Find research datasets worth reusing

opencc-by-4.0Jun 2015View details →

Figure 4 in Inter-oceanic comparison of planktonic copepod ecology (vertical distribution, abundance, community structure, population structure and body size) between the Okhotsk Sea and Oyashio region in autumn

Figure 4. Copepod species composition (centre) and copepodid stage structures of the dominant species (left: Oyashio region, right: Okhotsk Sea). All data are integrated means of a 0– 500 m water column based on the IONESS samples in the Oyashio region (St. 19) and Okhotsk Sea (St. OK24) from October to November 1996. Error bars for the copepodid stage indicate standard deviations of each daily duplicate.

opencc-by-4.0Jun 2015View details →

Figure 3 in Inter-oceanic comparison of planktonic copepod ecology (vertical distribution, abundance, community structure, population structure and body size) between the Okhotsk Sea and Oyashio region in autumn

Figure 3. Vertical distribution of zooplankton biovolume in the Oyashio region (upper panels) and Okhotsk Sea (lower panels) from September to December in 1996–1998. Note that the biovolume axes are not the same between panels. Tc: thermocline.

opencc-by-4.0Nov 2020View details →

Holocene regional population dynamics and climatic trends in the Near East: a first comparison using archaeo-demographic proxies (dataset and R scripts)

The present digital archive is the outcome of the paper: Palmisano, A., Lawrence, D., de Gruchy, M.W., Bevan, A., and Shennan, S., 2021. <a href="https://doi.org/10.1016/j.quascirev.2020.106739">Holocene regional population dynamics and climatic trends in the Near East: a first comparison using archaeo-demographic proxies</a>. Quaternary Science Reviews, 252. The dataset included here provides a collection of 10,606 radiocarbon dates, 1884 sites from archaeological surveys (1336 from Central Anatolia and 478 from Upper Mesopotamia) and 16 palaeoclimatic records for a period spanning between 14,000 and 2500 BP. In addition, the digital archive related to this paper provides reproducible analyses in the form of four scripts written in R statistical computing language. List of versions: <ul> <li>2.0. 15 December 2020 — Includes a few minor error corrections (the files 'References.txt' within the folder csv and the script 'radiocarbon.R').</li> <li>1.0  28 November 2020 — First public release of the dataset on Zenodo.</li> </ul>

opencc-by-4.0Dec 2023View details →

Fat oxidation rates and cardiorespiratory responses during exercise in different subject populations with post-acute sequelae of SARS-CoV-2 infection: a comparison with normative percentile values

INTRODUCTION: Post-acute sequelae of SARS-CoV-2 infection (PASC) presents a spectrum of symptoms following acute COVID-19, with exercise intolerance being a prevalent manifestation likely linked to disrupted oxygen metabolism and mitochondrial function. This study aims to assess maximal fat oxidation (MFO) and exercise intensity at MFO (FATmax) in distinct PASC subject groups and compare these findings with normative data. METHODS: Eight male subjects with PASC were involved in this study. The participants were divided in two groups: “endurance-trained” subjects (V̇O2max > 55 ml/min/kg) and “recreationally-active” subjects (V̇O2max < 55 ml/min/kg). Each subject performed a graded exercise test until maximal oxygen consumption (V̇O2max) to measure fat oxidation. Subsequently, MFO was assessed and FATmax calculated as the ratio between V̇O2 at MFO and V̇O2max. RESULTS: The MFO and FATmax of “endurance-trained” subjects were 0.85, 0.89, 0.71 and 0.42, and 68%, 69%, 64% and 53%, respectively. Three out of four subjects showed both MFO and FATmax values placed over the 80th percentile of normative data. The MFO and FATmax of “recreationally-active” subjects were 0.34, 0.27, 0.35 and 0.38, and 47%, 39%, 43% and 41%, respectively. All MFO and FATmax values of those subjects placed below the 20th percentile or between the 20th and 40th percentile. DISCUSSION: Significant differences in MFO and FATmax values between 'endurance-trained' and “recreationally-active” subjects suggest that specific endurance training, rather than simply an active lifestyle, may provide protective effects against alterations in mitochondrial function during exercise in subjects with PASC.

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A comparison of density estimation methods for monitoring marked and unmarked animal populations

These data were generated to compare different methods of estimating population density from marked and unmarked animal populations. We compare conventional live trapping with two more modern, non-invasive field methods of population estimation: genetic fingerprinting from hair-tube sampling and camera trapping for the European pine marten (Martes martes). We used arrays of camera traps, live traps, and hair tubes to collect the relevant data in the Ring of Gullion in Northern Ireland. We apply marked spatial capture-recapture models to the genetic and live trapping data where individuals were identifiable, and unmarked spatial capture-recapture (uSCR), distance sampling (CT-DS), and random encounter models (REM) to the camera trap data where individual ID was not possible. All five approaches produced plausible and relatively consistent point estimates (0.41 – 0.99 animals per km2), despite differences in precision, cost, and effort being apparent. In addition to the data, we provide novel code for running unmarked spatial capture-recapture (uSCR) and random encounter models (REM) to the camera trap data where individual ID was not possible.

opencc-zeroMay 2022View details →

Data for Survival probabilities of atmospheric particles: comparison based on theory, cluster population simulations, and observations in Beijing

Data for Survival probabilities of atmospheric particles: comparison based on theory, cluster population simulations, and observations in Beijing (https://doi.org/10.5194/acp-2022-484) Contact Santeri Tuovinen (santeri.tuovinen@helsinki.fi) for more details.

Fig. 5 in Comparison of sampling methodologies and estimation of population parameters for a temporary fish ectoparasite

Fig. 5. Histograms of emergence counts from the time-series emergence traps. Count bars for each day are subdivided by individual trap.

Fig. 4 in Comparison of sampling methodologies and estimation of population parameters for a temporary fish ectoparasite

Fig. 4. Scatterplot showing total body length in mm versus estimated volume of blood and plasma extracted in Ml. The box-and-whisker plots are centered on the mean body length for each of the three juvenile stages. The box edges are placed at the 2nd and 3rd quartiles for volume estimates and the whiskers show extreme minimum and maximum volumes. The mean estimate of extracted volume by juvenile stage is shown as a labeled dashed-red horizontal line. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Fig. 1 in Comparison of sampling methodologies and estimation of population parameters for a temporary fish ectoparasite

Fig. 1. Traps used in the first study. (A) Small emergence trap, (B) fish-baited emergence trap, (C) fish-baited tripod, (D) open-mesh fish-baited trap and (E) lighted plankton trap. Note that the sample container holding a small French grunt fish for the fish-baited emergence trap (B) and the fish-baited tripod trap (C) are identical units other than the sealed floats attached to the top of the sample container when used with the fish-baited emergence trap.

Fig. 2 in Comparison of sampling methodologies and estimation of population parameters for a temporary fish ectoparasite

Fig. 2. Traps used in the second study. The lighted plankton trap, in the left foreground, stands on short legs—four large emergence traps can be seen in the middleground to the right of the lighted plankton trap. A second lighted plankton trap in the background can be seen towards the center of the frame.

Fig. 3 in Comparison of sampling methodologies and estimation of population parameters for a temporary fish ectoparasite

Fig. 3. Scatterplots of total body length in mm plotted against eye length in mm along the long axis. The upper plot shows measurements for zuphea and the lower plot for praniza. The body length cutoff values separating juvenile stages are shown as a dotted-green line. Gnathiids collected from emergence traps are seen as gold-filled squares and those collected from light traps are presented as purple-filled triangles. Differences in the ontological sampling bias of these two trap designs can be seen by comparing the two scatterplots. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Fig. 6 in Comparison of sampling methodologies and estimation of population parameters for a temporary fish ectoparasite

Fig. 6. Histograms of trap counts by sample day and juvenile stage. The upper histograms show counts from emergence traps and the lower histograms show counts from light traps. Mean count for each histogram is shown as a dashed horizontal line. See text for an explanation of the number of sampling days shown in each plot.

opencc-by-4.0Nov 2018View details →

Comparison and Assessment of Family- and Population-based Genotype Imputation Methods in Large Pedigrees Dataset

Here is the data corresponding to the paper "Comparison and Assessment of Family- and Population-based Genotype Imputation Methods in Large Pedigrees" submitted to Genome Research.  The data includes the following: Simulated data for 1200 African and European subjects in pedigrees. Lists of subjects selected by each of the 4 subject selection methods examined; Primus, GIGI-Pick, Exome-Picks, and Random selection.  The positions of sparse markers for gl_auto for African and European data. The lists of GWAS SNPs for AFR and EUR.  Please see the paper for further details of the data generation, this metadata will be updated following publication.

opencc-by-4.0Sep 2019View details →

14-day smartphone ambulatory assessment of depression symptoms and mood dynamics in a general population sample: comparison with the PHQ-9 depression screening

This dataset contains 14 days of ambulatory assessment (AA) depression symptoms and mood ratings with timestamps, a retrospective Patient Health Questionnaire (PHQ-9) assessment and the demographic variables age and gender. The AA was conducted with users of the mobile mental health / depression screening app "Moodpath". ICD-10 depression symptoms were assessed with the following questions: ICD-10 symptom 1: "depressed mood" q1 = Are you feeling depressed? q2 = Are you feeling hopeless? ICD-10 symptom 2: "loss of interest and enjoyment" q3 = Do you feel like you are not interested in anything right now? q4 = Do you have less pleasure in doing things you usually enjoy? ICD-10 symptom 3: "increased fatigability" q5 = Do you currently have considerably less energy?  q6 = Are your everyday tasks making you very tired currently? ICD-10 symptom 4: "reduced concentration and attention" q11 = Is it hard for you to make decisions currently?  q12 = Is it hard for you to concentrate currently? ICD-10 symptom 5: "reduced self-esteem and self-confidence" q7 = Is your self-confidence clearly lower than usual? q8 = Are you feeling up to your tasks?   ICD-10 symptom 6: "ideas of guilt and unworthiness" q9 = Are you blaming yourself currently?  q10 = Do you think you are worth less than others right now? ICD-10 symptom 7: "bleak and pessimistic views of the future" q46 = Are you thinking that you will be doing well in the future?  q47 = Are you looking hopefully into the future? ICD-10 symptom 8: "ideas or acts of self-harm or suicide" q16 = Are you thinking about death more often than usual?  ICD-10 symptom 9: "disturbed sleep" q13 = Did you sleep badly last night?  ICD-10 symptom 10: "diminished appetite" q14 = Do you have less or no appetite today?

opencc-by-4.0Feb 2013View details →

Figure 1 in Comparison of two morphometric methods for discriminating honey bee (Apis mellifera L.) populations in Turkey

Figure 1. Sampling locations in Turkey (Thrace: 1–2; Aegean: 3; Central Anatolia/ Mediterranean: 4–11; Southeastern Anatolia: 12–13; Northeastern Anatolia: 14–15).

FIGURE 7 in Genetic comparison of populations of Piaractus brachypomus and P. orinoquensis (Characiformes: Serrasalmidae) of the Amazon and Orinoco basins

FIGURE 7 | Discriminant analysis of principal components (DAPC) based in six microsatellite loci of 95 individuals of Piraractus orinoquensis.

FIGURE 6 in Genetic comparison of populations of Piaractus brachypomus and P. orinoquensis (Characiformes: Serrasalmidae) of the Amazon and Orinoco basins

FIGURE 6 | Management units of Piaractus. In Piaractus brachypomus the color blue corresponds to the MUs of the sedimentary basin (1), the color violet represents the south shield MUs (2) and the sky-blue color represents the northern shield MUs (3). Piaractus orinoquensis is represented by a single MU indicated in orange (4).

FIGURE 3 in Genetic comparison of populations of Piaractus brachypomus and P. orinoquensis (Characiformes: Serrasalmidae) of the Amazon and Orinoco basins

FIGURE 3 | Haplotype genealogies of Piaractus orinoquensis. The circle size is proportional to the haplotype frequency. Each line represents a single mutation. Colors correspond to localities.