2,512 research outputs found
Plant succession on gopher mounds in Western Cascade meadows: consequences for species diversity and heterogeneity
Pocket gophers have the potential to alter the dynamics of grasslands by creating mounds that bury existing vegetation and locally reset succession. Gopher mounds may provide safe sites for less competitive species, potentially increasing both species diversity and vegetation heterogeneity (spatial variation in species composition). We compared species composition, diversity and heterogeneity among gopher mounds of different ages in three montane meadows in the Cascade Range of Oregon. Cover of graminoids and forbs increased with mound age, as did species richness. Contrary to many studies, we found no evidence that mounds provided safe sites for early successional species, despite their abundance in the soil seed bank, or that diversity peaked on intermediate-aged mounds. However, cover of forbs relative to that of graminoids was greater on mounds than in the adjacent meadow. Variation in species composition was also greater within and among mounds than in adjacent patches of undisturbed vegetation, suggesting that these small-scale disturbances increase heterogeneity within meadows
Atomic Layer Deposition Nucleation Dependence on Diamond Surface Termination
Surface termination and interfacial interactions are critical for advanced
solid-state quantum applications. In this paper, we demonstrate that atomic
layer deposition (ALD) can both provide valuable insight on the chemical
environment of the surface, having sufficient sensitivity to distinguish
between the common diamond (001) surface termination types and passivate these
interfaces as desired. We selected diamond substrates exhibiting both smooth
and anomalously rough surfaces to probe the effect of morphology on ALD
nucleation. We use high resolution in situ spectroscopic ellipsometry to
monitor the surface reaction with sub-angstrom resolution, to evaluate the
nucleation of an ALD Al2O3 process as a function of different ex and in situ
treatments to the diamond surface. In situ water dosing and high vacuum
annealing provided the most favorable environment for nucleation of
dimethylaluminum isopropoxide and water ALD. Hydrogen termination passivated
both smooth and rough surfaces while triacid cleaning passivated the smooth
surface only, with striking effectiveness.Comment: 31 pages, 14 figure
‘Superbull’ males : what role do they play and what drives their appearance within the Doryteuthis gahi Patagonian Shelf population?
This work was funded by the Falkland Islands Government. Thanks are due to FCT/MCTES for financial support to CESAM (UID/AMB/50017/2019) through national funds and ERDF co-financing, under the Partnership Agreement for the PT2020 and Compete 2020 programs. This work was funded by the Falkland Islands Government. The study was conducted using E.U. Copernicus Marine Service Information. We are grateful to the scientific observers from the Falkland Islands fisheries department for sample collection and to the director of fisheries, John Barton, for supporting this work.Peer reviewedPublisher PD
Software Citation Implementation Challenges
The main output of the FORCE11 Software Citation working group
(https://www.force11.org/group/software-citation-working-group) was a paper on
software citation principles (https://doi.org/10.7717/peerj-cs.86) published in
September 2016. This paper laid out a set of six high-level principles for
software citation (importance, credit and attribution, unique identification,
persistence, accessibility, and specificity) and discussed how they could be
used to implement software citation in the scholarly community. In a series of
talks and other activities, we have promoted software citation using these
increasingly accepted principles. At the time the initial paper was published,
we also provided guidance and examples on how to make software citable, though
we now realize there are unresolved problems with that guidance. The purpose of
this document is to provide an explanation of current issues impacting
scholarly attribution of research software, organize updated implementation
guidance, and identify where best practices and solutions are still needed
Statistical Algorithms for Ontology-based Annotation of Scientific Literature
Background: Ontologies encode relationships within a domain in robust data structures that can be used to annotate data objects, including scientific papers, in ways that ease tasks such as search and meta-analysis. However, the annotation process requires significant time and effort when performed by humans. Text mining algorithms can facilitate this process, but they render an analysis mainly based upon keyword, synonym and semantic matching. They do not leverage information embedded in an ontology’s structure. Methods: We present a probabilistic framework that facilitates the automatic annotation of literature by indirectly modeling the restrictions among the different classes in the ontology. Our research focuses on annotating human functional neuroimaging literature within the Cognitive Paradigm Ontology (CogPO). We use an approach that combines the stochastic simplicity of naïve Bayes with the formal transparency of decision trees. Our data structure is easily modifiable to reflect changing domain knowledge. Results: We compare our results across naïve Bayes, Bayesian Decision Trees, and Constrained Decision Tree classifiers that keep a human expert in the loop, in terms of the quality measure of the F1-mirco score. Conclusions: Unlike traditional text mining algorithms, our framework can model the knowledge encoded by the dependencies in an ontology, albeit indirectly. We successfully exploit the fact that CogPO has explicitly stated restrictions, and implicit dependencies in the form of patterns in the expert curated annotations
Automated Annotation of Functional Imaging Experiments via Multi-Label Classification
Identifying the experimental methods in human neuroimaging papers is important for grouping meaningfully similar experiments for meta-analyses. Currently, this can only be done by human readers. We present the performance of common machine learning (text mining) methods applied to the problem of automatically classifying or labeling this literature. Labeling terms are from the Cognitive Paradigm Ontology (CogPO), the text corpora are abstracts of published functional neuroimaging papers, and the methods use the performance of a human expert as training data. We aim to replicate the expert’s annotation of multiple labels per abstract identifying the experimental stimuli, cognitive paradigms, response types, and other relevant dimensions of the experiments. We use several standard machine learning methods: naive Bayes (NB), k -nearest neighbor, and support vector machines (specifically SMO or sequential minimal optimization). Exact match performance ranged from only 15% in the worst cases to 78% in the best cases. NB methods combined with binary relevance transformations performed strongly and were robust to overfitting. This collection of results demonstrates what can be achieved with off-the-shelf software components and little to no pre-processing of raw text
Size-dependent change in body shape and its possible ecological role in the Patagonian squid (Doryteuthis gahi) in the Southwest Atlantic
This study was supported by funding from the Falkland Islands Government. We are grateful to the scientific observers from the Falkland Islands Fisheries Department for sample collection and Beverley Reid for collecting traditional morphometric measurements and to three anonymous referees for their comments which greatly improved the manuscript. We thank the Director of Fisheries, John Barton, for supporting this work. The MASTS pooling initiative (Marine Alliance for Science and Technology for Scotland, funded by the Scottish Funding Council and contributing institutions; grant reference HR09011) is gratefully acknowledged. Thanks are due to FCT/MCTES for financial support to CESAM (UID/AMB/50017/2019) through national funds and ERDF co-financing, under the Partnership Agreement for the PT2020 and Compete 2020 programsPeer reviewedPostprin
On Dimensionality, Measurement Invariance, and Suitability of Sum Scores for the PHQ-9 and the GAD-7.
In psychiatry, severity of mental health conditions and their change over time are usually measured via sum scores of items on psychometric scales. However, inferences from such scores can be biased if psychometric properties such as unidimensionality and temporal measurement invariance for instruments are not met. Here, we aimed to evaluate these properties for common measures of depression (Patient Health Questionnaire-9) and anxiety (Generalized Anxiety Disorder Assessment-7) in a large clinical sample (N = 22,362) undergoing psychotherapy. In addition, we tested consistency in dimensionality results across different methods (parallel analysis, factor analysis, explained common variance, the partial credit model, and the Mokken model). Results showed that while both Patient Health Questionnaire-9 and Generalized Anxiety Disorder Assessment-7 are multidimensional instruments with highly correlated factors, there is justification for sum scores as measures of severity. Temporal measurement invariance across 10 therapy sessions was evaluated. Strict temporal measurement invariance was established in both scales, allowing researchers to compare sum scores as severity measures across time.NIH
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