The erudite priest Marciano Di Leo (1751–1819), a prominent personality in the historical and geographical panorama of his time, not only in his home territory, authored a vast literary and poetic production but also tried his hand at producing some maps, referring to a province of the Kingdom of Naples. At a time when the principles of geodetic cartography had become increasingly known, even locally, hand in hand with improvements in technology and accuracy of measurements, the author reflected on the historical narratives of the progress of the European (and Neapolitan) Enlightenment and translated them into an unpublished manuscript of statistical, historical, and geographical nature, accompanied by numerous maps of various scales. The rediscovery of a largely unknown—and therefore not very thorough—minor cartographic production underscores the spread, even in more marginal contexts, of the most innovative ideas and increasingly precise scientific foundations in the cartographic-mathematical representation of the territory. It also illustrates the role of a number of intellectuals in the service of the political choices of their time, in an attempt—often unrealized—to bring about a decisive change of course in public administration, in accordance with Enlightenment ideals and in the spirit of reform that spread throughout Europe thanks to the French Revolution.

To study the environment of the Kipushi mining locality (LMK), the evolution of its landscape was observed using Landsat images from 2000 to 2020. The evolution of the landscape was generally modified by the unplanned expansion of human settlements, agricultural areas, associated with the increase in firewood collection, carbonization, and exploitation of quarry materials. The problem is that this area has never benefited from change detection studies and the LMK area is very heterogeneous. The objective of the study is to evaluate the performance of classification algorithms and apply change detection to highlight the degradation of the LMK. The first approach concerned the classifications based on the stacking of the analyzed Landsat image bands of 2000 and 2020. And the second method performed the classifications on neo-images derived from concatenations of the spectral indices: Normalized Difference Vegetation Index (NDVI), Normalized Difference Building Index (NDBI) and Normalized Difference Water Index (NDWI). In both cases, the study comparatively examined the performance of five variants of classification algorithms, namely, Maximum Likelihood (ML), Minimum Distance (MD), Neural Network (NN), Parallelepiped (Para) and Spectral Angle Mapper (SAM). The results of the controlled classifications on the stacking of Landsat image bands from 2000 and 2020 were less consistent than those obtained with the index concatenation approach. The Para and DM classification algorithms were less efficient. With their respective Kappa scores ranging from 0.27 (2000 image) to 0.43 (2020 image) for Para and from 0.64 (2000 image) to 0.84 (2020 image) for DM. The results of the SAM classifier were satisfactory for the Kappa score of 0.83 (2000) and 0.88 (2020). The ML and NN were more suitable for the study area. Their respective Kappa scores ranged between 0.91 (image 2000) and 0.99 (image 2020) for the LM algorithm and between 0.95 (image 2000) and 0.96 (image 2020) for the NN algorithm.

This study explores approaches to optimizing inclusive education through international and local perspectives. It examines the role of educators in inclusive settings, highlights strategies for early detection of children’s developmental needs, and evaluates inclusive school management practices. Using qualitative case study methods, the research includes comprehensive observations and interviews at Fatma Kenanga Islamic Character School. Findings emphasize the importance of individualized learning plans, shadow teacher involvement, and collaborative stakeholder engagement. Integrating global insights, this study contributes to advancing inclusive education practices in Indonesia and beyond.

Tourism stands as a cornerstone industry, experiencing continual expansion within the global economy, and is increasingly acknowledged for its crucial role as an economic catalyst. The convergence of the tourism sector with the film culture industry amplifies the economic advantages of regions and enriches cultural narratives while bolstering the international resonance of regional brands. This study examines the promotional efficacy of adapted films in fostering the development of local tourism sectors. It investigates the impact of adapted films on the development of local tourism economy and provides a new analytical perspective to describe their specific contribution to the tourism economy. Empirical findings underscore that adapted films imbued with regional nuances substantially augment local tourism revenue, catalyzing the growth of the tourism sector. This highlights the capacity of adapted films to amplify regional exposure, nurturing the expansion of the local tourism economy. The findings of the study reveal that the promotional impact of adapted films on local tourism sectors is more pronounced in less developed regions than in more developed regions. Moreover, areas with limited transportation infrastructure witness a heightened promotional effect from the film industry. Rigorous robustness and endogeneity tests corroborate the reliability of these findings.