Jagged/Notch signalling is required for a subset of TGFβ1 responses in human kidney epithelial cells.

The Jagged/Notch pathway has been implicated in TGFß1 responses in epithelial cells in diabetic nephropathy and other fibrotic conditions in vivo. Here, we identify that Jagged/Notch signalling is required for a subset of TGFß1-stimulated gene responses in human kidney epithelial cells in vitro. TGFß1 treatment of HK-2 and RPTEC cells for 24 h increased Jagged1 (a Notch ligand) and Hes1 (a Notch target) mRNA. This response was inhibited by co-incubation with Compound E, an inhibitor of ?-secretase (GSI), an enzyme required for Notch receptor cleavage and transcription regulation. In both cell types, TGFß1-responsive genes associated with epithelial–mesenchymal transition such as E-cadherin and vimentin were also affected by ?-secretase inhibition, but other TGFß1 targets such as connective tissue growth factor (CTGF) and thrombospondin-1 (THBS1) were not. TGFß1-induced changes in Jagged1 expression preceded EMT-associated gene changes, and co-incubation with GSI altered TGFß1-induced changes in cell shape and cytoskeleton. Transfection of cells with the activated, cleaved form of Notch (NICD) triggered decreased expression of E-cadherin in the absence of TGFß1, but did not affect a-smooth muscle actin expression, suggesting differential requirements for Notch signalling within the TGFß1-responsive gene subset. Increased Jagged1 expression upon TGFß1 exposure required Smad3 signalling, and was also regulated by PI3K and ERK. These data suggest that Jagged/Notch signalling is required for a subset of TGFß1-responsive genes, and that complex signalling pathways are involved in the crosstalk between TGFß1 and Notch cascades in kidney epithelia.


--------------------------------------------------------------------------------

Maturity Model for Supply Chain Relationships in Construction

This study explores the special characteristics of the construction industry and develops a maturity model for measuring and improving the relationships between the key players of a construction supply chain. The model adopts the capability maturity methodology and defines four maturity levels of construction supply chain relationships. It is in a matrix format, consisting of 24 assessment criteria in eight categories at each maturity level. It also provides three different ways of using the model. The model is evaluated through a series of expert interviews. A case study is also presented to demonstrate the application of this model in practice.

Incorporating Higher Moments into Value at Risk Forecasting

Value-at-risk (VaR) forecasting generally relies on a parametric density function of portfolio returns that ignores higher moments or assumes them constant. In this paper, we propose a simple approach to forecasting of a portfolio VaR. We employ the Gram-Charlier expansion (GCE) augmenting the standard normal distribution with the first four moments, which are allowed to vary over time. In an extensive empirical study, we compare the GCE approach to other models of VaR forecasting and conclude that it provides accurate and robust estimates of the realized VaR. In spite of its simplicity, on our dataset GCE outperforms other estimates that are generated by both constant and time-varying higher-moments models.

Dynamic Density Forecasts for Multivariate Asset Returns

We propose a simple and flexible framework for forecasting the joint density of asset returns. The multinormal distribution is augmented with a polynomial in (time-varying) non-central co-moments of assets. We estimate the coefficients of the polynomial via the Method of Moments for a carefully selected set of co-moments. In an extensive empirical study, we compare the proposed model with a range of other models widely used in the literature. Employing a recently proposed as well as standard techniques to evaluate multivariate forecasts, we conclude that the augmented joint density provides highly accurate forecasts of the “negative tail” of the joint distribution.

Food-web structure in low- and high-dimensional trophic niche spaces

A question central to modelling and, ultimately, managing food webs concerns the dimensionality of trophic niche space, that is, the number of independent traits relevant for determining consumer-resource links. Food-web topologies can often be interpreted by assuming resource traits to be specified by points along a line and each consumer's diet to be given by resources contained in an interval on this line. This phenomenon, called intervality, has been known for 30 years and is widely acknowledged to indicate that trophic niche space is close to one-dimensional. We show that the degrees of intervality observed in nature can be reproduced in arbitrary-dimensional trophic niche spaces, provided that the processes of evolutionary diversification and adaptation are taken into account. Contrary to expectations, intervality is least pronounced at intermediate dimensions and steadily improves towards lower- and higher-dimensional trophic niche spaces.

Dynamic pricing model and algorithm for perishable products with fuzzy demand (ABS 2* Journal)

This paper studies the dynamic pricing problem of selling fixed stock of perishable items over a finite horizon, where the decision maker does not have the necessary historic data to estimate the distribution of uncertain demand, but has imprecise information about the quantity demand. We model this uncertainty using fuzzy variables. The dynamic pricing problem based on credibility theory is formulated using three fuzzy programming models, viz.: the fuzzy expected revenue maximization model, a-optimistic revenue maximization model, and credibility maximization model. Fuzzy simulations for functions with fuzzy parameters are given and embedded into a genetic algorithm to design a hybrid intelligent algorithm to solve these three models. Finally, a real-world example is presented to highlight the effectiveness of the developed model and algorithm.

Robust Dynamic Pricing Over Infinite Horizon in The Presence of Model Uncertainty( 2* Journal)

This paper studies a problem of dynamic pricing faced by a retailer with limited inventory, uncertain about the demand rate model, aiming to maximize expected discounted revenue over an infinite time horizon. The retailer doubts his demand model which is generated by historical data and views it as an approximation. Uncertainty in the demand rate model is represented by a notion of generalized relative entropy process, and the robust pricing problem is formulated as a two-player zero-sum stochastic differential game. The pricing policy is obtained through the Hamilton-Jacobi-Isaacs (HJI) equation. The existence and uniqueness of the solution of the HJI equation is shown and a verification theorem is proved to show that the solution of the HJI equation is indeed the value function of the pricing problem. The results are illustrated by an example with exponential nominal demand rate.

A framework for collaborative working environments

To utilize the advantages of existing and emerging Internet techniques and to meet the demands for a new generation of collaborative working environments, a framework with an upperware–middleware architecture is proposed, which consists of four layers: resource layer, middleware layer, upperware layer and application layer. The upperware contains intelligent agents and plug/play facilities; the former coordinates and controls multiple middleware techniques such as Grid computing, Web-services and mobile agents, while the latter are used for the applications, such as semantic CAD, to plug and loose couple into the system. The method of migrating legacy software using automatic wrapper generation technique is also presented. A prototype mobile environment for collaborative product design is presented to illustrate the utilization of the CWE framework in collaborative design and manufacture.

Somatic point mutations in mtDNA control region are influenced by genetic background and associated with healthy aging: a GEHA stud

Tissue specific somatic mutations occurring in the mtDNA control region have been proposed to provide a survival advantage. Data on twins and on relatives of long-lived subjects suggested that the occurrence/accumulation of these mutations may be genetically influenced. To further investigate control region somatic heteroplasmy in the elderly, we analyzed the segment surrounding the nt 150 position (previously reported as specific of Leukocytes) in various types of leukocytes obtained from 195 ultra-nonagenarians sib-pairs of Italian or Finnish origin collected in the frame of the GEHA Project. We found a significant correlation of the mtDNA control region heteroplasmy between sibs, confirming a genetic influence on this phenomenon. Furthermore, many subjects showed heteroplasmy due to mutations different from the C150T transition. In these cases heteroplasmy was correlated within sibpairs in Finnish and northern Italian samples, but not in southern Italians. This suggested that the genetic contribution to control region mutations may be population specific. Finally, we observed a possible correlation between heteroplasmy and Hand Grip strength, one of the best markers of physical performance and of mortality risk in the elderly. Our study provides new evidence on the relevance of mtDNA somatic mutations in aging and longevity and confirms that the occurrence of specific point mutations in the mtDNA control region may represent a strategy for the age-related remodelling of organismal functions.

Critical Success Factors for Transfer-Operate-Transfer Urban Water Supply Projects in China

Over the years, build-operate-transfer (BOT) has continuously attracted research interests. Many studies on BOT have been carried out. Variations of BOT such as build-own-operate-transfer and build-own-operate have also been reported in some relevant publications. However, few investigations thus far have been conducted for transfer-operate-transfer (TOT). Therefore, there is a knowledge gap in this particular field. TOT is a new model that is suitable for existing infrastructure and public utility projects formerly funded by the governments and currently operated by state-owned enterprises. It refers to the transfer of a running public project to a foreign business or domestic private entity. Based on four case studies carried out in the Chinese water supply industry, this paper examines why there is an increasing need for TOT projects and identifies the distinctive features of TOT practice in China. This is followed by an introduction of a framework of critical success factors (CSFs) for TOT projects. The most important factors include project profitability, asset quality, fair risk allocation, competitive tendering, internal coordination within government, employment of professional advisors, corporate governance, and government supervision. The identification of CSFs provides a useful guidance to project parties planning to participate in TOT practice.

Transaction Costs and Organizational Learning in Strategic Oursourcing Relationships

The present paper examines the role of organisational learning and transaction costs economics in strategic outsourcing decisions. Interorganisational learning is critical to competitive success, and organisations often learn more effectively by collaborating with other organisations. However, learning processes may also complicate the process of forming interorganisational partnerships which may increase transaction costs. Based on the literature, the authors develop refutable implications for outsourcing supply chain logistics and a sample of 121 firms in the supply chain logistics industry is used to test the hypotheses. The results show that trust and transaction costs are significant and substantial drivers of strategic outsourcing of supply chain logistics (a strategic flexibility action). Learning intent and knowledge acquisition have no significant influence on the decision to outsource supply chain logistics. The paper concludes with a discussion of the different and often conflicting implications for managing interorganisational learning processes.

Discrete Conditional Phase-type models utilising classification trees: Application to modelling health service capacities

Discrete Conditional Phase-type (DC-Ph) models consist of a process component (survival distribution) preceded by a set of related conditional discrete variables. This paper introduces a DC-Ph model where the conditional component is a classification tree. The approach is utilised for modelling health service capacities by better predicting service times, as captured by Coxian Phase-type distributions, interfaced with results from a classification tree algorithm. To illustrate the approach, a case-study within the healthcare delivery domain is given, namely that of maternity services. The classification analysis is shown to give good predictors for complications during childbirth. Based on the classification tree predictions, the duration of childbirth on the labour ward is then modelled as either a two or three-phase Coxian distribution. The resulting DC-Ph model is used to calculate the number of patients and associated bed occupancies, patient turnover, and to model the consequences of changes to risk status.

Creating advantage in peripheral regions: The role of publicly funded R&D centres

Regional investment in R&D, technological development and innovation is perceived as being strongly associated with productivity, growth and sustained international competitiveness. One policy instrument by which policy makers have attempted to create regional advantage has been the establishment of publicly funded research centres (PRCs). In this paper we develop a logic model for this type of regional intervention and examine the outputs and longer-term outcomes from a group of (18) publicly funded R&D centres. Our results suggest some positive regional impacts but also identify significant differences in terms of innovation, additionality and sustainability between university-based and company-based PRCs. University-based PRCs have higher levels of short-term additionality, demonstrate higher levels of organisational innovation but prove less sustainable. Company-based PRCs demonstrate more partial additionality in the short-term but ultimately prove more sustainable.

Using simulation to assess cardiac first-responder schemes exhibiting stochastic and spatial complexities

A Monte-Carlo simulation-based model has been constructed to assess a public health scheme involving mobile-volunteer cardiac First-Responders. The scheme being assessed aims to improve survival of Sudden-Cardiac-Arrest (SCA) patients, through reducing the time until administration of life-saving defibrillation treatment, with volunteers being paged to respond to possible SCA incidents alongside the Emergency Medical Services. The need for a model, for example, to assess the impact of the scheme in different geographical regions, was apparent upon collection of observational trial data (given it exhibited stochastic and spatial complexities). The simulation-based model developed has been validated and then used to assess the scheme's benefits in an alternative rural region (not a part of the original trial). These illustrative results conclude that the scheme may not be the most efficient use of National Health Service resources in this geographical region, thus demonstrating the importance and usefulness of simulation modelling in aiding decision making.