Scott Bessent was code-named “Sterling” in leaked emails between Jeffrey Epstein’s business partner and George Soros’s hedge fund.Nobody is talking about this while he tanks our economy, so I will — theleahfiles

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Archaeologists investigate a feared young woman’s 17th century vampiric grave in Poland

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CIA Director John Ratcliffe Visited Moscow

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How much sleep do I need? Why you can forget the eight‑hour rule

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The Hellenistic Origin of the Torah: A Review of Russell Gmirkin’s Books — Laurent Guyénot

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US set for largest mass visa revocation in history targeting up to 200,000 foreigners, officials say

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Supreme Court Lifts District Court Injunction Permitting Trump Administration to Move Forward on Postal Voting Plan

Today the Supreme Court ruled 6-3 [RULING HERE] that lifted one of the lower court injunctions that was filed as a lawsuit in Massachusetts. The court ruled that Boston-based Judge Indira Talwani (Obama appointee) engaged in “a string of speculations to find this suit justiciable.”

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Stress limits speech so much, the obvious is often shrouded

Nonconscious brain patterns can be modified through rewards

…In Decoded Neurofeedback experiments, brain scanning is used to monitor activity in the brain, and identify complex patterns of activity that resemble a specific memory or mental state. When the pattern is detected, we give our experimental participants a small reward. The simple action of repeatedly providing a reward every time the pattern is detected modifies the original memory or mental state. Importantly, participants do not need to be aware of the patterns’ content for this to work.

Nonconscious brain modulation to remove fears, increase confidence

Study: Differential Activation Patterns in the Same Brain Region Led to Opposite Emotional States

Mind captioning: Evolving descriptive text of mental content from human brain activity

…Fig. 2. Generating viewed content descriptions.

Descriptions were generated using features from all LM layers decoded from whole-brain activity. (A) Evolved descriptions during the optimization (see https://horikawa-t.github.io/MindCaptioningProject/ for more results with the original videos). (B) Descriptions after 100 iterations for all subjects (see fig. S3A for more example). In (A) and (B), the color indicates accuracy [inverse document frequency (IDF)–weighted BERTScore-P]. A reference caption of the video is shown below frames. (C) Feature correlations between features of generated descriptions and those decoded from the brain, as well as those computed from correct references. (D) Cohen’s d of discriminability (see fig. S4B for raw scores). Feat. corr., Feature correlation. (E) Video identification accuracy with varying numbers of candidates. (F) Effects of word-order shuffling on video identification accuracy and discriminability. (G) Scatterplot of the correlation distances (one minus feature correlation) between the original and shuffled descriptions against the difference in feature correlations to target features between original and shuffled descriptions. Each dot indicates a shuffled description. Shades in (C) and (E) and error bars in (D) and (F) indicate 95% confidence intervals (CIs) across samples (n = 72). Shades in (D) and (F) indicate 95% CI across subjects (n = 6). See fig. S4 for individual results.

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Survival of the wittiest (not friendliest): The art and science behind human linguistic and cognitive evolution

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Iryna Zarutska’s family files lawsuit against the City of Charlotte for alleged ‘systemic failures’ 

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