Recent technological advances in the fields of biomaterials and tissue engineering have spurred interest in biopolymers for various biomedical applications. The advantage of biopolymers is their favorable characteristics for these applications, among which proteins are of particular importance. Proteins are explored widely for 3D bioprinting and tissue engineering applications, wound healing, drug delivery systems, implants, etc., and the proteins mainly available include collagen, gelatin, albumin, zein, etc. Zein is a plant protein abundantly present in corn endosperm, and it is about 80% of total corn protein. It is a highly renewable source, and zein has been reported to be applicable in different industrial applications. Lately, it has gained attention in biomedical applications. This research interest in zein is on account of its biocompatibility, non-toxicity, and certain unique physico-chemical properties. Zein comes under the GRAS category and is considered safe for biomedical applications. The hydrophobic nature of this protein gives it an added advantage and has wider applications in drug delivery. This review focuses on details about zein protein, its properties, and potential applications in biomedical sectors.

A panel data analysis of nonlinear government expenditure and income inequality dynamics in a macroprudential policy regime was conducted on a panel of 15 emerging countries from 1985–2019, where there had been a non-prudential regime from 1985–1999 and a prudential regime from 2000–2019. The paper explored the validity of the nonlinearity between government expenditure and income inequality in the macroprudential policy regime as well as the threshold level at which excessive spending reduces income inequality using the Bayesian spatial lag panel smooth transition regression (BSPSTR) and fix effect models. The BSPSTR model was adopted due to its ability to address the problems of heterogeneity, endogeneity, and cross-section correlation in a nonlinear framework. Moreover, as the transition variable often varies across time and space, the effect of the independent variables can also be time- and space-varying. The results reveal evidence of a nonlinear effect between government spending and income inequality, where the minimum level of government spending is found to be 29.89 percent of GDP, above which expenditure reduces inequality in emerging countries. The findings confirmed an inverted U-shaped relationship. The focal policy recommendation is that fiscal policy decisions that will reinforce the need for more emphasis on education and public expenditure on education and health, as important tools for improving income inequality, are crucial for these economies. Caution is needed when introducing macroprudential policies, especially at a low level of government expenditure.

Metaverse technology has various uses in communication, education, entertainment, and other aspects of life. Consequently, it necessitates using some interactive mobile applications to enter the virtual world and gain real-time, face-to-face experiences, particularly among students. This research focused on the factors accelerating metaverse technology acceptance particularly, Metaverse Experience Browser application acceptance among the students under the factors proposed by the unified theory of acceptance and use of technology (UTAUT) model. Notably, lack of studies in metaverse browsers and their prevalence during the post pandemic era, indicates a strong literature gap. The researchers gathered data from n = 384 higher education students from the two cities in the United Arab Emirates and applied Structural Equation modelling (SEM) for data analysis. Results revealed that Performance Expectancy (p < 0.003) and Social Influence (p = 0.000) were significant factors affecting the Behavioral Intention of the students to consider Metaverse Experience Browser as an interactive mobile application. On the other hand, behavioural Intention significantly affects (p = 0.000) Effort Expectancy, which shows how fewer efforts and greater accessibility are associated with one’s behavioural Intention. Besides, the effect of Behavioral Intention (p = 0.000) on Metaverse Experience Browser acceptance also remained validated. Finally, Effort Expectancy (p = 0.000) also indicated its significant effect on the Metaverse Experience Browser. These results indicated that the factors proposed by UTAUT have greater applicability on the Metaverse Experience Browser as they showed their relevance to its acceptance. The present study concludes that the acceptance of Metaverse Experience Browser as an interactive mobile application is a level ahead in improving students’ experiences. Thus, the Metaverse Experience Browser is considered a modified way of creating, sharing, participating, and enjoying the virtual world, indicating its greater usage among students for different purposes, including education and learning.

An experiment was carried out to investigate the effect of different organic nutrient solutions and day of harvest on growth parameters, biomass and chemical composition of hydroponically grown sorghum red fodder. The experiment was a 3 × 2 factorial design comprising of 3 nutrient solutions (cattle, poultry and rabbit) and 2 harvesting regimes (8th and 10th day). Cattle, poultry and rabbit dungs were collected fresh and processed into nutrient solutions. Sorghum red seeds were treated, planted on trays, and irrigated twice per day with organic nutrient solution according to the treatments. Growth parameters which were investigated included fodder mat thickness, seedling height, leaf length and width, number of leaves, fresh and dry matter yield; and proximate composition. The results showed that sorghum red fodder irrigated with cattle manure nutrient solution (NS) harvested at 10 days was higher in all, except one (fodder mat thickness) of the growth parameters considered. The crude protein (CP) was highest and similar (P > 0.05) for Poultry NS harvested at 8 and 10 days, and Cattle NS at 10 days (13.13%, 12.67%, and 12.69% respectively). The ash content also favored Cattle NS at 10 days. Cattle NS at 10 days harvest was significantly (P < 0.05) the highest (7.00%), but comparable (P > 0.05) with Rabbit NS at 10 days for NDF. Fresh and DM yields were highest for Cattle harvested at 10 and 8 days respectively. The study recommends Cattle NS as hydroponic organic NS for sorghum red as it enhances fresh and dry matter yields, and nutritive values.

After the oil and economic boom of the 20th century, Doha experienced significant development in terms of the architectural scene, design, function, and sociocultural transformations. The advancements in global architecture have facilitated innovative and streamlined construction processes, while creating a paradigm shift in the overall architecture of dwellings and how people navigate around the house. In this context, this research aims to study the impact of globalization on housing typologies and the factors influencing their evolution, focusing on the city of Doha as a case study. This study is based on a qualitative research approach that centers its investigation on Doha while exploring strategies for preserving Arabic-Islamic identity. The research investigation used a content analysis methodology to analyze three additional case studies within the MENA region. The results indicate that new housing typologies have emerged in cities due to globalization and changes in physical and sociocultural dimensions. In addition, preserving older neighborhoods and housing typologies through a bottom-up approach is essential for design creativity and climatic and sociocultural sensitivity while exchanging knowledge and sharing experiences between generations. Furthermore, this article promotes heritage awareness and encourages local authorities to preserve Doha’s surviving historic neighborhoods and architectural language to restore the city’s urban identity. The findings of this research can provide helpful guidance to architects and urban planners on how Doha’s housing has developed until the contemporary period.

Given the heavy workload faced by teachers, automatic speaking scoring systems provide essential support. This study aims to consolidate technological configurations of automatic scoring systems for spontaneous L2 English, drawing from literature published between 2014 and 2024. The focus will be on the architecture of the automatic speech recognition model and the scoring model, as well as on features used to evaluate phonological competence, linguistic proficiency, and task completion. By synthesizing these elements, the study seeks to identify potential research areas, as well as provide a foundation for future research and practical applications in software engineering.