Calcium silicate hydrate—in-situ development of the silicate structure followed by infrared spectroscopy

In the current study, the development of the silicate structure of synthetic calcium silicate hydrates with different calcium contents was followed by in-situ infrared (IR) spectroscopy and correlated to the in-situ phase development evaluated by X-ray diffraction (XRD). A baseline correction method initially developed for X-ray diffractograms was successfully adapted for the complex background of the fingerprint region in in-situ IR, which significantly contributed to signal quality and reproducibility. The development of separate silicate infrared bands could be monitored over 24 h of reaction. These bands could be assigned to oligomeric and dimeric species based on their time and stoichiometry-dependent development. It was clearly shown that the main peak of the dimeric silicate species was overlooked in the literature. The correlation of time-dependent events to in-situ XRD revealed that changes in the unit cell of calcium silicate hydrate are related to silicate polymerization. The results were compared to ²⁹Si-MAS-NMR, which highlighted the benefits of in-situ IR spectroscopy.     

Modeling the Direct Synthesis of Dimethyl Ether using Artificial Neural Networks

Artificial neural networks (ANNs) are designed and implemented to model the direct synthesis of dimethyl ether (DME) from syngas over a commercial catalyst system. The predictive power of the ANNs is assessed by comparison with the predictions of a lumped model parameterized to fit the same data used for ANN training. The ANN training converges much faster than the parameter estimation of the lumped model, and the predictions show a higher degree of accuracy under all conditions. Furthermore, the simulations show that the ANN predictions are also accurate even at some conditions beyond the validity range.     

Aramid pulp treated with imidazolium ionic liquids as a filler in rigid polyurethane bio-foams

This article reports an aramid pulp (AP) treated with two ionic liquids (IL), namely 1-n-butyl-3-methylimidazolium chloride (C₄.Cl) and 1-carboxymethyl-3-methylimidazolium chloride (HO₂C), and its use as a filler in reinforced rigid polyurethane foams (RPUF). The RPUF were incorporated with the treated AP at three weight fractions (c.a. 0.1, 0.5, and 1.0 wt%) and were produced by the free rising method. The results showed that the studied IL promoted a better interaction between the AP and the RPUF system, which increased the overall reactivity, imparting a higher cell anisotropy. This also yielded a positive effect in mechanical properties and thermal stability of the RPUF. Compared to the neat RPUF, outstanding increases of approximately 50 and 20% were achieved in compressive modulus and strength, respectively. In all, the use of IL promoted increased compatibility between matrix and reinforcement, especially that HO₂C IL.     

Tetranorsesquiterpenoids as Attractants of Yucca Moths to Yucca Flowers

Journal of Chemical Ecology - The obligate pollination mutualism between Yucca and yucca moths is a classical example of coevolution. Oviposition and active pollination by female yucca moths occur...     

Bitwise dimensional co-clustering for analytical workloads

Analytical workloads in data warehouses often include heavy joins where queries involve multiple fact tables in addition to the typical star-patterns, dimensional grouping and selections. In this paper we propose a new processing and storage framework called bitwise dimensional co-clustering (BDCC) that avoids replication and thus keeps updates fast, yet is able to accelerate all these foreign key joins, efficiently support grouping and pushes down most dimensional selections. The core idea of BDCC is to cluster each table on a mix of dimensions, each possibly derived from attributes imported over an incoming foreign key and this way creating foreign key connected tables with partially shared clusterings. These are later used to accelerate any join between two tables that have some dimension in common and additionally permit to push down and propagate selections (reduce I/O) and accelerate aggregation and ordering operations. Besides the general framework, we describe an algorithm to derive such a physical co-clustering database automatically and describe query processing and query optimization techniques that can easily be fitted into existing relational engines. We present an experimental evaluation on the TPC-H benchmark in the Vectorwise system, showing that co-clustering can significantly enhance its already high performance and at the same time significantly reduce the memory consumption of the system.     

Performance models of storage contention in cloud environments

We propose simple models to predict the performance degradation of disk requests due to storage device contention in consolidated virtualized environments. Model parameters can be deduced from measurements obtained inside Virtual Machines (VMs) from a system where a single VM accesses a remote storage server. The parameterized model can then be used to predict the effect of storage contention when multiple VMs are consolidated on the same server. We first propose a trace-driven approach that evaluates a queueing network with fair share scheduling using simulation. The model parameters consider Virtual Machine Monitor level disk access optimizations and rely on a calibration technique. We further present a measurement-based approach that allows a distinct characterization of read/write performance attributes. In particular, we define simple linear prediction models for I/O request mean response times, throughputs and read/write mixes, as well as a simulation model for predicting response time distributions. We found our models to be effective in predicting such quantities across a range of synthetic and emulated application workloads.     

Simultaneous nonrigid registration of multiple point sets and atlas construction

Group-wise registration of a set of shapes represented by unlabeled point-sets is a challenging problem since, usually this involves solving for point correspondence in a nonrigid motion setting. In this paper, we propose a novel and robust algorithm that is capable of simultaneously computing the mean shape represented by a probability density function from multiple unlabeled point-sets and registering them non-rigidly to this emerging mean shape. This algorithm avoids the correspondence problem by minimizing the Jensen-Shannon (JS) divergence between the point sets. We motivate the use of the JS divergence by pointing out its close relationship to hypothesis testing. We derive the analytic gradient of the cost function in order to efficiently achieve the optimal solution. JS-divergence is symmetric with no bias toward any of the given shapes to be registered and whose mean is being sought. A by product of the registration process is a probabilistic atlas defined as the convex combination of the probability densities of the input point sets being aligned. Our algorithm can be especially useful for creating atlases of various shapes present in images as well as for simultaneously (rigidly or non-rigidly) registering 3D range data sets without having to establish any correspondence. We present experimental results on real and synthetic data.     

Tool-supported enhancement of diagnosis in model-driven verification

We show on a case study from an autonomous aerospace context how to apply a game-based model-checking approach as a powerful technique for the verification, diagnosis, and adaptation of system behaviors based on temporal properties. This work is part of our contribution within the SHADOWS project, where we provide a number of enabling technologies for model-driven self-healing. We propose here to use GEAR, a game-based model checker, as a user-friendly tool that can offer automatic proofs of critical properties of such systems. Although it is a model checker for the full modal μ-calculus, it also supports derived, more user-oriented logics. With GEAR, designers and engineers can interactively investigate automatically generated winning strategies for the games, by this way exploring the connection between the property, the system, and the proof. This work has been partially supported by the European Union Specific Targeted Research Project SHADOWS (IST-2006-35157), exploring a Self-Healing Approach to Designing cOmplex softWare Systems. The project’s web page is at . This article is an extended version of Renner et al. [18] presented at ISoLA 2007, Poitiers, December 2007.