Diabetic Retinopathy (DR) is one of the leading causes of blindness for people who have diabetes in the world. However, early detection of this disease can essentially decrease its effects on the patient. The recent breakthroughs in technologies, including the use of smart health systems based on Artificial intelligence, IoT and Blockchain are trying to improve the early diagnosis and treatment of diabetic retinopathy. In this study, we presented an AI-based smart teleopthalmology application for diagnosis of diabetic retinopathy. The app has the ability to facilitate the analyses of eye fundus images via deep learning from the Kaggle database using Tensor Flow mathematical library. The app would be useful in promoting mHealth and timely treatment of diabetic retinopathy by clinicians. With the AI-based application presented in this paper, patients can easily get supports and physicians and researchers can also mine or predict data on diabetic retinopathy and reports generated could assist doctors to determine the level of severity of the disease among the people.

The rapid expansion of nanotechnology has transformed numerous sectors, with nanoproducts now ubiquitous in everyday life, electronics, healthcare, and pharmaceuticals. Despite their widespread adoption, concerns persist regarding potential adverse effects, necessitating vigilant risk management. This systematic literature review advocates for leveraging artificial intelligence (AI) and machine learning (ML) methodologies to enhance simulations and refine safety assessments for nanomaterials (NMs). Through a comprehensive examination of the existing literature, this study seeks to explain the pivotal role of AI in boosting NMs sustainability efforts across six key research themes. It explores their significance in advancing sustainability, hazard identification, and their diverse applications in this field. In addition, it evaluates the past sustainability strategies for NMs while proposing innovative avenues for future exploration. By conducting this comprehensive analysis, the research aims to illuminate the current landscape, identify challenges, and outline potential pathways for integrating AI and ML to promote sustainable practices within nanotechnology. Furthermore, it advocates for extending these technologies to monitor the real-world behaviour of NMs delivery. Through its thorough investigation, this systematic literature review endeavours to address current obstacles and pave the way for the safe and sustainable utilization of nanotechnology, thereby minimizing associated risks.

This study seeks to determine the impact of agricultural subsidies on the efficiency of Algerian farms. To do so, we estimated a Stochastic Frontier Analysis (SFA) for Algerian data covering the period from1970 to 2020. Two variables were used to describe the agricultural subsidy: the first is total agricultural support, and the second is a dummy variable that takes the values 0 and 1 to express the coupling of subsidies to production. The variable of support for agriculture production and producers takes the value of one (1) in the era when the support is not related to production (decoupled support). It takes the value zero (0) when there is explicit support for production and producers (coupled support).The findings revealed that total subsidies had a negative impact and statistically significant on the technical efficiency of Algerian farms. While, the decoupling has a positive effect on efficiency (negative on inefficiency), but without significance.

The aim of this paper is to study, both theoretically and empirically, tourism as a channel of Migration and Development. Relaying on migration networks and trade literature, the study suppose that migration networks affect positively tourism flows to the origin countries. Theoretically, global migration networks effect on tourism is composed of migrant generations, transactions, preferences and emigrants’ life style effects. Such effects could adapt, promote and advertise tourism flows to origin countries. Empirically, the gravity model has been used to estimate the global effect of networks on Moroccan tourism inflows from the eight principal immigration countries during the periods (2000, 2010, 2011, 2012, 2013 and 2014). Our study reveals that a ten-percent rise in the emigration rate from Morocco increases the real value of Moroccan tourism inflows by 1.3 %.   Key words: Migration, Networks, Tourism, Development.