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opencc-zeroJan 2023View details →

Why do parents produce small broods of offspring that have lower body mass, survival, and lifetime reproductive success? A case study in a long-lived bird

Numerous studies have examined the correlation between offspring quantity and quality, and many have found that the most common brood size is often smaller than broods with the highest offspring quality or production. However, the reasons why these small broods with lower offspring quality are produced, are still poorly explained. Using data spanning 29 years, we investigated the effects of brood size on nestlings' body mass and the lifetime fitness for those offspring as adults (as proxies of offspring quality) in the Crested Ibis (Nipponia nippon). We also examined the temporal variation of brood size. We found that overall offspring quality increases with brood size and that individuals from broods of three had the highest quality, as quantified by larger body mass, higher adult survival, and lifetime reproductive success. Furthermore, brood size of an individual pair significantly varied across years, and the proportion of broods containing two offspring increased while broods of three decreased after 2000 when the population dispersed to low-quality habitat. These findings indicate that spatiotemporal variation in resources may impact variation in brood size and subsequent fitness consequences, and that small broods are more common in resource-poor years or low-quality habitats. In contrast, parents with access to high-quality resources produce larger broods of nestlings that achieve higher body mass and subsequently experience higher adult survival and lifetime fitness. This study highlights how variation in life history traits can be influenced by resource condition, and provides an insight into particular habitat that need conservation for Crested Ibis.

Case study n°10 : From hazards in Senegal to migrants' integration in the City of Paris, Impact Chain model

The case work led to the development of two correlated impact chains. The first impact chain (“risk sender”) models the components of the decision to migrate for rural Senegalese, accounting for hazard occurrence as well as the exposure and vulnerability. The outcome of the individual arbitrage is migration (internal or international), or immobility (willing or trapped). The second impact chain (“risk receiver”) considers the integration process for international migrants, accounting for the exposure and vulnerability of Paris in multiple dimensions (economic, social, cultural, linguistic, residential).

Artifact for ICSE'23 paper: Using Reactive Synthesis: An End-to-End Exploratory Case Study

Artifact for ICSE'23 paper: Using Reactive Synthesis: An End-to-End Exploratory Case Study

MetUM Simulations of 2nd February Case Study

This repository contains data to support the publication "Kilometre-scale simulations of trade-wind cumulus capture processes of mesoscale organization" submitted to JAMES. The data is from Met Office Unified Model simulations of the 2nd February 2020 EUREC4A case study. There are 3 kilometre-scale resolutions (1.1km, 2.2km, 4.4km) nested in ERA5 boundary conditions, and two 100m-scale resolutions (300m, 500m) nested in the 1.1km simulation. The simulations are initialised at 1st February 00:00. Also included are two sensitivity tests with the kilometre-scale simulations run with 1) evaporation of rain switched off and 2) a later start time (2nd February 00:00). The code used to analyse this data is at <a href="https://github.com/leosaffin/moisture_tracers">https://github.com/leosaffin/moisture_tracers</a>. The data is across four folders (full directory structure at the bottom) regridded - Contains model data regridded to the lowest resolution (4.4km) either fixed on the 100m-scale domain (coarse_grid) or following a Lagrangian trajectory for the kilometre-scale resolutions and sensitivity tests (lagrangian_grid). There are also files with model data following a different trajectory and smaller domain, to be consistent with <a href="https://doi.org/10.1029/2021MS002619">Narenpitak et al. (2021)</a>, for the default kilometre-scale simulations (lagrangian_grid_Ron_Brown). trajectories - Contains all the trajectories used to extract the domains in "regridded" simulated_satellite - Contains model simulated brightness temperatures from 11Z-21Z for each resolution simulation. These simulations were run with the same setup but on a different machine and also include a 150m-resolution simulation. full_grid - Contains 2d model output a T+36 from the 500m and 1.1km simulations which were used to make figure 1 in the paper. Full directory structure: <ul> <li>full_grid <ul> <li>D100m_500m <ul> <li>model-diagnostics_20200201T0000_T+35.nc</li> </ul> </li> <li>km1p1 <ul> <li>model-diagnostics_20200201T0000_T+35.nc</li> </ul> </li> </ul> </li> <li>regridded <ul> <li>D100m_300m <ul> <li>coarse_grid <ul> <li>20200201T0000_D100m_300m_T+{24..48}_coarse_grid.nc</li> </ul> </li> </ul> </li> <li>D100m_500m <ul> <li>coarse_grid <ul> <li>20200201T0000_D100m_500m_T+{24..48}_coarse_grid.nc</li> </ul> </li> </ul> </li> <li>km1p1 <ul> <li>coarse_grid <ul> <li>20200201T0000_km1p1_T+{24..48}_coarse_grid.nc</li> </ul> </li> <li>lagrangian_grid <ul> <li>20200201T0000_km1p1_T+{01..48}_lagrangian_grid.nc</li> <li>20200202T0000_km1p1_T+{01..24}_lagrangian_grid.nc</li> </ul> </li> <li>lagrangian_grid_no_evap <ul> <li>20200201T0000_km1p1_T+{24..48}_lagrangian_grid_no_evap.nc</li> </ul> </li> <li>lagrangian_grid_Ron_Brown <ul> <li>20200201T0000_km1p1_T+{24..48}_lagrangian_grid_Ron_Brown.nc</li> </ul> </li> </ul> </li> <li>km2p2 <ul> <li>coarse_grid <ul> <li>20200201T0000_km2p2_T+{24..48}_coarse_grid.nc</li> </ul> </li> <li>lagrangian_grid <ul> <li>20200201T0000_km2p2_T+{24..48}_lagrangian_grid.nc</li> <li>20200202T0000_km2p2_T+{01..24}_lagrangian_grid.nc</li> </ul> </li> <li>lagrangian_grid_no_evap <ul> <li>20200201T0000_km2p2_T+{24..48}_lagrangian_grid_no_evap.nc</li> </ul> </li> <li>lagrangian_grid_Ron_Brown <ul> <li>20200201T0000_km2p2_T+{24..48}_lagrangian_grid_Ron_Brown.nc</li> </ul> </li> </ul> </li> <li>km4p4 <ul> <li>coarse_grid <ul> <li>20200201T0000_km4p4_T+{24..48}_coarse_grid.nc</li> </ul> </li> <li>lagrangian_grid <ul> <li>20200201T0000_km4p4_T+{24..48}_lagrangian_grid.nc</li> <li>20200202T0000_km4p4_T+{01..24}_lagrangian_grid.nc</li> </ul> </li> <li>lagrangian_grid_no_evap <ul> <li>20200201T0000_km4p4_T+{24..48}_lagrangian_grid_no_evap.nc</li> </ul> </li> <li>lagrangian_grid_Ron_Brown <ul> <li>20200201T0000_km4p4_T+{24..48}_lagrangian_grid_Ron_Brown.nc</li> </ul> </li> </ul> </li> </ul> </li> <li>regridded_large_scale <ul> <li>km1p1 <ul> <li>lagrangian_grid <ul> <li>20200201T0000_km1p1_T+{24..48}_lagrangian_grid_large_scale.nc</li> <li>20200202T0000_km1p1_T+{01..24}_lagrangian_grid_large_scale.nc</li> </ul> </li> <li>lagrangian_grid_no_evap <ul> <li>20200201T0000_km1p1_T+{24..48}_lagrangian_grid_no_evap_large_scale.nc</li> </ul> </li> <li>lagrangian_grid_Ron_Brown <ul> <li>20200201T0000_km1p1_T+{24..48}_lagrangian_grid_Ron_Brown_large_scale.nc</li> </ul> </li> </ul> </li> <li>km2p2 <ul> <li>lagrangian_grid <ul> <li>20200201T0000_km2p2_T+{24..48}_lagrangian_grid_large_scale.nc</li> <li>20200202T0000_km2p2_T+{01..24}_lagrangian_grid_large_scale.nc</li> </ul> </li> <li>lagrangian_grid_no_evap <ul> <li>20200201T0000_km2p2_T+{24..48}_lagrangian_grid_no_evap_large_scale.nc</li> </ul> </li> <li>lagrangian_grid_Ron_Brown <ul> <li>20200201T0000_km2p2_T+{24..48}_lagrangian_grid_Ron_Brown_large_scale.nc</li> </ul> </li> </ul> </li> <li>km4p4 <ul> <li>lagrangian_grid <ul> <li>20200201T0000_km4p4_T+{24..48}_lagrangian_grid_large_scale.nc</li> <li>20200202T0000_km4p4_T+{01..24}_lagrangian_grid_large_scale.nc</li> </ul> </li> <li>lagrangian_grid_no_evap <ul> <li>20200201T0000_km4p4_T+{24..48}_lagrangian_grid_no_evap_large_scale.nc</li> </ul> </li> <li>lagrangian_grid_Ron_Brown <ul> <li>20200201T0000_km4p4_T+{24..48}_lagrangian_grid_Ron_Brown_large_scale.nc</li> </ul> </li> </ul> </li> </ul> </li> <li>simulated_satellite <ul> <li>UMRA3p3_MOapp_20200201T0000Z_HMscale_2D_Hourly_150m_Baseline_goes16_brt.nc</li> <li>UMRA3p3_MOapp_20200201T0000Z_HMscale_2D_Hourly_300m_Baseline_goes16_brt.nc</li> <li>UMRA3p3_MOapp_20200201T0000Z_HMscale_2D_Hourly_500m_Baseline_goes16_brt.nc</li> <li>UMRA3p3_MOapp_20200201T0000Z_KMscale_2D_Hourly_1p1km_Baseline_goes16_brt.nc</li> <li>UMRA3p3_MOapp_20200201T0000Z_KMscale_2D_Hourly_2p2km_Baseline_goes16_brt.nc</li> <li>UMRA3p3_MOapp_20200201T0000Z_KMscale_2D_Hourly_4p4km_Baseline_goes16_brt.nc</li> </ul> </li> <li>trajectories <ul> <li>trajectories_20200201_km1p1_500m.pkl</li> <li>trajectories_20200201_km2p2_500m.pkl</li> <li>trajectories_20200201_km4p4_500m.pkl</li> <li>trajectories_20200201_km1p1_500m_no_evap.pkl</li> <li>trajectories_20200201_km2p2_500m_no_evap.pkl</li> <li>trajectories_20200201_km4p4_500m_no_evap.pkl</li> <li>trajectories_20200201_km1p1_500m_Ron_Brown.pkl</li> <li>trajectories_20200201_km2p2_500m_Ron_Brown.pkl</li> <li>trajectories_20200201_km4p4_500m_Ron_Brown.pkl</li> <li>trajectories_20200202_km1p1_500m.pkl</li> <li>trajectories_20200202_km2p2_500m.pkl</li> <li>trajectories_20200202_km4p4_500m.pkl</li> </ul> </li> </ul>

Earth Food Security: Use Case Service

This use case service consists in a water availability index computed based on soil status from Earth Observation. For the computation of water availability, long-time series of Soil Moisture is used to establish climatology over West Africa.

Modeling Decarbonization Pathways in the Power Sector in Developing Countries: The case of Colombia (EMP-LAC 2023) - Dataset

Dataset of the project Modeling Decarbonization Pathways in the Power Sector in Developing Countries: The case of Colombia (EMP-LAC 2023) - Dataset

Reconstructing locomotor ecology of extinct avialans: a case study of Ichthyornis comparing sternum morphology and skeletal proportions

Avian skeletal morphology is associated with locomotor function, including flight style, swimming and terrestrial locomotion, and permits informed inferences on locomotion in extinct taxa. The fossil taxon Ichthyornis (Avialae: Ornithurae) has long been regarded as highly aerial, with flight similar to terns or gulls (Laridae), and skeletal features resembling foot-propelled diving adaptations. However, rigorous testing of locomotor hypotheses has yet to be performed on Ichthyornis, despite its notable phylogenetic position as one of the most crownward stem birds. We analysed separate datasets of 3D sternal shape (geometric morphometrics) and skeletal proportions (linear measurements across the skeleton), to examine how well these data types predict locomotor traits in Neornithes. We then used this information to infer locomotor capabilities of Ichthyornis. We find strong support for both soaring and foot-propelled swimming capabilities in Ichthyornis. Further, sternal shape and skeletal proportions provide complementary information on avian locomotion: skeletal proportions allow better predictions of the capacity for flight, whereas sternal shape predicts variation in more specific locomotor abilities such as soaring, foot-propelled swimming, and escape burst flight. These results have important implications for future studies of extinct avialan ecology, and underscore the importance of closely considering sternum morphology in investigations of fossil bird locomotion.

Supplementary data for "Testing the efficacy of different molecular tools for parasite conservation genetics: a case study using horsehair worms (Phylum Nematomorpha)"

Supplementary data for "Testing the efficacy of different molecular tools for parasite conservation genetics: a case study using horsehair worms (Phylum Nematomorpha)" alignments: alignments used for BEAST ("bayes") and PopArt ("popart"). The "popart" folder also has a traits file per each species. bayesian_plots: TSVs ("tsv") and PDF files ("ogs") generated by BEAST. The "tsv" folder also has the scripts for plotting the results in R. easysfs: scripts, population file and results from the VCF to SFS conversione done by easySFS. fineRADstructure: fineRADstructure input files and output PDF plots ("plots") for C. formosanus ipyrad and Stacks ("stacks") data.  logs: logs for ipyrad, ModelTest, PGDspider, PopArt ("popart") and Stacks ("stacks"). The "popart" folder also have the generated networks in a TXT file. The "stacks" folder also has ODS files for calculating the amount of loci per each M/n fixed value. snapclust: STR files used with R for snapclust. Scripts included. stairway_plot: input (blueprint files) and outputs for Stairway Plot 2 analyses. The C. formosanus folder ("chordodes") also has scripts for R plotting. vcfs: VCF and HDF5 files used in this study. Also scripts for filtering/converting data and plotting the PCA with ipyrad (activate python first!) for C. formosanus. "acutogordius" = A. taiwanensis "chordodes" = C. formosanus "gordius" = G. chiashanus

Using inbreeding to test the contribution of non-additive genetic effects to additive genetic variance: A case study in Drosophila serrata

Additive genetic variance, VA, is the key parameter for predicting adaptive and neutral phenotypic evolution. Changes in demography (e.g., increased close-relative inbreeding) can alter VA, but how depends on the, typically unknown, gene action and allele frequencies across many loci. For example, VA increases proportionally with the inbreeding coefficient when allelic effects are additive, but larger (or smaller) increases can occur when allele frequencies are unequal at causal loci with dominance effects. Here, we describe an experimental approach to assess the potential for rare, recessive alleles to inflate VA under inbreeding. Applying a powerful paired pedigree design in Drosophila serrata, we measured 11 wing traits on half-sibling families bred via either random or sibling mating, differing only in homozygosity (not allele frequency). Despite close inbreeding and substantial power to detect small VA, we detected no deviation from the expected additive effect of inbreeding on genetic (co)variances. Our results suggest the average dominance coefficient is very small relative to the additive effect, or that allele frequencies are relatively equal at loci affecting wing traits. We outline the further opportunities for this paired pedigree approach to reveal the characteristics of VA, providing insight into historical selection and future evolutionary potential.

DATASET RELATED TO ARTICLE"SORL1 GENE MUTATION AND OCTAPEPTIDE REPEAT INSERTION IN PRNP GENE IN A CASE PRESENTING WITH RAPIDLY PROGRESSIVE DEMENTIA AND CEREBRAL AMYLOID ANGIOPATHY"

electropherogram of prnp octarepeat region ngs analysis of causal and risk genes associated to dementia prnp octarepeat region analysis by size discrimination of pcr amplicons

datset related to aarticle "CASE 310"

clinical data of a single case study

How to estimate body condition in large lizards? Argentine black and white tegu (Salvator merianae, Duméril and Bibron, 1839) as a case study

Body condition is a measure of the health and fitness of an organism represented by available energy stores, typically fat. Direct measurements of fat are difficult to obtain non-invasively, thus body condition is usually estimated by calculating body condition indices (BCIs) using mass and length. The utility of BCIs is contingent on the relationship of BCIs and fat, thereby validation studies should be performed to select the best-performing BCI before application in ecological investigations. We evaluated 11 BCIs in 883 Argentine black and white tegus (Salvator merianae) removed from their non-native range in South Florida, United States. Because the length-mass relationship in tegus is allometric, a segmented linear regression model was fit to the relationship between mass and length to define size classes. We evaluated percent, residual, and scaled fat and determined percent fat was the best measure of fat because it was the least associated with snout-vent length (SVL). We evaluated performance of BCIs with the full dataset and within size classes and identified Fulton's K as the best-performing BCI for our sampled population, explaining up to 19% of the variation in fat content. Overall, we found that BCIs: 1) maintained relatively weak relationships with measures of fat and 2) splitting data into size classes reduced the strength of the relationship (i.e., bias) between percent fat and SVL but did not improve the performance of BCIs. We postulate that the weak performance of BCIs in our dataset was likely due to the weak association of fat with SVL, the body plan and life-history traits of tegus, and potentially inadequate accounting of available energy resources. We caution against assuming that BCIs are strong indicators of body condition across species and suggest that validation studies be implemented, or that alternative or complementary measures of health or fitness should be considered.

An Exploratory Study on the Usage and Readability of Messages Within Assertion Methods of Test Cases

This is the code and dataset that accompanies the study: "An Exploratory Study on the Usage and Readability of Messages Within Assertion Methods of Test Cases." This study has been accepted for publication at the 2023 International Workshop on Natural Language-based Software Engineering. Following is the abstract of the study: Unit testing is a vital part of the software development process and involves developers writing code to verify or assert production code. Furthermore, to help comprehend the test case and troubleshoot issues, developers have the option to provide a message that explains the reason for the assertion failure. In this exploratory empirical study, we examine the characteristics of assertion messages contained in the test methods in 20 open-source Java systems. Our findings show that while developers rarely utilize the option of supplying a message, those who do, either compose it of only string literals, identifiers, or a combination of both types. Using standard English readability measuring techniques, we observe that a beginner's knowledge of English is required to understand messages containing only identifiers, while a 4th-grade education level is required to understand messages composed of string literals. We also discuss shortcomings with using such readability measuring techniques and common anti-patterns in assert message construction. We envision our results incorporated into code quality tools that appraise the understandability of assertion messages.

Data for: Post-migratory nonbreeding movements of birds: a review and case study

Seasonal migrations are fascinating and ecologically important, but many migratory species are declining as climate change and land-use change alter the habitats used by migrants across the annual cycle. While some migratory birds use a single wintering site, others undertake large-scale post-migratory movements during the nonbreeding season. Technological advances that enable tracking individual birds are uncovering more examples of post-migratory nonbreeding movements. Documenting these movements is important for conservation, which requires understanding when and where migrants use habitats throughout their range. Here, we reviewed existing literature and collected information on the post-migratory nonbreeding movements of 92 migratory bird species from 18 orders across six continents. Among these records, the most commonly reported drivers of movements were resource availability and climate. This strong dependence of post-migratory nonbreeding movements on birds' abiotic and biotic environments suggests that environmental change will impact the patterns of these movements and potentially the fitness of species that undertake them. We also reviewed post-migratory nonbreeding movements in North American-breeding thrushes from the genus Catharus to examine the drivers of these movements in five closely related migratory species. We find that species that are less territorial are more likely to use multiple sites during the nonbreeding season; however, there is little evidence for dietary, evolutionary, or environmental differences between thrush species that move during winter and those that are stationary. While we believe our study represents the most comprehensive list of species exhibiting post-migratory nonbreeding movements to date, biases in sampling, a lack of common terminology for these movements, and the still-nascent availability of inexpensive, lightweight tracking devices mean that there are probably many more populations that undertake such movements. Future research into the consequences of post-migratory nonbreeding movements for individual fitness and ecosystem services would advance our understanding of their conservation importance and their evolution.

opencc-by-4.0Mar 2023View details →

AALTO - Channel Characterization at Sub-THz Band with Measurements and Ray Tracing in Indoor Case - DATA

The data set includes simulation results from radio propagation modelling of TERAWAY links (at 90, 95 and 100 GHz) in realistic university corridor environment. The modelling is performed using a Ray Tracing Tool developed in MATLAB environment at Aalto University. Ray tracing technique used in this tool is based on Image Theory (IT) algorithm. Unlike a quasi three-dimensional environment, it supports ray tracing in full three dimension. This data set contains propagation modelling results of the TERAWAY link. Output data includes (but is not limited to): Multipath component IDs, Path Distance (meter), Angle of Arrival AoA (degree), Angle of Departure AoD (degree), Direction of Arrival DoA (degree), Direction of Departure DoD (degree), E-Field (Volt/meter), H-Field (Ampere/meter), Phase (Radians), Power (Watts), Number of reflections a path experienced, Number of diffractions a path experienced, information that is it ground reflected path or not,  Receiver location (x and y coordinates), information that is it rooftop path or not.

opencc-zeroMar 2023View details →

A case report of an Eurasian Jay (Garrulus glandarius) attacking an incubating adult and depredating the eggs of the Japanese Tit (Parus minor)

In May 2021, we opportunistically observed one Eurasian Jay (Garrulus glandarius) attacking an adult incubating Japanese Tit (Parus minor) and depredating nine tit eggs at a nestbox where a woodpecker had greatly enlarged the entrance. After the predation event, the Japanese tits abandoned the nest. We recommend that when using artificial nest boxes to protect hole-nesting birds, the appropriate entrance size should be proportional to the body size of the target species. This observation gives us a better understanding of the potential predators of secondary hole-nesting birds.

opencc-by-4.0Mar 2023View details →

Dataset for proceedings paper: How international is co-authorship outside of Web of Science? The case of social sciences and humanities in Flanders, Belgium

This is an anonymized dataset containing data on international collaboration in the social sciences and humanities (SSH) in Flanders, Belgium. It is based on all peer-reviewed publications in <a href="https://www.ecoom.be/en/data-collections/vabb-shw">VABB-SHW</a>, regardless of their indexation in WoS or other databases. The dataset accompanies the conference paper 'How international is co-authorship outside of Web of Science? The case of social sciences and humanities in Flanders, Belgium,' which was submitted to <a href="https://cns-iu.github.io/workshops/2023-07-02_issi/index.html">ISSI 2023</a>.

opencc-by-4.0Apr 2022View details →

ClinSpEn Corpus: Parallel English-Spanish COVID-19 Clinical Cases, Terminology and Ontology Concepts

ClinSpEn Parallel Corpus Collection This repository contains the complete ClinSpEn corpus collection, which was used for the <a href="https://temu.bsc.es/clinspen">ClinSpEn shared task</a> at Biomedical WMT 2022. ClinSpEn is a collection of Gold Standard EN-ES parallel corpora of different types of clinical data: case reports, medical controlled vocabularies/ontologies, and clinical terms and entities extracted from medical content. It includes development and test data translated by professional medical translators that can be used to train and benchmark clinical EN-ES machine translation systems. Additionally, monolingual background data is provided so that the systems' performance can be analyzed in unseen data. If you use this dataset, please cite: <blockquote> <pre><code>inproceedings{biowmt22, title={Findings of the WMT 2022 Biomedical Translation Shared Task: Monolingual Clinical Case Reports}, author={Neves, Mariana and Yepes, Antonio Jimeno and Siu, Amy and Roller, Roland and Thomas, Philippe and Navarro, Maika Vicente and Yeganova, Lana and Wiemann, Dina and Di Nunzio, Giorgio Maria and Vezzani, Federica and others}, booktitle={WMT22-Seventh Conference on Machine Translation}, pages={694--723}, year={2022} } </code></pre> </blockquote> Data Description ClinSpEn proposes three different sub-tracks, each based on a different type of clinical data: 1. Clinical Cases: Parallel EN-ES COVID-19 clinical case reports. The direction of this sub-track is EN>ES. The dataset’s case reports were carefully selected to cover a wide range of aspects related to the disease: different types of patients (children, adults, elderly and pregnant people, babies), different comorbidities (cancer, mental health issues, immunosuppressed patients) and symptomatology (mild and severe presentations, dermatologic, immunologic and psychiatric manifestations, thrombosis, ...). The reports were translated from English to Spanish by a professional medical translator on a first step and revised by a clinical expert on a second step. The sample (dev) set and test set are made up of parallel txt files (50 and 152 documents each, respectively), with the Spanish version having a “.es” extension and the English files having a “.en” extension. Each report has been parallelized so that every sentence’s line number corresponds to the same sentence’s line number in both languages. The background data (9,804 files) is made up of a TSV file with four columns: filename, document number, line number and English line. The clinical cases themselves include COVID-19 case reports as well as diverse content extracted from PubMed. If you need to map the entries in the join test + background document provided in earlier versions, you may use the "clinspen_clinicalcases_test-set_filename_mapping.tsv" file. 2. Clinical Terminology: Parallel EN-ES clinical terms extracted from medical literature and clinical records, with particular focus on diseases, symptoms, findings, procedures and professions and translated and revised by professional medical translators. The direction of this sub-track is ES>EN. The sample (dev) set contains 7,000 terms as a tab-separated file (TSV), with the first column corresponding to English terms and the second column to Spanish terms. The test data (12,128 terms) is made up of a TSV file with three columns: term number, English term and Spanish term. The background data (201,890 terms) is made up of a TSV file with two columns: term number and Spanish term. The term number columns can be used to map the entries in the join test + background document provided in earlier versions. 3. Ontology Concepts: Parallel EN-ES concepts extracted from various open biomedical ontologies and taxonomies and then manually translated by a professional medical translator. The direction of this sub-track is EN>ES. The sample (dev) data includes 400 concepts. The terms are presented as tab-separated file (TSV), with the first column corresponding to English terms and the second column to Spanish terms. The third column includes the term’s origin ontology and its correspondent ID (separated by an underscore), while the fourth one includes a link to the concept in OBO Library. The test data (1,789 concepts) is made up of a TSV file with five columns: term number, English term, Spanish term, ontology id and OBO library URL. The background data (299,408 concepts) is made up of a TSV file with four columns: term number, English term, ontology id and OBO library URL. The term number columns can be used to map the entries in the join test + background document provided in earlier versions.   Related Links: <ul> <li> ClinSpEn website with more information: <a href="https://temu.bsc.es/clinspen/">https://temu.bsc.es/clinspen/</a> </li> <li> WMT website: <a href="https://www.statmt.org/wmt22/">https://www.statmt.org/wmt22/</a> </li> </ul> License This work is licensed under a <a href="http://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International License</a>. Contact If you have any question or suggestion, please contact us at the following addresses: - Salvador Lima-López (<salvador [dot] limalopez [at] gmail [dot] com>) - Darryl Estrada (<darrylestrada97 [at] gmail [dot] com>) - Martin Krallinger (<krallinger [dot] martin [at] gmail [dot] com>)

A Case Study on AI Engineering Practices: Developing an Autonomous Stock Trading System

The field note data related to a case study on AI engineering practices. During the case study, an autonomous stock trading system was developed, while 10 AI engineering practices were applied. We used field notes to document the application of each practice. Additionally, we documented any challenges we experienced. <ul> <li>field-notes-practices.csv: the documented experiences with the AI engineering practices containing the name of the practice, the perceived effectiveness of the practice on an ordinal scale (--, -, 0, +, ++), a description of how it was applied and its effects, and the date when it was applied (in DD.MM.YYYY format).</li> <li>field-notes-challenges.csv: the documented challenges experiences during the case study containing the date (in DD.MM.YYYY format), a description of the challenge, the source that made us became aware of the challenge, the solution we used to overcome the challenge, and a description of the frequency of occurrence.</li> </ul>

Single column 1D radiative transfer simulations for a case study of multilayer mixed-phase cloud in Punta Arena Chile

This data set contain the input files and output simulations from a single column 1D radiative transfer simulations using the Rapid Radiative Transfer Model for General Circulation Model (GCM) applications (RRTMG). The simulations are focused on a selected case study of multiple-layer mixed phase cloud observed in Punta Arenas Chile. The input parameters of the simulations are based on remote sensing observations, which were synergistically used with the Cloudnet and VOODOO algorithm to derive macro and microphysical properties of clouds. The atmospheric profiles of temperature, pressure, and ozone are from ERA5 (European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis) and values of surface albedo from CERES (Clouds and the Earth's Radiant Energy System) SYN1deg Ed. 4.1.