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Serial Drama as a Catalyst for Gender Equality:Introducing Gender Equality through Media Pedagogy
Get PDFIn this article, the editors highlight the pressing need for the educational reinforcement of gender equality as a principle in European societies. Media has been central both to the organisation of gender equality initiatives and activities and to the resistance to it. While media is often cited as the cause or agent of anti-gender rhetoric, it is also leveraged for the promotion of gender equality as evidenced in the increasing visibility of and attention to gender issues across various media including TV and film, broadcasting, social media and the press. The editors attend specifically to serial drama as a tool and catalyst for the promotion of gender equality. Focusing on young people as key stakeholders in gender equality and change agents for an equitable world, the introduction and contributions to the issue identify some of the challenges that educators face in teaching gender equality and proposes several valuable tools and techniques for using serial dramas addressed to or watched by young people.In this article, the editors highlight the pressing need for the educational reinforcement of gender equality as a principle in European societies. Media has been central both to the organisation of gender equality initiatives and activities and to the resistance to it. While media is often cited as the cause or agent of anti-gender rhetoric, it is also leveraged for the promotion of gender equality as evidenced in the increasing visibility of and attention to gender issues across various media including TV and film, broadcasting, social media and the press. The editors attend specifically to serial drama as a tool and catalyst for the promotion of gender equality. Focusing on young people as key stakeholders in gender equality and change agents for an equitable world, the introduction and contributions to the issue identify some of the challenges that educators face in teaching gender equality and proposes several valuable tools and techniques for using serial dramas addressed to or watched by young people
Aortic Root Replacement Procedures:A Validation Study of the Western Denmark Heart Registry from 1999 to 2022
Get PDFBackground/Objectives: We reviewed data from the Western Danish Heart Registry (WDHR), which collects mandatory information on heart surgeries in Western Denmark, to validate cases with aortic root replacement (ARR) and assess the validity of registered data for all recorded cases. Methods: Patients registered in the WDHR with Danish Health Care Classification System (SKS) codes KFC and KFM from January 1999 to April 2022 were reviewed using electronic medical records. All patients who underwent ARR were included, and clinical data from the WDHR were adjudicated against electronic medical records. Results: A total of 847 cases with ARR were identified. Missing values averaged 12.0% in baseline variables (range: 3.2–22.1%), 7.3% in EuroSCORE II variables (range: 0.8–48.9%), and 5.5% in postoperative outcome variables (range: 4.1–8.1%). After adjudication, unrecovered data averaged 6.5% for baseline variables (range: 0.1–11.7%), 5.3% for EuroSCORE II variables (range: 0–32.5%), and 0.5% for postoperative outcomes (range: 0–0.8%). Missing data among EuroSCORE II were lower from 2012 and beyond (2.9% (range: 0.6–14.3%)). The median EuroSCORE II according to the WDHR was 6.2% (95% confidence interval 1.4–6.3) and after adjudication 10.7% (95% confidence interval 3.3–13.3). The positive predictive value for arrhythmia, central nervous damage, dialysis, reoperation for bleeding, and reoperation for ischemia exceeded 95%. Conclusions: The WDHR demonstrated overall value for clinical epidemiological research in ARR, but cases require validation to differentiate between procedures due to insufficient coding, while adjudication resulted in significantly higher data completeness for the majority of the variables.</p
Thermosensory predictive coding underpins an illusion of pain
Get PDFThe human brain has a remarkable ability to learn and update its beliefs about the world. Here, we investigate how thermosensory learning shapes our subjective experience of temperature and the misperception of pain in response to harmless thermal stimuli. Through computational modeling, we demonstrate that the brain uses a probabilistic predictive coding scheme to update beliefs about temperature changes based on their uncertainty. We find that these expectations directly modulate the perception of pain in the thermal grill illusion. Quantitative microstructural brain imaging further revealed that individual variability in computational parameters related to uncertainty-driven learning and decision-making is reflected in the microstructure of brain regions such as the precuneus, posterior cingulate gyrus, cerebellum, as well as basal ganglia and brainstem. These findings provide a framework to understand how the brain infers pain from innocuous thermal inputs, with important implications for the etiology of thermosensory symptoms under chronic pain conditions.</p
Giving the child with diabetes a clear voice: what matters the most to children with type 1 diabetes attending a pediatric diabetes clinic? A substudy in the ProKidsDia project
No full textPreoperative prediction models for postoperative delirium in cardiac surgery patients–a scoping review
No full textBackground: Postoperative delirium is believed to be preventable in up to 40% of all cases. Researchers have proposed various preoperative risk prediction models for postoperative delirium in patients undergoing cardiac surgery, however, no consensus exists on which model is the most suitable. Aim: To identify and map existing preoperative risk prediction models, detecting cardiac surgery patients at elevated risk of developing postoperative delirium. Design: This scoping review considered cohort and case-control studies eligible if they developed or validated preoperative prediction models for postoperative delirium, in adult patients admitted for cardiac surgery via sternotomy. Data Sources: The primary search was conducted on May 6th, 2022, and a secondary search was conducted on September 18th, 2024. We searched MEDLINE, CINAHL, Embase, and PsycINFO where 2126 references were identified and 15 were included for full-text analysis. Method: This scoping review was conducted in line with the Systematic Reviews and Meta-Analyses extension for Scoping Reviews (the PRISMA-ScR) guideline. Results: Twelve unique risk prediction models and three validation studies were included in this review, comprising between 77 and 45,744 participants. In total, 157 candidate prognostic variables were investigated of which 40 had a predictive value and thus, were included in the prediction models. The included models revealed an AUC from 0.68–0.93 in the derivation cohorts and 0.61–0.89 in the validation cohorts. Conclusions: Twelve unique prediction models and 3 validation studies were identified and mapped. Collectively, the models demonstrated an AUC ranging from 0.61–0.93, indicating a fair to good discrimination performance. Protocol Registration: A protocol is registered at Open Science Framework (OSF) https://osf.io/wr93y/?view_only=d129c3bb6be04357bac35c2c41ba2a40.</p
Robust Distribution System State Estimation Considering Anomalous Real-Time Measurements and Topology Change
No full textThis paper develops a physics-guided graph network to enhance the robustness of distribution system state estimation (DSSE) against anomalous real-time measurements, as well as a deep auto-encoder (DAE)-based detector and a Gaussian process-aided residual learning (GARL) to deal with challenges arising from topology changes. A global-scanning jumping knowledge network (GSJKN) is first designed to establish the regression rule between the measurement data and state variables. The structural information of distribution system (DS) and a global-scanning module are incorporated to guide the propagation of scarce measurements in the graph topology, contributing to valid estimation precision in sparsely measured DSs. To monitor the topology changes of the network, a DAE network is employed to learn an efficient representation of the measurements of the system under a certain topology, which can achieve online monitoring of the network structure by observing the variation tendency of the reconstruction error. When the topology change occurs, a Gaussian process with a composite kernel is applied to the modeling of the pretrained GSJKN residual to adapt to the new topology. The embedding of the physical structural knowledge enables the proposed GSJKN method to restore the missing/noisy values utilizing the adjacent measurements, which enhances the robustness to typical data acquisition errors. The adopted DAE network and special GARL-based transfer method further allow the DSSE method to rapidly detect and adapt to the topology change, as well as achieve effective quantification of the estimation uncertainties. Comparative tests on balanced and unbalanced systems demonstrate the accuracy, robustness, and adaptability of the proposed DSSE method.</p
Telemedicine-based integrated management of atrial fibrillation in village clinics:a cluster randomized trial
No full textIn rural China, where healthcare relies on village doctors (nonspecialized practitioners who work exclusively in their village clinics), delivering integrated atrial fibrillation (AF) management poses challenges. We developed a telemedicine-based, village doctor-led integrated care model and conducted a cluster randomized clinical trial to assess its efficacy compared to usual care. A total of 30 village clinics were randomly assigned (1:1) to the intervention or control group, with 1,039 village residents aged ≥65 years with AF (44.3% women) recruited. The primary outcome in stage 1 is adherence to integrated AF care at 12 months. In stage 2, the primary outcome is a composite of cardiovascular death, all strokes, heart failure or acute coronary syndrome hospitalization, and AF emergency visits over 36 months. Both primary outcomes were met. At 12 months, 33.1% in the telemedicine-based, village doctor-led care group and 8.7% in the usual care group met all criteria for integrated AF care (between-group difference, 24.4% (95% confidence interval (CI), 18.3–30.5%); P < 0.001). Over 34.0 months, 41.8% in the telemedicine-based, village doctor-led care group and 10.3% in the usual care group met all criteria for integrated AF care (P < 0.001). The rate of the composite cardiovascular event outcome was lower in the telemedicine-based, village doctor-led care group than in the usual care group (6.2% versus 9.6% per year; hazard ratio, 0.64 (95% CI, 0.50–0.82); P < 0.001). Our trial intervention by this telemedicine-based integrated care delivery model of AF care in rural villages demonstrates better adherence and improved clinical outcomes compared to usual care. ClinicalTrials.gov registration: NCT04622514.</p
Metal-Organic Framework Glass Composites for Sustainable Water Solutions
No full textAccess to safe, clean, and adequate water is vital for human sustainability and well-being. Despite water covering 71% of Earth’s surface, hardly 0.03% of its freshwater is directly accessible for human use. Desalination of seawater, while a promising solution to access clean water, is hindered by the removal of scaling ions such as calcium (Ca²⁺) and magnesium (Mg²⁺), damaging equipment and reducing efficiency. Unfortunately, polymeric membranes and ion exchange resins employed in current desalination systems present several drawbacks such as thermal sensitivity, low selectivity, etc. This work introduces a unique hybrid material by functionalizing a metal-organic framework (MOF) glass with a traditional oxide glass. This novel composite material synergistically combines the processability and durability of traditional oxide glass with the adjustable porosity and ion selectivity of MOFs. The resulting hybrid demonstrates very high efficiency in removing Ca²⁺ and Mg²⁺ ions, outperforming existing adsorbents including current commercial standards. To validate its effectiveness, we have tested seawater samples obtained from various locations (Red Sea-Saudi Arabia, Mediterranean Sea-Spain, and Baltic Sea-Denmark), yielding excellent outcomes in seawater softening (removal of Ca2+ and Mg2+ ions) applications. Furthermore, we have developed a self-standing membrane based on the moldability of the hybrid systems, enabling scalable and reliable seawater softening
Eight-Element MIMO Antenna with Closely Spaced Loop Resonators for THz and 6G Systems
No full textThis study proposes an innovative terahertz (THz) MIMO antenna architecture comprising four pairs of loop elements, strategically positioned at the four corners of a low-profile Rogers 5880 substrate with dimensions of 155× 155 μ m 2. Each corner integrates closely spaced L-ring/loop resonators, designed to ensure minimal mutual coupling and maintain satisfactory isolation between adjacent elements. The antenna is optimized to operate efficiently within the 4.4-5.2 THz frequency range, offering polarization diversity and enhanced radiation coverage, which are critical for achieving seamless and robust connectivity in high-frequency communication systems. Extensive full-wave simulations have been carried out to evaluate key performance metrics such as gain, efficiency, isolation, and radiation patterns. The results demonstrate the antenna's strong potential for integration into future 6G and THz wireless platforms, where compactness, efficiency, and wide coverage are essential requirements.</p
Whole Genome Sequencing in Prenatal Diagnostics:The Danish Approach to Guideline Formation and Implementation Within Public Healthcare
No full textObjective: To describe the implementation of whole genome sequencing (WGS) in prenatal diagnostics and outline the national guideline system facilitating this. Methods: Clinical guidelines for WGS in prenatal diagnostics were developed and implemented by the Danish Fetal Medicine Society. Results: Guidelines were developed by expert consensus following a review of 75 studies. Diagnostic yield served as a key factor in prioritizing WGS for various phenotypes, improving diagnostic accuracy and informing clinical decisions. Phenotypes for WGS include nuchal translucency ≥ 6.0 mm, multiple anomalies, skeletal dysplasia, neuromuscular diseases, non-immune hydrops fetalis, central nervous system malformations, congenital diaphragmatic hernia and severe fetal growth restriction (< 3 SDs not explained by placental insufficiency). Small regional variations exist in indications, bioinformatics, and funding, but WGS is now routinely used nationwide for these indications. Conclusion: The Danish Fetal Medicine Society's guideline development, emphasizing diagnostic yield and gradual implementation, has supported the relatively uniform integration of WGS into prenatal diagnostics.</p