Resultados de investigación

[EN] The Study and Recovery of Musical Heritage project being developed by the UB and the CSIC, together with the CRAI Biblioteca de Fons Antic de la Universitat de Barcelona, ​​the Grupo de Investigación Patrimonio Musical Histórico de la Institución Milá y Fontanals de Investigación en Humanidades of the CSIC, the Archdiocese of Barcelona, ​​the Barcelona Cathedral, the Arxiu de l’Església de Santa Maria del Pi, and the Oratory of Sant Felip Neri in Barcelona, and, in collaboration with the Barcelona Music Museum, has recovered musical heritage: a musical piece by Carles Baguer (1768-1808) which is found in the manuscript Ms.1378 of the music collection of theCRAI Biblioteca de Fons Antic de la Universitat de Barcelona. This dataset contains two files: - Transcription of the Sonata in E minor by Carles Baguer from the manuscript Ms. 1378. - Sound recording of the piece performed by: Dani Espasa, with a piano Steinway, model D, on loan from the Barcelona Music Museum., [CA] Sota el marc del projecte Estudi i Recuperació de Patrimoni Musical que estan desenvolupant la UB i el CSIC, juntament amb el CRAI Biblioteca de Fons Antic de la Universitat de Barcelona, el Grup per a l’Estudi del Patrimoni Musical (GEPAM), el Grup de Recerca Patrimoni Musical Històric de la Institució Milà i Fontanals d’Investigació en Humanitats del CSIC, l’Arquebisbat de Barcelona, la Catedral de Barcelona, l’Arxiu de l’Església de Santa Maria del Pi i l'Oratori de Sant Felip Neri de Barcelona, i, en col·laboració amb el Museu de la Música de Barcelona, s'ha recuperat una peça musical de Carles Baguer (1768-1808) que es troba al manuscrit MS. 1378 del fons musical del CRAI Biblioteca de Fons Antic de la Universitat de Barcelona. Aquest dataset conté dos arxius: - Transcripció de la Sonata en Mi menor de Carles Baguer del manuscrit Ms. 1378. - Enregistrament sonor de la peça interpretada per: Dani Espasa, amb un piano Steinway, model D, cedit pel Museu de la Música de Barcelona., Peer reviewed

El dataset se puede consultar y descargar en el siguiente enlace: https://zenodo.org/records/15684002, This dataset contains the data and code to reproduce the figures in the research paper: Exploring Ozone-climate Interactions in Idealized CMIP6 DECK Experiments., Peer reviewed

Dataset and R codes of "Fire modulates the structural and functional drivers of individual-base plant-pollinator networks" by Larissa Alves de Lima & Diego Anjos et al. We used individual-based plant-pollinator networks to evaluate: (i) How do plant- (i.e., individual traits, phenology) and site-related attributes (i.e., spatial factors, local temperature) influence interaction patterns before and after a fire? (ii) How is individual plant fitness affected by the combination of these attributes and the role of individual plants within the interaction network (i.e., centrality) before and after fire? Our findings shows that facilitative interactions with conspecifics via pollinator sharing were diluted by fire, with potential delayed effects on population recovery. Our findings emphasize that fire causes a shift from facilitative processes to more competitive scenarios in plant-pollinator networks, with implications for population dynamics and community recovery., Fundação de Amparo à Pesquisa do Estado de Minas Gerais: Student Fellowship11589 Coordenação de Aperfeicoamento de Pessoal de Nível Superior: Researcher grant88887.466638/2019–00 Ministerio de Ciencia, Innovación y Universidades: VI Plan Propio de Investigación National Council for Scientific and Technological Development: Researcher grant403647/2021-5, Peer reviewed

I present a large-scale matrix documenting plant–herbivore associations between 5,109 species of Lepidoptera and 3,175 species of vascular plants across Europe. The dataset is organized as a binary interaction matrix, in which each Lepidoptera species is represented by a row and each plant species by a column (1 = recorded larval association, 0 = no record). The compilation is based on an extensive review of published literature, monographs, publicly accessible online repositories, and grey literature, integrating a wide spectrum of sources. All taxonomic names were carefully curated and standardized following the most up-to-date classifications of both Lepidoptera and vascular plants. The matrix encompasses trees, shrubs, and herbaceous plants, including native, naturalized, ornamental, and invasive taxa as delimited by the European Environment Agency. The resolution of this matrix enable the examination of fundamental ecological and evolutionary questions, such as the prevalence and drivers of host specialization, the determinants of herbivore diversity, and the large-scale architecture of plant–herbivore networks. Because Lepidoptera are highly diverse and ecologically significant herbivores, the matrix provides a valuable foundation for assessing resource use and niche partitioning in relation to host traits, plant phylogeny, and biogeographic patterns. Beyond its relevance for basic ecological research, the matrix has strong applied value. It can be used to inform biodiversity conservation strategies, as identifying keystone host plants that sustain large numbers of Lepidoptera species, or by evaluating the vulnerability of herbivore communities to host loss under scenarios of habitat conversion, agricultural intensification, or climate change. Furthermore, the matrix can be integrated with environmental and trait databases to support predictive modeling, risk assessment, and long-term monitoring initiatives. The matrix is provided in a machine-readable CSV format and is accompanied by detailed documentation, facilitating reuse, reproducibility, and interoperability with other biodiversity resources. By making this resource freely available, I aim to foster broad engagement across ecological and conservation communities, enhance comparative studies of plant–herbivore interactions, and provide a lasting foundation for research on the diversity, specialization, and resilience of European herbivore assemblages., Peer reviewed

Comprehensive list of existing and under development standards related to Raman spectroscopy, including documents and certified reference materials, clasifid by topic. This is a copy of a living document; an updated version will be regularly uploaded. If you are aware of a certified reference material or standard document that is not included in the table or want to suggest a correction, please send us the information. Thank you!, European Commission CHARISMA - Characterization and HARmonization for Industrial Standardisation of advanced MAterials: 952921, Peer reviewed

The dataset was created through the efforts of the Mosquito Alert team, collaborators and thousands of citizen scientists. Please credit the Mosquito Alert Community (www.mosquitoalert.com) if you use this dataset (e.g., 'Mosquito Alert dataset, downloaded from [link], CC BY-NC-SA 4.0'). The intellectual property (IP) rights of this dataset belong to the Mosquito Alert team. The license is included in the file license.txt within the dataset zip file, along with the images, labels and dataset description. The dataset consists of 10357 labeled images (approximately 9.8 GB in total). Images are accompanied by a designated CSV file called: annotations.csv. The CSV files include bounding box coordinates in the format: top left and bottom right notation ("bbx_xtl", "bbx_ytl", "bbx_xbr", "bbx_ybr"). The dataset consists of six distinct classes, including species and genus levels as well as a species complex. A summary of the mosquito classes, their descriptions, and corresponding class names used in the dataset: Aedes aegypti (species level) - class name: "aegypti" Aedes albopictus (species level) - class name: "albopictus" Anopheles (genus level) - class name: "anopheles" Culex (genus level) - class name: "culex" (species classification is challenging, so it is given at the genus level) Culiseta (genus level) - class name: "culiseta" Aedes japonicus/Aedes koreicus (species complex - difficult to differentiate between the two species) - class name: "japonicus-koreicus", [Label file:] The dataset includes a single CSV file: annotations.csv, which contains all the annotations for the images. Each row in the file provides the following information: img_fName: image file name img_w: image width img_h: image height bbx_xtl: bounding box top-left x-coordinate bbx_ytl: bounding box top-left y-coordinate bbx_xbr: bounding box bottom-right x-coordinate bbx_ybr: bounding box bottom-right y-coordinate class_label: class label (e.g., 'albopictus')., [Additional notes:] a broader description of the dataset and classes will be provided in the https://www.aicrowd.com/challenges/mosquitoalert-challenge-2023#dataset and https://www.youtube.com/watch?v=qSWJZUY-5DM challenge video exif information has been removed from the images for privacy protection most images contain a single mosquito with its corresponding bounding box and class label. However, in rare cases with multiple mosquitoes, only one mosquito is assigned a bounding box and label for consistency and compatibility., European Commission VEO - Versatile Emerging infectious disease Observatory: 874735, Peer reviewed

Ministerio de Ciencia, Innovación y Universidades Spanish Network for Stress Research Instituto de Salud Carlos III, Peer reviewed

We studied the impact of sublethal thermal stress (28ºC, 7 days) on the physiological rates and metabolic balance of three populations of the calanoid copepod Paracartia grani, reared at 19, 22 and 25ºC for multiple generations, This research was funded by Grants CTM2017-84288-R, PID2020-118645RB-I00 and PID2023-150548NB-I00 by MCIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe” and ERDF/EU. C. J. was supported by Grant [PRE2018-084738] funded by MCIN/AEI/10.13039/501100011033 and by “ESF Investing in your future”. The open-access publication fee was covered by the CSIC Open Access Publication Support Initiative through its Unit of Information Resources for Research (URICI), With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), Peer reviewed

Climate change is impacting sea turtles worldwide with the effects varying between species and populations. For example, rising temperatures have variable effects on the duration of the inter-nesting period (IP)—the time between two consecutive nests during a single nesting season. Specifically, a negative correlation between water temperature and IP has been reported in green (Chelonia mydas), hawksbill (Eretmochelys imbricata), and loggerhead (Caretta caretta) turtles. In contrast, previous studies have shown no correlation for olive ridley turtles (Lepidochelys olivacea). Here, we assessed whether this lack of a correlation in olive ridley turtles was a product of the small sample size used in previous studies (nmax=11). We used capture-mark-recapture data over 14 years to calculate the IP of olive ridley turtles (n=96) nesting on two different beaches in Costa Rica. Next, we calculated mean sea surface temperature (SST) during each IP within estimated inter-nesting areas (225 km2), as inferred from previous olive ridley telemetry studies, and using data from NASA’s multi-scale ultra-high-resolution sensor. Mean (±SD) IP was 22.5±6.0d (range: 13-41 d) and mean SST was 28.0±0.6℃ (range: 26.1-29.5 ℃). We observed a statistically significant negative relationship between SST and IP suggesting that elevated temperatures at inter-nesting habitats influence the phenology of olive ridley turtles as previously observed in other hard-shelled sea turtle species. Thus, we postulate that elevated temperatures due to climate change may influence the timing of nesting seasons for solitary nesting olive ridley turtles and may even alter timing of the olive ridley mass nesting aggregations known as arribadas, Funding over the years was provided by the Earthwatch Institute, the Schrey Distinguished Professorship of Purdue University Fort Wayne, the Betz Chair Endowment of Drexel University, the AZA Sea Turtle SAFE Program, Virginia Aquarium Camp; Marine Science Center, North Carolina Aquariums, South Carolina Aquarium, the Florida Aquarium and The Leatherback Trust. NJR was funded by the Spanish government (AEI) through the Ramon y Cajal postdoctoral program (#RYC2021-034381-I). Support to ICM was provided via the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S) and funded by the Agencia Estatal de Investigación (AEI) 10.13039/501100011033, Peer reviewed

With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), Offline biogeochemical model within the Regional Ocean Modeling System (ROMS). Works with: https://github.com/kthyng/COAWST-ROMS-OIL (Thyng et al., 2021). fennel.h : Addition of new tracers and their respective equations: phosphate (PO4), river detritus for N and C (RIVER_DON), and new oxygen computation: RW14_OXYGEN_SC. fennel_def.h : Definition of new input parameters in fennel_def.h. R_P2N (phyto phosphate:nitrogen ratio), K_PO4 (inverse half saturation for phytoplankton PO4 uptake), RDeRRN and RDeRRC (Remineralization rate for river detritus N and C). fennel_inp.h : Reads input parameters from Fennel configuration file. Addition of R_P2N (phyto phosphate:nitrogen ratio), K_PO4 (inverse half saturation for phytoplankton PO4 uptake), RDeRRN and RDeRRC (Remineralization rate for river detritus N and C). fennel_mod.h : allocation of new parameters for Fennel model. fennel_var.h : assigns metadata indices for the new variables PO4, RDeN and RDeC fennel_wrt.h : write out Fennel model parameters into output NetCDF files R_P2N, K_PO4, RDeRRN and RdeRRC lobaldefs.F : if OFFLINE & OFFLINE_BIOLOGY automatically activate ATCLIMATOLOGY for processing and allocating active tracers (T & S). Indispensable for Fennel model as temp is used for light limitation for phytoplankton growth and salt for O2 saturation. checkdefs.F : new options for checking C-processing options: PO4 (adds PO4 dynamics), RIVER_DON (adds river detritus equation), RIVER_BIOLOGY & BIOLOGY (river biology point sources). checkvars.F : if defined OFFLINE & ATCLIMATOLOGY, get active tracers (variables T & S). set_data.F : change set sea surface height climatology, set 3D momentum climatology not accessing subsequent time step value, Peer reviewed