TESTING FOR STATIONARITY IN HETEROGENEOUS PANEL DATA IN THE CASE OF MODEL MISSPECIFICATION

This paper investigates the performance of the tests proposed by Hadri and by Hadri and Larsson for testing for stationarity in heterogeneous panel data under model misspecification. The panel tests are based on the well known KPSS test (cf. Kwiatkowski et al.) which considers two models: stationarity around a deterministic level and stationarity around a deterministic trend. There is no study, as far as we know, on the statistical properties of the test when the wrong model is used. We also consider the case of the simultaneous presence of the two types of models in a panel. We employ two asymptotics: joint asymptotic, T, N -> infinity simultaneously, and T fixed and N allowed to grow indefinitely. We use Monte Carlo experiments to investigate the effects of misspecification in sample sizes usually used in practice. The results indicate that the assumption that T is fixed rather than asymptotic leads to tests that have less size distortions, particularly for relatively small T with large N panels (micro-panels) than the tests derived under the joint asymptotics. We also find that choosing a deterministic trend when a deterministic level is true does not significantly affect the properties of the test. But, choosing a deterministic level when a deterministic trend is true leads to extreme over-rejections. Therefore, when unsure about which model has generated the data, it is suggested to use the model with a trend. We also propose a new statistic for testing for stationarity in mixed panel data where the mixture is known. The performance of this new test is very good for both cases of T asymptotic and T fixed. The statistic for T asymptotic is slightly undersized when T is very small (

Elevated expression of Runx2 as a key parameter in the etiology of osteosarcoma

To understand the molecular etiology of osteosarcoma, we isolated and characterized a human osteosarcoma cell line (OS1). OS1 cells have high osteogenic potential in differentiation induction media. Molecular analysis reveals OS1 cells express the pocket protein pRB and the runt-related transcription factor Runx2. Strikingly, Runx2 is expressed at higher levels in OS1 cells than in human fetal osteoblasts. Both pRB and Runx2 have growth suppressive potential in osteoblasts and are key factors controlling competency for osteoblast differentiation. The high levels of Runx2 clearly suggest osteosarcomas may form from committed osteoblasts that have bypassed growth restrictions normally imposed by Runx2. Interestingly, OS1 cells do not exhibit p53 expression and thus lack a functional p53/p21 DNA damage response pathway as has been observed for other osteosarcoma cell types. Absence of this pathway predicts genomic instability and/or vulnerability to secondary mutations that may counteract the anti-proliferative activity of Runx2 that is normally observed in osteoblasts. We conclude OS1 cells provide a valuable cell culture model to examine molecular events that are responsible for the pathologic conversion of phenotypically normal osteoblast precursors into osteosarcoma cells.

ZnO based nanowires grown by chemical vapour deposition for selective hydrogenation of acetylene alcohols

Vertically aligned ZnO nanowires (NWs) with a length of 1.5-10 mu m and a mean diameter of ca. 150 nm were grown by chemical vapour deposition onto a c-oriented ZnO seed layer which was deposited by atomic layer deposition on Si substrates. The substrates were then spin-coated with an ethanol solution containing Pd nanoparticles with an average size of 2.7 and 4.5 nm. A homogeneous distribution of the Pd nanoparticles on ZnO NWs has been obtained using both Pd particle series. The catalytic activity of the ZnO NWs and Pd/ZnO NWs catalysts was measured in the semihydrogenation of 2-methyl-3-butyn-2-ol at 303-343 K and a pressure of 2-10 bar. The effect of the solvent used on the catalytic performance of the Pd/ZnO NWs catalyst was studied. The Pd/ZnO catalysts showed alkene selectivity of up to 95% at an alkyne conversion of 99%. A kinetic model is proposed to explain the activity and selectivity of the ZnO support and Pd/ZnO catalysts.

How can cells sense the elasticity of a substrate? An analysis using a cell tensegrity model

A eukaryotic cell attaches and spreads on substrates, whether it is the extracellular matrix naturally produced by the cell itself, or artificial materials, such as tissue-engineered scaffolds. Attachment and spreading require the cell to apply forces in the nN range to the substrate via adhesion sites, and these forces are balanced by the elastic response of the substrate. This mechanical interaction is one determinant of cell morphology and, ultimately, cell phenotype. In this paper we use a finite element model of a cell, with a tensegrity structure to model the cytoskeleton of actin filaments and microtubules, to explore the way cells sense the stiffness of the substrate and thereby adapt to it. To support the computational results, an analytical 1D model is developed for comparison. We find that (i) the tensegrity hypothesis of the cytoskeleton is sufficient to explain the matrix-elasticity sensing, (ii) cell sensitivity is not constant but has a bell-shaped distribution over the physiological matrix-elasticity range, and (iii) the position of the sensitivity peak over the matrix-elasticity range depends on the cytoskeletal structure and in particular on the F-actin organisation. Our model suggests that F-actin reorganisation observed in mesenchymal stem cells (MSCs) in response to change of matrix elasticity is a structural-remodelling process that shifts the sensitivity peak towards the new value of matrix elasticity. This finding discloses a potential regulatory role of scaffold stiffness for cell differentiation.

Implementation of Menter's Transition Model on an Isolated Natural Laminar Flow Nacelle

This study evaluates the implementation of Menter's gamma-Re-theta Transition Model within the CFX12 solver for turbulent transition prediction on a natural laminar flow nacelle. Some challenges associated with this type of modeling have been identified. The computational fluid dynamics transitional flow simulation results are presented for a series of cruise cases with freestream Mach numbers ranging from 0.8 to 0.88, angles of attack from 2 to 0 degrees, and mass flow ratios from 0.60 to 0.75. These were validated with a series of wind-tunnel tests on the nacelle by comparing the predicted and experimental surface pressure distributions and transition locations. A selection of the validation cases are presented in this paper. In all cases, computational fluid dynamics simulations agreed reasonably well with the experiments. The results indicate that Menter's gamma-Re-theta Transition Model is capable of predicting laminar boundary-layer transition to turbulence on a nacelle. Nonetheless, some limitations exist in both the Menter's gamma-Re-theta Transition Model and in the implementation of the computational fluid dynamics model. The implementation of a more comprehensive experimental correlation in Menter's gamma-Re-theta Transition Model, preferably the ones from nacelle experiments, including the effects of compressibility and streamline curvature, is necessary for an accurate transitional flow simulation on a nacelle. In addition, improvements to the computational fluid dynamics model are also suggested, including the consideration of varying distributed surface roughness and an appropriate empirical correction derived from nacelle experimental transition location data.

Effect of Inhibitor Compounds on N-epsilon-(Carboxymethyl)lysine (CML) and N-epsilon-(Carboxyethyl)lysine (CEL) Formation in Model Foods

The possible adverse effects on health of diet-derived advanced glycation endproducts (AGES) and advanced lipoxidation endproducts (ALES) is of current interest. This study had the objective of determining the effects of the addition of AGE/ALE inhibitors and different types of sugar and cooking oil on N-epsilon-(carboxymethyl)lysine (CML) and N-epsilon-(carboxyethyl)lysine (CEL) formation in model foods (sponge cakes). The cake baked using glucose produced the highest level of CML (2.07 +/- 0.24 mmol/mol lysine), whereas the cake baked using fructose produced the highest concentration of CEL (25.1 +/- 0.15 mmol/mol lysine). There were no significant differences between CML concentrations formed in the cakes prepared using different types of cooking oil, but significant differences (P

A two-tier model of polymyxin B resistance in Burkholderia cenocepacia

P>Burkholderia cenocepacia is an environmental bacterium causing serious human opportunistic infections and is extremely resistant to multiple antibiotics including antimicrobial peptides, such as polymyxin B (PmB). Extreme antibiotic resistance is attributed to outer membrane impermeability ('intrinsic' resistance). Previous work showed that production of full-length lipopolysaccharide (LPS) prevents surface binding of PmB. We hypothesized that two tiers of resistance mechanisms rendering different thresholds of PmB resistance exist in B. cenocepacia. To test this notion, candidate genes were mutated in two isogenic strains expressing full-length LPS or truncated LPS devoid of heptose ('heptoseless LPS') respectively. We uncovered various proteins required for PmB resistance only in the strain with heptoseless LPS. These proteins are not involved in preventing PmB binding to whole cells or permeabilization of the outer membrane. Our results support a two-tier model of PmB resistance in B. cenocepacia. One tier sets a very high threshold mediated by the LPS and the outer membrane permeability barrier. The second tier sets a lower threshold that may play a role in PmB resistance only when outer membrane permeability is compromised. This model may be of general applicability to understanding the high antimicrobial peptide resistance of environmental opportunistic pathogens.

The technical merits of turbogenerating shown through the design, validation and implementation of a 1 dimensional engine model

Turbocompounding is the process of recovering a proportion of an engine’s fuel energy that would otherwise be lost in the exhaust process and adding it to the output power. This was first seen in the 1930s and is carried out by coupling an exhaust gas turbine to the crankshaft of a reciprocating engine. It has since been recognised that coupling the power turbine to an electrical generator instead of the crankshaft has the potential to reduce the fuel consumption further with the added flexibility of being able to decide how this recovered energy is used. The electricity generated can be used in automotive applications to assist the crankshaft using a flywheel motor generator or to power ancillaries that would otherwise have run off the crankshaft. In the case of stationary power plants, it can assist the electrical power output. Decoupling the power turbine from the crankshaft and coupling it to a generator allows the power electronics to control the turbine speed independently in order to optimise the specific fuel consumption for different engine operating conditions. This method of energy recapture is termed ‘turbogenerating’.

This paper gives a brief history of turbocompounding and its thermodynamic merits. It then moves on to give an account of the validation of a turbogenerated engine model. The model is then used to investigate what needs to be done to an engine when a turbogenerator is installed. The engine being modelled is used for stationary power generation and is fuelled by an induced biogas with a small portion of palm oil being injected into the cylinder to initiate combustion by compression ignition. From these investigations, optimum settings were found that result in a 10.90% improvement in overall efficiency. These savings relate to the same engine without a turbogenerator installed operating with fixed fuelling.

Inscribing value on business model innovations: Insights from industrial projects commercializing disruptive digital innovations

In this paper we seek to show how marketing activities inscribe value on business model innovation, representative of an act, or sequence of socially interconnecting acts. Theoretically we ask two interlinked questions: (1) how can value inscriptions contribute to business model innovations? (2) how can marketing activities support the inscription of value on business model innovations? Semi-structured in-depth interviews were conducted with the thirty-seven members from across four industrial projects commercializing disruptive digital innovations. Various individuals from a diverse range of firms are shown to cast relevant components of their agency and knowledge on business model innovations through negotiation as an ongoing social process. Value inscription is mutually constituted from the marketing activities, interactions and negotiations of multiple project members across firms and functions to counter destabilizing forces and tensions arising from the commercialization of disruptive digital innovations. This contributes to recent conceptual thinking in the industrial marketing literature, which views business models as situated within dynamic business networks and a context-led evolutionary process. A contribution is also made to debate in the marketing literature around marketing's boundary-spanning role, with marketing activities shown to span and navigate across functions and firms in supporting value inscriptions on business model innovations.

Illumination invariant facial recognition using a piecewise-constant lighting model

In this paper we demonstrate a simple and novel illumination model that can be used for illumination invariant facial recognition. This model requires no prior knowledge of the illumination conditions and can be used when there is only a single training image per-person. The proposed illumination model separates the effects of illumination over a small area of the face into two components; an additive component modelling the mean illumination and a multiplicative component, modelling the variance within the facial area. Illumination invariant facial recognition is performed in a piecewise manner, by splitting the face image into blocks, then normalizing the illumination within each block based on the new lighting model. The assumptions underlying this novel lighting model have been verified on the YaleB face database. We show that magnitude 2D Fourier features can be used as robust facial descriptors within the new lighting model. Using only a single training image per-person, our new method achieves high (in most cases 100%) identification accuracy on the YaleB, extended YaleB and CMU-PIE face databases.

A Data Model for Content Modelling of Temporal Media

This paper describes a data model for content representation of temporal media in an IP based sensor network. The model is formed by introducing the idea of semantic-role from linguistics into the underlying concepts of formal event representation with the aim of developing a common event model. The architecture of a prototype system for a multi camera surveillance system, based on the proposed model is described. The important aspects of the proposed model are its expressiveness, its ability to model content of temporal media, and its suitability for use with a natural language interface. It also provides a platform for temporal information fusion, as well as organizing sensor annotations by help of ontologies.

Online Multiperson Tracking With Occlusion Reasoning and Unsupervised Track Motion Model

We address the problem of multi-target tracking in realistic crowded conditions by introducing a novel dual-stage online tracking algorithm. The problem of data-association between tracks and detections, based on appearance, is often complicated by partial occlusion. In the first stage, we address the issue of occlusion with a novel method of robust data-association, that can be used to compute the appearance similarity between tracks and detections without the need for explicit knowledge of the occluded regions. In the second stage, broken tracks are linked based on motion and appearance, using an online-learned linking model. The online-learned motion-model for track linking uses the confident tracks from the first stage tracker as training examples. The new approach has been tested on the town centre dataset and has performance comparable with the present state-of-the-art

'Trusting the numbers': mineral prospecting, raising finance and the governance of knowledge

Mineral prospecting and raising finance for ‘junior’ mining firms has historically been regarded as a speculative activity. For the regulators of securities markets upon which ‘junior’ mining companies seek to raise capital, a perennial problem has been handling not only the indeterminacy of scientific claims, but also the social basis of epistemic practices. This paper examines the production of a system of public warrant and associated knowledge practices intended to enable investors to differentiate between ‘destructive’ and ‘productive’ varieties of financial speculation. It traces the use of the notion of ‘disclosure’ in constructing and legitimizing the ‘juniors’ market in Canada. It argues that though the work of ‘economics’ may be necessary in the construction of markets, it is by no means sufficient. Attention must also be given to the ways in which legal models of ‘the free-market’ can be translated and constantly re-worked across the sites and spaces of regulatory practice, animating the geographies of markets.