Complexity classes for self-assembling flexible tiles

We present a theoretical model for self-assembling DNA tiles with flexible branches. We encode an instance of a “problem” as a pot of such tiles for which a “solution” is an assembled complete complex without any free sticky ends. Using the number of tiles in an assembled complex as a measure of complexity we show how NTIME classes (such as NP and NEXP) can be represented with corresponding classes of the model.     

The use of data-derived label hierarchies in multi-label classification

Instead of traditional (multi-class) learning approaches that assume label independency, multi-label learning approaches must deal with the existing label dependencies and relations. Many approaches try to model these dependencies in the process of learning and integrate them in the final predictive model, without making a clear difference between the learning process and the process of modeling the label dependencies. Also, the label relations incorporated in the learned model are not directly visible and can not be (re)used in conjunction with other learning approaches. In this paper, we investigate the use of label hierarchies in multi-label classification, constructed in a data-driven manner. We first consider flat label sets and construct label hierarchies from the label sets that appear in the annotations of the training data by using a hierarchical clustering approach. The obtained hierarchies are then used in conjunction with hierarchical multi-label classification (HMC) approaches (two local model approaches for HMC, based on SVMs and PCTs, and two global model approaches, based on PCTs for HMC and ensembles thereof). The experimental results reveal that the use of the data-derived label hierarchy can significantly improve the performance of single predictive models in multi-label classification as compared to the use of a flat label set, while this is not preserved for the ensemble models.     

3D‐vision based detection,localization, and sizing of broccoli heads in the field

This paper describes a 3D vision system for robotic harvesting of broccoli using low‐cost RGB‐D sensors, which was developed and evaluated using sensory data collected under real‐world field conditions in both the UK and Spain. The presented method addresses the tasks of detecting mature broccoli heads in the field and providing their 3D locations relative to the vehicle. The paper evaluates different 3D features, machine learning, and temporal filtering methods for detection of broccoli heads. Our experiments show that a combination of Viewpoint Feature Histograms, Support Vector Machine classifier, and a temporal filter to track the detected heads results in a system that detects broccoli heads with high precision. We also show that the temporal filtering can be used to generate a 3D map of the broccoli head positions in the field. Additionally, we present methods for automatically estimating the size of the broccoli heads, to determine when a head is ready for harvest. All of the methods were evaluated using ground‐truth data from both the UK and Spain, which we also make available to the research community for subsequent algorithm development and result comparison. Cross‐validation of the system trained on the UK dataset on the Spanish dataset, and vice versa, indicated good generalization capabilities of the system, confirming the strong potential of low‐cost 3D imaging for commercial broccoli harvesting.     

Using meta‐modeling in design and implementation of component‐based systems: the SOFA case study

To allow efficient and user‐friendly development of a component‐based application, component systems have to provide a rather complex development infrastructure, including a tool for component composition, component repository, and a run‐time infrastructure. In this paper, we present and evaluate benefits of using meta‐modeling during the process of defining a component system and also during creation of the development and run‐time infrastructures. Most of the presented arguments are based on a broad practical experience with designing the component systems SOFA and SOFA 2; the former designed in a classical ad hoc ‘manual’ way, whereas the latter with the help of meta‐modeling. Copyright © 2010 John Wiley & Sons, Ltd.     

Flash memory efficient LTL model checking

As the capacity and speed of flash memories in form of solid state disks grow, they are becoming a practical alternative for standard magnetic drives. Currently, most solid-state disks are based on NAND technology and much faster than magnetic disks in random reads, while in random writes they are generally not.So far, large-scale LTL model checking algorithms have been designed to employ external memory optimized for magnetic disks. We propose algorithms optimized for flash memory access. In contrast to approaches relying on the delayed detection of duplicate states, in this work, we design and exploit appropriate hash functions to re-invent immediate duplicate detection.For flash memory efficient on-the-fly LTL model checking, which aims at finding any counter-example to the specified LTL property, we study hash functions adapted to the two-level hierarchy of RAM and flash memory. For flash memory efficient off-line LTL model checking, which aims at generating a minimal counterexample and scans the entire state space at least once, we analyze the effect of outsourcing a memory-based perfect hash function from RAM to flash memory.Since the characteristics of flash memories are different to magnetic hard disks, the existing I/O complexity model is no longer sufficient. Therefore, we provide an extended model for the computation of the I/O complexity adapted to flash memories that has a better fit to the observed behavior of our algorithms.     

The State of the Art in Topology‐Based Visualization of Unsteady Flow

Vector fields are a common concept for the representation of many different kinds of flow phenomena in science and engineering. Methods based on vector field topology are known for their convenience for visualizing and analysing steady flows, but a counterpart for unsteady flows is still missing. However, a lot of good and relevant work aiming at such a solution is available. We give an overview of previous research leading towards topology‐based and topology‐inspired visualization of unsteady flow, pointing out the different approaches and methodologies involved as well as their relation to each other, taking classical (i.e. steady) vector field topology as our starting point. Particularly, we focus on Lagrangian methods, space–time domain approaches, local methods and stochastic and multifield approaches. Furthermore, we illustrate our review with practical examples for the different approaches.     

A Constraint-Based Approach for Deriving 3-D Structures of Cyclic Polypeptides

This paper presents an hybrid algorithm for deriving 3-D structures of cyclic polypeptides. The algorithm combines constraint-based techniques with the most widely used methods for non-cyclic polypeptides. The empirical results demonstrate that the proposed hybrid algorithm outperforms traditional methods especially with respect to running times.     

Unexpected products of the allyldiethylamine hydroformylation homogeneously catalyzed by rhodium complexes

Attempts to carry out the hydroformylation of allyldiethylamine homogeneously catalyzed by rhodium complexes led to unexpected formation of N,N,N,N-tetraethyl-1,4-diaminobutane and 4-(diethylamino)-1-butanole as final products. The role of the catalyst on the product formation and the reaction mechanism are briefly discussed.     

Transition layer thickness in microlaminar deposits

A theoretical analysis was carried out on the change of composition of a deposit obtained by the dual pulse method of forming laminar metal foils, with transition from a low current to a high current pulse, both in the galvanostatic and the potentiostatic mode of deposition. It was shown that the existence of a transition layer of varying composition between a layer of pure metal 1 and a layer consisting predominantly of the metal 2 is an inherent consequence of the electrochemical process, primarily because of an induction period in the concentration polarization with respect to ions of metal 1. The importance of this transition layer increases as the thickness of the layers of the two metals decreases. Eventually this limits the possibility of obtaining a sharp boundary between the layers, when the nanometre region of layer thickness is reached. Equations are given for calculating the deposition current density and rate of stirring of the electrolyte which provide a deposit of a required level of metal 1 in the layer of metal 2, as well as a required sharpness of the boundary between two layers. Experimental proof of the correctness of the analysis was sought. It was found that significant changes in the properties of the deposit occur in the same range of layer thickness in which the transition of the composition takes places.Nomenclature _c,1, a_c,2 transfer coefficient of the cathodic processes - C interfacial capacitance - C₁, C₂ concentration of the ions of metals 1 and 2 at the interface r - C ₀ ¹ , C ₀ ² concentration of ions of the metals 1 and 2 in solution - D ₁ diffusion coefficient for the diffusion of ions of the metal 1 - E _r,1,E _r,2 reversible potentials of metals 1 and 2, respectively - F the Faraday constant - J ₀ ¹ ,J ₀ ² exchange current density of the metals 1 and 2, respectively - M ₁,M ₂ atomic weights of the metals 1 and 2, respectively - kinematic viscosity of solution - ₁, ₂ densities of the metals 1 and 2 respectively - rotation speed (r.p.s.) - z number of electrons exchanged in the deposition process This paper is dedicated to Professor Brian E. Conway on the occasion of his 65th birthday, and in recognition of his outstanding contribution to electrochemistry.