Find research datasets worth reusing

opencc-by-4.0Sep 2024View details →

Infrared thermography of turbulence patterns of operational wind turbine rotor blades supported with high-resolution photography: KI-VISIR Dataset

<h2>Abstract</h2> With increasing wind energy capacity and installation of wind turbines, new inspection techniques are being explored to examine wind turbine rotor blades, especially during operation. A common result of surface damage phenomena (such as leading-edge erosion) is the premature transition of laminar to turbulent flow on the surface of rotor blades. In the KI-VISIR (Künstliche Intelligenz Visuell und Infrarot Thermografie – Artificial Intelligence-Visual and Infrared Thermography) project, infrared thermography is used as an inspection tool to capture so-called thermal turbulence patterns (TTP) that result from such surface contamination or damage. To compliment the thermographic inspections, high-resolution photography is performed to visualise, in detail, the sites where these turbulence patterns initiate. A convolutional neural network (CNN) was developed and used to detect and localise the turbulence patterns. A unique dataset combining the thermograms and visual images of operational wind turbine rotor blades has been provided, along with the simplified annotations for the turbulence patterns. Additional tools are available to allow users to use the data requiring only basic Python programming skills.

opencc-by-4.0Jul 2024View details →

"Wissen schaffen (lassen!?)". Workflows mit Generativer KI in den Digital Humanities

Die rasante Entwicklung von generativen KI-Technologien stellt eine bedeutende Veränderung für die Forschungspraxis nicht nur in den Digital Humanities dar. Dieser Vortrag untersucht den Einsatz von GPT-4-Tier LLM (Gemini Advanced und Claude 3) sowie deren Möglichkeiten und Grenzen in verschiedenen Forschungsprojekten der Digital Humanities. Der Fokus liegt dabei auf Workflows wie der Datenerfassung, Transkription, Übersetzung, Datenmodellierung, Datengenerierung oder -analyse sowie der Visualisierung geisteswissenschaftlicher Daten. Anhand ausgewählter Fallstudien wird die Integration von generativer KI in diese Prozesse dargestellt, wobei sowohl die Automatisierung von Standardaufgaben als auch die Unterstützung komplexerer, analytischer und anspruchsvoller Tätigkeiten wie Datenmodellierung thematisiert werden. Haben generative KI-Modelle, wenn sie im Einklang mit menschlicher Expertise und komplementären Systemen eingesetzt werden, das Potenzial, die Effizienz und Tiefe (digitaler) geisteswissenschaftlicher Forschung zu steigern? Die Studie betont auch die Notwendigkeit, die Grenzen und Herausforderungen, wie die Abhängigkeit von großen Technologieunternehmen beim Einsatz von generativer KI in den Digital Humanities kritisch zu hinterfragen.

opencc-by-4.0Feb 2024View details →

Adenosine deficiency facilitates CA1 synaptic hyperexcitability in the presymptomatic phase of a mouse KI model of Alzheimer disease.

All data points, statistical models and raw western blot images from "Adenosine deficiency facilitates CA1 synaptic hyperexcitability in the presymptomatic phase of a mouse KI model of Alzheimer disease" are available.

opencc-by-nc-nd-4.0Jun 2018View details →

Peshawar, Pakistan. Mound of Shah ji ki Dheri, the so-called Kanishka reliquary.

Peshawar, Pakistan. Mound of Shah ji ki Dheri, the so-called Kanishka reliquary, historic photograph with associated desposits. <ul> </ul>

opencc-by-4.0Jul 2024View details →

LCA inventories for metal iodides: Cuprous iodide (CuI), Potassium iodide (KI), Bismuth iodide (BiI3), Silver iodide (AgI), Antimony Triiodide (SbI3).

This dataset contains Life Cycle Assessment (LCA) inventories for a selection of metal iodides, including Cuprous Iodide (CuI), Potassium Iodide (KI), Bismuth Iodide (BiI3), Silver Iodide (AgI), and Antimony Triiodide (SbI3). These are industrial scale inventories, providing comprehensive data on the production of each of these compounds.

opencc-by-4.0Sep 2022View details →

KI in der Prävention - Befragungsmethoden und Schulungen trainieren, Krankheitserreger erkennen

AbstractDer ITC Digitale Transformation der Arbeitswelt vernetzt Dozenten und wissenschaftliche Mitarbeiter aller Departemente durch interne und externe Projekte. Mit Fördergeldern können so interdisziplinäre Projekte bearbeitet werden, die oft in SNF oder Innosuisse Projekten weitergeführt werden können. Weitere Beiträge aus dem DHIK-Forum 2022 auf Zenodo:<ul><li>Session #1: Viktor Sigrist: Internationalisierung - Partnerschaften für den Ausbau von Forschung und Entwicklung (DOI:<a href="https://zenodo.org/record/7123701">10.5281/zenodo.7123701</a>)</li><li>Session #2: Dieter Leonhard: DHIK- Strategien der internationalen Zusammenarbeit in Forschung und Lehre (DOI:<a href="https://zenodo.org/record/7123456">10.5281/zenodo.7123456</a>)</li><li>Session #3: Stephen Wittkopf: Wissens- und Innovationstransfer - Interdisziplinäre Zusammenarbeit mit Unternehmen und Institutionen (DOI:<a href="https://zenodo.org/record/7025707">10.5281/zenodo.7025707</a>)</li><li>Session #4: Xiao Feng: CDHAW - Chinesisch-Deutsche Hochschule für Angewandte Wissenschaften (DOI:<a href="https://zenodo.org/record/7123458">10.5281/zenodo.7123458</a>)</li><li>Session #5: Antonio Pita und Isabel Kreiner: Academy-Industry-Collaboration - Outreach Strategy (DOI:<a href="https://zenodo.org/record/7123460">10.5281/zenodo.7123460</a>)</li><li>Session #6: Martin Sternberg: Promotionsrecht – aktueller Stand an deutschen Hochschulen für angewandte Wissenschaften (DOI:<a href="https://zenodo.org/record/7123757">10.5281/zenodo.7123757</a>)</li><li>Session #7: Adrian Derungs: Duo mit Innovationskraft - Zusammenspiel von Forschung und Wirtschaft in der Zentralschweiz (DOI:<a href="https://zenodo.org/record/7123767">10.5281/zenodo.7123767</a>)</li><li>Session #8: Theres Paulsen: Transdisziplinäre Forschung - komplexe gesellschaftliche Herausforderungen erfordern diverse Ansätze (DOI:<a href="https://zenodo.org/record/7123769">10.5281/zenodo.7123769</a>)</li><li>Session #9: Jörg Schneider: International research collaboration - New funding opportunities for universities of applied sciences (DOI:<a href="https://zenodo.org/record/7123771">10.5281/zenodo.7123771</a>)</li><li>Session #10: Cornelia Spycher und Matthew Whellens: Horizon Europe - overview of funding opportunities for your research and innovation (DOI:<a href="https://zenodo.org/record/7123773">10.5281/zenodo.7123773</a>)</li><li>Session #11: Janique Siffert: Eureka Eurostars - erfolgreiche Förderung für internationale Innovationsprojekte (DOI:<a href="https://zenodo.org/record/7123777">10.5281/zenodo.7123777</a>)</li><li>Session #12: Ludger Fischer: Energy Lab - ein Netzwerk für innovative Lösungen im Energiebereich (DOI:<a href="https://zenodo.org/record/7123779">10.5281/zenodo.7123779</a>)</li><li>Session #13: Jörg Worlitschek: Thermal energy storage - heating the north, cooling the south (DOI:<a href="https://zenodo.org/record/7123781">10.5281/zenodo.7123781</a>)</li><li>Session #14: Jonas Mühlethaler: Neues DC Microgrid-Konzept – netzunabhängige Elektrifizierung in Entwicklungsländern (DOI:<a href="https://zenodo.org/record/7123783">10.5281/zenodo.7123783</a>)</li><li>Session #15: Tommy Claussen: Dekarbonisierung des Gebäudesektors - digitale Transformation in der Gebäudetechnik und im Gebäudemanagement (DOI:<a href="https://zenodo.org/record/7123785">10.5281/zenodo.7123785</a>)</li><li>Session #16: Christoph Imboden: Flexibility solutions - making the power grid fit for the future (DOI:<a href="https://zenodo.org/record/7123787">10.5281/zenodo.7123787</a>)</li><li>Session #17: Uwe Schulz: Spielerisches Sarnetz - Simulationen für die fossile Unabhängigkeit einer Ortschaft (DOI:<a href="https://zenodo.org/record/7123790">10.5281/zenodo.7123790</a>)</li><li>Session #18: Jana Koehler: Künstliche Intelligenz – Erfolg durch Erwünschtheit, Machbarkeit und Wirtschaftlichkeit (DOI:<a href="https://zenodo.org/record/7123792">10.5281/zenodo.7123792</a>)</li><li>Session #19: Rolf Kamps: KI in der Prävention - Befragungsmethoden und Schulungen trainieren, Krankheitserreger erkennen (<a href="#collapseTwo">Video</a>)</li><li>Session #20: Gwendolyne Pascua: Artificial Intelligence in Space - CIMON assisting astronauts on the International Space Station (DOI:<a href="https://zenodo.org/record/7123796">10.5281/zenodo.7123796</a>)</li><li>Session #21: Tobias Matter et.al.: Augmented Reality Soundscapes - mit maschinellem Lernen Klangkulissen von zukünftigen Bauvorhaben generieren (DOI:<a href="https://zenodo.org/record/7123798">10.5281/zenodo.7123798</a>)</li><li>Session #22: Angela Nicoara: Internet of Things - transforming businesses, people's lives and driving growth in the coming years (DOI:<a href="https://zenodo.org/record/7123800">10.5281/zenodo.7123800</a>)</li><li>Session #23: Adrian Koller: Feldrobotik - unermüdliche und zunehmend intelligentere Hilfe in der Landwirtschaft (DOI:<a href="https://zenodo.org/record/7123802">10.5281/zenodo.7123802</a>)</li><li>Session #24: Widar von Arx et.al.: Realisierung der Verkehrswende - Einfluss der Preispolitik in der Mobilität (DOI:<a href="https://zenodo.org/record/7124000">10.5281/zenodo.7124000</a>)</li><li>Session #25: Andreas Liebrich: Tourismusdateninfrastruktur - Was die Schweiz von Europa lernen kann (DOI:<a href="https://zenodo.org/record/7123806">10.5281/zenodo.7123806</a>)</li><li>Session #26: Frank Pöhlau und Stefan May: Find life on Mars - Schülerprojekte zur mobilien Robotik (DOI:<a href="https://zenodo.org/record/7123808">10.5281/zenodo.7123808</a>)</li><li>Session #27: Jiayun Shen: Open Innovation - Innovationsmanagement bei der Schweizerischen Post (DOI:<a href="https://zenodo.org/record/7123810">10.5281/zenodo.7123810</a>)</li><li>Session #28: Tobias Specker: Interkulturelles Management – innovative Konzepte zum Ausbau der China-Kompetenzen an Hochschulen (DOI:<a href="https://zenodo.org/record/7123812">10.5281/zenodo.7123812</a>)</li><li>Session #29: Elena Algorri: Swimming robots - exploring the unterwater from the surface (DOI:<a href="https://zenodo.org/record/7123814">10.5281/zenodo.7123814</a>)</li><li>Session #30: Sergio Camacho: Robotics and Digital Systems Engineering at the Tec de Monterrey (DOI:<a href="https://zenodo.org/record/7123816">10.5281/zenodo.7123816</a>)</li><li>Session #31: Thomas Dorn: Industrie 4.0 - Forschungskooperationen mit der CDHAW und der Tongji Universität Shanghai (DOI:<a href="https://zenodo.org/record/7123818">10.5281/zenodo.7123818</a>)</li><li>Session #32: Walter Reichert et.al.: Kollaboration und Unterstützung - Mobile Robotik und Exoskelette in der flexiblen Produktion (DOI:<a href="https://zenodo.org/record/7123820">10.5281/zenodo.7123820</a>)</li><li>Session #33: Louis Palmer: Solar Butterfly - climate pioneer world tour supported by HSLU (DOI:<a href="https://zenodo.org/record/7123822">10.5281/zenodo.7123822</a>)</li></ul>

opencc-by-4.0Oct 2022View details →

Tabular data of fast-scanning voltammetry and physiology experiments in LRRK2 KI mice

The tabular data of fast-scanning cyclic voltammetry and physiology experiments from manuscript: "R1441C and G2019S LRRK2 knockin mice have distinct striatal molecular, physiological, and behavioral alterations." by Xenias et al.

opencc-by-4.0Oct 2022View details →

Tabular data of striatal motor learning experiments in LRRK2 KI mice

The tabular data of the behavioral experiments described in the manuscript titled "R1441C and G2019S LRRK2 knockin mice have distinct striatal molecular, physiological, and behavioral alterations."

opencc-by-sa-4.0Jul 2024View details →

Nutzung von KI bei der Unterrichtsvorbereitung - Wie prompten?

Der Vortrag "Nutzung von KI bei der Unterrichtsvorbereitung" ist Teil der Reihe "Serviceeinheiten rund um das Thema digitales Unterrichten" und adressiert wirtschaftliche Lehrkräfte. Der Vortrag beinhaltet neben einer Abgrenzung von informationsabfragenden Systemen und generativen KI-Systemen, Erläuterungen und praxisnahe Beispiele zum Prompting für die Unterrichtsvorbereitung an beruflichen Schulen.

opencc-by-4.0Sep 2004View details →

Genre-KI-04

The web genre corpus 2004 (Genre-KI-04) is designed for the evaluation of techniques for genre classification. It consists of 1239 web documents classified into 8 genres and basic meta data for each of the files. The corpus consists of the HTML documents grouped into directories according to their respective genre. The first lines of each document contain the meta information for each document in a HTML comment. This information includes the URL the document was downloaded from as well as the document title and the parsed text. A definition of the genres can be found in the paper (http://dx.doi.org/10.1007/978-3-540-30221-6_20) or in the corpus. The distribution of the documents among the genres is summarized below. <ul> <li>Articles: 127 (10.2%)</li> <li>Discussion: 127 (10.3%)</li> <li>Download: 152 (12.3%)</li> <li>Help: 140 (11.3%)</li> <li>Link lists: 208 (16.8%)</li> <li>Portrait (non private): 179 (14.4%)</li> <li>Portrait (private): 131 (10.6%)</li> <li>Shop: 175 (14.1%)</li> <li>Sum: 1239 (100%)</li> </ul>

opencc-by-4.0Jan 2023View details →

Ki-67 and Bcl-2 data by flow cytometry in non-malignant bone marrow aspirates and aspirates from patients with myeloid malignancies.

This Data in Brief article displays a flow cytometric assay that was used for the acquisition and analyses of proliferation and anti-apoptosis in hematopoietic cells. This dataset includes analysis of the Ki-67 positive fraction (Ki-67 proliferation index) and Bcl-2 positive fraction (Bcl-2 anti-apoptotic index) of the different myeloid bone marrow (BM) cell population in non-malignant BM, and the BM disorders myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML). The present dataset comprises 1) the percentage of the CD34 positive blast cells, erythroid cells, myeloid cells and monocytic cells, and 2) the determined Ki-67 positive fraction and Bcl-2 positive fraction of these cell populations in tabular form. This allows the comparison and reproduction of the data when these analyses are repeated in a different setting. As gating the Ki-67 positive and Bcl-2 positive cells is a critical step in this assay, different gating approaches were compared to determine the most sensitive and specific approach. BM cells from aspirates of 50 non-malignant, 25 MDS and 50 AML cases were stained with 7 different antibody panels and subjected to flow cytometry for determination of the Ki-67 positive cells and Bcl-2 positive cells of the different myeloid cell populations. The Ki-67 or Bcl-2 positive cells were then divided by the total number of cells of the respective cell population to generate the Ki-67 positive fraction (Ki-67 proliferation index) or the Bcl-2 positive fraction (Bcl-2 anti-apoptotic index). The presented data may facilitate the establishment and standardization of flow cytometric analyses of the Ki-67 proliferation index and Bcl-2 anti-apoptotic index of the different myeloid cell populations in non-malignant BM as well as MDS and AML patients in other laboratories. Directions for proper gating of the Ki-67 positive and Bcl-2 positive fraction are crucial for achieving standardization among different laboratories. In addition, the data and the presented assay allows application of Ki-67 and Bcl-2 in a research and clinical setting and this approach can serve as the basis for optimization of the gating strategy and subsequent investigation of other cell biological processes besides proliferation and anti-apoptosis. These data can also promote future research about the role of these parameters in diagnosis of myeloid malignancies, prognosis of myeloid malignancies and therapeutic resistance against anti-cancer therapies in these malignancies. As specific populations based on cell biological characteristics were identified, these data can be useful for evaluating gating algorithms in flow cytometry in general by confirming the outcome (e.g. MDS or AML diagnosis) with the respective proliferation and anti-apoptotic profile of these malignancies. The Ki-67 proliferation index and Bcl-2 anti-apoptotic index may potentially be used for classification of MDS and AML based on supervised machine learning algorithms, while unsupervised machine learning can be deployed at the level of single cells to potentially distinguish non-malignant from malignant cells to identify minimal residual disease. Therefore, the present dataset may be of interest for internist-hematologists, immunologists with affinity for hemato-oncology, clinical chemists with sub-specialization of hematology and researchers in the field of hemato-oncology.

opencc-by-4.0Feb 2023View details →

Ki-67 and Bcl-2 data by flow cytometry in non-malignant bone marrow aspirates and patients with myeloid malignancies

This Data in Brief article displays a flow cytometric assay that was used for the acquisition and analyses of proliferative and anti-apoptotic activity in hematopoietic cells. This dataset includes analyses of the Ki-67 positive fraction (Ki-67 proliferation index) and Bcl-2 positive fraction (Bcl-2 anti-apoptotic index) of the different myeloid bone marrow (BM) cell populations in non-malignant BM, and in BM disorders, i.e. myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML). The present dataset comprises 1) the percentage of the CD34 positive blast cells, erythroid cells, myeloid cells and monocytic cells, and 2) the determined Ki-67 positive fraction and Bcl-2 positive fraction of these cell populations in tabular form. This allows the comparison and reproduction of the data when these analyses are repeated in a different setting. Because gating the Ki-67 positive and Bcl-2 positive cells is a critical step in this assay, different gating approaches were compared to determine the most sensitive and specific approach. BM cells from aspirates of 50 non-malignant, 25 MDS and 27 AML cases were stained with 7 different antibody panels and subjected to flow cytometry for determination of the Ki-67 positive cells and Bcl-2 positive cells of the different myeloid cell populations. The Ki-67 or Bcl-2 positive cells were then divided by the total number of cells of the respective cell population to generate the Ki-67 positive fraction (Ki-67 proliferation index) or the Bcl-2 positive fraction (Bcl-2 anti-apoptotic index). The presented data may facilitate the establishment and standardization of flow cytometric analyses of the Ki-67 proliferation index and Bcl-2 anti-apoptotic index of the different myeloid cell populations in non-malignant BM as well as MDS and AML patients in other laboratories. Directions for proper gating of the Ki-67 positive and Bcl-2 positive fraction are crucial for achieving standardization among different laboratories. In addition, the data and the presented assay allows application of Ki-67 and Bcl-2 in a research and clinical setting and this approach can serve as the basis for optimization of the gating strategy and subsequent investigation of other cell biological processes besides proliferation and anti-apoptosis. These data can also promote future research into the role of these parameters in diagnosis of myeloid malignancies, prognosis of myeloid malignancies and therapeutic resistance against anti-cancer therapies in these malignancies. As specific populations were identified based on cell biological characteristics, these data can be useful for evaluating gating algorithms in flow cytometry in general by confirming the outcome (e.g. MDS or AML diagnosis) with the respective proliferation and anti-apoptotic profile of these malignancies. The Ki-67 proliferation index and Bcl-2 anti-apoptotic index may potentially be used for classification of MDS and AML based on supervised machine learning algorithms, while unsupervised machine learning can be deployed at the level of single cells to potentially distinguish non-malignant from malignant cells in the identification of minimal residual disease. Therefore, the present dataset may be of interest for internist-hematologists, immunologists with affinity for hemato-oncology, clinical chemists with sub-specialization of hematology and researchers in the field of hemato-oncology.

ClinicalTrials.gov36/100

Assess Efficacy & Safety of Selumetinib in Combination With Docetaxel in Patients Receiving 2nd Line Treatment for v-Ki-ras2 Kirsten Rat Sarcoma Viral Oncogene Homolog (KRAS) Positive NSCLC

ClinicalTrials.gov study NCT01933932. IPD Sharing: YES. Countries: 26. Publications: 2.

controlledIPD-YESFeb 2026View details →

opencc-byJan 2022View details →

KI-HA 101

Source: Objaverse 1.0 / Sketchfab

opencc-bySep 2018View details →

Rajon ki Baoli stepwell, Delhi

The Rajon ki Baoli Stepwell is in Delhi near the Qutb Minar. Source: Objaverse 1.0 / Sketchfab

opencc-by-4.0Feb 2022View details →

Common molecular targets of a quinolone based bumped ki-nase inhibitor in Neospora caninum and Danio rerio

Supplementary files for paper submitted to IJMS

opencc-by-4.0Aug 2021View details →

KI Process Model Developed for SIAM Project

Process Model Diagram for KI Development Process improved with practices from SCRUM, XP, Design Thinking, and UX Methods by using the Method Engineering Tools Developed in the SIAM Project.  Updated with the source XMI file for Ki Process Specification (KiProcess.mprocesos) and the corresponding ecore metamodel (mprocesos.ecore)   *The names of the elements in the process are in Spanish.