A formal representation of assumptions in process modelling

In this work, we present a systematic approach to the representation of modelling assumptions. Modelling assumptions form the fundamental basis for the mathematical description of a process system. These assumptions can be translated into either additional mathematical relationships or constraints between model variables, equations, balance volumes or parameters. In order to analyse the effect of modelling assumptions in a formal, rigorous way, a syntax of modelling assumptions has been defined. The smallest indivisible syntactical element, the so called assumption atom has been identified as a triplet. With this syntax a modelling assumption can be described as an elementary assumption, i.e. an assumption consisting of only an assumption atom or a composite assumption consisting of a conjunction of elementary assumptions. The above syntax of modelling assumptions enables us to represent modelling assumptions as transformations acting on the set of model equations. The notion of syntactical correctness and semantical consistency of sets of modelling assumptions is defined and necessary conditions for checking them are given. These transformations can be used in several ways and their implications can be analysed by formal methods. The modelling assumptions define model hierarchies. That is, a series of model families each belonging to a particular equivalence class. These model equivalence classes can be related to primal assumptions regarding the definition of mass, energy and momentum balance volumes and to secondary and tiertinary assumptions regarding the presence or absence and the form of mechanisms within the system. Within equivalence classes, there are many model members, these being related to algebraic model transformations for the particular model. We show how these model hierarchies are driven by the underlying assumption structure and indicate some implications on system dynamics and complexity issues. (C) 2001 Elsevier Science Ltd. All rights reserved.

Stabilizer formalism for operator quantum error correction

Operator quantum error correction is a recently developed theory that provides a generalized and unified framework for active error correction and passive error avoiding schemes. In this Letter, we describe these codes using the stabilizer formalism. This is achieved by adding a gauge group to stabilizer codes that defines an equivalence class between encoded states. Gauge transformations leave the encoded information unchanged; their effect is absorbed by virtual gauge qubits that do not carry useful information. We illustrate the construction by identifying a gauge symmetry in Shor's 9-qubit code that allows us to remove 3 of its 8 stabilizer generators, leading to a simpler decoding procedure and a wider class of logical operations without affecting its essential properties. This opens the path to possible improvements of the error threshold of fault-tolerant quantum computing.

A novel approach to antigen-specific deletion of CTL with minimal cellular activation using alpha 3 domain mutants of MHC class I/peptide complex

In this study, we have compared the effector functions and fate of a number of human CTL clones in vitro or ex vivo following contact with variant peptides presented either on the cell surface or in a soluble multimeric format. In the presence of CD8 coreceptor binding, there is a good correlation between TCR signaling, killing of the targets, and Fast-mediated CTL apoptosis. Blocking CD8 binding using (alpha3 domain mutants of MHC class I results in much reduced signaling and reduced killing of the targets. Surprisingly, however, Fast expression is induced to a similar degree on these CTLs, and apoptosis of CTL is unaffected. The ability to divorce these events may allow the deletion of antigen-specific and pathological CTL populations without the deleterious effects induced by full CTL activation.

Subgeometric rates of convergence for a class of continuous-time Markov process

Let (Phi(t))(t is an element of R+) be a Harris ergodic continuous-time Markov process on a general state space, with invariant probability measure pi. We investigate the rates of convergence of the transition function P-t(x, (.)) to pi; specifically, we find conditions under which r(t) vertical bar vertical bar P-t (x, (.)) - pi vertical bar vertical bar -> 0 as t -> infinity, for suitable subgeometric rate functions r(t), where vertical bar vertical bar - vertical bar vertical bar denotes the usual total variation norm for a signed measure. We derive sufficient conditions for the convergence to hold, in terms of the existence of suitable points on which the first hitting time moments are bounded. In particular, for stochastically ordered Markov processes, explicit bounds on subgeometric rates of convergence are obtained. These results are illustrated in several examples.

Complex numbers and symmetries in quantum mechanics, and a nonlinear superposition principle for Wigner functions

Complex numbers appear in the Hilbert space formulation of quantum mechanics, but not in the formulation in phase space. Quantum symmetries are described by complex, unitary or antiunitary operators defining ray representations in Hilbert space, whereas in phase space they are described by real, true representations. Equivalence of the formulations requires that the former representations can be obtained from the latter and vice versa. Examples are given. Equivalence of the two formulations also requires that complex superpositions of state vectors can be described in the phase space formulation, and it is shown that this leads to a nonlinear superposition principle for orthogonal, pure-state Wigner functions. It is concluded that the use of complex numbers in quantum mechanics can be regarded as a computational device to simplify calculations, as in all other applications of mathematics to physical phenomena.

Compositional class refinement in object-Z

Object-Z allows coupling constraints between classes which, on the one hand, facilitate specification at a high level of abstraction, but, on the other hand, make class refinement non-compositional. The consequence of this is that refinement is not practical for large Systems. This paper overcomes this limitation by introducing a methodology for compositional class refinement in Object-Z. The key step is an equivalence transformation of an arbitrary Object-Z specification to one in which introduced constraints prohibit non-compositional refinements. The methodology also allows the constraints which couple classes to be refined yielding an unrestricted approach to compositional class refinement.

Modal functions of future tenses in French

The paper disputes two influential claims in the Romance Linguistics literature. The first is that the synthetic future tenses in spoken Western Romance are now rivalled, if not supplanted, as temporal functors by the more recently developed GO futures. The second is that these synthetic futures now have modal rather than temporal meanings in spoken Romance. These claims are seen as reflecting a universal cycle of diachronic change, in which verb forms originally expressing modal (or aspectual) values take on future temporal reference, becoming tenses. The new modal meanings supplant the temporal, which are then taken up by new forms. Challenges to this theory for French are raised on the basis of empirical evidence of two sorts. Positively, future tenses in spoken Romance continue to be used with temporal meaning. Negatively, evidence of modal meaning for these forms is lacking. The evidence comes froma corpora of spoken French, native speaker judgements and verb data from a daily broadsheet. Cumulatively, it points to the reverse of the claims noted above: the synthetic future in spoken French has temporal but little modal meaning.

A class of compact dwarf galaxies from disruptive processes in galaxy clusters

Dwarf galaxies have attracted increased attention in recent years, because of their susceptibility to galaxy transformation processes within rich galaxy clusters. Direct evidence for these processes, however, has been difficult to obtain, with a small number of diffuse light trails and intra-cluster stars, being the only signs of galaxy disruption. Furthermore, our current knowledge of dwarf galaxy populations may be very incomplete, because traditional galaxy surveys are insensitive to extremely diffuse or compact galaxies. Aware of these concerns, we recently undertook an all-object survey of the Fornax galaxy cluster. This revealed a new population of compact members, overlooked in previous conventional surveys. Here we demonstrate that these 'ultra-compact' dwarf galaxies are structurally and dynamically distinct from both globular star clusters and known types of dwarf galaxy, and thus represent a new class of dwarf galaxy. Our data are consistent with the interpretation that these are the remnant nuclei of disrupted dwarf galaxies, making them an easily observed tracer of galaxy disruption.

A first-principles density-functional calculation of the electronic and vibrational structure of the key melanin monomers

We report first-principles density-functional calculations for hydroquinone (HQ), indolequinone (IQ), and semiquinone (SQ). These molecules are believed to be the basic building blocks of the eumelanins, a class of biomacromolecules with important biological functions (including photoprotection) and with the potential for certain bioengineering applications. We have used the difference of self-consistent fields method to study the energy gap between the highest occupied molecular orbital and the lowest unoccupied molecular orbital, HL. We show that HL is similar in IQ and SQ, but approximately twice as large in HQ. This may have important implications for our understanding of the observed broadband optical absorption of the eumelanins. The possibility of using this difference in HL to molecularly engineer the electronic properties of eumelanins is discussed. We calculate the infrared and Raman spectra of the three redox forms from first principles. Each of the molecules have significantly different infrared and Raman signatures, and so these spectra could be used in situ to nondestructively identify the monomeric content of macromolecules. It is hoped that this may be a helpful analytical tool in determining the structure of eumelanin macromolecules and hence in helping to determine the structure-property-function relationships that control the behavior of the eumelanins.

The expression of messenger RNAs coding for growth factors, their receptors, and eph-class receptor tyrosine kinases in normal and ototoxically damaged chick cochleae

Messenger RNAs coding for growth factors and receptor tyrosine kinases were measured by quantitative competitive and by semi-quantitative reverse-transcription polymerase chain reaction in whole and dissected chick inner ears. The fibroblast growth factor (FGF) receptor 1 chick embryonic kinase (CEK) 1 was expressed in all structures examined (otocyst, hatchling whole cochlea, cochlear nerve ganglion, and cochlear and vestibular sensory epithelia), although slightly more heavily in the otocyst. The related fibroblast growth factor receptors CEK 2 and 3 were preferentially expressed in the nerve ganglion and in the vestibular sensory epithelium, respectively. FGF 1 mRNA was low in early development, increasing to mature levels at around embryonic age 11 days, while FGF2, mRNA was expressed at constant levels at all ages. In response to ototoxic damage, FGF1 mRNA levels were increased in the early damaged cochlear sensory epithelium. Immunohistochemistry for CEK1 showed that normal hair cells expressed the receptor heavily on the hair cell stereocilia, while with early damage, CEK1 came to be expressed heavily on the apical surfaces of the supporting cells. In normal chicks, the CEK4 and CEK8 eph-class receptor tyrosine kinases were expressed relatively heavily by the cochlear nerve ganglion, and CEK10 was expressed relatively heavily by the cochlear hair cell sensory epithelium. The results suggest that the FGF system may be involved in the response of the cochlear epithelium to ototoxic damage. The eph-class receptor tyrosine kinase CEK10 may be involved in cell interactions in the cochlear sensory epithelium, while CEK4 and CEK8 may play a role in the cochlear innervation.

Dependence of transient dynamics in a class-C laser upon variation of inversion with time

The transient statistics of a gain-switched coherently pumped class-C laser displays a linear correlation between the first passage time and subsequent peak intensity. Measurements are reported showing a positive or negative sign of this linear correlation, controlled through the switching time and the laser detuning. Further measurements of the small-signal laser gain combined with calculations involving a three-level laser model indicate that this sign fundamentally depends upon the way the laser inversion varies during the gain switching, despite the added dynamics of the laser polarization in the class-C laser. [S1050-2947(97)07112-6].

Fast evolution strategies

Evolution strategies are a class of general optimisation algorithms which are applicable to functions that are multimodal, nondifferentiable, or even discontinuous. Although recombination operators have been introduced into evolution strategies, the primary search operator is still mutation. Classical evolution strategies rely on Gaussian mutations. A new mutation operator based on the Cauchy distribution is proposed in this paper. It is shown empirically that the new evolution strategy based on Cauchy mutation outperforms the classical evolution strategy on most of the 23 benchmark problems tested in this paper. The paper also shows empirically that changing the order of mutating the objective variables and mutating the strategy parameters does not alter the previous conclusion significantly, and that Cauchy mutations with different scaling parameters still outperform the Gaussian mutation with self-adaptation. However, the advantage of Cauchy mutations disappears when recombination is used in evolution strategies. It is argued that the search step size plays an important role in determining evolution strategies' performance. The large step size of recombination plays a similar role as Cauchy mutation.

Papillomavirus virus-like particles can deliver defined CTL epitopes to the MHC class I pathway

To evaluate an antigen delivery system in which exogenous antigen can target the major histocompatibility complex (MHC) class I pathway, a single human papillomavirus (HPV) 16 E7 cytotoxic T lymphocyte (CTL) epitope and a single HIV gp160 CTL epitope were separately fused to the C-terminus or bovine papillomavirus 1 (BPV1) L1 sequence to form hybrid BPV1L1 VLPs. Mice immunized with these hybrid VLPs mounted strong CTL responses against the relevant target cells in the absence of any adjuvants. In addition, the CTL responses induced by immunization with BPV1L1/HPV16E7CTL VLPs protected mice against challenge with E7-transformed tumor cells. Furthermore, a high titer-specific antibody response against BPV1L1 VLPs was also induced, and this antiserum could inhibit papillomavirus-induced agglutination of mouse erythrocytes, suggesting that the antibody may recognize conformational determinates relevant to virus neutralization. These data demonstrate that hybrid BPV1L1 VLPs can be used as carriers to target antigenic epitopes to both the MHC class I and class II pathways, providing a promising strategy for the design of vaccines to prevent virus infection, with the potential to elicit therapeutic virus-specific CTL responses. (C) 1998 Academic Press.

Prediction of MHC class II-binding peptides using an evolutionary algorithm and artificial neural network

Motivation: Prediction methods for identifying binding peptides could minimize the number of peptides required to be synthesized and assayed, and thereby facilitate the identification of potential T-cell epitopes. We developed a bioinformatic method for the prediction of peptide binding to MHC class II molecules. Results: Experimental binding data and expert knowledge of anchor positions and binding motifs were combined with an evolutionary algorithm (EA) and an artificial neural network (ANN): binding data extraction --> peptide alignment --> ANN training and classification. This method, termed PERUN, was implemented for the prediction of peptides that bind to HLA-DR4(B1*0401). The respective positive predictive values of PERUN predictions of high-, moderate-, low- and zero-affinity binder-a were assessed as 0.8, 0.7, 0.5 and 0.8 by cross-validation, and 1.0, 0.8, 0.3 and 0.7 by experimental binding. This illustrates the synergy between experimentation and computer modeling, and its application to the identification of potential immunotheraaeutic peptides.