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Spectral Line Shapes in Astrophysics
The VI Serbian Conference on Spectral Line Shapes in Astrophysics was about the investigation of spectral line shapes in extragalactic objects, such as, active galactic nuclei, stellar atmospheres, and astrophysical spectra in general. Atomic spectral line shapes in various discharges and plasma devices was also discussed. The main purpose of the Conference was to present and discuss new results found by participants working in this research field, and to review significant topics.
Machine Learning in Chemistry
Recent advances in machine learning or artificial intelligence for vision and natural language processing that have enabled the development of new technologies such as personal assistants or self-driving cars have brought machine learning and artificial intelligence to the forefront of popular culture. The accumulation of these algorithmic advances along with the increasing availability of large data sets and readily available high performance computing has played an important role in bringing machine learning applications to such a wide range of disciplines. Given the emphasis in the chemical sciences on the relationship between structure and function, whether in biochemistry or in materials chemistry, adoption of machine learning by chemistsderivations where they are important
Creature
A powerful high-tech company. A postcard-pretty company town. Families. Children. Sunshine. Happiness. A high school football team that never-ever loses. And something else. Something horrible ... Now, there is a new family in town. A shy, nature-loving teenager. A new hometown. A new set of bullies. Maybe the team's sports clinic can help him. Rebuild him. They won't hurt him again. They won't dare.
Diamondoids
Over the past few decades, carbon nanomaterials, most commonly fullerenes, carbon nanotubes, and graphene, have gained increasing interest in both science and industry, due to their advantageous properties that make them attractive for many applications in nanotechnology. Another class of the carbon nanomaterials family that has slowly been gaining (re)newed interest is diamond molecules, also called diamondoids, which consist of polycyclic carbon cages that can be superimposed on a cubic diamond lattice. Derivatives of diamondoids are used in pharmaceutics, but due to their promising properties—well-defined structures, high thermal and chemical stability, negative electron affinity, and t...
Supervised Learning with Quantum Computers
Quantum machine learning investigates how quantum computers can be used for data-driven prediction and decision making. The books summarises and conceptualises ideas of this relatively young discipline for an audience of computer scientists and physicists from a graduate level upwards. It aims at providing a starting point for those new to the field, showcasing a toy example of a quantum machine learning algorithm and providing a detailed introduction of the two parent disciplines. For more advanced readers, the book discusses topics such as data encoding into quantum states, quantum algorithms and routines for inference and optimisation, as well as the construction and analysis of genuine ``quantum learning models''. A special focus lies on supervised learning, and applications for near-term quantum devices.
