Search results

Milk is often referred to as the ultimate food because it meets the nutritional needs of infants, children and adults alike. It is a rich source of protein, fat, sweetness, vitamins and minerals. Because of its widespread usage as a healthy dairy product, the issue of milk adulteration is of global significance. The increasing frequency of fraudulent methods in the dairy business raises concerns about its purity and quality.

A study was conducted and reviewed that looked at several approaches for detecting milk adulteration during the past 15 years. This study examines the current state of research and analyzes recent advances in development.

There are ways and technology available that can effectively put an end to the abhorrent practice of milk adulteration.

This research takes a unique approach, focusing on the application of milk adulteration. It provides an overview of milk adulteration detection and investigates the effectiveness of biosensors in identifying common milk adulterants.

Deep-learning techniques are recently gaining a lot of importance in the field of turbulence. This study focuses on addressing the problem of data imbalance to improve the performance of an existing deep learning neural network to infer the Reynolds-averaged Navier–Stokes solution, proposed by Thuerey et al. (2020), in the cases of airfoils with high wake formation behind them. The model is based on a U-Net architecture, which calculates pressure and velocity solutions for fluid flow around an airfoil.

In this work, we propose various methods for training the model on selectively generated data with different distributions, which would be representative of the under-performing test samples. The property we chose for selectively generating data was the fraction of negative x-velocity in the domain. We have used Grad-CAM to compare the layer activations of different models trained using the proposed methods.

We observed that using our methods, the average performance on the samples with high wake formation (i.e. flow over airfoils at high angle of attack) has improved. Using one of the proposed methods, an average performance improvement of 15.65% was observed for samples of unknown airfoils compared to a similar model trained using the original method.

This work demonstrates the use of imbalanced learning in the field of fluid mechanics. The performance of the model is improved by giving significance to the distribution of the training data without changes to the model architecture.

The purpose of this study was to develop a suitable module for digital conservation of traditional knowledge of medicinal plants (MPs) used by tribal communities living in the Anuppur district of Madhya Pradesh, Central India.

The research used a qualitative approach to gather the data of MPs through the use of literature review and field survey. Based on the acquired data, a prototype digital learning system was constructed and assessed. This study used digital learning technologies to assess the requirements for transmitting traditional knowledge of important MPs used by tribal communities so that people can absorb and conserve them.

Over time, the focus on the digital conservation of traditional MP’s knowledge has progressively increased globally. Despite the rise in this field of study, information technology methods to preserve and distribute traditional knowledge of MPs have remained a few. When adopting digital learning to maintain traditional knowledge of MPs, it was discovered that it would be necessary to engage with relevant knowledge keepers, use multimedia, and provide content in local languages.

This study helps in conservation of important MP species that are having biologically important therapeutic compounds meant for treating various ailments. Older generations of various tribal communities mainly hold traditional knowledge of important MPs, and unless it is preserved, it will perish along with its caretakers.

It is worth looking at a digital platform that can help future generations to maintain traditional knowledge of MPs, as it is a dynamic and ever-changing, it must involve a digital tool for its future conservation. Current methods for maintaining traditional knowledge of MPs were ineffective and constrained by space and time.

This chapter reviews the evidence on the role of physicians in shaping inequalities in access to and utilisation of healthcare. The authors examine three types of physician decisions that can influence inequalities in access and utilisation: location decisions, decisions to work in the public and/or private sector, and decisions or behaviours in the doctor–patient encounter. For each, the authors summarise the issues and empirical evidence on possible policies to help reduce inequalities in access. Future research to reduce inequalities should focus on changes to health systems that influence physician decisions, such as health insurance expansions, the public–private mix and financial incentives, as well as physician training and policies for a more diverse physician workforce.

Emerging from the COVID-19 pandemic, the Philippines has undergone the “new normal” transition, creating a strategic recovery effort to reinvigorate the industry. In tourism, these transitions aim to safeguard employees' and guests' health and safety, ensure continuity of business operations, boost tourism confidence leading to satisfaction, and establish a resilient and sustainable tourism industry in the postpandemic era. Hence, this chapter employs a system thinking leveraging a causal loop diagram (CLD) to construct a comprehensive roadmap for Philippine tourism's postpandemic resurgence through the system thinking lens. The CLD visually illustrates the inter-related factors influencing the recovery process, encompassing collaborative engagements, innovations, economic revitalization, and health and safety protocols. By analyzing the causal relationships among these variables, this chapter explicates the dynamic and interconnected nature of the postpandemic recovery leading to the recovery of the Philippine tourism industry, especially in the context of thinking small. Through this chapter, thinking small could involve a shift toward localized solutions and community-focused initiatives that allow them to foster local economies, build resilience, and create a more inclusive and sustainable postpandemic recovery.

This study aims to analyze the entrepreneurial intention (EI) manifested by potential entrepreneurs for LGBT (lesbian, gay, bisexual, and transgender) and traditional markets, thereby tracing a comparative EI for both markets. The intention is to understand the vision of potential future entrepreneurs related to markets focused on the LGBT public (i.e. if entrepreneurs perceive this market as an option for future business).

Using a quantitative research design, data were collected from a sample of 157 students in Brazil and analyzed by applying structural equation modeling.

This study primarily identified a difference between EI when comparing the focus on LGBT and traditional markets. Results show that the impact of personal attitude is significantly higher on EI for general markets (all markets) than for markets focused on LGBT audiences. Furthermore, the impact on entrepreneurship for traditional markets is generally significantly lower than for the LGBT market.

The study explored the EI for LGBT markets, which has not been studied extensively. It aims to gain a better understanding of various aspects that may influence the decision-making and perceptions of potential future entrepreneurs. Furthermore, the study compares traditional and LGBT audiences, providing valuable insights for potential future entrepreneurs in both scenarios. This comparison is a unique contribution to the literature and contributes to important analyses and debates.

Meat is a crucial source of protein and other nutrients for human health. However, excessive consumption of meat products is not advisable due to their elevated sodium and animal fat levels. Hence, there is a strong recommendation for reducing sodium and fat content in meat products. This study aims to delve into the current sodium, total and saturated fat content of meat products in the Brazilian market.

A total of 1,600 products underwent analysis.

The highest sodium concentrations were identified in jerked beef (5.48 g/100 g), charqui (5.21 g/100 g) and salted pork meat (2.58 g/100 g). In contrast, the highest total and saturated fat levels were observed in bacon (35.33 and 12.50 g/100 g), salami (26.00 and 9.25 g/100 g) and pork coppa (22.00 and 9.75 g/100 g). Most meat products were categorized as medium in terms of sodium (77.75%), total fat (52.93%) and saturated fat (48.25%). However, many meat products exhibited high total and saturated fat levels.

This study represents the first comprehensive examination of the sodium, total fat and saturated fat content listed on the labels of many meat products in Brazil.

This study aims to assess the effect of both apigenin-loaded zinc oxide nanoparticles (ZnONPs) and apigenin only against cisplatin (CP)-induced experimental cardiotoxicity.

A total of 32Wister rats (male) were randomly divided (n = 8) into four groups. Normal control group, CP group received CP (20 mg/kg); treated group I received CP and then received apigenin (0.78 mg/kg/day) orally; treated group II received CP and then received apigenin loaded ZnONPs. At the end of the experiment (10 days), samples were extracted from each rat for the assessment of complete blood picture, lipid profile, atherogenic indices, oxidative status, inflammatory and cardiotoxicity markers as well as histological examination.

The results indicated that CP produced significant alterations in the complete blood picture, lipidemic profile, atherogenic indices, antioxidation capacity and cardiac inflammatory markers as well as function enzymes as compared with the control group. Administration of apigenin only showed a non-significant change in the atherogenic indices, oxidative status and cardiotoxicity parameters, indicating incomplete cardio-protection against CP upon. Additionally, all the observed alterations in CP group were reversed when apigenin nanoparticle at lower dose was used with ZnONPs which was also confirmed by histopathological investigation.

The apigenin loaded ZnONPs exert protective effects against CP-induced experimental cardiotoxicity and improved cardiac function, suggesting a potential adjuvant role of apigenin nanoparticles against cardiotoxicity.

Smart urban governance research has progressed over the past few decades following changes and increasingly complicated city management difficulties. Therefore, the purpose of this paper is to use a scoping review and bibliometric analysis to examine all the publications on smart urban governance, especially in Asia.

A total of 1,900 smart urban governance articles indexed in the Scopus database was analyzed through scoping review and bibliometric analysis. The articles were analyzed by the number of publications per year, contributing countries, subject areas, authors, cited documents, related issues and cited papers. Furthermore, VOSviewer was used to provide a visual analysis of the co-occurrence of keywords.

This study indicated that urban smart governance publications continue to increase yearly. Even though the area of analysis is Asia, the USA and China seriously contributed to the analysis. Therefore, the topic of smart urban governance has become a discussion for scholars in the international. From the Scopus database analysis, the top three subject areas are social sciences (28%), environmental science (20%) and medicine (16%). The synthesis using bibliometric analysis by VOSviewer obtained 13 clusters.

This study only focuses on the Scopus database and one specific topic, using one bibliometric analysis tool. Meanwhile, national and international index databases are not used.

This paper examined publication trends on smart urban governance. This paper provided a comprehensive analysis of topic-specific knowledge areas based on previous studies. Additionally, this paper suggested the direction of the development of smart urban governance in the future.

Augmented reality (AR) is an advanced version of the dynamic physical space that is perceived and received via visual, audio, digital and other sensory stimuli. The capabilities of virtual technologies change the field of university and education considerably. The necessity of using virtual technologies in the education field was revealed more in unforeseen disasters such as the COVID-19 pandemic. The adoption of a technology by its users is an important factor in the successful implementation of the technology. The present study evaluates several factors affecting the adoption of AR technology in the realm of tertiary education.

This study is applied in nature, and the necessary data were gathered through a survey questionnaire. The opinions of 621 students were investigated using a simple random sampling method. The multinomial logit test was used in this research.

It was found that individual and social factors such as age, education level, major and economic characteristics such as one’s income in a month, expenses of a person in a month, the level of access to high-speed internet and access to a laptop or smartphone are effective in AR technology adoption in the field of academic education.

The theoretical contribution of this study is to identify the key factors that influence the adoption of AR technology and develop a model specifically applicable to the educational field. The results of this research can be used by university managers and educational policymakers for the efficient and effective use of this technology.