727 research outputs found
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Azaacene Diradicals Based on Non-Kekulé Meta-Quinodimethane with Large Two-Photon Cross-Sections in the Infrared Spectral Region [data]
No full textNon-Kekulé quinoidal azaacences m-A (1a,b) were synthesized and compared to their para- and ortho-quinodimethane analogues. m-A display high diradical characters (1b: y0 = 0.88) due to their meta-quinodimethane (m-QDM) topology. Electron paramagnetic, nuclear magnetic resonance spectroscopies and supraquantum interference device measurements in combination with quantum-chemical calculations revealed singlet ground states for m-A with singlet-triplet gaps ΔEST (0.13-0.25 kcal mol-1) and thermally populated triplet states. These non-Kekulé structures are over all void of zwitterionic character and possess record high two-photon absorption cross sections over a broad spectral range in the nearinfrared
How To Recognize Clustering of Luminescent Defects in Single-Wall Carbon Nanotubes [data]
No full textThis repository contains the data of the publication
"How to Recognize Clustering of Luminescent Defects in Single-Wall Carbon Nanotubes" (Nanoscale Horiz., 2024, 9, 2286-2294, 10.1039/D4NH00383G
Integrating VGI contributions for gully mapping using Kalman filter and machine learning
No full textThe codes and datsets included are related to experiments and results conducted to integrate different lines digitized by volunteers using Kalman filter with changing
amount of input lines. Three approaches are included: i) Kalman filtering integration to investigate the role of basemaps and a number of contributions, ii) Kalman filtering coupled with a self-learning stratergy and, iii) a cross-training strategy
Manually labeled terrestrial laser scanning point clouds of individual trees for leaf-wood separation
No full textThis dataset contains 11 terrestrial laser scanning (TLS) tree point clouds (in .LAZ format v1.4) of 7 different species, which have been manually labeled into leaf and wood points. The labels are contained in the Classification field (0 = wood, 1 = leaf). The point clouds have additional attributes (Deviation, Reflectance, Amplitude, GpsTime, PointSourceId, NumberOfReturns, ReturnNumber). Before labeling, all point clouds were filtered by Deviation, discarding all points with a Deviation greater than 50.
An ASCII file with tree species and tree positions (in ETRS89 / UTM zone 32N; EPSG:25832) is provided, which can be used to normalize and center the point clouds.
This dataset is intended to be used for training and validation of algorithms for semantic segmentation (leaf-wood separation) of TLS tree point clouds, as done by Esmorís et al. 2023 (Related Publication).
The point clouds are a subset of a larger dataset, which is available on PANGAEA (Weiser et al. 2022b, see Related Dataset). More details on data acquisition and processing, file formats, and quality assessments can be found in the corresponding data description paper (Weiser et al. 2022a, see Related Material)
Ergänzungsmaterial zu: Investigations at the Epigravettian site of Barmaky in Volhynia, north-west Ukraine: analyses and taxonomic reflections
No full textKnown since 1981 and investigated in several campaigns between 1982 and 2007, the site of Barmaky in north-west Ukraine has recently been the subject of renewed investigations from 2018 to 2020. The assemblage is strikingly similar to the one reported from the famous site of Mizyn, located at a distance of about 490 km to the east, except for the absence of a mammoth bone structure. With a weighted average of radiocarbon dates of 19,004 ± 60 calBP, Barmaky is the so far oldest site in north-west Ukraine after the hiatus of the Last Glacial Maximum. The early chronological and – compared to other Epigravettian sites – rather remote spatial position of the site raise several questions, for instance regarding the taxonomic attribution or the role in the resettlement process of the mid-northern latitudes after the Last Glacial Maximum. In this paper, we address these questions in light of the current state of knowledge on the stratigraphy, spatial organisation, faunal assem-blage as well as lithic typology and technology. Due to the circumstances since 2020 (pandemic and war), not all analysis could be completed, and some results must still be considered preliminary
IKAT-DE
No full textA corpus consisting of high-quality human annotations of missing and implied information in argumentative texts (German version). The data is further annotated with semantic clause types and commonsense knowledge relations
Prediction of improvement in Personality Functioning. Utilisation of machine learning to filter relevant variables for prediction [dataset]
No full textIntroduction. Since its introduction in the DSM-5 and the ICD-11, the construct of personality functioning has received increased research interest. Recent studies have shown that psychotherapy contributes to an improvement in personality functioning. However, it remains unclear which factors predict an improvement.
Methods. We used machine learning to filter out those variables that are relevant or irrelevant for the prediction of the improvement of personality functioning from all variables collected at the beginning of a therapy. We examined a sample of 648 completed psychotherapies from the Heidelberg Institute for Psychotherapy.
Results. Overall, we found 4 groups of variables that were predictive of improvement in Personality Functioning: The patient's ability to enter relationships, his internalized relationship patterns, symptom severity, and how psychiatric the patient's disorder is. In addition, individual demographic factors and the patient's childhood memories proved to be predictive of the improvement in personality functioning. In contrast, the specific disorder pattern proved to be hardly predictive.
Discussion. Our results thus reflect the experience of many therapists that for therapy to be successful, the external reality and inner world of experience should be the focus of treatment rather than the specific disorder. At the same time, our study with its many results provides a basis for future research
R-Code zu: Sorg, M. (2022). Fibelausstattung und Lebensalter in der Merowingerzeit: Studien zu Abnutzung und Gebrauch frühmittelalterlicher Bügelfibeln
No full textCommented R Code used for the re-analysis of the data from Sorg 2022 with results deeply diverging from Sorg 2022
Thermolysis of Biphenylene toward Cyclo-ortho-phenylenes [data]
No full textThe solvent and catalyst free thermolysis of biphenylenes at 350 °C furnishes [n]cyclo-ortho-phenylenes ([n]COPs, n=4–10) in one step and in high yields. At 400 °C biphenylene dimerizes into tetraphenylene, but lower reaction temperatures produce cyclooligomers. If suitably substituted, the oligomers are soluble and can be isolated and characterized. The products are exclusively cyclic. In the crystalline state, [6]COP displays an alternating crown-shaped conformation
Cata-Annulated Azaacene Bisimides [data]
No full textUltra-electron-deficient azaacenes were synthesized via Buchwald-Hartwig coupling of ortho-diaminoarenes with chlorinated mellophanic diimide followed by oxidation of the intermediate N,N’-dihydro compounds with MnO2 or PbO2. The resulting cata-annulated bisimide azaacenes have ultrahigh electron affinities with first reduction potentials as low as −0.35 V recorded for a tetraazapentacene. Attempts to prepare a tetrakis(dicarboximide)tetraazaheptacene resulted in the formation of a symmetric butterfly dimer