Efficient symbolic computation of approximated small-signal characteristics of analog integrated circuits

A symbolic analysis tool is presented that generates simplified symbolic expressions for the small-signal characteristics of large analog integrated circuits. The expressions are approximated while they are computed, so that only those terms are generated which remain in the final expression. This principle causes drastic savings in CPU time and memory, compared with previous symbolic analysis tools. In this way, the maximum size of circuits that can be analyzed, is largely increased. By taking into account a range for the value of a circuit parameter rather than one single number, the generated expressions are also more generally valid. Mismatch handling is explicitly taken into account in the algorithm. The capabilities of the new tool are illustrated with several experimental result

Symbolic analysis of large analog integrated circuits by approximation during expression generation

A novel algorithm is presented that generates approximate symbolic expressions for small-signal characteristics of large analog integrated circuits. The method is based upon the approximation of an expression while it is being computed. The CPU time and memory requirements are reduced drastically with regard to previous approaches, as only those terms are calculated which will remain in the final expression. As a consequence, the maximum circuit size amenable to symbolic analysis has largely increased. The simplification procedure explicitly takes into account variation ranges of the symbolic parameters to avoid inaccuracies of conventional approaches which use a single value. The new approach is also able to take into account mismatches between the symbolic parameters

A Family of matroid intersection algorithms for the computation of approximated symbolic network functions

In recent years, the technique of simplification during generation has turned out to be very promising for the efficient computation of approximate symbolic network functions for large transistor circuits. In this paper it is shown how symbolic network functions can be simplified during their generation with any well-known symbolic network analysis method. The underlying algorithm for the different techniques is always a matroid intersection algorithm. It is shown that the most efficient technique is the two-graph method. An implementation of the simplification during generation technique with the two-graph method illustrates its benefits for the symbolic analysis of large analog circuits

Algorithm for efficient symbolic analysis of large analogue circuits

An algorithm is presented that generates simplified symbolic expressions for the small-signal characteristics of large analogue circuits. The expressions are approximated while they are computed, so that only the most significant terms are generated which remain in the final expression. This principle leads to dramatic savings in CPU time and memory compared to existing techniques, significantly increasing the maximum size of circuits that can be analysed. By taking into account a range for the value of a circuit parameter rather than one single number the generated symbolic expressions are also generally valid

Entanglement of spin chains with general boundaries and of dissipative systems

We analyze the entanglement properties of spins (qubits) close to the boundary of spin chains in the vicinity of a quantum critical point and show that the concurrence at the boundary is significantly different from the one of bulk spins. We also discuss the von Neumann entropy of dissipative environments in the vicinity of a (boundary) critical point, such as two Ising-coupled Kondo-impurities or the dissipative two-level system. Our results indicate that the entanglement (concurrence and/or von Neumann entropy) changes abruptly at the point where coherent quantum oscillations cease to exist. The phase transition modifies significantly less the entanglement if no symmetry breaking field is applied and we argue that this might be a general property of the entanglement of dissipative systems. We finally analyze the entanglement of an harmonic chain between the two ends as function of the system size.Comment: 21 pages, 9 figure

Homo cerevisiae-Leveraging Yeast for Investigating Protein-Protein Interactions and Their Role in Human Disease.

peer reviewedUnderstanding how genetic variation affects phenotypes represents a major challenge, particularly in the context of human disease. Although numerous disease-associated genes have been identified, the clinical significance of most human variants remains unknown. Despite unparalleled advances in genomics, functional assays often lack sufficient throughput, hindering efficient variant functionalization. There is a critical need for the development of more potent, high-throughput methods for characterizing human genetic variants. Here, we review how yeast helps tackle this challenge, both as a valuable model organism and as an experimental tool for investigating the molecular basis of phenotypic perturbation upon genetic variation. In systems biology, yeast has played a pivotal role as a highly scalable platform which has allowed us to gain extensive genetic and molecular knowledge, including the construction of comprehensive interactome maps at the proteome scale for various organisms. By leveraging interactome networks, one can view biology from a systems perspective, unravel the molecular mechanisms underlying genetic diseases, and identify therapeutic targets. The use of yeast to assess the molecular impacts of genetic variants, including those associated with viral interactions, cancer, and rare and complex diseases, has the potential to bridge the gap between genotype and phenotype, opening the door for precision medicine approaches and therapeutic development

TNF-α- and tumor-induced skeletal muscle atrophy involves sphingolipid metabolism

Additional filesInternational audienceUNLABELLED: ABSTRACT: BACKGROUND: Muscle atrophy associated with various pathophysiological conditions represents a major health problem, because of its contribution to the deterioration of patient status and its effect on mortality. Although the involvement of pro-inflammatory cytokines in this process is well recognized, the role of sphingolipid metabolism alterations induced by the cytokines has received little attention. RESULTS: We addressed this question both in vitro using differentiated myotubes treated with TNF-α, and in vivo in a murine model of tumor-induced cachexia. Myotube atrophy induced by TNF-α was accompanied by a substantial increase in cell ceramide levels, and could be mimicked by the addition of exogenous ceramides. It could be prevented by the addition of ceramide-synthesis inhibitors that targeted either the de novo pathway (myriocin), or the sphingomyelinases (GW4869 and 3-O-methylsphingomyelin). In the presence of TNF-α, ceramide-synthesis inhibitors significantly increased protein synthesis and decreased proteolysis. In parallel, they lowered the expression of both the Atrogin-1 and LC3b genes, involved in muscle protein degradation by proteasome and in autophagic proteolysis, respectively, and increased the proportion of inactive, phosphorylated Foxo3 transcription factor. Furthermore, these inhibitors increased the expression and/or phosphorylation levels of key factors regulating protein metabolism, including phospholipase D, an activator of mammalian target of rapamycin (mTOR), and the mTOR substrates S6K1 and Akt. In vivo, C26 carcinoma implantation induced a substantial increase in muscle ceramide, together with drastic muscle atrophy. Treatment of the animals with myriocin reduced the expression of the atrogenes Foxo3 and Atrogin-1, and partially protected muscle tissue from atrophy. CONCLUSIONS: Ceramide accumulation induced by TNF-α or tumor development participates in the mechanism of muscle-cell atrophy, and sphingolipid metabolism is a logical target for pharmacological or nutritional interventions aiming at preserving muscle mass in pathological situations