Identification of an integral plasma membrane pool of protein kinase C in mammalian tissues and cells

Protein kinase C (PKC) is a family of serine/threonine protein kinases that are pivotal in cellular regulation. Since its discovery in 1977, PKCs have been known as cytosolic and peripheral membrane proteins. However, there are reports that PKC can insert into phospholipids vesicles in vitro. Given the intimate relationship between the plasma membrane and the activation of PKC, it is important to determine whether such “membrane-inserted” form of PKC exists in mammalian cells or tissues. Here, we report the identification of an integral plasma membrane pool for all the 10 PKC isozymes in vivo by their ability to partition into the detergent-rich phase in Triton X-114 phase partitioning, and by their resistance to extractions with 0.2 M sodium carbonate (pH 11.5), 2 M urea and 2 M sodium chloride. The endogenous integral membrane pool of PKC in mouse fibroblasts is found to be acutely regulated by phorbol ester or diacylglycerol, suggesting that this pool of PKC may participate in cellular processes known to be regulated by PKC. At least for PKCα, the C2–V3 region at the regulatory domain of the kinase is responsible for membrane integration. Further exploration of the function of this novel integral plasma membrane pool of PKC will not only shed new light on molecular mechanisms underlying its cellular functions but also provide new strategies for pharmaceutical modulation of this important group of kinases.

Integral terminal sliding mode cooperative control of multi-robot networks

This paper studies the integral terminal sliding mode cooperative control of multi-robot networks. Here, we first propose an integral terminal sliding mode surface for a class of first order systems. Then, we prove that finite time consensus tracking of multi-robot networks can be achieved on this integral terminal sliding mode surface. Simulation results are presented to validate the analysis.

Integral approach and numerical improvement to calculate the carbon concentration profiles in carburising process

In the present work, the carbon diffusion in steel, where the carbon diffusivity varies with the carbon content, was solved with the integral methods under the third boundary condition. The variation of carbon diffusivity in steel with the carbon content was described with two different functions ie. linear dependence and exponential dependence. The integral approximation for both cases was improved with the numerical computation to more accurately predict the carbon profiles. The integral solution is more accurate than the formulation based on the assumption of a constant diffusivity or those based on the assumption of a constant diffusivity and/or constant carbon content at part surface. It is also more easily used in practice than the numerical method to describe the carburising process and predict the carbon content at steel surface and carbon profiles in treated layer.

Automatic grain texture analysis using integral transforms

Tonewood for musical instruments is quarter-sawn and frequently quality-graded based on visual appearance, mechanical and acoustic properties. The assessment uses simple human (subjective) observation, and two ‘‘experts’’ can rate the same sample differently. This paper describes the application of integral transforms (Fourier and Radon) for automatic (objective) assessment of the visual appearance of 10 Sitka spruce (Picea sitchensis) sample images. This work considers surface classification on the basis of grain orientation, count, spacing, and evenness or uniformity.

Integral approach and numerical improvement to calculate carbon concentration profiles in carburising

The carbon diffusion in steel, where the carbon diffusivity varies with the carbon content, was solved with the integral methods under the third boundary condition. The variation of carbon diffusivity in steel with the carbon content was described with two different functions, linear dependence and exponential dependence. The integral approximation for both cases was improved with the numerical computation to more accurately predict the carbon profiles. The integral solution is more accurate than the formulation based on the assumption of a constant diffusivity or those based on the assumption of a constant diffusivity and/or constant carbon content at part surface. It is also more easily used in practice than the numerical method to describe the carburising process and predict the carbon content at steel surface and carbon profiles in treated layer.

The integral child

.

A fuzzy decision support method for customer preferences analysis based on Choquet integral

The explosion of the Web 2:0 platforms, with massive volume of user generated data, has presented many new opportunities as well as challenges for organizations in understanding consumer's behavior to support for business planning process. Feature based sentiment mining has been an emerging area in providing tools for automated opinion discovery and summarization to help business managers with achieving such goals. However, the current feature based sentiment mining systems were only able to provide some forms of sentiments summary with respect to product features, but impossible to provide insight into the decision making process of consumers. In this paper, we will present a relatively new decision support method based on Choquet Integral aggregation function, Shapley value and Interaction Index which is able to address such requirements of business managers. Using a study case of Hotel industry, we will demonstrate how this technique can be applied to effectively model the user's preference of (hotel) features. The presented method has potential to extend the practical capability of sentiment mining area, while, research findings and analysis are useful in helping business managers to define new target customers and to plan more effective marketing strategies.