Technische Universität Dresden: Qucosa
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Promoting Complex Problem Solving by Introducing Schema-Governed Categories of Key Causal Models
No full textThe ability to recognize key causal models across situations is associated with expertise. The acquisition of schema-governed category knowledge of key causal models may underlie this ability. In an experimental study (n = 183), we investigated the effects of promoting the construction of schema-governed categories and how an enhanced ability to recognize the key causal models relates to performance in complex problem-solving tasks that are based on the key causal models. In a 2 × 2 design, we tested the effects of an adapted version of an intervention designed to build abstract mental representations of the key causal models and a tutorial designed to convey conceptual understanding of the key causal models and procedural knowledge. Participants who were enabled to recognize the underlying key causal models across situations as a result of the intervention and the tutorial (i.e., causal sorters) outperformed non-causal sorters in the subsequent complex problem-solving task. Causal sorters outperformed the control group, except for the subtask knowledge application in the experimental group that did not receive the tutorial and, hence, did not have the opportunity to elaborate their conceptual understanding of the key causal models. The findings highlight that being able to categorize novel situations according to their underlying key causal model alone is insufficient for enhancing the transfer of the according concept. Instead, for successful application, conceptual and procedural knowledge also seem to be necessary. By using a complex problem-solving task as the dependent variable for transfer, we extended the scope of the results to dynamic tasks that reflect some of the typical challenges of the 21st century
Anatomy segmentation in laparoscopic surgery: Comparison of machine learning and human expertise: An experimental study
No full textBackground: Lack of anatomy recognition represents a clinically relevant risk in abdominal surgery. Machine learning (ML) methods can help identify visible patterns and risk structures; however, their practical value remains largely unclear.
Materials and methods: Based on a novel dataset of 13 195 laparoscopic images with pixel-wise segmentations of 11 anatomical structures, we developed specialized segmentation models for each structure and combined models for all anatomical structures using two state-of-the-art model architectures (DeepLabv3 and SegFormer) and compared segmentation performance of algorithms to a cohort of 28 physicians, medical students, and medical laypersons using the example of pancreas segmentation. Results: Mean Intersection-over-Union for semantic segmentation of intra-abdominal structures ranged from 0.28 to 0.83 and from 0.23 to 0.77 for the DeepLabv3-based structure-specific and combined models, and from 0.31 to 0.85 and from 0.26 to 0.67 for the SegFormer-based structure-specific and combined models, respectively. Both the structure-specific and the combined DeepLabv3-based models are capable of near-real-time operation, while the SegFormer-based models are not. All four models outperformed at least 26 out of 28 human participants in pancreas segmentation. Conclusions: These results demonstrate that ML methods have the potential to provide relevant assistance in anatomy recognition in minimally invasive surgery in near-real-time. Future research should investigate the educational value and subsequent clinical impact of the respective assistance systems
Long-term growth decline is not reflected in crown condition of European beech after a recent extreme drought
No full textGlobal warming poses a major threat to forest ecosystems around the world. In Central Europe, vitality losses and tree mortality have already been observed in various regions, especially after extreme drought episodes such as the 2018–2020 drought. European beech (Fagus sylvatica L.), which is the dominating deciduous tree species in large parts of temperate Europe, also suffered from the recent drought. In Germany, for example, losses in crown condition were observed. Within individual stands, however, the crown condition of beech differed strongly from non–/weakly damaged trees (hereafter referred to as vital trees) to severely damaged/dead trees (non-vital trees). Tree characteristics and micro-site conditions were apparently similar. Hence, we checked whether differences in growth behavior exist and (or) developed over time and assessed if observed differences between the non–/vital individuals might be genetically driven. We found that the climate sensitivity as well as the drought resistance of tree growth did not consistently differ between non–/vital trees. In both groups, a growing importance of water availability for tree growth was apparent. Further, long-term growth decline was widespread in both vital and non-vital trees, suggesting severe stress and future risks of tree mortality irrespective of crown condition. Only at one out of nine sites, we found significant differences in individual heterozygosity, signaling potential differences in the adaptation of trees to environmental stress. As a consequence, our study highlights that crown condition after an extreme drought is a poorer indicator of tree vitality than ring width in beech stands in Germany
From Jacobin flaws to transformative populism: Left populism and the legacy of European social democracy
No full textIn the established landscape of research in the social sciences, populism is seen as a type of politics that chiefly revolves around the distinction between the “people” and the “elite”.1 Within this, different forms of populism can be distinguished—ranging from right-wing and authoritarian to liberal-centrist and religious varieties. In the camp of the political left, populism is often cast as essentially a democratic endeavor. Drawing on a conception of inclusive peoplehood, which is not opposed to other vulnerable social groups “below” but solely to the “elite above”, many authors emphasize that it is crucial to pursue a populist strategy in order to overcome existing hegemonies, democratic deficits, ossifications, and class-rule (Grattan, 2016; Howse, 2019; Kempf, 2020; McCormick, 2001; Mouffe, 2018). Throughout the past few decades, the landscape of research on left populism has grown considerably. Various studies have investigated the history of anti-establishment popular movements of the 19th century, such as the Narodniki in Russia or the American Populist Party (Canovan, 1981; Kazin, 1995). Further, research has also looked at how, from the 1990s, anti-neoliberal alliances in Latin America had their momentum, entered governmental office, and established a far-reaching renewal of constitutional orders (Linera, 2014; Weyland, 2013). And in particular, in the last decade, the rejuvenation of left politics in Europe and the United States has often relied on populist approaches (Katsambekis & Kioupkiolis, 2019).... [Aus: Introduction
Successful Combination of Olaparib and ²²⁵Ac-Dotatate in a Patient with Neuroendocrine Tumor G3 and BRCA Mutation
No full textBased on the results of the NETTER-1 trial, peptide receptor radionuclide therapy with Lutetium-177 (¹⁷⁷Lu) – DOTATATE is authorized for the treatment of neuroendocrine tumors (NET) grade 1 (G1) and grade 2 (G2) of the intestine. After the failure of ¹⁷⁷Lu-DOTATATE therapy, targeted alpha-particle therapy (TAT) may be a possible treatment option. Here, we present a patient with cancer of unknown primary NET G2 later G3. The patient was referred to our hospital with urosepsis due to a second-degree urinary retention. After stent insertion, a contrast-enhanced computed tomography revealed a huge pelvic tumor without metastases. Initially, the patient had undergone surgical treatment. Later the patient developed liver metastasis and was treated by ¹⁷⁷Lu-DOTATATE therapy and four lines of systemic therapy. A disease progression was observed and with the knowledge of a germline BRCA1 mutation, the patient was treated with TAT (Actinium-225 [²²⁵Ac]-DOTATATE) combined with olaparib. The patient achieved a significant treatment response for 12 months indicating that a combination therapy with an alpha emitter and olaparib demands further investigations in clinical trials
Second generation of soluble transferrin receptor assay – consequences for the interpretation of the ‘Thomas plot’
No full textObjectives:
The ‘Thomas plot’ is a very helpful diagnostic tool for evaluation, monitoring and therapy of the iron status and on the hemoglobinization of the reticulocytes of patients. In 2021 Roche Diagnostics launched a second generation assay for determination of the soluble transferrin receptor (sTfR). Here we compare the old and the new assay for sTfR and analyze the consequences for the ‘Thomas plot’.
Methods:
Measurement of sTfR, ferritin and CRP were done using a Cobas8000 system. Hemoglobin content of reticulocytes (Ret-He) was determined using a Sysmex XN9000 system.
Results:
The second generation of sTfR assay showed consistently lower sTfR values compared to the first generation, which would result in a left shift of the ‘Thomas plot’ and may lead to false diagnosis of patients using the original cut-offs. Fifteen thousand five hundred ninty two data sets for ‘Thomas plot’ from 2016 to 2021 were retrospectively analyzed to estimate how many patients in our hospital would be affected. In result around 5 % of all ‘Thomas plots’ would be affected by the lower sTfR values of the second generation assays.
Conclusions:
Due to the lower sTfR values measured with the second generation assay new cut-offs for the Ferritin-Index (sTfR/lg Ferritin) should be used in order to correctly diagnose the iron status of patients
Carbon-saving benefits of various end-of-life strategies for different types of building structures
No full textAgainst the backdrop of advocating for ultra-low energy consumption buildings both domestically and internationally, much attention has been attracted to energy consumption and carbon emissions at the end-of-life (EoL) stage from the whole life cycle of buildings. Recycling of construction and demolition wastes (C&DW) is an inevitable step in achieving the goals of ultra-low energy consumption and “carbon neutrality.” In this paper, the life cycle assessment (LCA) theory was employed to study the carbon-saving benefits of four different EoL strategies (i.e., recycling, remanufacturing, reuse, and the integrated strategy) for various building structures (including frame, frame shear wall, shear wall, and light steel structures), in which the carbon-saving potential (CSP) was served as the evaluation index. The results show that compared with the traditional demolition and landfill disposal methods, the implementation of integrated management strategies for structural buildings in this study can reduce carbon emissions by 150.7–246.8 kgCO₂-e/m², with the carbon-savings of 11.9–34.8 times the carbon emissions generated by the abandoned landfill. Among the four structures, the light steel structure has the greatest CSP, reaching (73.75–77.24%), followed by the frame shear wall structure (42.67–46.93%), the frame structure (41.19–45.11%), and the shear wall structure (39.00–43.79%). When the building life span is 50 years, all CSPs of the four structural buildings significantly increased, at this point, deconstruction of the building is the most reasonable approach
Mild Behavioral Impairment: Overview and Aspects of Forensic Psychiatry
No full textSocially inappropriate behavior accompanies and modulates delinquency across the lifespan. In contrast to young people, the emergence of such traits among older individuals could indicate incipient neurodegenerative disease. Before developing a neurocognitive disorder, subtle behavioral changes may reflect a disintegration of neural networks involved in impulse control or social cognition. Whereas psychiatric evaluation often considers a comprehensive cognitive assessment, unremarkable results may discourage clinicians from recognizing brain disease underlying behavioral disturbance. We first provide an overview of its manifestations and neural correlates and the interrelations with mild cognitive impairment (MCI) before demonstrating how to investigate and diagnose mild behavioral impairment (MBI). Finally, we show how to appreciate MBI in geriatric forensic psychiatry
A Water Monitoring System for Proton Exchange Membrane Fuel Cells Based on Ultrasonic Lamb Waves: An Ex-Situ Proof of Concept
No full textUp to date, the efficiencies of proton exchange membrane fuel cells (PEMFCs) are limited by the water flooding issue. Water monitoring systems, which are a crucial step to overcoming these flooding-related problems, are mostly either invasive or compromise on the temporal resolution and field of view. Thus, we propose an ultrasonic-Lamb-waves-based, real-time, and nondestructive water monitoring system. Briefly, ultrasonic transducers are mounted on the back side of bipolar plates (BPPs) exciting Lamb waves along flow channels incorporated in BPPs. Echo signals from water droplets in the channels are also received by the transducers. Thus, with the knowledge of Lamb wave propagation velocity, water droplets are spatially resolved by the time of flight of each droplet echo. Meanwhile, the energy of each droplet-induced echo wave packet is used to quantify the local flooding status. We have implemented a flexible and generic system adaptable to various flow field designs. The working principle was demonstrated for ex situ conditions with a BPP with a 25-cm2 active area. A water sensitivity of at least 50 nL was realized, allowing for studying droplet and slug flows in PEMFCs. A 1.3-mm spatial resolution and a 2-kHz temporal resolution were simultaneously achieved. The high-performance water monitoring opens new horizons to study dynamic water evolution in channels of PEMFCs using cost-effective instrumentation, which may pave the way toward more efficient high-power PEMFCs with increased lifetimes
Modular Synthesis of Structurally Diverse Azulene-Embedded Polycyclic Aromatic Hydrocarbons by Knoevenagel-Type Condensation
No full textThe research interest in azulene-embedded polycyclic aromatic hydrocarbons (PAHs) has significantly increased recently, but the lack of efficient synthetic strategies impedes the investigation of their structure-property relationships and further opto-electronic applications. Here we report a modular synthetic strategy towards diverse azulene-embedded PAHs by a tandem Suzuki coupling and base-promoted Knoevenagel-type condensation with good yields and great structural versatility, including non-alternant thiophene-rich PAHs, butterfly- or Z-shaped PAHs bearing two azulene units, and the first example of a two-azulene-embedded double [5]helicene. The structural topology, aromaticity and photophysical properties were investigated by NMR, X-ray crystallography analysis and UV/Vis absorption spectroscopy assisted by DFT calculations. This strategy provides a new platform for rapidly synthesizing unexplored non-alternant PAHs or even graphene nanoribbons with multiple azulene units