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The purpose of this study is to investigate the motivations and barriers behind the adoption of bike-sharing services, explore the influence of individual values and environmental knowledge on bike-sharing adoption and analyze the relationship between reasons, attitude and intention to utilize bike-sharing.

The study initially conducted a semi-structured interview with 19 bike-sharing users and performed a thematic analysis to identify the context-specific motivators and barriers. The identified factors were then incorporated into the behavioral reasoning theory (BRT) framework and quantitatively examined using the data gathered from 412 Indian bike-sharing users.

The findings outlined the complex reasoning process underlying bike-sharing adoption and how environmental value and attitude are related to the reasons. Further, the study examined the moderating impact of environmental knowledge, which was overlooked in previous studies.

The study provides valuable suggestions to bike-sharing businesses, which helps them to induce facilitators and remove barriers.

Behavioral research in bike-sharing is in its embryonic stage. This is one of the initial attempts to address this knowledge deficit by comprehensively examining the factors affecting bike-sharing intention through the theoretical lens of BRT.

The purpose of this paper is to initially perform Senti-WordNet (SWN)- and point wise mutual information (PMI)-based polarity computation and based polarity updation. When the SWN polarity and polarity mismatched, the vote flipping algorithm (VFA) is employed.

Recently, in domains like social media(SM), healthcare, hotel, car, product data, etc., research on sentiment analysis (SA) has massively increased. In addition, there is no approach for analyzing the positive or negative orientations of every single aspect in a document (a tweet, a review, as well as a piece of news, among others). For SA as well as polarity classification, several researchers have used SWN as a lexical resource. Nevertheless, these lexicons show lower-level performance for sentiment classification (SC) than domain-specific lexicons (DSL). Likewise, in some scenarios, the same term is utilized differently between domain and general knowledge lexicons. While concerning different domains, most words have one sentiment class in SWN, and in the annotated data set, their occurrence signifies a strong inclination with the other sentiment class. Hence, this paper chiefly concentrates on the drawbacks of adapting domain-dependent sentiment lexicon (DDSL) from a collection of labeled user reviews and domain-independent lexicon (DIL) for proposing a framework centered on the information theory that could predict the correct polarity of the words (positive, neutral and negative). The proposed work initially performs SWN- and PMI-based polarity computation and based polarity updation. When the SWN polarity and polarity mismatched, the vote flipping algorithm (VFA) is employed. Finally, the predicted polarity is inputted to the mtf-idf-based SVM-NN classifier for the SC of reviews. The outcomes are examined and contrasted to the other existing techniques to verify that the proposed work has predicted the class of the reviews more effectually for different datasets.

There is no approach for analyzing the positive or negative orientations of every single aspect in a document (a tweet, a review, as well as a piece of news, among others). For SA as well as polarity classification, several researchers have used SWN as a lexical resource. Nevertheless, these lexicons show lower-level performance for sentiment classification (SC) than domain-specific lexicons (DSL). Likewise, in some scenarios, the same term is utilized differently between domain and general knowledge lexicons. While concerning different domains, most words have one sentiment class in SWN, and in the annotated data set their occurrence signifies a strong inclination with the other sentiment class.

The proposed work initially performs SWN- and PMI-based polarity computation, and based polarity updation. When the SWN polarity and polarity mismatched, the vote flipping algorithm (VFA) is employed.

The purpose of this paper is to investigate the momentum, heat and mass transfer characteristics of magnetic-nanofluid flow past a vertical plate embedded in a porous medium filled with ferrous nanoparticles. The analysis is carried out in the presence of pertinent physical parameters such as aligned magnetic field, thermal radiation, chemical reaction, radiation absorption, heat source/sink.

The flow governing PDEs are transformed into ODEs using appropriate conversions. Further, the set of ODEs is solved analytically using the perturbation technique. The flow quantities such as velocity, thermal and concentration fields are discussed under the influence of above-mentioned pertinent physical parameters with the assistance of graphical depictions. Moreover, the friction factor, local Nusselt and Sherwood number are discussed in tabular form.

The results indicate that flow and thermal transport phenomenon is more effective in the case of the aligned magnetic field as compared with the transverse magnetic field. Also, the nanoparticle volume fraction plays a vital role in controlling the wall friction and heat transfer performance. The validation of the obtained results is done by comparing them with the results of various numerical techniques, and hence found them in excellent agreement.

In present days, the external magnetic fields are very effective to set the thermal and physical properties of magnetic-nanofluids and regulate the flow and heat transfer characteristics. The strength of the applied magnetic field affects the thermal conductivity of magnetic-nanofluids and makes it aeolotropic. With this incentive, the authors investigated the flow and heat transfer characteristics of electrically conducting magnetic-nanofluids over a vertical surface embedded in a porous medium. The authors discussed the dual nature of ferrous-water nanofluid in the presence of aligned magnetic field and transverse magnetic field cases. The influence of several physical parameters on velocity, thermal and concentration field converses with the succour of graphs.

The zero-waste lifestyle (ZWL) is considered a reasonable step towards controlling waste generation and minimizing the consequences of human activities on the environment. The main aim of this study is to examine the behavioral antecedents of ZWL.

The study draws on the theoretical underpinnings of the theory of planned behavior (TPB) and the norm activation model (NAM) to develop a conceptual framework to understand the antecedents to ZWL. A cross-sectional survey among 349 randomly-selected consumers provided data analyzed with the partial least square-structural equation modeling (PLS-SEM) methodology.

The results demonstrate that personal norms, attitude, subjective norms and perceived behavioral control positively influenced the intention to adopt ZWL. Additionally, the study showed that the awareness of consequences influenced personal norms, attitudes and subjective norms. However, the study identified an intention–behavior gap in adopting ZWL.

This study serves as a pioneering exploration of the behavioral factors that impact the adoption of ZWL. Additionally, the paper endeavors to elucidate the underlying reasons behind the intention–behavior gap within this particular context. Consequently, the study offers substantial theoretical and practical implications aimed at promoting and fostering greater adoption of ZWL practices.

The purpose of this paper is to study the flow, heat and mass transfer of MHD Casson nanofluid due to an inclined stretching sheet using similarity transformation, the governing PDE’S equations of flow, heat and mass transfer are converted into ODE’S. The resulting non-linear ODE’S are solved numerically using an implicit finite difference method, which is known as Kellor-box method. The effects of various governing parameters on velocity, temperature and concentration are plotted for both Newtonian and non-Newtonian cases. The numerical values of skin friction, Nusselt number and Sherwood number are calculated and tabulated in various tables for different values of physical parameters. It is noticed that the effect of angle of inclination enhances the temperature and concentration profile whereas velocity decreases. The temperature decreases due to the increase in the parametric values of Pr and Gr due to thickening in the boundary layer.

Numerical method is applied to find the results.

Flow and heat transfer analysis w.r.t various flow and temperature are analyzed for different values of the physical parameters.

The numerical values of skin friction, Nusselt number and Sherwood number are calculated and tabulated in various tables for different values of physical parameters.

The study of the boundary layer flow, heat and mass transfer is important due to its applications in industries and many manufacturing processes such as aerodynamic extrusion of plastic sheets and cooling of metallic sheets in a cooling bath.

Here in this paper the authors have investigated the MHD boundary layer flow of a Casson nanofluid over an inclined stretching sheet along with the Newtonian nanofluid as a limited.

Inorganic pigments have been widely investigated due to their chemical stability such as resistance to chemical attacks by acids and alkalis, excellent hardness and high temperature stability. Cr_1.3Fe_0.7O₃ which is considered as a ceramic nanopigment also seems to be a highly efficient photovoltaic material. The paper aims to discuss these issues.

In this work, the paper reports the synthesis of a novel and high purity Cr_1.3Fe_0.7O₃ nanopigment via sol-gel process using stearic acid as complexing agent. The method includes formation of an organic precursor with metallic cations homogeneously distributed all over the matrix. Sample characterisations were performed by X-ray diffraction, electron microscopy, UV-vis diffused reflectance spectra and photoluminescence. The transport properties and colour characteristics were also investigated by spectroscopic and technological characterisation of the synthesised nanoparticles.

The prepared nanopigments were uniform in distribution and a spherical morphology with an average size of about 200 nm was observed. Cr_1.3Fe_0.7O₃ nanoparticles showed a direct band gap value of 2.85 eV and the colour efficiency of the nanopigments evaluated by colourimetric analysis resulted characteristic values of L*=39.96, a*=3.67 and b*=3.12.

This method for synthesis of nanopigments is novel and could be employed for various applications in synthesis of wide variety of nanoceramics.

This study aims to discuss the numerical solutions of weakly singular Volterra and Fredholm integral equations, which are used to model the problems like heat conduction in engineering and the electrostatic potential theory, using the modified Lagrange polynomial interpolation technique combined with the biconjugate gradient stabilized method (BiCGSTAB). The framework for the existence of the unique solutions of the integral equations is provided in the context of the Banach contraction principle and Bielecki norm.

The authors have applied the modified Lagrange polynomial method to approximate the numerical solutions of the second kind of weakly singular Volterra and Fredholm integral equations.

Approaching the interpolation of the unknown function using the aforementioned method generates an algebraic system of equations that is solved by an appropriate classical technique. Furthermore, some theorems concerning the convergence of the method and error estimation are proved. Some numerical examples are provided which attest to the application, effectiveness and reliability of the method. Compared to the Fredholm integral equations of weakly singular type, the current technique works better for the Volterra integral equations of weakly singular type. Furthermore, illustrative examples and comparisons are provided to show the approach’s validity and practicality, which demonstrates that the present method works well in contrast to the referenced method. The computations were performed by MATLAB software.

The convergence of these methods is dependent on the smoothness of the solution, it is challenging to find the solution and approximate it computationally in various applications modelled by integral equations of non-smooth kernels. Traditional analytical techniques, such as projection methods, do not work well in these cases since the produced linear system is unconditioned and hard to address. Also, proving the convergence and estimating error might be difficult. They are frequently also expensive to implement.

There is a great need for fast, user-friendly numerical techniques for these types of equations. In addition, polynomials are the most frequently used mathematical tools because of their ease of expression, quick computation on modern computers and simple to define. As a result, they made substantial contributions for many years to the theories and analysis like approximation and numerical, respectively.

This work presents a useful method for handling weakly singular integral equations without involving any process of change of variables to eliminate the singularity of the solution.

To the best of the authors’ knowledge, the authors claim the originality and effectiveness of their work, highlighting its successful application in addressing weakly singular Volterra and Fredholm integral equations for the first time. Importantly, the approach acknowledges and preserves the possible singularity of the solution, a novel aspect yet to be explored by researchers in the field.

Intellectual capital (IC) has been considered as a valuable asset in the wealth creation and sustainability of the company; however, limited and mixed results are found on its impact on firm financial performance and market value (MV). This paper aims to investigate the influence of IC toward MV and financial performance of publicly listed firms in Indonesia. In addition, this research also presents the comparison of the high and low level of knowledge industries regarding IC performance.

A balanced panel data of 127 firms from 12 industries in Indonesia during 2010 until 2017 was evaluated using dynamic panel regression and administering a well-developed Blundell–Bond instrument (dynamic panel data estimator) to account for endogeneity problem.

The results of this study showed that IC had a significant and positive impact on firm performance. Specifically, structural capital efficiency and capital employed (CE) efficiency have been contributed to the value creation of the company, after controlling for firm size and type of industry. Different to the theoretical expectation, this research found no significant relationship between IC and MV of the firm. However, when the sample was clustered into high-level and low-level knowledge industry, CE displayed positive and significant relationship in high-level industry.

This research contributes to IC research by having a larger sample of Indonesian firms from all industries except banks and financial institutions and using Modified Value Added Intellectual Capital measurement model. To address the endogeneity problem, dynamic panel regression using system generalized method of moment was applied.

The purpose of this paper is to focus on the cost-effective and environmentally sustainable operation of thermal power systems to allocate optimum active power generation resultant for a feasible solution in diverse load patterns using the grey wolf optimization (GWO) algorithm.

The economic dispatch problem is formulated as a bi-objective optimization subjected to several operational and practical constraints. A normalized price penalty factor approach is used to convert these objectives into a single one. The GWO algorithm is adopted as an optimization tool in which the exploration and exploitation process in search space is carried through encircling, hunting and attacking.

A linear interpolated price penalty model is developed based on simple analytical geometry equations that perfectly blend two non-commensurable objectives. The desired GWO algorithm reports a new optimum thermal generation schedule for a feasible solution for different operational strategies. These are better than the earlier reports regarding solution quality.

The proposed method seems to be a promising optimization tool for the utilities, thereby modifying their operating strategies to generate electricity at minimum energy cost and pollution levels. Thus, a strategic balance is derived among economic development, energy cost and environmental sustainability.

A single optimization tool is used in both quadratic and non-convex cost characteristics thermal modal. The GWO algorithm has discovered the best, cost-effective and environmentally sustainable generation dispatch.

The purpose of this paper is to minimize the mean flow time in open shop scheduling problem (OSSP). The scheduling problems consist of n jobs and m machines, in which each job has O operations. The processing time for 50 OSSP was generated using a linear congruential random number.

Different evolutionary algorithms are used to minimize the mean flow time of OSSP. This research study used simulated annealing (SA), Discrete Firefly Algorithm and a Hybrid Firefly Algorithm with SA. These methods are referred as A1, A2 and A3, respectively.

A comparison of the results obtained from the three methods shows that the Hybrid Firefly Algorithm with SA (A3) gives the best mean flow time for 76 percent instances. Also, it has been observed that as the number of jobs increases, the chances of getting better results also increased. Among the first 25 problems (i.e. job ranging from 3 to 7), A3 gave the best results for 13 instances, i.e., for 52 percent of the first 25 instances. While for the last 25 problems (i.e. Job ranging from 8 to 12), A3 gave the best results for all 25 instances, i.e. for 100 percent of the problems.

From the literature it has been observed that no researchers have attempted to solve OOSPs using Firefly Algorithm (FA). In this research work an attempt has been made to apply the FA and its hybridization to solve OSSP. Also the research work carried out in this paper can also be applied for a real-time Industrial problem.