Gutenberg Open Science (Univ. Mainz)
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Skyrmions as quasi-particles : from dynamics to application in unconventional computing
Get PDFThis dissertation explores the magnetic behavior and manipulation of skyrmions -
topologically protected spin textures in metallic thin films - focusing on their dynamics,
confinement, and application in low-power unconventional computation.
Skyrmion flow in the creep regime was studied in straight and modulated channels,
revealing boundary-dependent velocity profiles in qualitative agreement with
Thiele-based simulations.
Controlled He+ and Ga+ irradiation enabled tuning of magnetic properties and enabled
creating artificial barrier for e.g., skyrmion compression. The experimental
findings of the latter are compared and supported by adapted theoretical models
and simulations.
A key part is the development of a novel reservoir computing (RC) scheme based
on the Brownian dynamics of confined skyrmions. Even in a simplistic confining
geometry like an equilateral triangle, the system performs Boolean logic operations,
even nonlinear logic at ultra-low current densities. Its scalability and potential for
increased complexity make skyrmion-based RC a promising platform for energyefficient,
unconventional computing.xxv, 229 Seiten ; Illustrationen, Diagramm
Optimierung der Ventrikelkatheter-Anlage durch standardisiertes Training im Rahmen der neurochirurgischen Ausbildung
Get PDFBackground and objectives: External ventricular drain (EVD) placement is a critical, lifesaving procedure in cranial neurosurgery, often performed manually using anatomical landmarks that vary between individuals. This study evaluates the efficacy of a 3-dimensional (3D)-printed EVD training model designed to improve the accuracy of this procedure.
Methods: Computed tomography scans from 3 patients were used to create 3D-printed head models with narrow, wide, and normal ventricles. Twenty-five neurosurgeons participated in a three-round training protocol: pre-training, training with neuronavigation and a standardized protocol, and post-training. The accuracy of EVD placement was measured using an optical navigation system, and participants' confidence levels were assessed through questionnaires.
Results: Training significantly enhanced EVD placement accuracy. Pre-training, only 55.3% of placements were intraventricular (Kakarla grade 1), which increased to 84.0% post-training ( P < .001). The distance to the ideal entry point improved from 5.8 mm (SD, ±3.7 mm) to 4.1 mm (SD, ±1.5 mm), and the distance to the target point improved from 12.6 mm (SD, ±5.8 mm) to 8.3 mm (SD, ±4.0 mm) ( P < .001 for both). The time to identify entry points and puncture the ventricles also improved significantly. Left-sided EVDs were more frequently misplaced. In addition, right-handed participants (n = 24) performed better when placing left-sided EVDs with their right hand. Participants with more than 6 years of experience were more likely to misplace the EVD and overestimate their placement accuracy compared with less experienced participants. Post-training, both experienced and less experienced neurosurgeons achieved similar success rates. Confidence in EVD placement and puncture direction significantly increased post-training.
Conclusion: A standardized training protocol using a 3D-printed model significantly improves the accuracy and confidence of neurosurgeons in EVD placement. Regular training is recommended to maintain high clinical performance, emphasizing the need for standardized procedures and the use of neuronavigation for complex cases.iv, 74 Seiten ; Illustrationen, Diagramm
Ultrasound education in the digital era : face-to-face vs. webinar-teaching of head and neck ultrasound theory : a prospective multi-center study
Get PDFIntroduction: Digitalization offers significant potential benefits to ultrasound education. This study compares the effectiveness of webinar teaching against face-to-face teaching in providing theoretical competencies in certified head and neck ultrasound (HNUS) courses.
Patients and methods: This prospective, controlled, multicenter study was conducted in 2023 at three universities with certified HNUS courses. One course used webinar lessons (S), and the others used face-to-face teaching (C). The control group courses (C) were held on two consecutive days. The first day of the study group course was held as a webinar (S) 1 week before the second day and was also recorded for preparatory purposes. All participants completed three assessments: a pre-course self-evaluation (Evaluationpre), a post-course self-evaluation (Evaluationpost), and a post-course theory test (Theory Testpost). The evaluations used a Likert scale (1–7) to record the participants’ subjective assessments of competencies and attitudes toward webinar teaching. Theory Testpost included multiple-choice and free-answer questions on the sonographic pathologies of lymph nodes, the soft tissue of the neck, and salivary glands. A group of inexperienced medical students (V) completed the Theory Testpost for validation purposes.
Result: 128 data sets were analyzed (31 S; 30 C; 47 V). Both groups, S and C, rated their competencies after the courses significantly higher than before (p < 0.01) but at a similar level in comparison with each other (p = 0.34). Both groups supported teaching theoretical content through webinars (S: 6.7 ± 0.5 vs. C: 6.2 ± 0.9). Both groups achieved similar results in the Theory Testpost (p = 0.54), significantly outperforming the validation group (p < 0.001).
Conclusion: Our data suggest that webinars can be an effective alternative to face-to-face lessons in teaching theoretical competencies in HNUS. Participants gave overall positive evaluations of digital teaching methods. Our findings support evidence that digital learning methods are valuable for modern ultrasound education
Differential inflammation, oxidative stress and cardiovascular damage markers of nano- and micro-particle exposure in mice : implications for human disease burden
Get PDFParticulate matter (PM) poses a significant risk to human health; however, it remains uncertain which size fraction is especially harmful and what mechanisms are involved. We investigated the varying effects of particle size on specific organ systems using a custom mouse exposure system and synthetic PM (SPM). Whole-body exposure of mice showed that micrometer-sized fine SPM (2–4 μm) accumulated in the lungs, the primary entry organ, while nanometer-sized SPM (<250 nm) did not accumulate, suggesting a transition into circulation. Mice exposed to micro-SPM exhibited inflammation and NADPH oxidase-derived oxidative stress in the lungs. In contrast, nano-SPM-exposed mice did not display oxidative stress in the lungs but rather at the brain, heart, and vascular levels, supporting the hypothesis that they penetrate the lungs and reach the circulation. Sources of reactive oxygen species from micro-SPM in the lung are NOX1 and NOX2, driven by pulmonary inflammation, while oxidative stress from nano-SPM in the heart is mediated by protein kinase C-dependent p47phox phosphorylation, leading to NOX2 activation in infiltrated monocytes. Endothelial dysfunction and increased blood pressure were more pronounced in nano-SPM-exposed mice, also supported by elevated endothelin-1 and reduced endothelial nitric oxide synthase expression, which enhances constriction and diminishes vasodilation. Further, we estimated the cardiovascular disease burden of nano-particles in humans based on global exposure data and hazard ratios from an epidemiological cohort study. These results provide novel insights into the disease burdens of inhaled nano- and micro-particles (corresponding to fine and ultrafine categories), guiding future studies
When size matters : size-selective chemistry in the heterogeneous processing of organic aerosols
Get PDFNew particle formation and growth in the atmosphere critically influence cloud properties and climate, as well as human health through the presence of ultrafine particles. While the early stages of particle nucleation are increasingly understood, the mechanisms driving the subsequent growth of nanoparticles, particularly the role of organic compounds, remain unclear. This study investigates the heterogeneous ozonolysis of 5-norbornene-2-endo,3-exodicarboxylic acid (NDA) in size-selected aerosol particles (30–110 nm) under varying relative humidity and ozone conditions. NDA serves as a model compound representative of unsaturated monoterpene derivatives with low volatility and high particle-phase partitioning. Using real-time mass spectrometry, we explore how particle size influences both reactivity and product distribution. Our results reveal pronounced particle-size and humidity dependencies: smaller particles favor dimerization and oligomer formation, likely due to increased Laplace pressure, whereas larger particles promote hydrolysis and decomposition reactions. The findings suggest that nanometer-sized particles provide a distinct chemical microenvironment that alters the course of multiphase reactions, thereby affecting particle aging, volatility, and growth potential. These results underscore the importance of considering particle-size-dependent chemistry in models of atmospheric aerosol formation and evolution
Results of a multi-perspective examination of loneliness trajectories and its determinants in German adults during the COVID-19 pandemic
No full textMost research on adults’ vulnerability to loneliness during the pandemic has been of limited quality. This study aimed to overcome previous limitations by examining loneliness trajectories in German adults from a population-based cohort during the pandemic using face-to-face assessment, identifying risk factors and highlighting those particularly relevant to older adults. Analyses included two measurement points before and two during the pandemic, combining data from the population-based Gutenberg Health Study and COVID-19 Study (N = 7001; baseline: Mage = 51.72, SDage = 10.04). Growth mixture models identified distinct loneliness trajectories. Factors associated with these trajectories were tested by a multinomial logistic regression model including sociodemographic, individual, and pandemic-related predictors and interactions with age. Overall, mean loneliness increased. Three distinct classes were identified: No Loneliness (59.3%), Onset (23.3%), and Temporary Increase (17.4%). In comparison to No Loneliness, Onset was associated with reduction in social contact during the pandemic and Temporary Increase with sex, high school degree, pre-pandemic depression symptoms, pandemic-related stressors and social support. No unique risk factors for older adults were found. Interventions that strengthen one’s adaptability to (acute) stressors and promote social resources with special attention to women may be a promising way to prevent loneliness during the pandemic
Bottom-up background simulations of the 2016 COSI balloon flight
No full textThe Compton Spectrometer and Imager (COSI) is a Compton telescope designed to survey the 0.2–5 MeV sky, consisting of a compact array of cross-strip germanium detectors. As part of its development, in 2016 COSI had a successful 46 day flight on board NASA's Super Pressure Balloon platform. This was a precursor to the COSI Small Explorer (COSI-SMEX) satellite mission that will launch in 2027 into an equatorial low Earth (530 km) orbit. The observation of MeV gamma rays is dominated by background radiation, especially due to the activation of the detector materials induced by cosmic-ray interactions. Thus, background simulation and identification are crucial for the data analysis. Because the COSI-SMEX detectors will be similar to the ones used for the balloon flight, the balloon measurements provide an important tool for testing and cross-checking our background simulations for the upcoming space mission. In this work we perform Monte Carlo simulations of the background emission from the 2016 COSI balloon flight. Including a phenomenological shape correction, we obtain an agreement with the data at the 10%–20% level for energies between 0.1 and 1.6 MeV, and we successfully reproduce most of the activation lines induced by cosmic-ray interactions
Allantofuranone biosynthesis and precursor-directed mutasynthesis of hydroxylated analogues
No full textGenome mining and heterologous reconstitution of biosynthetic genes in Aspergillus oryzae enabled elucidation of the hitherto elusive biosynthetic route that produces allantofuranone, a bioactive natural product originally isolated from Allantophomopsis lycopodina. The core non-ribosomal peptide synthetase (NRPS)-like enzyme AlfA of the alf BGC produces polyporic acid from phenylpyruvic acid. In subsequent reactions, compound 2 is reductively dehydrated by the bifunctional enzyme AlfC and methylated by AlfD to produce terferol. In a final step, the quinol moiety of compound 6 is oxidatively cleaved and contracted by the aromatic ring cleavage dioxygenase AlfB. Using combinatorial biosynthesis, we were able to manipulate the biosynthetic route to yield hydroxylated pathway congeners, most notably the new natural products deoxyascocorynin, hydroxyterferol, and hydroxyallantofuranone
Single-port robot-assisted cervical esophagectomy (SP RACE) : combining precision mediastinal lymphadenectomy and complete extrapulmonary dissection
No full textHLN-Tree : a memory-efficient B+-Tree with huge leaf nodes and locality predictors
No full textKey-value stores in Cloud environments can contain more than 245 unique elements and be larger than 100 PByte. B+-Trees are well suited for these larger-than-memory datasets and seamlessly index data stored on thousands of secondary storage devices. Unfortunately, it is often uneconomical to even store all inner tree nodes in memory for these dataset sizes. Therefore, lookup performance is affected by the additional IOs for reading inner nodes.
This number of inner nodes can be reduced by increasing the size of leaf nodes. We propose HLN-Trees, which support huge leaf nodes without increasing the IO sizes for individual index operations. They partition leaf nodes in arrays of independent subnodes and combine ideas from BD-trees with rebalancing, learning key deviations, and storing locality predictors. HLN-Trees have been initially designed for uniform random key distributions and support arbitrary key distributions through an additional layer of hashing in leaf nodes. HLN-Trees decrease the number of inner nodes by up to 256× for uniform random key distributions and by 16× to 64× for arbitrary ones compared to B+-Trees, while keeping their performance at the same level even at high concurrency levels. We show analytically and through real-world and synthetic benchmarks that HLN-Trees also outperform state-of-the-art learned indexes for secondary storage