A neural network based technique for short-term forecasting of anomalous load periods

The paper illustrates a part of the research activity conducted by authors in the field of electric Short Term Load Forecasting (STLF) based on Artificial Neural Network (ANN) architectures. Previous experiences with basic ANN architectures have shown that, even though these architectures provide results comparable with those obtained by human operators for most normal days, they evidence some accuracy deficiencies when applied to ''anomalous'' load conditions occurring during holidays and long weekends. For these periods a specific procedure based upon a combined (unsupervised/supervised) approach has been proposed. The unsupervised stage provides a preventive classification of the historical load data by means of a Kohonen's Self Organizing Map (SOM) The supervised stage, performing the proper forecasting activity, is obtained by using a multi-layer perceptron with a backpropagation learning algorithm similar to the ones above mentioned. The unconventional use of information deriving from the classification stage permits the proposed procedure to obtain a relevant enhancement of the forecast accuracy for anomalous load situations

Dedicated multichannel readout ASIC coupled with single crystal diamond for dosimeter application

This paper reports on the tests of a low-noise, multi-channel readout integrated circuit used as a readout electronic front-end for a diamond multi-pixel dosimeter. The system is developed for dose distribution measurement in radiotherapy applications. The first 10-channel prototype chip was designed and fabricated in a 0.18 um CMOS process. Every channel includes a charge integrator with a 10 pF capacitor and a double slope A/D converter. The diamond multi-pixel detector, based on CVD synthetic single crystal diamond Schottky diodes, is made by a 3 × 3 sensor matrix. The overall device has been tested under irradiation with 6 MeV radio therapeutic photon beams at the Policlinico ``Tor Vergata'' (PTV) hospital. Measurements show a 20 fA RMS leakage current from the front-end input stage and a negligible dark current from the diamond detector, a stable temporal response and a good linear behaviour as a function of both dose and dose rate. These characteristics were common to each tested channel

Arc requires PSD95 for assembly into postsynaptic complexes involved with neural dysfunction and intelligence

Arc is an activity-regulated neuronal protein, but little is known about its interactions, assembly into multiprotein complexes, and role in human disease and cognition. We applied an integrated proteomic and genetic strategy by targeting a tandem affinity purification (TAP) tag and Venus fluorescent protein into the endogenous Arc gene in mice. This allowed biochemical and proteomic characterization of native complexes in wild-type and knockout mice. We identified many Arc-interacting proteins, of which PSD95 was the most abundant. PSD95 was essential for Arc assembly into 1.5-MDa complexes and activity-dependent recruitment to excitatory synapses. Integrating human genetic data with proteomic data showed that Arc-PSD95 complexes are enriched in schizophrenia, intellectual disability, autism, and epilepsy mutations and normal variants in intelligence. We propose that Arc-PSD95 postsynaptic complexes potentially affect human cognitive function