Karlsruhe Institute of Technology

To improve the superconducting properties of Rare Earth Barium Copper Oxides (REBCO) for applications at low temperatures and high fields, the defect landscape of lower-dimensional defects needs to be optimized. This can be achieved by forming solid solutions of various REBCO phases, so called mixed REBCO systems (mREBCO), which are characterized by disorder at the RE position depending on the used RE elements. These RE elements also determine the lattice parameters of the resulting mREBCO compound. Thereby, mREBCO thin films offer the opportunity to study RE mixing in deliberately tuned crystal structures. In order to investigate the influence of RE mixing on the superconducting properties, sets of mREBCO thin films were produced by chemical solution deposition. As these investigations show, the mean ionic RE radius of mREBCO thin films can be used to predict their lattice parameters. Therefore, the crystal structure of mREBCO compounds makes it possible to adapt the films to different substrates or buffer layers. It had been reported that RE mixing increases the microstrain along the c -axis, yet our sample sets showed a significant decrease with RE mixing, possibly due to different growth conditions. Surprisingly, the mREBCO sample sets showed no significant change of the weak-pinning contribution, which is associated with point-like defects. Yet the pinning force was positively influenced by RE mixing.

The characteristic and strongly precipitating cloud band near extratropical cyclones is associated with a coherent cross‐isentropically ascending airstream, the warm conveyor belt (WCB). The WCB ascent characteristics and associated diabatic heating are influenced by cloud microphysical processes and environmental conditions in the WCB inflow region. The former relies on the cloud microphysical parametrisation, and the latter on initial and/or boundary conditions of thermodynamic variables. Altogether, this introduces uncertainty in numerical weather prediction (NWP) forecasts of the WCB characteristics and ultimately the prediction of the large‐scale midlatitude flow. We quantify the relative influence of perturbations on various cloud microphysical processes and WCB inflow temperature and moisture (via modification of sea‐surface temperature) for a case study and thereby focus on uncertainty in WCB ascent behaviour, associated precipitation characteristics, and properties of the amplifying ridge downstream of the ascent region. To disentangle individual uncertainty contributions, we build a high‐resolution 70‐member perturbed parameter ensemble (PPE) with the Icosahedral Nonhydrostatic (ICON) modelling framework. The PPE systematically combines parameter perturbations and samples the phase space spanned by parameter uncertainty ranges. Based on the PPE, computationally cheap statistical surrogate models are developed that subsequently facilitate variance‐based sensitivity analysis for the target variables. Our results suggest that changes to environmental conditions controlling WCB inflow properties most strongly influence WCB ascent behaviour, total surface precipitation sums, and the ridge amplitude. Yet, the microphysical perturbations locally modify vertical velocity along WCB ascent and determine the precipitation efficiency, which affects meso‐scale precipitation characteristics as well as the spatial distribution and intensity of precipitation. Moreover, the microphysical perturbations distinctly influence the large‐scale flow pattern, albeit to a lesser extent than the perturbations applied to the WCB inflow characteristics.

In this work, the characterization of novel electrolytes based on the combination of propylene carbonate (PC) solvent with sodium bis(fluorosulfonyl)imide (NaFSI) and sodium difluoro(oxalato)borate (NaDFOB), as well as their application in sodium‐ion batteries (SIBs) is presented. The results show that dual‐salt electrolytes have a wide electrochemical stability window, excellent transport properties, and mostly suppress anodic dissolution. When combined with P2‐Na2/3Al1/9Fe1/9Mn2/3Ni1/9O2 (P2‐AFMNO) cathode electrode for SIBs operating at 4.3 V vs Na⁺/Na, they enable high performance and stability. XPS investigation revealed that this performance is related to the formation of a thin and homogeneous cathode electrolyte interphase (CEI) at the electrode surface.

A 12-year-old girl presented with inguinal swelling and recurrent groin pain since menarche. Ultrasound showed an inguinally located ovary with normal perfusion. Herniorrhaphy revealed an ectopic inguinal left ovary with fallopian tube and atretic hemiuterus and a closed internal inguinal ring. Laparoscopy revealed a right-sided hemiuterus and vaginally palpable cervix, leading to the diagnosis of ectopic OHVIRA syndrome type 1.2. The left hemiuterus was resected and the left ovary was pulled through the inguinal canal into the abdomen. During 12 months of follow-up, the left ovary showed normal perfusion and sonomorphologic appearance, menstrual periods were uneventful.

Zusammenfassung Das Typ-VI-Sekretionssystem (T6SS) ist eine molekulare Injektionsapparatur, mit der Bakterien Proteine in Zielzellen einschleusen, um Konkurrenten zu bekämpfen, eukaryotische Zellen zu manipulieren oder Nährstoffe zu gewinnen. Viele Bakterien besitzen unterschiedliche Versionen des T6SS. Die Rolle dieser Varianten und ihr Zusammenspiel ist dabei jedoch kaum verstanden.

We investigated event-related potentials (ERPs) in the context of autonomous vehicles (AVs)—specifically in ambiguous, morally challenging traffic situations. In our study, participants (n = 34) observed a putative artificial intelligence (AI) making decisions in a dilemma situation involving an AV, expanding on the Moral Machine (MM) experiment. Additionally to the original MM experiment, we incorporated electroencephalography recordings. We were able to replicate most of the behavioral findings of the original MM: In case of an unavoidable traffic accident, participants consistently favored sparing pedestrians over passengers, more characters over fewer characters, and humans over pets. Beyond that, in the ERP we observed an increased P3 (322–422 ms), and late positive potential (LPP) (500–900 MS) amplitude in fronto-central regions when the putative AI’s decision on a moral dilemma was incongruent to the participants’ decision. As P3, and LPP are associated with the processing of stimulus significance, our findings suggest that these ERP components could potentially be used to identify critical, or unacceptable situations during human-AI interactions involving moral decision-making. This might be useful in brain computer interfaces research when, classifying single-trial ERP components, to dynamically adopt an AV’s behavior.

Memristors are a class of emerging electronic devices for in-memory computation systems, which promise to overcome the von Neumann bottleneck in traditional computer architectures. Simulation plays a critical role in designing circuits for memristive in-memory computation systems. Fast and reliable simulations require a behavioral model that accurately emulates device characteristics, accounting for real-world non-idealities. In this work, we present a memristor behavioral model that incorporates key non-idealities, including cycle-to-cycle and device-to-device resistance variations, threshold voltage variations, resistance drift in the absence of external stimulus and variations in switching dynamics. The model has been fitted to experimental data from two types of real devices: vacuum-processed self-directed channel memristors and inkjet-printed electrochemical metallization memristors, showing good agreement with both datasets. This model is used to simulate memristive stateful logic gates. Our study highlights the significance of considering device non-idealities in the practical design of memristive circuits.

Purpose Identifying and quantifying coronary artery calcification (CAC) is crucial for preoperative planning, as it helps to estimate both the complexity of the 2D coronary angiography (2DCA) procedure and the risk of developing intraoperative complications. Despite the relevance, the actual practice relies upon visual inspection of the 2DCA image frames by clinicians. This procedure is prone to inaccuracies due to the poor contrast and small size of the CAC; moreover, it is dependent on the physician’s experience. To address this issue, we developed a workflow to assist clinicians in identifying CAC within 2DCA using data from 44 image acquisitions across 14 patients. Methods Our workflow consists of three stages. In the first stage, a classification backbone based on ResNet-18 is applied to guide the CAC identification by extracting relevant features from 2DCA frames. In the second stage, a U-Net decoder architecture, mirroring the encoding structure of the ResNet-18, is employed to identify the regions of interest (ROI) of the CAC. Eventually, a post-processing step refines the results to obtain the final ROI. The workflow was evaluated using a leave-out cross-validation. Results The proposed method outperformed the comparative methods by achieving an F1-score for the classification step of 0.87 (0.77 $-$ - 0.94) (median ± quartiles), while for the CAC identification step the intersection over minimum (IoM) was 0.64 (0.46 $-$ - 0.86) (median ± quartiles). Conclusion This is the first attempt to propose a clinical decision support system to assist the identification of CAC within 2DCA. The proposed workflow holds the potential to improve both the accuracy and efficiency of CAC quantification, with promising clinical applications. As future work, the concurrent use of multiple auxiliary tasks could be explored to further improve the segmentation performance.

Sequence‐programmable DNA building blocks offer high degree of freedom in designing arbitrarily complex networks of tunable viscoelastic properties. Yet, the deployment of DNA‐based functional materials remains limited due to insufficient control over the emerging structures and their mechanics. In an ongoing effort to place structure‐property relations in stimuli‐responsive DNA materials on a firm foundation, here a systematic rheological study of self‐assembling DNA networks is presented, comprised of short DNA nanomotifs, namely trivalent nanostars and bivalent linkers, where the latter differ in their composition on a single base‐pair level. Notably, we found through combining conventional bulk rheology with diffusing wave spectroscopy (DWS‐based) passive microrheology a relationship between the melting temperature of a DNA hydrogel and its DNA sequence composition. By providing a use case, we demonstrated how the determination of such empirical relations could impact the areas of biosensing and mechanical computing, where control over the system state and target identification are key.

Model parameterisation is essential, on one side, to offer insights into the internal states of a Li‐ion battery, and on the other side, to deliver realistic predictions of the battery performance. Multi‐step parameterisation including the C‐rate test, electrochemical impedance spectroscopy and, for the first time, nonlinear frequency response analysis has been implemented in this study. Via nonlinear frequency response analysis, an asymmetrical charge transfer process at the positive electrode is identified, whereby the charge transfer coefficient at the positive electrode is no longer 0.5 as assumed in many simulation works. Further, it is shown that nonlinear frequency response analysis in combination with electrochemical impedance spectroscopy can improve the uniqueness of the kinetic model parameters. Specifically, ambiguous sets of kinetic parameters, i.e., rate constant and charge transfer coefficient, are identified via only electrochemical impedance spectroscopy. The ambiguity can be resolved with additional nonlinear frequency response analysis.

Innovations in scalable fabrication processes are pivotal for transferring record power conversion efficiencies (PCEs) of spin‐coated perovskite/silicon‐based tandem solar cells (TSCs) from the laboratory scale to full‐size photovoltaics. In this regard, the homogeneous large‐area drying of precursor ink wet films poses one of the major hurdles. Gas‐assisted drying by linear high‐pressure slot jets comes along with an inhomogeneous flow field, causing unwanted backflows, non‐uniform drying patterns, and strong inhomogeneities at the sample edges. In response, it is demonstrated i) a new 2D comb‐nozzle (CN) drying technique that improves the homogeneity of drying processes and, ii) an adjusted strategy to fabricate high‐quality 2‐step slot‐die (SD)‐coated triple‐halide perovskite thin films. Remarkably, homogeneous and pinhole‐free large‐area SD‐coated perovskite SCs fabricated is demonstrated with all scalable techniques reaching up to 19.6% with enhanced mean PCE‐yields of 90% (compared to 62% with slot‐jet drying). Consequently, the CN drying method is employed for a material composition suitable for tandem applications (Eg ≈1.68 eV). Particularly, the reproducible fabrication of TSCs with PCEs up to 24.6% on large areas with homogeneous PCE variances of ±0.7%abs imply high homogeneity during the coating and drying process and confirms the importance of systematically controlled drying within an optimized 2‐step process.

The rapid and cost‐effective detection of food contaminants such as toxins and pathogens is a major challenge and a key concern for food safety. To this end, innovative, fast, cost‐effective, and easy‐to‐use sensors must be developed at the point where food is produced, distributed, and consumed. Therefore, timely detection and response to food contaminants can improve human health and reduce economic burden. However, affordable sensor technologies with specificity, sensitivity, and speed are required, which can be used by non‐specialized personnel and enable high throughput analysis. In this respect, advances in the development of nanoparticle‐based sensors, i.e., nanosensors, have shown the potential to provide the much‐anticipated versatile sensors. In addition, multiplex detection, i.e., the ability to detect multiple targets simultaneously, is another strategy facilitated by nanoparticle‐based sensors and will enable further improvements in sensor performance that are important for developing effective monitoring. This review summarizes the nanosensors for multiplex sensing of food samples with respect to hazardous contaminates reported over the past few years. In addition, special attention is paid to providing the reader with promising design principles and the current performance of the sensitivity and selectivity of such sensors for practical requirements, thereby inspiring new ideas for developing further advanced systems.

The purpose of this survey is to provide a comprehensive overview of recent advancements in text line segmentation and baseline detection techniques within the analysis of historical document images. Text line extraction is an essential step in the historical documents image analysis pipeline, as its results significantly impact the accuracy of subsequent processes, such as handwritten text recognition (HTR). Through a multi-stage procedure, we carefully selected 49 peer-reviewed studies published since 2019. Based on careful analysis of these studies, we summarize the information of the existing datasets, describe and categorize different methods, and summarize evaluation protocols. In addition, we compare the results of various methods on benchmark datasets. Finally, we highlight the gaps and suggest directions for future research. We believe that this comprehensive survey will be of great assistance to researchers working in the field of historical document image analysis, as it offers critical insights into the latest advancements and developments, providing a foundation for future research.

Introduction Exercise metabolomics research has revealed significant exercise-induced metabolic changes and identified several exerkines as mediators of physiological adaptations to exercise. However, the effect of exercise intensity on metabolic changes and circulating exerkine levels remains to be examined. Objectives This study compared the metabolic responses to moderate-intensity and vigorous-intensity aerobic exercise. Methods A two-period crossover trial was conducted under controlled conditions at the Max Rubner-Institute in Karlsruhe, Germany. Seventeen young, healthy, and physically active men performed 30 min moderate-intensity (50% VO2peak) and vigorous-intensity (75% VO2peak) aerobic exercise using two bicycle ergometer protocols in a randomized sequence. Blood samples obtained immediately before exercise and at four time points after exercise were analyzed in an untargeted metabolomics approach, and separate linear mixed models were applied to over 1000 metabolites. Results Vigorous-intensity exercise induced a greater metabolic response than moderate-intensity exercise. Several intensity-dependent metabolites were identified, primarily involved in amino acid metabolism and energy conversion pathways, including N-lactoyl-amino acids, TCA cycle intermediates, N-acetylated amino acids, and acylcholines. The exerkines N-lactoyl-phenylalanine, lactate, and succinate were among the most intensity-dependent metabolites. N-acetylated amino acids and acylcholines were systematically altered by exercise intensity, indicating potential physiological functions. Conclusion Exercise intensity significantly affects exercise-induced metabolic alterations and changes in exerkine levels. Our results expand the knowledge about exerkine dynamics and emphasize the role of exercise intensity in promoting physiological adaptations to exercise. The trial was registered on October 5, 2017, at the German Clinical Trials Register under the Registration Number DRKS00009743 (Universal Trial Number of WHO: U1111-1200-2530).

A bstract This paper investigates the search for heavy neutral leptons (HNL) in the type I seesaw mechanism at the Future Circular Collider in its e ⁺ e − stage (FCC-ee), considering a luminosity of 125 ab − 1 collected at $\sqrt{s}$ s = 91 . 2 GeV. The study examines two generations of heavy neutral leptons produced in association with Standard Model (SM) neutrinos and decaying to a purely leptonic final state. This theoretical framework can explain neutrino oscillations and other open questions of the SM, providing a broader perspective on the relevance of this experimental search. The analysis is performed using a fast simulation of the IDEA detector concept to study potential HNL interactions at the FCC-ee. The sensitivity contours are obtained from a selection of kinematic variables aimed at improving the signal-to-background ratio for the prompt production case. In the case of long-lived HNLs, the background can be almost fully eliminated by exploiting their displaced decay vertices. The study shows that the FCC-ee has a significant sensitivity to observing these objects in a region of the phase space not accessible by other experiments.

Societal Impact Statement Viticulture is facing increasing challenges due to climate change. The focus on fast growth and sweet berries has come at the expense of stress resilience. Grafting onto Phylloxera‐resistant rootstocks from American species has been the most successful form of ecological pest management. However, there is still a significant reliance on chemical plant protection. Additionally, abiotic stress has not been a primary concern in rootstock breeding efforts so far. To identify genetic factors that contribute to abiotic stress tolerance, we propose to explore the potential of the wild ancestor of grapevine, Vitis sylvestris. By identifying resilience factors, we can develop a new generation of rootstocks or enhance grafted cultivars to protect viticulture from the impact of abiotic constraints. Summary There is an urgent need to explore wild germplasm resources for resilience traits that enhance stress tolerance in grapevines. The challenges posed by climate change, including heat and drought stress, salinity, rising temperatures, and untimely cold snaps in spring, are intensifying. Traditional grapevine varieties often lack the resilience to withstand environmental threats because conventional breeding has historically prioritized yield and flavor over stress tolerance. In this review, we highlight the potential of the European Wild Grapevine, Vitis sylvestris, as a valuable genetic resource for resilience traits. Understanding the underlying mechanisms is crucial for developing molecular markers to support resilience breeding. Such traits can be directly integrated through introgression into productive cultivars. Alternatively, they can be used to develop a new generation of rootstocks that protect the scion from environmental stresses without compromising desirable oenological qualities. These markers may support the development of gene editing strategies to engineer more resilient genotypes.

One study in three forms: advancing science communication in the humanities The ERC CogGrant COSE project focuses on internet-based art that is not accessible in a straightforward manner and thus easily overlooked or lost. We develop new hybrid methods to retrieve and analyse online art and its embed-dedness in sociotechnological environments. With COSE’s MediaWiki archive, we hope to kickstart a future research environment for scholars.