Minimal regulation of platelet activity by PECAM-1.

PECAM-1 is a member of the superfamily of immunoglobulins (Ig) and is expressed on platelets at moderate level. PECAM-1 has been reported to have contrasting effects on platelet activation by the collagen receptor GPVI and the integrin, alphaIIbbeta3, even though both receptors signal through Src-kinase regulation of PLCgamma2. The present study compares the role of PECAM-1 on platelet activation by these two receptors and by the lectin receptor, CLEC-2, which also signals via PLCgamma2. Studies using PECAM-1 knockout-mice and cross-linking of PECAM-1 using specific antibodies demonstrated a minor inhibitory role on platelet responses to the above three receptors and also under some conditions to the G-protein agonist thrombin. The degree of inhibition was considerably less than that produced by PGI2, which elevates cAMP. There was no significant difference in thrombus formation on collagen in PECAM-1-/- platelets relative to litter-matched controls. The very weak inhibitory effect of PECAM-1 on platelet activation relative to that of PGI2 indicate that the Ig-receptor is not a major regulator of platelet activation. PECAM-1 has been reported to have contrasting effects on platelet activation. The present study demonstrates a very mild or negligible effect on platelet activation in response to stimulation by a variety of agonists, thereby questioning the physiological role of the immunoglobulin receptor as a major regulator of platelet activation.

Managing the complexity of information flow for construction small and medium-sized enterprises (CSMEs) using system dynamics and collaborative technologies

With the increase in e-commerce and the digitisation of design data and information,the construction sector has become reliant upon IT infrastructure and systems. The design and production process is more complex, more interconnected, and reliant upon greater information mobility, with seamless exchange of data and information in real time. Construction small and medium-sized enterprises (CSMEs), in particular,the speciality contractors, can effectively utilise cost-effective collaboration-enabling technologies, such as cloud computing, to help in the effective transfer of information and data to improve productivity. The system dynamics (SD) approach offers a perspective and tools to enable a better understanding of the dynamics of complex systems. This research focuses upon system dynamics methodology as a modelling and analysis tool in order to understand and identify the key drivers in the absorption of cloud computing for CSMEs. The aim of this paper is to determine how the use of system dynamics (SD) can improve the management of information flow through collaborative technologies leading to improved productivity. The data supporting the use of system dynamics was obtained through a pilot study consisting of questionnaires and interviews from five CSMEs in the UK house-building sector.

On the cardinality and complexity of the set of codings for self-similar sets with positive Lebesgue measure

Let λ1,…,λn be real numbers in (0,1) and p1,…,pn be points in Rd. Consider the collection of maps fj:Rd→Rd given by fj(x)=λjx+(1−λj)pj. It is a well known result that there exists a unique nonempty compact set Λ⊂Rd satisfying Λ=∪nj=1fj(Λ). Each x∈Λ has at least one coding, that is a sequence (ϵi)∞i=1 ∈{1,…,n}N that satisfies limN→∞fϵ1…fϵN(0)=x. We study the size and complexity of the set of codings of a generic x∈Λ when Λ has positive Lebesgue measure. In particular, we show that under certain natural conditions almost every x∈Λ has a continuum of codings. We also show that almost every x∈Λ has a universal coding. Our work makes no assumptions on the existence of holes in Λ and improves upon existing results when it is assumed Λ contains no holes.

Causation, complexity, and the concert: the pragmatics of causal explanation in international relations

A causal explanation provides information about the causal history of whatever is being explained. However, most causal histories extend back almost infinitely and can be described in almost infinite detail. Causal explanations therefore involve choices about which elements of causal histories to pick out. These choices are pragmatic: they reflect our explanatory interests. When adjudicating between competing causal explanations, we must therefore consider not only questions of epistemic adequacy (whether we have good grounds for identifying certain factors as causes) but also questions of pragmatic adequacy (whether the aspects of the causal history picked out are salient to our explanatory interests). Recognizing that causal explanations differ pragmatically as well as epistemically is crucial for identifying what is at stake in competing explanations of the relative peacefulness of the nineteenth-century Concert system. It is also crucial for understanding how explanations of past events can inform policy prescription.

An LDA and probability-based classifier for the diagnosis of Alzheimer's Disease from structural MRI

In this paper a custom classification algorithm based on linear discriminant analysis and probability-based weights is implemented and applied to the hippocampus measurements of structural magnetic resonance images from healthy subjects and Alzheimer’s Disease sufferers; and then attempts to diagnose them as accurately as possible. The classifier works by classifying each measurement of a hippocampal volume as healthy controlsized or Alzheimer’s Disease-sized, these new features are then weighted and used to classify the subject as a healthy control or suffering from Alzheimer’s Disease. The preliminary results obtained reach an accuracy of 85.8% and this is a similar accuracy to state-of-the-art methods such as a Naive Bayes classifier and a Support Vector Machine. An advantage of the method proposed in this paper over the aforementioned state of the art classifiers is the descriptive ability of the classifications it produces. The descriptive model can be of great help to aid a doctor in the diagnosis of Alzheimer’s Disease, or even further the understand of how Alzheimer’s Disease affects the hippocampus.

Efficiency of evolutionary algorithms in water network pipe sizing

The pipe sizing of water networks via evolutionary algorithms is of great interest because it allows the selection of alternative economical solutions that meet a set of design requirements. However, available evolutionary methods are numerous, and methodologies to compare the performance of these methods beyond obtaining a minimal solution for a given problem are currently lacking. A methodology to compare algorithms based on an efficiency rate (E) is presented here and applied to the pipe-sizing problem of four medium-sized benchmark networks (Hanoi, New York Tunnel, GoYang and R-9 Joao Pessoa). E numerically determines the performance of a given algorithm while also considering the quality of the obtained solution and the required computational effort. From the wide range of available evolutionary algorithms, four algorithms were selected to implement the methodology: a PseudoGenetic Algorithm (PGA), Particle Swarm Optimization (PSO), a Harmony Search and a modified Shuffled Frog Leaping Algorithm (SFLA). After more than 500,000 simulations, a statistical analysis was performed based on the specific parameters each algorithm requires to operate, and finally, E was analyzed for each network and algorithm. The efficiency measure indicated that PGA is the most efficient algorithm for problems of greater complexity and that HS is the most efficient algorithm for less complex problems. However, the main contribution of this work is that the proposed efficiency ratio provides a neutral strategy to compare optimization algorithms and may be useful in the future to select the most appropriate algorithm for different types of optimization problems.

Syntactic complexity in the comprehension of wh-questions and relative clauses in typical language development and autism

This study investigates effects of syntactic complexity operationalised in terms of movement, intervention and (NP) feature similarity in the development of A’ dependencies in 4-, 6-, and 8-year old typically developing (TD) French children and children with Autism Spectrum Disorders (ASD). Children completed an off-line comprehension task testing eight syntactic structures classified in four levels of complexity: Level 0: No Movement; Level 1: Movement without (configurational) Intervention; Level 2: Movement with Intervention from an element which is maximally different or featurally ‘disjoint’ (mismatched in both lexical NP restriction and number); Level 3: Movement with Intervention from an element similar in one feature or featurally ‘intersecting’ (matched in lexical NP restriction, mismatched in number). The results show that syntactic complexity affects TD children across the three age groups, but also indicate developmental differences between these groups. Movement affected all three groups in a similar way, but intervention effects in intersection cases were stronger in younger than older children, with NP feature similarity affecting only 4-year olds. Complexity effects created by the similarity in lexical restriction of an intervener thus appear to be overcome early in development, arguably thanks to other differences of this intervener (which was mismatched in number). Children with ASD performed less well than the TD children although they were matched on non-verbal reasoning. Overall, syntactic complexity affected their performance in a similar way as in their TD controls, but their performance correlated with non-verbal abilities rather than age, suggesting that their grammatical development does not follow the smooth relation to age that is found in TD children.

Brief behavioural activation for adolescent depression: working with complexity and risk

Given the long-term negative outcomes associated with depression in adolescence, there is a pressing need to develop brief, evidence based treatments that are accessible to more young people experiencing low mood. Behavioural Activation (BA) is an effective treatment for adult depression, however little research has focused on the use of BA with depressed adolescents, particularly with briefer forms of BA. In this article we outline an adaptation of brief Behavioral Activation Treatment of Depression (BATD) designed for adolescents and delivered in eight sessions (Brief BA). This case example illustrates how a structured, brief intervention was useful for a depressed young person with a number of complicating and risk factors.

The oscillatory bioelectrical signal from plants explained by a simulated electrical model and tested using Lempel-Ziv complexity

This paper demonstrates the oscillatory characteristics of electrical signals acquired from two ornamental plant types (Epipremnum pinnatum and Philodendron scandens - Family Araceae), using a noninvasive acquisition system. The electrical signal was recorded using Ag/AgCl superficial electrodes inside a Faraday cage. The presence of the oscillatory electric generator was shown using a classical power spectral density. The Lempel and Ziv complexity measurement showed that the plant signal was not noise despite its nonlinear behavior. The oscillatory characteristics of the signal were explained using a simulated electrical model that establishes that for a frequency range from 5 to 15 Hz, the oscillatory characteristic is higher than for other frequency ranges. All results show that non-invasive electrical plant signals can be acquired with improvement of signal-to-noise ratio using a Faraday cage, and a simple electrical model is able to explain the electrical signal being generated. (C) 2010 Elsevier B.V. All rights reserved.

Mixed multiplicities and the minimal number of generator of modules

Let (R, m) be a d-dimensional Noetherian local ring. In this work we prove that the mixed Buchsbaum-Rim multiplicity for a finite family of R-submodules of R(p) of finite colength coincides with the Buchsbaum-Rim multiplicity of the module generated by a suitable superficial sequence, that is, we generalize for modules the well-known Risler-Teissier theorem. As a consequence, we give a new proof of a generalization for modules of the fundamental Rees` mixed Multiplicity theorem, which was first proved by Kirby and Rees in (1994, [8]). We use the above result to give an upper bound for the minimal number of generators of a finite colength R-submodule of R(p) in terms of mixed multiplicities for modules, which generalize a similar bound obtained by Cruz and Verma in (2000, [5]) for m-primary ideals. (C) 2009 Elsevier B.V. All rights reserved.

A new proposal for the picture changing operators in the minimal pure spinor formalism

Using a new proposal for the ""picture lowering"" operators, we compute the tree level scattering amplitude in the minimal pure spinor formalism by performing the integration over the pure spinor space as a multidimensional Cauchy-type integral. The amplitude will be written in terms of the projective pure spinor variables, which turns out to be useful to relate rigorously the minimal and non-minimal versions of the pure spinor formalism. The natural language for relating these formalisms is the. Cech-Dolbeault isomorphism. Moreover, the Dolbeault cocycle corresponding to the tree-level scattering amplitude must be evaluated in SO(10)/SU(5) instead of the whole pure spinor space, which means that the origin is removed from this space. Also, the. Cech-Dolbeault language plays a key role for proving the invariance of the scattering amplitude under BRST, Lorentz and supersymmetry transformations, as well as the decoupling of unphysical states. We also relate the Green`s function for the massless scalar field in ten dimensions to the tree-level scattering amplitude and comment about the scattering amplitude at higher orders. In contrast with the traditional picture lowering operators, with our new proposal the tree level scattering amplitude is independent of the constant spinors introduced to define them and the BRST exact terms decouple without integrating over these constant spinors.

Medical image retrieval based on complexity analysis

Texture is one of the most important visual attributes used in image analysis. It is used in many content-based image retrieval systems, where it allows the identification of a larger number of images from distinct origins. This paper presents a novel approach for image analysis and retrieval based on complexity analysis. The approach consists of a texture segmentation step, performed by complexity analysis through BoxCounting fractal dimension, followed by the estimation of complexity of each computed region by multiscale fractal dimension. Experiments have been performed with MRI database in both pattern recognition and image retrieval contexts. Results show the accuracy of the method and also indicate how the performance changes as the texture segmentation process is altered.

Complexity and anisotropy in host morphology make populations less susceptible to epidemic outbreaks

One of the challenges in epidemiology is to account for the complex morphological structure of hosts such as plant roots, crop fields, farms, cells, animal habitats and social networks, when the transmission of infection occurs between contiguous hosts. Morphological complexity brings an inherent heterogeneity in populations and affects the dynamics of pathogen spread in such systems. We have analysed the influence of realistically complex host morphology on the threshold for invasion and epidemic outbreak in an SIR (susceptible-infected-recovered) epidemiological model. We show that disorder expressed in the host morphology and anisotropy reduces the probability of epidemic outbreak and thus makes the system more resistant to epidemic outbreaks. We obtain general analytical estimates for minimally safe bounds for an invasion threshold and then illustrate their validity by considering an example of host data for branching hosts (salamander retinal ganglion cells). Several spatial arrangements of hosts with different degrees of heterogeneity have been considered in order to separately analyse the role of shape complexity and anisotropy in the host population. The estimates for invasion threshold are linked to morphological characteristics of the hosts that can be used for determining the threshold for invasion in practical applications.

Structured minimal-memory inexact quasi-Newton method and secant preconditioners for augmented Lagrangian optimization

Augmented Lagrangian methods for large-scale optimization usually require efficient algorithms for minimization with box constraints. On the other hand, active-set box-constraint methods employ unconstrained optimization algorithms for minimization inside the faces of the box. Several approaches may be employed for computing internal search directions in the large-scale case. In this paper a minimal-memory quasi-Newton approach with secant preconditioners is proposed, taking into account the structure of Augmented Lagrangians that come from the popular Powell-Hestenes-Rockafellar scheme. A combined algorithm, that uses the quasi-Newton formula or a truncated-Newton procedure, depending on the presence of active constraints in the penalty-Lagrangian function, is also suggested. Numerical experiments using the Cute collection are presented.