number have a destabilizing effect. The Hartmann number, permeability parameter, magnetic field inclination, Prandtl number, wave number and thermal radiation parameter showed a stabilizing effect. The Eckert number has a negligible effect on the growth rate of the disturbances.

Linear stability analysis of Magnetohydrodynamics (MHD) mixed convection flow of a radiating nanofluid in porous channel in presence of viscous dissipation.

Climate change-related weather events significantly affect rice production. In this paper, we investigate the impact of and interrelationships between agriculture inputs, climate change factors and financial variables on rice production in India from 1970–2021.

This study is based on the time series analysis; the unit root test has been employed to unveil the integration order. Further, the study used various econometric techniques, including vector autoregression estimates (VAR), cointegration test, autoregressive distributed lag (ARDL) model and diagnostic test for ARDL, fully modified least squares (FMOLS), canonical cointegrating regression (CCR), impulse response functions (IRF) and the variance decomposition method (VDM) to validate the long- and short-term impacts of climate change on rice production in India of the scrutinized variables.

The study's findings revealed that the rice area, precipitation and maximum temperature have a significant and positive impact on rice production in the short run. In the long run, rice area (ß = 1.162), pesticide consumption (ß = 0.089) and domestic credit to private sector (ß = 0.068) have a positive and significant impact on rice production. The results show that minimum temperature and direct institutional credit for agriculture have a significant but negative impact on rice production in the short run. Minimum temperature, pesticide consumption, domestic credit to the private sector and direct institutional credit for agriculture have a negative and significant impact on rice production in the long run.

The present study makes valuable and original contributions to the literature by examining the short- and long-term impacts of climate change on rice production in India over 1970–2021. To the best of the authors’ knowledge, The majority of the studies examined the impact of climate change on rice production with the consideration of only “mean temperature” as one of the climatic variables, while in the present study, the authors have considered both minimum as well as maximum temperature. Furthermore, the authors also considered the financial variables in the model.

Fluid flows through rotatory disks are encountered in industrial and practical engineering processes, such as computer storage devices, gas turbine rotators, rotating machinery, air cleaning machines, etc. The primary purpose of this research is to examine the combined aspects of variable electrical conductivity, thermal radiation, Soret and Dufour effects on a magnetohydrodynamic Maxwell single-walled carbon nanotubes–graphene oxide–multi-walled carbon nanotubes–copper (SWCNT–GO–MWCNT–Cu)/sodium alginate tetra-hybrid nanofluid flow through a stretchable rotatory disk.

The modeled administrative equations of the present flow problem are converted to a non-dimensional system of ordinary differential equations by applying suitable similarity conversion and then solved numerically by implementing the bvp4c method. The impressions of noteworthy dimensionless parameters on velocity, temperature, concentration distributions, Nusselt number, skin friction and Sherwood number are reported via graphs and tables.

The authors figured out that the developed values of the rotation parameter diminish the temperature but enhance both the radial and angular velocities. Further, the mass and heat transmission rates are better for tetra-hybrid nanofluids than for ternary and hybrid nanofluids.

The present study emphasizes a special type of fluid called the tetra-hybrid nanofluid. The existing literature has not discussed the Maxwell tetra hybrid nanofluid flow through a stretchable rotatory disk with variable electrical conductivity. Besides, the novel aspects of magnetohydrodynamics, thermal radiation, Soret and Dufour effects are also incorporated into the present flow problem.