This study examined the dissatisfaction among Chinese medical students with online medical English courses, which overemphasize grammar yet fail to provide practical opportunities related to medical situations. This study compared co-teaching’s effects, involving native and non-native instructors, with a single-instructor (traditional) model on student satisfaction in online medical English courses. Using a qualitative design, pre- and post-course interviews were conducted with 49 second-year medical students across seven classes, exploring their perceptions of instruction, curriculum, and course satisfaction. The findings indicated that the co-teaching model improved student engagement and satisfaction, not specifically due to the native English-speaking instructor but likely because of the focus on more interactive and discussion-oriented strategies. In contrast, the single-instructor model maintained the traditional grammar-focused instruction, leading to lower satisfaction levels. Both instructional models faced limitations related to their reliance on textbooks for delivering core material needed for the course’s comprehensive exam. These results suggest that the instruction design and approach, rather than the native instructor alone, was the main driver of positive outcomes in co-teaching. The study’s findings suggest a need for curriculum reforms that reduce textbook dependence and incorporate more practical, interactive learning strategies. Future research should consider applying various research techniques, such as mixed-method approaches, longitudinal studies, and experimental designs, to comprehensively assess the long-term effects of instructional strategies and curriculum innovations on student outcomes.

Adopting electric vehicles (E.V.) is crucial for promoting sustainable mobility in metropolitan areas such as Medan, Indonesia. To achieve this, it is essential to comprehend the factors that influence E.V. adoption, with a particular focus on the impact of media. This study examines the adoption of electric vehicles in Medan and evaluates the influence of the media on the public’s perception and policy decisions. Opinions, concerns, and recommendations surrounding electric vehicles were examined through surveys and interviews with 35 stakeholders, including students, lawmakers, industry experts, business owners, and media professionals. The findings indicate a strong knowledge and favorable perception of electric vehicles in Medan. However, there are worries regarding the expenses associated with E.V.s and the availability of charging infrastructure. Notably, 60% of the respondents identified media as their primary source of information, highlighting its significant influence. Encouraging cooperation between media, professionals, and stakeholders is advisable to achieve accurate and balanced reporting. This can be done by employing techniques like showcasing success stories and emphasizing the environmental advantages to encourage acceptance and implementation. This study provides valuable insights into improving the adoption of electric vehicles in Medan. It emphasizes the significance of implementing effective media strategies and supportive policies to achieve sustainable transportation solutions.

The demography of Saudi Arabia has been discussed many times but its conflict with the theories of transition and associated structural changes is unexplained. This research explains the demographic differentials stated as lag - real from theoretical – separately for the native and total population. This research developed demographic indicators revealing trends and patterns by adopting a secondary data analysis method, utilizing the General Authority for Statistics census data and other online data. The demographic transition of Saudi Arabia is in line with the theoretical contentions of pretransition and transition (early, mid, and late) stages but at definite time intervals. The absolute size, percentage change, and annual growth rate are explanatory for natives and are considered separately. Moreover, the structural population changes reveal transition stages from expansive to near expansive and constricting and stabilizing. Furthermore, broad age groups indicate rapid declines in the percentage of children, rapid increases in young adults, slow increases in older adults, and no changes in older persons. Even the sex ratio of natives is at par with other populations in transition (slightly above 100). Thus, it could be concluded that a demographic transition with structural changes as per theories: flawless growth rates with an expanding demographic dividend. At this juncture, the integration of migrants into society by endorsing family life and enabling social and demographic balance appears as imperative to improving the labor sector, productivity, and the image of the country in the international spheres for comparisons and benchmarking.

Monitoring marine biodiversity is a challenge in some vulnerable and difficult-to-access habitats, such as underwater caves. Underwater caves are a great focus of biodiversity, concentrating a large number of species in their environment. However, most of the sessile species that live on the rocky walls are very vulnerable, and they are often threatened by different pressures. The use of these spaces as a destination for recreational divers can cause different impacts on the benthic habitat. In this work, we propose a methodology based on video recordings of cave walls and image analysis with deep learning algorithms to estimate the spatial density of structuring species in a study area. We propose a combination of automatic frame overlap detection, estimation of the actual extent of surface cover, and semantic segmentation of the main 10 species of corals and sponges to obtain species density maps. These maps can be the data source for monitoring biodiversity over time. In this paper, we analyzed the performance of three different semantic segmentation algorithms and backbones for this task and found that the Mask R-CNN model with the Xception101 backbone achieves the best accuracy, with an average segmentation accuracy of 82%.

Delay is the leading challenge in completing Engineering, Procurement, and Construction (EPC) projects. Delay can cause excess costs, which reduces company profits. The relationship between subcontractors and the main contractor is a critical factor that can support the success of an EPC project. The problematic financial condition of the main contractor can cause delay in payments to subcontractors. This research will set a model that combines the system dynamics and earned value method to describe the impact of subcontractor advance payments on project performance. The system dynamics method is used to model and analyze the impact of interactions between variables affecting project performance, while the earned value method is applied to quantitatively evaluate project performance and forecast schedule and cost outcomes. These two methods are used complementarily to achieve a holistic understanding of project dynamics and to optimize decision-making. The designed model selects the optimum scenario for project time and costs. The developed model comprises project performance, costs, cash flow, and performance forecasting sub-models. The novelty in this research is a new model for optimizing project implementation time and costs, adding payment rate variables to subcontractors and subcontractor performance rates. The designed model can provide additional information to assist project managers in making decisions.