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The cuprate superconductor La2−xBaxCuO4 (LBCO) near x = 0.125 is a striking example of intertwined electronic orders, where 3D superconductivity is anomalously suppressed, allowing spin and charge stripe order to develop. Understanding this interplay remains a key challenge in cuprates, highlighting the necessity of external tuning for deeper insight. While in-plane uniaxial stress enhances superc

Single motherhood has long been a feature of European family systems, but its meaning and determinants have changed substantially over time. Using longitudinal individual-level data from the Scanian Economic and Demographic Database (SEDD), covering southern Sweden between 1905 and 2015, we examine the changing demography of single motherhood from a long-term life course perspective. We analyze ho

What happens when the infrastructure designed to connect a city ends up dividing it instead? This thesis investigates the relationship between urban mobility and spatial justice, examining how roads, railways, and transit corridors generate barriers that are not only physical but social and cultural: separating communities, limiting access to opportunity, and reinforcing patterns of inequality ins

We present a summary of ideas that attempt to explain how the locomotor cerebellum may represent and process information. It includes the proposals that (i) the main network computation is a passive and unlearned effect of cell type morphologies and neural architecture; (ii) information has topographically defined spatial dimensions; (iii) it is coded at collective level, at any instant, in any ra

The pursuit of a unifying theory for non-BCS superconductivity has faced significant challenges. One approach to overcome such challenges is to perform systematic investigations into superconductors containing d-electron metals in order to elucidate their underlying mechanisms. Recently, the Sc6MTe2 (M = d-electron metal) family has emerged as a unique series of isostructural compounds exhibiting

The Kagome lattice has emerged as a promising platform for hosting unconventional chiral charge orders at high temperatures. In the context of the correlated Kagome superconductor LaRu3Si2, a room-temperature charge-ordered state with a propagation vector of ((Formula presented.), 0, 0) is previously reported. However, understanding the interplay between this charge order and superconductivity, pa

Freshwater ecosystems in the central Andes provide critical ecosystem services (ES), including water purification, baseflow regulation, groundwater recharge, and cultural and recreational benefits. However, these high-mountain systems are increasingly threatened by changing land use, climate variability, and accelerating pressure on water resources. Understanding local willingness to pay for conse

The interplay between superconductivity and charge or spin order is a key focus in condensed matter physics, with kagome lattice systems providing unique insights. The kagome superconductor LaRu3Si2 (Tc ≃ 6.5 K) features a characteristic kagome band structure and a hierarchy of charge order transitions at Tco,I ≃ 400 K and Tco,II ≃ 80 K, along with an additional transition at T* ≃ 35 K associated

Understanding how time-reversal symmetry (TRS) breaks in quantum materials is key to uncovering new states of matter and advancing quantum technologies. However, unraveling the interplay between TRS breaking, charge order, and superconductivity in kagome metals continues to be a compelling challenge. Here, we investigate the kagome metal Cs(V1−xNbx)3Sb5 with x = 0.07 using muon spin rotation (μSR)

Across Europe, freshwater ecosystems were simultaneously shaped by climate variability, land-use intensification, and accelerating socio-economic pressures, yet their combined effects on surface water quality and freshwater ecosystem service (FES) potential remained poorly understood at large spatial scales. While individual stressors were often examined in isolation, their interaction across hete

IntroductionAnal squamous cell carcinoma (ASCC) is an HPV-related tumor primarily treated with concurrent chemoradiotherapy (CRT). Salvage surgery is reserved for patients with residual or recurrent disease following CRT, representing a highly selected, high-risk subgroup. Population-based data on outcomes and prognostic factors after salvage surgery are limited. This study aimed to assess overall

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 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