Our Work

This is the story of a dramatic homecoming that felt more like a film plot than a political coup. In June 1930, Prince Carol II’s plane touched down at the Cluj airfield, marking a spectacular a…

This is the story of a dramatic homecoming that felt more like a film plot than a political coup. In June 1930, Prince Carol II’s plane touched down at the Cluj airfield, marking a spectacular and risky return to reclaim his throne. Moving away from the later propaganda, this work seeks to find the man behind the monarch. It offers a more intimate look at a ruler who arrived with the ambition of a saviour, only to find his reign swept away by the brutal tides of 20th-century extremism. Keywords: King Carol II of Romania, Restoration of Carol II, Cluj airfield, Interwar Romania, Romanian Monarchy, Aviation history. Acknowledgments: This work was financially supported by the project ”Quality, innovative and labor market relevant doctoral and postdoctoral research”: POCU/380/6/13/124146, a project co-financed from the European Social Fund, through the Human Capital Operational Program 2014-2020. 

Este repositorio contiene los datos y el código desarrollado (R-software) para el análisis y optimización del posicionamiento de nodos en la graduación de tablas de mortali…

Este repositorio contiene los datos y el código desarrollado (R-software) para el análisis y optimización del posicionamiento de nodos en la graduación de tablas de mortalidad mediante B-splines cúbicos, aplicado a la mortalidad de la población española. El objetivo principal es analizar cómo la localización de los nodos afecta a la calidad de la graduación y comparar diferentes estrategias para determinar su posición. Se consideran tres procedimientos basados en splines: nodos fijos equidistantes, utilizados como modelo de control; un procedimiento híbrido basado en MARS (Multivariate Adaptive Regression Splines) para la identificación de puntos de ruptura; y un algoritmo genético para la optimización de la posición de nodos libres. Como referencia paramétrica, se incluyen además las formulaciones de Heligman-Pollard de 8 y 12 parámetros. La comparación de los modelos se realiza mediante diferentes medidas de ajuste, parsimonia y suavidad, incluyendo AIC, BIC, RMSRE y un índice basado en segundas diferencias. El código incorpora asimismo análisis de residuos y heterocedasticidad, así como procedimientos de simulación Monte Carlo destinados a estudiar la estabilidad de las posiciones nodales ante variaciones muestrales. Para el algoritmo genético se analiza adicionalmente la evolución de las posiciones de los nodos durante el periodo 2000-2019, su estructura de correlación y su posible evolución temporal. Finalmente, se estudia el efecto actuarial de las diferentes graduaciones mediante su aplicación al cálculo de la prima única pura de un seguro temporal de fallecimiento. Los scripts permiten reproducir los principales análisis y resultados presentados en el Trabajo Fin de Máster. Los datos de mortalidad empleados proceden de Human Mortality Database (HMD).

This article provides a systematic analysis of the existing economic mechanisms for the efficientutilization of alternative energy resources in Uzbekistan’s energy industry and substantiates the…

This article provides a systematic analysis of the existing economic mechanisms for the efficientutilization of alternative energy resources in Uzbekistan’s energy industry and substantiates the priority directionsfor their improvement. The study evaluates the interrelationships among investment, financial, institutional, andmarket factors influencing the development of renewable energy sources. Furthermore, it proposes scientific andpractical recommendations aimed at assessing alternative energy projects based on comprehensive economicefficiency, introducing differentiated incentive mechanisms, ensuring the rational utilization of regional resourcepotential, increasing the level of localization, and implementing a digital monitoring system.

Full Changelog: https://github.com/bob-friedman/latent-reasoning-engine/compare/v1.1...v1.2

Many digital data repositories and archives face growing preservation challenges, driven by diverse data formats, rapidly increasing data volumes, and the overall complexity of long-term data manageme…

Many digital data repositories and archives face growing preservation challenges, driven by diverse data formats, rapidly increasing data volumes, and the overall complexity of long-term data management. The introduction of FAIR, CARE, and TRUST principles, alongside the need for long-term digital preservation (LTDP), has major implications for digital repositories and archives. The EU-funded EOSC EDEN (2025–2027) [1] project aims to address these challenges by standardizing preservation and curation practices to ensure digital objects remain FAIR and usable over time. Several key achievements of EOSC EDEN were released in 2025 to benefit the communities.  Core Preservation Processes - It comprises 30 core preservation processes (CPPs), each representing a specific action a Trustworthy Digital Archive should take - whether directly or through its affiliates or service providers - to fulfil its digital preservation mission (as outlined in its preservation policy) [2]. These CPPs were developed by a group of digital preservation practitioners in EOSC EDEN, which focuses on the operational activities required for maintaining the authenticity, integrity, and usability of digital objects. Each CPP is expressed as a series of implementable steps that may be executed manually or automatically.  Expert Curation and Digital Preservation Network - EOSC EDEN is establishing a network representing repositories (both generalist and specialist), archives, and organizations responsible for research data curation and preservation. Through this network, clear roles and responsibilities for curation and digital preservation tasks will be defined. The first EOSC EDEN Curation Workshop [3], held in October 2025 in Leuven (Belgium), brought together over thirty European experts to exchange knowledge and lay the foundations for this network. By building a coordinated, multinational network, EOSC EDEN will strengthen knowledge sharing, harmonise approaches, and enhance the long-term sustainability of digital preservation efforts.  System requirements, repository attributes, and service specifications – EOSC EDEN consolidates system requirements, repository attributes, and service specifications to support trusted, interoperable, and scalable preservation infrastructures across scientific domains, in line with standards such as the Open Archival Information System (OAIS) [4]. The recent analysis [5] highlights persistent interoperability challenges - technical (e.g., format fragmentation, inconsistent APIs), semantic (e.g., varying metadata models and vocabularies), and organisational (e.g., divergent policies and workflows). The project working group further examines interoperability, research output quality assurance, and rights and ethics, supported by concrete examples. Together, these insights provide a solid basis for developing a structured inventory of services relevant to digital preservation and curation.  Discipline Requirements and Needs - EOSC EDEN investigates discipline-specific requirements, gaps, and emerging needs related to LTDP and digital object quality (DOQ) [6]. The initial insights are provided from seven early-adopter disciplines: Climate Simulations, Earth & Environmental Sciences, Food Sciences, High-Energy Physics, Life Sciences & Bioinformatics, Linguistics, and Social Sciences. Many smaller, scholar-led repositories often lack well-documented LTDP and DOQ policies, leading to challenges in contextual, technical, and metadata quality. Across these domains, the most critical need is ensuring robust data documentation that supports both reliable preservation and sustained data utility.  Outcome of the presentation - The presentation will showcase how EOSC EDEN’s outcomes collectively advance long-term digital preservation and knowledge security for research data. Attendees will gain actionable insights into harmonizing preservation practices.  References  1. https://cordis.europa.eu/project/id/101188015  2. Lindlar, M., et al. (2025). Report on Identification of Core Preservation Processes (M1.1). Zenodo. https://doi.org/10.5281/zenodo.16992452  3. https://eden-fidelis.eu/blog/1st-eosc-eden-curation-workshop-leuven-belgium-gathering-experts-build-european-curation-and  4. Middelbos, W., et al. (2025). EOSC EDEN Specifications and Architecture (D2.1, Iteration 1). Zenodo. https://doi.org/10.5281/zenodo.17232536  5. CCSDS. (2012). Reference Model for an Open Archival Information System (OAIS). ISO 14721. https://www.iso.org/standard/87471.html  6. Andreassen, H. N., et al. (2025). Report on Discipline Requirements and Needs (D3.1). Zenodo. https://doi.org/10.5281/zenodo.15789261 

## Description This repository contains a semantic RDF/OWL knowledge base representing analytical measurements (IRMS isotope ratios and ICP-MS elemental concentrations) from gilthead seabream (*Sparus…

## Description This repository contains a semantic RDF/OWL knowledge base representing analytical measurements (IRMS isotope ratios and ICP-MS elemental concentrations) from gilthead seabream (*Sparus aurata*) samples. The knowledge base integrates chemical measurement data with standardized ontology annotations, enabling FAIR-compliant data sharing, food traceability, and authenticity verification research. ### Key Features - **115 fish samples** from aquaculture and wild-caught sources- **2,745 chemical measurements** with full semantic annotation- **16,750 RDF triples** linking to standard ontologies- **Multi-ontology integration**: ChEBI, Unit Ontology (UO), FoodOn, NCBITaxon- **24 analytes mapped**: 4 stable isotopes (δ13C, δ15N, δ34S, δ18O) + 20 elements ### Dataset Summary | Metric | Value ||--------|-------|| Host species | *Sparus aurata* (Gilthead Seabream) || Total samples | 115 || Total measurements | 2,745 || IRMS isotope ratios | 4 (δ13C, δ15N, δ34S, δ18O) || ICP-MS elements | 20 (Na, Mg, P, S, K, Ca, V, Cr, Mn, Fe, Co, Cu, Zn, As, Se, Rb, Sr, Mo, Ba, Hg) || Production methods | Aquaculture, Wild || RDF triples | 16,750 | ## Files | File | Description ||------|-------------|| `README_zenodo_fisheutrust_samples.md` | This documentation file || `FishEUTrust_samples_JSI.xlsx` | Original Excel file with IRMS and ICP-MS analytical data || `fisheutrust_knowledge_base.ttl` | RDF knowledge base in Turtle format (~650 KB) || `fisheutrust_knowledge_base.rdf` | RDF knowledge base in RDF/XML format (~1.7 MB) || `FishEUTrust_Complete_Ontology_Mapping.xlsx` | Complete ontology mapping tables || `FishEUTrust_Semantic_Annotation_Deliverable.docx` | Project deliverable document with methodology || `create_fisheutrust_knowledge_base.py` | Python script to generate the knowledge base || `README.md` | Technical documentation for the Python script || `requirements.txt` | Python package dependencies | ## Usage ### Loading the Knowledge Base **Python (rdflib):**```pythonfrom rdflib import Graph g = Graph()g.parse("fisheutrust_knowledge_base.ttl", format="turtle")print(f"Loaded {len(g)} triples")``` **Apache Jena:**```bashriot --validate fisheutrust_knowledge_base.ttl``` ### SPARQL Query Examples **Find all aquaculture samples:**```sparqlPREFIX fish: <http://example.org/fisheutrust/> SELECT ?sample ?sampleIDWHERE {  ?sample a fish:FishSample ;          fish:hasSampleID ?sampleID ;          fish:hasProductionMethod fish:Aquaculture .}``` **Get iron (Fe) measurements for all samples:**```sparqlPREFIX fish: <http://example.org/fisheutrust/>PREFIX chebi: <http://purl.obolibrary.org/obo/CHEBI_> SELECT ?sampleID ?valueWHERE {  ?sample fish:hasSampleID ?sampleID ;          fish:hasMeasurement ?meas .  ?meas fish:measuresAnalyte chebi:18248 ;        fish:hasValue ?value .}ORDER BY ?sampleID``` **Find samples with mercury (Hg) above threshold:**```sparqlPREFIX fish: <http://example.org/fisheutrust/>PREFIX chebi: <http://purl.obolibrary.org/obo/CHEBI_> SELECT ?sampleID ?hg_valueWHERE {  ?sample fish:hasSampleID ?sampleID ;          fish:hasMeasurement ?meas .  ?meas fish:measuresAnalyte chebi:25195 ;        fish:hasValue ?hg_value .  FILTER(?hg_value > 0.5)}``` **Compare δ13C between aquaculture and wild samples:**```sparqlPREFIX fish: <http://example.org/fisheutrust/>PREFIX chebi: <http://purl.obolibrary.org/obo/CHEBI_> SELECT ?method (AVG(?value) as ?avg_d13c)WHERE {  ?sample fish:hasProductionMethod ?method ;          fish:hasMeasurement ?meas .  ?meas fish:measuresAnalyte chebi:36928 ;        fish:hasValue ?value .}GROUP BY ?method``` ### Regenerating the Knowledge Base ```bashpip install -r requirements.txtpython create_fisheutrust_knowledge_base.py FishEUTrust_samples_JSI.xlsx output.ttl output.rdf``` ## Technical Specifications ### RDF Statistics | Component | Count ||-----------|-------|| Total triples | 16,750 || OWL classes | 6 || Object properties | 7 || Datatype properties | 4 || Sample instances | 115 || Measurement instances | 2,745 | ### Namespaces ```turtle@prefix fish: <http://example.org/fisheutrust/> .@prefix chebi: <http://purl.obolibrary.org/obo/CHEBI_> .@prefix uo: <http://purl.obolibrary.org/obo/UO_> .@prefix foodon: <http://purl.obolibrary.org/obo/FOODON_> .@prefix ncbitaxon: <http://purl.obolibrary.org/obo/NCBITaxon_> .@prefix pubchem: <http://pubchem.ncbi.nlm.nih.gov/compound/> .``` ### OWL Classes | Class | Description ||-------|-------------|| `fish:FishSample` | A biological sample from a fish specimen || `fish:FishSpecies` | A species of fish || `fish:Measurement` | Abstract measurement class || `fish:IRMSMeasurement` | Isotope ratio measurement (subclass) || `fish:ICPMSMeasurement` | Elemental concentration measurement (subclass) || `fish:ProductionMethod` | Aquaculture or Wild production | ## Requirements ### For using the knowledge base:- Any RDF-compatible triple store (Apache Jena, GraphDB, Blazegraph, Virtuoso, etc.)- Or: Python 3.8+ with rdflib ### For regenerating the knowledge base:- Python 3.8+- rdflib >= 7.0.0- pandas >= 2.0.0- openpyxl >= 3.1.0 ## License This work is licensed under a [Creative Commons Attribution 4.0 International License](http://creativecommons.org/licenses/by/4.0/). You are free to:- **Share** — copy and redistribute the material in any medium or format- **Adapt** — remix, transform, and build upon the material for any purpose, even commercially Under the following terms:- **Attribution** — You must give appropriate credit, provide a link to the license, and indicate if changes were made. ## Citation If you use this knowledge base in your research, please cite: ```bibtex@dataset{fisheutrust_sample_kb_2026,  author       = {{FishEUTrust Consortium}},  title        = {{FishEUTrust Fish Sample Analytical Data Knowledge Base:                    Semantic Annotation of IRMS and ICP-MS Measurements                    from Gilthead Seabream}},  year         = {2026},  publisher    = {Zenodo},  doi          = {10.5281/zenodo.XXXXXXX},  url          = {https://doi.org/10.5281/zenodo.XXXXXXX}}``` ## Related Resources - [FishEUTrust Project Website](https://fisheutrust.eu/)- [ChEBI - Chemical Entities of Biological Interest](https://www.ebi.ac.uk/chebi/)- [Unit Ontology](http://www.obofoundry.org/ontology/uo.html)- [FoodOn Food Ontology](http://www.obofoundry.org/ontology/foodon.html)- [NCBI Taxonomy](https://www.ncbi.nlm.nih.gov/taxonomy)- [OBO Foundry](http://www.obofoundry.org/) ## Contact For questions or issues regarding this dataset, please contact: - **FishEUTrust Project Team**- Website: [https://fisheutrust.eu/](https://fisheutrust.eu/) ## Version History | Version | Date | Changes ||---------|------|---------|| 1.0.0 | 2026-02 | Initial release with ChEBI, UO, FoodOn, NCBITaxon mappings | ## Acknowledgments We thank:- The European Bioinformatics Institute (EBI) for maintaining ChEBI- The OBO Foundry community for maintaining the ontologies used in this work- Jožef Stefan Institute (JSI) for providing the analytical data

This resource forms part of the Green ERA-Hub Living Archive, developed within the Horizon Europe Green ERA-Hub Coordination and Support Action (CSA). The Living Archive provides a curated collection …

This resource forms part of the Green ERA-Hub Living Archive, developed within the Horizon Europe Green ERA-Hub Coordination and Support Action (CSA). The Living Archive provides a curated collection of practical guidance, tools, templates and examples designed to support funders, programme managers and research organisations in planning, implementing and improving transnational research and innovation (R&I) collaboration. Resources are organised around four thematic areas: Funding Modalities, Research Prioritisation, Monitoring, Evaluation and Impact Assessment (MEIA), and Widening & Outreach. This practical example demonstrates how a structured, multi-method approach can be used to develop research priorities for a transnational research and innovation programme. Drawing on established practices from the Green ERA-Hub ecosystem and related European partnership initiatives, it illustrates a complete prioritisation pathway combining evidence gathering and portfolio analysis, stakeholder consultation, partner workshops, refinement and validation, and the translation of agreed priorities into call-ready topics. The example highlights practical challenges, success factors and lessons learned, showing how funding organisations and programme partners can reconcile different national priorities, integrate stakeholder perspectives and use evidence to develop clear, actionable and jointly agreed research priorities. It is intended to complement the Green ERA-Hub Research Prioritisation Decision Tool and associated guidance by demonstrating how these approaches can be applied in practice to support effective transnational research programming.

Ushbu maqolada davlat-xususiy sheriklik (DXSH) asosida xizmat ko‘rsatuvchi korxonalarni boshqarishning nazariy va amaliy asoslari, ularning o‘ziga xos boshqaruv tamoyillari hamda…

Ushbu maqolada davlat-xususiy sheriklik (DXSH) asosida xizmat ko‘rsatuvchi korxonalarni boshqarishning nazariy va amaliy asoslari, ularning o‘ziga xos boshqaruv tamoyillari hamda O‘zbekiston Respublikasida joriy etilayotgan DXSH modellarining samaradorligi tahlil qilinadi. DXSH korxonalarida boshqaruv ikki tomonlama manfaat, xavf-xatarlarni taqsimlash, xizmat sifati va barqarorlik mezonlariga asoslanadi. Tadqiqot davomida ushbu modeldagi boshqaruvning afzalliklari bilan bir qatorda, mavjud muammolar — huquqiy bo‘shliqlar, koordinatsiya zaifligi, moliyaviy risklar va monitoring tizimidagi kamchiliklar aniqlanadi. Maqolada ushbu muammolarni bartaraf etishga doir ilmiy-amaliy yechimlar taklif etilgan. O‘zbekiston tajribasi xalqaro yondashuvlar bilan solishtirib o‘rganilgan.

The article systematically analyses the organisational-legal, economic-financial, institutionalpartnership,marketing-digital and human-resource mechanisms for managing entrepreneurial activity inphysi…

The article systematically analyses the organisational-legal, economic-financial, institutionalpartnership,marketing-digital and human-resource mechanisms for managing entrepreneurial activity inphysical education and sport. Drawing on the legal acts and official indicators of the Republic of Uzbekistan,the priority of the public-private partnership mechanism is substantiated. A block diagram of the managementmechanisms is proposed together with recommendations for improving sectoral efficiency.