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While rapid increase in demand for foods but limited availability of croplands has forced to adopt input-intensive farming practices to increase yield, there are serious long-term ecological implications including degradation of biodiversity. It is increasingly recognised that ensuring agricultural sustainability under the changing climatic conditions requires a change in the production system along with necessary policies and institutional arrangements. In this context, this chapter examines if climate-smart agriculture (CSA) can facilitate adaptation and mitigation practices by improving resource utilisation efficiency in India. Such an attempt has special significance as the existing studies have very limited discussions on three main aspects, viz., resource productivity, adaptation practices and mitigation strategies in a comprehensive manner. Based on insights from the existing studies, this chapter points out that CSA can potentially make significant contribution to enhancing resource productivity, adaptation practices, mitigation strategies and food security, especially among the land-constrained farmers who are highly prone to environmental shocks. In this connection, staggered trench irrigation structure has facilitated rainwater harvesting, local irrigation and livelihood generation in West Bengal. However, it is necessary to revisit the existing approaches to promotion of CSA and dissemination of information on the design of local adaptation strategies. This chapter also proposes a change in the food system from climate-sensitive to CSA through integration of technologies, institutions and policies.

The performance of public sector institutions has always been contentious – this is as old as the system of government itself and its provision of collective goods, irrespective of whether they are tangible or intangible. In the context of South Africa, with its ever-increasing political competitiveness, this chapter assesses political leadership and the African philosophy of Ubuntu or humanism in improving public sector performance management in the country. It does so by addressing certain distinct questions: What is the state of public sector performance and leadership in South Africa? What have scholars contributed in linking public sector performance, and the politics and public administration dichotomy? Are the Batho Pele principles, underpinned by Ubuntu, a worthy notion on which to pillar African political leadership? By adopting an interpretivist, qualitative research design, the study reflects on the essence of a public administration that is effective in delivering political goods and managing the performance of bureaucracies and the political leadership therein. This chapter argues that the performance of public administrations remains a “wicked” problem in South Africa as political populism is on the rise in the country. However, the argument is made that with “good” political leadership – which naturally and effectively encompasses the philosophy of Ubuntu and which understands and mobilizes statecraft – great strides can be made beyond the current rhetoric.

This paper aims to focus on the basic principle of WO₃ gas sensors to achieve high gas-sensing performance with good stability and repeatability. Metal oxide-based gas sensors are widely used for monitoring toxic gas leakages in the environment, industries and households. For better livelihood and a healthy environment, it is extremely helpful to have sensors with higher accuracy and improved sensing features.

In the present review, the authors focus on recent synthesis methods of WO₃-based gas sensors to enhance sensing features towards toxic gases.

This work has proved that the synthesis method led to provide different morphologies of nanostructured WO₃-based material in turn to improve gas sensing performance along with its sensing mechanism.

In this work, the authors reviewed challenges and possibilities associated with the nanostructured WO₃-based gas sensors to trace toxic gases such as ammonia, H₂S and NO₂ for future research.

Metal matrix composites (MMC) has been a section which gives an overview of composite materials and owing to those exceptional physical and mechanical properties, particulate-reinforced aluminum MMCs have gained increasing interest in particular engineering applications. Owing to the toughness and abrasive quality of reinforcement components such as silicon carbide (SiC) and titanium carbide (TiC), such materials are categorized as difficult materials for machining. The work aims to develop the model for evaluating the machinability of the materials via the response surface technique by machining three distinct types of hybrid MMCs.

The combined effects of three machining parameters, namely “cutting speed” (s), “feed rate” (f) and “depth of cut” (d), together with three separate composite materials, were evaluated with the help of three performance characteristics, i.e. material removal rate (MRR), cutting force (CF) and surface roughness (SR). Response surface methodology and analysis of variance (ANOVA) both were initially used for analyzing the machining parameters results.

The contours were developed to observe the combined process parameters along with their correlations. The process variables were concurrently configured using grey relational analysis (GRA) and the composite desirability methodology. Both the GRA and composite desirability approach obtained similar results.

The results obtained in the present paper will be helpful for decision-makers in manufacturing industries, who work on metal cutting area especially composites, to select the suitable solution by implementing the Grey Taguchi and modeling techniques.

The originality of this research is to identify the suitability of process parameters combination based on the obtained research results. The optimization of machining parameters in turning of hybrid metal matrix composites is carried out with two different methods such as Grey Taguchi and composite desirability approach.

Buongiorno’s type nanofluid mass and heat transport appearances inside a cavity filled with gyrotactic microorganisms by captivating thermal radiation is analyzed in the present work. Finite element investigation is instigated to examine the converted momentum, temperature, concentration of microorganisms and concentration of nanofluid equations numerically.

Finite element investigation is instigated to examine the converted momentum, temperature, concentration of microorganisms and concentration of nanofluid equations numerically.

The sway of these influenced parameters on standard rates of heat transport, nanoparticles Sherwood number and Sherwood number of microorganisms is also illustrated through graphs. It is perceived that the rates of heat transport remarkably intensifies inside the cavity region with amplifying thermophoresis number values.

The research work carried out in this paper is original and no part is copied from others’ work.

This study provides a comprehensive framework of adaptation in triadic business relationship settings in the service sector. The framework is based on the industrial network approach (see, e.g., Axelsson & Easton, 1992; Håkansson & Snehota, 1995a). The study describes how adaptations initiate, how they progress, and what the outcomes of these adaptations are. Furthermore, the framework takes into account how adaptations spread in triadic relationship settings. The empirical context is corporate travel management, which is a chain of activities where an industrial enterprise, and its preferred travel agency and service supplier partners combine their resources. The scientific philosophy, on which the knowledge creation is based, is realist ontology. Epistemologically, the study relies on constructionist processes and interpretation. Case studies with in-depth interviews are the main source of data.

The purpose of this paper is to know the influence of heat generation/absorption and slip effects on heat and mass transfer flow of carbon nanotubes – water-based nanofluid over a rotating disk. Two types of carbon nanotubes, single and multi-walled, are considered in this analysis.

The non-dimensional system of governing equations is constructed using compatible transformations. These equations together with boundary conditions are solved numerically by using the most prominent Finite element method. The influence of various pertinent parameters such as magnetic parameter (0.4 – 1.0), nanoparticle volume fraction parameter (0.1 – 0.6), porosity parameter (0.3 – 0.6), radiation parameter (0.1 – 0.4), Prandtl number (2.2 – 11.2), space-dependent (−3.0 – 3.0), temperature-dependent (−3.0 – 1.5), velocity slip parameter (0.1 – 1.0), thermal slip parameter (0.1 – 0.4) and chemical reaction parameter (0.3 – 0.6) on nanofluids velocity, temperature and concentration distributions, as well as rates of velocity, temperature and concentration is calculated and the results are plotted through graphs and tables. Also, a comparative analysis is carried out to verify the validation of the present numerical code and found good agreement.

The results indicate that the temperature of the fluid elevates with rising values of nanoparticle volume fraction parameter. Furthermore, the rates of heat transfer rise from 4.8% to 14.6% when carbon nanotubes of 0.05 volume fraction are suspended into the base fluid.

The work carried out in this analysis is original and no part is copied from other sources.

This study has mainly aimed to compare and contrast two completely different image processing algorithms that are very adaptive for detecting prostate cancer using wearable Internet of Things (IoT) devices. Cancer in these modern times is still considered as one of the most dreaded disease, which is continuously pestering the mankind over a past few decades. According to Indian Council of Medical Research, India alone registers about 11.5 lakh cancer related cases every year and closely up to 8 lakh people die with cancer related issues each year. Earlier the incidence of prostate cancer was commonly seen in men aged above 60 years, but a recent study has revealed that this type of cancer has been on rise even in men between the age groups of 35 and 60 years as well. These findings make it even more necessary to prioritize the research on diagnosing the prostate cancer at an early stage, so that the patients can be cured and can lead a normal life.

The research focuses on two types of feature extraction algorithms, namely, scale invariant feature transform (SIFT) and gray level co-occurrence matrix (GLCM) that are commonly used in medical image processing, in an attempt to discover and improve the gap present in the potential detection of prostate cancer in medical IoT. Later the results obtained by these two strategies are classified separately using a machine learning based classification model called multi-class support vector machine (SVM). Owing to the advantage of better tissue discrimination and contrast resolution, magnetic resonance imaging images have been considered for this study. The classification results obtained for both the SIFT as well as GLCM methods are then compared to check, which feature extraction strategy provides the most accurate results for diagnosing the prostate cancer.

The potential of both the models has been evaluated in terms of three aspects, namely, accuracy, sensitivity and specificity. Each model’s result was checked against diversified ranges of training and test data set. It was found that the SIFT-multiclass SVM model achieved a highest performance rate of 99.9451% accuracy, 100% sensitivity and 99% specificity at 40:60 ratio of the training and testing data set.

The SIFT-multi SVM versus GLCM-multi SVM based comparison has been introduced for the first time to perceive the best model to be used for the accurate diagnosis of prostate cancer. The performance of the classification for each of the feature extraction strategies is enumerated in terms of accuracy, sensitivity and specificity.

To examine a possible link between substance use and risky sexual behaviour, a cross‐sectional study was conducted among 357 inmates across four South African prisons involved in a pre‐release intervention programme for parolees. About 93% of the participants reported using alcohol and 52% used marijuana prior to imprisonment, while 56% reported previous occurrence of sexually transmitted infections (STIs). Logistic regression analyses explored the impact of substance use on intention to reduce risky sexual behaviour. Age and inconsistent use of condoms were positively associated with having an STI prior to incarceration, while reported alcohol and marijuana intake had no effect. Never using condoms before was highly associated with lower intention to engage in preventive behaviours upon release. It can be concluded that inmates demonstrate high levels of substance use and engagement in risky sexual behaviours. Targeted pre‐release substance abuse interventions are essential to reduce the burden of disease amongst offenders.

The purpose of this paper is to emphasize on the impact of endoscope in MHD peristaltic flow of Carreau fluid. Heat and mass transfer phenomena are comprised of Soret and Dufour effects. Influences of mixed convection and viscous dissipation are also accounted. Wall properties and convective boundary conditions are used.

The Navier–Stokes and energy equations used the lubrication approach. The reduced system of equations is executed numerically. The graphical illustration of velocity, temperature, concentration and heat transfer coefficient for various emerging parameters is discussed.

The response of Weissenberg number and power law index is decaying toward velocity and temperature. Moreover impression of Soret and Dufour number on temperature is quite reverse to that of concentration.

The titled problem with the various considered effects has not been solved before, and it is of special importance in various industries. The problem is original.