Our Work

MGnify's amplicon pipeline v5.0. Including the Quality control for single-end and paired-end reads, rRNA-prediction, and ITS sub-WFs.

Raw and deconvoluted microscopy data, code and intermediate analysis of basal body average volumes acquired using expansion microscopy for the paper "Structure of the mammalian transition zone microtu…

Raw and deconvoluted microscopy data, code and intermediate analysis of basal body average volumes acquired using expansion microscopy for the paper "Structure of the mammalian transition zone microtubule doublet reveals a selective portal for motor entry into cilia" 2026

Maqolada maktabgaça ta'lim taşkilotlarida ma'naviy-ma'rifiy tadbir şakllarini maqsadga muvofiq tanlaş hamda vaqt resurslaridan samarali foydalanişni boşqaruv jarayonining muhim tarkibiy qismi sifatida…

Maqolada maktabgaça ta'lim taşkilotlarida ma'naviy-ma'rifiy tadbir şakllarini maqsadga muvofiq tanlaş hamda vaqt resurslaridan samarali foydalanişni boşqaruv jarayonining muhim tarkibiy qismi sifatida rejalaştiriş masalalari yoritilgan. Namunaviy iş rejasidagi 36 ta haftalik mavzu tavsifi örganilib, tadbir şakllarining qöllaniliş takroriyligi tahlil qilingan hamda ertalabki davra suhbatining mazkur faoliyatdagi tayanç örni aniqlangan. Guruhlar uçun tavsiya etilgan davomiylik me'yorlari va tayyorgarlik jadvali asosida bolalarning yil davomida kundalik maşğulotlar hamda yirik bayram tadbirlariga ajratadigan vaqti taxminiy hisoblangan. Natijalar kiçik yoşdagi bolalar tarbiyasida kundalik faoliyat şakllarining alohida ahamiyatga ega ekanini körsatgan. Şuningdek, ikkita texnologik xaritadagi vaqt taqsimoti qiyosiy tahlil qilinib, haftalik faoliyatni izçil va samarali boşqarişga oid amaliy tavsiyalar işlab çiqilgan.

Data and code for "Global agricultural trade displaces cropland and creates spatial ecological inequality" This archive holds the processed data and the analysis code behind the quantitative results r…

Data and code for "Global agricultural trade displaces cropland and creates spatial ecological inequality" This archive holds the processed data and the analysis code behind the quantitative results reported in the paper and its supplemental information. For the benchmark years 2020, 2015 and 2010, the study removes international trade in the four staple crops in a price-responsive partial-equilibrium model, allocates the resulting cropland change in space with the PLUS model, evaluates carbon storage, water yield, soil retention, biodiversity and food production for a baseline and a counterfactual simulation, and analyses the difference between the two simulations and its distribution across economies. The archive contains seven folders: 01_code (25 Python scripts that document the computation), 02_parameters (parameters of the counterfactual model, InVEST and PLUS), 03_counterfactual (cropland change of each economy and the land-use targets of the simulation), 04_land_cover and 05_ecosystem_services (rasters of both simulations for three years), 06_results (source data of the display items) and 07_robustness (sensitivity analyses and validation checks). Third-party input data are not redistributed; their sources are listed in Table S1-1 of the supplemental information. Data files are released under CC BY 4.0 and code files under the MIT License.

This repository contains Jupyter notebooks to reproduce findings relied on in the paper Engaging with Arguments and the Emergence of Biased Views. simulations.ipynb contains recipes to run the simula…

This repository contains Jupyter notebooks to reproduce findings relied on in the paper Engaging with Arguments and the Emergence of Biased Views. simulations.ipynb contains recipes to run the simulations. These recipes rely on auxiliary functions from advocacy.py and inquiry.py. data-analysis.ipynb generates the data and plots cited/used in the publication. Two pre-compiled data sets are provided (.csv files). These contain the data that were used for the publication. Python 3.9 or newer is required to run simulations and data analysis. Python 3.13 is recommended. The notebooks require additional Python packages, listed at the top of each notebook. Please note that running the simulations is CPU-heavy and can take >24hrs. The precompiled data was obtained with the help of a high-performance computing cluster. The simulations ran on dual Intel Xeon (Cascade Lake) processors with 72 threads. Walltime for the experiments was 36hrs43min for inquiry and 24hrs05min for advocates. Memory usage is low, it is often sufficient to allocate 1GB of RAM per thread.

MonitorEO-OBSNEV is an open monitoring tool of Essential Biodiversity Variables based on satellite sensors and models generated by the University of Granada. It enables citizens, managers, and scienti…

MonitorEO-OBSNEV is an open monitoring tool of Essential Biodiversity Variables based on satellite sensors and models generated by the University of Granada. It enables citizens, managers, and scientists to create maps and graphs of key ecosystem metrics to support decision-making.MonitorEO is an output of the EVEREST Project (PID2023-151939OB-I00), funded by MICIU/AEI 10.13039/501100011033, and co-funded by ERDF – European Union, as well as of the NevadEO Project (C-EXP-074-UGR23), co-funded by the ERDF 2014-2020 Program and the Regional Ministry of Economy, Knowledge, Enterprise, and Universities of the Regional Government of Andalusia. It is also an output of the PRESINMED Project (Preserving the singularity of Mediterranean high-mountain biodiversity hotspots: a NBS approach, PCI 2025-163175) of the Biodiversa+ NBS 2023 call.MonitorEO computes with Google Earth Engine (Gorelick et al., 2017). The references are those of the formulas and algorithms of its variables, of the Earth Engine datasets that it uses (cited as their pages of the Earth Engine catalog suggest) and of its methods; each result of MonitorEO lists its own.

This thesis examines the sources through which specialized vocabulary may develop in Uzbek Sign Language (UzSL), with attention to internal sign formation, contact-induced borrowing, fingerspelling, s…

This thesis examines the sources through which specialized vocabulary may develop in Uzbek Sign Language (UzSL), with attention to internal sign formation, contact-induced borrowing, fingerspelling, semantic extension and educational standardization. The analysis combines Uzbek legal and scholarly sources with established international research on sign-language lexicons. It distinguishes documented policy and general linguistic mechanisms from hypothetical examples that require verification with Deaf signers. A comparative matrix illustrates the strengths and limitations of different term-formation pathways. The study argues that sustainable terminological development depends on Deaf-community participation, video-based documentation, regional variation research and transparent evaluation of proposed signs. No original corpus or fieldwork is claimed.

The State of European Volunteering Report 2026 (SEVR2026) is a flagship initiative developed by the Centre for European Volunteering (CEV) for International Volunteer Year 2026 (IVY2026). It establish…

The State of European Volunteering Report 2026 (SEVR2026) is a flagship initiative developed by the Centre for European Volunteering (CEV) for International Volunteer Year 2026 (IVY2026). It establishes a lasting legacy for IVY 2026 across Europe, laying the groundwork for subsequent biennial publications beginning in 2028. This report is a self-reflection exercise that builds on available information in the CEV European Volunteering “Country Factsheets” and the “Volunteering Infrastructure in Europe” country reports. This material, compiled largely by CEV member organisations,  represents the primary sources for SEVR2026. Data and evidence on volunteering trends has been analysed, together with information about progress in different European countries towards a selection of the envisaged outcomes (indicators) in the Blueprint for Volunteering 2030 (BEV2030).

Dataset of 1147 synthetic water distribution networks laid out on the OpenStreetMap streets and Copernicus GLO-30 elevations of 428 cities, towns and rural settlements of Peru, with 255518 simulated l…

Dataset of 1147 synthetic water distribution networks laid out on the OpenStreetMap streets and Copernicus GLO-30 elevations of 428 cities, towns and rural settlements of Peru, with 255518 simulated leak scenarios and the results of four baseline leak localization methods. Each network includes its EPANET 2.2 model, one-week demand patterns with a 15 min step and sensor configurations for densities of 1, 5, 10 and 20 % of the service nodes. Each scenario stores the nominal pressure, the pressure difference caused by the leak and the leak parameters (pipe, position, type, equivalent diameter, start, growth and flow). The networks are split by place into training (788), validation (177) and test (182) sets. The test scenarios cover two days with a 15 min step; the training and validation scenarios keep the last 4 h of the pressure difference. Files: networks.zip, scenarios_train.zip, scenarios_validation.zip, scenarios_test.zip and the tables folder (network catalogue, verification checks, scenario summary and benchmark results). README.txt describes every file and key. Street data: © OpenStreetMap contributors, distributed under the Open Database License (ODbL).Elevation data produced using Copernicus WorldDEM-30 © DLR e.V. 2010-2014 and © Airbus Defence and Space GmbH 2014-2018 provided under COPERNICUS by the European Union and ESA; all rights reserved. The organisations in charge of the Copernicus programme by law or by delegation do not incur any liability for any use of the Copernicus WorldDEM-30.Population: WorldPop 2020 (CC BY 4.0).

BING simulation dataset: (1) BING peptide in water (2) BING peptide in a solvated DOPC membrane (3) BING peptide in a solvated DOPG membrane   Each folder contains simulation parameters and topol…

BING simulation dataset: (1) BING peptide in water (2) BING peptide in a solvated DOPC membrane (3) BING peptide in a solvated DOPG membrane   Each folder contains simulation parameters and topology in GROMACS, simulation trajectory and log file.