Despite the existence of a voluminous body of literature covering the impact of infrastructure public-private partnerships (PPPs) on public value within the context of Western countries, scant attention has been paid to this topic in the Middle East. Given that the region has hosted numerous PPP projects that were implemented even without the rudimentary legal and regulatory frameworks considered essential for such projects to succeed, a study of PPPs within that region would thus be particularly useful, since an unpacking of the success factors for PPPs in the Middle East can reveal important practical insights that will advance the knowledge of PPP success factors overall. This paper, therefore, explores the rehabilitation and expansion of Jordan’s Queen Alia International Airport via the PPP route. It finds that the factors contributing to the project’s successful implementation can be categorized into those on the macro level related to political support, and the micro level factors concerned with management of daily activities involved in the partnership between the public and private sectors.

Abrupt changes in environmental temperature, wind and humidity can lead to great threats to human life safety. The Gansu marathon disaster of China highlights the importance of early warning of hypothermia from extremely low apparent temperature (AT). Here a deep convolutional neural network model together with a statistical downscaling framework is developed to forecast environmental factors for 1 to 12 h in advance to evaluate the effectiveness of deep learning for AT prediction at 1 km resolution. The experiments use data for temperature, wind speed and relative humidity in ERA-5 and the results show that the developed deep learning model can predict the upcoming extreme low temperature AT event in the Gansu marathon region several hours in advance with better accuracy than climatological and persistence forecasting methods. The hypothermia time estimated by the deep learning method with a heat loss model agrees well with the observed estimation at 3-hour lead. Therefore, the developed deep learning forecasting method is effective for short-term AT prediction and hypothermia warnings at local areas.

Objectives: The unprecedented COVID-19 pandemic has intensified the stress on blood banks and deprived the blood sources due to the containment measures that restrict the movement and travel limitations among blood donors. During this time, Malaysia had a significant 40% reduction in blood supply. Blood centers and hospitals faced a huge challenge balancing blood demand and collection. The health care systems need a proactive plan to withstand the uncertain situation such as the COVID-19 pandemic. This study investigates the psychosocial factors that affect blood donation behavior during a pandemic and aims to propose evidence-based strategies for a sustainable blood supply. Study design: Qualitative design using focus group discussion (FGD) was employed. Methods: Data were acquired from the two FGDs that group from transfusion medicine specialists (N = 8) and donors (N = 10). The FGD interview protocol was developed based on the UTM Research Ethics Committee’s approval. Then, the data was analyzed using Nvivo based on the General Inductive Approach (GIA). Results: Analysis of the text data found that the psychology of blood donation during the pandemic in Malaysia can be classified into four main themes: (i) reduced donation; (ii) motivation of donating blood; (iii) trends of donation; and (iv) challenges faced by the one-off, occasional, and non-donors. Conclusions: Based on the emerging themes from the FGDs, this study proposes four psycho-contextual strategies for relevant authorities to manage sustainable blood accumulation during the pandemic: (1) develop standard operating procedure for blood donors; (2) organize awareness campaigns; (3) create a centralized integrated blood donors database; and (4) provide innovative Blood Donation Facilities.

Sustainable ocean tourism is required to establish a balance between the environmental, economic, social and cultural aspects of ocean tourism development. Sustainable ocean tourism also contributes to local and national economies, enhancing the quality of social life and protecting the ecology. Sustainable ocean tourism expands the positive contribution of tourism to biodiversity conservation and poverty reduction and aims to attain the common goals of sustainable developments for ocean tourism. Sustainable ocean tourism is possible due to the roles of regulators and private and government institutions. Government policies, regulations and guidelines play vital roles towards achieving the sustainability of ocean tourism. However, the role of institutions also cannot be ignored, which provide support in the innovation of technologies and the implementation of policies. The paper targets to investigate the roles of regulations, policies and institutions in the sustainability of ocean tourism. A primary online survey on the perception of tourism experts was conducted for this study using Google Forms. The tourism experts were invited from all over the world to participate in the survey. The study received a total of 33 responses, out of which only 30 valid responses were considered. Using the Tobit regression model, the study found that, while regulations in India relative to foreign countries significantly boost the sustainability of ocean tourism, government policies and public institutions in India relative to foreign countries remain insignificant in predicting the sustainability of ocean tourism. Therefore, government policies and public institutions in India need to be revised and reformulated to make them important drivers of the sustainability of ocean tourism.