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Datenschutzgutachten zum Praxisregister Schmerz offenbart fragwürdige Praktiken
Das Netzwerk Datenschutzexpertise übt scharfe Kritik am Praxisregister Schmerz. Daten würden intransparent fragwürdigen Auswertungen der Pharmaindustrie dienen.

About BB6 BAND
I live in my own little world, but it's OK. They know me here. And sometimes dreams do come true.
Red China Blues
#bb6Band

Red China Blues BB6 BAND
A version of Miles Davis' Red China Blues with lyrics to suit the title.

EANS: Reducing Energy Consumption for UAV with an Environmental Adaptive Navigation Strategy
Tian Liu, Han Liu, Boyang Li, Long Chen, Kai Huang
https://arxiv.org/abs/2506.20485

EANS: Reducing Energy Consumption for UAV with an Environmental Adaptive Navigation Strategy
Unmanned Aerial Vehicles (UAVS) are limited by the onboard energy. Refinement of the navigation strategy directly affects both the flight velocity and the trajectory based on the adjustment of key parameters in the UAVS pipeline, thus reducing energy consumption. However, existing techniques tend to adopt static and conservative strategies in dynamic scenarios, leading to inefficient energy reduction. Dynamically adjusting the navigation strategy requires overcoming the challenges including the…

sunset, n.:
Pronounced atmospheric scattering of shorter wavelengths,
resulting in selective transmission below 650 nanometers with
progressively reducing solar elevation.

Every company or government should think about this, prepare exit and contingency plans. Also for other dependencies.
https://www.theregister.com/2025/06/26/cost_of_microsoft_dependency/

What if Microsoft just turned you off? Security pro counts the cost of dependency
Comment: Czech researcher lays out a business case for reducing reliance on Redmond

Accept More, Reject Less: Reducing up to 19% Unnecessary Desk-Rejections over 11 Years of ICLR Data
Xiaoyu Li, Zhao Song, Jiahao Zhang
https://arxiv.org/abs/2506.20141

Accept More, Reject Less: Reducing up to 19% Unnecessary Desk-Rejections over 11 Years of ICLR Data
The explosive growth of AI research has driven paper submissions at flagship AI conferences to unprecedented levels, necessitating many venues in 2025 (e.g., CVPR, ICCV, KDD, AAAI, IJCAI, WSDM) to enforce strict per-author submission limits and to desk-reject any excess papers by simple ID order. While this policy helps reduce reviewer workload, it may unintentionally discard valuable papers and penalize authors' efforts. In this paper, we ask an essential research question on whether it is pos…

Reducing Self-Interaction Error in Transition-Metal Oxides with Different Exact-Exchange Fractions for Energy and Density
Harshan Reddy Gopidi, Ruiqi Zhang, Yanyong Wang, Abhirup Patra, Jianwei Sun, Adrienn Ruzsinszky, John P. Perdew, Pieremanuele Canepa
https://arxiv.org/abs/2506.20635 …

Reducing Self-Interaction Error in Transition-Metal Oxides with Different Exact-Exchange Fractions for Energy and Density
DFT is vital for materials discovery, and at the base of extensive molecular and materials databases, chemical reaction predictions, and machine learning potentials. The widespread use of DFT in chemistry and materials science aims for "chemical accuracy," but this is limited by the unknown exchange and correlation (XC) functional. A meta-GGA, the restored regularized strongly constrained and appropriately normed, r r2SCAN XC functional, fulfils 17 exact constraints of the XC energy. r2SCAN sti…

Teile des Malerweges verlaufen durch dichten Wald oder #Schluchten. Selbst bei 30 Grad ist es dort angenehm kühl. Es ist dennoch ratsam, an heißen Tagen zeitig mit der Tour zu starten.
Übrigens, #Wanderroutentipps in diesem Bundesland mit GPX-Track findet Ihr über

🇺🇦 #NowPlaying on KEXP's #MiddayShow
Boy Deluxe:
🎵 PUSH THE PAIN
#BoyDeluxe
https://boydeluxe.bandcamp.com/track/push-the-pain
https://open.spotify.com/track/1R8YATJiM2Dg6bAFnXu7Kf

Extracting Interpretable Models from Tree Ensembles: Computational and Statistical Perspectives
Brian Liu, Rahul Mazumder, Peter Radchenko
https://arxiv.org/abs/2506.20114

Extracting Interpretable Models from Tree Ensembles: Computational and Statistical Perspectives
Tree ensembles are non-parametric methods widely recognized for their accuracy and ability to capture complex interactions. While these models excel at prediction, they are difficult to interpret and may fail to uncover useful relationships in the data. We propose an estimator to extract compact sets of decision rules from tree ensembles. The extracted models are accurate and can be manually examined to reveal relationships between the predictors and the response. A key novelty of our estimator…