After the oil and economic boom of the 20th century, Doha experienced significant development in terms of the architectural scene, design, function, and sociocultural transformations. The advancements in global architecture have facilitated innovative and streamlined construction processes, while creating a paradigm shift in the overall architecture of dwellings and how people navigate around the house. In this context, this research aims to study the impact of globalization on housing typologies and the factors influencing their evolution, focusing on the city of Doha as a case study. This study is based on a qualitative research approach that centers its investigation on Doha while exploring strategies for preserving Arabic-Islamic identity. The research investigation used a content analysis methodology to analyze three additional case studies within the MENA region. The results indicate that new housing typologies have emerged in cities due to globalization and changes in physical and sociocultural dimensions. In addition, preserving older neighborhoods and housing typologies through a bottom-up approach is essential for design creativity and climatic and sociocultural sensitivity while exchanging knowledge and sharing experiences between generations. Furthermore, this article promotes heritage awareness and encourages local authorities to preserve Doha’s surviving historic neighborhoods and architectural language to restore the city’s urban identity. The findings of this research can provide helpful guidance to architects and urban planners on how Doha’s housing has developed until the contemporary period.

As urbanisation increases, questions arise about the desirability of further urban growth, as it was not accompanied by corresponding economic growth, and social and environmental problems began to grow in the largest cities in the world. The objective of the article is to substantiate the limits of urbanization growth in Kazakhstan based on the study of theoretical views on this process, analysis of the dependence of social and economic parameters of 134 countries on the urbanisation level and calculation of the urbanisation level that contributes most to economic growth and social well-being. To achieve the goal, the following tasks have been set and solved: theoretical views on the process of urbanization have been generalized; a hypothesis has been put forward about the emergence of an “urbanization trap” in which the growth of large cities is not accompanied by economic growth and improvement of social well-being; an analysis of the dependence of socio-economic indicators on the level of urbanization has been carried out on the example of 134 countries of the world; the level of urbanization that maximizes economic growth and social well-being is calculated; the necessity of the development of small towns in Kazakhstan is substantiated. To solve the problems, the methods of logical analysis, analogies and generalizations, economic statistics, index, graphical, Pearson correlation analysis, Spearman and Kendall rank regression based on models in SPSS were used. As a result, the following conclusions are made: the hypothesis of a possible deterioration of socio-economic indicators in large cities is confirmed; the best positive result is demonstrated by the level of urbanization of 50%–59%. The recommendations are justified: in Kazakhstan, it is necessary to adhere to the level of urbanization no higher than 59%; the growth of urbanization should be ensured through the development of small towns; it is necessary to improve the methods of managing the process of urbanization and develop individual city plans.

Hydroponics is a modern agricultural system that enables year-round plant growth. Biochar, derived from apple tree waste, and humic acid were investigated as a replacement for the Hoagland nutrient solution to grow strawberries in a greenhouse with three replications. Growth parameters, such as leaf area, the average number of fruits per plant, maximum fruit weight, and the weight of fresh and dry fruits, were measured. A 50% increase in fresh and dry fruit weight was observed in plants grown using biochar compared to the control. Additionally, the use of Hoagland chemical fertilizer led to a 25% increase in both fresh and dry weight. There was a 65% increase in the number of fruits per plant in the biochar-grown sample compared to the control. Moreover, biochar fertilizer caused a 100% increase in maximum fruit weight compared to the control and a 27% increase compared to the Hoagland chemical fertilizer. Biochar had a higher pH compared to the Hoagland solution, and such pH levels were conducive to strawberry plant growth. The results indicate that biochar has the potential to enhance the size and weight of fruits. The findings of the study demonstrate that biochar, when combined with humic acid, is a successful organic hydroponic fertilizer that improves the quality and quantity of strawberries. Moreover, this approach enables the more efficient utilization of garden waste.

Fire hazard is often mapped as a static conditional probability of fire characteristics’ occurrence. We developed a dynamic product for operational risk management to forecast the probability of occurrence of fire radiative power in the locally possible near-maximum fire intensity range. We applied standard machine learning techniques to remotely sensed data. We used a block maxima approach to sample the most extreme fire radiative power (FRP) MODIS retrievals in free-burning fuels for each fire season between 2001 and 2020 and associated weather, fuel, and topography features in northwestern south America. We used the random forest algorithm for both classification and regression, implementing the backward stepwise repression procedure. We solved the classification problem predicting the probability of occurrence of near-maximum wildfire intensity with 75% recall out-of-sample in ten annual test sets running time series cross validation, and 77% recall and 85% ROC-AUC out-of-sample in a twenty-fold cross-validation to gauge a realistic expectation of model performance in production. We solved the regression problem predicting FRP with 86% r² in-sample, but out-of-sample performance was unsatisfactory. Our model predicts well fatal and near-fatal incidents reported in Peru and Colombia out-of-sample in mountainous areas and unimodal fire regimes, the signal decays in bimodal fire regimes.

The silver nanoparticles (AgNPs) exhibit unique and tunable plasmonic properties. The size and shape of these particles can manipulate their localized surface plasmon resonance (LSPR) property and their response to the local environment. The LSPR property of nanoparticles is exploited by their optical, chemical, and biological sensing. This is an interdisciplinary area that involves chemistry, biology, and materials science. In this paper, a polymer system is used with the optimization technique of blending two polymers. The two polymer composites polystyrene/poly (4-vinylpyridine) (PS/P4VP) (50:50) and (75:25) were used as found suitable by their previous morphological studies. The results of 50, 95, and 50, 150 nm thicknesses of silver nanoparticles deposited on PS/P4VP (50:50) and (75:25) were explored to observe their optical sensitivity. The nature of the polymer composite embedded with silver nanoparticles affects the size of the nanoparticle and its distribution in the matrix. The polymer composites used are found to have a uniform distribution of nanoparticles of various sizes. The optical properties of Ag nanoparticles embedded in suitable polymer composites for the development of the latest plasmonic applications, owing to their unique properties, were explored. The sensing capability of a particular polymer composite is found to depend on the size of the nanoparticle embedded in it. The optimum result has been found for silver nanoparticles of 150 nm thickness deposited on PS/P4VP (75:25).

Tidal sea level variations in the Mediterranean basin, although altered and amplified by resonance phenomena in confined sub-basins (e.g., Adriatic Sea), are generally confined within 0.5 meters and exceptionally up to 1.5 meters. Here we explore the possibility of retrieving sea level measurements using data from GNSS antennas on duty for ground motion monitoring and analyze the spectral outcomes of such distinctive measurements. We estimate one year of GNSS data collected on the Mediterranean coasts in order to get reliable sea level data from all publicly available data and compare it with collocated tide gauges. A total of eleven stations were suitable for interferometric analysis (as of 2021), and all were able to supply centimeter-level sea level estimates. The spectra in the tidal frequency windows are remarkably similar to tide gauge data. We find that the O₁ and M₂ diurnal and semidiurnal tides and MK₃, MS₄ shallow sea water tides may be disturbed by aliasing effects.