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To explore a hybrid approach in order to attain optimal cutting conditions proficient of generating adequate dimensional accuracy in combination with virtuous surface finish during turning of commercially pure titanium (CP-Ti) grade 2.

In the present paper, an application of the hybrid fuzzy–VIKOR method has been proposed to estimate an optimal combination of process variables during turning of commercially pure titanium (CP-Ti) grade 2. Three distinct input factors, namely, cutting speed, feed rate and depth of cut, were selected, each varied at three levels. Thus, a series of experiments were performed based on Taguchi's 3-factor-3-level (L₂₇) orthogonal array. The major attention was given to acquire minimum cutting force and flank wear along with good surface finish. The adequacy of the proposed methodology was verified with the help of ANOVA test.

The results of the investigation revealed that the suggested hybrid technique is quite effective, easily understandable and time-saving approach, which can be successfully implemented to solve various problems either of similar or of different kinds.

Increasing demand of qualitative as well as low cost products is identified as the main challenging task in the current competitive market. Therefore, estimation and selection of the most suitable machining environment are of paramount importance in a real-time manufacturing system. Machining process involves both qualitative and quantitative factors, may be conflicting in nature, all to be considered together. Consequently, an appropriate combination of the machining variables is evidently desirable to meet the aforesaid challenges effectively.

In light of the shift in focus from information communication technology (ICT) access (access divide) and skills (skills divide) to the tangible impacts of ICT use (impact divide), a growing number of scholars have called for further investigation into the inter-territorial and multi-dimensional aspects of the digital divide in China. This study aims to address these gaps by examining the disparities across 31 provinces, particularly emphasizing the transition from the traditional access and skills divides to the impact divide.

Multivariate regression analysis extensively investigates the transition from the access and skills divides to the impact divide across 31 provinces. Additionally, ArcGIS software is used to analyze spatial agglomeration and the auto-correlation (Moran-i) and predict mapping patterns in the data corresponding to all three levels of the digital divide.

According to the study's findings, poverty is a significant factor in the digital divide between different regions in China. The research shows that provinces with advanced administrative systems, such as Guangdong, Shanghai, Beijing, Jiangsu, Shandon and Zhejiang, have high scores on the digital development index (DDI). However, regions with poverty-ridden and rural areas, primarily located in southwest, central and western China, tend to have lower DDI scores.

This study offers a novel contribution to the literature by presenting an innovative conceptual framework that explores the impact divide within China's provinces. The authors also address this lacuna in the literature by developing and testing two dimensions to examine the relationships statistically under a wide range of socioeconomic and ICT indicators.

In the era of knowledge economy, the significance of intellectual capital has been increasing globally. Similarly, recent studies have focused on the importance of green intellectual capital in mitigating environmental degradation. However, only a few studies have analysed green intellectual capital and its impacts in the specific case of Pakistan. Hence, this study aims to investigate the effects of green intellectual capital on green innovation adoption in Pakistan’s manufacturing small and medium-size enterprises (SMEs).

We used a data sample of 235 SMEs, gathered from the four manufacturing sectors of Pakistan including: textile, chemical, pharmaceutical and steel and analysed using a multiple regression analysis approach.

The empirical results of this research indicate that green human capital and green structural capital significantly increase green innovation adoption. However, it must be noted that green relational capital has a positive but insignificant impact on green innovation adoption in manufacturing SMEs in Pakistan.

The findings and recommended policy measures of this study are important for the managers of manufacturing SMEs and policymakers to mitigate environmental destruction and achieve sustainable development through green intellectual capital.

Currently, environmental and social concerns have made green innovation more popular among researchers and practitioners around the globe. Developed countries tend to focus more on this issue, compared to developing countries. However, the reality shows that small- to medium-sized enterprises (SMEs) are considered as high contributors to environmental pollution. This study is designed for, and conducted on, SMEs in a developing country, Pakistan. The purpose of this paper is to highlight the main determinants of green innovation adoption in SMEs in Pakistan.

A data sample of 288 SMEs from five different sectors was collected and analyzed using the partial least squares structural equation modeling technique.

The results of the study indicate that organizational and human resource factors, market and customer factors, and government support and technological factors have a positive and significant impact, whereas external partnership and cooperation, and rules and regulatory factors have an insignificant impact on green innovation adoption in SMEs in Pakistan.

The outcomes of the study have important implications for managers as well as for government policy makers regarding framing better policies to promote green practices in SMEs.

The purpose of this paper is to explore a multi-criteria decision-making (MCDM) methodology to determine an optimal combination of process parameters that is capable of generating favorable dimensional accuracy and product quality during turning of commercially pure titanium (CP-Ti) grade 2.

The present paper recommends an optimal combination of cutting parameters with an aim to minimize the cutting force (F_c), surface roughness (R_a), machining temperature (T_m) and to maximize the material removal rate (MRR) after turning of CP-Ti grade 2. This was achieved by the simultaneous optimization of the aforesaid output characteristics (i.e. F_c, R_a, T_m, and MRR) using the MCDM-based TOPSIS method. Taguchi’s L₉ orthogonal array was used for conducting the experiments. The output responses (cutting force: F_c, surface roughness: R_a, machining temperature: T_m and MRR) were integrated together and presented in terms of a single signal-to-noise ratio using the Taguchi method.

The results of the proposed methodology depict that the higher MRR with desirable surface quality and the lower cutting force and machining temperature were observed at a combination of cutting variables as follows: cutting speed of 105 m/min, feed rate of 0.12 mm/rev and depth of cut of 0.5 mm. The analysis of variance test was conducted to evaluate the significance level of process parameters. It is evident from the aforesaid test that the depth of cut was the most significant process parameter followed by cutting speed.

The selection of an optimal parametric combination during the machining operation is becoming more challenging as the decision maker has to consider a set of distinct quality characteristics simultaneously. This situation necessitates an efficient decision-making technique to be used during the machining operation. From the past literature, it is noticed that only a few works were reported on the multi-objective optimization of turning parameters using the TOPSIS method so far. Thus, the proposed methodology can help the decision maker and researchers to optimize the multi-objective turning problems effectively in combination with a desirable accuracy.

Fish are considered as one of the important aquatic animals in the planet. They play a vital role in the nutrient cycle. They can be considered as one of the healthy food for human beings. They can also act as a solution for some of the human health problems. If fish are affected by several diseases, they in turn provide an adverse effect on human health. Therefore, it is very much essential to protect fish from being affected by any diseases.

This paper is mainly focused on the identification of the red spot diseased area in fish. In this work, a fuzzy rule based method (FRBAM) and triangular membership function (TMFN) is used to identify the red spot disease (RSD) in the fish by analyzing several red spot diseased fish (RSDF) images. The canny edge detector is used for intermediate processing of RSDF images.

The proposed method is able to identify the red pixels over the fish by marking the affected area with red color by using a standard RGB model.

The proposed method follows FRBAM and TMFN in order to detect the RSD and canny edge detector for processing of RSDF images. Finally, it is tested using ten different image sizes and the results show its better performance in terms of detection of RSD affected regions of fish and execution time.

This paper aims to model the aerodynamic flow characteristics of NACA0010 for various angle of attacks including stall for incompressible flows using panel methods. This paper also aims to quantify the surface pressure distribution on streamlined bodies and validate the results with analytical Jukouwski method and inverse panel methods that can predict the aerodynamic flow behaviour using the geometric iteration approach.

The 2 D panel method was implemented in Qblade software v.06 which uses the fundamental panel method which rely on source strengths and influence coefficients to determine the velocity and pressure fields on the surface. The software implements the boundary layer or viscous effects to determine the influence on aerodynamic performance at various angles of attack. Jukouwski method is also evaluated for predicting aerodynamic characteristics and is based on the geometric iteration approach. Then complex aerodynamic flow potentials are determined based on the source strengths which are used to predict the pressure and velocity fields.

At low to moderate angles of attack, panel and Jukouwski methods predict similar results for surface pressure coefficients comparable to Hess and Smith inverse method. In comparison to panel method, results from the Jukouwski mapping method predicted the pressure coefficient conservatively for the same free stream conditions. With increase in Reynolds number, lift coefficient and aerodynamic performance improved significantly for un-tripped aerofoil when stall angle is approached when compared to tripped aerofoil.

This study demonstrated that panel methods have higher efficacy in terms of computational time or resources and thus can provide benefits to many real-world aircraft or aerospace design applications.

Even though panel and Jukouwski methods have been studied extensively in the past, this paper demonstrates the efficacy of both methods for modelling aerodynamic flows that range between moderate to high Reynolds number which are critical for many aircraft applications. Both methods have been validated with analytical and inverse design methods which are able to predict aerodynamic flow characteristics for simple bluff bodies, streamlined aerofoils as well as bio-inspired corrugated aerofoils.

Diesel engine can produce power more efficiently with lower exhaust emissions when operated at optimum input parameter settings. To achieve this goal, the purpose of this paper is to optimize the input parameters of diesel engine which will lead to optimum performance and exhaust emissions.

To achieve the goal of improving diesel engine performance and exhaust emissions, four input parameters were considered in the study. Five different levels of each input parameter were taken. Four response variables under no load, half load and full load conditions were recorded. Experiments were performed in random manner according to selected Taguchi L25 orthogonal array. The data were analyzed using grey relational analysis coupled with principal component analysis. Analysis of S/N ratio was performed to obtain the optimum combination of input parameters. The grey relational grade at optimum setting of the input parameters was obtained by regression analysis.

Results of the current research work give the optimum input parameter settings for no load, half load and full load conditions of diesel engine. Engine produces power more efficiently with low exhaust emissions when operated at these optimum settings.

In view of the compliance to the stringent air pollution norms of the nations and fast depleting fossil fuels, it is of the utmost importance to design and operate the engine in the optimum range of its input parameters so that it produces more power with low exhaust emissions. This paper aims at optimizing input parameters of diesel engine to improve performance and exhaust emissions. Results of the study presented in this paper are significantly useful for diesel engine-related researchers and professionals.

From the literature review, it appears that only few researchers have conducted studies pertaining to the optimization of the input parameters of diesel engine to improve performance or exhaust emissions. Although few studies related to the optimization of compression ratio, fuel injection timing, fuel injection pressure and air pressure have been reported, no work related to optimization of temperature and pressure of turbocharged air has been reported. Therefore, the main focus of the current research work is on optimizing the charge air temperature and pressure with respect to performance and exhaust emissions.

The purpose of this study is to analyze research output in the naturopathy field at the global level and to examine the various trends in scientific literature available on naturopathy using bibliometric analysis.

The data was collected from the SciVerse Scopus database published from 2000 through 2019. The search was conducted using Medical Subject headings entry terms, i.e. “Naturopathy” OR “Naturopathic Medicine” using the “Document” search option. The search results comprised of documents that had these above search terms in their article title, abstract and keywords. The retrieved documents were then analyzed concerning different parameters like the growth of publications, authorship patterns, productive countries and institutions, highly cited papers, top prolific authors, funding agencies and document types.

The results of this study reveal that a total of 1,099 documents were published during 20-year time span. The most preferred publication type is research articles 683 (62.14%). Germany, USA, Australia, India and Canada were the most productive countries in terms of the number of scientific documents. The findings also show that the most preferred journal in the field of naturopathy is MMW Fortschritte der Medizin, with 115 documents followed by Journal of Alternative and Complementary Medicine with 58 documents. In contrast, the journal BMC Complementary and Alternative Medicine had the highest citations per paper (17.85). For the 20-year study period, the average value for the degree of collaboration was calculated as 0.57, indicating 54% of the total publications in naturopathy were multi-authored. The value of the collaboration coefficient (CC) signifies the levels of multi-authored papers. CC was highest in the year 2019 (0.55) indicating that the publications were contributed in collaboration rather than in isolation and the number of multi-authored/mega-authored papers outnumbered the single authors in the collection of all authors in the year 2019. Bastyr University, USA was the most productive Institution. Journal articles were the most preferred form of publication.

This study traces various trends in the research behavior and preferences of researchers in the field of naturopathy. It thus can be of immense help to identify strong areas in naturopathy research. Further, this study will help the librarians to identify the core/preferred journals in naturopathy. 

This paper makes an endeavor to carry an extensive bibliometric study that provides an overview of emerging trends in naturopathy research.

In resolution A/RES/74/4, the U.N. Nations General Assembly adopted the Decade of Action to accelerate the achievement of the SDGs by 2030. The Decade of Action calls to improve actual efforts to accomplish the 2030 agenda for governments, civil society, the private sector, and other stakeholders. This call is the last opportunity we have to reach SDG9. Still, unfortunately, the COVID-19 pandemic has severely affected all industrial sectors, which is unlikely to achieve inclusive and sustainable industrialisation by 2030. This chapter illustrates the adverse effects that the construction, manufacturing, and hospitality industries have suffered since the beginning of the COVID-19 pandemic and how they gradually have returned to the new normal. It also shows the case of the industry that could be considered the ‘champion in the covid era’, the high-tech industry. Predominantly in covid times, high-tech firms have been a synonym for technological innovation, which is an absolute necessity to encourage competitiveness in all industrial sectors, mainly in essential activities. Finally, the chapter is closed with an invitation to reflect on the fundamental principle of SDG9, which is sustainable industrialisation, but above all, inclusivity. SDG9 cannot be considered achieved until its benefits are transferred to the countries in the global south.