In the present study, friction damper, an energy dissipating passive device is explored to reduce the response of open ground storey building under lateral loading due to earthquake. This damper is installed in the selected bays of open ground storey so that the response is reduced. The masonry infill wall is macro-modeled in the form of compression only diagonal members. Three different types of bracing system were installed along with Pall friction damper – single diagonal tension – compression brace with friction damper, tension only cross brace with friction damper and chevron brace with friction damper were modeled using Wen’s plastic link element in SAP2000. G+4 storey buildings were analyzed using nonlinear time history analysis. The storey displacement and inter-storey drift for all the cases were compared in the study.

The Organic Rankine Cycle (ORC) is an electricity generation system that uses organic fluid instead of water in the low temperature range. The Organic Rankine cycle using zeotropic working fluids has wide application potential. In this study, data mining (DM) model is used for performance analysis of organic Rankine cycle (ORC) using zeotropik working fluids R417A and R422D. Various DM models, including Linear Regression (LR), Multi-Layer Perceptron (MLP), M5 Rules, M5 Model Tree, Random Committee (RC), and Decision Tree (DT) models are used. The MLP model emerged as the most effective approach for predicting the thermal efficiency of both R417A and R422D. The MLP’s predicted results closely matched the actual results obtained from the thermodynamic model using Genetron software. The Root Mean Square Error (RMSE) for the thermal efficiency was exceptionally low, at 0.0002 for R417A and 0.0003 for R422D. Additionally, the R-squared (R²) values for thermal efficiency were very high, reaching 0.9999 for R417A and R422D. The findings demonstrate the effectiveness of the DM model for complex tasks like estimating ORC thermal efficiency. This approach empowers engineers with the ability to predict thermal efficiency in organic Rankine systems with high accuracy, speed, and ease.

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.

This paper carries out an analysis and reflection on how technoscience reaches Geography through Geographic Information Technologies, how it impacts the production of geographic knowledge and how it derives in the possibility of digital experimentation in the discipline in an environment called geo-digital reality. It is shown that advances in GIT have allowed overcoming old limitations, enriching more and more the observations made by Geography, and it is also highlighted the promising future of digital experimentation in Geography through all the possibilities offered by current technological developments.

In order to strengthen the study of soil-landscape relationships in mountain areas, a digital soil mapping approach based on fuzzy set theory was applied. Initially, soil properties were estimated with the regression kriging (RK) method, combining soil data and auxiliary information derived from a digital elevation model (DEM) and satellite images. Subsequently, the grouping of soil properties in raster format was performed with the fuzzy c-means (FCM) algorithm, whose final product resulted in a fuzzy soil class variation model at a semi-detailed scale. The validation of the model showed an overall reliability of 88% and a Kappa index of 84%, which shows the usefulness of fuzzy clustering in the evaluation of soil-landscape relationships and in the correlation with soil taxonomic categories.

Ce⁴⁺-doped nanometer ZnO powder was synthesized by so-l gel method. The microstructures and properties of the samples were characterized through XRD, UV-Vis and FTIR. The results indicated that the Ce⁴⁺ was successfully incorporated into ZnO, and the diameter of the nanometer was about 10.7nm. It induced the redshifting in the UV-Vis spectra. The photocatalytic activity of the samples was investigated using methylene blue (MB) as the model reaction under irradiation with ultraviolet light. The results showed that the doping of Ce⁴⁺ could increase the photocatalytic activities of ZnO nanopowders and that the best molar ratio of Ce⁴⁺ was n(Ce)/n(Zn) = 0.05, that the surfactant was sodium dodecyl sulfate, and that the nanometer ZnO was calcinated at 550 ℃ for 3 hours. Meanwhile, it inspected the effect of photocatalytic efficiency through the pH of MB, the amount of catalyst, and illumination time. The experimental results revealed that the initial mass concentration of MB was 10 mg/L, that the pH value was 7-8, that the dosage of Ce⁴⁺/ZnO photo-catalyst was 5 g/L, that the UV-irradiation time was 2 h, and that the removal rate of MB reached above 85%. Under the optimized conditions, the degradation rate of real dye wastewater was up to 87.67% and the removal efficiency of COD was 63.5%.