TU Braunschweig: LeoPARD - Publications And Research Data
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Prozess- und Werkzeugtechnologien für funktionsintegrierte hybride Bauweisen: Ergebnisse aus dem BMFTR-geförderten Verbundprojekt TechnoHyb
No full textTracking soil moisture dynamics with Vis-NIR spectroscopy during laboratory bare-soil evaporation
Full text linkNumerous studies have investigated the relationship between spectral signal and soil moisture in the laboratory, usually using data from soil samples with predefined moisture levels for model calibration. However, it remains untested whether spectral monitoring can accurately capture the dynamic moisture changes occurring at the soil surface during drying. We conducted evaporation experiments on 5 cm tall packed soil columns of two soil types (sand and silt loam). The surface water content of each soil column was assessed by repeatedly recording spectra in the visible, near infrared, and shortwave infrared domain using an ASD Fieldspec® Pro spectrometer (350–2500 nm). The inferred water contents were then compared to those obtained from a numerical simulation with the Richards equation, which used soil hydraulic properties determined with the simplified evaporation method and measured evaporation rates as boundary condition. To develop the spectral model, samples with defined water contents were independently analyzed with the ASD. Among the three tested spectral models (polynomial linear regression, principal component regression (PCR) and partial least squares regression (PLSR)), the best model performance was achieved by polynomial linear regression. Regarding the transient evaporation experiments, the spectral model led to generally lower surface water contents than those predicted by the Richards equation. While soil moisture estimates for the silt loam closely matched simulated values (mean error = 2.81 vol%), the sandy soil exhibited systematic underestimations (mean error = 7.13 vol%), likely due to factors related to measurement setup and contact probe placement
Children’s perspectives on autonomous vehicles: A usability and user experience study in a high-fidelity prototype
Full text linkDriverless or autonomous vehicles (AVs) have the potential to improve the mobility of children and young people without a driver’s license, who are currently dependent on adult drivers in everyday life. An essential prerequisite for offering children and adolescents autonomous rides for unaccompanied transportation in everyday life is that they can operate such an AV without the support of others. We therefore conducted a usability study in which children (supported by their parents) tested the high-fidelity prototype of the family AV “autoELF”. Fifteen parents and seventeen of their 7- to 14-year-old children tested the AV prototype in the laboratory. During an imaginary ride, the children used the safety and entertainment features required to operate the AV during a normal ride. In a post-session interview, the children reported on their experiences as users. Children and parents were asked about their willingness to integrate AV into their family’s mobility. The main findings were that the children were able to transfer their knowledge from their current interaction with cars and technology to the new AV context. Most children were able to use most of the AV’s features without help from their parents and on the first try, when the children were already familiar with the task. Icons and written keywords supported children’s understanding of the vehicle features and their functionality. The study provides practical recommendations for the design of child-friendly user interfaces in AVs
Sample Intake Port Geometries for a Light-Duty Diesel Engine
No full textIn Diesel engines, charge motion usually consists of swirl and squish flow patterns which are traditionally controlled through the design of the intake ports. A new fully parametric geometry was created and the simulational and experimental behavior when applied to a 2.0L VW light-duty Diesel engine is given in the conference entry "Simulation of Swirl and Discharge Coefficient Trade-off for Diesel Engine Intake Ports" to 17th International Conference on Engines & Vehicles for Sustainable Transport, Capri, Italy. Some of the intake ports with different parameters can be found in this repository
Sex-specific differences in the experience of adverse childhood experiences: transmission, protective, and risk factors from the perspectives of parents and their children-results of an 18-year German longitudinal study
Full text linkTheoretical background Adverse childhood experiences (ACEs) are strongly associated with mental and physical health problems across the lifespan, emphasizing the critical need for prevention. Sex-specific differences in both the prevalence and long-term consequences of ACEs have rarely been analyzed, especially in longitudinal studies, which are particularly needed. Objective This longitudinal study explores risk and protective factors as well as the intergenerational transmission of ACEs from parents to children, with a focus on sex-specific effects. Methods Data from 316 families participating in the 18-year German longitudinal project "Future Family" were analysed. The dataset included information from mothers (54 years), fathers (57 years), and their emerging adults (22 years). Results Daughters and mothers reported significantly more ACEs than fathers and sons, particularly in the categories of abuse and neglect. Experiencing four or more ACEs was associated with higher levels of psychological distress and lower life satisfaction for both parents and children. Approximately half of the emerging adults experienced a similar number of ACEs as their parents; however, the types of ACEs often differed, with children encountering distinct ACEs. Protective factors, such as higher maternal socio-economic status, maternal participation in the Positive Parenting Program (Triple P), and fewer internalizing problems in early childhood, were associated with a reduced number of ACEs in children by the age of 18. Conclusion Although women report higher rates of ACEs, men are not less affected in terms of psychological distress. Sex-specific considerations appear to be crucial in the prevention of ACEs and should be integrated into targeted strategies. Our findings highlight the importance of considering both parents' perspectives in developing and implementing effective preventive interventions in families
Smart Prussian Blue Analog Decorated with Zinc Oxide Nanohybrid: Fluorescent Sensing and Sustainability of Sunset Yellow in Food and Environment
Full text linkIn the current study, the Prussian blue analog decorated with zinc oxide (PBA@ZnO) was produced using a simple chemical co-precipitation method. The nanohybrid was examined using XRD, EDX, SEM, and TEM techniques, where it exhibited a polycrystalline structure with highly intense broadening peaks. The surface morphology was observed as thin nanosheets decorated with tiny spheres. Following excitation at 360 nm, the fluorescence spectra of PBA@ZnO showed fluorescence emission at 455 nm. The developed PBA@ZnO was used to qualitatively and quantitatively assess sunset yellow (SY), where its native fluorescence was selectively quenched as SY concentrations increased. For the first time, PBA@ZnO was used as a turn-off nano-sensor for the spectrofluorimetric measurement of SY. The method's markable sensitivity was demonstrated within an SY linearity range of 50-500 ng/mL, where the limit of detection was calculated as 9.77 ng/mL. Real sample analysis in the food industry, including samples from real food, soft drinks, and sun cream, was made possible by the detection of tiny amounts of SY. Analytical Greenness (AGREE), AGREEprep, and the complementing Green Analytical Procedure Index (Complex MoGAPI) were used to illustrate the new approach's exceptional eco-friendliness and greenness. The RGB 12 algorithm worked to demonstrate that the suggested approach is less costly, more environmentally friendly, more sustainable, analytically sound, and whiter than the ones that were previously published. In accordance with ICH principles, the suggested method was validated. This approach offers a promising way to rapidly and accurately identify and measure SY in the food industry, helping to guarantee food safety and maintain the health of customers
Datengetriebene Kraftmessung für tubuläre Kontinuumsroboter
Full text linkConcentric Tube Continuum Robots (CTRs) have the potential to become the next pivotal technology in minimally invasive surgeries due to their flexibility, compliance, and needle-size form factor. They excel in navigating complex anatomical passages without causing tissue damage, which makes them highly beneficial for medical applications. However, one of the significant challenges in deploying CTRs is the integration of accurate force sensing capabilities, which are crucial for ensuring safety and surgical precision. The embedding of force sensors into CTRs faces significant challenges due to these robots' small size and flexible structure. The complexity of accurately modeling the physical properties of CTRs makes it difficult for model-based estimation methods to balance the trade-off between computational cost and estimation accuracy. This thesis introduces novel data-driven techniques as an alternative to estimate the external contact forces on CTRs, leveraging machine learning models to find a mapping between the deflection of the robot and the contact forces acting on it. In other words, the goal is to turn the robot into a sensor by tracking only its shape. This thesis investigates how well and in which range data-driven methods using supervised learning can estimate tip contact forces by evaluating a set of features derived from the shape information of a CTR. Besides single contact force estimation, estimating the position and magnitude of multiple contact forces is essential when a CTR moves through confined spaces. However, this renders an ill-posed problem because a single shape of a CTR can be formed via multiple contact scenarios. Inspired by Direct Cascade Architectures, a novel cascaded learning scheme was established to estimate the forces at multiple contact points along the robot's backbone. A unique feature of CTRs is their capability to be optimized for a specific task and its constraints, for example, optimizing the stiffness parameters of the tubes to be able to exert a particular magnitude of force. This unique feature presents a problem for supervised learning methods and their dependency on sufficient data, as each new tube setup requires learning from scratch. However, acquiring new data is not always possible. Therefore, a novel feature-based transfer learning method was established based on finding diffeomorphisms between curved and non-curved tubes. This method enables the utilization of pretrained supervised learning models on data from entirely different tube setups without retraining. The methods developed in this thesis lay the groundwork for new data-driven types of virtual sensors for force measurements for CTRs. They not only address crucial challenges within the field but also open avenues for further innovations in robot-assisted surgeries.Concentric Tube Continuum Robots (CTRs) zeigen aufgrund ihrer außergewöhnlichen Flexibilität und ihrer geringen Größe, erhebliches Potenzial, eine Schlüsseltechnologie in der Domäne der robotergestützten minimalinvasiven Chirurgie zu werden. Diese Systeme sind besonders dadurch gekennzeichnet, dass sie in der Lage sind, durch schmale und komplexe anatomische Strukturen zu navigieren, ohne Gewebeschäden zu verursachen. Eine der primären Herausforderungen für den Einsatz von CTRs in klinischen Szenarien ist jedoch die Integration von Kraftsensoren. Dabei spielt die Kraftrückkopplung basierend auf Kraftsensoren eine wichtige Rolle für die Sicherheit und die präzise Durchführung chirurgischer Eingriffe. Die Integration von Sensoren in CTRs ist aufgrund der geringen Größe und der inhärenten Flexibilität dieser Roboterplattformen mit erheblichen Schwierigkeiten verbunden. Die Komplexität der genauen Modellierung der physikalischen Eigenschaften von CTRs erschwert zudem modellbasierte Schätzmethoden, die sich in einem Kompromiss zwischen intensiven Berechnungszeiten und Schätzgenauigkeit befinden. In der vorliegenden Dissertation werden neuartige, datengetriebene Verfahren als Alternative zur modellbasierten Schätzung externer Kontaktkräfte für CTRs präsentiert, die auf Modellen des maschinellen Lernens basieren. Diese Modelle nutzen die Auslenkung der Röhrchen des Kontinuumsroboters, um auf die auf ihn wirkenden Kontaktkräfte zu schließen. Es wird analysiert, in welchem Umfang und mit welcher Genauigkeit datengetriebene Methoden mittels überwachten Lernens fähig sind, die Normalkräfte an der Spitze von CTRs abzuschätzen. Neben der Schätzung einer einzelnen punktuell auftretenden Kraft ist auch die Schätzung der Lastverteilung entlang der Röhrchen eines CTRs wichtig, damit die Stärke von Kollisionen mit der Umgebung gemessen werden kann. Dies stellt jedoch ein besonderes Problem dar, da verschiedene Kontaktszenarien zur gleichen Verbiegung der Röhrchen des Roboters führen können. In dieser Arbeit wird ein datengetriebenes Verfahren vorgestellt, das Kaskaden neuronaler Netze verwendet, um mehrere mögliche Lösungen gleichzeitig zu schätzen. Eine Besonderheit von CTRs ist die Möglichkeit, ihre Röhrchen für eine bestimmte Aufgabe und deren Gegebenheiten anzupassen, z. B. um durch Optimierung der Steifigkeit die ausübbaren Kräfte zu verbessern. Da datengetriebene Verfahren Schätzungen basierend auf Daten treffen, müssen für jede neue Röhrchenkonfiguration neue Messungen gemacht werden, um die Relation zwischen Biegung und wirkender Kraft neu zu lernen. Um den Aufwand zu reduzieren, wird ein neuartiges Transferlernverfahren etabliert, das diffeomorphe Abbildungen zwischen der Geometrie gekrümmter und nicht gekrümmter Röhrchen findet und somit die Nutzung von vortrainierten überwachten Lernmodellen auf Daten von neuen, nicht gelernten Röhrchenkonfigurationen ohne erneutes Training ermöglicht. Die in dieser Arbeit entwickelten Methoden etablieren einen wichtigen Fortschritt für die Entwicklung virtueller Sensoren zur Kraftmessung in CTRs, adressieren kritische Herausforderungen in diesem Feld und eröffnen neue Wege für zukünftige Innovationen in der robotergestützten Chirurgie
Deciphering genetic causality between plasma BDNF and 91 circulating inflammatory proteins through bidirectional mendelian randomization
Full text linkPrior studies reported an association between the levels of brain-derived neurotrophic factor (BDNF) circulating in the bloodstream and those of different inflammatory factors. However, their causal relationship remains unclear. Here, we performed a Mendelian randomization (MR) study to investigate the causal relationships between plasma BDNF levels and 91 circulating inflammatory proteins to shed light on the possible role of BDNF in the pathogenesis and progression of inflammation-related neurological diseases in order to distinguish correlation from possible causal effects. Data for plasma BDNF levels were derived from a genome-wide association study (GWAS) encompassing 3,301 European participants. Genetic association estimates for 91 inflammation proteins were extracted from a GWAS meta-analysis that enrolled 14,824 European participants. The primary MR analysis employed the inverse variance weighted (IVW) method and was corroborated by additional methods including MR-Egger, weighted median, weighted mode, and simple mode. Analyses of sensitivity were performed by evaluating the heterogeneity, horizontal pleiotropy, and robustness of the results. Genetic evidence indicated that elevated plasma BDNF levels possibly contribute to decreased concentrations of 13 inflammation proteins (OR: 0.951-0.977), including beta-nerve growth factor (Beta-NGF), caspase 8 (CASP-8), interleukin-15 receptor subunit alpha (IL-15RA), interleukin-17 A (IL-17 A), interleukin-17 C (IL-17 C), interleukin-2 (IL-2), interleukin-20 (IL-20), interleukin-20 receptor subunit alpha (IL-20RA), interleukin-24 (IL-24), interleukin-33 (IL-33), leukemia inhibitory factor (LIF), neurturin (NRTN), as well as neurotrophin-3 (NT-3). The associations between BDNF and IL-33 remained statistically significant after FDR correction (FDR > 0.05). Furthermore, reverse MR analysis showed that C-C motif chemokine 23 (CCL23), CUB domain-containing protein 1 (CDCP1), and NRTN is suggestive for a positive causal effect on BDNF plasma levels (OR: 1.240-1.422). Moreover, 5 proteins are likely to be associated with lower plasma levels of BDNF (OR: 0.742-0.971), including adenosine deaminase (ADA), cystatin D (CST5), interleukin-13 (IL-13), interleukin-17 A (IL-17 A), and vascular endothelial growth factor A (VEGF-A). Genetically determined plasma BDNF levels influence IL-33 and are possibly associated with 12 circulating inflammatory proteins. The data suggest that 8 inflammatory proteins exhibit either negative or protective roles to BDNF levels, respectively. Of these, 5 are negatively associated with BDNF levels, while 3 play protective roles. These findings may offer new theoretical and empirical insights into the pathogenesis and progression of inflammation-related neurological diseases
Struvite Precipitation from Centrate—Identifying the Best Balance Between Effectiveness and Resource Efficiency
Full text linkIn the context of struvite precipitation, the most significant gap pertains to the transfer of knowledge from scientific research to practical applications. The primary objective of this study is twofold: firstly, to identify the most critical process parameters influencing struvite precipitation and, secondly, to translate these parameters into a pragmatic tool for real-world applications. This study investigates the precipitation of struvite from digestion centrate to obtain information on the appropriate precipitation conditions for different initial chemical compositions. We carried out 24 lab-scale experiments to investigate the effect of varying pH value (7.0–8.5), temperature (5 °C and 33 °C) and initial phosphate concentrations (353; 165; 68 mg/L) on struvite precipitation. Varying the pH had the strongest influence on precipitation efficiencies. Adjusting pH from 7 to 8.5 increased PO4-P removal from 1.4% to 98.8%, whereas temperature had little impact on PO4-P removal. Furthermore, we found that a saturation index of at least 1.7 is imperative to precipitate at least 90% of the available PO4-P. Based on the results, we developed a nomogram showing the resulting saturation index and the associated PO4-P removal efficiency for variable initial PO4-P and pH levels. The tool developed in this study enables users to directly identify the so-called ‘sweet spot’, which is the optimal balance between process effectiveness and resource efficiency, for each centrate
Young adults with migration background: mental health problems, risk behaviour, and educational and occupational development. Results of an 18-year longitudinal study
Full text linkThe few German studies on children, adolescents, and young adults with a migration background (MB) suggest a slightly greater burden compared to those without an MB. This difference is likely influenced by risk factors such as poorer living conditions and lower socio-economic status (SES). This study compares children with and without an MB (N = 316) at three assessment points over 18 years regarding mental health problems, substance use behaviour, and school and professional qualifications: in kindergarten, adolescence, and young adulthood. Young adults with an MB exhibited significantly more symptoms of depression and anxiety, poorer mental health, less social support, and more frequent risky alcohol and tobacco use compared to those without an MB. These differences persisted even when controlling for SES. The MB was found to be the most important predictor of mental health problems in young adulthood. Future studies should consider the heterogeneity of migrants