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Fig. 1. Tsaganomyid cheek teeth showing reference points for measurements, A, B in On Tsaganomyidae (Rodentia, Mammalia) of Asia
Fig. 1. Tsaganomyid cheek teeth showing reference points for measurements, A, B. Lateral view of cheek teeth. A. p4. B. Other cheek teeth except p4. C–E. Occlusal view of cheek teeth. C. Upper cheek teeth. D, E. Lower cheek teeth. D. Less worn. E. More worn. Abbreviations are: h, enamel height; h1, enamel height on lingual side of upper teeth (buccal side of lower teeth); h2, on buccal side of upper teeth (lingual side of lower teeth); h3, enamel height between two roots on anterobuccal side on p4; L, Length; and W, width.
Belonging to University in Southern Italy: a pilot study to measure students' levels of attachment among programs within the University of Palermo.
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Channel Measurements from Sitarjevec Mine for Propagation Modelling in a Cave Environment
<p>The dataset contains data collected during a measurement campaign using the <a href="https://www.qorvo.com/products/p/DW1000">DecaWave1000 </a>UWB pulse radio module in the <a href="https://rudniksitarjevec.si/en">Sitarjevec</a> mine in Litija, Slovenia. </p> <p>The measurements include complex channel impulse responses (CIRs) collected for 40 predefined positions with the following system parameters:</p> <ul> <li><strong>CONF1:</strong> Channel 4, DataRate 110, PRFR 16, PreambleLenght 4096, PreambleCode 7;</li> <li><strong>CONF2: </strong>Channel 4, DataRate 110, PRFR 64, PreambleLenght 4096, PreambleCode 17;</li> <li><strong>CONF3: </strong>Channel 7, DataRate 110, PRFR 16, PreambleLenght 4096, PreambleCode 7;</li> <li><strong>CONF4: </strong>Channel 7, DataRate 110, PRFR 64, PreambleLenght 4096, PreambleCode 17.</li> </ul> <p><strong>Measurement setup</strong></p> <p>Measurements were performed using the DecaWave1000 UWB pulse radio module in Segment 1 of the mine. Four points (Point A, Point B, Point C, and Point D) were selected for defining the positions of the nodes as shown in Figure 1. Point A denotes the main entrance, the entrance to the measurement segment is represented by Point B, and the beginning and the end of the measurement environment are denoted by Point C, and Point D, respectively. The length of the mine between Point A and Point D is approximately 60 m. </p> <p>The nodes were mounted on stands 1.4 m above the ground, which is not flat. They were placed on a straight line connecting Point C and Point D. The ANCHOR node was positioned in Point C, and the TAG node was moved along the reference line with a step of 1 m up to a maximum distance of 40 m. The nodes were always positioned so the antenna was centred above the reference line. </p> <p><strong>Folder structure</strong></p> <p>The measurements collected for each of the TAG node positions are stored in the corresponding folder. The folders are named m_n, with n=1, ..., 40 corresponding to the TAG's distance to the ANCHOR. Each folder contains four CSV files holding the CIR data measured using the four pre-defined configurations of the UWB system. Each CSV file stores CIRs of approximately 200 repeated measurements as separate records. The CIRs hold complex values of the 156 strongest multipath components corresponding to the taps in the DecaWave1000 accumulator, each of which represents a 1 ns sample interval. </p> <p><strong>Authors</strong></p> <p>Teodora Kocevska, Aleš Simončič, Grega Morano, Tomaž Javornik, and Andrej Hrovat</p> <p>Department of Communication Systems</p> <p>Jožef Stefan Institute, SI-1000 Ljubljana, Slovenia</p> <p>teodora.kocevska@ijs.si</p>
Constraining the dense matter equation of state with new NICER mass-radius measurements and new chiral effective field theory constraints: prior and posterior samples and scripts for generating plots
<p>Full reproduction package accompanying the paper: <em>Constraining the dense matter equation of state with new NICER mass-radius measurements and </em><em>new chiral effective field theory inputs</em></p> <p> </p> <p><em>*Note, the changes made from version to version are made visible in the CHANGELOG.rst file</em></p>
Рис. 2. Схема станΔартных промеров раковины Δвустворчатых моΛΛюсков по А. А. Зютину: L — ΔΛина раковины; H — тоΛщина раковины; D — ширина / выпукΛость Fig. 2. Scheme of bivalve mollusk shell standard measurements: L — shell length; H — shell thickness; D — width / convexity (according to A. A. Zyutin) in Morphometric characteristics of Black Sea mussels Mytilus galloprovincialis Lam. as biomarkers of the anthropogenic impact on the Black Sea coastal biocenoses in tourist destinations
Рис. 2. Схема станΔартных промеров раковины Δвустворчатых моΛΛюсков по А. А. Зютину: L — ΔΛина раковины; H — тоΛщина раковины; D — ширина / выпукΛость Fig. 2. Scheme of bivalve mollusk shell standard measurements: L — shell length; H — shell thickness; D — width / convexity (according to A. A. Zyutin)
Fig. 3 in Using experimental de-worming to measure the immunological and pathological impacts of lungworm infection in cane toads
Fig. 3. The effects of lungworm (Rhabdias pseudosphaerocephala infection level on lung pathology of 15 cane toads. (A) number of areas of inflammation predominated by lymphocytes, (B) number of areas of regional septal fibrosis, and (C) areas of inflammation predominated by neutrophils and macrophages. The size of the symbols represents sample size of each count.
Fig. 2 in Using experimental de-worming to measure the immunological and pathological impacts of lungworm infection in cane toads
Fig. 2. Effects of anthelmintic injection (Ivermectin) on the viability of adult lungworms (Rhabdias pseudosphaerocephala inside the lungs of cane toads (n = 10) hosts over a 7-day period following anthelmintic injection. Lungworm viability scores (see text for definitions) decreased with time since injection. The size of the symbols represents sample size of each score. Two toads had not been treated with anthelmintic when euthanized and were given scores of 0 days post injection.
Fig. 6 in Using experimental de-worming to measure the immunological and pathological impacts of lungworm infection in cane toads
Fig. 6. (A) The effects of anthelmintic treatment on relative liver mass of 5 de-wormed (open bars) vs. 6 not de-wormed (grey bars) free-ranging toads. (B) Effect of experimental treatment on relative liver mass of 49 captive cane toads. ID = infected, dewormed (n = 11), IC = infected, control (n = 13), ND = non-infected, de-wormed
Fig. 4 in Using experimental de-worming to measure the immunological and pathological impacts of lungworm infection in cane toads
Fig. 4. The effects of lungworm (Rhabdias pseudosphaerocephala) abundance on leukocyte concentrations in cane toads. Captive toads (n = 19) exhibited high leukocyte concentrations that were independent of the level of Rhabdias infection. In contrast, leukocyte concentrations in free-ranging toads (n = 11) increased with Rhabdias infection level.
Measurements of Methanethiol (MeSH) and dimethyl sulfide (DMS) in surface seawater during POLAR-CHANGE Antarctic expedition 2023 on board the BIO Hesperides.
<p>Global emissions of methanethiol (MeSH) are highly uncertain and the drivers influencing its seawater concentrations are quasi unexplored. Here we try to address this gap in our understanding by contributing new seawater concentration measurements from the Southern Ocean. The POLAR-CHANGE cruise was conducted in February and March 2023 on board the BIO RV Hesperides A33 in waters of the Antarctic Peninsula and the Weddell Sea. A Vocus PTR-ToF (TOFWERK AG, Thun, Switzerland, Vocus Scout) coupled to a segmented flow coil equilibrator (SFCE) was used to measure DMS and MeSH in seawater from the underway seawater inlet. This dataset contains MeSH and DMS surface seawater concentrations and relevant auxiliary data (chlorophyll a, sea surface temperature (SST) and sea surface salinity (SSS)). Sea surface temperature (SST) and sea surface salitity (SSS) were measured in seawater from the underway water inlet located at 4-5 m depth. There was good agreement between the underway SST, SSS and the CTD sensors, confirming that the underway sensors were well calibrated. Underway seawater fluorescence measurements were not calibrated for total chlorophyll a (Chl a) concentration by frequent discrete measurements of Chl a from the on-board 10AU Turner fluorometer. For calibrated Chl a data, please get in touch with the autors.</p> <p> </p> <p>From the beginning of the POLAR-CHANGE cruise we observed extremely high MeSH concentrations which immediately dropped down to within previously observed ranges, after cleaning the equilibrator daily with 10 % HCl. We decided to exclude all MeSH measurements before regular cleaning commenced from 26/02/2023 onwards as these datapoints are likely affected by biofouling. MeSH seawater concentrations prior to this date are replaced by -999 in the dataset shared here. Other gaps in the timestamp of data acquisition are due to calibrations or measuring other samples.</p> <p> </p> <p>Details on the measurement methodology can be found here:</p> <p>Wohl, C.; Güell-Bujons, Q.; Castillo, Y.M.; Calbet, A.; Simó, R. Volatile Organic Compounds Released by Oxyrrhis marina Grazing on Isochrysis galbana. Oceans 2023, 4, 151-169. https://doi.org/10.3390/oceans4020011</p> <p> </p> <p>Definitions of acronyms, site abbreviations, or other project-specific designations:</p> <p>Lat=latitude (negative indicates west and south)</p> <p>Lon=longitude (negative indicates west and south)</p> <p>Date= The mean measured concentration during each hour is shown, 30 min either side of the listed time. The timestamp indicates sampling time in UTC, expressed as DD/MM/YYYY HH:MM</p> <p>MeSH_nM= methanethiol surface seawater concentration in nM, defined as nmol dm^(-3)</p> <p>DMS_nM= dimethyl sulfide surface seawater concentration in nM, defined as nmol dm^(-3)</p> <p>fluo = surface fluorescence, a proxi for chlorophyll a concentration in mg m^(-3)</p> <p>SST= sea surface temperature in degrees Celsius</p> <p>SSS= sea surface salinity in practical salinity units (PSU)</p>
A FRET based biosensor for measuring Gα13 activation in single cells
<p>The figures and raw data that are presented in the paper "A FRET based biosensor for measuring Gα13 activation in single cells"</p>
BRAIN Journal-Brain signal analysis using EEG and Entropy to study the effect of physical and mental tasks on cognitive performance-Figure 2. Energy-VAS subjective measures for the participants (n=12) under two conditions (control and exercise involved cognitive task).
<p>As shown in Figure 2, it was found that there was a statistically significant interaction in the<br> percentage of mental fatigue between the condition type and time-on-task factor times (F(6, 22) =<br> 492.19, p < 0.001) as well as there was a significant main effect of time-on-task (time5 to time30)<br> (F(5, 22) = 463.794, p < 0.001). In addition, there was also a significant main effect in the condition type (F (1, 22) = 713.133, p < 0.001) which represented a large effect size. For the physical fatigue<br> subjective measure, there was a significant difference between the two experimental conditions (p <<br> 0.001), and within the subject test times (p < 0.001). However, there was no significant difference<br> between the means of the concentration visual analogue scale for these two experimental conditions<br> (p = 0.057) despite a significant difference (p < 0.001) in the time-on-task repeated measures.</p>
Figure 1. (a) Part of the acrylic structure where the patient is enclosed to avoid external stimulus; (b) Chin rest, corresponding proportions and measurements.-Design of a Novel Servo-motorized Laser Device for Visual Pathways Diseases Therapy
<p>The device consists mainly of an acrylic semi-spherical structure (Figure 1(a)) where visual<br> stimuli will be shown, according to a pre-designed therapy. Four servomotors will drive the lasers,<br> two inside the structure (short distances drive the lasers, two inside the structure (short distance<br> therapies) and two outside (middle-long distance therapies). A chin-rest must be used to have a<br> better line of sight fixation. A webcam with infrared light will catch the Purkinje-Sanson images to<br> identify the sight line (Borah, 2006; Halswanter, 2011; Pambakian et al., 2000). LabVIEW software<br> is used to control the device, including an audio stimulus along with an image-processing pipeline.<br> Finally a microcontroller is used to control the servo movements, laser beams and buzzers.</p>
Instantaneous, three-dimensional velocity fields past a bio-prosthetic aortic valve measured in-vitro with tomographic particle image velocimetry.
<p>Each folder contains instantaneous, three-dimensional velocity vector data obtained in a simplified model of the aortic root with a distinct size and geometry (small, medium, large, and sinus-less). The specific geometry of each aortic root model is contained in the corresponding folder.</p> <p>The velocity data is structured in the following way: Two separate folders for velocity data in the "ascending aorta" domain (AAo) and in the "sinus of Valsalva" domain (SOV). Each domain contains velocity datasets for instances t=0.00, 0.03, 0.06, ..., 0.39 s (t000, t003, t006, ..., t039). Each velocity dataset contains N=16 phase-locked instantaneous 3D velocity fields.</p> <p>The data was acquired using tomographic particle image velocimetry and a custom built hydraulic setup capable of replicating normal physiological flow conditions in the human aorta (heart rate = 72 bpm, cardiac output = 4.8 l)</p> <p>Data format:</p> <p>- aortic root geometry: STL (the geometry is provided with respect to the reference frame of the velocity data)</p> <p>- velocity data: NPY (NumPy), shape= (N_nodes, 6), columns contain X, Y, Z, U, V, W data, where U, V, W are the X, Y, Z components of the instantaneous vector field</p>
Exploiting the potential of neutron imaging measurements for life sciences applications at the neutron spallation source, ISIS, UK - Crabs X-ray CT
<p>A ZIP file containing slices (in TIFF format) from a X-ray CT scan of crabs from the Eocene of Spain. Specimen was scanned on a Nikon Metrology HMX ST 225 system at the Natural History Museum, London, using a 1.0 mm thick copper filter, 225 kV voltage and 180 μA current, giving a tomographic dataset with a voxel size of 46 µm.</p>
Room Impulse Response measurements of a rectangular room
<p>This archive contains the data for a Gitlab hosted project (https://github.com/epfl-lts2/joint_estimation_of_room_geometry_and_modes). This archive allows users to extract the Room impulse responses (RIRs) measurements for a real rectangular room. A total of 132 measurements are included. Furthermore, users have the option to perform several post processing steps on the RIRs such as filtering, downsampling and truncation in time domain. Please refer to the guidelines pdf for more information.</p>
Figure 1. CNN architecture (adopted from Krizhevsky et al. '12)-Measuring Customer Behavior with Deep Convolutional Neural Networks
<p>The architecture of a CNN can be described as following. A small pixel region goes to input neurons and then connects to a first convolution hidden layer (Figure1). There we can see a set of learnable filters, which are activated during the presentation some particular type of feature in pixel region in the input. On this phase, CNN does shift invariance, which is carried by feature map. Subsampling layer goes next. There we have two processes: local averaging and sampling. As a result, we get declining resolution of feature map. To correspond this task CNN needs supervised learning. Before starting the experiment, we gave a set of labeled videos with different emotional experience. The system analyses images and finds similar features. Then the system creates a map, where it arranges videos in accordance with similar features. Thereby, images with similar emotions form certain class. To test the system, we add other videos and correct the system when it refers them improperly. The proposed model consists of four convolutional layers, followed by max-pooling layers, and three fully-connected layers with a final classificatory presented with MLP (with six basic outputs, corresponding to basic emotions for emotion classification and two outputs for motion classification for typical and non-typical behavior). The input data was presented as infrared camera output.</p>
Multisensor measurement of healthy adult performance during standardised motor function test battery
<p>This dataset contains inertial data from 4 wearable sensor nodes and 1 wearable patch worn by 20 healthy adult participants performing a series of physical functioning tests (including the short physical performance battery, the timed up and go test, a walking test and balance tests). Details of patient demographics, the physical functioning tests and of each sensor are contained in files in the main folder.</p> <p>Inertial data (accelerometer and gyroscope) is contained in two folders relating to each sensor type. The start and end time for each sensor can be taken from the details in each folder structure, as detailed below. The times given are specific to each sensor's monitoring system which are not exactly synchronised. As such, a manual synchronisation shaking protocol was followed where all sensors were strapped together and shaken three times in succession at the start of each data collection period. The physical functioning test times will also need to be synchronised.</p> <p>-> Inertial sensor data / (subject id).zip / (subject id) / (date_time_crossTest_SD_session#) /<br> -> Wearable inertial patch / (subject id) / (date)T(time) /</p>
Beam Alignment Measurements using a Hybrid Massive MIMO Testbed
<p>Measurement data and processing code for Mathworks Matlab underlying the beam alignment results of the publication. The results compare 3 algorithms for beam alignment and are measured at 2.4GHz using the Hybrid Massive MIMO testbed of the CommIT chair of the Technische Universität Berlin.</p> <p>Type of Data: Processed data (Measurement results and processing code)</p> <p>Hardware/software used: Technische Universität Berlin CommIT Hybrid Massive MIMO testbed, Mathworks Matlab</p> <p>Data format: Measurements: Matlab mat data files, Code: m UTF8 text files</p> <p>Source: experiments</p> <p>Number of samples: 2 locations</p> <p>Size per sample: 10 files per location</p> <p>Total size of samples: 170MB</p>
Review of Recent Trends in Measuring the Computing Systems Intelligence-Figure 3. Intelligence of different living creature (accessed 01.11.2017). 3.1. A painting elephant (http://www.wittyfacts.com/suda-the-painting-elephant/); 3.2. A common octopus (https://en.wikipedia.org/wiki/Octopus). 3.3. An African grey parrot (https://en.wikipedia.org/wiki/Grey_parrot)
<p>Many observations proved that octopus species have an impressive spatial learning capacity, advanced navigational abilities, and advanced predatory techniques. The dexterity is important for using and manipulating tools. Zullo, Sumbre, Agnisola, Flash, & Hochner, (2009) studied the successful dexterity of octopuses. They have highly sensitive suction cups and prehensile arms, squid, and cuttlefish. This allows them to hold and manipulate objects. The motor skills of octopuses (Figure 3.2) do not seem to depend upon mapping their body. Some species of parrots are able to mimic very well the human speech. There were performed many studies with parrots that shown that some individuals are able to associate words with their meanings. Another observed ability is to form simple sentences. It has been shown that some grey parrots perform at the cognitive level of a 3-year-old child in some tasks. Pepperberg (2006) proved that some parrots can count up to 6. Figure 3.3 presents a frequently studied species of parrots, called African grey parrot.</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.