cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.18712/nsd-nsd3129-v1
title: Financial inclusion: Measurement, Determinant and Effect

description: This study conducts a comparative analysis of the factors affecting financial inclusion in Kenya and Ethiopia at macro and micro levels. A generalized linear model is used to examine the determinants of and barriers to financial inclusion using the 2017 Global Findex Database, whereas a descriptive analysis is used to explore their macro-level differences. Kenya has a higher level of financial inclusion than Ethiopia. Differences in financial liberalization policy, gross domestic product, percentage of rural population, and mobile money service expansion are some macro-level differences that explain this variation. Differences in literacy rates and means of receiving payments such as government transfers explain some of the micro-level variations between the two countries. In addition, gender, age, employment status, and owning a mobile phone have significant and positive effects on financial inclusion. However, lack of documentation, lack of trust, and lack of money are significant barriers to financial inclusion.

The area where it was collected was in Sidama region, Ethiopia. The respondents were business owners who pay value added tax and turn over tax. And the abbreviations stand for HZ for Hawassa Zuria district, BO for Boricha district and LA for Loka Abaya. All these districts are located in the Sidama region.
DOI: 10.18712/nsd-nsd3153-v1
title: Financial inclusion: Measurement, Determinant and Effect

description: This study conducts a comparative analysis of the factors affecting financial inclusion in Kenya and Ethiopia at macro and micro levels. A generalized linear model is used to examine the determinants of and barriers to financial inclusion using the 2017 Global Findex Database, whereas a descriptive analysis is used to explore their macro-level differences. Kenya has a higher level of financial inclusion than Ethiopia. Differences in financial liberalization policy, gross domestic product, percentage of rural population, and mobile money service expansion are some macro-level differences that explain this variation. Differences in literacy rates and means of receiving payments, such as government transfers, explain some of the micro-level variations between the two countries. In addition, gender, age, employment status, and owning a mobile phone have significant and positive effects on financial inclusion. However, lack of documentation, lack of trust, and lack of money are significant barriers to financial inclusion.

The data was collected in the Sidama region, Ethiopia. The respondents were farm households. The abbreviations stand for HZ for Hawassa Zuria district, BO for Boricha district and LA for Loka Abaya. All these districts are located in the Sidama region.
DOI: 10.48677/b83ff9b9-a2d8-42b4-b6b2-ce9d73f25a73
title: Höhen-Grid Stichtag 07.02.2012

description: Das Produkt besteht aus den beiden Teilen Höhen-Grid und Korrekturwerte zum Höhen-Grid:
 a) Höhen-Grid
 Das Höhen-Grid ermöglicht die Transformation orthometrischer Höhen im EVRS (European Vertical Reference System) mit Bezug Amsterdam in Höhen des MGI mit Bezug Adria 1875 (Gebrauchshöhen H.ü.A.).
 b) Korrekturwerte zum Höhen-Grid
 Die Korrekturwerte zum Höhen-Grid dienen der Korrektur der in den Punktkarten der Lagefestpunkte enthaltenen Gebrauchshöhen, um Konformität mit den mittels GNSS-Messungen, Geoidundulationen und Höhen-GRID abgeleiteten Gebrauchshöhen zu erlangen.

Stichtag = Erstellungsdatum:
Die Daten sind zu diesem Tag der aktuellste Datenbestand des BEV.
Dies ist nicht ident mit dem Aufnahme- bzw. Vermessungsdatum.
DOI: 10.6073/pasta/3e7f6e5c9b8b326ae9d2cc0b36c5d60d
title: Population Dynamics of Pink Lady Slipper in Weston MA 2014-2017

description: The pink lady slipper (Cypripedium acaule) is an iconic understory plant of Massachusetts forests. It is easy to find and identify and is on the United States Forest Service list of white-tailed deer browse. Brian Donahue and members of the Weston Conservation Commission engaged a local garden club to start surveying trails for pink lady slippers. The project was designed to engage the community in a citizen science project that would bring community members into the discussion of conservation land management decisions. It also supports the long-term goal of linking white-tailed deer browse to lady slipper community dynamics.
DOI: 10.48677/9ae63b19-62f0-4f59-95cf-509c5bfadc33
title: Höhen-Grid plus Geoid Stichtag 08.11.2013

description: Das Höhen-Grid plus Geoid beschreibt die Höhenunterschiede zwischen ellipsoidischen GNSSHöhen im System ETRS89 / GRS80 und Gebrauchshöhen im Höhenreferenzsystem „MilitärGeographisches Institut (MGI)“ mit Bezug auf Triest / Adria 1875 (H. ü. A.). Die Höhenunterschiede werden im Raster von 15 x 22,5 Bogensekunden im Koordinatenreferenzsystem MGI in den Formaten CSV, GeoTIFF und BIL-Raster-Datei ausgegeben. Mit diesen Höhenunterschieden können ellipsoidische GNSS-Höhen in
Gebrauchshöhen transformiert werden, und zwar in das Niveau der Nivellementhöhen. 

Das Produkt besteht aus den beiden Teilen:
 (a) Höhen-Grid plus Geoid
 Das Höhen-Grid plus Geoid ermöglicht die Transformation ellipsoidischer Höhen im System ERTS89/GRS80 in Höhen des MGI mit Bezug Adria 1875 (Gebrauchshöhen H.ü.A.) in einem Schritt.
 
 (b) Korrekturwerte der Höhen der Lagefestpunkte zum Höhen-Grid
 Die Korrekturwerte kLFP zum Höhen-Grid dienen der Korrektur der in den Punktkarten der Lagefestpunkte enthaltenen Gebrauchshöhen, um Konformität mit den mittels GNSS-Messungen, Geoidundulationen und Höhen-Grid abgeleiteten Gebrauchshöhen zu erlangen.

Stichtag = Erstellungsdatum:
Die Daten sind zu diesem Tag der aktuellste Datenbestand des BEV.
Dies ist nicht ident mit dem Aufnahme- bzw. Vermessungsdatum.
DOI: 10.5281/zenodo.7143329
title: conjunto de dados

description: Dataset used in "Co-citation analysis between coupler authors of a scientific domain's citation identity: a case study in Scientometrics"



	
Image Files: Figures 1, 2, 3, 4, 5, 6, 7 (.TIFF)
	
Network Files (Pajek, VosViewer, .svg)
	
File used in "The Coupler - Shiny App" (.txt)
	
Scopus files
	
Excel File: article references, matrix coupling, betweenness (.xlsx)
DOI: 10.5281/zenodo.7143330
title: conjunto de dados

description: Dataset used in "Co-citation analysis between coupler authors of a scientific domain's citation identity: a case study in Scientometrics"



	
Image Files: Figures 1, 2, 3, 4, 5, 6, 7 (.TIFF)
	
Network Files (Pajek, VosViewer, .svg)
	
File used in "The Coupler - Shiny App" (.txt)
	
Scopus files
	
Excel File: article references, matrix coupling, betweenness (.xlsx)
DOI: 10.5281/zenodo.10139153
title: Virtual Tissues of DLBCL lymphomas

description: TissueResolver is a package for converting bulk RNA-seq datasets into virtual tissues using information from similar single cell datasets by assigning weights to true single cells, maintaining their molecular integrity. Virtual tissues can be analyzed in a similar way as conventional single cell datasets.
The algorithm is described in Simeth et al., 2023, Virtual Tissue Expression Analysis.
This dataset contains combined RNA expression single cell and bulk data of diffuse large B-cell lymphomas (DLBCL) and derived virtual tissues, along with computed cell-type specific gene expression values.
This is in- and output of data used in the documentation of tissueResolver.
RNA-seq bulks used for the computation of the virtual tissues: Schmitz et al., 2018 (article).
Single cell datasets:

Roider et al., 2020 (article) EGA accession number EGAS00001004335
Steen et al., 2021 (article), GEO accession numbers GSE182434 and GSE182436
Data was combined after feature selection and TMM normalization.
DOI: 10.5281/zenodo.10139154
title: Virtual Tissues of DLBCL lymphomas

description: TissueResolver is a package for converting bulk RNA-seq datasets into virtual tissues using information from similar single cell datasets by assigning weights to true single cells, maintaining their molecular integrity. Virtual tissues can be analyzed in a similar way as conventional single cell datasets.
The algorithm is described in Simeth et al., 2023, Virtual Tissue Expression Analysis.
This dataset contains combined RNA expression single cell and bulk data of diffuse large B-cell lymphomas (DLBCL) and derived virtual tissues, along with computed cell-type specific gene expression values.
This is in- and output of data used in the documentation of tissueResolver.
RNA-seq bulks used for the computation of the virtual tissues: Schmitz et al., 2018 (article).
Single cell datasets:

Roider et al., 2020 (article) EGA accession number EGAS00001004335
Steen et al., 2021 (article), GEO accession numbers GSE182434 and GSE182436
Data was combined after feature selection and TMM normalization.
DOI: 10.5281/zenodo.10568550
title: Virtual Tissues of DLBCL lymphomas

description: TissueResolver is a package for converting bulk RNA-seq datasets into virtual tissues using information from similar single cell datasets by assigning weights to true single cells, maintaining their molecular integrity. Virtual tissues can be analyzed in a similar way as conventional single cell datasets.
The algorithm is described in Simeth et al., 2023, Virtual Tissue Expression Analysis.
This dataset contains combined RNA expression single cell and bulk data of diffuse large B-cell lymphomas (DLBCL) and derived virtual tissues, along with computed cell-type specific gene expression values.
This is in- and output of data used in the documentation of tissueResolver.
RNA-seq bulks used for the computation of the virtual tissues: Schmitz et al., 2018 (article).
Single cell datasets:

Roider et al., 2020 (article) EGA accession number EGAS00001004335
Steen et al., 2021 (article), GEO accession numbers GSE182434 and GSE182436
Data was combined after feature selection and TMM normalization.
DOI: 10.21942/uva.25061858.v2
title: CW measurement for Drift Detection

description: Full CW long measurement
DOI: 10.48677/beef0b35-35ec-44a1-96c6-8c44d50e209f
title: Österreichische Schwerekarte Stichtag 30.10.2008

description: Der Schwerewert ist der Betrag der Schwerebeschleunigung bezogen auf einen in Lage und Höhe definierten Punkt. Diese Punkte sind zumeist Punkte des Höhen- oder Lagefestpunktfeldes. Bezugsrahmen für alle Schwerewerte in Österreich ist das Österreichische Schweregrundnetz (ÖSGN), das aus ca. 800 Punkten besteht. Das Niveau ist durch 42 Punkte 0. Ordnung festgelegt, die mit Absolutschweremessungen (Freifall-Gravimeter) bestimmt wurden. Die Schwerewerte der Ordnungen 1 bis 3 wurden aus vernetzten Messungen mit Relativgravimetern (Federgravimeter) abgeleitet.

Darüber hinaus existieren ca. 22.000 Nivellementpunkte mit Schwerewerten und weitere 42.000 flächenhaft verteilte Gravimeterpunkte. Unter Verwendung des digitalen Geländehöhenmodells wurden mittlere Schwerewerte entlang der Lotlinie, sowie Bouguer-Anomalien berechnet. Aus dem Bouguerschwerefeld können Oberflächenschwerewerte an beliebigen Punkten interpoliert werden.

Die Schwerewerte werden gemeinsam mit den Nivellementpunkten in der Nivellement-Schweredatenbank (NSDB) verwaltet. Die Datensätze enthalten Oberflächenschwerewert, Koordinaten und Höhe des Bezugspunktes, weiters die berechneten Werte für die mittlere Lotlinienschwere und die Bouguerschwere. Für ÖSGN-Punkte existieren Punktbeschreibungen mit Schwerewert und Geokodierung.

Die Österreichische Schwerekarte ermöglicht einen Überblick über das Schwerefeld in Österreich in Form von Bouguer-Anomalien und lässt Rückschlüsse auf den Krustenaufbau und die Dichteverteilung zu.

Auf Anfrage können Schwerewerte unter Angabe von Koordinaten und Höhe aus dem Bouguerschwerefeld berechnet bzw. gemessen werden.

Stichtag = Erstellungsdatum:
Die Daten sind zu diesem Tag der aktuellste Datenbestand des BEV.
Dies ist nicht ident mit dem Aufnahme- bzw. Vermessungsdatum.
DOI: 10.6084/m9.figshare.24053064
title: Dataset for "Thermal Stressing of Volcanic Rock: Microcracking and Crack Closure Monitored through Acoustic Emission, Ultrasonic Velocity, and Thermal Expansion."

description: This README describes the contents of the dataset, split into P-wave velocity data (travel times, velocities, and raw signal waveforms), thermal expansion measurements, and acoustic emission monitoring data.Wave velocity dataCalculated velocitiesIn the folder /Acoustic velocity.For each experiment and heating/cooling cycle, the wave velocities are given in excel spreadsheets (e.g. EB_p_wave_data_cycle_1.xlsx). The columns contain the following data:* time: the time at which the measurement was made* TEMP: the furnace temperature* vp_cross_correlation: The P-wave velocity calculated using the cross-correlation method.Raw waveform dataThe raw waveform data is also provided for each heating/cooling cycle (e.g. EB_waveforms_cycle_1.csv). The CSV contains the text version of an array with shape (4001, N), where N is the number of measurements during a heating/cooling cycle. The first row of the file contains the times at which the measurement was made. The remaining 4000 rows of a column are the measured voltage values recorded at a 2 MHz sampling frequency.Thermal expansion dataIn the folder /Thermal expansionFor each of the three samples, there is an excel spreadsheet containing the following columns (e.g., Elongation_EB.xlsx).The sample elongation is measured over three heating and cooling cycles and the columns contain the following data:* Temp [°C]: sample temperature in degrees Celsius* Time/min: time elapsed in minutes* dL/Lo: change in length relative to initial lengthAcoustic emission (AE) monitoring dataIn the folder /Acoustic emissionsFor each experiment and heating/cooling cycle, the time and characteristics of each AE hit are given in excel spreadsheets (e.g. EB_AE_cycle_1.xlsx). The columns contain the following data:TIME: The time of the AE hit from the start of the experiment in seconds.RISE: The rise time from an AE signal’s first threshold crossing to its peak.COUN: The number of counts, or number of times the AE signal crosses the AE threshold.ENER: A measure of energy released during the AE event, equal to the integral of the voltagesignal over the duration of the AE hitDURATION: AE Duration is defined as the time from the first threshold crossing to the end of the last.AMP: The AE Amplitude is the maximum voltage (negative or posotive) during an AE hit (in dB).A-FRQ: The average frequency, equal to COUN / DURATION.RMS: The root mean square of the recorded voltage signal.ABS-ENERGY: The absolute energy of the AE signal, calculated as integral of the squared voltage waveform divided by the reference resistance (10 kohm).TEMP: The temperature at the time of the AE hitCUMABS-ENERGY: The cumulative absolute energy.CUMHITS: The cumulative number of AE hits
DOI: 10.7910/dvn/ybodcc
title: The Mini-Standard Model of Particle Physics

description: The "Standard Model of Elementary Particle Physics" attempts to describe the properties of all elementary particles that exist in the universe. There are actually many more different particles than can be found in ordinary matter. Most of these particles are unstable. The majority of all elementary particles decay relatively quickly into the particles we know on a daily basis. The weak interaction causes all heavy particles to decay into lighter particles. For example, a neutron decays into a proton, an electron, and an antineutrino. Here, however, a question arises that if the neutron and its decay product particles do not exist simultaneously, how can the interaction between the neutron and the decay products cause the neutron to decay. The solution lies in the general field theory, which tells us that each type of particle corresponds to a field in space. Such a field exists everywhere and always. A field can exist even if the corresponding particles do not exist yet. In this case, the field energy is minimal. The energy of the field increases "gradually", as particles, or quanta of the corresponding field, appear in the field. Any reaction can be understood as a transfer of energy from one field to another. In the following, we mainly describe the masses of protons, neutrons, electrons, quarks and their intermediate particles - gluons and photons. These particles are mostly stable in nature and also the most common elements in the universe. Therefore, it can be said that it is a "mini-standard model", i.e. a "smaller version" of the standard model of elementary particle physics, which describes only the most common and permanent particles in the entire universe. Protons, neutrons and electrons are the basic building blocks of all matter in the universe, as the atoms and molecules formed from them form the basis of any material structure in the universe. It can also be said that the "mini-standard model" is in turn the basis for this "large standard model" or "standard model of elementary particle physics".
DOI: 10.48677/cbffbfbf-d88d-4a25-9a13-30556a267651
title: Transformationsparameter - Global

description: Neben Koordinaten im System der Österreichischen Landesvermessung (Gebrauchssystem des Militärgeographischen Institutes = MGI) werden in zunehmendem Maße auch Koordinaten in dem auf GPS basierenden globalen System ETRS89 benötigt.
 
Ein Parametersatz, bestehend aus 7 Parametern (3 Verschiebungen, 3 Drehungen, 1 Maßstab) ermöglicht die Koordinatentransformation zwischen den Bezugssystemen MGI und ETRS89 in beiden Richtungen.
DOI: 10.13120/j23k-n088
title: Water column features, nutrients, Potential Toxic Elements (PTE) faecal indicator bacteria and antibiotic-resistance genes in Adriatic coastal waters and treated wastewater. AdSWiM project, 2019-2020

description: Time series of water column features, nutrients, Potential Toxic Elements (PTE) faecal indicator bacteria and antibiotic-resistance genes in Adriatic coastal waters and treated wastewater generated in the framework of the Interreg Italy-Croatia project AdSWiM (Managed use of treated urban wastewater for the quality of the Adriatic Sea). Related publication: https://doi.org/10.3390/w13233335.
DOI: 10.25500/edata.bham.00001050
title: Research data supporting "Low-cost source apportionment of indoor particulate matter in an educational institution"

description: Collection with an Alphasense OPC-N3
DOI: 10.6084/m9.figshare.20502050.v1
title: The effect of nigella supplementation on blood pressure: A systematic review and dose-response meta-analysis

description: This study was performed to assess the effect of nigella supplementation on blood pressure levels among the adult population. A comprehensive search was carried out through PubMed, Scopus, Web of Science, and Cochrane Library by using relevant keywords to find out the randomized clinical trials evaluating the effect of nigella administration on systolic blood pressure (SBP) and diastolic blood pressure (DBP). A random-effect model was applied to achieve the overall effect size. Subgroup analysis and meta-regression were used to explore the source of heterogeneity and the effects of the possible moderators. Of the twenty-two trials that were eligible for the present study, seventeen studies consisting of 1048 participants were included in the meta-analysis. The results indicated that nigella administration could significantly reduce both SBP (−4.58 mmHg; 95%CI: −6.22, −2.94) and DBP (−3.08 mmHg; 95%CI: −4.62, −1.55). Subgroup analysis did not show any superiority between subgroups of variables. Dose-response analysis detected a nonlinear association between dose and duration of administration and change in blood pressure outcomes, highlighting that maximum SBP and DBP reduction was experienced at 2000 mg/day and 8 weeks of nigella administration, respectively. The present study suggests that nigella supplementation can be beneficial for managing blood pressure.
DOI: 10.6084/m9.figshare.24786940
title: Adverse clinical outcomes associated with drug-related hospitalizations in people with dementia

description: This study aimed to determine the clinical impact associated with adverse drug reactions (ADRs) in patients with dementia. This case-control, propensity score-matched study utilized administrative data of people with dementia admitted to major public hospitals in Tasmania, Australia, from July 2010 to December 2019. Acute renal failure constituted the most common ADR. The length of hospital stay was greater for people with an ADR index admission, versus non-ADR index admission (median [IQR]: 9 [4–18] versus 6 [2–12]; <i>p</i> &lt; 0.001). In-hospital mortality and combined in-hospital and post-hospital mortality within 30, 60 and 90 days were higher for those whose index admission was ADR-related (in-hospital: HR 1.40, 95% CI 1.11–1.77, p-value &lt;0.001; 30 days: HR 1.25, 95% CI 1.05–1.49, p-value &lt;0.001; 60 days: HR 1.27, 95% CI 1.08–1.49, p-value &lt;0.001; 90 days: HR 1.29, 95% CI 1.10–1.50, p-value &lt;0.001). Subsequent ADR admission within 30, 60 and 90 days of index discharge was 9 to 10 times greater for people with dementia (30 days: OR 10.0, 95% CI 6.04–16.8, p-value &lt;0.001; 60 days: OR 8.96, 95% CI 5.57–14.4, p-value &lt;0.001; 90 days: OR 9.31, 95% CI 5.79–14.9, p-value &lt;0.001). Safe prescribing and vigilant monitoring of ADRs is pivotal to mitigate adverse outcomes in people with dementia.
DOI: 10.6084/m9.figshare.24786940.v1
title: Adverse clinical outcomes associated with drug-related hospitalizations in people with dementia

description: This study aimed to determine the clinical impact associated with adverse drug reactions (ADRs) in patients with dementia. This case-control, propensity score-matched study utilized administrative data of people with dementia admitted to major public hospitals in Tasmania, Australia, from July 2010 to December 2019. Acute renal failure constituted the most common ADR. The length of hospital stay was greater for people with an ADR index admission, versus non-ADR index admission (median [IQR]: 9 [4–18] versus 6 [2–12]; <i>p</i> &lt; 0.001). In-hospital mortality and combined in-hospital and post-hospital mortality within 30, 60 and 90 days were higher for those whose index admission was ADR-related (in-hospital: HR 1.40, 95% CI 1.11–1.77, p-value &lt;0.001; 30 days: HR 1.25, 95% CI 1.05–1.49, p-value &lt;0.001; 60 days: HR 1.27, 95% CI 1.08–1.49, p-value &lt;0.001; 90 days: HR 1.29, 95% CI 1.10–1.50, p-value &lt;0.001). Subsequent ADR admission within 30, 60 and 90 days of index discharge was 9 to 10 times greater for people with dementia (30 days: OR 10.0, 95% CI 6.04–16.8, p-value &lt;0.001; 60 days: OR 8.96, 95% CI 5.57–14.4, p-value &lt;0.001; 90 days: OR 9.31, 95% CI 5.79–14.9, p-value &lt;0.001). Safe prescribing and vigilant monitoring of ADRs is pivotal to mitigate adverse outcomes in people with dementia.
DOI: 10.6084/m9.figshare.24786729
title: The association between ACE inhibitors and psoriasis based on the drug-targeted Mendelian randomization and real-world pharmacovigilance analyses

description: Although a growing number of observational studies suggest that angiotensin-converting enzyme inhibitors (ACEIs) intake may be a risk factor for psoriasis, evidence is still insufficient to draw definitive conclusions. Drug-targeted Mendelian randomization (DTMR) was used to analyze the causality between genetic proxied ACEIs and psoriasis. Furthermore, we performed a disproportionality analysis based on the FDA adverse event reporting system (FAERS) database to identify more suspicious subclasses of ACEIs. Using two kinds of genetic proxy instruments, the present DTMR research identified genetic proxied ACEIs as risk factors for psoriasis. Furthermore, our disproportionality analysis revealed that ramipril, trandolapril, perindopril, lisinopril, and enalapril were associated with the risk of psoriasis, which validates and refines the findings of the DTMR. Our integrative study verified that ACEIs, especially ramipril, trandolapril, perindopril, lisinopril, and enalapril, tended to increase the risk of psoriasis statistically.