Synthesis and properties of conjugates between silver nanoparticles and DNA-PNA hybrids

We describe the preparation and properties of a stable conjugate between two 15 nm silver nanoparticles (AgNPs) and a DNA-PNA hybrid composed of 10 guanine-cytosine base pairs. We show that the conjugate is spontaneously formed during incubation of a DNA-PNA hybrid, containing phosphorothioate residues at both ends of the DNA strand with AgNPs. The conjugate molecules were separated from individual AgNPs and multiparticle structures by gel electrophoresis. We demonstrate that the absorption spectrum of the conjugate is broader than that of AgNPs, due to the interparticle plasmon coupling

The Effect of Testing on the Retention of Coherent and Incoherent Text Material

Research has shown that testing during learning can enhance the long-term retention of text material. In two experiments, we investigated the testing effect with a fill-in-the-blank test on the retention of text material. In Experiment 1, using a coherent text, we found no retention benefit of testing compared to a restudy (control) condition. In Experiment 2, text coherence was disrupted by scrambling the order of the sentences from the text. The material was subsequently presented as a list of facts as opposed to connected discourse. For the incoherent version of the text, testing slowed down the rate of forgetting compared to a restudy (control) condition. The results suggest that the connectedness of materials can play an important role in determining the magnitude of testing benefits for long-term retention. Testing with a completion test seems most beneficial for unconnected materials and less so for highly structured materials

Approximating Deterministic Lattice Automata

Abstract. Traditional automata accept or reject their input, and are therefore Boolean. Lattice automata generalize the traditional setting and map words to values taken from a lattice. In particular, in a fully-ordered lattice, the elements are 0, 1,..., n − 1, ordered by the standard ≤ order. Lattice automata, and in particular lattice automata defined with respect to fully-ordered lattices, have interesting theoretical properties as well as applications in formal methods. Minimal deterministic automata capture the combinatorial nature and complexity of a formal language. Deterministic automata have many applications in practice. In [13], we studied minimization of deterministic lattice automata. We proved that the problem is in general NP-complete, yet can be solved in polynomial time in the case the lattices are fully-ordered. The multi-valued setting makes it possible to combine reasoning about lattice automata with approximation. An approximating automaton may map a word to a range of values that are close enough, under some pre-defined distance metric, to its exact value. We study the problem of finding minimal approximating deterministic lattice automata defined with respect to fully-ordered lattices. We consider approximation by absolute distance, where an exact value x can be mapped to values in the range [x − t, x + t], for an approximation factor t, as well as approximation by separation, where values are mapped into t classes. We prove that in both cases the problem is in general NP-complete, but point to special cases that can be solved in polynomial time.