Forced intercalation probes (FIT Probes): thiazole orange as a fluorescent base in peptide nucleic acids for homogeneous single-nucleotide-polymorphism detection

Fluorescent base analogues in DNA are versatile probes of nucleic acid-nucleic acid and nucleic acid-protein interactions. New peptide nucleic acid (PNA) based probes are described in which the intercalator dye thiazole orange (TO) serves as a base surrogate. The investigation of six TO derivatives revealed that the linker length and the conjugation site decided whether a base surrogate conveys sequence-selective DNA binding and whether fluorescence is increased or decreased upon single-mismatched hybridization. One TO derivative conferred universal PNA-DNA base pairing while maintaining duplex stability and hybridization selectivity. TO fluorescence increased up to 26-fold upon hybridization. In contrast to most other probes, in which fluorescence is invariant once hybridization had occurred, the emission of TO-containing PNA probes is attenuated when forced to intercalate next to a mismatched base pair. The specificity of DNA detection is therefore not limited by the selectivity of probe-target binding and a DNA target can be distinguished from its single-base mutant under nonstringent hybridization conditions. This property should be of advantage for real-time quantitative PCR and nucleic acid detection within living cells.     

Path‐space Motion Estimation and Decomposition for Robust Animation Filtering

Renderings of animation sequences with physics‐based Monte Carlo light transport simulations are exceedingly costly to generate frame‐by‐frame, yet much of this computation is highly redundant due to the strong coherence in space, time and among samples. A promising approach pursued in prior work entails subsampling the sequence in space, time, and number of samples, followed by image‐based spatio‐temporal upsampling and denoising. These methods can provide significant performance gains, though major issues remain: firstly, in a multiple scattering simulation, the final pixel color is the composite of many different light transport phenomena, and this conflicting information causes artifacts in image‐based methods. Secondly, motion vectors are needed to establish correspondence between the pixels in different frames, but it is unclear how to obtain them for most kinds of light paths (e.g. an object seen through a curved glass panel). To reduce these ambiguities, we propose a general decomposition framework, where the final pixel color is separated into components corresponding to disjoint subsets of the space of light paths. Each component is accompanied by motion vectors and other auxiliary features such as reflectance and surface normals. The motion vectors of specular paths are computed using a temporal extension of manifold exploration and the remaining components use a specialized variant of optical flow. Our experiments show that this decomposition leads to significant improvements in three image‐based applications: denoising, spatial upsampling, and temporal interpolation.     

The Visual Computing of Projector‐Camera Systems

This article focuses on real‐time image correction techniques that enable projector‐camera systems to display images onto screens that are not optimized for projections, such as geometrically complex, coloured and textured surfaces. It reviews hardware‐accelerated methods like pixel‐precise geometric warping, radiometric compensation, multi‐focal projection and the correction of general light modulation effects. Online and offline calibration as well as invisible coding methods are explained. Novel attempts in super‐resolution, high‐dynamic range and high‐speed projection are discussed. These techniques open a variety of new applications for projection displays. Some of them will also be presented in this report.     

Theory and implementation of path planning by negotiation for decentralized agents

This paper presents a cooperative decentralized path-planning algorithm for a group of autonomous agents that provides guaranteed collision-free trajectories in real-time. The algorithm is robust with respect to arbitrary delays in the wireless traffic, possible sources being transmission time and error correction. Agents move on reserved areas which are guaranteed not to intersect, therefore ensuring safety. A handshaking procedure guarantees recent information states for the agents. Conflicts between agents are resolved by a cost-based negotiation process. The basic algorithm is augmented by the introduction of waypoints, which increase performance at the cost of additional wireless traffic. An implementation of the algorithm is tested in simulation and successfully applied to a real system of autonomous robots. The results are presented and discussed.     

Entwicklung Serviceorientierter Architekturen zur Integration von Produktion und Dienstleistung – Eine Konzeptionsmethode und ihre Anwendung am Beispiel des Recyclings elektronischer Geräte

Offering product-service bundles (consisting of products and services) is becoming more important for companies. Modifying the organizational structure of the cooperation as well as adapting to changing customer demands requires versatile information systems. Implementing Service Oriented Architectures (SOA) is one attempt to provide this flexibility. Currently, there is little methodical guidance for the identification, specification and implementation of services as building blocks of Service Oriented Architectures. Accounting for this need, a conceptual approach is designed, which adapts approaches of customer integration, and combines a business and IT analysis. The applicability of the method is demonstrated by designing a Service Oriented Architecture for the recycling of electronic equipment. Implementing services for other product-service bundles will support additional integration scenarios. By standardizing services, a sound integration of products and services can be backed by providing a reference architecture.     

Adaptive training of video sets for image recognition on mobile phones

We present an enhancement towards adaptive video training for PhoneGuide, a digital museum guidance system for ordinary camera-equipped mobile phones. It enables museum visitors to identify exhibits by capturing photos of them. In this article, a combined solution of object recognition and pervasive tracking is extended to a client–server-system for improving data acquisition and for supporting scale-invariant object recognition. A static as well as a dynamic training technique are presented that preprocess the collected object data differently and apply two types of neural networks (NN) for classification. Furthermore, the system enables a temporal adaptation for ensuring a continuous data acquisition to improve the recognition rate over time. A formal field experiment reveals current recognition rates and indicates the practicability of both methods under realistic conditions in a museum.

---