Today urban development lacks ecological foundations in many cities of Turkey. The purpose of this study is to reveal the relationship between urban green spaces and ecological zones in the sample of Aksaray/Turkey. In this study, a study design has been created to improve the urban ecological infrastructure and to associate the green space network with the ecological zones. This design is divided into four parts as data processing, landscape pattern of urban green spaces, analysis of the spatial boundaries of urban natural ecological zones, and determination of the importance of spatial regions by overlaying two different stratified analyses. This study proposes a methodological framework that can be integrated into efforts to identify ecological zones to increase the sustainability of urban ecology and green space quality. One potential limitation of the proposed methodology can be the lack of consensus and enthusiasm among the administrative actors regarding the issue. Therefore, it is recommended that the administrative bodies should be correctly informed by the relevant scholars and practitioners who are working on the subject.

The paper deals with the issues of the influence of forest cover on the average annual runoff of rivers in the Pripyat River basin. In the study area, under the influence of solar radiation, the temperature of the air and the soil surface increases, evaporation from the water surface also increases, and the moisture content of the upper layers of the soil decreases. In general, with an increase in forest cover, the annual layer of the runoff of the studied rivers increases, as well as with an increase in the amount of precipitation (in contrast to the runoff of short-term floods). However, with a forest cover of more than 20%–30% and a relatively small amount of precipitation, the runoff decreases, which is associated with the retention of part of the precipitation by the forest cover. With a large amount of precipitation and low forest cover, the runoff also decreases, which is probably due to the loss of precipitation water for evaporation, etc. The conducted studies show that, just as the forest affects water resources, the flow of moisture to watersheds also affects the state of forest systems. Moreover, this interaction is expressed by evaporation from forests. Under influence of change of a climate growth of evaporation is observed.

Vehicle detection stands out as a rapidly developing technology today and is further strengthened by deep learning algorithms. This technology is critical in traffic management, automated driving systems, security, urban planning, environmental impacts, transportation, and emergency response applications. Vehicle detection, which is used in many application areas such as monitoring traffic flow, assessing density, increasing security, and vehicle detection in automatic driving systems, makes an effective contribution to a wide range of areas, from urban planning to security measures. Moreover, the integration of this technology represents an important step for the development of smart cities and sustainable urban life. Deep learning models, especially algorithms such as You Only Look Once version 5 (YOLOv5) and You Only Look Once version 8 (YOLOv8), show effective vehicle detection results with satellite image data. According to the comparisons, the precision and recall values of the YOLOv5 model are 1.63% and 2.49% higher, respectively, than the YOLOv8 model. The reason for this difference is that the YOLOv8 model makes more sensitive vehicle detection than the YOLOv5. In the comparison based on the F1 score, the F1 score of YOLOv5 was measured as 0.958, while the F1 score of YOLOv8 was measured as 0.938. Ignoring sensitivity amounts, the increase in F1 score of YOLOv8 compared to YOLOv5 was found to be 0.06%.

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).

This study informs the academic and policy debate on the policy effectiveness of exchange rate interventions on exchange rate levels and volatility. Using a constructed data set comprising daily data on exchange rates, monetary policy fundamentals, exchange rate intervention dates and magnitudes of those interventions as well as financial news speculation of such interventions, we empirically estimate the policy effectiveness of Bank of Japan interventions in the exchange rate over the 12-year period between 2010 and 2022. This allows us to investigate the policy effectiveness of a variety of exchange rate interventions, or news of exchange rate interventions, across different time-horizons. We find that policy interventions in the yen exchange rate are more effective over short-horizons than long-horizons, more effective when the policy objective is a competitive devaluation of the yen rather than a revaluation, and more effective at influencing the level of the yen against major world currencies other than the US dollar. In fact, for the yen-dollar rate, we find that policy interventions may have the unintended consequences of weakening the yen (when the policy intention is to strengthen it) and increasing volatility in the yen-dollar exchange rate.

UAVs, also known as unmanned aerial vehicles, have emerged as an efficient and flexible system for offering a rapid and cost-effective solution. In recent years, large-scale mapping using UAV photogrammetry has gained significant popularity and has been widely adopted in academia as well as the private sector. This study aims to investigate the technical aspects of this field, provide insights into the procedural steps involved, and present a case study conducted in Cesme, Izmir. The findings derived from the case study are thoroughly discussed, and the potential applications of UAV photogrammetry in large-scale mapping are examined. The study area is divided into 12 blocks. The flight plans and the distribution of ground control point (GCP) locations were determined based on these blocks. As a result of the data processing procedure, average GCP positional errors ranging from 1 to 18 cm have been obtained for the blocks.