Presentation and automatic treatment of evolutive data in medicine. Application to clinical pancreatic pathology]

In this paper we propose a method allowing the representation of time-dependent changes in symptomatology. In algorithm, which automatically generates the sequence of stable states in patient's symptomatology evolution, describes slow, as well as fast, variations of diseases. This sequential representation of data can then be analysed by classical statistical procedures in a population of patients suffering from pancreatic diseases, to estimate the rate of global modification of clinical symptomatology in time.     

Probabilistic transitions for P systems

In this paper we use the abstract syntax and the structural operational semantics of the P systems given in ［1］, and add probabilities to the rules and to the communication targets. We take into account the number of possible combinations of rules which can be applied in a computation step, as well as the consumption degree of the current resources.     

DNA computing on surfaces

DNA computing was proposed as a means of solving a class of intractable computational problems in which the computing time can grow exponentially with problem size (the 'NP-complete' or non-deterministic polynomial time complete problems). The principle of the technique has been demonstrated experimentally for a simple example of the hamiltonian path problem (in this case, finding an airline flight path between several cities, such that each city is visited only once). DNA computational approaches to the solution of other problems have also been investigated. One technique involves the immobilization and manipulation of combinatorial mixtures of DNA on a support. A set of DNA molecules encoding all candidate solutions to the computational problem of interest is synthesized and attached to the surface. Successive cycles of hybridization operations and exonuclease digestion are used to identify and eliminate those members of the set that are not solutions. Upon completion of all the multistep cycles, the solution to the computational problem is identified using a polymerase chain reaction to amplify the remaining molecules, which are then hybridized to an addressed array. The advantages of this approach are its scalability and potential to be automated (the use of solid-phase formats simplifies the complex repetitive chemical processes, as has been demonstrated in DNA and protein synthesis). Here we report the use of this method to solve a NP-complete problem. We consider a small example of the satisfiability problem (SAT), in which the values of a set of boolean variables satisfying certain logical constraints are determined.     

Beethoven, a mouse model for dominant, progressive hearing loss DFNA36

Despite recent progress in identifying genes underlying deafness, there are still relatively few mouse models of specific forms of human deafness. Here we describe the phenotype of the Beethoven (Bth) mouse mutant and a missense mutation in Tmc1 (transmembrane cochlear-expressed gene 1). Progressive hearing loss (DFNA36) and profound congenital deafness (DFNB7/B11) are caused by dominant and recessive mutations of the human ortholog, TMC1 (ref. 1), for which Bth and deafness (dn) are mouse models, respectively.     

弹性材料平头压痕试验的有限元模拟

压痕试验是近些年来材料力学中应用十分广泛的力学试验之一．本文通过对弹性材料平头压痕试验的有限元数值模拟,比较了荷载一位移曲线和接触面分布应力的理论解和数值解,验证了有限元模型的有效性,并对有限元数值模型的几何尺寸、网格疏密、边界条件等参数进行了敏感性分析．该有限元模型的建立为研究压痕试验的应用提供了一种有效的数值分析方法．