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1,742 results for “Activity data”
Data from: Greater root phosphatase activity in nitrogen-fixing rhizobial but not actinorhizal plants with declining phosphorus availability
1. The abundance of nitrogen (N)-fixing plants in ecosystems where phosphorus (P) limits plant productivity poses a paradox because N fixation entails a high P cost. One explanation for this paradox is that the N-fixing strategy allows greater root phosphatase activity to enhance P acquisition from organic sources, but evidence to support this contention is limited. 2. We measured root phosphomonoesterase (PME) activity of 10 N-fixing species, including rhizobial legumes and actinorhizal Allocasuarina species, and eight non-N-fixing species across a retrogressive soil chronosequence showing a clear shift from N to P limitation of plant growth and representing a strong natural gradient in P availability. 3. Legumes showed greater root PME activity than non-legumes, with the difference between these two groups increasing markedly as soil P availability declined. By contrast, root PME activity of actinorhizal species was always lower than that of co-occurring legumes and not different from non-N-fixing plants. 4. The difference in root PME activity between legumes and actinorhizal plants was not reflected in a greater or similar reliance on N fixation for N acquisition by actinorhizal species compared to co-occurring legumes. 5. Synthesis. Our results support the idea that N-fixing legumes show high root phosphatase activity, especially at low soil P availability, but suggest that this is a phylogenetically conserved trait rather than one directly linked to their N-fixation capacity.
Data from: Zinc supplementation inhibits complement activation in age-related macular degeneration
Age-related macular degeneration (AMD) is the leading cause of blindness in the Western world. AMD is a multifactorial disorder but complement-mediated inflammation at the level of the retina plays a pivotal role. Oral zinc supplementation can reduce the progression of AMD but the precise mechanism of this protective effect is as yet unclear. We investigated whether zinc supplementation directly affects the degree of complement activation in AMD and whether there is a relation between serum complement catabolism during zinc administration and the complement factor H (CFH) gene or the Age-Related Maculopathy susceptibility 2 (ARMS2) genotype. In this open-label clinical study, 72 randomly selected AMD patients in various stages of AMD received a daily supplement of 50 mg zinc sulphate and 1 mg cupric sulphate for three months. Serum complement catabolism–defined as the C3d/C3 ratio–was measured at baseline, throughout the three months of supplementation and after discontinuation of zinc administration. Additionally, downstream inhibition of complement catabolism was evaluated by measurement of anaphylatoxin C5a. Furthermore, we investigated the effect of zinc on complement activation in vitro. AMD patients with high levels of complement catabolism at baseline exhibited a steeper decline in serum complement activation (p<0.001) during the three month zinc supplementation period compared to patients with low complement levels. There was no significant association of change in complement catabolism and CFH and ARMS2 genotype. In vitro zinc sulphate directly inhibits complement catabolism in hemolytic assays and membrane attack complex (MAC) deposition on RPE cells. This study provides evidence that daily administration of 50 mg zinc sulphate can inhibit complement catabolism in AMD patients with increased complement activation. This could explain part of the mechanism by which zinc slows AMD progression.
Data from: Distinct BOLD fMRI responses of capsaicin-induced thermal sensation reveal pain-related brain activation in nonhuman primates
Background: Approximately 20% of the adult population suffer from chronic pain that is not adequately treated by current therapies, highlighting a great need for improved treatment options. To develop effective analgesics, experimental human and animal models of pain are critical. Topically/intra-dermally applied capsaicin induces hyperalgesia and allodynia to thermal and tactile stimuli that mimics chronic pain and is a useful translation from preclinical research to clinical investigation. Many behavioral and self-report studies of pain have exploited the use of the capsaicin pain model, but objective biomarker correlates of the capsaicin augmented nociceptive response in nonhuman primates remains to be explored. Methodology: Here we establish an aversive capsaicin-induced fMRI model using non-noxious heat stimuli in Cynomolgus monkeys (n = 8). BOLD fMRI data were collected during thermal challenge (ON:20 s/42°C; OFF:40 s/35°C, 4-cycle) at baseline and 30 min post-capsaicin (0.1 mg, topical, forearm) application. Tail withdrawal behavioral studies were also conducted in the same animals using 42°C or 48°C water bath pre- and post- capsaicin application (0.1 mg, subcutaneous, tail). Principal Findings: Group comparisons between pre- and post-capsaicin application revealed significant BOLD signal increases in brain regions associated with the 'pain matrix', including somatosensory, frontal, and cingulate cortices, as well as the cerebellum (paired t-test, p<0.02, n = 8), while no significant change was found after the vehicle application. The tail withdrawal behavioral study demonstrated a significant main effect of temperature and a trend towards capsaicin induced reduction of latency at both temperatures. Conclusions: These findings provide insights into the specific brain regions involved with aversive, 'pain-like', responses in a nonhuman primate model. Future studies may employ both behavioral and fMRI measures as translational biomarkers to gain deeper understanding of pain processing and evaluate the preclinical efficacy of novel analgesics.
Data from: Differential neural processing during motor imagery of daily activities in chronic low back pain patients
Chronic low back pain (chronic LBP) is both debilitating for patients but also a major burden on the health care system. Previous studies reported various maladaptive structural and functional changes among chronic LBP patients on spine- and supraspinal levels including behavioral alterations. However, evidence for cortical reorganization in the sensorimotor system of chronic LBP patients is scarce. Motor Imagery (MI) is suitable for investigating the cortical sensorimotor network as it serves as a proxy for motor execution. Our aim was to investigate differential MI-driven cortical processing in chronic LBP compared to healthy controls (HC) by means of functional magnetic resonance imaging (fMRI). Twenty-nine subjects (15 chronic LBP patients, 14 HC) were included in the current study. MI stimuli consisted of randomly presented video clips showing every-day activities involving different whole-body movements as well as walking on even ground and walking downstairs and upstairs. Guided by the video clips, subjects had to perform MI of these activities, subsequently rating the vividness of their MI performance. Brain activity analysis revealed that chronic LBP patients exhibited significantly reduced activity compared to HC subjects in MI-related brain regions, namely the left supplementary motor area and right superior temporal sulcus. Furthermore, psycho-physiological-interaction analysis yielded significantly enhanced functional connectivity (FC) between various MI-associated brain regions in chronic LBP patients indicating diffuse and non-specific changes in FC. Current results demonstrate initial findings about differences in MI-driven cortical processing in chronic LBP pointing towards reorganization processes in the sensorimotor network.
Data from: Assessing the relationship between quality of life and behavioral activation using the Japanese behavioral activation for depression scale-short form
Quality of life (QOL) is an important health-related concept. Identifying factors that affect QOL can help develop and improve health-promotion interventions. Previous studies suggest that behavioral activation fosters subjective QOL, including well-being. However, the mechanism by which behavioral activation improves QOL is not clear. Considering that QOL improves when depressive symptoms improve post-treatment and that behavioral activation is an effective treatment for depression, it is possible that behavioral activation affects QOL indirectly rather than directly. To clarify the mechanism of the influence of behavioral activation on QOL, it is necessary to examine the relationships between factors related to behavioral activation, depressive symptoms, and QOL. Therefore, we attempted to examine the relationship between these factors. Participants comprised 221 Japanese undergraduate students who completed questionnaires on behavioral activation, QOL, and depressive symptoms: the Japanese versions of the Behavioral Activation for Depression Scale-Short Form (BADS-SF), WHO Quality of Life-BREF (WHOQOL-26), and Center for Epidemiologic Studies Depression Scale (CES-D). The BADS-SF comprises two subscales, Activation and Avoidance, and the WHOQOL-26 measures overall QOL and four domains, Physical Health, Psychological Health, Social Relationships, and Environment. Mediation analyses were conducted with BADS-SF activation and avoidance as independent variables, CES-D as a mediator variable, and each WHO-QOL as an outcome variable. Results indicated that depression completely mediated the relationship between Avoidance and QOL, and partially mediated the relationship between Activation and QOL. In addition, analyses of each domain of QOL showed that Activation positively affected all aspects of QOL directly and indirectly, but Avoidance had a negative influence on only part of QOL mainly through depression. The present study provides behavioral activation strategies aimed at QOL enhancement.
Raw data for EFQO activity assays
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Data for manuscript "Integrated microwave photonic notch filter using a heterogeneously integrated Brillouin and active-silicon photonic circuit"
<p>Experimental data and scripts to plot results for manuscript "Integrated microwave photonic notch filter using a heterogeneously integrated Brillouin and active-silicon photonic circuit"</p>
The impacts of active and self-supervised learning on efficient annotation of single-cell expression data - source data
<p>Source data used to create all figures in the manuscript.</p>
Raw data and code for publication "Optimisation of surfactin yield in Bacillus using active learning and high-throughput mass spectrometry"
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Research data for "Tidal modulation of the seismic activity related to the 2021 La Palma volcanic eruption"
<p>Research data for <br> <br> Tidal modulation of the seismic activity related to the 2021 La Palma volcanic eruption</p> <p>Luis Miguelsanz (1), José Fernández (1), Juan F.Prieto (2), Kristy F. Tiampo (3)</p> <p>(1) Institute of Geosciences (IGEO), CSIC-UCM, Calle del Doctor Severo Ochoa, 7. 28040-Madrid, Spain.<br> (2) E.T.S. de Ingenieros en Topografía, Geodesia y Cartografía, Universidad Politécnica de Madrid, 28031-Madrid, Spain.<br> (3) Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado Boulder, Boulder, CO, USA.</p> <p> <br> </p> <p><br> Introduction</p> <p>This set of files contains data supporting the tables and figures featured in the journal article.<br> <br> File Ts01.xlsx shows earthquake data belonging to the Phase 0 defined in the manuscript, as well as tidal stress phases and amplitudes obtained for each event using the methodology explained in the text. <br> Files Ts02.xlsx and Ts03.xlsx are datasets analog to File Ts01.xlsx, but using data corresponding to Phase 1 and Phase 2 respectively. <br> Data of Files Ts01.xlsx, Ts02.xlsx and Ts03.xlsx have been used to compose Tables 1, 2, 3, 4, and Figures 3, 4, 5, 6, 7.</p> <p>File Ts04.xlsx features tidal strain values (Volume strain and East-West, North-South and Vertical components) calculated at two-hour intervals for an imaginary focus whose epicenter is set at the <br> geographical center of all the epicenters of the catalogue, and whose depth is the mean depth of the events in the catalogue during the period 2021/08/31 – 2021/12/25.<br> Data from File Ts04.xlsx has been used for composition of Figures 9 and 10 in the manuscript.</p> <p>File Ts05.xlsx features tidal stress values (East-West, North-South and Vertical components) calculated at two-hour intervals for an imaginary focus whose epicenter is set at the geographical center <br> of all the epicenters of the catalogue, and whose depth is the mean depth of the events in the catalogue during the period 2021/08/31 – 2021/12/25. <br> Data from File Ts05.xlsx has been used for composition of Figure 11 in the manuscript.</p> <p>File Ts06.xlsx features tidal stress values (ocean-loading tides and body tides) calculated at two-hour intervals for an imaginary focus whose epicenter is set at the geographical center of all the <br> epicenters of the catalogue, and whose depth is the mean depth of the events in the catalogue during the period 2021/08/31 – 2021/12/25. <br> Data from File Ts06.xlsx has been used for composition of Figure 12 in the manuscript.</p> <p>File Ts07.xlsx shows tidal tilt phases and amplitudes obtained for each event in the three Phases 0, 1, and 2 (North-South and East-West components).<br> Data from File Ts07.xlsx has been used for composition of Figures 13 and 14 and Tables 5 and 6 in the manuscript.</p> <p>File Ts08.xlsx features tidal tilt values (North-South and East-West components) calculated at two-hour intervals for an imaginary focus whose epicenter is set at the geographical center of all <br> the epicenters of the catalogue during the period 2021/08/31 – 2021/12/25. <br> Data from File Ts08.xlsx has been used for composition of Figure 15 in the manuscript. </p> <p>File Ts09.xlsx shows tidal stress phases and amplitudes calculated at two-hour intervals for an imaginary focus whose epicenter is set at the geographical center of all the epicenters of the catalogue, <br> and whose depth is the mean depth of the events in the catalogue throughout the year 2021.<br> Data from File Ts09.xlsx has been used for the discussion in chapter 5 about the predominance of ocean-loading tides over solid earth tides.</p> <p>1. Ts01.xlsx Data used to detect tidal stress correlations in Phase 0 of the volcanic crisis.</p> <p>1.1 Column "Year", y.<br> 1.2 Column "Month", m.<br> 1.3 Column "Day", d.<br> 1.4 Column "Hour", h.<br> 1.5 Column "Minute", min.<br> 1.6 Column "Second", s.<br> 1.7 Column "Latitude", deg, latitude north of equator.<br> 1.8 Column "Longitude", deg, longitude east of Greenwich.<br> 1.9 Column "Depth", km.<br> 1.10 Column "Phase_confining_stress", deg, tidal phase angle assigned to the event, calculated for tidal confining stress.<br> 1.11 Column "Amplitude_confining_stress", Pa, amplitude of the tidal half cycle in which the event occurs, calculated for tidal confining stress.<br> 1.12 Column "Phase_confining_stress_rate", deg, tidal phase angle assigned to the event, calculated for tidal confining stress rate.<br> 1.13 Column "Amplitude_confining_stress_rate", Pa/h, amplitude of the tidal half cycle in which the event occurs, calculated for tidal confining stress rate.<br> 1.14 Column "Magnitude", earthquake magnitude.</p> <p><br> 2. Ts02.xlsx Data used to detect tidal stress correlations in Phase 1 of the volcanic crisis.</p> <p>2.1 Column "Year", y.<br> 2.2 Column "Month", m.<br> 2.3 Column "Day", d.<br> 2.4 Column "Hour", h.<br> 2.5 Column "Minute", min.<br> 2.6 Column "Second", s.<br> 2.7 Column "Latitude", deg, latitude north of equator.<br> 2.8 Column "Longitude", deg, longitude east of Greenwich.<br> 2.9 Column "Depth", km.<br> 2.10 Column "Phase_confining_stress", deg, tidal phase angle assigned to the event, calculated for tidal confining stress.<br> 2.11 Column "Amplitude_confining_stress", Pa, amplitude of the tidal half cycle in which the event occurs, calculated for tidal confining stress.<br> 2.12 Column "Phase_confining_stress_rate", deg, tidal phase angle assigned to the event, calculated for tidal confining stress rate.<br> 2.13 Column "Amplitude_confining_stress_rate", Pa/h, amplitude of the tidal half cycle in which the event occurs, calculated for tidal confining stress rate.<br> 2.14 Column "Magnitude", earthquake magnitude.<br> 2.15 Column "Autonum", autonumeric code.</p> <p><br> 3. Ts03.xlsx Data used to detect tidal stress correlations in Phase 2 of the volcanic crisis.</p> <p>3.1 Column "Year", y.<br> 3.2 Column "Month", m.<br> 3.3 Column "Day", d.<br> 3.4 Column "Hour", h.<br> 3.5 Column "Minute", min.<br> 3.6 Column "Second", s.<br> 3.7 Column "Latitude", deg, latitude north of equator.<br> 3.8 Column "Longitude", deg, longitude east of Greenwich.<br> 3.9 Column "Depth", km.<br> 3.10 Column "Phase_confining_stress", deg, tidal phase angle assigned to the event, calculated for tidal confining stress.<br> 3.11 Column "Amplitude_confining_stress", Pa, amplitude of the tidal half cycle in which the event occurs, calculated for tidal confining stress.<br> 3.12 Column "Phase_confining_stress_rate", deg, tidal phase angle assigned to the event, calculated for tidal confining stress rate.<br> 3.13 Column "Amplitude_confining_stress_rate", Pa/h, amplitude of the tidal half cycle in which the event occurs, calculated for tidal confining stress rate.<br> 3.14 Column "Magnitude", earthquake magnitude.<br> 3.15 Column "Autonum", autonumeric code.</p> <p><br> 4. Ts04.xlsx Tidal strain calculated at two-hour intervals for for an imaginary focus whose epicenter is set at the geographical center of all the epicenters of the catalogue, <br> and whose depth is the mean depth of the events in the catalogue during the period 2021/08/31 – 2021/12/25.</p> <p>4.1 Column "Latitude", deg, latitude north of equator.<br> 4.2 Column "Longitude", deg, longitude east of Greenwich.<br> 4.3 Column "Depth", km.<br> 4.4 Column "Date", date in format yyyymmdd.<br> 4.5 Column "Time", time in format hour : minute : second.<br> 4.6 Column "Volume strain", nanostrain, tidal volume strain.<br> 4.7 Column "East-West strain", nanostrain, tidal East-West strain.<br> 4.8 Column "North-South strain", nanostrain, tidal North-South strain.<br> 4.9 Column "Vertical strain", nanostrain, tidal Vertical strain.</p> <p><br> 5. Ts05.xlsx Tidal stress calculated at two-hour intervals for for an imaginary focus whose epicenter is set at the geographical center of all the epicenters of the catalogue, <br> and whose depth is the mean depth of the events in the catalogue during the period 2021/08/31 – 2021/12/25.</p> <p>5.1 Column "Latitude", deg, latitude north of equator.<br> 5.2 Column "Longitude", deg, longitude east of Greenwich.<br> 5.3 Column "Depth", km.<br> 5.4 Column "Date", date in format yyyymmdd.<br> 5.5 Column "Time", time in format hour : minute : second.<br> 5.6 Column "East-West stress", Pa, tidal East-West stress.<br> 5.7 Column "North-South stress", Pa, tidal North-South stress.<br> 5.8 Column "Vertical stress", Pa, tidal Vertical stress.</p> <p><br> 6. Ts06.xlsx tidal stress (ocean-loading tides and body tides) calculated at two-hour intervals for an imaginary focus whose epicenter is set at the geographical center of all <br> the epicenters of the catalogue, and whose depth is the mean depth of the events in the catalogue during the period 2021/08/31 – 2021/12/25. </p> <p>6.1 Column "Latitude", deg, latitude north of equator.<br> 6.2 Column "Longitude", deg, longitude east of Greenwich.<br> 6.3 Column "Depth", km.<br> 6.4 Column "Date", date in format yyyymmdd.<br> 6.5 Column "Time", time in format hour : minute : second.<br> 6.6 Column "Ocean tides stress", Pa, tidal stress due to ocean-loading tides.<br> 6.7 Column "Body tides stress", Pa, tidal stress due to body tides.</p> <p><br> 7. Ts07.xlsx Tidal tilt phases and amplitudes for the events in the three Phases 0, 1, and 2.</p> <p>7.1 Column "Phase", number of the phase of the seismic unrest, as defined in the manuscript (0, 1, and 2).<br> 7.2 Column "Year", y.<br> 7.3 Column "Month", m.<br> 7.4 Column "Day", d.<br> 7.5 Column "Hour", h.<br> 7.6 Column "Minute", min.<br> 7.7 Column "Second", s.<br> 7.8 Column "Latitude", deg, latitude north of equator.<br> 7.9 Column "Longitude", deg, longitude east of Greenwich.<br> 7.10 Column "Depth", km.<br> 7.11 Column "Phase_tilt_NS", deg, tidal phase angle assigned to the event, calculated for tidal tilt (North-South component).<br> 7.12 Column "Ampl_tilt_NS", nrad, amplitude of the tidal half cycle in which the event occurs, calculated for tidal tilt (North-South component).<br> 7.13 Column "Phase_tilt_EW", deg, tidal phase angle assigned to the event, calculated for tidal tilt (East-West component).<br> 7.14 Column "Ampl_tilt_NS", nrad, amplitude of the tidal half cycle in which the event occurs, calculated for tidal tilt (East-West component).<br> 7.15 Column "Magnitude", earthquake magnitude.</p> <p><br> 8. Ts08.xlsx Tidal tilt (North-South and East-West components) calculated at two-hour intervals for an imaginary focus whose epicenter is set at the geographical center of all <br> the epicenters of the catalogue during the period 2021/08/31 – 2021/12/25. </p> <p>8.1 Column "Latitude", deg, latitude north of equator.<br> 8.2 Column "Longitude", deg, longitude east of Greenwich.<br> 8.3 Column "Depth", km.<br> 8.4 Column "Date", date in format yyyymmdd.<br> 8.5 Column "Time", time in format hour : minute : second.<br> 8.6 Column "East-West tilt", nrad, East-West tidal tilt.<br> 8.7 Column "North-South tilt", nrad, North-South tidal tilt.</p> <p><br> 9. Ts09.xlsx tidal stress phases and amplitudes calculated at two-hour intervals for an imaginary focus whose epicenter is set at the geographical center of all <br> the epicenters of the catalogue, and whose depth is the mean depth of the events in the catalogue throughout the year 2021.<br> 9.1 Column "Latitude", deg, latitude north of equator.<br> 9.2 Column "Longitude", deg, longitude east of Greenwich.<br> 9.3 Column "Depth", km.<br> 9.4 Column "Date", date in format yyyymmdd.<br> 9.5 Column "Time", time in format hour : minute : second.<br> 9.6 Column "Phase (body tides)", degrees, tidal stress phase angle calculated for body tides.<br> 9.7 Column "Amplitude (body tides)", Pa, amplitude of the tidal half cycle, calculated for body tides.<br> 9.8 Column "Phase (ocean tides)", degrees, tidal stress phase angle calculated for ocean-loading tides.<br> 9.9 Column "Amplitude (ocean tides)", Pa, amplitude of the tidal half cycle, calculated for ocean-loading tides.</p>
Data from: Assessing Electrogenetic Activation via a Network Model of Biological Signal Propagation
<p>Simulation data from Assessing Electrogenetic Activation via a Network Model of Biological Signal Propagation, doi: 10.3389/fsysb.2024.1291293</p> <p>There are 10 csv files per network type, each dataset contains the Timestep, Node, Strain, Inducer Concentration/Duration, and Node weights for the timecourse of the simulation. </p>
Data for / Comparison of Antifungal Activity of Thymus Vulgaris Essential Oil and Triple Antibiotic Paste Against Candida Albicans Isolated from Root Canal (In Vitro Study)
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Data of industrial heat source between 2012 and 2021 using long-term Active Fire/Hotspot data in China
<p>Industrial heat sources serve as crucial indicators of energy consumption levels and air pollution. Energy-intensive industries are facing substantial challenges in transforming and upgrading in China. Therefore, accurately identifying industrial heat source locations and monitoring their temporal patterns are becoming utmost importance. In this study, a long-term industrial heat source datasets between 2012 and 2021 in China using long-term Active Fire/Hotspots (ACF) data has been constructed to monitor and analyze large-scale industrial heat sources. Firstly, density segmentation method based on an improved k-means algorithm using long-term ACF data and spatial topological correlation analysis was conducted to build industrial heat sources. Then, 4410 industrial heat sources were obtained between 2012 and 2021 in China, with an identification accuracy of 95.08% by manual verification using high-resolution remote sensing images and point of interest (POI) data. Finally, the trend in the spatio-temporal variation of industrial heat sources was analyzed using long-term series. The results from 2012 to 2021 showed that the spatial distribution of industrial heat sources in China exhibits local aggregation and a gradual shift from east to west.And,the number of industrial heat sources in China has followed a trend of an initial increase from 2012 to 2014, followed by a decrease since 2014, consistent with national energy reform-related policies.The result of this study indicated the temporal variation of industrial heat sources, enhanced the accuracy of fire points category identification, and demonstrated potential for advancing energy efficiency, emission reduction, and sustainable development in China.</p>
Data for the article: Residual Flexural Performance of Large-Scale Ferronickel Slag Alkali-Activated Concrete Slabs After Fire Exposure
<p>Figures and related data for the article Residual Flexural Performance of Large-Scale Ferronickel Slag Alkali-Activated Concrete Slabs After Fire Exposure</p>
raw data - In classical Hodgkin lymphoma, the activity of Thymidine kinase-1 is not related to the tumor size.
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Survey Material and Data - Illusion of visual stability through active perceptual serial dependence
<p>Survey Material and Data.</p>
Infectious disease modelling and the dynamics of the active cases - Data
<p>We developed a model that tries to describe the dynamics of the spread of a disease among a population, in particular the progress of infected active cases. The model is then applied to describe Italy CoViD-19 outbreak and subsequently, we tried to predict possible scenarios.</p>
Camera trap data: Density dependence of daily activity in three ungulate species
<p><span><span><span><span><span><span><span><span><span><span><span>Daily activity in herbivores reflects a balance between finding food and safety. The safety-in-numbers theory predicts that living in higher population densities increases safety, which should affect this balance. High-density populations are thus expected to show a more even distribution of activity – i.e. spread – and higher activity levels across the day. We tested these predictions for three ungulate species; red deer (<i>Cervus elaphus</i>), roe deer (<i>Capreolus capreolus</i>) and wild boar (<i>Sus scrofa</i>). We used camera traps to measure the level and spread of activity across ten forest sites at the Veluwe, the Netherlands, that widely range in ungulate density. Food availability and hunting levels were included as covariates. Daily activity was more evenly distributed when population density was higher for all three species. Both deer species showed relatively more feeding activity in broad daylight and wild boar during dusk. Activity level increased with population density only for wild boar. Food availability and hunting showed no correlation with activity patterns. These findings indicate that ungulate activity is to some degree density dependent. However, while these patterns might result from larger populations feeling safer as the safety-in-numbers theory states, we cannot rule out that they are the outcome of greater intraspecific competition for food, forcing animals to forage during suboptimal times of the day. Overall, this study demonstrates that wild ungulates adjust their activity spread and level based on their population size.</span></span></span></span></span></span></span></span></span></span></span></p>
Data and Scripts used in "Analysis of Relations Between Solar Activity, Cosmic Rays and Earth Climate Using Machine Learning Techniques"
<p>This archive contains the data in relation to the work:</p> <p>Analysis of relations between solar activity, cosmic rays and earth climate using machine learning techniques<br> B. Belen, U. M. Leloglu, and M. B. Demirkoz </p> <p>See README file for more details.</p>
Data from: Structure of the rare archaeal biosphere and seasonal dynamics of active ecotypes in surface coastal waters
Marine Archaea are important players among microbial plankton and significantly contribute to biogeochemical cycles, but details regarding their community structure and long-term seasonal activity and dynamics remain largely unexplored. In this study, we monitored the inter-annual archaeal community composition of abundant and rare biospheres in northwestern Mediterranean Sea surface waters by pyrosequencing 16S rDNA and rRNA. A detailed analysis of the rare biosphere structure showed that the rare archaeal community was composed of three distinct fractions. One contained the rare Archaea that became abundant at different times within the same ecosystem; these cells were typically not dormant, and we hypothesize that they represent a local seed bank that is specific and essential for ecosystem functioning through cycling seasonal environmental conditions. The second fraction contained cells that were uncommon in public databases and not active, consisting of aliens to the studied ecosystem and representing a non-local seed bank of potential colonizers. The third fraction contained Archaea that were always rare but actively growing; their affiliation and seasonal dynamics were similar to the abundant microbes and could not be considered a seed bank. We also showed that the major archaeal groups, Thaumarchaeota Marine Group-I (MGI) and Euryarchaeota Group-II.B (MGII.B) in winter and Euryarchaeota Group-II.A (MGII.A) in summer, contained different ecotypes with varying activities. Our findings suggest that archaeal diversity could be associated with distinct metabolisms or life strategies, and that the rare archaeal biosphere is composed of a complex assortment of organisms with distinct histories that affect their potential for growth.
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.