Theories of the state

[Introduction] The recent, unparalleled ascendancy of the liberal democratic state may seem to render alternative theories of the state redundant. But while the prevailing view might be that “I have seen the future, and it works”, it was not so long ago that this was said about a very different type of state. And while the liberal democratic state is an abundant form of government, in practice this often reflects an uneasy compromise of conflicting conceptions of politics. It thus remains important to unpick the theoretical underpinnings of conceptions of the state.

Sequence and Structure Based Protein Folding Studies With Implications

As the expression of the genetic blueprint, proteins are at the heart of all biological systems. The ever increasing set of available protein structures has taught us that diversity is the hallmark of their architecture, a fundamental characteristic that enables them to perform the vast array of functionality upon which all of life depends. This diversity, however, is central to one of the most challenging problems in molecular biology: how does a folding polypeptide chain navigate its way through all of the myriad of possible conformations to find its own particular biologically active form? With few overarching structural principles to draw upon that can be applied to all protein architecture, the search for a solution to the protein folding problem has yet to produce an algorithm that can explain and duplicate this fundamental biological process. In this thesis, we take a two-pronged approach for investigating the protein folding process. Our initial statistical studies of the distributions of hydrophobic and hydrophilic residues within α-helices and β-sheets suggest (i) that hydrophobicity plays a critical role in helix and sheet formation; and (ii) that the nucleation of these motifs may result in largely unidirectional growth. Most tellingly, from an examination of the amino acids found in the smallest β-sheets, we do not find any evidence of a β-nucleating code in the primary protein sequence. Complementing these statistical analyses, we have analyzed the structural environments of several ever-widening aspects of protein topology. Our examination of the gaps between strands in the smallest β-sheets reveals a common organizational principle underlying β-formation involving strands separated by large sequential gaps: with very few exceptions, these large gaps fold into single, compact structural modules, bringing the β-strands that are otherwise far apart in the sequence close together in space. We conclude, therefore, that β-nucleation in the smallest sheets results from the co-location of two strands that are either local in sequence, or local in space following prior folding events. A second study of larger β-sheets both corroborates and extends these findings: virtually all large sequential gaps between pairs of β-strands organize themselves into an hierarchical arrangement, creating a bread-crumb model of go-and-come-back structural organization that ultimately juxtaposes two strands of a parental β-structure that are far apart in the sequence in close spatial proximity. In a final study, we have formalized this go-and-come-back notion into the concept of anti-parallel double-strandedness (DS), and measure this property across protein architecture in general. With over 90% of all residues in a large, non-redundant set of protein structures classified as DS, we conclude that DS is a unifying structural principle that underpins all globular proteins. We postulate, moreover, that this one simple principle, anti-parallel double-strandedness, unites protein structure, protein folding and protein evolution.

A FUNCTIONAL, COMPARATIVE AND CLINICAL ANALYSIS OF SPERM-BORNE OOCYTE ACTIVATING FACTOR, PAWP

Successful fertilization depends upon the activation of metaphase II arrested oocytes by sperm-borne oocyte activating factor (SOAF). Failure of oocyte activation is considered as the cause of treatment failure in a proportion of infertile couples. SOAF induces the release of intracellular calcium in oocyte which leads to meiotic resumption and pronuclear formation. Calcium release is either in the form of single calcium transient in echinoderm and amphibian oocytes or several calcium oscillations in ascidian and mammalian oocytes. Although the SOAF attributes are established, it is not clear which sperm protein(s) play such role. Sperm postacrosomal WW binding protein (PAWP) satisfies a developmental criteria set for a candidate SOAF. This study shows that recombinant human PAWP protein or its transcript acts upstream of calcium release and fully activates the amphibian and mammalian oocytes. Interference trials provided evidence for the first time that PAWP mediates sperm-induced intracellular calcium release through a PPXY/WWI domain module in Xenopus, mouse and human oocytes. Clinical applications of PAWP were further investigated by prospective study on the sperm samples from patients undergoing intracytoplasmic sperm injection (ICSI). PAWP expression level, analyzed by flow cytometry, was correlated to ICSI success rate and embryonic development. This study also explored the developmental expression of the other SOAF candidate, PLCζ in male reproductive system and its function during fertilization. Our findings showed for the first time that PLCζ most likely binds to the sperm head surface during epididymal passage and is expressed in epididymis. We demonstrated that PLCζ is also compartmentalized early in spermiogenesis and thus could play an important role during spermiogenesis. Detailed analysis of in vitro fertilization revealed that PLCζ disappears from sperm head during acrosome reaction and is not detectable during sperm incorporation into the oocyte cytoplasm. In conclusion, this dissertation provides evidence for the essential non-redundant role of sperm PAWP in amphibian and mammalian fertilization; recommends PAWP as a biomarker for prediction of ICSI outcomes in infertile couples; and proposes that sperm PLCζ may have functions other than inducing oocyte activation during fertilization.

Cytohesin Binder and Regulator (Cybr) is Not Essential for T- and Dendritic-Cell Activation and Differentiation

Cybr (also known as Cytip, CASP, and PSCDBP) is an interleukin-12-induced gene expressed exclusively in hematopoietic cells and tissues that associates with Arf guanine nucleotide exchange factors known as cytohesins. Cybr levels are dynamically regulated during T-cell development in the thymus and upon activation of peripheral T cells. In addition, Cybr is induced in activated dendritic cells and has been reported to regulate dendritic cell (DC)-T-cell adhesion. Here we report the generation and characterization of Cybr-deficient mice. Despite the selective expression in hematopoietic cells, there was no intrinsic defect in T- or B-cell development or function in Cybr-deficient mice. The adoptive transfer of Cybr-deficient DCs showed that they migrated efficiently and stimulated proliferation and cytokine production by T cells in vivo. However, competitive stem cell repopulation experiments showed a defect in the abilities of Cybr-deficient T cells to develop in the presence of wild-type precursors. These data suggest that Cybr is not absolutely required for hematopoietic cell development or function, but stem cells lacking Cybr are at a developmental disadvantage compared to wild-type cells. Collectively, these data demonstrate that despite its selective expression in hematopoietic cells, the role of Cybr is limited or largely redundant. Previous in vitro studies using overexpression or short interfering RNA inhibition of the levels of Cybr protein appear to have overestimated its immunological role.

Rasch Analysis of the Daily Living Tasks Dependent on Vision (DLTV)

PURPOSE. To examine internal consistency, refine the response scale, and obtain a linear scoring system for the visual function instrument, the Daily Living Tasks Dependent on Vision (DLTV). METHODS. Data were available from 186 participants with a clinical diagnosis of AMD who completed the 22-item DLTV (DLTV-22) according to four-point ordinal response scale. An independent group of 386 participants with AMD were administered a reduced version of the DLTV with 11 items (DLTV-11), according to a five-point response scale. Rasch analysis was performed on both datasets and used to generate item statistics for measure order, response odds ratios per item and per person, and infit and outfit mean square statistics. The Rasch output from the DLTV-22 was examined to identify redundant items and for factorial validity and person item measure separation reliabilities. RESULTS. The average rating for the DLTV-22 changed monotonically with the magnitude of the latent person trait. The expected versus observed average measures were extremely close, with step calibrations evenly separated for the four-point ordinal scale. In the case of the DLTV-11, step calibrations were not as evenly separated, suggesting that the five-point scale should be reduced to either a four- or three-point scale. Five items in the DLTV-22 were removed, and all 17 remaining items had good infit and outfit mean squares. PCA with residuals from Rasch analysis identified two domains containing 7 and 10 items each. The domains had high person separation reliabilities (0.86 and 0.77 for domains 1 and 2, respectively) and item measure reliabilities (0.99 and 0.98 for domains 1 and 2, respectively). CONCLUSIONS. With the improved internal consistency, establishment of the accuracy and precision of the rating scale for the DLTV and the establishment of a valid domain structure we believe that it constitutes a useful instrument for assessing visual function in older adults with age-related macular degeneration.

Improved Process Monitoring Using Nonlinear Principal Component Models

This paper presents two new approaches for use in complete process monitoring. The firstconcerns the identification of nonlinear principal component models. This involves the application of linear
principal component analysis (PCA), prior to the identification of a modified autoassociative neural network (AAN) as the required nonlinear PCA (NLPCA) model. The benefits are that (i) the number of the reduced set of linear principal components (PCs) is smaller than the number of recorded process variables, and (ii) the set of PCs is better conditioned as redundant information is removed. The result is a new set of input data for a modified neural representation, referred to as a T2T network. The T2T NLPCA model is then used for complete process monitoring, involving fault detection, identification and isolation. The second approach introduces a new variable reconstruction algorithm, developed from the T2T NLPCA model. Variable reconstruction can enhance the findings of the contribution charts still widely used in industry by reconstructing the outputs from faulty sensors to produce more accurate fault isolation. These ideas are illustrated using recorded industrial data relating to developing cracks in an industrial glass melter process. A comparison of linear and nonlinear models, together with the combined use of contribution charts and variable reconstruction, is presented.

Learning soft computing control strategies in a modular neural network architecture

Modelling and control of nonlinear dynamical systems is a challenging problem since the dynamics of such systems change over their parameter space. Conventional methodologies for designing nonlinear control laws, such as gain scheduling, are effective because the designer partitions the overall complex control into a number of simpler sub-tasks. This paper describes a new genetic algorithm based method for the design of a modular neural network (MNN) control architecture that learns such partitions of an overall complex control task. Here a chromosome represents both the structure and parameters of an individual neural network in the MNN controller and a hierarchical fuzzy approach is used to select the chromosomes required to accomplish a given control task. This new strategy is applied to the end-point tracking of a single-link flexible manipulator modelled from experimental data. Results show that the MNN controller is simple to design and produces superior performance compared to a single neural network (SNN) controller which is theoretically capable of achieving the desired trajectory. (C) 2003 Elsevier Ltd. All rights reserved.

PLS modelling and fault detection on the Tennessee Eastman benchmark

This paper describes the application of multivariate regression techniques to the Tennessee Eastman benchmark process for modelling and fault detection. Two methods are applied : linear partial least squares, and a nonlinear variant of this procedure using a radial basis function inner relation. The performance of the RBF networks is enhanced through the use of a recently developed training algorithm which uses quasi-Newton optimization to ensure an efficient and parsimonious network; details of this algorithm can be found in this paper. The PLS and PLS/RBF methods are then used to create on-line inferential models of delayed process measurements. As these measurements relate to the final product composition, these models suggest that on-line statistical quality control analysis should be possible for this plant. The generation of `soft sensors' for these measurements has the further effect of introducing a redundant element into the system, redundancy which can then be used to generate a fault detection and isolation scheme for these sensors. This is achieved by arranging the sensors and models in a manner comparable to the dedicated estimator scheme of Clarke et al. 1975, IEEE Trans. Pero. Elect. Sys., AES-14R, 465-473. The effectiveness of this scheme is demonstrated on a series of simulated sensor and process faults, with full detection and isolation shown to be possible for sensor malfunctions, and detection feasible in the case of process faults. Suggestions for enhancing the diagnostic capacity in the latter case are covered towards the end of the paper.

Effects of Constraint Errors on Parallel Manipulators with Decoupled Motion

From perspective of structure synthesis, certain special geometric constraints, such as joint axes intersecting at one point or perpendicular to each other, are necessary in realizing the end-effector motion of kinematically decoupled parallel manipulators (PMs) along individual motion axes. These requirements are difficult to achieve in the actual system due to assembly errors and manufacturing tolerances. Those errors that violate the geometric constraint requirements are termed “constraint errors”. The constraint errors usually are more troublesome than other manipulator errors because the decoupled motion characteristics of the manipulator may no longer exist and the decoupled kinematic models will be rendered useless due to these constraint errors. Therefore, identification and prevention of these constraint errors in initial design and manufacturing stage are of great significance. In this article, three basic types of constraint errors are identified, and an approach to evaluate the effects of constraint errors on decoupling characteristics of PMs is proposed. This approach is illustrated by a 6-DOF PM with decoupled translation and rotation. The results show that the proposed evaluation method is effective to guide design and assembly.

A Paradoxical Effect of Systemic IL-23 in EAE – Limitation of Autoimmune Inflammatory Demyelination

The heterodimeric cytokine IL-23 plays a non-redundant function in the development of cell-mediated, organspecific autoimmune diseases such as experimental autoimmune encephalomyelitis (EAE). To further characterize the mechanisms of action of IL-23 in autoimmune inflammation, we administered IL-23 systemically at different time points during both relapsing and chronic EAE. Surprisingly, we found suppression of disease in all treatment protocols. We observed a reduction in the number of activated macrophages and microglia in the CNS, while T cell infiltration was not significantly affected. Disease suppression correlated with reduced expansion of myelin-reactive T cells, loss of T-bet expression, loss of lymphoid structures, and increased production of IL-6 and IL-4. Here we describe an unexpected function of exogenous IL-23 in limiting the scope and extent of organ-specific autoimmunity.

How to estimate scavenger fish abundance using baited camera data

Baited cameras are often used for abundance estimation wherever alternative techniques are precluded, e.g. in abyssal systems and areas such as reefs. This method has thus far used models of the arrival process that are deterministic and, therefore, permit no estimate of precision.
Furthermore, errors due to multiple counting of fish and missing those not seen by the camera have restricted the technique to using only the time of first arrival, leaving a lot of data redundant. Here, we reformulate the arrival process using a stochastic model, which allows the precision of abundance
estimates to be quantified. Assuming a non-gregarious, cross-current-scavenging fish, we show that prediction of abundance from first arrival time is extremely uncertain. Using example data, we show
that simple regression-based prediction from the initial (rising) slope of numbers at the bait gives good precision, accepting certain assumptions. The most precise abundance estimates were obtained
by including the declining phase of the time series, using a simple model of departures, and taking account of scavengers beyond the camera’s view, using a hidden Markov model.

Workspace evaluation of manipulators through finite-partition of SE(3)

Workspace analysis and optimization are important in a manipulator design. As the complete workspace of a 6-DOF manipulator is embedded into a 6-imensional space, it is difficult to quantify and qualify it. Most literatures only considered the 3-D sub workspaces of the complete 6-D workspace. In this paper, a finite-partition approach of the Special Euclidean group SE(3) is proposed based on the topology properties of SE(3), which is the product of Special Orthogonal group SO(3) and R^3. It is known that the SO(3) is homeomorphic to a solid ball D^3 with antipodal points identified while the geometry of R^3 can be regarded as a cuboid. The complete 6-D workspace SE(3) is at the first time parametrically and proportionally partitioned into a number of elements with uniform convergence based on its geometry. As a result, a basis volume element of SE(3) is formed by the product of a basis volume element of R^3 and a basis volume element of SO(3), which is the product of a basis volume element of D^3 and its associated integration measure. By this way, the integration of the complete 6-D workspace volume becomes the simple summation of the basis volume elements of SE(3). Two new global performance indices, i.e., workspace volume ratio Wr and global condition index GCI, are defined over the complete 6-D workspace. A newly proposed 3 RPPS parallel manipulator is optimized based on this finite-partition approach. As a result, the optimal dimensions for maximal workspace are obtained, and the optimal performance points in the workspace are identified.

From inconsistency handling to non-canonical requirements management: A logical perspective

As a class of defects in software requirements specification, inconsistency has been widely studied in both requirements engineering and software engineering. It has been increasingly recognized that maintaining consistency alone often results in some other types of non-canonical requirements, including incompleteness of a requirements specification, vague requirements statements, and redundant requirements statements. It is therefore desirable for inconsistency handling to take into account the related non-canonical requirements in requirements engineering. To address this issue, we propose an intuitive generalization of logical techniques for handling inconsistency to those that are suitable for managing non-canonical requirements, which deals with incompleteness and redundancy, in addition to inconsistency. We first argue that measuring non-canonical requirements plays a crucial role in handling them effectively. We then present a measure-driven logic framework for managing non-canonical requirements. The framework consists of five main parts, identifying non-canonical requirements, measuring them, generating candidate proposals for handling them, choosing commonly acceptable proposals, and revising them according to the chosen proposals. This generalization can be considered as an attempt to handle non-canonical requirements along with logic-based inconsistency handling in requirements engineering.

Bio-port Free Energy City

In an age of depleting oil reserves and increasing energy demand, humanity faces a stalemate between environmentalism and politics, where crude oil is traded at record highs yet the spotlight on being ‘green’ and sustainable is stronger than ever. A key theme on today’s political agenda is energy independence from foreign nations, and the United Kingdom is bracing itself for nuclear renaissance which is hoped will feed the rapacious centralised system that the UK is structured upon. But what if this centralised system was dissembled, and in its place stood dozens of cities which grow and monopolise from their own energy? Rather than one dominant network, would a series of autonomous city-based energy systems not offer a mutually profitable alternative? Bio-Port is a utopian vision of a ‘Free Energy City’ set in Liverpool, where the old dockyards, redundant space, and the Mersey Estuary have been transformed into bio-productive algae farms. Bio-Port Free Energy City is a utopian ideal, where energy is superfluous; in fact so abundant that meters are obsolete. The city functions as an energy generator and thrives from its own product with minimal impact upon the planet it inhabits. Algaculture is the fundamental energy source, where a matrix of algae reactors swamp the abandoned dockyards; which themselves have been further expanded and reclaimed from the River Mersey. Each year, the algae farm is capable of producing over 200 million gallons of bio-fuel, which in-turn can produce enough electricity to power almost 2 million homes. The metabolism of Free-Energy City is circular and holistic, where the waste products of one process are simply the inputs of a new one. Livestock farming – once traditionally a high-carbon countryside exercise has become urbanised. Cattle are located alongside the algae matrix, and waste gases emitted by farmyards and livestock are largely sequestered by algal blooms or anaerobically converted to natural gas. Bio-Port Free Energy City mitigates the imbalances between ecology and urbanity, and exemplifies an environment where nature and the human machine can function productively and in harmony with one another. According to James Lovelock, our population has grown in number to the point where our presence is perceptibly disabling the planet, but in order to reverse the effects of our humanist flaws, it is vital that new eco-urban utopias are realised.

Max separation clustering for feature extraction from Optical Emission Spectroscopy Data

This paper proposes max separation clustering (MSC), a new non-hierarchical clustering method used for feature extraction from optical emission spectroscopy (OES) data for plasma etch process control applications. OES data is high dimensional and inherently highly redundant with the result that it is difficult if not impossible to recognize useful features and key variables by direct visualization. MSC is developed for clustering variables with distinctive patterns and providing effective pattern representation by a small number of representative variables. The relationship between signal-to-noise ratio (SNR) and clustering performance is highlighted, leading to a requirement that low SNR signals be removed before applying MSC. Experimental results on industrial OES data show that MSC with low SNR signal removal produces effective summarization of the dominant patterns in the data.