The physics programme and the design are described of a new collider for particle and nuclear physics, the Large Hadron Electron Collider (LHeC), in which a newly built electron beam of 60 GeV, to possibly 140 GeV, energy collides with the intense hadron beams of the LHC. Compared to the first ep collider, HERA, the kinematic range covered is extended by a factor of twenty in the negative four-momentum squared, Q 2 , and in the inverse Bjorken x, while with the design luminosity of 10 33 cm −2 s −1 the LHeC is projected to exceed the integrated HERA luminosity by two orders of magnitude. The physics programme is devoted to an exploration of the energy frontier, complementing the LHC and its discovery potential for physics beyond the Standard Model with high precision deep inelastic scattering measurements. These are designed to investigate a variety of fundamental questions in strong and electroweak interactions. The LHeC thus continues the path of deep inelastic scattering (DIS) into unknown areas of physics and kinematics. The physics programme also includes electron-deuteron and electron-ion scattering in a (Q 2 1/x) range extended by four orders of magnitude as compared to previous lepton-nucleus DIS experiments for novel investigations of neutron's and nuclear structure, the initial conditions of Quark-Gluon Plasma formation and further quantum chromodynamic phenomena. The LHeC may be realised either as a ring-ring or as a linac-ring collider. Optics and beam dynamics studies are presented for both versions, along with technical design considerations on the interaction region, magnets including new dipole prototypes, cryogenics, RF, and further components. A design study is also presented of a detector suitable to perform high precision DIS measurements in a wide range of acceptance using state-ofthe art detector technology, which is modular and of limited size enabling its fast installation. The detector includes tagging devices for electron, photon, proton and neutron detection near to the beam pipe. Civil engineering and installation studies are presented for the accelerator and the detector. The LHeC can be built within a decade and thus be operated while the LHC runs in its high-luminosity phase. It so represents a major opportunity for progress in particle physics exploiting the investment made in the LHC.

Microorganisms, such as bacteria, which might be present as contamination inside an industrial food or pharmaceutical clean room process need to be identified on short time scales in order to minimize possible health hazards as well as production downtimes causing financial deficits. Here we describe the first results of single-particle micro-Raman measurements in combination with a classification method, the so-called support vector machine technique, allowing for a fast, reliable, and nondestructive online identification method for single bacteria.

Microbial contamination is not only a medical problem, but also plays a large role in pharmaceutical clean room production and food processing technology. Therefore many techniques were developed to achieve differentiation and identification of microorganisms. Among these methods vibrational spectroscopic techniques (IR, Raman and SERS) are useful tools because of their rapidity and sensitivity. Recently we have shown that micro-Raman spectroscopy in combination with a support vector machine is an extremely capable approach for a fast and reliable, non-destructive online identification of single bacteria belonging to different genera. In order to simulate different environmental conditions we analyzed in this contribution different Staphylococcus strains with varying cultivation conditions in order to evaluate our method with a reliable dataset. First, micro-Raman spectra of the bulk material and single bacterial cells that were grown under the same conditions were recorded and used separately for a distinct chemotaxonomic classification of the strains. Furthermore Raman spectra were recorded from single bacterial cells that were cultured under various conditions to study the influence of cultivation on the discrimination ability. This dataset was analyzed both with a hierarchical cluster analysis (HCA) and a support vector machine (SVM).

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Precise three-dimensional (3D) mapping of a large number of gene expression patterns, neuronal types and connections to an anatomical reference helps us to understand the vertebrate brain and its development. We developed the Virtual Brain Explorer (ViBE-Z), a software that automatically maps gene expression data with cellular resolution to a 3D standard larval zebrafish (Danio rerio) brain. ViBE-Z enhances the data quality through fusion and attenuation correction of multiple confocal microscope stacks per specimen and uses a fluorescent stain of cell nuclei for image registration. It automatically detects 14 predefined anatomical landmarks for aligning new data with the reference brain. ViBE-Z performs colocalization analysis in expression databases for anatomical domains or subdomains defined by any specific pattern; here we demonstrate its utility for mapping neurons of the dopaminergic system. The ViBE-Z database, atlas and software are provided via a web interface.