Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
6,452
datasets available to search
ShareScore release 0.9.0
Dataset results
6,452 results for “Application”
Data from: A method for detecting characteristic patterns in social interactions with an application to handover interactions
Social interactions are a defining behavioural trait of social animals. Discovering characteristic patterns in the display of such behaviour is one of the fundamental endeavours in behavioural biology and psychology, as this promises to facilitate the general understanding, classification, prediction and even automation of social interactions. We present a novel approach to study characteristic patterns, including both sequential and synchronous actions in social interactions. The key concept in our analysis is to represent social interactions as sequences of behavioural states and to focus on changes in behavioural states shown by individuals rather than on the duration for which they are displayed. We extend techniques from data mining and bioinformatics to detect frequent patterns in these sequences and to assess how these patterns vary across individuals or changes in interaction tasks. To illustrate our approach and to demonstrate its potential, we apply it to novel data on a simple physical interaction, where one person hands a cup to another person. Our findings advance the understanding of handover interactions, a benchmark scenario for social interactions. More generally, we suggest that our approach permits a general perspective for studying social interactions.
Allocating resources for land protection using continuous optimization: an application to US biodiversity conservation
Spatial optimization approaches that were originally developed to help conservation organizations determine protection decisions over small spatial scales are now used to inform global or continental scale priority setting. However, the different decision contexts involved in large-scale resource allocation need to be considered. We present a continuous optimization approach in which a decision-maker allocates funding to regional offices. Local decision-makers then use these funds to implement habitat protection efforts with varying effectiveness when evaluated in terms of the funder's goals. We illustrate this continuous formulation by examining the relative priority that should be given to different counties in the coterminous United States (US) when acquiring land to establish new protected areas. If weighting all species equally, counties in the southwest US, where large areas can be bought cheaply, are priorities for protection. If focusing only on species of conservation concern, priorities shift to locations rich in such species, particularly near expanding exurban areas facing high rates of future habitat conversion (e.g., south-central Texas). Priorities for protection are sensitive to what is assumed about local ecological and decision-making processes. For example, decision-makers who doubt the efficacy of local land protection efforts should focus on a few key areas, while optimistic decision-makers should disperse funding more widely. Efforts to inform large-scale conservation priorities should reflect better the types of choice that decision-makers actually face when working over these scales. They also need to report the sensitivity of recommended priorities to what are often unstated assumptions about local processes affecting conservation outcomes.
Data from: Combining noninvasive genetics and a new mammalian sex-linked marker provides new tools to investigate population size, structure and individual behaviour: an application to bats
Monitoring wild populations is crucial for their effective management. Noninvasive genetic methods provide robust data from individual free-ranging animals, which can be used in capture-mark-recapture (CMR) models to estimate demographic parameters without capturing or disturbing them. However, sex- and status-specific behaviour, which may lead to differences in detection probabilities, is rarely considered in monitoring. Here, we investigated population size, sex ratio, sex- and status-related behaviour in 19 Rhinolophus hipposideros maternity colonies (Northern France) with a noninvasive genetic CMR approach (using faeces) combined with parentage assignments. The use of the DDX3X/Y-Mam sexual marker designed in this study, which shows inter- and intra-chromosomal length polymorphism across placental mammals, together with 8 polymorphic microsatellite markers, produced high quality genetic data with limited genotyping errors and allowed us to reliably distinguish different categories of individuals (males, reproductive and non-reproductive females) and to estimate population sizes. We showed that visual counts represent well adult female numbers and that population composition in maternity colonies changes dynamically during the summer. Before parturition, colonies mainly harbour pregnant and non-pregnant females with a few visiting males whereas after parturition, colonies are mainly composed of mothers and their offspring with a few visiting non-mothers and males. Our approach gives deeper insight into sex- and status-specific behaviour, a prerequisite for understanding population dynamics and developing effective monitoring and management strategies. Provided sufficient samples can be obtained, this approach can be readily applied to a wide range of species.
Data from: An SNP-based second-generation genetic map of Daphnia magna and its application to QTL analysis of phenotypic traits
Background: Although Daphnia is increasingly recognized as a model for ecological genomics and biomedical research, there is, as of yet, no high-resolution genetic map for the genus. Such a map would provide an important tool for mapping phenotypes and assembling the genome. Here we estimate the genome size of Daphnia magna and describe the construction of an SNP array based linkage map. We then test the suitability of the map for life history and behavioural trait mapping. The two parent genotypes used to produce the map derived from D. magna populations with and without fish predation, respectively and are therefore expected to show divergent behaviour and life-histories. Results: Using flow cytometry we estimated the genome size of D. magna to be about 238 mb. We developed an SNP array tailored to type SNPs in a D. magna F2 panel and used it to construct a D. magna linkage map, which included 1,324 informative markers. The map produced ten linkage groups ranging from 108.9 to 203.6 cM, with an average distance between markers of 1.13 cM and a total map length of 1,483.6 cM (Kosambi corrected). The physical length per cM is estimated to be 160 kb. Mapping infertility genes, life history traits and behavioural traits on this map revealed several significant QTL peaks and showed a complex pattern of underlying genetics, with different traits showing strongly different genetic architectures. Conclusions: The new linkage map of D. magna constructed here allowed us to characterize genetic differences among parent genotypes from populations with ecological differences. The QTL effect plots are partially consistent with our expectation of local adaptation under contrasting predation regimes. Furthermore, the new genetic map will be an important tool for the Daphnia research community and will contribute to the physical map of the D. magna genome project and the further mapping of phenotypic traits. The clones used to produce the linkage map are maintained in a stock collection and can be used for mapping QTLs of traits that show variance among the F2 clones.
Data from: Differential metal-binding properties of dynamic acylhydrazone polymers and their sensing applications
As one of common dynamic covalent bonds, acylhydrazone bond plays an important role in developing intelligent responsive materials. In this report, we present acylhydrazone-based dynamic polymers with multi-stimuli responsiveness, particularly metal recognition behaviours and their modulation. A series of polyacylhydrazones with different metal-binding sites were designed and prepared in a modular fashion. Titration of these receptors with a diverse set of metal ions, including Cu2+, Zn2+ and La3+, resulted in unique optical changes, and both the sensitivity and selectivity profiles can be regulated. Moreover, the metal-binding feature was facilely modulated by changing the solvent. The addition of weakly basic anions was employed to further fine-tune the responsiveness of the polymers by taking advantage of the cooperative effect with metal coordination. Finally, the sensitive detection of 6-mercaptopurine and pyrophosphate was achieved to demonstrate the application potential of these systems.
Data from: Application of a dense genetic map for assessment of genomic responses to selection and inbreeding in Heliothis virescens
Adaptation of pest species to laboratory conditions and selection for resistance to toxins in the laboratory are expected to cause inbreeding and genetic bottlenecks that reduce genetic variation. Heliothis virescens, a major cotton pest, has been colonized in the laboratory many times, and a few laboratory colonies have been selected for Bacillus thuringiensis (Bt) resistance. We developed 350-bp double-digest restriction-site associated DNA-sequencing (ddRAD-seq) molecular markers to examine and compare changes in genetic variation associated with laboratory adaptation, artificial selection and inbreeding in this nonmodel insect species. We found that allelic and nucleotide diversity declined dramatically in laboratory-reared H. virescens as compared with field-collected populations. The declines were primarily a result of the loss of low frequency alleles present in field-collected H. virescens. A further, albeit modest decline in genetic diversity was observed in a Bt-selected population. The greatest decline was seen in H. virescens that were sib-mated for 10 generations, in which more than 80% of loci were fixed for a single allele. To determine which regions of the genome were resistant to fixation in our sib-mated line, we generated a dense intraspecific linkage map containing three PCR-based and 659 ddRAD-seq markers. Markers that retained polymorphism were observed in small clusters spread over multiple linkage groups, but this clustering was not statistically significant. Overall, we have confirmed and extended the general expectations for reduced genetic diversity in laboratory colonies, provided tools for further genomic analyses and produced highly homozygous genomic DNA for future whole genome sequencing of H. virescens.
Data from: Estimating national population sizes: methodological challenges and applications illustrated in the common nightingale, a declining songbird in the UK
1. Estimation of national population size can be important for setting conservation priorities but its methodology has received little critical attention. Sites for highly aggregated species are often prioritised if they contain 1% of national or biogeographical populations but the utility of this approach for other species is unclear. 2. To make recommendations for study design, we present methods used to estimate the UK population size of the common nightingale Luscinia megarhynchos. We assess the sensitivity of the population estimate to the analytical method used and identify sites of national importance for this territorial songbird. 3. Survey effort was directed by prior knowledge of the species' distribution and the survey design maximised detectability by focussing on the period of greatest song output. We used three different statistical methods to account for detectability, estimating that 55–65% of the national population was detected during surveys. 4. Birds in areas not known to contain the species accounted for 13–23% of the population estimate. Methods to account for these individuals contributed the greatest uncertainty to the results, due to the difficulty of surveying a very large sample of random sites and consequent need to stratify the sample. 5. The 12 derived estimates ranged between 5094 and 5938 territorial males, with the confidence limits ranging from 4764 to 6534. Site delimitation, using clustering based on nearest-neighbour distances, identified one site clearly of national importance and several others potentially nationally important, depending on the population threshold and clustering distance used. 6. Synthesis and applications. National population estimation is difficult and requires that species-specific variability in detectability and individuals present outside surveyed areas are accurately accounted for through survey design and statistical analysis. Accounting for these sources of error will not always be possible and will hamper efforts to assess true population size and consequently to determine whether sites, however defined, exceed critical thresholds of importance. Resources may be better invested in other activities, for example in generating population trends based on relative indices. The latter are generally easier to produce, potentially more robust and arguably more suitable for many conservation applications.
Data from: Application of benchmark concentration (BMC) analysis on zebrafish data – a new perspective for quantifying toxicity in alternative animal models
Over the past decade, the zebrafish is increasingly being used as a model to screen for chemical-mediated toxicities including developmental toxicity (DT) and neurotoxicity (NT). One of the major challenges is lack of harmonization in data analysis approaches, thereby posing difficulty in comparing findings across laboratories. To address this, we sought to establish a unified data analysis strategy for both DT and NT data, by adopting the benchmark concentration (BMC) analysis. There are two critical aspects in the BMC analysis: having a toxicity endpoint amenable for BMC and selecting a proper benchmark response (BMR) for the endpoint. For the former, in addition to the typical endpoints in NT assay (e.g., hyper/hypo- response quantified by distance moved), we also used endpoints that assess the differences in movement patterns between chemical-treated embryos and control embryos. For the latter, we standardized the selection of BMR, which is analogous to minimum activity threshold, based on intrinsic response variations in the endpoint. When comparing our BMC results with a traditionally used LOAEL method (Lowest-Observed-Adverse-Effect Level), we found high active compound concordance (100% for DT vs 74% for NT); generally, the BMC was more sensitive than LOAEL (# of BMC more sensitive/# of concordant active compounds, 43/50 for DT vs 16/26 for NT). Using the BMC with standardized toxicity endpoints and an appropriate BMR, we may now have a unified data-analysis approach to comparing results across different zebrafish datasets, for a better understanding of strengths and challenges when using the zebrafish as a screening tool.
Data from: High-throughput adaptive sampling for whole-slide histopathology image analysis (HASHI) via convolutional neural networks: application to invasive breast cancer detection
Precise detection of invasive cancer on whole-slide images (WSI) is a critical first step in digital pathology tasks of diagnosis and grading. Convolutional neural network (CNN) is the most popular representation learning method for computer vision tasks, which have been successfully applied in digital pathology, including tumor and mitosis detection. However, CNNs are typically only tenable with relatively small image sizes (200x200 pixels). Only recently, Fully convolutional networks (FCN) are able to deal with larger image sizes (500x500 pixels) for semantic segmentation. Hence, the direct application of CNNs to WSI is not computationally feasible because for a WSI, a CNN would require billions or trillions of parameters. To alleviate this issue, this paper presents a novel method, High-throughput Adaptive Sampling for whole-slide Histopathology Image analysis (HASHI), which involves: i) a new efficient adaptive sampling method based on probability gradient and quasi-Monte Carlo sampling, and, ii) a powerful representation learning classifier based on CNNs. We applied HASHI to automated detection of invasive breast cancer on WSI. HASHI was trained and validated using three different data cohorts involving near 500 cases and then independently tested on 195 studies from The Cancer Genome Atlas. The results show that (1) the adaptive sampling method is an effective strategy to deal with WSI without compromising prediction accuracy by obtaining comparative results of a dense sampling (~6 million of samples in 24 hours) with far fewer samples (~2,000 samples in 1 minute), and (2) on an independent test dataset, HASHI is effective and robust to data from multiple sites, scanners, and platforms, achieving an average Dice coefficient of 76%.
Data from: Development and application of a novel metric to assess effectiveness of biomedical data
Objective: Design a metric to assess the comparative effectiveness of biomedical data elements within a study that incorporates their statistical relatedness to a given outcome variable as well as a measurement of the quality of their underlying data. Materials and methods: The cohort consisted of 874 patients with adenocarcinoma of the lung, each with 47 clinical data elements. The p value for each element was calculated using the Cox proportional hazard univariable regression model with overall survival as the endpoint. An attribute or A-score was calculated by quantification of an element's four quality attributes; Completeness, Comprehensiveness, Consistency and Overall-cost. An effectiveness or E-score was obtained by calculating the conditional probabilities of the p-value and A-score within the given data set with their product equaling the effectiveness score (E-score). Results: The E-score metric provided information about the utility of an element beyond an outcome-related p value ranking. E-scores for elements age-at-diagnosis, gender and tobacco-use showed utility above what their respective p values alone would indicate due to their relative ease of acquisition, that is, higher A-scores. Conversely, elements surgery-site, histologic-type and pathological-TNM stage were down-ranked in comparison to their p values based on lower A-scores caused by significantly higher acquisition costs. Conclusions: A novel metric termed E-score was developed which incorporates standard statistics with data quality metrics and was tested on elements from a large lung cohort. Results show that an element's underlying data quality is an important consideration in addition to p value correlation to outcome when determining the element's clinical or research utility in a study.
Data from: Development of an Arabis alpina genomic contig sequence dataset and application to single nucleotide polymorphisms discovery
The alpine plant Arabis alpina is an emerging model in the ecological genomic field which is well-suited to identifying the genes involved in local adaptation in contrasted environmental conditions, a subject which remains poorly understood at molecular level. This paper presents the assembly of a pool of A. alpina genomic fragments using Next Generation Sequencing technologies. These contigs cover 172 Mb of the A. alpina genome (i.e. 50% of the genome) and were shown to contain sequences giving positive hits against 96% of the 458 CEGMA core genes (Core Eukaryotic Genes Mapping Approach), a set of highly conserved eukaryotic genes. Regions presenting high nucleic sequence identity with 77% of the close relative Arabidopsis thaliana's genes were found, with an unbiased distribution across the different functional categories of A. thaliana genes. This new resource was tested using a resequencing assay to identify polymorphic sites. Sixteen samples were successfully analyzed and 127,041 Single Nucleotide Polymorphisms identified. This contig dataset will contribute to improving understanding of the ecology of Arabis alpina, thus constituting an important resource for future ecological genomic studies.
Data from: Multiresponse algorithms for community-level modeling: review of theory, applications, and comparison to species distribution models
1.Community-level models (CLMs) consider multiple, co-occurring species in model fitting and are lesser known alternatives to species distribution models (SDMs) for analyzing and predicting biodiversity patterns. CLMs simultaneously model multiple species, including rare species, while reducing overfitting and implicitly considering drivers of co-occurrence. Many CLMs are direct extensions of well-known SDMs and therefore should be familiar to ecologists. However, CLMs remain underutilized, and there have been few tests of their potential benefits and no systematic reviews of their assumptions and implementations. Here we review this emerging field and provide examples in R to fit common CLMs. Our goal is to introduce CLMs to a broader audience, and discuss their attributes, benefits, and limitations relative to SDMs. 2.We review i) statistical implementations and applications of CLMs, ii) their advantages and limitations, and iii) comparative analyses of CLMs and SDMs. We also suggest directions for future research. 3.We identify seven CLM algorithms with similar data structures and predictive outputs as SDMs that should be most accessible to ecologists familiar with species-level modeling, including five methods that predict assemblage composition and individual species distributions and two methods that model compositional turnover along environmental gradients. CLMs have been applied to numerous taxa, regions, and spatial scales, and a variety of topics (e.g., studying drivers of community structure or assessing relationships between community composition and functional traits). Studies suggest that the relative benefits of CLMs and SDMs may be case specific, especially in terms of predicting species distributions and community composition. However, CLMs may offer advantages in terms of computational efficiency, modeling rare species, and projecting to no-analog climates. A major shortcoming of CLMs is their reliance on presence-absence community composition data. 4.Studies are needed to assess the relative merits of SDMs and CLMs, and different CLM algorithms, with a focus on three key areas: i) under which circumstances CLMs improve predictions for rare species, ii) how CLMs perform under different community compositions (e.g. relative abundance of rare vs. common species), including the extent to which co-occurrence patterns are structured by biotic interactions, and iii) ability to project across time/space.
Data from: Genomewide association analyses of fitness traits in captive-reared Chinook salmon: applications in evaluating conservation strategies
A novel application of genome-wide association analyses is to use trait-associated loci to monitor the effects of conservation strategies on potentially adaptive genetic variation. Comparisons of fitness between captive- and wild-origin individuals, for example, do not reveal how captive rearing affects genetic variation underlying fitness traits or which traits are most susceptible to domestication selection. Here, we used data collected across four generations to identify loci associated with six traits in adult Chinook salmon (Oncorhynchus tshawytscha), and then determined how two alternative management approaches for captive rearing affected variation at these loci. Loci associated with date of return to freshwater spawning grounds (return timing), length and weight at return, age at maturity, spawn timing, and daily growth coefficient were identified using 9108 restriction site-associated markers and Random Forest, an approach suitable for polygenic traits. Mapping of trait-associated loci, gene annotations, and integration of results across multiple studies revealed candidate regions involved in several fitness-related traits. Genotypes at trait-associated loci were then compared between two hatchery populations that were derived from the same source but are now managed as separate lines, one integrated with and one segregated from the wild population. While no broad scale change was detected across four generations, there were numerous regions where trait-associated loci overlapped with signatures of adaptive divergence previously identified in the two lines. Many regions, primarily with loci linked to return and spawn timing, were either unique to, or more divergent in, the segregated line, suggesting that these traits may be responding to domestication selection. This study is one of the first to utilize genomic approaches to demonstrate the effectiveness of a conservation strategy, managed gene flow, on trait-associated – and potentially adaptive – loci. The results will promote the development of trait-specific tools to better monitor genetic change in captive and wild populations.
Data from: Membrane-assisted extraction of monoterpenes: from in-silico solvent screening towards biotechnological process application
This work focuses on the process development of membrane-assisted solvent extraction of hydrophobic compounds such as monoterpenes. Beginning with the choice of suitable solvents, quantum chemical calculations with the simulation tool COSMO-RS were carried out to predict the partition coefficient (logP) of (S)-(+)-carvone and terpinen-4-ol in various solvent-water systems and validated afterwards with experimental data. COSMO-RS results show good prediction accuracy for nonpolar solvents like n-hexane, ethyl acetate and n-heptane even in the presence of salts and glycerol in aqueous medium. Based on the high logP value, n-heptane was chosen for the extraction of (S)-(+)-carvone in a lab-scale hollow-fiber membrane contactor. Two operation modes are investigated where experimental and theoretical mass transfer values, based on their related partition coefficients were compared. In addition, the process is evaluated in terms of extraction efficiency and overall product recovery, and its biotechnological application potential discussed. Our work demonstrates that the combination of in-silico prediction by COSMO-RS with membrane-assisted extraction is a promising approach for the recovery of hydrophobic compounds from aqueous solutions.
Data from: Optimizing the detection of wakeful and sleep-like states for future electrocorticographic brain computer interface applications
Previous studies suggest stable and robust control of a brain-computer interface (BCI) can be achieved using electrocorticography (ECoG). Translation of this technology from the laboratory to the real world requires additional methods that allow users operate their ECoG-based BCI autonomously. In such an environment, users must be able to perform all tasks currently performed by the experimenter, including manually switching the BCI system on/off. Although a simple task, it can be challenging for target users (e.g., individuals with tetraplegia) due to severe motor disability. In this study, we present an automated and practical strategy to switch a BCI system on or off based on the cognitive state of the user. Using a logistic regression, we built probabilistic models that utilized sub-dural ECoG signals from humans to estimate in pseudo real-time whether a person is awake or in a sleep-like state, and subsequently, whether to turn a BCI system on or off. Furthermore, we constrained these models to identify the optimal anatomical and spectral parameters for delineating states. Other methods exist to differentiate wake and sleep states using ECoG, but none account for practical requirements of BCI application, such as minimizing the size of an ECoG implant and predicting states in real time. Our results demonstrate that, across 4 individuals, wakeful and sleep-like states can be classified with over 80% accuracy (up to 92%) in pseudo real-time using high gamma (70–110 Hz) band limited power from only 5 electrodes (platinum discs with a diameter of 2.3 mm) located above the precentral and posterior superior temporal gyrus.
Data from: Convenient fabrication of conjugated polymer semiconductor nanotubes and their application in organic electronics
Organic heterojunction is indispensable in organic electronic devices, such as organic solar cells (OSCs), organic light-emitting diodes (OLEDs) and so on. Fabrication of core-shell nanostructure provides feasible and novel way to prepare organic heterojunction, which is beneficial for miniaturization and integration of organic electronic devices. Fabrication of nanotubes which constitute the core-shell structure in large quantity is the key for the realization of application. In this work, a simple and convenient method to prepare nanotubes utilizing conjugated copolymer of perylene diimide and dithienothiophene (P(PDI-DTT)) was demonstrated. The relationship between preparation condition (solvent atmosphere, solution concentration and pore diameter of templates) and morphology of nanostructure was studied systematically. P(PDI-DTT) nanotubes could be fabricated in regular shape and large quantity by preparing the solution with appropriate concentration and placing Anodic Aluminum Oxide (AAO) template with nanopore diameter of 200 nm in the solvent atmosphere. The tubular structure was confirmed by scanning electron microscope (SEM). P(PDI-DTT) nanotubes exhibited electron mobility of 0.02 cm2V-1s–1 in field effect transistors under ambient condition. Light emitting nanostructures were successfully fabricated by incorporating tetraphenyl ethylene (TPE) into polymer nanotubes.
Data from: Assessment of dysmyelination with RAFFn MRI: application to murine MPS I
Type I mucopolysaccharidosis (MPS I) is an autosomal recessive lysosomal storage disorder with neurological features. Humans and laboratory animals with MPS I exhibit various white matter abnormalities involving the corpus callosum and other regions. In this study, we first validated a novel MRI technique, entitled Relaxation Along a Fictitious Field in the rotating frame of rank n (RAFFn), as a measure of myelination and dysmyelination in mice. We then examined differences between MPS I mice and heterozygotes using RAFF5 and histology. RAFF5 (i.e., RAFFn with n = 5) relaxation time constants were highly correlated with histological myelin density (R2 = 0.68, P<0.001), and RAFF5 clearly distinguished between the hypomyelinated and dysmyelinated shiverer mouse and the wild-type mouse. Bloch-McConnell theoretical analysis revealed slower exchange correlation times and smaller exchange-induced relaxation rate constants for RAFF4 and RAFF5 compared to RAFF1-3, T1ρ, and T2ρ. These data suggest that RAFF5 may assess methylene protons in myelin lipids and proteins, though other mechanisms (e.g. detection of myelin-bound water) may also explain the sensitivity of RAFF5 to myelin. In MPS I mice, mean RAFF5 relaxation time constants were significantly larger for the striatum (P = 0.004) and internal capsule (P = 0.039), and marginally larger for the fornix (P = 0.15). Histological assessment revealed no differences between MPS I mice and heterozygotes in myelin density or corpus callosum thickness. Taken together, these findings support subtle dysmyelination in the brains of mice with MPS I. Dysmyelination may result from myelin lipid abnormalities caused by the absence of α-L-iduronidase. Our findings may help to explain locomotor and cognitive deficits seen in mice with MPS I.
Data from: Avian surface reconstruction in free-flight with application to flight stability analysis of a barn owl and peregrine falcon
Birds primarily create and control the forces necessary for flight through changing the shape and orientation of their wings and tail. Their wing geometry is characterised by complex variation in parameters such as camber, twist, sweep and dihedral. To characterise this complexity, a multi-stereo photogrammetry setup was developed for accurately measuring surface geometry in high-resolution during free-flight. The natural patterning of the birds was used as the basis for phase correlation-based image matching, allowing indoor or outdoor use while being non-intrusive for the birds. The accuracy of the method was quantified and shown to be sufficient for characterising the geometric parameters of interest, but with a reduction in accuracy close to the wing edge and in some localized regions. To demonstrate the method's utility, surface reconstructions are presented for a barn owl (Tyto alba) and peregrine falcon (Falco peregrinus) during three instants of gliding flight per bird. The barn owl flew with a consistent geometry, with positive wing camber and longitudinal anhedral. Based on flight dynamics theory this suggests it was longitudinally statically unstable during these flights. The peregrine flew with a consistent glide angle, but at a range of airspeeds with varying geometry. Unlike the barn owl, its glide configuration did not provide a clear indication of longitudinal static stability/instability. Aspects of the geometries adopted by both birds appeared to be related to control corrections and this method would be well suited for future investigations in this area, as well as for other quantitative studies into avian flight dynamics.
Kieker monitoring data of application operation call traces of CoCoME
<p>The uploaded files represent different runs of CoCoME with different<br> workload configurations. In general the workloads start with<br> 10 shoppers shopping and is then interrupted by some administration<br> operations to adjust prices for a special sale. After that shoppers<br> return to the site. Depending on the workload in various numbers and<br> for different durations.</p> <p>In the following we explain the different workload configurations:<br> - kieker-20141103-195412267-UTC-j2eeservice-KIEKER-TEST.tar.gz<br> - 70 shoppers for 100 iterations</p> <p>- kieker-20141104-140254415-UTC-j2eeservice-KIEKER-TEST.tar.gz<br> - 70 shoppers for 500 iterations</p> <p>- kieker-20141104-003902628-UTC-j2eeservice-KIEKER-TEST.tar.gz<br> - 70 shoppers for 150 iterations</p> <p>- kieker-20141103-232909805-UTC-j2eeservice-KIEKER-TEST.tar.gz<br> - 50 shoppers for 100 iterations</p> <p>- kieker-20141103-215630838-UTC-j2eeservice-KIEKER-TEST.tar.gz<br> - 120 shoppers for 100 iterations</p> <p>- kieker-20141104-070211796-UTC-j2eeservice-KIEKER-TEST.tar.gz<br> - 70 shoppers for 90 iterations</p> <p>- kieker-20141104-060042643-UTC-j2eeservice-KIEKER-TEST.tar.gz<br> - 70 shoppers for 70 iterations</p> <p>- kieker-20141104-050803295-UTC-j2eeservice-KIEKER-TEST.tar.gz<br> - 70 shoppers for 50 iterations</p> <p>- kieker-20141104-011853225-UTC-j2eeservice-KIEKER-TEST.tar.gz<br> - 70 shoppers for 200 iterations</p> <p>- kieker-20141104-032100601-UTC-j2eeservice-KIEKER-TEST.tar.gz<br> - 70 shoppers for 300 iterations</p> <p>- kieker-20141103-212010120-UTC-j2eeservice-KIEKER-TEST.tar.gz<br> - 10 shoppers for 100 iterations</p> <p>- kieker-20141103-190943649-UTC-j2eeservice-KIEKER-TEST.tar.gz<br> - 20 shoppers for 100 iterations</p> <p>- kieker-20141104-020617388-UTC-j2eeservice-KIEKER-TEST.tar.gz<br> - 70-20 shoppers for 100 iterations</p> <p>- kieker-20141103-194453375-UTC-j2eeservice-KIEKER-TEST.tar.gz<br> - 60 shoppers for 100 iterations</p> <p>- kieker-20141103-221637864-UTC-j2eeservice-KIEKER-TEST.tar.gz<br> - 130 shoppers for 100 iterations</p> <p>- kieker-20141103-200357512-UTC-j2eeservice-KIEKER-TEST.tar.gz<br> - 1 shoppers for 100 iterations</p> <p>- kieker-20141104-042254202-UTC-j2eeservice-KIEKER-TEST.tar.gz<br> - 70 shoppers for 30 iterations</p> <p>- kieker-20141103-192643168-UTC-j2eeservice-KIEKER-TEST.tar.gz<br> - 40 shoppers for 100 iterations</p> <p>- kieker-20141103-190203561-UTC-j2eeservice-KIEKER-TEST.tar.gz<br> - 10 shoppers for 100 iterations</p> <p>- kieker-20141104-044425791-UTC-j2eeservice-KIEKER-TEST.tar.gz<br> - 70 shoppers for 40 iterations</p> <p>- kieker-20141103-225338449-UTC-j2eeservice-KIEKER-TEST.tar.gz<br> - 30 shoppers for 100 iterations</p> <p>- kieker-20141104-053345728-UTC-j2eeservice-KIEKER-TEST.tar.gz<br> - 70 shoppers for 60 iterations</p> <p>- kieker-20141103-231115376-UTC-j2eeservice-KIEKER-TEST.tar.gz<br> - 40 shoppers for 100 iterations</p> <p>- kieker-20141105-114942900-UTC-j2eeservice-KIEKER-TEST.tar.gz<br> - 70 shoppers for 1000 iterations</p> <p>- kieker-20141103-193540165-UTC-j2eeservice-KIEKER-TEST.tar.gz<br> - 50 shoppers for 100 iterations</p> <p>- kieker-20141104-073538044-UTC-j2eeservice-KIEKER-TEST.tar.gz<br> - 80 shoppers for 100 iterations</p> <p>- kieker-20141103-191755265-UTC-j2eeservice-KIEKER-TEST.tar.gz<br> - 30 shoppers for 100 iterations</p> <p>- kieker-20141103-210048642-UTC-j2eeservice-KIEKER-TEST.tar.gz<br> - 100 shoppers for 100 iterations</p> <p>- kieker-20141103-234712972-UTC-j2eeservice-KIEKER-TEST.tar.gz<br> - 60 shoppers for 100 iterations</p> <p>- kieker-20141104-022613492-UTC-j2eeservice-KIEKER-TEST.tar.gz<br> - 70 shoppers for 250 iterations</p> <p>- kieker-20141105-144447507-UTC-j2eeservice-KIEKER-TEST.tar.gz<br> - 70 shoppers for 2000 iterations</p> <p>- kieker-20141104-081423319-UTC-j2eeservice-KIEKER-TEST.tar.gz<br> - 1 shoppers for 100 iterations</p> <p>- kieker-20141103-223632908-UTC-j2eeservice-KIEKER-TEST.tar.gz<br> - 20 shoppers for 100 iterations</p> <p>- kieker-20141104-000527717-UTC-j2eeservice-KIEKER-TEST.tar.gz<br> - 70 shoppers for 100 iterations</p> <p>- kieker-20141103-213652715-UTC-j2eeservice-KIEKER-TEST.tar.gz<br> - 110 shoppers for 100 iterations</p> <p>- kieker-20141104-063024890-UTC-j2eeservice-KIEKER-TEST.tar.gz<br> - 70 shoppers for 80 iterations</p> <p>- kieker-20141104-071827776-UTC-j2eeservice-KIEKER-TEST.tar.gz<br> - 70 shoppers for 100 iterations</p> <p>- kieker-20141104-075444826-UTC-j2eeservice-KIEKER-TEST.tar.gz<br> - 90 shoppers for 100 iterations</p> <p>contact: reiner.jung@email.uni-kiel.de</p>
The application of filter based assembly model to develop best practices for Pannonian sand grassland restoration
<p>Data used for a manuscript sent to JAE in 2015.</p>
ScienceDex guides
Understand access before you commit
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.