cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/n49xkddkgs
title: Spectroscopic data of soil samples doped with P2O5, Santander de Quilichao, Colombia

description: The dataset includes 152 reflectance spectra in the range of 200 to 900 nm, corresponding to soil samples prepared with a concentration of P2O5 and soil from Santander de Quilichao, Colombia. These data are used to determine the total phosphorus concentration in the soil. The readings were performed using a JASCO V-750 spectrophotometer. The dataset includes an Excel file with the spectral data and laboratory results, obtained from the dataset published at https://data.mendeley.com/datasets/fvgswvt5ws/3. Additionally, a .mat file created in MATLAB R2022a is provided, containing the same data to facilitate manipulation and analysis.
DOI: 10.17632/nfxrxy955z
title: Experiments to evaluate the workability of self-compacting concrete (Slump test, J-ring, V-funnel)

description: Title: To conduct experiments to evaluate the workability of self-compacting concrete.
Overview: The test was carried out in the Structural engineering laboratory at the Department of Civil Engineering, IIT Kharagpur, India. All the experiments were conducted in February 2024 by Kumar Anjneya, a research scholar in the Department of Civil Engineering, under the guidance of Prof. Arghya Deb.
Objective: To study the role of particle morphology on the rheology of self-compacting fresh concrete.
Tests conducted: Sieve analysis, Tests for material characterization of cement, sand and coarse aggregate, Slump test, V-funnel test (& T5 measurement for segregation potential), J-ring.
DOI: 10.6084/m9.figshare.12389750.v2
title: Digitisation of Yeh and Lindau Photoionisation Cross Section Tabulated Data

description: This document provides a digitised version of the tabulated atomic subshell photoionisation cross section data calculated by Yeh and Lindau (1985). The data from the original paper was manually mined and deposited into an Excel spreadsheet. <br><br>
DOI: 10.6084/m9.figshare.21585921.v1
title: Russulaceae of the Pakaraima Mountains of Guyana. IV. New species forming a distinct lineage of <i>Lactarius</i> subg. <i>Plinthogalus</i>

description: The Neotropics have recently emerged as an important region for studies of tropical ectomycorrhizal (ECM) fungi. Specific neotropical areas with high ECM host tree densities have ECM fungal diversities rivaling those of higher-latitude forests. Some forests of the Guiana Shield are dominated by endemic ECM trees of the Fabaceae, including species of <i>Dicymbe</i> (subfam. Detarioideae), <i>Aldina</i> (subfam. Papilionoideae), and <i>Pakaraimaea</i> (Cistaceae). One of the most species-rich ECM fungal families present in each of these systems is Russulaceae. Long-term sampling in forests in Guyana’s Pakaraima Mountains has revealed a number of species of the Russulaceae genera <i>Lactarius, Lactifluus</i>, and <i>Russula</i>. In this study, we document a previously unknown, distinct lineage of <i>Lactarius</i> subg. <i>Plinthogalus</i> containing eight species from the Guiana Shield. Here, we describe five of these species from Guyana as new to science: <i>Lactarius humiphilus, Lactarius mycenoides, Lactarius guyanensis, Lactarius dicymbophilus</i>, and <i>Lactarius aurantiolamellatus</i>. Morphological descriptions, habit, habitat, and known distribution are provided for each new species. Sequence data for the barcode internal transcribed spacer (ITS) locus are provided for types and most other collections of the new taxa, and a molecular phylogenetic analysis based on the ITS, 28S, and <i>RPB2</i> (second-largest subunit of the RNA polymerase II) loci across the genus <i>Lactarius</i> corroborates their morphology-based infrageneric placement. The discovery of this lineage changes our insights into the biogeography and evolutionary history of <i>Lactarius</i> subg. <i>Plinthogalus</i>.
DOI: 10.6084/m9.figshare.24222730.v2
title: Data and Do File

description: In this file are the data and the Do File used for the econometric logit model.
DOI: 10.17632/sr9dhcp6fz
title: Prevalence of Emotional and Psychological Behaviours in Post-partum Mothers

description: Numerous mothers face mental and emotional challenges in the postpartum phase, such as postpartum depression and anxiety. Hormonal fluctuations, lack of sleep, and the strain of taking care of a newborn are some of the causes of these problems. Accessing help and treatment remains difficult despite growing awareness. To enhance outcomes for mothers and their infants, as well as to promote maternal mental health, it is imperative to comprehend the prevalence of these issues and the variables that contribute to them. This will enable the development of efficient interventions and support systems. The present research intends to gain insight into the incidence of psychological and emotional tendencies in new mothers. A self-administered questionnaire measuring the emotional and psychological well-being of 247 postpartum mothers participated in the study. To guarantee a varied sample, participants were chosen from a variety of sources. The questionnaire included demographic information for mothers aged 22 to 45, as well as questions about emotional experiences throughout the postpartum period. Data gathering took place online. To analyse prevalence rates and investigate the connections between demographic characteristics and emotional outcomes, inferential techniques and descriptive statistics was used. The results of the questionnaire survey showed that 26.58% of new moms frequently experienced emotional and psychological dysfunction, and 17.1% of them continuously had emotional and psychological problems after giving birth. These findings show the incidence and durability of emotional difficulties experienced by postpartum mothers, emphasising the importance of tailored assistance and interventions to promote maternal mental health and well-being during this vital period. The findings indicate a high prevalence of mental health difficulties in this study, which is in accordance with previous studies on mothers' vulnerability at this key period.
DOI: 10.17632/2x65btsysm
title: Terminal Modification, Sequence, Length, and PIWI-Protein Identity Determine piRNA Stability

description: Original autoradiography, microscopy, and Western blotting images from "Terminal Modification, Sequence, Length, and PIWI-Protein Identity Determine piRNA Stability".

Filenames correspond to Figure numbers.
DOI: 10.17632/6cm9wyd5g5
title: Educational Attainment in North Carolina Public Schools: Use of statistical modeling, data mining techniques, and machine learning algorithms to explore 2014-2017 North Carolina Public School datasets.

description: The purpose of data mining analysis is always to find patterns of the data using certain kind of techiques such as classification or regression. It is not always feasible to apply classification algorithms directly to dataset. Before doing any work on the data, the data has to be pre-processed and this process normally involves feature selection and dimensionality reduction. We tried to use clustering as a way to reduce the dimension of the data and create new features. Based on our project, after using clustering prior to classification, the performance has not improved much. The reason why it has not improved could be the features we selected to perform clustering are not well suited for it. Because of the nature of the data, classification tasks are going to provide more information to work with in terms of improving knowledge and overall performance metrics. From the dimensionality reduction perspective: It is different from Principle Component Analysis which guarantees finding the best linear transformation that reduces the number of dimensions with a minimum loss of information. Using clusters as a technique of reducing the data dimension will lose a lot of information since clustering techniques are based a metric of 'distance'. At high dimensions euclidean distance loses pretty much all meaning. Therefore using clustering as a "Reducing" dimensionality by mapping data points to cluster numbers is not always good since you may lose almost all the information. From the creating new features perspective: Clustering analysis creates labels based on the patterns of the data, it brings uncertainties into the data. By using clustering prior to classification, the decision on the number of clusters will highly affect the performance of the clustering, then affect the performance of classification. If the part of features we use clustering techniques on is very suited for it, it might increase the overall performance on classification. For example, if the features we use k-means on are numerical and the dimension is small, the overall classification performance may be better. We did not lock in the clustering outputs using a random_state in the effort to see if they were stable. Our assumption was that if the results vary highly from run to run which they definitely did, maybe the data just does not cluster well with the methods selected at all. Basically, the ramification we saw was that our results are not much better than random when applying clustering to the data preprocessing. Finally, it is important to ensure a feedback loop is in place to continuously collect the same data in the same format from which the models were created. This feedback loop can be used to measure the model real world effectiveness and also to continue to revise the models from time to time as things change.
DOI: 10.17632/z2fp5kbgbh
title: Tracking Plant Growth Using Image Sequence Analysis- Datasets

description: This dataset consists of five subsets with annotated images in COCO format, designed for object detection and tracking plant growth:
1. Cucumber_Train Dataset (for Faster R-CNN)
- Includes training, validation, and test images of cucumbers from different angles.
- Annotations: Bounding boxes in COCO format for object detection tasks.

2. Tomato Dataset
- Contains images of tomato plants for 24 hours at hourly intervals from a fixed angle.
- Annotations: Bounding boxes in COCO format.

3. Pepper Dataset
- Contains images of pepper plants for 24 hours at hourly intervals from a fixed angle.
- Annotations: Bounding boxes in COCO format.

4. Cannabis Dataset
- Contains images of cannabis plants for 24 hours at hourly intervals from a fixed angle.
- Annotations: Bounding boxes in COCO format.

5. Cucumber Dataset
- Contains images of cucumber plants for 24 hours at hourly intervals from a fixed angle.
- Annotations: Bounding boxes in COCO format.

This dataset supports training and evaluation of object detection models across diverse crops.
DOI: 10.6084/m9.figshare.11309570.v1
title: Astec-half-Pm1 (Cut at 2-cell stage, half Phallusia mammillata embryo, live SPIM imaging, stages 6-16)

description: Astec-half-Pm1 Live embryonic development of Phallusia mammillata (Phlebobranch ascidian). <br><br><br>Cell membranes were fluorescently labeled by microinjection of mRNA encoding PH-tdtomato and KTR-Clover into unfertilized egg. The embryo has been live imaged with a MuVi-SPIM for four hours, from the WT equivalent 32-cell stage (Tp 0, St. 6) up to the WT equivalent late Neurula (Tp 150, St. 16), at 18°C. <br><br>Whole cells were segmented using the ASTEC pipeline. <br><br>* The four angle fusion images obtained using the ASTEC pipeline are shared in .inr format (fuse.tar.gz archive file).<br>* Whole cells were segmented using the ASTEC pipeline and shared in .inr format (post.tar.gz archive file).<br>* Individual cell geometric properties are shared in pkl formats (properties.tar.gz archive file).
DOI: 10.17632/6nr7symnjj
title: DermoCC-GAN dataset

description: This repository contains the image dataset and the scripts used to develop the DermoCC-GAN for standardizing dermatological images:
- Salvi M., Branciforti F., Veronese F., Zavattaro E., Tarantino V., Savoia P., and Meiburger K. M. , "DermoCC-GAN: A new approach for standardizing dermatological images using generative adversarial networks", Computer Methods and Programs in Biomedicine 2022

Abstract:
Dermatological images are typically diagnosed based on visual analysis of the skin lesion acquired using a dermoscope. However, the final quality of the acquired image is highly dependent on the illumination conditions during the acquisition phase. This variability in the light source can affect the dermatologist's diagnosis and decrease the accuracy of computer-aided diagnosis systems. Color constancy algorithms have proven to be a powerful tool to address this issue by allowing the standardization of the image illumination source, but the most commonly used algorithms still present some inherent limitations due to assumptions made on the original image.
In this work, we propose a novel Dermatological Color Constancy Generative Adversarial Network (DermoCC-GAN) algorithm to overcome the current limitations by formulating the color constancy task as an image-to-image translation problem. By training the generative adversarial network with a custom heuristic algorithm that performs well on the training set, the model learns the domain transfer task (from original to standardized image) and is then able to accurately apply the color constancy on test images characterized by different illumination conditions. The proposed algorithm outperforms state-of-the-art color constancy algorithms for dermatological images in terms of normalized median intensity and when using the color-normalized images in a deep learning framework for lesion classification (accuracy of the seven-class classifier: 79.2%) and segmentation (dice score: 90.9%). In addition, we validated the proposed approach on two different external datasets with highly satisfactory results.
The novel strategy presented here shows how it is possible to generalize a heuristic method for color constancy for dermatological image analysis by training a GAN. The overall approach presented here can be easily extended to numerous other applications.
DOI: 10.17632/gy8v292647
title: Laboratory tests in the adult gender-expansive population

description: Supplementary file 1: Data for serum/plasma laboratory tests with sex-specific reference intervals performed on patients with sexual orientation/gender identity (SOGI) field differences for legal sex/sex assigned at birth (SAAB)/gender identity (GI) in the electronic medical record (EMR) at the University of Iowa Hospitals and Clinics from January 1, 2021 to December 31, 2021. The data elements include: deidentified patient number, age (years) at time of laboratory testing, location type (outpatient, inpatient, or emergency department) at time of specimen collection, legal sex in EMR, SAAB in EMR, GI in EMR, presence of SOGI mismatch (yes/no), change of legal sex in EMR, gender-affirming gonadectomy (yes/no), GI from chart review, gender-affirming hormone and route of administration, values for tests for 17 laboratory tests, and how the values of these 17 laboratory tests were relative to age-matched reference intervals for cisgender men and women. Assays details and reference intervals are summarized in Supplemental file 3. Chart review for SOGI fields previously reported [1]. There are a total of 1,166 unique patients (all 18.0 years or older) and 7,530 laboratory tests. Supplementary file 2: Data for plasma creatinine performed for patients 18.0 years or older taking gender-affirming estradiol or testosterone at the University of Iowa Hospitals and Clinics from January 1, 2021 to December 31, 2021. The data elements include: deidentified patient number, age (years) at time of laboratory testing, location type at time of specimen collection, legal sex in EMR, SAAB in EMR, GI in EMR, GI from chart review, gender-affirming hormone and route of administration, self-declared race in EMR (African-American or not), plasma creatinine (mg/dL), estimated glomerular filtration rate (eGFR) calculation using female sex and the 2021 CKD-EPI equation without race refit, eGFR using male as sex, and chronic kidney disease (CKD) stage using either female or male as sex. eGFR equation and CKD stages are from references 2 and 3, respectively. There are a total of 620 unique patients and 1,469 plasma creatinine values. Supplementary file 3: Includes Supplemental Table 1 with details on laboratory assay and Supplemental Table 2 with reference intervals for the laboratory tests analyzed. Data tabs for Supplemental Files 1 and 2 include one for primary data and another defining abbreviations. [1] N.G. Hines et al, Patterns of gender identity data within electronic health record databases can be used as a tool for identifying and estimating the prevalence of gender-expansive people, JAMIA Open 6 (2) (2023) ooad042. DOI: 10.1093/jamiaopen/ooad042. [2] C. Delgado et al., A Unifying Approach for GFR Estimation: Recommendations of the NKF-ASN Task Force on Reassessing the Inclusion of Race in Diagnosing Kidney Disease, Am J Kidney Dis 79 (2) (2022) 268-288 e261. DOI: 10.1053/j.ajkd.2021.08.003. [3] Kidney Int Suppl (2011) 3 (1) (2013) 5-14.
DOI: 10.17632/ntwr9fwh5t
title: Data for: Facilitating student engagement through the flipped learning approach in K-12: A systematic review

description: This dataset contains a bibliography of the 107 included studies for the article “Facilitating student engagement through the flipped learning approach in K-12: A systematic review”. The corpus consists of articles retrieved from ERIC, Web of Science, Scopus, ProQuest, PsycINFO, Teacher Reference Center and Education Source, and published from 2012-2018 using an explicit and replicable search strategy, outlined in the article.
DOI: 10.6084/m9.figshare.22679116.v5
title: Deep Online Recommendations for Connected E-taxis by Coupling Trajectory Mining and Reinforcement Learning

description: This is the raw experiments data and codes of the paper "Deep Online Recommendations for Connected E-taxis by Coupling Trajectory Mining and Reinforcement Learning"
DOI: 10.6084/m9.figshare.12461774.v1
title: Untitled Item

description: XPS, XRD and indentation characterizations.
DOI: 10.17632/4tt4hcmxr4
title: Salt-responsive Metabolite, beta-hydroxybutyrate, Attenuates Hypertension

description: Salt-responsive Metabolite, beta-hydroxybutyrate, Attenuates Hypertension Chakraborty, S1, Galla, S1, Cheng X1, Yeo, J1, Mell, B1, Singh V1, Yeoh BS1, Saha P1, Mathew, AV2, Vijay-Kumar, M1, Joe B*1. 1Program in Physiological Genomics, Microbiome Consortium, Center for Hypertension and Personalized Medicine, Department of Physiology and Pharmacology, University of Toledo College of Medicine and Life Sciences, Toledo, OH, USA. 2 Department of Internal Medicine-Nephrology, University of Michigan, Ann Arbor, MI, USA. *Corresponding Author: Bina Joe, bina.joe@utoledo.edu Summary Dietary salt reduction and exercise are lifestyle modifications prescribed for salt-sensitive hypertensives. While exercise is known to have prominent metabolic effects, such effects of lower dietary salt are just emerging. Studies indicate that salt has adverse effect on metabolic syndrome, of which, hypertension is a hallmark. We hypothesized that dietary salt impacts metabolism in a salt-sensitive model of hypertension. Untargeted metabolomic profiling of rats with differential salt (NaCl) diets revealed that a high salt-induced increase in blood pressure was associated with lower circulating levels of the ketone body, beta-hydroxybutyrate (βOHB). Specific rescue of the βOHB levels by nutritional supplementation of its precursor, 1,3-butanediol attenuated hypertension and protected kidney disease despite the high salt intake. This beneficial effect of βOHB was observed independent of the gut-microbiotal effects of salt or the Th17-mediated renal effects. Instead, the mechanism for the observed renoprotective effect of βOHB on salt-sensitive hypertension was the βOHB-mediated inhibition of the pro-inflammatory cascade by the Nlrp3 inflammasome. In summary, the juxtaposed effects of dietary salt and exercise on salt-sensitive hypertension, which decrease and increase βOHB respectively, indicates that nutritional supplementation of a precursor of βOHB could be considered to provide a similar benefit to salt-sensitive hypertension as exercise.
DOI: 10.17632/m7jwxtjttr
title: Challenges of Artisanal Fishermen: A Case Study from Sonadia Island, Bangladesh

description: The southern part of Bangladesh is positioned on the orifice of Bay of Bengal and is abundant with marine fisheries' huge potential. Whereas marine resources are considered one of the essential sources of future economic development for many countries, Bangladesh is still lagging in this regard. The country cannot materialise full potentials of marine fisheries since more than 90% of fishers use artisanal fishing equipment, and the reasons behind being artisanal fishers are multifaceted. However, it is crucial to know the challenges of artisanal fishers in achieving Sustainable Development Goals (SDGs). This study explored the challenges associated with artisanal fisheries and finds out the solution to help achieve SDGs by providing recommendations. This study was conducted in one of the islands in Bangladesh's coastal area named Sonadia Island to unveil the challenges. Mainly primary data was collected through questionnaire and focus group discussion with the local government elected representative, fishermen association leader, representative of civil society and Upazila level government officials. Secondary data was used to analyse the regulatory and institutional framework. The targets of SDGs were aligned with the importance of artisanal fisheries and the rights of the fishermen. Piracy, local credit system, and complex market chain were identified as significant challenges. Pro-activeness of different government departments can improve the scenario drastically.
DOI: 10.25420/britishmuseum.26166208.v1
title: Focus group discussion

description: Shona transcript of a focus group discussion held at Great Zimbabwe with stonemasons, archaeologists, academics and community elders
DOI: 10.6084/m9.figshare.28696849.v1
title: The genus <i>Artomyces</i> (Auriscalpiaceae, Basidiomycota) from the Gaoligong Mountains and adjacent areas, southwestern China

description: Three new species of <i>Artomyces</i> from the Gaoligong Mountains and adjacent areas of southwestern China, namely, <i>A. brunneoalbus, A. hirtipes</i>, and <i>A. pteruloides</i>, are described based on morphological characteristics, molecular phylogenetic evidence, and ecological traits. Two other species described recently, <i>A. niveus</i> and <i>A. yunnanensis</i>, have also been identified in the same area. In addition, the occurrence of <i>A. pyxidatus</i> in southwestern China and North Macedonia was confirmed. Our study indicated that the species diversity of <i>Artomyces</i> is relatively high in East Asia. To date, seven species of <i>Artomyces</i> have been reported from the region, including the aforementioned species and <i>A. microsporus</i>. Given the diversity of forest ecosystems, from tropical to temperate areas in China, additional species of the genus could be revealed in the future.
DOI: 10.6084/m9.figshare.969694.v3
title: Inductive Reasoning Developmental Test Dataset

description: This dataset contains the asnwers of 1,459 Brazilians to the Inductive Reasoning Developmental Test (IRDT). The participants were aged between 5 to 86 years (M = 15.75, SD = 12.21), being 52.5% women and 47.5% men. The IRDT is a 56 items test (pencil-and-paper) constructed to measure seven stages of inductive reasoning, based on the Model of Hierarquical Complexity.
DOI: 10.17632/7gr395vffc
title: Dataset – Relationship between Eco-efficiency and Circular Economy

description: This Excel file contains the data resulting from a systematic literature review and thematic analysis on the relationship between eco-efficiency and the circular economy. It includes selected academic texts and references, coded according to key thematic categories. Each entry is accompanied by bibliographic details and interpretative notes. The dataset was used to identify patterns, gaps, and intersections in the existing literature.