Soil erosion is characterized by the wearing away or loss of the uppermost layer of soil, driven by water, wind, and human activities. This process constitutes a significant environmental issue, with adverse effects on water quality, soil health, and the overall stability of ecosystems across the globe. This study focuses on the Anuppur district of Madhya Pradesh, India, employing the Revised Universal Soil Loss Equation (RUSLE) integrated with Geographic Information System (GIS) tools to estimate and spatially analyze soil erosion and fertility risk. The various factors of the model, like rainfall erosivity (R), soil erodibility (K), slope length and steepness (LS), conservation practices (P), and cover management factor (C), have been computed to measure annual soil loss in the district. Each factor was derived using geospatial datasets, including rainfall records, soil characteristics, a Digital Elevation Model (DEM), land use/land cover (LULC) data, and information on conservation practices. GIS methods are used to map the geographical variation of soil erosion, providing important information on the area’s most susceptible to erosion. The outcome of the study reveals that 3371.23 km², which constitutes 91% of the district’s total area, is identified as having mild soil erosion; in contrast, 154 km², or 4%, is classified as moderate soil erosion, while 92 km², representing 2.5%, falls under the high soil erosion category. Ad

The COVID-19 pandemic has brought life changing conditions to families that require coping strategies in order to survive and achieve family well-being. This study aims to analyze differences between single earner and dual earner families during the COVID-19 pandemic and to analyze the factors that influence subjective family well-being. The research design used was a cross sectional study with sample collection through non-probability sampling. Data collection was carried out by filling out questionnaires online. The number of respondents involved in the study was 2084 intact families with children residing in DKI Jakarta, West Java, and Banten Provinces. Reliability and validity tests were conducted. The results of the independent t-test showed that dual-earner families experienced better life changes and a higher level of subjective family well-being than single-earner families and had lower economic pressure and lower economic coping than single earner families. The SEM analysis found that life changes affected economic coping negatively and subjective family well-being positively. Family income influenced economic coping negatively and subjective family well-being positively. Finally, it was found that economic coping had no effect on subjective family well-being.

Cardiovascular imaging analysis is a useful tool for the diagnosis, treatment and monitoring of cardiovascular diseases. Imaging techniques allow non-invasive quantitative assessment of cardiac function, providing morphological, functional and dynamic information. Recent technological advances in ultrasound have made it possible to improve the quality of patient treatment, thanks to the use of modern image processing and analysis techniques. However, the acquisition of these dynamic three-dimensional (3D) images leads to the production of large volumes of data to process, from which cardiac structures must be extracted and analyzed during the cardiac cycle. Extraction, three-dimensional visualization, and qualification tools are currently used within the clinical routine, but unfortunately require significant interaction with the physician. These elements justify the development of new efficient and robust algorithms for structure extraction and cardiac motion estimation from three-dimensional images. As a result, making available to clinicians new means to accurately assess cardiac anatomy and function from three-dimensional images represents a definite advance in the investigation of a complete description of the heart from a single examination. The aim of this article is to show what advances have been made in 3D cardiac imaging by ultrasound and additionally to observe which areas have been studied under this imaging modality.

Objective: To describe magnetic resonance imaging (MRI) findings of the brain in patients younger than 65 years who were studied by transcranial Doppler (TCD) with microbubble contrast, with a history of cryptogenic cerebrovascular accident (CVA) and suspected patent foramen ovale (PFO).

Materials and methods: This retrospective cross-sectional study included patients of both sexes, younger than 65 years of age.

Results: Our sample (n = 47.47% male and 53% female, mean age is 42 years) presented high-intensity transient signals (HITS) positive in 61.7% and HITS-negative in 38.3%. In HITS-positive patients, lesions at the level of the subcortical U-brains, single or multiple with bilaterally symmetrical distribution, predominated. In patients with moderate HITS, lesions in the vascular territory of the posterior circulation predominated.

Conclusion: In patients younger than 65 years with cryptogenic stroke and subcortical, single or multiple U-shaped lesions with bilateral and symmetrical distribution, a PFO should be considered as a possible cause of these lesions.

The range migration algorithm (RMA) is an accurate imaging method for processing synthetic aperture radar (SAR) signals. However, this algorithm requires a big amount of computation when performing Stolt mapping. In high squint and wide beamwidth imaging, this operation also requires big memory size to store the result spectrum after Stolt mapping because the spectrum will be significantly expanded. A modified Stolt mapping that does not expand the signal spectrum while still maintains the processing accuracy is proposed in this paper to improve the efficiency of the RMA when processing frequency modulated continuous wave (FMCW) SAR signals. The modified RMA has roughly the same computational load and required the same memory size as the range Doppler algorithm (RDA) when processing FMCW SAR data. In extreme cases when the original spectrum is significantly modified by the Stolt mapping, the modified RMA achieves better focusing quality than the traditional RMA. Simulation and real data is used to verify the performance of the proposed RMA.

This research delves into the correlation between institutional quality and tourism development in a panel of nine Mediterranean countries within the European Union spanning from 1996 to 2021. The study gauges tourism development by examining tourist arrivals, while considering GDP growth rate, inflation, higher education, environmental quality, and trade as control variables representing factors influencing tourism. Institutional quality is measured through indicators such as regulatory quality, rule of law, and control of corruption. Utilizing Fully Modified Ordinary Least Square (FMOLS) and Dynamic Ordinary Least Squares (DOLS) models, the study aims to quantify the impact of these factors on tourism development. The findings indicate a positive relationship between institutional quality and tourism, shedding light on the pivotal role of institutions in tourism management and their influence on the sector. These results have implications for shaping national development strategies.