For years, Shaoping Wu was part of an increasingly endangered group of human rights lawyers in China.
His work culminated in 2019, when he attended a meeting with other prominent lawyers and activists.
Within days, the Chinese government began to detain the participants.
Mr. Wu quickly fled to the United States, where in 2020 he applied for asylum.
🔥On Wednesday, Mr. Wu was detained by Immigration and Customs Enforcement in Pennsylvania, where he had been living wit…
faculty_hiring_us: Faculty hiring networks in the US (2022)
Networks of faculty hiring for all PhD-granting US universities over the decade 2011–2020. Each node is a PhD-granting institution, and a directed edge (i,j) indicates that a person received their PhD from node i and was tenure-track faculty at node j during time of collection (2011-2020). This dataset is divided into separate networks for all 107 fields, as well as aggregate networks for 8 domains, and an overall network for …
In one post, according to the US Attorney’s Office,
former women's track and field coach Steven Waithe wrote:
“Does anyone want to trade nudes?
I’m talking girls you actually know. Could be exes or whatever.
I have quite a few and [am] down to trade over snap[chat] or something.”
Legal documents do not name the sites on which Waithe distributed these images,
but Bellingcat found a cached version of a November 2020 post with that exact wording on Leake…
Back in 2020 (which is when this pic is from), you could put your laptop in a plate of ketchup and it wasn't a big deal. These days, there goes your life savings.
Erinnert ihr euch noch, 2020 , als Masken für viele Teufelszeug waren? KI macht vieles möglich 🤣
from my link log —
Lezer: a parser system in JavaScript.
https://lezer.codemirror.net/
saved 2020-10-21 https://dotat.at/:/VL4WJ.html
Sergeant Damon Christopher Gutzwiller was a 14-year veteran of the Santa Cruz County Sheriff's Office in California.
He was killed in the line of duty on June 6, 2020, during an ambush by an armed suspect in Ben Lomond, California.
On the day of his death, he and other deputies responded to a report of a suspicious van containing firearms and bomb-making materials.
When officers tracked the vehicle to a home, they were immediately ambushed with gunfire and improvised…
#Bruttospeicherleistung von #Batteriespeichern nach Marktakteur in #Deutschland ab 2012 mit Stand vom 30.06.2026.
Betrachtet werden Datensätze mit Betriebsstatus „akti…
The Trump administration is waging war on voting rights using justice department lawsuits,
FBI investigations,
and an executive order to limit voting by mail,
-- moves mirroring the US president’s false claims he lost the 2020 election due to voting fraud, say election experts and ex-officials.
🔥Since Donald Trump began his second term, numerous 2020 election denialists have been installed in key agencies such as the DoJ, the FBI and elsewhere to pursue widely discred…
Late #ThursDeath this week, it's still Thursday here for a bit. This week is this unreal new DESECRESY record, 'The Secret of Death'. Supposed to be out today, now, should definitely be up by tomorrow, the 22nd, etc. But these 2 singles are great, and I heard the rest, it is too.
2010's tech bros: here's how I use chemicals so I never need to sleep again
2020's tech bros: here's how I use applied statistics so I never have to be awake again
Seeing Inside the Storm: Improving Nowcasting by Integrating Meteorological Drivers
Minghui Qiu, Jun Chen, Lin Chen, Weifeng Chen, Shuxin Zhong, Zhidan Liu, Yu Zhang, Kaishun Wu
https://arxiv.org/abs/2605.24067 https://arxiv.org/pdf/2605.24067 https://arxiv.org/html/2605.24067
arXiv:2605.24067v1 Announce Type: new
Abstract: Most nowcasting systems, built on radar reflectivity, focus on current precipitation, ignoring the atmospheric precursors -- such as low-level convergence, turbulent eddies, and latent heating -- that offer a fleeting window to foresee storm birth. We introduce MeteoLogist, a physics-inspired radar intelligence framework that models the full life cycle of convection -- from its precursors to organized storm evolution. However, exploiting these precursors is non-trivial: they originate from multiple meteorological drivers -- thermodynamic, kinematic, and microphysical -- that evolve asynchronously (C1) and remain spatially fragmented (C2). To this end, MeteoLogist designs three tightly integrated components. The Physics-Tailored Encoders process radar echoes according to their intrinsic physical scales and semantics, forming thermodynamic, kinematic, and microphysical streams that capture distinct dynamical regimes. The Temporal-Phase Aligner addresses C1 by leveraging causal temporal attention to capture when and how different drivers interact and activate. The Cross-Field Spatial Aggregator addresses C2 through cross-regional fusion, aligning weak and scattered precursors across neighboring cells to expose upstream triggers and enforce spatial coherence. Evaluated on 3D-NEXRAD (2020--2022, US-wide), MeteoLogist boosts high-impact detection (CSI40) by 9.7% over strong baselines, and achieves a remarkable 37.67% gain during the storm-developing stage -- demonstrating true foresight in sensing storms before they appear. The code can be found in the supplementary material.
toXiv_bot_toot
Donald Trump has received another setback in his ongoing quest to control U.S. elections.
In a 5-4 split, the Supreme Court ruled that mail-in ballots do not need to be received by Election Day to be counted,
as long as they were postmarked by then.
Although a “rare victory for voting rights,” the conservative justices’ assertion that voting by mail is prone to fraud
— a disproven theory that Trump blames his loss in the 2020 election for
— is “very disturbing…
Visibility nowcasting in South Korea: a machine learning approach to class imbalance and distribution shift
Bong Gyun Shin, Chan Sik Lee, Hyesun Suh
https://arxiv.org/abs/2605.21507 https://arxiv.org/pdf/2605.21507 https://arxiv.org/html/2605.21507
arXiv:2605.21507v1 Announce Type: new
Abstract: Atmospheric visibility is a critical variable for transportation safety and air quality management, however, accurate prediction remains challenging due to the complex interactions between meteorological conditions and air pollutants, as well as the rarity of low-visibility events. This study introduces a machine learning framework to nowcast visibility in six major South Korean cities. To handle the imbalance in the 2018-2020 training data, we applied the Synthetic Minority Over-sampling Technique with Nominal and Continuous (SMOTENC) and Conditional Tabular Generative Adversarial Network (CTGAN). An ensemble approach combining machine learning and deep learning models was then used and evaluated on a 2021 test dataset. The results revealed a marked decline in predictive performance in the test set compared to the cross-validation phase. This degradation was attributed to a distributional shift between training and testing periods, which was quantitatively confirmed by measuring the Wasserstein distance of the most influential feature identified by SHAP analysis. In general, this study presents a methodology that aims to simultaneously address the dual challenges of data imbalance and temporal distributional shifts, and emphasizes the necessity of accounting for evolving external environmental factors when implementing nowcasting models on time-series data.
toXiv_bot_toot
How much household stuff can you move across 8 states, 1600 miles, in a Chevy Sonic? 🚗
A lot as my wife and I established in Nov. 2020 at the height of COVID. 🗓️ #throwback
Anyway, sad to say goodbye to that car today. 🎁 #donation
#tbt #throwbackThursday #accomplishment
From Licensing to Open Access: Designing a Sustainable Transition in Operational Weather Data
Emma Pidduck, Umberto Modigliani, Victoria L. Bennett, Fabio Venuti, Florian Pappenberger, Florence Rabier
https://arxiv.org/abs/2605.21673 https://arxiv.org/pdf/2605.21673 https://arxiv.org/html/2605.21673
arXiv:2605.21673v1 Announce Type: new
Abstract: This translational article documents the European Centre for Medium-Range Weather Forecasts (ECMWF) transition from a restricted data licensing model to open access under CC BY 4.0, completed in October 2025. The policy context included EU open data requirements and alignment with international data exchange frameworks. The transition was implemented through a tiered service model that kept core forecast data open while offering operationally supported delivery as a cost-recovered service. Between 2020 and 2025, ECMWF executed an iterative planning cycle: setting an annual target for revenue reduction, specifying additions to the open tier under that target, provisioning infrastructure, and assessing outcomes to update assumptions. Drawing on internal administrative records (2014 - 2025), we describe design choices, operational constraints, and early outcomes. In the six months following the end of the transition, more than 93% of previously paying organisations retained a Service Agreement, while open endpoint download volumes increased substantially. We discuss trade-offs in defining the open tier (resolution, parameters, schedule), the reduction of compliance overheads formerly associated with redistribution restrictions, and the scalability implications of global distribution. We note an emerging sustainability question as AI-based forecast products become freely available. The early evidence is consistent with the view that a tiered service model can be designed to reconcile open-access obligations with operational sustainability, subject to monitoring over longer contract renewal cycles (typically annual).
toXiv_bot_toot
@cdarwin@c.im
