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Tokamak fusion plasmas benefit from high pressures but are then susceptible to modes of instability. These magnetohydrodynamic (MHD) modes are macroscopic distortions of the plasma, but certain collective motions of individual particles can provide stabilizing effects opposing them. The presence of a resistive wall slows the mode growth, converting a kink to a resistive wall mode (RWM). A kinetic MHD model includes Maxwell’s equations, ideal MHD constraints, and kinetic effects included through the pressure tensor, calculated with the perturbed drift-kinetic distribution function of the particles. The kinetic stabilizing effects on the RWM arise through resonances between the plasma rotation and particle drift motions: precession, bounce, and transit. A match between particle motions and the mode allows efficient transfer of energy that would otherwise drive the growth of the mode, thus damping the growth. The first approach to calculating RWM stability is to write a set of equations for the complex mode frequency in terms of known quantities and then to solve the system. The “energy principle” approach, which has the advantage of clarity in distinguishing the various stabilizing and destabilizing effects, is to change the force balance equation into an equation in terms of changes of kinetic and potential energies, and then to write a dispersion relation for the mode frequency in terms of those quantities. These methods have been used in various benchmarked codes to calculate kinetic effects on RWM stability. The theory has illuminated the important roles of plasma rotation, energetic particles, and collisions in RWM stability.

Multiple sclerosis (MS) is a neurological disease that usually leads to permanent disabilities. It affects about 2.9 million people worldwide, and about 15,000 in Switzerland alone. One key feature of the disease is that it causes the patient’s own immune system to attack and destroy the myelin sheaths in the central nervous system.

These protective sheaths insulate the nerve fibers, much like the plastic coating around a copper wire. Myelin sheaths ensure that electrical impulses travel quickly and efficiently from nerve cell to nerve cell. If they are damaged or become thinner, this can lead to irreversible visual, speech and coordination disorders.

So far, however, it hasn’t been possible to visualize the myelin sheaths well enough to reliably diagnose and treat MS. Now researchers at ETH Zurich, led by Markus Weiger and Emily Baadsvik from the Institute for Biomedical Engineering, have developed a new magnetic resonance imaging (MRI) procedure that maps the condition of the myelin sheaths more accurately than was previously possible. The researchers successfully tested the procedure on healthy people for the first time.

We’re crawling with microbes, and scientists want to use them to treat disease.

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Shots enter early clinical trials for healthy people at high risk for disease.

Multifocal Choroiditis (MFC) patients with inflammatory choroidal neovascularization (iCNV) face challenges in visual and treatment outcomes. A recently published study delves into the effectiveness of Immunomodulatory Therapy (IMT) compared to an approach using steroids as needed, shedding light on visual and treatment outcomes. This study was published in the American Journal of Ophthalmology by Matteo Airaldi and colleagues.

Elon Musk said Neuralink’s first patient was recovering well after being implanted with a product called Telepathy.

Norway’s tiny NorSat-TD satellite has made its first contact with Earth from LEO using its innovative laser communications payload.

Research conducted by a team of scientists from Kaunas universities, Lithuania, revealed that low-frequency ultrasound influences blood parameters. The findings suggest that ultrasound’s effect on haemoglobin can improve oxygen’s transfer from the lungs to bodily tissues.

The research was undertaken on 300 blood samples collected from 42 pulmonary patients. The samples were exposed to six different low-frequency ultrasound modes at the Institute of Mechatronics of Kaunas University of Technology (KTU).

The changes in 20 blood parameters were registered using the blood analysing equipment at the Lithuanian University of Health Sciences (LSMU) laboratories. For the prediction of ultrasound exposure, artificial intelligence, i.e. analysis of variance (ANOVA), non-parametric Kruskal-Wallis method and machine learning algorithms were applied. The calculations were made at the KTU Artificial Intelligence Centre.