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4,276 results for “Estimation”
Apresentação para o Prêmio Iniciação Científica - CBEB2020: Evaluation of the Motor Performance of People with Parkinson's Disease through the Autocorrelation Function Estimated from Sinusoidal Drawings
<p>The objective of this work was to use the autocorrelation function to assess the fine motor performance of a healthy control group (CG) and people with Parkinson's disease (PD), whose fluctuations caused by the disease compromise motor skills, performed mainly by the hands and fingers essential for daily activities such as dressing, carrying objects and taking care of personal hygiene. For this, accelerometer signals were collected while the volunteers drew a sinusoidal pattern. The correlogram was estimated and two features were calculated from it: (i) the normalized area under the curve (𝑨𝒖𝑪); (ii) the difference between matching peaks and valleys from the reference and estimated correlograms (𝒗𝒎𝒎). These features allowed for the discrimination between drawing patterns of CG (𝒗𝒎𝒎= 0.154±0.063, 𝑨𝒖𝑪 = 0.204±0.040) and PD (𝒗𝒎𝒎 = 0.239±0.085, 𝑨𝒖𝑪 = 0.179±0.033) groups. Following the verification of normality (Shapiro-Wilk, p > 0.05), the t-test was applied to confirm the significant differences between groups (p < 0.05). The Cohen’s d effect size (p < 0.05) was medium (0.730) for 𝑨𝒖𝑪 and large (1.252) for 𝒗𝒎𝒎. This further confirms the differences between the features extracted from the groups. Therefore, the features 𝑨𝒖𝑪 and 𝒗𝒎𝒎 estimated from the autocorrelation function are effective for the assessment of the motor performance of healthy individuals and people with PD. </p>
Data from: Egg laying rather than host quality or host feeding experience drives habitat estimation in the parasitic wasp Nasonia vitripennis
<p>In variable environments, sampling information on habitat quality is essential for making adaptive foraging decisions. In insect parasitoids, females foraging for hosts have repeatedly been shown to employ behavioral strategies that are in line with predictions from optimal foraging models. Yet, which cues exactly are employed to sample information on habitat quality, has rarely been investigated. Using the gregarious parasitoid <i>Nasonia vitripennis</i> (Walker) (Hymenoptera: Pteromalidae), we provided females with different cues about hosts to elucidate, which of them would change a wasp's posterior behavior suggesting a change in information status. We employed posterior clutch size decisions on a host as proxy for a female's estimation of habitat quality. Taking into account changes in physiological state of the foraging parasitoid, we tested whether different host qualities encountered previously change the subsequent clutch size decision in females. Additionally, we investigated whether other kinds of positive experiences - such as ample time to investigate hosts, host feeding, or egg laying - would increase a wasp's estimated value of habitat quality. Contrary to our expectations, quality differences in previously encountered hosts did not affect clutch size decisions. However, we found that prior egg laying experience changes posterior egg allocation to a host, indicating a change in female information status. Host feeding and the time available for host inspection, though correlated with egg laying experience, did not seem to contribute to this change in information status.</p>
Robust estimates of the true (population) infection rate for COVID-19: a backcasting approach
<p>Differences in COVID-19 testing and tracing across countries, as well as changes in testing within each country over time, make it difficult to estimate the true (population) infection rate based on the confirmed number of cases obtained through RNA viral testing. We applied a backcasting approach to estimate a distribution for the true (population) cumulative number of infections (infected and recovered) for 15 developed countries. Our sample comprised countries with similar levels of medical care and with populations that have similar age distributions. Monte Carlo methods were used to robustly sample parameter uncertainty. We found a strong and statistically significant negative relationship between the proportion of the population who test positive and the implied true detection rate. Despite an overall improvement in detection rates as the pandemic has progressed, our estimates showed that, as at 31 August 2020, the true number of people to have been infected across our sample of 15 countries was 6.2 (95% CI: 4.3–10.9) times greater than the reported number of cases. In individual countries, the true number of cases exceeded the reported figure by factors that range from 2.6 (95% CI: 1.8–4.5) for South Korea to 17.5 (95% CI: 12.2–30.7) for Italy.</p>
Selective extinctions resulting from random habitat destruction lead to under‐estimates of local and regional biodiversity loss in a manipulative field experiment
<p>Land-use change is a significant cause of anthropogenic extinctions, which are likely to continue and accelerate as habitat conversion proceeds in most biomes. One way to understand the effects of habitat loss on biodiversity is through improved tools for predicting the number and identity of species losses in response to habitat loss. There are relatively few methods for predicting extinctions and even fewer opportunities for rigorously assessing the quality of these predictions. In this paper we address these issues by applying a new method based on rarefaction to predict species losses after random, but aggregated, habitat loss. We compare predictions from three rarefaction models, individual-based, sample-based, and spatially-clustered, to those derived from a commonly-used extinction estimation method, the Species-Area Relationship (SAR). We apply each method to a mesocosm experiment, in which we aim to predict species richness and extinctions of arthropods immediately following 50% habitat loss. While each model produced strikingly accurate predictions of species richness immediately after the habitat loss disturbance, each model significantly underestimated the number of extinctions occurring at both the local (within-mesocosm) and regional (treatment-wide) scales. Despite the stochastic nature of our small-scale, short-term, and randomly applied habitat loss experiment, we found surprisingly clear evidence for extinction selectivity, for example when abundant species with low extinction probabilities were extirpated following habitat loss. The important role played by selective extinction even in this contrived experimental system suggests that ecologically driven, trait-based extinctions play an equally important role to stochastic extinction, even when the disturbance itself has no clear selectivity. As a result, neutrally stochastic null models such as the SAR and rarefaction are likely to underestimate extinctions caused by habitat loss. Nevertheless, given the difficulty of predicting extinctions, null models provide useful benchmarks for conservation planning by providing minimum estimates and probabilities of species extinctions.</p>
Data for quantitative precipitation estimation with Rulefit
<p>This is the data that I used for quantitative precipitation estimation with Rulefit. rain represents the rain data, band 07-10 is the Himawari 8 satellite data. radar is the combined reflectivity data. Three kinds of data were preprocessed into the array with the shape of 301*279, and extracted the region of interest(east china) with python package(Salem). Then, these array are flattened and concatenated into pandas dataframe. nan value was dropped by dropna. I saved the data in the format of csv. As the review of manuscript progresses, I will continue to provide new versions and give new doi here.</p>
All simulation results, figures and code regarding the manuscript: Calibrating models of cancer invasion: parameter estimation using Approximate Bayesian Computation and gradient matching
<p>We present two different methods to estimate parameters within a partial differential equation (PDE) model of cancer invasion. The model describes the spatio-temporal evolution of three variables -- tumour cell density, extracellular matrix density and matrix degrading enzyme concentration -- in a one-dimensional tissue domain. The first method is a likelihood-free approach associated with Approximate Bayesian Computation (ABC); the second is a two-stage gradient matching method based on smoothing the data with a Generalized Additive Model (GAM) and matching gradients from the GAM to those from the model. Both methods performed well on simulated data. To increase realism, additionally we tested the gradient matching scheme with simulated measurement error and found that the ability to estimate some model parameters deteriorated rapidly as measurement error increased.</p>
Influence of Quaternary environmental changes on mole populations inferred from mitochondrial sequences and evolutionary rate estimation
<p><span><span><span><span><span><span><span><span><span><span><span>Quaternary environmental changes fundamentally influenced genetic diversity of the temperate-zone terrestrial animals, including those on the Japanese Archipelago. The genetic diversity of present-day populations are taxon and region specific, but its determinants are poorly understood. Here, we analyzed cytochrome <i>b</i> gene (<i>Cytb</i>) sequences (1,140 bp) of mitochondrial DNA (mtDNA) to elucidate factors determining the genetic variation in three species of large moles: <i>Mogera imaizumii</i> and <i>Mogera wogura</i> occur in Northern and Southern mainland Japan (Honshu, Shikoku, and Kyushu), and <i>Mogera robusta </i>occurs on the nearby Asian continent<i>.</i> Network construction with the <i>Cytb</i> sequences revealed 10 star-shaped clusters with apparent geographic affinity. Mismatch distribution analysis showed that modes of pairwise nucleotide differences (t values) were grouped into five classes in terms of the level, implying the occurrence of five stages for the rapid expansion. It is conceivable that a severe cold periods and a subsequent warm periods during the late Quaternary are responsible for the population expansion events. The first and third oldest events include island-derived haplotypes, indicative of involvement of land bridge formation between remote islands, hence suggesting association of the ends of the penultimate (PGM, ca. 130,000 years ago) and last (LGM, ca. 15,000 years ago) glacial maxima, respectively. Since the third one is followed by the fourth one, it is plausible that the termination of Younger Dryas and subsequent abrupt warming at ca. 11,500 years ago facilitated the fourth expansion event. The second is most likely corresponding to the early marine isotope stage (MIS) 3 (ca. 53,000 years ago) when the glaciation and subsequent warming period are predicted to have influenced biodiversity. Utilization of the critical times of 130,000, 53,000, 15,000, and 11,500, years ago as calibration points yielded evolutionary rates of 0.03, 0.045, 0.10 and 0.10 substitutions/site/million years, respectively, showing the time-dependent manner whose pattern is similar to that seen in small rodents reported in our previous studies. The age of the fifth expansion event was calculated to be 5,800 years ago with the rate of 0.10 substitutions/site/million years ago, during the mid-Holocene, suggestive of influence of humans or other unspecified reason, such as the Jomon marine transgression. </span></span></span></span></span></span></span></span></span></span></span></p>
June 2020 Eclipse Festival of Frequency Measurement - 10 MHz Frequency Estimation Data
<p>Frequency estimation and amplitude output from fldigi during the June Eclipse Festival of Frequency Measurement, synchronized as timetables in MATLAB. </p> <p>JEF_List: Station list with coordinates and basic information. <br> Freq.txt, Vpk.txt: short period of overlap between stations.<br> Freq_full.txt, Vpk_full.txt: Complete data, including practice and bonus data collection days. </p> <p>Thanks to all who collected data: 3V1E, 3V8SS, 9V1AW, 9V1KB, A45VU, A47RS, AD7TS, AD8Y, DK4BU, EAllUO, El7IG, F1ABL, F4IEW, GOLHZ, HZ1HM-SU9HM, JF9PKH, J13XOK/8, JJ1BDX, K1FR, K6FOD, K6RGI, KA3JAW, KD8CGH, KF5SMH, Luo Zhiwen, N7MN, NAOB, OE3WYC, PAOSLT, PAORWT, PA4WE, PD4C, PE1RCW, PE1RWP, PU3VRW, SA6EAL, SP9MUF, SP9WPN, SV1GRB, SV1IT, SV1ONK, SV1VC, SV2BBO, SV7BOT, Andrew Klekociuk, VK2DLR, VK3DFR, VK7KPC, W3LLA, and ZS6YZ.</p> <p>__________________________________________________________</p> <p><strong>Errata:</strong><br> Coordinate error: G0LHZ is <em>west</em> of the Greenwich line:<strong> G0LHZ Jim Carter 51.507468 - 1.080013</strong></p>
Distance estimates for "Gaia Early Data Release 3: The Galactic anticentre"
<p>Distance estimates used by "Gaia Early Data Release 3: The Galactic anticentre", Gaia Collaboration, Antoja et al.</p> <p>These are Bayesian distances with an iterative prior, referred to as d<sub>PM </sub>within the paper (Appendix C). A parallax zero-point correction of 17µas has been applied before calculation.</p> <p>Any use of these distances should cite that paper.</p>
Estimating individual level plant traits at scale: input data
<p>This dataset includes the input data to ensure replicability of the results. This dataset include the (1) reflectance for individual tree crowns, extracted from field and algorithmically delineated crowns in 2 NEON sites (OSBS and TALL); (2) the associated measures of tree traits (N%, C%, P%, LMA). The folder should be decompressed inside of the root directory of the project in https://github.com/MarconiS/Estimating-individual-level-plant-traits-at-scale/ for correctly replicate the analysis.</p>
Specular Meteor Radar wind estimates from Tirupati, used in "Validation of ICON-MIGHTI thermospheric wind observations: 2. Greenline comparisons to specular meteor radars" by Harding et al. (2021)"
<pre>This dataset was used to generate the figures in the paper mentioned above and is being made available for the sake of reproducibility and future analysis. The primary variables are u0, v0 (the zonal and meridional wind profiles observed by the meteor radar). Dimensions are "time" and "alt" (in km). Velocity units are m/s, and lat/lon are in degrees. More information can be found in the paper. Please contact and get permission from the data providers (M. Venkat Ratnam and S. Vijaya Bhaskara Rao) before using the data in any publications or presentations.</pre>
Uncertainties associated with microwave link rainfall estimates in an urban environment
<p>These dataset were collected from a dedicated microwave link setup between Mt View Reservoir (T) and 33 Lakeside Burwood (R). There were two OTT1 disdrometers installed at both ends of the microwave link complemented by 3 tipping bucket rain gauges. </p>
Estimating the inbreeding level and genetic relatedness in an isolated population of critically endangered Sichuan taimen (Hucho bleekeri) using genome wide SNP markers
<p>Sichuan taimen (Hucho bleekeri) is critically endangered fish listed in The Red List of Threatened Species compiled by the International Union for Conservation of Nature (IUCN). Specific locus amplified fragment sequencing (SLAF-seq)-based genotyping was performed for Sichuan taimen with 43 yearling individuals from 3 locations in Taibai River (a tributary of Yangtze River) that has been sequestered from its access to the ocean for more than 30 years since late 1980s. Applying the inbreeding level and genetic relatedness estimation using 15,396 genome wide SNP markers, we found that the inbreeding level of this whole isolated population was at a low level (average F=2.6×10-3±0.079), and the means of coancestry coefficients within and between the three sampling locations were all very low (close to 0), too. Genomic differentiation was negatively correlated with the geographical distances between the sampling locations (p < 0.001) and the 43 individuals could be considered as genetically independent two groups. The low levels of genomic inbreeding and relatedness indicated a relatively large number of sexually mature individuals were involved in reproduction in Taibai River. This study suggested a genomic-relatedness-guided breeding and conservation strategy for wild fish species without pedigree information records.</p>
Data from: Pliant pathogens: estimating viral spread when confronted with new vector, host, and environmental conditions
<p>1. Pathogen spread rates are determined, in part, by the performance of pathogens under altered environmental conditions and their ability to persist while switching among hosts and vectors.</p> <p>2. To determine the effects of new conditions (host, vector, and nutrient) on pathogen spread rate, we introduced a vector-borne, viral plant pathogen, Barley Yellow Dwarf Virus PAV (BYDV-PAV) into hosts, vectors, and host nutrient supplies that it had not encountered for thousands of viral generations. We quantified pathogen prevalence over the course of two serial inoculations under the new conditions. Using individual level transmission rates from this experiment, we parameterized a dynamical model of disease spread and projected spread across host populations through a growing season. </p> <p>3. A change in nutrient conditions (increased supply of phosphorus) reduced viral transmission whereas shifting to a new vector or host species had no effect on infection prevalence. However, the reduction in the new nutrient environment was only temporary; infection prevalence recovered after the second inoculation.</p> <p><i>4. Synthesis</i>. These results highlight how robust the pathogen, BYDV-PAV, is to changes in its biotic and abiotic environment. Our study also highlights the need to quantify longitudinal infection information beyond snapshot assessments to project disease risk for pathogens in new environments.</p>
Data from: Overcoming the challenge of small effective sample sizes in home-range estimation
Technological advances have steadily increased the detail of animal tracking datasets, yet fundamental data limitations exist for many species that cause substantial biases in home‐range estimation. Specifically, the effective sample size of a range estimate is proportional to the number of observed range crossings, not the number of sampled locations. Currently, the most accurate home‐range estimators condition on an autocorrelation model, for which the standard estimation frame‐works are based on likelihood functions, even though these methods are known to underestimate variance—and therefore ranging area—when effective sample sizes are small. Residual maximum likelihood (REML) is a widely used method for reducing bias in maximum‐likelihood (ML) variance estimation at small sample sizes. Unfortunately, we find that REML is too unstable for practical application to continuous‐time movement models. When the effective sample size N is decreased to N ≤ urn:x-wiley:2041210X:media:mee313270:mee313270-math-0001(10), which is common in tracking applications, REML undergoes a sudden divergence in variance estimation. To avoid this issue, while retaining REML's first‐order bias correction, we derive a family of estimators that leverage REML to make a perturbative correction to ML. We also derive AIC values for REML and our estimators, including cases where model structures differ, which is not generally understood to be possible. Using both simulated data and GPS data from lowland tapir (Tapirus terrestris), we show how our perturbative estimators are more accurate than traditional ML and REML methods. Specifically, when urn:x-wiley:2041210X:media:mee313270:mee313270-math-0002(5) home‐range crossings are observed, REML is unreliable by orders of magnitude, ML home ranges are ~30% underestimated, and our perturbative estimators yield home ranges that are only ~10% underestimated. A parametric bootstrap can then reduce the ML and perturbative home‐range underestimation to ~10% and ~3%, respectively. Home‐range estimation is one of the primary reasons for collecting animal tracking data, and small effective sample sizes are a more common problem than is currently realized. The methods introduced here allow for more accurate movement‐model and home‐range estimation at small effective sample sizes, and thus fill an important role for animal movement analysis. Given REML's widespread use, our methods may also be useful in other contexts where effective sample sizes are small.
Data from: Estimating synchronous demographic changes across populations using hABC and its application for a herpetological community from northeastern Brazil
Many studies propose that Quaternary climatic cycles contracted and /or expanded the ranges of species and biomes. Strong expansion-contraction dynamics of biomes presume concerted demographic changes of associated fauna. The analysis of temporal concordance of demographic changes can be used to test the influence of Quaternary climate on diversification processes. Hierarchical approximate Bayesian computation (hABC) is a powerful and flexible approach that models genetic data from multiple species, and can be used to estimate the temporal concordance of demographic processes. Using available single-locus data we can now perform large-scale analyses, both in terms of number of species and geographic scope. Here we first compared the power of four alternative hABC models for a collection of single-locus data. We found that the model incorporating an a priori hypothesis about the timing of simultaneous demographic change had the best performance. Secondly, we applied the hABC models to a dataset of 7 squamate and 4 amphibian species occurring in the Seasonally Dry Tropical Forests (Caatinga) in Northeastern Brazil, which, according to paleoclimatic evidence, experienced an increase in aridity during the Pleistocene. If this increase was important for the diversification of associated xeric-adapted species, simultaneous population expansions should be evident at the community level. We found a strong signal of synchronous population expansion in the Late Pleistocene, supporting the expansion of the Caatinga during this time. This expansion likely enhanced the formation of communities adapted to high aridity and seasonality and caused regional extirpation of taxa adapted to wet forest.
Data from: Estimating abundance of an open population with an N-mixture model using auxiliary data on animal movements
Accurate assessment of abundance forms a central challenge in population ecology and wildlife management. Many statistical techniques have been developed to estimate population sizes because populations change over time and space, and to correct for the bias resulting from animals that are present in a study area but not observed. The mobility of individuals makes it difficult to design sampling procedures that account for movement into and out of areas with fixed jurisdictional boundaries. Aerial surveys are the gold standard used to obtain data of large mobile species in geographic regions with harsh terrain, but these surveys can be prohibitively expensive and dangerous. Estimating abundance with ground based census methods have practical advantages, but it can be difficult to simultaneously account for temporary emigration and observer error to avoid biased results. Contemporary research in population ecology increasingly relies on telemetry observations of the states and locations of individuals to gain insight on vital rates, animal movements, and population abundance. Analytical models that use observations of movements to improve estimates of abundance have not been developed. Here we build upon existing multi-state mark recapture methods using a hierarchical N-mixture model with multiple sources of data, including telemetry data on locations of individuals, to improve estimates of population sizes. We used a state-space approach to model animal movements to approximate the number of marked animals present within the study area at any observation period, thereby accounting for a frequently changing number of marked individuals. We illustrate the approach using data on a population of elk (Cervus elaphus nelsoni) in Northern Colorado, USA. We demonstrate substantial improvement compared to existing abundance estimation methods and corroborate our results from the ground based surveys with estimates from aerial surveys during the same seasons. We develop a hierarchical Bayesian N-mixture model using multiple sources of data on abundance, movement and survival to estimate the population size of a mobile species that uses remote conservation areas. The model improves accuracy of inference relative to previous methods for estimating abundance of open populations.
Data from: Estimation of energetic condition in wild baboons using fecal thyroid hormone determination
Understanding how environmental and social factors affect reproduction through variation in energetic condition remains understudied in wild animals, in large part because accurately and repeatedly measuring energetic condition in the wild is a challenge. Thyroid hormones (THs), such as triiodothyronine (T3) and thyroxine (T4), have a key role in mitigating metabolic responses to energy intake and expenditure, and therefore are considered important biomarkers of an animal's energetic condition. Recent method development has shown that T3 and T4 metabolites can be measured in feces, but studies measuring THs in wild populations remain rare. Here we measured fecal T3 metabolites (mT3) in baboons, and tested whether the conditions of collection and storage used for steroid hormones could also be used for mT3; we focused on mT3 as it is the biologically active form of TH and because fecal T4 metabolites (mT4) were below detection levels in our samples. We also tested if mT3 could be determined in freeze-dried samples stored for long periods of time, and if these concentrations reflected expected biological variations across seasons and reproductive states. Our results show that mT3 can be measured with accuracy and precision in baboon feces. The conditions of collection and storage we use for steroid hormones are appropriate for mT3 determination. In addition, mT3 concentrations can be determined in samples stored at -20 °C for up to 9 years, and are not predicted by the amount of time in storage. As expected, wild female baboons have lower mT3 concentrations during the dry season. Interestingly, mT3 concentrations are lower in pregnant and lactating females, possibly reflecting an energy sparing mechanism. Retroactive determination of mT3 concentration in stored, freeze-dried feces opens the door to novel studies on the role of energetic condition on fitness in wild animals.
Population structure of five native sheep breeds of Sweden estimated with high density SNP genotypes
Background <p>Native Swedish sheep breeds are part of the North European short-tailed sheep group; characterized in part by their genetic uniqueness. Our objective was to study the population structure of native Swedish sheep. Five breeds were genotyped using the 600 K SNP array. Dalapäls and Klövsjö sheep are from the middle of Sweden; Gotland and Gute sheep from Gotland, an island in the Baltic Sea; and Fjällnäs sheep from northern Sweden. We studied population structure by: principal component analysis (PCA), cluster-based analysis of admixture, and an estimated population tree.</p> Results <p>The analyses of the five Swedish breeds revealed that these breeds are five distinct breeds, while Gute and Gotland are more closely related to each other as seen in all analyses. All breeds had long branch lengths in the population tree indicating they've been subjected to drift. We repeated our analyses using 39 K SNP and including 50 K SNP genotypes from other European and southwestern Asian breeds from the Sheep HapMap project and 600 K SNP genotypes from a dataset of French sheep. Results arranged breeds into five groups: south-west Asia, south-west Europe, central Europe, north Europe and north European short-tailed sheep. Within this last group, Norwegian and Icelandic breeds, Finn and Romanov sheep, Scottish breeds, and Gute and Gotland sheep were more closely related while the remaining Swedish breeds and Ouessant sheep were distinct from all breeds and had longer branches in the population tree.</p> Conclusions <p>We showed population structure of five Swedish breeds and their structure within European and southwestern Asian breeds. Swedish breeds are unique, distinct breeds that have been subjected to drift but group with other north European short-tailed sheep.</p>
Figure 2. Bird species accumulation curve and estimated richness curve obtained from the Chao 1 in Avifauna of the region of the Volta Grande Hydroelectric Power Plant in Southeast Brazil
Figure 2. Bird species accumulation curve and estimated richness curve obtained from the Chao 1 index for the study area located throughout the reservoir of the Volta Grande Hydroelectric Power Plant in Southeast Brazil. Vertical bars represent the standard deviation of the estimate.
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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.