To save patients’ lives, it is important to go for an early diagnosis of intracranial hemorrhage (ICH). For diagnosing ICH, the widely used method is non-contrast computed tomography (NCCT). It has fast acquisition and availability in medical emergency facilities. To predict hematoma progression and mortality, it is important to estimate the volume of intracranial hemorrhage. Radiologists can manually delineate the ICH region to estimate the hematoma volume. This process takes time and undergoes inter-rater variability. In this research paper, we develop and discuss a fine segmentation model and a coarse model for intracranial hemorrhage segmentations. Basically, two different models are discussed for intracranial hemorrhage segmentation. We trained a 2DDensNet in the first model for coarse segmentation and cascaded the coarse segmentation mask output in the fine segmentation model along with input training samples. A nnUNet model is trained in the second fine stage and will use the segmentation labels of the coarse model with true labels for intracranial hemorrhage segmentation. An optimal performance for intracranial hemorrhage segmentation solution is obtained.

The Ecuadorian electricity sector encompasses generation, transmission, distribution and sales. Since the change of the Constitution in Ecuador in 2008, the sector has opted to employ a centralized model. The present research aims to measure the efficiency level of the Ecuadorian electricity sector during the period 2012–2021, using a DEA-NETWORK methodology, which allows examining and integrating each of the phases defined above through intermediate inputs, which are inputs in subsequent phases and outputs of some other phases. These intermediate inputs are essential for analyzing efficiency from a global view of the system. For research purposes, the Ecuadorian electricity sector was divided into 9 planning zones. The results revealed that the efficiency of zones 6 and 8 had the greatest impact on the overall efficiency of the Ecuadorian electricity sector during the period 2012–2015. On the other hand, the distribution phase is the most efficient with an index of 0.9605, followed by sales with an index of 0.6251. It is also concluded that the most inefficient phases are generation and transmission, thus verifying the problems caused by the use of a centralized model.

Private banking institutions serve the financial sector’s wealthiest clientele via a dedicated value proposition. Based on the relevant tendencies and statistics, a remarkable expansion can be outlined since the mid-1990s. The aim of this study is to elaborate the Hungarian private banking market’s development as a case study. The paper also intends to add to the literature on this unique segment of the financial market. Based on the available statistics, the analysis primarily focuses on the Hungarian private banking market’s rapid development process. This can be underpinned by the clientele’s savings, number of accounts and respective segmentation limits of the institutions. Referring to the amount of savings, a correlation analysis indicates significant co-movements with specific social and economic variables. The growth rate of the Hungarian clientele’s savings outperformed the respective indicator in Western Europe during the review time period (2007–2020). The current paper also includes a section that summarises general challenges that private banking managers need to address during the development process. Generally, the literature on private banking can still be considered scarce, whereas there is a lack of studies on the Central-Eastern European region. The analysis of the Hungarian sector’s development path can serve with relevant information to any financial expert in the field.

Relying on the D-Vine copula model, this paper delves into the hedging capabilities of Brent crude oil against the exchange rate of oil-exporting and oil-importing nations. The results affirm Brent crude oil’s role as a safeguard and a refuge against the fluctuations of major currencies. Furthermore, we reaffirm that oil retains its robust hedging and safe-haven attributes during times of crisis, with currency co-movements across all countries exhibiting greater correlation than during the entire dataset. Additionally, our empirical findings highlight an unusually positive correlation between Brent crude oil and the Russian exchange rate during the Russia-Ukraine conflict, demonstrating that oil functions as a less effective hedge and a less dependable refuge for the Russian exchange rate in such geopolitical turbulence.

Infrastructure development policies have been criticised for lacking a deliberate pro-gender and pro-informal sector orientation. Since African economies are dual enclaves, with the traditional and informal sectors female-dominated, failure to have gendered infrastructure development planning and investment exacerbates gender inequality. The paper examines the effect of the infrastructure development index, the size of the informal economy, and the level of economic development on gender inequality. The paper applies the panel autoregressive distributed lag method to data on the gender inequality index, infrastructure development index, GDP per capita, and size of the informal sector for the period 2005–2018. The sample consists of 44 African countries. The research established that the infrastructure development index, its sub-indices, GDP per capita, and the size of the informal sector are crucial dynamics that governments need to consider carefully when formulating development policies to reduce gender inequality. The research found that investment in infrastructure in general, transport infrastructure, and energy infrastructure reduces gender inequality. infrastructure development has gender inequality increasing effects in some countries and gender inequality reducing effects in others. The pattern suggests that at the continental level a Kuznets-type patten in the relationship between gender inequality and infrastructure development, gender inequality and size of informal sector, and gender inequality and GDP per capita exists. Some countries are in the region where changes in these covariates positively correlate with gender inequality, while others are in the region where further increases in the covariates reduce gender inequality.