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XLSX.jl is a Julia package to read and write Excel spreadsheet files.

Inosine-guanine nucleoside hydrolase | IGNH; Leishmania infantum (strain JPCM5)

The aim of this deliverable is to develop a comprehensive plan for effectively disseminating and  communicating the public results of the ODEON project, as well as defining the methodology for op…

The aim of this deliverable is to develop a comprehensive plan for effectively disseminating and  communicating the public results of the ODEON project, as well as defining the methodology for operating the Living Labs to engage prosumers and energy stakeholders. These actions are crucial for promoting ODEON as a leading Cloud-Edge Data and Intelligence enabler for the Green and Digital Transition through robust dissemination and knowledge transfer of the project's outcomes. In line with this, the overarching objective is to harmonise the consortium's dissemination efforts to effectively meet the dissemination and communication objectives outlined in the Grant Agreement (GA). Additionally, the deliverable outlines the engagement strategy as a key component of employing a User-Driven Innovation Approach, wherein stakeholders actively participate in innovation processes. 

Abstract: Writing is an intricate and multifaceted activity influenced by intellectual processes, sociocultural contexts, rhetorical bonds, and increasingly, digital and artificial intelligence–…

Abstract: Writing is an intricate and multifaceted activity influenced by intellectual processes, sociocultural contexts, rhetorical bonds, and increasingly, digital and artificial intelligence–mediated settings. Traditional linear models of writing no longer sufficiently represent how texts are shaped in modern academic and professional situations. This review synthesizes practical and theoretical studies published between 2020 and 2025 to observe recent advances in major writing models, including cognitive, sociocultural, genre-based, technology-integrated, self-regulated, and AI-assisted methodologies. Cognitive models hypothesize writing as a recursive, goal-oriented process comprising planning, monitoring, and amendment, emphasizing executive control and metacognitive parameters. Sociocultural outlooks highpoint writing as a socially situated practice molded by identity, cooperation, audience awareness, and discourse communities, principally in multilingual contexts. Genre-based models focus on explicit instruction in rhetorical and structural conventions, supporting learners’ control over academic and professional scripts, especially when combined with digital support. The review further sightsees technology-mediated and AI-supported writing models, which have converted feedback practices, collaboration, and learner independence by providing immediate, adaptive, and personalized sustenance. Simultaneously, these innovations nurture pedagogical and ethical apprehensions, including over-reliance on robotics, equity of access, data privacy, and the conservancy of human agency in writing. Generally, the literature indicates a clear shift toward hybrid and integrative writing models that combine cognitive, social, genre-oriented, and technological scopes. The review concludes that such cohesive frameworks offer an inclusive foundation for contemporary writing instruction, though underscoring the need for further research into the long-term instructive, ethical, and assessment associations of AI-assisted writing across various learning contexts.

Interactive semantic map of digital literacy, neuroplasticity, ICT-enabled adult education, adaptive AI, online learning platforms, AI tutors, neurofeedback, AR/VR, gamification, the 2005–2025 e…

Interactive semantic map of digital literacy, neuroplasticity, ICT-enabled adult education, adaptive AI, online learning platforms, AI tutors, neurofeedback, AR/VR, gamification, the 2005–2025 empirical comparison, and ethical and accessibility challenges.

Overview This dataset provides global, gridded estimates of sector‑specific labor capacity under heat stress, derived from Wet Bulb Globe Temperature (WBGT) and mapped to economic sectors and labor ca…

Overview This dataset provides global, gridded estimates of sector‑specific labor capacity under heat stress, derived from Wet Bulb Globe Temperature (WBGT) and mapped to economic sectors and labor categories. It extends the global occupational heat‑stress labor capacity dataset of Kong & Huber (2026) by adding a new economic‑sector and labor‑type disaggregation, enabling detailed analysis of how warming affects different parts of the economy and different groups of workers. The underlying WBGT fields are based on ERA5 historical reanalysis (1995–2015) and bias‑corrected CMIP6 multi‑model ensemble projections at seven global warming levels (1–4°C above pre‑industrial) . WBGT is computed using the bias‑corrected data following Kong & Huber (2025).  Files File Description lancet_model_ensemble_v2607.zip Percent change in labor capacity- Model ensemble vs ERA5 reanalysis, 1995–2015 average - by economic activity and labor type lancet_png.zip Plots showing % change by economic acticity and labor category iso_model_ensemble_v2607.zip Percent change in labor capacity- Model ensemble vs ERA5 reanalysis, 1995–2015 average - by economic activity and labor type iso_png.zip Plots showing % change by economic acticity and labor category Data Structure Each NetCDF files follows the naming pattern: change_<Sector>_Labor_<Category>.nc Each file contains: labor_capacity_change - percent change relative to ERA5 baseline economic sector (embedded in filename) labor category (embedded in filename) warming level (1.0°C, 1.5°C, 2.0°C, 2.5°C, 3.0°C, 3.5°C, 4.0°C above pre‑industrial) 0.25° × 0.25° global grid, land‑only coverage What This Dataset Adds While the original dataset by Kong & Huber (2026) provides labor capacity for indoor/outdoor conditions, metabolic rates, and warming levels, the dataset provided here differentiates by economic sector and labor type. This dataset introduces: Economic sector classification (e.g., Agriculture, Manufacturing, Services, Construction, Extraction, Trade, Transportation) Labor categories (e.g., office, services, techpro, unskilled) Sector‑specific labor capacity change, expressed as percent change relative to the ERA5 1995–2015 baseline Future warming scenarios consistent with bias‑corrected CMIP6 ensemble mean projections (15 models) This enables researchers and policymakers to quantify which sectors lose labor capacity, which labor groups are most affected, and how impacts scale with warming. Methodology Input Data Labor capacity is computed using the same two independent response functions used in Kong & Huber (2026): ISO 7243 threshold‑based response (steep decline once WBGT exceeds metabolic‑rate‑specific limits) Lancet cumulative‑normal response, adapted from field observations (gradual decline across WBGT range) These functions bracket plausible upper and lower bounds on heat‑stress impacts on labor. Economic Activities and Labor Categories Sectoral and labor-type computation follows the methodology of Saeed et al. (2022), in which global WBGT-derived labor capacity fields are combined with spatially explicit sectoral employment distributions and labor-type shares to estimate sector-specific labor capacity based on labor parameters based on BLS provided by Saeed et al. (2022). Monthly labor capacity is calculated as the average daily labor capacity over all days within each calendar month. Monthly percentage changes are then computed by comparing each future warming scenario with the historical ERA5 climatological baseline. No. BLS Occupations Label in the Dataset 1 Management Occupations office  2 Business and Financial Operations Occupations office  3 Office and Administrative Support Occupations office        4 Computer and Mathematical Occupations techpro  5 Architecture and Engineering Occupations techpro  6 Life, Physical, and Social Science Occupations techpro  7 Community and Social Service Occupations techpro  8 Legal Occupations techpro  9 Education, Training, and Library Occupations techpro  10 Arts, Design, Entertainment, Sports, and Media Occupations techpro        11 Healthcare Practitioners and Technical Occupations services  12 Healthcare Support Occupations services  13 Protective Service Occupations services  14 Food Preparation and Serving Related Occupations services  15 Building and Grounds Cleaning and Maintenance Occupations services  16 Personal Care and Service Occupations services  17 Sales and Related Occupations services        18 Farming, Fishing, and Forestry Occupations unskilled 19 Construction and Extraction Occupations unskilled 20 Installation, Maintenance, and Repair Occupations unskilled 21 Production Occupations unskilled 22 Transportation and Material Moving Occupations unskilled For the agricultural sector, monthly averages and percentage changes are calculated only for the crop-specific growing season months, thereby representing periods of active agricultural labor demand. For all other economic sectors, calculations include all twelve months of the year representing average changes. No. BLS Economic Activities Economic Activities in the Dataset 1 Agriculture and related Agriculture 2 Mining, quarrying, and oil and gas extraction Extraction 3 Construction Construction 4 Manufacturing Manufacturing 5 Wholesale and retail trade Trade 6 Transportation and utilities Transport 7 Information Services 8 Financial activities Services 9 Professional and business services Services 10 Education and health services Services 11 Leisure and hospitality Services 12 Other services Services 13 Public administration Services Sun Exposure Agricultural outdoor labor exposure is allowed to vary across countries to reflect differences in production systems, mechanization, and technological development, following the exposure assumptions described in Saeed et al. (2022). For non-agricultural sectors, labor exposure is determined using sector- and labor-type-specific exposure factors. Air Conditioning Country-specific air conditioning (AC) penetration rates are incorporated to account for the mitigating effects of indoor climate control on occupational heat exposure. These adjustment factors reduce effective heat exposure for workers in occupations and regions where air conditioning is available, resulting in country-specific estimates of labor capacity under each warming scenario. Applications This dataset is designed for: sectoral economic impact assessments labor productivity modeling risk analysis for supply chains adaptation planning and occupational safety research integration with IAMs, CGE models, and input‑output frameworks Citation  If you use this dataset, please cite: Haqiqi, I., Kong, Q., & Moore, F. (2026). Global Gridded Sectoral Labor Capacity Change Under Heat Stress Based on ERA5 and Bias‑Corrected CMIP6 Projections. Zenodo. DOI: 10.5281/zenodo.21712766   References Kong, Q., & Huber, M. (2022). Explicit calculations of Wet Bulb Globe Temperature compared with approximations and why it matters for labor productivity. Earth's Future. Kong, Q., & Huber, M. (2025). A global high-resolution and bias-corrected dataset of CMIP6 projected heat stress metrics. Scientific Data, 12(1), 246. Kong, Q., & Huber, M. (2026). Global Gridded Occupational Heat Stress Labor Capacity Based on ERA5 and Bias‑Corrected CMIP6 Projections. Zenodo. DOI: 10.5281/zenodo.21636523 Saeed, W., Haqiqi, I., Kong, Q., Huber, M., Buzan, J. R., Chonabayashi, S., ... & Hertel, T. W. (2022). The poverty impacts of labor heat stress in West Africa under a warming climate. Earth's Future, 10(11), e2022EF002777.

Мақолада кадрлар тайёрлаш менежментида олий таълим хизматлри кўрсатишнинг меҳнат бозори талабларига мослаштиришнинг иқтисодий асослари таҳлил этилган. Жумладан, Ўзбекистон шароитида кадрлар&…

Мақолада кадрлар тайёрлаш менежментида олий таълим хизматлри кўрсатишнинг меҳнат бозори талабларига мослаштиришнинг иқтисодий асослари таҳлил этилган. Жумладан, Ўзбекистон шароитида кадрлар тайёрлаш менежменти орқали меҳнат бозори талабларига йўналтирилган олий таълим хизматлари кўрсатиш амалиётини такомиллааштириш имкониятлари аниқланган. 

This deliverable reports the progress achieved within WP4, ODEON Federated Data Sharing and Distributed Intelligence, between M6 and M21, covering T4.1 “Data Asset Marketplace and Smart Contract…

This deliverable reports the progress achieved within WP4, ODEON Federated Data Sharing and Distributed Intelligence, between M6 and M21, covering T4.1 “Data Asset Marketplace and Smart Contract Formalization Component”, T4.2 “Immutable Data Sharing Infrastructure and Operations Auditing”, T4.3 “Federated Intelligence Engines and Secure Multi-party Computations”, and T4.4 “AIOps Configuration and Orchestration”.