OBJECTIVE The authors investigated the effects of recently identified genome-wide significant schizophrenia genetic risk variants on cognition and brain structure. METHOD A panel of six single-nucleotide polymorphisms (SNPs) was selected to represent genome-wide significant loci from three recent genome-wide association studies (GWAS) for schizophrenia and was tested for association with cognitive measures in 346 patients with schizophrenia and 2,342 healthy comparison subjects. Nominally significant results were evaluated for replication in an independent case-control sample. For SNPs showing evidence of association with cognition, associations with brain structural volumes were investigated in a large independent healthy comparison sample. RESULTS Five of the six SNPs showed no significant association with any cognitive measure. One marker in the major histocompatibility complex (MHC) region, rs6904071, showed independent, replicated evidence of association with delayed episodic memory and was significant when both samples were combined. In the combined sample of up to 3,100 individuals, this SNP was associated with widespread effects across cognitive domains, although these additional associations were no longer significant after adjusting for delayed episodic memory. In the large independent structural imaging sample, the same SNP was also associated with decreased hippocampal volume. CONCLUSIONS The authors identified a SNP in the MHC region that was associated with cognitive performance in patients with schizophrenia and healthy comparison subjects. This SNP, rs6904071, showed a replicated association with episodic memory and hippocampal volume. These findings implicate the MHC region in hippocampal structure and functioning, consistent with the role of MHC proteins in synaptic development and function. Follow-up of these results has the potential to provide insights into the pathophysiology of schizophrenia and cognition.

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The target of the research activity presented in this paper is to design, to realize and to test an autonomous sensor node\ud able to measure the accelerations in correspondence of the axle box of a freight train. The final goal of the sensor is to\ud identify the derailment conditions by observing the variations in the spectra of the box accelerations, around the\ud frequencies associated to the wheel revolution and its multiples.\ud The sensor node embeds an accelerometer, a microprocessor, a transmission system, a piezoelectric bimorph energy\ud harvester and an integrated circuit for managing the power distribution to each component of the node.\ud In particular, a mechanical filter to be applied to the node was specifically designed to increment the energy recovered by\ud the harvester and to filter out the high frequency components of the axle-box acceleration, allowing the use of a more\ud sensitive accelerometer. The harvesting system was setup by means of laboratory tests carried out with an\ud electromechanical shaker and the sensor node was finally tested through field tests on freight trains

The aim of active vibration control is to enhance the performance of a system (eg. comfort, fatigue life, etc.) by limiting vibrations. One of the most effective technique to reach this goal is to increase the equivalent damping of the system and then the dissipation of the kinetic energy (the so called skyhook damping technique). Application of active vibration control often require a complex setup. When large structures are considered, it is often necessary to have a high number of sensors and actuators, suitably cabled, in addition to all the devices necessary to condition and amplify the signals of measurement and control and to execute in real time the control algorithms synthesized. This work arises from the need to simplify this situation, developing a standalone device that is able of carrying out operations of vibration control in an autonomous way, thus containing in itself an actuator, the sensors needed to evaluate the vibratory state of the structure, and a micro-controller embedding different control algorithm. The design of the smart damper covers many aspects and requires a strong integration of different disciplines. A prototype has been realized and tested on a vibrating structure. The experimental results show good performance in suppress vibration

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