cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/h8wk4pjhkb.1
title: LINF_350031300

description: hypothetical protein - conserved
Leishmania infantum (strain JPCM5)
DOI: 10.17632/ztbb9b6jxj.1
title: Effects of stalked barnacle extraction on a rocky shore intertidal community: Species coverage data

description: Species coverage data were collected in an experiment conducted between 2017 and 2019 in Asturias, North Spain, at the south shore of Biscay Bay in three locations: La Cruz (43°33N, 7°01W), Las Salsinas (43°35N, 6°14W), and Las Llanas (43°33N, 6°06W). The experiment was performed on 35 x 35 cm square plots, situated approximately in the middle of the vertical distribution of Pollicipes pollicipes populations. Half of the plots were covered with cages to prevent and control exploitation, while the other half were left uncovered to allow exploitation by harvesters. The same experimental setting was used in two different years, with distinct durations. The first setting began in July 2017 and ended in July 2019 (2-year treatment duration). The second setting started in July 2018 and ended in July 2019 (1-year treatment duration). The plots were photographed at the beginning of the experiment and every 3 months thereafter, to document changes over time. Experimental harvests were photographically documented in each plot before and after the extraction. Organisms were identified to the lowest taxonomic level possible using image analysis. All species present were recorded, and their percentage cover was quantified using the point intercept method with a 100-point grid overlaid on the picture of each plot. Species present but without detectable cover were assigned an arbitrary 0.1% cover. The net coverage change (%) of P. pollicipes was calculated as 100*(final coverage - initial coverage)/initial coverage, and the extraction intensity was estimated by calculating the cumulated removal throughout the entire experiment, detected with the image analysis.

The data includes the following variables: Site (Cruz, Salsinas, Llanas); Cage (Yes, No); Scientific extraction (Yes, No); Replicate (1, 2, 3); Experiment duration (1 year, 2 years); Year (2017, 2018, 2019); Month (July, October, December, April); Before/After (B = Before harvest, A = After harvest); Species coverage data in percentage.

Changes in the community structure were analyzed using analysis of variance for univariate data and non-parametric PERMANOVA for multivariate, community data. To determine the species responsible for the differences among treatments, SIMPER was used, and the Shannon-Wiener index was applied to measure ecological diversity.
DOI: 10.17632/6t3yx49wbs.3
title: Data extraction table for "Health effects of drinking 100% fruit and/or vegetable juice: An umbrella review of systematic reviews and meta-analyses"

description: The full data extraction table for "Health effects of drinking 100% fruit and/or vegetable juice: An umbrella review of systematic reviews and meta-analyses" - registered as "What are the effects of 100% fruit and/or vegetable juice consumption, as compared to placebo or low intakes, on human health outcomes relevant to population health?" PROSPERO 2022 CRD42022380588 Available from: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022380588 

We conducted an umbrella review of systematic literature reviews (SLRs) with meta-analyses (MAs) to summarise the health benefits of drinking 100% fruit and/or vegetable juice. Four electronic databases will be searched from inception with no date limits: MEDLINE (via PubMed), The Cochrane Library (Reviews and CENTRAL), EMBASE, and CINAHL (via EBSCO). The systematic search strategy was designed to include a combination of both controlled vocabulary (MeSH terms and publication type) and keywords (by title and abstract). The keywords repeated the controlled vocabulary terms plus keywords specific to the topic. The search strategy was designed in PubMed and then translated to the other databases. Types of study to be included Systematic literature reviews with meta-analysis.Exclusions: Systematic literature reviews with no meta-analysis, cross-sectional studies, single arm interventions, narrative reviews, expert opinion articles, or consensus guidelines.

Screening, quality, risk of bias and content overlap tools were applied, and extracted data are tabulated (tab 1), GRADE applied (tab 2) and ROBIS applied (tab 3). 

Data represent almost 2 million subject data points. Of the primary MAs 10 MAs reported health benefits (blood pressure, vascular function, inflammation, stroke mortality), three MAs reported adverse risks (CVD mortality, prostate cancer, type 2 diabetes risk), while most reported no effect (blood lipids, body composition, liver function, metabolic health, cancers, and inflammation). 

Findings confirm there are health benefits associated with 100% juice consumption, with limited harms identified at this level of evidence. The balance of evidence continues to support the inclusion of 100% juice as a core food in dietary guidelines.
DOI: 10.17632/9yvrzxktmr.5
title: MASAQ: Morphologically-Analyzed and Syntactically-Annotated Quran Dataset

description: The Morphologically-Analyzed and Syntactically-Annotated Quran (MASAQ) dataset is a high-quality, annotated resource designed to advance Arabic Natural Language Processing (NLP). Covering the entire Quran, MASAQ includes over 131K morphological and 123K syntactic entries, verified by expert linguists using traditional i'rab methodologies. Available in multiple formats, it supports a range of applications—from teaching Arabic grammar to enhancing NLP tools like parsers and taggers. By enabling precise language analysis, MASAQ fosters advancements in Arabic NLP and cross-linguistic research, licensed under Creative Commons for ethical use.
DOI: 10.17632/9yvrzxktmr.6
title: MASAQ: Morphologically-Analyzed and Syntactically-Annotated Quran Dataset

description: The Morphologically-Analyzed and Syntactically-Annotated Quran (MASAQ) dataset is a high-quality, annotated resource designed to advance Arabic Natural Language Processing (NLP). Covering the entire Quran, MASAQ includes over 131K morphological and 123K syntactic entries, verified by expert linguists using traditional i'rab methodologies. Available in multiple formats, it supports a range of applications—from teaching Arabic grammar to enhancing NLP tools like parsers and taggers. By enabling precise language analysis, MASAQ fosters advancements in Arabic NLP and cross-linguistic research, licensed under Creative Commons for ethical use.
DOI: 10.17632/9yvrzxktmr.1
title: Morphologically-Analyzed and Syntactically-Annotated Quran Dataset (MASAQ)

description: The Morphologically-Analyzed and Syntactically-Annotated Quran (MASAQ) dataset is a comprehensive resource designed to address the scarcity of annotated Quranic Arabic corpora and facilitate the development of advanced Natural Language Processing (NLP) models. MASAQ provides a detailed syntactic and morphological annotation of the entire Quranic text, utilizing a rigorously verified text from Tanzil.net. The dataset includes more than 131K morphological entries and 123K instances of syntactic functions, covering a wide range of grammatical roles and relationships. The annotation process involved a team of expert Arabic linguists who employed traditional i'rab methodologies to ensure high accuracy and consistency. The dataset is structured in multiple formats (txt, CSV, xlsx, XML, JSON) to cater to various research needs. The potential applications of MASAQ are vast, ranging from pedagogical uses in teaching Arabic grammar to developing sophisticated NLP tools. By providing a high-quality, syntactically annotated dataset, MASAQ aims to advance the field of Arabic NLP, enabling more accurate and more efficient language processing tools. The dataset is made available under the Creative Commons Attribution 3.0 License, ensuring compliance with ethical guidelines and respecting the integrity of the Quranic text.
The Morphologically-Annotated and Syntactically-Annotated Quran (MASAQ) dataset presents significant potential applications across domains. Pedagogically, it can simplify the teaching of Arabic grammar by focusing on fundamental concepts. In NLP, MASAQ can enhance tools like part-of-speech taggers and parsers, which are essential for automated language understanding. Linguistically, the dataset provides valuable syntactic analysis for linguistic research. Additionally, dependency parsers derived from MASAQ can efficiently analyze web content, resolve several types of sentence ambiguities, and contribute to semantic representations. The dataset also supports efforts like Universal Dependencies, facilitating cross-linguistic research and multilingual NLP tool development. Furthermore, integrating dependency parsing with machine learning classifiers can improve parsing accuracy and efficiency, particularly useful for languages with free word order, like Written Arabic. Overall, MASAQ offers a comprehensive resource for advancing both academic and practical applications in Arabic NLP.
DOI: 10.17632/9yvrzxktmr.2
title: MASAQ: Morphologically and Syntactically-Annotated Quran Dataset

description: The Morphologically-Analyzed and Syntactically-Annotated Quran (MASAQ) dataset is a comprehensive resource designed to address the scarcity of annotated Quranic Arabic corpora and facilitate the development of advanced Natural Language Processing (NLP) models. MASAQ provides a detailed syntactic and morphological annotation of the entire Quranic text, utilizing a rigorously verified text from Tanzil.net. The dataset includes more than 131K morphological entries and 123K instances of syntactic functions, covering a wide range of grammatical roles and relationships. The annotation process involved a team of expert Arabic linguists who employed traditional i'rab methodologies to ensure high accuracy and consistency. The dataset is structured in multiple formats (txt, CSV, xlsx, XML, JSON) to cater to various research needs. The potential applications of MASAQ are vast, ranging from pedagogical uses in teaching Arabic grammar to developing sophisticated NLP tools. By providing a high-quality, syntactically annotated dataset, MASAQ aims to advance the field of Arabic NLP, enabling more accurate and more efficient language processing tools. The dataset is made available under the Creative Commons Attribution 3.0 License, ensuring compliance with ethical guidelines and respecting the integrity of the Quranic text.
The Morphologically-Annotated and Syntactically-Annotated Quran (MASAQ) dataset presents significant potential applications across domains. Pedagogically, it can simplify the teaching of Arabic grammar by focusing on fundamental concepts. In NLP, MASAQ can enhance tools like part-of-speech taggers and parsers, which are essential for automated language understanding. Linguistically, the dataset provides valuable syntactic analysis for linguistic research. Additionally, dependency parsers derived from MASAQ can efficiently analyze web content, resolve several types of sentence ambiguities, and contribute to semantic representations. The dataset also supports efforts like Universal Dependencies, facilitating cross-linguistic research and multilingual NLP tool development. Furthermore, integrating dependency parsing with machine learning classifiers can improve parsing accuracy and efficiency, particularly useful for languages with free word order, like Written Arabic. Overall, MASAQ offers a comprehensive resource for advancing both academic and practical applications in Arabic NLP.
DOI: 10.17632/9yvrzxktmr.3
title: MASAQ: Morphologically and Syntactically Annotated Quran Dataset

description: The Morphologically-Analyzed and Syntactically-Annotated Quran (MASAQ) dataset is a high-quality, annotated resource designed to advance Arabic Natural Language Processing (NLP). Covering the entire Quran, MASAQ includes over 131K morphological and 123K syntactic entries, verified by expert linguists using traditional i'rab methodologies. Available in multiple formats, it supports a range of applications—from teaching Arabic grammar to enhancing NLP tools like parsers and taggers. By enabling precise language analysis, MASAQ fosters advancements in Arabic NLP and cross-linguistic research, licensed under Creative Commons for ethical use.
DOI: 10.17632/9yvrzxktmr.4
title: MASAQ: Morphologically-Analyzed and Syntactically-Annotated Quran Dataset

description: The Morphologically-Analyzed and Syntactically-Annotated Quran (MASAQ) dataset is a high-quality, annotated resource designed to advance Arabic Natural Language Processing (NLP). Covering the entire Quran, MASAQ includes over 131K morphological and 123K syntactic entries, verified by expert linguists using traditional i'rab methodologies. Available in multiple formats, it supports a range of applications—from teaching Arabic grammar to enhancing NLP tools like parsers and taggers. By enabling precise language analysis, MASAQ fosters advancements in Arabic NLP and cross-linguistic research, licensed under Creative Commons for ethical use.
DOI: 10.17632/zp5ytjzg4m.1
title: Precipitation estimates and drought conditions in Al-Karak, Southern Jordan 1981-2022

description: Monthly precipitation estimates for the period 1981 - 2022 for the Mazar district of Al-Karak governorate in Southern Jordan, obtained using the agro-climatology database of the NASA POWER platform.
Also presented, drought severity for each period calculated using the Standardised Precipitation Index (SPI) at 3, 6, and 12-month scales. Values over zero represent a wet period, while negative SPI values represent a dry period.
The data used in this analysis were obtained from the NASA Langley Research Center (LaRC) POWER Project funded through the NASA Earth Science/Applied Science Program.
Please cite this data as follows:
Al-Kilani, Muhammad Rasool; Al-Bakri, Jawad; Rahbeh, Michel (2022), “Precipitation estimates and drought conditions in Al-Karak, Southern Jordan 1981-2022”, Mendeley Data, V1, doi: 10.17632/zp5ytjzg4m.1
DOI: 10.17632/zp5ytjzg4m.2
title: Precipitation estimates and drought conditions in Al-Karak, Southern Jordan 1981-2022

description: Monthly precipitation estimates for the period 1981 - 2022 for the Mazar district of Al-Karak governorate in Southern Jordan, obtained using the agro-climatology database of the NASA POWER platform.
Also presented, drought intensity for each period calculated using the Standardised Precipitation Index (SPI) and Standardised Precipitation Evapotranspiration Index (SPEI) at 3, 6, and 12-month scales. Values over zero represent a wet period, while negative values represent a dry period. Seasonal wheat production (tons/year) is also provided for drought impact analysis.
Meteorological data used in this analysis were obtained from the NASA Langley Research Center (LaRC) POWER Project funded through the NASA Earth Science/Applied Science Program. Crop production data was obtained from the Jordanian Department of Statistics.
Please cite this data as follows:
Al-Kilani, Muhammad Rasool; Al-Bakri, Jawad; Rahbeh, Michel (2022), “Precipitation estimates and drought conditions in Al-Karak, Southern Jordan 1981-2022”, Mendeley Data, V1, doi: 10.17632/zp5ytjzg4m.1
DOI: 10.17632/6r5ffp7crw.1
title: LDHU3_13.0430

description: AMP-binding domain-containing protein; Leishmania donovani (HU3 strain)
DOI: 10.17632/w8xm7rpcvv.1
title: LDHU3_13.0440

description: Flagellar radial spoke protein | RSP4/6; Leishmania donovani (HU3 strain)
DOI: 10.17632/5jt53gzj53.1
title: Gaping behaviour of Blue mussels (Mytilus edulis) in relation to freshwater runoff risks - Supplementary Data

description: Raw and processed minute averaged gape sensing data from September 2020 in .txt/.csv format. 15 Blue mussels (Mytilus edulis) plus a control sensor. Column 1 = datetime. Columns 2-17 = mussel gapes (column 13 = control), column 18 = system voltage
DOI: 10.17632/dbs9nps58j.2
title: A Simplified DOC Fractionation SPE Method Without Recovering Sorbed Compounds

description: This research aims to advance the understanding of dissolved organic carbon (DOC) fractions in water treatment processes. Current fractionation methods, such as Solid Phase Extraction (SPE), primarily focus on recovering sorbed compounds and assume that treatment impacts only the quantity, not the characteristics, of DOC fractions. Additionally, varying recovery rates and inconsistent fractionation pH definitions complicate cross-study comparisons of hydrophilic (HPI) and hydrophobic (HPO) DOC composition. This study addresses these gaps by investigating the impact of different pH approaches (pH 3, pH 7, and sequential adjustment) on DOC fractionation focused on organic compounds in the SPE filtrate, as well as the effects of coagulation, softening, and filtration on DOC composition and characteristics.
We introduced a novel fractionation method using Bond Elut ENV cartridges at two pH levels—pH 3 and pH 7—to estimate major DOC fractions: hydrophilic neutral (HPIN), total acidic (TA), and hydrophobic neutral (HPON). This approach eliminates the need to recover sorbed DOC fractions, simplifying the process and enabling more consistent cross-study comparisons. Applying this method in a conventional coagulation/softening plant revealed HPON decreased while the relative amounts of HPI and TA increased after the treatment. However, the treated water HPI exhibited significantly higher STHMFP and contained approximately twice the proportion of low-molecular-weight compounds than raw water HPI, highlighting significant changes in both the content and properties of DOC fractions after the treatment process. Our study indicates the contribution of HPI DOC fraction to SUVA and THM formation potential (THMFP) in treated water is greater than that of HPO DOC.
The data collected, including DOC concentrations, UV254 absorbance, THMFP, and molecular weight distribution using high-performance size exclusion chromatography (HPSEC) across different water samples and in SPE filtrates at various fractionation pH values and SPE types (Bond Elit C18, C18-EWP, and ENV). Also, we conducted a thorough literature review on DOC fractions isolated using bulk resin or SPE methods in drinking water applications. The data provides a comprehensive view of DOC behavior in conventional water treatment processes. This dataset can help practitioners design more efficient processes by considering changes in DOC composition throughout treatment. Researchers can apply these findings to understand better the influence of pH-based fractionation, DOC aromaticity, and the roles of specific DOC fractions in THM formation.
DOI: 10.17632/78x9g3npf4.1
title: LDHU3_13.0550

description: ATP-dependent RNA helicase; Leishmania donovani (HU3 strain)
DOI: 10.17632/xxjbm2df2c.1
title: LINF_350032700

description: galactokinase-like protein
Leishmania infantum (strain JPCM5)
DOI: 10.17632/sdj23bwjyg.1
title: LDHU3_13.0480

description: ALBA-domain protein 1 | ALBA1; Leishmania donovani (HU3 strain)
DOI: 10.17632/tc6kssp9df.1
title: LINF_350032600

description: acyl-CoA dehydrogenase
Leishmania infantum (strain JPCM5)
DOI: 10.17632/c4ycwbkzb7.1
title: LDHU3_13.0460

description: Mitogen-activated protein kinase kinase 2 | MK2 | STK36; Leishmania donovani (HU3 strain)
DOI: 10.17632/c4p79fvmhk.1
title: Holocene variability of the Atlantic Multidecadal Oscillation and the Pacific Decadal Oscillation inferred from Chinese speleothem δ18O records

description: The current reconstructions of the Atlantic Multidecadal Oscillation (AMO) and Pacific Decadal Oscillation (PDO), the key internal drivers of climate variability in the Holocene, primarily rely on marine sediment proxies. However, the limited resolution of these records makes it difficult to precisely understand the short-term dynamics of the PDO and AMO, and consequently, their influence on global climate. This study unveils two new Holocene reconstructions of AMO and PDO derived from a large-scale compilation of speleothem isotope records (δ18Os) from Chinese monsoon region, in which spatial patterns of summer rainfall are generally accepted as good indicators of internal variability over the last millennium. Principal component analysis (PCA) applied to Chinese δ18Os records identifies the first principal component as representative of Holocene Asian monsoon (AM) variation. This data-driven approach reveals a significant shift in hydroclimatic conditions after 8.2 ka, potentially providing valuable insights into the underlying forcing mechanisms driving these changes. The remanent components, which show spatial rainfall patterns, are effectively validated through independent records of AMO and PDO derived from the previous paleo-proxy based reconstructions and model simulations. The present reconstructions suggest a significantly enhanced stability of the AMO and PDO in the middle Holocene, which may explain the concurrent more stable and optimum climate observed in the AM region. These findings also imply that the Holocene AM intensity recorded in Chinese cave records is largely controlled by external forcing, whereas the regionally heterogenous rainfall is regulated by internal variability. The successful attempt on the Holocene AMO and PDO reconstructions indicates an effective isolation between different modes of climate variability from paleoclimate records.
DOI: 10.17632/bvjsjcp32g.1
title: AgroBioDiv: Ökolandbau fördern – gesellschaftlichen Wandel gestalten

description: AgroBioDiv: Ökolandbau fördern – gesellschaftlichen Wandel gestalten

Marcus A. Koch1,2, Jale Tosun2,3, Laura Kellermann1, Charlene Marek3, Cornelia Wiethaler1, Markus Kiefer1
1Universität Heidelberg, Centre for Organismal Studies (COS)
2Universität Heidelberg, Heidelberg Center for the Environment (HCE)
3Universität Heidelberg, Institut für politische Wissenschaft


Ziel des Projektes "AgroBioDiv" ist die Erfassung und Auswertung von Kulturpflanzenarten und -Sorten und der Ackerbegleitflora sowie weiteren Randbedingungen und wird ergänzt um darauf aufbauende politikwissenschaftliche Untersuchungen im Bereich Governance, Implementationsnetzwerken und Zielgruppen-Verhalten im Themenumfeld „Agrarlandschaft und Biodiversität“. Mit Methoden der LimeSurvey unterstützen aber auch aufsuchender Befragungen wird die Biologische Vielfalt von Sorten der Kulturpflanzenarten mit einem Schwerpunkt bei Getreidesorten zusammen mit Kartierungen der Ackerwildkrautflora und sozialwissenschaftlichen Umfragen mittels Fragenbögen partizipativ mit Landwirten in Baden-Württemberg erfasst. 
Das Projekt wurde im Rahmen des Forschungsprogramm Ökologischer Landbau Baden-Württemberg vom Ministerium für Wissenschaft, Forschung und Kunst des Landes Baden-Württemberg von 2020-2024 finanziell unterstützt.
In dem Projektzeitraum wurden Daten von vier landwirtschaftlich arbeitenden Studiengruppen erhoben (Albkorn [AK], Linzgaukorn [LGK], Kraichgaukorn [KGK] und ökologisch wirtschaftende Landwirte mit Ökosorten im Anbau [OEKO]). Diese Daten umfassen Felddaten und Ertragsdaten, Hofstrukturdaten, und Umfrageergebnisse zu politischen Instrumenten.
Zwei weitere Umfragen erheben Begleitinformationen aus Landwirtschaftsverbänden in den Kreisen, Städten und Kommunen in Deutschland sowie eine Markchancenerhebung für Ökosorten in Deutschland.
Die Umfragen als Druckversion (PDF) sowie die exportierten Ergebnisse (Excel) sind entsprechend den nachfolgend genannten Dateinamen hinterlegt. Die Umfragen entsprechen den Vorgaben der Datenschutzgrundverordnung (DSGVO). Und auch wenn die Zustimmung zur Aufhebung der Anonymisierung in den relevanten Umfragen vorlag, wurden hier die Daten generell anonymisiert und stehen nach individueller Rücksprache zur Verfügung. 

Die hinterlegten Dateien (Projektdatendokumentation) sind in dem Dokument "Datenbanken_Mendeley_AgroBioDiv.pdf" genauer erläutert.
DOI: 10.17632/kt34mc26k3.1
title: Source data for "Competition and Synergy of Arp2/3 and Formins in Nucleating Actin Waves"

description: These files consist of the datasets used in the analysis of Chua et al, 2024.
DOI: 10.17632/nstxz7w577.1
title: LINF_350034200

description: mt-LAF5 | mitoribosomal LSU assembly factor 5
Leishmania infantum (strain JPCM5)