Is LRP2 Involved in Leptin Transport over the Blood-Brain Barrier and Development of Obesity?

The mechanisms underlying the transport of leptin into the brain are still largely unclear. While the leptin receptor has been implicated in the transport process, recent evidence has suggested an additional role of LRP2 (megalin). To evaluate the function of LRP2 for leptin transport across the blood-brain barrier (BBB), we developed a novel leptin-luciferase fusion protein (pLG), which stimulated leptin signaling and was transported in an in vitro BBB model based on porcine endothelial cells. The LRP inhibitor RAP did not affect leptin transport, arguing against a role of LRP2. In line with this, the selective deletion of LRP2 in brain endothelial cells and epithelial cells of the choroid plexus did not influence bodyweight, body composition, food intake, or energy expenditure of mice. These findings suggest that LRP2 at the BBB is not involved in the transport of leptin into the brain, nor in the development of obesity as has previously been described.     

High quality double wall carbon nanotubes with a defined diameter distribution by chemical vapor deposition from alcohol

We have synthesized double wall carbon nanotubes (DWNTs) with few defects and little amorphous carbon by hot wall chemical vapor deposition (CVD) of alcohol. Catalysts for the DWNT growth were made from cobalt and molybdenum acetates. Scanning electron microscopy, transmission electron microscopy, multi frequency resonance Raman spectroscopy and optical absorption spectroscopy were used for characterization of the product with regard to DWNT yield, the nanotube diameter distribution, defect concentration and amorphous carbon content. Base pressures lower than 1 × 10⁻⁵ mbar in the CVD reactor considerably suppress defects in the DWNTs. Optimized growth conditions for DWNT formation are presented.     

Automating Test Case Selection in Model-Based Software Product Line Development

We address the problem of how to select test cases for products in a controlled model-based software product line development process. CVL, the common variability language, gives a framework for materialisation of product models from a given base model, variability model and resolution model. From such product models, software products can be derived. In practise, test case development for the product line often is independent from the product development. Therefore, the problem arises which test cases can be applied to which products. In particular, the question is whether a test case for one speci c product can be also used for a "similar" product. In this paper, we show how the expected outcome of a test case to a product in a model-based software product line development can be determined. That is, we give a procedure for assigning the outcome of a given test case on an arbitrary member of a software product line. We recall the relevant de nitions for software product line engineering, describe our approach, and demonstrate it with the example of a product line of super-automatic espresso machines.     

Jet bundle formulation of infinite-dimensional port-Hamiltonian systems using differential operators

We consider infinite-dimensional port-Hamiltonian systems described on jet bundles. Based on a power balance relation we introduce the port-Hamiltonian system representation using differential operators regarding the structural mapping, the dissipation mapping and the input mapping. In contrast to the well-known representation on the basis of the underlying Stokes–Dirac structure our approach is not necessarily based on using energy-variables which leads to a different port-Hamiltonian representation of the analyzed partial differential equations. The presented constructions will be specialized to mechanical systems to which class also the presented examples belong.     

Aggregation behaviour of well defined amphiphilic diblock copolymers with poly(N-isopropylacrylamide) and hydrophobic blocks

Series of amphiphilic diblock copolymers with poly(N-isopropylacrylamide) as a hydrophilic block and a hydrophobic block consisting of either polystyrene or poly(tert-butyl methacrylate) were synthesised using RAFT polymerisations. Differential scanning calorimetry showed the chemically different blocks being phase separated in dry polymers. Light scattering and microcalorimetry studies were performed on aqueous solutions to investigate the phase behavior of the diblock copolymers. By carefully transferring the polymers from an organic solvent to water, either micellar particles or large aggregates were obtained depending on the relative lengths of the blocks. Large aggregates collapsed upon heating, whereas collapse occurred slowly within a broad temperature range in the case of micelle like structures. However, microcalorimetrically the collapse of the PNIPAM chains was observed to take place in all samples, suggesting that the shells of the micellar particles are crowded in a way which hinders the compression of the poly(N-isopropylacrylamide) chains.     

Bayesian estimation of Dirichlet mixture model with variational inference

In statistical modeling, parameter estimation is an essential and challengeable task. Estimation of the parameters in the Dirichlet mixture model (DMM) is analytically intractable, due to the integral expressions of the gamma function and its corresponding derivatives. We introduce a Bayesian estimation strategy to estimate the posterior distribution of the parameters in DMM. By assuming the gamma distribution as the prior to each parameter, we approximate both the prior and the posterior distribution of the parameters with a product of several mutually independent gamma distributions. The extended factorized approximation method is applied to introduce a single lower-bound to the variational objective function and an analytically tractable estimation solution is derived. Moreover, there is only one function that is maximized during iterations and, therefore, the convergence of the proposed algorithm is theoretically guaranteed. With synthesized data, the proposed method shows the advantages over the EM-based method and the previously proposed Bayesian estimation method. With two important multimedia signal processing applications, the good performance of the proposed Bayesian estimation method is demonstrated.     

Organic Nanoparticles with Polypropyleneoxide Chains as Support for Metallocene Catalysts: Ethylene Homopolymerization and Ethylene/α-olefin Copolymerization

Summary Novel organic nanoparticles functionalized with nucleophilic polypropyleneoxide (PPO) chains on their surfaces for supporting metallocene catalysts in heterogeneous olefin polymerization are presented. The nanoparticles (60–100 nm) were obtained by miniemulsion polymerization of styrene, divinylbenzene and PPO functionalized styrene. It is demonstrated that Me₂Si(2MeBenzlnd)₂ZrCl₂/MAO supported on these nanoparticles is suitable for the homopolymerization of ethylene, resulting in excellent product morphologies and high activities. lt is shown that by varying the MAO/Zr ratios and Zr concentrations the activities and productivities of the catalysts as well as the qualities of the polyethylene products can be tuned. These new supported catalysts are also suitable for the copolymerization of ethylene with several comonomers (1-hexene, 1-octene, 1-decene or norbornene). As the obtained product properties like crystallinity, melting temperature or bulk density match the results of silica supported systems, these organic nanoparticles can be considered as alternative carriers in comparison to the established inorganic ones.     

Branching-time logics with path relativisation

We define extensions of the full branching-time temporal logic CTL^? in which the path quantifiers are relativised by formal languages of infinite words, and consider its natural fragments obtained by extending the logics CTL and CTL⁺ in the same way. This yields a small and two-dimensional hierarchy of temporal logics parametrised by the class of languages used for the path restriction on one hand, and the use of temporal operators on the other. We motivate the study of such logics through two application scenarios: in abstraction and refinement they offer more precise means for the exclusion of spurious traces; and they may be useful in software synthesis where decidable logics without the finite model property are required. We study the relative expressive power of these logics as well as the complexities of their satisfiability and model-checking problems.     

Spatio‐temporal geometry fusion for multiple hybrid cameras using moving least squares surfaces

Multi‐view reconstruction aims at computing the geometry of a scene observed by a set of cameras. Accurate 3D reconstruction of dynamic scenes is a key component for a large variety of applications, ranging from special effects to telepresence and medical imaging. In this paper we propose a method based on Moving Least Squares surfaces which robustly and efficiently reconstructs dynamic scenes captured by a calibrated set of hybrid color+depth cameras. Our reconstruction provides spatio‐temporal consistency and seamlessly fuses color and geometric information. We illustrate our approach on a variety of real sequences and demonstrate that it favorably compares to state‐of‐the‐art methods.     

On‐the‐fly generation and rendering of infinite cities on the GPU

In this paper, we present a new approach for shape‐grammar‐based generation and rendering of huge cities in real‐time on the graphics processing unit (GPU). Traditional approaches rely on evaluating a shape grammar and storing the geometry produced as a preprocessing step. During rendering, the pregenerated data is then streamed to the GPU. By interweaving generation and rendering, we overcome the problems and limitations of streaming pregenerated data. Using our methods of visibility pruning and adaptive level of detail, we are able to dynamically generate only the geometry needed to render the current view in real‐time directly on the GPU. We also present a robust and efficient way to dynamically update a scene's derivation tree and geometry, enabling us to exploit frame‐to‐frame coherence. Our combined generation and rendering is significantly faster than all previous work. For detailed scenes, we are capable of generating geometry more rapidly than even just copying pregenerated data from main memory, enabling us to render cities with thousands of buildings at up to 100 frames per second, even with the camera moving at supersonic speed.