D-SPECT (Spectrum Dynamics, Israel) is a novel SPECT system for cardiac perfusion studies. Based on CZT detectors, region-centric scanning, high-sensitivity collimators and resolution recovery, it offers potential advantages over conventional systems. A series of measurements were made on a beta-version D-SPECT system in order to evaluate its performance in terms of energy resolution, scatter fraction, sensitivity, count rate capability and resolution. Corresponding measurements were also done on a conventional SPECT system (CS) for comparison. The energy resolution of the D-SPECT system at 140 keV was 5.5% (CS: 9.25%), the scatter fraction 30% (CS: 34%), the planar sensitivity 398 s(-1) MBq(-1) per head ((99m)Tc, 10 cm) (CS: 72 s(-1) MBq(-1)), and the tomographic sensitivity in the heart region was in the range 647-1107 s(-1) MBq(-1) (CS: 141 s(-1) MBq(-1)). The count rate increased linearly with increasing activity up to 1.44 M s(-1). The intrinsic resolution was equal to the pixel size, 2.46 mm (CS: 3.8 mm). The average reconstructed resolution using the standard clinical filter was 12.5 mm (CS: 13.7 mm). The D-SPECT has superior sensitivity to that of a conventional system with similar spatial resolution. It also has excellent energy resolution and count rate characteristics, which should prove useful in dynamic and dual radionuclide studies.

We study phase transitions in models of opinion formation which are based on the social impact theory. Two different models are discussed: (i) a cellular-automata based model of a finite group with a strong leader where persons can change their opinions but not their spatial positions, and (ii) a model with persons treated as active Brownian particles interacting via a communication field. In the first model, two stable phases are possible: a cluster around the leader, and a state of social unification. The transition into the second state occurs for a large leader strength and/or for a high level of social noise. In the second model, we find three stable phases, which correspond either to a "paramagnetic" phase (for high noise and strong diffusion), a "ferromagnetic" phase (for small nose and weak diffusion), or a phase with spatially separated "domains" (for intermediate conditions).

We investigate models of opinion formation which are based on the social impact theory. The following approaches are discussed: (i) general mean field theory of social impact, (ii) a social impact model with learning, (iii) a model of a finite group with a strong leader, (iv) a social impact model with dynamically changing social temperature, (v) a model with individuals treated as active Brownian particles interacting via a communication field.