Search Results
Scanning electron microscopy preparation of the cellular actin cortex: A quantitative comparison between critical point drying and hexamethyldisilazane drying
2021, Schu, Moritz, Terriac, Emmanuel, Koch, Marcus, Paschke, Stephan, Lautenschläger, Franziska, Flormann, Daniel A.D.
The cellular cortex is an approximately 200-nm-thick actin network that lies just beneath the cell membrane. It is responsible for the mechanical properties of cells, and as such, it is involved in many cellular processes, including cell migration and cellular interactions with the environment. To develop a clear view of this dense structure, high-resolution imaging is essential. As one such technique, electron microscopy, involves complex sample preparation procedures. The final drying of these samples has significant influence on potential artifacts, like cell shrinkage and the formation of artifactual holes in the actin cortex. In this study, we compared the three most used final sample drying procedures: critical-point drying (CPD), CPD with lens tissue (CPD-LT), and hexamethyldisilazane drying. We show that both hexamethyldisilazane and CPD-LT lead to fewer artifactual mesh holes within the actin cortex than CPD. Moreover, CPD-LT leads to significant reduction in cell height compared to hexamethyldisilazane and CPD. We conclude that the final drying procedure should be chosen according to the reduction in cell height, and so CPD-LT, or according to the spatial separation of the single layers of the actin cortex, and so hexamethyldisilazane.
Self-assembly of Co/Pt stripes with current-induced domain wall motion towards 3D racetrack devices
2024, Fedorov, Pavel, Soldatov, Ivan, Neu, Volker, Schäfer, Rudolf, Schmidt, Oliver G., Karnaushenko, Daniil
Modification of the magnetic properties under the induced strain and curvature is a promising avenue to build three-dimensional magnetic devices, based on the domain wall motion. So far, most of the studies with 3D magnetic structures were performed in the helixes and nanowires, mainly with stationary domain walls. In this study, we demonstrate the impact of 3D geometry, strain and curvature on the current-induced domain wall motion and spin-orbital torque efficiency in the heterostructure, realized via a self-assembly rolling technique on a polymeric platform. We introduce a complete 3D memory unit with write, read and store functionality, all based on the field-free domain wall motion. Additionally, we conducted a comparative analysis between 2D and 3D structures, particularly addressing the influence of heat during the electric current pulse sequences. Finally, we demonstrated a remarkable increase of 30% in spin-torque efficiency in 3D configuration.
Computational design and optimization of electro-physiological sensors
2021, Nittala, Aditya Shekhar, Karrenbauer, Andreas, Khan, Arshad, Kraus, Tobias, Steimle, Jürgen
Electro-physiological sensing devices are becoming increasingly common in diverse applications. However, designing such sensors in compact form factors and for high-quality signal acquisition is a challenging task even for experts, is typically done using heuristics, and requires extensive training. Our work proposes a computational approach for designing multi-modal electro-physiological sensors. By employing an optimization-based approach alongside an integrated predictive model for multiple modalities, compact sensors can be created which offer an optimal trade-off between high signal quality and small device size. The task is assisted by a graphical tool that allows to easily specify design preferences and to visually analyze the generated designs in real-time, enabling designer-in-the-loop optimization. Experimental results show high quantitative agreement between the prediction of the optimizer and experimentally collected physiological data. They demonstrate that generated designs can achieve an optimal balance between the size of the sensor and its signal acquisition capability, outperforming expert generated solutions.
Reply to Burgess et al: Catastrophic climate risks are neglected, plausible, and safe to study
2022, Kemp, Luke, Xu, Chi, Depledge, Joanna, Ebi, Kristie L., Gibbins, Goodwin, Kohler, Timothy A., Rockström, Johan, Scheffer, Marten, Schellnhuber, Hans Joachim, Steffen, Will, Lenton, Timothy M.
Research data management in agricultural sciences in Germany: We are not yet where we want to be
2022, Senft, Matthias, Stahl, Ulrike, Svoboda, Nikolai
To meet the future challenges and foster integrated and holistic research approaches in agricultural sciences, new and sustainable methods in research data management (RDM) are needed. The involvement of scientific users is a critical success factor for their development. We conducted an online survey in 2020 among different user groups in agricultural sciences about their RDM practices and needs. In total, the questionnaire contained 52 questions on information about produced and (re-)used data, data quality aspects, information about the use of standards, publication practices and legal aspects of agricultural research data, the current situation in RDM in regards to awareness, consulting and curricula as well as needs of the agricultural community in respect to future developments. We received 196 (partially) completed questionnaires from data providers, data users, infrastructure and information service providers. In addition to the diversity in the research data landscape of agricultural sciences in Germany, the study reveals challenges, deficits and uncertainties in handling research data in agricultural sciences standing in the way of access and efficient reuse of valuable research data. However, the study also suggests and discusses potential solutions to enhance data publications, facilitate and secure data re-use, ensure data quality and develop services (i.e. training, support and bundling services). Therefore, our research article provides the basis for the development of common RDM, future infrastructures and services needed to foster the cultural change in handling research data across agricultural sciences in Germany and beyond.
Near-real-time monitoring of global CO2 emissions reveals the effects of the COVID-19 pandemic
2020, Liu, Zhu, Ciais, Philippe, Deng, Zhu, Lei, Ruixue, Davis, Steven J., Feng, Sha, Zheng, Bo, Cui, Duo, Dou, Xinyu, Zhu, Biqing, Guo, Rui, Ke, Piyu, Sun, Taochun, Lu, Chenxi, He, Pan, Wang, Yuan, Yue, Xu, Wang, Yilong, Lei, Yadong, Zhou, Hao, Cai, Zhaonan, Wu, Yuhui, Guo, Runtao, Han, Tingxuan, Xue, Jinjun, Boucher, Olivier, Boucher, Eulalie, Chevallier, Frédéric, Tanaka, Katsumasa, Wei, Yiming, Zhong, Haiwang, Kang, Chongqing, Zhang, Ning, Chen, Bin, Xi, Fengming, Liu, Miaomiao, Bréon, François-Marie, Lu, Yonglong, Zhang, Qiang, Guan, Dabo, Gong, Peng, Kammen, Daniel M., He, Kebin, Schellnhuber, Hans Joachim
The COVID-19 pandemic is impacting human activities, and in turn energy use and carbon dioxide (CO2) emissions. Here we present daily estimates of country-level CO2 emissions for different sectors based on near-real-time activity data. The key result is an abrupt 8.8% decrease in global CO2 emissions (−1551 Mt CO2) in the first half of 2020 compared to the same period in 2019. The magnitude of this decrease is larger than during previous economic downturns or World War II. The timing of emissions decreases corresponds to lockdown measures in each country. By July 1st, the pandemic’s effects on global emissions diminished as lockdown restrictions relaxed and some economic activities restarted, especially in China and several European countries, but substantial differences persist between countries, with continuing emission declines in the U.S. where coronavirus cases are still increasing substantially.
Environmental co-benefits and adverse side-effects of alternative power sector decarbonization strategies
2019, Luderer, Gunnar, Pehl, Michaja, Arvesen, Anders, Gibon, Thomas, Bodirsky, Benjamin L., de Boer, Harmen Sytze, Fricko, Oliver, Hejazi, Mohamad, Humpenöder, Florian, Iyer, Gokul, Mima, Silvana, Mouratiadou, Ioanna, Pietzcker, Robert C., Popp, Alexander, van den Berg, Maarten, van Vuuren, Detlef, Hertwich, Edgar G.
A rapid and deep decarbonization of power supply worldwide is required to limit global warming to well below 2 °C. Beyond greenhouse gas emissions, the power sector is also responsible for numerous other environmental impacts. Here we combine scenarios from integrated assessment models with a forward-looking life-cycle assessment to explore how alternative technology choices in power sector decarbonization pathways compare in terms of non-climate environmental impacts at the system level. While all decarbonization pathways yield major environmental co-benefits, we find that the scale of co-benefits as well as profiles of adverse side-effects depend strongly on technology choice. Mitigation scenarios focusing on wind and solar power are more effective in reducing human health impacts compared to those with low renewable energy, while inducing a more pronounced shift away from fossil and toward mineral resource depletion. Conversely, non-climate ecosystem damages are highly uncertain but tend to increase, chiefly due to land requirements for bioenergy.
Evolutionary design of explainable algorithms for biomedical image segmentation
2023, Cortacero, Kévin, McKenzie, Brienne, Müller, Sabina, Khazen, Roxana, Lafouresse, Fanny, Corsaut, Gaëlle, Van Acker, Nathalie, Frenois, François-Xavier, Lamant, Laurence, Meyer, Nicolas, Vergier, Béatrice, Wilson, Dennis G., Luga, Hervé, Staufer, Oskar, Dustin, Michael L., Valitutti, Salvatore, Cussat-Blanc, Sylvain
An unresolved issue in contemporary biomedicine is the overwhelming number and diversity of complex images that require annotation, analysis and interpretation. Recent advances in Deep Learning have revolutionized the field of computer vision, creating algorithms that compete with human experts in image segmentation tasks. However, these frameworks require large human-annotated datasets for training and the resulting “black box” models are difficult to interpret. In this study, we introduce Kartezio, a modular Cartesian Genetic Programming-based computational strategy that generates fully transparent and easily interpretable image processing pipelines by iteratively assembling and parameterizing computer vision functions. The pipelines thus generated exhibit comparable precision to state-of-the-art Deep Learning approaches on instance segmentation tasks, while requiring drastically smaller training datasets. This Few-Shot Learning method confers tremendous flexibility, speed, and functionality to this approach. We then deploy Kartezio to solve a series of semantic and instance segmentation problems, and demonstrate its utility across diverse images ranging from multiplexed tissue histopathology images to high resolution microscopy images. While the flexibility, robustness and practical utility of Kartezio make this fully explicable evolutionary designer a potential game-changer in the field of biomedical image processing, Kartezio remains complementary and potentially auxiliary to mainstream Deep Learning approaches.
State-of-the-art global models underestimate impacts from climate extremes
2019, Schewe, Jacob, Gosling, Simon N., Reyer, Christopher, Zhao, Fang, Ciais, Philippe, Elliott, Joshua, Francois, Louis, Huber, Veronika, Lotze, Heike K., Seneviratne, Sonia I., van Vliet, Michelle T. H., Vautard, Robert, Wada, Yoshihide, Breuer, Lutz, Büchner, Matthias, Carozza, David A., Chang, Jinfeng, Coll, Marta, Deryng, Delphine, de Wit, Allard, Eddy, Tyler D., Folberth, Christian, Frieler, Katja, Friend, Andrew D., Gerten, Dieter, Gudmundsson, Lukas, Hanasaki, Naota, Ito, Akihiko, Khabarov, Nikolay, Kim, Hyungjun, Lawrence, Peter, Morfopoulos, Catherine, Müller, Christoph, Müller Schmied, Hannes, Orth, René, Ostberg, Sebastian, Pokhrel, Yadu, Pugh, Thomas A. M., Sakurai, Gen, Satoh, Yusuke, Schmid, Erwin, Stacke, Tobias, Steenbeek, Jeroen, Steinkamp, Jörg, Tang, Qiuhong, Tian, Hanqin, Tittensor, Derek P., Volkholz, Jan, Wang, Xuhui, Warszawski, Lila
Global impact models represent process-level understanding of how natural and human systems may be affected by climate change. Their projections are used in integrated assessments of climate change. Here we test, for the first time, systematically across many important systems, how well such impact models capture the impacts of extreme climate conditions. Using the 2003 European heat wave and drought as a historical analogue for comparable events in the future, we find that a majority of models underestimate the extremeness of impacts in important sectors such as agriculture, terrestrial ecosystems, and heat-related human mortality, while impacts on water resources and hydropower are overestimated in some river basins; and the spread across models is often large. This has important implications for economic assessments of climate change impacts that rely on these models. It also means that societal risks from future extreme events may be greater than previously thought.
Key determinants of global land-use projections
2019, Stehfest, Elke, van Zeist, Willem-Jan, Valin, Hugo, Havlik, Petr, Popp, Alexander, Kyle, Page, Tabeau, Andrzej, Mason-D’Croz, Daniel, Hasegawa, Tomoko, Bodirsky, Benjamin L., Calvin, Katherine, Doelman, Jonathan C., Fujimori, Shinichiro, Humpenöder, Florian, Lotze-Campen, Hermann, van Meijl, Hans, Wiebe, Keith
Land use is at the core of various sustainable development goals. Long-term climate foresight studies have structured their recent analyses around five socio-economic pathways (SSPs), with consistent storylines of future macroeconomic and societal developments; however, model quantification of these scenarios shows substantial heterogeneity in land-use projections. Here we build on a recently developed sensitivity approach to identify how future land use depends on six distinct socio-economic drivers (population, wealth, consumption preferences, agricultural productivity, land-use regulation, and trade) and their interactions. Spread across models arises mostly from diverging sensitivities to long-term drivers and from various representations of land-use regulation and trade, calling for reconciliation efforts and more empirical research. Most influential determinants for future cropland and pasture extent are population and agricultural efficiency. Furthermore, land-use regulation and consumption changes can play a key role in reducing both land use and food-security risks, and need to be central elements in sustainable development strategies.
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