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A Novel Approach to Aquifer Classification Using Hysteresis Loop Analysis and Deep Learning for Sustainable Groundwater Management

Aquifer classification plays a pivotal role in understanding groundwater dynamics and informing sustainable water resource management, especially in regions under significant stress from over-extraction. This study presents a novel remote sensing-based methodology for classifying aquifers represented by monitoring wells within the study area. The approach integrates stress-strain analysis, incorpo

Criticality Through Critical (Self- )Reflection in Student Teachers’ Placement in English Language Teacher Education

Critical reflection and self-reflection are two interrelated abilities universally perceived as fundamental for teachers’ professional practice. In European policy documents, these are also linked to the goal of building and consolidating education for democracy (Lenz et al., 2021, p. 9). Moreover, in the Swedish Higher Education Ordinance, they are mentioned in the second competence-and-skills ou

Changes in union density in the Nordic countries

Over the last 25 to 30 years, union density has experienced a significant decline in Denmark, Finland, and Sweden, while remaining relatively stable in Norway and completely unchanged in Iceland. In the first three countries, the weakening of Ghent systems (state-subsidised union unemployment funds) stands out as the primary factor contributing to union decline. In Sweden, this trend is further ex

Reimagining social work: letting go of futures past

Imminent crises and the much-needed transition to a sustainable society bring knowledge about de-implementation to the fore. Using case studies with inspiration from process tracing, and with tools from Charles Tilly’s theory on Durable inequality, we identify mechanisms that generate inequality and counteract the implementation of recovery – and strength-based practices. Our case studies of socia

Efficacy and Safety of Rituximab in Antiglomerular Basement Membrane Disease

Introduction: Anti–glomerular basement membrane (GBM) disease is caused by pathogenic antibodies usually targeting the noncollagenous domain of the α3 chain of type IV collagen and frequently presents as rapidly progressive glomerulonephritis and diffuse alveolar hemorrhage (DAH). Rapid reduction of these antibodies is imperative for kidney survival and the mainstay of therapy is the combination o

Nils Månsson Mandelgren och kampen för kulturens framtid

Nils Månsson Mandelgren och kampen för kulturens framtid är en antologi med syftet att ge nya perspektiv på Mandelgrens omfattande livsverk. Hittills har forskningen frmäst haft fokus på hans dokumentation av äldre kulturyttringar, men hans stridbarhet och oräddhet i att utmana etablissemanget hade sikte på hur samtidens och framtidens kulturinstitutioner borde utformas och organiseras. I boken di

Characterization of semiconductors by synchrotron-based techniques

Techniques based on intense photon beams from synchrotrons present unique opportunities for characterizing semiconductor materials, devices and processes. This is based on the unrivaled brightness in a broad wavelength range from infrared to hard X-rays. Synchrotron based methods can answer wide ranging questions in research and technology, and have seen an increase in use over many years as more

Development of a Software Based Telematic Gateway

Telematics units are widely spreading in the automotive industry. Getting realtime data from the systems is essential for creating services in the back office which builds value for both companies and end customers. The services created greatly impact maintenance strategies, future developments, and keeping the vehicle more sustainable and secure for both end users and customers. However, adding n

Privacy-Preserving Fall Detection using Federated Machine Learning in IoT-based Applications

Falls are one of the leading causes of injury and death among the elderly, creating a growing need for efficient and privacy-preserving fall detection systems. Traditional machine learning approaches for fall detection often rely on centralized data collection, where sensitive user data is collected and stored on a central server. This poses significant privacy risks, especially in the healthcare

ENHANCING DIGITAL TWINS WITH DEEP REINFORCEMENT LEARNING : A USE CASE IN MAINTENANCE PRIORITIZATION

This paper introduces an innovative framework that enhances digital twins with deep reinforcement learning (DRL) to support maintenance in manufacturing systems. Utilizing a sophisticated artificial intelligence (AI) layer, this framework integrates real-time and historical production data from a physical manufacturing system to a digital twin, enabling dynamic simulation and analysis. Maintenance

Maternal and perinatal outcomes after implementation of a more active management in late- and postterm pregnancies in Sweden : A population-based cohort study

Background The risk of perinatal death and severe neonatal morbidity increases : gradually after 41 weeks of pregnancy. We evaluated maternal and perinatal outcomes after a national shift from expectancy and induction at 42+0 weeks to a more active management of late-term pregnancies in Sweden offering induction from 41+0 weeks or an individual plan aiming at birth or active labour no later than 4