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Vīraratnaśekharaśikhā by Sāhibrām
No full textChapters 1-13, 16-17, 22, 33, 38-39, and parts of chapter 40 of this text were critically edited in a DFG-funded project at Marburg University between 2016 and 2024. This file provides the collated text for those chapters as well as diplomatic transcripts of the main text (mūla) for the remaining chapters, based predominantly on the most complete manuscript. Variant readings are included where available. For a detailed description of the manuscripts used in the edition, a historical introduction to the text, an analysis of the translation method and techniques employed by the author and numerous philological comments and appendices please refer to the published edition and translation: https://doi.org/10.11588/hasp.1630 and https://doi.org/10.11588/hasp.163
Digital Appendix: Glyco-STORM: lectins as a new labeling tool to decipher the nanoarchitecture of cells
No full textThis is the digital appendix to the dissertation with the title "Glyco-STORM: lectins as a new labeling tool to decipher the nanoarchitecture of cells" by Helene Schröter. In this study, previous obstacles in studying the glycome were overcome by combining fluorophore-conjugated lectins – carbohydrate-binding proteins – with super-resolution microscopy. This approach was termed Glyco-STORM and led to the establishment of new anatomical markers to analyse the architecture of cell organelles and synaptic specializations on the nanoscale. Since lectins reflect the carbohydrate-specific morphology of the underlying structures, the results enable a new – ‘glyco-centric’ – picture of cell machineries, achieving a new level in understanding the function of biological systems. Cracking the ‘sugar code’ by using lectins as labels in a biological context could bring a breakthrough in understanding health and disease of organisms
Source code and data for the PhD Thesis "Linguistically-Inspired Neural Coherence Modeling"
No full textThis dataset contains source code and data used in the PhD thesis "Linguistically-Inspired Neural Coherence Modeling". The dataset is split into five repositories:
StruSim: Source code to run experiments for Chapter 4 "Document Structure Similarity-Enhanced Coherence Modeling".
ConnRel: Source code to run experiments for Chapter 5 "Annotation-inspired Implicit Discourse Relation Classification".
Exp2Imp: Source code to run experiments for Chapter 6 "Explicit to Implicit Discourse Relation Classification".
RelCoh: Source code to run experiments for Chapter 7 "Discourse Relation-Enhanced Coherence Modeling".
EntyRelCoh: Source code to run experiments for Chapter 8 "Coherence Modeling Using Entities and Discourse Relations".
The data used in the experiments can be downloaded from Linguistic Data Consortium (https://www.ldc.upenn.edu/):
PDTB 2.0: https://catalog.ldc.upenn.edu/LDC2008T05
PDTB 3.0: https://catalog.ldc.upenn.edu/LDC2019T05
TOEFL Dataset: https://catalog.ldc.upenn.edu/LDC2014T06
GCDC: https://github.com/aylai/GCDC-corpus
CoheSentia: https://github.com/AviyaMn/CoheSentia
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DeformedTissue Dataset
No full textTissue deformation is a critical issue in soft-tissue surgery, particularly during tumor resection, as it causes landmark displacement, complicating tissue orientation. The authors conducted an experimental study on 45 pig head cadavers to simulate tissue deformation, approved by the Mannheim Veterinary Office (DE 08 222 1019 21).
We used 3D cameras and head-mounted displays to capture tissue shapes before and after controlled deformation induced by heating. The data were processed using software such as Meshroom, MeshLab, and Blender to create and evaluate 2½D meshes.
The dataset includes different levels of deformation, noise, and outliers, generated using the same approach as the SynBench dataset.
1. Deformation_Level:
10 different deformation levels are considered. 0.1 and 0.7 are representing minimum and maximum deformation, respectively. Source and target files are available in each folder. The deformation process is just applied to target files. For simplicity, the corresponding source files to the target ones are available in this folder with the same name, but source ones start with Source_ and the target files start with Target_. The number after Source_ and Target_ represents the primitive object in the “Data” folder. For example, Target_3 represents that this file is generated from object number 3 in the “Data” folder. The two other numbers in the file name represent the percentage number of control points and the width of the Gaussian radial basis function, respectively.
2. Noisy_Data
For all available files in the “Deformation_Level” folder (for all deformation levels), Noisy data is generated. They are generated in 4 different noise levels namely, 0.01, 0.02, 0.03, and 0.04 (More explanation about implementation can be found in the paper).
The name of the files is the same as the files in the “Deformation_Level” folder.
3. Outlier_Data
For all available files in the “Deformation_Level” folder (for all deformation levels), data with outliers is generated. They are generated in different outlier levels, in 5 categories, namely, 5%, 15%, 25%, 35%, and 45% (More explanation about implementation can be found in the paper).
The name of the files is the same as the files in the “Deformation_Level” folder. Furthermore, for each file, there is one additional file with the same name but is started with “Outlier_”. This represents a matrix with the coordinates of outliers. Then, it would be possible to use these files as benchmarks to check the validity of future algorithms.
Additional notes:
Considering the fact that all challenges are generated under small to large deformation levels, the DeformedTissue dataset makes it possible for users to select their desired data based on the ability of their proposed method, to show how robust to complex challenges their methods are
Benzobischalcogeno[3,2-c]quinolines: Tuning Electronic and Structural Properties with Group 16 Elements [data]
No full textChalcogen-substituted π-extended indolocarbazoles were synthesized through a nucleophilic cyclization of tethered diynes with sulfur, selenium or tellurium sources, followed by a Pictet–Spengler reaction. These combined synthetic strategies enabled the facile access to heptacyclic π-extended molecules, offering a broad modularity at various stages of the synthesis route. In total, twenty-six novel heptacyclic compounds were synthesized. Their photophysical and structural properties were investigated experimentally as well as theoretically
elAPI
No full textelAPI is a powerful, extensible API client for eLabFTW developed at the University Computing Centre (URZ, FIRE division) of University of Heidelberg. It supports serving all kinds of requests documented in eLabFTW API documentation with ease. elAPI provides a simple interface via its CLI executable, and numerous advanced APIs when it is used directly as a Python package.
elAPI v2.3.
Microenvironmental Confinement Drives Density-Dependent Neuron-Like Cell Proliferation and Contact-Dependent Neurite Outgrowth [data]
No full textThis dataset accompanies the manuscript entitled "Microenvironmental Confinement Drives Density-Dependent Neuron-Like Cell Proliferation and Contact-Dependent Neurite Outgrowth," and contains microscopy images (*.tiff) and associated raw tracing data (*.csv, \*.swc, *.traces) collected using Fiji's Simple Neurite Tracer plugin. Data was generated from PC12 cells cultured within 3D-printed confinement structures, acquired using an Olympus IX-81 inverted microscope. Python scripts (*.py) are provided to replicate analyses such as data filtering, statistical testing, and figure generation described in the manuscript. The dataset is structured by experiment IDs and days in vitro (DIV), facilitating detailed examination of neuron-like cell proliferation and neurite growth patterns under varied confinement conditions
Temporal aggregation of point clouds improves permanent laser scanning of landslides in forested areas [Source Code]
No full textAbstract: Permanent laser scanning has recently developed as a technology to monitor landslides by repeatedly acquiring point clouds at short intervals (e.g., sub-hourly). In such areas, forests can hinder the capture of ground points and reduce the quantity and thus the spatial coverage of direct surface change information. The objective of this study is to evaluate the effectiveness of aggregating sequential point clouds for improved point cloud analysis. A forested landslide that primarily consists of Pinus cembra and Picea abies is investigated using permanent laser scanning data comprising 600 scans with an acquisition frequency of three hours. With our application of tree trunk tracking, we demonstrate how temporal aggregation improves tree trunk representation, thereby enabling quantification of landslide displacement. Corresponding trunks are matched and tracked throughout the full time series to compute the 3D displacements of the trunks. The effects of temporal aggregation are analysed by applying it to a digital replica of the study site, which is generated by virtual laser scanning. This targeted temporal aggregation approach increased the number of detectable trunks in forested areas by a factor of 5-6. Similarly, the number of trunk matches across the time series increased by a factor of 5. Performance gains plateaued after three aggregated scans. By using a permanently installed terrestrial laser scanner that repeatedly scans through the canopy, our method allows direct quantification of 3D landslide displacements in densely forested terrain. Our findings demonstrate that temporal aggregation of point clouds significantly increases the applicability and performance of continuous, long-range laser scanning-based monitoring of forested environments
Phonologischer Erwerb des Galicischen als Zweitsprache: Eine qualitative Analyse phonologischer Fehler bei nicht-muttersprachlichen Sprechern
No full textDieses Datenpaket enthält Audio- und Begleitdaten aus dem Masterarbeitsprojekt „Der phonologische Erwerb des Galicischen als Zweitsprache: Eine qualitative Analyse phonologischer Fehler bei nicht-nativen Sprechern“.
Untersucht wurden Interferenzmuster bei galicischen L2-Lernenden mit verschiedenen Erstsprachen. Die Daten wurden im Rahmen strukturierter Sprechaufgaben (Wort-/Satzlesung, Spontansprache, Repetition) erhoben.
Alle Audiodaten sind pseudonymisiert. Eine wissenschaftliche Nachnutzung ist unter CC BY-NC 4.0 Lizenz möglich
Chirality of malaria parasites determines their motion patterns [data]
No full textThis is a data repository for the publication "Chirality of malaria parasites determines their motion patterns". It includes example data for the different experimental setups, which can be used to run the analysis code. The code is available in the git repository github.com/LeonLettermann/hei-sporo-code and therein linked repositories.
We present data for three different experiments here:
3D microscopy of sporozoites moving through hydrogels
Two-sided traction force of circling sporozoites
STED super-resolution microscopy of sporozoites underneath a hydrogel
For experiments 1 and 2, the data are presented as .mvd2 microscopy raw data, which can be opened and analyzed with the provided Python code. For experiment 3, we present a deconvoluted image as a .tif file. Additionally, different intermediate analysis results supporting experimentation with the provided code are available as .npy files.</p