Neural Modeling and Control of Diesel Engine with Pollution Constraints

The paper describes a neural approach for modelling and control of a turbocharged Diesel engine. A neural model, whose structure is mainly based on some physical equations describing the engine behaviour, is built for the rotation speed and the exhaust gas opacity. The model is composed of three interconnected neural submodels, each of them constituting a nonlinear multi-input single-output error model. The structural identification and the parameter estimation from data gathered on a real engine are described. The neural direct model is then used to determine a neural controller of the engine, in a specialized training scheme minimising a multivariable criterion. Simulations show the effect of the pollution constraint weighting on a trajectory tracking of the engine speed. Neural networks, which are flexible and parsimonious nonlinear black-box models, with universal approximation capabilities, can accurately describe or control complex nonlinear systems, with little a priori theoretical knowledge. The presented work extends optimal neuro-control to the multivariable case and shows the flexibility of neural optimisers. Considering the preliminary results, it appears that neural networks can be used as embedded models for engine control, to satisfy the more and more restricting pollutant emission legislation. Particularly, they are able to model nonlinear dynamics and outperform during transients the control schemes based on static mappings.Comment: 15 page

ProbCD: enrichment analysis accounting for categorization uncertainty

As in many other areas of science, systems biology makes extensive use of statistical association and significance estimates in contingency tables, a type of categorical data analysis known in this field as enrichment (also over-representation or enhancement) analysis. In spite of efforts to create probabilistic annotations, especially in the Gene Ontology context, or to deal with uncertainty in high throughput-based datasets, current enrichment methods largely ignore this probabilistic information since they are mainly based on variants of the Fisher Exact Test. We developed an open-source R package to deal with probabilistic categorical data analysis, ProbCD, that does not require a static contingency table. The contingency table for
the enrichment problem is built using the expectation of a Bernoulli Scheme stochastic process given the categorization probabilities. An on-line interface was created to allow usage by non-programmers and is available at: http://xerad.systemsbiology.net/ProbCD/. We present an analysis framework and software tools to address the issue of uncertainty in categorical data analysis. In particular, concerning the enrichment analysis, ProbCD can accommodate: (i) the stochastic nature of the high-throughput experimental techniques and (ii) probabilistic gene annotation

Superstrings with multiplicities

A superstring of a set of words P = s1, · · · , sp is a string that contains each word of P as substring. Given P, the well known Shortest Linear Superstring problem (SLS), asks for a shortest superstring of P. In a variant of SLS, called Multi-SLS, each word si comes with an integer m(i), its multiplicity, that sets a constraint on its number of occurrences, and the goal is to find a shortest superstring that contains at least m(i) occurrences of si. Multi-SLS generalizes SLS and is obviously as hard to solve, but it has been studied only in special cases (with words of length 2 or with a fixed number of words). The approximability of Multi-SLS in the general case remains open. Here, we study the approximability of Multi-SLS and that of the companion problem Multi-SCCS, which asks for a shortest cyclic cover instead of shortest superstring. First, we investigate the approximation of a greedy algorithm for maximizing the compression offered by a superstring or by a cyclic cover: the approximation ratio is 1/2 for Multi-SLS and 1 for Multi-SCCS. Then, we exhibit a linear time approximation algorithm, Concat-Greedy, and show it achieves a ratio of 4 regarding the superstring length. This demonstrates that for both measures Multi-SLS belongs to the class of APX problems. © 2018 Yoshifumi Sakai; licensed under Creative Commons License CC-BY.Peer reviewe

CpG-ODN-induced sustained expression of BTLA mediating selective inhibition of human B cells.

BTLA (B- and T-lymphocyte attenuator) is a prominent co-receptor that is structurally and functionally related to CTLA-4 and PD-1. In T cells, BTLA inhibits TCR-mediated activation. In B cells, roles and functions of BTLA are still poorly understood and have never been studied in the context of B cells activated by CpG via TLR9. In this study, we evaluated the expression of BTLA depending on activation and differentiation of human B cell subsets in peripheral blood and lymph nodes. Stimulation with CpG upregulated BTLA, but not its ligand: herpes virus entry mediator (HVEM), on B cells in vitro and sustained its expression in vivo in melanoma patients after vaccination. Upon ligation with HVEM, BTLA inhibited CpG-mediated B cell functions (proliferation, cytokine production, and upregulation of co-stimulatory molecules), which was reversed by blocking BTLA/HVEM interactions. Interestingly, chemokine secretion (IL-8 and MIP1β) was not affected by BTLA/HVEM ligation, suggesting that BTLA-mediated inhibition is selective for some but not all B cell functions. We conclude that BTLA is an important immune checkpoint for B cells, as similarly known for T cells

Vaccination of stage III/IV melanoma patients with long NY-ESO-1 peptide and CpG-B elicits robust CD8(+) and CD4(+) T-cell responses with multiple specificities including a novel DR7-restricted epitope.

Long synthetic peptides and CpG-containing oligodeoxynucleotides are promising components for cancer vaccines. In this phase I trial, 19 patients received a mean of 8 (range 1-12) monthly vaccines s.c. composed of the long synthetic NY-ESO-179-108 peptide and CpG-B (PF-3512676), emulsified in Montanide ISA-51. In 18/18 evaluable patients, vaccination induced antigen-specific CD8(+) and CD4(+) T-cell and antibody responses, starting early after initiation of immunotherapy and lasting at least one year. The T-cells responded antigen-specifically, with strong secretion of IFNγ and TNFα, irrespective of patients' HLAs. The most immunogenic regions of the vaccine peptide were NY-ESO-189-102 for CD8(+) and NY-ESO-183-99 for CD4(+) T-cells. We discovered a novel and highly immunogenic epitope (HLA-DR7/NY-ESO-187-99); 7/7 HLA-DR7(+) patients generated strong CD4(+) T-cell responses, as detected directly ex vivo with fluorescent multimers. Thus, vaccination with the long synthetic NY-ESO-179-108 peptide combined with the strong immune adjuvant CpG-B induced integrated, robust and functional CD8(+) and CD4(+) T-cell responses in melanoma patients, supporting the further development of this immunotherapeutic approach

String Matching and 1d Lattice Gases

We calculate the probability distributions for the number of occurrences $n$ of a given $l$ letter word in a random string of $k$ letters. Analytical expressions for the distribution are known for the asymptotic regimes (i) $k \gg r^l \gg 1$ (Gaussian) and $k,l \to \infty$ such that $k/r^l$ is finite (Compound Poisson). However, it is known that these distributions do now work well in the intermediate regime $k \gtrsim r^l \gtrsim 1$. We show that the problem of calculating the string matching probability can be cast into a determining the configurational partition function of a 1d lattice gas with interacting particles so that the matching probability becomes the grand-partition sum of the lattice gas, with the number of particles corresponding to the number of matches. We perform a virial expansion of the effective equation of state and obtain the probability distribution. Our result reproduces the behavior of the distribution in all regimes. We are also able to show analytically how the limiting distributions arise. Our analysis builds on the fact that the effective interactions between the particles consist of a relatively strong core of size $l$, the word length, followed by a weak, exponentially decaying tail. We find that the asymptotic regimes correspond to the case where the tail of the interactions can be neglected, while in the intermediate regime they need to be kept in the analysis. Our results are readily generalized to the case where the random strings are generated by more complicated stochastic processes such as a non-uniform letter probability distribution or Markov chains. We show that in these cases the tails of the effective interactions can be made even more dominant rendering thus the asymptotic approximations less accurate in such a regime.Comment: 44 pages and 8 figures. Major revision of previous version. The lattice gas analogy has been worked out in full, including virial expansion and equation of state. This constitutes the main part of the paper now. Connections with existing work is made and references should be up to date now. To be submitted for publicatio

Trisomy for Synaptojanin1 in Down syndrome is functionally linked to the enlargement of early endosomes

Enlarged early endosomes have been observed in neurons and fibroblasts in Down syndrome (DS). These endosome abnormalities have been implicated in the early development of Alzheimer's disease (AD) pathology in these subjects. Here, we show the presence of enlarged endosomes in blood mononuclear cells and lymphoblastoid cell lines (LCLs) from individuals with DS using immunofluorescence and confocal microscopy. Genotype-phenotype correlations in LCLs carrying partial trisomies 21 revealed that triplication of a 2.56 Mb locus in 21q22.11 is associated with the endosomal abnormalities. This locus contains the gene encoding the phosphoinositide phosphatase synaptojanin 1 (SYNJ1), a key regulator of the signalling phospholipid phosphatidylinositol-4,5-biphosphate that has been shown to regulate clathrin-mediated endocytosis. We found that SYNJ1 transcripts are increased in LCLs from individuals with DS and that overexpression of SYNJ1 in a neuroblastoma cell line as well as in transgenic mice leads to enlarged endosomes. Moreover, the proportion of enlarged endosomes in fibroblasts from an individual with DS was reduced after silencing SYNJ1 expression with RNA interference. In LCLs carrying amyloid precursor protein (APP) microduplications causing autosomal dominant early-onset AD, enlarged endosomes were absent, suggesting that APP overexpression alone is not involved in the modification of early endosomes in this cell type. These findings provide new insights into the contribution of SYNJ1 overexpression to the endosomal changes observed in DS and suggest an attractive new target for rescuing endocytic dysfunction and lipid metabolism in DS and in A

Detection of recombination in variable number tandem repeat sequences

Tandem repeats are repeated sequences whose copies are adjacent along the chromosomes. They account for large portion of eukaryotic genomes and are found in all types of living organisms. Among tandem repeats, those with repeat unit of middle size are called minisatellites. These loci depart from classical loci because of the propensity to vary in size due to the addition or the removal of one or more repeat units. Due to this polymorphism, they prove useful in genetic mapping, in population genetics, and forensic medicine. Moreover, some specific tandem repeat loci are involved in diseases, like the insulin minisatellite, which is implicated in type I diabetes and obesity. Those loci also undergo complex recombination events. Presently, some programs to compare tandem repeats alleles exist and yield good results when recombination is absent, but none correctly handles recombinant alleles. Our goal is to develop an adequate tool for the detection of recombinant among a set of minisatellite sequences. By combining a multiple alignment tool and a method based on phylogenetic profiling, we design a first solution, called MS_PhylPro, for this task. The method has been implemented, tested on real data sets from the insulin minisatellite, and proven to detect recombinant allele