Relaxin stimulates leukocyte adhesion and migration through a relaxin receptor LGR7-dependent mechanism

Leukocytes are critical effectors of inflammation and tumor biology. Chemokine-like factors produced by such inflammatory sites are key mediators of tumor growth that activate leukocytic recruitment and tumor infiltration and suppress immune surveillance. Here we report that the endocrine peptide hormone, relaxin, is a regulator of leukocyte biology with properties important in recruitment to sites of inflammation. This study uses the human monocytic cell line THP-1 and normal human peripheral blood mononuclear cells to define a novel role for relaxin in regulation of leukocyte adhesion and migration. Our studies indicate that relaxin promotes adenylate cyclase activation, substrate adhesion, and migratory capacity of mononuclear leukocytes through a relaxin receptor LGR7-dependent mechanism. Relaxin-stimulated cAMP accumulation was observed to occur primarily in non-adherent cells. Relaxin stimulation results in increased substrate adhesion and increased migratory activity of leukocytes. In addition, relaxin-stimulated substrate adhesion resulted in enhanced chemotaxis to monocyte chemoattractant protein-1. These responses in THP-1 and peripheral blood mononuclear cells are relaxin dose-dependent and proportional to cAMP accumulation. We further demonstrate that LGR7 is critical for mediating these biological responses by use of RNA interference lentiviral short hairpin constructs. In summary, we provide evidence that relaxin is a novel leukocyte stimulatory agent with properties affecting adhesion and chemomigration

Multiple perspectives on engaging future engineers

Engaging future engineers is a central topic in everyday conversations on engineering education. Considerable investments have been made to make engineering more engaging, recruit and retain aspiring engineers, and to design an education to prepare future engineers. However, the impact of these efforts has been less than intended. It is imperative that the community reflects on progress and sets a more effective path for the future.

Computationally efficient methods for solving time-variable-order time-space fractional reaction-diffusion equation

Fractional differential equations are becoming more widely accepted as a powerful tool in modelling anomalous diffusion, which is exhibited by various materials and processes. Recently, researchers have suggested that rather than using constant order fractional operators, some processes are more accurately modelled using fractional orders that vary with time and/or space. In this paper we develop computationally efficient techniques for solving time-variable-order time-space fractional reaction-diffusion equations (tsfrde) using the finite difference scheme. We adopt the Coimbra variable order time fractional operator and variable order fractional Laplacian operator in space where both orders are functions of time. Because the fractional operator is nonlocal, it is challenging to efficiently deal with its long range dependence when using classical numerical techniques to solve such equations. The novelty of our method is that the numerical solution of the time-variable-order tsfrde is written in terms of a matrix function vector product at each time step. This product is approximated efficiently by the Lanczos method, which is a powerful iterative technique for approximating the action of a matrix function by projecting onto a Krylov subspace. Furthermore an adaptive preconditioner is constructed that dramatically reduces the size of the required Krylov subspaces and hence the overall computational cost. Numerical examples, including the variable-order fractional Fisher equation, are presented to demonstrate the accuracy and efficiency of the approach.

Numerical analysis of the time variable fractional order mobile-immobile advection-dispersion model

Many physical processes exhibit fractional order behavior that varies with time or space. The continuum of order in the fractional calculus allows the order of the fractional operator to be considered as a variable. In this paper, we consider the time variable fractional order mobile-immobile advection-dispersion model. Numerical methods and analyses of stability and convergence for the fractional partial differential equations are quite limited and difficult to derive. This motivates us to develop efficient numerical methods as well as stability and convergence of the implicit numerical methods for the fractional order mobile immobile advection-dispersion model. In the paper, we use the Coimbra variable time fractional derivative which is more efficient from the numerical standpoint and is preferable for modeling dynamical systems. An implicit Euler approximation for the equation is proposed and then the stability of the approximation are investigated. As for the convergence of the numerical scheme we only consider a special case, i.e. the time fractional derivative is independent of time variable t. The case where the time fractional derivative depends both the time variable t and the space variable x will be considered in the future work. Finally, numerical examples are provided to show that the implicit Euler approximation is computationally efficient.

Numerical techniques for the variable order time fractional diffusion equation

In this paper we consider the variable order time fractional diffusion equation. We adopt the Coimbra variable order (VO) time fractional operator, which defines a consistent method for VO differentiation of physical variables. The Coimbra variable order fractional operator also can be viewed as a Caputo-type definition. Although this definition is the most appropriate definition having fundamental characteristics that are desirable for physical modeling, numerical methods for fractional partial differential equations using this definition have not yet appeared in the literature. Here an approximate scheme is first proposed. The stability, convergence and solvability of this numerical scheme are discussed via the technique of Fourier analysis. Numerical examples are provided to show that the numerical method is computationally efficient. Crown Copyright © 2012 Published by Elsevier Inc. All rights reserved.

An accurate and reliable stereo matching algorithm incorporating the rank constraint

A fundamental problem faced by stereo vision algorithms is that of determining correspondences between two images which comprise a stereo pair. This paper presents work towards the development of a new matching algorithm, based on the rank transform. This algorithm makes use of both area-based and edge-based information, and is therefore referred to as a hybrid algorithm. In addition, this algorithm uses a number of matching constraints,including the novel rank constraint. Results obtained using a number of test pairs show that the matching algorithm is capable of removing a significant proportion of invalid matches. The accuracy of matching in the vicinity of edges is also improved.

Narratives of the 'everyday' in Rio de Janeiro's favelas : community photographers' attempts at generating alternative news values [Narrativas do cotidiano nas favelas do Rio de Janeiro: tentativas de construção de valores-notícia alternativos pelos fotógrafos populares]

Abstract This paper presents the partial results of an ongoing research project which investigates ethnographically community (photo)journalism media initiatives, in Rio de Janeiro, Brazil. The Viva Rio and Observatorio de Favelas (NGOs) run projects that provide favela residents with skills to take, edit and print their own (photo) journalism contents that enables community-based framing and documentation of favela live, personalities and issues. Three months of fieldwork related to these projects in Rio's favelas generated remarkable theoretical issues that represent the community photographers' attempt to establish counter news values by shifting the focus from poverty, shortages, violence and criminality to images of the ordinary life which included the myriad events that occurs in the day of the favelas. Resumo Este artigo apresenta os resultados parciais de uma pesquisa em andamento que, a partir do método etnográfico, investiga os projetos de comunicação comunitária, jornalismo e fotojornalismo, no Rio de Janeiro, Brasil. As organizações não-governamentais (ONGs) Viva Rio e Observatório de Favela apoiam projetos que objetivam tornar moradores de favelas capazes de produzir, editar e publicar as suas próprias narrativas sobre personagens e questões do cotidiano de suas comunidades. O trabalho de campo sobre estes projetos, realizado durante três meses nas favelas do Rio de Janeiro, forneceu questões teóricas relevantes que representam o esforço dos fotógrafos populares para estabelecer contra valores-notícia transferindo o foco da pobreza, escassez, violência e criminalidade para imagens do cotidiano que inclui uma miríade de eventos que acontecem no dia-a-dia das favelas.

Users segmentations for recommendation

Traditional recommendation methods provide recommendations equally to all users. In this paper, a segmentation method using the Gaussian Mixture Model (GMM) is proposed to customize users’ needs in order to offer a specific recommendation strategy to each segment. Experiment is conducted using a live online dating network data.

A semi-supervised graph-based algorithm for detecting outliers in online-social-networks

In this paper, we propose a semi-supervised approach of anomaly detection in Online Social Networks. The social network is modeled as a graph and its features are extracted to detect anomaly. A clustering algorithm is then used to group users based on these features and fuzzy logic is applied to assign degree of anomalous behavior to the users of these clusters. Empirical analysis shows effectiveness of this method.

Supply chain regulation to protect the occupational health and safety of vulnerable workers

The last two decades have witnessed a fragmentation of previously integrated systems of production and service delivery with the advent of boundary-less, networked and porous organisational forms. This trend has been associated with the growth of outsourcing and increased use of contingent workers. One consequence of these changes is the development of production/service delivery systems based on complex national and international networks of multi-tiered subcontracting increasingly labelled as supply chains. A growing body of research indicates that subcontracting and contingent work arrangements affect design and decision-making processes in ways that can seriously undermine occupational health and safety (OHS). Elaborate supply chains also present a regulatory challenge because legal responsibility for OHS is diffused amongst a wider array of parties, targeting key decision-makers is more difficult, and government agencies encounter greater logistical difficulties trying to safeguard contingent workers. In a number of industries these problems have prompted new forms of regulatory intervention, including mechanisms for sheeting legal responsibility to the top of supply chains, contractual tracking devices and increasing industry, union and community involvement in enforcement. After describing the problems just alluded to this paper examines recent efforts to regulate supply chains to safeguard OHS in the United Kingdom and Australia.

Post-exercise cold water immersion attenuates acute anabolic signalling and long-term adaptations in muscle to strength training

We investigated functional, morphological and molecular adaptations to strength training exercise and cold water immersion (CWI) through two separate studies. In one study, 21 physically active men strength trained for 12 weeks (2 d⋅wk–1), with either 10 min of CWI or active recovery (ACT) after each training session. Strength and muscle mass increased more in the ACT group than in the CWI group (P<0.05). Isokinetic work (19%), type II muscle fibre cross-sectional area (17%) and the number of myonuclei per fibre (26%) increased in the ACT group (all P<0.05) but not the CWI group. In another study, nine active men performed a bout of single-leg strength exercises on separate days, followed by CWI or ACT. Muscle biopsies were collected before and 2, 24 and 48 h after exercise. The number of satellite cells expressing neural cell adhesion molecule (NCAM) (10−30%) and paired box protein (Pax7)(20−50%) increased 24–48 h after exercise with ACT. The number of NCAM+ satellitecells increased 48 h after exercise with CWI. NCAM+- and Pax7+-positivesatellite cell numbers were greater after ACT than after CWI (P<0.05). Phosphorylation of p70S6 kinaseThr421/Ser424 increased after exercise in both conditions but was greater after ACT (P<0.05). These data suggest that CWI attenuates the acute changes in satellite cell numbers and activity of kinases that regulate muscle hypertrophy, which may translate to smaller long-term training gains in muscle strength and hypertrophy. The use of CWI as a regular post-exercise recovery strategy should be reconsidered.

Stochastic model for simulating maize yield

Maize is one of the most important crops in the world. The products generated from this crop are largely used in the starch industry, the animal and human nutrition sector, and biomass energy production and refineries. For these reasons, there is much interest in figuring the potential grain yield of maize genotypes in relation to the environment in which they will be grown, as the productivity directly affects agribusiness or farm profitability. Questions like these can be investigated with ecophysiological crop models, which can be organized according to different philosophies and structures. The main objective of this work is to conceptualize a stochastic model for predicting maize grain yield and productivity under different conditions of water supply while considering the uncertainties of daily climate data. Therefore, one focus is to explain the model construction in detail, and the other is to present some results in light of the philosophy adopted. A deterministic model was built as the basis for the stochastic model. The former performed well in terms of the curve shape of the above-ground dry matter over time as well as the grain yield under full and moderate water deficit conditions. Through the use of a triangular distribution for the harvest index and a bivariate normal distribution of the averaged daily solar radiation and air temperature, the stochastic model satisfactorily simulated grain productivity, i.e., it was found that 10,604 kg ha(-1) is the most likely grain productivity, very similar to the productivity simulated by the deterministic model and for the real conditions based on a field experiment. © 2012 American Society of Agricultural and Biological Engineers.