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The European Union has set ambitious CO 2 reduction targets, stimulating renewable energy production and accelerating deployment of offshore wind energy in northern European waters, mainly the North Sea. With increasing size and clustering, offshore wind farms (OWFs) wake effects, which alter wind conditions and decrease the power generation efficiency of wind farms downwind become more important. We use a high-resolution regional climate model with implemented wind farm parameterizations to explore offshore wind energy production limits in the North Sea. We simulate near future wind farm scenarios considering existing and planned OWFs in the North Sea and assess power generation losses and wind variations due to wind farm wake. The annual mean wind speed deficit within a wind farm can reach 2–2.5 ms −1 depending on the wind farm geometry. The mean deficit, which decreases with distance, can extend 35–40 km downwind during prevailing southwesterly winds. Wind speed deficits are highest during spring (mainly March–April) and lowest during November–December. The large-size of wind farms and their proximity affect not only the performance of its downwind turbines but also that of neighboring downwind farms, reducing the capacity factor by 20% or more, which increases energy production costs and economic losses. We conclude that wind energy can be a limited resource in the North Sea. The limits and potentials for optimization need to be considered in climate mitigation strategies and cross-national optimization of offshore energy production plans are inevitable.

An extensive new multi-proxy database of paleo-temperature time series (Temperature 12k) enables a more robust analysis of global mean surface temperature (GMST) and associated uncertainties than was previously available. We applied five different statistical methods to reconstruct the GMST of the past 12,000 years (Holocene). Each method used different approaches to averaging the globally distributed time series and to characterizing various sources of uncertainty, including proxy temperature, chronology and methodological choices. The results were aggregated to generate a multi-method ensemble of plausible GMST and latitudinal-zone temperature reconstructions with a realistic range of uncertainties. The warmest 200-year-long interval took place around 6500 years ago when GMST was 0.7 °C (0.3, 1.8) warmer than the 19 th Century (median, 5 th , 95 th percentiles). Following the Holocene global thermal maximum, GMST cooled at an average rate −0.08 °C per 1000 years (−0.24, −0.05). The multi-method ensembles and the code used to generate them highlight the utility of the Temperature 12k database, and they are now available for future use by studies aimed at understanding Holocene evolution of the Earth system.

Arrhythmia recurrences after catheter ablation occur in up to 50% within one year but their prediction remains challenging. Recently, we developed a novel score for the prediction of rhythm outcomes after single AF ablation demonstrating superiority to other scores. The current study was performed to 1) prove the predictive value of the APPLE score in patients undergoing repeat AF ablation and 2) compare it with the CHADS2 and CHA2DS2-VASc scores. Rhythm outcome between 3-12 months after AF ablation were documented. The APPLE score (one point for Age >65 years, Persistent AF, imPaired eGFR (<60 ml/min/1.73m2), LA diameter ≥43 mm, EF <50%) was calculated in every patient before procedure. 379 consecutive patients from The Leipzig Heart Center AF Ablation Registry (60±10 years, 65% male, 70% paroxysmal AF) undergoing repeat AF catheter ablation were included. Arrhythmia recurrences were observed in 133 patients (35%). While the CHADS2 (AUC 0.577, p = 0.037) and CHA2DS2-VASc scores (AUC 0.590, p = 0.015) demonstrated low predictive value, the APPLE score showed better prediction of arrhythmia recurrences (AUC 0.617, p = 0.002) than other scores (both p<0.001). Compared to patients with an APPLE score of 0, the risk (OR) for arrhythmia recurrences was 2.9, 3.0 and 6.0 (all p<0.01) for APPLE scores 1, 2, or ≥3, respectively. The novel APPLE score is superior to the CHADS2 and CHA2DS2-VASc scores for prediction of rhythm outcomes after repeat AF catheter ablation. It may be helpful to identify patients with low, intermediate or high risk for recurrences after repeat procedure.

Background Recurrent atrial fibrillation (AF) occurs in up to 50 % of patients within 1 year after catheter ablation, and a clinical risk score to predict recurrence remains a critical unmet need. The aim of this study was to (1) develop a simple score for the prediction of rhythm outcome following catheter ablation; (2) compare it with the CHADS 2 and CHA 2 DS 2 -VASc scores, and (3) validate it in an external cohort. Methods Rhythm outcome between 3 and 12 months after AF catheter ablation were documented. The APPLE score [one point for age >65 years, persistent AF, impaired eGFR (<60 ml/min/1.73 m 2 ), LA diameter ≥43 mm, EF < 50 %] was associated with AF recurrence and was validated in an external cohort in 261 patients with comparable ablation and follow-up. Results In 1145 patients (60 ± 10 years, 65 % male, 62 % paroxysmal AF) the APPLE score showed better prediction of AF recurrences (AUC 0.634, 95 % CI 0.600–0.668, p  < 0.001) than CHADS 2 (AUC 0.538) and CHA 2 DS 2 -VASc (AUC 0.542). Compared to patients with an APPLE score of 0, the odds ratio for AF recurrences was 1.73, 2.79 and 4.70 for APPLE scores 1, 2, or ≥3, respectively (all p  < 0.05). In the external validation cohort, the APPLE score showed similar results (AUC 0.624, 95 % CI 0.562–0.687, p  < 0.001). Conclusions The novel APPLE score is superior to the CHADS 2 and CHA 2 DS 2 -VASc scores for prediction of rhythm outcome after catheter ablation. It holds promise as a useful tool to identify patients with low, intermediate, and high risk for AF recurrence.

Objective We aimed to assess the effect of SGLT2i on arrhythmias by conducting a meta-analysis using data from randomized controlled trials(RCTs). Background Sodium-glucose co-transporter 2 inhibitors (SGLT2i) have shown cardioprotective effects via multiple mechanisms that may also contribute to decrease arrhythmias risk. Methods We searched in databases (PubMed, Embase, Cochrane Library, and clinicaltrials.gov) up to April 2023. RCTs comparing SGLT2i with placebo were included. The effects of SGLT2i on atrial fibrillation(AF), atrial flutter(AFL), composite AF/AFL, ventricular fibrillation(VF), ventricular tachycardia(VT), ventricular extrasystoles(VES), sudden cardiac death(SCD) and composite VF/VT/SCD were evaluated. Results 33 placebo-controlled RCTs were included, comprising 88,098 patients (48,585 in SGLT2i vs. 39,513 in placebo). The mean age was 64.9 ± 9.4 years, 63.0% were male. The mean follow-up was 1.4 ± 1.1 years. The pooled-results showed that SGLT2i was associated with a significantly lower risk of AF [risk ratio(RR): 0.88, 95% confidence interval(CI) 0.78–1.00, P = 0.04] and composite AF/AFL (RR: 0.86, 95%CI 0.77–0.96, P = 0.01). This favorable effect appeared to be substantially pronounced in patients with HFrEF, male gender, dapagliflozin, and > 1 year follow-up. For SCD, only in heart failure patients, SGLT2i were found to be associated with a borderline lower risk of SCD (RR: 0.67, P = 0.05). No significant effects of SGLT2i on other ventricular arrhythmic outcomes were found. Conclusions SGLT2i lowers the risks of AF and AF/AFL, and this favorable effect appeared to be particularly pronounced in patients with HFrEF, male gender, dapagliflozin, and longer follow-up (> 1 year). SGLT2i lowers the risk of SCD only in heart failure patients. Graphical Abstract

Catheter ablation has emerged as an effective treatment for atrial arrhythmias, and pulmonary vein isolation (PVI) is the cornerstone of ablation strategies. Significant technological evolution and widespread increase in operator experience have facilitated the effectiveness of catheter ablation to achieve durable PVIs in single or multiple ablation procedures. Nevertheless, arrhythmia recurrence is a common problem even after establishing PVI. Data on catheter ablation in these patients are sparse and repeat ablation in this population is highly challenging. In this review we have summarized the available data as well as potential strategies of catheter ablation following the initial PVI.

A new automated vector-based mapping algorithm (AMA) for 3-dimensional (3D) mapping has been introduced. The aim of this study was to present our experience using AMA to recognize additional catheter ablation targets in patients with ventricular arrhythmias (VA). A total of 16 patients (ICM; ischemic cardiomyopathy, n  = 6; NICM; non-ischemic cardiomyopathy n  = 10) suffering from VA underwent catheter ablation. Following bipolar voltage mapping, AMA was utilized to reveal zones of decelerated conduction velocity vectors (CVV) and this information was superimposed onto the 3D reconstructions and compared with the presence of scar. Mapping time was 28.1 ± 10 min for the endocardial reconstruction of the left ventricle (LV) and 17 ± 5.4 min for the epicardium ( n  = 6 patients). The mean area of LV low voltage was 13.9 ± 15% (endocardial) and 11.9 ± 5.7% (epicardial). Decelerating CVV zones were revealed in all patients (mean conduction velocity threshold of 39.3 ± 13%). Sustained VA have been terminated through ablation and substrate modification was performed in all patients. Correlation between the presence of CVV deceleration zones and areas of abnormal low voltage from bipolar mapping was revealed in only 37.5% of patients, but there was good correlation between scar from unipolar voltage mapping and the presence of CCV deceleration zones (94%; p  = 0.008). The novel AMA may improve the understanding of individual VA substrates due to the visualization of decelerated CVV zones and their correlation with abnormal low voltage predominantly from unipolar mapping.

Cities are fundamental to climate change mitigation, and although there is increasing understanding about the relationship between emissions and urban form, this relationship has not been used to provide planning advice for urban land use so far. Here we present the Integrated Urban Complexity model (IUCm 1.0) that computes “climate-smart urban forms”, which are able to cut emissions related to energy consumption from urban mobility in half. Furthermore, we show the complex features that go beyond the normal debates about urban sprawl vs. compactness. Our results show how to reinforce fractal hierarchies and population density clusters within climate risk constraints to significantly decrease the energy consumption of urban mobility. The new model that we present aims to produce new advice about how cities can combat climate change.

Cardiac accessory pathways (APs) in Wolff–Parkinson–White (WPW) syndrome are conventionally diagnosed with decision tree algorithms; however, there are problems with clinical usage. We assessed the efficacy of the artificial intelligence model using electrocardiography (ECG) and chest X-rays to identify the location of APs. We retrospectively used ECG and chest X-rays to analyse 206 patients with WPW syndrome. Each AP location was defined by an electrophysiological study and divided into four classifications. We developed a deep learning model to classify AP locations and compared the accuracy with that of conventional algorithms. Moreover, 1519 chest X-ray samples from other datasets were used for prior learning, and the combined chest X-ray image and ECG data were put into the previous model to evaluate whether the accuracy improved. The convolutional neural network (CNN) model using ECG data was significantly more accurate than the conventional tree algorithm. In the multimodal model, which implemented input from the combined ECG and chest X-ray data, the accuracy was significantly improved. Deep learning with a combination of ECG and chest X-ray data could effectively identify the AP location, which may be a novel deep learning model for a multimodal model.