cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/p8xm4fx5ys.1
title: Chemical compound identified in Green Honey (GH)

description: The LC-MS/MS-QTOF to identify non-targeted derivatives in GH samples. This comprehensive analysis encompasses compound names, mass-to-charge values, species, retention times, and various other details. The analysis revealed a total of 42 chemical compounds, including 10 unidentified ones. Among the identified compounds, there were 9 carbohydrates, 9 organic acids, 7 amino acids, 6 fatty acids, 2 sugars, and one compound each of phenol, terpene, sulfur, and phosphate. These findings substantiate that green honey contains a substantial array of significant compounds, making it a safe choice for daily consumption. This dataset provides a thorough overview of the analyzed samples, allowing for a more in-depth understanding of the detected compounds and their characteristics.
DOI: 10.17632/cwn4mm3png.1
title: Chlorophyll and its derivatives identified in Green Honey (GH)

description: The LC-MS/MS-based targeted analysis found 16 different chlorophylls and their derivatives in Green Honey (GH), namely chlorophyll a, chlorophyll b, chlorophyll c, chlorophyll d, pheophytin a, pheophytin b, hydroxypheophytin a, hydroxypheophytin b, hydroxychlorophyll a, chlorophyllide a, chlorophyllide b, phyropheophytin a, bacteriochlorophyll a, bacteriochlorophyll b, phytol and phytanic acids and none were found in Tualang Honey (TH).
DOI: 10.17632/7cj8phvkh2.1
title: Chemical Compound identified in Tualang Honey (TH)

description: The LC-MS/MS-QTOF to identify non-targeted derivatives in TH samples. This comprehensive analysis encompasses compound names, mass-to-charge values, species, retention times, and various other details. The LC-MS/MS QTOF analysis of TH detected a total of 35 compounds, comprising 15 known and 20 unknown compounds. Major peaks were observed for compounds such as 3-β-Galactopyransoyl glucose, 3-Methoxy-4,5-Methylenedioxybenzoic acid, Nicotinamide riboside and others. The identification was verified based on molecular mass, retention time, and mass-to-charge ratio. Interestingly, three compounds (Dihydrocaffeic acid, 3-β-Galactopyransoyl glucose, and Ethyl-β-D-glucopyranoside) were found in both GH and TH samples. This dataset provides a thorough overview of the analyzed samples, allowing for a more in-depth understanding of the detected compounds and their characteristics.
DOI: 10.17632/bv2hvm4pmz.1
title: Indoor Air Quality Monitoring @ Brindisi Airport

description: The experimental dataset here represented is composed by 3 CSV files (ranging from 7M records to 11M records), each corresponding to air quality records -- related to the presence of gases (as a unified value concentration); the concentration of carbon dioxide (CO2), together with air temperature and humidity; and the concentration of particulate matter (PM) in the monitored environment (PM0.5, PM1, PM2.5, PM4, PM10) -- sampled (every 2 sec) over a 1-year period (October 2022-October 2023) in an indoor travelers’ transit area in the Brindisi airport, Italy, in the aim of the European project InSecTT (https://www.insectt.eu/, https://cordis.europa.eu/project/id/876038/). In particular, each CSV file has been generated by a prototypical Internet of Things (IoT) sensing node, designed at the IoTLab (https://iotlab.unipr.it/) of the University of Parma, Italy, exploiting a Raspberry Pi 4 (as processing unit) and three low-cost commercial sensors (namely: Adafruit MiCS5524, Sensirion SCD30, Sensirion SPS30). Then, as a time reference, each record contains the Unix-like data collection timestamp and the identity of the IoT node sampling the air parameters (for safety purposes, the association with a generic color name in the CSV file name has been a consequence of an anonymization naming process for the IoT nodes, in order to hide their precise positions inside the airside transit area).
DOI: 10.17632/bv2hvm4pmz.2
title: Indoor Air Quality Monitoring @ Brindisi Airport

description: The experimental dataset here represented is composed by 3 CSV files (ranging from 7M records to 11M records), each corresponding to air quality records -- related to the presence of gases (as a unified value concentration); the concentration of carbon dioxide (CO2), together with air temperature and humidity; and the concentration of particulate matter (PM) in the monitored environment (PM0.5, PM1, PM2.5, PM4, PM10) -- sampled (every 2 sec) over a 1-year period (October 2022-October 2023) in an indoor travelers’ transit area in the Brindisi airport, Italy, in the aim of the European project InSecTT (https://www.insectt.eu/, https://cordis.europa.eu/project/id/876038/). In particular, each CSV file has been generated by a prototypical Internet of Things (IoT) sensing node, designed at the IoTLab (https://iotlab.unipr.it/) of the University of Parma, Italy, exploiting a Raspberry Pi 4 (as processing unit) and three low-cost commercial sensors (namely: Adafruit MiCS5524, Sensirion SCD30, Sensirion SPS30). Then, as a time reference, each record contains the Unix-like data collection timestamp and the identity of the IoT node sampling the air parameters (for safety purposes, the association with a generic color name in the CSV file name has been a consequence of an anonymization naming process for the IoT nodes, in order to hide their precise positions inside the airside transit area).
DOI: 10.17632/x3tjyw3v5y.1
title: The Importance of Expert Testimony in Proving Corruption Crimes

description: The criminal act of corruption is an extraordinary crime that has an extraordinary impact on the state and the survival of its people. Corruption as an extraordinary crime requires extraordinary handling efforts as well, especially in the process of proving it. Proving corruption often requires the role of experts from several disciplines to ensure that corruption has actually occurred. The purpose of writing this article is to analyze the existence of expert testimony as evidence in proving corruption and the extent to which expert testimony contributes to convincing judges that corruption has occurred. The writing of this article uses normative legal research methods with a statutory approach. The results of this study are that the submission of expert testimony to the trial of corruption will increase the judge's confidence in the truth of other evidence submitted by the public prosecutor, and strengthen the judge's conviction to pass a sentence of punishment if indeed from the existing evidence the defendant is legally and convincingly proven to have committed corruption.
DOI: 10.17632/62mjzx6kpd.1
title: Experimental data for the manuscript "Electromagnetic Model of K-changes"

description: Experimental electric field data measured at Florida, Kennedy Space Center. The lightning flash with observed K changes occurred at 1929:29 UT on August 12, 2011. As a sensor served the flat-plate E-change antenna with a sensor having a decay time constant of 1 s with bandwidth of 0.16 Hz – 2.6 MHz and a sampling rate of 5 MHz. The sensor was operated by the group of atmospheric electricity of the University of Mississippi. The data were used also in by Stolzenburg et al. (2013).
DOI: 10.5281/zenodo.10183781
title: BP-tracer: Supplementary Data 2 Version 2.0

description: Supplementary Data 2 contains 1) the raw results obtained from the Benchmark Part of the paper, encompassing BP-Tracer, Reads, Contigs, MAGs and Correlation methods. 2) the raw results of BP-Tracer obtained from Real metagenomic datasets, including metagenomic datasets from clinical settings associated with pathogenic infection (urinary tract infections, UTIs), hospitalization (preterm infant using antibiotic), antibiotic exposure (healthy adults following antibiotic exposure) and the datasets from 7 different environments (Extended Data).
DOI: 10.17632/3p2bc47t5s.1
title: Clinical empathy in French speech and language pathology practitioners and students

description: The data set correspond to 2 cross national survey exploring the clinical empathy of French speech and language pathology practitioners and students
DOI: 10.5281/zenodo.10183780
title: BP-tracer: Supplementary Data 2 Version 2.0

description: Supplementary Data 2 contains 1) the raw results obtained from the Benchmark Part of the paper, encompassing BP-Tracer, Reads, Contigs, MAGs and Correlation methods. 2) the raw results of BP-Tracer obtained from Real metagenomic datasets, including metagenomic datasets from clinical settings associated with pathogenic infection (urinary tract infections, UTIs), hospitalization (preterm infant using antibiotic), antibiotic exposure (healthy adults following antibiotic exposure) and the datasets from 7 different environments (Extended Data).
DOI: 10.17632/chp9xy5ys7.1
title: An integrated three-way decision methodology for sustainability of wastewater circularity in thermal power plants

description: These Microsoft Excel files support our manuscript titled “An integrated three-way decision methodology for sustainability of wastewater circularity in thermal power plants”. 1. We include the file for our dataset of 11 expert decision-makers. This file is necessary for the application of our proposed 3WD-MARCOS method. 2. We include the computations of our Example 1 until Example 4. 3. We also include a file that presents our data for the best-worst method. The results from Lingo® optimization software are shown in this file. We detailed here the computations necessary in obtaining the attribute weights. This file supports Table 5 of our manuscript. 4. We attach here the file for the 3WD-MARCOS application of our case study. This file supports Table 8 and Table 9 of our manuscript. 5. We include the necessary computations of our sensitivity analysis, shown in Section 5 of our manuscript. This file supports Figure 3. 6. Finally, we include a file showing the computations of our comparative analysis (Section 5). This file supports Figure 4, Figure 5, and Table 10 of our manuscript.
DOI: 10.17632/yk9g44bdnd.1
title: Spatial-Temporal Modeling of the Relationship Between Surface Temperature and Air Temperature in Metropolitan Urban Systems

description: This data set contains surface (LST) and air temperature (AT) data collected in Philadelphia in 2022 and 2023 which was used to construct a spatiotemporal model using AT to predict LST. The code for that model in included as well.
DOI: 10.17632/zzx4v96ry9.1
title: HRIS Journal

description: This data is the result of a survey conducted on SMEs in Indonesia. This data represents SMEs' perceptions of HRIS.
DOI: 10.17632/rb8xc5dyjw.1
title: Sniffing Impairment in Spine Surgery

description: Raw data of the clinical trial NCT04194788. This research aims to observe detectable dysosmias after spine surgery, to explore any amplified affection of halogenates (DESflurane and SEVoflurane) against total intravenous anesthesia (TIVA), and to spot potential repercussions on the refeeding. The dataset was used to write the article "Perioperative Anesthesia and Acute Smell Alterations in Spine Surgery: A "Sniffing Impairment" Influencing Refeeding?", which was published by the journal Frontiers in Surgery in 2022.
DOI: 10.17632/rb8xc5dyjw.2
title: Sniffing Impairment in Spine Surgery (TASTEODOR; PI: M Briguglio)

description: Raw data of the clinical trial NCT04194788. This research aims to observe detectable dysosmias after spine surgery, to explore any amplified affection of halogenates (DESflurane and SEVoflurane) against total intravenous anesthesia (TIVA), and to spot potential repercussions on the refeeding. The dataset was used to write the article "Perioperative Anesthesia and Acute Smell Alterations in Spine Surgery: A "Sniffing Impairment" Influencing Refeeding?", which was published by the journal Frontiers in Surgery in 2022.
DOI: 10.17632/rb8xc5dyjw.3
title: Sniffing Impairment in Spine Surgery (TASTEODOR; PI: M Briguglio)

description: Raw data of the clinical study NCT04194788. This research aims to observe detectable dysosmias after spine surgery, to explore any amplified affection of halogenates (DESflurane and SEVoflurane) against total intravenous anesthesia (TIVA), and to spot potential repercussions on the refeeding. The dataset was used to write the article "Perioperative Anesthesia and Acute Smell Alterations in Spine Surgery: A "Sniffing Impairment" Influencing Refeeding?", which was published by the journal Frontiers in Surgery in 2022.
DOI: 10.17632/v9ffjfrdms.1
title: Eating habits in patients with end-stage osteoarthritis of the hip (NUTRIANCA; PI: M Briguglio)

description: Raw data of the clinical study NCT03981354. The study explored the role of nutritional status indicators, such as diet, in determining the strength of constitution, suitability for surgery, and recovery in the older population undergoing major orthopaedic surgery. The dataset was used to write the brief report "How do older patients with end-stage osteoarthritis of the hip eat prior to hip replacement? A preliminary snapshot that highlights a poor diet", which was published by the journal Nutrients in 2023.
DOI: 10.17632/zbstjj6zsm.1
title: Digital data for "Corotational force-based beam finite element with rigid joint offsets for 3D framed structures"

description: This dataset contains the data, in digital form, that have been used to create the figures of the paper: Di Re, P., Addessi, D., Gatta, C., Parente, L. and Sacco, E. "Corotational force-based beam finite element with rigid joint offsets for 3D framed structures" Computer Methods in Applied Mechanics and Engineering. https://doi.org/10.1016/j.cma.2023.116656
DOI: 10.17632/4dx4dr4t3c.1
title: Seminario de investigación 2

description: Data para Seminario de Investigación 2
DOI: 10.17632/cmg7vvxtp3.1
title: Classical and neural PCA for image compression - Matlab files

description: Matlab scripts, functions and image files for the classical and neural network-based PCA aproaches for lossy image compression. Scripts (require Matlab Deep Learning Toolbox and the helper functions given below): - CPCA_compression.m: image compression/decompression procedure using the classical PCA approach, - APCA_compression.m: image compression/decompression procedure using the neural linear autoencoder, - GPCA_compression.m: image compression/decompression procedure using the GHA neural network. Functions: - prep_diff_image.m: preparing the vectorized difference image frame matrix based on the original image matrix, - prep_decompr_image.m: preparing the reconstructed (decompressed) image matrix based on the reconstructed (decompressed) vectorized difference image frame matrix, - calc_error_coeffs.m: calculating different indicators of the image compression error, - gha.m: training the GHA neural network (Matlab function shared by David Gleich in https://www.cs.purdue.edu/homes/dgleich/projects/pca_neural_nets_website/neural-pca-ica.zip). Images: - baboon.tif, - barbara.tif, - lighthouse.tif.
DOI: 10.5281/zenodo.10171329
title: Dataset related to article "Immunometabolic interference between cancer and COVID-19"

description: This record contains raw data related to article "Immunometabolic interference between cancer and COVID-19"
Abstract:
Even though cancer patients are generally considered more susceptible to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, the mechanisms driving their predisposition to severe forms of coronavirus disease 2019 (COVID-19) have not yet been deciphered. Since metabolic disorders are associated with homeostatic frailty, which increases the risk of infection and cancer, we asked whether we could identify immunometabolic pathways intersecting with cancer and SARS-CoV-2 infection. Thanks to a combined flow cytometry and multiomics approach, here we show that the immunometabolic traits of COVID-19 cancer patients encompass alterations in the frequency and activation status of circulating myeloid and lymphoid subsets, and that these changes are associated with i) depletion of tryptophan and its related neuromediator tryptamine, ii) accumulation of immunosuppressive tryptophan metabolites (i.e., kynurenines), and iii) low nicotinamide adenine dinucleotide (NAD+) availability. This metabolic imbalance is accompanied by altered expression of inflammatory cytokines in peripheral blood mononuclear cells (PBMCs), with a distinctive downregulation of IL-6 and upregulation of IFNγ mRNA expression levels. Altogether, our findings indicate that cancer not only attenuates the inflammatory state in COVID-19 patients but also contributes to weakening their precarious metabolic state by interfering with NAD+-dependent immune homeostasis.
DOI: 10.5281/zenodo.10171330
title: Dataset related to article "Immunometabolic interference between cancer and COVID-19"

description: This record contains raw data related to article "Immunometabolic interference between cancer and COVID-19"
Abstract:
Even though cancer patients are generally considered more susceptible to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, the mechanisms driving their predisposition to severe forms of coronavirus disease 2019 (COVID-19) have not yet been deciphered. Since metabolic disorders are associated with homeostatic frailty, which increases the risk of infection and cancer, we asked whether we could identify immunometabolic pathways intersecting with cancer and SARS-CoV-2 infection. Thanks to a combined flow cytometry and multiomics approach, here we show that the immunometabolic traits of COVID-19 cancer patients encompass alterations in the frequency and activation status of circulating myeloid and lymphoid subsets, and that these changes are associated with i) depletion of tryptophan and its related neuromediator tryptamine, ii) accumulation of immunosuppressive tryptophan metabolites (i.e., kynurenines), and iii) low nicotinamide adenine dinucleotide (NAD+) availability. This metabolic imbalance is accompanied by altered expression of inflammatory cytokines in peripheral blood mononuclear cells (PBMCs), with a distinctive downregulation of IL-6 and upregulation of IFNγ mRNA expression levels. Altogether, our findings indicate that cancer not only attenuates the inflammatory state in COVID-19 patients but also contributes to weakening their precarious metabolic state by interfering with NAD+-dependent immune homeostasis.
DOI: 10.17632/mk8ttbt545.1
title: Super and typical enhancer switching in early mammalian development involves eRNA mediated SWI/SNF recruitment

description: Our data shows that the AT-hook domain of Brg1 is required for it's recruitment by an RNA dependent mechanism in distinct developmental stages. To further substantiate that the AT-hook Brg1 binds to the RNA, we purified the wild type and mutant AT-hook peptides and performed gel shift assay. Here, the gel images pertinent to the purification of the wild type and mutant AT-hook peptides and electrophoretic mobility shift assay (EMSA). The details of the experimental conditions for purification and EMSA are described in STAR Methods.
DOI: 10.17632/mk8ttbt545.2
title: Super and typical enhancer switching in early mammalian development involves eRNA mediated SWI/SNF recruitment

description: Our data shows that the AT-hook domain of Brg1 is required for it's recruitment by an RNA dependent mechanism in distinct developmental stages. To further substantiate that the AT-hook Brg1 binds to the RNA, we purified the wild type and mutant AT-hook peptides and performed gel shift assay. Here, the gel images pertinent to the purification of the wild type and mutant AT-hook peptides and electrophoretic mobility shift assay (EMSA). The details of the experimental conditions for purification and EMSA are described in STAR Methods.
DOI: 10.17632/sj3vrvm6w3.1
title: Pre-trained single-cell segmentation models

description: Two LACSS single-cell segmentation models. The first was trained on LIVECell dataset (bright field microscopy). The second was trained on TissueNet dataset (fluorescence tissue section).
DOI: 10.17632/sj3vrvm6w3.2
title: Pre-trained single-cell segmentation models

description: Two LACSS single-cell segmentation models. The first was trained on LIVECell dataset (bright field microscopy). The second was trained on TissueNet dataset (fluorescence tissue section).
DOI: 10.17632/sj3vrvm6w3.3
title: Pre-trained single-cell segmentation models

description: Pretrained LACSS single-cell segmentation models.
DOI: 10.17632/sj3vrvm6w3.4
title: Pre-trained single-cell segmentation models

description: Pretrained LACSS single-cell segmentation models.
DOI: 10.17632/ncdf5dvsm7.1
title: DIGITAL TRANSFORMATION AND SUSTAINABILITY: A SYSTEMATIC REVIEW OF THE LITERATURE.

description: Bibliometric data from search made at Scopus and Web of Science on November, 2023 Search Date: 21/11/2023 Search Query: All Fields: Digital Transformation, Sustainability, Industry 4.0, ESG.
DOI: 10.17632/mpwdrr6y3v.1
title: Open access dataset for Spelling Correction in Russian

description: Open access dataset for Spelling Correction in Russian. Each unit of the dataset consists of a word pair containing an incorrect spelling and its corresponding corrected form. The dataset comprises two parts for training and testing in scv format, containing 80,000 and 20,612 word pairs respectively. Each row accurately corresponds to a single word pair. Most of the pairs is obtained through word frequency analysis of the Wikipedia corpus, according to the method described in the paper [1]. [1] Whitelaw C. et al. Using the web for language independent spellchecking and autocorrection. – 2009.
DOI: 10.17632/gs8nt4c8r8.1
title: Why did shareholder liability disappear?

description: Replication files for the article 'Why did shareholder liability disappear?'
DOI: 10.17632/84y45dsp28.1
title: Data for:High-precision zirconium isotope analysis of Pacific seawater reveals large mass-dependent fractionations in the ocean

description: Supplemental data by Huang et al to be published by Geochimica et Cosmochimica Acta as "High-precision zirconium isotope analysis of Pacific seawater reveals large mass-dependent fractionations in the ocean"
DOI: 10.17632/84y45dsp28.2
title: Data for:High-precision zirconium isotope analysis of Pacific seawater reveals large mass-dependent fractionations in the ocean

description: Data and supplemental data by Huang et al for submission to Geochimica et Cosmochimica Acta as "High-precision zirconium isotope analysis of Pacific seawater reveals large mass-dependent fractionations in the ocean"
DOI: 10.17632/84y45dsp28.3
title: Data for:High-precision zirconium isotope analysis of Pacific seawater reveals large mass-dependent fractionations in the ocean

description: Data and supplemental data by Huang et al for submission to Geochimica et Cosmochimica Acta as "High-precision zirconium isotope analysis of Pacific seawater reveals large mass-dependent fractionations in the ocean"
DOI: 10.17632/cbvxkkgy38.2
title: Impacts of Livelihood Assets on Hydropower Displacees Livelihood Strategies: Insights from the Tanahu Hydropower Project in Nepal

description: Examining livelihood assets is crucial for displaced people, as it informs effective resource allocation and support. This study investigates the livelihood decisions of households displaced by Nepal's Tanahu Hydropower Project, using multinomial logistic regression to assess how different assets affect their choices. It finds that physical assets significantly influence livelihood strategies, promoting diversification and non-farm activities. Surprisingly, social assets have a negative impact, while natural, financial, and human assets show no significant effect. The research highlights the community's focus on economic stability, balancing immediate financial needs with long-term goals like children's education. However, it reveals ongoing financial struggles, with an average daily income of only 1.962 USD and many households remaining in poverty, especially those dependent on farming. The study also reflects on the mixed perceptions towards government policies, influenced by factors such as skill gaps and family aspirations. These findings provide essential insights for targeted support and resource allocation to displaced populations.