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This chapter examines elite polarisation as a challenge to governance in parliamentary democracies. We emphasise the distinction between ideological polarisation based on substantive policy disagreements from affective polarisation, characterised by identity-based animosity that creates barriers to cooperation even when policy compromise might otherwise be possible. While parliamentary regimes hav
The current rise in geopolitical tensions has heightened the need to understand the intricate relationship between sustainability and security, particularly in the context of the Global South. However, existing academic literature has paid limited attention to exploring this interconnection. This study aims to synthesize the existing knowledge on the nexus of sustainability and security in the Glo
BACKGROUND: It remains unclear why cool temperatures cause more persistent adverse health effects compared to hot weather. Fluid homeostasis may constitute a causal link between past temperatures and adverse health effects. In this study we investigated the association between past outdoor temperatures and current fluid homeostasis.METHODS: We studied participants from five cohorts during three de
Brazed stainless steel joints are critical in heat exchanger applications but often suffer from residual stresses and brittle intermetallics. Using in-situ synchrotron X-ray diffraction and fluorescence at the DanMAX beamline, we investigated Fe-based filler joints in SS316 under tensile loading. Elemental mapping and phase analysis revealed distinct interfacial solidification zones (ISZ), atherma
CONTEXT: Melatonin regulates circadian rhythms and influences glucose metabolism. Altered melatonin secretion may contribute to the pathogenesis of type 2 diabetes (T2D), but prospective population-based evidence is scarce.OBJECTIVE: To examine whether low nocturnal melatonin secretion is associated with an increased risk of incident T2D in adults.METHODS: This prospective cohort study, with follo
Isospin symmetry, combined with shell-model description, has long been successful in reproducing nuclear structure and predicting mirror energy differences. However, these descriptions have been primarily limited to mirror nuclei with well-bound ground states. As one approaches the proton drip line, coupling to the continuum becomes important. Despite this, little is known about medium-mass nuclei
Introduction: The contribution of aortopulmonary collateral (APC) flow to pleural effusion (PE) after total cavopulmonary connection (TCPC) remains unclear. Excessive APC flow may alter mesenteric perfusion and increase ventricular volume load. We evaluated echocardiographic and mesenteric flow parameters as predictors of PE duration and their association with magnetic resonance imaging (MRI)-deri
Considering the unstable condition of water resources in Iran and many other countries in arid and semi-arid regions, groundwater studies are very important. Therefore, the aim of this study is to model groundwater potential by qanat locations as indicators and ten advanced and soft computing models applied to the Beheshtabad Watershed, Iran. Qanat is a man-made underground construction which gath
Regarding the ever increasing issue of water scarcity in different countries, the current study plans to apply support vector machine (SVM), random forest (RF), and genetic algorithm optimized random forest (RFGA) methods to assess groundwater potential by spring locations. To this end, 14 effective variables including DEM-derived, river-based, fault-based, land use, and lithology factors were pro
Landslide susceptibility mapping is among the first works for disaster management and land use planning activities in a mountain area like Ganzhou City. The aims of the current study are to assess GIS-based landslide spatial modeling using four models, namely data-driven evidential belief function (EBF), frequency ratio (FR), maximum entropy (Maxent), and logistic regression (LR), and to compare t
Ever increasing demand for water resources for different purposes makes it essential to have better understanding and knowledge about water resources. As known, groundwater resources are one of the main water resources especially in countries with arid climatic condition. Thus, this study seeks to provide groundwater potential maps (GPMs) employing new algorithms. Accordingly, this study aims to v
Assessment of the most appropriate groundwater conditioning factors (GCFs) is essential when performing analyses for groundwater potential mapping. For this reason, in this work, we look at three statistical factor analysis methods-Variance Inflation Factor (VIF), Chi-Square Factor Optimization, and Gini Importance-to measure the significance of GCFs. From a total of 15 frequently used GCFs, 11 mo
Groundwater is considered one of the most valuable fresh water resources. The main objective of this study was to produce groundwater spring potential maps in the Koohrang Watershed, Chaharmahal-e-Bakhtiari Province, Iran, using three machine learning models: boosted regression tree (BRT), classification and regression tree (CART), and random forest (RF). Thirteen hydrological-geological-physiogra
The yellow rust pathogen (Puccinia striiformis Westend) poses a significant threat to wheat production in the world, necessitating a comprehensive understanding of its spatiotemporal distribution and the influence of climatic factors. In this study, we employed an ensemble of four prominent machine learning algorithms to assess the impact of various environmental and remote sensing variables on th
A quantitative understanding of the hydro-environmental factors that influence the occurrence of agricultural drought events would enable more strategic climate change adaptation and drought management plans. Practical drought hazard mapping remains challenging due to possible exclusion of the most pertinent drought drivers, and to the use of inadequate predictive models that cannot describe droug
Considering the ever increasing financial damages of floods and the need to manage the surface water, the use of new and more sufficient methods seems to be necessary. Therefore, the present study aims to investigate capability of the Gamma, Beta, Chi-square, and Weibull probability distribution functions (PDFs) for flood hydrograph derivation. The present study was conducted in the Bar watershed,
Landslide is one of the most important natural hazards that make numerous financial damages and life losses each year in the worldwide. Identifying the susceptible areas and prioritizing them in order to provide an efficient susceptibility management is very vital. In current study, a comparative analysis was made between combined bivariate and AHP models (bivariate-AHP) with a logistic regression
