Lifeboat Foundation

Elon Musk is using what Tesla knows about self-dr…’

Future batteries could charge up by relying on a quantum effect known as indefinite causal order, whereby the laws of cause and effect are scrambled and power can move through the system quicker.

Scientists may have found a more efficient water to desalinate water using solar power, according to new research, offering a solution for global water scarcity through the use of renewable energy.

Researchers at Nankai University in Tianjin, China, developed the concept of a solar-powered desalination system that produces fresh water by using smart DNA hydrogels that does not consume additional energy, compared to conventional desalination strategies currently in use, such as reverse osmosis, which use copious amounts of energy, according to a paper published in the journal Science Advances on Thursday.

The same process can be used simultaneously to extract uranium from seawater or treat uranyl containing nuclear wastewater, the researchers said.

It’s another reminder to always search through that museum drawer.

When it comes to delivering drugs to the body, a major challenge is ensuring that they remain in the area they’re treating and continuing to deliver their payload accurately. While major strides have been made in delivering drugs, monitoring them is a challenge that often requires invasive procedures like biopsies.

Researchers at NYU Tandon led by Jin Kim Montclare, Professor of Chemical and Biomolecular Engineering, have developed proteins that can assemble themselves into fibers to be used as therapeutic agents for the potential treatments of multiple diseases.

These biomaterials can encapsulate and deliver therapeutics for a host of diseases. But while Montclare’s lab has long worked on producing these materials, there was once a challenge that was hard to overcome—how to make sure that these proteins continued to deliver their therapeutics at the correct location in the body for the necessary amount of time.

A recent study by Carnegie Mellon University (CMU) shows that Google’s latest large language model, Gemini Pro, lags behind GPT-3.5 and far behind GPT-4 in benchmarks.

The results contradict the information provided by Google at the Gemini presentation. They highlight the need for neutral benchmarking institutions or processes.

Gemini Pro loses out to GPT-3.5 in benchmarks.

A non-organic intelligent system has for the first time designed, planned and executed a chemistry experiment, Carnegie Mellon University researchers report in the journal Nature (“Autonomous chemical research with large language models”).

I dont know about sleep weapons, it s possible probably. More concerning to me, i read a paper 20+ years back about cell towers and cell phone frequencies as a possible tool for mind control, some way connected to frequency of human brain.

China’s military is developing advanced psychological warfare and brain-influencing weapons as part of a new warfighting strategy, according to a report on People’s Liberation Army cognitive warfare.

The report, “Warfare in the Cognitive Age: NeuroStrike and the PLA’s Advanced Psychological Weapons and Tactics,” was published earlier this month by The CCP Biothreats Initiative, a research group.

Continue reading “Chinese brain warfare includes sleep weapons, thought control” »

The delivery of drugs to specific target tissues and cells in the brain poses a significant challenge in brain therapeutics, primarily due to limited understanding of how nanoparticle (NP) properties influence drug biodistribution and off-target organ accumulation. This study addresses the limitations of previous research by using various predictive models based on collection of large data sets of 403 data points incorporating both numerical and categorical features. Machine learning techniques and comprehensive literature data analysis were used to develop models for predicting NP delivery to the brain. Furthermore, the physicochemical properties of loaded drugs and NPs were analyzed through a systematic analysis of pharmacodynamic parameters such as plasma area under the curve. The analysis employed various linear models, with a particular emphasis on linear mixed-effect models (LMEMs) that demonstrated exceptional accuracy. The model was validated via the preparation and administration of two distinct NP formulations via the intranasal and intravenous routes. Among the various modeling approaches, LMEMs exhibited superior performance in capturing underlying patterns. Factors such as the release rate and molecular weight had a negative impact on brain targeting. The model also suggests a slightly positive impact on brain targeting when the drug is a P-glycoprotein substrate.