Neural networks have long fascinated scientific communities, serving as an elegant approach to machine learning modelled on our understanding of the human brain. Their increasing sophistication has led to the near ubiquitous role of machine learning – from transportation management to medical diagnostics to the voice recognition powering virtual assistants. The expansive reliance on machine learning now calls for radical thinking to address the ever-greater demand for computational power and speed.
Plasmas, or ionized gases, are key to many modern applications and are used, for example, in the production of thin films, space propulsion, wound sterilization in medicine, and environmental depollution.
Plasma is one of the four fundamental states of matter and is by far the most abundant one in the universe. It is ionized gas and has several applications including space travel and more precisely space propulsion. While visiting the Stanford Plasma Physics Laboratory under the supervision of Professor Mark Cappelli, I will continue an ongoing project by operating a Hall thruster with air. This thruster displaces electron with a magnetic field to ionize the air creating a plasma. This formed air plasma is finally accelerated by an electric field.
Large variations in seasonal temperature and rainfall threaten crop production, food prices, and food security at local to global scales. This project focuses on the impacts of climate variability on Europe’s agricultural regions, with an emphasis on wheat in France. Although France has a relatively small agricultural area, it has among the highest wheat yields in the world. Climateinduced shocks to crop production thus influence global prices for wheat and other commodities linked to wheat through markets.
The goal of the Stanford Solar Observatories Group is to study the origin of solar variability, characterize and understand the Sun's interior and the various components of magnetic activity. To achieve this goal, data analysis is performed from space missions. For a better understanding of the Sun and predictive capabilities for solar activity and space weather, these observations have to be accompanied by realistic numerical simulations of the subsurface flows and magnetic structures of the Sun.
In developed countries about 80% of the total population suffers from acute and 5–10% from permanent lower back pain (LBP). An early diagnosis is crucial to reduce patient suffering and lower the economic burden on the society. In a representative study for the western world, the cost of LBP in Switzerland was estimated at 2.6 billion Euros in 2005. Nevertheless, surprisingly little is known about geometrical abnormalities resulting in LBP. This is in part due to the subtle distinction between healthy geometrical variability and pathological abnormal deformities of the spine.
Symbiosis is a close interaction between different species. The bacteria Wolbachia is the most common endosymbiont (a symbiont living within host cells) described to date. In mosquitoes, Wolbachia induces a form of sterility in crosses between males and females infected with distinct Wolbachia types. This feature makes Wolbachia infection a promising non-chemical tool to reduce human diseases transmitted by mosquitoes. However, the molecular basis of the Wolbachia-induced sterility is still unknown.
The need for chiral compounds has escalated tremendously in recent years as many biological activities, flavors or fragrances are associated with their absolute molecular configuration. In chemistry, chirality (derived from the Greek, "kheir" "hand") refers to molecules that cannot be superimposed on their own mirror images. Historically, chiral compounds were generated by chemical transformation of a chiral precursor obtained from nature's chiral pool.
With the widespread use of satellite imaging, a wealth of information is available to help in the understanding and modeling of earth system processes. In particular, these data play a key role in the analysis of climate variability. However, satellitebased retrievals present spatial discontinuities due to incomplete coverage of the domain resulting from satellite orbital characteristics, or through occlusion by cloud cover and other atmospheric effects. The straightforward use of Geostatistical prediction methods is made impossible by the wealth of the datasets at stake.