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Objective: Electrocardiogramms (ECG) interpretation is increasingly supported by algorithms trained on large-scale datasets. Here we present a first manually annotated open-source ECG-database of children and adults with congenital heart defect (CHD) with arrhythmia annotations.
Approach: Signal data (ECG and intracardiac electrograms) were extracted from children and patients with CHD undergoing electrophysiological studies (EPS). The dataset is provided in the wave form database format. Annotations were manually annotated using the LightWAVE® software.
Main results: The dataset comprises 39 ECGs from 39 patients (duration ranging from 00:01:17 h to 02:30:31 h). A total of 113 924 beats were annotated. A large part of beats (33%) are normal sinus rhythm. However, the database also includes sinus rhythm beats with preexcitation (12%) or complete right bundle branch block (11%). Supraventricular tachycardias (23%) are further categorized into atrioventricular reentrant tachycardias (AVRT; 15.5%) and atrioventricular nodal reentrant tachycardias (AVNRT; 7.5%). Also, ventricular tachycardias (1.7%) and very rare conditions as aberrant conducted AVRT or AVNRT or AVNRT with 2nd degree heart block are represented. Additionally paced beats are included (12%), thereof 7% atrial paced beats and 5% ventricular paced beats. Premature beats (premature ventricular or atrial beats) make up 7% of the dataset.
Significance: This open-source database (https://physionet.org/content/leipzig-heart-center-ecg) containing many pathologies in children and patients with CHD may provide a foundation for ECG algorithms aimed at detecting ECG pathologies in this special patient population.
This thesis investigates the conversion of the unsignalized Lauerstraße & Wilhelmstraße intersection in Duisburg into a signalized intersection with the aim to improve the traffic safety and operational efficiency, and this intersection also interrupts an otherwise signalized arterial corridor. The study is driven by the need to address frequent unprotected left turn conflicts, lack of at-grade crossing infrastructure for vulnerable road users, and the planned demolition of the Blaue Brücke pedestrian flyover. Three control concepts are designed based on geometric surveys and official peak-hour turning-movement counts. Three control concepts are developed: fixed-time control, coordinated fixed-time control for the progression of green signals, and fully traffic-actuated control. The signal programs have been developed in LISA+ based on the RiLSA principles and tested in PTV VISSIM with the Level of Service and demand weighted average delay for both peak hours. The results indicate that all the signalized alternatives have acceptable operational quality.
Both traffic-actuated control and coordinated control enable some reduction of local weighted delay, and the latter ensures some usable bandwidth in the corridor. Overall, the results do support an operational concept of protected signalization, actuation and coordination that is time-of-day based.
Myokarditis früh erkennen
(2026)
From Scenario Farming to Learning: A Modular Low-Code Framework for Decision Support in Scheduling
(2025)
This paper presents a relational integration of the TSXor compression algorithm for regularly sampled time-series data. We design and implement a schema and compression pipeline within TimescaleDB, allowing lossless compression and in-database decompression using SQL and PL/pgSQL. Our approach replaces full timestamps with delta-based offsets and encodes floating-point values using reference-based XOR encoding. We evaluate the system on multiple real-world datasets, showing moderate compression ratios (up to 23%) and fast decompression performance. While the SQL-based implementation introduces storage and execution overhead, the integration enables transparent querying and lays the foundation for further database-native optimizations of time-series compression.
Heart failure with preserved ejection fraction (HFpEF) remains challenging to diagnose due to the complexity of diastolic function assessment during stress echocardiography, where multiple hemodynamic parameters must be evaluated under time pressure. Explainable artificial intelligence, specifically rule-based Clinical Decision Support Systems (CDSS), offers promising improvements in reproducibility and interpretability.
Methods: A rule-based CDSS was developed and clinically validated to automate left ventricular diastolic function assessment during semi-supine bicycle stress echocardiography. A prospective cohort of 134 patients (mean age 61.3 ± 8.7 years) with exertional dyspnea and preserved left ventricular ejection fraction (LVEF >50%) was enrolled, excluding individuals with significant valvular pathologies, arrhythmias, or unstable ischemia. Echocardiographic and Doppler data were collected using Toshiba Aplio500 and Esaote MyLabSIGMA systems. The algorithm incorporated manual input of measurements, computed derived indices (e.g., diastolic reserve index, myocardial stiffness, vascular resistance), and applied rule-based logic in accordance with ASE/EACVI (2016/2022) guidelines and the ESC HFpEF consensus.
Results: The CDSS generated diagnostic conclusions within 3 min per case, matching expert assessments in 93% of cases and correctly identifying stress-induced diastolic dysfunction in 85%. It demonstrated high diagnostic agreement (ICC &gt; 0.94) and discrimination (AUC = 0.92). Rule-based outputs, such as “Impaired diastolic reserve” or “Right ventricular dysfunction under load,” were based on combinations of parameters (e.g., E/e′ > 15, Δe′ ≤ 0, TAPSE < 17 mm, PCWR > 12 mmHg).
Conclusion: The explainable, guideline-compliant CDSS enables real-time, transparent analysis of diastolic function, supporting improved diagnostic consistency and augmented physician decision-making in cardiovascular care.
The article examines the strategic partnership in the development of the Eurasian transcontinental transport corridor system, as well as in the Republic of Kazakhstan and the People’s Republic of China. Special focus has been placed on the Kazakhstani section of the Middle Corridor (Trans-Caspian International Transport Route) – a multilateral, multimodal route connecting Chinese and European marketplaces through Kazakhstan and the Caspian Sea. The aim of the work is to determine how the mechanisms of synergy of infrastructure (infrastructure synergies) and factors defining corridor sustainability are determined using World Bank data (WITS, Logistics Performance Index), analytical material of international organizations, and scientific papers registered in Scopus. The article states that “physical” investments in railway, port, and terminal infrastructure can only yield long-term economic benefits if they are accompanied by trade facilitation, the electronic integration of all procedures, and the formation of institutional corridor governance structures. It has also been demonstrated that the primary restriction in the Middle Corridor is the extreme variability in transit times and costs; this restriction occurs in the majority of cases at intermodal nodes and border crossing points. Therefore, the authors propose a framework for developing corridors based on services, in which priorities are established end-to-end using indicators of logistics service reliability, and transit nodes are converted into logistics and industrial clusters. The practical importance of the research lies in substantiating the direction for Kazakhstan’s investment policies and forms of cooperation with China to reduce delays, increase predictability, and increase domestic value-added.
Accuracy of the Smart Watch iECG for Documentation of Supraventricular Tachycardias in Children
(2026)
Die vorliegende Arbeit beschäftigt sich mit der Elektromobilitätswende und den daraus resultierenden Herausforderungen für die deutsche Automobilindustrie. Der erstarkende Nachhaltigkeitsgedanke der modernen Gesellschaft verändert das Mobilitäts- und Nachfrageverhalten an weltweiten Märkten. Internationale Automobilhersteller stehen im aktuellen Wandel zwischen politischem Willen und multidimensionalen Grenzen der Umsetzbarkeit. Die wirtschaftlich aufstrebende Volksrepublik China konnte sich dabei in jüngster Vergangenheit als Leitmarkt etablieren. Der chinesische Automobilbau gewinnt dabei ebenso an Bedeutung und neue Marken, wie „BYD“ verstärken den Wettbewerbsdruck auf deutsche Hersteller zunehmend. Die Abhandlung ordnete die Bedeutung der deutschen Automobilindustrie für den Wirtschaftsstandort Deutschland anhand der Analyse quantitativer Indikatoren ein. Zusätzlich wurden traditionelle Stärken, Herausforderungen und Strategien in Bezug auf die Mobilitätswende für die drei erfolgreichsten deutschen Automobilunternehmen „Volkswagen“, „Mercedes Benz“ und „BMW“ untersucht. Die Relevanz Chinas, sowie die Besonderheiten des Marktumfeldes werden daran anknüpfend betrachtet, bevor die etablierten deutschen Hersteller mit dem chinesischen Disruptor „BYD“ gegenübergestellt wurden. Durchgeführt wurde hierzu eine Wettbewerbsanalyse mit Ausrichtung auf Produktdifferenziertheit nach dem „Fünf-Kräfte-Modell“ (Five-Forces) von Michael E. Porter. Die Gesamtstudie wurde abschließend durch eine Kombination von SWOT- und PESTEL-Analyse ausgewertet. Es wurden wesentliche Potentiale und Herausforderungen für deutsche Automobilhersteller abgeleitet. Diese sind nach globalem und chinesischem Kontext aufgeschlüsselt und in politische, ökonomische, soziale und technologische Dimensionen eingeordnet. Die Ergebnisse können als Grundlage für weiterführende Forschung konkreter Aspekte dienen.
