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113 results for “debt”
Data from: Sleep apnea, sleep debt and daytime sleepiness are independently associated with road accidents: a cross-sectional study on truck drivers
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Data from: Extinction debt and delayed colonization have had comparable but unique effects on plant community-climate lags since the Last Glacial Maximum
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Data from: A degradation debt? large-scale shifts in community composition and loss of biomass in a tropical forest fragment after 40 years of isolation
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Biodiversity data from: The mass extinction debt of the Anthropocene
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Evaluating the Agreement among Technical Debt Measurement Tools: Building an Empirical Benchmark of Technical Debt Liabilities
<p>Dataset containing TD measurements, at file level, from three TD tools. The Dataset served as the input for Archetypal Analysis.</p>
An Empirical Study of Refactorings and Technical Debt in Machine Learning Systems
<p>Machine Learning (ML), including Deep Learning (DL), systems, i.e., those with ML capabilities, are pervasive in today's data-driven society. Such systems are complex; they are comprised of ML models and many subsystems that support learning processes. As with other complex systems, ML systems are prone to classic technical debt issues, especially when such systems are long-lived, but they also exhibit debt specific to these systems. Unfortunately, there is a gap of knowledge in how ML systems actually evolve and are maintained. In this paper, we fill this gap by studying refactorings, i.e., source-to-source semantics-preserving program transformations, performed in real-world, open-source software, and the technical debt issues they alleviate. We analyzed 26 projects, consisting of 4.2 MLOC, along with 327 manually examined code patches. The results indicate that developers refactor these systems for various reasons, both specific and tangential to ML; some refactorings correspond to established technical debt categories. In contrast, others do not, and code duplication is a major cross-cutting theme that particularly involved ML configuration and model code, which was also the most refactored. We also introduce 14 and 7 new ML-specific refactorings and technical debt categories, respectively, and put forth several recommendations, best practices, and anti-patterns. The results can potentially assist practitioners, tool developers, and educators in facilitating long-term ML system usefulness.</p>
Data from: European ornamental garden flora as an invasion debt under climate change
1.Most naturalized and invasive alien plant species were originally introduced to regions for horticultural purposes. However, many regions now face an invasion debt from ornamental alien species, which have not yet naturalized. In this regard, climate change represents a threat as it may lower the barriers to naturalization for some ornamental alien species. Identifying those species is extremely important for anticipating impending invasions. 2.To identify predictors of naturalization, we modelled the effects of climate, nursery availability and species characteristics on the current European naturalization success of 2,073 ornamental aliens commonly planted in European gardens. We then used the resulting model together with climate projections for 2050 to forecast future naturalization risks for the 1,583 species not yet naturalized in Europe. 3.We found that non‐European naturalized range size, climatic suitability, propagule pressure, having a dioecious sexual system and plant height jointly explained current naturalization success in Europe. By 2050, naturalization probability projections increased by more than 0.1 for 41 species, and only decreased by more than 0.1 for one species. 4.Policy Implications. Using predictions based on our integrated model of alien ornamental naturalization success, we identified species with high future naturalization risk and species with high projected increases in naturalization potential in Europe under climate change. This species list allows for prioritization of monitoring and regulation of ornamental plants to mitigate the invasion debt.
Replication Package for Automating Technical Debt Management: Insights from Practitioner Discussions in Stack Exchange
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Technical Debt on Agile Projects: Managers' point of view at Stack Exchange
<p>Technical Debt on Agile Projects: Managers’ point of view at Stack Exchange</p> <p>XXI Simpósio Brasileiro de Qualidade de Software (SBQS '22), Nov 07--10, 2022, 2022, Curitiba, Paraná, Brasil.</p>
Software Practitioners' Point of View on Technical Debt Payment (Supporting Material)
<p>The InsighTD data set with answers on technical debt payment. </p>
Eliciting Public Discourse of SE Tool Providers in a Study on Requirements Process Debt – A Different Shade of Grey - Auxiliary Material
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Exploring Community Smells in Machine Learning Applications: Analytical Insights and Their Association with Self-Admitted Technical Debt
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Exploring Community Smells in Machine Learning Applications: Analytical Insights and Their Association with Self-Admitted Technical Debt
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Hearing the Voice of Software Practitioners on Technical Debt Monitoring: Understanding Monitoring Practices and the Practices' Avoidance Reasons: Data set
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Time lags and the invasion debt in plant naturalisations
Ecological processes often exhibit time lags. For plant invasions, lags of decades to centuries between species' introduction and establishment in the wild (naturalisation) are common, leading to the idea of an invasion debt: accelerating rates of introduction result in an expanding pool of introduced species that will naturalise in the future. Here, I show how a concept from survival analysis, the hazard function, provides an intuitive way to understand and forecast time lags. For plant naturalisation, theoretical arguments predict that lags between introduction and naturalisation will have a unimodal distribution, and that increasing horticultural activity will cause the mean and variance of lag times to decline over time. These predictions were supported by data on introduction and naturalisation dates for plant species introduced to Britain. While increasing trade and horticultural activity can generate an invasion debt by accelerating introductions, the same processes could lower that debt by reducing lag times.
ESG performance and cost of debt_data
<p>ESG performance and cost of debt stata data</p>
Health and Health Care Utilization Effects of Medical Debt Forgiveness
ClinicalTrials.gov study NCT04835012. IPD Sharing: YES. Countries: 1. Publications: 0.
Data from: European ornamental garden flora as an invasion debt under climate change
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Time lags and the invasion debt in plant naturalisations
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Beyond the Code: Mining Self-Admitted Technical Debt in Issue Tracker Systems
<p>Self-admitted technical debt (SATD) is a particular case of Technical Debt (TD) where developers explicitly acknowledge their sub-optimal implementation decisions. Previous studies mine SATD by searching for specific TD-related terms in source code comments.By contrast, in this paper we argue that developers can admit technical debt by other means, e.g., by creating issues in tracking systems and labelling them as referring to TD. We refer to this type of SATD as issue-based SATD or just SATD-I. We study a sample of 286 SATD-I instances collected from five open source projects, including Microsoft Visual Studio and GitLab Community Edition. We show that only 29% of the studied SATD-I instances can be tracked to source code comments. We also show that SATD-I issues take more time to be closed, compared to other issues, although they are not more complex in terms of code churn. Besides, in 45% of the studied issues TD was introduced to ship earlier, and in almost 60%it refers to Design flaws. Finally, we report that most developers pay SATD-I to reduce its costs or interests (66%). Our findings suggest that there is space for designing novel tools to support technical debt management, particularly tools that encourage developers to create and label issues containing TD concerns.</p>
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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.