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This study investigates the dependencies between the Global Food Security Index (GFSI) and its affordability-related indicators using Bayesian belief network (BBN) models. The research also aims to prioritise these indicators within a probabilistic network setting.

The research utilises BBN models to analyse data from 113 countries in 2022. Nine indicators related to food affordability, including income inequality, safety net programmes and trade freedom, are examined to understand their impact on food security. The methodology involves statistical modelling and analysis to identify critical factors influencing food security and to provide a comprehensive understanding of the global food affordability landscape.

The study reveals that income inequality, the presence and efficacy of safety net programmes and the degree of trade freedom are significant determinants of food affordability and overall food security outcomes. The analysis reveals marked disparities in performance across different countries, highlighting the need for context-specific interventions. The findings suggest that improving safety net programmes, implementing trade policy reforms and addressing income inequality are crucial for enhancing food affordability and security.

This research contributes to the literature by using BBN models to comprehensively analyse the relationship between the GFSI and affordability-related indicators. The study provides novel insights into how different socioeconomic factors influence food security across a diverse range of countries. The study offers actionable recommendations for policymakers to address food security challenges effectively, thereby supporting the development of more equitable and resilient food systems globally.

The purpose of this paper is to apply security policies over the mobile ad hoc networks. A mobile ad hoc network refers to infrastructure-less, persistently self-designing systems; likewise, there is a noteworthy innovation that supplies virtual equipment and programming assets according to the requirement of mobile ad hoc network.

It faces different execution and effectiveness-based difficulties. The major challenge is the compromise of performance because of unavailable resources with respect to the MANET. In order to increase the MANET environment’s performance, various techniques are employed for routing and security purpose. An efficient security module requires a quality-of-service (QoS)-based security policy. It performs the task of routing and of the mobile nodes, and it also reduces the routing cost by finding the most trusted node.

The experimental results specify that QoS-based security policy effectively minimizes the cost, response time as well as the mobile makespan (routing cost and response time) of an application with respect to other existing approaches.

In this paper, the authors proposed an enhancement of Cross Centric Intrusion Detection System named as PIHNSPRA Routing Algorithm (PIHNSPRA).

It maps the security with the secure IDS communication and distributes the packets among different destinations, based on priority. This calculation is proposed for the purpose of routing and security by considering greatest throughput with least routing cost and reaction time.

When the concept is applied to practical applications. Quality of Service introduced in the proposed research reduces the cost of routing and improves the throughput.

The proposed calculation is tested by NS2 simulator and the outcomes showed that the execution of the calculation is superior to other conventional algorithms.

Eat Right India (ERI) is a flagship initiative by the Food Safety and Standards Authority of India to transform the food system to ensure sustainable, safe and healthy food for all. The study summarizes the strategies, policies and programs using the NOURISHING framework.

This study identifies and reviews documents related to ERI through a comprehensive search of research literature, policy documents and information available from the institutional websites. The NOURISHING framework, which proposes a methodology to categorize, report and monitor actions to promote healthy eating, is used as a guiding framework.

Upon analyzing various strategies put forward by the ERI initiative, it was found that there are many inter-sectoral collaborations, successful institutionalizations and behavioral interventions implemented through the initiative. However, there are a few areas that require attention, which include health taxation, children's exposure to unhealthy food marketing, regulations in food advertisements and the incentivization of retailers and consumers for healthy food delivery and consumption. There is a need for a holistic approach with a congruence of health and food systems in the backdrop of a strong and efficient policy and regulatory framework to tackle the threat of Non-communicable diseases (NCD).

This article contributes to a significant discussion about transforming food systems to tackle (NCDs). It summarizes the existing initiatives in India for establishing healthy food environments and also suggests a few strategies for taking it forward. The study calls the policymakers to action for restructuring the food and health system into resilient, contextually relevant and interoperable mechanisms to address the threat of NCDs.

Purpose: This chapter aims to evaluate the impact of money laundering and terrorism financing on the Indian economy and to study the effectiveness of prevention of money laundering acts and terrorist financing as per the guidance of the financial protection task force.

Need for the study: Developing countries like India have been more vulnerable to terrorism and financial scams over the last four decades. Despite the establishment of regulating bodies and anti-money laundering acts, this problem continued to be a national threat. Therefore, examining the impact of money laundering and terrorism finance on the Indian economy is necessary.

Methodology: This study is based on secondary data gathered from the web portals of government agencies and international organisations dealing with money laundering and terror funding. Newspapers, journals, and annual reports are reviewed to identify the modus operandi of money laundering operators and their impact on the economy.

Findings: Money laundering and terrorism financing significantly threaten the Indian economy and national security. Despite different anti-money laundering laws and multiple regulating authorities, the system has pitfalls that allow economic fraud and money transactions for terrorist activities. There is a need for cyber security, and integrated enforcement agencies to combat money laundering at national and international levels.

Practical implications: This study would be helpful for academicians and policymakers to understand the nexus of money laundering and terrorism financing and its impacts on the Indian economy.

The purpose of this review is to comprehensively consider the material properties and processing of additive titanium alloy and provide a new perspective for the robotic grinding and polishing of additive titanium alloy blades to ensure the surface integrity and machining accuracy of the blades.

At present, robot grinding and polishing are mainstream processing methods in blade automatic processing. This review systematically summarizes the processing characteristics and processing methods of additive manufacturing (AM) titanium alloy blades. On the one hand, the unique manufacturing process and thermal effect of AM have created the unique processing characteristics of additive titanium alloy blades. On the other hand, the robot grinding and polishing process needs to incorporate the material removal model into the traditional processing flow according to the processing characteristics of the additive titanium alloy.

Robot belt grinding can solve the processing problem of additive titanium alloy blades. The complex surface of the blade generates a robot grinding trajectory through trajectory planning. The trajectory planning of the robot profoundly affects the machining accuracy and surface quality of the blade. Subsequent research is needed to solve the problems of high machining accuracy of blade profiles, complex surface material removal models and uneven distribution of blade machining allowance. In the process parameters of the robot, the grinding parameters, trajectory planning and error compensation affect the surface quality of the blade through the material removal method, grinding force and grinding temperature. The machining accuracy of the blade surface is affected by robot vibration and stiffness.

This review systematically summarizes the processing characteristics and processing methods of aviation titanium alloy blades manufactured by AM. Combined with the material properties of additive titanium alloy, it provides a new idea for robot grinding and polishing of aviation titanium alloy blades manufactured by AM.

With the diversification of modelling activities encouraged by versatile modelling tools, handling their datasets has become a formidable problem. A further impetus stems from the emergence of the real‐time forecasting culture, transforming data embedded in computer programs of one‐off modelling activities of the 1970s‐1980s into dataset assets, an important feature of modelling since the 1990s, where modelling has emerged as a practice with a pivotal role to data transactions. The scope for data is now vast but in legacy data management practices datasets are fragmented, not transparent outside their native software systems, and normally “monolithic”. Emerging initiatives on published interfaces will make datasets transparent outside their native systems but will not solve the fragmentation and monolithic problems. These problems signify a lack of science base in data management and as such it is necessary to unravel inherent generic structures in data. This paper outlines root causes for these problems and presents a tentative solution referred to as “systemic data management”, which is capable of solving the above problems through the assemblage of packaged data. Categorisation is presented as a packaging methodology and the various sources contributing to the generic structure of data are outlined, e.g. modelling techniques, modelling problems, application areas and application problems. The opportunities offered by systemic data management include: promoting transparency among datasets of different software systems; exploiting inherent synergies within data; and treating data as assets with a long‐term view on reuse of these assets in an integrated capability.

People start to acknowledge, accept and adopt fintech applications due to its flexibilities, compatibility, ease to use, security and usefulness. A growing body of research reveals a positive perception of micro-enterprises towards fintech instruments. Looking at the potential of the fintech platforms and tools in Malaysia, the purpose of this study is to look at the readiness of micro-entrepreneurs towards using it as a medium in generating more income and profit for their business.

This study uses a quantitative approach with 200 questionnaires distributed to micro-entrepreneurs in Malaysia. IBM SPSS was used to perform a preliminary analysis of the data (descriptive analysis), then partial least squares-structural equation modelling SmartPLS is used to test the hypothesised relationships.

This study found perceived ease of use H1 (β = 0.523, p < 0.01) and trust H4 (β = 0.211, p < 0.10) play an important role in readiness to adopt fintech. Whereas, security H3 (β = 0.068) and perceived usefulness, H2 (β = 0.120) are insignificant (rejected).

This study provides evidence on the factors that contribute most towards the inclination to use fintech application among micro-entrepreneurs. In fact, tightening the policy regarding the security matter could enhance the readiness of micro-entrepreneurs to use fintech application.

This study investigates factors that influence the readiness of micro-entrepreneurs to adopt fintech application, which were not considered by previous studies.

The purpose of this study is to examine the factors that influence people’s behaviour in paying zakat, explore their perceptions of the institutions, examine the factors that influence their trust and analyse the impact of trust on their behaviour in paying zakat to the institutions.

A questionnaire was distributed to 740 potential Zakat payers in the Federal Territory, Malaysia. In designing the questionnaire, a systematic literature review, focus group discussions and pilot study were conducted. Descriptive analysis and partial least squares structural equation model were used with SmartPLS software.

The result shows that trust, intention to pay zakat and age of the respondents have statistically significant impacts on people’s behaviour to pay zakat through institutions. Intention to pay zakat is influenced by attitudes, subjective norms and perceived behavioural control. In addition, the main common concerns expressed were lack of awareness of the importance of paying zakat, lack of transparency in zakat administration, especially in collection and distribution, and inefficiency in administration and distribution. Moreover, trust in the institutions could be established if the institution is able to fulfil its mission of collecting and distributing zakat to the entitled Asnaf and improve their welfare, as trust not only has a direct impact on people’s behaviour, but also strengthens people’s intention and influences their behaviour to pay zakat to the institutions.

This study focuses on a specific geographical area and zakat institution; hence, the study’s generalisability is limited. The use of self-reported and cross-sectional data may introduce bias and fail to capture the dynamic change of trust, intention and behaviour across time. The proposed solution of leveraging digital platforms may provide numerous hurdles and obstacles for adoption by the zakat institution.

This study shows the significant role of trust in influencing people’s intentions and behaviour in supporting organisations. Therefore, it can serve as an indicator of the performance or success of a particular institution. Thus, there is a need to find strategies to gain people’s trust by improving their ability, integrity and benevolence in performing their tasks.

This article aims to develop an accurate and efficient meshfree Galerkin method based on the strain smoothing technique for linear elastic continuous and fracture problems.

This paper proposed a generalized linear smoothed meshfree method (LSMM), in which the compatible strain is reconstructed by the linear smoothed strains. Based on the idea of the weighted residual method and employing three linearly independent weight functions, the linear smoothed strains can be created easily in a smoothing domain. Using various types of basic functions, LSMM can solve the linear elastic continuous and fracture problems in a unified way.

On the one hand, the LSMM inherits the properties of high efficiency and stability from the stabilized conforming nodal integration (SCNI). On the other hand, the LSMM is more accurate than the SCNI, because it can produce continuous strains instead of the piece-wise strains obtained by SCNI. Those excellent performances ensure that the LSMM has the capability to precisely track the crack propagation problems. Several numerical examples are investigated to verify the accurate, convergence rate and robustness of the present LSMM.

This study provides an accurate and efficient meshfree method for simulating crack growth.