Helsinki University of Technology

About: Helsinki University of Technology is a based out in . It is known for research contribution in the topics: Thin film & Vortex. The organization has 8962 authors who have published 20136 publications receiving 723787 citations. The organization is also known as: TKK & Teknillinen korkeakoulu.

Functional materials based on self-assembly of polymeric supramolecules

Abstract: Self-assembly of polymeric supramolecules is a powerful tool for producing functional materials that combine several properties and may respond to external conditions. We illustrate the concept using a comb-shaped architecture. Examples include the hexagonal self-organization of conjugated conducting polymers and the polarized luminance in solid-state films of rodlike polymers obtained by removing the hydrogen-bonded side chains from the aligned thermotropic smectic phase. Hierarchically structured materials obtained by applying different self-organization and recognition principles and directed assembly form a basis for tunable nanoporous materials, smart membranes, preparation of nano-objects, and anisotropic properties, such as proton conductivity.

Logic programs with stable model semantics as a constraint programming paradigm

Abstract: Logic programming with the stable model semantics is put forward as a novel constraint programming paradigm. This paradigm is interesting because it bring advantages of logic programming based knowledge representation techniques to constraint programming and because implementation methods for the stable model semantics for ground (variabledfree) programs have advanced significantly in recent years. For a program with variables these methods need a grounding procedure for generating a variabledfree program. As a practical approach to handling the grounding problem a subclass of logic programs, domain restricted programs, is proposed. This subclass enables efficient grounding procedures and serves as a basis for integrating builtdin predicates and functions often needed in applications. It is shown that the novel paradigm embeds classical logical satisfiability and standard (finite domain) constraint satisfaction problems but seems to provide a more expressive framework from a knowledge representation point of view. The first steps towards a programming methodology for the new paradigm are taken by presenting solutions to standard constraint satisfaction problems, combinatorial graph problems and planning problems. An efficient implementation of the paradigm based on domain restricted programs has been developed. This is an extension of a previous implementation of the stable model semantics, the Smodels system, and is publicly available. It contains, e.g., builtdin integer arithmetic integrated to stable model computation. The implementation is described briefly and some test results illustrating the current level of performance are reported.

Embedding transition-metal atoms in graphene: structure, bonding, and magnetism

Abstract: We present a density-functional-theory study of transition-metal atoms (Sc--Zn, Pt, and Au) embedded in single and double vacancies (SV and DV) in a graphene sheet. We show that for most metals, the bonding is strong and the metal-vacancy complexes exhibit interesting magnetic behavior. In particular, an Fe atom on a SV is not magnetic, while the Fe@DV complex has a high magnetic moment. Surprisingly, Au and Cu atoms at SV are magnetic. Both bond strengths and magnetic moments can be understood within a simple local-orbital picture, involving carbon $s{p}^{2}$ hybrids and the metal $spd$ orbitals. We further calculate the barriers for impurity-atom migration, and they agree well with available experimental data. We discuss the experimental realization of such systems in the context of spintronics and nanocatalysis.

Activation of human primary motor cortex during action observation: A neuromagnetic study

Abstract: The monkey premotor cortex contains neurons that discharge during action execution and during observation of actions made by others. Transcranial magnetic stimulation experiments suggest that a similar observation/execution matching system also is present in humans. We recorded neuromagnetic oscillatory activity of the human precentral cortex from 10 healthy volunteers while (i) they had no task to perform, (ii) they were manipulating a small object, and (iii) they were observing another individual performing the same task. The left and right median nerves were stimulated alternately (interstimulus interval, 1.5 s) at intensities exceeding motor threshold, and the poststimulus rebound of the rolandic 15- to 25-Hz activity was quantified. In agreement with previous studies, the rebound was strongly suppressed bilaterally during object manipulation. Most interestingly, the rebound also was significantly diminished during action observation (31–46% of the suppression during object manipulation). Control experiments, in which subjects were instructed to observe stationary or moving stimuli, confirmed the specificity of the suppression effect. Because the recorded 15- to 25-Hz activity is known to originate mainly in the precentral motor cortex, we concluded that the human primary motor cortex is activated during observation as well as execution of motor tasks. These findings have implications for a better understanding of the machinery underlying action recognition in humans.

Intensity and coherence of motifs in weighted complex networks

Abstract: The local structure of unweighted networks can be characterized by the number of times a subgraph appears in the network. The clustering coefficient, reflecting the local configuration of triangles, can be seen as a special case of this approach. In this paper we generalize this method for weighted networks. We introduce subgraph ``intensity'' as the geometric mean of its link weights and ``coherence'' as the ratio of the geometric to the corresponding arithmetic mean. Using these measures, motif scores and clustering coefficient can be generalized to weighted networks. To demonstrate these concepts, we apply them to financial and metabolic networks and find that inclusion of weights may considerably modify the conclusions obtained from the study of unweighted characteristics.