פרסומים

We review density functional theory (DFT) within the Kohn-Sham (KS) and the generalized KS (GKS) frameworks from a theoretical perspective for both time-independent and time-dependent problems. We focus on the use of range-separated hybrids within a GKS approach as a practical remedy for dealing with the deleterious long-range self-repulsion plaguing many approximate implementations of DFT. This technique enables DFT to be widely relevant in new realms such as charge transfer, radical cation dimers, and Rydberg excitations. Emphasis is put on a new concept of system-specific range-parameter tuning, which introduces predictive power in applications considered until recently too difficult for DFT.

We consider the problem of finding the mechanism that maximizes the revenue of a seller of multiple objects. This problem turns out to be significantly more complex than the case where there is only a single object (which was solved by Myerson [5]). The analysis is difficult even in the simplest case studied here, where there are two exclusive objects and a single buyer, with valuations uniformly distributed on triangular domains. We show that the optimal mechanisms are piecewise linear with either 2 or 3 pieces, and obtain explicit formulas for most cases of interest

The sub-coetaneous structures of human skin have been revealed to contain elements that demonstrate electromagnetic behavior in the sub-THz frequency range, reminiscent of low Q helical antennas. The structure in question is the coiled human sweat duct inside the epidermis. It was shown that the temporal behavior of the reflected spectral response mirrored physiological parameters such as blood pressure to a high degree of correlation. The current paper presents the experimental evidence of such and explores its parameters in terms of stress imposed on the subject.

The ability of invertebrates to perform complex cognitive tasks is widely debated. Bees utilize the number of landmarks en-route to their destination as cues for navigation, but their use of numerical information in other contexts has not been studied. Numerical regularity in the spatial distribution of food occurs naturally in some flowers, which contain a fixed number of nectaries. Bees that collect nectar from such flowers are expected to increase their foraging efficiency by avoiding return visits to empty nectaries. This can be achieved if bees base their flowerdeparture decisions on the number of nectaries they had already visited, or on other sources of information that co-vary with this number.We tested, through field observations and laboratory experiments, whether bees adapt their departure behavior to the number of available food resources. Videorecorded observations of bumblebees that visited Alcea setosa flowers with five nectaries revealed that the conditional probability of flower departure after five probings was 93%. Visit duration, the spatial attributes of the flowers and scent marks could be excluded as flower-leaving cues, while the volume of nectar collected may have guided part of the departure decisions. In the laboratory the bees foraged on two patches, each with three computer-controlled feeders, but could receive only up to two sucrose-solution rewards in each patch visit. The foragers gradually increased their tendency to leave the patches after the second reward, while the frequency of patch departure after the first reward remained constant. Patch-visit duration, nectar volume, scent marks and recurring visit sequences in a patch were ruled out as possible sources of patch-leaving information.We conclude that bumblebees distinguish among otherwise identical stimuli by their serial position in a sequence, and use this capability to increase foraging efficiency. Our findings support an adaptive role for a complicated cognitive skill in a seemingly small and simple invertebrate.

Protein–protein interactions (PPIs) govern all aspects of cell function and, as such, are a major target for research and therapeutic intervention. A major rate-limiting step in PPI research is the expression and purification of full-length proteins. The use of peptides to study PPIs significantly facilitates the structural and biophysical characterization of PPIs as well as the effort to develop drugs to control PPIs. Here we describe examples for the use of peptides to study PPI and some of the important experimental methods that are used in the field. Peptides have proved to be excellent tools to study PPIs and have been contributing both for understanding mechanisms of PPIs as well as for drug design for PPI modulation.