We present first significant limits on WIMP dark matter by the phonon-light technique, where combined phonon and light signals from a scintillating cryogenic detector are used. Data from early 2004 with two 300 g CRESST-II prototype detector modules are presented, with a net exposure of 20.5 kg days. The modules consist of a CaWO 4 scintillating "target" crystal and a smaller cryogenic light detector. The combination of phonon and light signals leads to a strong suppression of non-nuclear recoil backgrounds. Using this information to define an acceptance region for nuclear recoils we have 16 events from the two modules, corresponding to a rate for nuclear recoils between 12 and 40 keV of (0.87± 0.22) events/(kg day). This is compatible with the rate expected from neutron background, and most of these events lie in the region of the phonon-light plane anticipated for neutron-induced recoils. A particularly strong limit for WIMPs with coherent scattering results from selecting a region of the phonon-light plane corresponding to tungsten recoils, where the best module shows zero events.

The described method enables MR to pseudo-CT image conversion for the head in an accurate, robust, and fast manner without relying on anatomical prior knowledge. Potential applications include PET/MR-AC, and MR-guided RTP.

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In the early stages of running of the CRESST dark matter search using sapphire detectors at very low temperature, an unexpectedly high rate of signal pulses appeared. Their origin was finally traced to fracture events in the sapphire due to the very tight clamping of the detectors. During extensive runs the energy and time of each event was recorded, providing large data sets for such phenomena. We believe this is the first time the energy release in fracture has been directly and accurately measured on a microscopic event-by-event basis. The energy threshold corresponds to the breaking of only a few hundred covalent bonds, a sensitivity some orders of magnitude greater than that of previous technique.We report some features of the data, including energy distributions, waiting time distributions, autocorrelations and the Hurst exponent. The energy distribution appear to follow a power law, dN/dE ∝ E −β , similar to the power law for earthquake magnitudes, and after appropriate translation, with a similar exponent. In the time domain, the waiting time w or gap distribution between events has a power law behavior at small w and an exponential fall-off at large w, and can be fit ∝ w −α e −w/w 0 . The autocorrelation function shows time correlations lasting for substantial parts of an hour. An asymmetry is found around large events, with higher count rates after, as opposed to before, the large event .