This paper argues for a novel approach to financing infrastructure needs in Arab countries. It first describes the context of rising public debt in the region, contrasting it with the vast infrastructure needs. It then discusses the challenges in meeting these needs with traditional financing. The paper then makes the case for maximizing finance for development by using public-private partnerships and presents a few successful examples in Arab countries. Finally, the paper explores the way forward and concludes on the need for strong state capacity and integrity to promote the “maximizing finance for development” approach.

Cucumber Variety ‘Drite L108’ (Cucumis sativus L. Cv. Derit L108) was selected as the test material. In the solar greenhouse, different days (1, 3, 5, 7, 9 d) of light (PAR < 200 µmol·m^-2·s^-1) and normal light conditions were designed with shading nets to observe the growth indexes of cucumber plants and the changes of antioxidant enzyme activities in leaves. The results showed that: (1) continuous low light increased the SPAD (relative chlorophyll) value of cucumber leaves and decreased the net photosynthetic rate. The longer the continuous low light days are, the smaller the net photosynthetic rate of cucumber leaves and the worse the photosynthetic recovery ability would be. (2) The plant height, stem diameter and leaf area per plant were lower than CK, and the above indexes could not return to the normal level after 9 days of normal light recovery; the yield and marketability of cucumber fruit decreased under continuous low illumination. (3) The activities of SOD (superoxide dismutase) and POD (peroxidase) in cucumber leaves increased, the activities of CAT (catalase) first increased and then decreased, and the content of MDA (malondialdehyde) continued to increase. The longer the days of continuous light keep, the more seriously the cucumber leaves were damaged by membrane lipid peroxidation. After continuous light for more than 7 days, the metabolic function of cucumber leaves was difficult to recover to the normal level.

This multiple case study qualitative research examined the impact of adoption and diffusion of innovation on Small and Medium Enterprises (SME’s) growth in the hostile business landscape of Khyber-Pakhtunkhwa, Pakistan. This research is intended to investigate research data and consequent findings based on an interview protocol that was purposefully developed from extant literature, complemented by an initial pilot study of two pharmaceutical SMEs. The researcher conducted 20 interviews, guided by the semi-structured interview protocol offered to the respondents beforehand after sorting their informed consent. The 20 participants represented the different hierarchal levels of the 08 case study of pharmaceutical from the two industrial clusters of Khyber Pakhtunkhwa, Pakistan, located at the Hayatabad Industrial Estate, Peshawar, and the Rashkai Industrial Estate, Nowshera. The analysis of the data presented findings and corroborated the research propositions that those SMEs that are structurally entrepreneurial and adopt innovation amenably, are open to mobility and tourism, yield satisfactory results in terms of their growth as compared to those that are inertial and unentrepreneurial. Similarly, the results offer confirmation that the effectiveness of government agencies that are explicitly formed to address the problems of small businesses is insufficient. They rather create hindrances than assistance due to the excessive delays in approving innovative ideas and conceptions by these related organizations and ministries. Moreover, the proposed framework offers pragmatic recommendations to contextualize entrepreneurial culture and innovative structures in SMEs and their essential factors in critical environmental circumstances.

The pressing need to redefine the tourism industry’s relationship with nature and local communities has never been more critical. Ecotourism, as a paradigm of sustainable travel, holds transformative potential—not only for preserving our planet’s fragile ecosystems but also for fostering local cultural and economic development. In this context, the integration of circular economy principles offers innovative pathways to enhance sustainability across the tourism sector. The application of circular economy frameworks in tourism not only reduces environmental impact but also enhances economic viability by creating closed-loop systems. My interest in this topic stems from a personal conviction: Tourism should leave a positive mark, one that enriches rather than diminishes the destinations we visit. This study delves into how the hotel industry can align itself with ecotourism principles by embracing innovative, sustainable practices that minimize environmental impact while delivering authentic, high-quality experiences for travelers. Through the lens of green energy, resource optimization, and cultural integration, the research demonstrates that sustainability is both an ethical responsibility and a pathway to long-term competitiveness in tourism. By supporting local economies and protecting natural heritage, the industry can shift from being a passive observer of environmental degradation to a proactive steward of change. This work serves as a call to action for stakeholders: Our choices today will define the landscapes and cultural legacies available to future generations.

The integration of Big Earth Data and Artificial Intelligence (AI) has revolutionized geological and mineral mapping by delivering enhanced accuracy, efficiency, and scalability in analyzing large-scale remote sensing datasets. This study appraisals the application of advanced AI techniques, including machine learning and deep learning models such as Convolutional Neural Networks (CNNs), to multispectral and hyperspectral data for the identification and classification of geological formations and mineral deposits. The manuscript provides a critical analysis of AI’s capabilities, emphasizing its current significance and potential as demonstrated by organizations like NASA in managing complex geospatial datasets. A detailed examination of selected AI methodologies, criteria for case selection, and ethical and social impacts enriches the discussion, addressing gaps in the responsible application of AI in geosciences. The findings highlight notable improvements in detecting complex spatial patterns and subtle spectral signatures, advancing the generation of precise geological maps. Quantitative analyses compare AI-driven approaches with traditional techniques, underscoring their superiority in performance metrics such as accuracy and computational efficiency. The study also proposes solutions to challenges such as data quality, model transparency, and computational demands. By integrating enhanced visual aids and practical case studies, the research underscores its innovations in algorithmic breakthroughs and geospatial data integration. These contributions advance the growing body of knowledge in Big Earth Data and geosciences, setting a foundation for responsible, equitable, and impactful future applications of AI in geological and mineral mapping.