Nepo-baby Mayor Lurie has launched his website promoting his executive power grab.
And it prominently features coverage from the SF Standard - the outlet funded/created by billionaire Michael Moritz, who has also donated $2 million to the measures.
This is the new billionaire playbook: parallel media they control to support their anti-worker agenda.
🇺🇦 #NowPlaying on KEXP's #AfternoonShow
The Orb:
🎵 Little Fluffy Clouds
#TheOrb
https://stateazure.bandcamp.com/track/the-orb-little-fluffy-clouds-less-fluff-mix
https://open.spotify.com/track/7FVvHGA46aU7mkwx4iHMRE
Trump says the US will initiate a probe into the EU's practice of "robbing" US tech giants with fines, threatening the bloc with "substantial" tariffs (Kevin Breuninger/CNBC)
https://www.cnbc.com/2026/07/24/trump-tariffs-eu-trade-google-a…
🇺🇦 #NowPlaying on BBCRadio3's #InTune
Einojuhani Rautavaara, Kalevi Aho, Robert Treviño & Malmö SymfoniOrkester:
🎵 2 Sérénades (Arr. K. Aho for Violin & Orchestra): No. 1, Sérénade pour mon amour
#KaleviAho
https://open.spotify.com/track/5YNcetmADK1Pn3cBFtCoRU
So the country with a gigantic prison-industrial forced-labour workforce will now charge other countries an import tariff due to their supposed forced labour practices?
Trump accused of using forced labor as ‘convenient’ justification for tariffs | Trump tariffs | The Guardian
https://www.t…
Magnetic resonance imaging assessment of the suitability and consistency of radiotherapy treatment positioning achieved using intra-oral stents
Tanya Kairn (Royal Brisbane and Women's Hospital, Brisbane Qld, Australia, University of Queensland, Brisbane Qld, Australia, Queensland University of Technology, Brisbane Qld, Australia), Philip Chan (Royal Brisbane and Women's Hospital, Brisbane Qld, Australia, University of Queensland, Brisbane Qld, Australia), Benjamin Chua (Royal Brisbane and Women's Hospital, Brisbane Qld, Australia, University of Queensland, Brisbane Qld, Australia), Susannah Cleland (Royal Brisbane and Women's Hospital, Brisbane Qld, Australia, Herston Biofabrication Institute, Metro North Hospital and Health Service, Brisbane Qld, Australia), Jodi Dawes (Royal Brisbane and Women's Hospital, Brisbane Qld, Australia), Lizbeth Kenny (Royal Brisbane and Women's Hospital, Brisbane Qld, Australia, University of Queensland, Brisbane Qld, Australia), Charles Y. Lin (Royal Brisbane and Women's Hospital, Brisbane Qld, Australia, University of Queensland, Brisbane Qld, Australia), William R. McDowall (Royal Brisbane and Women's Hospital, Brisbane Qld, Australia), Tania Poroa (Royal Brisbane and Women's Hospital, Brisbane Qld, Australia, Herston Biofabrication Institute, Metro North Hospital and Health Service, Brisbane Qld, Australia), Scott B. Crowe (Royal Brisbane and Women's Hospital, Brisbane Qld, Australia, University of Queensland, Brisbane Qld, Australia, Queensland University of Technology, Brisbane Qld, Australia, Herston Biofabrication Institute, Metro North Hospital and Health Service, Brisbane Qld, Australia)
https://arxiv.org/abs/2606.25210 https://arxiv.org/pdf/2606.25210 https://arxiv.org/html/2606.25210
arXiv:2606.25210v1 Announce Type: new
Abstract: As head-and-neck radiotherapy treatments grow more complex and precise, it becomes increasingly important to assess the anatomical separations that can be achieved using intra-oral stents. A series of twenty T2-weighted turbo spin echo magnetic resonance images (MRI) were acquired of one healthy participant, with a range of different wax and 3D printed intra-oral stents in situ. The resulting measurements showed that a 3D printed modular stent containing hard polylactic acid (PLA) and flexible thermoplastic polyurethane (TPU) components made the largest and most reproducible separation between the cheeks (70.8 /- 0.3 mm), two hard PLA stents designed to exactly fit the participant's teeth produced the poorest positioning reproducibility (standard deviations of up to 3 mm between a range of landmarks measured in repeated images). Most stents were described as ``comfortable'' although the wax stents left small pieces of wax attached to the teeth after use. This MRI based comparison demonstrated that the materials and designs used for intra-oral stents can have substantial effects on the level of anatomical separation and positioning reproducibility that they produce.
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Deepfake News Detection: A Multimodal Framework Integrating LipNet, DeepSpeech and ResNET for Enhanced Audio-Visual Analysis
Ameena Khan, Muhammad Ahsan Aziz, Muhammad Junaid Asif, Naeem Akhter, Rana Fayyaz Ahmad
https://arxiv.org/abs/2607.20579 https://arxiv.org/pdf/2607.20579 https://arxiv.org/html/2607.20579
arXiv:2607.20579v1 Announce Type: new
Abstract: Deepfake news refers to AI-generated (or AI ma-nipulated) multimedia content intentionally generated to deceive audiences by manipulating the facial expressions, or speech while maintaining the realistic appearance. The rapid progress of generative AI has made the synthesis of highly realistic fake videos and cloned voices widely accessible, posing a serious threat to the authenticity of digital news media. This paper presents a multi-modal framework that discerns the authenticity of video content by jointly exploiting audio and visual cues, thereby addressing the challenge of detecting the deepfake videos. We proposed a framework that involves features extraction from lip movements, audio content and video frames. Lip movements and speech content are encoded using the LipNet and DeepSpeech2 models, while facial features are extracted by leveraging the use of BlazeFace and represented with ResNet18. The extracted feature vectors are concatenated into a holistic video representation and classified with an ensemble of machine learning and deep learning models, including Random Forest (RF), Multi-layer Perceptron (MLP) and Long Short-Term Memory (LSTM) networks. Exten-sive experiments performed on the FakeAVCeleb dataset shows that the proposed approach attains an accuracy of 94% using augmented audio features, outperforming a state-of-the-art multi-modal ensemble baseline. The results confirm the robustness and practical potential of the proposed framework for deepfake news detection.
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