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The current research aimed to examine the prevalence of Instagram posts featuring ultra-processed products targeted at adolescents in Uruguay and hence investigate the frequency of such posts among a vulnerable consumer segment in a country that cannot be classified as WEIRD (i.e. Western, educated, industrialized, rich and democratic).

The study relied on a cross-sectional content analysis. A total of 2,014 Instagram posts promoting ultraprocessed products or brands commercializing such products, generated by 118 Instagram accounts between August 15th, 2020, and February 15th, 2021, were analyzed. Nine indicators of food marketing targeted at adolescents were selected to identify posts targeted at this age segment. Inductive coding was used to describe the content of the posts. Descriptive statistics and generalized linear models were used to analyze the data.

In total, 17.6% of the posts were identified as targeted at adolescents. Graphic design and adolescent language were the most prevalent indicators of marketing targeted at adolescents, followed by explicit references to adolescents or young adults and memes. Posts identified as targeted at adolescents mainly promoted snacks and discretionary foods. Differences in the content of posts identified as targeted and not targeted at adolescents were observed.

The analysis was restricted to one social media platform in one country during a limited period of time, which limits the generalizability of the findings to other media platforms, samples and settings.

Results stress the need to implement digital food marketing regulations to reduce exposure of adolescents to the deleterious effects of stemming from marketing of unhealthy foods and provide empirical evidence to inform their development.

The study breaks new ground by analyzing the prevalence and exploring the characteristics and content of Instagram posts promoting ultra-processed products to adolescents in an under-researched geographic area of the world.

This case studies the growth of OYO Hotels (OYO) to illustrate the operational processes necessary to succeed in the service sector. The case allows for a discussion of employee- and customer-management systems, tech-driven solutions, and profit drivers. The material unfolds OYO's growth and its solution for making economy hotels discoverable and bookable online.

The case raises a series of questions around OYO's business model, its ability to translate across global markets, and growth potential. It has been successfully taught in a second-year MBA class on the management of service operations.

Challenges associated with ensuring the accuracy and reliability of cost estimation of highway construction bid items are of significant interest to state highway transportation agencies. Even with the existing research undertaken on the subject, the problem of inaccurate estimation of highway bid items still exists. This paper aims to assess the accuracy of the cost estimation methods employed in the selected studies to provide insights into how well they perform empirically. Additionally, this research seeks to identify, synthesize and assess the impact of the factors affecting highway unit prices because they affect the total cost of highway construction costs.

This paper systematically searched, selected and reviewed 105 papers from Scopus, Google Scholar, American Society of Civil Engineers (ASCE), Transportation Research Board (TRB) and Science Direct (SD) on conceptual cost estimation of highway bid items. This study used content and nonparametric statistical analyses to determine research trends, identify, categorize the factors influencing highway unit prices and assess the combined performance of conceptual cost prediction models.

Findings from the trend analysis showed that between 1983 and 2019 North America, Asia, Europe and the Middle East contributed the most to improving highway cost estimation research. Aggregating the quantitative results and weighting the findings using each study's sample size revealed that the average error between the actual and the estimated project costs of Monte-Carlo simulation models (5.49%) performed better compared to the Bayesian model (5.95%), support vector machines (6.03%), case-based reasoning (11.69%), artificial neural networks (12.62%) and regression models (13.96%). This paper identified 41 factors and was grouped into three categories, namely: (1) factors relating to project characteristics; (2) organizational factors and (3) estimate factors based on the common classification used in the selected papers. The mean ranking analysis showed that most of the selected papers used project-specific factors more when estimating highway construction bid items than the other factors.

This paper contributes to the body of knowledge by analyzing and comparing the performance of highway cost estimation models, identifying and categorizing a comprehensive list of cost drivers to stimulate future studies in improving highway construction cost estimates.

With the increased demand for the application of technology in property activities, there is a growing need for property professionals adept in using digital technology. Hence, it is important to assess the competence of academia in equipping property professionals with digital technology skills. This study, therefore, assesses property academics in Australian universities to identify their level of knowledge and use of digital technology applicable to the property industry.

Online questionnaire surveys were administered to 22 out of 110 property academics contacted through the Australia Property Institute (API) database to achieve this aim. The collected data were analysed using mean score ranking and ANOVA.

The study found that apart from databases and analytics platforms such as Corelogic RP data, price finder and industry-based software such as the Microsoft Office suite and ARGUS software, the academics were not knowledgeable in most identified and sampled proptech tools. Similarly, most proptech tools were not used or taught to the students. It was also found that early career academics (below five years in academia) were the most knowledgeable group about the proptech tools.

Relying on the API database to contact property academics potentially excludes the position of property academics who may not be affiliated or have contacts with API, hence, the findings of this study should be generalised with caution.

The study bears huge implications for the property education sector and industry in Australia; a low knowledge and use of nascent tools such as artificial intelligence, machine learning, blockchain, drones, fintech, which have received intense interest, reveals some level of skill gap of students who pass through that system and may need to be upskilled by employers to meet the current day demand.

In response to the clamour for technology-inclined property professionals, this paper presents itself as the first to assess the knowledge levels and application of digital technology by property academics.

Improving service quality, student satisfaction and student loyalty is important to higher education institutions’ sustainable growth. The objectives of this study are a twofold: first, the study seeks to determine the dimensions of higher education service quality with a specific focus on Vietnam. Second, it examines how the service quality dimensions impact student satisfaction and student loyalty, with the moderating role of the university image.

This study followed a rigorous procedure, including interviews, a survey, exploratory factor analysis (EFA) and reliability analysis to identify higher education service quality dimensions and their measures. After that, using the data obtained from 1,550 university students in Vietnam, confirmatory factor analysis was used to validate the identified dimensions and structural equation modeling was used to test a proposed model explaining the outcomes of higher education service quality.

The findings reveal five dimensions of higher education service quality: academic aspect, nonacademic aspect, programming issues, facilities and industry interaction. Most of these factors have a positive influence on student satisfaction. In addition, the university image moderates the positive relationship between student satisfaction and student loyalty.

This study’s findings highlight the complexity of service quality in the higher education context and encourage higher education institutions to improve their service quality in image to enhance student satisfaction and loyalty.

This study suggests a unique measure of higher education service quality dimensions and provides fresh insights into how they impact student satisfaction and loyalty in Vietnam.

Groups of students were enrolled in a course that sought to produce a three-phase theoretical model over three semesters.

A design project to comprehensively address school violence was launched at a university in eastern Pennsylvania.

This article updates the recent and most critical finding of the project by illuminating specific implications of the importance of teacher training and the development toward competence in recognition of children who are emotionally and psychologically injured through proactive measures such as screening for emotional and psychological well-being.

Although the model has not been tested, screening to identify those in need of emotional support and training to support teachers is clear. Screening and training offer important opportunities to help learners build skills toward resilience to soften the effects of trauma.

A view of the “whole child” with regard to academic success could further foster social and emotional development.

Early intervention can prevent the onset of symptoms associated with posttraumatic stress and related disorders. This effort alone may significantly reduce the uncomfortable incidences and perhaps ultimate prevention of the violence that is perpetuated among children.

Preliminary research supports a continued conversation regarding effective tools to find children emotionally and psychologically at-risk, which allows teachers an opportunity for timely emotional and psychological interventions.

In recent years, there has been growing interest in the use of stainless steel (SS) in reinforced concrete (RC) structures due to its distinctive corrosion resistance and excellent mechanical properties. To ensure effective synergy between SS and concrete, it is necessary to develop a time-saving approach to accurately determine the ultimate bond strength τ_u between the two materials in RC structures.

Three robust machine learning (ML) models, including support vector regression (SVR), random forest (RF) and extreme gradient boosting (XGBoost), are employed to predict τ_u between ribbed SS and concrete. Model hyperparameters are fine-tuned using Bayesian optimization (BO) with 10-fold cross-validation. The interpretable techniques including partial dependence plots (PDPs) and Shapley additive explanation (SHAP) are also utilized to figure out the relationship between input features and output for the best model.

Among the three ML models, BO-XGBoost exhibits the strongest generalization and highest accuracy in estimating τ_u. According to SHAP value-based feature importance, compressive strength of concrete f_c emerges as the most prominent feature, followed by concrete cover thickness c, while the embedment length to diameter ratio l/d, and the diameter d for SS are deemed less important features. Properly increasing c and f_c can enhance τ_u between ribbed SS and concrete.

An online graphical user interface (GUI) has been developed based on BO-XGBoost to estimate τ_u. This tool can be utilized in structural design of RC structures with ribbed SS as reinforcement.

Food literacy is a multidimensional concept that prioritises the aspects individuals require to navigate the contemporary foodscape successfully. The study aims to map the knowledge base and intellectual structure of the concept of food literacy to assess if the most cited definitions reflect these constructs.

The inclusion criteria of full-text, peer-reviewed articles or conference papers, in English, using “food literacy” within the title, abstract, keywords or linked to the research focus produced 538 articles from the Scopus database from its inception until January 31, 2023. Articles were analysed according to exponential growth, geolocations, authors, articles, research areas and keywords using VOSviewer, CiteSpace and Excel.

Food literacy research grew exponentially between 2012 and 2022 at a rate of 50% and spanned 62 research areas, with nutrition and dietetics being the most common. Vidgen and Gallegos were the most cited authors of the most cited article, and Australia was the most influential food literacy research geolocation. Research originating from developing countries within Asia, the Middle East, Africa and South America was underrepresented, and COVID-19 impacted research trends between 2020 and 2023.

It is recommended to link “food literacy” to appropriate publications to increase its visibility and that food literacy be redefined and conceptualised to better reflect its intellectual structure. To complete this task, further research guided by keyword clustering can enhance conceptual understanding.

This study provides new insight into the knowledge base and intellectual structure of food literacy and provides scope for future research to develop the concept further.