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1,047 results for “constraint”
Direct and indirect effects of environmental factors, spatial constraints, and functional traits on shaping the plant diversity of montane forests
Understanding the relative importance of the factors driving the patterns of biodiversity is a key research topic in community ecology and biogeography. However, the main drivers of plant species diversity in montane forests are still not clear. In addition, most existing studies make no distinction between direct and indirect effects of environmental factors, spatial constraints on plant biodiversity. Using data from 107 montane forest plots in Sichuan Giant Panda habitat, China, we quantified the direct and indirect effects of abiotic environmental factors, spatial constraints, and plant functional traits on plant community diversity. Our results showed significant correlations between abiotic environmental factors and trees (r = 0.10, P value = 0.001), shrubs (r = 0.19, P value = 0.001), or overall plant diversity (r = 0.18, P value = 0.001) in montane forests. Spatial constraints also showed significant correlations with trees, and shrubs. However, no significant correlations were found between functional traits and plant community diversity. Moreover, the diversity (richness and abundance) of shrubs, trees, and plant communities was directly affected by precipitation, latitude, and altitude. Mean annual temperature (MAT) had no direct effect on the richness of tree and plant communities. Further, MAT and precipitation indirectly affected plant communities via the tree canopy. The results revealed a stronger direct effect on montane plant diversity than indirect effect, suggesting that single-species models may be adequate for forecasting the impacts of climate factors in these communities. The shifting of tree canopy coverage might be a potential indicator for trends of plant diversity under climate change.
Data from: Metabolic scope as a proximate constraint on individual behavioral variation: effects on 'personality', plasticity, and predictability
Behavioral ecologists have hypothesized that among-individual differences in resting metabolic rate (RMR) may predict consistent individual differences in mean values for costly behaviors, or for behaviors that affect energy intake rate. This hypothesis has empirical support and presently attracts considerable attention, but notably it does not provide predictions for individual differences in (a) behavioral plasticity or (b) unexplained variation (residual variation from mean individual behavior, here termed predictability). We outline how consideration of aerobic maximum metabolic rate (MMR) and particularly aerobic scope (= MMR - RMR) can be used to simultaneously make predictions about mean, among- and within-individual variation in behavior. We predict that while RMR should be proportional to an individuals' mean level of sustained behavioral activity (one aspect of its personality), individuals with greater aerobic scope will also have greater scope to express behavioral plasticity and/or greater unpredictability in behavior (= greater residual variation). As a first step towards testing these predictions, we analyse existing activity data from selectively bred lines of mice that differ in both daily activity and aerobic scope. We find that replicate high-scope mice are more active on average, show greater among-individual variation in activity, greater among-individual variation in plasticity, and greater unpredictability. These data provide some tentative first support for our hypothesis, suggesting that further research on this topic would be valuable.
Data from: Optimizing the genetic composition of a translocation population: incorporating constraints and conflicting objectives
Translocations of threatened species can reduce the risk of extinction from a catastrophic event. For plants, translocation consists of moving individuals, seeds, or cuttings from a native (source) population to a new site. Ideally a translocation population would be genetically diverse and consist of fit founding individuals. In practice, there are challenges to designing such a population, including constraints on the availability of material, and tradeoffs between different goals. We present an approach for designing a translocation population that identifies sets of founders that are optimized according to multiple criteria (e.g., genetic diversity), while also conforming to constraints on the representation of different founders (e.g., propagation success). It uses flexible inputs, including SNP genotypes, matrices of similarity between individuals, and vectors of phenotype data. We apply the approach to a critically endangered plant, Hibbertia puberula subsp. glabrescens (Dilleniaceae), which was genotyped at thousands of SNP loci. The goals of minimizing genetic similarity among the founding individuals and maximizing genetic diversity were largely complementary – populations optimized for one of these criteria were near-optimal for the other. We also performed analyses in which we minimized genetic similarity among founding individuals while imposing selection (against hypothetical deleterious alleles, and against undesirable phenotypes, respectively), and here characterized sharp tradeoffs. This is useful in allowing the benefits of selection to be weighed against 'costs' in terms of genetic similarity. In sum, we present an approach for designing a translocation population that allows flexible inputs, the imposition of realistic constraints, and examination of conflicting goals.
Data from: Increased female resistance to mating promotes the effect of mechanical constraints on latency to pair
Size-assortative mating, defined as a positive linear association of body size between members of mating pairs, can arise from mechanical constraints on pairing efficiency, particularly when mating success is affected by males' mate-grasping force. In this context, female resistance is predicted to have an important role in changing the threshold force necessary for males to hold females, thereby contributing to the effect of mechanical constraints. Thus, increased female resistance is expected to increase the paring success of an optimally sized male relative to the female body size (sexual size ratio = male body size/female body size = 0.86), which leads to positive size-assortative mating. However, very little is known about the extent to which female resistance affects mechanical constraints on mate grasping. Here, using the water strider Gerris gracilicornis (Hemiptera: Gerridae), we tested whether the level of female resistance affected the relationship between the sexual size ratio and latency to pair. We found that optimally sized males mated sooner than other males when females resisted a male's mating attempts. When females did not resist, an effect of sexual size ratio on latency to pair was not found. Our results thus imply that increased female resistance to male mating attempts may strengthen the pattern of size-assortative mating. We provide clear empirical evidence that female resistance to mating influences the effect of mechanical constraints on size-assortative mating under sexual conflict. This result further suggests that patterns of size-assortative mating can be altered by a variety of ecological circumstances that change female resistance to mating in many other animal species under sexual conflict.
Data from: The roles of compensatory evolution and constraint in aminoacyl tRNA synthetase evolution
Mitochondrial protein translation requires interactions between transfer RNAs encoded by the mitochondrial genome (mt-tRNAs) and mitochondrial aminoacyl tRNA synthetase proteins (mt-aaRS) encoded by the nuclear genome. It has been argued that animal mt-tRNAs have higher deleterious substitution rates relative to their nuclear-encoded counterparts, the cytoplasmic tRNAs (cyt-tRNAs). This dynamic predicts elevated rates of compensatory evolution of mt-aaRS that interact with mt-tRNAs, relative to aaRS that interact with cyt-tRNAs (cyt-aaRS). We find that mt-aaRS do evolve at significantly higher rates (exemplified by higher dN and dN/dS) relative to cyt-aaRS, across mammals, birds, and Drosophila. While this pattern supports a model of compensatory evolution, the level at which a gene is expressed is a more general predictor of protein evolutionary rate. We find that gene expression level explains 10-56% of the variance in aaRS dN/dS, and that cyt-aaRS are more highly expressed in addition to having have lower dN/dS values relative to mt-aaRS, consistent with more highly expressed genes being more evolutionarily constrained. Furthermore, we find no evidence of positive selection acting on either class of aaRS protein, as would be expected under a model of compensatory evolution. Nevertheless, the signature of faster mt-aaRS evolution persists in mammalian, but not bird or Drosophila, lineages after controlling for gene expression, suggesting some additional effect of compensatory evolution for mammalian mt-aaRS. We conclude that gene expression is the strongest factor governing differential amino acid substitution rates in proteins interacting with mitochondrial versus cytoplasmic factors, with important differences in mt-aaRS molecular evolution among taxonomic groups.
Data from: Time constraint effects on phenology and life history synchrony in a damselfly along a latitudinal gradient
In organisms with complex life cycles living in seasonal environments, the synchronisation of phenological events is important from the ecological and evolutionary perspectives. Life history transitions should be synchronised to a greater degree at northern latitudes. We quantified hatching and emergence timing and synchrony in the obligate univoltine damselfly Lestes sponsa along a latitudinal gradient covering its entire north–south range in Europe. In our first experiment, populations from different latitudes were grown in separate climate chambers simulating temperature and photoperiod conditions occurring at their sites of origin. Northern populations expressed early and high synchronous hatching and emergence, central populations intermediate, and southern populations late and low synchronous hatching and emergence. This pattern was expressed at both population and full-sibling family levels, indicating stronger selection for timing and synchronisation in the north compared to the south. In our second experiment, populations from all latitudes were reared in conditions simulating an average temperature and photoperiod over the latitudinal gradient. Interestingly, the pattern of timing and synchronisation was reversed with respect to latitude when compared to the pattern shown in the first experiment, indicating the importance of environmental factors in shaping phenological events. Our results indicate strong selection for timing and synchronisation of life history events at northern latitudes, caused by time constraints. Our results also show that it is important to use as natural conditions as possible in experiments on life history shifts in organisms with complex life cycles in order to achieve a correct understanding of these shifts.
Tracer and Observationally-Derived Constraints on Diapycnal Diffusivities in an Ocean State Estimate
<p>Data used to generate the figures in Trossman et al. (2022) in Ocean Science, an EGU journal</p>
Exploiting Strict Constraints in the Computation of Cylindrical Algebraic Coverings - Illustration
<p>Graphical illustration of the running example in the bachelor thesis "Exploiting Strict Constraints in the Computation of Cylindrical Algebraic Coverings".</p>
Data for "Towards quantum gravity with neural networks: Solving the quantum Hamilton constraint of U(1) BF theory"
<h2>1. Repository Information</h2> <p>This repository contains the data produced during the work discussed in in the paper "<a href="https://iopscience.iop.org/article/10.1088/1361-6382/ad84af" target="_blank" rel="noopener">Towards quantum gravity with neural networks: Solving the quantum Hamilton constraint of U(1) BF theory</a>". Please refer to this paper for more details on how the data was produced.</p> <p> </p> <h2>2. Citing</h2> <p>In addition to citing this repository, please also cite the paper mentioned above if you use the data. The citations is:</p> <p>[1] Hanno Sahlmann and Waleed Sherif 2024 <em>Class. Quantum Grav.</em> <strong>41</strong> 225014</p> <p> </p> <h2>3. File Description</h2> <p>In this repository, you will find 4 general directories (here called parent directories):</p> <ol> <li>Tabulated Data</li> <li>Misc</li> <li>Entanglement Entropy</li> <li>Appendix Data</li> </ol> <p>Each of these directories correposnd to different data produced and discussed in the corresponding parts in the paper mentioned above (e.g. the directory "Tabulated Data" contains the data used in Table 1 and Table 2 in the paper).</p> <p>Each of these parent directories contain within them several sub-directories (child directories) corresponding to different produced data. The raw data can be found in a <code>.json</code> file inside the child directories.</p> <p> </p> <h2>4. Usage</h2> <h3>4.1 Raw Simulation Data</h3> <p>The <code>.json</code> files include the raw data produced during the study. These files can be easily accessed using a python script, as an example, by using:</p> <p><code>import json</code></p> <p><code>filePath = ...</code></p> <p><code>data = json.load(open(filePath))</code></p> <p>where <code>filePath</code> should hold the correct path to the local data once downloaded. Once loaded, the data is handled as a python <code>dict</code>. The dictionary will have a parent key called "Energy", which in itself is yet another dictionary which will always include the keys:</p> <ul> <li>iters</li> <li>Mean</li> <li>Variance</li> <li>Sigma</li> <li>R_hat</li> <li>TauCorr</li> </ul> <p>Hence, to access the "Mean" values, you use <code>data["Energy"]["Mean"]</code>. The data represents the values during a simulation of typically 500 iterations, hence, each of the keys mentioned above will correspond to an array of 500 items. The <code>iters</code> array includes merely the iteration number. The <code>Mean</code> array includes the value of the expectation value of the constraint at the corresponding iteration. The <code>Variance</code>, <code>Sigma</code>, <code>R_hat</code> and <code>TauCorr</code> includes the values of the variance and error in the expectation value at the given iteration as well as the split R-hat diagnostic and the time correlation also in the given iteration. </p> <p> </p> <h3>4.2 Variational State Data</h3> <p>Additionally, some child directories will include a <code>.npy</code> file, which holds the amplitudes of the variational state for the given simulation. These files should be loaded using numpy in python. For example:</p> <p><code>import numpy as np</code></p> <p><code>filePath = ...</code></p> <p><code>varState = np.load(filePath)</code></p> <p>This will load the amplitudes as an array into the <code>varState</code> variable.</p> <p> </p> <h3>4.3 Fluctuation results</h3> <p>In some child directories, there will be a <code>.txt</code> file which includes the output of the calculation of the expectation value of some operators and their quantum fluctuations. These are only results, and not data, as the data can only be computed during the simulation.</p> <p> </p> <h2>5. Contact</h2> <p>Shall you have any unanswered questions regarding the usage of the data, please contact the author:</p> <p>Waleed Sherif</p> <p>email: waleed.sherif@fau.de</p> <p> </p> <h2>6. References</h2> <p>The data provided in this repository was produced using the <a href="https://github.com/netket" target="_blank" rel="noopener">NetKet</a>[1] package</p> <p>[1] <a href="https://doi.org/10.21468/SciPostPhysCodeb.7" target="_blank" rel="noopener">doi: 10.21468/SciPostPhysCodeb.7</a></p> <p> </p>
Constraints on the inner core composition from the equations of state of Fe-Si-C-H alloys
Open the record for dataset details and reuse information.
Constraints on the Distances and Timescales of Solid Migration in the Early Solar System from Meteorite Magnetism
<p>Alternating field and thermal demagentisation data for the WIS 91600 meteorite, published in 'Constraints on the Distances and Timescales of Solid Migration in the Early Solar System from Meteorite Magnetism' (2020) <em>The Astrophysical Journal</em>, <strong>896</strong>, 103</p>
Dataset for "Divergent climate constraints and growth projections of Scots pine across Eurasia"
<p>Dataset for anonymous review of "Divergent climate constraints and growth projections of Scots pine across Eurasia"</p>
Seamount formation structure of the Tofua Arc 12 in the Lau basin: Constraints based on bathymetry and magnetic modeling
<p>Abstract</p> <p>We examined the seamount formation structures of Tofua Arc (TA) 12 in the South West Pacific by applying magnetization vector inversion (MVI) modeling to determine the structure of submarine hydrothermal deposits using bathymetric and magnetic data. Our model revealed that while ascending from deep to shallow layers, a strong concentration of magnetic susceptibility shifts from the surrounding slopes of the seamount to the caldera rim summits and directly under the caldera depression. The strong magnetic susceptibility estimated in the model correlated with the first eruption-forming seamounts and additional magma intrusion (second eruption) of the magnetic material displaced from the surrounding slope. The low magnetic susceptibility near the seafloor within this study area supports hydrothermal alteration around the inner ring fault created by the occurrence of landslides inside the caldera. Our study revealed the formation structure and the three-stage formation process of the TA 12 seamount.</p> <p> </p> <p>Data Source Description</p> <p>bathymetry : ta12-seadepm(utm)_resize_surfv6byOM.xyz</p> <p>Geomagnetic Intensity : ta12-totallevel(utm)_resize_surfv6byOM.xyz</p> <p>Total Magnetic Intensicy : ta12-anolevel(utm)_resize_surfv6byOM.xyz</p> <p>Analytic Singal : ta12-anal(utm)_resize_surfv6byOM.xyz</p> <p>Reduce to the Pole : ta12-rtp(utm)_resize_surfv6byOM.xyz</p> <p>3D Magnetization Vector Inversion : MVI_Zadd_2019_03_09_02_02_31.xyz</p> <p> </p>
"Understanding leisure constraints in tourism context: An investigation of Russian tourists' constraints in participating in recreational fishing in Finland", SPSS dataset
<p>SPSS Dataset for journal article titled ""Understanding leisure constraints in tourism context: An investigation of Russian tourists' constraints in participating in recreational fishing in Finland", SPSS dataset".<br> <br> <strong>Article abstract</strong><br> Research on leisure constraints brings insight on consumer preferences and benefits tourism service providers and developers. Understanding why people seek or avoid destination activities, such as recreational fishing, helps to develop strategies to address these constraints and to modulate participation. This case study utilizes the conceptual model of leisure constraints and extends leisure constraints research to an international setting, by focusing on Russian tourists’ recreational fishing activities in Finland. It also explores the customers’ views on the role of water quality in fishing activity. A panel data survey with 457 Russian tourists visiting Finland has showed that leisure constraints vary across recreational fishing participants, non-participants and potential participants. While Russian tourists, who have been fishing in Finland, barely express any constraints, intrapersonal and structural constraints related to knowledge about Finnish fishing environment and information about service providers received the highest ratings among non-participants and potential participants. The language barrier has become the most highly rated constraint across all groups. While females are generally more constrained than males, a closer look to gender differences among non-participants and potential participants shows that males are more constrained across several statements. This case study contributes to the leisure constraints literature, particularly applying the constraints framework to the context of international tourism and to water quality.</p>
Rysunki dla Task Allocation for Energy Optimization in Fog Computing Networks with Latency Constraints
<p>This resource contains the figures for Task Allocation for Energy Optimization in Fog Computing Networks with Latency Constraints</p>
Waveform data for the manuscript "Significant spatial variation of upper crustal anisotropy in southern Sichuan Basin, China: constraints from local shear wave splitting analysis"
<p>The folder contains the seismic waveform data (in SAC format) used for local S wave splitting measurements in this study.</p>
Robotic Modified Constraint -Induced Therapy in Patients With Spastic Hemiplegic Stroke Post Botulinum Toxin A Injection
ClinicalTrials.gov study NCT03807557. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Effect of Lower Limb Constraint Induced Movement Therapy Using a Torque-Assisted Exoskeletal Wearable Device
ClinicalTrials.gov study NCT06830707. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Dynamic Connectivity Under Metabolic Constraints
ClinicalTrials.gov study NCT04106882. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Use of Vibration During Constraint-induced Movement Therapy
ClinicalTrials.gov study NCT06452576. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
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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.