cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/pgr5pbhs7t.1
title: Obese pre-post Bariatric UAE

description: Obesity is a global concern, including in the United Arab Emirates, where bariatric surgery offers a potential solution, though its weight loss mechanisms remain uncertain. We investigated these mechanisms in 19 Emirati adults undergoing sleeve gastrectomy. Energy balance, gut peptides, hormones, and microbiota were examined. Three months post-surgery, we observed significant reductions in energy intake, appetite, anthropometric measures, insulin, leptin, and GLP-1, while PYY and GHR increased, and REE remained stable. Gut microbiota composition changed, with some taxa negatively correlated with energy intake, BMI, and appetite. These findings suggest that changes in gut peptides, hormones, and microbiota contribute to the effectiveness of bariatric surgery in promoting weight loss, offering insights for personalized obesity interventions. The raw data used for this study are attached.
DOI: 10.15468/dl.3n3q7u
title: Occurrence Download

description: A dataset containing 580 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Africa",
 "Country is Senegal",
 "OccurrenceStatus is Present",
 "TaxonKey is Acacia senegal (L.) Willd."
 ]
}

 The dataset includes 580 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004411-250117142028555/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/cj69j8bpn8.1
title: Local Microtubule and F-Actin Distributions Fully Constrain the Spatial Geometry of Drosophila Sensory Dendritic Arbors

description: Data and Model related to the manuscript named "Local microtubule and F-actin distributions fully constrain the spatial geometry of Drosophila sensory dendritic arbors"

Authors: Sumit Nanda, Shatabdi Bhattacharjee, Daniel N. Cox, Giorgio A. Ascoli1*

1. Center for Neural Informatics, Structures, & Plasticity and Neuroscience Program, Krasnow Institute for Advanced Study, George Mason University, Fairfax, VA 22030, USA
2. Neuroscience Institute, Georgia State University, Atlanta, GA 30303, USA
3. Bioengineering Department, College of Engineering and Computing, George Mason University, Fairfax, VA 22032, USA
*Correspondence: ascoli@gmu.edu


There are 5 folders. The SimFolder and Analyse folder are directly related to the model. 

1) Place the Real Multi-signal Reconstructions in the Primary Folder (Copy them from All_ClassI_Neurons or All_ClassIV_Neurons or use your own data). 
2) Go to the SimFolder
3) Run the Auto_M_F_Sim_MHSorted_With_Angle_HM.m file in Matlab to run the Simulation
4) Simulated Mat files will be generated in the SimFolder. Copy them to Anlyse folder (..\Analyse)
5) Run the createSwCsMultiNeu_multisignal.m file in the Anlyse folder to out simulated multi-signal swc file in the out folder (\out). 

Remaining three folders have the reconstructions and quantification codes. 

Please cite:
Nanda, S.; Bhattacharjee, S.; Cox, D.N.; Ascoli, G.A. Local Microtubule and F-Actin Distributions Fully Constrain the Spatial Geometry of Drosophila Sensory Dendritic Arbors. Int. J. Mol. Sci. 2023, 24, 6741. https://doi.org/10.3390/ijms24076741
DOI: 10.17632/b5pkxm9vpw.1
title: LINF_360024800

description: DEAD box RNA helicase | HAS1
Leishmania infantum (strain JPCM5)
DOI: 10.17632/mrmfyt2mv5.1
title: A contactless monitoring system for accurately predicting walking energy expenditure based on an ensemble neural network

description: The monitoring of walking energy expenditure (EE) plays an important role in health evaluations and management. Here, we present a datasets to develop a ensemble neural network model for accurately predicting walking EE of younger and older adults and stroke survivors. The datasets including original data, processed data, mechine learning model, ensemble neural network model and the Leave-One-Out Cross-Validation results.
DOI: 10.21942/uva.28228163
title: BJTU-UVA: The First Dataset for Automatic Spectral Calibration of Hyperspectral Images

description: We are proud to introduce <b>BJTU-UVA</b>, the <b>first dataset designed specifically for the task of automatic spectral calibration</b> of hyperspectral images (HSIs). This dataset addresses the critical challenge of minimizing illumination variability without relying on manual intervention or physical references.Key Highlights<b>Task Proposal</b>:<br>We propose the novel task of <b>automatic spectral calibration</b>, aiming to advance the robustness of hyperspectral imaging in diverse real-world scenarios.<b>Dataset Characteristics</b>:<b>Camera</b>: Specim IQ, featuring a spectral resolution of 3nm across the 400–1000nm range.<b>Recording Method</b>: Each scene is captured twice:<b>Without reference board</b>: Captures raw scene data.<b>With white reference board</b>: Records illumination conditions under the same settings.<br>This approach ensures asynchronous yet precise pairing of <b>uncalibrated</b> and <b>calibrated</b> HSIs, effectively minimizing illumination variability.<b>Dark Current Correction</b>: Dark current noise, intrinsic to the camera sensor, is carefully recorded and subtracted during post-processing, ensuring high data accuracy.<b>Scene Diversity</b>:<br>The dataset encompasses a wide range of <b>urban and natural scenes</b>, captured under various weather conditions, lighting scenarios, and times of day.<b>Benchmarking Standard</b>:<br>BJTU-UVA establishes a new standard for spectral calibration by combining real-world scene variability with rigorous illumination recording, offering a robust foundation for testing and advancing spectral calibration techniques.Citation@misc{du2024spectral,<br>title={Automatic Spectral Calibration of Hyperspectral Images: Method, Dataset and Benchmark},<br>author={Zhuoran Du and Shaodi You and Cheng Cheng and Shikui Wei},<br>year={2024},<br>eprint={2412.14925},<br>archivePrefix={arXiv},<br>primaryClass={cs.CV},<br>url={ https://arxiv.org/abs/2412.14925 },<br>}
DOI: 10.21942/uva.28228163.v2
title: BJTU-UVA: The First Dataset for Automatic Spectral Calibration of Hyperspectral Images

description: We are proud to introduce <b>BJTU-UVA</b>, the <b>first dataset designed specifically for the task of automatic spectral calibration</b> of hyperspectral images (HSIs). This dataset addresses the critical challenge of minimizing illumination variability without relying on manual intervention or physical references.Key Highlights<b>Task Proposal</b>:<br>We propose the novel task of <b>automatic spectral calibration</b>, aiming to advance the robustness of hyperspectral imaging in diverse real-world scenarios.<b>Dataset Characteristics</b>:<b>Camera</b>: Specim IQ, featuring a spectral resolution of 3nm across the 400–1000nm range.<b>Recording Method</b>: Each scene is captured twice:<b>Without reference board</b>: Captures raw scene data.<b>With white reference board</b>: Records illumination conditions under the same settings.<br>This approach ensures asynchronous yet precise pairing of <b>uncalibrated</b> and <b>calibrated</b> HSIs, effectively minimizing illumination variability.<b>Dark Current Correction</b>: Dark current noise, intrinsic to the camera sensor, is carefully recorded and subtracted during post-processing, ensuring high data accuracy.<b>Scene Diversity</b>:<br>The dataset encompasses a wide range of <b>urban and natural scenes</b>, captured under various weather conditions, lighting scenarios, and times of day.<b>Benchmarking Standard</b>:<br>BJTU-UVA establishes a new standard for spectral calibration by combining real-world scene variability with rigorous illumination recording, offering a robust foundation for testing and advancing spectral calibration techniques.Citation@misc{du2024spectral,<br>title={Automatic Spectral Calibration of Hyperspectral Images: Method, Dataset and Benchmark},<br>author={Zhuoran Du and Shaodi You and Cheng Cheng and Shikui Wei},<br>year={2024},<br>eprint={2412.14925},<br>archivePrefix={arXiv},<br>primaryClass={cs.CV},<br>url={ https://arxiv.org/abs/2412.14925 },<br>}
DOI: 10.21942/uva.28228163.v1
title: Automatic Spectral Calibration Dataset

description: This is the dataset of ASC project, rw denotes raw images to be calibrated while gt_files contains ground truth images
DOI: 10.17632/6xjpfr72sp.1
title: Replication package for: "Bailout Dynamics in a Monetary Union" by Michal Kobielarz

description: This package replicates the results in Kobielarz (2023), "Bailout Dynamics in a Monetary Union".

The Eurozone bailouts comprised credit lines with low interest rates and long maturity. The favorable lending conditions are equivalent to countries receiving implicit fiscal transfers and are often interpreted as meant to prevent a default in the Eurozone or resolve the crisis. Contrary to this narrative, Greece defaulted on its debt and went through a deep and prolonged recession, despite receiving fiscal assistance. This paper analyzes country bailouts in a monetary union within a framework where sovereign default and exit from the union are two separate decisions. The studied bailouts prevent an exit and, thus, do not exclude subsequent defaults. The model replicates the experience of Greece and captures the coexistence of bailouts, defaults, and recession. It also sheds new light on the moral hazard discussion of bailouts by showing no significant effects from exit-driven bailouts.
DOI: 10.17632/pjtftxhk42.1
title: Is the grass greener on the other side? A comparison of management preferences between stalked barnacle harvesters across Europe: Survey data

description: Survey data used in a perception study of stalked barnacle harvesters on the effectiveness of fisheries management practices in Spain, Portugal and France. Harvesters from the following six regions along the Atlantic Arc participated: Morbihan in Brittany (France), Asturias-East, Asturias-West and Galicia (Spain), the Reserva Natural das Berlengas (RNB; Portugal) and the Parque Natural do Sudoeste Alentejano e Costa Vicentina (PNSACV; Portugal). We administered 184 surveys from October 2019 to September 2020 and each region was treated as an independent population. The data includes: general demographic data (Region, Age, Gender, Level of Education, Main income source, Years of Experience); data of the perceived knowledge regarding management strategies (coded: k_name_of_strategy – using 0 = No; 1 = Yes: NA = No Answer); perception data of the effectiveness of the currently implemented management strategies in each region (coded: e_name_of_strategy – using Likert Scale with scores ranging from 1 = completely ineffective to 5 = very effective); data of the willingness for change of the currently implemented management (Yes, No, NA); and data of harvesters’ perceptions regarding the most important strategy to achieve sustainability in the fishery. Because the surveys were conducted both before and during the Covid-19 pandemic (the column Covid indicates whether the data was collected before or during the pandemic), we had to make adjustments in our data collection methods. We provided the following options for survey completion (see the Recollection_of_data column): by hand in a written format, online, or via an oral interview conducted with the assistance of a scientist per telephone.

Results:
In general, harvesters indicated a good understanding of the implemented strategies, however, some gaps were identified. Our results indicate that the majority of harvesters in the regions in Portugal and France were willing to make changes to current management strategies, reflecting their awareness of the need for improvement. In the fisheries with higher levels of governance and management success (Galicia and Asturias-West), this willingness was considerably smaller. Based on the AIC model selection analysis results, the model with the single variable region explained 83% of the cumulative model weight. The variable region was the best predictor of the trends in management strategy preferences, and presented a highly significant goodness-of-fit result (p&lt;0.001), suggesting that regional differences play a significant role in shaping these preferences. 
No clear trend emerged regarding a single "optimal" management strategy preferred by harvesters across regions. Our findings emphasise the importance of tailoring management strategies to each region's specific practices, needs, and characteristics.
DOI: 10.17632/v7bbs5cx7p.1
title: Sustainable Systematic Literature Reviews

description: Context: Systematic Literature Reviews (SLR) have been recognized as an important research method for summarizing evidence in Software Engineering (SE). At the same, SLR still presents several problems, such as the high resource consumption (mainly human resources) and lack of effective impact on SE practitioners, although much research has already been done. 
Objective: The main goal of this paper is to explore the concept of sustainability in the SLR area, intending to contribute to understanding better and solving such problems in an integrated way. More specifically, this paper characterizes what sustainable SLR are, their core characteristics, critical factors (i.e., sensitive points in the SLR process), and guidelines for conducting such SLR.
Method: We performed a meta-ethnographic study to find key concepts of sustainable software systems and transpose them to sustainable SLR. For this, we systematically selected 16 studies about sustainable software systems and 14 distinguished studies about SLR. Following, we extracted the main keywords and metaphors, determined how both areas are correlated, and transposed them to obtain a set of core characteristics of sustainable SLR as well as critical factors and guidelines. Additionally, we validated them with specialists using the Delphi method. 
Results: We found 15 core characteristics that offer a broad view of sustainable SLR, 15 critical factors in the SLR process that should be carefully addressed when conducting and updating SLR, and also 16 guidelines to manage SLR from the sustainability perspective. 
Conclusion: The concept of sustainability in SLR can contribute to solving SLR problems in a more integrated way, while this work could change the mindset of the SLR community about the need to conduct sustainable SLR.

This dataset provides all artifacts created in each step of this studies.
DOI: 10.17632/t8ss7t539f.1
title: Comparison of Bacterial Intracellular and Secreted Proteins produced in Milk Versus Medium for Escherichia coli by Proteomic Analysis

description: Escherichia coli, Quantitative proteomics, Bacterial intracellular proteins, Secreted proteins
DOI: 10.17632/88g6yh37xx.1
title: GPS displacement time-series and the GPS-derived hydrological mass variations in the Himachal region of NW Himalaya from a newly established permanent GNSS network

description: This dataset contains the Research Data related to the original research article, "Evidence of Transient and Tectonic Deformation in the Himachal region of NW Himalaya from continuous GPS measurements and their Hazard Implications", submitted to Tectonophysics for publication.

Dataset 1: GPS-Average-TWS-Variations.zip contains the GPS-derived average TWS variation time-series for the three geologically relevant subregions of Himachal Himalaya, i.e., Kangra Re-entrant, Nahan Salient and Higher Elevations in the vicinity of locking transition zone.

Dataset 2: Himachal-TS.zip contains the GPS displacement time-series in both ITRF 2014 and India-fixed reference frames, of all the established sites in this study in the Himachal region of NW Himalaya.
DOI: 10.17632/m6hkckzxzw
title: LDHU3_19.0610

description: Protein of unknown function - conserved; Leishmania donovani (HU3 strain)
DOI: 10.17632/m6hkckzxzw.1
title: LDHU3_19.0610

description: Protein of unknown function - conserved; Leishmania donovani (HU3 strain)
DOI: 10.17632/6rzb726x6g.1
title: LINF_070009400

description: EamA domain-containing protein; Leishmania infantum (strain JPCM5)
DOI: 10.17632/fm7v78y3r5
title: LDHU3_19.0600

description: MetAP1 | Methionine aminopeptidase 1; Leishmania donovani (HU3 strain)
DOI: 10.17632/fm7v78y3r5.1
title: LDHU3_19.0600

description: MetAP1 | Methionine aminopeptidase 1; Leishmania donovani (HU3 strain)
DOI: 10.17632/mz2g9yzdmg.1
title: Does Intelligent Technological Transformation Matter for Access to Finance?

description: This study investigates the impact of intelligent technological transformation on financial access. Existing literature mostly focuses on the influence of external finance on entrepreneurship, productivity, and artificial intelligence, with limited research assessing how intelligent technological transformation affects their access to finance. Using China's Smart Manufacturing Pilot Program since 2015, we employ difference-in-differences model to examine the promoting effect of intelligent technological transformation on access to bank loans. Our analysis reveals firms with smart manufacturing technologies obtain more loans from banks. Channel analysis shows that significantly amplifying firm reputation and strengthening competitive capabilities from intelligent technological transformation improves their access to bank loans. These findings shed light on the role of intelligent transformation activities in access to finance resources.
DOI: 10.17632/yvjbpp89xp.1
title: LINF_360025400

description: kinetoplastid kinetochore protein 1 | KKT1
Leishmania infantum (strain JPCM5)
DOI: 10.17632/wmdyxp3svr.1
title: LINF_360025200

description: NOC3
Leishmania infantum (strain JPCM5)
DOI: 10.15468/dl.vz6x4f
title: Occurrence Download

description: A dataset containing 349912 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Castanea sativa Mill."
 ]
}

 The dataset includes 349912 records from 1974 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004382-250117142028555/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.a7hj93
title: Occurrence Download

description: A dataset containing 854942 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Phoenicurus phoenicurus (Linnaeus, 1758))",
 "Geometry POLYGON((-9.36035 44.71551,-10.59082 42.81152,-11.82129 36.80928,-7.69043 36.17336,-3.38379 35.88905,3.12012 38.13456,9.18457 38.20366,11.7334 37.16032,12.78809 34.74161,17.09473 33.79741, 23.15918 34.23451,30.10254 32.62087,33.2666 32.99024,35.72754 35.03,33.00293 35.53223,28.69629 35.17381,28.34473 36.31513,25.7959 37.50973,24.91699 39.90974,28.78418 40.6473,30.71777 41.17865,36.87012 45.213,38.18848 46.98025,38.71582 47.7541,39.94629 47.93107,40.20996 49.61071,37.0459 50.34546,35.72754 50.40152,33.79395 52.26816,31.68457 51.94426,31.4209 53.27835,32.56348 53.43572,30.98145 54.77535,30.89355 55.52863,28.43262 56.02295,27.20215 57.65716,27.37793 58.30949,27.90527 59.17593,29.66309 59.88894,27.6416 60.58697,31.50879 62.75473,28.78418 69.83962,30.89355 70.28912,29.22363 71.55274,21.75293 71.30079,14.28223 70.14036,11.38184 67.47492,4.87793 63.66576,-5.53711 71.52491,-10.63477 71.69129,-21.5332 67.74276,-28.56445 65.36684,-24.3457 61.35461,-9.36035 44.71551))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "Year is less than or equal to 2021"
 ]
}

 The dataset includes 854942 records from 800 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0171194-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.b4we2r
title: Occurrence Download

description: A dataset listing the 450 species recorded in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "BasisOfRecord is Human Observation",
 "BasisOfRecord is Specimen",
 "BasisOfRecord is Occurrence evidence",
 "BasisOfRecord is Material sample"
 ]
 },
 "Geometry POLYGON((-114.1908 27.99316,-112.79553 27.99316,-112.79553 28.21289,-112.88342 28.31177,-112.86145 28.45459,-113.0592 28.52051,-113.26794 28.83911,-113.42175 28.927,-113.63049 29.28955,-114.20178 29.78394,-114.42151 29.8938,-114.64124 30.14648,-114.70715 30.95947,-114.86096 31.08032,-114.80603 31.61865,-114.80603 31.86035,-114.92688 31.91528,-115.00378 32.18115,-115.04732 32.25311,-114.92802 32.48418,-114.82237 32.48712,-114.78875 32.56419,-114.80915 32.55297,-114.80562 32.61566,-114.74289 32.66933,-114.72137 32.71866,-117.14612 32.53271,-117.03625 32.23608,-116.92639 32.14819,-116.81653 31.91748,-116.70667 31.84058,-116.65173 31.69775,-116.65173 31.52197,-116.34412 31.21436,-116.3551 30.96167,-116.09143 30.79688,-116.00354 30.4563,-115.82776 30.2915,-115.80579 30.02783,-115.75085 29.85205,-115.21252 29.4126,-115.0697 29.40161,-114.15784 28.56665,-114.06995 28.448,-114.12556 28.24969,-114.06995 28.27222,-114.1908 27.99316))",
 "OccurrenceStatus is Present",
 "TaxonKey is Mammalia"
 ]
}

 The dataset's 450 records were derived from 82 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0325435-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jf8639
title: Occurrence Download

description: A dataset containing 123 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Neobuxbaumia mezcalaensis (Bravo) Backeb."
 ]
}

 The dataset includes 123 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013691-230828120925497/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.a7tcc6
title: Occurrence Download

description: A dataset containing 4591 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is WII Herbarium Dataset"
 ]
}

 The dataset includes 4591 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0136007-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.eregva
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Chalcites meyerii (Salvadori, 1874)"
 ]
}

 The dataset includes 8 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0375430-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.aqbbde
title: Occurrence Download

description: A dataset containing 1013415 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Museums Victoria provider for OZCAM"
 ]
}

 The dataset includes 1013415 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004581-230918134249559/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.s2fwyh
title: Occurrence Download

description: A dataset containing 62192 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Rhinella marina (Linnaeus, 1758)"
 ]
}

 The dataset includes 62192 records from 404 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008596-231002084531237/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.