The first prototype of a photo-detection unit of the future KM3NeT neutrino telescope has been deployed in the deep waters of the Mediterranean Sea. This digital optical module has a novel design with a very large photocathode area segmented by the use of 31 three inch photomultiplier tubes. It has been integrated in the ANTARES detector for in-situ testing and validation. This paper reports on the first months of data taking and rate measurements. The analysis results highlight the capabilities of the new module design in terms of background suppression and signal recognition. The directionality of the optical module enables the recognition of multiple Cherenkov photons from the same 40 K decay and the localisation of bioluminescent activity in the neighbourhood. The single unit can cleanly identify atmospheric muons and provide sensitivity to the muon arrival directions. a

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A prototype detection unit of the KM3NeT deepsea neutrino telescope has been installed at 3500m depth 80 km offshore the Italian coast. KM3NeT in its final configuration will contain several hundreds of detection units. Each detection unit is a mechanical structure anchored to the sea floor, held vertical by a submerged buoy and supporting optical modules for the detection of Cherenkov light emitted by charged secondary particles emerging from neutrino interactions. This prototype string implements three optical modules with 31 photomultiplier tubes each. These optical modules were developed by the KM3NeT Collaboration to enhance the detection capability of neutrino interactions. The prototype detection unit was operated since its deployment in May 2014 until its decommissioning in July 2015. Reconstruction of the particle trajectories from the data requiresThe research leading to these results has received funding from the European Community Sixth Framework Programme under Contract 011937 and the Seventh Framework Programme under Grant Agreement 212525. a e-mail: simone.biagi@bo.infn.it b e-mail: creusot@apc.in2p3.fr c e-mail: dosamt@nikhef.nl d Also at Accademia Navale di Livorno, Livorno, Italy a nanosecond accuracy in the time calibration. A procedure for relative time calibration of the photomultiplier tubes contained in each optical module is described. This procedure is based on the measured coincidences produced in the sea by the 40 K background light and can easily be expanded to a detector with several thousands of optical modules. The time offsets between the different optical modules are obtained using LED nanobeacons mounted inside them. A set of data corresponding to 600 h of livetime was analysed. The results show good agreement with Monte Carlo simulations of the expected optical background and the signal from atmospheric muons. An almost background-free sample of muons was selected by filtering the time correlated signals on all the three optical modules. The zenith angle of the selected muons was reconstructed with a precision of about 3 • .

Affinity-type silicon-based nanowire biosensors rely on the biochemical interaction between target molecules and their molecular complements (recognition probes), located on the SiO2 insulator layer. This biochemical reaction is associated with twofold fluctuations through the mechanisms of binding/unbinding and regular charge thermal equilibrium processes. These fluctuations have a direct implication on the surface potential fluctuations which in turn affect, through the field effect transduction process, the electrical characteristics of the sensor device. The resulting noise could potentially contain detectable information, which can be extracted through the time constants (characteristic frequencies) related to the kinetics of the molecules under detection and their charge fluctuations. In this work, we present a comprehensive model for the fluctuations on the surface of the biosensor and attribute them to the two physical mechanisms. The spectral densities corresponding to these types of fluctuations add on the overall device noise spectrum and are directly detectable if they lie above the inherent noise level of the sensor device.

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