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Data set for lattice Boltzmann modelling of capillarity, adsorption and fluid retention in simple geometries: do capillary and film water have equal matric suction or not?
No full textThis data set includes the raw data of test cases, postprocessing method and final results for the numerical simulations presented in the article
El Natyasastra: la técnica del arte escénico.
No full textLa publicación de este libro constituye el primer estudio monográfico en castellano del “Natyasastra”. Aquí desarrollamos un análisis sistémico de las lecciones de este tratado integrando conceptos y temas que aparecen en sus páginas de forma aleatoria. Esto ha posibilitado articular metódicamente sus teorías del personaje, el lenguaje, la danza, la música, la escenografía, el vestuario, el maquillaje, y descubrir cómo se hallan contenidos en sus versículos y slokas los principios rectores de una dramaturgia universal que evidencian los pilares ancestrales de la puesta en escena. De igual modo, con esta investigación, ponemos de manifiesto la eficacia de las enseñanzas del “Natyasastra” en la formación actoral y la modernidad de su legado para el arte escénico.
Asimismo, la labor hermenéutica que durante años hemos desarrollado sobre la Obra Completa de Konstantin Stanislavski, investigación que dio como resultado el “Diccionario del actor. (Sistema de Konstantin S. Stanislavski)” en tres tomos, sirvió de antecedente para tratar en “El Natyasastra: la técnica del arte escénico”, los vínculos subyacentes que hemos descubierto entre este tratado y el sistema stanislavskiano, a pesar de que Stanislavski no tuvo conocimiento de su contenido por la divulgación del “Natyasastra” en Occidente después de su muerte.
The publication of this book constitutes the first monographic study in Spanish of the “Natyasastra”. Here, we develop a systematic analysis of the lessons of this treatise, integrating concepts and themes that appear randomly throughout its pages. This has made it possible to methodically articulate its theories of character, language, dance, music, stage design, costume, makeup, and to discover how the guiding principles of a universal dramaturgy that reflect the ancient pillars of stagecraft are contained within its verses and slokas. Likewise, with this research, we demonstrate the effectiveness of the “Natyasastra”'s teachings in actor training and the modernity of its legacy for the performing arts.
Likewise, the hermeneutical work we have been developing for years on the Complete Works of Konstantin Stanislavsky, research that resulted in the three-volume “Actor's Dictionary (Konstantin S. Stanislavsky's System),” served as a precedent for addressing in “The Natyasastra: The Technique of Stage Art,” the underlying links we have discovered between this treatise and the Stanislavskian system, despite the fact that Stanislavsky was unaware of its content due to the dissemination of the “Natyasastra” in the West after his death
Model weights for FastSurfer-CC: A robust, accurate and comprehensive framework for corpus callosum morphometry
No full textThe corpus callosum, the largest commissural structure in the human brain, is a central focus in research on aging and neurological diseases. It is also a critical target for interventions such as deep brain stimulation and serves as an important biomarker in clinical trials, including those investigating remyelination therapies. Despite extensive research on corpus callosum segmentation, few publicly available tools provide a comprehensive and automated analysis pipeline. To address this gap, we present FastSurfer-CC, an efficient and fully automated framework for corpus callosum morphometry. FastSurfer-CC automatically identifies mid-sagittal slices, segments the corpus callosum and fornix, localizes the anterior and posterior commissures to standardize head positioning, generates thickness profiles and subdivisions, and extracts eight shape metrics for statistical analysis. We demonstrate that FastSurfer-CC outperforms existing specialized tools across the individual tasks. Moreover, our method reveals statistically significant differences between Huntington's disease patients and healthy controls that are not detected by the current state-of-the-art.
Here we provide the model weights of FastSurfer-CC for download, e.g. by the FastSurfer toolbox (https://deep-mi.org/research/fastsurfer/
The Cirrus Guide III Data Set
No full textThe Cirrus Guide III data set contains
(i) The Cirrus Guide III in-situ data set (Krämer et al., 2020, Krämer et al., 2025):
Cloud and humidity observations in the troposhere, in particular in cirrus clouds, from research aircraft on a flight by flight basis.
The major parameters contained in the data set are: Cloud particle size distributions (PSDs), synchronized
to a logarithmically equidistant size grid, total water content (TWC = ice for temperatures T < -38C, liquid or ice or a
mixture between -38C - 0C, liquid for T > 0C), cloud particle number concentration N_cloud (physical state as for TWC),
mean mass radius R_cloud, in-cloud as well as the clear sky relative humidity with respect to ice (RH_ice) and clear sky
water vapor volume mixing ratios of H2O and O_3. Further, meteorological variables are included in the data set:
Time, Temperature, potential Temperature, Pressure, Altitude, Latitude, Longitude, Latitude, vertical velocity.
A description of the instruments, measurement methods and their uncertainties can be found in Krämer et al. (2016) and Krämer et al. (2020).
(ii) The Cirrus Guide data set with simulations of ice particle size distributions (Krämer et al., 2016, Krämer et al., 2025):
Simulations of the development of ice particle size distributions are performed for various conditions
(temperature, updraft, freezimg mechanism, freezing threshold, INP number) using the model MAID.
A description of the model is given in Krämer et al. (2016), Krämer et al. (2025).
Krämer, M., Rolf, C., Luebke, A., Afchine, A., Spelten, N., Costa, A., Meyer, J., Zöger, M., Smith, J., Herman, R. L., Buchholz, B., Ebert,
V., Baumgardner, D., Borrmann, S., Klingebiel, M., and Avallone, L.:
A microphysics guide to cirrus clouds – Part 1: Cirrus types, Atmos. Chem. Phys., 16, 3463–3483, https://doi.org/10.5194/acp-16-3463-2016, 2016.
Krämer, M., Rolf, C., Spelten, N., Afchine, A., Fahey, D., Jensen, E., Khaykin, S., Kuhn, T., Lawson, P., Lykov, A., Pan, L. L., Riese, M., Rollins, A., Stroh, F., Thornberry, T., Wolf, V., Woods, S., Spichtinger, P., Quaas, J., and Sourdeval, O.:
A Microphysics Guide to Cirrus – Part II: Climatologies of Clouds and Humidity from Observations, Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-40, in press, 2020.
Krämer, M., Rolf, C., Luebke, A., Afchine, A., Spelten, N., Costa, A., Meyer, J., Zöger, M., Smith, J., Herman, R. L., Buchholz, B., Ebert, V., Baumgardner, D., Borrmann, S., Klingebiel, M., and Avallone, L.:
A Microphysics Guide to Cirrus Clouds – Part 1: Cirrus types, Atmos. Chem. Phys., 16, 3463–3483, 2016
Natyasastra, de Bharata Muni.
No full textDespués de varios años dedicados al análisis textual del “Natyasastra”, publicamos por vez primera en castellano mi traducción de esta enciclopédica obra que constituye el primer gran tratado de artes escénicas que nos lega la antigüedad. Con el propósito de contextualizar sus conceptos dentro del ámbito original que fueron concebidos, he acompañado sus 36 capítulos de diversas expresiones en sánscrito que permiten a los estudiosos y especialistas su conocimiento, o la identificación de cada categoría. A su vez en todos los capítulos se desarrollan diversas notas críticas a fin de facilitar la comprensión y equivalencia de su terminología con el lenguaje escénico actual, siguiendo los siguientes criterios: mostrar la herencia de una categoría en el discurso teatral contemporáneo, destacar la vigencia de una idea o definición, corregir errores terminológicos, dar nuevas variantes o versiones de interpretación de diferentes pasajes a partir del estudio comparado que efectué de las dos ediciones clásicas de este libro fundacional.
En nuestro “Estudio preliminar” indago en las fuentes y orígenes del “Natyasastra”, investigo sus nexos con el teatro griego de la antigüedad, y revelamos en el epígrafe “El Natyasastra y la Poética” la consonancia de este tratado con la apreciación aristotélica de la escena.
After several years dedicated to textual analysis of the "Natyasastra," we are publishing for the first time in Spanish my translation of this encyclopedic work, the first major treatise on the performing arts left to us by antiquity. In order to contextualize its concepts within the original scope in which they were conceived, I have accompanied its 36 chapters with various Sanskrit expressions that allow scholars and specialists to understand them or identify each category. In turn, in all chapters various critical notes are developed in order to facilitate the understanding and equivalence of its terminology with the current stage language, also following the following criteria: to show the heritage of a category in contemporary theatrical discourse, to highlight the validity of an idea or definition, to correct terminological errors, to give new variants or versions of interpretation of different passages based on the comparative study that I carried out of the two classic editions of this foundational book.
In our “Preliminary Study” I delve into the sources and origins of the “Natyasastra”, I investigate its links with ancient Greek theatre, and we reveal in the section “The Natyasastra and Poetics” the consonance of this treatise with Aristotle’s appreciation of the stage
Long-term monitoring of plant diversity data in the “Montagna di Torricchio” strict Nature Reserve, Italy
No full textLong-term monitoring is pivotal to fully understanding spatio-temporal changes in plant diversity, particularly in protected areas. Here we present a dataset including plant presence and abundance data collected using a probabilistic sampling design in the “Montagna di Torricchio” Nature strict Reserve, central Apennines, Italy. Five surveys were conducted in 35 plots during a period spanning 22 years (2002-2024). The dataset allows to study plant diversity changes over space and time across different habitat types by using statistical inference based on solid sampling theory
Dataset for Training of a Deep Learning Based Digital Subtraction Angiography Method using Synthetic Data
No full textBackground: Digital subtraction angiography (DSA) is a fluoroscopy method primarily used for the diagnosis of cardiovascular diseases. Deep learning-based DSA (DDSA) is developed to extract DSA-like images directly from fluoroscopic images, which helps in saving dose while improving image quality. It can also be applied where C-arm or patient motion is present and conventional DSA cannot be applied. However, due to the lack of clinical training data and unavoidable artifacts in DSA targets, current DDSA models still cannot satisfactorily display specific structures, nor can they predict noise-free images.
Purpose: In this study, we propose a strategy for producing abundant synthetic DSA image pairs in which synthetic DSA targets are free of typical artifacts and noise commonly found in conventional DSA targets for DDSA model training.
Methods: More than 7,000 forward-projected CT images and more than 25,000 synthetic vascular projection images were employed to create contrast-enhanced fluoroscopic images and corresponding DSA images, which were utilized as DSA image pairs for training of the DDSA networks. The CT projection images and vascular projection images were generated from eight whole-body CT scans and 1,584 3D vascular skeletons, respectively. All vessel skeletons were generated with stochastic Lindenmayer systems. We trained DDSA models on this synthetic dataset and compared them to the trainings on a clinical DSA dataset, which contains nearly 4,000 fluoroscopic x-ray images obtained from different models of C-arms.
Results: We evaluated DDSA models on clinical fluoroscopic data of different anatomies, including the leg, abdomen, and heart. The results on leg data showed for different methods that training on synthetic data performed similarly and sometimes outperformed training on clinical data. The results on abdomen and cardiac data demonstrated that models trained on synthetic data were able to extract clearer DSA-like images than conventional DSA and models trained on clinical data. The models trained on synthetic data consistently outperformed their clinical data counterparts, achieving higher scores in the quantitative evaluation of PSNR and SSIM metrics for DDSA images, as well as accuracy, precision, and Dice scores for segmentation of the DDSA images.
Conclusions: We proposed an approach to train DDSA networks with synthetic DSA image pairs and extract DSA-like images from contrast-enhanced x-ray images directly. This is a potential tool to aid in diagnosis.Dataset containing the synthetic vascular projection images used in the paper. 98.2GB after extraction
Novel Signatures of Radiation Reaction in Electron-Laser Sidescattering
No full textIn this article we investigate novel signatures of radiation reaction via the angular deflection of an electron beam colliding at 90 degrees with an intense laser pulse. Due to the radiation reaction effect, the electrons can be deflected towards the beam axis for plane wave backgrounds, which is not possible in the absence of radiation reaction effects. The magnitude and size of the deflection angle can be controlled by tailoring the laser pulse shapes. The effect is first derived analytically using the Landau-Lifshitz equation, which allows to determine the important scaling behavior with laser intensity and particle energy. We then move on to full scale 3D Monte Carlo simulations to verify the effect is observable with present day laser technology. We investigate the opportunities for an indirect observation of laser depletion in such side scattering scenarios.
This record contains SMILEI namelists for the 1D and 3D simulations we have performed for this study. The open source particle-in-cell code SMILEI which we employed for our study can be found here: https://github.com/SmileiPIC/Smilei. Our simulations were performed on SMILEI v4.
Long-term monitoring of plant diversity data in the “Montagna di Torricchio” strict Nature Reserve, Italy
No full textLong-term monitoring is pivotal to fully understanding spatio-temporal changes in plant diversity, particularly in protected areas. Here we present a dataset including plant presence and abundance data collected using a probabilistic sampling design in the “Montagna di Torricchio” Nature strict Reserve, central Apennines, Italy. Five surveys were conducted in 35 plots during a period spanning 22 years (2002-2024). The dataset allows to study plant diversity changes over space and time across different habitat types by using statistical inference based on solid sampling theory
FastSurfer-HypVINN Segmentation Models for Sub-Segmentation of the Hypothalamus and Adjacent Sctructures
No full textThe hypothalamus plays a crucial role in the regulation of a broad range of physiological, behavioral, and cognitive functions. However, despite its importance, only a few small-scale neuroimaging studies have investigated its substructures, likely due to the lack of fully automated segmentation tools to address scalability and reproducibility issues of manual segmentation. While the only previous attempt to automatically sub-segment the hypothalamus with a neural network showed promise for 1.0 mm isotropic T1-weighted (T1w) magnetic resonance imaging (MRI), there is a need for an automated tool to sub-segment also high-resolutional (HiRes) MR scans, as they are becoming widely available, and include structural detail also from multi-modal MRI. We, therefore, introduce a novel, fast, and fully automated deep-learning method named HypVINN for sub-segmentation of the hypothalamus and adjacent structures on 0.8 mm isotropic T1w and T2w brain MR images that is robust to missing modalities. We extensively validate our model with respect to segmentation accuracy, generalizability, in-session test-retest reliability, and sensitivity to replicate hypothalamic volume effects (e.g., sex differences). The proposed method exhibits high segmentation performance both for standalone T1w images as well as for T1w/T2w image pairs. Even with the additional capability to accept flexible inputs, our model matches or exceeds the performance of state-of-the-art methods with fixed inputs. We, further, demonstrate the generalizability of our method in experiments with 1.0 mm MR scans from both the Rhineland Study and the UK Biobank—an independent dataset never encountered during training with different acquisition parameters and demographics. Finally, HypVINN can perform the segmentation in less than a minute (graphical processing unit [GPU]) and will be available in the open source FastSurfer neuroimaging software suite, offering a validated, efficient, and scalable solution for evaluating imaging-derived phenotypes of the hypothalamus.Training checkpoints for HypVINN (https://github.com/Deep-MI/FastSurfer) - please cite the paper when using this resource (https://doi.org/10.1162/imag_a_00034)