cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.4121/703fd633-9de8-4977-a05f-4b648cb1e94d.v1
title: Data and code related to the publication: Printed Stretchable Graphene Conductors for Wearable Technology

description: In the publication related to this dataset, we report on the screen printing of stretchable, graphene-based conductors for use in wearable technology. The conductors remained conductive even under 100% strain and demonstrated high fatigue resistance to cyclic strains of 20-50%. Using photonic annealing, the sheet resistance of the printed conductors was reduced from ca 34 Ω □−1 mil−1 to &lt;10 Ω □−1 mil−1, while the stretchability and fatigue resistance were preserved. This dataset contains the data and analysis scripts needed to reproduce the findings in the study.
DOI: 10.6084/m9.figshare.24511789
title: Supplementary Table 1 to: “Functional diversity of fungal communities across mixed forest plantations depends on soil chemical-biological variability”

description: This file contains the ASV table with taxonomic annotations.
DOI: 10.6084/m9.figshare.24511789.v1
title: Supplementary Table 1 to: “Functional diversity of fungal communities across mixed forest plantations depends on soil chemical-biological variability”

description: This file contains the ASV table with taxonomic annotations.
DOI: 10.25318/9810052301-fra
title: Langues utilisées au travail selon la première langue officielle parlée et la division de recensement du lieu de travail : Canada, provinces et territoires et divisions de recensement

description: Données sur la langue utilisée le plus souvent au travail selon les autres langues utilisées régulièrement au travail, la première langue officielle parlée et la division de recensement du lieu de travail pour la population active occupée âgée de 15 ans et plus dans les ménages privés au Canada, dans les provinces et territoires et les divisions de recensement.
DOI: 10.15129/0950371c-0dc5-4eea-a7c9-007c135290a5
title: Data for "Online evolution of a phased array by means of an adaptive data acquisition method"

description: Supporting dataset for the publication: "Online evolution of a phased array by means of an adaptive data acquisition method". The file contains all the signals used to produce the images in the paper, using information mentioned in the paper, e.g. pitch and filter centre frequency.
DOI: 10.25318/9810062101-eng
title: Population groups by housing suitability and condition of dwelling: Canada, provinces and territories, census metropolitan areas and census agglomerations

description: Population groups by housing suitability and condition of dwelling for Canada, provinces and territories, census metropolitan areas and census agglomerations. Includes tenure including presence of mortgage payments and subsidized housing (totals include farm operators), gender and primary household maintainer.
DOI: 10.25824/redu/4ozjmx
title: fitting_dataset.tab

description: :unav
DOI: 10.25824/redu/nabp1k
title: sand_predictive_dataset.tif

description: :unav
DOI: 10.25824/redu/sheggn
title: DI_TP_mask.tif

description: :unav
DOI: 10.25824/redu/sn9cz7
title: di.py

description: :unav
DOI: 10.25824/redu/0fcqxs
title: scientific_colormaps.py

description: :unav
DOI: 10.25824/redu/3hawtr
title: utilities.py

description: :unav
DOI: 10.25824/redu/8ehuas
title: org_p_percent_of_tot.nc4

description: :unav
DOI: 10.25824/redu/enixuk
title: soil_bulk_density.nc

description: :unav
DOI: 10.25824/redu/qdlwtp
title: avail_p_SE.nc4

description: :unav
DOI: 10.25824/redu/t1ar8c
title: LICENCE

description: :unav
DOI: 10.25824/redu/h4e2di
title: predicted_inorg_p.nc4

description: :unav
DOI: 10.25824/redu/i2sfsb
title: inorg_p_percent_of_tot.nc4

description: :unav
DOI: 10.25824/redu/jqfpc9
title: lon_predictive_dataset.tif

description: :unav
DOI: 10.25824/redu/d4obt4
title: slope_predictive_dataset.tif

description: :unav
DOI: 10.25824/redu/i0g44m
title: plot_maps.py

description: :unav
DOI: 10.25824/redu/i8xa0i
title: inorg_p_AVG.nc4

description: :unav
DOI: 10.25824/redu/miba2o
title: total_p_STD.nc4

description: :unav
DOI: 10.25824/redu/ulesau
title: soil_type_with_ID.tab

description: :unav
DOI: 10.25824/redu/xrbw7e
title: org_p_STD.nc4

description: :unav
DOI: 10.25824/redu/7h7kdg
title: table2raster.py

description: :unav
DOI: 10.25824/redu/eojgot
title: partial_dependence_plots.py

description: :unav
DOI: 10.25824/redu/ivboxk
title: org_p_SE.nc4

description: :unav
DOI: 10.25824/redu/qemmob
title: fitting_dataset_one_hot.tab

description: :unav
DOI: 10.25824/redu/rqddvv
title: avail_p_percent_of_tot.nc4

description: :unav
DOI: 10.25824/redu/dgibtv
title: lat_predictive_dataset.tif

description: :unav
DOI: 10.25824/redu/efikg1
title: sd_avg_se_pertot.py

description: :unav
DOI: 10.25824/redu/gwf7wy
title: avail_p_STD.nc4

description: :unav
DOI: 10.25824/redu/mwjjxp
title: toc_predictive_dataset.tif

description: :unav
DOI: 10.25824/redu/oinshj
title: DI_AP_mask.tif

description: :unav
DOI: 10.25824/redu/tgzmof
title: predicted_total_p.nc4

description: :unav
DOI: 10.25824/redu/ce85bc
title: ph_predictive_dataset.tif

description: :unav
DOI: 10.25824/redu/ejdjbu
title: DI_OP_mask.tif

description: :unav
DOI: 10.25824/redu/wut0tg
title: inorg_p_SE.nc4

description: :unav
DOI: 10.25824/redu/xvqxcl
title: org_p_density.nc4

description: :unav
DOI: 10.25824/redu/yc3hwb
title: Makefile

description: :unav
DOI: 10.25824/redu/3egq0s
title: silt_predictive_dataset.tif

description: :unav
DOI: 10.25824/redu/8qmw8z
title: predictor_dataset.tab

description: :unav
DOI: 10.25824/redu/gmrmyg
title: avail_p_AVG.nc4

description: :unav
DOI: 10.25824/redu/gyg08i
title: predict_P.py

description: :unav
DOI: 10.25824/redu/qv3mk5
title: total_p_AVG.nc4

description: :unav
DOI: 10.25824/redu/bmelym
title: tn_predictive_dataset.tif

description: :unav
DOI: 10.25824/redu/c3x063
title: predicted_org_p.nc4

description: :unav
DOI: 10.25824/redu/d2zdg6
title: Pmin1_Pocc.nc4

description: :unav
DOI: 10.25824/redu/dnajgb
title: org_p_AVG.nc4

description: :unav
DOI: 10.25824/redu/jcskbo
title: total_p_density.nc4

description: :unav
DOI: 10.25824/redu/wiocmb
title: predicted_min-occ_over_total_p.nc4

description: :unav
DOI: 10.25824/redu/1stopk
title: mask.qpj

description: :unav
DOI: 10.25824/redu/7h5ljc
title: map_predictive_dataset.tif

description: :unav
DOI: 10.25824/redu/xalvid
title: mask.zip

description: :unav
DOI: 10.25824/redu/xkmnpx
title: mat_predictive_dataset.tif

description: :unav
DOI: 10.25824/redu/xpie64
title: avail_p_density.nc4

description: :unav
DOI: 10.25824/redu/3rcvrz
title: DI_IP_mask.tif

description: :unav
DOI: 10.25824/redu/5gtgmn
title: requirements.txt

description: :unav
DOI: 10.25824/redu/a9vcqy
title: cell_area.nc

description: :unav
DOI: 10.25824/redu/cheosp
title: predicted_avail_p.nc4

description: :unav
DOI: 10.25824/redu/tttkln
title: clay_predictive_dataset.tif

description: :unav
DOI: 10.25824/redu/hd4pxm
title: total_p_SE.nc4

description: :unav
DOI: 10.25824/redu/kllvhl
title: README.md

description: :unav
DOI: 10.25824/redu/nibkaz
title: rforest_pfracs.py

description: :unav
DOI: 10.25824/redu/o1octw
title: inorg_p_density.nc4

description: :unav
DOI: 10.25824/redu/zw4ibn
title: final_dataset_pred_DI_Pforms.tab

description: :unav
DOI: 10.25824/redu/ep9uki
title: var_importances.py

description: :unav
DOI: 10.25824/redu/fcf5pn
title: P_quantiles.py

description: :unav
DOI: 10.25824/redu/fyavqp
title: soil_type_agg.tif

description: :unav
DOI: 10.25824/redu/ofkmwt
title: inorg_p_STD.nc4

description: :unav
DOI: 10.25824/redu/ownn7i
title: DI_ALL.asc

description: :unav
DOI: 10.25824/redu/tvobrs
title: README.pdf

description: :unav
DOI: 10.25824/redu/74yc8o
title: README.md

description: :unav
DOI: 10.25824/redu/mpfswm
title: elevation_predictive_dataset.tif

description: :unav
DOI: 10.25824/redu/obvne9
title: README.pdf

description: :unav
DOI: 10.25824/redu/ugpxxb
title: wrb_soil_type.tab

description: :unav
DOI: 10.25824/redu/wayepa
title: mask-1.zip

description: :unav
DOI: 10.25824/redu/4jfx0q
title: DI_mask_inorg_p.asc

description: :unav
DOI: 10.25824/redu/c0dhup
title: org_p_SD.nc

description: :unav
DOI: 10.25824/redu/dq3qhf
title: mineral_p_area_density.nc

description: :unav
DOI: 10.25824/redu/ktuzxq
title: total_p.nc

description: :unav
DOI: 10.25824/redu/mqtzoh
title: results.tab

description: :unav
DOI: 10.25824/redu/zs1aaz
title: README.md

description: :unav
DOI: 10.25824/redu/er8ktb
title: occ_p_AVG.nc

description: :unav
DOI: 10.25824/redu/kfit08
title: avail_p_SD.nc

description: :unav
DOI: 10.25824/redu/ldm7bk
title: DI_org_p.asc

description: :unav
DOI: 10.25824/redu/sce6zj
title: inorg_p_area_density.nc

description: :unav
DOI: 10.25824/redu/tokzmm
title: avail_p_AVG.nc

description: :unav
DOI: 10.25824/redu/0gqdts
title: inorg_p_SE.nc

description: :unav
DOI: 10.25824/redu/8kwfe4
title: DI_mask_org_p.asc

description: :unav
DOI: 10.25824/redu/ode53r
title: avail_p_area_density.nc

description: :unav
DOI: 10.25824/redu/uqywx6
title: total_p_AVG.nc

description: :unav
DOI: 10.25824/redu/xyh5v0
title: occ_p_area_density.nc

description: :unav
DOI: 10.25824/redu/b9mtlh
title: fitting_dataset.tab

description: :unav
DOI: 10.25824/redu/hqrnm8
title: total_p_area_density.nc

description: :unav
DOI: 10.25824/redu/oxymyu
title: DI_total_p.asc

description: :unav
DOI: 10.25824/redu/tdtpfi
title: DI_avail_p.asc

description: :unav
DOI: 10.25824/redu/uyot53
title: org_p.nc

description: :unav
DOI: 10.25824/redu/61cqof
title: inorg_p.nc

description: :unav
DOI: 10.25824/redu/a0evgv
title: avail_p_percentage_of_total_p.nc

description: :unav
DOI: 10.25824/redu/elbaaj
title: inorg_p_percentage_of_total_p.nc

description: :unav
DOI: 10.25824/redu/gvar4d
title: DI_mask_occ_p.asc

description: :unav
DOI: 10.25824/redu/igdroy
title: total_p_SD.nc

description: :unav
DOI: 10.25824/redu/441cnu
title: DI_mask_total_p.asc

description: :unav
DOI: 10.25824/redu/5vy1ag
title: occ_p.nc

description: :unav
DOI: 10.25824/redu/e4w64b
title: mineral_p_percentage_of_total_p.nc

description: :unav
DOI: 10.25824/redu/tkfzss
title: inorg_p_SD.nc

description: :unav
DOI: 10.25824/redu/tqt9ow
title: total_p_SE.nc

description: :unav
DOI: 10.25824/redu/xnxz3y
title: DI_mask_avail_p.asc

description: :unav
DOI: 10.25824/redu/ctcff6
title: inorg_p_AVG.nc

description: :unav
DOI: 10.25824/redu/g2977v
title: avail_p.nc

description: :unav
DOI: 10.25824/redu/st787p
title: org_p_SE.nc

description: :unav
DOI: 10.25824/redu/wmauxe
title: org_p_AVG.nc

description: :unav
DOI: 10.25824/redu/x6soqy
title: occ_p_percentage_of_total_p.nc

description: :unav
DOI: 10.25824/redu/ybvfky
title: occ_p_SE.nc

description: :unav
DOI: 10.25824/redu/4ltxwk
title: DI_occ_p.asc

description: :unav
DOI: 10.25824/redu/63asue
title: mineral_p.nc

description: :unav
DOI: 10.25824/redu/atue3y
title: org_p_percentage_of_total_p.nc

description: :unav
DOI: 10.25824/redu/i44qtm
title: DI_mask_ALL.asc

description: :unav
DOI: 10.25824/redu/phjo3l
title: DI_inorg_p.asc

description: :unav
DOI: 10.25824/redu/zye8zy
title: README.pdf

description: :unav
DOI: 10.25824/redu/6mg2jf
title: occ_p_SD.nc

description: :unav
DOI: 10.25824/redu/qaf5ep
title: org_p_area_density.nc

description: :unav
DOI: 10.25824/redu/qcn13o
title: avail_p_SE.nc

description: :unav
DOI: 10.25318/9810062101-fra
title: Groupes de population selon la taille convenable du logement et l'état du logement : Canada, provinces et territoires, régions métropolitaines de recensement et agglomérations de recensement

description: Groupes de population selon la taille convenable du logement et l'état du logement pour le Canada, les provinces et les territoires, les régions métropolitaines de recensement et les agglomérations de recensement. Comprend le mode d'occupation incluant la présence de paiements hypothécaires et logement subventionné (les totaux comprennent les exploitants agricoles), le genre et le principal soutien du ménage.
DOI: 10.4121/e3b31ece-cc88-4638-be10-8ccdd4c5f2f7.v1
title: The Growing Strawberries Dataset

description: The Growing Strawberries Dataset (GSD) is a curated multiple-object tracking dataset inspired by the growth monitoring of strawberries. The frames were taken at hourly intervals by six cameras for in total of 16 months in 2021 and 2022, covering 12 plants in two greenhouses respectively. The dataset consists of hourly images collected during the cultivation period, bounding box (bbox) annotations of strawberry fruits, and precise identification and tracking of strawberries over time. GSD contains two types of images - RGB (color) and OCN (orange, cyan, near-infrared). These images were captured throughout the cultivation period. Each image sequence represents all the images captured by one camera during the year of cultivation. These sequences are named using the format "&lt;RGB/OCN-1/2/3-2021/2022&gt;." In addition, a small sample captured by one of the RGB cameras is included, featuring images and annotations from a two-day period, along with a demo video spanning seven days. The ground-truth annotations of the bbox and trajectories of strawberries are provided with a coco-format JSON file and a TXT file for compatibility with the MOT Challenge evaluation tools. Images that were too dark for annotations are also available upon request.
DOI: 10.18712/nsd-nsd3130-v2
title: Inflammation, the kynurenines and mucosal injury during human experimental enterotoxigenic Escherichia coli infection

description: Enterotoxigenic Escherichia coli (ETEC) is an important cause of children’s and travelers’ diarrhea, especially in low- and middle-income countries. ETEC is a non-invasive gut pathogen, colonizing the small intestinal wall before secreting diarrhea-inducing enterotoxins. We sought to investigate the impact of ETEC infection on local and systemic host defenses by examining plasma markers of inflammation and mucosal injury, as well as kynurenine pathway metabolites.

Plasma from 21 volunteers experimentally infected with ETEC, were collected before and 1, 2, 3, and 7 days after ingesting the ETEC dose, grouped according to the level of intestinal ETEC proliferation: 14 volunteers experienced substantial proliferation (SP) and 7 had low proliferation (LP). Plasma markers of inflammation, kynurenine pathway metabolites, and related cofactors (vitamins B2 & B6) were quantified by using targeted mass spectrometry, while ELISA was used to quantify the mucosal injury markers Reg3a and iFABP.

We found increased concentrations of plasma C-reactive protein (CRP), serum amyloid A (SAA), neopterin, kynurenine/tryptophan ratio (KTR) and Reg3a in the SP group following dose ingestion. Vitamin B6 forms, pyridoxal 5&apos;-phosphate and pyridoxal, and decreased over time in the SP group. CRP, SAA and the pyridoxic acid ratio correlated with ETEC proliferation levels.

The observed changes following experimental ETEC infection indicate that ETEC, despite causing a non-invasive infection, induced systemic inflammation and mucosal injury when proliferating substantially, even in cases without diarrheal symptoms. It is conceivable that ETEC infections, especially when repeated, contribute to the negative health impact on young children living in ETEC-endemic areas.
DOI: 10.5281/zenodo.10075441
title: microcambeva_bendego_decontaminated_FSCR.fasta.gz

description: microcambeva_bendego_decontaminated_FSCR.fasta.gz
DOI: 10.6084/m9.figshare.24511927.v1
title: 所有数据

description: In this work, a multibody system dynamics model of a battery pack is constructed based on the recursive idea, which can characterize the state information of each cell, such as velocity, acceleration, deformation, etc., during extrusion. By utilizing machine learning techniques, it is possible to achieve both the forward and reverse design of the adhesive for the battery pack. This enables accurate prediction of battery deformation under various adhesive stiffness and damping coefficients, as well as different battery SOCs. Consequently, the design of the battery adhesive can be guided, resulting in minimal distortion of the battery pack during extrusion and reducing the risk of internal short circuits.
DOI: 10.14473/csda/ionqlg
title: Naše společnost 2021 - září

description: Výzkum provedl výzkumný tým CVVM Sociologického ústavu AV ČR, v.v.i., v rámci výzkumu „Naše společnost 2022". Sběr dat provedla tazatelská síť CVVM. Předmět výzkumu: Důvěra ústavním institucím v září/říjnu 2021 Občané o vývoji situace v Afghánistánu - září/říjen 2021
DOI: 10.25318/9810062201-eng
title: Population groups by housing suitability and condition of dwelling: Canada, provinces and territories, census divisions and census subdivisions

description: Population groups by housing suitability and condition of dwelling for Canada, provinces and territories, census divisions and census subdivisions. Includes tenure including presence of mortgage payments and subsidized housing (totals include farm operators), gender and primary household maintainer.
DOI: 10.5281/zenodo.10075440
title: microcambeva_bendego_decontaminated_FSCR.fasta.gz

description: microcambeva_bendego_decontaminated_FSCR.fasta.gz
DOI: 10.5281/zenodo.10048049
title: Land, carbon and biodiversity data for supply chain impact calculations

description: Monitoring, halting and reversing land conversion is fundamental to meeting international biodiversity and climate targets, and agriculture is the major driver of land conversion. We present an open access set of global data for calculating land use change impacts of agricultural supply chains. These data, originally prepared for the LandGriffon service, include indicators of deforestation, conversion of natural ecosystems, greenhouse gas emissions, and loss of intact or high integrity ecosystems following international standards and guidelines for reporting and target setting in the agriculture, forestry, and land use sector. In order to assign impacts to agricultural production, we prepare data using a spatial adaptation of the statistical Land Use Change (sLUC) accounting approach distributing impact to human activities across the local area using a 50km radius. The results are high resolution global maps of impact per hectare of land occupation. These can then be combined with land footprint data, cropland extent, or productivity maps to calculate land use change related impacts for specific crop volumes sourced from specific regions. Carbon and deforestation results are validated against FAO statistics at the national level.
DOI: 10.5281/zenodo.10048050
title: Land, carbon and biodiversity data for supply chain impact calculations

description: Monitoring, halting and reversing land conversion is fundamental to meeting international biodiversity and climate targets, and agriculture is the major driver of land conversion. We present an open access set of global data for calculating land use change impacts of agricultural supply chains. These data, originally prepared for the LandGriffon service, include indicators of deforestation, conversion of natural ecosystems, greenhouse gas emissions, and loss of intact or high integrity ecosystems following international standards and guidelines for reporting and target setting in the agriculture, forestry, and land use sector. In order to assign impacts to agricultural production, we prepare data using a spatial adaptation of the statistical Land Use Change (sLUC) accounting approach distributing impact to human activities across the local area using a 50km radius. The results are high resolution global maps of impact per hectare of land occupation. These can then be combined with land footprint data, cropland extent, or productivity maps to calculate land use change related impacts for specific crop volumes sourced from specific regions. Carbon and deforestation results are validated against FAO statistics at the national level.
DOI: 10.5281/zenodo.10075430
title: Land, carbon and biodiversity data for supply chain impact calculations

description: Monitoring, halting and reversing land conversion is fundamental to meeting international biodiversity and climate targets, and agriculture is the major driver of land conversion. We present an open access set of global data for calculating land use change impacts of agricultural supply chains. These data, originally prepared for the LandGriffon service, include indicators of deforestation, conversion of natural ecosystems, greenhouse gas emissions, and loss of intact or high integrity ecosystems following international standards and guidelines for reporting and target setting in the agriculture, forestry, and land use sector. In order to assign impacts to agricultural production, we prepare data using a spatial adaptation of the statistical Land Use Change (sLUC) accounting approach distributing impact to human activities across the local area using a 50km radius. The results are high resolution global maps of impact per hectare of land occupation. These can then be combined with land footprint data, cropland extent, or productivity maps to calculate land use change related impacts for specific crop volumes sourced from specific regions. Carbon and deforestation results are validated against FAO statistics at the national level.
DOI: 10.25381/cput.24271240
title: Factors responsible for motivation of administrative staff in a national government service delivery department.

description: <b>Ethical Clearance reference number: </b>2022 FBMSREC 034Organizations encounter concerns such as absenteeism, workplace conflicts, unproductive employees, and employees suffering from physical and mental illnesses (Hoel, Cooper and Einarsen, 2020:209-234). These problems are interconnected and are almost certainly caused by a lack of employee motivation. Failure to satisfy employee needs are most likely the cause of conflicts with their employees whereas unfair treatment and bias recognition supposedly cause low morale and conflicts with the employer as well as the fellow employees. These needs include fair pay for all employees, safety and security in their workplace as well as for their jobs, equal treatment of employees and more and they are some of the factors that motivate employees in the workplace. The conflicts in the workplace may give rise to negative work environment, which according to Hoel, Cooper and Einarsen, (2020:209-234) can lead to physical and mental problems, absenteeism, and productivity loss. Low morale has a number of negative consequences, including decreased productivity and mental health issues stated by (Gates, Gillespie and Succop, 2011:59-66).Depression affects 264 million people worldwide, according to the World Health Organization (WHO) worldwide and Business in the Community (2019) found that 39 percent of the 4000 employees polled experienced poor mental health the previous year (2018) as a result of their occupations.Because of the significant number of employees who are sad as a result of their jobs, many employees feel unmotivated or miserable at work (Chandrasekar K, 2011:1-19). This threatens organizational performance because according to (Shahzadi, Javed, Pirzada, Nasreen and Khanam, 2014:159-166), employee performance is positively influenced by employee motivation and as found by Rongen, Robroek, van Lenthe and Burdorf, (2013:406-415) low motivation gives rise to absenteeism and reduce productivity.The aforementioned difficulties highlight the necessity for companies, both public and private, to interact with employees to assess their personal needs and how they might be met while attaining corporate objectives.The researcher has used a mixed method approach to evaluate the association between variables because of the nature of the study. A total number of 100 administrative employees of the Department of Public Works and Infrastructure took take part in the study.
DOI: 10.5281/zenodo.10075451
title: monilaria_moniliformis_decontaminated_FSCR.fasta.gz

description: monilaria_moniliformis_decontaminated_FSCR.fasta.gz
DOI: 10.5281/zenodo.10075452
title: monilaria_moniliformis_decontaminated_FSCR.fasta.gz

description: monilaria_moniliformis_decontaminated_FSCR.fasta.gz
DOI: 10.5281/zenodo.10075462
title: INNOVATIVE WAYS TO ASSESS ENGLISH LITERACY IN SCHOOL
DOI: 10.5281/zenodo.10075461
title: INNOVATIVE WAYS TO ASSESS ENGLISH LITERACY IN SCHOOL