Our Work

Manual de la asignatura Psicología del Desarrollo II para estudiantes del Grado de Psicología.

Video material used in pilot experiment for "Investigating the Intersection of Consciousness and Emotion" 

Batch upload of files from directory 'nicotiana_occidentalis_decontaminated_FSCR'.

RetaBase continuously pulls the biomedical literature for a curated set of bioactive molecules (peptides, incretin agonists, metabolic and longevity compounds), classifies each paper by study design w…

RetaBase continuously pulls the biomedical literature for a curated set of bioactive molecules (peptides, incretin agonists, metabolic and longevity compounds), classifies each paper by study design with rule-based, auditable methods, and publishes a browsable, filterable dashboard ordered by evidence level. It does not rate the quality of individual studies. It also surfaces ClinicalTrials.gov registry studies and preprints in separate, clearly labeled sections.

NFKB–P53 Rheostat Analysis Pipeline (R) This record accompanies version 1.0 of the NFKB–P53 Rheostat Analysis Pipeline, an open-source R implementation of the rheostat model described in "…

NFKB–P53 Rheostat Analysis Pipeline (R) This record accompanies version 1.0 of the NFKB–P53 Rheostat Analysis Pipeline, an open-source R implementation of the rheostat model described in "The NFKB-P53 antagonism as part of a rheostat network: practical implication in solving the leukemia relapse principle" (Spiros Vlahopoulos, ORCID 0000-0001-6245-3863). The pipeline operationalizes the central abstraction of that work — that the antagonism between the inflammatory transcription factor complex NFKB and the tumor suppressor P53 can be collapsed into a single interpretable axis — as executable research code. It implements all eleven tasks of the article's proposed outline: definition of curated NFKB-activated and P53-activated gene sets (with helpers to fetch full MSigDB Hallmark sets), ingestion of bulk or single-cell RNA-seq data, per-sample scoring of both programs via ssGSEA or a transparent mean-of-z method, computation of the rheostat value (Rheostat = NFKB score − P53 score), visualization of sample positions along the axis, statistical comparison across clinical states such as diagnosis, remission, and relapse, association testing with survival and minimal residual disease endpoints, robustness checks across upstream drivers (mutations, infections, radiation, inflammatory triggers), optional integration of multi-omic layers such as ATAC-seq and proteomics, and derivation and evaluation of a simple high-risk decision rule. A complete simulated leukemia cohort allows the entire pipeline to run end-to-end without any data, so that users can verify their installation and learn the workflow before substituting their own datasets. The release consists of the pipeline script together with a beginner's guide that requires no prior R experience, covering installation, execution, adaptation to real data, and troubleshooting. The code is provided for research and exploratory purposes only: the rheostat is a functional readout intended to support biological insight and hypothesis generation, it summarizes downstream state and does not itself establish causality, and it is not intended to replace clinical judgment or to serve as the sole basis for diagnosis or treatment decisions. Any clinical application requires rigorous external validation, prospective evaluation, and regulatory review appropriate to the intended context of use. The gene lists shipped by default are indicative subsets and should be replaced with fully curated, published gene sets for any real analysis. This software and its accompanying documentation were prepared with the assistance of Mistral AI (Vibe) and are released under the MIT License; users are encouraged to cite this record when reusing or adapting the pipeline, and to report issues or extensions via the associated repository.

Renewable Energy Explained: Power Systems, Storage & Sustainable Technologies is a publication-grade Open Educational Resource (OER) module covering the thermodynamic principles, electrochemical m…

Renewable Energy Explained: Power Systems, Storage & Sustainable Technologies is a publication-grade Open Educational Resource (OER) module covering the thermodynamic principles, electrochemical modeling, conversion technologies, and grid integration of sustainable power systems. Serving as an integral core module within the Electrical and Electronic Engineering curriculum on Prep4Uni.Online, this text bridges solar PV, wind turbine aerodynamics, and electrochemical battery storage with contemporary AI-era computational paradigms, microgrid sizing, and clean energy economics. Key Features & Pedagogical Additions:• Theoretical Grounding & Contemporary Paradigms: Integrates classical renewable conversion principles (Betz limit aerodynamics, PV semiconductor physics, Callendar-Van Dusen equations, battery depth-of-discharge constraints) with Physics-Informed Neural Networks (PINNs) solving Doyle-Fuller-Newman (DFN) electrochemical battery diffusion equations, Fourier Neural Operators (FNOs) for atmospheric wind turbine wake aerodynamics, and Lie-group Invariant Extended Kalman Filters (IEKF) for grid-forming inverter synchronization.• Systems Engineering Architecture & Trade-Off Analysis: Structured comparison matrix contrasting single-axis tracking against fixed-tilt PV installations, Lithium Iron Phosphate (LFP) against Nickel Manganese Cobalt (NMC) chemistries, Vanadium Redox Flow Batteries (VRFB) against Lithium-Ion BESS, and green hydrogen electrolysis against utility-scale battery storage.• Worked Numerical Engineering Application: A complete, multi-step engineering calculation detailing a standalone off-grid solar PV array and LFP battery energy storage sizing study, evaluating balance-of-system derating, multi-day autonomy, and DC bus ampere-hour capacities.• Curricular Assessment & Analytical Inquiries: Contains 24 fully resolved foundational review questions, deep analytical design inquiries, and step-by-step numerical problems spanning PV peak power and daily energy yields, wind turbine aerodynamic power generation, battery round-trip efficiency (RTE), pumped hydroelectric potential energy storage, green hydrogen electrolysis production yields, Levelized Cost of Energy (LCOE) calculations, and flywheel kinetic energy storage.

Appendix C. Supplementary Imagery The following high-resolution imagery repositories provide reference datasets for model validation: (1)      Supplementary Image S1: Photogr…

Appendix C. Supplementary Imagery The following high-resolution imagery repositories provide reference datasets for model validation: (1)      Supplementary Image S1: Photographic catalog of C. lanceolata donor stand profiles, canopy structures, and main trunk dimensions. (2)      Supplementary Image S2: High-resolution field photography documenting the in-situ root network exposure and high-throughput camera setup. (3)      Supplementary Image S3: Optical scan registry containing individual root segment profiles before spatial reconstruction. (4)      Supplementary Image S4: Vector feature class archive containing the processed irregular cylinder (ic) geometries. (5)      Supplementary Image S5: High-density TIFF files detailing the unified structural configurations and multi-label spatial classification results.

Session-grouped evaluation of the Real Doppler RAD-DAR database. Twenty of twenty-one drone acquisitions reach out-of-fold recall between 0.90 and 0.99; one reaches 0.249. Held out of training entirel…

Session-grouped evaluation of the Real Doppler RAD-DAR database. Twenty of twenty-one drone acquisitions reach out-of-fold recall between 0.90 and 0.99; one reaches 0.249. Held out of training entirely, recall on a held-back half is 0.178, rising to 0.948 once the other half is in training, while the same experiment on a control acquisition, the weakest of another class, recovers 0.056.The repository contains the full pipeline (inventory and deduplication, acquisition grouping, the split comparison, the coverage experiment, the compression grid, the leave-one-acquisition-out test), eighteen unit tests of the claims the paper makes about the code, a synthetic self-test that runs the whole pipeline without the archive and without a GPU, and a verification script that reruns every experiment on the real archive and checks each number the paper states against a recorded tolerance.The Real Doppler RAD-DAR database itself is not redistributed here. It is obtained separately from Kaggle.