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#xed

0 posts0 participants0 posts today
sfm

"Xed-Editor was updated to 3.1.0, and Git integration was moved to a standalone extension. The developer also warns users to only download the app from the official sources: F-Droid, IzzyOnDroid and the project Github, as somebody has put the app on Play without their approval. The same person/company has done the same for WhatSave unfortunately."

Source: f-droid.org/2025/05/22/twif.ht

f-droid.orgRead It Or Rate It | F-Droid - Free and Open Source Android App RepositoryThis Week in F-DroidTWIF curated on Thursday, 22 May 2025, Week 21Community NewsDelta Chat and ArcaneChat were updated to 1.58.4. If you are a fan of Delta C...
#xed#fdroid#android
Norm

I'm writing a document in #Markdown and was somewhat disappointed to realise that #Xed (the default text editor in #LinuxMint) doesn't have a Markdown preview ability...

I didn't really want to install an app just for writing/previewing Markdown files, so searched online instead and found stackedit.io/app

It seems to work quite nicely, and it's #FOSS! Win-win.

stackedit.ioStackEditFree, open-source, full-featured Markdown editor.
#StackEdit#Linux#LMDE
AOSbot

Title: Projected changes in the Iberian Peninsula drought characteristics.

High spatial resolution drought projections for the Iberian Peninsula (IP)
have been examined in terms of duration, frequency, and severity of drought
events. For this end, a set of regional climate simulations wa [...]

Authors: M. García-Valdecasas Ojeda, S.R. Gámiz-Fortis, J.J. Rosa-Cánovas, E. Romero-Jiménez, P. Yeste, Y. Castro-Díez, M.J. Esteban-Parra

Link: arxiv.org/abs/2401.07104

arXiv.orgProjected changes in the Iberian Peninsula drought characteristicsHigh spatial resolution drought projections for the Iberian Peninsula (IP) have been examined in terms of duration, frequency, and severity of drought events. For this end, a set of regional climate simulations was completed using the Weather Research and Forecasting (WRF) model driven by two global climate models (GCMs), the CCSM4 and the MPI-ESM-LR, for a near (2021-2050) and a far (2071-2100) future, and under two representative concentration pathway (RCP) scenarios (RCP4.5 and RCP8.5). Projected changes for these simulations were analyzed using two drought indices, the Standardized Precipitation Evapotranspiration Index (SPEI) and the Standardized Precipitation Index (SPI), considering different timescales (3- and 12-months). The results showed that the IP is very likely to undergo longer and more severe drought events. Substantial changes in drought parameters (i.e., frequency, duration, and severity) were projected by both indices and at both time scales in most of the IP. These changes are particularly strong by the end of the century under RCP8.5. Meanwhile, the intensification of drought conditions is expected to be more moderate for the near future. However, the results also indicated key differences between indices. Projected drought conditions by using the SPEI showed more severe increases in drought events than those from SPI by the end of the century and, especially, for the high-emission scenario. The most extreme conditions were projected in terms of the duration of the events. Specifically, results from the 12-month SPEI analysis suggested a significant risk of megadrought events (drought events longer than 15 years) in many areas of IP by the end of the century under RCP8.5.
Continued thread
mlnf

Dateimanager (#nemo) oder Editor (#xed) merken sich Fenstergröße, aber nicht Position.

Rechner (#calculator) merkt sich die Position, aber nicht die Fenstergröße.

Nemo -> Suche:
mit Tab von "Dateien suchen" zu "Inhalt suchen" wechseln
mit Shift+Tab aber nicht Rückwärts

Jemand dazu Tipps und Kniffe?

(2/2)

AOSbot

Title: Assessing Long-Distance Atmospheric Transport of Soilborne Plant Pathogens.

Pathogenic fungi are a leading cause of crop disease and primarily spread
through microscopic, durable spores adapted differentially for both persistence
and dispersal. Computational Earth System Models [...]

Authors: Hannah Brodsky, Rocío Calderón, Douglas S. Hamilton, Longlei Li, Andrew Miles, Ryan Pavlick, Kaitlin M. Gold, Sharifa G. Crandall, Natalie Mahowald

Link: arxiv.org/abs/2304.09346

arXiv.orgAssessing Long-Distance Atmospheric Transport of Soilborne Plant PathogensPathogenic fungi are a leading cause of crop disease and primarily spread through microscopic, durable spores adapted differentially for both persistence and dispersal. Computational Earth System Models and air pollution models have been used to simulate atmospheric spore transport for aerial-dispersal-adapted (airborne) rust diseases, but the importance of atmospheric spore transport for soil-dispersal-adapted (soilborne) diseases remains unknown. This study adapts the Community Atmosphere Model, the atmospheric component of the Community Earth System Model, to simulate the global transport of the plant pathogenic soilborne fungus Fusarium oxysporum, F. oxy. Our sensitivity study assesses the model's accuracy in long-distance aerosol transport and the impact of deposition rate on long-distance spore transport in Summer 2020 during a major dust transport event from Northern Sub-Saharan Africa to the Caribbean and southeastern U.S. We find that decreasing wet and dry deposition rates by an order of magnitude improves representation of long distance, trans-Atlantic dust transport. Simulations also suggest that a small number of viable spores can survive trans-Atlantic transport to be deposited in agricultural zones. This number is dependent on source spore parameterization, which we improved through a literature search to yield a global map of F. oxy spore distribution in source agricultural soils. Using this map and aerosol transport modeling, we show how viable spore numbers in the atmosphere decrease with distance traveled and offer a novel danger index for viable spore deposition in agricultural zones.
AOSbot

Title: Simplified Two-Dimensional Model for Global Atmospheric Dynamics.

We present a simplified model of the atmosphere of a terrestrial planet as an
open two-dimensional system described by an ideal gas with velocity $\vec{v}$,
density $\rho$ and temperature $T$ fields. Starting with the Chern-Simons
equations for a free inviscid fluid, the external effects of radiation and the
ex [...]

Authors: Martín Jacques-Coper, Valentina Ortiz, Jorge Zanelli

Link: arxiv.org/abs/2206.01158

arXiv.orgSimplified Two-Dimensional Model for Global Atmospheric DynamicsWe present a simplified model of the atmosphere of a terrestrial planet as an open two-dimensional system described by an ideal gas with velocity $\vec{v}$, density $ρ$ and temperature $T$ fields. Starting with the Chern-Simons equations for a free inviscid fluid, the external effects of radiation and the exchange of matter with the strata, as well as diffusion and dissipation are included. The resulting dynamics is governed by a set of nonlinear differential equations of first order in time. This defines an initial value problem that can be integrated given the radiation balance of the planet. If the nonlinearities are neglected, the integration can be done in analytic form using standard Green function methods, with small nonlinearities incorporated as perturbative corrections in a consistent way. If the nonlinear approximation is not justified, the problem can be integrated numerically. The analytic expressions as well as the simulations of the linear regime for a continuous range of parameters in the equations is provided, which allows to explore the response of the model to changes of those parameters. In particular, it is observed that a 2.5% reduction in the emissivity of the atmosphere can lead to an increase of 7C degrees in the average global temperature.
AOSbot

Title: Pyrocast: a Machine Learning Pipeline to Forecast Pyrocumulonimbus (PyroCb) Clouds.

Pyrocumulonimbus (pyroCb) clouds are storm clouds generated by extreme
wildfires. PyroCbs are associated with unpredictable, and therefore dangerous,
wildfire spread. They can also inject smoke particles and trace gas [...]

Authors: Kenza Tazi, Emiliano Díaz Salas-Porras, Ashwin Braude, Daniel Okoh, Kara D. Lamb, Duncan Watson-Parris, Paula Harder, Nis Meinert

Link: arxiv.org/abs/2211.13052

arXiv.orgPyrocast: a Machine Learning Pipeline to Forecast Pyrocumulonimbus (PyroCb) CloudsPyrocumulonimbus (pyroCb) clouds are storm clouds generated by extreme wildfires. PyroCbs are associated with unpredictable, and therefore dangerous, wildfire spread. They can also inject smoke particles and trace gases into the upper troposphere and lower stratosphere, affecting the Earth's climate. As global temperatures increase, these previously rare events are becoming more common. Being able to predict which fires are likely to generate pyroCb is therefore key to climate adaptation in wildfire-prone areas. This paper introduces Pyrocast, a pipeline for pyroCb analysis and forecasting. The pipeline's first two components, a pyroCb database and a pyroCb forecast model, are presented. The database brings together geostationary imagery and environmental data for over 148 pyroCb events across North America, Australia, and Russia between 2018 and 2022. Random Forests, Convolutional Neural Networks (CNNs), and CNNs pretrained with Auto-Encoders were tested to predict the generation of pyroCb for a given fire six hours in advance. The best model predicted pyroCb with an AUC of $0.90 \pm 0.04$.
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