On‐the‐Spot Immobilization of Quantum Dots,Graphene Oxide,and Proteins via Hydrophobins

Class I hydrophobin Vmh2, a peculiar surface active and versatile fungal protein, is known to self‐assemble into chemically stable amphiphilic films, to be able to change wettability of surfaces, and to strongly adsorb other proteins. Herein, a fast, highly homogeneous and efficient glass functionalization by spontaneous self‐assembling of Vmh2 at liquid–solid interfaces is achieved (in 2 min). The Vmh2‐coated glass slides are proven to immobilize not only proteins but also nanomaterials such as graphene oxide (GO) and quantum dots (QDs). As models, bovine serum albumin labeled with Alexa 555 fluorophore, anti‐immunoglobulin G antibodies, and cadmium telluride QDs are patterned in a microarray fashion in order to demonstrate functionality, reproducibility, and versatility of the proposed substrate. Additionally, a GO layer is effectively and homogeneously self‐assembled onto the studied functionalized surface. This approach offers a quick and simple alternative to immobilize nanomaterials and proteins, which is appealing for new bioanalytical and nanobioenabled applications.     

Inorganic–organic hybrid materials with zirconium oxoclusters as protective coatings on aluminium alloys

Inorganic–organic hybrid materials are attracting a strong scientific interest mainly for their outstanding inherent mechanical and thermal properties, which can be traced back to the intimate coupling of both inorganic and organic components. By carefully choosing the experimental parameters used for their synthesis, chemically and thermally stable acrylate-based hybrid material embedding the zirconium oxocluster Zr₄O₄(OMc)₁₂, where OMcCH₂C(CH₃)C(O)O, can be deposited as UV-cured films on aluminium alloys.

In particular, the molar ratios between the oxocluster and the monomer, the polymerisation time, the amount of photo-initiator and the deposition conditions, by using an home-made spray-coating equipment, were optimised in order to obtain the best performing layers in terms of transparency and hardness to coat aluminium alloy (AA1050, AA6060 and AA2024) sheets. Furthermore, it was also evaluated whether the hybrid coatings behave as barrier to corrosion.

Several coated samples were prepared and characterised. Environmental scanning electronic microscopy (ESEM) and scratch test were used to investigate the morphology of the films and to evaluate their scratch resistance, respectively. Electrochemical impedance spectroscopy (EIS) was performed in order to evaluate if the coatings actually protect the metallic substrate from corrosion.

In order to measure shear storage modulus (G′) and loss modulus (G″) of the materials used for coatings, bulk samples were also obtained by UV-curing of the precursors solution. Dynamical mechanical thermal analysis (DMTA) was performed in shear mode on cured disks of both the hybrid materials and pristine polymer for comparison. The values of T_g were read off as the temperatures of peak of loss modulus. The length and mass of all the samples were measured before and after the DMTA analysis, so that the shrinkage of the materials in that temperature range was exactly evaluated.     

Semantische Informationsextraktion in medizinischen Informationssystemen

Zusammenfassung Dieser Artikel beschreibt einige Erfahrungen und typische Problemstellungen mit Textmining in der Medizin und gibt einen Einblick in aktuelle und zukünftige Herausforderungen in Forschung & Entwicklung. Interessant ist n?mlich, dass auch im ,,Multimedia-Zeitalter“ die meiste Information immer noch als ,,Text“ vorliegt. Mithilfe von statistischen und linguistischen Verfahren wird mit sogenannter ,,Textmining-Software“ versucht, aus Freitexten Information ,,heraus zu schürfen“ (deshalb ,,Textmining“). Allerdings ist es damit noch nicht genug. Der n?chste Schritt besteht darin, die Information sowohl nutzbar als auch brauchbar zu machen. Die jeweiligen End-Benutzerinnen und End-Benutzer müssen in die Lage versetzt werden, auf der Basis der gewonnenen Information deren Wissen zu erweitern. In unserem konkreten Fall sollen damit Entscheidungen im Rahmen ?rztlichen Handelns unterstützt werden. Probleml?sungen in diesem Bereich erfordern eine holistische Sicht- und Herangehensweise. Daher wird es immer wichtiger, Erkenntnisse aus Informatik und Psychologie zusammenflie?en zu lassen und auf systemischer Ebene technologisch umzusetzen.     

Self-adjusting the intensity of assortative mating in genetic algorithms

Mate selection plays a crucial role in both natural and artificial systems. While traditional Evolutionary Algorithms (EA) usually engage in random mating strategies, that is, mating chance is independent of genotypic or phenotypic distance between individuals, in natural systems non-random mating is common, which means that somehow this mechanism has been favored during the evolutionary process. In non-random mating, the individuals mate according to their parenthood or likeness. Previous studies indicate that negative assortative mating (AM)—also known as dissortative mating—, which is a specific type of non-random mating, may improve EAs performance by maintaining the genetic diversity of the population at a higher level during the search process. In this paper we present the Variable Dissortative Mating Genetic Algorithm (VDMGA). The algorithm holds a mechanism that varies the GA’s mating restrictions during the run by means of simple rule based on the number of chromosomes created in each generation and indirectly influenced by the genetic diversity of the population. We compare VDMGA not only with traditional Genetic Algorithms (GA) but also with two preceding non-random mating EAs: the CHC algorithm and the negative Assortative Mating Genetic Algorithm (nAMGA). We intend to study the effects of the different methods in the performance of GAs and verify the reliability of the proposed algorithm when facing an heterogeneous set of landscapes. In addition, we include the positive Assortative Mating Genetic Algorithm (pAMGA) in the experiments in order test both negative and positive AM mechanisms, and try to understand if and when negative AM (or DM) speeds up the search process or enables the GAs to escape local optima traps. For these purposes, an extensive set of optimization test problems was chosen to cover a variety of search landscapes with different characteristics. Our results confirm that negative AM is effective in leading EAs out of local optima traps, and show that the proposed VDMGA is at least as efficient as nAMGA when applied to the range of our problems, being more efficient in very hard functions were traditional GAs usually fail to escape local optima. Also, scalability tests have been made that show VDMGA ability to decrease optimal population size, thus reducing the amount of evaluations needed to attain global optima. We like to stress that only two parameters need to be hand-tuned in VDMGA, thus reducing the tuning effort present in traditional GAs and nAMGA.     

Improving Communication in E-democracy Using Natural Language Processing

E-democracy, the design and development of new techniques for improving communication between public administration and citizens, is a major application field for natural language processing and language engineering. Helping citizens access information in a friendly, intuitive way is the primary objective of a global e-democracy framework. The E-democracy European Network project (EDEN) aimed at discovering whether a particular NLP (natural language processing) approach could further e-democracy by increasing citizens' participation in the decision-making process. The goal was twofold: to test whether e-democracy requirements could be meet using advanced linguistic technology and to test whether augmented phrase structure grammars (APSGs) were robust and well-assessed enough to use in a real-world environment. Also, the aim is to develop two toolsets to improve communication between PAs and citizens in the context of urban planning: a set of NLP-based tools to simplify access to information and knowledge and a set of forum and polling devices     

Creating a Student Centered Learning Environment at the University of Denver

A team of faculty members at the University of Denver changed the learning environment in key courses in the Department of Engineering from predominately teacher centered to student centered. Through this funded project new grading methods were implemented, classrooms were renovated and wired with studio layouts to facilitate learning, the Engineering Circuits Laboratory was rewired and instrumented for automated data acquisition and reporting, and two new pedagogical approaches were developed. At the onset of the project, six goals were established related to student learning. The introduction of industry standard hardware and software provided students with unprecedented hands‐on experience and project related activities stimulated faculty innovations in other current and future courses. Assessment results indicate that the new grading system improved the clarity of expectations for students before assignments were given resulting in increased reported motivation for learning in many courses. Even though course GPAs did not always reflect higher achievement on graded work, faculty members firmly believe that deeper understanding was achieved because more complex material was assimilated.