Our Work

Code used to produce the results and figures in the manuscript Infrastructure-Aware Urban Flood Susceptibility from Multi-Event High-Water Marks: A Multi-Model Comparison.

Sound detection amidst noise presents an important challenge in audition. Many naturally occurring sounds (rain, wind) can be described and predicted statistically, so-called sound textures. Previous …

Sound detection amidst noise presents an important challenge in audition. Many naturally occurring sounds (rain, wind) can be described and predicted statistically, so-called sound textures. Previous research has demonstrated humans' ability to leverage this statistical predictability for sound recognition, but the neural mechanisms remain elusive. We trained mice to detect vocalizations embedded in sound textures with different statistical predictability, while recording and optogenetically modulating the neural activity in the auditory cortex. Mice showed improved performance and neural representation if they sampled the statistics longer per trial. Textures with more exploitable structure, specifically higher cross-frequency correlations (CFCs) improved performance and vocalization decoding. Activating parvalbumin-positive (PV) interneurons had an asymmetric effect, improving detection and neural representation of vocalizations for low, and vice versa for high CFCs. Thus, mice can exploit stimulus statistics to improve the sound detection in noise, reflected in performance and neural activity, while relying on PV interneurons.

Diagnosis of cystic echinococcosis is complex and has to be confirmed by the combination of immunological tests and imaging techniques. In this study heat shock proteins were induced and their immunor…

Diagnosis of cystic echinococcosis is complex and has to be confirmed by the combination of immunological tests and imaging techniques. In this study heat shock proteins were induced and their immunoreactivity was assessed by ELISA. Sera were collected from 34 hydatid patients who were admitted to the Rizgary Teaching Hospital through October 2013 to July 2017, in addition to 29 healthy donors and 18 non-hydatid cases. For heat shock response, two batches of 25000 protoscoleces (Ps) were incubated separately at 42°C and 45 °C for 4 hours. Heat treated and normal Ps were disrupted and the extracts were divided into two parts. One part was directly used as source of antigens (PE, PE42 and PE45) and the other one was partially purified on Sephadex G150. The immunoreactivity of these antigens, as well as hydatid fluidwas assessed by ELISA. The cutoff value to differentiate positive from negative sera was established by receiver operating characteristic (ROC) analysis. Two peaks of PE42 and three peaks of PE45 resulted by Sephadex G150. Extracts of 42ºC treated Ps resulted in two protein peaks and were used as PE42P1 and PE42P2 antigens. For 45°C treated Ps, the chromatography patterns resulted in three protein peaks and were used as PE45P1, PE45P2 and PE45P3 antigens. Highest rates of sensitivity, specificity and diagnostic accuracy were detected with PE42P2 (91.2%) and PE45P2 (91.2%). Sensitivity of ELISA was consistent for liver cysts with all applied antigens. Hydatid antigens extracted from heat treated Ps markedly raised the sensitivity of ELISA to detect anti-hydatid IgG.

What's Changed Add a from host radiative transfer solver by @K20shores in https://github.com/NCAR/tuv-x/pull/217 Update version to 0.17.0 by @boulderdaze in https://github.com/NCAR/tuv-x/pull/220 Fu…

What's Changed Add a from host radiative transfer solver by @K20shores in https://github.com/NCAR/tuv-x/pull/217 Update version to 0.17.0 by @boulderdaze in https://github.com/NCAR/tuv-x/pull/220 Full Changelog: https://github.com/NCAR/tuv-x/compare/v0.16.0...v0.17.0

El presente ensayo contiene reflexiones críticas sobre el rol de los Juegos Intercolegiados en la reducción de la deserción escolar en contextos rurales como el Municipio de Cotor…

El presente ensayo contiene reflexiones críticas sobre el rol de los Juegos Intercolegiados en la reducción de la deserción escolar en contextos rurales como el Municipio de Cotorra- Córdoba. Se sustenta en una investigación en desarrollo y tiene por objetivo analizar cómo la participación prejuvenil impacta la motivación académica y el sentido de pertenencia institucional. La revisión teórica integra antecedentes locales e internacionales, destacando que el deporte escolar fomenta la autoeficacia y la cohesión grupal. Los principales argumentos señalan que los Juegos Intercolegiales actúan como laboratorio social para la resiliencia emocional, contrarrestando factores socioeconómicos rurales mediante trabajo en equipo y reconocimiento. El análisis crítico revela vacíos en infraestructura y seguimiento longitudinal, pero enfatiza su potencial transformador pese a barreras como el sedentarismo y la pobreza. El estudio constituye un llamado a políticas integrales que vinculen el deporte y la educación para mitigar la deserción en la ruralidad

A native Julia implementation of the Faddeeva function using Weideman’s approximation, suitable for CPU and GPU execution.

The International Military Deployments Dataset (IMDT) is a dyadic dataset of 21,217 country-country-year observations recording interstate military deployments worldwide between 1962 and 2022. It cove…

The International Military Deployments Dataset (IMDT) is a dyadic dataset of 21,217 country-country-year observations recording interstate military deployments worldwide between 1962 and 2022. It covers 173 deploying states and 174 host countries and records: troop numbers (disaggregated where possible into combat personnel and military observers); mission types (peacekeeping, counter-insurgency, training, maritime security, air security, contested territory); organisational mandates (UN, NATO, EU, AU, ECOWAS, ECOMOG, ECCAS, NARC, SADC, OSCE, US-led non-NATO coalitions, other regional organisations); operation names; and provenance flags. Countries are coded using the Correlates of War (COW) numerical country code system, making the data directly compatible with ATOP, the COW Alliance Data, the UCDP/PRIO Armed Conflict Dataset, the Defense Cooperation Agreements Dataset, the SIPRI Arms Transfers Database, and other established quantitative IR resources. Source attribution. The primary empirical source is the International Institute for Strategic Studies (IISS) Military Balance annual publications, supplemented by the United Nations Department of Peace Operations peacekeeping databases, NATO and Canadian Department of National Defence web archives, Allen, Flynn and Martinez Machain (2022) for US deployment cross-validation, and Vignoli and Coticchia (2022) for Italian operations. Of the 21,217 observations, 20,747 (97.8%) are coded from Military Balance country entries; 454 are gap-filled from secondary sources; and 16 are constructed by temporal interpolation between anchor years. The IMDT records factual deployment information recoded into a novel dyadic Correlates of War framework. It does not distribute any text, tables, analytical commentary or editorial assessments from The Military Balance; users who need the detail of a source entry should consult the corresponding edition. Users of the IMDT should cite both the IMDT paper (Maltsev, Gatskovskaya and Stasevski, forthcoming, Conflict Management and Peace Science) and The Military Balance (London: International Institute for Strategic Studies, annual) in any work derived from this dataset. Version 2.4 (5 October 2026) removes the free-text field Additional_Info, which contained coders' transcriptions of the Military Balance entries used for coding (an internal audit trail, not used in any analysis). All observations and all other variables are unchanged, and all results in the article are reproduced identically. Version 2.3 should no longer be used or redistributed.

A catalogue entry whose data is gone no longer makes a cube impossible to build. Missing scenes are skipped instead of aborting the run (#95): when an asset listed in the STAC catalogue returns HTTP …

A catalogue entry whose data is gone no longer makes a cube impossible to build. Missing scenes are skipped instead of aborting the run (#95): when an asset listed in the STAC catalogue returns HTTP 404 (or "The specified key does not exist" on S3), the whole scene is dropped, a missing_asset_skip warning names it, and process() ends with one missing_assets_skipped summary. Before, a single dead scene anywhere in the time range failed the entire cube on every attempt. New parameter skip_missing_assets (default True); with False the run aborts with SentleMissingAssetError. A 404 is no longer retried. Everything else (403, 429, 5xx, timeouts) keeps retry-then-abort. Scenes are dropped whole, for Sentinel-2 and Sentinel-1: an item with one missing band or polarisation contributes nothing. A dropped Sentinel-2 scene counts as not listed, so an older processing of the same acquisition or an overlapping tile can fill its place. Output is unchanged wherever no asset is missing.

What's Changed Auto-format code changes by @github-actions[bot] in https://github.com/NCAR/MechanismConfiguration/pull/288 Add emissions configuration schema (inventories, species maps, sources) to m…

What's Changed Auto-format code changes by @github-actions[bot] in https://github.com/NCAR/MechanismConfiguration/pull/288 Add emissions configuration schema (inventories, species maps, sources) to mechanism v1 by @smeechncar in https://github.com/NCAR/MechanismConfiguration/pull/281 Introduce aerosol chemistry validation and parser support by @boulderdaze in https://github.com/NCAR/MechanismConfiguration/pull/282 Auto-format code changes by @github-actions[bot] in https://github.com/NCAR/MechanismConfiguration/pull/292 Refactor code organization after adding Aerosols and Emissions by @boulderdaze in https://github.com/NCAR/MechanismConfiguration/pull/293 Auto-format code changes by @github-actions[bot] in https://github.com/NCAR/MechanismConfiguration/pull/294 Add inline to version print helpers to avoid duplicate errors in downstream by @boulderdaze in https://github.com/NCAR/MechanismConfiguration/pull/295 Adds solvent floor and min halflife field for aerosol processes by @boulderdaze in https://github.com/NCAR/MechanismConfiguration/pull/296 Rename Arrhenius reference temperature to Equilibrium by @boulderdaze in https://github.com/NCAR/MechanismConfiguration/pull/299 Add ozone oxidation pathway in cloud chemistry configuration by @boulderdaze in https://github.com/NCAR/MechanismConfiguration/pull/301 Fix rate constant label by @mattldawson in https://github.com/NCAR/MechanismConfiguration/pull/303 Rename to Henry's Law by @mattldawson in https://github.com/NCAR/MechanismConfiguration/pull/304 Auto-format code changes by @github-actions[bot] in https://github.com/NCAR/MechanismConfiguration/pull/305 Make aerosol validation location-aware by @boulderdaze in https://github.com/NCAR/MechanismConfiguration/pull/306 Auto-format code changes by @github-actions[bot] in https://github.com/NCAR/MechanismConfiguration/pull/308 Preserve v0 species/reaction properties needed for v1 conversion by @K20shores in https://github.com/NCAR/MechanismConfiguration/pull/309 Fix remaining v0->v1 conversion gaps (third body, gas phase, surface prefix) by @K20shores in https://github.com/NCAR/MechanismConfiguration/pull/310 Allow photolysis reactions with no reactants by @K20shores in https://github.com/NCAR/MechanismConfiguration/pull/312 Point the intersphinx mappings at Read the Docs by @K20shores in https://github.com/NCAR/MechanismConfiguration/pull/314 Point the reaction cross-references at the micm structs that exist by @K20shores in https://github.com/NCAR/MechanismConfiguration/pull/315 V0 semantic validation by @K20shores in https://github.com/NCAR/MechanismConfiguration/pull/317 Update species parse and docs by @K20shores in https://github.com/NCAR/MechanismConfiguration/pull/318 set tracer type in unknown properties by @K20shores in https://github.com/NCAR/MechanismConfiguration/pull/319 Add per-inventory molecular weights to emissions schema by @smeechncar in https://github.com/NCAR/MechanismConfiguration/pull/320 Update the version to 2.1.0 by @boulderdaze in https://github.com/NCAR/MechanismConfiguration/pull/322 New Contributors @smeechncar made their first contribution in https://github.com/NCAR/MechanismConfiguration/pull/281 Full Changelog: https://github.com/NCAR/MechanismConfiguration/compare/v2.0.0...v2.1.0