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In the context of the massless Nelson model, we prove that two non-relativistic nucleons interacting with a massless meson field do not bind when a sufficiently strong Coulomb repulsion between the nucleons is added to the Hamiltonian. The result holds for both the renormalized and unrenormalized theories, and can also be applied to the so-called piezoelectric polaron model, which describes an electron interacting with the acoustical vibrational modes of a crystal through the piezoelectric interaction. The result can then be interpreted as well as a no-binding statement about piezoelectric bipolarons. The methods used allow also for a significant reduction of about 30% over previously known no-binding conditions for the optical bipolaron model of H. Fröhlich.

Information transfer and integration among functionally distinct areas of cerebral cortex of oscillatory activity require some degree of phase synchrony of the trains of action potentials that carry the information prior to the integration. However, propagation delays are obligatory. Delays vary with the lengths and conduction velocities of the axons carrying the information, causing phase dispersion. In order to determine how synchrony is achieved despite dispersion, we recorded EEG signals from multiple electrode arrays on five cortical areas in cats and rabbits, that had been trained to discriminate visual or auditory conditioned stimuli. Analysis by time-lagged correlation, multiple correlation and PCA, showed that maximal correlation was at zero lag and averaged 0.7, indicating that 50% of the power in the gamma range among the five areas was at zero lag irrespective of phase or frequency. There were no stimulus-related episodes of transiently increased phase locking among the areas, nor EEG "bursts" of transiently increased amplitude above the sustained level of synchrony. Three operations were identified to account for the sustained correlation. Cortices broadcast their outputs over divergent–convergent axonal pathways that performed spatial ensemble averaging; synaptic interactions between excitatory and inhibitory neurons in cortex operated as band pass filters for gamma; and signal coarse-graining by pulse frequency modulation at trigger zones enhanced correlation. The conclusion is that these three operations enable continuous linkage of multiple cortical areas by activity in the gamma range, providing the basis for coordinated cortical output to other parts of the brain, despite varying axonal conduction delays, something like the back plane of a main frame computer.

The aim of this study is to find spatial patterns of EEG amplitude in the gamma range of the EEGs from multiple sensory and limbic areas that demonstrate multisensory convergence and integration. 64 electrodes spread in small arrays were fixed on or in the olfactory, visual, auditory, somatomotor and entorhinal areas of cats and rabbits. The subjects were trained to discriminate 2 visual and then 2 auditory conditioned stimuli, one reinforced (CS+), the other not (CS-). A moving window was applied to the 6-s records from 20 trials of each CS including a 3-s prestimulus control (CS0). The root mean square amplitude was calculated for each signal in the gamma range, so each window gave a point in 64-space. EEG patterns from the CS+, CS- and CS0 conditions gave 3 clusters of points in 64-space. The Euclidean distance of each point to the nearest center of gravity of a cluster served for classification and estimation of the probability of correct classification. The results showed that the gamma activity (35–60 Hz in cats, 20–80 Hz in rabbits) in all five areas formed global patterns of amplitude modulation (AM) in time windows lasting ~100–200 ms and recurring at 2–4 Hz, which were correctly classified above chance levels (p<0.01). All areas contributed information to the AM patterns that served to classify the EEG epochs in the windows with respect to the conditioned stimuli. In conclusion, multisensory integration took place over the greater part of the hemisphere, despite lack of phase coherence among the gamma waves. The integration occurred rapidly enough that, within 300 ms of CS onset, activity in every sensory area was modified by what took place in every other sensory area.

The present report describes the dynamic foundations of long-standing experimental work in the field of oscillatory dynamics in the human and animal brain. It aims to show the role of multiple oscillations in the integrative brain function, memory, and complex perception by a recently introduced conceptional framework: the super-synergy in the whole brain. Results of recent experiments related to the percept of the grandmother-face support our concept of super-synergy in the whole brain in order to explain manifestation of Gestalts and Memory-Stages. This report may also provide new research avenues in macrodynamics of the brain.

The general problem of brain mechanisms involved in perception can now be studied directly by means of new analysis–methods for the activity of large population of neurons. These methods range from indirect means of measuring changes in cerebral blood flow in local regions of the human cortex (functional magnetic resonance imaging, fMRI), or changes in the electrical activity of the human brain with EEG-recording with topological distributed macroelectrodes, to the use of chronically implanted multiple microelectrodes in primates. fMRI has the disadvantage of low temporal resolution and with multiple microelectrodes long distance measurements cannot yet be properly performed. Accordingly, recording of macro-activity (EEG/ERP or MEG) with a time resolution of millisecond-range is the most possibly adequate method to measure the dynamic properties of memory and the integrative brain function.

Since neuroscientists have come to the general conclusion that large numbers of different brain regions have to cooperate for any brain function, the analysis of relationships between different regions of the brain is becoming more and more important.

Before new progresses and importance of EEG studies research became clear, scientists working with macrodynamics of the brain had a long way to go, in order to elucidate brain functioning. In this tutorial report we explain in a narrative way the developments leading to the concept of Macrodynamics in search of an integrative brain function. Moreover, elements of a brain theory, which we call neurons-brain theory describing the dynamics of electrical activity in the whole brain, are introduced. The concept of superbinding in integrative brain function, which emerged from experimental data, is a consequence of this theory.

Structure and electronic properties of the α-MoO₃(100) surface, as well as H adsorption on the α-MoO₃(100) surface have been studied with periodic slab Hartree–Fock calculations. Gradient corrected density functional calculations have been performed in this study. The structure and electronic properties of the (100) surface are in agreement with experimental and previous theoretical results. Local electronic structure near the different surface oxygen sites are analyzed with Mulliken Population Analysis. The oxide is partially ionic and the symmetrically oxygens exhibit more ionic feature while the terminal oxygens are more covalent. Electrostatic potentials show broad negative minima above the terminal oxygen centers, which suggest that electrophilic adparticles, like H, resulting from surface reactions, will be attracted preferentially at these sites. The results of the H adsorption on the (100) surface are interpreted based on charge-transfer interactions between the surface and H species. It is found that terminal oxygen sites are the most stable binding site. Ionic relaxation of the α-MoO₃(100) surface for the adsorption of hydrogen has no effect on the chemical properties and hydrogen atoms adsorbed favorably on the α-MoO₃(100) surface at full coverage.

Computational chemistry offers variety of tools to study properties of biological macromolecules. These tools vary in terms of levels of details from quantum mechanical treatment to numerous macroscopic approaches. Here, we provide a review of computational chemistry algorithms and tools for modeling the effects of genetic variations and their association with diseases. Particular emphasis is given on modeling the effects of missense mutations on stability, conformational dynamics, binding, hydrogen bond network, salt bridges, and pH-dependent properties of the corresponding macromolecules. It is outlined that the disease may be caused by alteration of one or several of above-mentioned biophysical characteristics, and a successful prediction of pathogenicity requires detailed analysis of how the alterations affect the function of involved macromolecules. The review provides a short list of most commonly used algorithms to predict the molecular effects of mutations as well.

Functional significance of the neural oscillations has been debated since long. In particular, oscillations have been suggested to play a major role in formation of communication channels between brain regions. It has been previously suggested that gamma coherence increases during communication between hemispheres when subjects perceive a horizontal motion in Stroboscopic Alternative Motion (SAM) stimulus. In addition, disruption of this coherence may change the horizontal perception of SAM. In this study, we investigated the changes of Cross-Frequency Coupling (CFC) in EEG signals from parietal and occipital cortices during horizontal and vertical perception of SAM. Our results suggested that while the strength of CFC in parietal electrodes showed no significant change, CFC in P3-P4 electrode-pair demonstrated a significant correlation during horizontal perception of SAM. Therefore, the CFC between theta- and gamma-band oscillations seems to be correlated with changes in functional interactions between brain regions. Accordingly, we propose that in addition to gamma coherence, CFC is perhaps another neurophysiological mechanism involved in neural communication.

The binding and acid-base equilibria of the two novel mesoporphyrin derivatives, PB07 and PB109 (quino[4,4a,5,6-efg]- annulated 7-demethyl-8-deethylmesoporphyrin and 2'-cyano-8'-formyl-N'-methyl-1',1a',5a',6'-tetrahydroacrido [4,5,5a,6-bcd]- annulated 2,3-dihydromesoporphyrin, resp.), which are promising agents for photodynamic therapy (PDT), were studied in aqueous solutions of different surfactants (Triton X-100 (TX-100), dodecyl maltoside (DDM), cetyltrimethylammonium bromide (CTAB), lithium dodecyl sulfate (LDS)) and phosphatidyl choline (PC) liposomes. In all cases, the porphyrins are solubilized at neutral/alkaline pH in monomeric form and remain micelle/liposome-bound independently of their ionization state. The dissociation constants of the solubilized porphyrins are found to be influenced by the charge of the surface groups of the carrier. The protonation of pyrrole/quinoline nitrogens of the studied porphyrins is facilitated in the following order: LDS ≫TX-100 (DDM, PC liposomes) > CTAB. The dissociation constants of PB07 carboxylic groups are similar in neutral/cationic micellar and liposome solutions and are significantly decreased for LDS-bound pigment. The results provide necessary information for the optimization of delivery systems for PB07 and PB109 when applied as sensitizers in PDT.

A pyridyl side arm porphyrin incorporating C${}_{10}$ alkyl chains at the periphery of the porphyrin suitable for surface immobilisation on HOPG has been synthesised and tested for two state switching in solution. Temperature switching, involving reversible complexation of a covalently appended pyridyl side arm to the Zn(II) porphyrin, was comprehensively characterised by using variable temperature ¹H NMR (-30 to +100${}^{\circ }$C) and UV-vis (10 to 90${}^{\circ }$C) in toluene. Molecular modelling assisted in understanding strain within the complex.

This paper presents a novel approach to the concurrent solution of three High-Level Synthesis (HLS) problems that are modeled as a Constraint-Satisfaction Problem (CSP) and solved using an Enhanced Genetic Algorithm (EGA). We focus on the core problems of high-level synthesis: Scheduling, Allocation, and Binding. Scheduling consists of assigning of operations in a Data-Flow Graph (DFG) to control steps or clock cycles. Allocation selects specific numbers and types of functional units from a hardware library to perform the operations specified in the DFG. Binding assigns constituent operations of the DFG to specific unit instances. A very general version of this problem is considered where functional units may perform different operations in different numbers of control steps. The EGA is designed to solve CSPs quickly and does not require a user to specify appropriate mutation and crossover rates a priori; these are determined automatically during the course of the genetic search. The enhancements include a directed mutation operator and a new type of elitism that avoids premature convergence. The HLS problems are solved by applying two EGAs in a hierarchical manner. The first performs allocation, while the second performs scheduling and binding and serves as the fitness function for the second. When compared to other, well-known techniques, our results show a reduction in time to obtain optimal solutions for standard benchmarks.

Scots pine (Pinus sylvestris) produces several small, highly homologous, disulfide-rich proteins (Sp-AMPs) in response to fungal pathogenic attacks. We report here the expression, structure and function of these proteins. One of the Sp-AMPs was cloned into and over-expressed in Pichia pastoris. The purified protein shows antifungal activity against Heterobasidion annosum, causing morphological changes in spores and hyphae. Binding studies revealed that it binds to soluble and insoluble β-(1,3)-glucans, major components of the fungal cell wall, with high affinity. Homology modeling studies suggest a Greek-key-β-barrel fold having a conserved patch on the surface that can accommodate at least 4 sugar units. We conclude that these proteins represent a new class of antimicrobial proteins that can be classified as pathogenesis related (PR) protein family 18.

The reading of a word can be used to illustrate the cognitive phenomena of the formation and decomposition of a chunk: a skilled reader perceives a word as a whole and can also report the letter at a certain position in a word. These processes pose a challenge to models of the brain that are based on biologically plausible principles of self-organisation. In most current models of word reading, it is not possible to go down from the word to the letter level for a specific letter position, or this process does not meet the requirements of self-organisation. A general model for the self-organisation of information-processing in the brain will be described: a conceptual network. In the application of this general model to the domain of letter- and word-recognition, the role of position in the perception of a word and in the identification of its letters becomes clear. Temporary connections (neural binding) play a fundamental role in the model as re-entrant pathways that come into existence during the perception of a word, and that are reactivated when a certain letter has to be identified. In simulations of the model the essential role of a critical threshold for the activation level of cell-assemblies has been shown, and the selective propagation of excitation loops at different time scales, during perception and response. Relations with recent empirical work on visual word-recognition and follow-up studies on self-organisation will be discussed.