Find research datasets worth reusing

opencc-by-4.0Apr 2024View details →

Simulation to optimize the laboratory diagnosis of bacteremia: event times dataset from observational and retrospective studies

<h1>Introduction</h1> Dataset consisting of three .csv files generated from observational and retrospective data analysis for the manuscript titled:   Simulation to optimize the laboratory diagnosis of bacteremia, by Gerada et al. Dataset consists of event time-stamps for blood cultures. All identifiers have been stripped.  <h1>Dataset summary</h1> <ul> <li>observational_data.csv – time-stamps generated from direct observation of blood culture processing. Note that data is in wide format, so that column names contain the event name. Also, events are not related to a particular specimen, therefore, column lengths are not equal. </li> <li>retrospecitve_audit.csv – time-stamps generated from manualk retrospective audit of laboratory information system. Column `Lab` indicates the incubator. Rows are per specimen. </li> <li>retrospective_data.csv – time-stamps pulled automatically from laboratory information system (without manual curation). Rows are per specimen.</li> </ul>

Figure 4 in Calling behavior in virgin females of Diatraea saccharalis (Fabricius, 1794) (Lepidoptera: Crambidae) in laboratory

Figure 4. Calling number of one, two and three- days- old Diatraea saccharalis virgin females. / Número de llamados de hembras vírgenes de Diatraea saccharalis de uno, dos y tres días de edad. * Error bars indicate standard error.

Figure 1 in Calling behavior in virgin females of Diatraea saccharalis (Fabricius, 1794) (Lepidoptera: Crambidae) in laboratory

Figure 1. Temporal pattern of calling behavior exhibited by Diatraea saccharalis females. / Patrón temporal de llamado de hembras de Diatraea saccharalis.

Figure 3 in Calling behavior in virgin females of Diatraea saccharalis (Fabricius, 1794) (Lepidoptera: Crambidae) in laboratory

Figure 3. Call duration of one, two and three days old Diatraea saccharalis females. / Duración de llamado de hembras de uno, dos y tres días de edad de Diatraea saccharalis en laboratorio. * Error bars indicate standard error.

Figure 2 in Calling behavior in virgin females of Diatraea saccharalis (Fabricius, 1794) (Lepidoptera: Crambidae) in laboratory

Figure 2. Diatraea saccharalis calling temporal pattern exhibited by one, two and three-days-old females. / Horario de llamado de hembras de Diatraea saccharalis de uno, dos y tres días de edad en laboratorio.

Figure 5 in Early development of Gongolaria montagnei (Fucales, Phaeophyta) germlings under laboratory conditions, with a view to enhancing restoration potential in the Eastern Mediterranean

Figure 5: Growth of Gongolaria montagnei embryos and germlings during incubation (31 days). Increase in relative growth rates (RGR) was observed in two phases (red lines), from days 8–15 (0.2 day−1) and days 21–31 (0.1 day−1).

Figure 4 in Early development of Gongolaria montagnei (Fucales, Phaeophyta) germlings under laboratory conditions, with a view to enhancing restoration potential in the Eastern Mediterranean

Figure 4: Divisions and developmental stages of Gongolaria montagnei. (A) Zygote after release from the conceptacle. (B) First division. (C) Second, most common, division. (D) Second, rare, division. (E) Development of the rhizoids (arrow). (F) Elongation of the rhizoids. (G) Fertilization membrane (arrow). (H) Hyaline apical hairs. (I) Germling after five weeks of culture. Scale bar = 100 μm.

Figure 2 in Early development of Gongolaria montagnei (Fucales, Phaeophyta) germlings under laboratory conditions, with a view to enhancing restoration potential in the Eastern Mediterranean

Figure 2: Thallus of Gongolaria montagnei during the reproductive period (A, scale bar = 3 cm), mature apical fronds (B, scale bar = 3 cm) and receptacles (C, scale bar = 2 mm).

Figure 1 in Early development of Gongolaria montagnei (Fucales, Phaeophyta) germlings under laboratory conditions, with a view to enhancing restoration potential in the Eastern Mediterranean

Figure 1: Map showing locations (marked with symbols and) where the reproductive phenology of Gongolaria montagnei was followed in sitU from February to May 2021. Mature receptacles were collected at Saronida ().

Figure 3 in Early development of Gongolaria montagnei (Fucales, Phaeophyta) germlings under laboratory conditions, with a view to enhancing restoration potential in the Eastern Mediterranean

Figure 3: Cross section of a receptacle of Gongolaria montagnei, showing antheridia (A) and oogonia (O). Scale bar = 100 μm.

opencc-by-4.0Nov 2024View details →

Simulation and laboratory eddy current testing data - modelling compound defects via perturbation theory

This dataset serves to fit and validate a perturbation approach to the modelling eddy current signals of compound defects. It was obtained during the AIFRI project (Artificial Intelligence for Rail Inspection). The simulation data was generated with the Faraday software by INTEGRATED Engineering Software, using its BEM Solver. The simulation data is supplied as csv. The laboratory data was gathered by Rainer Pohl in the eddy current laboratory of BAM, section 8.4. It is supplied in the DICONDE data format. The first frame of the pixel array in the DICONDE files corresponds to the real part and the second frame corresponds to the imaginary part of the signal. The data set is analyzed in an upcoming article.

opencc-by-4.0Apr 2024View details →

Testing Protocols for Obtaining Reliable PDFs from Laboratory x-ray Sources Using PDFgetX3

In this work, we explored data acquisition protocols and improved data reduction protocols using PDFgetX3 to obtain reliable data for atomic pair distribution function (PDF) analysis from a laboratory-based Mo x-ray source.  A variable counting scheme is described that preferentially counts in the high-angle region of the diffraction pattern. The effects on the resulting PDF are studied by varying the overall count time, the use of Soller slits, and limiting the out-of-plane divergence of the incident beam. The protocols are tested using an amorphous silica and a quartz sample. We also present a modification to the current PDFgetX3 data corrections to take care of sample absorption, which was previously neglected in the use of that program for high-energy synchrotron x-ray data.  We show that, despite limitations in the Q-range and flux of laboratory instruments, reasonable data for PDF model fits may be obtained using the best protocols in a few hours of counting.

opencc-by-4.0May 2024View details →

Data set from: Can laboratory-based XAFS compete with XRD and Mössbauer spectroscopy as a tool for quantitative species analysis?

Abstract: This work investigated the capability of quantitative laboratory X-ray Absorption Fine Structure Spectroscopy (lab-XAFS) via Linear Combination Fitting (LCF) of reference spectra in comparison with quantitative X-ray diffraction (XRD) and Mössbauer spectroscopy. While lab-XAFS already show good results when performing LCF with significant different spectra of the species to be identified, the method is challenging when the reference spectra and possibly species in the sample are very similar as it is the case for α-Fe2O3, γ- Fe2O3 and Fe3O4. For this investigation an iron oxide mineral with origin from Mexico (here named Mexican Magnetite) with different iron oxide phases was used and measured using all three methods.   This data set contains the raw data of the work “Can laboratory-based XAFS compete with XRD and Mössbauer spectroscopy as a tool for quantitative species analysis? Critical evaluation using the example of a natural iron ore” of XAFS, XRD and Mössbauer measurements. This includes XAFS, Mössbauer and XRD spectra of the reference materials α-Fe2O3, Fe3O4 and the sample Mexican magnetite, the XAFS spectra of the reference material γ- Fe2O3 and the XAFS, XRD and Mössbauer spectra of three different α-Fe2O3/Fe3O4 mixtures.   Sample information/sample list sample/references: The sample and the corresponding short cut name used in the data files is listed. Furthermore the method the sample was measured with is also listed. <table> <tbody> <tr> <td> Short cut name </td> <td>  Sample/reference </td> <td> Measured with </td> </tr> <tr> <td> MexicanMagnetite </td> <td>  Iron oxide mineral with origin in Mexico </td> <td> XAFS, XRD, Mössbauer </td> </tr> <tr> <td> Fe2O3 </td> <td> Fe2O3-alpha / Hematite </td> <td> XAFS, XRD, Mössbauer </td> </tr> <tr> <td> Fe3O4 </td> <td> Fe3O4 / Magnetite </td> <td> XAFS, XRD, Mössbauer </td> </tr> <tr> <td> Fe </td> <td> Iron powder </td> <td> XAFS </td> </tr> <tr> <td> Fe2O3-alpha </td> <td> Fe2O3-alpha / Hematite </td> <td> XAFS </td> </tr> <tr> <td> Fe2O3-gamma </td> <td> Fe2O3-gamma / Maghemite </td> <td> XAFS </td> </tr> <tr> <td> 30-70 </td> <td> Mixture of  30 % Fe2O3-alpha/ 70 %Fe3O4 </td> <td> XAFS, XRD, Mössbauer </td> </tr> <tr> <td> 50-50 </td> <td> Mixture of  50 % Fe2O3-alpha/ 50 %Fe3O4 </td> <td> XAFS, XRD, Mössbauer </td> </tr> <tr> <td> 70-30 </td> <td> Mixture of  70 % Fe2O3-alpha/ 30 %Fe3O4 </td> <td> XAFS, XRD, Mössbauer </td> </tr> </tbody> </table>   Mixtures ratios: The prepared Fe2O3-Fe3O4 model mixtures with the weight-in ratios and the actual achieved mass percentage ratio between the two iron species, taken impurities of the used materials into account, are listed below. The short cut name is the name used in the data files (see table above). <table> <tbody> <tr> <td> Short cut name </td> <td> Actual achieved weigh-in ratios m(Fe2O3)/m(Fe3O4)* </td> <td> Actual achieved mass percentage ratios ωrel(Fe2O3) / ωrel(Fe3O4) </td> </tr> <tr> <td> 30-70 </td> <td> 0.31380 g / 0.7059 g </td> <td> 31.8 / 68.2 </td> </tr> <tr> <td> 50-50 </td> <td> 0.5140 g / 0.5174 g </td> <td> 50.6 / 49.4 </td> </tr> <tr> <td> 70-30 </td> <td> 0.7037 g / 0.3041 g </td> <td> 70.5 / 29.5 </td> </tr> </tbody> </table> *the given masses here, ar the masses of the materials of the mixtures before sampel prepration. For the sample prepration the mass  applied on the tape or mixed with wax is about 5-10 mg. Spectrometer Specifications XAFS: The experimental setup for the laboratory XAFS measurement is based on the Highly Annealed Pyrolytic Graphite (HAPG) von Hámos spectrometer with the use of a cylindrically shaped crystal. As detector unit the pixelated X-ray hybrid-CMOS detector Dectris Eiger2 R 500k was used. The area of detection is 77.3 mm x 38.6 mm with a pixel size of 75 µm x 75 µm. The X-ray source was a water-cooled micro focus X-ray tube with molybdenum as anode material, a power of 30 Watt optimised at 15 kV and a spot size of 70 µm. Sample preparation: α-Fe2O3, Fe3O4, the three α-Fe2O3/Fe3O4 mixtures and the sample Mexican magnetite were applied on adhesive tape, sliced in 1cm x 1cm pieces characterized with XRF to determine the iron content as [Q] = mg/cm² and then stacked by taking the iron content of each slice into account to achieve an absorption of µ*Q of about 1 at the edge. The γ- Fe2O3 and also the three α-Fe2O3/Fe3O4 mixtures were prepared as Pellet. Here the sample material was mixed with Hoechst Wax C in a ratio of 1:6, mixed in a vortex shaker and then pressed with a hydraulic press with a Pellet diameter of 13 mm. The amount of the wax/sample powder material was weight before inserting in the press to the amount of Q to achieve a µ*Q of about 1 with a 13 mm Pellet. Shifts of the energy axis as well as a widening or compression of this axis could be present when comparing the data with other data sets of other spectrometer or synchrotron radiation facilities, since no precise energy calibration was carried out due to the reason that the samples were compared to the measured references and would have the same shift, widening or compression.   XRD: Two different commercial XRD set ups have been used. For the Mexican magnetite the Benchtop XRD spectrometer Bruker D2Phaser with a Cobalt X-ray source and a SSD160 detector (active length = 12 mm) was used. The measurement range was 10°- 90° 2theta with 0.014° step size and 4.8 s/step, resulting in a total measurement time of 8h. During the measurement the sample was rotated with 10 rpm. The sample was filled in PMMA-holders (Ø 2.5 mm) using the top-loading technique. The analysis was carried out using a 1-mm fixed divergence slit, a 2.5° primary and a 4° secondary soller collimator, a fixed knife edge (3 mm above the sample surface), and an Fe Kβ filter (2.5). For the X-ray diffraction measurements of the α-Fe2O3/Fe3O4 mixtures and the pure references a Panalytical X’Pert PRO diffractometer with a Bragg-Brentano setup was used. The diffractometer operates with a Cu anode and without a monochromator (Cu-Kalpha radiation) at 40 kV and 30 mA. The diffraction data were obtained over a measurement range of 10–120° 2theta. Samples were applied flat on a cut-off Si wafer attached to the sample holder.   Mössbauer: Mössbauer spectroscopy was performed at a MIMOS II type spectrometer with a 57Co source (in rhodium matrix). For the analyses the 57Fe-γ-line E = 14.4 keV was used and α-iron (α-Fe foil) was applied for the velocity calibration before the samples were analyzed. The samples were prepared in plastic powder sample holders and measured in transmission mode at room temperature. The measurement time varied between 12 h and 120 h depending on the sample.   Information on data sets XAFS - this folder contains the XAFS spectra as intensity file with I0 (without the sample) and the It (transmission signal through the sample) for each sample. Multiple samples (It) share the same I0 and are therefore in the same data set. The Number in the filename between “XAFS“ and “data-set..” is the date of the measurement in the following format: YYYY_MM_DD. The first column in each file is the energy in unit eV. The abbreviation “WP” after each sample name in the header means “Wax Pellet” and indicates that the measurement was performed on a sample prepared as a wax pellet, the number (WP1) indicates the number of the pellet. Two pellets of each mixture were prepared to investigate the influence of the sample preparation. If the sample name is missing “WP#” the sample was prepared on adhesive tape as described above. The information on the contents of each data set as well as the measurement time (t = #h) for each It of the sample/reference can be found in data_dictionary_v2.txt. The intensity is normalized to counts per 1800 seconds in a 0.25 eV (for data-set-1) and 1 eV (for data-set-2, data-set-3 and data-set-4) energy interval with the indicated central bin energy.   XRD - this folder contains the raw intensity files over 2theta (ASC-file). Each sample has its own file with the first column for the 2theta in unit degree and the second column for the measured intensity. The Number in the file name between XRD and sample name (e. g. Fe2O3, 30-70) is the date of the measurement in the following format: YYYY_MM_DD.   MOESSBAUER - this folder contains the recoil Lorentz site analysis fit data of the samples. The files  consist of the observed intensity (Iobs) over the velocity (v (mm/s)), including the calcucalted intensity (Icalc) and the fits of the subspectra (Sextet Site 1, etc. ).  Each sample has it owns file. While the references substances  Fe2O3 and Fe3O4 were measured between 2016 and 2019, the MexicanMagnetite was measured 2020. An exact measurement date can’t be determined anymore.   The corresponding sample to the short cut name (e. g. Fe2O3, 30-70,..) in the files can be found above and is listed in the data_dictionary.txt file as well.

opencc-by-4.0Dec 2021View details →

Datasets, codes and video clips for the laboratory flume tests of granular flow

Datasets, video clips, and codes related to the paper 'Insight into granular flow dynamics relying on basal stress measurements: from experimental flume tests', submitted to the Journal of Geophysical Research: Solid Earth. The datasets provides the raw and processed data for the laboratory flume tests of granular flow including parameters reflecting the granular flow behavior, basal normal stresses measured by a force plate, and deposit parameters of the  granular flows. S1_data_granular flow_velocity provides data of the velocity profiles with a 0.1 second time interval, the depth-averaged velocities, the depth-averaged shear rates,  and the solid inertial stresses of the granular flows under different experimental conditions. The original data were calculated through particle image velocimetry (PIV) method. The images for PIV analysis were recorded by a high-speed camera. S2_data_granular flow_stress provides the raw data of the measured basal normal stresses of the granular flows for all tests. The mean and fluctuating stress components extracted by applying a moving window average filter are also listed in the Table. S3_data_granular flow_flow depth provides the data of the granular flow depth extracted every 0,02 s through a image processing method based on the high-speed photographs.  S4_data_granular flow_deposit provides the parameters of the granular flow deposits for all tests including the apparent friction coefficient and equivalent friction coefficient. The deposit parameters were calculated based on the digital surface model (DSM) of deposit, which were obtained through a oblique photogrammetry method. S5_data_granular flow_density gives the data of the dynamic bulk flow densities of the granular flows under all experimental conditions. The dynamic bulk densities were calculated according to the measured and calculated normal stresses. The videos of the granular flows under different experimental conditions during their propagation are provided in 'S6_video_granular flow.zip' to show the granular flow behavior and its evolution. S6_video_granular flow includes the side-view of the granular flows under all experimental conditions and front-view of the IMF-223 granular flow .  S7_codes_data analysis provides the computer codes for the extraction of mean and fluctuating components and the calculation of granular flow depth. The former includes one file for conducting moving average filter. The latter contains four files, which are used for median filter, image erosion, threshold segmentation and floodfill, extracting flow depth.

opencc-by-4.0Jan 2022View details →

Laboratory Open Channel Flow: Video, Waterlevel and Surface Velocity

Video footage of an open channel flow in a laboratory setting, associated with the surface velocity and water level. - Video footage was collected using a Raspberry Pi Camera Module v2 attached to a Raspberry Pi 4 at 25fps from three positions and split into roughly 15s chunks. - A "mic+35/IU/TC" ultrasonic sensor (accuracy: ±1%) measured the water level - A "Nortek Vectrino" (accuracy: ±1% ±1mm/s) velocimeter measured the velocity at the surface   - The video files can be found in the folders position1, position2 and position3, each file name contains the initial timestamp to match frames to the measurements - The file "waterlevel.csv" contains the timestamps, Waterlevel [mm] and Percentage Full [%]. The waterlevel column is reversed, as the distance between the sensor and the surface was measured. This means, that lower values correspond to higher water levels. - The file "velocity.csv" contains the timestamps and surface velocity measurements [m/s]

opencc-by-4.0Feb 2022View details →

The Data Set for the Publication "Laboratory Testing of Small Scale Solar Facade Module with Phase Change Material and Adjustable Insulation Layer"

In the scope of the ambitious EU goals of carbon neutrality in 2050, building energy efficiency is one of the crucial segments. To ensure a faster energy transition process, innovations are needed at various built environment-related sectors - starting from building components up to urban level energy management advancements. Phase change material (PCM) enriched building components allow to shift the existing paradigm - to make a switch from the static building components to dynamic ones able to take an active part in building energy balance by ensuring energy storage in the building thermal envelope. The data set presented here supports the paper "Laboratory Testing of Small Scale Solar Facade Module with Phase Change Material and Adjustable Insulation Layer". The design of the façade module, experimental setup, used equipment, the plan of the experiment, and obtained results are described in the paper. The provided data set provides heat-flux and average temperature (in PCM) measurements.

opencc-by-4.0Apr 2022View details →

Data of complementary experiments of 'Vegetation-induced hyporheic exchange experiment in Ecoflume of St. Anthony Falls Laboratory on 2021'

Complementary dye release experiments were conducted to support the results of pervious vegetation-induced hyporheic exchange experiments. This data set includes the raw data of dye release experiments with a side-looking camera and dye calibration. The data of pervious expirements have been deposited in Data Repository for University of Minnesota (https://doi.org/10.13020/W282-JJ11).

opencc-by-4.0Dec 2021View details →

Fig. 3 in Observations On The Embryonic Development Of Trichuris Sylvilagi (Nematoda, Trichuridae) Under Laboratory Conditions

Fig. 3. Changes in the size of Trichuris sylvilagi eggs during embryogenesis at the temperature of 30 ° C: а — egg length; b — egg width; с — egg plug length; d — egg plug width; е — eggshell thickness (μm). А — zygote stage; В — larval stage; the small squares in the centre corresponds to the median, the lower and upper borders of the large rectangular correspond to the first and the third quartiles, respectively, vertical line segments, directed up and down from the rectangular, correspond to minimum and maximum values; * P <0.05, ** P <0.01, *** P <0.001 — relative to the parameters of eggs at the zygote stage (n = 15).

opencc-by-4.0Dec 2021View details →

Fig. 1 in Observations On The Embryonic Development Of Trichuris Sylvilagi (Nematoda, Trichuridae) Under Laboratory Conditions

Fig. 1. Stages of embryonic development Trichuris sylvilagi: а — zygote; b — formation of two blastomeres; с — blastomere cleavage; d — bean-shaped embryo; e — tadpole-shaped embryo; f — larva.