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The exact process of construction projects performance assessment and benchmarking still remains subjective relying on qualitative techniques, which does not allow stakeholders to address the issues and the drawbacks of their respective projects as effectively as possible for performance improvement purposes. Hence, this research aims to establish a unified project performance score (PPS) for assessing and comparing projects performance.

Data were collected from Construction Industry Institute (CII) members and through University of Wisconsin active research projects. Exploratory data analysis was done to investigate the calculated performance metrics and the collected data characteristics. Data were converted into six performance metrics which were used as the independent variables in creating the PPS model. Logistic regression model was developed to generate the unified PPS equation in order to explain the variables that significantly affect construction projects successful post-completion performance. The PPS model was then applied on the collected dataset to benchmark projects in terms of project delivery systems, compensation types and project types in order to showcase the PPS capabilities and possible applications.

The model revealed that construction cost and schedule growth are the most important metrics in assessing projects performance, while RFIs’ processing time and change orders per million dollars were the features with the least effect on the PPS value. The authors found that integrated project delivery (IPD) and target value (TV) projects outperformed all other project delivery and compensation types. While, industrial projects showed the worst performance, as compared to commercial or institutional projects.

The PPS model can be used to assess the performance of any pool of executed projects, and introducing a novel addition to the field of construction business analytics which is a supplementary tool to successful decision making and performance improvement. Additionally, the bidding selection system can be revolutionized from a cost-based to a performance based one using the PPS model to improve the outcomes of the buyout process.

The main purpose of this study resides essentially in the development of a new tool to quantify the biomass in the bioreactor operating under steady state conditions.

Modeling is the most relevant tool for understanding the functioning of some complex processes such as biological wastewater treatment. A steady state model equation of activated sludge model 1 (ASM1) was developed, especially for autotrophic biomass (XBA) and for oxygen uptake rate (OUR). Furthermore, a respirometric measurement, under steady state and endogenous conditions, was used as a new tool for quantifying the viable biomass concentration in the bioreactor.

The developed steady state equations simplified the sensitivity analysis and allowed the autotrophic biomass (XBA) quantification. Indeed, the XBA concentration was approximately 212 mg COD/L and 454 mgCOD/L for SRT, equal to 20 and 40 d, respectively. Under the steady state condition, monitoring of endogenous OUR permitted biomass quantification in the bioreactor. Comparing XBA obtained by the steady state equation and respirometric tool indicated a percentage deviation of about 3 to 13%. Modeling bioreactor using GPS-X showed an excellent agreement between simulation and experimental measurements concerning the XBA evolution.

These results confirmed the importance of respirometric measurements as a simple and available tool for quantifying biomass.

This study aims to assess the effect of water variation on bioethanol production from cassava peels (CP) using Saccharomyces cerevisiae yeast as the ethanologenic agent.

The milled CP was divided into three treatment groups in a small-scale flask experiment where each 20 g CP was subjected to two-stage hydrolysis. Different amount of water was added to the fermentation process of CP. The fermented samples were collected every 24 h for various analyses.

The results of the fermentation revealed that the highest ethanol productivity and fermentation efficiency was obtained at 17.38 ± 0.30% and 0.139 ± 0.003 gL⁻¹ h⁻¹. The study affirmed that ethanol production was increased for the addition of water up to 35% for the CP hydrolysate process.

The finding of this study demonstrates that S. cerevisiae is the key player in industrial ethanol production among a variety of yeasts that produce ethanol through sugar fermentation. In order to design truly sustainable processes, it should be expanded to include a thorough analysis and the gradual scaling-up of this process to an industrial level.

This paper is an original research work dealing with bioethanol production from CP using S. cerevisiae microbe.

1. Hydrolysis of cassava peels using 13.1 M H₂SO₄ at 100 ^oC for 110 min gave high Glucose productivity

2. Highest ethanol production was obtained at 72 h of fermentation using Saccharomyces cerevisiae

3. Optimal bioethanol concentration and yield were obtained at a hydration level of 35% agitation

4. Highest ethanol productivity and fermentation efficiency were 17.3%, 0.139 g.L⁻¹.h⁻¹

Hydrolysis of cassava peels using 13.1 M H₂SO₄ at 100 ^oC for 110 min gave high Glucose productivity

Highest ethanol production was obtained at 72 h of fermentation using Saccharomyces cerevisiae

Optimal bioethanol concentration and yield were obtained at a hydration level of 35% agitation

Highest ethanol productivity and fermentation efficiency were 17.3%, 0.139 g.L⁻¹.h⁻¹

Recognising the as-built state of construction elements is crucial for construction progress monitoring. Construction scholars have used computer vision-based algorithms to automate this process. Robust object recognition from indoor site images has been inhibited by technical challenges related to indoor objects, lighting conditions and camera positioning. Compared with traditional machine learning algorithms, one-stage detector deep learning (DL) algorithms can prioritise the inference speed, enable real-time accurate object detection and classification. This study aims to present a DL-based approach to facilitate the as-built state recognition of indoor construction works.

The one-stage DL-based approach was built upon YOLO version 4 (YOLOv4) algorithm using transfer learning with few hyperparameters customised and trained in the Google Colab virtual machine. The process of framing, insulation and drywall installation of indoor partitions was selected as the as-built scenario. For training, images were captured from two indoor sites with publicly available online images.

The DL model reported a best-trained weight with a mean average precision of 92% and an average loss of 0.83. Compared to previous studies, the automation level of this study is high due to the use of fixed time-lapse cameras for data collection and zero manual intervention from the pre-processing algorithms to enhance visual quality of indoor images.

This study extends the application of DL models for recognising as-built state of indoor construction works upon providing training images. Presenting a workflow on training DL models in a virtual machine platform by reducing the computational complexities associated with DL models is also materialised.

Studies on developed economies showed that imposing taxes on animal-based foods could effectively reduce agricultural greenhouse gas emissions (AGHGEs), while this taxation may not be appropriate in developing countries due to the complex nutritional status across income classes. Hence, this study aims to explore optimal tax rate levels considering both emission reduction and nutrient intake, and examine the heterogenous effects of taxation across various income classes in urban and rural China.

The authors estimated the Quadratic Almost Ideal Demand System model to calculate the price elasticities for eight food groups, and performed three simulations to explore the relative optimal tax regions via the relationships between effective animal protein intake loss and AGHGE reduction by taxes.

The results showed that the optimal tax rate bands can be found, depending on the reference levels of animal protein intake. Designing taxes on beef, mutton and pork could be a preliminary option for reducing AGHGEs in China, but subsidy policy should be designed for low-income populations at the same time. Generally, urban residents have more potential to reduce AGHGEs than rural residents, and higher income classes reduce more AGHGEs than lower income classes.

This study fills the gap in the literature by developing the methods to design taxes on animal-based foods from the perspectives of both nutrient intake and emission reduction. This methodology can also be applied to analyze food taxes and GHGE issues in other developing countries.

Stigma is a major impediment to human rights in health care that causes discrimination, isolation and the exclusion of individuals from essential health-care services. It fosters fear, leading to negative stereotyping of individuals based on their social, cultural or health status and undermines their dignity and respect, consequently violating their right to health. Therefore, the purpose of this study is to evaluate the moderating role of psychological flexibility in the relationship between stigma (enacted, anticipated and internalized), mental health and the quality of life of substance users.

This study was based on a cross-sectional design and included 200 male patients with an age range of 18–65 years from 23 rehabilitation centers in four cities in Pakistan. The purposive sampling technique was used, and the sample size ranged from 4 to 23 participants for each site. Four scales were used to measure stigma, general mental health, quality of life and psychological flexibility in substance users.

The data were analyzed using SPSS and Smart PLS, which showed that stigma (enacted, anticipated and internalized) had a detrimental effect on substance users’ mental health and quality of life. Additionally, psychological flexibility acts as an efficient moderator between them.

This research unveils the moderating role of psychological flexibility in mitigating stigma’s adverse effects on individuals with substance use disorders. Future investigations should prioritize interventions aimed at enhancing psychological flexibility to ameliorate the repercussions of stigma, ultimately enhancing the well-being and quality of life of substance users.

Scuba diving tourism is reputed to be a potential low-impact recreational activity that allow environmental conservation and socioeconomic benefits for local communities. Few studies have addressed the issue of sustainability of scuba diving tourism through the simultaneously investigation on the economic and socio-cultural aspects and its implications for tourism development. This study aims to examine the scuba diving tourism in three under-explored North African tourism destinations with high ecotourist potential. The authors present an exploratory picture of scuba diving tourist demand, divers' preferences, motivations for recreational diving experiences and their propensity towards conservation.

The authors developed a case study research strategy collecting profile data on 123 divers. Furthermore, regression analysis was performed to investigate the divers' preferences, motivations and propensity towards conservation.

The divers' limited number, the presence of mainly local seasonal tourists and a moderate propensity towards conservation influence the potential of the diving tourism segment to generate significant socioeconomic benefits for local sustainable development in these destinations. However, establishing a marine protected area (MPA) could foster the development of a long-term strategy for scuba diving tourism, improve conservation awareness and increase divers' satisfaction.

Diverse profiles, preferences and motivations can provide tools to sustainably manage and preserve coastal and marine biodiversity, while also maximising the quality of the recreational experience. One of the most effective site-based strategies to orient the diving sector towards sustainability involves the design and strengthening of MPAs.

The research provides an original contribution to the debate on sustainable tourism strategies by demonstrating how the study of economic and socio-cultural aspects of scuba diving could provide guidelines to orient the tourism development of marine and coastal areas towards the principles of sustainability (also through the establishment of MPAs). The findings present an overview of the sustainability of the scuba diving tourism segment by investigating the preferences, motivations and inclination towards conservation among tourists for whom the diving experience is not a core holiday activity.

In today’s information and knowledge society, it is indispensable for citizens to acquire the requisite digital and information literacy (IL) skills to search information independently to meet their multiple and diverse information needs. As a result of digitalisation in the world, development and acquisition of digital and information skills is critical even for students and learners to retrieve digitised and online information to meet or achieve their curriculum-related accomplishments. The purpose of this study is to investigate the status of the digital and information literacies in South Africa from 2016 to 2022.

This qualitative study used a scoping review approach to collect data from research articles, conference articles and textbooks on digital literacy and IL – published in the years ranging between 2016 and 2022 from Google Scholar.

The major findings revealed that majority of the citizens especially students and learners lack digital and IL skills to recognise when information is needed, to find, locate, evaluate and use the retrieved information to meet an information need in a particular situation or context. Practical implications of this study include the alignment of curricula towards information and communication technologies to face the everchanging digital information technologies.

The study used scoping literature review research where empirical studies were retrieved and selected to address the objectives. This study provided significant approaches regarding promoting information and digital literacies in developing countries such as South Africa.

This study examines the mediating role of motivation on outdoor recreation on the attitude–behavior and social marketing–behavior linkages. The paper scrutinizes the moderating impact of coronavirus disease 2019 (COVID-19) risk perception in transforming individual motivation on nature-based outdoor recreation into environmentally responsible behavior.

Data were collected and conducted in Vietnamese National Parks. The dataset consists of 900 valid responses by domestic travelers. The research was operationalized using empirical data and employed structural equation modeling (SEM) and SPSS PROCESS analysis.

First, this study confirms that outdoor recreation activities and business's marketing on social networks tend to transform into support for individual behavior in terms of protecting environment and having responsibility for environment. Second, the current paper also represents the academic efforts to contribute to outdoor recreation literature by explaining the current global problem that has caused serious upheaval in global society as well as individual life. The findings not only confirmed the mediating role of nature-based outdoor recreation motivation between attitude and behavior, but also examined the moderating effect of COVID-19 risk perception in the relationship between motivation and behavior.

The findings indicate the significant association of social marketing, environment attitudes, outdoor recreation motivation and environmentally responsible behavior. The findings not only confirmed the mediating role of nature-based outdoor recreation motivation between attitude and behavior, but also examined the moderating effect of COVID-19 risk perception in the relationship between motivation and behavior. These results provide key insights about examining visitors' behavior for environment protection during future infectious disease outbreaks.

The surging cost of living and shortage of affordable and sustainable homes fuel the global housing crisis. Earthship buildings are marketed as the epitome of affordable and sustainable alternative housing. This paper aimed to elicit the perception of Earthship buildings among youngsters in the United Kingdom using immersive virtual reality technology. Additionally, the impact of virtual reality on perception compared with two-dimensional drawings was investigated in the study.

A three-phase, experiment-based survey was adopted: Phase 1: literature review, Earthship house model conception and the virtual environment creation; Phase 2: two-dimensional drawing-based pre-visualisation survey; Phase 3: virtual reality–based post-visualisation survey.

The findings indicated that youngsters had a remarkable, positive change in attitude towards the uptake of the Earthship houses after virtual reality visualisation. In contrast, sustainability experts shared more concerns regarding the concept's viability in the United Kingdom, even after the virtual reality visualisation. However, both youngsters and experts agreed with the pre-eminence of virtual reality over two-dimensional drawings.

The lack of awareness about Earthship buildings for posterity was noted in previous studies, which could be attributed to there being very few Earthship buildings in the United Kingdom. The importance of this awareness among youngsters cannot be over-emphasised since youngsters are affected most by the shortage of affordable and sustainable homes. This gap was addressed by enlightening the youth about Earthship houses and imparting awareness through near-real-life virtual reality visualisation.