Implementation of a Microcode-controlled State Machine and Simulator in AVR Microcontrollers (MICoSS)

This paper describes the design of a microcode-controlled state machine and its software implementation in Atmel AVR microcontrollers. In particular, ATmega103 and ATmega128 microcontrollers are used. This design is closely related to the software implementation of a simulator in AVR microcontrollers. This simulator communicates with the designed state machine and presents a complete design environment for microcode development and debugging. These two devices can be interconnected by a flat cable and linked to a computer through a serial or USB interface.Both devices share the control software that allows us to create and edit microprograms and to control the whole state machine. It is possible to start, cancel or step through the execution of the microprograms. The operator can also observe the current state of the state machine. The second part of the control software enables the operator to create and compile simulating programs. The control software communicates with both devices using commands. All the results of this communication are well arranged in dialog boxes and windows.

Predicting collapse of adaptive networked systems without knowing the network

The collapse of ecosystems, the extinction of species, and the breakdown of economic and financial networks usually hinges on topological properties of the underlying networks, such as the existence of self-sustaining (or autocatalytic) feedback cycles. Such collapses can be understood as a massive change of network topology, usually accompanied by the extinction of a macroscopic fraction of nodes and links. It is often related to the breakdown of the last relevant directed catalytic cycle within a dynamical system. Without detailed structural information it seems impossible to state, whether a network is robust or if it is likely to collapse in the near future. Here we show that it is nevertheless possible to predict collapse for a large class of systems that are governed by a linear (or linearized) dynamics. To compute the corresponding early warning signal, we require only non-structural information about the nodes’ states such as species abundances in ecosystems, or company revenues in economic networks. It is shown that the existence of a single directed cycle in the network can be detected by a “quantization effect” of node states, that exists as a direct consequence of a corollary of the Perron–Frobenius theorem. The proposed early warning signal for the collapse of networked systems captures their structural instability without relying on structural information. We illustrate the validity of the approach in a transparent model of co-evolutionary ecosystems and show this quantization in systems of species evolution, epidemiology, and population dynamics

An overview of generalized entropic forms

The aim of this focus letter is to present a comprehensive classification of the main entropic forms introduced in the last fifty years in the framework of statistical physics and information theory. Most of them can be grouped into three families, characterized by two-deformation parameters, introduced respectively by Sharma, Taneja, and Mittal (entropies of degree $(\alpha,\,\beta$)), by Sharma and Mittal (entropies of order $(\alpha,\,\beta)$), and by Hanel and Thurner (entropies of class $(c,\,d)$). Many entropic forms examined will be characterized systematically by means of important concepts such as their axiomatic foundations {\em \`{a} la} Shannon-Khinchin and the consequent composability rule for statistically independent systems. Other critical aspects related to the Lesche stability of information measures and their consistency with the Shore-Johnson axioms will be briefly discussed on a general ground.Comment: 14 pages, 6 tables, no figures, to appear on EPL: Focus Issues "Progresses on Statistical Physics and Complexity

Cross-Talk with Myeloid Accessory Cells Regulates Human Natural Killer Cell Interferon-γ Responses to Malaria

Data from a variety of experimental models suggest that natural killer (NK) cells require signals from accessory cells in order to respond optimally to pathogens, but the precise identity of the cells able to provide such signals depends upon the nature of the infectious organism. Here we show that the ability of human NK cells to produce interferon-γ in response to stimulation by Plasmodium falciparum–infected red blood cells (iRBCs) is strictly dependent upon multiple, contact-dependent and cytokine-mediated signals derived from both monocytes and myeloid dendritic cells (mDCs). Contrary to some previous reports, we find that both monocytes and mDCs express an activated phenotype following short-term incubation with iRBCs and secrete pro-inflammatory cytokines. The magnitude of the NK cell response (and of the KIR(−) CD56(bright) NK cell population in particular) is tightly correlated with resting levels of accessory cell maturation, indicating that heterogeneity of the NK response to malaria is a reflection of deep-rooted heterogeneity in the human innate immune system. Moreover, we show that NK cells are required to maintain the maturation status of resting mDCs and monocytes, providing additional evidence for reciprocal regulation of NK cells and accessory cells. However, NK cell–derived signals are not required for activation of accessory cells by either iRBCs or bacterial lipolysaccharide. Together, these data suggest that there may be differences in the sequence of events required for activation of NK cells by non-viral pathogens compared to the classical model of NK activation by virus-infected or major histocompatibility complex–deficient cells. These findings have far-reaching implications for the study of immunity to infection in human populations

A dynamical approach to the spatiotemporal aspects of the Portevin-Le Chatelier effect: Chaos,turbulence and band propagation

Experimental time series obtained from single and poly-crystals subjected to a constant strain rate tests report an intriguing dynamical crossover from a low dimensional chaotic state at medium strain rates to an infinite dimensional power law state of stress drops at high strain rates. We present results of an extensive study of all aspects of the PLC effect within the context a model that reproduces this crossover. A study of the distribution of the Lyapunov exponents as a function of strain rate shows that it changes from a small set of positive exponents in the chaotic regime to a dense set of null exponents in the scaling regime. As the latter feature is similar to the GOY shell model for turbulence, we compare our results with the GOY model. Interestingly, the null exponents in our model themselves obey a power law. The configuration of dislocations is visualized through the slow manifold analysis. This shows that while a large proportion of dislocations are in the pinned state in the chaotic regime, most of them are at the threshold of unpinning in the scaling regime. The model qualitatively reproduces the different types of deformation bands seen in experiments. At high strain rates where propagating bands are seen, the model equations are reduced to the Fisher-Kolmogorov equation for propagative fronts. This shows that the velocity of the bands varies linearly with the strain rate and inversely with the dislocation density, consistent with the known experimental results. Thus, this simple dynamical model captures the complex spatio-temporal features of the PLC effect.Comment: 17 pages, 18 figure

Spin-Dependent Mass Enhancement under Magnetic Field in the Periodic Anderson Model

In order to study the mechanism of the mass enhancement in heavy fermion compounds in the presence of magnetic field, we study the periodic Anderson model using the fluctuation exchange approximation. The resulting value of the mass enhancement factor z^{-1} can become up to 10, which is significantly larger than that in the single-band Hubbard model. We show that the difference between the magnitude of the mass enhancement factor of up spin (minority spin) electrons z^{-1}_up and that of down spin (majority spin) electrons z^{-1}_down increases by the applied magnetic field B//z, which is consistent with de Haas-van Alphen measurements for CeCoIn_5, CeRu_2Si_2 and CePd_2Si_2. We predict that z^{-1}_up >z^{-1}_down in many Ce compounds, whereas z^{-1}_up < z^{-1}_down in Yb compounds.Comment: 5 pages, 4 figure

Novel transcribed regions in the human genome

We have used genomic tiling arrays to identify transcribed regions throughout the human genome. Analysis of the mapping results of RNA isolated from five cell/tissue types, NB4 cells, NB4 cells treated with retinoic acid (RA), NB4 cells treated with 12-O-tetradecanoylphorbol-13 acetate (TPA), neutrophils, and placenta, throughout the ENCODE region reveals a large number of novel transcribed regions. Interestingly, neutrophils exhibit a great deal of novel expression in several intronic regions. Comparison of the hybridization results of NB4 cells treated with different stimuli relative to untreated cells reveals that many new regions are expressed upon cell differentiation. One such region is the Hox locus, which contains a large number of novel regions expressed in a number of cell types. Analysis of the trinucleotide composition of the novel transcribed regions reveals that it is similar to that of known exons. These results suggest that many of the novel transcribed regions may have a functional role. Copyright 2006, Cold Spring Harbor Laboratory Press © 2006 Cold Spring Harbor Laboratory Press

High-Resolution Copy-Number Variation Map Reflects Human Olfactory Receptor Diversity and Evolution

Olfactory receptors (ORs), which are involved in odorant recognition, form the largest mammalian protein superfamily. The genomic content of OR genes is considerably reduced in humans, as reflected by the relatively small repertoire size and the high fraction (∼55%) of human pseudogenes. Since several recent low-resolution surveys suggested that OR genomic loci are frequently affected by copy-number variants (CNVs), we hypothesized that CNVs may play an important role in the evolution of the human olfactory repertoire. We used high-resolution oligonucleotide tiling microarrays to detect CNVs across 851 OR gene and pseudogene loci. Examining genomic DNA from 25 individuals with ancestry from three populations, we identified 93 OR gene loci and 151 pseudogene loci affected by CNVs, generating a mosaic of OR dosages across persons. Our data suggest that ∼50% of the CNVs involve more than one OR, with the largest CNV spanning 11 loci. In contrast to earlier reports, we observe that CNVs are more frequent among OR pseudogenes than among intact genes, presumably due to both selective constraints and CNV formation biases. Furthermore, our results show an enrichment of CNVs among ORs with a close human paralog or lacking a one-to-one ortholog in chimpanzee. Interestingly, among the latter we observed an enrichment in CNV losses over gains, a finding potentially related to the known diminution of the human OR repertoire. Quantitative PCR experiments performed for 122 sampled ORs agreed well with the microarray results and uncovered 23 additional CNVs. Importantly, these experiments allowed us to uncover nine common deletion alleles that affect 15 OR genes and five pseudogenes. Comparison to the chimpanzee reference genome revealed that all of the deletion alleles are human derived, therefore indicating a profound effect of human-specific deletions on the individual OR gene content. Furthermore, these deletion alleles may be used in future genetic association studies of olfactory inter-individual differences

A probabilistic model for gene content evolution with duplication, loss, and horizontal transfer

We introduce a Markov model for the evolution of a gene family along a phylogeny. The model includes parameters for the rates of horizontal gene transfer, gene duplication, and gene loss, in addition to branch lengths in the phylogeny. The likelihood for the changes in the size of a gene family across different organisms can be calculated in O(N+hM^2) time and O(N+M^2) space, where N is the number of organisms, $h$ is the height of the phylogeny, and M is the sum of family sizes. We apply the model to the evolution of gene content in Preoteobacteria using the gene families in the COG (Clusters of Orthologous Groups) database

Drug-resistant genotypes and multi-clonality in Plasmodium falciparum analysed by direct genome sequencing from peripheral blood of malaria patients.

Naturally acquired blood-stage infections of the malaria parasite Plasmodium falciparum typically harbour multiple haploid clones. The apparent number of clones observed in any single infection depends on the diversity of the polymorphic markers used for the analysis, and the relative abundance of rare clones, which frequently fail to be detected among PCR products derived from numerically dominant clones. However, minority clones are of clinical interest as they may harbour genes conferring drug resistance, leading to enhanced survival after treatment and the possibility of subsequent therapeutic failure. We deployed new generation sequencing to derive genome data for five non-propagated parasite isolates taken directly from 4 different patients treated for clinical malaria in a UK hospital. Analysis of depth of coverage and length of sequence intervals between paired reads identified both previously described and novel gene deletions and amplifications. Full-length sequence data was extracted for 6 loci considered to be under selection by antimalarial drugs, and both known and previously unknown amino acid substitutions were identified. Full mitochondrial genomes were extracted from the sequencing data for each isolate, and these are compared against a panel of polymorphic sites derived from published or unpublished but publicly available data. Finally, genome-wide analysis of clone multiplicity was performed, and the number of infecting parasite clones estimated for each isolate. Each patient harboured at least 3 clones of P. falciparum by this analysis, consistent with results obtained with conventional PCR analysis of polymorphic merozoite antigen loci. We conclude that genome sequencing of peripheral blood P. falciparum taken directly from malaria patients provides high quality data useful for drug resistance studies, genomic structural analyses and population genetics, and also robustly represents clonal multiplicity